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ANNUAL WINTER MAINTENANCE REPORT
Wisconsin Department of TransportationDivision of Transportation System DevelopmentBureau of Highway MaintenanceWinter Operations Unit
FINAL December 2017
2016-2017It's Only Cold if You're Standing Still
W i s D O T | A n n u a l W i n t e r M a i n t e n a n c e R e p o r t
AcknowledgmentsMany people at Wisconsin DOT contributed to the development of this report, including:
• James Hughes, Bureau of Highway Maintenance
• Mike Sproul, Bureau of Highway Maintenance
• Allan Johnson, Bureau of Highway Maintenance
• Mike Adams, Bureau of Highway Maintenance
• Cathy Meinholz, Bureau of Highway Maintenance
• Lisa Meinholz, Bureau of Highway Maintenance
• Donald Lyden, Bureau of Transportation Safety
• Asadur Rahman, Transportation Modeling & Information Unit
We wish to thank these individuals for their contributions to and assistance with this report.
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Table of Contents
1. Introduction.......................................................................................................................................5About This Report .................................................................................................................................................7Report Structure and Data Sources ....................................................................................................................7Working with County Highway Departments .......................................................................................................8This Winter in Wisconsin ......................................................................................................................................10
2. Winter Weather ................................................................................................................................19Winter Weather Challenges .................................................................................................................................20This Winter’s Weather ..........................................................................................................................................20Winter Severity Index ............................................................................................................................................21
3. Winter Operations ............................................................................................................................313A Materials ..........................................................................................................................................................32
Salt ..................................................................................................................................................................32Abrasives ........................................................................................................................................................36Prewetting ......................................................................................................................................................37Anti-icing ........................................................................................................................................................39
3B Equipment & Technology ................................................................................................................................46RWIS ..............................................................................................................................................................46MDSS ..............................................................................................................................................................48Equipment Calibration ...................................................................................................................................49Product and Equipment Testing ....................................................................................................................49Winter Maintenance Research .....................................................................................................................49
3C Labor ................................................................................................................................................................51Winter Operations Training ...........................................................................................................................52
4. Performance .....................................................................................................................................694A Compass ..........................................................................................................................................................704B Winter Maintenance Management ................................................................................................................70
Storm Reports ................................................................................................................................................71Winter Patrol Sections ...................................................................................................................................72Route Optimization ........................................................................................................................................72
4C Response Time ................................................................................................................................................73Maintenance Crew Reaction Time ................................................................................................................73Time to Bare/Wet Pavement .........................................................................................................................74
4D Costs ................................................................................................................................................................754E Travel and Crashes ..........................................................................................................................................80
5. Looking Ahead..................................................................................................................................111
Appendix ................................................................................................................................................113
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List of Tables
1. Introduction.......................................................................................................................................5Table 1.1. Statewide Summary: This Winter Versus Last Winter, by the Numbers .........................................6Table 1.2. Highway Categories for Winter Maintenance ....................................................................................8Table 1.3. County Winter Service Groups ............................................................................................................9Table 1.4. Winter in Wisconsin, 2016–2017 ......................................................................................................13
2. Winter Weather ................................................................................................................................19Table 2.1. Storms and Incidents .........................................................................................................................25
3. Winter Operations ............................................................................................................................31Table 3.1. Statewide Prewetting Agent Use for Salt ...........................................................................................38Table 3.2. Cost of Anti-icing vs. Deicing ..............................................................................................................39Table 3.3. Statewide Anti-icing Agent Use ...........................................................................................................39Table 3.4. Labor Hours/Lane Miles/Severity Index Ranking .............................................................................60
4. Performance .....................................................................................................................................69Table 4.1. Statewide Compass Measures for Winter .........................................................................................70Table 4.2. Average Patrol Section Lengths by Winter Service Group ................................................................72Table 4.3. Maintenance Crew Reaction Time .....................................................................................................74Table 4.4. Average Time to Bare/Wet Pavement ................................................................................................74Table 4.5. Total Winter Costs Relative to Winter Severity ..................................................................................75Table 4.6. Winter Costs as Billed to WisDOT by Counties ..................................................................................78Table 4.7. Crashes and Vehicle Miles Traveled by Region .................................................................................82Table 4.8. Winter Maintenance Sections ............................................................................................................85Table 4.9. Storm Start vs. Crew Out ....................................................................................................................86Table 4.10. Winter Maintenance Costs per Lane Mile .......................................................................................92Table 4.11. Cost per Lane Mile per Severity Index Ranking ..............................................................................98Table 4.12. Crashes per 100 Million Vehicle Miles of Travel .............................................................................106Table 4.13. Motor Vehicle Crashes on Roads with Snow/Ice/Slush .................................................................109
Appendix ................................................................................................................................................113Table A-1. Storm Report Summary ......................................................................................................................117Table A-2. Weather Forecasting Service Usage ..................................................................................................129Table A-3. Anti-icing Details ..................................................................................................................................135Table A-4. Annual Anti-icing Agent Usage ............................................................................................................143Table A-5. Actual Anti-Icing Costs .........................................................................................................................149Table A-6. Salt Brine Use ......................................................................................................................................152Table A-7. Annual Prewetting Agent Usage for Salt .............................................................................................154Table A-8. Annual Abrasives Usage and Prewetting Agent Usage for Abrasives...............................................160Table A-9. History of Salt Use on State Trunk Highways .....................................................................................166
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List of Figures
1. Introduction.......................................................................................................................................5Figure 1.1. WisDOT Regional Divisions ................................................................................................................8
2. Winter Weather ................................................................................................................................19Figure 2.1. Statewide Snowfall, 2016–2017 ......................................................................................................20Figure 2.2. Winter Severity Index, 2016–2017 ..................................................................................................21Figure 2.3. 2016–2017 Winter Severity Index vs. 5-Year Average ....................................................................21
3. Winter Operations ............................................................................................................................31Figure 3.1. Salt Use per Lane Mile and Average Severity Index ........................................................................32Figure 3.2. Salt Used per Lane Mile and Severity Index ....................................................................................33Figure 3.3. Salt Prices Across the United States ................................................................................................34Figure 3.4. Salt Prices Over Time ........................................................................................................................35Figure 3.5. Statewide Sand Use From Storm Reports Data...............................................................................36Figure 3.6. Anti-icing as a Percentage of Winter Costs ......................................................................................39Figure 3.7. Counties Using Anti-Icing ...................................................................................................................40Figure 3.8. Counties Using Closed Loop Ground Speed Controllers .................................................................41Figure 3.9. Counties Using Underbody Plows .....................................................................................................42Figure 3.10. Counties Prewetting Salt .................................................................................................................43Figure 3.11. Counties Using Route Optimization ................................................................................................44 Figure 3.12. 2016–2017 Salt Use per Lane Mile vs. 5-Year Average - WI ........................................................55Figure 3.13. Gallons of Brine/Lane-Mile .............................................................................................................56Figure 3.14. Tons of Salt/Lane-Mile ....................................................................................................................57Figure 3.15. Winter Cost/Lane-Mile ....................................................................................................................58Figure 3.16. Labor Cost/Lane-Mile ......................................................................................................................59
4. Performance .....................................................................................................................................69Figure 4.1. Winter Costs per Lane Mile ...............................................................................................................75Figure 4.2. Total Winter Maintenance Cost by Region .......................................................................................75Figure 4.3. Statewide Winter Costs by Category .................................................................................................76Figure 4.4. Regional Winter Costs by Category ...................................................................................................77Figure 4.5. Costs per Lane Mile by Category ......................................................................................................79Figure 4.6. Winter Crashes and Winter Severity Index .......................................................................................81Figure 4.7. Winter Crashes by Highway Type .......................................................................................................82Figure 4.8. 2016–2017 Winter Costs vs. 5-Year Average ..................................................................................97
Appendix ................................................................................................................................................113Figure A-1. WisDOT Regional Map .......................................................................................................................115
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Glossary
AVL - GPS: Automated Vehicle Location - Global Positioning System
BHM: Bureau of Highway Maintenance
BMP: Best Management Practice
BTO: Bureau of Traffic Operations
FHWA: Federal Highway Administration
GUI: Graphical User Interface
MDSS: Maintenance Decision Support System
NWS: National Weather Service
RWIS: Roadway Weather Information System
STOC: State Traffic Operations Center
WISDOT: State of Wisconsin Department of Transportation
5
To our partnersWhether you are in Ashland County along Lake Superior or Kenosha County on the southern border, fighting winter storms in Wisconsin can vary greatly. But geography isn’t the only variable in keeping the roads safe for travelers. The weather and the roads themselves can make the difference in how the road is treated. From two-lane sheltered roadways, to four-lane interstates with frequently windy conditions to six-lane urban highways with high traffic volumes, different roads require different treatments to meet the public’s expectation that the road will be traversable in a reasonable amount of time after a winter storm.
The Wisconsin Department of Transportation commends county maintenance crews, staff and administration for their dedicated and timely response to every winter storm and for working with us to be increasingly cost effective and good stewards of Wisconsin’s environment. The Bureau of Highway Maintenance also recognizes the WisDOT regional staff and management who coordinate these efforts, provide priorities and stress the importance of improving processes in winter maintenance. The unique partnership between the counties and state DOT continues to prove to be economical for Wisconsin’s taxpayers.
This report is a compilation of information and data from many resources:
• winter incident and storm reporting by county staff;
• salt purchasing and use data from DOT records and contracts with salt vendors;
• information from other partnering states who participate in Clear Roads and MDSS pooled fund studies;
• MDSS (Maintenance Decision Support System).
There is a wide range of material in this report – valuable for both high-level overviews and detailed analysis. There are also links to other sites and resources which can provide more detail and information -- including to WisDOT’s Highway Maintenance Manual, which is the defining policy document for state highway maintenance. If you need additional information, you may contact your regional WISDOT representative or Allan Johnson, WISDOT’s state winter maintenance engineer, at [email protected].
Sincerely,
James P. Hughes, P.E. State Highway Maintenance EngineerBureau of Highway Maintenance
Introduction1
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Infrastructure
2015-2016 winter 2016-2017 winter
Lane miles 34,486 miles 34,620 miles
Patrol sections 754.0 755.0
Average patrol section length 45.73 lane miles 45.85 lane miles
Weather
Average statewide Winter Severity Index (100=normal) 90.35 91.14
Number of storms, statewide average and range across counties
Average: 29Range: 8 to 64
Average: 26Range: 13-55
Snowfall, statewide average and range across counties Average: 58.3 inches Range: 23 to 212 inches
Average: 60.2Range: 14.8 to 132
Materials1
Salt used 399,046 tons11.6 tons per lane mile
526,199 tons15.2 tons per lane mile
Average cost of salt $71.35 per ton $68.74 per ton
Prewetting liquid used 2,116,648 gal. 3,018,207 gal.
Anti-icing agents used 1,909,207 gal. 1,918,324 gal.
Sand used 9,255 cubic yd. 14,036 cubic yd.
Costs, Equipment and Performance
Total winter costs2 $71,988,308 $87,836,693
Total winter costs per lane mile $2,087 $2,537
Average crew reaction time from start of storm 4.34 hours 2.22 hours
Percentage of roads to bare/wet pavement (Within WisDOT target times) 74% 70%
Road Weather Information System (RWIS) stations 65 68
Counties with salt spreaders equipped with on-board prewetting unit 68 of 72 (94%) 68 of 72 (94%)
Counties with salt spreaders equipped with ground-speed controller unit 68 of 72 (94%) 68 of 72 (94%)
Underbody plows 355 355
Counties with underbody plows 54 of 72 (75%) 54 of 72 (75%)
Counties equipped to use anti-icing agents 66 of 72 (92%) 66 of 72 (92%)
Counties that used anti-icing agents during the winter season 63 of 72 (88%) 63 of 72 (88%)
Labor and Services
Regular county winter labor hours3 142,983 hrs. 147,395 hrs.
Overtime county winter labor hours 82,630 hrs. 122,220 hrs.
Public service announcements aired 4,971 total4,311 radio; 660 TV
13,936 total12,269 radio; 1,667 TV
Cost of public service announcements$36,000
($195,381 market value)
$36,000 ($498,411
market value)
1. All material usage quantities are from the county storm reports except for salt. Salt quantities are from WisDOT’s Salt Inventory Reporting System.2. Costs refer to final costs billed to WisDOT for all winter activities, including activities such as installing snow fences and thawing culverts. 3. Labor hours come from county storm reports, and reflect salting, sanding, plowing and anti-icing efforts.
Table 1.1. Statewide Summary: This Winter Versus Last Winter, by the Numbers
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ABOUT THIS REPORTEvery year, WisDOT gathers a multitude of data on winter weather and the state’s response to it. Tracking and analyzing this data helps us become more efficient by identifying good performance as well as areas that need improvement. In this way we use our limited resources to achieve the greatest benefit.
Through this report, WisDOT’s Bureau of Highway Maintenance shares data with the department’s regional maintenance staff and with our partners in the county highway departments. This allows regional and county staff to compare resource use with that of their peers across the state. The report has also been shared with the WisDOT Secretary’s Office, the state legislature, national organizations such as Clear Roads, and the general public.
REPORT STRUCTURE AND DATA SOURCESFollowing this section, this report is divided into four main sections:
• Section 2: Weather
• Section 3: Winter Operations
• Section 4: Performance
• Section 5: Looking Ahead
Each section has several subsections; refer to the Table of Contents for more detail. To improve readability,the report includes more statewide summary tables within the text, while county-by-county data appears at the end of each section.
Within many of the county-by-county tables in this report, the counties are grouped by region, in acknowledgement of the role that WisDOT’s regional staff plays in coordinating winter maintenance in their counties. In some tables, counties are divided by Winter Service Group (Groups A, B, C , D, E and F), which reflect the difference in the level of service provided on roads in these counties and facilitate comparisons within these groups. See Table 1.3 on page 9 for more information on Winter Service Groups.
In most tables, raw numbers (such as total salt used) are presented along with data that has been adjusted for differences between counties (such as salt used per lane mile per Winter Severity Index point). This allows more accurate comparisons between regions in different parts of the state.
This report presents data from several sources:
• The weekly winter storm reports completed by the county highway departments, which detail the counties’ estimates of the weather they faced and the materials, equipment and labor they used in responding to it. (See Section 4 for more information about storm reports.)
• Final cost and materials data as billed to WisDOT.
• Data on weather, crashes, travel and other topics from other bureaus within WisDOT and other agencies.
The final billed amounts are considered the most accurate source of cost and materials data, and are presented wherever possible.
When interpreting the data in this report, readers should remember that many factors affect a county’s response to winter, including the local Winter Severity Index, local traffic generators, the mix of highway types and classifications in a county, the type of equipment being used, and the length of patrol sections. Some tables in this report give data that is adjusted for one or more of these factors (for example, salt use per lane mile per severity index point), while others provide raw data.
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WORKING WITH COUNTY HIGHWAY DEPARTMENTS WisDOT’s Bureau of Highway Maintenance, in partnership with the five WisDOT regional offices, is responsible for the maintenance of the state trunk and Interstate highway system. This system includes 34,620 lane miles of highway and around 4,570 bridges.
WisDOT contracts with the state’s 72 county highway departments to provide snow and ice control on all state- and U.S.-owned highways in Wisconsin, including the Interstate system. This partnership was set up more than 100 years ago and is unique in the nation.
This relationship benefits both WisDOT and the county highway departments. WisDOT receives the services of a skilled, experienced work force at fair labor rates, and the counties are able to purchase more pieces and types of equipment than they could otherwise afford. This equipment is then available for use on both county and state roads, an arrangement that allows WisDOT and the counties to avoid duplicating equipment and facilities. This arrangement also allows for increased efficiencies in work crews, thus reducing labor costs to taxpayers.
Staff at WisDOT’s five regional offices work closely with the county highway departments. Regional managers administer the contracts with the counties, and work with the counties to plan maintenance activities and set priorities. Regional staff oversee county highway departments’ maintenance expenditures, and are responsible for ensuring that the counties use resources efficiently and adhere to state guidelines for materials use. Regional staff also serve as a resource for the counties on state and federal rules and regulations, and can provide training assistance.
Snow Removal StrategyIn order to gain the most benefit from limited resources, counties provide different levels of service on highways according to the amount of daily traffic they receive. High-volume roads typically receive 24-hour coverage, while lower-volume roads receive 18-hour coverage. On 18-hour routes the service hours are adjusted based on timing of the storms. On lower-volume four-lane highways, the passing lanes may receive less attention than the driving lanes and ramps.
Table 1.2 shows how WisDOT categorizes the state’s highways for winter maintenance.
Category Definition Lane miles % of total
1 Major urban freeways and most highways with six lanes and greater 3,436 10%
2 High volume four-lane highways (Average Daily Traffic > 25,000) and some four-lane highways (ADT < 25,000), and some 6-lane highways. 3,269 9%
3 All other four-lane highways (ADT < 25,000) 8,861 26%
4 Most high volume two-lane highways (ADT > 5,000) and some 2-lanes (ADT <5000) 4,680 14%
5 All other two-lane highways 14,376 42%
Total 34,620
Table 1.2. Highway Categories for Winter Maintenance
Figure 1.1. WisDOT Regional DivisionsFigure 1.1. WisDOT Regional Divisions
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To facilitate comparisons between counties that provide similar levels of service, WisDOT divides the 72 counties into six Winter Service Groups—A, B, C, D, E and F, with A being the most urban and F the most rural. Table 1.3 explains the divisions between the groups. This table also shows which counties are assigned to each service group. In many tables throughout this report, the counties are arranged according to these groups. Group A contains the fewest counties, while Group B has the most.
In addition, each county highway department divides its highways into winter patrol sections. One snowplow truck is generally assigned to each patrol section. This winter, there were 755 patrol sections on state-maintained highways, with an average of 45.85 lane miles per patrol section. Patrol section length is another factor that can affect performance; see Section 4 for a complete discussion of patrol sections.
Winter ServiceGroup
Definition County Names Number of Counties
% of Counties
A
• 1,000 or more lane miles and all counties have some roads with six or more lanes
• 900,000 or more square feet of bridge deck
• 20 or more plow routes; most routes are 24 hour routes
Dane, Milwaukee,Waukesha 3 4%
B
• 600 to 1,000 lane miles; some counties have roads with six or more lanes; all counties have high mileage on four-lane roads
• 400,000 to 900,000 square feet of bridge deck
• 14 to 20 plow routes; most routes are 24 hour routes
Brown, Chippewa, Columbia, Dodge, Eau Claire, Fond du Lac, Grant, Jefferson, Kenosha, Marathon, Monroe, Outagamie, Portage, Racine, Rock, Sauk, St. Croix, Walworth, Washington, Waupaca, Winnebago
21 29%
C
• 450 to 600 lane miles; some counties have roads with six or more lanes; all counties medium mileage on four-lane roads
• 170,000 to 450,000 square feet of bridge deck
• 7 to 14 plow routes; mix of 18 and 24 hour routes
Barron, Clark, Crawford, Douglas, Dunn, Iowa, Jackson, Juneau, La Crosse, Lincoln, Manitowoc, Oconto, Pierce, Shawano, Sheboygan, Vernon, Wood
17 24%
D
• 325 to 450 lane miles; no counties have roads with six or more lanes; all counties have low to medium mileage on four-lane roads; highest mileage is in two-lane roads
• 140,000 to 170,000 square feet of bridge deck
• 4 to 7 plow routes; mix of 18 and 24 hour routes
Bayfield, Buffalo, Door, Green, Lafayette, Marinette, Marquette, Oneida, Ozaukee, Polk, Richland, Trempealeau, Washburn, Waushara
14 19%
E
• 175 to 325 lane miles; no counties have roads with six or more lanes; few counties have four-lane roads; medium to high mileage on two-lane roads
• 50,000 to 140,000 square feet of bridge deck
• 2 to 4 plow routes; nearly all with 18 hour routes
Ashland, Burnett, Calumet, Forest, Iron, Langlade, Pepin, Price, Rusk, Sawyer, Taylor, Vilas 12 17%
F
• 90 to 175 lane miles; no counties have roads with six or more lanes; counties have 0 to 5 lane miles of four-lane roads; two-lane roads have low to medium mileage
• Less than 50,000 square feet of bridge deck
• Fewer than 2 plow routes; all 18 hour routes
Adams, Florence, Green Lake, Kewaunee, Menominee 5 7%
Table 1.3. County Winter Service Groups
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THIS WINTER IN WISCONSINTable 1.4 on pages 13-17 summarizes key data from this winter for all 72 counties, including total salt use and cost data. This table facilitates comparisons in these core areas across regions and counties, and serves as a quick reference for commonly used data. Data are sorted by salt used per lane mile per Severity Index. The table uses a similar format to the Storm Report Summary (Table A-1 on pages 117-122 of the Appendix), but the cost data in Table 1.4 are actual billed costs as submitted to WisDOT by the counties, rather than estimates from the storm reports.
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COUNTY-BY-COUNTY
QUICK REFERENCE WINTER SUMMARY TABLE
FOR SECTION 1: INTRODUCTION
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NC
Table 1.4. Winter in Wisconsin, 2016-2017
County Lane milesSeverity
IndexSnowfall(inches)
Total salt used (tons)
Salt used (tons) per lane mile
Salt used per lane mile per Severity
IndexTotal salt
costs
Total salt costs
per lane mile
Total winter costs
Totalwinter
costs per lane mile
Totalwinter
costs per lane mile
perSeverity
IndexNorth Central Region
Adams 193.20 111.59 45.8 3,374 17.47 0.16 $272,218 $1,409 $573,424 $2,968 $26.60Florence 141.07 132.71 91.6 2,627 18.62 0.14 $182,446 $1,293 $401,903 $2,849 $21.47Forest 312.38 108.97 90.3 4,434 14.20 0.13 $298,456 $955 $707,869 $2,266 $20.80Green Lake 158.44 79.01 42.0 1,599 10.09 0.13 $111,822 $706 $294,407 $1,858 $23.52Iron 249.56 145.20 131.9 5,063 20.29 0.14 $369,230 $1,480 $794,966 $3,185 $21.94Langlade 299.21 106.60 72.3 3,533 11.81 0.11 $228,901 $765 $629,835 $2,105 $19.75Lincoln 405.55 125.63 86.0 4,887 12.05 0.10 $353,616 $872 $1,077,493 $2,657 $21.15Marathon 874.81 112.64 64.2 11,158 12.75 0.11 $863,140 $987 $2,071,933 $2,368 $21.03Marquette 245.75 58.14 40.5 4,541 18.48 0.32 $328,253 $1,336 $649,598 $2,643 $45.46Menominee 90.26 77.67 58.7 1,558 17.26 0.22 $97,132 $1,076 $190,488 $2,110 $27.17Oneida 396.79 107.70 86.3 8,247 20.78 0.19 $629,491 $1,586 $1,308,566 $3,298 $30.62Portage 584.63 112.02 61.7 7,415 12.68 0.11 $552,286 $945 $1,601,886 $2,740 $24.46Price 322.26 142.11 126.0 4,203 13.04 0.09 $313,860 $974 $773,357 $2,400 $16.89Shawano 520.57 93.65 72.9 7,968 15.31 0.16 $505,930 $972 $1,305,431 $2,508 $26.78Vilas 305.24 127.73 108.5 6,083 19.93 0.16 $480,346 $1,574 $1,051,479 $3,445 $26.97Waupaca 546.74 88.42 51.9 7,702 14.09 0.16 $507,864 $929 $1,296,495 $2,371 $26.82Waushara 345.01 86.57 52.6 3,612 10.47 0.12 $244,441 $709 $573,587 $1,663 $19.20Wood 422.62 107.76 72.7 6,695 15.84 0.15 $507,262 $1,200 $988,873 $2,340 $21.71
Region total 6,414.09 94,700 $6,846,692 $16,291,588Region average 356.34 106.90 75.3 5261 14.76 0.14 $380,372 $1,067 $905,088 $2,540 $23.76
Sources: Cost data are final billed costs as billed to WisDOT by the counties. Salt data is taken from WisDOT's Salt Inventory Reporting System.
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Table 1.4. Winter in Wisconsin, 2016-2017
County Lane milesSeverity
IndexSnowfall(inches)
Total salt used (tons)
Salt used (tons) per lane mile
Salt used per lane mile per Severity
IndexTotal salt
costs
Total salt costs
per lane mile
Total winter costs
Totalwinter
costs per lane mile
Totalwinter
costs per lane mile
perSeverity
Index
Northeast RegionBrown 890.40 66.41 64.1 12,709 14.27 0.21 $732,820 $823 $2,052,368 $2,305 $34.71Calumet 201.71 95.00 58.2 1,804 8.94 0.09 $110,178 $546 $406,701 $2,016 $21.22Door 271.80 84.58 63.9 3,541 13.03 0.15 $230,004 $846 $766,700 $2,821 $33.35Fond du Lac 605.30 71.19 55.0 8,118 13.41 0.19 $561,731 $928 $1,454,304 $2,403 $33.75Kewaunee 111.35 63.96 65.5 1,313 11.79 0.18 $78,014 $701 $222,751 $2,000 $31.28Manitowoc 426.01 78.98 58.5 6,165 14.47 0.18 $381,691 $896 $1,158,183 $2,719 $34.42Marinette 436.66 125.00 68.4 5,553 12.72 0.10 $370,546 $849 $883,441 $2,023 $16.19Oconto 468.90 92.14 58.9 5,014 10.69 0.12 $326,068 $695 $868,436 $1,852 $20.10Outagamie 538.63 72.91 56.7 4,941 9.17 0.13 $305,476 $567 $1,275,031 $2,367 $32.47Sheboygan 527.86 81.72 57.1 8,721 16.52 0.20 $598,497 $1,134 $1,321,889 $2,504 $30.64Winnebago 626.56 66.88 46.0 9,081 14.49 0.22 $581,263 $928 $1,601,661 $2,556 $38.22
Region total 5,105.18 66,960 $4,276,288 $12,011,465Region average 464.11 81.71 59.3 6087 13.12 0.16 $388,753 $838 $1,091,951 $2,353 $28.80
Sources: Cost data are final billed costs as billed to WisDOT by the counties. Salt data is taken from WisDOT's Salt Inventory Reporting System.
NE
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Table 1.4. Winter in Wisconsin, 2016-2017
County Lane milesSeverity
IndexSnowfall(inches)
Total salt used (tons)
Salt used (tons) per lane mile
Salt used per lane mile per Severity
IndexTotal salt
costs
Total salt costs
per lane mile
Total winter costs
Totalwinter
costs per lane mile
Totalwinter
costs per lane mile
perSeverity
IndexNorthwest Region
Ashland 245.35 144.99 119.6 2,691 10.97 0.08 $191,453 $780 $555,915 $2,266 $15.63Barron 428.77 115.12 63.1 3,979 9.28 0.08 $285,141 $665 $982,278 $2,291 $19.90Bayfield 316.42 143.66 96.0 4,976 15.73 0.11 $328,683 $1,039 $807,830 $2,553 $17.77Buffalo 317.02 98.17 69.3 3,188 10.06 0.10 $224,572 $708 $581,655 $1,835 $18.69Burnett 237.93 97.80 45.4 2,986 12.55 0.13 $199,384 $838 $724,224 $3,044 $31.12Chippewa 654.65 96.46 85.9 12,230 18.68 0.19 $921,625 $1,408 $2,028,369 $3,098 $32.12Clark 402.56 103.14 83.2 5,083 12.63 0.12 $392,906 $976 $909,985 $2,260 $21.92Douglas 451.40 168.87 84.7 7,713 17.09 0.10 $463,694 $1,027 $1,226,879 $2,718 $16.09Dunn 519.24 96.23 63.3 10,075 19.40 0.20 $750,600 $1,446 $1,505,687 $2,900 $30.13Eau Claire 540.70 64.13 58.1 11,059 20.45 0.32 $842,691 $1,559 $1,654,632 $3,060 $47.72Jackson 515.44 67.43 53.5 8,531 16.55 0.25 $668,527 $1,297 $1,452,745 $2,818 $41.80Pepin 112.38 93.23 58.3 698 6.21 0.07 $53,661 $477 $208,398 $1,854 $19.89Pierce 369.46 90.76 59.1 4,340 11.75 0.13 $311,058 $842 $804,266 $2,177 $23.98Polk 385.81 126.40 55.1 5,244 13.59 0.11 $383,998 $995 $856,407 $2,220 $17.56Rusk 213.47 90.36 60.4 2,415 11.31 0.13 $181,706 $851 $445,642 $2,088 $23.10Saint Croix 645.34 83.62 59.2 12,199 18.90 0.23 $840,313 $1,302 $1,793,155 $2,779 $33.23Sawyer 367.44 112.20 58.4 4,285 11.66 0.10 $330,219 $899 $664,549 $1,809 $16.12Taylor 233.90 110.61 66.5 3,233 13.82 0.12 $273,609 $1,170 $593,046 $2,535 $22.92Trempeleau 442.48 81.87 64.1 6,902 15.60 0.19 $498,825 $1,127 $1,045,931 $2,364 $28.87Washburn 372.14 101.72 46.2 6,151 16.53 0.16 $413,972 $1,112 $866,989 $2,330 $22.90
Region total 7,771.90 117,978 $8,556,636 $19,708,581Region average 388.60 104.34 67.5 5899 14.14 0.14 $427,832 $1,101 $985,429 $2,536 $24.30
Sources: Cost data are final billed costs as billed to WisDOT by the counties. Salt data is taken from WisDOT's Salt Inventory Reporting System.
NW
16 // W i s D O T | A n n u a l W i n t e r M a i n t e n a n c e R e p o r t
Table 1.4. Winter in Wisconsin, 2016-2017
County Lane milesSeverity
IndexSnowfall(inches)
Total salt used (tons)
Salt used (tons) per lane mile
Salt used per lane mile per Severity
IndexTotal salt
costs
Total salt costs
per lane mile
Total winter costs
Totalwinter
costs per lane mile
Totalwinter
costs per lane mile
perSeverity
Index
Southeast RegionKenosha 653.56 66.20 14.8 10,524 16.10 0.24 $654,645 $1,002 $1,483,608 $2,270 $34.29Milwaukee 1,955.81 62.67 36.7 27,642 14.13 0.23 $1,660,987 $849 $6,274,416 $3,208 $51.19Ozaukee 309.19 66.92 53.0 6,985 22.59 0.34 $409,576 $1,325 $1,043,878 $3,376 $50.45Racine 681.88 65.10 50.9 7,950 11.66 0.18 $500,188 $734 $1,252,592 $1,837 $28.22Walworth 706.03 65.50 36.4 12,878 18.24 0.28 $765,417 $1,084 $1,716,710 $2,431 $37.12Washington 611.91 78.49 54.4 12,212 19.96 0.25 $797,154 $1,303 $1,848,309 $3,021 $38.48Waukesha 1,073.97 54.70 44.2 20,596 19.18 0.35 $1,279,568 $1,191 $2,627,918 $2,447 $44.73
Region total 5,992.35 98,787 $6,067,535 $16,247,431Region average 856.05 65.65 41.5 14112 16.49 0.25 $866,791 $1,013 $2,321,062 $2,711 $41.30
Sources: Cost data are final billed costs as billed to WisDOT by the counties. Salt data is taken from WisDOT's Salt Inventory Reporting System.
SE
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Table 1.4. Winter in Wisconsin, 2016-2017
County Lane milesSeverity
IndexSnowfall(inches)
Total salt used (tons)
Salt used (tons) per lane mile
Salt used per lane mile per Severity
IndexTotal salt
costs
Total salt costs
per lane mile
Total winter costs
Totalwinter
costs per lane mile
Totalwinter
costs per lane mile
perSeverity
IndexSouthwest Region
Columbia 787.40 96.38 57.0 18,933 24.04 0.25 $1,509,448 $1,917 $2,749,811 $3,492 $36.23Crawford 395.79 88.75 44.4 4,291 10.84 0.12 $310,976 $786 $694,937 $1,756 $19.78Dane 1,543.70 72.88 30.3 30,402 19.69 0.27 $2,198,247 $1,424 $5,112,227 $3,312 $45.44Dodge 637.85 63.82 49.1 13,465 21.11 0.33 $944,324 $1,480 $1,918,150 $3,007 $47.12Grant 622.06 77.41 32.6 7,594 12.21 0.16 $508,766 $818 $1,084,789 $1,744 $22.53Green 314.64 62.48 34.2 2,139 6.80 0.11 $159,981 $508 $465,386 $1,479 $23.67Iowa 473.13 84.40 36.4 6,799 14.37 0.17 $488,133 $1,032 $1,157,080 $2,446 $28.98Jefferson 549.67 63.75 34.2 9,057 16.48 0.26 $619,560 $1,127 $1,322,027 $2,405 $37.73Juneau 496.27 76.38 59.5 8,215 16.55 0.22 $634,923 $1,279 $1,304,123 $2,628 $34.40LaCrosse 503.31 46.37 58.0 6,959 13.83 0.30 $471,810 $937 $1,245,319 $2,474 $53.36Lafayette 299.38 63.03 24.4 2,249 7.51 0.12 $158,327 $529 $524,772 $1,753 $27.81Monroe 654.43 92.34 60.6 11,241 17.18 0.19 $853,344 $1,304 $1,629,259 $2,490 $26.96Richland 327.64 82.23 34.1 3,359 10.25 0.12 $258,432 $789 $592,792 $1,809 $22.00Rock 686.50 48.04 36.8 7,730 11.26 0.23 $512,122 $746 $1,256,426 $1,830 $38.10Sauk 576.25 95.71 53.7 9,834 17.07 0.18 $774,051 $1,343 $1,560,638 $2,708 $28.30Vernon 468.36 79.14 41.9 5,507 11.76 0.15 $391,463 $836 $959,892 $2,049 $25.90
Region total 9,336.38 147,773 $10,793,907 $23,577,628Region average 583.52 74.57 43.0 9236 15.83 0.21 $674,619 $1,156 $1,473,602 $2,525 $33.87
Statewide total 34,619.90 60.2 526,198 15.20 $36,541,058 $87,836,693Statewide average 91.14 $1,035 $2,533 $27.79
Sources: Cost data are final billed costs as billed to WisDOT by the counties. Salt data is taken from WisDOT's Salt Inventory Reporting System.
SW
18 // W i s D O T | A n n u a l W i n t e r M a i n t e n a n c e R e p o r t
19
Every winter is different. The number and type of storms, the range of temperatures, the amount of snow – these factors, along with many others, combine to create varying challenges for Wisconsin's county highway departments each year.
The 2016-2017 winter was more mild than the previous year's moderate winter. Above average temperatures were common and snowfall was lighter statewide. This year's snowfall (60 in.) was slightly below the 10-year average of 64 in.
This section describes the weather Wisconsin experienced during the 2016-2017 winter, and the tools and methodologies WisDOT uses to analyze individual storms and the winter as a whole. The Winter Severity Index is one such tool – WisDOT uses it to facilitate comparisons from one winter to the next, and from county to county within the same season.
Statewide average
Range across counties
Total snowfall1 60.2 inches 15-132 inchesWinter Severity Index 91.1 35-185Winter storms 26 13-55Frost events 3.8 0-17Freezing rain events 6.5 1-25
Winter Weather, 2016–2017
1. All data in this table is from Winter Storm Reports, 2016–2017.
Tracking the WinterEach week during winter,
representatives from the 72 county highway departments complete
winter storm reports. These reports give WisDOT the tools to manage statewide materials use
and maintenance expenses as the winter progresses. See page 71 for
more information.
Photo Credit: Pixabay- Creative Commons License
In this section...Winter Weather Challenges.......................20This Winter’s Weather.................................20Winter Severity Index..................................21
Winter Weather2
20 // W i s D O T | A n n u a l W i n t e r M a i n t e n a n c e R e p o r t
WINTER WEATHER CHALLENGESEach year, county highway departments face unique combinations of temperatures and storms, and draw on their experience in deciding what combination of snow and ice control strategies to employ. The number of storms has a more significant impact on resources expended than snowfall totals, since staff and equipment may be mobilized even if only 0.1 inches of snow or freezing rain falls. Weekend and evening storms may also be more costly than weekday storms because of overtime pay.
Storms with low temperatures can be difficult for crews because deicing agents become less effective at lower temperatures. Storms with high winds also are a challenge, because snow blows back onto the roadway quickly after the plows pass.
Counties in the northern half of the state tend to face colder temperatures and heavier snowfall than those in the southern half. Wisconsin’s average annual snowfall ranges from about 40 inches in the south to as much as 160 inches along the shores of Lake Superior. The statewide average annual snowfall is 47.7 inches (30-year normal as recorded by the Wisconsin State Climatology Office).
On average, about 35 to 40 winter weather events hit Wisconsin each winter. While only a couple of large freezing rain events normally strike the state each winter, the state experiences numerous freezing drizzle and freezing fog events that cause roads to ice over.
THIS WINTER’S WEATHERWhile snowfall ended up slightly below average statewide, there was a large variance. Parts of central Wisconsin saw above-average snowfall, while southern Wisconsin ended up well below average. Temperatures averaged about 5 degrees above the mean.
November was very mild with much lower than average snowfall. In fact, only far northern Wisconsin received any significant snowfall. December temperatures returned to more seasonal levels. Most of the state saw above-average snowfall, with the greatest departures being in the southeast. Storms hit much of the state almost weekly, with the heaviest snow falling on December 17 and 18.
January featured a return to milder weather across the state. There were two major events. One hit the north on January 10th, while the second hit west central Wisconsin on the 26th. A significant freezing rain event caused icing conditions across the south on the 17th.
February brought near-record warmth to much of the state. Temperatures were 8 to 10 degrees above average statewide. With the warmth came a dearth of snowfall, though one storm did strike a small part of west central Wisconsin on the 25th.
Figure 2.1. Statewide Snowfall, 2016-2017 From Winter Storm Reports
120
9685132
10945 46 58
9092
126 8655 63 60
86 7259
6786 6459 63 59
6483
73
68
59 586658 6452627369
64 54 5759
584660
53 466158
4241 55 5742 5754 49 535434
4430
333736 4434
5134 363724 15
Snow Totals(Inches)
15 - 37
38 - 53
54 - 69
70 - 96
97 - 132
Note: If you are looking at a black-and-white version of this map, you may download a color version of this report at http://wisconsindot.gov/Pages/doing-bus/local-gov/hwy-mnt/winter-maintenance/default.aspx
2 0 1 6 - 2 0 1 7 | I t ' s O n l y C o l d i f Y o u ' r e S t a n d i n g S t i l l / / 21
7377
11396 92
144
67
125
112
90
94
92
64
169
98
96
142
96
108
79
103
76
96
84
8882
84
71
48
111
98
109
128145
64
73
126
87
63
115 126
89
79
91
107
82
62
64 55
66
112
102
108 66
8246
6758
78
79
133
145
112
8578
64
65
95
66
93
63
67
WINTER SEVERITYINDEX VALUES
<= 60
61 - 90
91 - 120
121 - 150
> 150
Statewide Average: 91.18-Year Average: 102.0
March featured wild swings. It started warm, turned cold for a couple weeks, then rapidly warmed again. These transitions caused March to be snowier than normal across the south, while the north stayed relatively dry.
During the 2016-17 winter season, county highway departments responded to:
• A statewide average of 26 winter events per county, or 3 less than the previous winter. The high was 55 events in Price and Douglas Counties and the low was 13 events in Fond du Lac and Lafayette Counties.
• A statewide average of 4 frost events.
• A statewide average of 7 freezing rain events.
Figure 2.1 shows the total snowfall received in Wisconsin this winter based on storm report data. Snowfall varied significantly across the state; the highest snowfall recorded was in Iron County, at 132 inches; the lowest was in Kenosha County, at 15 inches. Statewide, this winter’s total snowfall of 60.2 inches was slightly below the 10-year average of 64 inches.
WINTER SEVERITY INDEXWisDOT’s Winter Severity Index is a management tool that allows the department to maximize winter maintenance efficiency by evaluating the materials, labor and equipment used based on the severity of the winter in a given county or region.
Developed in 1995, the severity index is calculated using a formula that includes:
• Number of snow events
• Number of freezing rain events
• Total snow amount
• Total storm duration
• Total number of incidents
Since all of these factors can affect materials use, the severity index gives the department a simple way to quantify severity that incorporates multiple factors into a single number. WisDOT uses the severity index in two ways:
1. Season-to-season comparisons. This lets the department compare apples to apples when evaluating materials use and costs over several seasons, and identify trends in winter weather that can be useful in planning materials purchases. In the case of cost trends, adjusting cost data for severity index ranking can help WisDOT separate cost increases due to more severe winters from those due to increased labor costs, equipment costs, lane miles and other factors.
Note: If you are looking at a black-and-white version of the maps on this page, you may download a color version of this report at http://wisconsindot.gov/Pages/doing-bus/local-gov/hwy-mnt/winter-maintenance/default.aspx
Figure 2.2. Winter Severity Index, 2016-2017
Figure 2.3. 2016-2017 Winter Severity Index vs. 5-Year Average (2012–2013 to 2016-2017)
8
8
0
7
0
-2-9
-3
-8
21
-1 -5-12
2
-14
-7
-8 -4
-9-6
-8
2
-1
-27
-30 -25
-11
-33
-15
-9
-12
17
-10
-13
-27
10
-10-12
-4
14
-26
-26
-21
-10
-12
-22
-19
-39
-30
-13
-26
-17
-5
-10
-19
-18 -22
-15
-47-19
-23
-15
15
-31
-12
-12
-16
-26
20
-13
-28
-16
WSI 2016-17 vs5-year average WSI
Much less severe (-15% or less)
Less severe (0 to -14.9%)
More severe (0 to +14.9%
Much more severe (+15% or greater)
22 // W i s D O T | A n n u a l W i n t e r M a i n t e n a n c e R e p o r t
2. Regional comparisons. Since snowfall, number of storms, and other factors vary widely across the state, the severity index also helps WisDOT compare resources use from one region or county to another within a single winter. This allows WisDOT to assess whether materials are being used consistently, whether counties have enough staff, and other factors that affect each region’s response to winter.
Data from weekly storm reports are used to calculate the Winter Severity Index for each county according to a weighted formula. Results are scaled such that the 5-year average is 100. A number above 100 indicates higher-than-average severity; a number below 100 indicates lower-than-average severity. We have begun scaling severity this way in order to make the numbers more easily understood. This winter:
• The statewide average Winter Severity Index was 91.14, which is 14.8 percent lower than the average of the previous five winters (105.9), and 12.3 percent lower than the average of the previous ten winters (103.4).
• Douglas, Ashland/Iron Counties had the highest severity indexes, 169 and 145 respectively.
• La Crosse and Rock Counties had the lowest severity indexes, 46 and 48 respectively.
With some exceptions across the state, this winter was much less severe than normal. Figure 2.2 on the previous page shows how severity index varied by county this winter, while Figure 2.3 shows how this winter’s severity index for each county compares to the average of the previous five years in that county.
Since the Winter Severity Index is an important tool for comparing cost and materials data from year to year, this report includes several charts that compare trends in winter measures over time with changes in severity index.
This includes Figure 3.1, as well as Figure 3.2 (salt used per lane mile; page 33), Figure 4.1 (winter costs; page 70), and Figure 4.6 (winter crashes; page 81).
More information on the severity index is available by request from WisDOT:
• A report describing the process that was used to develop the severity index, including data on the five-year-average severity index for each county (March 1998).
• A table showing Winter Severity Index values for each county for the previous 10 winter seasons.
On pages 25-30, Table 2.1 gives details about the types of storms and other incidents (such as frost, ice, and drifting or blowing snow) that each county experienced this winter, as reported by the counties in their winter storm reports.
2 0 1 6 - 2 0 1 7 | I t ' s O n l y C o l d i f Y o u ' r e S t a n d i n g S t i l l / / 23
COUNTY-BY-COUNTY
TABLES FOR SECTION 2
WINTER WEATHER
24 // W i s D O T | A n n u a l W i n t e r M a i n t e n a n c e R e p o r t
2 0 1 6 - 2 0 1 7 | I t ' s O n l y C o l d i f Y o u ' r e S t a n d i n g S t i l l / / 25
Reg
ion
Cou
nty
Snow
D
epth
Lane
M
iles
Salt
Use
dTo
ns/L
M
Num
ber
ofSt
orm
sW
et
Snow
Dry
Sn
owFr
eezi
ng R
ain
Slee
t
Num
ber
of
Inci
dent
sDrif
ting
Blo
win
g S
now
Fros
tIc
eB
ridge
Dec
ksC
lean
Up
Tabl
e 2.
1. S
torm
s an
d In
cide
nts
Ant
i-Ic
ing
appl
ic.
Type
s of
Sto
rms
Type
s of
Inci
dent
s
From
Win
ter S
torm
Rep
orts
, 201
6-20
17
GR
EE
N L
AK
E42
.015
8.44
1599
10.0
917
113
105
154
63
01
54
NC
WAU
SHAR
A52
.634
5.01
3612
10.4
723
116
84
199
122
10
72
LAN
GLA
DE
72.3
299.
2135
3311
.81
3330
156
132
85
68
011
21
LIN
CO
LN86
.040
5.55
4887
12.0
532
3411
1219
217
61
119
1518
POR
TAG
E61
.758
4.63
7415
12.6
836
227
93
228
72
63
73
MA
RA
THO
N64
.287
4.81
1115
812
.75
3117
96
331
1211
78
117
23
PRIC
E12
6.0
322.
2642
0313
.04
5522
3010
189
84
86
65
8
WAU
PAC
A51
.954
6.74
7702
14.0
924
710
76
238
56
50
133
FOR
ES
T90
.331
2.38
4434
14.1
938
2314
56
82
01
50
43
SHAW
AN
O72
.952
0.57
7968
15.3
125
1114
75
308
42
815
1710
WO
OD
72.7
422.
6266
9515
.84
3117
1411
1117
710
712
08
8
ME
NO
MIN
EE58
.790
.26
1558
17.2
624
911
40
250
00
170
110
ADAM
S45
.819
3.20
3374
17.4
621
236
2514
84
30
40
322
MA
RQ
UE
TTE
40.5
245.
7545
4118
.48
167
86
414
10
24
010
6
FLO
REN
CE
91.6
141.
0726
2718
.62
4140
610
1624
117
96
48
13
VILA
S10
8.5
305.
2460
8319
.93
4732
1210
1621
00
05
119
9
IRO
N13
1.9
249.
5650
6320
.29
5021
226
718
810
08
09
0
ON
EID
A86
.339
6.79
8247
20.7
833
1021
77
62
02
42
14
Reg
ion
Aver
age
75.3
356.
3452
6115
.29
3219
129
819
65
37
29
9
Fina
l tot
als
as o
f Thu
rsda
y, J
une
22, 2
017
Page
1 o
f 6
26 // W i s D O T | A n n u a l W i n t e r M a i n t e n a n c e R e p o r t
Reg
ion
Cou
nty
Snow
D
epth
Lane
M
iles
Salt
Use
dTo
ns/L
M
Num
ber
ofSt
orm
sW
et
Snow
Dry
Sn
owFr
eezi
ng R
ain
Slee
t
Num
ber
of
Inci
dent
sDrif
ting
Blo
win
g S
now
Fros
tIc
eB
ridge
Dec
ksC
lean
Up
Tabl
e 2.
1. S
torm
s an
d In
cide
nts
Ant
i-Ic
ing
appl
ic.
Type
s of
Sto
rms
Type
s of
Inci
dent
s
From
Win
ter S
torm
Rep
orts
, 201
6-20
17
CA
LUM
ET
58.2
201.
7118
048.
9420
915
93
3216
23
50
1013
NE
OU
TAG
AM
IE56
.753
8.63
4941
9.17
2114
43
715
45
68
35
2
OC
ON
TO58
.946
8.90
5014
10.6
924
139
911
253
52
174
1413
KE
WA
UN
EE
65.5
111.
3513
1311
.79
168
71
418
1211
05
09
1
MA
RIN
ETT
E68
.443
6.66
5553
12.7
234
1817
107
488
917
2133
3326
DO
OR
63.9
271.
8035
4113
.03
1818
126
1324
98
816
07
14
FON
D D
U L
AC
55.0
605.
3081
1813
.41
137
41
326
199
55
16
11
BRO
WN
64.1
890.
4012
709
14.2
722
99
14
71
00
42
217
MA
NIT
OW
OC
58.5
426.
0161
6514
.47
179
57
520
35
72
212
22
WIN
NE
BA
GO
46.0
626.
5690
8114
.49
1812
63
823
66
109
811
6
SHEB
OY
GA
N57
.152
7.86
8721
16.5
218
1410
65
279
85
51
1313
Reg
ion
Aver
age
59.3
464.
1160
8712
.68
2012
95
624
86
69
511
13
Fina
l tot
als
as o
f Thu
rsda
y, J
une
22, 2
017
Page
2 o
f 6
2 0 1 6 - 2 0 1 7 | I t ' s O n l y C o l d i f Y o u ' r e S t a n d i n g S t i l l / / 27
Reg
ion
Cou
nty
Snow
D
epth
Lane
M
iles
Salt
Use
dTo
ns/L
M
Num
ber
ofSt
orm
sW
et
Snow
Dry
Sn
owFr
eezi
ng R
ain
Slee
t
Num
ber
of
Inci
dent
sDrif
ting
Blo
win
g S
now
Fros
tIc
eB
ridge
Dec
ksC
lean
Up
Tabl
e 2.
1. S
torm
s an
d In
cide
nts
Ant
i-Ic
ing
appl
ic.
Type
s of
Sto
rms
Type
s of
Inci
dent
s
From
Win
ter S
torm
Rep
orts
, 201
6-20
17
PEP
IN58
.311
2.38
698
6.21
2215
188
1718
1211
1515
27
13N
W
BAR
RO
N63
.142
8.77
3979
9.28
3421
107
827
1314
38
612
2
BUFF
ALO
69.3
317.
0231
8810
.06
2718
143
524
105
214
09
10
ASH
LAN
D11
9.6
245.
3526
9110
.97
4926
205
820
120
35
07
3
RU
SK60
.421
3.47
2414
11.3
136
1913
77
154
22
37
80
SAW
YER
58.4
367.
4442
7611
.64
3620
135
525
99
118
37
0
PIER
CE
59.1
369.
4643
4011
.75
2615
149
1414
76
56
38
5
BUR
NE
TT45
.423
7.93
2986
12.5
536
1616
77
115
62
40
80
CLA
RK
83.2
402.
5650
8312
.63
3020
84
423
168
14
012
9
POLK
55.1
385.
8152
4413
.59
3816
1115
521
1214
112
04
10
TAY
LOR
66.5
233.
9032
3313
.82
3325
149
524
1510
112
811
18
TRE
MP
EAL
EAU
64.1
442.
4869
0215
.60
2318
106
1111
25
26
44
4
BAY
FIE
LD96
.031
6.42
4976
15.7
343
1932
111
4018
95
172
251
WAS
HBU
RN
46.2
372.
1460
5816
.28
3319
1411
1111
35
84
35
7
JAC
KSO
N53
.551
5.44
8531
16.5
520
135
310
163
11
100
110
DO
UG
LAS
84.7
451.
4077
1317
.09
5523
2213
1327
1611
14
821
3
CH
IPP
EW
A85
.965
4.65
1223
018
.68
2525
06
122
149
21
217
3
SAIN
T C
RO
IX59
.264
5.34
1219
918
.90
3217
148
70
00
00
00
0
DU
NN
63.3
519.
2410
075
19.4
029
179
68
185
55
62
95
EAU
CLA
IRE
58.1
540.
7011
059
20.4
522
136
22
100
00
10
61
Reg
ion
Aver
age
67.5
388.
6058
9414
.12
3219
137
819
97
38
310
5
Fina
l tot
als
as o
f Thu
rsda
y, J
une
22, 2
017
Page
3 o
f 6
28 // W i s D O T | A n n u a l W i n t e r M a i n t e n a n c e R e p o r t
Reg
ion
Cou
nty
Snow
D
epth
Lane
M
iles
Salt
Use
dTo
ns/L
M
Num
ber
ofSt
orm
sW
et
Snow
Dry
Sn
owFr
eezi
ng R
ain
Slee
t
Num
ber
of
Inci
dent
sDrif
ting
Blo
win
g S
now
Fros
tIc
eB
ridge
Dec
ksC
lean
Up
Tabl
e 2.
1. S
torm
s an
d In
cide
nts
Ant
i-Ic
ing
appl
ic.
Type
s of
Sto
rms
Type
s of
Inci
dent
s
From
Win
ter S
torm
Rep
orts
, 201
6-20
17
RAC
INE
50.9
681.
8879
5011
.66
185
104
514
72
110
811
3SE
MIL
WAU
KEE
36.7
1,95
5.81
2764
214
.13
1511
27
12
00
20
20
6
KEN
OS
HA
14.8
653.
5610
524
16.1
023
127
71
00
01
00
023
WAL
WO
RTH
36.4
706.
0312
878
18.2
418
104
40
252
45
113
913
WAU
KESH
A44
.21,
073.
9720
596
19.1
817
107
54
21
01
10
021
WAS
HIN
GTO
N54
.461
1.91
1221
219
.96
1812
44
316
102
94
13
8
OZA
UKE
E53
.030
9.19
6985
22.5
919
119
42
125
33
21
57
Reg
ion
Aver
age
41.5
856.
0514
112
17.4
118
106
52
104
23
42
412
Fina
l tot
als
as o
f Thu
rsda
y, J
une
22, 2
017
Page
4 o
f 6
2 0 1 6 - 2 0 1 7 | I t ' s O n l y C o l d i f Y o u ' r e S t a n d i n g S t i l l / / 29
Reg
ion
Cou
nty
Snow
D
epth
Lane
M
iles
Salt
Use
dTo
ns/L
M
Num
ber
ofSt
orm
sW
et
Snow
Dry
Sn
owFr
eezi
ng R
ain
Slee
t
Num
ber
of
Inci
dent
sDrif
ting
Blo
win
g S
now
Fros
tIc
eB
ridge
Dec
ksC
lean
Up
Tabl
e 2.
1. S
torm
s an
d In
cide
nts
Ant
i-Ic
ing
appl
ic.
Type
s of
Sto
rms
Type
s of
Inci
dent
s
From
Win
ter S
torm
Rep
orts
, 201
6-20
17
GR
EEN
34.2
314.
6421
396.
8019
68
54
125
06
00
914
SW
LAFA
YETT
E24
.429
9.38
2249
7.51
138
37
517
312
56
31
9
RIC
HLA
ND
34.1
327.
6433
5910
.25
1815
910
321
63
314
012
11
CR
AWFO
RD
44.4
395.
7942
9110
.84
2411
135
228
118
616
19
6
RO
CK
36.8
706.
0377
3010
.95
176
114
012
10
11
29
1
VER
NO
N41
.946
8.36
5507
11.7
614
74
54
2112
114
71
29
LA C
RO
SSE
58.0
503.
3161
4012
.20
149
41
34
43
21
03
3
GR
ANT
32.6
622.
0675
9412
.21
1811
84
426
39
119
16
8
IOW
A36
.447
3.13
6799
14.3
722
126
73
213
74
40
812
JEFF
ER
SON
34.2
549.
6790
5716
.48
198
86
213
75
132
06
18
JUN
EAU
59.5
496.
2782
1516
.55
2011
64
720
66
25
49
9
SAU
K53
.757
6.25
9834
17.0
720
1411
96
297
34
170
1321
MO
NR
OE
60.6
654.
4311
241
17.1
829
1614
53
75
40
12
58
DAN
E30
.31,
543.
7030
402
19.6
921
106
42
50
33
20
05
DO
DG
E49
.163
7.85
1346
521
.11
1411
55
611
55
23
15
7
CO
LUM
BIA
57.0
787.
4018
933
24.0
415
118
37
2618
223
24
921
Reg
ion
Aver
age
43.0
584.
7491
8514
.31
1910
85
417
66
46
17
10
Fina
l tot
als
as o
f Thu
rsda
y, J
une
22, 2
017
Page
5 o
f 6
30 // W i s D O T | A n n u a l W i n t e r M a i n t e n a n c e R e p o r t
Reg
ion
Cou
nty
Snow
D
epth
Lane
M
iles
Salt
Use
dTo
ns/L
M
Num
ber
ofSt
orm
sW
et
Snow
Dry
Sn
owFr
eezi
ng R
ain
Slee
t
Num
ber
of
Inci
dent
sDrif
ting
Blo
win
g S
now
Fros
tIc
eB
ridge
Dec
ksC
lean
Up
Tabl
e 2.
1. S
torm
s an
d In
cide
nts
Ant
i-Ic
ing
appl
ic.
Type
s of
Sto
rms
Type
s of
Inci
dent
s
From
Win
ter S
torm
Rep
orts
, 201
6-20
17
481
7296
26.0
15.1
10.4
6.5
6.3
18.5
6.9
5.6
3.8
6.7
2.5
8.6
Stat
ewid
e Av
erag
es8.
8--
14.5
6
Fina
l tot
als
as o
f Thu
rsda
y, J
une
22, 2
017
Page
6 o
f 6
31
Total salt used1 526,198 tonsTotal salt used per lane mile 15.2 tonsTotal cost of salt used2 $36,541,058Average cost per ton of salt $69.44Total prewetting agents used3 3,018,207 gal.Counties prewetting salt 66 of 72 (92%)Total abrasives used 14,467 cubic yardsCounties prewetting abrasives 15 of 47 using sand (32%)Total anti-icing agents used 1,918,324 gal.Counties equipped to use anti-icing 66 of 72 (92%)
MDSS....................................................49Equipment Calibration........................50Product and Equipment Testing.........51Winter Maintenance Research..........52
3C Labor.......................................................54Winter Operations Training ................55
Wisconsin county highway departments use an array of strategies to combat winter storms. Materials, equipment and labor are three key pieces of the puzzle; county patrol superintendents use their skills and experience to combine these pieces in the most efficient way possible for each storm.
This section describes the counties’ response to the 2016-2017 winter season, including materials use, best practices in equipment and technology, and training efforts. Most counties have added prewetting and anti-icing to their arsenal of best practices—strategies that help them use materials efficiently, save money and minimize environmental impacts.
Statewide Materials Use, 2016-2017
1. Salt use data is final data from WisDOT’s Salt Inventory Reporting System.2. Cost data is actual salt costs as billed to WisDOT by the counties. 3. Prewetting, abrasives and anti-icing data are estimates from Winter Storm Reports.
There’s More on the Web!Looking for more information about winter maintenance in
Wisconsin? WisDOT’s extranet site features detailed reports on products, equipment, best
practices and more.
See http://wisconsindot.gov/Pag-es/doing-bus/local-gov/hwy-mnt/winter-maintenance/default.aspx
Winter Operations3
Photo Credit: Pixabay-Creative Commons License
In this section...3A Materials...............................................34
Salt........................................................34Abrasives..............................................38Prewetting............................................39Anti-icing...............................................41
3B Equipment & Technology......................48RWIS ....................................................48
32 // W i s D O T | A n n u a l W i n t e r M a i n t e n a n c e R e p o r t
Figure 3.2 on page 33 shows salt use per lane mile in each county, overlaid with severity index to allow a further “apples to apples” comparison of salt use in each county. The counties in Winter Service Groups A and B have more urban highways and tend to use more salt per lane mile for a given level of severity. See Figure 3.14 on page 57 for a statewide map of tons of salt used per lane-mile.
For more detail on salt use in previous years, see Table A-9, “History of Salt Use on State Trunk Highways,” on page 166 of the Appendix.
Page 1
0
20
40
60
80
100
120
140
160
0.0
5.0
10.0
15.0
20.0
25.0
92-93
93-94
94-95
95-96
96-97
97-98
98-99
99-00
00-01
01-02
02-03
03-04
04-05
05-06
06-07
07-08
08-09
09-10
10-11
11-12
12-13
13-14
14-15
15-16
16-17
Seve
rity
Inde
x
Salt
Use
(Ton
s Pe
r Lan
e M
ile)
WINTER
SALT USE AVG STATEWIDE SEVERITY INDEX
3A. MATERIALSSalt remains the primary material used in winter maintenance. The advent of prewetting technology (see pgs.37-38) use has improved the efficiency of materials use (by keeping more of the material on the road instead of scattering off the edges), and proactive anti-icing applications (see pgs. 39-40) have reduced the amount of salt needed to keep roads clear.
SaltSalt is a critical part of a highway crew’s response to winter storms in Wisconsin. When salt combines with ice or snow, it creates a brine solution with a lower freezing point than water. This solution then acts to break the bond between the ice or packed snow and the pavement, which allows the snow to be removed more easily through plowing.
Due to cost and environmental concerns, maintenance crews strive to use the smallest amount of salt necessary to provide an appropriate level of service for each roadway. Best practices to reduce salt use include prewetting, anti-icing, under body plows, etc.
Historically, counties have used disproportionately more salt during more severe winters. Between the winters of 2006 -07 and 2014-15, Winter Severity Index has fluctuated greatly, as has salt usage. However, the past three winters have been similarly mild with varying levels of salt usage. Figure 3.1 plots the average statewide salt use per lane mile versus the average statewide Winter Severity Index. Looking back over the past 20 plus years of data, this year’s salt use and severity index was most similar to 1995-1996 and 1997-1998. This winter's statewide Winter Severity Index of 91.14 was less than one percent higher than the previous year, while salt use was 32 percent higher than the previous year, at 526,199 tons. See Table 1.4 on pages 13-17 for county-by-county salt use data for this winter.
Wisconsin counties applied a statewide average of 15.2 tons of salt per lane mile on state highways, an increase of thirty-two percent compared with the 2015-2016 winter. (See Figure 3.12 on page 55 for a county-by-county comparison.) When compared with nearby states, which differ by winter severity and level of service standards, Wisconsin salt use is relatively high. In the last year with comparable data available - 2015-2016 - Wisconsin used 11.6 tons of salt per lane mile on state highways. In that same year, Minnesota (5.2 tons per lane mile), Iowa (6.1) and Illinois (7.2) used less while Michigan (15.1)used more (see http://clearroads.org/winter-maintenance-survey/ for updated numbers as they become available). Better use of BMPs may contribute
to other states’ lower rates of salt used per Figure 3.1. Salt Use per Lane Mile and Average Severity Index lane mile, including salt shortages that From Salt Inventory Reporting System, 1992–2017prevented several states from obtaining the Salt-Severity Chart
quantity of salt that they would normally use. TOTAL SALT USE PER LANE MILE AND AVERAGE SEVERITY INDEX
Winter severity also varies from state to state.
2 0 1 6 - 2 0 1 7 | I t ' s O n l y C o l d i f Y o u ' r e S t a n d i n g S t i l l / / 33
Figure 3.2. Salt Used per Lane Mile and Severity IndexFrom Salt Inventory Reporting System, 2016-2017
0
20
40
60
80
100
120
140
160
180
200
-
5.00
10.00
15.00
20.00
25.00
30.00
35.00
Seve
rity
Inde
x
Salt
used
(ton
s)
per l
ane
mile
Salt used per lane mile and Severity Index (Group A)
0
20
40
60
80
100
120
140
160
180
200
-
5.00
10.00
15.00
20.00
25.00
30.00
35.00
Seve
rity
Inde
x
Salt
used
(ton
s)
per l
ane
mile
Salt used per lane mile and Severity Index (Group C)
0
20
40
60
80
100
120
140
160
180
200
-
5.00
10.00
15.00
20.00
25.00
30.00
35.00
Seve
rity
Inde
x
Salt
used
(ton
s)
per l
ane
mile
Salt used per lane mile and Severity Index (Group E)
0
20
40
60
80
100
120
140
160
180
200
-
5.00
10.00
15.00
20.00
25.00
30.00
35.00
Seve
rity
Inde
x
Salt
used
(ton
s)
per l
ane
mile
Salt used per lane mile and Severity Index (Group D)
0
20
40
60
80
100
120
140
160
180
200
-
5.00
10.00
15.00
20.00
25.00
30.00
35.00
Seve
rity
Inde
x
Salt
used
(ton
s)
per l
ane
mile
Salt used per lane mile and Severity Index (Group B)
0
20
40
60
80
100
120
140
160
180
200
-
5.00
10.00
15.00
20.00
25.00
30.00
35.00
Seve
rity
Inde
x
Salt
used
(ton
s)
per l
ane
mile
Salt used per lane mile and Severity Index (Group F)
0
20
40
60
80
100
120
140
160
180
200
-
5
10
15
20
25
30
35
Seve
rity
Inde
x
Salt
used
(ton
s)
per l
ane
mile
Salt used per lane mile and Severity Index (Group A)
Salt used (tons) per lane mile Severity Index
Salt Used per Lane Mile and Severity Index (Group A) Salt Used per Lane Mile and Severity Index (Group B)
Salt Used per Lane Mile and Severity Index (Group C) Salt Used per Lane Mile and Severity Index (Group D)
Salt Used per Lane Mile and Severity Index (Group E) Salt Used per Lane Mile and Severity Index (Group F)
Seve
rity
Inde
x
Seve
rity
Inde
x
Seve
rity
Inde
x
Seve
rity
Inde
x
Seve
rity
Inde
x
Seve
rity
Inde
x
Tons
per
Lan
e M
ile
Tons
per
Lan
e M
ile
Tons
per
Lan
e M
ile
Tons
per
Lan
e M
ile
Tons
per
Lan
e M
ile
Tons
per
Lan
e M
ile
34 // W i s D O T | A n n u a l W i n t e r M a i n t e n a n c e R e p o r t
Figure 3.3. Salt Prices Across the United States 2016-2017Source: Clear Roads
$0
$20
$40
$60
$80
$100
$120
$140
$160
$180
Pric
e pe
r ton
2016-2017 Salt Prices
Wisconsin
2 0 1 6 - 2 0 1 7 | I t ' s O n l y C o l d i f Y o u ' r e S t a n d i n g S t i l l / / 35
Cost of SaltSalt prices have generally leveled out after several years of increases. This winter, WisDOT spent $36,541,058 on salt statewide, purchasing salt at an average of $68.74 per ton. The average of $68.74 per ton is a decrease of four percent (4%) from last year. Each of the previous two winters WisDOT has renewed its existing salt contracts at lower prices in lieu of rebidding.
The department speculates that the flexibility of its contracting method might account for some of these salt price cost savings. Wisconsin’s contracts include a 100 percent provision, which means that the department guarantees that it will purchase 100 percent of the contracted amount of salt. Some other states’ contracts include an 80/120 provision that requires the salt vendor to keep 120 percent of the contracted salt amount on reserve, and commits the state to purchasing only 80 percent of the contracted amount. This 40 percent spread could translate to higher costs for states under an 80/120 contract.
For more on costs, see Section 4 starting on page 69.
A Note About Materials DataThis winter marks the eighth year that all salt data in this report comes from WisDOT’s Salt Inventory Reporting System (SIRS). In previous years, some tables used preliminary salt use data collected in the weekly winter storm reports. Sand use data continues to come from the storm reports, as does some detailed anti-icing and prewetting data. These materials use estimates are included in this report because they provide a level of detail and correlation with storm events that is not available from SIRS or from final financial data. The source of each table’s data is indicated below the table title.
Figure 3.4. Salt Prices Over TimeSource: Historical data supplied by Clear Roads. From 1999 to present, the number of states reporting data has increased from 14 to 34 states.
$0$10$20$30$40$50$60$70$80$90
Average cost per ton of road salt for 14+ states
14+ States WisDOT
36 // W i s D O T | A n n u a l W i n t e r M a i n t e n a n c e R e p o r t
AbrasivesCounty highway departments sometimes use sand and other abrasives to improve vehicles’ traction on icy or snowy roads or when temperatures are too low for salt to be effective. Abrasives are somewhat effective in low-speed trouble spots and intersections. Abrasives should be prewetted with a liquid agent for better adherence to the roadway.
A total of 14,036 cubic yards of sand was used by 47 counties on state highways this winter, a decrease of 82 percent compared with 2007–2008’s record-setting 80,133 cubic yards, and a 38 percent decrease from the average of the five previous winters (23,414 cubic yards).
In 2008, the Bureau of Highway Maintenance commissioned a synthesis report, “Limitations of the Use of Abrasives in Winter Maintenance Operations” to substantiate WisDOT’s guidance to Wisconsin counties on reducing sand use. The report cites factors recommending against the use of sand that have been supported by research, and offers the following general conclusions:
• Sand used in a salt-abrasive mixture has not been shown to reduce accidents.
• Salt is more cost-effective than sand in winter maintenance operations.
• A salt-sand mixture requires approximately three times more material applied to the road to achieve the same effectiveness as pre-wetted salt and results in plows making more frequent return trips to the sand pile to fill up.
The 2008 synthesis report is available on-line at: http://clearroads.org/wp-content/uploads/dlm_uploads/tsr-limitations-of-abrasives.pdf
Figure 3.5 compares this winter’s statewide sand use with previous years’. Refer to Table A-8 on pages 160-165 of the Appendix for county-by-county sand use data for this winter.
Figure 3.5. Statewide Sand Use From Storm Reports Data, 1998-2017
- 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 90,000
1998
-99
1999
-200
020
00-0
120
01-0
220
02-0
320
03-0
420
04-0
520
05-0
620
06-0
720
07-0
820
08-0
920
09-1
020
10-1
120
11-1
220
12-1
320
13-1
420
14-1
520
15-1
620
16-1
7
Sand Used (cubic yards)
2 0 1 6 - 2 0 1 7 | I t ' s O n l y C o l d i f Y o u ' r e S t a n d i n g S t i l l / / 37
Prewetting
Prewetting salt and sand with liquid deicing agents before or during their application to the pavement has several advantages. When used with dry rock salt, prewetting reduces loss of salt from bouncing and traffic action, which reduces the amount of material needed. Prewetting also improves salt penetration into ice and snow pack, and begins dissolving the dry salt, which allows it to work more quickly. When used with abrasives, prewetting helps keep the sand on the pavement and may allow crews to use higher truck spreading speeds.
WisDOT encourages all county highway departments to prewet their salt and sand, and to explore stocking one or more deicing agents so that different agents can be used as conditions warrant. For example, salt brine can be reasonably used at pavement temperatures down to about 15°F, whereas agents such as magnesium chloride and calcium chloride are effective at lower pavement temperatures, to about 0°F. See Table 3.1 on page 38 for details on statewide prewetting agent use.
Salt brine is a relatively inexpensive choice for prewetting. Salt brine use has increased significantly since counties first tested it a decade ago; 64 counties used salt brine for prewetting this winter (see Table A-6 on page 152-153 of the Appendix for details). Counties used more salt brine for prewetting this winter—3,018,207 gallons. Overall use of prewetting salt brine use increased by 43% percent. Nearly all counties are now applying this best practice to their winter road maintenance programs.
In addition to salt brine, some counties used calcium chloride, magnesium chloride, or agricultural-based products for prewetting this year. See Table A-7 on pages 154-159 for details. Organic blends seem to be preferred over the straight chemical products because they stick to pavement longer. The addition of the organics helps reduce corrosion to equipment.
Although once the only option for prewetting, calcium chloride is a more corrosive chemical than other prewetting liquids, and can damage equipment and be more difficult for operators to handle.
BEST PRACTICES: On-Board Prewetting (see Figure 3.10)WisDOT encourages counties to prewet salt before applying it to the roadway. Agencies across the country and worldwide consider prewetting a best practice, and some require that all material be prewetted before it is placed. Studies have shown that prewetting significantly improves the amount of material that stays on the road. On-Board prewetting is preferred because it is the simplest way to ensure that salt is being uniformly prewetted. Some counties choose to prewet their salt directly in the pile. The benefit to this approach is that less equipment is required on salt trucks. Juneau County has had success with this method.
Wisconsin Transportation Bulletin No. 22 (December 2005) notes that as much as 26 percent more salt stays on the roadway when prewetted versus when dry salt is used. Pre-wetting salt has been used since the late 1960s. In addition to reduced loss of salt from bounce and scatter, advantages of pre-wetting salt include:
1) Quicker melting.
2) Better salt penetration into ice and snow pack.
3) Salt melts at lower temperature if wetted with other deicing chemicals(generally limited to pavement temperatures above 20º F).
For more information on prewetting, see Chapter 6, Section 20 of the State Highway Maintenance Manual.
Faster melting action is the main benefit of pre-wetting salt. After 20 minutes the difference is significant. This photo shows two salt particles penetrating ice. The one on the right was pre-wetted.
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Nearly all counties (94 percent) pretreat salt, in which a liquid prewetting agent is spray-applied to the salt supply before the salt is placed in storage. According to the Minnesota Snow and Ice Control Field Handbook for Snowplow Operators (published by the Minnesota Local Road Research Board), when treating a stockpile of salt, a liquid deicing chemical should be applied at a rate of 4 to 6 gallons/ton. Since liquid prewetting increases the leach risk of the stockpile, salt should be stored on an impervious pad.
While prewetting salt is the best practice in Wisconsin—68 of 72 counties (94 percent) prewetted their salt this winter—prewetting abrasives is far less common. Of the 47 counties that used sand this winter, only 15 counties prewetted it (see Table A-8 on pages 160-165 for details). WisDOT strongly encourages counties to prewet their sand, since keeping sand on the pavement can reduce the amount of material used, which saves money and reduces environmental impacts. The Minnesota Snow and Ice Control Field Handbook for Snowplow Operators recommends prewetting sand at a rate of 4 gallons of salt brine/ton of sand.
BEST PRACTICES: Anti-icing (see Figure 3.7)Anti-icing is a best practice not only nationwide, but across the globe. Anti-icing is the process of applying brine to the dry pavement-in the right conditions- prior to a winter storm. Agencies are finding that this technique, once reserved for bridge decks and trouble spots, yields excellent results on highways as well. More agencies are turning to anti-icing to help them use labor and materials ef-ficiently, and to reduce overall salt usage.
This winter, Wisconsin counties used 1,918,324 gallons of anti-icing liquid—the most on record and an increase of 0.5 percent over last winter’s total. Yet at 1.4 percent of total winter expenditures, anti-icing continues to represent a small fraction of winter costs which is why anti-icing is a highly recommended practice when appropriate. For more information on anti-icing, see Chapter 6, Section 15 of the State Highway Maintenance Manual.
Gallons CountiesDeicing Agent Used Using
Salt Brine 2,783,720 66
Calcium Chloride – liquid 76,188 10 Calcium Chloride with rust inhibitor 4,625 1
Magnesium Chloride 10,046 7 Freeze Guard 49,026 10
Ice Ban M80 11,705 3 IceBite 55 2,172 2 MC95 9,399 7 Geomelt 65,124 5 Biomelt 64 455 1 Amp 7,919 10
TOTAL
Calcium Chloride-based Products
Magnesium Chloride-based Products
Agricultural-based Products
68 3,020,379
gallons of liquid
Table 3.1. Statewide Prewetting Agent Use for Salt
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Anti-icingAnti-icing is a proactive snow and ice control strategy that involves applying a small amount of liquid deicing agent to pavements and bridge decks before a storm to prevent snow and ice from bonding with the surface. It is often used prior to light snowfall or freezing drizzle, and is also effective at preventing frost from forming on bridge decks and pavements. Anti-icing can reduce salt use, reduce materials costs, and improve safety.
This winter, counties used a record 1,918,324 gallons of anti-icing liquid (see Table A-4 on pages 143-148 for details). Currently, 66 of 72 counties (92 percent) are equipped to perform anti-icing operations, and this winter all 66 counties made at least one anti-icing application. (Counties may choose not to anti-ice if weather conditions do not warrant it.) The total statewide brine usage of 1,918,324 gallons was a 0.5% increase from the total used in 2015-16. See Figure 3.13 on page 56 for gallons of brine used per lane mile. See Table A-6 on pages 152-153 of the Appendix for county-by-county data on salt brine use.
WisDOT encourages counties to explore stocking one or more agent for prewetting and anti-icing, so that a choice of agents is available for use according to pavement temperature and weather conditions. Table 3.3 shows the agents used for anti-icing in Wisconsin this winter.
Winter Service Group
Counties reporting anti-icing
costs
Counties reporting deicing costs
2012- 2013- 2014- 2015- 2016- 2012- 2013- 2014- 2015- 2016-2013 2014 2015 2016 2017 2013 2014 2015 2016 2017
A $3,630 $2,088 $809 $1,287 $2,245 3 $16,382 $61,801 $26,133 $19,656 $21,706 1B $1,437 $932 $724 $1,033 $1,193 11 $4,240 $5,984 $4,062 $6,178 $4,875 13C $653 $710 $484 $543 $732 6 $1,567 $3,100 $3,223 $2,417 $4,485 16D $692 $789 $834 $618 $829 10 $1,734 $2,661 $2,759 $3,309 $3,766 13E $793 $486 $322 $480 $763 5 $1,770 $2,395 $2,113 $2,080 $2,504 10F $614 $620 $512 $360 $631 1 NA $878 $3,067 $1,163 $1,603 2
Average cost of anti-icing treatment for possible frost Average cost of deicing treatment for frost event
Table 3.2. Cost of Anti-icing vs. Deicing
Chemical Gallons used Counties usingSalt brine 1,865,565 64
Calcium chloride – liquid 10,343 4
Magnesium chloride 4,100 3
Freeze Guard 8,422 3
IceBAN M80 261 1
GeoMelt 17,370 3
Amp 12,424 4
Total 1,918,485 66
Table 3.3. Statewide Anti-icing Agent Use
Note: Total cost data differs slightly from cost data elsewhere in this report due to rounding.
Figure 3.6. Winter Costs by Activity Code, 2016-2017
Plowing & applying chemicals
41%
Nonstorm related winter activities
15%
Applying liquid anti-icing chemicals
1%Alternate chemicals
0%Trucking salt - shed to
shed within county0%
Trucking salt - depot to user county
0%Back pay
0%
Winter activities58%
Salt costs42%
Winter Costs by Activity Code, 2016-2017Actual billed costs, by category
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Bayfield
Price
Marathon
Clark
Marinette
Sawyer
Dane
Grant
Douglas
Oneida
Vilas
Forest
Polk
Taylor
Rusk
Oconto
Iron
Lincoln
Jackson
Ashland
Burnett
Barron
Sauk
Dunn Chippewa
Dodge
Monroe
Iowa
Langlade
Vernon
Portage Wood
Shawano
Rock
Buffalo
Columbia
Saint Croix
Pierce
Lafayette Green
Fond du Lac
Eau Claire
Waushara
Florence
Racine
Juneau
Washburn
Waupaca
Adams
Trempealeau
Jefferson
Richland
Crawford
Brown Outagamie
Walworth
Manitowoc
Door
Waukesha
La Crosse
Sheboygan Marquette
Winnebago
Washington
Green Lake
Calumet
Menominee
Kewaunee Pepin
Kenosha
Ozaukee
Milwaukee
BEST PRACTICESAnti-Icing (2015-16)
Anti-Icing UseHeavy
Some
None
Figure 3.7. Counties Using Anti-Icing
Bayfield
Price
Marathon
Clark
Marinette
Sawyer
Dane
Grant
Douglas
Oneida
Vilas
Forest
Polk
Taylor
Rusk
Oconto
Iron
Lincoln
Jackson
Ashland
Burnett
Barron
Sauk
Dunn Chippewa
Dodge
Monroe
Iowa
Langlade
Vernon
Portage Wood
Shawano
Rock
Buffalo
Columbia
Saint Croix
Pierce
Lafayette Green
Fond du Lac
Eau Claire
Waushara
Florence
Racine
Juneau
Washburn
Waupaca
Adams
Trempealeau
Jefferson
Richland
Crawford
Brown Outagamie
Walworth
Manitowoc
Door
Waukesha
La Crosse
Sheboygan Marquette
Winnebago
Washington
Green Lake
Calumet
Menominee
Kewaunee Pepin
Kenosha
Ozaukee
Milwaukee
BEST PRACTICESAnti-Icing (2016-17)
Anti-Icing UseHeavy
Some
None
Map created: July 2017
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Figure 3.8. Counties Using Closed Loop Ground Speed Controllers
Bayfield
Price
Marathon
Clark
Marinette
Sawyer
Dane
Grant
Douglas
Oneida
Vilas
Forest
Polk
Taylor
Rusk
Oconto
Iron
Lincoln
Jackson
Ashland
Burnett
Barron
Sauk
Dunn Chippewa
Dodge
Monroe
Iowa
Langlade
Vernon
Portage Wood
Shawano
Rock
Buffalo
Columbia
Saint Croix
Pierce
Lafayette Green
Fond du Lac
Eau Claire
Waushara
Florence
Racine
Juneau
Washburn
Waupaca
Adams
Trempealeau
Jefferson
Richland
Crawford
Brown Outagamie
Walworth
Manitowoc
Door
Waukesha
La Crosse
Sheboygan Marquette
Winnebago
Washington
Green Lake
Calumet
Menominee
Kewaunee Pepin
Kenosha
Ozaukee
Milwaukee
BEST PRACTICESClosed-Loop Ground Speed Controllers
Closed Loop Ground Speed Controllers
All
Some
None
Map created: July 2017
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Figure 3.9. Counties Using Underbody Plows
Bayfield
Price
Marathon
Clark
Marinette
Sawyer
Dane
Grant
Douglas
Oneida
Vilas
Forest
Polk
Taylor
Rusk
Oconto
Iron
Lincoln
Jackson
Ashland
Burnett
Barron
Sauk
Dunn Chippewa
Dodge
Monroe
Iowa
Langlade
Vernon
Portage Wood
Shawano
Rock
Buffalo
Columbia
Saint Croix
Pierce
Lafayette Green
Fond du Lac
Eau Claire
Waushara
Florence
Racine
Juneau
Washburn
Waupaca
Adams
Trempealeau
Jefferson
Richland
Crawford
Brown Outagamie
Walworth
Manitowoc
Door
Waukesha
La Crosse
Sheboygan Marquette
Winnebago
Washington
Green Lake
Calumet
Menominee
Kewaunee Pepin
Kenosha
Ozaukee
Milwaukee
BEST PRACTICESUnderbody Plows
UnderbodyPlow Status
Have
Do not have
Map created: July 2017
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Figure 3.10. Counties Prewetting
Bayfield
Price
Marathon
Clark
Marinette
Sawyer
Dane
Grant
Douglas
Oneida
Vilas
Forest
Polk
Taylor
Rusk
Oconto
Iron
Lincoln
Jackson
Ashland
Burnett
Barron
Sauk
Dunn Chippewa
Dodge
Monroe
Iowa
Langlade
Vernon
Portage Wood
Shawano
Rock
Buffalo
Columbia
Saint Croix
Pierce
Lafayette Green
Fond du Lac
Eau Claire
Waushara
Florence
Racine
Juneau
Washburn
Waupaca
Adams
Trempealeau
Jefferson
Richland
Crawford
Brown Outagamie
Walworth
Manitowoc
Door
Waukesha
La Crosse
Sheboygan Marquette
Winnebago
Washington
Green Lake
Calumet
Menominee
Kewaunee Pepin
Kenosha
Ozaukee
Milwaukee
BEST PRACTICESOn-Board Prewetting
On-boardPrewetting Status
Entire fleet equipped
Some trucks equipped
No trucks equipped
Map created: July 2017
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Figure 3.11. Counties using Route Optimization
Bayfield
Price
Marathon
Clark
Marinette
Sawyer
Dane
Grant
Douglas
Oneida
Vilas
Forest
Polk
Taylor
Rusk
Oconto
Iron
Lincoln
Jackson
Ashland
Burnett
Barron
Sauk
Dunn Chippewa
Dodge
Monroe
Iowa
Langlade
Vernon
Portage Wood
Shawano
Rock
Buffalo
Columbia
Saint Croix
Pierce
Lafayette Green
Fond du Lac
Eau Claire
Waushara
Florence
Racine
Juneau
Washburn
Waupaca
Adams
Trempealeau
Jefferson
Richland
Crawford
Brown Outagamie
Walworth
Manitowoc
Door
Waukesha
La Crosse
Sheboygan Marquette
Winnebago
Washington
Green Lake
Calumet
Menominee
Kewaunee Pepin
Kenosha
Ozaukee
Milwaukee
Route Optimization Status
StatusMultiple Counties Combining Routes
Complete
In Progress
Planned
None
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3B. EQUIPMENT AND TECHNOLOGY As winter maintenance technology and practices evolve, the counties are continually expanding their arsenal of snow and ice control strategies. In recent years, Road Weather Information Systems (RWIS) have become an effective tool for anticipating winter weather. These systems are automatic weather stations and measure real-time conditions. MDSS is another key system WisDOT has implemented. MDSS assists in assessing conditions and recommends appropriate treatments for routes. Equipment calibration is another strategy which not only ensures materials are applied to the roadway consistently, but also reduces product waste and costs. Winter Maintenance Research is also important to help crews continue to stay up to date on the latest tools and practices. There are several research initiatives that WisDOT is part of including Clear Roads, Aurora and Madis.
Road Weather Information Systems (RWIS)WisDOT has had a Road Weather Information System in place since 1986, and continues to expand and enhance the information avail-able through this system. Designed to provide maintenance crews with the most accurate information about current and future weather conditions, WisDOT’s RWIS system includes:
• 68 weather and pavement condition sensors along state highways.
• Detailed weather forecasts via the Maintenance Decision Support System (MDSS).
• A winter storm warning service for WisDOT and county highway departments.
• Over 1,000 mobile infrared pavement temperature sensors on patrol trucks around the state.
WisDOT contracts with an RWIS consultant to manage its RWIS program. This onsite consultant serves as WisDOT’s staff meteorolo-gist and RWIS program manager, and provides ongoing technical and administrative support for the state’s RWIS systems.
Major activities in WisDOT’s RWIS program this year included:
• Management of the MDSS, as well as attending three meetings of the MDSS Pooled Fund Technical Panel.
• Assisting with WisDOT’s AVL-GPS.
A roadside weather sensor.
BEST PRACTICES: Underbody Plow (see Figure 3.9)
WisDOT encourages counties to use underbody plows when possible. If the plow blade is positioned in this way, it will apply downward pressure and can remove more snow pack and ice than a front-mounted plow. The underbody plow is most effective when removing hard packed snow and ice. In light and fluffy snow conditions, snow will compact a under truck with an underbody blade. Unevenness in pavement can also cause operating issues for this type of blade.
Photo credit: fancy-cats-are-happy-cats (https://commons.wikimedia.org/wiki/File:DesCoPlow.tif)
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• Coordinating with Iteris on forecast services.
• Performing an annual weather forecast verification study, monthly interim reports, and monitoring comments from counties using the service.
• Providing MDSS and RWIS training for regional operations staff, the STOC, and county highway departments.
• Overseeing maintenance and repair of the department’s RWIS equipment.
• Managing WisDOT’s rest area weather program.
• Representing WisDOT on the Aurora Program board and the MDSS Technical Panel.
In addition, the RWIS program manager works to coordinate WisDOT’s RWIS activities within Wisconsin and with other state and national agencies, including:
• Coordinating activities with the National Weather Service.
• Participating in national RWIS initiatives, such as MADIS.
• Providing RWIS presentations to WisDOT groups and agencies both inside and outside WisDOT.
• Working with NWS and BTO to develop the FHWA Pathfinder initiative
Other ongoing services provided by the RWIS program manager include:
• Managing contracts for weather forecast and winter storm warning services, and for system maintenance.
• Coordinating use of Winter Severity Index data as an accurate tool to measure the relative severity of winter seasons and researching a potential new winter severity index based on MDSS data.
• Establishing a plan for replacement of aging infrastructure, such as roadside towers and television monitors at rest areas.
• Ongoing assessment of new RWIS technology.
• RWIS program management (budgeting, billing, planning, etc.).
• Developing enhanced methods of data display using GIS technology.
BEST PRACTICES: Ground speed controllers (see Figure 3.8)Ground speed controllers have been shown to reduce salt use by controlling the amount of salt spread according to the speed of the truck. These controllers can also provide accurate data on salt use.
In addition to reducing costs, controlling salt application can help limit the amount of chlorides that get into the environment, minimizing the degradation of plant species and water quality near roadways. See Chapter 6, Section 20 in the Winter Maintenance Manual for more information.
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Maintenance Decision Support System (MDSS) MDSS is a major project undertaken by WisDOT since 2009. Initial deployment took place in 2009 along the Interstate corridors. The bulk of the second phase of deployment occurred in 2010-11. During this phase, WisDOT added four or five “representative” routes in each county so that county highway departments could get an accurate weather forecast and treatment recommendation for the various types of routes in their county. In 2011, BHM input the remainder of the state’s routes into MDSS. These are used for tracking purposes only, i.e., MDC/AVL data tracking.
MANAGEMENT TOOLS. Use of the new MDSS-based severity index continued. The MDSS database now contains 5 years of data. With one more season, we will be able to compute a 5-year average severity for comparison to the current season, similar to what is now done with the storm report severity index.
TRAINING. Training sessions were held in each region in November. These were a joint effort between Iteris and WMS. The sessions also emphasized the web version of MDSS. There was a detailed session on how to set up winter storm alerts. Attendance was about the same as the previous year.
MONITORING. BHM worked with Iteris to obtain monthly MDSS usage statistics.
BHM also coordinated regularly with Iteris to obtain usage statistics for the mobile and web versions. Mobile version statistics were included in the GUI using numbers. Iteris did develop some tracking for the web version. However, we have yet to determine a method to combine the two separate statistics into one usage number.
PAVEMENT BUCKLING. BHM used previously-developed maps in MDSS to monitor conditions during the pavement buckle season. He also sent a timely reminder to the regions concerning MDSS tools available for monitoring potential pavement buckling episodes.
ALTERNATIVE PLATFORMS. The PM continued to coordinate with Iteris on a regular basis on two new MDSS platforms.
• Mobile Devices. As stated previously, BHM included training on mobile devices in the overall training sessions. MDSS apps are available for both Android and iOS. They work much better on tablets than on phones just due to the amount of information that can be displayed. A new capability to report road conditions via the mobile apps was added.
• Browser-based. BHM continued to provide feedback to Iteris in order to improve the web MDSS, which is called WebMDSS. In FY 2018, it will encompass most of the functionality of the desktop version. We plan to transition users to this version with training in the Fall.
COORDINATION. BHM attended three MDSS Pooled Fund Study Technical Panel meetings in Sioux Falls, SD. They made two presentations on how WisDOT is using MDSS.
PATENT ISSUES. For the past few winters, WisDOT stopped the flow of AVL data to MDSS in an effort to not infringe on a patent. Those patent issues have now been resolved, so BHM hopes to have all trucks reporting AVL data by next winter.
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Equipment CalibrationEnsuring correct calibration of winter operations equipment—including salt spreaders, anti-icing applicators, and prewetting application equipment—is a key step in providing precise, consistent materials application, which reduces waste and saves money. Winter vehicles should be calibrated prior to the start of the season and whenever equipment is repaired. WisDOT regional staff are tasked with working with the counties to ensure proper calibration.
CALIBRATION SCALES. Proper calibration has been and always will be an important part of winter maintenance. If the calibration is off by even 10 percent, thousands of dollars worth of salt can be wasted in one winter season. The purchase of three ScaleTech scales has shown that to be a benefit with respect to the process of calibrating salt spreaders. The scales increase the accuracy, speed up the process, and make the process safer for the technicians doing the work. Originally there was going to be a two year study on the scales but after calibrating a few spreaders it was very obvious that the scales would help the process. Therefore the study was discontinued and an email was sent to all the counties recommending that each county should consider adding a scale to their inventory. At about $3k per scale the costs of the scales can be recovered in less than one winter season.
Product and Equipment Innovations Winter maintenance is a continuously evolving field—new technology and innovations are developed each year and best practices are being disseminated to staff as efficiently as possible. One tool that has facilitated winter road maintenance staff's evaluation of deicing chemicals is a training DVD that was developed by Clear Roads and funded by 20 DOTs across the US (including Wisconsin).
The DVD was created to help DOTs meet level of service requirements under increasing budget and environmental constraints. The training helps DOTs determine the "best value" for both chemical and mechanical snow/ice removal practices. Initially Clear Roads developed a step-by-step Field Guide for Testing Deicing Chemicals. More recently Clear Roads has developed a step-by-step instructional video to accompany the field guide which demonstrates three levels of field testing that can be performed to determine the effectiveness of a deicing chemical. The final result was a DVD of approximately 15 minutes in length that is distributed to state DOTs for use in training their maintenance staff on basic field testing. The video is also available on YouTube. More information can be found on the Clear Roads website: http://clearroads.org/project/developing-a-training-video-for-field-testing-of-deicing-materials/.
Winter Maintenance ResearchIn an effort to stay informed of the latest methods, equipment and materials, WisDOT joins other state DOTs in funding research projects of common interest. These pooled fund projects allow WisDOT to leverage its research dollars to support projects at a higher funding level that are important to all research partners. WisDOT participates in these three pooled fund projects:
CLEAR ROADS. In 2008–2009, Wisconsin handed over the role of lead state in this pooled fund project to Minnesota. The pooled fund project focuses on rigorous testing of winter maintenance materials, equipment and methods for use by highway maintenance crews. Launched in 2004, Clear Roads now has 35 member states and has completed 33 research projects.
Clear Roads research addresses topics that may be of interest to Wisconsin counties and WisDOT regional staff. See the Clear Roads Web site (http://www.clearroads.org/completed-research/) for a list of completed projects.
Examples of projects that have been completed include:
• Synthesis of Best Practices for Eliminating Fogging and Icing on Winter Maintenance Vehicles• Determining Effectiveness of Deicing Materials and Procedures• Developing and Evaluating Safe Winter Driving Messages
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• Identifying the Parameters for Effective Implementation of Liquid-Only Plow Routes• Cost-Benefit Analysis Toolkit• Mapping Weather Severity Zones• Snow Removal at Extreme Temperatures (Phase I)• Cost-Benefit Analysis Toolkit (Phase II)• Determining the Toxicity of Deicing Materials• Understanding the True Costs of Snow and Ice Control• Environmental Factors Causing Fatigue in Snowplow Operators• Synthesis on GPS/AVL Equipment Used for Winter Maintenance• Plug-and-Play Initiative: Phase II• North American Study on Contracting Snow and Ice Response• Snowplow Operator and Supervisor Training• Snow Removal Performance Metrics
Synthesis Reports compile research and best practices on topics including:• Monitoring stockpiles of solid winter maintenance materials• Snowplow truck washing practices
These reports are available for download at http://clearroads.org/synthesis-reports/.
Clear Roads produces a quarterly e-newsletter of winter maintenance news items, publications and research in progress. Read the newsletter online at http://www.clearroads.org/winter-maintenance-newsletter/. Highlights from the February 2016 edition included:
• Michigan Tests GPS Plow Trackers• Nevada Installs Automated Deicer Sprayer• Illinois Village Creates Plow Ride-Along Program• Iowa Tests Slick Road Sensor
AURORA. Aurora is an international pooled fund partnership of public agencies that work together to perform joint research on road weather information systems (RWIS). Its membership includes 15 state DOTs, FHWA, and one international agency. WisDOT attended two meetings in person and participated in two web conferences. WisDOT is a member of several project technical panels. The most notable of these is a study of weight restriction models.
For a full list of Aurora projects, please go to http://www.aurora-program.org/projects.cfm.
research for winter highway maintenance
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3C. LABOROver 1,500 employees of Wisconsin’s county highway departments are licensed to operate a snowplow, and over 1,000 of them are permanently assigned to the state highway system. Because a snowstorm can hit at any time of day, snowplow operators frequently put in overtime, and may plow for extended periods during heavy snowfall.
Labor costs vary from county to county according to each area’s contracts, which also defines when overtime hours can be charged. See Figure 3.16 on page 59 for a statewide map of labor cost per lane-mile. This winter, counties spent nearly $21 million on labor, for an average of $601 per lane mile. Per-lane-mile labor expenditures increased nine percent compared with last year’s winter. An average of 24 percent of counties’ winter maintenance costs were spent on labor, with a high of 33 percent in the Southeast Region, where hourly labor rates tend to be higher. Labor hours were up three (3) percent for regular hours and 48 percent for overtime hours compared with last winter. See Table 4.10 on pages 92-96 for county-by-county labor expenditures, and see Table 3.4 on pages 60-67 for county-by-county estimated labor hours and costs from the winter storm reports.
Photo Credit: Pixabay Commons License
52 // W i s D O T | A n n u a l W i n t e r M a i n t e n a n c e R e p o r t
Winter Operations TrainingBefore each winter season, BHM provides and supports a variety of training efforts for WisDOT regional staff and county highway departments. Recent efforts have included:
• AASHTO Computer-Based Training. AASHTO offers eight computer-based training courses that can be completed by winter maintenance staff at their own pace as schedules permit. Course topics include anti-icing/RWIS, mitigating environmental impacts, equipment maintenance, plowing techniques, deicing, mitigating blowing snow, performance measures, and winter maintenance management. Counties are encouraged to have their operators complete the appropriate training courses, including courses for supervisors. For more information, see http://sicop.transportation.org/Documents/CBT_Flyer_v2b%5B1%5D.pdf.
• RWIS Training. WisDOT’s RWIS program manager provides training for both WisDOT regional operations staff and county highway departments. A summary of these training activities can be found in the RWIS Annual Report, available at https://dot-auth-prod.wi.gov/Pages/doing-bus/local-gov/hwy-mnt/winter-maintenance/reports.aspx.
• Regional Operations/County Fall Training Sessions. These sessions are held in all regions in preparation for the upcoming winter season, at some locations in conjunction with Snowfighters’ Roadeos. WisDOT provided support and participated in some of these training sessions.
• Snowfighters’ Roadeos. These events are held by some counties annually, with some roadeos held jointly by two or three counties. WisDOT prepared a Roadeo Manual in August 1997 to assist counties in organizing these roadeos. In addition, organizations such as the Wisconsin chapter of the American Public Works Association and the Wisconsin County Highways Association periodically host statewide Snowfighters’ Roadeos.
• MDSS Training. Training was reconfigured in FY 2015. Two introductory sessions for new users were held, one in Wisconsin Rapids and one in Waukesha. These covered the basics of MDSS for those who had never used it. This allowed the "main" MDSS training to focus on more advanced topics such as how to set up winter storm alerts and how to integrate MDSS into the decision-making process. Attendees included county patrol superintendents, state patrol, a few highway commissioners, and WisDOT Region personnel.
• Clear Roads. Clear Roads began developing snowplow operator/supervisor training modules in 2015. The Wisconsin County Highway Association training committee reviewed the modules and made comments from the Wisconsin perspective. Twenty-four (24) modules were completed in Fall 2016.
2 0 1 6 - 2 0 1 7 | I t ' s O n l y C o l d i f Y o u ' r e S t a n d i n g S t i l l / / 53
COUNTY-BY-COUNTY TABLES AND FIGURES FOR SECTION 3: SNOW AND ICE CONTROL
54 // W i s D O T | A n n u a l W i n t e r M a i n t e n a n c e R e p o r t
2 0 1 6 - 2 0 1 7 | I t ' s O n l y C o l d i f Y o u ' r e S t a n d i n g S t i l l / / 55
Figure 3.12. 2016-2017 Salt Use per Lane Mile vs. 5-Year Average
Price-14%
Clark8%
Dane-17%
Grant10%
Vilas-12%
Rusk8%
Polk-10%
Iron14%
Bayfield0%
Sawyer-1%
Sauk9%
Oneida15%
Forest-23%
Douglas5%
Taylor16%
Dunn25%
Iowa36%
Marathon9%
Rock-24%
Marinette3%
Dodge7%
Oconto-2%
Wood31%
Barron3%
Jackson19%
Lincoln11%
Ashland-13%
Burnett28%
Juneau30%
Monroe36%
Vernon5%
Portage22%
Chippewa30%
Adams36%
Shawano16%
Buffalo69%
Langlade-1%
Pierce13%
Green21%
Columbia14%
Washburn21%
Waupaca5% Brown
12%
Saint Croix20%
Lafayette30%
Richland44%
Eau Claire44%
Crawford21%
Jefferson3%
Waushara20%
Outagamie-25%
Walworth3%
Florence5%
Waukesha28%
Racine-20%
La Crosse38%
Sheboygan20%
Marquette60%
Kenosha23%
Door4%
Fond du Lac5%
Trempealeau34%
Manitowoc8%
Pepin-4%
Winnebago7%
Calumet-3%
Washington9%
Green Lake58%
Kewaunee17%
Menominee31%
Ozaukee7%
Milwaukee-25%
Increase more than 40%
Increase 31 to 40%
Increase 21 to 30%
Increase 11 to 20%
Increase 1 to 10%
Decrease
56 // W i s D O T | A n n u a l W i n t e r M a i n t e n a n c e R e p o r t
Figure 3.13 Gallons of Brine/Lane-Mile 2016-2017
Bayfield 72
Price 349
Marathon 135
Clark 13
Marinette 270
Sawyer 4
Dane 118
Grant 145
Douglas 37
Oneida 219
Vilas 251
Forest 100
Polk 59
Taylor 313
Rusk 0
Iron 139
Lincoln 519
Jackson 6
Ashland 167
Burnett 115
Barron 48
Sauk 53
Dunn 27
Chippewa 12
Dodge 160
Monroe 99
Iowa 132
Langlade 291
Vernon 104
Portage 82
Wood 101
Rock 44
Buffalo 68
Columbia 189
Saint Croix30
Pierce 73
Lafayette 45
Green 90
Eau Claire 57
Jefferson 185
Richland 95
Waushara 64
Outagamie 336
Walworth 88
Florence 565
Racine 58
Oconto 103
Shawano 165
Juneau 279
Washburn 54
Waupaca 90
Adams 278
Fond du Lac218
Trempealeau46
Crawford 107
Brown 134
Manitowoc 336
Door 226
Waukesha 401
La Crosse 197
Sheboygan 322
Marquette 335
Winnebago 448
Washington 140
Green Lake 86
Calumet 163
Menominee 34
Kewaunee 126
Pepin 98
Kenosha 10
Ozaukee 153
Milwaukee 55
Gallons of Brine/Lane-Mile2016/17
LegendVery low
Low
Average
High
Very high
2 0 1 6 - 2 0 1 7 | I t ' s O n l y C o l d i f Y o u ' r e S t a n d i n g S t i l l / / 57
Bayfield 15.7
Price 13
Marathon 12.8
Clark 12.6
Marinette 12.7
Sawyer 11.7
Dane 19.7
Grant 12.2
Douglas 17
Oneida 20.8
Vilas 19.9
Forest 14.2
Polk 13.6
Taylor 13.8
Rusk 11.3
Iron 20.3
Lincoln 12.1
Jackson 16.6
Ashland 11
Burnett 12.5
Barron 9.3
Sauk 17.1
Dunn 19.4
Chippewa 18.7
Dodge 21.1
Monroe 17.2
Iowa 14.4
Langlade 11.8
Vernon 11.8
Portage 12.7
Wood 15.8
Rock 11.3
Buffalo 10.1
Columbia 24
Saint Croix18.9
Pierce 11.7
Lafayette 7.5
Green 6.8
Eau Claire 20.5
Jefferson 16.5
Richland 10.3
Waushara 10.5
Outagamie 9.2
Walworth 18.2
Florence 18.6
Racine 11.7
Oconto 10.7
Shawano 15.3
Juneau 16.6
Washburn 16.5
Waupaca 14.1
Adams 17.5
Fond du Lac13.4
Trempealeau15.6
Crawford 10.8
Brown 14.3
Manitowoc 14.5
Door 13
Waukesha 19.2
La Crosse 13.8
Sheboygan 16.5
Marquette 18.5
Winnebago 14.5
Washington 20
Green Lake 10.1
Calumet 8.9
Menominee 17.3
Kewaunee 11.8
Pepin 6.2
Kenosha 16.1
Ozaukee 22.6
Milwaukee 14.1
Tons of Salt/Lane-Mile2016/17
LegendVery low
Low
Average
High
Very high
Figure 3.14 Tons of Salt/Lane-Mile 2016-2017
58 // W i s D O T | A n n u a l W i n t e r M a i n t e n a n c e R e p o r t
Bayfield $2,553
Price $2,400
Marathon $2,368
Clark $2,260
Marinette $2,023
Sawyer $1,809
Dane $3,312
Grant $1,744
Douglas $2,710
Oneida $3,298
Vilas $3,445
Forest $2,266
Polk $2,220
Taylor $2,535
Rusk $2,088
Iron $3,185
Lincoln $2,657
Jackson $2,818
Ashland $2,266
Burnett $3,044
Barron $2,291
Sauk $2,708
Dunn $2,900
Chippewa $3,098
Dodge $3,007
Monroe $2,490
Iowa $2,446
Langlade $2,105
Vernon $2,049
Portage $2,740
Wood $2,340
Rock $1,830
Buffalo $1,835
Columbia $3,492
Saint Croix$2,779
Pierce $2,177
Lafayette $1,753
Green $1,479
Eau Claire $3,060
Jefferson $2,405
Richland $1,809
Waushara $1,663
Outagamie $2,367
Walworth $2,431
Florence $2,849
Racine $1,837
Oconto $1,852
Shawano $2,508
Juneau $2,628
Washburn $2,330
Waupaca $2,371
Adams $2,968
Fond du Lac$2,403
Trempealeau$2,364
Crawford $1,756
Brown $2,305
Manitowoc $2,719
Door $2,821
Waukesha $2,447
La Crosse $2,474
Sheboygan $2,504
Marquette $2,643
Winnebago $2,556
Washington $3,021
Green Lake $1,858
Calumet $2,016
Menominee $2,110
Kewaunee $2,000
Pepin $1,854
Kenosha $2,270
Ozaukee $3,376
Milwaukee $3,208
Winter Cost/Lane-Mile2016/17
LegendVery low
Low
Average
High
Very high
Figure 3.15 Winter Cost/Lane-Mile 2016-2017
2 0 1 6 - 2 0 1 7 | I t ' s O n l y C o l d i f Y o u ' r e S t a n d i n g S t i l l / / 59
Bayfield $515
Price $421
Marathon $502
Clark $519
Marinette $444
Sawyer $352
Dane $821
Grant $350
Douglas $573
Oneida $571
Vilas $614
Forest $313
Polk $449
Taylor $520
Rusk $277
Iron $634
Lincoln $610
Jackson $400
Ashland $447
Burnett $418
Barron $741
Sauk $582
Dunn $638
Chippewa $697
Dodge $552
Monroe $381
Iowa $540
Langlade $540
Vernon $434
Portage $693
Wood $453
Rock $462
Buffalo $457
Columbia $638
Saint Croix$539
Pierce $575
Lafayette $348
Green $447
Eau Claire $560
Jefferson $410
Richland $412
Waushara $426
Outagamie $779
Walworth $437
Florence $426
Racine $484
Oconto $473
Shawano $597
Juneau $515
Washburn $397
Waupaca $528
Adams $593
Fond du Lac$612
Trempealeau$467
Crawford $343
Brown $494
Manitowoc $763
Door $630
Waukesha $505
La Crosse $490
Sheboygan $628
Marquette $499
Winnebago $598
Washington $660
Green Lake $524
Calumet $516
Menominee $257
Kewaunee $501
Pepin $739
Kenosha $620
Ozaukee $848
Milwaukee $1592
Labor Cost/Lane-Mile2016/17
LegendVery low
Low
Average
High
Very high
Figure 3.16 Labor Cost/Lane-Mile 2016-2017
60 // W i s D O T | A n n u a l W i n t e r M a i n t e n a n c e R e p o r t
Tabl
e 3.
4. L
abor
Hou
rs/L
ane
Mile
s/Se
verit
y In
dex
Ran
king
(Gro
up A
)Fr
om W
inte
r Sto
rm R
epor
ts, 2
016-
2017
Tota
l Hrs
per
Lane
Mi/S
IC
ount
yLa
ne
Mile
sSe
verit
yIn
dex
Salt
per
Lane
Mi
Labo
r Cos
tpe
r Lan
e M
iR
eg Hrs
OT
Hrs
Tota
lH
ours
% OT
Tota
l Hrs
pe
r Lan
e M
iR
egio
n
0.14
DAN
E15
43.7
072
.88
24.4
0$7
0745
7611
439
1601
571
.4%
10.3
7S
W
0.13
MIL
WAU
KEE
1955
.81
62.6
713
.60
$554
7227
8427
1565
453
.8%
8.00
SE
0.12
WAU
KESH
A10
73.9
754
.70
22.0
4$3
8040
8532
0872
9344
.0%
6.79
SE
Gro
up A
Avg
1,52
4.49
63.4
10.
1320
.01
$547
5296
7691
1298
756
.4%
8.39
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als
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Tabl
e 3.
4. L
abor
Hou
rs/L
ane
Mile
s/Se
verit
y In
dex
Ran
king
(Gro
up B
)Fr
om W
inte
r Sto
rm R
epor
ts, 2
016-
2017
Tota
l Hrs
per
Lane
Mi/S
IC
ount
yLa
ne
Mile
sSe
verit
yIn
dex
Salt
per
Lane
Mi
Labo
r Cos
tpe
r Lan
e M
iR
eg Hrs
OT
Hrs
Tota
lH
ours
% OT
Tota
l Hrs
pe
r Lan
e M
iR
egio
n
0.20
BRO
WN
890.
4066
.41
19.9
0$6
1270
8949
6312
052
41.2
%13
.54
NE
0.15
EAU
CLA
IRE
540.
7064
.13
13.4
8$4
0736
8014
5351
3328
.3%
9.49
NW
0.13
WIN
NEB
AGO
626.
5666
.88
15.1
3$4
4228
3027
0655
3648
.9%
8.84
NE
0.13
KEN
OSH
A65
3.56
66.2
011
.49
$445
4217
1446
5663
25.5
%8.
66S
E
0.13
DO
DG
E63
7.85
63.8
220
.53
$330
1878
3410
5288
64.5
%8.
29S
W
0.13
FON
D D
U L
AC
605.
3071
.19
14.5
9$4
8421
6932
8654
5560
.2%
9.01
NE
0.11
OU
TAG
AMIE
538.
6372
.91
10.6
0$3
8529
4015
7245
1234
.8%
8.38
NE
0.11
RO
CK
706.
0348
.04
9.71
$291
1318
2289
3607
63.5
%5.
11S
W
0.11
WAL
WO
RTH
706.
0365
.50
18.0
6$3
1941
1577
648
9115
.9%
6.93
SE
0.10
WAS
HIN
GTO
N61
1.91
78.4
920
.00
$408
1912
2989
4901
61.0
%8.
01S
E
0.10
JEFF
ER
SO
N54
9.67
63.7
515
.47
$354
1413
2147
3560
60.3
%6.
48S
W
0.10
SAU
K57
6.25
95.7
118
.19
$421
2864
2681
5545
48.3
%9.
62S
W
0.10
CH
IPPE
WA
654.
6596
.46
16.9
3$5
0628
2234
3162
5354
.9%
9.55
NW
0.09
POR
TAG
E58
4.63
112.
0213
.46
$464
4399
1789
6188
28.9
%10
.58
NC
0.09
RAC
INE
681.
8865
.10
12.3
0$3
9216
4524
8341
2860
.2%
6.05
SE
0.08
WAU
PAC
A54
6.74
88.4
216
.37
$321
3171
930
4101
22.7
%7.
50N
C
0.08
CO
LUM
BIA
787.
4096
.38
22.2
2$4
4229
0134
4263
4354
.3%
8.06
SW
0.08
MAR
ATH
ON
874.
8111
2.64
12.5
9$4
2251
7225
5477
2633
.1%
8.83
NC
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Fina
l tot
als
as o
f
62 // W i s D O T | A n n u a l W i n t e r M a i n t e n a n c e R e p o r t
Tabl
e 3.
4. L
abor
Hou
rs/L
ane
Mile
s/Se
verit
y In
dex
Ran
king
(Gro
up B
)Fr
om W
inte
r Sto
rm R
epor
ts, 2
016-
2017
Tota
l Hrs
per
Lane
Mi/S
IC
ount
yLa
ne
Mile
sSe
verit
yIn
dex
Salt
per
Lane
Mi
Labo
r Cos
tpe
r Lan
e M
iR
eg Hrs
OT
Hrs
Tota
lH
ours
% OT
Tota
l Hrs
pe
r Lan
e M
iR
egio
n
0.07
GR
ANT
622.
0677
.41
9.73
$245
1415
1891
3306
57.2
%5.
31S
W
0.07
SAIN
T C
RO
IX64
5.34
83.6
213
.98
$327
1393
2261
3654
61.9
%5.
66N
W
0.06
MO
NR
OE
654.
4392
.34
15.7
2$2
6318
5620
4939
0552
.5%
5.97
SW
Gro
up B
Avg
652.
1378
.45
0.11
15.2
6$3
9429
1424
0753
2146
.6%
8.09
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als
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Tabl
e 3.
4. L
abor
Hou
rs/L
ane
Mile
s/Se
verit
y In
dex
Ran
king
(Gro
up C
)Fr
om W
inte
r Sto
rm R
epor
ts, 2
016-
2017
Tota
l Hrs
per
Lane
Mi/S
IC
ount
yLa
ne
Mile
sSe
verit
yIn
dex
Salt
per
Lane
Mi
Labo
r Cos
tpe
r Lan
e M
iR
eg Hrs
OT
Hrs
Tota
lH
ours
% OT
Tota
l Hrs
pe
r Lan
e M
iR
egio
n
0.16
VER
NO
N46
8.36
79.1
411
.69
$567
3124
2803
5927
47.3
%12
.65
SW
0.14
LA C
RO
SSE
503.
3146
.37
9.02
$331
1368
1848
3216
57.5
%6.
39S
W
0.12
MAN
ITO
WO
C42
6.01
78.9
815
.82
$390
2654
1316
3970
33.1
%9.
32N
E
0.10
IOW
A47
3.13
84.4
012
.07
$402
2451
1587
4038
39.3
%8.
53S
W
0.10
SHAW
ANO
520.
5793
.65
15.5
9$3
9331
2517
0248
2735
.3%
9.27
NC
0.09
JUN
EAU
496.
2776
.38
13.8
9$3
5219
8715
5135
3843
.8%
7.13
SW
0.09
JAC
KSO
N51
5.44
67.4
312
.94
$281
1644
1589
3233
49.1
%6.
27N
W
0.09
DU
NN
519.
2496
.23
17.2
7$4
7822
1022
0244
1249
.9%
8.50
NW
0.08
SHEB
OYG
AN52
7.86
81.7
214
.11
$322
2365
1215
3580
33.9
%6.
78N
E
0.08
BAR
RO
N42
8.77
115.
129.
58$3
7027
3699
437
3026
.6%
8.70
NW
0.07
LIN
CO
LN40
5.55
125.
6311
.11
$434
2596
1224
3820
32.0
%9.
42N
C
0.07
PIER
CE
369.
4690
.76
11.3
6$3
3214
0310
2224
2542
.1%
6.56
NW
0.07
CLA
RK
402.
5610
3.14
13.6
2$3
4916
5513
2629
8144
.5%
7.41
NW
0.07
WO
OD
422.
6210
7.76
17.6
8$3
5915
5317
0032
5352
.3%
7.70
NC
0.07
OC
ON
TO46
8.90
92.1
410
.31
$295
1497
1404
2901
48.4
%6.
19N
E
0.07
CR
AWFO
RD
395.
7988
.75
10.2
2$2
5612
1111
1023
2147
.8%
5.86
SW
0.06
DO
UG
LAS
451.
4016
8.87
17.2
3$4
3928
1014
4342
5333
.9%
9.42
NW
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l tot
als
as o
f
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Tabl
e 3.
4. L
abor
Hou
rs/L
ane
Mile
s/Se
verit
y In
dex
Ran
king
(Gro
up C
)Fr
om W
inte
r Sto
rm R
epor
ts, 2
016-
2017
Tota
l Hrs
per
Lane
Mi/S
IC
ount
yLa
ne
Mile
sSe
verit
yIn
dex
Salt
per
Lane
Mi
Labo
r Cos
tpe
r Lan
e M
iR
eg Hrs
OT
Hrs
Tota
lH
ours
% OT
Tota
l Hrs
pe
r Lan
e M
iR
egio
n
Gro
up C
Avg
458.
5493
.91
0.09
13.1
5$3
7321
4115
3236
7242
.2%
8.01
Page
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l tot
als
as o
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Tabl
e 3.
4. L
abor
Hou
rs/L
ane
Mile
s/Se
verit
y In
dex
Ran
king
(Gro
up D
)Fr
om W
inte
r Sto
rm R
epor
ts, 2
016-
2017
Tota
l Hrs
per
Lane
Mi/S
IC
ount
yLa
ne
Mile
sSe
verit
yIn
dex
Salt
per
Lane
Mi
Labo
r Cos
tpe
r Lan
e M
iR
eg Hrs
OT
Hrs
Tota
lH
ours
% OT
Tota
l Hrs
pe
r Lan
e M
iR
egio
n
0.11
MAR
QU
ETTE
245.
7558
.14
15.2
8$2
8998
362
716
1038
.9%
6.55
NC
0.10
GR
EEN
314.
6462
.48
6.60
$255
962
933
1895
49.2
%6.
02S
W
0.10
OZA
UKE
E30
9.19
66.9
221
.71
$320
1115
860
1975
43.5
%6.
39S
E
0.10
ON
EID
A39
6.79
107.
7013
.99
$439
3833
242
4075
5.9%
10.2
7N
C
0.09
TREM
PEAL
EAU
442.
4881
.87
13.0
3$3
5514
1118
0132
1256
.1%
7.26
NW
0.08
DO
OR
271.
8084
.58
12.4
5$4
0961
611
8818
0465
.9%
6.64
NE
0.08
RIC
HLA
ND
327.
6482
.23
7.95
$288
1264
810
2074
39.1
%6.
33S
W
0.08
LAFA
YETT
E29
9.38
63.0
35.
42$1
9867
773
914
1652
.2%
4.73
SW
0.07
WAU
SHAR
A34
5.01
86.5
710
.17
$256
1936
285
2221
12.8
%6.
44N
C
0.07
BAYF
IELD
316.
4214
3.66
15.0
0$4
3723
3392
332
5628
.3%
10.2
9N
W
0.07
MAR
INET
TE43
6.66
125.
0014
.09
$368
3788
117
3905
3.0%
8.94
NE
0.07
BUFF
ALO
317.
0298
.17
9.45
$291
1393
777
2170
35.8
%6.
84N
W
0.06
WAS
HBU
RN
372.
1410
1.72
12.7
6$2
7414
6687
323
3937
.3%
6.29
NW
0.05
POLK
385.
8112
6.40
13.6
6$2
9616
9069
923
8929
.3%
6.19
NW
Gro
up D
Avg
341.
4892
.03
0.08
12.2
5$3
2016
7677
724
5335
.5%
7.08
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66 // W i s D O T | A n n u a l W i n t e r M a i n t e n a n c e R e p o r t
Tabl
e 3.
4. L
abor
Hou
rs/L
ane
Mile
s/Se
verit
y In
dex
Ran
king
(Gro
up E
)Fr
om W
inte
r Sto
rm R
epor
ts, 2
016-
2017
Tota
l Hrs
per
Lane
Mi/S
IC
ount
yLa
ne
Mile
sSe
verit
yIn
dex
Salt
per
Lane
Mi
Labo
r Cos
tpe
r Lan
e M
iR
eg Hrs
OT
Hrs
Tota
lH
ours
% OT
Tota
l Hrs
pe
r Lan
e M
iR
egio
n
0.36
CAL
UM
ET20
1.71
95.0
08.
29$1
,697
1389
5471
6860
79.8
%34
.01
NE
0.10
PEPI
N11
2.38
93.2
36.
42$4
3760
544
510
5042
.4%
9.34
NW
0.08
VILA
S30
5.24
127.
7318
.21
$477
1939
1099
3038
36.2
%9.
95N
C
0.08
LAN
GLA
DE
299.
2110
6.60
11.1
5$3
7617
0077
424
7431
.3%
8.27
NC
0.07
RU
SK21
3.47
90.3
69.
82$2
7295
739
913
5629
.4%
6.35
NW
0.07
TAYL
OR
233.
9011
0.61
12.9
0$3
4411
7863
418
1235
.0%
7.75
NW
0.07
FOR
EST
312.
3810
8.97
14.4
2$2
8413
4591
322
5840
.4%
7.23
NC
0.06
PRIC
E32
2.26
142.
1115
.83
$350
1824
972
2796
34.8
%8.
68N
C
0.06
IRO
N24
9.56
145.
2014
.31
$418
1355
738
2093
35.3
%8.
39N
C
0.06
BUR
NET
T23
7.93
97.8
012
.85
$285
653
679
1332
51.0
%5.
60N
W
0.05
ASH
LAN
D24
5.35
144.
9911
.02
$396
1342
605
1947
31.1
%7.
94N
W
0.05
SAW
YER
367.
4411
2.20
11.7
9$2
6811
5786
320
2042
.7%
5.50
NW
Gro
up E
Avg
258.
4011
4.57
0.09
12.2
5$4
6712
8711
3324
2040
.8%
9.92
Page
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f 1M
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l tot
als
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Tabl
e 3.
4. L
abor
Hou
rs/L
ane
Mile
s/Se
verit
y In
dex
Ran
king
(Gro
up F
)Fr
om W
inte
r Sto
rm R
epor
ts, 2
016-
2017
Tota
l Hrs
per
Lane
Mi/S
IC
ount
yLa
ne
Mile
sSe
verit
yIn
dex
Salt
per
Lane
Mi
Labo
r Cos
tpe
r Lan
e M
iR
eg Hrs
OT
Hrs
Tota
lH
ours
% OT
Tota
l Hrs
pe
r Lan
e M
iR
egio
n
0.07
KEW
AU
NEE
111.
3563
.96
9.78
$208
463
5451
710
.4%
4.64
NE
0.06
GR
EEN
LAK
E15
8.44
79.0
110
.03
$238
466
340
806
42.2
%5.
09N
C
0.06
FLO
REN
CE
141.
0713
2.71
17.5
0$3
2091
423
111
4520
.2%
8.12
NC
0.06
MEN
OM
INEE
90.2
677
.67
16.4
5$1
5931
394
407
23.1
%4.
51N
C
0.05
ADAM
S19
3.20
111.
5914
.98
$275
1021
156
1177
13.3
%6.
09N
C
Gro
up F
Avg
138.
8692
.99
0.06
13.7
5$2
4063
517
581
021
.8%
5.69
Page
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y, J
une
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als
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68 // W i s D O T | A n n u a l W i n t e r M a i n t e n a n c e R e p o r t
69
Total lane miles 34,620Total patrol sections 755Average lane miles per patrol section 45.9Roads to bare/wet pavement within WisDOT targets1 70%
Total tons of salt/lane-mile 15.2Total gallons of brine/lane-mile 142.6Average crew reaction time from start of storm 2.22 hours
Total winter costs2 $ 87,836,693Total winter costs per lane mile $ 2,537Total winter crashes3 5,282Total winter crashes per 100 million VMT 18
Since weather can vary drastically from year to year, planning and budgeting for winter highway maintenance can be challenging. Throughout the winter, WisDOT staff and county highway departments evaluate progress in several areas, including materials use, money spent, and response time. When the season is complete, WisDOT can gather all the data and analyze this winter’s performance across all regions and compared to previous winters.
This section begins with a description of the winter maintenance portion of Compass, WisDOT’s operations performance measurement program, which measures trends in areas like response time and winter costs per lane mile. This section also discusses costs, using charts to visually compare spending in different categories from region to region and from year to year, and presents winter crash rates and customer satisfaction data.
Performance and Costs, 2016-2017
1. Time to bare/wet pavement and crew reaction time data are from storm reports.2. Cost data are actual costs as billed to WisDOT by the counties. 3. Crash data are from WisDOT’s Bureau of Transportation Safety.
An Economical ChoiceProactive anti-icing operations
are about three times less costly than treating frost once it has formed. Anti-icing costs made
up only 2 percent of total winter maintenance costs this year. See page 39 for more information on
anti-icing costs.
Photo Credit: Jan Tik (Flickr - Creative Commons License)
In this section...4A Compass................................................704B Winter Maintenance Management....70
Storm Reports......................................71Winter Patrol Sections.........................72Route Optimization.............................72
4C Response Time.....................................73Maintenance Crew Reaction Time.....73Time to Bare/Wet Pavement..............74
Performance44D Costs......................................................754E Travel and Crashes...............................80
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4A. COMPASSDeveloped in 2001, Compass is WisDOT’s quality assurance and asset management program for highway maintenance and operations. Annual Compass reports provide information on winter maintenance activities as well as other aspects of highway maintenance and operations.
Measures for winter operations were established in 2003, and data from the winter of 2003–2004 was used to establish baseline measures for future winter seasons. The measures that were chosen included:
• time to bare/wet pavement• winter weather crashes per vehicle miles traveled• cost per lane mile per Winter Severity Index point
Table 4.1 gives the statewide average values for these measures for the last five winters. More detail on these measures is provided later in this section.
WisDOT has gathered several years of baseline data, this data can be used to make a year-to-year comparison in these areas.
Annual Compass reports are available at http://wisconsindot.gov/Pages/doing-bus/local-gov/hwy-mnt/compass/reports/reports.aspx.
4B. WINTER MAINTENANCE MANAGEMENTHistory of Snow and Ice Control in WisconsinThe counties’ plowing and salting strategies have evolved considerably over the past several decades. For many years beginning in the 1950s, WisDOT maintained a “bare pavement” policy for state highways, striving to ensure that the roadways were kept essentially clear of ice and snow during winter. Snowplows operated continuously during storms and simultaneously applied deicing salts. In the 1970s, however, economic and environmental concerns compelled the department to modify this policy. The national energy crisis and the high cost of employee overtime strained the maintenance budget, and WisDOT made the decision to reduce winter maintenance coverage on less traveled state highways. To address the risk of environmental damage by chloride chemicals, the policy was modified further to include provisions calling for the prudent use of chemicals, and limiting each application of salt to 300 pounds per lane mile.
In 2002, a detailed salt application table was added to the maintenance manual’s winter guidelines. The table provides variable salt application rates for initial and repeated applications, depending on the type of precipitation, pavement temperature, wind speeds, and other weather variables. Anti-icing application rates were also established; county highway
Table 4.1. Statewide Compass Measures for Winter
2012-13 2013-14 2014-15 2015-16 2016-17Percentage of roads to bare/wet pavement (Within WisDOT target times)
73% 63% 70% 74% 70%
Cost per lane mile $2,778 $3,304 $2,155 $2,087 $2,537
Winter Severity Index 115.2 133.6 99.28 90.35 91.14
Cost per lane mile per Winter Severity Index point
$24.11 $24.73 $21.71 $23.09 $27.85
Winter weather crashes29 per
100 million VMT44 per
100 million VMT25 per
100 million VMT18 per
100 million VMT18 per
100 million VMT
2 0 1 6 - 2 0 1 7 | I t ' s O n l y C o l d i f Y o u ' r e S t a n d i n g S t i l l / / 71
departments were instructed to perform anti-icing applications prior to predicted frost, black ice, or snow events in order to minimize the amount of salt used during the event. With the implementation of MDSS, this process has become more automated. Patrol superintendents receive treatment recommendations based on the characteristics of the route, such as traffic volume and pavement type, residual de-icers, and forecasted weather.
Storm ReportsOne way that WisDOT has worked to increase efficiency in recent years is through the Winter Storm Reports. Every week during the winter, the county highway departments complete online storm report forms. These storm reports let county and WisDOT staff track the season’s weather and the counties’ response to it throughout the season, which allows the counties to adjust their resource use midseason if necessary. Storm reports track data such as types of storm events, salt use, anti-icing applications, labor hours, and cost estimates. Uses for this data include:
WisDOT Central Office• Create weekly reports and maps that track salt use and costs. These can help identify inconsistencies in service
levels provided by neighboring counties.
• Calculate the severity index; use this to justify additional funding if conditions are more severe than normal
• MAPSS measures
• DTSD Performance Measures
WisDOT Regional Offices• Justify additional funding if conditions are more severe than normal
• Manage salt inventory
• Post-storm analysis of county’s response
• Training tool for new staff
Counties• Post-storm analysis of crew’s response
• Compare their response (materials use, anti-icing, labor hours, etc.) to that of neighboring counties
• Justify funding to county boards
See https://transportal.cee.wisc.edu/storm-report/ for more detail on how to use the storm report data.
WisDOT relies on the county highway departments to make the storm reports a reliable tool by entering data accurately each week. Historically, the cost and salt use data in the storm reports has been relatively accurate when compared with final costs billed to WisDOT and end-of-season salt inventory figures. In 2010 the UW TOPS Lab took over the storm report input programming. As a result the data entry has been restricted to the point that erroneous entries have been nearly eliminated. This will result in even more accuracy going forward.
BEST PRACTICES: Automatic Vehicle Location (AVL-GPS)AVL-GPS is used to determine the location of a vehicle and allows management to monitor the location of an entire fleet. This system can assist in the management of labor, equipment and materials. WisDOT primarily uses data from AVL-GPS to improve MDSS recommendations.
Additionally, AVL can record and transmit operational data from snowplows. Data such as application rates, pavement temperatures, and the position of blades and plows can all be captured. This data can be stored and used for reporting and analysis at a later date.
72 // W i s D O T | A n n u a l W i n t e r M a i n t e n a n c e R e p o r t
Winter Patrol SectionsMany factors influence a county’s response to winter storms, including the timing of snow events, the mix of highway types and classifications in a county, and the type of equipment being used. Another important factor is the length of each county’s patrol sections.
Each county highway department divides the state highways it is responsible for plowing into patrol sections. In general, one snowplow operator is assigned to each patrol section. This winter, the state highway system was divided into 755 winter patrol sections, an average of 10.5 sections per county. The length of patrol sections varies, with counties that are more urban (Group A) tending to have shorter patrol sections than more rural counties (Groups D, E and F). Local traffic patterns, highway geometrics, number of traffic lanes, intersections, interchanges, and other factors affect the length of patrol sections in each county.
In responding to a storm, operators in longer patrol sections may use more salt in an effort to melt any snow that accumulates between plowings. In addition, drivers may notice that some roads appear to be cleared faster than others, since the longer a patrol section, the longer it takes a snowplow operator to clear all the roads in his section.
Table 4.2 shows the average patrol section length for the counties in each Winter Service Group. For county-by- county patrol section data, see Table 4.8 on page 85.
Route OptimizationAfter a discussion about Winter Patrol Sections, it is appropriate to mention the newest trend across the country, Route Optimization. Route Optimization is just what it implies – optimizing a route traveled by taking less left turns or U-turns and equalizing the length of time between routes. Winter road maintenance route optimization highway segments are designed for plow speeds of 25-35 mph and a maximum rate of 300 lbs. of salt/lane-mile over the course of 2.5-3 hours. The 2.5-3 hours optimal plow route time is used because that is typically how long salt or salt brine will remain on the road before it becomes too diluted to be effective. Route optimization is used by major private sector companies including FedEx and UPS, and is considered a best practice for efficiency. In recent years, the public sector has seen success with the process too.
In 2016, 34 Wisconsin counties volunteered to collaborate with WisDOT on a pilot project to determine the value of using GIS technology to optimize snow plow routes. Of the 34 Wisconsin counties involved, both Dane and Brown have begun analyzing return on investment from the 2016-2107 winter. Return on Investment is unique to each county. WisDOT expects to experience significant savings related to operations, salt use, fuel consumption and increases in safety. Preliminary numbers show:
• When routes are absorbed into larger routes through optimization, it creates savings of roughly $85,000 annually per route.
• Brown County is saving $1.2M this year in equipment costs, as route optimization effectively absorbed 165 new lane miles and eliminated the need to expand the fleet.
Winter service group Average patrol section length (lane miles)
Range of average patrol section lengths by county (lane miles)
A 54.1 49.8 - 56.5B 46.6 31.7 - 70.9C 43.5 28.2 - 57.3D 47.8 30.2 - 62.9E 47.6 33.6 - 61.2F 42.0 37.1 - 47.0
Statewide average 46.9 28.2 - 70.9
Table 4.2. Average Patrol Section Lengths by Winter Service Group
2 0 1 6 - 2 0 1 7 | I t ' s O n l y C o l d i f Y o u ' r e S t a n d i n g S t i l l / / 73
• Dane County was able to eliminate four additional trucks from its fleet after a second round of optimization. The further analysis was performed to incorporate new shop and shed locations.
Expect to see more details and costs savings in future reports as more counties implement Route Optimization.
4C. RESPONSE TIMEWisDOT tracks two types of response time data—the time it takes a maintenance crew to get on the road after the start of a storm, and the time it takes the pavement to return to a bare/wet condition after the end of a storm. The first measure can impact the second. In general, a quicker response means the crews are dealing with less packed snow. However, WisDOT guidelines dictate that lower-volume highways receive 18-hour winter maintenance coverage rather than 24-hour coverage, so slower average reaction times are expected on 18-hour roads.
Maintenance Crew Reaction Time Being proactive in getting on the road—even before the start of a storm—can result in bare/wet pavement being achieved faster and with less effort. Knowing this, county highway departments are becoming more proactive in their response to winter storms. Plows and salt spreader trucks are often on the road before a storm starts or shortly afterward. Sometimes counties wait until the sun comes out so their salting and plowing are more effective, which can increase average reaction times.
ÆU
ÆU
Sta rt
Sto p/ Dep art
©O pe nSt ree tMa p( and )c ont ribu tor s,C C- BY -SA
Path Overview Map
Polk County State Routes
Route: 1
Date: 2017-09-21Scale: 1 : 116990
C: \ FR_projects \ PolkState \ net \ nt_ara170913_144524 \cy_ara \ rc_ara \ rt_1 \ aru170913_1439_1.rt
Route Optimization mapping completed for Polk County.
74 // W i s D O T | A n n u a l W i n t e r M a i n t e n a n c e R e p o r t
Using data from the weekly winter storm reports, Table 4.3 shows the average reaction time to storm events in each Winter Service Group. This winter's reaction time was faster than in previous years. This winter the average reaction time of 2.22 was 31 percent faster than the latest 10-year average. As expected, average reaction times for Group A counties, which provide the highest level of service (24-hour coverage), were less than those counties that provide 18-hour coverage.
Last year's average reaction time of 4.34 hours was one of the slower reaction times recorded since the Department began tracking this metric. The 2016-2017 winter slightly more mild than the previous winter, but saw a drastic 49% decrease in average statewide reaction time from the prior year.
Time to Bare/Wet PavementAs explained in Section 1, county highway departments provide different levels of effort during and after a storm according to each highway’s category rating, as determined by average daily traffic. It would be expected that an urban freeway would receive more materials, labor and equipment—and would show a quicker recovery to bare/wet pavement—than a rural, two-lane highway. For more information on these categories, see page 8.
“Time to bare/wet pavement” is measured from the reported end time of a storm. Table 4.4 shows that the trend for average time to bare/wet pavement is as expected: More heavily traveled highways show a shorter average time to bare/
Highway Category 2009 2010 2011 2012 2013 2014 2015 2016 201724-Hour Roads 61% 70% 69% 83% 75% 66% 75% 78% 79%18-Hour Roads 56% 65% 66% 76% 70% 59% 67% 71% 70%Target 70% 70% 70% 70% 70% 70% 70% 70% 70%
Percent of Time the Highway Category Target Time to Bare/Wet Pavement was Met (TargetTimes: 4 hours for 24‐Hour Roads; 6 hours for 18 Hour Roads)
Table 4.4. Percentage to Bare/Wet Pavement
Bare/wet condition is when the lanes of travel are wet and snow is no longer visible in the lane. Some winter levels of service are not expected to achieve a bare/wet condition as quickly as others.
Average reaction time (hours) 10-year Average
Percent change
Winter Service Group
2007-2008
2008-2009
2009-2010
2010-2011
2011-2012
2012-2013
2013-2014
2014-2015
2015-2016
2016-2017
2007-2008 to 2016-2017
2016-2017 vs. 10-year Average
A 0.61 1.02 1.74 0.49 0.19 0.63 2.31 0.32 1.21 0.37 0.89 -58%
B 1.38 1.46 1.78 1.60 1.11 1.27 4.48 1.67 2.40 1.07 1.82 -41%
C 2.87 2.70 3.37 2.87 2.15 2.38 4.99 2.57 3.19 2.22 2.93 -24%
D 2.89 3.46 4.23 3.25 2.54 3.77 6.23 2.86 3.91 2.06 3.52 -41%
E 4.05 4.00 4.71 3.48 3.16 2.99 9.36 3.77 6.72 3.94 4.62 -15%
F 5.04 5.08 5.79 5.68 3.39 3.79 14.81 4.78 8.62 3.64 6.06 -40%Statewide average
(unweighted)2.66 2.78 3.38 2.74 2.08 2.42 7.03 2.66 4.34 2.22 3.23 -31%
Table 4.3. Maintenance Crew Reaction Time From winter storm reports, 2007/2008–2016/2017
2 0 1 6 - 2 0 1 7 | I t ' s O n l y C o l d i f Y o u ' r e S t a n d i n g S t i l l / / 75
Figure 4.1. Statewide Average Winter Costs per Lane Mile and Winter Severity Index, 1997-98 thru 2016-17
0
20
40
60
80
100
120
140
$0
$500
$1,000
$1,500
$2,000
$2,500
$3,000
$3,500
Seve
rity
inde
x
Cos
ts p
er la
ne m
ile
Winter season
Costs per lane mile Severity index
wet pavement. From storm to storm, however, most variability is due to weather effects (type, duration and severity of storms throughout the winter season), according to analysis performed through the Compass program.
The 2016-17 percentage of roadways cleared to bare/wet pavement stayed nearly the same from the previous year. Last year's and this year's winters were both considered mild.
4D. COSTSThe total billed cost of statewide winter operations this winter was $87.8 million, making it 22 percent more costly than 2015-16. A number of factors drive the cost of winter maintenance, including both the nature and severity of the winter (i.e. how much work has to be performed), as well as the unit costs of the component elements of winter maintenance (i.e. cost per lane mile for salt, labor and equipment).
Winter maintenance costs per lane mile increased significantly 2016-17 by about 21 percent from 2015-16. See Figure 3.14 for a statewide map of winter cost per lane-mile. Figure 4.1 shows the statewide average winter cost per lane mile and Winter Severity Index since the 1997-98 winter.
The average Winter Severity Index decreased slightly in the SE and NC regions compared with last winter while the remaining regions saw a light increase.
Table 4.5 show total winter maintenance costs statewide and for each region per lane mile, as well as relative to the region's average Winter Severity Index. The level of service provided in each county affects the total costs, and the mix of counties in a region affects the overall comparative costs.
Figure 4.2 shows, in 2016-17, all regions experienced higher winter maintenance costs as compared to 2015-2016. However, regions had costs that were similar to their most recent 5-year average. This year's slight increase in winter severity over the 2015-16 can be attributed to the higher costs.
Region Average Winter Severity Index
Actual cost per lane mile
Relative cost per severity index point
SW 74.57 $2,525 $33.87
SE 65.65 $2,711 $41.30
NE 81.70 $2,353 $28.80
NC 106.9 $2,540 $23.76
NW 104.34 $2,536 $24.30
Statewide 91.14 $2,533 $27.79
Table 4.5. Total Winter Costs Relative to Winter Severity, 2016-2017
Figure 4.2. Total Winter Maintenance Cost by Region, 2016-17 vs. 2015-16 vs. Previous 5-Year Average
$-
$5,000,000
$10,000,000
$15,000,000
$20,000,000
$25,000,000
Region 1 /Southwest
Region 2 /Southeast
Region 3 /Northeast
Region 4 /Northcentral
Region 5 /Northwest
2015-2016 Total Cost 2016-2017 Total Cost 5-Yr Avg Cost ('12-'16)
76 // W i s D O T | A n n u a l W i n t e r M a i n t e n a n c e R e p o r t
There are five major cost categories in the Department's winter maintenance billing system. These include: cost of salt used, labor costs, cost of other materials furnished by the county, and administration costs. Figure 4.3 below shows the breakdown of the $87.6 million in 2016-17 statewide winter maintenance costs by these billing categories.
Figure 4.3. Statewide Winter Costs by Category
Figure 4.4 on page 77 shows the breakdown of costs by billing category for each of the five regions. More specific, detailed cost figures by region and for the state as a whole are shown in Table 4.6 on page 78.
In the five individual winter maintenance expenditure categories for 2016-17 statewide, the following trends were noted: • Salt expenditures were $36.5 million - nearly a 30 percent increase compared to the previous winter. The
Northeast region experiencing the smallest increase from last winter at only 6 percent while the Southwest, Northcentral and Northwest all nearly had 30 percent increases.
• Equipment expenditures were $24.9 million, an increase of 20 percent compared to the previous winter.
• Labor expenditures were $20.8 million, an increase of seventeen percent (17 percent) from the previous winter.
• County Furnished Material Costs were $3.2 million, an increase of 10 percent compared with the previous winter. .
Labor Costs24%
Equipment Costs28%County
Furnished Material Costs
3%
Administration Costs
3%
Cost of Salt Used 42%
Statewide Winter Costs2016-17 Total Cost: $87,836,693
2 0 1 6 - 2 0 1 7 | I t ' s O n l y C o l d i f Y o u ' r e S t a n d i n g S t i l l / / 77
Figure 4.4. Regional Winter Costs by Category, 2016-17
Labor Costs21%
Equipment Costs26%
County Furnished
Material Costs4%
Administration Costs
3%
Cost of Salt Used 46%
Southwest Region Winter Costs2016-17 Total Cost: $23,577,628
Brine Used: 1.21 M Gallons
Labor Costs33%
Equipment Costs27%County Furnished
Material Costs1%
Administration Costs
2%
Cost of Salt Used 37%
Southeast Region Winter Costs2016-17 Total Cost: $16,247,431
Brine Used: 0.78 M Gallons
Labor Costs25%
Equipment Costs32%
County Furnished Material Costs
4%
Administration Costs
3%
Cost of Salt Used 36%
Northeast Region Winter Costs2016-17 Total Cost: $12,011,465
Brine Used: 1.30 M Gallons
Labor Costs21%
Equipment Costs31%
County Furnished
Material Costs3%
Administration Costs
3%
Cost of Salt Used 42%
Northcentral Region Winter Costs2016-17 Total Cost: $16,291,588
Brine Used: 1.24 M Gallons
Labor Costs21%
Equipment Costs27%
County Furnished
Material Costs6%
Administration Costs
3%
Cost of Salt Used 43%
Northwest Region Winter Costs2016-17 Total Cost: $19,708,581
Brine Used: 0.41 M Gallons
78 // W i s D O T | A n n u a l W i n t e r M a i n t e n a n c e R e p o r t
Win
ter 2
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xper
ienc
efo
r Cou
nty
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ices
Cou
nty
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atio
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er F
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ear
Ave
rage
Reg
ion
1 / S
outh
wes
t$4
,943
,862
$6,2
18,1
41$9
40,0
94$6
81,6
24$1
0,79
3,90
7$2
3,57
7,62
8$2
1,83
3,80
010
8%
Reg
ion
2 / S
outh
east
$5,3
66,0
79$4
,449
,903
$106
,784
$257
,130
$6,0
67,5
35$1
6,24
7,43
1$1
6,53
1,60
098
%
Reg
ion
3 / N
orth
east
$3,0
07,4
20$3
,880
,637
$445
,980
$401
,140
$4,2
76,2
88$1
2,01
1,46
5$1
1,27
9,60
010
6%
Reg
ion
4 / N
orth
cent
ral
$3,4
00,3
16$5
,056
,785
$532
,045
$455
,750
$6,8
46,6
92$1
6,29
1,58
8$1
5,05
1,60
010
8%
Reg
ion
5 / N
orth
wes
t$4
,079
,854
$5,3
08,2
40$1
,130
,341
$633
,510
$8,5
56,6
36$1
9,70
8,58
1$1
7,47
5,00
011
3%
Reg
ion
Tot
als
$20,
797,
531
$24,
913,
706
$3,1
55,2
44$2
,429
,154
$36,
541,
058
$87,
836,
693
$82,
171,
600
107%
Tabl
e 4.
6
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Figure 4.5 shows the total cost per lane mile for winter maintenance in each region, along with the region’s Winter Severity Index. The level of service provided in each county affects total costs, as do the factors listed below. For these reasons, the Southeast Region historically experiences significantly higher costs relative to winter severity than the other regions, however, this year appears to be the exception with the SE Region have significantly lower costs.
Components of Winter CostsMajor components of winter costs include labor, equipment, salt, other materials such as sand and chemicals, and administrative costs. A region’s expenditures in each area are affected by the severity of its winter and the portion of its highways receiving 24-hour coverage. In addition:
• Labor costs are based on rates set in each county’s union contracts. Hourly rates tend to be higher in more urban counties. Timing of storms can increase labor costs if more overtime hours are required.
• Equipment costs are determined by the state Machinery Management Committee, which assigns an hourly rate to each piece of equipment that includes depreciation from the purchase price, maintenance costs, and fuel costs. Rising fuel costs have contributed to increased equipment costs, as have some counties’ purchase of larger, more expensive vehicles. These larger vehicles are often more useful for year-round maintenance tasks and are also more efficient in the winter, as they can accommodate larger plows and carry more salt.
• Salt costs are affected by salt prices per ton, which vary because of transportation costs. For example, salt entering the state at the Port of Milwaukee doesn’t have to travel as far to reach counties in the Southeast region
Figure 4.5. Costs per Lane Mile by Category
$-
$200
$400
$600
$800
$1,000
$1,200
$1,400
SW SE NE NC NW
Salt Costs Per Lane MileActual billed costs, 2016-17
Costs by Region Statewide Avg
$-
$200.00
$400.00
$600.00
$800.00
$1,000.00
Southwest Southeast Northeast Northcentral Northwest
Labor Costs Per Lane MileActual billed costs, 2016-17
Costs by Region Statewide Average
$600.00
$650.00
$700.00
$750.00
$800.00
Southwest Southeast Northeast Northcentral Northwest
Equipment Costs Per Lane MileActual billed costs, 2016-17
Costs by Region Statewide Average
$-
$50.00
$100.00
$150.00
$200.00
$250.00
Southwest Southeast Northeast Northcentral Northwest
Other Costs Per Lane MileActual billed costs, 2016-17
Costs by Region Statewide Average
80 // W i s D O T | A n n u a l W i n t e r M a i n t e n a n c e R e p o r t
as it does to reach counties in the center of the state.
• Costs for materials other than salt, such as sand, are also affected by transportation costs. In addition, some counties use more expensive deicing agents that are more effective at lower temperatures (see Table 3.3 on page 39 for details on deicing agent costs).
• Administrative costs are calculated at 4.25 percent of each county’s combined labor, equipment and materials costs, and cover the overhead costs for office activities.
However, the breakdown of expenditures by category varies among regions because of the factors described above. For example, the Southeast Region spends more on labor because hourly labor rates tend to be higher in those counties, while equipment expenditures make up a smaller percentage of that region’s total expenditures. Figure 4.4 on page 77 shows the distribution of costs by category for each region.
County-by-county cost data is available in Table 4.10 on pages 92-96.
A Note About Cost DataThe tables at the end of this section were generated with data from two sources—final costs as billed to WisDOT, and preliminary costs from the winter storm reports. The tables created from preliminary storm reports data (such as Table 4.11 on pages 98-105, Cost per Lane Mile per Severity Index Ranking) are included in this report because they provide county-by-county breakdowns of cost data not available elsewhere. Many of the tables in the Appendix also include cost data from the storm reports. The source of each table’s data is indicated below the table title.
Final cost data includes expenses for all winter activities, including putting up snow fence, transporting salt, filling salt sheds, thawing out frozen culverts, calibrating salt spreaders, producing and storing salt brine, and anti-icing applications, as well as plowing and salting. Cost data from storm reports, however, include only plowing, sanding, salting and anti-icing expenses.
4E. TRAVEL AND CRASHESFrom black ice to freezing rain to white-out snowstorms, winter weather creates challenging conditions for even the most careful drivers. Many factors influence winter crash rates, most of which cannot be controlled by winter maintenance crews. However, by keeping roads as clear as possible within their expected level of service (18- or 24-hour coverage), maintenance crews have an opportunity to help prevent some winter crashes.
In the winter of 2016-2017, there were 5,282 reported winter weather crashes (those that occurred on pavements covered with snow, slush or ice) a 4 percent increase over the previous winter. The crash rate (number of crashes per 100 million vehicle miles traveled) stayed the same as last winter - a statewide average of 18.
Crash rates tend to decrease in less severe winters. Figure 4.6 shows the trends in total crashes statewide over the last 18 years overlaid with the Winter Severity Index. Compared to the severe winter in 2013-2014, it is no surprise that the number of crashes has been lower in 2014-15, 2015-16 and 2016-17.
It’s important to note that crash rates provide only a portion of the picture of overall winter safety. Crash rates include only “reportable” crashes, which exclude those that cause property damage under $1,000 that aren’t required by law to be reported to police. Also, crashes in urban areas are more likely to occur at lower speeds and cause fewer deaths, while crashes on high-speed rural roads are more likely than low-speed crashes to be fatal.
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Crashes and Vehicle Miles TraveledMore urban areas such as the Southeast Region often have fewer winter weather crashes per 100 million vehicle miles traveled. This is partly due to the fact that a single crash in a county with low VMT has a bigger impact on the overall crash rate. In addition, urban regions have more highways with 24-hour coverage, which means that these roadways are more likely to be in passable condition. This year, the southeast and southwest regions saw decreases in crash rates. The southeast region saw the greatest percentage reduction in crash rates (a 29 percent reduction), with this year’s crash rate at 12 crashes per 100 million VMT (see Table 4.7). The north central region saw the greatest percentage increase in crash rates (a 28 percent increase) compared to its crash rate last year (18 crashes per 100 million VMT). Table 4.12 on pages 106-108 gives the estimated number of vehicle miles traveled in each county this winter (November 2016 to April 2017), and the number of crashes that occurred in each county.
WisDOT tracks crashes according to the type of road where they occurred (urban or rural, and Interstate or other state or U.S. highway), and whether the road was divided or nondivided. Figure 4.7 shows that most winter crashes occur on rural state or U.S. highways, largely because there are more lane miles in this category than in the others. Table 4.13 on pages 109-110 shows the breakdown of crashes in each county according to highway type.
How VMT Is CalculatedWisDOT’s Traffic Forecasting Section uses a number of factors to estimate Vehicle Miles of Travel for the state’s roads. Annual average daily traffic counts are taken in about one-third of Wisconsin’s counties every year, and estimates are made for the counties not counted. In addition, forecasters factor in gallons of gas sold, fuel tax collected, and average vehicle miles per gallon.
Source: WisDOT Bureau of Transportation Safety
Figure 4.6. Winter Crashes and Winter Severity Index
0
20
40
60
80
100
120
140
0
2,000
4,000
6,000
8,000
10,000
12,000
14,000
Seve
rity
inde
x
Cra
shes
Winter season
Winter Crashes Severity Index
82 // W i s D O T | A n n u a l W i n t e r M a i n t e n a n c e R e p o r t
Total winter VMT for all counties is shown in Table 4.12 on page 106-108 This winter, total VMT ranged from a low of 18.8 million in Menominee County to a high of 3.2 billion in Milwaukee County. VMT estimates at the county level tend to be less reliable than at the statewide level, because current traffic counts are not available for all counties, and more variability exists in the data at finer levels of resolution.
Region Winter Severity Index (2016-17)
VMT (100 million)
(Nov 2016 - April 2017)
Snow/Slush/Ice Crashes
(Nov 2016 - April 2017)
Crashes per 100M VMT (2015–16)
Crashes per 100M VMT
(2015–2016)NC 106.90 36.80 860 18 23
NW 104.34 44.35 887 16 20
NE 81.71 56.14 1,131 20 20
SE 65.65 82.97 1,034 17 12
SW 74.57 73.24 1,370 20 19
Statewide 91.14 293.50 5,282 18 18
Table 4.7. Crashes and Vehicle Miles of Travel by Region
Source: WisDOT Bureau of Transportation Safety
Figure 4.7. Winter Crashes by Highway Type, Bureau of Transportation Safety Data 2016-2017
Urban STH29%
Rural STH52%
Urban IH6%
Rural IH13%
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COUNTY-BY-COUNTY TABLES AND FIGURE FOR SECTION 4: PERFORMANCE
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Table 4.8. Winter Maintenance Sections
County Lane MilesWinter Patrol Sections 2017
Survey
Lane Miles per
Patrol Section
Winter Service Group
County Lane MilesWinter Patrol Sections 2017
Survey
Lane Miles per
Patrol Section
Winter Service Group
Adams 193.20 5 38.64 F Ashland 245.35 5 49.07 EFlorence 141.07 3 47.02 F Barron 428.77 12 35.73 CForest 312.38 6 52.06 E Bayfield 316.42 6 52.74 DGreen Lake 158.44 4 39.61 D Buffalo 317.02 7 45.29 DIron 249.56 6 41.59 E Burnett 237.93 5 47.59 ELanglade 299.21 6 49.87 E Chippewa 654.65 16 40.92 BLincoln 405.55 10 40.56 C Clark 402.56 10 40.26 CMarathon 874.81 19 46.04 B Douglas 451.40 9 50.16 CMarquette 245.75 5 49.15 D Dunn 519.24 11 47.20 CMenominee 90.26 2 45.13 F Eau Claire 540.70 13 41.59 BOneida 396.79 10 39.68 D Jackson 515.44 9 57.27 CPortage 584.63 15 38.98 B Pepin 112.38 3 37.46 EPrice 322.26 6 53.71 E Pierce 369.46 7 52.78 CShawano 520.57 14 37.18 C Polk 385.81 7 55.12 DVilas 305.24 7 43.61 E Rusk 213.47 5 42.69 EWaupaca 546.74 13 42.06 B Saint Croix 645.34 11 58.67 BWaushara 345.01 7 49.29 D Sawyer 367.44 6 61.24 EWood 422.62 15 28.17 C Taylor 233.90 4 58.48 ERegion Average 43.46 Trempeleau 442.48 11 40.23 D
Washburn 372.14 8 46.52 DRegion Average 48.05
County Lane MilesWinter Patrol Sections 2017
Survey
Lane Miles per
Patrol Section
Winter Service Group
County Lane MilesWinter Patrol Sections 2017
Survey
Lane Miles per
Patrol Section
Winter Service Group
Brown 890.40 21 42.40 B Columbia 787.40 15 52.49 BCalumet 201.71 6 33.62 E Crawford 395.79 8 49.47 CDoor 271.80 9 30.20 D Dane 1543.70 31 49.80 AFond du Lac 605.30 10 60.53 B Dodge 637.85 9 70.87 BKewaunee 111.35 3 37.12 F Grant 622.06 11 56.55 BManitowoc 426.01 11 38.73 C Green 314.64 5 62.93 DMarinette 436.66 9 48.52 D Iowa 473.13 10 47.31 EOconto 468.90 10 46.89 C Jefferson 549.67 12 45.81 BOutagamie 538.63 17 31.68 B Juneau 496.27 10 49.63 CSheboygan 527.86 13 40.60 C LaCrosse 503.31 13 38.72 CWinnebago 626.56 18 34.81 B Lafayette 299.38 5 59.88 DRegion Average 40.46 Monroe 654.43 13 50.34 B
Richland 327.64 7 46.81 DRock 686.50 15 45.77 BSauk 576.25 15 38.42 BVernon 468.36 11 42.58 CRegion Average 50.46
County Lane MilesWinter Patrol Sections 2017
Survey
Lane Miles per
Patrol Section
Winter Service Group
Lane Miles
Winter Patrol
Sections 2017 Survey
Lane Miles per
Patrol Section
Kenosha 653.56 17 38.44 B Statewide Totals 34,619.90 755.0 45.85Milwaukee 1955.81 35 55.88 A Statewide Averages 480.83 10.5 45.85Ozaukee 309.19 6 51.53 D Group A Averages 1509.23 30.0 51.38Racine 681.88 17 40.11 B Group B Averages 646.68 14.4 46.19Walworth 706.03 14 50.43 B Group C Averages 457.63 10.7 43.85Washington 611.91 12 50.99 B Group D Averages 328.95 6.9 49.11Waukesha 1073.97 19 56.52 A Group E Averages 275.39 5.7 48.20Region Average 49.13 Group F Averages 133.97 3.3 41.98
NC Region NW Region
NE Region SW Region
SE Region
86 // W i s D O T | A n n u a l W i n t e r M a i n t e n a n c e R e p o r t
County Region Dry Snow
Freezing Rain
Wet Snow
Sleet All Precip. Types
Precipitation Type
(Average Time in Hours)
SeverityIndex
Cost per LM per
Severity Index
Table 4.9. Storm Start vs. Crew Out by Precipitation Type, Group A
Note: 1) A negative number indicates that the crews were on the road when the storm started. 2) A discrepancy is inherent in these calculation because an individual storm may have several precipitation types but when calculating the average time difference for a particular precipitation type this is not taken into account.
From Winter Storm Reports, 2016-2017
DANE SW 0.20 0.250.75 0.00 0.45 72.88 2.58WAUKESHA SE 1.58 0.360.43 0.37 0.79 54.70 1.79MILWAUKEE SE 0.00 -0.250.00 0.00 -0.13 62.67 0.93
0.59 0.120.39 0.12 0.37 63.41 1.76Group A Averages
Final totals as of Monday, June 26, 2017 Page 1 of 1
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County Region Dry Snow
Freezing Rain
Wet Snow
Sleet All Precip. Types
Precipitation Type
(Average Time in Hours)
SeverityIndex
Cost per LM per
Severity Index
Table 4.9. Storm Start vs. Crew Out by Precipitation Type, Group B
Note: 1) A negative number indicates that the crews were on the road when the storm started. 2) A discrepancy is inherent in these calculation because an individual storm may have several precipitation types but when calculating the average time difference for a particular precipitation type this is not taken into account.
From Winter Storm Reports, 2016-2017
EAU CLAIRE NW 0.75 3.301.58 3.00 1.77 64.13 4.62SAUK SW 0.80 1.130.78 0.90 1.03 95.71 3.98COLUMBIA SW 0.00 -0.07-0.06 0.00 -0.03 96.38 3.64DODGE SW 3.88 2.920.56 0.40 2.46 63.82 3.62WASHINGTON SE 0.38 1.330.73 0.67 0.72 78.49 3.52PORTAGE NC 4.14 0.922.64 1.67 2.49 112.02 3.50JEFFERSON SW 1.29 0.210.87 1.25 0.84 63.75 3.41FOND DU LAC NE 1.75 1.001.43 1.00 1.50 71.19 3.12WAUPACA NC 1.83 1.061.36 0.67 1.44 88.42 3.09SAINT CROIX NW 0.68 1.000.71 0.86 0.86 83.62 3.05MONROE SW 1.00 1.170.66 0.50 0.84 92.34 2.96WINNEBAGO NE 0.90 0.280.42 0.71 0.56 66.88 2.96KENOSHA SE 0.50 0.000.00 -0.50 0.13 66.20 2.85BROWN NE -0.33 -0.14-0.17 -0.25 -0.20 66.41 2.62WALWORTH SE 0.13 0.500.75 0.69 65.50 2.55OUTAGAMIE NE 0.13 1.060.93 1.29 0.79 72.91 2.50GRANT SW 2.58 1.632.11 2.00 1.97 77.41 2.20MARATHON NC 4.17 2.951.91 3.00 3.08 112.64 2.16RACINE SE 0.35 0.071.00 -0.10 0.44 65.10 2.13ROCK SW 0.05 -0.500.33 -0.03 48.04 1.83
1.25 0.990.93 0.95 1.07 77.55 3.02Group B Averages
Final totals as of Monday, June 26, 2017 Page 1 of 1
88 // W i s D O T | A n n u a l W i n t e r M a i n t e n a n c e R e p o r t
County Region Dry Snow
Freezing Rain
Wet Snow
Sleet All Precip. Types
Precipitation Type
(Average Time in Hours)
SeverityIndex
Cost per LM per
Severity Index
Table 4.9. Storm Start vs. Crew Out by Precipitation Type, Group C
Note: 1) A negative number indicates that the crews were on the road when the storm started. 2) A discrepancy is inherent in these calculation because an individual storm may have several precipitation types but when calculating the average time difference for a particular precipitation type this is not taken into account.
From Winter Storm Reports, 2016-2017
JACKSON NW 1.10 0.750.69 0.65 0.80 67.43 6.31WOOD NC 4.36 2.814.00 4.45 3.53 107.76 4.70DUNN NW 1.61 0.190.16 -0.21 0.69 96.23 4.61LINCOLN NC 7.86 2.552.82 2.53 4.23 125.63 4.55DOUGLAS NW 2.39 3.412.57 2.71 2.66 168.87 4.39CLARK NW 5.06 4.253.80 4.37 4.30 103.14 4.36MANITOWOC NE 0.80 0.580.31 0.25 0.94 78.98 4.33PIERCE NW 2.91 3.213.00 3.42 2.88 90.76 4.10JUNEAU SW 0.58 0.441.09 0.43 0.78 76.38 4.04IOWA SW 2.83 0.620.95 0.67 1.34 84.40 3.80VERNON SW 4.13 0.861.14 0.83 1.93 79.14 3.78BARRON NW 1.55 2.112.00 1.81 2.03 115.12 3.65SHAWANO NC 3.42 3.893.22 2.60 3.78 93.65 3.61CRAWFORD SW 2.55 0.290.94 -1.25 1.67 88.75 3.56SHEBOYGAN NE 1.00 0.140.37 -0.13 0.64 81.72 3.50LA CROSSE SW 2.12 2.002.94 3.75 2.36 46.37 3.02OCONTO NE 3.33 2.463.17 3.05 3.17 92.14 2.88
2.80 1.801.95 1.76 2.22 93.91 4.07Group C Averages
Final totals as of Monday, June 26, 2017 Page 1 of 1
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County Region Dry Snow
Freezing Rain
Wet Snow
Sleet All Precip. Types
Precipitation Type
(Average Time in Hours)
SeverityIndex
Cost per LM per
Severity Index
Table 4.9. Storm Start vs. Crew Out by Precipitation Type, Group D
Note: 1) A negative number indicates that the crews were on the road when the storm started. 2) A discrepancy is inherent in these calculation because an individual storm may have several precipitation types but when calculating the average time difference for a particular precipitation type this is not taken into account.
From Winter Storm Reports, 2016-2017
MARQUETTE NC 1.29 1.311.25 1.63 1.25 58.14 7.97BAYFIELD NW 4.22 2.393.26 1.95 3.74 143.66 6.72OZAUKEE SE 0.17 0.071.28 0.75 0.66 66.92 6.56ONEIDA NC 5.95 5.573.38 4.07 5.50 107.70 6.38DOOR NE 2.62 1.282.00 1.44 1.97 84.58 6.29WASHBURN NW 3.79 2.472.76 2.18 3.44 101.72 4.69RICHLAND SW 3.83 2.333.79 2.67 3.50 82.23 4.31BUFFALO NW 1.11 0.110.67 0.20 0.70 98.17 4.28POLK NW 1.64 2.391.80 4.25 2.28 126.40 4.24TREMPEALEAU NW 1.15 -0.220.17 0.00 0.52 81.87 4.12WAUSHARA NC -0.67 0.961.14 0.25 0.74 86.57 3.89MARINETTE NE 1.41 0.681.75 1.79 1.10 125.00 3.84GREEN SW 4.62 0.360.67 0.50 2.18 62.48 3.41LAFAYETTE SW 1.33 1.361.57 0.80 1.27 63.03 3.31
2.32 1.501.82 1.61 2.06 92.03 5.00Group D Averages
Final totals as of Monday, June 26, 2017 Page 1 of 1
90 // W i s D O T | A n n u a l W i n t e r M a i n t e n a n c e R e p o r t
County Region Dry Snow
Freezing Rain
Wet Snow
Sleet All Precip. Types
Precipitation Type
(Average Time in Hours)
SeverityIndex
Cost per LM per
Severity Index
Table 4.9. Storm Start vs. Crew Out by Precipitation Type, Group E
Note: 1) A negative number indicates that the crews were on the road when the storm started. 2) A discrepancy is inherent in these calculation because an individual storm may have several precipitation types but when calculating the average time difference for a particular precipitation type this is not taken into account.
From Winter Storm Reports, 2016-2017
CALUMET NE 2.36 2.923.25 0.00 2.60 95.00 13.50PEPIN NW 4.85 3.455.50 2.88 4.43 93.23 12.50IRON NC 5.50 3.663.86 5.57 4.33 145.20 9.45VILAS NC 7.25 3.734.95 3.47 4.96 127.73 8.61TAYLOR NW 3.42 3.072.32 2.20 2.80 110.61 8.37ASHLAND NW 5.05 3.563.16 3.50 3.96 144.99 7.07RUSK NW 3.88 3.603.89 3.86 4.17 90.36 6.89BURNETT NW 4.66 4.554.50 2.14 4.42 97.80 5.98PRICE NC 2.33 1.201.36 1.11 1.83 142.11 5.70LANGLADE NC 3.77 2.703.53 4.50 3.41 106.60 5.33FOREST NC 6.57 3.783.82 2.00 4.97 108.97 5.18SAWYER NW 6.27 4.933.72 2.40 5.46 112.20 4.01
4.66 3.433.65 2.80 3.94 114.57 7.72Group E Averages
Final totals as of Monday, June 26, 2017 Page 1 of 1
2 0 1 6 - 2 0 1 7 | I t ' s O n l y C o l d i f Y o u ' r e S t a n d i n g S t i l l / / 91
County Region Dry Snow
Freezing Rain
Wet Snow
Sleet All Precip. Types
Precipitation Type
(Average Time in Hours)
SeverityIndex
Cost per LM per
Severity Index
Table 4.9. Storm Start vs. Crew Out by Precipitation Type, Group F
Note: 1) A negative number indicates that the crews were on the road when the storm started. 2) A discrepancy is inherent in these calculation because an individual storm may have several precipitation types but when calculating the average time difference for a particular precipitation type this is not taken into account.
From Winter Storm Reports, 2016-2017
MENOMINEE NC 3.45 2.003.28 3.15 77.67 16.66FLORENCE NC 4.75 2.753.74 3.38 3.95 132.71 14.79ADAMS NC 7.08 3.973.44 4.27 4.71 111.59 10.83KEWAUNEE NE 6.00 1.501.25 1.13 3.31 63.96 10.64GREEN LAKE NC 5.83 3.612.06 1.88 3.06 79.01 7.78
5.42 2.772.76 2.66 3.64 92.99 12.14Group F Averages
Final totals as of Monday, June 26, 2017 Page 1 of 1
92 // W i s D O T | A n n u a l W i n t e r M a i n t e n a n c e R e p o r t
Tabl
e 4.
10. W
inte
r Mai
nten
ance
Cos
ts p
er L
ane
Mile
Fisc
al Y
ear
2017
Win
ter
Mai
nten
ance
Cos
ts P
er L
ane
Mile
Lab
or $
's p
erE
quip
$'s
per
Mat
eria
ls $
'sC
ost o
fT
ons o
fT
otal
FY
201
720
17 L
OS
Win
ter
Cos
ts P
er
Cou
nty
#L
abor
Lan
e M
ileE
quip
men
tL
ane
Mile
Mat
eria
lsL
ane
Mile
Adm
inSa
lt U
sed
Salt
Use
dW
inte
r C
osts
Lan
e M
iles
Lan
e M
ile
RE
GIO
N 1
/ SO
UT
HW
EST
11C
olum
bia
$502
,058
$638
$578
,523
$735
$78,
291
$99
$81,
491
$1,5
09,4
4818
,933
$2,7
49,8
1178
7.40
$3,4
92
12C
raw
ford
$135
,769
$343
$182
,594
$461
$39,
347
$99
$26,
251
$310
,976
4,29
1$6
94,9
3739
5.79
$1,7
56
13D
ane
$1,2
67,5
80$8
21$1
,254
,051
$812
$240
,938
$156
$151
,411
$2,1
98,2
4730
,402
$5,1
12,2
271,
543.
70$3
,312
14D
odge
$3
52,2
03$5
52$5
39,2
08$8
45$3
7,29
5$5
8$4
5,12
0$9
44,3
2413
,465
$1,9
18,1
5063
7.85
$3,0
07
22G
rant
$217
,826
$350
$272
,472
$438
$56,
693
$91
$29,
032
$508
,766
7,59
4$1
,084
,789
622.
06$1
,744
23G
reen
$140
,608
$447
$139
,900
$445
$11,
630
$37
$13,
267
$159
,981
2,13
9$4
65,3
8631
4.64
$1,4
79
25Io
wa
$255
,501
$540
$288
,300
$609
$90,
618
$192
$34,
528
$488
,133
6,79
9$1
,157
,080
473.
13$2
,446
28Je
ffer
son
$225
,236
$410
$367
,722
$669
$43,
269
$79
$66,
240
$619
,560
9,05
7$1
,322
,027
549.
67$2
,405
29Ju
neau
$255
,588
$515
$321
,689
$648
$62,
462
$126
$29,
461
$634
,923
8,21
5$1
,304
,123
496.
27$2
,628
32L
a C
ross
e$2
46,5
66$4
90$4
07,7
61$8
10$8
3,69
4$1
66$3
5,48
8$4
71,8
106,
959
$1,2
45,3
1950
3.31
$2,4
74
33L
afay
ette
$104
,260
$348
$168
,400
$562
$76,
568
$256
$17,
217
$158
,327
2,24
9$5
24,7
7229
9.38
$1,7
53
41M
onro
e$2
49,5
93$3
81$4
35,6
69$6
66$5
5,52
7$8
5$3
5,12
6$8
53,3
4411
,241
$1,6
29,2
5965
4.43
$2,4
90
52R
ichl
and
$134
,990
$412
$169
,167
$516
$11,
542
$35
$18,
661
$258
,432
3,35
9$5
92,7
9232
7.64
$1,8
09
53R
ock
$317
,361
$462
$369
,524
$538
$17,
979
$26
$39,
440
$512
,122
7,73
0$1
,256
,426
686.
50$1
,830
56Sa
uk$3
35,2
25$5
82$4
10,6
14$7
13$6
,575
$11
$34,
173
$774
,051
9,83
4$1
,560
,638
576.
25$2
,708
62V
erno
n$2
03,4
98$4
34$3
12,5
47$6
67$2
7,66
6$5
9$2
4,71
8$3
91,4
635,
507
$959
,892
468.
36$2
,049
SW T
OT
AL
$4,9
43,8
62$5
30$6
,218
,141
$666
$940
,094
$101
$681
,624
$10,
793,
907
147,
774
$23,
577,
628
9,33
6.38
$2,5
25
2 0 1 6 - 2 0 1 7 | I t ' s O n l y C o l d i f Y o u ' r e S t a n d i n g S t i l l / / 93
Tabl
e 4.
10. W
inte
r Mai
nten
ance
Cos
ts p
er L
ane
Mile
Fisc
al Y
ear
2017
Win
ter
Mai
nten
ance
Cos
ts P
er L
ane
Mile
Lab
or $
's p
erE
quip
$'s
per
Mat
eria
ls $
'sC
ost o
fT
ons o
fT
otal
FY
201
720
17 L
OS
Win
ter
Cos
ts P
er
Cou
nty
#L
abor
Lan
e M
ileE
quip
men
tL
ane
Mile
Mat
eria
lsL
ane
Mile
Adm
inSa
lt U
sed
Salt
Use
dW
inte
r C
osts
Lan
e M
iles
Lan
e M
ile
RE
GIO
N 2
/ SO
UT
HE
AST
30K
enos
ha$4
05,2
59$6
20$4
50,0
14$6
89($
62,0
64)
($95
)$3
5,75
4$6
54,6
4510
,524
$1,4
83,6
0865
3.56
$2,2
70
40M
ilwau
kee
$3,1
13,5
99$1
,592
$1,4
69,6
44$7
51$3
0,18
6$1
5$1
,660
,987
27,6
42$6
,274
,416
1,95
5.81
$3,2
08
45O
zauk
ee$2
62,0
42$8
48$3
28,0
33$1
,061
$16,
492
$53
$27,
735
$409
,576
6,98
5$1
,043
,878
309.
19$3
,376
51R
acin
e$3
30,3
08$4
84$3
75,4
17$5
51$1
0,44
9$1
5$3
6,23
0$5
00,1
887,
950
$1,2
52,5
9268
1.88
$1,8
37
64W
alw
orth
$308
,438
$437
$583
,714
$827
$4,3
40$6
$54,
801
$765
,417
12,8
78$1
,716
,710
706.
03$2
,431
66W
ashi
ngto
n$4
03,8
44$6
60$5
50,1
82$8
99$5
2,89
8$8
6$4
4,23
1$7
97,1
5412
,212
$1,8
48,3
0961
1.91
$3,0
21
67W
auke
sha
$542
,589
$505
$692
,899
$645
$54,
483
$51
$58,
379
$1,2
79,5
6820
,596
$2,6
27,9
181,
073.
97$2
,447
SE T
OT
AL
$5,3
66,0
79$8
95$4
,449
,903
$743
$106
,784
$18
$257
,130
$6,0
67,5
3598
,787
$16,
247,
431
5,99
2.35
$2,7
11
RE
GIO
N 3
/ N
OR
TH
EA
ST
5B
row
n$4
39,4
14$4
94$7
75,6
65$8
71$1
3,64
1$1
5$9
0,82
8$7
32,8
2012
,709
$2,0
52,3
6889
0.40
$2,3
05
8C
alum
et$1
04,1
73$5
16$1
68,6
16$8
36$1
1,13
2$5
5$1
2,60
2$1
10,1
781,
804
$406
,701
201.
71$2
,016
15D
oor
$171
,100
$630
$245
,900
$905
$91,
851
$338
$27,
845
$230
,004
3,54
1$7
66,7
0027
1.80
$2,8
21
20Fo
nd d
u L
ac$3
70,6
41$6
12$4
50,9
64$7
45$2
8,19
1$4
7$4
2,77
7$5
61,7
318,
118
$1,4
54,3
0460
5.30
$2,4
03
31K
ewan
ee$5
5,78
0$5
01$7
2,87
7$6
54$9
,936
$89
$6,1
44$7
8,01
41,
313
$222
,751
111.
35$2
,000
36M
anito
woc
$325
,016
$763
$341
,245
$801
$60,
262
$141
$49,
969
$381
,691
6,16
5$1
,158
,183
426.
01$2
,719
38M
arin
ette
$193
,722
$444
$276
,998
$634
$18,
415
$42
$23,
760
$370
,546
5,55
3$8
83,4
4143
6.66
$2,0
23
42O
cont
o$2
21,6
63$4
73$2
90,6
00$6
20$7
,058
$15
$23,
047
$326
,068
5,01
4$8
68,4
3646
8.90
$1,8
52
44O
utag
amie
$419
,472
$779
$412
,749
$766
$95,
760
$178
$41,
574
$305
,476
4,94
1$1
,275
,031
538.
63$2
,367
59Sh
eboy
gan
$331
,470
$628
$313
,183
$593
$44,
994
$85
$33,
745
$598
,497
8,72
1$1
,321
,889
527.
86$2
,504
70W
inne
bago
$374
,969
$598
$531
,840
$849
$64,
740
$103
$48,
849
$581
,263
9,08
1$1
,601
,661
626.
56$2
,556
NE
TO
TA
L$3
,007
,420
$589
$3,8
80,6
37$7
60$4
45,9
80$8
7$4
01,1
40$4
,276
,288
66,9
60$1
2,01
1,46
55,
105.
18$2
,353
94 // W i s D O T | A n n u a l W i n t e r M a i n t e n a n c e R e p o r t
Tabl
e 4.
10. W
inte
r Mai
nten
ance
Cos
ts p
er L
ane
Mile
Fisc
al Y
ear
2017
Win
ter
Mai
nten
ance
Cos
ts P
er L
ane
Mile
Lab
or $
's p
erE
quip
$'s
per
Mat
eria
ls $
'sC
ost o
fT
ons o
fT
otal
FY
201
720
17 L
OS
Win
ter
Cos
ts P
er
Cou
nty
#L
abor
Lan
e M
ileE
quip
men
tL
ane
Mile
Mat
eria
lsL
ane
Mile
Adm
inSa
lt U
sed
Salt
Use
dW
inte
r C
osts
Lan
e M
iles
Lan
e M
ile
RE
GIO
N 4
/ N
OR
TH
CE
NT
RA
L
1A
dam
s$1
14,4
94$5
93$1
54,9
89$8
02$1
6,15
5$8
4$1
5,56
8$2
72,2
183,
374
$573
,424
193.
20$2
,968
19Fl
oren
ce$6
0,06
8$4
26$1
27,9
83$9
07$8
,925
$63
$22,
481
$182
,446
2,62
7$4
01,9
0314
1.07
$2,8
49
21Fo
rest
$97,
690
$313
$259
,951
$832
$30,
785
$99
$20,
987
$298
,456
4,43
4$7
07,8
6931
2.38
$2,2
66
24G
reen
Lak
e$8
3,02
2$5
24$8
4,30
0$5
32$7
,241
$46
$8,0
22$1
11,8
221,
599
$294
,407
158.
44$1
,858
26Ir
on$1
58,3
07$6
34$2
40,6
44$9
64$8
,565
$34
$18,
220
$369
,230
5,06
3$7
94,9
6624
9.56
$3,1
85
34L
angl
ade
$161
,502
$540
$214
,870
$718
$4,7
09$1
6$1
9,85
3$2
28,9
013,
533
$629
,835
299.
21$2
,105
35L
inco
ln$2
47,3
81$6
10$3
81,3
82$9
40$6
3,33
3$1
56$3
1,78
1$3
53,6
164,
887
$1,0
77,4
9340
5.55
$2,6
57
37M
arat
hon
$439
,463
$502
$633
,421
$724
$81,
481
$93
$54,
428
$863
,140
11,1
58$2
,071
,933
874.
81$2
,368
39M
arqu
ette
$122
,641
$499
$151
,217
$615
$32,
342
$132
$15,
145
$328
,253
4,54
1$6
49,5
9824
5.75
$2,6
43
73M
enom
inee
$23,
159
$257
$55,
394
$614
$10,
840
$120
$3,9
63$9
7,13
21,
558
$190
,488
90.2
6$2
,110
43O
neid
a$2
26,4
78$5
71$3
33,6
43$8
41$8
9,50
3$2
26$2
9,45
1$6
29,4
918,
247
$1,3
08,5
6639
6.79
$3,2
98
49Po
rtag
e$4
05,1
24$6
93$5
35,1
89$9
15$6
2,25
9$1
06$4
7,02
8$5
52,2
867,
415
$1,6
01,8
8658
4.63
$2,7
40
50Pr
ice
$135
,517
$421
$262
,717
$815
$36,
859
$114
$24,
404
$313
,860
4,20
3$7
73,3
5732
2.26
$2,4
00
58Sh
awan
o$3
10,5
42$5
97$4
32,9
01$8
32$9
,019
$17
$47,
039
$505
,930
7,96
8$1
,305
,431
520.
57$2
,508
63V
ilas
$187
,375
$614
$343
,330
$1,1
25$1
4,03
9$4
6$2
6,38
9$4
80,3
466,
083
$1,0
51,4
7930
5.24
$3,4
45
68W
aupa
ca$2
88,7
58$5
28$4
22,5
52$7
73$4
2,77
5$7
8$3
4,54
6$5
07,8
647,
702
$1,2
96,4
9554
6.74
$2,3
71
69W
aush
ara
$147
,138
$426
$161
,827
$469
$4,3
13$1
3$1
5,86
8$2
44,4
413,
612
$573
,587
345.
01$1
,663
71W
ood
$191
,657
$453
$260
,475
$616
$8,9
02$2
1$2
0,57
7$5
07,2
626,
695
$988
,873
422.
62$2
,340
NC
TO
TA
L$3
,400
,316
$530
$5,0
56,7
85$7
88$5
32,0
45$8
3$4
55,7
50$6
,846
,692
94,6
99$1
6,29
1,58
86,
414.
09$2
,540
2 0 1 6 - 2 0 1 7 | I t ' s O n l y C o l d i f Y o u ' r e S t a n d i n g S t i l l / / 95
Tabl
e 4.
10. W
inte
r Mai
nten
ance
Cos
ts p
er L
ane
Mile
Fisc
al Y
ear
2017
Win
ter
Mai
nten
ance
Cos
ts P
er L
ane
Mile
Lab
or $
's p
erE
quip
$'s
per
Mat
eria
ls $
'sC
ost o
fT
ons o
fT
otal
FY
201
720
17 L
OS
Win
ter
Cos
ts P
er
Cou
nty
#L
abor
Lan
e M
ileE
quip
men
tL
ane
Mile
Mat
eria
lsL
ane
Mile
Adm
inSa
lt U
sed
Salt
Use
dW
inte
r C
osts
Lan
e M
iles
Lan
e M
ile
RE
GIO
N 5
/ N
OR
TH
WE
ST
2A
shla
nd$1
09,6
94$4
47$1
75,1
92$7
14$5
4,19
1$2
21$2
5,38
5$1
91,4
532,
691
$555
,915
245.
35$2
,266
3B
arro
n$3
17,6
51$7
41$3
01,1
48$7
02$3
6,96
9$8
6$4
1,36
9$2
85,1
413,
979
$982
,278
428.
77$2
,291
4B
ayfie
ld$1
62,9
86$5
15$2
71,3
23$8
57$2
2,09
2$7
0$2
2,74
6$3
28,6
834,
976
$807
,830
316.
42$2
,553
6B
uffa
lo$1
44,8
40$4
57$1
92,9
94$6
09$1
,163
$4$1
8,08
6$2
24,5
723,
188
$581
,655
317.
02$1
,835
7B
urne
tt$9
9,41
6$4
18$1
18,1
00$4
96$2
77,6
55$1
,167
$29,
669
$199
,384
2,98
6$7
24,2
2423
7.93
$3,0
44
9C
hipp
ewa
$456
,351
$697
$459
,805
$702
$128
,934
$197
$61,
654
$921
,625
12,2
30$2
,028
,369
654.
65$3
,098
10C
lark
$209
,023
$519
$266
,683
$662
$3,4
50$9
$37,
923
$392
,906
5,08
3$9
09,9
8540
2.56
$2,2
60
16D
ougl
as$2
59,2
89$5
73$4
20,9
45$9
30$4
0,28
1$8
9$4
2,67
0$4
63,6
947,
713
$1,2
26,8
7945
2.73
$2,7
10
17D
unn
$331
,044
$638
$383
,235
$738
$5,6
71$1
1$3
5,13
7$7
50,6
0010
,075
$1,5
05,6
8751
9.24
$2,9
00
18E
au C
lair
e$3
02,7
22$5
60$4
22,7
88$7
82$4
3,43
7$8
0$4
2,99
4$8
42,6
9111
,059
$1,6
54,6
3254
0.70
$3,0
60
27Ja
ckso
n$2
05,9
74$4
00$3
70,5
88$7
19$1
73,9
40$3
37$3
3,71
6$6
68,5
278,
531
$1,4
52,7
4551
5.44
$2,8
18
46Pe
pin
$83,
042
$739
$65,
033
$579
$0$0
$6,6
62$5
3,66
169
8$2
08,3
9811
2.38
$1,8
54
47Pi
erce
$212
,466
$575
$243
,391
$659
$12,
070
$33
$25,
281
$311
,058
4,34
0$8
04,2
6636
9.46
$2,1
77
48Po
lk$1
73,0
83$4
49$2
60,7
92$6
76$1
4,13
6$3
7$2
4,39
8$3
83,9
985,
244
$856
,407
385.
81$2
,220
54R
usk
$59,
104
$277
$106
,413
$498
$71,
211
$334
$27,
208
$181
,706
2,41
5$4
45,6
4221
3.47
$2,0
88
57Sa
wye
r$1
29,5
11$3
52$1
76,2
15$4
80$1
3,68
4$3
7$1
4,92
0$3
30,2
194,
285
$664
,549
367.
44$1
,809
55St
. Cro
ix$3
47,7
54$5
39$3
36,4
26$5
21$1
96,8
58$3
05$7
1,80
4$8
40,3
1312
,199
$1,7
93,1
5564
5.34
$2,7
79
60T
aylo
r$1
21,6
95$5
20$1
69,0
35$7
23$1
2,85
6$5
5$1
5,85
1$2
73,6
093,
233
$593
,046
233.
90$2
,535
61T
rem
peal
eau
$206
,487
$467
$295
,308
$667
$11,
505
$26
$33,
806
$498
,825
6,90
2$1
,045
,931
442.
48$2
,364
65W
ashb
urn
$147
,722
$397
$272
,826
$733
$10,
238
$28
$22,
231
$413
,972
6,15
1$8
66,9
8937
2.14
$2,3
30
NW
TO
TA
L$4
,079
,854
$525
$5,3
08,2
40$6
83$1
,130
,341
$145
$633
,510
$8,5
56,6
3611
7,97
8$1
9,70
8,58
17,
773.
23$2
,535
96 // W i s D O T | A n n u a l W i n t e r M a i n t e n a n c e R e p o r t
Tabl
e 4.
10. W
inte
r Mai
nten
ance
Cos
ts p
er L
ane
Mile
Fisc
al Y
ear
2017
Win
ter
Mai
nten
ance
Cos
ts P
er L
ane
Mile
L
abor
$'s
per
Equ
ip $
's p
erM
ater
ials
$'s
Cos
t of
Ton
s of
Tot
al F
Y 2
017
2017
LO
SW
inte
r C
osts
Per
Cou
nty
#L
abor
Lan
e M
ileE
quip
men
tL
ane
Mile
Mat
eria
lsL
ane
Mile
Adm
inSa
lt U
sed
Salt
Use
dW
inte
r C
osts
Lan
e M
iles
Lan
e M
ile
STA
TE
WID
E S
UM
MA
RY
SW R
egio
n$4
,943
,862
$530
$6,2
18,1
41$6
66$9
40,0
94$1
01$6
81,6
24$1
0,79
3,90
714
7,77
4$2
3,57
7,62
89,
336.
38$2
,525
SE R
egio
n$5
,366
,079
$895
$4,4
49,9
03$7
43$1
06,7
84$1
8$2
57,1
30$6
,067
,535
98,7
87$1
6,24
7,43
15,
992.
35$2
,711
NE
Reg
ion
$3,0
07,4
20$5
89$3
,880
,637
$760
$445
,980
$87
$401
,140
$4,2
76,2
8866
,960
$12,
011,
465
5,10
5.18
$2,3
53
NC
Reg
ion
$3,4
00,3
16$5
30$5
,056
,785
$788
$532
,045
$83
$455
,750
$6,8
46,6
9294
,699
$16,
291,
588
6,41
4.09
$2,5
40
NW
Reg
ion
$4,0
79,8
54$5
25$5
,308
,240
$683
$1,1
30,3
41$1
45$6
33,5
10$8
,556
,636
117,
978
$19,
708,
581
7,77
3.23
$2,5
35
Stat
ewid
e T
otal
s$2
0,79
7,53
1$6
01$2
4,91
3,70
6$7
20$3
,155
,244
$91
$2,4
29,1
54$3
6,54
1,05
852
6,19
8$8
7,83
6,69
334
,621
.23
$2,5
37
prep
ared
by:
Cat
hy M
einh
olz/
Bur
eau
of H
ighw
ay M
aint
enan
ce
u:\w
inte
r\fy1
7wnt
r. xl
wA
ugus
t 2, 2
017
2 0 1 6 - 2 0 1 7 | I t ' s O n l y C o l d i f Y o u ' r e S t a n d i n g S t i l l / / 97
Figure 4.8. 2016-2017 Winter Costs vs. 5-Year Average
Price-9
Clark9
Dane0
Polk-11
Grant0
Vilas-1
Iron-10
Bayfield-7
Rusk7
Sawyer-14
Oneida6
Marathon6
Sauk14
Forest-20
Douglas8
Iowa28
Dunn18
Taylor11
Marinette8
Rock-20
Oconto-5
Wood17
Barron-2 Lincoln
12
Burnett69
Jackson28
Ashland-13
Monroe28
Dodge 12
Vernon2
Juneau27
Portage21
Chippewa29
Buffalo35
Adams27
Shawano17
Langlade3
Green4
Pierce6
St. Croix20
Brown21
Columbia14
Waupaca14
Washburn 4
Lafayette-10
Richland27Crawford
9
Jefferson2
Waushara5
Walworth-1
Eau Claire21
Outagamie-4
Florence4
Waukesha3
Racine-20
Kenosha1
Door15
Fond du Lac6
Trempealeau24
Manitowoc9
La Crosse27 Marquette
53 Sheboygan-2
Pepin15
Winnebago9
Calumet6
Kewanee-1
Washington17
Green Lake23
Menominee29
Ozaukee9
Milwaukee -6
Increase more than 40%
Increase 30 to 39%
Increase 20 to 29%
Increase 10 to 19%
Increase 0 to 9%
Decrease
98 // W i s D O T | A n n u a l W i n t e r M a i n t e n a n c e R e p o r t
Cou
nty
Snow
D
epth
(in
)
Salt
(ton)
Tota
lC
ost
Lane
M
iles
Tota
l $/
LM
Tabl
e 4.
11. C
ost p
er L
ane
Mile
per
Sev
erity
Inde
x R
anki
ng (
Gro
up
Seve
rity
Inde
xC
ost p
er L
M
per S
ever
ity
Inde
x
Salt
per
LMSa
lt pe
r LM
pe
r Sev
erity
In
dex
Reg
ion
From
Win
ter S
torm
Rep
orts
, 201
6-20
17
A)
SW
DAN
E30
.330
402
$6,1
05,0
001,
543.
70$3
,981
72.8
82.
5819
.69
0.27
SE
WA
UKE
SHA
44.2
2059
6$2
,059
,000
1,07
3.97
$1,9
1754
.70
1.79
19.1
80.
35
SE
MIL
WAU
KEE
36.7
2764
2$3
,540
,000
1,95
5.81
$1,8
1062
.67
0.93
14.1
30.
23
Gro
up37
.126
213
$3,9
01,3
331,
524.
49$2
,569
63.4
11.
7617
.67
0.28
AA
vera
ges W
edne
sday
, Jun
e 28
, 201
7Pa
ge 1
of 1
Fina
l tot
als
as o
f
2 0 1 6 - 2 0 1 7 | I t ' s O n l y C o l d i f Y o u ' r e S t a n d i n g S t i l l / / 99
Cou
nty
Snow
D
epth
(in
)
Salt
(ton)
Tota
lC
ost
Lane
M
iles
Tota
l $/
LM
Tabl
e 4.
11. C
ost p
er L
ane
Mile
per
Sev
erity
Inde
x R
anki
ng (
Gro
up
Seve
rity
Inde
xC
ost p
er L
M
per S
ever
ity
Inde
x
Salt
per
LMSa
lt pe
r LM
pe
r Sev
erity
In
dex
Reg
ion
From
Win
ter S
torm
Rep
orts
, 201
6-20
17
B)
NW
EAU
CLA
IRE
58.1
1105
9$1
,347
,000
540.
70$2
,496
64.1
34.
6220
.45
0.32
SW
SAU
K53
.798
34$1
,323
,000
576.
25$2
,295
95.7
13.
9817
.07
0.18
NW
CH
IPPE
WA
85.9
1223
0$1
,624
,000
654.
65$2
,480
96.4
63.
7918
.68
0.19
SW
CO
LUM
BIA
57.0
1893
3$2
,260
,000
787.
40$2
,870
96.3
83.
6424
.04
0.25
SW
DO
DG
E49
.113
465
$1,4
71,0
0063
7.85
$2,3
0763
.82
3.62
21.1
10.
33
SE
WAS
HIN
GTO
N54
.412
212
$1,3
20,0
0061
1.91
$2,1
5778
.49
3.52
19.9
60.
25
NC
POR
TAG
E61
.774
15$1
,195
,000
584.
63$2
,044
112.
023.
5012
.68
0.11
SW
JEFF
ER
SO
N34
.290
57$1
,031
,000
549.
67$1
,875
63.7
53.
4116
.48
0.26
NE
FON
D D
U L
AC55
.081
18$1
,143
,000
605.
30$1
,889
71.1
93.
1213
.41
0.19
NC
WA
UPA
CA
51.9
7702
$923
,000
546.
74$1
,687
88.4
23.
0914
.09
0.16
NW
SAIN
T C
RO
IX59
.212
199
$1,2
71,0
0064
5.34
$1,9
6983
.62
3.05
18.9
00.
23
SW
MO
NR
OE
60.6
1124
1$1
,267
,000
654.
43$1
,936
92.3
42.
9617
.18
0.19
NE
WIN
NEB
AGO
46.0
9081
$1,1
61,0
0062
6.56
$1,8
5266
.88
2.96
14.4
90.
22
SE
KEN
OSH
A14
.810
524
$1,2
19,0
0065
3.56
$1,8
6566
.20
2.85
16.1
00.
24
NE
BRO
WN
64.1
1270
9$2
,074
,000
890.
40$2
,330
66.4
12.
6214
.27
0.21
SE
WA
LWO
RTH
36.4
1287
8$1
,270
,000
706.
03$1
,798
65.5
02.
5518
.24
0.28
NE
OU
TAG
AMIE
56.7
4941
$727
,000
538.
63$1
,349
72.9
12.
509.
170.
13
SW
GR
ANT
32.6
7594
$850
,000
622.
06$1
,367
77.4
12.
2012
.21
0.16
Wed
nesd
ay, J
une
28, 2
017
Page
1 o
f 2Fi
nal t
otal
s as
of
100 // W i s D O T | A n n u a l W i n t e r M a i n t e n a n c e R e p o r t
Coun
tySn
ow
Dept
h (in
)
Salt
(ton)
Tota
lCo
stLa
ne
Mile
sTo
tal
$/LM
Tabl
e 4.
11. C
ost p
er L
ane
Mile
per
Sev
erity
Inde
x Ra
nkin
g ( G
roup
Seve
rity
Inde
xCo
st p
er L
M
per S
ever
ity
Inde
x
Salt
per
LMSa
lt pe
r LM
pe
r Sev
erity
In
dex
Regi
on
From
Win
ter S
torm
Rep
orts
, 201
6-20
17
B)
NCM
ARAT
HON
64.2
1115
8$1
,654
,000
874.
81$1
,890
112.
642.
1612
.75
0.11
SERA
CINE
50.9
7950
$991
,000
681.
88$1
,453
65.1
02.
1311
.66
0.18
SWRO
CK36
.877
30$9
14,0
0070
6.03
$1,2
9448
.04
1.83
10.9
50.
23
Grou
p51
.610
382
$1,2
87,3
8165
2.13
$1,9
6278
.45
3.05
15.9
00.
21B
Aver
ages
Wed
nesd
ay, J
une
28, 2
017
Page
2 o
f 2Fi
nal t
otal
s as
of
2 0 1 6 - 2 0 1 7 | I t ' s O n l y C o l d i f Y o u ' r e S t a n d i n g S t i l l / / 101
Coun
tySn
ow
Dept
h (in
)
Salt
(ton)
Tota
lCo
stLa
ne
Mile
sTo
tal
$/LM
Tabl
e 4.
11. C
ost p
er L
ane
Mile
per
Sev
erity
Inde
x Ra
nkin
g ( G
roup
Seve
rity
Inde
xCo
st p
er L
M
per S
ever
ity
Inde
x
Salt
per
LMSa
lt pe
r LM
pe
r Sev
erity
In
dex
Regi
on
From
Win
ter S
torm
Rep
orts
, 201
6-20
17
C)
NWJA
CKSO
N53
.585
31$1
,677
,000
515.
44$3
,253
67.4
36.
3116
.55
0.25
NCW
OO
D72
.766
95$8
40,0
0042
2.62
$1,9
8810
7.76
4.70
15.8
40.
15
NWDU
NN63
.310
075
$1,2
43,0
0051
9.24
$2,3
9396
.23
4.61
19.4
00.
20
NCLI
NCO
LN86
.048
87$7
49,0
0040
5.55
$1,8
4612
5.63
4.55
12.0
50.
10
NWDO
UGLA
S84
.777
13$8
94,0
0045
1.40
$1,9
8016
8.87
4.39
17.0
90.
10
NWCL
ARK
83.2
5083
$707
,000
402.
56$1
,756
103.
144.
3612
.63
0.12
NEM
ANIT
OW
OC
58.5
6165
$786
,000
426.
01$1
,845
78.9
84.
3314
.47
0.18
NWPI
ERCE
59.1
4340
$560
,000
369.
46$1
,515
90.7
64.
1011
.75
0.13
SWJU
NEAU
59.5
8215
$996
,000
496.
27$2
,007
76.3
84.
0416
.55
0.22
SWIO
WA
36.4
6799
$852
,000
473.
13$1
,800
84.4
03.
8014
.37
0.17
SWVE
RNO
N41
.955
07$8
30,0
0046
8.36
$1,7
7279
.14
3.78
11.7
60.
15
NWBA
RRO
N63
.139
79$6
70,0
0042
8.77
$1,5
6311
5.12
3.65
9.28
0.08
NCSH
AWAN
O72
.979
68$9
77,0
0052
0.57
$1,8
7793
.65
3.61
15.3
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106 // W i s D O T | A n n u a l W i n t e r M a i n t e n a n c e R e p o r t
Table 4.12. Winter Crashes per 100 Million Vehicle Miles of TravelBureau of Transportation Safety data, November 1, 2016 - April 30, 2017
WisDOT REGION / COUNTY
2016-17 WINTERVEHICLE MILES OF TRAVEL
2016-17 WINTER CRASHES
CRASH RATE PER 100M VMT
NORTH CENTRALADAMS 108,000,000 15 13.88888889FLORENCE 32,800,000 3 9FOREST 62,800,000 23 37GREEN LAKE 111,300,000 6 5IRON 48,400,000 4 8LANGLADE 129,700,000 30 23LINCOLN 223,600,000 46 21MARATHON 780,200,000 215 28MARQUETTE 131,100,000 13 10MENOMINEE 18,800,000 2 11ONEIDA 229,500,000 60 26PORTAGE 432,300,000 126 29PRICE 85,700,000 13 15SHAWANO 328,500,000 63 19VILAS 169,600,000 32 19WAUPACA 291,000,000 82 28WAUSHARA 178,900,000 49 27WOOD 318,200,000 78 25Region Total 3,680,400,000 860 23
NORTHEASTBROWN 1,156,500,000 197 17CALUMET 215,700,000 54 25DOOR 211,100,000 27 13FOND DU LAC 563,800,000 124 22KEWAUNEE 110,300,000 22 20MANITOWOC 414,400,000 71 17MARINETTE 469,900,000 40 9OCONTO 376,100,000 55 15OUTAGAMIE 759,700,000 166 22SHEBOYGAN 508,600,000 109 21WINNEBAGO 827,900,000 266 32Region Total 5,614,000,000 1,131 20
Table 4.12. Winter Crashes per 100 Million Vehicle Miles of TravelBureau of Transportation Safety data, November 1, 2016 - April 30, 2017
WisDOT REGION / COUNTY
2016-17 WINTERVEHICLE MILES OF TRAVEL
2016-17 WINTER CRASHES
CRASH RATE PER 100M VMT
NORTHWESTASHLAND 87,500,000 14 16BARRON 297,200,000 40 13BAYFIELD 134,800,000 19 14BUFFALO 97,000,000 15 15BURNETT 94,100,000 9 10CHIPPEWA 424,700,000 91 21CLARK 221,300,000 61 28DOUGLAS 258,100,000 66 26DUNN 322,900,000 78 24EAU CLAIRE 497,200,000 144 29JACKSON 291,400,000 61 21PEPIN 38,000,000 13 34PIERCE 165,800,000 44 27POLK 231,700,000 29 13RUSK 90,100,000 15 17ST.CROIX 123,000,000 86 70SAWYER 592,100,000 11 2TAYLOR 91,700,000 21 23TREMPEALEAU 225,700,000 49 22WASHBURN 150,200,000 21 14Region Total 4,434,500,000 887 20
SOUTHEASTKENOSHA 713,100,000 130 18MILWAUKEE 3,196,200,000 328 10OZAUKEE 477,300,000 56 12RACINE 758,400,000 110 15WALWORTH 594,400,000 95 16WASHINGTON 719,600,000 142 20WAUKESHA 1,837,800,000 173 9Region Total 8,296,800,000 1,034 12
2 0 1 6 - 2 0 1 7 | I t ' s O n l y C o l d i f Y o u ' r e S t a n d i n g S t i l l / / 107
Table 4.12. Winter Crashes per 100 Million Vehicle Miles of TravelBureau of Transportation Safety data, November 1, 2016 - April 30, 2017
WisDOT REGION / COUNTY
2016-17 WINTERVEHICLE MILES OF TRAVEL
2016-17 WINTER CRASHES
CRASH RATE PER 100M VMT
NORTH CENTRALADAMS 108,000,000 15 13.88888889FLORENCE 32,800,000 3 9FOREST 62,800,000 23 37GREEN LAKE 111,300,000 6 5IRON 48,400,000 4 8LANGLADE 129,700,000 30 23LINCOLN 223,600,000 46 21MARATHON 780,200,000 215 28MARQUETTE 131,100,000 13 10MENOMINEE 18,800,000 2 11ONEIDA 229,500,000 60 26PORTAGE 432,300,000 126 29PRICE 85,700,000 13 15SHAWANO 328,500,000 63 19VILAS 169,600,000 32 19WAUPACA 291,000,000 82 28WAUSHARA 178,900,000 49 27WOOD 318,200,000 78 25Region Total 3,680,400,000 860 23
NORTHEASTBROWN 1,156,500,000 197 17CALUMET 215,700,000 54 25DOOR 211,100,000 27 13FOND DU LAC 563,800,000 124 22KEWAUNEE 110,300,000 22 20MANITOWOC 414,400,000 71 17MARINETTE 469,900,000 40 9OCONTO 376,100,000 55 15OUTAGAMIE 759,700,000 166 22SHEBOYGAN 508,600,000 109 21WINNEBAGO 827,900,000 266 32Region Total 5,614,000,000 1,131 20
Table 4.12. Winter Crashes per 100 Million Vehicle Miles of TravelBureau of Transportation Safety data, November 1, 2016 - April 30, 2017
WisDOT REGION / COUNTY
2016-17 WINTERVEHICLE MILES OF TRAVEL
2016-17 WINTER CRASHES
CRASH RATE PER 100M VMT
NORTHWESTASHLAND 87,500,000 14 16BARRON 297,200,000 40 13BAYFIELD 134,800,000 19 14BUFFALO 97,000,000 15 15BURNETT 94,100,000 9 10CHIPPEWA 424,700,000 91 21CLARK 221,300,000 61 28DOUGLAS 258,100,000 66 26DUNN 322,900,000 78 24EAU CLAIRE 497,200,000 144 29JACKSON 291,400,000 61 21PEPIN 38,000,000 13 34PIERCE 165,800,000 44 27POLK 231,700,000 29 13RUSK 90,100,000 15 17ST.CROIX 123,000,000 86 70SAWYER 592,100,000 11 2TAYLOR 91,700,000 21 23TREMPEALEAU 225,700,000 49 22WASHBURN 150,200,000 21 14Region Total 4,434,500,000 887 20
SOUTHEASTKENOSHA 713,100,000 130 18MILWAUKEE 3,196,200,000 328 10OZAUKEE 477,300,000 56 12RACINE 758,400,000 110 15WALWORTH 594,400,000 95 16WASHINGTON 719,600,000 142 20WAUKESHA 1,837,800,000 173 9Region Total 8,296,800,000 1,034 12
108 // W i s D O T | A n n u a l W i n t e r M a i n t e n a n c e R e p o r t
Table 4.12. Winter Crashes per 100 Million Vehicle Miles of TravelBureau of Transportation Safety data, November 1, 2016 - April 30, 2017
WisDOT REGION / COUNTY
2016-17 WINTERVEHICLE MILES OF TRAVEL
2016-17 WINTER CRASHES
CRASH RATE PER 100M VMT
SOUTHWESTCOLUMBIA 512,100,000 103 20CRAWFORD 123,800,000 29 23DANE 2,356,300,000 288 12DODGE 489,800,000 64 13GRANT 261,400,000 50 19GREEN 155,700,000 31 20IOWA 196,600,000 36 18JEFFERSON 498,200,000 74 15JUNEAU 324,100,000 79 24LA CROSSE 515,700,000 156 30LAFAYETTE 110,200,000 29 26MONROE 378,400,000 83 22RICHLAND 104,400,000 26 25ROCK 752,300,000 188 25SAUK 386,600,000 91 24VERNON 158,500,000 43 27Region Total 7,324,100,000 1,370 19
STATEWIDE TOTAL 29,349,800,000 5,282 18
2 0 1 6 - 2 0 1 7 | I t ' s O n l y C o l d i f Y o u ' r e S t a n d i n g S t i l l / / 109
Table 4.12. Winter Crashes per 100 Million Vehicle Miles of TravelBureau of Transportation Safety data, November 1, 2016 - April 30, 2017
WisDOT REGION / COUNTY
2016-17 WINTERVEHICLE MILES OF TRAVEL
2016-17 WINTER CRASHES
CRASH RATE PER 100M VMT
SOUTHWESTCOLUMBIA 512,100,000 103 20CRAWFORD 123,800,000 29 23DANE 2,356,300,000 288 12DODGE 489,800,000 64 13GRANT 261,400,000 50 19GREEN 155,700,000 31 20IOWA 196,600,000 36 18JEFFERSON 498,200,000 74 15JUNEAU 324,100,000 79 24LA CROSSE 515,700,000 156 30LAFAYETTE 110,200,000 29 26MONROE 378,400,000 83 22RICHLAND 104,400,000 26 25ROCK 752,300,000 188 25SAUK 386,600,000 91 24VERNON 158,500,000 43 27Region Total 7,324,100,000 1,370 19
STATEWIDE TOTAL 29,349,800,000 5,282 18
NC Region
COUNTY TOTAL Urban STH Rural STH Urban IH Rural IH Non-div Divided Unkn Non-div Divided UnknADAMS 15 0 15 0 0 0 0 0 15 0 0FLORENCE 3 0 3 0 0 0 0 0 3 0 0FOREST 23 0 23 0 0 0 0 0 23 0 0GREEN LAKE 6 3 3 0 0 3 0 0 3 0 0IRON 4 0 4 0 0 0 0 0 3 1 0LANGLADE 30 5 25 0 0 5 0 0 23 2 0LINCOLN 46 4 42 0 0 4 0 0 19 22 1MARATHON 215 51 131 15 18 20 31 0 35 93 3MARQUETTE 13 0 6 0 7 0 0 0 6 0 0ONEIDA 60 3 57 0 0 2 1 0 50 7 0PORTAGE 126 21 53 13 39 9 12 0 18 34 1PRICE 13 0 13 0 0 0 0 0 12 1 0SHAWANO 63 6 57 0 0 6 0 0 22 34 1VILAS 32 0 32 0 0 0 0 0 29 3 0WAUPACA 82 2 80 0 0 1 1 0 38 42 0WAUSHARA 49 0 38 0 11 0 0 0 35 3 0WOOD 78 47 31 0 0 21 26 0 20 11 0MENOMINEE 2 0 2 0 0 0 0 0 2 0 0TOTAL 860 142 615 28 75 71 71 0 356 253 6
NE Region
COUNTY TOTAL Urban STH Rural STH Urban IH Rural IH Non-div Divided Unkn Non-div Divided UnknBROWN 197 140 33 17 7 44 94 2 8 24 1CALUMET 54 21 27 6 0 14 7 0 26 1 0DOOR 27 5 22 0 0 3 2 0 14 8 0FOND DU LAC 124 42 82 0 0 25 16 1 36 46 0KEWAUNEE 22 0 22 0 0 0 0 0 22 0 0MANITOWOC 71 20 19 0 32 11 9 0 18 0 1MARINETTE 40 9 31 0 0 6 3 0 14 17 0OCONTO 55 0 55 0 0 0 0 0 12 42 1OUTAGAMIE 166 72 94 0 0 28 43 1 40 53 1SHEBOYGAN 109 33 47 3 26 26 7 0 31 15 1WINNEBAGO 266 87 169 10 0 35 50 2 35 127 7TOTAL 1,131 429 601 36 65 192 231 6 256 333 12
NW Region
COUNTY TOTAL Urban STH Rural STH Urban IH Rural IH Non-div Divided Unkn Non-div Divided UnknASHLAND 14 6 8 0 0 3 3 0 8 0 0BARRON 40 2 38 0 0 0 2 0 20 18 0BAYFIELD 19 0 19 0 0 0 0 0 19 0 0BUFFALO 15 0 15 0 0 0 0 0 15 0 0BURNETT 9 0 9 0 0 0 0 0 9 0 0CHIPPEWA 91 12 79 0 0 1 11 0 17 62 0CLARK 61 0 61 0 0 0 0 0 26 35 0DOUGLAS 66 40 18 8 0 18 21 1 7 11 0DUNN 78 20 34 4 20 16 4 0 28 5 1EAU CLAIRE 144 71 29 9 35 12 57 2 15 14 0JACKSON 61 0 20 0 41 0 0 0 18 2 0PEPIN 13 0 13 0 0 0 0 0 13 0 0PIERCE 44 6 38 0 0 6 0 0 38 0 0POLK 29 0 29 0 0 0 0 0 28 1 0RUSK 15 0 15 0 0 0 0 0 15 0 0ST. CROIX 86 10 39 4 33 6 4 0 31 7 1SAWYER 11 0 11 0 0 0 0 0 10 1 0TAYLOR 21 0 21 0 0 0 0 0 20 1 0TREMPEALEAU 49 0 48 0 1 0 0 0 46 2 0WASHBURN 21 0 21 0 0 0 0 0 7 14 0TOTAL 887 167 565 25 130 62 102 3 390 173 2
Motor Vehicle Crashes on Roads with Snow/Ice/SlushBureau of Transportation Safety data, Nov. 1, 2016 - April 30, 2017 State, U.S. and Interstate Highways only
Urban State Highway Rural State Highway
Urban State Highway Rural State Highway
Urban State Highway Rural State Highway
Table 4.13 Motor Vehicle Crashes on Roads with Snow/Ice/Slush
110 // W i s D O T | A n n u a l W i n t e r M a i n t e n a n c e R e p o r t
SE Region
COUNTY TOTAL Urban STH Rural STH Urban IH Rural IH Non-div Divided Unkn Non-div Divided UnknKENOSHA 130 40 50 15 25 24 16 0 21 29 0MILWAUKEE 328 213 0 115 0 71 139 3 0 0 0OZAUKEE 56 9 6 10 31 6 3 0 1 5 0RACINE 110 61 35 0 14 25 36 0 11 24 0WALWORTH 95 16 50 5 24 7 9 0 32 18 0WASHINGTON 142 65 77 0 0 22 43 0 22 54 1WAUKESHA 173 63 42 41 27 8 55 0 21 21 0TOTAL 1,034 467 260 186 121 163 301 3 108 151 1
SW Region
COUNTY TOTAL Urban STH Rural STH Urban IH Rural IH Non-div Divided Unkn Non-div Divided UnknCOLUMBIA 103 4 55 3 41 3 1 0 53 2 0CRAWFORD 29 8 21 0 0 7 1 0 21 0 0DANE 288 119 99 21 49 18 100 1 51 48 0DODGE 64 7 57 0 0 2 5 0 27 30 0GRANT 50 2 48 0 0 2 0 0 36 12 0GREEN 31 7 24 0 0 1 6 0 23 1 0IOWA 36 0 36 0 0 0 0 0 14 22 0JEFFERSON 74 17 36 0 21 15 2 0 14 22 0JUNEAU 79 0 28 1 50 0 0 0 27 1 0LA CROSSE 156 92 32 14 18 51 41 0 14 18 0LAFAYETTE 29 0 29 0 0 0 0 0 21 8 0MONROE 83 16 29 6 32 8 8 0 27 1 1RICHLAND 26 0 26 0 0 0 0 0 21 5 0ROCK 188 68 72 17 31 38 28 2 55 17 0SAUK 91 10 45 0 36 9 1 0 22 23 0VERNON 43 0 43 0 0 0 0 0 42 1 0TOTAL 1,370 350 680 62 278 154 193 3 468 211 1
STH = State highways or non-interstate US highwaysIH = Interstate highways Non-div = Non-dividedRural = An unincorporated area or an incorporated area with a population under 5,000Urban = An incorporated area with a population of 5,000 or more.
*2017 figures are preliminary at this time.**Does not include deer or other animal crashes
Urban State Highway Rural State Highway
Urban State Highway Rural State Highway
2 0 1 6 - 2 0 1 7 | I t ' s O n l y C o l d i f Y o u ' r e S t a n d i n g S t i l l / / 111
WisDOT is excited to be taking advantage of national research to strengthen both service and efficiency on Wisconsin’s winter roads. Areas of focus for the 2017-2018 winter include:
1. Brining. Brine is great for prewetting salt and anti-icing – and it can work harder for us. Research-based brining procedures and state-of-the-art brining equipment have been proven to use up to three times less salt than using dry materials. This saves taxpayer dollars, and reduces harm to the groundwater and environment.
This winter, WisDOT will partner with at least four counties to pilot high-capacity and more versatile brine-makers, and with six counties to pilot Direct Liquid Application (also known as “Liquid-Only Routes”). On liquid-only routes, a truck has little to no rock salt, and instead carries a much larger brine tank which is used to apply liquid brine directly to the pavement. Look for public service announcements (on Facebook and regular media sources) from WisDOT in December 2017.
2. Route Optimization. Using computer algorithms to identify the most effective and efficient snow-plow routes improves driver and public safety, and saves taxpayer dollars.
WisDOT launched a multi-year route optimization pilot last winter. As a result of analysis completed on 12 counties during Summer 2017, Wisconsin taxpayers will pay for 24 fewer snowplows on state and county highways during the winter of 2017-18 -- while receiving the same level of service. We continue to work closely with counties that elect to participate – providing initial routes, tweaking those routes, and tweaking the program as we learn from the pilot.
3. Tow plows. Research has demonstrated that these “plows attached to a trailer” greatly increase the width that one plow truck can accomplish in one pass – providing the same or better service for fewer dollars.
WisDOT owns two tow plows, and partners with counties to learn more about this technology. Brown County used both tow plows last winter. We learned that they appear to be most effective on four-lane highways with routes that involve minimal turning around. Brown County was pleased with the performance and savings from the tow plows; they will use the plows again this winter, and plan to purchase more for Winter 2019.
4. Strategic salt storage. Having the right salt storage in the right places ensures we have salt when we need it, and that we can purchase salt at a good price. Maintaining and replacing salt sheds as they age is critical.
WisDOT works with counties and contractors to identify and implement the most cost-effective sites and designs.
Photo credit: Pixabay Creative Commons License
5 Looking Ahead
112
113
AppendixFigure A-1. WisDOT Regional Organization .........................................................................................................115Table A-1. Storm Report Summary ......................................................................................................................117Weather Forecast Service Evaluation Summary ................................................................................................123Table A-2. Weather Forecasting Service Usage ..................................................................................................129Table A-3. Anti-icing Details ..................................................................................................................................135Table A-4. Annual Anti-icing Agent Usage ............................................................................................................143Table A-5. Actual Anti-icing Costs .........................................................................................................................149Table A-6. Salt Brine Use ......................................................................................................................................152Table A-7. Annual Prewetting Agent Usage for Salt .............................................................................................154Table A-8. Annual Abrasives Usage and Prewetting Agent Usage for Abrasives...............................................160Table A-9. History of Salt Use on State Trunk Highways .....................................................................................166
114
115
Wisconsin Department of Transportation New regional organization Effective May 29, 2005 (updated July 18, 2005)
Southwest RegionSoutheast Region
Northeast Region
North Central Region
Northwest Region
Figure A-1
Wisconsin Department of TransportationRegion MapOctober 2017
116
117Tabl
e A
.1 -
Stor
m R
epor
t Sum
mar
yN
otes
: 1) C
osts
sho
wn
in ta
ble
are
estim
ated
and
do
not i
nclu
de th
e 4.
47%
Adm
inis
trat
ive
Cos
ts; 2
) Mat
eria
l Cos
ts in
clud
es S
alt,
Sand
, and
oth
er D
eici
ng a
nd A
nti-i
cing
Age
nts;
3)
Equi
pmen
t Cos
ts a
re b
ased
on
$60
per h
our p
er u
nit;
4) L
abor
Cos
ts a
re b
ased
on
each
Cou
nty'
s av
erag
e la
bor r
ate;
5) T
otal
Sal
t Ava
ilabl
e =
salt
in s
heds
as
of M
ay p
lus
early
fill,
pl
us s
easo
nal f
ill, p
lus
vend
or re
serv
e av
aila
ble.
From
Win
ter S
torm
Rep
orts
, 201
6-20
17
Reg
ion
NC
Cou
nty
Lane
Mile
sSe
verit
yIn
dex
Snow
Amou
nt
(inch
es)
Anti-
Icin
gSt
orm
sIn
ci-
dent
Free
z. R
ain
Eve
nts
Tota
l Sa
lt Av
ail.
(tons
)
Tota
l Sa
lt U
sed
(tons
)
Tota
l Sa
lt R
emai
n.
(tons
)
Tota
l Sa
nd
Use
d (C
Y)
Tota
l R
eg.
Hou
rs
Tota
l O
T H
ours
Mat
'lEq
uip
Labo
rTo
tal
Estim
ated
To
tal C
ost
to D
ate
Salt
Use
d pe
r LM
(to
ns)
Even
ts th
is S
easo
nEs
timat
ed C
ost P
er L
ane
Mile
Salt
per
LM p
er
Seve
rity
Inde
x
Tota
l Th
aw-
Rox
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ns)
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l C
lear
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ne
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LAS
305.
2412
7.73
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59
4721
299,
316
6,08
33,
233
880
1939
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99.0
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74$5
77$4
77$2
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0.16
00
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6.79
107.
7086
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336
1710
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8,24
72,
623
1579
3833
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$1,5
86$5
07$4
39$2
,532
$1,0
04,6
0420
.80.
190
0
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N24
9.56
145.
2013
1.9
050
1816
6,96
05,
063
1,89
769
1355
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8.0
$1,4
80$4
60$4
18$2
,358
$588
,473
20.3
0.14
00
ADAM
S19
3.2
111.
5945
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218
323,
849
3,37
447
59
1021
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6.0
$1,4
73$3
43$2
75$2
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$403
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17.5
0.16
00
FLO
REN
CE
141.
0713
2.71
91.6
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3,44
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627
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0$1
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$474
$320
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140
0
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TAG
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112.
0261
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3622
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381
7,41
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966
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89.0
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$464
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44$1
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12.7
0.11
00
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OD
422.
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7.76
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150
0
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QU
ETTE
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40.5
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320
0
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ATH
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2.64
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110
0
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520.
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72.9
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3125
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$393
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160
0
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CO
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3221
306,
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71,
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100
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2.26
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6.0
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6,25
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0$9
74$5
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50$1
,837
$591
,955
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0.09
00
WAU
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A54
6.74
88.4
251
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2423
98,
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7,70
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3171
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$321
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22,5
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160
0
FOR
EST
312.
3810
8.97
90.3
338
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7,92
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3,48
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130
0
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GLA
DE
299.
2110
6.60
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110
0
MEN
OM
INEE
90.2
677
.67
58.7
024
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1,85
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558
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7131
3.0
94.0
$1,0
76$2
69$1
59$1
,504
$135
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17.3
0.22
00
WAU
SHAR
A34
5.01
86.5
752
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2319
134,
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3,61
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30
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$378
$256
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120
0
GR
EEN
LAK
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8.44
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918
1,59
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466.
034
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$238
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95,3
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.10.
130
0
Reg
ion
Tota
lR
egio
n Av
erag
e10
6.90
122,
725
94,6
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45$3
48$1
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$12,
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458
$682
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75.3
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19.1
16.1
6,81
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1,55
730
1
----
----
----
----
----
----
--0.
150 0
0 0
Page
1 o
f 6W
edne
sday
, Nov
embe
r 15,
201
7Fi
nal t
otal
s as
of
118 Tabl
e A
.1 -
Stor
m R
epor
t Sum
mar
yN
otes
: 1) C
osts
sho
wn
in ta
ble
are
estim
ated
and
do
not i
nclu
de th
e 4.
47%
Adm
inis
trat
ive
Cos
ts; 2
) Mat
eria
l Cos
ts in
clud
es S
alt,
Sand
, and
oth
er D
eici
ng a
nd A
nti-i
cing
Age
nts;
3)
Equi
pmen
t Cos
ts a
re b
ased
on
$60
per h
our p
er u
nit;
4) L
abor
Cos
ts a
re b
ased
on
each
Cou
nty'
s av
erag
e la
bor r
ate;
5) T
otal
Sal
t Ava
ilabl
e =
salt
in s
heds
as
of M
ay p
lus
early
fill,
pl
us s
easo
nal f
ill, p
lus
vend
or re
serv
e av
aila
ble.
From
Win
ter S
torm
Rep
orts
, 201
6-20
17
Reg
ion
NE
Cou
nty
Lane
Mile
sSe
verit
yIn
dex
Snow
Amou
nt
(inch
es)
Anti-
Icin
gSt
orm
sIn
ci-
dent
Free
z. R
ain
Eve
nts
Tota
l Sa
lt Av
ail.
(tons
)
Tota
l Sa
lt U
sed
(tons
)
Tota
l Sa
lt R
emai
n.
(tons
)
Tota
l Sa
nd
Use
d (C
Y)
Tota
l R
eg.
Hou
rs
Tota
l O
T H
ours
Mat
'lEq
uip
Labo
rTo
tal
Estim
ated
To
tal C
ost
to D
ate
Salt
Use
d pe
r LM
(to
ns)
Even
ts th
is S
easo
nEs
timat
ed C
ost P
er L
ane
Mile
Salt
per
LM p
er
Seve
rity
Inde
x
Tota
l Th
aw-
Rox
(to
ns)
Tota
l C
lear
-La
ne
(tons
)BR
OW
N89
0.4
66.4
164
.117
227
715
,238
12,7
092,
529
070
89.0
4963
.0$8
25$8
93$6
12$2
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$2,0
74,1
1314
.30.
210
0
FON
D D
U L
AC60
5.3
71.1
955
.011
1326
410
,846
8,11
82,
728
521
69.0
3286
.0$9
28$4
77$4
84$1
,889
$1,1
43,1
4713
.40.
190
0
WIN
NEB
AGO
626.
5666
.88
46.0
618
2311
12,5
639,
081
3,48
20
2830
.027
06.0
$928
$482
$442
$1,8
52$1
,160
,630
14.5
0.22
00
SHEB
OYG
AN52
7.86
81.7
257
.113
1827
911
,135
8,72
12,
414
123
65.0
1215
.0$1
,134
$393
$322
$1,8
49$9
76,1
8216
.50.
200
0
MAN
ITO
WO
C42
6.01
78.9
858
.522
1720
108,
790
6,16
52,
625
026
54.0
1316
.0$8
96$5
59$3
90$1
,845
$785
,960
14.5
0.18
00
DO
OR
271.
884
.58
63.9
1418
2412
4,72
93,
541
1,18
82
616.
011
88.0
$903
$399
$409
$1,7
11$4
61,7
0013
.00.
150
0
MAR
INET
TE43
6.66
125.
0068
.426
3448
207,
382
5,55
31,
829
5237
88.0
117.
0$8
49$4
58$3
68$1
,675
$731
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12.7
0.10
00
CAL
UM
ET20
1.71
95.0
058
.213
2032
122,
907
1,80
41,
103
013
89.0
347.
8$5
46$4
80$3
38$1
,364
$275
,227
8.9
0.09
00
OC
ON
TO46
8.9
92.1
458
.913
2425
167,
246
5,01
42,
232
014
97.0
1404
.0$6
95$3
61$2
95$1
,352
$633
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10.7
0.12
00
OU
TAG
AMIE
538.
6372
.91
56.7
221
159
10,2
344,
941
5,29
38
2940
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72.0
$567
$397
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$1,3
49$7
26,5
199.
20.
130
0
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EE11
1.35
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1,31
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245
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054
.0$7
01$2
76$2
08$1
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$131
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11.8
0.18
00
Reg
ion
Tota
lR
egio
n Av
erag
e81
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92,8
4566
,960
25,8
8511
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27.3
1651
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71$3
87$1
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00,4
66$8
27,3
1512
.759
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440
6,08
72,
353
10
----
----
----
----
----
----
--0.
160 0
0 0
Page
2 o
f 6W
edne
sday
, Nov
embe
r 15,
201
7Fi
nal t
otal
s as
of
119Tabl
e A
.1 -
Stor
m R
epor
t Sum
mar
yN
otes
: 1) C
osts
sho
wn
in ta
ble
are
estim
ated
and
do
not i
nclu
de th
e 4.
47%
Adm
inis
trat
ive
Cos
ts; 2
) Mat
eria
l Cos
ts in
clud
es S
alt,
Sand
, and
oth
er D
eici
ng a
nd A
nti-i
cing
Age
nts;
3)
Equi
pmen
t Cos
ts a
re b
ased
on
$60
per h
our p
er u
nit;
4) L
abor
Cos
ts a
re b
ased
on
each
Cou
nty'
s av
erag
e la
bor r
ate;
5) T
otal
Sal
t Ava
ilabl
e =
salt
in s
heds
as
of M
ay p
lus
early
fill,
pl
us s
easo
nal f
ill, p
lus
vend
or re
serv
e av
aila
ble.
From
Win
ter S
torm
Rep
orts
, 201
6-20
17
Reg
ion
NW
Cou
nty
Lane
Mile
sSe
verit
yIn
dex
Snow
Amou
nt
(inch
es)
Anti-
Icin
gSt
orm
sIn
ci-
dent
Free
z. R
ain
Eve
nts
Tota
l Sa
lt Av
ail.
(tons
)
Tota
l Sa
lt U
sed
(tons
)
Tota
l Sa
lt R
emai
n.
(tons
)
Tota
l Sa
nd
Use
d (C
Y)
Tota
l R
eg.
Hou
rs
Tota
l O
T H
ours
Mat
'lEq
uip
Labo
rTo
tal
Estim
ated
To
tal C
ost
to D
ate
Salt
Use
d pe
r LM
(to
ns)
Even
ts th
is S
easo
nEs
timat
ed C
ost P
er L
ane
Mile
Salt
per
LM p
er
Seve
rity
Inde
x
Tota
l Th
aw-
Rox
(to
ns)
Tota
l C
lear
-La
ne
(tons
)JA
CKS
ON
515.
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020
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IRE
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00
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NN
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0$1
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UG
LAS
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10
SAIN
T C
RO
IX64
5.34
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259
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320
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991,
834
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$327
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18.9
0.23
00
TAYL
OR
233.
911
0.61
66.5
1833
2415
4,39
43,
233
1,16
130
1178
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4.0
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70$4
45$3
44$1
,959
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13.8
0.12
00
TREM
PEAL
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442.
4881
.87
64.1
423
1113
7,36
46,
902
462
014
11.0
1801
.0$1
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$338
$355
$1,8
21$8
05,7
3415
.60.
190
0
CLA
RK
402.
5610
3.14
83.2
930
2316
7,20
75,
083
2,12
40
1655
.013
26.0
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$431
$349
$1,7
56$7
06,8
6112
.60.
120
0
WAS
HBU
RN
372.
1410
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Page
3 o
f 6W
edne
sday
, Nov
embe
r 15,
201
7Fi
nal t
otal
s as
of
120 Tabl
e A
.1 -
Stor
m R
epor
t Sum
mar
yN
otes
: 1) C
osts
sho
wn
in ta
ble
are
estim
ated
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do
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inis
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ive
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ts; 2
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eria
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, and
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ng a
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nti-i
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ts a
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ased
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ts a
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ased
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nty'
s av
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e la
bor r
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otal
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ay p
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us s
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nal f
ill, p
lus
vend
or re
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Win
ter S
torm
Rep
orts
, 201
6-20
17
Reg
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verit
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Page
4 o
f 6W
edne
sday
, Nov
embe
r 15,
201
7Fi
nal t
otal
s as
of
121Tabl
e A
.1 -
Stor
m R
epor
t Sum
mar
yN
otes
: 1) C
osts
sho
wn
in ta
ble
are
estim
ated
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de th
e 4.
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inis
trat
ive
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ts; 2
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eria
l Cos
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, and
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eici
ng a
nd A
nti-i
cing
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nts;
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t Cos
ts a
re b
ased
on
$60
per h
our p
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nit;
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ased
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nty'
s av
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e la
bor r
ate;
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otal
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t Ava
ilabl
e =
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ay p
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us s
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vend
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ter S
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Rep
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, 201
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Page
5 o
f 6W
edne
sday
, Nov
embe
r 15,
201
7Fi
nal t
otal
s as
of
122 Tabl
e A
.1 -
Stor
m R
epor
t Sum
mar
yN
otes
: 1) C
osts
sho
wn
in ta
ble
are
estim
ated
and
do
not i
nclu
de th
e 4.
47%
Adm
inis
trat
ive
Cos
ts; 2
) Mat
eria
l Cos
ts in
clud
es S
alt,
Sand
, and
oth
er D
eici
ng a
nd A
nti-i
cing
Age
nts;
3)
Equi
pmen
t Cos
ts a
re b
ased
on
$60
per h
our p
er u
nit;
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abor
Cos
ts a
re b
ased
on
each
Cou
nty'
s av
erag
e la
bor r
ate;
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otal
Sal
t Ava
ilabl
e =
salt
in s
heds
as
of M
ay p
lus
early
fill,
pl
us s
easo
nal f
ill, p
lus
vend
or re
serv
e av
aila
ble.
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Win
ter S
torm
Rep
orts
, 201
6-20
17
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es)
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orm
sIn
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dent
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z. R
ain
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nts
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l Sa
lt Av
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(tons
)
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l Sa
lt U
sed
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)
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l Sa
lt R
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n.
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l Sa
nd
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d (C
Y)
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l R
eg.
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rs
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l O
T H
ours
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'lEq
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rTo
tal
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ated
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tal C
ost
to D
ate
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d pe
r LM
(to
ns)
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ts th
is S
easo
nEs
timat
ed C
ost P
er L
ane
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per
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er
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rity
Inde
x
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l Th
aw-
Rox
(to
ns)
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l C
lear
-La
ne
(tons
)
Page
6 o
f 6W
edne
sday
, Nov
embe
r 15,
201
7Fi
nal t
otal
s as
of
123
5/22/2017
Michael J. Adams
WEATHER FORECAST SERVICES EVALUATION 2017
WMS
124
This document contains the verification study of forecasts provided by Iteris to Wisconsin DOT for the winter of 2016-17. It is a statistical analysis of the accuracy of those forecasts, using a methodology developed over 15 years ago and refined several times since then.
125
Executive Summary
Introduction
In 2016-17, the Wisconsin Department of Transportation (WisDOT) continued using weather and pavement forecast information provided by Iteris. The information is received through the Maintenance Decision Support System (MDSS) and through alerts received via text or voice messages. In order to assess the quality of these weather and pavement temperature forecasts provided to WisDOT and the county highway departments who provide winter maintenance on the state trunk highway system, the WisDOT Road Weather Information System (RWIS) Program Manager performed a verification study on these forecasts. The primary aim of this study is to uncover any potential problems in forecast accuracy, with the ultimate goal being to use the findings to improve the quality of weather and pavement temperature forecast information provided by Iteris or any other provider of forecast information. All information presented in this report is for forecasts provided by Iteris since 2005-06, first via a web site and, after 2009-10, MDSS.
Verification Procedures
Forecasts for eight locations were examined: Madison, Milwaukee, Green Bay, Wausau, La Crosse, Eau Claire, and Rhinelander, and Rice Lake. The time period covered by the verification study was December 1, 2016 through March 31, 2017. Four specific criteria were examined: snow, freezing precipitation, wind speed, and pavement temperature. Due to road construction at the La Crosse RWIS site, no pavement temperature verification was performed there. For the first two criteria, the verification methodology is based on a paper presented by John Thornes at the 1998 Standing International Road Weather Commission (SIRWEC) conference. It is based on common meteorological forecast verification techniques. The basis of the method is to choose two time periods (in our case 0 to 6 hours and 6 to 24 hours after forecast issuance) during the forecasts and see if the particular criterion was forecast to occur and whether it actually occurred during the periods being examined. In other words, was snow forecast to occur and did it occur? Two-by-two contingency tables are then constructed. A number of statistics were calculated, each of which provides a different piece of intelligence. Goal scores for each statistic have also been established. For pavement temperature and wind speed, the forecast values 3 and 9 hours after forecast issuance times were compared to the actual values and error statistics were computed. In addition, the timing error for the start and stop of precipitation and the lead time provided by the winter storm alert service were also examined. Results of this and previous studies are made available to Iteris or whoever the current forecast provider is. It is expected that Iteris will use the results of these studies to continue to improve upon their weather support to WisDOT and the county highway departments.
126
Verification Results
• Precipitation forecasts. Accuracy improved in the both the short and long term forecasts. The False Alarm Rate, which had been an issue the past two winters, improved this season, though there was a corresponding decline in the Probability of Detection.
• Timing error. Timing errors for both the start and end times of snow continue to be superb. The average timing error for the start of storms in the short term forecasts was 1 hour, 12 minutes, 15 minutes better than last year. This was the best result ever recorded.
• Pavement temperature. Performance declined and failed to meet goal scores. Forecasts exhibited somewhat of a cold bias.
127
• Winds. Wind forecast accuracy continued to be excellent and remained steady compared to last year. The only issue was a strong tendency to over forecast speeds near the 15 mph threshold.
• Winter storm alerts. Performance was about the same as the previous winter, and again failed to meet expectations. For the winter, only 59 percent of events were preceded by an alert issued more than two hours in advance, as required by WisDOT’s contract with Iteris.
Legend:Met: warning issued more than 2 hours before event onset
Before: warning issued before event onsetAfter: warning issued after event onset
Never: no warning ever issued for event
128
• Action Items
Iteris must investigate the cause of the strong tendency to over-forecast wind speeds near the 15 mph threshold. Iteris must investigate improvements to the MetAlert warning system to ensure that more events are preceded by alerts meeting the required 2-hour lead time.
129
Cou
nty
Goo
dFa
irPo
orTi
mes
Use
dTi
mes
N
ot
Use
d
% o
f Ev
ents
Use
d
Salt
Use
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ns)
Snow
A
mou
nt
(inch
es)
Seve
rity
Inde
xN
o. o
f A
nti-I
ce
App
l.
No.
of
Stor
ms
Even
ts
No.
of
Inci
dent
s R
epor
ted
No.
of
Free
zing
Rai
ns
Tabl
e A
-2. W
eath
er F
orec
astin
g Se
rvic
e U
sage
Salt
per
LM p
er
Seve
rity
Inde
x
Reg
ion
From
Win
ter S
torm
Rep
orts
, 201
6-20
17
MAR
QU
ETTE
112
619
386
%4,
541
40.5
58.1
616
146
0.32
NC
MEN
OM
INEE
66
214
1058
%1,
558
58.7
77.7
024
254
0.22
ON
EID
A0
361
370
100%
8,24
786
.310
7.7
433
67
0.19
SHAW
ANO
313
117
1849
%7,
968
72.9
93.7
1025
307
0.16
WAU
PAC
A0
60
621
22%
7,70
251
.988
.43
2423
70.
16
ADAM
S22
180
403
93%
3,37
445
.811
1.6
2221
825
0.16
VILA
S1
491
515
91%
6,08
310
8.5
127.
79
4721
100.
16
WO
OD
037
239
010
0%6,
695
72.7
107.
88
3117
110.
15
FLO
REN
CE
435
1554
010
0%2,
627
91.6
132.
713
4124
100.
14
IRO
N24
84
3614
72%
5,06
313
1.9
145.
20
5018
60.
14
FOR
EST
246
535
685
%4,
434
90.3
109.
03
388
50.
13
GR
EEN
LAK
E6
122
201
95%
1,59
942
.079
.04
1715
100.
13
WAU
SHAR
A7
150
223
88%
3,61
252
.686
.62
2319
80.
12
MAR
ATH
ON
716
427
2750
%11
,158
64.2
112.
623
3131
60.
11
POR
TAG
E2
1225
390
100%
7,41
561
.711
2.0
336
229
0.11
LAN
GLA
DE
836
549
591
%3,
533
72.3
106.
621
3332
60.
11
LIN
CO
LN0
00
050
0%4,
887
86.0
125.
618
3221
120.
10
PRIC
E2
610
630
100%
4,20
312
6.0
142.
18
559
100.
09
6.5
21.0
4.1
31.6
9.2
5,26
1.1
75.3
106.
98.
732
.119
.18.
80.
15R
egio
n A
vera
ge76
.7%
Wed
nesd
ay, J
une
28, 2
017
Page
1 o
f 6Fi
nal t
otal
s as
of
130
Cou
nty
Goo
dFa
irPo
orTi
mes
Use
dTi
mes
N
ot
Use
d
% o
f Ev
ents
Use
d
Salt
Use
d (to
ns)
Snow
A
mou
nt
(inch
es)
Seve
rity
Inde
xN
o. o
f A
nti-I
ce
App
l.
No.
of
Stor
ms
Even
ts
No.
of
Inci
dent
s R
epor
ted
No.
of
Free
zing
Rai
ns
Tabl
e A
-2. W
eath
er F
orec
astin
g Se
rvic
e U
sage
Salt
per
LM p
er
Seve
rity
Inde
x
Reg
ion
From
Win
ter S
torm
Rep
orts
, 201
6-20
17
WIN
NEB
AGO
218
323
196
%9,
081
46.0
66.9
618
233
0.22
NE
BRO
WN
118
120
1951
%12
,709
64.1
66.4
1722
71
0.21
SHEB
OYG
AN24
30
274
87%
8,72
157
.181
.713
1827
60.
20
FON
D D
U L
AC1
111
1311
54%
8,11
855
.071
.211
1326
10.
19
KEW
AU
NEE
016
016
194
%1,
313
65.5
64.0
116
181
0.18
MAN
ITO
WO
C6
172
2514
64%
6,16
558
.579
.022
1720
70.
18
DO
OR
1711
129
391
%3,
541
63.9
84.6
1418
246
0.15
OU
TAG
AMIE
414
422
196
%4,
941
56.7
72.9
221
153
0.13
OC
ON
TO4
203
2710
73%
5,01
458
.992
.113
2425
90.
12
MAR
INET
TE33
00
3327
55%
5,55
368
.412
5.0
2634
4810
0.10
CA
LUM
ET
293
032
197
%1,
804
58.2
95.0
1320
329
0.09
11.9
11.0
1.4
24.3
8.4
6,08
7.3
59.3
81.7
12.5
20.1
24.1
5.1
0.16
Reg
ion
Ave
rage
78.0
%
Wed
nesd
ay, J
une
28, 2
017
Page
2 o
f 6Fi
nal t
otal
s as
of
131
Cou
nty
Goo
dFa
irPo
orTi
mes
Use
dTi
mes
N
ot
Use
d
% o
f Ev
ents
Use
d
Salt
Use
d (to
ns)
Snow
A
mou
nt
(inch
es)
Seve
rity
Inde
xN
o. o
f A
nti-I
ce
App
l.
No.
of
Stor
ms
Even
ts
No.
of
Inci
dent
s R
epor
ted
No.
of
Free
zing
Rai
ns
Tabl
e A
-2. W
eath
er F
orec
astin
g Se
rvic
e U
sage
Salt
per
LM p
er
Seve
rity
Inde
x
Reg
ion
From
Win
ter S
torm
Rep
orts
, 201
6-20
17
EAU
CLA
IRE
615
223
010
0%11
,059
58.1
64.1
122
102
0.32
NW
JAC
KSO
N0
00
020
0%8,
531
53.5
67.4
020
163
0.25
SAI
NT
CR
OIX
013
1629
391
%12
,199
59.2
83.6
032
08
0.23
DU
NN
1315
230
488
%10
,075
63.3
96.2
529
186
0.20
CH
IPPE
WA
02
13
2511
%12
,230
85.9
96.5
325
226
0.19
TRE
MP
EA
LEA
188
127
010
0%6,
902
64.1
81.9
423
116
0.19
WA
SH
BU
RN
720
1138
295
%6,
058
46.2
101.
77
3311
110.
16
PIER
CE
1813
031
010
0%4,
340
59.1
90.8
526
149
0.13
BUR
NET
T0
333
360
100%
2,98
645
.497
.80
3611
70.
13
RU
SK0
00
036
0%2,
414
60.4
90.4
036
157
0.13
TAYL
OR
337
040
1178
%3,
233
66.5
110.
618
3324
90.
12
CLA
RK
03
2629
1074
%5,
083
83.2
103.
19
3023
40.
12
BAYF
IELD
00
00
440%
4,97
696
.014
3.7
143
401
0.11
POLK
022
224
2450
%5,
244
55.1
126.
410
3821
150.
11
SAW
YER
00
00
360%
4,27
658
.411
2.2
036
255
0.10
BUFF
ALO
270
027
1073
%3,
188
69.3
98.2
1027
243
0.10
DO
UG
LAS
1228
545
1378
%7,
713
84.7
168.
93
5527
130.
10
BAR
RO
N0
340
342
94%
3,97
963
.111
5.1
234
277
0.08
ASH
LAN
D2
500
520
100%
2,69
111
9.6
145.
03
4920
50.
08
PEPI
N22
90
314
89%
698
58.3
93.2
1322
188
0.07
7.9
13.6
3.5
25.0
12.2
5,89
3.8
67.5
104.
34.
732
.518
.96.
80.
15R
egio
n A
vera
ge66
.0%
Wed
nesd
ay, J
une
28, 2
017
Page
3 o
f 6Fi
nal t
otal
s as
of
132
Cou
nty
Goo
dFa
irPo
orTi
mes
Use
dTi
mes
N
ot
Use
d
% o
f Ev
ents
Use
d
Salt
Use
d (to
ns)
Snow
A
mou
nt
(inch
es)
Seve
rity
Inde
xN
o. o
f A
nti-I
ce
App
l.
No.
of
Stor
ms
Even
ts
No.
of
Inci
dent
s R
epor
ted
No.
of
Free
zing
Rai
ns
Tabl
e A
-2. W
eath
er F
orec
astin
g Se
rvic
e U
sage
Salt
per
LM p
er
Seve
rity
Inde
x
Reg
ion
From
Win
ter S
torm
Rep
orts
, 201
6-20
17
WAU
KESH
A21
10
2216
58%
20,5
9644
.254
.721
172
50.
35SE
OZA
UKE
E8
161
251
96%
6,98
553
.066
.97
1912
40.
34
WAL
WO
RTH
136
221
1068
%12
,878
36.4
65.5
1318
254
0.28
WA
SH
ING
TON
124
126
010
0%12
,212
54.4
78.5
818
164
0.25
KEN
OS
HA
00
00
460%
10,5
2414
.866
.223
230
70.
24
MIL
WAU
KEE
142
117
481
%27
,642
36.7
62.7
615
27
0.23
RAC
INE
017
118
386
%7,
950
50.9
65.1
318
144
0.18
8.1
9.4
0.9
18.4
11.4
14,1
12.4
41.5
65.7
11.6
18.3
10.1
5.0
0.27
Reg
ion
Ave
rage
69.8
%
Wed
nesd
ay, J
une
28, 2
017
Page
4 o
f 6Fi
nal t
otal
s as
of
133
Cou
nty
Goo
dFa
irPo
orTi
mes
Use
dTi
mes
N
ot
Use
d
% o
f Ev
ents
Use
d
Salt
Use
d (to
ns)
Snow
A
mou
nt
(inch
es)
Seve
rity
Inde
xN
o. o
f A
nti-I
ce
App
l.
No.
of
Stor
ms
Even
ts
No.
of
Inci
dent
s R
epor
ted
No.
of
Free
zing
Rai
ns
Tabl
e A
-2. W
eath
er F
orec
astin
g Se
rvic
e U
sage
Salt
per
LM p
er
Seve
rity
Inde
x
Reg
ion
From
Win
ter S
torm
Rep
orts
, 201
6-20
17
DO
DG
E0
00
021
0%13
,465
49.1
63.8
714
115
0.33
SW
DAN
E4
122
188
69%
30,4
0230
.372
.95
215
40.
27
LA C
RO
SSE
114
217
010
0%6,
140
58.0
46.4
314
41
0.26
JEFF
ER
SON
025
429
878
%9,
057
34.2
63.7
1819
136
0.26
CO
LUM
BIA
213
318
1850
%18
,933
57.0
96.4
2115
263
0.25
RO
CK
00
00
180%
7,73
036
.848
.01
1712
40.
23
JUN
EAU
89
118
1162
%8,
215
59.5
76.4
920
204
0.22
MO
NR
OE
34
18
2922
%11
,241
60.6
92.3
829
75
0.19
SAU
K8
185
3110
76%
9,83
453
.795
.721
2029
90.
18
IOW
A2
147
2311
68%
6,79
936
.484
.412
2221
70.
17
GR
ANT
167
326
010
0%7,
594
32.6
77.4
818
264
0.16
VER
NO
N7
80
158
65%
5,50
741
.979
.19
1421
50.
15
RIC
HLA
ND
020
626
390
%3,
359
34.1
82.2
1118
2110
0.12
CR
AWFO
RD
126
229
197
%4,
291
44.4
88.8
624
285
0.12
LAFA
YE
TTE
49
316
673
%2,
249
24.4
63.0
913
177
0.12
GR
EEN
175
123
1070
%2,
139
34.2
62.5
1419
125
0.11
4.6
11.5
2.5
18.6
10.1
9,18
4.7
43.0
74.6
10.1
18.6
17.1
5.3
0.20
Reg
ion
Ave
rage
63.7
%
Wed
nesd
ay, J
une
28, 2
017
Page
5 o
f 6Fi
nal t
otal
s as
of
134
Cou
nty
Goo
dFa
irPo
orTi
mes
Use
dTi
mes
N
ot
Use
d
% o
f Ev
ents
Use
d
Salt
Use
d (to
ns)
Snow
A
mou
nt
(inch
es)
Seve
rity
Inde
xN
o. o
f A
nti-I
ce
App
l.
No.
of
Stor
ms
Even
ts
No.
of
Inci
dent
s R
epor
ted
No.
of
Free
zing
Rai
ns
Tabl
e A
-2. W
eath
er F
orec
astin
g Se
rvic
e U
sage
Salt
per
LM p
er
Seve
rity
Inde
x
Reg
ion
From
Win
ter S
torm
Rep
orts
, 201
6-20
17
7.4
14.2
2.8
24.4
10.3
7,29
5.5
60.2
91.1
8.8
26.0
18.5
6.5
0.17
Stat
ewid
e A
vera
ge70
.4%
Wed
nesd
ay, J
une
28, 2
017
Page
6 o
f 6Fi
nal t
otal
s as
of
135
Tabl
e A
.3. A
nti-i
cing
Det
ails
From
Win
ter S
torm
Rep
orts
, 201
6-20
17
Cou
nty
$ M
at'l
$ Eq
uip
$ La
bor
$ To
tal
Estim
ated
Cos
tsA
nti-
Icin
gap
plic
.
Wha
t wea
ther
pre
dict
ion
caus
ed y
ou to
ant
i-ice
? O
r did
you
do
anti-
icin
g on
a ro
utin
e sc
hedu
le?
Wet
Sno
wD
ry S
now
Frz
Rai
nSl
eet
Fros
tR
outin
e
Reg
ion
WA
US
HA
RA
096
059
71,
557
20
00
01
1N
C
FOR
ES
T0
540
294
834
33
00
10
0
WA
UP
ACA
01,
260
941
2,20
13
01
00
30
POR
TAG
E0
2,40
01,
534
3,93
43
10
00
20
GR
EE
N L
AKE
01,
560
1,04
32,
603
43
04
10
0
ON
EID
A0
3,42
02,
364
5,78
44
20
30
10
MA
RQ
UE
TTE
03,
840
3,20
97,
049
61
11
01
3
PR
ICE
01,
980
1,28
93,
269
81
01
07
0
WO
OD
02,
400
1,68
24,
082
85
03
06
0
VIL
AS
06,
120
4,13
810
,258
94
03
00
5
SH
AW
ANO
04,
440
2,44
86,
888
102
13
00
6
FLO
RE
NC
E0
4,86
03,
116
7,97
613
90
64
30
LIN
CO
LN0
11,5
807,
587
19,1
6718
150
114
00
LAN
GLA
DE
06,
120
5,30
511
,425
2113
24
02
5
AD
AM
S8,
050
4,98
03,
921
16,9
5122
140
173
03
MA
RA
THO
N0
19,8
6016
,159
36,0
1923
00
00
221
Wed
nesd
ay, J
une
28, 2
017
Page
1 o
f 8Fi
nal t
otal
s as
of
136
Tabl
e A
.3. A
nti-i
cing
Det
ails
From
Win
ter S
torm
Rep
orts
, 201
6-20
17
Cou
nty
$ M
at'l
$ Eq
uip
$ La
bor
$ To
tal
Estim
ated
Cos
tsA
nti-
Icin
gap
plic
.
Wha
t wea
ther
pre
dict
ion
caus
ed y
ou to
ant
i-ice
? O
r did
you
do
anti-
icin
g on
a ro
utin
e sc
hedu
le?
Wet
Sno
wD
ry S
now
Frz
Rai
nSl
eet
Fros
tR
outin
e
Reg
ion
Reg
ion
Tota
lR
egio
n Av
erag
e8,
050
503
76,3
20
4,77
0
55,6
27
3,47
7
139,
997
8,75
0
157 10
735
5613
2844
----
----
----
Wed
nesd
ay, J
une
28, 2
017
Page
2 o
f 8Fi
nal t
otal
s as
of
137
Tabl
e A
.3. A
nti-i
cing
Det
ails
From
Win
ter S
torm
Rep
orts
, 201
6-20
17
Cou
nty
$ M
at'l
$ Eq
uip
$ La
bor
$ To
tal
Estim
ated
Cos
tsA
nti-
Icin
gap
plic
.
Wha
t wea
ther
pre
dict
ion
caus
ed y
ou to
ant
i-ice
? O
r did
you
do
anti-
icin
g on
a ro
utin
e sc
hedu
le?
Wet
Sno
wD
ry S
now
Frz
Rai
nSl
eet
Fros
tR
outin
e
Reg
ion
KE
WA
UN
EE
024
017
041
01
00
00
01
NE
OU
TAG
AMIE
024
023
547
52
00
00
20
WIN
NE
BA
GO
03,
360
4,70
68,
066
60
12
16
0
FON
D D
U L
AC
011
,280
9,85
621
,136
110
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2010
2084
----
----
----
Wed
nesd
ay, J
une
28, 2
017
Page
3 o
f 8Fi
nal t
otal
s as
of
138
Tabl
e A
.3. A
nti-i
cing
Det
ails
From
Win
ter S
torm
Rep
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, 201
6-20
17
Cou
nty
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----
----
----
Wed
nesd
ay, J
une
28, 2
017
Page
4 o
f 8Fi
nal t
otal
s as
of
139
Tabl
e A
.3. A
nti-i
cing
Det
ails
From
Win
ter S
torm
Rep
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, 201
6-20
17
Cou
nty
$ M
at'l
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uip
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bor
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dict
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g on
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Sno
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now
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----
----
----
Wed
nesd
ay, J
une
28, 2
017
Page
5 o
f 8Fi
nal t
otal
s as
of
140
Tabl
e A
.3. A
nti-i
cing
Det
ails
From
Win
ter S
torm
Rep
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, 201
6-20
17
Cou
nty
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at'l
$ Eq
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bor
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tal
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tsA
nti-
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gap
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.
Wha
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dict
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caus
ed y
ou to
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? O
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you
do
anti-
icin
g on
a ro
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hedu
le?
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now
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Wed
nesd
ay, J
une
28, 2
017
Page
6 o
f 8Fi
nal t
otal
s as
of
141
Tabl
e A
.3. A
nti-i
cing
Det
ails
From
Win
ter S
torm
Rep
orts
, 201
6-20
17
Cou
nty
$ M
at'l
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uip
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bor
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tal
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tsA
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gap
plic
.
Wha
t wea
ther
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dict
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caus
ed y
ou to
ant
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? O
r did
you
do
anti-
icin
g on
a ro
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e sc
hedu
le?
Wet
Sno
wD
ry S
now
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Rai
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Tota
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----
----
----
Wed
nesd
ay, J
une
28, 2
017
Page
7 o
f 8Fi
nal t
otal
s as
of
142
Tabl
e A
.3. A
nti-i
cing
Det
ails
From
Win
ter S
torm
Rep
orts
, 201
6-20
17
Cou
nty
$ M
at'l
$ Eq
uip
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bor
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tal
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tsA
nti-
Icin
gap
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.
Wha
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dict
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caus
ed y
ou to
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? O
r did
you
do
anti-
icin
g on
a ro
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hedu
le?
Wet
Sno
wD
ry S
now
Frz
Rai
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Fros
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Reg
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Stat
ewid
e To
tal
632
146
32,7
3336
8,58
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270
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122
4311
330
8
Wed
nesd
ay, J
une
28, 2
017
Page
8 o
f 8Fi
nal t
otal
s as
of
143
Reg
ion
Cou
nty
CaC
l2
(gal
)N
aCl
Brin
e (g
al)
MgC
l2(g
al)
IB_M
80 (g
al)
Free
zeG
uard
(gal
)
Tabl
e A
.4. A
nnua
l Ant
i-ici
ng A
gent
Usa
ge
CaC
l2D
OW
(gal
)
Arc
tic
Cle
ar
Gol
d
MC
95(g
al)
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iber
M
1000
(gal
)
Cal
iber
M
2000
(gal
)
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Mel
t 6
4(g
al)
Geo
-M
elt
(gal
)
Ice
Bite
55
(gal
)
From
Win
ter S
torm
Rep
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, 201
6-20
17
AM
P(g
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eat
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Reg
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Tota
l0
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Wed
nesd
ay, J
une
28, 2
017
Page
1 o
f 6Fi
nal t
otal
s as
of
144
Reg
ion
Cou
nty
CaC
l2
(gal
)N
aCl
Brin
e (g
al)
MgC
l2(g
al)
IB_M
80 (g
al)
Free
zeG
uard
(gal
)
Tabl
e A
.4. A
nnua
l Ant
i-ici
ng A
gent
Usa
ge
CaC
l2D
OW
(gal
)
Arc
tic
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ar
Gol
d
MC
95(g
al)
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iber
M
1000
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)
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iber
M
2000
(gal
)
Bio
Mel
t 6
4(g
al)
Geo
-M
elt
(gal
)
Ice
Bite
55
(gal
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From
Win
ter S
torm
Rep
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, 201
6-20
17
AM
P(g
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Bee
t H
eat
(gal
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NE
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Wed
nesd
ay, J
une
28, 2
017
Page
2 o
f 6Fi
nal t
otal
s as
of
145
Reg
ion
Cou
nty
CaC
l2
(gal
)N
aCl
Brin
e (g
al)
MgC
l2(g
al)
IB_M
80 (g
al)
Free
zeG
uard
(gal
)
Tabl
e A
.4. A
nnua
l Ant
i-ici
ng A
gent
Usa
ge
CaC
l2D
OW
(gal
)
Arc
tic
Cle
ar
Gol
d
MC
95(g
al)
Cal
iber
M
1000
(gal
)
Cal
iber
M
2000
(gal
)
Bio
Mel
t 6
4(g
al)
Geo
-M
elt
(gal
)
Ice
Bite
55
(gal
)
From
Win
ter S
torm
Rep
orts
, 201
6-20
17
AM
P(g
al)
Bee
t H
eat
(gal
)
NW
AS
HLA
ND
05,
893
00
622
00
00
00
00
00
BA
RR
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045
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00
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00
00
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FFA
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NET
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00
00
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140
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UG
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01,
350
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300
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00
00
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810
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0
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600
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100
00
00
00
00
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TRE
MP
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LEA
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12,0
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100
00
00
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SH
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428
00
00
00
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00
00
0
Reg
ion
Tota
l80
267
,483
010
092
20
00
00
00
00
0
Wed
nesd
ay, J
une
28, 2
017
Page
3 o
f 6Fi
nal t
otal
s as
of
146
Reg
ion
Cou
nty
CaC
l2
(gal
)N
aCl
Brin
e (g
al)
MgC
l2(g
al)
IB_M
80 (g
al)
Free
zeG
uard
(gal
)
Tabl
e A
.4. A
nnua
l Ant
i-ici
ng A
gent
Usa
ge
CaC
l2D
OW
(gal
)
Arc
tic
Cle
ar
Gol
d
MC
95(g
al)
Cal
iber
M
1000
(gal
)
Cal
iber
M
2000
(gal
)
Bio
Mel
t 6
4(g
al)
Geo
-M
elt
(gal
)
Ice
Bite
55
(gal
)
From
Win
ter S
torm
Rep
orts
, 201
6-20
17
AM
P(g
al)
Bee
t H
eat
(gal
)
SE
KE
NO
SH
A0
03,
805
00
00
00
00
00
00
MIL
WA
UK
EE
029
,000
00
00
00
00
00
00
0
OZA
UK
EE
1,35
09,
700
00
00
00
00
00
00
0
RA
CIN
E0
1,90
00
00
00
00
00
00
00
WA
LWO
RTH
026
,050
00
00
00
00
00
00
0
WA
SH
ING
TON
03,
300
00
00
00
00
00
00
0
WAU
KESH
A8,
191
141,
473
00
00
00
00
016
,390
00
0
Reg
ion
Tota
l9,
541
211,
423
3,80
50
00
00
00
016
,390
00
0
Wed
nesd
ay, J
une
28, 2
017
Page
4 o
f 6Fi
nal t
otal
s as
of
147
Reg
ion
Cou
nty
CaC
l2
(gal
)N
aCl
Brin
e (g
al)
MgC
l2(g
al)
IB_M
80 (g
al)
Free
zeG
uard
(gal
)
Tabl
e A
.4. A
nnua
l Ant
i-ici
ng A
gent
Usa
ge
CaC
l2D
OW
(gal
)
Arc
tic
Cle
ar
Gol
d
MC
95(g
al)
Cal
iber
M
1000
(gal
)
Cal
iber
M
2000
(gal
)
Bio
Mel
t 6
4(g
al)
Geo
-M
elt
(gal
)
Ice
Bite
55
(gal
)
From
Win
ter S
torm
Rep
orts
, 201
6-20
17
AM
P(g
al)
Bee
t H
eat
(gal
)
SW
CO
LUM
BIA
013
0,40
00
00
00
00
00
00
00
CR
AW
FOR
D0
16,5
000
00
00
00
00
00
00
DA
NE
030
,615
00
00
00
00
00
00
0
DO
DG
E0
37,3
180
00
00
00
00
00
3,70
00
GR
AN
T0
50,1
300
00
00
00
00
00
3,25
00
GR
EE
N0
8,37
50
00
00
00
00
00
00
IOW
A0
49,8
420
00
00
00
00
00
5,41
80
JEFF
ER
SO
N0
18,4
120
00
00
00
00
00
560
JUN
EA
U0
93,0
700
07,
500
00
00
00
00
00
LA C
RO
SS
E0
30,2
230
00
00
00
00
00
00
LAFA
YE
TTE
07,
950
00
00
00
00
00
00
0
MO
NR
OE
033
,155
00
00
00
00
00
00
0
RIC
HLA
ND
012
,432
00
00
00
00
00
00
0
RO
CK
02,
400
00
00
00
00
00
00
0
SA
UK
024
,555
00
00
00
00
019
00
00
VE
RN
ON
023
,725
00
00
00
00
00
00
0
Reg
ion
Tota
l0
569,
102
00
7,50
00
00
00
019
00
12,4
240
Wed
nesd
ay, J
une
28, 2
017
Page
5 o
f 6Fi
nal t
otal
s as
of
148
Reg
ion
Cou
nty
CaC
l2
(gal
)N
aCl
Brin
e (g
al)
MgC
l2(g
al)
IB_M
80 (g
al)
Free
zeG
uard
(gal
)
Tabl
e A
.4. A
nnua
l Ant
i-ici
ng A
gent
Usa
ge
CaC
l2D
OW
(gal
)
Arc
tic
Cle
ar
Gol
d
MC
95(g
al)
Cal
iber
M
1000
(gal
)
Cal
iber
M
2000
(gal
)
Bio
Mel
t 6
4(g
al)
Geo
-M
elt
(gal
)
Ice
Bite
55
(gal
)
From
Win
ter S
torm
Rep
orts
, 201
6-20
17
AM
P(g
al)
Bee
t H
eat
(gal
)
10,3
431,
865,
565
4,10
010
08,
422
Gra
nd T
otal
00
00
00
17,3
700
12,4
240
Wed
nesd
ay, J
une
28, 2
017
Page
6 o
f 6Fi
nal t
otal
s as
of
149
Region County Cost to Apply Liquid Anti-icing Chemicals
Total Billed Winter Maintenance Costs
Anti-icing as a % of Winter Costs
SOUTHWEST Columbia $32,388 $1,240,363 1.18%Crawford $3,809 $383,962 0.55%Dane $23,753 $2,913,980 0.46%Dodge $63,257 $973,826 3.30%Grant $27,402 $576,023 2.53%Green $5,816 $305,406 1.25%Iowa $35,248 $668,948 3.05%Jefferson $29,755 $702,467 2.25%Juneau $72,701 $669,200 5.57%La Crosse $93,650 $773,509 7.52%Lafayette $5,969 $366,445 1.14%Monroe $41,861 $775,914 2.57%Richland $28,228 $334,359 4.76%Rock $3,352 $744,303 0.27%Sauk $18,332 $786,587 1.17%Vernon $8,400 $568,429 0.88%SW TOTAL $493,921 $12,783,721 2.09%
SOUTHEAST Kenosha $29,974 $828,962 2.02%Milwaukee $21,468 $4,613,429 0.34%Ozaukee $16,663 $634,303 1.60%Racine $3,785 $752,404 0.30%Walworth $11,407 $951,293 0.66%Washington $3,409 $1,051,155 0.18%Waukesha $51,433 $1,348,350 1.96%SE TOTAL $138,139 $10,179,896 0.85%
NORTHEAST Brown $22,778 $1,319,548 1.11%Calumet $14,772 $296,522 3.63%Door $24,775 $536,696 3.23%Fond du Lac $27,716 $892,574 1.91%Kewanee $6,368 $144,737 2.86%Manitowoc $17,988 $776,493 1.55%Marinette $9,245 $512,895 1.05%Oconto $23,677 $542,368 2.73%Outagamie $969,554 0.00%Sheboygan $9,258 $723,392 0.70%Winnebago $15,486 $1,020,398 0.97%NE TOTAL $172,063 $7,735,177 1.43%
Table A-5. Actual Anti-icing Costs, 2016-2017
150
Region County Cost to Apply Liquid Anti-icing Chemicals
Total Billed Winter Maintenance Costs
Anti-icing as a % of Winter Costs
NORTHCENTRAL Adams $8,128 $301,206 1.42%Florence $9,007 $219,456 2.24%Forest $1,100 $409,413 0.16%Green Lake $368 $182,585 0.12%Iron $425,736 0.00%Langlade $15,244 $400,935 2.42%Lincoln $65,226 $723,876 6.05%Marathon $53,767 $1,208,796 2.60%Marquette $7,762 $321,346 1.19%Menominee $309 $93,357 0.16%Oneida $75,057 $679,075 5.74%Portage $4,464 $1,049,599 0.28%Price $6,962 $459,498 0.90%Shawano $9,215 $799,501 0.71%Vilas $8,685 $571,132 0.83%Waupaca $18,744 $788,630 1.45%Waushara $8,319 $329,145 1.45%Wood $7,682 $481,610 0.78%NC TOTAL $300,039 $9,444,896 1.84%
NORTHWEST Ashland $6,463 $364,463 1.16%Barron $1,158 $697,137 0.12%Bayfield $744 $479,146 0.09%Buffalo $8,756 $357,083 1.51%Burnett $524,840 0.00%Chippewa $1,106,744 0.00%Clark $4,940 $517,080 0.54%Douglas $6,723 $763,185 0.55%Dunn $10,150 $755,087 0.67%Eau Claire $12,392 $811,941 0.75%Jackson $727 $784,218 0.05%Pepin $9,219 $154,737 4.42%Pierce $7,978 $493,208 0.99%Polk $2,238 $472,408 0.26%Rusk $263,936 0.00%Sawyer $334,330 0.00%St. Croix $952,842 0.00%Taylor $7,084 $319,438 1.19%Trempealeau $9,444 $547,106 0.90%Washburn $5,260 $453,016 0.61%NW TOTAL $93,276 $11,151,945 0.47%
Table A-5. Actual Anti-icing Costs, 2016-2017
151
STATEWIDE SUMMARY
SW Region $493,921 $12,783,721 2.09%SE Region $138,139 $10,179,896 0.85%NE Region $172,063 $7,735,177 1.43%NC Region $300,039 $9,444,896 1.84%NW Region $93,276 $11,151,945 0.47%
Statewide Totals $1,197,438 $51,295,635 1.36%
prepared by: Cathy Meinholz/Bureau of Highway Maintenanceu:\winter\fy17wntr activities.xls August 2, 2017
Table A-5. Actual Anti-icing Costs, 2016-2017
152
Table A-6. Salt Brine UseFrom Winter Storm Reports, 2016-2017
REGION GROUP COUNTY PREWETTING ANTI-ICING TOTAL(GALLONS) (GALLONS) (GALLONS)
SOUTHWEST B COLUMBIA 18,450 130,400 148,850C CRAWFORD 25,661 16,500 42,161A DANE 151,195 30,615 181,810B DODGE 60,951 41,018 101,969B GRANT 36,528 53,380 89,908D GREEN 19,925 8,375 28,300E IOWA 7,015 55,260 62,275B JEFFERSON 83,356 18,468 101,824C JUNEAU 37,787 100,570 138,357C LA CROSSE 68,849 30,223 99,072D LAFAYETTE 5,495 7,950 13,445B MONROE 31,512 33,155 64,667D RICHLAND 18,604 12,432 31,036B ROCK 28,018 2,400 30,418B SAUK 5,971 24,745 30,716C VERNON 24,904 23,725 48,629
TOTAL 624,221 589,216 1,213,437
SOUTHEAST B KENOSHA 2,975 3,805 6,780A MILWAUKEE 79,250 29,000 108,250D OZAUKEE 36,160 11,050 47,210B RACINE 37,349 1,900 39,249A WALWORTH 36,320 26,050 62,370B WASHINGTON 82,475 3,300 85,775A WAUKESHA 264,559 166,054 430,613
TOTAL 539,088 241,159 780,247
NORTHEAST B BROWN 65,730 53,800 119,530E CALUMET 9,631 23,250 32,881D DOOR 16,284 45,100 61,384B FOND DU LAC 91,332 40,473 131,805F KEWAUNEE 12,385 1,600 13,985C MANITOWOC 33,819 109,300 143,119D MARINETTE 34,822 82,900 117,722C OCONTO 18,412 29,811 48,223B OUTAGAMIE 180,138 900 181,038C SHEBOYGAN 138,130 31,729 169,859B WINNEBAGO 249,387 31,125 280,512
TOTAL 850,070 449,988 1,300,058
153
Table A-6. Salt Brine UseFrom Winter Storm Reports, 2016-2017
REGION GROUP COUNTY PREWETTING ANTI-ICING TOTAL(GALLONS) (GALLONS) (GALLONS)
NORTH CENTRAL F ADAMS 6450 47,350 53,800F FLORENCE 25460 54,250 79,710E FOREST 28012 3,300 31,312D GREEN LAKE 7885 5,725 13,610E IRON 34,685 34,685E LANGLADE 36,152 50,969 87,121C LINCOLN 44,779 165,740 210,519B MARATHON 48,745 69,075 117,820D MARQUETTE 30,290 52,085 82,375F MENOMINEE 3,103 3,103D ONEIDA 69,450 17,400 86,850B PORTAGE 43,539 4,247 47,786E PRICE 103,478 8,984 112,462C SHAWANO 42649 43,050 91,556E VILAS 48,506 28,172 74,564B WAUPACA 46,392 2,557 22,607D WAUSHARA 20,050 1,950 30,951C WOOD 29,001 13,800 682,426
TOTAL 668,626 568,654 1,237,280
NORTHWEST E ASHLAND 34,408 6,515 40,923C BARRON 20,020 450 20,470D BAYFIELD 22,409 500 22,909D BUFFALO 11,170 10,500 21,670E BURNETT 27,345 27,345B CHIPPEWA 1,100 6,622 7,722C CLARK 3,029 2,140 5,169C DOUGLAS 15,042 1,650 16,692C DUNN 10,383 3810 12,183B EAU CLAIRE 28,855 1,800 28,855C JACKSON 3,150 11,200E PEPIN 2,955 8,050 9,755E PIERCE 20,110 6,800 20,902D POLK 21,828 792 21,828E RUSK 0B SAINT CROIX 19,186 19,186E SAWYER 1,425 1,425E TAYLOR 67,115 6,100 73,215D TREMPEALEAU 8,005 12,150 20,155D WASHBURN 18,667 1,428 20,095
TOTAL 336,202 69,307 405,509
STATE TOTAL 3,018,207 1,918,324 4,936,531# OF COUNTIES 71 65
2016-2017 3,018,207 1,918,324 4,936,531PREVIOUS USE 2015-2016 2,111,119 1,909,303 4,020,422
2014-2015 1,816,818 1,483,653 3,300,4712013-2014 3,060,116 872,780 3,932,8962012-2013 1,082,163 1,164,394 2,246,5572010-2011 1,674,472 714,760 2,389,2322009-2010 933,690 649,909 1,583,5992008-2009 1,028,457 467,943 1,496,4002007-2008 965,797 305,409 1,271,2062006-2007 530,733 456,875 987,6082005-2006 570,203 394,991 965,1942004-2005 398,661 246,813 695,4742003-2004 285,710 241,780 527,4902002-2003 174,413 228,524 402,9372001-2002 144,505 194,349 338,8542000-2001 111,816 48,149 159,965
154
Reg
ion
Cou
nty
Salt
(CY)
CaC
l2 (g
al)
NaC
l B
rine
(gal
)
MgC
l2(g
al)
IB-M
80
(gal
)Fr
eeze
Gar
d(g
al)
Tabl
e A
.7. A
nnua
l Pre
wet
ting
Age
nt U
sage
for S
alt C
aCl2
DO
W
(gal
)
Arc
tic C
lear
G
old
MC
95
(gal
)C
alib
er
M20
00
(gal
)
Bio
Me
lt64
(gal
)
Geo
Mel
t(g
al)
Ice
Bite
(gal
)
From
Win
ter S
torm
Rep
orts
, 201
6-20
17A
MP
(gal
)B
eet
Hea
t(g
al)
NC
AD
AM
S3,
374
100
2,12
50
00
4,22
50
00
00
00
0FL
OR
ENC
E2,
627
025
,460
00
00
00
00
00
00
FOR
ES
T4,
434
028
,012
00
00
00
00
00
00
GR
EEN
LA
KE
1,59
90
7,88
50
00
00
00
00
00
0IR
ON
5,06
30
34,6
850
00
00
00
00
00
0LA
NG
LAD
E3,
533
035
,975
177
00
00
00
00
00
0LI
NC
OLN
4,88
70
42,6
900
010
00
00
00
00
0M
AR
ATH
ON
11,1
580
48,5
000
150
00
00
00
00
0M
AR
QU
ETTE
4,54
10
27,1
750
00
00
3,11
50
00
00
0M
EN
OM
INE
E1,
558
03,
103
00
00
00
00
00
00
ON
EID
A8,
247
057
,178
08,
165
00
00
00
00
00
PO
RTA
GE
7,41
50
42,0
040
00
00
00
00
00
0P
RIC
E4,
203
099
,963
3,02
50
00
00
00
00
00
SH
AW
AN
O7,
968
042
,569
00
00
00
00
00
00
VIL
AS
6,08
30
46,6
860
00
00
00
00
00
0W
AU
PA
CA
7,70
20
46,3
920
00
00
00
00
00
0W
AU
SH
AR
A3,
612
019
,966
00
840
00
00
00
00
WO
OD
6,69
50
29,0
010
00
00
00
00
00
0
Reg
ion
Tota
l94
,699
100
639,
369
3,20
28,
180
944,
225
03,
115
00
00
00
Wed
nesd
ay, J
une
28, 2
017
Page
1 o
f 6Fi
nal t
otal
s as
of
155
Reg
ion
Cou
nty
Salt
(CY)
CaC
l2 (g
al)
NaC
l B
rine
(gal
)
MgC
l2(g
al)
IB-M
80
(gal
)Fr
eeze
Gar
d(g
al)
Tabl
e A
.7. A
nnua
l Pre
wet
ting
Age
nt U
sage
for S
alt C
aCl2
DO
W
(gal
)
Arc
tic C
lear
G
old
MC
95
(gal
)C
alib
er
M20
00
(gal
)
Bio
Me
lt64
(gal
)
Geo
Mel
t(g
al)
Ice
Bite
(gal
)
From
Win
ter S
torm
Rep
orts
, 201
6-20
17A
MP
(gal
)B
eet
Hea
t(g
al)
NE
BR
OW
N12
,709
065
,730
00
00
00
00
00
00
CA
LUM
ET
1,80
40
9,63
10
00
00
00
00
00
0D
OO
R3,
541
016
,284
00
00
00
00
00
00
FON
D D
U L
AC8,
118
090
,567
00
00
076
50
00
00
0K
EW
AU
NE
E1,
313
012
,385
00
00
00
00
00
00
MA
NIT
OW
OC
6,16
50
33,8
190
00
00
00
00
00
0M
AR
INET
TE5,
553
034
,822
00
00
00
00
00
00
OC
ON
TO5,
014
018
,412
00
00
00
00
00
00
OU
TAG
AM
IE4,
941
018
0,13
80
00
00
00
00
00
0S
HE
BO
YGA
N8,
721
013
8,13
00
00
00
00
00
00
0W
INN
EB
AG
O9,
081
024
9,19
140
00
00
156
00
00
00
Reg
ion
Tota
l66
,960
084
9,10
940
00
00
921
00
00
00
Wed
nesd
ay, J
une
28, 2
017
Page
2 o
f 6Fi
nal t
otal
s as
of
156
Reg
ion
Cou
nty
Salt
(CY)
CaC
l2 (g
al)
NaC
l B
rine
(gal
)
MgC
l2(g
al)
IB-M
80
(gal
)Fr
eeze
Gar
d(g
al)
Tabl
e A
.7. A
nnua
l Pre
wet
ting
Age
nt U
sage
for S
alt C
aCl2
DO
W
(gal
)
Arc
tic C
lear
G
old
MC
95
(gal
)C
alib
er
M20
00
(gal
)
Bio
Me
lt64
(gal
)
Geo
Mel
t(g
al)
Ice
Bite
(gal
)
From
Win
ter S
torm
Rep
orts
, 201
6-20
17A
MP
(gal
)B
eet
Hea
t(g
al)
NW
AS
HLA
ND
2,69
10
28,0
560
05,
863
00
00
00
00
0B
AR
RO
N3,
979
016
,600
00
00
00
00
00
00
BA
YFIE
LD4,
976
022
,409
00
00
00
00
00
00
BU
FFA
LO3,
188
011
,170
00
00
00
00
00
00
BU
RN
ETT
2,98
60
00
027
,345
00
00
00
00
0C
HIP
PEW
A12
,230
100
1,00
00
00
00
00
00
00
0C
LAR
K5,
083
302,
380
599
020
00
00
00
00
0D
OU
GLA
S7,
713
010
,284
00
4,70
30
00
00
550
00
DU
NN
10,0
750
6,56
00
00
00
00
03,
743
00
0E
AU
CLA
IRE
11,0
5920
,506
7,82
40
00
00
00
052
50
00
JAC
KS
ON
8,53
10
03,
150
00
00
00
00
00
0P
EPI
N69
80
2,95
50
00
00
00
00
00
0P
IER
CE
4,34
035
519
,755
00
00
00
00
00
00
PO
LK5,
244
016
,976
00
4,65
70
019
50
00
00
0R
USK
2,41
40
00
00
00
00
00
00
0S
AIN
T C
RO
IX12
,199
19,1
860
00
00
00
00
00
00
SA
WYE
R4,
276
00
00
00
01,
352
00
00
00
TAYL
OR
3,23
30
67,1
150
00
00
00
00
00
0TR
EM
PE
ALE
AU
6,90
20
1,20
00
3,52
570
00
02,
580
00
00
00
WA
SH
BU
RN
6,05
80
18,6
670
00
00
00
00
00
0
Reg
ion
Tota
l11
7,87
540
,177
232,
951
3,74
93,
525
43,2
880
04,
127
00
4,32
30
00
Wed
nesd
ay, J
une
28, 2
017
Page
3 o
f 6Fi
nal t
otal
s as
of
157
Reg
ion
Cou
nty
Salt
(CY)
CaC
l2 (g
al)
NaC
l B
rine
(gal
)
MgC
l2(g
al)
IB-M
80
(gal
)Fr
eeze
Gar
d(g
al)
Tabl
e A
.7. A
nnua
l Pre
wet
ting
Age
nt U
sage
for S
alt C
aCl2
DO
W
(gal
)
Arc
tic C
lear
G
old
MC
95
(gal
)C
alib
er
M20
00
(gal
)
Bio
Me
lt64
(gal
)
Geo
Mel
t(g
al)
Ice
Bite
(gal
)
From
Win
ter S
torm
Rep
orts
, 201
6-20
17A
MP
(gal
)B
eet
Hea
t(g
al)
SE
KE
NO
SH
A10
,524
00
2,97
50
00
00
00
00
00
MIL
WAU
KE
E27
,642
17,5
5058
,500
00
00
00
00
00
00
OZA
UK
EE
6,98
59,
345
26,8
150
00
00
00
00
00
0R
ACIN
E7,
950
3,94
133
,408
00
00
00
00
00
00
WA
LWO
RTH
12,8
780
36,3
200
00
00
00
00
00
0W
AS
HIN
GTO
N12
,212
082
,475
00
00
00
00
00
00
WA
UK
ES
HA
20,5
965,
075
255,
714
00
00
00
00
3,77
00
00
Reg
ion
Tota
l98
,787
35,9
1149
3,23
22,
975
00
00
00
03,
770
00
0
Wed
nesd
ay, J
une
28, 2
017
Page
4 o
f 6Fi
nal t
otal
s as
of
158
Reg
ion
Cou
nty
Salt
(CY)
CaC
l2 (g
al)
NaC
l B
rine
(gal
)
MgC
l2(g
al)
IB-M
80
(gal
)Fr
eeze
Gar
d(g
al)
Tabl
e A
.7. A
nnua
l Pre
wet
ting
Age
nt U
sage
for S
alt C
aCl2
DO
W
(gal
)
Arc
tic C
lear
G
old
MC
95
(gal
)C
alib
er
M20
00
(gal
)
Bio
Me
lt64
(gal
)
Geo
Mel
t(g
al)
Ice
Bite
(gal
)
From
Win
ter S
torm
Rep
orts
, 201
6-20
17A
MP
(gal
)B
eet
Hea
t(g
al)
SW
CO
LUM
BIA
18,9
330
18,4
500
00
00
00
00
00
0C
RAW
FOR
D4,
291
025
,359
00
00
00
00
00
00
DAN
E30
,402
015
1,19
50
00
00
00
00
00
0D
OD
GE
13,4
650
55,4
810
00
00
00
00
05,
470
0G
RA
NT
7,59
40
36,5
280
00
00
00
00
00
0G
RE
EN2,
139
019
,692
00
00
00
00
00
00
IOW
A6,
799
06,
856
00
00
00
00
00
159
0JE
FFER
SO
N9,
057
080
,666
00
040
00
00
00
02,
290
0JU
NE
AU8,
215
031
,932
00
5,40
00
00
045
50
00
0LA
CR
OS
SE
6,14
00
10,8
280
00
00
00
057
,031
00
0LA
FAYE
TTE
2,24
90
5,49
50
00
00
00
00
00
0M
ON
RO
E11
,241
031
,512
00
00
00
00
00
00
RIC
HLA
ND
3,35
90
17,6
200
00
00
00
00
00
0R
OC
K7,
730
028
,018
00
00
00
00
00
00
SA
UK
9,83
40
5,97
10
00
00
00
00
00
0V
ER
NO
N5,
507
023
,655
00
860
01,
163
00
00
00
Reg
ion
Tota
l14
6,95
50
549,
258
00
5,48
640
00
1,16
30
455
57,0
310
7,91
90
Wed
nesd
ay, J
une
28, 2
017
Page
5 o
f 6Fi
nal t
otal
s as
of
159
Reg
ion
Cou
nty
Salt
(CY)
CaC
l2 (g
al)
NaC
l B
rine
(gal
)
MgC
l2(g
al)
IB-M
80
(gal
)Fr
eeze
Gar
d(g
al)
Tabl
e A
.7. A
nnua
l Pre
wet
ting
Age
nt U
sage
for S
alt C
aCl2
DO
W
(gal
)
Arc
tic C
lear
G
old
MC
95
(gal
)C
alib
er
M20
00
(gal
)
Bio
Me
lt64
(gal
)
Geo
Mel
t(g
al)
Ice
Bite
(gal
)
From
Win
ter S
torm
Rep
orts
, 201
6-20
17A
MP
(gal
)B
eet
Hea
t(g
al)
525,
276
76,1
882,
763,
919
9,96
611
,705
48,8
68St
atew
ide
Tota
l4,
625
09,
326
045
565
,124
07,
919
0
Wed
nesd
ay, J
une
28, 2
017
Page
6 o
f 6Fi
nal t
otal
s as
of
160
Reg
ion
Cou
nty
Sand
(C
Y)C
aCl2
(g
al)
NaC
l B
rine
(gal
)
MgC
l2
(gal
)IB
-M80
(gal
)Fr
eeze
Gar
dG
uard
Tabl
e A
.8. A
nnua
l Abr
asiv
es a
nd P
rew
ettin
g A
gent
Usa
ge fo
r Abr
asiv
es
CaC
l2
DO
W
(gal
)
Arc
tic
Cle
arG
old
MC
95
(gal
)C
alib
er
M20
00
(gal
)
Bio
Me
lt64
(gal
)
Geo
Mel
t(g
al)
Ice
Bite
(gal
)
From
Win
ter S
torm
Rep
orts
, 201
6-20
17
NC
AD
AM
S9
00
00
00
00
00
00
FLO
REN
CE
980
00
00
00
00
00
0FO
RES
T13
00
00
00
00
00
00
GR
EE
N L
AKE
00
00
00
00
00
00
0IR
ON
690
00
00
00
00
00
0LA
NG
LAD
E0
00
00
00
00
00
00
LIN
CO
LN1,
197
02,
089
00
00
00
00
00
MAR
ATH
ON
153
023
00
00
00
00
00
0M
ARQ
UET
TE0
00
00
00
00
00
00
MEN
OM
INEE
710
00
00
00
00
00
0O
NE
IDA
1,57
90
4,10
70
00
00
00
00
0P
OR
TAG
E95
70
1,53
50
00
00
00
00
0P
RIC
E35
80
490
800
00
00
00
00
SH
AW
AN
O10
00
00
00
00
00
00
VIL
AS
880
01,
820
00
00
00
00
00
WA
UP
AC
A0
00
00
00
00
00
00
WA
US
HA
RA
00
00
00
00
00
00
0W
OO
D23
00
00
00
00
00
00
Reg
ion
Tota
l5,
417
010
,271
800
00
00
00
00
Wed
nesd
ay, J
une
28, 2
017
Page
1 o
f 6Fi
nal t
otal
s as
of
161
Reg
ion
Cou
nty
Sand
(C
Y)C
aCl2
(g
al)
NaC
l B
rine
(gal
)
MgC
l2
(gal
)IB
-M80
(gal
)Fr
eeze
Gar
dG
uard
Tabl
e A
.8. A
nnua
l Abr
asiv
es a
nd P
rew
ettin
g A
gent
Usa
ge fo
r Abr
asiv
es
CaC
l2
DO
W
(gal
)
Arc
tic
Cle
arG
old
MC
95
(gal
)C
alib
er
M20
00
(gal
)
Bio
Me
lt64
(gal
)
Geo
Mel
t(g
al)
Ice
Bite
(gal
)
From
Win
ter S
torm
Rep
orts
, 201
6-20
17
NE
BR
OW
N0
00
00
00
00
00
00
CA
LUM
ET
00
00
00
00
00
00
0D
OO
R2
00
00
00
00
00
00
FON
D D
U L
AC5
00
00
00
00
00
00
KE
WA
UN
EE
450
00
00
00
00
00
0M
ANIT
OW
OC
00
00
00
00
00
00
0M
ARIN
ETTE
520
00
00
00
00
00
0O
CO
NTO
00
00
00
00
00
00
0O
UTA
GA
MIE
80
00
00
00
00
00
0S
HE
BO
YGA
N1
00
00
00
00
00
00
WIN
NE
BAG
O0
00
00
00
00
00
00
Reg
ion
Tota
l11
30
00
00
00
00
00
0
Wed
nesd
ay, J
une
28, 2
017
Page
2 o
f 6Fi
nal t
otal
s as
of
162
Reg
ion
Cou
nty
Sand
(C
Y)C
aCl2
(g
al)
NaC
l B
rine
(gal
)
MgC
l2
(gal
)IB
-M80
(gal
)Fr
eeze
Gar
dG
uard
Tabl
e A
.8. A
nnua
l Abr
asiv
es a
nd P
rew
ettin
g A
gent
Usa
ge fo
r Abr
asiv
es
CaC
l2
DO
W
(gal
)
Arc
tic
Cle
arG
old
MC
95
(gal
)C
alib
er
M20
00
(gal
)
Bio
Me
lt64
(gal
)
Geo
Mel
t(g
al)
Ice
Bite
(gal
)
From
Win
ter S
torm
Rep
orts
, 201
6-20
17
NW
AS
HLA
ND
292
040
10
088
00
00
00
0B
AR
RO
N1,
527
03,
420
00
00
00
00
00
BA
YFIE
LD14
00
00
00
00
00
00
0B
UFF
ALO
210
00
00
00
00
00
0B
UR
NE
TT0
00
00
00
00
00
00
CH
IPP
EW
A45
30
00
00
00
00
00
0C
LAR
K0
00
00
00
00
00
00
DO
UG
LAS
840
00
080
00
00
00
0D
UN
N2
00
00
00
00
00
00
EA
U C
LAIR
E4
00
00
00
00
00
00
JAC
KS
ON
00
00
00
00
00
00
0P
EP
IN0
00
00
00
00
00
00
PIE
RC
E85
00
00
00
00
00
00
PO
LK15
30
00
00
00
00
00
0R
US
K10
10
00
00
00
00
00
0S
AIN
T C
RO
IX37
00
00
00
00
00
00
SA
WYE
R14
90
00
00
00
730
00
0TA
YLO
R30
00
00
00
00
00
00
TRE
MP
EA
LEA
U0
00
00
00
00
00
00
WA
SH
BU
RN
00
00
00
00
00
00
0
Reg
ion
Tota
l3,
078
03,
821
00
168
00
730
00
0
Wed
nesd
ay, J
une
28, 2
017
Page
3 o
f 6Fi
nal t
otal
s as
of
163
Reg
ion
Cou
nty
Sand
(C
Y)C
aCl2
(g
al)
NaC
l B
rine
(gal
)
MgC
l2
(gal
)IB
-M80
(gal
)Fr
eeze
Gar
dG
uard
Tabl
e A
.8. A
nnua
l Abr
asiv
es a
nd P
rew
ettin
g A
gent
Usa
ge fo
r Abr
asiv
es
CaC
l2
DO
W
(gal
)
Arc
tic
Cle
arG
old
MC
95
(gal
)C
alib
er
M20
00
(gal
)
Bio
Me
lt64
(gal
)
Geo
Mel
t(g
al)
Ice
Bite
(gal
)
From
Win
ter S
torm
Rep
orts
, 201
6-20
17
SE
KE
NO
SH
A19
20
00
00
00
00
00
0M
ILW
AU
KE
E0
03,
200
00
00
00
00
00
OZA
UK
EE
00
00
00
00
00
00
0R
AC
INE
00
00
00
00
00
00
0W
ALW
OR
TH2
00
00
00
00
00
00
WA
SH
ING
TON
00
00
00
00
00
00
0W
AU
KE
SH
A0
00
00
00
00
00
00
Reg
ion
Tota
l19
40
3,20
00
00
00
00
00
0
Wed
nesd
ay, J
une
28, 2
017
Page
4 o
f 6Fi
nal t
otal
s as
of
164
Reg
ion
Cou
nty
Sand
(C
Y)C
aCl2
(g
al)
NaC
l B
rine
(gal
)
MgC
l2
(gal
)IB
-M80
(gal
)Fr
eeze
Gar
dG
uard
Tabl
e A
.8. A
nnua
l Abr
asiv
es a
nd P
rew
ettin
g A
gent
Usa
ge fo
r Abr
asiv
es
CaC
l2
DO
W
(gal
)
Arc
tic
Cle
arG
old
MC
95
(gal
)C
alib
er
M20
00
(gal
)
Bio
Me
lt64
(gal
)
Geo
Mel
t(g
al)
Ice
Bite
(gal
)
From
Win
ter S
torm
Rep
orts
, 201
6-20
17
SW
CO
LUM
BIA
645
00
00
00
00
00
00
CR
AWFO
RD
326
030
20
00
00
00
00
0D
ANE
140
00
00
00
00
00
0D
OD
GE
00
00
00
00
00
00
0G
RA
NT
2,02
10
00
00
00
00
00
0G
RE
EN
720
233
00
00
00
00
00
IOW
A12
10
00
00
00
00
00
0JE
FFER
SON
00
00
00
00
00
00
0JU
NE
AU0
00
00
00
00
00
00
LA C
RO
SSE
198
00
00
00
00
00
00
LAFA
YETT
E1,
237
099
00
00
00
00
00
0M
ON
RO
E34
00
00
00
00
00
00
RIC
HLA
ND
515
098
40
00
00
00
00
0R
OC
K51
00
00
00
00
00
00
SA
UK
00
00
00
00
00
00
0VE
RN
ON
431
00
00
00
00
00
00
Reg
ion
Tota
l5,
665
02,
509
00
00
00
00
00
Wed
nesd
ay, J
une
28, 2
017
Page
5 o
f 6Fi
nal t
otal
s as
of
165
Reg
ion
Cou
nty
Sand
(C
Y)C
aCl2
(g
al)
NaC
l B
rine
(gal
)
MgC
l2
(gal
)IB
-M80
(gal
)Fr
eeze
Gar
dG
uard
Tabl
e A
.8. A
nnua
l Abr
asiv
es a
nd P
rew
ettin
g A
gent
Usa
ge fo
r Abr
asiv
es
CaC
l2
DO
W
(gal
)
Arc
tic
Cle
arG
old
MC
95
(gal
)C
alib
er
M20
00
(gal
)
Bio
Me
lt64
(gal
)
Geo
Mel
t(g
al)
Ice
Bite
(gal
)
From
Win
ter S
torm
Rep
orts
, 201
6-20
17
14,4
670
19,8
0180
016
8St
atew
ide
Tota
l0
073
00
00
Wed
nesd
ay, J
une
28, 2
017
Page
6 o
f 6Fi
nal t
otal
s as
of
166
Table A-9. History of Salt Use on State Trunk HighwaysFrom Salt Inventory Reporting System
Winter Tons of Salt Lane Miles Tons/Lane Mile
Million Vehicle Miles Traveled STH
System (Winter)============ ============ =========== ============ =============
1959/60 93,673 19,521 4.8 8,8281960/61 54,805 19,948 2.7 9,2541961/62 109,412 19,966 5.5 9,5581962/63 77,719 19,756 3.9 9,7821963/64 82,033 19,717 4.2 10,0641964/65 149,329 19,911 7.5 10,5661965/66 111,634 19,505 5.7 11,1221966/67 181,230 20,137 8.0 11,9331967/68 137,729 22,395 6.2 12,1401968/69 193,004 22,675 8.5 12,8701969/70 199,353 22,831 8.7 13,8531970/71 273,010 23,120 11.8 15,1331971/72 223,249 25,543 8.7 14,3251972/73 256,571 25,673 10.0 15,3011973/74 218,189 N/A N/A 16,1981974/75 237,916 N/A N/A 15,8071975/76 257,154 N/A N/A 16,1981976/77 188,011 N/A N/A 18,5561977/78 210,054 N/A N/A 19,6211978/79 235,193 N/A N/A 21,0531979/80 220,180 N/A N/A 20,4031980/81 151,021 N/A N/A 19,3601981/82 192,740 N/A N/A 20,2101982/83 234,529 27,407 8.6 20,0561983/84 224,368 27,416 8.2 20,8731984/85 217,136 27,598 7.9 21,2141985/86 304,296 27,632 11.0 22,1101986/87 196,035 27,613 7.1 23,1761987/88 224,573 27,743 8.1 24,3461988/89 230,403 27,872 8.3 24,5501989/90 297,004 28,024 10.6 25,3701990/91 364,174 28,006 13.0 26,2471991/92 337,079* 28,104 12.0* 27,3911992/93 416,594* 28,182 14.8* 28,2521993/94 314,489* 28,221 11.1* 28,8591994/95 295,479* 28,312 10.4* 29,2101995/96 440,488* 28,374 15.5 30,0771996/97 509,147* 28,545 17.8* 31,1221997/98 413,824* 29,619 14.0* 32,0831998/99 371,602 30,119 12.4 33,2361999/00 346,963* 30,340 11.4* 33,8252000/01 521,056 30,553 17.1 34,6572001/02 308,954 30,909 10.0 34,0762002/03 328,922 30,975 10.6 35,0882003/04 390,664 31,429 12.4 35,6622004/05 407,924 31,810 12.8 36,0132005/06 410,570 33,022 12.4 35,6422006/07 405,793 33,221 12.2 27,9112007/08 644,484 33,297 19.4 27,9312008/09 569,985 33,531 17.0 26,8882009/10 408,523 33,532 12.2 26,1092010/11 573,253 33,776 17.0 26,9982011/12 355,519 33,944 10.5 25,6692012/13 621,207 34,192 18.2 26,5122013/14 669,807 34,339 19.5 26,7742014/15 388,797 34,435 11.3 28,2182016/17 526,198 34,621 15.2 29,350
* Quantities adjusted