DETERMINING WATERSHED BOUNDARIES AND AREA USING GPS,DEMS, AND TRADITIONAL METHODS: A COMPARISON

Boris Poff Duncan Leao,Aregai Teele,and Daniel G.Neary

Defining a watershed's boundary is criticalfor understanding the movement of wateracross the landscape. In the past, hydrolo-gists defined watersheds using topographicmap !features such as contour lines, streamnetworks, and traditional surveys. However,the more advanced current techniques fordefining watershed boundaries use Geo-graphic Information Systems (GIS) in con-junction with Digital Elevation Models(DEMs; Maidment 1999). GIS is an impor-tant tool in resource management today.Because of its precision and accuracy, weexpect the Global Positioning System (GPS)to be more appropriate for delineatingwatershed boundaries and calculating areathan traditional forestry field methods ofusing a compass and chain. We also expectGPS surveyed boundaries to be more precisethan those determined using DEMs, becauseDEMs rely on 10 m topographic intervals,which can lead to faulty results, especially inareas with small elevation differences.

After" selective availability" was re-moved from GPS technology in May of 2000,potential point location error without differ-ential correction dropped from 100 to 3 m.According to Oderwald and Boucher (2003),this indicates that a single point observationon average is within approximately 3 m ofits true location. In contrast, on a 1:24,000topographic map, a 0.5 mm pencil line is 12m wide (Oderwald and Boucher 2003).

In our study, we chose not to apply post-processing differential correction to our datafor three reasons. First, users may not haveaccess to base stations to differentially cor-

rect their data or may not have the expertiseto do so. Second, low-end, consumer-gradeGPS units may not offer the option of differ-ential correction. Third, we assume that forareas greater than 20 hectares (ha) in sizecumulative error is insignificant due to therandomness distribution of the horizontal

error distance (which averages between 3and 4 m for each point; Wilson 2000).

DEMs are digital representations of sur-face elevations laid out over the landscape.A DEM is produced from digitized mapcontours, spot elevations, and hydrographyoverlays or from manual scanning of aerialphotographs (Elassal and Caruso 1983;Maidment and Djokic 2000). DEMs are valu-able because they provide managers withthe same information as contour maps, butin a digital format suitable for processing bycomputer-based systems rather than in ananalog format (Cho and Lee 2001). The accu-racy of DEMs for use in watershed delinea-tion depends mostly on their cell size andresolution. The smaller the cell size thegreater the resolution; therefore, smallerwatersheds require a smaller cell size toaccurately represent the watershed area.According to Maidment and Djokic (2000)for most hydrologic and geomorphic model-ing applications 10 m DEMs are sufficient.Currently, the USGS has DEMs with 30, 100,500, and 1000 m cell sizes available for theUnited States. A 30 m DEM means that eachcell covers an area of 30 m x 30 m (Maid-ment 1999). Higher resolution DEMs such as5 and 10 m are more readily available fromstate governments and the USGS through its

422 Paft, Leaa, Teele, and Neary

partner ATDI (http:/ /www.atdi-us.com;accessed March 2004).

From October 2002 through January 2004,two large, four medium, and three smallwatersheds were mapped using a hand-heldGPS receiver. The two large watersheds-Watershed 20 (Bar M) and Watershed 19(Woods Canyon)-as well as three smallsub-watersheds (85, 86, and 87) within Wat-ershed 19 are located in the Beaver Creek

Experimental Watershed in central Arizona(Figure 1). The four medium-sized water-sheds-the East and West Forks of CastleCreek and the North and South Forks ofThomas Creek-are in eastern Arizona

(Figure 1). The objective of this study was tocompare watershed area and boundarydetermined using a GPS (without post-processing differential correction of data)with watershed parameters determinedusing traditional methods of area calcula-tion, and with watersheds determined usingDEMs in GIS.

STUDY AREAS

The Forest Service had established experi-mental watersheds in Arizona to determine

the amount and sustainability of water yieldproduced from various silvicultural prac-tices. Twenty pilot watersheds were set upby the USDA Forest Service between 1957and 1962 in the Beaver Creek ExperimentalWatershed, which is located within the Co-conino National Forest of northern Arizona(Figure 1). Of the 20 watersheds, 18 range insize from 27 to 824 ha. The remaining twowatersheds, Bar M (Watershed 20) andWoods Canyon (Watershed 19), are muchlarger and are located in the ponderosa pineforest ecosystem, encompassing 6620 and4893 ha, respectively (Baker and Ffolliott1999). The four mid-sized watersheds arelocated 14-25 km south of the town of

Alpine in the Apache-Sitgreaves NationalForest in eastern Arizona (Figure 1). TheWest and East Fork experimental water-sheds of Castle Creek were established in1955 and are 354 and 458 ha in size, respec-tively. The East Fork was subject to pre-harvest prescribed burning (Gottfried and

DeBano 1988). The North and South Forks ofThomas Creek, established in the mid 1960s,are 184 and 221 ha in size, respectively(Dietrich 1980; Ffolliott and Gottfried 1991).

METHODS

The original identification and mapping ofthe study watersheds involved several steps.The boundary of each watershed wasroughly delineated on a topographic map toinstall a flume at the mouth of each water-

shed. Following flume installation, theboundary of each watershed was flagged,beginning at the lowest elevation and end-ing at the highest elevation. Upon markingthe boundary, in the Beaver Creek water-sheds trees wefe painted at eye level withyellow paint to make the boundary perma-nent and visible from a substantial distance

in any direction. At Thgmas Creek, treeswere painted with white paint. In the ab-sence of trees, the paint marks were appliedto rocks or stumps. Next, surveyors usedtraditional forestry surveying techniques tomap the boundaries. Beginning at the streamgauging equipment, surveyors measuredshort segments of the boundary using a 2-chain steel tape while correcting for slopeusing a clinometer. With a compass, thebearing of each segment was taken andplotted on a Reinhardt Redy Mapper (a hardplastic board with imprinted grid and com-pass bearings). The Castle Creek watershedswere not delineated on the ground.

Field Methodology

In the Beaver Creek Experimental Water-shed we used the paint markings made bysurveying crews in the late 1950s as guidesto locate ridge points, and we followed thesewhen we delineated the watershed bounda-

ries with our GPS receiver. Originally treeshad been marked in close proximity to oneanother, however not all the trees and mark-ings exist today. Some of the marked treeshave since died, burned, or been harvested,or their markings have faded away as aresult of exposure to sunlight. Wherever weencountered gaps between marked trees, wedepended on the topographic features of the

Poft, Leao, Teele, and Neary 423

12km

Figure 1 . Location of study watersheds within the Coconino and Apache-Sitgreaves National Forestsin Arizona.

landscape to delineate the watershedboundary. The longest unmarked boundaryline we encountered was approximately 500m on a well-defined ridgeline. In the CastleCreek watersheds we relied on a distinct

ridge as well as a compass and a topograph-ic map with 5-foot contour intervals thatcircumscribed the watershed boundary. Inthe Thomas Creek watersheds, we used acombination of topographic features,marked trees, a compass, and a topographicmap with 5-foot contours on which thewatershed boundary had been marked, todetermine the actual watershed boundaryon the ground. The beginning and endinglocation of the survey of each watershed wasthe respective gauging station of that water-shed.

GIS/GPS MethodologyWe used a Trimble GeoExplorer3 handheldGPS receiver to record our position alongthe boundary and to record line data in akinematic mode. GPS data were recorded inUniversal Transverse Mercator (UTM)format and were projected using the NorthAmerican Datum (NAD) of 1927.The typicaldistance between each recorded point on theline was about 5 m, but varied up to a maxi-mum of 30 m. The GPS receiver recorded

points every few seconds, depending onreception. Reception, in turn, depended onthe topographic features and canopy closure(Karsky 2001), which varied from a to 100percent. In rare cases we had to wait severalminutes before a point was recorded. Theboundaries of small and medium sized

424 Poff, Leao, Teele, and Neary

watersheds were recorded in a timeframe of

one or two days each. The large watershedboundaries, Bar M and Woods Canyon,were recorded over the course of several

months. We walked and recorded adjacentsections of the boundary two or three daysper week. We then downloaded the line datausing Pathfinder Office 2.90 (Trimble 2002)software. We eliminated obvious outliers

and artificially created polygons manuallyin Pathfinder. We viewed the recorded line

data files on either the same or the next dayto eliminate outlier points. Such outlierswould include points that were severalmeters away from where we walked in astraight line with the GPS. After cleaning upthe individual line files, we combined thefiles for each watershed and exported thesedata as polyline shapefiles for further proc-essing using a GIS software application. InArcView GIS 3.3 (ESRI 2003), we used a fea-ture called Xtools to convert the polylines-shapefile into one polygon-shapefile for eachwatershed. Once imported into ArcMap(ESRI 2004), we determined the area for eachrespective watershed.

To delineate the watersheds using DEMs,we used 10 m DEMs and the ArcView

CRWR Preprocessor (Maidment and Djokic2000;ESRI2002).DEMswere obtained fromthe Arizona Regional Image Archive (ARIA)and projected in UTM NAD 1927. All DEMswere merged using the map calculator tocreate one complete DEM for analysis. Astream shapefile obtained from the ArizonaLand Resource Information Service was

burned into the DEM and appropriate stepswere followed in the CRWR Preprocessor tofill sinks, compute the flow direction andflow accumulation grids, construct the basicstream network, segment streams intostream links, find link outlets, delineate thewatersheds, and vectorize the stream andwatershed grids. After the above steps werecompleted, sub-watersheds were merged tocreate the specific watersheds of this study.

Determining DischargeUsing HEC-HMS

Determining the discharge from all water-sheds and their respective areas from each

method involved several activities. First,watershed characteristics such as soil type,stream patterns, vegetation type, slope, andland use characteristics were obtained in theform of shape files from the Arizona LandResource Information Service (ALRIS) andthe Coconino National Forest. After gather-ing all watershed data, we used the ArmyCorp of Engineers surface runoff modelingsystem, HEC-HMS (Scharffenburg 2001).The surface runoff system is a softwareprogram capable of using multiple methodsto determine surface runoff from a water-shed using various infiltration, baseflow,and runoff calculations. We used the Natur-al Resource Conservation Service (NRCS;formerly Soil Conservation Service) rainfall-runoff model (McCuen 1982; NRCS 1986;Scharffenburg 2001) to determine the event-based surface runoff under two storm events

in average moisture conditions. The NRCSmodel is categorized as a lumped based andempirical model (Scharffenburg 2001). Weused the NRCS method because it is easy toapply, is most widely used by hydrologists,and was developed to evaluate downstreamimpacts from various management treat-ments (Woodward et al. 2002). The twoevents that we used to generate runoff were25 and 100 yr return period storms coveringthe entire watershed area. We used the SCS

type II 24 hr rainfall distribution pattern forthe 25 and 100 yr storms, and the stormdepths were determined to be 6.8 and 8.5 cmof precipitation respectively (U.S. ArmyCorp of Engineers 2000).

RESULTS

The results of this study are threefold. First,we have established the boundaries of thewatersheds in a GIS format that has been

derived using various methods. Second, wecompared the watershed areas determinedusing our GPS method to the areas deter-mined using traditional cartographicmethods as well as to the areas calculated

using the computer analysis of DEMs. Wealso compared the results of computer anal-ysis to the traditional method of determin-ing watershed areas. Third, we used theHEC-HMS surface-runoff software to de-

termine differences between the variousmethods of delineating a watershed, interms of modeling output.

Area Discrepancies

Figure 2 shows a section of the Bar M GISlayer created in this study using the GPSdata overlaid with a GIS layer currentlyinuse by the USDA Forest Service. The dif-ferences between the two layers are minor inmost instances but can easily reach a magni-tude of 50 ha or more in some areas. These

discrepancies also have a cumulative effecton the entire watershed. Even though DEMsused by government agencies, such as theUSDA Forest Service or the USGS, are

developed to National Map Accuracy Stand-ards (Longley et al. 2001), the 10 m contourlines in Figure 2 fit our GPS layer arguablybetter than those currently in use by theForest Service.

Poff, Leao, Teele, and Neary 425

Another example of area discrepancy isgiven in Figure 3, which shows the differ-ence between a layer we created using a 10m DEM and our GPS layer. Here the GPSlayer is very close to the traditionally deter-mined boundary. However, according to theDEM layer, Woods Canyon should include asection of approximately 200 ha, which itdoes not. This discrepancy probably resultsfrom the DEM's failure to capture the lessthan 10 m elevation difference between theboundaries.

We encountered another major area dif-ference while creating our DEM layers forsub-watershed 85. Here the DEM created

two separate watersheds for the area thathad been determined to be one watershed

using the traditional methods (Figure 4).However, for the purpose of our area com-parisons, we combined the area of these twowatersheds into one.

USDA Forest Service Watershed Layers =solid background

GPS Bar MWatershed Layer =cross hatched

Figure 2. Comparison of a portion of the Bar M watershed with a USDA Forest Service GIS layer; 10m contour interval derived from USGS digital elevation model.

426 Poff, Leao, Teele, and Neary

Figure 3. According to our 10m OEMs, an area of ca. 200 ha should be included in our GPS layer ofthe Woods Canyon watershed. Even the Woods Canyon gauging station does not fall within the OEMlayer.

Area Calculations

We determined the area for all nine water-sheds using DEMs, GPS, and GIS technolo-gies and compared the results with thetraditional USDA Forest Service approach aswell as with each other. Table 1 gives thetotal area of each watershed surveyed in thisstudy. The net difference in percent is givenin Table 2. Because our data are not normal-ly distributed, we ran several nonparametricequivalent tests of a one sample repeatedmeasurement design. Although the sub-watersheds are nested within one watershed

and some watersheds are adjacent to eachother, we believe that our statistics areappropriate because the measurements areseparate and watershed areas have a func-tional independence.

The Friedman procedure tests the nullhypothesis that k variables come from thesame population; in our case these variablesare the watershed areas. The test statistic is

based on these ranks. We also performed theKendall's W, the Wilcoxon rank tests, and amulti-response permutation procedure for ablock design (MRBP) based on Euclidean

distance for unreplicated randomized blockdesign (Table 3). Test results gave us signifi-cance values between .2 and .5, suggestingthat we do not have enough information toreject the null hypothesis that there is nodifference between methods used. Hence,we conclude that there is no statisticallysignificant difference in area among any ofthe three methods. However, we believethere are several management implicationsto these differences, depending on manage-ment objectives and goals, as discussedbelow.

Surface Runoff ModelingAlthough each method of watershed de-

lineation produced varying areas, the resultsof the surface runoff modeling using HEC-HMS show a small difference in runoff peakdischarges. For the 25 yr return periodstorm, differences in discharge ranged from0.06 to 0.17 cubic meters per second (2-6cubic feet per second) among all methods.For the 100 yr return period storm differ-ences in discharge ranged from 0.23 to 0.53cms (8-19 cfs) among all methods of areadelineation. The difference in discharge was

Poff, Leao, Teele, and Neary 427

DEM determinedwatersheds= solid background

GPS WS85 watershed layerbased on traditionallysurveyed parameter= hatched

Gauging Station ..

E~

C'!,....

Figure 4. According to our 10 m OEMs, watershed 85 should be two separate watersheds, whereastraditional surveying techniques suggest one watershed.

primarily proportional to the watershedarea. For example, watersheds 85, 86, and 87produced discharge at the lower end of theabove discharge ranges, whereas the Bar M,Woods Canyon, Castle Creek, and ThomasCreek watersheds produced discharge at thehigher end of the discharge ranges.

DISCUSSION

The results in Tables 1 and 2 show that de-

pending on the size of a watershed it may beadvantageous to incorporate GPS technol-ogy into the watershed survey procedure.Using a GPS receiver allows for a faster, less

complicated estimate when calculating thearea of a watershed and determining itsboundary. Training field users to collectuncorrected GPS data has a steep learningcurve; the equipment is inexpensive andrelatively easy to use compared to thetraditional forestry field methods of using acompass and chain. Collecting GPS dataallows ground truthing of watersheds andavoids adding additional area or leaving outarea, which may be the case when usingDEMs to determine watersheds. In our

study the size of the errors seems relativelyconstant with respect to watershed size, so

428 Poff, Leao, Teele, and Neary

Table 1. Watershed areas (ha) estimated using the traditional Forest Service approach, DEM, and GPStechnologies.

Table 2. Net difference in percent between watershed areas estimated using the traditional ForestService approach, DEM, and GPS technologies.

Table 3. Test statistics indicating similarity between watershed areas estimated using the traditionalForest Service approach, DEM, and GPS technologies.

WatershedTraditionally

Calculated Area DEM Area GPS Area

BarM 6621 6641 6662

Woods Canyon 4893 5017 4884Sub-watershed 85 70.4 64.2 61.5Sub-watershed 86 40.9 40.9 40.5Sub-watershed 87 23.5 26.1 22.3Castle Creek East 458 456 467Castle Creek West 354 398 364Thomas Creek South Fork 221 236 230Thomas Creek North Fork 184 185 191

Traditionally TraditionallyCalculated Calculated

Watershed Area vs. DEM Area vs. GPS GPS vs. DEM

BarM -0.31 -0.62 -0.31

Woods Canyon -2.52 0.19 2.65Sub-watershed 85 8.82 12.64 4.19Sub-watershed 86 -0.07 0.98 1.05Sub-watershed 87 -11.21 5.16 14.71Castle Creek East 0.35 -1.86 -2.22Castle Creek West -12.39 -2.94 8.41Thomas Creek South Fork -6.58 --4.12 2.31Thomas Creek North Fork -0.54 -3.59 -3.03

TraditionalTest p-Value Method DEM GPS

MRBP .228 6.98 3.49 10.69Wilcoxon .495 11.56 15.89 14.56Friedman .236 1.67 2.44 1.89Kendall's W .236 1.67 2.44 1.89

for large watersheds, these errors seeminsignificant. On the other hand, any studyusing the Woods Canyon gauging station(Figure 3) would need a more precisemeasurement of watershed area, regardlessof monetary significance; otherwise the databecome meaningless. The greatest discrep-ancy we found was in sub-watershed 85.Here the DEM created two separate water-sheds for the area that had been determined

to be one watershed using the traditionalmethods. In this instance, which we assumeto be a problem primarily with smaller scalewatersheds, ground truthing is probably themost reliable technique for determiningboundaries. Carrying a GPS receiver whiledoing so, in turn, is also a cost-effectivemethod of recording and verifying a water-shed boundary.

Another concern we have is that certain

methods may include or exclude topogra-phy or area during delineation. Wu et al.(2003) have pointed out that not only sizebut also the relief of a watershed can affect

the accuracy of its delineation, and theyadvise caution when delineating watershedsthat are small with little or no relief. There

may be a negative relationship between thesteepness of the terrain (and therefore thewatershed divides) and the relative error inmeasuring watershed boundaries.

The discrepancies in the Woods Canyonwatershed delineation using the differentmethods (see Figure 3) are caused by the flatterrain, and suggest that more precise meth-ods are needed in flat terrain, or in placeswhere watershed divides are low. There

may not be a significant correlation betweenoverall watershed relief and the relief of thewatershed divides at certain scales.

This study compares the use of the tradi-tional topographic method, DEMs, and GPSto delineate watershed boundaries and

derive their areas. However, future compari-sons of watershed area should include abso-lute (rather than net) differences in water-shed area size and their effects on watershedwater balance. Although each methodproduced slightly different watershed areas,

Paft, Leaa, Teele, and Neary 429

the difference in runoff modeling using thevarious watershed areas for model inputseemed small. Even so, scientists and landmanagers need to use special care duringthe modeling process, and should be awareof how a watershed area was determined

and what potential pitfalls exist according tothe method of delineation.

ACKNOWLEDGMENTSWe thank Scott Walker and Steve Andariese

of Northern Arizona University's Depart-ment of Geography and School of Forestry,respectively, for their technical help in theuse of GIS; Jonathan Long and RuihongHuang for their reviews; and Steve Overbyand Geoff Seymour for their assistance inthe field. Funding for this study was pro-vided by Arizona State Prop. 301, theBureau of Forestry Research, and the USDAMcIntire-Stennis funding as well as theUSDA Forest Service Rocky MountainResearch Station in Flagstaff, AZ.

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TheColoradoPlateauIIBIOPHYSICAL, SOCIOECONOMIC, AND CULTURAL RESEARCH

Edited by Charles van Riper III and David J. Mattson

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This volume is based on research presented at the SeventhBiennial Conference of Research on the Colorado Plateau.

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