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Surface Water Quality Monitoring:Surface Water Quality Monitoring:
Sergei G.Touchinski
AMEC Earth & EnvironmentalCalgary, Alberta
April 18, 2008
Program Design for Data AnalysisProgram Design for Data Analysis
1
Water Quality Assessment Operation
Survey
Monitoring
Surveillance
WQ Assessment Operation
SurveyA finite duration, intensive programto measure, evaluate and report the quality of the aquatic environment for a specific purpose
MonitoringLong-term standardized systemof measurements, observations, evaluations and reporting of the aquatic environmentto define status and trends
SurveillanceContinuous, specific systemof measurements, observations and reportingfor water quality management and operational activities
Monitoring Operation and Surveillance
S u r v e I l l a n c e M O N I T O R I N G OBSERVATION ENVIRONMENTAL NETWORK ASSESSMENT Environmental Management ENVIRONMENTAL ENVIRONMENTAL MODELLING ASSESSMENT M O N I T O R I N G E N V I R O N M E N T A L M A N A G E M E N T
WQ Assessments Programs
Simple monitoring• limited number of samples• simple analysis of observations
Intermediate-level monitoring• specific lab facilities• computer processing and interpretation
Advanced level monitoring• sophisticated techniques• highly trained personal• advanced data analysis and interpretation
Inadequate Assessments Programs
The objectives of the assessment were not properly definedThe program was developed with insufficient knowledge of the water bodyThere was inadequate planning of sampling frequency and analysisDatabase were poorly developedData were improperly interpreted and reported
Impact from Inadequate Sampling Frequency
-3
-2
-1
0
1
2
3
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43
Series1Series2Series3
Observation Network
Source of uncertainties and data misinterpretationMultidimensional nature:• Concentration / value = f (x, y, z, t)• Representative Parameters• Parameters to support analysis
Network parameters:• Temporal – Frequency• Spatial – Discreteness• List of parameters
Spatial Discreteness
RiversUpstream vs. Midstream and DownstreamFall vs. Spring• Surface-groundwater interactions
LakesHydrodynamics / mixingEffects of seasonality• Composite samples vs. lake homogeneity
Water Quality Time Series ComparisonMidstream Rainbow Creek (Total Dissolved Solids)
30
60
90
120
150
180
210
240
270
300
Sep
-88
Apr
-89
Oct
-89
May
-90
Nov
-90
Jun-
91
Dec
-91
Jul-9
2
Jan-
93
Date
Conc
entra
tion
(mg/
L)
WQ04 Rainbow CreekBelow Confluence withMeadow CreekWQ05 Rainbow Creekat Philip Main Bridge
Midstream Rainbow Creek (Total Dissolved Solids)
30
60
90
120
150
180
210
240
270
300
May
-06
Jul-0
6
Aug
-06
Oct
-06
Nov
-06
Jan-
07
Mar
-07
Apr
-07
Jun-
07
Aug
-07
Sep
-07
Date
Conc
entra
tion
(mg/
L)
WQ04 Rainbow CreekBelow Confluence withMeadow Creek
WQ05 Rainbow Creekat Philip Main Bridge
WQ22 Rainbow CreekDownstream of KingRichard Creek
WQ25 Rainbow Creekdownstream of EskerLakes outlet
WQ26 Rainbow Creekdownstream of Site 6stream mounth
Midstream Rainbow Creek (Total Suspended Solids)
0
10
20
30
40
50
60
Sep
-88
Apr
-89
Oct
-89
May
-90
Nov
-90
Jun-
91
Dec
-91
Jul-9
2
Jan-
93
Date
Conc
entr
atio
n (m
g/L)
WQ04 Rainbow CreekBelow Confluence withMeadow CreekWQ05 Rainbow Creekat Philip Main Bridge
Midstream Rainbow Creek (Total Suspended Solids)
0
10
20
30
40
50
60
May
-06
Jul-0
6
Aug
-06
Oct
-06
Nov
-06
Jan-
07
Mar
-07
Apr
-07
Jun-
07
Aug
-07
Sep
-07
Date
Conc
entr
atio
n (m
g/L)
WQ04 Rainbow CreekBelow Confluence withMeadow Creek
WQ05 Rainbow Creekat Philip Main Bridge
WQ25 Rainbow Creekdownstream of EskerLakes outlet
WQ26 Rainbow Creekdownstream of Site 6stream mounth
Concentration % source
Concentration % source
Beginning of winter (1 mo)Beginning of winter (1 mo)
End of winterEnd of winter
Lakes Heterogeneity - Winter
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
Lakes Heterogeneity - SummerLakes Heterogeneity - Summer
Concentration % source
Concentration % source
Beginning of summer
Beginning of summer
End of summerEnd of summer
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
Applications:
Water Quality Management – Surveillance
Water Quality Trends – Planning
Water Supply System Example
CITYCITYT
T T
P
River Water Supply System
Riv
er
Wat
er S
uppl
y Sy
stem
I
Includes: • rivers, • reservoirs, • canals • pumping stations• water treatment plants
Problems: • organic and nutrient pollution • algae blooming in reservoirs• bacteria contamination• pesticides and heavy metals• high natural water colour
TP
Water Quality Management Selective Withdrawal
4/12
*77.1 ⎟⎟
⎠
⎞⎜⎜⎝
⎛=
Egqδ
Discharge Q m3/sec
Stability 10-6 cm-1
Withdrawal Layer, m
4 1.0 2.8 4 0.1 5.0 4 0.01 8.9 7 1.0 3.7 7 0.1 6.7 7 0.01 11.8
14 1.0 5.3 14 0.1 9.4 14 0.01 16.7
Q
Win
ter
Sum
mer
Aut
umn
Watershed Water Quality Management
Total Pollutant Annual Loading
LP = Σ (ECPU x AU)
LP Total Pollutant Annual Load (kg/yr)
ECPU Export Coefficient (kg/ha/yr), by land use activity
AU Area of land use type (ha)
Water Quality Indicator (δLp)
δLp = ( Lpi – Lpi+1) / Lpi
Lpi TPAL for the 1st yearLpi+1 TPAL for the next
year (or years)
Potential Land Use Changes (Example)
Trend in Total Pollutant Annual Loadings
(Water Quality Indicator)
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
2003 2004 2005 2006
YearsLp
- tr
end
TN Pollutant Load trend
TP Pollutant Load trend
TSS Pollutant Load trend
Average Pollutant Load trend
0%10%20%30%40%50%60%70%80%90%100%
2003 2004 2005 2006Urban ResidentialPastureForestFeedlot (CFO)Industrial
Water Supply System Structure
Water system includes ponds, reservoirs, and river / creeks• pollution sources: point sources, surface runoff, air
emissions Surface water supply• drinking water (reservoirs)
Recreation (ponds and reservoirs)• swimming, water sports activity, fishing
Water Quality Survey Program
Extensive Survey Program• water sampling• bottom sediments collection• snow collection (before spring snowmelt)
Survey Network with focus on:• spatial heterogeneity of water quality in reservoirs• temporal variability in existing databases• heavy metals in water and sediments• watersheds pollution from deposition to snow
Water Quality Monitoring Design
Evaluation of spatio-temporal heterogeneity in water quality• multivariate statistical analysis (cluster and
regression analysis)• time-series analysis (temporal variations)• historical analysis of pollution loads from bottom
sediments coresRecommendations for• improvement of WQ monitoring networks• concurrent water intakes
Monitor to Support Aquatic Health
Recommended