![Page 1: Yuzhou Luo, Ph.D. AGIS Lab, UC Davis 06/16/ · PDF fileYuzhou Luo, Ph.D. AGIS Lab, UC‐Davis. 06/16/2009. Background and objectives y Contamination of pesticides in water and sediment](https://reader033.vdocument.in/reader033/viewer/2022042801/5a9df49a7f8b9a4a238cb246/html5/thumbnails/1.jpg)
Yuzhou Luo, Ph.D.AGIS Lab, UC‐Davis
06/16/2009
![Page 2: Yuzhou Luo, Ph.D. AGIS Lab, UC Davis 06/16/ · PDF fileYuzhou Luo, Ph.D. AGIS Lab, UC‐Davis. 06/16/2009. Background and objectives y Contamination of pesticides in water and sediment](https://reader033.vdocument.in/reader033/viewer/2022042801/5a9df49a7f8b9a4a238cb246/html5/thumbnails/2.jpg)
Background and objectivesContamination of pesticides in water and sediment
California’s 303(d) list, 2006. Source: SWRCB
![Page 3: Yuzhou Luo, Ph.D. AGIS Lab, UC Davis 06/16/ · PDF fileYuzhou Luo, Ph.D. AGIS Lab, UC‐Davis. 06/16/2009. Background and objectives y Contamination of pesticides in water and sediment](https://reader033.vdocument.in/reader033/viewer/2022042801/5a9df49a7f8b9a4a238cb246/html5/thumbnails/3.jpg)
Background and objectivesContamination of pesticides in water and sedimentBest Management Practices (BMPs)
Grassed waterways Mixed annual cover crop Tailwater pond Riparian buffer
[1] Preventative BMPs (pesticide management; application management; re‐formulation)
[2] Mitigative BMPs:
![Page 4: Yuzhou Luo, Ph.D. AGIS Lab, UC Davis 06/16/ · PDF fileYuzhou Luo, Ph.D. AGIS Lab, UC‐Davis. 06/16/2009. Background and objectives y Contamination of pesticides in water and sediment](https://reader033.vdocument.in/reader033/viewer/2022042801/5a9df49a7f8b9a4a238cb246/html5/thumbnails/4.jpg)
Background and objectivesContamination of pesticides in water and sedimentBest Management Practices (BMPs)Modeling vs. monitoring
Continuous predictionsNot limited by site locationsKey processes/parametersScenario analysis Initialize and
evaluate models
Guide future
monitoring efforts
![Page 5: Yuzhou Luo, Ph.D. AGIS Lab, UC Davis 06/16/ · PDF fileYuzhou Luo, Ph.D. AGIS Lab, UC‐Davis. 06/16/2009. Background and objectives y Contamination of pesticides in water and sediment](https://reader033.vdocument.in/reader033/viewer/2022042801/5a9df49a7f8b9a4a238cb246/html5/thumbnails/5.jpg)
Background and objectivesContamination of pesticides in water and sedimentBest Management Practices (BMPs)Modeling vs. monitoringModeling of pesticide transport and mitigation effectiveness
‐
EPA handbook for developing watershed plans
![Page 6: Yuzhou Luo, Ph.D. AGIS Lab, UC Davis 06/16/ · PDF fileYuzhou Luo, Ph.D. AGIS Lab, UC‐Davis. 06/16/2009. Background and objectives y Contamination of pesticides in water and sediment](https://reader033.vdocument.in/reader033/viewer/2022042801/5a9df49a7f8b9a4a238cb246/html5/thumbnails/6.jpg)
Model development
Transport simulation
SWAT model (USDA)PRZM model (USEPA)Hydrology simulationPesticide transportManagement practicesWeather generation Plant growth
ArcGIS/ArcObjects
Spatial frameworkGeo‐database
developmentSpatial analysisInput preparationOutput visualizationWeb‐GIS
Evaluation system
Statistical evaluationStochastic simulationModel calibrationModel validationUncertainty and
sensitivity analysisScenario analysis
![Page 7: Yuzhou Luo, Ph.D. AGIS Lab, UC Davis 06/16/ · PDF fileYuzhou Luo, Ph.D. AGIS Lab, UC‐Davis. 06/16/2009. Background and objectives y Contamination of pesticides in water and sediment](https://reader033.vdocument.in/reader033/viewer/2022042801/5a9df49a7f8b9a4a238cb246/html5/thumbnails/7.jpg)
Modeling studiesWatershed model
Model developmentModel evaluation
Structural BMPs
Model sensitivityBMP representation
IPM
Integrated pesticide management
Human health risk
Cumulative risk analysis for 13 OPs
Climate change
HydrologyAgricultural runoff
Soil property
Soil data processingImpact on model
performance
Scaling effects
Spatial delineationImpact on model
performance
Field‐scale model
Linear routingEco‐system risk
analysis
![Page 8: Yuzhou Luo, Ph.D. AGIS Lab, UC Davis 06/16/ · PDF fileYuzhou Luo, Ph.D. AGIS Lab, UC‐Davis. 06/16/2009. Background and objectives y Contamination of pesticides in water and sediment](https://reader033.vdocument.in/reader033/viewer/2022042801/5a9df49a7f8b9a4a238cb246/html5/thumbnails/8.jpg)
AcknowledgementCalifornia Water Quality Control BoardCoalition for Urban/Rural Environmental Stewardship (CURES)California Department of Pesticide RegulationProf. Minghua Zhang and other colleagues in the AGIS lab @ UCD
![Page 9: Yuzhou Luo, Ph.D. AGIS Lab, UC Davis 06/16/ · PDF fileYuzhou Luo, Ph.D. AGIS Lab, UC‐Davis. 06/16/2009. Background and objectives y Contamination of pesticides in water and sediment](https://reader033.vdocument.in/reader033/viewer/2022042801/5a9df49a7f8b9a4a238cb246/html5/thumbnails/9.jpg)
[1] SWAT description[2] Model settings for the San Joaquin Valley[3] Model evaluation[4] Model simulation results
![Page 10: Yuzhou Luo, Ph.D. AGIS Lab, UC Davis 06/16/ · PDF fileYuzhou Luo, Ph.D. AGIS Lab, UC‐Davis. 06/16/2009. Background and objectives y Contamination of pesticides in water and sediment](https://reader033.vdocument.in/reader033/viewer/2022042801/5a9df49a7f8b9a4a238cb246/html5/thumbnails/10.jpg)
SWAT model
Soil and Water Assessment Tool, is a surface hydrology and water quality modelDeveloped to quantify the impact of land management practices on water quality at large and complex watershedsModel inputs: weather, land use, soil, stream network, management (fertilizer, pesticide…)Model outputs: stream flow, concentrations of sediment, nutrients, pesticides
![Page 11: Yuzhou Luo, Ph.D. AGIS Lab, UC Davis 06/16/ · PDF fileYuzhou Luo, Ph.D. AGIS Lab, UC‐Davis. 06/16/2009. Background and objectives y Contamination of pesticides in water and sediment](https://reader033.vdocument.in/reader033/viewer/2022042801/5a9df49a7f8b9a4a238cb246/html5/thumbnails/11.jpg)
Pesticide simulation in SWAT“Land phase”: pesticide transport at field scale, to estimate pesticide outputs from a landscape unit“Water phase”
“Land phase”
simulation of pesticide (Neitsch et al., 2005)
![Page 12: Yuzhou Luo, Ph.D. AGIS Lab, UC Davis 06/16/ · PDF fileYuzhou Luo, Ph.D. AGIS Lab, UC‐Davis. 06/16/2009. Background and objectives y Contamination of pesticides in water and sediment](https://reader033.vdocument.in/reader033/viewer/2022042801/5a9df49a7f8b9a4a238cb246/html5/thumbnails/12.jpg)
Pesticide simulation in SWAT“Land phase”“Water/routing phase”: pesticide transport in stream network, to route pesticide fluxes to a downstream site (e.g., watershed outlet)
Convective movement (outflow)Solid‐liquid partitioningDegradationVolatilizationDiffusionSettling/resuspension/burial
![Page 13: Yuzhou Luo, Ph.D. AGIS Lab, UC Davis 06/16/ · PDF fileYuzhou Luo, Ph.D. AGIS Lab, UC‐Davis. 06/16/2009. Background and objectives y Contamination of pesticides in water and sediment](https://reader033.vdocument.in/reader033/viewer/2022042801/5a9df49a7f8b9a4a238cb246/html5/thumbnails/13.jpg)
Landscape characterizationSimulation domainNorthern San Joaquin
Valley watershed
![Page 14: Yuzhou Luo, Ph.D. AGIS Lab, UC Davis 06/16/ · PDF fileYuzhou Luo, Ph.D. AGIS Lab, UC‐Davis. 06/16/2009. Background and objectives y Contamination of pesticides in water and sediment](https://reader033.vdocument.in/reader033/viewer/2022042801/5a9df49a7f8b9a4a238cb246/html5/thumbnails/14.jpg)
Landscape characterizationSimulation domainWatershed delineation15 sub‐basins (by
CVRWQCB)
![Page 15: Yuzhou Luo, Ph.D. AGIS Lab, UC Davis 06/16/ · PDF fileYuzhou Luo, Ph.D. AGIS Lab, UC‐Davis. 06/16/2009. Background and objectives y Contamination of pesticides in water and sediment](https://reader033.vdocument.in/reader033/viewer/2022042801/5a9df49a7f8b9a4a238cb246/html5/thumbnails/15.jpg)
Landscape characterizationSimulation domainWatershed delineationHydrologic Response Unit (HRU) distributionOverlaying land use and
soil maps
![Page 16: Yuzhou Luo, Ph.D. AGIS Lab, UC Davis 06/16/ · PDF fileYuzhou Luo, Ph.D. AGIS Lab, UC‐Davis. 06/16/2009. Background and objectives y Contamination of pesticides in water and sediment](https://reader033.vdocument.in/reader033/viewer/2022042801/5a9df49a7f8b9a4a238cb246/html5/thumbnails/16.jpg)
GIS databasesDEM and stream network
![Page 17: Yuzhou Luo, Ph.D. AGIS Lab, UC Davis 06/16/ · PDF fileYuzhou Luo, Ph.D. AGIS Lab, UC‐Davis. 06/16/2009. Background and objectives y Contamination of pesticides in water and sediment](https://reader033.vdocument.in/reader033/viewer/2022042801/5a9df49a7f8b9a4a238cb246/html5/thumbnails/17.jpg)
GIS databasesDEM and stream networkLand use
![Page 18: Yuzhou Luo, Ph.D. AGIS Lab, UC Davis 06/16/ · PDF fileYuzhou Luo, Ph.D. AGIS Lab, UC‐Davis. 06/16/2009. Background and objectives y Contamination of pesticides in water and sediment](https://reader033.vdocument.in/reader033/viewer/2022042801/5a9df49a7f8b9a4a238cb246/html5/thumbnails/18.jpg)
GIS databasesDEM and stream networkLand useSoil
![Page 19: Yuzhou Luo, Ph.D. AGIS Lab, UC Davis 06/16/ · PDF fileYuzhou Luo, Ph.D. AGIS Lab, UC‐Davis. 06/16/2009. Background and objectives y Contamination of pesticides in water and sediment](https://reader033.vdocument.in/reader033/viewer/2022042801/5a9df49a7f8b9a4a238cb246/html5/thumbnails/19.jpg)
GIS databasesDEM and stream networkLand useSoilWeather: CA Irrigation Management Information System (CDWR) Pesticide use: Pesticide Use Reporting (CDPR)Monitoring data (CDPR and USGS)
Surface Water DatabaseNational Water Information System
![Page 20: Yuzhou Luo, Ph.D. AGIS Lab, UC Davis 06/16/ · PDF fileYuzhou Luo, Ph.D. AGIS Lab, UC‐Davis. 06/16/2009. Background and objectives y Contamination of pesticides in water and sediment](https://reader033.vdocument.in/reader033/viewer/2022042801/5a9df49a7f8b9a4a238cb246/html5/thumbnails/20.jpg)
Simulation designModel initialization and parameterizationTest agents: diazinon and chlorpyrifos
Daily simulations during 1990 though 2005Model calibration
Hydrology (stream flow), and Water quality (sediment, nutrients, and pesticides)
![Page 21: Yuzhou Luo, Ph.D. AGIS Lab, UC Davis 06/16/ · PDF fileYuzhou Luo, Ph.D. AGIS Lab, UC‐Davis. 06/16/2009. Background and objectives y Contamination of pesticides in water and sediment](https://reader033.vdocument.in/reader033/viewer/2022042801/5a9df49a7f8b9a4a238cb246/html5/thumbnails/21.jpg)
Statistical methodsData preparation for model inputs
Descriptive analysis (trend and variability)Spatial aggregationCorrelation and regression
![Page 22: Yuzhou Luo, Ph.D. AGIS Lab, UC Davis 06/16/ · PDF fileYuzhou Luo, Ph.D. AGIS Lab, UC‐Davis. 06/16/2009. Background and objectives y Contamination of pesticides in water and sediment](https://reader033.vdocument.in/reader033/viewer/2022042801/5a9df49a7f8b9a4a238cb246/html5/thumbnails/22.jpg)
Statistical methodsData preparation for model inputsModel calibration
Multiple‐objective functionsShuffled complex evolution (SCE) algorithm
![Page 23: Yuzhou Luo, Ph.D. AGIS Lab, UC Davis 06/16/ · PDF fileYuzhou Luo, Ph.D. AGIS Lab, UC‐Davis. 06/16/2009. Background and objectives y Contamination of pesticides in water and sediment](https://reader033.vdocument.in/reader033/viewer/2022042801/5a9df49a7f8b9a4a238cb246/html5/thumbnails/23.jpg)
Statistical methodsData preparation for model inputsModel calibrationResidue variance analysis for model evaluation
Nash‐Sutcliffe (NS) coefficientRange: ‐∞ ~ 1.0Satisfactory modeling: NS> 0.35Good modeling: NS> 0.75
Root mean square error (RMSE)Coefficient of determination (R2)
∑
∑
−
−−=
jj
jjj
OO
PONS
2
2
)(
)(1
![Page 24: Yuzhou Luo, Ph.D. AGIS Lab, UC Davis 06/16/ · PDF fileYuzhou Luo, Ph.D. AGIS Lab, UC‐Davis. 06/16/2009. Background and objectives y Contamination of pesticides in water and sediment](https://reader033.vdocument.in/reader033/viewer/2022042801/5a9df49a7f8b9a4a238cb246/html5/thumbnails/24.jpg)
Statistical methodsData preparation for model inputsModel calibrationResidue variance analysis for model evaluationUncertainty/sensitivity analysis
Latin Hypercube samplingMonte Carlo simulationSensitivity index (in a central difference numerical scheme)
)(2)()(
)( IPI
IIIPIIP
IPI
IPSI Δ
Δ−−Δ+=
∂∂
=
![Page 25: Yuzhou Luo, Ph.D. AGIS Lab, UC Davis 06/16/ · PDF fileYuzhou Luo, Ph.D. AGIS Lab, UC‐Davis. 06/16/2009. Background and objectives y Contamination of pesticides in water and sediment](https://reader033.vdocument.in/reader033/viewer/2022042801/5a9df49a7f8b9a4a238cb246/html5/thumbnails/25.jpg)
Model evaluation and resultsCalibration/validation at sub‐basin outlets
Simulation results (taken from: Luo et al., 2008. Environmental Pollution, 156:1171‐1181)
![Page 26: Yuzhou Luo, Ph.D. AGIS Lab, UC Davis 06/16/ · PDF fileYuzhou Luo, Ph.D. AGIS Lab, UC‐Davis. 06/16/2009. Background and objectives y Contamination of pesticides in water and sediment](https://reader033.vdocument.in/reader033/viewer/2022042801/5a9df49a7f8b9a4a238cb246/html5/thumbnails/26.jpg)
Stream flow @ watershed
Predicted and observed stream flow
(m3/s) in the San Joaquin River at Vernalis during 1992‐2005
![Page 27: Yuzhou Luo, Ph.D. AGIS Lab, UC Davis 06/16/ · PDF fileYuzhou Luo, Ph.D. AGIS Lab, UC‐Davis. 06/16/2009. Background and objectives y Contamination of pesticides in water and sediment](https://reader033.vdocument.in/reader033/viewer/2022042801/5a9df49a7f8b9a4a238cb246/html5/thumbnails/27.jpg)
Stream flows @ subbasins
![Page 28: Yuzhou Luo, Ph.D. AGIS Lab, UC Davis 06/16/ · PDF fileYuzhou Luo, Ph.D. AGIS Lab, UC‐Davis. 06/16/2009. Background and objectives y Contamination of pesticides in water and sediment](https://reader033.vdocument.in/reader033/viewer/2022042801/5a9df49a7f8b9a4a238cb246/html5/thumbnails/28.jpg)
Sediment @ watershed
Predicted and observed sediment load
(kg/month) in the San Joaquin River at Vernalis during 1992‐2005
![Page 29: Yuzhou Luo, Ph.D. AGIS Lab, UC Davis 06/16/ · PDF fileYuzhou Luo, Ph.D. AGIS Lab, UC‐Davis. 06/16/2009. Background and objectives y Contamination of pesticides in water and sediment](https://reader033.vdocument.in/reader033/viewer/2022042801/5a9df49a7f8b9a4a238cb246/html5/thumbnails/29.jpg)
Diazinon @ watershed
Predicted and observed dissolved diazinon loads
(kg/month) in the San Joaquin River at Vernalis during 1992‐2005
![Page 30: Yuzhou Luo, Ph.D. AGIS Lab, UC Davis 06/16/ · PDF fileYuzhou Luo, Ph.D. AGIS Lab, UC‐Davis. 06/16/2009. Background and objectives y Contamination of pesticides in water and sediment](https://reader033.vdocument.in/reader033/viewer/2022042801/5a9df49a7f8b9a4a238cb246/html5/thumbnails/30.jpg)
Chlorpyrifos @ watershed
Predicted and observed dissolved chlorpyrifos loads (kg/month) in the San Joaquin River at Vernalis during 1992‐2005
![Page 31: Yuzhou Luo, Ph.D. AGIS Lab, UC Davis 06/16/ · PDF fileYuzhou Luo, Ph.D. AGIS Lab, UC‐Davis. 06/16/2009. Background and objectives y Contamination of pesticides in water and sediment](https://reader033.vdocument.in/reader033/viewer/2022042801/5a9df49a7f8b9a4a238cb246/html5/thumbnails/31.jpg)
Pesticides @ subbasins
![Page 32: Yuzhou Luo, Ph.D. AGIS Lab, UC Davis 06/16/ · PDF fileYuzhou Luo, Ph.D. AGIS Lab, UC‐Davis. 06/16/2009. Background and objectives y Contamination of pesticides in water and sediment](https://reader033.vdocument.in/reader033/viewer/2022042801/5a9df49a7f8b9a4a238cb246/html5/thumbnails/32.jpg)
[1] Interpretation of model results[2] Model sensitivity analysis and simulations for
structural BMPs
![Page 33: Yuzhou Luo, Ph.D. AGIS Lab, UC Davis 06/16/ · PDF fileYuzhou Luo, Ph.D. AGIS Lab, UC‐Davis. 06/16/2009. Background and objectives y Contamination of pesticides in water and sediment](https://reader033.vdocument.in/reader033/viewer/2022042801/5a9df49a7f8b9a4a238cb246/html5/thumbnails/33.jpg)
Modeling for managementDetermine temporal variation in pesticide yieldIndicate “hot‐spots” of pesticide loadings/exposure
Areas with high pesticide useAreas with high pesticide runoff potentialAreas contributing to high pesticide concentrations
Predict effectiveness of pesticide management and structural BMPs in improving water qualityConduct scenario analysis for management planning
![Page 34: Yuzhou Luo, Ph.D. AGIS Lab, UC Davis 06/16/ · PDF fileYuzhou Luo, Ph.D. AGIS Lab, UC‐Davis. 06/16/2009. Background and objectives y Contamination of pesticides in water and sediment](https://reader033.vdocument.in/reader033/viewer/2022042801/5a9df49a7f8b9a4a238cb246/html5/thumbnails/34.jpg)
SeasonalityLAPU (load as percent of use) = load/useHigh LAPU for dormant (wet) seasonBased on simulation of chlorpyrifos during 1992‐2005
Annual overall LAPU: 0.03% During January and February, LAPU=0.12%6.6% of chlorpyrifos application in January and February, generating 28.5% of chlorpyrifos load
![Page 35: Yuzhou Luo, Ph.D. AGIS Lab, UC Davis 06/16/ · PDF fileYuzhou Luo, Ph.D. AGIS Lab, UC‐Davis. 06/16/2009. Background and objectives y Contamination of pesticides in water and sediment](https://reader033.vdocument.in/reader033/viewer/2022042801/5a9df49a7f8b9a4a238cb246/html5/thumbnails/35.jpg)
Spatial distributionHigher pesticide runoff potential in the western watersheds of the San Joaquin River
Annual average pesticide yields (g/km2) during 1998‐2005 (Luo et al., 2008)
![Page 36: Yuzhou Luo, Ph.D. AGIS Lab, UC Davis 06/16/ · PDF fileYuzhou Luo, Ph.D. AGIS Lab, UC‐Davis. 06/16/2009. Background and objectives y Contamination of pesticides in water and sediment](https://reader033.vdocument.in/reader033/viewer/2022042801/5a9df49a7f8b9a4a238cb246/html5/thumbnails/36.jpg)
Spatial distributionHigher pesticide runoff potential in the western watersheds of the San Joaquin RiverRelationship to topography and soil propertiesRelationship to hydrologic condition
Risks to aquatic ecosystem: Exposure events of chlorpyrifos (>0.015 µg/L): 42.2% of 1990‐2005 in Orestimba Creek
Areas with high runoff potential and ecosystem risk were indicated for future monitoring and mitigation efforts
![Page 37: Yuzhou Luo, Ph.D. AGIS Lab, UC Davis 06/16/ · PDF fileYuzhou Luo, Ph.D. AGIS Lab, UC‐Davis. 06/16/2009. Background and objectives y Contamination of pesticides in water and sediment](https://reader033.vdocument.in/reader033/viewer/2022042801/5a9df49a7f8b9a4a238cb246/html5/thumbnails/37.jpg)
Sensitivity analysis (“land phase”)
![Page 38: Yuzhou Luo, Ph.D. AGIS Lab, UC Davis 06/16/ · PDF fileYuzhou Luo, Ph.D. AGIS Lab, UC‐Davis. 06/16/2009. Background and objectives y Contamination of pesticides in water and sediment](https://reader033.vdocument.in/reader033/viewer/2022042801/5a9df49a7f8b9a4a238cb246/html5/thumbnails/38.jpg)
Sensitivity analysis (“water phase”)
![Page 39: Yuzhou Luo, Ph.D. AGIS Lab, UC Davis 06/16/ · PDF fileYuzhou Luo, Ph.D. AGIS Lab, UC‐Davis. 06/16/2009. Background and objectives y Contamination of pesticides in water and sediment](https://reader033.vdocument.in/reader033/viewer/2022042801/5a9df49a7f8b9a4a238cb246/html5/thumbnails/39.jpg)
BMP representation with SWATSimulated by built‐in functions in SWAT
Vegetated filter stripsSediment ponds
Implemented by altering model parameters, e.g.,Residue management: reduce SCS curve number (CN2) and USLE practice factor (USLE_K), increaseroughness for overland flow (OV_N)Grassed waterway: reduce channel erosion coefficients (CH_COV and CH_EROD), increase roughness for channel flow (CH_N2)
![Page 40: Yuzhou Luo, Ph.D. AGIS Lab, UC Davis 06/16/ · PDF fileYuzhou Luo, Ph.D. AGIS Lab, UC‐Davis. 06/16/2009. Background and objectives y Contamination of pesticides in water and sediment](https://reader033.vdocument.in/reader033/viewer/2022042801/5a9df49a7f8b9a4a238cb246/html5/thumbnails/40.jpg)
Predicted effectiveness
•Pond dimensions are determined by USDA NRCS Technical Guide; an
operating depth of 2.44 m (8 ft) is used based on field survey.• Residue management is parameterized for 500 kg/ha residue
![Page 41: Yuzhou Luo, Ph.D. AGIS Lab, UC Davis 06/16/ · PDF fileYuzhou Luo, Ph.D. AGIS Lab, UC‐Davis. 06/16/2009. Background and objectives y Contamination of pesticides in water and sediment](https://reader033.vdocument.in/reader033/viewer/2022042801/5a9df49a7f8b9a4a238cb246/html5/thumbnails/41.jpg)
Effectiveness of grassed waterway
0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.40
50
100
150
pest
icid
e lo
ad (g
/mon
)
0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.40
1000
2000
3000
channel roughness coefficients (Manning's "n")
sedi
men
t loa
d (to
n/m
on)
Sensitivity of CHN2 on chlorpyrifos load at the Orestimba Creek outlet
dissolved phaseparticulate phasetotal pesticide
![Page 42: Yuzhou Luo, Ph.D. AGIS Lab, UC Davis 06/16/ · PDF fileYuzhou Luo, Ph.D. AGIS Lab, UC‐Davis. 06/16/2009. Background and objectives y Contamination of pesticides in water and sediment](https://reader033.vdocument.in/reader033/viewer/2022042801/5a9df49a7f8b9a4a238cb246/html5/thumbnails/42.jpg)
ConclusionsSWAT model could be reliably used to simulate monthly hydrologic and water quality parameters in the Lower San Joaquin River watershed;Factors for the spatial and temporal variability of OP pesticide loads in surface water
Magnitude and timing of surface runoffMagnitude and timing of pesticide applicationsSoil propertiesPesticide properties related to processes in soil
![Page 43: Yuzhou Luo, Ph.D. AGIS Lab, UC Davis 06/16/ · PDF fileYuzhou Luo, Ph.D. AGIS Lab, UC‐Davis. 06/16/2009. Background and objectives y Contamination of pesticides in water and sediment](https://reader033.vdocument.in/reader033/viewer/2022042801/5a9df49a7f8b9a4a238cb246/html5/thumbnails/43.jpg)
ConclusionsSWAT model could be reliably used to simulate monthly hydrologic and water quality parameters in the Lower San Joaquin River watershed;Factors for the spatial and temporal variability of OP pesticide loads in surface water;Management implications
Pesticide loads could be significantly reduced by decreasing use amounts during dormant (wet) seasonAreas with high pesticide yields were identified and could be candidates for further management evaluations
![Page 44: Yuzhou Luo, Ph.D. AGIS Lab, UC Davis 06/16/ · PDF fileYuzhou Luo, Ph.D. AGIS Lab, UC‐Davis. 06/16/2009. Background and objectives y Contamination of pesticides in water and sediment](https://reader033.vdocument.in/reader033/viewer/2022042801/5a9df49a7f8b9a4a238cb246/html5/thumbnails/44.jpg)
ReferenceLuo, Y., et al., 2008. Dynamic Modeling of Organophosphate Pesticide Load in Surface Water in the Northern San Joaquin Valley of California. Environmental Pollution, 156(3): 1171‐1181Luo, Y. and M. Zhang, 2009. Multimedia Transport and Risk Assessment of Organophosphate Pesticides and a Case Study in theNorthern San Joaquin Valley of California. Chemosphere, 75(7):969‐978Luo, Y. and M. Zhang, 2009. A Geo‐Referenced Modeling Environment for Ecosystem Risk Assessment: Organophosphate Pesticides in an Agricultural Dominated Watershed. Journal of Environmental Quality, 38(2): 664‐674Luo, Y. and M. Zhang, 2009. Management‐Oriented Sensitivity Analysis for Pesticide Transport in Watershed‐Scale Water Quality Modeling. Environmental Pollution (In review)