nutrient modeling overview
TRANSCRIPT
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a da ab
erNutrient Modeling
Ov viewOverview
Mazdak Arabi Professor Civil and Environmental Engineering Colorado State University
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Ov viewOverview
Role of models in watershed management
A simple continuum of model types
Complexity and uncertainty
Review of a few commonly used modelsReview of a few commonly used models
Case study
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t
Model Applica ionModel Application
� The implication of changing land use and climate
� The implication of anthropogenic activities � The implication of anthropogenic activities
� Urban water management
� Nutrient trading
� Emerging contaminants
� Analysis of alternative management scenarios and policy
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Model ContinuumModel Continuum
Total Uncertainty
Less Complex Empirical/Statistical
More Complex Physically‐Based/Deterministic
Point of Minimum Uncertainty
Empirical/Statistical Physically Based/Deterministic
Less Data Intensive Rigid
More Parameters More Data Intensive Rigid
Trend Analysis More Data Intensive
Flexible Process Specific Analysis
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Total Uncertainty
Less Complex Empirical/Statistical
More Complex Physically‐Based/MechanisticEmpirical/Statistical Physically Based/Mechanistic
GS ssion
ROW
WLF
AL2E
WMM
WASP
WAT
GNPS
HSPF
USG
Regres
SPARR GW
QUA
SW W SW
AnnAG H
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Important Considerations in pSelection of A Model
� Type of analysis: trend analysis or process details
� Critical hydrologic and water quality processes � Critical hydrologic and water quality processes
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Hydrologic Balance
Precipitation
Evaporation and Transpiration
Root Zone Infiltration/plant uptake/ Soil moisture redistribution
Surface Runoff
Sh ll
Vadose (unsaturated)
Zone
moisture redistribution Lateral Flow
Revap from Percolation to Shallow (unconfined)
Aquifer
Confining Layer
Return Flow
Revap from shallow aquifer
Percolation to shallow aquifer
Deep (confined) Aquifer Recharge to
deep aquifer Flow out of watershed
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ocessesUpland PrUpland Processes
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In-Stream Processes & Point Sources
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Important Considerations in pSelection of Models
� Type of analysis: trend analysis or process details
� Critical hydrologic and water quality processes
� Time-step: hourly (or less) to annual, storm event, steady-state
� Spatial scale: field-scale versus watershed scale
� LLumpedd versus didistributted: grid ids, HRUHRUs� t ib d
� Urban, agricultural, and forested systems
�� Point and nonpoint sources Point and nonpoint sources
� Representation of BMPs and conservation practices
� Level of expertise, data requirement, user interface, tech support, …
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Scale and Water Qualityy Variables
MODEL Time Step Spatial Scale
Water Quality
USGS Regression Annual Large basins Nutrients
SPARROW Annual Large basins Sediment, Nutrient, Pesticides
GWLF Monthly HUC12, 8 Sediment, Nutrient
QUAL2E Steady-St. Water body TN, TP, NH3, DO, chlorophyll a, pathogens
WASP Hourly Water body TN, TP, NH3, DO, chlorophyll a,TSS, Toxics
SWMM Sub-Daily Small basins Sediment, Nutrient, Pesticide, Metals, BOD
SWAT Daily M-L basins Sediment, Nutrient, Pesticide, Metals, BOD
HSPF Sub-Daily M-L basins Sediment, Nutrient, Pesticide, Metals, BOD
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Scale and Water Qualityy Variables
MODEL Time Step Spatial Scale
Water Quality
USGS Regression Annual Large basins Nutrients
SPARROW Annual Large basins Sediment, Nutrient, Pesticides
GWLF Monthly HUC12, 8 Sediment, Nutrient
QUAL2E Steady-St. Water body TN, TP, NH3, DO, chlorophyll a, pathogens
WASP Hourly Water body TN, TP, NH3, DO, chlorophyll a,TSS, Toxics
SWMM Sub-Daily Small basins Sediment, Nutrient, Pesticide, Metals, BOD
SWAT Daily M-L basins Sediment, Nutrient, Pesticide, Metals, BOD
HSPF Sub-Daily M-L basins Sediment, Nutrient, Pesticide, Metals, BOD
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Delivery of N and P to the yGulf of Mexico: SPARROW
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er Sources of Nutrients
Deliv ed to the Gulf ofDelivered to the Gulf of Mexico: SPARROW
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Scale and Water Qualityy Variables
MODEL Time Step Spatial Scale
Water Quality
USGS Regression Annual Large basins Nutrients
SPARROW Annual Large basins Sediment, Nutrient, Pesticides
GWLF Monthly HUC12, 8 Sediment, Nutrient
QUAL2E Steady-St. Water body TN, TP, NH3, DO, chlorophyll a, pathogens
WASP Hourly Water body TN, TP, NH3, DO, chlorophyll a,TSS, Toxics
SWMM Sub-Daily Small basins Sediment, Nutrient, Pesticide, Metals, BOD
SWAT Daily M-L basins Sediment, Nutrient, Pesticide, Metals, BOD
HSPF Sub-Daily M-L basins Sediment, Nutrient, Pesticide, Metals, BOD
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Land and Water Features Supported
MODEL Urban Ag / Rural
Forest River Lake Reservoir Coastal / Estuary
USGS Regression
SPARROW
GWLF
QUAL2E
WASP
SWMM
SWAT
HSPF
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t t t
Management PracticesManagement Practices
MODEL BMPs
USGS Regression
SPARROW Wetlands SPARROW Wetlands
GWLF Vegetative practices
SWMM Detention basins, Infiltration practices, Wetlands, Ponds, Stormwater
SWAT Agricultural conservation practices, Detention basins, Infiltration ti P d V ti ti I i ti Til d i S SWAT practices, Ponds, Vegetative practices, Irrigation, Tile drains, Street
sweeping, Wetlands
HSPF Nutrient management, Contouring, Terracing, Ponds, Wetlands
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Model Application: Standard ppProtocol
� Application of watershed models requires rigorous planning.
� Use of a modeling protocol serves a number of benefits g p
� Reduce potential modeler bias
� Providing a roadmap to be followed � Providing a roadmap to be followed
� Allow others to assess decisions made in modeling
� Allow others to repeat the study, and
� Improve acceptance of model results
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Modeling ProtocolModeling Protocol
� Define Purpose � Select Model � Collect Data � Sensitivity Analysis � Calibration and Corroboration (Testing) � Uncertainty Analysis � Scenario Analysis � Results Interpretation and communication of uncertainty � Postaudit
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Eagle Creek Watershed, IN
Source of drinking water for city of Indianapolis
High : 298
Low : 239.
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Flow and Load Duration Curves
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Calibration and TestingCalibration and Testing Importance of rule of thumb measures
� Calibration is typically performed based on simulation of fluxes of flow, particles and chemicals at stream locations
� Error statistics: relative error, R2, Nash-Sutcliffe efficiency coefficient, …
� Multisite multivariable calibration
� Rule of thumb measures, e.g.,
� Nitrate from tile drains
� Denitrification
� Management implications
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StNitrogen Loss Rate in
Streams Alexander et al., 2000, Nature
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eas co u ca ed s a e o de s
emar s
Closing R kClosing Remarks
� Data collection and assimilation is challenging, in particular management data
� Despite significant progress, comprehensive models require extensive knowledge of GIS and model componentscomponents
� Existing models rarely provide outputs that can be easily communicated with stakeholdersy
� The need for a standard modeling approach
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F t C lli CO 80523
Questions? Comments?Questions? Comments?
Mazdak Arabi
1372 Campus Delivery Fort Collins, CO 80523
(970) 491-4639