CEE 795 Water Resources Modeling and GIS Learning Objectives: Describe the steps in hydrologic modeling Evaluate different types of hydrologic models Summarize.

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CEE 795 Water Resources Modeling and GIS Learning Objectives: Describe the steps in hydrologic modeling Evaluate different types of hydrologic models Summarize the components of AGWA Handouts: Assignments: Lecture 8: Hydrologic Modeling and AGWA April 3, 2006

Hydrologic/Watershed Modeling Thomas Piechota, Ph.D., P.E. Department of Civil and Environmental Engineering University of Nevada, Las Vegas

Definitions Watershed: area that topographically contributes to the drainage to a point of interest Streamflow: runoff (rate or volume) at a specified point in a watershed. Hydrologic budget: accounting of water in a system.

Conceptual Model of Watershed Modeling Typical Input Topography Soil Characteristics Land cover Land use Meteorological data Typical Output Streamflow Subsurface Flow Depth to water table

Steps to Hydrologic Modeling 1.Delineate watershed 2.Obtain hydrologic and geographic data 3.Select modeling approach 4.Calibrate/Verify model 5.Use model for assessment/prediction/design

What is a Watershed? Area that topographically contributes to the drainage to a point of interest Natural Watershed Points of Interest Road crossing Stream gage Reservoir inlet Wastewater treatment plant Location of stream restoration

Urban Watershed

USGS Quad Map

Digital Elevation Model (DEM) Digital file that stores the elevation of the land surface a specified grid cell size (e.g., 30 meters)

Steps to Hydrologic Modeling 1.Delineate watershed 2.Obtain hydrologic and geographic data 3.Select modeling approach 4.Calibrate/Verify model 5.Use model for assessment/prediction/design

Geographic Data Land coverLand use

Geographic Data Soil type/classification

Hydrologic Data Meteorological Data –Temperature –Precipitation –Wind speed –Humidity Extrapolation of point measurements –Theissen Polygons –Inverse distance weighting

Hydrologic Data –Streamflow Peak discharge Daily flow volume Annual flow volume –Soil moisture –Groundwater level Streamflow

Steps to Hydrologic Modeling 1.Delineate watershed 2.Obtain hydrologic and geographic data 3.Select modeling approach 4.Calibrate/Verify model 5.Use model for assessment/prediction/design

Modeling Approaches (examples) TIME SCALE Event-based (minute to day) Continuous Simulation (days – years) Empirical Regression equ’s Transfer Functions Simple models Rational Method SCS Unit HydrographSimple Model Physically-based Based on physical processes Complicated Many parameters KINEROS Stanford Watershed Model TOPMODEL SWAT VIC-3L TOPMODEL

Basis for Many Hydrologic Models Hydrologic Budget (In – Out = ΔStorage) Watershed Precipitation (P) Groundwater in (GW in ) Evaporation (E) Transpiration (T) Streamflow (Q) Groundwater out (GW out ) Reservoir Infiltration (I) (P + GW in ) – (E + T + I + GW out + Q) = ΔStorage reservoir

Which Model Should be Used? It Depends on: –What time scale are you working at? –What hydrologic quantity are you trying to obtain? –What data do you have for your watershed? –How fast of a computer do you have?

Spatial Scaling of Models Lumped Parameters assigned to each subbasin A1A1 A2A2 A3A3 Fully-Distributed Parameters assigned to each grid cell Semi-Distributed Parameters assigned to each grid cell, but cells with same parameters are grouped

Stanford Watershed Model (HSPF) Physically-based and continuous simulation

Kinematic Runoff and Erosion Model (KINEROS) Developed by USDA Event oriented & physically based Describes the processes of interception, infiltration, surface runoff and erosion

TOPMODEL Semi-distributed & physically-based Relates hydrologic processes (e.g., overland flow, subsurface flow) to topographic characteristics of watershed Efficiency of lumped model and physical theory of a distributed model Infiltration Drainage Macropore Flow Subsurface Flow Total Flow Overland Flow Source Area Precipitation Evapotranspiration

TOPMODEL Example

Variable Infiltration Capacity (VIC-3L) Continuous simulation and physically-based Macroscale hydrologic model that solves full water and energy balances

VIC-3L Example

Steps to Hydrologic Modeling 1.Delineate watershed 2.Obtain hydrologic and geographic data 3.Select modeling approach 4.Calibrate/Verify model 5.Use model for assessment/prediction/design

Calibrating a Model Typically the model is calibrated against observed streamflow data Depending on the model complexity, parameters are adjusted until observed streamflow equals model streamflow Which observed value to use: –Q peak –Q volume –t peak Q peak Q t t peak Q volume

Sensitive Parameters Precipitation Soil parameters –Hydraulic conductivity –Soil water holding capacity Evaporation (for continuous simulation) Flow routing parameters (for event- based)

Uncertainties Precipitation –Extrapolation of point to other areas –Temporal resolution of data Soils information –Surveys are based on site visits and then extrapolated Routing parameters –Usually assigned based on empirical studies

Steps to Hydrologic Modeling 1.Delineate watershed 2.Obtain hydrologic and geographic data 3.Select modeling approach 4.Calibrate/Verify model 5.Use model for assessment/prediction/design

Use of Models Assessment –What happens if land use/land cover is changed? Prediction –Flood forecasting Design –How much flow will occur in a 100 year storm?

AUTOMATED GEOSPATIAL WATERSHED ASSESSMENT A GIS-BASED WATERSHED MODELING TOOL William Kepner and Darius Semmens US – EPA Landscape Ecology Branch Las Vegas, NV David Goodrich, Mariano Hernandez, Shea Burns, Averill Cate, Soren Scott, and Lainie Levick USDA-ARS Southwest Watershed Research Center, Tucson, AZ Phillip Guertin University of Arizona, Tucson, AZ Scott Miller University of Wyoming, Laramie, WY

Project Background & Acknowledgements Long-Term Research Project – Landscape Ecology Branch – 5 years Interdisciplinary – Watershed management – Landscape ecology – Atmospheric modeling – Remote sensing – GIS Multi-Agency – USDA – ARS – US – EPA – University of Arizona – University of Wyoming – USGS Student Support – 2 Post-Doc – 2 PhD – 2 Masters USDA-ARS David Goodrich Mariano Hernandez Averill Cate Ian Burns Casey Tifft Soren Scott US-EPA Bill Kepner Darius Semmens Dan Heggem Bruce Jones Don Ebert University of Arizona Phil Guertin University of Wyoming Scott Miller

PC-based GIS tool for watershed modeling –KINEROS & SWAT (modular) Investigate the impacts of land-use/cover change on runoff, erosion, and water quality at multiple scales Compare and visualize results Targeted for use by research scientists and management specialists Useful in conducting TMDL analyses Widely applicable Introduction

Used with US-EPA Analytical Tool Interface for Landscape Assessment (ATtILA) Simple, direct method for model parameterization Provide accurate, repeatable results Require basic, attainable GIS data –30m USGS DEM (free, US coverage) –STATSGO soil data (free, US coverage) –US-EPA NALC & MRLC landscape data (regional) Useful for scenario development, alternative futures simulation work. Objectives of the AGWA tool

(SWAT) Daily time step Distributed: empirical and physically-based model Hydrology, sediment, nutrient, and pesticide yields Larger watersheds (> 1,000 km 2 ) Similar effort used by BASINS Soil and Water Assessment Tool pseudo- channel 71 channel 73 Abstract Routing Representation to next channel

(KINEROS2) Event-based (< minute time steps) Distributed: physically-based model with dynamic routing Hydrology, erosion, sediment transport Smaller watersheds (< 100 km 2 ) Kinematic Runoff and Erosion Model Abstract Routing Representation

AGWA ArcView Interface

Watershed Discretization (model elements) + Land Cover Soils Rain (Observed or Design Storm) Results Run model and import results Intersect model elements with Watershed Delineation using Digital Elevation Model (DEM) Sediment yield (t/ha)Sediment discharge (kg/s) Water yield (mm)Channel Scour (mm) Transmission loss (mm)Peak flow (m 3 /s or mm/hr) Channel Disch. (m 3 /day)Sediment yield (kg) Percolation (mm)Runoff (mm or m 3 ) ET (mm)Plane Infiltration (mm) Precipitation (mm)Channel Infiltration (m 3 /km) SWAT OutputsKINEROS Outputs AGWA Conceptual Design: Inputs and Outputs Output results that can be displayed in AGWA

PROCESS runoff, sediment hydrograph time runoff STATSGO NALC, MRLC USGS 7.5' DEM Conceptual Design of AGWA Build Model Input Files Derive Secondary Parameters look-up tables Characterize Model Elements f (land cover, topography, soils) Discretize Watershed f (topography) View Model Results link model to GIS Build GIS Database PRODUCTS Contributing Source Area Gravelly loam Soil  Ks = 9.8 mm/hr  G = 127 mm  Por. = intensity time 10-year, 30-minute event

Navigating Through AGWA Subdivide Watershed Into Model Elements SWATKINEROS Generate rainfall input files Daily Rainfall from…  Gauge locations  Thiessen map  Pre-defined continuous record Storm Event from…  NOAA Atlas-II  Pre-defined return-period / magnitude  “Create-your-own” Intersect Soils & Land Cover Generate Watershed Outline grid polygon Choose the model to run look-up tables

Navigating Through AGWA, Cont’d… Subwatersheds & Channels Continuous Rainfall Records Prepare input data Run The Hydrologic Model & Import Results Display/Compare Results SWAT outputs: Runoff, water yield (mm) Channel Discharge (m 3 /day) Evapotranspiration (mm) Percolation (mm) Transmission Losses (mm) Sediment Yields (mm) Channel & Plane Elements Event (Return Period) Rainfall KINEROS outputs: Runoff (mm,m 3 ) Sediment Yield (kg/ha) Infiltration (mm) Transmission losses (m 3 /km) Peak runoff rate (m 3 /s) Peak sediment discharge (kg/s) external to AGWA Visualization for each model element

NLCD Land coverABCD Cover (%) High intensity residential (22) Bare rock/sand/clay (31) Forest (41) Shrubland (51) Grasslands/herbaceous (71) Small grains (83) CURVE NUMBER Hydrologic Soil Group SWAT Parameter Estimation - Example: Curve Number from NLCD land cover  Higher numbers result in higher runoff

Texture Ksat Suction Porosity Smax CV Sand Silt Clay Dist Kff Clay Fractured Bedrock Clay Loam Sandy Clay Loam Silt Loam Sandy Loam Gravel KINEROS Parameter Estimation  Parameters based on soil texture (STATSGO, SSURGO, FAO)  Parameters based on land-cover classification (e.g. NLCD) Land Cover Type Interception (mm/hr) Canopy (%) Manning's n Forest Oak Woodland Mesquite Woodland Grassland Desertscrub Riparian Agriculture Urban

AZ061 Component 1 20% Component 2 45% Component 3 35% 9 inches Layer 1 Layer 2 Layer Layers for component 3 Components for MUID AZ061 Intersection of model element with soils map AGWA Soil Weighting (KINEROS) Area and depth weighting of soil parameters Area weighting of averaged MUID values for each watershed element AZ076 AZ067

Parameter Manipulation (optional) Ksat Can manually change parameters for each channel and plane element Stream channel attributes Upland plane attributes Ksat

Automated tracking of simulation inputs Calculate and view differences between model runs Multiple simulation runs for a given watershed Color-ramping of results for each element to show spatial variability Visualization of Results

Spatial and Temporal Scaling of Results High urban growth Upper San Pedro River Basin >WY Water yield change between 1973 and 1997 SWAT Results Sierra Vista Subwatershed KINEROS Results N Forest Oak Woodland Mesquite Desertscrub Grassland Urban 1997 Land Cover Concentrated urbanization  Using SWAT and KINEROS for integrated watershed assessment  Land cover change analysis and impact on hydrologic response

Urbanization Effects (KINEROS2) Pre-urbanization 1973 Land cover Post-urbanization 1997 Land cover Results from pre- and post-urbanization simulations using the 10-year, 1-hour design storm event

Limitations of GIS - Model Linkage Model Parameters are based on look-up tables - need for local calibration for accuracy - FIELD WORK! Subdivision of the watershed is based on topography - prefer it be based on intersection of soil, lc, topography No sub-pixel variability in source (GIS) data - condition, temporal (seasonal, annual) variability - MRLC created over multi-year data capture No model element variability in model input - averaging due to upscaling Most useful for relative assessment unless calibrated

Land-Cover Modification Tool  Allows users to build management scenarios  Location of land-cover alterations specified by either drawing a polygon on the display, or specifying a polygon map Types of Land-Cover Changes: Change entire user-defined area to new land cover Change one land-cover type to another in user-defined area Change land-cover type within user-supplied polygon map Create a random land-cover pattern e.g. to simulate burn pattern, change to 64% barren, 31% desert scrub, and 5% mesquite woodland

Alternative Futures: Base Change Scenarios 1.CONSTRAINED – Assumes population increase less than 2020 forecast (78,500). Development in existing areas, e.g. 90% urban. 2.PLANS – Assumes population increase as forecast for 2020 (95,000). Development in mostly existing areas, e.g. 80% urban and 15% suburban. 3.OPEN – Assumes population increase more than 2020 forecast (111,500). Most constraints on land development removed. Development occurs mostly into rural areas (60%) and less in existing urban areas (15%).

Percent Change in Runoff under Future Scenarios There is considerable variation – particularly between extremes produced by constrained and open scenarios (Kepner et al., 2004) Surface runoff will increase in all three scenarios Sediment yield will increase especially as new surfaces are disturbed and surface runoff increases (Derived from using future land covers and AGWA)

Plans

Applications of National & International Significance National NYCDEP – Catskill/Delaware watershed assessmentNYCDEP – Catskill/Delaware watershed assessment Upper San Pedro Partnership – watershed planning, cost-benefit analysisUpper San Pedro Partnership – watershed planning, cost-benefit analysis EMAP – Oregon (AGWA-ATtILA) integrated alternative futures assessmentEMAP – Oregon (AGWA-ATtILA) integrated alternative futures assessment ReVA – SEQL alternative futuresReVA – SEQL alternative futures EPA Region 9 – CWA 404 and NEPAEPA Region 9 – CWA 404 and NEPA EPA Region 10 – 404/NEPA, transportation planningEPA Region 10 – 404/NEPA, transportation planning NWS – Real-time flood warningNWS – Real-time flood warning USFS – Post-fire assessment & rehabilitation planningUSFS – Post-fire assessment & rehabilitation planning AZ – State is using AGWA for TMDL planning and education of municipal officialsAZ – State is using AGWA for TMDL planning and education of municipal officialsInternational NATO Committee on the Challenges to Modern Society (CCMS) – Integrated hydrologic/ecological landscape change assessmentNATO Committee on the Challenges to Modern Society (CCMS) – Integrated hydrologic/ecological landscape change assessment Southwest Consortium for Environmental Research and Policy (SCERP) – U.S./Mexico trans-border watershed managementSouthwest Consortium for Environmental Research and Policy (SCERP) – U.S./Mexico trans-border watershed management UNESCO Global Network for Water and Development Information (G-WADI) – International arid-region hydrologic modelingUNESCO Global Network for Water and Development Information (G-WADI) – International arid-region hydrologic modeling

AGWA 1.1 released at the Fed. Interagency Hydrologic Modeling Conference, July 2002AGWA 1.1 released at the Fed. Interagency Hydrologic Modeling Conference, July 2002 Externally peer-evaluated through two separate federal review processes (EPA/600/R-02/046 & ARS/137460)Externally peer-evaluated through two separate federal review processes (EPA/600/R-02/046 & ARS/137460) AGWA added toAGWA added to EPA Council for Regulatory Environmental Modeling (CREM) databaseEPA Council for Regulatory Environmental Modeling (CREM) database NASA Applied Sciences Directorate model and analysis systemsNASA Applied Sciences Directorate model and analysis systems USGS Surface-water Modeling Interest Group archivesUSGS Surface-water Modeling Interest Group archives AGWA 1.4 released in July, 2004AGWA 1.4 released in July, 2004 AGWA integrated into BASINS 3.1 release, August 2004AGWA integrated into BASINS 3.1 release, August 2004 Training – national and internationalTraining – national and international Free public download and full documentation via parallel EPA and ARS web sitesFree public download and full documentation via parallel EPA and ARS web sites registered users (excluding BASINS users)1200+ registered users (excluding BASINS users) AGWA Milestones

AGWA Support & Distribution Fact Sheets, Product Announcement, Brochures Documentation and User Manual Quality Assurance Report l Research Plan l Code Structure (Avenue Scripts, Dialogs, System Calls) l EPA and USDA/ARS companion Websites l Journal Publications (Hernandez et al. 2000, Miller et al. 2002a, Miller et al. 2002b, Kepner et al., 2004) l Training: Las Vegas (2001); Reston (2002); Tucson (2003); San Diego (2004) AGWA Web Sites

Future Directions Final ArcView version (AGWA 1.5) release at FIHMC (April 2006)Final ArcView version (AGWA 1.5) release at FIHMC (April 2006) Detailed, peer reviewed design plan for AGWA migration to ArcGIS and Internet completed April, 2005Detailed, peer reviewed design plan for AGWA migration to ArcGIS and Internet completed April, 2005 Beta-release of ArcGIS and Internet versions, 2006Beta-release of ArcGIS and Internet versions, 2006 Final ArcGIS and Internet release with full documentation, 2007Final ArcGIS and Internet release with full documentation, 2007 Migrating to ArcGIS (AGWA 2.0) and the Internet (DotAGWA) Integration of additional models Opus – USDA-ARS integrated simulation model for transport of non- point source pollutants (2007)Opus – USDA-ARS integrated simulation model for transport of non- point source pollutants (2007) MODFLOW – USGS ground-water model will be coupled with AGWA- KINEROS surface-water model (planning meeting 2006)MODFLOW – USGS ground-water model will be coupled with AGWA- KINEROS surface-water model (planning meeting 2006) GAP habitat models – integrated hydrologic and ecological assessments (proposal pending)GAP habitat models – integrated hydrologic and ecological assessments (proposal pending)