Rapid National Model Assessments to Support US Conservation Policy Planning Mike White

Transcription

1 Rapid National Model Assessments to Support US Conservation Policy Planning Mike White USDA-ARS Grassland, Soil and Water Research Laboratory, Temple, TX 1

2 Topics Current National Assessments Future National Assessments Supporting Data and Tools Grassland, Soil and Water Research Laboratory, Temple, TX 2

3 US National Assessments CEAP - Conservation Effects Assessment Project Justify US conservation expenditures (about 2 billion annually) Quantitative predictions of water quality improvements 18 river basins simulated using SWAT and APEX Grassland, Soil and Water Research Laboratory, Temple, TX 3

4 CEAP Framework Cultivated Agriculture NRI Survey Data Other Landuses Public Data APEX SWAT Predicted Load Predicted Load SWAT Routing Delivered Load Prediction Grassland, Soil and Water Research Laboratory, Temple, TX 4

5 Rapid - CEAP Purpose Rapidly respond to congressional inquiries Support US Farm Bill development Approach Identical to CEAP Structure Integrate 18 river basin models into a single model 2,200 subbasins 45,000 HRUs Grassland, Soil and Water Research Laboratory, Temple, TX 5

6 Calibration Streamflow (Surface runoff and Baseflow) calibrated at the 8 digit level to USGS estimated runoff Automated calibration using CEAP software Sediment and Nutrients Calibrated to individual estimated loads at ~ 100 sites Automatic calibration using heuristic algorithms USGS Interpolated Runoff and Baseflow USGS Gages with Flow, Sediment and Nutrient Loads Grassland, Soil and Water Research Laboratory, Temple, TX 6

7 Predicted Streamflow and Sediment Yield Green Low Red - High Grassland, Soil and Water Research Laboratory, Temple, TX 7

8 Predicted Nutrient Yields Grassland, Soil and Water Research Laboratory, Temple, TX 8

9 Load Allocation Results Mississippi River total loads to Gulf of Mexico Grassland, Soil and Water Research Laboratory, Temple, TX 9

10 Beyond CEAP (ECLIPS) Environmental and Conservation on Landscapes for Integrated Policy Scenarios Remove dependency on proprietary data Increase spatial resolution 2,200 Subbasins (HUC 8) to 80,000 (HUC 12) Improve calibration data Rapidly incorporate new data Grassland, Soil and Water Research Laboratory, Temple, TX 10

11 ECLIPS Framework Research Configuration Public Data Public Data Optional Configuration NRI Survey Data Complete SWAT Model Partial SWAT Model APEX Field Level Delivered Load Prediction Complete Model SWAT Routing Delivered Load Prediction Grassland, Soil and Water Research Laboratory, Temple, TX 11

12 National Model Inputs Derived from CEAP (Except Cultivated Ag) Subbasin & Reach Properties Pasture and Range Management Urban and Forest Management Climate Point Sources Agricultural Crop Fractions Cropland Data Layer CDL Management Fertilizer Tillage Management Operation Planting Harvest Dates Tillage Dates and Implements Irrigation Tile Drains Manure Application Reservoirs National Inventory of Dams Grassland, Soil and Water Research Laboratory, Temple, TX 12

13 Agricultural Crops 2009 CDL Data Reclassified from 256 categories Corn Small grains Cotton Vegetables Soybeans Sorghum Fallow Grassland, Soil and Water Research Laboratory, Temple, TX 13

14 Fertilizer Application Rates Derived from Agricultural Census Yield and Fertilizer use data Grassland, Soil and Water Research Laboratory, Temple, TX 14

15 Tillage Practices USGS Conservation Technology Information Center (CTIC) Survey Data Types Conventional Ridge Reduced Mulch No-Till Grassland, Soil and Water Research Laboratory, Temple, TX 15

16 Management RUSLE2 20,000 Templates Converter Checker RUSLE2 Management Extensive Conversion Cropping Assumptions Plants Kills Harvests Fertilization 6,000 mgt converted SWAT Format Grassland, Soil and Water Research Laboratory, Temple, TX 16

17 Large Models Rapid Execution Currently 2,200 subbasins 45,000 HRU Future 80,000 subbasins 2 million HRUs Parallel Processing is REQUIRED Grassland, Soil and Water Research Laboratory, Temple, TX 17

18 Parallelizing SWAT 2 Approaches Parallelize the model Not Readily Compatible with Existing Architecture Parallelize the problem No code changes Windows Cluster 45,000 HRU model run for 37 Years takes 15 min Grassland, Soil and Water Research Laboratory, Temple, TX 18

19 Quality Control - SWAT Checker Models are Difficult to Check BAD INPUT DATA OR IMPROPER CALIBRATION CAN CAUSE PROBLEMS Identify Model Outputs out of Normal Ranges. Show Visual Representations of Model Outputs Grassland, Soil and Water Research Laboratory, Temple, TX 19

20 Acknowledgements The Temple CEAP Team A National USDA Effort NRCS ARS NASS Texas A&M & Other Universities Grassland, Soil and Water Research Laboratory, Temple, TX 20

21 Questions and Comments? Grassland, Soil and Water Research Laboratory, Temple, TX 21