State of USDA Science: Water Management and Water Conservation

1. State of USDA Science: Water Management and Water Conservation Dale Bucks, Susan Moran, Dave Goodrich, Mark Weltz, and Numerous ARS Scientists

2. USDA Science Related to Water Management and Water Conservation Covered in This Presentation Near surface soil moisture Root zone soil moisture Snowmelt and runoff Water and energy balance Water quality Precipitation forecasting Weather generation Land cover assessment Vegetation and water stress CO2 flux

3. Near Surface Soil Moisture Maps Derived from Synthetic Aperture Radar (SAR) Images Tombstone Tombstone 12 January 1997 23 March 1997 Soil dry Soil near saturation 0 5 10 15 20 25 30 35 40 45 50 55 60 Percent Volumetric Soil Moisture

4. Aqua AMSR-E Watershed Soil Moisture Validation Projects Soil Moisture Field Experiments (SMEX) USDA/ARS Watershed Experiment Sites • Diverse vegetation, topography, soils, climate (Iowa, 2002; Oklahoma, Georgia, 2003; Arizona, Idaho, 2005) Approach • Intensive sampling (satellite/airborne/ground) • Short time duration (~1 month) • Aircraft underflights of AMSR to scale from in-situ to satellite footprint and evaluate heterogeneity • Study spatial/temporal soil moisture dynamics and effects of vegetation, temperature, texture & topography on soil moisture accuracy Measurements • Soil moisture (gravimetric, probe) • Soil bulk density, texture, surface roughness • Biomass, Soil temperature (IR, probe) • Airborne (PSR-C, AESMIR, ESTAR, PALS) • Ground-based radiometers Idaho Iowa SGP Arizona Georgia USDA/ARS Watershed Experiment Sites PSR-C and PALS airborne radiometer imagery SMEX02 (June 2002, Ames, Iowa) -- Experiment Plan http://hydrolab.arsusda.gov/smex02/smex02.htm

5. Reynolds Creek, ID Walnut Gulch, AZ Little River, GA Little Washita, OK AMSR-E Soil Moisture Validation AMSR-E SMEX03,05 U.S. Soil Moisture Validation Sites

6. 1985 2002 2010 High Aqua Meteorological Satellites HYDROS Bare Vegetated Sensitivity Low 1 2 3 5 10 20 30 50 Frequency (GHz) Global Soil Moisture Monitoring 2010 • AMSR is better than the past • A lower frequency instrument is needed • HYDROS • Optimal frequency • Better spatial resolution than previous missions

7. Global Soil Moisture Monitoring 2010 HYDROS provides the first global view of Earth's changing soil moisture and land surface freeze/thaw conditions, leading to breakthroughs in weather and climate prediction and in the understanding of processes linking water, energy, and carbon cycles, which enhances our agricultural competitiveness. • INSTRUMENT: • Low frequency • Antenna technology to provide 10 km resolution PARTNERS: NASA, MIT, JPL, DOD, IPO, Italy, Canada, and Science Team (ARS) HYDROS was submitted to the NASA Earth System Science Pathfinder Program. It has been selected to serve as an alternative to the selected missions, should they encounter difficulties during initial development phases. New science and application priorities could affect selection.

8. Snowmelt Runoff: MODIS and Modeling MODIS 250 m Processing System Overview NASA – DAAC Data Sets MODIS 250 m. HDF files Meteorological real time data Internet Zone • Digital Basis • DEM’s • Basin contours • Ground control points • GIS / Computer Codes • Preprocessing • HDF extraction • Geometric correction • Radiometric correction Snow DepletionCurves SRM Model Level 1b HDF Files Snow Maps Snowmelt Runoff Forecasts Snow Cover Tables • HDF Tools • Webwinds (NASA-JPL) • MS2GT (Wisconsin University) • Commercial: IDL, ENVI • USGS database • Pyrenees digital database • Product Users • U.S. Bureau of Reclamation (USA) • Elephant Butte Irrigation District (USA) • ENHER, Barcelona (Spain)

9. Snowmelt Runoff: MODIS and Modeling Forecasted and Measured Daily Streamflow of Rio Grande at Del Norte Using SRM with No Updating – 2001 Snowmelt Season Forecasted volume: 682.1 Hm3 Measured volume: 808.2 Hm3 V= 16.9 % • Obtained from conditions of an average year: 1976 (temperature and precipitation) • Snow cover derived from 2001 conditions measured by MODIS satellite snow maps

10. Evapotranspiration: Optical Remote Sensing and Modeling 1 2 2-STAGE FLUX DISAGGREGATION PROCEDURE ABL TA (z=50m) TRAD GOES Landsat Cover Landsat MODIS 5 km 60 m

11. Evapotranspiration: Optical Remote Sensing and Modeling ER09 ER01 ER05 ER13 DISALEXI – OUTPUT AT 30M RESOLUTION El Reno, OK 2 July 1997 1 GOES pixel

12. Evapotranspiration: Optical Remote Sensing and Modeling x DISALEXI – VALIDATION Comparison of DisALEXI disaggregated surface energy fluxes with eddy covariance measurements at same locations Flux components Rn G H ET DisALEXI Flux (W/m2) x Eddy Covariance Flux (W/m2)

13. Water Quality: Sediment, Nutrients, and Chlorophyll

14. Water Quality: Sediment, Nutrients, and Chlorophyll Landsat Image Derived Image Lake Chicot, Arkansas

15. Seasonal Precipitation Forecast Nov-Dec-Jan 2002

16. Daily Precipitation Forecasting

17. Daily Precipitation Forecasting

18. Distributed elevation, soil, vegetation & model calibration information Combining Remote Sensing and Modeling for Grassland Assessment: SEHEM - Spatially Explicit Hydro-Ecological Model SEHEM Calibration Procedure Satellite spectral data for model calibration and validation Maximum energy conversion efficiency and initial root biomass Surface reflectance and temperature Visible Radiative Transfer Model Thermal Radiative Transfer Model Real time, distributed simulations of the diurnal, seasonal and multi-year pattern of plant growth, soil water and energy fluxes Distributed meteorological and precipitation data Leaf Area Index Leaf temperature Soil temperature Hydrologic SubModel Plant Growth SubModel SEHEM: Spatially Explicit Hydro-Ecological Model

19. 160 mean = 66.0 140 mean = 92.5 1991 1990 120 mean = 65.9 mean = 89.5 1993 1992 100 80 mean = 75.2 mean = 50.7 1995 1994 60 mean = 47.1 mean = 76.8 1996 1997 40 20 mean = 82.9 mean = 91.8 1998 1999 An Example of SEHEM Output Annual Net Primary Production 1990-1999

20. intensity time runoff time Land Cover and Land Cover Change Key component of most hydrologic models RAINFALL Remotely sensed imagery transformed into land cover Land Cover DEM Soils HYDROLOGIC MODELS Urbanization - 277% Increase 415% basin increase in Mesquite from ’73-’86 RUNOFF SEDIMENT Multi-decadal RS Land Cover Change

21. Hydrologic Impacts of Land Cover Change using AGWA • Using SWAT and KINEROS for integrated watershed assessment • Land cover change analysis and impact on hydrologic response San Pedro River Basin Pre-urbanization High urban growth 1973-1997 Sierra Vista Subwatershed 1973 Runoff KINEROS Results Concentrated urbanization Post-urbanization 1997 Runoff Water yield change between 1973 and 1997 <<WY >>WY 1997 Land Cover SWAT Results

22. 260 (1993) 274 (1994) 242 (1998) 269 (1999) Optical Remote Sensing: WDI Predicts Large-Scale Grassland CO2 Flux

23. Little Washita River Experimental Watershed Maricopa Agricultural Center Oklahoma New Mexico Arizona Jornada Experimental Range Texas Walnut Gulch Experimental Watershed Maricopa Agricultural Center, Walnut Gulch Experimental Watershed, Jornada Experimental Range and Little Washita River Experimental Watershed

24. ARS Watershed Locations

25. State of Science USDA Science: Summary of Primary Target and Agricultural Applications for Remote Sensing/Decision Support Systems Primary Target: Agriculture, Water and the Environment Primary Goal: Clean and Abundant Water Primary Applications: Soil moisture Drought and water scarcity predictions Variations in local weather, precipitation, and water resources Water quality indicators Global climate change effects Etc.