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

4. 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 SGP Iowa Georgia Idaho Arizona PSR-C and PALS airborne radiometer imagery USDA/ARS Watershed Experiment Sites Aqua AMSR-E Watershed Soil Moisture Validation Projects SMEX02 (June 2002, Ames, Iowa) -- Experiment Plan http://hydrolab.arsusda.gov/smex02/smex02.htm

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

6. 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 20021985 123510203050 Low High Frequency (GHz) Sensitivity Bare Aqua Meteorological Satellites 2010 HYDROS Vegetated

7. INSTRUMENT: Low frequency Antenna technology to provide 10 km resolution PARTNERS: NASA, MIT, JPL, DOD, IPO, Italy, Canada, and Science Team (ARS) 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. 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. Global Soil Moisture Monitoring 2010

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

9. Forecasted and Measured Daily Streamflow of Rio Grande at Del Norte Using SRM with No Updating – 2001 Snowmelt Season Obtained from conditions of an average year: 1976 (temperature and precipitation) Snow cover derived from 2001 conditions measured by MODIS satellite snow maps Forecasted volume: 682.1 Hm 3 Measured volume: 808.2 Hm 3  V= 16.9 % Snowmelt Runoff: MODIS and Modeling

10. 5 km 1 1 T A ( z=50m ) GOES MODIS T RAD Cover ABL Landsat 60 m 2 2 2-S TAGE F LUX D ISAGGREGATION P ROCEDURE Evapotranspiration: Optical Remote Sensing and Modeling

11. D IS ALEXI – O UTPUT A T 30 M R ESOLUTION ER01 ER05ER09ER13 El Reno, OK 2 July 1997 1 GOES pixel Evapotranspiration: Optical Remote Sensing and Modeling

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

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

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

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

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

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

22. Optical Remote Sensing: WDI Predicts Large-Scale Grassland CO 2 Flux 260 (1993)274 (1994) 242 (1998)269 (1999)

23. Arizona New Mexico Texas Oklahoma Maricopa Agricultural Center Walnut Gulch Experimental Watershed Jornada Experimental Range Little Washita River 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 Applications: Soil moisture Drought and water scarcity predictions Variations in local weather, precipitation, and water resources Water quality indicators Global climate change effects Etc. Primary Target: Agriculture, Water and the Environment Primary Goal: Clean and Abundant Water