Extending the societal and economic benefits of Earth science research, information, and technology

Transcription

1 NASA WATER SCIENCE & APPLICATIONS NASA S APPLIED SCIENCES PROGRAM Steven Ambrose 1, Jared Entin 2, David Toll 3 and Ted Engman 4 1- Applied Sciences Program, NASA/HQ 2-TerrestrialHydrology Program & NASA Energy Water Cycle, NASA HQ 3-Hydrological Sciences NASA/GSFC 4- Hydrological Sciences, NASA/GSFC/SAIC Extending the societal and economic benefits of Earth science research, information, and technology

2 OUTLINE NASA Applied Sciences Program Water Resources NASA Data and Data Products Applied Science Water Resources Examples How to Participate ;

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4 NASA Remote Sensing and Modeling Systems

5 NASA Societal Benefit Areas Natural Disasters Water Resources Ecosystems Agriculture Air Quality Weather Climate Public Health

6 Goals of NASA s Hydrology Research Fundamental Research Water and Energy Cycle Science Global Hydrological Cycle Fresh Water Resources and Availability Climate Change Soil Moisture Evapotranspiration Applied Research Science Utilization Reservoir Regulation River Flow Management & Floods Agriculture Planning Hydro Power Planning Drought Assessment e Weather Forecasting Water Quality

7 NASA Data and Data Products The major space agencies and met services maintain a vast array of Earth observing satellites capable of providing basic water cycle data. These data have the potential ti for providing critical inputs for sustainable water resources planning and management. In addition, models developed from satellite data have great potential for applications.

8 Precipitation: The types of data needed include: Remote-Sensing: SSM/I, TRMM, AMSR, GOES, AVHRR, GPM In-Situ: Surface Gages and Doppler Radar Radiation: Remote-Sensing: MODIS, GOES, AVHRR In-Situ: DOE-ARM, Mesonets, USDA-ARS Surface Temperature: Remote-Sensing: AVHRR, MODIS, SSM/I, GOES In-Situ: DOE-ARM, Mesonets, NWS-ASOS, USDA-NRCS Soil Moisture: Remote-Sensing: TRMM, SSM/I, AMSR, SWAT, ESTAR, NOHRSC, SMOS In-Situ: DOE-ARM, Mesonets, Global Soil Moisture Data Bank, USDA-NRCS Groundwater: Remote-Sensing: GRACE In-Situ: Well Observations, Piezometers, pumping tests Snow Cover, Depth & Water: In-Situ: SNOTEL Streamflow: Remote-Sensing: AVHRR, MODIS, SSM/I, AMSR, GOES, NWCC, NOHRSC Remote-Sensing: Laser/Radar Altimeter (SWoT) In-Situ: Real-Time USGS, USDA-ARS Vegetation: Remote-Sensing: AVHRR, TM, VCL, MODIS, GOES In-Situ: Field Experiments Others: Soils, DEM, Latent & Sensible heat fluxes, etc.

9 Research to Application GISS Model III GSFC GOCART GMAO Atmosphere Push Partnership Pull MODELS Applied Research Domain End User/ Decision Maker Benefits Terra Aqua Aura QuikScat TRMM Landsat-7 Science and Research Products User Specific Operational Products Remote Sensing Missions

10 What We Cannot Measure Directly, We Can Model Land Surface Prediction: Accurate hydrologic model prediction is essential to estimate all fluxes and storages in time and space. Based on water and energy balance. Input - Output = Storage Change P + Gin (Q + ET + Gout) = ΔS Rn - G = Le + H E T a n d P r e c i p S o u r c e A r e a O v e r l a n d F l o w In filtr a tio n S u b s u r f a c e F l o w T o t a l F l o w

11 But There Are Still Discontinuities in Space and Time Among Measured Variables and Model Produced Variables, Solution: 4 - D Land Data Assimilation Systems: Quantification and prediction of hydrologic variability (time and space) Critical for initialization and improvement of hydrologic DSTs For applications such as flood forecasting, water supply, ground water management, etc. Maturing of hydrologic observation and prediction tools: Observation: Forcing, storages (states), fluxes, and parameters. Simulation: Land process models (Hydrology). Assimilation: Short-term state constraints (satellite & in situ data) LDAS concept: Bring state-of-the-art tools together to operationally obtain high quality land surface storages and fluxes. Optimal integration of land surface observations, satellite data and model predictions. Continuous in time&space; multiple scales, realtime, and forecast O b s 4D D A M o d e l Im proved prod uct s, predictions, understanding

12 NASA Applied Sciences Program Water Resources Examples Goal: NASA Earth science routinely used in an integrated water resources approach for the U.S. & internationally for the sustainable use of water. Also includes extreme events of drought and floods and the adaptation and mitigation to climate change. For International activities many NASA satellite and modeling products (e.g., precipitation and streamflow) have applications in data poor countries of the world. NASA data are typically free with open use of data. In many cases may be obtained in near-real time and retrospectively. International work primarily through groups such as USAID, Department of State (Paul Simon Water for the Poor Act ), World Bank & GEO (Global Earth Observing) Water Resources categorized in to functional themes (Application Projects) - Streamflow and floods (includes snowpack {4-Projects} - Drought (monitoring and prediction) {4-Projects} - Irrigation and Water Delivery {3-Projects} - Water Quality {1-Project Ended} - Climate Change and Water Resources (New)

13 Water Resources Program Functional Themes Projects Summary FLOODS & STREAMFLOW FORECASTING IRRIGATION & WATER DELIVERY - Improved streamflow for NOAA River Three projects are currently addressing Forecast Centers. various aspects of improving ET - Using NASA satellite and modeling estimates for use in the BoR AWARDSproducts for Seasonal Forecast in W. US ET Toolbox and similar il DSTs. Focus on - NASA-NOAA-USGS Flash Flood using MODIS data and LDAS/LIS Project using NASA products and estimates of ET & soil moisture. One modeling. Iraqi irrigated agriculture mapping - Using NASA Snow Products and LIS for NOAA Snow and Water Forecast DROUGHT Four Projects. Two using satellite (AMSR-E, Quickscat/Sea Winds, MODIS and GRACE) and modeling/data assimilation products to improve the US Drought Monitor. Two other improving seasonal predictions and the downscaling of climate predictions for US Drought Outlook. In support of the National Integrated Drought Information System (NIDIS). WATER QUALITY Nonpoint source pollution project to assess the impact of MODIS land data products and impact of LIS precipitation and ET products to improve the continuous hydrologic model, HSPF, used in the EPA BASINS DST.

14 I. FLOODS AND STREAMFLOW FORECASTING

15 NASA - BUREAU OF RECLAMATION WATER SUPPLY & FORECAST Aqua Terra RiverWare Decision Support Tools (NASA) (NOAA) (BoR-USDA) Regulating Reservoirs D. Boyle/DRI NASA LIS Modeling

16 II. Water Supply and Irrigation Delivery

17 (R. Allen, University of Idaho)

18 III. Drought

19 Drought Monitor Study by JPL/USGS/NOAA Using NASA Products (Gheim and Verdin) QSCAT daily maps of surface water increase due to precipitation (left panels), and USDM weekly drought maps (right panels) showing changes in drought conditions. AMSR-E AMSR-E monthly averaged soil moisture (volumetric %) for August 2002 showing dry conditions over western U.S..

20 IV. Water Quality

21 NASA-EPA Study Using NASA Products for Nonpoint Source Water Quality BASINS-HSPF: Precipitation & Evapotranspiration for Flow, & Land Cover Disturbances Modeled Flow Estimations for NE Anacostia Basin STATISTICS NATIONAL vs. USGS Rain Gauges not Representative of Precipitation Correlation Coefficient Events Satellite/Doppler Spatial Data Compliments Gauge RMS Error Data Model Fit Efficiency (NS) MODIS/Landsat/Hyperion derived defoliation for NLDAS 1/8 th Degree vs. USGS estimating Nitrate exports Correlation Coefficient Chesapeake RMS Error Model Fit Efficiency (NS) Bay Watershed = BASINS default rain gauges g = NLDAS Stage II precipitation it ti

22 V. International

23 Arab LDAS Project GOAL: Produce maps of hydrological states and fluxes in the Middle East - North Africa (MENA) region, which will serve as a basis for regional water resources assessments. METHOD: Optimize a land data assimilation system (LDAS) for the MENA region, in which NASA satellite data, surface observations from Arab countries, and publically-available available meteorological analyses will be used to parameterize, force, and constrain a sophisticated land surface model. BENEFITS: Near-real time monitoring of water resources across political boundaries Historical and regional perspective on local hydrological variability Rapid assessment of the severity and extent of droughts and floods A scientific tool for agricultural planning, including irrigation Potential to assess hydrological impacts of climate change

24 How to Participate NASA is looking for a broad range of partners, including universities, all levels of government, and private firms. Must use NASA data or products. Google NASA ROSES