Water Management Session: 16th Federation Meeting - Jan 4-6, 2006 Notes/Highlights

From Earth Science Information Partners (ESIP)

NASA Water Management Program

Presentation by Mayra Montrose, David Toll, Kristi Arsenault, Edwin Engman, Jon Triggs


Fundamental Research

Water and energy cycle

Applied Research

Science utilization

Improve predictions (water cycle)

  • Variables include: Soil moisture, snow water equivalent, surface runoff, evapotranspiration, rainfall

--Take data from Earth-Sun observations and plug into Earth systems models to make predictions and observations --

  • Groundwater = GRACE
  • Precipitation = TRMM/GPM
    • TRMM will lead to GPM for Global precipitation
  • Soil Moisture = Hydros (cancelled, hopefully be back in 07)
    • We plan to address soil moisture intensively - Hyrdos provides soil moisture and freeze/thaw info
  • Snow
  • Surface water
  • Snow-water equivalent measured by AMSR-E

--Sensors in concept CLPP mission

--Pathfinder proposed mission provides reservoir height and discharge estimates using 3 methods

  • Altimetry
  • Laser
  • Parallax interferometer approach

--Land Information System (LIS) high performance, high resolution (1 km) for local to global land modeling and data assimilation system

  • Follows ESMF modeling framework -- single or multiple processors
  • 5+ land surface models -- ingest different types of data sets, dependent on availability, model the data, outputs include: soil moisture, ET, Water availability parameters.
    • Goal is to get groups to use the suite more.

Data Assimilation

--Use with satellite data, or model data, in-situ data. Bring them all together to improve the overal output.

Model by itself has many imperfections...Use MODIS data to assimilate more accurately when compared to "truth" data. Satellite data improves the models.

NASA application partners:

  • Reclamation: Water supply, demand and forecast
    • Integration of NASA products: land cover, snow, ET, Streamflow, other
    • Ex. Land cover with snow cover to get LSM snow water equivalent
    • Used with NOAA Weather forecast model
  • EPA: non-point source water quality
    • MODIS vegetation index foliar biomass loss and nitrogen deposition
  • Army: global soil moisture (to 100m) trafficability
  • Dept. Agriculture: water supply forecast, drought assessment, agriculture

Parameters aren't physically based in other models, so they don't show up as well as they should in the end product

--Another project -- Improving NOAA/NWS river forecast center DSS with NASA satellite and land info system products

Satellites, Surface, In-situ sensing + grid computing + data mining + prediction models, DSS, critical applications = Integrated Environmental Information System