85th AMS Annual Meeting

Monday, 10 January 2005
The use of NASA land data assimilated products to improve flood and drought risk analysis and forecasting for water resources management in the Columbia River Basin
Kristi R. Arsenault, University of Maryland, Baltimore County, Greenbelt, MD; and P. R. Houser, S. M. Hunter, D. Frevert, R. Stodt, and D. Matthews
This paper summarizes the activities and progress of the collaborative project between U.S. Bureau of Reclamation (USBR), NASA Goddard Space Flight Center (NASA GSFC), and UMBC Goddard Earth Science and Technology Center (GEST) for FY03-04. The overarching objective of the project is to demonstrate the value added by information from satellite, radar, the Land Surface Data Assimilation System (LDAS) and related products toward the improvement of flood and drought risk analyses and forecasts. These products will be tested by water resource managers in the Yakima River Basin. Results from the LDAS land surface models (LSMs) and hydrologic runoff models will be integrated into the river basin decision support systems that the Reclamation’s managers routinely use to manage the complex operation of the river system. The applications work focuses on the “leave behind” concept where an improved hydrologic operation and forecasting system is being developed through major collaborative efforts between NASA and Reclamation. The improved system will be implemented into water resource management operations and flood and drought forecasting after successful demonstration of this project.

The goals of this project are: (1) developing and demonstrating the value added by information from satellite, radar, Land Data Assimilation System (LDAS) and Land Information System (LIS) products in the improvement of flood and drought forecasts. The forecasts will be used by water resource managers and emergency managers, initially in the Yakima River Basin, a tributary of the Upper Columbia River Basin, as a model demonstration. (2) Testing and evaluating different land surface models and hydrologic runoff models that simulate and forecast flood and drought events. These models will use satellite and radar remote sensing information and conventional surface observations to demonstrate the value added to improved streamflow simulations and forecasts. (3) Performing retrospective case studies to determine the performance of LDAS/LIS, the land surface models, and quality of the model forcing data when compared against observations of both Reclamation and other sources. (4) Validating model results and remote sensing data. (5) Establishing a system that will feed operational simulation output from GSFC to Reclamation to test the quality and efficiency of the data stream. Evaluating the operational runs at Reclamation will prepare our main goal of establishing a feed of forecasted LDAS products. (6) And improving the flood and drought forecasts through these collaborative efforts, but it is also our intention to contribute our results and forecast system to water resource managers, the scientific community, and to the public.

This paper addresses the needs and motivation for the research and preliminary plans and results. Accurate and timely hydrometeorological information is essential for reservoir operations and river basin management conducted at the Bureau of Reclamation (Reclamation) facilities. Consequently, river basin managers must have timely data from remote areas that are often inaccessible in winter, and have a means of quickly analyzing the impacts of precipitation and snowmelt on streamflow for routine river system management, and emergency responses to extreme events. Therefore, Reclamation uses a variety of hydrometeorological observing systems that it maintains and cooperates with other agencies in collection of additional data and to use the data for decision support tools.

The Land Data Assimilation Systems (LDAS) and Land Information System (LIS) teams of the Hydrological Sciences Branch at NASA GSFC and affiliated with UMBC GEST Center are developing a system that runs multiple land surface models, assimilating and using as forcing the latest in surface observations and remotely-sensed data both operationally and retrospectively. The emphasis of LDAS (Mitchell et al, 2003; Rodell et al., 2004) and LIS (Peters-Lidard et al., 2004) is on capturing the most realistic representations of land surface dynamics and their interactions with the atmosphere over large areas and at high resolutions. The main hydrometeorological variables that LDAS focuses on are soil moisture, evaporation, snow cover, runoff, precipitation, and also radiation and energy budget variables. All of these, to some capacity, can serve water resource managers in helping to assess and predict flood and drought conditions. The Reclamation and LDAS/LIS research teams are developing and evaluating a system that utilizes these key strengths to monitor, predict, and assess the effects of flood and drought activity. This paper will present results focused on decision making that enables water operations managers in the Upper Columbia River Basin to make the most effective use of information technology in transferring emerging science to the water resource manager on a daily basis.

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