HR: 11:38h
AN: SF12A-07 INVITED     [Abstracts]
TI: Online Tools at the U.S. Bureau of Reclamation
AU: * Hunter, S M
EM: smhunter@do.usbr.gov
AF: U.S. Bureau of Reclamation, D-8510 P.O. Box 25007, Denver, CO 80225-0007 United States
AB: Reclamation is the major Federal water resources management agency operating in the 17 western States, where it has over 350 reservoirs, numerous irrigation systems, and related infrastructure. Escalating human needs for finite water supplies make it essential that Reclamation manage its many water systems with the greatest practical efficiency. Efficient system operation depends heavily on accurate short-term and seasonal streamflow forecasts. Spring streamflows, derived largely from snowmelt and rains on snow, are especially critical to Reclamation's water management. The inability to quantitatively predict such streamflows beyond climatological values has been a major problem, and one of the major causes of this inability is inaccurate or spatially sparse quantitative precipitation estimate (QPE) data. To address these shortcomings, Reclamation's River Systems and Meteorology group has developed several online tools for QPE data access and visualization. The major tool is the Agricultural WAter Resources Decision Support (AWARDS) system. The purpose of the AWARDS system is to improve the efficiency of water management and irrigation scheduling by providing guidance on when and where to deliver water, and how much to apply. The AWARDS system has been designed for use by reservoir system operators, water district staff, and on-farm irrigators. AWARDS is operational in several regions of the West. At the heart of AWARDS is near-real-time QPE from the national WSR-88D radar network, providing hourly and daily accumulations at a nominal 2 km spatial resolution. The QPE is produced by either the National Weather Service Multi-sensor Precipitation Estimator (MPE) or Reclamation's Precipitation Accumulation Algorithm (PAA). The latter algorithm can estimate snow water equivalent (SWE) or snow depth from snowfall. Reclamation scientists have pursued close collaboration with other agencies in the formulation of AWARDS and precipitation-related information systems. A recent example of such collaboration is with the NOAA National Severe Storms Laboratory (NSSL). This partnership has resulted in application of NSSL's Quantitative Precipitation Estimation and Segregation Using Multiple Sensors (QPE SUMS) system in the Lower Colorado River basin. QPE SUMS combines gauge, radar, and satellite measurements into a single sophisticated suite of algorithms, producing 3-D mosaicked data and several QPE ensembles. QPE SUMS will be deployed in Colorado soon to assist snowpack assessment. Data for this assessment are already being displayed on the web via the Snow Data Assimilation System (SNODAS). SNODAS is a fully-distributed, energy-and-mass-balance snow model that assimilates several types of snow observations, numerical weather model output, satellite, radar and airborne data. SNODAS was developed by the NWS National Operational Hydrologic Remote Sensing Center. We display SNODAS SWE at 1 km resolution and compute basin-average SWE from those data, on a daily basis. This output is used for decision support by the Colorado Water Conservation Board and other water management agencies in the state. It is planned to include several more variables (e.g., snow depth, snowmelt, snowpack temperature) on the web site. The principal goal is to demonstrate any value added to water management over traditional snow measurements, which are primarily taken from surface Snow Telemetry (SNOTEL) sites. Finally, we intend to couple QPE data with hydrologic models and river basin modeling decision support systems, thereby improving those schemes. Such a coupling has already been tested with Reclamation's PAA and two distributed models in the Lower Colorado River basin.
UR: http://www.usbr.gov/pmts/rivers/awards/index.html
DE: 3354 Precipitation (1854)
DE: 3360 Remote sensing
SC: Special Focus: Advances in Data Acquisition, Management, Analysis and Display [SF]
MN: 2004 AGU Fall Meeting