Application of Coupled Snowpack/Hydrologic Modeling to Water Supply and Flood Forecasting in Colorado
Water management officials of the Colorado Water Conservation Board (CWCB) and Reclamation wish to know the timing and volume of streamflows from snowmelt in Colorado rivers, for both water supply and flooding forecasts. A major limitation in these forecasts has been a lack of detailed knowledge of the spatial and temporal evolution of the snowpack's snow water equivalent (SWE) in the mountains. This R&D proposes to apply the most sophisticated modeling and data assimilation system available for SWE to answering this limitation. This system is the Snow Data Assimilation System or SNODAS.
SNODAS will be further enhanced by accurate, real-time, multisensor precipitation estimation in the form of a system known as QPE SUMS. This combined precipitation/snowpack measurement system will provide water managers with the most accurate and timely information about snowmelt water volumes, which represents crucial decision support for both CWCB and Reclamation water operations managers.
Need and Benefit
Snowfall monitoring and flood warning systems have traditionally relied on precipitation gauges to measure precipitation. A major problem with gauges is that they provide sparsely distributed point measurements; this is especially true in mountainous areas such as the Colorado Rockies. Another limitation for gauges is that they have more difficulties measuring snow vs. rain, and snow is a major part of the annual precipitation in the state, particularly in the mountains. The primary gauge system for snowfall measurements in the mountains is SNOTEL; these gauges are very few in number, particularly above 10,000 feet where much of the snowpack is found. Therefore it is difficult to accurately measure snowfall over wide areas of the mountains, and therefore difficult to gauge the snow water equivalent (SWE) in the mountain snowpack.
Even if snowfall is accurately measured, it is still a challenge to track ablation (melt and sublimation) of the snowpack and its SWE. This challenge owes to a situation analogous to that of snowfall measurement, i.e., the sparseness of measurement sites - current measurements are taken at SNOTEL sites and snow courses. This data sparseness leads to coarse and sometimes erroneous spring snowmelt and runoff forecasts. Since snowmelt contributes, on average, around 80% of water storage in Western reservoirs, such forecasts can be very problematic for Reclamation's water management. Not knowing how much snowmelt will enter the reservoirs can lead to inappropriate releases of water from dams, causing floods or reduced conservation pool storage and water delivery (volumes).
This information was last updated on September 1, 2014
Contact the Research and Development Office with questions or comments about this page