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Streamflow Response to Climate Variability Jefferson River, Montana

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Streamflow Response to Climate Variability Jefferson River, Montana Streamflow Response to Climate Variability Jefferson River, Montana PROBLEM The Jefferson River, a headwater to the Missouri River, is formed by the confluence of the Ruby, Beaverhead, and Big Hole Rivers in southwestern Montana. Approximately 350 square miles of crops and pasture are irrigated by the Jefferson River and its tributaries. These same streams are also an important recreational and commercial destination for anglers and boaters. During the irrigation season, much of the flow within the tributaries to the Jefferson River is diverted before reaching the main stem of the river. During dry years, runoff and base flow to the main stem are severely reduced, streamflows are not sufficient for irrigation and boating, and increased temperatures in the river severely reduce habitat suitability for fish. Examination of historical and recent precipitation and temperature cycles indicates that the warmer temperatures occurring across the western United States could continue into the future. Scientists have shown that warmer temperatures will produce more precipitation as rainfall instead of snowfall at lower and middle elevations and cause most of the mountain snowpack to melt earlier. These changes would tend to increase streamflows throughout the winter and spring and decrease streamflows in the summer. Decreased summer flows will negatively affect management of surface water resources in the Jefferson River and its tributaries and the capacity of the system to support agriculture, recreation, and fisheries. One way to understand streamflow trends and variability is Jefferson River Watershed by analyzing long-term streamflow gaging records. Currently (2010) the United States Geological Survey (USGS) operates 19 streamflow gaging stations on the Red Rock, Big Hole, Beaverhead, Ruby, and Boulder Rivers (combined stream length of 521 miles) and 3 gaging stations on the 90-mile long Jefferson River. Most of these gaging stations are funded through partnerships with Federal, State, and local agencies. Financial support is precarious from year-to-year and often gaging stations must be discontinued due to loss of funding. Missing streamflow data are impossible to replace and difficult to estimate. 3 PROPOSED PROJECTS • A watershed model will be developed for the 9,635-square mile Jefferson River Watershed. This model will enable users to calculate streamflows in the Jefferson River and its tributaries given daily inputs of precipitation and temperature. Streamflows resulting from future climate scenarios will be simulated using the watershed model. • Fish population sampling in the Jefferson River will be continued and fisheries data correlated with modeling results. • Streamflow gaging stations will be retained and, if possible, re-established. APPROACH Hydrologists at the USGS Montana Water Science Center will use the USGS Precipitation-Runoff Modeling System (PRMS) to model the watershed. Daily temperature and precipitation data from National Weather Service climate stations and from Natural Resources Conservation Service Snowpack Telemetry (SNOTEL) stations will be collected along with topography, soils, and vegetation information for the watershed. The model will be calibrated to historical streamflow data. Projected temperatures and precipitation output from a regional climate model developed at Oregon State University will be input to the PRMS model to estimate future streamflows in the Jefferson River. Biologists at the Montana Department of Fish, Wildlife & Parks (FWP) will continue to sample fish populations in the Jefferson River. FWP and USGS Northern Rocky Mountain Science Center biologists will interpret the biological impacts from the projected streamflow changes. USGS hydrologists and biologists will determine which streamflow gages are vital for understanding streamflow variability across the Jefferson watershed. The USGS will continue to operate gaging stations and, if possible, re-establish discontinued gaging stations. BENEFITS The watershed model will provide an increased understanding of watershed dynamics in the Jefferson River watershed and help users quantify the relative importance of snowmelt, rainfall, evaporation, and tributary flows during different times of the year. The model will serve as a tool for understanding the effects of varying climate conditions on streamflow. PRMS can be paired with water management software such as RiverWare to help water users plan for and adapt to variable water availability and changing irrigation demands. PRMS can also be coupled with existing and proposed groundwater models to further understand surfacewater- groundwater interactions and effects of changing irrigation methods on streamflows. Modeling future climate scenarios will enable planners and water users to estimate streamflows 10, 50, and 90 years into the future based on projected climate conditions. Correlating model results with fisheries data will allow scientists and managers to estimate potential impacts to fisheries and to develop management strategies to mitigate those impacts. Data from streamflow gaging stations provide invaluable information about the availability and variability of flows at different locations through time. These data are essential for verifying results from watershed models. Streamflow data are becoming increasingly important as scientists and water managers try to understand how much water is available under a variable climate. Photo and daily discharge data from the Jefferson River at Parsons Bridge near Silver Star (06027600). COSTS Development of the PRMS watershed model would cost about $290,000, and simulating climate change scenarios in PRMS is estimated to cost $219,000. Fish population sampling costs approximately $34,500 per year. The cost for maintaining a USGS real-time streamflow gaging station in 2010 is approximately $16,000. This includes quality assurance of the data and posting the data on the USGS website, http://mt.water.usgs.gov/. .
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