Development of a Hydrologic Model to Explore Impacts of Climate Change on Water Resources in the Big Wood Basin, Idaho

Development of a Hydrologic Model to Explore Impacts of Climate Change on Water Resources in the Big Wood Basin, Idaho
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Total Pages : 73
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ISBN-10 : OCLC:892662581
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Book Synopsis Development of a Hydrologic Model to Explore Impacts of Climate Change on Water Resources in the Big Wood Basin, Idaho by : Allison Marshall Inouye

Download or read book Development of a Hydrologic Model to Explore Impacts of Climate Change on Water Resources in the Big Wood Basin, Idaho written by Allison Marshall Inouye and published by . This book was released on 2014 with total page 73 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the Western United States where 50-70% of annual precipitation comes in the form of winter snowfall, water supplies may be particularly sensitive to a warming climate. We worked with a network of stakeholders in the Big Wood Basin, Idaho, to explore how climate change may affect water resources and identify strategies that may help mitigate the impacts. The 8,300 square kilometer region in central Idaho contains a mixture of public and private land ownership, a diversity of landcover ranging from steep forested headwaters to expansive desert shrublands to a concentrated area of urban development that has experienced a quadrupling of population since the 1970s. With nearly 60% of precipitation falling as winter snow, stakeholders expressed concern regarding the vulnerability of the quantity and timing of seasonal snowpack as well as surface water supplies used primarily for agricultural irrigation under projected climate change. Here, we achieve two objectives. The first is the development of a hydrologic model to represent the dynamics of the surface water system in the Big Wood Basin. We use the semi-distributed model Envision-Flow to represent surface water hydrology, reservoir operations, and agricultural irrigation. We calibrated the model using a multi-criteria objective function that considered three metrics related to streamflow and one metric related to snow water equivalent. The model achieved higher an efficiency of 0.74 for the main stem of the Big Wood River and 0.50 for the Camas Creek tributary during the validation period. The second objective is an analysis of the Big Wood Basin hydrology under alternative future climate scenarios. We forced the calibrated model with three downscaled CMIP5 climate model inputs representing a range of possible future conditions over the period 2010-2070. The climate models simulate an increase in basin average annual air temperature ranging from 1.6-5.7oC in the 2060s compared to the 1980-2009 average. The climate models show less of a clear trend regarding precipitation but in general, one model simulates precipitation patterns similar to historic, one is slightly wetter than historic, and one is slightly drier than historic by the mid-21st century. Under these future climate scenarios, the depth of April 1 SWE may decline by as much as 92% in the 2060s compared to the historic average. Mid to high elevations exhibit the largest reductions in SWE. Simulated streamflows show a shift in timing, with peak flows occurring up to three weeks earlier and center of timing from two to seven weeks earlier in the 2050-2069 period compared to the historic period. Reduced peak flows of 14-70% were simulated by mid-century. The simulated total annual streamflow, though, fell within the historic interquartile range for most years in the future period. These and other metrics considered suggest that the surface water hydrology of the Big Wood Basin is likely to be impacted by climate change. If the natural water storage provided by the annual snowpack is reduced and timing of streamflows shifts, water resource use and management may need to change in the future. This work provides a foundation from which to explore alternative management scenarios. The approach used here can be transferred to other watersheds to further assess how water resources may be affected by climate change.


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