2017
DOI: 10.1002/hyp.11150
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Integrating downscaled CMIP5 data with a physically based hydrologic model to estimate potential climate change impacts on streamflow processes in a mixed-use watershed

Abstract: Climatic changes have altered surface water regimes worldwide, and climate projections suggest that such alterations will continue. To inform management decisions, climate projections must be paired with hydrologic models to develop quantitative estimates of watershed scale water regime changes. Such modeling approaches often involve downscaling climate model outputs, which are generally presented at coarse spatial scales. In this study, Coupled Model Intercomparison Project Phase 5 climate model projections w… Show more

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Cited by 47 publications
(58 citation statements)
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“…Similar trends were found in other areas in the region, such as Hinkson Creek, Missouri (Sunde et al. ) where elevated future spring and fall total water yield under RCP 8.5 scenario in mid‐century was simulated. Gautam et al.…”
Section: Resultssupporting
confidence: 81%
“…Similar trends were found in other areas in the region, such as Hinkson Creek, Missouri (Sunde et al. ) where elevated future spring and fall total water yield under RCP 8.5 scenario in mid‐century was simulated. Gautam et al.…”
Section: Resultssupporting
confidence: 81%
“…The researchers used a semi-distributed model, Soil and Water Assessment Tool (SWAT), to assess the effect of future climate change on hydrologic components of the Upper Mississippi River Basin. Similar SWAT model studies were able to identify specific changes in local hydrology and ecosystem consequences due to climate change for other watersheds across the globe (Moradkhani et al 2010;Park et al 2011;Ficklin et al 2013;Ye and Grimm 2013;Chattopadhyay et al 2017;Meaurio et al 2017;Sunde et al 2017;Bajracharya et al 2018;Reshmidevi et al 2018). They also evaluated the sensitivity of the Upper Mississippi River Basin to atmospheric, precipitation, and temperature changes.…”
Section: Introductionmentioning
confidence: 90%
“…In this study, the 16 GCMs were statistically downscaled after bias-correlation, making it possible to characterize the potential uncertainties arisen from the GCMs. Moreover, several studies have demonstrated the reliability of the selected GCMs in global and regional climate change studies (Tan et al, 2017;Srinivasa Raju et al, 2017;Sunde et al, 2017;Merabti et al, 2018).…”
Section: Uncertainties Arising From the Future Projectionsmentioning
confidence: 99%