Santa Clara University
SCVWD Runoff and System Operation Analysis[Authors]IntroductionHuman-caused climate disruption is already affecting hydrologic systems and will produce increasing impacts through the 21st century ADDIN EN.CITE <EndNote><Cite><Author>Melillo</Author><Year>2014</Year><RecNum>1375</RecNum><DisplayText>(Melillo<style face="italic"> et al.</style>, 2014)</DisplayText><record><rec-number>1375</rec-number><foreign-keys><key app="EN" db-id="p0v2vwzem5s2taer90pv90xiwaswvzstwr29" timestamp="1472604482">1375</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Melillo, Jerry M</author><author>Richmond, Terese TC</author><author>Yohe, GW</author></authors></contributors><titles><title>Climate change impacts in the United States</title><secondary-title>Third National Climate Assessment</secondary-title></titles><periodical><full-title>Third National Climate Assessment</full-title></periodical><dates><year>2014</year></dates><urls></urls></record></Cite></EndNote>(Melillo et al., 2014). In California these impacts include increasing intensity and duration of droughts ADDIN EN.CITE <EndNote><Cite><Author>Diffenbaugh</Author><Year>2015</Year><RecNum>1376</RecNum><DisplayText>(Diffenbaugh<style face="italic"> et al.</style>, 2015; Mann & Gleick, 2015)</DisplayText><record><rec-number>1376</rec-number><foreign-keys><key app="EN" db-id="p0v2vwzem5s2taer90pv90xiwaswvzstwr29" timestamp="1472604643">1376</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Diffenbaugh, Noah S</author><author>Swain, Daniel L</author><author>Touma, Danielle</author></authors></contributors><titles><title>Anthropogenic warming has increased drought risk in California</title><secondary-title>Proceedings of the National Academy of Sciences</secondary-title></titles><periodical><full-title>Proceedings of the National Academy of Sciences</full-title><abbr-1>Proc. National Academy Sci.</abbr-1></periodical><pages>3931-3936</pages><volume>112</volume><number>13</number><dates><year>2015</year></dates><isbn>0027-8424</isbn><urls></urls></record></Cite><Cite><Author>Mann</Author><Year>2015</Year><RecNum>1377</RecNum><record><rec-number>1377</rec-number><foreign-keys><key app="EN" db-id="p0v2vwzem5s2taer90pv90xiwaswvzstwr29" timestamp="1472604653">1377</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Mann, Michael E</author><author>Gleick, Peter H</author></authors></contributors><titles><title>Climate change and California drought in the 21st century</title><secondary-title>Proceedings of the National Academy of Sciences</secondary-title></titles><periodical><full-title>Proceedings of the National Academy of Sciences</full-title><abbr-1>Proc. National Academy Sci.</abbr-1></periodical><pages>3858-3859</pages><volume>112</volume><number>13</number><dates><year>2015</year></dates><isbn>0027-8424</isbn><urls></urls></record></Cite></EndNote>(Diffenbaugh et al., 2015; Mann & Gleick, 2015) and increasing floods due to changing precipitation patterns and snowmelt dynamics PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5QaWVyY2U8L0F1dGhvcj48WWVhcj4yMDEzPC9ZZWFyPjxS
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ADDIN EN.CITE.DATA (Das et al., 2013; Pierce et al., 2013). For managed water systems, these changes can cause complex interactions ADDIN EN.CITE <EndNote><Cite><Author>Hanak</Author><Year>2012</Year><RecNum>1378</RecNum><DisplayText>(Anderson<style face="italic"> et al.</style>, 2008; Hanak & Lund, 2012)</DisplayText><record><rec-number>1378</rec-number><foreign-keys><key app="EN" db-id="p0v2vwzem5s2taer90pv90xiwaswvzstwr29" timestamp="1472604914">1378</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Hanak, Ellen</author><author>Lund, Jay R</author></authors></contributors><titles><title>Adapting California’s water management to climate change</title><secondary-title>Climatic Change</secondary-title></titles><periodical><full-title>Climatic Change</full-title><abbr-1>Climatic Change</abbr-1></periodical><pages>17-44</pages><volume>111</volume><number>1</number><dates><year>2012</year></dates><isbn>0165-0009</isbn><urls></urls></record></Cite><Cite><Author>Anderson</Author><Year>2008</Year><RecNum>417</RecNum><record><rec-number>417</rec-number><foreign-keys><key app="EN" db-id="p0v2vwzem5s2taer90pv90xiwaswvzstwr29" timestamp="0">417</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Anderson, J.</author><author>Chung, F.</author><author>Anderson, M.</author><author>Brekke, L.D.</author><author>Easton, D.</author><author>Ejeta, M.</author><author>Peterson, R.</author><author>Snyder, R.</author></authors></contributors><titles><title>Progress on incorporating climate change into management of California’s water resources</title><secondary-title>Climatic Change</secondary-title></titles><periodical><full-title>Climatic Change</full-title><abbr-1>Climatic Change</abbr-1></periodical><pages>S91–S108, DOI 10.1007/s10584-007-9353-1</pages><volume>87 (Suppl 1)</volume><dates><year>2008</year></dates><urls></urls></record></Cite></EndNote>(Anderson et al., 2008; Hanak & Lund, 2012), which can require modifications to operating decisions or produce changes in the reliability of water deliveries or the level of flood protection. To assess the risks posed by climate change to a managed water system, a typical approach uses projected meteorology (precipitation, temperature) to drive a hydrology model, which produces new inflows to the managed system PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5IYW1sZXQ8L0F1dGhvcj48WWVhcj4xOTk5PC9ZZWFyPjxS
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ADDIN EN.CITE.DATA (e.g., Brekke et al., 2004; Hamlet & Lettenmaier, 1999; Vicuna et al., 2010). While hydrology models can perform quite well by many metrics, even small biases can be enough to confound the use of the generated flows by a water resources system model. For this reason, alternative approaches are often employed that make use of existing data sets of inflows, perturbing them to reflect system inflows in a changed climate scenario ADDIN EN.CITE <EndNote><Cite><Author>Snover</Author><Year>2003</Year><RecNum>1337</RecNum><DisplayText>(Snover<style face="italic"> et al.</style>, 2003; Vicuna<style face="italic"> et al.</style>, 2007)</DisplayText><record><rec-number>1337</rec-number><foreign-keys><key app="EN" db-id="p0v2vwzem5s2taer90pv90xiwaswvzstwr29" timestamp="1452555459">1337</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Snover, Amy K.</author><author>Hamlet, Alan F.</author><author>Lettenmaier, Dennis P.</author></authors></contributors><titles><title>Climate-Change Scenarios for Water Planning Studies: Pilot Applications in the Pacific Northwest</title><secondary-title>Bulletin of the American Meteorological Society</secondary-title></titles><periodical><full-title>Bulletin of the American Meteorological Society</full-title><abbr-1>Bull. Am. Met. Soc.</abbr-1></periodical><pages>1513-1518</pages><volume>84</volume><number>11</number><dates><year>2003</year><pub-dates><date>2003/11/01</date></pub-dates></dates><publisher>American Meteorological Society</publisher><isbn>0003-0007</isbn><urls><related-urls><url> app="EN" db-id="p0v2vwzem5s2taer90pv90xiwaswvzstwr29" timestamp="1472606204">1380</key></foreign-keys><ref-type name="Generic">13</ref-type><contributors><authors><author>Vicuna, Sebastian</author><author>Maurer, Edwin P</author><author>Joyce, Brian</author><author>Dracup, John A</author><author>Purkey, David</author></authors></contributors><titles><title>The sensitivity of California water resources to climate change scenarios</title></titles><dates><year>2007</year></dates><publisher>Wiley Online Library</publisher><isbn>1752-1688</isbn><urls></urls></record></Cite></EndNote>(Snover et al., 2003; Vicuna et al., 2007). Bias correcting land surface runoff or routed streamflows has been successfully used in different hydrologic forecasting environments, as well as in climate change studies PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5ZdWFuPC9BdXRob3I+PFllYXI+MjAxMjwvWWVhcj48UmVj
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ADDIN EN.CITE.DATA (Maurer et al., 2014; Reclamation, 2013). These projections are based on precipitation and temperature output from global climate models (or general circulation models, GCMs) simulations conducted as part of the Coupled Model Intercomparison Project Phase 5 ADDIN EN.CITE <EndNote><Cite><Author>Taylor</Author><Year>2012</Year><RecNum>670</RecNum><Prefix>CMIP5`, </Prefix><DisplayText>(CMIP5, Taylor<style face="italic"> et al.</style>, 2012)</DisplayText><record><rec-number>670</rec-number><foreign-keys><key app="EN" db-id="p0v2vwzem5s2taer90pv90xiwaswvzstwr29" timestamp="1339370503">670</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Taylor, K.E.</author><author>Stouffer, R.J.</author><author>Meehl, G.A.</author></authors></contributors><titles><title>An Overview of CMIP5 and the experiment design</title><secondary-title>Bulletin of the American Meteorological Society</secondary-title></titles><periodical><full-title>Bulletin of the American Meteorological Society</full-title><abbr-1>Bull. Am. Met. Soc.</abbr-1></periodical><pages>485-498, doi: 10.1175/BAMS-D-11-00094.1</pages><volume>93</volume><dates><year>2012</year></dates><urls></urls></record></Cite></EndNote>(CMIP5, Taylor et al., 2012), which formed the basis for the climate projections used in the Fifth Assessment of the Intergovernmental Panel on Climate Change ADDIN EN.CITE <EndNote><Cite><Author>IPCC</Author><Year>2013</Year><RecNum>855</RecNum><DisplayText>(IPCC, 2013)</DisplayText><record><rec-number>855</rec-number><foreign-keys><key app="EN" db-id="p0v2vwzem5s2taer90pv90xiwaswvzstwr29" timestamp="1427139818">855</key></foreign-keys><ref-type name="Book">6</ref-type><contributors><authors><author>IPCC</author></authors><tertiary-authors><author>T.F. Stocker</author><author>D. Qin</author><author>G.-K. Plattner</author><author>M. Tignor</author><author>S.K. Allen</author><author>J. Boschung</author><author>A. Nauels</author><author>Y. Xia</author><author>V. Bex</author><author>P.M. Midgley</author></tertiary-authors></contributors><titles><title>Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change</title></titles><pages>1535</pages><dates><year>2013</year></dates><pub-location>Cambridge, United Kingdom and New York, NY, USA</pub-location><publisher>Cambridge University Press</publisher><isbn>ISBN 978-1-107-66182-0</isbn><urls><related-urls><url></url></related-urls></urls><electronic-resource-num>10.1017/CBO9781107415324</electronic-resource-num></record></Cite></EndNote>(IPCC, 2013). Since the climate model output is at a native spatial scale of 100 km or more, it must be downscaled to provide regionally-applicable information. The precipitation and temperature data obtained for this study was downscaled to 1/8° latitude/longitude resolution (~ 12 km) using the BCSD method, originally developed by Wood et al. PEVuZE5vdGU+PENpdGUgRXhjbHVkZUF1dGg9IjEiPjxBdXRob3I+V29vZDwvQXV0aG9yPjxZZWFy
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ADDIN EN.CITE.DATA (e.g., Barnett et al., 2008; Das et al., 2013; Ficklin et al., 2012) and around the globe ADDIN EN.CITE <EndNote><Cite><Author>Girvetz</Author><Year>2009</Year><RecNum>483</RecNum><DisplayText>(Girvetz<style face="italic"> et al.</style>, 2009)</DisplayText><record><rec-number>483</rec-number><foreign-keys><key app="EN" db-id="p0v2vwzem5s2taer90pv90xiwaswvzstwr29" timestamp="1264808177">483</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Girvetz, E.H.</author><author>Zganjar, C.</author><author>Raber, G.T.</author><author>Maurer, E.P.</author><author>Kareiva, P.</author><author>Lawler, J.J.</author></authors></contributors><titles><title>Applied Climate-Change Analysis: The Climate Wizard Tool</title><secondary-title>PLoS ONE</secondary-title></titles><periodical><full-title>PLoS ONE</full-title></periodical><pages>e8320</pages><volume>4</volume><number>12</number><dates><year>2009</year></dates><publisher>Public Library of Science</publisher><urls><related-urls><url>;(Girvetz et al., 2009) in studies of the hydrological impact of climate change.As part of a past effort ADDIN EN.CITE <EndNote><Cite><Author>Reclamation</Author><Year>2011</Year><RecNum>739</RecNum><DisplayText>(Reclamation, 2011)</DisplayText><record><rec-number>739</rec-number><foreign-keys><key app="EN" db-id="p0v2vwzem5s2taer90pv90xiwaswvzstwr29" timestamp="1354051216">739</key></foreign-keys><ref-type name="Report">27</ref-type><contributors><authors><author>Reclamation</author></authors></contributors><titles><title>West-Wide Climate Risk Assessments: Bias-Corrected and Spatially Downscaled Surface Water Projections, Technical Memorandum No. 86-68210–2011-01</title></titles><pages>138</pages><dates><year>2011</year></dates><pub-location>Denver, Colorado</pub-location><publisher>U.S. Dept. of Interior – Bureau of Reclamation, Technical Service Center</publisher><urls></urls></record></Cite></EndNote>(Reclamation, 2011), the downscaled precipitation and temperature projections for the period 1950-2099 were used to drive the Variable Infiltration Capacity ADDIN EN.CITE <EndNote><Cite><Author>Liang</Author><Year>1994</Year><RecNum>22</RecNum><Prefix>VIC`, </Prefix><DisplayText>(VIC, Liang<style face="italic"> et al.</style>, 1994)</DisplayText><record><rec-number>22</rec-number><foreign-keys><key app="EN" db-id="p0v2vwzem5s2taer90pv90xiwaswvzstwr29" timestamp="0">22</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Liang, X.</author><author>Lettenmaier, D.P.</author><author>Wood, E.</author><author>Burges, S.J.</author></authors></contributors><titles><title>A simple hydrologically based model of land surface water and energy fluxes for general circulation models</title><secondary-title>Journal of Geophysical Research</secondary-title></titles><periodical><full-title>Journal of Geophysical Research</full-title><abbr-1>J. Geophys Res.</abbr-1></periodical><pages>14415-14428</pages><volume>99</volume><number>D7</number><dates><year>1994</year></dates><urls></urls></record></Cite></EndNote>(VIC, Liang et al., 1994) hydrology model, producing runoff estimates across the conterminous U.S. For this study, we used precipitation, temperature, and runoff produced by the 10 GCMs listed in Table 1. For the data based on each GCM run, we used a historical simulation and the future projection associated with the emission pathway RCP8.5 (for which the total added radiative forcing at year 2100 is 8.5 W/m2), which represents increasing greenhouse gas emissions essentially as a business-as-usual scenario and also most closely traces observed emissions thus far in the 21st century ADDIN EN.CITE <EndNote><Cite><Author>Fuss</Author><Year>2014</Year><RecNum>1345</RecNum><DisplayText>(Fuss<style face="italic"> et al.</style>, 2014)</DisplayText><record><rec-number>1345</rec-number><foreign-keys><key app="EN" db-id="p0v2vwzem5s2taer90pv90xiwaswvzstwr29" timestamp="1459982094">1345</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Fuss, Sabine</author><author>Canadell, Josep G.</author><author>Peters, Glen P.</author><author>Tavoni, Massimo</author><author>Andrew, Robbie M.</author><author>Ciais, Philippe</author><author>Jackson, Robert B.</author><author>Jones, Chris D.</author><author>Kraxner, Florian</author><author>Nakicenovic, Nebosja</author><author>Le Quere, Corinne</author><author>Raupach, Michael R.</author><author>Sharifi, Ayyoob</author><author>Smith, Pete</author><author>Yamagata, Yoshiki</author></authors></contributors><titles><title>Betting on negative emissions</title><secondary-title>Nature Clim. Change</secondary-title></titles><periodical><full-title>Nature Clim. Change</full-title></periodical><pages>850-853</pages><volume>4</volume><number>10</number><dates><year>2014</year><pub-dates><date>10//print</date></pub-dates></dates><publisher>Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.</publisher><isbn>1758-678X</isbn><work-type>Commentary</work-type><urls><related-urls><url>;(Fuss et al., 2014).[describe the delta method here]A second method used to perturb the design SCVWD inflow sequences was the Hybrid Delta method ADDIN EN.CITE <EndNote><Cite><Author>Tohver</Author><Year>2014</Year><RecNum>1374</RecNum><DisplayText>(Tohver<style face="italic"> et al.</style>, 2014)</DisplayText><record><rec-number>1374</rec-number><foreign-keys><key app="EN" db-id="p0v2vwzem5s2taer90pv90xiwaswvzstwr29" timestamp="1472070419">1374</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Tohver, Ingrid M.</author><author>Hamlet, Alan F.</author><author>Lee, Se-Yeun</author></authors></contributors><titles><title>Impacts of 21st-Century Climate Change on Hydrologic Extremes in the Pacific Northwest Region of North America</title><secondary-title>JAWRA Journal of the American Water Resources Association</secondary-title></titles><periodical><full-title>JAWRA Journal of the American Water Resources Association</full-title></periodical><pages>1461-1476</pages><volume>50</volume><number>6</number><keywords><keyword>Columbia River basin</keyword><keyword>hydrologic extremes</keyword><keyword>flood</keyword><keyword>low flow</keyword><keyword>climate change</keyword><keyword>downscaled global climate models</keyword><keyword>hydrologic models</keyword></keywords><dates><year>2014</year></dates><isbn>1752-1688</isbn><urls><related-urls><url>;(Tohver et al., 2014), as applied directly to streamflow for bias correction ADDIN EN.CITE <EndNote><Cite><Author>Snover</Author><Year>2003</Year><RecNum>1337</RecNum><DisplayText>(Snover<style face="italic"> et al.</style>, 2003)</DisplayText><record><rec-number>1337</rec-number><foreign-keys><key app="EN" db-id="p0v2vwzem5s2taer90pv90xiwaswvzstwr29" timestamp="1452555459">1337</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Snover, Amy K.</author><author>Hamlet, Alan F.</author><author>Lettenmaier, Dennis P.</author></authors></contributors><titles><title>Climate-Change Scenarios for Water Planning Studies: Pilot Applications in the Pacific Northwest</title><secondary-title>Bulletin of the American Meteorological Society</secondary-title></titles><periodical><full-title>Bulletin of the American Meteorological Society</full-title><abbr-1>Bull. Am. Met. Soc.</abbr-1></periodical><pages>1513-1518</pages><volume>84</volume><number>11</number><dates><year>2003</year><pub-dates><date>2003/11/01</date></pub-dates></dates><publisher>American Meteorological Society</publisher><isbn>0003-0007</isbn><urls><related-urls><url>;(Snover et al., 2003). This method as used in this study applies a common quantile mapping procedure ADDIN EN.CITE <EndNote><Cite><Author>Panofsky</Author><Year>1968</Year><RecNum>369</RecNum><DisplayText>(Gudmundsson<style face="italic"> et al.</style>, 2012; Panofsky & Brier, 1968)</DisplayText><record><rec-number>369</rec-number><foreign-keys><key app="EN" db-id="p0v2vwzem5s2taer90pv90xiwaswvzstwr29" timestamp="0">369</key></foreign-keys><ref-type name="Book">6</ref-type><contributors><authors><author>Panofsky, H.A.</author><author>Brier, G.W.</author></authors></contributors><titles><title>Some Applications of Statistics to Meteorology</title></titles><pages>224</pages><dates><year>1968</year></dates><pub-location>University Park, PA, USA</pub-location><publisher>The Pennsylvania State University</publisher><urls></urls></record></Cite><Cite><Author>Gudmundsson</Author><Year>2012</Year><RecNum>732</RecNum><record><rec-number>732</rec-number><foreign-keys><key app="EN" db-id="p0v2vwzem5s2taer90pv90xiwaswvzstwr29" timestamp="1354046613">732</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Gudmundsson, L.</author><author>Bremnes, J. B.</author><author>Haugen, J. E.</author><author>Engen-Skaugen, T.</author></authors></contributors><titles><title>Technical Note: Downscaling RCM precipitation to the station scale using statistical transformations - a comparison of methods</title><secondary-title>Hydrol. Earth Syst. Sci.</secondary-title></titles><periodical><full-title>Hydrol. Earth Syst. Sci.</full-title></periodical><pages>3383-3390</pages><volume>16</volume><number>9</number><dates><year>2012</year></dates><publisher>Copernicus Publications</publisher><isbn>1607-7938</isbn><urls><related-urls><url>;(Gudmundsson et al., 2012; Panofsky & Brier, 1968) to monthly streamflows. For each representative point (labeled E and W in Figure 1) sequences of runoff were obtained from the archive described above, and these were adjusted as described below. Each runoff sequence was bias-corrected using quantile mapping, using the overlapping 1950-1999 period as the base climatology. This procedure involves separating the data (for 1950-1999) by month, and for each month assembling all inflow values for both the historic sequence (the SCVWD data) and the VIC-produced simulated runoff into cumulative distribution functions (CDFs), producing 12 CDFs for the VIC simulated flows and 12 for observed inflows. Then for each month in the VIC simulation (using the entire 1950-2099 period), the quantile is determined using the CDF for VIC simulations, and a new value is drawn for the same quantile from the observation-based CDF. This produces a new 1950-2099 runoff sequence that statistically matches the observations for the 1950-1999 period (though, importantly, sequencing is not preserved) but evolves into the future as simulated by each GCM. These are referred to here as ‘bias-corrected’ inflowsFinally, an inverse quantile mapping is applied to ‘perturb’ the historic SCVWD record of reservoir inflows. This uses a similar method to that above, but develops new sets of CDFs, both based on the bias-corrected inflows. The first is for 1950-1999, representing recent historical values, and the second based on 2025-2054, representing a changed climatology applicable to the 2040 planning horizon. The historical SCVWD inflows (for 1922-2015) are then adjusted with a quantile mapping from the historic to the future CDFs. This results in a sequence of inflows that has the same temporal pattern as the historical sequence, including extended dry and wet periods, but including projected changes as indicated by the downscaled GCM precipitation and temperature.[describe SWAT modeling][describe methods of analyzing output, statistical tests, …]Results and DiscussionConclusionsReferences ADDIN EN.REFLIST Anderson, J., Chung, F., Anderson, M., Brekke, L. D., Easton, D., Ejeta, M., Peterson, R., & Snyder, R. (2008). 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Water Resources Research, 48(12), W12519.Table SEQ Table \* ARABIC 1 - GCMs included in this study.GCM No.Model NameModeling Group1gfdl-esm2g NOAA Geophysical Fluid Dynamics Laboratory2canesm2 Canadian Centre for Climate Modelling and Analysis3cnrm-cm5 Centre National de Recherches Météorologiques / Centre Européen de Recherche et Formation Avancée en Calcul Scientifique4csiro-mk3-6-0 Commonwealth Scientific and Industrial Research Organization in collaboration with Queensland Climate Change Centre of Excellence5inmcm4 Institute for Numerical Mathematics6miroc5 Atmosphere and Ocean Research Institute (The University of Tokyo), National Institute for Environmental Studies, and Japan Agency for Marine-Earth Science and Technology7mpi-esm-lr Max-Planck-Institut für Meteorologie (Max Planck Institute for Meteorology)8mri-cgcm3 Meteorological Research Institute9ccsm4 National Center for Atmospheric Research10noresm1-m Norwegian Climate CentreFigure SEQ Figure \* ARABIC 1 - Region of Study: cross-hatching indicates areas draining into SCVWD reservoirs; points labeled W and E are the two representative locations used for each side of the valley. ................
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