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Press, 996 pp . Tang , Z. , B. A. Engel , B. C. Pijanowski , and K. J. Lim , 2005 : Forecasting land use change and its environmental impact at a watershed scale . J. Environ. Manage. , 76 , 35 – 45 . USGS , cited 2009 : Daily streamflow for the nation . U.S. Geological Survey. [Available online at http://waterdata.usgs.gov/nwis/inventory/?site_no=02349500 .] Viger , R. J. , and G. H. Leavesley , 2007 : The GIS Weasel user’s manual . U.S. Geological Survey Techniques and
Press, 996 pp . Tang , Z. , B. A. Engel , B. C. Pijanowski , and K. J. Lim , 2005 : Forecasting land use change and its environmental impact at a watershed scale . J. Environ. Manage. , 76 , 35 – 45 . USGS , cited 2009 : Daily streamflow for the nation . U.S. Geological Survey. [Available online at http://waterdata.usgs.gov/nwis/inventory/?site_no=02349500 .] Viger , R. J. , and G. H. Leavesley , 2007 : The GIS Weasel user’s manual . U.S. Geological Survey Techniques and
discharge for each year in each simulation. For a particular simulation period, this results in an m × n matrix containing the ensemble of model forecasts, representing m years of annual maximum daily discharges (11 years) and n GCM–scenario combinations (15 members). A log transformation of the annual maximum discharges was used to ensure that discharges generated by the resampling approach would be nonnegative. Thus, the term x i , j represents the natural log of the maximum daily
discharge for each year in each simulation. For a particular simulation period, this results in an m × n matrix containing the ensemble of model forecasts, representing m years of annual maximum daily discharges (11 years) and n GCM–scenario combinations (15 members). A log transformation of the annual maximum discharges was used to ensure that discharges generated by the resampling approach would be nonnegative. Thus, the term x i , j represents the natural log of the maximum daily
agricultural production and water supply in the study basins. An increase in temperature has the potential to impact agricultural production due to the northern migration of competing plants and an increase in insects that is expected to accompany the forecast climate changes ( Janetos et al. 2008 ). In the fire-prone areas of the Rockies and Sierra Nevada study basins, an increase in GSL can cause an increase in tree mortality, which can increase the fuel sources for potential wildfires ( Ryan et al. 2008
agricultural production and water supply in the study basins. An increase in temperature has the potential to impact agricultural production due to the northern migration of competing plants and an increase in insects that is expected to accompany the forecast climate changes ( Janetos et al. 2008 ). In the fire-prone areas of the Rockies and Sierra Nevada study basins, an increase in GSL can cause an increase in tree mortality, which can increase the fuel sources for potential wildfires ( Ryan et al. 2008
distributed watershed models that simulate streamflow in addition to various water and energy fluxes within a basin. Dibike and Coulibaly ( Dibike and Coulibaly 2005 ) compared two statistical downscaling and hydrologic modeling techniques to simulate runoff in a watershed in northern Quebec, Canada. Both downscaling methods resulted in increased winter low flow and earlier spring high flows, which was consistent with reduced freezing and increasing trends in temperature and snowmelt. Downscaled data from
distributed watershed models that simulate streamflow in addition to various water and energy fluxes within a basin. Dibike and Coulibaly ( Dibike and Coulibaly 2005 ) compared two statistical downscaling and hydrologic modeling techniques to simulate runoff in a watershed in northern Quebec, Canada. Both downscaling methods resulted in increased winter low flow and earlier spring high flows, which was consistent with reduced freezing and increasing trends in temperature and snowmelt. Downscaled data from
vs streamflow using the five GCMs and three emission scenarios calculated for each of the 88 windows for the 14 selected basins. 5. Discussion There are numerous sources of uncertainty at each step of simulation associated with this study: uncertainty in the GCMs, in the downscaling technique, and in the hydrologic model. Starting with the GCMs, large uncertainties are associated with the representation of the physical processes, model structure, and feedbacks within the climate system ( Alley et
vs streamflow using the five GCMs and three emission scenarios calculated for each of the 88 windows for the 14 selected basins. 5. Discussion There are numerous sources of uncertainty at each step of simulation associated with this study: uncertainty in the GCMs, in the downscaling technique, and in the hydrologic model. Starting with the GCMs, large uncertainties are associated with the representation of the physical processes, model structure, and feedbacks within the climate system ( Alley et
forecasts and limitations of the downscaling technique to interpolate these forecasts to a finer resolution serve as an important constraint on the fineness of the spatial and temporal scales at which the hydrologic modeling can be carried out. As a result, many of the regional hydrologic studies of climate change impacts cited above and in general use lumped or semidistributed models and do not have an explicit routing scheme. Gosling et al. ( Gosling et al. 2010 ) point out that uncertainty of climate
forecasts and limitations of the downscaling technique to interpolate these forecasts to a finer resolution serve as an important constraint on the fineness of the spatial and temporal scales at which the hydrologic modeling can be carried out. As a result, many of the regional hydrologic studies of climate change impacts cited above and in general use lumped or semidistributed models and do not have an explicit routing scheme. Gosling et al. ( Gosling et al. 2010 ) point out that uncertainty of climate
