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  • 1
    Electronic Resource
    Electronic Resource
    Oxford, UK : Blackwell Publishing Ltd
    Journal of the American Water Resources Association 29 (1993), S. 0 
    ISSN: 1752-1688
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Architecture, Civil Engineering, Surveying , Geography
    Notes: : The Gunnison River drains a mountainous basin in western Colorado, and is a large contributor of water to the Colorado River. As part of a study to assess water resource sensitivity to alterations in climate in the Gunnison River basin, climatic and hydrologic processes are being modeled. A geographic information system (GIS) is being used in this study as a link between data and modelers - serving as a common data base for project personnel with differing specialties, providing a means to investigate the effects of scale on model results, and providing a framework for the transfer of parameter values among models. Specific applications presented include: (1) developing elevation grids for a precipitation model from digital elevation model (DEM) point-elevation values, and visualizing the effects of grid resolution on model results; (2) using a GIS to facilitate the definition and parameterization of a distributed-parameters, watershed model in multiple basins; and (3) nesting atmospheric and hydrologic models to produce possible scenarios of climate change.
    Type of Medium: Electronic Resource
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  • 2
    Electronic Resource
    Electronic Resource
    Oxford, UK : Blackwell Publishing Ltd
    Journal of the American Water Resources Association 26 (1990), S. 0 
    ISSN: 1752-1688
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Architecture, Civil Engineering, Surveying , Geography
    Notes: : The Thornthwaite moisture index is a useful indicator of the supply of water (precipitation) in an area relative to the demand for water under prevailing climatic conditions (potential evapotranspiration). This study examines the effects of changes in climate (temperature and precipitation) on the Thornthwaite moisture index in the conterminous United States. Estimates of changes in mean annual temperature and precipitation for doubled-atmospheric CO2 conditions derived from three general circulation models (GCMs) are used to study the response of the moisture index under steady-state doubled-CO2 conditions. Results indicate that temperature and precipitation changes under doubled-CO2 conditions generally will cause the Thornthwaite moisture index to decrease, implying a drier climate for most of the United States. The pattern of expected decrease is consistent among the three GCMs, although the amount of decrease depends on which GCM climatic-change scenario is used. Results also suggest that changes in the moisture index are related mainly to changes in the mean annual potential evapotranspiration as a result of changes in the mean annual temperature, rather than to changes in the mean annual precipitation.
    Type of Medium: Electronic Resource
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  • 3
    Electronic Resource
    Electronic Resource
    Oxford, UK : Blackwell Publishing Ltd
    Journal of the American Water Resources Association 34 (1998), S. 0 
    ISSN: 1752-1688
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Architecture, Civil Engineering, Surveying , Geography
    Notes: : Observed April 1 snowpack accumulations within and near the Gunnison River basin in southwestern Colorado are compared with simulations from the Rhea-orographic-precipitation model to determine if the model simulates reliable magnitudes and temporal and spatial variability in winter precipitation for the basin. Twenty simulations of the Rhea model were performed using‘optimal’parameter sets determined for 10-kilometer (km) grids (10-km by 10-km grid cells) through stochastic calibration. Comparisons of Rhea-model simulations of winter precipitation with April 1 snowpack accumulations at 32 snowcourse stations were performed for the years 1972–1990. For most stations and most years the Rhea model reliably simulates the temporal and spatial variability in April 1 snowpack accumulations. However, in general, the Rhea-model underestimates April 1 snowpack accumulations in the Gunnison River basin area, and the underestimation is greatest for locations that receive the largest amount of snow. A significant portion of the error in Rhea-model simulations is due to the calibration of the Rhea model using gauge-catch precipitation measurements which can be as much as 50 percent below actual snowfall accumulations. Additional error in the Rhea-model simulations is a result of the comparison of gridded precipitation values to observed values measured at points.
    Type of Medium: Electronic Resource
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  • 4
    Electronic Resource
    Electronic Resource
    Oxford, UK : Blackwell Publishing Ltd
    Journal of the American Water Resources Association 38 (2002), S. 0 
    ISSN: 1752-1688
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Architecture, Civil Engineering, Surveying , Geography
    Notes: : A monthly water-balance (WB) model was tested in 44 river basins from diverse physiographic and climatic regions across the conterminous United States (U.S.). The WB model includes the concepts of climatic water supply and climatic water demand, seasonality in climatic water supply and demand, and soil-moisture storage. Exhaustive search techniques were employed to determine the optimal set of precipitation and temperature stations, and the optimal set of WB model parameters to use for each basin. It was found that the WB model worked best for basins with: (1) a mean elevation less than 450 meters or greater than 2000 meters, and/or (2) monthly runoff that is greater than 5 millimeters (mm) more than 80 percent of the time. In a separate analysis, a multiple linear regression (MLR) was computed using the adjusted R-square values obtained by comparing measured and estimated monthly runoff of the original 44 river basins as the dependent variable, and combinations of various independent variables [streamflow gauge latitude, longitude, and elevation; basin area, the long-term mean and standard deviation of annual precipitation; temperature and runoff; and low-flow statistics (i.e., the percentage of months with monthly runoff that is less than 5 mm)]. Results from the MLR study showed that the reliability of a WB model for application in a specific region can be estimated from mean basin elevation and the percentage of months with gauged runoff less than 5 mm. The MLR equations were subsequently used to estimate adjusted R-square values for 1,646 gauging stations across the conterminous U.S. Results of this study indicate that WB models can be used reliably to estimate monthly runoff in the eastern U.S., mountainous areas of the western U.S., and the Pacific Northwest. Applications of monthly WB models in the central U.S. can lead to uncertain estimates of runoff.
    Type of Medium: Electronic Resource
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  • 5
    Electronic Resource
    Electronic Resource
    Oxford, UK : Blackwell Publishing Ltd
    Journal of the American Water Resources Association 36 (2000), S. 0 
    ISSN: 1752-1688
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Architecture, Civil Engineering, Surveying , Geography
    Notes: : Simulated daily precipitation, temperature, and runoff time series were compared in three mountainous basins in the United States: (1) the Animas River basin in Colorado, (2) the East Fork of the Carson River basin in Nevada and California, and (3) the Cle Elum River basin in Washington State. Two methods of climate scenario generation were compared: delta change and statistical downscaling. The delta change method uses differences between simulated current and future climate conditions from the Hadley Centre for Climate Prediction and Research (HadCM2) General Circulation Model (GCM) added to observed time series of climate variables. A statistical downscaling (SDS) model was developed for each basin using station data and output from the National Center for Environmental Prediction/National Center for Atmospheric Research (NCEPINCAR) reanalysis regridded to the scale of HadCM2. The SDS model was then used to simulate local climate variables using HadCM2 output for current and future conditions. Surface climate variables from each scenario were used in a precipitation-runoff model. Results from this study show that, in the basins tested, a precipitation-runoff model can simulate realistic runoff series for current conditions using statistically down-scaled NCEP output. But, use of downscaled HadCM2 output for current or future climate assessments are questionable because the GCM does not produce accurate estimates of the surface variables needed for runoff in these regions. Given the uncertainties in the GCMs ability to simulate current conditions based on either the delta change or downscaling approaches, future climate assessments based on either of these approaches must be treated with caution.
    Type of Medium: Electronic Resource
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  • 6
  • 7
    Publication Date: 2018-05-01
    Description: The accuracy of statistically downscaled (SD) general circulation model (GCM) simulations of monthly surface climate for historical conditions (1950–2005) was assessed for the conterminous United States (CONUS). The SD monthly precipitation (PPT) and temperature (TAVE) from 95 GCMs from phases 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5) were used as inputs to a monthly water balance model (MWBM). Distributions of MWBM input (PPT and TAVE) and output [runoff (RUN)] variables derived from gridded station data (GSD) and historical SD climate were compared using the Kolmogorov–Smirnov (KS) test For all three variables considered, the KS test results showed that variables simulated using CMIP5 generally are more reliable than those derived from CMIP3, likely due to improvements in PPT simulations. At most locations across the CONUS, the largest differences between GSD and SD PPT and RUN occurred in the lowest part of the distributions (i.e., low-flow RUN and low-magnitude PPT). Results indicate that for the majority of the CONUS, there are downscaled GCMs that can reliably simulate historical climatic conditions. But, in some geographic locations, none of the SD GCMs replicated historical conditions for two of the three variables (PPT and RUN) based on the KS test, with a significance level of 0.05. In these locations, improved GCM simulations of PPT are needed to more reliably estimate components of the hydrologic cycle. Simple metrics and statistical tests, such as those described here, can provide an initial set of criteria to help simplify GCM selection.
    Electronic ISSN: 1087-3562
    Topics: Geography , Geosciences , Physics
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  • 8
    Publication Date: 2015-12-17
    Description: Continental-domain assessments of climate change impacts on water resources typically rely on statistically downscaled climate model outputs to force hydrologic models at a finer spatial resolution. This study examines the effects of four statistical downscaling methods [bias-corrected constructed analog (BCCA), bias-corrected spatial disaggregation applied at daily (BCSDd) and monthly scales (BCSDm), and asynchronous regression (AR)] on retrospective hydrologic simulations using three hydrologic models with their default parameters (the Community Land Model, version 4.0; the Variable Infiltration Capacity model, version 4.1.2; and the Precipitation–Runoff Modeling System, version 3.0.4) over the contiguous United States (CONUS). Biases of hydrologic simulations forced by statistically downscaled climate data relative to the simulation with observation-based gridded data are presented. Each statistical downscaling method produces different meteorological portrayals including precipitation amount, wet-day frequency, and the energy input (i.e., shortwave radiation), and their interplay affects estimations of precipitation partitioning between evapotranspiration and runoff, extreme runoff, and hydrologic states (i.e., snow and soil moisture). The analyses show that BCCA underestimates annual precipitation by as much as −250 mm, leading to unreasonable hydrologic portrayals over the CONUS for all models. Although the other three statistical downscaling methods produce a comparable precipitation bias ranging from −10 to 8 mm across the CONUS, BCSDd severely overestimates the wet-day fraction by up to 0.25, leading to different precipitation partitioning compared to the simulations with other downscaled data. Overall, the choice of downscaling method contributes to less spread in runoff estimates (by a factor of 1.5–3) than the choice of hydrologic model with use of the default parameters if BCCA is excluded.
    Print ISSN: 1525-755X
    Electronic ISSN: 1525-7541
    Topics: Geography , Geosciences , Physics
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  • 9
  • 10
    Publication Date: 2020-01-19
    Print ISSN: 1354-1013
    Electronic ISSN: 1365-2486
    Topics: Biology , Energy, Environment Protection, Nuclear Power Engineering , Geography
    Published by Wiley
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