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- Author or Editor: Steven L. Markstrom x
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Abstract
The accuracy of statistically downscaled general circulation model (GCM) simulations of daily surface climate for historical conditions (1961–99) and the implications when they are used to drive hydrologic and stream temperature models were assessed for the Apalachicola–Chattahoochee–Flint River basin (ACFB). The ACFB is a 50 000 km2 basin located in the southeastern United States. Three GCMs were statistically downscaled, using an asynchronous regional regression model (ARRM), to ⅛° grids of daily precipitation and minimum and maximum air temperature. These ARRM-based climate datasets were used as input to the Precipitation-Runoff Modeling System (PRMS), a deterministic, distributed-parameter, physical-process watershed model used to simulate and evaluate the effects of various combinations of climate and land use on watershed response. The ACFB was divided into 258 hydrologic response units (HRUs) in which the components of flow (groundwater, subsurface, and surface) are computed in response to climate, land surface, and subsurface characteristics of the basin. Daily simulations of flow components from PRMS were used with the climate to simulate in-stream water temperatures using the Stream Network Temperature (SNTemp) model, a mechanistic, one-dimensional heat transport model for branched stream networks.
The climate, hydrology, and stream temperature for historical conditions were evaluated by comparing model outputs produced from historical climate forcings developed from gridded station data (GSD) versus those produced from the three statistically downscaled GCMs using the ARRM methodology. The PRMS and SNTemp models were forced with the GSD and the outputs produced were treated as “truth.” This allowed for a spatial comparison by HRU of the GSD-based output with ARRM-based output. Distributional similarities between GSD- and ARRM-based model outputs were compared using the two-sample Kolmogorov–Smirnov (KS) test in combination with descriptive metrics such as the mean and variance and an evaluation of rare and sustained events. In general, precipitation and streamflow quantities were negatively biased in the downscaled GCM outputs, and results indicate that the downscaled GCM simulations consistently underestimate the largest precipitation events relative to the GSD. The KS test results indicate that ARRM-based air temperatures are similar to GSD at the daily time step for the majority of the ACFB, with perhaps subweekly averaging for stream temperature. Depending on GCM and spatial location, ARRM-based precipitation and streamflow requires averaging of up to 30 days to become similar to the GSD-based output.
Evaluation of the model skill for historical conditions suggests some guidelines for use of future projections; while it seems correct to place greater confidence in evaluation metrics which perform well historically, this does not necessarily mean those metrics will accurately reflect model outputs for future climatic conditions. Results from this study indicate no “best” overall model, but the breadth of analysis can be used to give the product users an indication of the applicability of the results to address their particular problem. Since results for historical conditions indicate that model outputs can have significant biases associated with them, the range in future projections examined in terms of change relative to historical conditions for each individual GCM may be more appropriate.
Abstract
The accuracy of statistically downscaled general circulation model (GCM) simulations of daily surface climate for historical conditions (1961–99) and the implications when they are used to drive hydrologic and stream temperature models were assessed for the Apalachicola–Chattahoochee–Flint River basin (ACFB). The ACFB is a 50 000 km2 basin located in the southeastern United States. Three GCMs were statistically downscaled, using an asynchronous regional regression model (ARRM), to ⅛° grids of daily precipitation and minimum and maximum air temperature. These ARRM-based climate datasets were used as input to the Precipitation-Runoff Modeling System (PRMS), a deterministic, distributed-parameter, physical-process watershed model used to simulate and evaluate the effects of various combinations of climate and land use on watershed response. The ACFB was divided into 258 hydrologic response units (HRUs) in which the components of flow (groundwater, subsurface, and surface) are computed in response to climate, land surface, and subsurface characteristics of the basin. Daily simulations of flow components from PRMS were used with the climate to simulate in-stream water temperatures using the Stream Network Temperature (SNTemp) model, a mechanistic, one-dimensional heat transport model for branched stream networks.
The climate, hydrology, and stream temperature for historical conditions were evaluated by comparing model outputs produced from historical climate forcings developed from gridded station data (GSD) versus those produced from the three statistically downscaled GCMs using the ARRM methodology. The PRMS and SNTemp models were forced with the GSD and the outputs produced were treated as “truth.” This allowed for a spatial comparison by HRU of the GSD-based output with ARRM-based output. Distributional similarities between GSD- and ARRM-based model outputs were compared using the two-sample Kolmogorov–Smirnov (KS) test in combination with descriptive metrics such as the mean and variance and an evaluation of rare and sustained events. In general, precipitation and streamflow quantities were negatively biased in the downscaled GCM outputs, and results indicate that the downscaled GCM simulations consistently underestimate the largest precipitation events relative to the GSD. The KS test results indicate that ARRM-based air temperatures are similar to GSD at the daily time step for the majority of the ACFB, with perhaps subweekly averaging for stream temperature. Depending on GCM and spatial location, ARRM-based precipitation and streamflow requires averaging of up to 30 days to become similar to the GSD-based output.
Evaluation of the model skill for historical conditions suggests some guidelines for use of future projections; while it seems correct to place greater confidence in evaluation metrics which perform well historically, this does not necessarily mean those metrics will accurately reflect model outputs for future climatic conditions. Results from this study indicate no “best” overall model, but the breadth of analysis can be used to give the product users an indication of the applicability of the results to address their particular problem. Since results for historical conditions indicate that model outputs can have significant biases associated with them, the range in future projections examined in terms of change relative to historical conditions for each individual GCM may be more appropriate.
Abstract
The hydrologic response of different climate-change emission scenarios for the twenty-first century were evaluated in 14 basins from different hydroclimatic regions across the United States using the Precipitation-Runoff Modeling System (PRMS), a process-based, distributed-parameter watershed model. This study involves four major steps: 1) setup and calibration of the PRMS model in 14 basins across the United States by local U.S. Geological Survey personnel; 2) statistical downscaling of the World Climate Research Programme’s Coupled Model Intercomparison Project phase 3 climate-change emission scenarios to create PRMS input files that reflect these emission scenarios; 3) run PRMS for the climate-change emission scenarios for the 14 basins; and 4) evaluation of the PRMS output.
This paper presents an overview of this project, details of the methodology, results from the 14 basin simulations, and interpretation of these results. A key finding is that the hydrological response of the different geographical regions of the United States to potential climate change may be very different, depending on the dominant physical processes of that particular region. Also considered is the tremendous amount of uncertainty present in the climate emission scenarios and how this uncertainty propagates through the hydrologic simulations. This paper concludes with a discussion of the lessons learned and potential for future work.
Abstract
The hydrologic response of different climate-change emission scenarios for the twenty-first century were evaluated in 14 basins from different hydroclimatic regions across the United States using the Precipitation-Runoff Modeling System (PRMS), a process-based, distributed-parameter watershed model. This study involves four major steps: 1) setup and calibration of the PRMS model in 14 basins across the United States by local U.S. Geological Survey personnel; 2) statistical downscaling of the World Climate Research Programme’s Coupled Model Intercomparison Project phase 3 climate-change emission scenarios to create PRMS input files that reflect these emission scenarios; 3) run PRMS for the climate-change emission scenarios for the 14 basins; and 4) evaluation of the PRMS output.
This paper presents an overview of this project, details of the methodology, results from the 14 basin simulations, and interpretation of these results. A key finding is that the hydrological response of the different geographical regions of the United States to potential climate change may be very different, depending on the dominant physical processes of that particular region. Also considered is the tremendous amount of uncertainty present in the climate emission scenarios and how this uncertainty propagates through the hydrologic simulations. This paper concludes with a discussion of the lessons learned and potential for future work.
Abstract
Understanding the effects of climate change on the vegetative growing season is key to quantifying future hydrologic water budget conditions. The U.S. Geological Survey modeled changes in future growing season length at 14 basins across 11 states. Simulations for each basin were generated using five general circulation models with three emission scenarios as inputs to the Precipitation-Runoff Modeling System (PRMS). PRMS is a deterministic, distributed-parameter, watershed model developed to simulate the effects of various combinations of precipitation, climate, and land use on watershed response. PRMS was modified to include a growing season calculation in this study. The growing season was examined for trends in the total length (annual), as well as changes in the timing of onset (spring) and the end (fall) of the growing season. The results showed an increase in the annual growing season length in all 14 basins, averaging 27–47 days for the three emission scenarios. The change in the spring and fall growing season onset and end varied across the 14 basins, with larger increases in the total length of the growing season occurring in the mountainous regions and smaller increases occurring in the Midwest, Northeast, and Southeast regions. The Clear Creek basin, 1 of the 14 basins in this study, was evaluated to examine the growing season length determined by emission scenario, as compared to a growing season length fixed baseline condition. The Clear Creek basin showed substantial variation in hydrologic responses, including streamflow, as a result of growing season length determined by emission scenario.
Abstract
Understanding the effects of climate change on the vegetative growing season is key to quantifying future hydrologic water budget conditions. The U.S. Geological Survey modeled changes in future growing season length at 14 basins across 11 states. Simulations for each basin were generated using five general circulation models with three emission scenarios as inputs to the Precipitation-Runoff Modeling System (PRMS). PRMS is a deterministic, distributed-parameter, watershed model developed to simulate the effects of various combinations of precipitation, climate, and land use on watershed response. PRMS was modified to include a growing season calculation in this study. The growing season was examined for trends in the total length (annual), as well as changes in the timing of onset (spring) and the end (fall) of the growing season. The results showed an increase in the annual growing season length in all 14 basins, averaging 27–47 days for the three emission scenarios. The change in the spring and fall growing season onset and end varied across the 14 basins, with larger increases in the total length of the growing season occurring in the mountainous regions and smaller increases occurring in the Midwest, Northeast, and Southeast regions. The Clear Creek basin, 1 of the 14 basins in this study, was evaluated to examine the growing season length determined by emission scenario, as compared to a growing season length fixed baseline condition. The Clear Creek basin showed substantial variation in hydrologic responses, including streamflow, as a result of growing season length determined by emission scenario.
Abstract
Changes in temperature and precipitation projected from five general circulation models, using one late-twentieth-century and three twenty-first-century emission scenarios, were downscaled to three different baseline conditions. Baseline conditions are periods of measured temperature and precipitation data selected to represent twentieth-century climate. The hydrologic effects of the climate projections are evaluated using the Precipitation-Runoff Modeling System (PRMS), which is a watershed hydrology simulation model. The Almanor Catchment in the North Fork of the Feather River basin, California, is used as a case study.
Differences and similarities between PRMS simulations of hydrologic components (i.e., snowpack formation and melt, evapotranspiration, and streamflow) are examined, and results indicate that the selection of a specific time period used for baseline conditions has a substantial effect on some, but not all, hydrologic variables. This effect seems to be amplified in hydrologic variables, which accumulate over time, such as soil-moisture content. Results also indicate that uncertainty related to the selection of baseline conditions should be evaluated using a range of different baseline conditions. This is particularly important for studies in basins with highly variable climate, such as the Almanor Catchment.
Abstract
Changes in temperature and precipitation projected from five general circulation models, using one late-twentieth-century and three twenty-first-century emission scenarios, were downscaled to three different baseline conditions. Baseline conditions are periods of measured temperature and precipitation data selected to represent twentieth-century climate. The hydrologic effects of the climate projections are evaluated using the Precipitation-Runoff Modeling System (PRMS), which is a watershed hydrology simulation model. The Almanor Catchment in the North Fork of the Feather River basin, California, is used as a case study.
Differences and similarities between PRMS simulations of hydrologic components (i.e., snowpack formation and melt, evapotranspiration, and streamflow) are examined, and results indicate that the selection of a specific time period used for baseline conditions has a substantial effect on some, but not all, hydrologic variables. This effect seems to be amplified in hydrologic variables, which accumulate over time, such as soil-moisture content. Results also indicate that uncertainty related to the selection of baseline conditions should be evaluated using a range of different baseline conditions. This is particularly important for studies in basins with highly variable climate, such as the Almanor Catchment.
Abstract
The potential effects of long-term urbanization and climate change on the freshwater resources of the Flint River basin were examined by using the Precipitation-Runoff Modeling System (PRMS). PRMS is a deterministic, distributed-parameter watershed model developed to evaluate the effects of various combinations of precipitation, temperature, and land cover on streamflow and multiple intermediate hydrologic states. Precipitation and temperature output from five general circulation models (GCMs) using one current and three future climate-change scenarios were statistically downscaled for input into PRMS. Projections of urbanization through 2050 derived for the Flint River basin by the Forecasting Scenarios of Future Land-Cover (FORE-SCE) land-cover change model were also used as input to PRMS. Comparison of the central tendency of streamflow simulated based on the three climate-change scenarios showed a slight decrease in overall streamflow relative to simulations under current conditions, mostly caused by decreases in the surface-runoff and groundwater components. The addition of information about forecasted urbanization of land surfaces to the hydrologic simulation mitigated the decreases in streamflow, mainly by increasing surface runoff.
Abstract
The potential effects of long-term urbanization and climate change on the freshwater resources of the Flint River basin were examined by using the Precipitation-Runoff Modeling System (PRMS). PRMS is a deterministic, distributed-parameter watershed model developed to evaluate the effects of various combinations of precipitation, temperature, and land cover on streamflow and multiple intermediate hydrologic states. Precipitation and temperature output from five general circulation models (GCMs) using one current and three future climate-change scenarios were statistically downscaled for input into PRMS. Projections of urbanization through 2050 derived for the Flint River basin by the Forecasting Scenarios of Future Land-Cover (FORE-SCE) land-cover change model were also used as input to PRMS. Comparison of the central tendency of streamflow simulated based on the three climate-change scenarios showed a slight decrease in overall streamflow relative to simulations under current conditions, mostly caused by decreases in the surface-runoff and groundwater components. The addition of information about forecasted urbanization of land surfaces to the hydrologic simulation mitigated the decreases in streamflow, mainly by increasing surface runoff.
Abstract
The U.S. Geological Survey Precipitation-Runoff Modeling System (PRMS) model was applied to basins in 14 different hydroclimatic regions to determine the sensitivity and variability of the freshwater resources of the United States in the face of current climate-change projections. Rather than attempting to choose a most likely scenario from the results of the Intergovernmental Panel on Climate Change, an ensemble of climate simulations from five models under three emissions scenarios each was used to drive the basin models.
Climate-change scenarios were generated for PRMS by modifying historical precipitation and temperature inputs; mean monthly climate change was derived by calculating changes in mean climates from current to various future decades in the ensemble of climate projections. Empirical orthogonal functions (EOFs) were fitted to the PRMS model output driven by the ensemble of climate projections and provided a basis for randomly (but representatively) generating realizations of hydrologic response to future climates. For each realization, the 1.5-yr flood was calculated to represent a flow important for sediment transport and channel geomorphology. The empirical probability density function (pdf) of the 1.5-yr flood was estimated using the results across the realizations for each basin. Of the 14 basins studied, 9 showed clear temporal shifts in the pdfs of the 1.5-yr flood projected into the twenty-first century. In the western United States, where the annual peak discharges are heavily influenced by snowmelt, three basins show at least a 10% increase in the 1.5-yr flood in the twenty-first century; the remaining two basins demonstrate increases in the 1.5-yr flood, but the temporal shifts in the pdfs and the percent changes are not as distinct. Four basins in the eastern Rockies/central United States show at least a 10% decrease in the 1.5-yr flood; the remaining two basins demonstrate decreases in the 1.5-yr flood, but the temporal shifts in the pdfs and the percent changes are not as distinct. Two basins in the eastern United States show at least a 10% decrease in the 1.5-yr flood; the remaining basin shows little or no change in the 1.5-yr flood.
Abstract
The U.S. Geological Survey Precipitation-Runoff Modeling System (PRMS) model was applied to basins in 14 different hydroclimatic regions to determine the sensitivity and variability of the freshwater resources of the United States in the face of current climate-change projections. Rather than attempting to choose a most likely scenario from the results of the Intergovernmental Panel on Climate Change, an ensemble of climate simulations from five models under three emissions scenarios each was used to drive the basin models.
Climate-change scenarios were generated for PRMS by modifying historical precipitation and temperature inputs; mean monthly climate change was derived by calculating changes in mean climates from current to various future decades in the ensemble of climate projections. Empirical orthogonal functions (EOFs) were fitted to the PRMS model output driven by the ensemble of climate projections and provided a basis for randomly (but representatively) generating realizations of hydrologic response to future climates. For each realization, the 1.5-yr flood was calculated to represent a flow important for sediment transport and channel geomorphology. The empirical probability density function (pdf) of the 1.5-yr flood was estimated using the results across the realizations for each basin. Of the 14 basins studied, 9 showed clear temporal shifts in the pdfs of the 1.5-yr flood projected into the twenty-first century. In the western United States, where the annual peak discharges are heavily influenced by snowmelt, three basins show at least a 10% increase in the 1.5-yr flood in the twenty-first century; the remaining two basins demonstrate increases in the 1.5-yr flood, but the temporal shifts in the pdfs and the percent changes are not as distinct. Four basins in the eastern Rockies/central United States show at least a 10% decrease in the 1.5-yr flood; the remaining two basins demonstrate decreases in the 1.5-yr flood, but the temporal shifts in the pdfs and the percent changes are not as distinct. Two basins in the eastern United States show at least a 10% decrease in the 1.5-yr flood; the remaining basin shows little or no change in the 1.5-yr flood.
Abstract
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.
Abstract
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.
