CLIMATE CHHANGE SENSITIVITY ASSESSMENT ON UPPER MISSISSIPPI RIVER BASIN STREAMFLOWS USING SWAT1

ABSTRACT: The Soil and Water Assessment Tool (SWAT) model was used to assess the effects of potential future climate change on the hydrology of the Upper Mississippi River Basin (UMRB). Calibration and validation of SWAT were performed using monthly stream flows for 1968–1987 and 1988–1997, respectively. The R² and Nash‐Sutcliffe simulation efficiency values computed for the monthly comparisons were 0.74 and 0.69 for the calibration period and 0.82 and 0.81 for the validation period. The effects of nine 30‐year (1968 to 1997) sensitivity runs and six climate change scenarios were then analyzed, relative to a scenario baseline. A doubling of atmospheric CO₂ to 660 ppmv (while holding other climate variables constant) resulted in a 36 percent increase in average annual streamflow while average annual flow changes of ?49, ?26, 28, and 58 percent were predicted for precipitation change scenarios of ?20, ?10, 10, and 20 percent, respectively. Mean annual streamflow changes of 51,10, 2, ?6, 38, and 27 percent were predicted by SWAT in response to climate change projections generated from the CISRO‐RegCM2, CCC, CCSR, CISRO‐Mk2, GFDL, and HadCMS general circulation model scenarios. High seasonal variability was also predicted within individual climate change scenarios and large variability was indicated between scenarios within specific months. Overall, the climate change scenarios reveal a large degree of uncertainty in current climate change forecasts for the region. The results also indicate that the simulated UMRB hydrology is very sensitive to current forecasted future climate changes.     

AN EVALUATION OF TWO HYDROLOGIC MODELS FOR CLIMATE CHANGE SCENARIOS1

ABSTRACT: Understanding the effects of climate change on water resources requires coupling atmospheric and hydrologic models. With the wide array of hydrologic models, from simple empirical to complex physically based, it is not clear which is preferable to simulate hydrologic variations over long time scales. To address this issue, a black-box artificial neural network (ANN) model was compared to a distributed parameter conceptual Geographic Information System based Hydrologic Modeling System (GIS-HMS). Both models computed daily direct surface runoff in four sub-basins of the West Branch of the Susquehanna River Basin, Pennsylvania and were evaluated with five objective functions. Overall, results were comparable between models. However, the ANN was favored in the larger sub-basins, while GIS-HMS was more accurate in the smaller catchments. Both models were impaired by the poor spatial and temporal resolution of precipitation data and the simplified representation of antecedent soil-moisture conditions. In the context of climate change, where simulations are limited by computing power, results suggest that both models are appropriate. When detailed simulations are essential, GIS-HMS is a preferable model to use. On the other hand, the ANN model is more suitable when multiple scenarios require immediate analysis and the distributed qualities of runoff are not required.     

ASSESSMENT OF IMPACTS OF CLIMATE CHANGE ON WATER QUALITY IN THE SOUTHEASTERN UNITED STATES1

ABSTRACT: An assessment of current and future water quality conditions in the southeastern United States has been conducted using the EPA BASINS GIS/database system. The analysis has been conducted for dissolved oxygen, total nitrate nitrogen and pH. Future streamflow conditions have been predicted for the region based on the United Kingdom Hadley Center climate model. Thus far, the analyses have been conducted at a fairly coarse spatial scale due to time and resource limitations. Two hydrologic modeling techniques have been employed in future streamflow prediction: a regional stochastic approach and the application of a physically based soil moisture model. The regional model has been applied to the entire area while the physically based model is being used at selected locations to enhance and support the stochastic model. The results of the study reveal that few basins in the southeast exhibit dissolved oxygen problems, but that several watersheds exhibit high nitrogen levels. These basins are located in regions of intense agricultural activity or in proximity to the gulf coast. In many of these areas, streamflow is projected to decline over the next 30–50 years, thus exacerbating these water quality problems.     

COMPARISON OF PROCESS‐BASED AND ARTIFICIAL NEURAL NETWORK APPROACHES FOR STREAMFLOW MODELING IN AN AGRICULTURAL WATERSHED1

ABSTRACT: The performance of the Soil and Water Assessment Tool (SWAT) and artificial neural network (ANN) models in simulating hydrologic response was assessed in an agricultural watershed in southeastern Pennsylvania. All of the performance evaluation measures including Nash‐Sutcliffe coefficient of efficiency (E) and coefficient of determination (R²) suggest that the ANN monthly predictions were closer to the observed flows than the monthly predictions from the SWAT model. More specifically, monthly streamflow E and R² were 0.54 and 0.57, respectively, for the SWAT model calibration period, and 0.71 and 0.75, respectively, for the ANN model training period. For the validation period, these values were ?0.17 and 0.34 for the SWAT and 0.43 and 0.45 for the ANN model. SWAT model performance was affected by snowmelt events during winter months and by the model's inability to adequately simulate base flows. Even though this and other studies using ANN models suggest that these models provide a viable alternative approach for hydrologic and water quality modeling, ANN models in their current form are not spatially distributed watershed modeling systems. However, considering the promising performance of the simple ANN model, this study suggests that the ANN approach warrants further development to explicitly address the spatial distribution of hydrologic/water quality processes within watersheds.     

CLIMATE CHANGE AND EXTRATROPICAL STORMINESS IN THE UNITED STATES: AN ASSESSMENT1

ABSTRACT: Climate change due to enrichment of the atmosphere with carbon dioxide is projected to change the circulation of the atmosphere, increase its moisture content, warm the surface layers, and increase precipitation. Extratropical storms are the intermediate agent in mid-latitudes between changes in the circulation of the atmosphere and surface water resources. The climatology of extratropical storms for the period 1885–1996 is presented, and major changes in storminess are detected across much of North America. General Circulation Model (GCM) projections of storm frequency and storm track are found to have little in common with the observed pattern of storms and evidence no systematic changes in response to an enrichment of the atmosphere with carbon dioxide.     

APPLICATIONS OF A GIS FOR MODELING THE SENSITIVITY OF WATER RESOURCES TO ALTERATIONS IN CLIMATE IN THE GUNNISON RIVER BASIN,COLORADO1

ABSTRACT: 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.     

MODELED REGIONAL CLIMATE CHANGE IN THE HYDROLOGIC REGIONS OF CALIFORNIA: A CO2 SENSITIVITY STUDY1

ABSTRACT: Using a regional climate model (RegCM2.5), the potential impacts on the climate of California of increasing atmospheric CO₂ concentrations were explored from the perspective of the state's 10 hydrologic regions. Relative to preindustrial CO₂ conditions (280 ppm), doubled preindustrial CO₂ conditions (560 ppm) produced increased temperatures of up to 4°C on an annual average basis and of up to 5°C on a monthly basis. Temperature increases were greatest in the central and northern regions. On a monthly basis, the temperature response was greatest in February, March, and May for nearly all regions. Snow accumulation was significantly decreased in all months and regions, with the greatest reduction occurring in the Sacramento River region. Precipitation results indicate drier winters for all regions, with a large reduction in precipitation from December to April and a smaller decrease from May to November. The result is a wet season that is slightly reduced in length. Findings suggest that the total amount of water in the state will decrease, water needs will increase, and the timing of water availability will be greatly perturbed.     

A REVISED VERSION OF PnET‐II TO SIMULATE THE HYDROLOGIC CYCLE IN SOUTHEASTERN FORESTED AREAS1

ABSTRACT: The PnET‐II model uses hydroclimatic data on maximum and minimum temperatures, precipitation, and solar radiation, together with vegetation and soil parameters, to produce estimates of net primary productivity, evapotranspiration (ET), and runoff on a monthly time step for forested areas. In this study, the PnET‐II model was employed to simulate the hydrologic cycle for 17 Southeastern eight‐digit hydrologic unit code (HUC) watersheds dominated by evergreen or deciduous tree species. Based on these control experiments, model biases were quantified and tentative revision schemes were introduced. Revisions included: (1) replacing the original single soil layer with three soil layers in the water balance routine; (2) introducing calibrating factors to rectify the phenomenon of overestimation of ET in spring and early summer months; (3) parameterizing proper values of growing degree days for trees located in different climate zones; and (4) adjusting the parameter of fast‐flow (overland flow) fraction based on antecedent moisture condition and precipitation intensity. The revised PnET‐II model, called PnET‐II3SL in this work, substantially improved runoff simulations for the 17 selected experimental sites, and therefore may offer a more powerful tool to address issues in water resources management.     

A COMPARISON OF SIX POTENTIAL EVAPOTRANSPIRATION METHODS FOR REGIONAL USE IN THE SOUTHEASTERN UNITED STATES1

ABSTRACT: Potential evapotranspiration (PET) is an important index of hydrologic budgets at different spatial scales and is a critical variable for understanding regional biological processes. It is often an important variable in estimating actual evapotranspiration (AET) in rainfall‐runoff and ecosystem modeling. However, PET is defined in different ways in the literature and quantitative estimation of PET with existing mathematical formulas produces inconsistent results. The objectives of this study are to contrast six commonly used PET methods and quantify the long term annual PET across a physiographic gradient of 36 forested watersheds in the southeastern United States. Three temperature based (Thornthwaite, Hamon, and Hargreaves‐Samani) and three radiation based (Turc, Makkink, and Priestley‐Taylor) PET methods are compared. Long term water balances (precipitation, streamflow, and AET) for 36 forest dominated watersheds from 0.25 to 8213 km² in size were estimated using associated hydrometeorological and land use databases. The study found that PET values calculated from the six methods were highly correlated (Pearson Correlation Coefficient 0.85 to 1.00). Multivariate statistical tests, however, showed that PET values from different methods were significantly different from each other. Greater differences were found among the temperature based PET methods than radiation based PET methods. In general, the Priestley‐Taylor, Turc, and Hamon methods performed better than the other PET methods. Based on the criteria of availability of input data and correlations with AET values, the Priestley‐Taylor, Turc, and Hamon methods are recommended for regional applications in the southeastern United States.     

PACIFIC NORTHWEST REGIONAL ASSESSMENT: THE IMPACTS OF CLIMATE VARIABILITY AND CLIMATE CHANGE ON THE WATER RESOURCES OF THE COLUMBIA RIVER BASIN1

ABSTRACT: The Pacific Northwest (PNW) regional assessment is an integrated examination of the consequences of natural climate variability and projected future climate change for the natural and human systems of the region. The assessment currently focuses on four sectors: hydrology/water resources, forests and forestry, aquatic ecosystems, and coastal activities. The assessment begins by identifying and elucidating the natural patterns of climate vanability in the PNW on interannual to decadal timescales. The pathways through which these climate variations are manifested and the resultant impacts on the natural and human systems of the region are investigated. Knowledge of these pathways allows an analysis of the potential impacts of future climate change, as defined by IPCC climate change scenarios. In this paper, we examine the sensitivity, adaptability and vulnerability of hydrology and water resources to climate variability and change. We focus on the Columbia River Basin, which covers approximately 75 percent of the PNW and is the basis for the dominant water resources system of the PNW. The water resources system of the Columbia River is sensitive to climate variability, especially with respect to drought. Management inertia and the lack of a centralized authority coordinating all uses of the resource impede adaptability to drought and optimization of water distribution. Climate change projections suggest exacerbated conditions of conflict between users as a result of low summertime streamfiow conditions. An understanding of the patterns and consequences of regional climate variability is crucial to developing an adequate response to future changes in climate.     

A CALIBRATION PROCEDURE USING TOPMODEL TO DETERMINE SUITABILITY FOR EVALUATING POTENTIAL CLIMATE CHANGE EFFECTS ON WATER YIELD1

ABSTRACT: An evaluation was conducted on three forested upland watersheds in the northeastern U.S. to test the suitability of TOPMODEL for predicting water yield over a wide range of climatic scenarios. The analysis provides insight of the usefulness of TOPMODEL as a predictive tool for future assessments of potential long-term changes in water yield as a result of changes in global climate. The evaluation was conducted by developing a calibration procedure to simulate a range of climatic extremes using historical temperature, precipitation, and streamfiow records for years having wet, average, and dry precipitation amounts from the Leading Ridge (Pennsylvania), Fernow (West Virginia), and Hubbard Brook (New Hampshire) Experimental Watersheds. This strategy was chosen to determine whether the model could be successfully calibrated over a broad range of soil moisture conditions with the assumption that this would be representative of the sensitivity necessary to predict changes in streamfiow under a variety of climate change scenarios. The model calibration was limited to a daily time step, yet performed reasonably well for each watershed. Model efficiency, a least squares measure of how well a model performs, averaged between 0.64 and 0.78. A simple test of the model whereby daily temperatures were increased by 1.7°C, resulted in annual water yield decreases of 4 to 15 percent on the three watersheds. Although these results makes the assumption that the model components adequately describe the system, this version of TOPMODEL is capable to predict water yield impacts given subtle changes in the temperature regime. This suggests that adequate representations of the effects of climate change on water yield for regional assessment purposes can be expected using the TOPMODEL concept.     

POTENTIAL CLIMATE CHANGE IMPACTS ON MOUNTAIN WATERSHEDS IN THE PACIFIC NORTHWEST1

ABSTRACT: Global climate change due to the buildup of greenhouse gases in the atmosphere has serious potential impacts on water resources in the Pacific Northwest. Climate scenarios produced by general circulation models (GCMs) do not provide enough spatial specificity for studying water resources in mountain watersheds. This study uses dynamical downscaling with a regional climate model (RCM) driven by a GCM to simulate climate change scenarios. The RCM uses a subgrid parameterization of orographic precipitation and land surface cover to simulate surface climate at the spatial scale suitable for the representation of topographic effects over mountainous regions. Numerical experiments have been performed to simulate the present-day climatology and the climate conditions corresponding to a doubling of atmospheric CO₂ concentration. The RCM results indicate an average warming of about 2.5°C, and precipitation generally increases over the Pacific Northwest and decreases over California. These simulations were used to drive a distributed hydrology model of two snow dominated watersheds, the American River and Middle Fork Flathead, in the Pacific Northwest to obtain more detailed estimates of the sensitivity of water resources to climate change. Results show that as more precipitation falls as rain rather than snow in the warmer climate, there is a 60 percent reduction in snowpack and a significant shift in the seasonal pattern of streamflow in the American River. Much less drastic changes are found in the Middle Fork Flathead where snowpack is only reduced by 18 percent and the seasonal pattern of streamflow remains intact. This study shows that the impacts of climate change on water resources are highly region specific. Furthermore, under the specific climate change scenario, the impacts are largely driven by the warming trend rather than the precipitation trend, which is small.     

INTEGRATION OF A BASIN-SCALE WATER QUALITY MODEL WITH GIS1

ABSTRACT: Geographic Information Systems (GIS) have been successfully integrated with distributed parameter, single-event, water quality models such as AGNPS (AGricultural NonPoint Source) and ANSWERS (Areal Nonpoint Source Watershed Environmental Response Simulation). These linkages proved to be an effective way to collect, manipulate, visualize, and analyze the input and output date of water quality models. However, for continuous-time, basin large-scale water quality models, collecting and manipulating the input data are more time-consuming and cumbersome due to the method of disaggregation (subdivisions are based on topographic boundaries). SWAT (Soil and Water Assessment Tool), a basin-scale water quality model, was integrated with a GIS to extract input data for modeling a basin. This paper discusses the detailed development of the integration of the SWAT water quality model with GRASS (Geographic Resources Analysis Support System) GIS, along with an application and advantages. The integrated system was applied to simulated a 114 sq. km upper portion of the Seco Creek Basin by subdividing it into 37 subbasins. The average monthly predicted streamflw is in agreement with measured monthly streamflw values.     

A COMPARISON OF DELTA CHANGE AND DOWNSCALED GCM SCENARIOS FOR THREE MOUNTAINOUS BASINS IN THE UNITED STATES1

ABSTRACT: 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.     

REGIONAL SCALE MODELING OF SURFACE AND GROUND WATER INTERACTION IN THE SNAKE RIVER BASIN1

ABSTRACT: Changes in irrigation and land use may impact discharge of the Snake River Plain aquifer, which is a major contributor to flow of the Snake River in southern Idaho. The Snake River Basin planning and management model (SRBM) has been expanded to include the spatial distribution and temporal attenuation that occurs as aquifer stresses propagate through the aquifer to the river. The SRBM is a network flow model in which aquifer characteristics have been introduced through a matrix of response functions. The response functions were determined by independently simulating the effect of a unit stress in each cell of a finite difference groundwater flow model on six reaches of the Snake River. Cells were aggregated into 20 aquifer zones and average response functions for each river reach were included in the SRBM. This approach links many of the capabilities of surface and ground water flow models. Evaluation of an artificial recharge scenario approximately reproduced estimates made by direct simulation in a ground water flow model. The example demonstrated that the method can produce reasonable results but interpretation of the results can be biased if the simulation period is not of adequate duration.     

EFFECTS OF CLIMATE CHANGE ON HYDROLOGY AND WATER RESOURCES IN THE COLUMBIA RIVER BASIN1

ABSTRACT: As part of the National Assessment of Climate Change, the implications of future climate predictions derived from four global climate models (GCMs) were used to evaluate possible future changes to Pacific Northwest climate, the surface water response of the Columbia River basin, and the ability of the Columbia River reservoir system to meet regional water resources objectives. Two representative GCM simulations from the Hadley Centre (HC) and Max Planck Institute (MPI) were selected from a group of GCM simulations made available via the National Assessment for climate change. From these simulations, quasi-stationary, decadal mean temperature and precipitation changes were used to perturb historical records of precipitation and temperature data to create inferred conditions for 2025, 2045, and 2095. These perturbed records, which represent future climate in the experiments, were used to drive a macro-scale hydrology model of the Columbia River at 1/8 degree resolution. The altered streamflows simulated for each scenario were, in turn, used to drive a reservoir model, from which the ability of the system to meet water resources objectives was determined relative to a simulated hydrologic base case (current climate). Although the two GCM simulations showed somewhat different seasonal patterns for temperature change, in general the simulations show reasonably consistent basin average increases in temperature of about 1.8–2.1°C for 2025, and about 2.3–2.9°C for 2045. The HC simulations predict an annual average temperature increase of about 4.5°C for 2095. Changes in basin averaged winter precipitation range from -1 percent to + 20 percent for the HC and MPI scenarios, and summer precipitation is also variously affected. These changes in climate result in significant increases in winter runoff volumes due to increased winter precipitation and warmer winter temperatures, with resulting reductions in snowpack. Average March 1 basin average snow water equivalents are 75 to 85 percent of the base case for 2025, and 55 to 65 percent of the base case by 2045. By 2045 the reduced snowpack and earlier snow melt, coupled with higher evapotranspiration in early summer, would lead to earlier spring peak flows and reduced runoff volumes from April-September ranging from about 75 percent to 90 percent of the base case. Annual runoff volumes range from 85 percent to 110 percent of the base case in the simulations for 2045. These changes in streamflow create increased competition for water during the spring, summer, and early fall between non-firm energy production, irrigation, instream flow, and recreation. Flood control effectiveness is moderately reduced for most of the scenarios examined, and desirable navigation conditions on the Snake are generally enhanced or unchanged. Current levels of winter-dominated firm energy production are only significantly impacted for the MPI 2045 simulations.