Estimating Potential Climate Change Effects on the Upper Neuse Watershed Water Balance Using the SWAT Model

Climate change poses water resource challenges for many already water stressed watersheds throughout the world. One such watershed is the Upper Neuse Watershed in North Carolina, which serves as a water source for the large and growing Research Triangle Park region. The aim of this study was to quantify possible changes in the watershed’s water balance due to climate change. To do this, we used the Soil and Water Assessment Tool (SWAT) model forced with different climate scenarios for baseline, mid‐century, and end‐century time periods using five different downscaled General Circulation Models. Before running these scenarios, the SWAT model was calibrated and validated using daily streamflow records within the watershed. The study results suggest that, even under a mitigation scenario, precipitation will increase by 7.7% from the baseline to mid‐century time period and by 9.8% between the baseline and end‐century time period. Over the same periods, evapotranspiration (ET) would decrease by 5.5 and 7.6%, water yield would increase by 25.1% and 33.2%, and soil water would increase by 1.4% and 1.9%. Perhaps most importantly, the model results show, under a high emission scenario, large seasonal differences with ET estimated to decrease by up to 42% and water yield to increase by up to 157% in late summer and fall. Planning for the wetter predicted future and corresponding seasonal changes will be critical for mitigating the impacts of climate change on water resources.     

MODELING ACTUAL EVAPOTRANSPIRATION FROM FORESTED WATERSHEDS ACROSS THE SOUTHEASTERN UNITED STATES1

ABSTRACT: About 50 to 80 percent of precipitation in the southeastern United States returns to the atmosphere by evapotranspiration. As evapotranspiration is a major component in the forest water balances, accurately quantifying it is critical to predicting the effects of forest management and global change on water, sediment, and nutrient yield from forested watersheds. However, direct measurement of forest evapotranspiration on a large basin or a regional scale is not possible. The objectives of this study were to develop an empirical model to estimate long‐term annual actual evapotranspiration (ART) for forested watersheds and to quantify spatial AET patterns across the southeast. A geographic information system (GIS) database including land cover, daily streamflow, and climate was developed using long term experimental and monitoring data from 39 forested watersheds across the region. Using the stepwise selection method implemented in a statistical modeling package, a long term annual AET model was constructed. The final multivariate linear model includes four independent variables—annual precipitation, watershed latitude, watershed elevation, and percentage of forest coverage. The model has an adjusted R² of 0.794 and is sufficient to predict long term annual ART for forested watersheds across the southeastern United States. The model developed by this study may be used to examine the spatial variability of water availability, estimate annual water loss from mesoscale watersheds, and project potential water yield change due to forest cover change.     

HYDROLOGIC SIMULATION OF THE LITTLE WASHITA RIVER EXPERIMENTAL WATERSHED USING SWAT1

ABSTRACT: Precipitation and streamflow data from three nested subwatersheds within the Little Washita River Experimental Watershed (LWREW) in southwestern Oklahoma were used to evaluate the capabilities of the Soil and Water Assessment Tool (SWAT) to predict streamflow under varying climatic conditions. Eight years of precipitation and streamflow data were used to calibrate parameters in the model, and 15 years of data were used for model validation. SWAT was calibrated on the smallest and largest sub‐watersheds for a wetter than average period of record. The model was then validated on a third subwatershed for a range in climatic conditions that included dry, average, and wet periods. Calibration of the model involved a multistep approach. A preliminary calibration was conducted to estimate model parameters so that measured versus simulated yearly and monthly runoff were in agreement for the respective calibration periods. Model parameters were then fine tuned based on a visual inspection of daily hydrographs and flow frequency curves. Calibration on a daily basis resulted in higher baseflows and lower peak runoff rates than were obtained in the preliminary calibration. Test results show that once the model was calibrated for wet climatic conditions, it did a good job in predicting streamflow responses over wet, average, and dry climatic conditions selected for model validation. Monthly coefficients of efficiencies were 0.65, 0.86, and 0.45 for the dry, average, and wet validation periods, respectively. Results of this investigation indicate that once calibrated, SWAT is capable of providing adequate simulations for hydrologic investigations related to the impact of climate variations on water resources of the LWREW.     

The Impact of Projected Climate Change Scenarios on Nitrogen Yield at a Regional Scale for the Contiguous United States

Improved understanding of the potential regional impacts of projected climatic changes on nitrogen yield is needed to inform water resources management throughout the United States (U.S.). The objective of this research is to look broadly at watersheds in the contiguous U.S. to assess the potential regional impact of changes in precipitation (P) and air temperature (T) on nitrogen yield. The SPAtially Referenced Regression On Watershed attributes model and downscaled P and T outputs from 14 general circulation models were used to explore impacts on nitrogen yield. Results of the analysis suggest that projected changes in P and T will decrease nitrogen yield for the majority of the contiguous U.S., including the watersheds of the Chesapeake Bay and Gulf of Mexico. Some regions, however, such as the Pacific Northwest and Northern California, are projected to face climatic conditions that, according to the model results, may increase nitrogen yield. Combining the projections of climate‐driven changes in nitrogen yield with projected changes in watershed nitrogen inputs could help water resource managers develop regionally specific, long‐term strategies to mitigate nitrogen pollution.     

Sensitivity of Stream flow and Water Table Depth to Potential Climatic Variability in a Coastal Forested Watershed1

Dai, Zhaohua, Carl C. Trettin, Changsheng Li, Devendra M. Amatya, Ge Sun, and Harbin Li, 2010. Sensitivity of Streamflow and Water Table Depth to Potential Climatic Variability in a Coastal Forested Watershed. Journal of the American Water Resources Association (JAWRA) 1–13. DOI: 10.1111/j.1752-1688.2010.00474.x Abstract: A physically based distributed hydrological model, MIKE SHE, was used to evaluate the effects of altered temperature and precipitation regimes on the streamflow and water table in a forested watershed on the southeastern Atlantic coastal plain. The model calibration and validation against both streamflow and water table depth showed that the MIKE SHE was applicable for predicting the streamflow and water table dynamics for this watershed with an acceptable model efficiency (E > 0.5 for daily streamflow and >0.75 for monthly streamflow). The simulation results from changing temperature and precipitation scenarios indicate that climate change influences both streamflow and water table in the forested watershed. Compared to current climate conditions, the annual average streamflow increased or decreased by 2.4% with one percentage increase or decrease in precipitation; a quadratic polynomial relationship between changes in water table depth (cm) and precipitation (%) was found. The annual average water table depth and annual average streamflow linearly decreased with an increase in temperature within the range of temperature change scenarios (0-6°C). The simulation results from the potential climate change scenarios indicate that future climate change will substantially impact the hydrological regime of upland and wetland forests on the coastal plain with corresponding implications to altered ecosystem functions that are dependent on water.     

THE EFFECTS OF CLIMATE CHANGE ON STREAM FLOW AND NUTRIENT LOADING'

ABSTRACT: This study assesses the potential impact of climate change on stream flow and nutrient loading in six watersheds of the Susquehanna River Basin using the Generalized Watershed Loading Function (GWLF). The model was used to simulate changes in stream flow and nutrient loads under a transient climate change scenario for each watershed. Under an assumption of no change in land cover and land management, the model was used to predict monthly changes in stream flow and nutrient loads for future climate conditions. Mean annual stream flow and nutrient loads increased for most watersheds, but decreased in one watershed that was intensively cultivated. Nutrient loading slightly decreased in April and late summer for several watersheds as a result of early snowmelt and increasing evapotranspiration. Spatial and temporal variability of stream flow and nutrient loads under the transient climate scenario indicates that different approaches for future water resource management may be useful.     

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.     

Water Stress Projections for the Northeastern and Midwestern United States in 2060: Anthropogenic and Ecological Consequences

Future climate and land‐use changes and growing human populations may reduce the abundance of water resources relative to anthropogenic and ecological needs in the Northeast and Midwest (U.S.). We used output from WaSSI, a water accounting model, to assess potential changes between 2010 and 2060 in (1) anthropogenic water stress for watersheds throughout the Northeast and Midwest and (2) native fish species richness (i.e., number of species) for the Upper Mississippi water resource region (UMWRR). Six alternative scenarios of climate change, land‐use change, and human population growth indicated future water supplies will, on average across the region, be adequate to meet anthropogenic demands. Nevertheless, the number of individual watersheds experiencing severe stress (demand > supplies) was projected to increase for most scenarios, and some watersheds were projected to experience severe stress under multiple scenarios. Similarly, we projected declines in fish species richness for UMWRR watersheds and found the number of watersheds with projected declines and the average magnitude of declines varied across scenarios. All watersheds in the UMWRR were projected to experience declines in richness for at least two future scenarios. Many watersheds projected to experience declines in fish species richness were not projected to experience severe anthropogenic water stress, emphasizing the need for multidimensional impact assessments of changing water resources.     

SENSITWITY OF IRRIGATION DEMAND IN A HUMID-TEMPERATE REGION TO HYPOTHETICAL CLIMATIC CHANGE1

ABSTRACT: An irrigation model based on a modified Thornthwaite water balance was used to simulate the effects of various hypothetical climatic changes on annual irrigation demand in a humidtemperate climate. The climatic-change scenarios consisted of combinations of changes in temperature, precipitation, and stomatal resistance of plants to transpiration. The objectives were to (1) examine the effects of long-term changes in these components of climatic change on annual irrigation demand, and (2) identify which of these factors would cause the largest changes in annual irrigation demand. Hypothetical climatic changes that only included increases in temperature and changes in precipitation resulted in increased annual irrigation demand, even with a 20 percent increase in precipitation. The model results showed that, for the ranges of changes in temperature and precipitation used in this study, changes in irrigation demand were more sensitive to changes in temperature than to changes in precipitation. Model results also indicated that increased stomatal resistance to transpiration counteracted the effects of increases in temperature and decreases in precipitation on irrigation demand. Changes in irrigation demand were even more sensitive to changes in stomatal resistance than to changes in temperature. A large amount of uncertainty is associated with predictions of future climatic conditions; however, uncertainty associated with natural climatic variability may be larger and may mask the effects of climatic change on irrigation demand.     

APPLICATION OF AN INTEGRATED BASIN-SCALE HYDROLOGIC MODEL TO SIMULATE SURFACE-WATER AND GROUND-WATER INTERACTIONS1

ABSTRACT: Hydrologic models have become an indispensable tool for studying processes and water management in watersheds. A physically-based, distributed-parameter model, Basin-Scale Hydro-logic Model (BSIIM), has been developed to simulate the hydrologic response of large drainage basins. The model formulation is based on equations describing water movement both on the surface and in the subsurface. The model incorporates detailed information on climate, digital elevation, and soil moisture budget, as well as surface-water and ground-water systems. This model has been applied to the Big Darby Creek Watershed, Ohio in a 28-year simulation of rainfall-runoff processes. Unknown coefficients for controlling runoff, storativity, hydraulic conductivity, and streambed permeability are determined by a trial-and-error calibration. The performance of model calibration and predictive capability of the model was evaluated based on the correlation between simulated and observed daily stream discharges. Discrepancies between observed and simulated results exist because of limited precipitation data and simplifying assumptions related to soil, land use, and geology.     

CLIMATIC VARIATION AND SURFACE WATER RESOURCES IN THE GREAT BASIN REGION1

ABSTRACT: There is mounting evidence that increasing amounts of atmospheric carbon dioxide may lead to significant changes in global climate during the next century. The possible effects of such climatic changes on surface runoff in the Great Basin Region of the western United States has been investigated by applying water balance models to four watersheds in Nevada and Utah. The most probable change, a 2°C increase in average annual temperature coupled with a 10 percent decrease in precipitation, would reduce runoff from 17 to 28 percent of the present mean, with drier basins showing the greatest change. Decreasing precipitation by 25 percent causes runoff reductions of 33 to 51 percent. Equivalent changes to a cooler and wetter climate show corresponding increases in runoff of approximately the same magnitude, but such a shift is not considered likely. Based on projected water requirements for the year 2000, a change to a warmer and drier climate would cause severe water shortages in many parts of the Great Basin.     

Addressing data challenges in riverine nutrient load modeling of an intensively managed agro-industrial watershed

Data limitations often challenge the reliability of water quality models, especially in intensively managed watersheds. While numerous studies report successful hydrological model setup and calibration, few have addressed in detail the data challenges for multisite and multivariable model calibration to an intensively managed watershed. In this study, we address some of these challenges based on our reflective experience calibrating the Soil and Water Assessment Tool (SWAT) to the Upper Sangamon River Watershed in central Illinois based on daily flow, annual crop yield, and monthly sediment, nitrate, and total phosphorus loads. We highlight some challenges in SWAT calibration processes due to data errors and inconsistencies, and insufficient precipitation and water quality observations. Following, we demonstrate the merits of additional weather and water quality observations that could help reduce input uncertainties, and we provide suggestions for selecting appropriate observations for the model calibration. After dealing with the data issues, we show that the SWAT model could be calibrated with acceptable results for the case study watershed.     

Hydrologic Calibration and Validation of SWAT in a Snow‐Dominated Rocky Mountain Watershed,Montana, U.S.A.1

Abstract: The Soil and Water Assessment Tool (SWAT) has been applied successfully in temperate environments but little is known about its performance in the snow‐dominated, forested, mountainous watersheds that provide much of the water supply in western North America. To address this knowledge gap, we configured SWAT to simulate the streamflow of Tenderfoot Creek (TCSWAT). Located in central Montana, TCSWAT represents a high‐elevation watershed with ～85% coniferous forest cover where more than 70% of the annual precipitation falls as snow, and runoff comes primarily from spring snowmelt. Model calibration using four years of measured daily streamflow, temperature, and precipitation data resulted in a relative error (RE) of 2% for annual water yield estimates, and mean paired deviations (Dv) of 36 and 31% and Nash‐Sutcliffe (NS) efficiencies of 0.90 and 0.86 for monthly and daily streamflow, respectively. Model validation was conducted using an additional four years of data and the performance was similar to the calibration period, with RE of 4% for annual water yields, Dv of 43% and 32%, and NS efficiencies of 0.90 and 0.76 for monthly and daily streamflow, respectively. An objective, regression‐based model invalidation procedure also indicated that the model was validated for the overall simulation period. Seasonally, SWAT performed well during the spring and early summer snowmelt runoff period, but was a poor predictor of late summer and winter base flow. The calibrated model was most sensitive to snowmelt parameters, followed in decreasing order of influence by the surface runoff lag, ground water, soil, and SCS Curve Number parameter sets. Model sensitivity to the surface runoff lag parameter reflected the influence of frozen soils on runoff processes. Results indicated that SWAT can provide reasonable predictions of annual, monthly, and daily streamflow from forested montane watersheds, but further model refinements could improve representation of snowmelt runoff processes and performance during the base flow period in this environment.     

STREAMFLOW CHARACTERISTICS OF SMALL WATERSHEDS IN THE BLUE MOUNTAINS OF OREGON1

ABSTRACT: Streamflow data for water years 1978–84 were evaluated to identify streamflow characteristics for 13 small watersheds (0.46–7.00 mi²) in the Blue Mountains of eastern Oregon and to determine differences among grazing intensities and vegetation types. The ranges for mean annual water yields, peak flows, and 7-day low flows for the 13 watersheds were 5.5–28.1 inches, 2.0–34.7 cfsm, and 0.006–0.165 cfsm, respectively. Two classes of vegetation were evaluated: (1) western larch-Douglas-fir (nine watersheds) and (2) other (four watersheds representing fir-spruce, lodgepole pine, ponderosa pine, and mountain meadow). The means for annual peak flows and the slopes of the flow.duration curve were significantly different (p=0.05) for the two vegetation classes; differences in mean annual water yield were marginallysignificant(0.05< p <0.10). After they were adjusted for precipitation, the means for annual water yield, peak flows, and slopes of the flow-duration curve were significantly different for the two vegetation classes; differences in the means for annual 7-day low flows were marginally significant. The western larch-Douglas-fir group had somewhat lower water yields but, overall, tended to have more favorable streamfiow characteristics including lower peak flows, higher low flows, and more evenly distributed flow regimes (flatter flow-duration curves) than the “other” class. Four levels of grazing intensity had no effect on streamilow characteristics.     

CLIMATIC CHANGE AND U.S. WATER RESOURCES: FROM MODELED WATERSHED IMPACTS TO NATIONAL ESTIMATES1

ABSTRACT: Water is potentially one of the most affected resources as climate changes. Though knowledge and understanding has steadily evolved about the nature and extent of many of the physical effects of possible climate change on water resources, much less is known about the economic responses and impacts that may emerge. Methods and results are presented that examine and quantify many of the important economic consequences of possible climate change on U.S. water resources. At the core of the assessment is the simulation of multiple climate change scenarios in economic models of four watersheds. These Water Allocation and Impact Models (Water‐AIM) simulate the effects of modeled runoff changes under various climate change scenarios on the spatial and temporal dimensions of water use, supply, and storage and on the magnitude and distribution of economic consequences. One of the key aspects and contributions of this approach is the capability of capturing economic response and adaptation behavior of water users to changes in water scarcity. By reflecting changes in the relative scarcity (and value) of water, users respond by changing their patterns of water use, intertemporal storage in reservoirs, and changes in the pricing of water. The estimates of economic welfare change that emerge from the Water‐AIM models are considered lower‐bound estimates owing to the conservative nature of the model formulation and key assumptions. The results from the Water‐AIM models form the basis for extrapolating impacts to the national level. Differences in the impacts across the regional models are carried through to the national assessment by matching the modeled basins with basins with similar geographical, climatic, and water use characteristics that have not been modeled and by using hydro‐logic data across all U.S. water resources regions. The results from the national analysis show that impacts are borne to a great extent by nonconsumptive users that depend on river flows, which rise and fall with precipitation, and by agricultural users, primarily in the western United States, that use a large share of available water in relatively low‐valued uses. Water used for municipal and industrial purposes is largely spared from reduced availability because of its relatively high marginal value. In some cases water quality concerns rise, and additional investments may be required to continue to meet established guidelines.     

THE POTENTIAL EFFECTS OF GLOBAL WARMING ON THE PRIMARY PRODUCTIVITY OF A SUBALPINE LAKE1

ABSTRACT Atmospheric scientists have predicted that large-scale climatic changes will result from increasing levels of tropospheric CO₂ We have investigated the potential effects of climate change on the primary productivity of Castle Lake, a mountain lake in Northern California. Annual algal productivity was modeled empirically using 25 years of limnological data in order to establish predictive relationships between productivity and the climatic variables of accumulated snow depth and precipitation. The outputs of monthly temperature and precipitation from three general circulation models (GCMs) of doubled atmospheric CO₂ were then used in the regression model to predict annual algal productivity. In all cases, the GCM scenarios predicted increased algal productivity for Castle Lake under cenditions of doubled atmospheric CO₂The primary cause of enhanced productivity was the increased length of the growing season resulting from earlier spring ice-out.     

Drivers of future streamflow changes in watersheds across the Northeastern United States

Accurate projections of streamflow, which have implications for flooding, water resources, hydropower, and ecosystems, are critical to climate change adaptation and require an understanding of streamflow sensitivity to climate drivers. The northeastern United States has experienced a dramatic increase in extreme precipitation over the past 25 years; however, the effects of these changes, as well as changes in other drivers of streamflow, remain unclear. Here, we use a random forest model forced with a regional climate model to examine historical and future streamflow dynamics of four watersheds across the Northeast. We find that streamflow in the cold season (November–May) is primarily driven by 3-day rainfall and antecedent wetness (Antecedent Precipitation Index) in three rainfall-dominant watersheds, and 30-day rainfall, antecedent wetness, and 30-day snowmelt in the fourth, more snowmelt-dominated watershed. In the warm season (June–October), streamflow is driven by antecedent wetness and rainfall in all watersheds. By the end of the century (2070–2099), cold season streamflow depends on the importance placed on snow in the machine learning model, with changes ranging from −7% (with snow) to +40% (without snow) in a single watershed. Simulated future warm season streamflow increases in two watersheds (56% and 193%) due to increased precipitation and antecedent soil wetness, but decreases in the other two watersheds (−6% and −27%) due to reduced precipitation.     

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.     

SENSITIVITY OF A PRAIRIE WETLAND TO INCREASED TEMPERATURE AND SEASONAL PRECIPITATION CHANGES1

ABSTRACT: We assessed the potential effects of increased temperature and changes in amount and seasonal timing of precipitation on the hydrology and vegetation of a semi-permanent prairie wetland in North Dakota using a spatially-defined, rule-based simulation model. Simulations were run with increased temperatures of 2°C combined with a 10 percent increase or decrease in total growing season precipitation. Changes in precipitation were applied either evenly across all months or to individual seasons (spring, summer, or fall). The response of semi-permanent wetland P1 was relatively similar under most of the seasonal scenarios. A 10 percent increase in total growing season precipitation applied to summer months only, to fall months only, and over all months produced lower water levels compared to those resulting from the current climate due to increased evapotranspiration. Wetland hydrology was most affected by changes in spring precipitation and runoff. Vegetation response was relatively consistent across scenarios. Seven of the eight seasonal scenarios produced drier conditions with no open water and greater vegetation cover compared to those resulting from the current climate. Only when spring precipitation increased did the wetland maintain an extensive open water area (49 percent). Potential changes in climate that affect spring runoff, such as changes to spring precipitation and snow melt, may have the greatest impact on prairie wetland hydrology and vegetation. In addition, relatively small changes in water level during dry years may affect the period of time the wetland contains open water. Emergent vegetation, once it is established, can survive under drier conditions due to its ability to persist in shallow water with fluctuating levels. The model's sensitivity to changes in temperature and seasonal precipitation patterns accentuates the need for accurate regional climate change projections from general circulation models.     

Modeling Climate Change Impacts on Hydrology and Nutrient Loading in the Upper Assiniboine Catchment1

Shrestha, Rajesh R., Yonas B. Dibike, and Terry D. Prowse, 2011. Modeling Climate Change Impacts on Hydrology and Nutrient Loading in the Upper Assiniboine Catchment. Journal of the American Water Resources Association (JAWRA) 48(1): 74‐89. DOI: 10.1111/j.1752‐1688.2011.00592.x Abstract: This paper presents a modeling study on climate‐induced changes in hydrologic and nutrient fluxes in the Upper Assiniboine catchment, located in the Lake Winnipeg watershed. The hydrologic and agricultural chemical yield model, Soil and Water Assessment Tool (SWAT) was employed to model a 21‐year baseline (1980‐2000) and future (2042‐2062) periods with model forcings for future climates derived from three regional climate models (RCMs) and their ensemble means. The modeled future scenarios reveal that potential future changes in the climatic regime are likely to modify considerably hydrologic and nutrient fluxes. The effects of future changes in climatic variables, especially precipitation and temperature, are clearly evident in the resulting snowmelt and runoff regimes. The future hydrologic scenarios consistently show earlier onsets of spring snowmelt and discharge peaks, and higher total runoff volumes. The simulated nutrient loads closely match the dynamics of the future runoff for both nitrogen and phosphorus, in terms of earlier timing of peak loads and higher total loads. However, nutrient concentrations could decrease due to the higher rate of runoff increase. Overall, the effects of these changes on the nutrient transport regime need to be considered together with possible future changes in land use, crop type, fertilizer application, and transformation processes in the receiving water bodies.