58 research outputs found

    Technical Note: The impact of spatial scale in bias correction of climate model output for hydrologic impact studies

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    Statistical downscaling is a commonly used technique for translating large-scale climate model output to a scale appropriate for assessing impacts. To ensure downscaled meteorology can be used in climate impact studies, downscaling must correct biases in the large-scale signal. A simple and generally effective method for accommodating systematic biases in large-scale model output is quantile mapping, which has been applied to many variables and shown to reduce biases on average, even in the presence of non-stationarity. Quantile-mapping bias correction has been applied at spatial scales ranging from hundreds of kilometers to individual points, such as weather station locations. Since water resources and other models used to simulate climate impacts are sensitive to biases in input meteorology, there is a motivation to apply bias correction at a scale fine enough that the downscaled data closely resemble historically observed data, though past work has identified undesirable consequences to applying quantile mapping at too fine a scale. This study explores the role of the spatial scale at which the quantile-mapping bias correction is applied, in the context of estimating high and low daily streamflows across the western United States. We vary the spatial scale at which quantile-mapping bias correction is performed from 2° ( ∼  200 km) to 1∕8° ( ∼  12 km) within a statistical downscaling procedure, and use the downscaled daily precipitation and temperature to drive a hydrology model. We find that little additional benefit is obtained, and some skill is degraded, when using quantile mapping at scales finer than approximately 0.5° ( ∼  50 km). This can provide guidance to those applying the quantile-mapping bias correction method for hydrologic impacts analysis

    Climate Change Impacts on Streamflow and Subbasin- Scale Hydrology in the Upper Colorado River Basin

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    In the Upper Colorado River Basin (UCRB), the principal source of water in the southwestern U.S., demand exceeds supply in most years, and will likely continue to rise. While General Circulation Models (GCMs) project surface temperature warming by 3.5 to 5.6uC for the area, precipitation projections are variable, with no wetter or drier consensus. We assess the impacts of projected 21st century climatic changes on subbasins in the UCRB using the Soil and Water Assessment Tool, for all hydrologic components (snowmelt, evapotranspiration, surface runoff, subsurface runoff, and streamflow), and for 16 GCMs under the A2 emission scenario. Over the GCM ensemble, our simulations project median Spring streamflow declines of 36% by the end of the 21st century, with increases more likely at higher elevations, and an overall range of 2100 to +68%. Additionally, our results indicated Summer streamflow declines with median decreases of 46%, and an overall range of 2100 to +22%. Analysis of hydrologic components indicates large spatial and temporal changes throughout the UCRB, with large snowmelt declines and temporal shifts in most hydrologic components. Warmer temperatures increase averageannual evapotranspiration by ,23%, with shifting seasonal soil moisture availability driving these increases in late Winter and early Spring. For the high-elevation water-generating regions, modest precipitation decreases result in an even greater water yield decrease with less available snowmelt. Precipitation increases with modest warming do not translate into the same magnitude of water-yield increases due to slight decreases in snowmelt and increases in evapotranspiration. For these basins, whether modest warming is associated with precipitation decreases or increases, continued rising temperatures may make drier futures. Subsequently, many subbasins are projected to turn from semi-arid to arid conditions by the 2080 s. In conclusion, water availability in the UCRB could significantly decline with adverse consequences for water supplies, agriculture, and ecosystem health

    Development and application of a hydroclimatological stream temperature model within the Soil and Water Assessment Tool

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    We develop a stream temperature model within the Soil and Water Assessment Tool (SWAT) that reflects the combined influence of meteorological (air temperature) and hydrological conditions (streamflow, snowmelt, groundwater, surface runoff, and lateral soil flow) on water temperature within a watershed. SWAT currently uses a linear air-stream temperature relationship to determine stream temperature, without consideration of watershed hydrology. As SWAT uses stream temperature to model various in-stream biological and water quality processes, an improvement of the stream temperature model will result in improved accuracy in modeling these processes. The new stream temperature model is tested on seven coastal and mountainous streams throughout the western United States for which high quality flow and water temperature data were available. The new routine does not require input data beyond that already supplied to the model, can be calibrated with a limited number of calibration parameters, and achieves improved representation of observed daily stream temperature. For the watersheds modeled, the Nash-Sutcliffe (NS) coefficient and mean error (ME) for the new stream temperature model averaged 0.81 and −0.69°C, respectively, for the calibration period and 0.82 and −0.63°C for the validation period. The original SWAT stream temperature model averaged a NS of −0.27 and ME of 3.21°C for the calibration period and a NS of −0.26 and ME of 3.02°C for the validation period. Sensitivity analyses suggest that the new stream temperature model calibration parameters are physically reasonable and the model is better able to capture stream temperature changes resulting from changes in hydroclimatological conditions

    Natural and Managed Watersheds Show Similar Responses to Recent Climate Change

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    Changes in climate are driving an intensification of the hydrologic cycle and leading to alterations of natural streamflow regimes. Human disturbances such as dams, land-cover change, and water diversions are thought to obscure climate signals in hydrologic systems. As a result, most studies of changing hydroclimatic conditions are limited to areas with natural streamflow. Here, we compare trends in observed streamflow from natural and human-modified watersheds in the United States and Canada for the 1981–2015 water years to evaluate whether comparable responses to climate change are present in both systems. We find that patterns and magnitudes of trends in median daily streamflow, daily streamflow variability, and daily extremes in human-modified watersheds are similar to those from nearby natural watersheds. Streamflow in both systems show negative trends throughout the southern and western United States and positive trends throughout the northeastern United States, the northern Great Plains, and southern prairies of Canada. The trends in both natural and human-modified watersheds are linked to local trends in precipitation and reference evapotranspiration, demonstrating that water management and land-cover change have not substantially altered the effects of climate change on human-modified watersheds compared with nearby natural watersheds

    Modeling Water Flux at the Base of the Rooting Zone for Soils with Varying Glacial Parent Materials

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    Poster presented at American Geophysical Union meeting in 2013.Soils of varying glacial parent materials in the Great Lakes Region (USA) are characterized by thin unsaturated zones and widespread use of agricultural pesticides and nutrients that affect shallow groundwater. To better our understanding of the fate and transport of contaminants, improved models of water fluxes through the vadose zones of various hydrogeologic settings are warranted. Furthermore, calibrated unsaturated zone models can be coupled with watershed models, providing a means for predicting the impact of varying climate scenarios on agriculture in the region. To address these issues, a network of monitoring sites was developed in Indiana that provides continuous measurements of precipitation, potential evapotranspiration (PET), soil volumetric water content (VWC), and soil matric potential to parameterize and calibrate models. Flux at the base of the root zone is simulated using two models of varying complexity: 1) the HYDRUS model, which numerically solves the Richards equation, and 2) the soil-water-balance (SWB) model, which assumes vertical flow under a unit gradient with infiltration and evapotranspiration treated as separate, sequential processes. Soil hydraulic parameters are determined based on laboratory data, a pedo-transfer function (ROSETTA), field measurements (Guelph permeameter), and parameter optimization. Groundwater elevation data are available at three of six sites to establish the base of the unsaturated zone model domain. Initial modeling focused on the groundwater recharge season (Nov–Feb) when PET is limited and much of the annual vertical flux occurs. HYDRUS results indicate that base of root zone fluxes at a site underlain by glacial ice-contact parent materials are 48% of recharge season precipitation (VWC RMSE=8.2%), while SWB results indicate that fluxes are 43% (VWC RMSE=3.7%). Due in part to variations in surface boundary conditions, more variable fluxes were obtained for a site underlain by alluvium with the SWB model (68% of recharge season precipitation, VWC RMSE=7.0%) predicting much greater drainage than HYDRUS (38% of recharge season precipitation, VWC RMSE=6.6%). Results also show that when calculating drainage flux over the recharge period, HYDRUS is highly sensitive to model initialization using observed water content from in-situ instrumentation. Simulated recharge season drainage flux is as much as 3.5 times higher when a one-month spin-up period was performed in the HYDRUS model for the same site. SWB results are less sensitive to water content initialization, but drainage flux is 1.6 times higher at one site using the same spin-up analysis. The long-term goals of this effort are to leverage the robust calibration data set to establish optimal approaches for determining hydraulic parameters such that water fluxes in the lower vadose zone can be modeled for a wider range of geomorphic settings where calibration data are unavailable

    Climate change and stream temperature projections in the Columbia River basin: habitat implications of spatial variation in hydrologic drivers

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    Water temperature is a primary physical factor regulating the persistence and distribution of aquatic taxa. Considering projected increases in air temperature and changes in precipitation in the coming century, accurate assessment of suitable thermal habitats in freshwater systems is critical for predicting aquatic species\u27 responses to changes in climate and for guiding adaptation strategies. We use a hydrologic model coupled with a stream temperature model and downscaled general circulation model outputs to explore the spatially and temporally varying changes in stream temperature for the late 21st century at the subbasin and ecological province scale for the Columbia River basin (CRB). On average, stream temperatures are projected to increase 3.5 °C for the spring, 5.2 °C for the summer, 2.7 °C for the fall, and 1.6 °C for the winter. While results indicate changes in stream temperature are correlated with changes in air temperature, our results also capture the important, and often ignored, influence of hydrological processes on changes in stream temperature. Decreases in future snowcover will result in increased thermal sensitivity within regions that were previously buffered by the cooling effect of flow originating as snowmelt. Other hydrological components, such as precipitation, surface runoff, lateral soil water flow, and groundwater inflow, are negatively correlated to increases in stream temperature depending on the ecological province and season. At the ecological province scale, the largest increase in annual stream temperature was within the Mountain Snake ecological province, which is characterized by migratory coldwater fish species. Stream temperature changes varied seasonally with the largest projected stream temperature increases occurring during the spring and summer for all ecological provinces. Our results indicate that stream temperatures are driven by local processes and ultimately require a physically explicit modeling approach to accurately characterize the habitat regulating the distribution and diversity of aquatic taxa

    The Future of Indiana’s Water Resources: A Report from the Indiana Climate Change Impacts Assessment

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    This report from the Indiana Climate Change Impacts Assessment (IN CCIA) applies climate change projections for the state to explore how continued changes in Indiana’s climate are going to affect all aspects of water resources, including soil water, evaporation, runoff, snow cover, streamflow, drought, and flooding. As local temperatures continue to rise and rainfall patterns shift, managing the multiple water needs of communities, natural systems, recreation, industry, and agriculture will become increasingly difficult. Ensuring that enough water is available in the right places and at the right times will require awareness of Indiana’s changing water resources and planning at regional and state levels

    VanCampernolle et al 2019

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    Folder includes species locality data and current and future environmental data used for Maxent species distribution models. The 'Calibration fish localities' file includes individual georeferenced species localities used for Maxent model calibration (training). The 'Validation fish localities' file includes individual georeferenced species localities used for Maxent model validation (testing). The 'Currrent_environment' folder includes GIS habitat data for Maxent modeling of contemporary species distributions. The 'Future_environment' folder includes GIS habitat data for Maxent projection of future species distributions. The 'Future_environment' folder contains subfolders with all Global Climate Model (GCM) scenarios used for future Maxent projections
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