Watershed-scale Models Research Articles

Microbial kinetics and thermodynamic (MKT) processes for soil organic matter decomposition and dynamic oxidation-reduction potential: Model descriptions and applications to soil N2O emissions

A conversion of the global terrestrial carbon sink to a source is critically dependent on the microbially mediated decomposition of soil organic matter (SOM). We have developed a detailed, process-based, mechanistic model for simulating SOM decomposition and its associated processes, based on Microbial Kinetics and Thermodynamics, called the MKT model. We formulated the sequential oxidation-reduction potential (ORP) and chemical reactions undergoing at the soil-water zone using dual Michaelis-Menten kinetics. Soil environmental variables, as required in the MKT model, are simulated using one of the most widely used watershed-scale models - the soil water assessment tool (SWAT). The MKT model was calibrated and validated using field-scale data of soil temperature, soil moisture, and N2O emissions from three locations in the province of Saskatchewan, Canada. The model evaluation statistics show good performance of the MKT model for daily soil N2O simulations. The results show that the proposed MKT model can perform better than the more widely used process-based and SWAT-based models for soil N2O simulations. This is because the multiple processes of microbial activities and environmental constraints, which govern the availability of substrates to enzymes were explicitly represented. Most importantly, the MKT model represents a step forward from conceptual carbon pools at varying rates.

Quantifying pollutant loading from channel sources: Watershed-scale application of the River Erosion Model

Phosphorus and fine sediment pollution are primary causes of water quality degradation. Streambank erosion is a potentially significant source of fine sediment and particulate phosphorus to watersheds, but it remains difficult to quantify the magnitude of this loading. A new, easily applied, watershed scale model was used to simulate the potential for future phosphorus and sediment loading from channel erosion in two watersheds: Big Dry Creek, Colorado and Lick Creek, North Carolina. The projected magnitude of loading for phosphorus is about an order of magnitude higher in Big Dry Creek compared to Lick Creek (∼280 kg/yr and ∼50 kg/yr, respectively), while sediment loading results are similar (∼950 ton/yr). In both watersheds, model results suggest that channel erosion will not contribute a significant amount of phosphorus to the watershed (∼1–4% of historic watershed total from all pollutant sources) but will contribute a large amount of sediment (30–100% of historic watershed total). Uncertainty in these estimates is high, but quantifying confidence in model projections is important for understanding and using model results. Importantly, modeling shows no decrease in loading over the 40-year model time frame in either watershed, suggesting that the channels are not adjusting to a new stable state and erosion will continue to be a pollutant source. Lick Creek model results are sensitive to upstream sediment supply while Big Dry Creek's are not, reinforcing the importance of considering alterations to both the hydrologic and sediment regimes when analyzing potential channel changes — at least in vertically active channels. This new modeling approach is useful for estimating historic and future phosphorus and sediment loading from channel erosion, an important first step in effective management to improve water quality.

A watershed-scale model for depressional wetland-rich landscapes

Wetlands are often dominant features in low relief, depressional landscapes and provide an array of hydrologically driven ecosystem services. However, contemporary models do not adequately represent the role of spatially distributed wetlands in watershed-scale water storage and flows. Such tools are critical to better understand wetland hydrological, biogeochemical, and biological functions and predict management and policy outcomes at varying spatial scales. To develop a new approach for simulating depressional landscapes, we modified the Soil and Water Assessment Tool (SWAT) model to incorporate improved representations of depressional wetland structure and hydrological processes. Specifically, we refined the model to incorporate: (1) water storage capacity and surface flowpaths of individual wetlands and (2) local wetland surface and subsurface exchange. We utilized this model, termed SWAT-DSF (DSF for Depressional Storage and Flows), to simulate the ∼289 km2 Greensboro watershed within the Delmarva Peninsula of the US Coastal Plain. Model calibration and verification used both daily streamflow observations and remotely sensed surface water extent data (ca. 2-week temporal resolution), allowing us to assess model performance with respect to both streamflow and watershed inundation patterns. Our findings demonstrate that SWAT-DSF can successfully replicate distributed wetland processes and resultant watershed-scale hydrology. SWAT-DSF provides improved temporal and spatial characterization of watershed-scale water storage and flows in depressional landscapes, providing a new tool to quantify wetland functions at broad spatial scales.

Simple regression models can act as calibration-substitute to approximate transient storage parameters in streams

Transient storage models in combination with tracer tests are widely used to study solute transport dynamics in streams. Storage parameters included in such models are typically calibrated for one or more study reaches by monitoring solute concentrations and fitting breakthrough curve data. Since stream characteristics vary spatially and temporally, it is challenging to generalize these calibrated parameters for another stream reach. This study investigates the ability of simple regression models to predict transient storage parameters such as dispersion coefficient (D), transient storage area (As) and storage exchange coefficient (α). A meta-analysis of 834 tracer studies from 67 published papers was used to develop parsimonious non-linear regression models that relate storage parameters to easily available stream parameters such as discharge, velocity, flow width and flow depth. Correlation analysis showed moderate correlation of D with velocity, depth and width; and high correlation of As with the ratio of discharge to depth. Exchange coefficient (α) did not show significant correlation with available stream parameters. The models were tested using a subset of meta-analysis data and experimental tracer data from Hubbard Brook Experimental Forest located in the US and Kielstau Catchment located in Germany. We predicted storage and breakthrough curves with reasonable accuracy (R2 > 0.5) by using new regression equations and incorporating it into an advection-dispersion-storage model. These equations provide a viable alternative to approximate transient storage parameters in circumstances where time and cost-intensive reach-specific calibration is impossible. Therefore, such regression-based estimates of storage parameters can also form an integral part of larger watershed scale models by predicting solute transport and storage in stream reaches.

Evaluating connectivity for two mid-sized mammals across modified riparian corridors with wildlife crossing monitoring and species distribution modeling

The movement of wildlife can be constrained by river development projects owing to the presence of artificial structures. This study analyzes the spatial riparian crossing patterns of two mammal species, the leopard cat (Felis bengalensis euptilura) and water deer (Hydropotes inermis). We examine their ability to traverse from habitat on one side of the river to the other, through riparian vegetation, embankments, and the river,. We used 34 months of monitoring on 104 stream segments with varying levels of human modification on the Seom river, South Korea, to analyze their riparian crossing preferences across the river between suitable habitats on either side of the steam. Environmental variables were used for two scales of analysis: a watershed scale and a stream segment scale that examined both riparian habitat suitability and riparian crossings. At the watershed scale, habitat suitability was determined using species distribution modeling. The resulting maps were inputted with other predictor variables to logistic regression models to predict areas of high probability for the species' occurences. For the river segment analyses, we determined species’ presences and potential crossings from snow tracking, heat sensor cameras, and scat. We compared the predicted crossing locations from the watershed scale model to observed crossings. The watershed models indicate that leopard cats prefer upland forest, while water deer prefer the forest edge and riparian corridor. For both target species, the best riparian habitats were characterized by the presence of vegetation cover on the embankment and by at least one side of an embankment being adjacent to farmland or forest cover. The two species showed different riparian crossing preferences. Water deer crossed through large culverts or under bridges, whereas leopard cats utilized drainage pipes and smaller culvert boxes. Stream reaches located close to a river tributary had the highest connectivity values, and areas modeled as good habitats were linked near riparian and watershed areas with high density for both species as well as culvert boxes with a high openness ratio. Artifacts such as steep banks, concrete embankments, and adjacent roads were found to degrade the riparian connectivity of wildlife. These outcomes can be used to identify suitable riparian wildlife habitats of mammals, to evaluate lateral connectivity of riparian corridors for mammals, and to develop criteria for river conservation and restoration in urbanizing areas and developing countries.

CoBAGNPS: A Toolbox to Estimate Sediment Removal Efficiency of WASCoBs–Pipe Risers and Blind Inlets

Water and Sediment Control Basin (WASCoB) is an important BMP constructed along concentrated flow-paths (gullies etc.) to control the movement of water and sediment within a watershed. A WASCoB constitutes of a berm, surface inlets, and a drainage pipe to route water into a ditch. Direct runoff ponded behind the berm is routed through surface inlets into an underground drainage pipe. Therefore, surface inlets are an exceedingly important constituent of a WASCoB. Further pipe risers and blind inlets are the two most common type of surface inlets used. Therefore, maximum sediment removal efficiency of WASCoBs at a watershed-scale can be attained by the appropriate selection of a surface inlet, since the efficiency of a WASCoB is greatly impacted by the quantity of runoff and sediment leaving the surface inlet. In this study a toolbox was developed viz., CoBAGNPS to compute the sediment removal efficiency of pipe risers and blind inlets. A watershed-scale model (AGNPS) was integrated within the toolbox. Output files of the AGNPS model are fed as input files into the toolbox where a sediment routing module is programmed separately for pipe risers and blind inlets to obtain the sediment removal efficiency for each type of surface inlet. Further, the sediment routing module programmed for blind inlets integrates the AGNPS model with the HYDRUS 1-D model. The toolbox developed was applied to the Gully Creek watershed in Ontario, and the sediment load routed through pipe risers and blind inlets were compared.

Microbial Water Quality: Monitoring and Modeling

Microbial water quality lies in the nexus of human, animal, and environmental health. Multidisciplinary efforts are under way to understand how microbial water quality can be monitored, predicted, and managed. This special collection of papers in the was inspired by the idea of creating a special section containing the panoramic view of advances and challenges in the arena of microbial water quality research. It addresses various facets of health-related microorganism release, transport, and survival in the environment. The papers analyze the spatiotemporal variability of microbial water quality, selection of predictors of the spatiotemporal variations, the role of bottom sediments and biofilms, correlations between concentrations of indicator and pathogenic organisms and the role for risk assessment techniques, use of molecular markers, subsurface microbial transport as related to microbial water quality, antibiotic resistance, real-time monitoring and nowcasting, watershed scale modeling, and monitoring design. Both authors and editors represent international experience in the field. The findings underscore the challenges of observing and understanding microbial water quality; they also suggest promising research directions for improving the knowledge base needed to protect and improve our water sources.

Controls of Chloride Loading and Impairment at the River Network Scale in New England.

Chloride contamination of rivers due to nonpoint sources is increasing throughout developed temperate regions due to road salt application in winter. We developed a river-network model of chloride loading to watersheds to estimate road salt application rates and investigated the meteorological factors that control riverine impairment by chloride at concentrations above thresholds protective of aquatic organisms. Chloride loading from road salt was simulated in the Merrimack River watershed in New Hampshire, which has gradients in development density. After calibration to a regional network of stream chloride data, the model captured the distribution of regional discharge and chloride observations with efficiencies of 93 and 75%, respectively. The estimate of road salt application is within uncertainties of inventoried estimates of road salt loading and is 122 to 214% greater than recommended targets. Model predictions of chloride showed seasonal variation in chloride concentrations despite a large groundwater storage pool. Interannual variation of mean summer chloride concentration near the outlet varied up to 18%, and the total river length exceeding impairment thresholds varied 12%. Annual snowfall, which drives road salt loading, correlated with chloride impairment only in headwater streams, whereas concentration variability at the outlet was driven primarily by dilution from clean runoff-draining undeveloped forested areas of the watershed. The role of summer meteorology complicates the protection of freshwater systems from chloride contamination.

Calibration Parameter Selection and Watershed Hydrology Model Evaluation in Time and Frequency Domains

Watershed scale models simulating hydrological and water quality processes have advanced rapidly in sophistication, process representation, flexibility in model structure, and input data. With calibration being an inevitable step prior to any model application, there is need for a simple procedure to assess whether or not a parameter should be adjusted for calibration. We provide a rationale for a hierarchical selection of parameters to adjust during calibration and recommend that modelers progress from parameters that are most uncertain to parameters that are least uncertain, namely starting with pure calibration parameters, followed by derived parameters, and finally measured parameters. We show that different information contained in time and frequency domains can provide useful insight regarding the selection of parameters to adjust in calibration. For example, wavelet coherence analysis shows time periods and scales where a particular parameter is sensitive. The second component of the paper discusses model performance evaluation measures. Given the importance of these models to support decision-making for a wide range of environmental issues, the hydrology community is compelled to improve the metrics used to evaluate model performance. More targeted and comprehensive metrics will facilitate better and more efficient calibration and will help demonstrate that the model is useful for the intended purpose. Here, we introduce a suite of new tools for model evaluation, packaged as an open-source Hydrologic Model Evaluation (HydroME) Toolbox. We apply these tools in the calibration and evaluation of Soil and Water Assessment Tool (SWAT) models of two watersheds, the Le Sueur River Basin (2880 km2) and Root River Basin (4300 km2) in southern Minnesota, USA.

Assessing the impacts of land use on downstream water quality using a hydrologically sensitive area concept

Understanding the relationship between land use and water quality is essential to improve water quality through carefully managing landscape change. This study applies a linear mixed model at both watershed and hydrologically sensitive areas (HSAs) scales to assess such a relationship in 28 northcentral New Jersey watersheds located in a rapidly urbanizing region in the United States. Two models differ in terms of the geographic scope used to derive land use matrices that quantify land use conditions. The land use matrices at the watershed and HSAs scales represent the land use conditions in these watersheds and their HSAs, respectively. HSAs are the hydrological “hotspots” in a watershed that are prone to runoff generation during storm events. HSAs are derived using a soil topographic index (STI) that predicts hydrological sensitivity of a landscape based on a variable source area hydrology concept. The water quality indicators in these models are total nitrogen (TN), total phosphorus (TP) and total suspended solids (TSS) concentrations in streams observed at the watershed outlets. The modeling results suggest that presence of low density urban land, agricultural land and wetlands elevate while forest decreases TN, TP and/or TSS concentrations in streams. The watershed scale model tends to emphasize the role of agricultural lands in water quality degradation while the HSA scale model highlights the role of forest in water quality improvement. This study supports the hypothesis that even though HSAs are relatively smaller area compared to watershed, still the land uses within HSAs have similar impacts on downstream water quality as the land uses in entire watersheds, since both models have negligible differences in model evaluation parameters. Inclusion of HSAs brings an interesting perspective to understand the dynamic relationships between land use and water quality.

Improved Soil Temperature Modeling Using Spatially Explicit Solar Energy Drivers.

Modeling the spatial and temporal dynamics of soil temperature is deterministically complex due to the wide variability of several influential environmental variables, including soil column composition, soil moisture, air temperature, and solar energy. Landscape incident solar radiation is a significant environmental driver that affects both air temperature and ground-level soil energy loading; therefore, inclusion of solar energy is important for generating accurate representations of soil temperature. We used the U.S. Environmental Protection Agency’s Oregon Crest-to-Coast (O’CCMoN) Environmental Monitoring Transect dataset to develop and test the inclusion of ground-level solar energy driver data within an existing soil temperature model currently utilized within an ecohydrology model called Visualizing Ecosystem Land Management Assessments (VELMA). The O’CCMoN site data elucidate how localized ground-level solar energy between open and forested landscapes greatly influence the resulting soil temperature. We demonstrate how the inclusion of local ground-level solar energy significantly improves the ability to deterministically model soil temperature at two depths. These results suggest that landscape and watershed-scale models should incorporate spatially distributed solar energy to improve spatial and temporal simulations of soil temperature.

Perennial vegetation impacts on stream discharge and channel sources of sediment in the Minnesota River Basin

While sediment loads in streams draining agricultural landscapes have traditionally been attributed to field sources via overland flow and surface erosion, recent research has identified important nonfield sources of sediment in the Minnesota River Basin. We evaluate the impacts of altered vegetation on water budget and sediment loading in Seven Mile Creek, an agricultural watershed with important nonfield sources of sediment. Using the Soil and Water Assessment Tool (SWAT) and monitoring data for different locations, we developed an approach to account for different sediment sources and show that nonfield sediment export is strongly affected by changes in stream discharge, which is affected by vegetation impacts on water yield. This is important because many watershed-scale models are calibrated to sediment loads at the watershed outlet based on the assumption that all sediment is derived from field sources. This can lead to overestimation of erosion from field sources and unrealistic expectations for watershed-scale reductions based on some conservation practices. In Seven Mile Creek watershed under current conditions, approximately 76% of the sediment delivered to the watershed outlet originates from nonfield sources (streambanks and ravines). Relative to the current landscape, increases in perennial grasses or switchgrass (Panicum virgatum L.) cause decreases in water yield owing to differences in evapotranspiration (especially in the spring). As streamflow decreases, sediment export is disproportionately reduced from nonfield sources. These results demonstrating an interaction between evapotranspiration and streambank/ravine erosion are important for showing that nonfield sources of sediment can be important in some watersheds, and that realistic approaches for improving water quality may need to include strategies for managing water quantity.

Simulating seasonal variability of phytoplankton in stream water using the modified SWAT model

The ability to simulate algal systems is critical for watershed-scale models. The objective of this study was to develop and evaluate a modified algal module that simulates the dynamics of three major algal groups (cyanobacteria, green algae, and diatoms) in a stream using variables available in the Soil and Water Assessment Tool. The proposed module 1) models the dynamics of the three algal groups while accounting for nutrients from algal die-off and 2) has temperature multipliers that consider the effect of temperature changes on kinetic rates. Data to test the module were collected from a forest-dominated watershed over two years. The modified module was efficient in predicting seasonal variations in algal group biomass and simulated the regeneration of nutrients after algal die-off. This module will be useful in predicting the dynamics of the three studied algal groups and evaluating the best management practices for algal blooms in watersheds.

A novel technique for establishing soil topographic index thresholds in defining hydrologically sensitive areas in landscapes

Hydrologically sensitive areas (HSAs) are useful for analyzing a watershed. However, correct delineation of HSAs is critical for conducting such analysis. Scientifically defensible methods for delineating HSAs are lacking. The objectives of this study are to identify threshold soil topographic indices (STIs) based on the relationship between the observed soil moisture and the calculated STI in two sites using a trellis plot approach, and validate the identified threshold STIs in delineating HSAs in 15 watersheds in North Central New Jersey based on a linear mixed modeling of the relationship between land use and water quality at the watershed and HSA scales. Field soil moisture data are collected during April, May, June, July, August, and September for three years at Christie Hoffman Park and Fairview Farm in Central New Jersey. The linear mixed models assess the relationship between land use metrics in terms of percentages of land uses and three water quality indicators including total suspended solids, total nitrogen and total phosphorus in streams at both watershed and HSA scales. Trellis plot analyses based on a polynomial regression model of order of two to four identify the threshold STIs ranging from nine to 15 for delineating HSAs. The linear mixed modeling results indicate that the relationships between land use and three water quality indicators at the HSA scales are similar to their relationships at the watershed scale. The predictive powers of these HSA and watershed scale models are very similar. These results suggest that it is appropriate for policymakers and watershed managers to use HSAs rather than entire watersheds to characterize watersheds and devise management strategies to optimize resource uses. The novel technique developed in this study can be used in other parts of the world.

Parameter estimation and uncertainty analysis of the Spatial Agro Hydro Salinity Model (SAHYSMOD) in the semi-arid climate of Rechna Doab, Pakistan

Manual calibration of distributed models with many unknown parameters can result in problems of equifinality and high uncertainty. In this study, the Generalized Likelihood Uncertainty Estimation (GLUE) technique was used to address these issues through uncertainty and sensitivity analysis of a distributed watershed scale model (SAHYSMOD) for predicting changes in the groundwater levels of the Rechna Doab basin, Pakistan. The study proposes and then describes a stepwise methodology for SAHYSMOD uncertainty analysis that has not been explored in any study before. One thousand input data files created through Monte Carlo simulations were classified as behavior and non-behavior sets using threshold likelihood values. The model was calibrated (1983–1988) and validated (1998–2003) through satisfactory agreement between simulated and observed data. Acceptable values were observed in the statistical performance indices. Approximately 70% of the observed groundwater level values fell within uncertainty bounds. Groundwater pumping (Gw) and hydraulic conductivity (Kaq) were found to be highly sensitive parameters affecting groundwater recharge.

Release from Streambed to Water Column during Baseflow Periods: A Modeling Study.

Streambed sediments can harbor large populations that are released into the water column during high-flow events. Few studies have been conducted on the rates of transfer from streambed sediment to water column in low-flow conditions in natural streams. The aim of this work was to apply the watershed-scale model SWAT (Soil and Water Assessment Tool) to a natural stream to evaluate the need to account for the release from streambed sediments during baseflow periods and to compare the results of simulating such a release by assuming predominantly passive transport, driven by groundwater influx, against simulations assuming predominantly active transport of random or chemotaxis-driven bacteria movement. concentrations in water during baseflow periods were substantially underestimated when release from the streambed was attributed only to streambed sediment resuspension. When considered in addition to the release due to sediment resuspension at high flows, the active and passive release assumptions provided 42 and 4% improvement, respectively, in the RMSE of logarithms of concentrations. Estimated fluxes to water column during the baseflow periods from June to November ranged from 3.3 × 10 colony-forming units (CFU) m d in the game land area to 1.4 × 10 CFU m d in the mixed pasture and cropland. Results demonstrate that release of from streambed sediments during baseflow periods is substantial and that water column concentrations are dependent on not only land management practices but also on in-stream processes.

Urban Stormwater Characterization, Control, and Treatment.

The following review presents a synthesis of 181 journal articles published during 2015 that represent progress toward better characterizing, controlling, and treating urban stormwater runoff. The review is structured by general topical areas related to (1) stormwater quality and quantity characterization; (2) engineered stormwater control and treatment practices, including erosion and sediment control, stormwater ponds, constructed stormwater wetlands, bioretention, permeable pavement, greenroofs, and rainwater harvesting systems; and (3) watershed-scale modeling and optimization of stormwater control and treatment practices. Common research themes emerging from this collection of studies include potential to enhance hydrologic and pollutant treatment performance of stormwater practices via media amendments and the use of innovative outlet control structures, as well as development of a more mechanistic understanding of hydrologic and water-quality functions to inform modeling and performance predictions. These studies serve to expand the field's knowledge base and will inform future efforts to further improve stormwater control and treatment at various spatial and temporal scales.

Watershed-scale modeling on the fate and transport of polycyclic aromatic hydrocarbons (PAHs)

PAHs are potentially carcinogenic substances that are persistent in the environment. Increasing concentrations of PAHs were observed due to rapid urbanization, thus; monitoring PAHs concentrations is necessary. However, it is expensive to conduct intensive monitoring activities of a large number of PAHs. This study addressed this issue by developing a multimedia model coupled with a hydrological model (i.e., Soil and Water Assessment Tool (SWAT)) for Taehwa River (TR) watershed in Ulsan, the industrial capital of South Korea. The hydrologic module of the SWAT was calibrated, and further used to simulate the fate and transport of PAHs in soil and waterbody. The model demonstrated that the temporal or seasonal variation of PAHs in soil and waterbody can be well reproduced. Meanwhile, the spatial distribution of PAHs showed that urban areas in TR watershed have the highest PAH loadings compared to rural areas. Sensitivity analyses of the PAH soil and PAH water parameters were also able to determine the critical processes in TR watershed: degradation, deposition, volatilization, and wash off mechanism. We hope that this model will be able to aid the stakeholders in: regulating PAH concentrations emitted by various sources; and also apply the model to other Persistent Organic Pollutants (POPs).

Development of a Component-Based Modeling Framework for Agricultural Water-Resource Management

Because hydrologic responses of an agricultural watershed are influenced by many natural and man-made factors including pond/reservoir, management practices, and/or irrigation/drainage, strategies of hydrological modeling for the watershed must be case-dependent and thus carefully designed to effectively reflect their roles as critical hydrologic components in simulation processes. In this study, we propose a component-based modeling framework that accommodates a flexible modeling approach to consider a variety of hydrologic processes and management practices, especially irrigation-reservoir operation and paddy-farming practices, in watershed-scale modeling. The objectives of this study are twofold: to develop a COmponent-based Modeling Framework for Agricultural water-Resources Management (COMFARM) using an object-oriented programming technique, and to evaluate its applicability as a modeling tool to predict the responses of an agricultural watershed characterized with diverse land uses in a case study. COMFARM facilitates quick and easy development of watershed-specific hydrologic models by providing multiple interchangeable simulation routines for each hydrologic component considered. COMFARM is developed with the JAVA programming language, using Eclipse software. The framework developed in this study is applied to simulating hydrologic processes of the Seon-Am irrigation-district watershed consisting primarily of reservoir-irrigated rice paddies in South Korea. The application study clearly demonstrates the applicability of the framework as a convenient method to build models for hydrologic simulation of an agricultural watershed. The newly developed modeling framework, COMFARM is expected to serve as a useful tool in watershed management planning by allowing quick development of case-oriented analysis tools and evaluation of management scenarios customized to a specific watershed.

A New Open-Access HUC-8 Based Downscaled CMIP-5 Climate Model Forecast Dataset for the Conterminous United States

Watershed-scale hydrologic simulation models generally require climate data inputs including precipitation and temperature. These climate inputs can be derived from downscaled global climate simulations which have the potential to drive runoff forecasts at the scale of local watersheds. While a simulation designed to drive a local watershed model would ideally be constructed at an appropriate scale, global climate simulations are, by definition, arbitrarily determined large rectangular spatial grids. This paper addresses the technical challenge of making climate simulation model results readily available in the form of downscaled datasets that can be used for watershed scale models. Specifically, we present the development and deployment of a new Coupled Model Intercomparison Project phase 5 (CMIP5) based database which has been prepared through a scaling and weighted averaging process for use at the level of U.S. Geological Survey (USGS) Hydrologic Unit Code (HUC)-8 watersheds. The resulting dataset includes 2,106 virtual observation sites (watershed centroids) each with 698 associated time series datasets representing average monthly temperature and precipitation between 1950 and 2099 based on 234 unique climate model simulations. The new dataset is deployed on a HydroServer and distributed using WaterOneFlow web services in the WaterML format. These methods can be adapted for downscaled General Circulation Model (GCM) results for specific drainage areas smaller than HUC-8. Two example use cases for the dataset also are presented.