Watershed models are essential for evaluating the impact of watershed management; however, they contain many parameters that are not directly measurable. These parameters are commonly estimated by calibration against observed data, often streamflow. Unfortunately, many areas lack long-term streamflow records, making parameter estimation in low data environments (LDE) challenging. A new calibration technique, simultaneous multi-basin calibration (MBC), was developed to estimate model parameters in LDE. Three Soil and Water Assessment Tool (SWAT) model initializations for USGS gages with ~ 2-year records in the Lake Champlain Basin of Vermont, USA, were evaluated by comparing MBC and the commonly used similarity-based regionalization (SBR) approach, where calibrated parameters from a watershed with an extended data record are transferred to the LDE receptor watersheds. In MBC, each watershed is initialized, and observed flows from each initialization are aggregated to generate a combined streamflow record of sufficient length to calibrate using a differential evolution algorithm. New hydrological insights for the region: Using this new MBC method, we demonstrate improved model performance and more realistic model parameter values. This study demonstrates that short periods of hydrological measurement from multiple locations in a basin can represent a system similarly to long term measurements and that even short records taken at multiple locations significantly improve our hydrologic knowledge of a system as compared to relying on the similarity of a basin with a long record of flow. In addition, this study revealed that the hydrologic response is mediated by the interplay of very low soil-saturated hydraulic conductivity (Ksat) and cracking soils. As a result, even if Ksat is very low, cracking clays have a large impact on runoff production Garna et al. (2022). IntroductionWatershed scale hydrological models are often used to quantify and predict diverse and complicated hydrologic system behavior and are often used to manage environmental and water resources. A process based hydrological model consists of equations and parameters that describe watershed processes such as snow accumulation, groundwater flow, runoff generation, and
Hydrological models require a complete and accurate time series of weather inputs to adequately represent watershed-scale responses. The Global Historical Climatology Network (GHCN) is the most comprehensive ground-based global weather database and is often used in hydrological modeling studies. Since higher density, lower reliability precipitation measurements from private citizens collected by the Community Collaborative Rain, Hail, and Snow (CoCoRaHS) network data were integrated into the GHCN, hydrological modelers in the U.S. have access to a much greater amount of weather data. However, the benefit of using CoCoRaHS data has not been assessed. The objectives of this work were to develop a method for generating a complete weather data time series based on the combination of data from multiple GHCN monitors and to assess several methods for estimation of missing weather data. Weather data from GHCN monitors located within a specific radius of a watershed were obtained and interpolated using three estimation methods (Inverse Distance Weighting (IDW), Inverse Distance and Elevation Weighting (IDEW), and Closest Station), creating a seamless time-series of weather observations. To evaluate the performance of the methodologies, weather data obtained from each estimation method was used to force the Soil and Water Assessment Tool (SWAT) models of 21 U.S. Department of Agriculture-Conservation Effects Assessment Project watersheds in different climate regions to simulate daily streamflow for 2010-2021. Except for three watersheds, all SWAT models had Nash-Sutcliffe Efficiency above 0.5, the ratio of the root mean square error to the standard deviation of observations below 0.7, and percent bias from -25% to 25% with a satisfactory performance rating. Overall, IDEW and IDW performed similarly, and the Closest Station method resulted in the poorest streamflow simulation. A comparison with published SWAT model results further corroborated improved model performance using newly combined GHCN data with all Closest Station, IDW, and IDEW methods.
Watershed models are essential for evaluating the impact of watershed management; however, they contain many parameters that are not directly measurable. These parameters are commonly estimated by calibration against observed data, often streamflow. Unfortunately, many areas lack long-term streamflow records, making parameter estimation in low data environments (LDE) challenging. A new calibration technique, simultaneous multi-basin calibration (MBC), was developed to estimate model parameters in LDE. Three Soil and Water Assessment Tool (SWAT) model initializations for USGS gages with ~ 2-year records in the Lake Champlain Basin of Vermont, USA, were evaluated by comparing MBC and the commonly used similarity-based regionalization (SBR) approach, where calibrated parameters from a watershed with an extended data record are transferred to the LDE receptor watersheds. In MBC, each watershed is initialized, and observed flows from each initialization are aggregated to generate a combined streamflow record of sufficient length to calibrate using a differential evolution algorithm. New hydrological insights for the region: Using this new MBC method, we demonstrate improved model performance and more realistic model parameter values. This study demonstrates that short periods of hydrological measurement from multiple locations in a basin can represent a system similarly to long term measurements and that even short records taken at multiple locations significantly improve our hydrologic knowledge of a system as compared to relying on the similarity of a basin with a long record of flow. In addition, this study revealed that the hydrologic response is mediated by the interplay of very low soil-saturated hydraulic conductivity (Ksat) and cracking soils. As a result, even if Ksat is very low, cracking clays have a large impact on runoff production Garna et al. (2022). IntroductionWatershed scale hydrological models are often used to quantify and predict diverse and complicated hydrologic system behavior and are often used to manage environmental and water resources. A process based hydrological model consists of equations and parameters that describe watershed processes such as snow accumulation, groundwater flow, runoff generation, and
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