Abstract
There has been a steady shift towards modeling and model-based approaches as primary methods of assessing watershed response to hydrologic inputs and land management, and of quantifying watershed-wide best management practice (BMP) effectiveness. Watershed models often require some degree of calibration and validation to achieve adequate watershed and therefore BMP representation. This is, however, only possible for gauged watersheds. There are many watersheds for which there are very little or no monitoring data available, thus the question as to whether it would be possible to extend and/or generalize model parameters obtained through calibration of gauged watersheds to ungauged watersheds within the same region. This study explored the possibility of developing regionalized model parameter sets for use in ungauged watersheds. The study evaluated two regionalization methods: global averaging, and regression-based parameters, on the SWAT model using data from priority watersheds in Arkansas. Resulting parameters were tested and model performance determined on three gauged watersheds. Nash-Sutcliffe efficiencies (NS) for stream flow obtained using regression-based parameters (0.53–0.83) compared well with corresponding values obtained through model calibration (0.45–0.90). Model performance obtained using global averaged parameter values was also generally acceptable (0.4 ≤ NS ≤ 0.75). Results from this study indicate that regionalized parameter sets for the SWAT model can be obtained and used for making satisfactory hydrologic response predictions in ungauged watersheds.
Highlights
For a number of years, there has been a steady shift towards modeling and model-based approaches as primary methods of assessing watershed response to hydrologic inputs and land management and of quantifying watershed-wide best management practice (BMP) effectiveness
For the Illinois River watershed, the ground water revaporation (GW_REVAP) value obtained from global averaging was close to that obtained through calibration (Table 1) while the global surface runoff lag value obtained was closer to the calibrated value for Cadron Creek watershed (Table 1)
Model performance obtained using regression-based parameters was comparable to that obtained through calibration, based on Table 4
Summary
For a number of years, there has been a steady shift towards modeling and model-based approaches as primary methods of assessing watershed response to hydrologic inputs and land management and of quantifying watershed-wide best management practice (BMP) effectiveness. Watershed Environment Response Simulation model, ANSWERS [3]; and, the Hydrological. The use of modeling, necessitates a certain degree of model accuracy. This can, to a large extent, be determined through comparisons of model predictions to observed data at gauging stations within the watersheds and at the watershed outlet. Where available, watershed characterization data can be used to furnish model parameters in lieu of default values, presumably improving model performance. Often existing models require some degree of calibration and validation to achieve adequate watershed and
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