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In this study, 52 asymptotic Curve Number (CN) regression equations were developed for combinations of representative land covers and hydrologic soil groups. In addition, to overcome the limitations of the original Long-term Hydrologic Impact Assessment (L-THIA) model when it is applied to larger watersheds, a watershed-scale L-THIA Asymptotic CN (ACN) regression equation model (watershed-scale L-THIA ACN model) was developed by integrating the asymptotic CN regressions and various modules for direct runoff/baseflow/channel routing. The watershed-scale L-THIA ACN model was applied to four watersheds in South Korea to evaluate the accuracy of its streamflow prediction. The coefficient of determination (R²) and Nash-Sutcliffe Efficiency (NSE) values for observed versus simulated streamflows over intervals of eight days were greater than 0.6 for all four of the watersheds. The watershed-scale L-THIA ACN model, including the asymptotic CN regression equation method, can simulate long-term streamflow sufficiently well with the ten parameters that have been added for the characterization of streamflow. [ABSTRACT FROM AUTHOR]

The topography, and the biotic and abiotic parameters are typically upscaled to make watershed-scale hydrologic-biogeochemical models computationally tractable. However, upscaling procedure can produce biases when nonlinear interactions between different processes are not fully captured at coarse resolutions. Here we applied the Proper Orthogonal Decomposition Mapping Method (PODMM) to downscale the field solutions from a coarse (7 km) resolution grid to a fine (220 m) resolution grid. PODMM trains a reduced -order model (ROM) with coarse-resolution and fine-resolution solutions, here obtained using PAWS+CLM, a quasi-3-D watershed processes model that has been validated for many temperate watersheds. Subsequent fine-resolution solutions were approximated based only on coarse-resolution solutions and the ROM. The approximation errors were efficiently quantified using an error estimator. By jointly estimating correlated variables and temporally varying the ROM parameters, we further reduced the approximation errors by up to 20%. We also improved the method's robustness by constructing multiple ROMs using different set of variables, and selecting the best approximation based on the error estimator. The ROMs produced accurate downscaling of soil moisture, latent heat flux, and net primary production with O(1000) reduction in computational cost. The subgrid distributions were also nearly indistinguishable from the ones obtained using the fine-resolution model. Compared to coarse-resolution solutions, biases in upscaled ROM solutions were reduced by up to 80%. This method has the potential to help address the long-standing spatial scaling problem in hydrology and enable long-time integration, parameter estimation, and stochastic uncertainty analysis while accurately representing the heterogeneities. [ABSTRACT FROM AUTHOR]

This article reports a case study for applying DRAINMOD-GIS, a DRAINMOD-based lumped parameter watershed model, to Chicod Creek watershed, a 11100 ha coastal plain watershed in North Carolina that is not intensively instrumented or documented. The study utilized the current database of land use, topography, stream network, soil, and weather data available to state and federal agencies. Methods for collecting, evaluating, and formatting watershed data for model input are described. The study demonstrated that the lumped parameter model may be used to characterize the hydrology and water quality of Chicod Creek. Hydrology predictions were within 5% of the measured data. Predicted mean monthly nitrate-nitrogen (NO3-N) loads compared well with the measured data. Mean annual delivery ratios of each field ranged from 81% to 99% with a watershed mean of 90%. Application of the model to evaluate the effects of changing land use is presented. [ABSTRACT FROM AUTHOR]

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. • The modified algal module was applied to the SWAT model. • The algae-specific temperature correction term was applied to the process rates. • The regeneration of organic nutrients after algal die-off was reasonably introduced. • The module successfully reproduced the seasonal variation in phytoplankton biomass. [ABSTRACT FROM AUTHOR]