Watershed health, including the natural environment, hydrology, water quality, and aquatic ecology, is assessed for the Han River basin (34 148 km²) in South Korea by using the Soil and Water Assessment Tool (SWAT). The evaluation procedures follow those of the Healthy Watersheds Assessment by the U.S. Environmental Protection Agency (EPA). Six components of the watershed landscape are examined to evaluate the watershed health (basin natural capacity): stream geomorphology, hydrology, water quality, aquatic habitat condition, and biological condition. In particular, the SWAT is applied to the study basin for the hydrology and water-quality components, including 237 sub-watersheds (within a standard watershed on the Korea Hydrologic Unit Map) along with three multipurpose dams, one hydroelectric dam, and three multifunction weirs. The SWAT is calibrated (2005–2009) and validated (2010–2014) by using each dam and weir operation, the flux-tower evapotranspiration, the time-domain reflectometry (TDR) soil moisture, and groundwater-level data for the hydrology assessment, and by using sediment, total phosphorus, and total nitrogen data for the water-quality assessment. The water balance, which considers the surface–groundwater interactions and variations in the stream-water quality, is quantified according to the sub-watershed-scale relationship between the watershed hydrologic cycle and stream-water quality. We assess the integrated watershed health according to the U.S. EPA evaluation process based on the vulnerability levels of the natural environment, water resources, water quality, and ecosystem components. The results indicate that the watershed's health declined during the most recent 10-year period of 2005–2014, as indicated by the worse results for the surface process metric and soil water dynamics compared to those of the 1995–2004 period. The integrated watershed health tended to decrease farther downstream within the watershed.

This study developed a multi-criteria approach to spatially assess the robust water resource vulnerability in sub-basins and applied it to the Han River basin. The Intergovernmental Panel on Climate Change (IPCC) suggested three factors of vulnerability; namely, exposure, sensitivity and adaptive capacity were used in this study with respect to water quantity and quality. In this study, 16 water quantity indicators and 13 water quality indicators were selected to identify the vulnerability using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method. Environmental and socioeconomic data were obtained from the national statistics database, and hydrological data were simulated using the calibrated Soil and Water Assessment Tool (SWAT) model. Expert surveys and Shannon entropy method were used to determine subjective and objective weights for all indicators, individually. As a result, water quantity-vulnerable sub-basins were associated with high water use and water leakage ratios. Water quality-vulnerable sub-basins were associated with relatively high values of maximum consecutive dry days and heatwave days. The water quantity indices of both weighting methods showed relatively similar spatial distributions, while the distribution of water quality indices was distinct. These results suggest that considering different weighting methods is important for assessing the robust water resource vulnerability of sub-basins.

This study evaluates the watershed-scale effects of non-point-source (NPS) pollution loads caused by rice straw mulching and no-tillage applications in upland crop areas using the Hydrological Simulation Program–Fortran (HSPF) model. The study area is the Byulmi-cheon watershed (1.21 km²) of South Korea. Hourly rainfall, discharge and stream water quality data were collected for three years (2011–2013) at the watershed outlet. The HSPF model under conventional (no rice straw mulching or tillage) conditions was calibrated and validated using 20 rainfall events for runoff and 14 rainfall events for stream water quality (sediment, T-N and T-P). The average Nash–Sutcliffe model efficiency value for runoff was 0.61, and determination coefficients for runoff, sediment, total nitrogen (T-N) and total phosphorus (T-P) were 0.70, 0.56, 0.58 and 0.61, respectively. The results of field experiments with slopes of 3% and 8% for radish and sesame cultivation showed decreases in the runoff ratio, sediment, T-N and T-P of 9.0%, 95.9%, 32.6% and 43.5% for rice straw mulching plots and 22.5%, 82.5%, 67.8 and 70.6% for no-tillage plots. The HSPF model parameters soil infiltration capacity (INFILT), soil bulk density (BD), wilting point (WP) and field capacity (FC) were controlled for the upland crop areas during the evaluation of the rice straw mulching and no-tillage effects. The HSPF evaluation using the application of Best Management Practices (BMPs) showed that the watershed runoff ratio, sediment, T-N and T-P values were reduced by 10.4%, 68.7%, 31.6% and 41.3% using rice straw mulching and 21.5%, 83.4%, 51.9% and 60.2% under no-tillage conditions compared with conventional conditions. The land use change scenarios for the baseline (upland crop areas 5%), Scenario 1 (upland crop areas 10%) and Scenario 2 (upland crop areas 30%) were applied in the model. The results of the evaluation show that the proportion of NPS pollution loads increased by a ratio approximately equal to that of the increasing upland crop area.

This study evaluated SWAT model when measured Evapotranspiration (ET) and Soil Moisture (SM) in addition to streamflow (Q) data were used to calibrate the simulated values in a 8.54 km² hillslope watershed of South Korea. By using 7 years (2003–2009) daily Q at the watershed outlet, 3 years (2007–2009) daily ET and SM data measured in the mixed forest, the SWAT model was calibrated and validated with the average Nash-Sutcliffe model efficiency (E) for Q of 0.76, and the coefficient of determination (R²) for SM and ET of 0.55 and 0.59, respectively. The use of measured hydrological state variables such as ET or SM in SWAT modeling provided more reliable interpretation of model parameters by inducing the reduction of parameter uncertainty and understanding the behavior of the watershed water balance. When the watershed has only Q data for model calibration, it is encouraged to consider soil (ESCO) and plant related parameters (EPCO and CANMX) in addition to surface runoff (CN2, and Surlag) and groundwater related parameters (GW_ DELAY and GW_ REVAP).