To investigate the recent effects of climate change in the upper Geum River basin in South Korea, a detailed trend analysis of 17 extreme climate indices based on 33 years (1988–2020) of daily precipitation, and daily (minimum and maximum) temperature data has been analyzed in this study. Out of the 17 extreme climate indices, nine (eight) indices were based on temperature (precipitation) data. Trend analysis based on detailed temporal scales (annual, seasonal, monthly) were performed through the Mann–Kendall trend test and the Theil–Sen slope method. Furthermore, the Mann–Whitney–Pettit test was also applied in this study, to detect abrupt changes in the extreme climate indices. Based on the results of this study, the climate conditions at the upper Geum River basin for the past three decades can be summarized as follows: general increase in temperature intensity, decrease in cold duration, increased heat duration, increased precipitation intensity, and increased consecutive wet and dry durations. Furthermore, a prolonged summer season (shorter spring, and autumn periods) and precipitation shifts, were detected based on trend analysis results of seasonal, and monthly time scales. The results presented in this study can provide supplementary data for improving watershed management strategies in the upper Geum River basin.

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Reservoirs are essential structures to provide reliable water supply, hydropower, and flood control. Climate change could be a significant factor that increases the sediment yield leading to rapid reduction of the reservoir’s storage capacity and design life. Previous studies of reservoir sedimentation-related impact of climate change often coupled a hydrological model with the raw outputs of general circulation model (GCM)/regional circulation model (RCM), which shows bias when comparing with observations data. This study aims to integrate the soil and water assessment tool (SWAT) model with 14 bias-corrected GCM/RCM models under two emissions scenarios, representative concentration pathway (RCP) 4.5 and 8.5, applied to Pleikrong reservoir to estimate its sedimentation in the long term period. The results show the reduction in reservoir storage capacity due to sedimentation ranges from 25% to 62% by 2050, depending on the defferent climate change models. The reservoir reduced storage volume’s rate in considering the impact of climate change is much faster than in the case of no climate change. The outcomes of this study will be helpful for a sustainable and climate-resilient plan of sediment management for the Pleikrong reservoir.

Precipitation is a significant input variable required in hydrological models such as the Soil & Water Assessment Tool (SWAT). The utilization of inaccurate precipitation data can result in the poor representation of the true hydrologic conditions of a catchment. SWAT utilizes the conventional nearest neighbor method in assigning weather parameters for each subbasin; a method inaccurate in representing spatial variations in precipitation over a large area, with sparse network of gauging stations. Therefore, this study aims to improve the spatial variation in precipitation data to improve daily streamflow simulation with SWAT, even pre-model calibration. The daily streamflow based on four interpolation methods, nearest neighbor (default), inverse-distance-weight, radial-basis function, and ordinary kriging, were evaluated to determine which interpolation method is best represents the precipitation at Yongdam watershed. Based on the results of this study, the application of spatial interpolation methods generally improved the performance of SWAT to simulate daily streamflow even pre-model calibration. In addition, no universal method can accurately represent the long-term spatial variation of precipitation at the Yongdam watershed. Instead, it was observed that the optimal selection of interpolation method at the Yongdam watershed is dependent on the long-term climatological conditions of the watershed. It was also observed that each interpolation method was optimal based on certain meteorological conditions at Yongdam watershed: nearest neighbor for cases when the occurrence probability of extreme precipitation is high during wet to moderately wet conditions; radial-basis function for cases when the number of dry days were high, during wet, severely dry, and extremely dry conditions; and ordinary kriging or inverse-weight-distance method for dry to moderately dry conditions. The methodology applied in this study improved the daily streamflow simulations at Yongdam watershed, even pre-model calibration of SWAT.

A B S T R A C TNon-point source (NPS) pollutants are generated and washed off from various land uses during storm events. Different pollutants and soil particles can be discharged to stream and lakes. In this study, three different land use types such as urban, agricultural, and livestock areas were selected to determine the physico-chemical characteristics of the discharged sediments. The results showed that sediment generated from urban areas consists of large particle sizes such as sand. Moreover, sediments from agricultural and livestock areas mainly consisted of silt and sand particles. The sediment from urban areas showed the highest content of non-biodegradable organic matters, which was mainly composed of hydrocarbons caused by vehicular activities, compared to other land use types. On the other hand, the livestock area showed high-nitrogen content concentration caused by livestock wastewater. Comparing the metal concentration in sediments coming from different land use types showed that the generated metal pollution was below the Korean soil standard. This implied that these sediments can be recycled. However, the results also showed that establishment of best management practices are necessary to mitigate water pollution. Furthermore, management practice from pollution source sites to river entrance should be practiced.