Seomijn River Basin has numerous hydraulic structures designed to satisfy water demands and mitigate future droughts. However, the increasing water demand and export to neighboring areas cause water deficits and conflicts between water users. Therefore, practical strategies to mitigate the potential damage from climate change are essential. In this study, we aimed to propose practical strategies under climate change by examining the future water security of the Seomjin River Basin under five different water allocation scenarios referenced from the practical policies of various countries. Future climate models determined based on extreme precipitation indices of the ETCCDI were used to investigate their impact on water security, which was evaluated using unmet demand; demand coverage; reliability, resilience, and vulnerability; and aggregation index metrics. We found that prioritizing domestic and industrial water use is the optimal water security strategy, and unconditional allocation of instream flow can cause a significant water deficit for other water uses. However, prioritizing all water uses equally also proved effective under some conditions. Thus, our study highlights the importance of adaptive management and suggests that the optimal water allocation strategy lies in its flexibility in response to varying circumstances.

Climate change not only affects the water resource system but also has a great impact on the aquatic ecosystem, which is complexly linked to various organic and inorganic matter. It is difficult to simulate the current aquatic ecosystem and predict the future system due to the immensity and complexity of aquatic ecosystems; however, a spatial analysis of future aquatic ecological health is necessary if we are to adapt and take action against future climate change. In this study, we evaluated the aquatic ecological health of the Han River basin under the future climate change RCP4.5 and RCP8.5 scenarios using three indices: fish assessment index (FAI), trophic diatom index (TDI), and benthic macroinvertebrate index (BMI). For this, we developed the SWAT-XGBoost linkage algorithm, and the algorithm accuracy for the FAI, TDI, and BMI was 89.3~95.2%. In the case of the FAI and BMI assessment of aquatic ecological health, the upstream Han River was classified as a hot spot. In the case of the TDI, the downstream area of the Han River was classified as a cold spot. However, as the current TDI downstream was classified as grades D and E, continuous management is needed.

This study evaluated the impact of climate change and water allocation scenarios on water security in the Seomjin River Basin using K-WEAP (Korea-Water Evaluation and Planning System). The findings indicated that domestic water and instream flow are vulnerable to climate change, while industrial water supply may fail to meet future demand in certain regions. Moreover, prioritizing instream flow was found to compromise the stability of the domestic water, and equal allocation adversely affected both domestic and industrial water security. Consequently, maintaining the current system appears to be the most effective approach; however, future studies should focus on developing flexible strategies that consider the effects of climate change and regional characteristics in a more detailed manner.

Climate change and urbanization have complex impacts on the hydrological and nutrient cycles of river basins, often leading to an increase in pollutants from non-point sources and the direct loading of pollutants into rivers, which can cause multifaceted environmental problems. Therefore, the purpose of this study was to evaluate the effects of future climate change and urbanization on the loads of major pollutants, including suspended solids (SS), total-nitrogen (T-N), and total-phosphorus (T-P) in the Anseong River Basin in South Korea. The Soil and Water Assessment Tool (SWAT) model was set up and calibrated using observed streamflow and water quality data, indicating satisfactory performance (R2 = 0.72–0.87). Time-series trend analysis showed that SS and T-N loads increased under wet climate and extreme urbanization scenarios. Monthly analysis indicated that higher SS in summer, while T-N and T-P decreased due to reduced infiltration from impervious surfaces. Pollution load duration curve analysis revealed that over 10% of pollutant loads occurred during high-flow events, emphasizing the need to manage first flush effects. This study provides the necessity for establishing future water quality management strategies and customized reduction measures for non-point source pollution.

The accurate estimation of low flow is necessary for effective water resource management, especially in regions with limited hydrological data. This study aims to enhance low-flow prediction by developing regional regression models based on climatological variables. Cluster analysis based on Ward’s method and K-means algorithm was applied to delineate hydrologically homogeneous regions within the Nakdong River Basin. Multiple regression models were developed for each cluster to estimate low-flow indicators, Q95 and 7Q. The results demonstrated that regional regression models outperformed the global regression model with log and square-root transformations improving predictive accuracy. Spatial analysis revealed that the key determinants of low-flow estimation may vary across hydrologic conditions, emphasizing the necessity of regionalized approaches for the estimation of low flow due to the limitations of a single global model in heterogeneous watersheds. The proposed methodology is believed to provide a robust framework for hydrological regionalization that can improve the estimation of low flow and support water resource management.