Water quality assessment using water quality index (WQI) is performed based on major variables reflecting the river characteristics. We evaluated the water quality of tributaries of the Nam River in South Korea. We analyzed the tributaries spatial characteristics using cluster analyses and selected the main water quality variables (Cluster 1: chemical oxygen demand [COD], total organic carbon [TOC], total nitrogen, and total phosphorus; Cluster 2: water temperature [WT], dissolved oxygen [DO], COD, and TOC; Cluster 3: WT, DO, electrical conductance, COD, and TOC) of the clustered rivers. The WQI for each tributary was calculated using variables selected post statistical analysis. We verified that the WQI calculated in this study was similar to the annual change in water quality of the target river. Finally, it was analyzed that performing river water quality evaluation using the major variables selected using statistical analysis reflects the current water quality status of the river in more detail. (WQI grade was S1 Good (63.0), S2 Poor (53.3), S3 Excellent (98.4), S4 Poor (48.4), S5 (Excellent (100.0), S6 Good (77.6), S7 Good (76.2), S8 Good (76.5), S9 Good (69.9), S10 Excellent (81.5), S11 Good (71.2), S12 Good (63.1), and S13 Good (63.5).) Our method effectively reduced the number of variables required for index calculation compared with WQI methods of the MOE. Further, the reduced number of variables simplified the analysis process, reduced analysis time, and enabled water quality assessment that reflected the water quality characteristics of the river to be evaluated.

The Geumho River in South Korea passes through a metropolitan area with a high population density and multiple industrial complexes; therefore, the water quality of this river is of significance for human health and economic activities. This study assesses the water quality of the Geumho River to inform river water quality management and improve pollution control using multivariate statistics and the Korean Water Quality Index (KWQI). Principal component and factor analyses identified factors related to organic pollutants and metabolism (principal factor 1) and phosphorus and fecal coliform content (principal factor 2). Based on the results of the cluster analysis, it was classified into four groups in time and three groups in space. Six temporal variables and seven spatial variables were extracted from discriminant analysis results; the most important water quality variables were high during the spring and summer seasons and in the midstream and downstream regions. Temporally, the KWQI was the highest in winter and the lowest in spring; spatially, the KWQI was the highest in the upstream and the lowest in the midstream sections. These results indicate that to improve effectiveness, water management interventions in the Geumho River should focus on the urban midstream section and spring season.

As a response to climate change, South Korea has established its third National Climate Change Adaptation Plan (2021–2025) alongside the local governments’ plans. In this study, proxy variables in 22 sub-watersheds of the Nakdong River, Korea were used to investigate climate exposure, sensitivity, adaptive capacity, and non-point pollution in sub-watersheds, a climate change vulnerability index (CCVI) was established, and the vulnerability of each sub-watershed in the Nakdong River was evaluated. Climate exposure was highest in the Nakdong Estuary sub-watershed (75.5–81.7) and lowest in the Geumhogang sub-watershed (21.1–28.1). Sensitivity was highest (55.7) in the Nakdong Miryang sub-watershed and lowest (19.6) in the Habcheon dam sub-watershed. Adaptive capacity and the resulting CCVI were highest in the Geumhogang sub-watershed (96.2 and 66.2–67.9, respectively) and lowest in the Wicheon sub-watershed (2.61 and 18.5–20.4, respectively), indicating low and high vulnerabilities to climate change, respectively. The study revealed that the high CCVI sensitivity was due to adaptive capacity. These findings can help establish rational climate change response plans for regional water resource management. To assess climate change vulnerability more accurately, regional bias can be prevented by considering various human factors, including resources, budget, and facilities.

In this study, changes in water quality characteristics were compared before and after the construction of eight multifunctional weirs in the Nakdong River Basin in South Korea. A cluster analysis of spatial variation showed that the locations classified as Cluster 1 pre-construction (sites ND7 and ND8) shifted into Cluster 2 post-construction, indicating that spatial cluster types changed after the construction of multifunctional weirs. Principal component and factor analyses revealed that nitrogen and phosphorous nutrients at the pre-construction stage (total nitrogen, total phosphorous, and phosphate-phosphorus) and electrical conductivity were extracted in principal component 1, while biochemical oxygen demand, chemical oxygen demand, pH, and chlorophyll-a were extracted in principal component 2. However, biochemical oxygen demand, chemical oxygen demand, total organic carbon, and chlorophyll-a at the post-construction stage were extracted in principal component 1, while total nitrogen, nitrate-nitrogen, and dissolved oxygen were extracted in principal component 2. The key water quality indicators transitioned from nutrients to organic pollutants after the construction of the multifunctional weirs. A water quality trend analysis with seasonal Mann–Kendall testing and locally weighted scatter plot smoothing methods showed that organic pollutant indicators such as chemical oxygen demand and total organic carbon tended to increase after the construction of multifunctional weirs. Therefore, the key quality indicators for water quality improvement and management should be chemical oxygen demand and total organic carbon.