Abstract:Although close relationships between the water quality of streams and the types of land use within their watersheds have been well-documented in previous studies, many aspects of these relationships remain unclear. We examined the relationships between urban land use and water quality using data collected from 527 sample points in five major rivers in Korea-the Han, Geum, Nakdong, Younsan, and Seomjin Rivers. Water quality data were derived from samples collected and analyzed under the guidelines of the Korean National Aquatic Ecological Monitoring Program, and land use was quantified using products provided by the Korean Ministry of the Environment, which were used to create a Geographic Information System. Linear models (LMs) and generalized additive models were developed to describe the relationships between urban land use and stream water quality, including biological oxygen demand (BOD), total nitrogen (TN), and total phosphorous (TP). A comparison between LMs and non-linear models (in terms of R 2 and Akaike's information criterion values) indicated that the general additive models had a better fit and suggested a non-linear relationship between urban land use and water quality. Non-linear models for BOD, TN, and TP showed that each parameter had a similar relationship with urban land use, which had two breakpoints. The non-linear models suggested that the relationships between urban land use and water quality could be categorized into three regions, based on the proportion of urban land use. In moderate urban land use conditions, negative impacts of urban land use on water quality were observed, which confirmed the findings of previous studies. However, the relationships were different in very low urbanization or very high urbanization conditions. Our results could be used to develop strategies for more efficient stream restoration and management, which would enhance water quality based on the degree of urbanization in watersheds. In particular, land use management for enhancing stream water quality might be more effective when urban land use is in the range of 1.1%-31.5% of a watershed. If urban land use exceeds 31.5% in a watershed, a more comprehensive approach would be required because water quality would not respond as rapidly as expected.

This study examined the non-stationary relationship between the ecological condition of streams and the proportions of forest and developed land in watersheds using geographically-weighted regression (GWR). Most previous studies have adopted the ordinary least squares (OLS) method, which assumes stationarity of the relationship between land use and biological indicators. However, these conventional OLS models cannot provide any insight into local variations in the land use effects within watersheds. Here, we compared the performance of the OLS and GWR statistical models applied to benthic diatom, macroinvertebrate, and fish communities in sub-watershed management areas. We extracted land use datasets from the Ministry of Environment LULC map and data on biological indicators in Nakdong river systems from the National Aquatic Ecological Monitoring Program in Korea. We found that the GWR model had superior performance compared with the OLS model, as assessed based on R 2 , Akaike's Information Criterion, and Moran's I values. Furthermore, GWR models revealed specific localized effects of land use on biological indicators, which we investigated further. The results of this study can be used to inform more effective policies on watershed management and to enhance ecological integrity by prioritizing sub-watershed management areas

-Despite numerous previous studies, relationships between watershed land use and adjacent streams and rivers at various scales in Korea remain unclear. This study investigated the relationships between land uses and the physical, chemical, and biological characteristics of 720 sites of streams and rivers across the country. The land uses at two spatial scales, including a 1-km buffer and the base watershed management region (BWMR), were computed in a geographical information system (GIS) with a digital land use/land cover map. Characteristics of land uses at two spatial scales were then correlated with the monitored multidimensional characteristics of the streams and rivers. The results of this study indicate that land use types have significant effects on stream and river characteristics. Specifically, most characteristics were negatively correlated with the proportions of urban, rice paddy, agricultural, and bare soil areas and positively correlated with the amount of forest. The site-scale and BWMR-scale analyses suggest that BWMR land use patterns were more strongly related to ecological integrity than they were to site land use patterns. Improving our understanding of land use effects will largely depend on relating the results of site-specific studies that use similar response techniques and measures to evaluate ecological integrity. In addition, our results clearly indicate that the characteristics of streams and rivers are closely linked and that land use types differentially affect those characteristics. Thus, effective restoration and management for ecological integrity of lotic system should consider the physical, chemical, and biological factors in combination.

Understanding the complex relationships between land use and stream water quality is critical for water pollution control and watershed management. This study aimed to investigate the relationship between land use types and water quality indicators at multiple spatial scales, namely, the watershed and riparian scales, using the ordinary least squares (OLS) and geographically weighted regression (GWR) models. GWR extended traditional regression models, such as OLS to address the spatial variations among variables. Our results indicated that the water quality indicators were significantly affected by agricultural and forested areas at both scales. We found that extensive agricultural land use had negative effects on water quality indicators, whereas, forested areas had positive effects on these indicators. The results also indicated that the watershed scale is effective for management and regulation of watershed land use, as the predictive power of the models is much greater at the watershed scale. The maps of estimated local parameters and local R2 in GWR models showcased the spatially varying relationships and indicated that the effects of land use on water quality varied over space. The results of this study reinforced the importance of watershed management in the planning, restoration, and management of stream water quality. It is also suggested that planners and managers may need to adopt different strategies, considering watershed characteristics—such as topographic features and meteorological conditions—and the source of pollutants, in managing stream water quality.

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Understanding the complex human and natural processes that occur in watersheds and stream ecosystems is critical for decision makers and planners to ensure healthy stream ecosystems. This study aims to characterize the Han River watershed in Korea and extract key relationships among watershed attributes and biological indicators of streams using principal component analysis (PCA) and self-organizing maps (SOM). This study integrated watershed attributes and biological indicators of streams to delineate the watershed and stream biological status. Results from PCA strongly suggested that the proportions of watershed and riparian land use are key factors that explain the total variance in the datasets. Forest land in the watershed appeared to be the most significant factor. Furthermore, SOM planes showed that the biological indicators of streams have strong positive relationships with forest land, well-drained soil, and slope, whereas they have inverse relationships with urban areas, agricultural areas, and poorly drained soil. Hierarchical clustering classified the watersheds into three clusters, exclusively located in the study areas depending on the degree of forest, urban, and agricultural areas. The findings of this study suggest that different management strategies should be established depending on the characteristics of a cluster to improve the biological condition of streams.

It is imperative to develop a methodology to identify river impairment sources, particularly the relative impact of socioeconomic sources, to enhance the efficiency of various river restoration schemes and policies and to have an internal diagnosis system in place. This study, therefore, aims to identify and analyze the relative importance of the socioeconomic factors affecting river ecosystem impairment in South Korea. To achieve this goal, we applied the Analytical Hierarchy Process (AHP) to evaluate expert judgement of the relative importance of different socioeconomic factors influencing river ecosystem impairment. Based on a list of socioeconomic factors influencing stream health, an AHP questionnaire was prepared and administered to experts in aquatic ecology. Our analysis reveals that secondary industries form the most significant source of stream ecosystem impairment. Moreover, the most critical socioeconomic factors affecting stream impairment are direct inflow pollution, policy implementation, and industrial wastewater. The results also suggest that the AHP is a rapid and robust approach to assessing the relative importance of different socioeconomic factors that affect river ecosystem health. The results can be used to assist decision makers in focusing on actions to improve river ecosystem health.

The relationships between land cover characteristics in riparian areas and the biological integrity of rivers and streams are critical in riparian area management decision-making. This study aims to evaluate such relationships using the Trophic Diatom Index (TDI), Benthic Macroinvertebrate Index (BMI), Fish Assessment Index (FAI), and random forest regression, which can capture nonlinear and complex relationships with limited training datasets. Our results indicate that the proportions of land cover types in riparian areas, including urban, agricultural, and forested areas, have greater impacts on the biological communities in streams than those offered by land cover spatial patterns. The proportion of forests in riparian areas has the greatest influence on the biological integrity of streams. Partial dependence plots indicate that the biological integrity of streams gradually improves until the proportion of riparian forest areas reach about 60%; it rapidly decreases until riparian urban areas reach 25%, and declines significantly when the riparian agricultural area ranges from 20% to 40%. Overall, this study highlights the importance of riparian forests in the planning, restoration, and management of streams, and suggests that partial dependence plots may serve to provide insightful quantitative criteria for defining specific objectives that managers and decision-makers can use to improve stream conditions.