No abstract

Spatial-temporal patterns of river water quality, the identification of pollution sources and contaminated areas are crucial to water environment protection and sustainable development of the river basin. In this study, spatial-temporal characteristics of river water quality in the Yihe river basin were investigated through multivariate analysis methods, including principal component analysis (PCA), cluster analysis (CA), discriminant analysis (DA), and one-way ANOVA. The water quality indicators (Hydrogen ion concentration (pH), electric conductivity (EC), dissolved oxygen (DO), turbidity, chemical oxygen demand (COD), total phosphorus (TP), and ammonia nitrogen (NH4 + -N)) were investigated at 17 sampling sites in three periods (i.e., high-, mean-, low flow period) during 2016 ~ 2017. The results show that: (1) PCA served to extract and recognize the most significant indicators affecting water quality in the Yihe river basin, i.e., pH, EC, COD, and NH4 + -N. (2) CA divided the Yihe river basin into three groups with similar water quality features, namely the upper, middle, and lower reaches. (3) DA demonstrated strong dimensionality reduction ability with the accuracy of clustering was 94.1%, and only a few indicators (i.e., DO, EC, turbidity, NH4 + -N, and TP) could reflect the spatial variations in water quality. (4) One-way ANOVA indicated that the water quality was the worst in the lower reach of Yihe river basin during the mean-flow period, followed by which in the upper and middle reaches during the high-flow period. (5) The spatiotemporal characteristics of water quality were mainly restrained by human factors (e.g., the construction of highway and agricultural activities), climate change (e.g., precipitation and temperature), and natural environments (e.g., topography).

Ecosystem services (ES) can link natural ecosystems with socioeconomic systems. The Yi River basin is one of the most important sub-basins of the Yellow River basin, and the landscape pattern of this basin has changed dramatically in recent years. However, the assessment of landscape patterns on ecosystem services value (ESV) in such basin has been little studied. Therefore, the temporal-spatial evolution of the landscape pattern and ESV of the Yi River basin was evaluated through the landscape indices analysis method and the method for evaluating the value equivalent factor in unit area, based on land cover data from 1987 to 2020. The effects of changes in landscape patterns on ESV were then quantified. The results show that (1) Forest was the dominant landscape type in the Yi River basin, followed by grassland, with the total area of both accounting for 80% of the basin area. From 1987 to 2020, the area of forest and construction land has increased, while that of farmland and grassland has decreased. In addition, the stability of the landscape within the basin was low, and the fragmentation of patches was serious. The landscape shape index (LSI) for 2015 and 2020 was 52.57 and 42.38, respectively, and Shannon's diversity index (SHDI) value increased from 1.04 to 1.17 in the same period, indicating that the degree of heterogeneity in the landscape of the Yi River basin was considerably reduced and the dominant patches were well connected. (2) From 1987 to 2020, the total ESV (supply, regulation, support, and cultural services) in the Yi River basin showed an “N” pattern of variation. Specifically, such total ESV increased noticeably from 1987 to 2005, decreased after 2005, bottomed out in 2015, and began to recover by 2020. Forest regulating services contributed the most to the total ESV at 77%. (3) The results of correlation analysis displayed that total ESV was negatively correlated with LSI and positively correlated with SHDI. Moreover, water supply services had a significant inverse relationship with the largest patch index (LPI), LSI, and SHDI. The LSI and patch density index (PD) had a strong positive correlation with biodiversity. Human activities (e.g., urbanization) were found to be the main drivers of a landscape pattern change and ESV decline in the Yi River basin, thus the level of biodiversity and overall ecosystem service provision in such basin can be improved by increasing the degree of landscape heterogeneity and reducing the complexity of landscape shape. The assessment of the evolution of landscape patterns and the quantification of its impact on ESV can help provide scientific information for improving the ecological qualify and supporting sustainable development in the Yi River basin.