The Potential of Integrating Landscape, Geochemical and Economical Indices to Analyze Watershed Ecological Environment

Abstract. A river watershed is a complicated ecosystem, and its spatial structure and temporal dynamics are driven by various natural factors such as soil properties and topographic features, human activities, and their interactions. Thus, characterizing the river watershed ecosystem and monitoring its dynamics is very challenging. In this study, we explored the characteristics of the ecosystem and environment of Yalong River watershed in Ganzi Tibetan Autonomous Prefecture, Sichuan Province of China by analyzing and modeling the relationships among economic indices, heavy metal elements and landscape metrics. Landsat 8 data were used to generate a land cover classification map and to derive landscape pattern indices. Governmental finance statistics yearbook data were referred to provide economic indices. Moreover, a total of 9 water samples were collected from the upstream to the downstream to obtain the values of heavy metal concentrations in the water body. Then, both correlation and regression analyses were applied to analyze and model the relationships among these indices. The results of this study showed that 1) The ecological status and process of this river watershed could be explained by analyzing the relationships among the economic indices, heavy metal elements and landscape pattern indices selected based on correlation analysis; 2) Compared with the economic indices, the accumulated economic indices were more significantly correlated with most of the heavy metal elements and should be applied for the integrated assessment of the watershed ecological environment; 3) Landscape pattern indices SHDI and IJI had strong correlations with the important economic indices Population and Population Density and could be used for the integrated assessment of the watershed characteristics; 4) Compared with land cover area, land cover area ratios were more sensitive to the variation of the economic indices. The dominated land cover types Forest and Grassland had strong relationships with the economic indices; and 5) Cu and Zn had significant correlations with the landscape pattern indices. This study implied that analyzing and modeling the relationships among the economic indices, heavy metal elements and landscape pattern indices can provide a powerful tool for characterizing the ecosystem of the river watershed and useful guidelines for the watershed management and sustainable development.