A framework for identifying priority areas through integrated eco-environmental risk assessment for a holistic watershed management approach

Abstract

Identifying priority management areas (PMAs) through assessing integrated eco-environmental risk (IER) of watersheds is vital for efficient integrated watershed management (IWM). However, there is a lack of effective tools to support IWM. A novel framework, which couples the analytical network process with the mean-square deviation decision method to quantify reciprocal feedbacks between ecosystems and socio-economic systems for assessing IER, was developed to identify PMAs for IWM through a case study in the upper Beiyun River watershed, China. The results show that water pollution, water resources, soil loss, hazards (i.e., floods, debris flows, collapses, and landslides), and vegetation degradation are noticeable environmental problems in the watershed. Water pollution, floods, and vegetation degradation risks are high in the southeast plain areas and low in the northwest mountainous areas of the watershed, while the other eco-environmental risks are opposite that of the three risks. The soil loss is mainly dominated by negligible class with a mean of 10.87 (t·km−2·yr−1). The weights of water pollution risk and socio-economic indicator for IER are 0.2906 and 0.1837, respectively. It indicates that water pollution control is crucial for IWM, and socio-economic systems have a significant impact on IER. The PMAs, which are identified as zones with extremely high IER values, account for 6.46 % (72.91 km2) of the watershed. They are centrally distributed in the southeastern areas with high risks of both water pollution and vegetation degradation caused by large population density. The framework provides an effective tool to assess IER and identify PMAs for IWM.