A Fuzzy Logic Method for River Health Assessment and Restoration Diagnosis

The global river health condition is increasingly critical, requiring comprehensive understanding as well as appropriate conservation measures. River health assessment provides important information for river conservation. In this paper, a set of metrics are designed on the basis of abiotic environments to assess river health status. Then, a fuzzy logic method is developed to integrate metrics to understand the status of river health with consideration of interactions among key components of rivers. The response sensibility analysis reveals that the fuzzy logic method is highly sensitive to single metrics since the influences of single metrics on the assessment result are amplified by interacting with other metrics. Taking the advantages of the feature of the fuzzy logic method, an approach is developed to diagnose factors whose restoration can gain the most significant improvements on river health status. This approach provides useful guidance for river health restoration which has little been performed until recently. The effectiveness of the fuzzy logic method is shown in the case study of the mainstream of the Yellow River. The results show that comprehensive restoration of water quality and flow regime needs to be carried out to improve river health status in the study area.