Assessment of river health based on an improved entropy-based fuzzy matter-element model in the Taihu Plain, China

Abstract

Rivers are valuable to human beings because of their various functions. Unfortunately, ecological integrity of rivers has been seriously threatened by human activities, resulting in poor river functions. It is thus necessary to evaluate and maintain river health. Meanwhile, it is challenging to comprehensively assess river health with a single method alone. It is therefore relevant to combine the advantages of multiple methods in river health assessment. By classifying and characterizing river functions, we first established an indicator system for river health assessment in plain river network regions. We then assessed the health status of the Taihu Plain in terms of an improved entropy-based fuzzy matter-element model. We found that the overall health status of the Taihu Plain is below “good”. In particular, the health status of Yang-Cheng-Dian-Mao and Hang-Jia-Hu Region is “moderate”; the Wu-Cheng-Xi-Yu Region displays the poorest natural and social river functions. We also found that flood control is the most important influential factor in river health. Our findings suggest that rivers in the Taihu Plain must be restored to maintain their health, with the Wu-Cheng-Xi-Yu Region that must be restored preferentially, and that the river function of flood control must be improved at the scale of whole watershed. Comparing with other four commonly used comprehensive assessment methods, our improved entropy-based fuzzy matter-element model outperforms in reflecting objective fact and can be applied to river health assessment. Our results are generally consistent with existing studies, confirming that the proposed method for river health assessment is effective and feasible. Therefore, it provides a useful reference for river health assessment in other plain river network regions.