Regional water resource carrying capacity evaluation based on multi-dimensional precondition cloud and risk matrix coupling model

Chengguo Wu; Liyang Zhou; Juliang Jin; Shaowei Ning; Zixiao Zhang; Lu Bai

doi:10.1016/j.scitotenv.2019.136324

Regional water resource carrying capacity evaluation based on multi-dimensional precondition cloud and risk matrix coupling model

Sci Total Environ. 2020 Mar 25:710:136324. doi: 10.1016/j.scitotenv.2019.136324. Epub 2019 Dec 28.

Authors

Chengguo Wu¹, Liyang Zhou², Juliang Jin³, Shaowei Ning¹, Zixiao Zhang², Lu Bai⁴

Affiliations

¹ School of Civil Engineering, Hefei University of Technology, Hefei, Anhui 230009, China; Institute of Water Resources and Environmental Systems Engineering, Hefei University of Technology, Hefei, Anhui 230009, China.
² School of Civil Engineering, Hefei University of Technology, Hefei, Anhui 230009, China.
³ School of Civil Engineering, Hefei University of Technology, Hefei, Anhui 230009, China; Institute of Water Resources and Environmental Systems Engineering, Hefei University of Technology, Hefei, Anhui 230009, China,. Electronic address: [email protected].
⁴ CSCEC AECOM Consultants Co., Ltd, Lanzhou, Gansu 730000, China.

PMID: 31923681
DOI: 10.1016/j.scitotenv.2019.136324

Abstract

Water resource carrying capacity modelling is a fundamental task to explore the interaction mechanism between socio-economic development and water resource carrying system. To reasonably quantify regional water resource carrying capacity, firstly, the water resource carrying system was divided into pressure, support and regulation forces subsystems, then the multi-dimensional precondition cloud algorithm was introduced to quantify the belonging degree of single evaluation index, and the comprehensive belonging degree of each sample was further obtained through risk matrix and index weight, and finally the multi-dimensional precondition cloud and risk matrix coupling model (PCRM) was established to recognize carrying grade and reveal carrying mechanism. The application results of PCRM model indicated that water resource carrying capacity in Anhui province, China presented a slightly improving trend in both provincial and city scales during 2005 to 2015. Meanwhile, evaluation result of PCRM model was more approaching to the average characteristic value of different approaches, which indicated that PCRM coupling model is effectively to explore properties of indexes and subsystems of water resource carrying system, and could be further applied in other system evaluation and regulation research fields in the future.

Keywords: Certainty degree; Evaluation; Fuzzy analytic hierarchy process; Multi-dimensional precondition cloud algorithm; Risk matrix; Water resource carrying capacity.