Water security sustainability evaluation: Applying a multistage decision support framework in industrial region

Faced with risks aroused by the ever-increasing expansion of industrialization and urbanization, water security sustainability takes more and more effect on balancing regional sustainability and development, especially for industrial regions. Introducing sustainability into the indicator framework of water security is an indispensable issue should be addressed. The indicators of water security sustainability in practice are measured by observation data obtained from a monitoring period. These data are commonly expressed in various forms, such as ratio and qualitative linguistic, which makes them hard to be quantified and evaluated. As multiply influential criteria are involved the water security sustainability evaluation process, it can be treated as a multi-criteria decision making problem. An appropriate evaluation framework with scientific and strategic multi-criteria decision making techniques is supposed to be constructed. This paper incorporates the dimensions related to sustainability into the indicator framework of water security sustainability. Another contribution of this paper is that it establishes an observation data conversion standard and adopts linguistic distribution assessments as information representation. Linguistic distribution assessments can capture the natural characteristics of the observation data of water security sustainability indicators. More importantly, a multistage decision support framework integrated with multi-criteria decision making techniques, such as best-worst method (BWM), decision making trial and evaluation laboratory (DEMATEL) and technique for order performance by similarity to ideal solution (TOPSIS), is constructed for water security sustainability evaluation. Then, deep analyzes about the evaluation results and influential factors are provided, thereby certifying the reliability of evaluation results and facilitating the enhancement of water security sustainability. (C) 2018 Elsevier Ltd. All rights reserved.