Assessment on water resources carrying capacity in karst areas by using an innovative DPESBRM concept model and cloud model

Highlights: • A new concept model is proposed the first time. • Water resources carrying capacity can be described by the model and 28 indicators. • Cloud model is used to conduct assessment on water resources carring capacity. • Guiyang's water resources carrying capacity showed a clear trend of change. • Result of cloud model is more beneficial to recognize water resources carrying grade. The shortage of water resources in karst areas is mainly caused by the development of karst landforms, poor availability of water resources and the difficulty of utilization. To reasonably evaluate water resources carrying capacity (WRCC) of karst areas, based on characteristics of urban water resources utilization in karst areas, this study put forward DPESBRM (Driver-Pressure-Engineering water shortage-State-Ecological basis-Response-Management) concept model the first time to build an urban evaluation index system of WRCC in karst areas. Based on this index system and in allusion to uncertainties that exist during the evaluation process, a cloud model is used to represent index weights and perform comprehensive evaluation calculations, which fully considers the randomness and ambiguity of evaluation objects. WRCC from 2009 to 2018 were evaluated and were classified as five grades (Serious overload – Overload – Critical – Weak carrying capacity – Strong carrying capacity). Results proved that WRCC had improved year after year, gradually changing from a serious overload state in 2009 to a strong carrying capacity state in 2018. 2009 and 2016 were classified as I grade (serious overload). 2010 and 2011 were classified as II grade (overload). 2012, 2013 and 2015 were classified as IV grade (weak bearing capacity). 2014, 2017 and 2018 were classified as V grade (strong bearing capacity). Cloud model assessment results are compared with that of TOPSIS method, and assessment results are basically unanimous. It shows that the established WRCC evaluation method based on cloud model in this study is reasonable and feasible. Population density, urbanization rate and per capital water consumption are important driving factors affecting WRCC. Hence, strengthening the construction of water conservancy facilities, optimizing the water consumption structure, improving the efficiency of industrial water use, reducing per capital water consumption, and narrowing urban water supply and demand gap are important measures to ensure WRCC.