Abstract
The contradiction of water supply and demand has increased in China recently due to rapid economic and social development. Lacking of water has become one of problems that need to be improved and solved urgently. So assessment on water resources carrying capacity (WRCC) is an important basis for maintaining the sustainable development of water resources. In allusion to the uncertainty in the evaluation process, this study put forward an assessment method for WRCC based on the multi-dimensional cloud model after referring to the one-dimensional cloud model theory. Each evaluation index is regarded as a one-dimensional variable of the multi-dimensional cloud model. According to the cloud theory and WRCC assessment standards, appropriate cloud model digital characteristics were selected. After considering the information amount and correlation of indicators, and by using the sum of deviation square method to determine weights of all evaluation indicators, then a multi-dimensional cloud model corresponding to each evaluation level that integrated all evaluation indexes was generated. Then measured values of all indicators were entered to obtain the comprehensive certainty degree that belonged to each evaluation level, and WRCC level was determined under the principle of maximum certainty. To verify the rationality and effectiveness of the model, this study took a typical karst area (Guiyang) as an example, and compared assessment results with that of the one-dimensional cloud model and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method. Results showed that the multi-dimensional cloud model is effective in the assessment on WRCC. It can intuitively and quickly determine the carrying level of water resources, and provide a new method for the assessment on WRCC. Moreover, based on assessment results of the study area, some reasonable policies and measures were put forward to ensure the effective utilization of water resources and improve the bearing capacity of regional water resources.
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This study was financially supported by Programme of basic research in Guizhou province (science and technology fund) (foundation of Guizhou Grant no. [2020]1Y215).
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Peng, T., Jin, Z. & Xiao, L. Assessment on water resources carrying capacity in karst areas under a novel multi-dimensional cloud model—a case study. Arab J Geosci 16, 267 (2023). https://doi.org/10.1007/s12517-023-11348-7
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DOI: https://doi.org/10.1007/s12517-023-11348-7