Variable precondition S-type cloud algorithm: Theory and application on water resources carrying capacity assessment.

• We assess the regional water resources carrying capacity (WRCC) scientifically. • Level of regional WRCC is assessed from three subsystems. • Change of WRCC can assess benefits of South-to-North Water Diversion Project (SWDP). • A new variable precondition S-type cloud algorithm is proposed to assess WRCC. • SWDP can increase carrying capacity of local water resources by 3.80% in Beijing. The purpose of water resources carrying capacity (WRCC) research is to meet the sustainable utilization of water resources and realize its sustainable development strategy. Scientifically evaluating the carrying capacity of regional water resources is extremely important. In this study, a variable precondition S-type cloud algorithm (VPSCA) is developed for assessment of regional WRCC based on social economic subsystem, water resources subsystem, ecological and environmental subsystem including thirteen indicators, which can overcome the shortcoming that the existing evaluation methods rarely consider fuzziness, randomness, and dynamic variability of parameters at the same time. First, forward S-type cloud generator algorithm (FSCGA) is developed based on segmented S-type membership function. On this basis, precondition S-type cloud generator algorithm (PSCGA) is proposed. Moreover, the VPSCA is developed by embedding PSCGA into variable fuzzy evaluation (VFE) method. Taking Beijing as a typical research area, this paper analyzes and forecasts the comprehensive benefits of water supply of the Middle Route of South-to-North Water Diversion Project (SWDP) in 2030 using VPSCA. The results show that SWDP can increase the carrying capacity of local water resources by 3.80%. In addition, feasibility and validity of VPSCA are further verified by comparison with other existing methods. This study aims to provide some suitable theoretical and practical implications of the evaluation of WRCC. [ABSTRACT FROM AUTHOR]