Cloud model driven assessment of interregional water ecological carrying capacity and analysis of its spatial-temporal collaborative relation

Abstract

Water ecological carrying capacity (WECC) plays a significant role in the regional sustainable development. This study integrates techniques of normal cloud model, variable-weight combination prediction model, binary and multivariate spatial-temporal matching models, and the improved data envelopment analysis model for analyzing historical and future evolution, spatial-temporal collaborative relation, and input-output efficiency of WECC in the Beijing-Tianjin-Hebei (BTH) and Yangtze River Economic Zone (YREZ). Results reveal a generally fluctuating upward tendency of WECC level in the BTH and YREZ, in which water resources subsystem and socio-economic subsystem should be preferentially monitored in the eastern and midwestern YREZ, respectively. Combination prediction model has lower error than individual ones in terms of WECC forecasts. The binary spatial-temporal matching degrees between two WECC subsystems are equal to or above the medium state in the BTH and YREZ. The multivariate matching degrees decline and extremely fluctuate compared with the binary ones. WECC level and per capita GDP is presented as inverted N-shaped in the western region, while the rest regions are shown as U-shaped or N-shaped. WECC efficiency rises in fluctuation, especially in the central YREZ, while that in the BTH and western YREZ increases slowly with growth rates of 0.28% and 0.26%, respectively. These findings can facilitate improving regional WECC and making rational planning of water resources.