The water resources carrying capacity (WRCC) shows remarkable fuzziness and randomness, which causes the uncertainty and instability of the WRCC assessment (WRCCA). In order to solve these problems, we proposed a novel hybrid approach for WRCCA, in which the fuzzy comprehensive evaluation (FCE) and analytical hierarchy process (AHP) methods were integrated with the cloud model (CM). Firstly, an evaluation indicator system of WRCC was constructed. Secondly, the AHP and FCE methods were subsequently improved with the CM. The CM was used to scale the relative importance and aggregate the judgment matrices, where the weights of the clouds were obtained. These integrations of AHP and CM greatly reduced the randomness in the weight calculation; the CM was used to describe the comment sets, calculate the membership degree matrices and determine the assignment clouds, the evaluation sets and the WRCCA index clouds were obtained. These integrations of FCE and CM effectively blurred the boundary fuzziness and gave more intuitive results. Finally, the hybrid FCE-AHP-CM approach was applied to a case study. It was concluded that the novel approach has particular advantages in dealing with the fuzziness and randomness comprehensively, and therefore could assess the WRCC and enhance the robustness and intuition of WRCCA results.

A three dimensional finite element model (FEFLOW) has been used for regional ground water flow modeling of Mihuaishun plain located in the south of Beijing, China. The numerical groundwater flow model is developed considering recharge components (precipitation infiltration, river leakage, and irrigation return flow). GIS interface is created for each source of recharge. Hydraulic conductivities and storage coefficient have been calibrated by the steady state model using the recorded data from 2007 to 2009. The model results is useful to identify the aquifer characteristics and to analyze the groundwater dynamics. The groundwater level monitoring network will be improved by analyzing groundwater levels. The future development scenarios are proposed to predict the trend changes of groundwater levels.