The standard cuckoo searching algorithm(SCSA)is a population intelligent optimization algorithm, which is also a new heuristic searching algorithm. The advantages of SCSA (such as convenient operation, heuristic searching, etc.) make it easy to find the optimal solution and maintain wider searching range. However, SCSA also has some drawbacks, such as long searching time, easy to fall into local optimum. In order to solve the problems existed in SCSA, in this paper, the improved standard cuckoo searching algorithm (ISCSA) was studied, which includes chaotic initialization and Gaussian disturbed algorithm. As a case study, taking economic, social and ecological benefits as the objective function, the multi-objective water resources optimal allocation models were constructed in Xianxiang Region, China. The ISCSA was applied to solve the water allocation models and the multi-objective optimal water supply scheme for Xinxiang region was obtained. The water resources optimal allocation schemes in the planning level year (2025) for 12 water supply sub-regions were predicted. The desirable eco-environment and benefits were achieved using the studied methods. The results show that the ISCSA has obvious advantages in the solution of water resources optimal allocation and planning.