Abstract:

Land Use/Cover Change (LUCC) and its hydrological impacts on watershed are the highlighted research issue on the global change, and delving into and quantifying the hydrological effects caused by land use/cover change contribute to an overall assessment of the hydrological cycle and water resources evolution within the watershed. The forcing factors that drive LUCC in watershed are so numerous and the nonlinear relationships between the factors and LUCC are so complicated that it is very difficult to build a simulation model. Intelligent modeling with the capability of nonlinearity and selfadaption provided an efficient route for the simulation of the dynamic evolution of complicated system. In this paper, a coupled CAANN model based on Cellular Automata (CA) and Artificial Neutral Network (ANN) was established for the simulation of LUCC in watershed. The upstream watershed of Hanjiang basin was taken as the case study, with land use in 1980 and 2000 as calibration and validation, respectively, and the transferring area and probability of LUCC were analyzed. The CAANN coupled model was built for the simulation of the transition rules and dynamic evolution of LUCC and the satisfied accuracy in LUCC simulation was obtained. The scenario of land use/cover in 2020s was simulated by using the established CAANN coupled model. The results showed that the paddy field, dry farm, shrubbery and construction land area in 2020 would increase in varying degrees. The woodland, grassland and water body area would decrease. The simulated results corresponded to the trends of LUCC in the upstream watershed of Hanjiang basin, which demonstrated that the coupled CAANN model could simulate the complicated nonlinear dynamic evolving process of LUCC land use/cover change in watershed. On this basis, this study applied the distributed hydrological model (SWAT model) to simulate the hydrological processes in the upstream watershed of the Hanjiang Basin, and analyzed the variation of surface runoff and evapotranspiration in watershed under different LUCC scenarios. The results indicated that the annual average runoff tended to increase and the annual LUCC had more significant impact on runoff than the flood season, average annual evapotranspiration of years showed a upward trend under the LUCC scenarios of 1980s, 2000s and the simulated 2020s