Climatic change has great implications for hydrological cycle and water resources planning. In order to assess this impact, a macro-scale and semi-distributed monthly water balance model was proposed and developed to simulate and predict the hydrological processes. GIS techniques were used as a tool to analyze topography, river networks, land-use, human activities, vegetation and soil characteristics. The model parameters were linked to these basin characteristics by regression and optimization methods. A parameterization scheme was developed and the model parameters were estimated for each grid element. Based on the different GCM and RCM outputs, the sensitivities of hydrology and water resources for China to global warming were studied. The proposed models are capable of roducing both the magnitude and timing of runoff and water resources conditions. The semi-dry regions, such as Liaohe, Haihe, Ruanhe and Huaihe River basins in north China, The runoffs of these basins are small or even zero during dry season (from Oct. to May) and are very sensitive to temperature increase and rainfall decrease. While in the basins of the humid south China like Yangtze River basin, the runoffs are perennial and the base flow normally occupies a large portion of the total runoff volume. These humid basins are less vulnerable to climate change. Results of the study also indicated that runoff is more sensitive to variation in precipitation than to increase in temperature. Climate change challenges existing water resources management practices by additional uncertainty. Integrated water resources management will enhance the potential for adaptation to change.

Effects of the catchment runoff coefficient on the performance of TOPMODEL in simulating catchment rainfall-runoff relationships are investigated in this paper, with an aim to improve TOPMODEL's simulation efficiency in catchments with a low runoff coefficient. Application of TOPMODEL in the semi-arid Yihe catchment, with an area of 2623 km2 in the Yellow River basin of China, produced a Nash-Sutcliffe model efficiency of about 80%. To investigate how the catchment runoff coefficient affects the performance of TOPMODEL, the whole observed discharge series of the Yihe catchment is multiplied with a larger-than-unity scale factor to obtain an amplified discharge series. Then TOPMODEL is used to simulate the amplified discharge series given the original rainfall and evaporation data. For a set of different scale factors, TOPMODEL efficiency is plotted against the corresponding catchment runoff coefficient and it is found that the efficiency of TOPMODEL increases with the increasing catchment runoff coefficient before reaching a peak (e.g. about 90%); after the peak, however, the efficiency of TOPMODEL decreases with the increasing catchment runoff coefficient. Based on this finding, an approach called the discharge amplification method is proposed to enhance the simulation efficiency of TOPMODEL in rainfall-runoff modelling in catchments with a low runoff coefficient.