A macro-scale and semi-distributed monthly water balance model to predict climate change impacts in China

Abstract

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 producing 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.

Introduction

Global climatic change caused by growing atmospheric concentration of carbon dioxide and other trace gases has become evident (IPCC, 1995, Houghton et al., 2001, Kamga, 2001). Climate change or its increased variability is expected to alter the timing and magnitude of runoff. As a result it has important implications for existing water resources systems as well as for future water resources planning and management. For instance, under the climate change in recent years, the imbalance between water supply and water demands has been increasing, which has given rise to great attention from both the relevant authorities and the general public to water resources planning programs. Hence, urgent action is required for understanding and solving potential water resources problems for human's existence and well-being, especially, quantitative estimates of hydrological effects of climate change are essential.

In assessing climate change impacts, an important topic is the long-term forecasting of the water cycle changes and their spatial distribution, which includes two steps. The first step is to employ the general circulation models (GCMs) and regional climate models (RCMs) to produce the values of temperature and precipitation for each grid. The second step is the application of the macro-scale distributed hydrological models, normally the monthly water balance model, to each grid, for converting the projected rainfall into runoff. Generally, the monthly water balance model is mainly applied in three fields, i.e. reconstruction of the hydrology of basins, assessment of climatic change impacts, and evaluation of the seasonal and geographical patterns of water supply and irrigation demand (Xu and Singh, 1998).

Currently there are many different monthly water balance models and many researches in this field have been intensively conducted. In the 1940s and 1950s, Thornthwaite and Mather (1955) developed a set of deterministic monthly water balance models, in which only two parameters were used. In developing an index of meteorological drought, Palmer (1965) suggested a model that divides the soil moisture storage into two layers. In 1981, Thomas proposed a four-parameter abcd water balance model. Alley (1984) reviewed and examined the Thornthwaite–Mather models, the Palmer (1965) model, and the Thomas, 1981, Thomas et al., 1983 abcd models in considerable detail. He concluded that predication errors were relatively similar among these models. Gleick (1987) developed a monthly water balance model specifically for climate impact assessment and addressed the advantages of using water balance type models in practice. In the 1990s, more monthly water balance models were developed for studying the impact of climate change on the hydrological balance and for general water resources planning and management (Mimikou et al., 1991, Vandewiele et al., 1992, Guo, 1995, Guo and Yin, 1997, Panagoulia and Dimou, 1997, Xu and Singh, 1998, Xiong and Guo, 1997, Xiong and Guo, 1999).

For the purpose of water resources assessment and study of climate change impacts, a semi-distributed monthly water balance model was proposed and developed in this paper to simulate and predict the hydrological process and water resources in the macro-scale basins of China. 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.