A Semi-Distributed Monthly Water Balance Model and its Application in a Climate Change Impact Study in the Middle and Lower Yellow River Basin

Abstract

Human activities and climatic change have greatly impacted hydrological cycles and water resources planning in the Yellow River basin. In order to assess these impacts, a semi-distributed monthly water balance model was proposed and developed to simulate and predict the hydrological processes in the middle and lower Yellow River basin. GIS techniques were used as a tool to analyze topography, river networks, land-use, human activities, vegetation, and soil characteristics. The model parameters were calibrated in 35 gauged sub-basins in the middle Yellow River, and then the relationships between the model parameters and the basin physical characteristics were established. A parameterization scheme was developed in which the model parameters were estimated for each grid element by regression and optimization methods. Based on the different outputs of general circulation models (GCMs) and regional climate models (RCMs), the sensitivities to global warming of hydrology and water resources for the Yellow River basin were studied. The proposed models are capable of producing both the magnitude and timing of runoff and water resources conditions. The runoffs are found to be very sensitive to temperature increases and rainfall decreases. Results of the study also indicated that runoff is more sensitive to variation in precipitation than to increase in temperature. The additional uncertainty of climate change has posed a challenge to the existing water resources management practices, and the integration of water resources management will be necessary to enhance the water use efficiency in the Yellow River basin.