标题：Predicting Land Use and Climate Changes Scenarios Impacts on Runoff and Soil Erosion: A Case Study in Hoa Binh Province, Lower Da River Basin, Northwest Vietnam
出版社：Thai Society of Higher Eduction Institutes on Environment
摘要：Land use and climate changes are the key factor for altering runoff and soil erosion, and understanding its impacts play an important role in developing as sustainable program to preserve watershed. However, there is lack of detailed studies on land use and climate change impact on hydrology and soil erosion for the sustainable water management in Vietnam. Therefore, the study aims to predict future runoff and sediment yield, and soil loss in Hoa Binh province, Lower Da river basin, Northwest Vietnam using Soil and Water Assessment Tool (SWAT) model. Two projected land use changes (LU,: economic scenarios and LU,: conservation scenarios) were simulated based on the Vietnam government's restrictions for land use change. Future climate projections were derived from three Regional Climate Models (RCMs). In the study, A, and B, scenarios were selected for the study because scenario A, assumes a very heterogeneous future world, with continuously increasing population and regionally oriented economic development, whereas, scenario B, is an intermediate level of economic development. Results indicated that SWAT model was a powerful tool for simulating the impacts of land use and climate change on hydrology and sediment yield. The results show that in future land use and climate change are to be responsible for a 0.35 to 1.07% increase in runoff and 0.86 to 6.96 % increase in sediment yield, respectively. Moreover, it can be seen that the areas of moderate and very high soil erosion intensity mainly occupied in Hoa Binh province ranges from 23 to 52 ton/ha*yr. In conclusion, the results obtained in this study can provide useful information for land use planning and management as well as soil and water conservation in the Hoa Binh province, Lower Da river basin, Northwest Vietnam.
关键词：Climate Change; Land Use Change; Remote Sensing; Runofif; Sediment Yield; SWAT model.
