DROUGHT MONITORING AND DROUGHT PREDICTION IN CHINA USING REMOTE SENSING, LAND SURFACE MODELS (LSM) AND DATA ASSIMILATION: PRELIMINARY RESULTS OF THE LOESS PLATEAU FIELD EXPERIMENT IN 2005 (LOPEX05)

摘要

Drought disasters have often caused great hunger, social instability, large scale migration of the population and the distinction of civilizations in the history. The conflict between supply and demand of water resources constitutes the biggest problem for food security of a huge population in China and drought has become a key factor constraining China's economic development. The Dragon project "drought monitoring and drought prediction" will be used to develop a system to monitor and generate predictions of the soil moisture conditions in the root zone. The methodology that will be employed is based on the direct assimilation of satellite observation in a land surface modeling framework. The advantage of this methodology is that physically based methods can be used as compared to (semi-) empirical direct-retrieval algorithms. Within the framework of this project a field campaign was held in the summer of 2005 near the city of Pingliang in Gansu province, China. The ground truth data set collected during this experiment consists of continuous time series of land surface radiation, water and heat fluxes and an extensive set of land surface parameter observations, such as soil moisture, Vegetation Water Content (VWC) and Leaf Area Index (LAI). In conjunction with the ground observations a series of EnviSat AATSR, ASAR and MERIS scenes have been requested. This data set will be used to develop the drought monitoring and forecasting systems. In this paper, some of the preliminary results from the ASAR and MERIS data sets are presented.