基于遥感观测和同化技术的区域陆地水循环模拟研究

The terrestrial water cycle has been was altered by the global change. It is primary important to know when, where and what extent of the essential hydrological variables were changed.In this project, we proposal to simulate the terrestrial water cycle during the past 30 years over Northern China. Four numerical experiments will be conducted at first. In the first experiment, default land use and land cover (LULC) parameters will be adopted, while in the second experiment, the time series of remote sensing data will be employed to represent 'real' LULC changes in the VIC model.By comparing the results of experiment 1 and 2 against in situ observation, the advantages of using dynamic parameters derived from remote sensing can be identified.In order to solve the scale mismatch problem resulting from using the "point-measured" parameters in big grid simulation, we proposal to develop a remote-sensing-data-based parameters optimization method. With using the method the soil parameters in VIC will be optimized and used in experiment 4. By comparing the results of experiment 4 and experiment 3 ,in which default soil parmeters will be used, agaist station measurements, we can validate the parameter optimization method. We proposal to develop a land data assimilation system which merging multi-platform and multi-source observation into VIC, to reproduce the water cycle variables accuratly. The approval of this proposal will result in a cross-discipline project, which coving the fields of remote sensing, hydrology and global change. The conduction of this project will facillate the global change research, and will benefit to the research community and society.

全球变化对陆地水循环产生了不可逆转的影响，为了增强应对全球变化的能力，必须研究全球变化对区域水循环的影响机制，准确、定量地分析水循环关键变量（如地表径流、地下水位、土壤含水量和蒸散量）的时空分布特征。本项目以中国北方区域为研究对象，以VIC模型为例，围绕水文模型参数的时空变异性以及陆地水循环关键变量的演变机制等关键科学问题开展研究；利用时序遥感观测数据，诊断分析了现有模型的"静态"参数问题；利用多尺度多层次遥感资料，发展基于遥感数据的水文模型参数"面源"率定/优化方法；建立陆面数据同化系统，将多源对地观测资料和陆面水文模型有机融合，实现区域陆地水循环关键变量的精确模拟，重现过去30年我国北方的陆地水循环过程。本项目在遥感、水文学和全球变化的交叉研究领域进行探讨，有望在水文模型参数优化方面取得创新性成果，应用于全球变化下的水循环研究，具有重要的现实意义和科学价值。

全球变化对陆地水循环产生了不可逆转的影响，为了增强应对全球变化的能力，必须研究全球变化对区域水循环的影响机制，准确、定量地分析水循环关键变量（如降水、土壤水、地表径流等）的时空分布特征。本项目以青藏高原及其下游的湄公河流域为研究对象，以CoLM和GBHM模型为例，围绕陆地水循环关键变量的时空分布特征和演变机制等关键科学问题开展研究；综合开展了多套大气驱动数据和水循环关键变量遥感资料的交叉比较和不确定性分析，为水循环模拟和数据同化提供了关键信息；建立和发展了陆面数据同化系统，改进了地表状态的模拟精度；利用多源遥感资料，发展了基于遥感数据的水文模型，并开展参数率定和比较分析；利用所研发的的水文模型，开展了气候变化对湄公河流域水循环过程的影响评价研究，分析了该流域未来洪水风险的时空变化特征和影响机制。研究表明综合利用多源遥感数据、陆面水文模型和数据同化技术，可以提高水文模型的空间代表性，提高模式在资料匮乏区域的模拟精度，进而提高对全球变化背景下区域水循环特征和机理的科学理解。