基于多源遥感数据的黑河流域高分辨率土壤水分同化研究

Based on multi-source data achieved by airborne-, satellite-, and ground-based instruments or observations during the period of Heihe Watershed Allied Telemetry Experimental Research (HiWATER), we adopt land surface model (CoLM, Common Land Model) to conduct a series of soil moisture data assimilation experiments in two intensive observation regions located at the upstream (Baobaohe sub-basin) and middle-stream (Yingke-Daman irrigation region) of Heihe river basin. Firstly, we will develop a multi-sensor soil moisture data assimilation scheme which can simutanlously assimilate multi-sensor observations from airbone-based sensors such as microwave radiometer，imaging spectrometer，thermal imaging camera. Then, we will further to develop a multi-scale soil moistuer data assimilation scheme which can assimilate multi-resolution observations from saterlite-based sensors such as coarse-resolution observatiosn from microwave radiometer sensors aboard on satelite (SMOS, AQUA, FY-3) and fine-resolution data products from MODIS (leaf area index and land surface temperature). Finally, we will integrate Heihe river high-resolution soil moisture data assimilation system which can assimilate mult-source (multi-sensor, multi-resolution, and multi-variable) remote sensing data. This project will promote and expand the application of remote sensing data in watershed ecology-hydrological research , and provide theories and methods for the production of high spatial and temporal resolution of watershed-scale soil moisture products.

以“黑河流域生态—水文过程综合遥感观测联合试验”获得的“星-机-地”多源观测数据为基础，以陆面过程模型CoLM（Common Land Model）为模型骨架，在黑河中游（盈科-大满灌区）和上游（八宝河小流域）分别开展基于机载遥感数据的多传感器协同土壤水分数据同化方法研究和基于星载遥感数据的多尺度土壤水分数据同化方法研究，发展可同化多源遥感数据（多传感器、多变量、多空间分辨率）的土壤水分同化策略，构建黑河流域高分辨率土壤水分数据同化系统，促进和拓展遥感数据在流域生态-水文研究领域的深入应用，为生产全流域高时空分辨率的土壤水分产品提供理论和方法。

以“黑河流域生态—水文过程综合遥感观测联合试验”获得的“星-机-地”多源观测数据为基础，在黑河中游（盈科-大满灌区）和上游（八宝河小流域）分别开展一系列土壤水分数据同化方法研究。主要研究成果包括：（1）发展了基于卡尔曼平滑算法的土壤水分数据同化方法，该方法可以有效的提高观测稀疏情况下的土壤水分同化精度；（2）深入研究了“状态-参数”同步估计的土壤水分数据同化方法。比较了已有“状态-参数”同步估计方法对土壤水分同化结果的影响，在此基础上发展了基于双集合卡尔曼平滑算法的土壤水分数据同化方法，实现了土壤质地参数和土壤水分的同步估计；（3）探索了多源观测联合同化的土壤水分同化方法。实现了土壤水分和土壤温度联合同化、机载L波段微波亮温和MODIS地表温度产品的联合同化、以及AMSR-E亮度温度和MODIS地表温度产品的联合同化。目前已正式发表论文11篇，其中SCI论文5篇，EI论文1篇；培养研究生7名。