拟利用土壤水分主动被动卫星(SMAP)L波段(空间分辨率：被动36km/主被动融合9km) 微波亮度温度资料，对以往因忽视低频微波信号穿透土壤层较深、粗略估算土壤有效温度导致土壤湿度反演精度低的情况，基于我们新的土壤有效温度模型 (Lv Soil Effective Temperature Scheme)构建土壤有效温度与发射率耦合算法；并利用黄河源区土壤湿度观测网络验证资料，借助地面微波辐射计(ELBARA -II) 与SMAP卫星的同步观测，发展新的SMAP卫星土壤湿度反演模型并提高其产品精度，获得黄河源区高精度(0.04m3/m3)连续时间序列土壤湿度产品；分析引入土壤有效温度-发射率耦合机制对陆面模式同化微波亮度温度过程的影响。通过项目研究提交的任务，以期推动高原尺度陆-气能量水分交换过程研究。

In this research, we’re going to develop a new microwave remote sensing soil moisture retrieval model base on the Soil Moisture Active Passive (SMAP) satellite microwave observations and our soil effective temperature scheme (Lv soil effective temperature scheme) to estimate high accuracy (RMS error less than 0.04 m3/m3) soil moisture product by coupling soil effective temperature and soil emissivity over the source region of the Yellow River (SRYR). SMAP is the latest generation for microwave soil moisture detecting project which will provide soil moisture both in 36km (passive) and 9km (active/passive combined). SMAP works on L-band (1.4GHz) which is strongly affected by its sampling depth. Meanwhile the Lv soil effective temperature scheme is proved to identify the sampling depth through considering soil moisture/soil temperature/texture in its analytic expression. With Maqu soil moisture detecting networks in SRYR and the brightness temperature observations collected by ELBARA II, the soil effective temperature-emissivity coupled soil moisture retrieving model will be tested to improve SMAP’s soil moisture product and the current microwave transfer model. The improved soil moisture produce will offer a better understanding of the interaction between land surface and atmosphere at the Qinghai-Tibetan Plateau scale.