Satellite-based Estimation Of Surface Soil Moisture In The Three-rivers Headwaters Region

As the largest natural reserve in China,the harsh natural environment of the Three-Rivers Headwaters Region(TRHR)makes its ecosystem community structure simple,resists external interference and has poor recovery ability,Soil moisture plays a significant role in the fields of hydrology,climate,agriculture,and ecology Function,Remote sensing technology can fully and real-time obtain the spatial distribution of soil moisture.This paper mainly uses the combination of apparent thermal inertia method and temperature vegetation drought index method based on MODIS data to retrieve the spatial and temporal distribution characteristics of soil water content and its influencing factors in TRHR,which is of great significance to the development and utilization of local water resources and ecological protection.The result indicated that:(1)In the time series,the inversion result of apparent thermal inertia(ATI)is better than the temperature and drought vegetation index method(TVDI).In space,both inversion effects are better,but in summer in the study area,the temperature and TVDI is a little better than the inversion result of ATI.(2)The inversion results show that from 2003 to 2018,the soil water content in TRHR fluctuated as a whole,and the Mann-Kendall trend test method also found that the overall change was very small.(3)According to the statistics of different types of land use in TRHR,it is found that the value of soil moisture are as follows: water body> forest area> grassland> cultivated land> bare soil,and the spatial water content of the whole south-central and southeast of the study area is relatively high,The soil water content around the water body is relatively high in the northwest area,and the soil water content is relatively low in the north central and northeast of the study area.(4)The GLDAS product data validates the inversion results,indicating that the ATI and TVDI inversion results are reliable in spatial distribution,and in time series,the ATI has a high correlation with the first layer(0-10cm)of GLDAS data.As the depth increases,the correlation is significantly lower.Field measurement results show that the inversion results of the two methods are relatively reliable.(5)From 2003 to 2017,statistical analysis found that the change trend between the NDVI and the ATI is basically the same,and the correlation between the two in the time series reaches 0.5166,taking into account the impact of the water body,Study the relationship between NDVI,ATI and TVDI in the spatial elimination of water bodies,and find that they have a good linear relationship.(6)The change trend between ATI and rainfall in 2003-2017 is basically the same and the correlation between the two reaches 0.5448.The relationship between air temperature and ATI is that there is a certain lag in the influence of air temperature on apparent thermal inertia,that is,the greater the temperature,the smaller the ATI will be in the next year.(7)The 2017 evapotranspiration study in the calculation study area found that there is a good response between evapotranspiration and soil moisture,that is,the greater the soil water content,the greater the evapotranspiration.