Inversion Of Deep Soil Moisture Based On TVDI Model And Soil Moisture Estimation Model

As a key element of crop growth and development,soil moisture can only be absorbed by crop roots and then utilized by crops in the soil.Corresponding natural rainfall and artificial watering can only exert its greatest effect if it is transformed into soil.In arid and semi-arid regions,when rainfall is insufficient,soil moisture is too low,and scientific and rational irrigation is lacking,agricultural crops will be reduced in production due to the inability of soil moisture to meet their normal water requirements.Timely and accurate monitoring and understanding of soil moisture are of great practical value.The traditional soil moisture monitoring is to directly use the precipitation,soil,temperature,etc.,or meteorological data provided by meteorological stations,and the mathematical model is used to estimate the soil moisture content.However,the traditional methods for monitoring soil moisture content are lagging and unable to perform dynamics.monitor.Although remote sensing image data can be used to understand a wide range of surface soil moisture conditions in real time,the monitoring of deep soil moisture is not accurate.If the surface soil moisture can be obtained through remote sensing image inversion,and then the mathematical model can be used to estimate the deep soil moisture,the soil moisture content can be dynamically monitored in time and space,which will help timely formulate and determine the soil moisture content.Adjust the water plan.This study used Rencun Township in Taigu County as the study area,combined with Landsat 8 OLI remote sensing image data,firstly used the temperature vegetation drought index model to detect the soil dryness and wetness in Rencun Township from May to October,and analyzed its temporal and spatial distribution patterns;Using the relationship between the obtained temperature vegetation drought index and the measured soil moisture content of 0-30 cm in the surface layer of Rencun Township,the distribution of soil moisture in each layer of 0-30 cm in the surface layer of Rencun Town was obtained,and finally the soil moisture was estimated in combination with Biswas.The model estimates the depth of soil water storage in the 60 to 100 cm depth of the village.Research indicates:1 In 0-30 cm soil layers,the relationship between temperature vegetation drought index value and soil water content of 10-20 cm is the highest,indicating that the temperature vegetation drought index value is more accurate in the soil water content of 10-20 cm.2 The soil moisture content of each soil layer at 20-50 cm in the surface layer and the soil moisture content of 20-160 cm soil layer were significantly correlated at the 0.05 level,indicating that the deep soil moisture can be estimated based on the surface soil moisture.3 According to the remote sensing image inversion of surface soil moisture data,the relative error between the deep soil water storage and the measured data estimated by Biswas model is less than 20%,which indicates that it is feasible to estimate the deep soil water storage using remote sensing inversion data.