Utilization of satellite data on meteorological and land surface characteristics in the model of water and heat exchange for vast agricultural region territories&#160;
Authors: Muzylev Eugene , Startseva Zoya , Volkova Elena , Vasilenko Eugene 
Published: March 2021

&lt;p&gt;The method is developed to calculate soil water content W, evapotranspiration Ev and other water and heat regime (WHR) characteristics of agricultural regions for vegetation season (VS). The base of the method is the physical-mathematical model of vertical water and heat transfer in the &amp;#8220;Soil-Vegetation-Atmosphere&amp;#8221; system (SVAT), suitable for utilizing satellite-retrieved estimates of vegetation and meteorological characteristics such as vegetation index NDVI, emissivity E, vegetation cover fraction B, leaf area index LAI, precipitation, and land surface temperature LST. These estimates were built under thematic processing satellite data obtained by radiometers AVHRR/NOAA, SEVIRI/Meteosat-10, -11, -8; MSU-MR/Meteor-M No 2 in visible and IR ranges. Soil and vegetation characteristics were the model parameters and meteorological characteristics were considered to be the input variables.&lt;/p&gt;&lt;p&gt;The case study was carried out for forest-steppe territory of 227,300 km&lt;sup&gt;2&lt;/sup&gt; located in the Central Black Earth Region of European Russia, for steppe black earth Rostov region of 100,000 km&lt;sup&gt;2&lt;/sup&gt;, and for arid steppe territory of the Saratov and Volgograd Trans-Volga region of 66,600 km&lt;sup&gt;2&lt;/sup&gt; for VS of 2017-2018.&lt;/p&gt;&lt;p&gt;Estimates of daily, ten-day and monthly precipitation sums were carried out using the Multi Threshold Method for detecting cloudiness, identifying its types, allocating precipitation zones and determining rainfall intensity maximum. The key point of the method is the transition from assessing the rainfall intensity to estimating its daily sums.Comparing calculated daily, ten-day and monthly rainfall sums with each other for all sensors and with similar ground-based data showed the coincidence of the satellite-detected and actual precipitation zones in 75-85% of cases for each radiometer.&lt;/p&gt;&lt;p&gt;Satellite LST estimates were retrieved by the Generalized Split-Window method using the regression equations for the satellite-measured radiation temperature. Comparison of these estimates with each other for all radiometers, with the model calculation results and with ground-measured air temperature values for named VS showed their differences to be within acceptable limits.&lt;/p&gt;&lt;p&gt;Because of the different climatic conditions in the study areas, the empirical formulae to calculate B and LAI were analyzed and their detailed estimates were made, the errors of which were about 15 and 20%, respectively.&lt;/p&gt;&lt;p&gt;The possibility to use soil surface moisture estimates obtained from the scatterometer ASCAT/MetOp data in the microwave range for modeling is shown (to select initial conditions when calculating W and to assess evaporation from soil surface).&lt;/p&gt;&lt;p&gt;To calculate W, Ev and other WHR components the developed procedures to assimilate satellite-retrieved B, LAI, precipitation and LST estimates in the model were adapted to the territories under study. These procedures included replacing ground-based estimates of these values by their satellite-retrieved estimates in all computational grid nodes at each time step. The efficiency of these procedures was confirmed by comparing modeled and measured values of W and Ev. The final modeling results are distributions of W, Ev and other WHR components over the areas of interest. Estimation errors for W (10-15%) and Ev (20-25%) (even for the arid Trans-Volga region) are acceptable values.&lt;/p&gt;&lt;p&gt;As a conclusion, the developed method can be used to assess water resource components for vast agricultural regions.&lt;/p&gt;