Using satellite data in the Land Surface Model to estimate water availability of arid agricultural region

Eugene Muzylev,Eugene Vasilenko,Elena Volkova,Zoya Startseva

doi:10.5194/egusphere-egu2020-13037

Abstract

&lt;p&gt;The water availability of agricultural arid regions can be assessed at presence using the physical-mathematical model of water and heat exchange between land surface and atmosphere LSM (Land Surface Model) adapted to satellite-derived estimates of meteorological and vegetation characteristics. The LSM is designed to calculate soil water content W, evapotranspiration Ev, vertical heat fluxes and other water and heat regime elements. Soil and vegetation characteristics were used in the LSM as parameters and meteorological characteristics were utilized as input variables.&lt;/p&gt;&lt;p&gt;The case study was carried out for the territory of the Saratov and Volgograd Trans-Volga region (the left-bank part of the Saratov and Volgograd regions) of 66600 km&lt;sup&gt;2&lt;/sup&gt; for the vegetation seasons 2016-2018.&lt;/p&gt;&lt;p&gt;The satellite measurement data from radiometers AVHRR/NOAA, SEVIRI/Meteosat-10, -11, -8, and MSU-MR/Meteor-M No. 2 in visible and IR ranges were thematic processed to built estimates of vegetation index NDVI, emissivity E, vegetation cover fraction B, leaf index LAI, land surface temperature LST and precipitation.&lt;/p&gt;&lt;p&gt;LAI and B estimates were obtained using empirical dependencies on NDVI. The adequacy of the LAI and B estimates obtained from all sensor data was verified when comparing the LAI time behavior built for named vegetation seasons. Errors of determining B and LAI were 15 and 20%, respectively.&lt;/p&gt;&lt;p&gt;Satellite-derived estimates of daily, decadal and monthly precipitation sums for each pixel were obtained using the Multi Threshold Method (MTM) for detecting clouds, identifying its types allocating precipitation zones and determining their maximum intensity. The MTM is based on the developed algorithm of the transition from the assessment of precipitation intensity to the assessment of their daily amounts. Testing of the method was carried out when comparing these amounts with observed at meteorological stations. The probability of satellite-detected precipitation zones corresponded to the actual ones was ~ 80% for all radiometers.&lt;/p&gt;&lt;p&gt;Based on the MTM, computational algorithm to evaluate the LST was developed and verified on the study region data. Comparison of ground-measured and satellite-derived LST showed that the latter estimates for the overwhelming number of observation turned out to be comparable in accuracy with each other and with the ground-based data.&lt;/p&gt;&lt;p&gt;Calculations of water and heat regime elements (being the final products of the simulation) were carried out when replacing ground-based estimates of precipitation, LST, LAI and B in the LSM by satellite-derived ones at each time step in all nodes of the computational grid. The efficiency of such replacement procedures was confirmed by comparing measured and calculated values of W and Ev (the difference between them didn&amp;#8217;t exceed 15% for W and 25% for Ev).&lt;/p&gt;&lt;p&gt;The possibility of using soil surface moisture estimates obtained from all-weather measurements by the scatterometer ASCAT/MetOp in the microwave range when simulating soil water content was also revealed. These estimates may use to set initial conditions for the vertical soil water transfer equation, as well as for calculating evaporation from the soil surface and the subsequent formation of the upper boundary condition for this equation.&lt;/p&gt;&lt;p&gt;As a summary, the described approach can be considered as a method for assessing the water availability for agricultural arid region.&lt;/p&gt;

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