It is established that the Aral Sea problem, which is due to the negative impact of human activity over time, has led to environmental degradation in the Aral Sea region and changes in the soil cover. The extent of this ecological problem can be detected using geoinformation technologies and remote sensing methods. In this study, the maximum likelihood classification algorithm was applied in the presentation of Landsat images to detect changes in the soil cover based on multispectral satellite data obtained from Landsat 7 and Landsat 8 for 2008 and 2018, respectively. The resulting land-use maps indicate a significant increase in saline land from 18% to 22% during the period under study. These land transformations pose a severe threat to the land resources of the area. Consequently, proper management of the land resources is required to preserve them and to ensure that they continue to play their part in the socio-economic development of the region.

The article deals with the issue of hydromodule zoning of agricultural land. The negative impact of the environmental factors of the Aral Sea requires more work on the efficient use of agricultural land in the region. The focus of the research is on the efficient use of agricultural land based on the optimal placement of Agricultural crops. Optimizing the use of agricultural land by dividing areas into taxonomic units is considered to be one of the effective methods. In this study, the land of P. Seytov’s massive, Chimboy district of the Republic of Karakalpakstan, within the Republic of Uzbekistan, was selected as a study area. Hydromodule zoning of the cultivated areas of the research object was done using GIS technologies. In this, data on soil types and mechanical composition of the object, groundwater, and irrigation methods were used. Overlay, raster calculation, and raster classification methods were used using ArcGIS 10.6 software. As a result, a hydromodule map of the research object was created. Based on the created hydromodule map, the scenario of placement of agricultural crops based on 2 different options was developed and water consumption was analyzed.