This research focuses on determination of irrigation — drainage networks conditions, salinity of irrigated areas in Shavat district of Khorezm region (Uzbekistan) by geospatial analysis and giving recommendations for their elimination. Additionally, obtaining monthly ground truth data from observation wells and interpolate them with IDW interpolation algorithm methods of Geographic Information Systems (GIS) technologies in order to monitoring changes of groundwater level and mineralization in vegetation period of main agricultural crops are highlighted. Besides that, by using remote sensing technologies, the obtained data about the irrigation regime was determined in agricultural areas. As a result of the usage of GIS and RS methods, there have been created thematic maps on analysing salinity of soils, the actual condition of irrigation and collector of networks, actual level and mineralization of groundwater as well as their dynamic changes. On the basis of the obtained results, there have been given recommendations for improving the conditions of ameliorative arable lands on keeping the level of groundwater at a specified depth and cultivation of agricultural crops in periods of water scarcity.

Badland reclamation and low productive farmlands always have been one of the most detrimental effects on the national economy, typically in agricultural sector of Uzbekistan. Nonetheless, such kind of lands has been used extensively for major crops like cotton and winter wheat. However, it is difficult to assessing real productivity of them. Advanced technologies as GIS and RS are vital tool for geospatially analysing and making decisions on this type of fields. This research was carried out for real-time crop monitoring and yield forecasting in case of low productive (3.5 ha) and high productive (8.3 ha) cotton areas of Jarkurgan district (Surkhandarya region, Uzbekistan) based on geospatial analyses of multi-temporal satellite images, condition of groundwater, soil salinity, and ground truth data. For monitoring vegetation phenology of cotton and forecasting its harvest, False Colour, NDVI (Normalized Difference Vegetation Index) and SI (Salinity Index) analyses of areas were carried out by using 6 temporal windows of multi-temporal Sentinel 2 from April through August 2019. Besides, groundwater condition data which was obtained from observation wells these located in massives consists of both cotton fields was analysed by IDW (Inverse Distance Weighting) interpolation algorithm method to determine groundwater’s effect to vegetation development and yield.

No abstract

In the given article the state of Kharshi pumping station, which is considered as one of the huge pumping stations cascade in Central Asia is described through analysing and visualising the geographic information systems (GIS) and remote sensing (RS) methods. As data there were used Shuttle Radar Topographic Mission - SRTM and high-resolution optical images of the area, provided by ESRI. For data processing and visualization, there was used the software of ArcGIS 10.5 by ESRI company and the results were obtained. At the same time the geographical location of pumping stations and water elevating points and the state of water flowing canals were analysed remotely along with the results from the cross-sectional area of cascade were obtained. In assessing, the accuracy of results it was compared with the data based on field search work and the obtained results from the distance showed 86% accuracy.

In the case of increasing water scarcity, determining the water demand of irrigated land is an important process. The water demand for irrigated lands and crops in the Republic of Uzbekistan is realized through nine hydromodular zones, which were developed regarding Bespolov’s methodology in the 1980s. However, in order to determine the water regime in each crop field, it is necessary to create electronic hydromodular zoning maps based on GIS technologies. This study uses GIS technology to create electronic hydromodular zoning maps of the irrigated fields in the Bukhara region of Uzbekistan while considering the mechanical properties of the soils and groundwater levels. Soil mechanical composition of the agricultural land’s geodatabase was created and mapped with three categories of soils: light, medium and heavy. Annually obtained data from observation wells was analysed to determine the distribution of groundwater level by Inverse Distance Weighting (IDW) interpolation method referenced detected coordinate values. The raster calculator function of ArcGIS is used to identify the distribution of hydro module zones by definite criteria of soil and groundwater level. As a result, hydromodular zoning maps of irrigated agricultural lands of the Bukhara region were created for the first time in electronic form.