Clarifying Soil Texture and Salinity Using Local Spatial Statistics (Getis-Ord Gi* and Moran’s I) in Kazakh–Uzbekistan Border Area, Central Asia

The purpose of this paper was to study the spatial characteristics and possible influencing factors of farmland soil texture and salt content in the Syr Darya River Basin. Data on the soil grain size and salt content were collected at 56 sampling sites in the southern part of the Shardara Reservoir and the left bank of the Syr Darya River irrigation area. With the methods of local spatial statistics (Getis-Ord Gi* and Moran’s I), the hotspots of soil salinity and grain size in the study area were revealed, and along with the use of correlation analysis, the possible factors affecting soil salt distribution were discussed. Among the 56 soil sampling sites, sandy loam, loamy loam, and chalky loam accounted for 20%, 50%, and 30%, respectively, and mildly, moderately, and severely saline soils accounted for 80.36%, 14.28%, and 5.36%, respectively. There was statistically significant spatial autocorrelation between sand, silt, and clay content in the soils, but the spatial autocorrelation for salt content was weak. The results show that high and high-cluster areas (hotspots) with statistically significant salt content are mainly distributed in the northwest of the study area and that the hotspot distribution of salt content is mainly affected by topography (altitude), but the effect of soil texture on salt content is not significant. The control of soil salinity should prioritize low-altitude areas, especially in the northwestern region. The results are of great significance for the regulation and control of soil salinity and the sustainable utilization of soil in arid Central Asia

Dimensionality-Transformed Remote Sensing Data Application to Map Soil Salinization at Lowlands of the Syr Darya River

The problem of saving soil resources and their reclamation measures under current climate change conditions attracts the world community’s close attention. It is relevant in the Syr Darya River’s lowlands, where the secondary soil salinization processes have intensified. The demand for robust methods to assess soil salinity is high, and the primary purpose of this study was to develop a quantitative analysis method for soil salinity estimation. We found a correspondence between the sum of salts in a topsoil layer to the Landsat 8 data in the Tasseled cap transformation of the image values. After testing several methods, we built a prediction model. The K-nearest neighborhood (KNN) model with a coefficient of determination equal to 0.96 using selected predictors proved to be the most appropriate for soil salinity assessment. We also performed a quantitative assessment of soil salinity. A significant increase in a salt-affected area and the mean soil sum expressing an intensification of secondary soil salinization from 2018 to 2021 was found. The increasing temperature values, decreasing soil moisture, and agricultural use affect the extension of salt-affected ground areas in the study area. Thus, the soil moisture trend in the Qazaly irrigation zone is negative and declining, with the highest peaks in early spring. The maximum temperature has a mean value of 15.6 °C (minimum = −15.1 °C, maximum = 37.4 °C) with an increasing trend. These parameters are evidence of climate change that also affects soil salinization. PCA transformation of the Landsat-8 satellite images helped to remove redundant spectral information from multiband datasets and map soil salinity more precisely. This approach simultaneously extends mapping opportunities involving visible and invisible bands and results in a smaller dataset

Spatial and Vertical Variations and Heavy Metal Enrichments in Irrigated Soils of the Syr Darya River Watershed, Aral Sea Basin, Kazakhstan

In the Syr Darya River watershed, 225 samples from three different layers in 75 soil profiles were collected from irrigated areas in three different spatial regions (I: n = 29; II: n = 17; III: n = 29), and the spatial and vertical variation characteristics of potentially toxic elements (Cd, Co, Cu, Ni, and Zn) and a metallic element (Mn) were studied. The human health risks and enrichment factors were also evaluated in the Syr Darya River watershed of the Aral Sea Basin in Kazakhstan. There were significant differences in the contents of heavy metals in the different soil layers in the different sampling regions. Based on element variation similarity revealed by hierarchical cluster analysis, the elemental groupings were consistent in the different layers only in region I. For regions II and III, the clustered elemental groups were the same between surface layer A and B, but differed from those in the deep layer C. In sampling region I, the heavy metals in surface soils were significantly correlated with the ones in deep layers, reflecting that they were mainly affected by the elemental composition of parent materials. In region II, the significant correlations only existed for Cu, Mn, and Zn between the surface and deep layers. The similar phenomenon with significant correlation was also observed for heavy metals in sampling region III, except for Cd. Finally, enrichment factor was used to study the mobilization and enrichment of potentially toxic elements. The enrichment factors of Zn, Cu, and Cd in surface layer A that were greater than 1.5 accounted for 1.16%, 6.79%, and 24.36% of sampling region I, respectively. In sampling region II, the enrichment factors of Zn, Cu, Cd, and Co that were greater than 1.5 accounted for 0.03%, 4.76%, 0.54%, and 9.03% of the total area, respectively. In sampling region III, only the enrichment factors of Zn, Cu, and Cd that exceeded 1.5 accounted for 0.24%, 4.90%, and 6.89% of the total area, respectively. Although the contents of the heavy metals were not harmful to human health, the effects of human activities on the heavy metals in the irrigated soils revealed by enrichment factors have been shown in this study area

Mapping of Cornfield Soil Salinity in Arid and Semi-Arid Regions

Soil salinization and their annual increase in volume is not only one of the main problems of arid and subarid regions, but it is becoming global. Studying the problem of salinization and its spatial distribution using operational remote sensing methods is very important for Kazakhstan, where almost half of the agricultural land is exposed to salinization, but it is at the initial stage of development in the use of space technologies of research. The main goal of this study is to conduct a field study of soil salinity in corn fields, one of the most common crops in the arid region of the country, located in the Shaulder irrigated massif, using space-based methods, and to create algorithms for compiling a salinity map based on remote sensing data. For this purpose, firstly, using Sentinel-2 images, the method of separating corn from other dominant crops in the region by creating NDVI dynamics covering all phases of growth of agricultural crops was shown. Then, a regression analysis was performed on soil and vegetation indices calculated using satellite images and data on soil salinity obtained through field studies. As a result of the analysis, the main predictor of deciphering salinized soils was determined. By dividing the predictive image into quartiles, contours of salinized soils were determined and a soil salinity map was created. With the help of the soil salinity map, it was found that, non-saline soils – 2912.2 ha; slightly saline soils – 3288.4 ha, moderately saline soils – 2615.2 ha, and strongly saline soils – 1284.3 ha in the study area

A Study of the Processes of Desertification at the Modern Delta of the Ili River with the Application of Remote Sensing Data

The water regime is the main factor contributing to the formation of landscapes in the river deltas of arid zones, any fluctuations in which lead to a change in the integral hydromorphic landscape. After the construction of the Kapshagai reservoir, the anthropogenic load on the ecosystem of the Ili River delta increased, as a result of which degradation processes, such as drying out and salinization, intensified. In the short term, this phenomenon may lead to the desertification of about 1 million ha of land in the modern river delta. In this regard, the main goal of this study is to look at the processes of desertification in the modern delta of the Ili River, using remote sensing data, which allows for quick identification of the long-term dynamics of degradation processes. For this, the authors used satellite data from Landsat 1–5 MSSS and Landsat 8OLI satellites for 1979 and 2019 and soil analysis data obtained through the ground (field) surveys. Using regression analysis of space and soil data, predictors for interpreting space images were identified and maps of landscape drying and soil salinization were compiled, reflecting the changes that have occurred over the past 40 years. As a result, it was found that in 2019, compared to 1979, the area of landscapes covered with vegetation had decreased by 12% and there was a transformation of hydromorphic landscapes into salt marshes and solonetzes. Over the past 40 years, the volume of non-saline soils has decreased by 41.3% and the volume of saline soils has increased to varying degrees. That is, at present, on the territory of the modern delta, a difficult land improvement situation has developed associated with the cessation of spring and summer floods due to the intensive water use at the Chinese and Kazakh sides