Environmental factors of spatial distribution of soil salinity on flat irrigated terrain

Abstract

Inefficient irrigation and the excessive use of water on agricultural land in the Aral Sea Basin over several decades have led to saline soils. The main objective of this paper is to identify the environmental predictors to model the spatial distribution of soil salinity in a highly irrigated landscape. Soil salinity at farm scale was measured in the topsoil (Total Dissolved Solids, TDS) and down to a depth of 1.5 m by electromagnetic conductivity meter (CMv) over a regular grid covering an area of approximately 15 km 2 in Khorezm Province, Uzbekistan. Six nested samplings within selected grids were conducted to reveal short-distance variation. Apart from widely-used terrain indices and those acquired from remote sensing, data on distance to drainage channels and long-term average groundwater observations were used to account for local parameters possibly influencing soil salinity. Topsoil salinity (TDS) was seen to be highly variable even at short distances (40 m) compared to average bulk soil salinity (CMv). CMv readings were better correlated with factors obtained from remote sensing and distance to drains than TDS. This might be attributable to the fact that topsoil salts are dynamic in nature, and land management practices (e.g. leaching, cultivation, and irrigation) might have contributed considerably to spatial variation. The CMv shows the average amount of salt within a larger soil volume and to greater depth and is less affected by land management than topsoil salinity, which is reflected in the TDS. Most terrain indices showed a low correlation with topsoil and bulk salinity. There was a strong indication that the effects of water management are dominant and tend to outweigh the effects of environmental factors. The very low R 2 for relationship of TDS with environmental factors is evidence that taking TDS samples close to the soil surface is not a good way to assess salinity trends in irrigated land. These findings have important implications for salinity survey methods on flat irrigated terrain: CMv seems to be a more reliable predictor than environmental proxy factors, even if the latter are easier to determine.

Modeling and Mapping of Soil Salinity with Reflectance Spectroscopy and Landsat Data Using Two Quantitative Methods (PLSR and MARS)

“…The reason behind the tendency of the MARS models to overestimate the measured ECe is not clear, but it can probably be attributed to spectral characteristics of the imagery or model generalization [18]. In spite of this tendency, the MARS models are satisfactory and resulted in very good R 2 values for all maps, indicating that the models mostly learned well and had good generalization ability (Figure 8b,d) [73][74][75]. Therefore, the excess accumulation of salts at the soil surface is probably varied due to the distribution of different factors across the study area.…”

“…Therefore, the excess accumulation of salts at the soil surface is probably varied due to the distribution of different factors across the study area. For example, Akramkhanov et al [74] found that the spatial distribution of soil salinity in the Khorezm Province, Uzbekistan, is likely due to soil texture, land management practices, and water table. We found that the spatial distribution of soil salinity was variable over the investigated areas.…”

SPOT-Based Sub-Field Level Monitoring of Vegetation Cover Dynamics: A Case of Irrigated Croplands

“…This has caused elevated groundwater tables and enhanced capillary rise during the crop growing season. Resultant secondary soil salinization can be observed in irrigated croplands throughout the entire region [34]. Adverse impacts of soil and groundwater salinity on crop yields, as well as land abandonment due to LD are increasingly common in the study region.…”

Comparison of Medium Spatial Resolution ENVISAT-MERIS and Terra-MODIS Time Series for Vegetation Decline Analysis: A Case Study in Central Asia

“…The cotton and winter wheat cropping pattern is regulated by the state policy that defines cultivation areas for cotton and yield targets for both crops [36]. Land degradation in the form of secondary soil salinization is particularly widespread in these lowland areas, mainly due to inefficient irrigation and drainage practices which cause a rise in groundwater tables and threaten crop yields [37,38].…”