Detecting Irrigation-Induced Soil Salinization Using Remote Sensing Indicators: A Case Study of Arkadag City, Turkmenistan

Soil salinization is one of the main forms of land degradation in dry regions. It occurs when soluble salts accumulate in the soil and begin to affect plant growth, soil fertility, and agricultural productivity. This process is common in arid and semi-arid areas because low rainfall and high evaporation make it difficult for salts to be naturally removed from the soil profile. In Turkmenistan, salinization is especially important because the country has a dry climate and a large share of agricultural activity takes place under conditions where salt accumulation can develop naturally over time. In areas such as the Ahal region and Arkadag city, high evaporation, limited precipitation, flat terrain, and local soil characteristics create favorable conditions for salinity development. Therefore, soil salinization in Turkmenistan is closely connected to the country’s natural environmental conditions and remains an important challenge for sustainable land and agricultural management.

This article focuses on the detection of soil salinization in Arkadag city, located in the Ahal region of Turkmenistan, using remote sensing indicators and GIS-based spatial analysis. The study applies the Normalized Difference Vegetation Index (NDVI) to assess vegetation health and a drought index to evaluate environmental stress conditions. By combining these two indicators, the research examines how vegetation condition changes across the study area and whether these changes correspond to areas of higher environmental stress.

The methodology is based on satellite image processing, spatial zoning, and statistical analysis. The study area was divided into three representative zones to compare different levels of vegetation condition and environmental stress. Pearson’s correlation coefficient was also used to measure the relationship between NDVI and drought index values. This approach made it possible to move beyond visual interpretation and support the findings with quantitative analysis.

The results show clear spatial differences within the study area. Areas with lower NDVI values generally correspond to areas with higher drought index values, meaning that weaker vegetation is closely linked with stronger environmental stress. The correlation analysis confirmed this relationship, showing a very strong negative correlation between NDVI and the drought index, with a coefficient of r = -0.97.

The zonal analysis also showed that Zone 2 had the strongest signs of degradation, while Zone 3 showed healthier vegetation conditions and Zone 1 represented an intermediate condition.

Overall, the article demonstrates that remote sensing can be an effective tool for identifying salinity-affected areas at a local scale. Although the study does not directly measure soil salinity through field sampling, the combination of NDVI, drought index mapping, spatial zoning, and correlation analysis provides strong evidence of salinity-related vegetation stress in Arkadag city. The findings highlight the importance of using GIS and satellite-based methods for environmental monitoring in Turkmenistan and support the need for further research that combines remote sensing with field-based soil analysis.

All article is here.

Menli Atayeva,

Masters student at the Kazakh-German University,

Educational program in Integrated Water Resources Management,

Faculty of Economics and Entrepreneurship, Almaty, Kazakhstan.