Assessment of agricultural land salinization via soil analysis and remote sensing data: Case study in Pavlodar region, Kazakhstan

• Published in: Soil and water research Vol. 19; no. 2; pp. 111 - 121
• Main Authors: Rakhmanov, Dauren, Šarapatka, Bořivoj, Alibekova, Kamilla, Černohorský, Jan, Hekera, Petr, Smanov, Zhassulan
• Format: Journal Article
• Language: English
• Published: Prague Czech Academy of Agricultural Sciences (CAAS) 01.01.2024; Czech Academy of Agricultural Sciences
• Subjects: Agricultural ecosystems; Agricultural land; Agricultural research; arid regions; Arid zones; Cation exchange; Cation exchanging; Climatic conditions; Crop growth; Crop yield; Data analysis; Flood irrigation; Indicators; Irrigation; Landsat; landsat image; Landsat satellites; Normalized difference vegetative index; Remote sensing; Saline soils; Salinity; Salinity effects; Salinization; Semi arid areas; Semiarid zones; Soil analysis; Soil degradation; Soil properties; Soil salinity; Sprinkler irrigation; Vegetation; Kazakhstan
• DOI: 10.17221/5/2024-SWR
• ISSN: 1801-5395

Soil salinization is one of the most widespread soil degradation processes, especially in arid and semi-arid regions. In such climatic conditions, soluble salts accumulate in the soil, leading to deterioration in soil properties and ultimately reduced crop yield. The purpose of this study was to analyse the relationship between the level of soil salinity and the main spectral indicators obtained from Landsat satellite data. The studied area was the Maisky district, which is located in the southeastern part of the Pavlodar region of Kazakhstan. The variants of the research were agricultural lands using sprinkler irrigation and flood irrigation, as well as sites without irrigation. To analyse the relationships, we used the normalized difference vegetation index (NDVI), salinity indices (SI) and soil indices such as SI 1, SI 2, SI 3, SI 4, normalized difference salinity index (NDSI), soil adjusted vegetation index (SAVI), and brightness index (BI). The normalized difference salinity index (R-NIR)/(R + NIR), using a quadratic statistical relationship, showed the best correlation with the laboratory data. The vegetation index NDVI showed the weakest correlation due to dryness or poor crop growth. As a result of the lack of clear control over irrigation and agrotechnical measures, the indicators of cation exchange capacity in irrigated plots using the flooding method were higher than in other irrigation methods. During irrigation, it is necessary to ensure clear rules, according to which the supplied water and fertilizers will have a positive effect on the soil and the entire agroecosystem. The methods used in this research can be useful in mapping and studying saline soils using satellite data in natural and climatic conditions of arid and semi-arid regions.