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Spatial characteristics and critical groundwater depth of soil salinization in arid artesian irrigation area of northwest China

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  • Chang, Cui
  • Yang, Guiyu
  • Li, Shuoyang
  • Wang, Hao
  • Song, Yaomingqi

Abstract

Soil salinization readily occurs in artesian irrigation areas within arid regions due to prolonged irrigation, leading to diminished soil productivity and consequential impacts on regional food security and ecological stability. The present study focuses on the northern area of Qingtongxia artesian irrigation district in Ningxia, the spatial characteristics of soil salinity were investigated using the three-dimensional inverse distance weight interpolation, and the types of soil salt accumulation were determined. Furthermore, the high probability partition of each type was determined by the Indicator Kriging method. Additionally, the path analysis method was employed to determine the critical groundwater depth, which is a significant factor influencing the occurrence and development of soil salinization. The results indicate the salt accumulation types in the soil profile are divided into surface accumulation (SA) type, middle accumulation (MA) type, and bottom accumulation (BA) type. The depth to groundwater is a crucial influential factor, with critical depths prior to spring irrigation identified for each type: 2.1 m for the SA type and 1.8 m for both MA and BA types. To mitigate salinization deterioration, it is essential that the depth to groundwater in the distribution area of each type exceeds the corresponding critical depth.

Suggested Citation

  • Chang, Cui & Yang, Guiyu & Li, Shuoyang & Wang, Hao & Song, Yaomingqi, 2025. "Spatial characteristics and critical groundwater depth of soil salinization in arid artesian irrigation area of northwest China," Agricultural Water Management, Elsevier, vol. 307(C).
    • Handle: RePEc:eee:agiwat:v:307:y:2025:i:c:s0378377424005328
    DOI: 10.1016/j.agwat.2024.109196
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    References listed on IDEAS

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    1. Gong, Xuewen & Qiu, Rangjian & Sun, Jingsheng & Ge, Jiankun & Li, Yanbin & Wang, Shunsheng, 2020. "Evapotranspiration and crop coefficient of tomato grown in a solar greenhouse under full and deficit irrigation," Agricultural Water Management, Elsevier, vol. 235(C).
    2. Ramos, T.B. & Simionesei, L. & Jauch, E. & Almeida, C. & Neves, R., 2017. "Modelling soil water and maize growth dynamics influenced by shallow groundwater conditions in the Sorraia Valley region, Portugal," Agricultural Water Management, Elsevier, vol. 185(C), pages 27-42.
    3. Qianqian Liu & Gulimire Hanati & Sulitan Danierhan & Guangming Liu & Yin Zhang & Zhiping Zhang, 2020. "Identifying Seasonal Accumulation of Soil Salinity with Three-Dimensional Mapping—A Case Study in Cold and Semiarid Irrigated Fields," Sustainability, MDPI, vol. 12(16), pages 1-14, August.
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