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Remote Sensing Inversion of Salinization Degree Distribution and Analysis of Its Influencing Factors in an Arid Irrigated District

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  • Shuoyang Li

    (State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin 300072, China
    State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, Beijing 100038, China
    China Institute of Water Resources and Hydropower Research, Beijing 100038, China)

  • Guiyu Yang

    (State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, Beijing 100038, China
    China Institute of Water Resources and Hydropower Research, Beijing 100038, China)

  • Cui Chang

    (State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, Beijing 100038, China
    China Institute of Water Resources and Hydropower Research, Beijing 100038, China
    School of Water Resources and Environment, China University of Geosciences (Beijing), Beijing 100083, China)

  • Hao Wang

    (State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, Beijing 100038, China
    China Institute of Water Resources and Hydropower Research, Beijing 100038, China)

  • Hongling Zhang

    (Ningxia Institute of Water Resources Research, Yinchuan 750021, China)

  • Na Zhang

    (Ningxia Institute of Water Resources Research, Yinchuan 750021, China)

  • Zhigong Peng

    (State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, Beijing 100038, China
    China Institute of Water Resources and Hydropower Research, Beijing 100038, China)

  • Yaomingqi Song

    (State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, Beijing 100038, China
    China Institute of Water Resources and Hydropower Research, Beijing 100038, China
    School of Water Resources and Environment, China University of Geosciences (Beijing), Beijing 100083, China)

Abstract

Salinization is one of the significant factors that impede agricultural development, threaten ecological security, and hinder sustainable development. This study successfully achieved precise and expeditious identification of salinization grades by integrating optical satellite data with other geospatial information. It effectively enhanced the accuracy of salinization inversion, with a recognition rate of 85.34%. The salinization in the Hexi irrigation area showed a decreasing trend from 2014 to 2023, with no and slight salinization increasing by 8.37% and 3.54%, while moderate and severe salinization decreased by 17.23% and 19.11%. This was mainly due to changes in hydrological processes, shown by a 5.6% and 6.8% decrease in water diversion and drainage, and a roughly 0.45 m rise in groundwater depth. Through the analysis of the relationship between salinization and groundwater depth, it is found that the further north the area is, the more severe the salinization. And the shallower the groundwater depth, the more difficult it is to maintain the groundwater depth at the threshold to prevent salinization. It is primarily due to obstructed drainage in the northern region, leading to salinization. Through exploring the reasons for drainage obstruction, the causes of salinization in different regions were identified. This research aims to provide some reference for the investigation, regulation, and management of regional salinization.

Suggested Citation

  • Shuoyang Li & Guiyu Yang & Cui Chang & Hao Wang & Hongling Zhang & Na Zhang & Zhigong Peng & Yaomingqi Song, 2024. "Remote Sensing Inversion of Salinization Degree Distribution and Analysis of Its Influencing Factors in an Arid Irrigated District," Land, MDPI, vol. 13(4), pages 1-18, March.
  • Handle: RePEc:gam:jlands:v:13:y:2024:i:4:p:422-:d:1364219
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    References listed on IDEAS

    as
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    2. Hongfang Li & Jian Wang & Hu Liu & Zhanmin Wei & Henglu Miao, 2022. "Quantitative Analysis of Temporal and Spatial Variations of Soil Salinization and Groundwater Depth along the Yellow River Saline–Alkali Land," Sustainability, MDPI, vol. 14(12), pages 1-13, June.
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    6. Jiang, Donglin & Ao, Chang & Bailey, Ryan T. & Zeng, Wenzhi & Huang, Jiesheng, 2022. "Simulation of water and salt transport in the Kaidu River Irrigation District using the modified SWAT-Salt," Agricultural Water Management, Elsevier, vol. 272(C).
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