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Identifying and managing risk factors for salt-affected soils: a case study in a semi-arid region in China

  • De Zhou
  • Jianchun Xu
  • Li Wang
  • Zhulu Lin
  • Liming Liu
Article

Abstract

Soil salinization and desalinization are complex processes caused by natural conditions and human-induced risk factors. Conventional salinity risk identification and management methods have limitations in spatial data analysis and often provide an inadequate description of the problem. The objectives of this study were to identify controllable risk factors, to provide response measures, and to design management strategies for salt-affected soils. We proposed to integrate spatial autoregressive (SAR) model, multi-attribute decision making (MADM), and analytic hierarchy process (AHP) for these purposes. Our proposed method was demonstrated through a case study of managing soil salinization in a semi-arid region in China. The results clearly indicated that the SAR model is superior to the OLS model in terms of risk factor identification. These factors include groundwater salinity, paddy area, corn area, aquaculture (i.e., ponds and lakes) area, distance to drainage ditches and irrigation channels, organic fertilizer input, and cropping index, among which the factors related to human land use activities are dominant risk factors that drive the soil salinization processes. We also showed that ecological irrigation and sustainable land use are acceptable strategies for soil salinity management.

Keywords

Soil salinization Risk factor identification Spatial autoregressive model Hierarchical framework Multi-attribute decision making Yinchuan Plain 

Notes

Acknowledgments

Funding for this research was provided by the National Natural Science Fund, China (No. 41301619 and 41130526). We express our sincere thanks to Mr. Yuanpei Zhang, Agricultural Biotechnology Research Center, Ningxia Academy of Agriculture and Forestry of China for the soil and groundwater salinity data and strong support during the study period. The authors want to thank the anonymous reviewers for their invaluable comments that led to a much improved manuscript.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • De Zhou
    • 1
  • Jianchun Xu
    • 1
  • Li Wang
    • 1
  • Zhulu Lin
    • 2
  • Liming Liu
    • 3
  1. 1.Department of Land Resources ManagementZhejiang Gongshang UniversityHangzhouChina
  2. 2.Department of Agricultural and Biosystems EngineeringNorth Dakota State UniversityFargoUSA
  3. 3.Department of Land Resources ManagementChina Agricultural UniversityBeijingChina

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