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Modelling groundwater-dependent vegetation index using Entropy theory

Author

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  • Zhang, Gengxi
  • Su, Xiaoling
  • Singh, Vijay P.

Abstract

An ecosystem is vulnerable to the scarcity of water resources and sparse vegetation cover in arid regions. Groundwater plays an important role in maintaining ecological environment and strongly impacts the ecosystem through influencing vegetation structure and species distribution. It is therefore important to clearly understand the relationship between vegetation patterns and groundwater depth(GWD). In this paper, Tsallis entropy theory was applied to derive a functional relationship between GWD and vegetation distribution. The theory was tested using observed data from arid regions in northwestern China. Results showed that higher vegetation coverage exist at places of shallow GWD. The values of NDVI gradually increase with increasing GWD until reaching a maximum at the optimum depth, after which they decrease with increasing groundwater depth when GWD is less than approximately 10 m. Beyond that depth, a low level of vegetation coverage is maintained. The correlation coefficients between measured and simulated values of NDVI were above 0.9 (p < 0.01) in the Ejina, Qaidam and Hailiutu basins. The theory is applicable to different regions and vegetation types and may improve our ability to sustainably manage land and groundwater resources in arid regions, especially where the vegetation is groundwater-dependent.

Suggested Citation

  • Zhang, Gengxi & Su, Xiaoling & Singh, Vijay P., 2020. "Modelling groundwater-dependent vegetation index using Entropy theory," Ecological Modelling, Elsevier, vol. 416(C).
    • Handle: RePEc:eee:ecomod:v:416:y:2020:i:c:s0304380019304247
    DOI: 10.1016/j.ecolmodel.2019.108916
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    References listed on IDEAS

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    1. Sohoulande Djebou, Dagbegnon C. & Singh, Vijay P., 2015. "Retrieving vegetation growth patterns from soil moisture, precipitation and temperature using maximum entropy," Ecological Modelling, Elsevier, vol. 309, pages 10-21.
    2. Singh, Vijay P. & Cui, Huijuan, 2015. "Modeling sediment concentration in debris flow by Tsallis entropy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 420(C), pages 49-58.
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    Cited by:

    1. Wenjia Zhang & Xiaoya Deng & Yi Xiao & Ji Zhang & Cai Ren & Wen Lu & Aihua Long, 2023. "Study on the Suitable Ecological Groundwater Depth and the Suitable Well–Canal Combined Irrigation Ratio in the Weigan River Irrigation District," Sustainability, MDPI, vol. 15(20), pages 1-22, October.
    2. Chen, Mingli & Wu, Zijian & Fu, Xinxi & Ouyang, Linnan & Wu, Xiaofu, 2021. "Thermodynamic analysis of an ecologically restored plant community:Number of species," Ecological Modelling, Elsevier, vol. 455(C).

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