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Evaluation of meteorological drought effects on underground water level fluctuations using data mining methods (case study: semi-deep wells of Golestan province)

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Abstract

In most arid and semi-arid environments, groundwater is one of the precious resources threatened by water table decline and desiccation, thus it must be constantly monitored. Identifying the causes influencing the variations of the subsurface water level, such as meteorological drought, is one approach for monitoring these fluctuations. In the present study, the effect of two meteorological drought indices SPI and SPEI on the fluctuations of the underground water level was evaluated, as was their relationship with the drought index of the subsurface water level (SWI) using multivariate linear regression and M5 decision tree regression. After calculating climatic and hydrological drought indices in a 6-month time window for a long-term statistical period (1989–2018), the semi-deep aquifers of Golestan province, which is located in northern Iran, were considered as a research location for this purpose. The results demonstrated that the effect of meteorological drought does not immediately manifest in the changes of the subsurface water table and the hydrological drought index. By adding the meteorological drought index with a 6-month lag step, the average air temperature, and the total rainfall from the previous 6 months as new variables, the correlation with the SWI index increases, so that in the best-case scenario, the M5 decision tree model provides the best result in predicting the SWI index. The second half of the year yielded a coefficient of determination of 0.92 and an error value of RMSE = 0.27 for the SPEI index. Among the meteorological drought indices, the SPEI index, which is based on precipitation and evapotranspiration, created a stronger link with the SWI index, which highlights the significance of potential evapotranspiration. It is a warning that, as a result of global warming, subsurface water tables in this region may fall in the future.

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Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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Acknowledgements

This manuscript is extracted from an MSc thesis at the Gorgan University Agricultural Sciences and Natural Resources, Gorgan, Iran. The authors are grateful to the University for providing the conditions for conducting this research.

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Authors and Affiliations

  1. Water Resources Engineering, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran

    Ameneh Roshan

  2. Department of Water Engineering, Faculty of Water and Soil Engineering, Gorgan University of Agricultural Sciences and Natural Resource, Gorgan, Iran

    Khalil Ghorbani & Meysam Salarijazi

  3. Atmospheric Science and Meteorological Research Center, Tehran, Iran

    Ebrahim Asadi Oskouei

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  1. Ameneh Roshan
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  2. Khalil Ghorbani
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Contributions

Ameneh Roshan: formal analysis, modeling; Khalil Ghorbani: supervision; validation; writing—original draft, writing—review and editing, authorship, methodology and software; Meysam Salarijazi: investigation, methodology, project administration, resources, software; Ebrahim Asadi Oskouei: visualization.

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Correspondence to Khalil Ghorbani.

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Roshan, A., Ghorbani, K., Salarijazi, M. et al. Evaluation of meteorological drought effects on underground water level fluctuations using data mining methods (case study: semi-deep wells of Golestan province). Environ Monit Assess 196, 236 (2024). https://doi.org/10.1007/s10661-024-12415-6

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