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

Author:

Roshan Ameneh,Ghorbani Khalil,Salarijazi Meysam,Oskouei Ebrahim Asadi

Publisher

Springer Science and Business Media LLC

Reference48 articles.

1. Abbasi, F., Azarakhshi, M., Chapi, K., & Bashiri, M. (2016). Spatial and temporal variations of groundwater level in Qorveh-Dehgolan plain and its relationship with drought. Water and Soil Science, 26(3–2), 143–155. https://water-soil.tabrizu.ac.ir/article_5845.html

2. Achite, M., Katipoğlu, O. M., Jehanzaib, M., Elshaboury, N., Kartal, V., & Ali, S. (2023a). Hydrological drought prediction based on hybrid extreme learning machine: Wadi Mina basin case study. Algeria. Atmosphere, 14(9), 1447.

3. Achite, M., Katipoglu, O. M., Şenocak, S., Elshaboury, N., Bazrafshan, O., & Dalkılıç, H. Y. (2023b). Modeling of meteorological, agricultural, and hydrological droughts in semi-arid environments with various machine learning and discrete wavelet transform. Theoretical and Applied Climatology, 154(1–2), 413–451.

4. Alaminie, A. A., Tilahun, S. A., Legesse, S. A., Zimale, F. A., Tarkegn, G. B., & Jury, M. R. (2021). Evaluation of past and future climate trends under CMIP6 scenarios for the UBNB (Abay) Ethiopia. Water, 13(15), 2110.

5. Aleboali, A., Ghazavi, R., & satatinejad, seyd javad. (2016). Study the effects of drought on groundwater resources using SPI Index (a case study: Kashan plain). Desert Ecosystem Engineering Journal, 5(10), 13–22. https://deej.kashanu.ac.ir/article-1-289-en.html

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