Evaluation of drought events in various climatic conditions using data-driven models and a reliability-based probabilistic model
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DOI: 10.1007/s11069-021-05019-7
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References listed on IDEAS
- Granata, Francesco, 2019. "Evapotranspiration evaluation models based on machine learning algorithms—A comparative study," Agricultural Water Management, Elsevier, vol. 217(C), pages 303-315.
- Maroufpoor, Saman & Shiri, Jalal & Maroufpoor, Eisa, 2019. "Modeling the sprinkler water distribution uniformity by data-driven methods based on effective variables," Agricultural Water Management, Elsevier, vol. 215(C), pages 63-73.
- Jalal Shiri & Ali Keshavarzi & Ozgur Kisi & Sahar Mohsenzadeh Karimi & Sepideh Karimi & Amir Hossein Nazemi & Jesús Rodrigo-Comino, 2020. "Estimating Soil Available Phosphorus Content through Coupled Wavelet–Data-Driven Models," Sustainability, MDPI, vol. 12(5), pages 1-23, March.
- Salim Djerbouai & Doudja Souag-Gamane, 2016. "Drought Forecasting Using Neural Networks, Wavelet Neural Networks, and Stochastic Models: Case of the Algerois Basin in North Algeria," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(7), pages 2445-2464, May.
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- Željka Brkić & Mladen Kuhta, 2022. "Lake Level Evolution of the Largest Freshwater Lake on the Mediterranean Islands through Drought Analysis and Machine Learning," Sustainability, MDPI, vol. 14(16), pages 1-28, August.
- Reza Rezaiy & Ani Shabri, 2024. "An innovative hybrid W-EEMD-ARIMA model for drought forecasting using the standardized precipitation index," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 120(14), pages 13513-13542, November.
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Keywords
Drought index; Precipitation; Evaporation; Climate change; Artificial intelligence models; Reliability analysis;All these keywords.
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