Aderyani FR, Jamshid Mousavi S, and Jafari F (2022) Short‑term rainfall forecasting using machine learning‑based approaches of PSO‑SVR, LSTM and CNN. Journal of Hydrology 678:128‑140
Aguasca-Colomo R, Castellanos-Nieves D, and Méndez M (2019) Comparative analysis of rainfall prediction models using machine learning in islands with complex orography: Tenerife Island. Applied Sciences 9(22):4931
Anochi JA, de Almeida VA, and de Campos Velho HF (2021) Machine learning for climate precipitation prediction modeling over South America. Remote Sensing 13(13):2468
Bayat-Afshary N, Khoejh S and Danesh Yazdi M (2022) Identification and analysis of the dominant factors contributing in intensification of floods and damages in the Karkheh Basin in April 2018. Iran-Water Resources Research 18(3):92–110 (In Persian)
Belete DM and Huchaiah MD (2022) Grid search in hyperparameter optimization of machine learning models for prediction of HIV/AIDS test results. International Journal of Computers and Applications, Taylor & Francis 44(9):875–886
Bochenek B and Ustrnul Z (2022) Machine learning in weather prediction and climate analyses-applications and perspectives. Atmosphere 13(2):180
Chen L, Han B, Wang X, Zhao J, Yang W, and Yang Z (2023) Machine learning methods in weather and climate applications: A Survey. Applied Sciences 13(21):12019
Friedman JH (2001) Greedy function approximation: A gradient boosting machine. The Annals of Statistics. Institute of Mathematical Statistics 29(5):1189 – 1232
Karbassiyazdi E, Fattahi F, Yousefi N, Tahmassebi A, Taromi AA, et al. (2022) XGBoost model as an efficient machine learning approach for PFAS removal: Effects of material characteristics and operation conditions. Environmental Research 215(Pt 1):114286
Kumar V, Kedam N, Sharma KV, Khedher KM and Alluqmani AE (2023) A Comparison of Machine Learning Models for Predicting Rainfall in Urban Metropolitan Cities. Sustainability 15(18):13724
Latif SD, Alyaa Binti Hazrin N, Hoon Koo C, Lin Ng J, Chaplot B, Feng Huang Y, El-Shafie A and Najah Ahmed A (2023) Assessing rainfall prediction models: Exploring the advantages of machine learning and remote sensing approaches. Alexandria Engineering Journal 38(1):1‑15
Liyew CM and Melese HA (2021) Machine learning techniques to predict daily rainfall amount. Journal of Big Data 8(1):1–11
Monego VS, Anochi JA and de Campos Velho HF (2022) South America seasonal precipitation prediction by Gradient-Boosting Machine-Learning Approach. Atmosphere 13(2):243
Ougahi JH and Rowan JS (2025) Enhanced streamflow forecasting using hybrid modelling integrating glacio-hydrological outputs, deep learning and wavelet transformation. Scientific Reports 15:87187
Rahman A, Abbas S, Gollapalli M, Ahmed R, Aftab S, Ahmad M, Khan MA, and Mosavi A (2022) Rainfall prediction system using machine learning fusion for smart cities. Sensors 22(9):3504
Shah U, Garg S, Sisodiya N, Dube N and Sharma S (2018) Rainfall prediction: Accuracy enhancement using machine learning and forecasting techniques. 5th IEEE International Conference on Parallel, Distributed and Grid Computing (PDGC-2018), 20-22 Dec, 2018, Solan, India
Woldesenbet TA, Elagib NA, Ribbe L, and Heinrich J (2017) Gap filling and homogenization of climatological datasets in the headwater region of the Upper Blue Nile Basin, Ethiopia. International Journal of Climatology 37(4):2122–2140
Yang B, Xiao Z, Meng Q, Yuan Y, Wang W, Wang H, Wang Y and Feng X (2023) Deep learning-based prediction of effluent quality of a constructed wetland. Environmental Science and Pollution Research 30(5):5300‑5315
Yu J, Li Y, Huang X, and Ye X (2025) Data quality and uncertainty issues in flood prediction: A systematic review. International Journal of Digital Earth. Taylor & Francis 18(1):2495738
