Publisher
Springer Science and Business Media LLC
Subject
General Agricultural and Biological Sciences,Environmental Chemistry,Environmental Engineering
Reference97 articles.
1. Achite M, Jehanzaib M, Elshaboury N, Kim TW (2022) Evaluation of machine learning techniques for hydrological drought modeling: A case study of the wadi ouahrane basin in algeria. Water 14(3):431
2. Ahmad A, van der Wens P, Baken K, de Waal L, Bhattacharya P, Stuyfzand P (2020) Arsenic reduction to < 1 µg/L in Dutch drinking water. Environ Int 134:105253
3. Ahmadi A, Olyaei M, Heydari Z, Emami M, Zeynolabedin A, Ghomlaghi A, Daccache A, Fogg GE, Sadegh M (2022) Groundwater level modeling with machine learning: a systematic review and meta-analysis. Water 14(6):949
4. Ahoulé DG, Lalanne F, Mendret J, Brosillon S, Maïga AH (2015) Arsenic in African waters: a review. Water Air Soil Pollut 226(9):1–13
5. Akbari M, Soleimani K, Mahdavi M and Habibnejhad M (2011), Monitoring of regional low-flow frequency using artificial neural networks.