SI Climate Change Impact on Water Resources Using Machine Learning Algorithms | Journal of Water and Climate Change

Journal of Water & Climate Change Special Issue on:

Assessment of Climate Change Impact on Water Resources Using Machine Learning Algorithms

Water resources and many other aspects of life are influenced by global climate change in many developing and developed countries worldwide. For instance, its inevitable effects can be seen as the untimely occurrence of droughts or floods in different parts of the world. Thus, research on climate change has become essential.

In several parts of the globe, hydro-climatic variables, such as precipitation and temperature, are affected due to the consequences of climate change. In this regard, General Circulation Models (GCMs) are utilized to study future temperature and precipitation fluctuations. Assessment of climate change impacts on water resources can be facilitated using available approaches, such as machine learning (ML), fuzzy logic, and Multicriterion Decision Making, to name a few.

This Special Issue explores the utility of ML algorithms and allied techniques in studying those aspects. It is postulated that the proposed Special Issue can significantly help researchers and policy-makers while modeling and making water management-related decisions. In addition to applying ML models to the impact the assessment of climate change on water resources, comprehensive review-type papers on the topic are also welcomed.

We invite prospective authors to submit a manuscript to the Journal of Water & Climate Change for possible publication in the Special Issue.

Topics include (but are not limited to):

Impact of climate change on hydrological extreme events (e.g., floods and droughts)
Impact of climate change on river water quantity and quality
Impact of climate change on groundwater quantity and quality
Statistical computation for hydrological assessment of climate change
Novel downscaling techniques
The ranking or clustering GCMs
Climate change impacts on water supply

Guest Editors:

Majid Niazkar, Free University of Bozen-Bolzano, Italy

Mohammad Zakwan, Maulana Azad National Urdu University, India

Mohammad Reza Goodarzi, Yazd University, Iran

Mohammad Azamathulla Hazi, The University of the West Indies, West Indies

Editorial: Assessment of Climate Change Impact on Water Resources Using Machine Learning Algorithms

Majid Niazkar; Mohammad Zakwan; Mohammad Reza Goodarzi; Mohammad Azamathulla Hazi

Journal of Water and Climate Change (1 June 2024) 15 (6): iii–vi.

DOI: https://doi.org/10.2166/wcc.2024.002

Analysis of past and projected changes in extreme precipitation indices in some watersheds in Côte d'Ivoire

N'da Jocelyne Maryse Christine Amichiatchi; Jean Hounkpè; Gneneyougo Emile Soro; Ojelabi Oluwatoyin Khadijat; Isaac Larbi; Andrew Manoba Limantol; Abdul-Rauf Malimanga Alhassan; Tie Albert Goula Bi; Agnidé Emmanuel Lawin

Journal of Water and Climate Change (1 February 2024) 15 (2): 392–406.

DOI: https://doi.org/10.2166/wcc.2023.365

A case study of an extreme flooding episode in Charikar, Eastern Afghanistan

Farahnaz Fazel-Rastgar; Venkataraman Sivakumar

Journal of Water and Climate Change (1 December 2023) 14 (12): 4689–4707.

DOI: https://doi.org/10.2166/wcc.2023.462

Multivariate multi-step LSTM model for flood runoff prediction: a case study on the Godavari River Basin in India

Nikita Garg; Srishti Negi; Ridhima Nagar; Shruthi Rao; Seeja K. R.

Journal of Water and Climate Change (1 October 2023) 14 (10): 3635–3647.

DOI: https://doi.org/10.2166/wcc.2023.374

Effects of climate change on streamflow in the Dez Basin of Iran using the IHACRES model based on the CMIP6 model

Mohammad Reza Goodarzi; Mohammad Javad Abedi; Majid Niazkar