Flood prediction using machine learning models: Literature review

A Mosavi, P Ozturk, K Chau - Water, 2018 - mdpi.com
Floods are among the most destructive natural disasters, which are highly complex to model.
The research on the advancement of flood prediction models contributed to risk reduction …

Know to predict, forecast to warn: a review of flood risk prediction tools

KT Antwi-Agyakwa, MK Afenyo, DB Angnuureng - Water, 2023 - mdpi.com
Flood prediction has advanced significantly in terms of technique and capacity to achieve
policymakers' objectives of accurate forecast and identification of flood-prone and impacted …

An ensemble prediction of flood susceptibility using multivariate discriminant analysis, classification and regression trees, and support vector machines

B Choubin, E Moradi, M Golshan, J Adamowski… - Science of the Total …, 2019 - Elsevier
Floods, as a catastrophic phenomenon, have a profound impact on ecosystems and human
life. Modeling flood susceptibility in watersheds and reducing the damages caused by …

[PDF][PDF] Al-Biruni Based Optimization of Rainfall Forecasting in Ethiopia.

ESM El-Kenawy, AA Abdelhamid… - … Systems Science & …, 2023 - academia.edu
Rainfall plays a significant role in managing the water level in the reservoir. The
unpredictable amount of rainfall due to the climate change can cause either overflow or dry …

[HTML][HTML] Flooding and its relationship with land cover change, population growth, and road density

M Rahman, C Ningsheng, GI Mahmud, MM Islam… - Geoscience …, 2021 - Elsevier
Bangladesh experiences frequent hydro-climatic disasters such as flooding. These disasters
are believed to be associated with land use changes and climate variability. However …

A novel machine learning-based approach for the risk assessment of nitrate groundwater contamination

F Sajedi-Hosseini, A Malekian, B Choubin… - Science of the total …, 2018 - Elsevier
This study aimed to develop a novel framework for risk assessment of nitrate groundwater
contamination by integrating chemical and statistical analysis for an arid region. A standard …

Flood susceptibility modeling in Teesta River basin, Bangladesh using novel ensembles of bagging algorithms

S Talukdar, B Ghose, Shahfahad, R Salam… - … Research and Risk …, 2020 - Springer
The flooding in Bangladesh during monsoon season is very common and frequently
happens. Consequently, people have been experiencing tremendous damage to properties …

Assessing the performance of machine learning algorithms for soil salinity map** in Google Earth Engine platform using Sentinel-2A and Landsat-8 OLI data

S Aksoy, A Yildirim, T Gorji, N Hamzehpour… - Advances in Space …, 2022 - Elsevier
Soil salinization caused by natural and anthropogenic factors is an important environmental
hazard especially in arid and semi-arid regions of the world. Accumulation of salts in the soil …

Modeling monthly pan evaporation using wavelet support vector regression and wavelet artificial neural networks in arid and humid climates

SN Qasem, S Samadianfard, S Kheshtgar… - Engineering …, 2019 - Taylor & Francis
Evaporation rate is one of the key parameters in determining the ecological conditions and it
has an irrefutable role in the proper management of water resources. In this paper, the …

Earth fissure hazard prediction using machine learning models

B Choubin, A Mosavi, EH Alamdarloo, FS Hosseini… - Environmental …, 2019 - Elsevier
Earth fissures are the cracks on the surface of the earth mainly formed in the arid and the
semi-arid basins. The excessive withdrawal of groundwater, as well as the other …