An overview of flood concepts, challenges, and future directions

A Mishra, S Mukherjee, B Merz, VP Singh… - Journal of hydrologic …, 2022 - ascelibrary.org
This review provides a broad overview of the current state of flood research, current
challenges, and future directions. Beginning with a discussion of flood-generating …

[HTML][HTML] Flood susceptibility modelling using advanced ensemble machine learning models

ARMT Islam, S Talukdar, S Mahato, S Kundu… - Geoscience …, 2021 - Elsevier
Floods are one of nature's most destructive disasters because of the immense damage to
land, buildings, and human fatalities. It is difficult to forecast the areas that are vulnerable to …

[HTML][HTML] Soft computing ensemble models based on logistic regression for groundwater potential mapping

PT Nguyen, DH Ha, M Avand, A Jaafari, HD Nguyen… - Applied Sciences, 2020 - mdpi.com
Groundwater potential maps are one of the most important tools for the management of
groundwater storage resources. In this study, we proposed four ensemble soft computing …

[HTML][HTML] 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 …

[HTML][HTML] GIS-based machine learning algorithms for gully erosion susceptibility mapping in a semi-arid region of Iran

X Lei, W Chen, M Avand, S Janizadeh, N Kariminejad… - Remote Sensing, 2020 - mdpi.com
In the present study, gully erosion susceptibility was evaluated for the area of the Robat Turk
Watershed in Iran. The assessment of gully erosion susceptibility was performed using four …

[HTML][HTML] Groundwater potential mapping combining artificial neural network and real AdaBoost ensemble technique: the DakNong province case-study, Vietnam

PT Nguyen, DH Ha, A Jaafari, HD Nguyen… - International journal of …, 2020 - mdpi.com
The main aim of this study is to assess groundwater potential of the DakNong province,
Vietnam, using an advanced ensemble machine learning model (RABANN) that integrates …

[HTML][HTML] A novel hybrid soft computing model using random forest and particle swarm optimization for estimation of undrained shear strength of soil

BT Pham, C Qi, LS Ho, T Nguyen-Thoi, N Al-Ansari… - Sustainability, 2020 - mdpi.com
Determination of shear strength of soil is very important in civil engineering for foundation
design, earth and rock fill dam design, highway and airfield design, stability of slopes and …

Flood susceptible prediction through the use of geospatial variables and machine learning methods

NM Gharakhanlou, L Perez - Journal of hydrology, 2023 - Elsevier
Floods are one of the most perilous natural calamities that cause property destruction and
endanger human life. The spatial patterns of flood susceptibility were assessed in this study …

Exploring the additional value of class imbalance distributions on interpretable flash flood susceptibility prediction in the Black Warrior River basin, Alabama, United …

Ö Ekmekcioğlu, K Koc, M Özger, Z Işık - Journal of Hydrology, 2022 - Elsevier
This study proposes a novel flash flood susceptibility prediction framework with a particular
emphasis on the extent of imbalance between the number of flooding and non-flooding …

[HTML][HTML] Flood hazard and risk mapping by applying an explainable machine learning framework using satellite imagery and GIS data

G Antzoulatos, IO Kouloglou, M Bakratsas… - Sustainability, 2022 - mdpi.com
Flooding is one of the most destructive natural phenomena that happen worldwide, leading
to the damage of property and infrastructure or even the loss of lives. The escalation in the …