Comprehensive overview of flood modeling approaches: A review of recent advances

V Kumar, KV Sharma, T Caloiero, DJ Mehta, K Singh - Hydrology, 2023 - mdpi.com
As one of nature's most destructive calamities, floods cause fatalities, property destruction,
and infrastructure damage, affecting millions of people worldwide. Due to its ability to …

Unmanned aerial vehicles in hydrology and water management: Applications, challenges, and perspectives

BS Acharya, M Bhandari, F Bandini… - Water Resources …, 2021 - Wiley Online Library
The hydrologic sciences and water resources management have long depended on a
combination of in situ measurements and remotely sensed data for research and regulatory …

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 …

Advancement of remote sensing for soil measurements and applications: A comprehensive review

MI Abdulraheem, W Zhang, S Li, AJ Moshayedi… - Sustainability, 2023 - mdpi.com
Remote sensing (RS) techniques offer advantages over other methods for measuring soil
properties, including large-scale coverage, a non-destructive nature, temporal monitoring …

Recent advancement in remote sensing technology for hydrology analysis and water resources management

W Duan, S Maskey, PLB Chaffe, P Luo, B He, Y Wu… - Remote sensing, 2021 - mdpi.com
Water is undoubtedly the most valuable resource of human society and an essential
component of the ecosystem. Under climate change and human activities, water resources …

How far spatial resolution affects the ensemble machine learning based flood susceptibility prediction in data sparse region

TK Saha, S Pal, S Talukdar, S Debanshi… - Journal of …, 2021 - Elsevier
Although the effect of digital elevation model (DEM) and its spatial resolution on flood
simulation modeling has been well studied, the effect of coarse and finer resolution image …

Deep learning semantic segmentation for water level estimation using surveillance camera

NA Muhadi, AF Abdullah, SK Bejo, MR Mahadi… - Applied Sciences, 2021 - mdpi.com
The interest in visual-based surveillance systems, especially in natural disaster applications,
such as flood detection and monitoring, has increased due to the blooming of surveillance …

[HTML][HTML] Analysis of two sources of variability of basin outflow hydrographs computed with the 2D shallow water model Iber: Digital Terrain Model and unstructured …

G García-Alén, J González-Cao, D Fernández-Nóvoa… - Journal of …, 2022 - Elsevier
Modelling hydrological processes with fully distributed models based on the shallow water
equations implies a high computational cost, which often limits the resolution of the …

Deep learning for filtering the ground from ALS point clouds: A dataset, evaluations and issues

N Qin, W Tan, L Ma, D Zhang, H Guan, J Li - ISPRS Journal of …, 2023 - Elsevier
The capability of partially penetrating vegetation canopy and efficiently collecting high-
precision point clouds over large areas makes airborne laser scanning (ALS) a valuable tool …

Geospatial modelling of floods: A literature review

E Avila-Aceves, W Plata-Rocha… - … Research and Risk …, 2023 - Springer
Floods are one of the most frequent, dangerous natural disasters globally. During the period
from 1990 to 2020, more than 50% of the world's recorded disasters were related to floods …