Flood prediction using machine learning models: Literature review
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 …
The research on the advancement of flood prediction models contributed to risk reduction …
Deep learning in statistical downscaling for deriving high spatial resolution gridded meteorological data: A systematic review
Y Sun, K Deng, K Ren, J Liu, C Deng, Y ** - ISPRS Journal of …, 2024 - Elsevier
Nowadays, meteorological data plays a crucial role in various fields such as remote sensing,
weather forecasting, climate change, and agriculture. The regional and local studies call for …
weather forecasting, climate change, and agriculture. The regional and local studies call for …
Geospatial Modeling based-multi-criteria decision-making for flash flood susceptibility zonation in an arid area
Identifying areas susceptible to flash flood hazards is essential to mitigating their negative
impacts, particularly in arid regions. For example, in southeastern Sinai, the Egyptian …
impacts, particularly in arid regions. For example, in southeastern Sinai, the Egyptian …
Deep learning-based maximum temperature forecasting assisted with meta-learning for hyperparameter optimization
Time series forecasting of meteorological variables such as daily temperature has recently
drawn considerable attention from researchers to address the limitations of traditional …
drawn considerable attention from researchers to address the limitations of traditional …
Review of studies on hydrological modelling in Malaysia
Hydrological models are vital component and essential tools for water resources and
environmental planning and management. In recent times, several studies have been …
environmental planning and management. In recent times, several studies have been …
Monsoonal precipitation over Peninsular Malaysia in the CMIP6 HighResMIP experiments: the role of model resolution
This study investigates the ability of 20 model simulations which contributed to the CMIP6
HighResMIP to simulate precipitation in different monsoon seasons and extreme …
HighResMIP to simulate precipitation in different monsoon seasons and extreme …
A comparative assessment of hydrological models in the Upper Cauvery catchment
This paper presents a comparison of the predictive capability of three hydrological models,
and a mean ensemble of these models, in a heavily influenced catchment in Peninsular …
and a mean ensemble of these models, in a heavily influenced catchment in Peninsular …
A novel study of SWAT and ANN models for runoff simulation with application on dataset of metrological stations
H Zakizadeh, H Ahmadi, G Zehtabian, A Moeini… - … of the Earth, Parts a/b/c, 2020 - Elsevier
Rainfall-runoff simulation is one of the most important processes in flood simulation,
especially in the watersheds (Darake watershed) located upstream of large cities (populated …
especially in the watersheds (Darake watershed) located upstream of large cities (populated …
Metalearning approach coupled with CMIP6 multi-GCM for future monthly streamflow forecasting
MNM Adib, S Harun - Journal of hydrologic engineering, 2022 - ascelibrary.org
Spatial and temporal variability of streamflow due to climate change affects hydrological
processes and irrigation demands at a basin scale. This study investigated the impacts of …
processes and irrigation demands at a basin scale. This study investigated the impacts of …
Comparison of different artificial intelligence techniques to predict floods in Jhelum River, Pakistan
Floods are among the major natural disasters that cause loss of life and economic damage
worldwide. Floods damage homes, crops, roads, and basic infrastructure, forcing people to …
worldwide. Floods damage homes, crops, roads, and basic infrastructure, forcing people to …