Global review of groundwater potential models in the last decade: parameters, model techniques, and validation

NN Thanh, P Thunyawatcharakul, NH Ngu… - Journal of …, 2022 - Elsevier
This paper aims to review parameters, model techniques, validation methods in
groundwater potential field. According to statistics, there are three major model groups used …

Evaluation efficiency of hybrid deep learning algorithms with neural network decision tree and boosting methods for predicting groundwater potential

Y Chen, W Chen, S Chandra Pal, A Saha… - Geocarto …, 2022 - Taylor & Francis
Delineation of the groundwater's potential zones is a growing phenomenon worldwide due
to the high demand for fresh groundwater. Therefore, the identification of potential …

Novel ensemble machine learning models in flood susceptibility mapping

P Prasad, VJ Loveson, B Das, M Kotha - Geocarto International, 2022 - Taylor & Francis
The research aims to propose the new ensemble models by combining the machine
learning techniques, such as rotation forest (RF), nearest shrunken centroids (NSC), k …

A groundwater potential zone mapping approach for semi-arid environments using remote sensing (RS), geographic information system (GIS), and analytical …

ST Owolabi, K Madi, AM Kalumba… - Arabian journal of …, 2020 - Springer
Theme unsuitability is noted to have inhibited the accuracy of groundwater potential zones
(GWPZs) mapping approach, especially in a semi-arid environment where surface water …

Groundwater potential mapping using multi-criteria decision, bivariate statistic and machine learning algorithms: evidence from Chota Nagpur Plateau, India

M Hasanuzzaman, MH Mandal, M Hasnine… - Applied Water Science, 2022 - Springer
Increased consumption of water resource due to rapid growth of population has certainly
reduced the groundwater storage beneath the earth which leads certain challenges to …

Groundwater potential mapping in hubei region of china using machine learning, ensemble learning, deep learning and automl methods

Z Bai, Q Liu, Y Liu - Natural Resources Research, 2022 - Springer
Freshwater scarcity has become more widespread on a global scale in recent years. Surface
water resources are no longer sufficient to meet the demands of human productivity and …

Machine learning-based monitoring and design of managed aquifer rechargers for sustainable groundwater management: scope and challenges

AG Sheik, A Kumar, AG Sharanya, SR Amabati… - … Science and Pollution …, 2024 - Springer
Managed aquifer recharge (MAR) replenishes groundwater by artificially entering water into
subsurface aquifers. This technology improves water storage, reduces over-extraction, and …

Soil erosion susceptibility mapping using ensemble machine learning models: A case study of upper Congo river sub-basin

LC Kulimushi, JB Bashagaluke, P Prasad, AB Heri-Kazi… - Catena, 2023 - Elsevier
Despite its large size, the Congo Basin (CB), which spans ten countries, has remained an
area of particular interest for scientific discovery due to gaps in Earth science, environmental …

Evaluation and comparison of the earth observing sensors in land cover/land use studies using machine learning algorithms

P Prasad, VJ Loveson, P Chandra, M Kotha - Ecological Informatics, 2022 - Elsevier
The rapid transformation of land cover/land use (LCLU) is a strong indication of global
environmental change. In order to monitor LCLU through maps, a significant dataset and …

Application of machine learning algorithms in hydrology

H Mosaffa, M Sadeghi, I Mallakpour… - Computers in earth and …, 2022 - Elsevier
Hydrology is the science of studying the natural flow of water and the effect of human activity
on the water. Hydrological modeling is essential for the management and conservation of …