[HTML][HTML] Characterizing drought prediction with deep learning: A literature review

A Márquez-Grajales, R Villegas-Vega… - MethodsX, 2024 - Elsevier
Drought prediction is a complex phenomenon that impacts human activities and the
environment. For this reason, predicting its behavior is crucial to mitigating such effects …

[HTML][HTML] Utilizing machine learning and CMIP6 projections for short-term agricultural drought monitoring in central Europe (1900–2100)

S Mohammed, S Arshad, F Alsilibe, MFU Moazzam… - Journal of …, 2024 - Elsevier
Water availability for agricultural practices is dynamically influenced by climatic variables,
particularly droughts. Consequently, the assessment of drought events is directly related to …

Forecasting of stage-discharge in a non-perennial river using machine learning with gamma test

DK Vishwakarma, A Kuriqi, SA Abed, G Kishore… - Heliyon, 2023 - cell.com
Abstract Knowledge of the stage-discharge rating curve is useful in designing and planning
flood warnings; thus, develo** a reliable stage-discharge rating curve is a fundamental …

Multi-ahead electrical conductivity forecasting of surface water based on machine learning algorithms

D Kumar, VK Singh, SA Abed, VK Tripathi, S Gupta… - Applied Water …, 2023 - Springer
The present research work focused on predicting the electrical conductivity (EC) of surface
water in the Upper Ganga basin using four machine learning algorithms: multilayer …

Modeling of soil moisture movement and wetting behavior under point-source trickle irrigation

DK Vishwakarma, R Kumar, SA Abed, N Al-Ansari… - Scientific Reports, 2023 - nature.com
The design and selection of ideal emitter discharge rates can be aided by accurate
information regarding the wetted soil pattern under surface drip irrigation. The current field …

Daily suspended sediment yield estimation using soft-computing algorithms for hilly watersheds in a data-scarce situation: a case study of Bino watershed …

PS Tulla, P Kumar, DK Vishwakarma, R Kumar… - Theoretical and Applied …, 2024 - Springer
Water erosion creates adverse impacts on agricultural production, infrastructure, and water
quality across the world, especially in hilly areas. Regional-scale water erosion assessment …

Hybrid river stage forecasting based on machine learning with empirical mode decomposition

S Heddam, DK Vishwakarma, SA Abed, P Sharma… - Applied Water …, 2024 - Springer
The river stage is certainly an important indicator of how the water level fluctuates overtime.
Continuous control of the water stage can help build an early warning indicator of floods …

Drought index time series forecasting via three-in-one machine learning concept for the Euphrates basin

L Latifoğlu, S Bayram, G Aktürk, H Citakoglu - Earth Science Informatics, 2024 - Springer
Droughts are among the most hazardous and costly natural disasters and are hard to
quantify and characterize. Accurate drought forecasting reduces droughts' devastating …

Estimation of crop evapotranspiration using statistical and machine learning techniques with limited meteorological data: a case study in Udham Singh Nagar, India

A Satpathi, A Danodia, AS Nain, M Dhyani… - Theoretical and Applied …, 2024 - Springer
Accurate forecasting of daily evapotranspiration (ET) is essential for enhancing real-time
irrigation scheduling and informed decision-making in water resources allocation. This study …

Evaluation of CatBoost method for predicting weekly Pan evaporation in subtropical and sub-humid regions

DK Vishwakarma, P Kumar, KK Yadav, R Ali… - Pure and Applied …, 2024 - Springer
Pan evaporation modeling and forecasting are needed to provide timely, continuous, and
valuable information to support water management. This study aimed to overcome the …