The groundwater resources are the essential sources for irrigation and agriculture
management. Forecasting groundwater levels (GWL) for the current and future periods is an …

The challenges of urbanization, land degradation, water scarcity, and climate change are
threatening agricultural systems and food security. Therefore, it is essential to manage land …

The effects of developing technology and rapid population growth on the environment have
been expanding gradually. Particularly, the growth in water consumption has revealed the …

The present study investigates the prediction accuracy of standalone Reduced Error Pruning
Tree model and its integration with Bagging (BA), Dagging (DA), Additive Regression (AR) …

A Good many research works focused on investigating wetland habitat state and trophic
state (TS) but as far the knowledge is concerned, very little attention was paid to the …

In the present paper, we propose a new approach for monthly streamflow prediction based
on the extreme learning machine (ELM) and the metaheuristic bat algorithm (Bat-ELM). The …

This study aims to evaluate the performance of four ensemble machine learning methods, ie,
Random Committee, Discretization Regression, Reduced Error Pruning Tree, and Additive …

Accurate prediction of daily river flow (Q t) is a challenging task in hydrological modeling,
particularly vital for flood mitigation and water resource management. This study introduces …

In this study, the vote algorithm used to improve the performances of three machine-learning
models including M5Prime (M5P), random forest (RF), and random tree (RT) is developed …

Global warming and unprecedented human impacts causing environmental degradation are
taking place at an alarming rate. As one of the most valuable and important water resources …