Estimating evapotranspiration (ET) has been one of the most critical research areas in
agriculture because of water scarcity, the growing population, and climate change. The …

In this study, the main objective is to develop and compare several advanced Artificial
Intelligent (AI) models namely Adaptive Network based Fuzzy Inference System optimized …

This paper presents a model for predicting the water temperature of the reservoir
incorporating with solar radiation to analyze and evaluate the water temperature of large …

This study presents a hybrid approach that integrates seasonal-trend decomposition and
machine learning (termed STL-ML) for predicting the rainfall time series one step ahead …

Elucidating the biophysical mechanisms governing the exchange of water vapor between
land and the atmosphere is particularly crucial for addressing water scarcity under climate …

Precipitation is useful information for assessing vital water resources, agriculture,
ecosystems and hydrology. Data-driven model predictions using deep learning algorithms …

This study investigates the performance of the M5Tree model, multivariate adaptive
regression spline, least square support vector regression (LSSVR), gene expressing …

Precipitation (PP) prediction is an interesting topic in the meteorology or hydrology field
since it is directly related to agriculture, the management of water resources in hydrologic …

Rainfall is crucial for the development and management of water resources. Six hybrid soft
computing models, including multilayer perceptron (MLP)–Henry gas solubility optimization …

General circulation models, which forecast by first modelling actual conditions in the
atmosphere and ocean, are used extensively for monthly rainfall forecasting. We show how …