Recently, there has been a notable tendency towards employing ensemble learning
methodologies in assorted areas of engineering, such as hydrology, for simulation and …

Drought is a prolonged period of low precipitation that negatively impacts agriculture,
animals, and people. Over the last decades, gradual changes in drought indices have been …

Prediction of suspended sediment load (SSL) in streams is significant in hydrological
modeling and water resources engineering. Development of a consistent and accurate …

The aim of this study is to select the best model (combination of different lag times) for
predicting the standardized precipitation index (SPI) and the standardized precipitation and …

The drought index, which mainly focuses on the moisture supply side of the atmosphere,
which has been mainly used in the field of drought monitoring, has limitations that cannot …

Drought is considered one of the costliest natural disasters that result in water scarcity and
crop damage almost every year. Drought monitoring and forecasting are essential for the …

Forecasting of drought can be very useful in preparing to reduce its impacts, especially in
the agricultural sector. Three machine learning models of MLP neural network, GRNN …

The overall quality of Groundwater (GW) is important, primarily because it determines the
suitability of water for drinking, irrigation, and domestic purposes. In this study, the adaptive …

Drought is the least understood natural disaster due to the complex relationship of multiple
contributory factors. Its beginning and end are hard to gauge, and they can last for months or …

Drought modeling is essential in water resources planning and management in mitigating its
effects, especially in arid regions. Climate change highly influences the frequency and …