Assessing diverse parameters like water quality, quantity, and occurrence of hydrological
extremes and their management is crucial to perform efficient water resource management …

The word" inhomogeneity" in a time-series analysis is defined as those changes that occur
in the time-series datasets due to non-climatic factors. Rainfall datasets without the presence …

Streamflow forecasting is essential for planning, designing, and managing watershed
systems. This research study investigates the use of artificial neural networks (ANN) …

Agricultural water management plays a significant role in the sustainable development of the
watershed. Three different water management techniques based on the water harvesting …

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 …

Conventional hydrological modeling is highly tedious for a data-sparse tropical river basin
heavily loaded by hydraulic structures. The application of promising machine learning …

Recently, coupled Wavelet transform and Neural Networks models (WANN) were
extensively used in hydrological drought forecasting, which is an important task in drought …

Water resource management in the agricultural sector is a necessity that profoundly impacts
water resources conservation for future generations. With the aim of rivers water abstraction …

ABSTRACT Recently, Artificial Neural Network (ANN) methods, which have been
successfully applied in many fields, have been considered for a large number of reliable …

Changes in streamflow within catchments can have a significant impact on agricultural
production, as soil moisture loss, as well as frequent drying and wetting, may have an effect …