Water resource modeling is an important means of studying the distribution, change,
utilization, and management of water resources. By establishing various models, water …

Machine learning (ML) applications in hydrology are revolutionizing our understanding and
prediction of hydrological processes, driven by advancements in artificial intelligence and …

Drought is one of the costliest natural disasters worldwide and weakens countries
economically by causing negative impacts on hydropower and agricultural production …

Tea plant (Camellia sinensis) is a major global crop consumed as a drink after water.
Quantifying carbon flux, specifically the net ecosystem exchange (NEE), in tea plantations is …

This study investigates monthly streamflow modeling at Kale and Durucasu stations in the
Black Sea Region of Turkey using remote sensing data. The analysis incorporates key …

Hydrological forecasting plays a crucial role in mitigating flood risks and managing water
resources. Data-driven hydrological models demonstrate exceptional fitting capabilities and …

Accurate and reliable short-term runoff prediction plays a pivotal role in water resource
management, agriculture, and flood control, enabling decision-makers to implement timely …

The utilisation of modelling tools in hydrology has been effective in predicting future floods
by analysing historical rainfall and inflow data, due to the association between climate …

Accurate forecast of monthly streamflow is helpful to improve the social capability in risk
management. Diverse input features are crucial to the accuracy of machine learning-based …

Accurate and reliable daily reservoir inflow forecast plays an essential role in several
applications involving the management and planning of water resources, such as …