Climate change and extreme weather events (such as droughts, heatwaves, rainstorms and
floods) pose serious challenges for water management, in terms of both water resources …

There has been an unsettling rise in the river contamination due to the climate change and
anthropogenic activities. Last decades' research has immensely focussed on river basin …

In this study, it was investigated that how machine learning (ML) methods show performance
in different problems having different characteristics. Six ML approaches including Artificial …

Develo** accurate lake water level (WL) forecasting models is important for flood control,
shoreline maintenance and sustainable water resources planning and management. In this …

Dissolved oxygen (DO) is an essential indicator for assessing water quality and managing
aquatic environments, but it is still a challenging topic to accurately understand and predict …

The water is the main pivotal sources of irrigation in agricultural activities and affects human
daily activities such as drinking. The water quality has a significant impact on various …

In this study, the predictive power of three different machine learning (ML)-based
approaches, namely, multi-gene genetic programming (MGGP), M5 model trees (M5Tree) …

Rivers, as one of the freshwater resources, are generally put in the state of jeopardy in terms
of quantity and quality due to the development in industry, agriculture, and urbanization …

Data-driven models are important to predict groundwater quality which is controlling human
health. The water quality index (WQI) has been developed based on the physicochemical …

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 …