Develo** accurate soft computing methods for groundwater level (GWL) forecasting is
essential for enhancing the planning and management of water resources. Over the past two …

River flow (Q flow) is a hydrological process that considerably impacts the management and
sustainability of water resources. The literature has shown great potential for nature-inspired …

Streamflow (Q flow) prediction is one of the essential steps for the reliable and robust water
resources planning and management. It is highly vital for hydropower operation, agricultural …

The development of computer aid models for heavy metals (HMs) simulation has been
remarkably advanced over the past two decades. Several machine learning (ML) models …

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

Accurate and reliable prediction of streamflow is vital to the optimization of water resources
management, reservoir flood operations, catchment, and urban water management. In this …

The rising salinity trend in the country's coastal groundwater has reached an alarming rate
due to unplanned use of groundwater in agriculture and seawater see** into the …

Hydrological models play a crucial role in water planning and decision making. Machine
Learning-based models showed several drawbacks for frequent high and a wide range of …

The utilization of CO 2 flooding is a widely applied enhanced oil recovery (EOR) technique
in mature onshore oil fields. As well as being able to increase oil production and recovery it …

Suspended sediment load (SSL) estimation is a required exercise in water resource
management. This article proposes the use of hybrid artificial neural network (ANN) models …