This paper offers a comprehensive overview of machine learning (ML) methodologies and
algorithms, highlighting their practical applications in the critical domain of water resource …

Water erosion creates adverse impacts on agricultural production, infrastructure, and water
quality across the world, especially in hilly areas. Regional-scale water erosion assessment …

Pan evaporation modeling and forecasting are needed to provide timely, continuous, and
valuable information to support water management. This study aimed to overcome the …

The main challenges for utilizing daily evapotranspiration (ET) estimation in the study area
revolve around the need for accurate and reliable data inputs, as well as the interpretation of …

The seismic stability of unsupported rectangular excavations poses significant challenges in
geotechnical engineering, especially in underground structures. This study addresses the …

The river stage is certainly an important indicator of how the water level fluctuates overtime.
Continuous control of the water stage can help build an early warning indicator of floods …

This paper investigates the application of three nature-inspired optimisation algorithms–
SHO, MFO, and GOA–combined with four machine learning methods–Gaussian Processes …

Improving the forecasting accuracy of agricultural commodity prices is critical for many
stakeholders namely, farmers, traders, exporters, governments, and all other partners in the …

Suspended sediment concentration prediction is critical for the design of reservoirs, dams,
rivers ecosystems, various operations of aquatic resource structure, environmental safety …

Contamination control in cleanrooms is crucial across various industries. In semiconductor
manufacturing, operator-induced contamination presents a significant challenge, as it …