Due to rapid development, the occurrence of flood has become more and more frequent.
However, due to the complex nature and limited knowledge, the conventional hydrological …

Sediment data pertains to various hydrological variables with complex sediment
hydrodynamics such as sedimentation rates which are often incompletely presented. Thus …

The formation of oil–mineral aggregates (OMAs) is essential for understanding the behavior
of oil spills in estuaries and coastal waters. We utilized statistical methods (screening …

Hydrokinetic power is a small-scale, zero-head form of hydropower with the potential to
address renewable energy needs for many communities, including those in the Arctic. An …

Rainfall data plays a vital role in various fields including agriculture, hydrology, climatology,
and water resource management. Stakeholders had raised concerns over the issue of …

Siltation impacts ecosystem and environment negatively as it will result in water pollution
which leads to poor water quality, and subsequently, create harmful effects towards human …

Suspended sediment load (SSL) prediction study is critical to water resource management.
This paper presents studies related to the prediction of SSL using machine learning (ML) …

Cardiovascular diseases (CVDs) persist as a primary cause of mortality on a global scale,
necessitating effective prediction methods. This study presents a novel modelling approach …

This thesis investigates two key areas of northern energy planning through mathematical
modelling. Firstly, a predictive machine learning model is developed to estimate stream …