The recent advancement in data science coupled with the revolution in digital and satellite
technology has improved the potential for artificial intelligence (AI) applications in the …

In recent years, Earth system sciences are urgently calling for innovation on improving
accuracy, enhancing model intelligence level, scaling up operation, and reducing costs in …

Artificial Intelligence (AI) is believed to have a significant potential use in tackling climate
change. This paper explores the connections between AI and climate change research as a …

Ever since the first introduction of Artificial Intelligence into the field of hydrology, it has
further generated immense interest in researching aspects for further improvements to …

Long lead-time streamflow forecasting is of great significance for water resources planning
and management in both the short and long terms. Despite of some studies using machine …

In achieving water resource management goals such as irrigation scheduling, an accurate
estimate of reference evapotranspiration (ET 0) is critical. Support vector regression (SVR) …

Monthly streamflow forecasting is required for short-and long-term water resources
management especially in extreme events such as flood and drought. Therefore, there is …

Conventional machine learning models have been widely used for reservoir inflow and
rainfall prediction. Nowadays, researchers focus on a new computing architecture in the …

Accurate prediction of daily river flow (Q t) remains a challenging yet essential task in
hydrological modeling, particularly crucial for flood mitigation and water resource …

Accurate and timely monitoring of streamflow and its variation is crucial for water resources
management in watersheds. This study aimed at evaluating the performance of two process …