More information: M. Almetwally Ahmed et al, Machine Learning Model for River Discharge Forecast: A Case Study of the Ottawa River in Canada, Hydrology (2024). DOI: 10.3390/hydrology11090151 ...

Using a recently developed processing approach, these sensors can monitor river discharge changes. Among many other applications, stream flow data are important for drought monitoring, flood hazard ...

The investigation originated in 2018 when scientists first detected irregularities suggesting the presence of this deep ...

image: Deep learning improves stream discharge-based estimates of subsurface permeability, allowing scientists to create more accurate watershed models. view more ...

In the hydrological sciences, the outstanding challenge of regional modeling requires to capture common and event-specific hydrologic behaviors driven by rainfall spatial variability and catchment ...

The unprecedented research assimilates 9.18 million river discharge estimates made from 155,710 orbital satellite images into hydrologic model simulations of 486,493 Arctic river reaches from 1984 ...

The New Zealand Hydrological Society (Incorporated) is a non-profit organisation founded in 1961. Our mission is: To further the science of hydrology and its application to the understanding and ...

Notably, one-third of spring gauges exhibit escalating discharge across future scenarios, while half of all gauges show increased discharge in the fall. This increase is attributed to amplified ...

If the first two months of 2018 are any indication, events to play out over the rest of the year will have a major impact on what constitutes a “discharge” subject to regulation under Section ...