Hydrological Sciences

Summary of the August 26th, 2026, Himalayan flash flood

György Hetényi and Shiba Subedi August 28, 2026

3D view in GoogleEarth, facing the cliff and glacier (on the left) at the source of the event

At the time of preparing this blog entry, we are less than 48 hours after the catastrophe which has hit the Himalaya. While the flow of new information continues, it is useful to summarize and clarify the key points around this event. WHAT? The massive destruction was caused by a flash flood. It was such a high energy that is rarely seen. Numerous videos can be found online. WHERE? The caus ...[Read More]

Drought in Europe

Bettina Schaefli August 18, 2026

On the shore of lake Constance (Ermatingen), 12 Aug 2026, Tobias Wechsler

Many of us are experiencing it right now: Europe is suffering from a long lasting large scale drought (Fig. 1), with record heat and low-flow levels that probably nobody of us has seen before; and current forecasts do not announce any relieve for the coming weeks. The pictures of record low levels in the river Rhine are scaring – knowing how strongly Europe depends on this fluvial transport ...[Read More]

Has groundwater finally gone mainstream?

Luka Vucinic August 13, 2026

Photo by Sandor Rodriguez Castro. Source: Unsplash

Groundwater has always had an image problem. Throughout my career, I have lost count of how many times we have described groundwater as an “invisible resource” or similar. It is almost a cliché in hydrogeology. We use the phrase because it captures something really fundamental: groundwater is hidden physically, but it has also been hidden from public consciousness. What people cannot see or easily ...[Read More]

What machine learning can and cannot tell us about floods

Emma Ford July 23, 2026

Collage based on a picture by Imad Clicks via Pexel

Floods are shaped by complex and nonlinear interactions between weather patterns, rainfall, soil properties, topography, land cover, and how wet a catchment already is. This complexity is one reason machine learning (ML) is increasingly used in hydrology. ML models can learn patterns from large and complex datasets with many variables. Early in my PhD, while exploring machine learning models for ...[Read More]