Runoff prediction in ungauged and scarcely gauged catchments is a key research field in
surface water hydrology. There have been numerous studies before and since the launch of …

Process-based hydrological models have a long history dating back to the 1960s. Criticized
by some as over-parameterized, overly complex, and difficult to use, a more nuanced view is …

This paper is derived from a keynote talk given at the Google's 2020 Flood Forecasting
Meets Machine Learning Workshop. Recent experiments applying deep learning to rainfall …

Abstract Earth System Models (ESMs) are essential tools for understanding and predicting
global change, but they cannot explicitly resolve hillslope‐scale terrain structures that …

We present a new data set of attributes for 671 catchments in the contiguous United States
(CONUS) minimally impacted by human activities. This complements the daily time series of …

We introduce the first catchment dataset for large sample studies in Chile. This dataset
includes 516 catchments; it covers particularly wide latitude (17.8 to 55.0∘ S) and elevation …

Modeling dynamic geophysical phenomena is at the core of Earth and environmental
studies. The geoscientific community relying mainly on physical representations may want to …

In the current human-modified world, or Anthropocene, the state of water stores and fluxes
has become dependent on human as well as natural processes. Water deficits (or droughts) …

Abstract Karst regions represent 7–12% of the Earth's continental area, and about one
quarter of the global population is completely or partially dependent on drinking water from …

Abstract The Prediction in Ungauged Basins (PUB) initiative of the International Association
of Hydrological Sciences (IAHS), launched in 2003 and concluded by the PUB Symposium …