River systems have undergone a massive transformation since the Anthropocene. The
natural properties of river systems have been drastically altered and reshaped, limiting the …

This study proposed a novel double machine learning (DML) approach to merge multiple
satellite-based precipitation products (SPPs) and gauge observations, and tested its …

In recent years, satellite precipitation products (SPPs) have emerged as an essential source
of data and information. This work intends to summarize lessons learnt on using SPPs for …

Flood inundation modeling across large data sparse areas has been increasing in recent
years, driven by a desire to provide hazard information for a wider range of locations. The …

Coastal river deltas are susceptible to flooding from pluvial, fluvial, and coastal flood drivers.
Compound floods, which result from the co-occurrence of two or more of these drivers …

Better understanding and quantification of river floods for very local and “flashy” events calls
for modeling capability at fine spatial and temporal scales. However, long-term discharge …

Spatial variability of river network drainage density (D d) is a key feature of river systems, yet
few existing global hydrography datasets have properly accounted for it. Here, we present a …

Abstract Changes in a river's width reflect natural and anthropogenic impacts on local and
upstream/downstream hydraulic and hydrologic processes. Temporal variation of river width …

Bedload is notoriously challenging to measure and model; its dynamics, therefore, remains
largely unknown in most fluvial systems worldwide. We present results from a global scale …

Monitoring the spatiotemporal dynamics of surface water from remote sensing imagery is
essential for understanding water's impact on the global ecosystem and climate change …