Random forests (RF) is a supervised machine learning algorithm, which has recently started
to gain prominence in water resources applications. However, existing applications are …

Abstract The United Nations' Convention on Biological Diversity set forth the 30× 30 target,
an agenda for countries to protect at least 30% of their terrestrial, inland water, and coastal …

We live in a world where biophysical and social processes are tightly coupled. Hydrologic
systems change in response to a variety of natural and human forces such as climate …

Evaluating the eutrophication risk of a receiving reservoir is crucial for scientific water
transfer schemes. However mega water transfer projects would greatly affect both water …

A large fraction of major waterways have dams influencing streamflow, which must be
accounted for in large-scale hydrologic modeling. However, daily streamflow prediction for …

Many studies have found that damming a river can change downstream hydrology, sediment
transport, channel morphology, and fish habitat. However, little is known about river dam …

A key challenge to understanding ecohydrologic responses to dam regulation is the
absence of a universally transferable classification framework for how dams operate. In the …

Nowadays, alteration of the natural flow regime is considered one the most widespread and
damaging impacts for river ecosystems. Hence, increasing our understanding of large-scale …

River scientists strive to understand how streamflow regimes vary across space and time
because it is fundamental to predicting the impacts of climate change and human activities …

Modeling the interactions of water and energy systems is important to the enforcement of
infrastructure security and system sustainability. To this end, recent technological …