Atmospheric carbon dioxide concentration ([CO2]) is increasing, which increases leaf‐scale
photosynthesis and intrinsic water‐use efficiency. These direct responses have the potential …

Predictions of floods, droughts, and fast drought‐flood transitions are required at different
time scales to develop management strategies targeted at minimizing negative societal and …

Deep learning (DL), a new generation of artificial neural network research, has transformed
industries, daily lives, and various scientific disciplines in recent years. DL represents …

This paper is the outcome of a community initiative to identify major unsolved scientific
problems in hydrology motivated by a need for stronger harmonisation of research efforts …

Assessing reliability of global models is critical because of increasing reliance on these
models to address past and projected future climate and human stresses on global water …

Land surface models (LSMs) are a vital tool for understanding, projecting, and predicting the
dynamics of the land surface and its role within the Earth system, under global change …

Nowadays, mathematical models of hydrological systems are used routinely to guide
decision making in diverse subjects, such as: environmental and risk assessments, design …

Many of the scientific and societal challenges in understanding and preparing for global
environmental change rest upon our ability to understand and predict the water cycle …

The diversity in hydrologic models has historically led to great controversy on the correct
approach to process-based hydrologic modeling, with debates centered on the adequacy of …

Recently, deep learning (DL) has emerged as a revolutionary and versatile tool transforming
industry applications and generating new and improved capabilities for scientific discovery …