The causes of recent hydrological droughts and their future evolution under a changing climate are still poorly understood. Banking on a 216-year river flow time series at the Po River outlet, we show that the 2022 hydrological drought is the worst event (30% lower than the second worst, with a six-century return period), part of an increasing trend in severe drought occurrence. The decline in summer river flows (−4.14 cubic meters per second per year), which is more relevant than the precipitation decline, is attributed to a combination of changes in the precipitation regime, resulting in a decline of snow fraction (−0.6% per year) and snowmelt (−0.18 millimeters per day per year), and to increasing evaporation rate (+0.013 cubic kilometers per year) and irrigated areas (100% increment from 1900). Our study presents a compelling case where the hydrological impact of climate change is exacerbated by local changes in hydrologic seasonality and water use.

River floods claim thousands of lives every year, but effective and high‐resolution methods to map human exposure to floods at the global scale are still lacking. We use satellite nightlight data to prove that nocturnal lights close to rivers are consistently related to flood damages. We correlate global data of economic losses caused by flooding events with nighttime lights and find that increasing nightlights are associated to flood damage intensification. Then, we analyze the temporal evolution of nightlights along the river network all over the world from 1992 to 2012 and obtain a global map of nightlight trends, which we associate with increasing human exposure to floods, at 1 km² resolution. An enhancement of exposure to floods worldwide, particularly in Africa and Asia, is revealed, which may exacerbate the projected effects of climate change on flood‐related losses and therefore argues for the development of valuable flood preparedness and mitigation strategies.

Artificial intelligence can enhance our ability to manage natural disasters. However, understanding and addressing its limitations is required to realize its benefits. Here, we argue that interdisciplinary, multistakeholder, and international collaboration is needed for developing standards that facilitate its implementation.

Reproducibility and repeatability of experiments are the fundamental prerequisites that allow researchers to validate results and share hydrological knowledge, experience and expertise in the light of global water management problems. Virtual laboratories offer new opportunities to enable these prerequisites since they allow experimenters to share data, tools and pre-defined experimental procedures (i.e. protocols). Here we present the outcomes of a first collaborative numerical experiment undertaken by five different international research groups in a virtual laboratory to address the key issues of reproducibility and repeatability. Moving from the definition of accurate and detailed experimental protocols, a rainfall–runoff model was independently applied to 15 European catchments by the research groups and model results were collectively examined through a web-based discussion. We found that a detailed modelling protocol was crucial to ensure the comparability and reproducibility of the proposed experiment across groups. Our results suggest that sharing comprehensive and precise protocols and running the experiments within a controlled environment (e.g. virtual laboratory) is as fundamental as sharing data and tools for ensuring experiment repeatability and reproducibility across the broad scientific community and thus advancing hydrology in a more coherent way.

River networks play a key role in the spatial organization of human settlements. Both river networks and human settlements have been found to exhibit regular self‐similar patterns, but little is known about the generalized spatial patterns of human settlements embedded within river networks. Here based on night light data, we find a universal fractal structure at the global scale, with both robust Hortonian scaling relationships with the extent of human settlements and statistically significant power law scaling of the power spectra of human area functions. Globally, we find consistent patterns of power law preferential downstream clustering of human settlements across all six populated continents, typically up to 40% of the maximum flow length. This downstream clustering suggests an optimum distribution of humans in large river basins for trade, transport, and natural resource utilization but with attendant implications for human impacts on rivers. Recognition of such spatial patterns helps generalize assessments of human impacts on rivers, with direct implications for management of water quality and biological diversity in river networks.

We explore how to address the challenges of adaptation of water resources systems under changing conditions by supporting flexible, resilient and low-regret solutions, coupled with on-going monitoring and evaluation. This will require improved understanding of the linkages between biophysical and social aspects in order to better anticipate the possible future co-evolution of water systems and society. We also present a call to enhance the dialogue and foster the actions of governments, the international scientific community, research funding agencies and additional stakeholders in order to develop effective solutions to support water resources systems adaptation. Finally, we call the scientific community to a renewed and unified effort to deliver an innovative message to stakeholders. Water science is essential to resolve the water crisis, but the effectiveness of solutions depends, inter alia, on the capability of scientists to deliver a new, coherent and technical vision for the future development of water systems.