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Flowing waters have a unique role in supporting global biodiversity, biogeochemical cycles and human societies(1-5). Although the importance of permanent watercourses is well recognized, the prevalence, value and fate of non-perennial rivers and streams that periodically cease to flow tend to be overlooked, if not ignored(6-8). This oversight contributes to the degradation of the main source of water and livelihood for millions of people(5). Here we predict that water ceases to flow for at least one day per year along 51-60 per cent of the world's rivers by length, demonstrating that non-perennial rivers and streams are the rule rather than the exception on Earth. Leveraging global information on the hydrology, climate, geology and surrounding land cover of the Earth's river network, we show that non-perennial rivers occur within all climates and biomes, and on every continent. Our findings challenge the assumptions underpinning foundational river concepts across scientific disciplines(9). To understand and adequately manage the world's flowing waters, their biodiversity and functional integrity, a paradigm shift is needed towards a new conceptual model of rivers that includes flow intermittence. By mapping the distribution of non-perennial rivers and streams, we provide a stepping-stone towards addressing this grand challenge in freshwater science.

Glacier shrinkage and the development of post-glacial ecosystems related to anthropogenic climate change are some of the fastest ongoing ecosystem shifts, with marked ecological and societal cascading consequences1,2,3,4,5,6. Yet, no complete spatial analysis exists, to our knowledge, to quantify or anticipate this important changeover7,8. Here we show that by 2100, the decline of all glaciers outside the Antarctic and Greenland ice sheets may produce new terrestrial, marine and freshwater ecosystems over an area ranging from the size of Nepal (149,000 ± 55,000 km2) to that of Finland (339,000  ±  99,000  km2). Our analysis shows that the loss of glacier area will range from 22 ± 8% to 51 ± 15%, depending on the climate scenario. In deglaciated areas, the emerging ecosystems will be characterized by extreme to mild ecological conditions, offering refuge for cold-adapted species or favouring primary productivity and generalist species. Exploring the future of glacierized areas highlights the importance of glaciers and emerging post-glacial ecosystems in the face of climate change, biodiversity loss and freshwater scarcity. We find that less than half of glacial areas are located in protected areas. Echoing the recent United Nations resolution declaring 2025 as the International Year of Glaciers’ Preservation9 and the Global Biodiversity Framework10, we emphasize the need to urgently and simultaneously enhance climate-change mitigation and the in situ protection of these ecosystems to secure their existence, functioning and values.

Rapid shifts in biotic communities due to environmental variability challenge the detection of anthropogenic impacts by current biomonitoring programs. Metacommunity ecology has the potential to inform such programs, because it combines dispersal processes with niche-based approaches and recognizes variability in community composition. Using intermittent rivers—prevalent and highly dynamic ecosystems that sometimes dry—we develop a conceptual model to illustrate how dispersal limitation and flow intermittence influence the performance of biological indices. We produce a methodological framework integrating physical- and organismal-based dispersal measurements into predictive modeling, to inform development of dynamic ecological quality assessments. Such metacommunity-based approaches could be extended to other ecosystems and are required to underpin our capacity to monitor and protect ecosystems threatened under future environmental changes.

Abstract Biota in disturbance‐prone landscapes have evolved a variety of strategies to persist long term, either locally ( resistance ) or by regional recolonization ( resilience ). Habitat fragmentation and isolation can limit the availability of recolonization pathways, and thus the dynamics of post‐disturbance community reestablishment. However, empirical studies on how isolation may control the mechanisms that enable community recovery remain scarce. Here, we studied a pristine intermittent stream (Chalone Creek, Pinnacles National Park, California) to understand how isolation (distance from a perennial pool) alters invertebrate community recolonization after drying. We monitored benthic invertebrate reestablishment during the rewetting phase along a ~2‐km gradient of isolation, using mesh traps that selected for specific recolonization pathways (i.e., drift, flying, swimming/crawling, and vertical migration from the hyporheic). We collected daily emigration samples, surveyed the reestablished benthic community after 6 weeks, and compared assemblages across trap types and sites. We found that isolation mediated migration dynamics by delaying peak vertical migration from the hyporheic by ca. 1 day on average per 250 m of dry streambed. The relative importance of reestablishment mechanisms varied longitudinally–with more resistance strategists (up to 99.3% of encountered individuals) in the upstream reaches, and increased drift and aerial dispersers in the more fragmented habitats (up to 17.2% and 18%, respectively). Resistance strategists persisting in the hyporheic dominated overall (88.2% of individuals, ranging 52.9%–99.3% across sites), but notably most of these organisms subsequently outmigrated downstream (85.6% on average, ranging 52.1%–96% across sites). Thus, contrary to conventional wisdom, resistance strategists largely contributed to downstream resilience as well as to local community recovery. Finally, increased isolation was associated with a general decrease in benthic invertebrate diversity, and up to a 3‐fold increase in the relative abundance of drought‐resistant stoneflies. Our results advance the notion that understanding spatial context is key to predicting post‐disturbance community dynamics. Considering the interaction between disturbance and fragmentation may help inform conservation in ecosystems that are subject to novel environmental regimes.

Regional-scale ecological processes, such as the spatial flows of material, energy, and organisms, are fundamental for maintaining biodiversity and ecosystem functioning in river networks. Yet these processes remain largely overlooked in most river management practices and underlying policies. Here, we propose adoption of a meta-system approach, where regional processes acting at different levels of ecological organization – populations, communities, and ecosystems – are integrated into conventional river conservation, restoration, and biomonitoring. We also describe a series of measurements and indicators that could be assimilated into the implementation of relevant biodiversity and environmental policies. Finally, we highlight the need for alternative management strategies that can guide practitioners toward applying recent advances in ecology to preserve and restore river ecosystems and the ecosystem services they provide, in the context of increasing alteration of river network connectivity worldwide.

Here we introduce the LakeATLAS dataset, which provides a broad range of hydro-environmental characteristics for more than 1.4 million lakes and reservoirs globally with an area of at least 10 ha. LakeATLAS forms part of the larger HydroATLAS data repository and expands the existing datasets of sub-basin and river reach descriptors by adding equivalent information for lakes and reservoirs in a compatible structure. Matching its HydroATLAS counterparts, version 1.0 of LakeATLAS contains data for 56 variables, partitioned into 281 individual attributes and organized in six categories: hydrology; physiography; climate; land cover & use; soils & geology; and anthropogenic influences. LakeATLAS derives these attributes by processing and reformatting original data from well-established global digital maps at 15 arc-second (~500 m) grid cell resolution and assigns the information spatially to each lake by aggregating it within the lake, in a 3-km vicinity buffer around the lake, and/or within the entire upstream drainage area of the lake. The standardized format of LakeATLAS ensures versatile applicability in hydro-ecological assessments from regional to global scales.

Rivers are rich in biodiversity and act as ecological corridors for plant and animal species. With climate change and increasing anthropogenic water demand, more frequent and prolonged periods of drying in river systems are expected, endangering biodiversity and river ecosystems. However, understanding and predicting the hydrological mechanisms that control periodic drying and rewetting in rivers is challenging due to a lack of studies and hydrological observations, particularly in non-perennial rivers. Within the framework of the Horizon 2020 DRYvER (Drying River Networks and Climate Change) project, a hydrological modelling study of flow intermittence in rivers is being carried out in three European catchments (Spain, Finland, France) characterised by different climate, geology, and anthropogenic use. The objective of this study is to represent the spatio-temporal dynamics of flow intermittence at the reach level in mesoscale river networks (between 120 and 350 km2). The daily and spatially distributed flow condition (flowing or dry) is predicted using the J2000 distributed hydrological model coupled with a random forest classification model. Observed flow condition data from different sources (water level measurements, photo traps, citizen science applications) are used to build the predictive model. This study aims to evaluate the impact of the observed flow condition dataset (sample size, spatial and temporal representativity) on the performance of the predictive model. Results show that the hybrid modelling approach developed in this study allows the spatio-temporal patterns of drying to be accurately predicted in the three catchments, with a sensitivity criterion above 0.9 for the prediction of dry events in the Finnish and French case studies and 0.65 in the Spanish case study. This study shows the value of combining different data sources of observed flow condition to reduce the uncertainty in predicting flow intermittence.

Recent improvements in initialization procedures and representation of large-scale hydrometeorological processes have contributed to advancing the accuracy of hydroclimatic forecasts, which are progressively more skillful over seasonal and longer timescales. These forecasts are potentially valuable for informing strategic multisector decisions, including irrigated agriculture, for which they can improve crop choices and irrigation scheduling. In this operational context, the accuracy associated with the forecast system setup does not necessarily yield proportional marginal benefit, as this is also affected by how forecasts are employed by end users. This paper aims at quantifying the value of hydroclimatic forecasts in terms of potential economic benefit to the end users, which allows for the inference of a relation between gains in forecast skill and gains in end user profit. We also explore the sensitivity of this benefit to both forecast system setup and end user behavioral factors. These analyses are supported by an evaluation framework demonstrated on the Lake Como system (Italy), a regulated lake operated for flood protection and irrigation supply. Our framework relies on an integrated modeling chain composed of three building blocks: bias-adjusted seasonal meteorological forecasts are used as input to the continentally calibrated E-HYPE hydrological model; predicted lake inflows are used for conditioning the daily lake operations; and the resulting lake releases feed an agricultural model to estimate the net profit of the farmers in a downstream irrigation district. Results suggest that despite the gain in average conditions being negligible, informing the operations of Lake Como based on seasonal hydrological forecasts during intense drought episodes allows about 15 % of the farmers' profit to be gained with respect to a baseline solution not informed by any forecast. Moreover, our analysis suggests that behavioral factors capturing different perceptions of risk and uncertainty significantly impact the quantification of the benefit to the end users, whereby the estimated forecast value is potentially undermined by different levels of end user risk aversion. Lastly, our results show an intricate skill-to-value relation modulated by the underlying hydrologic conditions, which is well aligned over an exponential function in dry years, while the gains in profit are almost insensitive to the improvements in forecast skill in wet years.

Probabilistic seasonal forecasts are important for many water-intensive activities requiring long-term planning. Among the different techniques used for seasonal forecasting, the ensemble streamflow prediction (ESP) approach has long been employed due to the singular dependence on past meteorological records. The Swedish Meteorological and Hydrological Institute is currently extending the use of long-range forecasts within its operational warning service, which requires a thorough analysis of the suitability and applicability of different methods with the national S-HYPE hydrological model. To this end, we aim to evaluate the skill of ESP forecasts over 39 493 catchments in Sweden, understand their spatio-temporal patterns, and explore the main hydrological processes driving forecast skill. We found that ESP forecasts are generally skilful for most of the country up to 3 months into the future but that large spatio-temporal variations exist. Forecasts are most skilful during the winter months in northern Sweden, except for the highly regulated hydropower-producing rivers. The relationships between forecast skill and 15 different hydrological signatures show that forecasts are most skilful for slow-reacting, baseflow-dominated catchments and least skilful for flashy catchments. Finally, we show that forecast skill patterns can be spatially clustered in seven unique regions with similar hydrological behaviour. Overall, these results contribute to identifying in which areas and seasons and how long into the future ESP hydrological forecasts provide an added value, not only for the national forecasting and warning service, but also, most importantly, for guiding decision-making in critical services such as hydropower management and risk reduction.

Rivers integrate processes occurring throughout their watersheds and are therefore sentinels of change across broad spatial scales. River chemistry also regulates ecosystem function across Earth’s land–ocean continuum, exerting control from the micro- (for example, local food web) to the macro- (for example, global carbon cycle) scale. In the rapidly warming Arctic, a wide range of processes—from permafrost thaw to biological uptake and transformation—might reasonably alter river water chemistry. Here we use data from major rivers that collectively drain two-thirds of the Arctic Ocean watershed to assess widespread change in biogeochemical function within the pan-Arctic basin from 2003 to 2019. While the oceanward flux of alkalinity and associated ions increased markedly over this time frame, nitrate and other inorganic nutrient fluxes declined. Fluxes of dissolved organic carbon showed no overall trend. This divergence in response indicates the perturbation of multiple processes on land, with implications for biogeochemical cycling in the coastal ocean. We anticipate that these findings will facilitate refinement of conceptual and numerical models of current and future functioning of Arctic coastal ecosystems and spur research on scale-dependent change across the river-integrated Arctic domain.Divergent trends in biogeochemical constituents of the six largest rivers in the Arctic from 2003 to 2019 support multi-faceted changes on the Arctic landscape under global environmental change.