A unified explanation for the morphology of raised peatlands.

Raised peatlands, or bogs, are gently mounded landforms that are composed entirely of organic matter1-4 and store the most carbon per area of any terrestrial ecosystem5. The shapes of bogs are critically important because their domed morphology4,6,7 accounts for much of the carbon that bogs store and determines how they will respond to interventions8,9 to stop greenhouse gas emissions and fires after anthropogenic drainage10-13. However, a general theory to infer the morphology of bogs is still lacking4,6,7. Here we show that an equation based on the processes universal to bogs explains their morphology across biomes, from Alaska, through the tropics, to New Zealand. In contrast to earlier models of bog morphology that attempted to describe only long-term equilibrium shapes4,6,7 and were, therefore, inapplicable to most bogs14-16, our approach makes no such assumption and makes it possible to infer full shapes of bogs from a sample of elevations, such as a single elevation transect. Our findings provide a foundation for quantitative inference about the morphology, hydrology and carbon storage of bogs through Earth's history, as well as a basis for planning natural climate solutions by rewetting damaged bogs around the world.

Global prediction of extreme floods in ungauged watersheds.

Floods are one of the most common natural disasters, with a disproportionate impact in developing countries that often lack dense streamflow gauge networks1. Accurate and timely warnings are critical for mitigating flood risks2, but hydrological simulation models typically must be calibrated to long data records in each watershed. Here we show that artificial intelligence-based forecasting achieves reliability in predicting extreme riverine events in ungauged watersheds at up to a five-day lead time that is similar to or better than the reliability of nowcasts (zero-day lead time) from a current state-of-the-art global modelling system (the Copernicus Emergency Management Service Global Flood Awareness System). In addition, we achieve accuracies over five-year return period events that are similar to or better than current accuracies over one-year return period events. This means that artificial intelligence can provide flood warnings earlier and over larger and more impactful events in ungauged basins. The model developed here was incorporated into an operational early warning system that produces publicly available (free and open) forecasts in real time in over 80 countries. This work highlights a need for increasing the availability of hydrological data to continue to improve global access to reliable flood warnings.

Anthropogenic fingerprints in daily precipitation revealed by deep learning.

According to twenty-first century climate-model projections, greenhouse warming will intensify rainfall variability and extremes across the globe1-4. However, verifying this prediction using observations has remained a substantial challenge owing to large natural rainfall fluctuations at regional scales3,4. Here we show that deep learning successfully detects the emerging climate-change signals in daily precipitation fields during the observed record. We trained a convolutional neural network (CNN)5 with daily precipitation fields and annual global mean surface air temperature data obtained from an ensemble of present-day and future climate-model simulations6. After applying the algorithm to the observational record, we found that the daily precipitation data represented an excellent predictor for the observed planetary warming, as they showed a clear deviation from natural variability since the mid-2010s. Furthermore, we analysed the deep-learning model with an explainable framework and observed that the precipitation variability of the weather timescale (period less than 10 days) over the tropical eastern Pacific and mid-latitude storm-track regions was most sensitive to anthropogenic warming. Our results highlight that, although the long-term shifts in annual mean precipitation remain indiscernible from the natural background variability, the impact of global warming on daily hydrological fluctuations has already emerged.

A global rise in alluvial mining increases sediment load in tropical rivers.

Increasing gold and mineral mining activity in rivers across the global tropics has degraded ecosystems and threatened human health1,2. Such river mineral mining involves intensive excavation and sediment processing in river corridors, altering river form and releasing excess sediment downstream2. Increased suspended sediment loads can reduce water clarity and cause siltation to levels that may result in disease and mortality in fish3,4, poor water quality5 and damage to human infrastructure6. Although river mining has been investigated at local scales, no global synthesis of its physical footprint and impacts on hydrologic systems exists, leaving its full environmental consequences unknown. We assemble and analyse a 37-year satellite database showing pervasive, increasing river mineral mining worldwide. We identify 396 mining districts in 49 countries, concentrated in tropical waterways that are almost universally altered by mining-derived sediment. Of 173 mining-affected rivers, 80% have suspended sediment concentrations (SSCs) more than double pre-mining levels. In 30 countries in which mining affects large (>50 m wide) rivers, 23 ± 19% of large river length is altered by mining-derived sediment, a globe-spanning effect representing 35,000 river kilometres, 6% (±1% s.e.) of all large tropical river reaches. Our findings highlight the ubiquity and intensity of mining-associated degradation in tropical river systems.

The challenge of unprecedented floods and droughts in risk management.

Risk management has reduced vulnerability to floods and droughts globally1,2, yet their impacts are still increasing3. An improved understanding of the causes of changing impacts is therefore needed, but has been hampered by a lack of empirical data4,5. On the basis of a global dataset of 45 pairs of events that occurred within the same area, we show that risk management generally reduces the impacts of floods and droughts but faces difficulties in reducing the impacts of unprecedented events of a magnitude not previously experienced. If the second event was much more hazardous than the first, its impact was almost always higher. This is because management was not designed to deal with such extreme events: for example, they exceeded the design levels of levees and reservoirs. In two success stories, the impact of the second, more hazardous, event was lower, as a result of improved risk management governance and high investment in integrated management. The observed difficulty of managing unprecedented events is alarming, given that more extreme hydrological events are projected owing to climate change3.

Global prevalence of non-perennial rivers and streams.

Flowing waters have a unique role in supporting global biodiversity, biogeochemical cycles and human societies1-5. 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 ignored6-8. This oversight contributes to the degradation of the main source of water and livelihood for millions of people5. 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 disciplines9. 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.

Human alteration of global surface water storage variability.

Knowing the extent of human influence on the global hydrological cycle is essential for the sustainability of freshwater resources on Earth1,2. However, a lack of water level observations for the world's ponds, lakes and reservoirs has limited the quantification of human-managed (reservoir) changes in surface water storage compared to its natural variability3. The global storage variability in surface water bodies and the extent to which it is altered by humans therefore remain unknown. Here we show that 57 per cent of the Earth's seasonal surface water storage variability occurs in human-managed reservoirs. Using measurements from NASA's ICESat-2 satellite laser altimeter, which was launched in late 2018, we assemble an extensive global water level dataset that quantifies water level variability for 227,386 water bodies from October 2018 to July 2020. We find that seasonal variability in human-managed reservoirs averages 0.86 metres, whereas natural water bodies vary by only 0.22 metres. Natural variability in surface water storage is greatest in tropical basins, whereas human-managed variability is greatest in the Middle East, southern Africa and the western USA. Strong regional patterns are also found, with human influence driving 67 per cent of surface water storage variability south of 45 degrees north and nearly 100 per cent in certain arid and semi-arid regions. As economic development, population growth and climate change continue to pressure global water resources4, our approach provides a useful baseline from which ICESat-2 and future satellite missions will be able to track human modifications to the global hydrologic cycle.

Spatiotemporal origin of soil water taken up by vegetation.

Vegetation modulates Earth's water, energy and carbon cycles. How its functions might change in the future largely depends on how it copes with droughts1-4. There is evidence that, in places and times of drought, vegetation shifts water uptake to deeper soil5-7 and rock8,9 moisture as well as groundwater10-12. Here we differentiate and assess plant use of four types of water sources: precipitation in the current month (source 1), past precipitation stored in deeper unsaturated soils and/or rocks (source 2), past precipitation stored in groundwater (source 3, locally recharged) and groundwater from precipitation fallen on uplands via river-groundwater convergence toward lowlands (source 4, remotely recharged). We examine global and seasonal patterns and drivers in plant uptake of the four sources using inverse modelling and isotope-based estimates. We find that (1), globally and annually, 70% of plant transpiration relies on source 1, 18% relies on source 2, only 1% relies on source 3 and 10% relies on source 4; (2) regionally and seasonally, source 1 is only 19% in semi-arid, 32% in Mediterranean and 17% in winter-dry tropics in the driest months; and (3) at landscape scales, source 2, taken up by deep roots in the deep vadose zone, is critical in uplands in dry months, but source 4 is up to 47% in valleys where riparian forests and desert oases are found. Because the four sources originate from different places and times, move at different spatiotemporal scales and respond with different sensitivity to climate and anthropogenic forces, understanding the space and time origins of plant water sources can inform ecosystem management and Earth system models on the critical hydrological pathways linking precipitation to vegetation.

Aridity is expressed in river topography globally.

It has long been suggested that climate shapes land surface topography through interactions between rainfall, runoff and erosion in drainage basins1-4. The longitudinal profile of a river (elevation versus distance downstream) is a key morphological attribute that reflects the history of drainage basin evolution, so its form should be diagnostic of the regional expression of climate and its interaction with the land surface5-9. However, both detecting climatic signatures in longitudinal profiles and deciphering the climatic mechanisms of their development have been challenging, owing to the lack of relevant global data and to the variable effects of tectonics, lithology, land surface properties and human activities10,11. Here we present a global dataset of 333,502 river longitudinal profiles, and use it to explore differences in overall profile shape (concavity) across climate zones. We show that river profiles are systematically straighter with increasing aridity. Through simple numerical modelling, we demonstrate that these global patterns in longitudinal profile shape can be explained by hydrological controls that reflect rainfall-runoff regimes in different climate zones. The most important of these is the downstream rate of change in streamflow, independent of the area of the drainage basin. Our results illustrate that river topography expresses a signature of aridity, suggesting that climate is a first-order control on the evolution of the drainage basin.

Twentieth-century hydroclimate changes consistent with human influence.

Although anthropogenic climate change is expected to have caused large shifts in temperature and rainfall, the detection of human influence on global drought has been complicated by large internal variability and the brevity of observational records. Here we address these challenges using reconstructions of the Palmer drought severity index obtained with data from tree rings that span the past millennium. We show that three distinct periods are identifiable in climate models, observations and reconstructions during the twentieth century. In recent decades (1981 to present), the signal of greenhouse gas forcing is present but not yet detectable at high confidence. Observations and reconstructions differ significantly from an expected pattern of greenhouse gas forcing around mid-century (1950-1975), coinciding with a global increase in aerosol forcing. In the first half of the century (1900-1949), however, a signal of greenhouse-gas-forced change is robustly detectable. Multiple observational datasets and reconstructions using data from tree rings confirm that human activities were probably affecting the worldwide risk of droughts as early as the beginning of the twentieth century.

Geological activity shapes the microbiome in deep-subsurface aquifers by advection.

Subsurface environments host diverse microorganisms in fluid-filled fractures; however, little is known about how geological and hydrological processes shape the subterranean biosphere. Here, we sampled three flowing boreholes weekly for 10 mo in a 1478-m-deep fractured rock aquifer to study the role of fracture activity (defined as seismically or aseismically induced fracture aperture change) and advection on fluid-associated microbial community composition. We found that despite a largely stable deep-subsurface fluid microbiome, drastic community-level shifts occurred after events signifying physical changes in the permeable fracture network. The community-level shifts include the emergence of microbial families from undetected to over 50% relative abundance, as well as the replacement of the community in one borehole by the earlier community from a different borehole. Null-model analysis indicates that the observed spatial and temporal community turnover was primarily driven by stochastic processes (as opposed to deterministic processes). We, therefore, conclude that the observed community-level shifts resulted from the physical transport of distinct microbial communities from other fracture(s) that outpaced environmental selection. Given that geological activity is a major cause of fracture activity and that geological activity is ubiquitous across space and time on Earth, our findings suggest that advection induced by geological activity is a general mechanism shaping the microbial biogeography and diversity in deep-subsurface habitats across the globe.

Flash drought early warning based on the trajectory of solar-induced chlorophyll fluorescence.

Flash drought often leads to devastating effects in multiple sectors and presents a unique challenge for drought early warning due to its sudden onset and rapid intensification. Existing drought monitoring and early warning systems are based on various hydrometeorological variables reaching thresholds of unusually low water content. Here, we propose a flash drought early warning approach based on spaceborne measurements of solar-induced chlorophyll fluorescence (SIF), a proxy of photosynthesis that captures plant response to multiple environmental stressors. Instead of negative SIF anomalies, we focus on the subseasonal trajectory of SIF and consider slower-than-usual increase or faster-than-usual decrease of SIF as an early warning for flash drought onset. To quantify the deviation of SIF trajectory from the climatological norm, we adopt existing formulas for a rapid change index (RCI) and apply the RCI analysis to spatially downscaled 8-d SIF data from GOME-2 during 2007-2018. Using two well-known flash drought events identified by the operational US Drought Monitor (in 2012 and 2017), we show that SIF RCI can produce strong predictive signals of flash drought onset with a lead time of 2 wk to 2 mo and can also predict drought recovery with several weeks of lead time. While SIF RCI shows great early warning potential, its magnitude diminishes after drought onset and therefore cannot reflect the current drought intensity. With its long lead time and direct relevance for agriculture, SIF RCI can support a global early warning system for flash drought and is especially useful over regions with sparse hydrometeorological data.

Microplastics and anthropogenic fibre concentrations in lakes reflect surrounding land use.

Pollution from microplastics and anthropogenic fibres threatens lakes, but we know little about what factors predict its accumulation. Lakes may be especially contaminated because of long water retention times and proximity to pollution sources. Here, we surveyed anthropogenic microparticles, i.e., microplastics and anthropogenic fibres, in surface waters of 67 European lakes spanning 30° of latitude and large environmental gradients. By collating data from >2,100 published net tows, we found that microparticle concentrations in our field survey were higher than previously reported in lakes and comparable to rivers and oceans. We then related microparticle concentrations in our field survey to surrounding land use, water chemistry, and plastic emissions to sites estimated from local hydrology, population density, and waste production. Microparticle concentrations in European lakes quadrupled as both estimated mismanaged waste inputs and wastewater treatment loads increased in catchments. Concentrations decreased by 2 and 5 times over the range of surrounding forest cover and potential in-lake biodegradation, respectively. As anthropogenic debris continues to pollute the environment, our data will help contextualise future work, and our models can inform control and remediation efforts.

Long-term climate and hydrologic regimes shape stream invertebrate community responses to a hurricane disturbance.

Disturbances can produce a spectrum of short- and long-term ecological consequences that depend on complex interactions of the characteristics of the event, antecedent environmental conditions, and the intrinsic properties of resistance and resilience of the affected biological system. We used Hurricane Harvey's impact on coastal rivers of Texas to examine the roles of storm-related changes in hydrology and long-term precipitation regime on the response of stream invertebrate communities to hurricane disturbance. We detected declines in richness, diversity and total abundance following the storm, but responses were strongly tied to direct and indirect effects of long-term aridity and short-term changes in stream hydrology. The amount of rainfall a site received drove both flood duration and flood magnitude across sites, but lower annual rainfall amounts (i.e. aridity) increased flood magnitude and decreased flood duration. Across all sites, flood duration was positively related to the time it took for invertebrate communities to return to a long-term baseline and flood magnitude drove larger invertebrate community responses (i.e. changes in diversity and total abundance). However, invertebrate response per unit flood magnitude was lower in sub-humid sites, potentially because of differences in refuge availability or ecological-evolutionary interactions. Interestingly, sub-humid streams had temporary large peaks in invertebrate total abundance and diversity following recovery period that may be indicative of the larger organic matter pulses expected in these systems because of their comparatively well-developed riparian vegetation. Our findings show that hydrology and long-term precipitation regime predictably affected invertebrate community responses and, thus, our work underscores the important influence of local climate to ecosystem sensitivity to disturbances.

Organic Matter Accumulation and Hydrology as Drivers of Greenhouse Gas Dynamics in Newly Developed Artificial Channels.

Artificial channels, common features of inland waters, have been suggested as significant contributors to methane (CH4) and carbon dioxide (CO2) dynamics and emissions; however, the magnitude and drivers of their CH4 and CO2 emissions (diffusive and ebullitive) remain unclear. They are characterized by reduced flow compared to the donor river, which results in suspended organic matter (OM) accumulation. We propose that in such systems hydrological controls will be reduced and OM accumulation will control emissions by promoting methane production and outgassing. Here, we monitored summertime CH4 and CO2 concentrations and emissions on six newly constructed river-fed artificial channels, from bare riparian mineral soil to lotic channels, under two distinct flow regimes. Chamber-based fluxes were complemented with hydrology, total fluxes (diffusion + ebullition), and suspended OM accumulation assessments. During the first 6 weeks after the flooding, inflowing riverine water dominated the emissions over in-channel contributions. Afterwards, a substantial accumulation of riverine suspended OM (≥50% of the channel's volume) boosted in-channel methane production and led to widespread ebullition 10× higher than diffusive fluxes, regardless of the flow regime. Our finding suggests ebullition as a dominant pathway in these anthropogenic systems, and thus, their impact on regional methane emissions might have been largely underestimated.

Hydrologic Connectivity Regulates Riverine N2O Sources and Dynamics.

Indirect nitrous oxide (N2O) emissions from streams and rivers are a poorly constrained term in the global N2O budget. Current models of riverine N2O emissions place a strong focus on denitrification in groundwater and riverine environments as a dominant source of riverine N2O, but do not explicitly consider direct N2O input from terrestrial ecosystems. Here, we combine N2O isotope measurements and spatial stream network modeling to show that terrestrial-aquatic interactions, driven by changing hydrologic connectivity, control the sources and dynamics of riverine N2O in a mesoscale river network within the U.S. Corn Belt. We find that N2O produced from nitrification constituted a substantial fraction (i.e., >30%) of riverine N2O across the entire river network. The delivery of soil-produced N2O to streams was identified as a key mechanism for the high nitrification contribution and potentially accounted for more than 40% of the total riverine emission. This revealed large terrestrial N2O input implies an important climate-N2O feedback mechanism that may enhance riverine N2O emissions under a wetter and warmer climate. Inadequate representation of hydrologic connectivity in observations and modeling of riverine N2O emissions may result in significant underestimations.