Explore the vast range of titles available.

Headwaters are hotspots of carbon dioxide (CO2) evasion from rivers. While emerging evidence suggests that groundwater contributes disproportionately to CO2 in headwater streams, the processes of CO2 delivery to streams and subsequent evasion to the atmosphere remain largely unknown. Here we show the variability of CO2 input and evasion fluxes based on coupled measurements of dissolved CO2 along streams and in adjacent groundwater from two headwater catchments of the tropical and temperate zones. We find that the processes can be highly localized in both space and time. Spatially, they are significantly influenced by heterogeneities in the subsurface and stream landscape; temporally, they predominately occur during the transient activation of connected subsurface water flows. We highlight sharp increases and decreases in the stream CO2 flux, and suggest that current models fail to capture the true magnitude of CO2 evasion. The high spatial and temporal variability of CO2 input from groundwater and evasion to the atmosphere makes accurate assessment of CO2 evasion fluxes difficult, and will require a collaborative effort by catchment hydrologists and aquatic ecologists to fully understand the contribution of groundwater to stream CO2 emissions.

Mountainous headwater streams are sustained by both snowmelt‐driven streamflow and groundwater discharge in the Upper Colorado River Basin. However, predicting headwater stream discharge magnitude and peak flow timing is challenging in mountainous terrains, where snowmelt rates vary with vegetation type and elevation, and heterogeneous subsurface physical properties influence groundwater storage and its release. We used a model‐data integration approach to investigate the roles of snowmelt and subsurface structure in stream discharge and groundwater level. We ran an ensemble of 100 integrated surface‐subsurface hydrologic models for a mountainous headwater catchment near Crested Butte, Colorado, USA. We also evaluated and calibrated these models against observed data sets, including snow depth measurements using distributed temperature probes, stream discharge, and groundwater levels. Calibration with multiple data sources using neural density estimators has further constrained uncertainty in subsurface properties and snowmelt rates. Results indicated that observed slower snowmelt rates in evergreen forests delayed the peak flow and baseflow onset. In upstream areas with lower subsurface permeability, water was stored within the subsurface but was not released as interflow or shallow groundwater flow, and thereby not contributing to downstream streamflow during recession limb periods. Double peaks in groundwater occurred in areas with spatial subsurface heterogeneity, in our case due to the contrast between granodiorite and Mancos shale. These process‐based insights into groundwater and snowmelt dynamics in mountainous headwaters will help improve predictions of headwater hydrology.

The Three‐River Headwater Region, also known as China's water tower, is highly sensitive to climate change and has experienced profound hydrological alterations in the last few decades. This study assessed the potential impacts of climate change on all the important hydrological components such as precipitation, evapotranspiration, streamflow, snow‐melt flow, and soil moisture (SM) content in the region. For this, climate data (i.e., temperature, precipitation, relative humidity, and windspeed) of three Global Climate Models (i.e., CanESM5, MPI‐ESM1.2‐HR, and NorESM2‐MM) was downscaled with the Statistical DownScaling Model (SDSM) and their ensemble was forced into a hydrological model to simulate the hydrological processes for 1981–2100. The screening process, which is central to all downscaling techniques, is very subjective in the SDSM. Therefore, we developed a quantitative screening approach by modifying the method applied by Mahmood and Babel (2013, https://doi.org/10.1007/s00704‐012‐0765‐0) for the selection of a set of logical predictors to cope with multi‐collinearity and their ranking. The analyses were performed for the near future period (NFP, 2021–2060) and far future period (FFP, 2061–2100) relative to the baseline period (BLP, 1981–2020). The results showed that the region will be hotter and wetter in the future, with intensive and frequent floods. For example, temperature, precipitation, evapotranspiration, and streamflow will increase by 1.0–1.5 (1–1.9)°C, 9–21 (15–27)%, 6–17 (9–29)%, and 9–46 (22–64)% in the NFP and by 2.0–2.8 (2.7–4.6)°C, 16–40 (43–87)%, 11–31 (24–73)%, and 20–95 (60–198)% in the FFP, respectively, under SSP2‐4.5 (SSP5‐8.5). Similar projections were explored for other hydrological components. Among all, surface flow showed an unprecedented increase (500%–1,000%) in the FFP. Peak flows will be much higher and will shift forward, and snowmelt will start earlier in the future. The results of the present study can be a good source for understanding the hydrological cycle and be used for the planning and management of water resources of the highly elevated and complex region of the Qinghai Tibetan Plateau. Plain Language Summary The Three‐River Headwater Region, which is also known as the Sanjiangyuan in Chinese, is located in Qinghai Tibetan Plateau, China. It is considered the water tower of China because it is the source of three giant rivers the Yangtze, Yellow, and Lancang (Mekong). However, its water resources (hydrological cycle) are very sensitive and vulnerable to changing climate. Therefore, we assessed the potential impact of climate change on all the important hydrological components such as precipitation, streamflow, snow melt flow, surface flow, baseflow, soil moisture (SM), and changes in terrestrial water storage. Previous studies mainly focused on precipitation, streamflow, and SM. Global Climate Models (GCMs) are the main tool to assess the future changes in hydrological components under changing climate. Since GCMs have a coarse spatial resolution and biases in their outputs, a statistical downscaling model (SDSM) was applied to fix these issues and used to generate climate data (e.g., temperature and precipitation) for the future (2021–2100) under two scenarios (i.e., SSP2‐4.5 and SSP5‐8.5). These scenarios represent the global development and greenhouse gas emissions in the future. SSP2‐4.5 scenario typically involves moderate greenhouse gas emissions reduction efforts and some adaptation and mitigation measures to address climate change impacts, and SSP5‐8.5 represents high greenhouse gas emissions and limited efforts to mitigate climate change impacts. The screening process, which is central to all downscaling techniques, is very subjective in the SDSM. Therefore, we developed a quantitative screening approach by modifying the method applied by Mahmood and Babel (2013, https://doi.org/10.1007/s00704‐012‐0765‐0) for the selection of a set of logical predictors to cope with multi‐collinearity and their ranking. The downscaled future climate data was used as input to run a hydrological model (HEC‐HMS) to generate hydrological components under both scenarios. The future changes in the hydrological components were obtained for 2021–2060 and 2061–2100 with respect to the baseline period 1981–2020. The results showed that the region will be hotter and wetter in the future, with intensive and frequent floods. Almost all components are expected to increase in the future under both scenarios. Among all, surface flow showed an unprecedented increase (500%–1,000%) in the second half of the twenty‐first century (2061–2100). Peak flows are expected to be much higher than the present conditions and to shift forward. Snowmelt will start earlier in the future. This study will be very useful in understanding the hydrological cycle and can be used by policymakers, planners, and stakeholders for proactive adaptation strategies such as water resources planning and management, investments in water infrastructure, land use planning, ecosystem restoration, and community resilience‐building initiatives to mitigate potential risks. Key Points The region will be hotter and wetter, with intensive and frequent floods The hydrological components are expected to increase in the future Surface flow showed an unprecedented increase of 500%–1,000%

Groundwater plays a critical role in the functioning of alpine hydrological systems, and its importance is expected to increase under climate change. However, quantification of groundwater processes in these systems remains highly uncertain. Terrestrial time‐lapse gravimetry (TLG) is a geophysical and geodetic technique whose measured variable (g $g$) varies directly with groundwater storage changes (GWSC). TLG is thus well suited to applications in alpine environments, which often lack subsurface monitoring infrastructure. Here, we use TLG to measure GWSC in an alpine headwater catchment over snow‐free and snow accumulation/melt periods. We compare absolute‐referenced Δg ${\\Delta }g$ measurements with locally referenced (relative) ones and investigate the advantages of mobile surveys using the most recent generation of relative gravimeters. The results reveal a spatially variable, dynamic system with greater GWSC magnitudes in higher‐elevation regions and demonstrate the untapped utility of TLG for alpine groundwater investigations.

The wetland ecosystem in the “Three-River Headwaters” (TRH) region plays an irreplaceable role in water source conservation, run-off adjustment and biodiversity maintenance. In recent years, assessment of wetland resources affected by climate changes has aroused enormous attention, since it can further protect wetland resources and provide a scientific basis for decision makers. In this study, wetland changes and its response to climate changes in the TRH region from the early 1990s to 2012 were analyzed by remote sensing (RS) image interpretation and climate change trend analysis. The results showed that wetlands occupied 6.3% of the total land area in 2012, and swamps, streams & rivers and lakes were the dominant wetland types in the TRH region. Since the early 1990s, wetlands have undergone great changes, and total wetland area increased by 260.57 km2 (1.17%). Lakes, reservoir & ponds took on continuous increasing trend, but swamps, streams & rivers had a continuous decreasing trend. On the other hand, the wetland area in the Yangtze River basin showed an overall increasing trend, while in the Yellow River and Langcang River basins, it decreased in general. The climate turned from Warm-Dry to Warm-Wet. The average temperature and precipitation increased by 0.91 °C and 101.99 mm, respectively, from 1990 to 2012, and the average humidity index (HI) increased by 0.06 and showing an upward trend and a shifting of the dividing line towards the northwest in both the areas of semi-humid and semi-arid zone. The correlation analysis of wetland changes with meteorological factors from 1990 to 2012 indicated that the regional humidity differences and the interannual variation trend, caused by the change of precipitation and evaporation, was the main driving factor for the dynamic variation of wetland change in the TRH region. In the general, the increase of HI in the THR region since the 1990s, especially in the western TRH region, contributed to wetland increase continuously. The conclusions of this study will provide some scientific references for the management and protection of wetlands in the TRH region, especially for restoration, reconstruction and conservation of degradation wetland.

Sustained glacier melt in the Himalayas has gradually spawned more than 5,000 glacier lakes that are dammed by potentially unstable moraines. When such dams break, glacier lake outburst floods (GLOFs) can cause catastrophic societal and geomorphic impacts. We present a robust probabilistic estimate of average GLOFs return periods in the Himalayan region, drawing on 5.4 billion simulations. We find that the 100-y outburst flood has an average volume of 33.5+3.7/−3.7 × 10⁶ m³ (posterior mean and 95% highest density interval [HDI]) with a peak discharge of 15,600+2,000/−1,800 m³·s−1. Our estimated GLOF hazard is tied to the rate of historic lake outbursts and the number of present lakes, which both are highest in the Eastern Himalayas. There, the estimated 100-y GLOF discharge (∼14,500 m³·s−1) is more than 3 times that of the adjacent Nyainqentanglha Mountains, and at least an order of magnitude higher than in the Hindu Kush, Karakoram, and Western Himalayas. The GLOF hazard may increase in these regions that currently have large glaciers, but few lakes, if future projected ice loss generates more unstable moraine-dammed lakes than we recognize today. Flood peaks from GLOFs mostly attenuate within Himalayan headwaters, but can rival monsoon-fed discharges in major rivers hundreds to thousands of kilometers downstream. Projections of future hazard from meteorological floods need to account for the extreme runoffs during lake outbursts, given the increasing trends in population, infrastructure, and hydropower projects in Himalayan headwaters.

Flowing stream networks dynamically extend and retract, both seasonally and in response to precipitation events. These network dynamics can dramatically alter the drainage density and thus the length of subsurface flow pathways to flowing streams. We mapped flowing stream networks in a small Swiss headwater catchment during different wetness conditions and estimated their effects on the distribution of travel times to the catchment outlet. For each point in the catchment, we determined the subsurface transport distance to the flowing stream based on the surface topography and determined the surface transport distance along the flowing stream to the outlet. We combined the distributions of these travel distances with assumed surface and subsurface flow velocities to estimate the distribution of travel times to the outlet. These calculations show that the extension and retraction of the stream network can substantially change the mean travel time and the shape of the travel time distribution. During wet conditions with a fully extended flowing stream network, the travel time distribution was strongly skewed to short travel times, but as the network retracted during dry conditions, the distribution of the travel times became more uniform. Stream network dynamics are widely ignored in catchment models, but our results show that they need to be taken into account when modeling solute transport and interpreting travel time distributions.

Boreal streams represent potentially important conduits for the exchange of carbon dioxide (CO(2)) between terrestrial ecosystems and the atmosphere. The gas transfer coefficient of CO(2) (K(CO2)) is a key variable in estimating this source strength, but the scarcity of measured values in lotic systems creates a risk of incorrect flux estimates even when stream gas concentrations are well known. This study used 114 independent measurements of K(CO2) from 14 stream reaches in a boreal headwater system to determine and predict spatiotemporal variability in K(CO2). The K(CO2) values ranged from 0.001 to 0.207 min(-1) across the 14 sites. Median K(CO2) for a specific site was positively correlated with the slope of the stream reach, with higher gas transfer coefficients occurring in steeper stream sections. Combining slope with a width/depth index of the stream reach explained 83% of the spatial variability in K(CO2). Temporal variability was more difficult to predict and was strongly site specific. Variation in K(CO2), rather than pCO(2), was the main determinant of stream CO(2) evasion. Applying published generalized gas transfer velocities produced an error of up to 100% in median instantaneous evasion rates compared to the use of actual measured K(CO2) values from our field study. Using the significant relationship to local slope, the median K(CO2) was predicted for 300,000 km of watercourses (ranging in stream order 1-4) in the forested landscape of boreal/nemoral Sweden. The range in modeled stream order specific median K(CO2) was 0.017-0.028 min(-1) and there was a clear gradient of increasing K(CO2) with lower stream order. We conclude that accurate regional scale estimates of CO(2) evasion fluxes from running waters are possible, but require a good understanding of gas exchange at the water surface.

The Mars 2020 mission will seek the signs of ancient life on Mars and will identify, prepare, document, and cache a set of samples for possible return to Earth by a follow-on mission. Mars 2020 and its Perseverance rover thus link and further two long-held goals in planetary science: a deep search for evidence of life in a habitable extraterrestrial environment, and the return of martian samples to Earth for analysis in terrestrial laboratories. The Mars 2020 spacecraft is based on the design of the highly successful Mars Science Laboratory and its Curiosity rover, but outfitted with a sophisticated suite of new science instruments. Ground-penetrating radar will illuminate geologic structures in the shallow subsurface, while a multi-faceted weather station will document martian environmental conditions. Several instruments can be used individually or in tandem to map the color, texture, chemistry, and mineralogy of rocks and regolith at the meter scale and at the submillimeter scale. The science instruments will be used to interpret the geology of the landing site, to identify habitable paleoenvironments, to seek ancient textural, elemental, mineralogical and organic biosignatures, and to locate and characterize the most promising samples for Earth return. Once selected, ∼35 samples of rock and regolith weighing about 15 grams each will be drilled directly into ultraclean and sterile sample tubes. Perseverance will also collect blank sample tubes to monitor the evolving rover contamination environment. In addition to its scientific instruments, Perseverance hosts technology demonstrations designed to facilitate future Mars exploration. These include a device to generate oxygen gas by electrolytic decomposition of atmospheric carbon dioxide, and a small helicopter to assess performance of a rotorcraft in the thin martian atmosphere. Mars 2020 entry, descent, and landing (EDL) will use the same approach that successfully delivered Curiosity to the martian surface, but with several new features that enable the spacecraft to land at previously inaccessible landing sites. A suite of cameras and a microphone will for the first time capture the sights and sounds of EDL. Mars 2020’s landing site was chosen to maximize scientific return of the mission for astrobiology and sample return. Several billion years ago Jezero crater held a 40 km diameter, few hundred-meter-deep lake, with both an inflow and an outflow channel. A prominent delta, fine-grained lacustrine sediments, and carbonate-bearing rocks offer attractive targets for habitability and for biosignature preservation potential. In addition, a possible volcanic unit in the crater and impact megabreccia in the crater rim, along with fluvially-deposited clasts derived from the large and lithologically diverse headwaters terrain, contribute substantially to the science value of the sample cache for investigations of the history of Mars and the Solar System. Even greater diversity, including very ancient aqueously altered rocks, is accessible in a notional rover traverse that ascends out of Jezero crater and explores the surrounding Nili Planum. Mars 2020 is conceived as the first element of a multi-mission Mars Sample Return campaign. After Mars 2020 has cached the samples, a follow-on mission consisting of a fetch rover and a rocket could retrieve and package them, and then launch the package into orbit. A third mission could capture the orbiting package and return it to Earth. To facilitate the sample handoff, Perseverance could deposit its collection of filled sample tubes in one or more locations, called depots, on the planet’s surface. Alternatively, if Perseverance remains functional, it could carry some or all the samples directly to the retrieval spacecraft. The Mars 2020 mission and its Perseverance rover launched from the Eastern Range at Cape Canaveral Air Force Station, Florida, on July 30, 2020. Landing at Jezero Crater will occur on Feb 18, 2021 at about 12:30 PM Pacific Time.