Multi-year time series of daily solute and isotope measurements from three Swiss pre-Alpine catchments.

Time series analyses of solute concentrations in streamwater and precipitation are powerful tools for unraveling the interplay of hydrological and biogeochemical processes at the catchment scale. While such datasets are available for many sites around the world, they often lack the necessary temporal resolution or are limited in the number of solutes they encompass. Here we present a multi-year dataset encompassing daily records of major ions and a range of trace metals in both streamwater and precipitation in three catchments in the northern Swiss Pre-Alps. These time series capture the temporal variability observed in solute concentrations in response to storm events, snow melt, and dry summer conditions. This dataset additionally includes stable water isotope data as an extension of a publicly available isotope dataset collected concurrently at the same locations, and together these data can provide insights into a range of ecohydrological processes and enable a suite of analyses into hydrologic and biogeochemical catchment functioning.

Rapid groundwater decline and some cases of recovery in aquifers globally.

Groundwater resources are vital to ecosystems and livelihoods. Excessive groundwater withdrawals can cause groundwater levels to decline1-10, resulting in seawater intrusion11, land subsidence12,13, streamflow depletion14-16 and wells running dry17. However, the global pace and prevalence of local groundwater declines are poorly constrained, because in situ groundwater levels have not been synthesized at the global scale. Here we analyse in situ groundwater-level trends for 170,000 monitoring wells and 1,693 aquifer systems in countries that encompass approximately 75% of global groundwater withdrawals18. We show that rapid groundwater-level declines (>0.5 m year-1) are widespread in the twenty-first century, especially in dry regions with extensive croplands. Critically, we also show that groundwater-level declines have accelerated over the past four decades in 30% of the world's regional aquifers. This widespread acceleration in groundwater-level deepening highlights an urgent need for more effective measures to address groundwater depletion. Our analysis also reveals specific cases in which depletion trends have reversed following policy changes, managed aquifer recharge and surface-water diversions, demonstrating the potential for depleted aquifer systems to recover.

Advances in Catchment Science, Hydrochemistry, and Aquatic Ecology Enabled by High-Frequency Water Quality Measurements.

High-frequency water quality measurements in streams and rivers have expanded in scope and sophistication during the last two decades. Existing technology allows in situ automated measurements of water quality constituents, including both solutes and particulates, at unprecedented frequencies from seconds to subdaily sampling intervals. This detailed chemical information can be combined with measurements of hydrological and biogeochemical processes, bringing new insights into the sources, transport pathways, and transformation processes of solutes and particulates in complex catchments and along the aquatic continuum. Here, we summarize established and emerging high-frequency water quality technologies, outline key high-frequency hydrochemical data sets, and review scientific advances in key focus areas enabled by the rapid development of high-frequency water quality measurements in streams and rivers. Finally, we discuss future directions and challenges for using high-frequency water quality measurements to bridge scientific and management gaps by promoting a holistic understanding of freshwater systems and catchment status, health, and function.

Impulse Response Functions for Nonlinear, Nonstationary, and Heterogeneous Systems, Estimated by Deconvolution and Demixing of Noisy Time Series.

Impulse response functions (IRFs) are useful for characterizing systems' dynamic behavior and gaining insight into their underlying processes, based on sensor data streams of their inputs and outputs. However, current IRF estimation methods typically require restrictive assumptions that are rarely met in practice, including that the underlying system is homogeneous, linear, and stationary, and that any noise is well behaved. Here, I present data-driven, model-independent, nonparametric IRF estimation methods that relax these assumptions, and thus expand the applicability of IRFs in real-world systems. These methods can accurately and efficiently deconvolve IRFs from signals that are substantially contaminated by autoregressive moving average (ARMA) noise or nonstationary ARIMA noise. They can also simultaneously deconvolve and demix the impulse responses of individual components of heterogeneous systems, based on their combined output (without needing to know the outputs of the individual components). This deconvolution-demixing approach can be extended to characterize nonstationary coupling between inputs and outputs, even if the system's impulse response changes so rapidly that different impulse responses overlap one another. These techniques can also be extended to estimate IRFs for nonlinear systems in which different input intensities yield impulse responses with different shapes and amplitudes, which are then overprinted on one another in the output. I further show how one can efficiently quantify multiscale impulse responses using piecewise linear IRFs defined at unevenly spaced lags. All of these methods are implemented in an R script that can efficiently estimate IRFs over hundreds of lags, from noisy time series of thousands or even millions of time steps.

Four years of daily stable water isotope data in stream water and precipitation from three Swiss catchments.

Time series of the natural isotopic composition (2H, 18O) of precipitation and streamwater can provide important insights into ecohydrological phenomena at the catchment scale. However, multi-year, high-frequency isotope datasets are generally scarce, limiting our ability to study highly dynamic short-term ecohydrological processes. Here we present four years of daily isotope measurements in streamwater and precipitation at the Alp catchment (area 47 km2) in Central Switzerland and two of its tributaries (0.7 km2 and 1.6 km2). This data set reveals short-term responses of streamflow isotopes to precipitation events, which otherwise remain obscured when isotopes are sampled weekly or monthly. The observations span the period June 2015 through May 2019, during which several hydrometeorologic extreme events occurred, including a very dry summer in 2018 and below-average snow accumulation in winter 2016/2017. In addition, we provide daily time series of key hydrometeorological variables that, in combination with the isotope data, can be useful for assessing the robustness of ecohydrological models.

Widespread potential loss of streamflow into underlying aquifers across the USA.

Most rivers exchange water with surrounding aquifers1,2. Where groundwater levels lie below nearby streams, streamwater can infiltrate through the streambed, reducing streamflow and recharging the aquifer3. These 'losing' streams have important implications for water availability, riparian ecosystems and environmental flows4-10, but the prevalence of losing streams remains poorly constrained by continent-wide in situ observations. Here we analyse water levels in 4.2 million wells across the contiguous USA and show that nearly two-thirds (64 per cent) of them lie below nearby stream surfaces, implying that these streamwaters will seep into the subsurface if it is sufficiently permeable. A lack of adequate permeability data prevents us from quantifying the magnitudes of these subsurface flows, but our analysis nonetheless demonstrates widespread potential for streamwater losses into underlying aquifers. These potentially losing rivers are more common in drier climates, flatter landscapes and regions with extensive groundwater pumping. Our results thus imply that climatic factors, geological conditions and historic groundwater pumping jointly contribute to the widespread risk of streams losing flow into surrounding aquifers instead of gaining flow from them. Recent modelling studies10 have suggested that losing streams could become common in future decades, but our direct observations show that many rivers across the USA are already potentially losing flow, highlighting the importance of coordinating groundwater and surface water policy.

Groundwater level observations in 250,000 coastal US wells reveal scope of potential seawater intrusion.

Seawater intrusion into coastal aquifers can increase groundwater salinity beyond potable levels, endangering access to freshwater for millions of people. Seawater intrusion is particularly likely where water tables lie below sea level, but can also arise from groundwater pumping in some coastal aquifers with water tables above sea level. Nevertheless, no nation-wide, observation-based assessment of the scope of potential seawater intrusion exists. Here we compile and analyze ~250,000 coastal groundwater-level observations made since the year 2000 in the contiguous United States. We show that the majority of observed groundwater levels lie below sea level along more than 15% of the contiguous coastline. We conclude that landward hydraulic gradients characterize a substantial fraction of the East Coast (>18%) and Gulf Coast (>17%), and also parts of the West Coast where groundwater pumping is high. Sea level rise, coastal land subsidence, and increasing water demands will exacerbate the threat of seawater intrusion.

Climate models can correctly simulate the continuum of global-average temperature variability.

Climate records exhibit scaling behavior with large exponents, resulting in larger fluctuations at longer timescales. It is unclear whether climate models are capable of simulating these fluctuations, which draws into question their ability to simulate such variability in the coming decades and centuries. Using the latest simulations and data syntheses, we find agreement for spectra derived from observations and models on timescales ranging from interannual to multimillennial. Our results confirm the existence of a scaling break between orbital and annual peaks, occurring around millennial periodicities. That both simple and comprehensive ocean-atmosphere models can reproduce these features suggests that long-range persistence is a consequence of the oceanic integration of both gradual and abrupt climate forcings. This result implies that Holocene low-frequency variability is partly a consequence of the climate system's integrated memory of orbital forcing. We conclude that climate models appear to contain the essential physics to correctly simulate the spectral continuum of global-mean temperature; however, regional discrepancies remain unresolved. A critical element of successfully simulating suborbital climate variability involves, we hypothesize, initial conditions of the deep ocean state that are consistent with observations of the recent past.

Branching geometry of valley networks on Mars and Earth and its implications for early Martian climate.

Mars' surface bears the imprint of valley networks formed billions of years ago. Whether these networks were formed by groundwater sapping, ice melt, or fluvial runoff has been debated for decades. These different scenarios have profoundly different implications for Mars' climatic history and thus for its habitability in the distant past. Recent studies on Earth revealed that valley networks in arid landscapes with more surface runoff branch at narrower angles, while in humid environments with more groundwater flow, branching angles are much wider. We find that valley networks on Mars generally tend to branch at narrow angles similar to those found in arid landscapes on Earth. This result supports the inference that Mars once had an active hydrologic cycle and that Mars' valley networks were formed primarily by overland flow erosion, with groundwater seepage playing only a minor role.

Insensitivity of Tree-Ring Growth to Temperature and Precipitation Sharpens the Puzzle of Enhanced Pre-Eruption NDVI on Mt. Etna (Italy).

On Mt. Etna (Italy), an enhanced Normalized Difference in Vegetation Index (NDVI) signature was detected in the summers of 2001 and 2002 along a distinct line where, in November 2002, a flank eruption subsequently occurred. These observations suggest that pre-eruptive volcanic activity may have enhanced photosynthesis along the future eruptive fissure. If a direct relation between NDVI and future volcanic eruptions could be established, it would provide a straightforward and low-cost method for early detection of upcoming eruptions. However, it is unclear if, or to what extent, the observed enhancement of NDVI can be attributed to volcanic activity prior to the subsequent eruption. We consequently aimed at determining whether an increase in ambient temperature or additional water availability owing to the rise of magma and degassing of water vapour prior to the eruption could have increased photosynthesis of Mt. Etna's trees. Using dendro-climatic analyses we quantified the sensitivity of tree ring widths to temperature and precipitation at high elevation stands on Mt. Etna. Our findings suggest that tree growth at high elevation on Mt. Etna is weakly influenced by climate, and that neither an increase in water availability nor an increase in temperature induced by pre-eruptive activity is a plausible mechanism for enhanced photosynthesis before the 2002/2003 flank eruption. Our findings thus imply that other, yet unknown, factors must be sought as causes of the pre-eruption enhancement of NDVI on Mt. Etna.

Marine Primary Productivity as a Potential Indirect Source of Selenium and Other Trace Elements in Atmospheric Deposition.

Atmospheric processes play an important role in the supply of the trace element selenium (Se) as well as other essential trace elements to terrestrial environments, mainly via wet deposition. Here we investigate whether the marine biosphere can be identified as a source of Se and of other trace elements in precipitation samples. We used artificial neural network (ANN) modeling and other statistical methods to analyze relationships between a high-resolution atmospheric deposition chemistry time series (March 2007-January 2009) from Plynlimon (UK) and exposure of air masses to marine chlorophyll a and to other source proxies. Using ANN sensitivity analyses, we found that higher air mass exposure to marine productivity leads to higher concentrations of dissolved organic carbon (DOC) in rainfall. Furthermore, marine productivity was found to be an important but indirect factor in controlling Se as well as vanadium (V), cobalt (Co), nickel (Ni), zinc (Zn), and aluminum (Al) concentrations in atmospheric deposition, likely via scavenging by organic compounds derived from marine organisms. Marine organisms may thus play an indirect but important role in the delivery of trace elements to terrestrial environments and food chains.

Sensors in the Stream: The High-Frequency Wave of the Present.

New scientific understanding is catalyzed by novel technologies that enhance measurement precision, resolution or type, and that provide new tools to test and develop theory. Over the last 50 years, technology has transformed the hydrologic sciences by enabling direct measurements of watershed fluxes (evapotranspiration, streamflow) at time scales and spatial extents aligned with variation in physical drivers. High frequency water quality measurements, increasingly obtained by in situ water quality sensors, are extending that transformation. Widely available sensors for some physical (temperature) and chemical (conductivity, dissolved oxygen) attributes have become integral to aquatic science, and emerging sensors for nutrients, dissolved CO2, turbidity, algal pigments, and dissolved organic matter are now enabling observations of watersheds and streams at time scales commensurate with their fundamental hydrological, energetic, elemental, and biological drivers. Here we synthesize insights from emerging technologies across a suite of applications, and envision future advances, enabled by sensors, in our ability to understand, predict, and restore watershed and stream systems.

Fractal water quality fluctuations spanning the periodic table in an intensively farmed watershed.

Recently developed measurement technologies can monitor surface water quality almost continuously, creating high-frequency multiparameter time series and raising the question of how best to extract insights from such rich data sets. Here we use spectral analysis to characterize the variability of water quality at the AgrHys observatory (Western France) over time scales ranging from 20 min to 12 years. Three years of daily sampling at the intensively farmed Kervidy-Naizin watershed reveal universal 1/f scaling for all 36 solutes, yielding spectral slopes of 1.05 ± 0.11 (mean ± standard deviation). These 36 solute concentrations show varying degrees of annual cycling, suggesting different controls on watershed export processes. Twelve years of daily samples of SO4, NO3, and dissolved organic carbon (DOC) show that 1/f scaling does not continue at frequencies below 1/year in those constituents, whereas a 12-year daily record of Cl shows a general 1/f trend down to the lowest measurable frequencies. Conversely, approximately 12 months of 20 min NO3 and DOC measurements show that at frequencies higher than 1/day, the spectra of these solutes steepen to slopes of roughly 3, and at time scales shorter than 2-3 h, the spectra flatten to slopes near zero, reflecting analytical noise. These results confirm and extend the recent discovery of universal fractal 1/f scaling in water quality at the relatively pristine Plynlimon watershed in Wales, further demonstrating the importance of advective-dispersive transport mixing in catchments. However, the steeper scaling at subdaily time scales suggests additional short-term damping of solute concentrations, potentially due to in-stream or riparian processes.

Universal fractal scaling in stream chemistry and its implications for solute transport and water quality trend detection.

The chemical dynamics of lakes and streams affect their suitability as aquatic habitats and as water supplies for human needs. Because water quality is typically monitored only weekly or monthly, however, the higher-frequency dynamics of stream chemistry have remained largely invisible. To illuminate a wider spectrum of water quality dynamics, rainfall and streamflow were sampled in two headwater catchments at Plynlimon, Wales, at 7-h intervals for 1-2 y and weekly for over two decades, and were analyzed for 45 solutes spanning the periodic table from H(+) to U. Here we show that in streamflow, all 45 of these solutes, including nutrients, trace elements, and toxic metals, exhibit fractal 1/f(α) scaling on time scales from hours to decades (α = 1.05 ± 0.15, mean ± SD). We show that this fractal scaling can arise through dispersion of random chemical inputs distributed across a catchment. These 1/f time series are non-self-averaging: monthly, yearly, or decadal averages are approximately as variable, one from the next, as individual measurements taken hours or days apart, defying naive statistical expectations. (By contrast, stream discharge itself is nonfractal, and self-averaging on time scales of months and longer.) In the solute time series, statistically significant trends arise much more frequently, on all time scales, than one would expect from conventional t statistics. However, these same trends are poor predictors of future trends-much poorer than one would expect from their calculated uncertainties. Our results illustrate how 1/f time series pose fundamental challenges to trend analysis and change detection in environmental systems.

High-frequency water quality time series in precipitation and streamflow: from fragmentary signals to scientific challenge.

Eighteen months of 7-hourly analyses of rainfall and stream water chemistry are presented, spanning a wide range of chemical determinands and building on over 20 years of weekly records for the moorland headwaters of the river Severn. The high-frequency time series data show that hydrochemical responses to major hydrological and biological drivers of short-term variability in rainfall and rivers are not captured by conventional low-frequency monitoring programmes. A wealth of flow related, flow independent, diurnal, seasonal and annual fluctuations indicate a cacophony of interactions within the catchment and stream. The complexity of the chemical dynamics is visually obvious, although there appears to be no clear way of translating this complexity into a simple algorithm. The work provides a proof of concept for the complex structure of catchment functioning revealed by extensive high-frequency measurements coupled with high analytical sensitivity and reproducibility. It provides new insights into hydrogeochemical functioning and a novel resource for catchment modelling.

Quantifying remediation effectiveness under variable external forcing using contaminant rating curves.

Remediation efforts are typically assessed through before-and-after comparisons of contaminant concentrations or loads. These comparisons can be misleading when external drivers, such as weather conditions, differ between the pre- and postremediation monitoring periods. Here, we show that remediation effectiveness may be better assessed by comparing pre- and postremediation contaminant rating curves, which permit "all else equal" comparisons of pre- and postremediation contaminant concentrations and loads under at any specified external forcing. We illustrate this approach with a remediation case study at an abandoned mercury mine in Northern California. Measured mercury loads in the stream draining the mine site were a factor of 1000 smaller after the remediation than before, superficially suggesting that the cleanup was 99.9% effective, but rainstorms were weaker and less frequent during the postremediation monitoring period. Our analysis shows that this difference in weather conditions alone reduced mercury loads at our site by a factor of 73-85, with a further factor of 12.6-14.5 being attributable to the remediation itself, implying that the cleanup was 92-93% (rather than 99.9%) effective. Our results illustrate the need to account for external confounding drivers when assessing remediation efforts, particularly in systems with highly episodic forcing.