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Floodplain societies decide whether to protect themselves against floods (fight), live with floods (adapt), or adopt an approach that represents some combination of the two. The formation of a levee system is an important factor in determining whether a society fights or adapts to floods; however, these factors have been considered fixed boundaries in previous studies in human–flood interactions. We analyze a levee system transformation process covering the past century, from the indigenous ring-type levee system with floods to modern continuous levees against floods in the Kiso River basin in Japan by applying a historical sociohydrological approach. The results show degradation processes of the indigenous levee system and traditional communities alongside the installation of modern continuous levees, and a trade-off relationship was observed between the lengths of both. There are interactions between the levee systems and the human–water system through various water uses and different-scale components, and the dynamics within the region are connected to external socioeconomic trends through the installed modern levees and institutions. [ABSTRACT FROM AUTHOR]

Large sample datasets are transforming the catchment sciences, but there are few off-the-shelf stream water chemistry datasets with complementary atmospheric deposition, streamflow, meteorology, and catchment physiographic attributes. The existing CAMELS (Catchment Attributes and Meteorology for Large-sample Studies) dataset includes data on topography, climate, streamflow, land cover, soil, and geology across the continental US. With CAMELS-Chem, we pair these existing attribute data for 516 catchments with atmospheric deposition data from the National Atmospheric Deposition Program and water chemistry and instantaneous discharge data from the US Geological Survey over the period from 1980 through 2018 in a relational database and corresponding dataset. The data include 18 common stream water chemistry constituents: Al, Ca, Cl, dissolved organic carbon, total organic carbon, HCO 3 , K, Mg, Na, total dissolved N, total organic N, NO 3 , dissolved oxygen, pH (field and lab), Si, SO 4 , and water temperature. Annual deposition loads and concentrations include hydrogen, NH 4 , NO 3 , total inorganic N, Cl, SO 4 , Ca, K, Mg, and Na. We demonstrate that CAMELS-Chem water chemistry data are sampled effectively across climates, seasons, and discharges for trend analysis and highlight the coincident sampling of stream constituents for process-based understanding. To motivate their use by the larger scientific community across a variety of disciplines, we show examples of how these publicly available datasets can be applied to trend detection and attribution, biogeochemical process understanding, and new hypothesis generation via data-driven techniques. [ABSTRACT FROM AUTHOR]

Spatially explicit mathematical models are key to a mechanistic understanding of environmental processes in rivers. Such models necessitate extended information on networks' morphology, which is often retrieved from geographic information system (GIS) software, thus hindering the establishment of replicable script-based workflows. Here I present rivnet, an R package for GIS-free extraction and analysis of river networks based on digital elevation models (DEMs). The package exploits TauDEM's flow direction algorithm in user-provided or online accessible DEMs, and allows for computing covariate values and assigning hydraulic variables across any network node. The package is designed so as to require minimal user input while allowing for customization for experienced users. It is specifically intended for application in models of ecohydrological, ecological or biogeochemical processes in rivers. As such, rivnet aims to make river network analysis accessible to users unfamiliar with GIS-based and geomorphological methods and therefore enhance the use of spatially explicit models in rivers. [ABSTRACT FROM AUTHOR]

Accurate, unbiased wetland inventories are critical to monitor and protect wetlands from future harm or land conversion. However, most wetland inventories are constructed through manual image interpretation or automated classification of multi-band imagery and are biased towards wetlands that are easy to directly detect in aerial and satellite imagery. Wetlands that are obscured by forest canopy, that occur ephemerally, and that have no visible standing water are, therefore, often missing from wetland maps. To aid in the detection of these cryptic wetlands, we developed the Wetland Intrinsic Potential (WIP) tool, based on a wetland-indicator framework commonly used on the ground to detect wetlands through the presence of hydrophytic vegetation, hydrology, and hydric soils. Our tool uses a random forest model with spatially explicit input variables that represent all three wetland indicators, including novel multi-scale topographic indicators that represent the processes that drive wetland formation, to derive a map of wetland probability. With the ability to include multi-scale topographic indicators that help identify cryptic wetlands, the WIP tool can identify areas conducive to wetland formation while providing a flexible approach that can be adapted to diverse landscapes. For a study area in the Hoh River watershed in western Washington, USA, classification of the output probability with a threshold of 0.5 provided an overall accuracy of 91.97 %. Compared to the National Wetlands Inventory, the classified WIP tool output identified over 2 times the wetland area and reduced errors of omission from 47.5 % to 14.1 % but increased errors of commission from 1.9 % to 10.5 %. The WIP tool is implemented as an ArcGIS toolbox using a combination of R and Python scripts. [ABSTRACT FROM AUTHOR]

The National Aeronautics and Space Administration (NASA) has launched a new initiative, the Open-Source Science Initiative (OSSI), to enable and support science towards openness. The OSSI supports open-source software development and dissemination. In this work, we present NASAaccess, which is an open-source software package and web-based environmental modeling application for earth observation data accessing, reformatting, and presenting quantitative data products. The main objective of developing the NASAaccess platform is to facilitate exploration, modeling, and understanding of earth data for scientists, stakeholders, and concerned citizens whose objectives align with the new OSSI goals. The NASAaccess platform is available as software packages (i.e., the R and conda packages) as well as an interactive-format web-based environmental modeling application for earth observation data developed with Tethys Platform. NASAaccess has been envisioned as lowering the technical barriers and simplifying the process of accessing scalable distributed computing resources and leveraging additional software for data and computationally intensive modeling frameworks. Specifically, NASAaccess has been developed to meet the need for seamless earth observation remote-sensing and climate data ingestion into various hydrological modeling frameworks. Moreover, NASAaccess is also contributing to keeping interested parties and stakeholders engaged with environmental modeling, accessing the information available in various remote-sensing products. NASAaccess' current capabilities cover various NASA datasets and products that include the Global Precipitation Measurement (GPM) data products, the Global Land Data Assimilation System (GLDAS) land surface states and fluxes, and the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) Coupled Model Intercomparison Project Phase 5 (CMIP5) and Coupled Model Intercomparison Project Phase 6 (CMIP6) climate change dataset products. [ABSTRACT FROM AUTHOR]

Transit time distributions (TTDs) of streamflow are useful descriptors for understanding flow and solute transport in catchments. Catchment-scale TTDs can be modeled using tracer data (e.g. oxygen isotopes, such as δ18O) in inflow and outflows by employing StorAge Selection (SAS) functions. However, tracer data are often sparse in space and time, so they need to be interpolated to increase their spatiotemporal resolution. Moreover, SAS functions can be parameterized with different forms, but there is no general agreement on which one should be used. Both of these aspects induce uncertainty in the simulated TTDs, and the individual uncertainty sources as well as their combined effect have not been fully investigated. This study provides a comprehensive analysis of the TTD uncertainty resulting from 12 model setups obtained by combining different interpolation schemes for δ18O in precipitation and distinct SAS functions. For each model setup, we found behavioral solutions with satisfactory model performance for in-stream δ18O (KGE > 0.55, where KGE refers to the Kling–Gupta efficiency). Differences in KGE values were statistically significant, thereby showing the relevance of the chosen setup for simulating TTDs. We found a large uncertainty in the simulated TTDs, represented by a large range of variability in the 95 % confidence interval of the median transit time, varying at the most by between 259 and 1009 d across all tested setups. Uncertainty in TTDs was mainly associated with the temporal interpolation of δ18O in precipitation, the choice between time-variant and time-invariant SAS functions, flow conditions, and the use of nonspatially interpolated δ18O in precipitation. We discuss the implications of these results for the SAS framework, uncertainty characterization in TTD-based models, and the influence of the uncertainty for water quality and quantity studies. [ABSTRACT FROM AUTHOR]

Wetlands and reservoirs are important water flow and storage regulators in a river basin; therefore, they can play a crucial role in mitigating flood and hydrological drought risks. Despite the advancement of river basin theory and modeling, our knowledge is still limited about the extent to which these two regulators could perform such a role, especially under future climate extremes. To improve our understanding, we first coupled wetlands and reservoir operations into a semi-spatially explicit hydrological model and then applied it in a case study involving a large river basin in northeast China. The projection of future floods and hydrological droughts was performed using the hydrological model during different periods (near future: 2026–2050, middle century: 2051–2075, and end century: 2076–2100) under five future climate change scenarios. We found that the risk of future floods and hydrological droughts can vary across different periods – in particular, it will experience relatively large increases and slight decreases. This large river basin will experience flood events of longer duration, with larger peak flows and volume, and of enhanced flashiness compared to the historical period. Simultaneously, the hydrological droughts will be much more frequent, with longer durations and more serious deficits. Therefore, the risk of floods and droughts will, overall, increase further under future climate change even under the combined influence of reservoirs and wetlands. These findings highlight the hydrological regulation function of wetlands and reservoirs and attest that the combining of wetlands with reservoir operation cannot fully eliminate the increasing future flood and drought risks. To improve a river basin's resilience to the risks of future climate change, we argue that the implementation of wetland restoration and the development of accurate forecasting systems for effective reservoir operation are of great importance. Furthermore, this study demonstrated a wetland–reservoir integrated modeling and assessment framework that is conducive to risk assessment of floods and hydrological droughts and that can be used for other river basins in the world. [ABSTRACT FROM AUTHOR]

Intensified extreme precipitation and corresponding floods are the most relevant consequences of climate change over the northeastern US (NEUS). To evaluate the impacts of climate change or certain climate perturbations on future extreme weather events which are dynamically similar to historic analogs, the pseudo-global warming (PGW) method has been frequently employed; however, this method lacks precise definition and guidelines, thus limiting its application. More specifically, three key questions related to the application of the PGW method remain unanswered: at what spatial scale should climate perturbations be applied? Among the different meteorological variables available, which ones should be perturbed? And will PGW projections vary significantly when different perturbations are applied? To address these questions, we examine the sensitivity and robustness of conclusions drawn from the PGW method over the NEUS by conducting multiple PGW experiments with varied perturbation spatial scales and choice of perturbed meteorological variables. The results show that the projections of precipitation and other essential variables at the regional mean scale are consistent across the PGW simulations, with a relative difference of much less than 10 %; however, different perturbation modifications can cause significant displacements of the storm events being simulated. Several previously assumed advantages of modifying only the temperature at regional mean scale, such as the preservation of geostrophic balance, do not appear to hold. Also, for these experiments, we find the regional mean perturbation produces a positive precipitation bias because it ignores the land–ocean warming contrast, which is a robust regional response to global warming. Overall, PGW experiments with perturbations from temperature or the combination of temperature and wind at the grid point scale are both recommended, depending on the research questions. The first approach can isolate the spatially dependent thermodynamic impact, and the latter incorporates both the thermodynamic and dynamic impacts. [ABSTRACT FROM AUTHOR]

Soluble reactive phosphorus (SRP) concentrations in agricultural headwaters can display pronounced seasonal variability at low flow, often with the highest concentrations occurring in summer. These SRP concentrations often exceed eutrophication levels, but their main sources, spatial distribution, and temporal dynamics are often unknown. The purpose of this study is therefore to differentiate between potential SRP losses and releases from soil drainage, anoxic riparian wetlands, and stream sediments in an agricultural headwater catchment. To identify the dominant SRP sources, we carried out three longitudinal stream sampling campaigns for SRP concentrations and fluxes. We used salt dilution tests and natural 222 Rn to determine water fluxes in different sections of the stream, and we sampled for SRP, Fe, and 14 C dissolved organic carbon (DOC) to examine possible redox-mediated mobilization from riparian wetlands and stream sediments. The results indicate that a single short section in the upper headwater reach was responsible for most of the SRP fluxes to the stream. Analysis of samples taken under summer low-flow conditions revealed that the stream water SRP concentrations, the fraction of SRP within total dissolved P (TDP), and DOC radiocarbon ages matched those in the groundwater entering the gaining section. Pore water from the stream sediment showed evidence of reductive mobilization of SRP, but the exchange fluxes were probably too small to contribute substantially to SRP stream concentrations. We also found no evidence that shallow flow paths from riparian wetlands contributed to the observed SRP loads in the stream. Combined, the results of this campaign and previous monitoring suggest that groundwater is the main long-term contributor of SRP at low flow, and agricultural phosphorus is largely buffered in the soil zone. We argue that the seasonal variation of SRP concentrations was mainly caused by variations in the proportion of groundwater present in the streamflow, which was highest during summer low-flow periods. Accurate knowledge of the various input pathways is important for choosing effective management measures in a given catchment, as it is also possible that observations of seasonal SRP dilution patterns stem from increased mobilization in riparian zones or from point sources. [ABSTRACT FROM AUTHOR]

In 2018–2019, Central Europe experienced an unprecedented 2-year drought with severe impacts on society and ecosystems. In this study, we analyzed the impact of this drought on water quality by comparing long-term (1997–2017) nitrate export with 2018–2019 export in a heterogeneous mesoscale catchment. We combined data-driven analysis with process-based modeling to analyze nitrogen retention and the underlying mechanisms in the soils and during subsurface transport. We found a drought-induced shift in concentration–discharge relationships, reflecting exceptionally low riverine nitrate concentrations during dry periods and exceptionally high concentrations during subsequent wet periods. Nitrate loads were up to 73 % higher compared to the long-term load–discharge relationship. Model simulations confirmed that this increase was driven by decreased denitrification and plant uptake and subsequent flushing of accumulated nitrogen during rewetting. Fast transit times (<2 months) during wet periods in the upstream sub-catchments enabled a fast water quality response to drought. In contrast, longer transit times downstream (>20 years) inhibited a fast response but potentially contribute to a long-term drought legacy. Overall, our study reveals that severe droughts, which are predicted to become more frequent across Europe, can reduce the nitrogen retention capacity of catchments, thereby intensifying nitrate pollution and threatening water quality. [ABSTRACT FROM AUTHOR]

Essentially all hydrogeological processes are strongly influenced by the subsurface spatial heterogeneity and the temporal variation of environmental conditions, hydraulic properties, and solute concentrations. This spatial and temporal variability generally leads to effective behaviors and emerging phenomena that cannot be predicted from conventional approaches based on homogeneous assumptions and models. However, it is not always clear when, why, how, and at what scale the 4D (3D + time) nature of the subsurface needs to be considered in hydrogeological monitoring, modeling, and applications. In this paper, we discuss the interest and potential for the monitoring and characterization of spatial and temporal variability, including 4D imaging, in a series of hydrogeological processes: (1) groundwater fluxes, (2) solute transport and reaction, (3) vadose zone dynamics, and (4) surface–subsurface water interactions. We first identify the main challenges related to the coupling of spatial and temporal fluctuations for these processes. We then highlight recent innovations that have led to significant breakthroughs in high-resolution space–time imaging and modeling the characterization, monitoring, and modeling of these spatial and temporal fluctuations. We finally propose a classification of processes and applications at different scales according to their need and potential for high-resolution space–time imaging. We thus advocate a more systematic characterization of the dynamic and 3D nature of the subsurface for a series of critical processes and emerging applications. This calls for the validation of 4D imaging techniques at highly instrumented observatories and the harmonization of open databases to share hydrogeological data sets in their 4D components. [ABSTRACT FROM AUTHOR]

Large agricultural streams receive excessive inputs of nitrogen. However, quantifying the role of these streams in nitrogen processing remains limited because continuous direct measurements of the interacting and highly time-varying nitrogen processing pathways in larger streams and rivers are very complex. Therefore, we employed a monitoring-driven modelling approach with high-frequency in situ data and the river water quality model Water Quality Analysis Simulation Program (WASP) 7.5.2 in the 27.4 km reach of the sixth-order agricultural stream called Lower Bode (central Germany) for a 5-year period (2014–2018). Paired high-frequency sensor data (15 min interval) of discharge, nitrate, dissolved oxygen, and chlorophyll a at upstream and downstream stations were used as model boundaries and for setting model constraints. The WASP model simulated 15 min intervals of discharge, nitrate, and dissolved oxygen with Nash–Sutcliffe efficiency values higher than 0.9 for calibration and validation, enabling the calculation of gross and net dissolved inorganic nitrogen uptake and pathway rates on a daily, seasonal, and multiannual scale. Results showed daily net uptake rate of dissolved inorganic nitrogen ranged from - 17.4 to 553.9 mgNm-2d-1. The highest daily net uptake could reach almost 30 % of the total input loading, which occurred at extreme low flow in summer 2018. The growing season (spring and summer) accounted for 91 % of the average net annual uptake of dissolved inorganic nitrogen in the measured period. In spring, both the DIN gross and net uptake were dominated by the phytoplankton uptake pathway. In summer, benthic algae assimilation dominated the gross uptake of dissolved inorganic nitrogen. Conversely, the reach became a net source of dissolved inorganic nitrogen with negative daily net uptake values in autumn and winter, mainly because the release from benthic algae surpassed uptake processes. Over the 5 years, average gross and net uptake rates of dissolved inorganic nitrogen were 124.1 and 56.8 mgNm-2d-1 , which accounted for only 2.7 % and 1.2 % of the total loadings in the Lower Bode, respectively. The 5-year average gross DIN uptake decreased from assimilation by benthic algae through assimilation by phytoplankton to denitrification. Our study highlights the value of combining river water quality modelling with high-frequency data to obtain a reliable budget of instream dissolved inorganic nitrogen processing which facilitates our ability to manage nitrogen in aquatic systems. This study provides a methodology that can be applied to any large stream to quantify nitrogen processing pathway dynamics and complete our understanding of nitrogen cycling. [ABSTRACT FROM AUTHOR]

Excess export of nitrate to streams affects ecosystem structure and functions and has been an environmental issue attracting worldwide attention. The dynamics of catchment-scale solute export from diffuse nitrogen sources can be explained by the changes of dominant flow paths, as solute attenuation (including the degradation of nitrate) is linked to the age composition of outflow. Previous data-driven studies suggested that catchment topographic slope has strong impacts on the age composition of streamflow and consequently on in-stream solute concentrations. However, the impacts have not been systematically assessed in terms of solute mass fluxes and solute concentration levels, particularly in humid catchments with strong seasonality in meteorological forcing. To fill this gap, we modeled the groundwater flow and nitrate transport for a small agricultural catchment in Central Germany. We used the fully coupled surface and subsurface numerical simulator HydroGeoSphere (HGS) to model groundwater and overland flow and nitrate transport. We computed the water ages using numerical tracer experiments. To represent various topographic slopes, we additionally simulated 10 synthetic catchments generated by modifying the topographic slope from the real-world scenario. Results suggest a negative correlation between the young streamflow fraction and the topographic slope. This correlation is more pronounced in flat landscapes with slopes <1:60. Flatter landscapes tend to retain more N mass in the soil (including mass degraded in soil) and export less N mass to the stream, due to reduced leaching and increased degradation. The mean in-stream nitrate concentration shows a decreasing trend in response to a decreasing topographic slope, suggesting that a large young streamflow fraction is not sufficient for high in-stream concentrations. Our results improve the understanding of nitrate export in response to topographic slope in a temperate humid climate, with important implications for the management of stream water quality. [ABSTRACT FROM AUTHOR]

Climate change may significantly increase flood risk globally, but there are large uncertainties in both future climatic changes and how these propagate into changing river flows. Here, the impact of climate change on the magnitude and frequency of high flows is analysed for Great Britain (GB) to provide the first spatially consistent GB projections to include both climate ensembles and hydrological model parameter uncertainties. We use the latest high-resolution (12 km) regional climate model ensemble from the UK Climate Projections (UKCP18). These projections are based on a perturbed-physics ensemble of 12 regional climate model simulations and allow exploration of climate model uncertainty beyond the variability caused by the use of different models. We model 346 larger (>144 km 2) catchments across GB using the DECIPHeR hydrological modelling framework. Generally, results indicated an increase in the magnitude and frequency of high flows (Q10, Q1, and annual maximum) along the western coast of GB in the future (2050–2075), with increases in annual maximum flows of up to 65 % for western Scotland. In contrast, median flows (Q50) were projected to decrease across GB. Even when using an ensemble based on a single regional climate model (RCM) structure, all flow projections contained large uncertainties. While the RCM parameters were the largest source of uncertainty overall, hydrological modelling uncertainties were considerable in eastern and south-eastern England. Regional variations in flow projections were found to relate to (i) differences in climatic change and (ii) catchment conditions during the baseline period as characterised by the runoff coefficient (mean discharge divided by mean precipitation). Importantly, increased heavy-precipitation events (defined by an increase in 99th percentile precipitation) did not always result in increased flood flows for catchments with low runoff coefficients, highlighting the varying factors leading to changes in high flows. These results provide a national overview of climate change impacts on high flows across GB, which will inform climate change adaptation, and highlight the impact of hydrological model parameter uncertainties when modelling climate change impact on high flows. [ABSTRACT FROM AUTHOR]

Relationships between nitrate concentrations and discharge rates (C–Q) at the catchment outlet can provide insights into sources, mobilization and biogeochemical transformations of nitrate within the catchment. Nitrate C–Q relationships often exhibit considerable scatter that might be related to variable hydrologic conditions during runoff events at sampling time, corresponding to variable sources and flow paths despite similar discharge (Q) rates. Although previous studies investigated the origins of this scatter in individual or in a few catchments, the role of different runoff event types across a large set of catchments is not yet fully understood. This study combines a hydrological runoff event classification framework with low-frequency nitrate samples in 184 catchments to explore the role of different runoff events in shaping long-term C–Q relationships and their variability across contrasting catchments. In most of the catchments, snow-impacted events produce positive deviations of concentrations, indicating an increased nitrate mobilization compared to the long-term pattern. In contrast, negative deviations occur mostly for rainfall-induced events with dry antecedent conditions, indicating the occurrence of lower nitrate concentrations (C) in river flows than their long-term pattern values during this type of event. Pronounced differences in event runoff coefficients among different event types indicate their contrasting levels of hydrologic connectivity that in turn might play a key role in controlling nitrate transport due to the activation of faster flow paths between sources and streams. Using long-term, low-frequency nitrate data, we demonstrate that runoff event types shape observed scatter in long-term C–Q relationships according to their level of hydrologic connectivity. In addition, we hypothesize that the level of biogeochemical attenuation of catchments can partially explain the spatial variability of the scatter during different event types. [ABSTRACT FROM AUTHOR]

The Millennium Drought lasted more than a decade and is notable for causing persistent shifts in the relationship between rainfall and runoff in many southeastern Australian catchments. Research to date has successfully characterised where and when shifts occurred and explored relationships with potential drivers, but a convincing physical explanation for observed changes in catchment behaviour is still lacking. Originating from a large multi-disciplinary workshop, this paper presents and evaluates a range of hypothesised process explanations of flow response to the Millennium Drought. The hypotheses consider climatic forcing, vegetation, soil moisture dynamics, groundwater, and anthropogenic influence. The hypotheses are assessed against evidence both temporally (e.g. why was the Millennium Drought different to previous droughts?) and spatially (e.g. why did rainfall–runoff relationships shift in some catchments but not in others?). Thus, the strength of this work is a large-scale assessment of hydrologic changes and potential drivers. Of 24 hypotheses, 3 are considered plausible, 10 are considered inconsistent with evidence, and 11 are in a category in between, whereby they are plausible yet with reservations (e.g. applicable in some catchments but not others). The results point to the unprecedented length of the drought as the primary climatic driver, paired with interrelated groundwater processes, including declines in groundwater storage, altered recharge associated with vadose zone expansion, and reduced connection between subsurface and surface water processes. Other causes include increased evaporative demand and harvesting of runoff by small private dams. Finally, we discuss the need for long-term field monitoring, particularly targeting internal catchment processes and subsurface dynamics. We recommend continued investment in the understanding of hydrological shifts, particularly given their relevance to water planning under climate variability and change. [ABSTRACT FROM AUTHOR]

In forest headwater streams, metabolic processes are predominately heterotrophic and depend on both the availability of carbon (C) and nitrogen (N) and a favourable C:N stoichiometry. In this context, hydrological conditions and the presence of riparian forests adjacent to streams can play an important, yet understudied role in determining dissolved organic carbon (DOC) and nitrate (NO 3-) concentrations and DOC:NO3- molar ratios. Here, we aimed to investigate how the interplay between hydrological conditions and riparian forest coverage drives DOC and NO 3- supply and DOC:NO3- stoichiometry in an oligotrophic headwater Mediterranean stream. We analysed DOC and NO 3- concentrations and DOC:NO3- molar ratios during both base flow and storm flow conditions at three stream locations along a longitudinal gradient of increased riparian forest coverage. Further, we performed an event analysis to examine the hydroclimatic conditions that favour the transfer of DOC and NO 3- from riparian soils to the stream during storms. Stream DOC and NO 3- concentrations were generally low (overall averages ± SD were 1.0±0.6 mg C L -1 and 0.20±0.09 mg N L -1), although significantly higher during storm flow compared to base flow conditions in all three stream sites. Optimal DOC:NO3- stoichiometry for stream heterotrophic microorganisms (corresponding to DOC:NO3- molar ratios between 4.8 and 11.7) was prevalent at the midstream and downstream sites under both flow conditions, whereas C-limited conditions were prevalent at the upstream site, which had no surrounding riparian forest. The hydroclimatic analysis of storms suggested that large and medium storm events display a distinct mechanism of DOC and NO 3- mobilization. In comparison to large storms, medium storm events showed limited hydrological responses that led to significantly lower increases in stream DOC and NO 3- concentrations. During large storm events, different patterns of DOC and NO 3- mobilization arise, depending on antecedent soil moisture conditions: drier antecedent conditions promoted rapid elevations of the riparian groundwater table, hydrologically activating a wider and shallower soil layer, and leading to relatively higher increases in stream DOC and NO 3- concentrations compared to large storm events preceded by wet conditions. Our results suggest that (i) increased supply of limited resources during storms can potentially sustain in-stream heterotrophic activity during high flows, especially during large storm events preceded by dry conditions, and (ii) C-limited conditions upstream were overcome downstream, likely due to higher C inputs from riparian forests present at lower elevations. The contrasting spatiotemporal patterns in DOC and NO 3- availability and DOC:NO3- stoichiometry observed at the studied stream suggest that groundwater inputs from riparian forests are essential for maintaining in-stream heterotrophic activity in oligotrophic, forest headwater catchments. [ABSTRACT FROM AUTHOR]

The Budyko framework posits that a catchment's long-term mean evapotranspiration (ET) is primarily governed by the availabilities of water and energy, represented by long-term mean precipitation (P) and potential evapotranspiration (PET), respectively. This assertion is supported by the distinctive clustering pattern that catchments take in Budyko space. Several semi-empirical, nonparametric curves have been shown to generally represent this clustering pattern but cannot explain deviations from the central tendency. Parametric Budyko equations attempt to generalize the nonparametric framework, through the introduction of a catchment-specific parameter (n or w). Prevailing interpretations of Budyko curves suggest that the explicit functional forms represent trajectories through Budyko space for individual catchments undergoing changes in the aridity index, PETP , while the n and w values represent catchment biophysical features; however, neither of these interpretations arise from the derivation of the Budyko equations. In this study, we reexamine, reinterpret, and test these two key assumptions of the current Budyko framework both theoretically and empirically. In our theoretical test, we use a biophysical model for ET to demonstrate that n and w values can change without invoking changes in landscape biophysical features and that catchments are not required to follow Budyko curve trajectories. Our empirical test uses data from 728 reference catchments in the United Kingdom (UK) and United States (US) to illustrate that catchments rarely follow Budyko curve trajectories and that n and w are not transferable between catchments or across time for individual catchments. This nontransferability implies that n and w are proxy variables for ETP , rendering the parametric Budyko equations underdetermined and lacking predictive ability. Finally, we show that the parametric Budyko equations are nonunique, suggesting their physical interpretations are unfounded. Overall, we conclude that, while the shape of Budyko curves generally captures the global behavior of multiple catchments, their specific functional forms are arbitrary and not reflective of the dynamic behavior of individual catchments. [ABSTRACT FROM AUTHOR]

Understanding concentration–discharge (C – Q) relationships can inform catchment solute and particulate export processes. Previous studies have shown that the extent to which baseflow contributes to streamflow can affect C – Q relationships in some catchments. However, the current understanding on the effects of baseflow contribution in shaping the C – Q patterns is largely derived from temperate catchments. As such, we still lack quantitative understanding of these effects across a wide range of climates (e.g. arid, tropical and subtropical). The study aims to assess how baseflow contributions, as defined by the median and the range of daily baseflow indices within individual catchments (BFI_m and BFI_range, respectively), influence C – Q slopes across 157 catchments in Australia spanning five climate zones. This study focuses on six water quality variables: electrical conductivity (EC), total phosphorus (TP), soluble reactive phosphorus (SRP), total suspended solids (TSS), the sum of nitrate and nitrite (NO x) and total nitrogen (TN). The impact of baseflow contributions is explored with a novel Bayesian hierarchical model. For sediments and nutrient species (TSS, NO x , TN and TP), we generally see largely positive C – Q slopes, which suggest a dominance of mobilization export patterns. Further, for TSS, NO x and TP we see stronger mobilization (steeper positive C – Q slopes) in catchments with higher values in both the BFI_m and BFI_range, as these two metrics are positively correlated for most catchments. The enhanced mobilization in catchments with higher BFI_m or BFI_range is likely due to the more variable flow pathways that occur in catchments with higher baseflow contributions. These variable flow pathways can lead to higher concentration gradients between low flows and high flows, where the former is generally dominated by groundwater/slow subsurface flow while the latter by surface water sources, respectively. This result highlights the crucial role of flow pathways in determining catchment exports of solutes and particulates. Our study also demonstrates the need for further studies on how the temporal variations of flow regimes and baseflow contributions influence flow pathways and the potential impacts of these flow pathways on catchment C – Q relationships. [ABSTRACT FROM AUTHOR]

The accelerated consumption of water resources caused by the rapid increase in population and urbanization is intensifying the complex interactions across water resources, socioeconomic development, ecological protection, and food security (WSEF), which causes not only the imbalance between water supply and demand but also the vulnerability of both food and ecological systems. Therefore, identifying the dynamic coevolution and feedback process is one of the most crucial ways of achieving the goal of sustainable water use. In this study, we developed an integrated modeling framework to better identify the dynamic interaction and coevolution process of the nexus across WSEF systems in the context of sustainable water uses by coupling system dynamic (SD) model and multi-objective optimization model. The SD model is used to simulate both the dynamic interaction of each agent and the coevolution process of the whole nexus system by positive/negative feedback loops. The multi-objective optimization model is used to quantify the negative feedback loops of the SD model by generating the optimal scheme of different water users. Finally, the model uncertainty considering different weighting factors is analyzed. The framework is applied to the upper reaches of the Guijiang River basin, China. Results show that (i) the rapid economic growth increases the conflict between the water uses for socioeconomic development and ecological protection, intensifying the ecological awareness and resulting in more water shortages of socioeconomic and food agents, which is unable to support such rapid development. (ii) Once the economic growth rate decreases, water resources are able to support economic development with a decreased overload index and stable crop yield, which further contributes to water sustainability. (iii) The river ecological agent is the critical factor that affects the robustness of the model. (iv) The equal consideration of each water usage is the most beneficial to sustainable development. These results highlight the importance of water resources management, considering the tradeoffs across multiple stakeholders, and give a strong reference to policymakers for comprehensive urban planning. [ABSTRACT FROM AUTHOR]

Nitrate (NO3-) excess in rivers harms aquatic ecosystems and can induce detrimental algae growths in coastal areas. Riverine NO3- uptake is a crucial element of the catchment-scale nitrogen balance and can be measured at small spatiotemporal scales, while at the scale of entire river networks, uptake measurements are rarely available. Concurrent, low-frequency NO3- concentration and streamflow (Q) observations at a basin outlet, however, are commonly monitored and can be analyzed in terms of concentration discharge (C – Q) relationships. Previous studies suggest that steeper positive log⁡(C) – log⁡(Q) slopes under low flow conditions (than under high flows) are linked to biological NO3- uptake, creating a bent rather than linear log⁡(C) – log⁡(Q) relationship. Here we explore if network-scale NO3- uptake creates bent log⁡(C) – log⁡(Q) relationships and when in turn uptake can be quantified from observed low-frequency C – Q data. To this end we apply a parsimonious mass-balance-based river network uptake model in 13 mesoscale German catchments (21–1450 km2) and explore the linkages between log⁡(C) – log⁡(Q) bending and different model parameter combinations. The modeling results show that uptake and transport in the river network can create bent log⁡(C) – log⁡(Q) relationships at the basin outlet from log–log linear C – Q relationships describing the NO3- land-to-stream transfer. We find that within the chosen parameter range the bending is mainly shaped by geomorphological parameters that control the channel reactive surface area rather than by the biological uptake velocity itself. Further we show that in this exploratory modeling environment, bending is positively correlated to percentage of NO3- load removed in the network (Lr.perc) but that network-wide flow velocities should be taken into account when interpreting log⁡(C) – log⁡(Q) bending. Classification trees, finally, can successfully predict classes of low (∼4 %), intermediate (∼32 %) and high (∼68 %) Lr.perc using information on water velocity and log⁡(C) – log⁡(Q) bending. These results can help to identify stream networks that efficiently attenuate NO3- loads based on low-frequency NO3- and Q observations and generally show the importance of the channel geomorphology on the emerging log⁡(C) – log⁡(Q) bending at network scales. [ABSTRACT FROM AUTHOR]

Understanding the controls on event-driven dissolved organic carbon (DOC) export is crucial as DOC is an important link between the terrestrial and the aquatic carbon cycles. We hypothesized that topography is a key driver of DOC export in headwater catchments because it influences hydrological connectivity, which can inhibit or facilitate DOC mobilization. To test this hypothesis, we studied the mechanisms controlling DOC mobilization and export in the Große Ohe catchment, a forested headwater in a mid-elevation mountainous region in southeastern Germany. Discharge and stream DOC concentrations were measured at an interval of 15 min using in situ UV-Vis (ultraviolet–visible) spectrometry from June 2018 until October 2020 at two topographically contrasting subcatchments of the same stream. At the upper location (888 m above sea level, a.s.l.), the stream drains steep hillslopes, whereas, at the lower location (771 m a.s.l.), it drains a larger area, including a flat and wide riparian zone. We focus on four events with contrasting antecedent wetness conditions and event size. During the events, in-stream DOC concentrations increased up to 19 mg L -1 in comparison to 2–3 mg L -1 during baseflow. The concentration–discharge relationships exhibited pronounced but almost exclusively counterclockwise hysteresis loops which were generally wider in the lower catchment than in the upper catchment due to a delayed DOC mobilization in the flat riparian zone. The riparian zone released considerable amounts of DOC, which led to a DOC load up to 7.4 kg h -1. The DOC load increased with the total catchment wetness. We found a disproportionally high contribution to the total DOC export of the upper catchment during events following a long dry period. We attribute this to the low hydrological connectivity in the lower catchment during drought, which inhibited DOC mobilization, especially at the beginning of the events. Our data show that not only event size but also antecedent wetness conditions strongly influence the hydrological connectivity during events, leading to a varying contribution to DOC export of subcatchments, depending on topography. As the frequency of prolonged drought periods is predicted to increase, the relative contribution of different subcatchments to DOC export may change in the future when hydrological connectivity will be reduced more often. [ABSTRACT FROM AUTHOR]

Following the rise of R as a scientific programming language, the increasing requirement for more transferable research and the growth of data availability in hydrology, R packages containing hydrological models are becoming more and more available as an open-source resource to hydrologists. Corresponding to the core of the hydrological studies workflow, their value is increasingly meaningful regarding the reliability of methods and results. Despite package and model distinctiveness, no study has ever provided a comparison of R packages for conceptual rainfall–runoff modelling from a user perspective by contrasting their philosophy, model characteristics and ease of use. We have selected eight packages based on our ability to consistently run their models on simple hydrology modelling examples. We have uniformly analysed the exact structure of seven of the hydrological models integrated into these R packages in terms of conceptual storages and fluxes, spatial discretisation, data requirements and output provided. The analysis showed that very different modelling choices are associated with these packages, which emphasises various hydrological concepts. These specificities are not always sufficiently well explained by the package documentation. Therefore a synthesis of the package functionalities was performed from a user perspective. This synthesis helps to inform the selection of which packages could/should be used depending on the problem at hand. In this regard, the technical features, documentation, R implementations and computational times were investigated. Moreover, by providing a framework for package comparison, this study is a step forward towards supporting more transferable and reusable methods and results for hydrological modelling in R. [ABSTRACT FROM AUTHOR]

Surface waters are under pressure from diffuse pollution from agricultural activities, and groundwater is known to be a connection between the agricultural fields and streams. This paper is one of the first to calculate long-term in-stream concentrations of tritium, chloride, and nitrate using dynamic groundwater travel time distributions (TTDs) derived from a distributed, transient, 3D groundwater flow model using forward particle tracking. We tested our approach in the Springendalse Beek catchment, a lowland stream in the east of the Netherlands, for which we collected a long time series of chloride and nitrate concentrations (1969–2018). The Netherlands experienced a sharp decrease in concentrations of solutes leaching to groundwater in the 1980s due to legislations on the application of nitrogen to agricultural fields. Stream measurements of chloride and nitrate showed that the corresponding trend reversal in the groundwater-fed stream occurred after a time lag of 5–10 years. By combining calculated TTDs with the known history of nitrogen and chloride inputs, we found that the variable contribution of different groundwater flow paths to stream water quality reasonably explained the majority of long-term and seasonal variation in the measured stream nitrate concentrations. However, combining only TTDs and inputs underestimated the time lag between the peak in nitrogen input and the following trend reversal of nitrate in the stream. This feature was further investigated through an exploration of the model behaviour under different scenarios. A time lag of several years, and up to decades, can occur due to (1) a thick unsaturated zone adding a certain travel time, (2) persistent organic matter with a slow release of N in the unsaturated zone, (3) a long mean travel time (MTT) compared to the rate of the reduction in nitrogen application, (4) areas with a high application of nitrogen (agricultural fields) being located further away from the stream or drainage network, or (5) a higher presence of nitrate attenuating processes close to the stream or drainage network compared to the rest of the catchment. By making the connection between dynamic groundwater travel time distributions and in-stream concentration measurements, we provide a method for validating the travel time approach and make the step towards application in water quality modelling and management. [ABSTRACT FROM AUTHOR]

The Water Informatics in Science and Engineering Centre for Doctoral Training (WISE CDT) offers a postgraduate programme that fosters enhanced levels of innovation and collaboration by training a cohort of engineers and scientists at the boundary of water informatics, science and engineering. The WISE CDT was established in 2014 with funding from the UK Engineering and Physical Sciences Research Council (EPSRC) amongst the universities of Bath, Bristol, Cardiff and Exeter. The WISE CDT will ultimately graduate over 80 PhD candidates trained in a non-traditional 4-year UK doctoral programme that integrates teaching and research elements in close collaboration with a range of industrial partners. WISE focuses on cohort-based education and equips the PhD candidates with a wide range of skills developed through workshops and other activities to maximise candidate abilities and experiences. We discuss the need for, the structure and results of the WISE CDT, which has been ongoing from 2013–2022 (final year of graduation). We conclude with lessons learned and an outlook for PhD training, based on our experience with this programme. [ABSTRACT FROM AUTHOR]

Characterizing and understanding spatial variability in water quality for a variety of chemical elements is an issue for present and future water resource management. However, most studies of spatial variability in water quality focus on a single element and rarely consider headwater catchments. Moreover, they assess few catchments and focus on annual means without considering seasonal variations. To overcome these limitations, we studied spatial variability and seasonal variation in dissolved C, N, and P concentrations at the scale of an intensively farmed region of France (Brittany). We analysed 185 headwater catchments (from 5–179 km 2) for which 10-year time series of monthly concentrations and daily stream flow were available from public databases. We calculated interannual loads, concentration percentiles, and seasonal metrics for each element to assess their spatial patterns and correlations. We then performed rank correlation analyses between water quality, human pressures, and soil and climate features. Results show that nitrate (NO 3) concentrations increased with increasing agricultural pressures and base flow contribution; dissolved organic carbon (DOC) concentrations decreased with increasing rainfall, base flow contribution, and topography; and soluble reactive phosphorus (SRP) concentrations showed weaker positive correlations with diffuse and point sources, rainfall and topography. An opposite pattern was found between DOC and NO 3 : spatially, between their median concentrations, and temporally, according to their seasonal cycles. In addition, the quality of annual maximum NO 3 concentration was in phase with maximum flow when the base flow index was low, but this synchrony disappeared when flow flashiness was lower. These DOC–NO 3 seasonal cycle types were related to the mixing of flow paths combined with the spatial variability of their respective sources and to local biogeochemical processes. The annual maximum SRP concentration occurred during the low-flow period in nearly all catchments. This likely resulted from the dominance of P point sources. The approach shows that despite the relatively low frequency of public water quality data, such databases can provide consistent pictures of the spatio-temporal variability of water quality and of its drivers as soon as they contain a large number of catchments to compare and a sufficient length of concentration time series. [ABSTRACT FROM AUTHOR]

We present a method to simulate fluid flow with reactive solute transport in structured, partially saturated soils using a Lagrangian perspective. In this context, we extend the scope of the Lagrangian Soil Water and Solute Transport Model (LAST) (Sternagel et al., 2019) by implementing vertically variable, non-linear sorption and first-order degradation processes during transport of reactive substances through a partially saturated soil matrix and macropores. For sorption, we develop an explicit mass transfer approach based on Freundlich isotherms because the common method of using a retardation factor is not applicable in the particle-based approach of LAST. The reactive transport method is tested against data of plot- and field-scale irrigation experiments with the herbicides isoproturon and flufenacet at different flow conditions over various periods. Simulations with HYDRUS 1-D serve as an additional benchmark. At the plot scale, both models show equal performance at a matrix-flow-dominated site, but LAST better matches indicators of preferential flow at a macropore-flow-dominated site. Furthermore, LAST successfully simulates the effects of adsorption and degradation on the breakthrough behaviour of flufenacet with preferential leaching and remobilization. The results demonstrate the feasibility of the method to simulate reactive solute transport in a Lagrangian framework and highlight the advantage of the particle-based approach and the structural macropore domain to simulate solute transport as well as to cope with preferential bypassing of topsoil and subsequent re-infiltration into the subsoil matrix. [ABSTRACT FROM AUTHOR]

Agricultural watersheds are significant contributors to downstream nutrient excess issues. The timing and magnitude of nutrient mobilization in these watersheds are driven by a combination of anthropogenic, hydrologic, and biogeochemical factors that operate across a range of spatial and temporal scales. However, how, when, and where these complex factors drive nutrient mobilization has previously been difficult to capture with low-frequency or spatially limited data sets. To address this knowledge gap, we analyzed daily nitrate concentration (c) and discharge (Q) data for a 4-year period (2016–2019) from five nested, agricultural watersheds in the midwestern United States that contribute nutrient loads to the Gulf of Mexico. These records allow us to investigate nutrient mobilization patterns at a temporal and spatial resolution not previously possible. The watersheds span two distinct landforms shaped by differences in glacial history, resulting in natural soil properties that necessitated different drainage infrastructure across the study area. To investigate nutrient export patterns under different hydrologic conditions, we partitioned the hydrograph into stormflow and baseflow periods and examined those periods separately through the analysis of their concentration–discharge (c – Q) relationships on annual, seasonal, and event timescales. Stormflow showed consistent chemostatic patterns across all seasons, while baseflow showed seasonally dynamic c – Q patterns. Baseflow exhibited chemodynamic conditions in the summer and fall and more chemostatic conditions in the winter and spring, suggesting that water source contributions during baseflow were nonstationary. Baseflow chemodynamic behavior was driven by low-flow, low-NO 3- conditions during which in-stream and near-stream biological processing likely moderated in-stream NO 3- concentrations. Additionally, inputs from deeper groundwater with longer residence times and lower-NO 3- concentration likely contributed to low-NO 3- conditions in stream, particularly in the larger watersheds. Stormflow c – Q behavior was consistent across watersheds, but baseflow c – Q behavior was linked to the intensity of agriculture and the density of built drainage infrastructure, with more drainage infrastructure associated with higher loads and more chemostatic export patterns across the watersheds. This suggests that the way humans replumb the subsurface in response to geologic conditions has implications for hydrologic connectivity, homogenization of source areas, and, subsequently, nutrient export during both baseflow and stormflow. Our analysis also showed that anomalous flow periods greatly influenced overall c – Q patterns, suggesting that the analysis of high-resolution records at multiple scales is critical when interpreting seasonal or annual patterns. [ABSTRACT FROM AUTHOR]

The model of single-well push–pull (SWPP) test has been widely used to investigate reactive radial dispersion in remediation or parameter estimation of in situ aquifers. Previous analytical solutions only focused on a completely isolated aquifer for the SWPP test, excluding any influence of acquitards bounding the tested aquifer, and ignored the wellbore storage of the chaser and rest phases in the SWPP test. Such simplification might be questionable in field applications when test durations are relatively long because solute transport in or out of the bounding acquitards is inevitable due to molecular diffusion and cross-formational advective transport. Here, a new SWPP model is developed in an aquifer–acquitard system with wellbore storage, and the analytical solution in the Laplace domain is derived. Four phases of the test are included: the injection phase, the chaser phase, the rest phase and the extraction phase. As the permeability of the acquitard is much smaller than the permeability of the aquifer, the flow is assumed to be perpendicular to the acquitard; thus only vertical dispersive and advective transports are considered for the acquitard. The validity of this treatment is tested against results grounded in numerical simulations. The global sensitivity analysis indicates that the results of the SWPP test are largely sensitive (i.e., influenced by) to the parameters of porosity and radial dispersion of the aquifer, whereas the influence of the acquitard on results could not be ignored. In the injection phase, the larger radial dispersivity of the aquifer could result in the smaller values of breakthrough curves (BTCs), while there are greater BTC values in the chaser and rest phases. In the extraction phase, it could lead to the smaller peak values of BTCs. The new model of this study is a generalization of several previous studies, and it performs better than previous studies ignoring the acquitard effect and wellbore storage for interpreting data of the field SWPP test reported by Yang et al. (2014). [ABSTRACT FROM AUTHOR]

Transit time distributions (TTDs) integrate information on timing, amount, storage, mixing and flow paths of water and thus characterize hydrologic and hydrochemical catchment response unlike any other descriptor. Here, we simulate the shape of TTDs in an idealized low-order catchment and investigate whether it changes systematically with certain catchment and climate properties. To this end, we used a physically based, spatially explicit 3-D model, injected tracer with a precipitation event and recorded the resulting forward TTDs at the outlet of a small (∼6000 m 2) catchment for different scenarios. We found that the TTDs can be subdivided into four parts: (1) early part – controlled by soil hydraulic conductivity and antecedent soil moisture content, (2) middle part – a transition zone with no clear pattern or control, (3) later part – influenced by soil hydraulic conductivity and subsequent precipitation amount, and (4) very late tail of the breakthrough curve – governed by bedrock hydraulic conductivity. The modeled TTD shapes can be predicted using a dimensionless number: higher initial peaks are observed if the inflow of water to a catchment is not equal to its capacity to discharge water via subsurface flow paths, and lower initial peaks are connected to increasing available storage. In most cases the modeled TTDs were humped with nonzero initial values and varying weights of the tails. Therefore, none of the best-fit theoretical probability functions could describe the entire TTD shape exactly. Still, we found that generally gamma and log-normal distributions work better for scenarios of low and high soil hydraulic conductivity, respectively. [ABSTRACT FROM AUTHOR]

Studying the response of streamwater chemistry to changes in discharge can provide valuable insights into how catchments store and release water and solutes. Previous studies have determined concentration–discharge (cQ) relationships from long-term, low-frequency data of a wide range of solutes. These analyses, however, provide little insight into the coupling of solute concentrations and flow during individual hydrologic events. Event-scale cQ relationships have rarely been investigated across a wide range of solutes and over extended periods of time, and thus little is known about differences and similarities between event-scale and long-term cQ relationships. Differences between event-scale and long-term cQ behavior may provide useful information about the processes regulating their transport through the landscape. Here we analyze cQ relationships of 14 different solutes, ranging from major ions to trace metals, as well as electrical conductivity, in the Swiss Erlenbach catchment. From a 2-year time series of sub-hourly solute concentration data, we determined 2-year cQ relationships for each solute and compared them to cQ relationships of 30 individual events. The 2-year cQ behavior of groundwater-sourced solutes was representative of their cQ behavior during hydrologic events. Other solutes, however, exhibited very different cQ patterns at the event scale and across 2 consecutive years. This was particularly true for trace metals and atmospheric and/or biologically active solutes, many of which exhibited highly variable cQ behavior from one event to the next. Most of this inter-event variability in cQ behavior could be explained by factors such as catchment wetness, season, event size, input concentrations, and event-water contributions. We present an overview of the processes regulating different groups of solutes, depending on their origin in and pathways through the catchment. Our analysis thus provides insight into controls on solute variations at the hydrologic event scale. [ABSTRACT FROM AUTHOR]

Lateral carbon flux through river networks is an important and poorly understood component of the global carbon budget. This work investigates how temperature and hydrology control the production and export of dissolved organic carbon (DOC) in the Susquehanna Shale Hills Critical Zone Observatory in Pennsylvania, USA. Using field measurements of daily stream discharge, evapotranspiration, and stream DOC concentration, we calibrated the catchment-scale biogeochemical reactive transport model BioRT-Flux-PIHM (Biogeochemical Reactive Transport–Flux–Penn State Integrated Hydrologic Model, BFP), which met the satisfactory standard of a Nash–Sutcliffe efficiency (NSE) value greater than 0.5. We used the calibrated model to estimate and compare the daily DOC production rates (Rp ; the sum of the local DOC production rates in individual grid cells) and export rate (Re ; the product of the concentration and discharge at the stream outlet, or load). Results showed that daily Rp varied by less than an order of magnitude, primarily depending on seasonal temperature. In contrast, daily Re varied by more than 3 orders of magnitude and was strongly associated with variation in discharge and hydrological connectivity. In summer, high temperature and evapotranspiration dried and disconnected hillslopes from the stream, driving Rp to its maximum but Re to its minimum. During this period, the stream only exported DOC from the organic-poor groundwater and from organic-rich soil water in the swales bordering the stream. The DOC produced accumulated in hillslopes and was later flushed out during the wet and cold period (winter and spring) when Re peaked as the stream reconnected with uphill and Rp reached its minimum. The model reproduced the observed concentration–discharge (C–Q) relationship characterized by an unusual flushing–dilution pattern with maximum concentrations at intermediate discharge, indicating three end-members of source waters. A sensitivity analysis indicated that this nonlinearity was caused by shifts in the relative contribution of different source waters to the stream under different flow conditions. At low discharge, stream water reflected the chemistry of organic-poor groundwater; at intermediate discharge, stream water was dominated by the organic-rich soil water from swales; at high discharge, the stream reflected uphill soil water with an intermediate DOC concentration. This pattern persisted regardless of the DOC production rate as long as the contribution of deeper groundwater flow remained low (<18 % of the streamflow). When groundwater flow increased above 18 %, comparable amounts of groundwater and swale soil water mixed in the stream and masked the high DOC concentration from swales. In that case, the C–Q patterns switched to a flushing-only pattern with increasing DOC concentration at high discharge. These results depict a conceptual model that the catchment serves as a producer and storage reservoir for DOC under hot and dry conditions and transitions into a DOC exporter under wet and cold conditions. This study also illustrates how different controls on DOC production and export – temperature and hydrological flow paths, respectively – can create temporal asynchrony at the catchment scale. Future warming and increasing hydrological extremes could accentuate this asynchrony, with DOC production occurring primarily during dry periods and lateral export of DOC dominating in major storm events. [ABSTRACT FROM AUTHOR]

Benchmarking model performance across large samples of catchments is useful to guide model selection and future model development. Given uncertainties in the observational data we use to drive and evaluate hydrological models, and uncertainties in the structure and parameterisation of models we use to produce hydrological simulations and predictions, it is essential that model evaluation is undertaken within an uncertainty analysis framework. Here, we benchmark the capability of several lumped hydrological models across Great Britain by focusing on daily flow and peak flow simulation. Four hydrological model structures from the Framework for Understanding Structural Errors (FUSE) were applied to over 1000 catchments in England, Wales and Scotland. Model performance was then evaluated using standard performance metrics for daily flows and novel performance metrics for peak flows considering parameter uncertainty. Our results show that lumped hydrological models were able to produce adequate simulations across most of Great Britain, with each model producing simulations exceeding a 0.5 Nash–Sutcliffe efficiency for at least 80 % of catchments. All four models showed a similar spatial pattern of performance, producing better simulations in the wetter catchments to the west and poor model performance in central Scotland and south-eastern England. Poor model performance was often linked to the catchment water balance, with models unable to capture the catchment hydrology where the water balance did not close. Overall, performance was similar between model structures, but different models performed better for different catchment characteristics and metrics, as well as for assessing daily or peak flows, leading to the ensemble of model structures outperforming any single structure, thus demonstrating the value of using multi-model structures across a large sample of different catchment behaviours. This research evaluates what conceptual lumped models can achieve as a performance benchmark and provides interesting insights into where and why these simple models may fail. The large number of river catchments included in this study makes it an appropriate benchmark for any future developments of a national model of Great Britain. [ABSTRACT FROM AUTHOR]

Increased anthropogenic inputs of nitrogen (N) to the biosphere during the last few decades have resulted in increased groundwater and surface water concentrations of N (primarily as nitrate), posing a global problem. Although measures have been implemented to reduce N inputs, they have not always led to decreasing riverine nitrate concentrations and loads. This limited response to the measures can either be caused by the accumulation of organic N in the soils (biogeochemical legacy) – or by long travel times (TTs) of inorganic N to the streams (hydrological legacy). Here, we compare atmospheric and agricultural N inputs with long-term observations (1970–2016) of riverine nitrate concentrations and loads in a central German mesoscale catchment with three nested subcatchments of increasing agricultural land use. Based on a data-driven approach, we assess jointly the N budget and the effective TTs of N through the soil and groundwater compartments. In combination with long-term trajectories of the C – Q relationships, we evaluate the potential for and the characteristics of an N legacy. We show that in the 40-year-long observation period, the catchment (270 km 2) with 60 % agricultural area received an N input of 53 437 t, while it exported 6592 t, indicating an overall retention of 88 %. Removal of N by denitrification could not sufficiently explain this imbalance. Log-normal travel time distributions (TTDs) that link the N input history to the riverine export differed seasonally, with modes spanning 7–22 years and the mean TTs being systematically shorter during the high-flow season as compared to low-flow conditions. Systematic shifts in the C – Q relationships were noticed over time that could be attributed to strong changes in N inputs resulting from agricultural intensification before 1989, the break-down of East German agriculture after 1989 and the seasonal differences in TTs. A chemostatic export regime of nitrate was only found after several years of stabilized N inputs. The changes in C – Q relationships suggest a dominance of the hydrological N legacy over the biogeochemical N fixation in the soils, as we expected to observe a stronger and even increasing dampening of the riverine N concentrations after sustained high N inputs. Our analyses reveal an imbalance between N input and output, long time-lags and a lack of significant denitrification in the catchment. All these suggest that catchment management needs to address both a longer-term reduction of N inputs and shorter-term mitigation of today's high N loads. The latter may be covered by interventions triggering denitrification, such as hedgerows around agricultural fields, riparian buffers zones or constructed wetlands. Further joint analyses of N budgets and TTs covering a higher variety of catchments will provide a deeper insight into N trajectories and their controlling parameters. [ABSTRACT FROM AUTHOR]

The hydrological and biogeochemical response of rivers carries information about solute sources, pathways, and transformations in the catchment. We investigate long-term water quality data of 11 Swiss catchments with the objective to discern the influence of major catchment characteristics and anthropic activities on delivery of solutes in stream water. Magnitude, trends, and seasonality of water quality samplings of different solutes are evaluated and compared across catchments. Subsequently, the empirical dependence between concentration and discharge is used to classify the solute behaviors. While the anthropogenic impacts are clearly detectable in the concentration of certain solutes (i.e., Na+ , Cl- , NO3 , DRP), the influence of single catchment characteristics such as geology (e.g., on Ca2+ and H4SiO4), topography (e.g., on DOC, TOC, and TP), and size (e.g., on DOC and TOC) is only sometimes visible, which is also because of the limited sample size and the spatial heterogeneity within catchments. Solute variability in time is generally smaller than discharge variability and the most significant trends in time are due to temporal variations of anthropogenic rather than natural forcing. The majority of solutes show dilution with increasing discharge, especially geogenic species, while sediment-bonded solutes (e.g., total phosphorous and organic carbon species) show higher concentrations with increasing discharge. Both natural and anthropogenic factors affect the biogeochemical response of streams, and, while the majority of solutes show identifiable behaviors in individual catchments, only a minority of behaviors can be generalized across the 11 catchments that exhibit different natural, climatic, and anthropogenic features. [ABSTRACT FROM AUTHOR]

Quantifying the influence of human activities, such as reservoir building, water abstraction, and land use change, on hydrology is crucial for sustainable future water management, especially during drought. Model-based methods are very time-consuming to set up and require a good understanding of human processes and time series of water abstraction, land use change, and water infrastructure and management, which often are not available. Therefore, observation-based methods are being developed that give an indication of the direction and magnitude of the human influence on hydrological drought based on limited data. We suggest adding to those methods a "paired-catchment" approach, based on the classic hydrology approach that was developed in the 1920s for assessing the impact of land cover treatment on water quantity and quality. When applying the paired-catchment approach to long-term pre-existing human influences trying to detect an influence on extreme events such as droughts, a good catchment selection is crucial. The disturbed catchment needs to be paired with a catchment that is similar in all aspects except for the human activity under study, in that way isolating the effect of that specific activity. In this paper, we present a framework for selecting suitable paired catchments for the study of the human influence on hydrological drought. Essential elements in this framework are the availability of qualitative information on the human activity under study (type, timing, and magnitude), and the similarity of climate, geology, and other human influences between the catchments. We show the application of the framework on two contrasting case studies, one impacted by groundwater abstraction and one with a water transfer from another region. Applying the paired-catchment approach showed how the groundwater abstraction aggravated streamflow drought by more than 200 % for some metrics (total drought duration and total drought deficit) and the water transfer alleviated droughts with 25 % to 80 %, dependent on the metric. Benefits of the paired-catchment approach are that climate variability between pre- and post-disturbance periods does not have to be considered as the same time periods are used for analysis, and that it avoids assumptions considered when partly or fully relying on simulation modelling. Limitations of the approach are that finding a suitable catchment pair can be very challenging, often no pre-disturbance records are available to establish the natural difference between the catchments, and long time series of hydrological data are needed to robustly detect the effect of the human activities on hydrological drought. We suggest that the approach can be used for a first estimate of the human influence on hydrological drought, to steer campaigns to collect more data, and to complement and improve other existing methods (e.g. model-based or large-sample approaches). [ABSTRACT FROM AUTHOR]

A novel approach to stochastic rainfall generation that can reproduce various statistical characteristics of observed rainfall at hourly to yearly timescales is presented. The model uses a seasonal autoregressive integrated moving average (SARIMA) model to generate monthly rainfall. Then, it downscales the generated monthly rainfall to the hourly aggregation level using the Modified Bartlett–Lewis Rectangular Pulse (MBLRP) model, a type of Poisson cluster rainfall model. Here, the MBLRP model is carefully calibrated such that it can reproduce the sub-daily statistical properties of observed rainfall. This was achieved by first generating a set of fine-scale rainfall statistics reflecting the complex correlation structure between rainfall mean, variance, auto-covariance, and proportion of dry periods, and then coupling it to the generated monthly rainfall, which were used as the basis of the MBLRP parameterization. The approach was tested on 34 gauges located in the Midwest to the east coast of the continental United States with a variety of rainfall characteristics. The results of the test suggest that our hybrid model accurately reproduces the first- to the third-order statistics as well as the intermittency properties from the hourly to the annual timescales, and the statistical behaviour of monthly maxima and extreme values of the observed rainfall were reproduced well. [ABSTRACT FROM AUTHOR]

Soil erosion and sediment transport play important roles in terrestrial landscape evolution and biogeochemical cycles of nutrients and contaminants. Although discharge is considered to be a controlling factor in sediment transport, its correlation with sediment concentration varies across the Yellow River basin (YRB) and is not fully understood. This paper provides analysis from gauges across the YRB covering a range of climates, topographic characteristics, and degrees of human intervention. Our results show that discharge control on sediment transport is dampened at gauges with large mean annual discharge, where sediment concentration becomes more and more stable. This emergent stationarity can be attributed to vegetation resistance. Our analysis shows that sediment concentration follows a bell shape with vegetation index (normalized difference vegetation index, NDVI) at an annual scale despite heterogeneity in climate and landscape. We obtain the counterintuitive result that, as mean annual discharge increases, the dominant control on sediment transport shifts from streamflow erosion to vegetation retardation in the YRB. [ABSTRACT FROM AUTHOR]

Recently, deep learning (DL) has emerged as a revolutionary and versatile tool transforming industry applications and generating new and improved capabilities for scientific discovery and model building. The adoption of DL in hydrology has so far been gradual, but the field is now ripe for breakthroughs. This paper suggests that DLbased methods can open up a complementary avenue toward knowledge discovery in hydrologic sciences. In the new avenue, machine-learning algorithms present competing hypotheses that are consistent with data. Interrogative methods are then invoked to interpret DL models for scientists to further evaluate. However, hydrology presents many challenges for DL methods, such as data limitations, heterogeneity and co-evolution, and the general inexperience of the hydrologic field with DL. The roadmap toward DL-powered scientific advances will require the coordinated effort from a large community involving scientists and citizens. Integrating process-based models with DL models will help alleviate data limitations. The sharing of data and baseline models will improve the efficiency of the community as a whole. Open competitions could serve as the organizing events to greatly propel growth and nurture data science education in hydrology, which demands a grassroots collaboration. The area of hydrologic DL presents numerous research opportunities that could, in turn, stimulate advances in machine learning as well. [ABSTRACT FROM AUTHOR]

Time series of groundwater and stream water quality often exhibit substantial temporal and spatial variability, whereas typical existing monitoring data sets, e.g. from environmental agencies, are usually characterized by relatively low sampling frequency and irregular sampling in space and/or time. This complicates the differentiation between anthropogenic influence and natural variability as well as the detection of changes in water quality which indicate changes in single drivers. We suggest the new term dominant changes for changes in multivariate water quality data which concern (1) multiple variables, (2) multiple sites and (3) long-term patterns and present an exploratory framework for the detection of such dominant changes in data sets with irregular sampling in space and time. Firstly, a non-linear dimension-reduction technique was used to summarize the dominant spatiotemporal dynamics in the multivariate water quality data set in a few components. Those were used to derive hypotheses on the dominant drivers influencing water quality. Secondly, different sampling sites were compared with respect to median component values. Thirdly, time series of the components at single sites were analysed for long-term patterns. We tested the approach with a joint stream water and groundwater data set quality consisting of 1572 samples, each comprising sixteen variables, sampled with a spatially and temporally irregular sampling scheme at 29 sites in northeast Germany from 1998 to 2009. The first four components were interpreted as (1) an agriculturally induced enhancement of the natural background level of solute concentration, (2) a redox sequence from reducing conditions in deep groundwater to post-oxic conditions in shallow groundwater and oxic conditions in stream water, (3) a mixing ratio of deep and shallow groundwater to the streamflow and (4) sporadic events of slurry application in the agricultural practice. Dominant changes were observed for the first two components. The changing intensity of the first component was interpreted as response to the temporal variability of the thickness of the unsaturated zone. A steady increase in the second component at most stream water sites pointed towards progressing depletion of the denitrification capacity of the deep aquifer. [ABSTRACT FROM AUTHOR]

The young water fraction Fyw, defined as the proportion of catchment outflow younger than approximately 2-3 months, can be estimated directly from the amplitudes of seasonal cycles of stable water isotopes in precipitation and streamflow. Thus, Fyw may be a useful metric in catchment inter-comparison studies that investigate landscape and hydro-climatic controls on streamflow generation. Here, we explore how Fyw varies with catchment characteristics and climatic forcing, using an extensive isotope data set from 22 small- to medium-sized (0.7-351 km²) Swiss catchments. We find that flow-weighting the tracer concentrations in streamwater resulted in roughly 26% larger young water fractions compared to the corresponding unweighted values, reflecting the fact that young water fractions tend to be larger when catchments are wet and discharge is correspondingly higher. However, flow-weighted and unweighted young water fractions are strongly correlated with each other among the catchments. They also correlate with terrain, soil, and land-use indices, as well as with mean precipitation and measures of hydrologic response. Within individual catchments, young water fractions increase with discharge, indicating an increase in the proportional contribution of faster flow paths at higher flows. We present a new method to quantify the discharge sensitivity of Fyw, which we estimate as the linear slope of the relationship between the young water fraction and flow. Among the 22 catchments, discharge sensitivities of Fyw are highly variable and only weakly correlated with Fyw itself, implying that these two measures reflect catchment behaviour differently. Based on strong correlations between the discharge sensitivity of Fyw and several catchment characteristics, we suggest that low discharge sensitivities imply greater persistence in the proportions of fast and slow runoff flow paths as catchment wetness changes. In contrast, high discharge sensitivities imply the activation of different dominant flow paths during precipitation events, such as when subsurface water tables rise into more permeable layers and/or the river network expands further into the landscape. [ABSTRACT FROM AUTHOR]

Urbanisation has been associated with a reduction in the long-term correlation within a streamflow series, quantified by the Hurst exponent (H). This presents an opportunity to use the H exponent as an index for the classification of catchments on a scale from natural to urbanised conditions. However, before using the H exponent as a general index, the relationship between this exponent and level of urbanisation needs to be further examined and verified on catchments with different levels of imperviousness and from different climatic regions. In this study, the H exponent is estimated for 38 (deseasonalised) mean daily runoff time series, 22 from the USA and 16 from Australia, using the traditional rescaled-range statistic (R=S) and the more advanced multifractal detrended fluctuation analysis (MF-DFA). Relationships between H and catchment imperviousness, catchment size, annual rainfall and specific mean discharge were investigated. No clear relationship with catchment area was found, and a weak negative relationship with annual rainfall and specific mean streamflow was found only when the R=S method was used. Conversely, both methods showed decreasing values of H as catchment imperviousness increased. The H exponent decreased from around 1.0 for catchments in natural conditions to around 0.6 for highly urbanised catchments. Three significantly different ranges of H exponents were identified, allowing catchments to be parsed into groups with imperviousness lower than 5% (natural), catchments with imperviousness between 5 and 15% (peri-urban) and catchments with imperviousness larger than 15% (urban). The H exponent thus represents a useful metric to quantitatively assess the impact of catchment imperviousness on streamflow regime. [ABSTRACT FROM AUTHOR]

Hydrology has undergone almost transformative changes over the past 50 years. Huge strides have been made in the transition from early empirical approaches to rigorous approaches based on the fluid mechanics of water movement on and below the land surface. However, progress has been hampered by problems posed by the presence of heterogeneity, including subsurface heterogeneity present at all scales. The inability to measure or map the heterogeneity everywhere prevented the development of balance equations and associated closure relations at the scales of interest, and has led to the virtual impasse we are presently in, in terms of development of physically based models needed for hydrologic predictions. An alternative to the mapping of heterogeneity everywhere is a new Earth system science view, which sees the heterogeneity as the end result of co-evolutionary hydrological, geomorphological, ecological, and pedological processes, each operating at a different rate, which help to shape the landscapes that we find in nature, including the heterogeneity that we do not readily see. The expectation is that instead of specifying exact details of the heterogeneity in our models, we can replace it (without loss of information) with the ecosystem function that they perform. Guided by this new Earth system science perspective, development of hydrologic science is now addressing new questions using novel holistic co-evolutionary approaches as opposed to the physical, fluid mechanics based reductionist approaches that we inherited from the recent past. In the emergent Anthropocene, the co-evolutionary view has expanded further to involve interactions and feedbacks with human-social processes as well. In this paper, I present my own perspective of key milestones in the transformation of hydrologic science from engineering hydrology to Earth system science, drawn from the work of several students and colleagues of mine, and discuss their implication for hydrologic observations, theory development, and predictions. [ABSTRACT FROM AUTHOR]

The complexity and heterogeneity of human water use over large spatial areas and decadal timescales can impede the understanding of hydrological change, particularly in regions with sparse monitoring of the water cycle. In the Arkavathy watershed in southern India, surface water inflows to major reservoirs decreased over a 40-year period during which urbanization, groundwater depletion, modification of the river network, and changes in agricultural practices also occurred. These multiple, interacting drivers combined with limited hydrological monitoring make attribution of the causes of diminishing water resources in the watershed challenging and impede effective policy responses. To mitigate these challenges, we developed a novel, spatially distributed dataset to understand hydrological change by characterizing the residual trends in surface water extent that remain after controlling for precipitation variations and comparing the trends with historical land use maps to assess human drivers of change. Using an automated classification approach with subpixel unmixing, we classified water extent in nearly 1700 man-made lakes, or tanks, in Landsat images from 1973 to 2010. The classification results compared well with a reference dataset of water extent of tanks (R2 = 0.95). We modeled the water extent of 42 clusters of tanks in a multiple regression on simple hydrological covariates (including precipitation) and time. Inter-annual variability in precipitation accounted for 63% of the predicted variability in water extent. However, precipitation did not exhibit statistically significant trends in any part of the watershed. After controlling for precipitation variability, we found statistically significant temporal trends in water extent, both positive and negative, in 13 of the clusters. Based on a water balance argument, we inferred that these trends likely reflect a nonstationary relationship between precipitation and watershed runoff. Independently of precipitation, water extent increased in a region downstream of Bangalore, likely due to increased urban effluents, and declined in the northern portion of the Arkavathy. Comparison of the drying trends with land use indicated that they were most strongly associated with irrigated agriculture, sourced almost exclusively by groundwater. This suggests that groundwater abstraction was a major driver of hydrological change in this watershed. Disaggregating the watershed-scale hydrological response via remote sensing of surface water bodies over multiple decades yielded a spatially resolved characterization of hydrological change in an otherwise poorly monitored watershed. This approach presents an opportunity to understand hydrological change in heavily managed watersheds where surface water bodies integrate upstream runoff and can be delineated using satellite imagery. [ABSTRACT FROM AUTHOR]

During the last 6 decades, forest biomass has increased in Sweden mainly due to forest management, with a possible increasing effect on evapotranspiration. However, increasing global CO2 concentrations may also trigger physiological water-saving responses in broadleaf tree species, and to a lesser degree in some needleleaf conifer species, inducing an opposite effect. Additionally, changes in other forest attributes may also affect evapotranspiration. In this study, we aimed to detect the dominating effect(s) of forest change on evapotranspiration by studying changes in the ratio of actual evapotranspiration to precipitation, known as the evaporative ratio, during the period 1961-2012. We first used the Budyko framework of water and energy availability at the basin scale to study the hydroclimatic movements in Budyko space of 65 temperate and boreal basins during this period.We found that movements in Budyko space could not be explained by climatic changes in precipitation and potential evapotranspiration in 60%of these basins, suggesting the existence of other dominant drivers of hydroclimatic change. In both the temperate and boreal basin groups studied, a negative climatic effect on the evaporative ratio was counteracted by a positive residual effect. The positive residual effect occurred along with increasing standing forest biomass in the temperate and boreal basin groups, increasing forest cover in the temperate basin group and no apparent changes in forest species composition in any group. From the three forest attributes, standing forest biomass was the one that could explain most of the variance of the residual effect in both basin groups. These results further suggest that the water-saving response to increasing CO2 in these forests is either negligible or overridden by the opposite effect of the increasing forest biomass. Thus, we conclude that increasing standing forest biomass is the dominant driver of long-term and large-scale evapotranspiration changes in Swedish forests. [ABSTRACT FROM AUTHOR]

We propose new metrics to assist global sensitivity analysis, GSA, of hydrological and Earth systems. Our approach allows assessing the impact of uncertain parameters on main features of the probability density function, pdf, of a target model output, y. These include the expected value of y, the spread around the mean and the degree of symmetry and tailedness of the pdf of y. Since reliable assessment of higher-order statistical moments can be computationally demanding, we couple our GSA approach with a surrogate model, approximating the full model response at a reduced computational cost. Here, we consider the generalized polynomial chaos expansion (gPCE), other model reduction techniques being fully compatible with our theoretical framework. We demonstrate our approach through three test cases, including an analytical benchmark, a simplified scenario mimicking pumping in a coastal aquifer and a laboratory-scale conservative transport experiment. Our results allow ascertaining which parameters can impact some moments of the model output pdf while being uninfluential to others. We also investigate the error associated with the evaluation of our sensitivity metrics by replacing the original system model through a gPCE. Our results indicate that the construction of a surrogate model with increasing level of accuracy might be required depending on the statistical moment considered in the GSA. The approach is fully compatible with (and can assist the development of) analysis techniques employed in the context of reduction of model complexity, model calibration, design of experiment, uncertainty quantification and risk assessment. [ABSTRACT FROM AUTHOR]

Despite growing interest in resilience, there is still significant scope for increasing its conceptual clarity and practical relevance in socio-hydrological contexts: specifically, questions of how socio-hydrological systems respond to and cope with perturbations and how these connect to resilience remain unanswered. In this opinion paper, we propose a novel conceptual framework for understanding and assessing resilience in coupled socio-hydrological contexts, and encourage debate on the inter-connections between socio-hydrology and resilience. Taking a systems perspective, we argue that resilience is a set of systematic properties with three dimensions: absorptive, adaptive, and transformative, and contend that socio-hydrological systems can be viewed as various forms of human-water couplings, reflecting different aspects of these interactions. We propose a framework consisting of two parts. The first part addresses the identity of socio-hydrological resilience, answering questions such as "resilience of what in relation to what". We identify three existing framings of resilience for different types of human-water systems and subsystems, which have been used in different fields: (1) the water subsystem, highlighting hydrological resilience to anthropogenic hazards; (2) the human subsystem, foregrounding social resilience to hydrological hazards; and (3) the coupled human-water system, exhibiting socio-hydrological resilience. We argue that these three system types and resiliences afford new insights into the clarification and evaluation of different water management challenges. The first two types address hydrological and social states, while the third type emphasises the feedbacks and interactions between human and water components within complex systems subject to internal or external disturbances. In the second part, we focus on resilience management and develop the notion of the "resilience canvas", a novel heuristic device to identify possible pathways and to facilitate the design of bespoke strategies for enhancing resilience in the socio-hydrological context. The resilience canvas is constructed by combining absorptive and adaptive capacities as two axes. At the corners of the resulting twodimensional space are four quadrants which we conceptualise as representing resilient, vulnerable, susceptible, and resistant system states. To address projected change-induced uncertainties, we recommend that efforts now be focused on shifting socio-hydrological systems from resistant towards resilient status. In sum, the novel framework proposed here clarifies the ambiguity inherent in socio-hydrological resilience, and provides a viable basis for further theoretical and practical development. [ABSTRACT FROM AUTHOR]

Non-aqueous-phase liquid (NAPL) contaminants introduced into the unsaturated zone spread as a liquid phase; however, they can also vaporize and migrate in a gaseous state. Vapor plumes migrate easily and thus pose a potential threat to underlying aquifers. Large-scale column experiments were performed to quantify partitioning processes responsible for the retardation of carbon disulfide (CS2) vapor in partially saturated porous media. The results were compared with a theoretical approach taking into account the partitioning into the aqueous phase as well as adsorption to the solid matrix and to the air--water interface. The experiments were conducted in large, vertical columns (i.d. of 0.109 m) of 2m length packed with different porous media. A slug of CS2 vapor and the conservative tracer argon was injected at the bottom of the column followed by a nitrogen chase. Different seepage velocities were applied to characterize the transport and to evaluate their impact on retardation. Concentrations of CS2 and argon were measured at the top outlet of the column using two gas chromatographs. The temporal-moment analysis for step input was employed to evaluate concentration breakthrough curves and to quantify dispersion and retardation. The experiments conducted showed a pronounced retardation of CS2 in moist porous media which increased with water saturation. The comparison with an analytical solution helped to identify the relative contributions of partitioning processes to retardation. Thus, the experiments demonstrated that migrating CS2 vapor is retarded as a result of partitioning processes. Moreover, CS2 dissolved in the bulk water is amenable to biodegradation. The first evidence of CS2 decay by biodegradation was found in the experiments. The findings contribute to the understanding of vapor-plume transport in the unsaturated zone and provide valuable experimental data for the transfer to field-like conditions. [ABSTRACT FROM AUTHOR]

Although column experiments are frequently used to investigate the transport of organic micropollutants, little guidance is available on what they can be used for, how they should be set up, and how the experiments should be carried out. This review covers the use of column experiments to investigate the fate of organic micropollutants. Alternative setups are discussed together with their respective advantages and limitations. An overview is presented of published column experiments investigating the transport of organic micropollutants, and suggestions are offered on how to improve the comparability of future results from different experiments. The main purpose of column experiments is to investigate the transport and attenuation of a specific compound within a specific sediment or substrate. The transport of (organic) solutes in groundwater is influenced by the chemical and physical properties of the compounds, the solvent (i.e., the groundwater, including all solutes), and the substrate (the aquifer material). By adjusting these boundary conditions a multitude of different processes and related research questions can be investigated using a variety of experimental setups. Apart from the ability to effectively control the individual boundary conditions, the main advantage of column experiments compared to other experimental setups (such as those used in field experiments, or in batch microcosm experiments) is that conservative and reactive solute breakthrough curves can be derived, which represent the sum of the transport processes. There are well-established methods for analyzing these curves. The effects observed in column studies are often a result of dynamic, non-equilibrium processes. Time (or flow velocity) is an important factor, in contrast to batch experiments where all processes are observed until equilibrium is reached in the substrate-solution system. Slight variations in the boundary conditions of different experiments can have a marked influence on the transport and degradation of organic micropollutants. This is of critical importance when comparing general results from different column experiments investigating the transport behavior of a specific organic compound. Such variations unfortunately mean that the results from most column experiments are not transferable to other hydrogeochemical environments but are only valid for the specific experimental setup used. Column experiments are fast, flexible, and easy to manage; their boundary conditions can be controlled and they are cheap compared to extensive field experiments. They can provide good estimates of all relevant transport parameters. However, the obtained results will almost always be limited to the scale of the experiment and are not directly transferrable to field scales as too many parameters are exclusive to the column setup. The challenge for the future is to develop standardized column experiments on organic micropollutants in order to overcome these issues. [ABSTRACT FROM AUTHOR]

We present an interrupted-flow centrifugation technique to characterise preferential flow in low permeability media. The method entails a minimum of three phases: centrifuge-induced flow, no flow and centrifuge-induced flow, which may be repeated several times in order to most effectively characterise multi-rate mass transfer behaviour. In addition, the method enables accurate simulation of relevant in situ total stress conditions during flow by selecting an appropriate centrifugal force. We demonstrate the utility of the technique for characterising the hydraulic properties of smectite-clay-dominated core samples. All core samples exhibited a non-Fickian tracer breakthrough (early tracer arrival), combined with a decrease in tracer concentration immediately after each period of interrupted flow. This is indicative of dual (or multi-)porosity behaviour, with solute migration predominately via advection during induced flow, and via molecular diffusion (between the preferential flow network(s) and the low hydraulic conductivity domain) during interrupted flow. Tracer breakthrough curves were simulated using a bespoke dual porosity model with excellent agreement between the data and model output (Nash-Sutcliffe model efficiency coefficient was >0.97 for all samples). In combination, interrupted-flow centrifuge experiments and dual porosity transport modelling are shown to be a powerful method to characterise preferential flow in low permeability media. [ABSTRACT FROM AUTHOR]