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Subsurface contamination due to excessive nutrient surpluses is a persistent and widespread problem in agricultural areas across Europe. The vulnerability of a particular location to pollution from reactive solutes, such as nitrate, is determined by the interplay between hydrologic transport and biogeochemical transformations. Current studies on the controls of subsurface vulnerability do not consider the transient behaviour of transport dynamics in the root zone. Here, using state-of-the-art hydrologic simulations driven by observed hydroclimatic forcing, we demonstrate the strong spatiotemporal heterogeneity of hydrologic transport dynamics and reveal that these dynamics are primarily controlled by the hydroclimatic gradient of the aridity index across Europe. Contrasting the space-time dynamics of transport times with reactive timescales of denitrification in soil indicate that ~75% of the cultivated areas across Europe are potentially vulnerable to nitrate leaching for at least one-third of the year. We find that neglecting the transient nature of transport and reaction timescale results in a great underestimation of the extent of vulnerable regions by almost 50%. Therefore, future vulnerability and risk assessment studies must account for the transient behaviour of transport and biogeochemical transformation processes. Excess fertilizer use causes subsurface contamination. Here, the authors conduct an assessment of water quality vulnerability across Europe, finding that 75% of agricultural regions are susceptible to nitrate contamination for least one-third of the year, two times more than using standard estimation procedure. [ABSTRACT FROM AUTHOR]

The concept of water quality has often generally revolved around the all-round safety of water for human consumption. The quality of much of the 3% of the earth's humanly consumable water classed as freshwater is under threat of climate change, rising population numbers, indiscriminate land usage, detrimental agricultural practices and contamination from poor waste management. The need for optimal water quality enhancement has become more germane to sustainable socio-economic development. This paper examines the evolution of efforts made by the scientific community over the years to ensure water quality can be characterized and properly managed to ensure the global ever-growing demand for clean water for human consumption is continually met. The development of state-of-the-art computational decision support systems (DSS) should play a vital role. However, efforts in this regard are currently bedevilled by major challenges such as quantifying, measuring, processing and controlling the numerous metrics of water quality, as well as their adaptation and integration into a fully developed universal water quality model. In addressing these challenges, a shift towards simpler modelling approaches and the integration of uni-purpose models which can be cascaded into decision-making systems is being popularly proposed. However, with technological advancements already stimulating a water quality management revolution, there is a shift in paradigm to more universal modelling attempts with great optimism towards overcoming the challenges of developing universal water quality models and DSS. The prospects and opportunities of a water quality management renaissance offered by radical scientific innovations look promising, as the world races with time to provide support systems that can help deal better with the dynamics of sustainable water supply in increasingly contaminable environments and progressively unpredictable climates. [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]

Excess nutrient inputs from agricultural and urban sources have accelerated eutrophication and increased the incidence of algal blooms in the Great Lakes Basin (GLB). Lake basin management to address these threats relies on understanding the key drivers of pollution. Here, we use a random forest machine learning model to leverage information from 202 monitored streams in the GLB to predict seasonal and annual flow‐weighted concentrations of nitrogen and phosphorus, as well as nutrient ratios across the GLB. Land use (agricultural and urban land) and land management (tile drainage and wetland density) emerge as the two most important predictors for dissolved inorganic nitrogen (DIN; NO3− + NO2−) and soluble reactive phosphorus (SRP; PO43), while soil type and wetland density are more important for particulate P (PP). Partial dependence plots demonstrate increasing nutrient concentrations with increasing tile density and decreasing wetland density. In addition, increasing tile and livestock densities and decreasing forest cover correspond to higher SRP:Total Phosphorus (TP) ratios. Seasonally, the highest proportions of SRP occur in summer and fall. Higher livestock densities are also correlated with increasing N:P (DIN:TP) ratios. Livestock operations can contribute to the buildup of soil nutrients from excess manure application, while increasing subsurface drainage can provide transport pathways for dissolved nutrients. Given that both SRP:TP and the N:P ratios are strong predictors of harmful algal blooms, our study highlights the importance of livestock management, drainage management, and wetland restoration in efforts to address eutrophication in intensively managed landscapes. Plain Language Summary: While attempts have been made to improve water quality and reduce algal blooms in the Great Lakes Basin, we still have a limited understanding of where the greatest inputs of nutrients to the lakes are coming come from and why. In the current study, we have used nitrogen and phosphorus concentration data from over 200 monitoring stations around the Great Lakes to model daily, seasonal, and annual concentrations and to link these concentration magnitudes to a variety of watershed characteristics. Our results show that land use and land management are important predictors of nitrogen and phosphorus concentrations, with tile drainage emerging as a key driver of higher nitrate and soluble phosphorus concentrations. For particulate phosphorus, however, our results show that soil type and wetland density are more important predictors. Higher tile drainage densities and livestock densities were found to be associated with higher N:P ratios and higher ratios of soluble to total phosphorus. We also found that concentrations of soluble reactive phosphorus are highest during the summer and fall months in watersheds dominated by agriculture, which is in contrast to seasonal patterns observed in less‐impacted watersheds. Understanding watershed drivers of nutrient concentrations is critical for managing and improving water quality Key Points: Random forest model, developed using data from 202 streams, identifies various land use and management controls on nutrientsHigh livestock densities correspond with greater proportions of bioavailable P and higher N:P ratios, and thus greater risk of bloomsThe highest proportions of bioavailable P occur seasonally in summer and fall, and in the Lake Erie Basin [ABSTRACT FROM AUTHOR]

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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]

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]

Environmental data are the key to defining and addressing water quality and quantity challenges at the catchment scale. Here, we present the first large-sample water quality data set for 1386 German catchments covering a large range of hydroclimatic, topographic, geologic, land use, and anthropogenic settings. QUADICA (water QUAlity, DIscharge and Catchment Attributes for large-sample studies in Germany) combines water quality with water quantity data, meteorological and nutrient forcing data, and catchment attributes. The data set comprises time series of riverine macronutrient concentrations (species of nitrogen, phosphorus, and organic carbon) and diffuse nitrogen forcing data (nitrogen surplus, atmospheric deposition, and fixation) at the catchment scale. Time series are generally aggregated to an annual basis; however, for 140 stations with long-term water quality and quantity data (more than 20 years), we additionally present monthly median discharge and nutrient concentrations, flow-normalized concentrations, and corresponding mean fluxes as outputs from Weighted Regressions on Time, Discharge, and Season (WRTDS). The catchment attributes include catchment nutrient inputs from point and diffuse sources and characteristics from topography, climate, land cover, lithology, and soils. This comprehensive, freely available data collection with a large spatial and temporal coverage can facilitate large-sample data-driven water quality assessments at the catchment scale as well as mechanistic modeling studies. QUADICA is available at 10.4211/hs.0ec5f43e43c349ff818a8d57699c0fe1 (Ebeling et al., 2022b) and 10.4211/hs.88254bd930d1466c85992a7dea6947a4 (Ebeling et al., 2022a). [ABSTRACT FROM AUTHOR]

How does climate control river chemistry? Existing literature has examined extensively the response of river chemistry to short‐term weather conditions from event to seasonal scales. Patterns and drivers of long‐term, baseline river chemistry have remained poorly understood. Here we compile and analyze chemistry data from 506 minimally impacted rivers (412,801 data points) in the contiguous United States (CAMELS‐Chem) to identify patterns and drivers of river chemistry. Despite distinct sources and diverse reaction characteristics, a universal pattern emerges for 16 major solutes at the continental scale. Their long‐term mean concentrations (Cm) decrease with mean discharge (Qm), with elevated concentrations in arid climates and lower concentrations in humid climates, indicating overwhelming regulation by climate compared to local Critical Zone characteristics such as lithology and topography. To understand the CmQm pattern, a parsimonious watershed reactor model was solved by bringing together hydrology (storage–discharge relationship) and biogeochemical reaction theories from traditionally separate disciplines. The derivation of long‐term, steady state solutions lead to a power law form of CmQm relationships. The model illuminates two competing processes that determine mean solute concentrations: solute production by subsurface biogeochemical and chemical weathering reactions, and solute export (or removal) by mean discharge, the water flushing capacity dictated by climate and vegetation. In other words, watersheds function primarily as reactors that produce and accumulate solutes in arid climates, and as transporters that export solutes in humid climates. With space‐for‐time substitution, these results indicate that in places where river discharge dwindles in a warming climate, solute concentrations will elevate even without human perturbation, threatening water quality and aquatic ecosystems. Water quality deterioration therefore should be considered in the global calculation of future climate risks. Key Points: Continental‐scale river chemistry data show that mean discharge predominantly regulates mean concentrations of 16 solutesA simple watershed hydro‐biogeochemical reactor model illuminates that river chemistry is driven by the relative rates of solute addition (by reactions and input) and solute exportWhere river discharge dwindles in a warmer climate, higher concentrations will deteriorate water quality even without human perturbations [ABSTRACT FROM AUTHOR]

Diffuse Nitrogen pollution from agriculture maintains high pressures on groundwater and aquatic ecosystems. Further mitigation requires targeted measures that reconcile agricultural interests in environmental protection. However, the agriculture‐related processes of catchment N modeling remain poorly defined due to discipline‐specific data and knowledge gaps. Using field‐experimental data, crop N uptake responses to fertilizer management were parsimoniously conceptualized and integrated into a catchment diffuse‐N model. The improved catchment modeling further facilitated integration with agricultural budget‐based assessments. The integrated analysis in a mesoscale catchment disentangled contrasting agri‐environment functional mechanisms in typically flashy chemodynamic and transport‐limited chemostatic export regimes. Moreover, the former was actively responsive to interannual climatic variability and agricultural practices; the latter exhibited drought‐induced enhancement of N enrichment, which could likely be mitigated through reduced fertilization. This interdisciplinary integration of data and methods provided an insightful evidence base for multi‐sector targeted measures, especially under cumulative impacts of changing climate and fertilizer‐use intensities. Plain Language Summary: Due to intensive nitrogen fertilizer use in agriculture over recent decades, excessive nitrogen has largely accumulated in soil and groundwater systems and is gradually being released to surface waters, polluting aquatic environments. Considering the changing climate and growing food demand, future environmental mitigation should pursue actions that specifically target high‐risk areas and periods in order to better reconcile agricultural demand and environmental protection needs. This study integrated long‐term agricultural data sets into catchment nonpoint N pollution modeling, in ways that are methodologically complementary and provide interdisciplinary benefits. The integrated analysis advances scientific understanding of important catchment agri‐environmental processes that are coupled both spatially and temporally. The enhanced knowledge base can further support decision‐making for sustainable solutions between the needs of agriculture and the water environment. Key Points: Parsimonious crop responses to Nitrogen fertilizer are derived from agricultural experimental data and upscaled by catchment N modelingIntegrating agricultural budgets and catchment modeling reveals spatio‐temporally different agri‐environmental behaviors across scalesThe integrated analysis provides implications for targeted mitigation measures under varying climatic conditions and fertilizer inputs [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]

Understanding hydrological processes controlling stream chemistry and quantifying solute concentrations over time is crucial for estimating future alterations of water quality due to land use or climate change impacts, as well as for setting preventive or remedial actions. In the current study, soluble sodium (Na+), potassium (K+), calcium (Ca2+), and magnesium (Mg2+) concentrations and loads were assessed in waters from two small catchments located at different distances to the sea (9 km Valiñas and 30 km Abelar) in NW Spain from 2003 to 2016. Solute concentrations were determined using spectrometric techniques, while streamflow data were employed for estimating loads. Moreover, concentration-discharge relations were calculated for each solute and catchment. The average concentrations of soluble Na+, K+, Ca2+ and Mg2+ were, respectively, 16.5, 2.6, 7.9 and 4.1 mg L [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]

Regime shifts of major salinity constituents (Ca, Mg, Na, K, SO4, Cl, HCO3, and NO3) in the lower Salinas River, an agricultural ecosystem, can have major impacts on ecosystem services central to continued agricultural production in the region. Regime shifts are large, persistent, and often abrupt changes in the structure and dynamics of social-ecological systems that occur when there is a reorganization of the dominant feedbacks in the system. Monitoring information on changes in the system state, controlling variables, and feedbacks is a crucial contributor to applying sustainability and ecosystem resilience at an operational level. To better understand the factors driving salinization of the lower Salinas River on the central coast of California, we examined a 27-year record of concentrations of major salinity constituents in the river. Although limited in providing an understanding of solute flux behavior during storm events, long-term "grab sampling" datasets with accompanying stream discharges can be used to estimate the actual history of concentrations and fluxes. We developed new concentration–discharge relationships to evaluate the dynamics of chemical weathering, hydrological processes, and agricultural practices in the watershed. Examinations of long-term records of surface water and groundwater salinity are required to provide both understanding and perspective towards managing salinity in arid and semi-arid regions while also enabling determination of the influence of external climatic variability and internal drivers in the system. We found that rock weathering is the main source of Ca, Mg, Na, HCO3, and SO4 in the river that further enables ion exchange between Ca, Mg, and Na. River concentrations of K, NO3, and Cl were associated with human activities while agricultural practices were the major source of K and NO3. A more direct anthropogenic positive trend in NO3 that has persisted since the mid-1990s is associated with the lag or memory effects of field cropping and use of flood irrigation. Event to inter-year scale patterns in the lower Salinas River salinity are further controlled by antecedent hydrologic conditions. This study underscores the importance of obtaining long-term monitoring records towards understanding watershed changes-of-state and time constants on the range of driving processes. [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]

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 Canadian Prairies are subject to cold winter dynamics, spring snowmelt runoff, and summer storms; a process variability that makes it difficult to identify an adequate sampling strategy for capturing representative water quality data. Hence, our research objective was to compare multiple water quality sampling strategies for Prairie watersheds and rank them based on operational and statistical criteria. The focus was on the Catfish Creek Watershed (Manitoba, Canada), which drains into the hypereutrophic Lake Winnipeg. Water samples were collected every 7 h during the 2013 open-water season and notably analyzed for nitrate and orthophosphate. The original high-frequency dataset (7 h) was then deconstructed into lower-frequency datasets to mimic strategies involving sample collection on a daily, weekly, bi-weekly, monthly, and seasonal basis. A comparison and decision matrix was also built to assess the ability of the lower-frequency datasets to retain the statistical properties of the original (7 h) dataset. Results indicate that nutrient concentrations vary significantly over short timescales and are affected by both sampling time (day versus night) and water level fluctuations. The decision matrix revealed that seasonal sampling is sufficient when the goal is only to capture mean water quality conditions; however, sub-daily to daily sampling is required for accurate process signal representation. While we acknowledge that sampling programs designed by researchers and public agencies are often driven by different goals, we found daily sampling to be the most parsimonious strategy for the study watershed and suggest that it would help to better quantify nutrient loads to Lake Winnipeg. [ABSTRACT FROM AUTHOR]

Contents of inorganic nitrogen ( $$ {\text{NH}}^{ + }_{4} - {\text{N}} $$ and $$ {\text{NO}}^{ - }_{3} - {\text{N}} $$ ) in soil profiles were measured in five typical zones ( including permanently flooded floodplain (B), 1-year floodplain (O), 5-year floodplain (F), 10-year floodplain (T), and 100-year floodplain (H) ) from Huolin River floodplain in Erbaifangzi, Jilin Province of China, in the soil-defrozen period (May of 1999). Contour maps and profile maps were constructed to describe the spatial distributions of $$ {\text{NH}}^{ + }_{4} - {\text{N}} $$ and $$ {\text{NO}}^{ - }_{3} - {\text{N}} $$ in order to identify the influences of flood frequencies on them. Results showed that $$ {\text{NH}}^{ + }_{4} - {\text{N}} $$ generally increased with depth in soil profiles from the five areas, but $$ {\text{NH}}^{ + }_{4} - {\text{N}} $$ contents in T or H areas significantly differed from those in other areas. For $$ {\text{NO}}^{ - }_{3} - {\text{N}} $$ , with the exception that there was a significant cumulative peak (6.77 ± 0.08 mg kg-1) at 15-cm depth (10-20 cm) in B area, no significant difference was observed between $$ {\text{NO}}^{ - }_{3} - {\text{N}} $$ contents in soil profiles from the other four areas. The horizontal distributions of $$ {\text{NH}}^{ + }_{4} - {\text{N}} $$ and $$ {\text{NO}}^{ - }_{3} - {\text{N}} $$ in top soils (0-10 cm) were different in the five areas, which were greatly influenced by flood frequencies. The highest content of $$ {\text{NH}}^{ + }_{4} - {\text{N}} $$ or $$ {\text{NO}}^{ - }_{3} - {\text{N}} $$ did not appear in B area but in the floodplain with certain flood frequency. For example, $$ {\text{NH}}^{ + }_{4} - {\text{N}} $$ content (16.81 mg kg−1) in 5-year floodplain wetland was highest, and the highest content of $$ {\text{NO}}^{ - }_{3} - {\text{N}} $$ (1.69 mg kg−1) appeared in 1-year floodplain wetland. In addition, $$ {\text{NH}}^{ + }_{4} - {\text{N}} $$ contents were significantly correlated with soil pH, and $$ {\text{NO}}^{ - }_{3} - {\text{N}} $$ contents had significant correlation with inorganic carbon, but there were no significant correlations between inorganic nitrogen and other selected soil properties. [ABSTRACT FROM AUTHOR]

Fluid transit time is understood to be an important control on the shape of concentration‐discharge (C‐q) relationships, yet empirical evidence supporting this linkage is limited. We investigated C‐q relationships for weathering‐derived solutes across seven Antarctic glacial meltwater streams. We hypothesized that (H1) solute fluxes in McMurdo Dry Valley streams are reaction limited so that C‐q relationships are characterized by dilution and that (H2) transit time explains between‐stream variability in the degree of C‐q dilution. Results show that C‐q relationships are chemostatic because solute equilibrium times are shorter than stream corridor fluid transit times. Between‐stream variability in the efficiency of solute production is positively correlated with transit time, suggesting that transit time is an important control on the solute export regime. These results provide empirical evidence for the controls on weathering‐derived C‐q relationships and have important implications for Antarctic ecosystems and solute export regimes of watersheds worldwide. Plain Language Summary: Relationships between solute concentration and stream discharge (i.e., streamflow) rates in rivers contain important information regarding how water moves through a watershed. In this research, we use a combination of observations and mathematical modeling to show that the shape of concentration‐discharge relationships is related to hydrologic transit time, the duration of time a parcel of water spends moving through the watershed. Because the time scales of chemical reactions are shorter than hydrologic transit times, solute concentration is invariant with discharge. Results of this work empirically corroborate previous theoretical work regarding the physical controls on concentration‐discharge relationships, and have important implications for understanding chemical concentration patterns in rivers worldwide. Key Points: Antarctic streams exhibit chemostatic concentration‐discharge relationships for weathering‐derived solutesHydrologic transit times are short (less than four months), yet solute export is predominantly transport limited because equilibrium time scales are also short (<13 days)Hydrologic transit time explains between‐stream variability in the shape of concentration‐discharge relationships [ABSTRACT FROM AUTHOR]