Stream restoration can reduce nitrate levels in agricultural landscapes.

The EU Water Framework Directive (WFD) has emphasized that altered stream/river morphology and diffuse pollution are the two major pressures faced by European water bodies at catchment scales. Increasing efforts have been directed toward restoration to meet WFD standards for ecological health, but this work has achieved limited success. One challenge is that little is known about how morphological changes (i.e., re-meandering) may affect nitrate retention within whole stream networks. We investigated this issue in the well-monitored Bode catchment (3200 km2) in central Germany. First, we implemented a fully distributed process-based mHM-Nitrate model, exploring its performance over the period from 2015 to 2018. Second, we simulated the effects of restoring more natural stream morphology (i.e., increasing sinuosity) on nitrate retention. The mHM-Nitrate model performed well in replicating daily discharge and nitrate concentrations (median Kling-Gupta values of 0.78 and 0.74, respectively). Within the stream network, mean and standard deviation (SD) of gross nitrate retention efficiency was 5.1 ± 0.61 % and 74.7 ± 23.2 % in the winter and summer, respectively; this measure took into account both denitrification and assimilatory uptake. In the summer, the denitrification rate was about twice as high in a lowland sub-catchment dominated by agricultural lands as in a mountainous sub-catchment dominated by forested areas (median ± SD of 204 ± 22.6 and 102 ± 22.1 mg N m-2 d-1, respectively). Similarly, in the same season, the assimilatory uptake rate was approximately five times higher in streams surrounded by lowland agricultural areas than in streams in higher-elevation, forested areas (median ± SD of 200 ± 27.1 and 39.1 ± 8.7 mg N m-2 d-1, respectively). This suggests that restoration strategies targeted at lowland agricultural areas may have a greater potential for increasing nitrate retention. In our simulation, restoring stream sinuosity was found to increase net nitrate retention efficiency by up to 25.4 ± 5.3 %; greater effects were seen in small streams. Taken together, our results indicate that restoration efforts should consider augmenting stream sinuosity to increase nitrate retention and decrease nitrate concentrations at the catchment scale.

Reservoir water quality deterioration due to deforestation emphasizes the indirect effects of global change.

Deforestation is currently a widespread phenomenon and a growing environmental concern in the era of rapid climate change. In temperate regions, it is challenging to quantify the impacts of deforestation on the catchment dynamics and downstream aquatic ecosystems such as reservoirs and disentangle these from direct climate change impacts, let alone project future changes to inform management. Here, we tackled this issue by investigating a unique catchment-reservoir system with two reservoirs in distinct trophic states (meso­ and eutrophic), both of which drain into the largest drinking water reservoir in Germany. Due to the prolonged droughts in 2015-2018, the catchment of the mesotrophic reservoir lost an unprecedented area of forest (exponential increase since 2015 and ca. 17.1% loss in 2020 alone). We coupled catchment nutrient exports (HYPE) and reservoir ecosystem dynamics (GOTM-WET) models using a process-based modeling approach. The coupled model was validated with datasets spanning periods of rapid deforestation, which makes our future projections highly robust. Results show that in a short-term time scale (by 2035), increasing nutrient flux from the catchment due to vast deforestation (80% loss) can turn the mesotrophic reservoir into a eutrophic state as its counterpart. Our results emphasize the more prominent impacts of deforestation than the direct impact of climate warming in impairment of water quality and ecological services to downstream aquatic ecosystems. Therefore, we propose to evaluate the impact of climate change on temperate reservoirs by incorporating a time scale-dependent context, highlighting the indirect impact of deforestation in the short-term scale. In the long-term scale (e.g. to 2100), a guiding hypothesis for future research may be that indirect effects (e.g., as mediated by catchment dynamics) are as important as the direct effects of climate warming on aquatic ecosystems.

Nutrient mitigation under the impact of climate and land-use changes: A hydro-economic approach to participatory catchment management.

Excessive nutrient loadings into rivers are a well-known ecological problem. Implemented mitigation measures should ideally be cost-effective, but perfectly ranking alternative nutrient mitigation measures according to cost-effectiveness is a difficult methodological challenge. Furthermore, a particularly practical challenge is that cost-effective measures are not necessarily favoured by local stakeholders, and this may impede their successful implementation in practice. The objective of this study was to evaluate the cost-effectiveness of mitigation measures using a methodology that includes a participatory process and social learning to ensure their successful implementation. By combining cost data, hydrological modelling and a bottom-up approach for three different European catchment areas (the Latvian Berze, the Swedish Helge and the German Selke rivers), the cost-effectiveness of 16 nutrient mitigation measures were analysed under current conditions as well as under selected scenarios for future climate and land-use changes. Fertiliser reduction, wetlands, contour ploughing and municipal wastewater treatment plants are the measures that remove nutrients with the highest cost-effectiveness in the respective case study context. However, the results suggest that the cost-effectiveness of measures not only depends on their design, specific location and the conditions of the surrounding area, but is also affected by the future changes the area may be exposed to. Climate and land-use changes do not only affect the cost-effectiveness of measures, but also shape the overall nutrient loads and potential target levels in a catchment.

Balancing indicators for sustainable intensification of crop production at field and river basin levels.

Adequate tools for evaluating sustainable intensification (SI) of crop production for agro-hydrological system are not readily available. Building on existing concepts, we propose a framework for evaluating SI at the field and river basin levels. The framework serves as a means to assess and visualise SI indicator values, including yield, water-use efficiency and nitrogen-use efficiency (NUE), alongside water and nitrogen surpluses and their effects on water quantity and quality. To demonstrate the SI assessment framework, we used empirical data for both the field level (the Static Fertilization Experiment at Bad Lauchstädt) and the river basin level (the Selke basin, 463 km2) in central Germany. Crop yield and resource use efficiency varied considerably from 1980 to 2014, but without clear trends. NUE frequently fell below the desirable range (<50%), exposing the environment to a large N surplus (>80 kg N ha-1). For the catchment as a whole, the average nitrate-N concentration (3.6 mg L-1) was slightly higher than the threshold of 2.5 mg L-1 nitrate-N in surface water. However, weather and climate-related patterns, due to their effects on transport capacity and dilution, influenced water quantity and quality indicators more than agronomic practices. To achieve SI of crop production in the Selke basin, irrigation and soil moisture management are required to reduce yield variability and reduce N surpluses at field level. In addition, optimum application of fertiliser and manure could help to reduce the nitrate-N concentration below the set water quality standards in the Selke basin. In this way, there is scope for increase in yields and resource use efficiencies, and thus potential reduction of environmental impacts at basin level. We conclude that the framework is useful for assessing sustainable production, by simultaneously considering objectives related to crop production, resource-use efficiency and environmental quality, at both field and river basin levels.

Limited nitrogen retention in an urban river receiving raw sewage and wastewater treatment plant effluent.

Excessive dissolved inorganic nitrogen (DIN) added to urban river systems by point-source (PS) inputs, including raw sewage and wastewater treatment plant (WWTP) effluent, constitutes a water-quality problem of growing concern worldwide. However, the quantification of their impacts on DIN retention capacity and pathways in receiving water still remains partial. In this study, a spatially intensive water quality monitoring campaign was conducted to support the application of a water quality model to a PS-impacted urban river in Hefei City, China. The DIN retention capacities and pathway of a reference upstream Reach A, a raw-sewage-impacted Reach B and a WWTP-effluent-dominated Reach C were quantified using the model results after a Bayesian approach for parameter estimation and uncertainty analysis. The results showed that the raw sewage discharge elevated the assimilatory uptake rate but lowered its efficiency in Reach B, while the WWTP effluent discharge elevated both the denitrification rate and efficiency and made Reach C a denitrification hotspot with an increased nitrate concentration and hypoxic environment. The effects of the PS inputs on the DIN retention pathways (assimilatory uptake vs. denitrification) were regulated by their impacts on river metabolism. Despite different pathways, the total DIN retention ratios of Reaches A, B and C under low-flow conditions were 30.3% km-1, 14.3% km-1 and 6.5% km-1, respectively, which indicated that the instream DIN retention capacities were significantly impaired by the PS inputs. This result suggests that the DIN discharged from PS inputs to urban rivers will be transported with the potential to create long-term ecological implications not only locally but also more distant downstream.

Autotrophic nitrate uptake in river networks: A modeling approach using continuous high-frequency data.

High-frequency sensor measurements enable calculation of continuous autotrophic nitrate uptake rate based on its intrinsic relationship with gross primary production (GPP). The spatiotemporally available data offer prospects to advance process understandings across scales. We used continuous 15-min data (2011-2015) from a forest upstream reach and an agricultural downstream reach of the Selke River, Germany. Based on the high-frequency data, we developed a parsimonious approach for regionalizing the autotrophic uptake rate, considering effects of global radiation and riparian shading. For networked modeling, we integrated this approach into the fully distributed mesoscale hydrological nitrate model (mHM-Nitrate). Daily GPP-based uptake rate calculations showed distinct seasonal patterns and ranges in the agricultural and forest streams (mean values were 80.9 and 15.5 mgNm-2d-1, respectively). Validation in the two streams showed acceptable performance (R2 = 0.47 and 0.45, respectively) and spatial transferability of the regionalization approach, given its parsimony. Networked modeling results showed high spatiotemporal variability in nitrate transport and uptake throughout the river network. The magnitude of gross uptake increased, whereas uptake efficiency decreased significantly along stream order. Longitudinal analysis in the main stem of the Selke River revealed that riparian shading and inter-annual hydrochemical variations strongly influenced daily dynamics of the uptake efficiency. This study provides a parsimonious and transferable procedure for regionalizing in-stream autotrophic nitrate uptake based on high-frequency data at reach scale. Integrating this approach in the mHM-Nitrate model allows detailed nitrate transport and in-stream uptake processes to be investigated throughout river networks.

The Baltic Sea as a time machine for the future coastal ocean.

Coastal global oceans are expected to undergo drastic changes driven by climate change and increasing anthropogenic pressures in coming decades. Predicting specific future conditions and assessing the best management strategies to maintain ecosystem integrity and sustainable resource use are difficult, because of multiple interacting pressures, uncertain projections, and a lack of test cases for management. We argue that the Baltic Sea can serve as a time machine to study consequences and mitigation of future coastal perturbations, due to its unique combination of an early history of multistressor disturbance and ecosystem deterioration and early implementation of cross-border environmental management to address these problems. The Baltic Sea also stands out in providing a strong scientific foundation and accessibility to long-term data series that provide a unique opportunity to assess the efficacy of management actions to address the breakdown of ecosystem functions. Trend reversals such as the return of top predators, recovering fish stocks, and reduced input of nutrient and harmful substances could be achieved only by implementing an international, cooperative governance structure transcending its complex multistate policy setting, with integrated management of watershed and sea. The Baltic Sea also demonstrates how rapidly progressing global pressures, particularly warming of Baltic waters and the surrounding catchment area, can offset the efficacy of current management approaches. This situation calls for management that is (i) conservative to provide a buffer against regionally unmanageable global perturbations, (ii) adaptive to react to new management challenges, and, ultimately, (iii) multisectorial and integrative to address conflicts associated with economic trade-offs.

Improving nitrate load estimates in an agricultural catchment using Event Response Reconstruction.

Low-frequency grab sampling cannot capture fine dynamics of stream solute concentrations, which results in large uncertainties in load estimates. The recent development of high-frequency sensors has enabled monitoring solute concentrations at sub-hourly time scales. This study aimed to improve nitrate (NO3) load estimates using high-resolution records (15-min time interval) from optical sensors to capture the typical concentration response to storm events. An empirical model was developed to reconstruct NO3 concentrations during storm events in a 100-km2 agricultural catchment in Germany. Two years (Jan 2002 to Dec 2002 and Oct 2005 to Sep 2006) of high-frequency measurements of NO3 concentrations, discharge and precipitation were used. An Event Response Reconstruction (ERR) model was developed using NO3 concentration descriptor variables and predictor variables calculated from discharge and precipitation records. Fourteen events were used for calibration, and 27 events from four periods of continuous records of high-frequency measurement were used for validation. During all selected storm events, NO3 concentration decreased during flow rise and increased during the recession phase of the hydrograph. Three storm descriptor variables were used to describe these dynamics: relative change in concentration between initial and minimum NO3 concentrations (rdN), time to maximum change in NO3 concentration (TdN) and time to 50% recovery of NO3 concentration (TN rec ). The ERR consisted of building linear models of discharge and precipitation to predict these three descriptors. The ERR approach greatly improved NO3 load estimates compared to linear interpolation of grab sampling data (error decreased from 10 to 1%) or flow-weighted estimation of load (error is 7%). This study demonstrated that ERR based on a few months of high-resolution data enables accurate load estimates from low-frequency NO3 data.

Potential of vegetated ditches to manage organic pollutants derived from agricultural runoff and domestic sewage: A case study in Sinaloa (Mexico).

This case study presents the fate of selected organic, priority and emerging pollutants along a 3.6km sector of a vegetated, agricultural ditch situated in Sinaloa (Mexico). The ditch receives runoff of agriculture and domestic wastewater from an adjacent community. During 2013, the occurrence of 38 organic pollutants (pesticides, polycyclic aromatic hydrocarbons (PAHs), artificial sweeteners and pharmaceutical residues) was monitored monthly at five selected points in the ditch water. Additionally, sediment and Typha domingensis (cattail) plants were collected in March, June, and September 2013 and investigated concerning their ability to absorb and accumulate pollutants. The concentrations of the selected pollutants in the ditch water ranged from sub ngL-1 (metolachlor, atrazine) to µgL-1 (metalaxyl, acesulfame). The metabolites endosulfan sulfate and endosulfan lactone exceeded mostly the concentration of the precursor insecticide endosulfan. Sorption on sediments was of minor relevance for accumulation of pollutants in the ditch system. Concentrations in the sediments varied seasonally and ranged from 0.2 to 12,432µgkg-1 dry weight (d.w.). T. domingensis accumulated ten of the studied pollutants mainly in roots (5-1065µgkg-1 d.w.). Overall, the monitoring results of the ditch compartments indicated that downstream the concentrations of the target pollutants decreased. Under no-flow conditions in the hot season, the ditch revealed a noticeable potential to mitigate pollutants. Among the high microbial activity in the water and the subtropical climate conditions, the ditch vegetation contributed to natural attenuation of the selected pollutants.

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

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

Disentangling the influence of hydroclimatic patterns and agricultural management on river nitrate dynamics from sub-hourly to decadal time scales.

Despite extensive efforts to reduce nitrate transfer in agricultural areas, limited response is often observed in the nitrate concentration in rivers. To investigate the reasons for this limited response, nitrate dynamics in a 100km(2) agricultural catchment in eastern Germany was analysed from sub-hourly to decadal time-scales. Sub-hourly analysis of storm event dynamics during a typical hydrological year (2005-2006) was performed to identify periods of the year with high leaching risk and to link the latter to agricultural management practices in the catchment. Dynamic Harmonic Regression analysis of a 32-year (1982-2014) record of nitrate and discharge revealed that i) the long-term trend in nitrate concentration was closely related to that in discharge, suggesting that large-scale weather and climate patterns were masking the effect of improved nitrogen management on nitrate trends; ii) a persistent seasonal pattern with winter concentration maxima and summer minima could be observed, which was interpreted in terms of a dynamic nitrate concentration profile in the soil and subsoil; and iii) the catchment progressively changed from chemodynamic to more chemostatic behaviour over the three decades of study, which is a sign of long-term homogenisation of nitrate concentrations distribution over depth. This study shows that detailed physical understanding of nitrate dynamics across time scales can be obtained only through combined analysis of long-term records and high-resolution sensor data. Hence, a joint effort is advocated between environmental authorities, who usually perform long-term monitoring, and scientific programmes, which usually perform high-resolution monitoring.