The need to develop and provide integrated observation systems to better understand and manage global and regional environmental change is one of the major challenges facing Earth system science today. In 2008, the German Helmholtz Association took up this challenge and launched the German research infrastructure TERrestrial ENvironmental Observatories (TERENO). The aim of TERENO is the establishment and maintenance of a network of observatories as a basis for an interdisciplinary and long-term research programme to investigate the effects of global environmental change on terrestrial ecosystems and their socio-economic consequences. State-of-the-art methods from the field of environmental monitoring, geophysics, remote sensing, and modelling are used to record and analyze states and fluxes in different environmental disciplines from groundwater through the vadose zone, surface water, and biosphere, up to the lower atmosphere. Over the past 15 years we have collectively gained experience in operating a long-term observing network, thereby overcoming unexpected operational and institutional challenges, exceeding expectations, and facilitating new research. Today, the TERENO network is a key pillar for environmental modelling and forecasting in Germany, an information hub for practitioners and policy stakeholders in agriculture, forestry, and water management at regional to national levels, a nucleus for international collaboration, academic training and scientific outreach, an important anchor for large-scale experiments, and a trigger for methodological innovation and technological progress. This article describes TERENO’s key services and functions, presents the main lessons learned from this 15-year effort, and emphasises the need to continue long-term integrated environmental monitoring programmes in the future.

Excess nitrogen (N) from anthropogenic sources deteriorates freshwater resources. Actions taken to reduce N inputs to the biosphere often show no or only delayed effects in receiving surface waters hinting at large legacy N stores built up in the catchments soils and groundwater. Here, we quantify transport and retention of N in 238 Western European catchments by analyzing a unique data set of long-term N input and output time series. We find that half of the catchments exhibited peak transport times larger than five years with longer times being evident in catchments with high potential evapotranspiration and low precipitation seasonality. On average the catchments retained 72% of the N from diffuse sources with retention efficiency being specifically high in catchments with low discharge and thick, unconsolidated aquifers. The estimated transport time scales do not explain the observed N retention, suggesting a dominant role of biogeochemical legacy in the catchments’ soils rather than a legacy store in the groundwater. Future water quality management should account for the accumulated biogeochemical N legacy to avoid long-term leaching and water quality deteriorations for decades to come.

In 2018–2019, Central Europe experienced an unprecedented multi-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 modelling 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 70% 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 multi-year 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.

Runoff events play an important role for nitrate export from catchments, but the variability of nutrient export patterns between events and catchments is high and the dominant drivers remain difficult to disentangle. Here, we rigorously asses if detailed knowledge on runoff event characteristics can help to explain this variability. To this end, we conducted a long-term (1955 - 2018) event classification using hydro-meteorological data, including soil moisture, snowmelt and the temporal organization of rainfall, in six neighboring mesoscale catchments with contrasting land use types. We related these event characteristics to nitrate export patterns from high-frequency nitrate concentration monitoring (2013 - 2017) using concentration-discharge relationships. Our results show that small rainfall-induced events with dry antecedent conditions exported lowest nitrate concentrations and loads but exhibited highly variable concentration-discharge relationships. We explain this by a low fraction of active flow paths, revealing the spatial heterogeneity of nitrate sources within the catchments and by an increased impact of biogeochemical retention processes. In contrast, large rainfall or snowmelt-induced events exported highest nitrate concentrations and loads and converged to similar chemostatic export patterns across all catchments, without exhibiting source limitation. We explain these homogenous export patterns by high catchment wetness that activated a high number of flow paths. Long-term hydro-meteorological data indicated an increase of events with dry antecedent conditions in summer and decreased snow-influenced events. These trends will likely continue and lead to an increased nitrate concentration variability during low-flow seasons and to changes in the timing of largest nitrate export peaks during high-flow seasons.

Understanding catchment controls on catchment solute export is a prerequisite for water quality management. StorAge Selection (SAS) functions encapsulate essential information about catchment functioning in terms of discharge selection preference and solute export dynamics. However, they lack information on the spatial origin of solutes when applied at the catchment scale, thereby limiting our understanding of the internal (subcatchment) functioning. Here, we parameterized SAS functions in a spatially explicit way to understand the internal catchment responses and transport dynamics of reactive dissolved nitrate (N-NO3). The model was applied in a nested mesoscale catchment (457 km²), consisting of a mountainous partly forested, partly agricultural subcatchment, a middle-reach forested subcatchment, and a lowland agricultural subcatchment. The model captured flow and nitrate concentration dynamics not only at the catchment outlet but also at internal gauging stations. Results reveal disparate subsurface mixing dynamics and nitrate export among headwater and lowland subcatchments. The headwater subcatchment has high seasonal variation in subsurface mixing schemes and younger water in discharge, while the lowland subcatchment has less pronounced seasonality in subsurface mixing and much older water in discharge. Consequently, nitrate concentration in discharge from the headwater subcatchment shows strong seasonality, whereas that from the lowland subcatchment is stable in time. The temporally varying responses of headwater and lowland subcatchments alternates the dominant contribution to nitrate export in high and low-flow periods between subcatchments. Overall, our results demonstrate that the spatially explicit SAS modeling provides useful information about internal catchment functioning, helping to develop or evaluate spatial management practices.

Elevated nitrate concentrations in German water bodies are a widespread problem, potentially resulting from a long history of excess nitrogen (N) inputs. Here, we investigated long-term (1950-2014) N dynamics across 89 German catchments using a process-based model. Results showed that the mean fractions of N surplus (excess) exported to the river, removed by denitrification, accumulated in the soil zone, and accumulated in groundwater across all catchments are 27%, 58%, 14%, and 1%, respectively. Dissolved inorganic N in groundwater could affect the stream N levels over decades as indicated by long groundwater transit times. A cluster identified four catchment groups with distinct archetypal long-term N transport and retention dynamics, which can be partly linked to the catchments’ topographic and geological conditions. This hints at underlying mechanisms that explain spatial differences in the fate of diffuse N inputs to catchments and opens the possibility for better-targeted management

StorAge Selection (SAS) functions describe how catchments selectively remove water of different ages in storage via discharge, thus controlling the transit time distribution (TTD) and solute composition of discharge. SAS-based models have been emerging as promising tools for quantifying catchment-scale solute export, providing a coherent framework for describing both velocity and celerity driven transport. However, due to their application in headwaters only, the spatial heterogeneity of catchment physiographic characteristics, land-use management practices, and large-scale validation have not been adequately addressed with SAS-based models. In this study, we integrated SAS functions into the grid-based mHM-Nitrate model (mesoscale Hydrological Model) at both grid scale (distributed model) and catchment scale (lumped model). The proposed model provides a spatially distributed representation of nitrogen dynamics within the soil zone and a unified approach for representing both velocity and celerity driven subsurface transport below the soil zone. The model was tested in a heterogeneous mesoscale catchment. Simulated results show a strong spatial heterogeneity in nitrogen dynamics within the soil zone, highlighting the necessity of a spatially explicit approach for describing near-surface nitrogen processing. The lumped model could well capture instream nitrate concentration dynamics and the concentration-discharge relationship at the catchment outlet. In addition, the model could satisfactorily represent the relations between subsurface storage, mixing scheme, solute export, and the TTDs of discharge. The distributed model shows comparable results with the lumped model. Overall, the results reveal the potential for large-scale applications of SAS-based transport models, contributing to the understanding of water quality-related issues in agricultural landscapes.

Elevated nutrient inputs and reduced riverine concentration variability challenge the health and functioning of aquatic ecosystems. To improve riverine water quality management, it is necessary to understand the underlying biogeochemical and physical processes and their interactions at catchment scale. We hypothesize that spatial heterogeneity of nutrient sources dominantly controls the variability of instream concentrations among different catchments. Therefore, we investigated controls of mean nitrate (NO), phosphate (PO), and total organic carbon (TOC) concentrations and concentration-discharge (C-Q) relationships from observations in 787 German catchments covering a wide range of physiographic and anthropogenic settings. Using partial least square regressions and random forests we linked water quality metrics to catchment characteristics. We found archetypal C-Q patterns with enrichment dominating NO and TOC, and dilution dominating PO export. Across the catchments, we found a positive but heteroscedastic relation between mean NO concentrations and agricultural land use. We argue that denitrification, particularly pronounced in sedimentary aquifers, buffers high inputs and causes a decline in concentration with depth resulting in chemodynamic, strongly positive C-Q patterns. Consequently, chemodynamic NO enrichment patterns could indicate effective subsurface denitrification. Mean PO concentrations were related to point sources though the low predictive power suggests effects of unaccounted processes. In contrast, diffuse inputs better explained the spatial differences in PO C-Q patterns. TOC levels were positively linked to the abundance of riparian wetlands as well as negatively to NO concentrations suggesting interacting processes. This study shows that vertical concentration heterogeneity mainly drives nutrient export dynamics, partially modified by interactions with other controls.

Defining effective measures to reduce nitrate pollution in heterogeneous mesoscale catchments remains challenging if based on concentration measurements at the outlet only. One reason is our limited understanding of the sub-catchment contributions to nitrate export and their importance at different time scales. While upstream sub-catchments often disproportionally contribute to runoff generation and in turn to nutrient export, agricultural areas, which are typically found in downstream lowlands, are known to be a major source for nitrate pollution. To disentangle the interplay of these contrasting drivers of nitrate export, we analyzed seasonal long-term trends and event dynamics of nitrate concentrations, loads and the concentration-discharge relationship in three nested catchments within the Selke catchment (456 km²), Germany. The upstream sub-catchments (40.4 % of total catchment area, 34.5 % of N input) had short transit times and dynamic concentration-discharge relationships with elevated nitrate concentrations during wet seasons and events. Consequently, the upstream sub-catchments dominated nitrate export during high flow and disproportionally contributed to overall annual nitrate loads at the outlet (64 %). The downstream sub-catchment was characterized by higher N input, longer transit times and relatively constant nitrate concentrations between seasons, dominating nitrate export during low flow periods. Neglecting the disproportional role of upstream sub-catchments for temporally elevated nitrate concentrations and net annual loads can lead to an overestimation of the role of agricultural lowlands. Nonetheless, in agricultural lowlands, constantly high concentrations from nitrate legacies pose a long-term threat to water quality. This knowledge is crucial for an effective and site-specific water quality management.

Improving nitrogen (N) status in European water bodies is a pressing issue. N levels depend not only on current but also past N inputs to the landscape, that have accumulated through time in legacy stores (e.g. soil, groundwater). Catchment-scale N models, that are commonly used to investigate in-stream N levels, rarely examine the magnitude and dynamics of legacy components. This study aims to gain a better understanding of the long-term fate of the N inputs and its uncertainties, using a legacy-driven N model (ELEMeNT) in Germany’s largest national river basin (Weser; 38,450 km2) over the period 1960-2015. We estimate the nine model parameters based on a progressive constraining strategy, to assess the value of different observational datasets. We demonstrate that beyond in-stream N loading, soil N content and in-stream N concentration allow to reduce the equifinality in model parameterizations. We find that more than 50% of the N surplus denitrifies (1480-2210 kg ha-1) and the stream export amounts to around 18% (410-640 kg ha-1), leaving behind as much as around 230-780 kg ha-1 of N in the (soil) source zone and 10-105 kg ha-1 in the subsurface. A sensitivity analysis reveals the importance of different factors affecting the residual uncertainties in simulated N legacies, namely hydrologic travel time, denitrification rates, a coefficient characterising the protection of organic N in source zone and N surplus input. Our study calls for proper consideration of uncertainties in N legacy characterization, and discusses possible avenues to further reduce the equifinality in water quality modelling.