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Catchment-scale nitrate dynamics involve complex coupling of hydrological transport and biogeochemical transformations, imposing challenges for source control of diffuse pollution. The Damköhler number (Da) offers a dimensionless dual-lens concept that integrates the timescales of exposure and processing, but quantifying both timescales in heterogeneous catchments remains methodologically challenging. Here, we propose a novel spatio-temporal framework for catchment-scale quantification of Da based on the ecohydrological modeling platform EcH2O-iso that coupled isotope-aided water age tracking and nitrate modeling. We examined Da variability of soil denitrification in the heterogeneous Selke catchment (456 km2, central Germany). Results showed that warm-season soil denitrification was of catchment-wide significance (Da >1), while its high spatial variations were co-determined by varying exposure times and removal efficiencies (e.g., channel-connected lowland areas are hotspots). Moreover, Da seasonally shifted from processing-dominance to transport-dominance during the wet-spring season (from >1 to <1), implying important linkages between summer terrestrial denitrification and subsequent winter river water quality. Under the prolonged 2018–2019 droughts, denitrification removal generally reduced, resulting in further accumulation in agricultural soils. Moreover, the space-time responses of Da variability indicated important implications for catchment water quality. The older water in lowland areas exhibited extra risks of groundwater contamination, whilst agricultural areas in the hydrologically responsive uplands became sensitive hotspots for export and river water pollution. Importantly, the lowland pixels intersecting river channels exhibited high removal efficiencies, as well as high resilience to the disturbances (wet-spring Da shifted to >1 under drought conditions). The proposed catchment-wide Da framework is implied by mechanistic

Calibrating distributed hydrological models often leads to equifinality due to complex model structures, which can be further exacerbated in wetlands due to spatio-temporal heterogeneity in ecohydrological processes. Here, step-wise calibrations of the physically-based distributed model EcH2O-iso was conducted in a data-rich wetland by minimizing a weighted average of the errors on discharge, stream isotopes, groundwater (GW) isotopes, and soil moisture. Results showed multi-criteria calibration outperformed single-criterion calibration as it strongly increased the overall performance, yet only marginally degraded performance of each calibration target. Isotopes were highlighted as appropriate auxiliary data as they effectively constrained the model with relatively small weights (0.1). However, those parameter sets that minimize the errors could still lead to physically implausible simulations of uncalibrated internal states or fluxes. This was further demonstrated by an approach developed to check internal fluxes based on soft data (transpiration and lateral flow), suggesting 54% of optimized models gave “right answers for the wrong reasons.” By excluding those models against soft data, such an approach further constrained equifinality, and unraveled potential inconsistencies between observations and calibration. Modeling represented the wetland as a slow-draining system mainly fed by GW, but also influenced by near-surface flow during winter or summer convectional events. Further, heterogeneity in hydrological functioning was partly attributed to distinct evapotranspiration patterns between contrasting vegetation communities. Therefore, this study not only provided insights into wetland functioning, but also revealed potential equifinality even with abundant data for calibration, and potential solutions based on the integration of isotopes and soft data.

Stable isotopes of water are ideal tracers to integrate into process-based models, advancing ecohydrological understanding. Current tracer-aided ecohydrological modeling is mostly conducted in relatively small-scale catchments, due to limited tracer data availability and often highly damped stream isotope signals in larger catchments (>100 km2). Recent model developments have prioritized better spatial representation, offering new potential for advancing upscaling in tracer-aided modeling. Here we adapted the fully distributed EcH2O-iso model to the Selke catchment (456 km2, Germany), incorporating monthly sampled isotopes from seven sites between 2012-2017. Parameter sensitivity analysis indicated that the information content of isotope data was generally complementary to discharge and more sensitive to runoff partitioning, soil water and energy dynamics. Multi-criteria calibrations revealed that inclusion of isotopes could significantly improve discharge performance during validations and isotope simulations, resulting in more reasonable estimates of stream water age seasonality. However, capturing isotopic signals of highly non-linear near-surface processes remained challenging for the upscaled model, but still allowed for plausible simulation of water ages reflecting non-stationarity in transport and mixing. The detailed modeling also helped unravel spatio-temporally varying patterns of water storage-flux-age interactions and their interplay under severe drought conditions. Embracing the upscaling challenges, this study demonstrated that even coarsely sampled isotope data can be of value in aiding ecohydrological modeling and consequent process representation in larger catchments. The derived innovative insights into ecohydrological functioning at scales commensurate with management decision making, are of particular importance for guiding science-based measures for tackling environmental changes.

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 inter-annual 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.

Stable isotopes of water are ideal tracers to integrate into process-based models, advancing ecohydrological understanding. Current tracer-aided ecohydrological modeling is mostly conducted in relatively small-scale catchments, due to limited tracer data availability and often highly damped stream isotope signals in larger catchments (>100 km2). Recent model developments have prioritized better spatial representation, offering new potential for advancing upscaling in tracer-aided modeling. Here we adapted the fully distributed EcH2O-iso model to the Selke catchment (456 km2, Germany), incorporating monthly sampled isotopes from seven sites between 2012-2017. Parameter sensitivity analysis indicated that the information content of isotope data was generally complementary to discharge and more sensitive to runoff partitioning, soil water and energy dynamics. Multi-criteria calibrations revealed that inclusion of isotopes could significantly improve discharge performance during validations and isotope simulations, resulting in more reasonable estimates of stream water age seasonality. However, capturing isotopic signals of highly non-linear near-surface processes remained challenging for the upscaled model, but still allowed for plausible simulation of water ages reflecting non-stationarity in transport and mixing. The detailed modeling also helped unravel spatio-temporally varying patterns of water storage-flux-age interactions and their interplay under severe drought conditions. Embracing the upscaling challenges, this study demonstrated that even coarsely sampled isotope data can be of value in aiding ecohydrological modeling and consequent process representation in larger catchments. The derived innovative insights into ecohydrological functioning at scales commensurate with management decision making, are of particular importance for guiding science-based measures for tackling environmental changes.

Stable isotopes of water are ideal tracers to integrate into process-based models, advancing ecohydrological understanding. Current tracer-aided ecohydrological modeling is mostly conducted in relatively small-scale catchments, due to limited tracer data availability and often highly damped stream isotope signals in larger catchments (>100 km2). Recent model developments have prioritized better spatial representation, offering new potential for advancing upscaling in tracer-aided modeling. Here we adapted the fully distributed EcH2O-iso model to the Selke catchment (456 km2, Germany), incorporating monthly sampled isotopes from seven sites between 2012-2017. Parameter sensitivity analysis indicated that the information content of isotope data was generally complementary to discharge and more sensitive to runoff partitioning, soil water and energy dynamics. Multi-criteria calibrations revealed that inclusion of isotopes could significantly improve discharge performance during validations and isotope simulations, resulting in more reasonable estimates of stream water age seasonality. However, capturing isotopic signals of highly non-linear near-surface processes remained challenging for the upscaled model, but still allowed for plausible simulation of water ages reflecting non-stationarity in transport and mixing. The detailed modeling also helped unravel spatio-temporally varying patterns of water storage-flux-age interactions and their interplay under severe drought conditions. Embracing the upscaling challenges, this study demonstrated that even coarsely sampled isotope data can be of value in aiding ecohydrological modeling and consequent process representation in larger catchments. The derived innovative insights into ecohydrological functioning at scales commensurate with management decision making, are of particular importance for guiding science-based measures for tackling environmental changes.

Nitrate (NO3-N) mobilization is generally controlled by available sources, hydrological connectivity and biogeochemical transformations along the dominant flow paths. However, their spatial heterogeneity and complex interactions often impede integrated understanding of NO3-N dynamics at the catchment scale. To fully integrate spatiotemporal information for NO3-N simulations, a grid-based model, mHM-Nitrate, was applied to a 68 km2 lowland, mixed land use catchment (Demnitzer Millcreek, DMC) near Berlin. The model successfully captured the spatiotemporal distribution of flow and NO3-N between 2001-2019, but was less successful in 1992-2000 due to land management changes. Re-optimization of relative parameters was subsequently conducted for this period to understand management effects. The simulated results revealed landscape characteristics and hydroclimatic variability as the main controlling factors on respective spatial and temporal patterns. The combined effects of vegetation cover and fertilizer inputs dictated the spatial distribution of water and NO3-N fluxes, while wetness condition determined the temporal NO3-N dynamics by regulating hydrological connectivity and NO3-N mobilization. Denitrification was also closely coupled with hydroclimatic conditions, which accounted for ∼20% of NO3-N inputs. In contrast, restoration of riparian wetlands had a modest impact on NO3-N export (∼10% reduction during 2001-2019), suggesting further interventions (e.g., reducing fertilizer application or increased wetland areas) are needed. Our modelling application demonstrated that mHM-Nitrate could provide robust spatially distributed simulations of hydrological and NO3-N fluxes over a long-term period and could successfully differentiate the key controlling factors. This underlines the model’s value in contributing to an evidence base to guide future management practices under climate change.

Distributed models have been increasingly applied at finer spatiotemporal resolution. However, most diagnostic analyses aggregate performance measures in space or time, which might bias subsequent inferences. Accordingly, this study explores an approach for quantifying the parameter sensitivity in a spatiotemporally explicit way. We applied the Morris method to screen key parameters within four different sampling spaces in a grid-based model (mHM-Nitrate) for NO3-N simulation in a mixed landuse catchment using a one-year moving window for each grid. The results showed that an overly-wide range of aquatic denitrification rates could mask the sensitivity of the other parameters, leading to their spatial patterns only related to the proximity to outlet. With adjusted parameter space, spatial sensitivity patterns were determined by NO3-N inputs and hydrological transport capacity, while temporal dynamics were regulated by annual wetness conditions. The relative proportion of parameter sensitivity further indicated the shifts in dominant hydrological/NO3-N processes between wet and dry years. By identifying not only which parameter(s) is(are) influential, but where and when such influences occur, SSA can help evaluate current model parameterisation. Given the marked sensitivity in agricultural areas, we suggest that the current NO3-N parameterisation scheme (land use-dependent) could be further disentangled in these regions (e.g., into croplands with different rotation strategies) but aggregated in non-agricultural areas; while hydrological parameterisation could be resolved into a finer level (from spatially constant to land use-dependent especially in nutrient-rich regions). The spatiotemporal sensitivity pattern also highlights NO3-N transport within soil layers as a focus for future model development.

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 inter-annual 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.

High spatial heterogeneity of catchment properties enhances the variability of ecohydrological responses to changing natural and anthropogenic conditions, like the European‐wide droughts in 2018‐2019. Based on new adaptations of a tracer‐aided, process‐based ecohydrological model (EcH2O‐iso), we investigated drought‐induced nonstationary ecohydrological behaviour in a small agricultural headwater catchment (1.44 km2) in central Germany. Multiple environmental time‐series helped inform various aspects of catchment functioning that have been impacted by agricultural activity and changing climate conditions, and helped to further constrain model calibration. Multi‐criteria calibration showed that data collected during drought years were highly informative in reproducing the changes in stream water dynamics. Further, inclusion of 2H and 18O data were valuable for reducing model uncertainty and increasing confidence in simulations of green‐ and blue‐water flux partitioning and storage‐flux‐age interactions. Using the best‐performing calibrations, we further analyzed the high spatiotemporal variability of internal ecohydrological processes and the varying responses of fluxes and associated water ages to prolonged drought stress. Under drought conditions, modelled stream runoff contributed from deeper, older storages increased significantly after a particularly wet season, resulting in a sharp increase in stream water age. Unlike relatively minor changes in soil evaporation, seasonally typical transpiration fluxes were initially maintained in April‐June but dramatically decreased as the drought further developed in July‐September. Importantly, the tracer‐based transpired water age was much older after April, providing a potential indicator of drought impacts and the need for precautionary management responses. Our findings are important for similar agricultural headwater ecosystems in other drought‐sensitive regions.

Small run-of-river hydropower may significantly contribute towards meeting global renewable energy targets. However, exploitation of river flows for energy production triggers environmental impacts and conflicts among stakeholders, thereby requiring optimal water resources allocation strategies. The variety of interests at stake demands instruments to quantitatively assess manifold effects of water management choices. In this work, analytic tools to guide design of run-of-river power plants when incommensurable objectives must be jointly maximized are presented. The approach is grounded on the concept of Paretian efficiency and applied to a hypothetical case study in Scotland, where energy production could compete with regionally relevant ecosystem services. We found that a multi-objective design complying with predefined environmental regulation entails significant economic losses without safeguarding ecological functions. Conversely, if the environmental flow is regarded as a decision variable subject to minimum lawful values, economically appealing and ecologically effective plant configurations emerge. Our findings suggest the existence of broadly valid alternative strategies for designing small run-of-river hydropower while preserving ecological functions, associated to small or large plant capacities. Local hydrologic conditions and target ecosystem services determine the most effective strategy for specific case studies. The analysis indicates that larger power plants are sometimes the most effective way to preserve ecosystems services through economically viable projects. Therefore, renewable energy policy should avoid incentive schemes that penalize a priori larger installations. The approach offers an objective basis to identify effective hydropower design, management and policies when additional ecosystems services are considered, thus supporting a sustainable intensification of run-of-river energy production.

Pristine tropical forests play a critical role in regional and global climate systems. For a better understanding of the eco‐hydrology of tropical “evergreen” vegetation, it is essential to know the partitioning of water into transpiration and evaporation, runoff and associated water ages. For this purpose, we evaluated how topography and vegetation influence water flux and age dynamics at high temporal (hourly) and spatial (10 m) resolution using the Spatially Distributed Tracer‐Aided Rainfall‐Runoff model for the tropics (STARRtropics). The model was applied in a tropical rainforest catchment (3.2 km2) where data were collected biweekly to monthly and during intensive monitoring campaigns from January 2013 to July 2018. The STARRtropics model was further developed, incorporating an isotope mass balance for evapotranspiration partitioning into transpiration and evaporation. Results exhibited a rapid streamflow response to rainfall inputs (water and isotopes) with limited mixing and a largely time‐invariant baseflow isotope composition. Simulated soil water storage showed a transient response to rainfall inputs with a seasonal component directly resembling the streamflow dynamics which was independently evaluated using soil water content measurements. High transpiration fluxes (max 7 mm/day) were linked to lower slope gradients, deeper soils and greater leaf area index. Overall water partitioning resulted in 65% of the actual evapotranspiration being driven by vegetation with high transpiration rates over the drier months compared to the wet season. Time scales of water age were highly variable, ranging from hours to a few years. Stream water ages were conceptualized as a mixture of younger soil water and slightly older, deeper soil water and shallow groundwater with a maximum age of roughly 2 years during drought conditions (722 days). The simulated soil water ages ranged from hours to 162 days and for shallow groundwater up to 1,200 days. Despite the model assumpt

The fate of the vast stocks of organic carbon stored in permafrost of the Western Siberian Lowland, the world's largest peat-land, is uncertain. Specifically, the amount of greenhouse gas emissions from rivers in the region is unknown. Here we present estimates of annual CO2 emissions from 58 rivers across all permafrost zones of the Western Siberian Lowland, between 56 and 67 degrees N. We find that emissions peak at the permafrost boundary, and decrease where permafrost is more prevalent and in colder climatic conditions. River CO2 emissions were high, and on average two times greater than downstream carbon export. We suggest that high emissions and emission/export ratios are a result of warm temperatures and the long transit times of river water. We show that rivers in the Western Siberian Lowland play an important role in the carbon cycle by degassing terrestrial carbon before its transport to the Arctic Ocean, and suggest that changes in both temperature and precipitation are important for understanding and predicting high-latitude river CO2 emissions in a changing climate.

The Western Siberian Lowlands (WSL) store large quantities of organic carbon that will be exposed and mobilized by the thawing of permafrost. The fate of mobilized carbon, however, is not well understood, partly because of inadequate knowledge of hydrological controls in the region which has a vast low-relief surface area, extensive lake and wetland coverage and gradually increasing permafrost influence. We used stable water isotopes to improve our understanding of dominant landscape controls on the hydrology of the WSL. We sampled rivers along a 1700 km South-North transect from permafrost-free to continuous permafrost repeatedly over three years, and derived isotope proxies for catchment hydrological responsiveness and connectivity. We found correlations between the isotope proxies and catchment characteristics, suggesting that lakes and wetlands are intimately connected to rivers, and that permafrost increases the responsiveness of the catchment to rainfall and snowmelt events, reducing catchment mean transit times. Our work provides rare isotope-based field evidence that permafrost and lakes/wetlands influence hydrological pathways across a wide range of spatial scales (10-105 km2) and permafrost coverage (0%-70%). This has important implications, because both permafrost extent and lake/wetland coverage are affected by permafrost thaw in the changing climate. Changes in these hydrological landscape controls are likely to alter carbon export and emission via inland waters, which may be of global significance.

Headwater catchments in the Andes provide critical sources of water for downstream areas with large agricultural communities dependent upon irrigation. Data from such remote headwater catchments are sparse, and there is limited understanding of their hydrological function to guide sustainable water management. Here, we present the findings of repeat synoptic tracer surveys as rapid appraisal tools to understand dominant hydrological flow paths in the semi-arid Rio Grande basin, a 572-km(2) headwater tributary of the 11,696-km(2) Limari basin in central Chile. Stable isotopes in stream water show a typical altitudinal effect, with downstream enrichment in delta H-2 and delta O-18 ratios. Seasonal signals are displayed in the isotopic composition of the springtime melting season water line with a steeper gradient, whilst evaporative effects are represented by lower seasonal gradients for autumn and summer. Concentrations of solutes indexed by electrical conductivity indicate that there are limited contributions of deeper mineralised groundwater to streamflow and that weathering rates vary in the different sub-catchments. Although simplistic, the insights gained from the study could be used to inform the structure and parameterisation of rainfall runoff models to provide seasonal discharge predictions as an evidence base for decision making in local water management.