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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.