资源环境科技发展态势分析平台

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.

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