Science-based, multinational management of the Baltic Sea offers lessons on amelioration of highly disturbed marine ecosystems.

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Hydrological water quality models have gained wide acceptance from environmental scientists and water managers to address deterioration of surface water quality. Higher spatiotemporal accuracy of such models is increasingly required for better understanding the functional heterogeneity of catchments and improving management decisions at different governance levels. However, balancing spatial representation and model complexity remains challenging. We present a new flexibly designed, fully distributed nitrate transport and removal model (mHM‐Nitrate) at catchment scale. The model was developed mainly based on the mesoscale Hydrological Model (mHM) and the Hydrological Predictions for the Environment (HYPE) model. The mHM‐Nitrate model was tested in the Selke catchment (Central Germany), which is characterized by heterogeneous physiographic and land‐use conditions, using adequate observed hydrological and nitrate data at three nested gauging stations. Long term (1997–2015) daily simulations showed that the model well reproduced the seasonal dynamics of biweekly nitrate observations in forested, agricultural and urban areas. High‐frequency measurements (2010‐2015) were additionally used to validate model performance of simulating short‐term changes in stream‐water concentrations that reflect changes in runoff partitioning and event‐based dilution effects. Uncertainty analysis confirmed the model's robustness. Moreover, model calculations showed that mean terrestrial nitrate input/output (in total 105 kg ha−1 yr−1) and in‐stream removal (8% of mean nitrate load) were in comparable ranges with literature, respectively. The new mHM‐Nitrate model is capable of providing detailed spatial information on nitrate concentrations and fluxes, which can motivate more specific catchment investigations on nitrate transport processes and provide guidance on spatially differentiated agricultural practices and measures.

Water quality models are increasingly used to predict nutrient losses from anthropogenically impacted catchments, but comprehensive model calibration and transfer of model parameters are often difficult. The objectives of this study are (i) to assess the Hydrological Predictions for the Environment (HYPE) model for simulating runoff and inorganic nitrogen (IN) leaching in nested and spatially heterogeneous mesoscale catchments in central Germany and (ii) to investigate the temporal and spatial variations of IN leaching. A multi‐site and multi‐objective calibration approach using the parameter estimation tool PEST was employed. Results showed that parameters related to evapotranspiration were most sensitive for runoff simulation. The nitrogen balance was controlled by plant uptake and denitrification. Runoff was well reproduced for both calibration (1994–1999) and validation (1999–2004) periods at all three gauging stations, with the lowest Nash–Sutcliffe efficiency (NSE) of 0·86 and bias (PBIAS) of less than 15%. In addition, the model was tested successfully to predict the dynamics of soil water storage during extreme climatological events. IN concentrations showed increase in magnitude and decrease in dynamics from upstream to downstream of the catchment, reflecting the combined effects of nutrient inputs and IN in‐stream retention. The dynamics of monthly IN loads were well represented by the model during the whole simulation period, with the lowest NSE and PBIAS of 0·69 and 33%, respectively. Results revealed seasonal dynamics of IN leaching due to the combined effects of hydrological and biogeochemical processes, which is consistent with runoff dynamics. This indicates the controlling role of hydrology on nitrogen transport processes. Copyright © 2013 John Wiley & Sons, Ltd.