Modelling the interplay between nitrogen cycling processes and mitigation options in farming catchments

Abstract

Quantitative assessment of mitigation measures for nitrogen (N) pollution requires adequate models, good knowledge of catchment functioning and a thorough understanding of agricultural systems and stakeholder constraints. The current paper analyses a set of results from simulations, with two models, of agricultural changes in two catchments in different contexts with different constraints. The results show that reducing N inputs and increasing grassland areas are the most efficient measures, not only because they reduce N fluxes in streams but also because they enhance N use by agriculture and the whole catchment system. Introducing catch crops, hedgerows and riparian buffers are interesting complementary measures but of limited impact when implemented alone. These results are sensitive to the way mitigation measures are translated into model inputs, and their operational implications are discussed.

Nitrate removal and young stream water fractions at the catchment scale

“…This is similar to the value of 25.6 kg/ha estimated by Casal et al (2019), who used the TNT2 model (coupling a crop model with a hydrological model to refine N processes at the soil–plant compartment). Nitrate removal represents a moderate fraction of nitrate export (less than 10%), which is consistent with current knowledge about effective but limited N removal capacity of such anthropized catchments (Beaujouan, Durand, Ruiz, Aurousseau, & Cotteret, 2002; Casal et al, 2018; Durand et al, 2015). Estimates of nitrate removal at Naizin were also provided by Molénat and Gascuel‐Odoux (2002) using MODFLOW.…”

Reduction of stream nitrate concentrations by land management in contrasted landscapes

“…These areas are limited in the catchment to strips of deep soils to sand lenses patches (Paul et al 2015). This is coherent with other modelling studies showing a large variability of the efficiency of mitigation measures and N retention processes depending on the physiographic context (Durand et al 2015;Ferrant et al 2013;Hashemi et al 2018;Thomas et al 2016). At the Auradé site, the reduction of N losses in the scenarios is partly due to a reduction of water flows, which is not the case in Kervidy-Naizin.…”

“…First, a Monte-Carlo procedure was applied to calibrate the hydrological module using the Nash Sutcliffe coefficient (NS) (Nash and Sutcliffe 1970) for daily water discharge as the objective function. Parameter values were initialized using previous simulations Durand et al (2015) for Kervidy-Naizin and Ferrant et al (2011) for Auradé. The transmissivity at soil saturation, its exponential decrease coefficient and drainage porosity of the deeper layer, which are the most sensitive parameters for discharge simulation (Beaujouan et al 2002;Moreau et al 2013) were allowed to vary around 10% of their initial values.…”

“…Under the ESCAPADE project (ANR-12-AGRO-0003) (Drouet et al 2016), agro-environmental nitrogen management scenarios were constructed in contrasting rural headwater catchments to better understand how reactive nitrogen forms are transformed and transferred into the agro-ecosystem (Galloway et al 2003) as a function of agricultural and landscape management. The practical aim was to assess whether different types of mitigation strategies are likely to achieve the objective of reducing nitrate concentrations in groundwater or streams (Durand et al 2015).…”

Eutrophication: A new wine in an old bottle?

“…Models are commonly used to assess prospective scenarios. That said, replicability remains limited without substantial data on the zone under study, and the uncertainty of the results often receives little evaluation (Udovyk and Gilek, 2013;Durand et al, 2015). Very few examples integrate coupling with climate hazard and the ecological vulnerability of aquatic environments.…”