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This article in JEQ

  1. Vol. 37 No. 6, p. 2155-2169
     
    Received: Sept 24, 2007


    * Corresponding author(s): tisseuil@cict.fr
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doi:10.2134/jeq2007.0507

Modeling the Stream Water Nitrate Dynamics in a 60,000-km2 European Catchment, the Garonne, Southwest France

  1. Clément Tisseuil *a,
  2. Andrew J. Wadeb,
  3. Loïc Tudesquea and
  4. Sovan Leka
  1. a Laboratoire Evolution et Diversité Biologique (EDB) UMR 5174, CNRS- Université Paul Sabatier, 118 route de Narbonne, 31062 Toulouse cedex 4– France
    b Aquatic Environments Research Centre, School of Human and Environmental Sciences, Univ. of Reading, RG6 6AB, UK

Abstract

The spatial and temporal dynamics in the stream water NO3–N concentrations in a major European river-system, the Garonne (62,700 km2), are described and related to variations in climate, land management, and effluent point-sources using multivariate statistics. Building on this, the Hydrologiska Byråns Vattenbalansavdelning (HBV) rainfall-runoff model and the Integrated Catchment Model of Nitrogen (INCA-N) are applied to simulate the observed flow and N dynamics. This is done to help us to understand which factors and processes control the flow and N dynamics in different climate zones and to assess the relative inputs from diffuse and point sources across the catchment. This is the first application of the linked HBV and INCA-N models to a major European river system commensurate with the largest basins to be managed under the Water Framework Directive. The simulations suggest that in the lowlands, seasonal patterns in the stream water NO3–N concentrations emerge and are dominated by diffuse agricultural inputs, with an estimated 75% of the river load in the lowlands derived from arable farming. The results confirm earlier European catchment studies. Namely, current semi-distributed catchment-scale dynamic models, which integrate variations in land cover, climate, and a simple representation of the terrestrial and in-stream N cycle, are able to simulate seasonal NO3–N patterns at large spatial (>300 km2) and temporal (≥ monthly) scales using available national datasets.

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Copyright © 2008. American Society of Agronomy, Crop Science Society of America, Soil Science SocietyAmerican Society of Agronomy, Crop Science Society of America, and Soil Science Society of America