4.7 Article

Assessing N emissions in surface water at the national level: Comparison of country-wide vs. regionalized models

期刊

SCIENCE OF THE TOTAL ENVIRONMENT
卷 443, 期 -, 页码 152-162

出版社

ELSEVIER
DOI: 10.1016/j.scitotenv.2012.10.011

关键词

Nitrate; Nutrient retention; Nitrogen surplus; Statistical modeling; Load estimation; Catchment

资金

  1. ONEMA, the French National Agency for Water and Aquatic Environments

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Many countries are developing models to estimate N emissions in rivers as part of national-scale water quality assessments. Generally, models are applied with national databases, while at the regional scale, more detailed databases are sometimes available. This paper discusses pros and cons of developing regionalized models versus applying countrywide models. A case study is used to support the discussion. The model used, called Nutting-N (NUTrient Transfer modelING-Nitrogen), relies on a statistical approach linking nitrogen sources and watershed land and river characteristics and aims to evaluate the risk of water bodies failing to reach quality objectives defined by national and federal policies. After calibration and evaluation at the national scale (France), the predictive quality of the model was compared with two regionalized models in a crystalline massif (Brittany, western France, 27,000 km(2)) and in a sedimentary basin (Seine, Paris basin, 78,000 km2), where detailed regional databases are available. The national-scale model provided robust predictions in most conditions encountered in France (efficiency=0.69). Terrestrial retention was related mainly to specific runoff, and its median value was estimated at 49% of the N surplus, whereas median river retention represented 18% of incoming N discharge. Regionalizing the model generally improved goodness-of-fit, as the root mean squared error was reduced by 6-24%. However, precision of parameter estimates degraded when too few monitoring basins were available or when variability in land and river characteristics was too low in the calibration dataset Hence, regional-scale models should be advocated only after the trade-off between improvement of fit and degradation of parameter estimates is examined. (C) 2012 Elsevier B.V. All rights reserved.

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