Modelling nitrogen loads at the catchment scale under the influence of land use.

Payraudeau, S. and Cernesson, F. and Tournoud, M. G. and Beven, Keith J. (2004) Modelling nitrogen loads at the catchment scale under the influence of land use. Physics and Chemistry of the Earth, 29 (11-12). pp. 811-819. ISSN 1474-7065

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Abstract

Land use data are essential for water quality models. Pollutant inputs to streams are indeed a direct function of human activities that can be represented, at least approximately, in terms of land use. Remote sensing is a valuable data source to determine the land use on a catchment. However the land use data obtained by this kind of information are subject to significant uncertainties, including misclassification or categorical uncertainty. This paper presents a method to analyse the impact of the land use categorical uncertainty on the responses of a nitrogen load model at the outlet of a catchment. We use the POL model, a semi-distributed event-based model on a French Mediterranean rural catchment and we focus on agricultural land use. First, the sensitivity analysis realised by simulations considering a uniform land use on the catchment, shows a great sensitivity of the estimated load to the land use change. Second, the categorical land use uncertainty is analysed on a total nitrogen load prediction set calculated with randomly generated land use maps consistent with the confusion matrix that characterizes misclassification of land use. Thus, from 1% to 10% of misclassified agricultural area results in a variation of almost 40% on nitrogen loads for the three studied events. Misclassified areas explain from 46% to 75% of the variance of the estimated nitrogen load. These first results illustrate the importance of sensitivity and uncertainty analyses to improve the confidence of a water quality model and need to be extended to other input data sets.

Item Type:
Journal Article
Journal or Publication Title:
Physics and Chemistry of the Earth
Uncontrolled Keywords:
/dk/atira/pure/researchoutput/libraryofcongress/ge
Subjects:
?? PREDICTION UNCERTAINTYMODEL SENSITIVITYLAND USEWATER QUALITY MODELGEOCHEMISTRY AND PETROLOGYGEOPHYSICSGE ENVIRONMENTAL SCIENCES ??
ID Code:
21343
Deposited By:
Deposited On:
12 Jan 2009 10:23
Refereed?:
Yes
Published?:
Published
Last Modified:
15 Sep 2023 03:49