Record number :
958901
Title of article :
Multispectral remotely sensed data in modelling the annual variability of nitrate concentrations in the leachate
Author/Authors :
Carsten Montzka a، نويسنده , , *، نويسنده , , Morton Canty، نويسنده , , Peter Kreins b، نويسنده , , Ralf Kunkel a، نويسنده , , Gunter Menz c، نويسنده , , Harry Vereecken ، نويسنده , , Frank Wendland a، نويسنده ,
Issue Information :
ماهنامه با شماره پیاپی سال 2008
Pages :
12
From page :
1070
To page :
1081
Abstract :
The advantages of using multispectral remotely sensed data instead of CORINE Land Cover for the modelling of nitrate concentrations in the leachate of the Rur catchment are presented and discussed in this paper. In this context it has been shown that the identification of main crops and annual crop rotation in the Rur catchment by SPOT, LANDSAT and ASTER imagery provides the key for a spatial and thematic enhancement of the model results. The spatial resolution of the nitrogen surplus data set which denotes the linkage between RAUMIS and GROWA is enhanced from district level to field/pixel level. In parallel, the empirical water balance model GROWA is enhanced to differentiate between agricultural crops in the real evapotranspiration calculation. It is calibrated by runoff data measured at gauging stations. Results indicate, e.g., an average nitrate concentration in the leachate of 42 mg NO3/L in the relatively wet year of 2002 and almost 62 mg NO3/L in the dry year of 2003. There is a 20 mg NO3/L weather-induced difference which can be modelled in a more detailed way using self-processed remotely sensed data. The model results were compared to nitrate concentrations observed in the top parts of multi-level wells. In this way the related coefficient of determination has been improved from a value (R) of 0.50 using CORINE to 0.59 by using self-processed remotely sensed data, thus demonstrating the potential of the enhanced model system.
Keywords :
Remote sensing , disaggregation , nitrate concentration , crop rotation , Model coupling , diffuse pollution
Journal title :
Environmental Modelling and Software
Serial Year :
2008
Link To Document :
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