![Hier klicken, um den Treffer aus der Auswahl zu entfernen](images/unchecked.gif) |
Titel |
Agro-hydrology and multi-temporal high-resolution remote sensing: toward an explicit spatial processes calibration |
VerfasserIn |
S. Ferrant, S. Gascoin, A. Veloso, J. Salmon-Monviola, M. Claverie, V. Rivalland, G. Dedieu, V. Demarez, E. Ceschia, J.-L. Probst, P. Durand, V. Bustillo |
Medientyp |
Artikel
|
Sprache |
Englisch
|
ISSN |
1027-5606
|
Digitales Dokument |
URL |
Erschienen |
In: Hydrology and Earth System Sciences ; 18, no. 12 ; Nr. 18, no. 12 (2014-12-16), S.5219-5237 |
Datensatznummer |
250120566
|
Publikation (Nr.) |
copernicus.org/hess-18-5219-2014.pdf |
|
|
|
Zusammenfassung |
The growing availability of high-resolution satellite image series offers
new opportunities in agro-hydrological research and modeling. We
investigated the possibilities offered for improving crop-growth dynamic
simulation with the distributed agro-hydrological model: topography-based
nitrogen transfer and transformation (TNT2). We used a leaf area index (LAI) map series
derived from 105 Formosat-2 (F2) images covering the period 2006–2010. The
TNT2 model (Beaujouan et al., 2002), calibrated against discharge and
in-stream nitrate fluxes for the period 1985–2001, was tested on the
2005–2010 data set (climate, land use, agricultural practices, and discharge
and nitrate fluxes at the outlet). Data from the first year (2005) were used
to initialize the hydrological model. A priori agricultural practices obtained from
an extensive field survey, such as seeding date, crop cultivar, and amount
of fertilizer, were used as input variables. Continuous values of LAI as a
function of cumulative daily temperature were obtained at the crop-field
level by fitting a double logistic equation against discrete
satellite-derived LAI. Model predictions of LAI dynamics using the a priori input
parameters displayed temporal shifts from those observed LAI profiles that are
irregularly distributed in space (between field crops) and time (between
years). By resetting the seeding date at the crop-field level, we have
developed an optimization method designed to efficiently minimize this
temporal shift and better fit the crop growth against both the spatial
observations and crop production. This optimization of simulated LAI
has a negligible impact on water budgets at the catchment scale (1 mm yr−1 on
average) but a noticeable impact on in-stream nitrogen fluxes (around 12%), which is of interest when considering nitrate stream contamination
issues and the objectives of TNT2 modeling. This study demonstrates the
potential contribution of the forthcoming high spatial and temporal
resolution products from the Sentinel-2 satellite mission for improving
agro-hydrological modeling by constraining the spatial representation of
crop productivity. |
|
|
Teil von |
|
|
|
|
|
|