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| Titel |
Brugga basin’s TACD Model Adaptation to current GIS PCRaster 4.1 |
| VerfasserIn |
Nicolas Antonio Lopez Rozo, Gerald Augusto Corzo Perez, Germán Ricardo Santos Granados |
| Konferenz |
EGU General Assembly 2017
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| Medientyp |
Artikel
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| Sprache |
en
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 19 (2017) |
| Datensatznummer |
250153507
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| Publikation (Nr.) |
 EGU/EGU2017-18498.pdf |
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| Zusammenfassung |
| The process-oriented catchment model TACD (Tracer-Aided Catchment model – Distributed)
was developed in the Brugga Basin (Dark Forest, Germany) with a modular structure in the
Geographic Information System PCRaster Version 2, in order to dynamically model the
natural processes of a complex Basin, such as rainfall, air temperature, solar radiation,
evapotranspiration and flow routing among others. Further research and application on this
model has been done, such as adapting other meso-scaled basins and adding erosion
processes in the hydrological model.
However, TACD model is computationally intensive. This has made it not efficient on
large and well discretized river basins. Aswell, the current version is not compatible
with latest PCRaster Version 4.1, which offers new capabilities on 64-bit hardware
architecture, hydraulic calculation improvements, in maps creation, some error and bug
fixes.
The current work studied and adapted TACD model into the latest GIS PCRaster Version
4.1. This was done by editing the original scripts, replacing deprecated functionalities without
losing correctness of the TACD model. The correctness of the adapted TACD model was
verified by using the original study case of the Brugga Basin and comparing the adapted
model results with the original model results by Stefan Roser in 2001. Small differences were
found due to the fact that some hydraulic and hydrological routines were optimized since
version 2 of GIS PCRaster. Therefore, the hydraulic and hydrological processes are well
represented.
With this new working model, further research and development on current topics like
uncertainty analysis, GCM downscaling techniques and spatio-temporal modelling are
encouraged. |
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