Streamflow Simulations by the Land Surface Model ORCHIDEE Over the Mississippi River Basin: Impact of Resolution and Data Source on the Model
Abstract
The aim of this study is to validate the ability of the Land Surface Model ORCHIDEE (Organizing Carbon and Hydrology In Dynamic EcosystEms) to simulate streamflows when it is forced by atmospheric conditions at different resolutions (spatially and temporally). The forcing data used are NCC (Ngo-Duc & al., 2005) and NLDAS (Cosgrove & al., 2003) which differ in resolution. ORCHIDEE resolution is dependent on the forcing; here the model has a eighth degree grid when it is forced by NLDAS. The study focuses on the Mississippi river basin over the period 1997-1999 and an hydrological balance is performed for each of the five sub- basins. We compare streamflows simulated by the model to measurements available at seventeen stations. The results are sensitive to the data resolution: generally the magnitudes of the streamflows simulated by ORCHIDEE with the NCC forcing are overestimated whereas they are underestimated with NLDAS. However, the highest resolution has a smaller error. The streamflow seasonalities are correctly represented over many stations during the three years, with both forcing, specifically streamflow associated with large basin (correlation is about 0.85 at Vicksburg station but 0.5 at Sidney station). We also compare ORCHIDEE to four other models which have performed the same simulation with NLDAS (Lohman & al., 2004). For the five stations of the Mississippi river basin studied in this paper, we compare their measured streamflow variations to the simulated ones. We notice a large difference between the five models. ORCHIDEE and NOAH are the most similar and able to represent the peaks accurately.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2008
- Bibcode:
- 2008AGUFM.H43G1112G
- Keywords:
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- 1814 Energy budgets;
- 1839 Hydrologic scaling;
- 1843 Land/atmosphere interactions (1218;
- 1631;
- 3322);
- 1847 Modeling;
- 1855 Remote sensing (1640)