Journal cover Journal topic
Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
Hydrol. Earth Syst. Sci., 14, 1801-1817, 2010
http://www.hydrol-earth-syst-sci.net/14/1801/2010/
doi:10.5194/hess-14-1801-2010
© Author(s) 2010. This work is distributed
under the Creative Commons Attribution 3.0 License.
 
11 Oct 2010
Climatology-based regional modelling of potential vegetation and average annual long-term runoff for Mesoamerica
P. Imbach1, L. Molina1, B. Locatelli2, O. Roupsard1,3, P. Ciais4, L. Corrales5, and G. Mahé6 1CATIE 7170, Turrialba, Cartago 30501, Costa Rica
2CIRAD UPR Forest Ecosystem Services, Montpellier, France, CIFOR ENV Program, Bogor, Indonesia
3CIRAD, UPR80, Fonctionnement et Pilotage des Ecosystémes de Plantations, Montpellier, France
4IPSL – LSCE, CEA CNRS UVSQ, Centre d'Etudes Orme des Merisiers, 91191 Gif sur Yvette, France
5The Nature Conservancy, P.O. Box, 230–1225, San José, Costa Rica
6IRD/HydroSciences Montpellier, Case MSE, Université Montpellier 2, 34095 Montpellier, Cedex 5, France
Abstract. Mean annual cycles of runoff, evapotranspiration, leaf area index (LAI) and potential vegetation were modelled for Mesoamerica using the SVAT model MAPSS with different climatology datasets. We calibrated and validated the model after building a comprehensive database of regional runoff, climate, soils and LAI. The performance of several gridded precipitation climatology datasets (CRU, FCLIM, WorldClim, TRMM, WindPPT and TCMF) was evaluated and FCLIM produced the most realistic runoff. Annual runoff was successfully predicted (R2=0.84) for a set of 138 catchments, with a low runoff bias (12%) that might originate from an underestimation of the precipitation over cloud forests. The residuals were larger in small catchments but remained homogeneous across elevation, precipitation, and land-use gradients. Assuming a uniform distribution of parameters around literature values, and using a Monte Carlo-type approach, we estimated an average model uncertainty of 42% of the annual runoff. The MAPSS model was most sensitive to the parameterization of stomatal conductance. Monthly runoff seasonality was mimicked "fairly" in 78% of the catchments. Predicted LAI was consistent with MODIS collection 5 and GLOBCARBON remotely sensed global products. The simulated evapotranspiration:runoff ratio increased exponentially for low precipitation areas, highlighting the importance of accurately modelling evapotranspiration below 1500 mm of annual rainfall with the help of SVAT models such as MAPSS. We propose the first high-resolution (1 km2 pixel) maps combining average long-term runoff, evapotranspiration, leaf area index and potential vegetation types for Mesoamerica.

Citation: Imbach, P., Molina, L., Locatelli, B., Roupsard, O., Ciais, P., Corrales, L., and Mahé, G.: Climatology-based regional modelling of potential vegetation and average annual long-term runoff for Mesoamerica, Hydrol. Earth Syst. Sci., 14, 1801-1817, doi:10.5194/hess-14-1801-2010, 2010.
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