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BNPP/ASB Functional Value of Biodiversity Project – Phase II |
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| Model |
DHSVM (Distributed Hydrology Soil Vegetation Model) |
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| Lead | University of Washington | |||||||||||||||||||||||||||||||||
| Collaborator | ICRAF-SEA | |||||||||||||||||||||||||||||||||
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Scope, dataframe, spatial resolution
(complete metadata: sources, definitions, dates, resolution, etc)
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| Climatology |
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| Machinery |
Distributed Hydrology Soil Vegetation Model (DHSVM, Wigmosta et al, 1994) Our original commitment was to also use VIC for the Mae Chem work. But we were concerned that the physics as so represented in VIC would not accurately represent the steep topography and finer-scale issues of the Mae Chaem basin. As noted, VIC is conceptualized as a larger, regional scale model. As such, its application to smaller-scale basins and sub-basins, such as the Mae Chaem, is questionable. So to examine problems at this scale, we decided to make the commitment to utilizing our high-resolution hydrologic model, the Distributed Hydrology Soil Vegetation Model (DHSVM, Wigmosta et al, 1994). Unlike VIC, DHSVM is intended for application to small to moderate (typically less than about 1000 km2) drainage areas, over which digital topographic data allows explicit representation of the mechanisms by which water travels over the surface and through the subsurface. Like VIC, it represents runoff generation via the saturation excess mechanism. Unlike VIC, it explicitly represents topographic effects, including the formation of perched water tables, on runoff generation, incident solar radiation (hence net radiation), and explicitly represents the vegetation and its properties (like root depth), as well as soil properties, on a pixel-by-pixel basis. The
model grid resolution typically is 30-150 m, several orders of magnitude
higher than VIC. However,
because of the large computational burden (and data limitations), DHSVM is
restricted to relatively small catchments.
We have conducted some limited experiments comparing DHSVM
sensitivity, for instance, to vegetation and vegetation change (Van Shaar et
al, 2002). Although the
macroscale performance of the two models is similar in gross features
(e.g., ability to reproduce seasonal fluctuations in runoff), there are
important differences in predicted runoff and other surface fluxes,
especially at shorter time scales. |
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| Functions modeled | total yield, high flows, low flows | |||||||||||||||||||||||||||||||||
| Land cover scenarios |
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| Process |
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| Reporting and analysis of model runs |
Reporting of direct hydrological flows
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| Milestones |
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| Date Expected | See status/target of activities above. | |||||||||||||||||||||||||||||||||
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Notes, comments. |
See Data availability and requirements | |||||||||||||||||||||||||||||||||
| References | DHSVM references. See: http://www.hydro.washington.edu/Lettenmaier/Models/DHSVM/publications.htm | |||||||||||||||||||||||||||||||||
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| Global Partnership
| Amazon
| Congo Basin
| Southeast Asia |
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Last updated: 03 March, 2004 ©2003 ASB. All rights reserved. |
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