Abstract
A framework is described to compute and map forest evapotranspiration and net primary productivity over complex mountainous terrain. The methodology is based on the interface of geographic information processing and remote sensing with FOREST-BGC, a nonlinear deterministic model designed to simulate carbon, water and nitrogen cycles in a forest ecosystem. The model as input the geographic patterns of leaf area index (lai), available soil water capacity (swc) and microclimatic parameters over the landscape. These patterns are represented with the use of a template consisting of the set of hillslopes, stream channels and subwatersheds that completely define the landscape. A geo-referenced database containing digital elevation data, remotely sensed information and other environmental data are stratified by this template. We have found that the stratification of the surface data sets by a hillslope or watershed template produces landscape units with low internal variance of the important model parameters but high between unit variance. By producing templates at different levels of resolution, we have the ability to reorganize the model parameter set to different levels of surface generalization. The model is directly parameterized for each of these surface units which can then be simulated in parallel, providing the ability to expand the simulation to large regions.
Original language | English |
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Pages (from-to) | 171-196 |
Number of pages | 26 |
Journal | Ecological Modelling |
Volume | 56 |
Issue number | C |
DOIs | |
State | Published - 1991 |
Funding
This research was funded by NASA Grants NAGW-1234, and Grant 677-21-31-01.
Funders | Funder number |
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National Aeronautics and Space Administration | NAGW-1234, 677-21-31-01 |