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United States Department of Agriculture

Agricultural Research Service

Research Project: SNOW AND HYDROLOGIC PROCESSES IN THE INTERMOUNTAIN WEST

Location: Northwest Watershed Management Research

Title: Long term inter-annual variability of vegetation production

Authors
item Finzel, Julie -
item Seyfried, Mark
item Weltz, Mark
item Launchbaugh, Karen -

Submitted to: Proceedings American AGU Chapman Conference on the GIS in the Vadose Zone
Publication Type: Abstract Only
Publication Acceptance Date: September 30, 2009
Publication Date: August 1, 2009
Citation: Finzel, J.A., Seyfried, M.S., Weltz, M.A., Launchbaugh, K. 2009. Long Term Inter-Annual Variability of Vegetation Production. Proceedings American AGU Chapman Conference on the GIS in the Vadose Zone.

Technical Abstract: It is well established that plant productivity in arid and semiarid regions is primarily limited by water availability and that inter-annual precipitation amounts are highly variable. It follows that plant productivity should also be highly variable in such environments. This variability is critical from at least two perspectives. First, optimal land management (e.g., livestock), is based on plant production. Second, carbon balance is directly related to plant production and therefore water availability. Direct measurement of either plant production or carbon dynamics is difficult and costly, so that it is unlikely that sufficient data will be collected to understand inter-annual variability. In an environment with little or no water loss to deep percolation or overland flow, soil water dynamics are indicative of plant water use and hence productivity. We use soil water data collected over 32 years to evaluate the accuracy of simulated soil water dynamics. Plant production is estimated from an index based on the assumption that production is a linear function of the ratio of actual to potential transpiration. We found reasonably good correspondence between measured and simulated water contents. Estimated production was highly variable and closely related to precipitation amount.

Last Modified: 8/30/2014
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