WATER RESOURCES RESEARCH GRANT PROPOSAL
Project ID: 2002WY7B
Title: Drought prediction model development and dissemination in Wyoming
Project Type: Research
Focus Categories: Agriculture, Drought, Management and Planning
Keywords: Agriculture, Bioindicators, Biomonitoring, Decision models, Range Management, Risk Analysis, Risk Management
Start Date: 03/01/2003
End Date: 02/29/2003
Federal Funds: $0.00
Matching Funds: $54207.00
Congressional District: 1
Principal Investigators: Smith, Michael A. (Univ. Wyoming); Thurow, Thomas L.; Rosenlund, Philip A.
Abstract: Drought is a recurring,
albeit unpredictable, climatic phenomena that is a prime source of annual
variation of rangeland productivity in Wyoming and most other semi-arid regions
of the world. Most drought indices focus on characterizing current conditions.
Such information are not as useful to managers as would be predictive tools.
Time series analyses of data from a site in southeast Wyoming (Saratoga)
that winter/spring climate can be used to predict annual forage production.
Development and refinement of this type of predictive tool for representative
locales within Wyoming would equip land managers with insights that would
enable them to develop proactive management strategies regarding stocking
levels, grazing season length, alternative forage sources, marketing or other
accommodations to compensate for forage production shortfalls or take advantage
of additional forage production. We propose to continue existing data collection
near Saratoga, initiate forage production-precipitation relationship studies
in other areas of Wyoming, and compile agency data sets that will allow the
development of a predictive tool for each major land resource area across
Wyoming. Cooperatively developed and maintained forage production sites will
be established with PI’s of this project, county-based UW cooperative
extension service (CES) personnel, and with personnel at federal land management
or other agencies that are able to participate. Data analysis will consist
of time series analysis and multi-variate regression of winter/spring precipitation,
temperature/elevation and soil variables relative to how they can be used
to predict non-irrigated herbage production.
Progress/Completion Report PDF