Publication Date
Spring 2026
Degree Type
Thesis
Degree Name
Master of Science (MS)
Department
Meteorology and Climate Science
Advisor
Craig Clements; Minghui Diao; Roger Ottmar
Abstract
Dead fuel moisture (DFM) is a critical parameter in wildland fire, influencing both fire behavior and fire effects. Of particular interest is the 100–hour DFM time lag class which exhibits both fire behavioral characteristics of smaller fuels (such as the 10–hour class) and fire effects characteristics of larger fuels (such as the 1000–hour class). Historically, DFM measurements were made manually with the United States Forest Service’s standard fuel stick. In the 1980s, Remote Automated Weather Stations (RAWS) allowed these manual measurements to be replaced with modeled values within the National Fire Danger Rating System (NFDRS). These values were supplemented by an automated DFM sensor in following years, but only for the 10–hour class. As no regular DFM measurements are taken in the 100–hour class, this study investigated the behavior of those fuels at high temporal resolution using a custom, automated, electronic sensor. Three sensors were deployed at SJSU RAWS sites for intercomparison with NFDRS modeled values after being calibrated to gravimetric lab data. Analysis indicated that: 100–hour fuels exhibit a diurnal variability on the order of two to three percent moisture content, likely related to the moisture response of the outer surface being different from the core; NFDRS does not capture that variability; and large differences exist between measured and modeled values during precipitation events, indicating a potential need for further refinement of the NFDRS precipitation model.
Recommended Citation
Perlaky, Nicolas S., "Development and Deployment of an Automated, Electronic 100-Hour Dead Woody Moisture Sensor with a Comparison Against NFDRs" (2026). Master's Theses. 5791.
DOI: https://doi.org/10.31979/etd.7bu8-z7kv
https://scholarworks.sjsu.edu/etd_theses/5791
