Development of a prediction model of fuel moisture changes in a deciduous forest of yeongdong region in Korea

Si Young Lee, Chun Geun Kwon, Dongwook W. Ko, Gwan Soo Park, Shoji Ohga

Research output: Contribution to journalArticle

Abstract

Understanding how fuel moisture changes after a rainfall is important to predict forest fire risk, and knowing such change in advance can greatly assist in fire risk monitoring To better understand the fuel moisture dynamics sifter a rainfall, we investigated how fuel moisture level changes across four different fuel layers (fall leaves, humus, top soil layer (<5cm depth), and lower soil layer (5-10 cm depth)) under three different stand density levels (high, medium and low) after a significant rainfall event (>5 mm) during spring season We measured variables including effective humidity, solar irradiation, wind speed, and days after rainfall These variables were incorporated into developing a fuel moisture prediction regression model. Variables were measured daily for 6 days after a rainfall, for a total of 4 rainfall events in the spring of 2008 for model development, and one event in the spring of 2009 for model validation Results show that in a low density stand, fuel moisture of the fallen leaves layer reached a dangerously dry level of 17% only after 3 days since rainfall, while at the medium and high density stands, fuel moisture level remained at 19-20% after 6 days since rainfall Fuel moisture at the humus level was highest among all fuel layers, and remained at greater than 57% even after 6 days since rainfall Top and lower soil layers both showed small to no changes in fuel moisture content throughout the sampling period The prediction regression model showed a reasonable performance (R2=0.56-0.90, p-value <0.001) and validated well against an independent set of measurements.

Original languageEnglish
Pages (from-to)19-24
Number of pages6
JournalJournal of the Faculty of Agriculture, Kyushu University
Volume59
Issue number1
Publication statusPublished - Feb 1 2014

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All Science Journal Classification (ASJC) codes

  • Biotechnology
  • Agronomy and Crop Science

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