A simple model for the live fuel moisture of chamise

Plant moisture content plays an important role in determining the availability of natural fuels for wildfires in Mediterranean ecosystems. While dead fuel moisture variation mainly depends exclusively on the weather conditions, live herbaceous moisture content is relatively more difficult to predict due to its seasonality in response to plants' physiological and phenological processes such as spring flushing and fall curing as well as soil water availability. Efforts have been made using some kind of indices that employ routinely measured meteorological parameters to model live plant moisture content, such as the Keetch-Byram drought index (Keetch and Byram 1968), the cumulative water balance index (Dennison and Roberts 2003), field-sampled soil moisture (Qi et al. 2012), among others.

We have developed a simple model to accurately predict the live fuel moisture (LFM) content of Adenostoma Fasciculatum (chamise) as measured at several southern California sites where large wildfires often occur when the fuels are dry and the Santa Ana winds are strong. The key variable is soil moisture from the 40-100 cm layer derived from the North American Land Data Assimilation System (NLDAS) reanalysis. Our model consists of a time function to represent the average annual cycle and soil moisture departures from its own annual variation to capture LFM departures from normal. With this approach, correlation coefficients for the most accurately modeled sites exceed 0.9, if an (elevation and soil type dependent) time lag on the order of 20-40 days is incorporated. Because we are employing a gridded reanalysis, our strategy facilitates the reconstruction of past events as well as data gap filling. The improved live fuel moisture model can work with other components of fuel moisture to help monitor vegetation conditions in southern California regions for fire danger assessment.

Caption for figure: Time series of observed LFM (black dots) and predicted values (red curve) for the Laurel Canyon site in northern Los Angeles county. Grey dots denote the time function that represents the LFM annual cycle for this location. The (one year) “extended” time period represents out-of-sample observations (white dots) and predictions (green curve).