Takeaways from Soil Moisture & Wildfire Prediction Workshop

1. More fire all of the time

          • Incidence of wildfire is increasing across the US

          • Especially noticeable increase in large fires, however there is the possibility that there are more complexes (e.g., multiple fires that become one) instead

             of individual fires which makes the ‘individual’ fire size larger

          • Fire ignition is difficult to predict, but fire potential may be more realistically predicted


2. Soil moisture is useful to fire danger and prediction

          • As soil moisture datasets become more available, there is a shift toward using more quantitative measures of soil moisture instead of previously used

             indices of soil moisture and drought.

          • Recent research has indicated that soil moisture is a valuable dataset for the fire modeling community.


3. Some outstanding questions about soil moisture and wildfire relationships

          • What role can soil moisture play in fire potential assessments?

          • Can soil moisture be integrated into existing prediction systems to gain benefit of soil moisture mapping?

          • What are the benefits of using in situ or remotely sensed soil moisture data, and can they be complimentary?

          • How can the soil moisture memory help different systems and us?

          • Can we glean a useful relationship between soil moisture and fuel moisture and loads (live and dead), and do this to help decision-makers?


4. Who are the stakeholders for this work?

          • The public

          • National, regional, and local decision makers need fire danger/potential information

          • Decision makers are generally not really seeking soil moisture information (perhaps because it has historically been unavailable)

          • The fire community is very diverse


5. Time intervals and spatial resolution:

          • Found that there was a very wide range of information used to make management decisions and predictions depending upon application and audience.

          • There is a need to engage target audiences to help narrow focus.


6. There is still a need to conduct empirical research.

          • Both statistical and physical models are important

          • Significant value to comparing/exploring data and protocols for areas outside the US