Modelling Soil Moisture Deficit and Moisture Content of Ground Vegetation: Progress Towards Development of a Fire Weather Index System Appropriate to the UK

摘要

Most of the wildfires in upland Britain occur in Spring, with the highest peak in April. However, the highest values of the Met Office Fire Severity Index (MOFSI, based on the Canadian Forest Fire Weather Index System) occur in the height of summer, thus successfully predicting extreme fire weather conditions, but failing to predict when the majority of real fires occur. Here we illustrate this discrepancy with data from the English Peak District, and present an alternative model which calculates a proposed shrub fire index (SFI) and compares it with randomly generated numbers to simulate fire occurrence. The major peaks in the SFI dynamics occur in spring, reflecting the effect of drought stress on shrubs caused by damaged leaf cuticles during winter and the lack of resources to alleviate the damage during the pre-green-up period. The model presented here shows a reasonable performance in reproducing the seasonal distribution of wild fire occurrence, and may therefore prove helpful for future development of a fire prediction system designed specifically for British conditions. An effective wildfire prediction system will have great value for increasing the preparedness of land managers, National Park Authority staff and the Fire and Rescue Services. A weather index that accurately predicts the fuel moisture content of the dominant shrubs will also be valuable to land managers who use prescribed fire for vegetation management.