Soil moisture prototype improves fire risk forecasts
KBDI and the rescaled JASMIN soil dryness for the State Mine fire in NSW, Oct 2013.
New research that has developed a prototype, high-resolution soil-moisture analysis system called JASMIN, which is a significant improvement in accuracy compared to currently used models. It is based on research that examines the use of land surface models, remotely sensed satellite measurements and data assimilation techniques to improve the monitoring and prediction of soil dryness. The new information will be calibrated for use within the existing fire prediction systems. This retains the accuracy, temporal and spatial resolution of the new product without changing the overall climatology of Forest Fire Danger Index and other calculations based on soil moisture.
Immediate benefits for emergency and land management agencies will be improvements to the fire danger rating and warning system, fire behaviour and flood prediction models, which will flow on to emergency warnings issued to the public.
Vinodkumar, Dharssi I, Bally J, Steinle P, McJannet D, and Walker J (2017), Comparison of soil wetness from multiple models over Australia with observations, Water Resources Research 53, pp. 633-646, doi:10.1002/2015WR017738.
Vinodkumar and Dharssi I (2017), Evaluation of daily soil moisture deficit used in Australian forest fire danger rating system, Bushfire and Natural Hazards CRC.
Originally posted in Hazard Note, 14 Jun 2017 (link)
(Visited 71 times, 1 visits today)