Mitigating the effects of severe fires, floods and heatwaves through the improvements of land dryness measures and forecasts. (#12)
Knowledge of landscape dryness is critical for the management and warning of fires, floods, heatwaves and landslips. This project will address fundamental limitations in our ability to prepare for these events. Currently landscape dryness is estimated using simplified soil moisture accounting systems developed in the 1960’s. Similarly, flood prediction, runoff potential and water catchment/dam management also are not using the best available science and technology.
This research will examine the use of detailed land surface models, satellite measurements and ground based observations for the monitoring and prediction of landscape dryness. The new information will be calibrated for use within existing fire and flood forecasting systems.
An inter-comparison will be performed of the traditional Keetch-Byram Drought Index and Soil Dryness Index with weather prediction models, satellite measurements, ground based measurements, and rainfall-runoff models. Soil moisture from weather prediction and reanalysis will be calibrated for the calculation of a high resolution historical dataset of KBDI and SDI. These datasets will be a valuable resource for researchers working on fire climatologies across Australia. The outputs of this project will improve Australia’s ability to manage multiple hazard types and create a more resilient community, by developing a state of the art, world’s best practice in soil moisture analysis that underpins flood, fire and heatwave forecasting.
Longer term work will explore the use of multi-model predictions and data assimilation to forecast soil dryness indices for operational application to fire, flood and heat wave hazards. The vegetation and soil parameterisations in current land surface models will be developed to match Australian conditions.
This research will examine the use of detailed land surface models, satellite measurements and ground based observations for the monitoring and prediction of landscape dryness. The new information will be calibrated for use within existing fire and flood forecasting systems.
An inter-comparison will be performed of the traditional Keetch-Byram Drought Index and Soil Dryness Index with weather prediction models, satellite measurements, ground based measurements, and rainfall-runoff models. Soil moisture from weather prediction and reanalysis will be calibrated for the calculation of a high resolution historical dataset of KBDI and SDI. These datasets will be a valuable resource for researchers working on fire climatologies across Australia. The outputs of this project will improve Australia’s ability to manage multiple hazard types and create a more resilient community, by developing a state of the art, world’s best practice in soil moisture analysis that underpins flood, fire and heatwave forecasting.
Longer term work will explore the use of multi-model predictions and data assimilation to forecast soil dryness indices for operational application to fire, flood and heat wave hazards. The vegetation and soil parameterisations in current land surface models will be developed to match Australian conditions.