@article {bnh-6237, title = {Disaggregation of JASMIN soil moisture product to 1KM resolution}, number = {521}, year = {2019}, month = {12/2019}, institution = {Bushfire and Natural Hazards CRC}, address = {Melbourne}, abstract = {

Fire intensity, spread rate, and ignition are very sensitive to fuel dryness which in turn is strongly linked to soil moisture deficit. Though the value of soil moisture deficit in predicting fire danger has been long established, very few fire danger rating systems employ a comprehensive methodology to estimate it. Most such fire danger rating systems use very simple empirical water balance models which are found to have errors. The Bureau of Meteorology has recently developed a prototype, highresolution, land surface modelling based, state-of-the-art soil moisture analysis for Australia. The product, called Joint United Kingdom Land Environment Simulator (JULES) based Australian Soil Moisture Information (JASMIN), has a spatial resolution of 5 km at hourly timesteps. However, applications like fire danger mapping may require soil moisture information at higher spatial resolution due to the large spatial variability of soil moisture in the landscape. We focus on some of the research carried out to downscale the JASMIN product from 5 km to 1 km spatial resolution. We discuss the application of three downscaling algorithms: two regression-based methods and one with a theoretical basis. The three methods applied are based on the well-known surface temperature {\textendash} vegetation index space. We present an overview of the application of each method, along with an evaluation and comparison against each other and against ground-based soil moisture observations. Results from comparison with ground-based soil moisture measurements indicate that there is no significant degradation of the bias in the three methods, when going into higher spatial resolutions. However, the regression methods, in general, fail to capture the observed temporal variability. The theoretical based method, on the other hand, provides a temporal correlation of 0.81 and captures the skill of the parent JASMIN product.

}, keywords = {dryness, Emergency management, JASMIN, resolution, Soil moisture}, issn = {521}, author = {Vinod Kumar and Imtiaz Dharssi and Paul Fox-Hughes} } @article {bnh-5684, title = {Use of remote sensing measurements and data assimilation techniques to improve estimates of landscape dryness}, number = {482}, year = {2019}, month = {07/2019}, institution = {Bushfire and Natural Hazards CRC}, address = {Melbourne}, abstract = {

Fire intensity, spread rate and ignition are very sensitive to the fuel dryness which in turn is strongly linked to soil moisture deficit. Though the value of soil moisture deficit in predicting fire danger has been long established, very few fire danger rating systems employ a comprehensive methodology to estimate it. Most fire danger rating systems use very simple empirical water balance models which are found to have errors. Hence they are poor drivers of the sophisticated fire models used operationally to manage and warn for dangerous fire conditions and spread. With advances in the science of measurement, in the form of satellite remote sensing, and in prediction, in the form of physically based land surface models, soil moisture can now be better analysed and predicted. Neither observations nor models give a complete picture of the soil moisture state in isolation, however. Data assimilation combines observational and model information optimally, yielding increasingly consistent and complete estimates of soil moisture. In this paper, we touch on the various operational satellite observations available. We also discuss land surface
data assimilation methods used widely in soil moisture research and operations. This report is prepared for those with very limited technical and scientific background in satellite remote sensing or data assimilation. Hence complex mathematical and physical formulations are carefully omitted. However, the problems discussed here are highly non-trivial and inter-desciplinary, with much progress made in recent decades. Hence some technicalities are unavoidable. Also, the discussion is not intended to be complete. Our intention is to highlight, especially to the emergency management community, soil moisture estimation methods that may not be well known outside the scientific community.

}, keywords = {dryness, fire rate, fire spread, Landscape ecology, Soil moisture deficit}, issn = {482}, author = {Vinod Kumar and Imtiaz Dharssi} }