This paper presents a method to analyze and improve the set of equations constituting a rainfall-runoff model structure based on a combination of a data assimilation algorithm and polynomial updates to the state equations. The method, which we have called “Data Assimilation Informed model Structure Improvement” (DAISI) is generic, modular, and demonstrated with an application to the GR2M model and 201 catchments in South-East Australia. Our results show that the updated model generated with DAISI generally performed better for all metrics considered included KGE, NSE on log transform flow and flow duration curve bias. In addition, the modelled elasticity of runoff to rainfall is higher in the updated model, which suggests that the structural changes could have a significant impact on climate change simulations. Finally, the DAISI diagnostic identified a reduced number of update configurations in the GR2M structure with distinct regional patterns in three sub-regions of the modelling domain (Western Victoria, central region, and Northern New South Wales). These configurations correspond to specific polynomials of the state variables that could be used to improve equations in a revised model. Several potential improvements of DAISI are proposed including the use of additional observed variables such as actual evapotranspiration to better constrain the model internal fluxes.

A reliable understanding of linkages between meteorological, hydrological and agricultural droughts (MD, HD and AD respectively) is crucial to building resilience and planning for future climate changes. Despite Australia being prone to severe droughts, lagtimes of propagation (and recovery) from meteorological to hydrological and agricultural droughts across its large hydroclimatic regions are not well understood. Therefore, we investigate the characteristics of drought propagation and recovery time lags for droughts of four timescales and a combination of drought onset and cessation criteria in 407 unregulated catchments within six major precipitation zones across Australia. We find that the propagation and recovery lags are dependent on climatic conditions, drought criteria and timescales. The average propagation times from MD to HD across Australia varied from 0.8 to 1.7 months for monthly timescales, increasing to 2 to 4.5 months for 12-monthly timescales. The corresponding recovery lagtimes were 1.3 to 3.7 and 1.7 to 7.5 months respectively. Similarly, the average propagation times from MD to AD ranged from 0.9 to 1.9 months for monthly timescales, increasing to 0.8 to 5 months for 12-monthly timescales. The corresponding recovery lagtimes were 0.7 to 2.8 and 0.3 to 9.4 months respectively. For droughts of smaller timescales, propagation and recovery lags are linearly correlated with recovery lagtimes consistently greater than the propagation times. As the timescale increases, these relationships weaken suggesting effects of other catchment attributes (e.g. groundwater contributions) on lag relationships. Notably, recovery lagtimes are generally longer for the high-yielding catchments in eastern Australia compared to the other regions

Bushfires are common in Australia and can cause vegetation loss and affect hydrological processes such as interception, evapotranspiration, soil water storage and streamflow. This study investigates bushfire impacts on catchment mean annual streamflow for 14 Australian catchments that have been severely impacted by the 2009 Victoria bushfire, the second worst bushfire disaster in Australia. A statistical approach based on sensitivity coefficients was used for quantifying the climate variability impacts on streamflow and the time-trend analysis method was used to estimate the annual streamflow changes due to bushfire respectively. Our results show that bushfire has caused a noticeable increase in mean annual streamflow in majority of burnt catchments for an immediate post bushfire period (2009-2015), when the bushfire impact on streamflow is evidently larger than the climate change impact. Furthermore, the bushfire impact on mean annual streamflow linearly increases with the burnt percentage area. These results provide strong evidence for evaluating large-scale bushfire impact on streamflow at small to medium sized catchments, and guidance for process-based hydrological models for simulating bushfire impacts on hydrological processes for the immediate period after bushfire.