@article {bnh-6057, title = {Quantitative assessment of flood discharges and floodway failures through cross-cultivation of advancement in knowledge and traditional practices}, journal = {International journal of disaster resilience in the built environment}, volume = {9}, year = {2018}, month = {11/2018}, pages = { 435-456}, abstract = {

Purpose

The 2011 and 2013 Queensland, Australia flood events caused massive infrastructure damage for low-level stream crossings such as floodways and culverts in regional Queensland. Failures of newly built floodways during the 2013 Queensland flood event in the Lockyer Valley Regional Council area raised significant concerns with respect to floodway design practices adopted in Australia and attracted significant research interest to enhance the resilience of floodways. Review of existing floodway design guidelines indicates that floodway design process is closely related to hydraulic and hydrological aspects. However, conducting a hydrological analysis is a challenging in rural areas, mainly owing to information scarcity. Floodways in rural areas often require a simple and economical solution contrast to more detailed hydrological analysis approaches adopted in urbanised areas. This paper aims to identify and apply the rational method to estimate maximum flood discharges at selected floodway locations in the Lockyer Valley Regional Council area. The paper further attempts to provide the first insight of flood characteristics during the 2011 and 2013 Queensland flood events at three catchment outputs across the selected case study area. It also highlights modern day challenges for practising engineers and researchers when estimating flood characteristics in rural areas. The paper shows that cross-cultivation of advancement in engineering practices and traditional approaches can promote quantitative approaches when assessing floodway damage in regional areas.

Design/Methodology/Approach

The research identifies limitations when assessing flood impact in rural regions in collaboration with experience from industry partners and authors themselves. The authors developed a framework to overcome those limitations arising from information scarcity to minimise the trial and error design approaches utilised in the current design practices for floodways.

Findings

This paper developed a simple and effective hydrological method with minimum inputs. It also provides an example on collating available but scattered resources and traditional method to quantitatively assess flood discharges of a rural catchment in Australia. Flood discharges at three catchment outlets along the Left-Hand Branch Road in the Lockyer Valley Region during both 2011 and 2013 Queensland flood events are estimated for the first time. The findings highlight the impact of flood discharges and flooded period on floodway failures.

Research implications/limitations

The current research is based on a selected case study area in Australia. However, similar challenges are expected all across the world, due to the scarcity of rainfall and flood measurement gauges.

Practical implications

Floodway designers can apply similar framework to estimate the flood discharges instead of current practice of trial and error process. This will provide more scientific and reliable estimation and assessment process.

Social implications

One of the social impacts identified in the broader research is the community outrages and disagreement between floodway design engineers and the community. Following the developed framework in the manuscript, design engineers will be able to justify their assumptions and design work.

Originality/value

The paper presents a novel framework on collating different and scattered information towards estimating flood discharges in rural areas. The manuscript presents the first insights on estimated flood discharges in the selected case study area during the 2011 and 2013 Queensland flood events. This will enable further research to be performed in a quantitative manner rather than the present approach of qualitative manner.

}, keywords = {Damaged assets, Flood discharge, Flooding, rainfall}, doi = {https://doi.org/10.1108/IJDRBE-09-2017-0051}, url = {https://www.emerald.com/insight/content/doi/10.1108/IJDRBE-09-2017-0051/full/html}, author = {Buddhi Wahalathantri and Weena Lokuge and Karu Karunasena and Sujeeva Setunge} } @mastersthesis {bnh-4629, title = {Estimating areal rainfall time series using input data reduction, model inversion, and data assimilation}, year = {2017}, month = {11/2017}, pages = {146}, school = {Monash University}, address = {Melbourne}, abstract = {

Floods are devastating natural hazards that can have severe socio-economic impacts and lead to a loss of life. Consequently, the key driver for this research is to provide techniques that will lead to an increase in flood forecast skill. As fluvial floods are a direct result of rainfall, detailed knowledge of uncertainties in rainfall observations provides a fundamental foundation for improving both rainfall and flood forecast skill. As the understanding of uncertainties present in rainfall time series is developed, so too will the confidence in rainfall forecasts, and short- and long-term streamflow forecasts. For a description of rainfall uncertainty to be complete it must take into account uncertainty when rainfall was not observed, thus allowing, model structural errors to be correctly identified, analyzed, and treated. Therefore the focus of this thesis is to develop a robust methodology to estimate rainfall time series and its uncertainty such that it is consistent with both streamflow and soil moisture observations. To effectively estimate rainfall time series, a method to reduce hydrological input data dimensionality was identified. The effective reduction of hydrological input data dimensionality allows modern parameter estimation algorithms to simultaneously estimate rainfall time series and model parameters. Due to their wide-spread use as model input data reduction techniques in other fields, the discrete cosine transform (DCT) and discrete wavelet transform (DWT) were used, for comparative purposes, to reduce the dimensionality of observed rainfall time series for the 438 catchments in the Model Parameter Estimation Experiment (MOPEX) data set. Once the time series were reduced to a small number of parameters, the rainfall time series were reconstructed for comparison with the observed hyetographs. The rainfall time signals are then reconstructed and compared to the observed hyetographs using standard simulation performance summary metrics and descriptive statistics. Analysis of the results demonstrate that, when compared to the DCT, the DWT is superior at preserving both short- and long-term rainfall patterns. Second, the DWT was used to reduce the dimensionality of the input rainfall time x series for the catchment of Warwick, Queensland, Australia. The DREAM(ZS) sampling algorithm, in conjunction with a likelihood function that considers both rainfall and streamflow, was then used to estimate the input rainfall time series. Model parameters and rainfall time series were simultaneously estimated. The inclusion of rainfall in the estimation process improved the root mean square error (RMSE) of streamflow simulations by a factor of up to 1.78. This was achieved while estimating an entire rainfall time series, inclusive of days when none was observed. Last, rainfall time series for the catchment of Warwick were estimated using three different rainfall-runoff models. Using the rainfall time series and model parameter estimates, remotely sensed soil moisture observations from the Soil Moisture Ocean Salinity (SMOS) and Advanced Microwave Scanning Radiometer - Earth observing system (AMSR-E) satellites were assimilated into each of the models using an ensemble Kalman filter (EnKF). Through analysis of the innovations from the observed and simulated soil moisture it was found that the combination of model choice and remotely sensed soil moisture product had a significant impact on the quality of rainfall estimated. When compared to streamflow simulations obtained via the sole estimation of model parameters, all models that jointly estimated rainfall time series and model parameters produced superior streamflow estimates. Rainfall estimates obtained using the Sacramento Soil Moisture Accounting (SAC-SMA) model were the most realistic. When the SMOS remotely sensed soil moisture product was assimilated into the SAC-SMA, innovations that indicated errors are of a Gaussian nature were obtained. Further, streamflow simulations obtained from the SAC-SMA had the best RMSE. The research presented in this thesis developed a methodology that can be used to estimate and evaluate rainfall estimates obtained using model input data reduction, model inversion, and data assimilation techniques. These rainfall estimates can be used to condition rainfall forecasts and consequently improve flood forecast skill.

}, keywords = {Emergency management, Flood, hydrology, modelling., rainfall}, url = {http://users.monash.edu.au/~jpwalker/theses/AshleyWright.pdf}, author = {Ashley Wright} } @article {bnh-4626, title = {Estimating rainfall time series and model parameter distributions using model data reduction and inversion techniques}, journal = {AGU}, year = {2017}, month = {07/2017}, abstract = {

Floods are devastating natural hazards. To provide accurate, precise, and timely flood forecasts, there is a need to understand the uncertainties associated within an entire rainfall time series, even when rainfall was not observed. The estimation of an entire rainfall time series and model parameter distributions from streamflow observations in complex dynamic catchments adds skill to current areal rainfall estimation methods, allows for the uncertainty of entire rainfall input time series to be considered when estimating model parameters, and provides the ability to improve rainfall estimates from poorly gauged catchments. Current methods to estimate entire rainfall time series from streamflow records are unable to adequately invert complex nonlinear hydrologic systems. This study aims to explore the use of wavelets in the estimation of rainfall time series from streamflow records. Using the Discrete Wavelet Transform (DWT) to reduce rainfall dimensionality for the catchment of Warwick, Queensland, Australia, it is shown that model parameter distributions and an entire rainfall time series can be estimated. Including rainfall in the estimation process improves streamflow simulations by a factor of up to 1.78. This is achieved while estimating an entire rainfall time series, inclusive of days when none was observed. It is shown that the choice of wavelet can have a considerable impact on the robustness of the inversion. Combining the use of a likelihood function that considers rainfall and streamflow errors with the use of the DWT as a model data reduction technique allows the joint inference of hydrologic model parameters along with rainfall.

}, keywords = {catchments, communities., Emergency management, Flood, rainfall, streamflow}, url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1002/2017WR020442}, author = {Ashley Wright and Jeffrey Walker and Valentijn Pauwels} } @article {BF-4272, title = {Environmental assessment of erosion following prescribed burning in the Mount Lofty Ranges, Australia}, journal = {International Journal of Wildland Fire}, year = {2013}, month = {10/2013}, abstract = {Erosion following fire has the potential to affect water quality, alter soil profiles and detrimentally affect human infrastructure. There is a clear need for environmental assessments to have regard for erosion concerns from prescribed burning. This study focussed on 10 prescribed burns conducted in the Southern Mount Lofty Ranges. Generalised additive modelling was used to determine the main significant environmental variables influencing the presence of sediment movement at 505 field-assessed sites. Sediment movement after the 10 prescribed burns was minor. Fire severity was a highly significant environmental determinant for the presence of sediment movement after prescribed burning. To predict erosion concerns, a suite of environmental variables is more reliable than focusing solely on slope steepness, as occurred before this study. These results indicate that erosion assessments need to consider a range of environmental variables to assess potential erosion and that land managers and scientists need to incorporate spatial sampling designs into erosion assessments.}, keywords = {bioturbation, erosion assessment, fire severity, rainfall, sediment movement, slope, topography}, doi = {http://dx.doi.org/10.1071/WF13011}, url = {http://www.publish.csiro.au/paper/WF13011.htm}, author = {Morris, Rowena and Ross Bradstock and Deirdre Dragovich and Henderson, M. K. and Trent Penman and Bertram Ostendorf} }