Academic literature on the topic 'Flood forecasting Victoria'

Abstract. Lakes are of fundamental importance in the Earth system as they support essential environmental and economic services, such as freshwater supply. Streamflow variability and temporal evolution are impacted by the presence of lakes in the river network; therefore, any change in the lake state can induce a modification of the regional hydrological regime. Despite the importance of the impact of lakes on hydrological fluxes and the water balance, a representation of the mass budget is generally not included in climate models and global-scale hydrological modeling platforms. The goal of this study is to introduce a new lake mass module, MLake (Mass-Lake model), into the river-routing model CTRIP to resolve the specific mass balance of open-water bodies. Based on the inherent CTRIP parameters, the development of the non-calibrated MLake model was introduced to examine the influence of such hydrological buffer areas on global-scale river-routing performance. In the current study, an offline evaluation was performed for four river networks using a set of state-of-the-art quality atmospheric forcings and a combination of in situ and satellite measurements for river discharge and lake level observations. The results reveal a general improvement in CTRIP-simulated discharge and its variability, while also generating realistic lake level variations. MLake produces more realistic streamflows both in terms of daily and seasonal correlation. Excluding the specific case of Lake Victoria having low performances, the mean skill score of Kling–Gupta efficiency (KGE) is 0.41 while the normalized information contribution (NIC) shows a mean improvement of 0.56 (ranging from 0.15 to 0.94). Streamflow results are spatially scale-dependent, with better scores associated with larger lakes and increased sensitivity to the width of the lake outlet. Regarding lake level variations, results indicate a good agreement between observations and simulations with a mean correlation of 0.56 (ranging from 0.07 to 0.92) which is linked to the capability of the model to retrieve seasonal variations. Discrepancies in the results are mainly explained by the anthropization of the selected lakes, which introduces high-frequency variations in both streamflows and lake levels that degraded the scores. Anthropization effects are prevalent in most of the lakes studied, but they are predominant for Lake Victoria and are the main cause for relatively low statistical scores for the Nile River However, results on the Angara and the Neva rivers also depend on the inherent gap of ISBA-CTRIP process representation, which relies on further development such as the partitioned energy budget between the snow and the canopy over a boreal zone. The study is a first step towards a global coupled land system that will help to qualitatively assess the evolution of future global water resources, leading to improvements in flood risk and drought forecasting.

An extensive search has been carried out to find all major flood and very heavy rainfall events in Victoria since 1876 when Southern Oscillation (SOI) data became available. The synoptic weather patterns were analysed and of the 319 events studied,121 events were found to be East Coast Lows (ECLs) and 82 were other types of low-pressure systems. Tropical influences also played a large role with 105 events being associated with tropical air advecting down to Victoria into weather systems. Examples are presented of all the major synoptic patterns identified. The SOI was found to be an important climate driver with positive SOIs being associated with many events over the 144 years studied. The 1976 Climate Shift and its influence on significant Victorian rainfall events is studied and negative SOI monthly values were shown to dominate following the Shift.However,one of the most active periods in 144 years of Victorian heavy rain occurred after the shift with a sustained period of positive SOI events from 2007 to 2014. Therefore, it is critical for forecasting future Victorian heavy rainfall is to understand if sequences of these positive SOI events continue like those preceding the Shift. Possible relationships between the Shift and Global Temperature rises are also explored. Upper wind data available from some of the heaviest rainfall events showed the presence of anticyclonic turning of the winds between 850hPa and 500hPa levels which has been found to be linked with extreme rainfall around the Globe.

Thesis (M.Eng. (Hons.)) -- University of Western Sydney, 2008.
A thesis submitted towards the degree of Master of Engineering (Honours) in the University of Western Sydney, College of Health and Science, School of Engineering. Includes bibliographical references.

Design flood estimation in small to medium sized ungauged catchments is frequently required in hydrologic analysis and design and is of notable economic significance. For this task Australian Rainfall and Runoff (ARR) 1987, the National Guideline for Design Flow Estimation, recommends the Probabilistic Rational Method (PRM) for general use in South- East Australia. However, there have been recent developments that indicated significant potential to provide more meaningful and accurate design flood estimation in small to medium sized ungauged catchments. These include the L moments based index flood method and a range of quantile regression techniques. This thesis focuses on the quantile regression techniques and compares two methods: ordinary least squares (OLS) and generalised least squares (GLS) based regression techniques. It also makes comparison with the currently recommended Probabilistic Rational Method. The OLS model is used by hydrologists to estimate the parameters of regional hydrological models. However, more recent studies have indicated that the parameter estimates are usually unstable and that the OLS procedure often violates the assumption of homoskedasticity. The GLS based regression procedure accounts for the varying sampling error, correlation between concurrent flows, correlations between the residuals and the fitted quantiles and model error in the regional model, thus one would expect more accurate flood quantile estimation by this method. This thesis uses data from 133 catchments in the state of Victoria to develop prediction equations involving readily obtainable catchment characteristics data. The GLS regression procedure is explored further by carrying out a 4-stage generalised least squares analysis where the development of the prediction equations is based on relating hydrological statistics such as mean flows, standard deviations, skewness and flow quantiles to catchment characteristics. This study also presents the validation of the two techniques by carrying out a split-sample validation on a set of independent test catchments. The PRM is also tested by deriving an updated PRM technique with the new data set and carrying out a split sample validation on the test catchments. The results show that GLS based regression provides more accurate design flood estimates than the OLS regression procedure and the PRM. Based on the average variance of prediction, standard error of estimate, traditional statistics and new statistics, rankings and the median relative error values, the GLS method provided more accurate flood frequency estimates especially for the smaller catchments in the range of 1-300 km2. The predictive ability of the GLS model is also evident in the regression coefficient values when comparing with the OLS method. However, the performance of the PRM method, particularly for the larger catchments appears to be satisfactory as well.
Master of Engineering (Honours)

Floods are one of the most costly types of natural disasters in Australia and other parts of the world. It was reported that the average annual cost of flood damage in Australia was about $300 million as at 1994. However, the effects of flooding can be mitigated, and thereby reduce the loss of life and damage to property. Flood mitigation measures can be categorised into two groups. The first group, the structural measures, involves civil works in the flood plain and/or catchment. The second group, the non-structural measures, includes flood forecasting, flood warning and emergency planning, planning controls and acquisition of flood prone land within the catchment, and providing flood insurance to affected people. The flood damage mitigation in the catchment or basin depends on complex social, economical and environmental conditions. It is not always feasible to completely control or manage flood damage through structural measures due to economic, technological, environmental and social constraints. Therefore, non-structural measures such as flood forecasting and warning often play an important role in minimizing flood damage, especially, when there are no feasible structural measures that can be implemented. While planning, design, construction and operation of most structural measures can be done using definite mechanisms, the decisions of non-structural measures, especially flood forecasting and warning, are complex and are not uniquely defined. Therefore, such decisions require the aid of mathematical model results, and require both quantitative and qualitative decision modelling steps. Thus, these decisions can be effectively obtained through the use of a Decision Support System. The Decision Support Systems (DSSs) have recently become popular in making decisions related to complex water resource problems. However, the design and the development of some of these applications do not contain all essential elements of a modern-day DSS, such as effective databases and file management facilities, user-friendly interfaces, appropriate simulation models, spatial and graphical data display and analysis modules, and facilities for effective decision making. Moreover, the theory of DSS and computer science has developed rapidly since the initial development of some of these applications. Furthermore, only a few applications of DSS in flood control and warning exists in the literature. These applications cited in the literature mostly deal with planning aspects of flood control, and not real-time flood forecasting and warning. Therefore, considering the above facts, it is timely and necessary to develop an effective DSS to facilitate decision making of flood warning using all recent advances in DSS theory and computer science, and combining all necessary and desirable elements of a DSS into one system. The Maribyrnong River basin is a medium size catchment located in the northwest of Melbourne in Victoria, Australia. Its low-lying flood plains along the lower sections of the river have been frequently being inundated by floods. A flood warning system has been established in 1975 after a major flood in 1974 to minimise flood damage in the lower part of the catchment. This system uses several numerical models such as the RORB model and the HEC-2 model for flood forecasting. However, there is no single computer-based system that integrates these models to facilitate analysis of different scenarios in controlling and managing the flood damage, and in making objective and effective decisions. Furthermore, the use of these separate models is time consuming and can lead to errors in transferring information from one model to another. Therefore, a computer-based DSS for flood forecasting and warning in the Maribyrnong River basin would enhance the effectiveness of flood warning in this catchment. As part of this research, the author has defined the DSS as an interactive computer-based system that helps decision-makers to use data and models to solve semi-structured problems effectively. This DSS should allow the user to participate in principal steps of the decision making process, to simulate many steps in the process of decision making, to investigate alternative scenarios, to seek the overall goal for decision, and to improve the effectiveness of decision making. The author also suggested a DSS in water resources, which in most cases deals with spatial data display and analysis, should include five essential components: a database subsystem, a modelbase subsystem, an interface subsystem, a decision support subsystem, and a spatial and graphic data display and analysis subsystem. Most previous research work on DSS development, especially in the area of water resources do not give details of the conceptual system design and details of the subsystems. This thesis provides the details of the conceptual system designs of all subsystems and their major functions. These approaches will help further system development of the DSS of this thesis. The general concept used in this thesis can be used for DSS studies in other water resource studies and in other fields. Based on well-designed system, a unique decision support system, DSSFCMR (Decision Support System for Flood Control in the Maribyrnong River basin) was developed in this thesis to help decision making in flood forecasting and warning from data entry to search of final decisions. The DSSFCMR consists of five subsystems, namely Database Management System (DBMS), Modelbase, Spatial and Graphic Data Display and Analysis (SGDDA), Decision Support, and Interface. The DSSFCMR can consider various forecast rainfall depths in three different forecast periods. The developed Database subsystem can perform various tasks for database management related to flood warning. The URBS hydrological and HEC-RAS hydraulic models in the Modelbase subsystem are used to calculate flood hygrographs and corresponding flood water levels along the flood prone area respectively. Based on the calculated water levels, the shapefile for flood inundated area is instantly created, which is then used for spatial analysis of the flood inundated area through the developed interactive map interface. Two separate methods were developed in the SGDDA subsystem to perform spatial data display and analysis of the flood inundated area for use by different users (with different computer skills) and/or for organizations with different levels of resources. The process of complicated data transfer within DSSFCMR (e.g. the peak discharge to the flood water level, then flood water level to the shapefile of flood area) is automated by the developed system functions. The technology developed for decision choice support in this study helps to locate the required scenarios from many scenario results using the database technology. All functions are properly integrated together for the benefit of the user to make the decisions effectively. The use of DSSFCMR to provide decision support for flood forecasting and warning in the Maribyrnong River basin was illustrated. The application was on the flood event that occurred on 04 October 1983, but under 1997 topographical conditions. Essentially, the application concentrated on flood forecasting and warning decisions at a particular time during the event. The system effectively performed calibration of the URBS and HEC-RAS models, forecasting of flood hydrographs, calculation of flood water levels, spatial data display of flood inundated areas and decision selection support for flood warning at this particular time. Generally, the developed system DSSFCMR can efficiently forecast flood hydrographs and calculate the flood water levels; the process of complex data transfer is done automatically and quickly; the data can be displayed flexibly in various formats; the system is easy to use by different users with different computer skills; the user can use DSSFCMR to investigate decision making variables related to flood warning (e.g. people relocation) conveniently and quickly. In summary, this system helps the decision maker to make the decisions in relation to flood forecasting and warning in the Maribyrnong River basin effectively.