Development of a decision support system for flood forecasting and warning – a case study on the Maribyrnong River

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.