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Hydroinformatics Applied to Hydraulic Experiments
Published in Marian (Editor-in-Chief) Muste, Dennis A. Lyn, David M. Admiraal, Robert Ettema, Vladimir Nikora, Marcelo H. Garcia, Experimental Hydraulics: Methods, Instrumentation, Data Processing and Management, 2017
Marian (Editor-in-Chief) Muste, Dennis A. Lyn, David M. Admiraal, Robert Ettema, Vladimir Nikora, Marcelo H. Garcia
Arising in the early 1990s as a consequence of the evolution of computers and information systems, hydroinformatics is a conceptual framework that facilitates informatics-based data management and investigations. Hydroinformatics ‘‘integrates knowledge and understanding of both water quantity and quality with the latest developments in information technology to improve technical and business decision making within the water industry. It embraces not only methods of data capture, storage, processing, analysis and graphical display, but also the use of advanced modeling, simulation, optimization and knowledge-based tools and systems infrastructure’’ (Abbott, 1991). Although initial hydroinformatics efforts have focused on numerical modeling of various components of the hydrologic cycle in natural-scale landscapes, today the discipline focuses on a wider spectrum of information resulting from the integration of laboratory and field, numerical modeling, and theory, with the contextual information (e.g., social, economic, legal) regarding those landscapes (Abbott, 1993; Abbott, 1994; Price et al., 1994).
Data Integrative Studies in Hydroinformatics
Published in Praveen Kumar, Jay Alameda, Peter Bajcsy, Mike Folk, Momcilo Markus, Hydroinformatics: Data Integrative Approaches in Computation, Analysis, and Modeling, 2005
Hydroinformatics draws upon and builds on developments in several related disciplines such as computer science, computer networking, database engineering, and hydrologic science. As such, the basic principles of hydroinformatics are interspersed among a variety of fields making it difficult for a novice to obtain a comprehensive introduction to the basic concepts. The intent of this book is to bridge this void and provide a pedagogical introduction to a variety of related topics. While the contents of the book reflect the current state-of-the-art thinking, it is not meant to be an introduction to the state of the current research. Rather, the book is designed to introduce the basic concepts underlying lot of research developments in hydroinformatics. It is hoped that the reader will gain sufficient insight to pursue independent reading in any one or a combination of these areas.
Recommendations for developing flood- protection measures: the case study of Ayutthaya, Thailand
Published in Vorawit Meesuk, Point Cloud Data Fusion for Enhancing 2D Urban Flood Modelling, 2017
The historic city of Ayutthaya, inscribed on the World Heritage list in 1991, is located in the central floodplain of Chao Phraya River Basin. Ayutthaya was subjected to the extreme flooding in autumn 2011, which can be counted as one of the worst flood disasters in Thai’s history. Sixty-six of seventy-six provinces were inundated, of which Ayutthaya had the highest fatality of 97 deaths (BOE, 2011). In response to flooding in Ayutthaya Island, UNESCO Bangkok liaised with the Thai Ministry of Culture’s Fine Arts Department (FAD) in mobilising national and international expertise for assessing flood damage extents and their causes, which occurred in the city centre of Ayutthaya. Results of two years’ research proposed new flood-prevention approaches in cooperation with UNESCO-IHE, AIT, FAD, UNESCO Bangkok, HAII, and ADB. New approaches proposed to bypass floodwater from up streams along with enhancements of local flood-protection measures. Advances in urban flood models as hydroinformatics tools can play a significant role as scientific supports to new proposed flood-protection measures. In this chapter, identifying key problems of flooding in Ayutthaya case study is described in Section 8.1. Proposing regional and local flood-protection measures are expressed in Section 8.2. Establishments of flood-simulation results are shown in Section 8.3. Evaluations of new flood-protection measures are highlighted their benefits of using urban flood models as hydroinformatics supporting tools (Section 8.4). Some examples of public hearing and participations of local communities are shown (Section 8.5). Conclusions are given in Section 8.6.
An initial parameter estimation approach for urban catchment modelling
Published in Urban Water Journal, 2023
Siming Gong, James E Ball, Nicholas Surawski
Based on the difference between parameter estimation and optimisation approaches, it is possible to categorise the parameter estimation methods as Forward propagation method. Measure, digitise and compute catchment characteristics using hydroinformatics tools or interpreting external datasets (e.g. GIS and remote sensing data) and parameterise the results for catchment modelling systems.Backward propagation method. The parameters are inferred through optimisation algorithms to best fit the observed hydrological data. A lower accuracy of the initial parameters is tolerated but need high-quality catchment monitoring data.
Resilience in major Australian cities: assessing capacity and preparedness to respond to extreme weather events
Published in International Journal of Water Resources Development, 2018
One important example of clear relevance to urban areas is role of Australian Rainfall and Runoff (ARR) (Geoscience Australia, 2016a). ARR is a key national engineering advice document that “provides the best available information on design flood estimation in a manner suitable for use by Australian practitioners with varying levels of knowledge about the design flood problems, flood processes, and engineering hydrology” (Ball, Babister, Retallick, & Weinmann, 2015, p. 1.1). As part of a national consideration of the impact of climate change towards the end of the Millennium Drought, there was a fundamental reconsideration of the design rainfall estimates that were set out in the 1987 edition. The output of this work, ARR 2015, will have a profound impact on flood management in urban areas. It incorporates “advances in knowledge regarding flood processes, the increased computational capacity available to engineering hydrologists, expanding knowledge and application of hydroinformatics, and information about climate change” (Ball, Babister, Retallick, & Weinmann, 2015, p. 1.1).