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Developing a spatial approach to support local flood-risk-based land use planning

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posted on 2024-11-23, 03:11 authored by Hossain Pourali
Flood-risk-based land use planning is largely a local government responsibility in Australia. In my research I sought to develop a new spatial approach to improve the implementation of flood-risk-based land use planning that can be used by local governments. In Australia, strategies for floodplain management to reduce and control flooding are best implemented at the land use planning stage. Flood-risk-based land use planning results in sustainable land management activities, including floodplain management. Flood-risk-based land use planning is largely dependent on flood behaviour across the land development areas, which can be documented in the form of planning zones that warn land use planners about the flood-threatened area. However, these are often out-dated so do not reflect the influence of recent land use changes. This is particularly for peri-urban areas (largely focus on riverine floods) and expensive to update. Developing a new approach based on geospatial science facilitates the implementation of flood-risk-based land use planning process and can provide a better approach for local governments in terms of cost, accuracy and ease of updating. To develop a new approach, a clear understanding of responsibility for flood-risk-based land use planning, the workflow processes in the authority responsible for such planning, the quality of existing database and how new data sources and the technology (e.g., LiDAR data and crowd source data) that can be used for flood-risk-based land use planning, is essential. The research involved a case study to document the process of flood-risk-based land use planning processes used by a Victorian council, an assessment of flood-relevant database completeness and accuracy, determination of missing datasets and information in the council’s flood-relevant GIS database, and development of methods based on GIS-embedded hydrological models to generate those datasets.<br>

History

Degree Type

Doctorate by Research

Imprint Date

2014-01-01

School name

School of Science, RMIT University

Former Identifier

9921861380401341

Open access

  • Yes

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