| MD-WERP theme |
Hydrology |
| MD-WERP research question |
How can floodplain flow volumes, components, and inundation prediction be improved to support environmental watering and water resources planning? |
| Project title |
Enhancing floodplain inundation and volume prediction to support environmental watering and water resource planning |
| Research lead |
CSIRO |
| Authors |
Jin Teng, Dave Penton, Catherine Ticehurst, Ang Yang, Steve Marvanek, Robert Bridgart, Jai Vaze, Fathaha Khanam, Cherry Mateo, Francis Chiew, Hongxing Zheng, Jenet Austin, David Post and Eilish Brennan |
| Author contact details |
Jin Teng |
| Date of publication |
January 2025 |
| Report full title |
Advancing Floodplain Inundation and Volume Prediction for Water Management |
| Keywords |
Floodplain; inundation; Murray–Darling Basin; simulation; flood; water resource planning; climate; data; RQ7; Basin states; CEWO; |
| Summary of output |
- This project (known as RQ7) aims to build on the foundational models and capacities developed through previous research, advancing floodplain inundation modelling to support systematic management and scenario planning across the Murray–Darling Basin. The report is structured into 4 main sections:
- Review and Input Data Preparation: This section provides a review of existing literature, methodologies, and the extensive data preparation that underpins the model, datasets and relative research.
- Research: Here, we delve into the core research activities, including the development of methods and approaches designed to enhance surface water detection from remote sensing imagery and a water depth estimation model that is essential for inundation volume predictions.
- Datasets: This section outlines the datasets developed and utilized throughout the project, which serve as critical resources for modelling, validating floodplain responses, and investigating climate change impact on flooding.
- RQ7 Model: Finally, the report details the RQ7 inundation model, a tool that synthesizes the research findings and data, aiming to offer more accurate predictions of floodplain water volume and spatial inundation patterns.
|
| Key findings / recommendations |
- Our research activities focused on developing innovative methods to enhance the accuracy and coverage of floodplain inundation extent, depth, and volume predictions, tailored to the unique characteristics of the Basin. Specifically, we developed advanced techniques for detecting surface water from remote sensing imagery and benchmarked water depth estimation models, critical for precise inundation volume calculations. These advancements support both dataset production and modelling development, forming a crucial basis for future applications.
- We have created high-resolution datasets that include maps of inundation extents, water depth, persistent water presence, and the maximum number of consecutive dry years across the basin. These datasets are instrumental for quantifying flood characteristics and assessing the impacts of climate change on flooding patterns within the Basin.
- The core output of the project, the RQ7 Model, integrates these research findings and datasets into a predictive tool designed to provide reliable estimates of floodplain water volumes and spatial inundation patterns.
|
| Target audience |
Researchers, hydrological modellers, groundwater modellers, Australian Government, state governments, local governments, water and environmental consultants |
PDF