Spatially represented floodplain inundation behaviour is a critical input for many river-floodplain ecosystem studies. Such data is often sourced from geospatial products that link in-channel peak flow rates at a gauge to spatially explicit floodplain hydraulic conditions across a broad range of flow magnitudes. Here we present the Murrumbidgee Hydraulic Floodplain Inundation Model (Hy-FIM), developed to provide maximum inundation extent, water depth, water level and velocity information for multiple in-channel peak flow rates across the Murrumbidgee River catchment, NSW, Australia.
Hy-FIM was developed using sixteen calibrated two-dimensional hydraulic models, with each hydraulic model simulating inflow hydrographs with distributed peak flow rates. Inflow hydrographs were derived using median historical rates of rise and fall from similar-sized events. Twenty peak flow rates were modelled at each representative gauge, spanning from large fresh-sized flows to large flood events with ~1% annual exceedance probability.
Hydraulic model outputs were aggregated into two data products: (1) a raster file identifying the minimum peak flow rate required to inundate each cell, and (2) a NetCDF file containing all hydraulic outputs for every simulated event. These products cover the Murrumbidgee River floodplain from Gundagai to Balranald Weir as well as the upper Yanco–Colombo Creek system.
The Hy-FIM methodology provides an information-rich tool for assessing floodplain inundation dynamics relative to in-channel flow rates. It is suitable for assessments concerned with typical or average inundation outcomes, and development using calibrated hydraulic models provides high confidence in model accuracy within the context of clearly documented structural and operational assumptions. This approach addresses several limitations associated with satellite-image derived products. Hy-FIM’s methodology is transferrable for product development in other catchments, and presents an opportunity for scenario testing where different relationships between flow rates and inundation patterns (reflecting custom structural or operational scenarios) can be modelled for ecological models or assessments.