Dataset for article: "A framework to combine ongoing beach monitoring data with modular hazard and erosion risk modelling to inform operational coastal management", McCarroll et al. (2025)

Details below for article submitted to Ocean and Coastal Management (revised version submitted 6/7/2025) Article title: A framework to combine ongoing beach monitoring data with modular hazard and erosion risk modelling to inform operational coastal management Robert J. McCarroll1, David M. Kennedy1, Jin Liu2, Blake Allan3, Elisa Zavadil3, Daniel Ierodiaconou4 1 School of Geography, Earth and Atmospheric Sciences, The University of Melbourne, Parkville, Victoria, Australia 2 School of Biosciences, The University of Melbourne, Parkville, Victoria, Australia 3 Department of Energy Environment and Climate Action, Melbourne, Victoria, Australia 4 School of Life and Environmental Sciences, Deakin University, Warrnambool, Victoria, Australia Abstract Information on coastal erosion risk is essential for effective coastal management. Ideally, risk assessments should be regularly updated with ongoing monitoring data, allowing identification of local-scale, time-varying threats. Yet, due to resource requirements, this approach is rare. This work presents on a collaboration between a state government and a regional authority to establish cost-effective methods for dynamic reporting on coastal risk, covering 16 sites along the Great Ocean Road, Victoria, Australia, incorporating ongoing monitoring data (>300 drone surveys and 35 years of satellite-derived shorelines). A transect-based coastal database, maintained at the state level, provides a framework for modular analyses that scale in complexity according to site priority. Tools built into the framework include: (1) coastal erosion warning indicators; (2) potential land and asset impact; and (3) numerical modelling of coastal risk levels and beach management scenarios. Dynamic assessments were designed to support operational management, providing updates on short and long-term shoreline change. As part of the final pilot program assessment, 3 sites (of 16) had high long-term erosion trends, 4 experienced moderate short-term erosion (last 2 years), and a high risk of erosion to assets was predicted for 2 sites. Detailed risk modelling for a high-priority site (Marengo) was used to inform where further intervention was required, and to assess medium-term (10 years) beach nourishment scenarios. Use of a modular, scalable framework capable of incorporating ongoing monitoring data can provide effective decision support for time-sensitive management options. We suggest wide-reaching management benefits could be achieved by provision of large-scale coastal databases by national and provincial authorities, allowing resource-limited coastal managers to benefit through cost-efficient local-scale application of hazard and risk assessment tools. Keywords: coastal hazards, shoreline change, drone, UAV, satellite derived shorelines, beach nourishment