Some estuaries close intermittently when sand is deposited at their mouths and there is insufficient hydraulic energy to breach it. When closed, water levels may rise and flood surrounding land. These floods may adversely impact infrastructure, agriculture and ecosystems that are intolerant of inundation. Consequently, there is often pressure for managers to mechanically open such estuaries. Artificial openings can also cause serious adverse impacts, including mass fish kills, and there may be counter-pressure to leave the estuary closed. Thus, artificial estuary opening is complex and often contested. In response, managers are increasingly using quantitative measures of expected impact to inform and justify their decisions. Here, we demonstrate, using a case study, a tractable approach that quantifies the expected adverse impacts on native estuarine vegetation resulting from inundation. We used structured expert (n = 4) elicitation to gather mortality estimates of 18 prominent estuarine plant taxa under different inundation scenarios (3 salinities, 5 durations). We then used these data to quantify the expected impact on discrete vegetation types, each of which is characterised by one or more of the selected species. Using 1 cm LiDAR-derived elevation data and pre-existing mapping of vegetation types for specific estuaries, we simulated 105 inundation scenarios (7 depths; 3 salinities; 5 durations). From the extent of different vegetation types inundated in the simulations, and the various expected impacts of inundation on each vegetation type, we computed estuary-wide impact scores. These impact scores express the degree of vegetation mortality expected under a given flood scenario for a given estuary. We demonstrated this approach by computing impact scores for 28 artificially opened estuaries in Victoria, Australia. These scores can be used alongside other data (for infrastructure, other biota, etc), to inform mouth-opening decisions. The approach described could be applied to any estuary, provided there is adequate vegetation mapping, elevation data and knowledge or data on the impacts of flooding on the vegetation.
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