Hypoxic blackwater events occur worldwide, affecting inland and coastal waters. These events have been exacerbated by man-made floodplain drainage, leading to large-scale fish kills and ecological degradation. This paper presents a new method to identify estuarine catchment areas that are most likely to generate hypoxic conditions. The method uses established blackwater risk factors, including vegetation type, inundation extent and duration, ground-truthed in eastern Australia. A catchment is at higher risk of blackwater generation if (i) it is located where floodwaters are high and/or drainage is impeded, (ii) the site topography includes an extensive, low-lying floodplain; and/or (iii) the land-use and environmental characteristics have a high deoxygenation potential. Blackwater impacts in an estuary are determined by the floodplain connectivity with the estuary, and the discharge characteristics of the catchment drainage system. Where multiple, proximate catchments have similar drainage conditions, compounding blackwater plumes can overwhelm the assimilation capacity of the estuary. Climate change may significantly increase the volume and frequency of blackwater events in estuarine environments as a result of reduced drainage due to sea level rise, higher temperatures, and more intense and sporadic rainfall events. It is recommended that management measures be introduced to mitigate the effects of climate change and avoid further widespread hypoxic blackwater events.

Constructed flood mitigation and drainage systems are integral to the development of many estuarine floodplains. These systems function throughout the tidal range, protecting from high water levels while draining excess catchment flows to the low water level. However, drainage can only be achieved under gravity when suitable water levels are available for discharge. Changes to the tidal range and symmetry that occur throughout estuarine waters mean that the window of opportunity for gravity discharge will vary dynamically within and between different catchments. It will also be affected by sea level rise (SLR). Concerns regarding the impacts of SLR have focussed on the acute effects of higher water levels, but SLR will affect the full tidal range and drainage systems will be particularly vulnerable to changes in the low tide. This study introduces the concept of the “drainage window”; to assess how the tidal regime may influence the drainage of estuarine floodplains, and particularly the potential impact of changing tidal regimes under SLR. The results of applying the drainage window to two different estuaries indicate that SLR may substantially reduce the opportunity for discharging many estuarine floodplain drainage systems. Additionally, measures proposed to mitigate flood risks may exacerbate drainage risks. Reduced drainage creates a host of chronic problems that may necessitate changes to existing land uses. A holistic assessment of future changes to all water levels (including low tide water levels) is required to inform strategic land use planning and management.

Despite their global abundance and high ecological and socio-economic significance, the dynamics of coastal inlets often remain poorly quantified at multi-decadal time scales. Here, we introduce InletTracker, a new tool that reconstructs the time-evolving state of dynamic coastal inlets over the last 30+ years from publicly available Landsat 5, 7 and 8 and Sentinel 2 satellite imagery. InletTracker is a Google Earth Engine enabled python toolkit that uses a novel least cost pathfinding approach to trace inlets along and across the berm (i.e., barrier, bar), and then analyses the resulting transects to infer whether an inlet is open or closed. To evaluate the performance of InletTracker, we applied the tool at 12 intermittent coastal inlets with different maximum inlet widths (≤30-200m), geomorphological setting and opening frequency located across Southeastern and Southwestern Australia. This exercise involved 6363 unique binary inlet state predictions (i.e., open vs. closed) that were validated against visually inferred inlet states (from the satellite imagery itself), on-ground observational records, and in situ water levels from inside the inlets. InletTracker reproduced the visually inferred inlet states with an average accuracy across all sites of 89% for the combined Landsat and Sentinel 2 record (15-30m resolution) and 94% for the Sentinel 2 record only (10m resolution). Overall, we found good agreement between the predictions of the tool and the three independent validation datasets for all but the smallest sites. Our results demonstrate that InletTracker will enable coastal engineers, managers, and researchers to gain new insights into the dynamics and drivers of coastal inlets or similar shallow water landforms such as river mouths, tidal flats, floodplains, wetlands or delta channel networks. Further, the high spatial (i.e., 10m) and temporal (i.e., 5 daily) resolution provided by Sentinel 2 makes InletTracker a viable option for near real-time monitoring of even relatively small inlets with a minimum channel width of around 10m and frequent, short duration, openings.