Tidal inlets are a common feature along the world’s coastline. Inlet-adjacent coastlines have for millennia supported communities and livelihoods, and therefore, projected climate change driven variations in catchment-estuary-coast (CEC) system drivers (e.g., sea-level rise (SLR)) are likely to lead to substantial socio-economic impacts. One important SLR-driven process that affects inlet-adjacent shoreline change is basin-infilling (i.e., sediment import to the estuary from the coast to satisfy the SLR-driven increase of estuarine accommodation space). Due to the slow morphological response to hydrodynamic forcing, however, there is a time lag between basin infilling and SLR, which, in numerical models that simulate century-scale evolution of CEC systems, is represented by a basin infilling lag factor (M). To date, an indicative M value has only been derived for small tidal inlet systems (M ~0.5), and due to the lack of M estimates for larger systems, studies have been using M ~0.5 indiscriminately. Here, for the first time, we derive indicative M values for small, medium, and large tidal inlet systems (M ~0.5, ~0.25 and ~0.15 respectively) via analytical considerations. Subsequently, to investigate the consequences of using sub-optimal M values on twenty-first century projections of inlet-adjacent shoreline change, we apply a probabilistic, reduced complexity model (G-SMIC), under four IPCC AR6 climate scenarios, to three CEC systems representing small, medium and large systems. Results show that, in general, shoreline change projections are substantially lower(higher) when M values smaller(larger) than the indicative M for a given system are used. When smaller-than-optimal M values (0.25 and 0.15) are used for the small tidal inlet, both mid- and end-century shoreline retreats are under-estimated by 50–75% (across the four climate scenarios), relative to projections obtained with the optimal M value. For the medium-sized inlet, shoreline retreats for both future periods are over-estimated by ~100% with the larger-than-optimal M value of 0.5, while they are under-estimated by ~40–75% (across climate scenarios) with the smaller-than-optimal M value of 0.15. When the two higher-than-optimal M values (0.25 and 0.5) are used for the large tidal inlet system, shoreline retreat is over-estimated by ~ 65–240% (across climate scenarios) for both future periods. In terms of absolute values, these under/over-estimations increase in time and with the severity of emission scenario. ... Read more

The African coast contains heritage sites of ‘Outstanding Universal Value’ that face increasing risk from anthropogenic climate change. Here, we generated a database of 213 natural and 71 cultural African heritage sites to assess exposure to coastal flooding and erosion under moderate (RCP 4.5) and high (RCP 8.5) greenhouse gas emission scenarios. Currently, 56 sites (20%) are at risk from a 1-in-100-year coastal extreme event, including the iconic ruins of Tipasa (Algeria) and the North Sinai Archaeological Sites Zone (Egypt). By 2050, the number of exposed sites is projected to more than triple, reaching almost 200 sites under high emissions. Emissions mitigation from RCP 8.5 to RCP 4.5 reduces the number of very highly exposed sites by 25%. These findings highlight the urgent need for increased climate change adaptation for heritage sites in Africa, including governance and management approaches, site-specific vulnerability assessments, exposure monitoring, and protection strategies. ... Read more

The coastal zones in the vicinity of tidal inlets, which are commonly utilized for navigation, sand mining, waterfront developments, fishing and recreation, are under particularly high population pressure. The intensive population concentration and excessive natural resources exploitation in these areas could lead to biodiversity loss, destruction of habitats, pollution, as well as conflicts between potential uses, and space congestion problems, which will only be exacerbated by foreshadowed climate change (CC). Although a very few recent studies have investigated CC impacts on very large tidal inlet/basin systems, the nature and magnitude of CC impacts on the more commonly found small tidal inlet/estuary systems remains practically undnvestigated to date. These relatively small estuaries/lagoons (also known as "bar-built" or "barrier" estuaries, and hereon referred to as Small Tidal Inlets or STIs) are common along wave-dominated, micrcrotidal mainland coasts comprising about 50% of the world's coastline.
Due to their common occurrence in the tropical and sub-tropical zones, most STIs are found in developing countries, where data availability is generally poor (i.e. data poor environments) and community resilience to coastal change is low. Furthermore, STI environs in developing countries especially host a number of economic activities (and thousands of associated livelihoods) which connibute significantly to the national GDPs. The combination of pre-dominant occurrence in developing countries, socio-economic relevance and low community resilience, general lack of data, and high sensitivity to seasonal forcing makes STIs potentially very vulnerable to CC impacts and thus a high priority area of research. This study was therefore undertaken with the overarching objective of (a) developing methods and tools that can provide insights on potential CC impacts on STIs, and (b) demonstrating their application to assess CC impacts on the main types of STIs.
Throughout this Thesis, 3 case study STIs representing the 3 main STI Types are used:
- Negombo lagoon, Sri Lanka: Permanently open, locationally stable inlet (Type 1)
- Kalutara lagoon, Sri Lanka: Permanently open, alongshore migrating inlet (Type 2)
- Maha Oya river, Sri Lanka: Seasonally/Intermittently open, locationally stable inlet (Type 3)
To circumnavigate the inability of contemporary process based coastal area morphodynamic models to accurately simulate the morphological evolution of STIs over typical CC impact assessment time scales (e.g. 100 yrs) with concurrent tide, wave and riverflow forcing, 2 different snap-shot modelling approaches for data poor and data rich environments are proposed. The data poor approach uses schematized flat bed bathymetries that follow real world STIs and CC forcing derived from freely available coarse resolution global models while the data rich approach requires detailed bathymetries and downscaled CC forcing. Furthermore, to enable rapid assessments of CC impacts on STI stability, particularly to aid frontline coastal zone managers/planners, a reduced complexity model is developed based on existing knowledge and physical formulations. The model, which is capable of simulating 100 years in under 3 seconds on a standard PC, provides predictions of STI stability based on the Bruun inlet stability criterion.
Although CC driven STI Type changes appear to be rather unlikely in the 21th century, model results do show that CC is likely to change the level of stability of STIs, indicated by significant future changes of the value from its present value. At Type 1 STIs, future CC driven increases/decreases in longshore sediment transport may result in decreases/increases in their level of stability. At Type 2 and Type 3 STIs concurrent increases (decreases) in longshore sediment transport and decreases (increases) in riverflow may result in decreasing (increasing) the level of inlet stability. Sea level rise (SLR) appears not to be the main driver of change in the level of STI stability, with CC driven variations in wave direction emerging as the major driver of potential change in STI stability.
For future CC impacts assessment at STIs, an initial assessment using the reduced complexity model is recommended. If Type changes are predicted at any time (or if r drops below 10 for a Type 2 STI), or if specific insights (e.g. migration distance at Type 2 STIs, inlet closure time at Type 3 STIs) are desired, then it is essential that the (data poor or data rich, depending on which is feasible in the study area) process based snap-shot modelling approach be adopted. ... Read more

Tidal inlets are of great societal importance and are also the most morphologically dynamic regions in the coastal zone. Therefore, they are of great scientific interest. Their behaviour is governed by the delicate balance of oceanic processes such as tides, waves and mean sea level (MSL), and fluvial/estuarine processes such as riverflow. All of these processes can be significantly affected by climate change (CC) processes, which may result in negative physical impacts such as inlet closure/relocation, creation of new inlets, erosion of the coast adjacent to the inlet etc. Although CC impacts on some large tidal inlets (e.g. Wadden Sea inlets) have received some attention recently, the potential CC impacts on small tidal inlets (STIs) remain virtually unknown to date. Furthermore, whether currently available predictive tools are capable of simulating CC impacts on these systems also remains unknown. These knowledge gaps are a serious threat to effective adaptation to CC in STI environments. Just, this study attempts to investigate the potential range of CC impacts on the stability (i.e. closed/open state and locational stability) of STIs via the application of a sophisticated process based morphodynamic model (Delft3D) to strategically selected schematised inlet morphologies and forcing conditions.Results indicate that CC driven variations in system forcing are likely have profound impacts on inlet stability and also show that a process based coastal morphodynamic model (eg. Delft3D) is suitable for investigating potential CC impacts at small tidal inlets. ... Read more