Approximately one-quarter of the World's sandy beaches, most of which are interrupted by tidal inlets, are eroding. Understanding the long-term (50-100 year) evolution of inletinterrupted coasts in a changing climate is, therefore of great importance for coastal zone planners and managers. This study, therefore, focuses on the development and piloting of an innovative model that can simulate the climate-change driven evolution of inlet-interrupted coasts at 50-100 year time scales, while taking into account the contributions from catchment-estuary-coastal systems in a holistic manner. In this new model, the evolution of inlet-interrupted coasts is determined by: (1) computing the variation of total sediment volume exchange between the inlet-estuary system and its adjacent coast, and (2) distributing the computed sediment volume along the inlet-interrupted coast as a spatially and temporally varying quantity. The exchange volume, as computed here, consists of three major components: variation in fluvial sediment supply, basin (or estuarine) infilling due to the sea-level rise-induced increase in accommodation space, and estuarine sediment volume change due to variations in river discharge. To pilot the model, it is here applied to three different catchmentestuary-coastal systems: the Alsea estuary (Oregon, United States), Dyfi estuary (Wales, United Kigdom), and Kalutara inlet (Sri Lanka). Results indicate that all three systems will experience sediment deficits by 2100 (i.e., sediment importing estuaries). However, processes and system characteristics governing the total sediment exchange volume, and thus coastline change, vary markedly among the systems due to differences in geomorphic settings and projected climatic conditions. These results underline the importance of accounting for the different governing processes when assessing the future evolution of inlet-interrupted coastlines.

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The availability of accurate spatiotemporal rainfall data is of utmost importance for reliable predictions from hydroclimatological studies. Challenges and limitations faced due to the absence of dense rain gauge (RG) networks are seen especially in the developing countries. Therefore, alternative rainfall measurements such as satellite rainfall products (SRPs) are used when RG networks are scarce or completely do not exist. Noteworthy, rainfall data retrieved from satellites also possess several uncertainties. Hence, these SRPs should essentially be validated beforehand. The Mahaweli River Basin (MRB), the largest river basin in Sri Lanka, is the heart of the country’s water resources contributing to a significant share of the hydropower production and agricultural sector. Given the importance of the MRB, this study explored the suitability of SRPs as an alternative for RG data for the basin. Daily rainfall data of six types of SRPs were extracted at 14 locations within the MRB. Thereafter, statistical analysis was carried out using continuous and categorical evaluation indices to evaluate the accuracy of SRPs. Nonparametric tests, including the Mann-Kendall and Sen’s slope estimator tests, were used to detect the possibility of trends and the magnitude, respectively. Integrated MultisatellitE Retrievals for Global Precipitation Measurement (IMERG) outperformed among all SRPs, while Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) products showed dire performances. However, IMERG also demonstrated underestimations when compared to RG data. Trend analysis results showcased that the IMERG product agreed more with RG data on monthly and annual time scales while Tropical Rainfall Measurement Mission Multisatellite Precipitation Analysis–3B42 (TRMM-3B42) agreed more on the seasonal scale. Overall, IMERG turned out to be the best alternative among the SRPs analyzed for MRB. However, it was clear that these products possess significant errors which cannot be ignored when using them in hydrological applications. The results of the study will be valuable for many parties including river basin authorities, agriculturists, meteorologists, hydrologists, and many other stakeholders.

Sandy coastlines adjacent to tidal inlets are highly dynamic and widespread landforms, where large changes are expected due to climatic and anthropogenic influences. To adequately assess these important changes, both oceanic (e.g., sea-level rise) and terrestrial (e.g., fluvial sediment supply) processes that govern the local sediment budget must be considered. Here, we present novel projections of shoreline change adjacent to 41 tidal inlets around the world, using a probabilistic, reduced complexity, system-based model that considers catchment-estuary-coastal systems in a holistic way. Under the RCP 8.5 scenario, retreat dominates (90% of cases) over the twenty-first century, with projections exceeding 100 m of retreat in two-thirds of cases. However, the remaining systems are projected to accrete under the same scenario, reflecting fluvial influence. This diverse range of response compared to earlier methods implies that erosion hazards at inlet-interrupted coasts have been inadequately characterised to date. The methods used here need to be applied widely to support evidence-based coastal adaptation.