Future Shoreline Changes Research Articles

GIS-BASED ESTIMATION OF SHORELINE CHANGE AT THE OLIE PIER HARBOR HERITAGE SITE, MANGGAR, EAST BELITUNG, INDONESIA

The coastal area is a dynamic region influenced by continuous interactions between land and the sea. Changes in coastal compositions are closely related to shoreline instability. This study analyzes coastline changes at the Olie Pier Heritage Site, Manggar, East Belitung, Indonesia, using statistical-based techniques EPR (End Point Rate) and NSM (Net Shoreline Movement) 2015 to 2023. The DSAS (Digital Shoreline Analysis System) was employed to calculate the shoreline alterations in every transect with a distance of about 100 m. The study area is generally predominated by a moderate abrasion. The EPR and NSM values indicate a potential for future shoreline changes, considering the present status and future estimations of oceanographic parameters (currents, wind, waves, tides). The highest erosion is identified in the Lalang Village with a shoreline retreat (NSM) of -65.38 m and a retreat rate (EPR) of 8.78 m/year. On the other hand, the highest accretion is observed in the Baru Village with a NSM of -56.68 m and EPR of 7.61 m/year. The implications of these shoreline changes on the heritage site and the coastal environment contribute to the management of coastal areas amidst global environmental challenges. This study provides valuable insights into conservation and sustainable development efforts in the coastal region of East Belitung.

On the Bruun Rule suitability for modelling shoreline change

Modelling and understanding shoreline response to sea-level rise over decadal to centennial timescales is crucial for managing sandy coasts. Globally, the Bruun Rule is one of the most common shoreline model applied to facilitate this. However, there are several limitations to the Bruun Rule, which can compromise coastal management decisions. Here, we provide a novel assessment of the suitability of the Bruun Rule for application in sandy coasts by applying it to hindcast and project shoreline change in three morphologically different sandy beaches over yearly and decadal timescales. We also compare the Bruun Rule predictions against associated observations, published predictions from a hybrid shoreline model, and historical shoreline changes. Results show that the Bruun Rule fails to accurately hindcast and provide realistic projections of future shoreline change in sandy coasts. We attribute this to the Bruun Rule's assumption of linearity between shoreline retreat and relative sea-level rise and its inability to account for nearshore circulation. We, therefore, recommend limiting the use of the Bruun Rule for informing policy and the management of sandy coasts.

Coastal evolution and future projections in Conde County, Brazil: A multi-decadal assessment via remote sensing and sea-level rise scenarios

Global sea levels, having risen by approximately 20 cm since the mid-19th century, necessitate a critical examination of their impacts on shoreline dynamics. This research evaluates the historical (1985–2022) and future shoreline changes in Conde County, Paraíba State, Brazil, an area of significant touristic interest. Employing Landsat satellite imagery, the study utilized the Digital Shoreline Analysis System (DSAS) and a Kalman filter algorithm for cloud removal, while also assessing land use and land cover changes using data from the MapBiomas Project for 2000, 2010, and 2020. These analyses informed projections of potential inundation under various sea-level rise (SLR) scenarios: 1, 2, 5, and 10 m. Key findings revealed a negative average coastline change rate of −0.27 m/year from 1985 to 2022, indicative of erosive trends likely accelerated by human activities. Long-term projections for 2032 and 2042 anticipate continued erosion in areas identified as highly vulnerable. The SLR scenario analysis underscores the urgent need for adaptive climate measures; while a 1- or 2-meter SLR presents limited immediate effects, a 5-meter rise could lead to significant inundation across key sectors, including urban and agricultural landscapes. The projected severity of a 10-meter SLR necessitates immediate, comprehensive interventions to safeguard both natural and human systems.

PRELIMINARY INVESTIGATION OF SHORELINE RESPONSE IN SAN JUAN, LA UNION, PHILIPPINES

Coastal erosion has been affected by environmental factors and human development. The investigation of the coastal erosion in San Juan, La Union covers the analysis and quantitative data that can be applied to protect the coastal community, to minimize economic losses, and to plan for the improvement of coastal process response. The main objective of this study was to investigate the shoreline response based on the extent of the coastal erosion problem of the 5.36 km - coastline of San Juan La Union and predict the long-term erosion pattern and shoreline change. The characteristics of the triggering factors of coastal erosion were evaluated during normal and extreme weather conditions. The areas along the coastline were characterized whether it experienced dominant deposition or erosion. Changes in shoreline position were assessed to predict future shoreline change scenarios. Sediment transport analysis was conducted by using the Kamphuis Formula and the CERC Formula.

Evaluation of Cua Lo Estuary’s Morpho-Dynamic Evolution and Its Impact on Port Planning

Coastal erosion and accretion along the Quang Nam coast in Vietnam have been increasing in recent years, causing negative impacts on the inhabitants and local ecology. The Cua Lo estuary in Nui Thanh district has a complex hydrodynamic regime owing to its connection with two estuaries and three different tributaries. Therefore, a detailed study of the mechanisms and processes of these phenomena is crucial to understand the potential impact of a proposed 50,000-ton cargo port. In this study, the Delft3D model is employed to evaluate the morpho-dynamic changes in the area of Cua Lo under monsoon wave climate, storm, and flood conditions both before and after port and navigation channel construction. Results indicate that in the absence of the port, tidal currents and waves during monsoon storms cause significant erosion on the south bank and accretion on the north bank. Furthermore, the GenCade model is utilized to predict the future shoreline changes after the construction of two jetties. The model reveals that after 50 years of operation, the shoreline modifications will extend 449 m towards the sea, in comparison to natural conditions. However, the design of the northern jetty will ensure safe and proper operation without impacting the navigation channel. This study offers valuable insights into the morphological changes in the Cua Lo area and their potential implications, which can aid in the development of sustainable coastal management strategies for the region.

Improving multi-decadal coastal shoreline change predictions by including model parameter non-stationarity

Our ability to predict sandy shoreline evolution resulting from future changes in regional wave climates is critical for the sustainable management of coastlines worldwide. To this end, the present generation of simple and efficient semi-empirical shoreline change models have shown good skill at predicting shoreline changes from seasons up to several years at a number of diverse sites around the world. However, a key limitation of these existing approaches is that they rely on time-invariant model parameters, and assume that beaches will evolve within constrained envelopes of variability based on past observations. This raises an interesting challenge because the expected future variability in key meteocean and hydrodynamic drivers of shoreline change are likely to violate this ‘stationary’ approach to longer-term shoreline change prediction. Using a newly available, multi-decadal (28-year) dataset of satellite-derived shorelines at the Gold Coast, Australia, this contribution presents the first attempt to improve multi-decadal shoreline change predictions by allowing the magnitude of the shoreline model parameters to vary in time. A data assimilation technique (Ensemble Kalman Filter, EnKF) embedded within the well-established ShoreFor shoreline change model is first applied to a 14-year training period of approximately fortnightly shoreline observations, to explore temporal variability in model parameters. Then, the magnitudes of these observed non-stationary parameters are modelled as a function of selected wave climate covariates, representing the underlying seasonal to interannual variability in wave forcing. These modelled time-varying parameters are then incorporated into the shoreline change model and tested over the complete 28-year dataset. This new inclusion of non-stationary model parameters that are directly modelled as a function of the underlying wave forcing and corresponding time scales of beach response, is shown to outperform the multi-decadal predictions obtained by applying the conventional stationary approach (RMSEnon-stationary = 11.1 m; RMSEstationary = 254.3 m). Based on these results, it is proposed that a non-stationary approach to shoreline change modelling can reduce the uncertainty associated with the misspecification of physical processes driving shoreline change and should be considered for future shoreline change predictions.

Sea level rise and future shoreline changes along the sandy coast of Saloum Delta, Senegal

Sea level rise and future shoreline changes along the sandy coast of Saloum Delta, Senegal

Coastal erosion risk assessment and applied mitigation measures at Ezbet Elborg village, Egyptian delta

Coastal areas globally suffer from serious erosion and sedimentation problems. The assessment of coastal erosion risk is fundamental for better coastal management. The main goal of the current study was to enhance coastal management by identifying the coastal erosion risk and suggest possible mitigation measures. The study was developed for the Egyptian Northern Coast. MIKE 21 was used to evaluate the erosion and test the proposed measures. First, a bathymetric survey of the study area was conducted. Then the tidal data, storm surge, and global sea rise data were collected. The offshore wave data, shoreline data were compiled. And then, the different nearshore wave modeling and wave propagation were modeled. The model was calibrated using measured data in 2014 and validated using measured data in 2016. Future shoreline changes for the years 2029, 2039, and 2049 were depicted. A suitable mitigation measure was used and tested for the same years. The groins with a specific size and arrangement were tested. The main goal of the study is to find a suitable solution to protect the coast and investigate its impact on the shoreline in the next 30 years. The proposed mitigation measure minimized the coastal erosion of the study area rigorously.

Multi-decadal shoreline morphodynamics of a shelf-edge reef island, Great Barrier Reef: Implications for future island persistence

Future climatic change and sea-level rise threaten the persistence of reef islands potentially making them uninhabitable over the next century. Improved understanding of island morphodynamics at multiple time scales is required for resolving major drivers of shoreline change and predicting future island resilience. Utilising 45 individually mapped shorelines, the morphodynamic change of a shelf-edge reef island (Raine Island, Great Barrier Reef) has been quantified over a 57-year time scale in the context of environmental change and anthropogenic impacts. Results show that between 1963 and 2020, there has been an average net shoreline movement (NSM) of −4.71 m and an average rate of retreat of −0.11 m/yr. However, only 23% of the shoreline has exhibited statistically significant erosion while the remaining 77% has remained stable. Importantly, data reveal a remarkable level of long-term shoreline stability despite large seasonal fluctuations in wind and wave climate, episodic storm events, and a regional sea level rise currently outpacing the global mean. Direct human impact, through modifications of the beach profile since 2014, have resulted in localised increases in rates of shoreline change but have only slightly decreased the proportion of stable shoreline (91% since modifications commenced versus 96% prior to modifications). Interestingly, there is a significant decreasing trend in island planform area over the 57-year period and especially over the last decade. However, the length of the observation interval between sampled shorelines has a strong effect on the change in planform area recorded over the interval, suggesting increased sampling frequency, rather than sea level rise, is a more likely cause of the decreasing trend. The findings of this study have direct implications for more accurate assessments of past, present and future shoreline change on reef islands. They also support the concept of 21st century island persistence in the face of climate change although the relative resilience of a given island to change (e.g., sea level, human modifications) will depend on a continuous adequate supply of sediment from organisms living on the surrounding reef, which may or may not be threatened in the future.

Uncertainties in Shoreline Projections to 2100 at Truc Vert Beach (France): Role of Sea‐Level Rise and Equilibrium Model Assumptions

AbstractSandy shorelines morphodynamics responds to a myriad of processes interacting at different spatial and temporal scales, making shoreline predictions challenging. Shoreline modeling inherits uncertainties from the primary driver boundary conditions (e.g., sea‐level rise and wave forcing) as well as uncertainties related to model assumptions and/or misspecifications of the physics. This study presents an analysis of the uncertainties associated with future shoreline evolution at the cross‐shore transport dominated sandy beach of Truc Vert (France) over the 21st century. We explicitly resolve wave‐driven shoreline change using two different equilibrium modeling approaches to provide new insight into the contributions of sea‐level rise, and free model parameters uncertainties on future shoreline change in the frame of climate change. Based on a Global Sensitivity Analysis, shoreline response during the first half of the century is found to be mainly sensitive to the equilibrium model parameters, with the influence of sea‐level rise emerging in the second half of the century (∼2050 or later), under several simulated scenarios. The results reveal that the seasonal and interannual variability of the predicted shoreline position is sensitive to the choice of the wave‐driven equilibrium‐based model. Finally, we discuss the importance of the chronology of wave events in future shoreline change, calling for more continuous wave projection time series to further address uncertainties in future wave conditions. Our contribution demonstrates that unmitigated climate change can result in shoreline retreat of several tens of meters by 2100, even for sectors that have been stable or slightly accreting over the last century.

Deep uncertainties in shoreline change projections: an extra-probabilistic approach applied to sandy beaches

Abstract. Global mean sea level rise and its acceleration are projected to aggravate coastal erosion over the 21st century, which constitutes a major challenge for coastal adaptation. Projections of shoreline retreat are highly uncertain, however, namely due to deeply uncertain mean sea level projections and the absence of consensus on a coastal impact model. An improved understanding and a better quantification of these sources of deep uncertainty are hence required to improve coastal risk management and inform adaptation decisions. In this work we present and apply a new extra-probabilistic framework to develop shoreline change projections of sandy coasts that allows consideration of intrinsic (or aleatory) and knowledge-based (or epistemic) uncertainties exhaustively and transparently. This framework builds upon an empirical shoreline change model to which we ascribe possibility functions to represent deeply uncertain variables. The model is applied to two local sites in Aquitaine (France) and Castellón (Spain). First, we validate the framework against historical shoreline observations and then develop shoreline change projections that account for possible (although unlikely) low-end and high-end mean sea level scenarios. Our high-end projections show for instance that shoreline retreats of up to 200 m in Aquitaine and 130 m in Castellón are plausible by 2100, while low-end projections revealed that 58 and 37 m modest shoreline retreats, respectively, are also plausible. Such extended intervals of possible future shoreline changes reflect an ambiguity in the probabilistic description of shoreline change projections, which could be substantially reduced by better constraining sea level rise (SLR) projections and improving coastal impact models. We found for instance that if mean sea level by 2100 does not exceed 1 m, the ambiguity can be reduced by more than 50 %. This could be achieved through an ambitious climate mitigation policy and improved knowledge on ice sheets.

Forecasting shoreline changes along the Egyptian Nile Delta coast using Landsat image series and Geographic Information System.

Before construction of the Aswan High Dam, the Nile Delta was expanding and advancing into the Mediterranean Sea. Subsequently, it became a highly destructive Delta due to the lack of sediment discharge, climate change, subsidence, and coastal processes (e.g. wind, waves, tides, and littoral currents). Many coastal structures have been erected to stop or mitigate coastal problems in the study area. We used 31 Landsat images to monitor the fluctuation of erosion and deposition along the study area. The shorelines in these huge datasets were extracted using standard techniques. Linear regression ratio (LRR) and end-point rate (EPR) were used with Digital Shoreline Analysis System (DSAS) software to determine the rates of beach changes; we then forecast future shoreline changes. The accuracy of the model's results was checked using the ground field measurements of several studies. This model also creates an estimate of the position uncertainty at each time step. The value of the uncertainty is low (approximately half a pixel) along the shorelines without coastal protection. This study aimed to forecast future beach evolution to the year 2041 to evaluate its sensibility and facilitate proposals for coastal protection for human safety and habitats if the coastal processes and climate change continue to worsen with time.

Determining the Shoreline Retreat Rate of Australia Using Discrete and Hybrid Bayesian Networks

AbstractEvaluating shoreline retreat rate (SRR) on different spatial‐temporal scales is critical for effective coastal management. Large‐scale evaluations typically rely on data‐driven methods such as Discrete Bayesian networks (BNs). However, these BNs require discretization of continuous variables which can lead to information loss. Here, we propose a new method, the Hybrid BN to incorporate continuous variables without discretization. Both Discrete and Hybrid BNs were developed and compared to evaluate large‐scale (continental scale) SRR in Australia, using Digital Earth Australia data set. These BNs used forcing parameters (e.g., waves, tide, sediment sink/source, and sea level rise [SLR]) and geomorphic settings (e.g., geomorphology, backshore profile, and surfzone slope) to predict SRR. Validation of the BNs showed that Hybrid BNs, which provide a more realistic assessment of the range of SRR, outperform in predicting continuous variables, when compared with Discrete BNs. However, Discrete and Hybrid BNs provide consistent qualitative findings for the SRR of Australia. Among forcing parameters, the sediment sink/source was found to be the most informative variable to indicate the shoreline retreat, followed by tide, SLR rate, and wave processes. In the scenario of an increased SLR rate, tropical tidal flats were predicted as the most at risk coasts in Australia. We found that BNs can reflect the impact of different factors on coastal evolution, and predict future shoreline change by exploring historical data. The performance of these models can be further improved when more data sets become available.

VEdge_Detector: automated coastal vegetation edge detection using a convolutional neural network

ABSTRACT Coastal communities, land covers, and intertidal habitats are vulnerable receptors of erosion, flooding or both in combination. This vulnerability is likely to increase with sea level rise and greater storminess over future decadal-scale time periods. The accurate, rapid, and wide-scale determination of shoreline position, and its migration, is therefore imperative for future coastal risk adaptation and management. This paper develops and applies an automated tool, VEdge_Detector, to extract the coastal vegetation line from high spatial resolution (Planet’s 3 to 5 m) remote-sensing imagery, training a very deep convolutional neural network (holistically nested edge detection), to predict sequential vegetation line locations on annual to decadal timescales. Red, green, and near-infrared (RG-NIR) was found to be the optimum image spectral band combination during neural network training and validation. The VEdge_Detector outputs were compared with vegetation lines derived from ground-referenced positional measurements and manually digitized aerial photographs, which were used to ascertain a mean distance error of <6 m (two image pixels) and >84% producer accuracy (P A) at six out of the seven sites. Extracting vegetation lines from Planet imagery of the rapidly retreating cliffed coastline at Covehithe, Suffolk, United Kingdom, has identified a landward retreat rate >3 m year−1 (2010–2020). Plausible vegetation lines were successfully retrieved from images in The Netherlands and Australia, which were not used to train the neural network, although significant areas of exposed rocky coastline proved to be less well recovered by VEdge_Detector. The method therefore promises the possibility of generalizing to estimate retreat of sandy coastlines from Planet imagery in otherwise data-poor areas, which lack ground-referenced measurements. Vegetation line outputs derived from VEdge_Detector are produced rapidly and efficiently compared to more traditional non-automated methods. These outputs also have the potential to inform upon a range of future coastal risk management decisions, incorporating future shoreline change.

Mapping the Shoreface of Coastal Sediment Compartments to Improve Shoreline Change Forecasts in New South Wales, Australia

The potential response of shoreface depositional environments to sea level rise over the present century and beyond remains poorly understood. The shoreface is shaped by wave action across a sedimentary seabed and may aggrade or deflate depending on the balance between time-averaged wave energy and the availability and character of sediment, within the context of the inherited geological control. For embayed and accommodation-dominated coastal settings, where shoreline change is particularly sensitive to cross-shore sediment transport, whether the shoreface is a source or sink for coastal sediment during rising sea level may be a crucial determinant of future shoreline change. While simple equilibrium-based models (e.g. the Bruun Rule) are widely used in coastal risk planning practice to predict shoreline change due to sea level rise, the relevance of fundamental model assumptions to the shoreface depositional setting is often overlooked due to limited knowledge about the geomorphology of the nearshore seabed. We present high-resolution mapping of the shoreface-inner shelf in southeastern Australia from airborne lidar and vessel-based multibeam echosounder surveys, which reveals a more complex seabed than was previously known. The mapping data are used to interpret the extent, depositional character and morphodynamic state of the shoreface, by comparing the observed geomorphology to theoretical predictions from wave-driven sediment transport theory. The benefits of high-resolution seabed mapping for improving shoreline change predictions in practice are explored by comparing idealised shoreline change modelling based on our understanding of shoreface geomorphology and morphodynamics before and after the mapping exercise.

Beach nourishment versus sea level rise on Florida’s coasts

Beach nourishment and sea level rise will dominate future shoreline changes on Florida’s 665 miles of sandy coast. Shoreline changes from 2020-2100 are projected along this entire coast using equilibrium profile theory that accurately predicted shoreline changes on Florida’s east coast from 1970-2017 (Houston 2019). Projections for 2020- 2100 are made assuming past rates of beach nourishment for the 30-yr period from 1988-2017 will continue and sea level will rise according to recent projections of the Intergovernmental Panel on Climate Change (IPCC) that include the latest knowledge on ice melting in Antarctica (IPCC 2019). Using the beach nourishment and sea level rise data, equilibrium profile theory is then used to predict shoreline change from 2020-2100 for each IPCC sea level rise projection. Beach nourishment is shown to produce shoreline advance seaward on average for all IPCC scenarios for both the entire Florida coast and east coast and for all scenarios except the upper confidence level of the worst scenario for the southwest and Panhandle coasts. Some of the 30 counties on these coasts will require a greater rate of nourishment than in the past to offset sea level rise for some or all of the scenarios, whereas some will offset sea level rise for all scenarios with lower nourishment rates than in the past. The annual beach nourishment volume for which a county has a shortfall or surplus in offsetting sea level rise for each IPCC scenario can be calculated with the information provided and examples are presented. The approach can be used on coasts outside Florida if beach nourishment and sea level rise are expected to dominate future shoreline change.

Holocene paleoshoreline changes of the Red River Delta, Vietnam

The Red River Delta (RRD), one of the two largest deltas in Vietnam, has been severely affected by natural hazards induced by global climate change. Understanding the Holocene paleoshoreline is crucial in developing adaptive planning in response to future shoreline changes based on past natural shoreline changes. This study presents new data pertaining to pollen, grain size, lithological characteristics, and 14C dating of six cores from the RRD. The purpose of this study was to determine the paleoenvironments and paleoshorelines of the RRD in the Holocene to provide information useful for modeling future changes, e.g., for calibration sea level in paleobathymetry and sea level change models; for making the necessary ecological and cultural adaption to survive. We identified 4 units and 10 sedimentary facies indicating periods of sedimentary evolution since late Pleistocene. The main indicators for paleoshoreline interpretation are true mangrove and backmangrove pollen. The inferred paleoshoreline changes and five paleogeographic maps for 10.5, 9.2, 7.8, 6.5, and 3.7 cal. kyr BP were constructed based on paleoshoreline indicators, and paleoenvironmental reconstructions from the dataset of our whole RRD study area.

Documenting a Century of Coastline Change along Central California and Associated Challenges: From the Qualitative to the Quantitative

Wave erosion has moved coastal cliffs and bluffs landward over the centuries. Now climate change-induced sea-level rise (SLR) and the changes in wave action are accelerating coastline retreat around the world. Documenting the erosion of cliffed coasts and projecting the rate of coastline retreat under future SLR scenarios are more challenging than historical and future shoreline change studies along low-lying sandy beaches. The objective of this research was to study coastal erosion of the West Cliff Drive area in Santa Cruz along the Central California Coast and identify the challenges in coastline change analysis. We investigated the geological history, geomorphic differences, and documented cliff retreat to assess coastal erosion qualitatively. We also conducted a quantitative assessment of cliff retreat through extracting and analyzing the coastline position at three different times (1953, 1975, and 2018). The results showed that the total retreat of the West Cliff Drive coastline over 65 years ranges from 0.3 to 32 m, and the maximum cliff retreat rate was 0.5 m/year. Geometric errors, the complex profiles of coastal cliffs, and irregularities in the processes of coastal erosion, including the undercutting of the base of the cliff and formation of caves, were some of the identified challenges in documenting historical coastline retreat. These can each increase the uncertainty of calculated retreat rates. Reducing the uncertainties in retreat rates is an essential initial step in projecting cliff and bluff retreat under future SLR more accurately and in developing a practical adaptive management plan to cope with the impacts of coastline change along this highly populated edge.

COUNTERMEASURE AGAINST EROSION BEHIND SUBMERGED BREAKWATER DUE TO SEA LEVEL RISE

Submerged breakwaters are considered to be preferable countermeasures against beach erosion where the availability of sediments for nourishment is limited and tourism is prevalent because submerged breakwaters do not interfere with the view of the horizon from the shore. However, sandy beaches protected by submerged breakwaters are assumed to be vulnerable to relative sea level rise (SLR) and land subsidence because the crests of submerged breakwaters are below sea level. Kuriyama and Banno (2016) numerically predicted the future shoreline change under SLR and land subsidence on the Niigata West coast in Japan, which is protected by submerged breakwaters. The prediction showed that the shoreline will retreat 60 m over the next 100 years. In this study, we investigated the effects of countermeasures against the erosion due to SLR and land subsidence.

Changes in the shoreline at Paradip Port, India in response to climate change

One of the popular methods to predict shoreline shifts into the future involves use of a shoreline evolution model driven by the historical wave climate. It is however understood by now that historical wave conditions might substantially change in future in response to climate change induced by the global warming. The future shoreline changes as well as sediment transport therefore need to be determined with the help of future projections of wave climate. In this work this is done at the port of Paradip situated along the east coast of India. The high resolution wind resulting from a climate modelling experiment called: CORDEX, South Asia, was used to simulate waves over two time-slices of 25years each in past and future. The wave simulations were carried out with the help of a numerical wave model. Thereafter, rates of longshore sediment transport as well as shoreline shifts were determined over past and future using a numerical shoreline model. It was found that at Paradip Port the net littoral drift per metre width of cross-shore might go up by 37% and so also the net accumulated drift over the entire cross-shore width by 71%. This could be caused by an increase in the mean significant wave height of around 32% and also by changes in the frequency and direction of waves. The intensification of waves in turn might result from an increase in the mean wind speed of around 19%. Similarly, the horizontal extent of the beach accretion and erosion at the port's southern breakwater might go up by 4m and 8m, respectively, from the current level in another 25years. This study should be useful in framing future port management strategies.