We define the observed shoreline retreat in semi-arid urban coasts as the sum of shoreline retreat due to (1) coastal erosion resulting from sediment imbalance [32], and (2) coastal erosion resulting from sea-level rise caused by direct submersion [8, 33, 34], as described in the Supplementary Data, Section 2. We describe herein the results associated with measuring each of the above components of total shoreline retreat, and their dependency on land coverage, and finally forecast the total observed shoreline retreat up to 2100 at both sites along with its implications on current beach nourishment costs.
2.1 Total observed shoreline retreat
The temporal shoreline evolution monitored by diachronic airborne and orbital scenes for our two sites reveal rapidly changing coastal areas for both SC and HAM as shown in Supplementary Data Fig. S1 (a)(b). The Digital Shoreline Analysis System (DSAS) method allows the detailed assessment of non-linear shoreline change over the medium-term temporal monitoring periods of 1992-2005 and 2018, especially for coastal erosion hot spots, as defined by [4]. We classify observed erosion rates according to the classes of shoreline trends established by [19]. In Table 1, we observe an overall pattern of erosion (-0.5 to -1 m/yr) to severe erosion (-3 to -5 m/yr) that is prevalent throughout the two studied areas (Fig. 1(a)(b)).
Table 1
The shoreline evolution analysis at the study area beaches. the net shoreline movement (NSM) & the End-Point Rate (EPR) during the 1992-2018 period. negative values indicate erosion. accretion (> 0.5 m/yr), stable (0.5 to -0.5 m/yr), erosion (-1 to -0.5 m/yr), intense erosion (-1 to -3 m/yr), severe erosion (-3 to -5 m/yr) and extreme erosion (>5 m/yr) [54].
Study site
(Coast lenght)
|
Period
|
Max EPR (m/yr)
|
Min EPR (m/yr)
|
Average EPR (m/yr)
|
Error
EPR
(m/yr)
|
Max NSM (m)
|
Min NSM (m)
|
Average NSM
(m)
|
Error
MSN
(m)
|
Corona del Mar
(500 m)
|
1992-2018
|
-0.83
|
0.35
|
-0.25
|
0.22
|
-21.64
|
9
|
-6.43
|
5.7
|
1992-2005
|
-1.24
|
0.5
|
-0.36
|
0.18
|
-16.14
|
6.5
|
-4.84
|
2.3
|
2005-2018
|
-0.75
|
0.27
|
-0.16
|
0.12
|
-9.8
|
3.5
|
-2.06
|
1.5
|
Northern Hammamet
(500 m)
|
1992-2018
|
-3.61
|
-0.81
|
-2.45
|
0.25
|
-93.48
|
-20.97
|
-63.63
|
6.5
|
1992-2005
|
-4.34
|
-1.21
|
-3.03
|
0.3
|
-56.45
|
-15.78
|
-39.33
|
3.9
|
2005-2018
|
-4.49
|
-0.21
|
-1.88
|
0.18
|
-58.35
|
-2.77
|
-24.43
|
2.3
|
The change in shoreline retreats rates for the Corona del Mar State Beach in Southern California and the Hammamet North beach in Tunisia clearly show the erosion-dominated shoreline trend. For areas with the highest erosion rate, sandy beaches show severe retreat as shown in Fig. 1 (a)(b), with maximum Net Shoreline Movement (NSM) shoreline retreat rates over the last three decades (1992-2018) that exceed -35 m at the Corona del Mar State Beach and -90 m at Hammamet North beach, in urbanized areas.
For the End-Point Rate (EPR) of shoreline change of the Southern Californian beach, the medium-term assessment of the shoreline in the modern period (1992-2018) shows a variable small retreat range of -0.36 ± 0.18 m/yr over the period of 1992 to 2005. These changes are mostly attributed to natural coastal hazards such as the strong El Niño and flooding events. The Southern California coast shows maximum EPR of retreat by -0.75 m/yr (± 0.1) during the modern period from 2005 to 2018 (Table 1).
Even though the observed maximum EPR rate falls under the erosion rate (-0.5 m/yr), it is identified as a hot spot of shoreline retreat by the GSAM [4] where transects suggest erosive change rates greater than -0.5 m/yr over the decadal period of 1984-2016 for multi-kilometer-long sandy beaches using the automated analysis of orbital photogrammetric scenes.
Orbital time-lapse photogrammetric observations confirm the occurrence of alarming rates of shoreline retreat along the sandy coast of the northern bay of the Gulf of Hammamet [5].
This area is presently eroding at higher rates with maximum NSM losses of -93.48 m (± 6.5) and with maximum EPR ranges between -4.49 m/yr to -0.21 m/yr (± 0.18) over the last few decades (1992-2018) as shown in Table 1 and Fig. 1 (b).
Naturally, during the short-term period (i.e., inter-annual scale), the swash-aligned beaches move under seasonal storm surge variability along the cross-shore profile. During the summer period, the seaward sandbank features feed the shoreline via the cross-shore currents. Sediments are also driven by the longshore current from the neighboring sediment cell. The construction of harbors disturbs the longshore drift, resulting in a sediment budget deficit at the beach face. Moreover, urban construction disturbs the natural accretion/erosion equilibrium state of the coast and hence the erosion trends persist (Table 1, Fig. 1(b)).
Sandy beaches undergo non-linear evolution that is governed by the coastline’s physical characteristics, such as its hydrodynamic conditions, near-shore bathymetry, near-shore orientations of its currents, and geological setting [35, 36]. As coastal sediments for both headland-coast and embayed beaches are provided by fluvial sedimentation from several local drainage networks (Supplementary Data, Fig. S1 (a)(b)), the build-up of dams since the early to mid- century has considerably reduced natural sediment discharge to the coast, resulting in a sediment budget imbalance that causes the observed shoreline retreat [37].
Similarly, erosion problems along Southern California beaches can be directly attributed to the damming and flood control measures of many local rivers, which resulted in cutting off the sand supply to the beaches [28, 38]. Additionally, the construction of dike harbor infrastructure on both the Hammamet Bay and Southern California shores disturbs longshore drift, leading to a sediment budget deficit at their beaches. Hence, the response of shoreline evolution to such anthropogenic structures is clearly expressed by severe erosion during the modern period (1992-2018) [5].
The small study area of the Corona del Mar’s pocket beach spans along the San Pedro beach compartment and Laguna littoral sub-cell, where ~59% of the sediment budget is supplied by anthropogenic beach nourishment [39]. The Santa Ana and San Gabriel Rivers provide the total budget replenishment of natural sand for the coast. Damming in recent decades has obstructed sand transport to the beaches in Southern California by 47% from the total natural fluvial sand yield, estimated at nearly 1.5 million cubic meters of sand annually [39]. Sea cliff armoring reduces the sand supplied to Southern California’s beaches by another 10% of the natural sand supply, accounting for more than 26,750 cubic meters annually, which represents less than 7% of the total sand input [39].
Sediments flowing from the two major drainages of the Santa Ana and the San Gabriel Rivers, which both cross the mesa in the southwestern part of the Newport Bay estuary area (Supplementary Data, Fig. S1 (a)), formed the beaches, sandbars, and mudflats of the coastline of our study area. These lowlands and saltmarsh areas were significantly altered during the last century in order to deepen navigation maritime routes and to form habitable urban artificial islands [40].
The coastal substratum of both the Southern California and Hammamet areas expose several faults classified as seismically active with significant late Quaternary deformation. For instance, Tunisian coastal ridges are subject to subsidence phenomena and estimated by tide-gauge records to be 5.7 mm/yr [26], compared to 3 mm/yr in Southern California [41]. Several areas of Newport Beach are also vulnerable to liquefaction and related ground failures caused by seismically induced settlement. Such areas along the Southern California coastline include the Balboa Peninsula and the surroundings of both the Newport and Upper Newport Bays, all in the lower discharging parts of major streams in Newport Beach, and in the floodplain of the Santa Ana River [29]. The extensive coastal upland at the southern margin of the Los Angeles Basin has been deeply dissected by stream erosion, resulting in moderate to steep cliffs along the Upper Newport Bay. Newport Bay estuary is also considered as the one of the most biologically diverse and natural protected marine areas in southern California with major significance Grunion Pleistocene fish reproduction.
Decadal-scale coastal cliff erosion observed along the California-Mexico beaches from the period of 1930 to 2010 suggests that unconsolidated cliffs of friable materials fronted by sandy beaches retreated and eroded ~49% more than those without beaches [30]. Naturally, sandy beaches would protect cliffs against wave-driven erosion, but as the beaches are continuously thinning, the sea waves are directly hitting the cliff base during storms and daily tide fluctuations, triggering erosion. Changes in precipitation and periods of drought in semi-arid regions also destabilize the coarse-grained substratum of cliffs that have friable materials [41]. Shoreline retreat has subsequently threatened the substratum’s geotechnical stability and increased landslide occurrence. For example, the Corona del Mar area is located on the recent (1998 to 2009-2010) hot spot for cliff retreat, with a net cliff face retreat of -0.042 m/yr (mean range) and cliff top retreat rates with a mean of -0.12 m/yr [30]. Our study over the same period between 1992 to 2005 shows an erosion rate for the sandy beach with an average NSM rate of -4.84 m (± 2.3) (Table 1, Fig. 1(a)).
2.2 Shoreline retreat from Sea Level Rise
We use the common Bruun rule [8] to calculate Shoreline Retreat Rate (SRR) associated with coastal submersion from sea-level rise (SLR) from 1906 and 1925 to 2020 for our two study sites based on the nearshore morphology and physical parameters as described in section 2 of the supplementary data. The calculated values are listed in Supplementary Data: Table S2. As expected, the SLR values calculated from the Bruun formula are clearly inferior to the observed ones, as they do not account for the contribution of coastal erosion processes to the observed SRR. We note that the SRR in Corona del Mar is calculated at -0.67 m/yr in 2020 from the Bruun approach, whereas the observed SRR from DSAS is about -0.83 m/yr (Fig. 2). For the North African coast of HAM, the Bruun rule indicates an SRR of -1.4 m/yr caused by SLR, while the observed SRR is at -2.45 m/yr using the DSAS approach (Supplementary Data: Table S2). The observed shoreline rate (DSAS) which takes into account the sand supply imbalance and the beach face topography is clearly higher than the Brunn calculation by 12–19% in Orange County (OC) in Southern California and by 75–43% in HAM, respectively, in 1992 to 2020 as shown in Figure 2. This suggests that coastal erosion is rapidly growing along urban semi-arid areas, as the sediment imbalance is becoming more prominent due to the abrupt change in land coverage as well as the increase of aridification.
2.3 Decadal changes in land-use occupation
As stated in section 3 of the Supplementary Data, our supervised classification aiming to quantify coastal sediment transport contains five classes: (1) continental water bodies, (2) bare soils, (3) vegetation, (4) urban spaces and (5) sandy deposits as shown in Figure 2. Two supervised-scene classifications of orbital images from Landsat 1985 and 2015 provide land-cover classification of Orange County (OC) in Southern California (Fig. 3 (a)) and of the Hammamet (HAM) (Fig. 3 (b)) littorals and the temporal evolution of land-use and occupation class statistics (Fig. 4 (a) (b)). To corollate physical, environmental, and social variables with the landscape attributes and composition, we use a confusion matrix in post-classification algorithms in ENVI.
Evaluation of classification results for the two orbital scene sets from the confusion matrices indicate that the Kappa indices are 0.89 to 0.93 for Landsat 5 scenes (acquired in 1985) and 0.94 to 0.95 for Landsat 8 scenes (acquired in 2015) for OC and HAM respectively. The accuracy of both land-use maps is ~98% to ~96% respectively, suggesting a high confidence in our terrain classifications approach.
Spatial land-use occupation reveals that the vegetation and urban space classes covers the major space as it occupies more than 95% and 91% of the total areas, while the continental water, bare soil (i.e., bright areas) and sand deposits classes represents the smallest proportions under 5 to 9% of the OC and HAM areas respectively.
Figure 3 shows that during the period between 1985 to 2015 over the studied areas, urban sprawl increases along with a recession of vegetation coverage, and fluctuations in classes of continental water bodies, bare soils and sandy deposits.
To assess the land-use and occupancy patterns for different classes, we compare the Landsat dataset between the 1985 and 2015 scenes expressed herein by the statistical diagrams for the two studied areas (Fig. 4). The main changes experienced between 1985 and 2015 over the OC and HAM littoral cells was the decrease in vegetated areas and the significant expansion of the urban ones (Fig. 5). Urban areas doubled in the OC zones during this period, where 61,500 hectares of vegetation were transformed into urban space. HAM exhibits the same alarming changes in landscape over the last 30 years. During this period, 38,837 hectares of vegetation disappeared and were changed into urban areas. However, we also note that the bare soil class reveals an increase of 10% over the HAM littoral cell (Fig. 4). Our results suggest a dramatic recession of vegetation crops by a regression of ~19% to ~18% in the coastal plain in the OC and HAM coastal areas respectively.
The other classes in this case (namely, continental water covering the wetlands, and fresh water and sandy deposits) have not undergone significant modification.
The observed widespread erosion over the OC beaches is associated with energetic wave storms such as El Niño events [28]. Historically, the natural morphodynamic processes of the low sandy barrier and inlets extending into the San Pedro cell show a seasonal migration southward of the source yield (i.e., the river mouth) [42]. At the Laguna sub-cell, the sandy pocket beaches backed by low-cliffs depends on the forcing between wave energy levels and sediment supply from source to sink.
Modern rapid regional urbanization and human infrastructure development have considerably altered the coastal sediment dynamic, and have reduced terrestrial sand yield as shown in Figure 5 (a) and (b).
Rainfall records in Southern California and North African areas also reveal temporal variability. The combined effect of Global warming and anthropogenic drivers provoke rainfall fluctuations, and the periodic occurrence of high temperature increases and intensification of extreme hydrological and surge events, such as droughts, heavy rainfall events, El Niño and medicanes [43].
Southern California is experiencing severe multiyear drought that is unprecedented in its hydroclimatic records due to global warming [44]. The above is leading to long-term increase in aridity conditions that will increase the sediment imbalance at the coast. Hence, the increase in droughts could also increase the coastal vulnerability for the semi-arid regions of southern California due to precipitation deficits and resulting imbalance in the sediment supplied by natural river network to the coastline. Shoreline retreat resulting from anthropogenic trapping of sediments discharges to the coast is identified as the main factor for coastal high vulnerability in arid and semi-arid areas surpassing climate change drivers [45].
2.4 Forecasting shoreline retreat and its impacts
Past and future changes of the Shoreline Retreat Rate (SRR) over the period 1992 to 2100 are illustrated in Figure 6. For the currently measured period, the ratio of the SRR to the Population Density growth Rate (PDR) of the Corona del Mar area is 0.03 and for the HAM the SRR/PDR is ~0.11, meaning that for an increasing rate of population density by 10%, the sandy beach of OC lost 0.40 m/yr and the HAM shoreline retreated by 0.8 m/yr over the last decades. The Foresight scenarios of the SRR and PDR along the SC and HAM coasts reveal significant coastal erosion rates by 2100, especially for the OC beaches that exceed an average of -2 m/yr erosion rate (scenario 2) (Fig. 6(a)) (Supplementary Data: Table 3). The HAM coast reveals an alarming trend with an average SRR projection of -4 m/yr as shown in Figure 6(b). Such shoreline retreat rates are twice higher than the projected values suggested by the GSAM for sandy ambient trend of shoreline change estimated at -29.5 m for the West North America regions under RCP4.5 and RCP8.5 by the years 2100. It is important to note that the GSAM [4] only covered ambient sandy beaches and did not cover the arid or semi-arid ones as in the present study. Our results suggest that semi-arid beaches will be eroding at higher rates than ambient ones.
Beach erosion can result in considerable economic losses to coastal communities. To address the severe sediment deficits along Southern California coasts, federal, state and local authorities have spent over a billion dollars on beach nourishment programs over the past 20 years [47]. For instance, Newport Beach received over 7.64M m3 of sand between 1934 and 1936 and Santa Monica and Venice Beaches in Los Angeles received 21.M m3 of sand between 1947 and 1948 and another 7.64 M m3 of sand in the early 1960s. By contrast, Huntington Beach in Orange Country received ~1B m3 in 1990 [47]. The cumulative cost of beach nourishment since 1964 for the Surfside-Sunset Nourishment Program in Orange County is $3.85M [48]. Although the costs vary from county to county and state to state, an approximate 10-year average is $3.75 M/km (with approximately $4/m3 as expressed in 1996 dollars) for Western/Pacific coastal states [48].
From 1945 to 2002 more than 19M m3 of sand were placed on the San Pedro littoral cell as part of a nourishment program. This nourishment added an average rate of ~305,822 m3/yr to the sand budget of the extensive 24 km of San Pedro public beaches (~3,262 m3/yr/km) [49, 50, 51].
The present study highlights the increasing rate of shoreline retreat along the Orange County littoral cells, including the changing state of the sediment budget of the Corona del Mar pocket beach from stable (< 0.5 m/yr) to erosive change rates (>-0.5 m/yr) over the decadal period of 1984-2016. The overall natural beach nourishment of the Laguna sub-cell beaches is significantly reduced by river damming, the armoring of sea-cliffs, and jetties construction. The artificial nourishment contribution of 4% [36] of this pocket headland beach will not be enough to establish shoreface equilibrium. Scenario 2 provides the best estimate for a realistic average of the SRR for the SC beaches by 2100, with an erosion rate of -2 m/yr over one kilometer of the Corona del Mar State Beach. This rate is four times greater than present measured values. This coastline retreat will require a beach nourishment of 1,223 m3/yr to keep the beach at equilibrium. Considering that the current cost for one cubic meter of sand is averaged at $20 and that the sand cost is continuously rising at rate of ~6%/yr, in 2100 it could reach ~$100 /m3. The Corona del Mar State Beach will then need to be artificially nourished with ~5,000 m3/yr according to our projected erosion rate scenario. The beach nourishment price will be $500k /m3/yr for a total coastline of 1 km.
For the whole San Pedro littoral cell, the current annual sand volume needed for nourishing the sandy beaches is averaged at 305,822 m3/yr [52] considering an SRR of -0.5 m/yr. As this SRR value is expected to quadruple, the total cost for annually nourishing sandy beaches to equilibrium along the whole San Pedro coastline would be ~$122 M/yr.
In future studies, we will automate our approach developed in this study, as shown in Supplementary Data: Fig. S3, to perform a global forecast of SRR for all urban arid and semi-arid sandy beaches using as input the orbital time-lapse photogrammetric scenes of the considered areas.