Changes in the Shoreline Position Caused by Natural Processes for Coastline of Marsa Alam – Hamata, Red Sea, Egypt

doi:10.4236/ijg.2011.24055

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International Journal of Geosciences, 2011, 2, 523-529

doi:10.4236/ijg.2011.24055 Published Online November 2011 (http://www.SciRP.org/journal/ijg)

523

Changes in the Shoreline Position Caused by Natural

Processes for Coastline of Marsa Alam and Hamata,

Red Sea, Egypt

Khalid Dewidar

Department of Envi ron mental Science, Faculty of Science, Mansoura University, New Damietta City, Egypt

E-mail: [email protected]

Received June 17, 2011; revised July 26, 2011; accepted September 3, 2011

Abstract

The probability of storms and ice-drift events and their impact on coasts is expected to increase as result of

climate change. Multi-years shoreline mapping is considered a valuable task for coastal monitoring and as-

sessment. This paper presents shoreline maps illustrating the shoreline erosion accretion pattern in the coastal

area between Marsa Alam and Hamata of Red Sea coastline by using different sources of remote sensing

data. In the present study, Landsat MSS (1972), Landsat TM (1990), Landsat ETM+ (1998, 2000) and Terra

Aster (2007) satellite images were used. In this study, two techniques were used to estimate rate of shoreline

retreat. The first technique is corresponding to the formation of automated shoreline positions and the second

one is for estimating rate of shoreline change based on data of remote sensing applying Digital Shoreline

Analysis System (DSAS) software. In this study, the End Point Rate (EPR) was calculated by dividing the

distance of shoreline movement by the time elapsed between the earliest and latest measurements at each

transect. Alongshore rate changes shows that there are changes of erosion and accretion pattern due to

coastal processes and climate changes.

Keywords: Shoreline Changes, Red Sea, Satellite Images, Climate Changes, Coastal Processes

1. Introduction

The coastal area consists of the interface between land

and sea. It is highly dynamic environment with many

physical processes, such as tidal inundation, sea level

rise and coastal geomorphology. The horizontal position

of the land-water interface is constantly changing with

time as the water level moves up and down. Water level

of the sea fluctuates due to short-term effects of tides as

well as long-term relative sea level changes. It is also,

affected by wind, atmospheric pressure, river discharge,

beach changes, and steric effects due to changing salinity

and temperature of the water body. The Intergovernmen-

tal Panel on Climate Changes (IPCC) Fourth Assessment

Report (AR4) noted that coastal vulnerability assess-

ments still focus mainly on sea level rise, with less atten-

tion to other dimensions of climate change. The impacts

of rising temperatures are most unambiguous, both on

high latitude coasts subject to increased erosion as sea

level rise and permafrost melts and on low latitude coral

reef coasts subject to increased bleaching and mortality.

Also, increased sea surface temperatures due to global

warming may increase the frequency and intensity of

hurricanes [1]. These changes in storm frequency and

their intensity could also change patterns of alongshore

sediment transport. Ashton et al.[2] conducted that rais-

ing sea level not only increases the likelihood of coastal

flooding, but changes the template for waves and tides to

sculpt the coast, which can lead to land loss orders of

magnitude greater than that from direct inundation alone.

Nicholls et al. [3] stated that to better support climate

and coastal management policy development, more inte-

grated assessments of climate change in coastal areas are

required, including the significant non-climate changes.

The Red Sea region has been targeted for massive

tourism development in Egypt. The majority of the re-

sorts were built along a coastal stretch of the Red Sea

with about 50 - 300 m coastal setback depending on the

shoreline conditions. The climate of the Red Sea is equa-

torial, 35˚C - 41˚C in average. Water temperature is 18˚C

- 21˚C in winter and 21˚C - 26˚C in summer. The Red

Sea has relatively little water exchange with the Medi-

KH. DEWIDAR

524

terranean Sea and the Indian Ocean, and is regarded as

an enclosed sea. As a consequence, the salinity is higher

(40% - 41%) than in the open ocean. Red Sea water

flows towards the south as a dense, cool, salty layer. Be-

low the Red Sea water layer resides a relatively stagnant

layer of still denser Red Sea deep water, which is formed

during the winter months in the Gulf of Suez and Gulf of

Aqaba [4]. The thermohaline circulation is modified in

the upper two layers by the action of the wind field and

rotation which help generate a system of gyres, eddies

and boundary currents [5]. The tide is semidiurnal with a

mean tidal range of about 0.8m. Mean sea level shows

seasonal variations about 0.5m higher in winter than in

summer. The prevailing wind is NNW throughout the

year except for occasionally light southeasterly winds in

winter. The surface current is generally weak and varies

greatly in time and space. Waves oriented most of the

time NE-SW [6]. The average annual precipitation rate is

about 17.4 mm. The average evapotranspiration varies

between 8.7 mm/day in winter and 28 mm/day in sum-

mer. There are some projects launched to develop sus-

tainable tourism in the Red Sea region. GEF Project [7]

at Red Sea conducted a number of studies about the natu-

ral resources of the Red Sea and proposed management

guidelines for tourism. UNESCO Project [8] formed an

environmental evaluation of the Red Sea coast between

Wadi El Gemal and Halayeb. This study constructs land

use maps for the area between Wadi El Gamal and Ha-

layeb to help the decision makers for future development

of next generations.

Remote sensing data play a good role in determination

of coastline changes of water bodies; evaluate the coastal

processes, erosion and accretion pattern and study water

geomorphology landforms and sediment concentration,

especially in the last recent decades due to the problem

of global climate change and worsening ecology [9-11].

Remote sensing data has rapid, repetitive, synoptic and

multispectral coverage of the satellites. Various methods

for coastline extraction from optical imagery have been

developed [12-17]. Therefore, it is very essential to un-

derstand the amount of erosion and accretion to conceive

a master plan for socio-economic developments and

proper coastal zone management to utilize the coastal

area optimally. In this context rate of shoreline change

for the study area of Red Sea has been studied in this

paper from 1972 to 2007 using different satellite images.

The outcomes of this paper can be used as baseline in-

formation about the erosion and accretion pattern along

the study area.

2. Study area

The study area shoreline lies between 25˚25′00″N to

24˚20′00″N latitudes and 34˚40′00″E to 35˚20′00″E lon-

gitudes. It covers two stretches from the coastal zone of

Red Sea. The first stretch extends from Sharm Abu Da-

tab to Dream Village resort (Figure 1). The second

stretch extends from Marsa Um Tondoba to Marsa Malk

Figure 1. First stretch study area from Sharm Abu Datab to Dream Village resort showing major geomorphologic units iden-

ified from Terra Aster 2007 and field observations. t

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KH. DEWIDAR

(Figure 2). The length of the study area is about 160 km.

The main geomorphological unit in the study area in-

cludes basements rocks, sabkha, bare soil alluvium de-

posits and mangroves. The area between Marsa Alam

and Hamata are rich in natural attractions, from pristine

coral reefs offshore to wildlife, local communities, plants,

and geology and desert habitats. Wadi Al Gemal is one

of the most active valleys in the central part of the sec-

ond stretch. This natural protectorate is declared by the

Egyptian Governorate in 2003. It located about 40 km to

the south of Marsa Alam town. It is one of the richest

valleys in biodiversity, it is extends about 55 km into the

mountainous hinterland and 15 km into the Red Sea itself.

The coral reefs (Figure 3(a)) occupy the lee side of tidal

flat and the outer part of the subtidal zone. The mangrove

forest acts as a barrier to prevent any terrestrial inputs

reaching the coral communities. This area is away from

the coastal human effects and the direct floods from the

active valleys. The area contains some hotels, resorts,

diving centers. Ababda tribes still inhibited this area

from thousands of years ago. The shore in Abu Ghosoun

is sandy and there are fringing coral reefs, while that of

Wadi Ranga is somewhat rocky with many molluscan

shells of extra-ordinary sizes. Sabkas, massive mangrove

trees and coastal sand dune are found in the Ranga re-

gion (Figure 3(b)).

3. Material and Methods

The team work of field survey is consists of multidisci-

plinary of science was visited the study area two times.

The field survey along the study area is based on the

field observations, Landsat satellite image (true color

composite 321 RGB, scale 1:100000), geological and

topographic maps (scale 1:250000, source EGSMA [18].

In this study, a series of image data were acquired at in-

equitable intervals between 1972 and 2007, i.e., covering

a time span of 35 years at low tide (Table 1). This series

includes five shorelines: 1972, 1990, 1998, 2000 and

2007. The images have been acquired almost in summer

season in good quality, with no effective clouds or sensor

defects such as striping. The study area is encountered in

the MSS, ETM+ and Aster scene (Path/Row 143/38).

All image scenes were subjected to image processing

using Erdas Imagine software version 9.1 [20]. The im-

age data were geometrically rectified to the Universal

Transverse Mercator (UTM) map projection system;

zone 36 north, using a sufficient number of ground control

points evenly distributed within the Aster scene. The im-

age rectification accuracy is less than half pixel. Other

dates of the satellite images were registered to the recti-

fied Aster image of 2007. After that, all image data were

radiometrically calibrated and converted to reflectance

values. The reflectance values of each date were atmos-

pherically corrected by using 6S model [21]. The input

parameters of the 6S model describe the atmospheric

conditions, aerosol model and concentration, target and

sensor altitude, band definitions, definitions of the target

and environment reflectance and latitude and longitude

of the target, and azimuth and zenith angles of the sun

Figure 2. Second stretch study area from Marsa Um Tondoba to Marsa Malik showing major geomorphologic units identi-

fied from Terra Aster 2007 and field observations.

KH. DEWIDAR

526

Figure 3. Photograph showing the submerge d mangrove at Abu Ghosoun area (a). Photograph showing the Sabhka at Marsa

Alam area (b). Photograph showing the accretion of sediments at Hamata beach (c). Photograph showing the erosion of

sediments at Ras Hon Korab beach (d).

Table 1. Satellite sensor, acquired date, spatial resolution, scene centre time and high, low tide predicted at El Quseir station

from Simplified Harmonic Method for windows operating system [19], UK Hydrographic Office.

Statellite sensor Acquired date Spatial resolution (meter) Scene centre time (local time)High tide (local time) Low tide (local time)

Landsat MSS 14/09/1972 57.0 7:38 10:03 am 0.6 m

10:11 pm 0.6 m

03:50 am 0.3 m

03:58 pm 0.3 m

Landsat TM 31/08/1990 28.5 7:26 01:49 am 0.6 m

02:42 pm 0.5 m

08:23 am 0.2 m

08:38 pm 0.3 m

Landsat ETM+ 06/09/1998 14.25 8:55 05:29 am 0.7 m

05:54 pm 0.7 m

11:44 am 0.1 m

11:44 pm 0.1 m

Landsat ETM+ 05/10/2000 14.25 7:55 11:33 am 0.6 m

11:46 pm 0.7 m

05:12 am 0.3 m

05:34 pm 0.4 m

Tera ASTER 24/08/2007 14.25 8:24 04:00 am 0.6 m

04:36 pm 0.6 m

10:23 am 0.1 m

10:37 pm 0.2 m

and sensor. Continental type aerosol was assumed and a

locally measured visibility value for each date was taken

from the stations of the Egyptian Meteorological Author-

ity. The atmospheric corrected data was checked with the

standard spectral reflectance curve of the materials sand,

mud, vegetation and water [22]. The method of checking

the atmospheric data includes creation of reflectance

profiles for each material type (sand, vegetation and wa-

ter) from the corrected image by using the spectral pro-

file module of the ERDAS Imagine software. Using this

module the behavior of each spectral band curve was

graphically checked against the standard one.

In this study, two techniques were used to estimate

rate of shoreline retreat. The first technique is corre-

sponding to the formation of automated shoreline posi-

tions. The second one is for estimating rate of shoreline

change based on end point rate applying Digital Shore-

line Analysis System (DSAS) software. More details

about the automated shoreline extraction techniques are

cited in [16,17].

In this paper a Digital Shoreline Analysis System

(DSAS) version 3.2 programs developed by Thleler et al.

[23] was used to calculate rate of shoreline changes. This

system requires user data to meet specific field require-

ments. In this study the examined two date’s shoreline

positions were prepared for these requirements. Based on

our setting, DSAS program generates 732 transects for

first stretch and 803 transects for second stretch that are

oriented perpendicular to the baseline at a 100 m spacing

alongshore (Figure 1(b) & Figure 2(b)). In this study,

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KH. DEWIDAR

the End Point Rate (EPR) was calculated by dividing the

distance of shoreline movement by the time elapsed

between the earliest and latest measurements at each

transect. These transects span the entire study coastline

from Sharm Abu Datab to Sharm Marsa Malik (~160 km

length). To assess the spatial and temporal migration

trend of shoreline positions a hypothetical baseline was

created from north to south parallel to the present-day

coastline geometry with a position of approximately 2.5

km distance behind. The measured distance between the

fixed baseline point and the shoreline positions generated

by the program provides a reliable record monitoring the

changes of shoreline positions from 1972-1990 and from

1990-2007 at each coastline stretch. This time intervals

(~18 years) was found reasonable to represent the

magnitude of shoreline changes along the study area

4. Results and Discussions

Change in shoreline positions were determined by estab-

lishing a 732 transects for first stretch and 803 transects

for second stretch that are oriented perpendicular to the

baseline at 100 m spacing alongshore by using DSAS

software. The estimated rates of erosion and accretion

along the study area have shown alongshore pattern

changes during the examined time intervals (1972-1990

and 1990-2007). Alongshore pattern along the first

stretch from Abu Datab was changes from accretion to

erosion pattern with rate ranged from 5.5 m to –2.5 m/yr

(Figure 4(a)). The alongshore accretion pattern between

El Phistone resort to Sunset Marsa Alam resort is com-

pletely transformed to erosion pattern during the second

period of time (1990-2007). The alongshore erosion and

accretion pattern was still vulnerable between the Sunset

Marsa Alam and Dream village (Figure 4(a)). These

changes may be attributed to climate changes and coastal

processes with the sea at or near its present level, and

there will be additional responses to relative sea level

changes.

Eric, [24] conducted that the changes in coastal wind

regimes may increase sand blown from hinterland dunes

to beaches, or modify incident wave regimes to increase

Figure 4. Alongshore pattern along the first stretch (a) and the second stretch (b) in UTM map projection (meters).

KH. DEWIDAR

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longshore drifting. At Marsa Um Tondoba the along-

shore pattern was completely changes to erosion with

rates range from –3.7 m/yr to –1.2 m/yr during the pe-

riod of 1990-2007. The alongshore erosion pattern is

completely changes to accretion pattern at 5 km west of

Ras Hon Korab with rate 1.5 m/yr (Figure 4(b)). The

detected pattern of erosion versus the accretion along the

study area reflects the natural process of wave induced

longshore currents and sediment transport. At Hamata

the alongshore pattern is changes to accretion with rate 1

m/yr to 5 m/yr during the period of 1990-2007. During

field survey accretion was detected at many places along

the study area (Figure 3(c)). Decrease in beach width

has also been noticed in some areas (Figure 3(d)). One

of the main evidence to change the alongshore pattern is

mangrove colonies at Abu Ghsoun now is completely

found inside the sea. Pugh et al. [25] stated that Red Sea

coast will be affected by climate changes, through

change wind systems with global warming could led to

upwelling events along the southern eastern part of Red

Sea during the summer. This could increase coral reef

mortality with lowered water temperature and conversely

the increase in upwelled nutrients could increase local

fisheries. Ashton et al. [2] conducted that rising sea level

not only increases the likelihood of coastal flooding, but

changes the template for waves and tides to sculpt the

coast, which can lead to land loss orders of magnitude

greater than that from direct inundation alone. Also, Eric

[24] stated that beaches erode and accrete naturally over

seasonal cycles, driven by fluctuations of wave energy. It

takes many years or longer for a beach to recover from a

large storm event.

5. Conclusions

Shoreline position mapping is very valuable in regards to

climate changes. Based on this study it can be concluded

that remote sensing will be useful for long-term qualita-

tive monitoring of shoreline erosion and accretion pattern

in case lack of field data sources. Alongshore rate

changes shows that there are changes of erosion and ac-

cretion pattern due to coastal processes and climate

changes. The rate of erosion and accretion pattern esti-

mated from this study needs validation based on ground

topographic studies. But the most important things of this

study, it provide the decision makers with base knowl-

edge about the expected impacts of climate changes on

the coastline of southern part of Red Sea, which now

exposed to intensive tourism development. Also, long-

term monitoring in this study was made for success in

future planning and management of the coastal zone. It is

also recommended to invite more researches to study the

impacts of climate changes on the marine environment

especially coral reefs and mangroves. Also, more tide

gauge, wave gauge, marine surveys and satellites altim-

etry measurements should be established for future mo-

nitoring and assessment.

6. Acknowledgements

The author acknowledges the team work of UNSCO pro-

ject and the principle investigator of the project who help

him to purchase the Aster data from USGS Earth Re-

sources Observation and Science (EROS) to complete

this study. Also, Great thanks to Dr Dawn the customer

services of WIST who support me with free scene data

for the study area.

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