International Journal of Civil Engineering and Technology (IJCIET) Volume 10, Issue 05, May 2019, pp. 75-91, Article ID: IJCIET_10_05_009 Available online at http://iaeme.com/Home/issue/IJCIET?Volume=10&Issue=5 ISSN Print: 0976-6308 and ISSN Online: 0976-6316

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SHORELINE CHANGES USING DIGITIZING OF LANDSAT IMAGES AT TO BEACH, ,

Elbagory, I. A Assistant Doctor, Water and Water Structure Engineering Dept., Faculty of Engineering, Zagazig University, Zagazig, Egypt

Heikal, E. M Professor of Harbors and Marine Structures, Faculty of Engineering, Zagazig University, Zagazig, Egypt.

Koraim, A. S Professor of Harbors and Marine Structures, Faculty of Engineering, Zagazig University, Zagazig, Egypt.

ABSTRACT Alexandria city in Egypt is one of important cities in the Mediterranean coast. Alexandria suffers from many erosion problems along its coastline. The shore line of Alexandria beach was studied using remote senescing and field data. A case study of a submerged breakwater, which was constructed at Alexandria beach to stabilize the eroded beach of Miami - Montaza areas in years 2000 to 2016, is presented. The data of Alexandria beach were provided by Landsat7 satalite and proccseed by software program ERDAS IMAGINE 2013 which gives high resolution of the studied area. Then the shorelines were digitized by using software ARC GIS 10.1. This study introduce the shoreline response due to the construction of the submerged breakwater using the Digital Shoreline Analysis System (DSAS). The analysis shows shoreline accretion along most areas of Miamy - - Mandara - Montaza beach with range from 1 to 20 meter per year. The shoreline erosion exist at eastern part of Asafra beach and western part of Mandara beach with range from -1.5 to -10 meter per year. A beach width varied from 30 to 55 m compared to 0.0 to 25 m before the submerged breakwater. Shoreline change prediction model for coastal zone at Mimi to Montaza beach in years 2020, 2030, and 2050 is estimated according to DSAS settings and Linear regression rate. It was observed that during 2016-2050 the accretion distance along the coastline of Miami to montaza beach was varied between (5- 60) m. Also the predicted shoreline indicates that the erosion will take place in the Montaza beach with distance varied between (20) m.

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KEY WORDS: ARC GIS; Shoreline; submerged breakwaters; sediment transport. Alexandria Cite this Article: Elbagory, I. A, Heikal, E. M and Koraim, A. S, Shoreline Changes Using Digitizing of Landsat Images at Miami to Montaza Beach, Alexandria, Egypt. International Journal of Civil Engineering and Technology, 10(05), 2019, pp. 75-91 http://iaeme.com/Home/issue/IJCIET?Volume=10&Issue=5

1. INTRODUCTION The total length of the Mediterranean sea coastline is about 995 km. the Egyptian northern coast faces a serious problems such as erosion and accretion. The interaction between waves and currents causes the main problem of erosion and accretion [Frihy,1991]. Submerged breakwaters are suggested to control and protect this coastal zone. Miami to Montaza brach in Alexandria city is an example for case study in this research. Change detection is the process of identifying differences in the state of an object as a shoreline by observing it at different periods. Remote sensing has widely been used in environmental change detection studies.ERDAS Imagine software was used to perform image processing of satellite image. In addition image digitizing was applied for delineating the shoreline 46 trend at the study area using the ArcGIS V. 10.1 Software Package.

2. LITERATURE REVIEW

2.1. Description of Alexandria beach Alexandria's beaches are the main summer resort of the country and are considered one of the most notable summer resorts in the Middle East. Alexandria beaches stretch for 140 km along the Mediterranean Sea, from Abu Qir, in the east to Al-Alamein and Sidi Abdul Rahman, in the west as shown in Figure (1). These attributes make Alexandria a favorite tourist spot; more than one million local summer visitors together with about 4.5 million residents enjoy the summer season at Alexandria every year [Frihy et al. , 1996].

Figure: (1). Alexandria map

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2.2. Wave run-up over Alexandria coastline: Soliman and Reeve 2007 studied the phenomenon of wave run-up at Alexandria numerically using the 2-D BWNM to estimate the wave run-up due to wave attack. The section has been chosen as shown in Figure (2). Table (1) presents the estimated horizontal displacement of shoreline due to wave run-up using the numerical simulation. The expected beach width which will be attacked by wave run-up ranges from 9.56 m to 13.83 m and 11.69 m on average.

Figure (2): Section in Miami beach, including water depths, beach width and road details, Soliman and Reeve 2007

Table (1) Average estimated displacement due to wave run-up, Soliman and Reeve 2007

2.3. Miami to Montaza beach This zone is about 3500 meters long from Miami to Montaza beach. This area has suffered severe erosion in 2003 storm. With time, the beach width decreased and vanished in some locations. The waves attacked the road itself after washing all the sand as can be notice from Figure (3). Sub-aerial parallel rubble mound breakwater (4.0 meter above water level) was effective at controlling erosion in Mandara area (from Miamy beach to ). However, it had a quite severe adverse impact on beach amenity and aesthetics. El-Sharnouby, B., & Soliman, A. 2011

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Figure (3) :. Example of flooding at the Alexandrian coastline. [El-Sharnouby, B., & Soliman, A. 2011]. The installation of the emerged breakwater in 2005 led to a rapid deterioration in water quality as can see from Figure (4). [El-Sharnouby, B., & Soliman, A. 2011].

Figure (4): Contamination of water at the leeside of emerged breakwater, Miamy area. [El- Sharnouby, B., & Soliman, A. 2011]

2.4. ALEXANDRIA SUBMERGED BREAKWATER The 2520 meters rubble mound submerged breakwater in Alexandria is considered one of the longest,deepest, and widest submerged breakwaters all over the world (Allsop et al., 2009). A submerged breakwater system was installed to protect the seashore of Miamy - Asafra - Mandara -Montaza areas in Alexandria, Egypt in years 2006 to 2008. The submerged breakwater consists of three segments with two overlaps as shown in Figure (5), [A. Soliman et al, 2014]

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Figure (5): Plan of the submerged breakwater system for Miamy, Asafra, Mandara and Montaza area, [A. Soliman et al, 2014]. El-Sharnouby et al. (2007) gave details of the design procedures, environmental analysis, predicted wave and shoreline response of Alexandria submerged breakwater. The findings of El-Sharnouby et al. (2007) can be summarized as follows: 1. The shoreline is well protected from wave attack providing a width of beach sand not less than 30 meters. 2. Continuous submerged breakwater provides better shoreline stability with a 60% decrease of the total eroded volume. 3. Accretion will take place within 12 months after installation. The depth of water at the breakwater varies from 2.5 to 8.5 meters. Five cross sections at different locations are considered for design according to the depth and wave height. Details of the submerged breakwater cross section at water depths from 3 to 5 meters are shown in Figure (6).

Figure (6): Cross section 1-1 of submerged breakwater at depth 3 to 5 m, [El-Sharnouby et al. (2007)].

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3. SHORELINE ANALYSIS

3.1. Shoreline digitizing Befor constuction of the submerged breakwaters at maimi to montaza beach the shoreline was illustterated as shown in figure (7). The figure shows the photos of digitized shoreline for years from 2000 to 2006 before constuction of the submerged breakwaters. Thos photos taked by Landsat7 satalite and proccseed by software program ERDAS IMAGINE 2013 which gives high resolution of the studied area. Then the shorelines were digitized by using software ARC GIS 10.1. Change in shoreline position were determined by establishing 65 transects along coastline that are oriented perpendicular to the baseline at 50 m spacing alongshore by using DSAS model. The rates of erosion and accretion along the study area are calculated from three statistical approaches of DSAS (End point rate, Linear regression rate, Least median of square).

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Figure (7): the digitized shoreline for years from 2000 to 2006. After constuction of the submerged breakwaters by using proccessing of landsat images as illusteruted before. The shorelines from year 2010 to year 2016 for Miami to Montaza beach were digitizied as shown in figures (8).

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Figure (8): the digitized shoreline for years from 2010 to 2016.

3.2. Analysis of shoreline changes Digital Shoreline Analysis System (DSAS) softwar used to calulate the rate of changes in shoreline using 3 models: a- LRR Model; b- EPR Model ; c- LMS Model. The DSAS application is setup in ARC GIS software backages. The base line and transectes lines are draw to can calculate the rate of changes in shoreline as shown in figure (9) and figure (10). The distances between transects is 50 meter and it cover all distances of shorline and it pripindcular to the base line.

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a- Linear Regression Rate (LRR): A linear regression rate-of-change statistic can be determined by fitting a least-squares regression line to all shoreline points for a particular transect (figure 11). b- End Point Rate (EPR) : The end point rate is calculated by dividing the distance of shoreline movement by the time elapsed between the oldest and the most recent shoreline. c- Least Median of Squares (LMS) : In ordinary and weighted least-squares regression, the best-fit line is placed through the points in such a way as to minimize the sum of the squared residuals. In the least median of squares method the median value of the squared residuals is used instead of the mean to determine the best-fit equation for the line (figure 11); Rousseeuw and Leroy (1987).

Figure (9): digitizing of shorelines from year 2000 to year 2006 fo Maimi to Montaza beach

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Figure (10): digitizing of shorelines from year 2010 to year 2016 fo Maimi to Montaza beach

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Figure (11): comparison between the least median of squares rate and the linear regression rate

4. RESULTS AND DISCUSSION

4.1. Shoreline change along Miami to Montaza beach The rate of changes of the shoreline before construction of the breakwater (from year 2000 to year 2006) is shown in figures (12). The figure shows that the accretion in Miami zone was up to 20 m/year from the base line and about 15 m/year in Mandara area. But in Montaza area the erosin was about 10 m/year.

Figure (12) the rate of changes of shoreline form year 2000 to 2006.

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After construction of the submerged breakwater, the shoreline changed from year 2010 to year 2016 is shown in figures (13). Also the table 2 describes the rate of changes of the shorelines from year 2010 to 2016. The positive sign means accretion and the negative sign means erosion. The figure shows that the accretion in Miami zone was up to 10 m/year from the base line and about 20 m/year in Asafra to Mandara zone. But in Montaza area the erosin was about 40 meter/year.

Figure (13) the rate of changes of shoreline form year 2010 to 2016.

4.2. Comparison between current study and other studies: Figure (14) and table (3) presents a comparison between the present study and A.Soliman et al. ,(2014), for the same study area. The figure shows a reasonable agreement between the present study and A.Soliman et al ,(2014) results. Additionally, the figure shows that the present introduced higher values of value of accretion particularly in Mandara zone than other author for the same studied case.

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Table 2: the rate of changes of shoreline form year 2010 to 2016.

Figure (14): Comparison between current study and A.Soliman et al. ,(2014)

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Table 3: Comparison between current study and A.Soliman et al. ,(2014)

4.3. Prediction Model for Miami to Montaza Beach: The prediction accuracy of shoreline position depends on the pervious data (assumed to be captured by Landsat imagery data). In coastline analysis research, extrapolation of a constant rate of change is the most commonly used method to predict the shoreline. Several methods have been used for prediction of shoreline position as a function of time, rate of erosion and deposition. The most simple and useful ones are the End Point Rate (EPR) and the Linear Regression Rate (LRR) models. In the present study, the LRR model has been adopted to predict the future shoreline. The model is based on the assumption that the observed periodical rate of change of shoreline position is the best estimate for prediction of the future shoreline. The position of the future shoreline for a given data is estimated using the rate of shoreline movement (slope), time interval between observed and predicted shoreline. In that method the regression equation is used to get a relation between the time and distance from the baseline. The regression equation is given by the formula (y = mx + b) where (y) is the distance from the baseline in meters, (x) is the shoreline date, (m) is the rate of change given from DSAS for

http://iaeme.com/Home/journal/IJCIET 88 [email protected] Shoreline Changes Using Digitizing of Landsat Images at Miami to Montaza Beach, Alexandria, Egypt each transect, (b) is y-intercept (the value of y when x=0) is calculated by the equation [y- intercept (b) = (mean of y) - (mean of x) * m]. Examples of the estimate of the future scenarios that are obtained using the prediction model for all transects lines with continuous accretion and erosion are shown in Table (4) . Also, the estimated position of years 2030and 2050 shorelines presented in figure (15). It was observed that during 2016-2050 the accretion distance along the coastline of Miami to montaza beach was varied between (5- 10) m. Also the predicted shoreline indicates that the erosion will take place in the Asafra beach with very small distance varied between (5) m.

Figure (15): Predicted shorelines 2020, 2030, and 2050

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Table (4): Examples on the future estimates for shoreline retreat.

5. CONCLUSIONS Alexandria beach is one of the most important beaches along the Mediterranean coast, Egypt, Mimi to Montaza beach is a part of Alexandria beach and it faces many erosion and accretion

http://iaeme.com/Home/journal/IJCIET 90 [email protected] Shoreline Changes Using Digitizing of Landsat Images at Miami to Montaza Beach, Alexandria, Egypt problems. Alexandria submerged breakwater was installed to protect the sea shore of Miamy - Asafra -Mandara - Montaza areas in Alexandria, Egypt in years 2006 to 2008. Digitizing of landsat Images for shoreline from year 2000 to year 2016 were processed by the layer stacking function using ERDAS Imagine, 2013 and Geographic Information System (GIS) model. Change in shoreline position were determined by establishing 65 transects along coastline that are oriented perpendicular to the baseline at 50 m spacing alongshore by using DSAS model. The rates of erosion and accretion along the study area are calculated from three statistical approaches of DSAS (End point rate, Linear regression rate, Least median of square). Results showed that that the accretion in Miami zone was up to 10 m/year from the base line and about 5 m/year in Asafra to Mandara zone. But in Montaza area the erosin was about 40 meter/year for period. . Also the predicted shoreline indicates that the erosion will take place in the Montaza beach with distance varied between (10 -20) m/year.

ABBREVIATIONS GIS: Geographic Information System DSAS: Digital Shoreline Analysis System LRR: Linear regression rate EPR :End point rate LMS: Least median of square

REFERENCES

[1] A.Soliman, B. El-sharnouby, and H.Elkamhawy 2014. Shoreline changes due to construction of Alexandria submerged breakwater. Proceeding of 11th International Conference on Hydroscience & Engineering (ICHE2014), Hamburg, Germany.675 - 684 [2] El-Sharnouby, B., and Soliman, A. 2010. Shoreline Response for Long Wide and Deep Submerged Breakwater of Alexandria City, Egypt. Proceeding of 26th International Conference on Seaports and Maritime Transport, Arab Academy for Science, Technology & Maritime Transport, Alexandria, Egypt. [3] El-Sharnouby, B., & Soliman, A. 2011. Behavior of shore protection structures at Alexandria, Egypt, during the storm of December 2010.Proceedings of Coastal Engineering Practice, 780-792. [4] Frihy, O.E., Fanos, M.A., Khafagy, A.A., Komar, P.D., 1991. Nearshore sediment transport patterns along the Nile delta, Egypt. J. Coast. Eng. 15, 409–429. [5] Frihy, O.E., Dewidar, K.M., and El-Raey, M. 1996. Evaluation of coastal problems at Alexandria, Egypt. Journal of Ocean and coastal management, 30 (2-3), 281-295. [6] Frihy, O.E., El-Sayed, M.K., 2012. Vulnerability risk assessment and adaptation to climate change induced sea level rise along the Mediterranean coast of Egypt. Mitigation and Adaptation Strategies for Global Change 1–23. [7] Ranasinghe, R., and Turner, I. L. 2006. Shoreline response to submerged structures: A review. Coastal Engineering, 53, 65-79. [8] Soliman, A., and Reeve, D. 2007. Artificial Submerged Reefs: A solution for Erosion Problems along Alexandria Coastline, Egypt?. Proceeding of the IMA 2nd Conference on Flood Risk Assessment, Plymouth, UK, 41-50. [9] Quelennec, R.E., Manohar, M., 1977. Numerical wave refraction and computer estimation of littoral drift, application to the Nile delta coast. Proceedings UNESCO Seminar on Nile Delta Coastal Processes, Alexandria. Acad. Sci. Res. Techn., Alexandria, pp. 404–433.

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