Trends of Shoreline Position: An Approach to Future Prediction for Balasore Shoreline, Odisha, India


The present study aims to analyze the shift in shoreline due to coastal processes and formulate available for best estimate of future shoreline positions based on precedent shorelines. Information on rates and trends of shoreline change can be used to improve the understanding of the underlying causes and potential effects of coastal erosion which can support informed coastal management decisions. In this paper, researchers go over the changes in the recent positions of the shoreline of the Balasore coast for the 38 years from 1975 through 2013. The study area includes the Balasore coastal region from Rasalpur to Udaypur together with Chandipur, Choumukh, Chandrabali as well as Bichitrapur. Transects wise shoreline data base were developed for approximately 67 kilometers of shoreline and erosional/accretional scenario has also been analysed by delineating the shoreline from Landsat imageries of 1975, 1980, 1990, 1995, 2000, 2005, 2010 and 2013. A simple Linear Regression Model and End Point Rate (EPR) have been adopted to take out the rate of change of shoreline and its future positions, based on empirical observations at 67 transects along the Balasore coast. It is found that the north eastern part of Balasore coast in the vicinity of Subarnarekha estuary and Chandrabali beach undergo high rates of shore line shift. The shoreline data were integrated for long- (about 17 years) and short-term (about 7 years) shift rates analysis to comprehend the shoreline change and prediction. For the prediction of future shoreline, the model has been validated with the present shoreline position (2013). The rate of shoreline movement calculated from the fixed base line to shoreline position of 1975, 1980, 1990, 1995, 2000, 2005 and 2010 and based on this, the estimated shoreline of 2013 was calculated. The estimated shoreline was compared with the actual shoreline delineated from satellite imagery of 2013. The model error or positional shift at each sample point is observed. The positional error varies from ?4.82 m to 212.41 m. It has been found that model prediction error is higher in the left hand side of river Subarnarekha. The overall error for the entire predicted shoreline was found to be 41.88 m by Root Mean Square Error (RMSE). In addition, it was tested by means difference between actual and predicted shoreline positions using “t test and it has been found that predicted shore line is not significantly different from actual shoreline position at (t132 = 0.278) p < 0.01.

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Barman, N. , Chatterjee, S. and Khan, A. (2015) Trends of Shoreline Position: An Approach to Future Prediction for Balasore Shoreline, Odisha, India. Open Journal of Marine Science, 5, 13-25. doi: 10.4236/ojms.2015.51002.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] Lee, J. and Jurkevich, I. (1990) Coastline Detection and Tracing in SAR Images. IEEE Transactions in Geosciences and Remote Sensing, 28, 662-668.
[2] White, K. and El Asmar, H. (1999) Monitoring Changing Position of Coastlines Using Thematic Mapper Imagery, an Example from the Nile Delta. Geomorphology, 29, 93-105.
[3] Bertacchini, E. and Capra, A. (2010) Map Updating and Coastline Control with Very High Resolution Satellite Images: Application to Molise and Puglia Coasts (Italy). Italian Journal of Remote Sensing, 42, 103-115.
[4] Wright, H. and Pilkey, Jr., (1989) The Effect of Hard Stabilization upon Dry Beach Width. Proceedings of Coastal Zone ‘89, American Society of Civil Engineers. 676-790.
[5] Basco, D. (1991) Boundary Conditions and Long Term Shoreline Change Rates for the Southern Virginia Ocean Coastline. Shore and Beach, 59, 8-13.
[6] Paine, J. and Morton, R. (1989) Shoreline and Vegetation Line Movement, Texas Gulf Coast 1974 to 1982. The University of Texas at Austin, Bureau of Economic and Geology and Geological Circular, 89-1. 50.
[7] Siddiqui, M. and Maajid, S. (2004) Monitoring of Geomorphological Changes for Planning Reclamation Work in Coastal Area of Karachi, Pakistan. Advances in Space Research, 33, 1200-1205.
[8] Fenster, M., Dolan, R. and Elder, J. (1993) A New Method for Predicting Shoreline Positions from Historical Data. Journal of Coastal Research, 9, 147-171.
[9] Dolan, R., Fenster, M. and Holmes, S. (1991) Temporal Analysis of Shoreline Recession and Accretion. Journal of Coastal Research, 7, 723-744.
[10] Rissanen, J. (1978) Modeling by Shortest Data Description. Automatica, 14, 465-471.
[11] Douglas, B. and Crowell, M. (2000) Long-Term Shoreline Position Prediction and Error Propagation. Journal of Coastal Research, 16, 145-152.
[12] Maiti, S. and Bhattacharya, A. (2009) Shoreline Change Analysis and Its Application to Prediction: A Remote Sensing and Statistics Based Approach. Marine Geology, 257, 11-23.
[13] Ryu, J., Won, J. and Min, K. (2002) Waterline Extraction from Landsat TM Data in a Tidal Flat: A Case Study in Gosmo Bay, Korea. Remote Sensing of Environment, 83, 442-456.
[14] Eliot, J. and Clarke, D. (1989) Temporal and Spatial Bias in the Estimation of Shoreline Rate-of-Change Statistics from Beach Survey Information. Coastal Management, 17, 129-156.
[15] Li, R., Liu, J. and Felus, Y. (2001) Spatial Modelling and Analysis for Shoreline Change and Coastal Erosion Monitoring. Marine Geodesy, 24, 1-12.
[16] Thieler, E.R., O’Connell, J.F. and Schupp, C.A. (2001) The Massachusetts Shoreline Change Project—1800s to 1994. USGS Administrative Report to the Massachusetts Office of Coastal Zone Management, Boston, 26 p.
[17] Himmelstoss, E.A. (2009) DSAS 4.0—Installation Instructions and User Guide. In: Thieler, E.R., Himmelstoss, E.A., Zichichi, J.L. and Ergul, A., Eds., The Digital Shoreline Analysis System (DSAS) Version 4.0—An ArcGIS Extension for Calculating Shoreline Change: US Geological Survey Open-File Report 2008-1278, ver. 4.2. 81 p.

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