Rahisha Thottolil, Shreedhara V, K C Gouda
Abstract: Monitoring and prediction of shoreline has a pivotal role in coastal zone management by realizing the durability of the coastal area. The Mangalore coast is known to experience severe soil erosion in some places and it leads to the changes in the shoreline. Therefore, regular monitoring is an essential tool for enriching the spatial database of shore-lines. Predicting the future position of shoreline is also an important fac-tor to support the environmental impact assessment by estimating the rate of change of erosion and accretion of coastal land. Therefore, in this study, a shoreline prediction model was attempted using remote sensing together with Geographical Information System (GIS) and a numerical model for Mangalore region. Nine shoreline maps were delineated be-tween the years from 1982 to 2015 and the analysis of shorelines revealed significant changes in its pattern over a period of 33 years. The rate of change in shoreline is embedded into an End Point Rate (EPR) numerical model and the shoreline of Mangalore has been predicted for the year 2020 and 2030. This model is validated by predicting the past shoreline position and comparing it with the actual position which is observed from the satellite images for the same year. The positional shift and the accuracy of predicted and actual shorelines are estimated by Root Mean Square error (RMSE) method. The study investigated to estimate the quantitative amount of erosion and deposition at the Mangalore coast from the period 2015 to 2020 (short-term) and 2015 to 2030 (long-term). From the results, that the rate of erosion would be about 0.46 Km2, and the net accretion would be 0.33Km2 along the Mangalore coast by the end of 2030. This study aims to utilizes geo-informatic technologies to increase the efficiency of shoreline prediction model along the study sites at Mangalore.
Keywords: Shoreline mapping, Coastal zone, EPR Model, RS & GIS