Prediction of Shoreline Recession Using Geospatial Technology: A Case Study of Chennai Coast, Tamil Nadu, India

被引:26
|
作者
Dar, Imran A. [1 ]
Dar, Mithas A. [1 ]
机构
[1] Tamil Univ, Dept Ind & Earth Sci, Thanjavur 603001, Tamil Nadu, India
关键词
Erosion prediction; coastline; sea-level rise; shoreline evolution; SEA-LEVEL RISE; SOFT ROCK SHORES; EROSION; REGION; BEACH;
D O I
10.2112/JCOASTRES-D-09-00051.1
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This study quantifies the erosion of the Chennai coast in India and predicts how the shoreline will recede in the future. Previous studies in this region have reported erosion rates varying anywhere from 2 to 8 m/y. Such a high level of inconsistency in reported rates has hindered effective and sustainable coastal management. The research reported in this paper addresses this issue, using mapping data from 1904, 1974, 1996, and 2002 to estimate, by linear regression, the shoreline recession. The 10 km stretch of coast N of the fishing port at Chennai is repeatedly threatened during the NE monsoon, and as the process continues, the existence of a vital road link (the east-coast highway) is challenged by the fury of the waves. It is estimated that 260 ha of land has been lost between 1893 and 1955 and that 30 ha was destroyed by the sea between 1980 and 1989. Overall loss between 1893 and 1989 has been estimated in the order of 350 ha. The cost of land alone lost to the sea is in the order of US$40 million. The N Chennai coast has thus become volatile and is in need of immediate relief measures for the upkeep of the coastal region. Predictions for the next 250 years were then undertaken using a variety of techniques ranging from a process-based numerical model (Soft Cliff And Platform Erosion) to geometric approaches (including historical-trend analysis, the modified Bruun model, and Sunamura's shore platform model. The mean historic rate of erosion in the Chennai region is 1.11 m/y (+/- 0.15 m/y), significantly less than previously reported, though still very high. Subsequent predictions were used to identify a series of significant economic, ecological, and social features at risk, and to estimate when they will be lost to erosion if left unprotected.
引用
收藏
页码:1276 / 1286
页数:11
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