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Evaluation of Moisture Level Using Precipitation Indices as a Landslide Triggering Factor—A Study of Coonoor Hill Station

Centre for Advanced Research in Environment, School of Civil Engineering, SASTRA University, Thanjavur 613 401, India
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Climate 2019, 7(9), 111; https://doi.org/10.3390/cli7090111
Received: 27 July 2019 / Revised: 20 August 2019 / Accepted: 11 September 2019 / Published: 13 September 2019
Extreme heavy rainfall events in the hilly region pose a great threat to public safety and causes dangerous landslides in the region. Several factors contribute to a landslide and, hence, it is essential to analyze the causes of such related incidents in all possible ways. Though rainfall is the major triggering factor for most of the landslides in the Western Ghats, the long period antecedent moisture level prevailing in the soil of a hilly terrain cannot be ignored. Few of the drought assessing and monitoring indices available in literature can be adopted to predict the degree of wetness from long-term precipitation data of the region. In the present work, three moisture level assessment indices, namely, standardized precipitation index (SPI), China Z-index (CZI), and statistical Z-Score (SZS) index are used to categorize the antecedent moisture level of Coonoor station. Monthly rainfall data for a period of 81 years is used for the study. It is evident from the study that higher level of moisture followed by heavy rainfall triggers medium- to large-scale landslides. Further, from the study it is inferred that an early warning for a landslide can be given once cumulative rainfall exceeds 300 mm during continuous storm periods. View Full-Text
Keywords: rainfall; landslide; moisture; standardized precipitation index (SPI); China Z-index; statistical Z-score rainfall; landslide; moisture; standardized precipitation index (SPI); China Z-index; statistical Z-score
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Suribabu, C.R.; Sujatha, E.R. Evaluation of Moisture Level Using Precipitation Indices as a Landslide Triggering Factor—A Study of Coonoor Hill Station. Climate 2019, 7, 111.

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