Landslides are one of the major geo hazards responsible for the huge loss of resources worldwide. Since time immemorial, Nilgiris, a hilly district of Tamil Nadu, has been repeatedly ravaged by landslides. With an aim to develop landslide early warning systems for Nilgiris, the paper develops different models to assess landslide occurrence risk based on daily rainfall forecasts and rainfall thresholds. The paper employs Artificial Neural Networks to predict one day advance rainfall intensity and then assesses the risk of landslide occurrence by comparing it with rainfall thresholds. The data set comprises of daily recorded rainfall intensities at 14 rain gauge stations located in and around Coonoor. The results obtained and sensitivity analysis performed establishes the efficiency and adequacy of rainfall data as a supplement to different meteorological parameters and suitability of artificial neural networks in forecasting rainfall and hence evaluating the risk of landslide occurrence.

Renuga Devi S

Department of Communication Engineering

School of Electronics Engineering

Vellore Campus

Arulmozhivarman P

Department of Instrumentation

School of Electrical Engineering

Venkatesh C

Agarwal P

Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

Daily rainfall forecasting using artificial neural networks for early warning of landslides

2014 International Conference on Advances in Computing, Communications and Informatics (ICACCI)

India is among the top ten countries with the highest percentage of landslide fatalities for the past few years. Intense rainfall during the 2009 monsoon in the hilly district of Nilgiris, in the state of Tamilnadu in India, triggered landslides at more than 300 locations which affected road and rail traffic, destroyed buildings, caused the death of more than 40 people and left hundreds homeless. In this paper, three case histories from Nilgiris district are investigated: the slope failure of a railway track at Aravankadu, failure of retaining walls supporting buildings at Coonoor, failure of the slope and retaining wall along national highway (NH67) at Chinnabikatty. Laboratory investigations are carried out on soil samples collected at these sites. Soils at all the three locations have high fine content and low values of coefficient of permeability. Finite element analyses of all the three case histories were carried out using PLAXIS2D software in order to understand the failure mechanism and contributing factors. Slope stability analysis using strength reduction technique is carried out for the slope at Aravankadu to determine the critical slip surface and factor of safety. Results reveal that the increase in pore pressures led to a reduction in shear strength of the soil and consequently resulted in progressive failure of slope at Aravankadu site. Displacement analysis is carried out for Coonoor and Chinnabikatty sites. The results show that combined effect of surcharge load of building and high pore pressure led to intense shearing behind the retaining walls at Coonoor site. Results indicate occurrence of large displacements along the face and at toe of the slope at Chinnabikatty site. © 2012 Springer Science+Business Media Dordrecht.

Natural Hazards

Investigation on infrastructural damages by rainfall-induced landslides during November 2009 in Nilgiris, India

International Journal of Advances in Scientific Research and Engineering

Comparative Analysis of RCC and Composite Hospital Building Subjected to Seismic Forces by Using National Disaster Management Authority of India Guidelines Comparative Analysis of RCC and Composite Hospital Building Subjected to Seismic Forces by Using National Disaster Management Authority of India Guidelines

Journal of Ecology & Natural Resources

Tourism ‘Vs.’ Ecotourism - People Perception in Upper Nilgiris, Tamil Nadu, India

Water Resources Management

Monthly Rainfall Prediction Using Wavelet Neural Network Analysis

Landslide Science and Practice

Damages to Transport Facilities by Rainfall Induced Landslides During November 2009 in Nilgiris, India

Journal	Data powered by Typeset2014 International Conference on Advances in Computing, Communications and Informatics (ICACCI)
Publisher	Data powered by TypesetIEEE
ISSN	9781479930791
Open Access	0