Abstract
Rainfall induced landslides account for over 200 deaths and loss of over Rs.550 crores annually in Himalaya. Literature suggests sensors based site specific Early Warning System (EWS) to be feasible and economic to curtail losses due to landslides for high risk areas. Area selected for current study is Tangni landslide located in Chamoli district of Uttarakhand state, India due to high anticipated risk to the local community residing nearby. For realization of EWS, a near real time instrumentation setup was installed on the slope. The setup measures pore water pressure, sub-surface deformations, and surface displacements along with rainfall. Regression analysis models are developed using antecedent rainfall and deformation data which are further used to find out thresholds for sensors based on z-scores. In future using the results from the sensors installed in the field and laboratory characterizations, numerical analyses will be applied to develop a process based model.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Rai, P.K., Mohan, K., Kumra, V.K.: Landslide hazard and its mapping using remote sensing and GIS. J. Sci. Res. 58, 1–13 (2014)
Kanungo, D.P., Sharma, S.: Rainfall thresholds for prediction of shallow landslides around Chamoli-Joshimath region, Garhwal Himalayas, India. Landslides 11(4), 629–638 (2014)
Martelloni, G., Segoni, S., Fanti, R., Catani, F.: Rainfall thresholds for the forecasting of landslide occurrence at regional scale. Landslides 9(4), 485–495 (2012)
Chae, B.-G., Kim, M.-I.: Suggestion of a method for landslide early warning using the change in the volumetric water content gradient due to rainfall infiltration. Environ. Earth Sci. 66(7), 1973–1986 (2012)
Brand, E.W., Premchitt, J., Philipson, H.B.: Relationship between rainfall and landslides in Hong Kong. Paper presented at the 4th International Symposium on Landslides, Toronto, Canada (1984)
Baum, R.L., Godt, J.W.: Early warning of rainfall-induced shallow landslides and debris flows in the USA. Landslides 7(3), 259–272 (2010)
Dahal, R.K., Hasegawa, S.: Representative rainfall thresholds for landslides in the Nepal Himalaya. Geomorphology 100(3), 429–443 (2008)
Froehlich, W., Gil, E., Kasza, I., Starkel, L.: Thresholds in the transformation of slopes and river channels in the Darjeeling Himalaya, India. Mt. Res. Dev. 10, 301–312 (1990)
Gasmo, J.M., Rahardjo, H., Leong, E.C.: Infiltration effects on stability of a residual soil slope. Comput. Geotech. 26(2), 145–165 (2000)
Tsaparas, I., Rahardjo, H., Toll, D.G., Leong, E.C.: Controlling parameters for rainfall-induced landslides. Comput. Geotech. 29(1), 1–27 (2002)
Rahardjo, H., Lee, T.T., Leong, E.C., Rezaur, R.B.: Response of a residual soil slope to rainfall. Can. Geotech. J. 42(2), 340–351 (2005)
Rahardjo, H., Leong, E.C., Rezaur, R.B.: Effect of antecedent rainfall on pore water pressure distribution characteristics in residual soil slopes under tropical rainfall. Hydrol. Processes 22(4), 506–523 (2008)
Bonnard, C., Noverraz, F.: Influence of climate change on large landslides: assessment of long-term movements and trends. In: International Conference on Landslides: Causes, Impacts and Countermeasures (No. LMS-CONF-2001-002), pp. 121–138 (2001)
Chaturvedi, P., Jaiswal, B., Sharma, S., Tyagi, N.: Instrumentation Based Dynamics Study of Tangni Landslide near Chamoli, Uttrakhand. IJRAT 2, 127–132 (2014)
Weinberg, S.L., Abramowitz, S.K.: Data Analysis for the Behavioral Sciences Using SPSS. Cambridge University Press, Cambridge (2002)
Intrieri, E., Gigli, G., Mugnai, F., Fanti, R., Casagli, N.: Design and implementation of a landslide early warning system. Eng. Geol. 147, 124–136 (2012)
Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., Witten, I.H.: The WEKA data mining software: an update. SIGKDD Explor. 11(1), 10–18 (2009)
Todorovski, L., Ljubič, P., Džeroski, S.: Inducing Polynomial Equations for Regression, pp. 441–452. Springer, Heidelberg (2004)
Huffman, G.J., Adler, R.F., Bolvin, D.T., Gu, G., Nelkin, E.J., Bowman, K.P., Hong, Y., Stocker, E.F., Wolff, D.B.: The TRMM multi-satellite precipitation analysis: quasi-global, multi-year, combined-sensor precipitation estimates at fine scale. J. Hydrometeor. 8, 38–55 (2007)
Zhu, A.X., Wang, R., Qiao, J., Qin, C.Z., Chen, Y., Liu, J., Zhu, T.: An expert knowledge-based approach to landslide susceptibility mapping using GIS and fuzzy logic. Geomorphology 214, 128–138 (2014)
Hodge, V.J., Austin, J.: A survey of outlier detection methodologies. Artif. Intell. Rev. 22(2), 85–126 (2004)
Acknowledgement
The authors would like to thank Director, DTRL, DRDO and a team of scientists involved in the development of the instrumentation system for development of early warning system for landslide.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Chaturvedi, P., Srivastava, S., Kaur, P.B. (2017). Landslide Early Warning System Development Using Statistical Analysis of Sensors’ Data at Tangni Landslide, Uttarakhand, India. In: Deep, K., et al. Proceedings of Sixth International Conference on Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 547. Springer, Singapore. https://doi.org/10.1007/978-981-10-3325-4_26
Download citation
DOI: https://doi.org/10.1007/978-981-10-3325-4_26
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-3324-7
Online ISBN: 978-981-10-3325-4
eBook Packages: EngineeringEngineering (R0)