Abstract
This paper aims to develop a model for debris flow hazard assessment, since Taiwan is a mountainous country subject to bouts of heavy rainfall during the rainy and typhoon seasons and is thus frequently subject to landslide disasters. The database used is comprised of information from actual cases that occurred in areas of Hualien in eastern Taiwan during 2007 and 2008. The Kalman filter model is utilized to assess the occurrence of debris flows from computed indexes, to verify modeling errors. Comparisons are made between two models to determine which one is better in practical applications. The efficiency of the Kalman filter decision system has been proved, showing smaller average relative error and correspondingly larger ratio of success on debris flow assessment when compared to the neural network model. The relative error is calculated between the differences in the ratio of model outputs and that of actual occurrences. Such an error index can be decreased from 4.65 to 3.39% by introducing the concept of geographic divisions to the Kalman filter model, which demonstrates its ability to forecast the occurrence of debris flows for the coming year.
Similar content being viewed by others
References
Archetti R, Lamberti A (2003) Assessment of risk due to debris flow events. Nat Haz Rev 4(3):115–125
Calvo B, Savi F (2009) A real-world application of Monte Carlo procedure for debris flow risk assessment. Comput Geosci 35(5):967–977
Chang CP (1995) Application of geographic information system in determining potential risk of debris flow. Master thesis, National Cheng Kung University, Taiwan (in Chinese)
Chen KH (2006) The study of using fuzzy theory to the prediction system of debris flow. Master thesis, Feng Chia University, Taiwan (in Chinese)
Chen H, Lee CF (2000) Numerical simulation of debris flows. Can Geotech J 37(1):146–160
Chen SC, Ferng JW, Wang YT, Wu TY, Wang JJ (2008) Assessment of disaster resilience capacity of hillslope communities with high risk for geological hazards. Eng Geol 98(3–4):86–101
Chen SC, Wu CY, Wu TY (2009) Resilient capacity assessment for geological failure areas: examples from communities affected by debris flow disaster. Environ Geol 56(8):1523–1532
Crosta GB, Frattini P (2004) Controls on modern alluvial fan processes in the central Alps, northern Italy. Earth Surf Proc Landfor 29(3):267–293
Hsieh CL, Chiang CH, Chen LJ (1992) Field survey and analysis of debris flow in Hualien and Taitung. J Chinese Soil Water Conserv 23(2):109–122 (in Chinese)
Komma J, Blöschl G, Reszler C (2008) Soil moisture updating by ensemble Kalman filtering in real-time flood forecasting. J Hydrol 357:228–242
Landau ID, Lozano R, M’Saad M (1997) Adaptive control. Springer, Berlin
Lin JW (2001) Adaptive algorithms for the identification of nonlinear structural systems. Dissertation, Columbia University, New York
Lin JW (2011) Neural network model and geographic grouping for risk assessment of debris flow. Int J Phys Sci 6(6):1374–1378
Lin JW, Chen HJ (2009) Repetitive identification of structural systems using a nonlinear model parameter refinement approach. Shock Vibrat 16(3):229–240
Lin ML, Jan SS (1995) A preliminary research of application of geographic information system in determining risk of debris flow. J Chinese Inst Civil Hydraulic Eng 7(4):475–486 (in Chinese)
Liu X, Yue ZQ, Tham LG, Lee CF (2002) Empirical assessment of debris flow risk on a regional scale in Yunnan province, Southwestern China. Environ Manag 30(2):249–264
Rossa A, Liechti K, Zappa M, Bruen M, Germann U, Haase G, Keil C, Krahe P (2011) The COST 731 action: a review on uncertainty propagation in advanced hydro-meteorological forecast systems. Atmos Res 100:150–167
Yu FC, Chen CK (1991) Mechanism and investigation of debris flow. J Chinese Soil Water Conservat 24(1):67–79 (in Chinese)
Acknowledgments
The authors would like to thank the National Science Council of the Republic of China, Taiwan, for their financial support of this research under Contract Nos. NSC 95-2221-E-035-111, NSC 98-2221-E-366-006-MY2, NSC 100-2221-E-022-013-MY2 and NSC 100-2628-E-022-002-MY2.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Lin, JW., Chen, CW. & Peng, CY. Kalman filter decision systems for debris flow hazard assessment. Nat Hazards 60, 1255–1266 (2012). https://doi.org/10.1007/s11069-011-9907-4
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11069-011-9907-4