Abstract
Debris flows belong to sudden disasters which are difficult to forecast. Thus, a detailed and coherent hazard assessment seems a necessary step to prevent or relieve such disasters and mitigate the risk effectively. Previous researchers have proposed several methods, such as regression analysis, fuzzy mathematics, and artificial neural networks for debris-flow hazard assessment. However, these methods need further improvements to eliminate the high relativity existing in their results. The current study reported a similarity-based debris-flow hazard assessment model to determine hazard levels of debris flow in regions, with steps like determining hazard-level-type regions, selecting environmental factors and calculating the similarities between the assessment-pending regions and assessed hazard-level-type ones. This methodology was then employed to assess the regional debris hazard of Yunnan Province in China as a case study and was verified via comparison with field surveys. As the results indicate, the proposed similarity-based debris-flow risk assessment model is simple and efficient and can improve the comparability and reliability of the assessment to some degree.
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References
Aleotti P, Baldelli P, Polloni G, Puma F (1998) Different approaches to landslide hazard assessment. In: Sivakumar M, Chowdhury RN (ed) Proceedings of the 2nd international conference on environmental management (ICEM2). Elsevier, Wollongong, pp 3–10
Calvo B, Savi F (2009) A real-world application of Monte Carlo procedure for debris flow risk assessment. Comput Geosci 35(5):967–977
Gentile F, Bisantino T, Trisorio LG (2008) Debris-flow risk analysis in south Gargano watersheds (Southern-Italy). Nat Hazards 44(1):1–17
Hu H (2007) Researches on debris flow hazards evaluation indexes system and method in Beijing. China University of Geosciences, Beijing
Hu F, Gao J, Chen Z (2006) The risk evaluation of debris flow. J Catastrophol 21(3):36–41
Huang S, Li G, Chen W (2007) The debris flow risk assessment based on artificial neural network in Panshi city. Shanxi Archit 33(3):1–2
Hürlimann M, Copons R, Altimir J (2006) Detailed debris flow hazard assessment in Andorra: a multidisciplinary approach. Geomorphology 78(3–4):359–372
Kang Z, Li Z, Ma A (2004) Study on debris flow in China. Science Press, Beijing
Kuang L, Xu L, Liu B (2006) Debris flow hazard assessment based on extension method. China Railw Sci 27(5):1–6
Lees B (1996) Neural networks applications in the geosciences: an introduction. Comput Geosci 22:955–957
Li K, Tang C (2007) Progress in research on debris flow hazard assessment. J Catastrophol 22(1):106–111
Li F, Zhou K, Feng S (2005) A similarity calculation strategy based on the statistic of case feature. J Huazhong Univ Sci Technol (Nat Sci Ed) 33(6):80–82
Liang W, Zhuang D, Jiang D, Pan J, Ren H (2012) Assessment of debris flow hazards using a Bayesian network. Geomorphology 171:94–100
Lin J, Chen C, Peng C (2012) Potential hazard analysis and risk assessment of debris flow by fuzzy modeling. Nat Hazards 64:273–282
Liu X, Lei J (2003) A method for assessing regional debris flow risk: an application in Zhaotong of Yunnan province (SW China). Geomorphology 52(3–4):181–191
Liu X, Tang C (1995) Danger assessment on debris flow. Science Press, Beijing
Liu X, Yue ZQI et al (2002) Empirical assessment of debris flow risk on a regional scale in Yunnan Province, southwestern China. Environ Manag 30(2):249–264
Lu Z (2009) Fuzzy terrain expression based on similarity. Popular Sci Technol 2009(4):107–108
MacMillan R, Pettapiece W et al (2000) A generic procedure for automatically segmenting landforms into landform elements using DEMs, heuristic rules and fuzzy logic. Fuzzy Sets Syst 113(1):81–109
Shao S, Wang L (1999) Debris flow simulation and hazard zone mapping in mountainous regions of Beijing. J Beijing For Univ 21(6):9–16
Tang C, Zhu J (2001) Risk assessment of debris flows in Northwest Yunnan using GIS. J Soil Water Conserv 15(6):84–87
Tang C, Zhu J (2003) Research on landslide and debris flow hazards in Yunnan. The Commercial Press, Beijing
UN/ISDR (2004) Living with risk: a global review of disaster reduction initiatives. United Nation Publications, Geneva
Wang M (2000) Neural network-based classification of dangerous degree of debris flow. Hydrogeol Eng Geol 27(2):18–19
Wang M, Jin J, Li L (2002) Application of new projection pursuit method to evaluation of dangerous degree of debris flow. J Soil Water Conserv 16(6):79–81
Wang D, Meng Y, Song W (2009) Analysis of fuzzy similarity-based reasoning method and approximation properties of corresponding fuzzy systems. Chin J Eng Math 26(3):423–430
Wilson RC (2000) Climatic variations in rainfall thresholds for debris-flow activity. In: The EGS Plinius conference, Maratea, Italy, pp 415–442
Zadeh LA (1973) Outline of a new approach to the analysis of complex systems and decision processes. IEEE Trans Syst Man Cybern SMC-3(1):28–44
Zhong D, Wei F, Xie H (1994) Principles and indexes of the regionalization of debris flow danger degree in the upper reaches of Changjiang River. Mountain Res 12(2):78–83
Zhu A (1997) A similarity model for representing soil spatial information. Geoderma 77(2–4):217–242
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This work was supported by the Key Project of Knowledge Innovation Program of the Chinese Academy of Sciences (No. KZCX2-YW-Q03), National Key Technology R&D Program (No. 2008BAK50B06), and National Natural Science Foundation of China (No. 40830741).
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Liu, G., Dai, E., Ge, Q. et al. A similarity-based quantitative model for assessing regional debris-flow hazard. Nat Hazards 69, 295–310 (2013). https://doi.org/10.1007/s11069-013-0709-8
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DOI: https://doi.org/10.1007/s11069-013-0709-8