A Flood Risk Assessment Based on Maximum Flow Capacity of Canal System

详细信息    查看全文

• 关键词：Flood risk assessment ; Canal system ; Maximum flow problem ; Systems of network flows ; Copula with maximum entropy
• 刊名：Lecture Notes in Computer Science
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：9978
• 期：1
• 页码：136-148
• 全文大小：1,027 KB
• 参考文献：1.Borwein, J., Howlett, P., Piantadosi, J.: Modelling and simulation of seasonal rainfall using the principle of maximum entropy. Entropy 16, 747–769 (2014)MathSciNet CrossRef
  2.Chandran, B.G., Hochbaum, D.S.: A computational study of the pseudoflow and push-relabel algorithms for the maximum flow problem. Oper. Res. 57(2), 358–376 (2009)MathSciNet CrossRef MATH
  3.Fishbain, B., Hochbaum, D.S., Mueller, S.: Competitive Analysis of Minimum-Cut Maximum Flow Algorithms in Vision Problems (2010). arXiv preprint arXiv:​ 1007.​4531
  4.Fishbain, B., Hochbaum, D.S.: Hochbaum’s Pseudo-flow Matlab implementation (2012). http://​riot.​ieor.​berkeley.​edu/​riot/​Applications/​Pseudoflow/​maxflow.​html . Accessed 15 June 2014
  5.Ford Jr., L.R., Fulkerson, D.R.: A simple algorithm for finding maximal network flows and an application to the Hitchcock problem. Can. J. Math. 9, 210–218 (1957)MathSciNet CrossRef MATH
  6.Goldberg, A.V., Tarjan, R.E.: A new approach to the maximum flow problem. J. ACM 35, 921–940 (1988)MathSciNet CrossRef MATH
  7.Hochbaum, D.S.: The pseudoflow algorithm: A new algorithm for the maximum flow problem. Oper. Res. 56(4), 992–1009 (2008)MathSciNet CrossRef MATH
  8.Jaynes, E.T.: Information theory and statistical mechanics. Phys. Rev. 106, 620–630 (1957a)MathSciNet CrossRef MATH
  9.Jaynes, E.T.: Information theory and statistical mechanics II. Phys. Rev. 108, 171–190 (1957b)MathSciNet CrossRef MATH
  10.Joe, H.: Multivariate Models and Dependence Concepts. Chapman & Hall, London (1997)CrossRef MATH
  11.Kuichling, E.: The relation between the rainfall and the discharge of sewers in populous districts. Trans. Am. Soc. Civ. Eng. 20, 1–56 (1889)
  12.King, V., Rao, S., Tarjan, R.: A faster deterministic maximum flow algorithm. J. Algorithms 17(3), 447–474 (1994)MathSciNet CrossRef MATH
  13.McCuen, R.: Hydrologic Analysis and Design, 2nd edn. New Jersey, Prentice-Hall Inc. (1998)
  14.Nelsen, R.B.: An Introduction to Copulas, 2nd edn. Springer, New York (2006)MATH
  15.Poapongsakorn, N., Meethom, P.: Impact of the 2011 Floods, and Flood Management in Thailand. No. DP-2013-34 (2013)
  16.Piantadosi, J., Howlett, P.G., Borwein, J.M.: Copulas with maximum entropy. Optim. Lett. 6, 99–125 (2012)MathSciNet CrossRef MATH
  17.Piantadosi, J., Howlett, P.G., Borwein, J.M., Henstridge, J.: Maximum entropy methods for generating simulated rainfall. Numer. Algebra Control Optim. 2, 233–256 (2012)MathSciNet CrossRef MATH
  18.Schrijver, A.: On the history of the transportation and maximum flow problem. Math. Program. 91, 437–445 (2002)MathSciNet CrossRef MATH
  19.Suppaisarn, C.: Medium and heavy flood management in chao phraya river basin following the royal initiative. In: TRF Seminar (2011)
  20.Sklar, A.: Fonctions de repartition a n dimensions et leurs marges. Publications de lInstitut de Statistique de lUniversite de Paris 8, 229–231 (1959)MathSciNet MATH
  21.Smith, D.K.: Networks and Graphs: Techniques and Computational Methods. Woodhead Publishing Limited, Sawston (2011)
  
• 作者单位：Jirakom Sirisrisakulchai (18)
  Napat Harnpornchai (18)
  Kittawit Autchariyapanitkul (19)
  Songsak Sriboonchitta (18)
  
  18. Faculty of Economics, Chiang Mai University, Chiang Mai, Thailand
  19. Faculty of Economics, Maejo University, Chiang Mai, Thailand
  
• 丛书名：Integrated Uncertainty in Knowledge Modelling and Decision Making
• ISBN：978-3-319-49046-5
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349
• 卷排序：9978

文摘

System analysis of network of flows of water is essential for assessing risk of flooding. The flood risk management generally focuses on the meteorological forecasting together with the operation of hydraulic structure while overlooks the flood incurred by inefficient performance of natural instrument in flood mitigation, namely of canal systems. A new methodology for the risk assessment of flood from the prospect of the capacity of canal system is proposed in this paper. The methodology comprises the modeling of a canal system by a flow network in the graph theory, the formulation for the determination of the system capacity in terms of the maximum flow problem, the treatment of uncertainty using copula couple with maximum entropy models, the definition of flood risk event, and the method of risk assessment. The application of the proposed methodology is illustrated through a numerical example.