Natural Hazards

, Volume 84, Issue 3, pp 2071–2093 | Cite as

A cascading flash flood guidance system: development and application in Yunnan Province, China

  • Ziyue Zeng
  • Guoqiang Tang
  • Di LongEmail author
  • Chao Zeng
  • Meihong Ma
  • Yang HongEmail author
  • Hui Xu
  • Jing Xu
Original Paper


Yunnan Province, located in Southwest China, suffers from massive flash flood hazards due to its complex mountainous hydrometeorology. However, traditional flash flood forecasting approaches can hardly provide an effective and comprehensive guide. Aiming to build a multilevel guidance system of flash flood warning for Yunnan, this study develops a Cascading Flash Flood Guidance (CFFG) system, progressively from the Flash Flood Potential Index (FFPI), the Flash Flood Hazard Index (FFHI) to the Flash Flood Risk Index (FFRI). First, land cover and vegetation cover data from MODIS products, the Harmonized World Soil Database soil map, and SRTM slope data are used in generating a composite FFPI map. In this process, an integrated approach of the analytic hierarchy process and the information entropy theory is used as a weighting method. Then, three standardized rainfall amounts (average daily amount in flood seasons, maximum 6 h and maximum 24 h amount) are added to derive FFHI. Further inclusion of GDP, population and flood prevention measures as vulnerability factors for the FFRI enabled prediction of the flash flood risk. The spatial patterns of the CFFG indices indicate that counties in east Yunnan are most susceptible to flash floods, which agrees with the distribution of observed flash flood events. Compared to other approaches, the CFFG system could be a useful prototype in mapping characteristics of China’s flash floods in a cascading manner (i.e., potential, hazard and risk) for users at different administrative levels (e.g., town, county, province and even nation).


Flash flood forecasting Cascading flash flood guidance system Flash Flood Potential Index Flash Flood Hazard Index Flash Flood Risk Index 



This study is partially supported by technical service projects of the China Meteorological Administration, “Technical Research on Meteorological Risk Warning of Flash Floods” (Grant Number: 20142661168) and “Development and Transformation of a Multi-scale Meteorological Disaster Chain Forecasting Model in China” (Grant Number: 20151451484).


  1. Adger V (2006) Vulnerability. Glob Environ Change 16:268–281CrossRefGoogle Scholar
  2. Boyle DP (2001) Multicriteria calibration of hydrologic models. Dissertation, Department of Hydrology and Water Resources, University of ArizonaGoogle Scholar
  3. Brans JP, Vincke P, Mareschal B (1986) How to select and how to rank projects: the PROMETHEE method. Eur J Oper Res 24(2):228–238. doi: 10.1016/0377-2217(86)90044-5 CrossRefGoogle Scholar
  4. Brooks N (2003) Vulnerability, risk and adaptation: a conceptual framework. Tyndall Centre for Climate Change Research Working Paper 38:1–16Google Scholar
  5. Büchele B, Kreibich H, Kron A, Thieken A, Ihringer J, Oberle P, Nestmann F (2006) Flood-risk mapping: contributions towards an enhanced assessment of extreme events and associated risks. Nat Hazards Earth Syst Sci 6(4):485–503. doi: 10.5194/nhess-6-485-2006 CrossRefGoogle Scholar
  6. Bumash RJC, Ferral RL, McGuire RA (1973) A generalized streamflow simulation system-conceptual modeling for digital computers. US Department of Commerce, National Weather Service and State of California, Department of Water ResourcesGoogle Scholar
  7. Chen H, Yang D, Hong Y, Gourley JJ, Zhang Y (2013) Hydrological data assimilation with the ensemble square-root-filter: use of streamflow observations to update model states for real-time flash flood forecasting. Adv Water Resour 59:209–220. doi: 10.1016/j.advwatres.2013.06.010 CrossRefGoogle Scholar
  8. Clark RA, Gourley JJ, Flamig ZL, Hong Y, Clark E (2014) CONUS-wide evaluation of national weather service flash flood guidance products. Weather Forecast 29(2):377–392. doi: 10.1175/WAF-D-12-00124.1 CrossRefGoogle Scholar
  9. Creutin JD, Borga M, Gruntfest E, Lutoff C, Zoccatelli D, Ruin I (2013) A space and time framework for analyzing human anticipation of flash floods. J Hydrol 482:14–24. doi: 10.1016/j.jhydrol.2012.11.009 CrossRefGoogle Scholar
  10. De Roo A, Barredo JI, Lavalle C, Bodis K, Bonk R (2007) Potential flood hazard and risk mapping at pan-European scale. In: Digital terrain modelling development and applications in a policy support environment, pp 183–202Google Scholar
  11. DHA U (1992) Internationally agreed glossary of basic terms related to disaster management. UN DHA (United Nations Department of Humanitarian Affairs), GenevaGoogle Scholar
  12. Fuchs S (2009) Susceptibility versus resilience to mountain hazards in Austria-paradigms of vulnerability revisited. Nat Hazards Earth Syst Sci 9:337–352CrossRefGoogle Scholar
  13. Georgakakos KP (1987) Real-time flash flood prediction. J Geophys Res Atmos 92(D8):9615–9629CrossRefGoogle Scholar
  14. Hapuarachchi HAP, Wang QJ, Pagano TC (2011) A review of advances in flash flood forecasting. Hydrol Process 25(18):2771–2784. doi: 10.1002/hyp.8040 CrossRefGoogle Scholar
  15. Hong Y, Adler R, Huffman G (2007) Use of satellite remote sensing data in the mapping of global landslide susceptibility. Nat Hazards 43(2):245–256. doi: 10.1007/s11069-006-9104-z CrossRefGoogle Scholar
  16. Hong Y, Adhikari P, Gourley JJ (2013) Flash flood. Encyclopedia of natural hazards. Springer, The Netherlands, pp 324–325CrossRefGoogle Scholar
  17. Jiang JH, Shao LP (2010) Standard of mountain flood warning based on the precipitation observation data. J Hydraul Eng 41(4):458–463 (in Chinese) Google Scholar
  18. Jiang W, Deng L, Chen L, Wu J, Li J (2009) Risk assessment and validation of flood disaster based on fuzzy mathematics. Prog Nat Sci 19(10):1419–1425. doi: 10.1016/j.pnsc.2008.12.010 CrossRefGoogle Scholar
  19. Karmeshu (2003) Entropy measures, maximum entropy principle and emerging applications. Springer Science & Business Media, vol 119Google Scholar
  20. Khan SI, Adhikari P, Hong Y, Vergara H et al (2011) Hydroclimatology of Lake Victoria region using hydrologic model and satellite remote sensing data. Hydrol Earth Syst Sci 15(1):107–117. doi: 10.5194/hess-15-107-2011 CrossRefGoogle Scholar
  21. Koren V, Reed S, Smith M, Zhang Z, Seo DJ (2004) Hydrology laboratory research modeling system (HL-RMS) of the US national weather service. J Hydrol 291(3):297–318. doi: 10.1016/j.jhydrol.2003.12.039 CrossRefGoogle Scholar
  22. Lee G, Jun KS, Chung ES (2013) Integrated multi-criteria flood vulnerability approach using fuzzy TOPSIS and Delphi technique. Nat Hazards Earth Syst Sci 13(5):1293–1312. doi: 10.5194/nhess-13-1293-2013 CrossRefGoogle Scholar
  23. Li K, Wu S, Dai E, Xu Z (2012) Flood loss analysis and quantitative risk assessment in China. Nat Hazards 63(2):737–760. doi: 10.1007/s11069-012-0180-y CrossRefGoogle Scholar
  24. Lin X, Lin Q, Wang M, Zhao Y, Li Y (2015) Hazard zoning of flash flood in mountainous administrative region of town: a case study on Tiaoshi Town. J Nat Disasters 3(24):90–96 (in Chinese) Google Scholar
  25. Linstone HA, Turoff M (eds) (1975) The Delphi method: Techniques and applications, vol 29. Addison-Wesley, ReadingGoogle Scholar
  26. Long D, Shen YJ, Sun AY, Hong Y, Longuevergne L, Yang YT, Li B, Chen L (2014) Drought and flood monitoring over a large karst plateau in Southwest China using extended GRACE data. Remote Sens Environ 155:145–160Google Scholar
  27. Mogil HM, Monro JC, Groper HS (1978) NWS’s flash flood warning and disaster preparedness programs. Bull Am Meteorol Soc 59(6):690–699. doi: 10.1175/1520-0477(1978)059<0690:NFFWAD>2.0.CO;2 CrossRefGoogle Scholar
  28. Papaioannou G, Vasiliades L, Loukas A (2015) Multi-criteria analysis framework for potential flood prone areas mapping. Water Resour Manage 29(2):399–418. doi: 10.1007/s11269-014-0817-6 CrossRefGoogle Scholar
  29. Parsons A (2003) Burned area emergency rehabilitation (BAER) soil burn severity definitions and mapping guidelines Draft. USDA forest service, Rocky Mountain Research Station, MissoulaGoogle Scholar
  30. Pradhan B (2010) Flood susceptible mapping and risk area delineation using logistic regression, GIS and remote sensing. J Spatial Hydrol 9(2):1–18Google Scholar
  31. River Forecast Center Development Management Team (2003) Flash flood guidance improvement team-final report. Report to the operations subcommittee of the NWS corporate board.
  32. Saaty RW (1987) The analytic hierarchy process-what it is and how it is used. Math Modell 9(3):161–176CrossRefGoogle Scholar
  33. Saaty TL (1990) How to make a decision: the analytic hierarchy process. Eur J Oper Res 48(1):9–26CrossRefGoogle Scholar
  34. Sahoo GB, Ray C (2006) Flow forecasting for a Hawaii stream using rating curves and neural networks. J Hydrol 317(1):63–80. doi: 10.1016/j.jhydrol.2005.05.008 CrossRefGoogle Scholar
  35. Sarkar S, Kanungo DP (2004) An integrated approach for landslide susceptibility mapping using remote sensing and GIS. Photogramm Eng Remote Sens 70(5):617–625CrossRefGoogle Scholar
  36. Scheuer S, Haase D, Meyer V (2011) Exploring multicriteria flood vulnerability by integrating economic, social and ecological dimensions of flood risk and coping capacity: from a starting point view towards an end point view of vulnerability. Nat Hazards 58(2):731–751. doi: 10.1007/s11069-010-9666-7 CrossRefGoogle Scholar
  37. Schmidt JA, Anderson AJ, Paul JH (2007) Spatially-variable, physically-derived flash flood guidance. AMS 21st conference on hydrology, San Antonio, TX B, vol 6Google Scholar
  38. Sinha R, Bapalu GV, Singh LK, Rath B (2008) Flood risk analysis in the Kosi river basin, north Bihar using multi-parametric approach of analytical hierarchy process (AHP). J Indian Soc Remote Sens 36(4):335–349. doi: 10.1007/s12524-008-0034-y CrossRefGoogle Scholar
  39. Smith G (2003) Flash flood potential: determining the hydrologic response of FFMP basins to heavy rain by analyzing their physiographic characteristics. Available from the NWS Colorado Basin River Forecast Center.
  40. Smith GE (2010) Development of a flash flood potential index using physiographic data sets within a geographic information system. Doctoral dissertation, University of UtahGoogle Scholar
  41. Store R, Kangas J (2001) Integrating spatial multi-criteria evaluation and expert knowledge for GIS-based habitat suitability modelling. Landsc Urban Plann 55(2):79–93. doi: 10.1016/S0169-2046(01)00120-7 CrossRefGoogle Scholar
  42. Sun D, Zhang D, Cheng X (2012) Framework of national non-structural measures for flash Flood disaster prevention in China. Water 4(1):272–282. doi: 10.3390/w4010272 CrossRefGoogle Scholar
  43. Sweeney TL (1992) Modernized areal flash flood guidance. US Department of Commerce, National Oceanic and Atmospheric Administration, National Weather Service, Office of HydrologyGoogle Scholar
  44. Sweeney TL, Baumgardner TF (1999) Modernized flash flood guidance. NWS Office of Hydrology, Web Site Version, Updated 8, pp 16–99Google Scholar
  45. Tan H, Ping W, Yang T, Li S, Liu A, Zhou J, Sun Z (2007) The synthetic evaluation model for analysis of flooding hazards. Eur J Public Health 17(2):206–210. doi: 10.1093/eurpub/ckl067 CrossRefGoogle Scholar
  46. Tang C, Zhu J (2005) A GIS based regional torrent risk zonation. Acta Geograph Sinica 60(1):87–94 (in Chinese) Google Scholar
  47. Vaidya OS, Kumar S (2006) Analytic hierarchy process: an overview of applications. Eur J Oper Res 169(1):1–29. doi: 10.1016/j.ejor.2004.04.028 CrossRefGoogle Scholar
  48. Villagran de Leon JC (2006) Vulnerability—a conceptual and methodological review. UNU EHS, no 4/2006, Bonn, GermanyGoogle Scholar
  49. Wang J, Hong Y, Li L, Gourley JJ, Khan SI, Yilmaz KK et al (2011a) The coupled routing and excess storage (CREST) distributed hydrological model. Hydrol Sci J 56(1):84–98. doi: 10.1080/02626667.2010.543087 CrossRefGoogle Scholar
  50. Wang Y, Li Z, Tang Z, Zeng G (2011b) A GIS-based spatial multi-criteria approach for flood risk assessment in the Dongting Lake Region, Hunan, Central China. Water Resour Manage 25(13):3465–3484. doi: 10.1007/s11269-011-9866-2 CrossRefGoogle Scholar
  51. Zahedi F (1986) The analytic hierarchy process-a survey of the method and its applications. Interfaces 16(4):96–108CrossRefGoogle Scholar
  52. Zhang X, Luo J, Chen L et al (2000) Zoning of Chinese flood hazard risk. J Hydraul Eng 3:3–9 (in Chinese) Google Scholar
  53. Zhou G, Yan H (2007) The spatial and temporal distribution feature of precipitation field over Yunnan. J Yunnan Univ Nat Sci 29(1):55 (in Chinese) Google Scholar
  54. Zou ZH, Yi Y, Sun JN (2006) Entropy method for determination of weight of evaluating indicators in fuzzy synthetic evaluation for water quality assessment. J Environ Sci 18(5):1020–1023. doi: 10.1016/S1001-0742(06)60032-6 CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  1. 1.State Key Laboratory of Hydroscience and Engineering, Department of Hydraulic EngineeringTsinghua UniversityBeijingChina
  2. 2.College of Water SciencesBeijing Normal UniversityBeijingChina
  3. 3.School of Civil Engineering and Environmental ScienceUniversity of OklahomaNormanUSA
  4. 4.National Meteorological CenterChina Meteorological AdministrationBeijingChina
  5. 5.State Key Laboratory of Severe WeatherChinese Academy of Meteorological SciencesBeijingChina
  6. 6.State Key Laboratory of Hydroscience and Engineering, Department of Hydraulic EngineeringTsinghua UniversityBeijingChina

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