Skip to main content

Advertisement

Log in

Flash-flood potential assessment and mapping by integrating the weights-of-evidence and frequency ratio statistical methods in GIS environment – case study: Bâsca Chiojdului River catchment (Romania)

  • Published:
Journal of Earth System Science Aims and scope Submit manuscript

Abstract

Given the significant worldwide human and economic losses caused due to floods annually, reducing the negative consequences of these hazards is a major concern in development strategies at different spatial scales. A basic step in flood risk management is identifying areas susceptible to flood occurrences. This paper proposes a methodology allowing the identification of areas with high potential of accelerated surface run-off and consequently, of flash-flood occurrences. The methodology involves assessment and mapping in GIS environment of flash flood potential index (FFPI), by integrating two statistical methods: frequency ratio and weights-of-evidence. The methodology was applied for Bâsca Chiojdului River catchment (340 \(\hbox {km}^{2}\)), located in the Carpathians Curvature region (Romania). Firstly, the areas with torrential phenomena were identified and the main factors controlling the surface run-off were selected (in this study nine geographical factors were considered). Based on the features of the considered factors, many classes were set for each of them. In the next step, the weights of each class/category of the considered factors were determined, by identifying their spatial relationships with the presence or absence of torrential phenomena. Finally, the weights for each class/category of geographical factors were summarized in GIS, resulting the FFPI values for each of the two statistical methods. These values were divided into five classes of intensity and were mapped. The final results were used to estimate the flash-flood potential and also to identify the most susceptible areas to this phenomenon. Thus, the high and very high values of FFPI characterize more than one-third of the study catchment. The result validation was performed by (i) quantifying the rate of the number of pixels corresponding to the torrential phenomena considered for the study (training area) and for the results’ testing (validating area) and (ii) plotting the ROC (receiver operating characteristics) curve.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  • Arachchige R and Perera D J 2015 Mapping flash flood potential using GIS and the Flash Flood Potential Index (FFPI) in the Turtle River and Forest River watersheds in North Dakota. The University of North Dakota.

  • Bonham-Carter G F 1994 Geographic information systems for geoscientists: Modeling with GIS; In: Computer methods in the geoscientists, Pergamon Press, New York, 13 398.

  • Ceru J 2012 Flash Flood Potential Index for Pennsylvania; Proceedings, 2012 ESRI Federal GIS Conference.http://proceedings.esri.com/library/userconf/feduc12/papers/user/JoeCeru.pdf.

  • Chendeş V 2011 Resursele de apă din Subcarpaii de la Curbură: evaluări geospaiale; Edit. Academiei Române, ISBN 978-973-27-2131-5.

    Google Scholar 

  • Costache R 2014 Using GIS techniques for assessing lag time and concentration time in small river basins. Case study: Pecineaga River Basin, Romania; Geographia Technica 9(1) 31–38.

  • Costache R, Fontanine I and Corodescu E 2014 Assessment of surface runoff depth changes in Sǎrǎel River basin, Romania using GIS techniques; Cent. Eur. J. Geosci. 6(3) 363–372.

    Google Scholar 

  • Costache R, Pravalie R, Mitof I and Popescu C 2015 Flood vulnerability assessment in the low sector of Saratel Catchment. Case study: Joseni Village; Carpath. J. Earth. Environ. Sci.  10(1) 161–169.

    Google Scholar 

  • Corsini A, Cervi F and Ronchetti F 2009 Weight of evidence and artificial neural networks for potential groundwater spring mapping: An application to the Mt. Modino area (Northern Apennines, Italy); Geomorphology 111(1) 79–87.

    Article  Google Scholar 

  • Dahal R K, Hasegawa S, Nonomura A, Yamanaka M, Masuda T and Nishino K 2008 GIS-based weights-of-evidence modelling of rainfall-induced landslides in small catchments for landslide susceptibility mapping; Environ. Geol. 54 311–324.

    Article  Google Scholar 

  • DHI 2009 A modelling system for rivers and channels – Mike 11, Reference Manual.

  • Fontanine I E and Costache R 2013 The potential for water diffuse pollution with heavy metals in Arieş River Basin; Analele Stiintifice ale Universitatii “Alexandru Ioan Cuza” din Iasi-Seria Geografie 59(2) 59–72.

    Google Scholar 

  • Fuchs S 2009 Susceptibility versus resilience to mountain hazards in Austria – paradigms of vulnerability revisited; Nat. Hazard. Earth. Syst. Sci. 9(2) 337–352.

    Article  Google Scholar 

  • Fuchs S, Spachinger K, Dorner W, Rochman J and Serrhini K 2009 Evaluating cartographic design in flood risk mapping; Environ. Hazard. 8(1) 52–70.

    Article  Google Scholar 

  • Fuchs S, Keiler M and Zischg A 2015 A spatiotemporal multi-hazard exposure assessment based on property data; Nat. Hazard Earth. Syst. Sci. 15(9) 2127–2142.

    Article  Google Scholar 

  • Godfrey A, Ciurean R L, van Westen C J, Kingma N C and Glade T 2015 Assessing vulnerability of buildings to hydro-meteorological hazards using an expert based approach – An application in Nehoiu Valley, Romania; Int. J. Disaster Risk Reduction 13 229–241.

    Article  Google Scholar 

  • Gonçalves P, Marafuz I and Gomes A 2015 Flood hazard, Santa Cruz do Bispo Sector, Leça River, Portugal: A methodological contribution to improve land use planning; J. Maps 11(5) 760–771.

    Article  Google Scholar 

  • Karagiorgos K, Thaler T, Heiser M, Hübl J and Fuchs S 2016a Integrated flash flood vulnerability assessment: Insights from East Attica, Greece; J. Hydrol. 541 553–562.

    Article  Google Scholar 

  • Karagiorgos K, Thaler T, Hübl J, Maris F and Fuchs S 2016b Multi-vulnerability analysis for flash flood risk management; Nat. Hazards 82(1) 63–87.

    Article  Google Scholar 

  • Kayastha P, Dhital M R and De Smedt F 2012 Landslide susceptibility mapping using the weight of evidence method in the Tinau watershed, Nepal; Nat. Hazards 63(2) 479–498.

    Article  Google Scholar 

  • Kruzdlo R 2010 Flash Flood Potential Index for the Mount Holly Hydrologic Service 31 Area; http://www.state.nj.us/drbc/library/documents/Flood_Website/flood-warning/userforums/Krudzlo_NWS.pdf.

  • Kumar R and Anbalagan R 2015 Landslide susceptibility zonation in part of Tehri reservoir region using frequency ratio, fuzzy logic and GIS; J. Earth Syst. Sci. 124(2) 431–448.

    Article  Google Scholar 

  • IPCC 2014: Summary for policymakers; In: Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, 32p, http://ipcc-wg2.gov/AR5/report/.

  • Lee S and Choi J 2004 Landslide susceptibility mapping using GIS and the weight-of-evidence model; Int. J. Geogr. Inf. Sci. 18(8) 789–814.

    Article  Google Scholar 

  • Lee S and Pradhan B 2007 Landslide hazard mapping at Selangor, Malaysia using frequency ratio and logistic regression models; Landslides 4 33–41.

    Article  Google Scholar 

  • Lee S and Sambath T 2006 Landslide susceptibility mapping in the Damrei Romel area, Cambodia using frequency ratio and logistic regression models; Environ. Geol. 50(6) 847–855.

    Article  Google Scholar 

  • Mărgărint M, Grozavu A and Patriche C 2013 Assessing the spatial variability of coefficients of landslide predictors in different regions of Romania using logistic regression; Nat. Hazard Earth. Syst. Sci. 13(12) 3339–3355.

    Article  Google Scholar 

  • Meyer V, Kuhlicke C, Luther J, Fuchs S, Priest S, Dorner W, Serrhini K, Pardoe J, McCarthy S, Seidel J, Palka G, Unnerstall H, Viavattene C and Scheuer S 2012 Recommendations for the user-specific enhancement of flood maps; Nat. Hazard Earth. Syst. Sci. 12(5) 1701–1716.

    Article  Google Scholar 

  • Minea G 2013 Assessment of the flash flood potential of Bâsca River Catchment (Romania) based on physiographic factors; Cent. Eur. J. Geosci. 5(3) 344–353.

    Google Scholar 

  • Mohammady M, Pourghasemi H R and Pradhan B 2012 Landslide susceptibility mapping at Golestan Province, Iran: A comparison between frequency ratio, Dempster–Shafer, and weights-of-evidence models; J. Asian Earth Sci. 61 221–236.

    Article  Google Scholar 

  • National Engineering Handbook 2007, Chapter 7 – Hydrologic Soil Groups, United States Department of Agriculture – National Resources Conservation Service.

  • National Institute of Hydrology and Water Management (NIHWM) Romania 2015 Archive database, Bucharest.

  • Orthophotomaps 2008 National Agency for Cadastre and Land Registration (NACLR), Romania.

  • Pallant J 2013 SPSS survival manual; McGraw-Hill Education, London (UK).

    Google Scholar 

  • Park S, Choi C, Kim B and Kim J 2013 Landslide susceptibility mapping using frequency ratio, analytic hierarchy process, logistic regression, and artificial neural network methods at the Inje area, Korea; Environ. Earth Sci. 68(5) 1443–1464.

    Article  Google Scholar 

  • Pișota I, Zaharia Liliana and Diaconu D 2010 Hidrologie (Ediția a II-a revizuită și adădugită); Editura Universitară București, București.

  • Poudyal C P, Chang C, Oh H J and Lee S 2010 Landslide susceptibility maps comparing frequency ratio and artificial neural networks: A case study from the Nepal Himalaya; Environ. Earth Sci. 61(5) 1049–1064.

    Article  Google Scholar 

  • Pourghasemi H R, Pradhan B, Gokceoglu C, Mohammadi M and Moradi H R 2013 Application of weights-of-evidence and certainty factor models and their comparison in landslide susceptibility mapping at Haraz watershed, Iran; Arab. J. Geosci. 6(7) 2351–2365.

    Article  Google Scholar 

  • Pradhan B, Oh H J and Buchroithner M 2010 Weights-of-evidence model applied to landslide susceptibility mapping in a tropical hilly area; Geomat. Nat. Haz. Risk 1(3) 199–223.

    Article  Google Scholar 

  • Prăvălie R and Costache R 2013 The vulnerability of the territorial-administrative units to the hydrological phenomena of risk (flash-floods). Case study: The subcarpathian sector of Buzău Catchment; Analele Universităii din Oradea–Seria Geografie 23(1) 91–98.

    Google Scholar 

  • Prăvălie R and Costache R 2014 The analysis of the susceptibility of the flash-floods’ genesis in the area of the hydrographical basin of Bâsca Chiojdului river; Forum Geografic 13(1) 39–49.

    Google Scholar 

  • Regmi N R, Giardino J R and Vitek J D 2010 Modeling susceptibility to landslides using the weight of evidence approach: Western Colorado, USA; Geomorphology 115(1) 172–187.

    Article  Google Scholar 

  • Ruin I, Creutin J D, Anquetin S, Lutoff C 2008 Human exposure to flash floods – Relation between flood parameters and human vulnerability during a storm of September 2002 in southern France; J. Hydrol. 361(1) 199–213.

    Article  Google Scholar 

  • Smith G 2003 Flash flood potential: Determining the hydrologic response of FFMP basins to heavy rain by analyzing their physiographic characteristics; http://www.cbrfc.noaa.gov/papers/ffpwpap.pdf, 11p.

  • Špitalar M, Gourley J J, Lutoff C, Kirstetter P E, Brilly M and Carr N 2014 Analysis of flash flood parameters and human impacts in the US from 2006 to 2012; J. Hydrol. 519 863–870.

    Article  Google Scholar 

  • Teodor S and Matreata S 2011 A way of determining how small river basins of Somes river are susceptible to flash-floods; Carpath. J. Earth. Environ. 6(1) 89–98.

  • Terti G, Ruin I, Anquetin S and Gourley J J 2015 Dynamic vulnerability factors for impact-based flash flood prediction; Nat. Hazards 79(3) 1481–1497.

    Article  Google Scholar 

  • Van Westen C J, Montoya A L, Boerboom L G J and Badilla Coto E 2002 Multi-hazard risk assessment using GIS in urban areas: A case study for the city of Turrialba, Costa Rica; In: Proceedings of the regional workshop on best practices in disaster mitigation: Lessons learned from the Asian urban disaster mitigation program and other initiatives, 24–26 September 2002, Bali, Indonesia, pp. 120–136.

  • Van Westen C J, Rengers N and Soeters R 2003 Use of geomorphological information in indirect landslide assessment; Nat. Hazards 30(3) 399–419.

    Article  Google Scholar 

  • Yalcin A, Reis S, Aydinoglu A C and Yomralioglu T 2011 A GIS-based comparative study of frequency ratio, analytical hierarchy process, bivariate statistics and logistics regression methods for landslide susceptibility mapping in Trabzon, NE Turkey; Catena 85(3) 274–287.

    Article  Google Scholar 

  • Yilmaz I 2009 Landslide susceptibility mapping using frequency ratio, logistic regression, artificial neural networks and their comparison: A case study from Kat landslides (Tokat–Turkey); Comput. Geosci. 35(6) 1125–1138.

    Article  Google Scholar 

  • Youssef A M, Pradhan B and Hassan A M 2011 Flash flood risk estimation along the St. Katherine road, southern Sinai, Egypt using GIS based morphometry and satellite imagery; Environ. Earth Sci. 62(3) 611–623.

    Article  Google Scholar 

  • Zaharia L, Minea G, Ioana-Toroimac G, Barbu R and Sârbu I 2012 Estimation of the areas with accelerated surface runoff in the upper Prahova watershed (Romanian Carpathians), Balwois, Republic of Macedonia.

    Google Scholar 

  • Zaharia L, Costache R, Prăvălie R and Minea G 2015 Assessment and mapping of flood potential in the Slănic catchment in Romania; J. Earth Syst. Sci. 124(6) 1311–1324.

    Article  Google Scholar 

  • Zogg J and Deitsch K 2013 The Flash Flood Potential Index at WFO Des Moines, Iowa; National Weather Service working paper, http://www.crh.noaa.gov/images/dmx/hydro/FFPI/FFPI_WriteUp.pdf

Download references

Acknowledgements

Authors would like to thank the anonymous reviewers of the Journal of Earth System Science, for their critical and valuable comments that helped to bring the manuscript into its present form.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Romulus Costache.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Costache, R., Zaharia, L. Flash-flood potential assessment and mapping by integrating the weights-of-evidence and frequency ratio statistical methods in GIS environment – case study: Bâsca Chiojdului River catchment (Romania). J Earth Syst Sci 126, 59 (2017). https://doi.org/10.1007/s12040-017-0828-9

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s12040-017-0828-9

Keywords

Navigation