Skip to main content
SpringerLink
Log in

The Use of Geospatial Technologies in Flood Hazard Mapping and Assessment: Case Study from River Evros

  • Published:
Pure and Applied Geophysics Aims and scope Submit manuscript

Abstract

Many scientists link climate change to the increase of the extreme weather phenomena frequency, which combined with land use changes often lead to disasters with severe social and economic effects. Especially floods as a consequence of heavy rainfall can put vulnerable human and natural systems such as transboundary wetlands at risk. In order to meet the European Directive 2007/60/EC requirements for the development of flood risk management plans, the flood hazard map of Evros transboundary watershed was produced after a grid-based GIS modelling method that aggregates the main factors related to the development of floods: topography, land use, geology, slope, flow accumulation and rainfall intensity. The verification of this tool was achieved through the comparison between the produced hazard map and the inundation maps derived from the supervised classification of Landsat 5 and 7 satellite imageries of four flood events that took place at Evros delta proximity, a wetland of international importance. The comparison of the modelled output (high and very high flood hazard areas) with the extent of the inundated areas as mapped from the satellite data indicated the satisfactory performance of the model. Furthermore, the vulnerability of each land use against the flood events was examined. Geographically Weighted Regression has also been applied between the final flood hazard map and the major factors in order to ascertain their contribution to flood events. The results accredited the existence of a strong relationship between land uses and flood hazard indicating the flood susceptibility of the lowlands and agricultural land. A dynamic transboundary flood hazard management plan should be developed in order to meet the Flood Directive requirements for adequate and coordinated mitigation practices to reduce flood risk.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

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

References

  • Angelidis, P., Kotsikas, M., & Kotsovinos, N. (2010). Management of upstream dams and flood protection of the Transboundary River Evros/Maritza. Water Resources Management, 24, 2467–2484.

    Article  Google Scholar 

  • Arnoldus, H.M.J. (1980). An approximation of the rainfall factor in the Universal Soil Loss Equation. In M. De Boodt, and Gabriels, D. (Eds.), Assessment of erosion (pp. 127–132). Chichester: Wiley.

  • Becker, B. L., Lusch, D. P., & Qi, J. (2007). A classification-based assessment of the optimal spectral and spatial resolutions for Great Lakes coastal wetland imagery. Remote Sensing of Environment, 108, 111–120.

    Article  Google Scholar 

  • Bradshaw, C. J. A., Sodhi, N. S., Peh, K. S. H., & Brook, B. W. (2007). Global evidence that deforestation amplifies flood risk and severity in the developing world. Global Change Biology, 13, 2379–2395.

    Article  Google Scholar 

  • Brunsdon, C., Fotheringham, S., & Charlton, M. (1996). Geographically weighted regression: a method for exploring spatial non-stationarity. Geographical Analysis, 28, 281–298.

    Article  Google Scholar 

  • Castillejo-González, I. L., López-Granados, F., García-Ferrer, A., Peña-Barragán, J. M., Jurado-Expósito, M., de la Orden, M. S., et al. (2009). Object- and pixel-based analysis for mapping crops and their agro-environmental associated measures using QuickBird imagery. Computers and Electronics in Agriculture, 68, 207–215.

    Article  Google Scholar 

  • Charlton, M. and Fotheringham, S. (2009). Geographically weighted regression white paper (National Centre for Geocomputation National University of Ireland Maynooth, Maynooth, Co Kildare, Ireland) (http://www.geos.ed.ac.uk/~gisteac/fspat/gwr/arcgis_gwr/GWR_WhitePaper.pdf).

  • Chen, Y., Yu, J., & Khan, S. (2010). Spatial sensitivity analysis of multi-criteria weights in GIS-based land suitability evaluation. Environmental Modelling and Software, 25, 1582–1591.

    Article  Google Scholar 

  • Darmouth Flood Observatory. (2014). Global Active Archive of Large Flood Events (http://www.dartmouth.edu/~floods/Archives/index.html).

  • Davies, S.L. (2002). Discrepancy-based model selection criteria using cross-validation. Doctoral dissertation (University of Missouri-Columbia Department of Statistics, Columbia).

  • Davies, S. L., Neath, A. A., & Cavanaugh, J. E. (2005a). Cross validation model selection criteria for linear regression based on the Kullback-Leibler discrepancy. Statistical Methodology, 2, 249–266.

    Article  Google Scholar 

  • Davies, S. L., Neath, A. A., & Cavanaugh, J. E. (2005b). On the minimum variance unbiasedness property of AICc and MCp. Iowa City: Technical report (The University of Iowa Department of Biostatistics.

    Google Scholar 

  • De Smith, M., Goodchild, M., & Longley, P. (2007). Geospatial analysis: A comprehensive guide to principles, techniques and software tools. Winchelsea: Troubador Publishing Ltd.

    Google Scholar 

  • Debba, P., van Ruitenbeek, F. J. A., van der Meer, F. D., Carranza, E. J. M., & Stein, A. (2005). Optimal field sampling for targeting minerals using hyperspectral data. Remote Sensing of Environment, 99, 373–386.

    Article  Google Scholar 

  • Dimitriou, E., Mentzafou, A., Zogaris, S., Tzortziou, M., Gritzalis, K., Karaouzas, I., et al. (2011). Assessing the environmental status and identifying the dominant pressures of a trans-boundary river catchment, to facilitate efficient management and mitigation practices. Environmental Earth Sciences, 66, 1839–1852.

    Article  Google Scholar 

  • Dimitriou, E., Moussoulis, E., Mentzafou, A., Tzortziou, M., Zeri, C., Colombari, E. and Markogianni, V. (2010). Environmental status assessment for Evros river basin. Final Technical Report (in Greek), (Hellenic Centre for Marine Research, Athens).

  • Erwin, K. L. (2009). Wetlands and global climate change: the role of wetland restoration in a changing world. Wetlands Ecology and Management, 17, 71–84.

    Article  Google Scholar 

  • European Commission Council. (2000). European Commission Council Directive 2000/60/EC of the European Parliament and of the Council of 23 October 2000 establishing a framework for Community action in the field of water policy. Official Journal of the European Communities, L327, 1–72.

  • European Commission Council. (2007). Directive 2007/60/EC of the European Parliament and of the Council of 23 October 2007 on the assessment and management of flood risks. Official Journal of the European Union, L288, 27–34.

    Google Scholar 

  • European Environmental Agency—E.E.A. (2012), Corine Land Cover 2006 (http://www.eea.europa.eu).

  • Feyen, L., Barredo, J. I. and Dankers, R., Implications of global warming and urban land use change on flooding in Europe. In Water and Urban Development Paradigms—Towards an Integration of Engineering, Design and Management Approaches (ed. Feyen, J., Shannon, K., and Neville, M.) (Taylor and Francis, London 2009), pp. 217–225.

  • Fotheringham, S. (1992). Exploratory Spatial Data Analysis and GIS. Environment and Planning A, 24, 1675–1678.

    Google Scholar 

  • Fotheringham, S., & Brunsdon, C. (1999). Local forms of spatial analysis. Geographical Analysis, 31, 340–358.

    Article  Google Scholar 

  • Fotheringham, S., Brunsdon, C., & Charlton, M. (2002). Geographically weighted regression: The analysis of spatially varying relationships. Chichester: John Wiley & Sons Ltd.

    Google Scholar 

  • Fotheringham, S., Charlton, M., & Brunsdon, C. (1996). The geography of parameter space: an investigation of spatial non-stationarity. International Journal of Geographical Information Systems, 10, 605–627.

    Article  Google Scholar 

  • Fotheringham, S., Charlton, M., & Brunsdon, C. (1997). Two techniques for exploring non stationarity in geographical data. Geographical Systems, 4, 59–82.

    Google Scholar 

  • Fotheringham, S., & Rogerson, P. A. (1993). GIS and spatial analytical problems. International Journal of Geographical Information Science, 7, 3–19.

    Article  Google Scholar 

  • Fotopoulos, F., Makropoulos, C., & Mimikou, M. A. (2010). Flood forecasting in transboundary catchments using the open modeling interface. Environmental Modelling and Software, 25, 1640–1649.

    Article  Google Scholar 

  • Fournier, F. (1960). Climat et érosion: la relation entre l’érosion du sol par l’eau et les précipitations atmosphériques. Paris: Presses Universitaires de France.

    Google Scholar 

  • Gass, L., Norman, L.M., Villarreal, M.L., Tolle, C., Coe, M. and Jamwal, P. (2013), A Test of Methods to Measure Vegetation Change Adjacent to Gabions in Sonora, Mexico using Landsat imagery, Presented at the Santa Cruz River Researcher’s Day, Tucson Arizona.

  • Gemitzi, A., Petalas, C., Tsihrintzis, V. A., & Pisinaras, V. (2006). Assessment of groundwater vulnerability to pollution: a combination of GIS, fuzzy logic and decision making techniques. Environmental Geology, 49, 653–673.

    Article  Google Scholar 

  • General Directorate of Mineral Research and Exploration. (1961). Geological Map of Turkey, sheet Istanbul, 1:500,000, Ankara, Turkey.

  • Institute of Geology and Mineral Exploration—Division of General Geology and Economic Geology (1983), Geological Map of Greece, 1:500,000. Athens, Greece.

  • IPCC, Climate Change 2013—The Physical Science Basis—Working Group I Contribution to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change - Summary for Policymakers. (Cambridge University Press, United Kingdom and New York 2013).

  • Keiner, L. E., & Yan, X.-H. (1998). A neural network model for estimating sea surface chlorophyll and sediments from thematic mapper imagery. Remote Sensing of Environment, 66, 153–165.

    Article  Google Scholar 

  • Khandekar, M. L. (2013). The global warming—extreme weather link: a review of the state of science. London: The Global Warming Policy Foundation.

    Google Scholar 

  • Khandekar, M. L., Murty, T. S., & Chittibabu, P. (2005). The global warming debate: a review of the state of science. Pure and Applied Geophysics, 162, 1557–1586.

    Article  Google Scholar 

  • Kourgialas, N. N., & Karatzas, G. P. (2011). Flood management and a GIS modelling method to assess flood-hazard areas—a case study. Hydrological Sciences Journal, 56, 212–225.

    Article  Google Scholar 

  • Kramer, A. and Schellig, A. (2011). Meric River Basin: Transboundary Water Cooperation at the Border between the EU and Turkey, In Turkey’s Water Policy National: National Frameworks and International Cooperation (ed. Kramer, A., Kibaroglu, A., and Scheumann, W.) (Springer Berlin Heidelberg, New York) pp. 229–249.

  • Kundzewicz, Z. W., Lugeri, N., Dankers, R., Hirabayashi, Y., Döll, P., Pińskwar, I., et al. (2010). Assessing river flood risk and adaptation in Europe-review of projections for the future. Mitigation and Adaptation Strategies for Global Change, 15, 641–656.

    Article  Google Scholar 

  • Lathrop, R. G., Lillesand, T. M., & Yandell, B. S. (1991). Testing the utility of simple multi-date thematic mapper calibration algorithms for monitoring turbid inland waters. International Journal of Remote Sensing, 12, 2045–2063.

    Article  Google Scholar 

  • Malczewski, J. (2006). GIS-based multicriteria decision analysis: a survey of the literature. International Journal of Geographical Information Science, 20, 703–726.

    Article  Google Scholar 

  • Mallick, J., Singh, C. K., Al-Wadi, H., Ahmed, M., Rahman, A., Shashtri, S., et al. (2015). Geospatial and geostatistical approach for ground water potential zone delineation. Hydrological Processes, 29, 395–418.

    Article  Google Scholar 

  • Meyer, V., Scheuer, S., & Haase, D. (2009). A multicriteria approach for flood risk mapping exemplified at the Mulde river, Germany. Natural Hazards, 48, 17–39.

    Article  Google Scholar 

  • Michigan Technological University (2011), Geographic Information Science information and support - How to generate random points in ArcGIS, http://gis.mtu.edu/?p=127 (accessed on 27/02/2015).

  • Ministry of Environment Energy and Climate Change-Special Secretariat for Water, Flood directive 2007/60/EC: Preliminary Flood Risk Assessment (in Greek) (Athens, 2012).

  • Ministry of Forest and Water Management (2011), Official statistics (in Turkish) (http://www.milliparklar.gov.tr/Anasayfa/istatistik.aspx?sflang=tr).

  • Ministry of Infrastructure Transport and Networks—General Secretariat of Public Works—Earthquake Recovery Service (2014), Delimited flooded areas—credit measures (in Greek) (http://www.yas.gr/ApoList.asp?cat_apo_id=106).

  • Morgan, R. P. C. (2005). Soil erosion and conservation (3rd ed.). Oxford: Blackwell Publishing.

    Google Scholar 

  • Mousmouti, M. (2003). Hellenic-Bulgarian Bilateral Agreements for the Protection and Use of Transboundary Watercourses (http://www.nomosphysis.org.gr/attachments/10/contribution7.mousmouti.doc).

  • Oliver, J. E. (1980). Monthly precipitation distribution: a comparative index. Professional Geography, 32, 300–309.

    Article  Google Scholar 

  • Openshaw, S. (1993). Exploratory Space-Time-Attribute Pattern Analysers, In Spatial Analysis and CIS (ed. Fotheringham A.S. and Rogerson P.A.) (Taylor and Francis, London), pp. 147–63.

  • Papaioannou, G., Vasiliades, L., & Loukas, A. (2015). Multi-criteria analysis framework for potential flood prone areas mapping. Water Resources Management, 29, 399–418.

    Article  Google Scholar 

  • Papathanasiou, C., Serbis, D., & Mamassis, N. (2013). Flood mitigation at the downstream areas of a transboundary river. Water Utility Journal, 3, 33–42.

    Google Scholar 

  • Pasqualini, V., Oberti, P., Vigetta, S., Riffard, O., Panaiotis, C., Cannac, M., et al. (2011). A GIS-based multicriteria evaluation for aiding risk management Pinus pinaster Ait. Forests: a case study in Corsican Island, Western Mediterranean Region. Environmental Management , 48, 38–56.

    Article  Google Scholar 

  • Raaijmakers, R., Krywkow, J., & van der Veen, A. (2008). Flood risk perceptions and spatial multi-criteria analysis: an exploratory research for hazard mitigation. Natural Hazards, 46, 307–322.

    Article  Google Scholar 

  • Ratsiatou, I. and E. Stefanakis, Spatio-temporal multicriteria decision making under uncertainty, In Proceedings of the First International Symposium on Robust Statistics and Fuzzy Techniques in Geodesy and GIS (ed. Carosio, A. and Kutterer H.) (Zurich, 2001) pp. 169–174.

  • Schäuble, H., Marinoni, O., & Hinderer, M. (2008). A GIS-based method to calculate flow accumulation by considering dams and their specific operation time. Computers & Geosciences, 34, 635–646.

    Article  Google Scholar 

  • Semmler, T., & Jacob, D. (2004). Modeling extreme precipitation events-a climate change simulation for Europe. Global and Planetary Change, 44, 119–127.

    Article  Google Scholar 

  • Skias, S. and Kallioras, A., Cross Border Co-operation and the Problem of Flooding in the Evros Delta, In Many Rivers to cross: Cross-border Co-operation in River Management (ed. Verwijmeren, J. and Wiering, M.) (Eburon Academic Publishers, Delft, The Netherlands 2007) pp. 119–143.

  • Skoulikidis, N. T., Economou, A. N., Gritzalis, K. C. and Zogaris, S., Rivers of the Balkans, In Rivers of Europe (ed. Tockner, K., Uehlinger, U., and Robinson, C. T.) (Academic Press, London 2009) pp. 421–466.

  • Smith, R. M. (1986). Comparing traditional methods for selecting class Intervals on choropleth maps. Professional Geographer, 38, 62–67.

    Article  Google Scholar 

  • Stefanidis, S., & Stathis, D. (2013). Assessment of flood hazard based on natural and anthropogenic factors using analytic hierarchy process (AHP). Natural Hazards, 68, 569–585.

    Article  Google Scholar 

  • Turner, A. B., Colby, J. D., Csontos, R. M., & Batten, M. (2013). Flood Modeling Using a Synthesis of Multi-Platform LiDAR Data. Water, 5, 1533–1560.

    Article  Google Scholar 

  • UNECE (United Nations Economic Commission for Europe), Second Assessment of transboundary rivers, lakes and groundwaters (United Nations Publications, Geneva 2011).

  • UNECE (United Nations Economic Commission for Europe), Transboundary flood risk management: experiences from the UNECE region (United Nations Publications, New York and Geneva 2009).

  • U.S. Geological Survey (2003), Generalized Geology of Europe including Turkey (https://www.sciencebase.gov/catalog/).

  • WHO (World Meteorological Organization), Guide to hydrological practices. Volume I: Hydrology - From measurement to hydrological information (World Meteorological Organization, Geneva 2008).

  • YCEO - Yale Center for Earth Observation, Yale Institute of Biospheric Studies (2010). Index of CEO Documentation (http://www.yale.edu/ceo/Documentation/).

  • Zerger, A. (2002). Examining GIS decision utility for natural hazard risk modelling. Environmental Modelling and Software, 17, 287–294.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Hellenic Centre for Marine Research, Institute of Marine Biological Resources and Inland Waters, 46.7 km Athens-Sounio Ave., 19013, Anavissos Attikis, Greece

    Angeliki Mentzafou, Vasiliki Markogianni & Elias Dimitriou

Authors
  1. Angeliki Mentzafou
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Vasiliki Markogianni
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Elias Dimitriou
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Angeliki Mentzafou.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mentzafou, A., Markogianni, V. & Dimitriou, E. The Use of Geospatial Technologies in Flood Hazard Mapping and Assessment: Case Study from River Evros. Pure Appl. Geophys. 174, 679–700 (2017). https://doi.org/10.1007/s00024-016-1433-6

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00024-016-1433-6

Keywords

Search

Navigation