Evaluation of Geomorphic Descriptors Thresholds for Flood Prone Areas Detection on Ephemeral Streams in the Metropolitan Area of Bari (Italy) | SpringerLink
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Evaluation of Geomorphic Descriptors Thresholds for Flood Prone Areas Detection on Ephemeral Streams in the Metropolitan Area of Bari (Italy)

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Computational Science and Its Applications – ICCSA 2019 (ICCSA 2019)

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Abstract

Using geomorphic descriptors is a fast and reliable approach for mapping flood-prone areas exploiting Digital Elevation Models and their tools. However, calibration and validation procedures require a flooded map obtained by 1D/2D hydraulic simulation, which usually needs lots of information (available, for example, from remote sensing techniques) and important computational efforts. This approach is usually performed by calibration on a single event, using linear binary classifiers method and Receiver Operating Characteristics curves, in order to define an optimal threshold corresponding to a selected flooded map. On the other hand, the availability of flood-risk maps, provided by public or private institutions, is an important source of data for applying this procedure on a wide and hydrologically homogeneous area, in order to analyze some similitudes. In this study some interesting case studies located in Puglia region (Southern Italy) are investigated, using flooded maps for return periods of 30, 200 and 500 years provided by Basin Authority of Puglia; the aim of the proposed work is to compare the known flooded map areas with those obtained using several geomorphologic index on four case studies located in the metropolitan area of Bari (Puglia).

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References

  1. Milly, P.C.D., Wetherald, R.T., Dunne, K.A., Delworth, T.L.: Increasing risk of great floods in a changing climate. Nature 415(6871), 514 (2002)

    Article  Google Scholar 

  2. Salas, J.D., Obeysekera, J.: Revisiting the concepts of return period and risk for nonstationary hydrologic extreme events. J. Hydrol. Eng. 19(3), 554–568 (2013)

    Article  Google Scholar 

  3. De Paola, F., Giugni, M., Pugliese, F., Annis, A., Nardi, F.: GEV parameter estimation and stationary vs. non-stationary analysis of extreme rainfall in African test cities. Hydrology 5(2), 28 (2018)

    Article  Google Scholar 

  4. Obeysekera, J., Salas, J.D.: Quantifying the uncertainty of design floods under nonstationary conditions. J. Hydrol. Eng. 19(7), 1438–1446 (2013)

    Article  Google Scholar 

  5. Sangiorgio, V., Uva, G., Fatiguso, F.: Optimized AHP to overcome limits in weight calculation: building performance application. J. Constr. Eng. Manage. 144(2), 04017101 (2017)

    Article  Google Scholar 

  6. Ignacio, J.A.F., Cruz, G.T., Nardi, F., Henry, S.: Assessing the effectiveness of a social vulnerability index in predicting heterogeneity in the impacts of natural hazards: case study of the Tropical Storm Washi flood in the Philippines. Vienna Yearb. Popul. Res. 13(1), 91–130 (2015)

    Google Scholar 

  7. Feldman, A.D.: Hydrologic Engineering Center (U.S.), Hydrologic Modeling System HEC-HMS, US Army Corps of Engineers, Hydrologic Engineering Center (2000)

    Google Scholar 

  8. Fiorentino, M., Gioia, A., Iacobellis, V., Manfreda, S.: Analysis on flood generation processes by means of a continuous simulation model. Adv. Geosci. 7, 231–236 (2006). ISSN 1680-7340

    Article  Google Scholar 

  9. Merz, R., Blöschl, G.: Flood frequency hydrology: 1. Temporal, spatial, and causal expansion of information. Water Resour. Res. 44, W08432 (2008). https://doi.org/10.1029/2007WR006744

  10. Iacobellis, V., Fiorentino, M., Gioia, A., Manfreda, S.: Best fit selection of theoretical flood frequency distributions based on different runoff generation mechanisms. Water 2(2, 1), 239–256 (2010)

    Article  Google Scholar 

  11. Beven, K.: Rainfall-Runoff Modelling. The Primer, 2nd edn. Wiley-Blackwell, Chichester (2012)

    Book  Google Scholar 

  12. Gioia, A., Manfreda, S., Iacobellis, V., Fiorentino, M.: Performance of a theoretical model for the description of water balance and runoff dynamics in southern Italy. J. Hydrol. Eng. 19(6), 1113–1123 (2014)

    Article  Google Scholar 

  13. Di Modugno, M., et al.: Build-up/wash-off monitoring and assessment for sustainable management of first flush in an urban area. Sustainability 7, 5050–5070 (2015)

    Article  Google Scholar 

  14. Gioia, A., Iacobellis, V., Manfreda, S., Fiorentino, M.: Comparison of different methods describing the peak runoff contributing areas during floods. Hydrol. Process. 31(11), 2041–2049 (2017)

    Article  Google Scholar 

  15. De Wrachien, D., Mambretti, S.: Mathematical models for flood hazard assessment. Int. J. Saf. Secur. Eng. 1(4), 353–362 (2011)

    Article  Google Scholar 

  16. Iacobellis, V., Castorani, A., Di Santo, A.R., Gioia, A.: Rationale for flood prediction in karst endorheic areas. J. Arid Environ. 112(PA), 98–108 (2015)

    Article  Google Scholar 

  17. Bates, P., Anderson, M., Price, D., Hardy, R., Smith, C.: Analysis and development of hydraulic models for floodplain flows. In: Anderson, M.G., Walling, D.E., Bates, P.D. (eds.) Floodplain Processes. Wiley, New York (1996)

    Google Scholar 

  18. Aronica, G., Hankin, B., Beven, K.J.: Uncertainty and equifinality in calibrating distributed roughness coefficients in a flood propagation model with limited data. Adv. Water Resour. 22(4), 349–365 (1998)

    Article  Google Scholar 

  19. Jain, S.K., Singh, R.D., Jain, M.K., Lohani, A.K.: Delineation of flood-prone areas using remote sensing techniques. Water Resour. Manage. 19(4), 333–347 (2005)

    Article  Google Scholar 

  20. Fluet-Chouinard, E., Lehner, B., Rebelo, L.M., Papa, F., Hamilton, S.K.: Development of a global inundation map at high spatial resolution from topographic downscaling of coarse-scale remote sensing data. Remote Sens. Environ. 158, 348–361 (2015)

    Article  Google Scholar 

  21. Peña, F., Nardi, F.: Floodplain terrain analysis for coarse resolution 2D flood modeling. Hydrology 5(4), 52 (2018)

    Article  Google Scholar 

  22. Manfreda, S., et al.: Flood-prone areas assessment using linear binary classifiers based on flood maps obtained from 1D and 2D hydraulic models. Nat. Hazards 79(2), 735–754 (2015)

    Article  Google Scholar 

  23. Iacobellis, V., et al.: Investigation of a flood event occurred on lama Balice, in the context of hazard map evaluation in karstic-ephemeral streams. In: Gervasi, O., et al. (eds.) ICCSA 2018. LNCS, vol. 10964, pp. 317–333. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-95174-4_26

    Chapter  Google Scholar 

  24. Totaro, V., Gioia, A., Novelli, A., Caradonna, G.: The use of geomorphological descriptors and Landsat-8 spectral indices data for flood areas evaluation: a case study of Lato river basin. In: Gervasi, O., et al. (eds.) ICCSA 2017. LNCS, vol. 10407, pp. 30–44. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-62401-3_3

    Chapter  Google Scholar 

  25. Totaro, V., Peschechera, G., Gioia, A., Iacobellis, V., Fratino, U., Tarantino, E.: Comparison of satellite and geomorphic indices for flooded areas detection in a Mediterranean river basin (in preparation)

    Google Scholar 

  26. Bates, P.D., Horritt, M.S., Smith, C.N., Mason, D.C.: Integrating remote sensing observations of flood hydrology and hydraulic modelling. Hydrol. Process. 11, 1777–1795 (1997)

    Article  Google Scholar 

  27. Horritt, M.S., Mason, D.C., Luckman, A.J.: Flood boundary delineation from synthetic aperture radar imagery using a statistical active contour model. Int. J. Remote Sens. 22(13), 2489–2507 (2001)

    Article  Google Scholar 

  28. Mattia, F., et al.: Time series of COSMO-SkyMed data for landcover classification and surface parameter retrieval over agricultural sites. In: Proceedings of the IEEE 2012 International Geoscience and Remote Sensing Symposium, pp. 6511–6514 (2012). ISBN 978-1-4673-1159-5

    Google Scholar 

  29. Balenzano, A., et al.: On the use of multi-temporal series of COSMO-SkyMed data for landcover classification and surface parameter retrieval over agricultural sites. In: Proceedings of the 2011 IEEE International Geoscience and Remote Sensing Symposium, 24–29 July 2011, Vancouver, Canada, pp. 142–145 (2011)

    Google Scholar 

  30. Balenzano, A., et al.: A ground network for SAR-derived soil moisture product calibration, validation and exploitation in southern Italy. In: Proceedings of the IEEE 2014 International Geoscience and Remote Sensing Symposium, IGARSS 2014 (2014)

    Google Scholar 

  31. Tarantino, E., Novelli, A., Laterza, M., Gioia, A.: Testing high spatial resolution WorldView-2 imagery for retrieving the leaf area index. In: Third International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2015), vol. 9535, p. 95351N. International Society for Optics and Photonics (2015)

    Google Scholar 

  32. Trombetta, A., Iacobellis, V., Tarantino, E., Gentile, F.: Calibration of the AquaCrop model for winter wheat using MODIS LAI images. Agric. Water Manag. 164(Part 2), 304–316 (2016)

    Article  Google Scholar 

  33. Olang, L.O., Kundu, P., Bauer, T., Fürst, J.: Analysis of spatio-temporal land cover changes for hydrological impact assessment within the Nyando River Basin of Kenya. Environ. Monit. Assess. 179, 389–401 (2011)

    Article  Google Scholar 

  34. Pattison, I., Lane, S.N.: The link between land-use management and fluvial flood risk: a chaotic conception? Prog. Phys. Geogr. 36, 72–92 (2011)

    Article  Google Scholar 

  35. Balacco, G., Figorito, B., Tarantino, E., Gioia, A., Iacobellis, V.: Space-time LAI variability in Northern Puglia (Italy) from SPOT VGT data. Environ. Monit. Assess. 187, 434 (2015)

    Article  Google Scholar 

  36. Caprioli, M., Tarantino, E.: Identification of land cover alterations in the Alta Murgia National Park (Italy) with VHR satellite imagery. Int. J. Sustain. Dev. Plan. 1(3), 261–270 (2006)

    Article  Google Scholar 

  37. Crocetto, N., Tarantino, E.: A class-oriented strategy for features extraction from multidate ASTER imagery. Remote Sens. 1(4), 1171–1189 (2009)

    Article  Google Scholar 

  38. Fidelibus, M.D., Balacco, G., Gioia, A., Iacobellis, V., Spilotro, G.: Mass transport triggered by heavy rainfall: the role of endorheic basins and epikarst in a regional karst aquifer. Hydrol. Process. 31(2), 394–408 (2017)

    Article  Google Scholar 

  39. Figorito, B., Tarantino, E., Balacco, G., Fratino, U.: An object-based method for mapping ephemeral river areas from WorldView-2 satellite data. In: Remote Sensing for Agriculture, Ecosystems, and Hydrology XIV, vol. 8531, p. 85310B. International Society for Optics and Photonics (2012)

    Google Scholar 

  40. Saradjian, M.R., Hosseini, M.: Soil moisture estimation by using multipolarization SAR image. Adv. Space Res. 48(2), 278–286 (2011)

    Article  Google Scholar 

  41. Iacobellis, V., Gioia, A., Milella, P., Satalino, G., Balenzano, A., Mattia, F.: Inter-comparison of hydrological model simulations with time series of SAR-derived soil moisture maps. Eur. J. Remote Sens. 46(1), 739–757 (2013)

    Article  Google Scholar 

  42. Peschechera, G., Fratino, U.: Calibration of CLAIR model by means of Sentinel-2 LAI data for analysing wheat crops through Landsat-8 surface reflectance data. In: Gervasi, O., et al. (eds.) ICCSA 2018. LNCS, vol. 10964, pp. 294–304. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-95174-4_24

    Chapter  Google Scholar 

  43. Gioia, A., Iacobellis, V., Manfreda, S., Fiorentino, M.: Influence of infiltration and soil storage capacity on the skewness of the annual maximum flood peaks in a theoretically derived distribution. Hydrol. Earth Syst. Sci. 16, 937–951 (2012)

    Article  Google Scholar 

  44. Williams, W.A., Jensen, M.E., Winne, J.C., Redmond, R.L.: An automated technique for delineating and characterizing valley-bottom settings. Environ. Monit. Assess. 64(1), 105–114 (2000)

    Article  Google Scholar 

  45. Gallant, J.C., Dowling, T.I.: A multiresolution index of valley bottom flatness for mapping depositional areas. Water Resour. Res. 39(12), 1347 (2003). https://doi.org/10.1029/2002WR001426

  46. Nardi, F., Vivoni, E.R., Grimaldi, S.: Investigating a floodplain scaling relation using a hydrogeomorphic delineation method. Water Resour. Res. 42, W09409 (2006). https://doi.org/10.1029/2005WR004155

  47. Manfreda, S., Di Leo, M., Sole, A.: Detection of flood prone areas using digital elevation models. J. Hydrol. Eng. 16(10), 781–790 (2011)

    Article  Google Scholar 

  48. Samela, C., Manfreda, S., Paola, F.D., Giugni, M., Sole, A., Fiorentino, M.: DEM-based approaches for the delineation of flood-prone areas in an ungauged basin in Africa. J. Hydrol. Eng. 21(2), 06015010 (2015)

    Article  Google Scholar 

  49. Gioia, A., Totaro, V., Bonelli, R., Esposito, A.A.M.G., Balacco, G., Iacobellis, V.: Flood susceptibility evaluation on ephemeral streams of Southern Italy: a case study of lama Balice. In: Gervasi, O., et al. (eds.) ICCSA 2018. LNCS, vol. 10964, pp. 334–348. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-95174-4_27

    Chapter  Google Scholar 

  50. Cunnane, C.: Methods and merits of regional flood frequency analysis. J. Hydrol. 100(1–3), 269–290 (1988)

    Article  Google Scholar 

  51. Fiorentino, M., Gioia, A., Iacobellis, V., Manfreda, S.: Regional analysis of runoff thresholds behaviour in Southern Italy based on theoretically derived distributions. Adv. Geosci. 26, 139–144 (2011)

    Article  Google Scholar 

  52. Sangiorgio, V., Uva, G., Fatiguso, F.: User reporting–based semeiotic assessment of existing building stock at the regional scale. J. Perform. Constr. Facil. 32(6), 04018079 (2018)

    Article  Google Scholar 

  53. Mossa, M.: The floods in Bari: what history should have taught. J. Hydraul. Res. 45(5), 579–594 (2007)

    Article  Google Scholar 

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Authors and Affiliations

  1. Politecnico di Bari, Via E. Orabona, 470125, Bari, Italy

    Gabriella Balacco, Vincenzo Totaro, Andrea Gioia & Alberto Ferruccio Piccinni

Authors
  1. Gabriella Balacco
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  2. Vincenzo Totaro
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  3. Andrea Gioia
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  4. Alberto Ferruccio Piccinni
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Corresponding author

Correspondence to Vincenzo Totaro .

Editor information

Editors and Affiliations

  1. Covenant University, Ota, Nigeria

    Sanjay Misra

  2. University of Perugia, Perugia, Italy

    Osvaldo Gervasi

  3. University of Basilicata, Potenza, Italy

    Beniamino Murgante

  4. Saint Petersburg State University, Saint Petersburg, Russia

    Elena Stankova

  5. Saint Petersburg State University, Saint Petersburg , Russia

    Vladimir Korkhov

  6. Polytechnic University of Bari, Bari, Italy

    Carmelo Torre

  7. University of Minho, Braga, Portugal

    Ana Maria A.C. Rocha

  8. Monash University, Clayton, VIC, Australia

    David Taniar

  9. Kyushu Sangyo University, Fukuoka, Japan

    Bernady O. Apduhan

  10. Polytechnic University of Bari, Bari, Italy

    Eufemia Tarantino

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Balacco, G., Totaro, V., Gioia, A., Piccinni, A.F. (2019). Evaluation of Geomorphic Descriptors Thresholds for Flood Prone Areas Detection on Ephemeral Streams in the Metropolitan Area of Bari (Italy). In: Misra, S., et al. Computational Science and Its Applications – ICCSA 2019. ICCSA 2019. Lecture Notes in Computer Science(), vol 11622. Springer, Cham. https://doi.org/10.1007/978-3-030-24305-0_19

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  • DOI: https://doi.org/10.1007/978-3-030-24305-0_19

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