Tytuł artykułu
Wybrane pełne teksty z tego czasopisma
Identyfikatory
Warianty tytułu
Języki publikacji
Abstrakty
In this paper, the impact of maximum flow uncertainty on flood hazard zone is analyzed. Two factors are taken into account: (1) the method for determination of maximum flows and (2) the limited length of the data series available for calculations. The importance of this problem is a consequence of the implementation of the EU Flood Directive in all EU member states. The factors mentioned seem to be among the most important elements responsible for potential uncertainty and inaccuracy of the developed flood hazard maps. Two methods are analyzed, namely the quantiles method and the maximum likelihood method. The maximum flows are estimated for the Wronki gauge station located in the reach of the Warta river. This simple river system is located in the central part of Poland. The length of the available data is 44 years. Hence, the series of the lengths 40, 30 and 20 years are tested and compared with reference calculations for 44 years. The hydrodynamic model HECRAS is used to calculate water surface profiles in steady state flow. The Python scripting language is applied for automation of HEC-RAS calculations and processing of final results in the form of inundation maps. The number of trials for each factor is not huge to keep the presented methodology useful in practice. The chosen measure of uncertainty is the range of variability for maximum flow values as well as inundation areas. The estimated values stressed the great importance of the factors analyzed for the uncertainty of the maximum flows as well as inundation areas. The impact of the data series length on the maximum flows is straightforward; a shorter data series gives a wider range of variability. However, the dependencies between other factors are more complex. Hence, the application of methodology based on the simulation and GIS data processing for assessment of this problem seems to be quite a good approach.
Wydawca
Czasopismo
Rocznik
Tom
Strony
661--676
Opis fizyczny
Bibliogr. 59 poz.
Twórcy
autor
- Department of Hydraulic and Sanitary Engineering, Poznan University of Life Sciences, Poznan, Poland
autor
- Department of Hydraulic and Sanitary Engineering, Poznan University of Life Sciences, Poznan, Poland
autor
- Institute of Land Improvement, Environmental Development and Geodesy, Poznan University of Life Sciences, Poznan, Poland
autor
- Institute of Land Improvement, Environmental Development and Geodesy, Poznan University of Life Sciences, Poznan, Poland
Bibliografia
- 1. Albano R, Crăciun I, Mancusi L, Sole A, Ozunu A (2017) Flood damage assessment and uncertainty analysis: the case study of 2006 flood in Ilisua basin in Romania. Carpathian J Earth Environ Sci 12(2):335–346
- 2. Arseni M, Roșu A, Bocăneală C, Constantin D-E, Georgescu LP (2017) Flood hazard monitoring using GIS and remote sensing observations. Carpathian J Earth Environ Sci 12(2):329–334
- 3. Banasik K, Wałęga A, Weglarczyk S, Więzik B (2017) Update of methodology for calculation of maximum discharges and maximum precipitation with determined exceedance probability for controlled and uncontrolled watersheds and calibration of rainfall—runoff models (in Polish). Association of Polish Hydrologists, Warsaw. http://www.kzgw.gov.pl/files/zam-pub/20170402-przeglad-i-aktualizacja-map/zal-2-do-OPZ-ujednolicony-1.pdf. Accessed 22nd Dec 2018
- 4. Bates PD, Pappenberger F, Romanowicz RJ (2014) Uncertainty in flood inundation modelling. In: Beven K, Hall J (eds) Applied uncertainty analysis for flood risk management. Imperial Collage Press, London, pp 232–269
- 5. Beven KJ, Hall J (eds) (2014) Applied uncertainty analysis for flood risk management. Imperial College Press, London
- 6. Brunner GW (2016a) HEC-RAS river analysis system hydraulic reference manual. US Army Corps of Engineers. Report No. CPD-69; Hydrologic Engineering Center (HEC), Davis
- 7. Brunner GW (2016b) HEC-RAS river analysis system user’s manual version 5.0. US Army Corps of Engineers. Report No. CPD-68; Hydrologic Engineering Center (HEC), Davis
- 8. Calenda G, Mancini CP, Volpi E (2009) Selection of the probabilistic model of extreme floods: the case of the River Tiber in Rome. J Hydrol 371(1–4):1–11
- 9. Cameron T, Ackerman PE (2012) HEC-GeoRAS GIS tools for support of HEC-RAS using ArcGIS user’s manual. US Army Corps of Engineers, Institute for Water Resources, Hydroogic Engineering Center (HEC). http://www.hec.usace.army.mil/software/hec-georas/documentation/HEC-GeoRAS_43_Users_Manual.pdf. Accessed 7th July 2018
- 10. Chow VT, Maidment DR, Mays LW (1988) Applied hydrology. McGraw-Hill Book Company, New Year
- 11. Cook A, Merwade V (2009) Effect of topographic data, geometric configuration and modeling approach on flood inundation mapping. J Hydrol 377(1–2):131–142
- 12. Di Baldassarre G, Montanari A (2009) Uncertainty in river discharge observations: a quantitative analysis. Hydrol Earth Syst Sci 13(6):913–921
- 13. Di Baldassarre G, Montanari A, Lins H, Koutsoyiannis D, Brandimarte L, Blöschl G (2010) Flood fatalities in Africa: from diagnosis to mitigation. Geophys Res Lett 37(22):L22402
- 14. Di Baldassarre G, Laio F, Montanari A (2012) Effect of observation errors on the uncertainty of design floods. Phys Chem Earth Parts A/B/C 42:85–90
- 15. Dimitriadis P, Tegos A, Oikonomou A, Pagana V, Koukouvinos A, Mamassis N, Efstratiadis A (2016) Comparative evaluation of 1D and quasi-2D hydraulic models based on benchmark and real-world applications for uncertainty assessment in flood mapping. J Hydrol 534:478–492
- 16. Docan DC (2016) Learning ArcGIS for desktop. Packt Publishing. https://www.packtpub.com/application-development/learning-arcgis-desktop. Accessed 7th July 2018
- 17. Downey A, Elkner J, Meyers Ch (2002) How to think like a computer scientist. Learning with Python. Green Tea Press, Wellesley. http://www.greenteapress.com/thinkpython/thinkCSpy.pdf. Accessed 8th Nov 2017
- 18. Dysarz T (2018a) Development of RiverBox—an ArcGIS toolbox for river bathymetry reconstruction. Water 10(9):1266
- 19. Dysarz T (2018b) Application of Python scripting techniques for control and automation of HEC-RAS simulations. Water 10(10):1382
- 20. Dysarz T, Wicher-Dysarz J, Sojka M (2015) Assessment of the impact of new investments on flood hazard-study case: the bridge on the Warta River near Wronki. Water 7:5752–5767. http://www.mdpi.com/2073-4441/7/10/5752. Accessed 23rd July 2018
- 21. Engeland K, Steinsland I, Johansen SS, Petersen-Øverleir A, Kolberg S (2016) Effects of uncertainties in hydrological modelling. A case study of a mountainous catchment in Southern Norway. J Hydrol 536:147–160
- 22. European Parliament (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. http://data.europa.eu/eli/dir/2007/60/oj
- 23. Ewemoje TA, Ewemooje OS (2011) Best distribution and plotting positions of daily maximum flood estimation at Ona River in Ogun-oshun river basin, Nigeria. Agric Eng Int CIGR J 13(3), Manuscript No. 1380
- 24. Gąsiorowski D (2013) Analysis of floodplain inundation using 2D nonlinear diffusive wave equation solved with splitting technique. Acta Geophys 61(3):668–689
- 25. Gilles D, Young N, Schroeder H, Piotrowski J, Chang YJ (2012) Inundation mapping initiatives of the Iowa Flood Center: statewide coverage and detailed urban flooding analysis. Water 4(1):85–106
- 26. Goodell Ch (2014) Breaking HEC-RAS code. A user’s guide to automating HEC-RA. h2ls, Portland
- 27. Griffis VW, Stedinger JR (2007) The use of GLS regression in regional hydrologic analyses. J Hydrol 344(1–2):82–95
- 28. Hammond M, Robinson A (2000) Python programming on Win32. O’Reilly Media Inc, Sebastopol
- 29. Hirsh RM, Stedinger JR (1987) Plotting position for historical floods and their precision. Water Resour Res 23(4):715–727
- 30. Jung Y, Kim D, Kim D, Kim M, Lee SO (2014) Simplified flood inundation mapping based on flood elevation-discharge rating curves using satellite images in gauged watersheds. Water 6:1280–1299
- 31. Kolerski T (2018) Mathematical modeling of ice dynamics as a decision support tool in river engineering. Water 10(9):1241
- 32. Kundzewicz ZW, Stoffel M, Wyżga B, Ruiz-Villanueva V, Niedźwiedź T, Kaczka R, Ballesteros-Cánovas JA, Pińskwar I, Łupikasza E, Zawiejska J, Mikuś P, Choryński A, Hajdukiewicz H, Spyt B, Janecka K (2017) Changes of flood risk on the northern foothills of the Tatra Mountains. Acta Geophys 65:799–807
- 33. Laio F, Ganora D, Claps P, Galeati G (2011) Spatially smooth regional estimation of the flood frequency curve (with uncertainty). J Hydrol 408(1–2):67–77
- 34. Laks I, Sojka M, Walczak Z, Wróżyński R (2017) Possibilities of using low quality digital elevation models of floodplains in hydraulic numerical models. Water 9(4):283
- 35. Law M, Collins A (2018) Getting to know ArcGIS desktop, 5th edn. Esri Press, Redlands
- 36. Liu Z, Merwade V (2018) Accounting for model structure, parameter and input forcing uncertainty in flood inundation modeling using Bayesian model averaging. J Hydrol 565:138–149
- 37. Merz B, Thieken AH (2005) Separating natural and epistemic uncertainty in flood frequency analysis. J Hydrol 309(1–4):114–132
- 38. Nones M (2015) Implementation of the floods directive in selected EU member states. Water Environ J 29(3):412–418
- 39. Nones M (2017) Flood hazard maps in the European context. Water Int. 42(3):324–332
- 40. Pappenberger F, Beven KJ, Ratto M, Matgen P (2008) Multi-method global sensitivity analysis of flood inundation models. Adv Water Resour 31(1):1–14
- 41. Parkes B, Demeritt D (2016) Defining the hundred year flood: a Bayesian approach for using historic data to reduce uncertainty in flood frequency estimates. J Hydrol 540:1189–1208
- 42. Python Software Foundation (2017a) Python 2.7.14 documentation. https://docs.python.org/2/index.html. Accessed 8th Nov 2017
- 43. PythonCOM Documentation Index (2017) Python and COM. Blowing the rest away! http://docs.activestate.com/activepython/2.4/pywin32/html/com/win32com/HTML/docindex.html. Accessed 8 Nov 2017
- 44. Refsgaard JC, Storm B (1990) Construction, calibration and validation of hydrological models. Distributed hydrological modeling. Springer, Dordrecht, pp 41–54
- 45. Romanowicz R, Beven K (2003) Estimation of flood inundation probabilities as conditioned on event inundation maps. Water Resour Res 39(3):1073
- 46. Sampson CC, Fewtrell TJ, Duncan A, Shaad K, Horritt MS, Bates PD (2012) Use of terrestrial laser scanning data to drive decimetric resolution urban inundation models. Adv Water Resour 41:1–17
- 47. Schendel T, Thongwichian R (2015) Flood frequency analysis: confidence interval estimation by test inversion bootstrapping. Adv Water Resour 83:1–9
- 48. Schendel T, Thongwichian R (2017) Considering historical flood events in flood frequency analysis: is it worth the effort? Adv Water Resour 105:144–153
- 49. Serago JM, Vogel RM (2018) Parsimonious nonstationary flood frequency analysis. Adv Water Resour 112:1–16
- 50. Serinaldi F, Kilsby CG (2015) Stationarity is undead: uncertainty dominates the distribution of extremes. Adv Water Resour 77:17–36
- 51. Sibson R (1981) A brief description of nearest neighbor interpolation. Interpolating multivariate data. Wiley, New York
- 52. Sun H, Jiang T, Jing C, Su B, Wang G (2017) Uncertainty analysis of hydrological return period estimation, taking the upper Yangtze River as an example. Hydrol Earth Syst Sci Discuss 1–26. https://doi.org/10.5194/hess-2016-566
- 53. Szydłowski M, Szpakowski W, Zima P (2013) Numerical simulation of catastrophic flood: the case study of hypothetical failure of the Bielkowo hydro-power plant reservoir. Acta Geophys 61(5):1229–1245
- 54. Teng J, Jakeman AJ, Vaze J, Croke BF, Dutta D, Kim S (2017) Flood inundation modelling: a review of methods, recent advances and uncertainty analysis. Environ Model Softw 90:201–216
- 55. Van Alpen J, Passchier R (2007) Atlas of flood maps, examples from 19 European countries, USA and Japan. Ministry of Transport, Public Works and Water Management, The Hague
- 56. Van der Graaf SC (2016) Natural Neighbour Kriging and its potential for quality mapping and grid design, M.Sc. thesis, Delft University of Technology. https://repository.tudelft.nl/. Accessed 7th July 2018
- 57. Walczak Z, Sojka M, Laks I (2013) Assessment of mapping of embankments and control structure on digital elevation model based upon Majdany polder. Rocz Ochr Śr 15:2711–2724
- 58. Yuan F, Zhao C, Jiang Y, Ren L, Shan H, Zhang L, Shen H (2017) Evaluation on uncertainty sources in projecting hydrological changes over the Xijiang River basin in South China. J Hydrol 554:434–450
- 59. Zandbergen PA (2013) Python scripting for ArcGIS. Esri Press, Redlands
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-00a6907e-1cde-4846-a6ec-64ceffaaba01