Effect of the non-stationarity of rainfall events on the design of hydraulic structures for runoff management and its applications to a case study at Gordo Creek watershed in Cartagena de Indias, Colombia

The 24-h maximum rainfall (P 24h-max ) observations recorded at the synoptic weather station of Rafael Núñez airport (Cartagena de Indias, Colombia) were analyzed, and a linear increasing trend over time was identified. It was also noticed that the occurrence of the rainfall value (over the years of...

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2018
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Universidad Tecnológica de Bolívar
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Repositorio Institucional UTB
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eng
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oai:repositorio.utb.edu.co:20.500.12585/8730
Acceso en línea:
https://hdl.handle.net/20.500.12585/8730
Palabra clave:
Climate change
Non-stationary
Rainfall frequency analysis
Runoff management
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openAccess
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http://creativecommons.org/licenses/by-nc-nd/4.0/
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repository_id_str
dc.title.none.fl_str_mv Effect of the non-stationarity of rainfall events on the design of hydraulic structures for runoff management and its applications to a case study at Gordo Creek watershed in Cartagena de Indias, Colombia
title Effect of the non-stationarity of rainfall events on the design of hydraulic structures for runoff management and its applications to a case study at Gordo Creek watershed in Cartagena de Indias, Colombia
spellingShingle Effect of the non-stationarity of rainfall events on the design of hydraulic structures for runoff management and its applications to a case study at Gordo Creek watershed in Cartagena de Indias, Colombia
Climate change
Non-stationary
Rainfall frequency analysis
Runoff management
title_short Effect of the non-stationarity of rainfall events on the design of hydraulic structures for runoff management and its applications to a case study at Gordo Creek watershed in Cartagena de Indias, Colombia
title_full Effect of the non-stationarity of rainfall events on the design of hydraulic structures for runoff management and its applications to a case study at Gordo Creek watershed in Cartagena de Indias, Colombia
title_fullStr Effect of the non-stationarity of rainfall events on the design of hydraulic structures for runoff management and its applications to a case study at Gordo Creek watershed in Cartagena de Indias, Colombia
title_full_unstemmed Effect of the non-stationarity of rainfall events on the design of hydraulic structures for runoff management and its applications to a case study at Gordo Creek watershed in Cartagena de Indias, Colombia
title_sort Effect of the non-stationarity of rainfall events on the design of hydraulic structures for runoff management and its applications to a case study at Gordo Creek watershed in Cartagena de Indias, Colombia
dc.subject.keywords.none.fl_str_mv Climate change
Non-stationary
Rainfall frequency analysis
Runoff management
topic Climate change
Non-stationary
Rainfall frequency analysis
Runoff management
description The 24-h maximum rainfall (P 24h-max ) observations recorded at the synoptic weather station of Rafael Núñez airport (Cartagena de Indias, Colombia) were analyzed, and a linear increasing trend over time was identified. It was also noticed that the occurrence of the rainfall value (over the years of record) for a return period of 10 years under stationary conditions (148.1 mm) increased, which evidences a change in rainfall patterns. In these cases, the typical stationary frequency analysis is unable to capture such a change. So, in order to further evaluate rainfall observations, frequency analyses of P 24h-max for stationary and non-stationary conditions were carried out (by using the generalized extreme value distribution). The goodness-of-fit test of Akaike Information Criterion (AIC), with values of 753.3721 and 747.5103 for stationary and non-stationary conditions respectively, showed that the latter best depicts the increasing rainfall pattern. Values of rainfall were later estimated for different return periods (2, 5, 10, 25, 50, and 100 years) to quantify the increase (non-stationary versus stationary condition), which ranged 6% to 12% for return periods from 5 years to 100 years, and 44% for a 2-year return period. The effect of these findings were tested in the Gordo creek watershed by first calculating the resulting direct surface runoff (DSR) for various return periods, and then modeling the hydraulic behavior of the downstream area (composed of a 178.5-m creek's reach and an existing box-culvert located at the watershed outlet) that undergoes flooding events every year. The resulting DSR increase oscillated between 8% and 19% for return periods from 5 to 100 years, and 77% for a 2-year return period when the non-stationary and stationary scenarios were compared. The results of this study shed light upon to the precautions that designers should take when selecting a design, based upon rainfall observed, as it may result in an underestimation of both the direct surface runoff and the size of the hydraulic structures for runoff and flood management throughout the city. © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.
publishDate 2018
dc.date.issued.none.fl_str_mv 2018
dc.date.accessioned.none.fl_str_mv 2019-11-06T19:05:12Z
dc.date.available.none.fl_str_mv 2019-11-06T19:05:12Z
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dc.identifier.citation.none.fl_str_mv Fluids; Vol. 3, Núm. 2
dc.identifier.issn.none.fl_str_mv 2311-5521
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12585/8730
dc.identifier.doi.none.fl_str_mv 10.3390/fluids3020027
dc.identifier.instname.none.fl_str_mv Universidad Tecnológica de Bolívar
dc.identifier.reponame.none.fl_str_mv Repositorio UTB
identifier_str_mv Fluids; Vol. 3, Núm. 2
2311-5521
10.3390/fluids3020027
Universidad Tecnológica de Bolívar
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dc.format.medium.none.fl_str_mv Recurso electrónico
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spelling 2019-11-06T19:05:12Z2019-11-06T19:05:12Z2018Fluids; Vol. 3, Núm. 22311-5521https://hdl.handle.net/20.500.12585/873010.3390/fluids3020027Universidad Tecnológica de BolívarRepositorio UTBThe 24-h maximum rainfall (P 24h-max ) observations recorded at the synoptic weather station of Rafael Núñez airport (Cartagena de Indias, Colombia) were analyzed, and a linear increasing trend over time was identified. It was also noticed that the occurrence of the rainfall value (over the years of record) for a return period of 10 years under stationary conditions (148.1 mm) increased, which evidences a change in rainfall patterns. In these cases, the typical stationary frequency analysis is unable to capture such a change. So, in order to further evaluate rainfall observations, frequency analyses of P 24h-max for stationary and non-stationary conditions were carried out (by using the generalized extreme value distribution). The goodness-of-fit test of Akaike Information Criterion (AIC), with values of 753.3721 and 747.5103 for stationary and non-stationary conditions respectively, showed that the latter best depicts the increasing rainfall pattern. Values of rainfall were later estimated for different return periods (2, 5, 10, 25, 50, and 100 years) to quantify the increase (non-stationary versus stationary condition), which ranged 6% to 12% for return periods from 5 years to 100 years, and 44% for a 2-year return period. The effect of these findings were tested in the Gordo creek watershed by first calculating the resulting direct surface runoff (DSR) for various return periods, and then modeling the hydraulic behavior of the downstream area (composed of a 178.5-m creek's reach and an existing box-culvert located at the watershed outlet) that undergoes flooding events every year. The resulting DSR increase oscillated between 8% and 19% for return periods from 5 to 100 years, and 77% for a 2-year return period when the non-stationary and stationary scenarios were compared. The results of this study shed light upon to the precautions that designers should take when selecting a design, based upon rainfall observed, as it may result in an underestimation of both the direct surface runoff and the size of the hydraulic structures for runoff and flood management throughout the city. © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.Recurso electrónicoapplication/pdfengMDPI AGhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessAtribución-NoComercial 4.0 Internacionalhttp://purl.org/coar/access_right/c_abf2https://www2.scopus.com/inward/record.uri?eid=2-s2.0-85063714713&doi=10.3390%2ffluids3020027&partnerID=40&md5=cf64e424fc84a950b089594db6c3ba45Scopus 57208078895Scopus 57193337460Scopus 56074282700Scopus 35568240000Effect of the non-stationarity of rainfall events on the design of hydraulic structures for runoff management and its applications to a case study at Gordo Creek watershed in Cartagena de Indias, Colombiainfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArtículohttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_2df8fbb1Climate changeNon-stationaryRainfall frequency analysisRunoff managementGonzalez-Alvarez, A.Coronado Hernández, Óscar EnriqueFuertes Miquel, Vicente S.Ramos, H.M.Faber, B., Current methods for hydrologic frequency analysis (2010) Proceedings of the Workshop on Nonstationarity, Hydrologic Frequency Analysis, and Water Management, pp. 33-39. , http://www.cwi.colostate.edu/nonstationarityworkshop/index.shtml, Boulder, CO, USA, 13-15 January online: accessed on 21 December 2017Obeysekera, J., Salas, J.D., Quantifying the uncertainty of design floods under nonstationary conditions (2014) J. Hydrol. Eng., 19, pp. 1438-1446Wang, D., Hagen, S.C., Alizad, K., Climate change impact and uncertainty analysis of extreme rainfall events in the Apalachicola River basin, Florida (2012) J. Hydrol., 480, pp. 125-135Salas, J.D., Obeysekera, J., Vogel, R.M., Techniques for assessing water infrastructure for nonstationary extreme events: A review (2018) Hydrol. Sci. J.(2017) Resolution 0330 of 8 June 2017, Technical Guidelines for the Sector of Potable Water and Basic Sanitation (RAS), , http://www.minvivienda.gov.co/ResolucionesAgua/0330%20-%202017.pdf, Ministry of Housing, City, and Development MinViviendaRepublic of Colombia. online: accessed on 28 October 2017Poveda, G., Alvarez, D.M., The collapse of the stationarity hypothesis due to climate change and climate variability: Implications for hydrologic engineering design (2012) Rev. Ing. Univ. Andes, 36, pp. 65-76(2015) New Scenarios of Climate Change for Colombia 2011-2100 Scientific Tools for Deparment-Based Decision Making-National Emphasis: 3rd National Bulletin on Climate Change, , http://documentacion.ideam.gov.co/openbiblio/bvirtual/022964/documento_nacional_departamental.pdf, IDEAM, PNUD, MADS, DNP, CANCILLERÍA. online: accessed on 28 October 2017Chow, V.T., Maidment, D.R., Mays, L.W., (1988) Applied Hydrology, pp. 350-376. , 1st ed.McGraw-Hill: New York, NY, USAPalutikof, J.P., Brabson, B.B., Lister, D.H., Adcock, S.T., A review of methods to calculate extreme wind speeds (1999) Meteorol. Appl., 6, pp. 119-132Wilks, D.S., (2011) Statistical Methods in the Atmospheric Sciences, pp. 105-110. , 3rd ed.Academic Press: Oxford, UKWaltham, MA, USAGumbel, E.J., The return period of flood flows (1941) Ann. Math. Stat., 2, pp. 163-190Frechet, M., Sur la loi de probabilité de l'ecart máximum (On the probability law of maximum values) (1927) Ann Soc. Pol. Math., 6, pp. 93-116Weibull, W., A statistical theory of the strength of materials (1939) Proceedings of the Ingeniors Vetenskaps Akademien, (51), pp. 5-45. , http://www.scirp.org/%28S%28czeh2tfqyw2orz553k1w0r45%29%29/reference/ReferencesPapers.aspx?ReferenceID=1923153, The Royal Swedish Institute for Engineering Research. Stockholm, Swedenonline: accessed on 19 April 2018Pearson, K., On the systemic fitting of curves to observations and measurements (1902) Biometrika, 1, pp. 265-303Kolmogorov, A.N., Sulla determinazione empirica di una legge di distribuzione (1933) G. Inst. Ital. Attuari, 4, pp. 83-91Smirnov, N.V., Estimate of deviation between empirical distribution functions in two independent samples (1939) Bull. Moscow Univ., 2, pp. 3-16Smirnov, N.V., Table for estimating the goodness of fit of empirical distributions (1948) Ann. Math. Stat., 19, pp. 279-281Obeysekera, J., Salas, J.D., Frequency of recurrent extremes under nonstationarity (2016) J. Hydrol. Eng. ASCE, 21Akaike, H., A new look at the statistical model identification (1974) IEEE Trans. Autom. Control, 19, pp. 716-723(1985) National Engineering Handbook, Section 4, Hydrology (NEH-4), , https://policy.nrcs.usda.gov/OpenNonWebContent.aspx?content=18393.wba, USDA-SCS: Washington, DC, USA, online: accessed on 17 November 2017(1986) Conservation Engineering Division. Urban Hydrology for Small Watersheds, Technical Release 55 (TR-55), , https://www.nrcs.usda.gov/Internet/FSE_DOCUMENTS/stelprdb1044171.pdf, USDA-NRCS: Washington, DC, USA, online: accessed on 19 December 2017Mishra, S.K., Singh, V., (2003) Soil Conservation Service Curve Number (SCS-CN) Methodology, , 1st ed.Springer: Dordrecht, The NetherlandsPonce, V.M., Hawkins, R.H., Runoff curve number: Has it reached maturity? (1996) J. Hydrol. Eng. ASCE, 1, pp. 11-19Gericke, O.J., Smithers, J.C., Review of methods used to estimate catchment response time for the purpose of peak discharge estimation (2014) Hydrol. Sci. J., 59, pp. 1935-1971Sharifi, S., Hosseini, S.M., Methodology for identifying the best equations for estimating the time of concentration of watersheds in a particular region (2011) J. Irrig. Drain. Eng. ASCE, 137Kirpich, Z.P., Time of concentration of small agricultural watersheds (1940) Civ. Eng., 10, pp. 362-368Gonzalez, A., Temimi, M., Khanbilvardi, R., Adjustment to the curve number (NRCS-CN) to account for the vegetation effect on hydrological processes (2015) Hydrol. Sci. J., 60, pp. 591-605(1960) Flood-Frequency Analyses, Manual of Hydrology: Part 3, Flood-Flow Techniques, , https://pubs.usgs.gov/wsp/1543a/report.pdf, Government Printing Office: Washington, DC, USA, online: accessed on 17 December 2017(1965) Theoretical Implications of Under Fit Streams, Flood-Flow Techniques, , https://pubs.usgs.gov/pp/0452c/report.pdf, Government Printing Office: Washington, DC, USA, online: accessed on 17 December 2017Mohammed, E.A., Far, B.H., Emerging Business Intelligence Framework for a Clinical Laboratory Through Big Data Analytics 2015, pp. 577-602. , https://doi.org/10.1016/B978-0-12802508-6.00032-6, Chapter 32.. online: accessed on 28 January 2018Ramos, H.M., Pérez-Sánchez, M., Franco, A.B., López-Jiménez, P.A., Urban floods adaptation and sustainable drainage measures (2017) Fluids, 2, p. 61(2012) Guidelines for the Design and Construction of Stormwater Management Systems, , http://www.nyc.gov/html/dep/pdf/green_infrastructure/stormwater_guidelines_2012_final.pdf, New York City Department of Environmental Protection. New York City Department of Environmental Protection: New York, NY, USA, online: accessed on 4 January 2018http://purl.org/coar/resource_type/c_6501ORIGINALDOI10_3390fluidos3020027.pdfapplication/pdf14256647https://repositorio.utb.edu.co/bitstream/20.500.12585/8730/1/DOI10_3390fluidos3020027.pdfcc170f5460d1511a14f43d627b417192MD51TEXTDOI10_3390fluidos3020027.pdf.txtDOI10_3390fluidos3020027.pdf.txtExtracted texttext/plain66619https://repositorio.utb.edu.co/bitstream/20.500.12585/8730/4/DOI10_3390fluidos3020027.pdf.txtd7209730a289edf1d23bb5e770cef65cMD54THUMBNAILDOI10_3390fluidos3020027.pdf.jpgDOI10_3390fluidos3020027.pdf.jpgGenerated Thumbnailimage/jpeg87019https://repositorio.utb.edu.co/bitstream/20.500.12585/8730/5/DOI10_3390fluidos3020027.pdf.jpg60326bbbd19a01f6ae00abb62cee71b9MD5520.500.12585/8730oai:repositorio.utb.edu.co:20.500.12585/87302023-05-26 09:42:52.301Repositorio Institucional UTBrepositorioutb@utb.edu.co