Statistical Analysis to Quantify the Impact of Map Type on Estimating Peak Discharge in Non-Instrumented Basins

The calculation of peak discharge in non-instrumented basins requires including morphometric parameters, which in turn depend on the map type used. This study analyses the impact of and variation in peak discharges of the Caño Ricaurte basin, Colombia, based on three types of maps at different resol...

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Autores:: Sierra-Sánchez, Alexandra
Paternina-Verona, Duban A.
Gatica, Gustavo
Ramos, Helena M.
Coronado Hernández, Óscar Enrique

Tipo de recurso:: Article of journal

Fecha de publicación:: 2023

Institución:: Universidad Tecnológica de Bolívar

Repositorio:: Repositorio Institucional UTB

Idioma:: eng

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network_name_str	Repositorio Institucional UTB
repository_id_str
dc.title.spa.fl_str_mv	Statistical Analysis to Quantify the Impact of Map Type on Estimating Peak Discharge in Non-Instrumented Basins
dc.title.translated.spa.fl_str_mv	Statistical Analysis to Quantify the Impact of Map Type on Estimating Peak Discharge in Non-Instrumented Basins
title	Statistical Analysis to Quantify the Impact of Map Type on Estimating Peak Discharge in Non-Instrumented Basins
spellingShingle	Statistical Analysis to Quantify the Impact of Map Type on Estimating Peak Discharge in Non-Instrumented Basins basin time of concentration peak flow rate Ricaurte Cartagena Mapping
title_short	Statistical Analysis to Quantify the Impact of Map Type on Estimating Peak Discharge in Non-Instrumented Basins
title_full	Statistical Analysis to Quantify the Impact of Map Type on Estimating Peak Discharge in Non-Instrumented Basins
title_fullStr	Statistical Analysis to Quantify the Impact of Map Type on Estimating Peak Discharge in Non-Instrumented Basins
title_full_unstemmed	Statistical Analysis to Quantify the Impact of Map Type on Estimating Peak Discharge in Non-Instrumented Basins
title_sort	Statistical Analysis to Quantify the Impact of Map Type on Estimating Peak Discharge in Non-Instrumented Basins
dc.creator.fl_str_mv	Sierra-Sánchez, Alexandra Paternina-Verona, Duban A. Gatica, Gustavo Ramos, Helena M. Coronado Hernández, Óscar Enrique
dc.contributor.author.eng.fl_str_mv	Sierra-Sánchez, Alexandra Paternina-Verona, Duban A. Gatica, Gustavo Ramos, Helena M.
dc.contributor.author.none.fl_str_mv	Coronado Hernández, Óscar Enrique
dc.subject.eng.fl_str_mv	basin time of concentration peak flow rate Ricaurte Cartagena Mapping
topic	basin time of concentration peak flow rate Ricaurte Cartagena Mapping
description	The calculation of peak discharge in non-instrumented basins requires including morphometric parameters, which in turn depend on the map type used. This study analyses the impact of and variation in peak discharges of the Caño Ricaurte basin, Colombia, based on three types of maps at different resolution scales. The reference map used was the map made for the detailed designs of the channel analysed, which was extracted from the Master Plan of the City. Additionally, maps from a 90 × 90 m digital elevation model and contour lines extracted from Google Earth were used. The time of concentration was determined by different equations (Kirpich, Témez, Bureau, and TR-55) using the mapping methods described above, and the peak discharge was determined using rainfall-runoff models.
publishDate	2023
dc.date.accessioned.none.fl_str_mv	2023-12-29 13:09:03 2025-05-21T19:15:47Z
dc.date.available.none.fl_str_mv	2023-12-29 13:09:03
dc.date.issued.none.fl_str_mv	2023-12-29
dc.type.spa.fl_str_mv	Artículo de revista
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dc.type.local.eng.fl_str_mv	Journal article
dc.type.content.eng.fl_str_mv	Text
dc.type.version.eng.fl_str_mv	info:eu-repo/semantics/publishedVersion
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dc.identifier.uri.none.fl_str_mv	https://hdl.handle.net/20.500.12585/13514
dc.identifier.url.none.fl_str_mv	https://doi.org/10.32397/tesea.vol4.n2.522
dc.identifier.doi.none.fl_str_mv	10.32397/tesea.vol4.n2.522
dc.identifier.eissn.none.fl_str_mv	2745-0120
url	https://hdl.handle.net/20.500.12585/13514 https://doi.org/10.32397/tesea.vol4.n2.522
identifier_str_mv	10.32397/tesea.vol4.n2.522 2745-0120
dc.language.iso.eng.fl_str_mv	eng
language	eng
dc.relation.references.eng.fl_str_mv	Fernanda Julia Gaspari, Alfonso Martín Rodríguez Vagaría, Gabriela Elba Senisterra, Gerardo Andrés Denegri, María Isabel Delgado, and Sebastián Ignacio Besteiro. Caracterización morfométrica de la cuenca alta del río sauce grande, buenos aires, argentina. Augm Domus, 4:143–158, 2012. [2] MR Vidal-Abarca, Carlos Montes, ML Suárez, and L Ramirez Diaz. Caracterización morfométrica de la cuenca del río segura: Estudio cuantitativo de las formas de las subcuencas. Papeles de Geografía, (12), 1987. [3] Alejandra M Geraldi, M Piccolo, and Gerardo ME Perillo. Delimitación y estudio de cuencas hidrográficas con modelos hidrológicos. Investigaciones Geográficas (Esp), (52):215–225, 2010. [4] Adán Guillermo Ramírez García, Artemio Cruz León, Pastor Sánchez García, and Alejandro Ismael Monterroso Rivas. La caracterización morfométrica de la subcuenca del río moctezuma, sonora: ejemplo de aplicación de los sistemas de información geográfica. Revista de Geografía Agrícola, (55):27–43, 2015. [5] Rofiat Bunmi Mudashiru, Ismail Abustan, and Fauzi Baharudin. Methods of estimating time of concentration: a case study of urban catchment of sungai kerayong, kuala lumpur. In Proceedings of AICCE’19: Transforming the Nation for a Sustainable Tomorrow 4, pages 119–161. Springer, 2020. [6] Salvatore Grimaldi, Andrea Petroselli, Flavia Tauro, and Maurizio Porfiri. Time of concentration: a paradox in modern hydrology. Hydrological Sciences Journal, 57(2):217–228, 2012. [7] Washington Ramiro Sandoval Erazo and Eduardo Patricio Aguilera Ortiz. Determinación de caudales en cuencas con poco información hidrológica. Ciencia Unemi, 7(12):100–110, 2014. [8] T Bisantino, R Bingner, W Chouaib, F Gentile, and G Trisorio Liuzzi. Estimation of runoff, peak discharge and sediment load at the event scale in a medium-size mediterranean watershed using the annagnps model. Land degradation & development, 26(4):340–355, 2015. [9] Helena M Ramos and Óscar E Coronado-Hernández. Iot, machine learning and photogrammetry in small hydropower towards energy and digital transition: potential energy and viability analyses. Journal of Applied Research in Technology & Engineering, 2023. [10] Ockert J Gericke and Jeff C Smithers. Review of methods used to estimate catchment response time for the purpose of peak discharge estimation. Hydrological sciences journal, 59(11):1935–1971, 2014. [11] Asghar Azizian. Uncertainty analysis of time of concentration equations based on first-order-analysis (foa) method. American Journal of Engineering and Applied Sciences, 11(1):327–341, 2018. [12] Marzieh Mokarram and Majid Hojati. Comparis of digital elevation model (dem) and aerial photographs for drainage. Modeling Earth Systems and Environment, 1:1–6, 2015. [13] Leilei Li, Jintao Yang, and Jin Wu. A method of watershed delineation for flat terrain using sentinel-2a imagery and dem: A case study of the taihu basin. ISPRS International Journal of Geo-Information, 8(12):528, 2019. [14] Zhengqing Lai, Shuo Li, Guonian Lv, Zhirong Pan, and Guosong Fei. Watershed delineation using hydrographic features and a dem in plain river network region. Hydrological Processes, 30(2):276–288, 2016. [15] Marvin E Quesada and Matt Marsik. Uso de modelos de elevación digital como alternativa para mostrar errores en mapas topográficos. Revista Geográfica de América Central, 1(48):77–93, 2012. [16] AB Ariza-Villaverde, FJ Jiménez-Hornero, and E Gutiérrez De Ravé. Influence of dem resolution on drainage network extraction: A multifractal analysis. Geomorphology, 241:243–254, 2015. [17] D. Jiménez. Inundaciones en cartagena: sin soluciones definitivas ni parciales. http://moir.org.co/Inundaciones-en-Cartagena-sin.html [Accessed: June 14, 2016]. [18] Jorge Iván Pérez Alvarino et al. Análisis hidráulico del canal ricaurte como parte del drenaje de aguas lluvias en cartagena de indias mediante la implementación del programa hec-ras 4.1. Título el especialista en recursos hídricos. Universidad de los Andes Departamento de Ingeniería Civil y Ambiental Centro de Investigaciones en Acueductos y Alcantarillados, – CIACUA., 2016. [19] ZP Kirpich. Time of concentration of small agricultural watersheds. Civil engineering, 10(6):362, 1940. [20] Isabel Kaufmann De Almeida, Aleska Kaufmann Almeida, Jamil Alexandre Ayach Anache, Jorge Luiz Steffen, and Teodorico Alves Sobrinho. Estimation on time of concentration of overland flow in watersheds: a review. Geosciences= Geociências, 33(4):661–671, 2014. [21] Roger Cronshey. Urban hydrology for small watersheds. Time of concentration and travel. Number 55. US Department of Agriculture, Soil Conservation Service, Engineering Division, 2nd edition, 1986. pages 29–33. [22] POT (2001). Decreto no 0977 de 2001. http://curaduria2cartagena.com/pdf/POT.pdf [Accessed: March 23, 2021]. [23] Alvaro Gonzalez-Alvarez, Oscar E Coronado-Hernández, Vicente S Fuertes-Miquel, and Helena M Ramos. 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. Fluids, 3(2):27, 2018. [24] Alcaldía Mayor de Cartagena de Indias. Estudios y diseños del plan maestro de drenajes pluviales del distrito de cartagena de indias. https://www.yumpu.com/es/document/view/42121178/plan-maestro-de-drenajes-pluviales-cartagena-parte-1 [Accessed: September 24, 2019]. [25] Departamento Administrativo de Valorización Distrital. Estudios y diseños del plan maestro de drenajes pluviales del distrito de cartagena de indias, 2008.
dc.relation.ispartofjournal.eng.fl_str_mv	Transactions on Energy Systems and Engineering Applications
dc.relation.citationvolume.eng.fl_str_mv	4
dc.relation.citationstartpage.none.fl_str_mv	1
dc.relation.citationendpage.none.fl_str_mv	17
dc.relation.bitstream.none.fl_str_mv	https://revistas.utb.edu.co/tesea/article/download/522/382
dc.relation.citationedition.eng.fl_str_mv	Núm. 2 , Año 2023 : Transactions on Energy Systems and Engineering Applications
dc.relation.citationissue.eng.fl_str_mv	2
dc.rights.uri.eng.fl_str_mv	https://creativecommons.org/licenses/by/4.0
dc.rights.accessrights.eng.fl_str_mv	info:eu-repo/semantics/openAccess
dc.rights.creativecommons.eng.fl_str_mv	This work is licensed under a Creative Commons Attribution 4.0 International License.
dc.rights.coar.eng.fl_str_mv	http://purl.org/coar/access_right/c_abf2
rights_invalid_str_mv	https://creativecommons.org/licenses/by/4.0 This work is licensed under a Creative Commons Attribution 4.0 International License. http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv	openAccess
dc.format.mimetype.eng.fl_str_mv	application/pdf
dc.publisher.eng.fl_str_mv	Universidad Tecnológica de Bolívar
dc.source.eng.fl_str_mv	https://revistas.utb.edu.co/tesea/article/view/522
institution	Universidad Tecnológica de Bolívar
repository.name.fl_str_mv	Repositorio Digital Universidad Tecnológica de Bolívar
repository.mail.fl_str_mv	bdigital@metabiblioteca.com
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spelling	Sierra-Sánchez, AlexandraPaternina-Verona, Duban A. Gatica, GustavoRamos, Helena M.Coronado Hernández, Óscar Enriquevirtual::4629-12023-12-29 13:09:032025-05-21T19:15:47Z2023-12-29 13:09:032023-12-29https://hdl.handle.net/20.500.12585/13514https://doi.org/10.32397/tesea.vol4.n2.52210.32397/tesea.vol4.n2.5222745-0120The calculation of peak discharge in non-instrumented basins requires including morphometric parameters, which in turn depend on the map type used. This study analyses the impact of and variation in peak discharges of the Caño Ricaurte basin, Colombia, based on three types of maps at different resolution scales. The reference map used was the map made for the detailed designs of the channel analysed, which was extracted from the Master Plan of the City. Additionally, maps from a 90 × 90 m digital elevation model and contour lines extracted from Google Earth were used. The time of concentration was determined by different equations (Kirpich, Témez, Bureau, and TR-55) using the mapping methods described above, and the peak discharge was determined using rainfall-runoff models.application/pdfengUniversidad Tecnológica de BolívarAlexandra Sierra-Sánchez, Oscar E. Coronado-Hernandez, Duban A Paternina-Verona, Gustavo Gatica, Helena M. Ramos - 2023https://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessThis work is licensed under a Creative Commons Attribution 4.0 International License.http://purl.org/coar/access_right/c_abf2https://revistas.utb.edu.co/tesea/article/view/522basintime of concentrationpeak flow rateRicaurteCartagenaMappingStatistical Analysis to Quantify the Impact of Map Type on Estimating Peak Discharge in Non-Instrumented BasinsStatistical Analysis to Quantify the Impact of Map Type on Estimating Peak Discharge in Non-Instrumented BasinsArtículo de revistainfo:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Journal articleTextinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/version/c_970fb48d4fbd8a85Fernanda Julia Gaspari, Alfonso Martín Rodríguez Vagaría, Gabriela Elba Senisterra, Gerardo Andrés Denegri, María Isabel Delgado, and Sebastián Ignacio Besteiro. Caracterización morfométrica de la cuenca alta del río sauce grande, buenos aires, argentina. Augm Domus, 4:143–158, 2012. [2] MR Vidal-Abarca, Carlos Montes, ML Suárez, and L Ramirez Diaz. Caracterización morfométrica de la cuenca del río segura: Estudio cuantitativo de las formas de las subcuencas. Papeles de Geografía, (12), 1987. [3] Alejandra M Geraldi, M Piccolo, and Gerardo ME Perillo. Delimitación y estudio de cuencas hidrográficas con modelos hidrológicos. Investigaciones Geográficas (Esp), (52):215–225, 2010. [4] Adán Guillermo Ramírez García, Artemio Cruz León, Pastor Sánchez García, and Alejandro Ismael Monterroso Rivas. La caracterización morfométrica de la subcuenca del río moctezuma, sonora: ejemplo de aplicación de los sistemas de información geográfica. Revista de Geografía Agrícola, (55):27–43, 2015. [5] Rofiat Bunmi Mudashiru, Ismail Abustan, and Fauzi Baharudin. Methods of estimating time of concentration: a case study of urban catchment of sungai kerayong, kuala lumpur. In Proceedings of AICCE’19: Transforming the Nation for a Sustainable Tomorrow 4, pages 119–161. Springer, 2020. [6] Salvatore Grimaldi, Andrea Petroselli, Flavia Tauro, and Maurizio Porfiri. Time of concentration: a paradox in modern hydrology. Hydrological Sciences Journal, 57(2):217–228, 2012. [7] Washington Ramiro Sandoval Erazo and Eduardo Patricio Aguilera Ortiz. Determinación de caudales en cuencas con poco información hidrológica. Ciencia Unemi, 7(12):100–110, 2014. [8] T Bisantino, R Bingner, W Chouaib, F Gentile, and G Trisorio Liuzzi. Estimation of runoff, peak discharge and sediment load at the event scale in a medium-size mediterranean watershed using the annagnps model. Land degradation & development, 26(4):340–355, 2015. [9] Helena M Ramos and Óscar E Coronado-Hernández. Iot, machine learning and photogrammetry in small hydropower towards energy and digital transition: potential energy and viability analyses. Journal of Applied Research in Technology & Engineering, 2023. [10] Ockert J Gericke and Jeff C Smithers. Review of methods used to estimate catchment response time for the purpose of peak discharge estimation. Hydrological sciences journal, 59(11):1935–1971, 2014. [11] Asghar Azizian. Uncertainty analysis of time of concentration equations based on first-order-analysis (foa) method. American Journal of Engineering and Applied Sciences, 11(1):327–341, 2018. [12] Marzieh Mokarram and Majid Hojati. Comparis of digital elevation model (dem) and aerial photographs for drainage. Modeling Earth Systems and Environment, 1:1–6, 2015. [13] Leilei Li, Jintao Yang, and Jin Wu. A method of watershed delineation for flat terrain using sentinel-2a imagery and dem: A case study of the taihu basin. ISPRS International Journal of Geo-Information, 8(12):528, 2019. [14] Zhengqing Lai, Shuo Li, Guonian Lv, Zhirong Pan, and Guosong Fei. Watershed delineation using hydrographic features and a dem in plain river network region. Hydrological Processes, 30(2):276–288, 2016. [15] Marvin E Quesada and Matt Marsik. Uso de modelos de elevación digital como alternativa para mostrar errores en mapas topográficos. Revista Geográfica de América Central, 1(48):77–93, 2012. [16] AB Ariza-Villaverde, FJ Jiménez-Hornero, and E Gutiérrez De Ravé. Influence of dem resolution on drainage network extraction: A multifractal analysis. Geomorphology, 241:243–254, 2015. [17] D. Jiménez. Inundaciones en cartagena: sin soluciones definitivas ni parciales. http://moir.org.co/Inundaciones-en-Cartagena-sin.html [Accessed: June 14, 2016]. [18] Jorge Iván Pérez Alvarino et al. Análisis hidráulico del canal ricaurte como parte del drenaje de aguas lluvias en cartagena de indias mediante la implementación del programa hec-ras 4.1. Título el especialista en recursos hídricos. Universidad de los Andes Departamento de Ingeniería Civil y Ambiental Centro de Investigaciones en Acueductos y Alcantarillados, – CIACUA., 2016. [19] ZP Kirpich. Time of concentration of small agricultural watersheds. Civil engineering, 10(6):362, 1940. [20] Isabel Kaufmann De Almeida, Aleska Kaufmann Almeida, Jamil Alexandre Ayach Anache, Jorge Luiz Steffen, and Teodorico Alves Sobrinho. Estimation on time of concentration of overland flow in watersheds: a review. Geosciences= Geociências, 33(4):661–671, 2014. [21] Roger Cronshey. Urban hydrology for small watersheds. Time of concentration and travel. Number 55. US Department of Agriculture, Soil Conservation Service, Engineering Division, 2nd edition, 1986. pages 29–33. [22] POT (2001). Decreto no 0977 de 2001. http://curaduria2cartagena.com/pdf/POT.pdf [Accessed: March 23, 2021]. [23] Alvaro Gonzalez-Alvarez, Oscar E Coronado-Hernández, Vicente S Fuertes-Miquel, and Helena M Ramos. 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. Fluids, 3(2):27, 2018. [24] Alcaldía Mayor de Cartagena de Indias. Estudios y diseños del plan maestro de drenajes pluviales del distrito de cartagena de indias. https://www.yumpu.com/es/document/view/42121178/plan-maestro-de-drenajes-pluviales-cartagena-parte-1 [Accessed: September 24, 2019]. [25] Departamento Administrativo de Valorización Distrital. Estudios y diseños del plan maestro de drenajes pluviales del distrito de cartagena de indias, 2008.Transactions on Energy Systems and Engineering Applications4117https://revistas.utb.edu.co/tesea/article/download/522/382Núm. 2 , Año 2023 : Transactions on Energy Systems and Engineering Applications2Publication482051d5-f72e-4f5c-ab50-931342cd5b83virtual::4629-1482051d5-f72e-4f5c-ab50-931342cd5b83virtual::4629-120.500.12585/13514oai:repositorio.utb.edu.co:20.500.12585/135142025-06-24 14:46:01.996https://creativecommons.org/licenses/by/4.0Alexandra Sierra-Sánchez, Oscar E. Coronado-Hernandez, Duban A Paternina-Verona, Gustavo Gatica, Helena M. Ramos - 2023metadata.onlyhttps://repositorio.utb.edu.coRepositorio Digital Universidad Tecnológica de Bolívarbdigital@metabiblioteca.com

Statistical Analysis to Quantify the Impact of Map Type on Estimating Peak Discharge in Non-Instrumented Basins

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