Forecasting and communication key elements for low-cost fluvial flooding early warning system in urban areas
Fluvial flooding occurs when a river overspills its banks due to excessive rainfall, and it is the most common flood event. In urban areas, the increment of urbanization makes communities more susceptible to fluvial flooding since the excess of impervious surfaces reduced the natural permeable areas...
- Autores:
-
Acosta-Coll, Melisa
Solano-Escorcia, Andres
Ortega-Gonzalez, Lilia
Zamora-Musa, Ronald
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2021
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/8439
- Acceso en línea:
- https://hdl.handle.net/11323/8439
http://doi.org/10.11591/ijece.v11i5.pp4143-4156
https://repositorio.cuc.edu.co/
- Palabra clave:
- Disemination
Early warning system
Fluvial flooding
Forecasting
LoRaWAN
Zigbee
- Rights
- openAccess
- License
- Attribution-NonCommercial-NoDerivatives 4.0 International
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Forecasting and communication key elements for low-cost fluvial flooding early warning system in urban areas |
| title |
Forecasting and communication key elements for low-cost fluvial flooding early warning system in urban areas |
| spellingShingle |
Forecasting and communication key elements for low-cost fluvial flooding early warning system in urban areas Disemination Early warning system Fluvial flooding Forecasting LoRaWAN Zigbee |
| title_short |
Forecasting and communication key elements for low-cost fluvial flooding early warning system in urban areas |
| title_full |
Forecasting and communication key elements for low-cost fluvial flooding early warning system in urban areas |
| title_fullStr |
Forecasting and communication key elements for low-cost fluvial flooding early warning system in urban areas |
| title_full_unstemmed |
Forecasting and communication key elements for low-cost fluvial flooding early warning system in urban areas |
| title_sort |
Forecasting and communication key elements for low-cost fluvial flooding early warning system in urban areas |
| dc.creator.fl_str_mv |
Acosta-Coll, Melisa Solano-Escorcia, Andres Ortega-Gonzalez, Lilia Zamora-Musa, Ronald |
| dc.contributor.author.spa.fl_str_mv |
Acosta-Coll, Melisa Solano-Escorcia, Andres Ortega-Gonzalez, Lilia Zamora-Musa, Ronald |
| dc.subject.spa.fl_str_mv |
Disemination Early warning system Fluvial flooding Forecasting LoRaWAN Zigbee |
| topic |
Disemination Early warning system Fluvial flooding Forecasting LoRaWAN Zigbee |
| description |
Fluvial flooding occurs when a river overspills its banks due to excessive rainfall, and it is the most common flood event. In urban areas, the increment of urbanization makes communities more susceptible to fluvial flooding since the excess of impervious surfaces reduced the natural permeable areas. As flood prevention strategies, early warning systems (EWS) are used to reduce damage and protect people, but key elements need to be selected. This manuscript proposes the monitoring instruments, communication protocols, and media to forecast and disseminate EWS alerts efficiently during fluvial floods in urban areas. First, we conducted a systematic review of different EWS architectures for fluvial floods in urban areas and identified that not all projects monitor the most important variables related to the formation of fluvial floods and most use communication protocols with high-energy consumption.ZigBee and LoRaWAN are the communication protocols with lower power consumption from the review, and to determine which technology has better performance in urban areas, two wireless sensor networks were deployed and simulated in two urban areas susceptible to fluvial floods using Radio Mobile software. The results showed that although Zigbee technology has better-received signal strength, the difference with LoRAWAN is lower than 2dBm, but LoRaWAN has a better signal-to-noise ratio, power consumption, coverage, and deployment cost. |
| publishDate |
2021 |
| dc.date.accessioned.none.fl_str_mv |
2021-06-29T21:42:37Z |
| dc.date.available.none.fl_str_mv |
2021-06-29T21:42:37Z |
| dc.date.issued.none.fl_str_mv |
2021 |
| dc.type.spa.fl_str_mv |
Artículo de revista |
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http://purl.org/coar/resource_type/c_2df8fbb1 |
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Text |
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info:eu-repo/semantics/article |
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http://purl.org/redcol/resource_type/ART |
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info:eu-repo/semantics/acceptedVersion |
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acceptedVersion |
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https://hdl.handle.net/11323/8439 |
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http://doi.org/10.11591/ijece.v11i5.pp4143-4156 |
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Corporación Universidad de la Costa |
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REDICUC - Repositorio CUC |
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https://repositorio.cuc.edu.co/ |
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https://hdl.handle.net/11323/8439 http://doi.org/10.11591/ijece.v11i5.pp4143-4156 https://repositorio.cuc.edu.co/ |
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Corporación Universidad de la Costa REDICUC - Repositorio CUC |
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eng |
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eng |
| dc.relation.references.spa.fl_str_mv |
CRED and UNISDR, “The Human Cost of Weather Related Disasters 1995-2015,” 2015.[Online]. Available: https://www.unisdr.org/files/46796_cop21weatherdisastersreport2015.pdf. International Strategy for Disaster Reduction (ISDR), “Emerging Challenges for Early Warning Systems in context of Climate Change and Urbanization,” Switzerland, 2010. [Online]. Available: http://www.preventionweb.net/ files/15689_ewsincontextofccandurbanization.pdf. J. D. Miller and M. Hutchins, “The impacts of urbanisation and climate change on urban flooding and urban water quality: A review of the evidence concerning the United Kingdom,” J. Hydrol. Reg. Stud., vol. 12, pp. 345–362, 2017, doi: 10.1016/j.ejrh.2017.06.006. H. Apel, O. M. Trepat, N. N. Hung, D. T. Chinh, B. Merz, and N. V. Dung, “Combined fluvial and pluvial urban flood hazard analysis: Concept development and application to Can Tho city, Mekong Delta, Vietnam,” Natural Hazards and Earth System Sciences.,vol. 16, no. 4, pp. 941–961, 2016, doi: 10.5194/nhess-16-941-2016. World Resources Institute (WRI), “World’s 15 Countries with the Most People Exposed to River Floods,” 2015. [Online]. Available: https://www.wri.org/blog/2015/03/world-s-15-countries-most-people-exposed-river-floods. CRED, “Natural Disasters,” 2015. [Online]. Available: https://www.emdat.be/. S. Bae and H. Chang, “Urbanization and floods in the Seoul Metropolitan area of South Korea: What old maps tell us,” Int. J. Disaster Risk Reduct., vol. 37, Jul.,2019, Art. No. 101186, doi: 10.1016/j.ijdrr.2019.101186. J. Du, L. Cheng, Q. Zhang, Y. Yang, and W. Xu, “Different Flooding Behaviors Due to Varied Urbanization Levels within River Basin: A Case Study from the Xiang River Basin, China,” Int. J. Disaster Risk Sci, vol. 10, pp. 89–102, 2019, doi: 10.1007/s13753-018-0195-4. Y. Anker et al., “Effect of rapid urbanization on Mediterranean karstic mountainous drainage basins,” Sustain. Cities Soc., vol. 51, Nov. 2019, Art. No. 101704, doi: 10.1016/j.scs.2019.101704. UNDESA, “World Population Prospects. The 2017 Revision. Key Findings and Advance Tables,” United Nations Department of Economic and Social Affairs, New York, ESA/P/WP/248, 2017. [Online]. Available: https://population.un.org/wpp/Publications/Files/WPP2017_KeyFindings.pdf. S. J. McGrane, “Impacts of urbanisation on hydrological and water quality dynamics, and urban water management: a review,” Hydrol. Sci. J., vol. 61, no. 13, pp. 2295–2311, 2016, doi: 10.1080/02626667.2015.1128084. World Meteorological Organization, “Guidelines on Early Warning Systems and Application of Nowcasting and Warning Operations,” 2010. [Online]. Available: https://library.wmo.int/doc_num.php?explnum_id=9456. M. Acosta-Coll, F. Ballester-Merelo, and M. Martinez-Peiro, “Early warning system for detection of urban pluvial flooding hazard levels in an ungauged basin,” Nat. Hazards, vol. 92, pp. 1237–1265, 2018, doi: 10.1007/s11069-018-3249-4. M. Acosta-Coll, F. Ballester-Merelo, M. Martinez-Peiro, and E. de la Hoz-Franco, “Real-Time Early Warning System Design for Pluvial Flash Floods—A Review,” Sensors, vol. 18, no. 7, 2018, Art. No. 2255, doi: 10.3390/s18072255. S. E. Shumate, “Longley-Rice and ITU-P.1546 Combined: A New International Terrain-Specific Propagation Model,” 2010 IEEE 72nd Vehicular Technology Conference,Ottawa, Canada, 2010, pp. 1–5, doi: 10.1109/VETECF.2010.5594342. Gobernación del Atlántico, “Plan de Desarrollo 2020-2023,” Gobernación del Atlántico, Colombia, 2020. [Online]. Available:https://www.atlantico.gov.co/images/stories/plan_desarrollo/PlanDesarrollo_2020-2023-Definitivo-A1.pdf. F. C. C. Garcia, A. E. Retamar, and J. C. Javier, “Development of a predictive model for on-demandremote river level nowcasting: Case study in Cagayan River Basin, Philippines,” 2016 IEEE Region 10 Conference (TENCON), Singapore, 2016, pp. 3275–3279, doi: 10.1109/TENCON.2016.7848657. V. Balaji, A. Akshaya, N. Jayashree, and T. Karthika, “Design of ZigBee based wireless sensor network for early flood monitoring and warning system,” in 2017 IEEE Technological Innovations in ICT for Agriculture and Rural Development (TIAR), Chennai, 2017, pp. 236–240, doi: 10.1109/TIAR.2017.8273723. H. N. Do, M. Vo, V. Tran, P. V. Tan, and C. V. Trinh, “An early flood detection system using mobile networks,” in 2015 International Conference on Advanced Technologies for Communications (ATC), Ho Chi Minh, Vietnam, 2015, pp. 599–603, doi: 10.1109/ATC.2015.7388400. A. Dersingh, “Design and development of a flood warning system via mobile and computer networks,” in 2016 International Conference on Electronics, Information, and Communications (ICEIC), Danang, Vietnam, 2016, pp. 1–4, doi: 10.1109/ELINFOCOM.2016.7563023. V. Vunabandi, R. Matsunaga, S. Markon, and N. Willy, “Flood sensing framework by Arduino and Wireless Sensor Network in Rural-Rwanda,” in 2015 IEEE/ACIS 16th International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD), Takamatsu, 2015, pp. 1–6, doi: 10.1109/SNPD.2015.7176210. M. A. Islam, T. Islam, M. A. Syrus, and N. Ahmed, “Implementation of flash flood monitoring system based on wireless sensor network in Bangladesh,” in 2014 International Conference on Informatics, Electronics & Vision (ICIEV), Dhaka, Bangladesh, 2014, pp. 1–6, doi: 10.1109/ICIEV.2014.6850752. F. Khan, S. Memon, I. A. Jokhio, and S. H. Jokhio, “Wireless sensor network based flood/drought forecasting system,” in 2015 IEEE SENSORS, Busan, 2015, pp. 1–4, doi: 10.1109/ICSENS.2015.7370354. E. Leon, C. Alberoni, M. Wister, and J. A. Hernandez-Nolasco, “Flood Early Warning System by Twitter Using LoRa,” Proceedings, vol. 2, no. 19,2018, Art. No. 1213, doi: 10.3390/proceedings2191213. J. D. Guillot, C. A. Robles, and J. D. Callejas, “Adquisición de Señales Ambientales para un Sistema de Alerta Temprana,” Inf. Tecnológica, vol. 28, no. 5, pp. 45–54, 2017, doi: 10.4067/S0718-07642017000500007. R. Castillo and J. C. Espitia, “Caracterización de zonas de riesgo por crecientes de ríos de bajo caudal, para la implementación de un sistema de alertas tempranas (SAT) con tecnología LoRa y LoRaWAN,” Inf. Tecnológica, vol. 31, no. 2, pp. 47–54, 2020, doi: 10.4067/S0718-07642020000200047. L. Kolobe, B. Sigweni, and C. K. Lebekwe, “Systematic literature survey: applications of LoRa communication,” International Journal of Electrical and Computer Engineering(IJECE),vol. 10, no. 3, pp. 3176–3183, 2020, doi: 10.11591/ijece.v10i3.pp3176-3183 E. Ramirez-Cerpa, M. Acosta-Coll, and J. Velez-Zapata, “Análisis de condiciones climatológicas de precipitaciones de corto plazo en zonas urbanas: caso de estudio Barranquilla, Colombia,” Rev. IDESIA, vol. 35, no. 2, pp. 87–94, 2017, doi: 10.4067/S0718-34292017005000023. R. Lam et al., “Urban disaster preparedness of Hong Kong residents: A territory-wide survey,” Int J Disaster Risk Reduct, vol. 23, pp. 62–69, 2017, doi: 10.1016/j.ijdrr.2017.04.008. |
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Acosta-Coll, Melisa2d3f71f9a5df5bbb04417bc9f0a62e97Solano-Escorcia, Andres5e38c730e8c8621b0bae1c946ccfee07Ortega-Gonzalez, Lilia7bb466c7e2bd1130d0f7700779c9a286Zamora-Musa, Ronald555bf306ab5e4c15af82a7146021ef522021-06-29T21:42:37Z2021-06-29T21:42:37Z2021https://hdl.handle.net/11323/8439http://doi.org/10.11591/ijece.v11i5.pp4143-4156Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/Fluvial flooding occurs when a river overspills its banks due to excessive rainfall, and it is the most common flood event. In urban areas, the increment of urbanization makes communities more susceptible to fluvial flooding since the excess of impervious surfaces reduced the natural permeable areas. As flood prevention strategies, early warning systems (EWS) are used to reduce damage and protect people, but key elements need to be selected. This manuscript proposes the monitoring instruments, communication protocols, and media to forecast and disseminate EWS alerts efficiently during fluvial floods in urban areas. First, we conducted a systematic review of different EWS architectures for fluvial floods in urban areas and identified that not all projects monitor the most important variables related to the formation of fluvial floods and most use communication protocols with high-energy consumption.ZigBee and LoRaWAN are the communication protocols with lower power consumption from the review, and to determine which technology has better performance in urban areas, two wireless sensor networks were deployed and simulated in two urban areas susceptible to fluvial floods using Radio Mobile software. The results showed that although Zigbee technology has better-received signal strength, the difference with LoRAWAN is lower than 2dBm, but LoRaWAN has a better signal-to-noise ratio, power consumption, coverage, and deployment cost.application/pdfengAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2International Journal of Electrical and Computer Engineeringhttp://ijece.iaescore.com/index.php/IJECE/article/view/25405DiseminationEarly warning systemFluvial floodingForecastingLoRaWANZigbeeForecasting and communication key elements for low-cost fluvial flooding early warning system in urban areasArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/acceptedVersionCRED and UNISDR, “The Human Cost of Weather Related Disasters 1995-2015,” 2015.[Online]. Available: https://www.unisdr.org/files/46796_cop21weatherdisastersreport2015.pdf.International Strategy for Disaster Reduction (ISDR), “Emerging Challenges for Early Warning Systems in context of Climate Change and Urbanization,” Switzerland, 2010. [Online]. Available: http://www.preventionweb.net/ files/15689_ewsincontextofccandurbanization.pdf.J. D. Miller and M. Hutchins, “The impacts of urbanisation and climate change on urban flooding and urban water quality: A review of the evidence concerning the United Kingdom,” J. Hydrol. Reg. Stud., vol. 12, pp. 345–362, 2017, doi: 10.1016/j.ejrh.2017.06.006.H. Apel, O. M. Trepat, N. N. Hung, D. T. Chinh, B. Merz, and N. V. Dung, “Combined fluvial and pluvial urban flood hazard analysis: Concept development and application to Can Tho city, Mekong Delta, Vietnam,” Natural Hazards and Earth System Sciences.,vol. 16, no. 4, pp. 941–961, 2016, doi: 10.5194/nhess-16-941-2016.World Resources Institute (WRI), “World’s 15 Countries with the Most People Exposed to River Floods,” 2015. [Online]. Available: https://www.wri.org/blog/2015/03/world-s-15-countries-most-people-exposed-river-floods.CRED, “Natural Disasters,” 2015. [Online]. Available: https://www.emdat.be/.S. Bae and H. Chang, “Urbanization and floods in the Seoul Metropolitan area of South Korea: What old maps tell us,” Int. J. Disaster Risk Reduct., vol. 37, Jul.,2019, Art. No. 101186, doi: 10.1016/j.ijdrr.2019.101186.J. Du, L. Cheng, Q. Zhang, Y. Yang, and W. Xu, “Different Flooding Behaviors Due to Varied Urbanization Levels within River Basin: A Case Study from the Xiang River Basin, China,” Int. J. Disaster Risk Sci, vol. 10, pp. 89–102, 2019, doi: 10.1007/s13753-018-0195-4.Y. Anker et al., “Effect of rapid urbanization on Mediterranean karstic mountainous drainage basins,” Sustain. Cities Soc., vol. 51, Nov. 2019, Art. No. 101704, doi: 10.1016/j.scs.2019.101704.UNDESA, “World Population Prospects. The 2017 Revision. Key Findings and Advance Tables,” United Nations Department of Economic and Social Affairs, New York, ESA/P/WP/248, 2017. [Online]. Available: https://population.un.org/wpp/Publications/Files/WPP2017_KeyFindings.pdf.S. J. McGrane, “Impacts of urbanisation on hydrological and water quality dynamics, and urban water management: a review,” Hydrol. Sci. J., vol. 61, no. 13, pp. 2295–2311, 2016, doi: 10.1080/02626667.2015.1128084.World Meteorological Organization, “Guidelines on Early Warning Systems and Application of Nowcasting and Warning Operations,” 2010. [Online]. Available: https://library.wmo.int/doc_num.php?explnum_id=9456.M. Acosta-Coll, F. Ballester-Merelo, and M. Martinez-Peiro, “Early warning system for detection of urban pluvial flooding hazard levels in an ungauged basin,” Nat. Hazards, vol. 92, pp. 1237–1265, 2018, doi: 10.1007/s11069-018-3249-4.M. Acosta-Coll, F. Ballester-Merelo, M. Martinez-Peiro, and E. de la Hoz-Franco, “Real-Time Early Warning System Design for Pluvial Flash Floods—A Review,” Sensors, vol. 18, no. 7, 2018, Art. No. 2255, doi: 10.3390/s18072255.S. E. Shumate, “Longley-Rice and ITU-P.1546 Combined: A New International Terrain-Specific Propagation Model,” 2010 IEEE 72nd Vehicular Technology Conference,Ottawa, Canada, 2010, pp. 1–5, doi: 10.1109/VETECF.2010.5594342.Gobernación del Atlántico, “Plan de Desarrollo 2020-2023,” Gobernación del Atlántico, Colombia, 2020. [Online]. Available:https://www.atlantico.gov.co/images/stories/plan_desarrollo/PlanDesarrollo_2020-2023-Definitivo-A1.pdf.F. C. C. Garcia, A. E. Retamar, and J. C. Javier, “Development of a predictive model for on-demandremote river level nowcasting: Case study in Cagayan River Basin, Philippines,” 2016 IEEE Region 10 Conference (TENCON), Singapore, 2016, pp. 3275–3279, doi: 10.1109/TENCON.2016.7848657.V. Balaji, A. Akshaya, N. Jayashree, and T. Karthika, “Design of ZigBee based wireless sensor network for early flood monitoring and warning system,” in 2017 IEEE Technological Innovations in ICT for Agriculture and Rural Development (TIAR), Chennai, 2017, pp. 236–240, doi: 10.1109/TIAR.2017.8273723.H. N. Do, M. Vo, V. Tran, P. V. Tan, and C. V. Trinh, “An early flood detection system using mobile networks,” in 2015 International Conference on Advanced Technologies for Communications (ATC), Ho Chi Minh, Vietnam, 2015, pp. 599–603, doi: 10.1109/ATC.2015.7388400.A. Dersingh, “Design and development of a flood warning system via mobile and computer networks,” in 2016 International Conference on Electronics, Information, and Communications (ICEIC), Danang, Vietnam, 2016, pp. 1–4, doi: 10.1109/ELINFOCOM.2016.7563023.V. Vunabandi, R. Matsunaga, S. Markon, and N. Willy, “Flood sensing framework by Arduino and Wireless Sensor Network in Rural-Rwanda,” in 2015 IEEE/ACIS 16th International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD), Takamatsu, 2015, pp. 1–6, doi: 10.1109/SNPD.2015.7176210.M. A. Islam, T. Islam, M. A. Syrus, and N. Ahmed, “Implementation of flash flood monitoring system based on wireless sensor network in Bangladesh,” in 2014 International Conference on Informatics, Electronics & Vision (ICIEV), Dhaka, Bangladesh, 2014, pp. 1–6, doi: 10.1109/ICIEV.2014.6850752.F. Khan, S. Memon, I. A. Jokhio, and S. H. Jokhio, “Wireless sensor network based flood/drought forecasting system,” in 2015 IEEE SENSORS, Busan, 2015, pp. 1–4, doi: 10.1109/ICSENS.2015.7370354.E. Leon, C. Alberoni, M. Wister, and J. A. Hernandez-Nolasco, “Flood Early Warning System by Twitter Using LoRa,” Proceedings, vol. 2, no. 19,2018, Art. No. 1213, doi: 10.3390/proceedings2191213.J. D. Guillot, C. A. Robles, and J. D. Callejas, “Adquisición de Señales Ambientales para un Sistema de Alerta Temprana,” Inf. Tecnológica, vol. 28, no. 5, pp. 45–54, 2017, doi: 10.4067/S0718-07642017000500007.R. Castillo and J. C. Espitia, “Caracterización de zonas de riesgo por crecientes de ríos de bajo caudal, para la implementación de un sistema de alertas tempranas (SAT) con tecnología LoRa y LoRaWAN,” Inf. Tecnológica, vol. 31, no. 2, pp. 47–54, 2020, doi: 10.4067/S0718-07642020000200047.L. Kolobe, B. Sigweni, and C. K. Lebekwe, “Systematic literature survey: applications of LoRa communication,” International Journal of Electrical and Computer Engineering(IJECE),vol. 10, no. 3, pp. 3176–3183, 2020, doi: 10.11591/ijece.v10i3.pp3176-3183E. Ramirez-Cerpa, M. Acosta-Coll, and J. Velez-Zapata, “Análisis de condiciones climatológicas de precipitaciones de corto plazo en zonas urbanas: caso de estudio Barranquilla, Colombia,” Rev. IDESIA, vol. 35, no. 2, pp. 87–94, 2017, doi: 10.4067/S0718-34292017005000023.R. Lam et al., “Urban disaster preparedness of Hong Kong residents: A territory-wide survey,” Int J Disaster Risk Reduct, vol. 23, pp. 62–69, 2017, doi: 10.1016/j.ijdrr.2017.04.008.ORIGINALForecasting and communication key elements for low-cost fluvial flooding early warning system in urban areas.pdfForecasting and communication key elements for low-cost fluvial flooding early warning system in urban areas.pdfapplication/pdf1021777https://repositorio.cuc.edu.co/bitstream/11323/8439/1/Forecasting%20and%20communication%20key%20elements%20for%20low-cost%20fluvial%20flooding%20early%20warning%20system%20in%20urban%20areas.pdf22b139789caf0ae7d3579f410e3a631aMD51open accessCC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8805https://repositorio.cuc.edu.co/bitstream/11323/8439/2/license_rdf4460e5956bc1d1639be9ae6146a50347MD52open accessLICENSElicense.txtlicense.txttext/plain; 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