Pluvial Flood Detection And Prediction Methods

© 2020 by IJCTT Journal
Volume-68 Issue-11
Year of Publication : 2020
Authors : Idowu, S.A, Adekunle, Y.A, Ayankoya, F.Y, Oladapo K.A
DOI :  10.14445/22312803/IJCTT-V68I11P103

How to Cite?

Idowu, S.A, Adekunle, Y.A, Ayankoya, F.Y, Oladapo K.A, "Pluvial Flood Detection And Prediction Methods," International Journal of Computer Trends and Technology, vol. 68, no. 11, pp. 15-23, 2020. Crossref, 10.14445/22312803/IJCTT-V68I11P103

Pluvial flood is one category of a water-related natural hazard that has caused significant damages. However, the accurate detection and prediction of prone areas are considered difficult due to floods` complex and dynamic nature. In many parts of the world, flood prediction is among the few feasible measures to manage floods. This study applied an integrated review to assess the methodological strategies used in detecting and predicting pluvial flood. The identified literature was analyzed on an appraisal tool. According to the research question, a classification scheme followed this, including the model being used, characteristics, advantages, and limitations. Future directions in research and development were identified in tackling the challenges of managing pluvial flood.

[1] Eleutério, J. (2012). “Flood risk analysis: impact of uncertainty in hazard modeling and vulnerability assessments on damage estimations”. Université de Strasbourg.
[2] Noymanee, J., Nikitin, N. O., & Kalyuzhnaya, A. V. (2017). “Urban Pluvial Flood Forecasting using Open Data with Machine Learning Techniques in Pattani Basin”. Procedia Computer Science, 119(2017), 288–297.
[3] Jha, Abhas K.; Bloch, Robin; Lamond, Jessica. (, 2012). “Cities and Flooding: A Guide to Integrated Urban Flood Risk Management for the 21st Century”. World Bank.
[4] Acosta-Coll, M., Ballester-Merelo, F., Martinez-Peiró, M., & De la Hoz-Franco, E. (2018). “Real-Time Early Warning System Design for Pluvial Flash Floods - A Review”. Sensors (Switzerland), 18(7).
[5] “European Commission and Water Group Floods (WGF). Pluvial Flooding: An EU Overview”. European Commission and Water Group Floods (WGF): Berlin, Germany, 2016.
[6] Rosenzweig, B. R., McPhillips, L., Chang, H., Cheng, C., Welty, C., Matsler, M., … Davidson, C. I. (2018). “Pluvial flood risk and opportunities for resilience”. WIREs Water, 5(6), 1–18.
[7] Houston, D., Werritty, A., Bassett, D., Geddes, A., Hoolachan, A., & McMillan, M. (2011). Pluvial (rain-related) flooding in urban areas: the invisible hazard. (November), 96. Retrieved from
[8] Adelekan, I. O. (2011). “Vulnerability assessment of an urban flood in Nigeria: Abeokuta flood 2007”. Natural Hazards, 56(1), 215–231.
[9] Rözer, V. (2019). “Pluvial flood loss to private households (University of Potsdam)”. Retrieved from
[10] Susana, O.R. (2013). “Urban Pluvial Flood Modelling: Current Theory and Practice”. London, UK.
[11] Environment Agency (2009). “Thames Catchment Flood Management Plan - Chapter 3: Current flood risks and management.” Environment Agency, Bristol, UK. Document available online: Accessed 08.05.2020.
[12] Priest, S. J., Parker, D. J., Hurford, A. P., Walker, J. & Evans, K. (2011). “Assessing options for the development of surface water flood warning in England and Wales”. Journal of Environmental Management, 92 (12), 3038-3048
[13] Bui, D. T., Tsangaratos, P., Ngo, P. T. T., Pham, T. D., & Pham, B. T. (2019). “Flash flood susceptibility modeling using an optimized fuzzy rule-based feature selection technique and tree-based ensemble methods”. Science of the Total Environment, 668, 1038–1054.
[14] Cirella, G., & Iyalomhe, F. (2018). “Flooding Conceptual Review: Sustainability-Focalized Best Practices in Nigeria”. Applied Sciences, 8(9), 1558.
[15] Razavi Termeh, S. V., Kornejady, A., Pourghasemi, H. R., & Keesstra, S. (2018). “Flood susceptibility mapping using novel ensembles of adaptive neuro-fuzzy inference system and metaheuristic algorithms”. Science of the Total Environment, 615, 438–451.
[16] Shivaprasad Sharma, S. V., Roy, P. S., Chakravarthi, V., & Srinivasa Rao, G. (2018). “Flood risk assessment using multi-criteria analysis: A case study from Kopili river basin, Assam, India”. Geomatics, Natural Hazards, and Risk, 9(1), 79–93.
[17] Escuder-Bueno, I., Castillo-Rodriguez, J. T., Zechner, S., Jöbstl, C., Perales-Momparler, S., & Petaccia, G. (2012). “A quantitative flood risk analysis methodology for urban areas with the integration of social research data.” Natural Hazards and Earth System Science, 12(9), 2843–2863.
[18] Nkoana, R. (2011). “Artificial Neural Network Modelling of Flood Prediction and Early Warning”. University of the Free State Bloemfontein.
[19] Oladapo, K.A, Idowu, S.A, Adekunle Y.A, & Ayankoya F.Y (2020). “Categorization of Conditioning Variables for Pluvial Flood Risk Assessment” International Journal of Computer Applications Technology and Research Volume *– No.*, ______ 2020
[20] Nwoko, A. U. (2013). Flooding in Nigerian Cities: Problems and Prospects. A Case Study of Aba Urban, Abia State, Nigeria. Abia State University.
[21] Whittemore, R., & Knafl, K. (2005). “The Integrative Review: Updated Methodology”. Journal of Advanced Nursing, 52(5), 546–553.
[22] Chen, A. S., Djordjevi?, S., Leandro, J., & Savi?, D. A. (2007). “The urban inundation model with bidirectional flow interaction between 2D overland surface and 1D sewer networks”. Novatech, 2007, 465–472.
[23] Lewin, S., Booth, A., Glenton, C., Munthe-Kaas, H., Rashidian, A., Wainwright, M., … Noyes, J. (2018). “Applying GRADE-CERQual to qualitative evidence synthesis findings: introduction to the series”. Implementation Science, 13((Suppl 1):2), 1–10.
[24] Szewra?ski, S., Chrus?in?ki, J., Kazak, J., Swíader, M., Tokarczyk-Dorociak, K., & Zmuda, R. (2018). “Pluvial Flood Risk Assessment Tool (PFRA) for rainwater management and adaptation to climate change in newly urbanized areas”. Water (Switzerland), 10(4), 1–20.
[25] Nkwunonwo, U. C., Whitworth, M., Baily, B., & Inkpen, R. (2014). “The Development of a Simplified Model for Urban Flood Risk Mitigation in Developing Countries.” Vulnerability, Uncertainty, and Risk, American Society of Civil Engineers, (August 2016), 1116–1127.
[26] Zhao, G., Pang, B., Xu, Z., Peng, D., & Xu, L. (2019). “Assessment of urban flood susceptibility using semi-supervised machine learning model”. Science of the Total Environment, 659, 940–949.
[27] Hong, H., Tsangaratos, P., Ilia, I., Liu, J., Zhu, A. X., & Chen, W. (2018). “Application of fuzzy weight of evidence and data mining techniques in constructing the flood susceptibility map of Poyang County, China”. Science of the Total Environment, 625(January), 575–588.
[28] Leitão, J. P., Boonya-aroonnet1, S., Prodanovi, D., & Maksimovi, ?. (2008). “Influence of DEM resolution on surface flow network for pluvial urban flooding and simulations of the integrated system”. 11th International Conference on Urban Drainage, 1–11. Edinburgh, Scotland.
[29] Chang, N. Bin, & Guo, D. H. (2006). “Urban flash flood monitoring, mapping, and forecasting via a tailored sensor network system”. Proceedings of the 2006 IEEE International Conference on Networking, Sensing and Control, ICNSC`06, 757–761.
[30] Garcia, F. C. C., Retamar, A. E., & Javier, J. C. (2016). “A real-time urban flood monitoring system for Metro Manila”. Annual International Conference, Proceedings/TENCON, 3–7.
[31] Llort, X., Sánchez-Diezma, R., Rodríguez, Á., Sancho, D., Berenguer, M., & Sempere-Torres, D. (2014). “FloodAlert: a simplified radar-based EWS for urban flood warning.” Proceedings of the 11th International Conference on Hydroinformatics, 1–8. New York City, USA: HIC.
[32] Siqueira, R. C., Moura1#, P. M., & das Graças Silva, T. F. (2019). “Methodology for the construction of an urban flood hazard chart”. Revista Brasileira de Recursos Hidricos, 24, 1–16.
[33] Hofmann, J., & Schüttrumpf, H. (2019). “Risk-based early warning system for pluvial flash floods: Approaches and foundations”. Geosciences (Switzerland), 9(3).
[34] Fritsch, K., Assmann, A., & Tyrna, B. (2016). “Long-term experiences with pluvial flood risk management”. 3rd European Conference on Flood Risk Management, 7.
[35] Nkwunonwo, U. C., Whitworth, M., & Baily, B. (2019). “Urban flood modeling combining cellular automata framework with semi-implicit finite difference numerical formulation”. Journal of African Earth Sciences, 150(October 2018), 272–281.
[36] Simões, N. E. da C. (2012). Urban Pluvial Flood Forecasting by. Imperial College London.
[37] Hossein, M. R. (2018). “Flood risk assessment using multi-sensor remote sensing, geographic information system”, 2d hydraulic, and machine learning-based models. University of Technology Sydney (UTS), New South Wales, Australia.
[38] Thorndahl, S., Nielsen, J. E., & Jensen, D. G. (2016). “Urban pluvial flood prediction: A case study evaluating radar rainfall nowcasts and numerical weather prediction models as model inputs”. Water Science and Technology, 74(11), 2599–2610.
[39] Verbeiren, B., Seyoum, S. D., Lubbad, I., Xin, T., Veldhuis, M.-C. Ten, Onof, C., … Willems, P. (2018). “FloodCitiSense: Early Warning Service For Urban Pluvial Floods For And By Citizens and City Authorities”. 11th International Conference on Urban Drainage Modelling, 2(September), 96–101.
[40] Ghimire, B., Chen, A. S., Guidolin, M., Keedwell, E. C., Djordjevi?, S., & Savi?, D. A. (2013). “Formulation of a fast 2D urban pluvial flood model using a cellular automata approach”. Journal of Hydroinformatics, 15(3), 676–686.
[41] Chen, A. S., Djordjevic`, S., Leandro, J. & Savic`, D. A. (2010). “An analysis of the combined consequences of pluvial and fluvial flooding”. Water Science and Technology 62, 1491–1498.
[42] Falconer, R. H., Cobby, D., Smyth, P., Astle, G., Dent, J., & Golding, B. (2009). “Pluvial flooding: New approaches in flood warning, mapping, and risk management”. Journal of Flood Risk Management, 2(3), 198–208.
[43] Nkwunonwo, U. C. (2016). “A Review of Flooding and Flood Risk Reduction in Nigeria”. Global Journal of Human-Social Science, 16(2). Retrieved from
[44] Michael, E., & Patience, O. (2018). “Flood Prediction In Nigeria Using Artificial Neural Network.” American Journal of Engineering Research (AJER), 7(9), 15–21. Retrieved from
[45] Oladokun, V. O., & Proverbs, D. (2016). “Flood risk management in Nigeria: A review of the challenges and opportunities.” International Journal of Safety and Security Engineering, 6(3), 485–497.
[46] Choubin, B., Moradi, E., Golshan, M., Adamowski, J., Sajedi-Hosseini, F., & Mosavi, A. (2019). “An ensemble prediction of flood susceptibility using multivariate discriminant analysis, classification and regression trees, and support vector machines.” Science of the Total Environment, 651, 2087–2096.
[47] Nkwunonwo, U. C., Chiemelu, E. N., & Nkwunonwo, U. A. (2016). “Exploring the Inadequacy of Pertinent Capacities for Urban Flood Risk Management in the Developing Countries”. Journal of Social Sciences.
[48] Ayuba, W. T. (2014). “Flood Vulnerability Classification of Lafia Township, Nasarawa State, Nigeria”. International Conference on Earth, Environment and Life Sciences (EELS-2014), Dec. 23 - 24, 134–138.
[49] Orimoogunje, O. O. I., Fashae, O. A., Oke, T. O., & Akinwumiju, A. S. (2016). “Flood Vulnerability in a Part of Southwestern Nigeria”. Academia Journal of Environmental Science, 4(3), 55–61.
[50] Kavitha.R, Kavitha.R, Jayalakshmi .C and Senthil Kumar.K, "Dam Water Level Monitoring and Alerting System using IOT" SSRG International Journal of Electronics and Communication Engineering 5.6 (2019): 19-22.
[51] Seyoum, S., Willems, P., & Verbeiren, B. (2019). “Data-Driven Models for Pluvial Flood Forecasting in Brussels”. NOVATECH, 1–4. Stormwater and Urban Planning.
[52] Barroca, B., Bernardara, P., Mouchel, J. M., & Hubert, G. (2006). “Indicators for the identification of urban flooding vulnerability”. Natural Hazards and Earth System Sciences, 6(4), 553–561.
[53] Ologunorisa, T. E., & Abawua, M. J. (2005). “Flood Risk Assessment: A Review”. J. Appl. Sci. Environ. Mgt., 9(1), 57–63. Retrieved from

Pluvial Flood, Detection, Prediction, CERQual Tool, Classification Scheme