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Real-time river level estimation based on variations of radar reflectivity—a case study of the Quitandinha River watershed, Petrópolis, Rio de Janeiro (Brazil)

Bulletin of Atmospheric Science and Technology volume 2, Article number: 1 (2021) Cite this article

Abstract

The real-time warning for flash floods represents one of the major challenges for monitoring centers and civil defenses due to the short time frame in which such phenomena occur. That situation often takes place particularly in mountainous regions where high slope rate favors an increase in the velocity of the water flow and it might generate conditions to impact the water level due to potential for provoking erosion, landslides, and debris flow. An initial one new and unique prototype of hydrometeorological relationship for real-time, site-tunable, water level for flash flood prediction is presented. Time variations of the reflectivity measured by horizontal polarization radar are evaluated and correlated to generate the local estimate of the elevation of the Quitandinha River water level for the next hour. The proposal of this relationship is not intended to act as a simplified hydraulic model but to characterize if a critical elevation of the water level could be obtained from the radar reflectivity data and consequently whether the flash flooding event should be expected. We verified that the proposed relationship that tended to underestimate the water level peaks, however, qualitatively was initially able to indicate if a flood event could occur or not in the next hour. The expectation related to this initial relationship is to improve the obtained results in order to be used as a tool for decision-making in relation to the issuance of warnings delivered by environmental monitoring centers.

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References

  • Abboud IA, Nofal RA (2017) Morphometric analysis of Wadi Khumal basin, western coast of Saudi Arabia, using remote sensing and GIS techniques. J Afr Earth Sci 126(November):58–74. https://doi.org/10.1016/j.jafrearsci.2016.11.024

    Article  Google Scholar 

  • Alfieri L, Thielen J, Pappenberger F (2012) Ensemble hydrometeorological simulation for flash flood early detection in southern Switzerland. J Hydrol 424–425:143–153. https://doi.org/10.1016/j.jhydrol.2011.12.038

    Article  Google Scholar 

  • Bahiense JM, Júnior JEFF, Costa LF, Charge LT (2015) Monitoramento hidrológico quantitativo no estado do Rio de Janeiro: Importância, histórico e modernização. http://www.evolvedoc.com.br/sbrh/detalhes-991. Acessed 03 Jan 2016

  • Baldwin ME, Kain JS (2006) Sensitivity of several performance measures to displacement error, bias, and event frequency. Wea. Forecasting 21:636–648

  • Battan LJ (1973) Radar observation of the atmosphere. Univ. of Chicago Press, Chicago

    Google Scholar 

  • Bell VA, Moore RJ (2000) The sensitivity of catchment runoff models to rainfall data at different spatial scales. Hydrol Earth Syst Sci 4:653–667

    Article  Google Scholar 

  • Berenguer M, Corral C, Sanchez-Diesma R, Sempere-Torres D (2005) Hydrological validation of a radar-based nowcasting technique. J Hydrometeorol 6:532–549

    Article  Google Scholar 

  • Bernet DB, Prasuhn V, Weingartner R (2017) Surface water floods in Switzerland: what insurance claim records tell us about the damage in space and time. Nat Hazards Earth Syst Sci 17:1659–1682. https://doi.org/10.5194/nhess-17-1659-2017

    Article  Google Scholar 

  • Bolshakov V (2013) “Regression-based Daugava River flood forecasting and monitoring,” in Scientific Journal of RTU, Series 5, Computer Science

  • Borga M, Boscolo P, Zanon F, Sangati M (2007) Hydrometeorological analysis of the August 29, 2003 flash flood in the eastern Italian Alps. J Hydrometeorol 8:1049–1067

    Article  Google Scholar 

  • Borga M, Gaume E, Creutin JD, Marchi L (2008) Surveying flash flood response: gauging the ungauged extremes. Hydrol Process 22:3883–3885

    Article  Google Scholar 

  • Buzzi A, Davoilio S, Malguzzi P, Drofa O, Mastrangelo D (2013) Heavy rainfall episodes over Liguria of autumn 2011: numerical forecasting experiments. Nat Hazards Earth Syst Sci Discuss 1:7093–7135

    Google Scholar 

  • Cataneo R (1969) A method for estimating rainfall rate-radar reflectivity relationships. J Appl Meteorol 8:815–819

    Article  Google Scholar 

  • Creutin JD, Borga M (2003) Radar hydrology modifies the monitoring of flash flood hazard. Hydrol Process 17(7):1453–1456

    Article  Google Scholar 

  • Cunning JB, Sax I (1977) A Z–R relationship for the GATE B-scale array. Mon Weather Rev 105:1330–1336

    Article  Google Scholar 

  • Demargne J, Mullusky M, Werner K, Adams T, Lindsey S, Schwein N, Marosi W, Welles E (2009) Application of forecast verification science to operational river forecasting in the U.S. National Weather Service. Bull Am Meteorol Soc 90:779–784

    Article  Google Scholar 

  • Devia GK, Ganasri BP, Dwarakish GS (2015) A review on hydrological models. Aquati Procedia 4:1001–1007. https://doi.org/10.1016/j.aqpro.2015.02.126

  • Done J, Davis CA, Weisman M (2004) The next generation of NWP: 707 explicit forecasts of convection using the weather research and forecasting (WRF) model. Atmos Sci Lett 5(6):110–117

    Article  Google Scholar 

  • Durocher M, Chebana F, Ouarda TBMJ (2015) A nonlinear approach to regional flood frequency analysis using projection pursuit regression. J Hydrometeorol 16:1561–1574. https://doi.org/10.1175/JHM-D-14-0227.1

    Article  Google Scholar 

  • Federico S, Petracca M, Panegrossi G, Dietrich S (2017) Improvement of RAMS precipitation forecast at the short-range through lightning data assimilation. Nat Hazards Earth Syst Sci 17:61–76. https://doi.org/10.5194/nhess-17-61-2017

    Article  Google Scholar 

  • Gaume E, Borga M (2008) Post-flood field investigations in upland catchments after major flash floods: proposal of a methodology and illustrations. J Flood Risk Manag 1:175–189

    Article  Google Scholar 

  • Gerl T, Kreibich H, Franco G, Marechal D, Schröter K (2016) A review of flood loss models as basis for harmonization and benchmarking. PLoS One 11(7). https://doi.org/10.1371/journal.pone.0159791

  • Gourley JJ, Hong Y, Flamig ZL, Arthur A, Clark R, Calianno M, Ruin I, Ortel T, Wieczorek ME, Kirstetter PE, Clark E, Krajewski WF (2013) A unified flash flood database over the United States. Bull Am Meteorol Soc 94:799–805. https://doi.org/10.1175/BAMS-D-12-00198.1

    Article  Google Scholar 

  • GRASS Development Team (2017) Geographic Resources Analysis Support System (GRASS) software, version 7.2. Open Source Geospatial Foundation. Electronic document: http://grass.osgeo.org. Accessed 16 May 2020

  • Horton RE (1945) Erosional development of streams and their drainage basins; hydrophysical approach to quantitative morphology. Geol Soc Am Bull 56:275–370

  • INEA (2020) Instituto Estadual do Ambiente. http://www.inea.rj.gov.br. Acessed 16 May 2020

  • Jain SK, Mani P, Jain SK, Prakash P, Singh VP, Tullos D, Kumar S, Agarwal SP, Dimri AP (2018) A brief review of flood forecasting techniques and their applications. Int J River Basin Man 16:329–344. https://doi.org/10.1080/15715124.2017.1411920

    Article  Google Scholar 

  • Javelle P, Demargne J, Defrance D, Pansu J, Arnaud P (2014) Evaluating flash-flood warnings at ungauged locations using post-event surveys: a case study with the AIGA warning system. Hydrol Sci J 59:1390–1402

    Article  Google Scholar 

  • Jongman B, Kreibich H, Apel H, Barredo JI, Bates PD, Feyen L, Ward PJ (2012) Comparative flood damage 20 model assessment: towards a European approach. Nat Hazards Earth Syst Sci 12(12):3733–3752. https://doi.org/10.5194/nhess-12-3733-2012

    Article  Google Scholar 

  • Kain S, Weiss J, Levit JJ, Baldwin ME, Bright DR (2006) Examination of convection-allowing configurations of the WRF model for the prediction of severe convective weather. Weather Forecast 2006(21):167–181

    Article  Google Scholar 

  • Kumar LS, Lee YH, Yeo JX, Ong JT (2011) Tropical rain classification and estimation of rain from Z-R (reflectivity - rain rate) relationships. Progress in Electromagnetics Research 32:107–127

  • Krajewski W, Ceynar D, Demir I, Goska R, Kruger A, Lan-gel C, Mantilla R, Niemeier J, Quintero F, Seo B, Small S, Weber L, Young N (2017) Real-time flood forecasting and information system for the state of Iowa. Bull Am Meteorol Soc 98(3):539–554. https://doi.org/10.1175/BAMS-D-15-00243.1

    Article  Google Scholar 

  • Lumbroso DM, Gaume E (2012) Reducing the uncertainty in indirect estimates of extreme flash flood discharges. J Hydrol 414–415:16–30

    Article  Google Scholar 

  • Magesh NS, Chandrasekar N, Soundranayagam JP (2011) Morphometric evaluation of Papanasam and Manimuthar watersheds, parts of Western Ghats, Tirunelveli district, Tamil Nadu, India: a GIS approach. Environ Earth Sci 64(2):373–381

  • Marshall JP, Palmer WM (1948) The distribution of raindrops with size. J Meteor 5:165–166

  • Mendoza PA, McPhee J, Vargas X (2012) Uncertainty in flood forecasting: a distributed modeling approach in a sparse data catchment. Water Resour Res 48:W09532. https://doi.org/10.1029/2011wr011089

    Article  Google Scholar 

  • Miyoshi T, Kunii M, Ruiz J, Lien GY, Satoh S, Ushio T, Bessho K, Seko H, Tomita H, Ishikawa Y (2016) “Big data assimilation” revolutionizing severe weather prediction. Bull Am Meteorol Soc 97:1347–1354

    Article  Google Scholar 

  • Patel S, Hardaha MK, Mukesh K, Seetpal K, Madankar K (2016) Multiple linear regression model for stream flow estimation of Wainganga River. Am J Water Sci Eng 2(1):1–5

    Google Scholar 

  • Pattanaik DR, Mukhopadhyay B, Kumar A (2012) Monthly forecast of Indian Southwest monsoon rainfall based on NCEP’s coupled forecast system. Atmos Clim Sci 2:479–491

    Google Scholar 

  • Penny SG, Hamill TM (2017) Coupled data assimilation for integrated earth system analysis and prediction. Bull Am Meteorol Soc 98:ES169–ES172

    Article  Google Scholar 

  • Rai KP, Narayan V, Mohan K (2017) Remote Sensing Applications : Society and Environment. A study of morphometric evaluation of the Son basin , India using geospatial approach. Remote Sens Appl: Soc Environ 7:9–20. https://doi.org/10.1016/j.rsase.2017.05.001

    Article  Google Scholar 

  • Raynaud D, Thielen J, Salamon P, Burek P, Anquetin S, Alfieri L (2015) A dynamic runoff co-efficient to improve flash flood early warning in Europe: evaluation on the 2013 central European floods in Germany. Meteorol Appl 22:410–418

    Article  Google Scholar 

  • Reddy OGP, Maji AK, Gajbhiye SK (2004) Drainage morphometry and its influence on landform characteristics in a basaltic terrain, Central India—a remote sensing and GIS approach. Int J Appl Earth Obs Geoinformatics 6:1–16

  • Rossa AM, Del Guerra FL, Borga M, Zanon F, Settin T, Leuenberger D (2010) Radardriven high-resolution hydrometeorological forecasts of the 26 September 2007 Venice flash flood. J Hydrol 2010(394):230–244. https://doi.org/10.1016/j.jhydrol.2010.08.035

    Article  Google Scholar 

  • Ruiz-Villanueva V, Díez-Herrero A, Stoffel M, Bollschweiler M, Bodoque JM, Ballesteros JA (2010) Dating flash flood events by means of dendrogeomorphic analysis in a small ungauged mountain catchment (Spanish Central System). Geomorphology 118:383–392

    Article  Google Scholar 

  • Šálek M, Brezková L, Novák P (2006) The use of radar in hydrological modeling in the Czech Republic – case studies of flash floods. Nat Hazards Earth Syst Sci 6:229–236. https://doi.org/10.5194/nhess-6-229-2006

    Article  Google Scholar 

  • Schumm SA (1956) Evolution of drainage systems and slopes in bad lands at Perth Amboy. GSA Bulletin 67:597–646

  • Sharma V, Mishra VD, Joshi PK (2012) Snow cover variation and streamflow simulation in a snow-fed river basin of the Northwest Himalaya. J Mt Sci 9:853–868. https://doi.org/10.1007/s11629-012-2419-1

  • Siccardi F, Boni G, Ferraris L, Rudari R (2005) A hydrometeorological approach for probabilistic flood forecast. J Geophys Res 2005(110):d05101. https://doi.org/10.1029/2004jd005314

    Article  Google Scholar 

  • Silva FP, Rotunno Filho OC, Sampaio RJ, Dragaud ICV, Magalhães AAA, Justi da Silva MGA, Pires GD (2017) Evaluation of atmospheric thermodynamics and dynamics during heavy-rainfall and no-rainfall events in the metropolitan area of Rio de Janeiro, Brazil. Meteorog Atmos Phys 131:299–311. https://doi.org/10.1007/s00703-017-0570-5

    Article  Google Scholar 

  • Silva FP, Justi da Silva MGA, Rotunno Filho OC, Pires GD, Sampaio RJ, Magalhães AAA (2018) Synoptic thermodynamic and dynamic patterns associated with Quitandinha River flooding events in Petropolis, Rio de Janeiro (Brazil). Meteorog Atmos Phys 131:845–862. https://doi.org/10.1007/s00703-018-0609-2

    Article  Google Scholar 

  • Silva FP, Rotunno Filho OC, Justi da Silva MGA, Sampaio RJ, Pires GD, Magalhães AAA (2020a) Observed and estimated atmospheric thermodynamic instability using radiosonde observations over the city of Rio de Janeiro, Brazil. Meteorog Atmos Phys 132:297–314

    Article  Google Scholar 

  • Silva FP, Rotunno Filho OC, Justi da Silva MGA, Sampaio RJ, Pires GD, Magalhães AAA (2020b) Identification of rainfall and atmospheric patterns associated with Quitandinha River flooding events in Petropolis, Rio de Janeiro (Brazil). Nat Hazards 103:3745–3764. https://doi.org/10.1007/s11069-020-04153-y

    Article  Google Scholar 

  • Silva FP, Justi da Silva MGA, Rotunno Filho OC, Pires GD, Sampaio RJ, Magalhães AAA (2020c) Pattern evaluation of operational radar reflectivity–rainfall relationship for Quitandinha River flooding events: Petrópolis, Rio de Janeiro (Brazil). Environ Earth Sci 79. https://doi.org/10.1007/s12665-020-09273-z

  • Silvestro F, Rebora N, Cummings G, Ferraris L (2015) Experiences of dealing with flash floods using an ensemble hydrological nowcasting chain: implications of communication, accessibility and distribution of the results. J Flood Risk Manag 10:446–462. https://doi.org/10.1111/jfr3.12161

    Article  Google Scholar 

  • Smith MB, Seo DJ, Koren VI, Reed SM, Zhang Z, Duan Q, Moreda F, Cong S (2004) The distributed model intercomparison project (DMIP): motivation and experiment design. J Hydrol 298:4–26

    Article  Google Scholar 

  • Stout GE, Mueller EA (1968) Survey of relationships between rainfall rate and radar reflectivity in the measurement of precipitation. J Appl Meteorol 7:465–474

    Article  Google Scholar 

  • Strahler AN (1964) Quantitative geomorphology of drainage basins and channel networks. In: Chow VT (ed) Handbook of applied hydrology. McGraw-Hill, New York, pp 39–76

  • Sukovich EM, Ralph FM, Barthold FE, Reynolds DW, Novak DR (2014) Extreme quantitative precipitation forecast performance at the weather prediction center from 2001 to 2011. Weather Forecast 29:894–911. https://doi.org/10.1175/WAF-D-13-00061.1

    Article  Google Scholar 

  • Sukristiyanti S, Maria R, Lestiana H (2018) Watershed-based morphometric analysis: a review. Global Colloquium on GeoSciences and Engineering

  • Tokay A, Short DA (1996) Evidence from tropical raindrop spectra of the origin of rain from stratiform versus convective clouds. J Appl Meteorol 35:355–371

    Article  Google Scholar 

  • Toth Z, Tew M, Birkenheuer D, Albers S, Xie Y, Motta B (2014) Multiscale data assimilation and forecasting. Bull Am Meteorol Soc 95:ES30–ES33. https://doi.org/10.1175/BAMS-D-13-00088.1

    Article  Google Scholar 

  • Villela SM, Mattos A (1975) Hidrologia Aplicada. McGraw-Hill, São Paulo

  • Vivoni ER, Entekhabi D, Bras RL, Ivanov VY, Van Horne MP, Grassotti C, Hoffman RN (2006) Extending the predictability of hydrometeorological flood events using radar rainfall nowcasting. J Hydrometeorol 7:660–677

    Article  Google Scholar 

  • Wilks DS (1995) Statistical methods in the atmospheric sciences: an introduction, vol 59. Academic Press, San Diego 467 pp

    Book  Google Scholar 

  • Youssef AM, Pradhan B, Hassan AM (2011) Flash flood risk estimation along the St. Katherine road, southern Sinai, Egypt using GIS based morphometry and satellite imagery. Environ Earth Sci 62:611–623

    Article  Google Scholar 

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Acknowledgements

The authors would like to express their gratitude to the Civil Engineering Program of the Alberto Luiz Coimbra Institute of Postgraduate Studies and Research in Engineering (COPPE), which is part of the Federal University of Rio de Janeiro (UFRJ), for the support offered, particularly through availability of the Water Resources and Environmental Studies Laboratory (LABH2O).

Funding

The study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) – Finance Code 001, which also helped support this work through CAPES Call 27/2013 - Pró-Equipamentos Institucional and CAPES/MEC Call No. 03/2015 – BRICS. The authors are thankful to the National Council for Scientific and Technological Development (CNPq), which helped fund this work through CNPq Universal Call No. 14/2013 – Proceeding No. 485136/2013-9; No. 28 /2018 – Proceeding No. 435714/2018-0; and also by CNPq Call No. 12/2016 – Proceeding No. 306944/2016-2 and CNPq Call No. 06/2019 – Proceeding No. 303846/2019-4. The authors are also grateful to the Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ), which helped to fund this work through Project FAPERJ – Pensa Rio – Call 34/2014 (2014-2021).

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Authors and Affiliations

  1. Civil Engineering Program Alberto Luiz Coimbra Institute for Postgraduate Studies and Research in Engineering – COPPE, Universidade Federal do Rio de Janeiro, Rio de Janeiro, RJ, 21945-970, Brazil

    Fabricio Polifke da Silva, Otto Corrêa Rotunno Filho, Rafael João Sampaio & Gisele Dornelles Pires

  2. Engineering and Society Group, Exact Sciences and Technologies School, Universidade Iguaçu, UNIG, Av. Abílio Augusto Távora, 2134, Jardim Nova Era, Nova Iguaçu, RJ, 26275-580, Brazil

    Fabricio Polifke da Silva & Gisele Dornelles Pires

  3. Meteorology Laboratory, Science and Technology Center, Universidade Estadual do Norte Fluminense Darcy Ribeiro – UENF, Avenida Brenand, s.n., Imboassica, Macaé, RJ, 27925-535, Brazil

    Maria Gertrudes Alvarez Justi da Silva

  4. Department of Water Resources and Environment, Polytechnic School, Universidade Federal do Rio de Janeiro – UFRJ, Av. Athos da Silveira Ramos, CT, Escola Politécnica, Cidade Universitária, Rio de Janeiro, RJ, 21941-590, Brazil

    Afonso Augusto Magalhães de Araújo

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  1. Fabricio Polifke da Silva
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  2. Otto Corrêa Rotunno Filho
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da Silva, F.P., Rotunno Filho, O.C., Justi da Silva, M.G.A. et al. Real-time river level estimation based on variations of radar reflectivity—a case study of the Quitandinha River watershed, Petrópolis, Rio de Janeiro (Brazil). Bull. of Atmos. Sci.& Technol. 2, 1 (2021). https://doi.org/10.1007/s42865-021-00030-z

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Keywords

  • Reflectivity
  • River level
  • Weather radar reflectivity
  • Nowcasting