A Nowcasting System for Hydrometeorological Hazard Assessment of Landslides and Flooding – Part 1: Conceptual Formulation

Autores

DOI:

https://doi.org/10.11137/1982-3908_2024_47_62978

Palavras-chave:

Nowcasting, Hydroestimator/NOAA, Hydrometeorological hazards

Resumo

This study presents a novel very short-term hydro-meteorological forecasting system integrating precipitation data from Hydroestimator/NOAA. The system employs a variational version of the TopModel hydrological model alongside landslide and flood hazard models. Operating in continuous 15-minute cycles, it produces scalar and probabilistic two-dimensional hazard fields to support decision-making during extreme events across the State of Rio de Janeiro, Brazil, at a spatial resolution of 4 km. The evaluation of this system considers performance indicators based on contingency tables. Emphasizing a balanced approach between computational efficiency and product utility, this study aims to provide a robust analysis of the system's predictive capabilities in addressing hydro-meteorological challenges.

Biografia do Autor

Hugo Abi Karam, Universidade Federal do Rio de Janeiro, Instituto de Geociências, Departamento de Meteorologia

Universidade Federal do Rio de Janeiro, Instituto de Geociências, Departamento de Meteorologia, Rio de Janeiro, RJ, Brazil

Referências

Barnes, S.L. 1964, ‘A technique for maximizing details in numerical weather-map analysis’, Journal of Applied Meteorology, vol. 3, no. 4, pp.396-409.

Battan, L.J. 1973, Radar Observations of the Atmosphere. University of Chicago Press, Chicago, USA. 324 pp.

Beven, K.L. & Kirkby, M. 1979, ‘A physically based, variable contributing area model of basin hydrology/Un modèle à base physique de zone d'appel variable de l'hydrologie du bassin versant’, Hydrological Sciences Bulletin, vol. 24, no. 1, pp. 43-69.

Beven, K.L. (org.). 1997, Advances in Hydrological Processes, vol. 5, no. 1, John Wiley & Sons, New Jersey.

Beven, K.L. & Freer, J. 2001, ‘A dynamic TopModel’, Hydrol. Process, vol. 15, pp. 1993-2011, DOI: 10.1002/hyp.252.

Buytaert, W. 2022, TopModel: Implementation of the Hydrological Model TopModel in R, Library R-TopModel, viewed 23 February 2024, <https://github.com/ICHydro/TopModel>.

Burt, S. 2010, ‘British rainfall 1860-1993’, Weather, vol. 65, no. 5, pp. 121-8.

Coelho Netto, A.L. 1996, ‘Produção de Sedimentos em Bacias Fluviais Florestadas do Maciço da Tijuca, RJ: respostas aos eventos extremos de fevereiro de 1996’, Anais do II Encontro Nacional de Engenharia de Sedimentos, vol. 1, pp. 209-17.

De Blasio, F.V. 2011, Introduction to the physics of landslides: Lecture notes on the dynamics of mass wasting, Springer Science & Business Media, Germany.

D’Orsi, R.N., Feijo, L. & Paes, N.M. 2002, ‘Relatório de Escorregamentos’, Fundação Geo-Rio, 58p.

D’Orsi, R.N., Feijo, R.L. & Paes N.M. 2004, ‘2,500 operational days of Alerta Rio system: History and technical improvements of Rio de Janeiro Warning System for severe weather’, in Lacerda, Ehrlich, Fontoura & Sayão (eds.), Landslides: Evaluation and Stabilization, Taylor & Francis Group, London, pp. 831-36.

D’Orsi, R.N. 2016, ‘Lecture about Fundação GeoRio’, AlertaRio System of the Municipality of Rio de Janeiro-RJ, Brazil. 85 slides.

Deardorff, J.W. 1978, ‘Efficient prediction of ground surface temperature and moisture, with the inclusion of a layer of vegetation’, Journal of Geophysical Research: Oceans, vol. 83, no. C4, pp. 1889-1903.

Devia, G.K., Ganasri, B.P. & Dwarakish, G.S. 2015, ‘A review on hydrological models’, Aquatic procedia, vol. 4, pp. 1001-7.

Durran, D.R. 2013, Numerical methods for wave equations in geophysical fluid dynamics, vol. 32, Springer Science & Business Media.

Felsberg, A., Poesen, J., Bechtold, M., Vanmaercke, M. & De Lannoy, G.J. 2022, ‘Estimating global landslide susceptibility and its uncertainty through ensemble modeling’, Natural Hazards and Earth System Sciences, vol. 22, no. 9, pp. 3063-82.

Froude, P. 2018, ‘Global fatal landslide occurrence from 2004 to 2016’, Natural Hazards and Earth System Sciences, vol. 18, pp. 2161-81.

Gomez, H. & Kavzoglu, T. 2005,‘Assessment of shallow landslide susceptibility using artificial neural networks in Jabonosa River Basin, Venezuela’, Engineering Geology, vol. 78, no. 1-2, pp. 11-27.

Gonçalves, G.C., Escada, M.I.S. & Amaral, S. 2019, ‘Impervious surfaces for population estimate in Brazilian cities’, XIX Simpósio Brasileiro de Sensoriamento Remoto, INPE, Santos-SP, Brasil, pp. 1946-5.

Guidicini, G. & Iwasa, O.Y. 1976, ‘Correlation Study between Rainfall and Landslides in a Humid Tropical Environment’, Simpósio “Landslides and other Mass Moviment” da IAEG 1977, Praga, Publicação 1080 IPT.

Guzzetti, F., Reichenbach, P., Ardizzone, F., Cardinali, M. & Galli, M. 2006, ‘Estimating the quality of landslide susceptibility models’, Geomorphology, vol. 81, no. 1-2, pp. 166-184.

Hoffman, J.D. & Frankel, S. 2018, Numerical methods for engineers and scientists, CRC Press.

Horn, B.K.P. & Schunck, B.G. (1981). Determining optical flow. Artificial Intelligence, vol. 17, pp.185–203.

Inea-RJ 2023, Instituto Estadual do Ambiente do Estado do Rio de Janeiro, Brasil, viewed 23 February 2024, <http://www.inea.rj.gov.br>.

Jaiswal, R.K., Ali, S. & Bharti, B. 2020, ‘Comparative evaluation of conceptual and physical rainfall–runoff models’, Applied Water Science, vol. 10, no. 1, 48.

Jenson, S.K. & Domingue, J.O. 1988, ‘Extracting topographic structure from digital elevation data for geographic information system analysis’, Photogrammetric Engineering & Remote Sensing, vol. 54, no. 11, pp. 1593-1600.

Khan, S., Kirschbaum, D.B., Stanley, T.A., Amatya, P.M. & Emberson, R.A. 2022, ‘Global landslide forecasting system for hazard assessment and situational awareness’, Frontiers in Earth Science, vol. 10, 878996.

Karam, H.A., Pereira Filho, A.J. & Flores Rojas, J.L. 2017, ‘On the precipitation homogeneity hypothesis in TopModel applications: In Geo-Technologies and Natural Disasters (Special Edition)’, Brazilian Journal of Cartography, vol. 69, no. 1, pp. 13-22.

Karam, H.A., Blacket, M.A., Silva, R.B.P., Flores Rojas, J.L., Pereira Filho, A.J. Sanchez Peña, C.A., Vásquez Panduro, I.L., Siqueira, B.S. & Angeles Suazo, J.M. 2024, ‘Modeling of Soil Water Distribution in a Small Mid-Latitude Watershed on the British Isle for Short Term Landslide and Flood Risk Assessment’, Anuário do Instituto de Geociências, vol. 1, no. 47, 57297.

Keller, V.D.J., Tanguy, M., Prosdocimi, I., Terry, J.A., Hitt, O., Cole, S.J., Fry, M., Morris, D.G. & Dixon, H. 2015, ‘CEH-GEAR: 1 km resolution daily and monthly areal rainfall estimates for the UK for hydrological and other applications’, Earth System Science Data, vol. 7, no. 1, pp. 143-155.

Kirkby, M.J. 1997, ‘TopModel: A Personal View. In Distributed hydrological modeling: application of TopModel concept’, in Beven, K.L. (ed.), ‘Series: Advances in hydrological processes’, John Wiley & Sons.

Koch, S.E., DesJardins, M., & Kocin, P.J. 1983, ‘An interactive Barnes Objective Map Analysis Scheme for Use with Satellite and Conventional Data’, Journal of Applied Meteorology and Climatology, vol. 22, no. 9, pp. 1487-1503.

Lemons, D.S., & Gythiel, A. 1997, ‘Paul Langevin's 1908 paper “On the Theory of Brownian Motion”’, American Journal of Physics, Vol. 65, no. 11, pp.1079–1081.

Liu, G., Schwartz, F.W., Tseng, K.H. & Shum, C.K. 2015, ‘Discharge and water-depth estimates for ungauged rivers: Combining hydrologic, hydraulic, and inverse modeling with stage and water-area measurements from satellites’, Water Resources Research, vol. 51, pp. 6017-35, DOI:10.1002/2015WR016971.

Lucas, B.D. & Kanade, T. 1981, ‘An iterative image registration technique with an application to stereo vision’. In Proceedings of Imaging Understanding Workshop, pp. 121-30.

Marchuk, G. 2012, Numerical methods in weather prediction, Elsevier, Netherlands.

Marshall, J.S. & Palmer, W.McK. 1948, 'The distribution of raindrops with size', Journal of Meteorology, vol. 5, pp. 165-66.

Mesinger, F. & Arakawa, A. 1976, Numerical Methods Used in Atmospheric Models, GARP Publications Series, World Meteorological Organization Publication, no. 17, 70p.

Mesinger, F. & Arakawa, A. 1976, Numerical methods used in atmospheric models, WMO Publication, GARP Publications Series, no. 17, 70p.

Sanchez Peña, C.A., 2018. ‘Desenvolvimento de um modelo numérico para a avaliação de riscos naturais associados à precipitação na MARJ’, Master’s thesis, Universidade Federal do Rio de Janeiro, Brasil.

Orlanski, I. 1965, ‘A simple boundary condition for unbounded hyperbolic flows’, Journal of Computational Physics, vol. 21, no. 3, pp. 251-269.

Preti, F. & Letterio, T. 2015, ‘Shallow landslide susceptibility assessment in a data-poor region of Guatemala (Comitancillo municipality)’, Journal of Agricultural Engineering, vol. 46, no. 3, pp. 85-94.

Quinn, P., Beven, K., Chevallier, P. & Planchon, O. 1991, ‘The prediction of hillslope flow paths for distributed hydrological modeling using digital terrain models’, Hydrological Processes, vol. 5, no. 1, pp. 59-79.

Seller, W.D. 1965, ‘Physical Climatology’, University of Chicago Press.

Seibert, J.A.N., Bishop, K.H. & Nyberg, L. 1997, ‘A test of TopModel's ability to predict spatially distributed groundwater levels’, Hydrological processes, vol. 11, no. 9, pp. 1131-44.

Sharma, K.D., Sorooshian, S. & Wheater, H. 2008, Hydrological Modelling in Arid and Semi-Arid Areas. Cambridge University Press, New York.

Siqueira, B.S. 2017, ‘Investigação do papel da precipitação para análise do risco de deslizamentos de encostas’, Master’s thesis, Universidade Federal do Rio de Janeiro, Brasil.

Smolarkiewicz, P.K. 2006, ‘Multidimensional positive definite advection transport algorithm: An overview’, International Journal for Numerical Methods in Fluids, vol. 50, no. 10, pp. 1123-44.

Tatizana, C., Ogura, A.T., Cerri, L.E.S. & Rocha, M.C.M. 1987a, ‘Análise da correlação entre chuvas e escorregamentos na Serra do Mar, município de Cubatão’, Proceedings of the 5th Congresso Brasileiro de Geologia de Engenharia, São Paulo, vol. 2, pp. 225-36.

Tatizana, C., Ogura, A.T., Cerri, L.E.S. & Rocha, M.C.M. 1987b, ‘Modelamento numérico da análise de correlação entre chuvas e escorregamentos aplicado às encostas da Serra do Mar no município de Cubatão’, Proceedings of Congresso Brasileiro de Geologia de Engenharia (5th), São Paulo, vol. 2, pp. 237-48.

Thompson, P.D. 1961, Numerical weather analysis and prediction, Macmillan, New York.

Tomás, L.R., Soares, G.G., Jorge, A.A., Mendes, J.F., Freitas, V.L. & Santos, L.B. 2022, ‘Flood risk map from hydrological and mobility data: A case study in São Paulo (Brazil)’, Transactions in GIS, vol. 26, no. 5, pp. 2341-65.

Williams, G.P. 1978, Hydraulic Geometry of River Cross Sections - Theory of Minimum Variance, Geological Survey Professional Paper, Washington.

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Publicado

2024-12-10

Edição

v. 47 (2024): Anuário do Instituto de Geociências

Seção

Meteorologia

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Creative Commons License
Este trabalho está licenciado sob uma licença Creative Commons Attribution 4.0 International License.

Os artigos publicados nesta revista se encontram sob a llicença Creative Commons — Atribuição 4.0 Internacional — CC BY 4.0, que permite o uso, distribuição e reprodução em qualquer meio, contanto que o trabalho original seja devidamente citado.