TOPMODEL Hydrometeorological Modeling with Rain Gauge Data Integrated by High-Resolution Satellite Estimates. A Case Study in Muriaé River Basin, Brazil — Oak Academic Publishing
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TOPMODEL Hydrometeorological Modeling with Rain Gauge Data Integrated by High-Resolution Satellite Estimates. A Case Study in Muriaé River Basin, Brazil
Geological Survey of Brazil, São Paulo, Brazil
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Departamento de Ciências Atmosféricas, Instituto de Astronomia, Geofísica e Ciências Atmosféricas, Universidade de São Paulo, São Paulo, Brazil
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Departamento de Ciências Atmosféricas, Instituto de Astronomia, Geofísica e Ciências Atmosféricas, Universidade de São Paulo, São Paulo, Brazil
1 Geological Survey of Brazil, São Paulo, Brazil
2 Departamento de Ciências Atmosféricas, Instituto de Astronomia, Geofísica e Ciências Atmosféricas, Universidade de São Paulo, São Paulo, Brazil
3 Departamento de Ciências Atmosféricas, Instituto de Astronomia, Geofísica e Ciências Atmosféricas, Universidade de São Paulo, São Paulo, Brazil
This study consists of hydrological simulations of the Muriaé river watershed with the topography-based hydrological model (TOPMODEL) and available stream gauge and rain measurements between 2009 and 2013 for two subbasins, namely Carangola and Patrocínio do Muriaé . The simulations were carried out with the Climate Prediction Center morphing method (CMORPH) precipitation estimates and rain gauge measurements integrated into CM- ORPH by the Statistical Objective Analysis Scheme (SOAS). TOPMODEL calibration was performed with the shuffled complex evolution (SCE-UA) method with Nash-Sutcliffe efficiency (NSE). The best overall results were obtained with CMORPH (NSE ~ 0.6) for both subbasins. The simulations with SOAS resulted in an NSE ~ 0.2. However, in an analysis of days with high- level stages, SOAS simulations resulted in a better hit rate (23%) compared to CMORPH (10%). CMORPH simulations underestimated the flows at the flood periods, which indicates the importance to use multi-sensor precipitation data. The results with TOPMODEL allow an estimate of future discharges, which allows for better planning of a flood warning system and discharge measurement schedule.
Universidade Federal de Santa Catarina-Centro Universitário de Estudos e Pes-quisas sobre Desastres (UFSC-CEPED) (2012) Atlas brasileiro de desastres naturais 1991 a 2010: Volume Brasil. Universidade Federal de Santa Catarina-Centro Uni- versitário de Estudos e Pesquisas sobre Desastres, Florianópolis.
Tucci, C.E.M. (1998) Modelos hidrológicos. Ed. 10, Universidade Federal do Rio Grande do Sul, Porto Alegre.
Carvalho, C.S., Macedo, E.S. and Ogura, A.T. (orgs.) (2007) Mapeamento de riscos em encostas e margens de rios. Ministério das Cidades/Instituto de Pesquisas Tecno- lógicas—IPT. Brasília, DF, 176 p.
Goerl, R.F. and Kobiyama, M. (2005) Considerações sobre as inundações no Brasil. XVI Simpósio Brasileiro de Recursos Hídricos, João Pessoa, PB.
Tucci, C.E.M. and Bertoni, J.C. (orgs.) (2003) Inundações urbanas na América do Sul. Associação Brasileira de Recursos Hídricos (ABRH), Porto Alegre, RS.
Tominaga, L.K., Santoro, J. and Amaral, R. (orgs.) (2009) Desastres Naturais: Conhecer Para Prevenir. Instituto Geológico, São Paulo, 196 p.
Agência da Bacia do Rio Paraíba do Sul (AGEVAP) (2007) Plano de recursos hídricos da Bacia do Rio Paraíba do Sul: Resumo: Diagnóstico dos recursos hídricos: Relatório final. Agência da Bacia do Rio Paraíba do Sul, Resende.
Centro Nacional de Monitoramento e Alertas de Desastres Naturais (CEMADEN) (2020) Boletim da Sala de Situação.
Xu, C.Y. (2002) Hydrologic Models. Textbooks of Uppsala University, Department of Earth Sciences Hydrology, Uppsala.
Capozzoli, C. and Cardoso, A. (2020) Effects of Land Use Change on Discharge of the Paraíba do Sul River. Ciência e Natura, 42, Article No. e53. https://doi.org/10.5902/2179460X40832
Beven, K.J. (2001) Rainfall-Runoff Modeling: The Primer. John Wiley & Sons, Hoboken.
Beven, K.J. and Kirkby, M.J. (1979) A Physically Based, Variable Contributing Area Model of Basin Hydrology. Hydrological Sciences Bulletin, 24, 43-69. https://doi.org/10.1080/02626667909491834
Robson, A.J., Whitehead, P.G. and Johnson, R.C. (1993) An Application of a Physically-Based Semi-Distributed Model to the Balquhidder Catchments. Journal of Hy- drology, 145, 357-370. https://doi.org/10.1016/0022-1694(93)90063-F
Hornberger, G.M., Beven, K.J., Cosby, B.J. and Sappington, D.E. (1985) Shenandoah Watershed Study: Calibration of a Topography-Based, Variable Contributing Area Hydrological Model to a Small Forested Catchment. Water Resources Research, 21, 1841-1850. https://doi.org/10.1029/WR021i012p01841
Iorgulescu, I. and Jordan, J.P. (1994) Validation of TOPMODEL on a Small Swiss Catchment. Journal of Hydrology, 159, 255-273. https://doi.org/10.1016/0022-1694(94)90260-7
Campling, P., Gobin, A., Beven, K. and Feyen, J. (2002) Rainfall-Runoff Modeling of a Humid Tropical Catchment: The TOPMODEL Approach. Hydrological Processes, 16, 231-253. https://doi.org/10.1002/hyp.341
Rocha Filho, K.L.D. (2010) Modelagem Hidrológica da Bacia do Rio Pirajuçara com TOPMODEL, Telemetria e Radar Meteorológico. Masters Dissertation, Meteorology, Universidade de São Paulo, São Paulo.
Nourani, V., Roughani, A. and Gebremichael, M. (2011) TOPMODEL Capability for Rainfall-Runoff Modeling of the Ammameh Watershed at Different Time Scales Using Different Terrain Algorithms. Journal of Urban and Environmental Engineering, 5, 1-14.
Franchini, M., Wendling, J., Obled, C. and Todini, E. (1996) Physical Interpretation and Sensitivity Analysis of the TOPMODEL. Journal of Hydrology, 175, 293-338. https://doi.org/10.1016/S0022-1694(96)80015-1
Calvetti, L. and Pereira Filho, A.J. (2014) Ensemble Hydrometeorological Forecasts Using WRF Hourly QPF and TopModel for a Middle Watershed. Advances in Me- teorology, 2014, Article ID: 484120. https://doi.org/10.1155/2014/484120
Pereira Filho, A.J., Crawford, K.C. and Hartzell, C.L. (1998) Improving WSR-88D Hourly Rainfall Estimates. Weather and Forecasting, 13, 1016-1028. https://doi.org/10.1175/1520-0434(1998)013%3C1016:IWHRE%3E2.0.CO;2
Guo, H., Chen, S., Bao, A., Hu, J., Yang, B. and Stepanian, P.M. (2015) A Comprehensive Evaluation of High-Resolution Satellite-Based Precipitation Products over China. Atmosphere, 7, Article No. 6. https://doi.org/10.3390/atmos7010006
Pereira Filho, A.J. (2004) Integrating Gauge, Radar, and Satellite Rainfall. In Online Proceedings, 2nd Workshop of the International Precipitation Working Group, CGMS-IPWG/WMO, Monterey.
Legates, D.R. and DeLiberty, T.L. (1993) Precipitation Measurement Biases in the United States. JAWRA Journal of the American Water Resources Association, 29, 855-861. https://doi.org/10.1111/j.1752-1688.1993.tb03245.x
Groisman, P.Y. and Legates, D.R. (1994) The Accuracy of United States Precipitation Data. Bulletin of the American Meteorological Society, 75, 215-228. https://doi.org/10.1175/1520-0477(1994)075%3C0215:TAOUSP%3E2.0.CO;2
Di Paola, F., Casella, D., Dietrich, S., Mugnai, A., Ricciardelli, E., Romano, F. and Sanò, P. (2012) Combined MW-IR Precipitation Evolving Technique (PET) of Convective Rain Fields. Natural Hazards and Earth System Sciences, 12, 3557-3570. https://doi.org/10.5194/nhess-12-3557-2012
Joyce, R.J., Janowiak, J.E., Arkin, P.A. and Xie, P. (2004) CMORPH: A Method That Produces Global Precipitation Estimates from Passive Microwave and Infrared Data at High Spatial and Temporal Resolution. Journal of Hydrometeorology, 5, 487-503. https://doi.org/10.1175/1525-7541(2004)005%3C0487:CAMTPG%3E2.0.CO;2
Pereira Filho, A.J. and Crawford, K.C. (1995) Integrating WSR-88D Estimates and Oklahoma Mesonet Measurements of Rainfall Accumulations: A Statistical Approach. 27th International Conference on Radar Meteorology, Vail, Boston, 9-13 October 1995, 240-242.
Pereira Filho, A.J. and Crawford, K.C. (1999) Mesoscale Precipitation Fields. Part I: Statistical Analysis and Hydrologic Response. Journal of Applied Meteorology, 38, 82-101. https://doi.org/10.1175/1520-0450(1999)038%3C0082:MPFPIS%3E2.0.CO;2
Kalinga, O., Gan, T.Y. and Xie, J. (2003) Applying Radar Rainfall Data in Basin Hydrological. In: IAHS Publication, Proceedings of Weather Radar Information and Distributed Hydrological Modelling, Held during IUGG2003 at Sapporo, No. 282, 258-267.
Silva, F.D.D.S. (2006) Análise Objetiva Estatística da Precipitação Estimada com Radar medida por uma Rede Telemétrica. Tese de Doutorado, Meteorologia, Universidade de São Paulo, São Paulo.
Silva, F.D.D.S., Pereira Filho, A.J. and Hallak, R. (2009) Classificação de sistemas meteorológicos e comparação da precipitação estimada pelo radar e medida pela rede telemétrica na Bacia Hidrográfica do Alto Tietê. Revista Brasileira de Meteorologia, 24, 292-307. https://doi.org/10.1590/S0102-77862009000300004
Pereira Filho, A.J., Vemado, F., Vemado, G., Gomes Vieira Reis, F.A., Giordano, L.D.C., Cerri, R.I., Santos, C.C., Sampaio Lopes, E.S., Gramani, M.F., Ogura, A.T. and Zaine, J.E. (2018) A Step towards Integrating CMORPH Precipitation Estimation with Rain Gauge Measurements. Advances in Meteorology, 2018, Article ID: 209- 5304. https://doi.org/10.1155/2018/2095304
Moliĉová, H., Grimaldi, M., Bonell, M. and Hubert, P. (1997) Using TOPMODEL towards Identifying and Modeling the Hydrological Patterns within a Headwater, Humid, Tropical Catchment. Hydrological Processes, 11, 1169-1196. https://doi.org/10.1002/(SICI)1099-1085(199707)11:9%3C1169::AID-HYP551%3E3.0.CO;2-W
Schuler, A.E. (2003) Fluxos hidrológicos em microbacias com floresta e pastagem na Amazônia Oriental, Paragominas, Pará. Tese de Doutorado, Ciências, Universidade de S âo Paulo, S âo Paulo.
Embrapa (Brazilian Agricultural Research Corporation) (2006) Sistema brasileiro de classificação de solos. 2. ed. Rio de Janeiro. Centro Nacional de Pesquisa de Solos. Embrapa-SPI, Brasília, 306 p.
Prado, R.B.P., Dantas, M.E., Fidalgo, E.C.C., Gonçalves, A.O., Silveira, M.D.M.L., Guimarães, P.V., et al. (2005) Diagnóstico do meio físico da bacia hidrográfica do rio Muriaé. Embrapa Solos, Rio de Janeiro, RJ.
Ferraro, R.R. (1997) Special Sensor Microwave Imager Derived Global Rainfall Estimates for Climatological Applications. Journal of Geophysical Research: Atmospheres, 102, 16715-16735. https://doi.org/10.1029/97JD01210
Weng, F., Zhao, L., Ferraro, R.R., Poe, G., Li, X. and Grody, N.C. (2003) Advanced Microwave Sounding Unit Cloud and Precipitation Algorithms. Radio Science, 38, Article No. 8068. https://doi.org/10.1029/2002RS002679
Kummerow, C., Hong, Y., Olson, W.S., Yang, S., Adler, R.F., McCollum, J. and Wilheit, T.T. (2001) The Evolution of the Goddard Profiling Algorithm (GPROF) for Rainfall Estimation from Passive Microwave Sensors. Journal of Applied Meteorology and Climatology, 40, 1801-1820. https://doi.org/10.1175/1520-0450(2001)040%3C1801:TEOTGP%3E2.0.CO;2
Vicente, G.A., Davenport, J.C. and Scofield, R.A. (2002) The Role of Orographic and Parallax Corrections on Real-Time High-Resolution Satellite Rainfall Rate Distribution. International Journal of Remote Sensing, 23, 221-230. https://doi.org/10.1080/01431160010006935
Arkin, P.A. and Ardanuy, P.E. (1989) Estimating Climatic-Scale Precipitation from Space: A Review. Journal of Climate, 2, 1229-1238. https://doi.org/10.1175/1520-0442(1989)002%3C1229:ECSPFS%3E2.0.CO;2
Bhargava, M. and Danard, M. (1994) Application of Optimum Interpolation to the Analysis of Precipitation in Complex Terrain. Journal of Applied Meteorology, 33, 508-518. https://doi.org/10.1175/1520-0450(1994)033%3C0508:AOOITT%3E2.0.CO;2
Daley, R. (1993) Atmospheric Data Analysis (No. 2). Cambridge University Press, Cambridge.
Beven, K.J., Kirkby, M.J., Schofield, N. and Tagg, A.F. (1984) Testing a Physically-Based Flood Forecasting Model (TOPMODEL) for Three UK Catchments. Journal of Hydrology, 69, 119-143. https://doi.org/10.1016/0022-1694(84)90159-8
Betson, R.P. (1964) What Is Watershed Runoff? Journal of Geophysical Research (1896-1977), 69, 1541-1552. https://doi.org/10.1029/JZ069i008p01541
Dunne, T. and Black, R.D. (1970) Partial Area Contributions to Storm Runoff in a Small New England Watershed. Water Resources Research, 6, 1296-1311. https://doi.org/10.1029/WR006i005p01296
Clarke, R.T. (1973) A Review of Some Mathematical Models Used in Hydrology, with Observations on Their Calibration and Use. Journal of Hydrology, 19, 1-20. https://doi.org/10.1016/0022-1694(73)90089-9
Duan, Q., Sorooshian, S. and Gupta, V.K. (1992) Effective and Efficient Global Optimization for Conceptual Rainfall-Runoff Models. Water Resources Research, 28, 1015-1031. https://doi.org/10.1029/91WR02985
Madsen, H. (2000) Automatic Calibration of a Conceptual Rainfall-Runoff Model Using Multiple Objectives. Journal of Hydrology, 235, 276-288. https://doi.org/10.1016/S0022-1694(00)00279-1
Duan, Q., Sorooshian, S. and Gupta, V.K. (1994) Optimal Use of the SCE-UA Global Optimization Method for Calibrating Watershed Models. Journal of Hydrology, 158, 265-284. https://doi.org/10.1016/0022-1694(94)90057-4
Ajami, N.K., Gupta, H., Wagener, T. and Sorooshian, S. (2004) Calibration of a semi-Distributed Hydrologic Model for Streamflow Estimation along with a River System. Journal of Hydrology, 298, 112-135. https://doi.org/10.1016/j.jhydrol.2004.03.033
Ma, H.B., Dong, Z.C., Zhang, W.M. and Liang, Z.M. (2006) Application of SCE-UA Algorithm to Optimization of TOPMODEL Parameters. Journal of Hohai University (Natural Sciences), 4, 361-365.
Skøien, J.O., Blöschl, G., Laaha, G., Pebesma, E., Parajka, J. and Viglione, A. (2014) Rtop: An R Package for Interpolation of Data with Variable Spatial Support, with an Example from River Networks. Computers & Geosciences, 67, 180-190. https://doi.org/10.1016/j.cageo.2014.02.009
Nash, J.E. and Sutcliffe, J.V. (1970) River Flow Forecasting through Conceptual Models Part I—A Discussion of Principles. Journal of Hydrology, 10, 282-290. https://doi.org/10.1016/0022-1694(70)90255-6