Regionalization of reference streamflows for the Araguaia River basin in Brazil
DOI:
https://doi.org/10.5433/1679-0359.2020v41n3p829Keywords:
Cerrado, Statistical Hydrology, Hydrological Modelling.Abstract
Hydraulic projects and water management require reliable hydrological data. The Araguaia-Tocantins River basin, in addition to agricultural use, has great potential for hydroelectric exploitation. However, the streamflow monitoring network in the Araguaia River basin is composed of only a few stations, resulting in a lack of hydrological data. The regionalization of the reference streamflows is a technique that can help circumvent this lack of data, enabling the estimation of streamflows from easily obtainable explanatory variables. In this context, the objective of this study was to develop regional functions for the maximum streamflow (Qmax) applicable to different Return Periods (RP), the long-term mean streamflow (Qmlt) and the 95% streamflow permanence (Q95) of the upper and middle Araguaia River sub-basins. The dimensionless streamflow methodology was adopted with the drainage area as an explanatory variable. The tested regressive models were the linear, potential and quotient models. Leave-one-out cross-validation was used to assess the quality of the regional models. Ten statistical distributions of 2 to 5 parameters were used. (i) Satisfactory results were obtained for all reference streamflows. (ii) The cross-validation technique proved to be essential for the selection of the most robust model. (iii) The quotient model was shown to be superior to the potential linear model in most cases.Downloads
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References
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Basu, B., & Srinivas, V. V. (2015). A recursive multi-scaling approach to regional flood frequency analysis. Journal of Hydrology, 529, Part 1, p. 373-383. doi: 10.1016/j.jhydrol.2015.07.037
Bergstra, J., & Bengio, Y. (2012). Random search for hyper-parameter optimization. Journal of Machine Learning Research, 13(Feb), p. 281-305. Retrieved from http://www.jmlr.org/papers/volume13/ bergstra12a/bergstra12a.pdf
Beskow, S., Caldeira, T. L., Mello, C. R. de, Faria, L. C., & Guedes, H. A. S. (2015). Multiparameter probability distributions for heavy rainfall modeling in extreme southern Brazil. Journal of Hydrology: Regional Studies, 4, Part B, p. 123-133. doi: 10.1016/j.ejrh.2015.06.007
Beskow, S., Mello, C. R. de, Vargas, M. M., Corrêa, L. de L., Caldeira, T. L., Durães, M. F., & Aguiar, M. S. de. (2016). Artificial intelligence techniques coupled with seasonality measures for hydrological regionalization of Q90 under Brazilian conditions. Journal of Hydrology, 541, Part B, p. 1406-1419. doi: 10.1016/j.jhydrol.2016.08.046
Camargo, A. P. de, & Sentelhas, P. C. (1997). Avaliação do desempenho de diferentes métodos de estimativa da evapotranspiração potencial no estado de São Paulo, Brasil. Revista Brasileira de Agrometeorologia, 5(1), p. 89-97. Retrieved from http://www.leb.esalq.usp.br/agmfacil/artigos/artigos_sentelhas_1997/ 1997_RBAgro_5(1)_89-97_ETPM%E9todosSP.pdf
Cannarozzo, M., Noto, L. V., Viola, F., & La Loggia, G. (2009). Annual runoff regional frequency analysis in Sicily. Physics and Chemistry of the Earth, Parts A/B/C, 34, (10-12), p. 679-687. doi: 10.1016/j.pce.2009.05.001
Cassalho, F., Beskow, S., Mello, C. R., & Moura, M. M. (2018). Regional flood frequency analysis using L-moments for geographically defined regions: An assessment in Brazil. Journal of Flood Risk Management, e12453. doi: 10.1111/jfr3.12453
Cassalho, F., Beskow, S., Mello, C. R., Moura, M. M., Kerstner, L., & Ávila, L. F. (2017a). At-site flood frequency analysis coupled with multiparameter probability distributions. Water Resources Management, 32(1), p. 285-300. doi: 10.1007/s11269-017-1810-7
Cassalho, F., Beskow, S., Vargas, M. M., Moura, M. M, Ávila, L. F., & Mello, C. R. (2017b). Hydrological regionalization of maximum stream flows using an approach based on L-moments. RBRH, 22, e27. doi: 10.1590/2318-0331.021720160064
Cheng, H., Garrick, D. J., & Fernando, R. L. (2017). Efficient strategies for leave-one-out cross validation for genomic best linear unbiased prediction. Journal of Animal Science and Biotechnology, 8(1), p. 1-5. doi: 10.1186/s40104-017-0164-6
Environmental Systems Research Institute. (2002). REDLANDS. ArcGIS Schematics Documentation. (Version 9).
Hosking, J. R. M. (1990). L-moments: analysis and estimation of distributions using linear combinations of order statistics. Journal of the Royal Statistical Society. Series B (Methodological), 52(1), p. 105-124. Retrieved from http://www.jstor.org/stable/2345653
Jeong, B. Y., Murshed, M. S., Seo, Y. A., & Park, J.-S. (2014). A three-parameter kappa distribution with hydrologic application: a generalized gumbel distribution. Stochastic Environmental Research and Risk Assessment, 28(8), p. 2063-2074. doi: 10.1007/s00477-014-0865-8
Kjeldsen, T. R., Ahn, H., & Prosdocimi, I. (2017). On the use of a four-parameter kappa distribution in regional frequency analysis. Hydrological Sciences Journal, 62(9), p. 1354-1363. doi: 10.1080/02626667.2017.1335400
Latrubesse, E. M., & Stevaux, J. C. (2002). Geomorphology and environmental aspects of the Araguaia fluvial basin, Brazil. Zeitschrift fur Geomorphologie, Supplementband, 129, 109-127.
Mello, C. R., & Silva, A. M. de. (2013). Hidrologia: princípios e aplicações em sistemas agrícolas. Lavras: Ed. UFLA.
Mikshowsky, A. A., Gianola, D., & Weigel, K. A. (2017). Assessing genomic prediction accuracy for Holstein sires using bootstrap aggregation sampling and leave-one-out cross validation. Journal of Dairy Science, 100(1), p 453-464. doi: 10.3168/jds.2016-11496
Naghettini, M., & Pinto, É. J. A. (2007). Hidrologia Estatística. Belo Horizonte: CPRM.
Pruski, F. F., Rodriguez, R. G., Pruski, P. L., Nunes, A. A., & Rego, F. S. (2016). Extrapolation of regionalization equations for long-term average flow. Engenharia Agrícola, 36(5), 830-838. doi: 10.1590/1809-4430-Eng.Agric.v36n5p830-838/2016
Tucci, C. E. M. (2002). Regionalização de vazões. Porto Alegre: Ed. UFRGS.
Vezza, P., Comoglio, C., Rosso, M., & Viglione, A. (2010). Low Flows Regionalization in North-Western Italy. Water Resources Management, 24(14), p. 4049-4074. doi: 10.1007/s11269-010-9647-3
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Published
2020-04-07
How to Cite
Morais, M. A. V., Viola, M. R., Mello, C. R. de, Rodrigues, J. A. M., & Oliveira, V. A. de. (2020). Regionalization of reference streamflows for the Araguaia River basin in Brazil. Semina: Ciências Agrárias, 41(3), 829–846. https://doi.org/10.5433/1679-0359.2020v41n3p829
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