Análisis de Fisher-Shannon de la tasa de flujo del río São Francisco: la influencia de presas y embalses

Autores/as

DOI:

https://doi.org/10.33448/rsd-v9i10.8852

Palabras clave:

Análisis de fisher-shannon; Río San Francisco; Reservatórios.

Resumen

Investigamos cómo la construcción de las presas de Sobradinho y Xingó afectó el caudal diario del río San Francisco, utilizando el análisis de Fisher-Shannon. Se analizaron las series temporales de caudal diario de las estaciones fluviométricas Juazeiro / BA y Pan de Azucar / AL que se ubican aguas abajo de los embalses de Sobradinho y Xingó para los períodos anteriores a la construcción de ambos embalses, luego de la construcción de Sobradinho y antes de la construcción de Xingó, y después de la construcción de ambos embalses. Aplicamos el análisis de Fisher-Shannon a sub series de caudal y en ventanas móviles, evaluando las diferencias mediante la prueba de Kruskal-Wallis. Este método cuantifica simultáneamente las propiedades locales y globales de la función de densidad de probabilidad de la señal analizada. Observamos que en el régimen natural el grado de organización temporal de la serie de caudales disminuyó con el aumento del área de drenaje. Posteriormente a la construcción de Sobradinho el grado de regularidad de la dinámica del caudal fluvial disminuyó en comparación con el régimen natural, luego de la construcción del Xingó observamos una dinámica fluvial más regular y organizada. Así, las operaciones de los embalses cambiaron el grado de regularidad y organización temporal de la serie de caudales, como lo indican los valores de entropía y de información de Fisher, respectivamente.

Citas

ANA. (2020). Agência Nacional de Águas. Recuperado de http://hidroweb.ana.gov.br

Angulo, J. C., Antolín, J., & Sen, K. D. (2008). Fisher–Shannon plane and statistical complexity of atoms. Physics Letters A, 372(5), 670–674.

Barreto, I. D. de C., Stosic, T., Filho, M. C., Delrieux, C., Singh, V. P., Asce, D. M., & Stosic, B. (2020). Complexity Analyses of Sao Francisco River Streamflow : Influence of Dams and Reservoirs, 25(10), 1–8. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001996

Bezerra, B. G., Silva, L. L., Santos e Silva, C. M., & de Carvalho, G. G. (2019). Changes of precipitation extremes indices in São Francisco River Basin, Brazil from 1947 to 2012. Theoretical and Applied Climatology, 135(1–2), 565–576. https://doi.org/10.1007/s00704-018-2396-6

Chai, Y., Yue, Y., Zhang, L., Miao, C., Borthwick, A. G. L., Zhu, B., … Dolman, A. J. (2020). Homogenization and polarization of the seasonal water discharge of global rivers in response to climatic and anthropogenic effects. Science of The Total Environment, 709, 136062.

CHESF. (2015). Companhia Hidrelétrica do Rio São Francisco. Recuperado de https://www.chesf.gov.br

Dembo, A., Cover, T. M., & Thomas, J. A. (1991). Information theoretic inequalities. IEEE Transactions on Information Theory, 37(6), 1501–1518.

Döll, P., Fiedler, K., & Zhang, J. (2009). Global-scale analysis of river flow alterations due to water withdrawals and reservoirs. Hydrology and Earth System Sciences, 13(12), 2413–2432. https://doi.org/10.5194/hess-13-2413-2009

Fang, K., Sivakumar, B., & Woldemeskel, F. M. (2017). Complex networks, community structure, and catchment classification in a large-scale river basin. Journal of Hydrology, 545, 478–493.

Fisher, R. A. (1925). Theory of statistical estimation. In Mathematical Proceedings of the Cambridge Philosophical Society (Vol. 22, pp. 700–725). Cambridge University Press.

Fonseca, E. R., de Ávila Modesto, F., Carneiro, G. C. A., Lima, N. F. S., & de Almeida Monte-Mor, R. C. (2020). Conflitos pelo uso da água na Bacia Hidrográfica do rio São Francisco–Estudos de caso no Estado da Bahia. Research, Society and Development, 9(9), e823997929–e823997929.

Frieden, B. R. (1990). Fisher information, disorder, and the equilibrium distributions of physics. Physical Review A, 41(8), 4265.

Guignard, F., Lovallo, M., Laib, M., Golay, J., Kanevski, M., Helbig, N., & Telesca, L. (2019). Investigating the time dynamics of wind speed in complex terrains by using the Fisher–Shannon method. Physica A: Statistical Mechanics and Its Applications, 523, 611–621. https://doi.org/10.1016/j.physa.2019.02.048

Li, Z., & Zhang, Y.-K. (2008). Multi-scale entropy analysis of Mississippi River flow. Stochastic Environmental Research and Risk Assessment, 22(4), 507–512.

Magilligan, F. J., & Nislow, K. H. (2005). Changes in hydrologic regime by dams. Geomorphology, 71(1–2), 61–78.

Maneta, M. P., Torres, M., Wallender, W. W., Vosti, S., Kirby, M., Bassoi, L. H., & Rodrigues, L. N. (2009). Water demand and flows in the São Francisco River Basin (Brazil) with increased irrigation. Agricultural Water Management, 96(8), 1191–1200. https://doi.org/10.1016/j.agwat.2009.03.008

Martin, M. T., Pennini, F., & Plastino, A. (1999). Fisher’s information and the analysis of complex signals. Physics Letters A, 256(2–3), 173–180.

Matteau, M., Assani, A. A., & Mesfioui, M. (2009). Application of multivariate statistical analysis methods to the dam hydrologic impact studies. Journal of Hydrology, 371(1–4), 120–128.

Pfirman, S. L. (2003). Complex environmental systems: synthesis for earth, life, and society in the 21st century: A 10-year outlook for the National Science Foundation. National Science Foundation.

Pierini, J. O., Restrepo, J. C., Lovallo, M., & Telesca, L. (2015). Discriminating between different streamflow regimes by using the fisher-shannon method: An application to the Colombia rivers. Acta Geophysica, 63(2), 533–546. https://doi.org/10.2478/s11600-014-0229-2

Raykar, V. C., & Duraiswami, R. (2006). Fast optimal bandwidth selection for kernel density estimation. In Proceedings of the 2006 SIAM International Conference on Data Mining (pp. 524–528). SIAM.

Rego, C. R. C., Frota, H. O., & Gusmão, M. S. (2013). Multifractality of Brazilian rivers. Journal of Hydrology, 495, 208–215. https://doi.org/10.1016/j.jhydrol.2013.04.046

Richter, B. D., Baumgartner, J. V, Powell, J., & Braun, D. P. (1996). A method for assessing hydrologic alteration within ecosystems. Conservation Biology, 10(4), 1163–1174.

Richter, B. D., & Thomas, G. A. (2007). Restoring environmental flows by modifying dam operations. Ecology and Society, 12(1). https://doi.org/10.5751/ES-02014-120112

Sivakumar, B. (2009). Nonlinear dynamics and chaos in hydrologic systems: Latest developments and a look forward. Stochastic Environmental Research and Risk Assessment, 23(7), 1027–1036. https://doi.org/10.1007/s00477-008-0265-z

Stosic, T., Telesca, L., de Souza Ferreira, D. V., & Stosic, B. (2016). Investigating anthropically induced effects in streamflow dynamics by using permutation entropy and statistical complexity analysis: A case study. Journal of Hydrology, 540, 1136–1145. https://doi.org/10.1016/j.jhydrol.2016.07.034

Telesca, L., & Lovallo, M. (2017). On the performance of Fisher Information Measure and Shannon entropy estimators. Physica A: Statistical Mechanics and Its Applications, 484, 569–576. https://doi.org/10.1016/j.physa.2017.04.184

Telesca, L., Lovallo, M., Hsu, H.-L., & Chen, C.-C. (2011). Analysis of dynamics in magnetotelluric data by using the Fisher–Shannon method. Physica A: Statistical Mechanics and Its Applications, 390(7), 1350–1355.

Tongal, H., Demirel, M. C., & Moradkhani, H. (2017). Analysis of dam-induced cyclic patterns on river flow dynamics. Hydrological Sciences Journal, 62(4), 626–641.

Tonkin, J. D., Merritt, D. M., Olden, J. D., Reynolds, L. V, & Lytle, D. A. (2018). Flow regime alteration degrades ecological networks in riparian ecosystems. Nature Ecology & Evolution, 2(1), 86–93.

Vignat, C., & Bercher, J.-F. (2003). Analysis of signals in the Fisher–Shannon information plane. Physics Letters A, 312(1–2), 27–33.

Woldesenbet, T. A., Elagib, N. A., Ribbe, L., & Heinrich, J. (2017). Hydrological responses to land use/cover changes in the source region of the Upper Blue Nile Basin, Ethiopia. Science of the Total Environment, 575, 724–741.

Zhou, Y., Zhang, Q., Li, K., & Chen, X. (2012). Hydrological effects of water reservoirs on hydrological processes in the East River (China) basin: complexity evaluations based on the multi-scale entropy analysis. Hydrological Processes, 26(21), 3253–3262.

Zhou, Y., Zhang, Q., & Singh, V. P. (2014). Fractal-based evaluation of the effect of water reservoirs on hydrological processes: The dams in the Yangtze River as a case study. Stochastic Environmental Research and Risk Assessment, 28(2), 263–279. https://doi.org/10.1007/s00477-013-0747-5

Publicado

06/10/2020

Cómo citar

BARRETO, Íkaro D. de C. .; SANTOS, E. F. N. .; STOSIC, T. Análisis de Fisher-Shannon de la tasa de flujo del río São Francisco: la influencia de presas y embalses. Research, Society and Development, [S. l.], v. 9, n. 10, p. e5159108852, 2020. DOI: 10.33448/rsd-v9i10.8852. Disponível em: https://rsdjournal.org/index.php/rsd/article/view/8852. Acesso em: 22 nov. 2024.

Número

Sección

Ciencias Agrarias y Biológicas