Modelo hidrológico para la simulación de caudales recesivos: caso río “Jequetepeque”, aguas arriba de la presa Gallito Ciego, Perú

Jairo Isaí Alvarez Villanueva; José Francisco Huamán Vidaurre

Authors

Jairo Isaí Alvarez Villanueva Universidad Nacional de Cajamarca, Ingeniería Hidráulica, Av. Atahualpa Nº 1050, Cajamarca, Perú.
José Francisco Huamán Vidaurre Universidad Nacional de Cajamarca, Ingeniería Hidráulica, Av. Atahualpa Nº 1050, Cajamarca, Perú.

Keywords:

recessive flow, hydrological model, hydrograph, Jequetepeque river

Abstract

The research proposes a hydrological model to forecast recessive flows and it estimates a depletion coefficient for the "Jequetepeque" river, water from the top of the "Gallito Ciego", Contumazá, Peru. Recessive flows were used from the third break point of the flow hydrograph of the "Yonán" station of the "Jequetepeque" river, period 1988 - 2019. An exponential category hydrological model (ALVI) was used. Ranges of depletion coefficients 0.0148 < α < 0.0003 day^-1, and a calibration coefficient of 0.005 day^-1 were identified. The proposed model, ALVI, was validated, and it is based on statistical indicators, such as: NS (0.84), RMSE (0.62), R²(0.97), EEE (0.66) and IWM (0.84). The statistical indicators indicated a high degree of efficiency, it is inside within the metric of the ranges of the statistical indicators. The hydrological model (ALVI) was validated: Qb = Q0 / (1+e [1.32*Ln ((Q0/Qf) -1) - (0.003*Ln(A)+0.0057)*t]). The observed and simulated flows were identical to the non-parametric Mann-Whitney U test. The RStudio Cloud program was used with a significance level of 0.05, it was determined from the median that the observed and simulated flows are similar or identical.

Author Biographies

Jairo Isaí Alvarez Villanueva, Universidad Nacional de Cajamarca, Ingeniería Hidráulica, Av. Atahualpa Nº 1050, Cajamarca, Perú.

José Francisco Huamán Vidaurre, Universidad Nacional de Cajamarca, Ingeniería Hidráulica, Av. Atahualpa Nº 1050, Cajamarca, Perú.

References

Aksoy, H., & Wittenberg, H. (2015). Baseflow Recession Analysis for Flood-Prone Black Sea Watersheds in Turkey. CLEAN – Soil, Air, Water, 43(6), 857–866. https://doi.org/10.1002/CLEN.201400199

Anderson, M. G., & Burt, T. P. (1980). Interpretation of recession flow. Journal of Hydrology, 46(1–2), 89–101. https://doi.org/10.1016/0022-1694(80)90037-2

Arciniega-Esparza, S., Breña-Naranjo, J. A., Pedrozo-Acuña, A., & Appendini, C. M. (2017). HYDRORECESSION: A Matlab toolbox for streamflow recession analysis. Computers & Geosciences, 98, 87–92. https://doi.org/10.1016/J.CAGEO.2016.10.005

Arnold, J. G., Allen, P. M., Muttiah, R., & Bernhardt, G. (1995). Automated Base Flow Separation and Recession Analysis Techniques. Groundwater, 33(6), 1010–1018. https://doi.org/10.1111/J.1745-6584.1995.TB00046.X

Balocchi, F., Pizarro, R., Morales, C., & Olivares, C. (2014a). Mathematical modeling of recessive flows in the andean mediterranean region of maule; case study of estero upeo, Chile. Tecnologia y Ciencias Del Agua, 5(5).

Balocchi, F., Pizarro, R., Morales, C., & Olivares, C. (2014b). Tecnología y Ciencias del Agua. In Tecnología y ciencias del agua (Vol. 5, Issue 5). Instituto Mexicano de Tecnología del Agua. http://www.scielo.org.mx/scielo.php?script=sci_arttext&pid=S2007-24222014000500011&lng=es&nrm=iso&tlng=es

Brutsaert, W., & Nieber, J. L. (1977). Regionalized drought flow hydrographs from a mature glaciated plateau. Water Resources Research, 13(3), 637–643. https://doi.org/10.1029/WR013I003P00637

Cabrera, J. (2009). Calibración de Modelos Hidrológicos. Imefen.Uni.Edu.Pe, 1.

Callède, J., Guyot, J. L., Ronchail, J., L’Hôte, Y., Niel, H., & De Oliveira, E. (2011). Evolution du debit de l’Amazone à Óbidos de 1903 à 1999 / Evolution of the River Amazon’s discharge at Óbidos from 1903 to 1999. 49(1), 85–98. https://doi.org/10.1623/HYSJ.49.1.85.53992

Carlotto, T., & Chaffe, P. L. B. (2019). Master Recession Curve Parameterization Tool (MRCPtool): Different approaches to recession curve analysis. Computers & Geosciences, 132, 1–8. https://doi.org/10.1016/J.CAGEO.2019.06.016

Costa, D., Zhang, H., & Levison, J. (2021). Impacts of climate change on groundwater in the Great Lakes Basin: A review. Journal of Great Lakes Research, 47(6), 1613–1625. https://doi.org/10.1016/J.JGLR.2021.10.011

Haddeland, I., Heinke, J., Biemans, H., Eisner, S., Flörke, M., Hanasaki, N., Konzmann, M., Ludwig, F., Masaki, Y., Schewe, J., Stacke, T., Tessler, Z. D., Wada, Y., Wisser, D., Designed, J. S., & Performed, D. W. (n.d.). Global water resources affected by human interventions and climate change. https://doi.org/10.1073/pnas.1222475110

Homsi, R., Sanusi Shiru, M., Shahid, S., Ismail, T., Bin Harun, S., Al-Ansari, N., Chau, K.-W., & Mundher Yaseen, Z. (2020). Engineering Applications of Computational Fluid Mechanics ISSN: (Print) (a Precipitation projection using a CMIP5 GCM ensemble model: a regional investigation of Syria; e Sustainable Developments in Civil. Engineering Applications of Computational Fluid Mechanics, 14(1), 90–106. https://doi.org/10.1080/19942060.2019.1683076

Jones, P. N., & McGilchrist, C. A. (1978). Analysis of hydrological recession curves. Journal of Hydrology, 36(3–4), 365–374. https://doi.org/10.1016/0022-1694(78)90154-3

Kirchner, J. W. (2009). Catchments as simple dynamical systems: Catchment characterization, rainfall-runoff modeling, and doing hydrology backward. Water Resources Research, 45(2), 2429. https://doi.org/10.1029/2008WR006912

Krause, P., Boyle, D. P., & Bäse, F. (2005). Comparison of different efficiency criteria for hydrological model assessment. Advances in Geosciences, 5, 89–97. https://doi.org/10.5194/ADGEO-5-89-2005

Lee, J., Kim, J., Jang, W. S., Lim, K. J., & Engel, B. A. (2018). Assessment of Baseflow Estimates Considering Recession Characteristics in SWAT. Water 2018, Vol. 10, Page 371, 10(4), 371. https://doi.org/10.3390/W10040371

Maillet, E. (1905). Essais d’Hydraulique souterraine et fluviale. Nature, 72(1854), 25–26. https://doi.org/10.1038/072025a0

Moncada, W., & Willems, B. (2020). Tendencia anual del caudal de salida, en referencia. Ecología Aplicada, 19(2), 2020. https://doi.org/10.21704/rea.v19i2.1560

Neff, B., & Nicholas, J. (2005). Incertidumbre en el balance hídrico de los Grandes Lagos. https://pubs.er.usgs.gov/publication/sir20045100

Patterson, L. A., Lutz, B., & Doyle, M. W. (2013). Climate and direct human contributions to changes in mean annual streamflow in the South Atlantic, USA. Water Resources Research, 49(11), 7278–7291. https://doi.org/10.1002/2013WR014618

Pizarro-Tapia, R., Balocchi-Contreras, F., Garcia-Chevesich, P., Macaya-Perez, K., Bro, P., León-Gutiérrez, L., Helwig, B., & Valdés-Pineda, R. (2013). On Redefining the Onset of Baseflow Recession on Storm Hydrographs. Open Journal of Modern Hydrology, 03(04), 269–277. https://doi.org/10.4236/OJMH.2013.34030

Segadelli, S., Filippini, M., Monti, A., Celico, F., & Gargini, A. (2021). Estimation of recharge in mountain hard-rock aquifers based on discrete spring discharge monitoring during base-flow recession. Hydrogeology Journal, 29(3), 949–961. https://doi.org/10.1007/S10040-021-02317-Z/FIGURES/7

Shaw, S. B., & Riha, S. J. (2012). Examining individual recession events instead of a data cloud: Using a modified interpretation of dQ/dt–Q streamflow recession in glaciated watersheds to better inform models of low flow. Journal of Hydrology, 434–435, 46–54. https://doi.org/10.1016/J.JHYDROL.2012.02.034

Stoelzle, M., Stahl, K., & Weiler, M. (2013). Are streamflow recession characteristics really characteristic? Hydrology and Earth System Sciences, 17(2), 817–828. https://doi.org/10.5194/HESS-17-817-2013.