Citas bibligráficas
Yaranga, D., (2017). Simulación hidrológica en la cuenca del río Mala usando modelos hidrológicos agregados y semidistribuidos [Tesis, Universidad Nacional Agraria La Molina]. https://hdl.handle.net/20.500.12996/3054
Yaranga, D., Simulación hidrológica en la cuenca del río Mala usando modelos hidrológicos agregados y semidistribuidos [Tesis]. : Universidad Nacional Agraria La Molina; 2017. https://hdl.handle.net/20.500.12996/3054
@misc{renati/246378,
title = "Simulación hidrológica en la cuenca del río Mala usando modelos hidrológicos agregados y semidistribuidos",
author = "Yaranga Lázaro, David",
publisher = "Universidad Nacional Agraria La Molina",
year = "2017"
}
The use of hydrological models is a necessity and a tool when trying to understand the different processes that occur in the hydrological cycle. Furthermore, it provides us with the ability to calculate the water availability in places lacking hydrological stations. That is precisely the reason why it is useful for the planning and management of water usage. In the current study, aggregate and semi-distributed hydrological models under the RS-Minerve platform were applied in the case of the Mala river basin, which was measured on a daily-scale basis. In the basin that we are making reference to, 15 sub-basins were identified upstream the hydrological station at La Capilla and each sub-basin was divided in altitudinal ranges. The processes taken into account for the hydrological models applied in the study are: interception, infiltration, evapotranspiration, percolation, surface flow, groundwater and base flow. Prior to the modeling, an exploratory and a statistical analysis of the hydro-meteorological information was performed. The calibration of the models was carried out using daily average discharges registered in the station La Capilla between December 01, 2002 to December 31, 2010; for the following models: Sacramento, Socont, HBV and GR4J. The time between January 01, 2011 and March 31, 2015 was used for the validation of the models using the parameters obtained in the calibration. In order to test the models’ performance and adjustability, the following were used: Nash quotient indicators, Nash Ln, Pearson quotient, relative root mean squared error (RRMSE), the RSR reason, which relates the square root of the mean squared error and the standard deviation of the observations, and the volumetric error (Ev). Judging by the results shown on the indicators, the Sacramento hydrological model proved to have the best performance when matched against the four models used in the study. Likewise, the parameters sensibility analysis of each model used in the study was performed according to the Nash indicators and the Pearson quotient. Lastly, river flow simulations in 15 sub-basins were done using the Sacramento hydrological model.
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