Bibliographic citations
Zárate, C., (2020). Modelamiento hidrológico de caudales medios mensuales en cuencas sin información hidrométrica aplicando el método Lutz Scholz y las redes neuronales artificiales, en la microcuenca Huajuiri - Oropesa - Antabamba - Apurímac [Tesis, Universidad Peruana de Ciencias Aplicadas (UPC)]. http://hdl.handle.net/10757/656781
Zárate, C., Modelamiento hidrológico de caudales medios mensuales en cuencas sin información hidrométrica aplicando el método Lutz Scholz y las redes neuronales artificiales, en la microcuenca Huajuiri - Oropesa - Antabamba - Apurímac [Tesis]. PE: Universidad Peruana de Ciencias Aplicadas (UPC); 2020. http://hdl.handle.net/10757/656781
@misc{renati/396316,
title = "Modelamiento hidrológico de caudales medios mensuales en cuencas sin información hidrométrica aplicando el método Lutz Scholz y las redes neuronales artificiales, en la microcuenca Huajuiri - Oropesa - Antabamba - Apurímac",
author = "Zárate Torres, Cynthia",
publisher = "Universidad Peruana de Ciencias Aplicadas (UPC)",
year = "2020"
}
Central problem exposed in this thesis is lack of hydrometric information in some basins of Peru, in our case in Huajuiri micro basin, located in Oropesa district, Antabamba province, Apurímac department, there is a deficit of hydrometric stations with respect to the number of existing basins at national level, hydrometric information is insufficient and deficient, which results in not having data such as average monthly flows, relevant hydrological information to be able to know the water availability of basin in order to distribute water according to requirements of rural communities surrounding the water source, it is useful to design future hydraulic construction, as well as to carry out projections regarding the water behavior of basin. It is for this reason that calculation of average monthly flows in basins without information is proposed using Lutz Scholz method and artificial neural networks. In basin with hydrometric information (La Angostura), with proposed hydrological modeling, values were obtained close to average monthly flows. However, in basin without hydrometric information (Huajuiri), inclusion in hydrological modeling of artificial neural networks allowed obtaining values closer to flow measurement, than only by applying Lutz Scholz method.
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