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Article
Author(s)
Iván Ayala Bizarro, Joel Oré Iwanaga, David Requena Machuca, Richard Oré Cayetano, Edwin Torres Condori and Edwin Montes Raymundo
Full-Text PDF XML 1219 Views
DOI:10.17265/2162-5298/2018.10.001
Affiliation(s)
Department of Civil Engineering, National University of Huancavelica, Huancavelica 09001, Peru
ABSTRACT
The objective of the
investigation is to carry out the flow routing in the natural channel of the
experimental basin of the Ichu river, by means of the Artificial Intelligence
technique of ANNs (Artificial Neural Networks). Generally, hydrological and
hydraulic methods require different parameters of the river channel, while the
ANNs method simplifies the amount of data. The study area is located in the
experimental basin of the Ichu river, upstream of the city of Huancavelica in
an area of 607 km2. A calibrated and validated model of the
rain-runoff process was developed, with data recorded in 6 automatic
meteorological stations (rainfall) and one hydrological station (runoff). The
model HEC-1 was used to model the rain-runoff process and the Muskingun-Cunge
method for the flood rounting, generating historical records for 5 stretches of
the Ichu riverbed and obtaining 39 maximum historical records in the 2016
periods and 2017. The model obtained values of Nash-Sutcliffe efficiency
coefficients (E) equal to 0.851 and
0.828 for the calibration and validation stage, respectively. The ANNs were
built with different architectures to train and obtain the architecture that
best fits the historical phenomena. Finally, the architecture 1-5-1 presented a
better fit, whose statistical E was values of 0.881 and 0.859 in the training and
validation stage respectively.
KEYWORDS
Rain-runoff process, flood routing, ANNs.
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