Flow Routing in the Natural Channel of the Ichu River Experimental Basin through Artificial Neural Networks

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 km 2 . 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.

Generation of Flows Applying a Simple Method of Flood Routing to Monthly Level in La Leche Basin, Peru

“…section of any hydrographic basin, using for this purpose the historical records of the flow upstream of said basin (Bazargan & Norouzi, 2018); previously using the hydrometric and pluviometric information available in the study area (Kang & Zhou, 2018). In this sense, the optimal prediction of flows is required to allow the necessary measures to be taken not only for the protection, evacuation and warning systems of potential vulnerable areas in the short and medium term, but also for water resources management and territorial planning (Ayala et al, 2018). Another relevant aspect is the evaluation of the hydraulic infrastructure, since when maximum flows occur, these directly affect the useful life of the hydraulic infrastructure, generating uncertainty, especially in emergency situations (Guachamín et al, 2019;Matovelle et al, 2022).…”

“…In Peru, the flood routing has been scarcely studied, there are only two investigations published by Ayala et al (2018) and Arriola et al (2021), who point out the great capacity of Muskingum method for the estimation of flows based on the available climatic information. For these reasons, the importance of its application in other river basins arises, being the northwestern zone of Peru, a very important area to study, mainly the La Leche basin.…”