Modeling of hydrological processes applying artificial intelligence techniques: a systematic literature review

Keywords: Hydrological modeling, Artificial intelligence, Machine learning, Neural network, Evapotranspiration, Runoff, rainfall, Rainfall

Abstract

The field of hydrology is one of the sciences that focuses on the study, planning and quantification of water resources, generating a significant amount of data, which are indispensable in the branch of civil engineering. Currently these data are analyzed by a variety of techniques, among the predominant ones are artificial intelligence (IA) exclusively applied to the modeling of hydrological processes such as rain-runoff, floods, droughts, evapotranspiration, lake level and flow prediction. This document carried out a systematic review of the literature published between the years 2015 to 2021 in the various databases such as Scopus, Springer Link, EBSCOhost, SciELO and ScienceDirect. For this, a protocol process was established in which the selected database, definition of search terms and selection filters are entered. Indeed, after considering the protocol process, 50 indexed articles were obtained in addition to 4 articles and 1 book of web pages. As a consequence, it was found that artificial neural networks (ANNs) are the most widely used techniques for modeling hydrological processes where, with innovative programming languages, they can be encoded with much greater versatility. To date, the use of RNA is being implemented with other techniques to generate hybrid models that allow obtaining better estimates.

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Author Biographies

Willians Franklin Rafael Miñope

Ingeniería Civil, Universidad Señor de Sipán, Pimentel, Perú

Pedro Victor Raúl Vilcherres Lizárraga

Ingeniería Civil, Universidad Señor de Sipán, Pimentel, Perú

Sócrates Pedro Muñoz Pérez

Doctor, Universidad Señor de Sipán, Pimentel, Perú

Victor Alexci Tuesta Monteza

Magister, Universidad Señor de Sipán, Pimentel, Perú

Heber Ivan Mejía Cabrera

Magister, Universidad Señor de Sipán, Pimentel, Perú

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Published
2022-01-01
How to Cite
Rafael Miñope, W., Vilcherres Lizárraga, P., Muñoz Pérez, S., Tuesta Monteza, V., & Mejía Cabrera, H. (2022). Modeling of hydrological processes applying artificial intelligence techniques: a systematic literature review. ITECKNE, 19(1). https://doi.org/https://doi.org/10.15332/iteckne.v19i1.2645
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Accepted for Publication