Author(s): Mauricio Guillermo Ramirez Ambriz; Maritza Liliana Arganis Juarez; Ramon Dominguez Mora; Alejandro Mendoza Resendiz; Eliseo Carrizosa Elizondo; Eduardo Juan Diego
Linked Author(s): Mauricio Guillermo Ramirez Ambriz, Maritza Liliana Arganis Juárez, Alejandro Mendoza
Keywords: Probability distribution function; Area reduction factors; Convectivity factors; Rainfall-runoff methods; Distributed parameter models
Abstract: The estimation of design floods is of utmost importance, both for the proper development, in the construction stage of a work, and to ensure the safety of the same. For this reason, design floods are estimated from hydrometric and climatological data, using rainfall-runoff methods. These methods make it possible to determine runoff using characteristics specific to the basin and rainfall data, which are usually more abundant than runoff data. The watershed analysed in this study is located in Hydrological Region 22, Tehuantepec, which belongs to the State of Oaxaca, Mexico. The river called Los Perros, in recent years has registered several overflows of the main channel; this river crosses several important cities, such as: Ixtepec, Ixtaltepec and Juchitan de Zaragoza. In order to mitigate the effects, it is necessary to carry out an adequate estimation of the design floods that will be associated with different return periods for an analysis of the effects of the area. At present, there are several computer tools that contribute to the application of distributed parameter models. The Runoff Forecasting Model (MPE), developed by the Institute of Engineering of the UNAM, has the purpose of obtaining runoff hydrographs of a basin. The methods used in this work are based on the estimation of Area Reduction Factors (ARF) and Convectivity Factors, which help to estimate statistical storms and subsequently obtain design floods associated with different return periods with the support of probability distribution functions.
DOI: https://doi.org/10.3850/978-90-833476-1-5_iahr40wc-p0743-cd
Year: 2023