Author(s): Mauricio Guillermo Ramirez Ambriz; Ramon Dominguez Mora; Maritza Liliana Arganis Juarez; Eliseo Carrizosa Elizondo
Linked Author(s): Mauricio Guillermo Ramirez Ambriz, Ramón Domínguez, Maritza Liliana Arganis Juárez
Keywords: Runoff coefficient; Probability distribution function; Rainfall volume; Runoff volumes; Return period “Tr”
Abstract: The runoff coefficient is fundamental to obtain the design flow of hydraulic works helped with rainfall-runoff relationships. This article deals with the variation of the runoff coefficients depending on magnitude of the rains. In general, the techniques used to calculate direct runoff are based on tables and indicators which relate losses to runoff according to soil types and uses but not with the magnitude of the rain, this result in the need to obtain more specific runoff coefficients for studied areas where a good knowledge of the site is necessary. On the other hand, with the curve number method, the runoff coefficient varies according to the magnitude, but it is not validated theoretically or empirically, causing the direct runoff value to be overestimated or underestimated. The runoff coefficient method, used in this article, is based on obtaining volumes of rainfall (weather stations) and runoff (gauging stations) respectively, to subsequently calculate runoff coefficients associated to different return periods (Tr) using a probability distribution functions, regional methods, as well as Reduction Area Factors (RAF). The results obtained are analyzed drawing graphs that compare the total precipitation (P) and the effective precipitation (Pe), observing the behavior of the slope and discarding those greater than 1 (no physical sense), a value equal to one means all the precipitated rain will be transform into runoff, but that is not realistic because infiltration happen. The stations analyzed presented good results according to the records using this technique. For this case, the basins analyzed belong to the Hydrological Regions 10, 19 and 23 located in the States of Sinaloa, Guerrero and Chiapas, Mexico.
DOI: https://doi.org/10.3850/IAHR-39WC252171192022322
Year: 2022