Abstract

CAMPOS-ARANDA, Daniel Francisco. Modeling of the Monthly Rainfall-Runoff Process Through Regressions. Ing. invest. y tecnol. [online]. 2014, vol.15, n.4, pp.625-636. ISSN 2594-0732.

To solve the problems associated with the assessment of water resources of a river, the modeling of the rainfall-runoff process (RRP) allows the deduction of runoff missing data and to extend its record, since generally the information available on precipitation is larger. It also enables the estimation of inputs to reservoirs, when their building led to the suppression of the gauging station. The simplest mathematical model that can be set for the RRP is the linear regression or curve on a monthly basis. Such a model is described in detail and is calibrated with the simultaneous record of monthly rainfall and runoff in Ballesmi hydrometric station, which covers 35 years. Since the runoff of this station has an important contribution from the spring discharge, the record is corrected first by removing that contribution. In order to do this a procedure was developed based either on the monthly average regional runoff coefficients or on nearby and similar watershed; in this case the Tancuilín gauging station was used. Both stations belong to the Partial Hydrologic Region No. 26 (Lower Rio Panuco) and are located within the state of San Luis Potosi, México. The study performed indicates that the monthly regression model, due to its conceptual approach, faithfully reproduces monthly average runoff volumes and achieves an excellent approximation in relation to the dispersion, proved by calculation of the means and standard deviations.

Keywords : linear regression; polynomial regression; correlation coefficient; homogeneity; relative error; statistical parameters.

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