Abstract

ARAGON-HERNANDEZ, José Luis et al. Spatial distribution of hydrological variables. Implementation and evaluation of interpolation methods. Ing. invest. y tecnol. [online]. 2019, vol.20, n.2. ISSN 2594-0732.  https://doi.org/10.22201/fi.25940732e.2019.20n2.023.

Hydrological variables, on the one hand, have an important temporal and spatial distribution and on the other, they are registered with measuring equipment in a timely manner. For its use in engineering applications, it is sometimes necessary to consider its spatial distribution or the average value of the study area; for this, it is necessary to use interpolation methods of variables, which allow these distributions to be made from point data. To perform the spatial distribution of hydrological variables, a calculation code was developed through information in ASCII format, which incorporates three interpolation methods of variables (Thiessen polygons, inverse of distance and ordinary Kriging); It also allows to calculate the average rainfall of the study area with distributed and timely information; the latter with two traditional methods (arithmetic and Thiessen polygons), whose results can be very easily used as inputs in other models, for example rain-runoff models. The interpolation methods implemented were applied and evaluated in a physical laboratory device and a watershed, through the average rainfall obtained with the isohyets method, cross-correlation and lineal regression. Additionally, the sensitivity of these methods was evaluated based on the cell size by the discretization of the study area, and also with the exponent in the inverse distance method; with the ordinary Kriging method three models of theoretical variograms (exponential, Gaussian and spherical) were used, whose parameters were determined by non-linear regression. The comparison of the methods by the average precipitation from punctual data favors the method of the polygons of Thiessen, however, from the information distributed, the most adequate is the inverse method of the distance. On the other hand, the evaluation of interpolation methods through cross-correlation and lineal regression is led by the ordinary Kriging method.

Keywords : Average rainfall; spatial distribution; interpolation methods; cross correlation; variogram.

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