Analysis of reconstruction of historical series based on stochastic algorithm and IDW algorithm
DOI:
https://doi.org/10.35830/cn.vi92.771Keywords:
deduction of missing data, water resources, rainfallAbstract
Precipitation and temperature are crucial variables of the hydrological cycle, so they should represent spatial and temporal variability through a sufficiently dense distribution. However, the information collected by institutional databases has gaps. The present work analyzes the precipitation series according to the deduction of missing data based on the deterministic algorithm of the Inverse Distance Weighted (IDW) and the stochastic algorithm Multivariate Autoregressive Model of Climate Variables (MASCV). These algorithms were used for the reconstruction of five precipitation series in the Cuitzeo Lake basin. The analysis of the reconstructed series was carried out by means of graphical and quantitative analysis, obtaining acceptable results.
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Copyright (c) 2024 Alejandra Correa González, Marco Antonio Martinez Cinco, Joel Hernández Bedolla , Sonia Tatiana Sánchez Quispe, Mario Alberto Hernández Hernández
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Universidad Michoacana de San Nicolás de Hidalgo, Coordination of Scientific Research, Av. Francisco J. Mujica, Building "C-2", Ciudad Universitaria, Morelia, Michoacán, México, C.P. 58030. All rights reserved. This magazine may be reproduced for non-profit purposes, as long as the full source and its email address are cited. Otherwise it requires prior written permission from the institution and author.
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
