Estimación de variables climáticas mediante una interpolación espacialmente distribuida
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Date
2024
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Publisher
Universidad de Concepción
Abstract
La agricultura moderna depende de datos climáticos precisos para optimizar el riego y la productividad de los cultivos, sin embargo, la limitada red de estaciones meteorológicas y los nulos datos entregados por estas en algunas áreas de Chile dificulta la obtención de información necesaria para llevar a cabo actividades agrícolas. Esta investigación evalúa una metodología de interpolación para estimar variables climáticas en siete regiones de alta producción agrícola con escasa cobertura de estaciones meteorológicas. Se utilizaron datos diarios de 40 estaciones meteorológicas entre 2018 y 2022, procesados con un código en MATLAB para realizar interpolaciones tridimensionales, integrando las coordenadas de latitud, longitud y los valores de la variable climática a interpolar. La precisión se evaluó mediante NRMSE y gráficos de dispersión 1:1. Los resultados muestran una buena precisión general en la mayoría de las variables, destacando la evapotranspiración de referencia con un NRMSE entre 7,32% y 13,51%, mientras que la interpolación para precipitación y velocidad del viento presentó resultados inaceptables. La metodología demuestra ser efectiva para mejorar la disponibilidad de datos climáticos en áreas con deficiencia de estaciones meteorológicas, facilitando una gestión más eficiente del agua en la agricultura al optimizar las estrategias de riego y reducir el desperdicio de recursos hídricos.
Modern agriculture depends on accurate climatic data to optimize irrigation and crop productivity; however, the limited network of weather stations and the lack of data provided by them in some areas of Chile makes it difficult to obtain the information needed to carry out agricultural activities. This research evaluates an interpolation methodology to estimate climatic variables in seven regions of high agronomic production with low meteorological station coverage. Daily data from 40 meteorological stations between 2018 and 2022 were, processed with a code in MATLAB to perform three-dimensional interpolations, integrating the coordinates of latitude, longitude and the values of the climatic variable to be interpolated. Accuracy was evaluated using NRMSE and scatter plots. The results show a good overall accuracy for most variables, highlighting the reference evapotranspiration with a NRMSE between 7.32% and 13.51%, while the interpolation for precipitation and wind speed presented unacceptable results. The methodology proves to be effective in improving the availability of climate data in areas with a deficiency of meteorological stations, facilitating more efficient water management in agriculture by optimizing irrigation strategies and reducing the waste of water resources.
Modern agriculture depends on accurate climatic data to optimize irrigation and crop productivity; however, the limited network of weather stations and the lack of data provided by them in some areas of Chile makes it difficult to obtain the information needed to carry out agricultural activities. This research evaluates an interpolation methodology to estimate climatic variables in seven regions of high agronomic production with low meteorological station coverage. Daily data from 40 meteorological stations between 2018 and 2022 were, processed with a code in MATLAB to perform three-dimensional interpolations, integrating the coordinates of latitude, longitude and the values of the climatic variable to be interpolated. Accuracy was evaluated using NRMSE and scatter plots. The results show a good overall accuracy for most variables, highlighting the reference evapotranspiration with a NRMSE between 7.32% and 13.51%, while the interpolation for precipitation and wind speed presented unacceptable results. The methodology proves to be effective in improving the availability of climate data in areas with a deficiency of meteorological stations, facilitating more efficient water management in agriculture by optimizing irrigation strategies and reducing the waste of water resources.
Description
Tesis presentada para optar al título de Ingeniero Agrónomo
Keywords
Interpolación (Matemáticas), Meteorología, Evapotranspiración