Generation of daily and monthly flows using the GR4j Method and the ERA5 gridded climate information in the Pachachaca basin up to the Santa Rosa station

Proceedings of the 20th LACCEI International Multi-Conference for Engineering, Education and Technology: “Education, Research and Leadership in Post-pandemic Engineering: Resilient, Inclusive and Sustainable Actions” Pub Date : 1900-01-01 DOI:10.18687/laccei2022.1.1.306

Cesar David Alfaro-Gurrionero, Shantall Valeria Sovero-Gómez, Abel Carmona-Arteaga, Neicer Campos-Vásquez

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Abstract

– The objective sought with this research is to be able to build a series of daily flows in the Pachachaca basin to the Santa Rosa hydrometric station for a period of 30 years (1990-2020). These have been generated using rainfall and average temperature data from the ERA5 climate grid product and the flow measurement records of the Santa Rosa station for the days between the years 2019 to 2020, using the GR4j method. The simulated downloads were evaluated using statistical techniques of efficiency and error. Satisfactory results were obtained, which are shown in the calibration and validation stage of the GR4j hydrological model, obtaining in the validation a linear equation equal to y=0.9367x + 7.421; where the variable "x" represents the average monthly flows generated with the model and the values of "y" the original average flows registered, with a coefficient R2=0.8814; which is not giving an efficiency value that is between 80% and 100%. Statistical evaluation also showed that the GR4j model performs very well despite using only four parameters. This finding indicates that the evaluated models can be integrated as an alternative for strengthening the daily hydrological forecast in the Antabamba river basin up to the Santa Rosa station.

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利用GR4j方法和ERA5网格化气候信息生成Pachachaca盆地直至Santa Rosa站的日流量和月流量

-本研究的目标是能够在帕查恰卡盆地建立一系列每日流向圣罗莎水文站的流量，为期30年(1990-2020)。这些数据是利用ERA5气候网格产品的降雨和平均温度数据以及圣罗莎站2019年至2020年期间的流量测量记录，使用GR4j方法生成的。模拟下载使用效率和误差的统计技术进行评估。在GR4j水文模型的定标和验证阶段得到了满意的结果，在验证阶段得到线性方程= y=0.9367x + 7.421;其中变量“x”为模型生成的月平均流量，“y”为注册的原始月平均流量，系数R2=0.8814;并没有给出80%到100%之间的效率值。统计评估还表明，尽管只使用了四个参数，GR4j模型的性能仍然非常好。这一发现表明，评估的模型可以作为加强Antabamba河流域直至Santa Rosa站的每日水文预报的替代方案。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Proceedings of the 20th LACCEI International Multi-Conference for Engineering, Education and Technology: “Education, Research and Leadership in Post-pandemic Engineering: Resilient, Inclusive and Sustainable Actions”

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