- author = "F. Javier Ruiz-Ortega and Eddie Clemente and Alicia Martinez-Rebollar and J. Jasson Flores-Prieto",
- title = "An evolutionary parsimonious approach to estimate daily reference evapotranspiration",
- journal = "Scientific Reports",
- year = "2024",
- volume = "14",
- pages = "Article: 6736",
- keywords = "genetic algorithms, genetic programming, GPLAB, ETo, Climate sciences, Hydrology",
-
URL = "
https://rdcu.be/dJ1oU",
-
URL = "https://human-competitive.org/sites/default/files/entryform_4.txt",
-
URL = "
https://human-competitive.org/sites/default/files/paper_3.pdf",
-
DOI = "
10.1038/s41598-024-56770-3",
- broken_data = "https://cimis.water.ca.gov/",
-
video_url = "https://mediaspace.msu.edu/media/Ortega+movie+submitted+for+Humies%2C+July+17%2C+2024/1_d48rihmb",
- size = "23 pages",
- abstract = "The reference evapotranspiration (ETo) is an essential component in hydrological and ecological processes. The objective of this research is to develop an explicit model to estimate ETo only using commonly measurable meteorological parameters such as relative humidity, air temperature, and wind speed, where the measurements corresponding to solar radiation are omitted. The model was generated using Genetic Programming (GP), evaluated, and validated with reference data ETo using FAO56-PM. This reference data was obtained from different climates (warm-temperate and arid-warm) and latitudes, acquired from CIMIS stations in the state of California, United States, and the El Porvenir station in the state of Coahuila, in north-central Mexico. a total of 3754 results were generated, demonstrating a significant improvement in the estimation of ETo compared to the Hargreaves Samani model. our approach outperformed the Hargreaves-Samani model in the testing phase by 16%...",
-
notes = "HUMIES 2024 FINALIST
1st author: Francisco Javier Ruiz Ortega",
