Food security resilience against El Niño 2026 phenomenon in Ecuador: Analysis of availability and access using artificial intelligence and satellite big data
DOI:
https://doi.org/10.56124/allpa.v9i18.0163Keywords:
el niño 2026; food security; artificial intelligence; satellite big data; EcuadorAbstract
This article evaluates food security resilience in Ecuador facing the imminent 2026 El Niño phenomenon using a Satellite Big Data and Artificial Intelligence approach. Multi-sensor data from NOAA OISST (SST), NASA-USDA SMAP (soil moisture), and CHIRPS (precipitation) missions were integrated with socioeconomic microdata from the 2024 ENDI survey. Using Random Forest, agricultural yield vulnerability in strategic crops (rice and maize) was modeled, achieving an R2-Score of 0.9755 and a Kappa of 0.8780. Markov Chain analysis projects an 85% probability of an extraordinary event for the January-February 2027 quarter. Results identify Guayas and Los Rios provinces as epicenters of flooding risk and logistical disruption, correlating with increases in food inflation and risks in nutritional utilization. Anticipatory Action mechanisms are proposed, including focused monetary transfers, to mitigate the impact on chronic childhood malnutrition.
Keywords: el niño 2026; food security; artificial intelligence; satellite big data; Ecuador.
Downloads
References
Albuja Echeverría, W. S. (2022). Determinantes Socioeconómicos de La Desnutrición Crónica En Ecuador. Revista de Economía.
Andrade, J. F., & Satorre, E. H. (2015). Environmental Determinants of Annual Grain Yield. Field Crops Research. https://doi.org/10.1016/j.fcr.2015.03.008
Andrian, L., Álvarez, C. M., & Chávez, A. (2024). Efectos del fenómeno El Niño en la Región Andina: Una aproximación empírica. https://doi.org/10.18235/0005512
Arreguín-Cortés, F. I., López-Pérez, M., & Marengo-Mogollón, H. (2016). Las Inundaciones En Un Marco de Incertidumbre Climática. Tecnologia y Ciencias Del Agua, 7(5), 5–13.
Ayala Ayala, M., Lane, M., & Montúfar, R. (2023). Motivations to Adopt Agroecology in Northern Andes of ECUADOR. Ecuadorian J. S.T.E.A.M, 3.
Barrett, C. B. (2010). Measuring Food Insecurity. Science, 327(5967), 825–828. https://doi.org/10.1126/science.1182768
BCRP. (2024). Reporte de Inflación Marzo 2024: Impactos de El Niño En La Región Andina.
Breiman, L. (2001). Random Forests. Machine Learning, 45(1), 5–32. https://doi.org/10.1023/A:1010933404324
Cai, W., McPhaden, M. J., Grimm, A. M., Rodrigues, R. R., Taschetto, A. S., Garreaud, R. D., Dewitte, B., Puel, G., & Vera, C. (2020). Climate impacts of the El Niño–Southern Oscillation on South America. Nature Reviews Earth & Environment, 1(4), 215–231. https://doi.org/10.1038/s43017-020-0040-3
Cai, W., Santoso, A., Collins, M., Dewitte, B., Karamperidou, C., Kug, J.-S., Lengaigne, M., McPhaden, M. J., Stuecker, M. F., Taschetto, A. S., Timmermann, A., Wu, L., Yeh, S.-W., Wang, G., Ng, B., Jia, F., & Yang, Y. (2021). Changing El Niño–Southern Oscillation in a warming climate. Nature Climate Change, 11(6), 488–500. https://doi.org/10.1038/s41558-021-01131-5
Campbell, B. M., Vermeulen, S. J., Aggarwal, P. K., Corner-Dolloff, C., Girvetz, E., Loboguerrero, A. M., Ramirez-Villegas, J., Rosenstock, T. S., Sebastian, L., Thornton, P. K., & Wollenberg, E. (2016). Agriculture and Food Systems to 2050: Global Challenges and Mitigation Opportunities. Global Food Security, 11, 39–43. https://doi.org/10.1016/j.gfs.2016.05.001
Carrillo, J. M., & Parraga-Alava, J. (2018). Decision Trees for Predicting Agricultural Patterns. IEEE ETCM. https://doi.org/10.1109/ETCM.2018.8580295
Cashin, P., Mohaddes, K., & Raissi, M. (2015). Fair Weather or Foul? The Macroeconomic Effects of El Niño. https://doi.org/10.5089/9781484394021.001
Ceccarelli, V., Fremout, T., Chavez, E., Zonneveld, M., & Thomas, E. (2024). Vulnerability to climate change of cultivated and wild cacao in ECUADOR. Science of The Total Environment, 908, 167812. https://doi.org/10.1016/j.scitotenv.2023.167812
CIAT. (2014). Vulnerabilidad Al Cambio Climático de La Agricultura Andina.
Crane-Droesch, A. (2018). Machine Learning Methods for Crop Yield Prediction and Climate Change Impact Assessment in Agriculture. Environmental Research Letters, 13(11), 114010. https://doi.org/10.1088/1748-9326/aae159
Cusme Macias, B. L., & Gaibor, R. (2023). Agricultura Familiar En El Desarrollo Rural de Balzar. Ciencia Latina Revista Científica Multidisciplinar, 7(2), 1240–1255. https://doi.org/10.37811/cl_rcm.v7i2.5410
de la Casa, A., Ovando, G., Bressanini, L., Martínez, J., Díaz, G., & Miranda, C. (2021). Linking Data of ENSO, NDVI-MODIS and Crops Yield. Remote Sensing Applications: Society and Environment, 22, 100480. https://doi.org/10.1016/j.rsase.2021.100480
Fan, S., Yosef, S., & Pandya-Lorch, R. (2019). Reshaping Food Systems: The 2019 Global Food Policy Report. https://doi.org/10.2499/9780896293502
FAO. (2023). Impact of ENSO on Global Food Security: A Comprehensive Review. https://doi.org/10.4060/cc8557en
Fernández, P., Villalba, I., & Sánchez, R. (2021). Monitorización de Aparatos de Vía Frente a Eventos Climáticos Extremas. ResearchGate.
Fukuda, S., Spreer, W., Yasunaga, E., Yuge, R., Sardsud, V., & Müller, J. (2013). Random Forests Modelling for the Estimation of Mango Fruit Yields. Agricultural Water Management, 116, 142–150. https://doi.org/10.1016/j.agwat.2012.10.012
García, M., & Torres, R. (2016). Impactos de la Variabilidad Climática en la Infraestructura Logística Rural de la Costa Ecuatoriana. Revista Ecuatoriana de Ciencia Social y Desarrollo, 7(2), 45–58. https://doi.org/10.1016/j.ecusoc.2016.04.002
Gelagay, H. S., Leroux, L., Tamene, L., & Vlek, P. L. G. (2025). A Crop-Specific and Time-Variant Spatial Framework for Characterizing Rainfed Wheat. Agricultural Systems, 227, 104128. https://doi.org/10.1016/j.agsy.2024.104128
Godfray, H. C. J., Beddington, J. R., Crute, I. R., Haddad, L., Lawrence, D., Muir, J. F., Pretty, J., Robinson, S., Thomas, S. M., & Toulmin, C. (2010). Food Security: The Challenge of Feeding 9 Billion People. Science, 327(5967), 812–818. https://doi.org/10.1126/science.1185383
Grace, D., Lindahl, J., Wanyoike, F., Bett, B., Randolph, T., & Rich, K. M. (2012). Climate Change and Livestock Production: Complex Interactions. Nature Climate Change, 2(3), 145–150.
Hansen, J. W., Hodges, A. W., & Jones, J. W. (1998). ENSO Influences on Agriculture in the Southeastern United States. Agricultural Systems, 57(1), 81–94. https://doi.org/10.1016/S0308-521X(98)00006-2
INEC. (2024a). Encuesta Nacional sobre Desnutrición Infantil (ENDI) 2023-2024: Reporte Técnico.
INEC. (2024b). Encuesta Nacional sobre Desnutrición Infantil (ENDI) 2023-2024: Reporte Técnico.
Jeong, J. H., Resop, J. P., Mueller, N. D., Fleisher, D. H., Yun, K., Timlin, D. J., Shim, K. M., Gerber, J. S., & Timlin, D. (2016). Random Forests for Global and Regional Crop Yield Predictions. PLoS ONE, 11(6), e0156571. https://doi.org/10.1371/journal.pone.0156571
Khaki, S., & Wang, L. (2019). Crop Yield Prediction Using Deep Neural Networks. Frontiers in Plant Science, 10, 621. https://doi.org/10.3389/fpls.2019.00621
Llorente-Isidro, M., Diez-Herrero, A., & Laín-Huerta, L. (2009). Aplicaciones de Los SIG Al Análisis de Inundaciones. Cuadernos de La Sociedad Española de Ciencias Forestales, 29, 115–124.
Mbow, C., Rosenzweig, C., Barioni, L. G., Benton, T. G., Herrero, M., Krishnapillai, M., Liwenga, E., Pradhan, P., Rivera-Ferre, M. G., Sapkota, T., Tubiello, F. N., & Xu, Y. (2019). Food Security - IPCC Special Report on Climate Change and Land.
MTOP. (2025). Diagnóstico de la Red Vial Estatal ante Amenazas Naturales 2024-2025.
Phalkey, R. K., Aranda-Jan, C., Marx, S., Höser, C., & Sauerborn, R. (2015). Systematic review of current efforts to quantify the impacts of climate change on childhood undernutrition. The Lancet Global Health, 3(7), e375–e387. https://doi.org/10.1016/S2214-109X(15)00009-0
Podestá, G. P., Messina, C. D., Grondona, M. O., & Magrin, G. O. (1999). Associations Between Grain Crop Yields in Central-Eastern Argentina and ENSO. Journal of Applied Meteorology, 38(10), 1488–1498. https://doi.org/10.1175/1520-0450(1999)038<1488:ABGCYI>2.0.CO;2
Preti, F., Forzieri, G., & Chirico, G. B. (2011). Forest Cover Influence on Regional Flood Frequency Assessment in Mediterranean Catchments. Hydrology and Earth System Sciences, 15(10), 3077–3090. https://doi.org/10.5194/hess-15-3077-2011
Shukla, P. R., Skea, J., Calvo Buendia, E., Masson-Delmotte, V., Pörtner, H. O., Roberts, D. C., Zhai, P., Slade, R., Connors, S., & van Diemen, R. (2019). Climate Change and Land: An IPCC Special Report on Climate Change, Desertification, Land Degradation, Sustainable Land Management, Food Security, and Greenhouse Gas Fluxes in Terrestrial Ecosystems.
Thielen, D. R., Schuchmann, K.-L., Ramoni-Perazzi, P., Arias, J. I., Quintero, M. E., & Puche, C. (2023a). Effect of extreme El Niño events on the precipitation of Ecuador. Natural Hazards and Earth System Sciences, 23(4), 1507–1523. https://doi.org/10.5194/nhess-23-1507-2023
Thielen, D. R., Schuchmann, K.-L., Ramoni-Perazzi, P., Arias, J. I., Quintero, M. E., & Puche, C. (2023b). Effect of extreme El Niño events on the precipitation of ECUADOR. Natural Hazards and Earth System Sciences, 23(4), 1507–1523. https://doi.org/10.5194/nhess-23-1507-2023
Tirado, M. C., Crahay, P., Mahy, L., Zanev, C., Thompson, B., Jackson, R., Ngongi, N., Brown, L., Croft, L., Izwardi, D., & Sarmiento, O. (2010). Climate Change and Food Safety: A Review. Food Research International, 43(7), 1745–1765. https://doi.org/10.1016/j.foodres.2010.07.003
UNICEF. (2019). Estado Mundial de La Infancia 2019: Niños, Alimentos y Nutrición.
Vicente-Serrano, S. M., Aguilar, E., Martínez, R., Martín-Hernández, N., Azorin-Molina, C., Sánchez-Lorenzo, A., El Kenawy, A., López-Moreno, J. I., Nieto, R., Gimeno, L., & Nieto, R. (2016). The Complex Influence of ENSO on Droughts in ECUADOR. Climate Dynamics, 48(1), 405–427. https://doi.org/10.1007/s00382-016-3082-y
Vincenzi, S., Zucchetta, M., Franzoi, P., Torricelli, P., & De Leo, G. A. (2011). Application of a Random Forest Algorithm to Predict Spatial Distribution of Potential Yield. Ecological Modelling, 222(8), 1471–1478. https://doi.org/10.1016/j.ecolmodel.2011.02.007
Wheeler, T., & von Braun, J. (2013). Climate Change Impacts on Global Food Security. Science, 341(6145), 508–513. https://doi.org/10.1126/science.1239402
WHO. (2019a). Nutrition Landscape Information System Country Indicators.
WHO. (2019b). Nutrition Landscape Information System Country Indicators.
WMO. (2026). El Niño/La Niña Update (February 2026).
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Revista de Ciencias Agropecuarias ALLPA. ISSN: 2600-5883.
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
.jpg)
