Temporal variation of irrigation requirements in corn Rodionov method in DR001, Pabellón, Aguascalientes
DOI:
https://doi.org/10.29312/remexca.v14i5.3084Keywords:
climate change, mean changes, rainfall regime, variance changesAbstract
Some of the consequences of climate change will manifest themselves in temporal and spatial variations in precipitation and in an increase in the evaporative demand of the atmosphere, which in turn will lead to an increase in the demand for irrigation of agricultural crops. This work analyzed the temporal variation of agroclimatic irrigation requirements (AIRs) for corn in DR001 Pabellón, Aguascalientes, as well as the thermal growth period (TGP) with information from five climatological stations with 36 years of records. A base temperature of 9 °C was assumed to define three sowing dates: February 15, June 15 and October 15. The AIRs were estimated with a climatological station with more records (1943-2018), the Hargreaves method was used to calculate reference evapotranspiration and the United States Agricultural Service method was used for effective precipitation. The temporal variation (mean and standard deviation) of the AIRs was performed by the Rodionov method, by means of the indices of regime changes in the mean and in the variance (CSSI). The index values of regime changes indicate that an increase in the AIRs began in 1995, for the sowing date February 15, an initial change was observed in 2009 for that of June 15, while for October 15 there is an increase in the year 1993 with another in the years 2012 to 2018. No changes in CSSI, with evidence of changes in the AIRs, which are related to the variation of precipitation and temperature.
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Al Hinai, A. and Jayasuriya, H. 2021. Enhancing economic productivity of irrigation water by product value addition: case of dates. J. Saudi Soc. Agric. Sci. 20(8):553-558. https://doi.org/10.1016/j.jssas.2021.06.007.
Alexandersson, H. 1986. A homogeneity test applied to precipitation data. J. Climatol. 6(6):661-675. https://doi.org/10.1002/joc.3370060607. DOI: https://doi.org/10.1002/joc.3370060607
Allen, R. G.; Pereira, L. S.; Raes, D. y Smith, M. 2006. Evapotranspiración del cultivo: guía para la determinación de los requerimientos de agua de los cultivos, Roma. FAO 298. 17-28 pp.
Arista-Cortes, J.; Quevedo-Nolasco, A.; Zamora-Morales, B. P.; Bauer-Mengelberg, R.; Sonder, K. y Lugo-Espinosa, O. 2018. Temperaturas base y grados días desarrollo de 10 accesiones de maíz de México. Rev. Mex. Cienc. Agríc. 9(5):1023-1033. https://doi.org/10.29312/remexca.v9i5.1507.
CNA. 2005. Comisión Nacional del Agua. Formulación del plan director para la modernización integral del riego del distrito de riego 001, Pabellón. Subdirección general de infraestructura hidroagrícola gerencia de distritos de riego. 204 p.
CNA. 2018. Comisión Nacional del Agua. Estadísticas del agua en México. Capítulo 1. Contexto geográfico y soberanía socioeconómica. Secretaría de Medio Ambiente y Recursos Naturales. 10-25 pp. http://sina.conagua.gob.mx/publicaciones/EAM-2018.pdf.
Cortez-Villa, J.; Quevedo-Nolasco, A.; Arteaga-Ramírez, R. y Carrillo-Flores, G. 2021. Tendencia de la sequía meteorológica en el estado de Durango, México, por el método de Rodionov. Tecnología y ciencias del agua. 11(1):85-131. https://doi.org/10.24850/j-tyca-2020-01-03.
Easterling, D. R. and Peterson, T. C. 1995. A new method for detecting undocumented discontinuities in climatological time series. Inter. J. Climatol. 15(4):369-377. https://doi.org/10.1002/JOC.3370150403. DOI: https://doi.org/10.1002/joc.3370150403
FAO. 1992. Food and Agriculture Organization. Cropwat a computer program for irrigation planning and management. Irrigation and drainage paper 46. Rome. 65-80 pp.
FAO. 2012. Food and Agriculture Organization. Respuesta del rendimiento de los cultivos al agua. 119-125. http://www.fao.org/3/a-i2800s.pdf.
Gomaa, M. A.; Kandil, E. E.; El-Dein, A. A. M. Z.; Abou-Donia, M. E. M.; Ali, H. M. and Abdelsalam, N. R. 2021. Increase maize productivity and water use efficiency through application of potassium silicate under water stress. Scientific Reports. 11(1):1-8. https://doi.org/10.1038/s41598-020-80656-9.
Gullett, D. W.; Vincent, L. and Sajecki, P. J. F. 1990. Testing for homogeneity in temperature time series at Canadian climate stations. Atmospheric Environment Service. ON, Canada. 4-90 pp.
Kadambot, H. M. and Siddique, H. B. 2014. Water deficits: development. In: Encyclopedia of Natural Resources: land. Taylor and Francis: New York. 522-525 pp. DOI: https://doi.org/10.1081/E-ENRL-120049220
Lilliefors, H. W. 1967. On the Kolmogorov-Smirnov test for normality with mean and variance unknown. J. Am. Stat. Assoc. 62(318):399-402. Doi: 200.130.19.152. DOI: https://doi.org/10.1080/01621459.1967.10482916
López, F. A. J. y Hernández, C. D. 2016. Cambio climático y agricultura: una revisión de la literatura con énfasis en américa latina. El trimestre económico. 83(332):459-496. DOI: https://doi.org/10.20430/ete.v83i332.231
Maronna, R. and Yohai, V. J. 1978. A bivariate test for the detection of a systematic change in mean. J. Am. Stat. Assoc. 73(363):640-645. https://doi.org/10.1080/01621459 .1978.10480070. DOI: https://doi.org/10.1080/01621459.1978.10480070
Martínez-Austria, P. y Patiño-Gómez, C. 2012. Efectos del cambio climático en la disponibilidad de agua en México El cambio climático. Tecnología y Ciencias del Agua. 3(1):5-20.
Ojeda-Bustamante, W.; Hernández, B. L. y Sánchez, C. I. 2008. Tecnificación del riego. In: manual para diseño de zonas de riego pequeñas. Ed. Instituto Mexicano de Tecnología del Agua. México. Capítulo 1:15-44.
Ojeda-Bustamante, W.; Sitafuentes-Ibarra, E.; González-Camacho, J. M. y Guillen-González, J. A. y Unland-Weiss, H. 1999. Pronóstico del riego en tiempo real. Instituto Mexicano de Tecnología del Agua. México, DF. 17-80.
Perry, C.; Steduto, P.; Allen, R. G. and Burt, C. M. 2009. Increasing productivity in irrigated agriculture: agronomic constraints and hydrological realities. Agricultural Water Management. 96(11):1517-1524. https://doi.org/10.1016/j.agwat.2009.05.005. DOI: https://doi.org/10.1016/j.agwat.2009.05.005
Ramírez-Cabral, N.; Medina-García, G. and Kumar, L. 2020. Increase of the number of broods of fall armyworm (Spodoptera frugiperda) as an indicator of global warming. Rev. Chapingo Ser. Zonas Áridas. 19(1):1-16. https://doi.org/10.5154/r.rchsza.2020.11.01.
Rodionov, S. 2004. A sequential algorithm for testing climate regime shifts. Geophysical Research Letters. 31(9):2-5. Doi: 10.1029/2004GL019448. DOI: https://doi.org/10.1029/2004GL019448
Rodionov, S. 2005. A brief overview of the regime shift detection methods. Joint Institute for the Study of the Atmosphere and Ocean, University of Washington, Seattle, WA 98195, USA. 17-24. https://www.beringclimate.noaa.gov/regimes/rodionov-overview.pdf.
Rodionov, S. 2006. Help with regime shift detection software. Retrieved from. https://www.beringclimate.noaa.gov/regimes/help3.html.
Rodionov, S. and Overland, J. 2005. Application of a sequential regime shift detection method to the Bering Sea ecosystem. J. Marine Sci. 62(3):328-332. Doi: 10.1016/j.icesjms.2005.01.013. DOI: https://doi.org/10.1016/j.icesjms.2005.01.013
SADER-SIAP. 2020. Secretaría de Agricultura y Desarrollo Rural y Servicio de Información Agroalimentaria y Pesquera. Panorama Agroalimentario. Publicaciones SIAP. 90-92 pp. https://nube.siap.gob.mx/gobmx-publicaciones-siap/pag/2020/Atlas-Agroalimentario-2020.
Serna, L. 2022. Maize stomatal responses against the climate change. Frontiers in Plant Science. 13:01-09. https://doi.org/10.3389/fpls.2022.952146.
SMN. 2021. Servicio Meteorológico Nacional. Información estadística climatológica. https://smn.conagua.gob.mx/es/climatologia/informacion-climatologica/informacion-estadistica-climatologica.
Soares, M. D.; Peña A. y García, M. E. 2018. Una aproximación al marco conceptual, institucional y normativo relativo al cambio climático. In: Soares, M. D. y Peña, A. Ed. Impacto del cambio climático para la gestión integral de la cuenca hidrológica del río Apatlaco. Instituto Mexicano de Tecnología del Agua. 28-39 pp.
Tayanç, M.; Nüzhet, D. H.; Karaca, M. and Yenigün, O. 1998. A comparative assessment of different methods for detecting inhomogeneities in Turkish temperature data set. Inter. J. Climatol. 18(5):561-578. Doi: 10.1002/(sici)1097-0088(199804)18:5<561:aid-joc249 >3.0.co;2-y. DOI: https://doi.org/10.1002/(SICI)1097-0088(199804)18:5<561::AID-JOC249>3.0.CO;2-Y
Trenberth, K. E. and Asrar, G. R. 2014. Challenges and opportunities in water cycle research: WCRP contributions. Surv Geophys. 35:515-532. https://doi.org/10.1007/s107 12-012-9214-y. DOI: https://doi.org/10.1007/s10712-012-9214-y
Trenberth, K. E. and Fasullo, J. T. 2012. Tracking earth’s energy: from El Niño to global warming. Surv Geophys. 33(1):413-426. https://doi.org/10.1007/s10712-011-9150-2. DOI: https://doi.org/10.1007/s10712-011-9150-2
Trenberth, K. E.; Fasullo, J. T. and Balmaseda, M. A. 2014. Earth’s energy imbalance. J. Climate. 27(9):3129-3144. https://doi.org/10.1175/JCLI-D-13-00294.1. DOI: https://doi.org/10.1175/JCLI-D-13-00294.1
Utset, A. and Martínez-Cob, A. 2003. Estimación del posible efecto del cambio climático en el balance hídrico del maíz cultivado en una llanura mediterránea. Estudio de la zona no saturada del suelo. 305-312 pp.
Wilhite, D. A. and Glantz, M. H. 1985. Understanding: the drought phenomenon: the role of definitions. Water International. 10(3):111-120. Doi: 10.1080/02508068508686328 535. DOI: https://doi.org/10.1080/02508068508686328
Woznicki, S. A.; Nejadhashemi, A. P. and Parsinejad, M. 2015. Climate change and irrigation demand: Uncertainty and adaptation. Journal of Hydrology: Regional Studies. 3(1):247-264. ISSN 2214-5818. https://doi.org/10.1016/j.ejrh.2014.12.003. DOI: https://doi.org/10.1016/j.ejrh.2014.12.003
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