Drought and genetic programming to approach annual agriculture production normalized curves

Authors

  • Maritza Liliana Arganis-Juaréz National Autonomous University of Mexico https://orcid.org/0000-0003-1429-1243
  • Ariadne Sofía Drust-Nacarino National Autonomous University of Mexico
  • Rodolfo Silva-Casarín National Autonomous University of Mexico
  • Edgar Gerardo Mendoza-Baldwin National Autonomous University of Mexico
  • Óscar Arturo Fuentes-Mariles National Autonomous University of Mexico

DOI:

https://doi.org/10.17533/udea.redin.n77a09

Keywords:

genetic programming, agricultural production, regionalization, economic loss, drought

Abstract

Drought is a severe, recurrent disaster for Mexican agriculture, causing huge economic losses which could be reduced if appropriate planning and policies were carried out and the production lost could be predicted. This paper presents the application of genetic programming to obtain normalized curves of annual agricultural production for each state in Mexico as a function of the return period of drought events and, from them, an estimation of the normalized value of the yearly production. This value, multiplied by the historic mean production of the state, gives the production expressed in thousand millions of Mexican pesos for a specified return period.  Two techniques were used for this data analysis, the first one is general and includes each state separately; for the second technique the country was divided into 6 groups, depending on the value of the agricultural production’s variation coefficient. The results showed that for the first case large dispersion was found between the reported and computed data, while a better fit was found for the groups; specifically for groups 2, 3 and 6. The resulting functions can be used by decision makers at both federal and state levels, to better deal with drought events.

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Author Biographies

Maritza Liliana Arganis-Juaréz, National Autonomous University of Mexico

Faculty of Engineering.

Ariadne Sofía Drust-Nacarino, National Autonomous University of Mexico

Engineering Institute.

Rodolfo Silva-Casarín, National Autonomous University of Mexico

Engineering Institute.

Edgar Gerardo Mendoza-Baldwin, National Autonomous University of Mexico

Engineering Institute.

Óscar Arturo Fuentes-Mariles, National Autonomous University of Mexico

Faculty of Engineering. Definitive Researcher Holder A, Coordination: Hydraulics.

References

A. Kambekar and M. Deo, “Wave prediction using genetic programming and model trees”, Journal of Coastal Research , vol. 28, pp. 43-50, 2012.

J. Koza, “Hierarchical genetic algorithms operating on populations of computer programs”, in 11 th International Joint Conference on Artificial Intelligence , Detroit, USA, 1989, pp. 768-774.

C. Escalante and L. Reyes, “Análisis de la sequía meteorológica en el norte de México”, in XXII National Congress of Hydraulic , Acapulco, México, 2012, pp. 1-8.

T. Ross and N. Lott, “A climatology of 1980–2003 extreme Weather and climate events”, National Climatic Data Center, Asheville, USA, Tech. Rep. 2003- 01, Dec. 2003.

L. Feyen and R. Dankers, “Impact of global warming on streamfl ow drought in Europe”, Journal of geographical Research-Atmospheres , vol. 114, pp. 1-17, 2009.

N. Zeng, “Drought in the Sahel”, Science , vol. 302, pp. 999-1000, 2003.

B. Bates, Z. Kundzewicz, S. Wu and J. Palutikof, “Climate change and water”, Intergovernmental Panel on Climate Change (IPCC), Geneva, Switzerland, Tech. Paper VI. Jun. 2008.

Food and Agricultural Organisation of United Nations (FAO), “Report of FAO-CRIDA Expert Group Consultation on Farming System and Best Practices for Drought- prone Areas of Asia and the Pacific Region”, Central Research Institute for Dryland Agriculture, Hyderabad, India, Report, 2002.

G. Wong, M. Lambert and A. Metcalfe, “Trivariate copulas for characterisation of droughts”, ANZIAM , vol. 49, pp. 306-323, 2008.

C. Escalante, “La vulnerabilidad ante los extremos: la sequía”, Ingeniería Hidráulica en México , vol. 18, pp. 133-155, 2003.

G. Garza, “Climatología histórica: las ciudades mexicanas antes de la sequía (siglos XVII a XIX)”, Investigaciones Geográficas , vol. 63, pp. 77-92, 2007.

I. Flores and D. Campos, “Detección de periodos de sequía en la zona media del estado de San Luis Potosí, con base en registros precipitación mensual”, Ingeniería Hidráulica en México , vol. 13, pp. 45-56, 1998.

INEGI (National Institute of Statistics and Geography), Referencias geográficas y extensión territorial de México. [Online]. Available: http://www.inegi.org.mx/inegi/SPC/doc/internet/1-GeografiaDeMexico/MAN_REFGEOG_EXTTERR_VS_ENERO_30_2088.pdf. Accessed on: Jun. 1, 2015.

A. Browning , “ Corn, tomatoes, and a dead dog: Mexican agricultural restructuring after NAFTA and rural responses to declining maize production in Oaxaca, Mexico”, Mexican Studies , vol. 29, pp. 85-119, 2013.

E. Florescano and L. Espinosa, Fuentes para el estudio de la agricultura colonial en la diócesis de Michoacán. Series de diezmos, 1636-1810 , 1st ed. México, D. F., México: Instituto Nacional de Antropología e Historia, 1987.

E. Florescano and S. Swan, Breve historia de la sequía en México , 1 st ed. Xalapa, México: Universidad Veracruzana, Dirección Editorial, 1995.

G. Castorena, E. Sánchez, E. Florescano, G. Padilla and L. Rodríguez, Análisis histórico de las sequías en México . México, D. F., México: Secretaría de Agricultura y Recursos Hidráulicos, 1980.

D. Comte, “Weather highlights around the world”, Weatherwise , vol. 47, pp. 23-26, 1994.

D. Comte, “Weather highlights around the world”, Weatherwise , vol. 48, pp. 20-22, 1995.

J. Martínez and A. Fernández, Cambio climático: una visión desde México , 1 st ed. México, D. F., México: Instituto Nacional de Ecología, 2004.

E. Barrios et al., “Avances en el mejoramiento genético del frijol en México por tolerancia a temperatura alta y a sequía”, Revista Fitotecnia Mexicana , vol. 34, pp. 247- 255, 2011.

E. Pimienta, C. Robles and C. Martínez, “Respuesta ecofisiológica de árboles jóvenes nativos y exóticos a sequía y lluvia”, Revista Fitotecnia Mexicana, vol. 35, pp. 15-20, 2012.

Secretaría de Medio Ambiente y Recursos Naturales (SEMARNAT), “Informe de la situación del medio ambiente en México. Compendio de estadísticas ambientales indicadores clave y de desempeño ambiental”, SEMARNAT, México, D. F., México, Report, 2013.

E. Goldstein, G. Coco and A. Murray, “Prediction of wave ripple characteristics using genetic programming”, Continental Shelf Research , vol. 71, pp. 1-15, 2013.

Comisión Nacional del Agua, Estadísticas del agua en México. Sistema Nacional de Información sobre Cantidad, Calidad, Usos y Conservación del Agua . México, D. F., México: Comisión Nacional del Agua, 2006.

C. Conde, R. Ferrer and S. Orozco, “Climate change and climate variability impacts on rain–fed agricultural activities and possible adaptation measures. A mexican case study”, Atmósfera , vol. 19, pp. 181-194, 2006.

G. Medina, C. Ruiz and P. Martínez, Los Climas de México: Una Estratificación Ambiental Basada en el Componente Climático . Guadalajara, México: Centro de Investigación Regional del Pacífico Centro, INIFAP, SAGAR, 1998.

M. Hernandez, L. Torres and G. Valdez, “Sequía meteorológica”, in México: una visión hacia el siglo XXI. El cambio climático en México , C. Gay (ed). México, D. F., México: Instituto Nacional de Ecología, SEMARNAP, Universidad Nacional Autónoma de México, U.S. Country Studies Program, 2000, pp. 25-40.

SAGARPA, Secretaría de agricultura , ganadería, desarrollo rural, pesca y alimentación, 2015. [Online]. Available: http://www.sagarpa.gob.mx/Paginas/default.aspx . Accessed on: Jun. 1, 2015.

W. Riebsame and A. Magalhaes , “Assessing the regional implications of climate variability and change”, in 2 nd World Climate Conference , Geneva, Switzerland, 1990, pp. 415-430.

N. Cramer, “A representation for the adaptive generation of simple sequential programs”, in 1 st International Conference on Genetic Algorithms and the Applications , Pittsburgh, USA, 1985, pp. 183-187.

J. Koza, Genetic Programming . On the Programming of Computers by Means of Natural Selection , 1 st ed. Cambridge, USA: MIT Press, 1992.

K. Parasuraman, A. Elshorbagy and C. Bing, “Estimating Saturated Hydraulic Conductivity Using Genetic Programming”, Soil Science Society of American Journal , vol. 71, pp. 1676-1684, 2007.

H. Azamathulla and A. Zahiri, “Flow discharge prediction in compound channels using linear genetic programming”, Journal of Hydrology , vol. 454-455, pp. 203-207, 2012.

S. Nitsure, S. Londhe and K. Khare, “Wave forecasts using wind information and genetic programming”, Ocean Engineering , vol. 54, pp. 61-69, 2012.

W. Banzhaf, P. Nordin, R. Keller and F. Francone, Genetic Programming: An Introduction: On the Automatic Evolution of Computer Programs and its Applications. San Francisco, USA: Morgan Kaufmann Publishers Inc., 1998.

B. Juárez and E. Hansen, “Mexico: Grain and Feed Annual. Prolonged Drought Devastates Grain and Feed Sector”, Global Agricultural Information Network, Rep. MX2018, Mar. 2012. [Online]. Available: http://gain.fas.usda.gov/Recent%20GAIN%20Publications/Grain%20and%20Feed%20Annual_Mexico%20City_Mexico_3-30-2012.pdf. Accessed on: Jun. 1, 2015.

Comisión Nacional del Agua (CONAGUA), Resúmenes Mensuales (consulta de tabla nacional por entidad federativa y mapas) , 2015. [Online]. Available: http://smn.cna.gob.mx/index.php?option=com_%20content&view=article&id=12&Itemid=77. Accessed on: Jun. 1, 2015.

B. Bonaccorso, A. Cancelliere and G. Rossi, “An analytical formulation of return period of drought severity”, Stochastic Environmental Research and Risk Assessment , vol. 17, pp. 157-174, 2003.

N. Dalezios, A. Loukas, L. Vasiliades and E. Liakopoulos, “Severity-duration-frequency analysis of droughts and wet periods in Greece”, Hydrological Sciences Journal , vol. 45, pp. 751-769, 2000.

Z. Zhou and Z. Wang, “Theory of Drought System Analysis”, Nature and Science , vol. 1, pp. 62-66, 2003.

R. Katz and B. Brown, “Extreme events in a changing climate: variability is more important than averages”, Climatic change , vol. 21, pp. 289-302, 1992. 43. T. Knutson et al., “Tropical cyclones and climate change”, Nature Geoscience , vol. 3, pp. 157-163, 2010.

. T. Knutson et al., “Tropical cyclones and climate change”, Nature Geoscience, vol. 3, pp. 157-163, 2010

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Published

2015-12-16

How to Cite

Arganis-Juaréz, M. L., Drust-Nacarino, A. S., Silva-Casarín, R., Mendoza-Baldwin, E. G., & Fuentes-Mariles, Óscar A. (2015). Drought and genetic programming to approach annual agriculture production normalized curves. Revista Facultad De Ingeniería Universidad De Antioquia, (77), 63–74. https://doi.org/10.17533/udea.redin.n77a09

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