TITLE:
Climate Based Risk Assessment for Maize Producing Areas in Rainfed Agriculture in Mexico
AUTHORS:
I. Sanchez Cohen, G. Esquivel Arriaga, M. A. Velasquez Valle, Marco A. Inzunza Ibarra, Arcadio Muñoz Villalobos, P. Bueno Hurtado
KEYWORDS:
Risk Assessment, Water Balance, Crop Yield, Simulation, Rainfed
JOURNAL NAME:
Journal of Water Resource and Protection,
Vol.6 No.13,
September
29,
2014
ABSTRACT: Rainfed
areas in Mexico accounts for 14 million hectares where around 23 million people
live and are located in places where there is a little climatic information. The
severe drought that has impacted northern Mexico in the past several years as
well as other parts of the country, has forced decision takers to look for
improved tools and procedures to prevent and to cope with this natural hazard.
For this paper, the methodology of the Food and Agricultural Organization of
the United Nations (FAO) for estimating water balance variables was modified to
provide crop yield estimations under rainfed agriculture in maize producer
states of Mexico. The water balance accounts for the daily variation of soil
water content having main input rainfall (Pp) and main output crop
evapotranspiration (Eta). The algorithm computes crop yield using two
distinctive approaches: 1) one based on surplus/deficit functions for each crop
considered and 2) yield estimations based on soil water balance and water
function productions of the crop being analyzed. For computing water balance
and crop yields, a computer model is built that incorporates the FAO method for
water balance (MODEL SICTOD: Computational System for Decision Taking, acronym
in Spanish) which stochastically generate precipitation based on wet/dry
transition probabilities using a first order Markov chain scheme. Maps of
average crop yields were obtained after interpolating model outcomes for the
main maize producer states of Mexico: Jalisco, Michoacan, Guerrero, Puebla
Oaxaca and Chiapas. Different planting dates were analyzed, early (90 days of
length period), intermediate (120 days of length period) and late (150 days of
length period). Crop yield variability correlates to the transition probability
on having a wet day following a dry day. Results have shown high yield
variation and probability of crop yield failure and climatic risk follows a
distinctive pattern according to planting date and rainfall occurrence. The
approach used is of great support for decision taking processes.