Drought and genetic programming to approach annual agriculture production normalized curves

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.

Keywords

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