Climatic hazard indicators for rainfed maize in a developing country: the case of Bajo Balsas, Mexico

Abstract

Introduction: Rainfed agriculture is one of the most vulnerable forms of crop to the effects of climate change producing either drought or excess moisture and thus damaging crops and causing substantial economic damage. In developing countries with scarce resources for technological investment, rainfed agriculture is extremely important for the food production. The sowing of seasonal maize in the Bajo Balsas is for self-consumption, thence the importance of identifying climatic hazard indicators that threaten agricultural production of this culture. The purpose of this study was to build and validate climatic hazard indicators considering the different phenological stages of the plant. Method: First, we identify the climatic variables and characterize the phenological cycle of maize variety that is cultivated in the region; then we elaborate a database with the following daily and monthly climatic parameters: pluvial precipitation, maximum temperature and minimum temperature. We applied data mining with the WEKA software to validate and classify the maize production of 18 years, then, the years were classified by production defining three classes: 1) low hazard: a sinister area from 0 to 10%, without drought reports; 2) moderate hazard: a sinister area from 11 to 50%, with moderate drought reports; 3) high hazard: a sinister area from 51 to 100%, with reports of severe drought. Results: We determined ten climatic hazard indicators of which four correspond to the number of days with precipitation lower than zero in the months of June, July, August and September (DDE0jun, DDE0jul, DDE0aug, DDE0sep); two indicators with rainfall equal to 5 mm for June and August (DDL5jun, DDL5aug); two indicators associated with the maximum temperature of July and August (TX38jul, TX38aug), and two indicators with precipitation equal to or greater than 10 mm in October and November (WDH10oct, WDH10nov). The result of the Kappa statistic was 0.91, indicating a high reliability in the classification of three hazardness categories: high, moderate and low. Conclusion: The proposed method on the validation of climatic hazard with the WEKA software allowed to identify the most important indicators that affect the maize phenological cycle and therefore its yield; the mathematical validation of the method shows three primary indicators, which indicates that there are primary and secondary variables that determine its climatic hazard. The indicators of climatic hazard were automated and adjusted using ICC® (Indicators of Climatic Change) which offers a useful tool for future research on climate hazard analysis of other rainfed crops.

Keywords

• rainfed maize
• agriculture
• data mining analysis
• WEKA
• climatic hazard
• climate change