CR 38:155-169 (2009)  -  DOI: https://doi.org/10.3354/cr00778

ABSTRACT: Crop production in Southeast Asia is subject to considerable climate variability caused by the El Niño–Southern Oscillation phenomenon. El Niño causes comparatively dry conditions leading to substantial declines in crop yields, with severe consequences for the welfare of local farm households. Using an interdisciplinary modelling approach that combines regression analysis with linear programming (LP) and stochastic simulation, and integrates climatic and hydrologic modelling results, the objective of the present study is to assess the impact of El Niño on agricultural incomes of smallholder farmers in Central Sulawesi, Indonesia, and to derive suitable crop management strategies to mitigate income reductions. We identify 5 farm classes by cluster analysis. Our LP model maximises their cash balance at the end of the time period most severely affected by El Niño. Main activities are the cultivation of rice, maize and cocoa. Accounting for water supply, external Cobb-Douglas production functions generate output according to level of production intensity and predicted weather patterns. Stochastic simulation accounts for variations in crop yields due to factors not captured by the production functions. Iterative model runs produce probability distributions of the model outcomes for each household class, whereby the downside risk of failing to achieve a specified minimum level of income is particularly policy relevant. The results illustrate that drought-related crop management recommendations must be tailored to farm households according to their location, farming system and resource endowment. Furthermore, our findings demonstrate the importance of policy measures aimed at an ex post alleviation of drought impacts.

KEY WORDS: ENSO · Risk management · Linear programming · Stochastic simulation · Indonesia