Benchmark irrigation practices on olives using a structural equation modelling approach

Olive production is currently increasing in Portugal, particularly in the Guadiana river basin. In Serpa and Moura, a traditional region of dry farming olive plantations now comprise up to 50% of the total irrigated area. The present paper reports some of the results of a benchmarking study conducted in the framework of the AquaStress Integrated Project in the Guadiana Case Study (GCS). The aim of the work was to produce references to anticipate water requirements when the future Ardila Irrigation System, which is connected to the Alqueva dam, opens in 2010. This system is intended to supply water to some 30 000 ha of newly irrigated land in the region. During the study, public participation workshops were held to understand the specific needs and points of view of farmers and other stakeholders. The benchmarking analysis was based on continuous monitoring of 28 olive farms and collection of information on practices and production options available in 2007. An originality of this work is the use of a structural equation modelling (SEM) procedure to identify the effects of farmers’ agricultural and irrigation practices on production and quality parameters. SEM is a statistical technique for testing and estimating causal relationships using a combination of statistical data and qualitative causal assumptions. It allows both confirmatory and exploratory modelling, meaning it is suited to both theory testing and development. The benchmarking process was based on participatory workshops that helped farmers understand how to improve their own irrigation and agricultural practices based on the experience of the rest of the group. Our approach was based on a heterogeneous set of plots, and results indicated that certain technical irrigation parameters, namely the number and discharge of drippers per tree, might have a greater influence on final production than total water applied. Such an approach could also be applied to data collected on a regular basis by extension services to identify on long term the influence of production management and practices on productivity.