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This paper explores the sensitivity of irrigation energy productivity to changes happening at a farm level. Energy is vital to any agricultural system, particularly in systems which depend on groundwater for irrigation. It has been estimated by Lal (2004) that over 23% of direct energy use for crop production in the US is used for on-farm pumping, with similar results found in the arid zone of India. It is therefore important to know how changes within the environment will affect irrigation energy productivity.

Energy productivity (EP) refers to the outputs derived from energy inputs into a system. EP can be further expressed in terms of physical or economic productivity. In this paper EP is defined in terms of physical output. Physical productivity is a comparison between the quantity of yield produced (kg) and the quantity of the direct energy input (kW). Physical productivity is thus expressed as kg/kW. Assessing EP can help identify pathways to ensure the sustainability of irrigation in the agricultural sector, as well as provide an opportunity to identify the major sources of energy wastage and can aid policy makers in terms of providing a basis for the efficient management of natural resources.

The Vensim (TM) modelling environment was used to construct a model of on-farm irrigation EP for pasture production. Sensitivity analysis was performed to examine the results of changing the values of total crop water requirement and groundwater head lift in order to predict the effect on irrigation energy productivity. In this case, parameters which affect both yield and the energy required for pumping to produce agricultural crops were included. These inputs were changes to Crop Water Requirement (CWR) and groundwater lift head (m). The sensitivity analysis of EP was performed for three different irrigation methods (Flood, Centre Pivot and Drip irrigation). It was found that in both cases the overall trend for each irrigation method was similar; however the relative level of changes were different for each method.

The sensitivity analysis for changing CWR showed that the behaviour of EP when this input was changed was markedly different from current practices. The Flood irrigation method was found to be the most sensitive, followed by the Drip irrigation and then Pivot irrigation methods. When the effect of changing groundwater lift head was explored, it was found that EP is far less sensitive to this input due to smaller level of lift needed, as the behaviour was very similar to that for current practices. A sample result for this sensitivity analysis is shown below (Figure 1). The order of sensitivity between the irrigation methods was the same as the previous case, with the Flood irrigation method being the most sensitive, followed by the Drip irrigation and Pivot irrigation methods. This model was not calibrated against field measurements.

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The system dynamic modelling framework described in this paper could be useful for determining the suitability of different irrigation methods for time varying water and energy settings affecting energy productivity.