Analyzing the water-energy nexus in the Free State, South Africa

Introduction

South Africa is a major emerging economy with increasing demand for energy and water. With an average annual precipitation of only 450 mm, the country is classified as water stressed. Agriculture consumes almost 60% of surface and ground water for irrigation along with related energy requirements. Owing to complexity of water networks in the economy, regulating this agricultural water supply is a major challenge for policymakers. In order to alleviate the pressure on available water resources this study examined the contribution of blue (ground and surface water reservoirs) and green (rainfall) water used in agricultural systems by applying a System Dynamics Modelling (SDM) approach.

Methods

We used an SDM tool, Vensim PLE, to create a systems model for capturing the interactions of production in agricultural systems. We developed a generic model that can be replicated for any region by calibrating with region-specific data. For this research, we used data from 1990–2010 regarding three major crops of the Free State province: maize, wheat, and potatoes. The simulation was performed until 2035. We distinguished between food production in irrigated and rainfed areas, and quantified water and energy use of both types of farms. We further explored the systemic effects of increasing the role of In-site Rain Water Harvesting structures (IRWHs) to capture and use rainwater more efficiently on rainfed farms. We modelled the effects of IRWHs on food production, and the change in the proportion of rainfed areas with IRWHs, but did not incorporate any transition from irrigation to IRWHs. Data sources include various South African and African agricultural, government, and water-related statistics.

Results

The results from the simulated model include the forecast of water, land, and energy demand as well as monetary prices, and return on the water used for the selected crops. The forecasted results indicate that if agricultural production follows historical trends until 2035, demand for land would increase by around 12% compared to 2010, but for water and energy demand would rise almost six-fold, along with associated monetary expenses. The results also showed that the use of IRWHs meant that the green water saved allowed increased food production.

Conclusions

An operational generic systems dynamic model for the agriculture-energy nexus was constructed and calibrated for the Free State, South Africa. The main conclusions were increase in water and energy use in agriculture. However, with the inclusion of interventions like IRWH, the food production can be supported with increased use of rainwater and could lead to reduction in irrigation. It should be noted, however, that these regional forecasts assume continuation of historic population increases; no dietary changes; no influence of global commodity markets; availability of fertile land for crop expansion or intensification; and the appropriate availability of human and other resources for achieving potential yields. Depending on the policy question, the relatively simple systems dynamic model presented here may need to be further expanded. This highlights the complexity of social-ecological systems and challenges for modelling such highly interconnected networks.

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Last edited: 03 February 2016