13 November 2018

Making food and energy production in China compatible under limited water supply

Options Winter 2018/19: Researchers from IIASA and China collaborated on a study to find the most cost efficient way of producing enough food and energy while taking limitations on the availability of land and water into account.

 © Presse750 | Dreamstime

© Presse750 | Dreamstime

In northwest China the coal industry and agriculture are competing for limited land and water resources. The traditional approach to planning the development of each sector independently is failing, as solutions that optimize the outcome within individual sectors do not necessarily yield an optimal outcome for the overall economy.  

Researchers from IIASA and the China University of Mining and Technology have linked the agricultural and coal sectors in a new model to find the most cost efficient way of producing enough food and energy while taking constraints on the availability of land and water into account. 

By capturing the spatial characteristics of sub-regions, the researchers determined how the production sites of coal and various crops could be reallocated to take advantage of different climates and geographies. They also found that implementing water saving technologies makes it feasible to enhance production without increasing water demand. 

The model was applied to derive the optimal allocation of coal production and agriculture across the Shanxi province in China. The results show that the overall amount of crops and coal that can be produced depends critically on the availability of water. This demonstrates the need to take the variability of water supply into account to find solutions that work reasonably well under all availability scenarios.

Text by Melina Filzinger

Further information

Gao J, Xu X, Cao G-Y, Ermoliev Y, Ermolieva T, & Rovenskaya E (2018). Optimizing Regional Food and Energy Production under Limited Water Availability through Integrated Modeling. Sustainability 10 (6): e1689


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Last edited: 09 January 2019

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Elena Rovenskaya

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Advanced Systems Analysis

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Evolution and Ecology

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