Evaluating the bioenergy potential of cassava on marginal land using a biogeochemical process model in GuangXi, China

Dong Jiang; Mengmeng Hao; Jingying Fu; Yaohuan Huang; Kun Liu

doi:10.1117/1.JRS.9.097699

20 May 2015 Evaluating the bioenergy potential of cassava on marginal land using a biogeochemical process model in GuangXi, China

Dong Jiang, Mengmeng Hao, Jingying Fu, Yaohuan Huang, Kun Liu

Author Affiliations +

Journal of Applied Remote Sensing, Vol. 9, Issue 1, 097699 (May 2015). https://doi.org/10.1117/1.JRS.9.097699

Abstract

Bioenergy is expected to play an important role in future energy systems. Cassava is believed to be one of the most promising energy plants for fuel ethanol production in the tropics and subtropics. In China, plant-based bioenergy has to be developed on marginal land to avoid impacting food security. Cassava yield varies dramatically under different environmental conditions. Therefore, an efficient approach is needed to estimate cassava yield on marginal land. This paper presents a method for assessing the energy potential of cassava using a biogeochemical process model. First, the spatial distribution of marginal land was identified. A geographic information system-based biogeochemical process model, the GIS-based environmental policy integrated climate model, was used to simulate the spatial and temporal dynamics of the major processes of the soil-cassava-atmosphere management system. The model was calibrated and successfully applied to data from GuangXi province, Southwest China. The results indicated that the potential bioenergy of cassava on marginal land under rain-fed conditions in GuangXi province is 1,909,593.96 million MJ, which is equivalent to the energy of 17.0844 million tons of standard coal; the potential energy of irrigated cassava is 2,054,017.73 million MJ, which is equivalent to the energy of 18.3765 million tons of standard coal.

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Dong Jiang, Mengmeng Hao, Jingying Fu, Yaohuan Huang, and Kun Liu "Evaluating the bioenergy potential of cassava on marginal land using a biogeochemical process model in GuangXi, China," Journal of Applied Remote Sensing 9(1), 097699 (20 May 2015). https://doi.org/10.1117/1.JRS.9.097699

Published: 20 May 2015

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