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Journal of Integrative Agriculture  2016, Vol. 15 Issue (10): 2417-2425    DOI: 10.1016/S2095-3119(15)61247-3
Soil & Fertilization﹒Irrigation﹒Plant Nutrition﹒ Agro-Ecology & Environment Advanced Online Publication | Current Issue | Archive | Adv Search |
Linking a farmer crop selection model (FCS) with an agronomic model (EPIC) to simulate cropping pattern in Northeast China
HE Ying-bin1, 2, CAI Wei-min2
1 Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, P.R.China
2 Management School, Tianjin Polytechnic University, Tianjin 300387, P.R.China
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Abstract    In this paper, authors established a farmer crop selection model (FCS) for the three provinces of Liaoning, Jilin and Heilongjiang of the Northeast China. With linking to the environmental policy integrated climate model (EPIC), the simulated results of FCS model for maize, rice and soybean were spatialized with 1 km×1 km grids to obtain cropping pattern. The reference map of spatial distribution for the three staple crops acquired by remote sensing imageries was applied to validate the simulated cropping pattern. The results showed that (1) the total simulation accuracy for the study area was 78.62%, which proved simulation method was applicable and feasible; (2) simulation accuracy for Jilin Province was the highest among the three provinces with a rate of 82.45% since its simple cropping system and not complex topography; (3) simulation accuracy for maize was the best among the three staple crops with a ratio of 81.14% because the study area is very suitable for maize growth. We hope this study could provide the reference for cropping pattern forecasting and decision-making.
Keywords:  cropping pattern        staple crops        EPIC model        FCS model        simulation  
Received: 26 October 2015   Accepted: 01 October 2016

This research was funded by the National Natural Science Foundation of China (41001049, 2011–2013) and the China Regional Arable Land Resources Changes and its Warning - A Case Study in Northeast China, Ministry of Science and Technology of China (2004DIB3J092, 2003–2008).

Corresponding Authors:  CAI Wei-min, Tel/Fax: +86-22-83956271, E-mail:   
About author:  HE Ying-bin, Tel: +86-10-82106225, E-mail:

Cite this article: 

HE Ying-bin, CAI Wei-min. 2016. Linking a farmer crop selection model (FCS) with an agronomic model (EPIC) to simulate cropping pattern in Northeast China. Journal of Integrative Agriculture, 15(10): 2417-2425.

Barnaud C, Bousquet F, Trebuil G. 2008. Multi-agent simulations to explore rules for rural credit in a highland farming community of Northern Thailand. Ecological Economics, 66, 615–627.

Batty M. 2005. Cities and Complexity: Understanding Cities with Cellular Automata, Agent-Based Models, and Fractals. MIT Press, Cambridge, MA.

Berger T. 2001. Agent-based spatial models applied to agriculture: a simulation tool for technology diffusion, resource use changes and policy analysis. Agricultural Economics, 25, 245–260.

Berry B J L, Kiel L D, Elliott E. 2002. Adaptive agents, intelligence, and emergent human organization: capturing complexity through agent-based modeling. Proceeding of the National Academy of Sciences of the United States of America, 99, 7187–7188.

Bryant K J, Benson V W, Kiniry J R, Williams J R, Lacewell R D. 1992. Simulating maize yield response to irrigation timings - Validation of the EPIC model. Journal of Production Agriculture, 5, 237–242.

Cabelguenne M P, Debaeke A, Bouniols. 1999. EPIC phase, a version of the EPIC model simulating the effects of water and nitrogen stress on biomass and yield, taking account of developmental stages: Validation on maize, sunflower, sorghum, soybean, and winter wheat. Agricultural Systems, 60, 175–196.

Chavas D R, Izaurralde R C, Thomson A M, Gao X J, 2009. Long-term climate change impacts on agricultural productivity in eastern China. Agricultural and Forest Meteorology, 95, 203–215.

Chen H, Yang W G, Liang X Y, Wang T. 2010. Multi-scale modeling of land use based on the MAS from field to village: A case study for Mengcha Village of Mizhi County of Shaanxi Province. Geographical Research, 29, 1519–1527. (in Chinese)

Chen Y Q, Yao Y M, He Y B, Shi S Q, Li Z B. 2010. Assessment on Effects of Regional Arable Land Resources Changes and Food Security Early Warning. China Agricultural Science and Technology Press, Beijing. (in Chinese)

Fischer G, Sun L. 2001. Model based analysis of future land-use development in China. Agriculture, Ecosystem & Environment, 85, 163–176.

Frondoni R, Mollo B, Capotorti G. 2011. A landscape analysis of land cover change in the municipality of Rome (Italy): Spatio-temporal characteristics and ecological implications of land cover transitions from 1954 to 2001. Landscape and Urban Plan, 100, 117–128.

Grimm V, Revilla E, Berger U. 2005. Pattern-oriented modeling of agent-based complex systems: Lessons from ecology. Science, 310, 987–991.

Huang H Q, Pan L H, Wang Q, Zhen L. 2010. An artificial society model of land use change in terms of households’ behaviors: Model development and applications. Journal of Natural Resources, 25, 353–367. (in Chinese)

Huang H Q, Tang H J, Wu W B, Li D D, Liu J. 2013. Remote sensing based dynamic changes analysis of crop distribution pattern - taking northeast China as an example. Scientia Agricultura Sinica, 46, 2668–2676. (in Chinese)

IGBP (International Geosphere-Biosphere Program). 2001. Global Change and the Earth System: A Planet under Pressure (IGBP Science 4). IGBP, Stochholm.

Lambin E F, X Baulies N, Bockstael G, Fischer T, Krug R, Leemans E F, Moran R R, Rindfuss Y, Sato D, Skole B L, Turner II, Vogel C. 1999. Land Use and Land Cover Change (LUCC) Implementation Strategy, IGBP Report 48 & IHDP Report10. IGBP, Stockholm.

Li N, Gao M, Fu Y H, Ma G Q. 1994. Analysis on the characteristics of spring soybean in northeast China. Journal of Jilin Agricultural University, 16, 86–88. (in Chinese)

Liu J. 2009. A GIS-based tool for modelling large-scale crop-water relations. Environmental Modelling Software, 69, 115–133.

Liu J Y, Deng X Z. 2010. Progress of the research methodologies on the temporal and spatial process of LUCC. Chinese Science Bulletin, 55, 1–9.

Liu J Y, Zhang Z X, Xu X L, Kuang W H, Zhou W C, Zhang S W, Li R D, Yan C Z, Yu D S, Wu S X, Nan J. 2010. Spatial patterns and driving forces of land use change in China during the early 21st century. Journal of Geographical Science, 20, 483–494.

Liu Y L, Chen Z L, Wang J, Ye M W, Xu S Y. 2011. Multi-scale coupling and application of natural disaster risk analysis. In: The 19th International Conference on Geoinformatics.IEEE, Shanghai, China. pp. 1–5.

Manson S M. 2005. Agent-based modeling and genetic programming for modeling land change in the southern Yucatan Peninsula Region of Mexico. Agricultural Ecosystem & Environment, 111, 47–62.

Matthews R. 2006. The People and Landscape Model (PALM): Towards full integration of human decision-making and biophysical simulation models. Ecological Modelling, 194, 329–343.

National Bureau of Statistics of the People’s Republic of China. 1991–2010. China Statistical Yearbooks. China Statistics Press, Beijing. (in Chinese)

Niu X Z, William E, Cynthia J H, Allyson J, Linda M. 2009. Reliability and input-data induced uncertainty of the EPIC model to estimate climate change impact on sorghum yields in the U.S. Great Plains. Agriculture, Ecosystem & Environment, 129, 268–276.

Overmars K P, Verburg P H, Veldkamp T A. 2007. Comparison of a deductive and an inductive approach to specify land suitability in a spatially explicit land use model. Land Use Policy, 24, 584–599.

Parker D C, Manson S M, Janssen M A, Hoffmann M J, Deadman P. 2003. Multi-agent systems for the simulation of land-use and land-cover change: A review. Annual Association of American Geography, 93, 314–337.

Priya S, Shibasaki R. 2001. National spatial crop yield simulation using GIS-based crop production model. Ecological Modelling, 136, 113–129.

Ran Y H, Li X, Lu L. 2009. China land cover classification at 1 km spatial resolution based on a multi-source data fusion approach. Advances in Earth Science, 24, 192–203. (in Chinese)

Saeed A K, Barlas Y, Yemgun O. 2002. Long term sustainability in an agriculture development project: A system dynamics approach. Journal of Environmental Management, 64, 247–260.

Schreinemachers P, Berger T. 2011. An agent-based simulation model of human-environment interactions in agricultural systems. Environmental Modelling and Software, 26, 845–859.

Tang H J, Chen Y Q, Qiu J J, Chen Z X. 2004. Land Use and Land Cover in China. China Agriculture Science and Technology Press, Beijing. (in Chinese)

Tang H J, Wu W B, Yang P, Chen Y Q, Verburg P H. 2009. Recent progresses of land use and land cover change (LUCC) models. Acta Geographica Sinica, 64, 456–468. (in Chinese)

Turner II B L, Skole D, Sanderson S, Fischer G, Fresco L O, Leemans R. 1995. Land Use and Land Cover Change Science/Research Plan, IGBP Report 35& IHDP Report 7. IGBP, Stockholm.

Van Der Velde M, Wriedt G, Bouraoui F. 2010. Estimating irrigation use and effects on maize yield during the 2003 heatwave in France. Agriculture, Ecosystem & Environment, 1, 141–147.

 Verburg P H. 2006. Simulating feedback in land use and land cover change models. Landscape Ecology, 21, 1171–1183.

Verburg P H, Overmars K P. 2009. Combining top-down and bottom-up dynamics in land use modeling: Exploring the future of abandoned farmlands in Europe with the Dyna-CLUE model. Landscape Ecology, 24, 1167–1181.

Verburg P H, Schot P P, Dijst M J, Veldkamp A. 2004. Land use change modeling: Current practice and research priorities. GeoJournal, 61, 309–324.

Wang Z Q, Fang W H, He F, Xu H. 2008. Effect of climate change on wheat yield in northern China: A research based on EPIC model. Journal of Natural Disaster, 17, 109–114. (in Chinese)

Williams J R. Arnold J G. 2006. History of Model Development at Temple. Texas A&M University Press, College Station City, USA.

Williams J R, Jones C A, Dyke P T. 1984. A modeling approach to determining the relationship between erosion and soil productivity. Transactions of the Asea, 27, 129–144.

Wu J S, Feng Z, Gao Y, Huang X L, Liu H M, Huang L. 2012. Recent progress on the application and improvement of the CLUE-S Model. Progress of  Geography, 31, 3–10. (in Chinese)

Wu W B, Shibasaki R, Yang P, Tan G X, Matsumura K, Sugimoto K. 2007. Global-scale modelling of future changes in sown areas of major crops. Ecological Modelling, 27, 2137–2154.

Xie Y C, Yu M, Tian G J. 2005. Socio-economic driving forces of arable land conversion: A case study of Wuxian City, China. Global Environmental Change, 15, 238–252.

Yin P H, Fang X Q, Tian Q. 2006. Distribution and regional differences of the main output regions in grain production in China in the early 21st century. Acta Geographica Sinica, 61, 190–198.

Yu Q Y, Wu W B, Tang H J, Yang P, Li Z G, Xia T, Liu Z H, Zhou Q B. 2013. An agent-based model for simulating crop pattern dynamics at a regional scale: Model framework. Scientia Agricultura Sinica, 46, 3266–3276. (in Chinese)
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