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This study primarily examined the assessment of environmental risk in high intensity agricultural areas. Dongting Lake basin was taken as a case study, which is one of the major grain producing areas in China. Using data obtained from 1989 to 2012, we applied Material Flow Analysis (MFA) to show the material consumption, pollutant output and production storage in the agricultural-environmental system and assessed the environmental risk index on the basis of the MFA results. The results predicted that the status of the environmental quality of the Dongting Lake area is unsatisfactory for the foreseeable future. The direct material input (DMI) declined by 13.9%, the domestic processed output (DPO) increased by 28.21%, the intensity of material consumption (IMC) decreased by 36.7%, the intensity of material discharge (IMD) increased by 10%, the material productivity (MP) increased by 27 times, the environmental efficiency (EE) increased by 15.31 times, and the material storage (PAS) increased by 0.23%. The DMI and DPO was higher at rural places on the edge of cities, whereas the risk of urban agriculture has arisen due to the higher increasing rate of DMI and DPO in cities compared with the counties. The composite environmental risk index increased from 0.33 to 0.96, indicating that the total environmental risk changed gradually but seriously during the 24 years assessed. The driving factors that affect environmental risk in high intensity agriculture can be divided into five classes: social, economic, human, natural and disruptive incidents. This study discussed a number of effective measures for protecting the environment while ensuring food production yields. Additional research in other areas and certain improvements of this method in future studies may be necessary to develop a more effective method of managing and controlling agricultural-environmental interactions.

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Since China has undergone a series of economic reforms and implemented opening up policies, its farming systems have significantly changed and have dramatically influenced the society, economy, and environment of China. To assess the comprehensive impacts of these changes on food security and environmental sustainability, and establish effective and environment-friendly subsidy policies, this research constructed an agent-based model (ABM). Daligang Town, which is located in the two-season rice region of Southern China, was selected as the case study site. Four different policy scenarios, i.e., "sharply increasing" (SI), "no-increase" (NI), "adjusted-method" (AM), and "trend" (TD) scenarios were investigated from 2015 to 2029. The validation result shows that the relative prediction errors between the simulated and actual values annually ranged from -20 to 20%, indicating the reliability of the proposed model. The scenario analysis revealed that the four scenarios generated different variations in cropping systems, rice yield, and fertilizer and pesticide inputs when the purchase price of rice and the non-agricultural income were assumed to increase annually by 0.1 RMB per kg and 10% per person, respectively. Among the four different policy scenarios in Daligang, the TD scenario was considered the best, because it had a relatively high rice yield, fairly minimal use of fertilizers and pesticides, and a lower level of subsidy. Despite its limitations, ABM could be considered a useful tool in analyzing, exploring, and discussing the comprehensive effects of the changes in farming system on food security and environmental sustainability.