Assessing the effects of rural livelihood transition on non-point source pollution: a coupled ABM-IECM model

Authored by Chengcheng Yuan, Liming Liu, Xiaoxing Qi, Jinwei Ye, Guoping Ren, Dong Zhuo

Date Published: 2017

DOI: 10.1007/s11356-017-8812-0

Sponsors: Chinese National Natural Science Foundation

Platforms: No platforms listed

Model Documentation: Other Narrative Flow charts Mathematical description

Model Code URLs: Model code not found

Abstract

Water pollution caused by anthropogenic activities and driven by changes in rural livelihood strategies in an agricultural system has received increasing attention in recent decades. To simulate the effects of rural household livelihood transition on non-point source (NPS) pollution, a model combining an agent-based model (ABM) and an improved export coefficient model (IECM) was developed. The ABM was adopted to simulate the dynamic process of household livelihood transition, and the IECM was employed to estimate the effects of household livelihood transition on NPS pollution. The coupled model was tested in a small catchment in the Dongting Lake region, China. The simulated results reveal that the transition of household livelihood strategies occurred with the changes in the prices of rice, pig, and labor. Thus, the cropping system, land-use intensity, resident population, and number of pigs changed in the small catchment from 2000 to 2014. As a result of these changes, the total nitrogen load discharged into the river initially increased from 6841.0 kg in 2000 to 8446.3 kg in 2004 and then decreased to 6063.9 kg in 2014. Results also suggest that rural living, livestock, paddy field, and precipitation alternately became the main causes of NPS pollution in the small catchment, and the midstream region of the small catchment was the primary area for NPS pollution from 2000 to 2014. Despite some limitations, the coupled model provides an innovative way to simulate the effects of rural household livelihood transition on NPS pollution with the change of socioeconomic factors, and thereby identify the key factors influencing water pollution to provide valuable suggestions on how agricultural environmental risks can be reduced through the regulation of the behaviors of farming households in the future.

Tags

Land-use change ABM ECM Water-quality Cover change Multiagent systems Surface waters Yangtze-river Livelihood strategy Livelihood transition Non-point source pollution Export coefficient model Rice production Loess plateau Upper reaches