Resources Science ›› 2018, Vol. 40 ›› Issue (1): 44-52.doi: 10.18402/resci.2018.01.05

• Orginal Article • Previous Articles     Next Articles

Agricultural landscape pattern optimization of high intensive agricultural areas based on water quality control

Hongqing LI1(), Liming LIU2(), Fei ZHENG1, Yaoyang ZHAO1   

  1. 1. College of public administration, Hohai university, Nanjing 210098, China
    2. College of Resources and Environmental Sciences, China Agricultural University, Beijing 100193, China
  • Received:2017-05-26 Revised:2017-10-09 Online:2018-01-20 Published:2018-01-20


Agricultural non-point source pollution control has become a bottleneck for sustainable development especially in high intensive agricultural areas in China. Therefore, maintaining economic growth along with water quality improvements is a great challenge for policymakers. Taking Jinjing Town as a case study, we first analyzed water quality dynamics at spatial and temporal scales based on pollution monitoring data. Then, three different width buffer areas along the river were drawn to analyze the correlation between landscape pattern and water quality pollutions according to Pearson's correlation coefficient analysis; catchment was chosen as the suitable scale, and four landscape types forest, tea garden, paddy land and residential were chosen as major landscape parameters. A multiple regression analysis model was adopted to build the relationship between landscape pattern characteristics and water quality pollution for NO3--N, NH4+-N and TN for each season. According to the results, we designed agricultural landscape pattern modes from three aspects, one is landscape pattern optimization by changing land use types, shape and area; another is raising sanitary wastewater and solid waste treatment rate; and the third is livestock industry adjustment by livestock amount control. The assessment results show that water quality improves effectively and nitrogen pollutant concentration meets level V of environmental quality standards for surface water in the new landscape scenario. Biodiversity benefits, agricultural economic value, ecosystem service value and household net agricultural income are higher than in 2010. The relationship model method proposed here not only verifies the relationship between landscape pattern and water quality, but supports landscape pattern design. These landscape pattern optimization results will assist agricultural sustainable development and environmental protection planning for decision-makers.

Key words: landscape pattern, water quality, Regression Model, integrated assessment