Assessing effects of “source-sink” landscape on non-point source pollution based on cell units of a small agricultural catchment

• Published in: Journal of mountain science Vol. 16; no. 9; pp. 2048 - 2062
• Main Authors: Wang, Jin-liang, Chen, Cheng-long, Ni, Jiu-pai, Xie, De-ti, Guo, Xi, Luo, Zhi-jun, Zhao, Yue
• Format: Journal Article
• Language: English
• Published: Beijing Science Press 01.09.2019; Springer Nature B.V
• Subjects: Agricultural pollution; Agricultural runoff; Agricultural watersheds; Canyons; Catchment area; Catchments; Computer simulation; Correlation analysis; Earth Sciences; Ecology; Environment; Exports; Factor analysis; Geography; Landscape; Mineral nutrients; Nonpoint source pollution; Nutrient loss; Nutrients; Phosphorus; Point source pollution; Pollutant load; Pollutants; Pollution; Pollution control; Pollution effects; Pollution load; Rain; Rainfall; Runoff; Spatial distribution; Trends; Water pollution; Nutrient load; Non-point source pollution; Landscape index; Small catchment; Source sink
• ISSN: 1672-6316; 1993-0321; 1008-2786
• DOI: 10.1007/s11629-018-5268-8

Ascertaining the relationship between “source-sink” landscape and non-point source (NPS) pollution is crucial for reducing NPS pollution, however, it is not easy to realize this target on cell unit scale. To reveal the relationships between “source-sink” landscape and NPS pollution based on cell units of a small catchment in the Three Gorges Reservoir Region (TGRR), the runoff and nutrient yields were simulated first by rainfall events on a cell unit scale based on the Annualized AGricultural Non-Point Source Pollution Model (AnnAGNPS). Landscape structure and pattern were quantified with “source-sink” landscape indicators based on cell units including landscape area indices and location-weighted landscape indices. The results showed that: the study case of small Wangjiagou catchment highlighted a good prediction capability of runoff and nutrient export by the AnnAGNPS model. Throughout the catchment, the spatial distribution trends of four location-weighted landscape indices were similar to the trends of simulated total nitrogen (TN) and total phosphorus (TP), which highlighted the importance of spatial arrangement of “source” and “sink” landscape types in a catchment when estimating pollutant loads. Results by Pearson correlation analysis indicated that the location-weighted landscape index provided a more comprehensive account of multiple factors, and can better reflect NPS-related nutrient loss than other landscape indices applied in single-factor analysis. This study provides new findings for applying the “source-sink” landscape indices based on cell units in small catchments to explain the effect of “source-sink” landscape on nutrient export based on cell unit, and helps improve the understanding of the correlation between “source-sink” landscape and NPS pollution.