ORIGINAL RESEARCH
Quantifying the Relationships of Impact Factors
on Non-Point Source Pollution Using the Boosted
Regression Tree Algorithm
Wei Zhang1, Feng-Yun Sun2, Miao Liu3, Chun-Lin Li3
1College of Land and Environment, Shenyang Agricultural University, Shenyang 110866, China
2School of Geographic Sciences, East China Normal University, Shanghai 200241, China
3Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110164, China
2School of Geographic Sciences, East China Normal University, Shanghai 200241, China
3Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110164, China
Submission date: 2016-05-09
Final revision date: 2016-07-22
Acceptance date: 2016-07-26
Online publication date: 2017-01-31
Publication date: 2017-01-31
Pol. J. Environ. Stud. 2017;26(1):403–411
KEYWORDS
TOPICS
ABSTRACT
Non-point source (NPS) pollution contributes greatly to the contamination of surface water quality
and has aroused widespread concerns. NPS pollution is influenced by a multitude of site-related factors
whose effects are complicated. We estimated NPS pollution with a soil and water assessment tool (SWAT)
model in China’s Fan River watershed. A new method, boosted regression tree (BRT), was proposed to
study the relationship of impact factors on NPS pollution. We analyzed the effects of elevation, land use,
soil, and slope on the patterns of sediment transport, total nitrogen (TN), and total phosphorus (TP). The
results showed that R2 values were higher than 0.76, and NSE was higher than 0.67. The SWAT model can
estimate NPS pollution effectively in a study area. Although the spatial pattern of sediment and TP was
quite consistent, the relationship between sediment and TN was weak. The contribution of impact factors
for sediment TN and TP were different. Slope is the most important impact factor for sediment and TP load.
Land use is the most important impact factor for TN load. The BRT model can reduce barriers to factor
complexity and promote understanding of the NPS pollution formation mechanism. We proposed control
strategies of pollution sources, and our research has proven to be useful for the explanation of impact factors
in NPS pollution study, which is meaningful for NPS pollution control.
RELATED ARTICLE
We process personal data collected when visiting the website. The function of obtaining information about users and their behavior is carried out by voluntarily entered information in forms and saving cookies in end devices. Data, including cookies, are used to provide services, improve the user experience and to analyze the traffic in accordance with the Privacy policy. Data are also collected and processed by Google Analytics tool (more).
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.