Regression equations for NPS pollutants.

<div><p>Agricultural non-point source (NPS) pollution directly affects the quality of soil and water, ecological balance and human health, and is a key challenge to achieve sustainable environmental development and efficient resource management. Taking the Nansi Lake Basin (NLB) as the s...

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Bibliographic Details
Main Author:	Jiachen Liu (4639738) (author)
Other Authors:	Yuan Tian (225002) (author), Rongqiang Ma (13192189) (author), Wenhui Xie (495309) (author), Dongchao Wang (7313549) (author), Luoan Yang (20783718) (author), Xinyu Wang (341591) (author), Le Yin (5122007) (author), Baolei Zhang (3965114) (author)
Published:	2025
Subjects:	Biotechnology Ecology Science Policy Space Science Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Chemical Sciences not elsewhere classified provide scientific basis pollution directly affects chemical oxygen demand temporal distribution data multiple regression analysis complete runoff records study raise awareness soil organic matter point source pollution nansi lake basin efficient resource management div >< p agricultural nps pollution river runoff based point source distribution characteristics regression model watershed area total population topographic index study simulated study provides study period study explores study area significantly correlated rural employment quantitatively assessed quantitative calculation quantifying variation positively correlated pesticide use negatively correlated main sources key challenge influencing factors increasing trend important reference impact factors human health gully density fertilizer application economic factors ecological balance ammonia nitrogen allow researchers agricultural non
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Regression equations for NPS pollutants.

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