scholarly journals Improving the identification of hydrologically sensitive areas using LiDAR DEMs for the delineation and mitigation of critical source areas of diffuse pollution

2016 ◽  
Vol 556 ◽  
pp. 276-290 ◽  
Author(s):  
I.A. Thomas ◽  
P. Jordan ◽  
P.-E. Mellander ◽  
O. Fenton ◽  
O. Shine ◽  
...  
2019 ◽  
Vol 250 ◽  
pp. 109366 ◽  
Author(s):  
S.M. Reaney ◽  
E.B. Mackay ◽  
P.M. Haygarth ◽  
M. Fisher ◽  
A. Molineux ◽  
...  

2013 ◽  
Vol 179 ◽  
pp. 41-52 ◽  
Author(s):  
Joshua Thompson ◽  
Rachel Cassidy ◽  
Donnacha G. Doody ◽  
Ray Flynn

2018 ◽  
Vol 17 (2) ◽  
pp. 171-184 ◽  
Author(s):  
Al-amin Danladi Bello ◽  
Mohd Ridza Mohd Haniffah ◽  
Muhammad Nassir Hanapi ◽  
Aliyu Bamaiyi Usman

2013 ◽  
Vol 268 ◽  
pp. 123-133 ◽  
Author(s):  
Rewati Niraula ◽  
Latif Kalin ◽  
Puneet Srivastava ◽  
Christopher J. Anderson

2020 ◽  
Vol 12 (3) ◽  
pp. 964 ◽  
Author(s):  
Yingzhuang Guo ◽  
Xiaoyan Wang ◽  
Lili Zhou ◽  
Charles Melching ◽  
Zeqi Li

The spatiotemporal distribution of critical source areas (CSAs) will change with hydrological conditions. In this study, the CSAs of nitrogen load under different hydrological conditions in the Chaohe River watershed were identified using the cumulative pollution load curve method determined from the nitrogen pollution simulated using the Soil and Water Assessment Tool (SWAT) model. The results showed that: (1) The order of factors impacting nitrogen load intensity is as follows: fertilization intensity, rainfall, runoff, land use type, slope type, and soil type. (2) The primary and secondary CSAs are concentrated in the upper and lower areas of the watershed, where cultivated land (8.36%) and grassland (52.55%) are more abundant. The potential pollution source areas are concentrated in the upper and middle areas of the watershed, where cultivated land (6.99%), grassland (42.37%), and forest land (48.18%) are evenly distributed. The low-risk source areas are concentrated in the middle and left bank of the watershed, where forest land (67.65%) is dominant and the vegetation coverage is highest. The research results have significance for improving the accuracy of the implementation of best management practices, and can provide a reference for the formulation of drinking water protection policies for Beijing.


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