Spatiotemporal patterns of non-point source nitrogen loss in an agricultural catchment
Non-point source nitrogen loss poses a risk to sustainable aquatic ecosystems. However, non-point sources, as well as impaired river segments with high nitrogen concentrations, are difficult to monitor and regulate because of their diffusive nature, budget constraints, and resource deficiencies. For...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2016-04-01
|
| Series: | Water Science and Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1674237016300217 |
| _version_ | 1818253985262338048 |
|---|---|
| author | Jian-feng Xu Wei Yin Lei Ai Xiao-kang Xin Zhi-hua Shi |
| author_facet | Jian-feng Xu Wei Yin Lei Ai Xiao-kang Xin Zhi-hua Shi |
| author_sort | Jian-feng Xu |
| collection | DOAJ |
| description | Non-point source nitrogen loss poses a risk to sustainable aquatic ecosystems. However, non-point sources, as well as impaired river segments with high nitrogen concentrations, are difficult to monitor and regulate because of their diffusive nature, budget constraints, and resource deficiencies. For the purpose of catchment management, the Bayesian maximum entropy approach and spatial regression models have been used to explore the spatiotemporal patterns of non-point source nitrogen loss. In this study, a total of 18 sampling sites were selected along the river network in the Hujiashan Catchment. Over the time period of 2008–2012, water samples were collected 116 times at each site and analyzed for non-point source nitrogen loss. The morphometric variables and soil drainage of different land cover types were studied and considered potential factors affecting nitrogen loss. The results revealed that, compared with the approach using the Euclidean distance, the Bayesian maximum entropy approach using the river distance led to an appreciable 10.1% reduction in the estimation error, and more than 53.3% and 44.7% of the river network in the dry and wet seasons, respectively, had a probability of non-point source nitrogen impairment. The proportion of the impaired river segments exhibited an overall decreasing trend in the study catchment from 2008 to 2012, and the reduction in the wet seasons was greater than that in the dry seasons. High nitrogen concentrations were primarily found in the downstream reaches and river segments close to the residential lands. Croplands and residential lands were the dominant factors affecting non-point source nitrogen loss, and explained up to 70.7% of total nitrogen in the dry seasons and 54.7% in the wet seasons. A thorough understanding of the location of impaired river segments and the dominant factors affecting total nitrogen concentration would have considerable importance for catchment management. |
| first_indexed | 2024-12-12T16:48:46Z |
| format | Article |
| id | doaj.art-3cad9ab5093946e3947a80ca38cde8da |
| institution | Directory Open Access Journal |
| issn | 1674-2370 |
| language | English |
| last_indexed | 2024-12-12T16:48:46Z |
| publishDate | 2016-04-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Water Science and Engineering |
| spelling | doaj.art-3cad9ab5093946e3947a80ca38cde8da2022-12-22T00:18:25ZengElsevierWater Science and Engineering1674-23702016-04-019212513310.1016/j.wse.2016.03.003Spatiotemporal patterns of non-point source nitrogen loss in an agricultural catchmentJian-feng Xu0Wei Yin1Lei Ai2Xiao-kang Xin3Zhi-hua Shi4College of Resources and Environment, Huazhong Agricultural University, Wuhan 430070, ChinaChangjiang Water Resources Protection Institute, Wuhan 430051, ChinaCollege of Resources and Environment, Huazhong Agricultural University, Wuhan 430070, ChinaChangjiang Water Resources Protection Institute, Wuhan 430051, ChinaCollege of Resources and Environment, Huazhong Agricultural University, Wuhan 430070, ChinaNon-point source nitrogen loss poses a risk to sustainable aquatic ecosystems. However, non-point sources, as well as impaired river segments with high nitrogen concentrations, are difficult to monitor and regulate because of their diffusive nature, budget constraints, and resource deficiencies. For the purpose of catchment management, the Bayesian maximum entropy approach and spatial regression models have been used to explore the spatiotemporal patterns of non-point source nitrogen loss. In this study, a total of 18 sampling sites were selected along the river network in the Hujiashan Catchment. Over the time period of 2008–2012, water samples were collected 116 times at each site and analyzed for non-point source nitrogen loss. The morphometric variables and soil drainage of different land cover types were studied and considered potential factors affecting nitrogen loss. The results revealed that, compared with the approach using the Euclidean distance, the Bayesian maximum entropy approach using the river distance led to an appreciable 10.1% reduction in the estimation error, and more than 53.3% and 44.7% of the river network in the dry and wet seasons, respectively, had a probability of non-point source nitrogen impairment. The proportion of the impaired river segments exhibited an overall decreasing trend in the study catchment from 2008 to 2012, and the reduction in the wet seasons was greater than that in the dry seasons. High nitrogen concentrations were primarily found in the downstream reaches and river segments close to the residential lands. Croplands and residential lands were the dominant factors affecting non-point source nitrogen loss, and explained up to 70.7% of total nitrogen in the dry seasons and 54.7% in the wet seasons. A thorough understanding of the location of impaired river segments and the dominant factors affecting total nitrogen concentration would have considerable importance for catchment management.http://www.sciencedirect.com/science/article/pii/S1674237016300217Non-point source nitrogenBayesian maximum entropyRiver distanceSpatial regressionSpatiotemporal pattern |
| spellingShingle | Jian-feng Xu Wei Yin Lei Ai Xiao-kang Xin Zhi-hua Shi Spatiotemporal patterns of non-point source nitrogen loss in an agricultural catchment Water Science and Engineering Non-point source nitrogen Bayesian maximum entropy River distance Spatial regression Spatiotemporal pattern |
| title | Spatiotemporal patterns of non-point source nitrogen loss in an agricultural catchment |
| title_full | Spatiotemporal patterns of non-point source nitrogen loss in an agricultural catchment |
| title_fullStr | Spatiotemporal patterns of non-point source nitrogen loss in an agricultural catchment |
| title_full_unstemmed | Spatiotemporal patterns of non-point source nitrogen loss in an agricultural catchment |
| title_short | Spatiotemporal patterns of non-point source nitrogen loss in an agricultural catchment |
| title_sort | spatiotemporal patterns of non point source nitrogen loss in an agricultural catchment |
| topic | Non-point source nitrogen Bayesian maximum entropy River distance Spatial regression Spatiotemporal pattern |
| url | http://www.sciencedirect.com/science/article/pii/S1674237016300217 |
| work_keys_str_mv | AT jianfengxu spatiotemporalpatternsofnonpointsourcenitrogenlossinanagriculturalcatchment AT weiyin spatiotemporalpatternsofnonpointsourcenitrogenlossinanagriculturalcatchment AT leiai spatiotemporalpatternsofnonpointsourcenitrogenlossinanagriculturalcatchment AT xiaokangxin spatiotemporalpatternsofnonpointsourcenitrogenlossinanagriculturalcatchment AT zhihuashi spatiotemporalpatternsofnonpointsourcenitrogenlossinanagriculturalcatchment |