IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v17y2020i5p1790-d330630.html
   My bibliography  Save this article

The Influence of Different Forest Characteristics on Non-point Source Pollution: A Case Study at Chaohu Basin, China

Author

Listed:
  • Hao Cheng

    (Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China
    Priority Academic Program Development of Jiangsu High Education Institutions (PAPD), Nanjing Forestry University, Nanjing 210037, China)

  • Chen Lin

    (Key Laboratory of Watershed Geographic Sciences, Institute of Geography and Limnology, Chinese Academy Sciences, Nanjing 210008, China)

  • Liangjie Wang

    (Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China
    Priority Academic Program Development of Jiangsu High Education Institutions (PAPD), Nanjing Forestry University, Nanjing 210037, China)

  • Junfeng Xiong

    (Key Laboratory of Watershed Geographic Sciences, Institute of Geography and Limnology, Chinese Academy Sciences, Nanjing 210008, China)

  • Lingyun Peng

    (Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China
    Priority Academic Program Development of Jiangsu High Education Institutions (PAPD), Nanjing Forestry University, Nanjing 210037, China)

  • Chenxi Zhu

    (Jiangsu Institute of Land Surveying and Planning, Nanjing 210017, China)

Abstract

Forestland is a key land use/land cover (LULC) type that affects nonpoint source (NPS) pollution, and has great impacts on the spatiotemporal features of watershed NPS pollution. In this study, the forestland characteristics of the Chaohu Basin, China, were quantitatively represented using forestland types (FLTs), watershed forest coverage (WFC) and forest distance from the river (DFR). To clarify the impact of forests on NPS pollution, the relationship between forestland characteristics and watershed nutrient outputs (TN and TP) was explored on a monthly scale using SWAT (Soil and Water Assessment Tool) and the period simulation was 2008–2016. The results showed that: (1) the TN and TP showed similar output characteristics and the rainy season was the peak period of nitrogen and phosphorus output. (2) Among the forestland characteristics of forestland types, watershed forest coverage and forest distance from the river, watershed forest coverage and forest distance from the river had greater effects than forestland types on the control of watershed nutrient outputs (TN and TP). (3) In different forestland types, the watershed nutrient outputs intensity remained at the lowest level when the FLTs was mixed forest, with a TN output of 1244.73kg/km 2 and TP output of 341.39 kg/km 2 . (4) The watershed nutrient outputs and watershed forest coverage were negatively correlated, with the highest watershed forest coverage (over 75%) reducing the TN outputs by 56.69% and the TP outputs by 53.46% compared to the lowest watershed forest coverage (below 25%), it showed that in areas with high forest land coverage, the non-point source pollution load in the watershed is smaller than in other areas. (5) forest distance from the river had an uncertain effect on the TN and TP output of the basin, the forestland itself is a source of pollution, but it also has the function of intercepting pollution movement; the forest distance from the river in the range of 500–1000 m had the lowest NPS pollution. Considering the different forest characteristics and topographical factors, an optimal allocation mode of differentiated forest land was proposed, these suggestions will provide a scheme for surface source pollution prevention and control in the basin. This research gap is the basis of real forestland optimization. We may optimize the forestland layout for NPS pollution prevention and control by clarifying the internal mechanism.

Suggested Citation

  • Hao Cheng & Chen Lin & Liangjie Wang & Junfeng Xiong & Lingyun Peng & Chenxi Zhu, 2020. "The Influence of Different Forest Characteristics on Non-point Source Pollution: A Case Study at Chaohu Basin, China," IJERPH, MDPI, vol. 17(5), pages 1-19, March.
  • Handle: RePEc:gam:jijerp:v:17:y:2020:i:5:p:1790-:d:330630
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/17/5/1790/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/17/5/1790/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Liu, Y. & Tao, Y. & Wan, K.Y. & Zhang, G.S. & Liu, D.B. & Xiong, G.Y. & Chen, F., 2012. "Runoff and nutrient losses in citrus orchards on sloping land subjected to different surface mulching practices in the Danjiangkou Reservoir area of China," Agricultural Water Management, Elsevier, vol. 110(C), pages 34-40.
    2. Liu, Ruimin & Zhang, Peipei & Wang, Xiujuan & Chen, Yaxin & Shen, Zhenyao, 2013. "Assessment of effects of best management practices on agricultural non-point source pollution in Xiangxi River watershed," Agricultural Water Management, Elsevier, vol. 117(C), pages 9-18.
    3. Zhang, H. & Huang, G.H., 2011. "Assessment of non-point source pollution using a spatial multicriteria analysis approach," Ecological Modelling, Elsevier, vol. 222(2), pages 313-321.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yi Wang & Xinliang Liu & Yantai Gan & Yong Li & Ying Zhao, 2023. "Conversion of Forest Hillslopes into Tea Fields Increases Soil Nutrient Losses through Surface Runoff," Land, MDPI, vol. 12(2), pages 1-14, February.
    2. Yang, Lin & Pang, Shujiang & Wang, Xiaoyan & Du, Yi & Huang, Jieyu & Melching, Charles S., 2021. "Optimal allocation of best management practices based on receiving water capacity constraints," Agricultural Water Management, Elsevier, vol. 258(C).
    3. Zhang, XiaoHong & Pan, HengYu & Cao, Jun & Li, JinRong, 2015. "Energy consumption of China’s crop production system and the related emissions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 43(C), pages 111-125.
    4. Li, Zhi-guo & Gu, Chi-ming & Zhang, Run-hua & Ibrahim, Mohamed & Zhang, Guo-shi & Wang, Li & Zhang, Run-qin & Chen, Fang & Liu, Yi, 2017. "The benefic effect induced by biochar on soil erosion and nutrient loss of slopping land under natural rainfall conditions in central China," Agricultural Water Management, Elsevier, vol. 185(C), pages 145-150.
    5. Sumaryanto & Sri Hery Susilowati & Fitri Nurfatriani & Herlina Tarigan & Erwidodo & Tahlim Sudaryanto & Henri Wira Perkasa, 2022. "Determinants of Farmers’ Behavior towards Land Conservation Practices in the Upper Citarum Watershed in West Java, Indonesia," Land, MDPI, vol. 11(10), pages 1-21, October.
    6. Shuo Lei & Lu Zhang & Chunfei Hou & Yongwei Han, 2023. "Internet Use, Subjective Well-Being, and Environmentally Friendly Practices in Rural China: An Empirical Analysis," Sustainability, MDPI, vol. 15(14), pages 1-13, July.
    7. Yingzhuang Guo & Xiaoyan Wang & Lili Zhou & Charles Melching & Zeqi Li, 2020. "Identification of Critical Source Areas of Nitrogen Load in the Miyun Reservoir Watershed under Different Hydrological Conditions," Sustainability, MDPI, vol. 12(3), pages 1-22, January.
    8. Qi Zhou & Yong Pang & Xue Wang & Xiao Wang & Yong Niu & Jianjian Wang, 2017. "Determination of Key Risk Supervision Areas around River-Type Water Sources Affected by Multiple Risk Sources: A Case Study of Water Sources along the Yangtze’s Nanjing Section," Sustainability, MDPI, vol. 9(2), pages 1-23, February.
    9. Ning Huang & Tao Lin & Junjie Guan & Guoqin Zhang & Xiaoying Qin & Jiangfu Liao & Qiming Liu & Yunfeng Huang, 2021. "Identification and Regulation of Critical Source Areas of Non-Point Source Pollution in Medium and Small Watersheds Based on Source-Sink Theory," Land, MDPI, vol. 10(7), pages 1-23, June.
    10. Cabrini, Silvina M. & Calcaterra, Carlos P., 2016. "Modeling economic-environmental decision making for agricultural land use in Argentinean Pampas," Agricultural Systems, Elsevier, vol. 143(C), pages 183-194.
    11. Dai, Cuiting & Liu, Yaojun & Wang, Tianwei & Li, Zhaoxia & Zhou, Yiwen, 2018. "Exploring optimal measures to reduce soil erosion and nutrient losses in southern China," Agricultural Water Management, Elsevier, vol. 210(C), pages 41-48.
    12. repec:zbw:inwedp:542013 is not listed on IDEAS
    13. Jiang, Fei & Drohan, Patrick J. & Cibin, Raj & Preisendanz, Heather E. & White, Charles M. & Veith, Tamie L., 2021. "Reallocating crop rotation patterns improves water quality and maintains crop yield," Agricultural Systems, Elsevier, vol. 187(C).
    14. Wei Yan & Xuejun Duan & Jiayu Kang & Zhiyuan Ma, 2023. "Assessing the Impact of Rural Multifunctionality on Non-Point Source Pollution: A Case Study of Typical Hilly Watershed, China," Land, MDPI, vol. 12(10), pages 1-17, October.
    15. Ricci, Giovanni Francesco & D’Ambrosio, Ersilia & De Girolamo, Anna Maria & Gentile, Francesco, 2022. "Efficiency and feasibility of Best Management Practices to reduce nutrient loads in an agricultural river basin," Agricultural Water Management, Elsevier, vol. 259(C).
    16. Puertes, Cristina & Bautista, Inmaculada & Lidón, Antonio & Francés, Félix, 2021. "Best management practices scenario analysis to reduce agricultural nitrogen loads and sediment yield to the semiarid Mar Menor coastal lagoon (Spain)," Agricultural Systems, Elsevier, vol. 188(C).
    17. H. Zhang & Q. Liu & X. Yu & L. Wang, 2014. "Influences of mulching durations on soil erosion and nutrient losses in a peanut (Arachis hypogaea)-cultivated land," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 72(2), pages 1175-1187, June.
    18. Dai, C. & Cai, Y.P. & Ren, W. & Xie, Y.F. & Guo, H.C., 2016. "Identification of optimal placements of best management practices through an interval-fuzzy possibilistic programming model," Agricultural Water Management, Elsevier, vol. 165(C), pages 108-121.
    19. Minghao Mo & Zhao Liu & Jie Yang & Yuejun Song & Anguo Tu & Kaitao Liao & Jie Zhang, 2019. "Water and sediment runoff and soil moisture response to grass cover in sloping citrus land, Southern China," Soil and Water Research, Czech Academy of Agricultural Sciences, vol. 14(1), pages 10-21.
    20. Yang, Shengtian & Dong, Guotao & Zheng, Donghai & Xiao, Honglin & Gao, Yunfei & Lang, Yang, 2011. "Coupling Xinanjiang model and SWAT to simulate agricultural non-point source pollution in Songtao watershed of Hainan, China," Ecological Modelling, Elsevier, vol. 222(20), pages 3701-3717.
    21. Ricci, G.F. & Jeong, J. & De Girolamo, A.M. & Gentile, F., 2020. "Effectiveness and feasibility of different management practices to reduce soil erosion in an agricultural watershed," Land Use Policy, Elsevier, vol. 90(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:17:y:2020:i:5:p:1790-:d:330630. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.