IDEAS home Printed from https://ideas.repec.org/a/spr/waterr/v36y2022i4d10.1007_s11269-022-03082-8.html
   My bibliography  Save this article

Uncertainty Evaluation of Best Management Practice Effectiveness Based on the AnnAGNPS Model

Author

Listed:
  • Ying Chen

    (Fujian Normal University
    Fujian Normal University)

  • Binbin Lu

    (Fujian Normal University
    Fujian Normal University)

  • Chongyu Xu

    (University of Oslo)

  • Xingwei Chen

    (Fujian Normal University
    Fujian Normal University)

  • Meibing Liu

    (Fujian Normal University
    Fujian Normal University)

  • Lu Gao

    (Fujian Normal University
    Fujian Normal University)

  • Haijun Deng

    (Fujian Normal University
    Fujian Normal University)

Abstract

Uncertainty of best management practice (BMP) effectiveness is an important factor in the development of watershed management plans. This study explored the uncertainty of BMP effectiveness in reducing total nitrogen (TN) load owing to the uncertainty in hydrological parameters, thereby improving their reliability. A watershed model, annualized agricultural non-point source pollution (AnnAGNPS), was employed to evaluate the effectiveness of the four potentially feasible BMPs (i.e., riparian buffer, fertilization reduction, no-tillage, and parallel terraces) in the Shanmei Reservoir watershed, located in the southeastern coastal region of China. Annual and seasonal uncertainty variations in BMP effectiveness were evaluated based on ten parameter sets selected from 1000 parameter groups using Latin hypercube sampling. The results showed that the uncertainty of BMP effectiveness in reducing the TN load was larger than the uncertainty of TN load simulation at annual and seasonal time scales. The BMP effectiveness tended to be higher in summer than in the other seasons. The uncertainty of BMP effectiveness varied seasonally, and it was always lower in summer for most BMPs. This indicated that the impact of BMPs on reducing TN load was more effective, with a higher reduction rate and lower uncertainty in summer. Among the BMPs, the parallel terrace was the most effective measure for reducing TN load since it had the highest reduction rate and relatively low uncertainty. Although this study is a case study, it can provide a scientific reference for decision-making in uncertain situations when AnnAGNPS is applied for water quality simulations.

Suggested Citation

  • Ying Chen & Binbin Lu & Chongyu Xu & Xingwei Chen & Meibing Liu & Lu Gao & Haijun Deng, 2022. "Uncertainty Evaluation of Best Management Practice Effectiveness Based on the AnnAGNPS Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(4), pages 1307-1321, March.
    • Handle: RePEc:spr:waterr:v:36:y:2022:i:4:d:10.1007_s11269-022-03082-8
    DOI: 10.1007/s11269-022-03082-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11269-022-03082-8
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11269-022-03082-8?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Honghai Qi & Mustafa Altinakar, 2011. "Vegetation Buffer Strips Design Using an Optimization Approach for Non-Point Source Pollutant Control of an Agricultural Watershed," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(2), pages 565-578, January.
    2. Chahor, Y. & Casalí, J. & Giménez, R. & Bingner, R.L. & Campo, M.A. & Goñi, M., 2014. "Evaluation of the AnnAGNPS model for predicting runoff and sediment yield in a small Mediterranean agricultural watershed in Navarre (Spain)," Agricultural Water Management, Elsevier, vol. 134(C), pages 24-37.
    3. Xiaoyan Bai & Wen Shen & Peng Wang & Xiaohong Chen & Yanhu He, 2020. "Response of Non-point Source Pollution Loads to Land Use Change under Different Precipitation Scenarios from a Future Perspective," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(13), pages 3987-4002, October.
    4. Villamizar, Martha L. & Brown, Colin D., 2016. "Modelling triazines in the valley of the River Cauca, Colombia, using the annualized agricultural non-point source pollution model," Agricultural Water Management, Elsevier, vol. 177(C), pages 24-36.
    5. Xiaojing Ni & Prem B. Parajuli & Ying Ouyang, 2020. "Assessing Agriculture Conservation Practice Impacts on Groundwater Levels at Watershed Scale," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(4), pages 1553-1566, March.
    6. Schuwirth, Nele & Borgwardt, Florian & Domisch, Sami & Friedrichs, Martin & Kattwinkel, Mira & Kneis, David & Kuemmerlen, Mathias & Langhans, Simone D. & Martínez-López, Javier & Vermeiren, Peter, 2019. "How to make ecological models useful for environmental management," Ecological Modelling, Elsevier, vol. 411(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jinfeng Yang & Xuelei Wang & Xinrong Li & Zhuang Tian & Guoyuan Zou & Lianfeng Du & Xuan Guo, 2023. "Potential Risk Identification of Agricultural Nonpoint Source Pollution: A Case Study of Yichang City, Hubei Province," Sustainability, MDPI, vol. 15(23), pages 1-14, November.

    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. Brias, Antoine & Munch, Stephan B., 2021. "Ecosystem based multi-species management using Empirical Dynamic Programming," Ecological Modelling, Elsevier, vol. 441(C).
    2. Chuan Luo & Zhaofu Li & Hengpeng Li & Xiaomin Chen, 2015. "Evaluation of the AnnAGNPS Model for Predicting Runoff and Nutrient Export in a Typical Small Watershed in the Hilly Region of Taihu Lake," IJERPH, MDPI, vol. 12(9), pages 1-19, September.
    3. Negar Tayebzadeh Moghadam & Karim C. Abbaspour & Bahram Malekmohammadi & Mario Schirmer & Ahmad Reza Yavari, 2021. "Spatiotemporal Modelling of Water Balance Components in Response to Climate and Landuse Changes in a Heterogeneous Mountainous Catchment," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(3), pages 793-810, February.
    4. Mosai, Alseno K. & Tokwana, Bontle C. & Tutu, Hlanganani, 2022. "Computer simulation modelling of the simultaneous adsorption of Cd, Cu and Cr from aqueous solutions by agricultural clay soil: A PHREEQC geochemical modelling code coupled to parameter estimation (PE," Ecological Modelling, Elsevier, vol. 465(C).
    5. Karki, Ritesh & Tagert, Mary Love M. & Paz, Joel O. & Bingner, Ronald L., 2017. "Application of AnnAGNPS to model an agricultural watershed in East-Central Mississippi for the evaluation of an on-farm water storage (OFWS) system," Agricultural Water Management, Elsevier, vol. 192(C), pages 103-114.
    6. Di Pirro, E. & Sallustio, L. & Capotorti, G. & Marchetti, M. & Lasserre, B., 2021. "A scenario-based approach to tackle trade-offs between biodiversity conservation and land use pressure in Central Italy," Ecological Modelling, Elsevier, vol. 448(C).
    7. Pooja Patel & Arindam Sarkar, 2022. "Entropy-Based Flow and Sediment Routing in Data Deficit River Networks," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(8), pages 2757-2777, June.
    8. R. L. Bingner & R. R. Wells & H. G. Momm & J. R. Rigby & F. D. Theurer, 2016. "Ephemeral gully channel width and erosion simulation technology," 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. 80(3), pages 1949-1966, February.
    9. Haider, Saira M. & Benscoter, Allison M. & Pearlstine, Leonard & D'Acunto, Laura E. & Romañach, Stephanie S., 2021. "Landscape-scale drivers of endangered Cape Sable Seaside Sparrow (Ammospiza maritima mirabilis) presence using an ensemble modeling approach," Ecological Modelling, Elsevier, vol. 461(C).
    10. Momm, Henrique G. & Bingner, Ronald L. & Moore, Katy & Herring, Glenn, 2022. "Integrated surface and groundwater modeling to enhance water resource sustainability in agricultural watersheds," Agricultural Water Management, Elsevier, vol. 269(C).
    11. Yao Ji & Guo Huang & Wei Sun, 2015. "Nonpoint-Source Water Quality Management Under Uncertainty Through an Inexact Double-Sided Chance-Constrained Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(9), pages 3079-3094, July.
    12. Xiao Zhang & Xiaomin Chen & Wanshun Zhang & Hong Peng & Gaohong Xu & Yanxin Zhao & Zhenling Shen, 2022. "Impact of Land Use Changes on the Surface Runoff and Nutrient Load in the Three Gorges Reservoir Area, China," Sustainability, MDPI, vol. 14(4), pages 1-21, February.
    13. Haag, Fridolin & Chennu, Arjun, 2023. "Assessing whether decisions are more sensitive to preference or prediction uncertainty with a value of information approach," Omega, Elsevier, vol. 121(C).
    14. Sutton, G.F. & Martin, G.D., 2022. "Testing MaxEnt model performance in a novel geographic region using an intentionally introduced insect," Ecological Modelling, Elsevier, vol. 473(C).
    15. Callesen, I. & Magnussen, A., 2021. "TransparC2U–A two-pool, pedology oriented forest soil carbon simulation model aimed at user investigations of multiple uncertainties," Ecological Modelling, Elsevier, vol. 453(C).
    16. Chollet Ramampiandra, Emma & Scheidegger, Andreas & Wydler, Jonas & Schuwirth, Nele, 2023. "A comparison of machine learning and statistical species distribution models: Quantifying overfitting supports model interpretation," Ecological Modelling, Elsevier, vol. 481(C).
    17. Bobrowski, Maria & Weidinger, Johannes & Schwab, Niels & Schickhoff, Udo, 2021. "Searching for ecology in species distribution models in the Himalayas," Ecological Modelling, Elsevier, vol. 458(C).
    18. Wan, Wei & Han, Yiwen & Wu, Hanqing & Liu, Fan & Liu, Zhong, 2021. "Application of the source–sink landscape method in the evaluation of agricultural non-point source pollution: First estimation of an orchard-dominated area in China," Agricultural Water Management, Elsevier, vol. 252(C).
    19. Acosta-Arreola, Jaime & Domínguez-Hüttinger, Elisa & Aguirre, Pablo & González, Nicolás & Meave, Jorge A., 2023. "Predicting dynamic trajectories of a protected plant community under contrasting conservation regimes: Insights from data-based modelling," Ecological Modelling, Elsevier, vol. 484(C).
    20. dos Anjos, Lucas & Weber, Igor Daniel & Godoy, Wesley Augusto Conde, 2023. "Modelling the biocontrol of Spodoptera frugiperda: A mechanistic approach considering Bt crops and oviposition behaviour," Ecological Modelling, Elsevier, vol. 484(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:spr:waterr:v:36:y:2022:i:4:d:10.1007_s11269-022-03082-8. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.