IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v496y2024ics0304380024002151.html
   My bibliography  Save this article

Transport of nitrogen in grassed watersheds accounting for the combined influence of grazing and climate

Author

Listed:
  • Sadsad, Jeric S.
  • Chu, Maria L.
  • Guzman, Jorge A.
  • Moriasi, Daniel N.
  • Fortuna, Ann-Marie

Abstract

A comprehensive modeling framework utilizing MIKE-SHE to investigate the feasibility of enhancing livestock production while concurrently mitigating the impact of grassland ecosystems on surface water quality is presented. In this study, a modeling framework that simulates nitrogen transport was developed using a physically based distributed hydrologic model, MIKE SHE. The model was calibrated and validated using observed overland flow and water quality data from El Reno, Oklahoma's Water Resources and Erosion Unit watersheds. Different scenarios involving variations in timing, duration, and frequency of grazing activities, stocking rates, and climate conditions were simulated using the calibrated MIKE-SHE model. The goal was to explore the extent of the influence of these aspects of grazing on water quality through these scenario simulations. The results provided valuable insights into the key factors for developing an intelligent grazing decision tool to delineate targeted grazing windows that optimally balance heightened livestock production with environmental sustainability. The study's findings showed that the observed variability in existing literature originates mainly from climatic differences, with precipitation being the primary driver of nutrient loss, while evapotranspiration and soil moisture conditions are secondary factors. The simulations revealed that the impact of grazing on nitrogen loss in the pasture is evident only when grazing activities, irrespective of the stocking rate, duration, and frequency, occur under weather conditions conducive to nutrient loss in the pasture. These intertwined processes suggest that the impact of grazing on nitrogen loss can only be generalized within the context of the prevailing weather conditions in the pasture. Hence, strategically matching grazing activities with prevailing weather patterns can increase livestock production while promoting environmental sustainability in pasture management.

Suggested Citation

  • Sadsad, Jeric S. & Chu, Maria L. & Guzman, Jorge A. & Moriasi, Daniel N. & Fortuna, Ann-Marie, 2024. "Transport of nitrogen in grassed watersheds accounting for the combined influence of grazing and climate," Ecological Modelling, Elsevier, vol. 496(C).
    • Handle: RePEc:eee:ecomod:v:496:y:2024:i:c:s0304380024002151
    DOI: 10.1016/j.ecolmodel.2024.110827
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380024002151
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ecolmodel.2024.110827?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. Sengupta, Manajit & Xie, Yu & Lopez, Anthony & Habte, Aron & Maclaurin, Galen & Shelby, James, 2018. "The National Solar Radiation Data Base (NSRDB)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 89(C), pages 51-60.
    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. Neupane, Deependra & Kafle, Sagar & Karki, Kaji Ram & Kim, Dae Hyun & Pradhan, Prajal, 2022. "Solar and wind energy potential assessment at provincial level in Nepal: Geospatial and economic analysis," Renewable Energy, Elsevier, vol. 181(C), pages 278-291.
    2. Gueymard, Christian A. & Bright, Jamie M. & Lingfors, David & Habte, Aron & Sengupta, Manajit, 2019. "A posteriori clear-sky identification methods in solar irradiance time series: Review and preliminary validation using sky imagers," Renewable and Sustainable Energy Reviews, Elsevier, vol. 109(C), pages 412-427.
    3. Omoyele, Olalekan & Hoffmann, Maximilian & Koivisto, Matti & Larrañeta, Miguel & Weinand, Jann Michael & Linßen, Jochen & Stolten, Detlef, 2024. "Increasing the resolution of solar and wind time series for energy system modeling: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
    4. Vallianos, Charalampos & Candanedo, José & Athienitis, Andreas, 2023. "Application of a large smart thermostat dataset for model calibration and Model Predictive Control implementation in the residential sector," Energy, Elsevier, vol. 278(PA).
    5. Bracken, Cameron & Voisin, Nathalie & Burleyson, Casey D. & Campbell, Allison M. & Hou, Z. Jason & Broman, Daniel, 2024. "Standardized benchmark of historical compound wind and solar energy droughts across the Continental United States," Renewable Energy, Elsevier, vol. 220(C).
    6. Craig, Michael & Guerra, Omar J. & Brancucci, Carlo & Pambour, Kwabena Addo & Hodge, Bri-Mathias, 2020. "Valuing intra-day coordination of electric power and natural gas system operations," Energy Policy, Elsevier, vol. 141(C).
    7. Zimmerman, Ryan & Panda, Anurag & Bulović, Vladimir, 2020. "Techno-economic assessment and deployment strategies for vertically-mounted photovoltaic panels," Applied Energy, Elsevier, vol. 276(C).
    8. Sanzana Tabassum & Tanvin Rahman & Ashraf Ul Islam & Sumayya Rahman & Debopriya Roy Dipta & Shidhartho Roy & Naeem Mohammad & Nafiu Nawar & Eklas Hossain, 2021. "Solar Energy in the United States: Development, Challenges and Future Prospects," Energies, MDPI, vol. 14(23), pages 1-65, December.
    9. Amadeh, Ali & Lee, Zachary E. & Zhang, K. Max, 2022. "Quantifying demand flexibility of building energy systems under uncertainty," Energy, Elsevier, vol. 246(C).
    10. Sun, Yinong & Frew, Bethany & Dalvi, Sourabh & Dhulipala, Surya C., 2022. "Insights into methodologies and operational details of resource adequacy assessment: A case study with application to a broader flexibility framework," Applied Energy, Elsevier, vol. 328(C).
    11. Grubbs, E.K. & Gruss, S.M. & Schull, V.Z. & Gosney, M.J. & Mickelbart, M.V. & Brouder, S. & Gitau, M.W. & Bermel, P. & Tuinstra, M.R. & Agrawal, R., 2024. "Optimized agrivoltaic tracking for nearly-full commodity crop and energy production," Renewable and Sustainable Energy Reviews, Elsevier, vol. 191(C).
    12. Musaed Alhussein & Syed Irtaza Haider & Khursheed Aurangzeb, 2019. "Microgrid-Level Energy Management Approach Based on Short-Term Forecasting of Wind Speed and Solar Irradiance," Energies, MDPI, vol. 12(8), pages 1-27, April.
    13. Liu, Bai & Yang, Dazhi & Mayer, Martin János & Coimbra, Carlos F.M. & Kleissl, Jan & Kay, Merlinde & Wang, Wenting & Bright, Jamie M. & Xia, Xiang’ao & Lv, Xin & Srinivasan, Dipti & Wu, Yan & Beyer, H, 2023. "Predictability and forecast skill of solar irradiance over the contiguous United States," Renewable and Sustainable Energy Reviews, Elsevier, vol. 182(C).
    14. Manzano, J.M. & Salvador, J.R. & Romaine, J.B. & Alvarado-Barrios, L., 2022. "Economic predictive control for isolated microgrids based on real world demand/renewable energy data and forecast errors," Renewable Energy, Elsevier, vol. 194(C), pages 647-658.
    15. Khamlich, Imane & Zeng, Kuo & Flamant, Gilles & Baeyens, Jan & Zou, Chongzhe & Li, Jun & Yang, Xinyi & He, Xiao & Liu, Qingchuan & Yang, Haiping & Yang, Qing & Chen, Hanping, 2021. "Technical and economic assessment of thermal energy storage in concentrated solar power plants within a spot electricity market," Renewable and Sustainable Energy Reviews, Elsevier, vol. 139(C).
    16. Yang, Dazhi, 2018. "A correct validation of the National Solar Radiation Data Base (NSRDB)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 97(C), pages 152-155.
    17. Ryan S. Montrose & John F. Gardner & Aykut C. Satici, 2021. "Centralized and Decentralized Optimal Control of Variable Speed Heat Pumps," Energies, MDPI, vol. 14(13), pages 1-18, July.
    18. Krause, Max J. & Detwiler, Natalie & Schwarber, Amy & McCauley, Margaret, 2022. "An evaluation of solar thermal heating to support a freeze-thaw anaerobic digestion system for human waste treatment in subarctic environments," Renewable Energy, Elsevier, vol. 198(C), pages 618-625.
    19. DiOrio, Nicholas & Denholm, Paul & Hobbs, William B., 2020. "A model for evaluating the configuration and dispatch of PV plus battery power plants," Applied Energy, Elsevier, vol. 262(C).
    20. Yagli, Gokhan Mert & Yang, Dazhi & Srinivasan, Dipti, 2019. "Automatic hourly solar forecasting using machine learning models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 105(C), pages 487-498.

    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:eee:ecomod:v:496:y:2024:i:c:s0304380024002151. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/ecological-modelling .

    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.