IDEAS home Printed from https://ideas.repec.org/a/eee/agiwat/v252y2021ics0378377421001153.html
   My bibliography  Save this article

Modelling the effects of climate change, agricultural inputs, cropping diversity, and environment on soil nitrogen and phosphorus: A case study in Saskatchewan, Canada

Author

Listed:
  • Lychuk, Taras E.
  • Moulin, Alan P.
  • Lemke, Reynald L.
  • Izaurralde, Roberto C.
  • Johnson, Eric N.
  • Olfert, Owen O.
  • Brandt, Stewart A.

Abstract

The relative impact of climate change, agricultural inputs, crop diversity, and environment on soil nitrate-N (NO3-N) and labile soil phosphorus (P) has seldom been assessed in the scientific literature. Furthermore crop management of plant nutrients, based on a combination of agricultural inputs and crop diversity, has not been assessed with respect to adaptation to climate change. This modeling study assessed soil NO3-N leaching and labile P simulated with the Environmental Policy Integrated Climate (EPIC) model for historical and future climate scenarios for the Alternative Cropping Systems (ACS) study (1994–2013) in North-Western Saskatchewan, Canada. The EPIC model was updated with 19 years of field management information from the ACS study. The field study was a combination of the three levels of agricultural inputs [organic (ORG), reduced (RED), and high (HI)] and three levels of cropping diversity [low (LOW), diversified annual grains (DAG), and diversified annual & perennial (DAP)]. Recursive partitioning with multivariate analyses of agricultural inputs, cropping diversity, precipitation, growing degree days, and terrain were used to assess changes in NO3-N and P for each climate change scenario. This is the first analysis, with the EPIC model in the Canadian Prairies, of the effects of climate change on NO3-N losses in agricultural runoff, and soil P content in the context of different agricultural input systems in combinations with diversified rotations. NO3-N losses increased by 28% (from 27.1 to 34.7 kg ha−1 y−1), while labile soil P decreased by 12% (from 24.7 to 21.6 kg ha−1 y−1) under climate change, compared to historical weather. Summer precipitation explained 12% of total variation in future NO3-N losses. Combined, input and diversity explained 23% and 20% of variation in NO3-N losses and labile P, respectively. Cropping diversity was most significant, with reduced NO3-N leaching and labile P under climate change, accounting for 22% and 13% of total variation, respectively. Combined, RED inputs and DAG diversity reduced the impact of climate change on NO3-N losses and soil P and may provide a sustainable, adaptive solution for farming with regards to upcoming seasonal variations in temperature and precipitation. The scientific community, decision and policy makers will use this information to develop conceptual and practical farm- and field-scale technologies for producers, in order to adapt to the impact of climate change on agricultural production and the environment, with methodology which can be applied in Canada and other countries.

Suggested Citation

  • Lychuk, Taras E. & Moulin, Alan P. & Lemke, Reynald L. & Izaurralde, Roberto C. & Johnson, Eric N. & Olfert, Owen O. & Brandt, Stewart A., 2021. "Modelling the effects of climate change, agricultural inputs, cropping diversity, and environment on soil nitrogen and phosphorus: A case study in Saskatchewan, Canada," Agricultural Water Management, Elsevier, vol. 252(C).
  • Handle: RePEc:eee:agiwat:v:252:y:2021:i:c:s0378377421001153
    DOI: 10.1016/j.agwat.2021.106850
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378377421001153
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.agwat.2021.106850?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. Singer, J.W. & Malone, R.W. & Jaynes, D.B. & Ma, L., 2011. "Cover crop effects on nitrogen load in tile drainage from Walnut Creek Iowa using root zone water quality (RZWQ) model," Agricultural Water Management, Elsevier, vol. 98(10), pages 1622-1628, August.
    2. Wang, Zhaozhi & Zhang, T.Q. & Tan, C.S. & Taylor, R.A.J. & Wang, X. & Qi, Z.M. & Welacky, T., 2018. "Simulating crop yield, surface runoff, tile drainage and phosphorus loss in a clay loam soil of the Lake Erie region using EPIC," Agricultural Water Management, Elsevier, vol. 204(C), pages 212-221.
    3. Kiniry, James R. & Major, D. J. & Izarralde, R. C. & Williams, J. R. & Gassman, Philip W. & Morrison, M. & Bergentine, R. & Zentner, R. P., 1995. "Epic Model Parameters for Cereal, Oilseed, and Forage Crops in the Northern Great Plains Region," Staff General Research Papers Archive 894, Iowa State University, Department of Economics.
    4. Philip W. Gassman & Jimmy R. Williams & Verel W. Benson & R. César Izaurralde & Larry M. Hauck & C. Allan Jones & Jay D. Atwood & James Kiniry & Joan D. Flowers, 2005. "Historical Development and Applications of the EPIC and APEX Models," Center for Agricultural and Rural Development (CARD) Publications 05-wp397, Center for Agricultural and Rural Development (CARD) at Iowa State University.
    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. Alan F. Hamlet & Nima Ehsani & Jennifer L. Tank & Zachariah Silver & Kyuhyun Byun & Ursula H. Mahl & Shannon L. Speir & Matt T. Trentman & Todd V. Royer, 2024. "Effects of climate and winter cover crops on nutrient loss in agricultural watersheds in the midwestern U.S," Climatic Change, Springer, vol. 177(1), pages 1-21, January.

    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. Le, Kieu N. & Jeong, Jaehak & Reyes, Manuel R. & Jha, Manoj K. & Gassman, Philip W. & Doro, Luca & Hok, Lyda & Boulakia, Stéphane, 2018. "Evaluation of the performance of the EPIC model for yield and biomass simulation under conservation systems in Cambodia," Agricultural Systems, Elsevier, vol. 166(C), pages 90-100.
    2. Lychuk, Taras E. & Hill, Robert L. & Izaurralde, Roberto C. & Momen, Bahram & Thomson, Allison M., 2021. "Evaluation of climate change impacts and effectiveness of adaptation options on nitrate loss, microbial respiration, and soil organic carbon in the Southeastern USA," Agricultural Systems, Elsevier, vol. 193(C).
    3. Sheng Gong & Jason.S. Bergtold & Elizabeth Yeager, 2021. "Assessing the joint adoption and complementarity between in-field conservation practices of Kansas farmers," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 9(1), pages 1-24, December.
    4. Cabelguenne, M. & Debaeke, P. & Bouniols, A., 1999. "EPICphase, a version of the EPIC model simulating the effects of water and nitrogen stress on biomass and yield, taking account of developmental stages: validation on maize, sunflower, sorghum, soybea," Agricultural Systems, Elsevier, vol. 60(3), pages 175-196, June.
    5. Dennis Junior Choruma & Frank Chukwuzuoke Akamagwuna & Nelson Oghenekaro Odume, 2022. "Simulating the Impacts of Climate Change on Maize Yields Using EPIC: A Case Study in the Eastern Cape Province of South Africa," Agriculture, MDPI, vol. 12(6), pages 1-24, May.
    6. Gaiser, Thomas & Judex, Michael & Hiepe, Claudia & Kuhn, Arnim, 2010. "Regional simulation of maize production in tropical savanna fallow systems as affected by fallow availability," Agricultural Systems, Elsevier, vol. 103(9), pages 656-665, November.
    7. Liu, Junguo & Williams, Jimmy R. & Zehnder, Alexander J.B. & Yang, Hong, 2007. "GEPIC - modelling wheat yield and crop water productivity with high resolution on a global scale," Agricultural Systems, Elsevier, vol. 94(2), pages 478-493, May.
    8. Ascough II, J.C. & Andales, A.A. & Sherrod, L.A. & McMaster, G.S. & Hansen, N.C. & DeJonge, K.C. & Fathelrahman, E.M. & Ahuja, L.R. & Peterson, G.A. & Hoag, D.L., 2010. "Simulating landscape catena effects in no-till dryland agroecosystems using GPFARM," Agricultural Systems, Elsevier, vol. 103(8), pages 569-584, October.
    9. Shen Tan & Shengchao Qiao & Han Wang & Sheng Chang, 2024. "Predicting Wheat Potential Yield in China Based on Eco-Evolutionary Optimality Principles," Agriculture, MDPI, vol. 14(11), pages 1-15, November.
    10. Nina Noreika & Tailin Li & David Zumr & Josef Krasa & Tomas Dostal & Raghavan Srinivasan, 2020. "Farm-Scale Biofuel Crop Adoption and Its Effects on In-Basin Water Balance," Sustainability, MDPI, vol. 12(24), pages 1-15, December.
    11. Zilverberg, Cody J. & Williams, Jimmy & Jones, Curtis & Harmoney, Keith & Angerer, Jay & Metz, Loretta J. & Fox, William, 2017. "Process-based simulation of prairie growth," Ecological Modelling, Elsevier, vol. 351(C), pages 24-35.
    12. repec:ias:cpaper:13-tr50 is not listed on IDEAS
    13. Mary Ollenburger & Page Kyle & Xin Zhang, 2022. "Uncertainties in estimating global potential yields and their impacts for long-term modeling," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 14(5), pages 1177-1190, October.
    14. Choruma, Dennis Junior & Balkovic, Juraj & Pietsch, Stephan Alexander & Odume, Oghenekaro Nelson, 2021. "Using EPIC to simulate the effects of different irrigation and fertilizer levels on maize yield in the Eastern Cape, South Africa," Agricultural Water Management, Elsevier, vol. 254(C).
    15. Kirchner, Mathias & Mitter, Hermine & Schönhart, Martin & Schmid, Erwin, 2014. "Integrated land use modelling to analyse climate change adaptation in Austrian agriculture," 2014 International Congress, August 26-29, 2014, Ljubljana, Slovenia 182944, European Association of Agricultural Economists.
    16. Spencer, Daniel S. & Barnes, James N. & Coatney, Kalyn T. & Parman, Bryon J. & Coble, Keith H., 2017. "Property Rights And The Economics Of Non-Point Source Water Regulations In Agriculture: A New Biophysical-Economic Methodological Approach," 2017 Annual Meeting, February 4-7, 2017, Mobile, Alabama 252835, Southern Agricultural Economics Association.
    17. Ko, Jonghan & Piccinni, Giovanni & Steglich, Evelyn, 2009. "Using EPIC model to manage irrigated cotton and maize," Agricultural Water Management, Elsevier, vol. 96(9), pages 1323-1331, September.
    18. Dzotsi, K.A. & Basso, B. & Jones, J.W., 2013. "Development, uncertainty and sensitivity analysis of the simple SALUS crop model in DSSAT," Ecological Modelling, Elsevier, vol. 260(C), pages 62-76.
    19. Yang, Wei & Feng, Gary & Adeli, Ardeshir & Kersebaum, K.C. & Jenkins, Johnie N. & Li, Pinfang, 2019. "Long-term effect of cover crop on rainwater balance components and use efficiency in the no-tilled and rainfed corn and soybean rotation system," Agricultural Water Management, Elsevier, vol. 219(C), pages 27-39.
    20. Cavero, J. & Plant, R. E. & Shennan, C. & Williams, J. R. & Kiniry, J. R. & Benson, V. W., 1998. "Application of epic model to nitrogen cycling in irrigated processing tomatoes under different management systems," Agricultural Systems, Elsevier, vol. 56(4), pages 391-414, April.
    21. Kamruzzaman, Mohammad & Hwang, Syewoon & Choi, Soon-Kun & Cho, Jaepil & Song, Inhong & Jeong, Hanseok & Song, Jung-Hun & Jang, Teail & Yoo, Seung-Hwan, 2020. "Prediction of the effects of management practices on discharge and mineral nitrogen yield from paddy fields under future climate using APEX-paddy model," Agricultural Water Management, Elsevier, vol. 241(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:eee:agiwat:v:252:y:2021:i:c:s0378377421001153. 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.elsevier.com/locate/agwat .

    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.