IDEAS home Printed from https://ideas.repec.org/a/spr/endesu/v23y2021i8d10.1007_s10668-020-01112-2.html
   My bibliography  Save this article

Optimizing different adaptive strategies by using crop growth modeling under IPCC climate change scenarios for sustainable wheat production

Author

Listed:
  • Muhammad Rizwan Shahid

    (University of Agriculture)

  • Abdul Wakeel

    (University of Agriculture)

  • Wajid Ishaque

    (Soil and Environmental Sciences Division, Nuclear Institute for Agriculture and Biology)

  • Samia Ali

    (University of Agriculture)

  • Kamran Baksh Soomro

    (Pakistan Agricultural Research Council)

  • Muhammad Awais

    (University of Agriculture)

Abstract

Crop production is highly sensitive to climate. It is affected by long-term trends in average rainfall and temperature, inter-annual climate variability, shocks during specific phenological stages and extreme weather events. As climate changes, crop production strategies must change too. Field trials were conducted at Nuclear Institute for Agriculture and Biology, Faisalabad-Pakistan, on wheat to assess nutrient and water productivity in irrigated semiarid conditions of Faisalabad. The treatments were six dates of sowing (DOS) (20th October, 30th October, 10th November, 20th November, 30th November and 10th December) with five nitrogen levels (N-levels), i.e., (0, 60, 120, 180 and 240 kg ha−1). CSM-CERES wheat model under the umbrella of DSSAT (4.6) was used to assess the impact of changing climate on wheat production. Model was then evaluated on the basis of data collected during field experiments. Model’s performance was evaluated by computing different statistical variables (d, R2). Intergovernmental Panel on Climate Change’s (IPCC), Representative Concentration Pathways (RCPs) were used to assess the climatic changes in the near, the middle and at the last of the century (2030, 2050 and 2090). Data collected during field experiment showed that biological and grain yields were increased up to 10th November DOS and then a decreasing trend was started up to 10th December DOS. A statistically significant (p ≤ 0.05) interaction was observed between DOS and N-levels. DOS and N-levels interactive affect showed significantly higher biological and grain yields at 180 and 240 kg N ha−1, respectively, when crop was sown on 10th November, while significantly lower yield at 0 kg N ha−1 with sowing date 20th October. The model results indicated that N-levels have not much significant effect on wheat yield under changing climate scenarios RCPs. But the changes in DOS showed significant results under these RCPs in irrigated conditions. The DOS 30th November with 180 kg N ha−1 will performs better in 2030, 2050 and 2090 than other DOS as predicted by the model. Model predicts the lowest yields in the early date of sowing, i.e., 30th October, 10th November, etc. But in later DOS model showed significantly higher yields for 2030, 2050 and 2090.

Suggested Citation

  • Muhammad Rizwan Shahid & Abdul Wakeel & Wajid Ishaque & Samia Ali & Kamran Baksh Soomro & Muhammad Awais, 2021. "Optimizing different adaptive strategies by using crop growth modeling under IPCC climate change scenarios for sustainable wheat production," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(8), pages 11310-11334, August.
  • Handle: RePEc:spr:endesu:v:23:y:2021:i:8:d:10.1007_s10668-020-01112-2
    DOI: 10.1007/s10668-020-01112-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10668-020-01112-2
    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/s10668-020-01112-2?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. Ariel Ortiz-Bobea & Richard E. Just, 2013. "Modeling the Structure of Adaptation in Climate Change Impact Assessment," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 95(2), pages 244-251.
    2. Anwar, Muhuddin Rajin & Liu, De Li & Farquharson, Robert & Macadam, Ian & Abadi, Amir & Finlayson, John & Wang, Bin & Ramilan, Thiagarajah, 2015. "Climate change impacts on phenology and yields of five broadacre crops at four climatologically distinct locations in Australia," Agricultural Systems, Elsevier, vol. 132(C), pages 133-144.
    3. Jamie Sanderson & Sardar M. N. Islam, 2007. "Climate Change and Economic Development," Palgrave Macmillan Books, Palgrave Macmillan, number 978-0-230-59012-0, October.
    4. Junichi Fujino, Rajesh Nair, Mikiko Kainuma, Toshihiko Masui and Yuzuru Matsuoka, 2006. "Multi-gas Mitigation Analysis on Stabilization Scenarios Using Aim Global Model," The Energy Journal, International Association for Energy Economics, vol. 0(Special I), pages 343-354.
    5. van Vuuren, Detlef P. & Weyant, John & de la Chesnaye, Francisco, 2006. "Multi-gas scenarios to stabilize radiative forcing," Energy Economics, Elsevier, vol. 28(1), pages 102-120, January.
    6. Shilpa Rao and Keywan Riahi, 2006. "The Role of Non-CO2 Greenhouse Gases in Climate Change Mitigation: Long-term Scenarios for the 21st Century," The Energy Journal, International Association for Energy Economics, vol. 0(Special I), pages 177-200.
    7. Steven J. Smith and T.M.L. Wigley, 2006. "Multi-Gas Forcing Stabilization with Minicam," The Energy Journal, International Association for Energy Economics, vol. 0(Special I), pages 373-392.
    8. D.P. van Vuuren, B. Eickhout, P.L. Lucas and M.G.J. den Elzen, 2006. "Long-Term Multi-Gas Scenarios to Stabilise Radiative Forcing - Exploring Costs and Benefits Within an Integrated Assessment Framework," The Energy Journal, International Association for Energy Economics, vol. 0(Special I), pages 201-234.
    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. Guerra, Omar J. & Tejada, Diego A. & Reklaitis, Gintaras V., 2019. "Climate change impacts and adaptation strategies for a hydro-dominated power system via stochastic optimization," Applied Energy, Elsevier, vol. 233, pages 584-598.
    2. Samuel Carrara & Giacomo Marangoni, 2013. "Non-CO2 Greenhouse Gas Mitigation Modeling with Marginal Abatement Cost Curves: Technical Change, Emission Scenarios and Policy Costs," Working Papers 2013.110, Fondazione Eni Enrico Mattei.
    3. Zhang, Hailing & Liu, Changxin & Wang, Can, 2021. "Extreme climate events and economic impacts in China: A CGE analysis with a new damage function in IAM," Technological Forecasting and Social Change, Elsevier, vol. 169(C).
    4. Kuik, Onno & Brander, Luke & Tol, Richard S.J., 2009. "Marginal abatement costs of greenhouse gas emissions: A meta-analysis," Energy Policy, Elsevier, vol. 37(4), pages 1395-1403, April.
    5. Rose, Steven K. & Ahammad, Helal & Eickhout, Bas & Fisher, Brian & Kurosawa, Atsushi & Rao, Shilpa & Riahi, Keywan & van Vuuren, Detlef P., 2012. "Land-based mitigation in climate stabilization," Energy Economics, Elsevier, vol. 34(1), pages 365-380.
    6. A. Reisinger & P. Havlik & K. Riahi & O. Vliet & M. Obersteiner & M. Herrero, 2013. "Implications of alternative metrics for global mitigation costs and greenhouse gas emissions from agriculture," Climatic Change, Springer, vol. 117(4), pages 677-690, April.
    7. Chen, Yong & Marek, Gary W. & Marek, Thomas H. & Moorhead, Jerry E. & Heflin, Kevin R. & Brauer, David K. & Gowda, Prasanna H. & Srinivasan, Raghavan, 2019. "Simulating the impacts of climate change on hydrology and crop production in the Northern High Plains of Texas using an improved SWAT model," Agricultural Water Management, Elsevier, vol. 221(C), pages 13-24.
    8. Robinson, Sherman & Mason d'Croz, Daniel & Islam, Shahnila & Sulser, Timothy B. & Robertson, Richard D. & Zhu, Tingju & Gueneau, Arthur & Pitois, Gauthier & Rosegrant, Mark W., 2015. "The International Model for Policy Analysis of Agricultural Commodities and Trade (IMPACT): Model description for version 3:," IFPRI discussion papers 1483, International Food Policy Research Institute (IFPRI).
    9. Adolf Stroombergen & Andy Reisinger, 2012. "The Macroeconomic Impact on New Zealand of Alternative GHG Exchange Rate Metrics," EcoMod2012 4140, EcoMod.
    10. Samuel Carrara & Giacomo Marangoni, 2013. "Non-CO2 greenhouse gas mitigation modeling with marginal abatement cost curv es: technical change, emission scenarios and policy costs," ECONOMICS AND POLICY OF ENERGY AND THE ENVIRONMENT, FrancoAngeli Editore, vol. 2013(1), pages 91-124.
    11. Sohl, Terry L. & Wimberly, Michael C. & Radeloff, Volker C. & Theobald, David M. & Sleeter, Benjamin M., 2016. "Divergent projections of future land use in the United States arising from different models and scenarios," Ecological Modelling, Elsevier, vol. 337(C), pages 281-297.
    12. Mason-D'Croz, Daniel & Sulser, Timothy B. & Wiebe, Keith & Rosegrant, Mark W. & Lowder, Sarah K. & Nin-Pratt, Alejandro & Willenbockel, Dirk & Robinson, Sherman & Zhu, Tingju & Cenacchi, Nicola & Duns, 2019. "Agricultural investments and hunger in Africa modeling potential contributions to SDG2 – Zero Hunger," World Development, Elsevier, vol. 116(C), pages 38-53.
    13. Elettra Agliardi & Thomas Alexopoulos & Christian Cech, 2019. "On the Relationship Between GHGs and Global Temperature Anomalies: Multi-level Rolling Analysis and Copula Calibration," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 72(1), pages 109-133, January.
    14. G. Pranuthi & S. K. Tripathi, 2018. "Assessing the climate change and its impact on rice yields of Haridwar district using PRECIS RCM data," Climatic Change, Springer, vol. 148(1), pages 265-278, May.
    15. van Vuuren, Detlef P. & Hoogwijk, Monique & Barker, Terry & Riahi, Keywan & Boeters, Stefan & Chateau, Jean & Scrieciu, Serban & van Vliet, Jasper & Masui, Toshihiko & Blok, Kornelis & Blomen, Eliane , 2009. "Comparison of top-down and bottom-up estimates of sectoral and regional greenhouse gas emission reduction potentials," Energy Policy, Elsevier, vol. 37(12), pages 5125-5139, December.
    16. Duro, Juan Antonio & Giménez-Gómez, José-Manuel & Vilella, Cori, 2020. "The allocation of CO2 emissions as a claims problem," Energy Economics, Elsevier, vol. 86(C).
    17. Kayla A. Cotterman & Anthony D. Kendall & Bruno Basso & David W. Hyndman, 2018. "Groundwater depletion and climate change: future prospects of crop production in the Central High Plains Aquifer," Climatic Change, Springer, vol. 146(1), pages 187-200, January.
    18. Qian, Yuan & Scherer, Laura & Tukker, Arnold & Behrens, Paul, 2020. "China's potential SO2 emissions from coal by 2050," Energy Policy, Elsevier, vol. 147(C).
    19. Yong Chen & Gary W. Marek & Thomas H. Marek & Dana O. Porter & Jerry E. Moorhead & Qingyu Wang & Kevin R. Heflin & David K. Brauer, 2020. "Spatio-Temporal Analysis of Historical and Future Climate Data in the Texas High Plains," Sustainability, MDPI, vol. 12(15), pages 1-19, July.
    20. Riccardo Rebonato & Riccardo Ronzani & Lionel Melin, 2023. "Robust management of climate risk damages," Risk Management, Palgrave Macmillan, vol. 25(3), pages 1-43, September.

    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:endesu:v:23:y:2021:i:8:d:10.1007_s10668-020-01112-2. 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.