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Determining water-use-efficient irrigation strategies for cotton using the DSSAT CSM CROPGRO-cotton model evaluated with in-season data

Author

Listed:
  • Garibay, Victoria M.
  • Kothari, Kritika
  • Ale, Srinivasulu
  • Gitz, Dennis C.
  • Morgan, Gaylon D.
  • Munster, Clyde L.

Abstract

The Texas High Plains (THP) region, a vital part of U.S. grain and fiber production, is experiencing the effects of conflicting interests in the diminishing Ogallala Aquifer, making necessary the adoption of more efficient irrigation strategies. Decision Support System for Agrotechnology Transfer (DSSAT) is a process-based model that uses meteorological, soil, and crop management data to predict crop growth, development, and yield. A well-evaluated DSSAT model is useful for simulation of efficient crop and irrigation management strategies. This study details the evaluation of CROPGRO-Cotton module in the DSSAT model based on measured in-season biomass and canopy height, and crop yield data from a field study as well as the use of the evaluated model for determining the best irrigation strategy for cotton (Gossypium hirsutum L. var. hirsutum) in terms of crop yield and irrigation water use efficiency. Irrigation simulation experiments were conducted over a testing range for four separate irrigation scheduling strategies —Time Temperature Threshold (TTT)-5.5 h, TTT-7.5 h, Daily Irrigation (DI), and percent ET replacement —to determine the most efficient irrigation strategy that results in maximum yield with minimum irrigation water input. The DSSAT CROPGRO-Cotton model demonstrated potential to simulate the effects of various irrigation strategies on cotton yield and water use efficiency. The 12 mm, 7.5 h TTT strategy was found to be the best strategy to achieve a maximized yield with the greatest irrigation water use efficiency, with a modelled yield of 5887 kg ha−1 using 195 mm of irrigation throughout the season.

Suggested Citation

  • Garibay, Victoria M. & Kothari, Kritika & Ale, Srinivasulu & Gitz, Dennis C. & Morgan, Gaylon D. & Munster, Clyde L., 2019. "Determining water-use-efficient irrigation strategies for cotton using the DSSAT CSM CROPGRO-cotton model evaluated with in-season data," Agricultural Water Management, Elsevier, vol. 223(C), pages 1-1.
  • Handle: RePEc:eee:agiwat:v:223:y:2019:i:c:49
    DOI: 10.1016/j.agwat.2019.105695
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    1. O'Shaughnessy, S.A. & Evett, S.R. & Colaizzi, P.D. & Howell, T.A., 2011. "Using radiation thermography and thermometry to evaluate crop water stress in soybean and cotton," Agricultural Water Management, Elsevier, vol. 98(10), pages 1523-1535, August.
    2. Kothari, Kritika & Ale, Srinivasulu & Bordovsky, James P. & Thorp, Kelly R. & Porter, Dana O. & Munster, Clyde L., 2019. "Simulation of efficient irrigation management strategies for grain sorghum production over different climate variability classes," Agricultural Systems, Elsevier, vol. 170(C), pages 49-62.
    3. O'Shaughnessy, S.A. & Evett, S.R., 2010. "Canopy temperature based system effectively schedules and controls center pivot irrigation of cotton," Agricultural Water Management, Elsevier, vol. 97(9), pages 1310-1316, September.
    4. Adhikari, Pradip & Ale, Srinivasulu & Bordovsky, James P. & Thorp, Kelly R. & Modala, Naga R. & Rajan, Nithya & Barnes, Edward M., 2016. "Simulating future climate change impacts on seed cotton yield in the Texas High Plains using the CSM-CROPGRO-Cotton model," Agricultural Water Management, Elsevier, vol. 164(P2), pages 317-330.
    5. Wanjura, Donald F. & Upchurch, Dan R. & Mahan, James R. & Burke, John J., 2002. "Cotton yield and applied water relationships under drip irrigation," Agricultural Water Management, Elsevier, vol. 55(3), pages 217-237, June.
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    Cited by:

    1. Himanshu, Sushil Kumar & Fan, Yubing & Ale, Srinivasulu & Bordovsky, James, 2021. "Simulated efficient growth-stage-based deficit irrigation strategies for maximizing cotton yield, crop water productivity and net returns," Agricultural Water Management, Elsevier, vol. 250(C).
    2. Wang, Haidong & Cheng, Minghui & Liao, Zhenqi & Guo, Jinjin & Zhang, Fucang & Fan, Junliang & Feng, Hao & Yang, Qiliang & Wu, Lifeng & Wang, Xiukang, 2023. "Performance evaluation of AquaCrop and DSSAT-SUBSTOR-Potato models in simulating potato growth, yield and water productivity under various drip fertigation regimes," Agricultural Water Management, Elsevier, vol. 276(C).
    3. Himanshu, Sushil K. & Ale, Srinivasulu & Bell, Jourdan & Fan, Yubing & Samanta, Sayantan & Bordovsky, James P. & Gitz III, Dennis C. & Lascano, Robert J. & Brauer, David K., 2023. "Evaluation of growth-stage-based variable deficit irrigation strategies for cotton production in the Texas High Plains," Agricultural Water Management, Elsevier, vol. 280(C).
    4. Fan, Yubing & Himanshu, Sushil K. & Ale, Srinivasulu & DeLaune, Paul B. & Zhang, Tian & Park, Seong C. & Colaizzi, Paul D. & Evett, Steven R. & Baumhardt, R. Louis, 2022. "The synergy between water conservation and economic profitability of adopting alternative irrigation systems for cotton production in the Texas High Plains," Agricultural Water Management, Elsevier, vol. 262(C).
    5. Chen, Ning & Li, Xianyue & Shi, Haibin & Zhang, Yuehong & Hu, Qi & Sun, Ya’nan, 2023. "Modeling effects of biodegradable film mulching on evapotranspiration and crop yields in Inner Mongolia," Agricultural Water Management, Elsevier, vol. 275(C).

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