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Evaluating Climate Change Impacts on Cotton Phenology and Yield Under Full and Deficit Irrigation Conditions in an Extremely Arid Oasis

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Abstract

Sustaining cotton (Gossypium hirsutum L.) production under limited water availability and climate change in an extremely arid oasis is a key challenge for the stakeholders. This study was conducted to quantify the climate change impacts on cotton phenology and seed yield under full (638 mm) and deficit (478 mm) irrigation regimes in an extremely arid oasis in China. The Root Zone Water Quality (RZWQM2) model with the integration of six global circulation models (GCMs) under two representative concentration pathways (RCP 4.5 and 8.5) was used to determine the potential impacts of climate change on cotton for future periods (2022–2047, 2048–2073, and 2073–2099) compared to baseline (1975–2000). The results revealed that number of days to anthesis and maturity was expected to be reduced under RCP 4.5 and RCP 8.5 with full and deficit irrigation for future periods compared to baseline. However, this reduction was maximum under RCP 8.5 for 2074–2099 with full irrigation treatment. Seed cotton yield was also expected to decrease by 13–18% (RCP4.5) and 14–18% (RCP 8.5) with full irrigation, while decline in yield was 10–14% (RCP 4.5) and 11-19.6% (RCP 8.5) under deficit irrigation for future periods. The maximum decline in yield appeared with deficit irrigation under RCP 8.5 for 2074–2099. This reduction in seed cotton yield is primarily attributed to elevated temperature in the future climate. A 25% deficit of irrigation compared to normal irrigation has also ensured a reasonable seed yield in future climate, therefore it could be considered as an irrigation management strategy in future for cotton production in extremely arid regions. Findings of this study will provide a better guidance to cotton growers for applying deficit irrigation to sustain cotton production under changing climate with limited water availability in XUAR and other similar agro-climatic regions.

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References

  • Abbas, G., Ahmad, S., Ahmad, A., Nasim, W., Fatima, Z., Hussain, S., & Hoogenboom, G. (2017). Quantification the impacts of climate change and crop management on phenology of maize-based cropping system in Punjab, Pakistan. Agricultural and Forest Meteorology, 247, 42–55.

    Article  Google Scholar 

  • Adhikari, P., Ale, S., Bordovsky, J. P., Thorp, K. R., Modala, N. R., Rajan, N., & Barnes, E. 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, 164, 317–330.

    Article  Google Scholar 

  • Ahmad, S., Abbas, Q., Abbas, G., Fatima, Z., Atique-ur-Rehman, N. S., Younis, H., Khan, R. J., Nasim, W., Habib ur Rehman, Ahmad, M., Rasul, A., Khan, G., M.A., & Hasanuzzaman, M. (2017). Quantification of Climate Warming and Crop Management Impacts on Cotton Phenology. Plants, 6(1), 7.

  • Ahmed, Z., Gui, D., Qi, Z., Liu, Y., Liu, Y., & Azmat, M. (2022). Agricultural system modeling: current achievements, innovations, and future roadmap. Arabian Journal of Geosciences, 15(4), 1–13.

    Article  Google Scholar 

  • Ahuja, L. R., Rojas, K. W., Hanson, J. D., Shaffer, M. J., & Ma, L. (2000). Root zone water quality model. Highlands Ranch, CO: Water Resources Publications

  • Anapalli, S. S., Fisher, D. K., Reddy, K. N., Pettigrew, W. T., Sui, R., & Ahuja, L. R. (2016). Vulnerabilities and Adapting Irrigated and Rainfed Cotton to Climate Change in the Lower Mississippi Delta Region. Climate, 4, 55.

  • Arshad, A., Raza, M. A., Zhang, Y., Zhang, L., Wang, X., Ahmed, M., & Habib-ur-Rehman, M. (2021). Impact of climate warming on cotton growth and yields in China and Pakistan: a Regional Perspective. Agriculture, 11, 97.

    Article  CAS  Google Scholar 

  • Ayankojo, I. T., Thorp, K. R., Morgan, K. T., Kothari, K., & Ale, S. (2020). Assessing the impacts of future climate on cotton production in the Arizona low desert. Transaction of ASABE, 63, 1087–1098.

    Article  Google Scholar 

  • Babel, M. S., Deb, P., & Soni, P. (2019). Performance evaluation of AquaCrop and DSSAT-CERES for maize under different irrigation and manure application rates in the Himalayan Region of India. Agricultural Research, 8, 207–217.

    Article  Google Scholar 

  • Bange, M. P., & Milroy, S. P. (2004). Growth and dry matter partitioning of diverse cotton genotypes. Field Crops Research, 87(1), 73-87.

  • Bannayan, M., & Hoogenboom, G. (2009). Using pattern recognition for estimating cultivar coefficients of a crop simulation model. Field Crops Research, 111(3), 290–302. https://doi.org/10.1016/j.fcr.2009.01.007.

    Article  Google Scholar 

  • Chen, X., Feng, S., Qi, Z., Sima, M. W., Zeng, F., Li, L., Cheng, H., & Wu, H. (2022). Optimizing Irrigation Strategies to Improve Water Use Efficiency of Cotton in Northwest China Using RZWQM2. Agriculture, 12,383.

  • Cetin, O., & Basbag, S. (2010). Effects of climatic factors on cotton production in semi-arid regions-A review. Research on Crops, 11, 785–791.

    Google Scholar 

  • Chen, Y., Hao, X., Chen, Y., & Zhu, C. (2019). Study on water system connectivity and ecological protection countermeasures for the Tarim River Basin in Xinjiang. Bulletin of The Chinese Academy of Sciences, 34, 1156–1164.

    Google Scholar 

  • Cheng, H., Shu, K., Qi, Z., Ma, L., Jin, V. L., Li, Y., Schmer, M. R., Wienhold, B. J., & Feng, S. (2021). Effects of residue removal and tillage on greenhouse gas emissions in continuous corn systems as simulated with RZWQM2. Journal of Environmental Management, 285, 112097.

    Article  CAS  PubMed  Google Scholar 

  • Cottee, N. S., Tan, D. K. Y., Bange, M. P., Cothren, J. T., & Campbell, L. C. (2010). Multi-level determination of heat tolerance in cotton (Gossypium hirsutum L.) under field conditions. Crop Science, 50, 2553–2564.

    Article  Google Scholar 

  • Craufurd, P. Q., & Wheeler, T. R. (2009). Climate change and the flowering time of annual crops. Journal of Experimental Botany, 60(9), 2529e2539.

    Article  Google Scholar 

  • Ding, J., Hu, W., Wu, J., Yang, Y., & Feng, H. (2019). Simulating the effects of conventional versus conservation tillage on soil water, nitrogen dynamics, and yield of winter wheat with RZWQM2. Agriculture Water Management, 230, 105956.

    Article  Google Scholar 

  • Fang, Q., Ma, L., Ahuja, L. R., Trout, T. J., Malone, R. W., Zhang, H., Gui, D., & Yu, Q. (2017). Long-term simulation of growth stage-based irrigation scheduling in maize under various water constraints in Colorado, USA. Frontiers of Agricultural Science and Engineering, 4, 172–184.

    Article  Google Scholar 

  • Gent, P. R., Danabasoglu, G., Donner, L. J., Holland, M. M., Hunke, E. C., Jayne, S. R., & Vertenstein, M. (2011). The community climate system model version 4. Journal of Climate, 24(19), 4973–4991.

    Article  Google Scholar 

  • Gerardeaux, E., Loison, R., Palaï, O., & Sultan, B. (2018). Adaptation strategies to climate change using cotton (Gossypium hirsutum L.) ideotypes in rainfed tropical cropping systems in Sub-Saharan Africa. A modeling approach. Field Crops Research, 226, 38–47.

    Article  Google Scholar 

  • Hatfield, J. L., Boote, K. J., Kimball, B. A., Ziska, L. H., Izaurralde, R. C., Ort, D., Thomson, A. M., & Wolfe, D. (2011). Climate impacts on agriculture: implications for crop production. Agronomy Journal, 103(2), 351–370.

    Article  Google Scholar 

  • Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G., & Jarvis, A. (2005). Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology, 25, 1965–1978.

    Article  Google Scholar 

  • Huang, S., Wortmann, M., Duethmann, D., Menz, C., Shi, F., & Zhao, C. (2018). Adaptation strategies of agriculture and water management to climate change in the Upper Tarim River basin, NW China. Agriculture Water Management, 203, 207–222.

    Article  Google Scholar 

  • Hussein, F., Janat, M., & Yakoub, A. (2014). Assessment of yield and water use efficiency of drip-irrigated cotton (Gossypium hirsutum L.) as affected by deficit irrigation. Turkish Journal of Agriculture, 35, 611–621.

  • IPCC (Climate change 2014). : Impacts, adaptation, and vulnerability Field, C.B., Barros, V.R., Dokken, D.J., Mach, K.J., Mastrandrea, M.D., Bilir, T.E., & White, L.L. (2014). Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.

  • IPCC, C. C., & The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment. (2021). : Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press. In Press.

  • Iqbal, 2011. Modeling the Impact of Climate Change on Seed Cotton (Gossypium hirsutum L.) Yield in Punjab Pakistan. Ph.D Thesis. Dept. of Agron; Univ. of Agric., Faisalabad.

  • Iqbal, M. A., Ping, Q., Abid, M., Muhammad, M. K. S., & Rizwan, M. (2016). Assessing risk perceptions and attitude among cotton farmers: a case of Punjab province. International Journal of Disaster Risk Reduction, 16, 68–74.

    Article  Google Scholar 

  • Islam, A., Ahuja, L.R., Garcia, L.A., Ma, L., Saseendran, S.A., & Trout, T.J. (2012). Modeling the impact of climate change on irrigated maize production in the Central Great Plains. Agricultural Water Management, 110, 94–108.

  • Jones, J. W., Hoogenboom, G., Porter, C. H., Boote, K. J., Batchelor, W. D., Hunt, L. A., & Ritchie, J. T. (2003). The DSSAT cropping system model. European Journal of Agronomy, 18(3), 235-265.

  • Kamworapan, C., & Surussavadee, S. (2019). Evaluation of CMIP5 Global Climate Models for Simulating Climatological Temperature and Precipitation for Southeast Asia. Advances in Meteorology, 2019, 1067365.

  • Li, M., Du, Y., Zhang, F., Bai, Y., Fan, J., Zhang, J., & Chen, S. (2019). Simulation of cotton growth and soil water content under film-mulched drip irrigation using modified CSM-CROPGRO-cotton model. Agricultural Water Management, 218, 124–138.

    Article  Google Scholar 

  • Li, M., Du, Y., Zhang, F., Fan, J., Ning, Y., Cheng, H., & Xiao, C. (2020). Modification of CSM-CROPGRO-Cotton model for simulating cotton growth and yield under various deficit irrigation strategies. Computers and Electronics in Agriculture, 179, 105843.

    Article  Google Scholar 

  • Li, N., Ning, Y., Li, Y., Junqing, C., Deli, L., Asim, B., Linchao, L., Tianxue, W., & Xinguo, C. (2021). A meta-analysis of the possible impact of climate change on global cotton yield based on crop simulation approaches. Agricultural Systems, 193, 143–155.

    Article  Google Scholar 

  • Li, N., Li, Y., Biswas, A., Wang, J., Dong, H., Chen, J., & Fan, X. (2021). Impact of climate change and crop management on cotton phenology based on statistical analysis in the main-cotton-planting areas of China. Journal of Cleaner Production, 298, 126750.

    Article  Google Scholar 

  • Liu, Y., Snider, J. L., Bhattarai, A., & Collins, G. (2022). Economic penalties associated with irrigation during high rainfall years in the southeastern United States. Agricultural Water Management, 272, 107825.

    Article  Google Scholar 

  • Liu, C., Qi, Z., Gu, Z., Gui, D., & Zeng, F. (2017). Optimizing irrigation rates for cotton production in an extremely arid area using RZEWM2-simulated water stress. Transactions of the ASABE, 60, 2041–2052.

    Article  Google Scholar 

  • Loison, R., Audebert, A., Debaeke, P., Hoogenboom, G., Leroux, L., Oumarou, P., & Gerardeaux, E. (2017). Designing cotton ideotypes for the future: reducing risk of crop failure for low input rainfed conditions in Northern Cameroon. European Journal of Agronomy, 90, 162–173.

    Article  Google Scholar 

  • Luo, Q. (2011). Temperature thresholds and crop production: a review. Climate Change, 109, 583–598.

    Article  Google Scholar 

  • Nasim, W., Ahmad, A., Belhouchette, H., Fahad, S., & Hoogenboom, G. (2016). Evaluation of the OILCROP-SUN model for sunflower hybrids under different agro-meteorological conditions of Punjab-Pakistan. Field Crops Research, 188, 17–30.

    Article  Google Scholar 

  • Ma, L., Hoogenboom, G., Saseendran, S. A., Bartling, P. N. S., Ahuja, L. R., & Green, T. R. (2009). Effects of estimating soil hydraulic properties and root growth factor on soil water balance and crop production. Agronomy Journal, 101(3), 572-583.

  • Ma, L., Ahuja, L. R., Nolan, B. T., Malone, R. W., Trout, T. J., & Qi, Z. (2012). Root Zone Water Quality Model (RZWQM2): Model use, calibration, and validation. Transactions of ASABE, 55(4), 1425-1446.

  • Olesen, J., & Bindi, E. M. (2002). Consequences of climate change for european agricultural productivity, land use and policy. European Journal of Agronomy, 16, 239–262.

    Article  Google Scholar 

  • Rahman, M. H., Ahmad, A., Wang, X., Wajid, A., Nasim, W., Hussain, M., & Hoogenboom, G. (2018). Multi-model projections of future climate and climate change impacts uncertainty assessment for cotton production in Pakistan. Agricultural and Forest Meteorology, 253, 94–113.

    Article  Google Scholar 

  • Reddy, K. R., Doma, P. R., Mearns, L. O., Boone, M. Y. L., Hodges, H. F., Richardson, A. G., & Kakani, V. G. (2002). Simulating the impacts of climate change on cotton production in the Mississippi Delta. Climate Research, 22(3), 271e281.

    Google Scholar 

  • Ritchie, G.L., Whitaker, J.R., Bednarz, C.W., & Hook, J.E. (2009). Sub-surface drip and overhead irrigation: A comparison of plant boll distribution in upland cotton. Agronomy Journal, 101, 1336–1344.

    Article  Google Scholar 

  • Ruane, A. C., Goldberg, R., & Chryssanthacopoulos, J. (2015). Climate forcing datasets for agricultural modeling: Merged products for gap-filling and historical climate series estimation. Agricultural and Forest Meteorology, 200, 233-248.

  • Shareef, M., Gui, D., Zeng, F., Waqas, M., Zhang, B., & Iqbal, H. (2018). Water productivity, growth, and physiological assessment of deficit irrigated cotton on hyperarid desert-oases in northwest China. Agricultural Water Management, 206, 1–10.

    Article  Google Scholar 

  • Tan, S., Wang, Q., Zhang, J., Chen, Y., Shan, Y., & Xu, D. (2018). Performance of Aqua Crop model for cotton growth simulation under film-mulched drip irrigation in southern Xinjiang, China. Agricultural Water Management, 196, 99–113.

    Article  Google Scholar 

  • Thorp, K. R., Barnes, E. M., Hunsaker, D. J., Kimball, B. A., White, J. W., Nazareth, V. J., & Hoogenboom, G. (2014). Evaluation of CSM-CROPGRO-Cotton for simulating effects of management and climate change on cotton growth and evapotranspiration in an arid environment. Transactions of ASABE, 57(6), 1627-1642.

  • Tilman, C. D., Balzer, C., Hill, J., & Befort, B. L. (2011). Global food demand and the sustainable intensification of agriculture. Proceedings of the National Academy of Sciences, 108, 20260–20264.

  • Trenberth, K. E. (2011). Changes in precipitation with climate change. Climate Change Research Letters, 47, 123–138.

    Google Scholar 

  • Voldoire, A., Sanchez-Gomez, E., Salas y Melia, D., Decharme, B., Cassou, C., Senesi, S., & Chauvin, F. (2013). The CNRM94 TRANSACTIONS OF THE ASABE CM5.1 global climate model: description and basic evaluation. Climate Dynamics, 40, 2091–2121.

    Article  Google Scholar 

  • Wallach D, Goffinet B (1987) Mean squared error of prediction in models for studying ecological and agronomic systems. Biometrics: 43: 561– 573

    Article  Google Scholar 

  • Wang, X. (2015). Impact and Adaptation of Climate Change on Cotton Phenology, Yield and Fiber Quality in Xinjiang (Doctoral dissertation). China Agricultural University (in Chinese with English abstract).

  • Wang, X., Wang, H., Si, Z., Gao, Y., & Duan, A. (2020). Modelling responses of cotton growth and yield to pre-planting soil moisture with the CROPGRO-Cotton model for a mulched drip irrigation system in the Tarim Basin. Agricultural Water Management, 241, 106378.

    Article  Google Scholar 

  • Watanabe, M., Suzuki, T., O’ishi, R., Komuro, Y., Watanabe, S., Emori, S., & Sekiguchi, M. (2010). Improved climate simulation by MIROC5: Mean states, variability, and climate sensitivity. Journal of Climate, 23, 6312–6335.

    Article  Google Scholar 

  • Wu, L., Zhang, F., Zhou, H., Suo, Y., Xue, F., Zhou, J., & Liang, F. (2014). Effect of drip irrigation and fertilizer application on water use efficiency and cotton yield in north of Xinjiang. Transactions of the Chinese Society of Agricultural Engineering, 30, 137–146.

  • Yang, Y., Yang, Y., Han, S., Macadam, I., & Liu, D. L. (2014). Prediction of cotton yield and water demand under climate change and future adaptation measures. Agricultural water Management, 144(1), 42e53.

    Google Scholar 

  • Yu, S., Zhang, L., & Feng, W. (2015). Easy and enjoyable cotton cultivation: developments in China’s cotton production. Cotton Science, 27, 283–290.

    Google Scholar 

  • Yukimoto, S., Adachi, Y., Hosaka, M., Sakami, T., Yoshimura, H., Hirabara, M., & Kitoh, A. (2012). A new global climate model of the Meteorological Research Institute: MRI-CGCM3-model description and basic performance.Journal of the Meteorological Society of Japan,23–64.

  • Zhang, D., Luo, Z., Liu, S., Li, W., Wei, T., & Dong, H. (2016). Effects of deficit irrigation and plant density on the growth, yield and fiber quality of irrigated cotton. Field Crops Reseacrch, 197, 1–9.

  • Zhang, J., Zhang, H., Sima, M. W., Trout, T. J., Malone, R. W., & Wang, L. (2021). Simulated deficit irrigation and climate change effects on sunflower production in Eastern Colorado with CSM-CROPGRO-Sunflower in RZWQM2. Agricultural Water Management, 246, 106672.

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Funding

This study is supported by the grants from the Ministry of Science and Technology, China (QN2021046001L), National Natural Science Foundation of China (42171042), Tianshan Innovation Team (2020D14042) and the Tianshan Youth Project (2019Q086).

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Conceptualization (Zeeshan Ahmed and Dongwei Gui), original draft preparation (Zeeshan Ahmed and Sikandar Ali); review and editing (Xiaoping Chen and Zhiming Qi).

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Correspondence to Dongwei Gui.

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Ahmed, Z., Gui, D., Ali, S. et al. Evaluating Climate Change Impacts on Cotton Phenology and Yield Under Full and Deficit Irrigation Conditions in an Extremely Arid Oasis. Int. J. Plant Prod. 17, 49–63 (2023). https://doi.org/10.1007/s42106-022-00226-z

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