IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v12y2022i10p1589-d931316.html
   My bibliography  Save this article

Analysis of Soil Moisture, Temperature, and Salinity in Cotton Field under Non-Mulched Drip Irrigation in South Xinjiang

Author

Listed:
  • Hongbo Wang

    (College of Water Resource and Architecture Engineering, Tarim University, Alaer 843300, China
    Key Laboratory of Modern Agricultural Engineering, Tarim University, Alar 843300, China)

  • Hui Cao

    (College of Water Resource and Architecture Engineering, Tarim University, Alaer 843300, China)

  • Fuchang Jiang

    (College of Water Resource and Architecture Engineering, Tarim University, Alaer 843300, China)

  • Xingpeng Wang

    (College of Water Resource and Architecture Engineering, Tarim University, Alaer 843300, China
    Key Laboratory of Modern Agricultural Engineering, Tarim University, Alar 843300, China
    Key Laboratory of Northwest Oasis Water-Saving Agriculture, Ministry of Agriculture and Rural Affairs, Shihezi 832000, China)

  • Yang Gao

    (Institute of Farmland Irrigation, Chinese Academy of Agricultural Sciences, Xinxiang 453002, China)

Abstract

The mulch film residues in cotton fields in south Xinjiang have caused serious harm to the soil environment and ecological security in the oasis areas. Non-mulched planting provides an alternative approach to this problem. In this experiment, irrigation was provided on the basis of the reference crop evapotranspiration ( ET 0 ). Two layouts of drip tapes (1T4R—one tape for four rows; 2T4R—two tapes for four rows) were applied to the non-mulched, drip-irrigated cotton fields in south Xinjiang, and their impacts on soil water–heat–salt dynamic changes and the water consumption and yield of cotton were compared and analyzed. The experiment shows that the 2T4R layout provided an excellent soil water–salt environment for cotton growth and yield formation. Soil temperature decreased by 0.8 °C and drip irrigation belt input increased by CNY1200·hm −2 . However, a higher profit derived from the 2T4R layout could compensate for the increased expenditure. The results show that cotton cultivation using non-mulched drip irrigation instead of mulched drip irrigation can potentially alleviate soil environmental and ecological security problems caused by plastic mulch residues in oasis areas. Although cotton yield was reduced by about 15%, water and nitrogen strategies and other field management could be adjusted to compensate for the disadvantages.

Suggested Citation

  • Hongbo Wang & Hui Cao & Fuchang Jiang & Xingpeng Wang & Yang Gao, 2022. "Analysis of Soil Moisture, Temperature, and Salinity in Cotton Field under Non-Mulched Drip Irrigation in South Xinjiang," Agriculture, MDPI, vol. 12(10), pages 1-15, October.
    • Handle: RePEc:gam:jagris:v:12:y:2022:i:10:p:1589-:d:931316
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/12/10/1589/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2077-0472/12/10/1589/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wang, Xingpeng & Wang, Hongbo & Si, Zhuanyun & Gao, Yang & Duan, Aiwang, 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, Elsevier, vol. 241(C).
    2. Che, Zheng & Wang, Jun & Li, Jiusheng, 2021. "Effects of water quality, irrigation amount and nitrogen applied on soil salinity and cotton production under mulched drip irrigation in arid Northwest China," Agricultural Water Management, Elsevier, vol. 247(C).
    3. Lo, Tsz Him & Rudnick, Daran R. & Singh, Jasreman & Nakabuye, Hope Njuki & Katimbo, Abia & Heeren, Derek M. & Ge, Yufeng, 2020. "Field assessment of interreplicate variability from eight electromagnetic soil moisture sensors," Agricultural Water Management, Elsevier, vol. 231(C).
    4. Fontanet, Mireia & Scudiero, Elia & Skaggs, Todd H. & Fernàndez-Garcia, Daniel & Ferrer, Francesc & Rodrigo, Gema & Bellvert, Joaquim, 2020. "Dynamic Management Zones for Irrigation Scheduling," Agricultural Water Management, Elsevier, vol. 238(C).
    5. Desheng Wang & Chengkun Wang & Lichao Xu & Tiecheng Bai & Guozheng Yang, 2022. "Simulating Growth and Evaluating the Regional Adaptability of Cotton Fields with Non-Film Mulching in Xinjiang," Agriculture, MDPI, vol. 12(7), pages 1-20, June.
    6. Hui Cao & Hongbo Wang & Yong Li & Abdoul Kader Mounkaila Hamani & Nan Zhang & Xingpeng Wang & Yang Gao, 2021. "Evapotranspiration Partition and Dual Crop Coefficients in Apple Orchard with Dwarf Stocks and Dense Planting in Arid Region, Aksu Oasis, Southern Xinjiang," Agriculture, MDPI, vol. 11(11), pages 1-16, November.
    7. Yang, Pengju & Hu, Hongchang & Tian, Fuqiang & Zhang, Zhi & Dai, Chao, 2016. "Crop coefficient for cotton under plastic mulch and drip irrigation based on eddy covariance observation in an arid area of northwestern China," Agricultural Water Management, Elsevier, vol. 171(C), pages 21-30.
    8. Sandhu, Rupinder & Irmak, Suat, 2019. "Assessment of AquaCrop model in simulating maize canopy cover, soil-water, evapotranspiration, yield, and water productivity for different planting dates and densities under irrigated and rainfed cond," Agricultural Water Management, Elsevier, vol. 224(C), pages 1-1.
    9. Tan, Shuai & Wang, Quanjiu & Zhang, Jihong & Chen, Yong & Shan, Yuyang & Xu, Di, 2018. "Performance of AquaCrop model for cotton growth simulation under film-mulched drip irrigation in southern Xinjiang, China," Agricultural Water Management, Elsevier, vol. 196(C), pages 99-113.
    10. Yin, Minhua & Li, Yuannong & Fang, Heng & Chen, Pengpeng, 2019. "Biodegradable mulching film with an optimum degradation rate improves soil environment and enhances maize growth," Agricultural Water Management, Elsevier, vol. 216(C), pages 127-137.
    11. Cheng, Minghui & Wang, Haidong & Fan, Junliang & Xiang, Youzhen & Liu, Xiaoqiang & Liao, Zhenqi & Abdelghany, Ahmed Elsayed & Zhang, Fucang & Li, Zhijun, 2022. "Evaluation of AquaCrop model for greenhouse cherry tomato with plastic film mulch under various water and nitrogen supplies," Agricultural Water Management, Elsevier, vol. 274(C).
    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. Yunfeng Li & Quanqing Feng & Dongwei Li & Mingfa Li & Huifeng Ning & Qisheng Han & Abdoul Kader Mounkaila Hamani & Yang Gao & Jingsheng Sun, 2022. "Water-Salt Thresholds of Cotton ( Gossypium hirsutum L.) under Film Drip Irrigation in Arid Saline-Alkali Area," Agriculture, MDPI, vol. 12(11), pages 1-21, October.
    2. Che, Zheng & Wang, Jun & Li, Jiusheng, 2021. "Effects of water quality, irrigation amount and nitrogen applied on soil salinity and cotton production under mulched drip irrigation in arid Northwest China," Agricultural Water Management, Elsevier, vol. 247(C).
    3. Feng, Dingrui & Li, Guangyong & Wang, Dan & Wulazibieke, Mierguli & Cai, Mingkun & Kang, Jing & Yuan, Zicheng & Xu, Houcheng, 2022. "Evaluation of AquaCrop model performance under mulched drip irrigation for maize in Northeast China," Agricultural Water Management, Elsevier, vol. 261(C).
    4. Li, Meng & Du, Yingji & Zhang, Fucang & Bai, Yungang & Fan, Junliang & Zhang, Jianghui & Chen, Shaoming, 2019. "Simulation of cotton growth and soil water content under film-mulched drip irrigation using modified CSM-CROPGRO-cotton model," Agricultural Water Management, Elsevier, vol. 218(C), pages 124-138.
    5. Ma, Chao & Wang, Jun & Li, Jiusheng, 2023. "Utilization of soil and fertilizer nitrogen supply under mulched drip irrigation with various water qualities in arid regions," Agricultural Water Management, Elsevier, vol. 280(C).
    6. Cheng, Minghui & Wang, Haidong & Fan, Junliang & Xiang, Youzhen & Liu, Xiaoqiang & Liao, Zhenqi & Abdelghany, Ahmed Elsayed & Zhang, Fucang & Li, Zhijun, 2022. "Evaluation of AquaCrop model for greenhouse cherry tomato with plastic film mulch under various water and nitrogen supplies," Agricultural Water Management, Elsevier, vol. 274(C).
    7. Keikha, Mahdi & Darzi- Naftchali, Abdullah & Motevali, Ali & Valipour, Mohammad, 2023. "Effect of nitrogen management on the environmental and economic sustainability of wheat production in different climates," Agricultural Water Management, Elsevier, vol. 276(C).
    8. 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).
    9. Alex Zizinga & Jackson Gilbert Majaliwa Mwanjalolo & Britta Tietjen & Bobe Bedadi & Ramon Amaro de Sales & Dennis Beesigamukama, 2022. "Simulating Maize Productivity under Selected Climate Smart Agriculture Practices Using AquaCrop Model in a Sub-humid Environment," Sustainability, MDPI, vol. 14(4), pages 1-17, February.
    10. Tsakmakis, I.D. & Gikas, G.D. & Sylaios, G.K., 2021. "Integration of Sentinel-derived NDVI to reduce uncertainties in the operational field monitoring of maize," Agricultural Water Management, Elsevier, vol. 255(C).
    11. Dzikiti, S. & Lotter, D. & Mpandeli, S. & Nhamo, L., 2022. "Assessing the energy and water balance dynamics of rain-fed rooibos tea crops (Aspalathus linearis) under changing Mediterranean climatic conditions," Agricultural Water Management, Elsevier, vol. 274(C).
    12. Lu, Yang & Chibarabada, Tendai P. & Ziliani, Matteo G. & Onema, Jean-Marie Kileshye & McCabe, Matthew F. & Sheffield, Justin, 2021. "Assimilation of soil moisture and canopy cover data improves maize simulation using an under-calibrated crop model," Agricultural Water Management, Elsevier, vol. 252(C).
    13. Wang, Tianyu & Wang, Zhenhua & Zhang, Jinzhu & Ma, Kai, 2023. "Application effect of different oxygenation methods with mulched drip irrigation system in Xinjiang," Agricultural Water Management, Elsevier, vol. 275(C).
    14. Zhou, Beibei & Liang, Chaofan & Chen, Xiaopeng & Ye, Sitan & Peng, Yao & Yang, Lu & Duan, Manli & Wang, Xingpeng, 2022. "Magnetically-treated brackish water affects soil water-salt distribution and the growth of cotton with film mulch drip irrigation in Xinjiang, China," Agricultural Water Management, Elsevier, vol. 263(C).
    15. Yan, Fulai & Zhang, Fucang & Fan, Xingke & Fan, Junliang & Wang, Ying & Zou, Haiyang & Wang, Haidong & Li, Guodong, 2021. "Determining irrigation amount and fertilization rate to simultaneously optimize grain yield, grain nitrogen accumulation and economic benefit of drip-fertigated spring maize in northwest China," Agricultural Water Management, Elsevier, vol. 243(C).
    16. Zhang, Ting & Zuo, Qiang & Ma, Ning & Shi, Jianchu & Fan, Yuchuan & Wu, Xun & Wang, Lichun & Xue, Xuzhang & Ben-Gal, Alon, 2023. "Optimizing relative root-zone water depletion thresholds to maximize yield and water productivity of winter wheat using AquaCrop," Agricultural Water Management, Elsevier, vol. 286(C).
    17. Jamei, Mehdi & Maroufpoor, Saman & Aminpour, Younes & Karbasi, Masoud & Malik, Anurag & Karimi, Bakhtiar, 2022. "Developing hybrid data-intelligent method using Boruta-random forest optimizer for simulation of nitrate distribution pattern," Agricultural Water Management, Elsevier, vol. 270(C).
    18. Songjun Han & Di Xu & Zhiyong Yang, 2017. "Irrigation-Induced Changes in Evapotranspiration Demand of Awati Irrigation District, Northwest China: Weakening the Effects of Water Saving?," Sustainability, MDPI, vol. 9(9), pages 1-12, August.
    19. Yu, Qihua & Kang, Shaozhong & Zhang, Lu & Hu, Shunjun & Li, Yunfeng & Parsons, David, 2023. "Incorporating new functions into the WAVES model, to better simulate cotton production under film mulching and severe salinity," Agricultural Water Management, Elsevier, vol. 288(C).
    20. Umesh, Barikara & Reddy, K.S. & Polisgowdar, B.S. & Maruthi, V. & Satishkumar, U. & Ayyanagoudar, M.S. & Rao, Sathyanarayan & Veeresh, H., 2022. "Assessment of climate change impact on maize (Zea mays L.) through aquacrop model in semi-arid alfisol of southern Telangana," Agricultural Water Management, Elsevier, vol. 274(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:gam:jagris:v:12:y:2022:i:10:p:1589-:d:931316. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.