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Determining threshold values for root-soil water weighted plant water deficit index based smart irrigation

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  • Shi, Jianchu
  • Wu, Xun
  • Wang, Xiaoyu
  • Zhang, Mo
  • Han, Le
  • Zhang, Wenjing
  • Liu, Wen
  • Zuo, Qiang
  • Wu, Xiaoguang
  • Zhang, Hongfei
  • Ben-Gal, Alon

Abstract

Plant water deficit index (PWDI) represents the extent of water stress by relating soil moisture to the ability of a plant to take up water including consideration of the relative distribution of soil water to roots. However, for a smart irrigation decision support system, we are challenged in determining reliable thresholds of PWDI to initiate irrigation events to achieve predetermined yield and/or water use efficiency (WUE) targets. Taking drip irrigated maize and sprinkler irrigated alfalfa as examples, field experiments were conducted to investigate the choice and effects of PWDI thresholds. The results indicated that, with increasing PWDI thresholds, irrigation times and quantity of water, as well as crop transpiration, growth, and yield, were all significantly limited while WUE was enhanced except under extremely stressed conditions. To disconnect the unpredictable effects of other factors, yield and WUE were normalized to their corresponding potential values. Within the experimentally determined range of PWDI, relative yield and WUE were described with linear functions for maize, and linear and quadratic functions for alfalfa, allowing identification of the most efficient threshold value according to the objective parameter of choice. The method described can be adopted in smart irrigation decision support systems with consideration of spatial variability and after further verification and improvement under more complicated situations with various crop types and varieties, environmental conditions, cultivation modes, and wider or dynamic PWDI thresholds allowing regulated deficit irrigation.

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  • Shi, Jianchu & Wu, Xun & Wang, Xiaoyu & Zhang, Mo & Han, Le & Zhang, Wenjing & Liu, Wen & Zuo, Qiang & Wu, Xiaoguang & Zhang, Hongfei & Ben-Gal, Alon, 2020. "Determining threshold values for root-soil water weighted plant water deficit index based smart irrigation," Agricultural Water Management, Elsevier, vol. 230(C).
    • Handle: RePEc:eee:agiwat:v:230:y:2020:i:c:s0378377419320633
    DOI: 10.1016/j.agwat.2019.105979
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    1. Davis, S.L. & Dukes, M.D., 2010. "Irrigation scheduling performance by evapotranspiration-based controllers," Agricultural Water Management, Elsevier, vol. 98(1), pages 19-28, December.
    2. Wang, Feng-Xin & Kang, Yaohu & Liu, Shi-Ping, 2006. "Effects of drip irrigation frequency on soil wetting pattern and potato growth in North China Plain," Agricultural Water Management, Elsevier, vol. 79(3), pages 248-264, February.
    3. Candogan, Burak Nazmi & Sincik, Mehmet & Buyukcangaz, Hakan & Demirtas, Cigdem & Goksoy, Abdurrahim Tanju & Yazgan, Senih, 2013. "Yield, quality and crop water stress index relationships for deficit-irrigated soybean [Glycine max (L.) Merr.] in sub-humid climatic conditions," Agricultural Water Management, Elsevier, vol. 118(C), pages 113-121.
    4. Jalota, S.K. & Singh, Sukhvinder & Chahal, G.B.S. & Ray, S.S. & Panigraghy, S. & Bhupinder-Singh & Singh, K.B., 2010. "Soil texture, climate and management effects on plant growth, grain yield and water use by rainfed maize-wheat cropping system: Field and simulation study," Agricultural Water Management, Elsevier, vol. 97(1), pages 83-90, January.
    5. Wu, Xun & Zhang, Wenjing & Liu, Wen & Zuo, Qiang & Shi, Jianchu & Yan, Xudong & Zhang, Hongfei & Xue, Xuzhang & Wang, Lichun & Zhang, Mo & Ben-Gal, Alon, 2017. "Root-weighted soil water status for plant water deficit index based irrigation scheduling," Agricultural Water Management, Elsevier, vol. 189(C), pages 137-147.
    6. Kang, Shaozhong & Zhang, Lu & Liang, Yinli & Hu, Xiaotao & Cai, Huanjie & Gu, Binjie, 2002. "Effects of limited irrigation on yield and water use efficiency of winter wheat in the Loess Plateau of China," Agricultural Water Management, Elsevier, vol. 55(3), pages 203-216, June.
    7. English, Marshall & Raja, Syed Navaid, 1996. "Perspectives on deficit irrigation," Agricultural Water Management, Elsevier, vol. 32(1), pages 1-14, November.
    8. Emekli, Yasar & Bastug, Ruhi & Buyuktas, Dursun & Emekli, Nefise Yasemin, 2007. "Evaluation of a crop water stress index for irrigation scheduling of bermudagrass," Agricultural Water Management, Elsevier, vol. 90(3), pages 205-212, June.
    9. Rodriguez-Ortega, W.M. & Martinez, V. & Rivero, R.M. & Camara-Zapata, J.M. & Mestre, T. & Garcia-Sanchez, F., 2017. "Use of a smart irrigation system to study the effects of irrigation management on the agronomic and physiological responses of tomato plants grown under different temperatures regimes," Agricultural Water Management, Elsevier, vol. 183(C), pages 158-168.
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