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Developing a water and nitrogen management model for greenhouse vegetable production in China: Sensitivity analysis and evaluation

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  • Liang, Hao
  • Hu, Kelin
  • Batchelor, William D.
  • Qin, Wei
  • Li, Baoguo

Abstract

Excessive water and fertilizer inputs have led to a series of environmental problems in vegetable production areas in China. Identifying the fates of water and nutrients is crucial to develop best management strategies in intensive vegetable production systems. The objectives of this study were to (i) develop a scientific water and nitrogen (N) management tool for intensive greenhouse vegetable production in China, and (ii) evaluate the model performance in the simulating the fate of water and N, and vegetable growth under different water and N management practices in China. A vegetable growth component was added to the field soil-crop system model WHCNS (soil Water Heat Carbon Nitrogen Simulator), named WHCNS_Veg. Parameters for the model were estimated and a sensitivity analysis was conducted by coupling the model with the model-independent parameter estimation program (PEST). Data used to test the model came from two years of cucumber and tomato experiments with various water and N combinations in Shandong province, China. The results of sensitivity analysis showed that the soil hydraulic parameters and vegetable genetic parameters had a relatively higher sensitivity compared with those of N transformation parameters. The saturated soil water content had the highest sensitivity among soil hydraulic parameters, and the total available accumulated temperature, crop coefficient and maximum root depth had higher sensitivity for both vegetable crops. Among the N transformation parameters, the parameters related to nitrification had the highest sensitivity. The automatic optimization algorithm performed well in adjusting soil hydraulic parameters, vegetable genetic parameters and N transformation parameters. The normalized root mean square error for soil water content, soil nitrate concentration, marketable fresh yield and vegetable N uptake were 5.7%, 28.0%, 2.7% and 8.3%, respectively, and indices of agreement were 0.727, 0.730, 0.997 and 0.832, respectively. The results indicated that the WHCNS_Veg model has great potential to simulate and analyze water and N fates, and vegetable growth for the intensive greenhouse vegetable production in China.

Suggested Citation

  • Liang, Hao & Hu, Kelin & Batchelor, William D. & Qin, Wei & Li, Baoguo, 2018. "Developing a water and nitrogen management model for greenhouse vegetable production in China: Sensitivity analysis and evaluation," Ecological Modelling, Elsevier, vol. 367(C), pages 24-33.
    • Handle: RePEc:eee:ecomod:v:367:y:2018:i:c:p:24-33
    DOI: 10.1016/j.ecolmodel.2017.10.016
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    References listed on IDEAS

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    2. Zhang, Hongyuan & Batchelor, William D. & Hu, Kelin & Liang, Hao & Han, Hui & Li, Ji, 2022. "Simulation of N2O emissions from greenhouse vegetable production under different management systems in North China," Ecological Modelling, Elsevier, vol. 470(C).
    3. Liang, Hao & Lv, Haofeng & Batchelor, William D. & Lian, Xiaojuan & Wang, Zhengxiang & Lin, Shan & Hu, Kelin, 2020. "Simulating nitrate and DON leaching to optimize water and N management practices for greenhouse vegetable production systems," Agricultural Water Management, Elsevier, vol. 241(C).
    4. Shi, Xinrui & Hu, Kelin & Batchelor, William D. & Liang, Hao & Wu, Yali & Wang, Qihui & Fu, Jin & Cui, Xiaoqing & Zhou, Feng, 2020. "Exploring optimal nitrogen management strategies to mitigate nitrogen losses from paddy soil in the middle reaches of the Yangtze River," Agricultural Water Management, Elsevier, vol. 228(C).
    5. Liang, Hao & Chen, Qing & Liang, Bin & Hu, Kelin, 2020. "Modeling the effects of long-term reduced N application on soil N losses and yield in a greenhouse tomato production system," Agricultural Systems, Elsevier, vol. 185(C).
    6. Wang, Rong & Sun, Zhaojun & Yang, Dongyan & Ma, Ling, 2022. "Simulating cucumber plant heights using optimized growth functions driven by water and accumulated temperature in a solar greenhouse," Agricultural Water Management, Elsevier, vol. 259(C).
    7. Shi, Xinrui & Batchelor, William D. & Liang, Hao & Li, Sien & Li, Baoguo & Hu, Kelin, 2020. "Determining optimal water and nitrogen management under different initial soil mineral nitrogen levels in northwest China based on a model approach," Agricultural Water Management, Elsevier, vol. 234(C).
    8. Chen, Fangzheng & Xu, Xinlei & Chen, Shaoqing & Wang, Zihan & Wang, Bin & Zhang, Yajie & Zhang, Chenxia & Feng, Puyu & Hu, Kelin, 2024. "Soil buffering capacity enhances maize yield resilience amidst climate perturbations," Agricultural Systems, Elsevier, vol. 215(C).
    9. Wu, You & Yan, Shicheng & Fan, Junliang & Zhang, Fucang & Zhao, Wenju & Zheng, Jing & Guo, Jinjin & Xiang, Youzhen & Wu, Lifeng, 2022. "Combined effects of irrigation level and fertilization practice on yield, economic benefit and water-nitrogen use efficiency of drip-irrigated greenhouse tomato," Agricultural Water Management, Elsevier, vol. 262(C).

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