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Spatial and temporal sensitivity of water footprint assessment in crop production to modelling inputs and parameters

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  • Li, Zhibin
  • Feng, Bianbian
  • Wang, Wei
  • Yang, Xi
  • Wu, Pute
  • Zhuo, La

Abstract

Owing to increasingly limited water resources, evaluating large-scale regional crop water footprints (WFs) within acceptable errors is the basis for efficiency and productivity improvements for sustainable agriculture. However, quantitative sensitivity analysis of outputs to inputs and parameters of advanced and widely used crop WF accounting models are still lacking. In this study, we evaluated the spatial and temporal sensitivity of the blue and green WFs of crops to key input variables based on year-by-year simulations for wheat, rice, maize, and soybean production in China from 2010 to 2019. We employed one of the most widely used AquaCrop models to test different water supply and irrigation scenarios. Nine input variables or model parameters were selected, including reference evapotranspiration (ETo), crop transpiration coefficient (KcTr), soil evaporation coefficient (KE), maximum canopy cover (MCC), precipitation (PR), canopy decline coefficient (CDC), planting density of the crop (DC), reference harvest index (HI0), and normalised water productivity (WP*). The results showed that crop WFs are generally more sensitive to ETo among the input variables and KcTr and KE among the model parameters. We also found that the blue WF was more sensitive than the green WF. In most cases, WFs in rainfed scenarios were more sensitive to changes in input variables compared to WFs of irrigated crops. Of the four studied crops, the WFs of maize and wheat were more sensitive than the WFs of rice and soybean. Wheat, maize, and soybean also showed a visible spatial variation in the sensitivity of the WF to each input variable. Overall, the WF sensitivity was influenced by crop type, water supply, irrigation method, and regional climate features. The current analysis provides a feasible approach to comprehensively identify the key inputs and parameters to be calibrated for accurate crop WF accounting.

Suggested Citation

  • Li, Zhibin & Feng, Bianbian & Wang, Wei & Yang, Xi & Wu, Pute & Zhuo, La, 2022. "Spatial and temporal sensitivity of water footprint assessment in crop production to modelling inputs and parameters," Agricultural Water Management, Elsevier, vol. 271(C).
    • Handle: RePEc:eee:agiwat:v:271:y:2022:i:c:s0378377422003523
    DOI: 10.1016/j.agwat.2022.107805
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    References listed on IDEAS

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    1. Arjen Y. Hoekstra, 2017. "Water Footprint Assessment: Evolvement of a New Research Field," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(10), pages 3061-3081, August.
    2. Jonas Jägermeyr & Amandine Pastor & Hester Biemans & Dieter Gerten, 2017. "Reconciling irrigated food production with environmental flows for Sustainable Development Goals implementation," Nature Communications, Nature, vol. 8(1), pages 1-9, August.
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    Cited by:

    1. Qi Liu & Aidi Huo & Yanran Liu & Ping Zhang & Zhixin Zhao & Xuantao Zhao, 2024. "Evolution Analysis of the Ecological Footprint and the Ecological Carrying Capacity of Water Resources at Different Spatial and Temporal Scales: A Case Study of Gansu Province," Sustainability, MDPI, vol. 16(24), pages 1-15, December.
    2. Duan, Yiduo & Wang, Wei & Zhuo, La & Liu, Yilin & Wu, Pute, 2024. "Regional blue and green water-saving potential and regulation paths for crop production: A case study in the Yellow River Basin," Agricultural Water Management, Elsevier, vol. 291(C).
    3. Rodríguez, Paula Olivera & Holzman, Mauro Ezequiel & Aldaya, Maite M. & Rivas, Raúl Eduardo, 2024. "Water footprint in rainfed summer and winter crops: The role of soil moisture," Agricultural Water Management, Elsevier, vol. 296(C).
    4. Wang, Zhaoyang & Shi, Yinfang & Hou, Cheng & Zhang, Puhan, 2024. "Sensitivity analysis of simulated Lycium barbarum L. yield in the WOFOST model under different climate conditions," Ecological Modelling, Elsevier, vol. 488(C).

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