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1000 Titel
  • A gridded dataset of consumptive water footprints, evaporation, transpiration, and associated benchmarks related to crop production in China during 2000–2018
1000 Autor/in
  1. Wang, Wei |
  2. Zhuo, La |
  3. Ji, Xiangxiang |
  4. Yue, Zhiwei |
  5. Li, Zhibin |
  6. Li, Meng |
  7. Zhang, Huimin |
  8. Gao, Rong |
  9. Yan, Chenjian |
  10. Zhang, Ping |
  11. Wu, Pute |
1000 Verlag
  • Copernicus Publications
1000 Erscheinungsjahr 2023
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2023-10-31
1000 Erschienen in
1000 Quellenangabe
  • 15(11):4803-4827
1000 Copyrightjahr
  • 2023
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.5194/essd-15-4803-2023 |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • <jats:p>Abstract. Evapotranspiration over crop growth period, also referred to as the consumptive water footprint of crop production (WFCP), is an essential component of the hydrological cycle. However, the existing high-resolution consumptive WFCP datasets do not distinguish between soil evaporation and crop transpiration and disregard the impacts of different irrigation practices. This restricts the practical implementation of existing WFCP datasets for precise crop water productivity assessments, agricultural water-saving evaluations, the development of sustainable irrigation techniques, cropping structure optimization, and crop-related interregional virtual water trade analysis. This study establishes a 5-arcmin gridded dataset of monthly green and blue WFCP, evaporation, transpiration, and associated unit WFCP benchmarks for 21 crops grown in China during 2000–2018. The data simulation was based on calibrated AquaCrop modelling under furrow-, sprinkler-, and micro-irrigated as well as rainfed conditions. Data quality was validated by comparing the current results with multiple public datasets and remote sensing products. The improved gridded WFCP dataset is available at https://doi.org/10.5281/zenodo.7756013 (Wang et al., 2023) and effectively compensated for the gaps in the existing datasets through (i) revealing the intensity, structure, and spatiotemporal evolution of both productive and non-productive blue and green water consumption on a monthly scale, and (ii) including crop-by-crop unit WFCP benchmarks according to climatic zones. </jats:p>
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  1. Chinese Universities Scientific Fund |
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    1000 Förderer Chinese Universities Scientific Fund |
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1000 Erstellt am 2024-05-21T14:11:24.331+0200
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1000 Zuletzt bearbeitet 2024-05-22T10:23:46.481+0200
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