Most of the human appropriation of freshwater resources is for agriculture. Water availability is a major constraint to mankind’s ability to produce food. The notion of virtual water content (VWC), also known as crop water footprint, provides an effective tool to investigate the linkage between food and water resources as a function of climate, soil, and agricultural practices. The spatial variability in the virtual water content of crops is here explored, disentangling its dependency on climate and crop yields and assessing the sensitivity of VWC estimates to parameter variability and uncertainty. Here we calculate the virtual water content of four staple crops (i.e., wheat, rice, maize, and soybean) for the entire world developing a high-resolution (5 3 5 arc min) model, and we evaluate the VWC sensitivity to input parameters. We find that food production almost entirely depends on green water (>90%), but, when applied, irrigation makes crop production more water efficient, thus requiring less water. The spatial variability of the VWC is mostly controlled by the spatial patterns of crop yields with an average correlation coefficient of 0.83. The results of the sensitivity analysis show that wheat is most sensitive to the length of the growing period, rice to reference evapotranspiration, maize and soybean to the crop planting date. The VWC sensitivity varies not only among crops, but also across the harvested areas of the world, even at the subnational scale.
|Titolo:||Global sensitivity of high-resolution estimates of crop water footprint|
|Data di pubblicazione:||2015|
|Digital Object Identifier (DOI):||10.1002/2015WR017148|
|Appare nelle tipologie:||1.1 Articolo in rivista|
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|2015WRR - Tuninetti,etal - Global sensitivity of WF.pdf||Articolo versione editore||2. Post-print||PUBBLICO - Tutti i diritti riservati||Visibile a tuttiVisualizza/Apri|
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