Spatial-temporal assessment of agricultural virtual water and uncertainty analysis: The case of Kazakhstan (2000–2016)

Abstract

In this study, a fuzzy-vertex-based virtual-water analysis method (FVAM) is developed for assessing the virtual water content (VWC) of main agricultural products, imports, and exports at a national scale. FVAM has advantages in quantifying state-level VWC with a bottom-up approach and reflecting uncertain parameters based on vertex analysis technique. FVAM is applied to a real case of Kazakhstan in Central Asia. Results reveal that (i) the VWC of Kazakhstan's agricultural products is between 55.61 and 83.98 billion m3/yr in 2000–2016, where wheat is the largest water consumer and the Kostanay state has the largest VWC; (ii) Kazakhstan is a net exporter of virtual water, most of which flows to neighboring countries such as Russia and Azerbaijan; (iii) uncertainties in crop coefficient (Kc), feed water requirement (FWR), drinking water requirement (DWR) and service water requirement (SWR) can affect the VWC assessment; (iv) the massive export of water-intensive products makes the water resources more severe in Kazakhstan, which further squeezes the local ecological water use. Therefore, reducing the export of virtual water should be the focus of future agricultural policies. The findings are useful for decision makers to optimize Kazakhstan's agricultural structure, mitigate the national water scarcity, and facilitate the regional sustainable development.