Abstract
Abstract. Human water withdrawal has increasingly altered the global water cycle in past decades, yet our understanding of its driving forces and patterns is limited. Reported historical estimates of sectoral water withdrawals are often sparse and incomplete, mainly restricted to water withdrawal estimates available at annual and country scales, due to a lack of observations at seasonal and local scales. In this study, through collecting and consolidating various sources of reported data and developing spatial and temporal statistical downscaling algorithms, we reconstruct a global monthly gridded (0.5∘) sectoral water withdrawal dataset for the period 1971–2010, which distinguishes six water use sectors, i.e., irrigation, domestic, electricity generation (cooling of thermal power plants), livestock, mining, and manufacturing. Based on the reconstructed dataset, the spatial and temporal patterns of historical water withdrawal are analyzed. Results show that total global water withdrawal has increased significantly during 1971–2010, mainly driven by the increase in irrigation water withdrawal. Regions with high water withdrawal are those densely populated or with large irrigated cropland production, e.g., the United States (US), eastern China, India, and Europe. Seasonally, irrigation water withdrawal in summer for the major crops contributes a large percentage of total annual irrigation water withdrawal in mid- and high-latitude regions, and the dominant season of irrigation water withdrawal is also different across regions. Domestic water withdrawal is mostly characterized by a summer peak, while water withdrawal for electricity generation has a winter peak in high-latitude regions and a summer peak in low-latitude regions. Despite the overall increasing trend, irrigation in the western US and domestic water withdrawal in western Europe exhibit a decreasing trend. Our results highlight the distinct spatial pattern of human water use by sectors at the seasonal and annual timescales. The reconstructed gridded water withdrawal dataset is open access, and can be used for examining issues related to water withdrawals at fine spatial, temporal, and sectoral scales.
Highlights
With the rapid growth in population and income and the demand for energy, food, and livestock feed, global freshwater withdrawal increased from ∼ 2500 km3 yr−1 in 1970 to ∼ 4000 km3 yr−1 in 2010 (Shiklomanov, 2000; Döll et al, 2009; Wada and Bierkens, 2014)
Characterizing the impact of human water use on the hydrological cycle would entail a comprehensive assessment of the water life cycle from source to end use sectors, to changes to its quality, to its eventual return to the environment or consumption (Wada et al, 2014), we focus in this study on water withdrawal
The spatial and temporal downscaling is applied to Food and Agriculture Organization (FAO) AQUASTA and US Geological Survey (USGS) estimates independently to get the monthly gridded dataset following three steps: firstly the individual sectoral water withdrawal is downscaled from country level to grid level (0.5◦ × 0.5◦) by using spatial downscaling algorithms, annual time series of sector water withdrawal is obtained by using linear interpolation between the 5-year interval from reports, and a temporal downscaling procedure is adopted to generate monthly gridded water withdrawal data by sector
Summary
With the rapid growth in population and income and the demand for energy, food, and livestock feed, global freshwater withdrawal increased from ∼ 2500 km yr−1 in 1970 to ∼ 4000 km yr−1 in 2010 (Shiklomanov, 2000; Döll et al, 2009; Wada and Bierkens, 2014). Such large-scale human water withdrawals have significant impacts on the water cycle, the associated ecosystems, and society. Characterizing the impact of human water use on the hydrological cycle would entail a comprehensive assessment of the water life cycle from source (surface vs. groundwater) to end use sectors (irrigation, industrial, domestic), to changes to its quality (waste water), to its eventual return to the environment (return flow) or consumption (consumptive use) (Wada et al, 2014), we focus in this study on water withdrawal
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