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.