Abstract
Global warming has accelerated surface water loss around the world. This study investigates in detail the change and attribution of potential evapotranspiration (PET) across China from 1901 to 2100 by the Hargreaves model, based on a 1-km temperature dataset downscaled from the low-spatial-resolution datasets using a Delta downscaling framework. Results showed that (1) relative to 1961–1990, PET increased by 0.62% in the historic period (1901–2017) and 6.43–12.89% for the future period (2018–2100), suggesting considerable future drying for China. Moreover, these increments had strong spatial variations and the largest increases were detected in high-elevation regions; (2) PET over entire China demonstrated a nonsignificant upward trend during the historic period and significant upward trends for the future period. For each period and GCM, significant upward PET trends occupied a much larger percent area than significant downward trends; (3) PET variations during the historic period were most sensitive to mean temperature (TMP), while in the future period it was more sensitive to maximum temperature (TMX), suggesting a change in the primary sensitivity factor due to global warming; (4) minimum temperature (TMN) made the largest contribution (45%) to PET variations during the historic period, while TMX had the largest contribution (36–40%) in the future period. Therefore, the primary contributing factor might transform from TMN to TMX under climate change; and (5) PET variations exhibited strong spatial heterogeneity, detected on fine geographic scales, due to the use of downscaled dataset. Overall, the results present a deep insight for planning coping strategies of global warming in China.
Highlights
Global warming has become an indisputable fact and has large long-term effects on water resources, plant growth, crop yields, and economic behavior (Naumann et al, 2018)
This study investigates in detail the change and attribution of potential evapotranspiration (PET) across China from 1901 to 2100 by the Hargreaves model, based on a 1-km temperature dataset downscaled from the low-spatial-resolution datasets using a Delta downscaling framework
Results showed that (1) relative to 1961–1990, PET increased by 0.62% in the historic period (1901–2017) and 6.43–12.89% for the future period (2018–2100), suggesting considerable future drying for China
Summary
Global warming has become an indisputable fact and has large long-term effects on water resources, plant growth, crop yields, and economic behavior (Naumann et al, 2018). Global temperatures are projected to continuously increase (IPCC, 2013), which will accelerate water loss from Earth’s surface (Aouissi et al, 2016). Numerous approaches have been employed to estimate PET, including Budyko (Budyko, 1974), Priestley–Taylor (Priestley and Taylor, 1972), Hargreaves (Hargreaves and Samani, 1985), and FAO Penman–Monteith (Allen et al, 1998) models. These models have been widely evaluated and employed to study PET variations around the world. The Hargreaves model is more suitable than the FAO Penman–Monteith model for use in a drier climate and for longer time periods (Hargreaves and Allen, 2003; Odusanya et al, 2019)
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