Abstract

<strong class="journal-contentHeaderColor">Abstract.</strong> Snowmelt is a major fresh water resource, and quantifying snowmelt and its variability under climate change is necessary for the planning and management of water resources. Spatiotemporal changes in snow properties in China have drawn wide attention in recent decades; however, country-wide assessments of snowmelt are lacking. Using precipitation and temperature data with a high spatial resolution (0.5<span class="inline-formula"><sup>′</sup></span>; approximately 1 km), this study calculated the monthly snowmelt in China for the 1951–2017 period, using a simple temperature index model, and the model outputs were validated using snowfall, snow depth, snow cover extent and snow water equivalent. Precipitation and temperature scenarios developed from five CMIP5 models were used to predict future snowmelt in China under three different representative concentration pathway (RCP) scenarios (RCP2.6, RCP4.5 and RCP8.5). The results show that the mean annual snowmelt in China from 1951 to 2017 is <span class="inline-formula">2.41×10<sup>11</sup></span> <span class="inline-formula">m<sup>3</sup> yr<sup>−1</sup></span>. The mean annual snowmelt values in Northern Xinjiang, Northeast China and the Tibetan Plateau – China's three main stable snow cover regions – are <span class="inline-formula">0.18×10<sup>11</sup></span>, <span class="inline-formula">0.42×10<sup>11</sup></span> and <span class="inline-formula">1.15×10<sup>11</sup></span> <span class="inline-formula">m<sup>3</sup> yr<sup>−1</sup></span>, respectively. From 1951 to 2017, the snowmelt increased significantly in the Tibetan Plateau and decreased significantly in northern, central and southeastern China. In the whole of China, there was a decreasing trend in snowmelt, but this was not statistically significant. The mean annual snowmelt runoff ratios are generally more than 10 % in almost all third-level basins in West China, more than 5 % in third-level basins in North and Northeast China and less than 2 % in third-level basins in South China. From 1951 to 2017, the annual snowmelt runoff ratios decreased in most third-level basins in China. Under RCP2.6, RCP4.5 and RCP8.5, the projected snowmelt in China in the near future (2011–2040; mid-future –2041–2070; far future – 2071–2099) may decrease by 10.4 % (15.8 %; 13.9 %), 12.0 % (17.9 %; 21.1 %) and 11.7 % (24.8 %; 36.5 %) compared to the reference period (1981–2010), respectively. Most of the projected mean annual snowmelt runoff ratios in third-level basins in different future periods are lower than those in the reference period. Low temperature regions can tolerate more warming, and the snowmelt change in these regions is mainly influenced by precipitation; however, the snowmelt change in warm regions is more sensitive to temperature increases. The spatial variability in snowmelt changes may lead to regional differences in the impact of snowmelt on water supply.

Highlights

  • Snow properties have changed significantly under the ongoing warming of the global climate, and variations in snow cover exert strong feedbacks on the climate system due to its high albedo and low thermal conductivity as well as the high latent 35 heat of phase change (Zhang and Ma, 2018; Pulliainen et al, 2020; Vano, 2020; You et al, 2020)

  • Among China’s three main stable snow cover regions, the most accurate snowfall simulation was obtained for Northeast China, followed by North Xinjiang and the Tibetan Plateau

  • In basins in North and Northeast China, the snowmelt runoff ratio was generally more than 5%, whereas in basins in South China it was less than 2%

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Summary

Introduction

Snow properties have changed significantly under the ongoing warming of the global climate, and variations in snow cover exert strong feedbacks on the climate system due to its high albedo and low thermal conductivity as well as the high latent 35 heat of phase change (Zhang and Ma, 2018; Pulliainen et al, 2020; Vano, 2020; You et al, 2020). Climate warming has resulted in smaller snowfall/precipitation ratios, earlier snowmelt times and slower snowmelt rates 40 (Berghuijs et al, 2014; Musselman et al, 2017; Barnhart et al, 2020). This has changed seasonal runoff distributions, but has affected the total annual runoff (Bloschl et al, 2019; Jenicek and Ledvinka, 2020). Many studies have shown that due to the mathematical complexities and massive data requirements of physically based models, they do not 50 necessarily perform better than temperature index models (Hock, 2003; Jost et al, 2012; Skaugen et al, 2018; Lopez et al, 2020). Snow melting is aslo an important hydrological process in the Tibetan Plateau, which is the source

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