| 摘要: |
| 湖冰是冰冻圈水文学的重要研究对象,湖冰的生消对气候变化极其敏感,可以作为气候变化的指示因子,并通过影响湖泊与大气之间物质能量交换,调节区域气候和湖泊生态系统。湖冰厚度是研究湖冰生消过程的关键变量,明晰其生消特征对于揭示气候变化下湖泊响应过程具有重要的理论价值和现实意义。本文基于2013—2017年及2022—2023年度原型测冰数据,利用ERA5-Land再分析数据作为大气强迫场,通过SIMSTRAT模型重建2003—2022年南湖完整冰厚生消过程并分析其变化特征。结果表明：1)SIMSTRAT模型模拟与原型观测得到的初冰日和终冰日平均偏差3.4 d,冰厚数据平均偏差1.29 cm,模拟结果与现场观测结果具有较高的一致性。2)2003—2022年南湖冰期平均持续122天,冰厚生长期、平衡期、融化期平均日数分别为66天、34天、21天。南湖冰期整体呈缩短趋势,缩短率为 4.27 d/10 a；其中,融化期年际变化幅度较大,缩短趋势为3.67 d/10 a。3)近20年,南湖年均冰厚介于14~30cm,2012—2017年冰厚年际波动剧烈,整体呈下降趋势。南湖冰厚在每年12月份与1月份以0.43 cm/d、0.55 cm/d的速率快速增加,3月份为0.74 cm/d的融化速率快速融化。4)SIMSTRAT模型进一步揭示出,南湖冰厚生消受气温、降雪、风速等气象因素综合影响。气温是影响冰厚生消特征的主要因素,累积气温降低会显著延长冰厚生长期和平衡期日数,同时增大当年最大冰厚；降水(雪)量和风速对冰厚生消特征亦存在不同程度影响。 |
| 关键词: 湖冰 物候 冰厚 SIMSTRAT模型 南湖 |
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| 基金项目:国家自然科学基金联合基金项目(U23A2012)；国家自然科学基金(52379014)；内蒙古自然科学基金重点项目(2022ZD08)；内蒙古自然科学基金青年基金项目(2023QN05026) |
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| Analysis of ice formation and melting characteristics in South Lake in recent 20 years based on SIMSTRAT |
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Zhu Yunyin1, Luo Hongchun1,2, Ji Honglan1,2, Xue Zhongshu3, Zhang Baosen4, Gao Wenlong
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1.College of Water Conservancy and Civil Engineering, Inner Mongolia Agricultural University;2.Collaborative Innovation Center for integrated management of water resources and water environment in Inner Mongolia of Yellow River Basin;3.College of Water Conservancy and Civil Engineering,Inner Mongolia Agricultural University;4.Yellow River Institute of Hydraulic Research
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| Abstract: |
| Lake ice is a crucial subject in cryospheric hydrology. Its sensitivity to climate change makes it a key indicator. Lake ice growth and melt, as a response to climate variations, influence material and energy exchange between lakes and the atmosphere, thereby regulating regional climate and lake ecosystems. The thickness of lake ice is a pivotal variable in studying its growth and melt processes. Understanding its characteristics is of significant theoretical and practical importance for unraveling lake responses to climate change. This study, based on prototype ice measurements from 2013–2017 and 2022–2023, employs ERA5-Land reanalysis data as atmospheric forcing in the SIMSTRAT model. The model reconstructs the complete lake ice growth-melt processes in South Lake from 2003 to 2022, analyzing their temporal changes. Results show a consistent simulation with prototype observations and reveal trends such as a shortened lake ice duration, particularly in the melt period. The lake ice thickness exhibits annual fluctuations, with notable decreases from 2012 to 2017. The SIMSTRAT model further elucidates the comprehensive impact of meteorological factors, including temperature, precipitation (snowfall), and wind speed, on lake ice thickness dynamics. Temperature stands out as the primary factor, with decreased cumulative temperature significantly extending the ice growth and balance periods, concurrently increasing the maximum ice thickness for the year. Precipitation (snowfall) and wind speed also exhibit varying degrees of influence on lake ice thickness dynamics. This research contributes to a deeper understanding of lake ice processes and their response to climate change, providing valuable insights for future studies in related fields. |
| Key words: Lake ice phenology Ice thickness SIMSTRAT South Lake |
