| 引用本文: | 朱云印,罗红春,冀鸿兰,薛中姝,张宝森,高文龙.基于SIMSTRAT的近20年内蒙古南湖冰厚生消特征分析.湖泊科学,2025,37(1):304-317. DOI:10.18307/2025.0152 |
| Zhu Yunyin,Luo Hongchun,Ji Honglan,Xue Zhongshu,Zhang Baosen,Gao Wenlong.Ice thickness formation and melting characteristics of Lake Nanhu in Inner Mongolia based on the process-based model of SIMSTRAT. J. Lake Sci.2025,37(1):304-317. DOI:10.18307/2025.0152 |
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| 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的物质能量交换，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。本文以内蒙古南湖湖冰为研究对象，基于2013—2017年和2022—2023年原型测冰数据，利用ERA5-Land再分析数据作为大气强迫场，通过SIMSTRAT湖泊过程模型重建2003—2022年内蒙古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为3.40 d，冰厚数据平均偏差为1.29 cm，平均绝对误差为1.29 cm，均方根误差为1.90 cm。模拟结果与现场观测结果具有较高的一致性。2）2003—2022年南湖封冻期平均持续119 d，冰厚生长期、平衡期、融化期平均日数分别为64、34、21 d。南湖封冻期整体呈缩短趋势，缩短率为4.27 d/10 a；其中，融化期年际变化幅度较大，缩短率为3.67 d/10 a。3）近20年，南湖年均冰厚介于14~30 cm之间，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月与1月以0.43和0.55 cm/d的速率快速增加，3月以0.74 cm/d的融化速率快速融化。4）SIMSTRAT模型揭示了南湖冰厚生消受气温、降水、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；降水量和风速对冰厚生消特征也存在不同程度影响。 |
| 关键词: 湖冰 物候 冰厚 SIMSTRAT模型 内蒙古南湖 |
| DOI：10.18307/2025.0152 |
| 分类号: |
| 基金项目:国家自然科学基金联合基金项目(U23A2012)；国家自然科学基金项目(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)联合资助 |
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| Ice thickness formation and melting characteristics of Lake Nanhu in Inner Mongolia based on the process-based model of SIMSTRAT |
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Zhu Yunyin1，Luo Hongchun1，2，Ji Honglan1，2，Xue Zhongshu1，Zhang Baosen3，Gao Wenlong4
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1.College of Water Conservancy and Civil Engineering, Inner Mongolia Agricultural University, Hohhot 010018 , P.R.China ；2.Collaborative Innovation Center for Integrated Management of Water Resources and Water Environment in Inner Mongolia of Yellow River Basin, Hohhot 010018 , P.R.China ；3.Yellow River Institute of Hydraulic Research, Yellow River Conservancy Commission, Zhengzhou 450000 , P.R.China ；4.Hohhot Togtoh Toudaoguai Hydrological Station of Inner Mongolia, Hohhot 010018 , P.R.China
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| Abstract: |
| Lake ice is a crucial subject in cryospheric hydrology, and can be a key indicator to represent climate change due to its sensitivity to climate change. 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 critical 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. In this study, the ice in Lake Nanhu, Inner Mongolia was taken as the study area. Based on the prototype ice measurement data from 2013-2017 and 2022-2023, the ERA5-Land reanalysis data were used as the atmospheric forcing field. The process-based model of SIMSTRAT was used to reconstruct the growth-melt process in Lake Nanhu from 2003 to 2022, and to investigate its change characteristics. The results showed that: 1) The SIMSTRAT model showed a high level of agreement with prototype observations. The mean deviation of the simulated first ice day and final ice day was 3.4 days, while the mean bias for ice thickness was 1.29 cm. The mean absolute error and root mean square error of the ice thickness were 1.29 cm and 1.90 cm, respectively. 2) From 2003 to 2022, the average freezing period of Lake Nanhu lasted 119 days, with the ice growth, balance, and melting periods averaging 64, 34 and 21 days, respectively. The freezing period exhibited an overall shortening trend at a rate of 4.27 days per decade. Among these, the melting period showed the largest interannual variability, with a shortening rate of 3.67 days per decade. 3) Over the past 20 years, the annual average ice thickness of Lake Nanhu ranged from 14 to 30 cm. From 2012 to 2017, interannual fluctuations in ice thickness were pronounced, showing an overall declining trend. Ice thickness increased rapidly during December and January at rates of 0.43 cm/d and 0.55 cm/d respectively, and melted quickly in March at a rate of 0.74 cm/d. 4) The SIMSTRAT model further elucidated the comprehensive impact of meteorological factors, including air temperature, precipitation, and wind speed on lake ice thickness dynamics. Air temperature was identified 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 and wind speed also exhibited varying degrees of influence on lake ice thickness dynamics. This study enhanced our 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 Lake Nanhu in Inner Mongolia |
