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Hydrological drivers of record-setting water level rise on Earth's largest lake system

机译:创纪录的水位上升的水文驱动因素在地球上最大的湖泊系统中

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摘要

Between January 2013 and December 2014, water levels on Lake Superior and Lake Michigan-Huron, the two largest lakes on Earth by surface area, rose at the highest rate ever recorded for a 2 year period beginning in January and ending in December of the following year. This historic event coincided with below-average air temperatures and extensive winter ice cover across the Great Lakes. It also brought an end to a 15 year period of persistently below-average water levels on Lakes Superior and Michigan-Huron that included several months of record-low water levels. To differentiate hydrological drivers behind the recent water level rise, we developed a Bayesian Markov chain Monte Carlo (MCMC) routine for inferring historical estimates of the major components of each lake's water budget. Our results indicate that, in 2013, the water level rise on Lake Superior was driven by increased spring runoff and over-lake precipitation. In 2014, reduced over-lake evaporation played a more significant role in Lake Superior's water level rise. The water level rise on Lake Michigan-Huron in 2013 was also due to above-average spring runoff and persistent over-lake precipitation, while in 2014, it was due to a rare combination of below-average evaporation, above-average runoff and precipitation, and very high inflow rates from Lake Superior through the St. Marys River. We expect, in future research, to apply our new framework across the other Laurentian Great Lakes, and to Earth's other large freshwater basins as well.
机译:在2013年1月至2014年12月期间,按面积计算,地球上最大的两个湖泊苏必利尔湖和密歇根休伦湖的水位以有史以来的最高速度上升,始于下一年的一月至下一年的十二月年。这次历史性事件恰逢大湖区气温低于平均水平和大面积冬季冰雪覆盖。这也结束了苏必利尔湖和密歇根-休伦湖水位持续低于平均水平的15年期,其中包括数月以来的最低水位。为了区分最近水位上升背后的水文驱动因素,我们开发了贝叶斯马尔可夫链蒙特卡洛(MCMC)例程,以推断每个湖泊水预算主要组成部分的历史估算值。我们的结果表明,2013年,苏必利尔湖的水位上升是由于春季径流量增加和湖上降水增加所致。 2014年,减少的湖上蒸发量在苏必利尔湖水位上升中起了更重要的作用。 2013年密歇根湖-休伦湖的水位上升也是由于春季径流高于平均水平和持续的湖上降水,而在2014年,这是由于蒸发量低于平均水平,径流高于平均水平和降水的罕见组合,并且从苏必利尔湖穿过圣玛丽斯河的流量非常高。我们希望在未来的研究中,将我们的新框架应用于其他Laurentian大湖以及地球上其他大型淡水盆地。

著录项

  • 来源
    《Water resources research》 |2016年第5期|4026-4042|共17页
  • 作者单位

    NOAA, Great Lakes Environm Res Lab, 2205 Commonwealth Blvd, Ann Arbor, MI 48105 USA|Univ Michigan, Dept Civil & Environm Engn, Ann Arbor, MI 48109 USA;

    Environm & Climate Change Canada, Great Lakes St Lawrence Regulat Off, Cornwall, ON, Canada;

    Canadian Meteorol Ctr, Dorval, PQ, Canada;

    Univ Michigan, Cooperat Inst Limnol & Ecosyst Res, Ann Arbor, MI 48109 USA;

    NOAA, Great Lakes Environm Res Lab, 2205 Commonwealth Blvd, Ann Arbor, MI 48105 USA;

    Environm & Climate Change Canada, Canada Ctr Inland Waters, Burlington, ON, Canada;

    Univ Toledo, Dept Environm Sci, 2801 W Bancroft St, Toledo, OH 43606 USA;

    NOAA, Great Lakes Environm Res Lab, 2205 Commonwealth Blvd, Ann Arbor, MI 48105 USA;

    Canadian Meteorol Ctr, Dorval, PQ, Canada;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    water balance; hydrological cycle; Great Lakes; Bayesian;

    机译:水量平衡;水文循环;大湖区;贝叶斯;

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