Recent Water Level Declines in the Lake Michigan−Huron System

Sellinger, Cynthia E.; Stow, Craig A.; Lamon, E. Conrad; Qian, Song S.

doi:10.1021/es070664+

Cited by 92 publications

(60 citation statements)

References 32 publications

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“…As sensitive and good indicators of changing environments at both regional and global scales [3][4][5][6][7], lakes have long been an academic focus. The variations in lake area and lake water levels and the responses to climate change and intensifying anthropogenic activities have been widely investigated all over the world in recent years [8][9][10][11][12][13]. For lakes widely distributed across ungauged basins (i.e., those lacking meteorological and hydrological stations) and in remote and poor regions, it is very difficult to quantify lake dynamics and the causes of variations.…”

Section: Introductionmentioning

confidence: 99%

Application of Landsat Imagery to Investigate Lake Area Variations and Relict Gull Habitat in Hongjian Lake, Ordos Plateau, China

Liang

Yan

2017

Remote Sensing

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Abstract:Lakes in arid and semi-arid regions have an irreplaceable and important role in the local environment and wildlife habitat protection. Relict Gull (Larus relictus), which is listed as a "vulnerable" bird species in the IUCN Red List, uses only islands in lakes for habitat. The habitat with the largest colonies in Hongjian Lake (HL), which is located in Shaanxi Province in China, has been severely threatened by persistent lake shrinkage, yet the variations in the area of the lake and the islands are poorly understood due to a lack of in situ observations. In this study, using the Modified Normalized Difference Water Index, 336 Landsat remote sensing images from 1988-2015 were used to extract the monthly HL water area and lake island area, and the driving factors were investigated by correlation analysis. The results show that the lake area during 1988-2015 exhibited large fluctuations and an overall downward trend of −0.94 km 2 /year, and that the lake area ranged from 55.02 km 2 in 1997 to 30.90 km 2 in 2015. The cumulative anomaly analysis diagnosed the lake variations as two sub-periods with different characteristics and leading driving factors. The average and change trend were 52.88 and 0.21 km 2 /year during 1988-1998 and 38.85 and −1.04 km 2 /year during 1999 , respectively. During 1988-1998, the relatively high precipitation, low evapotranspiration, and low levels of human activity resulted in a weak increase in the area of HL. However, in 1999-2015, the more severe human activity as well as climate warming resulted in a fast decrease in the area of HL. The variations in lake island area were dependent on the area of HL, which ranged from 0.02 km 2 to 0.22 km 2 . As the lake size declined, the islands successively outcropped in the form of the four island zones, and the two zones located in Northwest and South of HL were the most important habitats for Relict Gull. The formation of these island zones can provide enough space for Relict Gull breeding.

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Section: Introductionmentioning

confidence: 99%

Application of Landsat Imagery to Investigate Lake Area Variations and Relict Gull Habitat in Hongjian Lake, Ordos Plateau, China

Liang

Yan

2017

Remote Sensing

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“…Specifically, some authors have found recent significant positive trends in evaporation [52,53], and although variability associated with evaporation has historically been too small to significantly affect the lake levels, a persistent positive decadal-scale evaporation anomaly is now resulting in significant cumulative lake-level changes [8]. As discussed in Section 2.1, the precipitation-driven lake-level components have explained a majority of the historic lake-level behavior; however, their time series are beginning to diverge, stemming from increasing evaporative losses over the past couple of decades.…”

Section: Discussionmentioning

confidence: 99%

Attribution of Decadal-Scale Lake-Level Trends in the Michigan-Huron System

Hanrahan

Roebber

Kravtsov

2014

Water

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This study disentangles causes of the Michigan-Huron system lake-level variability. Regional precipitation is identified as the primary driver of lake levels with sub-monthly time lag, implying that the lake-level time series can be used as a proxy for regional precipitation throughout most of the 1865-present instrumental record. Aside from secular variations associated with the Atlantic Multidecadal Oscillation, the lake-level time series is dominated by two near-decadal cycles with periods of 8 and 12 years. A combination of correlation analysis and compositing suggests that the 8-y cycle stems from changes in daily wintertime precipitation amounts associated with individual storms, possibly due to large-scale atmospheric flow anomalies that affect moisture availability. In contrast, the 12-y cycle is caused by changes in the number of instances, or frequency, of summertime convective precipitation due to a preferred upper-air trough pattern situated over the Great Lakes. In recent decades, the lake-level budget exhibited an abnormal-relative to the remainder of the instrumental record-evaporation-driven trend, likely connected to regional signatures of anthropogenic climate change. The latter effect must be accounted for, along with the effects of precipitation, when assessing possible scenarios of future lake-level variability.

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“…The method is an iterative nonparametric procedure using repeated loess fitting (Sellinger et al 2007). A time series of monthly monitoring data may be considered a sum of three components: high-frequency seasonal, low-frequency, long-term (or trend), residual (variation not explained by time).…”

Section: Methodsmentioning

confidence: 99%

“…Such variability results from the customary seasonal oscillation and from the superimposed effect of several nonseasonal forcing factors. Variation of the seasonal cycle has been studied using seasonal-trend decomposition using loess (local error sum of squares) (STL) method for water level (Lenters 2001;Sellinger et al 2007) and nutrient trend (Qian et al 2000;Wang et al 2012b). In this case, the trend of water level fluctuations in Lake Baiyangdian can be decomposed to depict intra-annual water level variation, using STL method.…”

Section: Introductionmentioning

confidence: 99%

Long-term periodic structure and seasonal-trend decomposition of water level in Lake Baiyangdian, Northern China

Wang

Zhao

et al. 2013

Int. J. Environ. Sci. Technol.

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Water level, as an intuitive factor of hydrologic conditions, is of great importance for lake management. In this study, periodic structures of water level and its fluctuations in Lake Baiyangdian are analyzed based on wavelet analysis and seasonal-trend decomposition using local error sum of squares (STL). Data of monthly time series are divided into three types with emphasis on anthropogenic influence from water allocation. It is found that intra-annual characteristics of water level fluctuations are the common periodic structures. Water allocation alters the periodic structures by decreasing and weakening the oscillations of water level, compared with the slight effects of natural hydrologic water supplies and short-term climate changes. An irregular water level decline and short-term oscillation with irregular periodicity are deduced from seasonal-trend decomposition analysis using STL. With seasonality depicted monthly, the influence of water allocation implies irregular oscillations with high-frequency components, especially for monthly changes. The water level fluctuations are influenced by seasonal changes, as demonstrated by three types of time series. The impacts of water allocation on seasonality show the differences with continuous single-peak oscillations representing no influences and continuous double-peak oscillations representing frequent influences. Furthermore, the accumulation of water allocation shows a slight rising trend in average monthly level fluctuations over the last several years. The study helps understand periodic structures and long-term trend changes of water level fluctuations, which will facilitate lake management of Lake Baiyangdian.

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Recent Water Level Declines in the Lake Michigan−Huron System

Cited by 92 publications

References 32 publications

Application of Landsat Imagery to Investigate Lake Area Variations and Relict Gull Habitat in Hongjian Lake, Ordos Plateau, China

Application of Landsat Imagery to Investigate Lake Area Variations and Relict Gull Habitat in Hongjian Lake, Ordos Plateau, China

Attribution of Decadal-Scale Lake-Level Trends in the Michigan-Huron System

Long-term periodic structure and seasonal-trend decomposition of water level in Lake Baiyangdian, Northern China

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