temporal and spatial pattern of thermokarst lake area change at yukon flats, alaska

Temporal and Spatial Pattern of Thermokarst Lake Area Change at Yukon Flats, Alaska

Min Chen(min@lanl.gov), Joel C. Rowland, Cathy J. Wilson, Garrett L. Altmann, Steven P. BrumbyDivision of Earth and Environmental Sciences, Los Alamos National Laboratory, Los Alamos, NM

Introduction

Data and Methods

Temporal Trend Spatial Pattern

Conclusion

The development, expansion and drainage of thermokarst lakes depend on the lateral and vertical degradation of permafrost (Hinzman et al.,2005). Consequently, areal changes in thermokarst lakes can reflect changes in the spatial distribution and depth of permafrost to certain degree. However, permafrost degradation is not the only factor that impacts thermokarst lakes, other factors also have significant impacts on lake areas, including precipitation, evaporation (Bowling et al.,2003), connectivity to the rivers (Anderson et al.,2007), floods (Lesack and Marsh,2007). Because of limited availability of remote sensing images and intense work involved in extracting lakes from those images, most investigations on lake area change were conducted by directly comparing lake areas over two to four time periods, without consideration of seasonal and inter-annual variability in lake areas that might be caused by other impacting factors. Lack of consideration of seasonal and inter-annual variability can thus limit our ability to infer causal mechanisms of lake area change and prevent us from separating long-term trends from inter-annual variability (Arp et al.,2011). Besides the long-term trend in lake area change at regional scale, spatial heterogeneity in lake behaviors has also been of increasing interest. The inter-lake variation can mask or skew detection of total lake area change at regional scale (Arp et al.,2011). Investigation of inter-lake variation in area change can help us better understand the hydrologic and geomorphic processes within a region (Arp et al.,2011). In order to better understand the linkage among lake area, permafrost and seasonal and inter-annual variability in climate, we selected a 422,382 ha study area southwest of the Yukon River to explore the temporal and spatial pattern in lake area changes from 1984 to 2009. The goal of our study was to detect whether there was statistically significant long term trend in lake area change and whether the lakes with similar change trend were clustered at certain locations or randomly distributed. If there were significant temporal trend and spatial patterns, we sought to identify key drivers for the temporal and spatial patterns.

Fig. 1. Location and Landsat imagery (August 16, 2000) of the study area.

Area: 422,382 haElevation: 88-150 mPermafrost: DiscontinuousAnnual Precip: 26.72 cmAnnual PET: 48.2 cm

Study Area

Periods Dates

I: 1984-1986August 12, 1984July 30, 1985June 15, 1986

II: 1994 September 9, 1994

III: 1999-2002

June 26, 28, 1999August 16, 22, 1999September 6, 8, 1999June 4, 6, 2000June 13, 2000July 6, 8 2000August 16, 2000June 16, 2001September 20, 2001July 21, 2002August 6, 2002

IV: 2009July 16, 2009August 17, 2009

Table 1 Landsat Image Data (USGS)

Table 2 Other Data

Sources Station Data

National Climatic Data Center(daily, monthly) Fairbanks INTL ARPT

PrecipitationPotential Evapotranspiration*Derived using Priestley-Taylor equation

Air TemperatureAlaska-Pacific River Forecast

Center Beaver, Fort Yukon Ice-jam flooding

NCAR/EOL Yukon Bridge Borehole data

Data Analysis

Temporal Trend

Statistical modeling in R TLA=a+b1•LWB+b2•MDT+b3i•PRD+e (eq. 1)TLA — total area of closed basin thermokarst lakes (ha); LWB — local water balance (cm), P-PET since preceding October; MDT — mean daily air temperature (°C), the average of daily

mean temperature over the period from May 1st to the date when Landsat image was acquired;

PRD — a dummy variable, represents different time periods, including 1984-1986, 1992, 1999-2002, 2009;

a, b — intercept and coefficients, iindicates different time periods; e — the error term

Spatial Pattern Moran’s I in ArcGIS Chi Squired Test in R

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Tot

al A

rea

of C

lose

d B

asin

T

herm

okar

st L

akes

(ha)

Period

1 2 3 4

Fig. 2. Total actual areas of closed basin thermokarst lakes over the study period. Different colors represent different time periods. For 2,280 (26.6% of all lakes) closed basin thermokarst lakes, with a

total area of 19, 264 ha (47.9% of total lake area within study area)

Predictors1 Estimates of coefficients2 P value

Intercept 23050 (a) <0.0001Local water balance (LWB) 87 (b1) 0.04

Mean daily temperature (MDT) -780 (b2) 0.0003

Period (PRD)1994 1701(b32) 0.08

1999-2002 -1106 (b33) 0.05 2009 -936 (b34) 0.15

Table 3 Regression Analysis of Lake Area and Local Water Balance, Summer Mean Daily Temperature and Time Periods

Note: 1. LWB, MDT, PRD are predictors and coefficients specified for regression model (eq. 1). 2. a, b1, b2, b32, b33,b34 are coefficients specified for regression model (eq. 2).

8/12

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Sum

mer

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ratu

re (�C

)

Loc

al W

ater

Bal

ance

(cm

)

Local Water Balance Summer Mean Temperature

Variability in Lake Area

Variability in Climate Factors

Fig. 3. Local water balance and summer mean daily temperature over the study period. Red bars indicate summer mean temperature and blue bars represent local water balance.

Temporal Trend in Lake Area Change

Regression analysis showed that local water balance, summer mean daily temperature and time period explained 94.1% of total variance in lake areas and they were all significant at significance level of 0.05. Lake area increased with local water balance and decreased with summer mean daily temperature (i.e. decreased with active layer depth). Local water balance and summer mean daily temperature together explained 82.1% of total variance in lake areas, and time period accounted for another 12.0%. Compared to lake area (12,296 ha) in 1984, lake area increased by 1,701 ha (13.8%) in 1994, but decreased by 1,106 ha (9.0%) during 1999-2002 and 936 ha (7.6%) in 2009.

a

b

Fig. 4. Lake clusters with different changing trends (a) and their surrounding surficial geology (b)

Observed FrequencyExpected Frequency

Adjusted Standardized Residual

Lake Changing Trend

Decrease No Change Increase Row Total

Deposit Types

Alluvial Fan37291.6

151152-0.2

29

-2.4190

Alluvial Terrace2261973.4

10201027-0.7

3658

-4.51282

Floodplain86

123-4.5

6506410.9

65366.1

801

Column Total 349 1821 103 2273

Pearson’s Chi-squared test: chi squared=53.9, df=4, p=5.6×10-11

Table 5 Association between lake changing trends and deposit types

Possible Drivers

NO Significant trend in air temperature, precipitation, permafrost temperature. Change in ice-jam flooding frequency coincided with lake area change at each

time period.

Periods

Ice-jam Flooding Frequency Average Winter

Snowfall (cm)Numberof years Fort Yukon Beaver Village Total

Average (per year)

1979-1986 8 3 0 3 0.375 4.11987-1994 8 4 1 5 0.625 4.41995-2002 8 0 0 0 0 3.22003-2009 7 2 0 2 0.286 3.3

Table 4 Ice-jam Flooding Frequency and Average Winter Snowfall

Possible Drivers

Ice-jam flooding frequency Vertical permafrost degradation caused by heating effect of lakes

Lake (A,B,C)

River (D)

Permafrost

Aquifer

Groundwater flow

A

B

C D

Potentiometric surface

Fig. 5. Sub-permafrost Groundwater flow in discontinuous permafrost region. Lake A recharges groundwater; Lake B has no connection to groundwater; Lake C is recharged by groundwater. River D is recharged by groundwater.

Taking the lake area (12,296 ha) in 1984 as a baseline, lake area increased by 13.8% in 1994, but decreased by 9.0% and 7.6% during 1999-2002 and in 2009, respectively.

Among the 2,280 closed basin thermokarst lakes, 350 lakes showed an area decrease and 103 lakes showed an increase between 1984-1986 (period I) and 1999-2002 (period III).

The expanding lakes were mainly distributed along the floodplain of Yukon River and its tributaries, while the shrinking lakes were located away from rivers or on alluvial terraces.

Fluctuating ice-jam flooding frequency might be the main driver for the observed temporal lake area change pattern.

Two mechanisms, decreasing ice-jam flooding frequency and local permafrost degradation due to heating effect of water bodies, might be driving the spatial pattern of individual lake area changes.

Poster ID: C21B-0468

LA-UR: 11-11849