scholarly journals Spatio-Temporal Analysis of Gyres in Oriented Lakes on the Arctic Coastal Plain of Northern Alaska Based on Remotely Sensed Images

2014 ◽  
Vol 6 (10) ◽  
pp. 9170-9193 ◽  
Author(s):  
Shengan Zhan ◽  
Richard Beck ◽  
Kenneth Hinkel ◽  
Hongxing Liu ◽  
Benjamin Jones
Keyword(s):  
Coastal Plain ◽  
Temporal Analysis ◽  
Remotely Sensed ◽  
The Arctic ◽  
Arctic Coastal Plain ◽  
Remotely Sensed Images ◽  
Spatio Temporal ◽  
Northern Alaska

scholarly journals Movements and habitat use of loons for assessment of conservation buffer zones in the Arctic Coastal Plain of northern Alaska

2020 ◽  
Vol 22 ◽  
pp. e00980
Author(s):  
Sharon A. Poessel ◽  
Brian D. Uher-Koch ◽  
John M. Pearce ◽  
Joel A. Schmutz ◽  
Autumn-Lynn Harrison ◽  
...  
Keyword(s):  
Habitat Use ◽  
Coastal Plain ◽  
The Arctic ◽  
Buffer Zones ◽  
Arctic Coastal Plain ◽  
Northern Alaska

scholarly journals Remote sensing of lake water volumes on the Arctic Coastal Plain of Northern Alaska

2020 ◽  
Author(s):  
Claire E. Simpson ◽  
Christopher D. Arp ◽  
Yongwei Sheng ◽  
Mark L. Carroll ◽  
Benjamin M. Jones ◽  
...  
Keyword(s):  
Lake Water ◽  
Coastal Plain ◽  
Water Storage ◽  
Regional Model ◽  
The Arctic ◽  
Lake Depth ◽  
Arctic Coastal Plain ◽  
Water Volumes ◽  
Northern Alaska

Abstract. The Pleistocene Sand Sea on the Arctic Coastal Plain (ACP) of northern Alaska is underlain by an ancient sand dune field, a geological feature that affects regional lake characteristics. Many of these lakes, which cover approximately 20 % of the Pleistocene Sand Sea, are relatively deep (up to 25 m). In addition to the natural importance of ACP Sand Sea lakes for water storage, energy balance, and ecological habitat, the need for winter water for industrial development and exploration activities makes lakes in this region a valuable resource. However, ACP Sand Sea lakes have received little prior study. Here, we use in situ bathymetric data to test 12 model variants for predicting Sand Sea lake depth based on analysis of Landast-8 Operational Land Imager (OLI) images. Lake depth gradients were measured at 17 lakes in mid-summer 2017 using a HumminBird 798ci HD SI Combo automatic sonar system (Simpson and Arp, 2018). The field measured data points were compared to Red-Green-Blue (RGB) bands of a Landsat-8 OLI image acquired on 8 August 2016 to select and calibrate the most accurate spectral-depth model for each study lake and estimate bathymetry (Simpson, 2019). Exponential functions using a simple band ratio (with bands selected based on lake turbidity and bed substrate) yielded the most successful model variants. For each lake, the most accurate model explained 81.8 % of the variation in depth, on average. Modeled lake bathymetries were integrated with remotely sensed lake surface area to quantify lake water storage volumes, which ranged from 1.056 × 10−3 km3 to 57.416 × 10−3 km3. Due to variation in depth maxima, substrate, and turbidity between lakes, a regional model is currently infeasible, rendering necessary the acquisition of additional in situ data with which to develop a regional model solution. Estimating lake water volumes using remote sensing will facilitate better management of expanding development activities and serve as a baseline by which to evaluate future responses to ongoing and rapid climate change in the Arctic. All sonar depth data and modeled lake bathymetry rasters can be freely accessed at https://doi.org/10.18739/A2SN01440 (Simpson and Arp, 2018) and https://doi.org/10.18739/A2TQ5RD83 (Simpson, 2019), respectively.

scholarly journals Landsat-derived bathymetry of lakes on the Arctic Coastal Plain of northern Alaska

2021 ◽  
Vol 13 (3) ◽  
pp. 1135-1150
Author(s):  
Claire E. Simpson ◽  
Christopher D. Arp ◽  
Yongwei Sheng ◽  
Mark L. Carroll ◽  
Benjamin M. Jones ◽  
...  
Keyword(s):  
Lake Water ◽  
Coastal Plain ◽  
Water Storage ◽  
Regional Model ◽  
The Arctic ◽  
Landsat 8 ◽  
Lake Depth ◽  
Arctic Coastal Plain ◽  
Northern Alaska

Abstract. The Pleistocene sand sea on the Arctic Coastal Plain (ACP) of northern Alaska is underlain by an ancient sand dune field, a geological feature that affects regional lake characteristics. Many of these lakes, which cover approximately 20 % of the Pleistocene sand sea, are relatively deep (up to 25 m). In addition to the natural importance of ACP sand sea lakes for water storage, energy balance, and ecological habitat, the need for winter water for industrial development and exploration activities makes lakes in this region a valuable resource. However, ACP sand sea lakes have received little prior study. Here, we collect in situ bathymetric data to test 12 model variants for predicting sand sea lake depth based on analysis of Landsat-8 Operational Land Imager (OLI) images. Lake depth gradients were measured at 17 lakes in midsummer 2017 using a Humminbird 798ci HD SI Combo automatic sonar system. The field-measured data points were compared to red–green–blue (RGB) bands of a Landsat-8 OLI image acquired on 8 August 2016 to select and calibrate the most accurate spectral-depth model for each study lake and map bathymetry. Exponential functions using a simple band ratio (with bands selected based on lake turbidity and bed substrate) yielded the most successful model variants. For each lake, the most accurate model explained 81.8 % of the variation in depth, on average. Modeled lake bathymetries were integrated with remotely sensed lake surface area to quantify lake water storage volumes, which ranged from 1.056×10-3 to 57.416×10-3 km3. Due to variations in depth maxima, substrate, and turbidity between lakes, a regional model is currently infeasible, rendering necessary the acquisition of additional in situ data with which to develop a regional model solution. Estimating lake water volumes using remote sensing will facilitate better management of expanding development activities and serve as a baseline by which to evaluate future responses to ongoing and rapid climate change in the Arctic. All sonar depth data and modeled lake bathymetry rasters can be freely accessed at https://doi.org/10.18739/A2SN01440 (Simpson and Arp, 2018) and https://doi.org/10.18739/A2HT2GC6G (Simpson, 2019), respectively.

scholarly journals Shifting balance of thermokarst lake ice regimes across the Arctic Coastal Plain of northern Alaska

2012 ◽  
Vol 39 (16) ◽  
pp. n/a-n/a ◽  
Author(s):  
C. D. Arp ◽  
B. M. Jones ◽  
Z. Lu ◽  
M. S. Whitman
Keyword(s):  
Coastal Plain ◽  
The Arctic ◽  
Lake Ice ◽  
Thermokarst Lake ◽  
Arctic Coastal Plain ◽  
Shifting Balance ◽  
Northern Alaska

scholarly journals Tundra landform and vegetation productivity trend maps for the Arctic Coastal Plain of northern Alaska

2018 ◽  
Vol 5 (1) ◽  
Author(s):  
Mark J. Lara ◽  
Ingmar Nitze ◽  
Guido Grosse ◽  
A. David McGuire
Keyword(s):  
Coastal Plain ◽  
The Arctic ◽  
Vegetation Productivity ◽  
Arctic Coastal Plain ◽  
Productivity Trend ◽  
Northern Alaska

scholarly journals Growing-Season Temperature Change across Four Decades in an Arctic Tundra Pond

ARCTIC ◽  
2018 ◽  
Vol 71 (3) ◽  
Author(s):  
Daniel C. McEwen ◽  
Malcolm G. Butler
Keyword(s):  
Coastal Plain ◽  
Growing Season ◽  
Early Spring ◽  
The Arctic ◽  
Thermal Dynamics ◽  
Arctic Coastal Plain ◽  
Water Temperature Data ◽  
Tundra Ponds ◽  
Arctic Climate Change ◽  
Northern Alaska

We examined temperature dynamics across a 42-year period in a low-centered tundra polygon pond on the Arctic Coastal Plain of northern Alaska to assess potential changes in thermal dynamics for ponds of this type. Using water temperature data from a pond near Barrow (now Utqiaġvik), Alaska, studied intensively during 1971 – 73 and again in 2007 – 12, we built an empirical model coupling historical air temperatures to measured pond temperatures for four summers. We then used the model to predict summer pond temperatures over a 42-year span, including 1974 – 2008, for which direct aquatic temperature records do not exist. Average pond temperatures during the growing season (1 May through 31 October) increased by 0.5˚C decade-1 or 2.2˚C over the 42-year period. Our simulations predicted the average date of spring thaw for the pond as 2 June (± 3 d), which did not change over the 42-year time period. However, average pond temperature during the first 30 days of the growing season increased from 1971 to 2012, suggesting that recently, ponds are warmer in early spring. The average date of pond sediment freeze over the 42 years shifted later by 15 days, from 28 September in 1971 to 13 October in 2012. These changes correspond to a growing season that has increased in length by 14 days, from 118 days in 1971 to 132 days in 2012. Contemporary temperature measurements in other shallow tundra ponds in northern Alaska show a high degree of temporal coherence (r = 0.93 – 0.99), which warrants the general conclusion that tundra ponds on Alaska’s Arctic Coastal Plain have undergone a significant change in thermal dynamics over the past four decades. Our results provide a means to incorporate these pond types into larger-scale simulations of Arctic climate change.

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