Quaternary geology of the Arctic Coastal Plain, northern Alaska

Author(s):  
John Blandford O'Sullivan
2020 ◽  
Vol 22 ◽  
pp. e00980
Author(s):  
Sharon A. Poessel ◽  
Brian D. Uher-Koch ◽  
John M. Pearce ◽  
Joel A. Schmutz ◽  
Autumn-Lynn Harrison ◽  
...  

2020 ◽  
Author(s):  
Claire E. Simpson ◽  
Christopher D. Arp ◽  
Yongwei Sheng ◽  
Mark L. Carroll ◽  
Benjamin M. Jones ◽  
...  

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.


2021 ◽  
Vol 13 (3) ◽  
pp. 1135-1150
Author(s):  
Claire E. Simpson ◽  
Christopher D. Arp ◽  
Yongwei Sheng ◽  
Mark L. Carroll ◽  
Benjamin M. Jones ◽  
...  

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.


2014 ◽  
Vol 6 (10) ◽  
pp. 9170-9193 ◽  
Author(s):  
Shengan Zhan ◽  
Richard Beck ◽  
Kenneth Hinkel ◽  
Hongxing Liu ◽  
Benjamin Jones

ARCTIC ◽  
2018 ◽  
Vol 71 (3) ◽  
Author(s):  
Daniel C. McEwen ◽  
Malcolm G. Butler

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.


1968 ◽  
Vol 46 (6) ◽  
pp. 1127-1130 ◽  
Author(s):  
David L. Chesemore

Food habits of white foxes were studied on the Teshekpuk Lake Section of the Arctic Coastal Plain, northern Alaska, from September 1961 through May 1963. Lemmings were the primary fox prey but sea mammal and caribou carrion also can be important year-round foods. Birds and bird eggs formed an important part of the summer diet. The increase in occurrence of non-food items in the winter diet may reflect the scarcity of suitable fox foods. Based on size, fox scats could be separated into adult and pup classes while the color of the scat reflected both its age and contents.


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