How to Assess Trajectories of Arctic Ponds and Lakes: a Circum-Arctic Perspective

• Main Authors: Muster, Sina, Roth, K., Cresto Aleina, Fabio, Langer, Moritz, Bartsch, Annett, Morgenstern, Anne, Grosse, Guido, Lange, Stephan, Boike, Julia
• Format: Conference Object
• Language: unknown
• Published: AGU 2015
• Subjects: Arctic; Canada; Ice; permafrost; Alaska; Siberia
• Online Access: https://epic.awi.de/id/eprint/39347/; https://hdl.handle.net/10013/epic.46596

Arctic ponds, i. e. water bodies with a surface area equal to or smaller than 10⁴ m² (1 ha), are currently not inventoried on a circum-arctic scale. However, they are a key element of the water, energy, and carbon balance and abundant in Arctic permafrost lowlands. Ponds and lakes have been subject to both wetting and drying in a warming climate yet studies remain ambivalent regarding the causes of these changes. Goals of this study are to (i) investigate the variability of water body size distributions as a function of landscape characteristics, and (ii) assess the vulnerability of water bodies in different landscapes to scenarios of wetting and drying. Ponds and lakes were mapped from high-resolution aerial and satellite imagery with resolutions of 4 m or better in 14 regions in Alaska, Canada, and Siberia covering a total area of ca. 1.6*104 km². Whereas lake distributions are similar, pond distributions in our study regions vary significantly with the area-normalized number of ponds differing up to 3 orders of magnitude. Landscape characteristics that may explain the current water body distributions include climate (eg., precipitation, evapotranspiration, temperature), permafrost (eg., ground ice content, maximum thaw depth) and terrain characteristics (eg., topography, glaciation, landscape age) which we derive from in situ, remote sensing and modeling data sources. Multivariate regression analysis are used to relate landscape characteristics to distribution parameters. This study for the first time allows to quantify the circum-arctic variability of pond distribution. The current maps are the start of a high-resolution circum-arctic water body inventory and present a baseline for future surface inundation mapping and modelling. We present representative regional probability density functions (pdf) and assess the potential to upscale pdfs using spatial landscape characteristics. We then discuss the vulnerability of water bodies to wetting or drying based on the distribution parameters, their correlation with landscape characteristics and the likeliness of both to change in different future climate scenarios.