Parameters and code for estimating methane emissions from Arctic-boreal lakes, 2022

This data set accompanies a paper looking at the relative importance of three variables in upscaling Arctic lake methane emissions: the area of small, non-inventoried lakes; lake aquatic vegetation coverage; and potential double counting with wetlands. A baseline bottom-up emissions estimate based o...

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Bibliographic Details
Main Authors: Ethan D. Kyzivat, Laurence C. Smith
Format: Dataset
Language:unknown
Published: Arctic Data Center 2023
Subjects:
Online Access:https://search.dataone.org/view/urn:uuid:2ac763ca-d06b-4193-935c-4799ec0fbf9e
Description
Summary:This data set accompanies a paper looking at the relative importance of three variables in upscaling Arctic lake methane emissions: the area of small, non-inventoried lakes; lake aquatic vegetation coverage; and potential double counting with wetlands. A baseline bottom-up emissions estimate based on temperature and lake area is provided for all inventoried lakes within the Boreal-Arctic Wetland and Lake Dataset (BAWLD, Olefeldt et al., 2021, https://doi.org/10.18739/A2C824F9X), with estimates for extrapolated lake area bins below the inventory resolution. The data set includes two compressed, comma separated value (CSV) files with an index column corresponding to either lakes in the HydroLAKES inventory (Messager et al., 2016; https://www.hydrosheds.org/products/hydrolakes), or grid cells in BAWLD. The global surface water data set (GSW, Pekel et al., 2016) was used to derive lake aquatic vegetation (LAV) and potential wetland double-counting, defined as areas within lakes corresponding to less than 50% water occurrence. A third CSV dataset provides estimates for lake and aquatic vegetation areas and methane emissions for extrapolated area bins corresponding to lakes below the 0.5 km2 inventory threshold used in the paper. The python package developed for this data analysis is also included. Further details are given below and in the accompanying publication.