Estimates of reservoir methane emissions based on a spatially balanced probabilistic‐survey

Abstract

AbstractGlobal estimates of methane (CH4) emissions from reservoirs are poorly constrained, partly due to the challenges of accounting for intra‐reservoir spatial variability. Reservoir‐scale emission rates are often estimated by extrapolating from measurement made at a few locations; however, error and bias associated with this approach can be large and difficult to quantify. Here, we use a generalized random tessellation survey (GRTS) design to generate unbiased estimates of reservoir‐CH4 emissions rates (±95% CI) for areas below tributary inflows, open‐waters, and at the whole‐reservoir scale. Total CH4 emission rates (i.e., sum of ebullition and diffusive emissions) were 4.8 (±2.1), 33.0 (±10.7), and 8.3 (±2.2) mg CH4 m−2 h−1 in open‐waters, tributary‐associated areas, and the whole‐reservoir for the period in August 2014 during which 115 sites were sampled across an 7.98 km2 reservoir in Southwestern, Ohio, U.S.A. Tributary areas occupy 12% of the reservoir surface, but were the source of 41% of total CH4 emissions, highlighting the importance of riverine‐lacustrine transition zones. Ebullition accounted for > 90% of CH4 emission at all spatial scales. Overall, CH4 emission rates were high for a temperate zone reservoir, possibly because earlier studies underestimated ebullition or did not include emission hot spots. Confidence interval estimates that incorporated spatial pattern in CH4 emissions were up to 29% narrower than when spatial independence is assumed among sites. The use of GRTS, or other probabilistic survey designs, can improve the accuracy and precision of reservoir emission rate estimates, which is needed to better constrain uncertainty in global scale emission estimates.