Abstract

Abstract. In the present study, we measured independently CH4 ebullition and diffusion in the footprint of an eddy covariance system (EC) measuring CH4 emissions in the Nam Theun 2 Reservoir, a recently impounded (2008) subtropical hydroelectric reservoir located in the Lao People's Democratic Republic (PDR), Southeast Asia. The EC fluxes were very consistent with the sum of the two terms measured independently (diffusive fluxes + ebullition = EC fluxes), indicating that the EC system picked up both diffusive fluxes and ebullition from the reservoir. We showed a diurnal bimodal pattern of CH4 emissions anti-correlated with atmospheric pressure. During daytime, a large atmospheric pressure drop triggers CH4 ebullition (up to 100 mmol m−2 d−1), whereas at night, a more moderate peak of CH4 emissions was recorded. As a consequence, fluxes during daytime were twice as high as during nighttime. Additionally, more than 4800 discrete measurements of CH4 ebullition were performed at a weekly/fortnightly frequency, covering water depths ranging from 0.4 to 16 m and various types of flooded ecosystems. Methane ebullition varies significantly seasonally and depends mostly on water level change during the warm dry season, whereas no relationship was observed during the cold dry season. On average, ebullition was 8.5 ± 10.5 mmol m−2 d−1 and ranged from 0 to 201.7 mmol m−2 d−1. An artificial neural network (ANN) model could explain up to 46% of seasonal variability of ebullition by considering total static pressure (the sum of hydrostatic and atmospheric pressure), variations in the total static pressure, and bottom temperature as controlling factors. This model allowed extrapolation of CH4 ebullition on the reservoir scale and performance of gap filling over four years. Our results clearly showed a very high seasonality: 50% of the yearly CH4 ebullition occurs within four months of the warm dry season. Overall, ebullition contributed 60–80% of total emissions from the surface of the reservoir (disregarding downstream emissions), suggesting that ebullition is a major pathway in young hydroelectric reservoirs in the tropics.

Highlights

  • The atmospheric methane (CH4) mixing ratio has recently reached up to 1875 ppb, which is 162 % higher than the preindustrial value (IPCC, 2013), and is the highest mixing ratio ever reported (Dlugokencky et al, 2009)

  • CH4 emission was measured with eddy covariance system (EC), floating chambers (FCs) and funnels, and calculated by thin boundary layer (TBL) at the Nam Theun 2 (NT2) Reservoir in Lao People’s Democratic Republic (PDR), Southeast Asia

  • The analysis confirmed that (1) surrounding terrestrial ecosystems were always outside the footprint (Supplement Fig. S1), (2) only 2 % of the fluxes were rejected because wind came from the power generator, and (3) all FC and funnels measurements were conducted within the EC footprint area

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Summary

Introduction

The atmospheric methane (CH4) mixing ratio has recently reached up to 1875 ppb, which is 162 % higher than the preindustrial value (IPCC, 2013), and is the highest mixing ratio ever reported (Dlugokencky et al, 2009). Diffusive CH4 fluxes at the air–water interface depend on the concentration gradient between the surface water and the atmosphere and the gas transfer velocity (Wanninkhof, 1992) They are usually estimated either by calculations or by floating chambers (FCs). CH4 emission was measured with EC, FC and funnels, and calculated by TBL at the Nam Theun 2 (NT2) Reservoir in Lao PDR, Southeast Asia This manmade lake was chosen because of its potential for high CH4 emissions owing to its recent impoundment (2008) (Abril et al, 2005; Barros et al, 2011), and for the fact that it encompasses large and fast water level variations that should enhance ebullition With an annual average depth of 7.8 m, the NT2 Reservoir falls into the shallow reservoir category

Sampling strategy
Instrumentation of the EC system
Data processing
EC data quality control
Diffusive fluxes
Estimate from surface CH4 concentrations
CH4 ebullition
Gas chromatography
Artificial neural network
Statistical analysis
Assessment of CH4 emissions at the reservoir surface by different methods
Diffusive emission
Methane ebullition
Total CH4 emissions
Method
Extrapolation of ebullition at the NT2 Reservoir scale by ANN

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