Alternate Wetting and Drying as an Effective Management Practice to Reduce Methane in Arkansas Rice Production

Abstract:

Approximately 15% of the global 308 Tg CH₄ emitted by anthropogenic sources is currently attributed to rice cultivation. Arkansas, the leading state in rice cultivation, produces over 42% of the total rice and represents over 43% of total land planted to rice in the US. Although rice production is generally water-intensive, some rice producers have adopted a conservation practice, ‘Alternate Wetting and Drying’ (AWD), in which the flood is released periodically during the growing season. In addition, implementing AWD can reduce CH₄ emissions though the introduction of aerobic conditions. To assess the magnitude of this reduction, conventionally flooded (CONV) and AWD fields were identically instrumented for the 2015 season and fluxes of CH₄ were measured with an open path IRGA. Other biophysical variables were monitored to determine the relative dominance of potential drivers. Half-hourly CH₄ fluxes from the AWD and CONV fields during their similar initial flood (DOY 138-161) were well correlated (R² = 0.762), indicating similar mechanisms controlling CH₄ emissions in both fields. After the initial drydown event in the AWD field (162 DOY), daily median CH₄ fluxes continued to rise to 7.80 mg CH₄ m^-2 h^-1 on 163 DOY before subsiding to a local minimum of 0.162 mg CH₄ m^-2 h^-1 on 171 DOY. Daily median CH₄ fluxes between 9.24 and 16.0 mg CH₄ m^-2 h^-1 were observed in the CONV field during this same period. Cumulative emissions from both fields following the drydown event and prior to rewetting demonstrated a reduction in CH₄ emissions by the AWD treatment by 82%. The substantial decrease in CH₄ emissions by AWD in the early growing season supports and expands upon previous chamber-based research and offers strong evidence for the efficacy of AWD in reducing CH₄ emissions in AR rice production. The presentation will also assess the latter portion of the growing season, currently underway, and will provide process-based relationships between biophysical parameters and CH­₄ emissions.