Year Established: 2016 Start Date: 2016-03-01 End Date: 2017-02-28
Total Federal Funds: $25,000 Total Non-Federal Funds: $50,000
Principal Investigators: Benjamin Runkle
Abstract: This project is aimed to resolve uncertainties in the evapotranspiration (ET) portion of the water balance as rice farms transition from conventional to alternate wetting-drying (AWD) irrigation strategies. This shift comes in the context of large-scale water use by rice agriculture – 35% of Arkansas’s irrigation water – and unsustainable depletion of the state’s water resources. Additionally, AWD is used to reduce methane production and emission from rice fields since the dry down period removes the chemically reduced conditions required for methane production. This savings has encouraged greater adoption of AWD as farmers may be eligible for funding through emission offsets programs. This project seeks continuation from a currently running USGS 104B project that has found, intriguingly, even greater evapotranspiration from AWD than flooded rice fields – though significant reductions in methane emissions. To help generate a nuanced accounting of evapotranspiration (ET), this project aims to partition ET into evaporation and transpiration components and determine the dominant meteorological and biological drivers of each component. This project will quantify ET rates at 4 rice fields – two pairs of fields where one field is AWD-irrigated and the other is conventionally flooded. The pairs are in the central and northern regions of the rice-growing area in Arkansas to enable comparison between different cultivation and soil conditions. The ET measurements will be taken with the eddy covariance technique that has successfully generated a near-continuous time series for the 2015 growing season. These measurements will be supplemented with biometeorological data collection, including on plant height, leaf area index, leaf nutrient status, and crop stage. Following data collection the eddy covariance data will be subject to a footprint analysis and standard quality checks. The Penman-Monteith equation will be used to help interpret this dataset. One aspect of this approach is that the equations will be inverted using the measured dataset to generate data-driven estimates of canopy conductance. This conductance term will be combined with models of energy and matter transfer to generate the two time series of soil- or water- evaporation and leaf-canopy transpiration. The product will be compared to the state’s irrigation scheduling tool to ensure both basic and applied research outputs.