Post-processed data and graphical tools for a CONUS-wide eddy flux evapotranspiration dataset.

Large sample datasets of in situ evapotranspiration (ET) measurements with well documented data provenance and quality assurance are critical for water management and many fields of earth science research. We present a post-processed ET oriented dataset at daily and monthly timesteps, from 161 stations, including 148 eddy covariance flux towers, that were chosen based on their data quality from nearly 350 stations across the contiguous United States. In addition to ET, the data includes energy and heat fluxes, meteorological measurements, and reference ET downloaded from gridMET for each flux station. Data processing techniques were conducted in a reproducible manner using open-source software. Most data initially came from the public AmeriFlux network, however, several different networks (e.g., the USDA-Agricultural Research Service) and university partners provided data that was not yet public. Initial half-hourly energy balance data were gap-filled and aggregated to daily frequency, and turbulent fluxes were corrected for energy balance closure error using the FLUXNET2015/ONEFlux energy balance ratio approach. Metadata, diagnostics of energy balance, and interactive graphs of time series data are included for each station. Although the dataset was developed primarily to benchmark satellite-based remote sensing ET models of the OpenET initiative, there are many other potential uses, such as validation for a range of regional hydrologic and atmospheric models.

Multiyear methane and nitrous oxide emissions in different irrigation management under long-term continuous rice rotation in Arkansas.

Rice paddies are one of the major sources of anthropogenic methane (CH4 ) emissions. The alternate wetting and drying (AWD) irrigation management has been shown to reduce CH4 emissions and total global warming potential (GWP) (CH4 and nitrous oxide [N2 O]). However, there is limited information about utilizing AWD management to reduce greenhouse gas (GHG) emissions from commercial-scale continuous rice fields. This study was conducted for five consecutive growing seasons (2015-2019) on a pair of adjacent fields in a commercial farm in Arkansas under long-term continuous rice rotation irrigated with either continuously flooded (CF) or AWD conditions. The cumulative CH4 emissions in the growing season across the two fields and 5 years ranged from 41 to 123 kg CH4 -C ha-1 for CF and 1 to 73 kg CH4 -C ha-1 for AWD. On average, AWD reduced CH4 emissions by 73% relative to CH4 emissions in CF fields. Compared to N2 O emissions, CH4 emissions dominated the GWP with an average contribution of 91% in both irrigation treatments. There was no significant variation in grain yield (7.3-11.9 Mg ha-1 ) or growing season N2 O emissions (-0.02 to 0.51 kg N2 O-N ha-1 ) between the irrigation treatments. The yield-scaled GWP was 368 and 173 kg CO2 eq. Mg-1 season-1 for CF and AWD, respectively, showing the feasibility of AWD on a commercial farm to reduce the total GHG emissions while sustaining grain yield. Seasonal variations of GHG emissions observed within fields showed total GHG emissions were predominantly influenced by weather (precipitation) and crop and irrigation management. The influence of air temperature and floodwater heights on GHG emissions had high degree of variability among years and fields. These findings demonstrate that the use of multiyear GHG emission datasets could better capture variability of GHG emissions associated with rice production and could improve field verification of GHG emission models and scaling factors for commercial rice farms.

P-FLUX: A phosphorus budget dataset spanning diverse agricultural production systems in the United States and Canada.

Quantifying spatial and temporal fluxes of phosphorus (P) within and among agricultural production systems is critical for sustaining agricultural production while minimizing environmental impacts. To better understand P fluxes in agricultural landscapes, P-FLUX, a detailed and harmonized dataset of P inputs, outputs, and budgets, as well as estimated uncertainties for each P flux and budget, was developed. Data were collected from 24 research sites and 61 production systems through the Long-term Agroecosystem Research (LTAR) network and partner organizations spanning 22 U.S. states and 2 Canadian provinces. The objectives of this paper are to (a) present and provide a description of the P-FLUX dataset, (b) provide summary analyses of the agricultural production systems included in the dataset and the variability in P inputs and outputs across systems, and (c) provide details for accessing the dataset, dataset limitations, and an example of future use. P-FLUX includes information on select site characteristics (area, soil series), crop rotation, P inputs (P application rate, source, timing, placement, P in irrigation water, atmospheric deposition), P outputs (crop removal, hydrologic losses), P budgets (agronomic budget, overall budget), uncertainties associated with each flux and budget, and data sources. Phosphorus fluxes and budgets vary across agricultural production systems and are useful resources to improve P use efficiency and develop management strategies to mitigate environmental impacts of agricultural systems. P-FLUX is available for download through the USDA Ag Data Commons (https://doi.org/10.15482/USDA.ADC/1523365).

Electromagnetic fields and health: DNA-based dosimetry.

We propose a biologically based measure of EMF radiation to replace the energy-based "specific absorption rate" (SAR). A wide range of EMF frequencies has been linked to an increased risk of cancer. The SAR value used to measure the EMF dose and set the safety standard in the radiofrequency (RF) range fails as a standard for predicting cancer risk in the ELF power frequency range. Because cancers are believed to arise from mutations in DNA, changes in DNA induced by interaction with EMF could be a better measure of the biologically effective dose in both frequency ranges. The changes can be measured by transcriptional alterations and/or translational changes in specific proteins. Because ionizing radiation also causes DNA damage, a biologically based standard related to stimulation of DNA could apply over a much wider range of the electromagnetic spectrum. A safety standard for exposure to a wide range of non ionizing frequencies can be based on the documented changes in DNA biochemistry that arise from interactions with EMF.

Practical analytical backscatter error bars for elastic one-component lidar inversion algorithm.

We present an analytical formulation to compute the total-backscatter range-dependent error bars from the well-known Klett's elastic-lidar inversion algorithm. A combined error-propagation and statistical formulation approach is used to assess inversion errors in response to the following error sources: observation noise (i.e., signal-to-noise ratio) in the reception channel, the user's uncertainty in the backscatter calibration, and in the (range-dependent) total extinction-to-backscatter ratio provided. The method is validated using a Monte Carlo procedure, where the error bars are computed by inversion of a large population of noisy generated lidar signals, for total optical depths tau < or = 5 and typical user uncertainties, all of which yield a practical tool to compute the sought-after error bars.