Cover crop (CC) growth and biomass production in the Mid-Atlantic region can be limited following double crop soybean due slow establishment related cool fall temperatures. Interseeding CC in summer before soybean canopy closure can improve establishment and spring biomass production. This practice can also increase the diversity of available CC species, reduce weed pressure and reduce nutrient losses. This study evaluates the effects of interseeded CC on soil temperature, soil water balances, evapotranspiration, infiltration, and yield and water use efficiency of corn (Zea mays L.) phase, following soybean (Glycine max L.) The study was conducted at the USDA Beltsville Agricultural Research Center, Beltsville, MD from 2017 through 2020. The cropping systems under study were primarily sequences of corn-soybean-wheat (Triticum aestivum L.)-double crop soybean all planted with no-tillage management. No cover crops (NC) were grown prior to corn in Systems 3 and 4. In System 5, a cover crop (CC) mixture of rye (Secale cereale L.)-hairy vetch (Vicia villosa Roth)-crimson clover (Trifolium incarnatum L.) was interseeded into DCS prior to soybean canopy closure. In System 6, red clover (rc, Trifolium pratense L.) was interseeded into wheat in March and rye was planted into rc after wheat harvest in July. Resources in this dataset: Resource Title: CCSP 2023 AGWAT Metadata File Name: CCSP 2023 AGWAT Metadata.docx Description: Meta information describing data collection procedures, estimation of ET and infiltration, and methods used to replace sensor data having errors. Resource Title: CCSP Experiment Setup Info Tables 1 Through 4 File Name: CCSP Experiment Setup Info Tables 1 Through 4.xlsx Description: File contains data from Tables 1 through 4 of the manuscript and a schematic of the crop rotation; Table 1 describes the four cropping systems; Table 2 provides corn planting and harvest dates, cumulative growing degree days (CumGDD oC), rainfall, and period of soil water measurement for the growing season; Table 3 describes the soil water sensors and soil depths measured; and Table 4 gives 10 year average monthly air temperature and rainfall (2011 to 2020). Cover crop varieties are included in an additional worksheet. [Note: file updated to include cover crop varieties worksheet on 07/21/2023] Resource Title: CCSP Corn Yield Cover Crop Biomass File Name: CCSP Corn Yield Cover Crop Biomass.xlsx Description: Cover crop biomass (kg/ha) and corn yields (kg/ha) for 2017 through 2020 are provided at the replication and cropping system treatment level. Details about biomass sampling and corn harvest are contained in the manuscript. Resource Title: CCSP ET Calc Input Output Data And Meta Info File Name: CCSP ET Calc Input Output Data And Meta Info.xlsx Description: Weather data used to estimate daily evapotranspiration using ETCalc, an online calculator (Danielescu, 2021 and 2022) [ https://etcalc.hydrotools.tech/pageMain.php]. The input and output data are provided in separate tabs of the excel file. The first tab provides additional meta information. Resource Title: CCSP Weather 2017-2020 Rain And Air Temp For GDD File Name: CCSP Weather 2017-2020 Rain And Air Temp For GDD.xlsx Description: Daily data collected from a nearby weather station used to calculate 10-year average rainfall and temperature and used to calculate growing degree days in each growing season. Growing degree day calculations are presented in tabs for each year. Resource Title: CCSP Soil Temperature And Soil Water By Depth File Name: Volumetric soil water content (m3/m3) (VWC) and soil temperature data collected at 4 depths in each plot. VWC was converted to mm water per depth and summed for the soil profile (0 to 862 mm). Measurements were averaged to daily values. Soil water storage and soil temperature data are given for each replication, cropping system treatment, and horizon depth in separate tabs for each year.

This dataset provides the city-specific air exchange rate measurements, modeled, literature-based as well as housing characteristics. This dataset is associated with the following publication: Baxter, L., C. Stallings, L. Smith, and J. Burke. Probabilistic estimation of residential air exchange rates for population-based human exposure modeling. Journal of Exposure Science and Environmental Epidemiology. Nature Publishing Group, London, UK, 27: 227-234, (2017).

The project this data comes from looks to make building wall retrofits less expensive and easier to install by using exterior insulating panels. This is done to make buildings more energy efficient without expensive wall retrofits or reconstruction. The "Measurement and Verification for Topic 1 Phase 1 Testing Guidance Draft" document includes the following: Standard Test Methods for Determining Thermal Performance: Controlled field testing and THERM simulations Standard Test Methods for Determining Air Leakage Rate: modified ASTM E779 Criteria for Moisture-Control Design Analysis in Buildings: WUFI simulations Moisture Management Plan: Relevant enclosure system design details. ABC Technology Scaling Framework: TRL characteristics relative to development phases Customer Discovery: Target customers and why they would buy/adopt the innovation. Also included in the submissions is the "Duct Blaster Test Report" from 8-25-2021 which includes a filled out test report form for a Duct Blaster which is used to directly pressure test a duct system for air leaks.

The data are derived from the field monitoring of irrigated furrows from 1998 to 2016 at the research farm of the USDA/ARS-Northwest Irrigation and Water Research Laboratory in Kimberly, Idaho, USA (south-central Idaho). For each monitored furrow, irrigation inflow rates, outflow rates, and sediment concentrations were recorded periodically during the irrigation. A gated pipe conveyed irrigation water across the plots at the head, or inflow-end, of the furrows and adjustable spigots supplied water to each irrigated furrow. The methodology used to obtain the field data is described by Lentz and Sojka (2009). Inflows were measured by timing the filling rate of a known volume, and runoff were measured with long-throated, v-notch flumes. Outflows were measured and runoff samples collected at 30 min intervals during the first 1-3 hr of an irrigation, and every hour or two for the next 3 to 5 hr. If the set was continued for an additional 12 hr, two to four additional measurements were made. Immediately after each flume reading, sediment concentration in furrow streams were measured by collecting one-liter runoff samples from free-flowing flume discharge. The weight of sediment per liter of runoff was determined from the settled volume of sediment using the Imhoff-cone technique. Three Imhoff-cone sediment samples were collected from each treatment in each irrigation. These were filtered, and the papers dried and weighed. A calibration function relating the 30-min, settled-sediment volume to sediment mass-per-unit-volume of runoff was then calculated and used to convert settled sediment volume in cones to sediment mass. The field data for each study or year were analyzed using the WASHOUT program (Lentz and Sojka, 1995). The WASHOUT program produces an output file (filename.out), which become components of this Ag Data Commons data set. For many years and irrigations, furrows were monitored at one or more locations along the furrow, as well as at the end (bottom) of the furrow. In these cases, data for each position within the furrow are listed in the data set, labelled for example as 'Top', 'Middle', and 'Bottom' (See Data Dictionary tab). For each furrow position the data represent the flow, infiltration, and runoff information for the length of furrow, which begins at its inflow end (top of the field) and ends at the defined furrow position. This distance is listed in the field data file for each furrow and irrigation. An Irrigation Data Summary is included as a tab in the data set spreadsheet. This is a summary list of the studies and irrigations that are included in the data set. Also included is a PAM-Application-Codes tab that lists description of the polyacrylamide (PAM) treatments that were employed in some of the included studies.

Simulated rainfall and overland-flow experiments are useful for enhancing understanding of surface hydrologic and erosion processes, quantifying runoff and erosion rates, and developing and testing predictive quantitative models. This extensive dataset (1021 experimental plots) consists of rainfall simulation (1300 plot runs, 0.5 m2 to 13 m2 scales) and overland flow (838 plot runs, ~9 m2 scale) experimental plot data coupled with associated measures of vegetation, ground cover, and surface soil properties across point to hillslope scales. The data were collected at three woodland-encroached sagebrush (Artemisia spp.) rangelands in the Great Basin, USA, under undisturbed/untreated conditions and 1 yr to 9 yr following fire and/or mechanical tree-removal treatments. The methodology employed and resulting experimental data contribute to quantifying and understanding scale-dependent surface hydrologic and erosion processes for Great Basin woodlands and sagebrush rangelands before and after tree removal and for sparsely vegetated sites elsewhere. The dataset is a valuable source for developing and testing hydrology and erosion models for applications to diverse vegetation and ground cover conditions. Lastly, the series of repeated measures in the dataset for some sites over time provides a valuable dataset for exploring long-term landscape vegetation and hydrologic and erosion responses to various land management practices and disturbances. The resulting collective dataset of 1021 experimental plots contains vegetation, ground cover, soils, hydrology, and erosion data collected across multiple spatial scales, diverse cover and surface conditions, three study sites, and five different study years. The collective dataset contains 57 plots at the hillslope scale (site characterization plots), 528 small-rainfall plots, 146 large-rainfall plots, and 290 overland-flow plots. The hydrology and erosion experiments yielded time series datasets for small-rainfall plot, large-rainfall plot, and overland-flow plot simulations. Some time series hydrographs and sedigraphs from rainfall and overland flow simulations were excluded due to various equipment failures. The final time series datasets consist of 1020 small-rainfall, 280 large-rainfall, and 838 overland-flow plot run hydrographs and sedigraphs, not excluding plots without runoff. Restricting the data to plots that generated runoff results in 749 small-rainfall, 251 large-rainfall, and 719 overland-flow plot simulation hydrographs and sedigraphs. Overall, the hydrology and erosion time series dataset amounts to 2138 hydrographs/sedigraphs including plots with zero runoff and 1719 hydrographs/sedigraphs for plots that generated runoff. Field experiments and data management were conducted as part of the Sagebrush Steppe Treatment Evaluation Project (SageSTEP, (www.sagestep.org) funded by the US Joint Fire Science Program, US Department of Interior (USDI) Bureau of Land Management, and US National Interagency Fire Center. This dataset is contribution number 134 of the Sagebrush Steppe Treatment Evaluation Project. See README file for information regarding experimental design and methods.

Numerous technical reports related to water in New Mexico regions