Richard L. Haney

USDA‐ARS Riesel Watersheds, Riesel, Texas, USA: Water quality research database

The 75 year legacy database including discharge, sediment loss, land management, and meteorological data for the USDA-ARS Riesel Watersheds, Riesel, TX, USA has been available on the web for more than a decade (www.ars.usda.gov/spa/hydro-data) and used in numerous studies and publications; however, only recently have these data been added to the Sustaining the Earths Watersheds, Agricultural Research Data System (STEWARDS) database (www.nrrig.mwa.ars.usda.gov/stewards/stewards.html). In addition, water quality data including dissolved inorganic N and P compounds measured from more than 1000 storm runoff events, 1300 base flow sampling events (lateral subsurface return flow or seepage flow), and 157 precipitation events through 2012 were added. The objectives of this manuscript are to present relevant background information on these data, summarize the data collection and analysis methodology, present the measured data along with cursory analyses, and convey the commitment of the USDA-ARS Riesel Watersheds to long-term data accessibility and database enhancement for water quality data and research.

Soil Organic Carbon under Pasture Management

Pastures are a significant land use in many eastern states of the U.S. (total of 31xa0Mha). Soil organic carbon (SOC) is generally greater under pastures than under row-cropping systems and is often equally as great as under forested land. There is great potential to improve the management of pastures, and subsequent sequestration of SOC, partly because many pastures are currently minimally managed as they provide adequate services to landowners without much input. Additional SOC can be sequestered with attention to soil fertility (i.e. applying inorganic and organic fertilizer sources when needed, but avoiding them when nutrients are sufficient), botanical composition (e.g. warm- vs. cool-season grasses and legumes, endophyte-infection status of tall fescue, annual vs. perennial growth), stocking rate, and stocking method (e.g. continuous vs. rotational, high vs. low density, short vs. long duration). Some information is available to characterize the response of SOC to management in particular soils or locations, but a much greater research effort is envisioned to provide more robust evaluation and recommendations. Soil organic C varies spatially under pastures in the vertical (depth) and horizontal directions (e.g. edaphic and animal behavior induced), and understanding this variation is essential to research and monitoring of pastures for SOC sequestration. Sequestration of SOC under pastures may occur for decades to centuries, but more long-term research is needed to establish these limits under different soil types and climatic conditions. Finally, SOC accumulation under pastures controls a suite of other potentially negative environmental effects in agricultural landscapes, such as excessive water runoff, sediment and nutrient losses to receiving bodies of water, threats to biodiversity, and radiatively active trace-gas emissions. An expanded network of comprehensive pasture-management research is needed for more complete information on SOC sequestration, but also for understanding and capturing the resiliency and sustainability of American agriculture for the future.

Comparison of Wheat Yield Simulated Using Three N Cycling Options in the SWAT Model

The Soil and Water Assessment Tool (SWAT) model has been successfully used to predict alterations in streamflow, evapotranspiration and soil water; however, it is not clear how effective or accurate SWAT is at predicting crop growth. Previous research suggests that while the hydrologic balance in each watershed is accurately simulated with SWAT, the SWAT model over or under predicts crop yield relative to fertilizer inputs. The SWAT model now has three alternative N simulation options: 1) SWAT model with an added flush of N (SWAT-flush); 2) N routines derived from the CENTURY model (SWAT-C); and 3) a one-pool C and N model (SWAT-One). The objective of this study was to evaluate the performance of SWAT-flush, SWAT-C, and SWAT-One as they affect wheat yield prediction. Simulated yields were compared to wheat yields in a 28-year fertilizer/wheat yield study in Lahoma, OK. Simulated yields were correlated with actual 28-year mean yield; however, none of the available N cycling models predicted yearly yields. SWAT-C simulated average yields were closer than other N sub-models to average actual yield. Annually there was a stronger correlation between SWAT-flush and actual yields than the other submodels. However, none of the N-cycling routines were able to accurately predict annual variability in yield at any fertilizer rate. We found that SWAT-C or SWAT-flush are the most viable choices for accurately simulating long-term average wheat yields although annual variations in yield prediction should be taken into consideration. Further research is needed to determine the effectiveness of SWAT-C and SWAT-flush in determining average and annual yield in various farming regions and with numerous agronomic crops.