1. Climate products and agricultural decision-making. Accurate, long-term precipitation data are needed for climate-informed decision support tools for agriculture, but few such records exist. Gridded estimates of precipitation from 1895 through the present were created by the PRISM Climate Group, but the accuracy of the gridded PRISM product required validation. Precipitation data gathered over several decades at the Grazinglands Research Laboratory, El Reno, Oklahoma, were used to check the PRISM product. The monthly gridded PRISM precipitation estimates are close to the observed data in terms of averages (smaller by 3 to 4.5%) and probability distributions (within approx. 4%), but with variability less for PRISM than for gauge data. For agricultural decision support, the PRISM estimates might be useful for probabilistic applications, such as downscaling climate forecasts or driving weather generators. However, because many monthly estimates differed from observed data by greater than 1.2", the PRISM estimates are not suited for retrospective month-by-month studies of interactions between climate, crop management, and productivity.
2. Landscape predictors of stream phosphorus concentrations. Agricultural land uses have been identified as one of the greatest contributors to impairment of water quality in the US, and in many regions high phosphorus (P) concentration has been identified as the most limiting factor related to impaired water quality. Based on long term studies in the Fort Cobb Reservoir Experimental Watershed, a Conservation Effects Assessment Project Benchmark Watershed, ARS scientists at El Reno, Oklahoma; Watkinsville, Georgia and College Station, Texas, identified spatial patterns in P in streams associated with landscape metrics during wet and dry periods. Stream P concentrations were 3 to 5 times higher during wet periods than dry periods. Lateral metrics (topography, soil, geology, management) were better predictors than in-stream metrics for P concentrations in streams. During the wet period, metrics indicative of rapid surface and subsurface water movement were associated with higher P stream concentrations. The ability to identify portions of the landscape more vulnerable to P losses is an essential first step in developing better strategies for targeting conservation practices and sites within a watershed.
3. A tool for analysis of big hydrologic datasets. There is a need in water science for computational tools to perform data manipulations and analyses of large spatially distributed datasets in one application, but few such tools exist. A conceptual data model and analysis tool, SPELLmap, was developed at the Grazinglands Research Laboratory, El Reno, Oklahoma, to rapidly process, manipulate, analyze, visualize, and provide data metrics for large geo-located datasets. SPELLmap has the capacity to represent three- or four-dimensional problems using a layer-data structure that can be used to assess data quality, perform statistical analyses, support modeling changes in land use, and perform spatial and temporal computations within integrated environmental modeling problems. This tool can advance hydrological research because high spatio-temporal resolution datasets best represent the spatial and temporal variability of hydrological processes and the associated transport of nutrients and contaminants at the watershed scale.
Arnold, J.G., Moriasi, D.N., Gassman, P.W., Abbaspour, K.C., White, M.J., Srinivasan, R., Santhi, C., Harmel, R.D., Van Griensven, A., Van Liew, M.W., Kannan, N., Jha, M.K. 2012. SWAT: Model use, calibration, and validation. Transactions of the ASABE. 55(4):1491-1508.