Location: Hydrology and Remote Sensing Laboratory
Project Number: 8042-12660-013-00-D
Project Type: Appropriated
Start Date: Oct 1, 2010
End Date: Aug 4, 2015
The ability to monitor and predict the ecological dynamics of carbon and nitrogen, agrichemicals, and invasive species over large areas will be critical for maintaining sustainable agricultural systems. Accordingly, this project has four objectives that focus on using remote sensing tools and modeling to scale point observations and field data from the landscape to regional scales. These are as follows: Objective 1: Develop measurement and remote sensing technologies for monitoring soil carbon and carbon exchange from field to regional scales to improve assessments of agricultural-management impacts on the carbon balance. Objective 2: Evaluate the impact of nutrient dynamics on the environment and agricultural production at field and watershed scales. Objective 3: Develop measurement techniques and models for quantifying field-scale herbicide volatilization. Objective 4: Evaluate the utility of remote sensing methods to detect invasive species and test models of invasive weed potential distribution using remotely-sensed data. In the first objective, new remote sensing methods will be investigated to quantify soil carbon redistribution, crop residue and carbon dioxide fluxes, and to identify critical process-based variables that will be incorporated into models and decision support systems. Research towards this objective will be focused in three areas: (1) assessing soil organic carbon at field and landscape scales; (2) measurement of crop residues with remote sensing; and (3) estimating regional scale soil carbon sequestration and carbon dioxide fluxes. In the second objective, innovative remote sensing methods will be used to maximize nitrogen use efficiency and crop nitrogen status, which feed into watershed-scale process models used to predict water quality. The specific goals for this objective are: (1) determine remotely sensed leaf chlorophyll content at high spatial resolutions; and (2) determine watershed nutrient budgets and evaluate the use of remote sensing data as inputs into watershed models. The third objective focuses on quantifying field-scale pesticide volatilization and the soil and climatic factors governing those emissions. Recent investigations have shown that pesticide emissions depend largely on weather and soil moisture conditions and this work will also strive to develop a model of pesticide volatilization that reproduces observed emissions and their response to these governing climatic factors. The fourth objective investigates the spread of invasive plant species and uses remote sensing as a cost-effective tool to obtain the distribution of various invasive species. This research will also investigate the utility of image texture analysis techniques for species identification, and use the classified images to test landscape-distribution models.
Research planned for this project will be conducted at a range of spatial scales from small fields to regional. Field-scale, intensive studies will be conducted at the Optimizing Production inputs for Economic and Environmental Enhancement (OPE3) site, which has extensive datasets on soils, topography, and surface and subsurface hydrology, and a long-term record of fluxes, weather, and yields. Remote sensing will be used to identify wet and dry areas at the field-scale and will be used to test the effects of soil moisture and temperature on agrichemical behavior using field data and eddy covariance techniques. Additionally, information on carbon and nutrient behavior gleaned from these field-scale studies will be extended to larger scales at two Conservation Effects Assessment Project (CEAP) watersheds: the Choptank River in Maryland and the South Fork of the Iowa River in Central Iowa. While the large watersheds have less data than the intensive site, there are many partners who are providing data to validate models and remote sensing techniques for regional scale applications. Soil organic carbon and crop residues will be measured at laboratory and field scales with high-spectral-resolution sensors. These and other satellite data will be used to test process-based models. Nitrogen status will be assessed for various crops with very-high-resolution imagery (< 1 cm pixel) so that plants and soil can be separated. The maps of nitrogen status and CEAP data will be used to evaluate the Soil and Water Assessment Tool (SWAT) water quality model. Photographs of leaves, plants, and small plots will be used to determine if image texture analysis can be used for invasive species classification. Resulting techniques will be used to plot the distribution of leafy spurge at the landscape scale, which will then be used to test the Weed Invasion Susceptibility Prediction (WISP) model.