Megan W. Lang

Water quality and conservation practice effects in the Choptank River watershed

The Choptank River is an estuary, tributary of the Chesapeake Bay, and an ecosystem in decline due partly to excessive nutrient and sediment loads from agriculture. The Conservation Effects Assessment Project for the Choptank River watershed was established to evaluate the effectiveness of conservation practices on water quality within this watershed. Several measurement frameworks are being used to assess conservation practices. Nutrients (nitrogen and phosphorus) and herbicides (atrazine and metolachlor) are monitored within 15 small, agricultural subwatersheds and periodically in the lower portions of the river estuary. Initial results indicate that land use within these subwatersheds is a major determinant of nutrient concentration in streams. In addition, the 18O isotope signature of nitrate was used to provide a landscape assessment of denitrification processes in the presence of the variable land use. Herbicide concentrations were not correlated to land use, suggesting that herbicide delivery to the streams is influenced by other factors and/or processes. Remote sensing technologies have been used to scale point measurements of best management practice effectiveness from field to subwatershed and watershed scales. Optical satellite (SPOT-5) data and ground-level measurements have been shown to be effective for monitoring nutrient uptake by winter cover crops in fields with a wide range of management practices. Synthetic Aperture Radar (RADARSAT-1) data have been shown to detect and to characterize accurately the hydrology (hydroperiod) of forested wetlands at landscape and watershed scales. These multiple approaches are providing actual data for assessment of conservation practices and to help producers, natural resource managers, and policy makers maintain agricultural production while protecting this unique estuary.

Use of Airborne Hyperspectral Imagery to Map Soil Properties in Tilled Agricultural Fields

Soil hyperspectral reflectance imagery was obtained for six tilled (soil) agricultural fields using an airborne imaging spectrometer (400–2450u2009nm, 10u2009nm resolution, 2.5u2009m spatial resolution). Surface soil samples () were analyzed for carbon content, particle size distribution, and 15 agronomically important elements (Mehlich-III extraction). When partial least squares (PLS) regression of imagery-derived reflectance spectra was used to predict analyte concentrations, 13 of the 19 analytes were predicted with , including carbon (0.65), aluminum (0.76), iron (0.75), and silt content (0.79). Comparison of 15 spectral math preprocessing treatments showed that a simple first derivative worked well for nearly all analytes. The resulting PLS factors were exported as a vector of coefficients and used to calculate predicted maps of soil properties for each field. Image smoothing with a low-pass filter prior to spectral data extraction improved prediction accuracy. The resulting raster maps showed variation associated with topographic factors, indicating the effect of soil redistribution and moisture regime on in-field spatial variability. High-resolution maps of soil analyte concentrations can be used to improve precision environmental management of farmlands.

Using satellite remote sensing to estimate winter cover crop nutrient uptake efficiency

Winter cover crops are recognized as an important agricultural conservation practice for reducing nitrogen (N) losses to groundwater following the summer growing season. Accordingly, cost-share programs have been established to promote winter cover crops for water quality on farms throughout the Chesapeake Bay watershed. However, current estimates of cover crop nutrient uptake are largely calculated from plot-scale studies extrapolated to watershed-scale based solely on enrollment acreage. Remote sensing provides a tool for rapid estimation of cover crop biomass production on working farms throughout the landscape. This project combined cost-share program enrollment data with satellite imagery and on-farm sampling to evaluate cover crop N uptake on 136 fields within the Choptank River watershed, on Marylands eastern shore. The Normalized Difference Vegetation Index was a successful predictor of aboveground biomass for fields with >210 kg ha−1 (>187 lb ac−1) of vegetation (corresponding to 4.2 kg ha−1 [3.7 lb ac−1] of plant N), below which the background reflectance of soils and crop residues obstructed the cover crop signal. Cover crops planted in the two weeks prior to the regional average first frost date (October 15) exhibited average fall aboveground N uptake rates of 18, 13, and 5 kg ha−1 (16, 12, 4 lb ac−1) for rye, barley, and wheat, respectively, corresponding to 1,260, 725, and 311 kg ha−1 (1,124, 647, 277 lb ac−1) of aboveground biomass, with associated cost-share implementation costs of

Relating nutrient and herbicide fate with landscape features and characteristics of 15 subwatersheds in the Choptank River watershed

5.49,

Distribution, Morphometry, and Land Use of Delmarva Bays

7.60, and

Sediment delivery estimates in water quality models altered by resolution and source of topographic data.

19.77 kg−1 N (

Assessing winter cover crop nutrient uptake efficiency using a water quality simulation model

2.50,

Metolachlor metabolite (MESA) reveals agricultural nitrate-N fate and transport in Choptank River watershed.

3.46, and

Impacts of Watershed Characteristics and Crop Rotations on Winter Cover Crop Nitrate-Nitrogen Uptake Capacity within Agricultural Watersheds in the Chesapeake Bay Region

8.99 lb−1 N). Cover crops planted after October 15 exhibited significantly reduced biomass and nutrient uptake, with associated program costs of

Soil physicochemical conditions, denitrification rates, and abundance in north Carolina coastal plain restored wetlands.

15.44 to