*2.2. Landscape, Soil, and Weather Data*

Landscape, soil, and weather data were collected to determine differences within and between fields for each location-year. Georeferenced landscape, soil, and weather data were assembled from the center point of each sub-plot (strip-plot for Missouri locations) using ArcGIS 10.1 (ESRI, Redlands CA, USA). Sub-plot elevations (m above sea level) were collected from the National Elevation Dataset [29]. Soil water-holding capacity (volume fraction), soil organic matter (%), soil texture, soil depth (cm), field slope, and soil erosion factors were gathered from the Soil Survey Geographic (SSURGO) database [30]. Soil texture data in SSURGO were used to rank textures by coarseness—clay (finest), silt, loam, and sand (coarsest)—using the USDA soil texture calculator [31].

A soil erosion index (SEI) was created using SSURGO [30] data, USDA Revised Universal Soil Loss Equation, version 2 (RUSLE2) data [32], and a modified universal soil loss equation to account for the physical factors of the fields [24]:

$$SEI = \begin{pmatrix} KF \times LS \times R \end{pmatrix} / TF \tag{1}$$

where *KF* is an erodibility factor due to water, *LS* is a soil length (*L*) and slope steepness (*S*) factor, *R* is the rainfall and runo ff factor from USDA RUSLE2 version 2.5.2.11 [32]; and *TF* is a soil tolerance factor.

Weather was measured by temperature [33], expressed as seasonal growing degree days. To calculate seasonal growing degree days, the positive values of daily average temperature minus 15.6 ◦C was summed over 1 April through 31 October for each site-year.

#### *2.3. Fertilizer N Management Net Returns*

Net returns for the FP, VRN 1, and VRN 2 treatments were estimated using sub-plot lint yields, fertilizer N rates, lint and N fertilizer prices, and partial budgeting costs for OS and VRN technologies (Table 2). Price and budget data are in real 2013 US dollars indexed using the annual Gross Domestic Product Price Deflator Index [34]. Crop revenues were estimated by multiplying lint yields for each N managemen<sup>t</sup> treatment by the national average marketing year cotton lint price of USD 1.86 kg−<sup>1</sup> received for 2011 through 2014 [35]. EQIP cost-share payments (NRCS precision nutrient managemen<sup>t</sup> practice code number 590) for each state for 2011 through 2014 were also added to crop revenues. Estimated payments were USD 68.21 ha−<sup>1</sup> in Mississippi [36], USD 68.46 ha−<sup>1</sup> in Louisiana [37], USD 65.85 ha−<sup>1</sup> in Tennessee [38], and USD 32.64 ha−<sup>1</sup> in Missouri [39].

Fertilizer N cost of USD 0.93 kg−<sup>1</sup> was multiplied by the fertilizer N rate to determine fertilizer N cost for each N managemen<sup>t</sup> regime. The fertilizer N price is the national average marketing year fertilizer N prices received for 2011 through 2014 [40]. Following Stefanini et al. [24], budgeted skilled operator labor and equipment operating and ownership costs of USD 2.14 ha−<sup>1</sup> and USD 2.45 ha−1, respectively, for OS of the crop canopy was assumed for GreenSeeker ™ sensors retrofitted to a boom sprayer measuring 24.7 m wide. The cost of yield monitoring data identifying yield productivity zones in the field was assumed to be used to augmen<sup>t</sup> OS information for the VRN 2 prescription and had a budgeted cost of USD 2.73 ha−1. In addition, the budgeted costs of a computer to manage yield monitor data of USD 0.31 ha−<sup>1</sup> and reported cost of technical advice for incorporating yield monitor with OS information of USD 12.63 ha−<sup>1</sup> [41], respectively, were included in the total cost for VRN 2. The cost of VRN application was estimated to be USD 6.60 ha−<sup>1</sup> more than for the FP [41].
