## 2 Materials and Methods
### Data Collection Protocol  
For Objective 1, iso-unsupervised classification with five land cover classes and four-color Infrared (CIR) bands was employed using ESRI ArcMap 10.6 and ERDAS Imagine 2016 software. A basic accuracy assessment ensured the representativeness of land cover classes. USGS EarthExplorer online portal facilitated data download, obtaining high-res NAIP imagery from May 2016 for the study area. Mosaicking was performed using ERDAS Imagine 2016, and iso-unsupervised classification with red, blue, green, and near-infrared (NIR) bands in ESRI's ArcMap 10.6 identified five land cover classes. These classes--improvious/developed, cropland, pasture/grassland, forest, and water--were determined based on pixel color values. ERDAS Imagine's \"calculate attribute statistics\" feature aided in calculating class percentages for drainage areas and the two large watersheds. The vector data (watershed boundaries, stream flow lines, drainage areas, roads, and county boundaries) were obtained from KyGeoportal and clipped to the study area. Forested and Ag watershed boundaries were defined by HUC 10 watershed units, while HUC 14 units outlined drainage areas around each stream site. Crop information in Ag watershed fields was obtained from the USDA National Agricultural Statistics Service (NASS) cropland data viewer. A natural color mosaic was created from USDA NAIP imagery, covering the entire study area, including both watersheds. USDA NAIP offers high-resolution aerial imagery captured during US growing seasons for environmental and agricultural uses [30]. The mosaic remains free from atmospheric interference, such as clouds, ensuring a clear view of the complete study area (Figure 2a). A classified raster of the entire study area was generated through the classification procedure and applied to the NAIP imagery mosaic (Figure 2b). Figure 1: Study area showing six headwater stream sites sampled within watersheds across two counties in Kentucky. The workflow, illustrated in Figure 3, provides a clear step-by-step overview of the process. For Objective 2, six headwater streams were selected: three in the agricultural watershed (Mulberry Creek, East Clear Creek, and Lutz Run Creek) and three in the forested watershed (Woodcocks Branch, Little Sixmile, and Indian Fork Creek), identified through Objective 1 results. Sampling occurred at each site three times per week (Monday, Wednes  
Figure 3: GIS workflow diagram. Figure 2: (a) Mosaic of USDA NAIP. (b) Classified raster of the study area. day, and Friday) over six months, from May to October 2018, covering the agricultural growing season. The sampling order between sites on each day was randomized using Excel 2016. A total of 463 measurements were taken, and each site was sampled approximately 74 times. Complete records for all stream sites were obtained on 75 out of 80 possible measurement days, resulting in a total of 466 measurements. Each stream had an average of 76 readings per month, contributing to a comprehensive dataset. Over the six-month period, the study area received 32.54 inches of precipitation, averaging 5.42 inches per month, according to the KY Mesonet weather station. Water quality parameters were monitored using an EPA-approved YSI ProDSS(r) Multiparameter Sampling Instrument (YSI Incorporated, Yellow Springs, OH, USA) with GPS. Optical dissolved oxygen (ODO), pH, turbidity, and total suspended solids (TSS) were taken at each site in the center of the water flow. The ProDSS was programmed to read TSS concentrations through a lab-based calibration of the turbidity sensor. Grab samples from stream sites underwent a lab analysis based on the US EPA gravimetric TSS method. Stream flow was measured using a Marsh-McBirney Flo-Mate 2000 electromagnetic flow meter (McCrometer, Inc., Hemet, CA, USA), with velocity measurements taken at each stream transect. Intervals between velocity measurements were determined by the distance between effective flow edges.