A Comparison Between the Predictions from the USGS (Cohn's) Estimator Model and Data from Volume Integrated Sampling Used at Stations in the Rhode River Watersheds

My work involves testing the utility of a USGS model  (ESTIMATOR) used for predicting nutrient concentrations based on discharge (flow), season, and year.  The model works with data derived from a discontinuous sampling method known as spot, or grab, sampling.  Such sampling requires a bottled sample on which instantaneous concentration measurements are made, as well as instantaneous flow information and the date of the sample.  If the data set meets the requirements for ESTIMATOR, the model can be used to discover relationships in the data.  Once the data have been fed through the model, I extrapolate concentration simply based on flow and year.  A good model with low error could then be used to predict nutrient concentrations without the need for time consuming and expensive quantitative chemical methods to determine concentrations.  SERC has a large data set including flow and concentration, and my research uses this data to compare ESTIMATOR predictions to the continuous record that volume integrated samplers produce.  Volume integrated samplers take continuous automated readings based on stream flow over the course of a week.  Technicians collect the samples and perform the necessary quantititative analyses.  I try to fit the model to the grab and spot samples, most of which were collected in the early 1980's, and then use the results on a record of flow.  After I have a working model, I make the final comparison to the volume integrated data and record the results.  Over the course of my work I have learned a good amount about SAS statistical software and sampling techniques.

This summer I have also participated in the ground truthing of digital orthoquads.  The digital orthoquads are aerial images taken by satellite or airplane using false color photography.  In this case, false color photography uses the infrared portion of the spectrum (part of the non-visible electro magnetic spectrum) and the in the resulting images, vegetation is shown in red.  In the field we take the digital computer images as well as paper printouts and track ourselves with a laptop linked to global positioning satellites.  On the laptop the software, using the signal from the satellites, gives our position on the aerial digital map relative to agricultural plots.  We identify the plots by crop type and record our findings on the paper maps.  This information will be used to calibrate the images so that, in theory, they can be used to identify crop type in the future.