University of Maryland, College Park, MD
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.
I found my experience at SERC to be a valuable glimpse into the world of professional research science that will undoubtedly help me decide the direction of my education and quite possibly my career. Since I study pre-med in addition to environmental science I have been interested in the field of epidemeology. Epidemeology, the study of the spread of disease across populations, merges virology, microbiology, geography, and statistics. In particular, I would like to employ remote sensing and other geographic techniques to study the spatial relationships exhibited by diseased populations. While I have many other ideas in my mind at present, the former seems to be the most noteworthy at the time.
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