You are here:
ASSESSING THE WATER QUALITY OF MINE-IMPACTED STREAMS USING HYPERSPECTRAL DATA
Citation:
Williams, D J. ASSESSING THE WATER QUALITY OF MINE-IMPACTED STREAMS USING HYPERSPECTRAL DATA. Presented at Above & Beyond 2001, An EPA Remote Sensing Conference, Las Vegas, NV, March 20-21, 2001.
Impact/Purpose:
The objectives of this task are to:
Assess new remote sensing technology for applicability to landscape characterization; Integrate multiple sensor systems data for improved landscape characterization;
Coordinate future technological needs with other agencies' sensor development programs;
Apply existing remote sensing systems to varied landscape characterization needs; and
Conduct remote sensing applications research for habitat suitability, water resources, and terrestrial condition indicators.
Description:
Streoan degradation by mining activities is a wide spread problem in the eastern US. Drainage from coal and ferrous metal mines can produce large quantities of sediment and acidity, which can have a deleterious impact an receiving waters. The mineralogy of these sediments is complex and the poorly crystalline nature of these minerals makes their characterization difficult. Toxic trace elements readily partition onto these minerals making the sediments a potentially hazardous material. These minerals form under predictable geochemical conditions, so by identifying the minerals residing in the streams, an estimation of the stream water quality can be made. Remote sensing can be an efficient method for landscape scale determinations of mine drainage in impacted areas. Hyperspectral data obtained by the HyMap sensor was used to analyze mine-drainage impacted waters in Ducktown, Tennessee, USA. Water and sediment samples as well as field based spectral measurements were obtained from the Ocoee River and its mine-impacted tributaries. The mineralogy of the sediment samples was determined by X-ray diffraction (XRD) and reflectance spectroscopy. Mine-drainage sediments occurring in low pH, high dissolved sulfate waters were composed of schwertmannite and goethite, while waters having near neutral pH values produced ferrihydrite. Field and laboratory reflectance spectra were used to create a spectral library database for automated image classification. The spectral signatures of the mine drainage minerals correlated to the pH of the source water (r2:: 0.87). The water quality (pH and dissolved sulfate) of the streams was then estimated by mapping the distribution of minerals occurring in the streams.