Hyperspectral remote sensing for the assessment of inland water quality can be used in enhancing the capabilities of resource managers to monitor water bodies in a timely and cost-effective manner. The key factor in assessing the accuracy of water quality assessments based on remote sensing is determining the relationships between optical indicators of water quality and remotely sensed data. The usefulness of the optical indicators may depend in large part to their applicability to interpreting data derived from multiple water bodies. The inland water quality parameters have been evaluated using both airborne and satellite-bound sensors. In 1999, a Compact Airborne Spectrographic Imager (CASI) was flown by airplane over the relatively shallow Great Miami River (GMR), Ohio, collecting hyperspectral bands of data. Corresponding water quality samples and field spectrometer data were collected directly from the river during the time of the flight. A similar study was executed in 2001 during which a CASI sensor was flown over a portion of the relatively deep Ohio River while the same types of groundtruth data were collected. Using the remotely sensed, field spectrometer and laboratory analyses data from each of these projects, spectral indices for the analysis of chlorophyll alpha, turbidity, phosphorus, and nitrogen were developed.