| dc.description.abstract | This article demonstrates the use of Maya, Autonomous Underwater Vehicle (AUV) for monitoring coastal waters, estuaries, rivers and dams. Maya is a mono hull structure with detachable nose and tail cones. The nose cone is mission specific, and offers the following sensor combinations: (a) dissolved oxygen and fluorometer, (b) conductivity temperature and depth, (c) hyperspectral irradiance, radiance and fluorometer. During a yoyo mission off-Goa in Nov 2006, a sensor suite (option c) was used to simultaneously measure the upwelling radiance (Lu) and down welling Irradiance (Ed) spectra, along with fluorescence Chlorophyll-a. The sampling frequency was 0.1 Hz. All sensors exhibited consistency during the various mission segments, consisting of surface, dive to 2m, cruise at 2m and accent to the surface. Maya was operated away from the mother ship, so as to decouple the optical measurements from all ship borne disturbances, like ship shadow and vibration of winch wire. Using the Ed and Lu spectra the hyperspectral remote sensing reflectance (Rrs), was derived along the mission track. Both irradiance and radiance, show an exponential decrease and increase respectively during the mission decent and assent segments. Fluorometer recorded chlorophyll-a values averaged at 0.52 ug/l. Water samples were collected along the path for estimating the Chlorophyll-a pigment using HPLC method. During another expedition at the SUPA dam in Karnataka during January 08, the spatial variations of dissolved oxygen, chlorophyll-a & backscatter was studied. A 3.3km path following, waypoint guided yoyo mission at 1m depth was executed at noon in the east to west direction. Maya was programmed to pop up for a GPS fix every 500m. A similar mission was executed at 2m depth in quick succession but in the west to east direction for a distance of 1.7km. The sensor time series outputs are presented. More recently under the biogeochemistry program, Maya was used to study the spatial (horizontal & vertical) salinity distribution in rivers and estuaries during the onset of tides. An improved path following algorithm was implemented to achieve minimal cross-track errors. Simulations carried out using hardware in loop technique for the deployment sites are presented. | |
