A study is done to develop fluvial particle monitoring system based on application of spectral imaging, image processing and artificial neural network. Research in this field has been initiated from 2004 at Kathmandu University. This research is applied to Bagmati river which is the principal river flowing and draining across Kathmandu Valley. Fluvial particles of Bagmati River were continuously monitored at 18 different strategic locations. These samples were continuously monitored in the Lab of Machine Vision at Kathmandu University in separate pre-monsoon, monsoon and post-monsoon seasons of 2011. A lab set up equipped with image processing and spectral imaging is developed to monitor the contents of fluvial particles. The set up resembles as a river path that contains upper reservoir and lower reservoir and a special transparent flow cell fabricated in between to monitor the particles instantaneously. An application is developed to characterize the particles that run on computer using Matrox imaging Library software and Mat lab 6.5 environments. The samples were taken in standard 125 millilitre jar. It characterizes organic and inorganic according to the spectral signature of the particles trained with Artificial Neural Network. Organic particles have different signature than that of inorganic and are most distinct at 630 and 670nm wavelength. Based on these characterizing properties samples from 18 strategic locations of Baghmati rivers were characterized. Reflectance property is used to characterize particles with Perceptron neural network and hardlim as a transfer function. The result depicted that the ratio of organic to inorganic is found to be 0.1111 at upstream of Sundarijal, 0.13889 at Guyeswori and 0.16 at Chobhar according to weight basis. Chobhar is the spot with high amount of both organic and in-organic contents. According to particles count the ratio of organic to inorganic is found to be 0.02362 at upstream of Sundarijal, 0.02955 at Guyeswori and 0.034576 at Chobhar. So this result shows that this system can be applied for water particles monitoring. This system can be used to find out the socio-economic activities at different points, suitable waste-water treatment plant area, irrigation and aquatic life preservation.

Full text: IJEIR-239 FINAL.pdf