POTENTIAL IMPACT OF WATER QUALITY AND HYDROLOGY ON FISH COMMUNITY IN UPPER MALWATHU OYA, SRI LANKA..

The Malwathu Oya is one of Sri Lanka's largest river basins. Due to changes in weather conditions in the river's watershed, the river's discharge varies throughout the year. Anthropogenic activities in the area have also impacted the quality of the water. The ichthyofauna in this fluvial environment can be affected by changes in water's hydrological and physiochemical factors. The goal of this study was to determine the relationships between fish species richness and Shannon diversity index in the upper Malwathu Oya in relation to five physicochemical factors (nitrate, phosphate, chloride, dissolved oxygen, and temperature) and two hydrological factors (River width and discharge). Over the course of two years, the study was conducted at twelve different sampling sites. Fish, water samples, and hydrological indicators were all monitored on a regular basis. The relationships between individual physicochemical parameters and hydrological factors, as well as species richness and Shannon index, were investigated using linear regression. Species richness was found to have significant positive associations with chloride (r2=0.12), nitrate (r2=0.39), phosphate (r2=0.16), dissolved oxygen (r2=0.15), and river width (r2=0.07). Chloride (r2=0.11), nitrate (r2=0.33), phosphate (r2=0.14), dissolved oxygen (r2=0.16), and river width (r2=0.20) all had substantial positive correlations with the Shannon index. Temperature, on the other hand, had a significant (P0.0001) inverse relationship with species richness and Shannon index. The width of the river widens as the discharge rises. There was no evidence of a significant linear relationship between species richness and river width, river discharge and species richness, or river discharge and Shannon index. Despite this, there was a strong linear association between Shannon index and river width (P0.02). With a total R2 of 48.7%, the results of the multiple linear regression revealed that only three variables (nitrate, chloride, and temperature) were significant to the model.

Please see the link :- https://www.ikprress.org/index.php/JOGEE/article/view/481