Measuring anthropogenic impact of the ox-bow lakes in moribund Ganges deltaic India

Abstract

Measuring the anthropogenic impact score (AIS) of the ox-bow lakes in order to explore the present situation and future ways of restoration is very necessary, particularly in highly populated areas. The present work targeted to do this considering 68 contributing parameters under eight AIS constituting components like pollution impact score (PIS), habitat alteration impact score (HAIS), hydrological alteration impact score (HYAIS), landscape alteration impact score (LAIS), etc. and tried to explore the major determinants behind. Machine learning (ML) algorithms were applied for computing component level and overall, AIS. A supervised correlation attribute evaluator (CAE) was applied for detecting major determinants.The result revealed out of total 44 major ox-bow lakes 40.90 % to 59.09 % (9.97 km2 to 14.69 km2) were identified as highly impacted both at the component level and overall scale as per the best predicted Random Forest (RF) model. Hydrologically connected lakes were less impacted than isolated ones. Genetically main river (Bhagirathi-Hooghly) left ox-bow lakes are less affected than those of the off-shoot channel. Larger size lakes witnessed less impact than medium and smaller lakes. Pollution, habitat, and hydrological components were found as the most dominant components of AIS. Reclamation, pollution, and eutrophication factors were identified as the dominant factors. AIS is negatively associated with fish yield and positively associated with the livelihood vulnerability of the dependent fishermen community. Since hydrological connectivity is a big issue; maintenance of it could be a good approach to its sustainability.