OpenLB
Open Library of Bioscience

Present study has attempted to measure Water Richness (WR) and Wetland Habitat Suitability (WHS) in deltaic environment and assessed their spatial linkages. Water richness exhibits availability of water in wetland and its dynamicity, whereas wetland habitat suitability depicts physical habitat ambiance of a wetland toward vibrant ecosystem. Both the components are very essential and should be measured to explore ecosystem service and environmental heath of a region. For investigating water richness of the wetland six water availability indicating parameters have been chosen and for assessing wetland habitat suitability four additional parameters have been taken into consideration. Four widely used and recognised machine learning algorithms like Reduced Error Pruning (REP) tree, Random forest, Artificial Neural Network (ANN) and Support Vector Machine (SVM) have been employed here in order to develop suitable model at two phases. Results reveal that very high water rich zone is found over 200-215 km wetland area followed by high water rich zone over 125-140 km wetland area in both the phases. Wetland habitat suitability assessment shows only 100-150 km of the wetland having very high suitability and 110-120 km of wetland having high suitability. Field investigation and accuracy assessment support the validity and acceptability of the results. Spatial linkage between water richness and habitat suitability demonstrates that 30-40% very high water rich zone represents very high habitat suitability figuring out importance of both the models. Therefore, results recommend that only water richness of the wetlands of the wetlands is not enough to represent the habitat suitability in the densely populated riparian flood plain region.