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Modelling Wetland Eco-hydrological state in Pressure-State-Response framework validating it using Ecosystem service potentiality approach

P. Singha,Swades Pal

Published 2021 in Unknown venue

ABSTRACT

The present study has tried to model the Eco-hydrological state of wetlands for both pre dam and post dam periods of the Lower Tangon river basin using Pressure-State-Response (PSR) framework with advanced machine learning (ML) algorithms and validated it with Ecosystem service potentiality (ESP) approach along with conventional approaches of validation. All the applied models have explored that 22.48–39.52% wetland under very good EHS zone has converted into 15.52–16.57% relatively lower category of EHS zones indicating the gradual degradation of EHS quality over wider parts of the wetland. The result of model validation has noted the acceptability of all the applied models but performance is found high in the case of REPtree and Bagging models. Expert-based ESP behaves accordingly with the EHS models. Based on the results, the study suggests using ML models for such modelling and used field-based validation approach like ESP.

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