Influence of hydrological state on trophic state in dam induced seasonally inundated flood plain wetland

Abstract

A Good many research works focused on investigating wetland habitat state and trophic state (TS) but as far the knowledge is concerned, very little attention was paid to the hydrological state (HS) modelling of wetlands, and no such attention was paid on exploring the linkage between HS and TS. But it is very essential to explore the role of hydrological characters on TS in order to frame hydrological management strategies. Considering this, the present study intended to build HS models using image-driven hydrological components like water presence frequency, hydro-period, water depth; to estimate trophic state index (TSI) using field-driven water samples and, finally linking HS and TSI of the wetland. Successful results can open up a new approach to improve the strategies for water quality and ecological efficiency management. Machine learning models were applied for building the HS model and Carlson's TSI method was applied to explore water quality and ecological state. The ordinary least square regression was applied for linking HS and TSI. Results showed that hydrological modification and associated causes obliterated 32.32 km2 of wetland between the pre-dam and post-dam periods. The support vector machine model was found as the best-suited HS model to all the applied models. TSI was found poor over a wider part of the wetland, especially over the hydrologically poor patches of the wetland. The hydrological worsening is a cause for the worsening of TS. So, it can be stated that managing hydrological components is a good way to manage TS.