Temporal Investigation of Chlorophyll-A in the Bhimgoda Barrage and Wetland Landscape Using Remote Sensing and GIS

Variability in the spatial and seasonal distribution of chlorophyll-a (Chl-a) concentration and turbidity with the evolving landscape can be easily identified in the visible region of the electromagnetic spectrum across the global inland water bodies. These water bodies are commonly associated with socioeconomic importance concerning multipurpose schemes for humanity and socio-environmental balance. The present study is an attempt to map the chlorophyll-a (Chl-a) concentration with the turbidity status and the change detection analysis of the Bhimgoda wetland using multispectral datasets acquired over the region for the period from 2016 to 2019. For the estimation of chlorophyll-a concentration, fluorescence line height (FLH)-violet and Normalized difference chlorophyll index (NDCI) and for turbidity visualization Normalized Difference Turbidity Index (NDTI) satellite reflectance-based algorithm were performed using Sentinel-2A (S2A) imageries. Indices like Normalized Difference Water Index (NDWI), Normalized Difference Vegetation Index (NDVI), and supervised classification were used in the extraction of water mask and identification of the landscape feature classes namely, water bodies, sediment, wetland marsh/swamp area, and wetland forest/vegetation in the region of interest. During the study period, the concentration of chlorophyll-a exhibited an increase from the pre-February 2016 period to the post-February 2016 period, with the maximum concentration occurring in the latter. In the year 2017, the values of the fluorescence line height (FLH) and normalized difference chlorophyll index (NDCI) showed a slightly higher value in the pre-datasets. However, between the years 2017 and 2019, a decreasing trend was observed in the maximum values of both NDCI and FLH for both pre- and post-datasets. Therefore, it is concluded that multi-spectral band indices are promising and applicable techniques useful in the satellite-based remote monitoring of water quality from space for the areas where the conventional data are limited and difficult to access.