Analysis of algal bloom intensification in mid-Ganga river, India, using satellite data and neural network techniques

Abstract

River Ganga is one of the most significant rivers in the country. This river is the adobe for numerous aquatic species and microorganisms. The color of the river suddenly changed to green due to the rise of algal bloom in the Varanasi and nearby regions of the river Ganga during May–June 2021. These algal blooms can be detrimental to the aquatic animals of the river. This study analyzes the occurrence and the possible reasons for the algal bloom generation in the river for the considered stretch. Several factors like nutrient accumulation in the river through agricultural run-off, warm river temperature, low flow condition of the river, thermal stratification, and less turbid river water can be considered as possible reasons for algal bloom development. In this work, the optical remote sensing-based Sentinel 2 datasets have been used for the duration of mid-May 2021 to mid-June 2021. These datasets have been processed in the Google Earth Engine (GEE) platform, and chlorophyll concentration has been calculated using different satellite-based indices or band ratios. The chlorophyll concentration measurements have quantified the algal bloom growth. These indices or band ratios have been analyzed using several artificial neural network (ANN) architectures like multilayer perceptron (MLP) and radial basis function (RBF) along with the in situ values. It has been found that chlorophyll concentration has been highest for the mid-June 2021 time period in the considered river stretch.