Monitoring of Turbidity Variation in the Ukai Reservoir, Gujarat, INDIA, during 1993-2018 using Landsat Series of Dataset
DOI:
https://doi.org//10.32628/IJSRST218620Keywords:
Turbidity, Ukai Reservoir, Relative Spectral Response (RSR), Landsat satellite.Abstract
Turbidity is one of the important water quality parameters, which is required to understand the eco-hydrological process such as a trophic state of water, soil erosion into the river system, mixing of other water sources, runoff, discharge etc. An algorithm has been developed to estimate the turbidity (in NTU: Nephelometric Turbidity Unit) over inland waters using Red band of optical multispectral dataset. Field measurements were carried out over Ukai reservoir for 27-28th March 2018 for pre monsoon and 27-30th September 2018 for post monsoon seasons, sampling sites ranging from turbid to clear water. Where in situ water leaving reflectance and turbidity were measured. Model was derived between in situ measured turbidity and spectral reflectance of Red band of Landsat series of datasets includes Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and Landsat 8 Operational Land Imager (OLI) data from 1993-2018. The model was applied to derive the turbidity maps of Ukai reservoir for pre-monsoon (March, April and May months) season and post monsoon (September, October and November months) seasons. Overall turbidity was in the range of 1.47-25 NTU during the field data collection for both pre and post monsoon seasons. To investigate the results in detail, the reservoir was divided into three parts, i.e. Down (A), Middle (B) and Up Streams (C). The water was relatively clear in the downstream portion with average turbidity less than 5 NTU over the study period. While maximum turbidity was observed in the upstream portion with values more than 20 NTU. In the middle portion, the turbidity values were fluctuating within the range 4-13 NTU with an average value of 6 NTU. These turbidity maps can be used to determine underwater light attenuation that has importance in ecosystem modelling.
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