<p><strong>Abstract.</strong> Aquatic macrophytes are important elements of freshwater ecosystems, fulfilling a pivotal role in the ecological functions of these environments and biogeochemical cycles. Although aquatic macrophytes are beneficial, some species can hinder human activity. They can clog reservoirs and reduce water availability for human needs. Surveys of macrophytes are hindered by logistic problems, and remote sensing represents a powerful alternative, allowing comprehensive assessment and monitoring. The objectives of this study was to map temporal changes in the macrophytes using time series multispectral dataset over Tapi River, Surat. The field trip was conducted over the Tapi River on 22nd June 2018, where <i>in-situ</i> spectral response dataset were acquired using ASD Spectroradiometer. Water samples were also collected over three locations, one before entering the city (Kamrej), second at the Sarthana water treatment plant and third at the outer end (causeway). The nutrient concentration was less before entering the city (Ammonical Nitrogen 0.056<span class="thinspace"></span>mg/L and phosphate 0.0145<span class="thinspace"></span>mg/l), while higher concentration (Ammonical Nitrogen 0.448<span class="thinspace"></span>mg/l and phosphate 0.05<span class="thinspace"></span>mg/l) was observed within the city. Maps of aquatic macrophytes fractional cover were produced using Resourcesat-2/2A (LISS-III) dataset covering a period of 2012&ndash;2018. Maximum extent was observed in February-March of every year. Although during monsoon, lot of agriculture run-off and nutrients will come into the river, but main flow of water will dilute its concentration. During summer, the same nutrient concentration will boost these macrophytes due to less availability of stream water. Within the area of 16<span class="thinspace"></span>km<sup>2</sup> between Kamrej and causeway, 3.35<span class="thinspace"></span>% was covered by macrophytes during March 2013. This area coverage increase to 36.41<span class="thinspace"></span>% in March 2018. Based on these maps, we discuss how remote sensing could support monitoring strategies and provide insight into spatial variability, and by identifying hotspot areas where invasive species could become a threat to ecosystem functioning.</p>
Turbidity is an optical determination of water clarity. It is one of the most important optically active water parameter to assess the water quality through the remote sensing observations. Turbidity measurements come from suspension of sediment such as silt or clay, inorganic materials, or organic matter such as algae, plankton and decaying material. Turbidity and total suspended matter often overlap each other. However, it is not a direct measurement of the total suspended materials in water. Instead, as a measure of relative clarity, turbidity is often used to indicate changes in the total suspended solids concentration in water without providing an exact measurement of solids. Through remote sensing we can monitor the turbidity in large water bodies, rives, coastal areas etc. An algorithm has been developed to estimate the turbidity (in NTU: Nephelometric Turbidity Unit) over inland waters (Ukai reservoir) using empirical relationship between normalized Green and Red bands (NDTI : Normalized Difference Turbidity Index) of Resourcesat-2 and Resourcsat-2A Linear Imaging Self Scanning-III (RS2 and R2A LISS-III) dataset. Derived algorithm shows a strong coefficient of determination (R2 = 0.97) with the in-situ turbidity measurements. The field measurements were carried out over Ukai reservoir on 27-28th March 2018, where synchronous in situ water leaving reflectance and turbidity were measured. Model was derived between in situ measured turbidity and NDTI derived from spectral reflectance of band 2 (Green) and band 3 (Red) of RS2 and R2A LISS-III. The model was applied to derive the turbidity maps of Ukai reservoir for pre-monsoon (March, April and May months) season during the period 2012 to 2018. Overall turbidity ranges from 1.47-20 NTU during the field data collection of pre-monsoon season and overall scene derived turbidity ranges are between 2 – 33 NTU. The highest observed turbidity value was more than fourteen times greater than the lowest value that shows the natural variability within the reservoir for the same season. Remotely sensed data sets can increase the abilities of water resources researchers and decision making persons to monitor waterbodies more effectively and frequently.
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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