scholarly journals Retrieval of Turbidity on a Spatio-Temporal Scale Using Landsat 8 SR: A Case Study of the Ramganga River in the Ganges Basin, India

2020 ◽  
Vol 10 (11) ◽  
pp. 3702
Author(s):  
Mona Allam ◽  
Mohd Yawar Ali Khan ◽  
Qingyan Meng

Nowadays, space-borne imaging spectro-radiometers are exploited for many environmental applications, including water quality monitoring. Turbidity is a standout amongst the essential parameters of water quality that affect productivity. The current study aims to utilize Landsat 8 surface reflectance (L8SR) to retrieve turbidity in the Ramganga River, a tributary of the Ganges River. Samples of river water were collected from 16 different locations on 13 March and 27 November 2014. L8SR images from 6 March and 17 November 2014 were downloaded from the United States Geological Survey (USGS) website. The algorithm to retrieve turbidity is based on the correlation between L8SR reflectance (single and ratio bands) and insitu data. The b2/b4 and b2/b3 bands ratio are proven to be the best predictors of turbidity, with R2 = 0.560 (p < 0.05) and R2 = 0.726 (p < 0.05) for March and November, respectively. Selected models are validated by comparing the concentrations of predicted and measured turbidity. The results showed that L8SR is a promising tool for monitoring surface water from space, even in relatively narrow river channels, such as the Ramganga River.

2021 ◽  
Author(s):  
Stefan Krause ◽  

&lt;p&gt;It is probably hard to overestimate the significance of the River Ganges for its spiritual, cultural and religious importance. As the worlds&amp;#8217; most populated river basin and a major water resource for the 400 million people inhabiting its catchment, the Ganges represents one of the most complex and stressed river systems globally. This makes the understanding and management of its water quality an act of humanitarian and geopolitical relevance. Water quality along the Ganges is critically impacted by multiple stressors, including agricultural, industrial and domestic pollution inputs, a lack and failure of water and sanitation infrastructure, increasing water demands in areas of intense population growth and migration, as well as the severe implications of land use and climate change. Some aspects of water pollution are readily visualised as the river network evolves, whilst others contribute to an invisible water crisis (Worldbank, 2019) that affects the life and health of hundreds of millions of people.&lt;/p&gt;&lt;p&gt;We report the findings of a large collaborative study to monitor the evolution of water pollution along the 2500 km length of the Ganges river and its major tributaries that was carried out over a six-week period in Nov/Dec 2019 by three teams of more than 30 international researchers from 10 institutions. Surface water and sediment were sampled from more than 80 locations along the river and analysed for organic contaminants, nutrients, metals, pathogen indicators, microbial activity and diversity as well as microplastics, integrating in-situ fluorescence and UV absorbance optical sensor technologies with laboratory sample preparation and analyses. Water and sediment samples were analysed to identify the co-existence of pollution hotspots, quantify their spatial footprint and identify potential source areas, dilution, connectivity and thus, derive understanding of the interactions between proximal and distal of sources solute and particulate pollutants.&lt;/p&gt;&lt;p&gt;Our results reveal the co-existence of distinct pollution hotspots for several contaminants that can be linked to population density and land use in the proximity of sampling sites as well as the contributing catchment area. While some pollution hotspots were characterised by increased concentrations of most contaminant groups, several hotspots of specific pollutants (e.g., microplastics) were identified that could be linked to specific cultural and religious activities. Interestingly, the downstream footprint of specific pollution hotspots from contamination sources along the main stem of the Ganges or through major tributaries varied between contaminants, with generally no significant downstream accumulation emerging in water pollution levels, bearing significant implications for the spatial reach and legacy of pollution hotspots. Furthermore, the comparison of the downstream evolution of multi-pollution profiles between surface water and sediment samples support interpretations of the role of in-stream fate and transport processes in comparison to patterns of pollution source zone activations across the channel. In reporting the development of this multi-dimensional pollution dataset, we intend to stimulate a discussion on the usefulness of large river network surveys to better understand the relative contributions, footprints and impacts of variable pollution sources and how this information can be used for integrated approaches in water resources and pollution management.&lt;/p&gt;


2020 ◽  
Vol 27 (34) ◽  
pp. 42582-42599 ◽  
Author(s):  
Md. Morshedul Haque ◽  
Nahin Mostofa Niloy ◽  
Omme K. Nayna ◽  
Konica J. Fatema ◽  
Shamshad B. Quraishi ◽  
...  

2016 ◽  
Vol 24 (2) ◽  
pp. 122-131 ◽  
Author(s):  
G.A. Gagnon ◽  
W. Krkosek ◽  
L. Anderson ◽  
E. McBean ◽  
M. Mohseni ◽  
...  

A review of available literature and current governance approaches related to the potential impacts of hydraulic fracturing on water quality (including drinking water) was developed. The paper identifies gaps in literature and (or) current governance approaches that should be addressed to guide decision-makers in the development of appropriate regulatory regimes that will enable assessment of the impacts of hydraulic fracturing on water quality. The lack of credible and comprehensive data are shown to have been a major setback to properly investigate and monitor hydraulic fracturing activities and their potential risks on the environment and water quality. A review of current governance approaches demonstrates that some jurisdictions have implemented baseline and post-operation water quality monitoring requirements; however, there are large variations in site-specific monitoring requirements across Canada and the United States. In light of recent information, a targeted approach is suggested based on risk priorities, which can prioritize sample collection and frequency, target contaminants, and the needed duration of the sampling. The steps outlined in this review help to interface with the public concerns associated with water quality, and appropriately ensure that public health is protected through appropriate water safety planning.


2021 ◽  
Author(s):  
Md Shajedul Islam ◽  
Md. Golam Mostafa

Abstract Groundwater is a vital source of irrigation water, and it provides over 80% of the irrigated water supply in Bangladesh. The study aimed to assess the status of irrigation water of the Ganges river basin areas in the middle-west part of Bangladesh through the hydrogeochemical characterization and classification of groundwater. The study parameters were pH, EC, TDS, Ca2+, Mg2+, total hardness, Na+, K+, B, Cl−, HCO3 −, SO 42−, NO3 −, and PO43− along with irrigation water quality index (IWQindex), Na%, soluble sodium percentage, sodium adsorption ratio, residual sodium bicarbonate, magnesium adsorption ratio, permeability index, and Kelley’s ratio. The results showed that most of the water samples were acidic in the pre-monsoon and alkaline in the post-monsoon seasons, and the water type was Ca-HCO3. The significant geochemical process in the area determined was calcite and dolomite mineral dissolution, and there was no active cation exchange, and silicate weathering occurred. The statistical analyses showed that both the geogenic and anthropogenic sources were controlling the chemistry of the groundwater aquifers. Concerning irrigation water quality, the results revealed that all the quality parameters and IWQindex (32.04 to 45.39) were within the safety ranges, except for the EC and total hardness. The study results would be useful for future groundwater monitoring and management of the Ganges basin areas of Bangladesh part.


2021 ◽  
Vol 13 (9) ◽  
pp. 1847
Author(s):  
Abubakarr S. Mansaray ◽  
Andrew R. Dzialowski ◽  
Meghan E. Martin ◽  
Kevin L. Wagner ◽  
Hamed Gholizadeh ◽  
...  

Agricultural runoff transports sediments and nutrients that deteriorate water quality erratically, posing a challenge to ground-based monitoring. Satellites provide data at spatial-temporal scales that can be used for water quality monitoring. PlanetScope nanosatellites have spatial (3 m) and temporal (daily) resolutions that may help improve water quality monitoring compared to coarser-resolution satellites. This work compared PlanetScope to Landsat-8 and Sentinel-2 in their ability to detect key water quality parameters. Spectral bands of each satellite were regressed against chlorophyll a, turbidity, and Secchi depth data from 13 reservoirs in Oklahoma over three years (2017–2020). We developed significant regression models for each satellite. Landsat-8 and Sentinel-2 explained more variation in chlorophyll a than PlanetScope, likely because they have more spectral bands. PlanetScope and Sentinel-2 explained relatively similar amounts of variations in turbidity and Secchi Disk data, while Landsat-8 explained less variation in these parameters. Since PlanetScope is a commercial satellite, its application may be limited to cases where the application of coarser-resolution satellites is not feasible. We identified scenarios where PS may be more beneficial than Landsat-8 and Sentinel-2. These include measuring water quality parameters that vary daily, in small ponds and narrow coves of reservoirs, and at reservoir edges.


2018 ◽  
Vol 7 (6) ◽  
pp. 357
Author(s):  
Jose Diorgenes Alves Oliveira ◽  
Biancca Correia De Medeiros ◽  
Jhon Lennon Bezerra Da Silva ◽  
Geber Barbosa De Albuquerque Moura ◽  
Frederico Abraão Costa Lins ◽  
...  

The High Ipanema watershed is located in a semiarid region and because of this, becomes more vulnerable and susceptible to the effects of environmental changes and the degradation process, it has serious economic and socio-environmental implications. In recent years with the advancement of remote sensing based on satellite imagery or other platforms, it has become possible to monitor different and large areas of the various biomes in the world. The objective of this study was to identify changes in the vegetation cover conditions in the Alto Ipanema watershed, using spectral analyzes of Landsat-8 OLI / TIRS satellite images, using remote sensing techniques. Landsat-8 OLI / TIRS satellite images were obtained from the United States Geological Survey – USGS, on 10/12/2013, 14/01/2015 and 12/08/2016, where they were processed from ERDAS IMAGINE® Software, version 9.1. The thematic maps of biophysical parameters were processed by ArcGis® 10.2.2 Software. With the biophysical parameters analyzed, it was found that the northwest portion of the watershed presents a considerable area of exposed soils with indication of a high degree of susceptibility to degradation and that the biophysical parameters evaluated by the SEBAL algorithm are efficient in understanding the dynamics of spatial and temporal areas of semiarid environments.


Author(s):  
P. Šádek ◽  
J. Struhár

<p><strong>Abstract.</strong> With the growing population, there is a growing demand for quality drinking water. Especially in developing parts of the world, this is a serious problem. The aim of this work is to test remote sensing methods for water quality monitoring. The presented part of the project is focused on introducing the process of water pollution assessment using vegetation indices, which are derived only using RGB images. Water quality monitoring is based on satellite imagery Landsat 8 and UAV images Phantom 3. As reference data was used in-site measurements in profiles points. In-site measurements were repeated every month in the vegetation period from April to September. Based on regression analysis, the equation for the calculation of the amount of chlorophyll and the statistical evaluation of the quality of these equations is derived for each vegetation index. The best results were achieved using the ratio aquatic vegetation index (RAVI) and ExG (Excess green) indices of 97% and 96.8% respectively.</p>


Author(s):  
John Dwyer ◽  
David Roy ◽  
Brian Sauer ◽  
Calli Jenkerson ◽  
Hankui Zhang ◽  
...  

Data that have been processed to allow analysis with a minimum of additional user effort are often referred to as Analysis Ready Data (ARD). The ability to perform large scale Landsat analysis relies on the ability to access observations that are geometrically and radiometrically consistent, and have had non-target features (clouds) and poor quality observations flagged so that they can be excluded. The United States Geological Survey (USGS) has processed all of the Landsat 4 and 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) archive over the conterminous United States (CONUS), Alaska, and Hawaii, into Landsat ARD. The ARD are available to significantly reduce the burden of pre-processing on users of Landsat data. Provision of pre-prepared ARD is intended to make it easier for users to produce Landsat-based maps of land cover and land-cover change and other derived geophysical and biophysical products. The ARD are provided as tiled, georegistered, top of atmosphere and atmospherically corrected products defined in a common equal area projection, accompanied by spatially explicit quality assessment information, and


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