scholarly journals An UAV and Satellite Multispectral Data Approach to Monitor Water Quality in Small Reservoirs

2020 ◽  
Vol 12 (9) ◽  
pp. 1514 ◽  
Author(s):  
Carmen Cillero Castro ◽  
Jose Antonio Domínguez Gómez ◽  
Jordi Delgado Martín ◽  
Boris Alejandro Hinojo Sánchez ◽  
Jose Luis Cereijo Arango ◽  
...  
Keyword(s):  
Near Infrared ◽  
Spectral Band ◽  
Water Reservoir ◽  
Cyanobacterial Blooms ◽  
Landsat 8 ◽  
Chl A ◽  
Multispectral Data ◽  
Small Reservoirs ◽  
In Situ Data ◽  
Drinking Water Reservoir

A multi-sensor and multi-scale monitoring tool for the spatially explicit and periodic monitoring of eutrophication in a small drinking water reservoir is presented. The tool was built with freely available satellite and in situ data combined with Unmanned Aerial Vehicle (UAV)-based technology. The goal is to evaluate the performance of a multi-platform approach for the trophic state monitoring with images obtained with MultiSpectral Sensors on board satellites Sentinel 2 (S2A and S2B), Landsat 8 (L8) and UAV. We assessed the performance of three different sensors (MultiSpectral Instrument (MSI), Operational Land Imager (OLI) and Rededge Micasense) for retrieving the pigment chlorophyll-a (chl-a), as a quantitative descriptor of phytoplankton biomass and trophic level. The study was conducted in a waterbody affected by cyanobacterial blooms, one of the most important eutrophication-derived risks for human health. Different empirical models and band indices were evaluated. Spectral band combinations using red and near-infrared (NIR) bands were the most suitable for retrieving chl-a concentration (especially 2 band algorithm (2BDA), the Surface Algal Bloom Index (SABI) and 3 band algorithm (3BDA)) even though blue and green bands were useful to classify UAV images into two chl-a ranges. The results show a moderately good agreement among the three sensors at different spatial resolutions (10 m., 30 m. and 8 cm.), indicating a high potential for the development of a multi-platform and multi-sensor approach for the eutrophication monitoring of small reservoirs.

Toxic cyanobacterial blooms in a drinking water reservoir - causes, consequences and management strategy

2001 ◽  
Vol 1 (2) ◽  
pp. 237-246 ◽  
Author(s):  
M. Tarczyńska ◽  
Z. Romanowska-Duda ◽  
T. Jurczak ◽  
M. Zalewski
Keyword(s):  
Drinking Water ◽  
Management Strategies ◽  
Cyanobacterial Bloom ◽  
Water Reservoir ◽  
Dry Weight ◽  
Cyanobacterial Blooms ◽  
Potential Health ◽  
North East ◽  
Drinking Water Reservoir ◽  
Lowland Reservoirs

Eutrophication of reservoirs used for drinking water supplies is a very common problem, particularly in lowland reservoirs. Long water retention time (60-120 days) favours cyanobacterial bloom occurrence in Sulejów Reservoir, Poland. The localisation of the water intake in a bay exposed to north-east winds favoured the Microcystis bloom accumulation, which formed a 0.5 m thick dense scum for the first time in September 1999. Cyanobacterial hepatotoxins can pose a potential health problem because the presence of about 0.8 μg/l microcystins was detected in drinking water during three series of analysis. An investigation of the efficiency of each stage of water treatment processes in the elimination of microcystins showed that pre-chlorination, coagulation, and rapid sand filtration were ineffective in removing microcystins from water. Significant elimination was observed after ozonation and chlorination. The concentration of microcystins in bloom material was between 12 to 860 μg/g dry weight of phytoplankton biomass. Management strategies for reservoirs should consider the important role of ecohydrological processes, which are often very easy to regulate, and which can be useful for bio-manipulation of the water ecosystem.

scholarly journals Earth observation for monitoring and mapping of cyanobacteria blooms. Case studies on five Italian lakes

2016 ◽  
Vol 76 (s1) ◽  
Author(s):  
Mariano Bresciani ◽  
Claudia Giardino ◽  
Rosaria Lauceri ◽  
Erica Matta ◽  
Ilaria Cazzaniga ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Algal Blooms ◽  
Remote Sensing Data ◽  
Late Summer ◽  
Eutrophic Lake ◽  
Cyanobacterial Blooms ◽  
Landsat 8 ◽  
Negative Effects ◽  
Eutrophic Lakes ◽  
Chl A

Cyanobacterial blooms occur in many parts of the world as a result of entirely natural causes or human activity. Due to their negative effects on water resources, efforts are made to monitor cyanobacteria dynamics. This study discusses the contribution of remote sensing methods for mapping cyanobacterial blooms in lakes in northern Italy. Semi-empirical approaches were used to flag scum and cyanobacteria and spectral inversion of bio-optical models was adopted to retrieve chlorophyll-a (Chl-a) concentrations. Landsat-8 OLI data provided us both the spatial distribution of Chl-a concentrations in a small eutrophic lake and the patchy distribution of scum in Lake Como. ENVISAT MERIS time series collected from 2003 to 2011 enabled the identification of dates when cyanobacterial blooms affected water quality in three small meso-eutrophic lakes in the same region. On average, algal blooms occurred in the three lakes for about 5 days a year, typically in late summer and early autumn. A suite of hyperspectral sensors on air- and space-borne platforms was used to map Chl-a concentrations in the productive waters of the Mantua lakes, finding values in the range of 20 to 100 mgm-3. The present findings were obtained by applying state of the art of methods applied to remote sensing data. Further research will focus on improving the accuracy of cyanobacteria mapping and adapting the algorithms to the new-generation of satellite sensors.

scholarly journals Field Research on Mixing Aeration in a Drinking Water Reservoir: Performance and Microbial Community Structure

2019 ◽  
Vol 16 (21) ◽  
pp. 4221 ◽  
Author(s):  
Zizhen Zhou ◽  
Tinlin Huang ◽  
Weijin Gong ◽  
Yang Li ◽  
Yue Liu ◽  
...  
Keyword(s):  
Drinking Water ◽  
Microbial Community ◽  
Water Temperature ◽  
Water Reservoir ◽  
Field Research ◽  
Pollutant Removal ◽  
Chl A ◽  
Drinking Water Reservoir ◽  
Aeration System ◽  
Significant Difference

Field research on the performance of pollutant removal and the structure of the microbial community was carried out on a drinking water reservoir. After one month of operation of a water-lifting aeration system, the water temperature difference between the bottom and the surface decreased from 9.9 to 3.1 °C, and the concentration of the dissolved oxygen (DO) in the bottom layer increased from 0 to 4.2 mg/L. The existing stratification in the reservoir was successfully eliminated. Total nitrogen (TN), total phosphorus (TP), and total organic carbon (TOC) concentrations were reduced by 47.8%, 66.7%, and 22.9%, respectively. High-throughput sequencing showed that Proteobacteria, Bacteroides, and Actinomycetes accounted for 67.52% to 78.74% of the total bacterial population. Differences in the bacterial changes were observed between the enhanced area and the control area. With the operation of the water-lifting aeration system, the populations of bacteria of the main genera varied temporally and spatially. Principal component analysis pointed out a clear evolution in the vertical distribution of the microbial structure controlled by the operation of the aeration system. Permutational analysis of variance showed a significant difference in the microbial community (p < 0.01). Redundancy analysis showed that physical (water temperature, DO) and chemical environmental factors (Chl-a, TOC, TN) were the key factors affecting the changes in the microbial communities in the reservoir water. In addition, a hierarchical partitioning analysis indicated that T, Chl-a, ORP, TOC, pH, and DO accounted for 24.1%, 8.7%, 6.7%, 6.2%, 5.8%, and 5.1% of such changes, respectively. These results are consistent with the ABT (aggregated boosted tree) analysis for the variations in the functional bacterial community, and provide a theoretical basis for the development and application of biotechnology.

scholarly journals Identification of Continental Wetlands Using Different Orbital Remote Sensors

Terr Plural ◽  
2021 ◽  
Vol 15 ◽  
pp. 1-25
Author(s):  
Isadora Taborda Silva ◽  
Jéssica Rabito Chaves ◽  
Helen Rezende Figueiredo ◽  
Bruno Silva Ferreira ◽  
César Claudio Cáceres Encina ◽  
...  
Keyword(s):  
Near Infrared ◽  
Spectral Band ◽  
Landsat 8 ◽  
Remote Sensors ◽  
False Color ◽  
False Color Composite ◽  
International Importance ◽  
Color Composite ◽  
Shortwave Infrared ◽  
Sentinel 2

This paper evaluates the potential of false-color composite images, from 3 different remote sensing satellites, for the identification of continental wetlands. Landsat 8, Sentinel-2 and CBERS-4 scenes from three different Ramsar sites (i.e., sites designated to be of international importance) two sites located within the Mato-Grossense Pantanal and one within the Sul-mato-grossense were used for analyses. For each site, images from both the dry and rainy seasons were analyzed using Near-Infrared (NIR), Shortwave Infrared (SWIR), and visible (VIS) bands. The results show that false-color composite images from both the Landsat 8 and the Sentinel-2 satellites, with both SWIR 2-NIR-BLUE and NIR-SWIR-RED spectral band combinations, allow the identification of wetlands.

scholarly journals The Use of Sentinel-3 Imagery to Monitor Cyanobacterial Blooms

Environments ◽  
2019 ◽  
Vol 6 (6) ◽  
pp. 60 ◽  
Author(s):  
Igor Ogashawara
Keyword(s):  
Remote Sensing ◽  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
Lake Erie ◽  
Water Governance ◽  
Spectral Band ◽  
Cyanobacterial Blooms ◽  
Chl A ◽  
Cyanobacterial Harmful Algal Blooms ◽  
New Algorithms

Cyanobacterial harmful algal blooms (CHABs) have been a concern for aquatic systems, especially those used for water supply and recreation. Thus, the monitoring of CHABs is essential for the establishment of water governance policies. Recently, remote sensing has been used as a tool to monitor CHABs worldwide. Remote monitoring of CHABs relies on the optical properties of pigments, especially the phycocyanin (PC) and chlorophyll-a (chl-a). The goal of this study is to evaluate the potential of recent launch the Ocean and Land Color Instrument (OLCI) on-board the Sentinel-3 satellite to identify PC and chl-a. To do this, OLCI images were collected over the Western part of Lake Erie (U.S.A.) during the summer of 2016, 2017, and 2018. When comparing the use of traditional remote sensing algorithms to estimate PC and chl-a, none was able to accurately estimate both pigments. However, when single and band ratios were used to estimate these pigments, stronger correlations were found. These results indicate that spectral band selection should be re-evaluated for the development of new algorithms for OLCI images. Overall, Sentinel 3/OLCI has the potential to be used to identify PC and chl-a. However, algorithm development is needed.

scholarly journals Assessing the Potential of LAPAN-A3 Data for Landuse/landcover Mapping

2018 ◽  
Vol 50 (2) ◽  
pp. 184 ◽  
Author(s):  
Zylshal Zylshal ◽  
Rachmad Wirawan ◽  
Dony Kushardono
Keyword(s):  
Near Infrared ◽  
Agricultural Land ◽  
Reference Data ◽  
Accuracy Assessment ◽  
Bare Soil ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Radiometric Correction ◽  
Multispectral Data ◽  
Blurring Effect

LAPAN-A3 / LAPAN-IPB is the third generation of micro-satellite developed by Indonesian National Institute of Aeronautics and Space (LAPAN). The satellite carries a multispectral push-broom sensor that can record the earth's surface at the visible and near-infrared spectrum. Being launched in June 2016, there has no been many publications related to the use of LAPAN-A3 multispectral data for landuse/landcover (LULC) mapping. This paper aims to provide information regarding the use of LAPAN-A3 data for the LULC extraction maximum likelihood algorithm as well as neural network and then evaluate the results. The LAPAN-A3 image was geometrically corrected by using Landsat-8 OLI image as reference data. Three test areas with a size of 1200x945 pixels are then selected for pixel-based classification with the two aforementioned algorithms. For comparison, both LAPAN-A3 and Landsat-8 data were classified for 3 test areas. Accuracy assessment was performed on both datasets using manually interpreted SPOT-6 Pansharpened image as reference data. Preliminary results showed that LAPAN-A3 were able to extract  10 different LULC classes, comprises of built-up area, forest, rivers, fishponds, shrubs, wetland forests, rice fields, sea, agricultural land, and bare soil. The overall accuracy of LAPAN-A3 data is generally lower than Landsat-8, which ranges from 49.76% to 71.74%. These results illustrate the potential of LAPAN-A3 data to derive LULC information. The lack of necessary parameters to perform radiometric correction and blurring effect are several issues that need to be solved to improve the accuracy LULC. 

scholarly journals Seasonal Water Quality and Algal Responses to Monsoon-Mediated Nutrient Enrichment, Flow Regime, Drought, and Flood in a Drinking Water Reservoir

2021 ◽  
Vol 18 (20) ◽  
pp. 10714
Author(s):  
Md Mamun ◽  
Usman Atique ◽  
Ji Yoon Kim ◽  
Kwang-Guk An
Keyword(s):  
Water Quality ◽  
Drinking Water ◽  
Flow Regime ◽  
Nutrient Enrichment ◽  
Water Reservoir ◽  
Reservoir Water ◽  
Chl A ◽  
Drought And Flood ◽  
Drinking Water Reservoir

Freshwater reservoirs are a crucial source of urban drinking water worldwide; thus, long-term evaluations of critical water quality determinants are essential. We conducted this study in a large drinking water reservoir for 11 years (2010–2020). The variabilities of ambient nutrients and total suspended solids (TSS) throughout the seasonal monsoon-mediated flow regime influenced algal chlorophyll (Chl-a) levels. The study determined the role of the monsoon-mediated flow regime on reservoir water chemistry. The reservoir conditions were mesotrophic to eutrophic based on nitrogen (N) and phosphorus (P) concentrations. An occasional total coliform bacteria (TCB) count of 16,000 MPN per 100 mL was recorded in the reservoir, presenting a significant risk of waterborne diseases among children. A Mann–Kendall test identified a consistent increase in water temperature, conductivity, and chemical oxygen demand (COD) over the study period, limiting a sustainable water supply. The drought and flood regime mediated by the monsoon resulted in large heterogeneities in Chl-a, TCB, TSS, and nutrients (N, P), indicating its role as a key regulator of the ecological functioning of the reservoir. The ambient N:P ratio is a reliable predictor of sestonic Chl-a productivity, and the reservoir was P-limited. Total phosphorus (TP) had a strong negative correlation (R2 = 0.59, p < 0.05) with the outflow from the dam, while both the TSS (R2 = 0.50) and Chl-a (R2 = 0.32, p < 0.05) had a strong positive correlation with the outflow. A seasonal trophic state index revealed oligo-mesotrophic conditions, indicating a limited risk of eutrophication and a positive outcome for long-term management. In conclusion, the Asian monsoon largely controlled the flood and drought conditions and manipulated the flow regime. Exceedingly intensive crop farming in the basin may lead to oligotrophic nutrient enrichment. Although the reservoir water quality was good, we strongly recommend stringent action to alleviate sewage, nutrient, and pollutant inflows to the reservoir.

scholarly journals Spatial Variability Assessment on The High-resolution Chlorophyll-a Extraction from Landsat 8and Sentinel 2 Imageries in Johor Waters

2020 ◽  
Vol 2 ◽  
pp. 38-43
Author(s):  
Fatin Nabihah Syahira Ridzuan ◽  
Mohd Nadzri Md Reba ◽  
Monaliza Mohd Din ◽  
Mazlan Hashim ◽  
Po Teen Lim ◽  
...  
Keyword(s):  
High Resolution ◽  
Chlorophyll A ◽  
Spatial Resolution ◽  
Coastal Region ◽  
Water Quality Monitoring ◽  
Landsat 8 ◽  
Statistical Regression ◽  
Chl A ◽  
In Situ Data ◽  
Sentinel 2

High resolution Chlorophyll-a (Chl-a) can indicate the trophic status of the water and provide useful information on optical features of water body in water quality monitoring. Remote sensing has great potential to offer the spatial and temporal coverage needed. Over the last decades the Sea WIFS and MODIS were applied, but not suitable due to the low spatial resolution for monitoring Chl-a in coastal area. However, the retrieval of Chl-a in the coastal region is usually challenging due to the other in-water substances regardless of Chl-a, hence resulting in the satellite retrieved Chl-a overestimation. By the advancement of the Sentinel-2 and Landsat 8 satellites, continuous high resolution optical imageries have served for remarkable coastal mapping capability thanks to the spectroscopic capability certain spectral bands and as high as 10-meter spatial resolution. This paper aims to evaluate the performance of the SEADASS and SNAP processor for Chl-a estimation from the Operational Land Imager (OLI)and MultiSpectral Instrument(MSI) data in Johor waters. The representative models, in standard algorithm OC3and C2RCC, were adapted to retrieve Chl-a concentration. The statistical regression has shown that these algorithms give an acceptable Chl-a estimation at medium and high resolution with R2=0.44 from OC3and R2=0.55from C2RCC comparing to the in-situ data. Despite of the spatial, temporal and spectral variability, this paper shows that OLI and MSI could provide Chl-a mapping capability at suitable Chl-a estimation techniques.

scholarly journals The Influence of Shadow Effects on the Spectral Characteristics of Glacial Meltwater

2020 ◽  
Vol 13 (1) ◽  
pp. 36
Author(s):  
Kornelia Anna Wójcik-Długoborska ◽  
Robert Józef Bialik
Keyword(s):  
Spectral Properties ◽  
Satellite Images ◽  
Near Infrared ◽  
Spectral Band ◽  
Spectral Characteristics ◽  
High Sensitivity ◽  
Surface Model ◽  
Landsat 8 ◽  
Pixel Resolution ◽  
Ice Phenomena

The phenomenon of shadows due to glaciers is investigated in Antarctica. The observed shadow effect disrupts analyses conducted by remote sensing and is a challenge in the assessment of sediment meltwater plumes in polar marine environments. A DJI Inspire 2 drone equipped with a Zenmuse x5s camera was used to generate a digital surface model (DSM) of 6 King George Island glaciers: Ecology, Dera, Zalewski, Ladies, Krak, and Vieville. On this basis, shaded areas of coves near glaciers were traced. For the first time, spectral characteristics of shaded meltwater were observed with the simultaneous use of a Sequoia+ spectral camera mounted on a Parrot Bluegrass drone and in Landsat 8 satellite images. In total, 44 drone flights were made, and 399 satellite images were analyzed. Among them, four drone spectral images and four satellite images were selected, meeting the condition of a visible shadow. For homogeneous waters (deep, low turbidity, without ice phenomena), the spectral properties tend to change during the approach to an obstacle casting a shadow especially during low shortwave downward radiation. In this case, in the shade, the amount of radiation reflected in the green spectral band decreases by 50% far from the obstacle and by 43% near the obstacle, while in near infrared (NIR), it decreases by 42% and 21%, respectively. With highly turbid, shallow water and ice phenomena, this tendency does not occur. It was found that the green spectral band had the highest contrast in the amount of reflected radiation between nonshaded and shaded areas, but due to its high sensitivity, the analysis could have been overestimated. The spectral properties of shaded meltwater differ depending on the distance from the glacier front, which is related to the saturation of the water with sediment particles. We discovered that the pixel aggregation of uniform areas caused the loss of detailed information, while pixel aggregation of nonuniform, shallow areas with ice phenomena caused changes and the loss of original information. During the aggregation of the original pixel resolution (15 cm) up to 30 m, the smallest error occurred in the area with a homogeneous water surface, while the greatest error (over 100%) was identified in the places where the water was strongly cloudy or there were ice phenomena.

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