scholarly journals Charophytes of Gornje Podunavlje ponds: Revitalization process aspect

2019 ◽  
pp. 123-131 ◽  
Author(s):  
Ivana Trbojevic ◽  
Dragana Predojevic ◽  
Jasmina Sinzar-Sekulic ◽  
Natasa Nikolic ◽  
Ivana Jovanovic ◽  
...  
Keyword(s):  
Water Quality ◽  
Field Survey ◽  
Water Hardness ◽  
Quality Parameters ◽  
Nutrient Concentrations ◽  
Natural Ecosystem ◽  
Field Surveys ◽  
Chara Globularis ◽  
Aquatic Flora

Unique marshland area in the Danube floodplain - Special Nature Re?serve Gornje Podunavlje is considered to be one of the last aquatic flora and fauna refuges in the region. The revitalization projects in SNP Gornje Podunavlje started in 2011. They were conducted in order to protect biodiversity and to provide the natural ecosystem. The aim of this study was to investigate and compare the present diversity and distribution of the charophytes in five ponds of SNR Gornje Podunavlje, depending on phases of the revitalization process within the ponds. The researched area includes the following ponds: Semenjaca, Sarkanj, Siroki rit, Sakajtas and Ribolov. The Siroki rit pond was under the process of revitalization during the field surveys, Semenjaca and Sarkanj have already been revitalized, and Ribolov and Sakajtas were not exposed to the revitalization processes at all. The field surveys were conducted monthly, from May to September 2016. Water quality parameters were measured in situ and in laboratory. Ponds differed considerably when it comes to water chemistry; Semenjaca and Sarkanj were associated with highest nutrient concentrations, while Siroki rit was characterized by highest conductivity and water hardness. The highest diversity was found in Siroki rit pond, which was still in process of revitalization when the field survey was conducted. Charophytes were not detected within previously revitalized ponds (Semenjaca and Sarkanj). Eight species of charophytes were detected: Chara contraria, Chara globularis, Chara tenuispina, Chara vulgaris, Nitella confervacea, Nitella gracilis, Nitella syncarpa and Tolypella prolifera.

scholarly journals Evaluasi Lahan Pembudidayaan Rumput Laut di Perairan Kampung Sakabu, Pulau Salawati, Kabupaten Raja Ampat

2014 ◽  
Vol 2 (3) ◽  
Author(s):  
Wihelmina Dimara ◽  
Edwin D Ngangi ◽  
Lukas L.J.J Mondoringin
Keyword(s):  
Water Quality ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Environmental Condition ◽  
Protection Factor ◽  
Environment Factors ◽  
Research Results ◽  
Bottom Substrate ◽  
Seaweed Culture

The objective of this research was to evaluate the suitability of several environment factors and water quality parameters for development of seaweed culture in Kampung Sakabu.  The research was conducted through observation at three stations while protection factor and bottom substrate of waters were observed visually. Water quality parameters including pH, salinity, current rate, temperature were measured in situ and the compared to Standard Water Quality Citeria by Bakosurtanal 1996.  Research results were divided into three suitability categories namely 1) very suitable, 2) suitable, and 3) less suitable.  In general, environmental condition and water quatily in Kampung Sakabu were categorized as suitable to very suitable. This results indicated that         waters of Kampung Sakabu was very potential for development of seaweed culture. Keywords:  Kampung Sakabu, seaweeds, area suitability, water quality

scholarly journals Monitoring Water Quality of Valle de Bravo Reservoir, Mexico, Using Entire Lifespan of MERIS Data and Machine Learning Approaches

2020 ◽  
Vol 12 (10) ◽  
pp. 1586
Author(s):  
Leonardo F. Arias-Rodriguez ◽  
Zheng Duan ◽  
Rodrigo Sepúlveda ◽  
Sergio I. Martinez-Martinez ◽  
Markus Disse
Keyword(s):  
Machine Learning ◽  
Remote Sensing ◽  
Water Quality ◽  
Water Quality Monitoring ◽  
Temporal Variations ◽  
Quality Parameters ◽  
Parameters Estimation ◽  
Learning Approaches ◽  
Effects Of Drought

Remote-sensing-based machine learning approaches for water quality parameters estimation, Secchi Disk Depth (SDD) and Turbidity, were developed for the Valle de Bravo reservoir in central Mexico. This waterbody is a multipurpose reservoir, which provides drinking water to the metropolitan area of Mexico City. To reveal the water quality status of inland waters in the last decade, evaluation of MERIS imagery is a substantial approach. This study incorporated in-situ collected measurements across the reservoir and remote sensing reflectance data from the Medium Resolution Imaging Spectrometer (MERIS). Machine learning approaches with varying complexities were tested, and the optimal model for SDD and Turbidity was determined. Cross-validation demonstrated that the satellite-based estimates are consistent with the in-situ measurements for both SDD and Turbidity, with R2 values of 0.81 to 0.86 and RMSE of 0.15 m and 0.95 nephelometric turbidity units (NTU). The best model was applied to time series of MERIS images to analyze the spatial and temporal variations of the reservoir’s water quality from 2002 to 2012. Derived analysis revealed yearly patterns caused by dry and rainy seasons and several disruptions were identified. The reservoir varied from trophic to intermittent hypertrophic status, while SDD ranged from 0–1.93 m and Turbidity up to 23.70 NTU. Results suggest the effects of drought events in the years 2006 and 2009 on water quality were correlated with water quality detriment. The water quality displayed slow recovery through 2011–2012. This study demonstrates the usefulness of satellite observations for supporting inland water quality monitoring and water management in this region.

scholarly journals Underwater Use of a Hyperspectral Camera to Estimate Optically Active Substances in the Water Column of Freshwater Lakes

2020 ◽  
Vol 12 (11) ◽  
pp. 1745
Author(s):  
Michael Seidel ◽  
Christopher Hutengs ◽  
Felix Oertel ◽  
Daniel Schwefel ◽  
András Jung ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Quality ◽  
Water Column ◽  
Hyperspectral Imaging ◽  
Quality Parameters ◽  
Optically Active ◽  
Freshwater Lakes ◽  
Active Substances ◽  
Optically Active Substances

Freshwater lakes provide many important ecosystem functions and services to support biodiversity and human well-being. Proximal and remote sensing methods represent an efficient approach to derive water quality indicators such as optically active substances (OAS). Measurements of above-ground remote and in situ proximal sensors, however, are limited to observations of the uppermost water layer. We tested a hyperspectral imaging system, customized for underwater applications, with the aim to assess concentrations of chlorophyll a (CHLa) and colored dissolved organic matter (CDOM) in the water columns of four freshwater lakes with different trophic conditions in Central Germany. We established a measurement protocol that allowed consistent reflectance retrievals at multiple depths within the water column independent of ambient illumination conditions. Imaging information from the camera proved beneficial for an optimized extraction of spectral information since low signal areas in the sensor’s field of view, e.g., due to non-uniform illumination, and other interfering elements, could be removed from the measured reflectance signal for each layer. Predictive hyperspectral models, based on the 470 nm–850 nm reflectance signal, yielded estimates of both water quality parameters (R² = 0.94, RMSE = 8.9 µg L−1 for CHLa; R² = 0.75, RMSE = 0.22 m−1 for CDOM) that were more accurate than commonly applied waveband indices (R² = 0.83, RMSE = 13.2 µg L−1 for CHLa; R² = 0.66, RMSE = 0.25 m−1 for CDOM). Underwater hyperspectral imaging could thus facilitate future water monitoring efforts through the acquisition of consistent spectral reflectance measurements or derived water quality parameters along the water column, which has the potential to improve the link between above-surface proximal and remote sensing observations and in situ point-based water probe measurements for ground truthing or to resolve the vertical distribution of OAS.

Generation of geolocated and radiometrically corrected true reflectance surfaces in the visible portion of the electromagnetic spectrum over large bodies of water using images from a sUAS

2020 ◽  
Vol 8 (3) ◽  
pp. 172-185
Author(s):  
Juan G. Arango ◽  
Brandon K. Holzbauer-Schweitzer ◽  
Robert W. Nairn ◽  
Robert C. Knox
Keyword(s):  
Water Quality ◽  
Near Infrared ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Quality Data ◽  
Electromagnetic Spectrum ◽  
Water Quality Data ◽  
Ground Control Points ◽  
Bodies Of Water

The focus of this study was to develop true reflectance surfaces in the visible portion of the electromagnetic spectrum from small unmanned aerial system (sUAS) images obtained over large bodies of water when no ground control points were available. The goal of the research was to produce true reflectance surfaces from which reflectance values could be extracted and used to estimate optical water quality parameters utilizing limited in-situ water quality analyses. Multispectral imagery was collected using a sUAS equipped with a multispectral sensor, capable of obtaining information in the blue (0.475 μm), green (0.560 μm), red (0.668 μm), red edge (0.717 μm), and near infrared (0.840 μm) portions of the electromagnetic spectrum. To develop a reliable and repeatable protocol, a five-step methodology was implemented: (i) image and water quality data collection, (ii) image processing, (iii) reflectance extraction, (iv) statistical interpolation, and (v) data validation. Results indicate that the created protocol generates geolocated and radiometrically corrected true reflectance surfaces from sUAS missions flown over large bodies of water. Subsequently, relationships between true reflectance values and in-situ water quality parameters were developed.

SentiLake - Sentinel-2 satellite data-based service for monitoring of Latvian lakes

2020 ◽  
Author(s):  
Dainis Jakovels ◽  
Agris Brauns ◽  
Jevgenijs Filipovs ◽  
Tuuli Soomets
Keyword(s):  
Water Quality ◽  
Satellite Data ◽  
Ecological Status ◽  
Quality Parameters ◽  
Water Bodies ◽  
Water Quality Parameters ◽  
Chl A ◽  
Regular Monitoring ◽  
Sentinel 2

<p>Lakes and water reservoirs are important ecosystems providing such services as drinking water, recreation, support for biodiversity as well as regulation of carbon cycling and climate. There are about 117 million lakes worldwide and a high need for regular monitoring of their water quality. European Union Water Framework Directive (WFD) stipulates that member states shall establish a programme for monitoring the ecological status of all water bodies larger than 50 ha, in order to ensure future quality and quantity of inland waters. But only a fraction of lakes is included in in-situ monitoring networks due to limited resources. In Latvia, there are 2256 lakes larger than 1 ha covering 1.5% of Latvian territory, and approximately 300 lakes are larger than 50 ha, but only 180 are included in Inland water monitoring program, in addition, most of them are monitored once in three to six years. Besides, local municipalities are responsible for the management of lakes, and they are also interested in the assessment of ecological status and regular monitoring of these valuable assets. </p><p>Satellite data is a feasible way to monitor lakes over a large region with reasonable frequency and support the WFD status assessment process. There are several satellite-based sensors (eg. MERIS, MODIS, OLCI) available specially designed for monitoring of water quality parameters, however, they are limited only to use for large water bodies due to a coarse spatial resolution (250...1000 m/pix). Sentinel-2 MSI is a space-borne instrument providing 10...20 m/pix multispectral data on a regular basis (every 5 days at the equator and 2..3 days in Latvia), thus making it attractive for monitoring of inland water bodies, especially the small ones (<1 km<sup>2</sup>). </p><p>Development of Sentinel-2 satellite data-based service (SentiLake) for monitoring of Latvian lakes is being implemented within the ESA PECS for Latvia program. The pilot territory covers two regions in Latvia and includes more than 100 lakes larger than 50 ha. Automated workflow for selecting and processing of available Sentinel-2 data scenes for extracting of water quality parameters (chlorophyll-a and TSM concentrations) for each target water body has been developed. Latvia is a northern country with a frequently cloudy sky, therefore, optical remote sensing is challenging in or region. However, our results show that 1...4 low cloud cover Sentinel-2 data acquisitions per month could be expected due to high revisit frequency of Sentinel-2 satellites. Combination of C2X and C2RCC processors was chosen for the assessment of chl-a concentration showing the satisfactory performance - R<sup>2</sup> = 0,82 and RMSE = 21,2 µg/l. Chl-a assessment result is further converted and presented as a lake quality class. It is expected that SentiLake will provide supplementary data to limited in situ data for filling gaps and retrospective studies, as well as a visual tool for communication with the target audience.</p>

scholarly journals CoastColour Round Robin data sets: a database to evaluate the performance of algorithms for the retrieval of water quality parameters in coastal waters

2015 ◽  
Vol 7 (2) ◽  
pp. 319-348 ◽  
Author(s):  
B. Nechad ◽  
K. Ruddick ◽  
T. Schroeder ◽  
K. Oubelkheir ◽  
D. Blondeau-Patissier ◽  
...  
Keyword(s):  
Water Quality ◽  
Coastal Waters ◽  
Reference Data ◽  
Quality Parameters ◽  
Round Robin ◽  
Water Quality Parameters ◽  
Quality Data ◽  
Data Sets ◽  
Ocean Colour

Abstract. The use of in situ measurements is essential in the validation and evaluation of the algorithms that provide coastal water quality data products from ocean colour satellite remote sensing. Over the past decade, various types of ocean colour algorithms have been developed to deal with the optical complexity of coastal waters. Yet there is a lack of a comprehensive intercomparison due to the availability of quality checked in situ databases. The CoastColour Round Robin (CCRR) project, funded by the European Space Agency (ESA), was designed to bring together three reference data sets using these to test algorithms and to assess their accuracy for retrieving water quality parameters. This paper provides a detailed description of these reference data sets, which include the Medium Resolution Imaging Spectrometer (MERIS) level 2 match-ups, in situ reflectance measurements, and synthetic data generated by a radiative transfer model (HydroLight). These data sets, representing mainly coastal waters, are available from doi:10.1594/PANGAEA.841950. The data sets mainly consist of 6484 marine reflectance (either multispectral or hyperspectral) associated with various geometrical (sensor viewing and solar angles) and sky conditions and water constituents: total suspended matter (TSM) and chlorophyll a (CHL) concentrations, and the absorption of coloured dissolved organic matter (CDOM). Inherent optical properties are also provided in the simulated data sets (5000 simulations) and from 3054 match-up locations. The distributions of reflectance at selected MERIS bands and band ratios, CHL and TSM as a function of reflectance, from the three data sets are compared. Match-up and in situ sites where deviations occur are identified. The distributions of the three reflectance data sets are also compared to the simulated and in situ reflectances used previously by the International Ocean Colour Coordinating Group (IOCCG, 2006) for algorithm testing, showing a clear extension of the CCRR data which covers more turbid waters.

scholarly journals Análisis multisensor para el estudio de los patrones de turbidez en el estuario del Guadalquivir

2016 ◽  
pp. 1 ◽  
Author(s):  
I. Caballero ◽  
G. Navarro
Keyword(s):  
Water Quality ◽  
Suspended Solids ◽  
Water Quality Management ◽  
Quality Parameters ◽  
In Situ Data ◽  
Nao Index ◽  
Del Rio ◽  
Different Characteristics

<p>A detailed study of the mechanisms generated through the turbidity plume and its variability at the Guadalquivir estuary has been carried out with remote sensing and in situ data. Several sensors with different characteristics have been required (spatial, temporal and spectral resolution), thereby providing information for a multi-sensor analysis. The main objective was to determine the water quality parameters (suspended solids and chlorophyll) and implement the methodology to define the empirical and semi-analytical algorithms from satellite data (MODIS, METIS, Deimos-1). The processes occurred in the estuary and adjacent region have been examined identifying those involved in the different variability scales. The forcings associated with rainfall and discharge from Alcalá del Río dam in addition to the climatic NAO index control seasonal and inter-annual fluctuations, while tide effects (semi-daily and fortnightly cycles) modulate the plume at the mouth throughout the year with significant variability. Special emphasis is focused on diagnosing the role of these mechanisms on the continental shelf ecosystems, constituting a powerful tool for the water quality management and coastal resources.</p>

scholarly journals Water Quality Distribution in Situ Gunung Putri Bogor Regency, Indonesia

2019 ◽  
pp. 1-8
Author(s):  
Zahidah Hasan ◽  
Thoriq Ilham ◽  
Yuli Andriani ◽  
Heti Herawati ◽  
Fachmijany Sulawesty
Keyword(s):  
Water Quality ◽  
Chemical Oxygen Demand ◽  
Secchi Depth ◽  
Oxygen Demand ◽  
Aquatic Organisms ◽  
Quality Parameters ◽  
Survey Method ◽  
Optimal Range ◽  
Surface Level

The purpose of this study was to determine water quality distribution in Situ Gunung Putri. This research was conducted from February to March 2019, carried out in Situ Gunung Putri and at the Limnology Research Center of the Indonesian Institute of Sciences, both located in Bogor, West Java. The method used was the survey method. The results showed that, at the surface level, the temperature ranged between (28.14±0.52 and 30.61±1.76)°C, transparency between (0.38±0.12 and 0.65±0.06) m, dissolved oxygen (DO) was between 1.92±1.10 and 5.7± 2.55 mg / L, chemical oxygen demand (COD) was between 42.22±9.86 and 54.09±15.89, nitrate between (0.047±0.009 and 0.05±0.015) mg / L, phosphate of (0.015±0.002 and 0.022± 0.004) mg / L and pH was between 7.11± 0.27 and 7.33 ±0.34. Meanwhile at the Secchi depth values of the temperature ranged between (2.93±0.71 and 29.96 ±1.71)°C, DO was 1.14 ±0.90 and 3.37±1.63  mg / L, nitrate was 0.045±0.008 and 0.056±0.019 mg / L, phosphate was 0.016±0.003 and 0.035± 0.043 mg / L and pH was between 6.68± 0.33 and 7.11 ±0.28.  Based on these values water quality parameters except COD in  Situ Gunung Putri is still at the optimal range  for aquatic organisms.

In situ monitoring of the Sinos River, southern Brazil: water quality parameters, biomarkers, and metal bioaccumulation in fish

2018 ◽  
Vol 25 (10) ◽  
pp. 9485-9500 ◽  
Author(s):  
Thaís Dalzochio ◽  
Gabriela Zimmermann Prado Rodrigues ◽  
Leonardo Airton Ressel Simões ◽  
Mateus Santos de Souza ◽  
Ismael Evandro Petry ◽  
...  
Keyword(s):  
Water Quality ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
In Situ Monitoring ◽  
Southern Brazil ◽  
Metal Bioaccumulation

scholarly journals Near real time water quality monitoring of Chivero and Manyame lakes of Zimbabwe

2018 ◽  
Vol 378 ◽  
pp. 85-92 ◽  
Author(s):  
Ronald Muchini ◽  
Webster Gumindoga ◽  
Sydney Togarepi ◽  
Tarirai Pinias Masarira ◽  
Timothy Dube
Keyword(s):  
Water Quality ◽  
Water Quality Monitoring ◽  
Remotely Sensed ◽  
Quality Parameters ◽  
Point Sources ◽  
Water Quality Parameters ◽  
Quality Monitoring ◽  
Quality Information ◽  
Web Portal

Abstract. Zimbabwe's water resources are under pressure from both point and non-point sources of pollution hence the need for regular and synoptic assessment. In-situ and laboratory based methods of water quality monitoring are point based and do not provide a synoptic coverage of the lakes. This paper presents novel methods for retrieving water quality parameters in Chivero and Manyame lakes, Zimbabwe, from remotely sensed imagery. Remotely sensed derived water quality parameters are further validated using in-situ data. It also presents an application for automated retrieval of those parameters developed in VB6, as well as a web portal for disseminating the water quality information to relevant stakeholders. The web portal is developed, using Geoserver, open layers and HTML. Results show the spatial variation of water quality and an automated remote sensing and GIS system with a web front end to disseminate water quality information.

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