Journal articles: 'Inland water quality'

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Yoshida, Tokuhisa. "Water quality conservation in Seto Inland Sea." Japan journal of water pollution research 8, no. 7 (1985): 398–401. http://dx.doi.org/10.2965/jswe1978.8.398.

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Jozić, Slaven, Vanja Baljak, Arijana Cenov, Dražen Lušić, Dominik Galić, Marin Glad, Daniel Maestro, et al. "Inland and Coastal Bathing Water Quality in the Last Decade (2011–2020): Croatia vs. Region vs. EU." Water 13, no. 17 (September 5, 2021): 2440. http://dx.doi.org/10.3390/w13172440.

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Europe is one of the leading tourist destinations where tourism is one of the key economic sectors. The quality of bathing waters is a very important factor when choosing a vacation destination. Croatia recognized this early and was one of the first Mediterranean countries to start systematic monitoring of bathing waters. On the other hand, monitoring of inland bathing waters is relatively new and includes a much smaller number of sites (41) compared to coastal waters (894). The aim of this paper was to summarize and analyze the water quality of inland and coastal bathing sites of Croatia, closer regions (non-EU Member States) and in the EU for the last decade. The share of excellent water quality in EU Member States increased by 10.1% and 6.6% for inland and coastal waters, respectively (2011–2020). Germany recorded the highest proportion of excellent water quality for inland waters (92.2%) and Cyprus for coastal waters (99.3%). Looking at the 10-year average of the proportion of bathing waters with excellent quality, the proportion of coastal bathing sites exceeds that of inland waters by 7.1%. It is clear that additional efforts should be made to improve the management and monitoring of inland waters.

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Falconer, Roger A. "Flow and water quality modelling in coastal and inland water." Journal of Hydraulic Research 30, no. 4 (July 1992): 437–52. http://dx.doi.org/10.1080/00221689209498893.

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Ma, Ting, Na Zhao, Yong Ni, Jiawei Yi, John P. Wilson, Lihuan He, Yunyan Du, et al. "China’s improving inland surface water quality since 2003." Science Advances 6, no. 1 (January 2020): eaau3798. http://dx.doi.org/10.1126/sciadv.aau3798.

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Increased human activity threatens inland water quality in China. Major efforts have been made to alleviate water pollution since 2001. Understanding how water quality responds to these forces can help to guide future efforts to maintain water security and sustainability. We here analyzed the nationwide variability of inland water quality across China from 2003 to 2017 and its responses to anthropogenic discharges. We show that water quality has been improved markedly or was maintained at favorable levels over the country because of reduced discharges in the industrial, rural, and urban residential sectors. However, growing discharges from the agricultural sector threaten these gains. Moreover, the present status of water pollution is relatively severe in north and northeast China. Our findings suggest that China’s water quality would further benefit from more flexible strategies for mitigation measures, which respond to regional differences in the factors that influence water pollution levels in specific regions.

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Michel, Jacqueline, and Mark Ploen. "Options for Minimizing Environmental Impacts of Inland Spill Response: New Guide From the American Petroleum Institute." International Oil Spill Conference Proceedings 2017, no. 1 (May 1, 2017): 1770–83. http://dx.doi.org/10.7901/2169-3358-2017.1.1770.

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ABSTRACT 2017-054 The 2016 American Petroleum Institute inland guide incorporates lessons learned from spill responses that can minimize the environmental impacts of inland oil spills. In addition, it provides new information on the changing risk profiles of inland spills in North America. such as the increase in oil transportation by rail, the added risks of fire and air quality concerns from spills of very light crude oils from light tight shale production areas, behavior of diluted bitumen products when spilled to fresh water, and special considerations for inland spill response. Best practices for inland oil spill response are organized by Oil Groups 1–4 and Group 5 submerged oil (oil that is suspended in the water column or moving along the bottom). It provided guidance on selecting appropriate cleanup endpoints for inland spills. Finally, it provides response guidelines for issues of special concern for inland spills, including: protection of water intakes, response to spills of ethanol-blended fuels, air quality monitoring and levels of concern, oil field produced waters, treatment of oiled debris, and fast-water booming strategies.

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El Serafy, Ghada Y. H., Blake A. Schaeffer, Merrie-Beth Neely, Anna Spinosa, Daniel Odermatt, Kathleen C. Weathers, Theo Baracchini, et al. "Integrating Inland and Coastal Water Quality Data for Actionable Knowledge." Remote Sensing 13, no. 15 (July 23, 2021): 2899. http://dx.doi.org/10.3390/rs13152899.

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Water quality measures for inland and coastal waters are available as discrete samples from professional and volunteer water quality monitoring programs and higher-frequency, near-continuous data from automated in situ sensors. Water quality parameters also are estimated from model outputs and remote sensing. The integration of these data, via data assimilation, can result in a more holistic characterization of these highly dynamic ecosystems, and consequently improve water resource management. It is becoming common to see combinations of these data applied to answer relevant scientific questions. Yet, methods for scaling water quality data across regions and beyond, to provide actionable knowledge for stakeholders, have emerged only recently, particularly with the availability of satellite data now providing global coverage at high spatial resolution. In this paper, data sources and existing data integration frameworks are reviewed to give an overview of the present status and identify the gaps in existing frameworks. We propose an integration framework to provide information to user communities through the the Group on Earth Observations (GEO) AquaWatch Initiative. This aims to develop and build the global capacity and utility of water quality data, products, and information to support equitable and inclusive access for water resource management, policy and decision making.

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Ogashawara, Igor, and Max Moreno-Madriñán. "Improving Inland Water Quality Monitoring through Remote Sensing Techniques." ISPRS International Journal of Geo-Information 3, no. 4 (November 14, 2014): 1234–55. http://dx.doi.org/10.3390/ijgi3041234.

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Julian, Jason P., Robert J. Davies-Colley, Charles L. Gallegos, and Trung V. Tran. "Optical Water Quality of Inland Waters: A Landscape Perspective." Annals of the Association of American Geographers 103, no. 2 (March 2013): 309–18. http://dx.doi.org/10.1080/00045608.2013.754658.

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Sokhi, R. "Inland and coastal water quality '93 — measurement and modelling." Environment International 21, no. 2 (1995): 109. http://dx.doi.org/10.1016/0160-4120(95)00016-x.

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Waara, K. O., A. Petersen, T. Lanaras, V. Paulauskas, S. Kleiven, G. Crosa, O. P. Penttinen, et al. "Inland Water Quality Assessment - A Joint European Masters Programme." Journal of Science Education and Technology 15, no. 5-6 (November 17, 2006): 409–15. http://dx.doi.org/10.1007/s10956-006-9032-4.

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Vannevel, Rudy, Dimitri Brosens, Ward De Cooman, Wim Gabriels, Frank Lavens, Joost Mertens, and Bart Vervaeke. "The inland water macro-invertebrate occurrences in Flanders, Belgium." ZooKeys 759 (May 22, 2018): 117–36. http://dx.doi.org/10.3897/zookeys.759.24810.

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The Flanders Environment Agency (VMM) has been performing biological water quality assessments on inland waters in Flanders (Belgium) since 1989 and sediment quality assessments since 2000. The water quality monitoring network is a combined physico-chemical and biological network, the biological component focusing on macro-invertebrates. The sediment monitoring programme produces biological data to assess the sediment quality. Both monitoring programmes aim to provide index values, applying a similar conceptual methodology based on the presence of macro-invertebrates. The biological data obtained from both monitoring networks are consolidated in the VMM macro-invertebrates database and include identifications at family and genus level of the freshwater phyla Coelenterata, Platyhelminthes, Annelida, Mollusca, and Arthropoda. This paper discusses the content of this database, and the dataset published thereof: 282,309 records of 210 observed taxa from 4,140 monitoring sites located on 657 different water bodies, collected during 22,663 events. This paper provides some background information on the methodology, temporal and spatial coverage, and taxonomy, and describes the content of the dataset. The data are distributed as open data under the Creative Commons CC-BY license.

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Malthus, Tim J., Renee Ohmsen, and Hendrik J. van der Woerd. "An Evaluation of Citizen Science Smartphone Apps for Inland Water Quality Assessment." Remote Sensing 12, no. 10 (May 15, 2020): 1578. http://dx.doi.org/10.3390/rs12101578.

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Rapid and widespread monitoring of inland and coastal water quality occurs through the use of remote sensing and near-surface water quality sensors. A new addition is the development of smartphone applications (Apps) to measure and record surface reflectance, water color and water quality parameters. In this paper, we present a field study of the HydroColor (HC, measures RGB reflectance and suspended particulate matter (SPM)) and EyeOnWater (EoW, determines the Forel–Ule scale—an indication to the visual appearance of the water surface) smartphone Apps to evaluate water quality for inland waters in Eastern Australia. The Brisbane river, multiple lakes and reservoirs and lagoons in Queensland and New South Wales were visited; hyperspectral reflection spectra were collected and water samples were analysed in the laboratory as reference. Based on detailed measurements at 32 sites, covering inland waters with a large range in sediment and algal concentrations, we find that both water quality Apps are close, but not quite on par with scientific spectrometers. EoW is a robust application that manages to capture the color of water with accuracy and precision. HC has great potential, but is influenced by errors in the observational procedure and errors in the processing of images in the iPhone. The results show that repeated observations help to reduce the effects of outliers, while implementation of camera response functions and processing should help to reduce systematic errors. For both Apps, no universal conversion to water quality composition is established, and we conclude that: (1) replicated measurements are useful; (2) color is a reliable monitoring parameter in its own right but it should not be used for other water quality variables, and; (3) tailored algorithms to convert reflectance and color to composition could be developed for lakes individually.

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Moses, Wesley J., and W. David Miller. "Editorial for the Special Issue “Remote Sensing of Water Quality”." Remote Sensing 11, no. 18 (September 19, 2019): 2178. http://dx.doi.org/10.3390/rs11182178.

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Uddin Sarker, Mohammad Khabir, Ahmad Kamruzzaman Majumder, Md Zahurul Haque, Md Sahadat Hossain, and Abdullah Al Nayeem. "ASSESSMENT OF INLAND WATER QUALITY PARAMETERS OF DHAKA CITY, BANGLADESH." Environment & Ecosystem Science 3, no. 1 (January 2, 2019): 13–16. http://dx.doi.org/10.26480/ees.01.2019.13.16.

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Kim, Tae-Woo, Han-Sup Shin, and Yong-Cheol Suh. "Airborne Hyperspectral Imagery availability to estimate inland water quality parameter." Korean Journal of Remote Sensing 30, no. 1 (February 28, 2014): 61–73. http://dx.doi.org/10.7780/kjrs.2014.30.1.6.

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Cimdinš, P., and M. Klavinš. "Water quality and species diversity of inland waters in Latvia." SIL Proceedings, 1922-2010 26, no. 3 (March 1998): 1209–11. http://dx.doi.org/10.1080/03680770.1995.11900911.

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Debén, S., J. R. Aboal, A. Carballeira, M. Cesa, C. Real, and J. A. Fernández. "Inland water quality monitoring with native bryophytes: A methodological review." Ecological Indicators 53 (June 2015): 115–24. http://dx.doi.org/10.1016/j.ecolind.2015.01.015.

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Gitelson, A., F. Szilagyi, and K. H. Mittenzwey. "Improving quantitative remote sensing for monitoring of inland water quality." Water Research 27, no. 7 (July 1993): 1185–94. http://dx.doi.org/10.1016/0043-1354(93)90010-f.

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Wang, Linhui, Xuejun Yue, Huihui Wang, Kangjie Ling, Yongxin Liu, Jian Wang, Jinbao Hong, Wen Pen, and Houbing Song. "Dynamic Inversion of Inland Aquaculture Water Quality Based on UAVs-WSN Spectral Analysis." Remote Sensing 12, no. 3 (January 26, 2020): 402. http://dx.doi.org/10.3390/rs12030402.

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The inland aquaculture environment is an artificial ecosystem, where the water quality is a key factor which is closely related to the economic benefits of inland aquaculture and the quality of aquatic products. Compared with marine aquaculture, inland aquaculture is normally smaller and susceptible to pollution, with poor self-purification capacity. Considering its low cost and large-scale monitoring ability, many researches have developed spectrum sensor on-board satellite platforms to allow remote monitoring of inland water surface. However, there remain many problems, such as low image resolution, poor flexible data acquisition, and anti-interference. Apart from that, the conventional forecasting model is of weak generalization ability and low accuracy. In our study, we combine unmanned aerial vehicles system (UAVs) with the wireless sensor network (WSN) to design a new ground water quality parameter and drone spectrum information acquisition approach, and to propose a novel dynamic network surgery-deep neural networks (DNS-DNNs) model based on multi-source feature fusion to forecast the distribution of dissolved oxygen (DO) and turbidity (TUB) in inland aquaculture areas. The result of using fused features, including characteristic spectrum, Gray-level co-occurrence matrix (GLCM) texture feature, and convolutional neural network (CNN) texture feature to build a model is that the characteristic spectrum+ CNN texture fusion features were the best input items for DNS-DNNs when forecasting DO, with the determination coefficient R 2 of the vertical set arriving at 0.8741, while the characteristic spectrum+ GLCM texture+ CNN texture fusion features were the best for TUB, with the R 2 reaching 0.8531. Compared with a variety of conventional models, our model had a better performance in the inversion of DO and TUB, and there was a strong correlation between predicted and real values: R 2 reached 0.8042 and 0.8346, whereas the root mean square error (RMSE) were only 0.1907 and 0.1794, separately. Our study provides a new insight about using remote sensing to rapidly monitor water quality in inland aquaculture regions.

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Topp, Simon N., Tamlin M. Pavelsky, Daniel Jensen, Marc Simard, and Matthew R. V. Ross. "Research Trends in the Use of Remote Sensing for Inland Water Quality Science: Moving Towards Multidisciplinary Applications." Water 12, no. 1 (January 7, 2020): 169. http://dx.doi.org/10.3390/w12010169.

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Remote sensing approaches to measuring inland water quality date back nearly 50 years to the beginning of the satellite era. Over this time span, hundreds of peer-reviewed publications have demonstrated promising remote sensing models to estimate biological, chemical, and physical properties of inland waterbodies. Until recently, most of these publications focused largely on algorithm development as opposed to implementation of those algorithms to address specific science questions. This slow evolution contrasts with terrestrial and oceanic remote sensing, where methods development in the 1970s led to publications focused on understanding spatially expansive, complex processes as early as the mid-1980s. This review explores the progression of inland water quality remote sensing from methodological development to scientific applications. We use bibliometric analysis to assess overall patterns in the field and subsequently examine 236 key papers to identify trends in research focus and scale. The results highlight an initial 30 year period where the majority of publications focused on model development and validation followed by a spike in publications, beginning in the early-2000s, applying remote sensing models to analyze spatiotemporal trends, drivers, and impacts of changing water quality on ecosystems and human populations. Recent and emerging resources, including improved data availability and enhanced processing platforms, are enabling researchers to address challenging science questions and model spatiotemporally explicit patterns in water quality. Examination of the literature shows that the past 10–15 years has brought about a focal shift within the field, where researchers are using improved computing resources, datasets, and operational remote sensing algorithms to better understand complex inland water systems. Future satellite missions promise to continue these improvements by providing observational continuity with spatial/spectral resolutions ideal for inland waters.

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Miranda, Rafael, Virgilio Hermoso, and Christopher Hassall. "Ecological quality and conservation status of inland waters." Inland Waters 9, no. 3 (July 3, 2019): 275–77. http://dx.doi.org/10.1080/20442041.2019.1645548.

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Pásler, M., and J. Komárková. "UTILIZATION OF LANDSAT DATA FOR WATER QUALITY OBSERVATION IN SMALL INLAND WATER BODIES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B8 (June 23, 2016): 373–77. http://dx.doi.org/10.5194/isprsarchives-xli-b8-373-2016.

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Many studies deal with water quality evaluation using remotely sensed data. In the field of remote sensing, there have been proposed several procedures how to observe selected parameters of water quality and conditions. The majority of works use methods and procedures based on satellite data but they usually do not deal with suitability and practicability of the satellite data. This paper provides summary of determinants and limitations of satellite data utilization for water quality evaluation. Cloud cover and its influence on size of visible water surfaces is the most deeply evaluated determinants. Temporal resolution, spatial resolution and some other technical factors are discussed as next determinants. The case study demonstrates evaluation of the determinants for Landsat 7 and Landsat 8 data (level 1) and for area of small ponds in part of Pardubice region in the Czech Republic. It clearly demonstrates several limitations of Landsat data for evaluation of selected parameters of water quality and changes of small water bodies.

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MURAKAMI, Keigo, Haruo SASANUMA, Jiro KOYAMA, Norio KOBAYASHI, and Mitsuei HIRAYAMA. "Water quality formation of inland water in drainage basin of Lake Chuzenji, Nikko." Japanese Journal of Limnology (Rikusuigaku Zasshi) 48, no. 4 (1987): 295–306. http://dx.doi.org/10.3739/rikusui.48.295.

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Pásler, M., and J. Komárková. "UTILIZATION OF LANDSAT DATA FOR WATER QUALITY OBSERVATION IN SMALL INLAND WATER BODIES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B8 (June 23, 2016): 373–77. http://dx.doi.org/10.5194/isprs-archives-xli-b8-373-2016.

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Many studies deal with water quality evaluation using remotely sensed data. In the field of remote sensing, there have been proposed several procedures how to observe selected parameters of water quality and conditions. The majority of works use methods and procedures based on satellite data but they usually do not deal with suitability and practicability of the satellite data. This paper provides summary of determinants and limitations of satellite data utilization for water quality evaluation. Cloud cover and its influence on size of visible water surfaces is the most deeply evaluated determinants. Temporal resolution, spatial resolution and some other technical factors are discussed as next determinants. The case study demonstrates evaluation of the determinants for Landsat 7 and Landsat 8 data (level 1) and for area of small ponds in part of Pardubice region in the Czech Republic. It clearly demonstrates several limitations of Landsat data for evaluation of selected parameters of water quality and changes of small water bodies.

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Leeuwen, Boudewijn van, László Henits, Minucsér Mészáros, Zalán Tobak, József Szatmári, Dragoslav Pavić, Stevan Savić, and Dragan Dolinaj. "Classification Methods for Inland Excess Water Modeling." Journal of Environmental Geography 6, no. 1-2 (April 1, 2013): 1–8. http://dx.doi.org/10.2478/v10326-012-0001-5.

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Abstract Inland excess water floodings are a common problem in the Carpathian Basin. Nearly every year large areas are covered by water due to lack of natural runoff of superfluous water. To study the development of this phenomenon it is necessary to determine where these inundations are occurring. This research evaluates different methods to classify inland excess water occurrences on a study area covering south-east Hungary and northern Serbia. The region is susceptible to this type of flooding due to its geographical circumstances. Three separate methods are used to determine their applicability to the problem. The methods use the same input data set but differ in approach and complexity. The input data set consists of a mosaic of RapidEye medium resolution satellite images. The results of the classifications show that all three methods can be applied to the problem and provide high quality satellite based inland excess water maps over a large area.

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Zhang, Wei, Shu Yan Cao, and Yu Fei Gu. "Reduction Potential of Carbon Emission from Inland Water Transportation Activities of Jiangxi Province." Advanced Materials Research 524-527 (May 2012): 3651–54. http://dx.doi.org/10.4028/www.scientific.net/amr.524-527.3651.

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Inland shipping is an important transportation mode that has increased over time in Jiangxi Province of China. CO2 emissions from inland shipping are significantly increasing and have remarkable impact on air quality. And CO2 reductions from inland waterborne transportation modes are therefore urgently required to reduce the impacts of climate change. CO2 emissions from inland shipping of Jiangxi Province are calculated by utilizing activities based energy consumption data, and potential CO2 reduciton are estimated using ASIF equation. Total emissions from inland ships of the province were estimated at 297 Mt CO2 in 2009, 3.3 times of that in 2000, and potential CO2 reduction would be in the relative range of 27% to30% in 20 15 and of 35% to 40% in 2020, compared to baseline projections of business-as-usual.

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Santiago-Rodriguez, Tasha M., Raymond L. Tremblay, Carlos Toledo-Hernandez, Joel E. Gonzalez-Nieves, Hodon Ryu, Jorge W. Santo Domingo, and Gary A. Toranzos. "Microbial Quality of Tropical Inland Waters and Effects of Rainfall Events." Applied and Environmental Microbiology 78, no. 15 (May 18, 2012): 5160–69. http://dx.doi.org/10.1128/aem.07773-11.

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ABSTRACTNovel markers of fecal pollution in tropical waters are needed since conventional methods recommended for other geographical regions may not apply. To address this, the prevalence of thermotolerant coliforms, enterococci, coliphages, and enterophages was determined by culture methods across a watershed. Additionally, human-, chicken-, and cattle-specific PCR assays were used to identify potential fecal pollution sources in this watershed. An enterococcus quantitative PCR (qPCR) assay was tested and correlated with culture methods at three sites since water quality guidelines could incorporate this technique as a rapid detection method. Various rainfall events reported before sample collection at three sites were considered in the data analyses. Thermotolerant coliforms, enterococci, coliphages, and enterophages were detected across the watershed. Human-specificBacteroidesbacteria, unlike the cattle- and chicken-specific bacteria, were detected mostly at sites with the corresponding fecal impact. Enterococci were detected by qPCR as well, but positive correlations with the culture method were noted at two sites, suggesting that either technique could be used. However, no positive correlations were noted for an inland lake tested, suggesting that qPCR may not be suitable for all water bodies. Concentrations of thermotolerant coliforms and bacteriophages were consistently lower after rainfall events, pointing to a possible dilution effect. Rainfall positively correlated with enterococci detected by culturing and qPCR, but this was not the case for the inland lake. The toolbox of methods and correlations presented here could be potentially applied to assess the microbial quality of various water types.

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Kwiatkowski, Roy E. "National Water Quality Index Network Options to Consider." Water Quality Research Journal 23, no. 4 (November 1, 1988): 476–87. http://dx.doi.org/10.2166/wqrj.1988.036.

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Abstract Canada’s federal water quality program is aimed at providing information for the management of Canada’s water resources to maximize social and economic benefits of these resources for Canadians while ensuring an adequate level of water quality. Adequate being defined as non-impairment of the most sensitive use. The extent of pollution from anthropogenically developed chemicals has become readily apparent over the last decade. As a result in recent years public anxiety about the environment particularly about water quality has increased dramatically. Water pollution issues are no longer solely restricted to the local or regional level. Issues are now discussed at the national, international and global level. As a result, the Water Quality Branch (WQB), Inland Waters Directorate, Department of the Environment, is establishing a National Water Quality Index Network, to provide scientific information and advice to water managers on water quality issues on a national scale. This paper outlines WQB’s present activities and the process used to develop the WQB’s National Water Quality Index Network.

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Tada, Kuninao, Munehiro Fujiwara, and Tsuneo Honjo. "Water Quality and Nori (Porphyra) Culture in the Seto Inland Sea." BUNSEKI KAGAKU 59, no. 11 (2010): 945–55. http://dx.doi.org/10.2116/bunsekikagaku.59.945.

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Ford, Ryan T., and Anthony Vodacek. "Determining improvements in Landsat spectral sampling for inland water quality monitoring." Science of Remote Sensing 1 (June 2020): 100005. http://dx.doi.org/10.1016/j.srs.2020.100005.

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Dekker, A. G., T. J. Malthus, and E. Seyhan. "Quantitative modeling of inland water quality for high-resolution MSS systems." IEEE Transactions on Geoscience and Remote Sensing 29, no. 1 (1991): 89–95. http://dx.doi.org/10.1109/36.103296.

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Abdelmalik, K. W. "Role of statistical remote sensing for Inland water quality parameters prediction." Egyptian Journal of Remote Sensing and Space Science 21, no. 2 (September 2018): 193–200. http://dx.doi.org/10.1016/j.ejrs.2016.12.002.

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Wei, Lifei, Yu Zhang, Can Huang, Zhengxiang Wang, Qingbin Huang, Feng Yin, Yue Guo, and Liqin Cao. "Inland Lakes Mapping for Monitoring Water Quality Using a Detail/Smoothing-Balanced Conditional Random Field Based on Landsat-8/Levels Data." Sensors 20, no. 5 (February 29, 2020): 1345. http://dx.doi.org/10.3390/s20051345.

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The sustainable development of water resources is always emphasized in China, and a set of perfect standards for the division of inland water environment quality have been established to monitor water quality. However, most of the 24 indicators that determine the water quality level in the standards are non-optically active parameters. The weak optical characteristics make it difficult to find significant correlations between the single parameters and the remote sensing imagery. In addition, traditional on-site testing methods have been unable to meet the increasingly extensive water-quality monitoring requirements. Based on the above questions, it’s meaningful that the supervised classification process of a detail-preserving smoothing classifier based on conditional random field (CRF) and Landsat-8 data was proposed in the two study areas around Wuhan and Huangshi in Hubei Province. The random forest classifier was selected to model the association potential of the CRF. The results (the first study area: OA = 89.50%, Kappa = 0.841; the second study area: OA = 90.35%, Kappa = 0.868) showed that the water-quality monitoring based on CRF model is feasible, and this approach can provide a reference for water-quality mapping of inland lakes. In the future, it may only require a small amount of on-site sampling to achieve the identification of the water quality levels of inland lakes across a large area of China.

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Niroumand-Jadidi, M., and F. Bovolo. "WATER QUALITY RETRIEVAL AND ALGAL BLOOM DETECTION USING HIGH-RESOLUTION CUBESAT IMAGERY." ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences V-3-2021 (June 17, 2021): 191–95. http://dx.doi.org/10.5194/isprs-annals-v-3-2021-191-2021.

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Abstract. Recent advancements in developing small satellites known as CubeSats provide an increasingly viable means of characterizing the dynamics of inland and nearshore waters with an unprecedented combination of high revisits (< 1 day) with a high spatial resolution (meter-scale). Estimation of water quality parameters can benefit from the very high spatiotemporal resolution of CubeSat imagery for monitoring subtle variations and identification of hazardous events like algal blooms. In this study, we present the first study on retrieving lake chlorophyll-a (Chl-a) concentration and detecting algal blooms using imagery acquired by the PlanetScope constellation which is currently the most prominent source of CubeSat data. Moreover, the concentration of total suspended matter (TSM) is retrieved that is an indicator of turbidity. The retrievals are based upon inverting the radiative transfer model. The low spectral resolution (four bands) of PlanetScope imagery poses challenges for such a physics-based inversion due to spectral ambiguities in optically-complex waters like inland waters. To deal with this issue, the number of variable parameters is minimized through inverse modeling. Given the significance of having high-quality water-leaving reflectance for physics-based models, a variable parameter (gdd) is considered to compensate for the atmospheric and sun-glint artifacts. The results compared to the in-situ data indicate high potentials of PlanetScope imagery in retrieving water quality parameters and detection of algal blooms in our case study (Lake Trasimeno, Italy).

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Kondraju, Tarun Teja, and K. S. Rajan. "Water Quality in Inland Water Bodies: Hostage to the Intensification of Anthropogenic Land Uses." Journal of the Indian Society of Remote Sensing 47, no. 11 (August 21, 2019): 1865–74. http://dx.doi.org/10.1007/s12524-019-01033-2.

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Ozbay, Gulnihal, Lathadevi Karuna Chintapenta, Talaysha Lingham, Stephen Lumor, Jung-lim Lee, Bettina Taylor, Shobha Sriharan, and Samuel Besong. "Delaware Inland Bays and Market Oyster (Crassostrea virginica) Quality for Consumption." Journal of Food Quality 2018 (June 14, 2018): 1–17. http://dx.doi.org/10.1155/2018/8765149.

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Consumption of raw oysters is known to cause serious health conditions due to bioaccumulation of contaminants. As filter feeders, oysters ingest bacteria along with phytoplankton from their surrounding habitats. Ensuring seafood safety for human consumption is always a concern. Since oysters are consumed raw, disease causing organisms, environmental contaminants, toxins, chemicals, and even physical hazards such as soils and metals retained in the oysters can enter through feeding. The objective of this study was to determine the quality of oysters collected from Delaware Inland Bays (DIB) and compare them with market oysters. Environmental parameters were monitored from local waters of DIB classified as closed versus open for shellfish harvesting. Total aerobic bacteria and vibrio were higher in market oysters during the warmer months, with open water having the least microbial loads. There were no significant differences in total vibrio counts between the study sites (p=0.396), but significant differences were recorded over time (p=0.004). Water temperature and turbidity were directly proportional to total vibrio in oysters, and salinity was inversely related. Research findings in this study may help bring awareness of changes in bacterial loads due to seasonal changes and additional handling and storage.

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Sandeep, K. P., S. P. Shukla, V. Harikrishna, A. P. Muralidhar, A. Vennila, C. S. Purushothaman, and R. Ratheesh Kumar. "Utilization of inland saline water for Spirulina cultivation." Journal of Water Reuse and Desalination 3, no. 4 (June 3, 2013): 346–56. http://dx.doi.org/10.2166/wrd.2013.102.

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An attempt was made to assess the suitability of the inland saline water of Rohtak (Haryana) for mass cultivation of Spirulina platensis, a salt loving cyanobacterium. Cultivation of S. platensis was performed in indoor and outdoor culture units. The investigation revealed that the yield of biomass in de-calcified inland saline water was comparable to the yield obtained in synthetic chemical-based prescribed growth medium. Further, the quality of biomass in terms of protein, chlorophyll a, carotenoids and phycocyanin contents was also comparable to the prescribed medium. The downstream processing of the biomass through a three-step process resulted in an appreciable quantity of a highly valuable pigment, phycocyanin (purity ratio: A620/A280 = 3.13–3.39). The overall observations of the study suggest that inland saline water can be used for cost-effective production of Spirulina biomass and value-added chemicals. The removal of calcium and salts from inland saline water by S. platensis cultivation also offers an added advantage for the reuse of the spent medium for agricultural and aquacultural purposes.

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Lee, In-cheol, Masao Ukita, Masahiko Sekine, and Hiroshi Nakanishi. "Study on the Water Quality Management in Seto Inland Sea by Using the Water and Sediment Quality Model." Doboku Gakkai Ronbunshu, no. 545 (1996): 101–12. http://dx.doi.org/10.2208/jscej.1996.545_101.

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Eugenio, Francisco, Javier Marcello, and Javier Martín. "Multiplatform Earth Observation Systems for Monitoring Water Quality in Vulnerable Inland Ecosystems: Maspalomas Water Lagoon." Remote Sensing 12, no. 2 (January 15, 2020): 284. http://dx.doi.org/10.3390/rs12020284.

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The accurate monitoring of water quality indicators, bathymetry and distribution of benthic habitats in vulnerable ecosystems is key to assessing the effects of climate change, the quality of natural areas and to guide appropriate biodiversity, tourism or fisheries policies. Coastal and inland water ecosystems are very complex but crucial due to their richness and primary production. In this context, remote sensing can be a reliable way to monitor these areas, mainly thanks to satellite sensors’ improved spatial and spectral capabilities and airborne or drone instruments. In general, mapping bodies of water is challenging due to low signal-to-noise (SNR) at sensor level, due to the very low reflectance of water surfaces as well as atmospheric effects. Therefore, the main objective of this work is to provide a robust processing framework to estimate water quality parameters in inland shallow waters using multiplatform data. More specifically, we measured chlorophyll concentrations (Chl-a) from multispectral and hyperspectral sensors on board satellites, aircrafts and drones. The Natural Reserve of Maspalomas, Canary Island (Spain), was chosen for the study because of its complexity as well as being an inner lagoon with considerable organic and inorganic matter and chlorophyll concentration. This area can also be considered a well-known coastal-dune ecosystem attracting a large amount of tourists. The water quality parameter estimated by the remote sensing platforms has been validated using co-temporal in situ measurements collected during field campaigns, and quite satisfactory results have been achieved for this complex ecosystem. In particular, for the drone hyperspectral instrument, the root mean square error, computed to quantify the differences between the estimated and in situ chlorophyll-a concentrations, was 3.45 with a bias of 2.96.

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Skerry, G. P., and J. G. Parker. "Impact of Lagoon Effluent on an Inland Stream – A 10 Year Perspective." Water Science and Technology 21, no. 2 (February 1, 1989): 289–92. http://dx.doi.org/10.2166/wst.1989.0065.

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The discharge of lagoon treated effluent to inland waterways has long been of contention in relation to the impact of residual algal cells and nutrients in the receiving water body, especially a water body used extensively for recreation. This paper examines the pre lagoon and post lagoon discharge effects on water quality in a major inland river over a ten year monitoring period. The impact of a lagoon discharge flow of up to 20 ML/day during summer conditions is assessed in relation to effect on receiving stream physical, chemical and biological water quality indicators and implications for management are assessed and evaluated.

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Soomets, Tuuli, Kristi Uudeberg, Dainis Jakovels, Agris Brauns, Matiss Zagars, and Tiit Kutser. "Validation and Comparison of Water Quality Products in Baltic Lakes Using Sentinel-2 MSI and Sentinel-3 OLCI Data." Sensors 20, no. 3 (January 29, 2020): 742. http://dx.doi.org/10.3390/s20030742.

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Inland waters, including lakes, are one of the key points of the carbon cycle. Using remote sensing data in lake monitoring has advantages in both temporal and spatial coverage over traditional in-situ methods that are time consuming and expensive. In this study, we compared two sensors on different Copernicus satellites: Multispectral Instrument (MSI) on Sentinel-2 and Ocean and Land Color Instrument (OLCI) on Sentinel-3 to validate several processors and methods to derive water quality products with best performing atmospheric correction processor applied. For validation we used in-situ data from 49 sampling points across four different lakes, collected during 2018. Level-2 optical water quality products, such as chlorophyll-a and the total suspended matter concentrations, water transparency, and the absorption coefficient of the colored dissolved organic matter were compared against in-situ data. Along with the water quality products, the optical water types were obtained, because in lakes one-method-to-all approach is not working well due to the optical complexity of the inland waters. The dynamics of the optical water types of the two sensors were generally in agreement. In most cases, the band ratio algorithms for both sensors with optical water type guidance gave the best results. The best algorithms to obtain the Level-2 water quality products were different for MSI and OLCI. MSI always outperformed OLCI, with R2 0.84–0.97 for different water quality products. Deriving the water quality parameters with optical water type classification should be the first step in estimating the ecological status of the lakes with remote sensing.

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Lougheed, Vanessa L., Barb Crosbie, and Patricia Chow-Fraser. "Primary determinants of macrophyte community structure in 62 marshes across the Great Lakes basin: latitude, land use, and water quality effects." Canadian Journal of Fisheries and Aquatic Sciences 58, no. 8 (August 1, 2001): 1603–12. http://dx.doi.org/10.1139/f01-102.

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We collected water quality, land use, and aquatic macrophyte information from 62 coastal and inland wetlands in the Great Lakes basin and found that species richness and community structure of macrophytes were a function of geographic location and water quality. For inland wetlands, the primary source of water quality degradation was inputs of nutrients and sediment associated with altered land use, whereas for coastal wetlands, water quality was also influenced by exposure and mixing with the respective Great Lakes. Wetlands within the subbasins of the less developed, more exposed upper Great Lakes had unique physical and ecological characteristics compared with the more developed, less sheltered wetlands of the lower Great Lakes and those located inland. Turbid, nutrient-rich wetlands were characterized by a fringe of emergent vegetation, with a few sparsely distributed submergent plant species. High-quality wetlands had clearer water and lower nutrient levels and contained a mix of emergent and floating-leaf taxa with a diverse and dense submergent plant community. Certain macrophyte taxa were identified as intolerant of turbid, nutrient-rich conditions (e.g., Pontederia cordata, Najas flaxilis), while others were tolerant of a wide range of conditions (e.g., Typha spp., Potamogeton pectinatus) occurring in both degraded and pristine wetlands.

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Fengjuan, Zhang, Xing Liting, Wang Song, Zhuang Huibo, Dou Tongwen, and Yang Zengyuan. "Research on Formation Mechanism of Jiyang Shallow Saline Ground Water." Open Chemical Engineering Journal 9, no. 1 (November 10, 2015): 155–60. http://dx.doi.org/10.2174/1874123101509010155.

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Shallow salt water in the inland plain has huge development potential. Taking saline water area in Sungeng Town, Jiyang County as an example, based on field water quality and water table tests., tracing test, methods such as mathematical statistical, hydrochemistry diagram of piper and numerical simulation by PHREEQC are used to analyze synthetically. 6862 groups data were studied. Results showed: (1) The groundwater presents typically “weather - evaporation” type, chemistry type is Cl.SO4-Mg.Na. and Cl.SO4-Na.Mg type. (2) In area of inland saline water presents characteristics of lagging water flow with high clay content in aquifer medium. Groundwater mineralization is obvious. (3) Hydrogeochemistry actions such as evaporation, alternate adsorption and water-rock interaction are the primary cause of the forming complex hydrochemistry type. The unique groundwater circulation characteristics of inland plains saltwater area makes water dynamic being relatively stable.

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Deng, Liang, Fang Zhen Song, Ming Ming Li, Bo Song, and Qing Lian Shu. "Static and Dynamic Finite Element Analysis of the Whole Ship Structural of Inland Waterway Bulk Carrier." Applied Mechanics and Materials 556-562 (May 2014): 996–1000. http://dx.doi.org/10.4028/www.scientific.net/amm.556-562.996.

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For the chase tank and large opening forms of inland waterway bulk carrier, using finite element method, the whole ship finite element model is established, the total intensity strength of the overall structure is conducted an evaluation study, the stress and strain distribution of the whole ship is obtained. The calculation methods of the entrained water quality is studied, and the entrained water quality is calculated by the method of Lewis and Todd, on this basis, the dynamic characteristics of the whole ship are calculated, the vibration characteristic of the whole ship is got, data is provided the support For the study of the important parts of inland waterway bulk carrier, and it is provided a certain reference for the design studies of inland waterway bulk carriers.

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Pu, Fangling, Chujiang Ding, Zeyi Chao, Yue Yu, and Xin Xu. "Water-Quality Classification of Inland Lakes Using Landsat8 Images by Convolutional Neural Networks." Remote Sensing 11, no. 14 (July 14, 2019): 1674. http://dx.doi.org/10.3390/rs11141674.

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Water-quality monitoring of inland lakes is essential for freshwater-resource protection. In situ water-quality measurements and ratings are accurate but high costs limit their usage. Water-quality monitoring using remote sensing has shown to be cost-effective. However, the nonoptically active parameters that mainly determine water-quality levels in China are difficult to estimate because of their weak optical characteristics and lack of explicit correlation between remote-sensing images and parameters. To address the problems, a convolutional neural network (CNN) with hierarchical structure was designed to represent the relationship between Landsat8 images and in situ water-quality levels. A transfer-learning strategy in the CNN model was introduced to deal with the lack of in situ measurement data. After the CNN model was trained by spatially and temporally matched Landsat8 images and in situ water-quality data that were collected from official websites, the surface quality of the whole water body could be classified. We tested the CNN model at the Erhai and Chaohu lakes in China, respectively. The experiment results demonstrate that the CNN model outperformed widely used machine-learning methods. The trained model at Erhai Lake can be used for the water-quality classification of Chaohu Lake. The introduced CNN model and the water-quality classification method could cover the whole lake with low costs. The proposed method has potential in inland-lake monitoring.

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Hadjimitsis, Diofantos Glafkou, Marinos Glafkou Hadjimitsis, Leonidas Toulios, and Chris Clayton. "Use of space technology for assisting water quality assessment and monitoring of inland water bodies." Physics and Chemistry of the Earth, Parts A/B/C 35, no. 1-2 (January 2010): 115–20. http://dx.doi.org/10.1016/j.pce.2010.03.033.

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Rizal Razm, Muhammad, Sakina Shaik Ahma, Shamsuddin Suhor, Rahmah Ismail, Azimon Abdul Aziz, and Kartini Aboo Talib. "Environmental Quality Act and Consumer Protection on Inland Water Resources Towards Sustainablity." Research Journal of Applied Sciences 6, no. 3 (March 1, 2011): 179–83. http://dx.doi.org/10.3923/rjasci.2011.179.183.

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Maier, P. M., and S. Keller. "ESTIMATING CHLOROPHYLL A CONCENTRATIONS OF SEVERAL INLAND WATERS WITH HYPERSPECTRAL DATA AND MACHINE LEARNING MODELS." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-2/W5 (May 29, 2019): 609–14. http://dx.doi.org/10.5194/isprs-annals-iv-2-w5-609-2019.

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<p><strong>Abstract.</strong> Water is a key component of life, the natural environment and human health. For monitoring the conditions of a water body, the chlorophyll a concentration can serve as a proxy for nutrients and oxygen supply. In situ measurements of water quality parameters are often time-consuming, expensive and limited in areal validity. Therefore, we apply remote sensing techniques. During field campaigns, we collected hyperspectral data with a spectrometer and in situ measured chlorophyll a concentrations of 13 inland water bodies with different spectral characteristics. One objective of this study is to estimate chlorophyll a concentrations of these inland waters by applying three machine learning regression models: Random Forest, Support Vector Machine and an Artificial Neural Network. Additionally, we simulate four different hyperspectral resolutions of the spectrometer data to investigate the effects on the estimation performance. Furthermore, the application of first order derivatives of the spectra is evaluated in turn to the regression performance. This study reveals the potential of combining machine learning approaches and remote sensing data for inland waters. Each machine learning model achieves an R2-score between 80% to 90% for the regression on chlorophyll a concentrations. The random forest model benefits clearly from the applied derivatives of the spectra. In further studies, we will focus on the application of machine learning models on spectral satellite data to enhance the area-wide estimation of chlorophyll a concentration for inland waters.</p>

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Arias-Rodriguez, Leonardo F., Zheng Duan, Rodrigo Sepúlveda, Sergio I. Martinez-Martinez, and Markus Disse. "Monitoring Water Quality of Valle de Bravo Reservoir, Mexico, Using Entire Lifespan of MERIS Data and Machine Learning Approaches." Remote Sensing 12, no. 10 (May 16, 2020): 1586. http://dx.doi.org/10.3390/rs12101586.

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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.

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Hu, Minqi, Ronghua Ma, Zhigang Cao, Junfeng Xiong, and Kun Xue. "Remote Estimation of Trophic State Index for Inland Waters Using Landsat-8 OLI Imagery." Remote Sensing 13, no. 10 (May 19, 2021): 1988. http://dx.doi.org/10.3390/rs13101988.

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Remote monitoring of trophic state for inland waters is a hotspot of water quality studies worldwide. However, the complex optical properties of inland waters limit the potential of algorithms. This research aims to develop an algorithm to estimate the trophic state in inland waters. First, the turbid water index was applied for the determination of optical water types on each pixel, and water bodies are divided into two categories: algae-dominated water (Type I) and turbid water (Type II). The algal biomass index (ABI) was then established based on water classification to derive the trophic state index (TSI) proposed by Carlson (1977). The results showed a considerable precision in Type I water (R2 = 0.62, N = 282) and Type II water (R2 = 0.57, N = 132). The ABI-derived TSI outperformed several band-ratio algorithms and a machine learning method (RMSE = 4.08, MRE = 5.46%, MAE = 3.14, NSE = 0.64). Such a model was employed to generate the trophic state index of 146 lakes (> 10 km2) in eastern China from 2013 to 2020 using Landsat-8 surface reflectance data. The number of hypertrophic and oligotrophic lakes decreased from 45.89% to 21.92% and 4.11% to 1.37%, respectively, while the number of mesotrophic and eutrophic lakes increased from 12.33% to 23.97% and 37.67% to 52.74%. The annual mean TSI for the lakes in the lower reaches of the Yangtze River basin was higher than that in the middle reaches of the Yangtze River and Huai River basin. The retrieval algorithm illustrated the applicability to other sensors with an overall accuracy of 83.27% for moderate-resolution imaging spectroradiometer (MODIS) and 82.92% for Sentinel-3 OLCI sensor, demonstrating the potential for high-frequency observation and large-scale simulation capability. Our study can provide an effective trophic state assessment and support inland water management.

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Journal articles on the topic 'Inland water quality'

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