Quantifying tolerance indicator values for common stream fish species of the United States

USGS Publications Warehouse

Meador, M.R.; Carlisle, D.M.

2007-01-01

The classification of fish species tolerance to environmental disturbance is often used as a means to assess ecosystem conditions. Its use, however, may be problematic because the approach to tolerance classification is based on subjective judgment. We analyzed fish and physicochemical data from 773 stream sites collected as part of the U.S. Geological Survey's National Water-Quality Assessment Program to calculate tolerance indicator values for 10 physicochemical variables using weighted averaging. Tolerance indicator values (TIVs) for ammonia, chloride, dissolved oxygen, nitrite plus nitrate, pH, phosphorus, specific conductance, sulfate, suspended sediment, and water temperature were calculated for 105 common fish species of the United States. Tolerance indicator values for specific conductance and sulfate were correlated (rho = 0.87), and thus, fish species may be co-tolerant to these water-quality variables. We integrated TIVs for each species into an overall tolerance classification for comparisons with judgment-based tolerance classifications. Principal components analysis indicated that the distinction between tolerant and intolerant classifications was determined largely by tolerance to suspended sediment, specific conductance, chloride, and total phosphorus. Factors such as water temperature, dissolved oxygen, and pH may not be as important in distinguishing between tolerant and intolerant classifications, but may help to segregate species classified as moderate. Empirically derived tolerance classifications were 58.8% in agreement with judgment-derived tolerance classifications. Canonical discriminant analysis revealed that few TIVs, primarily chloride, could discriminate among judgment-derived tolerance classifications of tolerant, moderate, and intolerant. To our knowledge, this is the first empirically based understanding of fish species tolerance for stream fishes in the United States.

A regional classification scheme for estimating reference water quality in streams using land-use-adjusted spatial regression-tree analysis

USGS Publications Warehouse

Robertson, Dale M.; Saad, D.A.; Heisey, D.M.

2006-01-01

Various approaches are used to subdivide large areas into regions containing streams that have similar reference or background water quality and that respond similarly to different factors. For many applications, such as establishing reference conditions, it is preferable to use physical characteristics that are not affected by human activities to delineate these regions. However, most approaches, such as ecoregion classifications, rely on land use to delineate regions or have difficulties compensating for the effects of land use. Land use not only directly affects water quality, but it is often correlated with the factors used to define the regions. In this article, we describe modifications to SPARTA (spatial regression-tree analysis), a relatively new approach applied to water-quality and environmental characteristic data to delineate zones with similar factors affecting water quality. In this modified approach, land-use-adjusted (residualized) water quality and environmental characteristics are computed for each site. Regression-tree analysis is applied to the residualized data to determine the most statistically important environmental characteristics describing the distribution of a specific water-quality constituent. Geographic information for small basins throughout the study area is then used to subdivide the area into relatively homogeneous environmental water-quality zones. For each zone, commonly used approaches are subsequently used to define its reference water quality and how its water quality responds to changes in land use. SPARTA is used to delineate zones of similar reference concentrations of total phosphorus and suspended sediment throughout the upper Midwestern part of the United States. ?? 2006 Springer Science+Business Media, Inc.

Water Quality Assessment for Deep-water Channel area of Guangzhou Port based on the Comprehensive Water Quality Identification Index Method

NASA Astrophysics Data System (ADS)

Chen, Yi

2018-03-01

The comprehensive water quality identification index method is able to assess the general water quality situation comprehensively and represent the water quality classification; water environment functional zone achieves pollution level and standard objectively and systematically. This paper selects 3 representative zones along deep-water channel of Guangzhou port and applies comprehensive water quality identification index method to calculate sea water quality monitoring data for different selected zones from year 2006 to 2014, in order to investigate the temporal variation of water quality along deep-water channel of Guangzhou port. The comprehensive water quality level from north to south presents an increased trend, and the water quality of the three zones in 2014 is much better than in 2006. This paper puts forward environmental protection measurements and suggestions for Pearl River Estuary, provides data support and theoretical basis for studied sea area pollution prevention and control.

Twenty five years of beach monitoring in Hong Kong: A re-examination of the beach water quality classification scheme from a comparative and global perspective.

PubMed

Thoe, W; Lee, Olive H K; Leung, K F; Lee, T; Ashbolt, Nicholas J; Yang, Ron R; Chui, Samuel H K

2018-06-01

Hong Kong's beach water quality classification scheme, used effectively for >25 years in protecting public health, was first established in local epidemiology studies during the late 1980s where Escherichia coli (E. coli) was identified as the most suitable faecal indicator bacteria. To review and further substantiate the scheme's robustness, a performance check was carried out to classify water quality of 37 major local beaches in Hong Kong during four bathing seasons (March-October) from 2010 to 2013. Given the enterococci and E. coli data collected, beach classification by the local scheme was found to be in line with the prominent international benchmarks recommended by the World Health Organization and the European Union. Local bacteriological studies over the last 15 years further confirmed that E. coli is the more suitable faecal indicator bacteria than enterococci in the local context. Copyright © 2018 Elsevier Ltd. All rights reserved.

Effect of the Clean Water Act on shellfish growing waters in the Gulf of Mexico

DOE Office of Scientific and Technical Information (OSTI.GOV)

Broutman, M.A.

1988-01-01

This report examines the classification of shellfish growing waters in the Gulf of Mexico as an indicator of bacterial water quality. Information presented includes the status of classified waters, sources of pollution affecting waters that are not classified as approved, and trends in classification between 1971 and 1985. Data were collected by site visits to the five Gulf states, interviews with state personnel, and reference to written materials. Data are used to assess the effectiveness of national efforts to improve bacterial water quality in the past fifteen years since passage of the Clean Water Act. The hypothesis to be testedmore » is that these efforts have not succeeded in reducing fecal coliform concentrations to levels required for approved harvest of shellfish, as established by the National Shellfish Sanitation Program.« less

Accounting for both local aquatic community composition and bioavailability in setting site-specific quality standards for zinc.

PubMed

Peters, Adam; Simpson, Peter; Moccia, Alessandra

2014-01-01

Recent years have seen considerable improvement in water quality standards (QS) for metals by taking account of the effect of local water chemistry conditions on their bioavailability. We describe preliminary efforts to further refine water quality standards, by taking account of the composition of the local ecological community (the ultimate protection objective) in addition to bioavailability. Relevance of QS to the local ecological community is critical as it is important to minimise instances where quality classification using QS does not reconcile with a quality classification based on an assessment of the composition of the local ecology (e.g. using benthic macroinvertebrate quality assessment metrics such as River InVertebrate Prediction and Classification System (RIVPACS)), particularly where ecology is assessed to be at good or better status, whilst chemical quality is determined to be failing relevant standards. The alternative approach outlined here describes a method to derive a site-specific species sensitivity distribution (SSD) based on the ecological community which is expected to be present at the site in the absence of anthropogenic pressures (reference conditions). The method combines a conventional laboratory ecotoxicity dataset normalised for bioavailability with field measurements of the response of benthic macroinvertebrate abundance to chemical exposure. Site-specific QSref are then derived from the 5%ile of this SSD. Using this method, site QSref have been derived for zinc in an area impacted by historic mining activities. Application of QSref can result in greater agreement between chemical and ecological metrics of environmental quality compared with the use of either conventional (QScon) or bioavailability-based QS (QSbio). In addition to zinc, the approach is likely to be applicable to other metals and possibly other types of chemical stressors (e.g. pesticides). However, the methodology for deriving site-specific targets requires additional development and validation before they can be robustly applied during surface water classification.

Oregon ground-water quality and its relation to hydrogeological factors; a statistical approach

USGS Publications Warehouse

Miller, T.L.; Gonthier, J.B.

1984-01-01

An appraisal of Oregon ground-water quality was made using existing data accessible through the U.S. Geological Survey computer system. The data available for about 1,000 sites were separated by aquifer units and hydrologic units. Selected statistical moments were described for 19 constituents including major ions. About 96 percent of all sites in the data base were sampled only once. The sample data were classified by aquifer unit and hydrologic unit and analysis of variance was run to determine if significant differences exist between the units within each of these two classifications for the same 19 constituents on which statistical moments were determined. Results of the analysis of variance indicated both classification variables performed about the same, but aquifer unit did provide more separation for some constituents. Samples from the Rogue River basin were classified by location within the flow system and type of flow system. The samples were then analyzed using analysis of variance on 14 constituents to determine if there were significant differences between subsets classified by flow path. Results of this analysis were not definitive, but classification as to the type of flow system did indicate potential for segregating water-quality data into distinct subsets. (USGS)

Data on assessment of groundwater quality for drinking and irrigation in rural area Sarpol-e Zahab city, Kermanshah province, Iran.

PubMed

Soleimani, Hamed; Abbasnia, Abbas; Yousefi, Mahmood; Mohammadi, Ali Akbar; Khorasgani, Fazlollah Changani

2018-04-01

In present study 30 groundwater samples were collected from Sarpol-e Zahab area, Kermanshah province of Iran in order to assess the quality of groundwater in subjected area and determining its suitability for drinking and agricultural purposes. Also the variations in the quality levels of groundwater were compared over the years of 2015 and 2016. Statistical analyses including Spearman correlation coefficients and factor analysis display good correlation between physicochemical parameters (EC, TDS and TH) and Na + , Mg 2+ , Ca 2+ , Cl - and [Formula: see text] ionic constituents. Also in order to assess water quality for irrigation we used the United States Department of Agriculture (USDA) classification which is based on SAR for irrigation suitability assessment. In addition, the residual sodium carbonate (RSC), %Na, PI, KR, SSP, MH, EC characteristics were calculated for all samples and used for assessment of irrigation suitability. Based on these indicators, for every two years, the quality of water for agriculture is in good and excellent category. The Piper classification for hydro geochemical facies indicates that the water in the study area is of Ca-HCO 3 - type. However, the study of water hardness shows that more than 80% of samples are in hard and very hard water class. Therefore, there is a need for decisions to refine and soften the water.

Algal Attributes: An Autecological Classification of Algal Taxa Collected by the National Water-Quality Assessment Program

USGS Publications Warehouse

Porter, Stephen D.

2008-01-01

Algae are excellent indicators of water-quality conditions, notably nutrient and organic enrichment, and also are indicators of major ion, dissolved oxygen, and pH concentrations and stream microhabitat conditions. The autecology, or physiological optima and tolerance, of algal species for various water-quality contaminants and conditions is relatively well understood for certain groups of freshwater algae, notably diatoms. However, applications of autecological information for water-quality assessments have been limited because of challenges associated with compiling autecological literature from disparate sources, tracking name changes for a large number of algal species, and creating an autecological data base from which algal-indicator metrics can be calculated. A comprehensive summary of algal autecological attributes for North American streams and rivers does not exist. This report describes a large, digital data file containing 28,182 records for 5,939 algal taxa, generally species or variety, collected by the U.S. Geological Survey?s National Water-Quality Assessment (NAWQA) Program. The data file includes 37 algal attributes classified by over 100 algal-indicator codes or metrics that can be calculated easily with readily available software. Algal attributes include qualitative classifications based on European and North American autecological literature, and semi-quantitative, weighted-average regression approaches for estimating optima using regional and national NAWQA data. Applications of algal metrics in water-quality assessments are discussed and national quartile distributions of metric scores are shown for selected indicator metrics.

Classification and Mapping of Agricultural Land for National Water-Quality Assessment

USGS Publications Warehouse

Gilliom, Robert J.; Thelin, Gail P.

1997-01-01

Agricultural land use is one of the most important influences on water quality at national and regional scales. Although there is great diversity in the character of agricultural land, variations follow regional patterns that are influenced by environmental setting and economics. These regional patterns can be characterized by the distribution of crops. A new approach to classifying and mapping agricultural land use for national water-quality assessment was developed by combining information on general land-use distribution with information on crop patterns from agricultural census data. Separate classification systems were developed for row crops and for orchards, vineyards, and nurseries. These two general categories of agricultural land are distinguished from each other in the land-use classification system used in the U.S. Geological Survey national Land Use and Land Cover database. Classification of cropland was based on the areal extent of crops harvested. The acreage of each crop in each county was divided by total row-crop area or total orchard, vineyard, and nursery area, as appropriate, thus normalizing the crop data and making the classification independent of total cropland area. The classification system was developed using simple percentage criteria to define combinations of 1 to 3 crops that account for 50 percent or more or harvested acreage in a county. The classification system consists of 21 level I categories and 46 level II subcategories for row crops, and 26 level I categories and 19 level II subcategories for orchards, vineyards, and nurseries. All counties in the United States with reported harvested acreage are classified in these categories. The distribution of agricultural land within each county, however, must be evaluated on the basis of general land-use data. This can be done at the national scale using 'Major Land Uses of the United States,' at the regional scale using data from the national Land Use and Land Cover database, or at smaller scales using locally available data.

Analysis of water quality on several waters affected by contamination in West Sumbawa Regency

NASA Astrophysics Data System (ADS)

Dewi, N. N.; Satyantini, W. H.; Sahidu, A. M.; Sari, L. A.; Mukti, A. T.

2018-04-01

This study reports the result of water quality in several waters in West Sumbawa Regency. The load of waste input from anthropogenic activity becomes an indication of the decrease of water quality in West Sumbawa Regency Waters. The existence of illegal mining activities around the water has the potential to cause water pollution. Sample of water were collected on April 2017 in four location such as Sejorong 1, Sejorong 2, Tongo, and Taliwang. Sample were analyzed as insitu and exsitu parameters. The result of this research showed that Sejorong 2 have the highest value of pollution index but generally four site on West Sumbawa Regency Waters were categorized lightly contaminated. Concentration of heavy metal cadmium at four locations exceed the water quality standard for fisheries and drinking water. However, the trophic classification using TSI and TRIX of all location was oligothropic water.

Characterizing groundwater quality ranks for drinking purposes in Sylhet district, Bangladesh, using entropy method, spatial autocorrelation index, and geostatistics.

PubMed

Islam, Abu Reza Md Towfiqul; Ahmed, Nasir; Bodrud-Doza, Md; Chu, Ronghao

2017-12-01

Drinking water is susceptible to the poor quality of contaminated water affecting the health of humans. Thus, it is an essential study to investigate factors affecting groundwater quality and its suitability for drinking uses. In this paper, the entropy theory, multivariate statistics, spatial autocorrelation index, and geostatistics are applied to characterize groundwater quality and its spatial variability in the Sylhet district of Bangladesh. A total of 91samples have been collected from wells (e.g., shallow, intermediate, and deep tube wells at 15-300-m depth) from the study area. The results show that NO 3 - , then SO 4 2- , and As are the most contributed parameters influencing the groundwater quality according to the entropy theory. The principal component analysis (PCA) and correlation coefficient also confirm the results of the entropy theory. However, Na + has the highest spatial autocorrelation and the most entropy, thus affecting the groundwater quality. Based on the entropy-weighted water quality index (EWQI) and groundwater quality index (GWQI) classifications, it is observed that 60.45 and 53.86% of water samples are classified as having an excellent to good qualities, while the remaining samples vary from medium to extremely poor quality domains for drinking purposes. Furthermore, the EWQI classification provides the more reasonable results than GWQIs due to its simplicity, accuracy, and ignoring of artificial weight. A Gaussian semivariogram model has been chosen to the best fit model, and groundwater quality indices have a weak spatial dependence, suggesting that both geogenic and anthropogenic factors play a pivotal role in spatial heterogeneity of groundwater quality oscillations.

Hierarchical clusters of phytoplankton variables in dammed water bodies

NASA Astrophysics Data System (ADS)

Silva, Eliana Costa e.; Lopes, Isabel Cristina; Correia, Aldina; Gonçalves, A. Manuela

2017-06-01

In this paper a dataset containing biological variables of the water column of several Portuguese reservoirs is analyzed. Hierarchical cluster analysis is used to obtain clusters of phytoplankton variables of the phylum Cyanophyta, with the objective of validating the classification of Portuguese reservoirs previewly presented in [1] which were divided into three clusters: (1) Interior Tagus and Aguieira; (2) Douro; and (3) Other rivers. Now three new clusters of Cyanophyta variables were found. Kruskal-Wallis and Mann-Whitney tests are used to compare the now obtained Cyanophyta clusters and the previous Reservoirs clusters, in order to validate the classification of the water quality of reservoirs. The amount of Cyanophyta algae present in the reservoirs from the three clusters is significantly different, which validates the previous classification.

A revisitation of TRIX for trophic status assessment in the light of the European Water Framework Directive: application to Italian coastal waters.

PubMed

Pettine, Maurizio; Casentini, Barbara; Fazi, Stefano; Giovanardi, Franco; Pagnotta, Romano

2007-09-01

The trophic status classification of coastal waters at the European scale requires the availability of harmonised indicators and procedures. The composite trophic status index (TRIX) provides useful metrics for the assessment of the trophic status of coastal waters. It was originally developed for Italian coastal waters and then applied in many European seas (Adriatic, Tyrrhenian, Baltic, Black and Northern seas). The TRIX index does not fulfil the classification procedure suggested by the WFD for two reasons: (a) it is based on an absolute trophic scale without any normalization to type-specific reference conditions; (b) it makes an ex ante aggregation of biological (Chl-a) and physico-chemical (oxygen, nutrients) quality elements, instead of an ex post integration of separate evaluations of biological and subsequent chemical quality elements. A revisitation of the TRIX index in the light of the European Water Framework Directive (WFD, 2000/60/EC) and new TRIX derived tools are presented in this paper. A number of Italian coastal sites were grouped into different types based on a thorough analysis of their hydro-morphological conditions, and type-specific reference sites were selected. Unscaled TRIX values (UNTRIX) for reference and impacted sites have been calculated and two alternative UNTRIX-based classification procedures are discussed. The proposed procedures, to be validated on a broader scale, provide users with simple tools that give an integrated view of nutrient enrichment and its effects on algal biomass (Chl-a) and on oxygen levels. This trophic evaluation along with phytoplankton indicator species and algal blooms contribute to the comprehensive assessment of phytoplankton, one of the biological quality elements in coastal waters.

FRAMEWORK FOR DEVELOPING SUSPENDED AND BEDDED SEDIMENT (SABS) WATER QUALITY CRITERIA: STEP 4 - DEFINE POTENTIAL RANGES IN VALUE OF THE SABS AND RESPONSE INDICATORS, AND CLASSIFICATION OF WATERBODIES USING AN EMPIRICAL APPROACH

EPA Science Inventory

After reviewing existing water quality criteria and consulting stakeholders, EPA developed a process that states, tribes, and regions can use to develop scientifically defensible SABS criteria. The process is flexible, can be adapted to utilize existing data sets, and can be gea...

[Spatial distribution characteristics of the physical and chemical properties of water in the Kunes River after the supply of snowmelt during spring].

PubMed

Liu, Xiang; Guo, Ling-Peng; Zhang, Fei-Yun; Ma, Jie; Mu, Shu-Yong; Zhao, Xin; Li, Lan-Hai

2015-02-01

Eight physical and chemical indicators related to water quality were monitored from nineteen sampling sites along the Kunes River at the end of snowmelt season in spring. To investigate the spatial distribution characteristics of water physical and chemical properties, cluster analysis (CA), discriminant analysis (DA) and principal component analysis (PCA) are employed. The result of cluster analysis showed that the Kunes River could be divided into three reaches according to the similarities of water physical and chemical properties among sampling sites, representing the upstream, midstream and downstream of the river, respectively; The result of discriminant analysis demonstrated that the reliability of such a classification was high, and DO, Cl- and BOD5 were the significant indexes leading to this classification; Three principal components were extracted on the basis of the principal component analysis, in which accumulative variance contribution could reach 86.90%. The result of principal component analysis also indicated that water physical and chemical properties were mostly affected by EC, ORP, NO3(-) -N, NH4(+) -N, Cl- and BOD5. The sorted results of principal component scores in each sampling sites showed that the water quality was mainly influenced by DO in upstream, by pH in midstream, and by the rest of indicators in downstream. The order of comprehensive scores for principal components revealed that the water quality degraded from the upstream to downstream, i.e., the upstream had the best water quality, followed by the midstream, while the water quality at downstream was the worst. This result corresponded exactly to the three reaches classified using cluster analysis. Anthropogenic activity and the accumulation of pollutants along the river were probably the main reasons leading to this spatial difference.

Water quality of Cisadane River based on watershed segmentation

NASA Astrophysics Data System (ADS)

Effendi, Hefni; Ayu Permatasari, Prita; Muslimah, Sri; Mursalin

2018-05-01

The growth of population and industrialization combined with land development along river cause water pollution and environmental deterioration. Cisadane River is one of the river in Indonesia where urbanization, industrialization, and agricultural are extremely main sources of pollution. Cisadane River is an interesting case for investigating the effect of land use to water quality and comparing water quality in every river segment. The main objectives with this study were to examine if there is a correlation between land use and water quality in Cisadane River and there is a difference in water quality between the upstream section of Cisadane River compared with its downstream section. This study compared water quality with land use condition in each segment of river. Land use classification showed that river segment that has more undeveloped area has better water quality compared to river segment with developed area. in general, BOD and COD values have increased from upstream to downstream. However, BOD and COD values do not show a steady increase in each segment Water quality is closely related to the surrounding land use.Therefore, it can not be concluded that the water quality downstream is worse than in the upstream area.

Reality check of socio-hydrological interactions in water quality and ecosystem management

NASA Astrophysics Data System (ADS)

Destouni, Georgia; Fischer, Ida; Prieto, Carmen

2017-04-01

Socio-hydrological interactions in water management for improving water quality and ecosystem status include as key components both (i) the societal measures taken for mitigation and control, and (ii) the societal characterization and monitoring efforts made for choosing management targets and checking the effects of measures taken to reach the targets. This study investigates such monitoring, characterization and management efforts and effects over the first six-year management cycle of the EU Water Framework Directive (WFD). The investigation uses Sweden and the WFD-regulated management of its stream and lake waters as a concrete quantification example, with focus on the nutrient and eutrophication conditions that determine the most prominent water quality and ecosystem problems in need of mitigation in the Swedish waters. The case results show a relatively small available monitoring base for determination of these nutrient and eutrophication conditions, even though they constitute key parts in the overall WFD-based approach to classification and management of ecosystem status. Specifically, actual nutrient monitoring exists in only around 1% (down to 0.2% for nutrient loads) of the Swedish stream and lake water bodies; modeling is used to fill the gaps for the remaining unmonitored fraction of classified and managed waters. The available data show that the hydro-climatically driven stream water discharge is a primary explanatory variable for the resulting societal classification of ecosystem status in Swedish waters; this may be due to the discharge magnitude being dominant in determining nutrient loading to these waters. At any rate, with such a hydro-climatically related, rather than human-pressure related, determinant of the societal ecosystem-status classification, the main human-driven causes and effects of eutrophication may not be appropriately identified, and the measures taken for mitigating these may not be well chosen. The available monitoring data from Swedish waters support this hypothesis, by showing that the first WFD management cycle 2009-2015 has led to only slight changes in measured nutrient concentrations, with moderate-to-bad status waters mostly undergoing concentration increases. These management results are in direct contrast to the WFD management goals that ecosystem status in all member-state waters must be improved to at least good level, and in any case not be allowed to further deteriorate. In general, the present results show that societal approaches to ecosystem status classification, monitoring and improvement may need a focus shift for improved identification and quantification of the human-driven components of nutrient inputs, concentrations and loads in water environments. Dominant hydro-climatic change drivers and effects must of course also be understood and accounted for. However, adaptation to hydro-climatic changes should be additional to and aligned with, rather than instead of, necessary mitigation of human-driven eutrophication. The present case results call for further science-based testing and evidence of societal water quality and ecosystem management actually targeting and following up the potential achievement of such mitigation.

Objective classification of ecological status in marine water bodies using ecotoxicological information and multivariate analysis.

PubMed

Beiras, Ricardo; Durán, Iria

2014-12-01

Some relevant shortcomings have been identified in the current approach for the classification of ecological status in marine water bodies, leading to delays in the fulfillment of the Water Framework Directive objectives. Natural variability makes difficult to settle fixed reference values and boundary values for the Ecological Quality Ratios (EQR) for the biological quality elements. Biological responses to environmental degradation are frequently of nonmonotonic nature, hampering the EQR approach. Community structure traits respond only once ecological damage has already been done and do not provide early warning signals. An alternative methodology for the classification of ecological status integrating chemical measurements, ecotoxicological bioassays and community structure traits (species richness and diversity), and using multivariate analyses (multidimensional scaling and cluster analysis), is proposed. This approach does not depend on the arbitrary definition of fixed reference values and EQR boundary values, and it is suitable to integrate nonlinear, sensitive signals of ecological degradation. As a disadvantage, this approach demands the inclusion of sampling sites representing the full range of ecological status in each monitoring campaign. National or international agencies in charge of coastal pollution monitoring have comprehensive data sets available to overcome this limitation.

Uncertainty result of biotic index in analysing the water quality of Cikapundung river catchment area, Bandung

NASA Astrophysics Data System (ADS)

Surtikanti, Hertien Koosbandiah

2017-05-01

The Biotic Index was developed in Western Countries in response to the need in water quality evaluation. This method analysis is based on the classification of aquatic macrobenthos as a bioindicator for clean and polluted water. The aim of this study is to compare the analysis of Cikapundung river using 6 different Biotic Indexes. BI Shannon-Weiner, Belgian Biological Index (BBI), Family Biotic Index (FBI), Biological Monitoring Working Party (BMWP), Biological Monitoring Working Party-Average Score Per Taxon (BMWP-ASPT), and A Scoring System for Macroinvertebrate in Australian River (A SIGNAL). Those analysis are compared with Physical Water Index (CPI) which is developed in Indonesia. The result shows that a decreasing water quality is detected upstream to downstream of Cikapundung River. However, based on the CPI analysis result, the BMWP-ASPT biotic index analysis is more comprehensive than other BI in explaining Cikapundung water quality.

Infectious waterborne diseases

USGS Publications Warehouse

Greeson, Phillip E.

1981-01-01

This is the third of several compilations of briefing papers on water quality by the U.S. Geological Survey. Each briefing paper is prepared in a simple, nontechnical, easy-to-understand manner. This U.S. Geological Survey Circular contains papers on selected organic substances in water. Briefing papers are included on ' Why study organic substances in water. ', ' Taste and odor in water ', and ' Classification and fractionation of organic solutes in natural waters'. (USGS)

Pattern recognition analysis and classification modeling of selenium-producing areas

USGS Publications Warehouse

Naftz, D.L.

1996-01-01

Established chemometric and geochemical techniques were applied to water quality data from 23 National Irrigation Water Quality Program (NIWQP) study areas in the Western United States. These techniques were applied to the NIWQP data set to identify common geochemical processes responsible for mobilization of selenium and to develop a classification model that uses major-ion concentrations to identify areas that contain elevated selenium concentrations in water that could pose a hazard to water fowl. Pattern recognition modeling of the simple-salt data computed with the SNORM geochemical program indicate three principal components that explain 95% of the total variance. A three-dimensional plot of PC 1, 2 and 3 scores shows three distinct clusters that correspond to distinct hydrochemical facies denoted as facies 1, 2 and 3. Facies 1 samples are distinguished by water samples without the CaCO3 simple salt and elevated concentrations of NaCl, CaSO4, MgSO4 and Na2SO4 simple salts relative to water samples in facies 2 and 3. Water samples in facies 2 are distinguished from facies 1 by the absence of the MgSO4 simple salt and the presence of the CaCO3 simple salt. Water samples in facies 3 are similar to samples in facies 2, with the absence of both MgSO4 and CaSO4 simple salts. Water samples in facies 1 have the largest selenium concentration (10 ??gl-1), compared to a median concentration of 2.0 ??gl-1 and less than 1.0 ??gl-1 for samples in facies 2 and 3. A classification model using the soft independent modeling by class analogy (SIMCA) algorithm was constructed with data from the NIWQP study areas. The classification model was successful in identifying water samples with a selenium concentration that is hazardous to some species of water-fowl from a test data set comprised of 2,060 water samples from throughout Utah and Wyoming. Application of chemometric and geochemical techniques during data synthesis analysis of multivariate environmental databases from other national-scale environmental programs such as the NIWQP could also provide useful insights for addressing 'real world' environmental problems.

Environmental quality of transitional waters: the lagoon of Venice case study.

PubMed

Micheletti, C; Gottardo, S; Critto, A; Chiarato, S; Marcomini, A

2011-01-01

The health status of European aquatic environments, including transitional waters such as coastal lagoons, is regulated by the Water Framework Directive (WFD), which requires the classification of the water bodies' environmental quality and the achievement of a good ecological status by 2015. In the Venice lagoon, a transitional water body located in the northeastern part of Italy, the achievement of a good ecological status is hampered by several anthropogenic and natural pressures, such as sediment and water chemical contamination, and sediment erosion. In order to evaluate the lagoon's environmental quality according to the WFD (i.e. 5 quality classes, from High to Bad), an integrated Weight-of-Evidence methodology was developed and applied to classify the quality of the lagoon water bodies, integrating biological, physico-chemical, chemical, ecotoxicological, and hydromorphological data (i.e. Lines of Evidence, LOE). The quality assessment was carried out in two lagoon habitat typologies (previously defined on the basis of morphological, sediment, and hydrodynamic characteristics) which were selected taking into account the ecological gradient from sea to land, and the differences in anthropogenic pressure and contamination levels. The LOE classification was carried out by using indicators scored by comparing site specific conditions to reference conditions measured in lagoon reference sites, or provided by local, national or European regulations (e.g. Environmental Quality Standards, EQS, for chemicals). Finally, the overall quality status for each water body was calculated by a probabilistic approach, i.e. by reporting the final result as the frequency distribution of quality classes. The developed procedure was applied by using data and information concerning selected LOE and collected from monitoring programs and research studies carried out in the last 15 years in the lagoon of Venice. A set of sampling stations characterized by spatially and temporally coherent information for each LOE was selected, and among these stations, potential reference sites for each water body typology were identified. The quality assessment highlighted that there are specific lagoon areas, especially those located near the industrially developed area, which are highly affected by anthropogenic activities, and that chemical contamination is one of the main pressures affecting ecological status (e.g. macro-benthonic biodiversity) in the Venice lagoon. The integrated quality assessment procedure that was developed provided a new tool supporting decision making, as well as lagoon assessment and management. Copyright © 2010 Elsevier Ltd. All rights reserved.

Water quality, hydrology, and the effects of changes in phosphorus loading to Pike Lake, Washington County, Wisconsin, with special emphasis on inlet-to-outlet short-circuiting

USGS Publications Warehouse

Rose, William J.; Robertson, Dale M.; Mergener, Elizabeth A.

2004-01-01

Simulations using water-quality models within the Wisconsin Lake Model Suite (WiLMS) indicated Pike Lake's response to 13 different phosphorus-loading scenarios. These scenarios included a base 'normal' year (2000) for which lake water quality and loading were known, six different percentage increases or decreases in phosphorus loading from controllable sources, and six different loading scenarios corresponding to specific management actions. Model simulations indicate that a 50-percent reduction in controllable loading sources would be needed to achieve a mesotrophic classification with respect to phosphorus, chlorophyll a, and Secchi depth (an index of water clarity). Model simulations indicated that short-circuiting of phosphorus from the inlet to the outlet was the main reason the water quality of the lake is good relative to the amount of loading from the Rubicon River and that changes in the percentage of inlet-to-outlet short-circuiting have a significant influence on the water quality of the lake.

Biomonitoring of water quality of the Osumi, Devolli, and Shkumbini rivers through benthic macroinvertebrates and chemical parameters.

PubMed

Duka, Sonila; Pepa, Bledar; Keci, Erjola; Paparisto, Anila; Lazo, Pranvera

2017-04-16

Environmental monitoring of river water quality in Albania, using biological and chemical parameters, is a fast and effective way to assess the quality of water bodies.The aim of this study was to investigate Ephemeroptera, Plecoptera and Trichoptera (EPT), Biotic index-Richness using macroinvertebrates to assess the water quality, with special reference to nutrient (phosphorus and nitrogen) levels in the Devolli, Shkumbini and Osumi rivers. Our objective was to investigate the relationships between the measures of benthic macroinvertebrate communities and nutrient concentrations to assess water quality. The rivers' benthic macroinvertebrates were collected during different seasons in 2012. The biological and chemical parameters used in the current study identified them as quick indicators of water quality assessment. The total number of macroinvertebrate individuals (n = 15,006) (Osumi river: n = 5,546 organisms; Devolli river: n = 3,469 organisms; and Shkumbini river: n = 5,991 organisms), together with the EPT group (Ephemeroptera, Plecoptera, and Trichoptera), showed that the water quality at the river stations during the above-mentioned period belonged to Classes II and III (fair water quality and good water quality, respectively). The classification of the water quality was also based on the nitrogen and total phosphorus contents. The pollution tolerance levels of macroinvertebrate taxa varied from the non-tolerating forms encountered in environments with low pollution levels to the tolerating forms that are typical of environments with considerable pollution levels.

Identification and Assessment of Potential Water Quality Impact Factors for Drinking-Water Reservoirs

PubMed Central

Gu, Qing; Deng, Jinsong; Wang, Ke; Lin, Yi; Li, Jun; Gan, Muye; Ma, Ligang; Hong, Yang

2014-01-01

Various reservoirs have been serving as the most important drinking water sources in Zhejiang Province, China, due to the uneven distribution of precipitation and severe river pollution. Unfortunately, rapid urbanization and industrialization have been continuously challenging the water quality of the drinking-water reservoirs. The identification and assessment of potential impacts is indispensable in water resource management and protection. This study investigates the drinking water reservoirs in Zhejiang Province to better understand the potential impact on water quality. Altogether seventy-three typical drinking reservoirs in Zhejiang Province encompassing various water storage levels were selected and evaluated. Using fifty-two reservoirs as training samples, the classification and regression tree (CART) method and sixteen comprehensive variables, including six sub-sets (land use, population, socio-economy, geographical features, inherent characteristics, and climate), were adopted to establish a decision-making model for identifying and assessing their potential impacts on drinking-water quality. The water quality class of the remaining twenty-one reservoirs was then predicted and tested based on the decision-making model, resulting in a water quality class attribution accuracy of 81.0%. Based on the decision rules and quantitative importance of the independent variables, industrial emissions was identified as the most important factor influencing the water quality of reservoirs; land use and human habitation also had a substantial impact on water quality. The results of this study provide insights into the factors impacting the water quality of reservoirs as well as basic information for protecting reservoir water resources. PMID:24919129

Identification and assessment of potential water quality impact factors for drinking-water reservoirs.

PubMed

Gu, Qing; Deng, Jinsong; Wang, Ke; Lin, Yi; Li, Jun; Gan, Muye; Ma, Ligang; Hong, Yang

2014-06-10

Various reservoirs have been serving as the most important drinking water sources in Zhejiang Province, China, due to the uneven distribution of precipitation and severe river pollution. Unfortunately, rapid urbanization and industrialization have been continuously challenging the water quality of the drinking-water reservoirs. The identification and assessment of potential impacts is indispensable in water resource management and protection. This study investigates the drinking water reservoirs in Zhejiang Province to better understand the potential impact on water quality. Altogether seventy-three typical drinking reservoirs in Zhejiang Province encompassing various water storage levels were selected and evaluated. Using fifty-two reservoirs as training samples, the classification and regression tree (CART) method and sixteen comprehensive variables, including six sub-sets (land use, population, socio-economy, geographical features, inherent characteristics, and climate), were adopted to establish a decision-making model for identifying and assessing their potential impacts on drinking-water quality. The water quality class of the remaining twenty-one reservoirs was then predicted and tested based on the decision-making model, resulting in a water quality class attribution accuracy of 81.0%. Based on the decision rules and quantitative importance of the independent variables, industrial emissions was identified as the most important factor influencing the water quality of reservoirs; land use and human habitation also had a substantial impact on water quality. The results of this study provide insights into the factors impacting the water quality of reservoirs as well as basic information for protecting reservoir water resources.

Evaluation of coal-mining impacts using numerical classification of benthic invertebrate data from streams draining a heavily mined basin in eastern Tennessee

USGS Publications Warehouse

Bradfield, A.D.

1986-01-01

Coal-mining impacts on Smoky Creek, eastern Tennessee were evaluated using water quality and benthic invertebrate data. Data from mined sites were also compared with water quality and invertebrate fauna found at Crabapple Branch, an undisturbed stream in a nearby basin. Although differences in water quality constituent concentrations and physical habitat conditions at sampling sites were apparent, commonly used measures of benthic invertebrate sample data such as number of taxa, sample diversity, number of organisms, and biomass were inadequate for determining differences in stream environments. Clustering algorithms were more useful in determining differences in benthic invertebrate community structure and composition. Normal (collections) and inverse (species) analyses based on presence-absence data of species of Ephemeroptera, Plecoptera, and Tricoptera were compared using constancy, fidelity, and relative abundance of species found at stations with similar fauna. These analyses identified differences in benthic community composition due to seasonal variations in invertebrate life histories. When data from a single season were examined, sites on tributary streams generally clustered separately from sites on Smoky Creek. These analyses compared with differences in water quality, stream size, and substrate characteristics between tributary sites and the more degraded main stem sites, indicated that numerical classification of invertebrate data can provide discharge-independent information useful in rapid evaluations of in-stream environmental conditions. (Author 's abstract)

Water quality assessment of the Li Canal using a functional fuzzy synthetic evaluation model.

PubMed

Feng, Yan; Ling, Liu

2014-07-01

Through introducing functional data analysis (FDA) theory into the conventional fuzzy synthetic evaluation (FSE) method, the functional fuzzy synthetic evaluation (FFSE) model is established. FFSE keeps the property of the conventional FSE that the fuzziness in the water quality condition can be suitably measured. Furthermore, compared with FSE, FFSE has the following advantages: (1) FFSE requires fewer conditions for observation, for example, pollutants can be monitored at different times, and missing data is accepted; (2) the dynamic variation of the water quality condition can be represented more comprehensively and intuitively. The procedure of FFSE is discussed and the water quality of the Li Canal in 2012 is evaluated as an illustration. The synthetic classification of the Li Canal is "II" in January, February and July, and "I" in other months, which can satisfy the requirement of the Chinese South-to-North Water Diversion Project.

Total nutrient and sediment loads, trends, yields, and nontidal water-quality indicators for selected nontidal stations, Chesapeake Bay Watershed, 1985–2011

USGS Publications Warehouse

Langland, Michael J.; Blomquist, Joel D.; Moyer, Douglas; Hyer, Kenneth; Chanat, Jeffrey G.

2013-01-01

The U.S. Geological Survey, in cooperation with Chesapeake Bay Program (CBP) partners, routinely reports long-term concentration trends and monthly and annual constituent loads for stream water-quality monitoring stations across the Chesapeake Bay watershed. This report documents flow-adjusted trends in sediment and total nitrogen and phosphorus concentrations for 31 stations in the years 1985–2011 and for 32 stations in the years 2002–2011. Sediment and total nitrogen and phosphorus yields for 65 stations are presented for the years 2006–2011. A combined nontidal water-quality indicator (based on both trends and yields) indicates there are more stations classified as “improving water-quality trend and a low yield” than “degrading water-quality trend and a high yield” for total nitrogen. The same type of 2-way classification for total phosphorus and sediment results in equal numbers of stations in each indicator class.

Lake water quality mapping from Landsat

NASA Technical Reports Server (NTRS)

Scherz, J. P.

1977-01-01

In the project described remote sensing was used to check the quality of lake waters. The lakes of three Landsat scenes were mapped with the Bendix MDAS multispectral analysis system. From the MDAS color coded maps, the lake with the worst algae problem was easily located. The lake was closely checked, and the presence of 100 cows in the springs which fed the lake could be identified as the pollution source. The laboratory and field work involved in the lake classification project is described.

Classification of High Spatial Resolution, Hyperspectral ...

EPA Pesticide Factsheets

EPA announced the availability of the final report,

Ecological risk assessment of cheese whey effluents along a medium-sized river in southwest Greece.

PubMed

Karadima, Constantina; Theodoropoulos, Chris; Rouvalis, Angela; Iliopoulou-Georgudaki, Joan

2010-01-01

An ecological risk assessment of cheese whey effluents was applied in three critical sampling sites located in Vouraikos river (southwest Greece), while ecological classification using Water Framework Directive 2000/60/EU criteria allowed a direct comparison of toxicological and ecological data. Two invertebrates (Daphnia magna and Thamnocephalus platyurus) and the zebra fish Danio rerio were used for toxicological analyses, while the aquatic risk was calculated on the basis of the risk quotient (RQ = PEC/PNEC). Chemical classification of sites was carried out using the Nutrient Classification System, while benthic invertebrates were collected and analyzed for biological classification. Toxicological results revealed the heavy pollution load of the two sites, nearest to the point pollution source, as the PEC/PNEC ratio exceeded 1.0, while unexpectedly, no risk was detected for the most downstream site, due to the consequent interference of the riparian flora. These toxicological results were in agreement with the ecological analysis: the ecological quality of the two heavily impacted sites ranged from moderate to bad, whereas it was found good for the most downstream site. The results of the study indicate major ecological risk for almost 15 km downstream of the point pollution source and the potentiality of the water quality remediation by the riparian vegetation, proving the significance of its maintenance.

Nutrient trends through time in Sweden's Baltic Drainage Area

NASA Astrophysics Data System (ADS)

Fischer, I.; Destouni, G.; Prieto, C.

2015-12-01

Changes in climate and land-use have and will continue to modify regional hydrology, in turn impacting environmental health, agricultural productivity and water resource quality and availability. The Baltic region is an area of interest as the coast spans nine countries- serving over 100 million people. The Baltic Sea contains one of the largest human caused hypoxic dead zones due to eutrophication driven by anthropogenic excess loading of nutrients. Policies to reduce these loads include also international directives and agreements, such as the EU Water Framework Directive, adopted in 2000 to protect and improve water quality throughout the European Union, and the Baltic Sea Action Plan under the Helsinki Commission aimed specifically at reducing the nutrient loading to and mitigating the eutrophication of the Baltic Sea. In light of these policies and amidst the number of studies on the Baltic Sea we ask, using the accessible nutrient and discharge data what does nutrient loading look like today? Are the most excessive loads going down? Observed nutrient and flow time series across Sweden allow for answering these questions, by spatial and temporal trend analysis of loads from various parts of Sweden to the Baltic Sea. Analyzing these observed time series in conjunction with the ecological health status classifications of the EU Water Framework Directive, allows in particular for answering the question if the loads into the water bodies with the poorest water quality, and from those to the Baltic Sea, are improving, being maintained or deteriorating. Such insight is required to contribute to relevant and efficient water and nutrient load management. Furthermore, empirically calculating nutrient loads, rather than only modeling, reveals that the water body health classification may not reflect what water bodies actually contribute the heaviest loads to the Baltic Sea. This work also underscores the importance of comprehensive analysis of all available data from long term monitoring programs over large spatial scales, including large water quality gradients, in order to assess and address water management problems of today and the future.

Geomorphology and its implication in urban groundwater environment: case study from Mumbai, India

NASA Astrophysics Data System (ADS)

Rani, V. R.; Pandalai, H. S.; Sajinkumar, K. S.; Pradeepkumar, A. P.

2015-06-01

Landforms of Mumbai Island have been largely modified by the urban sprawl and the demand for groundwater will increase exponentially in the future. Quality and quantity of groundwater occurrence in island are highly influenced by the geomorphic units. As this metropolis receives heavy rainfall, the area rarely faces the issue of water scarcity, nevertheless, quality always remains a question. The landforms of Mumbai Island have been shaped by a combination of fluvial, denudational and marine processes. These landforms are categorized into two broad zones on the basis of its influence in groundwater occurrence. Denudational landforms are categorized as runoff zones whereas the other two are categorized as storage zones. This classification is on the basis of occurrence and storage of groundwater. Mumbai Island is exposed to frequent sea water incursion and groundwater quality has deteriorated. The varied hydrogeological conditions prevalent in this area prevent rapid infiltration. This combined with the overextraction of groundwater resources for agriculture and industry has caused serious concern about the continued availability of potable water. This study aims at validating the geomorphic classification of the landforms with hydrogeochemistry and borehole data and it proved that geomorphology corroborates with groundwater chemistry and subsurface geology.

Hydrochemical Regions of the Glacial Aquifer System, Northern United States, and Their Environmental and Water-Quality Characteristics

USGS Publications Warehouse

Arnold, Terri L.; Warner, Kelly L.; Groschen, George E.; Caldwell, James P.; Kalkhoff, Stephen J.

2008-01-01

The glacial aquifer system in the United States is a large (953,000 square miles) regional aquifer system of heterogeneous composition. As described in this report, the glacial aquifer system includes all unconsolidated geologic material above bedrock that lies on or north of the line of maximum glacial advance within the United States. Examining ground-water quality on a regional scale indicates that variations in the concentrations of major and minor ions and some trace elements most likely are the result of natural variations in the geologic and physical environment. Study of the glacial aquifer system was designed around a regional framework based on the assumption that two primary characteristics of the aquifer system can affect water quality: intrinsic susceptibility (hydraulic properties) and vulnerability (geochemical properties). The hydrochemical regions described in this report were developed to identify and explain regional spatial variations in ground-water quality in the glacial aquifer system within the hypothetical framework context. Data analyzed for this study were collected from 1991 to 2003 at 1,716 wells open to the glacial aquifer system. Cluster analysis was used to group wells with similar ground-water concentrations of calcium, chloride, fluoride, magnesium, potassium, sodium, sulfate, and bicarbonate into five unique groups. Maximum Likelihood Classification was used to make the extrapolation from clustered groups of wells, defined by points, to areas of similar water quality (hydrochemical regions) defined in a geospatial model. Spatial data that represented average annual precipitation, average annual temperature, land use, land-surface slope, vertical soil permeability, average soil clay content, texture of surficial deposits, type of surficial deposit, and potential for ground-water recharge were used in the Maximum Likelihood Classification to classify the areas so the characteristics of the hydrochemical regions would resemble the characteristics of the clusters. The result of the Maximum Likelihood Classification is a map showing five hydrochemical regions of the glacial aquifer system. Statistical analysis of ion concentrations (calcium, chloride, fluoride, magnesium, sodium, potassium, sulfate, and bicarbonate) in samples collected from wells completed in the glacial aquifer system illustrates that variations in water quality can be explained, in part, by related environmental characteristics that control the movement of ground water through the aquifer system. A comparison of median concentrations of chemical constituents in ground water among the five hydrochemical regions indicates that ground water in the Midwestern Agricultural Region, the Urban-Influenced Region, and the Western Agriculture and Grassland Region has the highest concentrations of major and minor ions, whereas ground water in the Northern and Great Lakes Forested Region and the Mountain and Coastal Forested Region has the lowest concentrations of these ions. Median concentrations of barium, arsenic, lithium, boron, strontium, and nitrite plus nitrate as nitrogen also are significantly different among the hydrochemical regions.

Assessing the relationship between water quality parameters and changes in landuse patterns in the Upper Manyame River, Zimbabwe

NASA Astrophysics Data System (ADS)

Kibena, J.; Nhapi, I.; Gumindoga, W.

For the past 30 years, the increases in population pressure and external influences, such as economic growth, have accelerated the demand for land within the Upper Manyame River catchment in Zimbabwe which has caused substantial changes in landuse. The general objective of this research was to assess the impacts of landuse activities on the water quality of the Upper Manyame River which drains the rural and urbanised part of the catchment up to flow gauging station C21. Landcover data for the month of April in years of 1984, 1995, 2003 and 2011 were acquired from available Landsat TM and ETM images and were classified through the maximum likelihood digital image classification using the supervised classification approach. The status of water quality of the Upper Manyame River was also assessed through analyses of historical concentrations and pollution loads for TP, DO, COD, NH3-N, SS, Pb, NO3, BOD5, EC, PO4-P and TN at the Environmental Management Agency (EMA) gauging station CR21 sampling point for 1996, 2000/1 and 2008/9. Water quality of 15 monitoring sites comprising 25 water quality parameters were monitored monthly from January to June 2012. These locations were selected to reflect a wide array of landuse for both the dry and wet seasons. The results indicated that there was an increase in pollution load from 1995 to 2012; for TP from 130 kg/day to 376 kg/d, and for TN from 290 kg/day to 494 kg/d. This indicates high pollution levels which have severe impacts on downstream users and also severe sewage contamination. Significant deviations occurred in DO (0.1-6.8) mg/L, COD (11-569) mg/L, BOD5 (5-341) mg/L, PO4-P (0.01-4.45) mg/L, NH3-N (0.001-6.800) mg/L and EC (38-642) μS/cm. Hydrologic Response Unit and buffer analysis were used to determine the dominant landuse which contributes to a certain water quality. Results of digital image classification indicate that woodland/forest, grassland and bareland decreased between years 1984 to 2011 by 24.0%, 22.6% and 31.7% respectively. This was mainly due to expansion or increase of agriculture and urban areas by 24.4% and 41.6% respectively over the same time period. It was concluded that settlements and agricultural areas are the ones mainly affecting the water quality in Upper Manyame River with a Pearson's Correlation Coefficient of r = 0.97 for COD and r = 0.78 for TSS respectively. It was also observed that the water quality status of the Upper Manyame River and its tributaries is very poor and the level of pollution generally increases from upstream to downstream. The results obtained provided baseline information which may be used in the development of appropriate water quality management systems in the catchment. Thus the study recommended a combined programme of point source control and landuse modification.

Monitoring and assessment of water quality of Tasik Cempaka, Bangi

NASA Astrophysics Data System (ADS)

Sabri, Nurul Ain Syahirah Mohamad; Abdullah, Md Pauzi; Mat, Sohif

2014-09-01

A study was carried out to determine the status of water quality of Tasik Cempaka which is a part of Sg. Air Itam, located near the Bangi industrial area. The study was carried out for eight months from May and to December 2013. Eight sampling stations were selected from upstream to downstream of Sg. Air Itam which represent the entire body of the lake water. There are 8 parameters measured and Water Quality Indices (WQI) was calculated and classified according to the National Water Quality Standard (NWQS). The physical and chemical parameters were temperature, pH, conductivity, dissolve oxygen (DO), total suspended solid (TSS), ammoniacal nitrogen (AN), chemical oxygen demand (COD) and biochemical oxygen demand (BOD). Among parameters that are affected by pollution is AN, COD and BOD. Classification by WQI shows that the average for all sampling was 54 (dry) and 52 (wet). Both are of class III according to National Water Quality Standard (NWQS) indicating slightly polluted. This is mainly due to drainage from Bangi Golf Resort and Bangi-Putrajaya Hotel. Other factors are activities around Sg. Air Itam such as municipal activities, settlements and manufacturing industries.

Remote Sensing and GIS for Landuse/Landcover Classification and Water Quality in the Northern Ireland

NASA Astrophysics Data System (ADS)

Amer, R.; Ofterdinger, U.; Ruffell, A.; Donald, A.

2012-04-01

This study presents landuse/landcover (LULC) classifications of Northern Ireland in order to quantify land-use types driving chemical loading in the surface water bodies. The major LULC classes are agricultural land, bare land (mountainous areas), forest, urban areas, and water bodies. Three ENVISAT ASAR multi-look precision images acquired in 2011 and two Enhanced Thematic Mapper Plus (ETM+) acquired in 2003 were used for classification. The ASAR digital numbers were converted to backscattering coefficient (sigma nought) and enhanced using adaptive Gamma filter and Gaussian stretch. Supervised classifications of Maximum Likelihood, Mahalanobils Distance, Minimum Distance, Spectral Angel Mapper, Parallelepiped, and Winner Tercat were applied on ETM+ and ASAR images. A confusion matrix was used to evaluate the classification accuracy; the best results of ETM+ and ASAR were given by the winner classification (82.9 and 73.6 %), and maximum likelihood (81.7 and 72.5 %), respectively. Change detection was applied to identify the areas of significant changes in landuse/landcover over the last eight years. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) digital elevation model was processed to extract the drainage systems and watersheds. Water quality data of the first and second order streams were extracted from 2005 survey by Geological Survey of Northern Ireland. GIS spatially distributed modelling generated maps showing the distribution of phosphorus (P), nitrate (NO3), dissolved organic carbon (DOC), and some of the trace elements including fluoride (F), calcium (Ca), aluminium (Al), iron (Fe), copper (Cu), lead (Pb), zinc (Zn), and arsenic (As) across the watersheds of the Northern Ireland were generated. The distribution of these elements was evaluated against the LULC classes and bed rock geology. Concentration of these elements was classified into normal (safe level), moderate, high, and very high based on the World Health Organization (WHO, 2011) water quality standards. The results show that P concentration is generally high across all the watersheds. NO3 is within normal range in all watersheds. DOC is within normal range in urban areas, moderate to high in agricultural lands, and high in the forest areas and bare lands. F and Fe are within safe level in all watersheds. Al, Cu, and As are high in all watersheds around the bare land LULC class which are underlain by psammite and semipelite metamorphic rocks. Ca is within normal range in most of watersheds but it is high in the south western part of the study area because of the presence of limestone bedrock. Pb and Zn are within normal range in the urban and most of the agricultural land, and high in the mountainous areas underlain by psammite and semipelite metamorphic bed rock.

Development of a neural-based forecasting tool to classify recreational water quality using fecal indicator organisms.

PubMed

Motamarri, Srinivas; Boccelli, Dominic L

2012-09-15

Users of recreational waters may be exposed to elevated pathogen levels through various point/non-point sources. Typical daily notifications rely on microbial analysis of indicator organisms (e.g., Escherichia coli) that require 18, or more, hours to provide an adequate response. Modeling approaches, such as multivariate linear regression (MLR) and artificial neural networks (ANN), have been utilized to provide quick predictions of microbial concentrations for classification purposes, but generally suffer from high false negative rates. This study introduces the use of learning vector quantization (LVQ)--a direct classification approach--for comparison with MLR and ANN approaches and integrates input selection for model development with respect to primary and secondary water quality standards within the Charles River Basin (Massachusetts, USA) using meteorologic, hydrologic, and microbial explanatory variables. Integrating input selection into model development showed that discharge variables were the most important explanatory variables while antecedent rainfall and time since previous events were also important. With respect to classification, all three models adequately represented the non-violated samples (>90%). The MLR approach had the highest false negative rates associated with classifying violated samples (41-62% vs 13-43% (ANN) and <16% (LVQ)) when using five or more explanatory variables. The ANN performance was more similar to LVQ when a larger number of explanatory variables were utilized, but the ANN performance degraded toward MLR performance as explanatory variables were removed. Overall, the use of LVQ as a direct classifier provided the best overall classification ability with respect to violated/non-violated samples for both standards. Copyright © 2012 Elsevier Ltd. All rights reserved.

Surface-water quality in agricultural watersheds of the North Carolina Coastal Plain associated with concentrated animal feeding operations

USGS Publications Warehouse

Harden, Stephen L.

2015-01-01

A classification tree model was developed to examine relations of watershed environmental attributes among the study sites with and without CAFO manure effects. Model results indicated that variations in swine barn density, percentage of wetlands, and total acres available for applying swine-waste manures had an important influence on those watersheds where CAFO effects on water quality were either evident or mitigated. Measurable effects of CAFO waste manures on stream water quality were most evident in those SW and SP watersheds having lower percentages of wetlands combined with higher swine barn densities and (or) higher total acres available for applying waste manure at the swine CAFOs. Stream water quality was similar to background agricultural conditions in SW and SP watersheds with lower swine barn densities coupled with higher percentages of wetlands or lower acres available for swine manure applications. The model provides a useful tool for exploring and identifying similar, unmonitored watersheds in the North Carolina Coastal Plain with potential CAFO manure influences on water quality that might warrant further examination.

Estimation of urban runoff and water quality using remote sensing and artificial intelligence.

PubMed

Ha, S R; Park, S Y; Park, D H

2003-01-01

Water quality and quantity of runoff are strongly dependent on the landuse and landcover (LULC) criteria. In this study, we developed a more improved parameter estimation procedure for the environmental model using remote sensing (RS) and artificial intelligence (AI) techniques. Landsat TM multi-band (7bands) and Korea Multi-Purpose Satellite (KOMPSAT) panchromatic data were selected for input data processing. We employed two kinds of artificial intelligence techniques, RBF-NN (radial-basis-function neural network) and ANN (artificial neural network), to classify LULC of the study area. A bootstrap resampling method, a statistical technique, was employed to generate the confidence intervals and distribution of the unit load. SWMM was used to simulate the urban runoff and water quality and applied to the study watershed. The condition of urban flow and non-point contaminations was simulated with rainfall-runoff and measured water quality data. The estimated total runoff, peak time, and pollutant generation varied considerably according to the classification accuracy and percentile unit load applied. The proposed procedure would efficiently be applied to water quality and runoff simulation in a rapidly changing urban area.

Relation between urbanization and water quality of streams in the Austin area, Texas

USGS Publications Warehouse

Veenhuis, J.E.; Slade, R.M.

1990-01-01

The ratio of the number of samples with detectable concentrations to the total number of samples analyzed for 18 inorganic trace elements and the concentrations of many of these minor constituents increased with increasing development classifications. Twenty-two of the 42 synthetic organic compounds for which samples were analyzed were detected in one or more samples. The compounds were detected more frequently and in larger concentrations at the sites with more urban classifications.

Temporal water quality response in an urban river: a case study in peninsular Malaysia

NASA Astrophysics Data System (ADS)

VishnuRadhan, Renjith; Zainudin, Zaki; Sreekanth, G. B.; Dhiman, Ravinder; Salleh, Mohd. Noor; Vethamony, P.

2017-05-01

Ambient water quality is a prerequisite for the health and self-purification capacity of riverine ecosystems. To understand the general water quality situation, the time series data of selected water quality parameters were analyzed in an urban river in Peninsular Malaysia. In this regard, the stations were selected from the main stem of the river as well as from the side channel. The stations located at the main stem of the river are less polluted than that in the side channel. Water Quality Index scores indicated that the side channel station is the most polluted, breaching the Class IV water quality criteria threshold during the monitoring period, followed by stations at the river mouth and the main channel. The effect of immediate anthropogenic waste input is also evident at the side channel station. The Organic Pollution Index of side channel station is (14.99) 3 times higher than at stations at river mouth (4.11) and 6 times higher than at the main channel (2.57). The two-way ANOVA showed significant difference among different stations. Further, the factor analysis on water quality parameters yielded two significant factors. They discriminated the stations into two groups. The land-use land cover classification of the study area shows that the region near the sampling sites is dominated by urban settlements (33.23 %) and this can contribute significantly to the deterioration of ambient river water quality. The present study estimated the water quality condition and response in the river and the study can be an immediate yardstick for base lining river water quality, and a basis for future water quality modeling studies in the region.

Developing a Water Quality Index (WQI) for an Irrigation Dam.

PubMed

De La Mora-Orozco, Celia; Flores-Lopez, Hugo; Rubio-Arias, Hector; Chavez-Duran, Alvaro; Ochoa-Rivero, Jesus

2017-04-29

Pollution levels have been increasing in water ecosystems worldwide. A water quality index (WQI) is an available tool to approximate the quality of water and facilitate the work of decision-makers by grouping and analyzing numerous parameters with a single numerical classification system. The objective of this study was to develop a WQI for a dam used for irrigation of about 5000 ha of agricultural land. The dam, La Vega, is located in Teuchitlan, Jalisco, Mexico. Seven sites were selected for water sampling and samples were collected in March, June, July, September, and December 2014 in an initial effort to develop a WQI for the dam. The WQI methodology, which was recommended by the Mexican National Water Commission (CNA), was used. The parameters employed to calculate the WQI were pH, electrical conductivity (EC), dissolved oxygen (DO), total dissolved solids (TDS), total hardness (TH), alkalinity (Alk), total phosphorous (TP), Cl - , NO₃, SO₄, Ca, Mg, K, B, As, Cu, and Zn. No significant differences in WQI values were found among the seven sampling sites along the dam. However, seasonal differences in WQI were noted. In March and June, water quality was categorized as poor. By July and September, water quality was classified as medium to good. Quality then decreased, and by December water quality was classified as medium to poor. In conclusion, water treatment must be applied before waters from La Vega dam reservoir can be used for irrigation or other purposes. It is recommended that the water quality at La Vega dam is continually monitored for several years in order to confirm the findings of this short-term study.

Water quality of Danube Delta systems: ecological status and prediction using machine-learning algorithms.

PubMed

Stoica, C; Camejo, J; Banciu, A; Nita-Lazar, M; Paun, I; Cristofor, S; Pacheco, O R; Guevara, M

2016-01-01

Environmental issues have a worldwide impact on water bodies, including the Danube Delta, the largest European wetland. The Water Framework Directive (2000/60/EC) implementation operates toward solving environmental issues from European and national level. As a consequence, the water quality and the biocenosis structure was altered, especially the composition of the macro invertebrate community which is closely related to habitat and substrate heterogeneity. This study aims to assess the ecological status of Southern Branch of the Danube Delta, Saint Gheorghe, using benthic fauna and a computational method as an alternative for monitoring the water quality in real time. The analysis of spatial and temporal variability of unicriterial and multicriterial indices were used to assess the current status of aquatic systems. In addition, chemical status was characterized. Coliform bacteria and several chemical parameters were used to feed machine-learning (ML) algorithms to simulate a real-time classification method. Overall, the assessment of the water bodies indicated a moderate ecological status based on the biological quality elements or a good ecological status based on chemical and ML algorithms criteria.

Using high frequency water quality data to assess sampling strategies for the EU Water Framework Directive

NASA Astrophysics Data System (ADS)

Skeffington, R. A.; Halliday, S. J.; Wade, A. J.; Bowes, M. J.; Loewenthal, M.

2015-01-01

The EU Water Framework Directive (WFD) requires that the ecological and chemical status of water bodies in Europe should be assessed, and action taken where possible to ensure that at least "good" quality is attained in each case by 2015. This paper is concerned with the accuracy and precision with which chemical status in rivers can be measured given certain sampling strategies, and how this can be improved. High frequency (hourly) chemical data from four rivers in southern England were subsampled to simulate different sampling strategies for four parameters used for WFD classification: dissolved phosphorus, dissolved oxygen, pH and water temperature. These data sub-sets were then used to calculate the WFD classification for each site. Monthly sampling was less precise than weekly sampling, but the effect on WFD classification depended on the closeness of the range of concentrations to the class boundaries. In some cases, monthly sampling for a year could result in the same water body being assigned to one of 3 or 4 WFD classes with 95% confidence, whereas with weekly sampling this was 1 or 2 classes for the same cases. In the most extreme case, random sampling effects could result in the same water body being assigned to any of the 5 WFD quality classes. The width of the weekly sampled confidence intervals was about 33% that of the monthly for P species and pH, about 50% for dissolved oxygen, and about 67% for water temperature. For water temperature, which is assessed as the 98th percentile in the UK, monthly sampling biases the mean downwards by about 1 °C compared to the true value, due to problems of assessing high percentiles with limited data. Confining sampling to the working week compared to all seven days made little difference, but a modest improvement in precision could be obtained by sampling at the same time of day within a 3 h time window, and this is recommended. For parameters with a strong diel variation, such as dissolved oxygen, the value obtained, and thus possibly the WFD classification, can depend markedly on when in the cycle the sample was taken. Specifying this in the sampling regime would be a straightforward way to improve precision, but there needs to be agreement about how best to characterise risk in different types of river. These results suggest that in some cases it will be difficult to assign accurate WFD chemical classes or to detect likely trends using current sampling regimes, even for these largely groundwater-fed rivers. A more critical approach to sampling is needed to ensure that management actions are appropriate and supported by data.

Filtering high resolution hyperspectral imagery and analyzing it for quantification of water quality parameters and aquatic vegetation

NASA Astrophysics Data System (ADS)

Pande-Chhetri, Roshan

High resolution hyperspectral imagery (airborne or ground-based) is gaining momentum as a useful analytical tool in various fields including agriculture and aquatic systems. These images are often contaminated with stripes and noise resulting in lower signal-to-noise ratio, especially in aquatic regions where signal is naturally low. This research investigates effective methods for filtering high spatial resolution hyperspectral imagery and use of the imagery in water quality parameter estimation and aquatic vegetation classification. The striping pattern of the hyperspectral imagery is non-parametric and difficult to filter. In this research, a de-striping algorithm based on wavelet analysis and adaptive Fourier domain normalization was examined. The result of this algorithm was found superior to other available algorithms and yielded highest Peak Signal to Noise Ratio improvement. The algorithm was implemented on individual image bands and on selected bands of the Maximum Noise Fraction (MNF) transformed images. The results showed that image filtering in the MNF domain was efficient and produced best results. The study investigated methods of analyzing hyperspectral imagery to estimate water quality parameters and to map aquatic vegetation in case-2 waters. Ground-based hyperspectral imagery was analyzed to determine chlorophyll-a (Chl-a) concentrations in aquaculture ponds. Two-band and three-band indices were implemented and the effect of using submerged reflectance targets was evaluated. Laboratory measured values were found to be in strong correlation with two-band and three-band spectral indices computed from the hyperspectral image. Coefficients of determination (R2) values were found to be 0.833 and 0.862 without submerged targets and stronger values of 0.975 and 0.982 were obtained using submerged targets. Airborne hyperspectral images were used to detect and classify aquatic vegetation in a black river estuarine system. Image normalization for water surface reflectance and water depths was conducted and non-parametric classifiers such as ANN, SVM and SAM were tested and compared. Quality assessment indicated better classification and detection when non-parametric classifiers were applied to normalized or depth invariant transform images. Best classification accuracy of 73% was achieved when ANN is applied on normalized image and best detection accuracy of around 92% was obtained when SVM or SAM was applied on depth invariant images.

Spatiotemporal assessment of water chemistry in intermittently open/closed coastal lakes of Southern Baltic

NASA Astrophysics Data System (ADS)

Astel, Aleksander M.; Bigus, Katarzyna; Obolewski, Krystian; Glińska-Lewczuk, Katarzyna

2016-12-01

Ionic profile, pH, electrolytic conductivity, chemical oxygen demand and concentration of selected heavy metals (Ni, Cu, Zn, Fe and Mn) were determined in water of 11 intermittently closed and open lakes and lagoons (ICOLLs) located in Polish coastline. Multidimensional data set was explored by the use of the self-organizing map (SOM) technique to avoid supervised and predictable division for fully isolated, partially and fully connected lakes. Water quality assessment based on single parameter's mean value allowed classification of majority of lakes to first or second class of purity according to regulation presenting classification approach applicable to uniform parts of surface waters. The SOM-based grouping revealed seven clusters comprising water samples of similar physico-chemical profile. Fully connected lakes were characterized by the highest concentration of components characteristic for sea salts (NaCl, MgCl2, MgSO4, CaSO4, K2SO4 and MgBr2), however spring samples from Łebsko were shifted to another cluster suggesting that intensive surface run-off and fresh-water inflow through Łupawa river decreases an impact of sea water intrusions. Forecasted characteristic of water collected in Resko Przymorskie lake was disturbed by high contamination by nitrites indicating accidental and local contamination due to usage of sodium nitrite for the curing of meat. Some unexpected sources of contamination was discovered in intermittently open and closed lakes. Presumably Zn contamination is due to use of wood preservatives to protect small wooden playgrounds or camping places spread around one of the lake, while increased concentration of Ni could be connected with grass and vegetation burning. Waters of Jamno lake are under the strongest anthropogenic impact due to inefficient removal of phosphates by waste water treatment plant and contamination by Fe and Mn caused by backwashing of absorption filters. Generally, the quality of ICOLLs' water was diversified, while anthropogenic impact as well as sea water intrusions determine its quality in temporal and spatial scale.∖

Oil palm plantation effects on water quality in Kalimantan, Indonesia

NASA Astrophysics Data System (ADS)

Carlson, K. M.; Curran, L. M.

2011-12-01

Global demand for palm oil has stimulated a 7-fold increase in oil palm (Elaeis guineensis) plantation area in Indonesia since 1990. Expansion will continue as Indonesia plans to double current production by 2020. Oil palm fertilizers, effluent from oil palm mills, and erosion from land clearing and roads threaten river water quality near plantations. These rivers provide essential ecosystem services including water for drinking, cooking, and washing. Robust empirical measurements of plantation expansion impacts on water resources are necessary to discern the effects of agribusiness on local livelihoods and ecosystems. In Ketapang District, West Kalimantan, Indonesian Borneo, we evaluated the effects of land cover change on water quality by assessing water chemistry in streams draining four end-member watersheds ( ~600-1900 ha watershed-1): Logged forest, mixed agro-forest dominated by rubber and upland rice fallows, young oil palm forest (0-5 years), and old oil palm forest (10-15 years). To assess land cover change, we used CLASLite software to derive fractional cover from a time series (1989-2008) of Landsat data. Nearest neighbor classification and post-classification change detection yielded classes including primary forest, logged forest, secondary forest regrowth, smallholder agriculture, and oil palm. Stream water quality (temperature, dissolved oxygen, turbidity, optical chlorphyll, and pH) and quantity (discharge) were quantified with the YSI 6600-V2 sonde. The sonde was deployed in each stream for month-long intervals 2-3 times from 2009-2010. Such extended deployment captures episodic events such as intense storms and allows examination of interdiel dynamics by sampling continuously and at high frequency, every 10 minutes. We find that across the Ketapang District study region (~12,000 km2), oil palm has cleared mostly forests (49%) and agroforests (39%). What are the impacts of such land cover changes on water quality? Compared to forests and agroforests, streams draining oil palm show greater biological activity, as indicated by elevated pH and reduced dissolved oxygen levels. Moreover, turbidity is elevated in young oil palm plantations watersheds compared to forest, agroforest, and old oil palm land covers. We discuss the implications of these findings for communities and ecosystems.

Water quality real-time monitoring system via biological detection based on video analysis

NASA Astrophysics Data System (ADS)

Xin, Chen; Fei, Yuan

2017-11-01

With the development of society, water pollution has become the most serious problem in China. Therefore, real-time water quality monitoring is an important part of human activities and water pollution prevention. In this paper, the behavior of zebrafish was monitored by computer vision. Firstly, the moving target was extracted by the method of saliency detection, and tracked by fitting the ellipse model. Then the motion parameters were extracted by optical flow method, and the data were monitored in real time by means of Hinkley warning and threshold warning. We achieved classification warning through a number of dimensions by comprehensive toxicity index. The experimental results show that the system can achieve more accurate real-time monitoring.

A Novel approach for monitoring cyanobacterial blooms using an ensemble based system from MODIS imagery downscaled to 250 metres spatial resolution

NASA Astrophysics Data System (ADS)

El Alem, A.; Chokmani, K.; Laurion, I.; El-Adlouni, S. E.

2014-12-01

In reason of inland freshwaters sensitivity to Harmful algae blooms (HAB) development and the limits coverage of standards monitoring programs, remote sensing data have become increasingly used for monitoring HAB extension. Usually, HAB monitoring using remote sensing data is based on empirical and semi-empirical models. Development of such models requires a great number of continuous in situ measurements to reach an acceptable accuracy. However, Ministries and water management organizations often use two thresholds, established by the World Health Organization, to determine water quality. Consequently, the available data are ordinal «semi-qualitative» and they are mostly unexploited. Use of such databases with remote sensing data and statistical classification algorithms can produce hazard management maps linked to the presence of cyanobacteria. Unlike standard classification algorithms, which are generally unstable, classifiers based on ensemble systems are more general and stable. In the present study, an ensemble based classifier was developed and compared to a standard classification method called CART (Classification and Regression Tree) in a context of HAB monitoring in freshwaters using MODIS images downscaled to 250 spatial resolution and ordinal in situ data. Calibration and validation data on cyanobacteria densities were collected by the Ministère du Développement durable, de l'Environnement et de la Lutte contre les changements climatiques on 22 waters bodies between 2000 and 2010. These data comprise three density classes: waters poorly (< 20,000 cells mL-1), moderately (20,000 - 100,000 cells mL-1), and highly (> 100,000 cells mL-1) loaded in cyanobacteria. Results were very interesting and highlighted that inland waters exhibit different spectral response allowing them to be classified into the three above classes for water quality monitoring. On the other, even if the accuracy (Kappa-index = 0.86) of the proposed approach is relatively lower than that of the CART algorithm (Kappa-index = 0.87), but its robustness is higher with a standard-deviation of 0.05 versus 0.06, specifically when applied on MODIS images. A new accurate, robust, and quick approach is thus proposed for a daily near real-time monitoring of HAB in southern Quebec freshwaters.

Application of biomonitoring and support vector machine in water quality assessment*

PubMed Central

Liao, Yue; Xu, Jian-yu; Wang, Zhu-wei

2012-01-01

The behavior of schools of zebrafish (Danio rerio) was studied in acute toxicity environments. Behavioral features were extracted and a method for water quality assessment using support vector machine (SVM) was developed. The behavioral parameters of fish were recorded and analyzed during one hour in an environment of a 24-h half-lethal concentration (LC50) of a pollutant. The data were used to develop a method to evaluate water quality, so as to give an early indication of toxicity. Four kinds of metal ions (Cu2+, Hg2+, Cr6+, and Cd2+) were used for toxicity testing. To enhance the efficiency and accuracy of assessment, a method combining SVM and a genetic algorithm (GA) was used. The results showed that the average prediction accuracy of the method was over 80% and the time cost was acceptable. The method gave satisfactory results for a variety of metal pollutants, demonstrating that this is an effective approach to the classification of water quality. PMID:22467374

Spring water quality and usability in the Mount Cameroon area revealed by hydrogeochemistry.

PubMed

Ako, Andrew Ako; Shimada, Jun; Hosono, Takahiro; Kagabu, Makoto; Ayuk, Akoachere Richard; Nkeng, George Elambo; Eyong, Gloria Eneke Takem; Fouepe Takounjou, Alain L

2012-10-01

Groundwater is the only reliable water resource for drinking, domestic, and agricultural purposes for the people living in the Mount Cameroon area. Hydrogeochemical and R-mode factor analysis were used to identify hydrogeochemical processes controlling spring water quality and assess its usability for the above uses. Main water types in the study area are Ca-Mg-HCO(3) and Na-HCO(3). This study reveals that three processes are controlling the spring water quality. CO(2)-driven silicate weathering and reverse cation exchange are the most important processes affecting the hydrochemistry of the spring waters. While tropical oceanic monsoon chloride-rich/sulfate-rich rainwater seems to affect spring water chemistry at low-altitude areas, strong correlations exist between major ions, dissolved silica and the altitude of springs. In general, the spring waters are suitable for drinking and domestic uses. Total hardness (TH) values indicate a general softness of the waters, which is linked to the development of cardiovascular diseases. Based on Na %, residual sodium carbonate, sodium adsorption ratio, and the USSL classification, the spring waters are considered suitable for irrigation. Though there is wide spread use of chemical fertilizers and intense urban settlements at the lower flanks of the volcano, anthropogenic activities for now seem to have little impact on the spring water quality.

The river absorption capacity determination as a tool to evaluate state of surface water

NASA Astrophysics Data System (ADS)

Wilk, Paweł; Orlińska-Woźniak, Paulina; Gębala, Joanna

2018-02-01

In order to complete a thorough and systematic assessment of water quality, it is useful to measure the absorption capacity of a river. Absorption capacity is understood as a pollution load introduced into river water that will not cause permanent and irreversible changes in the aquatic ecosystem and will not cause a change in the classification of water quality in the river profile. In order to implement the method, the Macromodel DNS/SWAT basin for the Middle Warta pilot (central Poland) was used to simulate nutrient loads. This enabled detailed analysis of water quality in each water body and the assessment of the size of the absorption capacity parameter, which allows the determination of how much pollution can be added to the river without compromising its quality class. Positive values of the calculated absorption capacity parameter mean that it is assumed that the ecosystem is adjusted in such a way that it can eliminate pollution loads through a number of self-purification processes. Negative values indicate that the load limit has been exceeded, and too much pollution has been introduced into the ecosystem for it to be able to deal with through the processes of self-purification. Absorption capacity thus enables the connection of environmental standards of water quality and water quality management plans in order to meet these standards.

Spectral and spatial resolution analysis of multi sensor satellite data for coral reef mapping: Tioman Island, Malaysia

NASA Astrophysics Data System (ADS)

Pradhan, Biswajeet; Kabiri, Keivan

2012-07-01

This paper describes an assessment of coral reef mapping using multi sensor satellite images such as Landsat ETM, SPOT and IKONOS images for Tioman Island, Malaysia. The study area is known to be one of the best Islands in South East Asia for its unique collection of diversified coral reefs and serves host to thousands of tourists every year. For the coral reef identification, classification and analysis, Landsat ETM, SPOT and IKONOS images were collected processed and classified using hierarchical classification schemes. At first, Decision tree classification method was implemented to separate three main land cover classes i.e. water, rural and vegetation and then maximum likelihood supervised classification method was used to classify these main classes. The accuracy of the classification result is evaluated by a separated test sample set, which is selected based on the fieldwork survey and view interpretation from IKONOS image. Few types of ancillary data in used are: (a) DGPS ground control points; (b) Water quality parameters measured by Hydrolab DS4a; (c) Sea-bed substrates spectrum measured by Unispec and; (d) Landcover observation photos along Tioman island coastal area. The overall accuracy of the final classification result obtained was 92.25% with the kappa coefficient is 0.8940. Key words: Coral reef, Multi-spectral Segmentation, Pixel-Based Classification, Decision Tree, Tioman Island

Developing a Water Quality Index (WQI) for an Irrigation Dam

PubMed Central

De La Mora-Orozco, Celia; Flores-Lopez, Hugo; Rubio-Arias, Hector; Chavez-Duran, Alvaro; Ochoa-Rivero, Jesus

2017-01-01

Pollution levels have been increasing in water ecosystems worldwide. A water quality index (WQI) is an available tool to approximate the quality of water and facilitate the work of decision-makers by grouping and analyzing numerous parameters with a single numerical classification system. The objective of this study was to develop a WQI for a dam used for irrigation of about 5000 ha of agricultural land. The dam, La Vega, is located in Teuchitlan, Jalisco, Mexico. Seven sites were selected for water sampling and samples were collected in March, June, July, September, and December 2014 in an initial effort to develop a WQI for the dam. The WQI methodology, which was recommended by the Mexican National Water Commission (CNA), was used. The parameters employed to calculate the WQI were pH, electrical conductivity (EC), dissolved oxygen (DO), total dissolved solids (TDS), total hardness (TH), alkalinity (Alk), total phosphorous (TP), Cl−, NO3, SO4, Ca, Mg, K, B, As, Cu, and Zn. No significant differences in WQI values were found among the seven sampling sites along the dam. However, seasonal differences in WQI were noted. In March and June, water quality was categorized as poor. By July and September, water quality was classified as medium to good. Quality then decreased, and by December water quality was classified as medium to poor. In conclusion, water treatment must be applied before waters from La Vega dam reservoir can be used for irrigation or other purposes. It is recommended that the water quality at La Vega dam is continually monitored for several years in order to confirm the findings of this short-term study. PMID:28468230

Water Quality Conditions at Tributary Projects in the Omaha District: 2008 Report

DTIC Science & Technology

2009-01-01

SPONSOR/MONITOR’S ACRONYM(S) 11. SPONSOR/MONITOR’S REPORT NUMBER(S) 12. DISTRIBUTION /AVAILABILITY STATEMENT Approved for public release... distribution unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT Same as... Plankton

Agricultural Land Use mapping by multi-sensor approach for hydrological water quality monitoring

NASA Astrophysics Data System (ADS)

Brodsky, Lukas; Kodesova, Radka; Kodes, Vit

2010-05-01

The main objective of this study is to demonstrate potential of operational use of the high and medium resolution remote sensing data for hydrological water quality monitoring by mapping agriculture intensity and crop structures. In particular use of remote sensing mapping for optimization of pesticide monitoring. The agricultural mapping task is tackled by means of medium spatial and high temporal resolution ESA Envisat MERIS FR images together with single high spatial resolution IRS AWiFS image covering the whole area of interest (the Czech Republic). High resolution data (e.g. SPOT, ALOS, Landsat) are often used for agricultural land use classification, but usually only at regional or local level due to data availability and financial constraints. AWiFS data (nominal spatial resolution 56 m) due to the wide satellite swath seems to be more suitable for use at national level. Nevertheless, one of the critical issues for such a classification is to have sufficient image acquisitions over the whole vegetation period to describe crop development in appropriate way. ESA MERIS middle-resolution data were used in several studies for crop classification. The high temporal and also spectral resolution of MERIS data has indisputable advantage for crop classification. However, spatial resolution of 300 m results in mixture signal in a single pixel. AWiFS-MERIS data synergy brings new perspectives in agricultural Land Use mapping. Also, the developed methodology procedure is fully compatible with future use of ESA (GMES) Sentinel satellite images. The applied methodology of hybrid multi-sensor approach consists of these main stages: a/ parcel segmentation and spectral pre-classification of high resolution image (AWiFS); b/ ingestion of middle resolution (MERIS) vegetation spectro-temporal features; c/ vegetation signatures unmixing; and d/ semantic object-oriented classification of vegetation classes into final classification scheme. These crop groups were selected to be classified: winter crops, spring crops, oilseed rape, legumes, summer and other crops. This study highlights operational potentials of high temporal full resolution MERIS images in agricultural land use monitoring. Practical application of this methodology is foreseen, among others, in the water quality monitoring. Effective pesticide monitoring relies also on spatial distribution of applied pesticides, which can be derived from crop - plant protection product relationship. Knowledge of areas with predominant occurrence of specific crop based on remote sensing data described above can be used for a forecast of probable plant protection product application, thus cost-effective pesticide monitoring. The remote sensing data used on a continuous basis can be used in other long-term water management issues and provide valuable data for decision makers. Acknowledgement: Authors acknowledge the financial support of the Ministry of Education, Youth and Sports of the Czech Republic (grants No. 2B06095 and No. MSM 6046070901). The study was also supported by ESA CAT-1 (ref. 4358) and SOSI projects (Spatial Observation Services and Infrastructure; ref. GSTP-RTDA-EOPG-SW-08-0004).

Performance of biotic indices in comparison to chemical-based Water Quality Index (WQI) in evaluating the water quality of urban river.

PubMed

Wan Abdul Ghani, Wan Mohd Hafezul; Abas Kutty, Ahmad; Mahazar, Mohd Akmal; Al-Shami, Salman Abdo; Ab Hamid, Suhaila

2018-04-19

In order to evaluate the water quality of one of the most polluted urban river in Malaysia, the Penchala River, performance of eight biotic indices, Biomonitoring Working Party (BMWP), BMWP Thai , BMWP Viet , Average Score Per Taxon (ASPT), ASPT Thai , BMWP Viet , Family Biotic Index (FBI), and Singapore Biotic Index (SingScore), was compared. The water quality categorization based on these biotic indices was then compared with the categorization of Malaysian Water Quality Index (WQI) derived from measurements of six water physicochemical parameters (pH, BOD, COD, NH 3 -N, DO, and TSS). The river was divided into four sections: upstream section (recreational area), middle stream 1 (residential area), middle stream 2 (commercial area), and downstream. Abundance and diversity of the macroinvertebrates were the highest in the upstream section (407 individual and H' = 1.56, respectively), followed by the middle stream 1 (356 individual and H' = 0.82). The least abundance was recorded in the downstream section (214 individual). Among all biotic indices, BMWP was the most reliable in evaluating the water quality of this urban river as their classifications were comparable to the WQI. BMWPs in this study have strong relationships with dissolved oxygen (DO) content. Our results demonstrated that the biotic indices were more sensitive towards organic pollution than the WQI. BMWP indices especially BMWP Viet were the most reliable and could be adopted along with the WQI for assessment of water quality in urban rivers.

Remote sensing applications in agriculture and forestry. Applications of aerial photography and ERTS data to agricultural, forest and water resources management

NASA Technical Reports Server (NTRS)

1973-01-01

Remote sensing techniques are being used in Minnesota to study: (1) forest disease detection and control; (2) water quality indicators; (3) forest vegetation classification and management; (4) detection of saline soils in the Red River Valley; (5) corn defoliation; and (6) alfalfa crop productivity. Results of progress, and plans for future work in these areas, are discussed.

The Identification of Hunger Behaviour of Lates Calcarifer through the Integration of Image Processing Technique and Support Vector Machine

NASA Astrophysics Data System (ADS)

Taha, Z.; Razman, M. A. M.; Adnan, F. A.; Ghani, A. S. Abdul; Majeed, A. P. P. Abdul; Musa, R. M.; Sallehudin, M. F.; Mukai, Y.

2018-03-01

Fish Hunger behaviour is one of the important element in determining the fish feeding routine, especially for farmed fishes. Inaccurate feeding routines (under-feeding or over-feeding) lead the fishes to die and thus, reduces the total production of fishes. The excessive food which is not eaten by fish will be dissolved in the water and thus, reduce the water quality (oxygen quantity in the water will be reduced). The reduction of oxygen (water quality) leads the fish to die and in some cases, may lead to fish diseases. This study correlates Barramundi fish-school behaviour with hunger condition through the hybrid data integration of image processing technique. The behaviour is clustered with respect to the position of the centre of gravity of the school of fish prior feeding, during feeding and after feeding. The clustered fish behaviour is then classified by means of a machine learning technique namely Support vector machine (SVM). It has been shown from the study that the Fine Gaussian variation of SVM is able to provide a reasonably accurate classification of fish feeding behaviour with a classification accuracy of 79.7%. The proposed integration technique may increase the usefulness of the captured data and thus better differentiates the various behaviour of farmed fishes.

[The establishment, development and application of classification approach of freshwater phytoplankton based on the functional group: a review].

PubMed

Yang, Wen; Zhu, Jin-Yong; Lu, Kai-Hong; Wan, Li; Mao, Xiao-Hua

2014-06-01

Appropriate schemes for classification of freshwater phytoplankton are prerequisites and important tools for revealing phytoplanktonic succession and studying freshwater ecosystems. An alternative approach, functional group of freshwater phytoplankton, has been proposed and developed due to the deficiencies of Linnaean and molecular identification in ecological applications. The functional group of phytoplankton is a classification scheme based on autoecology. In this study, the theoretical basis and classification criterion of functional group (FG), morpho-functional group (MFG) and morphology-based functional group (MBFG) were summarized, as well as their merits and demerits. FG was considered as the optimal classification approach for the aquatic ecology research and aquatic environment evaluation. The application status of FG was introduced, with the evaluation standards and problems of two approaches to assess water quality on the basis of FG, index methods of Q and QR, being briefly discussed.

Discussion on Coking Wastewater Treatment and Control Measures in Iron and Steel Enterprises

NASA Astrophysics Data System (ADS)

Zhang, Lei; Hwang, Jiannyang; Leng, Ting; Xue, Gaifeng; Wu, Gaoming

According to the water quality characteristics of coking wastewater and the environmental protection requirements, the status of coking wastewater treatment technologies at home and abroad was described. Several methods and control measures of coking wastewater treatment were discussed in the effluent from iron and steel enterprises. It is an effective way to makes use of cleaner production technologies to reduce the amount of coking phenol cyanide wastewater produced from the source, and then adopt water supply for different water quality or series classification in-house according to the demand of water characters. It is necessary though looking for the available disposal way to reduce the coking wastewater effluent, which can provide a reference for process selection and research on treatment of coking wastewater in iron and steel enterprise.

Using hydrologic landscape classification to assess streamflow vulnerability to changes in climate

EPA Science Inventory

Identifying regions with similar hydrology is useful for assessing water quality and quantity across the U.S., especially areas that are difficult or costly to monitor. For example, hydrologic landscapes (HLs) have been used to map streamflow variability and assess the spatial di...

An assessment of streamflow vulnerability to climate using Hydrologic Landscape classification

EPA Science Inventory

Identifying regions with similar hydrology is useful for assessing water quality and quantity across the U.S., especially areas that are difficult or costly to monitor. For example, hydrologic landscapes (HLs) have been used to map streamflow variability and assess the spatial di...

Mapping Ecosystem Services in the Jordan Valley, Jordan

NASA Astrophysics Data System (ADS)

Luz, Ana; Marques, Ana; Ribeiro, Inês; Alho, Maria; Catarina Afonso, Ana; Almeida, Erika; Branquinho, Cristina; Talozi, Samer; Pinho, Pedro

2016-04-01

In the last decade researchers started using ecosystem services as a new framework to understand the relationships between environment and society. Habitat quality and water quality are related with ecosystem services regulation and maintenance, or even provision. According to the Common International Classification of Ecosystem Services (CICES) both habitat quality and water quality are associated with lifecycle maintenance, habitat and gene pool protection, and water conditions, among others. As there is increased pressure on habitats and rivers especially for agricultural development, mapping and evaluating habitat and water quality has important implications for resource management and conservation, as well as for rural development. Here, we model and map habitat and water quality in the Jordan Valley, Jordan. In this study, we aim to identify and analyse ecosystem services both through 1) habitat quality and 2) water quality modelling using InVest, an integrated valuation of ecosystem services and tradeoffs. The data used in this study mainly includes the LULC, Jordan River watershed and main threats and pollutants in the study area, such as agriculture, industry, fish farms and urbanization. Results suggest a higher pressure on natural habitats in the Northern region of the Jordan Valley, where industry is dominant. Agriculture is present along the Jordan Valley and limits the few natural forested areas. Further, water pollution is mainly concentrated in disposal sites due to the low flow of the Jordan River. Our results can help to identify areas where natural resources and water resource management is most needed in the Jordan Valley. Acknowledgements: Transbasin FP7 project

Validation of green-solvent extraction combined with chromatographic chemical fingerprint to evaluate quality of Stevia rebaudiana Bertoni.

PubMed

Teo, Chin Chye; Tan, Swee Ngin; Yong, Jean Wan Hong; Hew, Choy Sin; Ong, Eng Shi

2009-02-01

An approach that combined green-solvent methods of extraction with chromatographic chemical fingerprint and pattern recognition tools such as principal component analysis (PCA) was used to evaluate the quality of medicinal plants. Pressurized hot water extraction (PHWE) and microwave-assisted extraction (MAE) were used and their extraction efficiencies to extract two bioactive compounds, namely stevioside (SV) and rebaudioside A (RA), from Stevia rebaudiana Bertoni (SB) under different cultivation conditions were compared. The proposed methods showed that SV and RA could be extracted from SB using pure water under optimized conditions. The extraction efficiency of the methods was observed to be higher or comparable to heating under reflux with water. The method precision (RSD, n = 6) was found to vary from 1.91 to 2.86% for the two different methods on different days. Compared to PHWE, MAE has higher extraction efficiency with shorter extraction time. MAE was also found to extract more chemical constituents and provide distinctive chemical fingerprints for quality control purposes. Thus, a combination of MAE with chromatographic chemical fingerprints and PCA provided a simple and rapid approach for the comparison and classification of medicinal plants from different growth conditions. Hence, the current work highlighted the importance of extraction method in chemical fingerprinting for the classification of medicinal plants from different cultivation conditions with the aid of pattern recognition tools used.

Assessment of surface water quality using a growing hierarchical self-organizing map: a case study of the Songhua River Basin, northeastern China, from 2011 to 2015.

PubMed

Jiang, Mingcen; Wang, Yeyao; Yang, Qi; Meng, Fansheng; Yao, Zhipeng; Cheng, Peixuan

2018-03-30

The analysis of a large number of multidimensional surface water monitoring data for extracting potential information plays an important role in water quality management. In this study, growing hierarchical self-organizing map (GHSOM) was applied to a water quality assessment of the Songhua River Basin in China using 22 water quality parameters monitored monthly from 13 monitoring sites from 2011 to 2015 (14,782 observations). The spatial and temporal features and correlation between the water quality parameters were explored, and the major contaminants were identified. The results showed that the downstream of the Second Songhua River had the worst water quality of the Songhua River Basin. The upstream and midstream of Nenjiang River and the Second Songhua River had the best. The major contaminants of the Songhua River were chemical oxygen demand (COD), ammonia nitrogen (NH 3 -N), total phosphorus (TP), and fecal coliform (FC). In the Songhua River, the water pollution at downstream has been gradually eased in years. However, FC and biochemical oxygen demand (BOD 5 ) showed growth over time. The component planes showed that three sets of parameters had positive correlations with each other. GHSOM was found to have advantages over self-organizing maps and hierarchical clustering analysis as follows: (1) automatically generating the necessary neurons, (2) intuitively exhibiting the hierarchical inheritance relationship between the original data, and (3) depicting the boundaries of the classification much more clearly. Therefore, the application of GHSOM in water quality assessments, especially with large amounts of monitoring data, enables the extraction of more information and provides strong support for water quality management.

Using high-frequency water quality data to assess sampling strategies for the EU Water Framework Directive

NASA Astrophysics Data System (ADS)

Skeffington, R. A.; Halliday, S. J.; Wade, A. J.; Bowes, M. J.; Loewenthal, M.

2015-05-01

The EU Water Framework Directive (WFD) requires that the ecological and chemical status of water bodies in Europe should be assessed, and action taken where possible to ensure that at least "good" quality is attained in each case by 2015. This paper is concerned with the accuracy and precision with which chemical status in rivers can be measured given certain sampling strategies, and how this can be improved. High-frequency (hourly) chemical data from four rivers in southern England were subsampled to simulate different sampling strategies for four parameters used for WFD classification: dissolved phosphorus, dissolved oxygen, pH and water temperature. These data sub-sets were then used to calculate the WFD classification for each site. Monthly sampling was less precise than weekly sampling, but the effect on WFD classification depended on the closeness of the range of concentrations to the class boundaries. In some cases, monthly sampling for a year could result in the same water body being assigned to three or four of the WFD classes with 95% confidence, due to random sampling effects, whereas with weekly sampling this was one or two classes for the same cases. In the most extreme case, the same water body could have been assigned to any of the five WFD quality classes. Weekly sampling considerably reduces the uncertainties compared to monthly sampling. The width of the weekly sampled confidence intervals was about 33% that of the monthly for P species and pH, about 50% for dissolved oxygen, and about 67% for water temperature. For water temperature, which is assessed as the 98th percentile in the UK, monthly sampling biases the mean downwards by about 1 °C compared to the true value, due to problems of assessing high percentiles with limited data. Low-frequency measurements will generally be unsuitable for assessing standards expressed as high percentiles. Confining sampling to the working week compared to all 7 days made little difference, but a modest improvement in precision could be obtained by sampling at the same time of day within a 3 h time window, and this is recommended. For parameters with a strong diel variation, such as dissolved oxygen, the value obtained, and thus possibly the WFD classification, can depend markedly on when in the cycle the sample was taken. Specifying this in the sampling regime would be a straightforward way to improve precision, but there needs to be agreement about how best to characterise risk in different types of river. These results suggest that in some cases it will be difficult to assign accurate WFD chemical classes or to detect likely trends using current sampling regimes, even for these largely groundwater-fed rivers. A more critical approach to sampling is needed to ensure that management actions are appropriate and supported by data.

Water Quality Conditions at Tributary Projects in the Omaha District: 2006 Annual Report

DTIC Science & Technology

2007-12-01

ADDRESS(ES) 10. SPONSOR/MONITOR’S ACRONYM(S) 11. SPONSOR/MONITOR’S REPORT NUMBER(S) 12. DISTRIBUTION /AVAILABILITY STATEMENT Approved for public...release; distribution unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT...14 2.3.3 Plankton

Lake trophic applications: Wisconsin

NASA Technical Reports Server (NTRS)

Scarpace, F.

1981-01-01

Efforts to classify the water quality characteristics of lakes using LANDSAT imagery are reported. Image processing and registration techniques are described. A lake classification scheme which involves the assignment of a trophic class number was used in the data analysis. The resulting values were compared to the corresponding rank assignment derived from field measurements.

Sentinel-2 Level 2A Prototype Processor: Architecture, Algorithms And First Results

NASA Astrophysics Data System (ADS)

Muller-Wilm, Uwe; Louis, Jerome; Richter, Rudolf; Gascon, Ferran; Niezette, Marc

2013-12-01

Sen2Core is a prototype processor for Sentinel-2 Level 2A product processing and formatting. The processor is developed for and with ESA and performs the tasks of Atmospheric Correction and Scene Classification of Level 1C input data. Level 2A outputs are: Bottom-Of- Atmosphere (BOA) corrected reflectance images, Aerosol Optical Thickness-, Water Vapour-, Scene Classification maps and Quality indicators, including cloud and snow probabilities. The Level 2A Product Formatting performed by the processor follows the specification of the Level 1C User Product.

Irrigation water quality of Al-Gharraf Canal, south of Iraq

NASA Astrophysics Data System (ADS)

Hussein Ewaid, Salam

2018-05-01

To evaluate the water quality of Al-Gharraf Canal south of Iraq for irrigation purpose, analysis of 12 physiochemical parameters of water samples by standard methods was carried out at five stations during the year 2016 (water temperature, pH, electrical conductivity, total dissolved solids, bicarbonate, chloride, calcium, magnesium, sulfate, nitrate, sodium, potassium). Seven irrigation water quality indices were calculated like; sodium percentage (% Na), soluble sodium percentage (SSP), residual sodium bicarbonate (RSBC), Kelly’s ratio (KR), permeability index (PI), magnesium adsorption ratio (MAR), and sodium adsorption ratio (SAR). The results represented as diagrams (Piper, Stiff, Schoeller, Durov, Gibbs, and Wilcox) using AquaChem and RockWork hydro-chemical software. Chemical analysis for canal water demonstrates the calcic chlorinated water type, the dominance of alkalis water, the major cations was in the order of: Na+ > Ca2+ > K+ > Mg2+ and major anions was: Cl- > SO42- > HCO3- > NO3-, the mean values of the irrigation water quality indices were (in meq/l) were; SAR (2.37), % Na (43.4), PI (%) (52.3), SSP (% (38.1), MAR (%) (34.5), KR (0.61), RSBC (-1.78). The results indicate the suitability of canal water for irrigational purposes based on the calculated indices for the majority of crops under special management for salinity and permeability control. The presentation of chemical analysis by diagrams and numbers makes understanding of complex water system too simpler and quicker. This study is a comprehensive assessment towards providing indicators and classification indices on irrigation water quality of the canal ecosystem, which will be the basis for future planning decisions on agricultural demand management measures and water quality monitoring to protect this principal water resource.

LANDSAT digital data for water pollution and water quality studies in Southern Scandinavia

NASA Technical Reports Server (NTRS)

Hellden, U.; Akersten, I.

1977-01-01

Spectral diagrams, illustrating the spectral characteristics of different water types, were constructed by means of simple statistical analysis of the various reflectance properties of water areas in Southern Scandinavia as registered by LANDSAT-1. There were indications that water whose spectral reproduction is dominated by chlorophyllous matter (phytoplankton) can be distinguished from water dominated by nonchlorophyllous matter. Differences between lakes, as well as the patchiness of individual lakes, concerning secchi disc transparency could be visualized after classification and reproduction in black and white and in color by means of line printer, calcomp plotter (CRT), and ink jet plotter respectively.

Integrative image segmentation optimization and machine learning approach for high quality land-use and land-cover mapping using multisource remote sensing data

NASA Astrophysics Data System (ADS)

Gibril, Mohamed Barakat A.; Idrees, Mohammed Oludare; Yao, Kouame; Shafri, Helmi Zulhaidi Mohd

2018-01-01

The growing use of optimization for geographic object-based image analysis and the possibility to derive a wide range of information about the image in textual form makes machine learning (data mining) a versatile tool for information extraction from multiple data sources. This paper presents application of data mining for land-cover classification by fusing SPOT-6, RADARSAT-2, and derived dataset. First, the images and other derived indices (normalized difference vegetation index, normalized difference water index, and soil adjusted vegetation index) were combined and subjected to segmentation process with optimal segmentation parameters obtained using combination of spatial and Taguchi statistical optimization. The image objects, which carry all the attributes of the input datasets, were extracted and related to the target land-cover classes through data mining algorithms (decision tree) for classification. To evaluate the performance, the result was compared with two nonparametric classifiers: support vector machine (SVM) and random forest (RF). Furthermore, the decision tree classification result was evaluated against six unoptimized trials segmented using arbitrary parameter combinations. The result shows that the optimized process produces better land-use land-cover classification with overall classification accuracy of 91.79%, 87.25%, and 88.69% for SVM and RF, respectively, while the results of the six unoptimized classifications yield overall accuracy between 84.44% and 88.08%. Higher accuracy of the optimized data mining classification approach compared to the unoptimized results indicates that the optimization process has significant impact on the classification quality.

A study of Minnesota forests and lakes using data from Earth Resources Technology Satellites

NASA Technical Reports Server (NTRS)

1974-01-01

Highlights of research and practical benefits are discussed for the following projects which utilized ERTS 1 data to provide municipal, state, federal, and industrial users with environmental resource information for the state of Minnesota: (1) forest disease detection and control; (2) evaluation of water quality by remote sensing techniques; (3) forest vegetation classification and management; (4) detection of saline soils in the Red River Valley; (5) snowmelt flood prediction; (6) remote sensing applications to hydrology; (7) Rice Creek watershed project; (8) water quality in Lake Superior and the Duluth Superior Harbor; and (9) determination of Lake Superior currents from turbidity patterns.

Spatial patterning of water quality in Biscayne Bay, Florida as a function of land use and water management.

PubMed

Caccia, Valentina G; Boyer, Joseph N

2005-11-01

An objective classification analysis was performed on a water quality data set from 25 sites collected monthly during 1994-2003. The water quality parameters measured included: TN, TON, DIN, NH4+, NO3-, NO2-, TP, SRP, TN:TP ratio, TOC, DO, CHL A, turbidity, salinity and temperature. Based on this spatial analysis, Biscayne Bay was divided into five zones having similar water quality characteristics. A robust nutrient gradient, driven mostly by dissolved inorganic nitrogen, from alongshore to offshore in the main Bay, was a large determinant in the spatial clustering. Two of these zones (Alongshore and Inshore) were heavily influenced by freshwater input from four canals which drain the South Dade agricultural area, Black Point Landfill, and sewage treatment plant. The North Bay zone, with high turbidity, phytoplankton biomass, total phosphorus, and low DO, was affected by runoff from five canals, the Munisport Landfill, and the urban landscape. The South Bay zone, an embayment surrounded by mangrove wetlands with little urban development, was high in dissolved organic constituents but low in inorganic nutrients. The Main Bay was the area most influenced by water exchange with the Atlantic Ocean and showed the lowest nutrient concentrations. The water quality in Biscayne Bay is therefore highly dependent of the land use and influence from the watershed.

[Study on seed quality test and quality standard of Lonicera macranthoides].

PubMed

Zhang, Ying; Xu, Jin; Li, Long-Yun; Cui, Guang-Lin; She, Yue-Hui

2016-04-01

Referring to the rules for agricultural seed testing (GB/T 3543-1995) issued by China, the test of sampling, purity, thousand seed weight, moisture, viability, relative conductivity and germination rate had been studied for seed quality test methods of Lonicera macranthoides. The seed quality from 38 different collection areas was measured to establish quality classification standard by K-means clustering. The results showed that at least 7.5 g seeds should be sampled, and passed 20-mesh sieve for purity analysis.The 500-seed method used to measure thousand seed weight. The moisture was determined by crushed seeds dried in high temperature (130±2) ℃ for 3 h.The viability determined by 25 ℃ 0.1% TTC stained 5h in dark. 1.0 g seeds soaked in 50 ml ultra pure water in 25 ℃ for 12 hours to determine the relative conductivity. The seed by 4 ℃stratification for 80 days were cultured on paper at 15 ℃. Quality of the seeds from different areas was divided into three grades. The primary seed quality classification standard was established.The I grade and II grade were recommend use in production. Copyright© by the Chinese Pharmaceutical Association.

Environmental quality assessment of groundwater resources in Al Jabal Al Akhdar, Sultanate of Oman

NASA Astrophysics Data System (ADS)

Al-Kalbani, Mohammed Saif; Price, Martin F.; Ahmed, Mushtaque; Abahussain, Asma; O'Higgins, Timothy

2017-11-01

The research was conducted to assess the quality of groundwater resources of Al Jabal Al Akhdar, Oman. 11 drinking water sources were sampled during summer and winter seasons during 2012-2013 to evaluate their physico-chemical quality indicators; and assess their suitability for drinking and other domestic purposes. Sample collection, handling and processing followed the standard methods recommended by APHA and analyzed in quality assured laboratories using appropriate analytical methods and instrumental techniques. The results show that the quality parameters in all drinking water resources are within the permissible limits set by Omani and WHO standards; and the drinking water quality index is good or medium in quality based on NFS-WQI classification criteria, indicating their suitability for human consumption. There is an indication of the presence of high nitrate concentrations in some groundwater wells, which require more investigations and monitoring program to be conducted on regular basis to ensure good quality water supply for the residents in the mountain. The trilinear Piper diagram shows that most of the drinking water resources of the study area fall in the field of calcium and bicarbonate type with some magnesium bicarbonate type indicating that most of the major ions are natural in origin due to the geology of the region. This study is a first step towards providing indicators on groundwater quality of this fragile mountain ecosystem, which will be the basis for future planning decisions on corrective demand management measures to protect groundwater resources of Al Jabal Al Akhdar.

Improving oil classification quality from oil spill fingerprint beyond six sigma approach.

PubMed

Juahir, Hafizan; Ismail, Azimah; Mohamed, Saiful Bahri; Toriman, Mohd Ekhwan; Kassim, Azlina Md; Zain, Sharifuddin Md; Ahmad, Wan Kamaruzaman Wan; Wah, Wong Kok; Zali, Munirah Abdul; Retnam, Ananthy; Taib, Mohd Zaki Mohd; Mokhtar, Mazlin

2017-07-15

This study involves the use of quality engineering in oil spill classification based on oil spill fingerprinting from GC-FID and GC-MS employing the six-sigma approach. The oil spills are recovered from various water areas of Peninsular Malaysia and Sabah (East Malaysia). The study approach used six sigma methodologies that effectively serve as the problem solving in oil classification extracted from the complex mixtures of oil spilled dataset. The analysis of six sigma link with the quality engineering improved the organizational performance to achieve its objectivity of the environmental forensics. The study reveals that oil spills are discriminated into four groups' viz. diesel, hydrocarbon fuel oil (HFO), mixture oil lubricant and fuel oil (MOLFO) and waste oil (WO) according to the similarity of the intrinsic chemical properties. Through the validation, it confirmed that four discriminant component, diesel, hydrocarbon fuel oil (HFO), mixture oil lubricant and fuel oil (MOLFO) and waste oil (WO) dominate the oil types with a total variance of 99.51% with ANOVA giving F stat >F critical at 95% confidence level and a Chi Square goodness test of 74.87. Results obtained from this study reveals that by employing six-sigma approach in a data-driven problem such as in the case of oil spill classification, good decision making can be expedited. Copyright © 2017. Published by Elsevier Ltd.

Analysis of ground-water-quality data of the Upper Colorado River basin, water years 1972-92

USGS Publications Warehouse

Apodaca, L.E.

1998-01-01

As part of the U.S. Geological Survey's National Water-Quality Assessment program, an analysis of the existing ground-water-quality data in the Upper Colorado River Basin study unit is necessary to provide information on the historic water-quality conditions. Analysis of the historical data provides information on the availability or lack of data and water-quality issues. The information gathered from the historical data will be used in the design of ground-water-quality studies in the basin. This report includes an analysis of the ground-water data (well and spring data) available for the Upper Colorado River Basin study unit from water years 1972 to 1992 for major cations and anions, metals and selected trace elements, and nutrients. The data used in the analysis of the ground-water quality in the Upper Colorado River Basin study unit were predominantly from the U.S. Geological Survey National Water Information System and the Colorado Department of Public Health and Environment data bases. A total of 212 sites representing alluvial aquifers and 187 sites representing bedrock aquifers were used in the analysis. The available data were not ideal for conducting a comprehensive basinwide water-quality assessment because of lack of sufficient geographical coverage.Evaluation of the ground-water data in the Upper Colorado River Basin study unit was based on the regional environmental setting, which describes the natural and human factors that can affect the water quality. In this report, the ground-water-quality information is evaluated on the basis of aquifers or potential aquifers (alluvial, Green River Formation, Mesaverde Group, Mancos Shale, Dakota Sandstone, Morrison Formation, Entrada Sandstone, Leadville Limestone, and Precambrian) and land-use classifications for alluvial aquifers.Most of the ground-water-quality data in the study unit were for major cations and anions and dissolved-solids concentrations. The aquifer with the highest median concentrations of major ions was the Mancos Shale. The U.S. Environmental Protection Agency secondary maximum contaminant level of 500 milligrams per liter for dissolved solids in drinking water was exceeded in about 75 percent of the samples from the Mancos Shale aquifer. The guideline by the Food and Agriculture Organization of the United States for irrigation water of 2,000 milligrams per liter was also exceeded by the median concentration from the Mancos Shale aquifer. For sulfate, the U.S. Environmental Protection Agency proposed maximum contaminant level of 500 milligrams per liter for drinking water was exceeded by the median concentration for the Mancos Shale aquifer. A total of 66 percent of the sites in the Mancos Shale aquifer exceeded the proposed maximum contaminant level.Metal and selected trace-element data were available for some sites, but most of these data also were below the detection limit. The median concentrations for iron for the selected aquifers and land-use classifications were below the U.S. Environmental Protection Agency secondary maximum contaminant level of 300 micrograms per liter in drinking water. Median concentration of manganese for the Mancos Shale exceeded the U.S. Environmental Protection Agency secondary maximum contaminant level of 50 micrograms per liter in drinking water. The highest selenium concentrations were in the alluvial aquifer and were associated with rangeland. However, about 22 percent of the selenium values from the Mancos Shale exceeded the U.S. Environmental Protection Agency maximum contaminant level of 50 micrograms per liter in drinking water.Few nutrient data were available for the study unit. The only nutrient species presented in this report were nitrate-plus-nitrite as nitrogen and orthophosphate. Median concentrations for nitrate-plus-nitrite as nitrogen were below the U.S. Environmental Protection Agency maximum contaminant level of 10 milligrams per liter in drinking water except for 0.02 percent of the sites in the al

[Spatio-temporal characteristics and source identification of water pollutants in Wenruitang River watershed].

PubMed

Ma, Xiao-xue; Wang, La-chun; Liao, Ling-ling

2015-01-01

Identifying the temp-spatial distribution and sources of water pollutants is of great significance for efficient water quality management pollution control in Wenruitang River watershed, China. A total of twelve water quality parameters, including temperature, pH, dissolved oxygen (DO), total nitrogen (TN), ammonia nitrogen (NH4+ -N), electrical conductivity (EC), turbidity (Turb), nitrite-N (NO2-), nitrate-N(NO3-), phosphate-P(PO4(3-), total organic carbon (TOC) and silicate (SiO3(2-)), were analyzed from September, 2008 to October, 2009. Geographic information system(GIS) and principal component analysis(PCA) were used to determine the spatial distribution and to apportion the sources of pollutants. The results demonstrated that TN, NH4+ -N, PO4(3-) were the main pollutants during flow period, wet period, dry period, respectively, which was mainly caused by urban point sources and agricultural and rural non-point sources. In spatial terms, the order of pollution was tertiary river > secondary river > primary river, while the water quality was worse in city zones than in the suburb and wetland zone regardless of the river classification. In temporal terms, the order of pollution was dry period > wet period > flow period. Population density, land use type and water transfer affected the water quality in Wenruitang River.

Assessment of Pressure Sources and Water Body Resilience: An Integrated Approach for Action Planning in a Polluted River Basin.

PubMed

Mirauda, Domenica; Ostoich, Marco

2018-02-23

The present study develops an integrated methodology combining the results of the water-quality classification, according to the Water Framework Directive 2000/60/EC-WFD, with those of a mathematical integrity model. It is able to analyse the potential anthropogenic impacts on the receiving water body and to help municipal decision-makers when selecting short/medium/long-term strategic mitigation actions to be performed in a territory. Among the most important causes of water-quality degradation in a river, the focus is placed on pollutants from urban wastewater. In particular, the proposed approach evaluates the efficiency and the accurate localisation of treatment plants in a basin, as well as the capacity of its river to bear the residual pollution loads after the treatment phase. The methodology is applied to a sample catchment area, located in northern Italy, where water quality is strongly affected by high population density and by the presence of agricultural and industrial activities. Nearly 10 years of water-quality data collected through official monitoring are considered for the implementation of the system. The sample basin shows different real and potential pollution conditions, according to the resilience of the river and surroundings, together with the point and diffuse pressure sources acting on the receiving body.

The importance of lake-specific characteristics for water quality across the continental United States.

PubMed

Read, Emily K; Patil, Vijay P; Oliver, Samantha K; Hetherington, Amy L; Brentrup, Jennifer A; Zwart, Jacob A; Winters, Kirsten M; Corman, Jessica R; Nodine, Emily R; Woolway, R Iestyn; Dugan, Hilary A; Jaimes, Aline; Santoso, Arianto B; Hong, Grace S; Winslow, Luke A; Hanson, Paul C; Weathers, Kathleen C

2015-06-01

Lake water quality is affected by local and regional drivers, including lake physical characteristics, hydrology, landscape position, land cover, land use, geology, and climate. Here, we demonstrate the utility of hypothesis testing within the landscape limnology framework using a random forest algorithm on a national-scale, spatially explicit data set, the United States Environmental Protection Agency's 2007 National Lakes Assessment. For 1026 lakes, we tested the relative importance of water quality drivers across spatial scales, the importance of hydrologic connectivity in mediating water quality drivers, and how the importance of both spatial scale and connectivity differ across response variables for five important in-lake water quality metrics (total phosphorus, total nitrogen, dissolved organic carbon, turbidity, and conductivity). By modeling the effect of water quality predictors at different spatial scales, we found that lake-specific characteristics (e.g., depth, sediment area-to-volume ratio) were important for explaining water quality (54-60% variance explained), and that regionalization schemes were much less effective than lake specific metrics (28-39% variance explained). Basin-scale land use and land cover explained between 45-62% of variance, and forest cover and agricultural land uses were among the most important basin-scale predictors. Water quality drivers did not operate independently; in some cases, hydrologic connectivity (the presence of upstream surface water features) mediated the effect of regional-scale drivers. For example, for water quality in lakes with upstream lakes, regional classification schemes were much less effective predictors than lake-specific variables, in contrast to lakes with no upstream lakes or with no surface inflows. At the scale of the continental United States, conductivity was explained by drivers operating at larger spatial scales than for other water quality responses. The current regulatory practice of using regionalization schemes to guide water quality criteria could be improved by consideration of lake-specific characteristics, which were the most important predictors of water quality at the scale of the continental United States. The spatial extent and high quality of contextual data available for this analysis makes this work an unprecedented application of landscape limnology theory to water quality data. Further, the demonstrated importance of lake morphology over other controls on water quality is relevant to both aquatic scientists and managers.

Using texture analysis to improve per-pixel classification of very high resolution images for mapping plastic greenhouses

NASA Astrophysics Data System (ADS)

Agüera, Francisco; Aguilar, Fernando J.; Aguilar, Manuel A.

The area occupied by plastic-covered greenhouses has undergone rapid growth in recent years, currently exceeding 500,000 ha worldwide. Due to the vast amount of input (water, fertilisers, fuel, etc.) required, and output of different agricultural wastes (vegetable, plastic, chemical, etc.), the environmental impact of this type of production system can be serious if not accompanied by sound and sustainable territorial planning. For this, the new generation of satellites which provide very high resolution imagery, such as QuickBird and IKONOS can be useful. In this study, one QuickBird and one IKONOS satellite image have been used to cover the same area under similar circumstances. The aim of this work was an exhaustive comparison of QuickBird vs. IKONOS images in land-cover detection. In terms of plastic greenhouse mapping, comparative tests were designed and implemented, each with separate objectives. Firstly, the Maximum Likelihood Classification (MLC) was applied using five different approaches combining R, G, B, NIR, and panchromatic bands. The combinations of the bands used, significantly influenced some of the indexes used to classify quality in this work. Furthermore, the quality classification of the QuickBird image was higher in all cases than that of the IKONOS image. Secondly, texture features derived from the panchromatic images at different window sizes and with different grey levels were added as a fifth band to the R, G, B, NIR images to carry out the MLC. The inclusion of texture information in the classification did not improve the classification quality. For classifications with texture information, the best accuracies were found in both images for mean and angular second moment texture parameters. The optimum window size in these texture parameters was 3×3 for IK images, while for QB images it depended on the quality index studied, but the optimum window size was around 15×15. With regard to the grey level, the optimum was 128. Thus, the optimum texture parameter depended on the main objective of the image classification. If the main classification goal is to minimize the number of pixels wrongly classified, the mean texture parameter should be used, whereas if the main classification goal is to minimize the unclassified pixels the angular second moment texture parameter should be used. On the whole, both QuickBird and IKONOS images offered promising results in classifying plastic greenhouses.

Investigation of environmental indices from the Earth Resources Technology Satellite

NASA Technical Reports Server (NTRS)

Greeley, R. S. (Principal Investigator); Riley, E. L.; Stryker, S.; Ward, E. A.

1973-01-01

The author has identified the following significant results. Land use, quality, and air quality trends are being deduced from both ERTS-1 MSS and computer compatible tapes. The data analysis plan and the preliminary data analysis phase were conducted in January 1973. Results from these two phases are: (1) Method of analysis has been selected and checked out. (2) Land use for two dates have been generated for one test site. (3) Water quality for one date has been produced partially. (4) Air quality for three has been produced and compared with ground truth. (5) One of the two DCP stations is in operation; the second station will be installed in March 1973. Land use classification exceeds pre-launch expectations. Water quality (turbidity) is not progressing as expected. Finally, mesoscale air quality results have shown correlation with NOAA/EPA turbidity network. If air quality correlations continue to show favorable results, a rapid means of global turbidity may be available from ERTS-1 MSS observations.

A neural network approach to burst detection.

PubMed

Mounce, S R; Day, A J; Wood, A S; Khan, A; Widdop, P D; Machell, J

2002-01-01

This paper describes how hydraulic and water quality data from a distribution network may be used to provide a more efficient leakage management capability for the water industry. The research presented concerns the application of artificial neural networks to the issue of detection and location of leakage in treated water distribution systems. An architecture for an Artificial Neural Network (ANN) based system is outlined. The neural network uses time series data produced by sensors to directly construct an empirical model for predication and classification of leaks. Results are presented using data from an experimental site in Yorkshire Water's Keighley distribution system.

Water quality of potential reference lakes in the Arkansas Valley and Ouachita Mountain ecoregions, Arkansas

USGS Publications Warehouse

Justus, B.G.; Meredith, Bradley J.

2014-01-01

This report describes a study to identify reference lakes in two lake classifications common to parts of two level III ecoregions in western Arkansas—the Arkansas Valley and Ouachita Mountains. Fifty-two lakes were considered. A screening process that relied on land-use data was followed by reconnaissance water-quality sampling, and two lakes from each ecoregion were selected for intensive water-quality sampling. Our data suggest that Spring Lake is a suitable reference lake for the Arkansas Valley and that Hot Springs Lake is a suitable reference lake for the Ouachita Mountains. Concentrations for five nutrient constituents—orthophosphorus, total phosphorus, total kjeldahl nitrogen, total nitrogen, and total organic carbon—were lower at Spring Lake on all nine sampling occasions and transparency measurements at Spring Lake were significantly deeper than measurements at Cove Lake. For the Ouachita Mountains ecoregion, water quality at Hot Springs Lake slightly exceeded that of Lake Winona. The most apparent water-quality differences for the two lakes were related to transparency and total organic carbon concentrations, which were deeper and lower at Hot Springs Lake, respectively. Our results indicate that when nutrient concentrations are low, transparency may be more valuable for differentiating between lake water quality than chemical constituents that have been useful for distinguishing between water-quality conditions in mesotrophic and eutrophic settings. For example, in this oligotrophic setting, concentrations for chlorophyll a can be less than 5 μg/L and diurnal variability that is typically associated with dissolved oxygen in more productive settings was not evident.

THE USE OF GEOMORPHOLOGY AND STREAM STABILITY IN THE ASSESSMENT OF THE RISK OF STREAM IMPAIRMENT FROM SEDIMENT

EPA Science Inventory

The evaluation of the current condition is critical to the management of streams impaired by sediment and other non-point source stressors, which adversely affect both physical habitat and water quality. Several rating and classification systems based on geomorphic data exist for...

Water quality in the tropical Andes hotspot: The Yacuambi river (southeastern Ecuador).

PubMed

Villa-Achupallas, Mercedes; Rosado, Daniel; Aguilar, Silvio; Galindo-Riaño, María Dolores

2018-08-15

Yacuambi river waters (southeast Ecuador, Amazonian region) were assessed to evaluate the potential risk to populations, who use it for drinking and irrigation, and ecosystems, which are part of Tropical Andes hotspot and considered some of the most biodiverse in the world. The water quality index was calculated and some quality parameters were checked to comply with Ecuadorian and North American standards for human consumption, preservation of aquatic life and irrigation. Four samplings were carried out in six stations covering the entire length of the Yacuambi river. Several parameters were analyzed: pH, conductivity, dissolved oxygen, temperature, color, phosphates, nitrite, nitrate, biochemical oxygen demand, chemical oxygen demand, total solids, turbidity, metals (Ba, Cd, Cr, Pb, As and Hg), pesticides and fecal coliforms. The water quality in the Yacuambi river was good and medium according to the classification of the Water Quality Index. However, it was unsuitable for human consumption, preservation of aquatic life and irrigation according to Ecuadorian and North American standards. Arsenic, color and fecal coliforms exceeded the limits for human consumption in all samples tested. Thresholds of preservation of aquatic life were exceeded in all samples in the case of Pb and in some samples for As, pH, nitrite and nitrate. Arsenic and fecal coliforms made Yacuambi river waters unsuitable for irrigation. Copyright © 2018 Elsevier B.V. All rights reserved.

Heavy metal determinations in algae, mussels and clams. Their possible employment for assessing the sea water quality criteria

NASA Astrophysics Data System (ADS)

Locatelli, C.

2003-05-01

An empirical criterion for a possible classification of sea water quality is proposed. It is based on the knowledge of metal content in algae (Ulva Rigida) mussels (Mytilus Galloprovincialis) and clams (Tapes Philippinarum), three species present in marine ecosystems. The elements considered are Hg, Cu, Pb, Cd, Zn, Ni and Cr. The anatytical technique employed is Atomic Absorption Spectroscopy (AAS). The analytical procedure has been verified on three standard reference materials : Sea Water BCR-CRM 403, Ulva Lactuca BCR-CRM 279 and Mussel Tissue BCR-CRM 278. For all the elements, in addition to detection limits, accuracy and precision are given : the former, expressed as retative error (e). and the latter, expressed as relative standard deviation (sr), were in all cases lower than 6%.

Quantifying the connections-linkages between land-use and water in the Kathmandu Valley, Nepal.

PubMed

Davids, Jeffrey C; Rutten, Martine M; Shah, Ram Devi T; Shah, Deep N; Devkota, Nischal; Izeboud, Petra; Pandey, Anusha; van de Giesen, Nick

2018-04-23

Land development without thoughtful water supply planning can lead to unsustainability. In practice, management of our lands and waters is often unintegrated. We present new land-use, ecological stream health, water quality, and streamflow data from nine perennial watersheds in the Kathmandu Valley, Nepal, in the 2016 monsoon (i.e., August and September) and 2017 pre-monsoon (i.e., April and May) periods. Our goal was to improve understanding of the longitudinal linkages between land-use and water. At a total of 38 locations, the Rapid Stream Assessment (RSA) protocol was used to characterize stream ecology, basic water quality parameters were collected with a handheld WTW multi-parameter meter, and stream flow was measured with a SonTek FlowTracker Acoustic Doppler Velocimeter. A pixel-based supervised classification method was used to create a 30-m gridded land use coverage from a Landsat 8 image scene captured in the fall of 2015. Our results indicated that land-use had a statistically significant impact on water quality, with built land-uses (high and low) having the greatest influence. Upstream locations of six of the nine watersheds investigated had near natural status (i.e., river quality class (RQC) 1) and water could be used for all purposes (after standard treatments as required). However, downstream RSA measurements for all nine watersheds had RQC 5 (i.e., most highly impaired). Generally, water quality deteriorated from monsoon 2016 to pre-monsoon 2017. Our findings reinforce the importance of integrated land and water management and highlight the urgency of addressing waste management issues in the Kathmandu Valley.

Comparative analysis of hydroacoustic lakebed classification in three different Brazilian reservoirs

NASA Astrophysics Data System (ADS)

Hilgert, Stephan; Sotiri, Klajdi; Fuchs, Stephan

2017-04-01

Until today, the surface of artificial water bodies around the world reached an area of around 500,000 km2 equaling one third of the surface of natural water bodies. Most of the constructed waster bodies are reservoirs with a variety of usage purposes, reaching from drinking water supply, electricity production, flood protection to recreation. All reservoirs have in common, that they disrupt riverine systems and their biochemical cycles and promote the accumulation of sediments upstream of the dam. The accumulated sediments contain organic matter, nutrients and/or pollutants which have a direct influence on the water quality within the impoundment. Consequently, detailed knowledge about the amount and the quality of accumulated sediments is an essential information for reservoir management. In many cases the extensive areas covered by the impoundments make it difficult and expensive to assess sediment characteristics with a high spatial resolution. Spatial extrapolations and mass balances based on point information may suffer from strong deviations. We combined sediment point measurements (core and grab sampling) with hydroacoustic sediment classification in order to precisely map sediment parameters. Three different reservoirs (Vossoroca, Capivari, Passauna) in the south-east of Brazil were investigated between 2011 and 2015. A single beam echosounder (EA 400, Kongsberg) with two frequencies (200 & 38 kHz) was used for the hydroacoustic classification. Over 50 core samples and 30 grab samples were taken for physical and chemical analysis to serve as ground truthing of the hydroacoustic measurements. All three reservoirs were covered with dense measurement transects allowing for a lakebed classification of the entire sediment surface. Significant correlations of physical parameters like grain size distribution and density as well chemical parameters like organic carbon content and total phosphorous with a selection of hydroacoustic parameters were obtained. They enabled the derivation of empiric models used for the extrapolation of the sediment point information to the entire reservoir surface. With the obtained spatial information carbon and phosphorous budgets were calculated. Former stock calculations, which were based solely on point sampling, could be improved The results show that the method is transferable to different reservoirs with varying characteristics in regard of their catchments, morphology and trophic state.

Trophic classification of selected Colorado lakes

NASA Technical Reports Server (NTRS)

Blackwell, R. J.; Boland, D. H. P.

1979-01-01

Multispectral scanner data, acquired over several Colorado lakes using LANDSAT-1 and aircraft, were used in conjunction with contact-sensed water quality data to determine the feasibility of assessing lacustrine trophic levels. A trophic state index was developed using contact-sensed data for several trophic indicators. Relationships between the digitally processed multispectral scanner data, several trophic indicators, and the trophic index were examined using a supervised multispectral classification technique and regression techniques. Statistically significant correlations exist between spectral bands, several of the trophic indicators and the trophic state index. Color-coded photomaps were generated which depict the spectral aspects of trophic state.

Lake water quality mapping from LANDSAT

NASA Technical Reports Server (NTRS)

Scherz, J. P.

1977-01-01

The lakes in three LANDSAT scenes were mapped by the Bendix MDAS multispectral analysis system. Field checking the maps by three separate individuals revealed approximately 90-95% correct classification for the lake categories selected. Variations between observers was about 5%. From the MDAS color coded maps the lake with the worst algae problem was easily located. This lake was closely checked and a pollution source of 100 cows was found in the springs which fed this lake. The theory, lab work and field work which made it possible for this demonstration project to be a practical lake classification procedure are presented.

Water quality of the Lexington Reservoir, Santa Clara County, California, 1978-80

USGS Publications Warehouse

Iwatsubo, R.T.; Sylvester, M.A.; Gloege, I.S.

1988-01-01

Analysis of water samples from Lexington Reservoir and Los Gatos Creek upstream from the reservoir from June 1978 through September 1980 showed that water generally met water-quality objectives identified by California Regional Water Quality Control Board, San Francisco Bay Region. Water-temperature profiles show that Lexington Reservoir is a warm monomictic lake. During summer, dissolved-oxygen concentrations generally were not reduced below 5.0 mg/L in the hyplimnion; only once during the study did bottom waters become anoxic. Water transparency decreased with depth. The euphotic zone ranged from 1.0 to 5.4 m, depending on suspended solids and algae, and was greater in summer than in spring. Calcium and bicarbonate were dominant ions at all stations except during spring, following the rainy season, when waters were a mixed cation bicarbonate type. Nitrogen concentrations were greater in samples from reservoir stations than in those from Los Gatos Creek, with most of the nitrogen in ammonia and organic forms. The amount of dissolved nitrate appeared to be related to phytoplankton abundance. Phosphorus and trace-element concentrations were low at all stations. Estimates of net primary productivity and Carlson 's trophic-state index, based on chlorophyll-a concentrations, indicated that reservoir classification ranges from oligotrophic to mesotrophic. Blue-green algae generally were predominant in reservoir samples. (USGS)

Monitoring and evaluation of the water quality of Budeasa Reservoir-Arges River, Romania.

PubMed

Ion, Antoanela; Vladescu, Luminita; Badea, Irinel Adriana; Comanescu, Laura

2016-09-01

The purpose of this study was to monitor and record the specific characteristics and properties of the Arges River water in the Budeasa Reservoir (the principal water resources of municipal tap water of the big Romanian city Pitesti and surrounding area) for a period of 5 years (2005-2009). The monitored physical and chemical parameters were turbidity, pH, electrical conductivity, chemical oxygen demand, 5 days biochemical oxygen demand, free dissolved oxygen, nitrite, nitrate, ammonia nitrogen, chloride, total dissolved iron ions, sulfate, manganese, phosphate, total alkalinity, and total hardness. The results were discussed in correlation with the precipitation values during the study. Monthly and annual values of each parameter determined in the period January 2005-December 2009 were used as a basis for the classification of Budeasa Reservoir water, according to the European legislation, as well as for assessing its quality as a drinking water supply. Principal component analysis and Pearson correlation coefficients were used as statistical procedures in order to evaluate the data obtained during this study.

Water-resources investigations in Pennsylvania; programs and activities of the U.S. Geological Survey, 1990-91

USGS Publications Warehouse

McLanahan, L.O.

1991-01-01

The U.S. Geological Survey (USGS) was established by an act of Congress on March 3, 1879, to provide a permanent Federal agency to conduct the systematic and scientific 'classification of the public lands, and examination of the geological structure, mineral resources, and products of national domain'. Since 1879, the research and fact-finding role of the USGS has grown and has been modified to meet the changing needs of the Nation it serves. Moneys for program operation of the USGS in Pennsylvania come from joint-funding agreements with State and local agencies , transfer of funds from other Federal agencies, and direct Federal allotments to the USGS. Funding is distributed among the following programs: National Water Quality Assessment; water quality programs; surface water programs; groundwater programs; logging and geophysical services; computer services; scientific publication and information; hydrologic investigations; and hydrologic surveillance. (Lantz-PTT)

Drinking Water Microbiome as a Screening Tool for ...

EPA Pesticide Factsheets

Many water utilities in the US using chloramine as disinfectant treatment in their distribution systems have experienced nitrification episodes, which detrimentally impact the water quality. A chloraminated drinking water distribution system (DWDS) simulator was operated through four successive operational schemes, including two stable events (SS) and an episode of nitrification (SF), followed by a ‘chlorine burn’ (SR) by switching disinfectant from chloramine to free chlorine. The current research investigated the viability of biological signatures as potential indicators of operational failure and predictors of nitrification in DWDS. For this purpose, we examined the bulk water (BW) bacterial microbiome of a chloraminated DWDS simulator operated through successive operational schemes, including an episode of nitrification. BW data was chosen because sampling of BW in a DWDS by water utility operators is relatively simpler and easier than collecting biofilm samples from underground pipes. The methodology applied a supervised classification machine learning approach (naïve Bayes algorithm) for developing predictive models for nitrification. Classification models were trained with biological datasets (Operational Taxonomic Unit [OTU] and genus-level taxonomic groups) generated using next generation high-throughput technology, and divided into two groups (i.e. binary) of positives and negatives (Failure and Stable, respectively). We also invest

Wise use of water in smart cities - possibilities and limitations

NASA Astrophysics Data System (ADS)

Bąk, Joanna

2018-02-01

The need to save water is due, inter alia, to the paradigm of sustainable development. There are many ways to minimize the consumption of high quality water supplied by the water supply network. These include the simplest way and those complex, requiring additional installation. The lack of water is a big problem, but not only water deficit are dangerous. There is a possibility of secondary water pollution in the water supply network due to changes in network parameters. Changes in these parameters may occur due to reduced demand for water by residents and, as a result, reduced water flow - at the same pipe diameter. The article includes a review with comparative analysis of various classification systems for the tap fittings and other sanitary equipment, such as the Water Efficiency Label (WELL) in Europe or the Water Efficiency Labelling and Standards (WELS) in Australia. Several types of perlators and flow regulators were compared in the research section. This equipment was tested in the household. The possibilities of minimizing water consumption by using them was collated. In addition, the work also analyses the evolution of water consumption in Poland in recent years and their possible relationship with the threats quality of drinking water supplied to consumers.

A classification of freshwater Louisiana lakes based on water quality and user perception data.

PubMed

Burden, D G; Malone, R F

1987-09-01

An index system developed for Louisiana lakes was based on correlations between measurable water quality parameters and perceived lake quality. Support data was provided by an extensive monitoring program of 30 lakes coordinated with opinion surveys undertaken during summer 1984. Lakes included in the survey ranged from 4 to 735 km(2) in surface area with mean depths ranging from 0.5 to 8.0 m. Water quality data indicated most of these lakes are eutrophic, although many have productive fisheries and are considered recreational assets. Perception ratings of fishing quality and its associated water quality were obtained by distributing approximately 1200 surveys to Louisiana Bass Club Associaton members. The ability of Secchi disc transparency, total organic carbon, total Kjeldahl nitrogen, total phosphorus, and chlorophyll a to discriminate between perception classes was examined using probability distributions and multivariate analyses. Secchi disc and total organic carbon best reflected perceived lake conditions; however, these parameters did not provide the discrimination necessary for developing a quantitative risk assessment of lake trophic state. Consequently, an interim lakes index system was developed based on total organic carbon and perceived lake conditions. The developed index system will aid State officials in interpretating and evaluating regularly collected lake quality data, recognizing potential problem areas, and identifying proper management policies for protecting fisheries usage within the State.

Information support for decision making on dispatching control of water distribution in irrigation

NASA Astrophysics Data System (ADS)

Yurchenko, I. F.

2018-05-01

The research has been carried out on developing the technique of supporting decision making for on-line control, operational management of water allocation for the interfarm irrigation projects basing on the analytical patterns of dispatcher control. This technique provides an increase of labour productivity as well as higher management quality due to the improved level of automation, as well as decision making optimization taking into account diagnostics of the issues, solutions classification, information being required to the decision makers.

Global access to safe water: accounting for water quality and the resulting impact on MDG progress.

PubMed

Onda, Kyle; LoBuglio, Joe; Bartram, Jamie

2012-03-01

Monitoring of progress towards the Millennium Development Goal (MDG) drinking water target relies on classification of water sources as "improved" or "unimproved" as an indicator for water safety. We adjust the current Joint Monitoring Programme (JMP) estimate by accounting for microbial water quality and sanitary risk using the only-nationally representative water quality data currently available, that from the WHO and UNICEF "Rapid Assessment of Drinking Water Quality". A principal components analysis (PCA) of national environmental and development indicators was used to create models that predicted, for most countries, the proportions of piped and of other-improved water supplies that are faecally contaminated; and of these sources, the proportions that lack basic sanitary protection against contamination. We estimate that 1.8 billion people (28% of the global population) used unsafe water in 2010. The 2010 JMP estimate is that 783 million people (11%) use unimproved sources. Our estimates revise the 1990 baseline from 23% to 37%, and the target from 12% to 18%, resulting in a shortfall of 10% of the global population towards the MDG target in 2010. In contrast, using the indicator "use of an improved source" suggests that the MDG target for drinking-water has already been achieved. We estimate that an additional 1.2 billion (18%) use water from sources or systems with significant sanitary risks. While our estimate is imprecise, the magnitude of the estimate and the health and development implications suggest that greater attention is needed to better understand and manage drinking water safety.

Is the Maternal Q-Set a Valid Measure of Preschool Child Attachment Behavior?

ERIC Educational Resources Information Center

Moss, Ellen; Bureau, Jean-Francois; Cyr, Chantal; Dubois-Comtois, Karine

2006-01-01

The objective of this study is to examine preschool-age correlates of the maternal version of the Attachment Q-Set (AQS) (Waters & Deane, 1985) in order to provide validity data. Concurrent associations between the Attachment Q-Set and measures of separation-reunion attachment classifications (Cassidy & Marvin, 1992), quality of mother-child…

Study of copper (Cu) contents in blood cockles (Anadara sp.) at Surabaya coastal waters

NASA Astrophysics Data System (ADS)

Alfionita, S.; Pursetyo, K. T.; Sahidu, A. M.

2018-04-01

Heavy metal pollution categorized as harmful effect on the environment. This study aims to determine the content and the rate of accumulation of heavy metals copper (Cu) in the mussel of cockles (Anadara sp.) This study uses observation method with descriptive analysis. The test results Cu in sea water was <0.0223 mg/L. The results have exceeded the water quality standard according to state environmental ministerial decree number 51 2004 on marine water quality standards for marine biota maximum limit of Cu in sea water is 0.008 mg/L. Copper concentration in the sediment of 6.16 mg/kg at the Wonokromo station and at the Dadapan station is 4.03 mg/kg. According to the US-EPA in 2004 on the instructions of sediment pollution classification 49.98 mg Cu/kg. The results of shells fur Cu on Wonokromo was 1.833 mg/kg and Dadapan was 1.352 mg/kg. According to the MOH Decree No.0375/B/SK/1989 about Quality Standard Biota Consumption of Metals to the maximum limit of the existing Cu concentrations in marine biota was 20 ppm or 20 mg / kg so that the content of Cu in shellfish feathers still below the limit of existing quality standards.

Characterizing the Effects of Stormwater Mitigation on Nutrient Export and Stream Concentrations

NASA Astrophysics Data System (ADS)

Bell, Colin D.; McMillan, Sara K.; Clinton, Sandra M.; Jefferson, Anne J.

2017-04-01

Urbanization increases nutrient loading and lowers residence times for processing of reactive solutes, including nitrate, total dissolved nitrogen, orthophosphate, and dissolved organic carbon), which leads to increased stream concentrations and mass export. Stormwater control measures mitigate the impacts of urbanization, and have the potential to improve stream water quality, however the net effect instream is not well understood. We monitored two urban and two suburban watersheds in Charlotte, NC to determine if mitigation controlled the fraction of total mass export during storm, if development classification as either urban or suburban (defined by the age, density and distribution of urban development) controlled storm nutrient and carbon dynamics, and if stormwater control measures were able to change stream water chemistry. While average concentrations during stormflow were generally greater than baseflow, indicating that storms are important times of solute export, the fraction of storm-derived export was unrelated to mitigation by stormwater control measures. Development classification was generally not an important control on export of N and dissolved organic carbon. However, event mean concentrations of orthophosphate were higher at the suburban sites, possibly from greater fertilizer application. Stormwater control measures influenced instream water chemistry at only one site, which also had the greatest mitigated area, but differences between stormwater control measure outflow and stream water suggest the potential for water quality improvements. Together, results suggest stormwater control measures have the potential to decrease solute concentrations from urban runoff, but the type, location, and extent of urban development in the watershed may influence the magnitude of this effect.

Dishwashing water recycling system and related water quality standards for military use.

PubMed

Church, Jared; Verbyla, Matthew E; Lee, Woo Hyoung; Randall, Andrew A; Amundsen, Ted J; Zastrow, Dustin J

2015-10-01

As the demand for reliable and safe water supplies increases, both water quality and available quantity are being challenged by population growth and climate change. Greywater reuse is becoming a common practice worldwide; however, in remote locations of limited water supply, such as those encountered in military installations, it is desirable to expand its classification to include dishwashing water to maximize the conservation of fresh water. Given that no standards for dishwashing greywater reuse by the military are currently available, the current study determined a specific set of water quality standards for dishwater recycling systems for U.S. military field operations. A tentative water reuse standard for dishwashing water was developed based on federal and state regulations and guidelines for non-potable water, and the developed standard was cross-evaluated by monitoring water quality data from a full-scale dishwashing water recycling system using an innovative electrocoagulation and ultrafiltration process. Quantitative microbial risk assessment (QMRA) was also performed based on exposure scenarios derived from literature data. As a result, a specific set of dishwashing water reuse standards for field analysis (simple, but accurate) was finalized as follows: turbidity (<1 NTU), Escherichia coli (<50 cfu mL(-1)), and pH (6-9). UV254 was recommended as a surrogate for organic contaminants (e.g., BOD5), but requires further calibration steps for validation. The developed specific water standard is the first for dishwashing water reuse and will be expected to ensure that water quality is safe for field operations, but not so stringent that design complexity, cost, and operational and maintenance requirements will not be feasible for field use. In addition the parameters can be monitored using simple equipment in a field setting with only modest training requirements and real-time or rapid sample turn-around. This standard may prove useful in future development of civilian guidelines. Copyright © 2015 Elsevier B.V. All rights reserved.

Topological Relations-Based Detection of Spatial Inconsistency in GLOBELAND30

NASA Astrophysics Data System (ADS)

Kang, S.; Chen, J.; Peng, S.

2017-09-01

Land cover is one of the fundamental data sets on environment assessment, land management and biodiversity protection, etc. Hence, data quality control of land cover is extremely critical for geospatial analysis and decision making. Due to the similar remote-sensing reflectance for some land cover types, omission and commission errors occurred in preliminary classification could result to spatial inconsistency between land cover types. In the progress of post-classification, this error checking mainly depends on manual labour to assure data quality, by which it is time-consuming and labour intensive. So a method required for automatic detection in post-classification is still an open issue. From logical inconsistency point of view, an inconsistency detection method is designed. This method consist of a grids extended 4-intersection model (GE4IM) for topological representation in single-valued space, by which three different kinds of topological relations including disjoint, touch, contain or contained-by are described, and an algorithm of region overlay for the computation of spatial inconsistency. The rules are derived from universal law in nature between water body and wetland, cultivated land and artificial surface. Through experiment conducted in Shandong Linqu County, data inconsistency can be pointed out within 6 minutes through calculation of topological inconsistency between cultivated land and artificial surface, water body and wetland. The efficiency evaluation of the presented algorithm is demonstrated by Google Earth images. Through comparative analysis, the algorithm is proved to be promising for inconsistency detection in land cover data.

[Classification of Priority Area for Soil Environmental Protection Around Water Sources: Method Proposed and Case Demonstration].

PubMed

Li, Lei; Wang, Tie-yu; Wang, Xiaojun; Xiao, Rong-bo; Li, Qi-feng; Peng, Chi; Han, Cun-liang

2016-04-15

Based on comprehensive consideration of soil environmental quality, pollution status of river, environmental vulnerability and the stress of pollution sources, a technical method was established for classification of priority area of soil environmental protection around the river-style water sources. Shunde channel as an important drinking water sources of Foshan City, Guangdong province, was studied as a case, of which the classification evaluation system was set up. In detail, several evaluation factors were selected according to the local conditions of nature, society and economy, including the pollution degree of heavy metals in soil and sediment, soil characteristics, groundwater sensitivity, vegetation coverage, the type and location of pollution sources. Data information was mainly obtained by means of field survey, sampling analysis, and remote sensing interpretation. Afterwards, Analytical Hierarchy Process (AHP) was adopted to decide the weight of each factor. The basic spatial data layers were set up respectively and overlaid based on the weighted summation assessment model in Geographical Information System (GIS), resulting in a classification map of soil environmental protection level in priority area of Shunde channel. Accordingly, the area was classified to three levels named as polluted zone, risky zone and safe zone, which respectively accounted for 6.37%, 60.90% and 32.73% of the whole study area. Polluted zone and risky zone were mainly distributed in Lecong, Longjiang and Leliu towns, with pollutants mainly resulted from the long-term development of aquaculture and the industries containing furniture, plastic constructional materials and textile and clothing. In accordance with the main pollution sources of soil, targeted and differentiated strategies were put forward. The newly established evaluation method could be referenced for the protection and sustainable utilization of soil environment around the water sources.

Data Processing and Quality Evaluation of a Boat-Based Mobile Laser Scanning System

PubMed Central

Vaaja, Matti; Kukko, Antero; Kaartinen, Harri; Kurkela, Matti; Kasvi, Elina; Flener, Claude; Hyyppä, Hannu; Hyyppä, Juha; Järvelä, Juha; Alho, Petteri

2013-01-01

Mobile mapping systems (MMSs) are used for mapping topographic and urban features which are difficult and time consuming to measure with other instruments. The benefits of MMSs include efficient data collection and versatile usability. This paper investigates the data processing steps and quality of a boat-based mobile mapping system (BoMMS) data for generating terrain and vegetation points in a river environment. Our aim in data processing was to filter noise points, detect shorelines as well as points below water surface and conduct ground point classification. Previous studies of BoMMS have investigated elevation accuracies and usability in detection of fluvial erosion and deposition areas. The new findings concerning BoMMS data are that the improved data processing approach allows for identification of multipath reflections and shoreline delineation. We demonstrate the possibility to measure bathymetry data in shallow (0–1 m) and clear water. Furthermore, we evaluate for the first time the accuracy of the BoMMS ground points classification compared to manually classified data. We also demonstrate the spatial variations of the ground point density and assess elevation and vertical accuracies of the BoMMS data. PMID:24048340

Data processing and quality evaluation of a boat-based mobile laser scanning system.

PubMed

Vaaja, Matti; Kukko, Antero; Kaartinen, Harri; Kurkela, Matti; Kasvi, Elina; Flener, Claude; Hyyppä, Hannu; Hyyppä, Juha; Järvelä, Juha; Alho, Petteri

2013-09-17

Mobile mapping systems (MMSs) are used for mapping topographic and urban features which are difficult and time consuming to measure with other instruments. The benefits of MMSs include efficient data collection and versatile usability. This paper investigates the data processing steps and quality of a boat-based mobile mapping system (BoMMS) data for generating terrain and vegetation points in a river environment. Our aim in data processing was to filter noise points, detect shorelines as well as points below water surface and conduct ground point classification. Previous studies of BoMMS have investigated elevation accuracies and usability in detection of fluvial erosion and deposition areas. The new findings concerning BoMMS data are that the improved data processing approach allows for identification of multipath reflections and shoreline delineation. We demonstrate the possibility to measure bathymetry data in shallow (0-1 m) and clear water. Furthermore, we evaluate for the first time the accuracy of the BoMMS ground points classification compared to manually classified data. We also demonstrate the spatial variations of the ground point density and assess elevation and vertical accuracies of the BoMMS data.

Replicating the microbial community and water quality performance of full-scale slow sand filters in laboratory-scale filters.

PubMed

Haig, Sarah-Jane; Quince, Christopher; Davies, Robert L; Dorea, Caetano C; Collins, Gavin

2014-09-15

Previous laboratory-scale studies to characterise the functional microbial ecology of slow sand filters have suffered from methodological limitations that could compromise their relevance to full-scale systems. Therefore, to ascertain if laboratory-scale slow sand filters (L-SSFs) can replicate the microbial community and water quality production of industrially operated full-scale slow sand filters (I-SSFs), eight cylindrical L-SSFs were constructed and were used to treat water from the same source as the I-SSFs. Half of the L-SSFs sand beds were composed of sterilized sand (sterile) from the industrial filters and the other half with sand taken directly from the same industrial filter (non-sterile). All filters were operated for 10 weeks, with the microbial community and water quality parameters sampled and analysed weekly. To characterize the microbial community phyla-specific qPCR assays and 454 pyrosequencing of the 16S rRNA gene were used in conjunction with an array of statistical techniques. The results demonstrate that it is possible to mimic both the water quality production and the structure of the microbial community of full-scale filters in the laboratory - at all levels of taxonomic classification except OTU - thus allowing comparison of LSSF experiments with full-scale units. Further, it was found that the sand type composing the filter bed (non-sterile or sterile), the water quality produced, the age of the filters and the depth of sand samples were all significant factors in explaining observed differences in the structure of the microbial consortia. This study is the first to the authors' knowledge that demonstrates that scaled-down slow sand filters can accurately reproduce the water quality and microbial consortia of full-scale slow sand filters. Copyright © 2014 Elsevier Ltd. All rights reserved.

Determination of total Cr in wastewaters of Cr electroplating factories in the I.organize industry region (Kayseri, Turkey) by ICP-AES.

PubMed

Yilmaz, Selehattin; Türe, Melike; Sadikoglu, Murat; Duran, Ali

2010-08-01

The wastewater pollution in industrial areas is one of the most important environmental problems. Heavy metal pollution, especially chromium pollution in the wastewater sources from electroplating, dyeing, and tannery, has affected the life on earth. This pollution can affect on all ecosystems and human health directly or by food chain. Therefore, the determination of total chromium in this study is of great importance. In this study, accurate, rapid, sensitive, selective, simple, and low-cost technique for the direct determination of total Cr in wastewater samples collected from the some Cr electroplating factories in March 2008 by inductively coupled plasma-atomic emission spectrometry has been developed. The analysis of a given sample is completed in about 15 min by this technique applied. As the result of the chromium analysis, the limit of quantification for the total Cr were founded to be over the limit value (0.05 mg L(-1); WHO, EPA, TSE 266, and inland water quality classification) as 1,898.78+/-0.34 mg/L at station 1 and 3,189.02+/-0.56 mg/L at station 2. The found concentration of total Cr has been determined to be IV class quality water according to the inland water classification. In order to validate the applied method, recovery studies were performed.

Quality characterization and pollution source identification of surface water using multivariate statistical techniques, Nalagarh Valley, Himachal Pradesh, India

NASA Astrophysics Data System (ADS)

Herojeet, Rajkumar; Rishi, Madhuri S.; Lata, Renu; Dolma, Konchok

2017-09-01

Sirsa River flows through the central part of the Nalagarh valley, belongs to the rapid industrial belt of Baddi, Barotiwala and Nalagarh (BBN). The appraisal of surface water quality to ascertain its utility in such ecologically sensitive areas is need of the hour. The present study envisages the application of multivariate analysis, water utility class and conventional graphical representation to reveal the hidden factor responsible for deterioration of water quality and determine the hydrochemical facies and its evolution processes of water types in Nalagarh valley, India. The quality assessment is made by estimating pH, electrical conductivity (EC), total dissolved solids (TDS), total hardness, major ions (Na+, K+, Ca2+, Mg2+, HCO3 -, Cl-, SO4 2-, NO3 - and PO4 3-), dissolved oxygen (DO), biological oxygen demand (BOD) and total coliform (TC) to determine its suitability for drinking and domestic purposes. The parameters like pH, TDS, TH, Ca2+, HCO3 -, Cl-, SO4 2-, NO3 - are within the desirable limit as per Bureau of Indian Standards (Indian Standard Drinking Water Specification (Second Edition) IS:10500. Indian Standard Institute, New Delhi, pp 1-18, 2012). Mg2+, Na+ and K+ ions for pre monsoon and EC during pre and post monsoon at few sites and approx 40% samples of BOD and TC for both seasons exceeds the permissible limits indicate organic contamination from human activities. Water quality classification for designated use indicates that maximum surface water samples are not suitable for drinking water source without conventional treatment. The result of piper trillinear and Chadha's diagram classified majority of surface water samples for both seasons fall in the fields of Ca2+-Mg2+-HCO3 - water type indicating temporary hardness. PCA and CA reveal that the surface water chemistry is influenced by natural factors such as weathering of minerals, ion exchange processes and anthropogenic factors. Thus, the present paper illustrates the importance of multivariate techniques for reliable quality characterization of surface water quality to develop effective pollution reduction strategies and maintain a fine balance between the industrialization and ecological integrity.

Water Quality Research Program: Proceedings of the Corps Chemists Meeting (6th) Held in Vicksburg, Mississippi on 16-17 May 1989

DTIC Science & Technology

1990-09-01

of Water and Wastewater, Washington, DC. Bentz , A. P . 1977. "Oil Spill Identification System," US Coast Guard R& D Center, GC- D -52-77. Eisenberg D . M...contamination - site cleanup State of criteria, contamination assessment Florida 1987 US Coast Guard CG- D 52-77 Oil spill identification system Bentz ...Unclassified -a SECURITY CLASSIFICATION AUTHORITV 3 D STR1BUTrON, AVA .ABLfTY OF REPORT 2b DECLASSIFICATION/DOWNGRADING SCHEDULE Approved for public

Physical characteristics and chemical quality of selected springs in parts of Juab, Millard, Tooele, and Utah counties, Utah

USGS Publications Warehouse

Wilberg, D.E.; Stolp, B.J.

1985-01-01

Hydrologic, geologic, and partial water quality data were collected at 90 selected springs in west-central Utah, and chemical analyses performed on water samples from 62 of the springs. Descriptions of the physiographic and geologic conditions, climate, and vegetation patterns for the study area are included. Allowable limits of certain chemical constituents in water for human and livestock consumption are included with the water quality data. Three classifications of springs were established based on physical characteristics of the springs, and chemical composition of the springflow: (1) mountain springs; (2) non-thermal valley springs, and (3) thermal valley springs. Mountain springs are in and near recharge areas, have seasonal variations of discharge and temperature, typically discharge from extrusive and metamorphic geohydrologic units, and generally discharge freshwater. Non-thermal valley springs are peripheral to recharge areas, have seasonal variations of discharge and temperature, typically discharge from a variety of geohydrologic units, and have variable water composition. Thermal valley springs are near topographic low areas of valleys , and have little seasonal variation of discharge or temperature. They typically discharge from unconsolidated deposits (but the discharge probably has flowed through buried carbonate geohydrologic units). They also have a considerable range of water composition that reflects the relative complexity of the groundwater system. (Author 's abstract)

Surface-water quantity and quality, aquatic biology, stream geomorphology, and groundwater-flow simulation for National Guard Training Center at Fort Indiantown Gap, Pennsylvania, 2002-05

USGS Publications Warehouse

Langland, Michael J.; Cinotto, Peter J.; Chichester, Douglas C.; Bilger, Michael D.; Brightbill, Robin A.

2010-01-01

Base-line and long-term monitoring of water resources of the National Guard Training Center at Fort Indiantown Gap in south-central Pennsylvania began in 2002. Results of continuous monitoring of streamflow and turbidity and monthly and stormflow water-quality samples from two continuous-record long-term stream sites, periodic collection of water-quality samples from five miscellaneous stream sites, and annual collection of biological data from 2002 to 2005 at 27 sites are discussed. In addition, results from a stream-geomorphic analysis and classification and a regional groundwater-flow model are included. Streamflow at the facility was above normal for the 2003 through 2005 water years and extremely high-flow events occurred in 2003 and in 2004. Water-quality samples were analyzed for nutrients, sediments, metals, major ions, pesticides, volatile and semi-volatile organic compounds, and explosives. Results indicated no exceedances for any constituent (except iron) above the primary and secondary drinking-water standards or health-advisory levels set by the U.S. Environmental Protection Agency. Iron concentrations were naturally elevated in the groundwater within the watershed because of bedrock lithology. The majority of the constituents were at or below the method detection limit. Sediment loads were dominated by precipitation due to the remnants of Hurricane Ivan in September 2004. More than 60 percent of the sediment load measured during the entire study was transported past the streamgage in just 2 days during that event. Habitat and aquatic-invertebrate data were collected in the summers of 2002-05, and fish data were collected in 2004. Although 2002 was a drought year, 2003-05 were above-normal flow years. Results indicated a wide diversity in invertebrates, good numbers of taxa (distinct organisms), and on the basis of a combination of metrics, the majority of the 27 sites indicated no or slight impairment. Fish-metric data from 25 sites indicated results similar to the invertebrate data. Stream classification based on evolution of the stream channels indicates about 94 percent of the channels were considered to be in equilibrium (type B or C channels), neither aggrading nor eroding. A regional, uncalibrated groundwater-flow model indicated the surface-water and groundwater-flow divides coincided. Because of folding of rock layers, groundwater was under confined conditions and nearly all the water leaves the facility via the streams.

Water quality of Somerville Lake, south-central Texas

USGS Publications Warehouse

McPherson, Emma; Mendieta, H.B.

1983-01-01

The concentration of dissolved solids ranged from 139 to 292 milligrams per liter and averaged about 220 milligrams per liter. Dissolved chloride concentrations ranged from 20 to 68 milligrams per liter and averaged 43 milligrams per liter. Dissolved sulfate concentrations ranged from 30 to 130 milligrams per liter and averaged 63 milligrams per liter. The total hardness of the water ranged from 75 to 140 milligrams per liter, expressed as calcium carbonate, placing it in the moderately hard to hard (61 to 180 milligrams per liter) classification. The concentrations of principal dissolved constituents indicate that Somerville Lake is an excellent source of water for municipal, industrial, or agricultural use.

Characterization of Escherichia coli isolates from different fecal sources by means of classification tree analysis of fatty acid methyl ester (FAME) profiles.

PubMed

Seurinck, Sylvie; Deschepper, Ellen; Deboch, Bishaw; Verstraete, Willy; Siciliano, Steven

2006-03-01

Microbial source tracking (MST) methods need to be rapid, inexpensive and accurate. Unfortunately, many MST methods provide a wealth of information that is difficult to interpret by the regulators who use this information to make decisions. This paper describes the use of classification tree analysis to interpret the results of a MST method based on fatty acid methyl ester (FAME) profiles of Escherichia coli isolates, and to present results in a format readily interpretable by water quality managers. Raw sewage E. coli isolates and animal E. coli isolates from cow, dog, gull, and horse were isolated and their FAME profiles collected. Correct classification rates determined with leaveone-out cross-validation resulted in an overall low correct classification rate of 61%. A higher overall correct classification rate of 85% was obtained when the animal isolates were pooled together and compared to the raw sewage isolates. Bootstrap aggregation or adaptive resampling and combining of the FAME profile data increased correct classification rates substantially. Other MST methods may be better suited to differentiate between different fecal sources but classification tree analysis has enabled us to distinguish raw sewage from animal E. coli isolates, which previously had not been possible with other multivariate methods such as principal component analysis and cluster analysis.

A review of distributed parameter groundwater management modeling methods

USGS Publications Warehouse

Gorelick, Steven M.

1983-01-01

Models which solve the governing groundwater flow or solute transport equations in conjunction with optimization techniques, such as linear and quadratic programing, are powerful aquifer management tools. Groundwater management models fall in two general categories: hydraulics or policy evaluation and water allocation. Groundwater hydraulic management models enable the determination of optimal locations and pumping rates of numerous wells under a variety of restrictions placed upon local drawdown, hydraulic gradients, and water production targets. Groundwater policy evaluation and allocation models can be used to study the influence upon regional groundwater use of institutional policies such as taxes and quotas. Furthermore, fairly complex groundwater-surface water allocation problems can be handled using system decomposition and multilevel optimization. Experience from the few real world applications of groundwater optimization-management techniques is summarized. Classified separately are methods for groundwater quality management aimed at optimal waste disposal in the subsurface. This classification is composed of steady state and transient management models that determine disposal patterns in such a way that water quality is protected at supply locations. Classes of research missing from the literature are groundwater quality management models involving nonlinear constraints, models which join groundwater hydraulic and quality simulations with political-economic management considerations, and management models that include parameter uncertainty.

A Review of Distributed Parameter Groundwater Management Modeling Methods

NASA Astrophysics Data System (ADS)

Gorelick, Steven M.

1983-04-01

Models which solve the governing groundwater flow or solute transport equations in conjunction with optimization techniques, such as linear and quadratic programing, are powerful aquifer management tools. Groundwater management models fall in two general categories: hydraulics or policy evaluation and water allocation. Groundwater hydraulic management models enable the determination of optimal locations and pumping rates of numerous wells under a variety of restrictions placed upon local drawdown, hydraulic gradients, and water production targets. Groundwater policy evaluation and allocation models can be used to study the influence upon regional groundwater use of institutional policies such as taxes and quotas. Furthermore, fairly complex groundwater-surface water allocation problems can be handled using system decomposition and multilevel optimization. Experience from the few real world applications of groundwater optimization-management techniques is summarized. Classified separately are methods for groundwater quality management aimed at optimal waste disposal in the subsurface. This classification is composed of steady state and transient management models that determine disposal patterns in such a way that water quality is protected at supply locations. Classes of research missing from the literature are groundwater quality management models involving nonlinear constraints, models which join groundwater hydraulic and quality simulations with political-economic management considerations, and management models that include parameter uncertainty.

Classification scheme for acid rock drainage detection - the Hamersley Basin, Western Australia

NASA Astrophysics Data System (ADS)

Skrzypek, Grzegorz; Dogramaci, Shawan; McLean, Laura

2017-04-01

In arid environment where precipitation and surface water are very limited, groundwater is the most important freshwater resource. For this reasons it is intensively exploited and needs to be managed wisely and protected from pollutants. Acid rock drainage often constitutes a serious risk to groundwater quality, particularly in catchments that are subject to mining, large scale groundwater injection or abstraction. However, assessment of the potential acid rock drainage risk can be challenging, especially in carbonate rich environment, where the decreasing pH that usually accompanies pyrite oxidation, can be masked by the high pH-neutralisation capacity of carbonate minerals. In this study, we analysed 73 surface and groundwater samples from different water bodies and aquifers located in the Hamersley Basin, Western Australia. Although the majority of samples had a neutral pH, there was a large spatial variability in the dissolved sulphate concentrations that ranged from 1 mg/L to 15,000 mg/L. Waters with high dissolved sulphate concentration were found in areas with a high percentage of sulphide minerals (e.g. pyrite) located within the aquifer matrix and were characterised by low δ34SSO4 values (+1.2‰ to +4.6) consistent with signatures of aquifer matrix pyritic rock samples (+1.9‰ to +4.4). It was also found that the SO4 concentrations and acidity levels were not only dependent on δ34SSO4 values and existence of pyrite but also on the presence of carbonate minerals in the aquifer matrix. Based on the results from this study, a classification scheme has been developed for identification of waters impacted by acid rock drainage that also encompasses numerous concomitant geochemical processes that often occur in aqueous systems. The classification uses five proxies: SO4, SO4/Cl, SI of calcite, δ34SSO4 and δ18OSO4 to improve assessment of the contribution that oxidation of sulphide minerals has to overall sulphate ion concentrations, regardless of acidity levels of the aqueous system. This classification scheme enables a more direct monitoring regime for early detection of acid rock drainage processes and better groundwater quality management. References Dogramaci S., McLean L., Skrzypek G., 2017. Hydrochemical and stable isotope indicators of pyrite oxidation in carbonate-rich environment; the Hamersley Basin, Western Australia. Journal of Hydrology 545, 288-298.

A semi-automated image analysis procedure for in situ plankton imaging systems.

PubMed

Bi, Hongsheng; Guo, Zhenhua; Benfield, Mark C; Fan, Chunlei; Ford, Michael; Shahrestani, Suzan; Sieracki, Jeffery M

2015-01-01

Plankton imaging systems are capable of providing fine-scale observations that enhance our understanding of key physical and biological processes. However, processing the large volumes of data collected by imaging systems remains a major obstacle for their employment, and existing approaches are designed either for images acquired under laboratory controlled conditions or within clear waters. In the present study, we developed a semi-automated approach to analyze plankton taxa from images acquired by the ZOOplankton VISualization (ZOOVIS) system within turbid estuarine waters, in Chesapeake Bay. When compared to images under laboratory controlled conditions or clear waters, images from highly turbid waters are often of relatively low quality and more variable, due to the large amount of objects and nonlinear illumination within each image. We first customized a segmentation procedure to locate objects within each image and extracted them for classification. A maximally stable extremal regions algorithm was applied to segment large gelatinous zooplankton and an adaptive threshold approach was developed to segment small organisms, such as copepods. Unlike the existing approaches for images acquired from laboratory, controlled conditions or clear waters, the target objects are often the majority class, and the classification can be treated as a multi-class classification problem. We customized a two-level hierarchical classification procedure using support vector machines to classify the target objects (< 5%), and remove the non-target objects (> 95%). First, histograms of oriented gradients feature descriptors were constructed for the segmented objects. In the first step all non-target and target objects were classified into different groups: arrow-like, copepod-like, and gelatinous zooplankton. Each object was passed to a group-specific classifier to remove most non-target objects. After the object was classified, an expert or non-expert then manually removed the non-target objects that could not be removed by the procedure. The procedure was tested on 89,419 images collected in Chesapeake Bay, and results were consistent with visual counts with >80% accuracy for all three groups.

A Semi-Automated Image Analysis Procedure for In Situ Plankton Imaging Systems

PubMed Central

Bi, Hongsheng; Guo, Zhenhua; Benfield, Mark C.; Fan, Chunlei; Ford, Michael; Shahrestani, Suzan; Sieracki, Jeffery M.

2015-01-01

Plankton imaging systems are capable of providing fine-scale observations that enhance our understanding of key physical and biological processes. However, processing the large volumes of data collected by imaging systems remains a major obstacle for their employment, and existing approaches are designed either for images acquired under laboratory controlled conditions or within clear waters. In the present study, we developed a semi-automated approach to analyze plankton taxa from images acquired by the ZOOplankton VISualization (ZOOVIS) system within turbid estuarine waters, in Chesapeake Bay. When compared to images under laboratory controlled conditions or clear waters, images from highly turbid waters are often of relatively low quality and more variable, due to the large amount of objects and nonlinear illumination within each image. We first customized a segmentation procedure to locate objects within each image and extracted them for classification. A maximally stable extremal regions algorithm was applied to segment large gelatinous zooplankton and an adaptive threshold approach was developed to segment small organisms, such as copepods. Unlike the existing approaches for images acquired from laboratory, controlled conditions or clear waters, the target objects are often the majority class, and the classification can be treated as a multi-class classification problem. We customized a two-level hierarchical classification procedure using support vector machines to classify the target objects (< 5%), and remove the non-target objects (> 95%). First, histograms of oriented gradients feature descriptors were constructed for the segmented objects. In the first step all non-target and target objects were classified into different groups: arrow-like, copepod-like, and gelatinous zooplankton. Each object was passed to a group-specific classifier to remove most non-target objects. After the object was classified, an expert or non-expert then manually removed the non-target objects that could not be removed by the procedure. The procedure was tested on 89,419 images collected in Chesapeake Bay, and results were consistent with visual counts with >80% accuracy for all three groups. PMID:26010260

Proceedings of the Eleventh International Symposium on Remote Sensing of Environment, volume 2. [application and processing of remotely sensed data

NASA Technical Reports Server (NTRS)

1977-01-01

Application and processing of remotely sensed data are discussed. Areas of application include: pollution monitoring, water quality, land use, marine resources, ocean surface properties, and agriculture. Image processing and scene analysis are described along with automated photointerpretation and classification techniques. Data from infrared and multispectral band scanners onboard LANDSAT satellites are emphasized.

Assessment of phytoplankton and environmental variables for water quality and trophic state classification in the Gemlik Gulf, Marmara Sea (Turkey).

PubMed

Balci, Muharrem; Balkis, Neslihan

2017-02-15

Phytoplankton assemblages related to environmental factors and ecological status of the Gemlik Gulf were investigated between June 2010 and May 2011. A total 155 phytoplankton species were detected and 6 taxa (Amphisolenia laticincta, Archaeperidinium minutum, Cochlodinium sp., Gynogonadinium aequatoriale, Heterocapsa rotundata and Metaphalacroma sp.) were new records for the Turkish Seas. The lowest and highest total phytoplankton abundance among the sampling units (depths) was recorded in April 2011 (7.4×10 3 cellsL -1 ) and July 2010 (251.8×10 3 cellsL -1 ). Local small patches of visible red tide events were detected especially in the gulf, although a phytoplankton bloom was not observed. The water column was well stratified in the early autumn and well mixed in the early spring according to stratification index values. Surface nutrient concentrations increased especially at stations located inside of the gulf. The limiting effect of silicate was observed in early, mid-summer and early winter periods while the nitrogen was the limiting nutrient in the gulf during the whole sampling period. In the Gulf, low water quality-high mesotrophic and bad water quality-eutrophic status, high quality and low trophic level were generally detected according to Chl a, dissolved oxygen and trophic index. However, indices developed to determine the trophic level and water quality of the Mediterranean Sea can give unexpected results about the current environmental quality status when it is applied to the Marmara Sea which has limited photic zone by the halocline-pycnocline and thermocline. Copyright © 2016 Elsevier Ltd. All rights reserved.

Water resources of the Rio Grande de Anasco lower valley, Puerto Rico

USGS Publications Warehouse

Diaz, Jose Raul; Jordan, Donald G.

1987-01-01

A large amount of water suitable for most uses is available in the lower Rio Grande de Anasco Valley, the major source of which is the Rio Grande de Anasco which contributes about 95% of the surface water inflow to the lower valley. River flow at El Espino exceeds 100 cu ft/sec about 85% of the time and 200 cu ft/sec 50% of the time. Average daily flow for the driest months of the year (February, March, and April), is almost always <100 cu ft/sec. In contrast, the average daily flow for the wettest, months of the year (September, October, and November), is > 120 cu ft/sec. During the study period, flows of the Rio Canas averaged about 5 cu ft/sec. The lower valley is underlain by igneous rocks that have been eroded to depths of 350 ft or more below sea level. The valley is filled with 250 ft or more of limestone and clay, that in turn is overlain by as much as 100 ft of alluvium. The amount of groundwater available is unknown. There are large volumes of water in the saturated mostly fine-grained alluvium of Zone II, but as a whole the alluvium does not yield water readily to wells. Sand and gravel deposits associated with former river channels yield an estimated 100 to 150 gal/min to wells. The principal source of groundwater is the limestone of Zone III, that reportedly yields as much as 500 gal/min to wells. The quality of surface water especially that of Rio Grande de Anasco was very good. Specific conductance seldom exceeds 250 microsiemens/cm, even at low flows. Both salinity and sodium are low, falling in the Cl-S1 irrigation water classification. Water quality in the lower 5,000 ft or so of the river was affected by saltwater encroachment from the sea. The water quality of the other streams and canals in the lower valley was variable depending on susceptibility of saltwater encroachment, contamination from man-made sources, and concentration of minerals by evapotranspiration. Specific conductance however seldom exceeded 500 microsiemens/cm and the water usually falls in the C1-S2 classification. The quality of groundwater in the alluvial aquifer was about the same as that of the water of the Rio Grande de Anasco except where encroached by saltwater or contaminated. The water from the limestone was more mineralized than that of the alluvium (about 600 to 700 microsiemens/cm), and was somewhat similar to that of the smaller streams and canals in the valley. (Author 's abstract)

7 CFR 58.132 - Basis for classification.

Code of Federal Regulations, 2011 CFR

2011-01-01

... Specifications for Dairy Plants Approved for USDA Inspection and Grading Service 1 Quality Specifications for Raw Milk § 58.132 Basis for classification. The quality classification of raw milk for manufacturing...

7 CFR 58.132 - Basis for classification.

Code of Federal Regulations, 2010 CFR

2010-01-01

... Specifications for Dairy Plants Approved for USDA Inspection and Grading Service 1 Quality Specifications for Raw Milk § 58.132 Basis for classification. The quality classification of raw milk for manufacturing...

A Review of Wetland Remote Sensing.

PubMed

Guo, Meng; Li, Jing; Sheng, Chunlei; Xu, Jiawei; Wu, Li

2017-04-05

Wetlands are some of the most important ecosystems on Earth. They play a key role in alleviating floods and filtering polluted water and also provide habitats for many plants and animals. Wetlands also interact with climate change. Over the past 50 years, wetlands have been polluted and declined dramatically as land cover has changed in some regions. Remote sensing has been the most useful tool to acquire spatial and temporal information about wetlands. In this paper, seven types of sensors were reviewed: aerial photos coarse-resolution, medium-resolution, high-resolution, hyperspectral imagery, radar, and Light Detection and Ranging (LiDAR) data. This study also discusses the advantage of each sensor for wetland research. Wetland research themes reviewed in this paper include wetland classification, habitat or biodiversity, biomass estimation, plant leaf chemistry, water quality, mangrove forest, and sea level rise. This study also gives an overview of the methods used in wetland research such as supervised and unsupervised classification and decision tree and object-based classification. Finally, this paper provides some advice on future wetland remote sensing. To our knowledge, this paper is the most comprehensive and detailed review of wetland remote sensing and it will be a good reference for wetland researchers.

A Review of Wetland Remote Sensing

PubMed Central

Guo, Meng; Li, Jing; Sheng, Chunlei; Xu, Jiawei; Wu, Li

2017-01-01

Wetlands are some of the most important ecosystems on Earth. They play a key role in alleviating floods and filtering polluted water and also provide habitats for many plants and animals. Wetlands also interact with climate change. Over the past 50 years, wetlands have been polluted and declined dramatically as land cover has changed in some regions. Remote sensing has been the most useful tool to acquire spatial and temporal information about wetlands. In this paper, seven types of sensors were reviewed: aerial photos coarse-resolution, medium-resolution, high-resolution, hyperspectral imagery, radar, and Light Detection and Ranging (LiDAR) data. This study also discusses the advantage of each sensor for wetland research. Wetland research themes reviewed in this paper include wetland classification, habitat or biodiversity, biomass estimation, plant leaf chemistry, water quality, mangrove forest, and sea level rise. This study also gives an overview of the methods used in wetland research such as supervised and unsupervised classification and decision tree and object-based classification. Finally, this paper provides some advice on future wetland remote sensing. To our knowledge, this paper is the most comprehensive and detailed review of wetland remote sensing and it will be a good reference for wetland researchers. PMID:28379174

Effects of changes in reservoir operations on water quality and trophic state indicators in Voyageurs National Park, northern Minnesota, 2001-03

USGS Publications Warehouse

Christensen, Victoria G.; Payne, G.A.; Kallemeyn, Larry W.

2004-01-01

Implementation of an order by the International Joint Commission in January 2000 has changed operating procedures for dams that regulate two large reservoirs in Voyageurs National Park in northern Minnesota. These new procedures were expected to restore a more natural water regime and affect water levels, water quality, and trophic status. Results of laboratory analyses and field measurements of chemical and physical properties from May 2001 through September 2003 were compared to similar data collected prior to the change in operating procedures. Rank sum tests showed significant decreases in chlorophyll-a concentrations and trophic state indices for Kabetogama Lake (p=0.021) and Black Bay (p=0.007). There were no significant decreases in total phosphorus concentration, however, perhaps due to internal cycling of phosphorus. No sites had significant trends in seasonal total phosphorus concentrations, with the exception of May samples from Sand Point Lake, which had a significant decreasing trend (tau=-0.056, probability=0.03). May chlorophyll-a concentrations for Kabetogama Lake showed a significant decreasing trend (tau=-0.42, probability=0.05). Based on mean chlorophyll trophic-state indices (2001-03), Sand Point, Namakan, and Rainy Lakes would be classified oligotrophic to mesotrophic, and Kabetogama Lake and Rainy Lake at Black Bay would be classified as mesotrophic. The classification of Sand Point, Namakan, and Rainy Lakes remain the same for data collected prior to the change in operating procedures. In contrast, the trophic classification of Kabetogama Lake and Rainy Lake at Black Bay has changed from eutrophic to mesotrophic.

Global Access to Safe Water: Accounting for Water Quality and the Resulting Impact on MDG Progress

PubMed Central

Onda, Kyle; LoBuglio, Joe; Bartram, Jamie

2012-01-01

Monitoring of progress towards the Millennium Development Goal (MDG) drinking water target relies on classification of water sources as “improved” or “unimproved” as an indicator for water safety. We adjust the current Joint Monitoring Programme (JMP) estimate by accounting for microbial water quality and sanitary risk using the only-nationally representative water quality data currently available, that from the WHO and UNICEF “Rapid Assessment of Drinking Water Quality”. A principal components analysis (PCA) of national environmental and development indicators was used to create models that predicted, for most countries, the proportions of piped and of other-improved water supplies that are faecally contaminated; and of these sources, the proportions that lack basic sanitary protection against contamination. We estimate that 1.8 billion people (28% of the global population) used unsafe water in 2010. The 2010 JMP estimate is that 783 million people (11%) use unimproved sources. Our estimates revise the 1990 baseline from 23% to 37%, and the target from 12% to 18%, resulting in a shortfall of 10% of the global population towards the MDG target in 2010. In contrast, using the indicator “use of an improved source” suggests that the MDG target for drinking-water has already been achieved. We estimate that an additional 1.2 billion (18%) use water from sources or systems with significant sanitary risks. While our estimate is imprecise, the magnitude of the estimate and the health and development implications suggest that greater attention is needed to better understand and manage drinking water safety. PMID:22690170

Spatiotemporal classification of environmental monitoring data in the Yeongsan River basin, Korea, using self-organizing maps.

PubMed

Jin, Y-H; Kawamura, A; Park, S-C; Nakagawa, N; Amaguchi, H; Olsson, J

2011-10-01

Environmental monitoring data for planning, implementing and evaluating the Total Maximum Daily Loads (TMDL) management system have been measured at about 8-day intervals in a number of rivers in Korea since 2004. In the present study, water quality parameters such as Suspended Solids (SS), Biochemical Oxygen Demand (BOD), Dissolved Oxygen (DO), Total Nitrogen (TN), and Total Phosphorus (TP) and the corresponding runoff were collected from six stations in the Yeongsan River basin for six years and transformed into monthly mean values. With the primary objective to understand spatiotemporal characteristics of the data, a methodologically systematic application of a Self-Organizing Map (SOM) was made. The SOM application classified the environmental monitoring data into nine clusters showing exclusively distinguishable patterns. Data frequency at each station on a monthly basis identified the spatiotemporal distribution for the first time in the study area. Consequently, the SOM application provided useful information that the sub-basin containing a metropolitan city is associated with deteriorating water quality and should be monitored and managed carefully during spring and summer for water quality improvement in the river basin.

Quality of water resources in Kullu Valley in Himachal Himalayas, India: perspective and prognosis

NASA Astrophysics Data System (ADS)

Thakur, Nandini; Rishi, Madhuri; Sharma, Diana A.; Keesari, Tirumalesh

2018-03-01

The water quality in mountain regions of Himalaya is considered to be good and quantity adequate. However, recent reports suggest that urbanisation and population growth have been tremendous, which are impacting the land use/cover changes and also endangering the water resources both in quality and quantity. This paper elaborates the systematic investigation carried out on different attributes impacting the drinking water resources in Kullu valley. Two approaches were employed in this study: (1) ex-ante approach involving field survey and secondary data analysis from ancillary sources and (2) hydrochemical approach for the measurement of water quality parameters from springs. Results from ex-ante approach infer rise in population of about 15% during 2001-2011, which led to a significant change in land use pattern, microclimate and also increased water demand. Hydrochemistry of the water samples in the study area has indicated that the current status of spring waters is satisfactory for drinking purposes with a few incidences of high NO3 - which is mostly attributed to contamination from sewage, while F-, Cl- and TDS contamination is mainly confined to hot springs. From both ex-ante approach and primary hydrochemical data it can be inferred that springs need to be restored in terms of both quantity and quality. Hydrochemical interpretation suggests two main groups of samples: (1) low TDS and Ca-Mg-Cl-HCO3 type, which are mainly recharging waters with very less interaction with the aquifer material and (ii) moderate TDS and Mg-Ca-Cl, Ca-Na-HCO3, Na-Ca-Cl-SO4 and Ca-Mg-HCO3 and have undergone water-rock interaction. Based on the inferences obtained from the Piper's, Chadha's and Durov's classification no evidence of hot springs contaminating or contributing to other cold springs and shallow groundwater (hand pump) is found. The study concludes that the water resources are vulnerable to anthropogenic interventions and needs treatment prior to drinking. Periodic monitoring of water quality and adopting proper treatment procedures are essential for supplying safe and sustainable water to the community in the Kullu valley, Himachal Pradesh.

33 CFR 145.05 - Classification of fire extinguishers.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 33 Navigation and Navigable Waters 2 2011-07-01 2011-07-01 false Classification of fire... SECURITY (CONTINUED) OUTER CONTINENTAL SHELF ACTIVITIES FIRE-FIGHTING EQUIPMENT § 145.05 Classification of....05(c)—Portable and Semiportable Extinguishers Classification Type Size Soda-acid and water, gallons...

[Application of hyper-spectral remote sensing technology in environmental protection].

PubMed

Zhao, Shao-Hua; Zhang, Feng; Wang, Qiao; Yao, Yun-Jun; Wang, Zhong-Ting; You, Dai-An

2013-12-01

Hyper-spectral remote sensing (RS) technology has been widely used in environmental protection. The present work introduces its recent application in the RS monitoring of pollution gas, green-house gas, algal bloom, water quality of catch water environment, safety of drinking water sources, biodiversity, vegetation classification, soil pollution, and so on. Finally, issues such as scarce hyper-spectral satellites, the limits of data processing and information extract are related. Some proposals are also presented, including developing subsequent satellites of HJ-1 satellite with differential optical absorption spectroscopy, greenhouse gas spectroscopy and hyper-spectral imager, strengthening the study of hyper-spectral data processing and information extraction, and promoting the construction of environmental application system.

Headwater Influences on Downstream Water Quality

PubMed Central

Oakes, Robert M.

2007-01-01

We investigated the influence of riparian and whole watershed land use as a function of stream size on surface water chemistry and assessed regional variation in these relationships. Sixty-eight watersheds in four level III U.S. EPA ecoregions in eastern Kansas were selected as study sites. Riparian land cover and watershed land use were quantified for the entire watershed, and by Strahler order. Multiple regression analyses using riparian land cover classifications as independent variables explained among-site variation in water chemistry parameters, particularly total nitrogen (41%), nitrate (61%), and total phosphorus (63%) concentrations. Whole watershed land use explained slightly less variance, but riparian and whole watershed land use were so tightly correlated that it was difficult to separate their effects. Water chemistry parameters sampled in downstream reaches were most closely correlated with riparian land cover adjacent to the smallest (first-order) streams of watersheds or land use in the entire watershed, with riparian zones immediately upstream of sampling sites offering less explanatory power as stream size increased. Interestingly, headwater effects were evident even at times when these small streams were unlikely to be flowing. Relationships were similar among ecoregions, indicating that land use characteristics were most responsible for water quality variation among watersheds. These findings suggest that nonpoint pollution control strategies should consider the influence of small upland streams and protection of downstream riparian zones alone is not sufficient to protect water quality. PMID:17999108

Optimizing disinfection by-product monitoring points in a distribution system using cluster analysis.

PubMed

Delpla, Ianis; Florea, Mihai; Pelletier, Geneviève; Rodriguez, Manuel J

2018-06-04

Trihalomethanes (THMs) and Haloacetic Acids (HAAs) are the main groups detected in drinking water and are consequently strictly regulated. However, the increasing quantity of data for disinfection byproducts (DBPs) produced from research projects and regulatory programs remains largely unexploited, despite a great potential for its use in optimizing drinking water quality monitoring to meet specific objectives. In this work, we developed a procedure to optimize locations and periods for DBPs monitoring based on a set of monitoring scenarios using the cluster analysis technique. The optimization procedure used a robust set of spatio-temporal monitoring results on DBPs (THMs and HAAs) generated from intensive sampling campaigns conducted in a residential sector of a water distribution system. Results shows that cluster analysis allows for the classification of water quality in different groups of THMs and HAAs according to their similarities, and the identification of locations presenting water quality concerns. By using cluster analysis with different monitoring objectives, this work provides a set of monitoring solutions and a comparison between various monitoring scenarios for decision-making purposes. Finally, it was demonstrated that the data from intensive monitoring of free chlorine residual and water temperature as DBP proxy parameters, when processed using cluster analysis, could also help identify the optimal sampling points and periods for regulatory THMs and HAAs monitoring. Copyright © 2018 Elsevier Ltd. All rights reserved.

Response of lake water quality to wastewater inputs from land-based fish farm located on Yuvarlakçay Creek in Köyceğiz-Dalyan Specially Protected Area, Turkey.

PubMed

Taşeli, B K

2009-10-01

Köyceğiz Lake is located in the south-western part of Turkey. The area between the Köyceğiz Lake and the Mediterranean Sea is covered with four small lakes and several canals. The surroundings of the lake, canals and forests have a great potential as a reproduction areas for Mediterranean Sea turtles (Caretta caretta) and sheltering place for various animals. In the vicinity of this system there are agricultural areas and small settlements. In this region the most important economic activities are tourism and fisheries. However, the lake is currently threatened by pollution because of (1) non-point source pollution (agriculture); (2) point sources (land-based fish farms); (3) inefficient sewerage systems; (4) uncontrolled soil erosion in its drainage basin; (5) inappropriate flood control measures; and (6) channel traffic. This study evaluates the influence of its influent creeks namely Namnam and Yuvarlakçay Creek on the water quality of Köyceğiz Lake, mainly because the creeks are believed to be responsible for the major pollutant load reaching the lake. Accordingly, this study demonstrates (1) change in the water quality of Köyceğiz Lake from 2006 to 2007; (2) the water quality classification of the major influent creeks feeding Köyceğiz Lake; and (3) how land-based fish farm influences Yuvarlakçay Creek water quality in a Köyceğiz-Dalyan Specially Protected Area.

Spatial and Temporal Water Quality Dynamics in the Lake Maumelle Reservoir (Arkansas): Geochemical and Planktonic Variance in a Drinking Water Source

NASA Astrophysics Data System (ADS)

Carey, M. D.; Ruhl, L. S.

2017-12-01

The Lake Maumelle reservoir is Central Arkansas's main water supply. Maintaining a high standard of water quality is important to the over 400,000 residents of this area whom rely on this mesotrophic waterbody for drinking water. Lake Maumelle is also a scenic attraction for recreational boating and fishing. Past research has focused primarily on watershed management with land use/land cover modeling and quarterly water sampling of the 13.91mi2 reservoir. The surrounding land within the watershed is predominately densely forested, with timber farms and the Ouachita National Forest. This project identifies water quality changes spatially and temporally, which have not been as frequently observed, over a 6-month timespan. Water samples were collected vertically throughout the water column and horizontally throughout the lake following reservoir zonation. Parameters collected vertically for water quality profiles are temperature, dissolved oxygen, electrical conductivity, salinity, and pH. Soft sediment samples were collected and pore water was extracted by centrifuge. Cation and anion concentrations in the water samples were determined using ion chromatography, and trace element concentrations were determined using ICPMS. Planktonic abundances were determined using an inverted microscope and a 5ml counting chamber. Trace element, cation, and anion concentrations have been compared with planktonic abundance and location to determine microorganismal response to geochemical variance. During June 2017 sampling, parameters varied throughout the water column (temperature decreased 4 degrees Celsius and dissolved oxygen decreased from 98% to 30% from surface to bottom depths), revealing that the reservoir was becoming stratified. Collected plankton samples revealed the presence of copepod, daphnia, and dinoflagellate algae. Utricularia gibba was present in the littoral zone. Low electrical conductivity readings and high water clarity are consistent with the lake's mesotrophic state index classification. The results will be compared to previous sampling events, used to calculate enrichment factors of geochemical constituents, and used to create a geochemical and planktonic map of the lake through time.

A scope classification of data quality requirements for food composition data.

PubMed

Presser, Karl; Hinterberger, Hans; Weber, David; Norrie, Moira

2016-02-15

Data quality is an important issue when managing food composition data since the usage of the data can have a significant influence on policy making and further research. Although several frameworks for data quality have been proposed, general tools and measures are still lacking. As a first step in this direction, we investigated data quality requirements for an information system to manage food composition data, called FoodCASE. The objective of our investigation was to find out if different requirements have different impacts on the intrinsic data quality that must be regarded during data quality assessment and how these impacts can be described. We refer to the resulting classification with its categories as the scope classification of data quality requirements. As proof of feasibility, the scope classification has been implemented in the FoodCASE system. Copyright © 2015 Elsevier Ltd. All rights reserved.

In vivo automated quantification of quality of apples during storage using optical coherence tomography images

NASA Astrophysics Data System (ADS)

Srivastava, Vishal; Dalal, Devjyoti; Kumar, Anuj; Prakash, Surya; Dalal, Krishna

2018-06-01

Moisture content is an important feature of fruits and vegetables. As 80% of apple content is water, so decreasing the moisture content will degrade the quality of apples (Golden Delicious). The computational and texture features of the apples were extracted from optical coherence tomography (OCT) images. A support vector machine with a Gaussian kernel model was used to perform automated classification. To evaluate the quality of wax coated apples during storage in vivo, our proposed method opens up the possibility of fully automated quantitative analysis based on the morphological features of apples. Our results demonstrate that the analysis of the computational and texture features of OCT images may be a good non-destructive method for the assessment of the quality of apples.

Using UV-Vis spectroscopy for simultaneous geographical and varietal classification of tea infusions simulating a home-made tea cup.

PubMed

Diniz, Paulo Henrique Gonçalves Dias; Barbosa, Mayara Ferreira; de Melo Milanez, Karla Danielle Tavares; Pistonesi, Marcelo Fabián; de Araújo, Mário César Ugulino

2016-02-01

In this work we proposed a method to verify the differentiating characteristics of simple tea infusions prepared in boiling water alone (simulating a home-made tea cup), which represents the final product as ingested by the consumers. For this purpose we used UV-Vis spectroscopy and variable selection through the Successive Projections Algorithm associated with Linear Discriminant Analysis (SPA-LDA) for simultaneous classification of the teas according to their variety and geographic origin. For comparison, KNN, CART, SIMCA, PLS-DA and PCA-LDA were also used. SPA-LDA and PCA-LDA provided significantly better results for tea classification of the five studied classes (Argentinean green tea; Brazilian green tea; Argentinean black tea; Brazilian black tea; and Sri Lankan black tea). The proposed methodology provides a simpler, faster and more affordable classification of simple tea infusions, and can be used as an alternative approach to traditional tea quality evaluation as made by skilful tasters, which is evidently partial and cannot assess geographic origins. Copyright © 2015 Elsevier Ltd. All rights reserved.

The ecological status of Karavasta Lagoon (Albania): Closing the stable door before the horse has bolted?

PubMed

Munari, Cristina; Tessari, Umberto; Rossi, Remigio; Mistri, Michele

2010-02-01

Karavasta is the widest and most important lagoon in Albania. This study aimed to assess the ecological quality status of the lagoon, acquire knowledge of a natural environment which might be exploited for aquaculture, and give management hints on the basis of anthropogenic impact and ecological conditions. A sampling campaign was carried out in 2008: at six stations, benthic fauna, water, and sediment parameters were considered. Statistical analyses were carried out through multivariate procedures (PCA, classification-clustering, SIMPER, RDA, DISTLM, PERMANOVA). Ecological quality was assessed through the AZTI Marine Biotic Index (AMBI), the multivariate AMBI (M-AMBI) and the Benthic Index based on Taxonomic Sufficiency (BITS). Sediment characteristics (percent organic matter, %OM; redox potential discontinuity layer depth, RPDL; particle size composition) and salinity represented contributory influences on lagoon communities. It was possible to distinguish and characterise a confined area, and benthic communities, from a marine-influenced area and its biota. The number of species was quite low when compared with other open Adriatic lagoons. The M-AMBI and BITS classifications gave quite similar results, which seemed consistent with the ecological conditions of the lagoon, that is a distinction in the ecological quality between the seaward and landward stations, with higher ecological quality (EcoQ) at the seaward stations. Given the pressures and the ecological condition of Karavasta, an intensification of aquaculture activities must be considered with caution, since the lagoon seems at significant risk of serious hypereutrophication. This situation is made worse by the limited water exchange with the marine environment due to the irregular dredging of the communication channels. 2009 Elsevier Ltd. All rights reserved.

Heavy metal determinations in algae and clams and their possible employment for assessing the sea water quality criteria.

PubMed

Locatelli, C; Fabbri, D; Torsi, G

2001-01-01

An empirical criterion for a possible classification of sea water quality is proposed. It is based on the knowledge of metal content in algae (Ulva Rigida) and clams (Tapes Philippinarum), two species present in marine ecosystems. The elements considered are Hg, Cu, Pb, Cd, Zn. The analytical technique employed is Differential Pulse Anodic Stripping Voltammetry (DPASV) in the case of Cu, Pb, Cd, Zn, while the determination of mercury is obtained by the Cold Vapour Atomic Absorption Spectroscopy (CV-AAS) technique with SnCl2 as reducing agent. The analytical procedure has been verified on three standard reference materials: Sea Water BCR-CRM 403, Ulva Lactuca BCR-CRM 279 and Mussel Tissue BCR-CRM 278. For all the elements, in addition to detection limits, accuracy and precision are given: the former, expressed as relative error (e), and the latter, expressed as relative standard deviation (Sr), were in all cases lower than 6%.

A saprobic index for biological assessment of river water quality in Brazil (Minas Gerais and Rio de Janeiro states).

PubMed

Junqueira, Marilia Vilela; Friedrich, Günther; Pereira de Araujo, Paulo Roberto

2010-04-01

Based upon several years of experience in investigations with macrozoobenthos in rivers in the states of Minas Gerais and Rio de Janeiro, a biological assessment system has been developed to indicate pollution levels caused by easily degradable organic substances from sewers. The biotic index presented here is aimed at determining water's saprobic levels and was, therefore, named the "Saprobic Index for Brazilian Rivers in Minas Gerais and Rio de Janeiro states" (ISMR). For this purpose, saprobic valences and weights have been established for 122 taxa of tropical macrozoobenthos. Investigations were carried out in little, medium sized and big rivers in mountains and plains. Through ISMR, a classification of water quality and the respective cartographic representation can be obtained. Data collection and treatment methods, as well as the limitations of the biotic index, are thoroughly described. ISMR can also be used as an element to establish complex multimetric indexes intended for an ecological integrity assessment, where it is essential to indicate organic pollution.

Using "big data" to optimally model hydrology and water quality across expansive regions

USGS Publications Warehouse

Roehl, E.A.; Cook, J.B.; Conrads, P.A.

2009-01-01

This paper describes a new divide and conquer approach that leverages big environmental data, utilizing all available categorical and time-series data without subjectivity, to empirically model hydrologic and water-quality behaviors across expansive regions. The approach decomposes large, intractable problems into smaller ones that are optimally solved; decomposes complex signals into behavioral components that are easier to model with "sub- models"; and employs a sequence of numerically optimizing algorithms that include time-series clustering, nonlinear, multivariate sensitivity analysis and predictive modeling using multi-layer perceptron artificial neural networks, and classification for selecting the best sub-models to make predictions at new sites. This approach has many advantages over traditional modeling approaches, including being faster and less expensive, more comprehensive in its use of available data, and more accurate in representing a system's physical processes. This paper describes the application of the approach to model groundwater levels in Florida, stream temperatures across Western Oregon and Wisconsin, and water depths in the Florida Everglades. ?? 2009 ASCE.

Image aesthetic quality evaluation using convolution neural network embedded learning

NASA Astrophysics Data System (ADS)

Li, Yu-xin; Pu, Yuan-yuan; Xu, Dan; Qian, Wen-hua; Wang, Li-peng

2017-11-01

A way of embedded learning convolution neural network (ELCNN) based on the image content is proposed to evaluate the image aesthetic quality in this paper. Our approach can not only solve the problem of small-scale data but also score the image aesthetic quality. First, we chose Alexnet and VGG_S to compare for confirming which is more suitable for this image aesthetic quality evaluation task. Second, to further boost the image aesthetic quality classification performance, we employ the image content to train aesthetic quality classification models. But the training samples become smaller and only using once fine-tuning cannot make full use of the small-scale data set. Third, to solve the problem in second step, a way of using twice fine-tuning continually based on the aesthetic quality label and content label respective is proposed, the classification probability of the trained CNN models is used to evaluate the image aesthetic quality. The experiments are carried on the small-scale data set of Photo Quality. The experiment results show that the classification accuracy rates of our approach are higher than the existing image aesthetic quality evaluation approaches.

A Bioassay System Using Bioelectric Signals from Small Fish

NASA Astrophysics Data System (ADS)

Terawaki, Mitsuru; Soh, Zu; Hirano, Akira; Tsuji, Toshio

Although the quality of tap water is generally examined using chemical assay, this method cannot be used for examination in real time. Against such a background, the technique of fish bioassay has attracted attention as an approach that enables constant monitoring of aquatic contamination. The respiratory rhythms of fish are considered an efficient indicator for the ongoing assessment of water quality, since they are sensitive to chemicals and can be indirectly measured from bioelectric signals generated by breathing. In order to judge aquatic contamination accurately, it is necessary to measure bioelectric signals from fish swimming freely as well as to stably discriminate measured signals, which vary between individuals. However, no bioassay system meeting the above requirements has yet been established. This paper proposes a bioassay system using bioelectric signals generated from small fish in free-swimming conditions. The system records signals using multiple electrodes to cover the extensive measurement range required in a free-swimming environment, and automatically discriminates changes in water quality from signal frequency components. This discrimination is achieved through an ensemble classification method using probability neural networks to solve the problem of differences between individual fish. The paper also reports on the results of related validation experiments, which showed that the proposed system was able to stably discriminate between water conditions before and after bleach exposure.

Nutrient additions by waterfowl to lakes and reservoirs: predicting their effects on productivity and water quality

USGS Publications Warehouse

Manny, Bruce A.; Johnson, W.C.; Wetzel, R.G.

1994-01-01

Lakes and reservoirs provide water for human needs and habitat for aquatic birds. Managers of such waters may ask whether nutrients added by waterfowl degrade water quality. For lakes and reservoirs where primary productivity is limited by phosphorus (P), we developed a procedure that integrates annual P loads from waterfowl and other external sources, applies a nutrient load-response model, and determines whether waterfowl that used the lake or reservoir degraded water quality. Annual P loading by waterfowl can be derived from a figure in this report, using the days per year that each kind spent on any lake or reservoir. In our example, over 6500 Canada geese (Branta canadensis) and 4200 ducks (mostly mallards, Anas platyrhynchos) added 4462 kg of carbon (C), 280 kg of nitrogen (N), and 88 kg of P y-1 to Wintergreen Lake in southwestern Michigan, mostly during their migration. These amounts were 69% of all C, 27% of all N, and 70% of all P that entered the lake from external sources. Loads from all external sources totaled 840 mg P m-2 y-1. Application of a nutrient load-response model to this concentration, the hydraulic load (0.25 m y-1), and the water residence time (9.7 y) of Wintergreen Lake yielded an average annual concentration of total P in the lake of 818 mg m-3 that classified the lake as hypertrophic. This trophic classification agreed with independent measures of primary productivity, chlorophyll-a, total P, total N, and Secchi disk transparency made in Wintergreen Lake. Our procedure showed that waterfowl caused low water quality in Wintergreen Lake.

Physicochemical fingerprinting of thermal waters of Beira Interior region of Portugal.

PubMed

Araujo, A R T S; Sarraguça, M C; Ribeiro, M P; Coutinho, P

2017-06-01

Mineral natural waters and spas have been used for therapeutic purposes for centuries, with Portugal being a very rich country in thermal waters and spas that are mainly distributed by northern and central regions where Beira Interior region is located. The use of thermal waters for therapeutic purposes has always been aroused a continuous interest, being dependent on physicochemical fingerprinting of this type of waters the indication for a treatment in a specific pathological condition. In the present work, besides a literature review about the physicochemical composition of the thermal waters of the Beira Interior region and its therapeutic indications, it was carried out an exhaustive multivariate analysis-principal component analysis and cluster analysis-to assess the correlation between different physicochemical parameters and the therapeutic indications claims described for these spas and thermal waters. These statistical methods used for data analysis enables classification of thermal waters compositions into different groups, regarding to the different variable selected, making possible an interpretation of variables affecting water compositions. Actually, Monfortinho and Longroiva are clearly quite different of the others, and Cró and Fonte Santa de Almeida appear together in all analysis, suggesting a strong resemblance between these waters. Thereafter, the results obtained allow us to demonstrate the role of major components of the studied thermal waters on a particular therapeutic purpose/indication and hence based on compositional and physicochemical properties partially explain their therapeutic qualities and beneficial effects on human health. This classification agreed with the results obtained for the therapeutic indications approved by the Portuguese National Health Authority and proved to be a valuable tool for the regional typology of mineral medicinal waters, constituting an important guide of the therapeutic armamentarium for well and specific-oriented pathological disturbs.

An exploration of multilevel modeling for estimating access to drinking-water and sanitation.

PubMed

Wolf, Jennyfer; Bonjour, Sophie; Prüss-Ustün, Annette

2013-03-01

Monitoring progress towards the targets for access to safe drinking-water and sanitation under the Millennium Development Goals (MDG) requires reliable estimates and indicators. We analyzed trends and reviewed current indicators used for those targets. We developed continuous time series for 1990 to 2015 for access to improved drinking-water sources and improved sanitation facilities by country using multilevel modeling (MLM). We show that MLM is a reliable and transparent tool with many advantages over alternative approaches to estimate access to facilities. Using current indicators, the MDG target for water would be met, but the target for sanitation missed considerably. The number of people without access to such services is still increasing in certain regions. Striking differences persist between urban and rural areas. Consideration of water quality and different classification of shared sanitation facilities would, however, alter estimates considerably. To achieve improved monitoring we propose: (1) considering the use of MLM as an alternative for estimating access to safe drinking-water and sanitation; (2) completing regular assessments of water quality and supporting the development of national regulatory frameworks as part of capacity development; (3) evaluating health impacts of shared sanitation; (4) using a more equitable presentation of countries' performances in providing improved services.

Classifying Natural Waters with the Forel-Ule Colour Index System: Results, Applications, Correlations and Crowdsourcing.

PubMed

Garaba, Shungudzemwoyo P; Friedrichs, Anna; Voß, Daniela; Zielinski, Oliver

2015-12-18

Societal awareness of changes in the environment and climate has grown rapidly, and there is a need to engage citizens in gathering relevant scientific information to monitor environmental changes due to recognition that citizens are a potential source of critical information. The apparent colour of natural waters is one aspect of our aquatic environment that is easy to detect and an essential complementary optical water quality indicator. Here we present the results and explore the utility of the Forel-Ule colour index (FUI) scale as a proxy for different properties of natural waters. A FUI scale is used to distinguish the apparent colours of different natural surface water masses. Correlation analysis was completed in an effort to determine the constituents of natural waters related to FUI. Strong correlations with turbidity, Secchi-disk depth, and coloured dissolved organic material suggest the FUI is a good indicator of changes related to other constituents of water. The increase in the number of tools capable of determining the FUI colours, (i) ocean colour remote sensing products; (ii) a handheld scale; and (iii) a mobile device app, make it a versatile relative measure of water quality. It has the potential to provide higher spatial and temporal resolution of data for a modernized classification of optical water quality. This FUI colour system has been favoured by several scientists in the last century because it is affordable and easy to use and provides indicative information about the colour of water and the water constituents producing that colour. It is therefore within the scope of a growing interest in the application and usefulness of basic measurement methodologies with the potential to provide timely benchmark information about the environment to the public, scientists and policymakers.

Classifying Natural Waters with the Forel-Ule Colour Index System: Results, Applications, Correlations and Crowdsourcing

PubMed Central

Garaba, Shungudzemwoyo P.; Friedrichs, Anna; Voß, Daniela; Zielinski, Oliver

2015-01-01

Societal awareness of changes in the environment and climate has grown rapidly, and there is a need to engage citizens in gathering relevant scientific information to monitor environmental changes due to recognition that citizens are a potential source of critical information. The apparent colour of natural waters is one aspect of our aquatic environment that is easy to detect and an essential complementary optical water quality indicator. Here we present the results and explore the utility of the Forel-Ule colour index (FUI) scale as a proxy for different properties of natural waters. A FUI scale is used to distinguish the apparent colours of different natural surface water masses. Correlation analysis was completed in an effort to determine the constituents of natural waters related to FUI. Strong correlations with turbidity, Secchi-disk depth, and coloured dissolved organic material suggest the FUI is a good indicator of changes related to other constituents of water. The increase in the number of tools capable of determining the FUI colours, (i) ocean colour remote sensing products; (ii) a handheld scale; and (iii) a mobile device app, make it a versatile relative measure of water quality. It has the potential to provide higher spatial and temporal resolution of data for a modernized classification of optical water quality. This FUI colour system has been favoured by several scientists in the last century because it is affordable and easy to use and provides indicative information about the colour of water and the water constituents producing that colour. It is therefore within the scope of a growing interest in the application and usefulness of basic measurement methodologies with the potential to provide timely benchmark information about the environment to the public, scientists and policymakers. PMID:26694444

Using Microbial Source Tracking to Enhance Environmental Stewardship of Agriculture

NASA Astrophysics Data System (ADS)

Martin, Sherry; Rose, Joan; Flood, Matthew; Aw, Tiong; Hyndman, David

2016-04-01

Large scale agriculture relies on the application of chemical fertilizers and animal manure. It is well known that nutrients in excess of a plant's uptake and soil retention capacity can travel to nearby waterways via surface run-off and groundwater pathways, indirectly fertilizing these aquatic ecosystems. It has not yet been possible to distinguish water quality impacts of fertilizer from those derived from human and animal waste sources. However, new microbial source tracking (MST) tools allow specific identification of fecal pollution. Our objective was to examine pollution risks at the regional scale using MST, mapping and classification and regression tree analysis. We present results Bovine M2 genetic marker data from three flow regimes (baseflow, snow melt, and post-planting rain). Key landscape characteristics were related to the presence of the bovine markers and appear to be related to fate and transport. Impacts at this regional watershed scale will be discussed. Our research aims to identify the impacts of agricultural management practices on water quality by linking nutrient concentrations with fecal pollution sources. We hope that our research will provide guidance that will help improve water quality through agricultural best management practices to reduce pathogen contamination.

Assessment of groundwater quality at a MSW landfill site using standard and AHP based water quality index: a case study from Ranchi, Jharkhand, India.

PubMed

Chakraborty, Shubhrasekhar; Kumar, R Naresh

2016-06-01

Landfill leachate generated from open MSW dumpsite can cause groundwater contamination. The impact of open dumping of MSW on the groundwater of adjacent area was studied. To assess the spatial and temporal variations in groundwater quality, samples were collected around an open MSW dumping site in Ranchi city, Jharkhand, India. Groundwater samples were analysed for various physicochemical and bacteriological parameters for 1 year. Results indicated that the groundwater is getting contaminated due to vertical and horizontal migration of landfill leachate. Extent of contamination was higher in areas closer to the landfill as indicated by high alkalinity, total dissolved solids and ammonia concentration. Metals such as lead, iron, and manganese were present at concentrations of 0.097, 0.97 and 0.36 mg/L, respectively exceeding the Bureau of Indian Standards (BIS) 10,500 for drinking water. Enterobacteriaceae were also detected in several groundwater samples and highest coliform count of 2.1×10(4) CFU/mL was recorded from a dug well. In order to determine the overall groundwater quality, water quality index (WQI) was calculated using weighted arithmetic index method and this index was further modified by coupling with the analytical hierarchy process (AHP) to get specific information. WQI values indicated that the overall groundwater quality of the region came under "poor" category while zone wise classification indicated the extent of impact of landfill leachate on groundwater.

The water quality of the Vrgorska Matica River.

PubMed

Stambuk-Giljanović, Nives

2003-04-01

The article presents the results of investigations carried out on the 42 km long Vrgorska Matica River, which flows through the 15 km long Vrgorsko polje (polje = field) which covers an area of 3000 ha, and is at 24 m a.s.l., located in Southern Croatia. It covers the years 1997-2000 after this field had been reclaimed for agricultural use. The purpose of the investigations was to evaluate the influence of the Vrgorska Matica River which is part of the catchment area of the Trebizat River, on the water quality in Modro Oko Lake and Prud Spring, which are used for water supply and are located downstream of the Vrgorska Matica River on the right bank of the Neretva River. The water quality was evaluated by using the quality index based on the following nine parameters: temperature, mineralization, corrosion coefficient, K = (Cl + SO4)/HCO3, dissolved oxygen, BOD5, total N, protein N, total phosphorus and total coliform bacteria (100 mL)-1 (MPN coli (100 mL)-1) for which concentrations C95 are calculated. After completing the nine parameters the results of C95 were recorded and transferred to the score table to obtain the q-value. The q-value used is an attempt to quantify environmental factors which would otherwise be qualitative. For each parameter the q-value was multiplied by a weighting factor based upon the relative significance of the parameter. The nine resulting scores values were then added to arrive at an overall water quality index (sigmaS95). According to this index the water can be classified into four categories. The first category, according to the Croatian Water Classification Act (Official Bulletin No. 77,1998), includes ground and surface waters used for drinking or in the food industry either in its natural state or after disinfection, and surface water used for raising high-quality species of fish, ranging from 85-100 scores; the second category includes water used in its natural state for swimming and recreation, sports or for other species of fish and the treated water used for drinking and other industrial purposes ranging between 70-85 scores. The third category includes water used in industry with no specific requests upon water quality and in agriculture ranging from 50-70 scores; the fourth category includes water used only after being treated in areas with water shortage which is less than 50 scores. According to results obtained by investigations, the water of the Vrgorska Matica River and Prud Spring falls into the second (II) category, while water from the Modro Oko Lake belongs to the first (I) category. This means that the Matica River water does not influence the water quality of the Modro Oko Lake. This lake water quality is influenced by the Rastocka Matica River from the Rastocko polje which is located upstream from the Vrgorska Matica River. This has been proved by dyeing tests.

Global sensitivity analysis for urban water quality modelling: Terminology, convergence and comparison of different methods

NASA Astrophysics Data System (ADS)

Vanrolleghem, Peter A.; Mannina, Giorgio; Cosenza, Alida; Neumann, Marc B.

2015-03-01

Sensitivity analysis represents an important step in improving the understanding and use of environmental models. Indeed, by means of global sensitivity analysis (GSA), modellers may identify both important (factor prioritisation) and non-influential (factor fixing) model factors. No general rule has yet been defined for verifying the convergence of the GSA methods. In order to fill this gap this paper presents a convergence analysis of three widely used GSA methods (SRC, Extended FAST and Morris screening) for an urban drainage stormwater quality-quantity model. After the convergence was achieved the results of each method were compared. In particular, a discussion on peculiarities, applicability, and reliability of the three methods is presented. Moreover, a graphical Venn diagram based classification scheme and a precise terminology for better identifying important, interacting and non-influential factors for each method is proposed. In terms of convergence, it was shown that sensitivity indices related to factors of the quantity model achieve convergence faster. Results for the Morris screening method deviated considerably from the other methods. Factors related to the quality model require a much higher number of simulations than the number suggested in literature for achieving convergence with this method. In fact, the results have shown that the term "screening" is improperly used as the method may exclude important factors from further analysis. Moreover, for the presented application the convergence analysis shows more stable sensitivity coefficients for the Extended-FAST method compared to SRC and Morris screening. Substantial agreement in terms of factor fixing was found between the Morris screening and Extended FAST methods. In general, the water quality related factors exhibited more important interactions than factors related to water quantity. Furthermore, in contrast to water quantity model outputs, water quality model outputs were found to be characterised by high non-linearity.

Identification of surface water-groundwater interaction by hydrogeochemical indicators and assessing its suitability for drinking and irrigational purposes in Chennai, Southern India

NASA Astrophysics Data System (ADS)

Brindha, K.; Neena Vaman, K. V.; Srinivasan, K.; Sathis Babu, M.; Elango, L.

2014-06-01

Large cities face water quality and quantity problems due to increasing population and improper disposal of solid and liquid wastes. It is essential to monitor the water quality to take corrective measures. This study was carried out in one of the densely populated metropolitan cities in India to ascertain the suitability of groundwater for drinking and irrigation activity, identify the processes controlling the geochemistry of groundwater and the impact of Adyar River on the groundwater quality. Magnesium and pH concentration in groundwater of this area were within the maximum permissible limits of WHO standards. Sodium and potassium concentration of groundwater were greater than the permissible limit in 30.8 % and in 50 % of the samples, respectively. About 35 % of the groundwater samples were not permissible for drinking based on the electrical conductivity (EC). The EC of groundwater was increasing towards the coast. In general, the quality of groundwater for irrigation purpose vary from moderate to good based on Na%, magnesium hazard, residual sodium carbonate, sodium absorption ratio, permeability index, and USDA classification. Na-Cl and Ca-Mg-Cl were the dominant groundwater and surface water type. Increased ionic concentration of groundwater towards the eastern part of the study area is due to the discharge of industrial effluents and domestic sewage into the Adyar River. Seawater intrusion is also one of the reasons for Na-Cl dominant groundwater near the coast. Evaporation and ion exchange were the major processes controlling groundwater chemistry in this area. The groundwater quality of this region is affected by the contaminated surface water.

Hydrogeochemistry for the assessment of groundwater quality in Varanasi: a fast-urbanizing center in Uttar Pradesh, India.

PubMed

Janardhana Raju, Nandimandalam; Shukla, U K; Ram, Prahlad

2011-02-01

The hydrogeochemical parameters for groundwater samples of the Varanasi area, a fast-urbanizing region in India, were studied to evaluate the major ion chemistry, weathering and solute acquisition processes controlling water composition, and suitability of water quality for domestic and irrigation uses. Sixty-eight groundwater samples were collected randomly from dug wells and hand pumps in the urban Varanasi area and analyzed for various chemical parameters. Geologically, the study area comprises Quaternary alluvium made up of an alternating succession of clay, silty clay, and sand deposits. The Total dissolved solids classification reveals that except two locations, the groundwater samples are desirable for drinking, and all are useful for irrigation purposes. The cationic and anionic concentrations indicated that the majority of the groundwater samples belong to the order of Na>Ca>Mg>K and HCO3>Cl>SO4 types, respectively. Geochemical classification of groundwater based on the Chadha rectangular diagram shows that the majority (81%) of groundwater samples belong to the calcium-bicarbonate type. The HCO3/(HCO3+SO4) ratio (0.87) indicates mostly carbonic acid weathering process due to presence of kankar carbonate mixed with clay/fine sand. The high nitrate concentration (>45 mg/l) of about 18% of the groundwater samples may be due to the local domestic sewage, leakage of septic tanks, and improper management of sanitary landfills. In general, the calculated values of sodium adsorption ratio, percent sodium, residual sodium carbonate, and permeability index indicate good to permissible use of water for irrigation, and only a few locations demand remedial measures for better crop yields.

Groundwater dynamics converted to a groundwater classification as a tool for nature development programs in the dunes

NASA Astrophysics Data System (ADS)

Martens, Kristine; Van Camp, Marc; Van Damme, Dirk; Walraevens, Kristine

2013-08-01

Within the European Union, Habitat Directives are developed with the aim of restoration and preservation of endangered species. The level of biodiversity in coastal dune systems is generally very high compared to other natural ecosystems, but suffers from deterioration. Groundwater extraction and urbanisation are the main reasons for the decrease in biodiversity. Many restoration actions are being carried out and are focusing on the restoration of groundwater level with the aim of re-establishing rare species. These actions have different degrees of success. The evaluation of the actions is mainly based on the appearance of red list species. The groundwater classes, developed in the Netherlands, are used for the evaluation of opportunities for vegetation, while the natural variability of the groundwater level and quality are under-estimated. Vegetation is used as a seepage indicator. The existing classification is not valid in the Belgian dunes, as the vegetation observed in the study area is not in correspondence with this classification. Therefore, a new classification is needed. The new classification is based on the variability of the groundwater level on a long term with integration of ecological factors. Based on the new classification, the importance of seasonal and inter-yearly fluctuations of the water table can be deduced. Inter-yearly fluctuations are more important in recharge areas while seasonal fluctuations are dominant in discharge areas. The new classification opens opportunities for relating vegetation and groundwater dynamics.

Influence of Long-term Application of Feedlot Manure Amendments on Water Repellency of a Clay Loam Soil.

PubMed

Miller, Jim J; Beasley, Bruce W; Hazendonk, Paul; Drury, Craig F; Chanasyk, David S

2017-05-01

Long-term application of feedlot manure to cropland may increase the quantity of soil organic carbon (C) and change its quality, which may influence soil water repellency. The objective was to determine the influence of feedlot manure type (stockpiled vs. composted), bedding material (straw [ST] vs. woodchips [WD]), and application rate (13, 39, or 77 Mg ha) on repellency of a clay loam soil after 17 annual applications. The repellency was determined on all 14 treatments using the water repellency index ( index), the water drop penetration time (WDPT) method, and molarity of ethanol (MED) test. The C composition of particulate organic matter in soil of five selected treatments after 16 annual applications was also determined using C nuclear magnetic resonance-direct polarization with magic-angle spinning (NMR-DPMAS). Manure type had no significant ( > 0.05) effect on index and WDPT, and MED classification was similar. Mean index and WDPT values were significantly greater and MED classification more hydrophobic for WD than ST. Application rate had no effect on the index, but WDPT was significantly greater and MED classification more hydrophobic with increasing application rate. Strong ( > 0.7) but nonsignificant positive correlations were found between index and WDPT versus hydrophobic (alkyl + aromatic) C, lignin at 74 ppm (O-alkyl), and unspecified aromatic compounds at 144 ppm. Specific aromatic compounds also contributed more to repellency than alkyl, O-alkyl, and carbonyl compounds. Overall, all three methods consistently showed that repellency was greater for WD- than ST-amended clay loam soil, but manure type had no effect. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Improving LUC estimation accuracy with multiple classification system for studying impact of urbanization on watershed flood

NASA Astrophysics Data System (ADS)

Dou, P.

2017-12-01

Guangzhou has experienced a rapid urbanization period called "small change in three years and big change in five years" since the reform of China, resulting in significant land use/cover changes(LUC). To overcome the disadvantages of single classifier for remote sensing image classification accuracy, a multiple classifier system (MCS) is proposed to improve the quality of remote sensing image classification. The new method combines advantages of different learning algorithms, and achieves higher accuracy (88.12%) than any single classifier did. With the proposed MCS, land use/cover (LUC) on Landsat images from 1987 to 2015 was obtained, and the LUCs were used on three watersheds (Shijing river, Chebei stream, and Shahe stream) to estimate the impact of urbanization on water flood. The results show that with the high accuracy LUC, the uncertainty in flood simulations are reduced effectively (for Shijing river, Chebei stream, and Shahe stream, the uncertainty reduced 15.5%, 17.3% and 19.8% respectively).

Analysis of data on nutrients and organic compounds in ground water in the upper Snake River basin, Idaho and western Wyoming, 1980-91

USGS Publications Warehouse

Rupert, Michael G.

1994-01-01

Nutrient and organic compound data from the U.S. Geological Survey and the U.S. Environmental Protection Agency STORET data bases provided information for development of a preliminary conceptual model of spatial and temporal ground-water quality in the upper Snake River Basin. Nitrite plus nitrate (as nitrogen; hereafter referred to as nitrate) concentrations exceeded the Federal drinking-water regulation of 10 milligrams per liter in three areas in Idaho" the Idaho National Engineering Laboratory, the area north of Pocatello (Fort Hall area), and the area surrounding Burley. Water from many wells in the Twin Falls area also contained elevated (greater than two milligrams per liter) nitrate concentrations. Water from domestic wells contained the highest median nitrate concentrations; water from industrial and public supply wells contained the lowest. Nitrate concentrations decreased with increasing well depth, increasing depth to water (unsaturated thickness), and increasing depth below water table (saturated thickness). Kjeldahl nitrogen concentrations decreased with increasing well depth and depth below water table. The relation between kjeldahl nitrogen concentrations and depth to water was poor. Nitrate and total phosphorus concentrations in water from wells were correlated among three hydrogeomorphic regions in the upper Snake River Basin, Concentrations of nitrate were statistically higher in the eastern Snake River Plain and local aquifers than in the tributary valleys. There was no statistical difference in total phosphorus concentrations among the three hydrogeomorphic regions. Nitrate and total phosphorus concentrations were correlated with land-use classifications developed using the Geographic Information Retrieval and Analysis System. Concentrations of nitrate were statistically higher in area of agricultural land than in areas of rangeland. There was no statistical difference in concentrations between rangeland and urban land and between urban land and agricultural land. There was no statistical difference in total phosphorus concentrations among any of the land-use classifications. Nitrate and total phosphorus concentrations also were correlated with land-use classifications developed by the Idaho Department of Water Resources for the Idaho part of the upper Snake River Basin. Nitrate concentrations were statistically higher in areas of irrigated agriculture than in areas of dryland agriculture and rangeland. There was no statistical difference in total phosphorus concentrations among any of the Idaho Department of Water Resources land-use classifications. Data were sufficient to assess long-term trends of nitrate concentrations in water from only eight wells: four wells north of Burley and four wells northwest of Pocatello. The trend in nitrate concentrations in water from all wells in upward. The following organic compounds were detected in ground water in the upper Snake River Basin: cyanazine, 2,4-D DDT, dacthal, diazinon, dichloropropane, dieldrin, malathion, and metribuzin. Of 211 wells sampled for organic compounds, water from 17 contained detectable concentrations.

A water quality management strategy for regionally protected water through health risk assessment and spatial distribution of heavy metal pollution in 3 marine reserves.

PubMed

Zhang, Yinan; Chu, Chunli; Li, Tong; Xu, Shengguo; Liu, Lei; Ju, Meiting

2017-12-01

Severe water pollution and resource scarcity is a major problem in China, where it is necessary to establish water quality-oriented monitoring and intelligent watershed management. In this study, an effective watershed management method is explored, in which water quality is first assessed using the heavy metal pollution index and the human health risk index, and then by classifying the pollution and management grade based on cluster analysis and GIS visualization. Three marine reserves in Tianjin were selected and analyzed, namely the Tianjin Ancient Coastal Wetland National Nature Reserve (Qilihai Natural Reserve), the Tianjin DaShentang Oyster Reef National Marine Special Reserve (DaShentang Reserve), and the Tianjin Coastal Wetland National Marine Special Reserve (BinHai Wetland Reserve) which is under construction. The water quality and potential human health risks of 5 heavy metals (Pb, As, Cd, Hg, Cr) in the three reserves were assessed using the Nemerow index and USEPA methods. Moreover, ArcGIS10.2 software was used to visualize the heavy metal index and display their spatial distribution. Cluster analysis enabled classification of the heavy metals into 4 categories, which allowed for identification of the heavy metals whose pollution index and health risks were highest, and, thus, whose control in the reserve is a priority. Results indicate that heavy metal pollution exists in the Qilihai Natural Reserve and in the north and east of the DaShentang Reserve; furthermore, human health risks exist in the Qilihai Natural Reserve and in the BinHai Wetland Reserve. In each reserve, the main factor influencing the pollution and health risk were high concentrations of As and Pb that exceed the corresponding standards. Measures must be adopted to control and remediate the pollutants. Furthermore, to protect the marine reserves, management policies must be implemented to improve water quality, which is an urgent task for both local and national governments. Copyright © 2017 Elsevier B.V. All rights reserved.

Classification of heavy metal ions present in multi-frequency multi-electrode potable water data using evolutionary algorithm

NASA Astrophysics Data System (ADS)

Karkra, Rashmi; Kumar, Prashant; Bansod, Baban K. S.; Bagchi, Sudeshna; Sharma, Pooja; Krishna, C. Rama

2017-11-01

Access to potable water for the common people is one of the most challenging tasks in the present era. Contamination of drinking water has become a serious problem due to various anthropogenic and geogenic events. The paper demonstrates the application of evolutionary algorithms, viz., particle swan optimization and genetic algorithm to 24 water samples containing eight different heavy metal ions (Cd, Cu, Co, Pb, Zn, Ar, Cr and Ni) for the optimal estimation of electrode and frequency to classify the heavy metal ions. The work has been carried out on multi-variate data, viz., single electrode multi-frequency, single frequency multi-electrode and multi-frequency multi-electrode water samples. The electrodes used are platinum, gold, silver nanoparticles and glassy carbon electrodes. Various hazardous metal ions present in the water samples have been optimally classified and validated by the application of Davis Bouldin index. Such studies are useful in the segregation of hazardous heavy metal ions found in water resources, thereby quantifying the degree of water quality.

Pressure-specific and multiple pressure response of fish assemblages in European running waters☆

PubMed Central

Schinegger, Rafaela; Trautwein, Clemens; Schmutz, Stefan

2013-01-01

We classified homogenous river types across Europe and searched for fish metrics qualified to show responses to specific pressures (hydromorphological pressures or water quality pressures) vs. multiple pressures in these river types. We analysed fish taxa lists from 3105 sites in 16 ecoregions and 14 countries. Sites were pre-classified for 15 selected pressures to separate unimpacted from impacted sites. Hierarchical cluster analysis was used to split unimpacted sites into four homogenous river types based on species composition and geographical location. Classification trees were employed to predict associated river types for impacted sites with four environmental variables. We defined a set of 129 candidate fish metrics to select the best reacting metrics for each river type. The candidate metrics represented tolerances/intolerances of species associated with six metric types: habitat, migration, water quality sensitivity, reproduction, trophic level and biodiversity. The results showed that 17 uncorrelated metrics reacted to pressures in the four river types. Metrics responded specifically to water quality pressures and hydromorphological pressures in three river types and to multiple pressures in all river types. Four metrics associated with water quality sensitivity showed a significant reaction in up to three river types, whereas 13 metrics were specific to individual river types. Our results contribute to the better understanding of fish assemblage response to human pressures at a pan-European scale. The results are especially important for European river management and restoration, as it is necessary to uncover underlying processes and effects of human pressures on aquatic communities. PMID:24003262

18 CFR 367.26 - Departmental classification.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 18 Conservation of Power and Water Resources 1 2013-04-01 2013-04-01 false Departmental classification. 367.26 Section 367.26 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY... ACT General Instructions § 367.26 Departmental classification. Salaries and wages and all other costs...

18 CFR 367.26 - Departmental classification.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 18 Conservation of Power and Water Resources 1 2012-04-01 2012-04-01 false Departmental classification. 367.26 Section 367.26 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY... ACT General Instructions § 367.26 Departmental classification. Salaries and wages and all other costs...

18 CFR 367.26 - Departmental classification.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 18 Conservation of Power and Water Resources 1 2014-04-01 2014-04-01 false Departmental classification. 367.26 Section 367.26 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY... ACT General Instructions § 367.26 Departmental classification. Salaries and wages and all other costs...

18 CFR 367.26 - Departmental classification.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 18 Conservation of Power and Water Resources 1 2011-04-01 2011-04-01 false Departmental classification. 367.26 Section 367.26 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY... ACT General Instructions § 367.26 Departmental classification. Salaries and wages and all other costs...

18 CFR 367.26 - Departmental classification.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 18 Conservation of Power and Water Resources 1 2010-04-01 2010-04-01 false Departmental classification. 367.26 Section 367.26 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY... ACT General Instructions § 367.26 Departmental classification. Salaries and wages and all other costs...

Probability-based classifications for spatially characterizing the water temperatures and discharge rates of hot springs in the Tatun Volcanic Region, Taiwan.

PubMed

Jang, Cheng-Shin

2015-05-01

Accurately classifying the spatial features of the water temperatures and discharge rates of hot springs is crucial for environmental resources use and management. This study spatially characterized classifications of the water temperatures and discharge rates of hot springs in the Tatun Volcanic Region of Northern Taiwan by using indicator kriging (IK). The water temperatures and discharge rates of the springs were first assigned to high, moderate, and low categories according to the two thresholds of the proposed spring classification criteria. IK was then used to model the occurrence probabilities of the water temperatures and discharge rates of the springs and probabilistically determine their categories. Finally, nine combinations were acquired from the probability-based classifications for the spatial features of the water temperatures and discharge rates of the springs. Moreover, various combinations of spring water features were examined according to seven subzones of spring use in the study region. The research results reveal that probability-based classifications using IK provide practicable insights related to propagating the uncertainty of classifications according to the spatial features of the water temperatures and discharge rates of the springs. The springs in the Beitou (BT), Xingyi Road (XYR), Zhongshanlou (ZSL), and Lengshuikeng (LSK) subzones are suitable for supplying tourism hotels with a sufficient quantity of spring water because they have high or moderate discharge rates. Furthermore, natural hot springs in riverbeds and valleys should be developed in the Dingbeitou (DBT), ZSL, Xiayoukeng (XYK), and Macao (MC) subzones because of low discharge rates and low or moderate water temperatures.

Trihalomethanes in Lisbon indoor swimming pools: occurrence, determining factors, and health risk classification.

PubMed

Silva, Zelinda Isabel; Rebelo, Maria Helena; Silva, Manuela Manso; Alves, Ana Martins; Cabral, Maria da Conceição; Almeida, Ana Cristina; Aguiar, Fátima Rôxo; de Oliveira, Anabela Lopes; Nogueira, Ana Cruz; Pinhal, Hermínia Rodrigues; Aguiar, Pedro Manuel; Cardoso, Ana Sofia

2012-01-01

Characterization of water quality from indoor swimming pools, using chorine-based disinfection techniques, was performed during a 6-mo period to study the occurrence, distribution, and concentration factors of trihalomethanes (THM). Several parameters such as levels of water THM, water and air chloroform, water bromodichloromethane (BDCM), water dibromochloromethane (DBCM), water bromoform (BF), free residual chlorine (FrCl), pH, water and air temperature, and permanganate water oxidizability (PWO) were determined in each pool during that period. Chloroform (CF(W)) was the THM detected at higher concentrations in all pools, followed by BDCM, DBCM, and BF detected at 99, 34, and 6% of the samples, respectively. Water THM concentrations ranged from 10.1 to 155 μg/L, with 6.5% of the samples presenting values above 100 μg/L (parametric value established in Portuguese law DL 306/2007). In this study, air chloroform (CF(Air)) concentrations ranged from 45 to 373 μg/m³ with 24% of the samples presenting values above 136 μg/m³ (considered high exposure value). Several significant correlations were observed between total THM and other parameters, namely, CF(W), CF(Air), FrCl, water temperature (T(W)), and PWO. These correlations indicate that FrCl, T(W) and PWO are parameters that influence THM formation. The exposure criterion established for water THM enabled the inclusion of 67% of Lisbon pools in the high exposure group, which reinforces the need for an improvement in pool water quality.

Quality Evaluation of Land-Cover Classification Using Convolutional Neural Network

NASA Astrophysics Data System (ADS)

Dang, Y.; Zhang, J.; Zhao, Y.; Luo, F.; Ma, W.; Yu, F.

2018-04-01

Land-cover classification is one of the most important products of earth observation, which focuses mainly on profiling the physical characters of the land surface with temporal and distribution attributes and contains the information of both natural and man-made coverage elements, such as vegetation, soil, glaciers, rivers, lakes, marsh wetlands and various man-made structures. In recent years, the amount of high-resolution remote sensing data has increased sharply. Accordingly, the volume of land-cover classification products increases, as well as the need to evaluate such frequently updated products that is a big challenge. Conventionally, the automatic quality evaluation of land-cover classification is made through pixel-based classifying algorithms, which lead to a much trickier task and consequently hard to keep peace with the required updating frequency. In this paper, we propose a novel quality evaluation approach for evaluating the land-cover classification by a scene classification method Convolutional Neural Network (CNN) model. By learning from remote sensing data, those randomly generated kernels that serve as filter matrixes evolved to some operators that has similar functions to man-crafted operators, like Sobel operator or Canny operator, and there are other kernels learned by the CNN model that are much more complex and can't be understood as existing filters. The method using CNN approach as the core algorithm serves quality-evaluation tasks well since it calculates a bunch of outputs which directly represent the image's membership grade to certain classes. An automatic quality evaluation approach for the land-cover DLG-DOM coupling data (DLG for Digital Line Graphic, DOM for Digital Orthophoto Map) will be introduced in this paper. The CNN model as an robustness method for image evaluation, then brought out the idea of an automatic quality evaluation approach for land-cover classification. Based on this experiment, new ideas of quality evaluation of DLG-DOM coupling land-cover classification or other kinds of labelled remote sensing data can be further studied.

Application of multivariate statistical analysis and hydrochemical and isotopic investigations for evaluation of groundwater quality and its suitability for drinking and agriculture purposes: case of Oum Ali-Thelepte aquifer, central Tunisia.

PubMed

Hassen, Imen; Hamzaoui-Azaza, Fadoua; Bouhlila, Rachida

2016-03-01

Groundwater plays a dominant role in arid regions; it is among the most available water resources in Tunisia. Located in northwestern Tunisia, Oum Ali-Thelepte is a deep Miocene sedimentary aquifer, where groundwater is the most important source of water supply. The aim of the study is to investigate the hydrochemical processes leading to mineralization and to assess water quality with respect to agriculture and drinking for a better management of groundwater resources. To achieve such objectives, water analysis was carried out on 16 groundwater samples collected during January-February 2014. Stable isotopes and 26 hydrochemical parameters were examined. The interpretation of these analytical data showed that the concentrations of major and trace elements were within the permissible level for human use. The distribution of mineral processes in this aquifer was identified using conventional classification techniques, suggesting that the water facies gradually changes from Ca-HCO3 to Mg-SO4 type and are controlled by water-rock interaction. These results were endorsed using multivariate statistical methods such as principal component analysis and cluster analysis. The sustainability of groundwater for drinking and irrigation was assessed based on the water quality index (WQI) and on Wilcox and Richards's diagrams. This aquifer has been classified as "excellent water" serving good irrigation in the area. As for the stable isotope, the measurements showed that groundwater samples lay between global meteoric water line (GMWL) and LMWL; hence, this arrangement signifies that the recharge of the Oum Ali-Thelepte aquifer is ensured by rainwater infiltration through mountains in the border of the aquifer without evaporation effects.

Classification schemes for knowledge translation interventions: a practical resource for researchers.

PubMed

Slaughter, Susan E; Zimmermann, Gabrielle L; Nuspl, Megan; Hanson, Heather M; Albrecht, Lauren; Esmail, Rosmin; Sauro, Khara; Newton, Amanda S; Donald, Maoliosa; Dyson, Michele P; Thomson, Denise; Hartling, Lisa

2017-12-06

As implementation science advances, the number of interventions to promote the translation of evidence into healthcare, health systems, or health policy is growing. Accordingly, classification schemes for these knowledge translation (KT) interventions have emerged. A recent scoping review identified 51 classification schemes of KT interventions to integrate evidence into healthcare practice; however, the review did not evaluate the quality of the classification schemes or provide detailed information to assist researchers in selecting a scheme for their context and purpose. This study aimed to further examine and assess the quality of these classification schemes of KT interventions, and provide information to aid researchers when selecting a classification scheme. We abstracted the following information from each of the original 51 classification scheme articles: authors' objectives; purpose of the scheme and field of application; socioecologic level (individual, organizational, community, system); adaptability (broad versus specific); target group (patients, providers, policy-makers), intent (policy, education, practice), and purpose (dissemination versus implementation). Two reviewers independently evaluated the methodological quality of the development of each classification scheme using an adapted version of the AGREE II tool. Based on these assessments, two independent reviewers reached consensus about whether to recommend each scheme for researcher use, or not. Of the 51 original classification schemes, we excluded seven that were not specific classification schemes, not accessible or duplicates. Of the remaining 44 classification schemes, nine were not recommended. Of the 35 recommended classification schemes, ten focused on behaviour change and six focused on population health. Many schemes (n = 29) addressed practice considerations. Fewer schemes addressed educational or policy objectives. Twenty-five classification schemes had broad applicability, six were specific, and four had elements of both. Twenty-three schemes targeted health providers, nine targeted both patients and providers and one targeted policy-makers. Most classification schemes were intended for implementation rather than dissemination. Thirty-five classification schemes of KT interventions were developed and reported with sufficient rigour to be recommended for use by researchers interested in KT in healthcare. Our additional categorization and quality analysis will aid in selecting suitable classification schemes for research initiatives in the field of implementation science.

Guide to the measurement of tree characteristics important to the quality classification for young hardwood trees

Treesearch

David L. Sonderman

1979-01-01

A procedure is shown for measuring external tree characteristics that are important in determining the current and future quality of young hardwood trees. This guide supplements a precious study which describes the quality classification system for young hardwood trees

Remote sensing based detection of forested wetlands: An evaluation of LiDAR, aerial imagery, and their data fusion

NASA Astrophysics Data System (ADS)

Suiter, Ashley Elizabeth

Multi-spectral imagery provides a robust and low-cost dataset for assessing wetland extent and quality over broad regions and is frequently used for wetland inventories. However in forested wetlands, hydrology is obscured by tree canopy making it difficult to detect with multi-spectral imagery alone. Because of this, classification of forested wetlands often includes greater errors than that of other wetlands types. Elevation and terrain derivatives have been shown to be useful for modelling wetland hydrology. But, few studies have addressed the use of LiDAR intensity data detecting hydrology in forested wetlands. Due the tendency of LiDAR signal to be attenuated by water, this research proposed the fusion of LiDAR intensity data with LiDAR elevation, terrain data, and aerial imagery, for the detection of forested wetland hydrology. We examined the utility of LiDAR intensity data and determined whether the fusion of Lidar derived data with multispectral imagery increased the accuracy of forested wetland classification compared with a classification performed with only multi-spectral image. Four classifications were performed: Classification A -- All Imagery, Classification B -- All LiDAR, Classification C -- LiDAR without Intensity, and Classification D -- Fusion of All Data. These classifications were performed using random forest and each resulted in a 3-foot resolution thematic raster of forested upland and forested wetland locations in Vermilion County, Illinois. The accuracies of these classifications were compared using Kappa Coefficient of Agreement. Importance statistics produced within the random forest classifier were evaluated in order to understand the contribution of individual datasets. Classification D, which used the fusion of LiDAR and multi-spectral imagery as input variables, had moderate to strong agreement between reference data and classification results. It was found that Classification A performed using all the LiDAR data and its derivatives (intensity, elevation, slope, aspect, curvatures, and Topographic Wetness Index) was the most accurate classification with Kappa: 78.04%, indicating moderate to strong agreement. However, Classification C, performed with LiDAR derivative without intensity data had less agreement than would be expected by chance, indicating that LiDAR contributed significantly to the accuracy of Classification B.

18 CFR 3a.13 - Classification responsibility and procedure.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 18 Conservation of Power and Water Resources 1 2014-04-01 2014-04-01 false Classification responsibility and procedure. 3a.13 Section 3a.13 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY COMMISSION, DEPARTMENT OF ENERGY GENERAL RULES NATIONAL SECURITY INFORMATION Classification § 3a...

18 CFR 3a.31 - Classification markings and special notations.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 18 Conservation of Power and Water Resources 1 2012-04-01 2012-04-01 false Classification markings and special notations. 3a.31 Section 3a.31 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY COMMISSION, DEPARTMENT OF ENERGY GENERAL RULES NATIONAL SECURITY INFORMATION Classification...

18 CFR 3a.13 - Classification responsibility and procedure.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 18 Conservation of Power and Water Resources 1 2010-04-01 2010-04-01 false Classification responsibility and procedure. 3a.13 Section 3a.13 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY COMMISSION, DEPARTMENT OF ENERGY GENERAL RULES NATIONAL SECURITY INFORMATION Classification § 3a...

18 CFR 3a.11 - Classification of official information.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 18 Conservation of Power and Water Resources 1 2013-04-01 2013-04-01 false Classification of official information. 3a.11 Section 3a.11 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY COMMISSION, DEPARTMENT OF ENERGY GENERAL RULES NATIONAL SECURITY INFORMATION Classification § 3a...

18 CFR 3a.13 - Classification responsibility and procedure.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 18 Conservation of Power and Water Resources 1 2013-04-01 2013-04-01 false Classification responsibility and procedure. 3a.13 Section 3a.13 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY COMMISSION, DEPARTMENT OF ENERGY GENERAL RULES NATIONAL SECURITY INFORMATION Classification § 3a...

18 CFR 3a.11 - Classification of official information.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 18 Conservation of Power and Water Resources 1 2012-04-01 2012-04-01 false Classification of official information. 3a.11 Section 3a.11 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY COMMISSION, DEPARTMENT OF ENERGY GENERAL RULES NATIONAL SECURITY INFORMATION Classification § 3a...

18 CFR 3a.13 - Classification responsibility and procedure.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 18 Conservation of Power and Water Resources 1 2012-04-01 2012-04-01 false Classification responsibility and procedure. 3a.13 Section 3a.13 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY COMMISSION, DEPARTMENT OF ENERGY GENERAL RULES NATIONAL SECURITY INFORMATION Classification § 3a...

18 CFR 3a.31 - Classification markings and special notations.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 18 Conservation of Power and Water Resources 1 2013-04-01 2013-04-01 false Classification markings and special notations. 3a.31 Section 3a.31 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY COMMISSION, DEPARTMENT OF ENERGY GENERAL RULES NATIONAL SECURITY INFORMATION Classification...

18 CFR 3a.11 - Classification of official information.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 18 Conservation of Power and Water Resources 1 2010-04-01 2010-04-01 false Classification of official information. 3a.11 Section 3a.11 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY COMMISSION, DEPARTMENT OF ENERGY GENERAL RULES NATIONAL SECURITY INFORMATION Classification § 3a...

18 CFR 3a.11 - Classification of official information.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 18 Conservation of Power and Water Resources 1 2014-04-01 2014-04-01 false Classification of official information. 3a.11 Section 3a.11 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY COMMISSION, DEPARTMENT OF ENERGY GENERAL RULES NATIONAL SECURITY INFORMATION Classification § 3a...

18 CFR 3a.31 - Classification markings and special notations.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 18 Conservation of Power and Water Resources 1 2014-04-01 2014-04-01 false Classification markings and special notations. 3a.31 Section 3a.31 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY COMMISSION, DEPARTMENT OF ENERGY GENERAL RULES NATIONAL SECURITY INFORMATION Classification...

Cyber-physical system for a water reclamation plant: Balancing aeration, energy, and water quality to maintain process resilience

NASA Astrophysics Data System (ADS)

Zhu, Junjie

Aeration accounts for a large fraction of energy consumption in conventional water reclamation plants (WRPs). Although process operations at older WRPs can satisfy effluent permit requirements, they typically operate with excess aeration. More effective process controls at older WRPs can be challenging as operators work to balance higher energy costs and more stringent effluent limitations while managing fluctuating loads. Therefore, understandings of process resilience or ability to quickly return to original operation conditions at a WRP are important. A state-of-art WRP should maintain process resilience to deal with different kinds of perturbations even after optimization of energy demands. This work was to evaluate the applicability and feasibility of cyber-physical system (CPS) for improving operation at Metropolitan Water Reclamation District of Greater Chicago (MWRDGC) Calumet WRP. In this work, a process model was developed and used to better understand the conditions of current Calumet WRP, with additional valuable information from two dissolved oxygen field measurements. Meanwhile, a classification system was developed to reveal the pattern of historical influent scenario based on cluster analysis and cross-tabulation analysis. Based on the results from the classification, typical process control options were investigated. To ensure the feasibility of information acquisition, the reliability and flexibility of soft sensors were assessed to typical influent conditions. Finally, the process resilience was investigated to better balance influent perturbations, energy demands, and effluent quality for long-term operations. These investigations and evaluations show that although the energy demands change as the influent conditions and process controls. In general, aeration savings could be up to 50% from the level of current consumption; with a more complex process controls, the saving could be up to 70% in relatively steady-state conditions and at least 40% in relatively challenging transient conditions. The soft sensors can provide reliable and flexible performance on target predictions. The plant can still maintain at a similar level of process resilience after 50% aeration saving, even during long-term perturbations. Overall, this work shows that it is well feasible to provide more cost-effective operations at the Calumet WRP, and meanwhile influent perturbations, effluent quality, and process resilience are well in balance.

Unmanned Ground Vehicle Perception Using Thermal Infrared Cameras

NASA Technical Reports Server (NTRS)

Rankin, Arturo; Huertas, Andres; Matthies, Larry; Bajracharya, Max; Assad, Christopher; Brennan, Shane; Bellut, Paolo; Sherwin, Gary

2011-01-01

TIR cameras can be used for day/night Unmanned Ground Vehicle (UGV) autonomous navigation when stealth is required. The quality of uncooled TIR cameras has significantly improved over the last decade, making them a viable option at low speed Limiting factors for stereo ranging with uncooled LWIR cameras are image blur and low texture scenes TIR perception capabilities JPL has explored includes: (1) single and dual band TIR terrain classification (2) obstacle detection (pedestrian, vehicle, tree trunks, ditches, and water) (3) perception thru obscurants

Comparison of the resulting error in data fusion techniques when used with remote sensing, earth observation, and in-situ data sets for water quality applications

NASA Astrophysics Data System (ADS)

Ziemba, Alexander; El Serafy, Ghada

2016-04-01

Ecological modeling and water quality investigations are complex processes which can require a high level of parameterization and a multitude of varying data sets in order to properly execute the model in question. Since models are generally complex, their calibration and validation can benefit from the application of data and information fusion techniques. The data applied to ecological models comes from a wide range of sources such as remote sensing, earth observation, and in-situ measurements, resulting in a high variability in the temporal and spatial resolution of the various data sets available to water quality investigators. It is proposed that effective fusion into a comprehensive singular set will provide a more complete and robust data resource with which models can be calibrated, validated, and driven by. Each individual product contains a unique valuation of error resulting from the method of measurement and application of pre-processing techniques. The uncertainty and error is further compounded when the data being fused is of varying temporal and spatial resolution. In order to have a reliable fusion based model and data set, the uncertainty of the results and confidence interval of the data being reported must be effectively communicated to those who would utilize the data product or model outputs in a decision making process[2]. Here we review an array of data fusion techniques applied to various remote sensing, earth observation, and in-situ data sets whose domains' are varied in spatial and temporal resolution. The data sets examined are combined in a manner so that the various classifications, complementary, redundant, and cooperative, of data are all assessed to determine classification's impact on the propagation and compounding of error. In order to assess the error of the fused data products, a comparison is conducted with data sets containing a known confidence interval and quality rating. We conclude with a quantification of the performance of the data fusion techniques and a recommendation on the feasibility of applying of the fused products in operating forecast systems and modeling scenarios. The error bands and confidence intervals derived can be used in order to clarify the error and confidence of water quality variables produced by prediction and forecasting models. References [1] F. Castanedo, "A Review of Data Fusion Techniques", The Scientific World Journal, vol. 2013, pp. 1-19, 2013. [2] T. Keenan, M. Carbone, M. Reichstein and A. Richardson, "The model-data fusion pitfall: assuming certainty in an uncertain world", Oecologia, vol. 167, no. 3, pp. 587-597, 2011.

76 FR 60388 - Revision of Cotton Futures Classification Procedures

Federal Register 2010, 2011, 2012, 2013, 2014

2011-09-29

...-005] RIN 0581-AD16 Revision of Cotton Futures Classification Procedures AGENCY: Agricultural Marketing... update the procedures for cotton futures quality classification services by using Smith-Doxey classification data in the cotton futures classification process. In addition, references to a separate and...

77 FR 5379 - Revision of Cotton Futures Classification Procedures

Federal Register 2010, 2011, 2012, 2013, 2014

2012-02-03

... 0581-AD16 Revision of Cotton Futures Classification Procedures AGENCY: Agricultural Marketing Service... for cotton futures quality classification services by using Smith-Doxey classification data in the cotton futures classification process. In addition, references to a separate and optional review of...

New approach for rapid assessment of trophic status of Yellow Sea and East China Sea using easy-to-measure parameters

NASA Astrophysics Data System (ADS)

Kong, Xianyu; Liu, Yanfang; Jian, Huimin; Su, Rongguo; Yao, Qingzhen; Shi, Xiaoyong

2017-10-01

To realize potential cost savings in coastal monitoring programs and provide timely advice for marine management, there is an urgent need for efficient evaluation tools based on easily measured variables for the rapid and timely assessment of estuarine and offshore eutrophication. In this study, using parallel factor analysis (PARAFAC), principal component analysis (PCA), and discriminant function analysis (DFA) with the trophic index (TRIX) for reference, we developed an approach for rapidly assessing the eutrophication status of coastal waters using easy-to-measure parameters, including chromophoric dissolved organic matter (CDOM), fluorescence excitation-emission matrices, CDOM UV-Vis absorbance, and other water-quality parameters (turbidity, chlorophyll a, and dissolved oxygen). First, we decomposed CDOM excitation-emission matrices (EEMs) by PARAFAC to identify three components. Then, we applied PCA to simplify the complexity of the relationships between the water-quality parameters. Finally, we used the PCA score values as independent variables in DFA to develop a eutrophication assessment model. The developed model yielded classification accuracy rates of 97.1%, 80.5%, 90.3%, and 89.1% for good, moderate, and poor water qualities, and for the overall data sets, respectively. Our results suggest that these easy-to-measure parameters could be used to develop a simple approach for rapid in-situ assessment and monitoring of the eutrophication of estuarine and offshore areas.

Environmental effects of hydrothermal alteration and historical mining on water and sediment quality in Central Colorado

USGS Publications Warehouse

Church, S.E.; Fey, D. L.; Klein, T.L.; Schmidt, T.S.; Wanty, R.B.; deWitt, E.H.; Rockwell, B.W.; San, Juan C.A.

2009-01-01

The U.S. Geological Survey conducted an environmental assessment of 198 catchments in a 54,000-km2 area of central Colorado, much of which is on Federal land. The Colorado Mineral Belt, a northeast-trending zone of historical base- and precious-metal mining, cuts diagonally across the study area. The investigation was intended to test the hypothesis that degraded water and sediment quality are restricted to catchments in which historical mining has occurred. Water, streambed sediment, and aquatic insects were collected from (1) catchments underlain by single lithogeochemical units, some of which were hydrothermally altered, that had not been prospected or mined; (2) catchments that contained evidence of prospecting, most of which contain hydrothermally altered rock, but no historical mining; and (3) catchments, all of which contain hydrothermally altered rock, where historical but now inactive mines occur. Geochemical data determined from catchments that did not contain hydrothermal alteration or historical mines met water quality criteria and sediment quality guidelines. Base-metal concentrations from these types of catchments showed small geochemical variations that reflect host lithology. Hydrothermal alteration and mineralization typically are associated with igneous rocks that have intruded older bedrock in a catchment. This alteration was regionally mapped and characterized primarily through the analysis of remote sensing data acquired by the ASTER satellite sensor. Base-metal concentrations among unaltered rock types showed small geochemical variations that reflect host lithology. Base-metal concentrations were elevated in sediment from catchments underlain by hydrothermally altered rock. Classification of catchments on the basis of mineral deposit types proved to be an efficient and accurate method for discriminating catchments that have degraded water and sediment quality. Only about 4.5 percent of the study area has been affected by historical mining, whereas a larger part of the study area is underlain by hydrothermally altered rock that has weathered to produce water and sediment with naturally elevated geochemical baselines. 

Application of Sensor Fusion to Improve Uav Image Classification

NASA Astrophysics Data System (ADS)

Jabari, S.; Fathollahi, F.; Zhang, Y.

2017-08-01

Image classification is one of the most important tasks of remote sensing projects including the ones that are based on using UAV images. Improving the quality of UAV images directly affects the classification results and can save a huge amount of time and effort in this area. In this study, we show that sensor fusion can improve image quality which results in increasing the accuracy of image classification. Here, we tested two sensor fusion configurations by using a Panchromatic (Pan) camera along with either a colour camera or a four-band multi-spectral (MS) camera. We use the Pan camera to benefit from its higher sensitivity and the colour or MS camera to benefit from its spectral properties. The resulting images are then compared to the ones acquired by a high resolution single Bayer-pattern colour camera (here referred to as HRC). We assessed the quality of the output images by performing image classification tests. The outputs prove that the proposed sensor fusion configurations can achieve higher accuracies compared to the images of the single Bayer-pattern colour camera. Therefore, incorporating a Pan camera on-board in the UAV missions and performing image fusion can help achieving higher quality images and accordingly higher accuracy classification results.

Preliminary study on the radiological and physicochemical quality of the Umgeni Water catchments and drinking water sources in KwaZulu-Natal, South Africa.

PubMed

Manickum, T; John, W; Terry, S; Hodgson, K

2014-11-01

Raw and potable water sample sources, from the Umgeni Water catchment areas (rivers, dams, boreholes) in central KwaZulu-Natal (South Africa), were screened for Uranium concentration and alpha and beta radioactivity. Test methods used were gas flow proportional counting for alpha-beta radioactivity, and kinetic phosphorescence analysis (KPA), for Uranium. The uranium levels (median = 0.525 μg/L, range = <0.050-5.010) were well below the international World Health Organization (WHO) (2011) guideline for drinking-water quality (≤15 μg/L). The corresponding alpha and beta radioactivity was ≤0.5 Bq/L (median = 0.084, Interquartile Range (IR) = 0.038, range = 0.018-0.094), and ≤1.0 Bq/L (median = 0.114, IR = 0.096, range = 0.024-0.734), respectively, in compliance with the international WHO limits. For uranium radionuclide, the average dose level, at uranium level of ±0.525 μg/L, was 0.06 μSv/a, which complies with the WHO reference dose level for drinking water (<0.1 mSv/a). There was a distinct trend of cluster of relatively higher Uranium levels of some sources that were found to be associated with the geology/geography and groundwater sources. Overall, the radiological water quality classification, with respect to WHO, is "Blue" - ideal; additional physicochemical analyses indicated good water quality. The analytical test methods employed were found to be suitable for preliminary screening for potential radioactive "hot spots". The observed Uranium levels, and the alpha/beta radioactivity, indicate contribution largely from Naturally Occurring Radioactive Material (NORM), with no significant health risk to humans, or to the environment. Copyright © 2014 Elsevier Ltd. All rights reserved.

An assessment of streamflow vulnerability to climate using ...

EPA Pesticide Factsheets

Identifying regions with similar hydrology is useful for assessing water quality and quantity across the U.S., especially areas that are difficult or costly to monitor. For example, hydrologic landscapes (HLs) have been used to map streamflow variability and assess the spatial distribution of climatic response in Oregon, Alaska, and the Pacific Northwest. HLs have also been applied to assess historic and projected climatic impacts across the Western U.S. In this project, we summarized (1) the HL classification methodology and (2) the utility of using HLs as a tool to classify the vulnerability of streams to climatic changes in the Western U.S. During the HL classification process, we analyzed climate, seasonality, aquifer permeability, terrain, and soil permeability as the primary hydrologic drivers (and precipitation intensity as a secondary driver) associated with large scale hydrologic processes (storage, conveyance, and flow of water into or out of the watershed) in the West. We derived the dominant hydrologic pathways (surface runoff or deep or shallow groundwater) from the HL classification of different catchments to test our hypotheses: 1) Changes in climate will have greater impacts on streamflow in catchments dominated by surface runoff. 2) Catchments historically fed by surface runoff from winter snowmelt in the spring will experience greater impact if precipitation falls as rain instead of snow. We calculated S* (precipitation surplus, which includes

Agricultural land-use classification using landsat imagery data, and estimates of irrigation water use in Gooding, Jerome, Lincoln, and Minidoka counties, 1992 water year, Upper Snake River basin, Idaho and western Wyoming

USGS Publications Warehouse

Maupin, Molly A.

1997-01-01

As part of the U.S. Geological Survey's National Water-Quality Assessment Program in the upper Snake River Basin study unit, land- and water-use data were used to describe activities that have potential effects on water quality, including biological conditions, in the basin. Land-use maps and estimates of water use by irrigated agriculture were needed for Gooding, Jerome, Lincoln, and Minidoka Counties (south-central Idaho), four of the most intensively irrigated counties in the study unit. Land use in the four counties was mapped from Landsat Thematic Mapper imagery data for the 1992 water year using the SPECTRUM computer program. Land-use data were field verified in 108 randomly selected sections (640 acres each); results compared favorably with land-use maps from other sources. Water used for irrigation during the 1992 water year was estimated using land-use and ancillary data. In 1992, a drought year, estimated irrigation withdrawals in the four counties were about 2.9 million acre-feet of water. Of the 2.9 million acre-feet, an estimated 2.12 million acre-feet of water was withdrawn from surface water, mainly the Snake River, and nearly 776,000 acre-feet was withdrawn from ground water. One-half of the 2.9 million acre-feet of water withdrawn for irrigation was considered to be lost during conveyance or was returned to the Snake River; the remainder was consumptively used by crops during the growing season.

A Novel approach to monitor chlorophyll-a concentration using an adaptive model from MODIS data at 250 metres spatial resolution

NASA Astrophysics Data System (ADS)

El Alem, A.; Chokmani, K.; Laurion, I.; El Adlouni, S.

2013-12-01

Occurrence and extent of Harmful Algal Bloom (HAB) has increased in inland water bodies around the world. The appearance of these blooms reflects the advanced state of eutrophication of several aquatic systems caused by urban, agricultural, and industrial development. Algal blooms, especially those cyanobacterial origins, are capable to produce and release toxins, threatening human and animal health, quality of drinking water, and recreational water bodies. Conventional monitoring networks, based on infrequent sampling in a few fixed monitoring stations, cannot provide the information needed as HABs are spatially and temporally heterogeneous. Remote sensing represents an interesting alternative to provide the required spatial and temporal coverage. The usefulness of air-borne and satellite remote sensing data to detect HABs was demonstrated since three decades ago, and since several empirical and semi-empirical models, using satellite imagery, were developed to estimate chlorophyll-a concentration [Chl-a] as a proxy to detect bloom proliferations. However, most of those models presented several weaknesses that are generally linked to the range of [Chl-a] to be estimated. Indeed, models originally calibrated for high [Chl-a] fail to estimate low concentrations and vice versa. In this study, an adaptive model to estimate [Chl-a], spread over a wide range of concentrations, is developed for optically complex inland water bodies based on combination of water spectral response classification and three developed semi-empirical algorithms using a multivariate regression. Three distinct water types (low, medium, and high [Chl-a]) are first identified using the Classification and Regression Tree (CART) method performed on remote sensing reflectance over a dataset of 44 [Chl-a] samples collected from Lakes over Quebec province. Based on the water classification, a specific multivariate model to each water type is developed using the same dataset and the MODIS data at 250-m spatial resolution. By pre-clustering inland water bodies, the results were very interesting as the determination coefficients as well as the relative RMSE of the cross-validation were of 0.99, 0.98 and 0.95 and of 0.5%, 8% and 17% for high, medium, and low [Chl-a], respectively. On the other hand, the adaptive model reached a global success rate of 92% using an independent, semi-qualitative, [Chl-a] samples collected over more than twenty inland water bodies for the years 2009 and 2010 over the Quebec province.

Hydrogeological features and environmental impacts of geothermal waters in the Yıldız River Basin (Sivas, Turkey).

PubMed

Keskin, Tülay Ekemen; Kaçaroğlu, Fikret

2015-02-01

The study area, located in the Yıldız River Basin (Sivas), has eight geothermal waters, which are used for balneotherapy. The aim of this study was to investigate the natural and/or anthropogenic water pollution in terms of drinking and irrigation water in the Sıcak Çermik, Uyuz Çermiği, and Hamzaşeyh Çermiği geothermal areas. Na+, Cl-, SO4(-2), B, Mn, Fe, As, and Se concentrations of the geothermal waters generally exceed the upper limits stated in the Turkish Standards for Water Intended for Human Consumption and World Health Organization regulations. Based on the irrigation water classification by the U.S. Salinity Laboratory Diagram, it is concluded that these waters may have hazardous levels of salinity and sodium when used as irrigation water. Wastewater from these health and tourism centers is discharged into the Yıldız River and to agricultural land. This procedure causes increase in the concentrations of major and minor elements and negatively affects the river water quality.

Shallow-Water Mud Acoustics

DTIC Science & Technology

2015-09-30

1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Shallow- Water Mud Acoustics William L. Siegmann...shallow water over mud sediments and of acoustic detection, localization, and classification of objects buried in mud. OBJECTIVES • Develop...including long-range conveyance of information; detection, localization, and classification of objects buried in mud; and improvement of shallow water

Ice/water Classification of Sentinel-1 Images

NASA Astrophysics Data System (ADS)

Korosov, Anton; Zakhvatkina, Natalia; Muckenhuber, Stefan

2015-04-01

Sea Ice monitoring and classification relies heavily on synthetic aperture radar (SAR) imagery. These sensors record data either only at horizontal polarization (RADARSAT-1) or vertically polarized (ERS-1 and ERS-2) or at dual polarization (Radarsat-2, Sentinel-1). Many algorithms have been developed to discriminate sea ice types and open water using single polarization images. Ice type classification, however, is still ambiguous in some cases. Sea ice classification in single polarization SAR images has been attempted using various methods since the beginning of the ERS programme. The robust classification using only SAR images that can provide useful results under varying sea ice types and open water tend to be not generally applicable in operational regime. The new generation SAR satellites have capability to deliver images in several polarizations. This gives improved possibility to develop sea ice classification algorithms. In this study we use data from Sentinel-1 at dual-polarization, i.e. HH (horizontally transmitted and horizontally received) and HV (horizontally transmitted, vertically received). This mode assembles wide SAR image from several narrower SAR beams, resulting to an image of 500 x 500 km with 50 m resolution. A non-linear scheme for classification of Sentinel-1 data has been developed. The processing allows to identify three classes: ice, calm water and rough water at 1 km spatial resolution. The raw sigma0 data in HH and HV polarization are first corrected for thermal and random noise by extracting the background thermal noise level and smoothing the image with several filters. At the next step texture characteristics are computed in a moving window using a Gray Level Co-occurence Matrix (GLCM). A neural network is applied at the last step for processing array of the most informative texture characteristics and ice/water classification. The main results are: * the most informative texture characteristics to be used for sea ice classification were revealed; * the best set of parameters including the window size, number of levels of quantization of sigma0 values and co-occurence distance was found; * a support vector machine (SVM) was trained on results of visual classification of 30 Sentinel-1 images. Despite the general high accuracy of the neural network (95% of true positive classification) problems with classification of young newly formed ice and rough water arise due to the similar average backscatter and texture. Other methods of smoothing and computation of texture characteristics (e.g. computation of GLCM from a variable size window) is assessed. The developed scheme will be utilized in NRT processing of Sentinel-1 data at NERSC within the MyOcean2 project.

Classification of sea ice types with single-band (33.6 GHz) airborne passive microwave imagery

NASA Astrophysics Data System (ADS)

Eppler, Duane T.; Farmer, L. Dennis; Lohanick, Alan W.; Hoover, Mervyn

1986-09-01

During March 1983 extensive high-quality airborne passive Ka band (33.6 GHz) microwave imagery and coincident high-resolution aerial photography were obtained of ice along a 378-km flight line in the Beaufort Sea. Analysis of these data suggests that four classes of winter surfaces can be distinguished solely on the basis of 33.6-GHz brightness temperature: open water, frazil, old ice, and young/first-year ice. New ice (excluding frazil) and nilas display brightness temperatures that overlap the range of temperatures characteristic of old ice and, to a lesser extent, young/first-year ice. Scenes in which a new ice or nilas are present in appreciable amounts are subject to substantial errors in classification if static measures of Ka band radiometric brightness temperature alone are considered. Textural characteristics of nilas and new ice, however, differ significantly from textural features characteristic of other ice types and probably can be used with brightness temperature data to classify ice type in high-resolution single-band microwave images. In any case, open water is radiometrically the coldest surface observed in any scene. Lack of overlap between brightness temperatures characteristic of other surfaces indicates that estimates of the areal extent of open water based on only 33.6-GHz brightness temperatures are accurate.

A feed-forward Hopfield neural network algorithm (FHNNA) with a colour satellite image for water quality mapping

NASA Astrophysics Data System (ADS)

Asal Kzar, Ahmed; Mat Jafri, M. Z.; Hwee San, Lim; Al-Zuky, Ali A.; Mutter, Kussay N.; Hassan Al-Saleh, Anwar

2016-06-01

There are many techniques that have been given for water quality problem, but the remote sensing techniques have proven their success, especially when the artificial neural networks are used as mathematical models with these techniques. Hopfield neural network is one type of artificial neural networks which is common, fast, simple, and efficient, but it when it deals with images that have more than two colours such as remote sensing images. This work has attempted to solve this problem via modifying the network that deals with colour remote sensing images for water quality mapping. A Feed-forward Hopfield Neural Network Algorithm (FHNNA) was modified and used with a satellite colour image from type of Thailand earth observation system (THEOS) for TSS mapping in the Penang strait, Malaysia, through the classification of TSS concentrations. The new algorithm is based essentially on three modifications: using HNN as feed-forward network, considering the weights of bitplanes, and non-self-architecture or zero diagonal of weight matrix, in addition, it depends on a validation data. The achieved map was colour-coded for visual interpretation. The efficiency of the new algorithm has found out by the higher correlation coefficient (R=0.979) and the lower root mean square error (RMSE=4.301) between the validation data that were divided into two groups. One used for the algorithm and the other used for validating the results. The comparison was with the minimum distance classifier. Therefore, TSS mapping of polluted water in Penang strait, Malaysia, can be performed using FHNNA with remote sensing technique (THEOS). It is a new and useful application of HNN, so it is a new model with remote sensing techniques for water quality mapping which is considered important environmental problem.

Impacts of soil moisture content on visual soil evaluation

NASA Astrophysics Data System (ADS)

Emmet-Booth, Jeremy; Forristal, Dermot; Fenton, Owen; Bondi, Giulia; Creamer, Rachel; Holden, Nick

2017-04-01

Visual Soil Examination and Evaluation (VSE) techniques offer tools for soil quality assessment. They involve the visual and tactile assessment of soil properties such as aggregate size and shape, porosity, redox morphology, soil colour and smell. An increasing body of research has demonstrated the reliability and utility of VSE techniques. However a number of limitations have been identified, including the potential impact of soil moisture variation during sampling. As part of a national survey of grassland soil quality in Ireland, an evaluation of the impact of soil moisture on two widely used VSE techniques was conducted. The techniques were Visual Evaluation of Soil Structure (VESS) (Guimarães et al., 2011) and Visual Soil Assessment (VSA) (Shepherd, 2009). Both generate summarising numeric scores that indicate soil structural quality, though employ different scoring mechanisms. The former requires the assessment of properties concurrently and the latter separately. Both methods were deployed on 20 sites across Ireland representing a range of soils. Additional samples were taken for soil volumetric water (θ) determination at 5-10 and 10-20 cm depth. No significant correlation was observed between θ 5-10 cm and either VSE technique. However, VESS scores were significantly related to θ 10-20 cm (rs = 0.40, sig = 0.02) while VSA scores were not (rs = -0.33, sig = 0.06). VESS and VSA scores can be grouped into quality classifications (good, moderate and poor). No significant mean difference was observed between θ 5-10 cm or θ 10-20 cm according to quality classification by either method. It was concluded that VESS scores may be affected by soil moisture variation while VSA appear unaffected. The different scoring mechanisms, where the separate assessment and scoring of individual properties employed by VSA, may limit soil moisture effects. However, moisture content appears not to affect overall structural quality classification by either method. References Guimarães, R.M.C., Ball, B.C. & Tormena, C.A. 2011. Improvements in the visual evaluation of soil structure, Soil Use and Management, 27, 3: 395-403 Shepherd, G.T. 2009. Visual Soil Assessment. Field guide for pastoral grazing and cropping on flat to rolling country. 2nd edn. Horizons regional council, New Zealand.

Study on a pattern classification method of soil quality based on simplified learning sample dataset

USGS Publications Warehouse

Zhang, Jiahua; Liu, S.; Hu, Y.; Tian, Y.

2011-01-01

Based on the massive soil information in current soil quality grade evaluation, this paper constructed an intelligent classification approach of soil quality grade depending on classical sampling techniques and disordered multiclassification Logistic regression model. As a case study to determine the learning sample capacity under certain confidence level and estimation accuracy, and use c-means algorithm to automatically extract the simplified learning sample dataset from the cultivated soil quality grade evaluation database for the study area, Long chuan county in Guangdong province, a disordered Logistic classifier model was then built and the calculation analysis steps of soil quality grade intelligent classification were given. The result indicated that the soil quality grade can be effectively learned and predicted by the extracted simplified dataset through this method, which changed the traditional method for soil quality grade evaluation. ?? 2011 IEEE.

18 CFR 3a.31 - Classification markings and special notations.

Code of Federal Regulations, 2011 CFR

2011-04-01

... unit taking the action. When classification changes are made, the classification markings themselves... 18 Conservation of Power and Water Resources 1 2011-04-01 2011-04-01 false Classification markings... REGULATORY COMMISSION, DEPARTMENT OF ENERGY GENERAL RULES NATIONAL SECURITY INFORMATION Classification...

Proposal for a functional classification system of heart failure in patients with end-stage renal disease: proceedings of the acute dialysis quality initiative (ADQI) XI workgroup.

PubMed

Chawla, Lakhmir S; Herzog, Charles A; Costanzo, Maria Rosa; Tumlin, James; Kellum, John A; McCullough, Peter A; Ronco, Claudio

2014-04-08

Structural heart disease is highly prevalent in patients with chronic kidney disease requiring dialysis. More than 80% of patients with end-stage renal disease (ESRD) are reported to have cardiovascular disease. This observation has enormous clinical relevance because the leading causes of death for patients with ESRD are of cardiovascular disease etiology, including heart failure, myocardial infarction, and sudden cardiac death. The 2 systems most commonly used to classify the severity of heart failure are the New York Heart Association (NYHA) functional classification and the American Heart Association (AHA)/American College of Cardiology (ACC) staging system. With rare exceptions, patients with ESRD who do not receive renal replacement therapy (RRT) develop signs and symptoms of heart failure, including dyspnea and edema due to inability of the severely diseased kidneys to excrete sodium and water. Thus, by definition, nearly all patients with ESRD develop a symptomatology consistent with heart failure if fluid removal by RRT is delayed. Neither the AHA/ACC heart failure staging nor the NYHA functional classification system identifies the variable symptomatology that patients with ESRD experience depending upon whether evaluation occurs before or after fluid removal by RRT. Consequently, the incidence, severity, and outcomes of heart failure in patients with ESRD are poorly characterized. The 11th Acute Dialysis Quality Initiative has identified this issue as a critical unmet need for the proper evaluation and treatment of heart failure in patients with ESRD. We propose a classification schema based on patient-reported dyspnea assessed both pre- and post-ultrafiltration, in conjunction with echocardiography. Copyright © 2014 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Recognition and characterization of networks of water bodies in the Arctic ice-wedge polygonal tundra using high-resolution satellite imagery

NASA Astrophysics Data System (ADS)

Skurikhin, A. N.; Gangodagamage, C.; Rowland, J. C.; Wilson, C. J.

2013-12-01

Arctic lowland landscapes underlain by permafrost are often characterized by polygon-like patterns such as ice-wedge polygons outlined by networks of ice wedges and complemented with polygon rims, troughs, shallow ponds and thermokarst lakes. Polygonal patterns and corresponding features are relatively easy to recognize in high spatial resolution satellite imagery by a human, but their automated recognition is challenging due to the variability in their spectral appearance, the irregularity of individual trough spacing and orientation within the patterns, and a lack of unique spectral response attributable to troughs with widths commonly between 1 m and 2 m. Accurate identification of fine scale elements of ice-wedge polygonal tundra is important as their imprecise recognition may bias estimates of water, heat and carbon fluxes in large-scale climate models. Our focus is on the problem of identification of Arctic polygonal tundra fine-scale landscape elements (as small as 1 m - 2 m width). The challenge of the considered problem is that while large water bodies (e.g. lakes and rivers) can be recognized based on spectral response, reliable recognition of troughs is more difficult. Troughs do not have unique spectral signature, their appearance is noisy (edges are not strong), their width is small, and they often form connected networks with ponds and lakes, and thus they have overlapping spectral response with other water bodies and surrounding non-water bodies. We present a semi-automated approach to identify and classify Arctic polygonal tundra landscape components across the range of spatial scales, such as troughs, ponds, river- and lake-like objects, using high spatial resolution satellite imagery. The novelty of the approach lies in: (1) the combined use of segmentation and shape-based classification to identify a broad range of water bodies, including troughs, and (2) the use of high-resolution WorldView-2 satellite imagery (with resolution of 0.6 m) for this identification. The approach starts by segmenting water bodies from an image, which are then categorized using shape-based classification. Segmentation uses combination of pan sharpened multispectral bands and is based on the active contours without edges technique. The segmentation is robust to noise and can detect objects with weak boundaries that is important for extraction of troughs. We then categorize the segmented regions via shape based classification. Because segmentation accuracy is the main factor impacting the quality of the shape-based classification, for segmentation accuracy assessment we created reference image using WorldView-2 satellite image of ice-wedge polygonal tundra. Reference image contained manually labelled image regions which cover components of drainage networks, such as troughs, ponds, rivers and lakes. The evaluation has shown that the approach provides a good accuracy of segmentation and reasonable classification results. The overall accuracy of the segmentation is approximately 95%, the segmentation user's and producer's accuracies are approximately 92% and 97% respectively.

Preliminary classification of water areas within the Atchafalaya Basin Floodway System by using landsat imagery

USGS Publications Warehouse

Allen, Yvonne C.; Constant, Glenn C.; Couvillion, Brady R.

2008-01-01

The southern portion of the Atchafalaya Basin Floodway System (ABFS) is a large area (2,571 km2) in south central Louisiana bounded on the east and west sides by a levee system. The ABFS is a sparsely populated area that includes some of the Nation's most significant extents of bottomland hardwoods, swamps, bayous, and backwater lakes, holding a rich abundance and diversity of terrestrial and aquatic species. The seasonal flow of water through the ABFS is critical to maintaining its ecological integrity. Because of strong interdependencies among species, habitat quality, and water flow in the ABFS, there is a need to better define the paths by which water moves at various stages of the hydrocycle. Although river level gages have collected a long historical record of water level variation, very little synoptic information has been available regarding the distribution and character of water at more remote locations in the basin. Most water management plans for the ABFS strive to improve water quality by increasing water flow and circulation from the main stem of the Atchafalaya River into isolated areas. To describe the distribution of land and water on a basin-wide scale, we chose to use Landsat 5 and Landsat 7 imagery to determine the extent of water distribution from 1985 to 2006 and at a variety of river stages. Because the visual signature of river water is high turbidity, we also used Landsat imagery to describe the distribution of turbid water in the ABFS. The ability to track water flow patterns by tracking turbid waters will enhance the characterization of water movement and aid in planning.

Evaluating Sentinel-2 for Lakeshore Habitat Mapping Based on Airborne Hyperspectral Data.

PubMed

Stratoulias, Dimitris; Balzter, Heiko; Sykioti, Olga; Zlinszky, András; Tóth, Viktor R

2015-09-11

Monitoring of lakeshore ecosystems requires fine-scale information to account for the high biodiversity typically encountered in the land-water ecotone. Sentinel-2 is a satellite with high spatial and spectral resolution and improved revisiting frequency and is expected to have significant potential for habitat mapping and classification of complex lakeshore ecosystems. In this context, investigations of the capabilities of Sentinel-2 in regard to the spatial and spectral dimensions are needed to assess its potential and the quality of the expected output. This study presents the first simulation of the high spatial resolution (i.e., 10 m and 20 m) bands of Sentinel-2 for lakeshore mapping, based on the satellite's Spectral Response Function and hyperspectral airborne data collected over Lake Balaton, Hungary in August 2010. A comparison of supervised classifications of the simulated products is presented and the information loss from spectral aggregation and spatial upscaling in the context of lakeshore vegetation classification is discussed. We conclude that Sentinel-2 imagery has a strong potential for monitoring fine-scale habitats, such as reed beds.

Evaluating Sentinel-2 for Lakeshore Habitat Mapping Based on Airborne Hyperspectral Data

PubMed Central

Stratoulias, Dimitris; Balzter, Heiko; Sykioti, Olga; Zlinszky, András; Tóth, Viktor R.

2015-01-01

Monitoring of lakeshore ecosystems requires fine-scale information to account for the high biodiversity typically encountered in the land-water ecotone. Sentinel-2 is a satellite with high spatial and spectral resolution and improved revisiting frequency and is expected to have significant potential for habitat mapping and classification of complex lakeshore ecosystems. In this context, investigations of the capabilities of Sentinel-2 in regard to the spatial and spectral dimensions are needed to assess its potential and the quality of the expected output. This study presents the first simulation of the high spatial resolution (i.e., 10 m and 20 m) bands of Sentinel-2 for lakeshore mapping, based on the satellite’s Spectral Response Function and hyperspectral airborne data collected over Lake Balaton, Hungary in August 2010. A comparison of supervised classifications of the simulated products is presented and the information loss from spectral aggregation and spatial upscaling in the context of lakeshore vegetation classification is discussed. We conclude that Sentinel-2 imagery has a strong potential for monitoring fine-scale habitats, such as reed beds. PMID:26378538

Real-time contaminant detection and classification in a drinking water pipe using conventional water quality sensors: techniques and experimental results.

PubMed

Jeffrey Yang, Y; Haught, Roy C; Goodrich, James A

2009-06-01

Accurate detection and identification of natural or intentional contamination events in a drinking water pipe is critical to drinking water supply security and health risk management. To use conventional water quality sensors for the purpose, we have explored a real-time event adaptive detection, identification and warning (READiw) methodology and examined it using pilot-scale pipe flow experiments of 11 chemical and biological contaminants each at three concentration levels. The tested contaminants include pesticide and herbicides (aldicarb, glyphosate and dicamba), alkaloids (nicotine and colchicine), E. coli in terrific broth, biological growth media (nutrient broth, terrific broth, tryptic soy broth), and inorganic chemical compounds (mercuric chloride and potassium ferricyanide). First, through adaptive transformation of the sensor outputs, contaminant signals were enhanced and background noise was reduced in time-series plots leading to detection and identification of all simulated contamination events. The improved sensor detection threshold was 0.1% of the background for pH and oxidation-reduction potential (ORP), 0.9% for free chlorine, 1.6% for total chlorine, and 0.9% for chloride. Second, the relative changes calculated from adaptively transformed residual chlorine measurements were quantitatively related to contaminant-chlorine reactivity in drinking water. We have shown that based on these kinetic and chemical differences, the tested contaminants were distinguishable in forensic discrimination diagrams made of adaptively transformed sensor measurements.

Water quality and ecosystem management: Data-driven reality check of effects in streams and lakes

NASA Astrophysics Data System (ADS)

Destouni, Georgia; Fischer, Ida; Prieto, Carmen

2017-08-01

This study investigates nutrient-related water quality conditions and change trends in the first management periods of the EU Water Framework Directive (WFD; since 2009) and Baltic Sea Action Plan (BASP; since 2007). With mitigation of nutrients in inland waters and their discharges to the Baltic Sea being a common WFD and BSAP target, we use Sweden as a case study of observable effects, by compiling and analyzing all openly available water and nutrient monitoring data across Sweden since 2003. The data compilation reveals that nutrient monitoring covers only around 1% (down to 0.2% for nutrient loads) of the total number of WFD-classified stream and lake water bodies in Sweden. The data analysis further shows that the hydro-climatically driven water discharge dominates the determination of waterborne loads of both total phosphorus and total nitrogen across Sweden. Both water discharge and the related nutrient loads are in turn well correlated with the ecosystem status classification of Swedish water bodies. Nutrient concentrations do not exhibit such correlation and their changes over the study period are on average small, but concentration increases are found for moderate-to-bad status waters, for which both the WFD and the BSAP have instead targeted concentration decreases. In general, these results indicate insufficient distinction and mitigation of human-driven nutrient components in inland waters and their discharges to the sea by the internationally harmonized applications of the WFD and the BSAP. The results call for further comparative investigations of observable large-scale effects of such regulatory/management frameworks in different parts of the world.

Classification and Quality Evaluation of Tobacco Leaves Based on Image Processing and Fuzzy Comprehensive Evaluation

PubMed Central

Zhang, Fan; Zhang, Xinhong

2011-01-01

Most of classification, quality evaluation or grading of the flue-cured tobacco leaves are manually operated, which relies on the judgmental experience of experts, and inevitably limited by personal, physical and environmental factors. The classification and the quality evaluation are therefore subjective and experientially based. In this paper, an automatic classification method of tobacco leaves based on the digital image processing and the fuzzy sets theory is presented. A grading system based on image processing techniques was developed for automatically inspecting and grading flue-cured tobacco leaves. This system uses machine vision for the extraction and analysis of color, size, shape and surface texture. Fuzzy comprehensive evaluation provides a high level of confidence in decision making based on the fuzzy logic. The neural network is used to estimate and forecast the membership function of the features of tobacco leaves in the fuzzy sets. The experimental results of the two-level fuzzy comprehensive evaluation (FCE) show that the accuracy rate of classification is about 94% for the trained tobacco leaves, and the accuracy rate of the non-trained tobacco leaves is about 72%. We believe that the fuzzy comprehensive evaluation is a viable way for the automatic classification and quality evaluation of the tobacco leaves. PMID:22163744

Research on evaluating water resource resilience based on projection pursuit classification model

NASA Astrophysics Data System (ADS)

Liu, Dong; Zhao, Dan; Liang, Xu; Wu, Qiuchen

2016-03-01

Water is a fundamental natural resource while agriculture water guarantees the grain output, which shows that the utilization and management of water resource have a significant practical meaning. Regional agricultural water resource system features with unpredictable, self-organization, and non-linear which lays a certain difficulty on the evaluation of regional agriculture water resource resilience. The current research on water resource resilience remains to focus on qualitative analysis and the quantitative analysis is still in the primary stage, thus, according to the above issues, projection pursuit classification model is brought forward. With the help of artificial fish-swarm algorithm (AFSA), it optimizes the projection index function, seeks for the optimal projection direction, and improves AFSA with the application of self-adaptive artificial fish step and crowding factor. Taking Hongxinglong Administration of Heilongjiang as the research base and on the basis of improving AFSA, it established the evaluation of projection pursuit classification model to agriculture water resource system resilience besides the proceeding analysis of projection pursuit classification model on accelerating genetic algorithm. The research shows that the water resource resilience of Hongxinglong is the best than Raohe Farm, and the last 597 Farm. And the further analysis shows that the key driving factors influencing agricultural water resource resilience are precipitation and agriculture water consumption. The research result reveals the restoring situation of the local water resource system, providing foundation for agriculture water resource management.

National Drinking Water Advisory Council Report on the CCL Classification Process

EPA Pesticide Factsheets

Review of the National Research Council (NRC) 2001 report, Classifying Drinking Water Contaminants forRegulatory Consideration by the Contaminant Candidate List (CCL) Classification Process Work Group (the Work Group).

Landsat TM inventory and assessment of waterbird habitat in the southern altiplano of South America

USGS Publications Warehouse

Boyle, T.P.; Caziani, S.M.; Waltermire, R.G.

2004-01-01

The diverse set of wetlands in southern altiplano of South America supports a number of endemic and migratory waterbirds. These species include endangered endemic flamingos and shorebirds that nest in North America and winter in the altiplano. This research developed maps from nine Landsat Thematic Mapper (TM) images (254,300 km2) to provide an inventory of aquatic waterbird habitats. Image processing software was used to produce a map with a classification of wetlands according to the habitat requirements of different types of waterbirds. A hierarchical procedure was used to, first, isolate the bodies of water within the TM image; second, execute an unsupervised classification on the subsetted image to produce 300 signatures of cover types, which were further subdivided as necessary. Third, each of the classifications was examined in the light of field data and personal experience for relevance to the determination of the various habitat types. Finally, the signatures were applied to the entire image and other adjacent images to yield a map depicting the location of the various waterbird habitats in the southern altiplano. The data sets referenced with a global positioning system receiver were used to test the classification system. Multivariate analysis of the bird communities censused at each lake by individual habitats indicated a salinity gradient, and then the depth of the water separated the birds. Multivariate analysis of the chemical and physical data from the lakes showed that the variation in lakes were significantly associated with difference in depth, transparency, latitude, elevation, and pH. The presence of gravel bottoms was also one of the qualities distinguishing a group of lakes. This information will be directly useful to the Flamingo Census Project and serve as an element for risk assessment for future development.

Evaluation of air quality zone classification methods based on ambient air concentration exposure.

PubMed

Freeman, Brian; McBean, Ed; Gharabaghi, Bahram; Thé, Jesse

2017-05-01

Air quality zones are used by regulatory authorities to implement ambient air standards in order to protect human health. Air quality measurements at discrete air monitoring stations are critical tools to determine whether an air quality zone complies with local air quality standards or is noncompliant. This study presents a novel approach for evaluation of air quality zone classification methods by breaking the concentration distribution of a pollutant measured at an air monitoring station into compliance and exceedance probability density functions (PDFs) and then using Monte Carlo analysis with the Central Limit Theorem to estimate long-term exposure. The purpose of this paper is to compare the risk associated with selecting one ambient air classification approach over another by testing the possible exposure an individual living within a zone may face. The chronic daily intake (CDI) is utilized to compare different pollutant exposures over the classification duration of 3 years between two classification methods. Historical data collected from air monitoring stations in Kuwait are used to build representative models of 1-hr NO 2 and 8-hr O 3 within a zone that meets the compliance requirements of each method. The first method, the "3 Strike" method, is a conservative approach based on a winner-take-all approach common with most compliance classification methods, while the second, the 99% Rule method, allows for more robust analyses and incorporates long-term trends. A Monte Carlo analysis is used to model the CDI for each pollutant and each method with the zone at a single station and with multiple stations. The model assumes that the zone is already in compliance with air quality standards over the 3 years under the different classification methodologies. The model shows that while the CDI of the two methods differs by 2.7% over the exposure period for the single station case, the large number of samples taken over the duration period impacts the sensitivity of the statistical tests, causing the null hypothesis to fail. Local air quality managers can use either methodology to classify the compliance of an air zone, but must accept that the 99% Rule method may cause exposures that are statistically more significant than the 3 Strike method. A novel method using the Central Limit Theorem and Monte Carlo analysis is used to directly compare different air standard compliance classification methods by estimating the chronic daily intake of pollutants. This method allows air quality managers to rapidly see how individual classification methods may impact individual population groups, as well as to evaluate different pollutants based on dosage and exposure when complete health impacts are not known.

7 CFR 27.39 - Issuance of classification records.

Code of Federal Regulations, 2014 CFR

2014-01-01

... REGULATIONS COTTON CLASSIFICATION UNDER COTTON FUTURES LEGISLATION Regulations Cotton Class Certificates § 27... practicable after the classification of cotton has been completed by the Cotton and Tobacco Programs, the Quality Assurance Division shall issue an electronic cotton classification record showing the results of...

Random forest wetland classification using ALOS-2 L-band, RADARSAT-2 C-band, and TerraSAR-X imagery

NASA Astrophysics Data System (ADS)

Mahdianpari, Masoud; Salehi, Bahram; Mohammadimanesh, Fariba; Motagh, Mahdi

2017-08-01

Wetlands are important ecosystems around the world, although they are degraded due both to anthropogenic and natural process. Newfoundland is among the richest Canadian province in terms of different wetland classes. Herbaceous wetlands cover extensive areas of the Avalon Peninsula, which are the habitat of a number of animal and plant species. In this study, a novel hierarchical object-based Random Forest (RF) classification approach is proposed for discriminating between different wetland classes in a sub-region located in the north eastern portion of the Avalon Peninsula. Particularly, multi-polarization and multi-frequency SAR data, including X-band TerraSAR-X single polarized (HH), L-band ALOS-2 dual polarized (HH/HV), and C-band RADARSAT-2 fully polarized images, were applied in different classification levels. First, a SAR backscatter analysis of different land cover types was performed by training data and used in Level-I classification to separate water from non-water classes. This was followed by Level-II classification, wherein the water class was further divided into shallow- and deep-water classes, and the non-water class was partitioned into herbaceous and non-herbaceous classes. In Level-III classification, the herbaceous class was further divided into bog, fen, and marsh classes, while the non-herbaceous class was subsequently partitioned into urban, upland, and swamp classes. In Level-II and -III classifications, different polarimetric decomposition approaches, including Cloude-Pottier, Freeman-Durden, Yamaguchi decompositions, and Kennaugh matrix elements were extracted to aid the RF classifier. The overall accuracy and kappa coefficient were determined in each classification level for evaluating the classification results. The importance of input features was also determined using the variable importance obtained by RF. It was found that the Kennaugh matrix elements, Yamaguchi, and Freeman-Durden decompositions were the most important parameters for wetland classification in this study. Using this new hierarchical RF classification approach, an overall accuracy of up to 94% was obtained for classifying different land cover types in the study area.

Classifying environmental pollutants: Part 3. External validation of the classification system.

PubMed

Verhaar, H J; Solbé, J; Speksnijder, J; van Leeuwen, C J; Hermens, J L

2000-04-01

In order to validate a classification system for the prediction of the toxic effect concentrations of organic environmental pollutants to fish, all available fish acute toxicity data were retrieved from the ECETOC database, a database of quality-evaluated aquatic toxicity measurements created and maintained by the European Centre for the Ecotoxicology and Toxicology of Chemicals. The individual chemicals for which these data were available were classified according to the rulebase under consideration and predictions of effect concentrations or ranges of possible effect concentrations were generated. These predictions were compared to the actual toxicity data retrieved from the database. The results of this comparison show that generally, the classification system provides adequate predictions of either the aquatic toxicity (class 1) or the possible range of toxicity (other classes) of organic compounds. A slight underestimation of effect concentrations occurs for some highly water soluble, reactive chemicals with low log K(ow) values. On the other end of the scale, some compounds that are classified as belonging to a relatively toxic class appear to belong to the so-called baseline toxicity compounds. For some of these, additional classification rules are proposed. Furthermore, some groups of compounds cannot be classified, although they should be amenable to predictions. For these compounds additional research as to class membership and associated prediction rules is proposed.

A machine learning approach to multi-level ECG signal quality classification.

PubMed

Li, Qiao; Rajagopalan, Cadathur; Clifford, Gari D

2014-12-01

Current electrocardiogram (ECG) signal quality assessment studies have aimed to provide a two-level classification: clean or noisy. However, clinical usage demands more specific noise level classification for varying applications. This work outlines a five-level ECG signal quality classification algorithm. A total of 13 signal quality metrics were derived from segments of ECG waveforms, which were labeled by experts. A support vector machine (SVM) was trained to perform the classification and tested on a simulated dataset and was validated using data from the MIT-BIH arrhythmia database (MITDB). The simulated training and test datasets were created by selecting clean segments of the ECG in the 2011 PhysioNet/Computing in Cardiology Challenge database, and adding three types of real ECG noise at different signal-to-noise ratio (SNR) levels from the MIT-BIH Noise Stress Test Database (NSTDB). The MITDB was re-annotated for five levels of signal quality. Different combinations of the 13 metrics were trained and tested on the simulated datasets and the best combination that produced the highest classification accuracy was selected and validated on the MITDB. Performance was assessed using classification accuracy (Ac), and a single class overlap accuracy (OAc), which assumes that an individual type classified into an adjacent class is acceptable. An Ac of 80.26% and an OAc of 98.60% on the test set were obtained by selecting 10 metrics while 57.26% (Ac) and 94.23% (OAc) were the numbers for the unseen MITDB validation data without retraining. By performing the fivefold cross validation, an Ac of 88.07±0.32% and OAc of 99.34±0.07% were gained on the validation fold of MITDB. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

77 FR 30087 - Air Quality Designations for the 2008 Ozone National Ambient Air Quality Standards

Federal Register 2010, 2011, 2012, 2013, 2014

2012-05-21

...This rule establishes initial air quality designations for most areas in the United States, including areas of Indian country, for the 2008 primary and secondary national ambient air quality standards (NAAQS) for ozone. The designations for several counties in Illinois, Indiana, and Wisconsin that the EPA is considering for inclusion in the Chicago nonattainment area will be designated in a subsequent action, no later than May 31, 2012. Areas designated as nonattainment are also being classified by operation of law according to the severity of their air quality problems. The classification categories are Marginal, Moderate, Serious, Severe, and Extreme. The EPA is establishing the air quality thresholds that define the classifications in a separate rule that the EPA is signing and publishing in the Federal Register on the same schedule as these designations. In accordance with that separate rule, six nonattainment areas in California are being reclassified to a higher classification.

New insight into defining the lakes of the southern Baltic coastal zone.

PubMed

Cieśliński, Roman; Olszewska, Alicja

2018-01-29

There exist many classification systems of hydrographic entities such as lakes found along the coastlines of seas and oceans. Each system has its advantages and can be used with some success in the area of protection and management. This paper aims to evaluate whether the studied lakes are only coastal lakes or rather bodies of water of a completely different hydrological and hydrochemical nature. The attempt to create a new classification system of Polish coastal lakes is related to the incompleteness of lake information in existing classifications. Thus far, the most frequently used are classifications based solely on lake basin morphogenesis or hydrochemical properties. The classifications in this paper are based not only on the magnitude of lake water salinity or hydrochemical analysis but also on isolation from the Baltic Sea and other sources of water. The key element of the new classification system for coastal bodies of water is a departure from the existing system used to classify lakes in Poland and the introduction of ion-"tracking" methods designed to identify anion and cation distributions in each body of water of interest. As a result of the work, a new classification of lakes of the southern Baltic Sea coastal zone was created. Featured objects such as permanently brackish lakes, brackish lakes that may turn into freshwater lakes from time to time, freshwater lakes that may turn into brackish lakes from time to time, freshwater lakes that experience low levels of salinity due to specific incidents, and permanently freshwater lakes. The authors have adopted 200 mg Cl -  dm -3 as a maximum value of lake water salinity. There are many conditions that determine the membership of a lake to a particular group, but the most important is the isolation lakes from the Baltic Sea. Changing a condition may change the classification of a lake.

Cluster lot quality assurance sampling: effect of increasing the number of clusters on classification precision and operational feasibility.

PubMed

Okayasu, Hiromasa; Brown, Alexandra E; Nzioki, Michael M; Gasasira, Alex N; Takane, Marina; Mkanda, Pascal; Wassilak, Steven G F; Sutter, Roland W

2014-11-01

To assess the quality of supplementary immunization activities (SIAs), the Global Polio Eradication Initiative (GPEI) has used cluster lot quality assurance sampling (C-LQAS) methods since 2009. However, since the inception of C-LQAS, questions have been raised about the optimal balance between operational feasibility and precision of classification of lots to identify areas with low SIA quality that require corrective programmatic action. To determine if an increased precision in classification would result in differential programmatic decision making, we conducted a pilot evaluation in 4 local government areas (LGAs) in Nigeria with an expanded LQAS sample size of 16 clusters (instead of the standard 6 clusters) of 10 subjects each. The results showed greater heterogeneity between clusters than the assumed standard deviation of 10%, ranging from 12% to 23%. Comparing the distribution of 4-outcome classifications obtained from all possible combinations of 6-cluster subsamples to the observed classification of the 16-cluster sample, we obtained an exact match in classification in 56% to 85% of instances. We concluded that the 6-cluster C-LQAS provides acceptable classification precision for programmatic action. Considering the greater resources required to implement an expanded C-LQAS, the improvement in precision was deemed insufficient to warrant the effort. Published by Oxford University Press on behalf of the Infectious Diseases Society of America 2014. This work is written by (a) US Government employee(s) and is in the public domain in the US.

Modeling Study of the Marano and Grado Lagoon (Italy) to Support the Regional Water Protection Plan) TO SUPPORT THE REGIONAL WATER PROTECTION PLAN

NASA Astrophysics Data System (ADS)

Scroccaro, Isabella; Mattassi, Giorgio

2014-05-01

The Water Framework Directive 2000/60/EC (WFD) contemplates the classification of water bodies and establishes the quality objectives of water bodies to achieve a good status within 2015. Further, the Italian law which takes in the WFD with Decree n. 152/2006, allows to identify some water bodies as heavily modified (HMWB). The Regional Administration, involved in the setting up of the Water Protection Plan, according with the above mentioned decree and directive, has to establish specific programs to maintain or conform water quality to the requested quality objectives, also for heavily modified water bodies that have to reach the ecological potential. In the north-eastern part of Italy, in the Friuli Venezia Giulia Region, the Marano and Grado Lagoon is the most complex transitional ecosystem in which four water bodies have been temporarily classified as heavily modified. They are identified as FM1, FM2, FM3 and FM4. In particular, FM2 - "Paludo della Carogna" and FM3 - "Barbana" water bodies seem to be characterized by some confinement since they are delimited by a bridge, called "Ponte Belvedere". The preliminary evaluation of the quality status of FM2 and FM3 water bodies is conditioned by the value of one of the quality criteria: the macrophytes. In fact, macrophytes are represented by very few species in these two water bodies. In a preliminary way the overall judgement of FM2 and FM3 water bodies has been indicated by the experts as scarse. This means that a specific programme of measures has to be proposed to improve the quality status of these water bodies in order to reach the ecological potential. In this context modeling may be used as a scientific and technical tool to support the evaluation on FM2 and FM3 water bodies and the effectiveness of specific measures for the achievement of the quality objectives. Numerical simulations of the Marano and Grado lagoon were performed for hydrodynamic circulation, temperature and salinity behavior with the SHYFEM model, a shallow water finite element model developed at ISMAR-CNR in Venice (Ferrarin et al., 2010) and experimental data were used to calibrate the numerical model. In this study the effectiveness of some proposed measures is investigated with the SHYFEM model, trying to solve the problem of the scarse quality evaluation of FM2 and FM3 in the eastern part of the Marano and Grado lagoon. The proposals are: Modification of the bridge "Ponte Belvedere": the bridge, which divides FM2 and FM3 from the western part of the lagoon, has some openings which are not very large. The proposal is to enlarge these openings on the dam to assess if this action might improve the circulation and consequently the water quality. Excavation of a new channel on the bottom of the lagoon: besides the openings on the dam, it is also possible to hypothetically excavate one or more channels; these are preferential ways for the water to pass in and arrive to the areas in which the circulation has to be increased. This proposal seems to be efficient, with good effects on the inner circulation of the eastern lagoon.

40 CFR 52.171 - Classification of regions.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 3 2014-07-01 2014-07-01 false Classification of regions. 52.171... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS Arkansas § 52.171 Classification of regions. The Arkansas plan was evaluated on the basis of the following classifications: Air quality control...

40 CFR 52.921 - Classification of regions.

Code of Federal Regulations, 2011 CFR

2011-07-01

... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS Kentucky § 52.921 Classification of regions. The Kentucky plan was evaluated on the basis of the following classifications: Air quality control... 40 Protection of Environment 3 2011-07-01 2011-07-01 false Classification of regions. 52.921...

40 CFR 52.371 - Classification of regions.

Code of Federal Regulations, 2011 CFR

2011-07-01

... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS Connecticut § 52.371 Classification of regions. The Connecticut plan was evaluated on the basis of the following classifications: Air quality control... 40 Protection of Environment 3 2011-07-01 2011-07-01 false Classification of regions. 52.371...

40 CFR 52.971 - Classification of regions.

Code of Federal Regulations, 2010 CFR

2010-07-01

... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS Louisiana § 52.971 Classification of regions. The Louisiana plan was evaluated on the basis of the following classifications: Air quality control... 40 Protection of Environment 3 2010-07-01 2010-07-01 false Classification of regions. 52.971...

40 CFR 52.221 - Classification of regions.

Code of Federal Regulations, 2010 CFR

2010-07-01

... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS California § 52.221 Classification of regions. The California plan was evaluated on the basis of the following classifications: Air quality control... 40 Protection of Environment 3 2010-07-01 2010-07-01 false Classification of regions. 52.221...

40 CFR 52.971 - Classification of regions.

Code of Federal Regulations, 2011 CFR

2011-07-01

... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS Louisiana § 52.971 Classification of regions. The Louisiana plan was evaluated on the basis of the following classifications: Air quality control... 40 Protection of Environment 3 2011-07-01 2011-07-01 false Classification of regions. 52.971...

40 CFR 52.221 - Classification of regions.

Code of Federal Regulations, 2011 CFR

2011-07-01

... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS California § 52.221 Classification of regions. The California plan was evaluated on the basis of the following classifications: Air quality control... 40 Protection of Environment 3 2011-07-01 2011-07-01 false Classification of regions. 52.221...

40 CFR 52.171 - Classification of regions.

Code of Federal Regulations, 2011 CFR

2011-07-01

... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS Arkansas § 52.171 Classification of regions. The Arkansas plan was evaluated on the basis of the following classifications: Air quality control... 40 Protection of Environment 3 2011-07-01 2011-07-01 false Classification of regions. 52.171...

40 CFR 52.921 - Classification of regions.

Code of Federal Regulations, 2010 CFR

2010-07-01

... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS Kentucky § 52.921 Classification of regions. The Kentucky plan was evaluated on the basis of the following classifications: Air quality control... 40 Protection of Environment 3 2010-07-01 2010-07-01 false Classification of regions. 52.921...

40 CFR 52.571 - Classification of regions.

Code of Federal Regulations, 2010 CFR

2010-07-01

... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS Georgia> § 52.571 Classification of regions. The Georgia plan was evaluated on the basis of the following classifications: Air quality control... 40 Protection of Environment 3 2010-07-01 2010-07-01 false Classification of regions. 52.571...

40 CFR 52.371 - Classification of regions.

Code of Federal Regulations, 2010 CFR

2010-07-01

... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS Connecticut § 52.371 Classification of regions. The Connecticut plan was evaluated on the basis of the following classifications: Air quality control... 40 Protection of Environment 3 2010-07-01 2010-07-01 false Classification of regions. 52.371...

40 CFR 52.571 - Classification of regions.

Code of Federal Regulations, 2011 CFR

2011-07-01

... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS Georgia> § 52.571 Classification of regions. The Georgia plan was evaluated on the basis of the following classifications: Air quality control... 40 Protection of Environment 3 2011-07-01 2011-07-01 false Classification of regions. 52.571...

40 CFR 52.171 - Classification of regions.

Code of Federal Regulations, 2010 CFR

2010-07-01

... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS Arkansas § 52.171 Classification of regions. The Arkansas plan was evaluated on the basis of the following classifications: Air quality control... 40 Protection of Environment 3 2010-07-01 2010-07-01 false Classification of regions. 52.171...

40 CFR 52.421 - Classification of regions.

Code of Federal Regulations, 2010 CFR

2010-07-01

... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS Delaware § 52.421 Classification of regions. The Delaware plan was evaluated on the basis of the following classifications: Air quality control... 40 Protection of Environment 3 2010-07-01 2010-07-01 false Classification of regions. 52.421...

40 CFR 52.421 - Classification of regions.

Code of Federal Regulations, 2011 CFR

2011-07-01

... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS Delaware § 52.421 Classification of regions. The Delaware plan was evaluated on the basis of the following classifications: Air quality control... 40 Protection of Environment 3 2011-07-01 2011-07-01 false Classification of regions. 52.421...

Symposium on Machine Processing of Remotely Sensed Data, Purdue University, West Lafayette, Ind., June 29-July 1, 1976, Proceedings

NASA Technical Reports Server (NTRS)

1976-01-01

Papers are presented on the applicability of Landsat data to water management and control needs, IBIS, a geographic information system based on digital image processing and image raster datatype, and the Image Data Access Method (IDAM) for the Earth Resources Interactive Processing System. Attention is also given to the Prototype Classification and Mensuration System (PROCAMS) applied to agricultural data, the use of Landsat for water quality monitoring in North Carolina, and the analysis of geophysical remote sensing data using multivariate pattern recognition. The Illinois crop-acreage estimation experiment, the Pacific Northwest Resources Inventory Demonstration, and the effects of spatial misregistration on multispectral recognition are also considered. Individual items are announced in this issue.

A survey of supervised machine learning models for mobile-phone based pathogen identification and classification

NASA Astrophysics Data System (ADS)

Ceylan Koydemir, Hatice; Feng, Steve; Liang, Kyle; Nadkarni, Rohan; Tseng, Derek; Benien, Parul; Ozcan, Aydogan

2017-03-01

Giardia lamblia causes a disease known as giardiasis, which results in diarrhea, abdominal cramps, and bloating. Although conventional pathogen detection methods used in water analysis laboratories offer high sensitivity and specificity, they are time consuming, and need experts to operate bulky equipment and analyze the samples. Here we present a field-portable and cost-effective smartphone-based waterborne pathogen detection platform that can automatically classify Giardia cysts using machine learning. Our platform enables the detection and quantification of Giardia cysts in one hour, including sample collection, labeling, filtration, and automated counting steps. We evaluated the performance of three prototypes using Giardia-spiked water samples from different sources (e.g., reagent-grade, tap, non-potable, and pond water samples). We populated a training database with >30,000 cysts and estimated our detection sensitivity and specificity using 20 different classifier models, including decision trees, nearest neighbor classifiers, support vector machines (SVMs), and ensemble classifiers, and compared their speed of training and classification, as well as predicted accuracies. Among them, cubic SVM, medium Gaussian SVM, and bagged-trees were the most promising classifier types with accuracies of 94.1%, 94.2%, and 95%, respectively; we selected the latter as our preferred classifier for the detection and enumeration of Giardia cysts that are imaged using our mobile-phone fluorescence microscope. Without the need for any experts or microbiologists, this field-portable pathogen detection platform can present a useful tool for water quality monitoring in resource-limited-settings.

A coupled classification - evolutionary optimization model for contamination event detection in water distribution systems.

PubMed

Oliker, Nurit; Ostfeld, Avi

2014-03-15

This study describes a decision support system, alerts for contamination events in water distribution systems. The developed model comprises a weighted support vector machine (SVM) for the detection of outliers, and a following sequence analysis for the classification of contamination events. The contribution of this study is an improvement of contamination events detection ability and a multi-dimensional analysis of the data, differing from the parallel one-dimensional analysis conducted so far. The multivariate analysis examines the relationships between water quality parameters and detects changes in their mutual patterns. The weights of the SVM model accomplish two goals: blurring the difference between sizes of the two classes' data sets (as there are much more normal/regular than event time measurements), and adhering the time factor attribute by a time decay coefficient, ascribing higher importance to recent observations when classifying a time step measurement. All model parameters were determined by data driven optimization so the calibration of the model was completely autonomic. The model was trained and tested on a real water distribution system (WDS) data set with randomly simulated events superimposed on the original measurements. The model is prominent in its ability to detect events that were only partly expressed in the data (i.e., affecting only some of the measured parameters). The model showed high accuracy and better detection ability as compared to previous modeling attempts of contamination event detection. Copyright © 2013 Elsevier Ltd. All rights reserved.

Use of strontium isotopes to identify buried water main leakage into groundwater in a highly urbanized coastal area.

PubMed

Leung, Chi-Man; Jiao, Jiu Jimmy

2006-11-01

Previous studies indicate that the local aquifer systems in the Mid-Levels, a highly urbanized coastal area in Hong Kong, have commonly been affected by leakage from water mains. The identification of leakage locations was done by conventional water quality parameters including major and trace elements. However, these parameters may lead to ambiguous results and fail to identify leakage locations especially where the leakage is from drinking water mains because the chemical composition of drinking water is similar to that of natural groundwater. In this study, natural groundwater, seepage in the developed spaces, leakage from water mains, and parent aquifer materials were measured for strontium isotope (87Sr/86Sr) compositions to explore the feasibility of using these ratios to better constrain the seepage sources. The results show that the 87Sr/86Sr ratios of natural groundwater and leakage from water mains are distinctly different and thus, they can provide additional information on the sources of seepage in developed spaces. A classification system based on the aqueous 87Sr/86Sr ratio is proposed for seepage source identification.

A neural network approach for enhancing information extraction from multispectral image data

USGS Publications Warehouse

Liu, J.; Shao, G.; Zhu, H.; Liu, S.

2005-01-01

A back-propagation artificial neural network (ANN) was applied to classify multispectral remote sensing imagery data. The classification procedure included four steps: (i) noisy training that adds minor random variations to the sampling data to make the data more representative and to reduce the training sample size; (ii) iterative or multi-tier classification that reclassifies the unclassified pixels by making a subset of training samples from the original training set, which means the neural model can focus on fewer classes; (iii) spectral channel selection based on neural network weights that can distinguish the relative importance of each channel in the classification process to simplify the ANN model; and (iv) voting rules that adjust the accuracy of classification and produce outputs of different confidence levels. The Purdue Forest, located west of Purdue University, West Lafayette, Indiana, was chosen as the test site. The 1992 Landsat thematic mapper imagery was used as the input data. High-quality airborne photographs of the same Lime period were used for the ground truth. A total of 11 land use and land cover classes were defined, including water, broadleaved forest, coniferous forest, young forest, urban and road, and six types of cropland-grassland. The experiment, indicated that the back-propagation neural network application was satisfactory in distinguishing different land cover types at US Geological Survey levels II-III. The single-tier classification reached an overall accuracy of 85%. and the multi-tier classification an overall accuracy of 95%. For the whole test, region, the final output of this study reached an overall accuracy of 87%. ?? 2005 CASI.

SENTINEL-1 and SENTINEL-2 Data Fusion for Wetlands Mapping: Balikdami, Turkey

NASA Astrophysics Data System (ADS)

Kaplan, G.; Avdan, U.

2018-04-01

Wetlands provide a number of environmental and socio-economic benefits such as their ability to store floodwaters and improve water quality, providing habitats for wildlife and supporting biodiversity, as well as aesthetic values. Remote sensing technology has proven to be a useful and frequent application in monitoring and mapping wetlands. Combining optical and microwave satellite data can help with mapping and monitoring the biophysical characteristics of wetlands and wetlands` vegetation. Also, fusing radar and optical remote sensing data can increase the wetland classification accuracy. In this paper, data from the fine spatial resolution optical satellite, Sentinel-2 and the Synthetic Aperture Radar Satellite, Sentinel-1, were fused for mapping wetlands. Both Sentinel-1 and Sentinel-2 images were pre-processed. After the pre-processing, vegetation indices were calculated using the Sentinel-2 bands and the results were included in the fusion data set. For the classification of the fused data, three different classification approaches were used and compared. The results showed significant improvement in the wetland classification using both multispectral and microwave data. Also, the presence of the red edge bands and the vegetation indices used in the data set showed significant improvement in the discrimination between wetlands and other vegetated areas. The statistical results of the fusion of the optical and radar data showed high wetland mapping accuracy, showing an overall classification accuracy of approximately 90 % in the object-based classification method. For future research, we recommend multi-temporal image use, terrain data collection, as well as a comparison of the used method with the traditional image fusion techniques.

Comparison of the availability of groundwater information sources in Poland with other European countries. Knowledge inventory for hydrogeology research - project KINDRA

NASA Astrophysics Data System (ADS)

Tomaszewska, Barbara; Dendys, Marta; Tyszer, Magdalena

2017-11-01

Regulations of the Water Framework Directive 200/60/EC (WFD) had been applied by European Union countries into their legislation system. However, it does not guarantee that the groundwater research has the same standard and quality in EU countries. KINDRA international research project was launched to assessment of existing groundwater-related practical and scientific knowledge based on a new Hydrogeological Research Classification System (HRC-SYS). This classification is supported by a web-service - the European Inventory of Groundwater Research (EIGR). The main goal of the project is implementation policy of optimization in groundwater research in EU. The preliminary result of survey about groundwater management shows that in Poland is a good state of implementation WFD. Good level of implementation is especially related with groundwater monitoring. It is because a lot of institutions and municipal entities carry out their tasks referring to quality or quantity assessment. Results of their works are published as reports, newsletters, maps, bulletins etc. These materials are potential source of information which can be a valuable contribution to EIGR. However, a lot of information are published only in polish language, so it is impossible to spread this knowledge in Europe.

[Tobacco quality analysis of industrial classification of different producing area using near-infrared (NIR) spectrum].

PubMed

Wang, Yi; Ma, Xiang; Wen, Ya-Dong; Yu, Chun-Xia; Wang, Luo-Ping; Zhao, Long-Lian; Li, Jun-Hui

2012-10-01

In this study, tobacco quality analysis of industrial classification of different producing area was carried out applying spectrum projection and correlation methods. The group of industrial classification data was near-infrared (NIR) spectrum in 2010 year from different tobacco plant parts and colors of Hongta Tobacco (Group) Co., Ltd. 6 064 tobacco leaf samples of 17 classes from Yuxi, Chuxiong and Zhaotong, in Yunnan province and 6 industrial classifications were collected using near infrared spectroscopy, which from different parts and colors and all belong to tobacco varieties of K326. The conclusion showed that, the probability of the grading belonging by the first dimension was 84%, the probability of the producing area belonging by the second dimension was 71%. The study can explain the difference of tobacco quality of industrial classification and producing area by a projection method to get the quantitative similarity values. The quantitative similarity values were instructive in combination of tobacco leaf blending.

Multilingual Twitter Sentiment Classification: The Role of Human Annotators

PubMed Central

Mozetič, Igor; Grčar, Miha; Smailović, Jasmina

2016-01-01

What are the limits of automated Twitter sentiment classification? We analyze a large set of manually labeled tweets in different languages, use them as training data, and construct automated classification models. It turns out that the quality of classification models depends much more on the quality and size of training data than on the type of the model trained. Experimental results indicate that there is no statistically significant difference between the performance of the top classification models. We quantify the quality of training data by applying various annotator agreement measures, and identify the weakest points of different datasets. We show that the model performance approaches the inter-annotator agreement when the size of the training set is sufficiently large. However, it is crucial to regularly monitor the self- and inter-annotator agreements since this improves the training datasets and consequently the model performance. Finally, we show that there is strong evidence that humans perceive the sentiment classes (negative, neutral, and positive) as ordered. PMID:27149621

A fingerprint classification algorithm based on combination of local and global information

NASA Astrophysics Data System (ADS)

Liu, Chongjin; Fu, Xiang; Bian, Junjie; Feng, Jufu

2011-12-01

Fingerprint recognition is one of the most important technologies in biometric identification and has been wildly applied in commercial and forensic areas. Fingerprint classification, as the fundamental procedure in fingerprint recognition, can sharply decrease the quantity for fingerprint matching and improve the efficiency of fingerprint recognition. Most fingerprint classification algorithms are based on the number and position of singular points. Because the singular points detecting method only considers the local information commonly, the classification algorithms are sensitive to noise. In this paper, we propose a novel fingerprint classification algorithm combining the local and global information of fingerprint. Firstly we use local information to detect singular points and measure their quality considering orientation structure and image texture in adjacent areas. Furthermore the global orientation model is adopted to measure the reliability of singular points group. Finally the local quality and global reliability is weighted to classify fingerprint. Experiments demonstrate the accuracy and effectivity of our algorithm especially for the poor quality fingerprint images.

Computational approaches for the classification of seed storage proteins.

PubMed

Radhika, V; Rao, V Sree Hari

2015-07-01

Seed storage proteins comprise a major part of the protein content of the seed and have an important role on the quality of the seed. These storage proteins are important because they determine the total protein content and have an effect on the nutritional quality and functional properties for food processing. Transgenic plants are being used to develop improved lines for incorporation into plant breeding programs and the nutrient composition of seeds is a major target of molecular breeding programs. Hence, classification of these proteins is crucial for the development of superior varieties with improved nutritional quality. In this study we have applied machine learning algorithms for classification of seed storage proteins. We have presented an algorithm based on nearest neighbor approach for classification of seed storage proteins and compared its performance with decision tree J48, multilayer perceptron neural (MLP) network and support vector machine (SVM) libSVM. The model based on our algorithm has been able to give higher classification accuracy in comparison to the other methods.

Probability-based nitrate contamination map of groundwater in Kinmen.

PubMed

Liu, Chen-Wuing; Wang, Yeuh-Bin; Jang, Cheng-Shin

2013-12-01

Groundwater supplies over 50% of drinking water in Kinmen. Approximately 16.8% of groundwater samples in Kinmen exceed the drinking water quality standard (DWQS) of NO3 (-)-N (10 mg/L). The residents drinking high nitrate-polluted groundwater pose a potential risk to health. To formulate effective water quality management plan and assure a safe drinking water in Kinmen, the detailed spatial distribution of nitrate-N in groundwater is a prerequisite. The aim of this study is to develop an efficient scheme for evaluating spatial distribution of nitrate-N in residential well water using logistic regression (LR) model. A probability-based nitrate-N contamination map in Kinmen is constructed. The LR model predicted the binary occurrence probability of groundwater nitrate-N concentrations exceeding DWQS by simple measurement variables as independent variables, including sampling season, soil type, water table depth, pH, EC, DO, and Eh. The analyzed results reveal that three statistically significant explanatory variables, soil type, pH, and EC, are selected for the forward stepwise LR analysis. The total ratio of correct classification reaches 92.7%. The highest probability of nitrate-N contamination map presents in the central zone, indicating that groundwater in the central zone should not be used for drinking purposes. Furthermore, a handy EC-pH-probability curve of nitrate-N exceeding the threshold of DWQS was developed. This curve can be used for preliminary screening of nitrate-N contamination in Kinmen groundwater. This study recommended that the local agency should implement the best management practice strategies to control nonpoint nitrogen sources and carry out a systematic monitoring of groundwater quality in residential wells of the high nitrate-N contamination zones.

Reflecting on the structure of soil classification systems: insights from a proposal for integrating subsoil data into soil information systems

NASA Astrophysics Data System (ADS)

Dondeyne, Stefaan; Juilleret, Jérôme; Vancampenhout, Karen; Deckers, Jozef; Hissler, Christophe

2017-04-01

Classification of soils in both World Reference Base for soil resources (WRB) and Soil Taxonomy hinges on the identification of diagnostic horizons and characteristics. However as these features often occur within the first 100 cm, these classification systems convey little information on subsoil characteristics. An integrated knowledge of the soil, soil-to-substratum and deeper substratum continuum is required when dealing with environmental issues such as vegetation ecology, water quality or the Critical Zone in general. Therefore, we recently proposed a classification system of the subsolum complementing current soil classification systems. By reflecting on the structure of the subsoil classification system which is inspired by WRB, we aim at fostering a discussion on some potential future developments of WRB. For classifying the subsolum we define Regolite, Saprolite, Saprock and Bedrock as four Subsolum Reference Groups each corresponding to different weathering stages of the subsoil. Principal qualifiers can be used to categorize intergrades of these Subsoil Reference Groups while morphologic and lithologic characteristics can be presented with supplementary qualifiers. We argue that adopting a low hierarchical structure - akin to WRB and in contrast to a strong hierarchical structure as in Soil Taxonomy - offers the advantage of having an open classification system avoiding the need for a priori knowledge of all possible combinations which may be encountered in the field. Just as in WRB we also propose to use principal and supplementary qualifiers as a second level of classification. However, in contrast to WRB we propose to reserve the principal qualifiers for intergrades and to regroup the supplementary qualifiers into thematic categories (morphologic or lithologic). Structuring the qualifiers in this manner should facilitate the integration and handling of both soil and subsoil classification units into soil information systems and calls for paying attention to these structural issues in future developments of WRB.

Quality of water in the fractured-bedrock aquifer of New Hampshire

USGS Publications Warehouse

Moore, Richard Bridge

2004-01-01

Over the past few decades, New Hampshire has experienced considerable population growth, which is forcing some communities to look for alternative public and private water supplies in the bedrock aquifer. Because the quality of water from the aquifer can vary, the U.S. Geological Survey statistically analyzed well data from 1,353 domestic and 360 public-supply bedrock wells to characterize the ground water. The domestic-well data were from homeowner-collected samples analyzed by the New Hampshire Department of Environmental Services (NHDES) Environmental Laboratory from 1984 to 1994. Bedrock water in New Hampshire often contains high concentrations of iron, manganese, arsenic, and radon gas. Water samples from 21 percent of the domestic bedrock wells contained arsenic above the U.S. Environmental Protection Agency (USEPA) 10 micrograms per liter (?g/L) drinking-water standard for public-water supplies, and 96 percent had radon concentrations greater than the USEPA-proposed 300 picocurie per liter (pCi/L) standard for public-water supplies. Some elevated fluoride concentrations (2 percent of samples) were above the 4 milligrams per liter (mg/L) USEPA drinking-water standard for public-water supplies. Water from the bedrock aquifer also typically is soft to moderately hard, and has a pH greater than 7.0. Variations in bedrock water quality were discernable when the data were compared to lithochemical groupings of the bedrock, indicating that the type of bedrock has an effect on the quality of water in the bedrock aquifer of New Hampshire. Ground-water samples from the metasedimentary lithochemical group have greater concentrations of total iron and total manganese than do the felsic and mafic igneous lithochemical groups. Ground-water samples from the felsic igneous group have higher concentrations of total fluoride than do those from the other lithochemical groups. For arsenic, the calcareous metasedimentary group was identified, using the public-supply database, as having higher concentrations, on average, than the other lithochemical groups. The use of a radon-gas-potential classification of bedrock in the State indicated where high radon concentrations in the air and in water from private and public-supply wells were more likely to occur. In general, samples from the bedrock aquifer tend to have higher pH (are less acidic), greater hardness, much higher concentrations of iron, similar concentrations of manganese, and higher concentrations of fluoride and arsenic than do samples from stratified-drift aquifers in New Hampshire. An understanding of the water-quality conditions of water in bedrock aquifers is important from a public-health perspective because an increasing number of domestic bedrock wells are being drilled and relied upon as a source of drinking water in the State.

Nonlinear Classification of AVO Attributes Using SVM

NASA Astrophysics Data System (ADS)

Zhao, B.; Zhou, H.

2005-05-01

A key research topic in reservoir characterization is the detection of the presence of fluids using seismic and well-log data. In particular, partial gas discrimination is very challenging because low and high gas saturation can result in similar anomalies in terms of Amplitude Variation with Offset (AVO), bright spot, and velocity sag. Hence, a successful fluid detection will require a good understanding of the seismic signatures of the fluids, high-quality data, and good detection methodology. Traditional attempts of partial gas discrimination employ the Neural Network algorithm. A new approach is to use the Support Vector Machine (SVM) (Vapnik, 1995; Liu and Sacchi, 2003). While the potential of the SVM has not been fully explored for reservoir fluid detection, the current nonlinear methods classify seismic attributes without the use of rock physics constraints. The objective of this study is to improve the capability of distinguishing a fizz-water reservoir from a commercial gas reservoir by developing a new detection method using AVO attributes and rock physics constraints. This study will first test the SVM classification with synthetic data, and then apply the algorithm to field data from the King-Kong and Lisa-Anne fields in Gulf of Mexico. While both field areas have high amplitude seismic anomalies, King-Kong field produces commercial gas but Lisa-Anne field does not. We expect that the new SVM-based nonlinear classification of AVO attributes may be able to separate commercial gas from fizz-water in these two fields.

40 CFR 52.71 - Classification of regions.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 3 2013-07-01 2013-07-01 false Classification of regions. 52.71... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS Alaska § 52.71 Classification of regions. The Alaska plan was evaluated on the basis of the following classifications: Air quality control Region...

40 CFR 52.51 - Classification of regions.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 3 2014-07-01 2014-07-01 false Classification of regions. 52.51... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS Alabama § 52.51 Classification of regions. The Alabama plan was evaluated on the basis of the following classifications: Air quality control region...

40 CFR 52.71 - Classification of regions.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 3 2014-07-01 2014-07-01 false Classification of regions. 52.71... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS Alaska § 52.71 Classification of regions. The Alaska plan was evaluated on the basis of the following classifications: Air quality control Region...

40 CFR 52.51 - Classification of regions.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 3 2013-07-01 2013-07-01 false Classification of regions. 52.51... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS Alabama § 52.51 Classification of regions. The Alabama plan was evaluated on the basis of the following classifications: Air quality control region...

40 CFR 52.1471 - Classification of regions.

Code of Federal Regulations, 2010 CFR

2010-07-01

... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS (CONTINUED) Nevada § 52.1471 Classification of regions. The Nevada plan is evaluated on the basis of the following classifications: Air quality control... 40 Protection of Environment 4 2010-07-01 2010-07-01 false Classification of regions. 52.1471...

40 CFR 52.51 - Classification of regions.

Code of Federal Regulations, 2011 CFR

2011-07-01

... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS Alabama § 52.51 Classification of regions. The Alabama plan was evaluated on the basis of the following classifications: Air quality control region... 40 Protection of Environment 3 2011-07-01 2011-07-01 false Classification of regions. 52.51...

40 CFR 52.671 - Classification of regions.

Code of Federal Regulations, 2011 CFR

2011-07-01

... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS Idaho § 52.671 Classification of regions. The Idaho plan was evaluated on the basis of the following classifications: Air quality control region... 40 Protection of Environment 3 2011-07-01 2011-07-01 false Classification of regions. 52.671...

40 CFR 52.871 - Classification of regions.

Code of Federal Regulations, 2010 CFR

2010-07-01

... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS Kansas § 52.871 Classification of regions. The Kansas plan was evaluated on the basis of the following classifications: Air quality control region... 40 Protection of Environment 3 2010-07-01 2010-07-01 false Classification of regions. 52.871...

40 CFR 52.2371 - Classification of regions.

Code of Federal Regulations, 2011 CFR

2011-07-01

... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS (CONTINUED) Vermont § 52.2371 Classification of regions. The Vermont plan was evaluated on the basis of the following classifications: Air quality control... 40 Protection of Environment 4 2011-07-01 2011-07-01 false Classification of regions. 52.2371...

40 CFR 52.1971 - Classification of regions.

Code of Federal Regulations, 2011 CFR

2011-07-01

... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS (CONTINUED) Oregon § 52.1971 Classification of regions. The Oregon plan was evaluated on the basis of the following classifications: Air quality control... 40 Protection of Environment 4 2011-07-01 2011-07-01 false Classification of regions. 52.1971...

40 CFR 52.671 - Classification of regions.

Code of Federal Regulations, 2010 CFR

2010-07-01

... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS Idaho § 52.671 Classification of regions. The Idaho plan was evaluated on the basis of the following classifications: Air quality control region... 40 Protection of Environment 3 2010-07-01 2010-07-01 false Classification of regions. 52.671...

40 CFR 52.2671 - Classification of regions.

Code of Federal Regulations, 2010 CFR

2010-07-01

... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS (CONTINUED) Guam § 52.2671 Classification of regions. The Guam plan was evaluated on the basis of the following classifications. Air quality control... 40 Protection of Environment 4 2010-07-01 2010-07-01 false Classification of regions. 52.2671...

40 CFR 52.2621 - Classification of regions.

Code of Federal Regulations, 2011 CFR

2011-07-01

... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS (CONTINUED) Wyoming § 52.2621 Classification of regions. The Wyoming plan was evaluated on the basis of the following classifications: Air quality control... 40 Protection of Environment 4 2011-07-01 2011-07-01 false Classification of regions. 52.2621...

40 CFR 52.821 - Classification of regions.

Code of Federal Regulations, 2010 CFR

2010-07-01

... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS Iowa § 52.821 Classification of regions. The Iowa plan was evaluated on the basis of the following classification: Air quality control region... 40 Protection of Environment 3 2010-07-01 2010-07-01 false Classification of regions. 52.821...

40 CFR 52.771 - Classification of regions.

Code of Federal Regulations, 2011 CFR

2011-07-01

... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS Indiana § 52.771 Classification of regions. (a) The Indiana plan was evaluated on the basis of the following classifications: Air quality control... 40 Protection of Environment 3 2011-07-01 2011-07-01 false Classification of regions. 52.771...

40 CFR 52.2771 - Classification of regions.

Code of Federal Regulations, 2011 CFR

2011-07-01

... Classification of regions. The U.S. Virgin Islands plan was evaluated on the basis of the following classifications: Air quality control region Pollutant Particulate matter Sulfur oxides Nitrogen dioxide Carbon... 40 Protection of Environment 4 2011-07-01 2011-07-01 false Classification of regions. 52.2771...

40 CFR 52.2671 - Classification of regions.

Code of Federal Regulations, 2011 CFR

2011-07-01

... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS (CONTINUED) Guam § 52.2671 Classification of regions. The Guam plan was evaluated on the basis of the following classifications. Air quality control... 40 Protection of Environment 4 2011-07-01 2011-07-01 false Classification of regions. 52.2671...

40 CFR 52.621 - Classification of regions.

Code of Federal Regulations, 2011 CFR

2011-07-01

... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS Hawaii § 52.621 Classification of regions. The Hawaii plan was evaluated on the basis of the following classifications: Air quality control region... 40 Protection of Environment 3 2011-07-01 2011-07-01 false Classification of regions. 52.621...

40 CFR 52.2321 - Classification of regions.

Code of Federal Regulations, 2010 CFR

2010-07-01

... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS (CONTINUED) Utah § 52.2321 Classification of regions. The Utah plan was evaluated on the basis of the following classifications: Air quality control... 40 Protection of Environment 4 2010-07-01 2010-07-01 false Classification of regions. 52.2321...

40 CFR 52.2321 - Classification of regions.

Code of Federal Regulations, 2011 CFR

2011-07-01

... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS (CONTINUED) Utah § 52.2321 Classification of regions. The Utah plan was evaluated on the basis of the following classifications: Air quality control... 40 Protection of Environment 4 2011-07-01 2011-07-01 false Classification of regions. 52.2321...

40 CFR 52.1871 - Classification of regions.

Code of Federal Regulations, 2011 CFR

2011-07-01

... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS (CONTINUED) Ohio § 52.1871 Classification of regions. The Ohio plan was evaluated on the basis of the following classifications: Air quality control... 40 Protection of Environment 4 2011-07-01 2011-07-01 false Classification of regions. 52.1871...

40 CFR 52.2371 - Classification of regions.

Code of Federal Regulations, 2010 CFR

2010-07-01

... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS (CONTINUED) Vermont § 52.2371 Classification of regions. The Vermont plan was evaluated on the basis of the following classifications: Air quality control... 40 Protection of Environment 4 2010-07-01 2010-07-01 false Classification of regions. 52.2371...

40 CFR 52.2271 - Classification of regions.

Code of Federal Regulations, 2011 CFR

2011-07-01

... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS (CONTINUED) Texas § 52.2271 Classification of regions. (a) The Texas plan was evaluated on the basis of the following classifications: Air quality... 40 Protection of Environment 4 2011-07-01 2011-07-01 false Classification of regions. 52.2271...

40 CFR 52.2771 - Classification of regions.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Classification of regions. The U.S. Virgin Islands plan was evaluated on the basis of the following classifications: Air quality control region Pollutant Particulate matter Sulfur oxides Nitrogen dioxide Carbon... 40 Protection of Environment 4 2010-07-01 2010-07-01 false Classification of regions. 52.2771...

40 CFR 52.821 - Classification of regions.

Code of Federal Regulations, 2011 CFR

2011-07-01

... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS Iowa § 52.821 Classification of regions. The Iowa plan was evaluated on the basis of the following classification: Air quality control region... 40 Protection of Environment 3 2011-07-01 2011-07-01 false Classification of regions. 52.821...

40 CFR 52.771 - Classification of regions.

Code of Federal Regulations, 2010 CFR

2010-07-01

... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS Indiana § 52.771 Classification of regions. (a) The Indiana plan was evaluated on the basis of the following classifications: Air quality control... 40 Protection of Environment 3 2010-07-01 2010-07-01 false Classification of regions. 52.771...

40 CFR 52.2621 - Classification of regions.

Code of Federal Regulations, 2010 CFR

2010-07-01

... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS (CONTINUED) Wyoming § 52.2621 Classification of regions. The Wyoming plan was evaluated on the basis of the following classifications: Air quality control... 40 Protection of Environment 4 2010-07-01 2010-07-01 false Classification of regions. 52.2621...

40 CFR 52.521 - Classification of regions.

Code of Federal Regulations, 2011 CFR

2011-07-01

... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS Florida § 52.521 Classification of regions. The Florida plan was evaluated on the basis of the following classifications: Air quality control region... 40 Protection of Environment 3 2011-07-01 2011-07-01 false Classification of regions. 52.521...

40 CFR 52.2271 - Classification of regions.

Code of Federal Regulations, 2010 CFR

2010-07-01

... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS (CONTINUED) Texas § 52.2271 Classification of regions. (a) The Texas plan was evaluated on the basis of the following classifications: Air quality... 40 Protection of Environment 4 2010-07-01 2010-07-01 false Classification of regions. 52.2271...

40 CFR 52.71 - Classification of regions.

Code of Federal Regulations, 2010 CFR

2010-07-01

... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS Alaska § 52.71 Classification of regions. The Alaska plan was evaluated on the basis of the following classifications: Air quality control Region... 40 Protection of Environment 3 2010-07-01 2010-07-01 false Classification of regions. 52.71...

40 CFR 52.1471 - Classification of regions.

Code of Federal Regulations, 2011 CFR

2011-07-01

... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS (CONTINUED) Nevada § 52.1471 Classification of regions. The Nevada plan is evaluated on the basis of the following classifications: Air quality control... 40 Protection of Environment 4 2011-07-01 2011-07-01 false Classification of regions. 52.1471...

40 CFR 52.1971 - Classification of regions.

Code of Federal Regulations, 2010 CFR

2010-07-01

... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS (CONTINUED) Oregon § 52.1971 Classification of regions. The Oregon plan was evaluated on the basis of the following classifications: Air quality control... 40 Protection of Environment 4 2010-07-01 2010-07-01 false Classification of regions. 52.1971...

40 CFR 52.521 - Classification of regions.

Code of Federal Regulations, 2010 CFR

2010-07-01

... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS Florida § 52.521 Classification of regions. The Florida plan was evaluated on the basis of the following classifications: Air quality control region... 40 Protection of Environment 3 2010-07-01 2010-07-01 false Classification of regions. 52.521...

40 CFR 52.871 - Classification of regions.

Code of Federal Regulations, 2011 CFR

2011-07-01

... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS Kansas § 52.871 Classification of regions. The Kansas plan was evaluated on the basis of the following classifications: Air quality control region... 40 Protection of Environment 3 2011-07-01 2011-07-01 false Classification of regions. 52.871...

40 CFR 52.71 - Classification of regions.

Code of Federal Regulations, 2011 CFR

2011-07-01

... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS Alaska § 52.71 Classification of regions. The Alaska plan was evaluated on the basis of the following classifications: Air quality control Region... 40 Protection of Environment 3 2011-07-01 2011-07-01 false Classification of regions. 52.71...

A proposed classification scheme for Ada-based software products

NASA Technical Reports Server (NTRS)

Cernosek, Gary J.

1986-01-01

As the requirements for producing software in the Ada language become a reality for projects such as the Space Station, a great amount of Ada-based program code will begin to emerge. Recognizing the potential for varying levels of quality to result in Ada programs, what is needed is a classification scheme that describes the quality of a software product whose source code exists in Ada form. A 5-level classification scheme is proposed that attempts to decompose this potentially broad spectrum of quality which Ada programs may possess. The number of classes and their corresponding names are not as important as the mere fact that there needs to be some set of criteria from which to evaluate programs existing in Ada. An exact criteria for each class is not presented, nor are any detailed suggestions of how to effectively implement this quality assessment. The idea of Ada-based software classification is introduced and a set of requirements from which to base further research and development is suggested.

Design and Reproducibility of a Mini-Survey to Evaluate the Quality of Food Intake (Mini-ECCA) in a Mexican Population

PubMed Central

González-Gómez, Montserrat; Orozco-Gutiérrez, Jaime Fernando; Prado-Arriaga, Ruth Jackelyne; Márquez-Sandoval, Fabiola; Altamirano-Martínez, Martha Betzaida

2018-01-01

Evaluating food intake quality may contribute to the development of nutrition programs. In Mexico, there are no screening tools that can be administered quickly for the evaluation of this variable. The aim was to determine the reproducibility of a mini-survey designed to evaluate the quality of food intake (Mini-ECCA) in a Mexican population. Mini-ECCA consists of 12 questions that are based on Mexican and international recommendations for food and non-alcoholic beverage intake, with the support of photographs for food quantity estimation. Each question scores as 0 (unhealthy) or 1 (healthy), and the final score undergoes a classification procedure. Through the framework of a nutritional study, 152 employees of the municipal water company in Guadalajara, Mexico (April–August 2016), were invited to participate. The survey was administered in two rounds (test and retest) with a 15-day interval between them. We calculated the Spearman correlation coefficient, the intra-class correlation coefficient (ICC), and weighted kappa for score classification agreement (SPSS versus 14 p < 0.05 was considered statistically significant). The survey obtained a “good” reproducibility (ρ = 0.713, p < 0.001), and an excellent concordance (ICC = 0.841 Confidence Interval 95% 0.779, 0.885). It can thus be said that the Mini-ECCA displayed acceptable reproducibility and is suitable for the purpose of dietary assessment and guidance. PMID:29690618

Design and Reproducibility of a Mini-Survey to Evaluate the Quality of Food Intake (Mini-ECCA) in a Mexican Population.

PubMed

Bernal-Orozco, María Fernanda; Badillo-Camacho, Nayeli; Macedo-Ojeda, Gabriela; González-Gómez, Montserrat; Orozco-Gutiérrez, Jaime Fernando; Prado-Arriaga, Ruth Jackelyne; Márquez-Sandoval, Fabiola; Altamirano-Martínez, Martha Betzaida; Vizmanos, Barbara

2018-04-23

Evaluating food intake quality may contribute to the development of nutrition programs. In Mexico, there are no screening tools that can be administered quickly for the evaluation of this variable. The aim was to determine the reproducibility of a mini-survey designed to evaluate the quality of food intake (Mini-ECCA) in a Mexican population. Mini-ECCA consists of 12 questions that are based on Mexican and international recommendations for food and non-alcoholic beverage intake, with the support of photographs for food quantity estimation. Each question scores as 0 (unhealthy) or 1 (healthy), and the final score undergoes a classification procedure. Through the framework of a nutritional study, 152 employees of the municipal water company in Guadalajara, Mexico (April⁻August 2016), were invited to participate. The survey was administered in two rounds (test and retest) with a 15-day interval between them. We calculated the Spearman correlation coefficient, the intra-class correlation coefficient (ICC), and weighted kappa for score classification agreement (SPSS versus 14 p < 0.05 was considered statistically significant). The survey obtained a “good” reproducibility (ρ = 0.713, p < 0.001), and an excellent concordance (ICC = 0.841 Confidence Interval 95% 0.779, 0.885). It can thus be said that the Mini-ECCA displayed acceptable reproducibility and is suitable for the purpose of dietary assessment and guidance.

Methods for assessing the quality of mammalian embryos: How far we are from the gold standard?

PubMed

Rocha, José C; Passalia, Felipe; Matos, Felipe D; Maserati, Marc P; Alves, Mayra F; Almeida, Tamie G de; Cardoso, Bruna L; Basso, Andrea C; Nogueira, Marcelo F G

2016-08-01

Morphological embryo classification is of great importance for many laboratory techniques, from basic research to the ones applied to assisted reproductive technology. However, the standard classification method for both human and cattle embryos, is based on quality parameters that reflect the overall morphological quality of the embryo in cattle, or the quality of the individual embryonic structures, more relevant in human embryo classification. This assessment method is biased by the subjectivity of the evaluator and even though several guidelines exist to standardize the classification, it is not a method capable of giving reliable and trustworthy results. Latest approaches for the improvement of quality assessment include the use of data from cellular metabolism, a new morphological grading system, development kinetics and cleavage symmetry, embryo cell biopsy followed by pre-implantation genetic diagnosis, zona pellucida birefringence, ion release by the embryo cells and so forth. Nowadays there exists a great need for evaluation methods that are practical and non-invasive while being accurate and objective. A method along these lines would be of great importance to embryo evaluation by embryologists, clinicians and other professionals who work with assisted reproductive technology. Several techniques shows promising results in this sense, one being the use of digital images of the embryo as basis for features extraction and classification by means of artificial intelligence techniques (as genetic algorithms and artificial neural networks). This process has the potential to become an accurate and objective standard for embryo quality assessment.

Methods for assessing the quality of mammalian embryos: How far we are from the gold standard?

PubMed Central

Rocha, José C.; Passalia, Felipe; Matos, Felipe D.; Maserati Jr, Marc P.; Alves, Mayra F.; de Almeida, Tamie G.; Cardoso, Bruna L.; Basso, Andrea C.; Nogueira, Marcelo F. G.

2016-01-01

Morphological embryo classification is of great importance for many laboratory techniques, from basic research to the ones applied to assisted reproductive technology. However, the standard classification method for both human and cattle embryos, is based on quality parameters that reflect the overall morphological quality of the embryo in cattle, or the quality of the individual embryonic structures, more relevant in human embryo classification. This assessment method is biased by the subjectivity of the evaluator and even though several guidelines exist to standardize the classification, it is not a method capable of giving reliable and trustworthy results. Latest approaches for the improvement of quality assessment include the use of data from cellular metabolism, a new morphological grading system, development kinetics and cleavage symmetry, embryo cell biopsy followed by pre-implantation genetic diagnosis, zona pellucida birefringence, ion release by the embryo cells and so forth. Nowadays there exists a great need for evaluation methods that are practical and non-invasive while being accurate and objective. A method along these lines would be of great importance to embryo evaluation by embryologists, clinicians and other professionals who work with assisted reproductive technology. Several techniques shows promising results in this sense, one being the use of digital images of the embryo as basis for features extraction and classification by means of artificial intelligence techniques (as genetic algorithms and artificial neural networks). This process has the potential to become an accurate and objective standard for embryo quality assessment. PMID:27584609

Land Use Patterns and Fecal Contamination of Coastal Waters in Western Puerto Rico

NASA Technical Reports Server (NTRS)

Norat, Jose

1994-01-01

The Department of Environmental Health of the Graduate School of Public Health of the Medical Sciences Campus, University of Puerto Rico (UPR-RCM) conducted this research project on how different patterns of land use affect the microbiological quality of rivers flowing into Mayaguez Bay in Western Puerto Rico. Coastal shellfish growing areas, stream and ocean bathing beaches, and pristine marine sites in the Bay are affected by the discharge of the three study rivers. Satellite imagery was used to study watershed land uses which serve as point and nonpoint sources of pathogens affecting stream and coastal water users. The study rivers drain watersheds of different size and type of human activity (including different human waste treatment and disposal facilities). Land use and land cover in the study watersheds were interpreted, classified and mapped using remotely sensed images from NASA's Landsat Thematic Mapper (TM). This study found there is a significant relationship between watershed land cover and microbiological water quality of rivers flowing into Mayaguez Bay in Western Puerto Rico. Land covers in the Guanajibo, Anasco, and Yaguez watersheds were classified into forested areas, pastures, agricultural zones and urban areas so as to determine relative contributions to fecal water contamination. The land cover classification was made processing TM images with IDRISI and ERDAS software.

Classification of river water pollution using Hyperion data

NASA Astrophysics Data System (ADS)

Kar, Soumyashree; Rathore, V. S.; Champati ray, P. K.; Sharma, Richa; Swain, S. K.

2016-06-01

A novel attempt is made to use hyperspectral remote sensing to identify the spatial variability of metal pollutants present in river water. It was also attempted to classify the hyperspectral image - Earth Observation-1 (EO-1) Hyperion data of an 8 km stretch of the river Yamuna, near Allahabad city in India depending on its chemical composition. For validating image analysis results, a total of 10 water samples were collected and chemically analyzed using Inductively Coupled Plasma-Optical Emission Spectroscopy (ICP-OES). Two different spectral libraries from field and image data were generated for the 10 sample locations. Advanced per-pixel supervised classifications such as Spectral Angle Mapper (SAM), SAM target finder using BandMax and Support Vector Machine (SVM) were carried out along with the unsupervised clustering procedure - Iterative Self-Organizing Data Analysis Technique (ISODATA). The results were compared and assessed with respect to ground data. Analytical Spectral Devices (ASD), Inc. spectroradiometer, FieldSpec 4 was used to generate the spectra of the water samples which were compiled into a spectral library and used for Spectral Absorption Depth (SAD) analysis. The spectral depth pattern of image and field spectral libraries was found to be highly correlated (correlation coefficient, R2 = 0.99) which validated the image analysis results with respect to the ground data. Further, we carried out a multivariate regression analysis to assess the varying concentrations of metal ions present in water based on the spectral depth of the corresponding absorption feature. Spectral Absorption Depth (SAD) analysis along with metal analysis of field data revealed the order in which the metals affected the river pollution, which was in conformity with the findings of Central Pollution Control Board (CPCB). Therefore, it is concluded that hyperspectral imaging provides opportunity that can be used for satellite based remote monitoring of water quality from space.

Ethnopedology and soil quality of bamboo (Bambusa sp.) based agroforestry system.

PubMed

Arun Jyoti, Nath; Lal, Rattan; Das, Ashesh Kumar

2015-07-15

It is widely recognized that farmers' hold important knowledge of folk soil classification for agricultural land for its uses, yet little has been studied for traditional agroforestry systems. This article explores the ethnopedology of bamboo (Bambusa sp.) based agroforestry system in North East India, and establishes the relationship of soil quality index (SQI) with bamboo productivity. The study revealed four basic folk soil (mati) types: kalo (black soil), lal (red soil), pathal (stony soil) and balu (sandy soil). Of these, lal mati soil was the most predominant soil type (~ 40%) in bamboo-based agroforestry system. Soil physio-chemical parameters were studied to validate the farmers' soil hierarchal classification and also to correlate with productivity of the bamboo stand. Farmers' hierarchal folk soil classification was consistent with the laboratory scientific analysis. Culm production (i.e. measure of productivity of bamboo) was the highest (27culmsclump(-1)) in kalo mati (black soil) and the lowest (19culmsclump(-1)) in balu mati (sandy soil). Linear correlation of individual soil quality parameter with bamboo productivity explained 16 to 49% of the variability. A multiple correlation of the best fitted linear soil quality parameter (soil organic carbon or SOC, water holding capacity or WHC, total nitrogen) with productivity improved explanatory power to 53%. Development of SQI from ten relevant soil quality parameters and its correlation with bamboo productivity explained the 64% of the variation and therefore, suggest SQI as the best determinant of bamboo yield. Data presented indicate that the kalo mati (black soil) is sustainable or sustainable with high input. However, the other three folk soil types (red, stony and sandy soil) are also sustainable but for other land uses. Therefore, ethnopedological studies may move beyond routine laboratory analysis and incorporate SQI for assessing the sustainability of land uses managed by the farmers'. Additional research is required to incorporate principal component analysis for improving the SQI and site potential assessment. It is also important to evaluate the minimum data set (MDS) required for SQI and productivity assessment in agroforestry systems. Copyright © 2015 Elsevier B.V. All rights reserved.

18 CFR 1301.65 - Derivative classification.

Code of Federal Regulations, 2014 CFR

2014-04-01

... classification. 1301.65 Section 1301.65 Conservation of Power and Water Resources TENNESSEE VALLEY AUTHORITY PROCEDURES Protection of National Security Classified Information § 1301.65 Derivative classification. (a) In... classified, and the marking of newly developed material consistent with the classification markings that...

18 CFR 1301.65 - Derivative classification.

Code of Federal Regulations, 2013 CFR

2013-04-01

... classification. 1301.65 Section 1301.65 Conservation of Power and Water Resources TENNESSEE VALLEY AUTHORITY PROCEDURES Protection of National Security Classified Information § 1301.65 Derivative classification. (a) In... classified, and the marking of newly developed material consistent with the classification markings that...

18 CFR 1301.65 - Derivative classification.

Code of Federal Regulations, 2012 CFR

2012-04-01

... classification. 1301.65 Section 1301.65 Conservation of Power and Water Resources TENNESSEE VALLEY AUTHORITY PROCEDURES Protection of National Security Classified Information § 1301.65 Derivative classification. (a) In... classified, and the marking of newly developed material consistent with the classification markings that...

EXTENDING AQUATIC CLASSIFICATION TO THE LANDSCAPE SCALE HYDROLOGY-BASED STRATEGIES

EPA Science Inventory

Aquatic classification of single water bodies (lakes, wetlands, estuaries) is often based on geologic origin, while stream classification has relied on multiple factors related to landform, geomorphology, and soils. We have developed an approach to aquatic classification based o...

Knowledge categorization affects popularity and quality of Wikipedia articles

PubMed Central

Lomi, Alessandro

2018-01-01

The existence of a shared classification system is essential to knowledge production, transfer, and sharing. Studies of knowledge classification, however, rarely consider the fact that knowledge categories exist within hierarchical information systems designed to facilitate knowledge search and discovery. This neglect is problematic whenever information about categorical membership is itself used to evaluate the quality of the items that the category contains. The main objective of this paper is to show that the effects of category membership depend on the position that a category occupies in the hierarchical knowledge classification system of Wikipedia—an open knowledge production and sharing platform taking the form of a freely accessible on-line encyclopedia. Using data on all English-language Wikipedia articles, we examine how the position that a category occupies in the classification hierarchy affects the attention that articles in that category attract from Wikipedia editors, and their evaluation of quality of the Wikipedia articles. Specifically, we show that Wikipedia articles assigned to coarse-grained categories (i. e., categories that occupy higher positions in the hierarchical knowledge classification system) garner more attention from Wikipedia editors (i. e., attract a higher volume of text editing activity), but receive lower evaluations (i. e., they are considered to be of lower quality). The negative relation between attention and quality implied by this result is consistent with current theories of social categorization, but it also goes beyond available results by showing that the effects of categorization on evaluation depend on the position that a category occupies in a hierarchical knowledge classification system. PMID:29293627

Knowledge categorization affects popularity and quality of Wikipedia articles.

PubMed

Lerner, Jürgen; Lomi, Alessandro

2018-01-01

The existence of a shared classification system is essential to knowledge production, transfer, and sharing. Studies of knowledge classification, however, rarely consider the fact that knowledge categories exist within hierarchical information systems designed to facilitate knowledge search and discovery. This neglect is problematic whenever information about categorical membership is itself used to evaluate the quality of the items that the category contains. The main objective of this paper is to show that the effects of category membership depend on the position that a category occupies in the hierarchical knowledge classification system of Wikipedia-an open knowledge production and sharing platform taking the form of a freely accessible on-line encyclopedia. Using data on all English-language Wikipedia articles, we examine how the position that a category occupies in the classification hierarchy affects the attention that articles in that category attract from Wikipedia editors, and their evaluation of quality of the Wikipedia articles. Specifically, we show that Wikipedia articles assigned to coarse-grained categories (i. e., categories that occupy higher positions in the hierarchical knowledge classification system) garner more attention from Wikipedia editors (i. e., attract a higher volume of text editing activity), but receive lower evaluations (i. e., they are considered to be of lower quality). The negative relation between attention and quality implied by this result is consistent with current theories of social categorization, but it also goes beyond available results by showing that the effects of categorization on evaluation depend on the position that a category occupies in a hierarchical knowledge classification system.

Evaluation of water resources around Barapukuria coal mine industrial area, Dinajpur, Bangladesh

NASA Astrophysics Data System (ADS)

Howladar, M. Farhad; Deb, Pulok Kanti; Muzemder, A. T. M. Shahidul Huqe; Ahmed, Mushfique

2014-09-01

Water is a very important natural resource which can be utilized in renewable or non-renewable forms but before utilizing, the evaluation of the quality of this resource is crucial for a particular use. However, the problems of water quality are more severe in areas where the mining and mineral processes' industries are present. In mining processes, several classes of wastes are produced which may turn into ultimately the sources of water quality and environmental degradation. In consequences, the evaluations of water quality for livestock, drinking, irrigation purposes and environmental implications have been carried out around the Barapukuria Coal Mining Industry under different methods and techniques such as primarily the field investigation; secondly the laboratory chemical analysis and thirdly justified the suitability of the laboratory analysis with statistical representation and correlation matrix, Schoeller plot, Piper's Trilinear diagram, Expanded Durov diagram, Wilcox diagram, US salinity diagram, Doneen's chart and others. The results of all surface and ground water samples analysis show that the characteristics and concentrations of all the major physical and chemical parameters such as pH, EC, TDS, Na+, K+, Ca2+, Mg2+, Fetotal, Cl-, HCO3 -, CO3 2- and SO4 2- are varied from one sample to other but well analogous with the WHO and EQS standard limit for all purposes in the area where the abundance of the major ions is as follows: Ca2+ > Na+ > Mg2+ > K+ > Fetotal = HCO3 - > SO4 2- > Cl- > CO3 2-. The graphical exposition of analytical data demonstrates two major hydrochemical facies for example: calcium-bicarbonate (Ca2+- HCO3 -) and magnesium-bicarbonate (Mg2+- HCO3 -) type facies which directly support the shallow recently recharged alkaline water around the industry. The calculated values for the evaluation classification of water based on TDS, Na%, EC, SAR, PI, RSC, MH, and TH replicate good to excellent use of water for livestock, drinking and irrigation activities except in some cases. For example, the high hardness in both water samples specifies the active hydraulic relation between surface and groundwater. Moreover, the statistical application and interpretation exhibit a good positive correlation among most of the water constituents which might be the indicator of having tightly grouped, precise homogeneous good-quality water resources around the mining industry. Finally from the environmental degradation point of view, it can be implied that there are no significant parameters or factors observed which are much badly effective on environment except very few cases. Thus, this research strongly recommends for monitoring the water quality in every 6 months or annually around this industry which might be positive for keeping the safe environment and healthy production of the coal mine.

33 CFR 154.1016 - Facility classification by COTP.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 33 Navigation and Navigable Waters 2 2011-07-01 2011-07-01 false Facility classification by COTP... Facilities § 154.1016 Facility classification by COTP. (a) The COTP may upgrade the classification of: (1) An...) The COTP may downgrade, the classification of: (1) An MTR facility specified in § 154.1015(c) to a...

Assessment of metal exposure, ecological status and required water quality monitoring strategies in small- to medium-size temperate rivers.

PubMed

Marijić, Vlatka Filipović; Perić, Mirela Sertić; Kepčija, Renata Matoničkin; Dragun, Zrinka; Kovarik, Ivana; Gulin, Vesna; Erk, Marijana

2016-01-01

The present study was undertaken to obtain a better understanding of the seasonal variability of total dissolved metal/metalloid levels and physicochemical parameters within small- to medium-size freshwater ecosystems in temperate climate region. The research was conducted in four seasons in the Sutla River, medium-size polluted, and the Črnomerec Stream, small-size unpolluted watercourse in Croatia. In the Sutla River, characterized by the rural/industrial catchment, physicochemical parameters and total dissolved metal concentrations of 21 trace and 4 macro elements were analysed downstream of the point source of pollution, the glass production facility, indicating for the first time their variability across four seasons. Based on dissolved oxygen, total dissolved solids, nutrient concentrations, conductivity and total chemical oxygen demand, quality status of the Sutla River was good, but moderate to poor during summer, what was additionally confirmed by the highest levels of the most of 25 measured metals/metalloids in summer. Comparison with the reference small-size watercourse, the Črnomerec Stream, indicated significant anthropogenic impact on the Sutla River, most evident for Fe, Mn, Mo, Ni, Pb, Rb and Tl levels (3-70-fold higher in the Sutla River across all seasons). Generally, presented results indicated significant decrease of the water quality in the anthropogenically impacted small- to medium-size watercourses in summer, regarding physicochemical water parameters and total dissolved metal/metalloid concentrations, and pointed to significant seasonality of these parameters. Confirmed seasonality of river ecological status indicates that seasonal assessment represents a prerequisite for proper classification of the water quality in small- to medium-size temperate rivers.

Surface-water-quality assessment of the lower Kansas River basin, Kansas and Nebraska; project data November 1986 through April 1990

USGS Publications Warehouse

Fallon, J.D.; McChesney, J.A.

1993-01-01

Surface-water-quality data were collected from the lower Kansas River Basin in Kansas and Nebraska. The data are presented in 17 tables consisting of physical properties, concentrations of dissolved solids and major ions, dissolved and total nutrients, dissolved and total major metals and trace elements, radioactivity, organic carbon, pesticides and other synthetic-organic compounds, bacteria and chlorophyll-a, in water; particle-size distributions and concentrations of major metals and trace elements in suspended and streambed sediment; and concentrations of synthetic-organic compounds in streambed sediment. The data are grouped within each table by sampling sites, arranged in downstream order. Ninety-one sites were sampled in the study area. These sampling sites are classified in three, non-exclusive categories (fixed, synoptic, and miscellaneous sites) on the basis of sampling frequency and location. Sampling sites are presented on a plate and in 3 tables, cross-referenced by downstream order, alphabetical order, U.S. Geological Survey identification number, sampling-site classification category, and types of analyses performed at each site. The methods used to collect, analyze, and verify the accuracy of the data also are presented. (USGS)

Real Time Monitoring System of Pollution Waste on Musi River Using Support Vector Machine (SVM) Method

NASA Astrophysics Data System (ADS)

Fachrurrozi, Muhammad; Saparudin; Erwin

2017-04-01

Real-time Monitoring and early detection system which measures the quality standard of waste in Musi River, Palembang, Indonesia is a system for determining air and water pollution level. This system was designed in order to create an integrated monitoring system and provide real time information that can be read. It is designed to measure acidity and water turbidity polluted by industrial waste, as well as to show and provide conditional data integrated in one system. This system consists of inputting and processing the data, and giving output based on processed data. Turbidity, substances, and pH sensor is used as a detector that produce analog electrical direct current voltage (DC). Early detection system works by determining the value of the ammonia threshold, acidity, and turbidity level of water in Musi River. The results is then presented based on the level group pollution by the Support Vector Machine classification method.

High-frequency phosphorus and nitrate measurements for improved statutory water quality monitoring and management

NASA Astrophysics Data System (ADS)

Bieroza, Magdalena

2017-04-01

High-frequency nutrient (phosphorus and nitrogen) monitoring using wet-chemistry analysers and optical sensors has revolutionised the collection of biogeochemical data from streams, rivers and lakes. Matching the nutrient measurement time with timescales of hydrological responses has revealed biogeochemical patterns and nutrient hydrological responses not observed previously. Capturing a wider range of nutrient concentrations compared to traditional coarse resolution sampling enables more accurate estimation of mean concentrations and loads and thus improved water body classification. However, to date the scientific insights from the high-frequency nutrient monitoring studies have not been translated into policy and operational responses. The pertinent question is where and how often to measure nutrients to satisfy statutory monitoring requirements for the Water Framework Directive and the Nitrates Directive. Therefore this paper discusses how the reduced data uncertainty and improved process understanding obtained with the high-frequency measurements can improve statutory nutrient monitoring, using case studies from England and Sweden.

Methods of eutrophication assessment in the context of the water framework directive: Examples from the Eastern Mediterranean coastal areas

NASA Astrophysics Data System (ADS)

Pavlidou, Alexandra; Simboura, Nomiki; Rousselaki, Eleni; Tsapakis, Manolis; Pagou, Kalliopi; Drakopoulou, Paraskevi; Assimakopoulou, Georgia; Kontoyiannis, Harilaos; Panayotidis, Panayotis

2015-10-01

A set of methodological tools were tested in order to assess the eutrophication quality of selected coastal areas in Eastern Mediterranean Sea, Greece, in the context of the Water Framework Directive under various anthropogenic pressures. Three, five-step tools, namely, TRIX, chlorophyll-a (chl-a) biomass classification scheme, and eutrophication index (E.I.) were applied in oligotrophic waters for (a) the whole water column and (b) the euphotic zone. The relationship among the eutrophication assessment indices and the ecological quality status (EcoQ) assessment indices for benthic macroinvertebrates (BENTIX index) and macroalgae (ecological evaluation index-EEIc) was also explored. Agricultural activities and mariculture are the pressures mostly related to the eutrophication assessment of the selected Greek coastal water bodies. Chl-a proved to be the criterion with the best overall correlation with the EcoQ indices, while TRIX with the lowest. Moreover, among the eutrophication indices, E.I. showed better overall agreement with BENTIX showing that probably it reflects the indirect relation of macroinvertebrates with water eutrophication in a better way. Among the eutrophication indices used, TRIX rather overestimated the eutrophication status of the selected coastal areas. The first stage of eutrophication was reflected more efficiently using E.I. than TRIX, but E.I. seems to be a rather sensitive index. A future modification of the high to good boundary of E.I. may be needed in order to demonstrate the high status of the relatively undisturbed Greek coastal sites.

Telephone-quality pathological speech classification using empirical mode decomposition.

PubMed

Kaleem, M F; Ghoraani, B; Guergachi, A; Krishnan, S

2011-01-01

This paper presents a computationally simple and effective methodology based on empirical mode decomposition (EMD) for classification of telephone quality normal and pathological speech signals. EMD is used to decompose continuous normal and pathological speech signals into intrinsic mode functions, which are analyzed to extract physically meaningful and unique temporal and spectral features. Using continuous speech samples from a database of 51 normal and 161 pathological speakers, which has been modified to simulate telephone quality speech under different levels of noise, a linear classifier is used with the feature vector thus obtained to obtain a high classification accuracy, thereby demonstrating the effectiveness of the methodology. The classification accuracy reported in this paper (89.7% for signal-to-noise ratio 30 dB) is a significant improvement over previously reported results for the same task, and demonstrates the utility of our methodology for cost-effective remote voice pathology assessment over telephone channels.

18 CFR 401.35 - Classification of projects for review under Section 3.8 of the Compact.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 18 Conservation of Power and Water Resources 2 2011-04-01 2011-04-01 false Classification of... less than a daily average rate of 100,000 gallons except when the imported water is wastewater; (18... water during any 30-day period; and (18) Any other project that the Executive Director may specially...

33 CFR 154.1216 - Facility classification.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 33 Navigation and Navigable Waters 2 2012-07-01 2012-07-01 false Facility classification. 154.1216... Vegetable Oils Facilities § 154.1216 Facility classification. (a) The Coast Guard classifies facilities that... classification of a facility that handles, stores, or transports animal fats or vegetable oils. The COTP may...

33 CFR 154.1216 - Facility classification.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 33 Navigation and Navigable Waters 2 2014-07-01 2014-07-01 false Facility classification. 154.1216... Vegetable Oils Facilities § 154.1216 Facility classification. (a) The Coast Guard classifies facilities that... classification of a facility that handles, stores, or transports animal fats or vegetable oils. The COTP may...

33 CFR 154.1216 - Facility classification.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 33 Navigation and Navigable Waters 2 2013-07-01 2013-07-01 false Facility classification. 154.1216... Vegetable Oils Facilities § 154.1216 Facility classification. (a) The Coast Guard classifies facilities that... classification of a facility that handles, stores, or transports animal fats or vegetable oils. The COTP may...

33 CFR 157.04 - Authorization of classification societies.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 33 Navigation and Navigable Waters 2 2011-07-01 2011-07-01 false Authorization of classification... CARRYING OIL IN BULK General § 157.04 Authorization of classification societies. (a) The Coast Guard may authorize any classification society (CS) to perform certain plan reviews, certifications, and inspections...

33 CFR 157.04 - Authorization of classification societies.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 33 Navigation and Navigable Waters 2 2010-07-01 2010-07-01 false Authorization of classification... CARRYING OIL IN BULK General § 157.04 Authorization of classification societies. (a) The Coast Guard may authorize any classification society (CS) to perform certain plan reviews, certifications, and inspections...

18 CFR 3a.11 - Classification of official information.

Code of Federal Regulations, 2011 CFR

2011-04-01

... classification categories are defined as follows: (1) Top Secret. Top Secret refers to national security... 18 Conservation of Power and Water Resources 1 2011-04-01 2011-04-01 false Classification of... REGULATORY COMMISSION, DEPARTMENT OF ENERGY GENERAL RULES NATIONAL SECURITY INFORMATION Classification § 3a...

Evaluation of military field-water quality: Volume 6, Infectious organisms of military concern associated with nonconsumptive exposure: Assessment of health risks and recommendations for establishing related standards

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cooper, R.C.; Olivieri, A.W.; Danielson, R.E.

1986-02-01

This study is an assessment of the risk of illness due to exposure to water-related (i.e., water-based, water-washed) infectious organisms. The organisms under consideration are Aeromonas spp., Leptospira spp., Pseudomonas spp., Staphylococcus spp., non-cholerae Vibrio spp., Acanthamoeba spp., Balantidium coli, Naegleria spp., Ascaris lumbricoides, Dracunculus medinesis, Schistosoma spp., and the agents responsible for cercarial dermatitis (i.e., Trichobilharzia, Gigantobilharzia, and Austrobilharzia). Evaluation of the risk to disease associated with the above pathogens requires information in specific areas such as dose response, concentration of agents in the environment, and environmental persistence. The existing body of knowledge concerning these agents ranges from speculationmore » to established fact. Unfortunately, areas of information critical to risk assessment are frequently unavailable. Because of this lack of data, the risk assessment presented is semiquantitative and limited to the presentation of an environmental classification scheme. 14 refs., 2 figs., 57 tabs.« less

[Subtype classification of ceftriaxone sodium and its influence on the quality of product].

PubMed

Xue, Jing; Jia, Yan-Hua; Li, Jin; Yin, Li-Hui; Hu, Chang-Qin

2014-07-01

Powder X-ray diffraction (PXRD) technology combined with cluster analysis method was used to classify 75 batches of crystalline ceftriaxone sodium into subtypes, the crystalline characteristics of each subtype were measured with scanning electron microscope (SEM). By comparing some parameters of these subtypes correlated to crystallization process of ceftriaxone sodium, such as salification rate, water content in different subtypes, as well as by studying different lattice stabilities, different compatibilities with rubber closures during accelerated stability tests, the key point to improve the quality of domestic ceftriaxone sodium was disclosed. The results of this paper indicated that the fine structure of the products could be controlled well by improving the salification and crystallization process. As a result, the subtype II of ceftriaxone sodium with high stability can be produced.

Suggestion on the safety classification of spent fuel dry storage in China’s pressurized water reactor nuclear power plant

NASA Astrophysics Data System (ADS)

Liu, Ting; Qu, Yunhuan; Meng, De; Zhang, Qiaoer; Lu, Xinhua

2018-01-01

China’s spent fuel storage in the pressurized water reactors(PWR) is stored with wet storage way. With the rapid development of nuclear power industry, China’s NPPs(NPPs) will not be able to meet the problem of the production of spent fuel. Currently the world’s major nuclear power countries use dry storage as a way of spent fuel storage, so in recent years, China study on additional spent fuel dry storage system mainly. Part of the PWR NPP is ready to apply for additional spent fuel dry storage system. It also need to safety classificate to spent fuel dry storage facilities in PWR, but there is no standard for safety classification of spent fuel dry storage facilities in China. Because the storage facilities of the spent fuel dry storage are not part of the NPP, the classification standard of China’s NPPs is not applicable. This paper proposes the safety classification suggestion of the spent fuel dry storage for China’s PWR NPP, through to the study on China’s safety classification principles of PWR NPP in “Classification for the items of pressurized water reactor nuclear power plants (GB/T 17569-2013)”, and safety classification about spent fuel dry storage system in NUREG/CR - 6407 in the United States.

Groundwater hydrogeochemical characteristics in rehabilitated coalmine spoils

NASA Astrophysics Data System (ADS)

Gomo, M.; Masemola, E.

2016-04-01

The investigation aims to identify and describe hydrogeochemical processes controlling the evolution of groundwater chemistry in rehabilitated coalmine spoils and their overall influence on groundwater quality at a study area located in the Karoo basin of South Africa. A good understanding of the processes that controls the evolution of the mine water quality is vital for the planning, application and management of post-mining remedial actions. The study utilises scatter plots, statistical analysis, PHREEQC hydrogeochemical modelling, stoichiometric reaction ratios analysis, and the expanded Durov diagram as complimentary tools to interpret the groundwater chemistry data collected from monitoring boreholes from 1995 to 2014. Measured pH ranging between 6-8 and arithmetic mean of 7.32 shows that the groundwater system is characterised by circumneutral hydrogeochemical conditions period. Comparison of measured groundwater ion concentrations to theoretical reaction stoichiometry identifies Dolomite-Acid Mine Drainage (AMD) neutralisation as the main hydrogeochemical process controlling the evolution of the groundwater chemistry. Hydrogeochemical modelling shows that, the groundwater has temporal variations of calcite and dolomite saturation indices characterised by alternating cycles of over-saturation and under-saturation that is driven by the release of sulphate, calcium and magnesium ions from the carbonate-AMD neutralization process. Arithmetic mean concentrations of sulphate, calcium and magnesium are in the order of 762 mg/L, 141 mg/L and 108 mg/L. Calcium and magnesium ions contribute to very hard groundwater quality conditions. Classification based on total dissolved solids (TDS), shows the circumneutral water is of poor to unacceptable quality for drinking purposes. Despite its ability to prevent AMD formation and leaching of metals, the dolomite-AMD neutralisation process can still lead to problems of elevated TDS and hardness which mines should be aware of when developing water quality management plans.

Optimal Non-Invasive Fault Classification Model for Packaged Ceramic Tile Quality Monitoring Using MMW Imaging

NASA Astrophysics Data System (ADS)

Agarwal, Smriti; Singh, Dharmendra

2016-04-01

Millimeter wave (MMW) frequency has emerged as an efficient tool for different stand-off imaging applications. In this paper, we have dealt with a novel MMW imaging application, i.e., non-invasive packaged goods quality estimation for industrial quality monitoring applications. An active MMW imaging radar operating at 60 GHz has been ingeniously designed for concealed fault estimation. Ceramic tiles covered with commonly used packaging cardboard were used as concealed targets for undercover fault classification. A comparison of computer vision-based state-of-the-art feature extraction techniques, viz, discrete Fourier transform (DFT), wavelet transform (WT), principal component analysis (PCA), gray level co-occurrence texture (GLCM), and histogram of oriented gradient (HOG) has been done with respect to their efficient and differentiable feature vector generation capability for undercover target fault classification. An extensive number of experiments were performed with different ceramic tile fault configurations, viz., vertical crack, horizontal crack, random crack, diagonal crack along with the non-faulty tiles. Further, an independent algorithm validation was done demonstrating classification accuracy: 80, 86.67, 73.33, and 93.33 % for DFT, WT, PCA, GLCM, and HOG feature-based artificial neural network (ANN) classifier models, respectively. Classification results show good capability for HOG feature extraction technique towards non-destructive quality inspection with appreciably low false alarm as compared to other techniques. Thereby, a robust and optimal image feature-based neural network classification model has been proposed for non-invasive, automatic fault monitoring for a financially and commercially competent industrial growth.

Discrimination of different sub-basins on Tajo River based on water influence factor

NASA Astrophysics Data System (ADS)

Bermudez, R.; Gascó, J. M.; Tarquis, A. M.; Saa-Requejo, A.

2009-04-01

Numeric taxonomy has been applied to classify Tajo basin water (Spain) till Portugal border. Several stations, a total of 52, that estimate 15 water variables have been used in this study. The different groups have been obtained applying a Euclidean distance among stations (distance classification) and a Euclidean distance between each station and the centroid estimated among them (centroid classification), varying the number of parameters and with or without variable typification. In order to compare the classification a log-log relation has been established, between number of groups created and distances, to select the best one. It has been observed that centroid classification is more appropriate following in a more logic way the natural constrictions than the minimum distance among stations. Variable typification doesn't improve the classification except when the centroid method is applied. Taking in consideration the ions and the sum of them as variables, the classification improved. Stations are grouped based on electric conductivity (CE), total anions (TA), total cations (TC) and ions ratio (Na/Ca and Mg/Ca). For a given classification and comparing the different groups created a certain variation in ions concentration and ions ratio are observed. However, the variation in each ion among groups is different depending on the case. For the last group, regardless the classification, the increase in all ions is general. Comparing the dendrograms, and groups that originated, Tajo river basin can be sub dived in five sub-basins differentiated by the main influence on water: 1. With a higher ombrogenic influence (rain fed). 2. With ombrogenic and pedogenic influence (rain and groundwater fed). 3. With pedogenic influence. 4. With lithogenic influence (geological bedrock). 5. With a higher ombrogenic and lithogenic influence added.

78 FR 34915 - Approval and Promulgation of Air Quality Implementation Plans; Virginia; Revision to the...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-06-11

... ENVIRONMENTAL PROTECTION AGENCY 40 CFR Part 52 [EPA-R03-OAR-2013-0289; FRL-9822-3] Approval and Promulgation of Air Quality Implementation Plans; Virginia; Revision to the Classification and Implementation... approving these revisions to include the classification of Northern Virginia as ``marginal'' for the 2008...

A Quality Classification System for Young Hardwood Trees - The First Step in Predicting Future Products

Treesearch

David L. Sonderman; Robert L. Brisbin

1978-01-01

Forest managers have no objective way to determine the relative value of culturally treated forest stands in terms of product potential. This paper describes the first step in the development of a quality classification system based on the measurement of individual tree characteristics for young hardwood stands.

Infant-Mother Attachment Classification: Risk and Protection in Relation to Changing Maternal Caregiving Quality

ERIC Educational Resources Information Center

Developmental Psychology, 2006

2006-01-01

The relations between early infant-mother attachment and children's social competence and behavior problems during the preschool and early school-age period were examined in more than 1,000 children under conditions of decreasing, stable, and increasing maternal parenting quality. Infants' Strange Situation attachment classifications predicted…

Global hierarchical classification of deepwater and wetland environments from remote sensing products

NASA Astrophysics Data System (ADS)

Fluet-Chouinard, E.; Lehner, B.; Aires, F.; Prigent, C.; McIntyre, P. B.

2017-12-01

Global surface water maps have improved in spatial and temporal resolutions through various remote sensing methods: open water extents with compiled Landsat archives and inundation with topographically downscaled multi-sensor retrievals. These time-series capture variations through time of open water and inundation without discriminating between hydrographic features (e.g. lakes, reservoirs, river channels and wetland types) as other databases have done as static representation. Available data sources present the opportunity to generate a comprehensive map and typology of aquatic environments (deepwater and wetlands) that improves on earlier digitized inventories and maps. The challenge of classifying surface waters globally is to distinguishing wetland types with meaningful characteristics or proxies (hydrology, water chemistry, soils, vegetation) while accommodating limitations of remote sensing data. We present a new wetland classification scheme designed for global application and produce a map of aquatic ecosystem types globally using state-of-the-art remote sensing products. Our classification scheme combines open water extent and expands it with downscaled multi-sensor inundation data to capture the maximal vegetated wetland extent. The hierarchical structure of the classification is modified from the Cowardin Systems (1979) developed for the USA. The first level classification is based on a combination of landscape positions and water source (e.g. lacustrine, riverine, palustrine, coastal and artificial) while the second level represents the hydrologic regime (e.g. perennial, seasonal, intermittent and waterlogged). Class-specific descriptors can further detail the wetland types with soils and vegetation cover. Our globally consistent nomenclature and top-down mapping allows for direct comparison across biogeographic regions, to upscale biogeochemical fluxes as well as other landscape level functions.

Shallow ground-water quality beneath a major urban center: Denver, Colorado, USA

USGS Publications Warehouse

Bruce, B.W.; McMahon, P.B.

1996-01-01

A survey of the chemical quality of ground water in the unconsolidated alluvial aquifer beneath a major urban center (Denver, Colorado, USA) was performed in 1993 with the objective of characterizing the quality of shallow ground-water in the urban area and relating water quality to land use. Thirty randomly selected alluvial wells were each sampled once for a broad range of dissolved constituents. The urban land use at each well site was sub- classified into one of three land-use settings: residential, commercial, and industrial. Shallow ground-water quality was highly variable in the urban area and the variability could be related to these land-use setting classifications. Sulfate (SO4) was the predominant anion in most samples from the residential and commercial land-use settings, whereas bicarbonate (HCO3) was the predominant anion in samples from the industrial land-use setting, indicating a possible shift in redox conditions associated with land use. Only three of 30 samples had nitrate concentrations that exceeded the US national drinking-water standard of 10 mg l-1 as nitrogen, indicating that nitrate contamination of shallow ground water may not be a serious problem in this urban area. However, the highest median nitrate concentration (4.2 mg l-1) was in samples from the residential setting, where fertilizer application is assumed to be most intense. Twenty-seven of 30 samples had detectable pesticides and nine of 82 analyzed pesticide compounds were detected at low concentrations, indicating that pesticides are widely distributed in shallow ground water in this urban area. Although the highest median total pesticide concentration (0.17 ??g l-1) was in the commercial setting, the herbicides prometon and atrazine were found in each land-use setting. Similarly, 25 of 29 samples analyzed had detectable volatile organic compounds (VOCs) indicating these compounds are also widely distributed in this urban area. The total VOC concentrations in sampled wells ranged from nondetectable to 23 442 ??g l-1. Widespread detections and occasionally high concentrations point to VOCs as the major anthropogenic ground-water impact in this urban environment. Generally, the highest VOC concentrations occurred in samples from the industrial setting. The most frequently detected VOC was the gasoline additive methyl tertbutyl ether (MTBE, in 23 of 29 wells). Results from this study indicate that the quality of shallow ground water in major urban areas can be related to land-use settings. Moreover, some VOCs and pesticides may be widely distributed at low concentrations in shallow ground water throughout major urban areas. As a result, the differentiation between point and non-point sources for these compounds in urban areas may be difficult.

Inland-coastal water interaction: Remote sensing application for shallow-water quality and algal blooms modeling

NASA Astrophysics Data System (ADS)

Melesse, Assefa; Hajigholizadeh, Mohammad; Blakey, Tara

2017-04-01

In this study, Landsat 8 and Sea-Viewing Wide Field-of-View Sensor (SeaWIFS) sensors were used to model the spatiotemporal changes of four water quality parameters: Landsat 8 (turbidity, chlorophyll-a (chl-a), total phosphate, and total nitrogen) and Sea-Viewing Wide Field-of-View Sensor (SeaWIFS) (algal blooms). The study was conducted in Florda bay, south Florida and model outputs were compared with in-situ observed data. The Landsat 8 based study found that, the predictive models to estimate chl-a and turbidity concentrations, developed through the use of stepwise multiple linear regression (MLR), gave high coefficients of determination in dry season (wet season) (R2 = 0.86(0.66) for chl-a and R2 = 0.84(0.63) for turbidity). Total phosphate and TN were estimated using best-fit multiple linear regression models as a function of Landsat TM and OLI,127 and ground data and showed a high coefficient of determination in dry season (wet season) (R2 = 0.74(0.69) for total phosphate and R2 = 0.82(0.82) for TN). Similarly, the ability of SeaWIFS for chl-a retrieval from optically shallow coastal waters by applying algorithms specific to the pixels' benthic class was evaluated. Benthic class was determined through satellite image-based classification methods. It was found that benthic class based chl-a modeling algorithm was better than the existing regionally-tuned approach. Evaluation of the residuals indicated the potential for further improvement to chl-a estimation through finer characterization of benthic environments. Key words: Landsat, SeaWIFS, water quality, Florida bay, Chl-a, turbidity

Hydrogeochemistry and groundwater quality appraisal of part of south Chennai coastal aquifers, Tamil Nadu, India using WQI and fuzzy logic method

NASA Astrophysics Data System (ADS)

Krishna Kumar, S.; Bharani, R.; Magesh, N. S.; Godson, Prince S.; Chandrasekar, N.

2014-12-01

The present study was carried out to evaluate the groundwater quality and its suitability for drinking purposes in the urban coastal aquifers of part of south Chennai, Tamil Nadu, India. Twenty-three groundwater samples were collected during March 2012. The minimum and maximum values of pH (6.3-8 on scale), electrical conductivity (620-12,150 μS/cm), total dissolved solids (399.28-7,824.6 mg/l), carbonate (0-30 mg/l), bicarbonate (0.9-58.9 mg/l), chloride (70.9-4,067.89 mg/l), sulphate (17.4-105 mg/l), nitrate (0.4-6.0 mg/l), calcium (30-200 mg/l), magnesium (1.2-164 mg/l), sodium (69-1,490 mg/l) and potassium (8-340 mg/l) were recorded in the coastal aquifers of Chennai city. The groundwater samples show that the majority of the sampling points clustered on the NaCl and mixed CaMgCl facies of the piper trilinear diagram. In the Gibbs diagram, the majority of the sampling points fall under rock water and evaporation dominance field. Fuzzy membership classification suggests that the majority of the samples fall under good water type followed by excellent water and poor water categories. Groundwater quality index showing the majority of the samples falls under excellent to poor category of water. A positive correlation was observed with Cl-, SO4 2-, Ca2+, Na+, K+, EC and TDS. The extracted results of the correlation matrix and geochemical analysis suggest that the dominant ions of groundwater (Na+, Ca2+, K+, Cl- and SO4 2-) were derived from seawater intrusion and gypsum dissolution process. Nitrate concentration is most significantly derived from anthropogenic sources.

Dimensionality-varied deep convolutional neural network for spectral-spatial classification of hyperspectral data

NASA Astrophysics Data System (ADS)

Qu, Haicheng; Liang, Xuejian; Liang, Shichao; Liu, Wanjun

2018-01-01

Many methods of hyperspectral image classification have been proposed recently, and the convolutional neural network (CNN) achieves outstanding performance. However, spectral-spatial classification of CNN requires an excessively large model, tremendous computations, and complex network, and CNN is generally unable to use the noisy bands caused by water-vapor absorption. A dimensionality-varied CNN (DV-CNN) is proposed to address these issues. There are four stages in DV-CNN and the dimensionalities of spectral-spatial feature maps vary with the stages. DV-CNN can reduce the computation and simplify the structure of the network. All feature maps are processed by more kernels in higher stages to extract more precise features. DV-CNN also improves the classification accuracy and enhances the robustness to water-vapor absorption bands. The experiments are performed on data sets of Indian Pines and Pavia University scene. The classification performance of DV-CNN is compared with state-of-the-art methods, which contain the variations of CNN, traditional, and other deep learning methods. The experiment of performance analysis about DV-CNN itself is also carried out. The experimental results demonstrate that DV-CNN outperforms state-of-the-art methods for spectral-spatial classification and it is also robust to water-vapor absorption bands. Moreover, reasonable parameters selection is effective to improve classification accuracy.

Wetland Hydrologic Connectivity to Downstream Waters: A Classification Approach and National Assessment

NASA Astrophysics Data System (ADS)

Leibowitz, S. G.; Hill, R. A.; Weber, M.; Jones, C., Jr.; Rains, M. C.; Creed, I. F.; Christensen, J.

2017-12-01

Connectivity has become a major focus of hydrological and ecological studies. Connectivity enhances fluxes among landscape features, whereas isolation eliminates or reduces such flows. Thus connectivity can be an important characteristic controlling ecosystem services. Hydrologic connectivity is particularly significant, since chemical and biological flows are often associated with water movement. Wetlands have many important functions, and the degree to which they are hydrologically connected influences the effect they have on downstream waters. Wetlands with high connectivity can serve as sources (e.g., net exporters of dissolved organic carbon), while those with low connectivity can function as sinks (e.g., net importers of suspended sediments). We developed a system to classify wetlands based on type, magnitude, and frequency of hydrologic connectivity with downstream waters. We determined type (riparian, non-riparian surface, and non-riparian subsurface) by considering soil and bedrock permeability. For magnitude, we developed indices to represent travel time based on Manning's kinematic and Darcy's equations. We used soil drainage class as an indicator of frequency. We also included an index that assesses relative level of anthropogenic impacts to connectivity (e.g., presence of canals and ditches and impervious surfaces). The classification system was designed to be applied at various spatial scales using available data. The system was applied to 4.7 million wetlands in the conterminous United States, using the National Land Cover Dataset and other nationally available geospatial data, and the resulting maps were assessed for patterns in wetland connectivity. While wetland connectivity was dominated by fast, frequent riparian connections nationally, distributions of connectivity were characteristic for each region. Consideration of these distributions of connectivity should promote better management of watershed functions such as flood control and water quality improvement.

Retrospective analysis of associations between water quality and toxic blooms of golden alga (Prymnesium parvum) in Texas reservoirs: Implications for understanding dispersal mechanisms and impacts of climate change

USGS Publications Warehouse

Patino, Reynaldo; Dawson, D.; VanLandeghem, Matthew M.

2014-01-01

Toxic blooms of golden alga (GA, Prymnesium parvum) in Texas typically occur in winter or early spring. In North America, they were first reported in Texas in the 1980s, and a marked range expansion occurred in 2001. Although there is concern about the influence of climate change on the future distribution of GA, factors responsible for past dispersals remain uncertain. To better understand the factors that influence toxic bloom dispersal in reservoirs, this study characterized reservoir water quality associated with toxic GA blooms since 2001, and examined trends in water quality during a 20-year period bracketing the 2001 expansion. Archived data were analyzed for six impacted and six nonimpacted reservoirs from two major Texas basins: Brazos River and Colorado River. Data were simplified for analysis by pooling spatially (across sampling stations) and temporally (winter, December-February) within reservoirs and generating depth-corrected (1 m) monthly values. Classification tree analysis [period of record (POR), 2001-2010] using salinity-associated variables (specific conductance, chloride, sulfate), dissolved oxygen (DO), pH, temperature, total hardness, potassium, nitrate+nitrite, and total phosphorus indicated that salinity best predicts the toxic bloom occurrence. Minimum estimated salinities for toxic bloom formation were 0.59 and 1.02 psu in Brazos and Colorado River reservoirs, respectively. Principal component analysis (POR, 2001-2010) indicated that GA habitat is best defined by higher salinity relative to nonimpacted reservoirs, with winter DO and pH also being slightly higher and winter temperature slightly lower in impacted reservoirs. Trend analysis, however, did not reveal monotonic changes in winter water quality of GA-impacted reservoirs during the 20-year period (1991-2010) bracketing the 2001 dispersal. Therefore, whereas minimum levels of salinity are required for GA establishment and toxic blooms in Texas reservoirs, the lack of trends in water quality suggests that conditions favorable for toxic blooms pre-date the 2001 expansion. These observations are consistent with a climate change-independent scenario of past GA dispersals in Texas reservoirs driven by novel introductions into pre-existing favorable habitat. Reports of latent GA populations in certain nonimpacted reservoirs, however, provide a plausible scenario of future dispersals characterized by prolonged periods between colonization and toxic bloom development and driven by changes in water quality, natural, or anthropogenic.

Groundwater quality appraisal and its hydrochemical characterization in Ghaziabad (a region of indo-gangetic plain), Uttar Pradesh, India

NASA Astrophysics Data System (ADS)

Singh, Uday Veer; Abhishek, Amar; Singh, Kunwar P.; Dhakate, Ratnakar; Singh, Netra Pal

2014-06-01

India's growing population enhances great pressure on groundwater resources. The Ghaziabad region is located in the northern Indo-Gangetic alluvium plain of India. Increased population and industrial activities make it imperative to appraise the quality of groundwater system to ensure long-term sustainability of resources. A total number of 250 groundwater samples were collected in two different seasons, viz., pre-monsoon and post monsoon and analyzed for major physico-chemical parameters. Broad range and great standard deviation occurs for most parameters, indicating chemical composition of groundwater affected by process, including water-rock interaction and anthropogenic effect. Iron was found as predominant heavy metal in groundwater samples followed by copper and lead. An exceptional high concentration of Chromium was found in some locations. Industrial activities as chrome plating and wood preservative are the key source to metal pollution in Ghaziabad region. On the basis of classification the area water shows normal sulfate, chloride and bi-carbonate type, respectively. Base-exchange indices classified 76 % of the groundwater sources was the sodium-bicarbonate type. The meteoric genesis indices demonstrated that 80 % of groundwater sources belong to a shallow meteoric water percolation type. Chadha's diagram suggested that the hydro-chemical faces belong to the HCO3 - dominant Ca2+-Mg2+ type along with Cl--dominant Ca2+-Mg2+-type. There was no significant change in pollution parameters in the selected seasons. Comparison of groundwater quality with Indian standards proves that majority of water samples are suitable for irrigation purposes but not for drinking.

Compiling an Open Database of Dam Inundation Areas on the Irrawaddy, Salween, Mekong, and Red River Basins

NASA Astrophysics Data System (ADS)

Cutter, P. G.; Walcutt, A.; O'Neil-Dunne, J.; Geheb, K.; Troy, A.; Saah, D. S.; Ganz, D.

2016-12-01

Dam construction in mainland Southeast Asia has increased substantially in recent years with extensive regional impacts including alterations to water regimes, the loss and degradation of natural forests and biodiversity, and reductions in soil and water quality. The CGIAR Water Land Ecosystem program (WLE) and partners maintain a comprehensive database of locations and other data relating to existing, planned, and proposed dams in the region's major transboundary rivers spanning areas in Thailand, Cambodia, Laos, Vietnam, Myanmar, and China. A recent regional needs assessment and specific stakeholder requests revealed the need for a dataset reflecting the inundation areas of these dams for use in measuring impacts to river ecology, analyzing disaster risk, monitoring land cover and land use change, evaluating carbon emissions, and assessing the actual and potential impacts to communities. In conjunction with WLE and other partners, SERVIR-Mekong, a regional hub of the USAID and NASA-supported SERVIR program, formulated an explicit procedure to produce this dataset. The procedure includes leveraging data from OpenStreetMap and other sources, creating polygons based on surface water classification procedures achieved via Google Earth Engine, manual digitizing, and modeling of planned/proposed dams based on a DEM and the location and planned height of dams. A quality assurance step ensures that all polygons conform to spatial data quality standards agreed upon by a wide range of production partners. When complete, the dataset will be made publicly available to encourage greater understanding and more informed decisions related to the actual and potential impacts of dams in the region.

33 CFR 67.01-15 - Classification of structures.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 33 Navigation and Navigable Waters 1 2011-07-01 2011-07-01 false Classification of structures. 67.01-15 Section 67.01-15 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY AIDS TO NAVIGATION AIDS TO NAVIGATION ON ARTIFICIAL ISLANDS AND FIXED STRUCTURES General Requirements...

Forward osmosis niches in seawater desalination and wastewater reuse.

PubMed

Valladares Linares, R; Li, Z; Sarp, S; Bucs, Sz S; Amy, G; Vrouwenvelder, J S

2014-12-01

This review focuses on the present status of forward osmosis (FO) niches in two main areas: seawater desalination and wastewater reuse. Specific applications for desalination and impaired-quality water treatment and reuse are described, as well as the benefits, advantages, challenges, costs and knowledge gaps on FO hybrid systems are discussed. FO can play a role as a bridge to integrate upstream and downstream water treatment processes, to reduce the energy consumption of the entire desalination or water recovery and reuse processes, thus achieving a sustainable solution for the water-energy nexus. FO hybrid membrane systems showed to have advantages over traditional membrane process like high pressure reverse osmosis and nanofiltration for desalination and wastewater treatment: (i) chemical storage and feed water systems may be reduced for capital, operational and maintenance cost, (ii) water quality is improved, (iii) reduced process piping costs, (iv) more flexible treatment units, and (v) higher overall sustainability of the desalination and wastewater treatment process. Nevertheless, major challenges make FO systems not yet a commercially viable technology, the most critical being the development of a high flux membrane, capable of maintaining an elevated salt rejection and a reduced internal concentration polarization effect, and the availability of appropriate draw solutions (cost effective and non-toxic), which can be recirculated via an efficient recovery process. This review article highlights the features of hybrid FO systems and specifically provides the state-of-the-art applications in the water industry in a novel classification and based on the latest developments toward scaling up these systems. Copyright © 2014 Elsevier Ltd. All rights reserved.

Computer implemented classification of vegetation using aircraft acquired multispectral scanner data

NASA Technical Reports Server (NTRS)

Cibula, W. G.

1975-01-01

The use of aircraft 24-channel multispectral scanner data in conjunction with computer processing techniques to obtain an automated classification of plant species association was discussed. The classification of various plant species associations was related to information needed for specific applications. In addition, the necessity for multiple selection of training fields for a single class in situations where the study area consists of highly irregular terrain was detailed. A single classification was illuminated differently in different areas, resulting in the existence of multiple spectral signatures for a given class. These different signatures result since different qualities of radiation upwell to the detector from portions that have differing qualities of incident radiation. Techniques of training field selection were outlined, and a classification obtained from a natural area in Tishomingo State Park in northern Mississippi was presented.

Utility of a scanning densitometer in analyzing remotely sensed imagery

NASA Technical Reports Server (NTRS)

Dooley, J. T.

1976-01-01

The utility of a scanning densitometer for analyzing imagery in the NASA Lewis Research Center's regional remote sensing program was evaluated. Uses studied include: (1) quick-look screening of imagery by means of density slicing, magnification, color coding, and edge enhancement; (2) preliminary category classification of both low- and high-resolution data bases; and (3) quantitative measurement of the extent of features within selected areas. The densitometer was capable of providing fast, convenient, and relatively inexpensive preliminary analysis of aerial and satellite photography and scanner imagery involving land cover, water quality, strip mining, and energy conservation.

40 CFR 52.1621 - Classification of regions.

Code of Federal Regulations, 2010 CFR

2010-07-01

... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS (CONTINUED) New Mexico § 52.1621 Classification of regions. The New Mexico plan was evaluated on the basis of the following classifications: Air quality control region Pollutant Particulate matter Sulfur oxides Nitrogen dioxide Carbon monoxide Ozone...

40 CFR 52.1621 - Classification of regions.

Code of Federal Regulations, 2011 CFR

2011-07-01

... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS (CONTINUED) New Mexico § 52.1621 Classification of regions. The New Mexico plan was evaluated on the basis of the following classifications: Air quality control region Pollutant Particulate matter Sulfur oxides Nitrogen dioxide Carbon monoxide Ozone...

Presence of indicator plant species as a predictor of wetland vegetation integrity

USGS Publications Warehouse

Stapanian, Martin A.; Adams, Jean V.; Gara, Brian

2013-01-01

We fit regression and classification tree models to vegetation data collected from Ohio (USA) wetlands to determine (1) which species best predict Ohio vegetation index of biotic integrity (OVIBI) score and (2) which species best predict high-quality wetlands (OVIBI score >75). The simplest regression tree model predicted OVIBI score based on the occurrence of three plant species: skunk-cabbage (Symplocarpus foetidus), cinnamon fern (Osmunda cinnamomea), and swamp rose (Rosa palustris). The lowest OVIBI scores were best predicted by the absence of the selected plant species rather than by the presence of other species. The simplest classification tree model predicted high-quality wetlands based on the occurrence of two plant species: skunk-cabbage and marsh-fern (Thelypteris palustris). The overall misclassification rate from this tree was 13 %. Again, low-quality wetlands were better predicted than high-quality wetlands by the absence of selected species rather than the presence of other species using the classification tree model. Our results suggest that a species’ wetland status classification and coefficient of conservatism are of little use in predicting wetland quality. A simple, statistically derived species checklist such as the one created in this study could be used by field biologists to quickly and efficiently identify wetland sites likely to be regulated as high-quality, and requiring more intensive field assessments. Alternatively, it can be used for advanced determinations of low-quality wetlands. Agencies can save considerable money by screening wetlands for the presence/absence of such “indicator” species before issuing permits.

46 CFR 193.50-5 - Classification.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 46 Shipping 7 2010-10-01 2010-10-01 false Classification. 193.50-5 Section 193.50-5 Shipping COAST... Details § 193.50-5 Classification. (a) Hand portable fire extinguishers and semiportable fire...) Classification Type Size Soda-acid and water, gals. Foam, gals. Carbon dioxide, lbs. Dry chemical, lbs. A II 21/2...

46 CFR 193.50-5 - Classification.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 46 Shipping 7 2011-10-01 2011-10-01 false Classification. 193.50-5 Section 193.50-5 Shipping COAST... Details § 193.50-5 Classification. (a) Hand portable fire extinguishers and semiportable fire...) Classification Type Size Soda-acid and water, gals. Foam, gals. Carbon dioxide, lbs. Dry chemical, lbs. A II 21/2...

46 CFR 193.50-5 - Classification.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 46 Shipping 7 2012-10-01 2012-10-01 false Classification. 193.50-5 Section 193.50-5 Shipping COAST... Details § 193.50-5 Classification. (a) Hand portable fire extinguishers and semiportable fire...) Classification Type Size Soda-acid and water, gals. Foam, gals. Carbon dioxide, lbs. Dry chemical, lbs. A II 21/2...

46 CFR 193.50-5 - Classification.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 46 Shipping 7 2013-10-01 2013-10-01 false Classification. 193.50-5 Section 193.50-5 Shipping COAST... Details § 193.50-5 Classification. (a) Hand portable fire extinguishers and semiportable fire...) Classification Type Size Soda-acid and water, gals. Foam, gals. Carbon dioxide, lbs. Dry chemical, lbs. A II 21/2...

46 CFR 193.50-5 - Classification.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 46 Shipping 7 2014-10-01 2014-10-01 false Classification. 193.50-5 Section 193.50-5 Shipping COAST... Details § 193.50-5 Classification. (a) Hand portable fire extinguishers and semiportable fire...) Classification Type Size Soda-acid and water, gals. Foam, gals. Carbon dioxide, lbs. Dry chemical, lbs. A II 21/2...

Effects of human activities and climate variability on water resources in the Saveh plain, Iran.

PubMed

Mohammadi Ghaleni, M; Ebrahimi, K

2015-02-01

Quantity and quality distribution of surface water and groundwater are changing under the impacts of both climate variability and human activities. The main goal of this paper is to evaluate the abovementioned impacts on the water resources in the Saveh plain, central Iran. To achieve this aim, spatial and temporal changes of the surface and groundwater quality and quantity have been analyzed, using hydrometric and meteorological data. The nonparametric Mann-Kendall test was used to identify trends and change points in the annual rainfall and runoff for the period of 1946 to 2011. In order to analyze the impacts of the Saveh Dam on runoff, the dam operation year, 1994, was considered as a change point. Mann-Kendall test results show that rainfall time series was divided into two parts, namely, 1966-1989 and 1990-2007, and averages of annual rainfall in five stations increase from 10 to 21 %. Also, runoff time series was divided into two parts, namely, 1946-1995 and 1996-2007 and averages of annual runoff in four stations decrease from 8 to 83 %. Results show that rainfall changes in Shahabasi, Razin, Jalayer, Emamabad, and Ahmadabad stations increased from 9 to 33 % before and after 1994. Nevertheless, runoff decreased from 24 to 81 %. The results indicate that the greatest lack of runoff between stations is at Shahabasi station and one important reason for the severe lack is operation of the Saveh Dam in 1994. Highest groundwater level decline, about 168.67 cm, occurred in 1994 that is the operation year of the Saveh Dam. Trend analysis of surface water quality show that electrical conductivity increased 957.34 μmho/cm before and after 1994. Also, the Wilcox water quality classification method has been reduced from C3-S1 to C4-S2. Average groundwater electrical conductivity (EC) during 1999-2003 and 2004-2009 increased to 89.6 μmho/cm. Also, the groundwater quality indices for agricultural usages are classified in four classes including, C4-S2 16, C4-S1 46, C3-S1 30, and C2-S1 8 % of the total aquifer area. In conclusion, in order to have a sustainable development, the effects of water projects on environment and water resources need to be predicted very carefully.

[Revision of the drinking water regulations].

PubMed

Hauswirth, S

2011-11-01

The revision the Drinking Water Regulations will come into effect on 01.11.2011. Surveillance authorities and owners of drinking water supply systems had hoped for simplifications and reductions because of the new arrangements. According to the official statement for the revision the legislature intended to create more clarity, consider new scientific findings, to change regulations that have not been proved to close regulatory gaps, to deregulate and to increase the high quality standards. A detailed examination of the regulation text, however, raises doubts. The new classification of water supply systems requires different modalities of registration, water analyses and official observation, which will complicate the work of the authorities. In particular, the implementation of requirements of registration and examination for the owners of commercial and publicly-operated large hot-water systems in accordance with DVGW Worksheet W 551 requires more effort. According to the estimated 30 000 cases of legionellosis in Germany the need for a check of such systems for Legionella, however, is not called into question. Furthermore, the development of sampling plans and the monitoring of mobile water supply systems requires more work for the health authorities. © Georg Thieme Verlag KG Stuttgart · New York.

Classifications of central solar domestic hot water systems

NASA Astrophysics Data System (ADS)

Guo, J. Y.; Hao, B.; Peng, C.; Wang, S. S.

2016-08-01

Currently, there are many means by which to classify solar domestic hot water systems, which are often categorized according to their scope of supply, solar collector positions, and type of heat storage tank. However, the lack of systematic and scientific classification as well as the general disregard of the thermal performance of the auxiliary heat source is important to DHW systems. Thus, the primary focus of this paper is to determine a classification system for solar domestic hot water systems based on the positions of the solar collector and auxiliary heating device, both respectively and in combination. Field-testing data regarding many central solar DHW systems demonstrates that the position of the auxiliary heat source clearly reflects the operational energy consumption. The consumption of collective auxiliary heating hot water system is much higher than individual auxiliary heating hot water system. In addition, costs are significantly reduced by the separation of the heat storage tank and the auxiliary heating device.

Multidrug Resistance among New Tuberculosis Cases: Detecting Local Variation through Lot Quality-Assurance Sampling

PubMed Central

Lynn Hedt, Bethany; van Leth, Frank; Zignol, Matteo; Cobelens, Frank; van Gemert, Wayne; Viet Nhung, Nguyen; Lyepshina, Svitlana; Egwaga, Saidi; Cohen, Ted

2012-01-01

Background Current methodology for multidrug-resistant TB (MDR TB) surveys endorsed by the World Health Organization provides estimates of MDR TB prevalence among new cases at the national level. On the aggregate, local variation in the burden of MDR TB may be masked. This paper investigates the utility of applying lot quality-assurance sampling to identify geographic heterogeneity in the proportion of new cases with multidrug resistance. Methods We simulated the performance of lot quality-assurance sampling by applying these classification-based approaches to data collected in the most recent TB drug-resistance surveys in Ukraine, Vietnam, and Tanzania. We explored three classification systems—two-way static, three-way static, and three-way truncated sequential sampling—at two sets of thresholds: low MDR TB = 2%, high MDR TB = 10%, and low MDR TB = 5%, high MDR TB = 20%. Results The lot quality-assurance sampling systems identified local variability in the prevalence of multidrug resistance in both high-resistance (Ukraine) and low-resistance settings (Vietnam). In Tanzania, prevalence was uniformly low, and the lot quality-assurance sampling approach did not reveal variability. The three-way classification systems provide additional information, but sample sizes may not be obtainable in some settings. New rapid drug-sensitivity testing methods may allow truncated sequential sampling designs and early stopping within static designs, producing even greater efficiency gains. Conclusions Lot quality-assurance sampling study designs may offer an efficient approach for collecting critical information on local variability in the burden of multidrug-resistant TB. Before this methodology is adopted, programs must determine appropriate classification thresholds, the most useful classification system, and appropriate weighting if unbiased national estimates are also desired. PMID:22249242

Multidrug resistance among new tuberculosis cases: detecting local variation through lot quality-assurance sampling.

PubMed

Hedt, Bethany Lynn; van Leth, Frank; Zignol, Matteo; Cobelens, Frank; van Gemert, Wayne; Nhung, Nguyen Viet; Lyepshina, Svitlana; Egwaga, Saidi; Cohen, Ted

2012-03-01

Current methodology for multidrug-resistant tuberculosis (MDR TB) surveys endorsed by the World Health Organization provides estimates of MDR TB prevalence among new cases at the national level. On the aggregate, local variation in the burden of MDR TB may be masked. This paper investigates the utility of applying lot quality-assurance sampling to identify geographic heterogeneity in the proportion of new cases with multidrug resistance. We simulated the performance of lot quality-assurance sampling by applying these classification-based approaches to data collected in the most recent TB drug-resistance surveys in Ukraine, Vietnam, and Tanzania. We explored 3 classification systems- two-way static, three-way static, and three-way truncated sequential sampling-at 2 sets of thresholds: low MDR TB = 2%, high MDR TB = 10%, and low MDR TB = 5%, high MDR TB = 20%. The lot quality-assurance sampling systems identified local variability in the prevalence of multidrug resistance in both high-resistance (Ukraine) and low-resistance settings (Vietnam). In Tanzania, prevalence was uniformly low, and the lot quality-assurance sampling approach did not reveal variability. The three-way classification systems provide additional information, but sample sizes may not be obtainable in some settings. New rapid drug-sensitivity testing methods may allow truncated sequential sampling designs and early stopping within static designs, producing even greater efficiency gains. Lot quality-assurance sampling study designs may offer an efficient approach for collecting critical information on local variability in the burden of multidrug-resistant TB. Before this methodology is adopted, programs must determine appropriate classification thresholds, the most useful classification system, and appropriate weighting if unbiased national estimates are also desired.

40 CFR 52.621 - Classification of regions.

Code of Federal Regulations, 2010 CFR

2010-07-01

... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS Hawaii § 52.621 Classification of regions. The Hawaii plan was evaluated on the basis of the following classifications: Air quality control region... (hydrocarbons) State of Hawaii II III III III III [37 FR 10860, May 31, 1972] ...

Assessment of reproductive and developmental effects of DINP, DnHP and DCHP using quantitative weight of evidence.

PubMed

Dekant, Wolfgang; Bridges, James

2016-11-01

Quantitative weight of evidence (QWoE) methodology utilizes detailed scoring sheets to assess the quality/reliability of each publication on toxicity of a chemical and gives numerical scores for quality and observed toxicity. This QWoE-methodology was applied to the reproductive toxicity data on diisononylphthalate (DINP), di-n-hexylphthalate (DnHP), and dicyclohexylphthalate (DCHP) to determine if the scientific evidence for adverse effects meets the requirements for classification as reproductive toxicants. The scores for DINP were compared to those when applying the methodology DCHP and DnHP that have harmonized classifications. Based on the quality/reliability scores, application of the QWoE shows that the three databases are of similar quality; but effect scores differ widely. Application of QWoE to DINP studies resulted in an overall score well below the benchmark required to trigger classification. For DCHP, the QWoE also results in low scores. The high scores from the application of the QWoE methodology to the toxicological data for DnHP represent clear evidence for adverse effects and justify a classification of DnHP as category 1B for both development and fertility. The conclusions on classification based on the QWoE are well supported using a narrative assessment of consistency and biological plausibility. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Spatial and temporal changes of water quality, and SWAT modeling of Vosvozis river basin, North Greece.

PubMed

Boskidis, Ioannis; Gikas, Georgios D; Pisinaras, Vassilios; Tsihrintzis, Vassilios A

2010-09-01

The results of an investigation of the quantitative and qualitative characteristics of Vosvozis river in Northern Greece is presented. For the purposes of this study, three gaging stations were installed along Vosvozis river, where water quantity and quality measurements were conducted for the period August 2005 to November 2006. Water discharge, temperature, pH, dissolved oxygen (DO) and electrical conductivity (EC) were measured in situ using appropriate equipment. The collected water samples were analyzed in the laboratory for the determination of nitrate, nitrite and ammonium nitrogen, total Kjeldalh nitrogen (TKN), orthophosphate (OP), total phosphorus (TP), COD, and BOD. Agricultural diffuse sources provided the major source of nitrate nitrogen loads during the wet period. During the dry period (from June to October), the major nutrient (N, P) and COD, BOD sources were point sources. The trophic status of Vosvozis river during the monitoring period was determined as eutrophic, based on Dodds classification scheme. Moreover, the SWAT model was used to simulate hydrographs and nutrient loads. SWAT was validated with the measured data. Predicted hydrographs and pollutographs were plotted against observed values and showed good agreement. The validated model was used to test eight alternative scenarios concerning different cropping management approaches. The results of these scenarios indicate that nonpoint source pollution is the prevailing type of pollution in the study area. The SWAT model was found to satisfactorily simulate processes in ephemeral river basins and is an effective tool in water resources management.

Classifying land cover from an object-oriented approach - applied to LANDSAT 8 at the regional scale of the Lake Tana Basin (Ethiopia)

NASA Astrophysics Data System (ADS)

Lemma, Hanibal; Frankl, Amaury; Poesen, Jean; Adgo, Enyew; Nyssen, Jan

2017-04-01

Object-oriented image classification has been gaining prominence in the field of remote sensing and provides a valid alternative to the 'traditional' pixel based methods. Recent studies have proven the superiority of the object-based approach. So far, object-oriented land cover classifications have been applied either at limited spatial coverages (ranging 2 to 1091 km2) or by using very high resolution (0.5-16 m) imageries. The main aim of this study is to drive land cover information for large area from Landsat 8 OLI surface reflectance using the Estimation of Scale Parameter (ESP) tool and the object oriented software eCognition. The available land cover map of Lake Tana Basin (Ethiopia) is about 20 years old with a courser spatial scale (1:250,000) and has limited use for environmental modelling and monitoring studies. Up-to-date and basin wide land cover maps are essential to overcome haphazard natural resources management, land degradation and reduced agricultural production. Indeed, object-oriented approach involves image segmentation prior to classification, i.e. adjacent similar pixels are aggregated into segments as long as the heterogeneity in the spectral and spatial domains is minimized. For each segmented object, different attributes (spectral, textural and shape) were calculated and used for in subsequent classification analysis. Moreover, the commonly used error matrix is employed to determine the quality of the land cover map. As a result, the multiresolution segmentation (with parameters of scale=30, shape=0.3 and Compactness=0.7) produces highly homogeneous image objects as it is observed in different sample locations in google earth. Out of the 15,089 km2 area of the basin, cultivated land is dominant (69%) followed by water bodies (21%), grassland (4.8%), forest (3.7%) and shrubs (1.1%). Wetlands, artificial surfaces and bare land cover only about 1% of the basin. The overall classification accuracy is 80% with a Kappa coefficient of 0.75. With regard to individual classes, the classification show higher Producer's and User's accuracy (above 84%) for cultivated land, water bodies and forest, but lower (less than 70%) for shrubs, bare land and grassland. Key words: accuracy assessment, eCognition, Estimation of Scale Parameter, land cover, Landsat 8, remote sensing

Using additional external inputs to forecast water quality with an artificial neural network for contamination event detection in source water

NASA Astrophysics Data System (ADS)

Schmidt, F.; Liu, S.

2016-12-01

Source water quality plays an important role for the safety of drinking water and early detection of its contamination is vital to taking appropriate countermeasures. However, compared to drinking water, it is more difficult to detect contamination events because its environment is less controlled and numerous natural causes contribute to a high variability of the background values. In this project, Artificial Neural Networks (ANNs) and a Contamination Event Detection Process (CED Process) were used to identify events in river water. The ANN models the response of basic water quality sensors obtained in laboratory experiments in an off-line learning stage and continuously forecasts future values of the time line in an on-line forecasting step. During this second stage, the CED Process compares the forecast to the measured value and classifies it as regular background or event value, which modifies the ANN's continuous learning and influences its forecasts. In addition to this basic setup, external information is fed to the CED Process: A so-called Operator Input (OI) is provided to inform about unusual water quality levels that are unrelated to the presence of contamination, for example due to cooling water discharge from a nearby power plant. This study's primary goal is to evaluate how well the OI fits into the design of the combined forecasting ANN and CED Process and to understand its effects on the online forecasting stage. To test this, data from laboratory experiments conducted previously at the School of Environment, Tsinghua University, have been used to perform simulations highlighting features and drawbacks of this method. Applying the OI has been shown to have a positive influence on the ANN's ability to handle a sudden change in background values, which is unrelated to contamination. However, it might also mask the presence of an event, an issue that underlines the necessity to have several instances of the algorithm run in parallel. Other difficulties addressed in this study include the source and the format of the OI. This project tries to add to the ongoing research into algorithms for CED. It provides ideas for how results from the binary classification of time series could be evaluated in a more realistic fashion and shows what the advantages and limitations of such a method would be.

Surface Water Detection Using Fused Synthetic Aperture Radar, Airborne LiDAR and Optical Imagery

NASA Astrophysics Data System (ADS)

Braun, A.; Irwin, K.; Beaulne, D.; Fotopoulos, G.; Lougheed, S. C.

2016-12-01

Each remote sensing technique has its unique set of strengths and weaknesses, but by combining techniques the classification accuracy can be increased. The goal of this project is to underline the strengths and weaknesses of Synthetic Aperture Radar (SAR), LiDAR and optical imagery data and highlight the opportunities where integration of the three data types can increase the accuracy of identifying water in a principally natural landscape. The study area is located at the Queen's University Biological Station, Ontario, Canada. TerraSAR-X (TSX) data was acquired between April and July 2016, consisting of four single polarization (HH) staring spotlight mode backscatter intensity images. Grey-level thresholding is used to extract surface water bodies, before identifying and masking zones of radar shadow and layover by using LiDAR elevation models to estimate the canopy height and applying simple geometry algorithms. The airborne LiDAR survey was conducted in June 2014, resulting in a discrete return dataset with a density of 1 point/m2. Radiometric calibration to correct for range and incidence angle is applied, before classifying the points as water or land based on corrected intensity, elevation, roughness, and intensity density. Panchromatic and multispectral (4-band) imagery from Quickbird was collected in September 2005 at spatial resolutions of 0.6m and 2.5m respectively. Pixel-based classification is applied to identify and distinguish water bodies from land. A classification system which inputs SAR-, LiDAR- and optically-derived water presence models in raster formats is developed to exploit the strengths and weaknesses of each technique. The total percentage of water detected in the sample area for SAR backscatter, LiDAR intensity, and optical imagery was 27%, 19% and 18% respectively. The output matrix of the classification system indicates that in over 72% of the study area all three methods agree on the classification. Analysis was specifically targeted towards areas where the methods disagree, highlighting how each technique should be properly weighted over these areas to increase the classification accuracy of water. The conclusions and techniques developed in this study are applicable to other areas where similar environmental conditions and data availability exist.

Benthic Habitat Mapping by Combining Lyzenga’s Optical Model and Relative Water Depth Model in Lintea Island, Southeast Sulawesi

NASA Astrophysics Data System (ADS)

Hafizt, M.; Manessa, M. D. M.; Adi, N. S.; Prayudha, B.

2017-12-01

Benthic habitat mapping using satellite data is one challenging task for practitioners and academician as benthic objects are covered by light-attenuating water column obscuring object discrimination. One common method to reduce this water-column effect is by using depth-invariant index (DII) image. However, the application of the correction in shallow coastal areas is challenging as a dark object such as seagrass could have a very low pixel value, preventing its reliable identification and classification. This limitation can be solved by specifically applying a classification process to areas with different water depth levels. The water depth level can be extracted from satellite imagery using Relative Water Depth Index (RWDI). This study proposed a new approach to improve the mapping accuracy, particularly for benthic dark objects by combining the DII of Lyzenga’s water column correction method and the RWDI of Stumpt’s method. This research was conducted in Lintea Island which has a high variation of benthic cover using Sentinel-2A imagery. To assess the effectiveness of the proposed new approach for benthic habitat mapping two different classification procedures are implemented. The first procedure is the commonly applied method in benthic habitat mapping where DII image is used as input data to all coastal area for image classification process regardless of depth variation. The second procedure is the proposed new approach where its initial step begins with the separation of the study area into shallow and deep waters using the RWDI image. Shallow area was then classified using the sunglint-corrected image as input data and the deep area was classified using DII image as input data. The final classification maps of those two areas were merged as a single benthic habitat map. A confusion matrix was then applied to evaluate the mapping accuracy of the final map. The result shows that the new proposed mapping approach can be used to map all benthic objects in all depth ranges and shows a better accuracy compared to that of classification map produced using only with DII.

Classification and authentication of unknown water samples using machine learning algorithms.

PubMed

Kundu, Palash K; Panchariya, P C; Kundu, Madhusree

2011-07-01

This paper proposes the development of water sample classification and authentication, in real life which is based on machine learning algorithms. The proposed techniques used experimental measurements from a pulse voltametry method which is based on an electronic tongue (E-tongue) instrumentation system with silver and platinum electrodes. E-tongue include arrays of solid state ion sensors, transducers even of different types, data collectors and data analysis tools, all oriented to the classification of liquid samples and authentication of unknown liquid samples. The time series signal and the corresponding raw data represent the measurement from a multi-sensor system. The E-tongue system, implemented in a laboratory environment for 6 numbers of different ISI (Bureau of Indian standard) certified water samples (Aquafina, Bisleri, Kingfisher, Oasis, Dolphin, and McDowell) was the data source for developing two types of machine learning algorithms like classification and regression. A water data set consisting of 6 numbers of sample classes containing 4402 numbers of features were considered. A PCA (principal component analysis) based classification and authentication tool was developed in this study as the machine learning component of the E-tongue system. A proposed partial least squares (PLS) based classifier, which was dedicated as well; to authenticate a specific category of water sample evolved out as an integral part of the E-tongue instrumentation system. The developed PCA and PLS based E-tongue system emancipated an overall encouraging authentication percentage accuracy with their excellent performances for the aforesaid categories of water samples. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

Classification of air quality using fuzzy synthetic multiplication.

PubMed

Abdullah, Lazim; Khalid, Noor Dalina

2012-11-01

Proper identification of environment's air quality based on limited observations is an essential task to meet the goals of environmental management. Various classification methods have been used to estimate the change of air quality status and health. However, discrepancies frequently arise from the lack of clear distinction between each air quality, the uncertainty in the quality criteria employed and the vagueness or fuzziness embedded in the decision-making output values. Owing to inherent imprecision, difficulties always exist in some conventional methodologies when describing integrated air quality conditions with respect to various pollutants. Therefore, this paper presents two fuzzy multiplication synthetic techniques to establish classification of air quality. The fuzzy multiplication technique empowers the max-min operations in "or" and "and" in executing the fuzzy arithmetic operations. Based on a set of air pollutants data carbon monoxide, sulfur dioxide, nitrogen dioxide, ozone, and particulate matter (PM(10)) collected from a network of 51 stations in Klang Valley, East Malaysia, Sabah, and Sarawak were utilized in this evaluation. The two fuzzy multiplication techniques consistently classified Malaysia's air quality as "good." The findings indicated that the techniques may have successfully harmonized inherent discrepancies and interpret complex conditions. It was demonstrated that fuzzy synthetic multiplication techniques are quite appropriate techniques for air quality management.

Assessing Vermont's stream health and biological integrity using artificial neural networks and Bayesian methods

NASA Astrophysics Data System (ADS)

Rizzo, D. M.; Fytilis, N.; Stevens, L.

2012-12-01

Environmental managers are increasingly required to monitor and forecast long-term effects and vulnerability of biophysical systems to human-generated stresses. Ideally, a study involving both physical and biological assessments conducted concurrently (in space and time) could provide a better understanding of the mechanisms and complex relationships. However, costs and resources associated with monitoring the complex linkages between the physical, geomorphic and habitat conditions and the biological integrity of stream reaches are prohibitive. Researchers have used classification techniques to place individual streams and rivers into a broader spatial context (hydrologic or health condition). Such efforts require environmental managers to gather multiple forms of information - quantitative, qualitative and subjective. We research and develop a novel classification tool that combines self-organizing maps with a Naïve Bayesian classifier to direct resources to stream reaches most in need. The Vermont Agency of Natural Resources has developed and adopted protocols for physical stream geomorphic and habitat assessments throughout the state of Vermont. Separate from these assessments, the Vermont Department of Environmental Conservation monitors the biological communities and the water quality in streams. Our initial hypothesis is that the geomorphic reach assessments and water quality data may be leveraged to reduce error and uncertainty associated with predictions of biological integrity and stream health. We test our hypothesis using over 2500 Vermont stream reaches (~1371 stream miles) assessed by the two agencies. In the development of this work, we combine a Naïve Bayesian classifier with a modified Kohonen Self-Organizing Map (SOM). The SOM is an unsupervised artificial neural network that autonomously analyzes inherent dataset properties using input data only. It is typically used to cluster data into similar categories when a priori classes do not exist. The incorporation of a Bayesian classifier allows one to explicitly incorporate existing knowledge and expert opinion into the data analysis. Since classification plays a leading role in the future development of data-enabled science and engineering, such a computational tool is applicable to a variety of proactive adaptive watershed management applications.

Determination of mangrove change in Matang Mangrove Forest using multi temporal satellite imageries

NASA Astrophysics Data System (ADS)

Ibrahim, N. A.; Mustapha, M. A.; Lihan, T.; Ghaffar, M. A.

2013-11-01

Mangrove protects shorelines from damaging storm and hurricane winds, waves, and floods. Mangroves also help prevent erosion by stabilizing sediments with their tangled root systems. They maintain water quality and clarity, filtering pollutants and trapping sediments originating from land. However, mangrove has been reported to be threatened by land conversion for other activities. In this study, land use and land cover changes in Matang Mangrove Forest during the past 18 years (1993 to 2011) were determined using multi-temporal satellite imageries by Landsat TM and RapidEye. In this study, classification of land use and land cover approach was performed using the maximum likelihood classifier (MCL) method along with vegetation index differencing (NDVI) technique. Data obtained was evaluated through Kappa coefficient calculation for accuracy and results revealed that the classification accuracy was 81.25% with Kappa Statistics of 0.78. The results indicated changes in mangrove forest area to water body with 2,490.6 ha, aquaculture with 890.7 ha, horticulture with 1,646.1 ha, palm oil areas with 1,959.2 ha, dry land forest with 2,906.7 ha and urban settlement area with 224.1 ha. Combinations of these approaches were useful for change detection and for indication of the nature of these changes.

Quality assurance: The 10-Group Classification System (Robson classification), induction of labor, and cesarean delivery.

PubMed

Robson, Michael; Murphy, Martina; Byrne, Fionnuala

2015-10-01

Quality assurance in labor and delivery is needed. The method must be simple and consistent, and be of universal value. It needs to be clinically relevant, robust, and prospective, and must incorporate epidemiological variables. The 10-Group Classification System (TGCS) is a simple method providing a common starting point for further detailed analysis within which all perinatal events and outcomes can be measured and compared. The system is demonstrated in the present paper using data for 2013 from the National Maternity Hospital in Dublin, Ireland. Interpretation of the classification can be easily taught. The standard table can provide much insight into the philosophy of care in the population of women studied and also provide information on data quality. With standardization of audit of events and outcomes, any differences in either sizes of groups, events or outcomes can be explained only by poor data collection, significant epidemiological variables, or differences in practice. In April 2015, WHO proposed that the TGCS (also known as the Robson classification) is used as a global standard for assessing, monitoring, and comparing cesarean delivery rates within and between healthcare facilities. Copyright © 2015. Published by Elsevier Ireland Ltd.

77 FR 58868 - Public Land Order No. 7798; Partial Modification of Power Site Classification No. 126; Washington

Federal Register 2010, 2011, 2012, 2013, 2014

2012-09-24

...; WAOR-19641] Public Land Order No. 7798; Partial Modification of Power Site Classification No. 126... partially modifies a withdrawal which established Power Site Classification No. 126, insofar as it affects... under Power Site Classification No. 126 for water power purposes will not be injured by U.S. Forest...

Classification and area estimation of land covers in Kansas using ground-gathered and LANDSAT digital data

NASA Technical Reports Server (NTRS)

May, G. A.; Holko, M. L.; Anderson, J. E.

1983-01-01

Ground-gathered data and LANDSAT multispectral scanner (MSS) digital data from 1981 were analyzed to produce a classification of Kansas land areas into specific types called land covers. The land covers included rangeland, forest, residential, commercial/industrial, and various types of water. The analysis produced two outputs: acreage estimates with measures of precision, and map-type or photo products of the classification which can be overlaid on maps at specific scales. State-level acreage estimates were obtained and substate-level land cover classification overlays and estimates were generated for selected geographical areas. These products were found to be of potential use in managing land and water resources.

Empirical research on Kano’s model and customer satisfaction

PubMed Central

Lin, Feng-Han; Tsai, Sang-Bing; Lee, Yu-Cheng; Hsiao, Cheng-Fu; Zhou, Jie; Wang, Jiangtao; Shang, Zhiwen

2017-01-01

Products are now developed based on what customers desire, and thus attractive quality creation has become crucial. In studies on customer satisfaction, methods for analyzing quality attributes and enhancing customer satisfaction have been proposed to facilitate product development. Although substantial studies have performed to assess the impact of the attributes on customer satisfaction, little research has been conducted that quantitatively calculate the odds of customer satisfaction for the Kano classification, fitting a nonlinear relationship between attribute-level performance and customer satisfaction. In the present study, the odds of customer satisfaction were determined to identify the classification of quality attributes, and took customer psychology into account to suggest how decision-makers should prioritize the allocation of resources. A novel method for quantitatively assessing quality attributes was proposed to determine classification criteria and fit the nonlinear relationship between quality attributes and customer satisfaction. Subsequently, a case study was conducted on bicycle user satisfaction to verify the novel method. The concept of customer satisfaction odds was integrated with the value function from prospect theory to understand quality attributes. The results of this study can serve as a reference for product designers to create attractive quality attributes in their products and thus enhance customer satisfaction. PMID:28873418

Empirical research on Kano's model and customer satisfaction.

PubMed

Lin, Feng-Han; Tsai, Sang-Bing; Lee, Yu-Cheng; Hsiao, Cheng-Fu; Zhou, Jie; Wang, Jiangtao; Shang, Zhiwen

2017-01-01

Products are now developed based on what customers desire, and thus attractive quality creation has become crucial. In studies on customer satisfaction, methods for analyzing quality attributes and enhancing customer satisfaction have been proposed to facilitate product development. Although substantial studies have performed to assess the impact of the attributes on customer satisfaction, little research has been conducted that quantitatively calculate the odds of customer satisfaction for the Kano classification, fitting a nonlinear relationship between attribute-level performance and customer satisfaction. In the present study, the odds of customer satisfaction were determined to identify the classification of quality attributes, and took customer psychology into account to suggest how decision-makers should prioritize the allocation of resources. A novel method for quantitatively assessing quality attributes was proposed to determine classification criteria and fit the nonlinear relationship between quality attributes and customer satisfaction. Subsequently, a case study was conducted on bicycle user satisfaction to verify the novel method. The concept of customer satisfaction odds was integrated with the value function from prospect theory to understand quality attributes. The results of this study can serve as a reference for product designers to create attractive quality attributes in their products and thus enhance customer satisfaction.

Extruded Bread Classification on the Basis of Acoustic Emission Signal With Application of Artificial Neural Networks

NASA Astrophysics Data System (ADS)

Świetlicka, Izabela; Muszyński, Siemowit; Marzec, Agata

2015-04-01

The presented work covers the problem of developing a method of extruded bread classification with the application of artificial neural networks. Extruded flat graham, corn, and rye breads differening in water activity were used. The breads were subjected to the compression test with simultaneous registration of acoustic signal. The amplitude-time records were analyzed both in time and frequency domains. Acoustic emission signal parameters: single energy, counts, amplitude, and duration acoustic emission were determined for the breads in four water activities: initial (0.362 for rye, 0.377 for corn, and 0.371 for graham bread), 0.432, 0.529, and 0.648. For classification and the clustering process, radial basis function, and self-organizing maps (Kohonen network) were used. Artificial neural networks were examined with respect to their ability to classify or to cluster samples according to the bread type, water activity value, and both of them. The best examination results were achieved by the radial basis function network in classification according to water activity (88%), while the self-organizing maps network yielded 81% during bread type clustering.

Multidrug-resistant bacteria infection and nursing quality management application in the department of physical examination.

PubMed

Xu, Li; Luo, Qiang; Chen, Liangzhen; Jiao, Lingmei

2017-09-01

The main problem of clinical prevention and control of multi drug resistant bacteria infection is to strengthen the monitoring of pathogenic bacteria spectrum, this study research on the multi drug-resistant bacteria infection and nursing quality management application in the department of physical examination. The results of this study showed that the number of patients with multiple drug resistant infections showed an increasing trend. Therefore, once the patients with multiple drug-resistant bacteria infection are found, the prevention and control of the patients with multiple drug-resistant bacteria should be strictly followed, and the patient's medication care should be highly valued. Also, the nurses need to be classified based on the knowledge and skill characteristics of the nurses in the department of physical examination, and compare the nursing effect before and after classification and grouping. The physicians and individuals receiving physical examinations in the department of physical examination had a higher degree of satisfaction for nursing effect after classification compared with those before classification. Classification and grouping management helps improve the nursing quality and overall quality of the nurses in the department of physical examination.

Assessment of Pansharpening Methods Applied to WorldView-2 Imagery Fusion.

PubMed

Li, Hui; Jing, Linhai; Tang, Yunwei

2017-01-05

Since WorldView-2 (WV-2) images are widely used in various fields, there is a high demand for the use of high-quality pansharpened WV-2 images for different application purposes. With respect to the novelty of the WV-2 multispectral (MS) and panchromatic (PAN) bands, the performances of eight state-of-art pan-sharpening methods for WV-2 imagery including six datasets from three WV-2 scenes were assessed in this study using both quality indices and information indices, along with visual inspection. The normalized difference vegetation index, normalized difference water index, and morphological building index, which are widely used in applications related to land cover classification, the extraction of vegetation areas, buildings, and water bodies, were employed in this work to evaluate the performance of different pansharpening methods in terms of information presentation ability. The experimental results show that the Haze- and Ratio-based, adaptive Gram-Schmidt, Generalized Laplacian pyramids (GLP) methods using enhanced spectral distortion minimal model and enhanced context-based decision model methods are good choices for producing fused WV-2 images used for image interpretation and the extraction of urban buildings. The two GLP-based methods are better choices than the other methods, if the fused images will be used for applications related to vegetation and water-bodies.

Assessment of Pansharpening Methods Applied to WorldView-2 Imagery Fusion

PubMed Central

Li, Hui; Jing, Linhai; Tang, Yunwei

2017-01-01

Since WorldView-2 (WV-2) images are widely used in various fields, there is a high demand for the use of high-quality pansharpened WV-2 images for different application purposes. With respect to the novelty of the WV-2 multispectral (MS) and panchromatic (PAN) bands, the performances of eight state-of-art pan-sharpening methods for WV-2 imagery including six datasets from three WV-2 scenes were assessed in this study using both quality indices and information indices, along with visual inspection. The normalized difference vegetation index, normalized difference water index, and morphological building index, which are widely used in applications related to land cover classification, the extraction of vegetation areas, buildings, and water bodies, were employed in this work to evaluate the performance of different pansharpening methods in terms of information presentation ability. The experimental results show that the Haze- and Ratio-based, adaptive Gram-Schmidt, Generalized Laplacian pyramids (GLP) methods using enhanced spectral distortion minimal model and enhanced context-based decision model methods are good choices for producing fused WV-2 images used for image interpretation and the extraction of urban buildings. The two GLP-based methods are better choices than the other methods, if the fused images will be used for applications related to vegetation and water-bodies. PMID:28067770

The Influence of temporal sampling regime on the WFD classification of catchments within the Eden Demonstration Test Catchment Project

NASA Astrophysics Data System (ADS)

Jonczyk, Jennine; Haygarth, Phil; Quinn, Paul; Reaney, Sim

2014-05-01

A high temporal resolution data set from the Eden Demonstration Test Catchment (DTC) project is used to investigate the processes causing pollution and the influence of temporal sampling regime on the WFD classification of three catchments. This data highlights WFD standards may not be fit for purpose. The Eden DTC project is part of a UK government-funded project designed to provide robust evidence regarding how diffuse pollution can be cost-effectively controlled to improve and maintain water quality in rural river catchments. The impact of multiple water quality parameters on ecosystems and sustainable food production are being studied at the catchment scale. Three focus catchments approximately 10 km2 each, have been selected to represent the different farming practices and geophysical characteristics across the Eden catchment, Northern England. A field experimental programme has been designed to monitor the dynamics of agricultural diffuse pollution at multiple scales using state of the art sensors providing continuous real time data. The data set, which includes Total Phosphorus and Total Reactive Phosphorus, Nitrate, Ammonium, pH, Conductivity, Turbidity and Chlorophyll a reveals the frequency and duration of nutrient concentration target exceedance which arises from the prevalence of storm events of increasing magnitude. This data set is sub-sampled at different time intervals to explore how different sampling regimes affects our understanding of nutrient dynamics and the ramification of the different regimes to WFD chemical status. This presentation seeks to identify an optimum temporal resolution of data for effective catchment management and to question the usefulness of the WFD status metric for determining health of a system. Criteria based on high frequency short duration events needs to be accounted for.

Overview of groundwater management approaches at salinisation risk

NASA Astrophysics Data System (ADS)

Polemio, Maurizio; Zuffianò, Livia Emanuela

2013-04-01

All natural waters contain dissolved minerals from interactions with atmospheric and soil gases, mixing with other solutions, and/or interactions with the biosphere and lithosphere. In many cases, these processes result in natural waters containing solute or salinity above concentrations recommended for a specified use, which creates significant social and economic problems. Groundwater salinisation can be caused by natural phenomena and anthropogenic activities. For the former case, we can distinguish terrestrial and marine phenomena. Approximately 16% of the total area of continental earth is potentially involved in groundwater salinisation. Seawater intrusion can be considered to be the primary phenomenon to be studied in terms of groundwater salinisation. Three schematic approaches to the protection of groundwater via salinisation mitigation and/or groundwater salinity improvement are described based on the classifications of the primary salinisation sources and focusing on the effect of seawater intrusion. The complexity of these approaches generally increases due to difficulties caused by groundwater quality and quantity degradation and increased demand for quality water. In order from the lowest to the highest complexity, these approaches are the engineering approach, the discharge management approach, and the water and land management approach. The engineering approach is realised on the local or detailed scale with the purpose of controlling the salinisation, optimising the well discharge with specific technical solutions and/or completing works to improve the quality and/or quantity of the discharged fresh groundwater. The discharge management approach encompasses at least an entire coastal aquifer and defines rules concerning groundwater utilisation and well discharge. The water and land management approach should be applied on the regional scale. Briefly, this approach becomes necessary when one or more need creates an overall framework of high-quality water scarcity. These conditions, sometimes combined with an awareness of negative environmental effects, force people to accept new water saving practices and land use modifications. As the natural effects of salinisation can be enhanced by a multiplicity of human actions, the discharge management approach and the water and land management approach should generally be applied by water authorities or institutional and governmental organisations that are responsible for groundwater quality and availability. The practical study of Apulian karstic coastal aquifers is discussed in detail. Previously experienced management difficulties are described, as well as a proposed multi-methodological approach based on monitoring networks, the spatiotemporal analysis of groundwater quality changes, and multiparameter well logging. The core of this approach is the definition of the salinity threshold value between pure fresh groundwater and any fresh and saline groundwater mixture. The basic or single tools were defined to be simple, quick and cost-effective to be applicable to the widest range of situations.

Land use change and effects on water quality and ecosystem health in the Lake Tahoe basin, Nevada and California: year-1 progress

USGS Publications Warehouse

Forney, William; Raumann, Christian G.; Minor, T.B.; Smith, J. LaRue; Vogel, John; Vitales, Robert

2002-01-01

As part of the requirements for the Geographic Research and Applications Prospectus grants, this Open-File Report is the second of two that resulted from the first year of the project. The first Open-File Report (OFR 01-418) introduced the project, reviewed the existing body of literature, and outlined the research approach. This document will present an update of the research approach and offer some preliminary results from multiple efforts, specifically, the production of historical digital orthophoto quadrangles, the development of the land use/land cover (LULC) classification system, the development of a temporal transportation layer, the classification of anthropogenic cover types from the IKONOS imagery, a preliminary evaluation of landscape ecology metrics (quantification of spatial and temporal patterns of ecosystem structure and function with appropriate indices) and their utility in comparing two LULC systems, and a new initiative in community-based science and facilitation.

40 CFR 52.1971 - Classification of regions.

Code of Federal Regulations, 2014 CFR

2014-07-01

... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS (CONTINUED) Oregon § 52.1971 Classification of regions. The Oregon plan was evaluated on the basis of the following classifications: Air quality control... Interstate I IA III I I Southwest Oregon Intrastate II III III III III Northwest Oregon Intrastate III III...

40 CFR 52.1971 - Classification of regions.

Code of Federal Regulations, 2013 CFR

2013-07-01

... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS (CONTINUED) Oregon § 52.1971 Classification of regions. The Oregon plan was evaluated on the basis of the following classifications: Air quality control... Interstate I IA III I I Southwest Oregon Intrastate II III III III III Northwest Oregon Intrastate III III...

77 FR 20503 - Revision of Cotton Classification Procedures for Determining Cotton Leaf Grade

Federal Register 2010, 2011, 2012, 2013, 2014

2012-04-05

...-AD19 Revision of Cotton Classification Procedures for Determining Cotton Leaf Grade AGENCY... amending the procedures for determining the official leaf grade for Upland and Pima cotton. The leaf grade is a part of the official classification which denotes cotton fiber quality used in cotton marketing...

40 CFR 52.221 - Classification of regions.

Code of Federal Regulations, 2013 CFR

2013-07-01

... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS California § 52.221 Classification of regions. The California plan was evaluated on the basis of the following classifications: Air quality control... III III III Southeast Desert Intrastate I III III III I San Diego Intrastate II III III I I Lake...

40 CFR 52.221 - Classification of regions.

Code of Federal Regulations, 2012 CFR

2012-07-01

... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS California § 52.221 Classification of regions. The California plan was evaluated on the basis of the following classifications: Air quality control... III III III Southeast Desert Intrastate I III III III I San Diego Intrastate II III III I I Lake...

40 CFR 52.221 - Classification of regions.

Code of Federal Regulations, 2014 CFR

2014-07-01

... (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS California § 52.221 Classification of regions. The California plan was evaluated on the basis of the following classifications: Air quality control... III III III Southeast Desert Intrastate I III III III I San Diego Intrastate II III III I I Lake...

75 FR 78213 - Proposed Information Collection; Comment Request; 2012 Economic Census Classification Report for...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-12-15

... Economic Census Classification Report for the Construction, Manufacturing, and Mining Sectors and Selected... quality data describing the people and economy of the United States. Economic data are the Census Bureau's..., business, and the general public. The Economic Census Classification Report (NC-99026) collects data on...

Mapping bare soil in South West Wales, UK, using high resolution colour infra-red aerial photography for water quality and flood risk management applications

NASA Astrophysics Data System (ADS)

Sykes, Helena; Neale, Simon; Coe, Sarah

2016-04-01

Natural Resources Wales is a UK government body responsible for environmental regulation, among other areas. River walks in Water Framework Directive (WFD) priority catchments in South West Wales, UK, identified soil entering water courses due to poaching and bank erosion, leading to deterioration in the water quality and jeopardising the water quality meeting legal minimum standards. Bare soil has also been shown to cause quicker and higher hydrograph peaks in rural catchments than if those areas were vegetated, which can lead to flooding of domestic properties during peak storm flows. The aim was to target farm visits by operational staff to advise on practices likely to improve water quality and to identify areas where soft engineering solutions such as revegetation could alleviate flood risk in rural areas. High resolution colour-infrared aerial photography, 25cm in the three colour bands and 50cm in the near infrared band, was used to map bare soil in seven catchments using supervised classification of a five band stack including the Normalised Difference Vegetation Index (NDVI). Mapping was combined with agricultural land use and field boundary data to filter out arable fields, which are supposed to bare soil for part of their cycle, and was very successful when compared to ground truthing, with the exception of silage fields which contained sparse, no or unproductive vegetation at the time the imagery was acquired leading to spectral similarity to bare soil. A raindrop trace model was used to show the path sediment from bare soil areas would take when moving through the catchment to a watercourse, with hedgerows inserted as barriers following our observations from ground truthing. The findings have been used to help farmers gain funding for improvements such as fencing to keep animals away from vulnerable river banks. These efficient and automated methods can be rolled out to more catchments in Wales and updated using aerial imagery acquired more recently to examine the effects of change.

Comparing the MRI-based Goutallier Classification to an experimental quantitative MR spectroscopic fat measurement of the supraspinatus muscle.

PubMed

Gilbert, Fabian; Böhm, Dirk; Eden, Lars; Schmalzl, Jonas; Meffert, Rainer H; Köstler, Herbert; Weng, Andreas M; Ziegler, Dirk

2016-08-22

The Goutallier Classification is a semi quantitative classification system to determine the amount of fatty degeneration in rotator cuff muscles. Although initially proposed for axial computer tomography scans it is currently applied to magnet-resonance-imaging-scans. The role for its clinical use is controversial, as the reliability of the classification has been shown to be inconsistent. The purpose of this study was to compare the semi quantitative MRI-based Goutallier Classification applied by 5 different raters to experimental MR spectroscopic quantitative fat measurement in order to determine the correlation between this classification system and the true extent of fatty degeneration shown by spectroscopy. MRI-scans of 42 patients with rotator cuff tears were examined by 5 shoulder surgeons and were graduated according to the MRI-based Goutallier Classification proposed by Fuchs et al. Additionally the fat/water ratio was measured with MR spectroscopy using the experimental SPLASH technique. The semi quantitative grading according to the Goutallier Classification was statistically correlated with the quantitative measured fat/water ratio using Spearman's rank correlation. Statistical analysis of the data revealed only fair correlation of the Goutallier Classification system and the quantitative fat/water ratio with R = 0.35 (p < 0.05). By dichotomizing the scale the correlation was 0.72. The interobserver and intraobserver reliabilities were substantial with R = 0.62 and R = 0.74 (p < 0.01). The correlation between the semi quantitative MRI based Goutallier Classification system and MR spectroscopic fat measurement is weak. As an adequate estimation of fatty degeneration based on standard MRI may not be possible, quantitative methods need to be considered in order to increase diagnostic safety and thus provide patients with ideal care in regard to the amount of fatty degeneration. Spectroscopic MR measurement may increase the accuracy of the Goutallier classification and thus improve the prediction of clinical results after rotator cuff repair. However, these techniques are currently only available in an experimental setting.

On-line classification of pollutants in water using wireless portable electronic noses.

PubMed

Herrero, José Luis; Lozano, Jesús; Santos, José Pedro; Suárez, José Ignacio

2016-06-01

A portable electronic nose with database connection for on-line classification of pollutants in water is presented in this paper. It is a hand-held, lightweight and powered instrument with wireless communications capable of standalone operation. A network of similar devices can be configured for distributed measurements. It uses four resistive microsensors and headspace as sampling method for extracting the volatile compounds from glass vials. The measurement and control program has been developed in LabVIEW using the database connection toolkit to send the sensors data to a server for training and classification with Artificial Neural Networks (ANNs). The use of a server instead of the microprocessor of the e-nose increases the capacity of memory and the computing power of the classifier and allows external users to perform data classification. To address this challenge, this paper also proposes a web-based framework (based on RESTFul web services, Asynchronous JavaScript and XML and JavaScript Object Notation) that allows remote users to train ANNs and request classification values regardless user's location and the type of device used. Results show that the proposed prototype can discriminate the samples measured (Blank water, acetone, toluene, ammonia, formaldehyde, hydrogen peroxide, ethanol, benzene, dichloromethane, acetic acid, xylene and dimethylacetamide) with a 94% classification success rate. Copyright © 2016 Elsevier Ltd. All rights reserved.

Comparability of river quality assessment using macrophytes: a multi-step procedure to overcome biogeographical differences.

PubMed

Aguiar, F C; Segurado, P; Urbanič, G; Cambra, J; Chauvin, C; Ciadamidaro, S; Dörflinger, G; Ferreira, J; Germ, M; Manolaki, P; Minciardi, M R; Munné, A; Papastergiadou, E; Ferreira, M T

2014-04-01

This paper exposes a new methodological approach to solve the problem of intercalibrating river quality national methods when a common metric is lacking and most of the countries share the same Water Framework Directive (WFD) assessment method. We provide recommendations for similar works in future concerning the assessment of ecological accuracy and highlight the importance of a good common ground to make feasible the scientific work beyond the intercalibration. The approach herein presented was applied to highly seasonal rivers of the Mediterranean Geographical Intercalibration Group for the Biological Quality Element Macrophytes. The Mediterranean Group of river macrophytes involved seven countries and two assessment methods with similar acquisition data and assessment concept: the Macrophyte Biological Index for Rivers (IBMR) for Cyprus, France, Greece, Italy, Portugal and Spain, and the River Macrophyte Index (RMI) for Slovenia. Database included 318 sites of which 78 were considered as benchmarks. The boundary harmonization was performed for common WFD-assessment methods (all countries except Slovenia) using the median of the Good/Moderate and High/Good boundaries of all countries. Then, whenever possible, the Slovenian method, RMI was computed for the entire database. The IBMR was also computed for the Slovenian sites and was regressed against RMI in order to check the relatedness of methods (R(2)=0.45; p<0.00001) and to convert RMI boundaries into the IBMR scale. The boundary bias of RMI was computed using direct comparison of classification and the median boundary values following boundary harmonization. The average absolute class differences after harmonization is 26% and the percentage of classifications differing by half of a quality class is also small (16.4%). This multi-step approach to the intercalibration was endorsed by the WFD Regulatory Committee. © 2013 Elsevier B.V. All rights reserved.

Environmental study of ERTS-1 imagery Lake Champlain Basin and Vermont

NASA Technical Reports Server (NTRS)

Lind, A. O. (Principal Investigator)

1972-01-01

The author has idenfified the following significant results. A first approximation land-type map using three categories of classification was generated for the Burlington area. The identification and mapping of a major turbidity front separating turbid waters of the southern arm of Lake Champlain from the clearer main water mass was reported on RBV 1 and 2 imagery and on subsequent MSS bands 4 and 5. Significant industrial pollution of Lake Champlain has degraded environmental quality in certain sections of the lake. Wetlands were detected and recognized using a combination of RBV bands 2 and 3. Using first-look RBV band 2 imagery, major ice marginal features were identified by using tonal patterns associated with vegetative cover. Major rivers were detected and recognized through the use of RBV band 3 imagery and MSS bands 6 and 7.

Investigation of Pharmaceutical Residues in Hospital Effluents, in Ground- and Drinking Water from Bundeswehr Facilities, and their Removal During Drinking Water Purification (Arzneimittelrueckstaende in Trinkwasser(versorgungsanlagen) und Krankenhausabwaessern der Bundeswehr: Methodenentwicklung - Verkommen - Wasseraufbereitung)

DTIC Science & Technology

1999-11-01

Drinking water processing plant , Analysis, Calculation model, Field experiment 16. PRICE CODE 17. SECURITY CLASSIFICATION 18. SECURITY CLASSIFICATION...sewage effluents and from the sewer of the municipal sewage treatment plant in Berlin-Ruhleben. In the field trials, the MDWPUs that both apply reverse...waste water samples, along the municipal sewer system and In the influents and effluents of the receiving sewage treatment plants . To estimate the

PPS GPS: What Is It? And How Do I Get It

DTIC Science & Technology

1994-06-01

Positioning Service, Selective Availabilit B.PRICE CODIE 17. SECURITY CLASSIFICATION II. SECURITY CLASSIFICATION 19. SECURITY CLASSIFICATION 20...the TEC Water Detection Response Team which operates in remote areas of the world. These activities, require the GPS receiver to be capable of removing

Water-quality characteristics of selected public recreational lakes and ponds in Connecticut

USGS Publications Warehouse

Healy, D.F.; Kulp, K.P.

1995-01-01

Reconnaissance limnological and lakebed-sediment surveys were conducted in Connecticut during 1989-91 by the U.S. Geological Survey, in cooperation with the Connecticut Department of Environmental Protec- tion, to evaluate water-quality characteristics of selected public recreational lakes and ponds in the State. Limnological surveys were conducted on 49 lakes and ponds selected from a list of 105 publicly owned waterbodies that qualified for water- quality assessments under Section 314 of the Federal Clean Water Act. Lakebed-sediment surveys were conducted in 9 river impoundments and 1 riverine lake below industrial areas and 2 headwater lakes in relatively pristine areas. The limnological surveys consisted of two sampling events--during spring turnover and during the summer stratifi- cation. Each sampling event included depth profiles of water temperature, specific conductance, hydrogen-ion activity, and dissolved oxygen concen- trations; measurements of Secchi disc transparency; and the collection of samples for the analyses of alkalinity, chlorophyll, phosphorus, and nitrogen concentrations. Areal extent and population density of the dominant aquatic macrophytes were qualita- tively noted during the summer sampling event. These water-quality data were used to determine the trophic classification and acidification status of the 49 lakes. The trophic classification yielded the following results: 2 oligotrophic, 8 early mesotrophic, 13 mesotrophic, 5 late mesotrophic, 10 eutrophic, and 11 highly eutrophic lakes. In terms of acidification status, 7 lakes were classified as acid threatened and 42 as not threatened. A Wilcoxon two-tailed signed rank test was used to compare data for 13 lakes and ponds from the present survey with data from the 1973-75 or 1978-79 surveys conducted by the Connecticut Agricultural Experiment Station and Connecticut Department of Environmental Protection. The test showed no significant difference at the 90 percent confidence level for spring nitrogen and summer chlorophyll-a concen- trations, a significant increase at the 90 percent confidence level in summer phosphorus concentra- tions, and a significant decrease at the 95 percent confidence level in summer transparency. For the lakebed-sediment surveys, composite-grab samples were collected from the deepest part of each lake. Samples were analyzed for arsenic, cyanide, organic and inorganic carbon, selected metals, and methylene-extractable, synthetic organic compounds classified by the U.S. Environmental Protection Agency as semi-volatile priority pollutants. Hanover Pond, Eagleville Lake, and West Thompson Lake had three of the four highest concentrations of cadmium, chromium, copper, lead, nickel, zinc, and cyanide. The four lakes with the highest concentrations of arsenic (Aspinook Pond, Fitchville Pond, Mashapaug Pond, and West Thompson Lake) are located in the eastern part of Connecticut. The three samples with the highest mercury concentrations were from Lake Lillinonah and Lake Zoar. There appears to be a positive correlation between the concentrations of cadmium, chromium, copper, lead, nickel, zinc, and cyanide. Only 15 of the 54 synthetic organic compounds analyzed for were detected in 9 of the 12 lakes sampled. Of these 15 compounds, 14 are polycyclic aromatic hydrocarbons and the 15th is a phthalate ester. Hanover Pond had the most compounds detected (9), and phenanthrene was the compound detected in the most lakes (8).

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gardner, S.

Louisiana, now in a developmental stage of policy and planning, has completed a project aimed at reducing hazardous releases of air toxics in thee state. The state is also conducting a Comparative Risk Project and is using risk assessment practices to develop its waste quality standards. In developing an air toxic list, Louisiana incorporated four major criteria into the ranking: emission levels, human health effects, potential population exposure, and persistence or accumulation in the environment. For the human health effects criterion, data for each substance was gathered from numerous sources, although the Integrated Risk Information System (IRIS) database was usedmore » as a primary source for toxicological information. Following guidelines established by the Environmental Protection Agency (EPA), the Office of Water Resources, Water Pollution Control Division, has developed numerical criteria for human health protection based on risk assessment procedures in the 1989 Water Quality Standards Revision. Currently over 30 toxic substances have risk-based criteria for th protection of human health in the standards. Numerical criteria were calculated for carcinogenic substances having an EPA Classification of A, B1, B2, or C. Cancer class designations along with cancer potency slopes and reference doses were extracted from the IRIS database, with the exception of those chemicals that had not been assessed in IRIS as of December 1, 1988. The parameters necessary for calculating human health criteria for the missing chemicals were taken from 1980, 1984, and 1985 ambient water quality criteria documents: data on bioconcentration factors were included. Currently, Louisiana is working on a Comparative Risk Project, a ranking of the environmental issues in the state relative to potential risk to the public, which is the basis for a widespread 1991 public outreach effort.« less

A pragmatic approach to study the groundwater quality suitability for domestic and agricultural usage, Saq aquifer, northwest of Saudi Arabia.

PubMed

Nazzal, Yousef; Ahmed, Izrar; Al-Arifi, Nassir S N; Ghrefat, Habes; Zaidi, Faisal K; El-Waheidi, Mahmud M; Batayneh, Awni; Zumlot, Taisser

2014-08-01

The present study deals with detailed hydrochemical assessment of groundwater within the Saq aquifer. The Saq aquifer which extends through the NW part of Saudi Arabia is one of the major sources of groundwater supply. Groundwater samples were collected from about 295 groundwater wells and analyzed for various physico-chemical parameters such as electrical conductivity (EC), pH, temperature, total dissolved solids (TDS), Na(+), K(+), Ca(2+), Mg(2+), CO3 (-), HCO3 (-), Cl(-), SO4 (2-), and NO3 (-). Groundwater in the area is slightly alkaline and hard in nature. Electrical conductivity (EC) varies between 284 and 9,902 μS/cm with an average value of 1,599.4 μS/cm. The groundwater is highly mineralized with approximately 30 % of the samples having major ion concentrations above the WHO permissible limits. The NO3 (-) concentration varies between 0.4 and 318.2 mg/l. The depth distribution of NO3 (-) concentration shows higher concentration at shallow depths with a gradual decrease at deeper depths. As far as drinking water quality criteria are concerned, study shows that about 33 % of samples are unfit for use. A detailed assessment of groundwater quality in relation to agriculture use reveals that 21 % samples are unsuitable for irrigation. Using Piper's classification, groundwater was classified into five different groups. Majority of the samples show Mix-Cl-SO4- and Na-Cl-types water. The abundances of Ca(2+) and Mg(2+) over alkalis infer mixed type of groundwater facies and reverse exchange reactions. The groundwater has acquired unique chemical characteristics through prolonged rock-water interactions, percolation of irrigation return water, and reactions at vadose zone.

Stormwater harvesting from landscaped areas: effect of herbicide application on water quality and usage.

PubMed

Mbanaso, F U; Nnadi, E O; Coupe, S J; Charlesworth, S M

2016-08-01

The suitability of stormwater harvested from pervious pavement system (PPS) structures for reuse purposes was investigated in conditions where glyphosate-containing herbicides (GCH) are applied as part of PPS maintenance procedure. The experiment was based on the four-layered design previously described as detailed in CIRIA C582. Results indicated that the highest sodium absorption ratio (SAR) of 1.6 recorded in this study, was less than that at which loss of permeability begins to occur as well as deterioration of matrix structure. Furthermore, the maximum electrical conductivity (ECw) of 2990 μS cm(-1), recorded for 7200 mg L(-1) concentration (GCH) was slightly below the unstable classification range at which salinity problems related to water quality occur such that salts accumulate in the root zone to the extent that crop yields are adversely affected. However, GCH concentration of 720 mg L(-1) was within 'permissible' range while that of 72 mg L(-1) was within 'excellent' range. Current study raises some environmental concerns owing to the overall impact that GCH at concentrations above 72 mg L(-1) exerts on the net performance of the organic decomposers, heavy metal and hydrocarbon release from the system and thus, should be further investigated. However, effluent from all the test models including those dosed with high GCH concentration of 7200 mg L(-1) do not pose any threat in terms of infiltration or deterioration associated with salinity although, there are indications that high dosage of the herbicide could lead to an elevated electrical conductivity of the recycled water. Graphical abstract Impact of herbicide on irrigation water quality.

True colour classification of natural waters with medium-spectral resolution satellites: SeaWiFS, MODIS, MERIS and OLCI.

PubMed

Woerd, Hendrik J van der; Wernand, Marcel R

2015-10-09

The colours from natural waters differ markedly over the globe, depending on the water composition and illumination conditions. The space-borne "ocean colour" instruments are operational instruments designed to retrieve important water-quality indicators, based on the measurement of water leaving radiance in a limited number (5 to 10) of narrow (≈10 nm) bands. Surprisingly, the analysis of the satellite data has not yet paid attention to colour as an integral optical property that can also be retrieved from multispectral satellite data. In this paper we re-introduce colour as a valuable parameter that can be expressed mainly by the hue angle (α). Based on a set of 500 synthetic spectra covering a broad range of natural waters a simple algorithm is developed to derive the hue angle from SeaWiFS, MODIS, MERIS and OLCI data. The algorithm consists of a weighted linear sum of the remote sensing reflectance in all visual bands plus a correction term for the specific band-setting of each instrument. The algorithm is validated by a set of 603 hyperspectral measurements from inland-, coastal- and near-ocean waters. We conclude that the hue angle is a simple objective parameter of natural waters that can be retrieved uniformly for all space-borne ocean colour instruments.

Mapping shallow waters habitats using OBIA by applying several approaches of depth invariant index in North Kepulauan Seribu

NASA Astrophysics Data System (ADS)

Siregar, V. P.; Agus, S. B.; Subarno, T.; Prabowo, N. W.

2018-05-01

The availability of satellite imagery with a variety of spatial resolution, both free access and commercial become as an option in utilizing the remote sensing technology. Variability of the water column is one of the factors affecting the interpretation results when mapping marine shallow waters. This study aimed to evaluate the influence of water column correction (depth-invariant index) on the accuracy of shallow water habitat classification results using OBIA. This study was conducted in North of Kepulauan Seribu, precisely in Harapan Island and its surrounding areas. Habitat class schemes were based on field observations, which were then used to build habitat classes on satellite imagery. The water column correction was applied to the three pairs of SPOT-7 multispectral bands, which were subsequently used in object-based classification. Satellite image classification was performed with four different approaches, namely (i) using DII transformed bands with single pair band input (B1B2), (ii) multi pairs bands (B1B2, B1B3, and B2B3), (iii) combination of multi pairs band and initial bands, and (iv) only using initial bands. The accuracy test results of the four inputs show the values of Overall Accuracy and Kappa Statistics, respectively 55.84 and 0.48; 68.53 and 0.64; 78.68 and 0.76; 77.66 and 0.74. It shows that the best results when using DII and initial band combination for shallow water benthic classification in this study site.

Topobathymetric LiDAR point cloud processing and landform classification in a tidal environment

NASA Astrophysics Data System (ADS)

Skovgaard Andersen, Mikkel; Al-Hamdani, Zyad; Steinbacher, Frank; Rolighed Larsen, Laurids; Brandbyge Ernstsen, Verner

2017-04-01

Historically it has been difficult to create high resolution Digital Elevation Models (DEMs) in land-water transition zones due to shallow water depth and often challenging environmental conditions. This gap of information has been reflected as a "white ribbon" with no data in the land-water transition zone. In recent years, the technology of airborne topobathymetric Light Detection and Ranging (LiDAR) has proven capable of filling out the gap by simultaneously capturing topographic and bathymetric elevation information, using only a single green laser. We collected green LiDAR point cloud data in the Knudedyb tidal inlet system in the Danish Wadden Sea in spring 2014. Creating a DEM from a point cloud requires the general processing steps of data filtering, water surface detection and refraction correction. However, there is no transparent and reproducible method for processing green LiDAR data into a DEM, specifically regarding the procedure of water surface detection and modelling. We developed a step-by-step procedure for creating a DEM from raw green LiDAR point cloud data, including a procedure for making a Digital Water Surface Model (DWSM) (see Andersen et al., 2017). Two different classification analyses were applied to the high resolution DEM: A geomorphometric and a morphological classification, respectively. The classification methods were originally developed for a small test area; but in this work, we have used the classification methods to classify the complete Knudedyb tidal inlet system. References Andersen MS, Gergely Á, Al-Hamdani Z, Steinbacher F, Larsen LR, Ernstsen VB (2017). Processing and performance of topobathymetric lidar data for geomorphometric and morphological classification in a high-energy tidal environment. Hydrol. Earth Syst. Sci., 21: 43-63, doi:10.5194/hess-21-43-2017. Acknowledgements This work was funded by the Danish Council for Independent Research | Natural Sciences through the project "Process-based understanding and prediction of morphodynamics in a natural coastal system in response to climate change" (Steno Grant no. 10-081102) and by the Geocenter Denmark through the project "Closing the gap! - Coherent land-water environmental mapping (LAWA)" (Grant no. 4-2015).

[LiLa classification for paediatric long bone fractures. Intraobserver and interobserver reliability].

PubMed

Kamphaus, A; Rapp, M; Wessel, L M; Buchholz, M; Massalme, E; Schneidmüller, D; Roeder, C; Kaiser, M M

2015-04-01

There are two child-specific fracture classification systems for long bone fractures: the AO classification of pediatric long-bone fractures (PCCF) and the LiLa classification of pediatric fractures of long bones (LiLa classification). Both are still not widely established in comparison to the adult AO classification for long bone fractures. During a period of 12 months all long bone fractures in children were documented and classified according to the LiLa classification by experts and non-experts. Intraobserver and interobserver reliability were calculated according to Cohen (kappa). A total of 408 fractures were classified. The intraobserver reliability for location in the skeletal and bone segment showed an almost perfect agreement (K = 0.91-0.95) and also the morphology (joint/shaft fracture) (K = 0.87-0.93). Due to different judgment of the fracture displacement in the second classification round, the intraobserver reliability of the whole classification revealed moderate agreement (K = 0.53-0.58). Interobserver reliability showed moderate agreement (K = 0.55) often due to the low quality of the X-rays. Further differences occurred due to difficulties in assigning the precise transition from metaphysis to diaphysis. The LiLa classification is suitable and in most cases user-friendly for classifying long bone fractures in children. Reliability is higher than in established fracture specific classifications and comparable to the AO classification of pediatric long bone fractures. Some mistakes were due to a low quality of the X-rays and some due to difficulties to classify the fractures themselves. Improvements include a more precise definition of the metaphysis and the kind of displacement. Overall the LiLa classification should still be considered as an alternative for classifying pediatric long bone fractures.

Study on Classification Accuracy Inspection of Land Cover Data Aided by Automatic Image Change Detection Technology

NASA Astrophysics Data System (ADS)

Xie, W.-J.; Zhang, L.; Chen, H.-P.; Zhou, J.; Mao, W.-J.

2018-04-01

The purpose of carrying out national geographic conditions monitoring is to obtain information of surface changes caused by human social and economic activities, so that the geographic information can be used to offer better services for the government, enterprise and public. Land cover data contains detailed geographic conditions information, thus has been listed as one of the important achievements in the national geographic conditions monitoring project. At present, the main issue of the production of the land cover data is about how to improve the classification accuracy. For the land cover data quality inspection and acceptance, classification accuracy is also an important check point. So far, the classification accuracy inspection is mainly based on human-computer interaction or manual inspection in the project, which are time consuming and laborious. By harnessing the automatic high-resolution remote sensing image change detection technology based on the ERDAS IMAGINE platform, this paper carried out the classification accuracy inspection test of land cover data in the project, and presented a corresponding technical route, which includes data pre-processing, change detection, result output and information extraction. The result of the quality inspection test shows the effectiveness of the technical route, which can meet the inspection needs for the two typical errors, that is, missing and incorrect update error, and effectively reduces the work intensity of human-computer interaction inspection for quality inspectors, and also provides a technical reference for the data production and quality control of the land cover data.

Quality grading of Atlantic salmon (Salmo salar) by computer vision.

PubMed

Misimi, E; Erikson, U; Skavhaug, A

2008-06-01

In this study, we present a promising method of computer vision-based quality grading of whole Atlantic salmon (Salmo salar). Using computer vision, it was possible to differentiate among different quality grades of Atlantic salmon based on the external geometrical information contained in the fish images. Initially, before the image acquisition, the fish were subjectively graded and labeled into grading classes by a qualified human inspector in the processing plant. Prior to classification, the salmon images were segmented into binary images, and then feature extraction was performed on the geometrical parameters of the fish from the grading classes. The classification algorithm was a threshold-based classifier, which was designed using linear discriminant analysis. The performance of the classifier was tested by using the leave-one-out cross-validation method, and the classification results showed a good agreement between the classification done by human inspectors and by the computer vision. The computer vision-based method classified correctly 90% of the salmon from the data set as compared with the classification by human inspector. Overall, it was shown that computer vision can be used as a powerful tool to grade Atlantic salmon into quality grades in a fast and nondestructive manner by a relatively simple classifier algorithm. The low cost of implementation of today's advanced computer vision solutions makes this method feasible for industrial purposes in fish plants as it can replace manual labor, on which grading tasks still rely.

[Water resource quality as related to economic activity and health patterns in Sonora, Mexico].

PubMed

Manzanares Rivera, José Luis

2016-01-01

The aim of this work is to analyze the spatial distribution of potential pollution pathways of water resources given the economic activity in the Mexican border state of Sonora and propose a regional distribution in relation to cancer mortality rates across the state. The methodology is based in an exploratory and inferential data analysis using two sources of primary data: wastewater discharge concessions registered in the Public Registry on Water Rights [Registro Público de Derechos de Agua] (REPDA) and the records generated by the National Health Information System [Sistema Nacional de Información en Salud] (SINAIS) in the period 1998-2011 based on the International Classification of Disease (ICD-10). The spatial concentration analysis allows for the identification of specific cancer mortality causes at the regional level. Results indicate that the projected adjustments to the regulation NOM-250-SSA1-2014, which controls a subset of pollutants common in mining activity surroundings, is a matter of regional concern.

Advanced Land Use Classification for Nigeriasat-1 Image of Lake Chad Basin

NASA Astrophysics Data System (ADS)

Babamaaji, R.; Park, C.; Lee, J.

2009-12-01

Lake Chad is a shrinking freshwater lake that has been significantly reduced to about 1/20 of its original size in the 1960’s. The severe draughts in 1970’s and 1980’s and following overexploitations of water resulted in the shortage of surface water in the lake and the surrounding rivers. Ground water resources are in scarcity too as ground water recharge is mostly made by soil infiltration through soil and land cover, but this surface cover is now experiencing siltation and expansion of wetland with invasive species. Large changes in land use and water management practices have taken place in the last 50 years including: removal of water from river systems for irrigation and consumption, degradation of forage land by overgrazing, deforestation, replacing natural ecosystems with mono-cultures, and construction of dams. Therefore, understanding the change of land use and its characteristics must be a first step to find how such changes disturb the water cycle around the lake and affect the shrinkage of the lake. Before any useful thematic information can be extracted from remote sensing data, a land cover classification system has to be developed to obtain the classes of interest. A combination of classification systems used by Global land cover, Water Resources eAtlass and Lake Chad Basin Commission gave rise to 7 land cover classes comprising of - Cropland, vegetation, grassland, water body, shrub-land, farmland ( mostly irrigated) and bareland (i.e. clear land). Supervised Maximum likelihood classification method was used with 15 reference points per class chosen. At the end of the classification, the overall accuracy is 93.33%. Producer’s accuracy for vegetation is 40% compare to the user’s accuracy that is 66.67 %. The reason is that the vegetation is similar to shrub land, it is very hard to differentiate between the vegetation and other plants, and therefore, most of the vegetation is classified as shrub land. Most of the waterbodies are occupied by vegetation and other plant, therefore it can only be well identify if producer is present or using high resolution image, which is shown in the accuracy result of water for both producer and user (66.67%).

76 FR 80278 - Revision of Cotton Classification Procedures for Determining Cotton Leaf Grade

Federal Register 2010, 2011, 2012, 2013, 2014

2011-12-23

...-0066] RIN 0581-AD19 Revision of Cotton Classification Procedures for Determining Cotton Leaf Grade... Pima cotton. The leaf grade is a part of the official classification which denotes cotton fiber quality used in cotton marketing and manufacturing of cotton products. Currently, the leaf grade is determined...

Significance of perceptually relevant image decolorization for scene classification

NASA Astrophysics Data System (ADS)

Viswanathan, Sowmya; Divakaran, Govind; Soman, Kutti Padanyl

2017-11-01

Color images contain luminance and chrominance components representing the intensity and color information, respectively. The objective of this paper is to show the significance of incorporating chrominance information to the task of scene classification. An improved color-to-grayscale image conversion algorithm that effectively incorporates chrominance information is proposed using the color-to-gray structure similarity index and singular value decomposition to improve the perceptual quality of the converted grayscale images. The experimental results based on an image quality assessment for image decolorization and its success rate (using the Cadik and COLOR250 datasets) show that the proposed image decolorization technique performs better than eight existing benchmark algorithms for image decolorization. In the second part of the paper, the effectiveness of incorporating the chrominance component for scene classification tasks is demonstrated using a deep belief network-based image classification system developed using dense scale-invariant feature transforms. The amount of chrominance information incorporated into the proposed image decolorization technique is confirmed with the improvement to the overall scene classification accuracy. Moreover, the overall scene classification performance improved by combining the models obtained using the proposed method and conventional decolorization methods.

Application of LANDSAT system for improving methodology for inventory and classification of wetlands

NASA Technical Reports Server (NTRS)

Gilmer, D. S. (Principal Investigator)

1976-01-01

The author has identified the following significant results. A newly developed software system for generating statistics on surface water features was tested using LANDSAT data acquired previous to 1975. This software test provided a satisfactory evaluation of the system and also allowed expansion of data base on prairie water features. The software system recognizes water on the basis of a classification algorithm. This classification is accomplished by level thresholding a single near infrared data channel. After each pixel is classified as water or nonwater, the software system then recognizes ponds or lakes as sets of contiguous pixels or as single isolated pixels in the case of very small ponds. Pixels are considered to be contiguous if they are adjacent between successive scan lines. After delineating each water feature, the software system then assigns the feature a position based upon a geographic grid system and calculates the feature's planimetric area, its perimeter, and a parameter known as the shape factor.

Classifying coastal resources by integrating optical and radar imagery and color infrared photography

USGS Publications Warehouse

Ramsey, Elijah W.; Nelson, Gene A.; Sapkota, Sijan

1998-01-01

A progressive classification of a marsh and forest system using Landsat Thematic Mapper (TM), color infrared (CIR) photograph, and ERS-1 synthetic aperture radar (SAR) data improved classification accuracy when compared to classification using solely TM reflective band data. The classification resulted in a detailed identification of differences within a nearly monotypic black needlerush marsh. Accuracy percentages of these classes were surprisingly high given the complexities of classification. The detailed classification resulted in a more accurate portrayal of the marsh transgressive sequence than was obtainable with TM data alone. Individual sensor contribution to the improved classification was compared to that using only the six reflective TM bands. Individually, the green reflective CIR and SAR data identified broad categories of water, marsh, and forest. In combination with TM, SAR and the green CIR band each improved overall accuracy by about 3% and 15% respectively. The SAR data improved the TM classification accuracy mostly in the marsh classes. The green CIR data also improved the marsh classification accuracy and accuracies in some water classes. The final combination of all sensor data improved almost all class accuracies from 2% to 70% with an overall improvement of about 20% over TM data alone. Not only was the identification of vegetation types improved, but the spatial detail of the classification approached 10 m in some areas.

Determination of the health of Lunyangwa wetland using Wetland Classification and Risk Assessment Index

NASA Astrophysics Data System (ADS)

Wanda, Elijah M. M.; Mamba, Bhekie B.; Msagati, Titus A. M.; Msilimba, Golden

2016-04-01

Wetlands are major sources of various ecological goods and services including storage and distribution of water in space and time which help in ensuring the availability of surface and groundwater throughout the year. However, there still remains a poor understanding of the range of values of water quality parameters that occur in wetlands either in its impacted state or under natural conditions. It was thus imperative to determine the health of Lunyangwa wetland in Mzuzu City in Malawi in order to classify and determine its state. This study used the Escom's Wetland Classification and Risk Assessment Index Field Guide to determine the overall characteristics of Lunyangwa wetland and to calculate its combined Wetland Index Score. Data on site information, field measurements (i.e. EC, pH, temperature and DO) and physical characteristics of Lunyangwa wetland were collected from March, 2013 to February, 2014. Results indicate that Lunyangwa wetland is a largely open water zone which is dominated by free-floating plants on the water surface, beneath surface and emergent in substrate. Furthermore, the wetland can be classified as of a C ecological category (score = 60-80%), which has been moderately modified with moderate risks of the losses and changes occurring in the natural habitat and biota in the wetland. It was observed that the moderate modification and risk were largely because of industrial, agricultural, urban/social catchment stressors on the wetland. This study recommends an integrated and sustainable management approach coupled with continuous monitoring and evaluation of the health of the wetland for all stakeholders in Mzuzu City. This would help to maintain the health of Lunyangwa wetland which is currently at risk of being further modified due to the identified catchment stressors.

Riparian vegetation structure under desertification scenarios

NASA Astrophysics Data System (ADS)

Rosário Fernandes, M.; Segurado, Pedro; Jauch, Eduardo; Ferreira, M. Teresa

2015-04-01

Riparian areas are responsible for many ecological and ecosystems services, including the filtering function, that are considered crucial to the preservation of water quality and social benefits. The main goal of this study is to quantify and understand the riparian variability under desertification scenario(s) and identify the optimal riparian indicators for water scarcity and droughts (WS&D), henceforth improving river basin management. This study was performed in the Iberian Tâmega basin, using riparian woody patches, mapped by visual interpretation on Google Earth imagery, along 130 Sampling Units of 250 m long river stretches. Eight riparian structural indicators, related with lateral dimension, weighted area and shape complexity of riparian patches were calculated using Patch Analyst extension for ArcGis 10. A set of 29 hydrological, climatic, and hydrogeomorphological variables were computed, by a water modelling system (MOHID), using monthly meteorological data between 2008 and 2014. Land-use classes were also calculated, in a 250m-buffer surrounding each sampling unit, using a classification based system on Corine Land Cover. Boosted Regression Trees identified Mean-width (MW) as the optimal riparian indicator for water scarcity and drought, followed by the Weighted Class Area (WCA) (classification accuracy =0.79 and 0.69 respectively). Average Flow and Strahler number were consistently selected, by all boosted models, as the most important explanatory variables. However, a combined effect of hidrogeomorphology and land-use can explain the high variability found in the riparian width mainly in Tâmega tributaries. Riparian patches are larger towards Tâmega river mouth although with lower shape complexity, probably related with more continuous and almost monospecific stands. Climatic, hydrological and land use scenarios, singly and combined, were used to quantify the riparian variability responding to these changes, and to assess the loss of riparian functions such as nutrient incorporation and sediment flux alterations.

Monitoring Reservoir Storage in South Asia from Satellite Remote Sensing

NASA Astrophysics Data System (ADS)

Zhang, S.; Gao, H.; Naz, B.

2013-12-01

Realtime reservoir storage information is essential for accurate flood monitoring and prediction in South Asia, where the fatality rate (by area) due to floods is among the highest in the world. However, South Asia is dominated by international river basins where communications among neighboring countries about reservoir storage and management are extremely limited. In this study, we use a suite of NASA satellite observations to achieve high quality estimation of reservoir storage and storage variations at near realtime in South Asia. The monitoring approach employs vegetation indices from the Moderate Resolution Imaging Spectroradiometer (MODIS) 16-day 250 m MOD13Q1 product and the surface elevation data from the Geoscience Laser Altimeter System (GLAS) on board the Ice, Cloud and land Elevation Satellite (ICESat). This approach contains four steps: 1) identifying the reservoirs with ICESat GLAS overpasses and extracting the elevation data for these locations; 2) using the K-means method for water classification from MODIS andapplying a novel post-classification algorithm to enhance water area estimation accuracy; 3) deriving the relationship between the MODIS water surface area and the ICESat elevation; and 4) estimating the storage of reservoirs over time based on the elevation-area relationship and the MODIS water area time series. For evaluation purposes, we compared the satellite-based reservoir storage with gauge observations for 16 reservoirs in South Asia. The storage estimates were highly correlated with observations (R = 0.92 to 0.98), with values for the normalized root mean square error (NRMSE) ranging from 8.7% to 25.2%. Using this approach, storage and storage variations were estimated for 16 South Asia reservoirs from 2000 to 2012.

Data Quality Evaluation and Application Potential Analysis of TIANGONG-2 Wide-Band Imaging Spectrometer

NASA Astrophysics Data System (ADS)

Qin, B.; Li, L.; Li, S.

2018-04-01

Tiangong-2 is the first space laboratory in China, which launched in September 15, 2016. Wide-band Imaging Spectrometer is a medium resolution multispectral imager on Tiangong-2. In this paper, the authors introduced the indexes and parameters of Wideband Imaging Spectrometer, and made an objective evaluation about the data quality of Wide-band Imaging Spectrometer in radiation quality, image sharpness and information content, and compared the data quality evaluation results with that of Landsat-8. Although the data quality of Wide-band Imager Spectrometer has a certain disparity with Landsat-8 OLI data in terms of signal to noise ratio, clarity and entropy. Compared with OLI, Wide-band Imager Spectrometer has more bands, narrower bandwidth and wider swath, which make it a useful remote sensing data source in classification and identification of large and medium scale ground objects. In the future, Wide-band Imaging Spectrometer data will be widely applied in land cover classification, ecological environment assessment, marine and coastal zone monitoring, crop identification and classification, and other related areas.

Using self-organizing maps to develop ambient air quality classifications: a time series example

PubMed Central

2014-01-01

Background Development of exposure metrics that capture features of the multipollutant environment are needed to investigate health effects of pollutant mixtures. This is a complex problem that requires development of new methodologies. Objective Present a self-organizing map (SOM) framework for creating ambient air quality classifications that group days with similar multipollutant profiles. Methods Eight years of day-level data from Atlanta, GA, for ten ambient air pollutants collected at a central monitor location were classified using SOM into a set of day types based on their day-level multipollutant profiles. We present strategies for using SOM to develop a multipollutant metric of air quality and compare results with more traditional techniques. Results Our analysis found that 16 types of days reasonably describe the day-level multipollutant combinations that appear most frequently in our data. Multipollutant day types ranged from conditions when all pollutants measured low to days exhibiting relatively high concentrations for either primary or secondary pollutants or both. The temporal nature of class assignments indicated substantial heterogeneity in day type frequency distributions (~1%-14%), relatively short-term durations (<2 day persistence), and long-term and seasonal trends. Meteorological summaries revealed strong day type weather dependencies and pollutant concentration summaries provided interesting scenarios for further investigation. Comparison with traditional methods found SOM produced similar classifications with added insight regarding between-class relationships. Conclusion We find SOM to be an attractive framework for developing ambient air quality classification because the approach eases interpretation of results by allowing users to visualize classifications on an organized map. The presented approach provides an appealing tool for developing multipollutant metrics of air quality that can be used to support multipollutant health studies. PMID:24990361

Environmental setting and factors that affect water quality in the Georgia-Florida Coastal Plain study unit

USGS Publications Warehouse

Berndt, M.P.; Oaksford, E.T.; Darst, M.R.; Marella, R.L.

1996-01-01

The Georgia-Florida Coastal Plain study unit covers an area of nearly 62,000 square miles in the southeastern United States, mostly in the Coastal Plain physiographic province. Land resource provinces have been designated based on generalized soil classifications. Land resource provinces in the study area include: the Coastal Flatwoods, the Southern Coastal Plain, the Central Florida Ridge, the Sand Hills, and the Southern Piedmont. The study area includes all or parts of seven hydrologic subregions: the Ogeechee-Savannah, the Altamaha- St.Marys, the Suwannee, the Ochlockonee, the St. Johns, the Peace-Tampa Bay, and the Southern Florida. The primary source of water for public supply in the study area is ground water from the Upper Floridan aquifer. In 1990, more than 90 percent of the 2,888 million gallons per day of ground water used came from this aquifer. The population of the study area was 9.3 million in 1990. The cities of Jacksonville, Orlando, St. Petersburg, Tallahassee, and Tampa, Florida, and parts of Atlanta and Savannah, Georgia, are located in the study area. Forest and agricultural areas are the most common land uses in the study area, accounting for 48 percent and 25 percent of the study area, respectively. Climatic conditions range from temperate in Atlanta, Georgia, where mean annual temperature is about 61.3 degrees Fahrenheit, to subtropical in Tampa, Florida, where mean annual temperature is about 72.4 degrees Fahrenheit. Long-term average precipitation (1961-90) ranges from 43.9 inches per year in Tampa, Florida, and 44.6 in Macon, Georgia, to 65.7 inches per year in Tallahassee, Florida. Floods in the study area result from frontal systems, hurricanes, tropical storms, or severe thunderstorms. Droughts are not common in the study area,especially in the Florida part of the study area due to extensive maritime exposure. The primary physical and cultural characteristics in the study area include physiography, soils and land resource provinces, geologic setting, ground-water systems, surface- water systems, climate, floods, droughts, population, land use, and water use. Factors affecting water quality in the study area are land use (primarily urban and agricultural land uses), water use in coastal areas, hydrogeology, ground-water/surface-water interaction, geology, and climate. Surface-water quality problems in urban areas have occurred in the Ogeechee, Canoochee, Ocmulgee, St. Marys, Alapaha, Withlacoochee (north), Santa Fe, Ochlockonee, St. Johns, and Oklawaha Rivers and include nitrogen and phosphorus loading, low dissolved oxygen, elevated bacteria, sediment, and turbidity, and increased concentrations of metals. In agricultural areas, surface-water quality problems include elevated nitrogen and phosphorus concentrations, erosion, and sedimentation and have occurred in the Ocmulgee, St. Marys, Santa Fe, Ochlockonee, St. Johns, Oklawaha, Withlacoochee (South), Hillsborough, and Alafia Rivers. Ground water-quality problems such as saltwater intrusion have occurred mostly in coastal areas and were caused by excessive withdrawals.

Medical Devices; Immunology and Microbiology Devices; Classification of the Assayed Quality Control Material for Clinical Microbiology Assays. Final order.

PubMed

2017-07-27

The Food and Drug Administration (FDA, Agency, or we) is classifying the assayed quality control material for clinical microbiology assays into class II (special controls). The special controls that will apply to the device are identified in this order and will be part of the codified language for the assayed quality control material for clinical microbiology assays' classification. The Agency is classifying the device into class II (special controls) to provide a reasonable assurance of safety and effectiveness of the device.

Attribute Weighting Based K-Nearest Neighbor Using Gain Ratio

NASA Astrophysics Data System (ADS)

Nababan, A. A.; Sitompul, O. S.; Tulus

2018-04-01

K- Nearest Neighbor (KNN) is a good classifier, but from several studies, the result performance accuracy of KNN still lower than other methods. One of the causes of the low accuracy produced, because each attribute has the same effect on the classification process, while some less relevant characteristics lead to miss-classification of the class assignment for new data. In this research, we proposed Attribute Weighting Based K-Nearest Neighbor Using Gain Ratio as a parameter to see the correlation between each attribute in the data and the Gain Ratio also will be used as the basis for weighting each attribute of the dataset. The accuracy of results is compared to the accuracy acquired from the original KNN method using 10-fold Cross-Validation with several datasets from the UCI Machine Learning repository and KEEL-Dataset Repository, such as abalone, glass identification, haberman, hayes-roth and water quality status. Based on the result of the test, the proposed method was able to increase the classification accuracy of KNN, where the highest difference of accuracy obtained hayes-roth dataset is worth 12.73%, and the lowest difference of accuracy obtained in the abalone dataset of 0.07%. The average result of the accuracy of all dataset increases the accuracy by 5.33%.

Computer-aided analysis of Skylab multispectral scanner data in mountainous terrain for land use, forestry, water resource, and geologic applications

NASA Technical Reports Server (NTRS)

Hoffer, R. M. (Principal Investigator)

1975-01-01

The author has identified the following significant results. One of the most significant results of this Skylab research involved the geometric correction and overlay of the Skylab multispectral scanner data with the LANDSAT multispectral scanner data, and also with a set of topographic data, including elevation, slope, and aspect. The Skylab S192 multispectral scanner data had distinct differences in noise level of the data in the various wavelength bands. Results of the temporal evaluation of the SL-2 and SL-3 photography were found to be particularly important for proper interpretation of the computer-aided analysis of the SL-2 and SL-3 multispectral scanner data. There was a quality problem involving the ringing effect introduced by digital filtering. The modified clustering technique was found valuable when working with multispectral scanner data involving many wavelength bands and covering large geographic areas. Analysis of the SL-2 scanner data involved classification of major cover types and also forest cover types. Comparison of the results obtained wth Skylab MSS data and LANDSAT MSS data indicated that the improved spectral resolution of the Skylab scanner system enabled a higher classification accuracy to be obtained for forest cover types, although the classification performance for major cover types was not significantly different.

Evolution of the construction and performances in accordance to the applications of non-thermal plasma reactors

NASA Astrophysics Data System (ADS)

Hnatiuc, B.; Brisset, J. L.; Astanei, D.; Ursache, M.; Mares, M.; Hnatiuc, E.; Felea, C.

2016-12-01

This paper aims to present the evolution of the construction and performances of non-thermal plasma reactors, identifying specific requirements for various known applications, setting out quality indicators that would allow on the one hand comparing devices that use different kinds of electrical discharges but also their rigorous classification by identification of criteria in order to choose the correct cold plasma reactors for a specific application. It briefly comments the post-discharge effect but also the current dilemma on non-thermal plasma direct treatments versus indirect treatments, using plasma activated water (PAW) or plasma activated medium (PAM), promising in cancer treatment.

Remote sensing of submerged aquatic vegetation in lower Chesapeake Bay - A comparison of Landsat MSS to TM imagery

NASA Technical Reports Server (NTRS)

Ackleson, S. G.; Klemas, V.

1987-01-01

Landsat MSS and TM imagery, obtained simultaneously over Guinea Marsh, VA, as analyzed and compares for its ability to detect submerged aquatic vegetation (SAV). An unsupervised clustering algorithm was applied to each image, where the input classification parameters are defined as functions of apparent sensor noise. Class confidence and accuracy were computed for all water areas by comparing the classified images, pixel-by-pixel, to rasterized SAV distributions derived from color aerial photography. To illustrate the effect of water depth on classification error, areas of depth greater than 1.9 m were masked, and class confidence and accuracy recalculated. A single-scattering radiative-transfer model is used to illustrate how percent canopy cover and water depth affect the volume reflectance from a water column containing SAV. For a submerged canopy that is morphologically and optically similar to Zostera marina inhabiting Lower Chesapeake Bay, dense canopies may be isolated by masking optically deep water. For less dense canopies, the effect of increasing water depth is to increase the apparent percent crown cover, which may result in classification error.

Development of Policies, Institutions and Procedures for Water Reuse

NASA Astrophysics Data System (ADS)

Demouche, L.; Pfiefer, J.; Hanson, A.; Skaggs, R.

2009-12-01

In the arid, water scarce region of New Mexico and West Texas there is growing interest in the potential for water reuse to extend existing supplies and mitigate drought shortage impacts. There are no new sources of water in New Mexico, except reclaimed water. Communities and individuals are uncertain about and have many unanswered questions about polices, institutions involved (agencies), legal and regulatory requirements, and procedures governing water reuse. Issues to be addressed by this project include: the legal ability to reuse water, ownership of water rights, downstream or third party impacts, regulatory and procedural requirements, water quality concerns, state and local agency involvement, and cost effectiveness of water reuse compared to alternative sources. Presently, there is very little implementation or directives in New Mexico policy that addresses reuse, reclamation, or recycled water. The only regulations pertaining to reuse is New Mexico Environmental Department currently allows the use of reclaimed domestic wastewater for irrigation of golf courses and green spaces, which is listed in the Policy for the Above Ground Use of Reclaimed Domestic Wastewater (NMED, 2003). This document identifies the various reclaimed quality classifications that are required for specific applications and the permits required for application. This document does not identify or address policy applications on the distribution, ownership, or trading of reclaimed water. Even though reclaimed water reuse projects are currently being implemented in many cities in the U.S., mainly for commercial and municipal irrigation (golf courses and green space), its potential has not yet been exploited. A policy analysis matrix (PAM) is being designed to identify and examine the policy framework and consequences of non-policy implementation for decision makers and interest groups and assist them in understanding the consequences of policy actions and project outcomes if no laws or regulations are created. The clarity of definitions is critical in policy analysis. Good economic analysis is fascinating for economist, frustrating for noneconomist, and relevant for everyone because it focuses on linkages within an economy—on why one group’s actions influence others in the system. The water reuse PAM is being used to identify the legality of water reuse, ownership of water rights, downstream or third party impacts, regulatory and procedural requirements, water quality concerns, state and local agency involvement, and cost effectiveness of water reuse compared to alternative sources. This project hopes to identify everyone involved in water reuse policy and provide them with clarity about the issues to help in evaluating and making sound policy decisions.

Neural image analysis in the process of quality assessment: domestic pig oocytes

NASA Astrophysics Data System (ADS)

Boniecki, P.; Przybył, J.; Kuzimska, T.; Mueller, W.; Raba, B.; Lewicki, A.; Przybył, K.; Zaborowicz, M.; Koszela, K.

2014-04-01

The questions related to quality classification of animal oocytes are explored by numerous scientific and research centres. This research is important, particularly in the context of improving the breeding value of farm animals. The methods leading to the stimulation of normal development of a larger number of fertilised animal oocytes in extracorporeal conditions are of special importance. Growing interest in the techniques of supported reproduction resulted in searching for new, increasingly effective methods for quality assessment of mammalian gametes and embryos. Progress in the production of in vitro animal embryos in fact depends on proper classification of obtained oocytes. The aim of this paper was the development of an original method for quality assessment of oocytes, performed on the basis of their graphical presentation in the form of microscopic digital images. The classification process was implemented on the basis of the information coded in the form of microphotographic pictures of the oocytes of domestic pig, using the modern methods of neural image analysis.

Effect of filtration of signals of brain activity on quality of recognition of brain activity patterns using artificial intelligence methods

NASA Astrophysics Data System (ADS)

Hramov, Alexander E.; Frolov, Nikita S.; Musatov, Vyachaslav Yu.

2018-02-01

In present work we studied features of the human brain states classification, corresponding to the real movements of hands and legs. For this purpose we used supervised learning algorithm based on feed-forward artificial neural networks (ANNs) with error back-propagation along with the support vector machine (SVM) method. We compared the quality of operator movements classification by means of EEG signals obtained experimentally in the absence of preliminary processing and after filtration in different ranges up to 25 Hz. It was shown that low-frequency filtering of multichannel EEG data significantly improved accuracy of operator movements classification.

An improved global wind resource estimate for integrated assessment models

DOE PAGES

Eurek, Kelly; Sullivan, Patrick; Gleason, Michael; ...

2017-11-25

This study summarizes initial steps to improving the robustness and accuracy of global renewable resource and techno-economic assessments for use in integrated assessment models. We outline a method to construct country-level wind resource supply curves, delineated by resource quality and other parameters. Using mesoscale reanalysis data, we generate estimates for wind quality, both terrestrial and offshore, across the globe. Because not all land or water area is suitable for development, appropriate database layers provide exclusions to reduce the total resource to its technical potential. We expand upon estimates from related studies by: using a globally consistent data source of uniquelymore » detailed wind speed characterizations; assuming a non-constant coefficient of performance for adjusting power curves for altitude; categorizing the distance from resource sites to the electric power grid; and characterizing offshore exclusions on the basis of sea ice concentrations. The product, then, is technical potential by country, classified by resource quality as determined by net capacity factor. Additional classifications dimensions are available, including distance to transmission networks for terrestrial wind and distance to shore and water depth for offshore. We estimate the total global wind generation potential of 560 PWh for terrestrial wind with 90% of resource classified as low-to-mid quality, and 315 PWh for offshore wind with 67% classified as mid-to-high quality. These estimates are based on 3.5 MW composite wind turbines with 90 m hub heights, 0.95 availability, 90% array efficiency, and 5 MW/km 2 deployment density in non-excluded areas. We compare the underlying technical assumption and results with other global assessments.« less

An improved global wind resource estimate for integrated assessment models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Eurek, Kelly; Sullivan, Patrick; Gleason, Michael

This study summarizes initial steps to improving the robustness and accuracy of global renewable resource and techno-economic assessments for use in integrated assessment models. We outline a method to construct country-level wind resource supply curves, delineated by resource quality and other parameters. Using mesoscale reanalysis data, we generate estimates for wind quality, both terrestrial and offshore, across the globe. Because not all land or water area is suitable for development, appropriate database layers provide exclusions to reduce the total resource to its technical potential. We expand upon estimates from related studies by: using a globally consistent data source of uniquelymore » detailed wind speed characterizations; assuming a non-constant coefficient of performance for adjusting power curves for altitude; categorizing the distance from resource sites to the electric power grid; and characterizing offshore exclusions on the basis of sea ice concentrations. The product, then, is technical potential by country, classified by resource quality as determined by net capacity factor. Additional classifications dimensions are available, including distance to transmission networks for terrestrial wind and distance to shore and water depth for offshore. We estimate the total global wind generation potential of 560 PWh for terrestrial wind with 90% of resource classified as low-to-mid quality, and 315 PWh for offshore wind with 67% classified as mid-to-high quality. These estimates are based on 3.5 MW composite wind turbines with 90 m hub heights, 0.95 availability, 90% array efficiency, and 5 MW/km 2 deployment density in non-excluded areas. We compare the underlying technical assumption and results with other global assessments.« less

The software application and classification algorithms for welds radiograms analysis

NASA Astrophysics Data System (ADS)

Sikora, R.; Chady, T.; Baniukiewicz, P.; Grzywacz, B.; Lopato, P.; Misztal, L.; Napierała, L.; Piekarczyk, B.; Pietrusewicz, T.; Psuj, G.

2013-01-01

The paper presents a software implementation of an Intelligent System for Radiogram Analysis (ISAR). The system has to support radiologists in welds quality inspection. The image processing part of software with a graphical user interface and a welds classification part are described with selected classification results. Classification was based on a few algorithms: an artificial neural network, a k-means clustering, a simplified k-means and a rough sets theory.

Soil Quality Indicator: a new concept

NASA Astrophysics Data System (ADS)

Barão, Lúcia; Basch, Gottlieb

2017-04-01

During the last century, cultivated soils have been intensively exploited for food and feed production. This exploitation has compromised the soils' natural functions and many of the soil-mediated ecosystems services, including its production potential for agriculture. Also, soils became increasingly vulnerable and less resilient to a wide range of threats. To overcome this situation, new and better management practices are needed to prevent soil from degradation. However, to adopt the best management practices in a specific location, it is necessary to evaluate the soil quality status first. Different soil quality indicators have been suggested over the last decades in order to evaluate the soil status, and those are often based on the performance of soil chemical, physical and biological properties. However, the direct link between these properties and the associated soil functions or soil vulnerability to threats appears more difficult to be established. This present work is part of the iSQAPER project- Interactive Soil Quality Assessment in Europe and China for Agricultural Productivity and Environmental Resilience, where new soil quality concepts are explored to provide better information regarding the effects of the most promising agricultural management practices on soil quality. We have developed a new conceptual soil quality indicator which determines the soil quality status, regarding its vulnerability towards different threats. First, different indicators were specifically developed for each of the eight threats considered - Erosion, SOM decline, Poor Structure, Poor water holding capacity, Compaction, N-Leaching, Soil-borne pests and diseases and Salinization. As an example for the case of Erosion, the RUSLE equation for the estimate of the soil annual loss was used. Secondly, a reference classification was established for each indicator to integrate all possible results into a Good, Intermediate or Bad classification. Finally, all indicators were combined to return a single evaluation of the soil status, using different techniques that are dependent on the final use of the soil quality indicator. Some of the advantages of this new concept include the evaluation of soil quality based on its vulnerability to threats, together with the evaluation of soil properties in a given context while also suggesting soil management practices that are directly capable to mitigate soil vulnerability towards specific threats. Keywords: Soil Quality, Agriculture, Sustainability, Soil threats

46 CFR 34.50-5 - Classification-TB/ALL.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 46 Shipping 1 2010-10-01 2010-10-01 false Classification-TB/ALL. 34.50-5 Section 34.50-5 Shipping... Semiportable Extinguishers § 34.50-5 Classification—TB/ALL. (a) Portable and semiportable extinguishers shall...-5(c) Classification type (Size) Soda-acid and water (Gallons) Foam (Gallons) Carbon dioxide (Pounds...

46 CFR 34.50-5 - Classification-TB/ALL.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 46 Shipping 1 2012-10-01 2012-10-01 false Classification-TB/ALL. 34.50-5 Section 34.50-5 Shipping... Semiportable Extinguishers § 34.50-5 Classification—TB/ALL. (a) Portable and semiportable extinguishers shall...-5(c) Classification type (Size) Soda-acid and water (Gallons) Foam (Gallons) Carbon dioxide (Pounds...

46 CFR 34.50-5 - Classification-TB/ALL.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 46 Shipping 1 2011-10-01 2011-10-01 false Classification-TB/ALL. 34.50-5 Section 34.50-5 Shipping... Semiportable Extinguishers § 34.50-5 Classification—TB/ALL. (a) Portable and semiportable extinguishers shall...-5(c) Classification type (Size) Soda-acid and water (Gallons) Foam (Gallons) Carbon dioxide (Pounds...

33 CFR 67.01-15 - Classification of structures.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 33 Navigation and Navigable Waters 1 2010-07-01 2010-07-01 false Classification of structures. 67... AIDS TO NAVIGATION AIDS TO NAVIGATION ON ARTIFICIAL ISLANDS AND FIXED STRUCTURES General Requirements § 67.01-15 Classification of structures. (a) When will structures be assigned to a Class? The District...

One input-class and two input-class classifications for differentiating olive oil from other edible vegetable oils by use of the normal-phase liquid chromatography fingerprint of the methyl-transesterified fraction.

PubMed

Jiménez-Carvelo, Ana M; Pérez-Castaño, Estefanía; González-Casado, Antonio; Cuadros-Rodríguez, Luis

2017-04-15

A new method for differentiation of olive oil (independently of the quality category) from other vegetable oils (canola, safflower, corn, peanut, seeds, grapeseed, palm, linseed, sesame and soybean) has been developed. The analytical procedure for chromatographic fingerprinting of the methyl-transesterified fraction of each vegetable oil, using normal-phase liquid chromatography, is described and the chemometric strategies applied and discussed. Some chemometric methods, such as k-nearest neighbours (kNN), partial least squared-discriminant analysis (PLS-DA), support vector machine classification analysis (SVM-C), and soft independent modelling of class analogies (SIMCA), were applied to build classification models. Performance of the classification was evaluated and ranked using several classification quality metrics. The discriminant analysis, based on the use of one input-class, (plus a dummy class) was applied for the first time in this study. Copyright © 2016 Elsevier Ltd. All rights reserved.

Practical UXO Classification: Enhanced Data Processing Strategies for Technology Transition - Fort Ord: Dynamic and Cued Metalmapper Processing and Classification

DTIC Science & Technology

2017-06-06

OMB No. 0704-0188 Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for...Geophysical Mapping, Electromagnetic Induction, Instrument Verification Strip, Time Domain Electromagnetic, Unexploded Ordnance 16. SECURITY...Munitions Response QA Quality Assurance QC Quality Control ROC Receiver Operating Characteristic RTK Real- time Kinematic s Second SNR

Micro-Doppler Based Classification of Human Aquatic Activities via Transfer Learning of Convolutional Neural Networks.

PubMed

Park, Jinhee; Javier, Rios Jesus; Moon, Taesup; Kim, Youngwook

2016-11-24

Accurate classification of human aquatic activities using radar has a variety of potential applications such as rescue operations and border patrols. Nevertheless, the classification of activities on water using radar has not been extensively studied, unlike the case on dry ground, due to its unique challenge. Namely, not only is the radar cross section of a human on water small, but the micro-Doppler signatures are much noisier due to water drops and waves. In this paper, we first investigate whether discriminative signatures could be obtained for activities on water through a simulation study. Then, we show how we can effectively achieve high classification accuracy by applying deep convolutional neural networks (DCNN) directly to the spectrogram of real measurement data. From the five-fold cross-validation on our dataset, which consists of five aquatic activities, we report that the conventional feature-based scheme only achieves an accuracy of 45.1%. In contrast, the DCNN trained using only the collected data attains 66.7%, and the transfer learned DCNN, which takes a DCNN pre-trained on a RGB image dataset and fine-tunes the parameters using the collected data, achieves a much higher 80.3%, which is a significant performance boost.

Automatic intelligibility classification of sentence-level pathological speech

PubMed Central

Kim, Jangwon; Kumar, Naveen; Tsiartas, Andreas; Li, Ming; Narayanan, Shrikanth S.

2014-01-01

Pathological speech usually refers to the condition of speech distortion resulting from atypicalities in voice and/or in the articulatory mechanisms owing to disease, illness or other physical or biological insult to the production system. Although automatic evaluation of speech intelligibility and quality could come in handy in these scenarios to assist experts in diagnosis and treatment design, the many sources and types of variability often make it a very challenging computational processing problem. In this work we propose novel sentence-level features to capture abnormal variation in the prosodic, voice quality and pronunciation aspects in pathological speech. In addition, we propose a post-classification posterior smoothing scheme which refines the posterior of a test sample based on the posteriors of other test samples. Finally, we perform feature-level fusions and subsystem decision fusion for arriving at a final intelligibility decision. The performances are tested on two pathological speech datasets, the NKI CCRT Speech Corpus (advanced head and neck cancer) and the TORGO database (cerebral palsy or amyotrophic lateral sclerosis), by evaluating classification accuracy without overlapping subjects’ data among training and test partitions. Results show that the feature sets of each of the voice quality subsystem, prosodic subsystem, and pronunciation subsystem, offer significant discriminating power for binary intelligibility classification. We observe that the proposed posterior smoothing in the acoustic space can further reduce classification errors. The smoothed posterior score fusion of subsystems shows the best classification performance (73.5% for unweighted, and 72.8% for weighted, average recalls of the binary classes). PMID:25414544

Quality of alcohol-based hand disinfectants and their regulatory status. Development and marketing authorisation.

PubMed

Stengele, Michael

2008-10-01

A 2005 survey showed that there are at least four legal product classifications for hand disinfectants in the European Union: medicinal products, biocidal products, cosmetics and medical devices. An internationally harmonized classification does not exist. The regulatory status of those products is defined at national level. In order to assure compliance with the regulations these four classifications provide different levels of official surveillance varying from product-specific marketing authorisations and production site audits to the obligation to just work in accordance with certain general guidelines. Biocidal product regulations cover eco-toxicological and toxicological aspects, but do not very much address to the customers' quality and efficacy expectations. In contrast, the medicinal product legislation is the most ambitious one claiming quality, safety, efficacy, and an independent benefit risk-assessment by an authority. In respect of ambition, the two remaining product categories--cosmetics and medical devices--rank between the both classifications mentioned above. For medical devices, it is the responsibility of the manufacturer to make sure the products meet defined essential requirements regarding quality, safety and performance and to have an appropriate quality assurance system implemented under third party control. For cosmetics there are some legal restrictions, but within these it is the sole responsibility of the manufacturer to ensure that the products are safe and fulfil their claims. This paper describes one way out of this increasingly complex situation, the definition of a single quality standard meeting the users' expectations as well as all legal requirements regardless of the specific sales country. This international quality standard for products would take priority over any individual national standard, to the benefit of users.

Bacterial flora analysis of coliforms in sewage, river water, and ground water using MALDI-TOF mass spectrometry.

PubMed

Suzuki, Yoshihiro; Niina, Kouki; Matsuwaki, Tomonori; Nukazawa, Kei; Iguchi, Atsushi

2018-01-28

The aim of this study was to rapidly and effectively analyze coliforms, which are the most fundamental indicators of water quality for fecal pollution, using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS). Coliform bacteria were isolated from municipal sewage, river water, and groundwater. For each sample, 100 isolates were determined by MALDI-TOF MS. In addition, these same 100 isolates were also identified via 16S rRNA gene sequence analysis. Obtained MALDI-TOF MS data were compared with the 16S rRNA sequencing analysis, and the validity of MALDI-TOF MS for classification of coliform bacteria was examined. The concordance rate of bacterial identification for the 100 isolates obtained by MALDI-TOF MS analysis and 16S rRNA gene sequence analysis for sewage, river water, and ground water were 96%, 74%, and 62% at the genus level, respectively. Among the sewage, river water, and ground water samples, the coliform bacterial flora were distinct. The dominant genus of coliforms in sewage, river water, and groundwater were Klebsiella spp., Enterobacter spp., and Serratia spp., respectively. We determined that MALDI-TOF MS is a rapid and accurate tool that can be used to identify coliforms. Therefore, without using conventional 16S rRNA sequencing, it is possible to rapidly and effectively classify coliforms in water using MALDI-TOF MS.

[Remote sensing monitoring and screening for urban black and odorous water body: A review.

PubMed

Shen, Qian; Zhu, Li; Cao, Hong Ye

2017-10-01

Continuous improvement of urban water environment and overall control of black and odorous water body are not merely national strategic needs with the action plan for prevention and treatment of water pollution, but also the hot issues attracting the attention of people. Most previous researches concentrated on the study of cause, evaluation and treatment measures of this phenomenon, and there are few researches on the monitoring using remote sensing, which is often a strain to meet the national needs of operational monitoring. This paper mainly summarized the urgent research problems, mainly including the identification and classification standard, research on the key technologies, and the frame of remote sensing screening systems for the urban black and odorous water body. The main key technologies were concluded too, including the high spatial resolution image preprocessing and extraction technique for black and odorous water body, the extraction of water information in city zones, the classification of the black and odorous water, and the identification and classification technique based on satellite-sky-ground remote sensing. This paper summarized the research progress and put forward research ideas of monitoring and screening urban black and odorous water body via high spatial resolution remote sensing technology, which would be beneficial to having an overall grasp of spatial distribution and improvement progress of black and odorous water body, and provide strong technical support for controlling urban black and odorous water body.

Forest site classification in the interior uplands

Treesearch

Glendon W. Smalley

1989-01-01

Classification and evaluation of forest sites is an essential step in managing central hardwood forests. In Note 4.01, The Importance of Site Quality, the usefulness of land classification systems was discussed. The present Note describes one of those systems in more detail. It is an easy-to-use system developed for the Cumberland Plateau and Highland Rim-Pennyroyal...

A new classification scheme of European cold-water coral habitats: Implications for ecosystem-based management of the deep sea

NASA Astrophysics Data System (ADS)

Davies, J. S.; Guillaumont, B.; Tempera, F.; Vertino, A.; Beuck, L.; Ólafsdóttir, S. H.; Smith, C. J.; Fosså, J. H.; van den Beld, I. M. J.; Savini, A.; Rengstorf, A.; Bayle, C.; Bourillet, J.-F.; Arnaud-Haond, S.; Grehan, A.

2017-11-01

Cold-water corals (CWC) can form complex structures which provide refuge, nursery grounds and physical support for a diversity of other living organisms. However, irrespectively from such ecological significance, CWCs are still vulnerable to human pressures such as fishing, pollution, ocean acidification and global warming Providing coherent and representative conservation of vulnerable marine ecosystems including CWCs is one of the aims of the Marine Protected Areas networks being implemented across European seas and oceans under the EC Habitats Directive, the Marine Strategy Framework Directive and the OSPAR Convention. In order to adequately represent ecosystem diversity, these initiatives require a standardised habitat classification that organises the variety of biological assemblages and provides consistent and functional criteria to map them across European Seas. One such classification system, EUNIS, enables a broad level classification of the deep sea based on abiotic and geomorphological features. More detailed lower biotope-related levels are currently under-developed, particularly with regards to deep-water habitats (>200 m depth). This paper proposes a hierarchical CWC biotope classification scheme that could be incorporated by existing classification schemes such as EUNIS. The scheme was developed within the EU FP7 project CoralFISH to capture the variability of CWC habitats identified using a wealth of seafloor imagery datasets from across the Northeast Atlantic and Mediterranean. Depending on the resolution of the imagery being interpreted, this hierarchical scheme allows data to be recorded from broad CWC biotope categories down to detailed taxonomy-based levels, thereby providing a flexible yet valuable information level for management. The CWC biotope classification scheme identifies 81 biotopes and highlights the limitations of the classification framework and guidance provided by EUNIS, the EC Habitats Directive, OSPAR and FAO; which largely underrepresent CWC habitats.

Cyanobacteria as indicators of water quality in Campania coasts, Italy: a monitoring strategy combining remote/proximal sensing and in situ data

NASA Astrophysics Data System (ADS)

Teta, Roberta; Romano, Vincenza; Della Sala, Gerardo; Picchio, Stefano; De Sterlich, Carlo; Mangoni, Alfonso; Di Tullio, Giacomo; Costantino, Valeria; Lega, Massimiliano

2017-02-01

Cyanobacterial blooms (CBs) are generally triggered by eutrophic conditions due to anthropogenic nutrient inputs to local waters (wastewater or contaminated waters). During the bloom, some species produce toxic secondary metabolites (cyanotoxins) that are dangerous for humans and animals. Here, a multidisciplinary strategy for an early detection and constant monitoring is proposed. This strategy combines remote/proximal sensing technology with analytical/biotechnological analyses. To demonstrate the applicability of this strategy, four anthropogenically-impacted sites were selected along the Campania coast of southwestern Italy, in the so called ‘Land of Fires’. The sites were observed using satellite and aircraft images during summer, 2015. Algal community composition was determined using spectrophotometric analysis for the detection of the cyanobacterial pigment phycocyanin (PC). Complementary metagenomic analysis revealed the taxonomic presence of cyanobacteria belonging to genera associated with strong eutrophic conditions. Key elements of this strategy are the combination and integration of applying different methodological approaches such as the parallel and combined use of satellite, aerial and in-situ data, the simplified multispectral image indexing and classification for a truly efficient method in detecting early blooms of cyanobacteria. The effectiveness of the strategy has been validated also by the specific taxa of cyanobacteria found in the examined areas that confirm the assumption that cyanobacterial blooms may serve as useful bioindicators of degraded water quality in coastal ecosystems. To our knowledge this is the first time that the presence of cyanobacteria has been observed in water bodies along the Campania coast.

Geologic research in support of sustainable agriculture

USGS Publications Warehouse

Gough, L.P.; Herring, J.R.

1993-01-01

The importance and role of the geosciences in studies of sustainable agriculture include such traditional research areas as, agromineral resource assessments, the mapping and classification of soils and soil amendments, and the evaluation of landscapes for their vulnerability to physical and chemical degradation. Less traditional areas of study, that are increasing in societal importance because of environmental concerns and research into sustainable systems in general, include regional geochemical studies of plant and animal trace element deficiencies and toxicities, broad-scale water quality investigations, agricultural chemicals and the hydrogeologic interface, and minimally processed and ion-exchange agrominerals. We discuss the importance and future of phosphate in the US and world based on human population growth, projected agromineral demands in general, and the unavailability of new, high-quality agricultural lands. We also present examples of studies that relate geochemistry and the hydrogeologic characteristics of a region to the bioavailability and cycling of trace elements important to sustainable agricultural systems. ?? 1993.

NPDES (National Pollution Discharge & Elimination System) Minor Dischargers

EPA Pesticide Factsheets

As authorized by the Clean Water Act, the National Pollutant Discharge Elimination System (NPDES) permit program controls water pollution by regulating point sources that discharge pollutants into waters of the United States. The NPDES permit program regulates direct discharges from municipal and industrial wastewater treatment facilities that discharge directly into surface waters. The NPDES permit program is part of the Permit Compliance System (PCS) which issues, records, tracks, and regulates point source discharge facilities. Individual homes that are connected to a municipal system, use a septic system, or do not have a surface discharge do not need an NPDES permit. Facilities in PCS are identified as either major or minor. Within the major/minor classification, facilities are grouped into municipals or non-municipals. In many cases, non-municipals are industrial facilities. This data layer contains Minor dischargers. Major municipal dischargers include all facilities with design flows of greater than one million gallons per day; minor dischargers are less that one million gallons per day. Essentially, a minor discharger does not meet the discharge criteria for a major. Since its introduction in 1972, the NPDES permit program is responsible for significant improvements to our Nation's water quality.

Water quality and benthic fauna biodiversity in a unique small wetland at Messinia, Greece.

PubMed

Gritzalis, Konstantinos C; Anastasopoulou, Evangelia; Georgiopoulos, Nikolaos A; Markogianni, Vasiliki V; Skoulikidis, Nikolaos Th

2015-01-01

The wetland of Aghios Floros is located in the Prefecture of Messinia (S. W. Peloponnese, Greece) and occupies a small area, covered permanentlywith water. Flooding of the surrounding area is defended by an artificial channel that discharge large quantity of water into Pamisos River in whose river basin the Aghios Floros station belongs. At the sampling site various physico-chemical and conventional pollution parameters as well as hydrochemical variables were measured during the wet and the dry period of 2011. The hydromorphological and multihabitat approach of RIVPACS method was applied in situ, which gives an overall image of the landscape. The site was classified as 'Good' according to the Greek River Nutrient Classification System (GR.NCS) and the benthic macroinvertebrate fauna assemblages that dominated the area pointed out a 'Good' biological status as well. The biotic and abiotic sample processing, carried out in compliance with the demands of the Water Framework Directive, in general revealed high ecological status of the station. Specifically, a rich diversity and abundance of some macroinvertebrate families was recorded and regarding the aquatic flora the area is dominated by the water lilies species of Nymphaea alba which are unique in the area of Peloponnese.

Advanced Nursing Process quality: Comparing the International Classification for Nursing Practice (ICNP) with the NANDA-International (NANDA-I) and Nursing Interventions Classification (NIC).

PubMed

Rabelo-Silva, Eneida Rejane; Dantas Cavalcanti, Ana Carla; Ramos Goulart Caldas, Maria Cristina; Lucena, Amália de Fátima; Almeida, Miriam de Abreu; Linch, Graciele Fernanda da Costa; da Silva, Marcos Barragan; Müller-Staub, Maria

2017-02-01

To assess the quality of the advanced nursing process in nursing documentation in two hospitals. Various standardised terminologies are employed by nurses worldwide, whether for teaching, research or patient care. These systems can improve the quality of nursing records, enable care continuity, consistency in written communication and enhance safety for patients and providers alike. Cross-sectional study. A total of 138 records from two facilities (69 records from each facility) were analysed, one using the NANDA-International and Nursing Interventions Classification terminology (Centre 1) and one the International Classification for Nursing Practice (Centre 2), by means of the Quality of Diagnoses, Interventions, and Outcomes instrument. Quality of Diagnoses, Interventions, and Outcomes scores range from 0-58 points. Nursing records were dated 2012-2013 for Centre 1 and 2010-2011 for Centre 2. Centre 1 had a Quality of Diagnoses, Interventions, and Outcomes score of 35·46 (±6·45), whereas Centre 2 had a Quality of Diagnoses, Interventions, and Outcomes score of 31·72 (±4·62) (p < 0·001). Centre 2 had higher scores in the 'Nursing Diagnoses as Process' dimension, whereas in the 'Nursing Diagnoses as Product', 'Nursing Interventions' and 'Nursing Outcomes' dimensions, Centre 1 exhibited superior performance; acceptable reliability values were obtained for both centres, except for the 'Nursing Interventions' domain in Centre 1 and the 'Nursing Diagnoses as Process' and 'Nursing Diagnoses as Product' domains in Centre 2. The quality of nursing documentation was superior at Centre 1, although both facilities demonstrated moderate scores considering the maximum potential score of 58 points. Reliability analyses showed satisfactory results for both standardised terminologies. Nursing leaders should use a validated instrument to investigate the quality of nursing records after implementation of standardised terminologies. © 2016 John Wiley & Sons Ltd.

Semi-supervised classification tool for DubaiSat-2 multispectral imagery

NASA Astrophysics Data System (ADS)

Al-Mansoori, Saeed

2015-10-01

This paper addresses a semi-supervised classification tool based on a pixel-based approach of the multi-spectral satellite imagery. There are not many studies demonstrating such algorithm for the multispectral images, especially when the image consists of 4 bands (Red, Green, Blue and Near Infrared) as in DubaiSat-2 satellite images. The proposed approach utilizes both unsupervised and supervised classification schemes sequentially to identify four classes in the image, namely, water bodies, vegetation, land (developed and undeveloped areas) and paved areas (i.e. roads). The unsupervised classification concept is applied to identify two classes; water bodies and vegetation, based on a well-known index that uses the distinct wavelengths of visible and near-infrared sunlight that is absorbed and reflected by the plants to identify the classes; this index parameter is called "Normalized Difference Vegetation Index (NDVI)". Afterward, the supervised classification is performed by selecting training homogenous samples for roads and land areas. Here, a precise selection of training samples plays a vital role in the classification accuracy. Post classification is finally performed to enhance the classification accuracy, where the classified image is sieved, clumped and filtered before producing final output. Overall, the supervised classification approach produced higher accuracy than the unsupervised method. This paper shows some current preliminary research results which point out the effectiveness of the proposed technique in a virtual perspective.

A Bio-Inspired Herbal Tea Flavour Assessment Technique

PubMed Central

Zakaria, Nur Zawatil Isqi; Masnan, Maz Jamilah; Zakaria, Ammar; Shakaff, Ali Yeon Md

2014-01-01

Herbal-based products are becoming a widespread production trend among manufacturers for the domestic and international markets. As the production increases to meet the market demand, it is very crucial for the manufacturer to ensure that their products have met specific criteria and fulfil the intended quality determined by the quality controller. One famous herbal-based product is herbal tea. This paper investigates bio-inspired flavour assessments in a data fusion framework involving an e-nose and e-tongue. The objectives are to attain good classification of different types and brands of herbal tea, classification of different flavour masking effects and finally classification of different concentrations of herbal tea. Two data fusion levels were employed in this research, low level data fusion and intermediate level data fusion. Four classification approaches; LDA, SVM, KNN and PNN were examined in search of the best classifier to achieve the research objectives. In order to evaluate the classifiers' performance, an error estimator based on k-fold cross validation and leave-one-out were applied. Classification based on GC-MS TIC data was also included as a comparison to the classification performance using fusion approaches. Generally, KNN outperformed the other classification techniques for the three flavour assessments in the low level data fusion and intermediate level data fusion. However, the classification results based on GC-MS TIC data are varied. PMID:25010697

40 CFR 49.10495 - Classification of regions for episode plans.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Implementation Plan for the Port Gamble Indian Community of the Port Gamble Reservation, Washington § 49.10495 Classification of regions for episode plans. The air quality control region which encompasses the Port Gamble...

40 CFR 49.10255 - Classification of regions for episode plans.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Implementation Plan for the Kootenai Tribe of Idaho § 49.10255 Classification of regions for episode plans. The air quality control region which encompasses the Reservation of the Kootenai Tribe of Idaho is...

40 CFR 49.11075 - Classification of regions for episode plans.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Implementation Plan for the Confederated Tribes of the Warm Springs Reservation of Oregon § 49.11075 Classification of regions for episode plans. The air quality control region which encompasses the Warm Springs...

Surface water classification and monitoring using polarimetric synthetic aperture radar

NASA Astrophysics Data System (ADS)

Irwin, Katherine Elizabeth

Surface water classification using synthetic aperture radar (SAR) is an established practice for monitoring flood hazards due to the high temporal and spatial resolution it provides. Surface water change is a dynamic process that varies both spatially and temporally, and can occur on various scales resulting in significant impacts on affected areas. Small-scale flooding hazards, caused by beaver dam failure, is an example of surface water change, which can impact nearby infrastructure and ecosystems. Assessing these hazards is essential to transportation and infrastructure maintenance. With current satellite missions operating in multiple polarizations, spatio-temporal resolutions, and frequencies, a comprehensive comparison between SAR products for surface water monitoring is necessary. In this thesis, surface water extent models derived from high resolution single-polarization TerraSAR-X (TSX) data, medium resolution dual-polarization TSX data and low resolution quad-polarization RADARSAT-2 (RS-2) data are compared. There exists a compromise between acquiring SAR data with a high resolution or high information content. Multi-polarization data provides additional phase and intensity information, which makes it possible to better classify areas of flooded vegetation and wetlands. These locations are often where fluctuations in surface water occur and are essential for understanding dynamic underlying processes. However, often multi-polarized data is acquired at a low resolution, which cannot image these zones effectively. High spatial resolution, single-polarization TSX data provides the best model of open water. However, these single-polarization observations have limited information content and are affected by shadow and layover errors. This often hinders the classification of other land cover types. The dual-polarization TSX data allows for the classification of flooded vegetation, but classification is less accurate compared to the quad-polarization RS-2 data. The RS-2 data allows for the discrimination of open water, marshes/fields and forested areas. However, the RS-2 data is less applicable to small scale surface water monitoring (e.g. beaver dam failure), due to its low spatial resolution. By understanding the strengths and weaknesses of available SAR technology, an appropriate product can be chosen for a specific target application involving surface water change. This research benefits the eventual development of a space-based monitoring strategy over longer periods.

On the utilization of novel spectral laser scanning for three-dimensional classification of vegetation elements.

PubMed

Li, Zhan; Schaefer, Michael; Strahler, Alan; Schaaf, Crystal; Jupp, David

2018-04-06

The Dual-Wavelength Echidna Lidar (DWEL), a full waveform terrestrial laser scanner (TLS), has been used to scan a variety of forested and agricultural environments. From these scanning campaigns, we summarize the benefits and challenges given by DWEL's novel coaxial dual-wavelength scanning technology, particularly for the three-dimensional (3D) classification of vegetation elements. Simultaneous scanning at both 1064 nm and 1548 nm by DWEL instruments provides a new spectral dimension to TLS data that joins the 3D spatial dimension of lidar as an information source. Our point cloud classification algorithm explores the utilization of both spectral and spatial attributes of individual points from DWEL scans and highlights the strengths and weaknesses of each attribute domain. The spectral and spatial attributes for vegetation element classification each perform better in different parts of vegetation (canopy interior, fine branches, coarse trunks, etc.) and under different vegetation conditions (dead or live, leaf-on or leaf-off, water content, etc.). These environmental characteristics of vegetation, convolved with the lidar instrument specifications and lidar data quality, result in the actual capabilities of spectral and spatial attributes to classify vegetation elements in 3D space. The spectral and spatial information domains thus complement each other in the classification process. The joint use of both not only enhances the classification accuracy but also reduces its variance across the multiple vegetation types we have examined, highlighting the value of the DWEL as a new source of 3D spectral information. Wider deployment of the DWEL instruments is in practice currently held back by challenges in instrument development and the demands of data processing required by coaxial dual- or multi-wavelength scanning. But the simultaneous 3D acquisition of both spectral and spatial features, offered by new multispectral scanning instruments such as the DWEL, opens doors to study biophysical and biochemical properties of forested and agricultural ecosystems at more detailed scales.

Proposal of a New Adverse Event Classification by the Society of Interventional Radiology Standards of Practice Committee.

PubMed

Khalilzadeh, Omid; Baerlocher, Mark O; Shyn, Paul B; Connolly, Bairbre L; Devane, A Michael; Morris, Christopher S; Cohen, Alan M; Midia, Mehran; Thornton, Raymond H; Gross, Kathleen; Caplin, Drew M; Aeron, Gunjan; Misra, Sanjay; Patel, Nilesh H; Walker, T Gregory; Martinez-Salazar, Gloria; Silberzweig, James E; Nikolic, Boris

2017-10-01

To develop a new adverse event (AE) classification for the interventional radiology (IR) procedures and evaluate its clinical, research, and educational value compared with the existing Society of Interventional Radiology (SIR) classification via an SIR member survey. A new AE classification was developed by members of the Standards of Practice Committee of the SIR. Subsequently, a survey was created by a group of 18 members from the SIR Standards of Practice Committee and Service Lines. Twelve clinical AE case scenarios were generated that encompassed a broad spectrum of IR procedures and potential AEs. Survey questions were designed to evaluate the following domains: educational and research values, accountability for intraprocedural challenges, consistency of AE reporting, unambiguity, and potential for incorporation into existing quality-assurance framework. For each AE scenario, the survey participants were instructed to answer questions about the proposed and existing SIR classifications. SIR members were invited via online survey links, and 68 members participated among 140 surveyed. Answers on new and existing classifications were evaluated and compared statistically. Overall comparison between the two surveys was performed by generalized linear modeling. The proposed AE classification received superior evaluations in terms of consistency of reporting (P < .05) and potential for incorporation into existing quality-assurance framework (P < .05). Respondents gave a higher overall rating to the educational and research value of the new compared with the existing classification (P < .05). This study proposed an AE classification system that outperformed the existing SIR classification in the studied domains. Copyright © 2017 SIR. Published by Elsevier Inc. All rights reserved.

Classification of brain tumours using short echo time 1H MR spectra

NASA Astrophysics Data System (ADS)

Devos, A.; Lukas, L.; Suykens, J. A. K.; Vanhamme, L.; Tate, A. R.; Howe, F. A.; Majós, C.; Moreno-Torres, A.; van der Graaf, M.; Arús, C.; Van Huffel, S.

2004-09-01

The purpose was to objectively compare the application of several techniques and the use of several input features for brain tumour classification using Magnetic Resonance Spectroscopy (MRS). Short echo time 1H MRS signals from patients with glioblastomas ( n = 87), meningiomas ( n = 57), metastases ( n = 39), and astrocytomas grade II ( n = 22) were provided by six centres in the European Union funded INTERPRET project. Linear discriminant analysis, least squares support vector machines (LS-SVM) with a linear kernel and LS-SVM with radial basis function kernel were applied and evaluated over 100 stratified random splittings of the dataset into training and test sets. The area under the receiver operating characteristic curve (AUC) was used to measure the performance of binary classifiers, while the percentage of correct classifications was used to evaluate the multiclass classifiers. The influence of several factors on the classification performance has been tested: L2- vs. water normalization, magnitude vs. real spectra and baseline correction. The effect of input feature reduction was also investigated by using only the selected frequency regions containing the most discriminatory information, and peak integrated values. Using L2-normalized complete spectra the automated binary classifiers reached a mean test AUC of more than 0.95, except for glioblastomas vs. metastases. Similar results were obtained for all classification techniques and input features except for water normalized spectra, where classification performance was lower. This indicates that data acquisition and processing can be simplified for classification purposes, excluding the need for separate water signal acquisition, baseline correction or phasing.

The trophic classification of lakes using ERTS multispectral scanner data

NASA Technical Reports Server (NTRS)

Blackwell, R. J.; Boland, D. H.

1975-01-01

Lake classification methods based on the use of ERTS data are described. Preliminary classification results obtained by multispectral and digital image processing techniques indicate satisfactory correlation between ERTS data and EPA-supplied water analysis. Techniques for determining lake trophic levels using ERTS data are examined, and data obtained for 20 lakes are discussed.

Rural and Urban Differences in Air Quality, 2008–2012, and Community Drinking Water Quality, 2010–2015 — United States

PubMed Central

Kennedy, Caitlin; Monti, Michele; Yip, Fuyuen

2017-01-01

Problem/Condition The places in which persons live, work, and play can contribute to the development of adverse health outcomes. Understanding the differences in risk factors in various environments can help to explain differences in the occurrence of these outcomes and can be used to develop public health programs, interventions, and policies. Efforts to characterize urban and rural differences have largely focused on social and demographic characteristics. A paucity of national standardized environmental data has hindered efforts to characterize differences in the physical aspects of urban and rural areas, such as air and water quality. Reporting Period 2008–2012 for air quality and 2010–2015 for water quality. Description of System Since 2002, CDC’s National Environmental Public Health Tracking Program has collaborated with federal, state, and local partners to gather standardized environmental data by creating national data standards, collecting available data, and disseminating data to be used in developing public health actions. The National Environmental Public Health Tracking Network (i.e., the tracking network) collects data provided by national, state, and local partners and includes 21 health outcomes, exposures, and environmental hazards. To assess environmental factors that affect health, CDC analyzed three air-quality measures from the tracking network for all counties in the contiguous United States during 2008–2012 and one water-quality measure for 26 states during 2010–2015. The three air-quality measures include 1) total number of days with fine particulate matter (PM2.5) levels greater than the U.S. Environmental Protection Agency’s (EPA’s) National Ambient Air Quality Standards (NAAQS) for 24-hour average PM2.5 (PM2.5 days); 2) mean annual average ambient concentrations of PM2.5 in micrograms per cubic meter (mean PM2.5); and 3) total number of days with maximum 8-hour average ozone concentrations greater than the NAAQS (ozone days). The water-quality measure compared the annual mean concentration for a community water system (CWS) to the maximum contaminant level (MCL) defined by EPA for 10 contaminants: arsenic, atrazine, di(2-ethylhexyl) phthalate (DEHP), haloacetic acids (HAA5), nitrate, perchloroethene (PCE), radium, trichloroethene (TCE), total trihalomethanes (TTHM), and uranium. Findings are presented by urban-rural classification scheme: four metropolitan (large central metropolitan, large fringe metropolitan, medium metropolitan, and small metropolitan) and two nonmetropolitan (micropolitan and noncore) categories. Regression modeling was used to determine whether differences in the measures by urban-rural categories were statistically significant. Results Patterns for all three air-quality measures suggest that air quality improves as areas become more rural (or less urban). The mean total number of ozone days decreased from 47.54 days in large central metropolitan counties to 3.81 days in noncore counties, whereas the mean total number of PM2.5 days decreased from 11.21 in large central metropolitan counties to 0.95 in noncore counties. The mean average annual PM2.5 concentration decreased from 11.15 μg/m3 in large central metropolitan counties to 8.87 μg/m3 in noncore counties. Patterns for the water-quality measure suggest that water quality improves as areas become more urban (or less rural). Overall, 7% of CWSs reported at least one annual mean concentration greater than the MCL for all 10 contaminants combined. The percentage increased from 5.4% in large central metropolitan counties to 10% in noncore counties, a difference that was significant, adjusting for U.S. region, CWS size, water source, and potential spatial correlation. Similar results were found for two disinfection by-products, HAA5 and TTHM. Arsenic was the only other contaminant with a significant result. Medium metropolitan counties had 3.1% of CWSs reporting at least one annual mean greater than the MCL, compared with 2.4% in large central counties. Interpretation Noncore (rural) counties experienced fewer unhealthy air-quality days than large central metropolitan counties, likely because of fewer air pollution sources in the noncore counties. All categories of counties had a mean annual average PM2.5 concentration lower than the EPA standard. Among all CWSs analyzed, the number reporting one or more annual mean contaminant concentrations greater the MCL was small. The water-quality measure suggests that water quality worsens as counties become more rural, in regards to all contaminants combined and for the two disinfection by-products individually. Although significant differences were found for the water-quality measure, the odds ratios were very small, making it difficult to determine whether these differences have a meaningful effect on public health. These differences might be a result of variations in water treatment practices in rural versus urban counties. Public Health Action Understanding the differences between rural and urban areas in air and water quality can help public health departments to identify, monitor, and prioritize potential environmental public health concerns and opportunities for action. These findings suggest a continued need to develop more geographically targeted, evidence-based interventions to prevent morbidity and mortality associated with poor air and water quality. PMID:28640797

Rural and Urban Differences in Air Quality, 2008-2012, and Community Drinking Water Quality, 2010-2015 - United States.

PubMed

Strosnider, Heather; Kennedy, Caitlin; Monti, Michele; Yip, Fuyuen

2017-06-23

The places in which persons live, work, and play can contribute to the development of adverse health outcomes. Understanding the differences in risk factors in various environments can help to explain differences in the occurrence of these outcomes and can be used to develop public health programs, interventions, and policies. Efforts to characterize urban and rural differences have largely focused on social and demographic characteristics. A paucity of national standardized environmental data has hindered efforts to characterize differences in the physical aspects of urban and rural areas, such as air and water quality. 2008-2012 for air quality and 2010-2015 for water quality. Since 2002, CDC's National Environmental Public Health Tracking Program has collaborated with federal, state, and local partners to gather standardized environmental data by creating national data standards, collecting available data, and disseminating data to be used in developing public health actions. The National Environmental Public Health Tracking Network (i.e., the tracking network) collects data provided by national, state, and local partners and includes 21 health outcomes, exposures, and environmental hazards. To assess environmental factors that affect health, CDC analyzed three air-quality measures from the tracking network for all counties in the contiguous United States during 2008-2012 and one water-quality measure for 26 states during 2010-2015. The three air-quality measures include 1) total number of days with fine particulate matter (PM 2.5 ) levels greater than the U.S. Environmental Protection Agency's (EPA's) National Ambient Air Quality Standards (NAAQS) for 24-hour average PM 2.5 (PM 2.5 days); 2) mean annual average ambient concentrations of PM 2.5 in micrograms per cubic meter (mean PM 2.5 ); and 3) total number of days with maximum 8-hour average ozone concentrations greater than the NAAQS (ozone days). The water-quality measure compared the annual mean concentration for a community water system (CWS) to the maximum contaminant level (MCL) defined by EPA for 10 contaminants: arsenic, atrazine, di(2-ethylhexyl) phthalate (DEHP), haloacetic acids (HAA5), nitrate, perchloroethene (PCE), radium, trichloroethene (TCE), total trihalomethanes (TTHM), and uranium. Findings are presented by urban-rural classification scheme: four metropolitan (large central metropolitan, large fringe metropolitan, medium metropolitan, and small metropolitan) and two nonmetropolitan (micropolitan and noncore) categories. Regression modeling was used to determine whether differences in the measures by urban-rural categories were statistically significant. Patterns for all three air-quality measures suggest that air quality improves as areas become more rural (or less urban). The mean total number of ozone days decreased from 47.54 days in large central metropolitan counties to 3.81 days in noncore counties, whereas the mean total number of PM 2.5 days decreased from 11.21 in large central metropolitan counties to 0.95 in noncore counties. The mean average annual PM 2.5 concentration decreased from 11.15 μg/m 3 in large central metropolitan counties to 8.87 μg/m 3 in noncore counties. Patterns for the water-quality measure suggest that water quality improves as areas become more urban (or less rural). Overall, 7% of CWSs reported at least one annual mean concentration greater than the MCL for all 10 contaminants combined. The percentage increased from 5.4% in large central metropolitan counties to 10% in noncore counties, a difference that was significant, adjusting for U.S. region, CWS size, water source, and potential spatial correlation. Similar results were found for two disinfection by-products, HAA5 and TTHM. Arsenic was the only other contaminant with a significant result. Medium metropolitan counties had 3.1% of CWSs reporting at least one annual mean greater than the MCL, compared with 2.4% in large central counties. Noncore (rural) counties experienced fewer unhealthy air-quality days than large central metropolitan counties, likely because of fewer air pollution sources in the noncore counties. All categories of counties had a mean annual average PM 2.5 concentration lower than the EPA standard. Among all CWSs analyzed, the number reporting one or more annual mean contaminant concentrations greater the MCL was small. The water-quality measure suggests that water quality worsens as counties become more rural, in regards to all contaminants combined and for the two disinfection by-products individually. Although significant differences were found for the water-quality measure, the odds ratios were very small, making it difficult to determine whether these differences have a meaningful effect on public health. These differences might be a result of variations in water treatment practices in rural versus urban counties. Understanding the differences between rural and urban areas in air and water quality can help public health departments to identify, monitor, and prioritize potential environmental public health concerns and opportunities for action. These findings suggest a continued need to develop more geographically targeted, evidence-based interventions to prevent morbidity and mortality associated with poor air and water quality.

Aggregative Learning Method and Its Application for Communication Quality Evaluation

NASA Astrophysics Data System (ADS)

Akhmetov, Dauren F.; Kotaki, Minoru

2007-12-01

In this paper, so-called Aggregative Learning Method (ALM) is proposed to improve and simplify the learning and classification abilities of different data processing systems. It provides a universal basis for design and analysis of mathematical models of wide class. A procedure was elaborated for time series model reconstruction and analysis for linear and nonlinear cases. Data approximation accuracy (during learning phase) and data classification quality (during recall phase) are estimated from introduced statistic parameters. The validity and efficiency of the proposed approach have been demonstrated through its application for monitoring of wireless communication quality, namely, for Fixed Wireless Access (FWA) system. Low memory and computation resources were shown to be needed for the procedure realization, especially for data classification (recall) stage. Characterized with high computational efficiency and simple decision making procedure, the derived approaches can be useful for simple and reliable real-time surveillance and control system design.

Factors affecting breeding soundness classification of beef bulls examined at the Western College of Veterinary Medicine.

PubMed

Barth, Albert D; Waldner, Cheryl L

2002-04-01

Breeding soundness evaluation records from 2110 beef bulls, for the period of 1986 to 1999, were analyzed to determine the prevalence and importance of factors affecting breeding soundness classification. The percentage of all bulls classified as satisfactory ranged from 49.0% in January to 73.3% in May. The percentage of physically normal bulls with satisfactory semen quality ranged from 65.7% in January to 87.5% in June. Poor body condition or excessive body condition, below average or below the recommended minimum scrotal circumference, lameness, and severe scrotal frostbite significantly reduced the probability of a satisfactory breeding soundness classification. The percentage of sperm with midpiece defects declined significantly and the percentage of sperm with head defects increased significantly with the approach of summer. Photoperiod, cold stress, poor or excessive body condition, and reduced feed quality may interact to reduce semen quality in the winter months.

Detecting Water Bodies in LANDSAT8 Oli Image Using Deep Learning

NASA Astrophysics Data System (ADS)

Jiang, W.; He, G.; Long, T.; Ni, Y.

2018-04-01

Water body identifying is critical to climate change, water resources, ecosystem service and hydrological cycle. Multi-layer perceptron(MLP) is the popular and classic method under deep learning framework to detect target and classify image. Therefore, this study adopts this method to identify the water body of Landsat8. To compare the performance of classification, the maximum likelihood and water index are employed for each study area. The classification results are evaluated from accuracy indices and local comparison. Evaluation result shows that multi-layer perceptron(MLP) can achieve better performance than the other two methods. Moreover, the thin water also can be clearly identified by the multi-layer perceptron. The proposed method has the application potential in mapping global scale surface water with multi-source medium-high resolution satellite data.

The classification of hunger behaviour of Lates Calcarifer through the integration of image processing technique and k-Nearest Neighbour learning algorithm

NASA Astrophysics Data System (ADS)

Taha, Z.; Razman, M. A. M.; Ghani, A. S. Abdul; Majeed, A. P. P. Abdul; Musa, R. M.; Adnan, F. A.; Sallehudin, M. F.; Mukai, Y.

2018-04-01

Fish Hunger behaviour is essential in determining the fish feeding routine, particularly for fish farmers. The inability to provide accurate feeding routines (under-feeding or over-feeding) may lead the death of the fish and consequently inhibits the quantity of the fish produced. Moreover, the excessive food that is not consumed by the fish will be dissolved in the water and accordingly reduce the water quality through the reduction of oxygen quantity. This problem also leads the death of the fish or even spur fish diseases. In the present study, a correlation of Barramundi fish-school behaviour with hunger condition through the hybrid data integration of image processing technique is established. The behaviour is clustered with respect to the position of the school size as well as the school density of the fish before feeding, during feeding and after feeding. The clustered fish behaviour is then classified through k-Nearest Neighbour (k-NN) learning algorithm. Three different variations of the algorithm namely cosine, cubic and weighted are assessed on its ability to classify the aforementioned fish hunger behaviour. It was found from the study that the weighted k-NN variation provides the best classification with an accuracy of 86.5%. Therefore, it could be concluded that the proposed integration technique may assist fish farmers in ascertaining fish feeding routine.

Quality of surface waters in the lower Columbia River Basin

USGS Publications Warehouse

Santos, John F.

1965-01-01

This report, made during 1959-60, provides reconnaissance data on the quality of waters in the lower Columbia River basin ; information on present and future water problems in the basin; and data that can be employed both in water-use studies and in planning future industrial, municipal, and agricultural expansion within this area. The lower Columbia River basin consists of approximately 46,000 square miles downstream from the confluence of the Snake and Columbia Rivers The region can be divided into three geographic areas. The first is the heavily forested, sparsely populated mountain regions in which quality of water in general is related to geologic and climatological factors. The second is a semiarid plateau east of the Cascade Mountains; there differences in geology and precipitation, together with more intensive use of available water for irrigation, bring about marked differences in water quality. The third is the Willamette-Puget trough area in which are concentrated most of the industry and population and in which water quality is influenced by sewage and industrial waste disposal. The majority of the streams in the lower Columbia River basin are calcium magnesium bicarbonate waters. In general, the rivers rising in the. Coast Range and on the west slope of the Cascade Range contain less than 100 parts per million of dissolved solids, and hardness of the water is less than 50 parts per million. Headwater reaches of the streams on the east slope of the Cascade Range are similar to those on the west slope; but, downstream, irrigation return flows cause the dissolved-solids content and hardness to increase. Most of the waters, however, remain calcium magnesium bicarbonate in type. The highest observed dissolved-solids concentrations and also some changes in chemical composition occur in the streams draining the more arid parts of the area. In these parts, irrigation is chiefly responsible for increasing the dissolved-solids concentration and altering the chemical composition of the streams. The maximum dissolved-solids concentration and hardness of water observed in major irrigation areas were 507 and 262 parts per million, respectively, for the. Walla Walla River near Touchet, Wash. In terms of the U.S. Salinity Laboratory Staff classification (1954, p. 80), water in most streams in the basin has low salinity and sodium hazards and is suitable for irrigation. A salt-balance problem does exist in the Hermiston-Stanfield, Oreg., area of the Umatilla River basin, and because of poor drainage, improper irrigation practices could cause salt-balance problems in the Willamette River Valley, Oreg., in which irrigation is rapidly increasing. Pollution by sewage disposal has reached undesirable levels in the Walla Walla River, in the Willamette River from Eugene to Portland, Oreg., and in the Columbia River from Portland to Puget Island. In the lower reaches of the Willamette River, the pollution load from sewage and industrial-waste disposal at times depletes the dissolved oxygen in the water to concentrations below what is considered necessary for aquatic life. Water in most of the tributaries to the lower Columbia River is of excellent quality and after some treatment could be used for industrial and municipal supplies. The principal treatment required would be disinfection and turbidity removal.

Classification and global distribution of ocean precipitation types based on satellite passive microwave signatures

NASA Astrophysics Data System (ADS)

Gautam, Nitin

The main objectives of this thesis are to develop a robust statistical method for the classification of ocean precipitation based on physical properties to which the SSM/I is sensitive and to examine how these properties vary globally and seasonally. A two step approach is adopted for the classification of oceanic precipitation classes from multispectral SSM/I data: (1)we subjectively define precipitation classes using a priori information about the precipitating system and its possible distinct signature on SSM/I data such as scattering by ice particles aloft in the precipitating cloud, emission by liquid rain water below freezing level, the difference of polarization at 19 GHz-an indirect measure of optical depth, etc.; (2)we then develop an objective classification scheme which is found to reproduce the subjective classification with high accuracy. This hybrid strategy allows us to use the characteristics of the data to define and encode classes and helps retain the physical interpretation of classes. The classification methods based on k-nearest neighbor and neural network are developed to objectively classify six precipitation classes. It is found that the classification method based neural network yields high accuracy for all precipitation classes. An inversion method based on minimum variance approach was used to retrieve gross microphysical properties of these precipitation classes such as column integrated liquid water path, column integrated ice water path, and column integrated min water path. This classification method is then applied to 2 years (1991-92) of SSM/I data to examine and document the seasonal and global distribution of precipitation frequency corresponding to each of these objectively defined six classes. The characteristics of the distribution are found to be consistent with assumptions used in defining these six precipitation classes and also with well known climatological patterns of precipitation regions. The seasonal and global distribution of these six classes is also compared with the earlier results obtained from Comprehensive Ocean Atmosphere Data Sets (COADS). It is found that the gross pattern of the distributions obtained from SSM/I and COADS data match remarkably well with each other.

Identification of Water Bodies in a Landsat 8 OLI Image Using a J48 Decision Tree.

PubMed

Acharya, Tri Dev; Lee, Dong Ha; Yang, In Tae; Lee, Jae Kang

2016-07-12

Water bodies are essential to humans and other forms of life. Identification of water bodies can be useful in various ways, including estimation of water availability, demarcation of flooded regions, change detection, and so on. In past decades, Landsat satellite sensors have been used for land use classification and water body identification. Due to the introduction of a New Operational Land Imager (OLI) sensor on Landsat 8 with a high spectral resolution and improved signal-to-noise ratio, the quality of imagery sensed by Landsat 8 has improved, enabling better characterization of land cover and increased data size. Therefore, it is necessary to explore the most appropriate and practical water identification methods that take advantage of the improved image quality and use the fewest inputs based on the original OLI bands. The objective of the study is to explore the potential of a J48 decision tree (JDT) in identifying water bodies using reflectance bands from Landsat 8 OLI imagery. J48 is an open-source decision tree. The test site for the study is in the Northern Han River Basin, which is located in Gangwon province, Korea. Training data with individual bands were used to develop the JDT model and later applied to the whole study area. The performance of the model was statistically analysed using the kappa statistic and area under the curve (AUC). The results were compared with five other known water identification methods using a confusion matrix and related statistics. Almost all the methods showed high accuracy, and the JDT was successfully applied to the OLI image using only four bands, where the new additional deep blue band of OLI was found to have the third highest information gain. Thus, the JDT can be a good method for water body identification based on images with improved resolution and increased size.

Effects of Land-use/Land-cover and Climate Changes on Water Quantity and Quality in Sub-basins near Major US Cities in the Great Lakes Region

NASA Astrophysics Data System (ADS)

Murphy, L.; Al-Hamdan, M. Z.; Crosson, W. L.; Barik, M.

2017-12-01

Land-cover change over time to urbanized, less permeable surfaces, leads to reduced water infiltration at the location of water input while simultaneously transporting sediments, nutrients and contaminants farther downstream. With an abundance of agricultural fields bordering the greater urban areas of Milwaukee, Detroit, and Chicago, water and nutrient transport is vital to the farming industry, wetlands, and communities that rely on water availability. Two USGS stream gages each located within a sub-basin near each of these Great Lakes Region cities were examined, one with primarily urban land-cover between 1992 and 2011, and one with primarily agriculture land-cover. ArcSWAT, a watershed model and soil and water assessment tool used in extension with ArcGIS, was used to develop hydrologic models that vary the land-covers to simulate surface runoff during a model run period from 2004 to 2008. Model inputs that include a digital elevation model (DEM), Landsat-derived land-use/land-cover (LULC) satellite images from 1992, 2001, and 2011, soil classification, and meteorological data were used to determine the effect of different land-covers on the water runoff, nutrients and sediments. The models were then calibrated and validated to USGS stream gage data measurements over time. Additionally, the watershed model was run based on meteorological data from an IPCC CMIP5 high emissions climate change scenario for 2050. Model outputs from the different LCLU scenarios were statistically evaluated and results showed that water runoff, nutrients and sediments were impacted by LULC change in four out of the six sub-basins. In the 2050 climate scenario, only one out of the six sub-basin's water quantity and quality was affected. These results contribute to the importance of developing hydrologic models as the dependence on the Great Lakes as a freshwater resource competes with the expansion of urbanization leading to the movement of runoff, nutrients, and sediments off the land.

Spectroscopic classification of icy satellites of Saturn II: Identification of terrain units on Rhea

NASA Astrophysics Data System (ADS)

Scipioni, F.; Tosi, F.; Stephan, K.; Filacchione, G.; Ciarniello, M.; Capaccioni, F.; Cerroni, P.

2014-05-01

Rhea is the second largest icy satellites of Saturn and it is mainly composed of water ice. Its surface is characterized by a leading hemisphere slightly brighter than the trailing side. The main goal of this work is to identify homogeneous compositional units on Rhea by applying the Spectral Angle Mapper (SAM) classification technique to Rhea’s hyperspectral images acquired by the Visual and Infrared Mapping Spectrometer (VIMS) onboard the Cassini Orbiter in the infrared range (0.88-5.12 μm). The first step of the classification is dedicated to the identification of Rhea’s spectral endmembers by applying the k-means unsupervised clustering technique to four hyperspectral images representative of a limited portion of the surface, imaged at relatively high spatial resolution. We then identified eight spectral endmembers, corresponding to as many terrain units, which mostly distinguish for water ice abundance and ice grain size. In the second step, endmembers are used as reference spectra in SAM classification method to achieve a comprehensive classification of the entire surface. From our analysis of the infrared spectra returned by VIMS, it clearly emerges that Rhea’ surface units shows differences in terms of water ice bands depths, average ice grain size, and concentration of contaminants, particularly CO2 and hydrocarbons. The spectral units that classify optically dark terrains are those showing suppressed water ice bands, a finer ice grain size and a higher concentration of carbon dioxide. Conversely, spectral units labeling brighter regions have deeper water ice absorption bands, higher albedo and a smaller concentration of contaminants. All these variations reflect surface’s morphological and geological structures. Finally, we performed a comparison between Rhea and Dione, to highlight different magnitudes of space weathering effects in the icy satellites as a function of the distance from Saturn.

A Modified Hopfield Neural Network Algorithm (MHNNA) Using ALOS Image for Water Quality Mapping

PubMed Central

Kzar, Ahmed Asal; Mat Jafri, Mohd Zubir; Mutter, Kussay N.; Syahreza, Saumi

2015-01-01

Decreasing water pollution is a big problem in coastal waters. Coastal health of ecosystems can be affected by high concentrations of suspended sediment. In this work, a Modified Hopfield Neural Network Algorithm (MHNNA) was used with remote sensing imagery to classify the total suspended solids (TSS) concentrations in the waters of coastal Langkawi Island, Malaysia. The adopted remote sensing image is the Advanced Land Observation Satellite (ALOS) image acquired on 18 January 2010. Our modification allows the Hopfield neural network to convert and classify color satellite images. The samples were collected from the study area simultaneously with the acquiring of satellite imagery. The sample locations were determined using a handheld global positioning system (GPS). The TSS concentration measurements were conducted in a lab and used for validation (real data), classification, and accuracy assessments. Mapping was achieved by using the MHNNA to classify the concentrations according to their reflectance values in band 1, band 2, and band 3. The TSS map was color-coded for visual interpretation. The efficiency of the proposed algorithm was investigated by dividing the validation data into two groups. The first group was used as source samples for supervisor classification via the MHNNA. The second group was used to test the MHNNA efficiency. After mapping, the locations of the second group in the produced classes were detected. Next, the correlation coefficient (R) and root mean square error (RMSE) were calculated between the two groups, according to their corresponding locations in the classes. The MHNNA exhibited a higher R (0.977) and lower RMSE (2.887). In addition, we test the MHNNA with noise, where it proves its accuracy with noisy images over a range of noise levels. All results have been compared with a minimum distance classifier (Min-Dis). Therefore, TSS mapping of polluted water in the coastal Langkawi Island, Malaysia can be performed using the adopted MHNNA with remote sensing techniques (as based on ALOS images). PMID:26729148

A Global Perspective on Drinking-Water and Sanitation Classification: An Evaluation of Census Content

PubMed Central

Yu, Weiyu; Wardrop, Nicola A.; Bain, Robert E. S.; Lin, Yanzhao; Zhang, Ce; Wright, Jim A.

2016-01-01

Following the recent expiry of the United Nations’ 2015 Millennium Development Goals (MDGs), new international development agenda covering 2030 water, sanitation and hygiene (WASH) targets have been proposed, which imply new demands on data sources for monitoring relevant progress. This study evaluates drinking-water and sanitation classification systems from national census questionnaire content, based upon the most recent international policy changes, to examine national population census’s ability to capture drinking-water and sanitation availability, safety, accessibility, and sustainability. In total, 247 censuses from 83 low income and lower-middle income countries were assessed using a scoring system, intended to assess harmonised water supply and sanitation classification systems for each census relative to the typology needed to monitor the proposed post-2015 indicators of WASH targets. The results signal a lack of international harmonisation and standardisation in census categorisation systems, especially concerning safety, accessibility, and sustainability of services in current census content. This suggests further refinements and harmonisation of future census content may be necessary to reflect ambitions for post-2015 monitoring. PMID:26986472

A Global Perspective on Drinking-Water and Sanitation Classification: An Evaluation of Census Content.

PubMed

Yu, Weiyu; Wardrop, Nicola A; Bain, Robert E S; Lin, Yanzhao; Zhang, Ce; Wright, Jim A

2016-01-01

Following the recent expiry of the United Nations' 2015 Millennium Development Goals (MDGs), new international development agenda covering 2030 water, sanitation and hygiene (WASH) targets have been proposed, which imply new demands on data sources for monitoring relevant progress. This study evaluates drinking-water and sanitation classification systems from national census questionnaire content, based upon the most recent international policy changes, to examine national population census's ability to capture drinking-water and sanitation availability, safety, accessibility, and sustainability. In total, 247 censuses from 83 low income and lower-middle income countries were assessed using a scoring system, intended to assess harmonised water supply and sanitation classification systems for each census relative to the typology needed to monitor the proposed post-2015 indicators of WASH targets. The results signal a lack of international harmonisation and standardisation in census categorisation systems, especially concerning safety, accessibility, and sustainability of services in current census content. This suggests further refinements and harmonisation of future census content may be necessary to reflect ambitions for post-2015 monitoring.

Estuarial fingerprinting through multidimensional fluorescence and multivariate analysis.

PubMed

Hall, Gregory J; Clow, Kerin E; Kenny, Jonathan E

2005-10-01

As part of a strategy for preventing the introduction of aquatic nuisance species (ANS) to U.S. estuaries, ballast water exchange (BWE) regulations have been imposed. Enforcing these regulations requires a reliable method for determining the port of origin of water in the ballast tanks of ships entering U.S. waters. This study shows that a three-dimensional fluorescence fingerprinting technique, excitation emission matrix (EEM) spectroscopy, holds great promise as a ballast water analysis tool. In our technique, EEMs are analyzed by multivariate classification and curve resolution methods, such as N-way partial least squares Regression-discriminant analysis (NPLS-DA) and parallel factor analysis (PARAFAC). We demonstrate that classification techniques can be used to discriminate among sampling sites less than 10 miles apart, encompassing Boston Harbor and two tributaries in the Mystic River Watershed. To our knowledge, this work is the first to use multivariate analysis to classify water as to location of origin. Furthermore, it is shown that curve resolution can show seasonal features within the multidimensional fluorescence data sets, which correlate with difficulty in classification.

Assessment of water quality, road runoff, and bulk atmospheric deposition, Guanella Pass area, Clear Creek and Park Counties, Colorado, water years 1995-97

USGS Publications Warehouse

Stevens, Michael R.

2001-01-01

The Guanella Pass road, located about 40 miles west of Denver, Colorado, between the towns of Georgetown and Grant, has been designated a scenic byway and is being considered for reconstruction. The purpose of this report is to present an assessment of hydrologic and water-quality conditions in the Guanella Pass area and provide baseline data for evaluation of the effects of the proposed road reconstruction. The data were collected during water years 1995-97 (October 1, 1995, to September 30, 1997).Based on Colorado water-quality standards, current surface-water quality near Guanella Pass road was generally acceptable for specified use classifications of recreation, water supply, agriculture, and aquatic life. Streams had small concentrations of dissolved solids, nutrients, trace elements, and suspended sediment. An exception was upper Geneva Creek, which was acidic and had relatively large concentrations of iron, zinc, and other trace elements related to acid-sulfate weathering. Concentrations of many water-quality constituents, especially particle-related phases and suspended sediment, increased during peak snowmelt and rainstorm events and decreased to prerunoff concentrations at the end of runoff periods. Some dissolved (filtered) trace-element loads in Geneva Creek decreased during rainstorms when total recoverable loads remained generally static or increased, indicating a phase change that might be explained by adsorption of trace elements to suspended sediment during storm runoff.Total recoverable iron and dissolved zinc exceeded Colorado stream-water-quality standards most frequently. Exceedances for iron generally occurred during periods of high suspended-sediment transport in several streams. Zinc standards were exceeded in about one-half the samples collected in Geneva Creek 1.5 miles upstream from Grant.Lake-water quality was generally similar to that of area streams. Nitrogen and phosphorus ratios calculated for Clear and Duck Lakes indicated that phytoplankton in the lakes were probably phosphorus-limited. Measures of trophic status (secchi depth, total phosphorus, and chlorophyll-a) indicated that Duck and Clear Lakes were oligotrophic in 1997.Ground water had relatively low specific conductance (range 24 to 584 microsiemens per centimeter) and did not exceed U.S. Environmental Protection Agency drinking-water standards, except for samples collected from a single well, which exceeded the Proposed Maximum Contaminant Level for uranium.Runoff from the Guanella Pass road enters streams through surface channels connected to culverts and roadside ditches. Fifty-six percent of the total number of culvert and roadside-ditch drainage features on the Guanella Pass road showed evidence of recent surface runoff connection to an adjacent stream. Road runoff is generated during snowmelt and during summer rainstorms.At a road cross-drain culvert monitored continuously for discharge (water years 1996-97), most runoff (77 to 96 percent) was a result of snowmelt, and runoff from the road preceded the basinwide peak streamflow, resulting in sediment and water-quality constituent inputs to the stream when the stream?s capacity for dilution of the road runoff was low. Specific conductance of road-runoff samples ranged from 14 to 468 microsiemens per centimeter. Major-ion composition of some samples indicated effects from deicing salt (sodium chloride) and dust inhibitor (magnesium chloride) applied to sections of the road, but changes in the stream concentrations that might be attributed to the runoff were brief and relatively small.Nutrients were commonly measured in road-runoff samples at larger concentrations than in streamflow. Concentrations of nitrate and ammonia, especially during rainfall-generated road runoff, were more similar to the concentrations in precipitation than to the concentrations in stream water. Concentrations of ammonia plus organic nitrogen (total as N) (range less than 0.2 to 24 milligrams per liter) and t

Neural network approaches versus statistical methods in classification of multisource remote sensing data

NASA Technical Reports Server (NTRS)

Benediktsson, Jon A.; Swain, Philip H.; Ersoy, Okan K.

1990-01-01

Neural network learning procedures and statistical classificaiton methods are applied and compared empirically in classification of multisource remote sensing and geographic data. Statistical multisource classification by means of a method based on Bayesian classification theory is also investigated and modified. The modifications permit control of the influence of the data sources involved in the classification process. Reliability measures are introduced to rank the quality of the data sources. The data sources are then weighted according to these rankings in the statistical multisource classification. Four data sources are used in experiments: Landsat MSS data and three forms of topographic data (elevation, slope, and aspect). Experimental results show that two different approaches have unique advantages and disadvantages in this classification application.

Geology and forestry classification from ERTS-1 digital data

NASA Technical Reports Server (NTRS)

Lawrence, R. D.; Herzog, J. H.

1975-01-01

Computer classifications into seven and ten classes of two areas in central Oregon of interest to geology and forestry demonstrate the extraction of information from ERTS-1 data. The area around Newberry Caldera was classified into basalt, rhyolite obsidian, pumice flats, Newberry pumice, ponderosa pine, lodgepole pine, and water classes. The area around Mt. Washington was classified into two basalts, three forest, two clearcut, burn, snow, and water classes. Both also include an unclassified category. Significant details that cannot be extracted from photographic reconstitutions of the data emerge from these classifications, such as moraine locations and paleowind directions. Spectral signatures for the various rocks are comparable to those published elsewhere.

A comprehensive quality evaluation method by FT-NIR spectroscopy and chemometric: Fine classification and untargeted authentication against multiple frauds for Chinese Ganoderma lucidum

NASA Astrophysics Data System (ADS)

Fu, Haiyan; Yin, Qiaobo; Xu, Lu; Wang, Weizheng; Chen, Feng; Yang, Tianming

2017-07-01

The origins and authenticity against frauds are two essential aspects of food quality. In this work, a comprehensive quality evaluation method by FT-NIR spectroscopy and chemometrics were suggested to address the geographical origins and authentication of Chinese Ganoderma lucidum (GL). Classification for 25 groups of GL samples (7 common species from 15 producing areas) was performed using near-infrared spectroscopy and interval-combination One-Versus-One least squares support vector machine (IC-OVO-LS-SVM). Untargeted analysis of 4 adulterants of cheaper mushrooms was performed by one-class partial least squares (OCPLS) modeling for each of the 7 GL species. After outlier diagnosis and comparing the influences of different preprocessing methods and spectral intervals on classification, IC-OVO-LS-SVM with standard normal variate (SNV) spectra obtained a total classification accuracy of 0.9317, an average sensitivity and specificity of 0.9306 and 0.9971, respectively. With SNV or second-order derivative (D2) spectra, OCPLS could detect at least 2% or more doping levels of adulterants for 5 of the 7 GL species and 5% or more doping levels for the other 2 GL species. This study demonstrates the feasibility of using new chemometrics and NIR spectroscopy for fine classification of GL geographical origins and species as well as for untargeted analysis of multiple adulterants.

Formulation design for poorly water-soluble drugs based on biopharmaceutics classification system: basic approaches and practical applications.

PubMed

Kawabata, Yohei; Wada, Koichi; Nakatani, Manabu; Yamada, Shizuo; Onoue, Satomi

2011-11-25

The poor oral bioavailability arising from poor aqueous solubility should make drug research and development more difficult. Various approaches have been developed with a focus on enhancement of the solubility, dissolution rate, and oral bioavailability of poorly water-soluble drugs. To complete development works within a limited amount of time, the establishment of a suitable formulation strategy should be a key consideration for the pharmaceutical development of poorly water-soluble drugs. In this article, viable formulation options are reviewed on the basis of the biopharmaceutics classification system of drug substances. The article describes the basic approaches for poorly water-soluble drugs, such as crystal modification, micronization, amorphization, self-emulsification, cyclodextrin complexation, and pH modification. Literature-based examples of the formulation options for poorly water-soluble compounds and their practical application to marketed products are also provided. Classification of drug candidates based on their biopharmaceutical properties can provide an indication of the difficulty of drug development works. A better understanding of the physicochemical and biopharmaceutical properties of drug substances and the limitations of each delivery option should lead to efficient formulation development for poorly water-soluble drugs. Copyright © 2011 Elsevier B.V. All rights reserved.