Application of Rough Set Theory to Water Quality Analysis: A Case Study

This work proposes an approach to analyze water quality data that is based on rough set theory. Six major water quality indicators (temperature, pH, dissolved oxygen, turbidity, specific conductivity, and nitrate concentration) were collected at the outlet of the watershed that contains the George Mason University campus in Fairfax, VA during three years (October 2015–December 2017). Rough set theory is applied to monthly averages of the collected data to estimate one indicator (decision attribute) based on the remainder indicators and to determine what indicators (conditional attributes) are essential (core) to predict the missing indicator. The redundant attributes are identified, the importance degree of each attribute is quantified, and the certainty and coverage of any detected rule(s) is evaluated. Possible decision making rules are also assessed and the certainty coverage factor is calculated. Results show that the core water quality indicators for the Mason watershed during the study period are turbidity and specific conductivity. Particularly, if pH is chosen as a decision attribute, the importance degree of turbidity is higher than the one of conductivity. If the decision attribute is turbidity, the only indispensable attribute is specific conductivity and if specific conductivity is the decision attribute, the indispensable attribute beside turbidity is temperature.

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Analysis and assessment of confined and phreatic water quality using a rough set theory method in Jilin City, China

Water Science & Technology Water Supply ◽

10.2166/ws.2015.031 ◽

2015 ◽

Vol 15 (4) ◽

pp. 773-783 ◽

Cited By ~ 2

Author(s):

He Huang ◽

Xiujuan Liang ◽

Changlai Xiao ◽

Zhong Wang

Keyword(s):

Water Quality ◽

Groundwater Quality ◽

Pore Water ◽

Set Theory ◽

Rough Set ◽

Rough Set Theory ◽

Quality Data ◽

Confined Water ◽

Permissible Limits ◽

Phreatic Water

In groundwater quality assessments it is easier and more effective to reduce the number of parameters included in water quality indices. A total of 20 quaternary loose rock pore water and tertiary clastic rock cranny pore water data sets were used for Jilin City, China, as basic data, and 10 water quality parameters were selected for reduction using rough set theory and a statistical analysis of groundwater quality. Results showed that the quality of confined water was better than that of phreatic water in the study area. Confined water was of good quality, and met the permissible limits of the Quality Standards for Groundwater of China, with the exception of NH4+ and F−. For phreatic water, the five parameters of total dissolved solids, NH4+, NO2−, Fe, and F− exceeded the permissible limits, with levels of NH4+ and Fe having a 70% and 40% rate of exceedance, respectively. The results indicated that water evaluation before and after attribute reduction was consistent, which suggests that through rough set theory redundant parameters in indices were eliminated but the accuracy of water quality classification remained effective, while the complexity of the calculation was reduced. Rough set theory provides a convenient and appropriate way to manage large amounts of water quality data.

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Application of a Parallel Particle Swarm Optimization-Long Short Term Memory Model to Improve Water Quality Data

Water ◽

10.3390/w11071317 ◽

2019 ◽

Vol 11 (7) ◽

pp. 1317 ◽

Cited By ~ 3

Author(s):

Jianzhuo Yan ◽

Xinyue Chen ◽

Yongchuan Yu ◽

Xiaojuan Zhang

Keyword(s):

Water Quality ◽

Quality Indicators ◽

Short Term Memory ◽

Predictive Accuracy ◽

Quality Data ◽

Short Term ◽

Water Quality Data ◽

Swarm Optimization ◽

Water Quality Indicators ◽

Long Short Term Memory

Water quality data cleaning is important for the management of water environments. A framework for water quality time series cleaning is proposed in this paper. Considering the nonlinear relationships among water quality indicators, support vector regression (SVR) is used to forecast water quality indicators when some indicators are missing or when they show abnormal values at a certain point in time. Considering the time series of water quality information, long short-term memory (LSTM) networks are used to forecast water quality indicators when all indicators are missing at a certain point in time. A parallel model based on particle swarm optimization (PSO) and LSTM is realized based on a microservices architecture to improve the efficiency of model execution and the predictive accuracy of the LSTM networks. The performance of the model is evaluated in terms of the mean absolute error (MAE) and root-mean-square error (RMSE). Inlet water quality data from a wastewater treatment plant in Gaobeidian, Beijing, China is considered as a case study to examine the effectiveness of this approach. The experimental results reveal that this model has better predictive accuracy than other data-driven models because of smaller MAE and RMSE and has an advantage in terms of time consumption compared with standalone serial algorithms.

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Dampak Limbah Penambangan Emas Tanpa Izin (Peti) Terhadap Kualitas Air Sungai Limun Kabupaten Sarolangun Propinsi Jambi - The Impact Of Illegal Gold Mining Activity To The Water Quality Of Limun River, Sarolangun District, Jambi Province

Bulletin of Scientific Contribution ◽

10.24198/bsc.vol14.yr2016.art10969 ◽

2017 ◽

Vol 14 (3) ◽

pp. 251

Author(s):

Rita Yulianti ◽

Emi Sukiyah ◽

Nana Sulaksana

Keyword(s):

Water Quality ◽

Gold Mining ◽

Quality Standard ◽

Water Levels ◽

Quality Analysis ◽

Quality Data ◽

Mining Activities ◽

Water Quality Data ◽

The Impact

Daerah penelitian terletak di desa Muaro Limun, Kecamatan Limun Kabupaten Sarolangun Provinsi Jambi. Sungai limun, salah satu sungai besar di daerah kabupaten sarolangun yang dimanfaatkan oleh mayarakat sekitarnya sebagai sumber penghidupan. Penelitian bertujuan untuk mengetahui pengaruh kegiatan penambangan terhadap kualitas air sungai Batang Limun, dan perubahan sifat fisik dan kimia yang diakibatkan kegiatan penambangan.Metode yang digunakan adalah metode grab sampel, serta stream sedimen untuk dianalis di laboratorium. Sejumlah sampel diambil di beberapa lokasi Penambangan Emas berdasarkan Aliran Sub-DAS dan dibandingkan dengan beberapa sampel lain yang diambil pada lokasi yang belum terkontaminasi oleh kegiatan penambangan. Analisis kualitas air mengacu pada SMEWWke 22 tahun 2012 dan standar baku mutu air kelas II dalam PP No 82 yang dikeluarkan oleh Menteri Kesehatan No. 492/Menkes/Per/IV/2010. Diketahui sungai Batang Limun telah mengalami perubahan karakteristik fisika dan kimia. Dari grafik kosentrasi kekeruhan, pH, TSS, TDS Cu, Pb, Zn, Mn, Hg terlihat bahwa penambang emas tanpa izin (PETI) dengan cara amalgamasi yang menyebabkan terjadinya penurunan kualitas air sungai. Sejak tahun 2009 sampai tahun 2015 sungai Limun dan sekitarnya terus mengalami penurunan kualitas air. Penurunan kualitas yang cukup tinggi terjadi yaitu peningkatan nilai Rata-rata konsentrasi merkuri pada sungai Batang Limun dari 0,18ppb (0,00018 mg/l) menjadi 0,3ppb (0,0003 mg/l), peningkatan tersebut dipengaruhi oleh proses kegiatan penambangan dan nilai tersebut masih dibawah standar baku mutu air kelas II pp nomor 82 tahun 2010.Kata kunci : Kualitas Air, Sungai Limun,TSS, Merkuri, PETI Limun river is one of the major rivers in the area of Sarolangun, which utilized by the society as a source of livelihood. The aim of study to analyze the effect of mining activities on the water quality of Batang Limun River, and the changes of physical and chemical properties of water. The method used are grab and stream samples to sediment analyzed in the laboratory. A number of samples were taken at several locations based Flow Gold Mining Sub-watershed and compared to some other samples taken at the location that has not been contaminated by mining activities. Water quality analysis referring to SMEWW, 22nd edition 2012 and refers to Regulation No 82 that issued by Minister of Health No. 492 / Menkes / Per / IV / 2010.The results showed that the Limun river has undergone chemical changes in physical characteristics. These symptoms can be seen from the discoloration of clear water in the river before the mine becomes brownish after mining, based on graphic of muddiness concentration: pH, TSS, TDS Cu, Pb, Zn, Mn, Hg have seen that the illegal miner which used amalgamation caused deterioration in water quality, data from 2009 to 2015 Limun river and surrounding areas continue to experience a decrease in water quality. The decreasing of water quality showed in the TSS parameter which found in the area is to high based on the standard of water quality class II pp number 82 of 2010. An increase in the value of average concentrations of mercury in the Batang Limun river before mine 0,18ppb (0.00018 mg / l) into 0,3ppb (0.0003 mg / l) on the river after the mine. The increase was affected by the mining activities and the value is still below the air quality standard Grade II pp numbers 82 years 2010, although the value is still below with the standards quality standard, the mercury levels in water should still be a major concern because if it accumulates continuously in the water levels will increase and will be bad for health. In contrast to the concentration of mercury in sediments that have a higher value is 153 ppb (0,513ppm ) .Key Words : Water Quality, Limun River, Mercury, Illegal gold mining

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GRQA: Global River Water Quality Archive

10.5194/essd-2021-51 ◽

2021 ◽

Author(s):

Holger Virro ◽

Giuseppe Amatulli ◽

Alexander Kmoch ◽

Longzhu Shen ◽

Evelyn Uuemaa

Keyword(s):

Water Quality ◽

Time Series ◽

Quality Measurement ◽

Observation Time ◽

Quality Analysis ◽

Quality Data ◽

Observation Data ◽

Water Quality Data ◽

Spatial Coverage ◽

Global Datasets

Abstract. A major problem related to global water quality analysis and modelling has been the lack of available good quality and consistent water quality measurement datasets with a global spatial coverage. Current study aims to contribute into improving the global datasets on water quality by aggregating and harmonizing five national, continental and global datasets: CESI, GEMSTAT, GLORICH, WATERBASE and WQP. The GRQA compilation involved converting observation data from the five sources into a common format and harmonizing the corresponding metadata, flagging outliers, calculating time series characteristics and detecting duplicate observations from sources with a spatial overlap. The final dataset extends the spatial and temporal coverage of previously available water quality data and contains 42 parameters and over 16 million measurements around the globe covering the 1898–2020 time period. Metadata in the form of statistical tables, maps and figures are provided along with observation time series. The GRQA dataset, supplementary metadata and ﬁgures are available for download on the DataCite and OpenAire enabled repository of the University of Tartu, DataDOI, http://dx.doi.org/10.23673/re-273 (Virro et al., 2021).

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ANALISIS KONDISI LAMUN (SEAGRASS) DI PERAIRAN PULAU PRAMUKA, KEPULAUAN SERIBU

Jurnal SPATIAL Wahana Komunikasi dan Informasi Geografi ◽

10.21009/spatial.131.03 ◽

2015 ◽

Vol 13 (1) ◽

pp. 22-32

Author(s):

Septi Dwi Fajarwati ◽

Asma Irma Setianingsih ◽

Muzani Muzani

Keyword(s):

Water Quality ◽

Community Structure ◽

Ph Value ◽

Secondary Data ◽

Quality Analysis ◽

Quality Data ◽

Primary Data ◽

Seagrass Habitat ◽

Percentage Cover ◽

Water Quality Data

ABSTRACT This research aims to analyze the condition of seagrass ecosystem to see water quality data of the seagrass habitat and percentage cover of seagrass in the waters of the Pramuka Island, Seribu Islands. The research was conducted over two months from October to November 2014.This research used a descriptive method with field survey approach. The population in this study is the seagrass in Waters Pramuka Island. Determining the location with purposive sampling of the sampling is divided into three stations is North, East and South. Data collection techniques include primary data and secondary data. Primary data is data of seagrass (type, percentage cover and density of seagrass) and data of seagrass habitat environmental parameters (water temperature, current speed, brightness, depth, salinity, substrate, TSS, DO, pH) were obtained by direct measurement in the field, while secondary data include the general state of the research sites. Data analysis techniques used in this study using analysis of community structure of seagrass and water quality analysis. The results showed that seagrass species found in the Pramuka Island there are 6 types of seagrass Cymodocea rotundata, Cymodocea serrulata, Enhalus acoroides, Halophila ovalis, Halodule uninervis, Thalassia hemprichii. Conditions of seagrass in the waters of the Pramuka Island included into the category of less healthy-poor seagrass. At station 1 percentage by 31% classified seagrass less healthy conditions, while the other two stations are stations 2 and 3 belong to the category of the poor condition of seagrass, with each percentage cover of seagrass 19.4% and 20.3%. Of all water quality parameters measured, all the parameters are still in normal circumstances, but there are some parameters whose value is high at some stations TSS and pH value is high at station 2 with a value of TSS 18 mg/l and a pH value of 8.2. Water quality and seagrass communities in station 1 is still in good condition for the growth of seagrass, because at this station is an unspoiled area away from human activity, while the stations 2 and 3 have undergone changes in community structure of seagrass because at this station has several anthropogenic activities that disrupt the lives of seagrass, mostly from human activities such as domestic sewage and hoarding/reclamation, which affects the condition of seagrass at station 2 and 3 are poor seagrass. Keyword: Seagrass, Water Quality, Pramuka Island

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PERENCANAAN ARTIFICIAL REEF SEBAGAI RESTORASI TERUMBU KARANG DAN PENGAMAN PANTAIDI PULAU LEMUKUTAN KABUPATEN BENGKAYANG

Jurnal Teknologi Lingkungan Lahan Basah ◽

10.26418/jtllb.v3i1.9081 ◽

2015 ◽

Vol 3 (1) ◽

Cited By ~ 1

Author(s):

Dhiecho Mahar Dhiecha

Keyword(s):

Water Quality ◽

Coral Reefs ◽

Life Quality ◽

Artificial Reef ◽

Thick Layer ◽

Secondary Data ◽

Quality Analysis ◽

Quality Data ◽

Coastal Protection ◽

Water Quality Data

ABSTRACT Damage that occurs around the area Lemukutan Island caused the use of chemicals or cyanide to catch fish and coral reefs by local people, but it is also often made use of bombs surrounding communities to take beautiful corals that will be sold to destroy coral reef ecosystems in the waters .Artificial reef planning methods (Artificial reef ) as the restoration of coral reefs and coastal protection is to conduct a field survey using a measuring instrument GPS topographic, marine water quality data and using secondary data, statistical data, tidal, wave height, bathymetry map, direction of flow and wind direction. Water quality analysis carried out in-situ, parameter test in the brightness of the water, currents, salinity, temperature, pH. Analysis of the function of Artificial reefs for reef restoration and as coastal protection is to use a hollow dome type or reef balls. Appropriate placement location and located at coordinates N 00 45 '33.8 ", E 1080 42' 19.5" up to N 00 45 '29.2 "E 1070 15' 49.0", and the average depth of 3 meters. Results of water quality testing based on parameters salinity, current velocity, pH, turbidity, light intensity and temperature qualify coral life quality standards in Indonesia based on PERMEN LH No. 51 TAHUN 2004. The dimensions of Artificial reef s diameter of 1.80 m, height 1.50 m with a thick layer of 10 cm and a hole located on the sides of the Artificial reef for 34 holes with a diameter of 15 cm. Filler material used is concrete with a volume of 0.916 m3, equivalent to 2,198 tons. Binder or cement used type V, which is resistant to high sulfate levels. The amount of reef balls used is 834 pieces. Keywords: Artificial reef , Seawater Quality, Reef balls and coral reefs,.

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The Fluctuation of Water Quality of Ci Lutung flow areas in Majalengka and Sumedang.

E3S Web of Conferences ◽

10.1051/e3sconf/20187304013 ◽

2018 ◽

Vol 73 ◽

pp. 04013

Author(s):

Deddy Caesar Agusto ◽

Eko Kusratmoko

Keyword(s):

Water Quality ◽

Point Source ◽

Agricultural Land ◽

Quality Data ◽

Water Quality Data ◽

Water Quality Indicators ◽

Quality Of Water ◽

The Moment ◽

The Impact

The river is the main source of water in Indonesia, which at the moment, this quality tends to get worse and is no longer worth consuming for various needs. The cause of the pollution is the entry of pollutants both point source (industrial waste) and non-point source (residential and agricultural land). Rainfall can be a non-point source pollutant agent from a watershed to a water body. The impact of rainfall on increasing concentrations of pollutants is very significant, especially the high intensity rainfall that falls after the long dry season. In this study, water quality data is obtained from river outlets located in Damkamun taken every 30 minutes during the rainfall event so that fluctuation in water quality can be seen. Water quality indicators studied in this research are TDS, DHLNitrate, Phosphate and Ph. The author, in analyzing, using rainfall Himawari 8 which is obtained every 10 minutes. The result shows that rainfall is directly related to the water flow and the fluctuation of the discharge affects the water quality. From the calculations, the chemical quality of water is also influenced by the use of land in the watershed. Nitrate value increases when the occurrence of rain occurs in land use while phosphate experiences a high value during the event.

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A GIS Methodology to Determine the Critical Regions for Mitigating Eutrophication in Large Territories: The Case of Jalisco, Mexico

Sustainability ◽

10.3390/su13148029 ◽

2021 ◽

Vol 13 (14) ◽

pp. 8029

Author(s):

Enrique Cervantes-Astorga ◽

Oscar Aguilar-Juárez ◽

Danay Carrillo-Nieves ◽

Misael Sebastián Gradilla-Hernández

Keyword(s):

Water Quality ◽

Quality Indicators ◽

Trophic State ◽

Methodological Approach ◽

The State ◽

Geographical Information ◽

Quality Data ◽

Water Quality Indicators ◽

Critical Regions ◽

Over Time

Inadequate management practices for solid waste and wastewater are some of the main causes of eutrophication globally, especially in regions where intensive livestock, agricultural, and industrial activities are coupled with inexistent or ineffective waste and wastewater treatment infrastructure. In this study, a methodological approach is presented to spatially assess the trophic state of large territories based on public water quality databases. The trophic state index (TSI) includes total nitrogen, total phosphorus, chlorophyll A, chemical oxygen demand, and Secchi disk depth values as water quality indicators. A geographical information system (GIS) was used to manage the spatiotemporal attributes of the water quality data, in addition to spatially displaying the results of TSI calculations. As a case study, this methodological approach was applied to determine the critical regions for mitigating eutrophication in the state of Jalisco, Mexico. Although a decreasing trend was observed for the TSI values over time for most subbasins (2012–2019), a tendency for extreme hypereutrophication was observed in some regions, such as the Guadalajara metropolitan area and the Altos region, which are of high economic relevance at the state level. A correlation analysis was performed between the TSI parameters and rainfall measurements for all subbasins under analysis, which suggested a tendency for nutrient wash-off during the rainy seasons for most subbasins; however, further research is needed to quantify the real impacts of rainfall by including other variables such as elevation and slope. The relationships between the water quality indicators and land cover were also explored. The GIS methodology proposed in this study can be used to spatially assess the trophic state of large regions over time, taking advantage of available water quality databases. This will enable the efficient development and implementation of public policies to assess and mitigate the eutrophication of water sources, as well as the efficient allocation of resources for critical regions. Further studies should focus on applying integrated approaches combining on-site monitoring data, remote sensing data, and machine learning algorithms to spatially evaluate the trophic state of territories.

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Spatial and temporal trends in summertime climate and water quality indicators in the coastal embayments of Buzzards Bay, Massachusetts

Biogeosciences Discussions ◽

10.5194/bgd-12-13159-2015 ◽

2015 ◽

Vol 12 (15) ◽

pp. 13159-13192

Author(s):

J. E. Rheuban ◽

S. C. Williamson ◽

J. E. Costa ◽

D. M. Glover ◽

R. W. Jakuba ◽

...

Keyword(s):

Water Quality ◽

Quality Indicators ◽

Total Nitrogen ◽

Temporal Trends ◽

Nitrogen Loading ◽

Quality Data ◽

Water Quality Indicators ◽

Chl A ◽

Temperature And Precipitation ◽

Spatial And Temporal Trends

Abstract. Degradation of coastal ecosystems by eutrophication is largely defined by nitrogen loading from land via surface and groundwater flows. However, indicators of water quality are highly variable due to a myriad of other drivers, including temperature and precipitation. To evaluate these drivers, we examined spatial and temporal trends in a 22 year record of summer water quality data from 122 stations in 17 embayments within Buzzards Bay, MA (USA), collected through a citizen science monitoring program managed by Buzzards Bay Coalition. To identify spatial patterns across Buzzards Bay's embayments, we used a principle component and factor analysis and found that rotated factor loadings indicated little correlation between inorganic nutrients and organic matter and chlorophyll a (Chl a) concentration. Factor scores showed that embayment geomorphology in addition to nutrient loading was a strong driver of water quality, where embayments with surface water inputs showed larger biological impacts than embayments dominated by groundwater influx. A linear regression analysis of annual summertime water quality indicators over time revealed that from 1992 to 2013, most embayments (15 of 17) exhibited an increase in temperature (mean rate of 0.082 ± 0.025 (SD) °C yr−1) and Chl a (mean rate of 0.0171 ± 0.0088 log10 (Chl a; mg m−3) yr−1, equivalent to a 4.0 % increase per year). However, only 7 embayments exhibited an increase in total nitrogen (TN) concentration (mean rate 0.32 ± 0.47 (SD) μM yr−1). Average summertime log10 (TN) and log10 (Chl a) were correlated with an indication that yield of Chl a per unit total nitrogen increased with time suggesting the estuarine response to TN may have changed because of other stressors such as warming, altered precipitation patterns, or changing light levels. These findings affirm that nitrogen loading and physical aspects of embayments are essential in explaining observed ecosystem response. However, climate-related stressors may also need to be considered by managers because increased temperature and precipitation may worsen water quality and partially offset benefits achieved by reducing nitrogen loading.

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INDEKS KUALITAS AIR RAWA LEBAK DELING UNTUK BUDIDAYA PERIKANAN ALAMI

Jurnal Akuakultur Rawa Indonesia ◽

10.36706/jari.v6i2.7156 ◽

2018 ◽

Vol 6 (2) ◽

pp. 123-128

Author(s):

Irkhamiawan Ma’ruf ◽

Rahmad Kurniawan ◽

Khusnul Khotimah

Keyword(s):

Water Quality ◽

Fisheries Management ◽

Economic Benefits ◽

Quality Analysis ◽

Quality Data ◽

Water Quality Data ◽

Temperature Parameter ◽

Vegetation Water ◽

The One ◽

Quality Measurements

ABSTRACTAs a common properti, fisheries management in swamps need to be made to provides economic benefits for the parties on the one side (especially the community), and the sustainability of the ecosystem itself on the other side. Current conditions need to be obtained to formulate swamp resource management in a sustainable manner by reducing fishing activities with aquaculture activities. Aquaculture, besides providing greater income, can also control fishing activities and reduce pressure on the swamp ecosystem. The study was conducted in Rawa Deling, Deling Village, Pangkalan Lampam Sub-District, OKI District. Water quality measurements are carried out for 5 months, from March 2018 to July 2018 in 4 stations with differences depth and vegetation. Water quality analysis is carried out to get an overview of the swamp condition. Water quality data will determine the feasibility and treatment needed for aquaculture. The results of water quality measurements showed that temperature parameter values ranging from 28.1 - 32.2 oC, depths of 0.7 - 5 m, brightness of 20 - 50 cm, TDS 17 - 35 mgL-1, pH 4.1 - 5, DO 1 , 7 - 4.1 mgL-1, phosphate <0.060 - <0.090 mgL-1, total nitrogen 12.50 - 38.90 mgL-1, ammonia 0.68 - 0.93 mgL-1. Measuring water quality shows the potential for deling swamps to be developed in an effort to increase fish stocks and aquaculture activities.Keywords : lebak lebung swamps, sustainable fisheries management, swamp water quality

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