Best subset modelling of phosphorus in the Grand River using correlated variables

1996 ◽  
Vol 23 (4) ◽  
pp. 893-903 ◽  
Author(s):  
A. Tyagi ◽  
M. Sharma ◽  
E. McBean
Keyword(s):  
Water Quality ◽  
River Basin ◽  
Stepwise Regression ◽  
Suspended Solids ◽  
Statistical Modelling ◽  
Quality Parameters ◽  
Independent Variables ◽  
Modelling Procedure ◽  
Different Seasons ◽  
Grand River

Statistical models are developed for the estimation of phosphorus concentrations for different seasons and locations using routinely monitored water quality parameters in the Grand River Basin. Two methods of modelling, namely the best subset model and the stepwise regression method based on R2 and F values, are described. The best subset modelling procedure enables comparison between full model (containing all the independent variables) and subset models (containing subsets of independent variables). For correlated independent variables, the best subset modelling procedure is shown to provide a better model than the stepwise regression procedure. The statistical modelling results indicate that suspended solids play an important role in the prediction of phosphorus levels and consequently decreasing suspended solids would decrease the growth of aquatic plants in the Grand River Basin. Key words: regression modelling, water quality, phosphorus, suspended solids, rivers, statistics.

scholarly journals The Evaluation of Dissolved Oxygen (DO), Total Suspended Solids (TSS) and Suspended Sediment Concentration (SSC) in Terengganu River, Malaysia

2018 ◽  
Vol 7 (3.14) ◽  
pp. 44
Author(s):  
Noorjima Abd Wahab ◽  
Mohd Khairul Amri Kamarudin ◽  
Mohd Ekhwan Toriman ◽  
Frankie Marcus Ata ◽  
Hafizan Juahir ◽  
...  
Keyword(s):  
Water Quality ◽  
Land Use ◽  
Dissolved Oxygen ◽  
Suspended Sediment ◽  
River Basin ◽  
Suspended Solids ◽  
Suspended Sediment Concentration ◽  
Total Suspended Solids ◽  
Sediment Concentration ◽  
Quality Parameters

Terengganu River Basin is situated in the north eastern coastal region of Peninsular Malaysia. 29 sampling stations were selected. The water quality parameters were measured such as Dissolved Oxygen (DO), Total Suspended Solids (TSS) and Suspended Sediment Concentration (SSC). Results showed that the range of DO (2.11 mg/L – 8.07 mg/L), TSS (0.4 mg/L – 128.2 mg/L) and SSC (0.07 mg/L – 25.6 mg/L). The distribution of land use and land cover activities effected to the level of water quality in watersheds. The analyses of variance (ANOVA) was applied and provide a better understanding for the complex relationships among water quality parameters. Graphical data helps a better view of the overall analysis to appoint sources of pollutants to their effect. Terengganu River Basin is a shallow and has a sensitive ecosystem that responds to the land use changes and development activities of its surroundings. Water quality analysis showed that TSS and SSC were higher in the dry season but DO were higher in the wet season. Overall, the water in the Terengganu River Basin classified slightly contaminated especially the main sources of pollutants were possibly waste products and waste from development activities such as sand mining, farming, residential and agricultural.  

Seagrass depth range and water quality in southern Moreton Bay, Queensland, Australia

1996 ◽  
Vol 47 (6) ◽  
pp. 763 ◽  
Author(s):  
EG Abal ◽  
WC Dennison
Keyword(s):  
Water Quality ◽  
Chlorophyll A ◽  
Suspended Solids ◽  
Light Attenuation ◽  
River Mouth ◽  
Total Suspended Solids ◽  
Quality Parameters ◽  
Depth Range ◽  
Moreton Bay ◽  
A Site

Correlations between water quality parameters and seagrass depth penetration were developed for use as a biological indicator of integrated light availability and long-term trends in water quality. A year-long water quality monitoring programme in Moreton Bay was coupled with a series of seagrass depth transects. A strong gradient between the western (landward) and eastern (seaward) portions of Moreton Bay was observed in both water quality and seagrass depth range. Higher concentrations of chlorophyll a, total suspended solids, dissolved and total nutrients, and light attenuation coefficients in the water column and correspondingly shallower depth limits of the seagrass Zostera capricorni were observed in the western portions of the bay. Relatively high correlation coefficient values (r2 > 0.8) were observed between light attenuation coefficient, total suspended solids, chlorophyll a, total Kjeldahl nitrogen and Zostera capricorni depth range. Low correlation coefficient values (r2 < 0.8) between seagrass depth range and dissolved inorganic nutrients were observed. Seagrasses had disappeared over a five-year period near the mouth of the Logan River, a turbid river with increased land use in its watershed. At a site 9 km from the river mouth, a significant decrease in seagrass depth range corresponded to higher light attenuation, chlorophyll a, total suspended solids and total nitrogen content relative to a site 21 km from the river mouth. Seagrass depth penetration thus appears to be a sensitive bio-indicator of some water quality parameters, with application for water quality management.

scholarly journals Limnology of Merbok estuary, Kedah, Malaysia

2015 ◽  
Vol 41 (1) ◽  
pp. 13-19
Author(s):  
Kaniz Fatema ◽  
Wan Maznah Wan Omar ◽  
Mansor Mat Isa
Keyword(s):  
Water Quality ◽  
Dissolved Oxygen ◽  
Suspended Solids ◽  
Total Suspended Solids ◽  
Quality Parameters ◽  
The Other ◽  
Wet Season ◽  
Hand Temperature ◽  
Do Concentration ◽  
Merbok Estuary

Water quality in three different stations of Merbok estuary was investigated limnologically from October, 2010 to September, 2011. Water temperature, transparency and total suspended solids (TSS) varied from 27.45 - 30.450C, 7.5 - 120 cm and 10 -140 mg/l, respectively. Dissolved Oxygen (DO) concentration ranged from 1.22-10.8 mg/l, while salinity ranged from 3.5-35.00 ppt. pH and conductivity ranged from 6.35 - 8.25 and 40 - 380 ?S/cm, respectively. Kruskal Wallis H test shows that water quality parameters were significantly different among the sampling months and stations (p<0.05). This study revealed that DO, salinity, conductivity and transparency were higher in wet season and TSS was higher in dry season. On the other hand, temperature and pH did not follow any seasonal trends.Bangladesh J. Zool. 41(1): 13-19, 2013

Statistical and Data Mining Techniques for Understanding Water Quality Profiles in a Mining-Affected River Basin

2018 ◽  
Vol 9 (2) ◽  
pp. 1-19 ◽  
Author(s):  
Jose Simmonds ◽  
Juan A. Gómez ◽  
Agapito Ledezma
Keyword(s):  
Data Mining ◽  
Water Quality ◽  
River Basin ◽  
Suspended Solids ◽  
Water Quality Monitoring ◽  
High Flow ◽  
Quality Monitoring ◽  
Low Flow ◽  
Inverse Relation

This article contains a multivariate analysis (MV), data mining (DM) techniques and water quality index (WQI) metrics which were applied to a water quality dataset from three water quality monitoring stations in the Petaquilla River Basin, Panama, to understand the environmental stress on the river and to assess the feasibility for drinking. Principal Components and Factor Analysis (PCA/FA), indicated that the factors which changed the quality of the water for the two seasons differed. During the low flow season, water quality showed to be influenced by turbidity (NTU) and total suspended solids (TSS). For the high flow season, main changes on water quality were characterized by an inverse relation of NTU and TSS with electrical conductivity (EC) and chlorides (Cl), followed by sources of agricultural pollution. To complement the MV analysis, DM techniques like cluster analysis (CA) and classification (CLA) was applied and to assess the quality of the water for drinking, a WQI.

The Chao Phraya River Basin: water quality and anthropogenic influences

2018 ◽  
Vol 19 (5) ◽  
pp. 1287-1294 ◽  
Author(s):  
Nuanchan Singkran ◽  
Pitchaya Anantawong ◽  
Naree Intharawichian ◽  
Karika Kunta
Keyword(s):  
Water Quality ◽  
Land Use ◽  
River Basin ◽  
River Mouth ◽  
Oxygen Demand ◽  
Quality Parameters ◽  
Paddy Fields ◽  
Coliform Bacteria ◽  
Wet Season ◽  
Chao Phraya River

Abstract Land use influences and trends in water quality parameters were determined for the Chao Phraya River, Thailand. Dissolved oxygen (DO), biochemical oxygen demand (BOD), and nitrate-nitrogen (NO3-N) showed significant trends (R2 ≥ 0.5) across the year, while total phosphorus (TP) and faecal coliform bacteria (FCB) showed significant trends only in the wet season. DO increased, but BOD, NO3-N, and TP decreased, from the lower section (river kilometres (rkm) 7–58 from the river mouth) through the middle section (rkm 58–143) to the upper section (rkm 143–379) of the river. Lead and mercury showed weak/no trends (R2 &lt; 0.5). Based on the river section, major land use groups were a combination of urban and built-up areas (43%) and aquaculture (21%) in the lower river basin, paddy fields (56%) and urban and built-up areas (21%) in the middle river basin, and paddy fields (44%) and other agricultural areas (34%) in the upper river basin. Most water quality and land use attributes had significantly positive or negative correlations (at P ≤ 0.05) among each other. The river was in crisis because of high FCB concentrations. Serious measures are suggested to manage FCB and relevant human activities in the river basin.

scholarly journals Effects of Opened and Closed Spillway Operations of a Large Tropical Hydroelectric Dam on the Water Quality of the Downstream River

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Fiona-Annilow Wera ◽  
Teck-Yee Ling ◽  
Lee Nyanti ◽  
Siong-Fong Sim ◽  
Jongkar Grinang
Keyword(s):  
Water Quality ◽  
River Basin ◽  
Aquatic Organisms ◽  
Quality Parameters ◽  
Regulated River ◽  
Land Uses ◽  
Hydroelectric Dam ◽  
Water Ph ◽  
The Impact

Water quality downstream of a hydroelectric dam is potentially affected by dam operations and other land uses in the river basin. Previous short-distance studies below the large Bakun Dam indicated poorer water quality during closed spillway. However, the extent of the impact is still unknown. Such knowledge is essential for mitigating the impact of the dam. Thus, the objectives of this study were to determine the water quality up to a distance of 210 km under two spillway operations, namely, closed and opened spillways, and also to determine the changes in water quality from the predam condition. Physicochemical parameters were measured at 15 stations along the Rajang River. Results of this preliminary study indicated that there were significant differences in eight out of nine water quality parameters between opened and closed spillway operations with opened spillway showing better water quality. During closed spillway, as we approached the dam, there was an increasing acidity and a decreasing oxygen content. Furthermore, as the water flows downstream, the unhealthy DO level (<5 mg/L) extended up to 165 km and the linear model showed an increasing DO rate of 0.09 mg/L per km. With opened spillway, DO decreased exponentially from 9.74 mg/L towards the downstream direction to 7.67 mg/L. The increasing turbidity and TSS in the downstream direction indicate contributions from erosion due to other land uses. The river is polluted with organics as indicated by COD of Class IV or V with sources from the dam and the activities in the river basin. Compared to the predam condition, the regulated river is less turbid but warmer and higher in ammonia. Closed spillway led to lower DO and acidic water. However, opened spillway water pH and DO were similar to those in the predam condition. Thus, it is recommended that DO be consistently high enough for the health of sensitive aquatic organisms downstream.

scholarly journals Real-time water quality monitoring through Internet of Things and ANOVA-based analysis: a case study on river Krishna

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Prasad M. Pujar ◽  
Harish H. Kenchannavar ◽  
Raviraj M. Kulkarni ◽  
Umakant P. Kulkarni
Keyword(s):  
Water Quality ◽  
Internet Of Things ◽  
Real Time ◽  
River Basin ◽  
Water Quality Monitoring ◽  
Quality Parameters ◽  
Quality Monitoring ◽  
Quality Analysis ◽  
Water Quality Analysis

AbstractIn this paper, an attempt has been made to develop a statistical model based on Internet of Things (IoT) for water quality analysis of river Krishna using different water quality parameters such as pH, conductivity, dissolved oxygen, temperature, biochemical oxygen demand, total dissolved solids and conductivity. These parameters are very important to assess the water quality of the river. The water quality data were collected from six stations of river Krishna in the state of Karnataka. River Krishna is the fourth largest river in India with approximately 1400 km of length and flows from its origin toward Bay of Bengal. In our study, we have considered only stretch of river Krishna flowing in state of Karnataka, i.e., length of about 483 km. In recent years, the mineral-rich river basin is subjected to rapid industrialization, thus polluting the river basin. The river water is bound to get polluted from various pollutants such as the urban waste water, agricultural waste and industrial waste, thus making it unusable for anthropogenic activities. The traditional manual technique that is under use is a very slow process. It requires staff to collect the water samples from the site and take them to the laboratory and then perform the analysis on various water parameters which is costly and time-consuming process. The timely information about water quality is thus unavailable to the people in the river basin area. This creates a perfect opportunity for swift real-time water quality check through analysis of water samples collected from the river Krishna. IoT is one of the ways with which real-time monitoring of water quality of river Krishna can be done in quick time. In this paper, we have emphasized on IoT-based water quality monitoring by applying the statistical analysis for the data collected from the river Krishna. One-way analysis of variance (ANOVA) and two-way ANOVA were applied for the data collected, and found that one-way ANOVA was more effective in carrying out water quality analysis. The hypotheses that are drawn using ANOVA were used for water quality analysis. Further, these analyses can be used to train the IoT system so that it can take the decision whenever there is abnormal change in the reading of any of the water quality parameters.

scholarly journals Comparative analysis of the outflow water quality of two sustainable linear drainage systems

2014 ◽  
Vol 70 (8) ◽  
pp. 1341-1347 ◽  
Author(s):  
V. C. Andrés-Valeri ◽  
D. Castro-Fresno ◽  
L. A. Sañudo-Fontaneda ◽  
J. Rodriguez-Hernandez
Keyword(s):  
Water Quality ◽  
Petroleum Hydrocarbons ◽  
Suspended Solids ◽  
Drainage System ◽  
Quality Parameters ◽  
Total Petroleum Hydrocarbons ◽  
Drainage Systems ◽  
System A ◽  
Car Park

Three different drainage systems were built in a roadside car park located on the outskirts of Oviedo (Spain): two sustainable urban drainage systems (SUDS), a swale and a filter drain; and one conventional drainage system, a concrete ditch, which is representative of the most frequently used roadside drainage system in Spain. The concentrations of pollutants were analyzed in the outflow of all three systems in order to compare their capacity to improve water quality. Physicochemical water quality parameters such as dissolved oxygen, total suspended solids, pH, electrical conductivity, turbidity and total petroleum hydrocarbons were monitored and analyzed for 25 months. Results are presented in detail showing significantly smaller amounts of outflow pollutants in SUDS than in conventional drainage systems, especially in the filter drain which provided the best performance.

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