scholarly journals Water Transparency Prediction of Plain Urban River Network: A Case Study of Yangtze River Delta in China

2021 ◽  
Vol 13 (13) ◽  
pp. 7372
Author(s):  
Yipeng Liao ◽  
Yun Li ◽  
Jingxiang Shu ◽  
Zhiyong Wan ◽  
Benyou Jia ◽  
...  
Keyword(s):  
Water Quality ◽  
Flow Velocity ◽  
Oxygen Demand ◽  
Water Quality Monitoring ◽  
Yangtze River Delta ◽  
Quality Parameters ◽  
River Network ◽  
Urban River ◽  
Water Transparency ◽  
Ann Model

Water transparency is commonly used to indicate the combined effect of hydrodynamics and the aquatic environment on water quality throughout a river network. However, how water transparency responds to these indicators still needs to be explored, especially their complicated nonlinear relationship; thus, this study represents an analysis of the Suzhou civil river network. Using an artificial neural network (ANN) hydrological model and a multiple linear model (MLR) with in-situ data between 2013–2019, we investigated the Suzhou River’s sensitivity to the six factors and water transparency, which including flow velocity and data from five categories of water-quality monitoring data: total suspended matter (TSS), water temperature (TE), dissolved oxygen (DO), chlorophyll (Chl) and chemical oxygen demand (COD). The results suggest that the ANN model can achieve better performance than the MLR model. Furthermore, results also show a well-established correlation between enhanced hydrodynamics and improved water transparency when the flow velocity ranged from 0.22 to 0.45 m/s. Overall, COD is a vital factor for the SD prediction because including the COD can see a notable improvement in the ANN model (with a correlation coefficient of 0.918). This study demonstrates that the ANN model with hydrodynamic and water quality parameters can achieve a better prediction of water transparency than other discussed models for a coastal plain urban river network.

scholarly journals EVALUATING SURFACE WATER QUALITY AND WATER MONITORING PARAMETERS IN THE TIEN RIVER, VIETNAMESE MEKONG DELTA

2021 ◽  
Vol 83 (3) ◽  
pp. 29-36
Author(s):  
Thanh Giao Nguyen ◽  
Vo Quang Minh
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Monitoring Program ◽  
Oxygen Demand ◽  
Surface Water Quality ◽  
Principal Component ◽  
Water Quality Monitoring ◽  
Quality Parameters ◽  
Water Monitoring ◽  
Water Quality Parameters

The study aimed to evaluate the surface water quality of the Tien River and identify water quality parameters to be monitored using the water quality monitoring data in the period of 2011 - 2019. The water samples were collected at five locations from Tan Chau to Cho Moi districts, An Giang province for three times per year (i.e., in March, June, and September). Water quality parameters included temperature (oC), pH, dissolved oxygen (DO), total suspended solids (TSS), nitrate (NO3--N), orthophosphate (PO43--P), biological oxygen demand (BOD), and coliforms. These parameter results were compared with the national technical regulation on surface water quality QCVN 08-MT: 2015/BTNMT, column A1. Principal component analysis (PCA) was used to identify the sources of pollution and the main factors affecting water quality. The results of this study showed that DO concentration was lower and TSS, BOD, PO43--P, coliforms concentrations in the Tien river exceeded QCVN 08-MT: 2015/BTNMT, column A1. pH, temperature, and NO3--N values were in accordance with the permitted regulation. The water monitoring parameters were seasonally fluctuated. DO, BOD, TSS, and coliforms concentrations were higher in the rainy season whereas NO3--N and PO43--P were higher in the dry season. The PCA results illustrated that pH, TSS, DO, BOD, PO43--P and coliforms should be included in the monitoring program. Other indicators such as temperature and NO3--N could be considered excluded from the program to save costs. 

scholarly journals Water Quality Monitoring with Emphasis on Estimation of Point and Diffuse Pollution Sources

2019 ◽  
Vol 21 (2) ◽  
pp. 163-171
Keyword(s):  
Water Quality ◽  
Organic Nitrogen ◽  
Nitrate Nitrogen ◽  
Anthropogenic Activities ◽  
Oxygen Demand ◽  
Water Quality Monitoring ◽  
Total Coliform ◽  
Ammonium Nitrogen ◽  
Quality Parameters ◽  
Water Quality Parameters

<p>Population growth, urbanization and anthropogenic activities are becoming a serious problem for water resources in Turkey, which necessitates their monitoring and maintenance of water quality. In this study, water quality was implemented in the Porsuk Stream in Inner Anatolia, Turkey. Water samples were collected at monthly intervals between the period of 2008-2010 at four selected stations. Twenty one water quality parameters were measured which are water temperature (T), pH, dissolved oxygen (DO), electrical conductivity (EC), salinity, turbidity, chloride, suspended solids, dissolved solids, organic nitrogen (Org-N), ammonium nitrogen (NH3-N), nitrite nitrogen (NO2-N), nitrate nitrogen (NO3-N), total organic carbon, biological oxygen demand (BOD), chemical oxygen demand (COD), total coliform, alkalinity, orthophosphate phosphorus (PO43--P), total phosphorus and chlorophyll-a. The monitoring was conducted to see how the water quality changed along the stream in response to various anthropogenic activities. Besides, a paired t-test was utilized to determine the concentration differences at stations above and below the single most important point source of pollutants (Eskişehir city). Moreover, a regression model was used to establish relations between water quality parameters and flow and to estimate nonpoint source loadings.</p>

Risk prediction of microcystins based on water quality surrogates: A case study in a eutrophicated urban river network

2021 ◽  
Vol 275 ◽  
pp. 116651
Author(s):  
Xinchen He ◽  
Hua Wang ◽  
Wei Zhuang ◽  
Dongfang Liang ◽  
Yanhui Ao
Keyword(s):  
Water Quality ◽  
Risk Prediction ◽  
River Network ◽  
Urban River

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 Cladoceran abundance in relation to water quality parameters of Chakki Talab, Bodhan, Telangana

2018 ◽  
Vol 8 (01) ◽  
Author(s):  
Vasudha Lingampally ◽  
V.R. Solanki ◽  
D. L. Anuradha ◽  
Sabita Raja
Keyword(s):  
Water Quality ◽  
Dissolved Oxygen ◽  
Oxygen Demand ◽  
Total Dissolved Solids ◽  
Quality Parameters ◽  
Biological Oxygen Demand ◽  
Water Quality Parameters ◽  
Total Alkalinity ◽  
Total Hardness ◽  
One Year

In the present study an attempt has been made to evaluate water quality and related density of Cladocerans for a period of one year, October 2015 to September 2016. Water quality parameters such as temperature, PH, total dissolved solids, dissolved oxygen, biological oxygen demand, total alkalinity, total hardness, chlorides, phosphates, and nitrates are presented here to relate with the abundance of Cladocerans. The Cladoceran abundance reflects the eutrophic nature of the Chakki talab.

scholarly journals Water monitoring and analytic based thingspeak

2020 ◽  
Vol 10 (4) ◽  
pp. 3588
Author(s):  
Abbas Hussien Miry ◽  
Gregor Alexander Aramice
Keyword(s):  
Water Quality ◽  
Normal Values ◽  
Water Quality Monitoring ◽  
Lag Time ◽  
Quality Parameters ◽  
Quality Monitoring ◽  
Proposed Model ◽  
Response To Water ◽  
Matlab Programming ◽  
The Internet Of Things

Diseases associated with bad water have largely reported cases annually leading to deaths, therefore the water quality monitoring become necessary to provide safe water. Traditional monitoring includes manual gathering of samples from different points on the distributed site, and then testing in laboratory. This procedure has proven that it is ineffective because it is laborious, lag time and lacks online results to enhance proactive response to water pollution. Emergence of the Internet of Things (IoT) and step towards the smart life poses the successful using of IoT. This paper presents a water quality monitoring using IoT based ThingSpeak platform that provides analytic tools and visualization using MATLAB programming. The proposed model is used to test water samples using sensor fusion technique such as TDS and Turbidity, and then uploading data online to ThingSpeak platform to monitor and analyze. The system notifies authorities when there are water quality parameters out of a predefined set of normal values. A warning will be notified to user by IFTTT protocol.

scholarly journals Physicochemical and Microbiological Water Quality Assessment of Aba Waterside River, Aba, Nigeria

2019 ◽  
Vol 3 (1) ◽  
pp. 142-148
Author(s):  
L. O. Bobor ◽  
C. M. Umeh
Keyword(s):  
Water Quality ◽  
Drinking Water ◽  
Management Strategies ◽  
Oxygen Demand ◽  
Water Quality Monitoring ◽  
Control Measures ◽  
Fecal Coliforms ◽  
Water Quality Control ◽  
Inorganic Substances ◽  
The Impact

The indiscriminate disposal of industrial effluents and solid wastes in surface water bodies is detrimental to humans and aquatic organisms. Water quality monitoring is critical to identify pollutants of concern and develop effective management strategies. Hence, this study was conducted to assess the impact of waste disposal on the water quality of Aba Waterside River, Ogbor hill, Aba. Grab samples were collected upstream, midstream and downstream and some physicochemical and microbiological parameters were analyzed in accordance with standard methods for the analysis of water and wastewater. The results were compared with the Nigerian standard for drinking water quality and the national environmental effluent limitation regulations. Turbidity levels (10 -31mg/l) exceeded the maximum permissible levels for drinking water (5mg/l) and may be associated with higher levels of embedded disease-causing microbes and potentially harmful organic and inorganic substances. The biological oxygen demand midstream (1960mg/l) was remarkably high due to the effluent discharged from the abattoirs at that point. Fecal coliforms (3-198MPN/100ml) were detected in all samples, indicating the presence of other potentially harmful microorganisms. The findings of this study indicate that the water is unsuitable for direct drinking water purposes and stringent water quality control measures should be implemented.

Ecological assessment of water quality for different water uses: the upstream sub-basin of the Dnieper and Desna rivers

2021 ◽  
Vol 12 (2) ◽  
Author(s):  
V Strokal ◽  
◽  
A Kovpak ◽  
Keyword(s):  
Water Pollution ◽  
Water Quality ◽  
Oxygen Demand ◽  
Agricultural Runoff ◽  
Ammonium Nitrogen ◽  
Quality Parameters ◽  
Harmful Algae ◽  
Main Research ◽  
Average Temperature ◽  
The Status

Novelties of this study include a synthesis of water quality parameters for the upstream sub-basin of the Dnieper River. This upstream sub-basin includes the Desna River. The synthesis revels new insights on the sources of the water pollution and the status of the water quality for different purposes such as drinking, aquaculture and recreation. The main research objective was to identify the main sources of water pollution and how those sources could decrease the water quality. As a result of our analysis, we conclude the following. The levels of ammonium-nitrogen and nitrite-nitrogen in the Desna River (upstream sub-basin) are by 2-43 times and up to 53 times higher than the water quality thresholds, respectively. This poses a risk for recreational activities since too much nutrients often lead to blooms of harmful algae. We also find an increased level of biological oxygen demand in the river for drinking purposes. For aquaculture, decreased levels of dissolved oxygen are found. Climate change has an impact on water quality. For example, extreme floods caused by too much precipitation can bring pollutants to nearby waters. Monthly average temperature has increased by +2.7 degrees contributing to increased microbiological processes that could stimulate blooms of harmful algae. Main sources of water pollution are sewage discharges in cities, agricultural runoff and erosion activities after floods.

scholarly journals Use of Artificial Neural Networks and Multiple Linear Regression Model for the Prediction of Dissolved Oxygen in Rivers: Case Study of Hydrographic Basin of River Nyando, Kenya

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-23 ◽  
Author(s):  
Yashon O. Ouma ◽  
Clinton O. Okuku ◽  
Evalyne N. Njau
Keyword(s):  
Water Quality ◽  
Linear Regression ◽  
Dissolved Oxygen ◽  
Multiple Linear Regression ◽  
Pearson Correlation ◽  
Multiple Linear Regression Model ◽  
Water Quality Monitoring ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Quality Monitoring

The process of predicting water quality over a catchment area is complex due to the inherently nonlinear interactions between the water quality parameters and their temporal and spatial variability. The empirical, conceptual, and physical distributed models for the simulation of hydrological interactions may not adequately represent the nonlinear dynamics in the process of water quality prediction, especially in watersheds with scarce water quality monitoring networks. To overcome the lack of data in water quality monitoring and prediction, this paper presents an approach based on the feedforward neural network (FNN) model for the simulation and prediction of dissolved oxygen (DO) in the Nyando River basin in Kenya. To understand the influence of the contributing factors to the DO variations, the model considered the inputs from the available water quality parameters (WQPs) including discharge, electrical conductivity (EC), pH, turbidity, temperature, total phosphates (TPs), and total nitrates (TNs) as the basin land-use and land-cover (LULC) percentages. The performance of the FNN model is compared with the multiple linear regression (MLR) model. For both FNN and MLR models, the use of the eight water quality parameters yielded the best DO prediction results with respective Pearson correlation coefficient R values of 0.8546 and 0.6199. In the model optimization, EC, TP, TN, pH, and temperature were most significant contributing water quality parameters with 85.5% in DO prediction. For both models, LULC gave the best results with successful prediction of DO at nearly 98% degree of accuracy, with the combination of LULC and the water quality parameters presenting the same degree of accuracy for both FNN and MLR models.

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