scholarly journals Modelling of nitrates in River Nzoia using MIKE 11

2017 ◽  
Vol 12 (1) ◽  
pp. 217-223 ◽  
Author(s):  
Edwin K. Kanda ◽  
Emmanuel C. Kipkorir ◽  
Job R. Kosgei
Keyword(s):  
Industrial Wastewater ◽  
Lake Victoria ◽  
Model Performance ◽  
Quality Data ◽  
Strong Positive Correlation ◽  
Nitrogen And Phosphorus ◽  
Water Quality Data ◽  
Mike 11 ◽  
Run Off ◽  
The Relationship

Eutrophication is a serious problem in Lake Victoria as a result of enrichment by nutrients transported by the rivers draining into it. River Nzoia is one of the main rivers draining into the lake. The main aim of this study was to simulate the level of nitrates using MIKE 11 and to establish relationship between nitrogen and phosphorus. The model was calibrated using water quality data for 2009 and validated with March 2013 data and then it was used to simulate nitrate concentration for the wet month of April 2013. The model performance was good with R2 values of between 0.87 and 0.98 and EF values of between 0.73 and 0.96. From the simulations, the effluent discharge from municipal and industrial wastewater ponds elevated the concentration of the nitrates in the river. Analysis of the concentrations of nitrates for wet and dry periods showed significant variations indicating significant contributions from the catchment through run-off. The relationship between total nitrogen and total phosphorus was analysed and found to have a strong positive correlation (r = 0.714, p < 0.05) indicating that both originate from similar sources or are influenced by the same factors such as agriculture.

Simulation of organic carbon loading using MIKE 11 model: a case of River Nzoia, Kenya

2015 ◽  
Vol 10 (2) ◽  
pp. 298-304 ◽  
Author(s):  
Edwin K. Kanda ◽  
Job R. Kosgei ◽  
Emmanuel C. Kipkorir
Keyword(s):  
Lake Victoria ◽  
Agricultural Runoff ◽  
Point Sources ◽  
Low Flow ◽  
Quality Data ◽  
Coefficient Of Determination ◽  
Lake Victoria Basin ◽  
Water Quality Data ◽  
Mike 11 ◽  
Mike 11 Model

River Nzoia is the largest river draining into the Kenyan portion of Lake Victoria. This river receives both point sources of pollution from industrial and municipal wastes, and non-point sources from agricultural runoff in the catchment. The objective of this study was to simulate dissolved oxygen (DO) and biochemical oxygen demand (BOD) of the middle section of River Nzoia using MIKE 11 model. The model was calibrated using discharge and water quality data for 2009 and validated with March–April 2013 data. The model performance was good with coefficient of determination (R2) values of between 0.845 and 0.995, Nash–Sutcliffe efficiency values of between 0.748 and 0.993 and percent bias of less than 10 for both calibration and validation of electrical conductivity (EC), DO and BOD. EC and BOD values were lower for April compared to March which could be attributed to dilution during high flows. DO values were above the recommended minimum level of 4 mg/l in all the sections of the river in the wet period but some sections had lower than 4 mg/l during low flow period. The government agencies such as Water Resources Management Authority and National Environment Management Authority should enforce the effluent standards to ensure that industries and wastewater treatment plants adhere to the maximum allowable limit for BOD and also improve their treatment efficiencies of wastewater plants so as to improve the quality of River Nzoia which is important in the overall management of the Lake Victoria basin.

Post-fire water-quality response in the western United States

2018 ◽  
Vol 27 (3) ◽  
pp. 203 ◽  
Author(s):  
Ashley J. Rust ◽  
Terri S. Hogue ◽  
Samuel Saxe ◽  
John McCray
Keyword(s):  
United States ◽  
Water Quality ◽  
Stream Water ◽  
Western United States ◽  
Change Point Analysis ◽  
Quality Data ◽  
Stream Water Quality ◽  
Nitrogen And Phosphorus ◽  
Water Quality Data ◽  
Quality Response

Wildfires are increasing in size and severity in forested landscapes across the Western United States. Not only do fires alter land surfaces, but they also affect the surface water quality in downstream systems. Previous studies of individual fires have observed an increase in various forms of nutrients, ions, sediments and metals in stream water for different post-fire time periods. In this research, data were compiled for over 24 000 fires across the western United States to evaluate post-fire water-quality response. The database included millions of water-quality data points downstream of these fires, and was synthesised along with geophysical data from each burned watershed. Data from 159 fires in 153 burned watersheds were used to identify common water-quality response during the first 5 years after a fire. Within this large dataset, a subset of seven fires was examined further to identify trends in water-quality response. Change-point analysis was used to identify moments in the post-fire water-quality data where significant shifts in analyte concentrations occurred. Evaluating individual fires revealed strong initial increases or decreases in concentrations, depending on the analyte, that are masked when averaged over 5 years. Evidence from this analysis shows significant increases in nutrient flux (different forms of nitrogen and phosphorus), major-ion flux and metal concentrations are the most common changes in stream water quality within the first 5 years after fire. Dissolved constituents of ions and metals tended to decrease in concentration 5 years after fire whereas particulate matter concentration continued to increase. Assembling this unique and extensive dataset provided the opportunity to determine the most common post-fire water-quality changes in the large and diverse Western USA. Results from this study could inform studies in other parts of the world, will help parameterise and validate post-fire water-quality models, and assist communities affected by wildfire to anticipate changes to their water quality.

scholarly journals Pioneering water quality data on the Lake Victoria watershed: effects on human health

2015 ◽  
Vol 13 (3) ◽  
pp. 920-930 ◽  
Author(s):  
Tamie J. Jovanelly ◽  
Julie Johnson-Pynn ◽  
James Okot-Okumu ◽  
Richard Nyenje ◽  
Emily Namaganda
Keyword(s):  
Water Quality ◽  
Drinking Water ◽  
Lake Victoria ◽  
Fecal Coliforms ◽  
World Health ◽  
Quality Data ◽  
Water Quality Data ◽  
Data Set ◽  
Forest Reserves ◽  
Elevated Exposure

Four forest reserves within 50 km of Kampala in Uganda act as a critical buffer to the Lake Victoria watershed and habitat for local populations. Over a 9-month period we capture a pioneering water quality data set that illustrates ecosystem health through the implementation of a water quality index (WQI). The WQI was calculated using field and laboratory data that reflect measured physical and chemical parameters (pH, dissolved oxygen, biological oxygen on demand, nitrates, phosphates, fecal coliform, and temperature turbidity). Overall, the WQI for the four forest reserves reflect poor to medium water quality. Results compared with US Environmental Protection Agency and World Health Organization drinking water standards indicate varying levels of contamination at most sites and all designated drinking water sources, with signatures of elevated nitrates, phosphates, and/or fecal coliforms. As critical health problems are known to arise with elevated exposure to contaminants in drinking water, this data set can be used to communicate necessary improvements within the watershed.

scholarly journals Long-Term Nitrogen and Phosphorus Dynamics in Waters Discharging from Forestry-Drained and Undrained Boreal Peatlands

2021 ◽  
Vol 232 (9) ◽  
Author(s):  
Mika Nieminen ◽  
Sakari Sarkkola ◽  
Eliza Maher Hasselquist ◽  
Tapani Sallantaus
Keyword(s):  
Quality Data ◽  
Phosphorus Concentration ◽  
Tree Stand ◽  
Nitrogen And Phosphorus ◽  
Concentration Data ◽  
Water Quality Data ◽  
Stand Volume ◽  
Temperature Sum ◽  
Nitrogen Concentrations

AbstractContradictory results for the long-term evolution of nitrogen and phosphorus concentrations in waters discharging from drained peatland forests need reconciliation. We gathered long-term (10–29 years) water quality data from 29 forested catchments, 18 forestry-drained and 11 undrained peatlands. Trend analysis of the nitrogen and phosphorus concentration data indicated variable trends from clearly decreasing to considerably increasing temporal trends. While the variations in phosphorus concentration trends over time did not correlate with any of our explanatory factors, trends in nitrogen concentrations correlated positively with tree stand volume in the catchments and temperature sum. A positive correlation of increasing nitrogen concentrations with temperature sum raises concerns of the future evolution of nitrogen dynamics under a warming climate. Furthermore, the correlation with tree stand volume is troublesome due to the generally accepted policy to tackle the climate crisis by enhancing tree growth. However, future research is still needed to assess which are the actual processes related to stand volume and temperature sum that contribute to increasing TN concentrations.

Ranking methods to set restoration and remediation priorities on a watershed scale

2008 ◽  
Vol 58 (10) ◽  
pp. 2025-2030 ◽  
Author(s):  
William T. Stringfellow
Keyword(s):  
Water Quality ◽  
Implementation Process ◽  
Scientific Data ◽  
Quality Data ◽  
Quadrant Analysis ◽  
Ranking Methods ◽  
Water Quality Data ◽  
Management Actions ◽  
Sources Of Pollution ◽  
The Relationship

The establishment of a total maximum daily load (TMDL) is part of management process that results in the institution of watershed-based controls of otherwise unregulated sources of pollution. In California (USA), the implementation of a TMDL is driven forward in a process where watershed stakeholders are expected to cooperate on actions needed to improve ecosystem health. In the TMDL process, methods are needed for synthesizing complex scientific data into actionable management information. Where pollutant load analysis may be misleading or perceived as unfair, non-parametric statistical methods can be applied to flow and water quality data to guide the selection of drainages for remediation. The calculation of normalized rank means (NRMs) for flow and water quality can be used to set priorities for the implementation of TMDL management actions. Drainages can be classified into one of four categories (quadrants) based on the relationship between flow and water quality NRMs. Drainages can be included or excluded from management action based on their quadrant classification. Although there are many possible alternative approaches, this “quadrant analysis” is suggested as a scientifically rigorous methods for identifying priority watersheds in the often contentious, stakeholder driven TMDL implementation process.

Dynamic Multivariate Analysis for Pollution Profiling and Abatement Recommendation in La Buong Watershed of Vietnam

2021 ◽  
Author(s):  
Luan Hong Pham ◽  
Dung Duc Tran ◽  
Hien Dieu Thi Le ◽  
Toan Quang Dinh ◽  
Quan Hong Nguyen ◽  
...  
Keyword(s):  
Water Quality ◽  
Time Series ◽  
Separation Of Variables ◽  
Temporal Patterns ◽  
Point Sources ◽  
Quality Data ◽  
Dynamic Factor ◽  
Water Quality Data ◽  
Run Off ◽  
Local Point

Abstract Analysis of temporal patterns of high-dimensional time-series water quality data is essential in informing better pollution management. In this study, Dynamic Factor Analysis (DFA) and Cluster Analysis (CA) were adopted to analyze time-series water quality data monitored at five stations SB1, SB2, SB3, SB4 and SB5 on La Buong river in the Southern Vietnam. Application of DFA identified two temporal patterns in SB1 and SB2 and three temporal patterns in SB3, SB4 and SB5. Analysis of factor loadings of water variables revealed run-off-driven patterns with the contribution of Total Suspended Solid (TSS), turbidity or Fe at all stations. The association of other variables like BOD5, COD at SB1, SB2, SB4, and SB5 to this run-off pattern exposed their sharing of common driver. On the contrary, separation of variables like Phosphate (PO43−) in SB3, SB4 and SB5 from run-off pattern suggested their local point-source origin. The derived factors from DFA were later used in time-point CA to explore temporal distribution of pollution intensities. Comparisons between clusters’ value and two regulatory benchmarks A2 and B1 for drinking and irrigation water respectively suggested land-use approach for abating TSS, Fe and BOD5, COD at most sites. The control of point sources of BOD5 and COD pollutants is needed at SB3 along with PO43−, Ammonium (NH4+) and Escherichia coli (E.coli) at SB1 and SB4.

scholarly journals Prediction of dissolved oxygen in urban rivers at the Three Gorges Reservoir, China: extreme learning machines (ELM) versus artificial neural network (ANN)

2019 ◽  
Vol 55 (1) ◽  
pp. 106-118 ◽  
Author(s):  
Senlin Zhu ◽  
Salim Heddam
Keyword(s):  
Neural Network ◽  
Water Quality ◽  
Dissolved Oxygen ◽  
Three Gorges Reservoir ◽  
Model Performance ◽  
Quality Data ◽  
Urban Rivers ◽  
Three Gorges ◽  
Water Quality Data ◽  
The Three Gorges

Abstract In the present study, two non-linear mathematical modelling approaches, namely, extreme learning machine (ELM) and multilayer perceptron neural network (MLPNN) were developed to predict daily dissolved oxygen (DO) concentrations. Water quality data from four urban rivers in the backwater zone of the Three Gorges Reservoir, China were used. The water quality data selected consisted of daily observed water temperature, pH, permanganate index, ammonia nitrogen, electrical conductivity, chemical oxygen demand, total nitrogen, total phosphorus and DO. The accuracy of the ELM model was compared with the standard MLPNN using several error statistics such as root mean squared error, mean absolute error, the coefficient of correlation and the Willmott index of agreement. Results showed that the ELM and MLPNN models perform well for the Wubu River, acceptably for the Yipin River and moderately for the Huaxi River, while poor model performance was obtained at the Tributary of Huaxi River. Model performance is negatively correlated with pollution level in each river. The MLPNN model slightly outperforms the ELM model in DO prediction. Overall, it can be concluded that MLPNN and ELM models can be applied for DO prediction in low-impacted rivers, while they may not be appropriate for DO modelling for highly polluted rivers. This article has been made Open Access thanks to the kind support of CAWQ/ACQE (https://www.cawq.ca).

scholarly journals Utilisation of Maqalika Reservoir as a source of potable water for Maseru city in Lesotho

2005 ◽  
Author(s):  
◽  
Masupha Letsie
Keyword(s):  
Water Quality ◽  
National Standards ◽  
Quality Data ◽  
Ungauged Catchments ◽  
Water Quality Data ◽  
Mean Values ◽  
Run Off ◽  
Remaining Capacity ◽  
The Impact

Lesotho is a land locked country, entirely surrounded by the Republic of South Africa. Maseru is the capital of Lesotho and the country’s main centre for commerce and industry. The study area is located on the North-Eastern outskirts of the Maseru urban area. The catchment occupies an area of 44km2 with a length of about 13 km and channel slope of 0.4 km/km. The Maqalika Reservoir was built in 1983 to meet the water demands for Maseru city up to 1995, and its storage capacity was 3.7 Mm3. The storage is gradually decreasing as sediment, carried by the natural run-off accumulates in the reservoir. Moreover, water pumped into the reservoir from the Caledon River (which is heavily sedimented) adds its own contribution of silt. The reservoir is located in a very densely populated area, and is heavily polluted leading to high purification costs. The study was motivated by the fact that Welbedacht Dam was constructed in 1973 in the Caledon catchment but downstream of Maqalika. After 20 years, 85% of the volume of the dam was silted. The study was intended in finding whether the positioning of the Maqalika reservoir is acceptable and to find its remaining capacity as a water body supplying a fast growing city. Consideration was also given to the effect of land use practices on the water quality of the Maqalika reservoir, including the cost incurred during purification. The water quality data on physico- chemical was collected from the Water and Sewerage Authority and was analysed using excel spreadsheets. Results obtained were compared with WHO, SABS and National Standards of Lesotho. It was found that nitrates, phosphates and faecal coliforms levels were by far above minimum standards rendering water to be very contaminated and the source being leaking sewers, defeacation in dongas and leachate from Tsosane and Lower Thamae dumping site. Iron levels were also high with mean values beyond 0.3mg/l and the source being leachate from dumping sites, poor disposal of scraps and minerals from soil. Conductivity levels were high and the suspected source is waste solid disposal having a maximum of 442mS/m in March 2001. Hardness, temperature and alkalinity do not pose much danger to Maqalika water since recorded results were almost within limits. Turbidity levels were very high and the main source was found to be catchment sedimentation through run-off. For determination of the impact of sedimentation through pumping, hydrological data was obtained from the Department of Water Affair (DWA) and analysed using Excel spreadsheets to get sediment concentrations. A linear regression graph was plotted using discharge against sediment concentration that yielded y = 0.0007x – 0.0019. This was used in the Rooseboom mathematical equation for estimation of volume occupied by sediment from 1983 - 2002 and was found to be 6789 m3. For determination of the impact due to catchment run-off, a map method of estimating sedimentation from ungauged catchments developed by Rooseboom was used and a volume of 4.598 x 106 m3 was obtained showing that the main contributor of sedimentation in the reservoir is catchment run-off. The chemical costs employed during purification were also compared between WASA and Umgeni Water of Kwazulu- Natal and WASA was found to be expensive with 9 cents/kl while Umgeni spent only 5.24 cents/kl.

Assessing water-quality data: The relationship between the water quality amelioration of Lake Balaton and the construction of its mitigation wetland

2014 ◽  
Vol 40 (1) ◽  
pp. 115-125 ◽  
Author(s):  
István Gábor Hatvani ◽  
Adrienne Clement ◽  
József Kovács ◽  
Ilona Székely Kovács ◽  
János Korponai
Keyword(s):  
Water Quality ◽  
Quality Data ◽  
Lake Balaton ◽  
Water Quality Data ◽  
Mitigation Wetland ◽  
The Relationship
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