Implications of Dynamic Interactions between Meteorological Patterns and Surface Water Quality on Environmental Health—A Case Study of the Nairobi River

Urban areas face significant challenges in maintaining water quality amidst increasing urbanization and changing climatic patterns. This study investigates the complex interplay between meteorological variables and water quality parameters in Nairobi City, focusing on the impacts of rainfall and temperature on surface water quality. Data from multiple sources, including the Water Resources Authority, Nairobi Water and Sewerage Company, and the World Bank’s Climate Change Knowledge Portal, were analyzed to assess the relationships between meteorological variables (rainfall and temperature) and water quality parameters (such as electroconductivity, biochemical oxygen demand, chloride, and pH). The analysis reveals varying impacts of rainfall and temperature on different water quality parameters. While parameters like iron and pH show strong relationships with both rainfall and temperature, others such as ammonia and nitrate exhibit moderate relationships. Additionally, the study highlights the influence of runoff, urbanization, and industrial activities on water quality, emphasizing the need for holistic management approaches. Recommendations encompass the establishment of annual publications on Nairobi River water quality, online accessibility of water quality data, development of hydrological models, spatial analysis, and fostering cross-disciplinary research collaborations. Implementing these recommendations can enhance water quality management practices, mitigate risks, and safeguard environmental integrity in Nairobi City.

Exploring groundwater quality in semi-arid areas of Algeria:Impacts on potable water supply and agricultural sustainability

Groundwater quality assessment is important to assure safe and durable water use.In semi-arid areas of Algeria,groundwater represents the main water resource for drinking water supply of the rural population as well as for irrigation of agricultural lands.Groundwater samples from wells and springs were collected from the Gargaat Tarf and Annk Djemel sub-watersheds of the Oum El Bouaghi,Algeria,and were analyzed and compared with the World Health Organization(WHO)standards.Results showed that most of the measured physical and chemical parameters exceeded the quality limits according to the WHO standards.Groundwater had a slightly alkaline water pH(7.00-7.79),electrical conductivity>1500μS/cm,chloride>500 mg/L,calcium>250 mg/L,and magnesium>155 mg/L.Water quality index(WQI)results showed that 68%of the area had excellent water quality,24%of the samples fell into good category,and only 8%were of poor quality and unsuitable for human consumption.Six wells in the area showed bacterial contamination.Total coliforms(453.9(±180.3)CFU(colony-forming units)/100 mL),fecal coliforms(243.2(±99.2)CFU/100 mL),and fecal streptococci(77.9(±32.0)CFU/100 mL)loads were above the standard limits set by the WHO.These results confirmed that water resources in the study area were strongly influenced by anthropogenic activities and were not recommended for consumption as drinking water.

Monitoring and evaluation of the water quality of the Lower Neches River, Texas, USA

Increasing bacteria levels in the Lower Neches River caused by Hurricane Harvey has been of a serious concern.This study is to analyze the historical water sampling measurements and real-time water quality data collected with wireless sensors to monitor and evaluate water quality under different hydrological and hydraulic conditions.The statistical and Pearson correlation analysis on historical water samples determines that alkalinity,chloride,hardness,conductivity,and pH are highly correlated,and they decrease with increasing flow rate due to dilution.The flow rate has positive correlations with Escherichia coli,total suspended solids,and turbidity,which demonstrates that runoff is one of the causes of the elevated bacteria and sediment loadings in the river.The correlation between E.coli and turbidity indicates that turbidity greater than 45 nephelometric turbidity units in the Neches River can serve as a proxy for E.coli to indicate the bacterial outbreak.A series of statistical tools and an innovative two-layer data smoothing filter are developed to detect outliers,fill missing values,and filter spikes of the sensor measurements.The correlation analysis on the sensor data illustrates that the elevated sediment/bacteria/algae in the river is either caused by the first flush rain and heavy rain events in December to March or practices of land use and land cover.Therefore,utilizing sensor measurements along with rainfall and discharge data is recommended to monitor and evaluate water quality,then in turn to provide early alerts on water resources management decisions.

Riparian habitat quality as an indicator of land use/land cover effects on riverine water quality

Riparian land use/land cover(LULC)plays a crucial role in maintaining riverine water quality by altering the transport of pollutants and nutrients.Nevertheless,establishing a direct relationship between water quality and LULC is challenging due to the multi-indicator nature of both factors.Water quality encompasses a multitude of physical,chemical,and biological parameters,while LULC represents a diverse array of land use types.Riparian habitat quality(RHQ)serves as an indicator of LULC.Yet,it remains to be seen whether RHQ can act as a proxy of LULC for assessing the impact of LULC on riverine water quality.This study examines the interplay between RHQ,LULC and water quality,and develops a comprehensive indicator to predict water quality.We measured several water quality parameters,including pH(potential of hydrogen),TN(total nitrogen),TP(total phosphorus),T_(water)(water temperature),DO(dissolved oxygen),and EC(electrical conductivity)of the Yue and Jinshui Rivers draining to the Han River during 2016,2017 and 2018.The water quality index(WQI)was further calculated.RHQ is assessed by the InVEST(Integrated Valuation of Ecosystem Services and Tradeoffs)model.Our study found noticeable seasonal differences in water quality,with a higher WQI observed in the dry season.The RHQ was strongly correlated with LULC compositions.RHQ positively correlated with WQI,and DO concentration and vegetation land were negatively correlated with T_(water),TN,TP,EC,cropland,and construction land.These correlations were stronger in the rainy season.Human-dominated land,such as construction land and cropland,significantly contributed to water quality degradation,whereas vegetation promoted water quality.Regression models showed that the RHQ explained variations in WQI better than LULC types.Our study concludes that RHQ is a new and comprehensive indicator for predicting the dynamics of riverine water quality.

Formation of Water Quality of Surface Water Bodies Used in the Material Processing

In the process of production or processing of materials by various methods,there is a need for a large volume of water of the required quality.Today in many regions of the world,there is an acute problem of providing industry with water of a required quality.Its solution is an urgent and difficult task.The water quality of surface water bodies is formed by a combination of a large number of both natural and anthropogenic factors,and is often significantly heterogeneous not only in the water area,but also in depth.As a rule,the water supply of large industrial enterprises is located along the river network.Mergers are the most important nodes of river systems.Understanding the mechanism of transport of pollutants at the confluence of rivers is critical for assessing water quality.In recent years,thanks to the data of satellite images,the interest of researchers in the phenomenon of mixing the waters of merging rivers has increased.The nature of the merger is influenced by the formation of transverse circulation.Within the framework of this work,a study of vorticity,as well as the width of the mixing zone,depending on the distance from the confluence,the speeds of the merging rivers and the angle of confluence was carried out.Since the consumer properties of water are largely determined by its chemical and physical indicators,the intensity of mixing,determined largely by the nature of the secondary circulation,is of fundamental importance for assessing the distribution of hydrochemical indicators of water quality in the mixing zone.These characteristics are important not only for organizing water intake for drinking and technical purposes with the best consumer properties,but also for organizing an effective monitoring system for confluence zones.

Surface Water Quality Profiling Using Physicochemical Parameters in Open Defecation Free and Non-Open Defecation Free Local Government Areas in Benue State, Nigeria

Physicochemical parameters of surface water sources in the study of local government areas (LGAs) were assessed using standard procedures. The mean physicochemical parameters for pH (5.49), NO2 (0.23 mg/L), SO4 (0.77 mg/L), Na (28.72 mg/L), Ca (28.94 mg/L), Mg (17.50 mg/L), Cl (11.65 mg/L), TSS (6.27 mg/L), TDS (104.23 mg/L), BOD (2.83 mg/L) and F (0.87 mg/L) were below WHO standards irrespective of their defecation status. The values for electrical conductivity (EC) (2770.50 µs/cm, turbidity (481.24 NTU), dissolved oxygen (DO) (5.32 mg/L), chemical oxygen demand (COD) (445.50 mg/L), K (125.06 mg/L), PO4 (0.78 mg/L) and Fe (0.57 mg/L) were above the WHO limits for safe water. Higher EC and COD values obtained in the study is evidence of pollution of the water sources by organic matter.

Spatial-temporal Variation Characteristics of Water Quality in the Lower Reaches of the Nenjiang River

As an important river in the western part of Jilin Province,the lower reach of the Nenjiang River is an important wetland water source conservation area in Jilin Province.Within the watershed,it governs the Momoge Wetland,the Xianghai Wetland,and the Danjiang Wetland in Jilin Province.The main problem in the lower reaches of the Nenjiang River is the uneven distribution of water resources in time and space,and the intensification of land salinization.Zhenlai County and Da an City in the Nenjiang River Basin have sufficient surface water resources,with surface water as the drinking water source.Baicheng City and Tongyu County have scarce surface water resources,and both use groundwater as their domestic water source.The main polluted section in the basin is the Xianghai Reservoir,and the annual water quality evaluation is Class V.However,the water quality of the Tao er River,the main stream of the Nenjiang River,is significantly better than that of the Xianghai Reservoir.In order to better study the water environmental pollution situation in the Nenjiang River basin,monitoring data from five sections of non seasonal rivers in the basin from 2012 to 2021 were selected for studying water quality.This in-depth exploration of the water pollution status and river water quality change trends in the Nenjiang River basin is of great significance for future rural development,agricultural pattern transformation,and the promotion of water ecological civilization construction.

Assessment of Rainwater Quality in Warri and Environ, Southern Nigeria for Domestic Purposes

The study aimed at assessing the physiochemical characteristics of rainwater in Warri and it environ was investigated. Pb, Zn, Cd, Cu and Cr concentrations in rainwater from roof and non-roof sources were determined using Atomic Absorption Spectrophotometry. Three geospatial locations comprising Jakpa, Udu, and Ubeji were selected based on prevailing anthropogenic activities. The rainwater samples were systematically collected from (aluminum) roof and non-roof sources for the months of April, June, and August and October 2022, treated and analyzed in the laboratory for sixteen physicochemical parameters. Results were statistically analyzed using ANOVA, and T-test for the determination of the level of relationships and variations across geospatial locations. Significant correlations (r = 0.72) exist between Cr in rainwater from roof and non-roof sources. Implying point-source contaminations and may be emanating from the influence of roof materials. Furthermore, high concentrations of Cd and Pb in roof source above WHO standards were mostly in Jakpa and Ubeji. Calculated Health Risk Index (HRI) for children and adult is greater than 1. The results showed that most samples from the locations are considered not safe (HRI > 1) especially for Cd, which means that there are potential health risks consuming rainwater from Jakpa, Udu and Ubeji. Therefore, there is need for prompt sensitization program to dissuade people from directly drinking rainwater from these locations.

Dynamics of Potable Well Water Quality in Key Mining Chiefdoms in Kono District, Eastern Sierra Leone

Groundwater is increasingly being used due to its universal availability and generally good quality. However, the risk of contamination of groundwater due to various human activities such as mining is equally increasing across the globe. In this study, the physical parameters of potable well waters in the key mining areas in Nimikoro and Tankoro Chiefdoms in Kono District were analyzed for compliance with drinking water quality standard. To do this, both unpurged and purged well water samples were collected once every month for a period of one year. Some of the well water properties like temperature, Total Dissolved Solids (TDS) and Electrical Conductivity (EC) were measured on site and others determined in the laboratory. The data collected from the laboratory analyses were statistically analyzed in MS Excel, SPSS and ArcGIS environments for quality trends in time-space fabric. The results showed that well water quality in the study area generally fell short of drinking water quality standards of Sierra Leone and WHO. There were high temperature and turbidity during the dry season and then high TDS and EC during the rainy season. Temperature and turbidity also significantly influenced well water quality in the study area, much more than TDS and EC. The implications for drinking water of lower quality than the standard could be huge for the local population and therefore needs the attention of stakeholders in the study area and decision makers in the country.

Integrated Analysis of Water Quality in Artificial Fishponds Using WQI and GIS in South-East Sierra Leone

Artificial fishponds play a pivotal role in global aquaculture, serving as a source of livelihood and nourishment for many communities. Ensuring the sustained health and productivity of Fishes in these environments relies heavily on water quality management. This assessment was done to determine the water quality of ten artificial fishponds in the south-eastern part of Sierra Leone using twelve physicochemical factors (pH, BOD, EC, TDS, turbidity, COD, Fe2+, Mg2+, Ca2+, NH3, , and alkalinity) to find out the Water Quality Index (WQI) and spatial distribution of respective parameters. The assessment of artificial fishponds using WQI and Inverse Distant Weighting (IDW) integration represents a relatively underexplored area within the domain of environmental water resources. The WQI was determined using the “Weighted Arithmetic Water Quality Index’’ method. The results of WQI in the study area range from 65.05 to 147.26. Several locations have water quality deemed unsuitable for consumption, while others range from good to very poor. It is essential to address and improve water quality in locations categorized as unsuitable for consumption and very poor to ensure safe and healthy water sources. It was also clear from the calculation that the smaller the mean concentration value of the pH as compared to the ideal value (7), the smaller the WQI value and the better the water quality. To keep the artificial fishpond water in good condition, mass domestic use should be controlled, and draining of surrounding organic matter should be stopped in ponds Bo_001, Kenema_001, and Kenema_002.

Spatial and Temporal Variation and Trend Analysis of Water Quality in Large Reservoirs in Ji’an City

Based on the water quality monitoring data of 5 large reservoirs in Ji’an City,Jiangxi Province from 2015-2021,the temporal and spatial variation characteristics and trends of water quality of the reservoirs were analyzed by single-factor evaluation method and seasonal Kendall test to evaluate the trophic status of the reservoirs and explore the influencing factors of characteristic pollutants.The results showed that:①the water quality of the reservoirs was good and could meet the water needs of various functions;②the water quality of the reservoirs had generally changed from bad to good in recent years,indicating that the implementation of“river chief system”has achieved certain results;③Kendall test analysis showed that,except for individual projects which showed an upward trend in water quality,other projects showed no obvious change trend or downward trend,indicating that the water quality of the reservoirs is indeed improving;④the causes of water pollution in reservoir area were further analyzed by exploring the natural and human factors of the characteristic pollutant total phosphorus.It is recommended to strengthen supervision in the later stage to control point and non-point source pollution.

Research Status of Water Quality Criteria and Standards and Analysis on the Transformation Methods

Under the vision of development for the new era,China has entered a stage of high-quality economic development and an important window period in which we have the conditions and ability to address the prominent issue of economic development and ecological protection in a coordinated way.However,all kinds of environmental benchmark values in China are lacking and need to be constantly supplemented and improved.Therefore,exploring and putting forward a simple and efficient method for the transformation of environmental criteria into environmental standards is an important basis for the rapid establishment of relevant environmental criteria system and the effective promotion of the development of environmental standards system towards a scientific and reasonable direction.In this paper,the water environment is taken as the research object.By analyzing the research progress of environmental criteria and standards at home and abroad,and the foreign method of transforming environmental criteria into environmental standards,combined with the problems faced in the process of transforming environmental criteria into environmental standards in China,an effective method to transform China's environmental criteria into environmental standards is analyzed.After analysis and comparison,it is found that the pollution reduction accounting method could achieve their simple and efficient conversion.Under the premise of obtaining environmental criteria for certain pollutants,environmental criteria for certain pollutants could be obtained by distributing pollutants reduction costs,and accounting economic benefits after reaching standard,thus obtaining the environmental standard of this type of pollutant,which provides reference to determine the environmental standard limits of such pollutants.

Correlation Analysis of Turbidity and Total Phosphorus in Water Quality Monitoring Data

At present,water pollution has become an important factor affecting and restricting national and regional economic development.Total phosphorus is one of the main sources of water pollution and eutrophication,so the prediction of total phosphorus in water quality has good research significance.This paper selects the total phosphorus and turbidity data for analysis by crawling the data of the water quality monitoring platform.By constructing the attribute object mapping relationship,the correlation between the two indicators was analyzed and used to predict the future data.Firstly,the monthly mean and daily mean concentrations of total phosphorus and turbidity outliers were calculated after cleaning,and the correlation between them was analyzed.Secondly,the correlation coefficients of different times and frequencies were used to predict the values for the next five days,and the data trend was predicted by python visualization.Finally,the real value was compared with the predicted value data,and the results showed that the correlation between total phosphorus and turbidity was useful in predicting the water quality.

Characteristics of Surface Water Quality Affected by Agricultural Non-point Sources in Guigang City

[Objectives]To analyze the influence characteristics of surface water quality by agricultural non-point sources in Guigang City of Guangxi.[Methods]The daily concentration series of water quality indicators at three state-controlled monitoring stations in Guigang City from^(2)019 to 2021 was analyzed by using Daubechies(db)wavelet,and Morlet wavelet was used to analyze the daily average concentration of water quality indicators.Continuous wavelet transform(CWT)was used to analyze the monthly concentration series of water quality indicators at three state-controlled monitoring stations in Guigang City from^(2)014 to 2021.[Results]The Daubechies(db)wavelet analysis showed that the concentrations of COD_(Mn),TP,and TN had the maximum values during June-July and October-November,and there were spatial differences among monitoring stations(COD_(Mn) concentration exceeding the standard was the most serious in Shizui,and DO concentration not up to standard was the most in Thermal Power Plant,and NH_(3)-N,TP and TN exceeding the standard was the most in Wulin Ferry).Morlet results showed that principal period of wavelet variance graphs of COD_(Mn),NH_(3)-N,and TP was 340 d,and there was the same sub-period of 140 d,and principal period of wavelet variance graph of DO was 260 d.CWT results showed that COD_(Cr) had similar resonance periods of about 1-2 and 5-7 months;BOD 5 and COD_(Mn) was dominant by the resonance period of 1-4 months(2014-2017);DO had a similar resonance period of about 1-3 months;NH_(3)-N was dominant by the resonance period of 1-5 months.[Conclusions]The surface water quality of Guigang City was mainly affected by the residual nitrogen and phosphorus nutrients and pesticide residues from agricultural production activities.

Spatial changes and driving factors of lake water quality in Inner Mongolia, China

Lakes play important roles in sustaining the ecosystem and economic development in Inner Mongolia Autonomous Region of China,but the spatial patterns and driving mechanisms of water quality in lakes so far remain unclear.This study aimed to identify the spatial changes in water quality and the driving factors of seven lakes(Juyanhai Lake,Ulansuhai Lake,Hongjiannao Lake,Daihai Lake,Chagannaoer Lake,Hulun Lake,and Wulannuoer Lake)across the longitudinal axis(from the west to the east)of Inner Mongolia.Large-scale research was conducted using the comprehensive trophic level index(TLI(Σ)),multivariate statistics,and spatial analysis methods.The results showed that most lakes in Inner Mongolia were weakly alkaline.Total dissolved solids and salinity of lake water showed obvious zonation characteristics.Nitrogen and phosphorus were identified as the main pollutants in lakes,with high average concentrations of total nitrogen and total phosphorus being of 4.05 and 0.21 mg/L,respectively.The values of TLI(Σ)ranged from 49.14 to 71.77,indicating varying degrees of lake eutrophication,and phosphorus was the main driver of lake eutrophication.The lakes of Inner Mongolia could be categorized into lakes to the west of Daihai Lake and lakes to the east of Daihai Lake in terms of salinity and TLI(Σ).The salinity levels of lakes to the west of Daihai Lake exceeded those of lakes to the east of Daihai Lake,whereas the opposite trend was observed for lake trophic level.The intensity and mode of anthropogenic activities were the driving factors of the spatial patterns of lake water quality.It is recommended to control the impact of anthropogenic activities on the water quality of lakes in Inner Mongolia to improve lake ecological environment.These findings provide a more thorough understanding of the driving mechanism of the spatial patterns of water quality in lakes of Inner Mongolia,which can be used to develop strategies for lake ecosystem protection and water resources management in this region.

Anthropogenic disturbance of aquatic biodiversity and water quality of an urban river in Penang, Malaysia

Malaysia's rapid economic and demographic development have placed negative pressure on its water supplies and the quality of the Juru River, which is close to the nation's capital and its major source of water. Healthy aquatic ecosystems are supported by physicochemical properties and biological diversity. This study evaluated the anthropogenic impacts on aquatic biodiversity, especially plankton, fish, and macrobenthos, as well as the water quality of the Juru River in the Penang area. Aquatic biodiversity and river water parameters were collected from ten sampling stations along the Juru River. Seven variables were used to assess the physicochemical environment: pH, temperature, total suspended solids (TSS), salinity, dissolved oxygen (DO), biochemical oxygen demand (BOD), and chemical oxygen demand. At each sampling station, the total number of plankton, fish, and macrobenthic taxa were counted and analyzed. The relationships between the physicochemical parameters and aquatic biodiversity were investigated with biotypological analysis, principal component analysis, hierarchical cluster analysis, and linear regression analysis. These analyses showed that the richness and diversity indices were generally influenced by salinity, temperature, TSS, BOD, and pH. The data obtained in this study supported the bioindicator concept. The findings, as they related to scientifically informed conservation, could serve as a model for Juru River management, as well as for river management throughout Malaysia and other tropical Asian countries.

A Stacked Ensemble Deep Learning Approach for Imbalanced Multi-Class Water Quality Index Prediction

A common difficulty in building prediction models with real-world environmental datasets is the skewed distribution of classes.There are significantly more samples for day-to-day classes,while rare events such as polluted classes are uncommon.Consequently,the limited availability of minority outcomes lowers the classifier’s overall reliability.This study assesses the capability of machine learning(ML)algorithms in tackling imbalanced water quality data based on the metrics of precision,recall,and F1 score.It intends to balance the misled accuracy towards the majority of data.Hence,10 ML algorithms of its performance are compared.The classifiers included are AdaBoost,SupportVector Machine,Linear Discriminant Analysis,k-Nearest Neighbors,Naive Bayes,Decision Trees,Random Forest,Extra Trees,Bagging,and the Multilayer Perceptron.This study also uses the Easy Ensemble Classifier,Balanced Bagging,andRUSBoost algorithm to evaluatemulti-class imbalanced learning methods.The comparison results revealed that a highaccuracy machine learning model is not always good in recall and sensitivity.This paper’s stacked ensemble deep learning(SE-DL)generalization model effectively classifies the water quality index(WQI)based on 23 input variables.The proposed algorithm achieved a remarkable average of 95.69%,94.96%,92.92%,and 93.88%for accuracy,precision,recall,and F1 score,respectively.In addition,the proposed model is compared against two state-of-the-art classifiers,the XGBoost(eXtreme Gradient Boosting)and Light Gradient Boosting Machine,where performance metrics of balanced accuracy and g-mean are included.The experimental setup concluded XGBoost with a higher balanced accuracy and G-mean.However,the SE-DL model has a better and more balanced performance in the F1 score.The SE-DL model aligns with the goal of this study to ensure the balance between accuracy and completeness for each water quality class.The proposed algorithm is also capable of higher efficiency at a lower computational time against using the standard SyntheticMinority Oversampling Technique(SMOTE)approach to imbalanced datasets.

Application of Time Serial Model in Water Quality Predicting

Water resources are an indispensable and valuable resource for human survival and development.Water quality predicting plays an important role in the protection and development of water resources.It is difficult to predictwater quality due to its random and trend changes.Therefore,amethod of predicting water quality which combines Auto Regressive Integrated Moving Average(ARIMA)and clusteringmodelwas proposed in this paper.By taking thewater qualitymonitoring data of a certain river basin as a sample,thewater quality Total Phosphorus(TP)index was selected as the prediction object.Firstly,the sample data was cleaned,stationary analyzed,and white noise analyzed.Secondly,the appropriate parameters were selected according to the Bayesian Information Criterion(BIC)principle,and the trend component characteristics were obtained by using ARIMA to conduct water quality predicting.Thirdly,the relationship between the precipitation and the TP index in themonitoring water field was analyzed by the K-means clusteringmethod,and the random incremental characteristics of precipitation on water quality changes were calculated.Finally,by combining with the trend component characteristics and the random incremental characteristics,the water quality prediction results were calculated.Compared with the ARIMA water quality prediction method,experiments showed that the proposed method has higher accuracy,and its Mean Absolute Error(MAE),Mean Square Error(MSE),and Mean Absolute Percentage Error(MAPE)were respectively reduced by 44.6%,56.8%,and 45.8%.

Artificial Intelligence in Internet of Things System for Predicting Water Quality in Aquaculture Fishponds

Aquaculture has long been a critical economic sector in Taiwan.Since a key factor in aquaculture production efficiency is water quality,an effective means of monitoring the dissolved oxygen content(DOC)of aquaculture water is essential.This study developed an internet of things system for monitoring DOC by collecting essential data related to water quality.Artificial intelligence technology was used to construct a water quality prediction model for use in a complete system for managing water quality.Since aquaculture water quality depends on a continuous interaction among multiple factors,and the current state is correlated with the previous state,a model with time series is required.Therefore,this study used recurrent neural networks(RNNs)with sequential characteristics.Commonly used RNNs such as long short-term memory model and gated recurrent unit(GRU)model have a memory function that appropriately retains previous results for use in processing current results.To construct a suitable RNN model,this study used Taguchi method to optimize hyperparameters(including hidden layer neuron count,iteration count,batch size,learning rate,and dropout ratio).Additionally,optimization performance was also compared between 5-layer and 7-layer network architectures.The experimental results revealed that the 7-layer GRU was more suitable for the application considered in this study.The values obtained in tests of prediction performance were mean absolute percentage error of 3.7134%,root mean square error of 0.0638,and R-value of 0.9984.Therefore,thewater qualitymanagement system developed in this study can quickly provide practitioners with highly accurate data,which is essential for a timely response to water quality issues.This study was performed in collaboration with the Taiwan Industrial Technology Research Institute and a local fishery company.Practical application of the system by the fishery company confirmed that the monitoring system is effective in improving the survival rate of farmed fish by providing data needed to maintain DOC higher than the standard value.

Development and Application of Water Quality Index (WQI) for the Evaluation of the Physico-Chemical Quality of Groundwater in Gold Mining Areas of Southeastern Senegal

Water is the most essential requirement for life. It provides a variety of purposes such as a source of water supply for drinking, domestic and industrial use, irrigated agriculture, livestock, and mining activities. Evaluating the status of water quality from traditional approaches does not guarantee the whole overview of the water quality situation. Therefore, developing a tool that can convert multiple parameters data into information that is understandable by both technical and non-technical personnel is vital. In this context, the purpose of this paper was to develop, calculate, and apply a water quality index for assessing the suitability (for drinking purposes) of groundwater in the gold mining areas in south-eastern Senegal. The development of this index based on WHO water quality guidelines followed the five standards steps i.e., parameters selection, sub-index formation, parameters weighting and sub-index aggregation and evaluation. Finally, the WQI summarized twelve key water quality parameters into 05 simple terms (excellent, good, medium, poor, and very poor) which is more relevant for reporting to managers and the public in a consistent manner. Thus, it was observed in the study area, that the water quality indexes in artisanal and industrial mining areas are either poor or very poor while in the reference stations (where there are no mining activities) WQI are either good or excellent. This situation was attributed to the effects of mining activities in such zones which contribute to the pollution of groundwater with heavy metals, nitrates, and suspended solids.