Visualizing the spatial water quality of Bentota,Sri Lanka in the presence of seawater intrusion

Seawater flows towards the inlands along with the rivers and canals, through the process of infiltration and leaks in the ground water characterized by high concentrations of soluble salts. High salinity concentrations can make groundwater unsuitable for public consumption and surface water unsuitable for irrigation and agricultural activities. This study envisages the fluctuations of ground and surface water quality of Bentota area in the presence of seawater intrusion. The temporal and spatial variations of eleven water parameters were monitored by collecting the water samples during one year period. Spatial distributions were assessed by applying the Inverse distance weighted (IDW) interpolation method in Arc GIS 10.5 software. Water quality is assessed on the integration of all parameters in terms of an index based on the World Health Organization (WHO) standards. The significant linear relationship between the considered parameters of surface water (SW) and groundwater (GW) were identified applying correlation analysis using SPSS software. All parameters of surface water were above the permissible limits of WHO standards. Surface water quality index values with respect to 60% of canals show very poor quality (>1 250) of surface water indicating their unsuitability for irrigation activities. Those surface water bodies indicated very highly saline conditions during dry months. The spatial distribution of ground water quality index with respect to the highest parameter values of each sampling location indicates that 52.2% of total land extent of Bentota Divisional Secretariat Division (DSD) has good quality of ground water which is suitable for drinking. Its 47.2% of total land extent has poor quality of ground water for drinking purpose and less than 0.5% of the area consists of excellent or very poor quality of ground water in each. This study helps to manage coastal aquifers by understanding the extreme water quality conditions and coastal salinity.     

Visualizing the spatial water quality of Bentota,Sri Lanka in the presence of seawater intrusion

Seawater flows towards the inlands along with the rivers and canals, through the process of infiltration and leaks in the ground water characterized by high concentrations of soluble salts. High salinity concentrations can make groundwater unsuitable for public consumption and surface water unsuitable for irrigation and agricultural activities. This study envisages the fluctuations of ground and surface water quality of Bentota area in the presence of seawater intrusion. The temporal and spatial variations of eleven water parameters were monitored by collecting the water samples during one year period. Spatial distributions were assessed by applying the Inverse distance weighted (IDW) interpolation method in Arc GIS 10.5 software. Water quality is assessed on the integration of all parameters in terms of an index based on the World Health Organization (WHO) standards. The significant linear relationship between the considered parameters of surface water (SW) and groundwater (GW) were identified applying correlation analysis using SPSS software. All parameters of surface water were above the permissible limits of WHO standards. Surface water quality index values with respect to 60% of canals show very poor quality (>1 250) of surface water indicating their unsuitability for irrigation activities. Those surface water bodies indicated very highly saline conditions during dry months. The spatial distribution of ground water quality index with respect to the highest parameter values of each sampling location indicates that 52.2% of total land extent of Bentota Divisional Secretariat Division (DSD) has good quality of ground water which is suitable for drinking. Its 47.2% of total land extent has poor quality of ground water for drinking purpose and less than 0.5% of the area consists of excellent or very poor quality of ground water in each. This study helps to manage coastal aquifers by understanding the extreme water quality conditions and coastal salinity.     

Use of geospatial information system based tool for renovation and rehabilitation of water distribution systems

Normally, decision makers use number of pipe broken in specific sections of water distribution systems to determine the pipes to be replaced. This index cannot solely evaluate hydraulic and quality parameters of the system and effects of pipe renovation on the system performance. In this study, a methodology is presented to manage the rehabilitation and replacement of water distribution network using hydraulic and geospatial information systems models. A preprocessor subroutine is developed to link geospatial information systems and hydraulic software. Hydraulic parameters together with the attribute data of pipes are used to determine the required renovation schemes based on several criteria. The proposed indices consist of pipe breaks and leakage analyses, hydraulic and quality performance and mechanical reliability of the network. A novel approach is also introduced to calculate leakage values throughout the network. Results of a real case study by the developed model introduced replacement of 4 km 40 mm galvanized pipes instead of 11 km 100 mm asbestos-cement pipes from conventional method. It is observed that the suggested geographic information system based model produces more realistic results with less cost for renovation schemes in comparison with conventional method which just consider number of bursts as a key criterion.     

Analysis of aquifer vulnerability and water quality using SINTACS and geographic weighted regression

Aquifer vulnerability and water quality were assessed in the Central Valleys of Oaxaca (Mexico) using the SINTACS method, based on a geographic information system. SINTACS layers were prepared using data such as climate (rainfall and temperature), water table, hydraulic conductivity, geology, soil type and topographic model. Maps for water quality index (WQI), contamination index and pollution sources index (PSI) were also obtained by this work. Groundwater quality in the Central Valleys may be affected by two factors, those with an anthropogenic origin and those with natural origin. High vulnerability values are located in the valleys of the basin, where granular sediments are exposed. Low vulnerability values are distributed in the basin??s ranges, where metamorphic rocks are found. Given that many of the zones with the highest groundwater vulnerability values correspond to zones with the greatest PSI values, there is great risk of groundwater contamination for the area of study because external (indicated by PSI) and internal (indicated by SINTACS) factors that cause pollution can be frequently observed in the same place. Geographic weighted regression (GWR) is used to test the dependency between WQI as dependent variable and SINTACS, PSI, Urban localities, Agriculture, Pastures and Rivers as predictors. The results indicate the non-stationary behavior of the dependent variable with respect to the predictors. While the obtained GWR models used to model WQI cannot be used in practical situations to predict the behavior of said variable, they can be used to estimate the degree to which the predictors influence the variable of interest.     

Classification of rivers based on water quality assessment using factor analysis in Taizi River basin, northeast China

A method for river classification based on water quality assessment (WQA) was introduced using factor analysis (FA) in this paper. Sixty-nine sampling sites and 20 water quality parameters in Taizi River basin were selected for monitoring and analysis. Five factors were determined in FA, denoted as general, hardness, trophic, nitrogen pollution, and physical factors. The total factor scores (TFSs) of the WQA results from all sampling sites were calculated by the eigenvalue and factor score of each factor. The TFSs of 69 sites were interpolated with the measure of inverse distance weighted in the river buffer zone generated by ArcGIS 9.2 software to form a continuous spatial distribution along river channels. All streams were divided into five classes marked “excellent”, “good”, “fair”, “poor”, and “seriously polluted”. The classification result showed that the water quality of Taizi River basin deteriorated gradually from the mountain area to the plain area. Sewage and intensive human activities contributed to the deterioration of water quality since towns and farmland were dotted densely along the river basin.     

Development and application of a soil organic matter-based soil quality index in mineralized terrane of the Western US

Soil quality indices provide a means of distilling large amounts of data into a single metric that evaluates the soil’s ability to carry out key ecosystem functions. Primarily developed in agroecosytems, then forested ecosystems, an index using the relation between soil organic matter and other key soil properties in more semi-arid systems of the Western US impacted by different geologic mineralization was developed. Three different sites in two different mineralization types, acid sulfate and Cu/Mo porphyry in California and Nevada, were studied. Soil samples were collected from undisturbed soils in both mineralized and nearby unmineralized terrane as well as waste rock and tailings. Eight different microbial parameters (carbon substrate utilization, microbial biomass-C, mineralized-C, mineralized-N and enzyme activities of acid phosphatase, alkaline phosphatase, arylsulfatase, and fluorescein diacetate) along with a number of physicochemical parameters were measured. Multiple linear regression models between these parameters and both total organic carbon and total nitrogen were developed, using the ratio of predicted to measured values as the soil quality index. In most instances, pooling unmineralized and mineralized soil data within a given study site resulted in lower model correlations. Enzyme activity was a consistent explanatory variable in the models across the study sites. Though similar indicators were significant in models across different mineralization types, pooling data across sites inhibited model differentiation of undisturbed and disturbed sites. This procedure could be used to monitor recovery of disturbed systems in mineralized terrane and help link scientific and management disciplines.     

Development of a framework of automated water quality parameter optimization and its application

This paper presents a methodology and framework for the development of an automated least-squares optimization tool for calibrating water quality parameters in QUAL2E. The method has been applied to estimate the optimal water quality parameters in simulation of stream water quality for the Anyang stream in Korea. The Monte Carlo analysis is used to assess the relative importance of model parameters for water quality constituents. It is found that μ_max and ρ are the most influential parameters for Chlorophyll-a modeling and K ₁ and K ₃ are critical parameters for variation of DO and BOD in the Anyang stream. A computer program for automated parameter calibration has been developed using a nonlinear GRG optimization algorithm. The application framework provides an intuitive and easy-to-use interface and allows visual evaluation of results. According to the simulation results, the automated approach is computationally efficient for evaluation of model parameters and converges on a best fit more rapidly and reliably than a trial and error method. The methodology proposed herein can be extended to other models to obtain the best possible parameter values.     

资料缺失河道水质风险分析

资料缺失是进行水质风险分析的薄弱环节。结合水质指标浓度分布的先验信息及已有水质资料,在分析水质指标相关关系基础上建立其随时间变化的浓度分布模型,应用Bayes理论及Gibbs抽样方法对模型涉及的大量参数和超参数的统计特征进行了同步估计。在假定缺失数据为随机变量的基础上,应用该方法得到的大量样本较好实现了对缺失数据的估计,并结合风险分析理论进一步量化了水质超标风险。通过实例验证了模型的合理性,为资料缺失地区的水质风险分析提供了新的思路和方法。     

Mathematical attributes of some soil–water characteristic curve models

Numerous mathematical models have been proposed in the research literature to represent soil–water characteristic curve data. A number of proposed mathematical models are summarized and the significance of each of the associated soil parameters is illustrated. The advantages and disadvantages of the various mathematical models are outlined. The derivatives for each of the model equations are presented along with comments regarding the efficiency of the best-fit regression procedures.The models using three soil parameters models proved to be superior for representing the wide range of soil suctions required in solving geotechnical problems. Regression analyses using three soil parameters were shown to be numerically more stable, converging with a reasonable number of iterations.     

Heavy metal contamination and its indexing approach for river water

The objective of the study is to reveal the seasonal variations in the river water quality with respect to heavy metals contamination. To get the extend of trace metals contamination, water samples were collected from twelve different locations along the course of the river and its tributaries on summer and the winter seasons. The concentrations of trace metals such as cadmium, cromium, copper, cobalt, iron, manganese, nickel, lead, mercury and zinc were determined using atomic absorption spectrophotometer. Most of the samples were found within limit of Indian drinking water standard (IS: 10500). The data generated were used to calculate the heavy metal pollution index of river water. The mean values of HPI were 36.19 in summer and 32.37 for winter seasons and these values are well below the critical index limit of 100 because of the sufficient flow in river system. Mercury and chromium could not be traced in any of the samples in the study area.     

Water quality index and fractal dimension analysis of water parameters

Statistical analysis of water quality parameters were analyzed at Harike Lake on the confluence of Beas and Sutlej rivers of Punjab (India). Mean, median, mode, standard deviation, kurtosis, skewness, coefficient of variation, regression lines, correlation coefficient, Hurst exponent, fractal dimension and predictability index were estimated for each water parameter. Monthly variation of water quality index using month-wise and parameter-wise value of quality rating and actual value present in water sample was calculated and compared with World Health Organization/Environmental Protection Agency standard value of these parameters. It was observed that Brownian time series behavior exists of potential of hydrogen with total dissolved solids, hardness, alkalinity, sulfate, chloride and conductance parameters; biochemical oxygen demand with total dissolved solids, hardness, alkalinity, sulfate, chloride, conductance and calcium parameters; dissolved oxygen with total dissolved solids, hardness, alkalinity, sulfate, chloride, conductance and calcium parameters; ferrous with total dissolved solids, hardness, alkalinity, sulfate, conductance and calcium parameters; chromium with total dissolved solids, hardness, alkalinity, sulfate, chloride, conductance and zinc parameters; zinc with total dissolved solids, hardness, sulfate, chloride, conductance and calcium parameters; fluoride with total dissolved solids, hardness, alkalinity, sulfate, chloride and conductance parameters; nitrate with total dissolved solids, sulfate and conductance parameters; nitrite with potential of hydrogen, total dissolved solids, hardness, alkalinity, sulfate, chloride, conductance and calcium parameters. Also, using water quality index, it was observed that water of the lake was severely contaminated and became unfit for drinking and industrial use.     

Water quality parameters along rivers

Water samples have been collected from a part of Surma River along different points and analyzed for various water quality parameters during dry and monsoon periods. Effects of industrial wastes, municipal sewage, and agricultural runoff on river water quality have been investigated. The study was conducted within the Chattak to Sunamganj portion of Surma River, which is significant due to the presence of two major industries-a paper mill and a cement factory. The other significant feature is the conveyors that travel from India to Chattak. This study involves determination of physical, biological and chemical parameters of surface water at different points. The river was found to be highly turbid in the monsoon season. But BOD and fecal coliform concentration was found higher in the dry season. The water was found slightly acidic. The mean values of parameters were Conductivity 84–805μs; DO: dry- 5.52 mg/L, monsoon-5.72 mg/L; BOD: dry-1 mg/L, monsoon-0.878 mg/L; Total Solid: dry-149.4 mg/L, monsoon- 145.7 mg/L. A model study was also conducted and values of different model parameters were estimated.     

Groundwater quality assessment in urban environment

The assessment of environmental effects generated by urban areas (with various activities as agriculture, industry, human activities) on groundwater quality became essential for the use and conservation of the water resources. The main objective was to apply a water quality index to the groundwater sources using the specific methodology, establishing the suitability for drinking for groundwater. Water resources were monitored in October 2011, the samples were collected from 22 points for groundwater, and more parameters were analyzed: pH, electrical conductivity, turbidity, oxygen regime, hardness, alkalinity, nutrients regime (nitrates, ammonium, phosphates) which were considered important and utilized for water quality index computation that reveal poor quality for groundwater. The oxidability should be included in computation formula and the final results used for water management, taking into consideration the limits of the current model. Multivariate statistical analysis was used to indicate the influence of urban area on the quality of groundwater resources. Results of the analysis highlight an influence of geology and a contamination of agricultural origin.     

Application of Landsat 5 and Landsat 7 images data for water quality mapping in Mosul Dam Lake,Northern Iraq

Mosul Dam Lake is the main reservoir in Iraq, supporting the water demand of Mosul, Baghdad, and other cities. The aim of this study is to derive simple and accurate algorithms for the retrieval of water quality parameters for Mosul Dam Lake from Landsat 5 and Landsat 7 reflectance data. The water quality measurements were performed in situ during March and July 2011. These measurements included temperature, turbidity, Secchi disk, chlorophyll-a, nitrate, nitrite, phosphate, total inorganic carbon, dissolved organic carbon, total dissolved solids, and pH. In order to properly use the values of reflectance bands, images enhancement techniques have been used. The field measurements were compared with reflectance values of Landsat 5 and Landsat 7 bands using different band combination of empirical algorithms. Generally, the results of analysis showed significant correlation between these models and water quality parameters with R ²?>?0.7 and p?R ²?>?0.9 and p?R ²?>?0.9, and values of the root mean square error ranged from 0.9 to 0.001. ArcGIS 10 was used to simulate the distribution values of water quality parameters calculated from spectral values of TM5 and ETM+ bands. The results of spatial analysis demonstrate that it is possible to use the TM5 and ETM+ images to evaluate the water quality for Mosul Dam Lake.     

Ground water quality classification by decision tree method in Ardebil region,Iran

A decision tree-based approach is proposed to predict ground water quality based on the United States Salinity Laboratory (USSL) diagram using the data from aquifers in agricultural lands of Ardebil province, northwest of Iran. Several combinations of hydro chemical parameters of groundwater and monthly precipitation with different lag time were considered to find an accurate and economical alternative for groundwater quality classification. The performance evaluation was based on the number of correctly classified instances (CCI) and kappa statistics. The results suggested the suitability of decision tree-based classification approach for the used data sets. The overall average of CCI and kappa statistic for the prediction of groundwater quality classes based on the USSL diagram was 0.88 and 0.83 %, respectively. Principal component analysis (PCA) was also used to determine the important parameters for groundwater quality classification. The results showed that groundwater quality classification by decision tree is more precise and efficient in comparison with PCA. The best alternative could evaluate groundwater quality class with only two parameters: electrical conductivity and cumulative precipitation of 11 months earlier. The developed model is able to predict water quality class by only two variables and this lead to a reduction in the number of variables analyzed on a routine basis, resulting in a significant reduction in laboratory costs and latency times between the sampling moment and the outcome of the laboratory analyses.     

黄河典型河段水量水质一体化调配模型

以黄河兰州至河口镇河段为研究对象,采用分解、协调、耦合和控制技术,通过数据实时传递与反馈实现水量水质的同步耦合,以河段取水量、断面下泄流量和水功能区水质指标为辨识参数实现调配目标的在线辨识与过程控制,建立具有循环迭代、在线反馈和滚动修正功能的水量水质一体化调配模型。以1956-2000年天然径流为输入,以2020水平年黄河上游需水和排污为例,通过优化提出河段水量水质一体化调配方案。结果表明,通过对取水量及其过程、污染物入河量与过程的协调控制,2020年水平河口镇以上河段地表耗水量125.2亿m3,低于黄河分水指标,COD和氨氮入河量控减率分别为50.6%和65.7%,水功能区水质达标率100%。模型可实现河段水量水质一体化调配。     

Water quality index of the ground water of bitumen deposit impacted farm settlements using entropy weighted method

Ground water of the farm settlements in the bitumen deposit area of Western Nigeria were tested for pH, conductivity, turbidity, total dissolved solid, sulphate, phosphate, nitrogen nitrate, chloride, alkalinity, total hardness, calcium, magnesium, sodium, potassium and total coliform in the dry season (March) and rainy season (August) of years 2008 and 2009 using atomic absorption spectrometer and standard analytical methods. Conductivity, pH, turbidity, phosphate ions and total coliform values obtained in some of the wells were out of the recommended range for drinking water. Water quality index analysis was carried out using information entropy method. Water quality index of the wells when compared with the permissible limits of international standards, ranked the bore hole as ‘excellent’ in the dry season of year 2009 and just ‘good’ in the rainy season of the same year. Ground water sampling stations were ranked extremely poor at least once out of the four seasons considered. Water quality index ranking also showed that the quality of the wells declined over the years. The correlation coefficient matrix (p < 0.05) of water quality index and the parameters showed significant relationships between water quality index and total coliform (0.99), total dissolved solids and conductivity (0.96), hardness and Ca²⁺ (0.68), hardness and Mg²⁺ (0.75). Water quality index also showed moderate significant relationship with total dissolved solid, conductivity and N–NO₃ ^?. High concentration of total coliform in most of the shallow wells in the environment, due to bitumen deposit, renders them unfit for human consumption unless properly treated.     

Groundwater quality assessment for drinking purpose in Raipur city,Chhattisgarh using water quality index and geographic information system

An effort has been made to comprehend the groundwater quality of Raipur city for drinking purpose utilizing Water Quality Index (WQI) and Geographic Information System (GIS) techniques. In this study thirty four groundwater samples were collected during May, 2015. Standard methods has been adopted in groundwater sampling which are prescribed by the American Public Health Association (APHA, 1995). Eight water quality parameters have been considered to ascertained water quality index viz. pH, chloride, fluoride, calcium, magnesium, alkalinity, hardness and nitrate. The Bureau of Indian Standard (BIS, 2009) has been considered to assess the suitability of groundwater for drinking purposes and for the calculation of WQI. This study reveals that 76% area is falling under excellent, very good and good category and 24% area is falling under poor, very poor and unfit category as per the WQI classification. The predicted accuracy of the obtained result is around 97.05% reflecting capability of adopted techniques. Anthropogenic activities are influencing the groundwater quality of the study area. The present study is helpful in proper planning and management of available water resource for drinking purpose.     

Prediction of water quality from simple field parameters

Water quality parameters like temperature, pH, total dissolved solids (TDS), total suspended solids (TSS), dissolved oxygen (DO), oil and grease, etc., are calculated from the field while parameters like biological oxygen demand (BOD) and chemical oxygen demand (COD) are interpreted through the laboratory tests. On one hand parameters like temperature, pH, DO, etc., can be accurately measured with the exceeding simplicity, whereas on the other hand calculation of BOD and COD is not only cumbersome but also inaccurate many times. A number of previous researchers have tried to use different empirical methods to predict BOD and COD but these empirical methods have their limitations due to their less versatile application. In this paper, an attempt has been made to calculate BOD and COD from simple field parameters like temperature, pH, DO, TSS, etc., using Artificial Neural Network (ANN) method. Datasets have been obtained from analysis of mine water discharge of one of the mines in Jharia coalfield, Jharkhand, India. 73 data sets were used to establish ANN architecture out of which 58 datasets were used to train the network while 15 datasets for testing the network. The results show encouraging similarity between experimental and predicted values. The RMSE values obtained for the BOD and COD are 0.114 and 0.983 %, respectively.     

Evaluation of groundwater quality for irrigation and drinking using GIS and geostatistics in a peri-urban area of Delhi, India

Intensive agriculture by indiscriminate use of agrochemicals, sewage water, and polluted drain water has posed a serious threat to groundwater quality in some peri-urban areas of Delhi like Najafgarh block. The objective of the study was to determine the groundwater quality and to map their spatial variation in terms of suitability for irrigation and drinking purpose. Ordinary kriging method was used for preparation of thematic maps of groundwater quality parameters such as electrical conductivity, sodium adsorption ratio, bicarbonate, magnesium/calcium ratio, total dissolved solids, chloride, nitrate and hardness. Exponential semivariogram model was best fitted for all quality parameters except chloride and hardness, where spherical model fitted best. Pollution level was highest at south and south-eastern part of the study area. Better quality groundwater may be expected at the northern and western part. High salinity was due to high chloride concentration in the groundwater. Nitrate pollution level was found to be very alarming and need immediate interventions. High dissolved solids and hardness made the groundwater unsuitable for drinking. There were negligible sodium and bicarbonate hazard in the study area. The groundwater quality index was devised to analyse the combined impact of different quality parameters on irrigation and drinking purposes. The irrigation water quality index and drinking water quality index distribution maps delineated an area of 47.29 and 6.54 km² suitable for irrigation and drinking, respectively. These safe zones were found as a small strip along the northern boundary and a very small pocket at the western side of the study area.