Water Quality Assessment and Modeling of an Effluent-Dominated Stream, the Notwane River, Botswana

In an effort to assess current and future water quality of the only perennial river in southeastern Botswana, this study presents water quality monitoring and modeling results for the effluent-dependent Notwane River. The water quality along the Notwane River, pre- and post-implementation of secondary wastewater treatment, was compared and results demonstrated that water quality improved after the new wastewater treatment plant (WWTP) went online. However, stream standards for chemical oxygen demand, total dissolved phosphorous, and fecal coliform were exceeded in most locations and the critical dissolved oxygen (DO) reached concentrations of less than 4 mg L⁻¹. High dissolved P concentrations and intense macrophyte growth at the impounding ponds and at sites within 30 km of the effluent waste stream confluence suggest that eutrophication was a function of P release from the ponds. Results of DO modeling demonstrated that an unpolluted inflow at approximately 10 km downstream of the confluence was responsible for raising DO concentrations by 2.3 mg L⁻¹, while SOD was responsible for a decline in DO concentrations of 1.4 mg L⁻¹ at 6 km downstream of the confluence. Simulations also showed higher DO concentrations during winter months, when water temperatures were lower. Simulations, in which the distributed biochemical oxygen demand (BOD) loading from cattle excrement was decreased, produced nominal increases in DO concentrations. An increase in WWTP BOD loadings to projected 2020 values resulted in a 1.3 mg L⁻¹ decrease in the critical DO concentration. Furthermore, a decrease in treatment plant efficiency, from 94% to 70% BOD removal, produced critical DO concentrations and anoxia along much of the modeled reach. This has significant implications for Gaborone, especially if decreased WWTP efficiency occurs as a result of the expected future increase in pollutant loadings.     

釜溪河自贡城区段季节性低氧成因研究

釜溪河为沱江一级支流,在自贡城区段设有国考碳研所断面。收集碳研所断面近10年来水质自动站数据,分析溶解氧(DO)变化特征,采样调查釜溪河自贡城区段水质及河道底泥污染状况,采用相关性分析、数值模拟等,研究分析釜溪河自贡城区段溶解氧分布特征及碳研所断面季节性低氧成因。研究结果表明,碳研所断面的溶解氧质量浓度变化特征呈现春末夏初最低,白天高晚上低的特征。釜溪河碳研所断面河水耗氧类污染物质量浓度较沱江流域内其他断面高,耗氧强度较大,溶解氧质量浓度较沱江流域其他断面偏低;其次,研究河段中釜溪河污水厂以下河段受污水厂低氧水排入和金子凼堰底层低氧水下泄影响,其溶解氧水平整体较污水厂以上河段低;最后,河段底泥有机质含量较高,春夏季气温升高将导致微生物分解活性增强大量消耗溶解氧,同时,闸坝和外来水体排入的水文扰动造成污水厂以下河段水温梯度弱,表层溶解氧易受底层低氧水影响,促使断面形成季节性低氧现象。溶解氧预测模型结果也进一步证实了温度变化和垂向温度梯度弱是碳研所断面溶解氧质量浓度季节性偏低的主要因素。     

Temporal scale-induced uncertainty in load duration curves for instream-dissolved oxygen

Load duration curves were developed using the Hydrological Simulation Program FORTRAN (HSPF) for dissolved oxygen (DO) for the Amite River in Louisiana, USA. The concept of ‘dissolved oxygen reserve’, defined as the total quantity of DO, is introduced. The effect of temporal resolution on duration curves of DO reserve was examined using duration curves developed based on daily, weekly, biweekly, and monthly average data. Duration curves for DO exhibited high variability in the load estimated using daily data as compared to those based on biweekly and monthly data. A seasonal analysis revealed the trend in the DO reserve. The daily DO reserve for the Amite River at Port Vincent was 44,049.31 kg when daily summer data were used and 74,255.15 kg for daily annual data. A surplus of 10,691 kg of DO reserve was shown in the monthly data during critical summer months. The coefficient of variation (CV), used to define the temporal scale-induced uncertainty, was found to be linearly and inversely correlated with the logarithm of the time scale. Regression equations were developed to extrapolate near real-time flow and water quality data, greatly simplifying flow and water quality monitoring and reducing the cost involved in flow and water quality monitoring.     

Calibration and verification of a dissolved oxygen management model for a highly polluted river with extreme flow variations in Pakistan

A dissolved oxygen (DO) model is calibrated and verified for a highly polluted River Ravi with large flow variations. The model calibration is done under medium flow conditions (431.5 m³/s), whereas the model verification is done using the data collected during low flow conditions (52.6 m³/s). Biokinetic rate coefficients for carbonaceous biochemical oxygen demand (CBOD) and nitrogenous biochemical oxygen demand (NBOD) (i.e, K _cr and K _n ) are determined through the measured CBOD and ammonia river profiles. The calculated values of K _cr and K _n are 0.36 day^?1 and 0.34 day^?1, respectively. The close agreement between the DO model results and the field values shows that the verified model can be used to develop DO management strategies for the River Ravi. The biokinetic coefficients are known to vary with degree of treatment (DOT) and therefore need to be adjusted for a rational water quality management model. The effect of this variation on level of treatment has been evaluated by using the verified model to attain a DO standard of 4 mg/L in the river using the biokinetic rate coefficients as determined during the model calibration and verification process. The required DOT in this case is found to be 96 %, whereas the DOT is 86 % if adjusted biokinetic rate coefficients are used to reflect the effect of wastewater treatment. The cost of wastewater treatment is known to increase exponentially as the removal efficiency increases; therefore, the use of appropriate biokinetic coefficients to manage the water quality in rivers is important.     

基于WASP 7模型的水质模拟应用——以淮沭新河东海段为例

应用WASP 7模型的EUTRO子模块对淮沭新河东海段的溶解氧(DO)和化学需氧量(COD)指标进行模拟研究,采用2014年与2015年的水文、水质数据进行模型参数率定,并以2016年1月—2017年9月的水质数据进行验证,验证结果为DO和COD的模拟值与实际值的相对误差分别能控制在15%和10%以内,线性回归分析结论显示相关系数R2均在0.9以上,表明两者的吻合度较高。     

Study of the Climate Change Impacts on Water Quality in the Upstream Portion of the Cau River Basin,Vietnam

This paper presents simulations of climate change impacts on water quality in the upstream portion of the Cau River Basin in the North of Vietnam. The integrated modeling system GIBSI was used to simulate hydrological processes, pollutant and sediment wash-off in the river basin, and pollutant transport and transformation in the river network. Three projections for climate change based on emission scenarios B1, B2, and A2 of IPCC Special Report on Emission Scenarios (SRES) were considered. By assuming that the input pollution sources and watershed configuration were constant, based on 2008 data, water quality in the river network was simulated up to the terminal year 2050. For each climate change scenario, patterns of precipitation in wet and dry year were considered. The change in annual and monthly trends for dissolved oxygen (DO), biochemical oxygen demand (BOD), and ammonium ions (NH4+) load and concentration for different portions of the watershed have been analyzed. The results of these simulations show that climate change has more impact on changing the seasonal water quality parameters than on altering the average annual load of the pollutants. The percent change and change pattern in water quality parameters are different for wet and dry year, and the changes in wet year are smaller than those in dry year.     

Development of Dissolved Oxygen Model for a Highly Variable Flow River: A Case Study of Ravi River in Pakistan

A framework for dissolved oxygen (DO) modeling of the Ravi River has been developed based on a combination of laboratory measurements and field and monitoring data. Both the classical Streeter-Phelps (CSP) and the modified Streeter-Phelps (MSP) models are used for DO simulations. The MSP model considers the carbonaceous biochemical oxygen demand (CBOD) and nitrogenous biochemical oxygen demand (NBOD) separately, whereas the CSP model is evaluated considering only the CBOD and NBOD is incorporated in the overall BOD utilization rate. CBOD, NBOD and BOD rates have been determined through long-term BOD analysis of five main wastewater outfalls and two surface drains discharging into the Ravi River over a 98 km stretch. Analysis by Thomas Method manifests strong coefficient of determination “R²” between 0.72 and 0.98 for all the three types of BOD rates. Sensitivity analyses have also been carried out to find out a suitable reaeration rate formula for highly variable flows in the Ravi River. The CSP model results based on classical approach of considering only CBOD show significant difference between the model predictions and field measurements suggesting that NBOD needs to be incorporated for the model development. The dissolved oxygen values calculated using the MSP model and the CSP model based on overall BOD rate are in close agreement with field measurements and are thus suitable to model DO levels in the Ravi River.     

右江百色水库下游断面低溶解氧形成原因分析

广西右江东笋断面溶解氧(DO)呈现5—11月浓度较低,12月及1—4月浓度较高的变化规律。从水温、藻类呼吸、沉积物耗氧、有机物耗氧、上游来水等方面分析了东笋断面低DO形成的原因。结果表明,5—11月东笋断面DO浓度较低,主要是受夏季高温和水利工程运行等非污染型因素的影响。右江流域夏秋季水温较高,限制了水体DO浓度的上限。热分层现象导致百色水库中层水体DO浓度较低,而水利枢纽发电时的下泄水正是中层水体,因此,下泄水DO浓度低是导致5—11月东笋断面DO浓度低的主要原因。东笋河段沉积物和有机物耗氧对DO浓度的影响很小,藻类呼吸作用对DO浓度的影响有限。     

Spatiotemporal trend analysis of recent river water quality conditions in Japan

In order to promote pollutant monitoring and preservation of water resources, we evaluate the spatiotemporal trends in recent water quality conditions in Japanese rivers. Trend analysis is conducted on the 92 major rivers in Japan using the available water quality data recorded from 1992 to 2005 and the characteristics of major pollutants in these rivers are analyzed. Spatial and temporal analysis of trends for six water quality indicators is conducted using the Mann Kendall test, a non-parametric statistical method. The indicators analyzed are biochemical oxygen demand (BOD), chemical oxygen demand (COD), dissolved oxygen (DO), total nitrogen (TN), total phosphorus (TP) and pH. The majority of sampling locations monitoring BOD, COD, TN and TP show trends toward decreasing concentrations over time. Many sampling locations show increasing DO concentrations. Our results show that water quality in Japanese rivers has improved dramatically over the past decade, although there are still problems in some places, most notably in the Hokkaido, Kanto, Kinki and Kyushu regions. The improvements seen in water quality appear to be the result of improved wastewater treatment and other water quality improvement efforts achieved through government initiative.     

Potential effects on the marine environment of dredging of the Bonny channel in the Niger Delta

This study is an assessment of the possible effects of the dredging project on the water quality of the surrounding environment. Water quality data for the Bonny offshore river were collected. The parameters assessed were temperature, dissolved oxygen (DO), pH, biochemical oxygen demand (BOD), total dissolved solids (TDS), total suspended solids (TSS), nitrogen as nitrate, and phosphate. The concentrations of TDS, TSS, and nitrate far exceeded the permissible standard. There were significant differences between the dry and rainy season values of BOD5, TDS, TSS, nitrate, and phosphate. Also, the sediment physicochemical analysis indicated the presence of heavy metals such as Pb, Fe, Cd, Zn, Cr, and elements such as Ca, K, and Na. Following an assessment of the potential impact of the project using interaction matrix and checklist questionnaires, results showed that the major physicochemical parameters influenced by dredging are DO, TDS, TSS, heavy metals and calcium, potassium, and sodium. Mitigation measures for eliminating or reducing the negative impacts of dredging are presented.     

A Three-Dimensional Water Quality Model of Chicago Area Waterway System (CAWS)

As outfalls from various water reclamation plants, pumping stations, and combined sewer overflow outfalls discharge into the Chicago Area Waterway System (CAWS), an enhanced understanding of the final fate of crucial water quality state variables is of utmost importance. This paper reports the development and application of a 3D water quality model for a modified CAWS combined with the hydrodynamic kernel of Environmental Fluid Dynamics Code (EFDC). The modified CAWS is used to demonstrate the usefulness of the model while eliminating complications beyond the scope of this initial effort. The water quality model developed and presented in this research is a simplistic dissolved oxygen (DO)—biochemical oxygen demand model with the facility to account for the interaction between the water column and the bed. The aforementioned model is applied for the month of May 2009. The results from the hydrodynamic (EFDC) and water quality model is validated with the help of the observed data obtained from United States Geological Survey gaging stations and Metropolitan Water Reclamation District of Greater Chicago monitoring stations present inside the modeled domain. The 3D modeling captured the hydrodynamic and water-quality processes in CAWS in a satisfactory manner. Furthermore, modeling results showed and proved the interdependence of water quality characteristics in Bubbly Creek and CAWS with the effluent concentration from Racine Avenue Pumping Station situated at the head of Bubbly Creek, South Fork of South Branch of Chicago River.     

Water Quality Changes in Chini Lake, Pahang, West Malaysia

A study of the water quality changes of Chini Lake was conducted for 12 months, which began in May 2004 and ended in April 2005. Fifteen sampling stations were selected representing the open water body in the lake. A total of 14 water quality parameters were measured and Malaysian Department of Environment Water Quality Index (DOE-WQI) was calculated and classified according to the Interim National Water Quality Standard, Malaysia (INWQS). The physical and chemical variables were temperature, dissolved oxygen (DO), conductivity, pH, total dissolved solid (TDS), turbidity, chlorophyll-a, biochemical oxygen demand (BOD), chemical oxygen demand (COD), total suspended solid (TSS), ammonia-N, nitrate, phosphate and sulphate. Results show that base on Malaysian WQI, the water in Chini Lake is classified as class II, which is suitable for recreational activities and allows body contact. With respect to the Interim National Water Quality Standard (INWQS), temperature was within the normal range, conductivity, TSS, nitrate, sulphate and TDS are categorized under class I. Parameters for DO, pH, turbidity, BOD, COD and ammonia-N are categorized under class II. Comparison with eutrophic status indicates that chlorophyll-a concentration in the lake was in mesotrophic condition. In general water quality in Chini Lake varied temporally and spatially, and the most affected water quality parameters were TSS, turbidity, chlorophyll-a, sulphate, DO, ammonia-N, pH and conductivity.     

Optimizing water quality monitoring networks using continuous longitudinal monitoring data: a case study of Wen-Rui Tang River, Wenzhou, China

Identification of representative sampling sites is a critical issue in establishing an effective water quality monitoring program. This is especially important at the urban-agriculture interface where water quality conditions can change rapidly over short distances. The objective of this research was to optimize the spatial allocation of discrete monitoring sites for synoptic water quality monitoring through analysis of continuous longitudinal monitoring data collected by attaching a water quality sonde and GPS to a boat. Sampling was conducted six times from March to October 2009 along a 6.5 km segment of the Wen-Rui Tang River in eastern China that represented an urban-agricultural interface. When travelling at a velocity of ～2.4 km h(-1), this resulted in water quality measurements at ～20 m interval. Ammonia nitrogen (NH(4)(+)-N), electrical conductivity (EC), dissolved oxygen (DO), and turbidity data were collected and analyzed using Cluster Analysis (CA) to identify optimal locations for establishment of long-term monitoring sites. The analysis identified two distinct water quality segments for NH(4)(+)-N and EC and three distinct segments for DO and turbidity. According to our research results, the current fixed-location sampling sites should be adjusted to more effectively capture the distinct differences in the spatial distribution of water quality conditions. In addition, this methodology identified river reaches that require more comprehensive study of the factors leading to the changes in water quality within the identified river segment. The study demonstrates that continuous longitudinal monitoring can be a highly effective method for optimizing monitoring site locations for water quality studies.     

南京市地表水溶解氧分布特征及低氧成因初探——以外秦淮河七桥瓮为例

于2018—2021年对南京市及国考断面七桥瓮进行水质调查,分析其溶解氧变化特征,采用水质水量联合评价及皮尔逊相关分析法,并结合水文气象等相关信息,对南京市地表水溶解氧分布特征及国考七桥瓮断面低氧成因进行研究分析。结果表明,南京市地表水溶解氧浓度夏季最低,中心主城区及附近区域溶解氧浓度均相对较低。七桥瓮断面溶解氧浓度在2.25~11.07 mg/L,其中5—9月溶解氧易出现超标波动。溶解氧浓度昼间高于夜间,与pH值呈正相关关系,与水温、高锰酸盐指数、氨氮、总磷均呈负相关关系。水温和上游来水带入的耗氧污染物是七桥瓮断面溶解氧偏低的主要成因,其中,溶解氧浓度与水温相关性最为显著。研究结论可为七桥瓮断面稳定达标提供基础支撑,为秦淮河流域精准治污提供技术依据,为南京市水环境多源同治提供治理思路。     

Evaluation of Water Quality Management Alternatives to Control Dissolved Oxygen and Un-ionized Ammonia for Ravi River in Pakistan

Different water quality management alternatives, including conventional wastewater treatment, transportation of wastewater, flow augmentation, low-cost treatment with reuse, and wetlands, are evaluated by using a verified dissolved oxygen (DO) model for the Ravi River. Biokinetic rate coefficients of the Ravi River for both the carbonaceous and nitrogenous oxygen-demanding wastes are adjusted, keeping in view the type and level of wastewater treatment. The conventional activated sludge process with nitrification comes out to be the most expansive alternative to meet the DO standard of 4 mg/L. Additional treatment cost is required to maintain un-ionized ammonia levels <0.02 mg/L, which corresponds to achieving treatment levels of 5 mg/L of DO in the river. Under critical low-flow conditions (i.e., minimum average seven consecutive days) of 9.2 m³/s, a flow augmentation of 10 m³/s can reduce 30 % of the cost with conventional wastewater treatment. Transportation of wastewater from the city of Lahore is a cost-effective alternative with 2.5 times less cost than the conventional process. Waste stabilization ponds (WSP) technology is a low-cost solution with 3.5 times less cost as compared to the conventional process. Further reduction in pollution loads to the Ravi River can be achieved by reusing WSP effluents for irrigation in the near proximity of Lahore along the Ravi River. The study results show that, for highly polluted rivers with such extreme flow variations as in case of the Ravi River, meeting un-ionized ammonia standards can reduce the efforts required to develop carbonaceous biochemical oxygen demand-based waste load allocations.     

Effects of land use types on surface water quality across an anthropogenic disturbance gradient in the upper reach of the Hun River, Northeast China

Surface water quality is vulnerable to pollution due to human activities. The upper reach of the Hun River is an important water source that supplies 52 % of the storage capacity of the Dahuofang Reservoir, the largest reservoir for drinking water in Northeast China, which is suffering from various human-induced changes in land use, including deforestation, reclamation/farming, urbanization and mine exploitation. To investigate the impacts of land use types on surface water quality across an anthropogenic disturbance gradient at a local scale, 11 physicochemical parameters (pH, dissolved oxygen [DO], turbidity, oxygen redox potential, conductivity, biochemical oxygen demand [BOD₅], chemical oxygen demand [COD], total nitrogen [TN], total phosphorus [TP], NO ₃ ^? -N, and NH ₄ ⁺ -N) of water from 12 sampling sites along the upper reach of the Hun River were monitored monthly during 2009–2010. The sampling sites were classified into four groups (natural, near-natural, more disturbed, and seriously disturbed). The water quality exhibited distinct spatial and temporal characteristics; conductivity, TN, and NO ₃ ^? -N were identified as key parameters indicating the water quality variance. The forest and farmland cover types played significant roles in determining the surface water quality during the low-flow, high-flow, and mean-flow periods based on the results of a stepwise linear regression. These results may provide incentive for the local government to consider sustainable land use practices for water conservation.     

Sizing an Off-stream Reservoir with Respect to Water Availability,Water Quality,and Biological Integrity

Sizing a new reservoir is a challenging task, which normally requires simultaneously a cost-effective, risk-informed, and forward-looking decision analysis with respect to basin-wide hydrological features, environmental quality, and biological integrity. Such a sustainable planning approach takes into account the global trend to balance the needs of economic growth, ecological conservation, and environmental protection. To achieve the goal of sustainability, emphasis in this paper was placed upon the correlation of three physical, chemical, and biological indices, including the dissolved oxygen (DO), the 5-day biochemical oxygen demand (BOD₅), and the index of biotic integrity (IBI), for the optimal planning of a reservoir in a river basin. This new methodological paradigm has been employed for sizing an off-stream reservoir in the Hou-Lung River Basin, central Taiwan. The internal linkage between the water quality parameters (DO and BOD₅) and the IBI levels further enables us to formulate a special biotic integrity constraint which reflects fish community attributes to suit a relatively low-density and unspecialized freshwater fish fauna in response to the changing water quality conditions in the river basin. The tradeoffs among economic, environmental, and ecological aspects for reservoir sizing can then be based on the river flow patterns, the water demand, the water quality standards, and the anticipated biological integrity in some critical river reaches. Findings in a preliminary case study suggest that an optimal pumping scheme may be smoothly maintained on a yearly basis within a combined multicriteria and multiobjective decision-making process.     

Artificial neural network modeling of dissolved oxygen in reservoir

The water quality of reservoirs is one of the key factors in the operation and water quality management of reservoirs. Dissolved oxygen (DO) in water column is essential for microorganisms and a significant indicator of the state of aquatic ecosystems. In this study, two artificial neural network (ANN) models including back propagation neural network (BPNN) and adaptive neural-based fuzzy inference system (ANFIS) approaches and multilinear regression (MLR) model were developed to estimate the DO concentration in the Feitsui Reservoir of northern Taiwan. The input variables of the neural network are determined as water temperature, pH, conductivity, turbidity, suspended solids, total hardness, total alkalinity, and ammonium nitrogen. The performance of the ANN models and MLR model was assessed through the mean absolute error, root mean square error, and correlation coefficient computed from the measured and model-simulated DO values. The results reveal that ANN estimation performances were superior to those of MLR. Comparing to the BPNN and ANFIS models through the performance criteria, the ANFIS model is better than the BPNN model for predicting the DO values. Study results show that the neural network particularly using ANFIS model is able to predict the DO concentrations with reasonable accuracy, suggesting that the neural network is a valuable tool for reservoir management in Taiwan.     

地表水BOD_5的快速预测预报

地表水五日生化需氧量（ＢＯＤ５）的测试需要五天时间，分析周期较长。本文建立了ＢＯＤ５与高锰酸盐指数（ＣＯＤＭｎ）、ＢＯＤ５与溶解氧（ＤＯ）之间的直线回归方程，通过测定地表水的ＣＯＤＭｎ和ＤＯ可分别对地表水的ＢＯＤ５实现快速预测预报。现场使用溶解氧测定仪检测ＤＯ，可立即预报地表水的ＢＯＤ５。     

Artificial neural network modeling of dissolved oxygen in the Heihe River, Northwestern China

Identification and quantification of dissolved oxygen (DO) profiles of river is one of the primary concerns for water resources managers. In this research, an artificial neural network (ANN) was developed to simulate the DO concentrations in the Heihe River, Northwestern China. A three-layer back-propagation ANN was used with the Bayesian regularization training algorithm. The input variables of the neural network were pH, electrical conductivity, chloride (Cl^?), calcium (Ca²⁺), total alkalinity, total hardness, nitrate nitrogen (NO₃-N), and ammonical nitrogen (NH₄-N). The ANN structure with 14 hidden neurons obtained the best selection. By making comparison between the results of the ANN model and the measured data on the basis of correlation coefficient (r) and root mean square error (RMSE), a good model-fitting DO values indicated the effectiveness of neural network model. It is found that the coefficient of correlation (r) values for the training, validation, and test sets were 0.9654, 0.9841, and 0.9680, respectively, and the respective values of RMSE for the training, validation, and test sets were 0.4272, 0.3667, and 0.4570, respectively. Sensitivity analysis was used to determine the influence of input variables on the dependent variable. The most effective inputs were determined as pH, NO₃-N, NH₄-N, and Ca²⁺. Cl^? was found to be least effective variables on the proposed model. The identified ANN model can be used to simulate the water quality parameters.