Simulation of water environmental capacity and pollution load reduction using QUAL2K for water environmental management

Simulation and modelling of heavy metals and water quality parameters in the river

A one-dimensional qualitative model was created for this study's modelling and phase transfer of the heavy metal dissolved in the river. The advection-diffusion equation considers the environmental variables temperature, dissolved oxygen, pH, and electrical conductivity as influencing parameters on the change in the concentration of the dissolved phase of heavy metals lead, cadmium, and zinc in springtime and winter. Hec-Ras hydrodynamic model and Qual2kw qualitative model have been used to determine the hydrodynamic and environmental parameters in the created model. The approach of minimizing simulation errors and Vba coding was employed to identify the constant coefficients for these relations, and the linear relation incorporating all of the parameters is thought to be the final connection. In order to simulate and calculate the concentration of the heavy metals in the dissolved phase at each site, the kinetic coefficient of the reaction corresponding to that point should be employed because the kinetic coefficient of the reaction varies in different portions of the river. Additionally, if the above mentioned environmental parameters are used in the spring and winter term of advection-diffusion equations, the accuracy of the developed model significantly improves, and the effect of other qualitative parameters is negligible, indicating that the model is effective at simulating the dissolved phase of heavy metals in the river.

Modeling Risk Dynamics of Contaminants of Emerging Concern in a Temperate-region Wastewater Effluent-dominated Stream

Wastewater effluent-dominated streams are becoming increasingly common worldwide, including in temperate regions, with potential impacts on ecological systems and drinking water sources. We recently quantified the occurrence/ spatiotemporal dynamics of pharmaceutical mixtures in a representative temperate-region wastewater effluent-dominated stream (Muddy Creek, Iowa) under baseflow conditions and characterized relevant fate processes. Herein, we quantified the ecological risk quotients (RQs) of 19 effluent-derived contaminants of emerging concern (CECs; including: 14 pharmaceuticals, 2 industrial chemicals, and 3 neonicotinoid insecticides) and 1 run-off-derived compound (atrazine) in the stream under baseflow conditions, and estimated the probabilistic risks of effluent-derived CECs under all-flow conditions (i.e., including runoff events) using stochastic risk modeling. We determined that 11 out of 20 CECs pose medium-to-high risks to local ecological systems (i.e., algae, invertebrates, fish) based on literature-derived acute effects under measured baseflow conditions. Stochastic risk modeling indicated decreased, but still problematic, risk of effluent-derived CECs (i.e., RQ≥0.1) under all-flow conditions when runoff events were included. Dilution of effluent-derived chemicals from storm flows thus only minimally decreased risk to aquatic biota in the effluent-dominated stream. We also modeled in-stream transport. Thirteen out of 14 pharmaceuticals persisted along the stream reach (median attenuation rate constant k<0.1 h^-1) and entered the Iowa River at elevated concentrations. Predicted and measured concentrations in the drinking water treatment plant were below the human health benchmarks. This study demonstrates the application of probabilistic risk assessments for effluent-derived CECs in a representative effluent-dominated stream under variable flow conditions (when measurements are less practical) and provides an enhanced prediction tool transferable to other effluent-dominated systems.

Impacts of Climate Change and Non-Point-Source Pollution on Water Quality and Algal Blooms in the Shoalhaven River Estuary, NSW, Australia

This study quantifies some of the potential impacts of climate change and nutrient pollution to identify the most important factors on water quality changes and algal blooms in the study region. Three variables, air temperature and streamflow, representing climate change, and nutrient runoff, were varied in eight hypothetical scenarios to determine their impact on water quality and algal blooms by the calibrated and validated water quality model QUAL2K. Water quality was assessed by the concentrations of dissolved oxygen, total nitrogen, and phosphorus. Algal blooms were identified by phytoplankton concentration. An increase in air temperature of up to 2 °C resulted in an average increase of 3% in water temperature and 4.79% in phytoplankton concentration, and an average decrease of 0.48% in dissolved-oxygen concentration. Projected decreases in streamflow not only made the above phenomenon more significant but also significantly increased the concentration of total nitrogen, total phosphorus, and phytoplankton with the same pollution inputs. Under climate change, the biggest cause of concern for estuarine water quality is reduced streamflow due to decreases in rainfall. Water quality improvement is possible by regulating the concentration of non-point-source pollution discharge. By reducing nutrient runoff, the total nitrogen and phosphorus concentrations were also reduced, resulting in a significant increase in the dissolved oxygen concentration. This study highlights the most significant factors for managing water quality in estuaries subject to climate change.

Surface Water Resources Assessment and Planning with the QUAL2KW Model: A Case Study of the Maroon and Jarahi Basin (Iran)

Mathematical models are useful for predicting the reactions of watercourses such as rivers due to the entry of contaminants. Some of these models are able to simulate the effects of present and future loadings as well as aid managers and officials in making decisions even if the data are sparse. In other words, river water quality preservation requires more investment in wastewater treatment and/or the installation of collection and control systems; it may also limit activity expansion in the river basin. The conservation of watersheds such as the Maroon and Jarahi basin, which provide water for drinking and for industrial and agricultural use, is socio-economically vital. Therefore, the first stage of managing the conservation of water resources is understanding their qualitative changes. For this purpose, the QUAL2KW mathematical model was utilized to simulate the river water quality in this example region. According to the reported values of water quality parameters and pollutants at monitoring stations, it was established that the river is at a critical condition in terms of biochemical oxygen demand (BOD) pollution due to the discharge of urban and industrial wastewater, as well as high electrical conductivity (EC) due to the drainage of agricultural lands. Based on the statistics calculated during the validation step, the authors concluded that the QUAL2KW water quality model is reliable in the simulation of qualitative parameters and the pollution data of the study area; namely the Maroon and Jarahi river basin located in the south-west of Iran. This will help stakeholders to better manage watersheds with sparse data. This region has been suffering from climate change which has led to droughts and the construction of several dams to retain water. For the second and third stations, the NASH (named after the mathematician John Forbes Nash) values were 0.96 and 0.92, respectively, indicating a relatively high model accuracy. The evaluation using the root mean square errors (RMSE) and NASH showed that the quality of water at the second station was better than the other two stations based on the coefficient of determination R2. Since there were three drains at station number 3, the wastewater entering the Maroon River had a higher level of contamination.

Assessment of the environmental carrying capacity of pollutants in Tam Giang-Cau Hai Lagoon (Viet Nam) and solutions for the environment protection of the lagoon

Tam Giang-Cau Hai lagoon is the largest lagoon in Viet Nam. It has two inlets that exchange water with the sea: Thuan An inlet in the north and Tu Hien inlet in the south. Every year, Tam Giang-Cau Hai lagoon receives a large amount of wastewater from five coastal districts with various waste sources such as residences, aquaculture, livestock and industry among others. Due to the low water exchange through the two inlets, wastewater is discharged into the lagoon and pollutants accumulate in the water. This results in pollution concentrations in the water exceeding the environmental limits and causing adverse effects on aquatic life. This paper presents the environmental carrying capacity (ECC) of the lagoon based on calculations from the Delft-3D model using three scenarios: 1) ECC following Vietnamese regulations; 2) maximum ECC or dangerous scenario (which the water body can no longer purify itself or becomes a dead water body); 3) proposed ECC for the protection of aquatic life. Based on the study results, some solutions have been proposed to protect the lagoon with the construction of wastewater treatment plants being the most important action to reduce pollution load in the lagoon.

Selection of Optimum Pollution Load Reduction and Water Quality Improvement Approaches Using Scenario Based Water Quality Modeling in Little Akaki River, Ethiopia

The collective impacts of rapid urbanization, poor pollution management practices and insufficient sanitation infrastructure have driven the water quality deterioration in Little Akaki River (LAR), Ethiopia. Water quality modeling using QUAL2Kw was conducted in the LAR aimed at selecting the optimal water quality improvement and pollution load reduction approaches based on the evaluation of five scenarios: modification of point sources (PS) load (S1), modification of nonpoint sources (NPS) load (S2), simultaneous modification of PS and NPS load (S3), application of local oxygenators and fish passages using cascaded rock ramps (S4), and an integrated scenario (S5). Despite the evaluation of S1 resulting in an average load reduction of Biochemical Oxygen Demand (BOD) (17.72%), PO4-P (37.47%), NO3-N (19.63%), the water quality objective (WQO) in LAR could not be attained. Similarly, though significant improvement of pollution load was found by S2 and S3 evaluation, it did not secure the permissible BOD and PO4-P pollution load in the LAR. Besides, as part of an instream measure, a scenario evaluated using the application of rock ramps (S4) resulted in significant reduction of BOD load. All the individual scenarios were not successful and hence an integration of scenarios (S5) was evaluated in LAR that gave a relatively higher pollutant load reduction rate and ultimately was found a better approach to improve pollution loads in the river. In conclusion, pollution load management and control strategy integrally incorporating the use of source-based wastewater treatment, control of diffuse pollution sources through the application of best management practices and the application of instream measures such as the use of cascaded rock ramps could be a feasible approach for better river water quality management, pollution reduction, aquatic life protection and secure sustainable development in the LAR catchment.

Scenario-based pollution discharge simulations and mapping using integrated QUAL2K-GIS

Malaysia is a tropical country that is highly dependent on surface water for its raw water supply. Unfortunately, surface water is vulnerable to pollution, especially in developed and dense urban catchments. Therefore, in this study, a methodology was developed for an extensive temporal water quality index (WQI) and classification analysis, simulations of various pollutant discharge scenarios using QUAL2K software, and maps with NH₃-N as the core pollutant using an integrated QUAL2K-GIS. It was found that most of the water quality stations are categorized as Class III (slightly polluted to polluted). These stations are surrounded by residential areas, industries, workshops, restaurants and wet markets that contribute to the poor water quality levels. Additionally, low WQI values were reported in 2010 owing to development and agricultural activities. However, the WQI values improved during the wet season. High concentrations of NH₃-N were found in the basin, especially during dry weather conditions. Three scenarios were simulated, i.e. 10%, 50% and 70% of pollution discharge into Skudai river using a calibrated and validated QUAL2K model. Model performance was evaluated using the relative percentage difference. An inclusive graph showing the current conditions and pollution reduction scenarios with respect to the distance of Skudai river and its tributaries is developed to determine the WQI classification. Comprehensive water quality maps based on NH₃-N as the core pollutant are developed using integrated QUAL2K-GIS to illustrate the overall condition of the Skudai river. High NH₃-N in the Skudai River affects water treatment plant operations. Pollution control of more than 90% is required to improve the water quality classification to Class II. The methodology and analysis developed in this study can assist various stakeholders and authorities in identifying problematic areas and determining the required percentage of pollution reduction to improve the Skudai River water quality.

Artificial neural network model to predict transport parameters of reactive solutes from basic soil properties

Measurement of solute-transport parameters through soils for a wide range of solute- and soil-types is time-consuming, laborious, expensive and practically impossible. So, indirect methods for estimating the transport parameters by pedo-transfer functions are now advancing. This study developed and evaluated an Artificial Neural Network (ANN) model for estimating the transport velocity (V), dispersion coefficient (D) and retardation factor (R) of NaAsO₂, Pb(NO₃)₂, Cd(NO₃)₂, C₉H₉N₃O₂ and CaCl₂ from the basic soil properties. Breakthrough data of the solutes were measured in 14 agricultural soils of Bangladesh by time-domain reflectometry (TDR) in repacked soil columns under unsaturated steady-state water-flow conditions. The transport parameters of the chemicals were determined by analyzing the solute breakthrough data. Bulk density (γ), organic carbon (OC), clay (C) content, pH, median grain diameter (D₅₀) and uniformity coefficient (C_u) of the soils were determined. An ANN model for V, D and R was developed by using data of eight soils, validated/tested with the data of five soils and verified with the data of one soil. Clay content and bulk density of the soils were the most sensitive input variables to the ANN model followed by other soil properties (OC, C, pH, D₅₀ and C_u). The model reliably predicted V, D and R with relative root-mean-square error (RRMSE) of 0.028-0.363, mean error (ME) of - 0.00004 to 0.0005, bias error (BOE%) of 0-0.003 and modeling efficiency (EF) of >0.99. Thus, the ANN model can significantly enhance prediction of pollution transport through soils in terms of cost and effort.

Distribution of clinically relevant antibiotic resistance genes in Lake Tai, China

Lake Tai is China's third largest freshwater lake and an important water resource for agriculture, industrial sectors, and as drinking water for several large cities. In this study, the occurrence of five antibiotic resistance genes (sul1, bla_TEM, bla_NDM-1, bla_CTX-M-32, mcr-1) was investigated in water and sediment samples collected from Lake Tai. Antibiotic resistances are currently increasing, posing a significant threat to public health. The sulfonamide resistance gene sul1 was highly abundant in all analyzed water and sediment samples. In addition, the two β-lactamase genes bla_TEMand bla_NDM-1 - encoding clinically relevant antibiotic resistances - were detected in 67.1 and 7.3% of the water samples and in 70.7 and 15.4% of the sediment samples. The third β-lactamase gene, bla_CTX-M-32, was only detected in water samples (13.4%), while the colistin resistance gene mcr-1 was not detected in any of the samples. No significant variations between different sampling sites or time points could be observed. The investigation of drinking water treatment at Lake Tai, using lake water as influent, showed a significant reduction of the antibiotic resistance genes through the treatment process. Microbial source tracking showed only low fecal contamination by humans, ruminants, and pigs, indicating the relevance of other sources such as fish farms. Overall, our results provide important insights into the occurrence and abundance of antibiotic resistance genes in the Lake Tai water system and their elimination via drinking water treatment.

Research on the Relationship between Water Diversion and Water Quality of Xuanwu Lake, China

Water diversion is often used to improve water quality to reach the standard of China in the short term. However, this large amount of water diversion can not only improve the water quality, but also lead to a decline in the water quality (total phosphorus, total nitrogen) of Xuanwu Lake. Through theoretical analysis, the relationship between water quality and water diversion is established. We also found that the multiplication of the pollutant degradation coefficient (K) and the water residence time (T) is a constant (N), K⋅T=N. The water quality changed better at first, with the increase of inflow discharge, and then became worse, and the optimal water quality inflow discharge is 180,000 m³/day. By constructing two-dimensional hydrodynamic and water quality models, the optimal diversion water plan is calculated. Through model calculations, it can be seen that reducing the inflow discharge makes the water residence time longer (15.3 days changed to 23.8 days). Thereby, increasing the degradation of pollutants, and thus improving water quality. Compared with other wind directions, the southwest wind makes the water quality of Xuanwu Lake the most uniform. The concentration of water quality first became smaller and then became larger, as the wind speed increased, and eventually became constant. Implementing these results for water quality improvement in small and medium lakes will significantly reduce the cost of water diversion.

Spatial and Seasonal Dynamics of Water Environmental Capacity in Mountainous Rivers of the Southeastern Coast, China

The south-east littoral is one of the most populous and developed regions in China suffering from serious water pollution problems, and the Xian-Jiang Basin in the mid of this region is among the most polluted watersheds. Critical information is needed but lacking for improved pollution control and water quality assessment, among which water environmental capacity (WEC) is the most important variable but is difficult to calculate. In this study, a one-dimensional water quality model combined with a matrix calculation algorithm was first developed and calibrated with in-situ observations in the Xian-Jiang basin. Then, the model was applied to analyze the spatial and temporal patterns of WEC of the entire basin. The results indicated that, in 2015, the total pollutant discharges into the river reached 6719.68 t/yr, 488.12 t/yr, and 128.57 t/yr for COD, NH₃-N and TP, respectively. The spatial pattern suggested a strong correlation between these water contaminants and industrial enterprises, residential areas, and land-use types in the basin. Furthermore, it was noticed that there was a significant seasonal pattern in WEC that the dry season pollution is much greater than that in the plum season, while that in the typhoon season appears to be the weakest among all seasons. The WEC differed significantly among the 24 sub-basins during the dry season but varied to a smaller extent in other seasons, suggesting differential complex spatial-temporal dependency of the WEC.

Estimation of environmental flow incorporating water quality and hypothetical climate change scenarios

Environmental flows (Eflow, hereafter) are the flows to be maintained in the river for its healthy functioning and the sustenance and protection of aquatic ecosystems. Estimation of Eflow in any river stretch demands consideration of various factors such as flow regime, ecosystem, and health of river. However, most of the Eflow estimation studies have neglected the water quality factor. This study urges the need to consider water quality criterion in the estimation of Eflow and proposes a framework for estimating Eflow incorporating water quality variations under present and hypothetical future scenarios of climate change and pollution load. The proposed framework is applied on the polluted stretch of Yamuna River passing through Delhi, India. Required Eflow at various locations along the stretch are determined by considering possible variations in future water quantity and quality. Eflow values satisfying minimum quality requirements for different river water usage classes (classes A, B, C, and D as specified by the Central Pollution Control Board, India) are found to be between 700 and 800 m³/s. The estimated Eflow values may aid policymakers to derive upstream storage-release policies or effluent restrictions. Generalized nature of this framework will help its implementation on any river systems.

Control of Pollutants in the Trans-Boundary Area of Taihu Basin, Yangtze Delta

This work focuses on pollution control in the trans-boundary area of Taihu Basin. Considering the unique characteristics of the river network in the study area, a new methodology of pollution control is proposed aiming at improving the water quality in the trans-boundary area and reducing conflicts between up and downstream regions. Based on monitoring data and statistical analysis, important trans-boundary cross sections identified by the regional government were selected as important areas for consideration in developing management objectives; using a 1-D mathematicmodel and an effective weight evaluation model, the trans-boundary effective control scope (TECS) of the study area was identified as the scope for pollutant control; the acceptable pollution load was then estimated using an established model targeting bi-directional flow. The results suggest that the water environmental capacity for chemical oxygen demand (COD), in order to guarantee reaching the target water quality standard in the TECS, is 160,806 t/year, and amounts to 16,098 t/year, 3493 t/year, and 39,768 t/year for ammonia nitrogen, total nitrogen, and total phosphorus, respectively. Our study method and results have been incorporated into the local government management project, and have been proven to be useful in designing a pollution control strategy and management policy.

Simulation-based optimization framework for reuse of agricultural drainage water in irrigation

A simulation-based optimization framework for agricultural drainage water (ADW) reuse has been developed through the integration of a water quality model (QUAL2Kw) and a genetic algorithm. This framework was applied to the Gharbia drain in the Nile Delta, Egypt, in summer and winter 2012. First, the water quantity and quality of the drain was simulated using the QUAL2Kw model. Second, uncertainty analysis and sensitivity analysis based on Monte Carlo simulation were performed to assess QUAL2Kw's performance and to identify the most critical variables for determination of water quality, respectively. Finally, a genetic algorithm was applied to maximize the total reuse quantity from seven reuse locations with the condition not to violate the standards for using mixed water in irrigation. The water quality simulations showed that organic matter concentrations are critical management variables in the Gharbia drain. The uncertainty analysis showed the reliability of QUAL2Kw to simulate water quality and quantity along the drain. Furthermore, the sensitivity analysis showed that the 5-day biochemical oxygen demand, chemical oxygen demand, total dissolved solids, total nitrogen and total phosphorous are highly sensitive to point source flow and quality. Additionally, the optimization results revealed that the reuse quantities of ADW can reach 36.3% and 40.4% of the available ADW in the drain during summer and winter, respectively. These quantities meet 30.8% and 29.1% of the drainage basin requirements for fresh irrigation water in the respective seasons.

Simulation and evaluation of pollution load reduction scenarios for water environmental management: a case study of inflow river of Taihu Lake, China

In the beginning of the 21st century, the deterioration of water quality in Taihu Lake, China, has caused widespread concern. The primary source of pollution in Taihu Lake is river inflows. Effective pollution load reduction scenarios need to be implemented in these rivers in order to improve the water quality of Taihu Lake. It is important to select appropriate pollution load reduction scenarios for achieving particular goals. The aim of this study was to facilitate the selection of appropriate scenarios. The QUAL2K model for river water quality was used to simulate the effects of a range of pollution load reduction scenarios in the Wujin River, which is one of the major inflow rivers of Taihu Lake. The model was calibrated for the year 2010 and validated for the year 2011. Various pollution load reduction scenarios were assessed using an analytic hierarchy process, and increasing rates of evaluation indicators were predicted using the Delphi method. The results showed that control of pollution from the source is the optimal method for pollution prevention and control, and the method of “Treatment after Pollution” has bad environmental, social and ecological effects. The method applied in this study can assist for environmental managers to select suitable pollution load reduction scenarios for achieving various objectives.

Spatio-temporal distribution patterns in environmental factors, chlorophyll-a and microcystins in a large shallow lake, Lake Taihu, China

The spatio-temporal distribution of environmental factors, chlorophyll-a (Chl-a), and microcystins (MCs) in a shallow lake, Lake Taihu (China), were investigated from 2009 to 2011 on a monthly basis at nine sampling stations. The annual mean concentration ranges of total nitrogen (TN), total phosphorus (TP), Chl-a, MC-LR and MC-RR were 0.17–10.53 mg/L, 0.027–0.581 mg/L, 0.10–129.75 µg/L, 0.013–2.019 µg/L and 0.002–0.794 µg/L, respectively. The average TN, ammonium (NH₄⁺) and TP concentrations in Meiliang Bay decreased from 3.54 to 2.26 mg/L, 0.63 to 0.31 mg/L and 0.150 to 0.124 mg/L, respectively, when compared with values from 2006–2008, indicating that water quality has improved in severe cyanobacterial bloom areas in recent years. Additionally, the distribution of MCs was northern lake areas > western lake areas > central lake areas > macrophyte-dominated areas. Correlation analysis revealed that nutrients were the most important variable accounting for the variation of extracellular MC-LR concentration in heavy cyanobacterial bloom areas of Lake Taihu. During the study period, the maximum MCs concentration reached 2.75 ± 0.27 μg/L in the bloom period in the northern lake areas, which is more than two times the safety limit of 1 μg/L MCs required for drinking water. However, microcystins decreased gradually as the water quality improved from 2009 to 2011, indicating that the risk of MCs exposure was slightly decreased in Lake Taihu.

From eutrophic to mesotrophic: modelling watershed management scenarios to change the trophic status of a reservoir

Management decisions related with water quality in lakes and reservoirs require a combined land-water processes study approach. This study reports on an integrated watershed-reservoir modeling methodology: the Soil and Water Assessment Tool (SWAT) model to estimate the nutrient input loads from the watershed, used afterwards as boundary conditions to the reservoir model, CE-QUAL-W2. The integrated modeling system was applied to the Torrão reservoir and drainage basin. The objective of the study was to quantify the total maximum input load that allows the reservoir to be classified as mesotrophic. Torrão reservoir is located in the Tâmega River, one of the most important tributaries of the Douro River in Portugal. The watershed is characterized by a variety of land uses and urban areas, accounting for a total Waste Water Treatment Plants (WWTP) discharge of ~100,000 p.e. According to the criteria defined by the National Water Institute (based on the WWTP Directive), the Torrão reservoir is classified as eutrophic. Model estimates show that a 10% reduction in nutrient loads will suffice to change the state to mesotrophic, and should target primarily WWTP effluents, but also act on diffuse sources. The method applied in this study should provide a basis for water environmental management decision-making.