Application of Qual2Kw model as a tool for water quality management: Cértima River as a case study

Water quality management by enhancing assimilation capacity with flow augmentation: a case study for the Yamuna River, Delhi

This paper aims to assess the requirement of load reductions and flow augmentation to enhance the assimilation yield of the Yamuna River, Delhi. The framework QUAL2kw was used to predict river quality. The model was calibrated and confirmed in critical flow conditions of pre-monsoon periods. Three strategies were established for varying pollutant loads. The DO concentration was predicted with changing BOD and COD loads. The 16 outfalling drains were considered pollutant sources between the 22 km stretch of the river. Four cases with 41 scenarios were studied with varying flow augmentation upstream and varying load. It has been observed that with 80 cumecs of upstream flow, the reach can assimilate 31.33 tonnes per day of BOD and 142.85 tonnes per day of COD load, maintaining the desired level of DO (≥4 mg/L) and BOD (≤3 mg/L) throughout the reach.

Spatio-temporal investigation of physico-chemical water quality parameters based on comparative assessment of QUAL 2Kw and WASP model for the upper reaches of Yamuna River stretching from Paonta Sahib, Sirmaur district to Cullackpur, North Delhi districts of North India

An accurate investigation of bio-physical and chemical parameters as proxy of in situ water quality conditions in the Himalayan region is highly challenging owing to cumbersome, strenuous, and physically exhausting sampling exercises at high altitude locations. The upper stretches of Yamuna River in the Himachal Pradesh are typical examples of such sampling locations that have rarely been examined in the past studies. A widely accepted and recognized QUAL 2Kw model is applied for estimating the water quality parameters on the upper segment of the Yamuna River from Paonta Sahib to Cullackpur. These water quality indicators mainly included electric conductivity, pH, dissolved oxygen, temperature, carbonaceous biological oxygen demand (CBOD), inorganic suspended solids, total nitrogen, total phosphorus, and alkalinity, which were systematically investigated for predicting the spatio-temporal trends during the year 2018. A total of 12 distantly located river sites were identified for sample collection and data validation using QUAL 2Kw model. The present investigation attempts to reveal long-term degraded impact of untreated wastewater and biased agricultural practices on the water quality conditions over the upper stretches of Yamuna River. The QUAL 2Kw-derived values for selected variables were inter-compared with in situ values, and any deviation from measured values was ascertained based on meaningful statistical measures. The lower error of RMSE, MRE, and BIAS, corresponding to < 15%, ± 10%., ± 20%, and ~ 1 slope evidently indicated better matchup of values, wherein, higher slope correlation coefficient (R²) of ~ 90% indicated the robust performance of the QUAL 2Kw algorithm in accurately predicting the chosen variables. A comparative assessment of QUAL 2Kw and WASP has been performed to justify aptness of water quality model in scenarios of lean flow.

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.

A case study of an enhanced eutrophication model with stoichiometric zooplankton growth sub-model calibrated by Bayesian method

Urban lakes in China have suffered from severe eutrophication over the past several years, particularly those with relatively small areas and closed watersheds. Many efforts have been made to improve the understanding of eutrophication physiology with advanced mathematical models. However, several eutrophication models ignore zooplankton behavior and treat zooplankton as particles, which lead to the systematic errors. In this study, an eutrophication model was enhanced with a stoichiometric zooplankton growth sub-model that simulated the zooplankton predation process and the interplay among nitrogen, phosphorus, and oxygen cycles. A case study in which the Bayesian method was used to calibrate the enhanced eutrophication model parameters and to calculate the model simulation results was carried out in an urban lake in Tianjin, China. Finally, a water quality assessment was also conducted for eutrophication management. Our result suggests that (1) integration of the Bayesian method and the enhanced eutrophication model with a zooplankton feeding behavior sub-model can effectively depict the change in water quality and (2) the nutrients resulting from rainwater runoff laid the foundation for phytoplankton bloom.

Estimation of contribution ratios of pollutant sources to a specific section based on an enhanced water quality model

Because water quality monitoring sections or sites could reflect the water quality status of rivers, surface water quality management based on water quality monitoring sections or sites would be effective. For the purpose of improving water quality of rivers, quantifying the contribution ratios of pollutant resources to a specific section is necessary. Because physical and chemical processes of nutrient pollutants are complex in water bodies, it is difficult to quantitatively compute the contribution ratios. However, water quality models have proved to be effective tools to estimate surface water quality. In this project, an enhanced QUAL2Kw model with an added module was applied to the Xin'anjiang Watershed, to obtain water quality information along the river and to assess the contribution ratios of each pollutant source to a certain section (the Jiekou state-controlled section). Model validation indicated that the results were reliable. Then, contribution ratios were analyzed through the added module. Results show that among the pollutant sources, the Lianjiang tributary contributes the largest part of total nitrogen (50.43%), total phosphorus (45.60%), ammonia nitrogen (32.90%), nitrate (nitrite + nitrate) nitrogen (47.73%), and organic nitrogen (37.87%). Furthermore, contribution ratios in different reaches varied along the river. Compared with pollutant loads ratios of different sources in the watershed, an analysis of contribution ratios of pollutant sources for each specific section, which takes the localized chemical and physical processes into consideration, was more suitable for local-regional water quality management. In summary, this method of analyzing the contribution ratios of pollutant sources to a specific section based on the QUAL2Kw model was found to support the improvement of the local environment.

Integration of Bayesian analysis for eutrophication prediction and assessment in a landscape lake

Eutrophication models have been widely used to assess water quality in landscape lakes. Because flow rate in landscape lakes is relatively low and similar to that of natural lakes, eutrophication is more dominant in landscape lakes. To assess the risk of eutrophication in landscape lakes, a set of dynamic equations was developed to simulate lake water quality for total nitrogen (TN), total phosphorous (TP), dissolve oxygen (DO) and chlorophyll a (Chl a). Firstly, the Bayesian calibration results were described. Moreover, the ability of the model to reproduce adequately the observed mean patterns and major cause-effect relationships for water quality conditions in landscape lakes were presented. Two loading scenarios were used. A Monte Carlo algorithm was applied to calculate the predicated water quality distributions, which were used in the established hierarchical assessment system for lake water quality risk. The important factors affecting the lake water quality risk were defined using linear regression analysis. The results indicated that the variations in the landscape lake receiving recharge water quality caused considerable landscape lake water quality risk in the surrounding area. Moreover, the Chl a concentration in lake water was significantly affected by TP and TN concentrations; the lake TP concentration was the limiting factor for growth of plankton in lake water. The lake water TN concentration provided the basic nutritional requirements. Lastly, lower TN and TP concentrations in the receiving recharge water caused increased lake water quality risk.