An Optimization Model for Waste Load Allocation under Water Carrying Capacity Improvement Management, A Case Study of the Yitong River, Northeast China

Uncertainty analysis and economic value prediction of water environmental capacity based on Copula and Bayesian model: A case study of Yitong River, China

Water environmental capacity (WEC) is an indicator of environment management. The uncertainty analysis of WEC is more closely aligned with the actual conditions of the water body. It is crucial for accurately formulating pollution total emissions control schemes. However, the current WEC uncertainty analysis method ignored the connection between water quality and discharge, and required a large amount of monitoring data. This study analyzed the uncertainty of the WEC and predicted its economic value based on Copula and Bayesian model for the Yitong River in China. The Copula model was employed to calculate joint probabilities of water quality and discharge. And the posterior distribution of WEC with limited data was obtained by the Bayesian formula. The results showed that the WEC-COD in the Yitong River was 9009.67 t/a, while NH3-N had no residual WEC. Wanjinta Highway Bridge-Kaoshan Town reach had the most serious pollution. In order to make it have WEC, the reduction of COD and NH3-N was 5330.47 t and 3017.87 t. The economic value of WEC-COD was 5.97 × 107 CNY, and the treatment cost was 2.04 × 108 CNY to make NH3-N have residual WEC. The economic value distribution of WEC was extremely uneven, which could be utilized by adjusting the sewage outlet. In addition, since the treated water was discharged into the Sihua Bridge-Wanjinta Highway Bridge reach, the WEC-COD and the economic value were 19,488.51 t/a and 8.24 × 107 CNY. Increasing the flow of rivers could effectively improve WEC and economic value. This study provided an evaluation tool for guiding river water environment management.

River water quality management using an integrated multi-objective optimization-simulation approach based on bankruptcy rules

The aim of this research is to allocate the river's self-purification (acceptance capacity of pollution) fairly between the beneficiaries (pollutant sources) using bankruptcy theory. For this purpose, four bankruptcy rules (CAE, CEL, P, and TAL) were called using the link of the water quality simulation model (QULA2Kw) to an evolutionary optimization algorithm (multi-objective imperialist competition algorithm (MOICA)). The objective functions were reducing polluters' wastewater treatment costs and preventing biochemical oxygen demand (BOD) violations of the standard level along the river. The applicability of the approach is demonstrated by the case study that was carried out on the Dez River in Iran. According to the results, the CEL scenario is the most effective method for the Dez River when taking into account the most optimal state for both objective functions (selecting the best compromise solution from the Pareto front). This is because it has the lowest violation value of the standard level for BOD along the river when compared to other scenarios. Alternatively, when considering Solution 20, which focuses on the maximum cost of treating the polluters while staying within the acceptable level of pollution in the river, the results indicated that the CEA rule emerged as the most favorable option. This is due to its lower treatment cost (156.9 (1000$)) and higher pollution discharge to the river (681.91 g/s).

Coupling Two-Stage Stochastic Robust Programming with Improved Export Coefficient for Water Allocation among Industrial Sectors

Water scarcity and water pollution are essential factors limiting coordinated regional development, especially in water-deprived regions. Industrial restructuring is an effective water management solution to alleviate water scarcity and mitigate water pollution. However, due to widely existing inexact parameter information in the water resource management system, it is challenging to allocate water resources among industrial sectors. To address these problems, an export coefficient coupled with a two-stage stochastic robust programming method (EC-TSRP) was developed through integrating an export coefficient model (ECM), two-stage stochastic programming (TSP) and robust optimization. The proposed EC-TSRP model could effectively deal with the multiple uncertainties expressed as stochastic and the intervals with fluctuation ranges, and enhance the robustness of optimal plans for supporting water resource allocation among industrial sectors under complex uncertainties. It was then applied to Bayan Nur City, in arid north-west China. The optimization alternatives indicate that wheat, sheep and services would be the most sensitive sectors among all industrial sectors, when non-point source (NPS) pollution exports are restricted. In addition, comparing the EC-TSRP results with the deterministic model, the reliability of the system could be improved significantly, while the value of the objective function would be decreased slightly. The simulation results were also compared with the historical data from 2012 to 2016. Although the total revenue of Bayan Nur City would decrease by 1.52%, the pollutant loads of total nitrogen, total phosphorus and chemical oxygen demand (TN, TP and COD) would decrease by 14.5%, 7.75% and 2.07%, respectively, and total water allocation also would decrease from 4.6 billion m3 to 4.23 billion m3.

Pollution characteristics of antibiotics and antibiotic resistance of coliform bacteria in the Yitong River, China

In this study, the concentrations of nine typical antibiotics, including sulfadiazine (SD), sulfamerazine (SMR), sulfamethazine (SM2), sulfamethoxazole (SMZ), ofloxacin (OFX), ciprofloxacin (CIP), trimethoprim (TMP), oxytetracycline (OTC), and tetracycline hydrochloride (TC), were detected in the Yitong River by solid-phase extraction high-performance liquid chromatography. The concentrations of the antibiotics were analyzed. Additionally, an improved immobilized substrate enzyme substrate method (DST-enzyme substrate method) was developed and used to evaluate the antibiotic resistance of coliform bacteria to OFX, CIP, enrofloxacin (ENR), TC, sulfisoxazole (SOX), and TMP in the Yitong River. The results showed that the concentrations of the nine antibiotics ranged from nd (not detected) to 1.361 μg/L. The detection rate and concentration of OFX were the highest, followed by CIP, and the detection rate and concentration of SM2 and OTC were the lowest. The detection rate and concentrations of antibiotics were higher in August and November than those in May. The antibiotics were mainly distributed in the livestock sewage discharge and suburban domestic sewage discharge areas. Moreover, the drug resistance of total coliform bacteria to fluoroquinolones, sulfonamides, tetracyclines, and TMP varied with season.

A fuzzy multi-stakeholder socio-optimal model for water and waste load allocation

This study proposes a fuzzy multi-stakeholder socio-optimal methodology for joint water and waste load allocation (WWLA) in river systems while addressing upstream flow uncertainty and different social choice rules (SCRs). QUAL2Kw, as the numerical river water quality model, is executed for various scenarios of water and waste loads to construct a comprehensive dataset of plausible settings, which is in turn used to train a meta-model in the form of multivariate linear regressions. The river upstream flow as the main uncertain parameter is assessed by fuzzy transformation method (FTM). Then, for different confidence levels of fuzzy uncertain input, the meta-model is linked with the non-dominated sorting genetic algorithm (NSGA-II) multi-objective optimization model to generate trade-off curves among the stakeholders' utility functions. Subsequently, five SCRs are utilized at each confidence level to determine the fuzzy interval solutions for each objective. Next, the possibility degree method is applied to rank the fuzzy interval solutions in each α-cut level. Finally, considering the priorities of all stakeholders, the fallback bargaining method is used to specify the most appropriate SCR in each confidence level. Application of the proposed methodology in Kor River, Iran, shows its efficacy to realize the socio-optimal WWLA scenario(s) among different stakeholders.

An Interval Two-Stage Stochastic Programming Model for Flood Resources Allocation under Ecological Benefits as a Constraint Combined with Ecological Compensation Concept

The Momoge National Nature Reserve (MNNR) is located at the intersection of Nenjiang and Taoer Rivers in Baicheng City, Jilin Province, where the Taoer River is the main source of water for the nature reserve. However, due to the construction of the water control project in the upper reaches of the Taoer River, the MNNR has been in a state of water shortage for a long time. To guarantee the wetland function of the nature reserve, the government planned to carry out normal and flood water supply from Nenjiang River through the West Water Supply Project of Jilin Province. Therefore, how to improve the utilization of flood resources effectively has become one of the key issues of ecological compensation for the MNNR. In this paper, a flood resources optimal allocation model that is based on the interval two-stage stochastic programming method was constructed, and the corresponding flood resource availability in different flow scenarios of Nenjiang River were included in the total water resources to improve their utilization. The results showed that the proportion of flood resources that were used in the MNNR after optimization was more than 70% under different flow scenarios, among which the proportion of flood resources under a low-flow scenario reached 77%, which was 23% higher than the proposed increase. In addition, the ecological benefits of low, medium, and high flow levels reached the range of 26.30 (10⁶ CNY) to 32.14(10⁶ CNY), 28.21(10⁶ CNY) to 34.49(10⁶ CNY) and 29.41(10⁶ CNY) to 35.94(10⁶ CNY), respectively. According to the results, flood resources significantly reduce the utilization of normal water resources, which can be an effective supplement to the ecological compensation of nature reserves and provide a basis for the distribution of transit flood resources in other regions.