Simultaneous estimation of model parameters and diffuse pollution sources for river water quality modeling

Parameter Identification of an Ultrafiltration Model for Organics Removal in a Full-Scale Wastewater Reclamation Plant with Sparse and Incomplete Monitoring Data

Ultrafiltration (UF) has become one of the dominant treatment processes for wastewater reclamation in China. Modeling is an effective instrument to understand and optimize UF systems. To this end, a previously developed UF model for organics removal was applied to the UF process in a typical, full-scale wastewater reclamation plant (WRP) in China. However, the sparse and incomplete field monitoring data from the studied WRP made the traditional model analysis approaches hardly work in this case. Therefore, two strategies, namely Strategy 1 and Strategy 2, were proposed, following a regional sensitivity analysis approach, for model parameter identification. Strategy 1 aimed to identify the model parameters and the missing model input, i.e. sampling times, simultaneously, while Strategy 2 tried to separate these two processes to reduce the dimension of the identification problem through an iteration procedure. With these two strategies, the model performed well in the Qinghe WRP with the absolute relative errors between the simulated and observed total organic carbon (TOC) generally below 10%. The four model parameters were all sensitive and identifiable, and even the sampling times could be roughly identified. Given the incomplete model input, these results were encouraging and added to the trustworthiness of model when it was applied to the Qinghe WRP.

Optimization of industrial structure based on water environmental carrying capacity in Tieling City

A system dynamics optimization model of the industrial structure of Tieling City based on water environmental carrying capacity has been established. This system is divided into the following subsystems: water resources, economics, population, contaminants, and agriculture and husbandry. Three schemes were designed to simulate the model from 2011 to 2020, and these schemes were compared to obtain an optimal social and economic development model in Tieling City. Policy recommendations on industrial structure optimization based on the optimal solution provide scientific decision-making advice to develop a strong and sustainable economy in Tieling.

Modeling riverine pathogen fate and transport in Mexican rural communities and associated public health implications

The discharge of untreated or poorly treated wastewater to river systems remains a major problem affecting public and environmental health, particularly in rural communities of less developed countries. One of the primary goals in setting policies for wastewater management is to reduce risks to human health associated with microbial contamination of receiving water. In this study, we apply a surface water quality model to develop an Escherichia coli based indicator that reflects the quality of surface water and the potential impact to recreational users in a large, rural river in northwest Mexico (upper Sonora River). The model assesses the relative importance of streamflow variations and the uncertainty in E. coli removal coefficient parameters for the predictions of E. coli concentrations in the river. Given the sparse information on streamflow, we use a physically-based, distributed hydrologic model to generate tributary contributions to the river. We determined the best estimate and uncertainty of E. coli removal rates to explore the impacts of parameter uncertainty on the transport of E. coli downstream from two wastewater discharge zones. Our results depict the regions in the river that are in noncompliance with fresh water pathogen norms. The impact of streamflow variability and uncertainty in the removal rates of pathogen indicators was used to derive a range of river distances in noncompliance. The comparison between two sites with different streamflow behaviors was used to illustrate the impacts of streamflow spatiotemporal variability on pathogen indicators. We derive a simple relationship that can be used to assess the relative importance of dilution (ratio of wastewater discharge to river discharge) and pathogen removal (ratio of residence time to reaction time).