Water Quality Modeling

Water quality in Cha-Am, Thailand is of particular concern because of the area's extensive oceanfront and its importance to the City’s tourism and real estate industries. PCSWMM was used to help improve water quality by simulating the effluent quality of the aerated lagoon system which treats municipal wastewater and consists of three ponds and a natural wetland.

The ponds were considered storage zones, and water quality sampling for Total Suspended Solid (TSS), Total Kjeldahl Nitrogen (TKN), Escherichia coli (E. coli), Chemical Oxygen Demand (COD), as well as evaporation measurements, were conducted on a bi-weekly basis for three months to calibrate the model.

Based on the observed water quality data distribution, Monte Carlo simulation was used (1,000 iterations) to receive the most probable input concentration for each pond and determine the appropriate treatment fractions for the model. Data on daily inflow rates, pump operation and bathymetric survey data also were obtained from the system operator as model input.

The dynamic wave method was used with observed inflow rates to generate a continuous water quality simulation from July 19th to September 12th, 2015. Observed mean treatment efficiency was 51.93%, 77.27%, 99.59% and 9.36% for TSS, TKN, E. coli and COD respectively; and observed concentrations at the outlet ranged between 10-25.5 mg/L, 0.98-3.92 mg/L, 0.1-260 CFU/100 ml and 48-119 mg/L for TSS, TKN, E. coli and COD respectively.

Able to accurately represent the outlet concentrations, the treatment fraction approach in PCSWWM was successful. This project has helped to protect Cha-Am’s oceanfront against pollution that threatens the City's tourism and real estate markets, and has assisted in informing individuals working toward improving water quality throughout the municipality.

Agricultural production continues to expand and intensify around the world. In rural watersheds with complex stormwater conveyance systems, models designed to predict the downstream impact on water quality and quality due to changes in on-farm management practices tend to inadequately represent the spatial and temporal resolution required in the simulation of hydraulic systems.

In search of an innovative and cost-effective solution for increasing water quality, conserving water and lowering energy use, Ausable Bayfield Conservation Authority (ABCA) retained Emmons and Olivier Resources Inc. to assist in launching a new Rural Stormwater Management Model (RSWMM) as part of the Healthy Lake Huron project.

PCSWMM and SWMM were chosen to help simulate the downstream impacts of a suite of Best Management Practices (BMPs) in order to improve water quality and quantity in the Bayfield North watershed. PCSWMM was used to manually verify subcatchment delineation, perform calibrations through its Sensitivity-based Radio Tuning Calibration (SRTC) tool and simulate sand, silt and clay using its Modified Universal Soil Loss Equation (MUSLE) routine.

Additionally, four pollutants were calculated using PCSWMM’s Derive Functions tool: Total Nitrogen (TN), Total Suspended Solids (TSS), Particulate Phosphorus (PP) and Total Phosphorus (TP). Setting up BMPs using a field shapefile was facilitated by the software’s ability to (a) define enforced value lists for attributes; (b) group attributes into customizable categories; and (c) auto-express attributes.

This exciting new resource is enabling landowners to make increasingly informative decisions about erosion and runoff control projects; and rural extension staff are now better equipped to design soil and water conservation projects which protect and improve water quality in Lake Huron.

Settling solids upstream of a Combined Sewer Overflow (CSO) in Cincinnati have led to an undesirable odour issue in warm temperatures and elevated environmental pollutant loading during the first flush period of wet weather events.

To improve odour and reduce solids during the first flush portion of wet weather events, a first order solids transport model from Willems (2009) was refined to incorporate the concept of uniform settling on the wetted surfaces within the collection system. The collection system’s hydraulic conditions were modeled and compared to the monitored data using PCSWMM.

Over a 10-year period, the model has been expanded and recalibrated. For this project, model comparisons were performed using a set of seven wet weather events where Total Suspended Solid (TSS) samples were collected.

Modeled flow data time series were used as inputs to support water quality modeling. Three simulations were conducted with the hydraulic network in PCSWMM: a Dry Weather Flow (DWF) analysis; a continuous simulation with rain series input during the special sampling period from November, 2010 to January, 2011; and a simulation for the 1970 typical year rain series.

Overall, the Metropolitan Sewer District of Greater Cincinnati (MSDGC) learned that a reduced settling surface area decreased the amount of build-up during dry weather flow within the collection system and subsequently sheds less mass during wet weather events.

Using the hydraulic data from the collection system hydraulic model as an input to the water quality model process, the modeled results suggest that the inclusion of a dry weather channel could provide a reduction in solids during the first flush portion of wet weather events between 26.5% and ~59%.