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EMC/DWC - SRG
- teamcity (Deactivated)
- Nicole Norris (Deactivated)
- dugald (Unlicensed)
The Event Mean Concentration (EMC) Dry Weather Concentration (DWC) model applies two fixed constituent concentrations (EMC & DWC) to a functional unit (FU) to calculate total constituent load.
This model is applied at the functional unit scale within a sub-catchment. Therefore the user needs to ensure that the values used to populate the model correspond with the scale at which the EMC/DWC data were collected. For example, paddock (edge-of-field) scale runoff concentrations of pollutants can be rapidly attenuated in transport by dilution, deposition and trapping. Filtering and or in stream decay processes may need to be incorporated into the model at the FU and or link scales. Equally, EMC values derived from sub-catchment scale data (where losses and inputs have already occurred during transport) should not be applied at the FU scale. The model is a scaling factor using static concentrations through time and is independent of the basic time-step of the model. It is therefore more appropriate for estimating long term loads. |
Principal developer
Cooperative Research Centre for Catchment Hydrology.
Version
Source v3.8.10
Availability/conditions
EMC/DWC is automatically installed with Source.
Flow phase
This model calculates constituent load at a time-step by applying the EMC value to quick (surface) flow, and the DWC value to slow (base) flow.
For constituent C
| Equation 1 |  |
|---|
where:
EMC is the flow-weighted average constituent concentration over a storm event.
DWC is the constituent concentration measured during dry weather.
SF is slow flow.
QF is quick flow.
It is important to distinguish between the EMC and DWC because EMC values can be an order of magnitude different than DWC values.
 EMC/DWC values should be used with caution and will require considerable qualitative judgement as the EMC and DWC values depend on the land-use, soil type, slope, climate and management practices of the catchment (Chiew & Scanlon 2002). |
Input data
The input data required are a single value for Event Mean Concentration (EMC) and Dry Weather Concentration (DWC). These values are typically specified in mg/L.
Some lookup tables of EMC/DWC values are available (Bartley et al., 2011; Chiew & Scanlon 2002; Duncan 1999; Fletcher et al 2004) which are region specific, ideally values should be derived using analysis of local data.
There are a range of methods to derive EMC/DWC values from observed flow and constituent data. Some common methods include:
- Using Flow duration curves to differentiate between ‘event’ and ‘dry’ whether conditions for which the samples were collected (Chiew & Scanlon 2002).
- Dividing the quick flow Load by the quick flow volume for EMC.
- In the absence of flow data, averaging concentrations for events.
- In the absence of flow data, averaging concentrations for events. DWC values are often derived by calculating a mean concentration from water quality samples collected during periods where base flow runoff is observed.
Figure 1: Separation of Quick and Slow Flow in a Rainfall Event
Calculation of these values requires considerable flow and concentration data, or load estimates from which you can "back-calculate" values.
Ideally where an EMC and DWC value is required for a specific FU or land use type then the EMC/DWC values used to parameterise the model should reflect the constituent generation concentrations for that given FU type. |
Parameters or settings
The parameters for this model are summarised in Table 1.
Table 1. Model parameters
Parameter | Description | Units | Default Min | Default Max |
|---|---|---|---|---|
DWC | Dry weather concentration | mg/L | 0 | ∞ |
EMC | Event mean concentration | mg/L | 0 | ∞ |
Output data
The EMC/DWC output data are a scaled derivation of the input data, that is, flow is scaled by concentration to give output load. The scaling is not dependent on the input data time-step.
The output constituent loads are expressed in units of kg per time-step.
Configuration
To create an Effective Mean Concentration model, choose the EMC/DWC model and give both parameters the same value.
The EMCDWC model requires explicit spatial configuration of functional units within each subcatchment in order to apply it in Source. Therefore, it can only be directly used within a Catchments scenario. For further details, refer to the User Guide. |
References
Bartley, R., Speirs W., Ellis, T., Waters,. D. (2011) A review of sediment and nutrient concentration data from Australia for use in catchment water quality models. Marine Pollution Bulletin.
Chiew, F & Scanlon, P 2002, Estimation of pollutant concentrations for EMSS modelling of the South-East Queensland region, Technical Report, Cooperative Research Centre for Catchment Hydrology, Canberra.
Duncan, H 1999, Urban Stormwater quality: a statistical overview, Report 99/3, Cooperative Research Centre for Catchment Hydrology, Canberra.
Fletcher, T, Duncan, H, Poelsma, P & Lloyd, L 2004, Stormwater flow and quality, and the effectiveness of non-proprietary stormwater treatment measures - a review & gap analysis, Technical Report 04/8, Cooperative Research Centre for Catchment Hydrology, Canberra.