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The WATS model Microbial and chemical processes related to human waste have always caused problems and nuisances.

Spreading of diseases, odors and unaesthetic conditions have been key concerns leading to the installation

of sewer networks. By conveying waterborne waste in channels or pipes, odor and health problems are

reduced significantly. However, confining the human waste to underground structures does not prevent

microbial and chemical transformations to take place; it only constricts the processes to locations where

they cause less harm. The WATS model is the first model concept developed to model these processes. It is

continuously being developed and is still today the most comprehensive sewer process concept.

WATS is a concept for modeling biological, chemical, and physical processes in sewer systems. It is

developed concurrently with new research on sewer systems and processes. As such it forms the

conceptual backbone of a numerical sewer process model – the WATS model – which can be used to

simulate a wide range of processes in sewer systems.

In brief, modeling with WATS typically aims at solving the following in-sewer problems, in practice often

related to an analysis of these problems and potentially including corresponding process controls and

management strategies:

Concrete corrosion caused by hydrogen sulfide

Hydrogen sulfide impacts on human health

Odor nuisance caused by hydrogen sulfide and VOCs being emitted from the wastewater and

following vented into the urban atmosphere

Hydrogen sulfide and VOC controls

Analysis of wastewater quality at inflows to wastewater treatment plants

The current state of the WATS model can be found in the sewer process book (reference below) and later

journal publications. The authors of the sewer process book are the people behind the concept and give in

the book a detailed description of key processes included in the model. It also gives the mathematical

formulation of the concept which is needed to build a numerical instant of WATS.

Hvitved-Jacobsen T, Vollertsen J, Nielsen AH (2013). Sewer Processes: Microbial and Chemical Process

Engineering of Sewer Networks. Second Edition, pp 408, CRC Press, ISBN 978-1-4398-8177-4

Disclaimer: It has become known to us, the developers of the WATS model concept, that the software

producer DHI (Danish Hydraulic Institute) claims that they have included the WATS model in the Mike

Urban software. This is strongly misleading as DHI has only included parts of the very earliest version of the

concept as it was in the late 1990’ies. The concept that DHI has included in the Mike Urban software is only

adequate for a rough prediction of hydrogen sulfide formation in force mains, and cannot be applied to

simulate hydrogen sulfide and its management in complete sewer networks. We, the developer of the

WATS model concept, strongly distance ourselves here from. We furthermore clearly state that we have

had no part, what so ever, in the doings of DHI.

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HV-Consult ApS Hellevangen 48, DK-9210 Aalborg SØ, Denmark

A multi-phase model The processes taking place in sewers during conveyance of wastewater are of physical, chemical and

biological nature. The transformation processes occur in wastewater, biofilms, and sewer sediments. These

biological transformations change the quality of the wastewater important for sewer corrosion, odor

problems, wastewater treatment and combined sewer overflows. The transformations taking place in

sewers are strongly interlinked, and the importance of a process cannot be predicted without knowing the

importance of the other processes. As an example: To the question whether or not hydrogen sulfide will

occur in a certain sewer network, it must first be determined if conditions are anaerobic (absence of both

oxygen and nitrate). To do so, the complete mass balance for oxygen must be established, i.e. reaeration

and oxygen consumptions in bulk water, biofilms, and sediments must be known. In order to predict the

reaeration, the sewer geometry, temperature and flow conditions must be known, and in order to know

the oxygen consumptions, the quality (composition of the COD) of the wastewater must be known.

The WATS model is a multi-phase model which includes bulk wastewater, submerged biofilms, sewer

sediments, sewer atmosphere, moist sewer surfaces, as well as ventilation of sewer gas into the urban

atmosphere. It does so by defining a number of coupled differential equations describing transformation

processes in these phases as well as transport between phases. It simulates the conveyance of water as

well as sewer gas in distributed sewer networks.

The WATS concept covers microbial and chemical transformation processes related to organic matter,

sulfurous compounds, oxygen, nitrate, nitrite, and iron. It also simulates the wastewater pH which is crucial

when predicting processes related to hydrogen sulfide and sewer malodors (Table 1, Figure 1).

Table 1. Major processes simulated by the WATS model

Phase Transport and transformation process

Above the gas/water interface Gas flow along the sewer line. Ventilation of sewer gas into the urban atmosphere. Oxidation of hydrogen sulfide on the moist surfaces of the sewer walls. Concrete corrosion.

At the gas/water interface Transport between sewer atmosphere and bulk water of oxygen, hydrogen sulfide, carbon dioxide, mercaptanes and other specific malodorous organic compounds.

Below the gas/water interface and in pressure mains

Water flow along the sewer line. Transformation processes in the bulk water, the sewer biofilms, and the sewer sediments of organic matter, sulfurous compounds, specific organic compounds, oxygen, nitrate, and nitrite. Precipitation of hydrogen sulfide by iron. Chemical oxidation of hydrogen sulfide by strong oxidizing agents. pH and buffer strength of wastewater

WATS focuses on dry weather problems and not wet weather problems.

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Figure 1: Microbial and chemical processes in a gravity sewer

How the WATS concept describes sewer processes The concept describes microbial and chemical transformation processes of organic matter and sulfurous

compounds under aerobic, anoxic, and anaerobic conditions.

Aerobic conditions

When oxygen is present, heterotrophic microorganisms cause the main part of the oxygen consumption.

They oxidize organic matter (COD) to yield energy for growth and maintenance. At the same time, the

organisms use the COD as constituents in the formation of new biomass. Most of the COD present in

wastewater is not immediately suited as substrate for the biomass. The molecules are typically too large to

pass the cell walls and must be broken down into smaller, more readily degradable compounds. This

process is called hydrolysis, and hereby the main bulk of the wastewater COD can be made available for the

biomass. There is, however, always a small fraction of COD that is inert and cannot be made available for

the biomass. This fraction is included in the slow hydrolysable substrate fraction (Figure 2).

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Figure 2. Overview over aerobic transformations

Hydrogen sulfide formed under anaerobic conditions becomes oxidized under aerobic conditions. The

oxidation process is chemical as well as biological. Both process rates are significant under sewer

conditions. The oxidation products are a mixture of oxidized sulfur forms, primarily sulfate, thiosulfate and

elemental sulfur.

Anoxic conditions

In the absence of oxygen and when nitrate or nitrite is present, the latter compounds take over the role of

oxygen. The processes are very similar to processes under aerobic conditions and largely the same

microorganisms utilize both oxygen and nitrate/nitrite (Figure 3). However, processes occur at lower rates

when the microorganisms reduce nitrate/nitrate compared to oxygen.

Figure 3. Overview over anoxic transformations

Anaerobic conditions

In the absence of both oxygen and nitrate, the previously mentioned heterotrophic organisms become

inactive. Instead other organisms take over. Some of these ferment organic matter. Others reduce sulfate

and oxidize COD. Another group of microorganisms produce methane from the COD. The first process –

fermentation – gives rise to end products that are both desirable and undesirable. The end products have

typically an unpleasant odor, however, they are excellent substrates for aerobic and anoxic treatment plant

organisms. The second group – the sulfate reducing organisms – produce sulfide (Figure 4). Sulfides being

related to a number of problems like odors, health hazards, toxicity towards microorganisms and corrosion.

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HV-Consult ApS Hellevangen 48, DK-9210 Aalborg SØ, Denmark

Figure 4. Overview over anaerobic transformations

Reaeration and release of hydrogen sulfide and other volatile compounds

The processes of reaeration and gas release are strongly related, and can be described by the flow

characteristics of the water phase. Both processes are relatively slow and consequently often limiting for

the transformations in the sewer. At structures with high turbulence, however, the reaeration and gas

release is significantly faster than in the sewer line itself.

Corrosion

The hydrogen sulfide that is released into the gas phase of a sewer will be oxidized on the moist surfaces

within the sewer. The end-product of this oxidation is sulfuric acid, which attacks both concrete and metals

and causes corrosion.

The numerical instant of the WATS model Two software instants of the WATS model have been developed with the purpose of dynamic simulation of

biological corrosion of branched sewer networks. The models are developed in Delphi Pascal. The first

instant applies semi-stationary hydraulics and is designed to simulate large sewer networks. It is

appropriate for assessing sewer processes on catchment scale. The second instant applies non-stationary

hydraulics (the full Saint-Venant’s equations) and is designed for smaller systems consisting of a limited

number of force mains and gravity sewers. It is appropriate for in-depth studies of selected parts of the

sewer systems such as force mains and gravity sewers downstream here off.

Model requirements The models require exact geometric information on the sewer layout, similar to what is needed in a

hydrodynamic model such as InfoWorks. The models calculate processes in individual pipes that are

connected by manholes/nodes. They are basically hydraulic models (for both gas and water phases) to

which wastewater quality transformations and exchange processes between phases are coupled. They

furthermore require input on dry weather flow.

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A vast number of experimental studies in the laboratory, on pilot scale setups and in the field have been

conducted to build the knowledge necessary for the WATS concept. These studies have also provided a

range of default model parameters which are used as starting point of a simulation. However, to yield the

best results the model should be calibrated to data from the catchment where it is applied.

Input data For the WATS model as well as any other model, it must be kept in mind that The Model Output will Never

be Better than the Model Input Allows. If only limited data can be made available, experience and

knowledge on wastewater composition depending on catchment characteristics must be applied as a

substitute and the accuracy of the predictions decreases correspondingly.

The model calculates processes in a number of individual pipes, which are connected by manholes/nodes

(Figure 5). It is basically a hydraulic model (for both gas and water phases) to which wastewater quality

transformations are coupled. The input for the model is the physical geometry of the sewer (slope,

diameter, and so on) as well as dry weather flow inputs. The flow inputs occur solely in upstream manholes.

In Figure 5, this means that e.g. pipe 0 receives flow into manhole 0. The uppermost manholes need not to

be the very upper ends of the sewer, where only a few houses are connected (the model is mathematically

capable of doing calculations on this part, including thousands of individual pipes, but it does not always

make good engineering sence to do so). Alternatively, lumped values from upstream catchments can be

used, e.g. lumping 100-10,000 Person Equivalents of wastewater into each node and correspondingly focus

on trunk and intercepting sewer lines. Table 2 shows major input data requirements of the model.

Figure 5. An example of a network layout.

Table 2: Major data input to the corrosion model. Note that all information relates to dry weather conditions, not rainfall runoff.

Variable Comment

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Pipe identifier What is this pipe called?

Upstream node identifier Where does the water come from? (In Figure 5, the red pipe, this is Node ‘2’)

Downstream node identifier Where is the water discharged to? (In Figure 5, the red pipe, this is Node ‘3’)

(x,y,z) coordinate upstream node

This info is used for drawing the result on a plan, indicating the system conditions

(x,y,z) coordinate upstream node

This info is used for drawing the result on a plan, indicating the system conditions

Pipe type G=gravity pipe; P=force main

Slope The slope of the pipe

Pipe diameter The inner diameter of the pipe

Equivalent sand roughness The equivalent sand roughness or alternatively the Manning number

Sewer length Between manhole centres

Pipe shape Special pipe shapes are can be defined

Acid corrodibility If the pipe can be corroded by acid attack or not. E.g. a if it is a plastic pipe, this is ‘false’ if it is a concrete pipe, this is ‘true’.

Equivalent alkalinity of the pipe material

Depending on the materials a concrete pipe is made of, it can have a higher or lower alkalinity, which acts as a neutralizer for the acid formed.

Input flow to the nodes This is not the actual flow in the pipe, but the flow that enters the trunk sewer network from the ‘outside world’. I.e. in Figure 5Fejl! Henvisningskilde ikke fundet., the red pipe, it is the flow that enters node ‘2’ from the sub-catchments lumped to it, i.e. NOT from pipes ‘0’ and ‘1’.

Height of drop structure or pressure loss due to a turbulence in a node during dry weather conditions

This is not to be confused with losses in manholes during rainfall runoff. Only where there is a pressure loss (e.g. a drop, an outlet from a pressure main or a sharp change of direction)

Ventilation The gas tightness of the sewer is chosen

Wastewater quality parameters:

COD The COD content of the input flow to the nodes

BOD The BOD content of the input flow to the nodes

Sulfate The sulfate content of the input flow to the nodes

pH The average pH of the input flow to the nodes

Alkalinity The average alkalinity of the input flow to the nodes

Temperature The average temperature

Stochastic modeling It is seldom – or more correctly: it is never – possible to determine all inputs and all process parameters for

a given sewer. This is partly due to the amount of information needed being rather large, partly due to a

large natural variability of wastewater quality and process parameters, and partly due to the fact that we

often want to simulate future scenarios. The WATS model must consequently be seen as simulating an

‘average situation’, depending on the chosen system characteristics.

The WATS model is a deterministic model. It has a level of complexity similar to the hydrodynamic models

used for simulation of stormwater runoff. For the pipe hydraulics, WATS needs similar data as any

hydrodynamic model. In addition hereto, WATS must receive input data on the quality of the wastewater.

The parameters describing the transformation processes in the WATS model are varying in space and time.

In most cases, the effort to determine all model parameters is furthermore huge, and only the most

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important parameters are measured during model calibration. To overcome these issues, stochastic

modeling can be applied.

For stochastic modeling, each model parameter is associated with a parameter distribution and a Monte

Carlo simulation approach is used to solve the model complex. By this methodology, the distribution of

model compounds (e.g. hydrogen sulfide) at any location within the sewer is calculated. An example of

such simulation is seen in Figure 6. The figure tells that e.g. for location B, there is a 50% possibility of

hydrogen sulfide to be above 2.6 mg/L.

Figure 6. Outcome of a stochastic simulation of hydrogen sulfide in 3 points of a sewer

Another example is shown in Figure 7 where the diurnal variation of hydrogen sulfide in the sewer gas of a

manhole is shown. The graph shows the median value as the full black line and the fields of 25th to 75th

percentiles (strong green) and the fields of 5th to 25th as well as 75th to 95th percentiles (soft green). The

simulations originate from a large sewer catchment in the Arabic region.

Figure 7. Outcome of a stochastic simulation of a the diurnal variation of hydrogen sulfide in the

atmosphere of a sewer (5th, 25th, 50th, 75th, and 95th percentiles)

Hydrogen sulfide [mg/l]

0 2 4 6 8 10 12 14 16

Pe

rce

ntile

[%

]

1

10

30

50

70

90

99

Location A

Location B

Location C

00:00 04:00 08:00 12:00 16:00 20:00 00:00

H2S

in g

as p

hase [ppm

]

0

50

100

150

200