MIKE URBAN as a tool to model the

1D drainage system; Case study:

Kulmbach (Germany)

Study Project

At the Faculty of Civil, Geo and Environmental Engineering of the

Technical University of Munich

Supervised by MSc. Punit Kumar Bhola

Chair of Hydrology and River Basin Management

Submitted by Manish Basnet

Madelegabelstr. 62

81825 Munich

+49 17 626 543 689

Submitted on Munich, 30 March 2017

1

Declaration of Authorship

I, Manish Basnet, declare that this Study Project, titled "MIKE URBAN as a tool to model

the 1D drainage systems; case study: city Kulmbach (Germany)", and the work

presented in it are my own, except where otherwise acknowledged. This Study Project

was not previously presented to another examination board and has not been published.

Signed:

Date:

2

Abstract

The global trend of urbanization and climate change have led to unprecedented

increase in urban flood risk due to their adverse impacts on environment of urban areas

and precipitation extremes. Urban floods pose significant risk to people and enterprises,

and their asset, as they concentrate in cities and urban centres and become highly

dependent on infrastructure networks, utilities, communication systems and supply

chains for well-being. Thus there is a clear impetus to model flood risk in urban areas to

plan protection measures, emergency responses and evacuation.

The purpose of the study project is to understand the fundamental theories and methods

employed in urban flood modelling, to perform one dimensional hydraulic flood

modelling using MIKE URBAN and to assess critical parameters and factors influencing

the modelling process. The study reviews urban storm, flood events and urban runoff,

drainage infrastructure and urban drainage modelling. The key elements and criteria

required to perform urban hydraulic modelling are introduced and MIKE URBAN’s

example of one dimensional model coupled with two dimesnional hydrological model is

simulated. Following the general analysis, urban hydraulic model for city of Kulmbach

in Germany is developed and modelled and results are discussed. The results obtained

from modeling are important outcomes as they provide an overview of spatial extent and

depth of flooding and can be processed for further study and analysis.

3

Acknowledgement

This study project has been completed with considerable guidance and assistance from

many individuals.

I would like to express my gratitude to Punit Bhola from the Chair of Hydrology and River

Basin Management, Technical University of Munich, for introducing the fundamental

theories and aspects of flood modelling and for his contribution and advices as a

supervisor in the course of this study project.

This report has also benefited from the valuable lessons provided in the lecture “Flood

Risk and Flood Management” by Prof. Dr.-Ing. Markus Disse, Dr.-Ing. Olga Spackova

and Msc. Axel Kasparek held in 2015 at the Technical University of Munich.

4

Contents

1. Introduction......................................................................................................................... 4

1.1. Background ................................................................................................................ 4

1.2. Motivation ................................................................................................................... 4

1.3. Objective ..................................................................................................................... 4

2. Overview - Flood ............................................................................................................... 5

2.1. Need for Urban Drainage ......................................................................................... 7

2.2. Urban Drainage Terminology .................................................................................. 8

2.3. Types of Urban Drainage ......................................................................................... 8

3. Introduction to Flood Models ......................................................................................... 10

3.1. Brief overview of Urban Flood Modelling ............................................................. 11

3.2. 1D Hydraulic Modelling .......................................................................................... 13

3.2.1. Basic Terms ..................................................................................................... 13

3.2.2. Types of drainage flows ................................................................................. 14

3.2.3. Modelling flow in a Sewerage ........................................................................ 16

3.3. Surface Runoff Modelling ....................................................................................... 17

3.3.1. Deduction of initial and continuous losses .................................................. 17

3.3.2. Catchment Delineation in Hydrological Modelling ...................................... 18

3.3.3. Different Routing Techniques ........................................................................ 19

4. Selection of Modelling Tool............................................................................................ 21

4.1. MIKE URBAN ........................................................................................................... 23

4.2. MIKE URBAN 2D Overland Tutorial ..................................................................... 24

4.3. 1D Model Setup ....................................................................................................... 25

4.3.1. Nodes and Structures ..................................................................................... 25

4.3.2. Pipes and canals ............................................................................................. 25

4.3.3. Catchments ...................................................................................................... 26

4.4. 2D Overland Flow Model Setup ............................................................................ 26

4.4.1. 2D Overland coupling ..................................................................................... 28

4.5. Running the Simulation .......................................................................................... 28

4.6. Results and Discussion .......................................................................................... 28

5. Methodology..................................................................................................................... 30

5.1. Study Area ................................................................................................................ 30

5.2. Landuse classification ............................................................................................ 31

5.3. Runoff coefficient ..................................................................................................... 32

5.3.1. Determination of Runoff Coefficient ............................................................. 33

5

5.4. Imperviousness ....................................................................................................... 33

5.4.1. Determination of Imperviousness ................................................................. 34

5.5. Digitization of Manholes and Collection Networks ............................................. 35

5.6. Model Set Up ........................................................................................................... 37

5.6.1. Importing the manholes and pipelines layers ............................................. 37

5.6.2. Catchment Delineation ................................................................................... 38

5.6.3. Catchment Parameters .................................................................................. 40

5.6.4. Boundary Conditions ...................................................................................... 41

5.6.5. Set up and running the Simulation ............................................................... 42

5.6.6. 2D Overland coupling and simulation .......................................................... 43

5.7. Results and Discussion .............................................................................................. 44

5.7.1. 1D Simulation ....................................................................................................... 44

5.7.2. 2D Overland + Network Simulation .................................................................. 44

6. Conclusion and Outlook ................................................................................................. 46

7. Bibliography ..................................................................................................................... 48

1

Abbreviations

1D One Dimensional

2D Two Dimensional

AAL Annual Average Losses

CS Collection System

CSO Combined Sewer Overflow

DEM Digital Elevation Model

DHI Danish Hydraulic Institute

DTM Digital Terrain Model

EC European Commission

EIA Effective Impervious Area

ESRI GIS Environmental Systems Research Institute Geographic Information

Systems

FloodEvac Flood Evacuation

MU MIKE URBAN

PIMP Percent Impervious

RDI Rainfall Dependent Infiltration

SWMM Storm Water Management Model

TIA Total Impervious Area

UHM Unit Hydrograph Method

US EPA United Sates Environment Protection Agency

WD Water Distribution

WTP Wastewater Treatment Plant

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List of Figures

Figure 2.1 Effect of Urbanization on peak rate of runoff based on Butler and Davies, 2011…………………………………………………………..

6

Figure 2.2 Key features of urban hydrology and drainage based on Dawson et al., 2007……………………………………………………………...

7

Figure 2.3 Schematic diagram of Combined System (left) and Combined Sewer Overflow (right)………………………………………………...

9

Figure 2.4 Schematic Plan of Separate System………………………………... 9

Figure 2.5 Urban Water Phases based on Price and Vojinovic (2011)……… 10

Figure 3.1 Links between physical components of urban flood model………. 12

Figure 3.2 Profile of part-full pipe flow based on Butler and Davies (2011)…. 15

Figure 3.3 Illustration of Unit Hydrograph (based on Butler and Davies, 2011)…………………………………………………………………….

20

Figure 4.1 MIKE URBAN’s modular structure (DHI 2016b)…………………… 24

Figure 4.2 Screenshot of the Network and catchment boundary with DEM in the background………………………………………………………...

26

Figure 4.3 Screenshot of DEM and 2D overland settings in MIKE URBAN…. 27

Figure 4.4 Screenshot of the links selected for the profile plot……………….. 28

Figure 4.5 Screenshot of the horizontal profile plot of the links showing the surcharge……………………………………………………………….

29

Figure 4.6 Study area with flood extent in the network (left) and flood depth (right)……………………………………………………………………

30

Figure 5.1 Land-use classification of Kulmbach……………………………….. 32

Figure 5.2 Digitized manholes of Kulmbach city……………………………….. 36

Figure 5.3 Digitized pipelines of Kulmbach city………………………………… 36

Figure 5.4 Drainage network selected for study……………………………….. 37

Figure 5.5 MIKE URBAN’s Import/Export dialog box………………………….. 38

Figure 5.6 Manhole geometry in MIKE URBAN (DHI, 2016)…………………. 38

Figure 5.7 Catchment delineation based on polyline layer……………………. 39

Figure 5.8 Figure of drainage network with manholes and pipe links after catchment delineation…………………………………………………

40

Figure 5.9 Screenshot of imperviousness that was calculated and assigned to each sub-catchment………………………………………………..

41

Figure 5.10 Boundary condition – rainfall intensity as constant……………….. 42

Figure 5.11 Screenshot of the corresponding profile plot of the section selected in Figure 5.11………………………………………………..

44

Figure 5.12 DEM of Kulmbach and selected study area………………………... 45

Figure 5.13 Resulting flooding and flood extent in the study area……………... 46

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List of Tables

Table 4.1 Comparison of different features offered by SWMM and MIKE

URBAN……………………………………………………………………

22

Table 4.1 Default set of values of parameters for Nodes and Structures……. 25

Table 4.2 Default set of values of parameters for Pipes and Canals…………. 26

Table 4.3 Default set of values of parameters for 2D Overland Flow

simulation…………………………………………………………………

27

Table 5.1 Landuse classification of the study site………………………... 31

Table 5.2 Runoff Coefficient values based on GHKSAR 2000…………………. 33

Table 5.3 Degree of imperviousness for different land-use classes (Douglas

et al. 2007)……………………………………………………………….

35

Table 5.4 Landuse classification for the selected section of the network and

corresponding imperviousness, runoff and roughness

coefficients………………………………………………………………...

41

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1. Introduction

1.1. Background

In today’s rapidly urbanizing world, urban flood management constitutes a vital element

in integrated urban water management and water-induced disaster risk management.

Urban areas are adding 1.4 Million people per week (United Nations Department of

Social and Economic Affairs (UN DESA) 2014) and global Annual Average Losses

(AAL) from disasters in built environments are estimated at USD 314 Billion (United

Nations Office for Disaster Risk Reduction (UNISDR) 2015a). The pronounced effect of

changing climate and consequent adverse impacts of natural disasters, in particular

floods, are felt acutely in the cities and expanding urban sprawls. Therefore, it is critical

to understand factors and processes that govern cities’ and their infrastructures’

response to extreme rainfall events, identify shock and stress points and recognize the

extent of damage different flood scenarios can trigger in order to improve safety of

people and asset and build robust coping mechanism and resilience in case of a flood

event. Developing decision support systems and early warning systems based on such

studies and understandings will facilitate in better preparation and response to disasters.

In this regard, rainfall-runoff relationship and corresponding stress on storm-water

collection and management in cities is one of the significant processes in urban

hydrology and a major component of urban flood study and modelling.

1.2. Motivation

The catastrophic German flood of 2013 in Middle Europe and subsequent damages

have highlighted vulnerability to urban flooding and led to consensus for need to assess

flood risk and obtain reliable predictions of flood hazards in urban areas. Urban floods

are more likely to cause damages to public utilities, services, transportation and

infrastructure. In particular, emergency service providers face disruptions in delivery of

services due to increasing frequency of such disasters and difficulties in assessing risk

and managing appropriate response. This has given renewed impetus to map flood risks

and incorporate its assessment in urban land use, planning and emergency responses.

In case of a flood event, transport infrastructure in urban centers are lynchpin for both

rescuers and affected people escaping the flood. Hence, there is opportunity for better

understanding of urban flood risk, its assessment and management.

1.3. Objective

The main objective of the study project is to

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Understand the theories and processes involved in urban flood modelling

Perform 1D flood modelling in part of Kulmbach city in Germany using MIKE

URBAN as a flood modelling tool

The study undertaken aims to predict and map the potential stress areas in part of the

cities to assess risk in case of an extreme flood event within a broader framework of

disaster risk reduction. The findings from the study will contribute to the research project

“FloodEvac”, Chair of Hydrology and River Basin Management – Technical University

of Munich, whose objective is to enhance civil security in case of major inland flooding

through new and improved methodologies, technologies and devices in an international

perspective.

2. Overview - Flood

Floods are extreme natural event and can occur in a wider geographical scale like river

basin or in a smaller scale such as catchment and watershed (Ochoa-Rodriguez et al.

2015). These areas can be rural or urban and are called rural flooding or urban flooding

respectively. Rural flooding or river basin flooding is often caused by heavy rainfall

combined with snowmelt followed by flows exceeding the natural river/water courses.

Some other major causes of floods are:

Man-made or natural obstruction in the natural water course leading to

surcharge

Dam failures

Landslide and/or mudslide

Rapid snowmelt

Deforestation and human-induced land use changes in the river basins (Douglas

et al. 2007).

In contrast to rural flood, urban floods can have both area-wide and localized origin.

Impacts of urbanization could entail a substantial increase in frequency and magnitude

of flooding (Zhou 2014). As per Shaw (1994), the major effects of urbanization are (i)

large proportion of precipitation is converted into runoff, (ii) catchment response is

accelerated for specific rainfall this leading to steeper rising limb of flow hydrograph with

reduced lag time and time to peak, (iii) increased magnitude of peak flow, (iv) decline in

low or base flow due to less contribution from groundwater flow and less replenishment,

and (v) degraded water quality in the streams and rivers due to effluents discharge.

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Figure 2.1: Effect of Urbanization on peak rate of runoff based on Butler

and Davies, 2011

In case of inland cities faraway from shores, urban floods have become more severe

and occurs in the built-up areas as a result of heavy rain and subsequent rainfall runoff

(Paquier et al. 2015). They are further exacerbated by the high intensity rainfall in cities

combined with inappropriate sewer system and diverse land cover (Salvan et al. 2016).

In general, urban floods occur because of high stages and overflows in the major

neighboring rivers due to meteorological disturbances or high intensity thunderstorm

and cloudbursts in and around surrounding urban areas. Inland flooding occur mainly

as a result of

Intensive precipitation and pluvial runoff that causes stormwater surcharges

and surface flows

Fluvial flooding caused by high river flows

Flash floods caused by streams and rivers due to heavy rainfall or thunderstorm

or cloudburst occurring over the parts of urban area or in surrounding

mountainous/steep catchments

Groundwater floods due to groundwater table rising

Also, small-scale urban flooding in cities that employ sewers to transport both storm

water and wastewater drainage is often caused by the sewer overflow due to

inappropriate sewer design or inadequate carrying capacities of sewers (Adeogun et al,

2015).

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Figure 2.2: Key features of urban hydrology and drainage based on Dawson et al.,

2007

However, urban flood modelling represents a challenge as urban flooding occurs due to

interaction of natural and engineered processes (Dawson et al. 2008). Due to extensive

paving and built up area in cities, infiltration is lower compared to natural catchments

leading to excess surface flows or peak flows and decreasing the response time of the

runoff. This excess surface flows or peak flows has to be collected and removed.

Collection system, either open or closed, transport and drain stormwater and/or waste

water from urban areas to water treatment facility and into an appropriate nearest

streams or rivers.

Urban rainfall-runoff models are employed to understand the governing processes of

urban hydrology and predict the flood risk hazard and are now indispensable tools in

urban water management. Urban flood represents a huge challenge due to the

complexity involving an array of political, social, economic, institutional and technical

factors within both urban and rural environments (World Bank 2015). A holistic

knowledge of physical characteristics of both urban environments and surrounding

periphery and understanding of urban hydro-meteorological issues are paramount for

urban flood management. In Europe, European Flood Directives has underlined the

importance of urban flood risk mapping (2007/60/EC) (CEC, 2007).

2.1. Need for Urban Drainage

Urban areas are more susceptible to frequent flooding than rural regions (Zhou 2014).

It is necessary to properly dispose rainwater and subsequent runoff to protect lives and

properties from flooding. Hence, urban drainage systems are employed to collect

precipitation and resulting runoff (Loucks et al. 2005). Stormwater drainage system

dates back several millennia BC (Burian, Edwards 2002). The primary function of

stormwater drainage is to move surface runoff away from urbanized zones as fast as

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possible (Delleur 2003). According to Butler and Davies (2011), consumption and use

of water requires water abstraction and need to provide it for daily human uses. Thus,

there are two types of water that needs to be drained from urban areas; the first is

stormwater i.e. precipitation in the built-up area and the second is wastewater resulting

from the human consumption to maintain living standard. Management of both types of

water is crucial to avoid damage, inconvenience, property and life threats. Urban

drainage deals with both sets of water types to negate the negative implications on

human life and nature.

2.2. Urban Drainage Terminology

Urban drainages have developed from simple ditches to complex system that consists

of curbs, gutters, surface and underground conduits. Urban drainage tends to be more

complex compared to rural ones (Zoppou 2001) and it is important to know basic

hydrologic and hydraulic terminology and processes that take place.

In urban drainage network system, all the inlet points or collection points such as

manholes or gullies are linked together to a discharge point or an outfall. The inter-

linkages of the pipes are carried out through series of pipe networks and can be

differentiated based on the location in the network. ‘Drains’ carry flow from individual

properties while ‘Sewer’ transport water from larger areas.

Flow in a drainage network occur from the random precipitation and runoff generated

over space and time. Flow occur periodically and are hydraulically unsteady (Butler,

Davies 2011). ‘Surcharge’, pressure flow and even flooding may occur if the rainfall

runoff exceeds the drainage system capacity. Surcharge means that a closed pipe or

conduit which behaves as an open channel may run full and starts acting as a pipe

under pressure (Chen et al. 2005).

2.3. Types of Urban Drainage

Urban drainage systems needs to transport two types of water: stormwater and

wastewater. According to Butler and Davies (2011) the most common types of drainage

systems are combined, separate, hybrid sewer networks and the dual system.

In Europe, combined sewer system is most widely used drainage system. For instance,

around 70% of the sewer system in Germany are combined sewer systems (Butler,

Davies 2011). Both stormwater and wastewater are transported in a single conduit pipe

in combined sewerage collection system. Combined sewers are characterized by two

important elements combined sewer overflow (CSOs) and storage through which the

9

transported water runs through before it is drained into water treatment plant (WTP).

The main reason for this is: during dry season, the system carries only waste water but

during heavy rainfall, the flow increases significantly. It is not cost-effective to provide

drainage capacity for such large volume of runoff, the excess water is diverted out of

the drainage into a natural watercourse. Thus, CSOs are installed to divert excess

stormwater and wastewater to water course (spill flow) with suitable quantity transported

to WTP (continuation flow). When storage is available, some amount of flow is retained

before it is discharged.

Figure 2.3: Schematic diagram of Combined System (left) and Combined Sewer Overflow (right)

The second type of sewerage system is separate system in which the stormwater and

wastewater are transported separately in two conduits usually laid parallel. One relative

advantage of separate sewerage system over combined system is that the stormwater

is not mixed with wastewater and thus can be directly transported and discharged into

a water course (Zhou 2014). Similarly, the wastewater conduits directly drain

wastewater to WTP. In most cases the size of the stormwater pipe is same as that of

combined sewerage pipe while the size of the wastewater pipe is smaller. One potential

drawback of this system is that wrong connections and cross-connection may lead to

infiltration and mixing of both flows (Butler, Davies 2011).

Figure 2.4: Schematic Plan of Separate System

10

Meanwhile, many cities in developing countries are often characterized by poor water

distribution networks and open waste water/sewage and storm-water collection which

pose grave health risk. These factors poses added complexity during urban flood

modelling as relevant data are often not readily available and in many cases do not

exist. Also, the collection system including sewage, series of drainage pipes and its

networks, manholes and drainage structures needs to be integrated in the model.

Figure 2.5: Urban Water Phases based on Price and Vojinovic (2011)

3. Introduction to Flood Models

In case of flood modelling, mathematical approaches are necessary to create different

rainfall and flow scenarios and understand consequential impact in areas of interest.

Simulations are tools that help to design and operate large-scale systems of flood

control. A simulation model can be defined as “...a set of equations and algorithms that

describe the real system and imitate the behavior of the system…” (Viessman et al.

1989). In context of flood modelling, simulation refers to mathematical description of a

system response to a storm event. These modelling tools consist of algebraic equations

with known variables (parameters) and unknown variables (decision variables) (Loucks

et al. 2005).

Viessmann and Lewis (1989) have defined models as mathematical representation of

real world phenomena. Many system behavior and real world processes may be

misrepresented in a model. Even verified models have limitations which needs to be

taken into account. However, simulations of hydrologic processes have many

advantages. When dealing with complex water flows that involves different interacting

11

components and feedback loops, simulation can be a plausible tool (Price, Vojinovic

2012). Different design parameters and alternatives can easily be tested and compared.

Particularly, stochastic models are suitable tool as they allow representation of

uncertainty in their output.

3.1. Brief overview of Urban Flood Modelling

Urban hydrological models are primarily employed (i) to evaluate effect of urbanization

on natural water system and to build the knowledge of this complex system; (ii) to

compensate for the lack of reliable data as measurements in urban environment is more

challenging than natural environment; (ii) to make future predictions with respect to flood

forecasting, landuse changes, climate change impacts and ecosystem protection (Elga

et al. 2015). Similarly, urban drainage models have two main applications: design of

new sewers and analysis of existing ones. When analyzing existing sewers, the physical

characteristics of the system have already been defined and the objective is to

investigate how the system behaves under certain conditions regarding the flow, water

depth and flooding. Urban flow models must be able to depict the rapid changing

behavior of urban catchments as they have short response to storm and rainfall events.

The main physical processes such as hydrologic inputs (rainfall, runoff, sewer flow) and

required information (flow, depth, pressure) need to be represented.

Many of the urban stormwater models includes all the pertinent phenomena and

physical processes and interaction between different elements in physical

runoff/drainage system. These models consists of two basic components: first, rainfall

runoff modelling which deals with surface runoff and second, transport modelling that

includes flow of water through various stormwater collection infrastructure (Zoppou

2001). Rainfall runoff modelling is also called 2D overland rainfall-runoff modelling and

involves overland flow routing and surface runoff. Similarly, transport modelling is also

termed as 1D hydraulic modelling and includes gutter flow routing, pipe flow routing and

surface flooding. Hydraulic model is further divided into street flow model and pipe flow

model.

In the first step, a design storm/rainfall preferably a rainfall intensity over time is

determined. The design rainfall can be constant rainfall or rainfall intensity and duration

profile. The latter is usually created with a certain return period by using Intensity-

Duration-Frequency relationships. Second, the losses needs to be taken into account

and should be deducted from the design storm/rainfall. However, deduction of losses

from the rainfall is a complex progress. These losses must be considered only if they

affect the simulation (Mark et al. 2004). Third, the remaining runoff after deducting the

12

losses, also called overland flow or initial flow of runoff, is routed to gutter using overland

flow equations. The surface has impacts on the flow and hence these impacts and

influences should be factored in during the simulation. Flow routing procedures involve

complex physical processes. Routing can be differentiated into two types: hydrologic

and hydraulic routing. In hydrologic routing, flow is estimated as function of time based

on upstream flows and storage attenuation while in hydraulic routing, flow is estimated

as function of time and space throughout the system (Government of the Hong Kong

Special Administrative Region (GHKSAR) 2013). At the end of the above process,

rainfall hyetograph results into surface runoff hydrograph which is the output of 2D

hydrologic modelling. This hydrograph is usually available for each sub-catchment and

is used as input for 1D hydraulic models.

Figure 3.1: Links between physical components of urban flood model

1D hydraulic model deals with the gutter flow that needs to be routed to sewer inlet

points and sewer/pipe flow routing. Many flood modelling software portray sewer pipes

as ‘links’ and sewer inlet points or manholes as ‘nodes’. Sewer pipes hold important

hydraulic properties such as diameter, roughness, gradient, depth and flow rate while

manholes also hold important information on head losses and level changes. 1D

hydraulic model’s output is an outflow hydrograph. If the capacity of sewerage system

is exceeded, surface flooding should also be included in the output (Butler, Davies

2011). Both the surface inundation simulation and surcharge in the pipe system should

be modelled and represented. In order to carry out these processes, the model has to

able to perform 1D-2D and 2D-1D interactions (Viessman et al. 1989).

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3.2. 1D Hydraulic Modelling

3.2.1. Basic Terms

The basic condition behind modelling the sewerage flow is the continuity of flow. It

means that in a conduit with a constant diameter and no cross-sections, the mass of

liquid that flows into the conduit at point must be equal to mass of the fluid discharging

from the conduit at another point (Price, Vojinovic 2012). Thus, based on the assumption

that the density stays same, volume of liquid entering must be same as the volume

flowing out.

The second condition is continuity of flow rate that builds on the fundamental condition

of continuity of flow. The flow rate (in m3/s) Q1 at inlet point must be equal to flow rate

Q2 at outlet point. However, when one observes the velocity of liquid in the pipe, it differs

across the flow cross-section. The maximum velocity can be detected at the center of

the pipe (Butler, Davies 2011). The mean velocity is defined as the flow-rate per unit

area.

𝑣 = 𝑄/𝐴

Roughness (ks) and shape of the pipes are important parameters that affect the flow in

a sewage system. Roughness values vary depending on the type of materials pipes are

made of. Pipe’s shapes vary depending on the region and countries. Some of the most

common shapes are circular, egg-shaped, horse-shoe and U-shaped form.

Pipes are exposed to water pressure depending on type of conduit and amount of water

flowing through it. Pressure are further differentiated as absolute pressure or gauge

pressure in hydraulics. Absolute pressure refers to pressure relative to vacuum and

gauge pressure refers to pressure relative to atmospheric pressure. In hydraulic

equations and calculations, gauge pressure is widely used (Butler, Davies 2011).

Pressure in liquid is directly proportional to the depth

∆𝑝 = 𝜌𝑔∆𝑦

Increase in pressure ∆𝑝 (N/m2) depends on the product of the liquid’s density 𝜌 (kg/m3),

the gravitational acceleration g (9.81 m/s2) and the change in depth ∆𝑦 (m). Loucks et

al (2005) said that to express the energy level of a flowing liquid in a network, three

components are important:

Pressure

Velocity

14

Potential

These three components are usually represented by energy head, energy per unit head.

The energy head is the sum of pressure head, velocity head and the potential head

(elevation above certain base level). The energy level of a flow constantly changes. It

may increase for instance through pumps or decrease for instance through friction

losses.

𝑝𝑟𝑒𝑠𝑠𝑢𝑟𝑒 ℎ𝑒𝑎𝑑 𝑝

𝜌𝑔 𝑣𝑒𝑙𝑜𝑐𝑖𝑡𝑦 ℎ𝑒𝑎𝑑

𝑣2

2𝑔 𝑝𝑜𝑡𝑒𝑛𝑡𝑖𝑎𝑙 ℎ𝑒𝑎𝑑 𝑧

3.2.2. Types of drainage flows

In hydraulic modelling, there are mainly two types of flow, open-channel flow and flow

under pressure. There is a hybrid flow which is a combination of both types and called

as part-full pipe flow. According to Butler and Davies (2011), this is the most common

type of flow and each type of slow have specific characteristics that need to considered

while modelling.

For a flow to be considered under pressure, the liquid flowing in the pipe must fill the

whole cross-section of the pipe and cover the whole length of the conduit. In such cases

the flow is also considered to be surcharged (Vojinovic, Tutulic 2009). For instance, the

flow in a pipe may be surcharged when flood volume exceeds the pipe design capacity.

As more of excess water enters the sewer system, the capacity of the conduit remains

same and cannot be enlarged by increasing the depth of the flow. The capacity of a

conduit depends on the diameter, roughness and hydraulic gradient and thus the only

way to increase the capacity of the conduit is by raising the hydraulic gradient. Hence,

when the hydraulic gradient raises above the ground level, manhole overflows and

surface flooding occur.

For an open-channel flow, the liquid flows by gravity forces with free surface at

atmospheric pressure. The cross-section of the flow changes with in conjunction with

the flow. The velocity of open channel flow is estimated by using Manning’s equation.

Open channel flow is further divided into:

Uniform flow, and

Non-uniform flow

In uniform flow, flow consists of normal flow depth which means the energy line,

hydraulic grade line and channel bed are all parallel to each other (Butler, Davies 2011).

15

This is rarely the case as changes in pipe diameter, roughness of the pipe and the slope

of the pipe stops energy lines from being parallel.

Part-full pipe flow is a combination of open-channel flow and flow under pressure. The

flow can occupy the whole cross-section of the pipe if volume and flow-rate is higher

than designed capacity of the pipe. Similarly, when the flow is considerably lower than

the designed capacity, the liquid flows as in open-channel flow.

Figure 3.2: Profile of part-full pipe flow based on Butler and Davies (2011)

Flow in the sewerage can also be classified as steady/unsteady and uniform/non-

uniform flow. Steady flow refers to constant flow with time and uniform flow means

constant flow with distance. Respectively, unsteady flow is not constant with time and

non-uniform flow is not constant with distance. Flow in sewerage is usually unsteady

(Government of the Hong Kong Special Administrative Region (GHKSAR) 2013). Based

on steady/unsteady and uniform/non-uniform flow, following conditions exist;

Steady and uniform

Steady and non-uniform

Unsteady and uniform

Unsteady and non-uniform

Further, the flow can be distinguished into laminar and turbulent flow. The viscosity of

liquid due to interaction of fluid molecules generates friction forces between different

layers of fluids flowing at different speeds. Usually during high velocity, the erratic motion

between the fluids is higher leading to turbulent flow. Whilst, lower velocity leads to

laminar flow.

16

3.2.3. Modelling flow in a Sewerage

Flow in a sewerage is usually unsteady and tends to be non-uniform due to frictions,

head losses in the pipe and is usually represented by unsteady non-uniform flow. There

are many methods to analyze and simulate the flow behavior in a sewerage. One of the

common theoretical method to model gradually varied unsteady flow in open channel or

part-full pipes is through Saint-Venant equations.

The St-Venant equations consists of dynamic and continuity equations and can be used

to represent water depth (y), discharge (Q) and mean velocity (v) (Vojinovic, Tutulic

2009). The equation can be expressed as follows (Equation 1)

(1)

(2)

Equation (1) is referred to as the mass conservation equation, and Equation (2) is the

momentum conservation equation (Danish Hydraulic Institute (DHI) 2016b). In this,

Q is the flow discharge or flow-rate in m3/s (Q = v*A where v is the cross-sectional

averaged velocity and A in the cross-section surface area),

A is the cross-sectional area of the flow in m2

g is the acceleration of gravity in m2/s,

y is the cross-sectional averaged water depth in m,

S0 is the bed slope in the longitudinal direction,

Sf is the friction slope (the slope of the energy line) and

t is time in s

Here the momentum equation is expressed in conservative form. It is possible to

substitute vA for Q in Equations (1) and (2), expand Equation (2) and simplify it using

Equation (1) to yield the mathematically correct non-conservative form of the momentum

equation.

𝜕𝑄

𝜕𝑥+

𝜕𝐴

𝜕𝑡= 0

𝜕𝑄

𝜕𝑡 +

𝜕

𝜕𝑥(

𝑄2

𝐴) + 𝑔𝐴

𝜕𝑦

𝜕𝑥 − 𝑔𝐴(𝑆0 − 𝑆𝑓) = 0

Local

acceleration

term

Convective

acceleration

term

Pressure

force

term

Gravity

force

term

Friction

force

term

17

3.3. Surface Runoff Modelling

Hydrological modelling is used to transform rainfall runoff hyetograph into surface runoff

hydrograph. Hydrological models can be categorized into two classes: surface runoff

models and continuous hydrological models. Surface runoff model deals with runoff that

take place on the surface while the latter deals with both surface and sub-surface runoff

(Danish Hydraulic Institute (DHI) 2016e). Loucks et al., (2005) said that surface runoff

models are widely employed to investigate urban rainfall runoff analysis.

Surface runoff models should incorporate two main subjects while computing surface

runoff due to excess rainfall; mainly, the deduction of initial and continuous losses and

the surface flow routing. Flow routing deals with converting the effective precipitation

into overland flow and its passing to enter the drainage network. This can be done

through various methods that usually employ catchment data, model-specific catchment

data and model-specific parameters (Danish Hydraulic Institute (DHI) 2016e).

3.3.1. Deduction of initial and continuous losses

Loucks et al. (2005) stated that majority of the models accounts for initial losses due to

surface wetting and filling of depression storage. Depression storage can be described

as:

𝑑 = 𝑘1

√𝑠

In above equation, k1 represents the perviousness coefficients of the surface and s

represents the ground slope. It can be deduced that depression storage is high for

pervious areas and ground with smaller slope. Regarding interception loss in urban

environments and during strong storm events, it occurs in negligible quantity and small

magnitude and hence is omitted or added to depression storage. However, initial losses

should not be neglected when less severe events and in more pervious environments

(Butler, Davies 2011). In modelling process, initial losses are usually deducted in the

beginning of rainfall event to come up with net rainfall (Danish Hydraulic Institute (DHI)

2016a).

Continuous losses play significant role especially in urban catchments. But

evapotranspiration resulting from short duration rainfall events is negligible and in many

cases is omitted or included in initial losses. Loucks et al., 2005 have deduced that in

case of heavy rainfall events (greater than 25mm depth), rain falling on a hot surface

(above 60oC), the maximum loss of 1 mm may occur. In case of infiltration, the loss rate

18

is usually high during the initial moments and lowers to a final steady rate after the upper

soil is saturated. Horton’s equation is used to represent the infiltration:

𝑓𝑡 = 𝑓𝑐 + (𝑓𝑜 + 𝑓𝑐) 𝑒−𝑘2𝑡

Where,

ft is infiltration rate at time t (in mm/h)

fc is final infiltration rate (in mm/h)

fo is initial rate (in mm/h)

k2 is decay constant (in h-1)

These parameters are dependent on soil/surface type and initial moisture content in the

soil.

3.3.2. Catchment Delineation in Hydrological Modelling

While modelling the surface runoff, boundaries of the whole catchment including each

sub-catchment within it needs to be defined. This is done in such a way that the

precipitation falling on the ground is directed to certain inlet point (drainage point) by

gravity. Hence, both topography and drainage network play significant role in manually

determining the catchments. However, Mark et al. (2004) points that it is comparatively

difficult to delineate boundary in plain areas where boundaries are blurry. There are

methods to automatically delineate the catchment boundaries. The three methods

commonly employed are

Distance based method: Areas are allocated based on the distance from the

drainage point

DEM based method: Use of algorithms to calculate the most likely flow path

depending on the terrain and ground slope

DEM based with digital image method: Similar to DEM based method but with

addition of digital image and information on land-use

Another important parameters that needs to be accounted for are type of land-use

accompanied by imperviousness (Elga et al. 2015). This affects the losses and hence

the runoff to the drainage point. After catchment delineation, the total area and type of

surfaces that drain into the drainage point/network needs to be identified. Impervious

surface can be quantified by using percent impervious. It can be derived manually

through the aerial maps and images or can be calculated by using density of housing in

a specific area.

19

Runoff coefficient is one of the parameters that is significant in surface runoff modelling.

It represents the amount of rainfall that adds to the surface runoff generated. It is

dimensionless parameter and its values depend on the surface terrain, slope,

imperviousness and other retention properties of the surface. Manuals developed by

GHKSAR 2005, shows that soil characteristics and conditions, vegetation and land-use

cover and rainfall intensity have considerable influence on runoff coefficient.

The expression – time of concentration (tc), describes the time taken by the surface

runoff to flow from the farthest point in the catchment to the point under consideration

i.e. drainage point. Hence, each location in a catchment has a different time of

concentration with respect to the reference point. Further, Butler and Davies 2011

differentiate two components of tc: the overland flow time or also called time of entry te,

and sewer flow time known as time of flow tf.

3.3.3. Different Routing Techniques

According to Butler and Davies (2011), there are mainly two types of overland flow

routing techniques that are mostly applied: unit hydrograph method and kinematic wave

model. The former belongs to linear reservoir models while latter is part of non-reservoir

models.

The unit hydrograph method is based on relation between net rainfall and direct runoff.

It is based on the assumption that net rainfall fall over certain area produces unique and

time-invariant hydrograph (Neal et al.). It describes the outflow hydrograph resulting

from the unit depth of rainfall falling equally over the catchment area. This occurs for

constant rainfall rate i and for certain duration D and hence the system is considered to

be linear and time-invariant. The duration D is usually for one hour. Thus, unit

hydrograph can be used as a base to develop a hydrograph response to any rainfall

event.

20

Figure 3.3: Illustration of Unit Hydrograph (based on Butler

and Davies, 2011)

The y-axis of the unit hydrograph represents effective rain volume, u(D,t), at any given

time t. In GHKSAR (2000), it is stated that direct runoff caused by a net rainfall of certain

duration can be derived by the liner superposition of the responses of different rainfall

depths. This derivation is also known as convolution and can be expressed as:

𝑄(𝑡) = ∑ =

𝑁

𝑤=1

𝑢 (𝐷, 𝑗)𝐼𝑤

In above equation, Q(t) represents runoff hydrograph ordinate at time t (in m3/s), the

term u(D,j) represents the D-h unit hydrograph ordinate at time j (in m3/s). Iw is rainfall

depth in in wth of N blocks of the duration D (in m). Use of unit hydrograph method

requires use of unit hydrograph and a loss model. For a loss model, unit hydrograph

method assumes that it can be described as fixed initial and constant loss (by ø-index)

or constant proportional loss (by runoff coefficient) or fixed initial and continuous loss

(by the SCS curve). Similarly, unit hydrograph for a catchment can be derived by

observing rainfall and consequent runoff. However, for catchments with no gauges or

measurements it can be predicted based on catchments with similar characteristics.

Butler and Davies (2011) proposes three methods to do this:

Synthetic unit hydrography

Reservoir models, and

Time area method

21

4. Selection of Modelling Tool

There are many rainfall – runoff modelling packages, available both commercially and

non-commercially, to simulate urban flooding. MIKE URBAN (MU) by Danish Hydraulic

Institute (DHI) is selected to perform 1D flood model in the present study. MU is GIS

based software system which performs numeric modelling (1D) and provides platform

for analysis of urban storm water collection and drainage, and waste water systems for

both combined and separate sewer collection system. Further, it also performs 2D

overland flow modelling for urban drainage network.

US EPA’s Storm Water Management Model (SWMM) is similar modelling tool

comparable to MIKE URBAN. It is an open source and free ware and one of the most

widely used hydrological and hydraulic modelling tool for planning, analysis and design

of stormwater runoff (Rossman, Huber 2016). Being a freeware, it allows the

users/modelers to go through the codes and understand how the simulation process is

taking place. However, Rossman (2016) states that SWMM allows for only 1D modelling

in terms of urban rainfall runoff modelling. This provides a clear limitations in simulating

and visualizing the flood depth and flood extent. In this regard, MU has an advantage

as it allows for 1D-2D coupling to simulate urban flooding allowing to visualize both flood

inundation and flood extent (Danish Hydraulic Institute (DHI) 2016c).

As per DHI (2016a), MIKE URBAN uses SWMM engine and hence it is equipped with

all the functionalities that SWMM brings. Further, it has linkages with ArcGIS and GIS

files can easily be integrated into the model. Comparatively, SWMM has no linkages

with GIS and the user/modeler has to build in-house GIS linkages or rely on propriety

Graphical User Interface (GUI). Lockie (HAL) has presented the findings that simulation

speed of SWMM hydraulic engine is slightly slower than other common hydraulic

engines. Further, DHI provides formal support to the users using MU. In contrast, no

support is offered by US EPA for SWMM users. MU provides advanced user interface

and has more in built data management capabilities which provides more stability to the

users (Lockie).

The main disadvantage of MIKE URBAN is that it is a commercial software package and

is limited to relatively smaller users group due to purchase expenses compared to

SWMM. Also, users cannot make changes to the MU software codes and to certain

simulation processes as desired. In comparison, SWMM is freely available worldwide

and is an open source software. This provides the platform to modelers and users

community to contribute to the software’s development by continuously debugging and

improving it. It also offers independent developers to release tailored SWMM models to

22

consultants and researchers thus avoiding the need to purchase expensive packages.

An additional features can also be incorporated by the modeler as per need and

requirement (Rossman, Huber 2016). Many alternative packages including MIKE

URBAN utilizes SWMM hydraulic model as their basis which is testament to SWMM’s

robust hydraulic performances. Bisht et al. (2007) have stated that the hydraulic engine

of SWMM has been proven and tested since 1970’s and is one of the most widely storm

water runoff modelling tool. This directly translates to wider publications of researches

articles and journals that aids user/modeler using SWMM for their researches.

Table 4.1: Comparison of different features offered by SWMM and MIKE URBAN

Topic Item SWMM MIKE URBAN

Basic Features

Cost SWMM is open source and freely available, No support provided by the

developer

MIKE URBAN is a commercial software

package and is costly; Support is provided by the

developer

User display and

interface

Basic user interface Comparatively better user interface

Result Display

Allows decent display of results

Better display of results with options to view and analyze in other MIKE

products

ArcGIS SWMM has no linkages with ArcGIS and user has

to build in-house GIS linkage.

Linkages with ArcGIS and GIS files can easily be

integrated.

User Community

SWMM has been proven and tested since 1970’s and is one of the most

widely used storm water runoff modelling tool.

Mu is limited to small number of user groups. MU users cannot make

changes to software codes and simulation processes as desired.

Modelling

Urban Rainfall Runoff

Modelling

SWMM only allows 1D modelling in terms of urban rainfall runoff

modelling.

MU allows 1D-2D coupling to simulate urban

flooding and both flood inundation and extent can

be visualized.

Surface Runoff

SWMM employs non-linear reservoir model to

simulate the runoff.

MU has options for four different runoff models to simulate the runoff. They are Time Area Method,

Kinematic Wave method, Linear Reservoir and Unit

Hydrograph Method.

Infiltration SWMM provides three methods to calculate

infiltration: Curve Number, Horton’s equation and

Green Ampt.

MU employs Rainfall Dependent

Infiltration/Inflow (RDII), Horton and Soil

Conservation Services (SCS) methods.

23

4.1. MIKE URBAN

Model manager is the foundation of MIKE URBAN and it oversees the input of data,

visualization of data, simulations and analysis of results and simulations. SWMM5 is a

part of the model manager and allows hydrodynamic computation of stormwater

drainage network. Similarly, there are different modules built on the model manager. CS

(Collection System) and WD (Water Distribution) modules are two important modules

that deals with urban sewerage network and water supply respectively. For urban flood

modelling, CS-Rainfall-Runoff, CS-Pipeflow, CS-Control and 2D-Overland flow modules

within a broad framework of CS modules play prominent roles (Figure 10).

CS-Rainfall-Runoff module uses MOUSE engine from DHI. Precipitation plays key role

in this module. Different hydrological methods such as time area method, kinetic wave

method and unit hydrograph method (UHM) are included in the module. Further, these

hydrological methods are given within a defined catchment area. A catchment in MIKE

URBAN is defined as geographical boundary which represent hydrological urban

catchment or wastewater drainage area. The module also includes additional flows and

rainfall dependent infiltration.

CS-Pipeflow includes automatic assessment of sewer system. It deals with

hydrodynamic computation of the surcharge. It also allows simulation of specific event

and long term series-simulations. With CS-Control module, control structures such as

pumps and weirs can be regulated and modified in a sewer system. These structures

can also be changed or intervened during simulation phase. 2D-Overland flow module

is an important module to perform urban flood simulation.

24

Figure 4.1: MIKE URBAN’s modular structure (DHI 2016b)

4.2. MIKE URBAN 2D Overland Tutorial

MIKE URBAN 2D Overland Tutorial by DHI was run in order to understand the practical

aspect of MU modelling. Generally, MU MOUSE requires three sets of data to compute

the simulation: catchment parameters, network and boundary data (Bisht et al. 2016).

Network data consists of nodes and links. Nodal data can be configured as nodes,

basins or outlets as specified in the urban drainage network that is to be modelled. Nodal

data contain the information regarding ground elevations, invert level, dimensions and

spatial locations. These nodes are connected by links. The main inputs of links data are

their elevations, dimensions, hydraulic properties and roughness parameters (Danish

Hydraulic Institute (DHI) 2016b). Catchment parameters include input of catchment area

which are assumed to freely drain into collection points. A catchment is discretized into

number of sub-catchments and defining the hydraulic network through nodes, links and

outlets. Also impervious percent is another important parameter that governs the

amount of rainfall in sub-catchment draining into the nodes. DHI (2016) in their user

manual have said that there are three types of boundary conditions in MU MOUSE

available, catchment loads, network load and external water levels.

The data provided in the tutorial includes complete 1D model network with manholes,

pipes and one outlet. Similarly, Digital Elevation Model (DEM) of the area to be modelled

is provided and it has a high resolution of 2 meters. All the manholes in the 1D Network

Mike Urban Model Manager

Network data management

SWMM for storm water sewer modelling

CS - Rainfall-Runoff

Includes TA, Kinematic wave, linear reservoir, UHM and RDI

CS Pipe flow

MOUSE Engine

CS Control

regulation of control structures such as weirs, pupms, valves

2D overland flow simulation

MIKE FLOOD simulation combining 1D pipeflow and 2D Overland flow

25

are defined as nodes except for one which is defined as the outlet. As a boundary

condition, a rainfall time series is included.

4.3. 1D Model Setup

4.3.1. Nodes and Structures

The first step in setting up the model is defining the 1D Network data. The network data

given in the tutorial is setup and all the network components are created. Some of the

basic information for nodes and structures such as geometry, location, node type are

defined. Besides these general parameters, there are other factors which are crucial

when coupling with the 2D overland flow simulation. The user has to define “Max flow”,

“Inlet Area” and “Qdh factor” and the equation to setup flow exchange between 1D-2D

model (Danish Hydraulic Institute (DHI) 2016d).

“Max Flow” is used to define the upper limit of the discharge which is able to flow through

the component. “Inlet area” defines the flow exchange between 1D model structures

and 2D overland model. Physically “Inlet area” is equivalent to manhole area (Bisht et

al. 2016). “Qdh factor” indicates the water level at which discharge should be oppressed

(DHI, 2016). To define the exchange flow between 1D network and 2D overland, MU

offers three different methods or equations: i) Orifice equation, ii) Weir equation and ii)

Exponential function.

For the tutorial, the default values are assigned for max flow, inlet area and Qdh factor.

Table 4.2: Default set of values of parameters for Nodes and Structures

Parameters Values

Max flow 0.10

Inlet Area 0.16

Qdh factor 0.0

Exchange flow equation Orifice equation with coefficient 0.98

4.3.2. Pipes and canals

The type, cross-section and materials of the links play important role in pipe flow runoff.

The cross-section of the pipes are set to circular and the materials are set to concrete

as default. Similarly following values are added as given in Table 4.2. Equivalent

roughness in also known as Colebrook White coefficient which is given by surface

roughness of the pipe divided by its hydraulic radius.

26

Table 4.3: Default set of values of parameters for Pipes and Canals

Parameters Values

Manning 75

Equivalent roughness 0.00015

H-W coefficient 120

Diameter 0.15-2 m

4.3.3. Catchments

The catchment can be created as a polygon and manually delineated in MIKE URBAN.

Also, catchment can be delineated automatically using the catchment delineation

function provided in MU (Danish Hydraulic Institute (DHI) 2016c). The nodes should be

connected to each catchment so that the computed runoff from each catchment is

collected in the corresponding collection points or nodes.

Figure 4.2: Screenshot of the Network and catchment boundary

with DEM in the background

4.4. 2D Overland Flow Model Setup

DEM file provided in the tutorial file is added to the model setup. MIKE URBAN accepts

ESRI Grid format or DFS2 format files for DEM (Danish Hydraulic Institute (DHI) 2016c).

27

After DEM is implemented 2D overland setting and parameters are set through 2D

overland settings and tools provided in MU. These setting allows user to define the

modelling parameters and the extent of the model area (Figure 12). The parameters are

set as default and are listed in Table 3.

Table 4.4: Default set of values of parameters for 2D Overland Flow simulation

Parameters Values

2D Model Mike 21 Single grid using rectangular cell solver

Drying depth 0.002

Flooding depth 0.003

Bedding Resistance Manning Number: 32

Eddy Viscosity Default value = 0.02*dx*dy/dt

Land value Highest land value + 10

Figure 4.3: Screenshot of DEM and 2D overland settings in MIKE

URBAN

28

4.4.1. 2D Overland coupling

After completing 1D and 2D model setup, both models are coupled. It is necessary to

couple the pipe flow components with the overland flow model. Pipe flow components

include manholes (nodes), basins, outlets, weirs and pumps. The coupling is done with

the specific 2D overland cells which is selected automatically after user defines it. MIKE

URBAN gives user two default coupling options: cells with certain width and height that

are nearest to the nodes are selected or defining the radius from the nodes so that all

the cells within given radius are selected.

4.5. Running the Simulation

The model simulation is defined as “Network + 2D overland” in the simulation toolbar.

Also, the simulation time steps and output files are specified. For this tutorial, Unit

Hydrograph Method (UHM) (model D) is set as the hydrological model for simulation.

4.6. Results and Discussion

The results of 1D network and 2D overland simulation helps in understanding the extent

of flow in pipe components and its interactions with overland through manholes and

outlets. Figure 13 shows that pipes in lower parts become flooded and overfilled. These

manholes discharge the excess water to overland through the pipes, also known as

surcharge.

Figure 4.4: Screenshot of the links selected for the profile plot

29

Figure 4.5: screenshot of the horizontal profile plot of the links showing the

surcharge

It can be deduced that overland is flooded equally in the lower parts. From the rainfall

time series, rainfall peaks at around 1 pm but the maximum flood peaks at around 1 pm

in the lower area. It is identifiable that the flood in the upper area quickly diminishes

when compared with the flood in the lower areas of the DEM. In lower parts, flood keep

increasing and peaks at 1 pm. The extent and depth of flood in the area is visualized in

Figure 15.

30

Figure 4.6: Study area with flood extent in the network (left) and flood depth (right)

5. Methodology

An urban drainage area is characterized by the area, shape, slope, soil-type, land use

pattern, percent imperviousness, roughness and different man-made and natural

storage systems. There are several important parameters that are used in context of

hydrological modelling and routing processes. The main factors affecting the rainfall-

runoff analysis and runoff estimation in urban areas and urban rainfall modelling are

land use and imperviousness. Modelling set up process and important terms and

parameters used during the modelling are described below.

5.1. Study Area

The study is undertaken in a part of Kulmbach town that lies in the Upper Franconian

district of Kulmbach. It is located on the River Main in Upper Main Basin. Its total area

31

is 92.77 km2 and total inhabitants are 26,000. It has traditionally been manufacturing

base for the drinks and food industry.

5.2. Landuse classification

Urban sprawls have great variety of ground cover and urban development comes in

many styles and occurs in different types of landscapes. Each land cover have its own

co-relation with flood/water propagation and influence the runoff accordingly. Flow

processes, flood propagation and water retention are different in water bodies,

vegetated areas and built-up areas. Due to their distinctive difference, these factors

should be accounted for while modelling urban flood.

Firstly, Digital Terrain Model (DTM) and shape file with land-use classification of

Kulmbach city are obtained. Urban area of Kulmbach is classified into following land-

use classification after analyzing the most critical land cover required for urban flood

modelling (Figure 16).

Table 5.1: Landuse classification of the study site

Landuse Classification

Agricultural Area

Areas with mixed use

Areas with special functional use

Cemetery

Forest and woods

Industrial and commercial space

Non vegetated area

Residential area

Roads and railway tracks

Sports and Recreational Areas

Swamp

Water Body

32

Figure 5.1 : Land-use classification of Kulmbach

5.3. Runoff coefficient

The runoff coefficient represents the integrated effects of infiltration, evaporation,

retention and interception all of which affect the volume of runoff. It is a dimensionless

coefficient relating the amount of runoff to amount of precipitation received.

In urban area, surface runoff are considered to be one of the crucial drivers of flood

(Elga et al. 2015). Horton described surface runoff as precipitation that exceeds the

infiltration capacity of the topsoil layer. According to Douglas et al. (1978), new concepts

developed have shown that saturation flow in the topsoil layers and the water bodies

also influence the surface runoff generated.

Similarly, sub-surface flows are marked by the interflow or hypodermic flow that forms

in the unsaturated soil layer and flows directly through the soil layer to the river. Interflow

is reduced in urban areas due to the human made changes to the natural environment.

Due to sealing of the surfaces, infiltration from the precipitation is reduced and hence

less water reaches the unsaturated soil layer (Douglas et al. 2007).

Another important factor affecting the urban flood is groundwater flow. Groundwater can

be defined as the subsurface water that fills in the pore and cavities of lithosphere

(saturated zone). Groundwater flow is comparatively slower process than surface runoff

and sub-surface runoff, and it can take years for infiltrated precipitation water to reach

33

the rivers. However, urbanization and surface sealing reduces infiltration of precipitation

and hence groundwater recharge.

5.3.1. Determination of Runoff Coefficient

Runoff coefficient is measured by determining soil type, gradient, permeability and land

use. With the assumption that impervious areas contribute 100% of rainfall to the runoff

and pervious areas contribute 0% of rainfall to runoff, the coefficient can be calculated

as C=PIMP/100. In general, larger areas with permeable soils, dense vegetation and

lower gradient have lower C values. In contrast, smaller areas with dense impermeable

soil, moderate to steep gradient and sparse vegetation have higher C values. Runoff

coefficient and percent imperviousness are related but however they are not necessarily

always same as runoff can generate from pervious surfaces as well.

Table 5.2: Runoff Coefficient values based on GHKSAR 2000

Landuse Classification Runoff Coefficient [-]

Agricultural Area 0.3

Areas with mixed use 0.1

Areas with special functional use 0.1

Cemetery 0.1

Forest and woods 0.1

Industrial and commercial space 0.7

Non vegetated area 0.1

Residential area 0.6

Roads and railway tracks 0.5

Sports and Recreational Areas 0.2

Swamp 0.07

Water Body 0.07

5.4. Imperviousness

Urban areas are characterized by extensive built-up area consisting of asphalt,

concrete, bricks, stones and other construction materials. In these sealed areas

precipitation, which normally infiltrates the subsurface, is reduced and leads to

increased surface runoff. The sealed areas or impermeable areas vary greatly in urban

centers. The extent of imperviousness plays key role in urban surface runoff drainage

and is an important parameter in urban hydrological models (Canters et al.).

34

Many sealed surfaces in urban areas are not connected to storm water pipe drainage.

When these sealed areas are surrounded by gardens and green spaces, they discharge

the surface runoff into these green areas, hollows, drains or depressions which

increases the infiltration into the ground. Pasche et al., 2004 categorized the sealing

rate into total sealed area (Total Impervious Area) and the proportion connected to storm

water drainage pipes (Effective Impervious Area).

Total Impervious Area (TIA) can be defined as the portion of the urban area covered by

non-infiltrating constructed built-up spaces. However, TIA ignores nominally “pervious”

areas that have significant contribution to the runoff and includes non-contributing

impervious areas that do not have any effect on surface-runoff generation (Pasche

2007).

Effective Impervious Area (EIA) can be defined as impervious areas that have direct

access to downstream drainage (stream) or are connected to storm water drainage

network. EIA excludes TIA draining into pervious area. EIA is widely used to

characterize the urban development in hydrological models. However, direct

measurement of EIA is very complicated. To derive EIA, direct measurement and

calculation of both TIA and EIA is required. Detailed analysis of land cover facilitates the

detailed evaluation of imperviousness. However, owing to cost and time constraints,

usually a coarser analysis of land cover is performed that permits evaluation of only total

imperviousness.

For the ease, impervious area are also classified as hydraulically connected impervious

area and non-hydraulically connected impervious area (Karamouz et al. 2010).

Hydraulically connected impervious area is similar to Effective Impervious Area defined

by Pasche et al. as it defines areas that are directly connected to drainage system and

drains into it. For instance, street with curbs and gutters which collects the surface runoff

and drains it into storm sewer is an example of hydraulically connected impervious area.

The areas where runoff drains into pervious areas and are not directly drain into storm

water drainage system are non-hydraulically connected impervious areas.

5.4.1. Determination of Imperviousness

In most cases, imperviousness is estimated based on land use. Imperviousness is often

quantified based on percent imperviousness (PIMP). There are many ways to derive

PIMP: it can be derived manually from maps or automatically from aerial pictures or can

be approximated based on population/housing density. For this study, the impervious is

based on the study presented by Douglas et al. (2007).

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Table 5.3: Degree of imperviousness, runoff and roughness coefficient for landuse

classes

Landuse Classification Imperviousness

[%]

Runoff

Coefficient

[-]

Roughness

Coefficient

[s/m1/3]

Agricultural Area 12 0.3 20

Areas with mixed use 10 0.1 15

Areas with special functional use 10 0.1 20

Cemetery 10 0.1 25

Forest and woods 15 0.1 10

Industrial and commercial space 80 0.7 15

Non vegetated area 12 0.1 20

Residential area 70 0.6 15

Roads and railway tracks 50 0.5 45

Sports and Recreational Areas 25 0.2 25

Swamp 7 0.07 30

Water Body 7 0.07 30

5.5. Digitization of Manholes and Collection Networks

Map of the city with manholes and pipelines and their information are obtained. MIKE

URBAN is integrated with ArcGIS and thus the manhole and pipeline shape-files can be

directly imported into it. The manhole and pipeline are digitized in ArcGIS. 1D network

model requires information on diameter, elevations and slopes of manholes and

connecting pipes. Thus, the detail information such as ground elevation, diameters and

slope angle for each manhole and pipeline is digitized and verified manually by

comparing the data in the map with the digitized data. After verification, these data are

added to the attribute tables of manhole shape-file and pipeline shape-file respectively.

36

Figure 5.2: Digitized manholes of Kulmbach city

Figure 5.3: Digitized pipelines of Kulmbach city

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5.6. Model Set Up

5.6.1. Importing the manholes and pipelines layers

A small section of the whole network is selected for the initial study to observe the initial

simulation processes and to record any instability or errors in the pipeline networks. The

digitized manholes and pipeline networks is imported directly into Mike Urban Collection

System. The software is fully integrated with GIS and provides platform to directly import

manholes and network files.

Figure 5.4: Drainage network selected for study

In Mike Urban, nodes (manholes) and links (pipelines) layers are imported through its

Import/Export function. While importing the nodes and links, important features such as

the ground height, surface height, slope and diameter of manholes and pipelines are

also included. The Collection System creates new layers of nodes and links necessary

to perform 1D network model after completion of import.

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Figure 5.5: MIKE URBAN’s Import/Export dialog box

The diameter of the pipes and other attributes can be edited by going through the Nodes

and Links section in the Edit tab of Mike Urban. The diameter of the pipes are entered

as one meter and the type is selected as circular. Similarly, the geometry and the type

of nodes, which can be manholes, basin or outlet are edited accordingly and defined.

Figure 5.6: Manhole geometry in MIKE URBAN (DHI, 2016)

5.6.2. Catchment Delineation

The next step in the modelling is delineation of the catchment in the network. The

catchment and its sub-catchments have to be defined. In MIKE URBAN, catchments

are “hydrological units where storm runoff and infiltration (RDI) are generated on a basis

39

of a single set of model parameters and input data. The catchments represent the level

of discretization of the hydrological model” (Danish Hydraulic Institute (DHI) 2016e).

Catchments can easily be created as a polygon with the help of catchment delineation

wizard provided in MIKE URBAN. Delineation of sub-catchments can be done based on

the point layer (manholes) or polyline layer (pipelines). In this case, catchments are

defined based on the polyline layer as it better represents the specific intensity of rainfall

that will be collected within the node included in the catchment.

Figure 5.7: catchment delineation based on polyline layer

After the catchments are defined, each node should be connected to the catchment so

that the surface runoff computed from that particular catchment flows into the given

nodes and thus into the collection network. This is achieved through the catchment

connection wizard. It is possible to connect more than one catchment to one node of the

model (Danish Hydraulic Institute (DHI) 2016c).

40

Figure 5.8: Figure of drainage network with manholes and pipe links after catchment

delineation

5.6.3. Catchment Parameters

After delineation of the catchment, it is necessary to calculate percent impervious for

each catchment. Each catchment covers various land use classes in different

proportions and hence the percent impervious of each catchment should be calculated.

The catchment layer is imported as shapefile to ArcGIS and then the percent impervious

is calculated based on the average method. This calculates the percent impervious

based on land use classes covered in a catchment, makes an average of the

imperviousness of all these land use classes and assigns the value to that particular

catchment. These calculated percent imperviousness is imported for all the delineated

catchments. For the selected catchment, landuse classification with the imperviousness,

surface and roughness coefficient is used as shown in Table

41

Table 5.4: Landuse classification for the selected section of the network and

corresponding imperviousness, runoff and roughness coefficients

Landuse

class

Imperviousness [-] Runoff

Coefficient [-]

Roughness

Coefficient [s/m1/3]

Swamp 0.07 0.07 30

Water Body 0.07 0.07 30

Settlement 0.70 0.6 15

Vegetation 0.15 0.1 10

Traffic Areas 0.50 0.5 45

Figure 5.9: Screenshot of calculated imperviousness assigned to each sub-catchment

5.6.4. Boundary Conditions

Different meteorological conditions such as temperature, evapotranspiration and rainfall

intensity are taken as “Boundary Conditions” in MIKE URBAN. Rainfall intensity is one

of the most important boundary condition applied during the modelling. MIKE URBAN

allows both time-series or constant rainfall intensity as boundary condition. The rainfall

and the boundary condition can be applied to whole catchment/study area or to specific

catchment. For the modelling, the boundary condition of rainfall intensity is kept as

constant and at 25µm/s.

42

Figure 5.10: Boundary condition – rainfall intensity as constant

5.6.5. Set up and running the Simulation

The first step in modelling is runoff simulation after setting up all the required parameters

necessary for the simulation. Hydrological model is one of the major component of the

simulation. In MIKE URBAN, there exists different concepts for simulating runoff, mainly

time-area and kinematic wave methods. The runoff is simulated using time-area method

which is a simple runoff model requiring minimum data.

5.6.5.1. Time-Area method

In case of time-area method, abstract lines are drawn that represents equal time of flow

travel (isochrones) from catchment’s outfall point. The most remote line from the outfall,

i.e. the maximum flow travel time, represents the time of concentration of the catchment.

DHI (2016e) says that a time area diagram can be created by adding up the areas

between different isochrones and this diagram defines the catchment’s runoff response.

43

From the conception point, the catchment is divided into several cells. The area of each

cell is dependent on the respective time-area curve that is used and can be either

rectangular or divergent or convergent. After the runoff is started, water from each cell

moves to the next neighboring cell in downstream direction. Therefore, the water volume

in a particular cell is the sum of inflow, outflow and current rainfall in that particular cell

multiplied with the cell area. The outflow from the last cell in the catchment represents

the runoff hydrograph of the catchment (Danish Hydraulic Institute (DHI) 2016e).

Nittaya Wangwongwiroj has suggested formulae covering the curve shapes “in

between” three standard ones (rectangular, divergent or convergent) which has been

included in MIKE URBAN. The curves are specified by giving Time Area coefficient

directly instead of specifying a Time-Area curve (Danish Hydraulic Institute (DHI)

2016e).

𝑦 = 1 − (1 − 𝑥)1𝑎 𝑓𝑜𝑟 0 < 𝑎 < 1

𝑦 = 𝑥𝑎 𝑓𝑜𝑟 1 ≤ 𝑎

Where,

y = Accumulated Dimensionless area

x = Dimensionless concentration time

a = Time area curve coefficient

The outputs from the runoff simulation is stored as files with CRF extension which are

used during the network simulation. This output is necessary for hydrodynamic

calculations.

The next step after the completion of runoff simulation is network simulation. The result

of the rainfall-runoff simulation is specified as the network boundary condition while

performing network simulation. Time period of the simulation is set accordingly in the

given tab. Network simulation is performed for four hours with continuous rainfall and

time-step of 0.5.

5.6.6. 2D Overland coupling and simulation

After completing 1D simulation of drainage network, 2D model is set up to run 2D

overland flow simulation. As a prerequisite, DEM of Kulmbach is obtained and the nodes

are coupled. The default settings and parameter values are used for simulation. Then

“2D overland + Network simulation is run to obtain the flood extent and depth in the

area.

44

5.7. Results and Discussion

5.7.1. 1D Simulation

The results obtained from the 1D network simulation shows how the manholes and pipes

interacts and response during the rainfall event. The result presented in Figure 5.12

shows pipe section of the study area and how it gets overloaded at a given time. As the

time increases, the volume of runoff generated is beyond the carrying capacity of the

pipes and the manholes and they become over flooded. The manholes become

overfilled and the water discharges out in the overland. It can be concluded that the

overland is flooded in the lower section or downstream. Figure 5.12 shows profile plot

of a section of the network and resulting surcharge. It can clearly be deduced that lower

part of the area are heavily inundated compared to the upper section.

Figure 5.11: Screenshot of the corresponding profile plot of a section of the network

As the rainfall time progresses, the manholes in the upper section are also flooded and

the water is discharged out onto the surface. However, the flood depth in the lower

section is much higher. The maximum flood extent and flood depth occurs at the end of

the simulation time period. As the rainfall is assumed to be continuous for the given

simulation time period (four hours), the peak occurs at 10 pm.

5.7.2. 2D Overland + Network Simulation

DEM file of the study area is added to the model setup (Figure 27). MIKE URBAN

accepts ESRI Grid format or DFS2 format files for DEM. After DEM is implemented 2D

overland setting and parameters are set through 2D overland settings and tools

provided in MU.

45

Figure 5.12: DEM of Kulmbach and selected study area

The results of flood inundation from the 2D overland flow simulation also clearly shows

that heavy flood and high flood depth occurs in and around the outlets. In contrast,

overland flooding does not occur in the other parts of the network.

46

Figure 5.13: Results showing flooding and flood extent in the study area

However, the result shows that certain areas are flooded by more than 30m. Also, the

model abruptly stops after running the simulation for some time. This may be due to

numerical instability in the model. Also the flooding is concentrated in and around few

manholes. An earlier 1D modelling’s result (Figure 5.11) clearly shows the surcharge

and hence flooding occurs in the manholes in upper areas as well. It can be inferred that

the result obtained is not a correct representation of the flood depth and extent.

6. Conclusion and Outlook

The study project, employing MIKE URBAN, simulated the 1D flooding and 2D overland

network flooding in a part of urban sprawl of Kulmbach city. MIKE URBAN modeling

was set up based on the city’s sewer network, DEM and parameters derived based on

the properties of the study area and the sewer structures. The flood processes were

simulated for 100 year rainfall as a boundary condition.

The 1D and 2D Overland flow simulation showed the extent and depth of the flooding

as rainfall progresses in the selected section of the sewer network. However, the 2D

overland result showed the flood concentrated only in few nodes in contrast to 1D flood

modelling which clearly pictured the surcharge occurring in most of the manholes. One

47

of the reason for abrupt stop in simulation maybe due to numerical instability. The

simulation was performed for constant rainfall of 25µm/s which is equivalent to rainfall

intensity of 90mm/hr. Due to such a large rainfall, the network might have been

overloaded and as a result simulation may have terminated. To counter this, rainfall-

time series can be used so that the rainfall gradually increases and recedes to simulate

real rainfall scenario and to observe the model’s performance and result.

The next logical step for the modeler is to simulate the 1D network model and 2D

overland flow model for a given intensity of rainfall in the whole urban extent of

Kulmbach. MIKE URBAN provides the platform for the user to integrate many detailed

information and parameters. However, MIKE URBAN is a demanding model with a high

degree of complexity in terms of hydrology and hydraulics features included. A

comprehensive knowledge of hydrology and hydraulics and corresponding processes

and equations is a prerequisite to handle the software. Further, understanding of the

parameters and values used for processing in the software is also important to extract

desired information and results.

Also, it is necessary to investigate and validate the manholes, pipelines and outlet points

of the sewerage network in Kulmbach to build a coherent network in MIKE URBAN.

Though the map of Kulmbach depicting the manholes and pipeline network was

obtained, the map is not comprehensive in charting out the sewer networks, collection

basins and outlet points. Also, attributes of the manholes and pipelines are not clear

leading to difficulty in assigning the corresponding features and attributes to manholes

and pipelines. Once the sound and stable structure of the whole network is built, it will

aid in understanding different parameters setting of feature rich MIKE URBAN software

and result in better outcomes.

To conclude, MIKE URBAN offers 1D-2D simulation and good linkages with ArcGIS.

After the sound structure of the models is given, simulations can be run fairly quickly

and the changes can also be applied in easy and fast manner. It is necessary for the

modeler and analyst to understand the underlying formulae and parameters that needs

to defined in the model. Also, there are many usages of the outcomes of the simulation.

After investigating the reliability of simulation results, the maps can be directly exported

to create flood inundation maps or can be saved in different formats which can be used

by other modeling software for further analysis.

48

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