Norwegian University of Department of Hydraulic and Science and Technology Environmental Engineering 0 NTNU

ASSESSING INFRASTRUCTURE VULNERABILITY TO MAJOR FLOODS

By Lars Jenssen

A Dissertation Submitted to the Faculty of Civil Engineering, the Norwegian University of Science and Technology, in partial fulfilment of the requirements for the degree of Doctor Engineer

Trondheim, Norway, May 1998 IVB Report B2-1998-2 DISCLAIMER

Portions of this document may be illegible in electronic image products. Images are produced from the best available original document. Abstract A modem society is complex and depends on several important utilities and types of physical infrastructure, e.g. power supply, transport systems, drinking-water supply, etc. Major floods have devastating effects on society in the flooded areas, and impacts on the infrastructure on which we depend will be felt far outside the inundated area.

The objective of this work has been to suggest a method of assessing the direct effects of serious floods on a physical infrastructure or utility. The information was believed to be potentially useful for contingency planning and for designing of structures that are liable to be damaged by flooding.

The first part of this work offers a review of a number of topics that are needed to assess the effects of flooding: 1) methods of floodplain management and strategies for mitigating floods, 2) methods of risk analysis which will become increasingly important in the field of flood management, 3) methods for hydraulic computations, 4) a variety of scour assessment methods and 5) several applications of GIS to the analysis of flood vulnerability.

Three computer programs were developed to facilitate the practical use of the findings from the review: CULVCAP for computing the headwater level for circular and box culverts; SCOUR for assessing riprap stability and scour depths; and FASTFLOOD, which prepares input rainfall series and input files for the rainfall-runoff model used in the case study.

The road system in Orkdal municipality in S0r-Tr0ndelag County in central Norway was chosen for exploring how to analyse the flood vulnerability of an infrastructure. The road system was analysed in two stages. First, a general analysis was performed to assess how major floods effect the road system. The objective of this stage was to identify the parts of the road system that are vulnerable to flooding and to develop methods for assessing the vulnerability of the road system in a specific area. The next stage dealt with evaluating the vulnerability of flooding of the main roads in Orkdal. First, potentially vulnerable objects were identified. Secondly, the objects were investigated for three flood scenarios: the 100-year flood, the 1000- year flood and the Probable Maximum Flood.

Finally, a method for analysing the flood vulnerability of physical infrastructure has been proposed. The method involves a general stage that will provide data on which parts of the infrastructure are potentially vulnerable to flooding and methods for analysing them, and a specific stage which is concerned with analysing one particular kind of physical infrastructure in a study area.

i 1 Preface This thesis provides a summary of literature reviews, field surveys and calculations carried out between 1994 and 1998, during the development of a method of assessing the potential damage to physical infrastructure from flooding. I have been enrolled as a doctoral student at the Norwegian University of Science and Technology (NTNU), Department of Hydraulic and Environmental Engineering, with a scholarship from NTNU.

Special thanks go first and foremost to Professor Dagfinn K. Lysne at NTNU, Department of Hydraulic and Environmental Engineering, under whose supervision the studies in this thesis has been carried out. I thank him in particular for his kindness and support, and for his advice during innumerable discussions.

I also wish to thank friends and colleagues at the Department of Hydraulic and Environmental Engineering. In particular I thank Leif Lia, for his friendship and valuable support during the final part of the study, and Hilbjprg Sandvik for always being so friendly and helpful.

Last but not least, I thank Ingunn for her absolute support and patience during the long periods when this study took up most of my time and left little time for anything else. Table of content

ABSTRACT i PREFACE ii

1 INTRODUCTION 1

2 BACKGROUND. OBJECTIVE AND SCOPE 2

2.1 Some characteristic effects of large floods 2 2.2 Planning for a flood emergency 2 2.3 Objectives 5 2.4 Organisation of the work 5

3 FLOOD MANAGEMENT AND RISK ANALYSIS 7

3.1 Understanding flood impacts 7 3.1.1 The physical destruction mechanisms of floods 7 3.1.2 Direct flood impacts 7 3.1.3 Indirect flood impacts 7 3.1.4 Classification of flood losses 8 3.2 Methods for estimating flood damage 8 3.2.1 The stage -damage curve 8 3.3 Floodplain management 11 3.3.1 Classification of flood mitigation measures 11 3.4 RISK ANALYSIS 14 3.4.1 AN OVERVIEW OF THE RISK ANALYSIS PROCESS 14 3.4.2 Methods for risk analysis 16 3.4.3 PRELIMINARY HAZARD ANALYSIS 16 3.4.4 RISK ANALYSIS APPLIED TO FLOOD RELATED-PROBLEMS 17 3.4.5 The risk and vulnerability (ROS) project in Orkdal MUNICIPALITY 17

4 HYDRAULIC COMPUTATIONS 20

4.1 Computing water profiles 20 4.1.1 Computation of gradually varying flow 20 4.1.2 Data REQUIREMENTS 22

iii 4.1.3 Model output analysis and model verification 23 4.1.4 Modelling bridges 23 4. l .5 G uidelines for bridge modelling with HEC-RAS 26 4.2 Computing culvert capacities 28 4.2.1 Culvert types 28 4.2.2 Culvert hydraulics 28 4.2.3 CULVCAP: A PROGRAM FOR RAPID ASSESSMENT OF CULVERT CAPACITY 33 4.3 Estimating roughness coefficients 35 4.3.1 Engineering judgement 36 4.3.2 Empirical formulae 36 4.4 Summary and recommendations 37

5 SCOUR AND SEDIMENT TRANSPORT 39

5.1 G eneral scour in uniform flow 39 5.1.1 THE shear stress approach to initiation of motion 39 5.1.2 The velocity approach 41 5.1.3 Stream power and erodibility index method 43 5.1.4 Stream bed armouring 44 5.1.5 Cohesive material 44 5.1.6 Erosion ON vegetated slopes 45 5.2 Scour in constrictions 46 5J Local scouring 46 5.3.1 SCOUR AT BRIDGES 47 5.3.2 SCOUR AT CULVERT OUTLETS 55 5.3.3 Scour by overtopping flow 59 5.3.4 Internal erosion 60 5.4 SCOUR - A PROGRAM FOR SCOUR CALCULATIONS 61 5.4.1 G eneral stability of riprap and bed material . 62 5.4.2 Riprap stability at piers 62 5.4.3 Scour depth at piers 63 5.4.4 Riprap stability at bridge abutments 63 5.4.5 Scour depth at culvert outlets 64 5.4.6 Scouring by overtopping flow 65

6 GIS AS A TOOL FOR FLOOD HAZARD ASSESSMENT 67

6.1 AN INTRODUCTION TO GIS 67 6.1.1 Data classes and data structures 68 6.2 The Idrisi GIS 70

IV 6.3 GIS AND HYDROLOGICAL MODELS 72 6.3.1 LUMPED HYDROLOGICAL MODELS 72 6.3.2 Distributed hydrological models 73 6.4 THE USE OF GIS IN FLOODPLAIN STUDIES 73 6.4.1 DATA ACQUISITION AND PRE-PROCESSING FOR FLOODPLAIN STUDIES 74 6.4.2 Preparing input data for the hydraulic model 75 6.4.3 Handling output data from hydraulic models 75 6.4.4 FLOOD DAMAGE ASSESSMENT 76 6.5 GIS APPLICATIONS IN RISK ASSESSMENT AND MANAGEMENT 76 6.5.1 Application of GIS in hazard assessment 77 6.5.2 Applications of GIS in vulnerability analysis 78 6.5.3 Applications of GIS in risk analysis 79 6.5.4 Applications of GIS in decision -making 79 6.5.5 THE USE OF GIS IN EMERGENCY MANAGEMENT 80 6.6 Applications of GIS in the current study 81 6.6.1 DATA ACQUISITION FOR THE CASE STUDY 81 6.6.2 AN OVERVIEW OF GIS APPLICATION OF THE CASE STUDY 83 6.6.3 EXAMPLES OF EXPERIMENTAL GIS APPLICATIONS 83 6.6.4 Identification of road sections vulnerable to debris flows 87

7 METHODS OF ESTIMATING FLOODS 91

7.1 Frequency analysis 91 7.1.1 Single -series flood frequency analysis 91 7.1.2 regional flood frequency analysis 92 7.2 Rainfall - runoff methods 92 7.2.1 THE RATIONAL METHOD 92 7.2.2 THE UNIT HYDROGRAPH 93 7.2.3 THE RAINFALL-RUNOFF MODEL PQFLOM 93 7.3 A ssessing rainfall 95 7.4 Recommendations 96 7.5 The flood model FASTFLOOD 96 7.6 Flood analysis during the case study 98

8 A GENERAL ANALYSIS OF THE FLOOD VULNERABILITY OF ROADS 102

8.1 Involved parties and their need for information 102 8.2 D escription of the road infrastructure 104 8.3 A ssessing undesired events , their causes and consequences 104 8.3.1 A nalysis of historical data on flood damage to roads 104 8.3.2 Preliminary Hazard Analysis 105 8.4 Undesired events and vulnerable objects 109 8.4.1 Undesired events identified during the study 109 8.4.2 Flood -vulnerable objects and their characteristics 112 8.4.3 Developing checklists for vulnerability assessment 113

9 ANALYSIS OF ROADS IN ORKDAT.118

9.1 Objectives of the analysis 119 9.2 Organisation of the work 119 9.3 Selection of flood scenarios 119 9.4 D escription of the road system in Orkdal 119 9.4.1 Subdividing the road system and assigning priorities 119 9.5 Identification of vulnerable objects 120 9.6 The evaluation of flood vulnerable objects 123 9.6.1 Preliminary screening of vulnerable objects 123 9.6.2 In depth hazard evaluation of each object 125 9.6.3 G eneral hazard evaluation of roads 125 9.6.4 Hazard evaluation at culverts 128 9.6.5 Hazard evaluation at bridges 130 9.6.6 Assessment of overall object performance during selected FLOOD SCENARIOS 131 9.7 Examples 131 9.7.1 Hazard analysis of culvert 9-7 Storbekken 131 9.7.2 Hazard analysis of Route 714 close to Skjenaldelv - Object 9-4 140 9.7.3 Hazard analysis of the bridge where Route 710 crosses Skjenaldelv - Object 8-2 143 9.7.4 Assessing road flooding along the River Orkla 148 9.8 Some experiences from the flood vulnerability assessment 151 9.8.1 Capacity calculations at culverts and bridges 151 9.8.2 Trees falling over the road 151 9.8.3 Debris flows 151 9.8.4 Sediment deposits and alluvial fans 151 9.9 D escription OF FLOOD VULNERABILITY IN THE STUDY AREA 152 9.9.1 The expected effects of Q100 152 9.9.2 The expected effects of Q iooo 152 9.9.3 THE EXPECTED EFFECTS OF PMF 152

VI 10 A METHOD FOR ASSESSING INFRASTRUCTURE FLOOD VULNERABILITY 156

10.1 Some important aspects of flood vulnerability analysis 156 10.1.1 Identifying vulnerable objects 158 10.2 General flood vulnerability analysis 159 10.2.1 Organisation of work 159 10.2.2 Description of the system 159 10.2.3 Identify parties involved and assess their need for INFORMATION 159 10.2.4 Methods for assessing vulnerable objects and typical DAMAGE 160 10.2.5 Compiling the results for the analysis of a specific infrastructure 169 10.3 Flood vulnerability analysis of a specific infrastructure 169

11 SUMMARY. DISCUSSION AND RECOMMENDATIONS 172

11.1 Summary of the study 172 11.2 D iscussion 172 11.2.1 IS THERE A DEMAND FOR FLOOD VULNERABILITY ANALYSIS? 174 11.3 Recommendations for further work 174

LIST OF SYMBOLS APPENDIX A LIST OF OBJECTS APPENDIX B MAPS APPENDIX C 1. Introduction

1 Introduction Major floods have devastating effects on society in the flooded area: farmland and crops are flooded, houses destroyed and social and economic activities are disrupted. Community officials, police and managers of vital aspects of the infrastructure are faced with challenges far beyond their previous experience.

Well-prepared contingency plans are essential to effectively handle extreme flood situations. Such plans must be based on a realistic understanding of what the situation will be when they are put into effect. First, events that will require emergency actions must be identified. Secondly any obstacles to carrying out the emergency actions must be identified and accounted for.

Demands for action and the obstacles hampering relief operations will be of a magnitude rarely experienced by emergency managers: flooded roads and destroyed bridges, breakdowns of power supply and telecommunications, etc. For those responsible for safety management in utilities or of vital physical infrastructure, a systematic approach is needed to assess vulnerability to the effects of serious flooding.

This work is concerned with developing a method for assessing the vulnerability of physical infrastructure to serious floods. The method is general and it is believed to be potentially useful for analysing a wide range of utilities.

The work is organised in four parts: 1. Tool-kit development. The tool-kit is concerned with solving the practical problems of flood assessment, capacity calculations, scour damage etc. 2. A case study investigating the flood vulnerability of roads in Orkdal. 3. Development of a method for vulnerability assessment. A two-stage approach to vulnerability assessment is suggested. The first stage is a general analysis of flood impacts on the infrastructure under study. The second stage deals with the analysis of a specific infrastructure in an area. 4. Discussion and recommendations.

1 2. Background, objective and scope

2 Background, objective and scope

2.1 Some characteristic effects of large floods Several definitions of floods exist. In general, a flood occurs when the river flow exceeds bankfull and a part of the floodplain is inundated. This happens quite frequently in many rivers. At longer intervals, serious flooding may take place. This work is concerned with floods that are capable of causing major damage, i.e. floods with recurrence intervals from 100 years up to the Probable Maximum Flood (PMF).

Direct effects of large floods Extreme flood events may have such severe consequences that they are regarded as natural disasters. These exhibit characteristics that make them significantly different from more frequently occurring disasters such as major fires, toxic gas releases, offshore blowouts etc. Natural disasters have a much larger spatial extent. They affect not only single buildings, industrial plants or even towns, but up to thousands of square kilometres at a time. Natural hazards often last much longer than other disasters. While a large fire will be brought under control in a matter of days, a major flood may last for weeks or even months.

Such floods are also unique in terms of the number of different systems and activities that are affected. Traffic is disrupted due to flooded roads and damaged bridges. Wastewater treatment plants are flooded or ineffective because of the large inflow of flood water. The drinking water supply is disrupted because treatment plants are flooded, or because the inflow of contaminants pollutes the water source. Hooding of transformers and switchyards can lead to long power outages. Telecommunication systems are liable to suffer problems for the same reasons.

Secondary effects of large floods The effects of large floods are not limited to the damage caused by the direct impact of flood water on structures. The complex inter-dependency of different classes of infrastructure makes the situation far more complex and difficult to assess: water supply systems depend on electric power for the operation of pumps and treatment plants. If the electricity system fails, the water supply may fail in turn. The telephone system also depends on electric power. It will not function if a power outage lasts for more than a few hours. As consequence of the complex interactions, it is extremely difficult to assess the overall effects of large floods.

2.2 Planning for a flood emergency It is easy to see that much of the technical infrastructure on which society depends and generally takes for granted will experience serious problems during large

2 2. Background, objective and scope floods. Local government officials and managers at important utilities have an obligation to prepare for emergencies. For local authorities and man y types of utility, this is required by law.

Emergency planning for an organisation or utility involves the main steps listed below (FEMA 1993): 1. Establish a planning team. 2. Analyse the capabilities of the organisation. 3. Conduct a vulnerability analysis. 4. Develop a plan. 5. Implement the plan.

Planning for extreme floods involves the same set of activities. However, the nature of a natural disaster makes the whole pl anning process much more complex. Several factors contribute to this: 1. A large flood is likely to result in a wide range of undesirable events. 2. These events take place over a large area. 3. These take place at the same time. 4. These may last for a long time. 5. A severe flood will adversely affect a number of utility services. 6. Emergency services such as the fire brigade and police will have their hands full and cannot provide the assistance they normally do. 7. The ability to carry out emergency operations will be severely limited by the situation: general confusion, lack of oversight, flooded roads, damaged bridges, power outages, etc. 8. There will be a shortage of people capable of performing emergency actions.

The complexity of the situation calls for a holistic approach that takes into account both the direct impact of the fioodwater, and how the effects propagate through a complex system of interdependent utilities.

An infrastructure cannot be analysed in isolation, but as part of a whole. In order to fully apprehend the scope of the situation it is necessary to assess the impact of flooding on each of the elements that have important effect on the emergency situation as a whole. The elements can then be put together to provide a preliminary flood impact scenario. The initial scenario will allow the impact assessments for each aspect of the infrastructure to be upgraded. The new assessments are in turn compiled into a new flood impact scenario. This iterative process is repeated until the final scenario does not change from one iteration to the next. The procedure is illustrated in Figure 2-1.

3 2. Background, objective and scope

However, it is beyond the scope of this work to investigate all aspects of holistic emergency planning for natural disasters. This work is primarily concerned with the basic building blocks of the procedure; assessments of the direct impacts of flooding on an infrastructure or utility.

More systems

Flood zone Community emergency planning Composite vulnerability image Utility emergency planning Power supply system Land use regulations

Flood management Road system and mitigation planning

Drinking water supply system

Figure 2-1: Composite vulnerability assessment

Analysing one infrastructure involves assessing the impacts of flooding on a number of objects that comprise the infrastructure. Analysing the direct flood impacts on a structure is itself a complex problem that requires expertise in several fields: 1. Hydrological assessment, involving rainfall and flood computations. 2. Hydraulic computations, involving-flood surface profile computations and flood-zone delineation.

4 2. Background, objective and scope

3. Scour assessment in order to identify damage to structures exposed to the flood- water. 4. Impact assessment, which deals with assessments of the direct effect of the flood on the object concerned. 5. Consequence analysis which is concerned with assessing the immediate and direct consequences for the object concerned.

The first four stages require extensive knowledge of hydrology and hydraulics. Assessing impacts and consequences also requires in-depth knowledge of the infrastructure concerned.

A review of the literature has not revealed much information on methods for assessing the overall effects of natural disasters. No information has been found on how to perform a vulnerability study involving several infrastructures exposed to flooding. However, several methods have been found for assessing the impacts of floods on specific structures such as bridges and levees.

It is believed that a holistic approach along the lines discussed in this section may be feasible. Such an approach would provide a comprehensive picture of the situation that will face emergency managers during extreme flood events, and thus permit more realistic emergency plans to be drawn up than current practice allows.

2.3 Objectives The overall objective of this work is to suggest and explore a method for assessing the vulnerability of an infrastructure to severe flooding. This involves two main activities: 1. The development of a general method for organising the flood vulnerability assessment of an infrastructure. 2. The suggestion of methods for dealing with the practical hydrological, hydraulic and scour assessment problems that will be encountered during a flood vulnerability study.

2.4 Organisation of the work The rest of this work can be divided into four parts: 1. Review of methods essential for the performance of a flood vulnerability study. Methods concerning flood management, hydraulic computations, scour assessment and flood assessment are reviewed, and recommendations are made regarding how the methods should be applied. Several computer tools have been developed to facilitate effective use of the recommended methods. The first part consists of five chapters: 1. Review of flood management and risk analysis methods (Chapter 3). 2. Methods for surface profile and culvert capacity computations (Chapter 4).

5 2. Background, objective and scope

3. Methods for scour assessment (Chapter 5). 4. GIS as a tool in flood hazard assessment (Chapter 6). 5. Methods for estimating flood characteristics (Chapter 7). 2. A case study of the road system in Orkdal. The study has two parts: 1. A general analysis of how the road infrastructure is effected by floods (Chapter 8). The findings from this part are used as a basis for the second part. 2. Analysis of the flood vulnerability of the main roads in Orkdal (Chapter 9). Three scenarios were investigated: 1) the 100-year flood, 2) the 1000-year flood and 3) the PMF. 3. Development of a method for assessing the vulnerability of an infrastructure to severe flooding (Chapter 10). 4. Discussion and recommendations. The suggested approach is discussed and improvements are suggested (Chapter 11).

6 3. Flood management and risk analysis

3 Flood management and risk analysis The first part of this chapter reviews floodplain management strategies. This is a wide field, which deals with the impacts of flooding and the various strategies available for coping with floods.

The second part reviews risk analysis techniques and their application in flood management.

3.1 Understanding flood impacts Every year floods cause enormous damage throughout the world. Riverine flooding results in loss of life and human injury, damage to property and agriculture, disruption of production and utility services. The different approaches used to characterise flood impacts are briefly reviewed in this section.

3.1.1 The physical destruction mechanisms of floods The destruction mechanisms are the direct impacts of the floodwater on nature, on the river or on a structure. A number of destruction mechanisms contribute to flood damage, and understanding them is very important when vulnerability to flooding is being assessed. Which destruction mechanism to consider in any given case will depend both on the structure itself and on its surroundings. Some important mechanisms are listed below: 1. Inundation of land and structures. 2. Water pressure on structures. 3. Uplift forces on structures. 4. Scouring at foundations, around buildings, of farmland etc. 5. Intakes or constrictions clogged by floating debris.

3.1.2 Direct flood impacts Direct impacts of natural hazards are those that directly result from exposure to the hazard. They typically include injury and death to people and livestock, damage to structures and their contents, damage to crops, physical changes along the watercourse and psychological trauma.

3.1.3 Indirect flood impacts Indirect impacts are the direct outcome of direct impacts and include secondary effects such as homelessness, shutdowns of business and industry, disruption of utility services, financial expenditure for clean-up and recovery operations, insurance pay-outs, etc. In turn, secondary effects may lead to higher-order effects such as unemployment, loss of business or income, falls in land values and loss of community socio-economic viability.

7 3. Flood management and risk analysis

3.1.4 Classification of flood losses Several types of loss classification exist (Petak and Atkisson 1982; Cochrane 1992; Ellingwood et al. 1993; Moser 1994; Yevjevich 1994b). In general, flood losses may be divided into direct and indirect losses. Both groups consist of tangible and intangible losses.

Direct economic effects are caused by damage to assets and interruption of production processes and related income flows. Indirect economic effects are the loss of value added due to interruptions in the supply of inputs or demand for outputs directly attributable to physical damage sustained in the course of the flood event, i.e. loss of labour and loss of market shares.

Death by drowning or losses of personal memorabilia are examples of direct intangible loss. Stress and reduced quality of health care or education are indirect, intangible losses.

Since the main interest in evaluating flood impacts has been on the part of engineers evaluating the economic feasibility of flood mitigation measures, the framework for evaluating flood impacts focuses on direct economic costs. In spite of this economic losses resulting from natural hazards are poorly documented. Studies of flood damage data in the National Weather Service data base, the most frequently quoted in the USA, showed that the quality of the data was so poor that no one in the flood research community believed in them ((Grazulis 1989) in (Cochrane 1992)).

3.2 Methods for estimating flood damage Two distinct approaches have been taken to estimating flood damage (Ellingwood et al. 1993): 1) the historical approach and 2) the synthetic approach. The historical approach relies on the use of records of flood losses that have occurred in the past at the place of interest, to predict future damage at the same place.

The more widely used synthetic method utilises past flood damage data from a wide range of incidents and generalises these data to yield damage functions that can be applied to other sites.

3.2.1 The stage-damage curve For a river reach, the total direct economic flood damage dependence on flood water level is expressed through the stage-damage curve. The curve expresses the total damage to all structures as a function of water stage at a reference location. The approach for developing the stage-damage curve involves the following steps (Moser 1994): 1. Enumerate and classify each structure in the study area. 2. Establish the elevation of the first (ground) floor.

8 3. Flood management and risk analysis

3. Estimate the value of each structure. 4. Estimate the value of the contents. 5. Estimate the damage to structure and contents at various water depths for each building. 6. Estimate the depth of water at each location that corresponds to individual stages at a reference location. 7. Aggregate estimated damages at all locations for each reference flood stage.

To calculate the average flood damage for the reach a stage-frequency curve must be developed at a reference location. This is done by combining a discharge- frequency curve and a stage-discharge curve. The discharge-frequency curve is normally found from flood frequency analysis, and the stage-discharge curve from direct measurements or hydraulic modelling. Combining the stage-damage curve and the stage-probability curve yields the damage-frequency curve. The schematic for developing a stage-damage curve and a damage-frequency curve is shown in Figure 3-1.

The method described focuses on direct economic losses. Estimating indirect economic losses may be extremely difficult as this involves calculating the net effect of all future economic changes within the relevant region that may be attributed to the flood occurrence. It seems that no formal method currently exists of identifying and measuring indirect flood damage, although this would be extremely useful in evaluating the economics of flood damage and mitigation. Comprehensive evaluations of indirect costs are seldom performed. Instead the indirect losses are calculated by rule of thumb on the basis of direct losses, i.e. the indirect damage in residential areas is estimated to be 15 % of direct losses (EUingwood et al. 1993).

Intangible losses may be of comparable importance to tangible losses, but the literature reports few attempts to consider intangible losses formally (EUingwood et al. 1993).

9 3. Flood management and risk analysis

Structure first floor elevation

Depth of water Flood-water over first floor surface elevation

Structure Structure Contents Value of Contents depth value contents depth damage structure damage curve value ratio curve i —r Structural Contents damage damage

Damage

Figure 3-1: Schematic for developing the stage-damage curve and the damage- frequency curve (Based on (Moser 1994))

10 3. Flood management and risk analysis

3.3 Floodplain management Floodplain management can be described as:

"A continuous process of making decisions about whether and how floodplain lands and waters are to be used. It encompasses the choices made by owners of floodplain homes and businesses, decisions made by officials at all levels of government, development plans made by owners of commercial floodprone land and the judgements of farmers with pastures and fields stretching to the riverbanks. The process also focuses the attention of decision-makers on the relationship between human use and the conservation of natural resources" (Thomas 1994).

The objective of floodplain management is to find the best mix of measures to optimise the development of the floodplain considering all the often conflicting interests and objectives of all the stakeholders in the floodplain. Obviously, this complicated process will involve a wide array of professional and political decisions.

"Unfortunately, human development on floodplains usually results in flood damage and disruption to people and the infrastructure they create, as well as adverse alteration of natural systems. The costs and limitations of trying to control flooding have been enormous and well-documented, and the extent of the harm this approach has caused to natural systems is only now beginning to be fully understood" (Thomas 1994).

This quote from the "National Program for Floodplain Management" points to two important experiences in coping with floods: 1) despite enormous investments in flood-control measures flood damage is still increasing, and 2) structural flood control measures and the resulting economic development of floodplains has caused considerable damage to the environment.

This indicates that defence from floods must not be regarded in isolation, but rather as a part of the total management of the catchment and its floodplains. It is beyond the scope of this work to go into the very wide subject of floodplain management. However, the following paragraphs will introduce the main strategies for floodplain management and flood mitigation.

3.3.1 Classification of flood mitigation measures Flood mitigation covers a wide range of measures from the “do nothing ” alternative to intensive structural measures. A classification is useful in order to obtain a systematic view of the range of mitigation measures available.

11 3. Flood management and risk analysis

Yevjevich (1994a) describes several classifications and suggests a classification based on basic categories of individual measures. Yevjevich ’s classification distinguishes five categories: 1) prevention, 2) prediction, 3) proofing, 4) physical control and 5) insurance.

Flood prevention measures This includes all measures directed at preventing floods from occurring; rainfall suppression, modification of large storms and control of human-induced floods. Storm prevention and rainfall suppression are unlikely to become feasible alternatives in the near future.

Human-induced floods include dam-break floods and floods from operating flood gates. Both can lead to serious flood disasters, and strict operational controls are necessary.

Measures based on prediction of floods Mitigation based on flood prediction includes the four sub-groups: 1. Forecast of incoming floods. Forecasts are important for warning everyone who will be affected by the flood and gaining time for evacuation and defence. 2. Flood warning. Timely and credible warning is the most important non- structural measure. 3. Evacuation prior to flood events. Success depends on the accuracy of flood forecasts and warnings, and on how well it is planned and managed. 4. Defence from floods. Involves the reinforcement of structures on the floodplain and the building of temporary defence structures.

Proofing floodplains to better withstand flood events Proofing involves modifying the use of floodplains according the risk of flooding: 1. Zoning the use of floodplains. The floodplains are delimited into flood risk zones and activities are regulated according to the degree of risk. Zoning can be based on several criteria such as the probability of inundation or the danger posed by destruction mechanisms such as scour and high velocity flow. 2. Coding activities and constructions in the floodplain. To withstand flood impacts regulations may prescribe building codes in different zones of the floodplain. Other activities in the floodplain (industry, agriculture) may also be controlled to reduce flood impacts. 3. Educating people in how to live with floods. Knowledge of all aspects of floods may result in a significant decrease in flood impacts both during and after floods.

12 3. Flood management and risk analysis

4. Changing people's attitudes to floods. This is done to change people ’s attitudes to what can be done to alleviate flood impacts, and includes attitudes to forecasting, warning, zoning, coding, and other activities in the best interests of the population.

Extensive structural flood control measures Extensive physical measures are spread over an area of a catchment. Such measures include: 1. Land control. Maintenance of forests and grasslands for erosion control, rainfall interception and water retention and infiltration. 2. General soil control. Various activities in the catchment that are intended to decrease the supply of sediment to watercourses. 3. Controlling effects of urbanisation. Urbanisation affects rainfall interception, evaporation and runoff by introducing impermeable surfaces and drainage systems resulting in increased flood peaks and volumes. These effects may be reduced by measures such as flood-retention basins and the use of natural drainage systems.

Intensive structural flood-control measures Intensive structural flood-control measures are usually concentrated at a point, or developed along a line. Dams and weirs are typical point structures. Levees and retaining walls are typical structures along lines. These structures often require large localised investments, qualified operation and maintenance. The consequences of failure or malfunction may be severe, and can affect large areas. Intensive measures include: 1. Levees, dikes and walls. Their major objective is to defend land in the floodplain against inundation, but they also have several negative effects: the structures themselves must be defended against floods (erosion, piping, etc.), defended land must be drained and water removed by pumping, downstream flood volumes and flood peaks are increased and the flow during low flow season is decreased. 2. Reservoirs and retention basins. The major objective of flood retention measures is to reduce flood peaks downstream by the intermediate storage of flood waters in reservoirs. The reservoir may be built for flood defence only or as a multi-purpose project providing irrigation water or hydropower in addition to flood mitigation. The negative aspects of large storage basins are the loss of land to storage space, the undesirable environmental impacts and the potential for disasters resulting from faulty operation or breaches. 3. Increased channel capacity. Well-designed diversion channels are a good flood control measure, but many projects have experienced serious trouble due to channel bed degradation or aggradation caused by changes in the sediment­ carrying capacity of the river.

13 3. Flood management and risk analysis

4. Floodplain polders and floodplain platforms. Polders encircle flood-prone structures by a dike or levee to protect them from large floods. Platforms are earth fills that elevate the structures to be protected well above the flood level. Both measures reduce floodplain area and flow cross-section. The polders must be drained and water removed by pumping.

Flood insurance Insurance is based on the concept of distributing loss due to flooding. Insurance is one of the most important non-structural measures available for coping with flood impacts. 1. Public disaster approach to flood insurance. Government help to flood victims in one way or another is a general public insurance method. All taxpayers pay their premiums through taxes. 2. Government insurance. In some countries, the government institutes a special flood insurance programme, i.e. the National Flood Insurance Program in the USA. 3. Mixed public - private insurance. The government and private insurance companies jointly insure flood-related losses, or the government guarantees compensation for damage beyond a given sum. Private insurance companies often need government involvement to share the large payouts involved after extreme floods.

3.4 Risk analysis Risk analysis comprises a set of techniques for identifying hazards, for assessing consequences and for risk management. This section offers a brief review of risk analysis in general and applications to flood risk in particular.

3.4.1 An overview of the risk analysis process Since its initial development in the military and nuclear industry, the use of risk analysis has continually been applied to new fields. Risk analysis techniques are well developed and integrated in the economic analysis of flood damage, whereas the application to several other important aspects of flooding is still new and unexplored. The report of the Commission on Flood Protection Measures (Nj0s et al. 1996) following the serious flood in Norway in 1995 encourages the application of risk analysis to flood management.

14 3. Flood management and risk analysis

Risk designates the danger that undesired events represent for humans, the environment and material values. Risk is expressed by the probability and consequences of undesirable events (NSF 1991). Risk analysis is a systematic approach to the description and calculation of risk. A risk analysis includes three main activities: 1. Identification of undesired events 2. Causal analysis 3. Consequence analysis.

An undesired event is an event or condition that is capable of causing human injury or environmental or material damage (NSF 1991). A risk analysis often starts by identifying what undesired events may occur. For example, undesired events at dams may be overtopping of the dam crest, a landslide into the reservoir, piping through the dam, etc.

The next step in the analysis is to identify possible chains of events that may lead to the undesired events, i.e. the causal analysis. Causal analysis is a systematic procedure for describing and/or calculating the probability of causes of undesired events (NSF 1991). From the example above: possible causes of overtopping may be insufficient spillway capacity, faulty operation of the system, malfunction of the spillway gate, etc.

The third step in the risk analysis is concerned with assessing the consequences of the undesired events. A consequence is the possible result of an undesired event. The consequences may be expressed verbally or numerically to define the extent of injury to humans or of environmental or material damage (NSF 1991).

A total risk analysis will involve several elements in addition to the three main tasks described above. Requirements for Risk Analyses (NSF 1991) gives a detailed description of the elements to be included in the analysis. The most important of these are mentioned in the following paragraphs.

The risk analysis must include a description of the background and objectives of the risk analysis. The decisions to be made and the criteria for making them should be included.

The subject of the analysis must be described. The description should include all aspects of relevance to the risk analysis. In particular, all conditions related to the safety of the object should be described.

The methods used during the risk analysis and background for the choice of methods must be described.

15 3. Flood management and risk analysis

A description of the risk is the main result of the analysis. A list of consequences and their probabilities is used to describe the risk. Risk may be compared with the decision criteria in order to assess whether corrective measures will be required.

3.4.2 Methods for risk analysis Several risk analysis methods exist. The different methods are suitable for different parts of the risk analysis process. Some are used to identify undesired events, some in the causal analysis and others to assess consequences. The choice of method depends on the subject being analysed, the objective of the analysis and the data available. The methods range from simple to sophisticated methods that require expert knowledge.

Some common risk analysis methods are: 1. Preliminary Hazard Analysis. 2. Failure Mode Effect and Criticality Analysis (FMECA). 3. Hazard and Operability Studies (HAZOP). 4. Fault tree analysis. 5. Event tree analysis.

Their application in the cause — undesired event — consequence chain is shown in Table 3-1. For a description of the methods see (Rausand 1991) or (Aven 1994).

Table 3-1: Methods of risk analysis Causal analysis Identification of Consequence undesirable analysis events Preliminary hazard (x) X (x) analysis Fault tree analysis X FMECA X X HAZOP X X X Event tree analysis X

3.4.3 Preliminary Hazard Analysis Preliminary Hazard Analysis is a frequently-used method of identifying undesired events - hazards. The analysis is performed by a working group. It starts by subdividing the system into its main components. For each component, the working group attempts to identify all relevant hazards. When a hazard has been identified the possible causes and consequences are described.

16 3. Flood management and risk analysis

Preliminary Hazard Analysis is an easy-to-use method that may be performed without expert knowledge of risk analysis. It is often used at an early design stage when detailed system information is not available, and focuses mainly in detecting hazards.

3.4.4 Risk analysis applied to flood related-problems Risk analysis has a long tradition in one field of floodplain management, namely, estimating flood losses. The damage - frequency curve, which was described in Section 3.2.1, describes the flood risk in monetary terms.

Methods for assessing direct flood damage are well established and computer tools for damage calculations have been available for many years. However, available methods usually consider the effects of water level and ignore the effects of flow velocity, scour, debris flow, etc. When analysing flooding in steep rivers these important mechanisms of destruction must not be omitted.

The findings from a review of the literature on the use of risk analysis for flood studies may be summarised as follows: 1. Well-established methods exist for assessing direct inundation costs on floodplains along mildly sloping rivers. 2. Systematic methods for assessing the damage caused by destruction mechanisms other than inundation are few. 3. Systematic methods for performing an overall flood risk analysis were not found. 4. A number of risk analysis applications exist in the fields of dam safety, levee safety, and for analysing the operation of flood control and hydropower systems.

When planning how to handle flood emergencies it is vital to know how roads, power supply, telecommunication, etc. will be affected by the flood. The mech anisms of destruction are many and the effect of interdependencies between different kinds of infrastructure are not easy to assess. Analysing such impacts is a complex process for which methods are not readily available, but to which existing risk analysis techniques may be adapted, and for which new methods may be developed.

3.4.5 The risk and vulnerability (ROS) project in Orkdal municipality The disintegration of the Eastern Bloc and consequent changes to the security situation in Norway resulted in a restructuring of Norwegian Civil Defence, with more attention being paid to the han dling of peacetime disasters. Consequently the Directorate for Civil Defence and Emergency Planning developed “A guide to risk

17 3. Flood management and risk analysis and vulnerability assessment in the municipality ” (Direktoratet for sivilt beredskap 1994) and encouraged municipalities to implement risk and vulnerability assessment (ROS) in the planning process.

A test project was carried out, in which several municipalities in Central Norway worked together with the Directorate for Civil Defence and Emergency Planning, the County Emergency Planning Office and a consulting firm to assess how ROS could be implemented in the planning process. The project report (Fylkesmannen i S0r-Tr0ndelag 1995), which provides a practical guide to ROS in addition to several case studies, has become a template for ROS projects in a number of municipalities.

The ROS project uses a technique used for identifying undesired events that closely reassembles Preliminary Hazard Analysis. In order to obtain an overview of the risk involved the events are classified according to probability and consequences and placed in a risk matrix as shown in Table 3-2. The matrix is used for deciding which events will require mitigation measures, and the method of mitigation to be used. The ideal situation is that all undesired events fall below the diagonal (00) from the upper left to the lower right comer, as this indicates both low probability and minor consequences. Table 3-2: The risk matrix Probability ______Consequence ______Little danger Some danger Critical Catastrophic Very probable 00 Probable 00 Less probable 00 Improbable 00

Events that lie above the diagonal are unacceptable, and must be mitigated by reducing their probability. Events at the diagonal (00) are at the acceptability threshold and their probability and/or consequences should be reduced. No mitigation measures are needed for events that lie below the diagonal.

During 1996, Orkdal municipality used the ROS procedure to assess the impacts of flooding. A study group was set up with representatives of the municipality, the police department, the Red Cross, the County Emergency Planning Office and the Norwegian Water Resources and Energy Administration (NVE), in which the author also participated. The flood impacts on several utilities were investigated for floods with 10,50,100 and 1000-year recurrence interval (Qi0, Qso, Qioo and Qiooo) (Selboe 1997). The analysis provided important results that will be used for

18 3. Flood management and risk analysis contingency and land use planning in Orkdal, as well as valuable inputs to this study.

However, during the study it became clear to the author that the recommended ROS procedure (Direktoratet for sivilt beredskap 1994; Fylkesmannen i S0r-Tr0ndelag 1995) was not sufficient as a means of analysing the complex situation that a major flood would involve. Important factors that contributed to this were: • As the ROS method is general it does not provide any information on how to estimate direct flood impacts. • The ROS method did not provide an efficient method of analysing a large number of undesired events that could happen at the same time. • The ROS method did not provide a means of analysing the complex interaction between different utilities. • There are no clear definitions of the probability and consequence classes involved. • It is not sufficient to base mitigation measures on how the event is placed in the risk matrix. The decision criterion must also include the costs of mitigation.

19 4. Hydraulic computations

4 Hydraulic computations A wide range of different hydraulic computations is necessary for any flood hazard analysis. Flood surface profile calculations are needed to determine water levels and flood zones. More detailed hydraulic data such as velocity and shear stress distributions are required for scour and erosion assessment. Computations at special structures such as bridges and culverts are needed to assess their ability to convey floodwaters and their effect on the general flood profile.

The objective of this chapter is to review and discuss relevant hydraulic computation methods, and to suggest how they should be applied in a flood hazard analysis. This chapter has five sections that deal with the following topics: 1. General flood profile computations. 2. Flood profile computations through bridges. 3. Culvert capacity computations. 4. The development of a computer program for simplified culvert computations. 5. Methods for assessing hydraulic roughness parameters.

4.1 Computing water profiles The computer program HEC-RAS was used for most of the profile calculations. This discussion therefore focuses on the computational methods used in HEC-RAS and on the program ’s capabilities. The following discussion is based on the “HEC- RAS Users Manual ” (HEC 1997a) and the “Hydraulic Reference Manual ” (HEC 1997b).

The Hydrologic Engineering Center ’s River Analysis System (HEC-RAS) is a piece of software developed for one-dimensional hydraulic analysis. The current version (2.1) can compute subcrifical, supercritical and mixed-flow conditions in a single channel or in a network of channels. It can compute free surface and pressure flow through bridges, and flow through single or multiple barrel culverts. HEC-RAS is also capable of computing contraction scour, pier scour and abutment scour at bridges.

4.1.1 Computation of gradually varying flow The basis for computing gradually varying flow is the energy equation: (4-1) r2+Z2+5£i = yi+z,+^£L+A, 2 g 2 g where: Y = Depth of water Z = Elevation of channel invert above datum U = Average flow velocity

20 4. Hydraulic computations a = Velocity weighting coefficient he = Energy head loss g = Acceleration of gravity

The terms in the energy equation are shown in Figure 4-1.

Water surface

Channel

Datum

Figure 4-1: Energy equation definition sketch

The energy head loss is made up of friction losses, contraction and expansion losses. The friction loss is computed using Mannin g's formula. The contraction or expansion loss is computed by applying a coefficient to the change in velocity head. a2Ul a{J[ (4-2) h e = LSf + C 2 g 2 g where: L = Discharge weighted reach length Sf = Friction slope between two sections C = Expansion or contraction coefficient U = Average flow velocity a = Velocity weighting coefficient he = Energy head loss

The unknown water surface at a cross-section is determined by means of an iterative solution of the energy and head-loss equation. First the unkn own water surface is assumed. The conveyance and velocity head is calculated on the basis of the assumed elevation. The energy head loss is then computed from Equation (4-2) and the unknown water surface is computed from the energy equation. The computed water surface elevation is compared with the assumed elevation. The iterations continue until the values agree to within 0.003 m.

21 4. Hydraulic computations

For situations with rapidly varying flow the momentum equation or empirical equations are used to compute the surface profile. In HEC-RAS the momentum equation is used at transitions from subcritical to supercritical flow, low flow at bridges and flow at stream junctions.

The following limitations apply when using the program: 1. The flow must be steady. 2. Flow must be gradually varied. 3. Flow must be one-dimensional. 4. The river channel must have small slopes.

4.1.2 Data requirements The data required to run the model will depend on the scope of the study, but the basic data may be grouped as follows: 1. Geometric data consist of: • The river system schematic which shows how the various reaches of the river are connected. • Cross-sectional data. • Reach lengths. • Stream junction data. 2. Energy loss coefficients consist of hydraulic roughness data and contraction and expansion coefficients. The hydraulic roughness is described using Manning ’s n. 3. Special structures data include geometric data, roughness data and loss data for hydraulic structures such as bridges, culverts and weirs. 4. Steady-flow data at upstream cross-sections and at tributaries. 5. Boundary conditions are needed at upstream or downstream cross-sections depending on the state of flow.

River cross-sections must be placed at representative locations throughout a river reach and at locations where changes occur in slope, cross-section width, roughness or discharge. Cross-sections are required at control structures, bridges and culverts, and at locations where abrupt changes take place. Distances between the cross- sections will depend on the river size, slope and cross-section uniformity. In general, large uniform rivers of flat slope no rmally require the fewest cross- sections.

The selection of hydraulic roughness parameters is of great importance for the quality of the results of the water-surface profile computations. Methods for selecting Manning ’s n are discussed later in this chapter.

22 4. Hydraulic computations

4.1.3 Model output analysis and model verification Modelling is a process of iteration whereby input parameters are adjusted and readjusted on the basis of computed output. Key variables in model output should be examined in order to identify errors or situations that strongly influence the model results. Large variations in water surface elevation, flow velocity, conveyance or surface width are indications of erroneous input or of excessive distances between cross-sections.

Observed high-water marks and rating curves at stream gauges should be used to calibrate the model. The lack of good quality discharge data from major floods is always a problem when preparing models for extreme flood events. Detailed descriptions of model analysis and verification may be found in (Hoggan 1989).

4.1.4 Modelling bridges The main objective of modelling flow through bridges is to compute the backwater effect of the bridge. This section will discuss the hydraulics of bridges and bridge ­ modelling approaches. The discussion borrows heavily from the "HEC-RAS Hydraulic Reference Manual" (HEC 1997b) and "Computer-Assisted Floodplain Hydrology and Hydraulics" (Hoggan 1989).

Flow through bridges may be divided into two broad classes: 1) low flow exists when there is a free surface flow, i.e. the water profile is below the highest low chord of the bridge, and 2) high flow exists when the water profile is above the maximum low chord of the bridge. The various flow situations are shown in Figure 4-2.

Low flow Low flow is subdivided into three classes depending on the state of flow: 1. Class A flow exists when flow through the bridge is entirely subcritical. 2. Class B flow exists when the flow profile passes the critical depth. 3. Class C flow exists when the profile is entirely supercritical.

Class A flow For class A flow HEC-RAS provides four methods of computing losses through a bridge: 1. Energy method. The energy method is the most generally applicable method for profile computations. It treats the bridge as a natural river section and computes the energy losses from friction, expansion and contraction. The losses occur in three zones: 1) expansion losses immediately downstream of the bridge, 2) friction losses through the bridge, and 3) contraction losses in the reach immediately upstream of the bridge.

23 4. Hydraulic computations

2. Momentum balance method. The method is based on balancing momentum from a cross-section immediately upstream of the bridge to a cross-section immediately downstream. 3. Yamell equation. The Yamell equation is an empirical equation that is based on a large number of laboratory experiments. The method should only be used at bridges where the majority of losses are associated with the piers. 4. FHWA WSPRO Method. WSPRO is an energy-based method with some empirical attributes, that was developed for the Federal Highway Administration (USA).

Class B flow Class B flow exists in two cases: 1. When a subcritical profile passes through critical depth in the bridge constriction resulting in a hydraulic jump forming immediately downstream. 2. When the bridge acts as a control in a supercritical profile, causing a subcritical backwater immediately upstream.

HEC-RAS uses momentum balance to compute an upstream water surface above critical depth and a downstream water surface below critical depth.

Class Cflow. Class C flow exists when the water profile through the bridge is entirely supercritical. The energy equation or the momentum balance method can be used.

High flow High flow exists when the whole width of the low chord is in contact with the flow. The flow through the bridge will be pressurised, and if the upstream water level exceeds the bridge deck level weir flow will also exist. During high flow water may also pass the bridge on the floodplains. HEC-RAS has two methods for computing high flow: 1) energy equation and 2) pressure and weir flow.

Energy equation Computations are based on balancing energy losses through the bridge in the same manner as for low flows. The flow through the bridge is treated as open-channel flow but flow area and wetted perimeter are adjusted to account for the submerged bridge.

24 4. Hydraulic computations

Low flow situations High flow situations

Class A flow Pressure flow

I Yc

Class B flow Pressure and weir flow

Class C flow

Figure 4-2: Various flow situations at bridges

Pressure and weir flow Two separate hydraulic equations are combined to compute the flow: 1. Pressure flow computations. When the flow comes into contact with the upstream side of the bridge a backwater occurs and orifice flow is established. An orifice equation is used to calculate the flow through the bridge. 2. Weir flow computations. Weir flow is computed using the standard weir equation. The default value of the discharge coefficient is 1.4 but the user may adjust this value. Weir flow is reduced to allow for the effect of submergence when the downstream water level is high. 3. Combination flow. When there is a combination of pressure and weir flows the program iterates until the pressure flow method and the weir flow method both have the same upstream energy level.

25 4. Hydraulic computations

4.1.5 Guidelines for bridge modelling with HEC-RAS

Location of cross-sections The flow through a bridge may be subdivided into three reaches: 1. In the contraction reach the flow contracts from full channel width flow to the flow width of the bridge opening. 2. Flow through the bridge. 3. The expansion reach where flow expands from bridge opening width to full channel width.

Four cross-sections are needed when computing the flow profile. The cross-sections are placed as shown in Figure 4-3: 1. Cross-section 1 is placed at the end of the expansion reach, sufficiently downstream so that the bridge does not affect the flow. Several criteria exist for locating the downstream section. Resent research indicates an expansion ratio, ER, in the range of 1:1 to 1:2 and it has also been found that the expansion ratio is closely related to the Froude numbers at cross-section 1 and 2 ((HEC 1995) in (HEC 1997b)). In this study an average expansion ratio of 1.5 was used for placingcross-section 1. 2. Cross-section 2 is located immediately downstream of the bridge and represents the effective flow area just outside the bridge. 3. Cross-section 3 is placed a short distance upstream of the bridge, just before the abrupt acceleration of the flow starts. 4. Cross-section 4 is placed at the upstream end of the contraction reach where the flow lines are approximately parallel. The contraction length is generally shorter than the expansion length. Several criteria exist for determining the contraction length. A rule of thumb suggests a contraction ratio of 1:1. Recent research has found the contraction ratio to be highly dependent on the ratio of the Froude number in the contracted section to the Froude number in the full- channel section. The contraction length is also closely related to the ratio of flow on the overbanks to the total flow ((HEC 1995) in (HEC 1997b)). In this study, a contraction ratio of 1:1 was used to locate cross-section 4.

Ineffective flow areas must be defined in cross-sections 2 and 3. For low flow and pressure flow the area on each side of the bridge opening will normally be ineffective. For weir flow, when the bridge is overtopped, this area may once again become effective.

26 4. Hydraulic computations

4

Contraction reach Lc CR

3

2

Le Expansion reach ER 1 \

1

Figure 4-3: Location of cross-sections at bridges

Bridge modelling approach For low flow, four modelling approaches are available: energy, momentum, Yamell and WSPRO. In general the momentum and energy methods are the most physically based. The user may request the program to use one or more of these methods. If more than one method is used the highest headwater result is used by the program. Some examples for the selection of computational method are given in the following paragraphs. They were used as a basis when selecting the bridge ­ modelling approach during the case study. 1. In cases where friction losses are dominant the momentum method or the energy method should be used. 2. In cases in which both pier losses and friction losses are important either the momentum or the energy method can be used. 3. In cases with subcritical flow and considerable pier drag the momentum method or the Yamell equation provide the best answers. 4. In cases with supercritical flow or flow transitions the Yamell and WSPRO method can not be used. 5. The WSPRO method is particularly suitable for bridges that constrict wide floodplains with heavily vegetated banks.

27 4. Hydraulic computations

For high flow the selection of method depends on the bridge submergence: 1. When the bridge deck offers only a minor obstruction to the flow, and the flow through the bridge opening is not pressurised, the energy method should be used. 2. When the bridge deck offers a major obstruction to the flow and creates a backwater the weir and pressure method should be used. 3. When the bridge and road embankment is overtopped but the bridge is not highly submerged by the tailwater, the weir and pressure method should be used. 4. When the bridge is highly submerged and is not acting as a weir the energy method should be used.

4.2 Computing culvert capacities A culvert is a short closed conduit which connects two open-channel segments or bodies of water. Culverts are often used for leading streams and small rivers through road embankments. Insufficient culvert capacity may result in a high upstream water level and overtopping flow which damages the road embankment.

This section discusses the computation of culvert capacity in general and the computational method used in HEC-RAS. A computer program for simplified culvert computation that was developed during this project is also discussed.

4.2.1 Culvert types Common culvert types are circular pipe culverts or box culverts. Smaller culverts are often in the form of a pipe placed through the road embankment. Pipes of plastic, concrete or corrugated steel are frequently used. The choice of material depends on dimensions, earth pressure, corrosion danger etc. Box culverts are used for larger discharges. They are mostly built in concrete, but many old box culverts are made of masonry.

4.2.2 Culvert hydraulics “An exact theoretical analysis of culvert flow is extremely complex because the flow is non-uniform, with regions of both gradually and rapidly varying flow. An exact analysis involves backwater and draw down calculations, energy and momentum balance, and application of the results of hydraulic model studies. ”

“Hydraulic Design of Highway Culverts” (Normann et al. 1985)

There are six main flow situations through a culvert as sketched in Figure 4-4. Several intermediate flow situations also exist. Details may be found in “Hydraulic

28 4. Hydraulic computations

Design of Highway Culverts” (Normann et al. 1985), “Open Channel Hydraulics” (Chow 1973) or (French 1987). To simplify the analysis the concepts of inlet control and outlet control are often used.

A complete flow-capacity calculation involves computation of both inlet and outlet control headwater for several flow situations and is normally done by the aid of a computer programme. Nomograms are available for computing the capacity of culverts with inlet control or full flow (Nordal 1988; Berg et al. 1992).

4: Submerged outlet

3: Tranquil flow 6:Full flow free outlet

Figure 4-4: Classification of culvert flow

Culverts with inlet control Inlet control occurs when the carrying capacity of the inlet is less than the capacity of the barrel. This normally occurs in smooth or steep culverts with low tailwater levels. Inlet control is defined by three regions of flow: 1) un submerged weir flow, 2) transition and 3) orifice flow. How situations 1 and 5 in Figure 4-4 are examples of inlet control. The transition from free surface to orifice flow occurs when the headwater depth is approximately 1.5 times the culvert height.

For inlet control the flow capacity is determined by the approach flow, the upstream water depth, the inlet geometry and the culvert bed slope. Model tests have been

29 4. Hydraulic computations used to define the flow control curves for a wide range of culvert shapes (Normann et al. 1985).

Culverts with outlet control Outlet control occurs when the culvert capacity is controlled by the tailwater conditions or the barrel capacity. This typically happens in long culverts with a rough surface and flat slope, or if the tailwater level is high. Outlet control includes flow situations 2, 3,4, 6 in Figure 4-4.

All the factors that influence inlet control also influence the performance of a culvert in outlet control. In addition the barrel characteristics and tailwater elevation also affect culvert capacity. Outlet control conditions are normally calculated on the basis of energy balance. The total loss of energythrough the culvert is made up of the entrance loss, the friction losses through the barrel and the exit loss. In addition it may be necessary to include losses at screens, singular losses at contractions or expansions, and losses at bends. A water profile calculation for the downstream reach may be needed as a starting point for calculating culvert capacity.

Culvert capacity computations using HEC-RAS Culvert computations are complicated and time-consuming and are normally done by a computer program. This section describes the culvert procedure used by HEC- RAS (HEC 1997b).

Computing inlet control headwater Two situations of inlet control may exist: 1) submerged and 2) un submerged inlet. HEC-RAS uses inlet control equations developed by the Federal Highway Administration (Normann et al. 1985) that are based on extensive laboratory tests. The equations are not dimensionally correct.

Un submerged inlet: Y + Y + 2 g 2 8 Q (4-3) + *i -0.5 S n D D AD 0.5 Submerged inlet: Y +& (4-4) = K. ( Q ) + y-0.55 n D AD 0.5 where: U = Velocity of approach flow, fps Uc = Flow velocity at critical depth, fps Y = Headwater depth above the invert at the culvert inlet, ft Yc = Critical depth, ft

30 4. Hydraulic computations

D = Diameter of culvert barrel, ft Q = Discharge through the culvert, cfs A = Full cross-sectional area of the culvert barrel, ft2 So = Culvert barrel slope, - Ki, K2, P = Equation constants depending on culvert shape and entrance conditions

Computing outlet control headwater The energy equation is used to compute the upstream water level for outlet control. Entrance losses, friction losses and exit losses are considered. Several possible tailwater conditions and flow conditions in the culvert barrel must be taken into consideration during the computation. The flow chart in Figure 4-5 illustrates the logic of the computations (HEC 1997b).

For culverts flowing partially full the surface profile in the culvert is computed using the direct step method. The profile computations start inside the culvert at the downstream end. The first step is to determine the starting water depth at the downstream end of the barrel. If the tailwater depth is less than the critical depth the starting condition inside the culvert is assumed to be critical depth. If the tailwater depth is greater than the critical depth an energy balance is performed to determine the starting water surface inside the culvert. The profile computations continue to the upstream end of the culvert barrel or until the water surface reaches the top of the barrel. In this case energy loss through the remaining culvert reach is computed assuming full flow.

Assessingthe type of flow The headwater is computed for both inlet and outlet control and the control that gives the highest upstream energy level controls the flow. If the inlet control answer comes out higher than the outlet control answer the program checks if this flow situation can actually exist. If a hydraulic jump will form inside the barrel, and the jump will fill the entire height of the barrel, it is assumed that the barrel will be pressurised and the outlet control answer is used.

31 4. Hydraulic computations

M2 Drawdown: M2 Drawdown: Compute inlet Compute inlet depth by direct depth by direct step method, step method, starting with starting with tailwater depth critical depth Upstream energy = Inlet energy + entrance loss

Figure 4-5: Flow chart for outlet control computations (HEC 1997b)

32 4. Hydraulic computations

Figure 4-6: Culvert inlet section

4.2.3 CULVCAP: A program for rapid assessment of culvert capacity The case study involved flood hazard evaluation at a large number of highway culverts. Often the parameters of importance for culvert capacity were difficult to estimate because of non-traditional culvert design (Figure 4-6) or deterioration of the culvert. This warranted a capacity computation that could be used with a minimum of input data and in which the uncertainty in input parameters could be rapidly evaluated.

In the course of this work a computer program for computing culvert capacity charts was developed. It was coded into a spreadsheet using the Visual Basic programming language. The program calculates culvert capacity for the most important flow situations in both circular and box culverts: 1. Uniform flow in the culvert. 2. Free flow inlet control. This is flow situation 1 in Figure 4-4. Inlet control was computed assuming critical flow at the culvert inlet. For circular culverts the

33 4. Hydraulic computations

critical flow depth was calculated using an empirical critical depth formula ((Straub 1982) in (French 1987)). When the headwater level exceeded 1.5 culvert diameters the inlet was assumed to become submerged. 3. Submerged inlet control. This is flow situation 5 in Figure 4-4. The inlet capacity during orifice flow depends mainly on the edge geometry and the submergence ratio. Depending on the rounding the inlet may be considered sharp-edged or rounded. Rounding of the inlet has a major influence on the culvert capacity and must be taken into account in the computations. The program calculates the capacity for both sharp-edged and the well-rounded culvert inlets. The culvert inlet is assumed to be flush in the headwall. The submergence ratio also has a considerable influence on culvert performance and was accounted for by fitting a second-order polynomial to a table of culvert discharge coefficients ((Bodhaine 1976) in (French 1987)). The polynomial was used to compute the discharge coefficient for sharp-edged and well-rounded culvert inlets as a function of headwater depth. 4. Outlet control with full flowing barrel and un submerged outlet. This is flow situation 6 in Figure 4-4. The energy head is computed by balancing headwater energy level with inlet loss, friction loss and outlet loss.

The capacity is computed for a range of headwater levels as specified by the user. The capacity curve is calculated for each of the flow situations mentioned above. Computational results are presented in the form of capacity tables and curves as shown in Figure 4-7.

The user must decide which flow situation exists, and thus which curve to use. The highest energy answer controls the upstream head and the flow situation is found by comparing the capacity curves for inlet control and outlet control. By using the capacity curves and comparing different flow situations the user can rapidly assess the effect of changes in input parameters or flow situations.

CULVCAP is not suitable for flow situations with submerged outlets or for outlet control with free surface flow in the culvert barrel. For the extreme floods considered in the case study (Chapter 9) the inlet was often submerged while the outlet had free flow, and CULVCAP proved to be an efficient tool for assessing capacities.

34 4. Hydraulic computations

Culvert capacity calculations with CULVCAP

Culvert data: L = 15 m D = 0.6 m G 1 • n = 0.013

O 0.8 -

Headwater or depth of flow in barrel, Y (m)

Free flow inlet control -e-Submeged Inlet control, square edge Submeged Inlet control, rounded Full flow outlet control -e-Uniform flow

Figure 4-7: Sample results from CULVCAP

4.3 Estimating roughness coefficients An important task when calculating water surface profiles in gradually varying flow is that of estimating the friction. The friction is most often described with the Manning's friction factor, n. This Section discusses methods for estimating the Manning's friction factor.

Friction losses may be broadly divided into friction caused by the boundary roughness (skin friction) and friction caused boundary irregularities (form friction). For most practical applications they are not treated separately. Instead a single coefficient is used to describe total friction, i.e. Manning ’s n. Manning ’s n is highly variable and depends on a number of factors of which the most important are: surface roughness represented by the size and shape of the grains along the perimeter, vegetation on the banks and floodplains, channel irregularity that causes variations in shape and size of the cross-section and changes in channel alignment due to curves and bends.

The stage and discharge may also have important effects. Normally n decreases with increasing discharge. However, the presence of floodplains may increase the roughness dramatically when the stage exceeds bankfull.

Three methods can be used to estimate the roughness factor: 1) engineering judgement, 2) empirical formulae, 3) field observations.

35 4. Hydraulic computations

4.3.1 Engineering judgement Values of the roughness coefficient are taken from tables. Selection of the appropriate coefficient can be helped by the use of pictures showing typical cross- sections and their roughness coefficient. Tables and pictures can be found in (Chow 1973) or (French 1987).

Cowan ((Cowan 1956) in (Chow 1973)) developed a procedure for estimating the value of n. First a base value n for a straight uniform smooth channel is selected. Then correction factors are applied to account for factors affecting n, i.e. vegetation, variation in cross-section and alignment, irregularities and obstructions. A similar method was suggested by the US Soil Conservation Service and is described in (French 1987).

4.3.2 Empirical formulae Empirical formulae are important in that they reduce the subjectivity of the assessment procedure. Several have been suggested, some of which are shown below (metric units).

(4-5) n = 0.047d™ (Stickler)

0.1137?1/6 (4-6) ""l.!6 + 2.01og(^) (Limerinos)

(4-7) n = 0.325°'38 /?"°16 (Jarrett)

(4-8) n = 0.104S°177 (Bray) where: n = Manning's friction factor, s/mm d50 = Particle diameter for which 50 % by weight of sediment is finer, m dg4 = Particle diameter for which 84 % by weight of sediment is finer, m R = Hydraulic radius, m Sf = Friction slope, -

In Stickler's formula (4-5) Manning ’s n is taken as a function of bed particle size only. Several versions of the equation exist, and there seems to be considerable uncertainty about the conditions from which it was derived (French 1987). Equation (4-5) is given by Subramanya ((Subramanya 1982) in (French 1987)).

36 4. Hydraulic computations

Limerinos (1970) formula (4-6) is based on data from 50 measurements made at 11 river reaches in California. Slopes ranged from 0.00068 to 0.024 and the flow ranged from low to Qa, the flood with a two-year recurrence interval.

Jarrett (1989) investigated flow in steep rivers. He made 75 measurements in 21 river reaches with slopes 0.002 - 0.054. Jarrett found that n is considerably higher in steep rivers than in mildly sloping rivers with the same relative roughness. Jarrett states that most engineers underestimate the roughness coefficient in steep rivers.

Bray (1982) collected roughness data from 67 gravel bed reaches in Alberta where slopes ranged from 0.0002 to 0.015 and the flow was approximately Qa. Bray used his data to investigate the performance of several of the predictive formulae. Stickler’s formula showed the poorest performance, and was not statistically significant even at the 1 % level. Limerinos ’ formula performed best of the formulae investigated. Cowan ’s method using engineering judgement gave almost the same results as Limerinos ’ formula. Jarrett’s formula was not tested. A simple power function (4-8) with the slope as parameter explained the data better than any of the other formulae and was suggested by Bray (1982).

Ugarte and Madrid (1994) used data from 19 Chilean rivers to evaluate roughness formulae. Stickler’s formula performed poorly with an average error of 45 %. By optimi sing the coefficient the error could be reduced to 15 %. Limerinos ’ formula gave an average error of 15 % and could not be improved further. Jarrett’s formula showed an average error of 19 %.

Wahl (1994) investigated the effect of flow rates on the results of several formulae. He subdivided his data into low flow, medium flow and high flow based on the ratio Q/Qm Qm being the median annual peak discharge. All formulae underestimated n at low flow. For average and high flow Limerinos ’ formula showed no bias. Jarrett’s formula overestimated n by 10 % on average. Bray’s formula was not tested.

4.4 Summary and recommendations This chapter has reviewed and discussed several subjects of importance for computations of water surface profile. The computation of gradually varying flow and two common situations of rapidly varying flow through bridges and culverts have been discussed. The development of a computer program, CULVCAP, for rapid culvert capacity assessment has been demonstrated and discussed. Finally methods for assessing the Manning ’s n was reviewed.

During the case study two methods were used for assessing Mannin g’s n. First n was estimated using tables and pictures. Second, Equation (4-8) was used to

37

r-c- 7^ 4. Hydraulic computations calculate n. The average of the two methods was used for the main river channel. Only tables and pictures were used to assess the value of Manning ’s n on the floodplains.

The review in this chapter formed an important basis for the hydraulic computations performed during the case study. However, it is not feasible to compile a list of specific guidelines. The topic is too wide and the situations encountered when performing a practical analysis are too many. However, two general recommendations can be made: 1. The engineer performing the hydraulic analysis must have a good understanding of the physical processes involved. 2. The engineer must have a detailed understanding of the computational model being used, its capabilities and its limitations.

38 5. Scour and sediment transport

5 Scour and sediment transport Damage due to scour is common during floods. Typical types of damages include: bridge failures caused by scour around piers and abutments, bank failures and failures of levees due to internal erosion or scour by overtopping flow. Assessing the potential for scour damage is an important part of evaluating vulnerability to floods. Several questions need to be answered: 1) at what flow rate will scouring start, 2) what will be the extent of scouring and 3) how fast will it develop? In this chapter several scour assessment methods are reviewed, and an approach to estimating scour damage is suggested.

Scour may be divided into three main types: 1) general scour, 2) contraction scour and 3) local scour. Scour may also be classified according to the sediment transport situation: 1) dear-water scour and 2) live-bed scour. Clear-water scour occurs if the bed material upstream of the scour area is at rest. Live-bed scouring occurs if there is general erosion of the bed upstream. Sediment transport into the scour area will then limit scour depths. For clear-water conditions the scour is not reduced by inflow of sediments and greater scour depths may result.

5.1 General scour in uniform flow This section reviews methods for assessing riprap stability in uniform flow, scour in cohesive soils and scouring of vegetated slopes.

General scour occurs when the flow is uniform and the stream forces on the flow boundary are constant in the direction of flow. Uniform scour in granular material has been widely studied using laboratory flumes. Three approaches to estimating the initiation of motion are discussed in the following sections: 1) the shear stress approach, 2) the velocity approach and 3) the stream power approach.

5.1.1 The shear stress approach to initiation of motion

The critical shear stress, Tc, is the shear stress above which the bed particles become unstable and start to move with the flow. By use of dimensional analysis (Vanoni 1977) it may be shown that the critical dimensionless shear stress, t*c, is a function of the particle Reynolds number: = /(^) (5-1) (Ys ~7 )d where: Tc = Critical shear stress T* c = Critical dimensionless shear stress, Shields' parameter U* c = Critical shear velocity y s = Specific weight of sediment

39 5. Scour and sediment transport y = Specific weight of water v = Kinematic viscosity d = Characteristic diameter of sediment particle

On the basis of data from Shields and others, Rouse showed this relationship graphically in what is known as Shields' diagram. The critical dimensionless shear stress, T* c, called Shields' parameter, was assumed to have a constant value of 0.056 for particle Reynolds number R* > 1000. Later research suggests that the Shields' parameter is not constant. By using data from tests in flumes with a steep slope (0.0 < So < 0.2) Graf and Suszka (1987) found xc to be a function of the bed slope and suggested using:

(5-2) T* c =0.042-lO2'250 where: T* c = Shields' parameter S0 = Slope of channel bottom

Kilgore and Young (1993) used riprap stability data from several sources and found that t*c was not constant for Froude numbers larger than 0.8, and suggested using: (5-3) T*c= 0.052F2-1 + 0.05 FM).8 where: T*c = Shields' parameter F = Froude number

In “Evaluating Scour at Bridges, Hydraulic Engineering Circular No. 18" (HEC-18) (Richardson and Davis 1995) it is stated that the Shields' parameter ranges from 0.01 to 0.25 and is a function of bed material size, Froude number and size distribution. Typical values of Shields' parameter as a function of bed material size are (Richardson and Davis 1995) 0.047 for sand (0.065 mm < d50 < 2 mm), 0.03 for medium coarse bed material (2 mm < dso < 40 mm) and 0.02 for coarse bed material (d50 > 40 mm). Here d50 is the particle diameter for which 50 % by weight of sediment is finer.

The Shields' parameter will also depend on the shape of the bed material. Angular rock is known to be more stable than rounded. Wittier and Abt (1990) found that well graded riprap was less stable than poorly graded riprap, but when graded riprap fails it does so over a period of time. The poorly graded riprap fails very suddenly.

In order to size riprap it is necessary to know the shear stress distribution. Shear stress distributions from investigations using membrane analogies are shown in several textbooks (Chow 1973; French 1987). The distributions are only valid for

40 5. Scour and sediment transport laminar flow. Shear stress distributions measured in turbulent flow (for example (Ghosh and Roy 1970) in (Chao-Lin 1985) or (Maynord 1990)) are significantly different and should be used when sizing riprap.

Riprap placed on a sloping bank is less stable than on a fiat bed. The traditional approach to sizing riprap on a sloping bank is to compare critical tractive-force on the slope and on the bed (Chow 1973). This approach yields the tractive-force ratio, K. The tractive-force ratio expression normally found in most text books is based on invalid assumptions and should not be used (Lysne 1987). A curve based on experiments and experience is suggested in its place (Lysne 1987).

Shear stress distribution in river bends River curvature has a significant influence on shear stress distributions. The most important parameter in determining the shear stress distribution is the relative curvature which is defined as the ratio of bend curvature to stream width, rcAV (Chen and Shen 1983). For r 3.5 maximum shear stresses stay close to the outer h ank throughout the entire stream bend, and maximum to average shear stress ratios may exceed 1.6. When tJW decreases the maximum shear stress ratio increases and moves toward the inner bank. Shear stress measurement in channels and natural rivers seem to produce higher maximum shear stress ratios than observed in flumes (Chen and Shen 1983; Dietrich et al. 1983). This may be due to the formation of bars that direct flow towards the outer bank (Maynord 1993).

5.1.2 The velocity approach The initiation of motion may be related to flow velocity rather than shear stress. Dimensional analysis shows that velocity and stable bed material size in rough flow are related by the dimensionless groups (Neill 1967):

(5-4) | = C where: d = Characteristic diameter of sediment particle Y = Depth of water U = Flow velocity g = Acceleration of gravity Ss = Specific gravity of sediment C, P = Dimensionless parameters that must be found through experiments

Several authors have suggested functional relationships between the two groups (Neill 1967; Maynord et al. 1989; Maynord 1993; Escarameia and May 1995). The Izbash equation uses p = 1. Escarameia and May (1995) uses P = 1. Combining the

41 5. Scour and sediment transport

Shields' parameter, the Manning formula and Stickler’s formula for n gives (3 = 1.5 (Maynord et al. 1989). P = 1.25 is used in the Corps of Engineers (COE) guidelines (Maynord et al. 1989; Maynord 1993).

Several definitions of the relevant velocity have been used. The Izbash equation uses a near-bed velocity, Neill (1967) used average velocity and local depth- averaged velocity is used in the COE guidelines (Maynord 1993). Escarameia and May (1995) compared local depth-averaged velocity and point velocity measured 10 % of the depth above the bed and found that the point velocity gave the best results.

The COE guidelines (Maynord 1993) recommends the following expression for assessing riprap stability: 2.5 \U2 uv (5-5) ^30 — CfCsCyCTY 7s-r ■J^gr where: d3o = Particle diameter for which 30 % by weight of sediment is finer Uy = Local depth-averaged velocity Y = Depth water y s = Specific weight of sediment y = Specific weight of water Cf= Safety factor Cs = Stability factor for incipient failure (0.30 for angular rock, and 0.375 for rounded rock) Cy = Vertical velocity distribution coefficient Ct = Blanket thickness coefficient Ks = Side slope factor

On the basis of point velocity, ub , Escarameia and May (1995) found the best fit equation for normal turbulence levels: 2 (5-6) 0.36-----^------2g(S,-l) where: d„ = Size of a cube which has the same weight as d50 ub = Point velocity 10 % of the depth above the bed Ss = Specific gravity of sediment (dso = Particle diameter for which 50 % by weight of sediment is finer)

42 5. Scour and sediment transport

The local depth-averaged velocity may be easier to assess than the point velocity and Escarameia and May (1995) suggested the following equation which uses local depth-averaged velocity: ' 0.075t/ y2 \0.78 (5-7) 2g(^-i)y > where: dn = Size of a cube which has the same weight as d5o Y = Depth of water Uy = Local depth-averaged velocity Ss = Specific gravity of sediment (dso = Particle diameter for which 50 % by weight of sediment is finer)

Equation (5-7) is valid for normal turbulence levels and side slopes not steeper than 1:2.5. Equation (5-6) is preferred to (5-7) as it fits the results more closely and is valid for all side slopes tested (Escarameia and May 1995).

An important problem when using velocity-based methods is that of estimating the relevant velocity. Various methods have been suggested (Maynord 1993): two- dimensional numerical models, physical models, empirical methods, analytical methods and the use of prototype data.

5.1.3 Stream power and credibility index method A method suggested by Annandale (Annandale 1995; Annandale and Parkhill 1995; Smith and Annandale 1995) uses a relationship between the erosive power of water and a geo-mechanical material classification system known as the credibility index to predict scour in a wide range of materials. The erosive power of water is expressed as the energy dissipation per unit width of flow and is called the stream power. At the credibility threshold, the stream power and the capacity of rock and earth material to resist erosion can be expressed as: (5-8) ? = /(&*) where: P = Stream power (energy dissipation per unit width) Kh = Erodibility index.

The erodibility index is a dimensionless number: (5-9) where: Kh = Erodibility index. Ms = Mass strength number

43 5. Scour and sediment transport

Kb = Block/particle size number K

Analyses of 150 field observations and published data on initiation of motion have been used to establish the credibility threshold. The credibility thresholds of various materials are shown graphically in (Annandale 1995), and methods for estimating stream power for special flow situations are discussed in (Annandale 1995; Annandale and Parkhill 1995).

5.1.4 Stream bed armouring The Shields' curve and other expressions for the initiation of motion apply to uniform sediments, but most river gravels have a broad size distribution which results in the formation of an armour layer on the bed surface. The finer grains are removed from the bed while the larger are left and form a coarse protective layer. When the shear stresses exceed the critical value, however, the armour layer will become unstable and break up.

The limiting armour formation is reached when u7U* ac > 0.9 (Breusers and Raudkivi 1991). U* is the shear velocity and U* ac is the critical armour shear velocity. In the limiting case the ratio of d^ax/dsoa approaches a lower limit of 1.8 and the size distribution of the armour layer is close to uniform (Breusers and Raudkivi 1991). d^ is the maximum particle diameter of the bed sediments and d50a is the particle diameter for which 50 % of the sediment in the armour layer is finer by weight.

Armour layers often form in the gravel-bed rivers that are common in Norway. As long as the armour layer is stable it will prevent or reduce sediment transport. During heavy floods the shear stresses may exceed the critical value for the armour layer, resulting in a rapid change from the normal dear-water situation to a situation characterised by extremely large bed transport. Rivers that only carry an insignificant bed load during normal floods may completely change their behaviour if the protective armour cover is destroyed, resulting in large and rapid changes in the river cross-section and alignment.

5.1.5 Cohesive material Soil with more than 10 % clay content is dominated by the cohesive properties of the clay. Erosion in cohesive materials is not well understood, and we lack methods for calculating the threshold of erosion. Some attempts have been made to relate critical shear stress to such parameters as the index of plasticity, pressure strength or clay content, but the results have not been conclusive. Several approaches are discussed in “Sedimentation Engineering ” (Vanoni 1977). Table 5-1 shows critical

44 5. Scour and sediment transport

shear stress and velocity for different cohesive soils as given by Lane ((Lane 1952) in (Dodge 1988)).

Scour in clay and silts will reach the same depths as in sand-bed streams. The effect of cohesion is to influence the time it takes to reach maximum scour. With sand-bed material maximum scour may develop in the course of a few hours, while with cohesive bed material it may take much longer to reach the maximum scour depth (Richardson and Davis 1995).

Table 5-1: Limiting velocities and shear stresses in cohesive materials ((Lane 1952) in (Dodge 1988)) Compactness of sediment bed Loose Fairly compact Compact Limiting velocities and limiting shear stress Material Pa m/s Pa m/s Pa m/s Sandy clays (sand 1.9 0.45 7.5 0.9 30.1 1.8 content < 50 %) Lean clayey soil 1.0 0.3 4.6 0.7 16.9 1.4 Heavy clayey soil 1.5 0.4 6.8 0.9 27.0 1.7 Clay 1.2 0.4 5.9 0.8 25.4 1.6

5.1.6 Erosion on vegetated slopes It is often necessary to evaluate the degree of protection provided by grass and bushes that form a protective cover on surfaces that will be subjected to flow.

Vegetation has several effects. It increases boundary roughness and decreases water velocity. Grass will bend with the flow and form a protective cover while its root system reinforces the soil and binds it together. The protection provided depends on grass type and density. For plain grass the erosion resistance is considered in terms of the hydraulic loading parameters of 1) velocity and 2) duration of flow. Design values have been suggested in (Hewlett et al. 1987).

The hydraulic roughness of the vegetation cover is needed to estimate the flow velocity. The roughness of a grass cover depends on the flow. When the flow depth or velocity increases the vegetation bends with the flow, reducing flow resistance. For slopes flatter than 1:10, n should be estimated using the VR method (Chow 1973; Hewlett et al. 1987). In the VR method n is estimated on the basis of flow velocity (V) and hydraulic radius (R). For steeper slopes the grass tends to be laid flat and n becomes less dependent on the hydraulic loading, n = 0.03 is suggested for slopes 1:10 and n = 0.02 for slopes steeper than 1:3 (Hewlett et al. 1987).

45 5. Scour and sediment transport

5.2 Scour in constrictions Contraction of the flow area results in increased velocity, increased shear stresses and scouring of bed material. There are two forms of contraction scour: 1) dear- water contraction scour and 2) live-bed contraction scour.

Clear-water contraction scour occurs when there is negligible sediment transport from upstream. The scour will continue until the shear stress falls below the critical shear stress of the bed material. Normally the width of the contraction is constricted, with the result that the depth will increase until equilibrium is reached. Scour depth may be calculated by finding the cross-sectional area so that t = xc.

Live-bed contraction scour occurs when there is transport of bed material into the constriction from upstream. The cross-section will scour until the sediment inflow equals the sediment outflow. “HEC-18 ” (Richardson and Davis 1995) recommends a modified version of Laursens 1960 equation for predicting the scour depth: 6/7 "e2~ Wi" P (5-10) r, LaJ kJ where: Yi = Average depth in the upstream main channel Y2 = Average depth in the contracted section Qi = Flow in the upstream channel transporting sediment Qa = Flow in the contracted section Wi = Bottom width of the upstream main channel W2 = Bottom width of the contracted section, less pier widths P = Exponent depending on the mode of bed material transport

Coarse sediments armouring the bed may limit scour depths. If coarse bed material is present "HEC-18" (Richardson and Davis 1995) recommends that the scour depths should be calculated for both the clear-water and the live-bed situation, and the lesser value used.

5.3 Local scouring Local scour results directly from the interaction of structure and flow. The local scour situations discussed in this section are, scour at bridge piers, scour at abutments and scour below culvert outlets.

Local scour introduces one or two more spatial dimensions than general scour. For this reason, investigation of local scour is much more complex. Although extensive data have been published on local scour, large divergences exist. When applied to the same situation different equations may give results that differ by several hundred percent.

46 5. Scour and sediment transport

Many authors use different, non-comparable variables to explain the same phenomena. Some authors omit variables that other authors have found to be important. It may thus be very difficult to compare equations and explain differences between different authors.

Further problems arise when projecting experimental results to real-life situations. Most local scour formulas have been derived from small-scale flume tests and have not been verified in the field.

5.3.1 Scour at bridges Scour at bridges during floods is a serious problem. Scouring destroyed 23 important bridges during the record flood in Mississippi in 1993. Roods resulting from the tropical storm Alberto damaged 500 bridges in Georgia. A survey of 384 bridge failures in the USA attributed 25 % of the failures to pier scour and 72 % to abutment scour (Richardson and Davis 1995).

Assessing the potential scour damage to bridges caused by heavy floods is important in the evaluation of total flood hazard. The following discussion is based largely on “Evaluating Scour at Bridges” (HEC-18) (Richardson and Davis 1995) which gives a thorough, up-to-date, review of methods of calculatingscour.

Total scour at brides is comprised of four components: 1. Long term aggradation and degradation 2. Local scour at piers and abutments 3. Scour caused by constriction of the flow area 4. Lateral migration of the stream

In addition, eddies that form downstream of the bridge contraction may scour the riverbed and the abutment slope.

Total scour depth is normally estimated as the sum of the individual components. This section discusses the first three components listed above, focusing mainly on pier and abutment scour. Scour in constrictions was discussed in Section 5.2.

Long-term channel aggradation or degradation Natural processes and human activity cause long-term changes in streambed elevation. Increased sediment supply from farming, deforestation and road construction may cause river aggradation. Excavation of gravel is probably the most common cause of riverbed degradation in Norway. Degradation may be a serious threat to the stability of bridge foundations and a flood hazard analysis should attempt to take future river-bed development into account. However, this is a

47 5. Scour and sediment transport difficult task and may not be feasible. The reader is referred to “HEC-18 ” (Richardson and Davis 1995) for further information.

Scour at bridge piers A pier in flowing water will disturb the normal pattern of flow. Water flowing down along the nose of the pier results in a horseshoe vortex forming along the base of the pier, and flow separation on the downstream side of the pier results in vertical vortexes in the wake zone. The main scouring action is caused by the horseshoe vortex that forms a scour-hole along the sides and upstream face of the pier. More detailed descriptions of flow and erosion patterns can be found in (Breusers and Raudkivi 1991) or in “HEC-18” (Richardson and Davis 1995).

Riprap stability at piers Chiew (1995) investigated the stability of a riprap layer at a circular pier. He described three failure mechanisms: 1. Riprap shear failure which occurs when the riprap stones are not large enough to remain stable and are removed by the flow. 2. Winnowing failure by removal of the underlying finer material through the voids in the riprap layer. 3. Edge failure by formation of scour-holes in the finer bed material at the outer edge of the riprap layer.

Scour at piers start at lower velocities than in undisturbed flow. Breusers and Raudkivi (1991) claim that scouring starts when U/Us > 0.5, and Chiew (1995) reports that it starts when U/Us > 0.3. U is the undisturbed approach flow velocity and Us is the critical velocity for sediment entrainment in uniform flow. A general expression for the minimu m stable riprap size may be derived combinin g Shields' parameter and Strickler’s formula: 3/2

where: k = Constant used in Strickler’s formula tc* = Shields' parameter U = Undisturbed flow velocity upstream pier U’ = Critical U/Us for the initiation of pier scorning Us = Critical velocity for sediment entrainment in uniform flow y s = Specific weight of sediment y = Specific weight of water d = Characteristic diameter of sediment particle

48 5. Scour and sediment transport

The limiting velocity ratio U/Us was found to increase as the relative thickness of the riprap layer increased, and also to rice as the area covered by riprap increased.

Chiew (1995) suggests that the velocity ratio (U/Us) at which scouringstarts should be corrected for the effect of relative sediment size and relative depth: (5-12) — = [/'=------—----- /(f)/(i) where: U = Undisturbed flow velocity upstream pier Us = Critical velocity for sediment entrainment in uniform flow B = Pier width d = Characteristic diameter of sediment particle Y = Depth of water

Equations for_/(B/d) and/[Y/B) are given by Chiew (1995) Corrections apply when the relative sediment size is large; B/d5o < 50, or the depth is small; Y/B < 3, else AB/d) =/(Y/B) =1

Parola (1993) defined a riprap stability number Nc and investigated the influence of several dimensionless quantities found from dimensional analysis: pU 2 (5-13) Nc =- (ys-y)d where: Nc = Stability number p = Density of water U = Undisturbed flow velocity upstream pier Ys = Specific weight of sediment. Y = Specific weight of water d = Characteristic diameter of sediment particle t = Thickness of riprap layer B = Pier width Y = Depth of water Ksh = Pier shape and orientation factor

For rectangular piers the relative position of the riprap above the bed surface was the most significant parameter in explaining variations in Nc. The lowest values of Nc, i.e. the lowest stability, occurred when the riprap material was placed slightly below the streambed. Smaller rocks (relative to pier width) are displaced at lower values of Nc than are large rocks. For riprap placed above the bed, Nc decreases as flow depth increases. Stability of riprap placed at or below bed level was independent of flow depth. To be stable rocks at square-nosed piers must be double

49 5. Scour and sediment transport the size of rocks at round-nosed piers. Rocks at round-nosed piers must be 2 - 4 times as large as in undisturbed flow.

Scour-hole dimensions A scour-hole will form at the base of the pier if the riprap protection is not sufficient. The scour-hole may undermine the foundations and result in subsidence or foundation failure. Expected scour-hole depth is important when assessing bridge vulnerability during flooding. Several scour-depth equations exist, but most of the data are based on small-scale flume models using narrowly graded sand as bed material under live-bed conditions. Field data for verifying model results still remain a problem.

Several factors influence scour depth: 1. Pier width. Pier width is the main factor in estimating scour depth. Scour depth increases in proportion to pier width until the pier becomes very wide (wider than 10 m (Richardson and Davis 1995)). 2. Flow velocity. Scour depth increases with flow velocity. 3. Flow depth. Increase in flow depth may increase the scour depth by a factor of two or more (Richardson and Davis 1995). 4. Pier skew and length. Scour depth may increase dramatically when a pier is skewed to the flow. If skewed, the length of the pier will influence the scour depth but if the pier is aligned parallel to the flow the pier length has no effect on scour depth. 5. Bed material. If the bed particles are small enough to be transported out of the scour-hole the size does not affect maximum scour depth. However, large particles in the bed material may armour the scour-hole and significantly reduce scour depth. Fine-grained bed material bounded by cohesion will have the same maximum scour depth as sand, but the time taken to reach the maximum depth will be much greater (Richardson and Davis 1995).

6. Pier shape. Streamlining of the pier nose reduces scour depths. Square-nosed

piers may have scour depths that are 10 % larger than those of circular piers. 7. Pier foundations. The influence of pier foundation depends on the elevation of the foundation relative to the bed. Foundations that protrude into the flow will intercept the approaching flow, thus creating stronger vortices and greater scour depths. Foundations below the bed will not affect the approach flow but they protect the bed material from erosion and reduce scour depths (Melville and Raudkivi 1996).

50 5. Scour and sediment transport

8 . Debris build-up. Debris that accumulate around piers will reduce the flow area and increase velocities. Both contraction scour and scour at piers and abutments may increase. Melville (1992) investigated the effect of a debris raft on a pier and suggested a method for calculating the effect on scour depth, but how to estimate the debris accumulation at the bridge pier remains an unsolved problem.

Equations for calculating scour depth Experiments show that scour depth is directly proportional to pier width. For circular piers the maximum scour-depth to pier-width ratio is = 2.4. Many scour depth formulas use this ratio as a base value and apply correction factors to account for conditions that are different from the base value. (5-14) Ys = 2ABK,KdKaKSHKY where: Ys = Scour depth measured from bed to bottom of scour-hole B = Pier width Ki = Flow intensity factor Kd = Sediment size factor K„ - Skew angle factor Ksh = Pier shape factor Ky = Depth factor

Breusers and Raudkivi (1991) suggest that a first-order estimate for a pier of any shape may be calculated as Ys = 2.3BKa unless detailed flow and sediment information is available.

“HEC-18 ” (Richardson and Davis 1995) recommends the CSU equation for calculating scour depth: (5-15) ^ = 2KSHK,K,Kt where: Ys = Scour depth measured from bed to bottom of scour-hole B = Pier width Ksh = Pier shape factor K„ = Skew angle factor

K3 = Bed condition factor

K4 = Factor for armouring of bed Y = Depth of water upstream pier F = Froude number for the approach flow

51 5. Scour and sediment transport

Based on field observations in coarse bed channels Froehlich and Ameson (1995) suggested the scour depth equation: (5-16) ^ = 2AKvKYKd D where: Ys = Scour depth measured from bed to bottom of scour-hole B = Pier width Ku = Clear-water condition factor KY = Relative depth factor Kd = Relative bed material size factor

By using data from 64 field observations of scour depths at circular piers in coarse bed channels, he found the best-fit relation for the correction factors. Equation (5-16) is interesting for two reasons. It is a best fit expression and thus mores suitable for predicting scour depths than the enveloping equations used for design, and it is based on data from rivers with coarse bed material (8 mm < d < 150 mm) which are common in Norway.

Comparison with field data Johnson (1995) compared seven common scour depth equations with actual field data. The data contained a total of 515 data points covering a wide range of flow and sediment situations. All equations yielded maximum ratios of calculated scour to measured scour larger than five. The large biases typically occurred at low flow depths (YZB < 1.5) and in the transition from clear-water to live-bed scour (0.7 < U/Us < 1.2). In most cases the CSU equation overpredicted the scour depths by a factor of 1.2 - 3. Only for seven of the data points did the CSU equation predict scour depths of less than 50 % of what were observed. The comparison did not include the equations suggested in (Breusers and Raudkivi 1991) or by Froehlich and Ameson (1995) (5-16). The field data did not include sediment gradation, and uniform sediments were assumed in all cases.

Scour at abutments Abutment scour is caused by the convergence of flow from the channel and floodplain at the abutment end. Thus flow conditions in both the channel and floodplain are important in assessing abutment scour, which makes this type of scour far more complicated than pier scour.

A great deal of experimental data has been published, mainly from small-scale flume investigations with sand-bed channels. It has, been claimed that several of these investigations fail to account properly for channel-floodplain interactions (Richardson and Richardson 1993). There are few field data available to confirm the scour depth equations that have been proposed, but what there are indicate that

52 5. Scour and sediment transport the equations predict excessively great scour depths (Richardson and Richardson 1993).

Stability of riprap at abutments Data on riprap protection of abutments are scarce. Atayee (1993) investigated riprap as scour protection for spill-through abutments in a flume. The riprap apron comprised two layers of uniformly graded gravel protecting the end of a spill- through abutment. The length of the abutment had no influence on the location of the failure zone. Atayee found the best-fit equation of initiation of motion, in metric units: 0.6y 0.27 ll.99n2U/8 6 Icf (5-17) ^50 - 0?, "I) where: dso = Particle diameter for which 50 % by weight of sediment is finer, m n = Manning's friction factor, s/m1/3 UCf = Depth-averaged velocity on contracted floodplain, m/s Ycf = Average flow depth on contracted floodplain, m Ss = Specific gravity of sediment, - g = Acceleration of gravity, m/s2

Atayee (1993) found that neither the length of the abutment nor the proximity to the main channel significantly influenced the stability of the riprap.

Atayee et al. (1993) compiled results from tests on both spill-through and vertical wall abutments. On spill-through abutments the failure zone always developed at the toe of the abutment just downstream of the abutment centreline and progressed downstream, while in vertical wall abutments the failure zone was located at the toe upstream of the centreline. For Froude numbers, F < 0.8 the following design equation was suggested for both vertical wall and spill-through abutments: dso _ K Ul_ (5-18) Ya (Ss-l)[gY a where: dso = Particle diameter for which 50 % by weight of sediment is finer Ya = Row depth at abutment toe Ua = Row velocity at abutment toe Ss = Specific gravity of sediment K = 0.89 for spill-through abutments K = 1.02 for vertical wall abutments

53 5. Scour and sediment transport

For F > 0.8 Atayee et al. (1993) recommended:

■10.14 K (5-19) "50 ______EL gY a where: K = 0.61 for spill-through abutments K = 0.69 for vertical wall abutments.

Both equations are design equations that envelop most of the data and which overpredict d# up to 500 percent.

Scour depth at abutments Several methods for estimating scour depths at abutments have been published, but it is generally recognised that most equations predict excessive scour depths. "HEC- 18" (Richardson and Davis 1995) recommends the following equation as a check on the potential scour depth, Ys, for the live-bed condition: 0.43 Fo.6i +1 (5-20) = 2.21 K,K 2 Yf where: Ys = Scour depth measured from bed to bottom of scour-hole Yf = Average flow depth on floodplain Ki = Factor for abutment shape

K2 = Factor for abutment angle L = Length of abutment projected normal to flow F = Fronde number for approach flow upstream of the abutment

The 1 was added as a penalty term to encompass 98 % of the 170 data points.

Melville (1997) published a comprehensive work on pier and abutment scour. The scour depth is calculated by applying correction factors to a base maximum scour depth: (5-2i) % = where: Ys = Scour depth measured from bed to bottom of scour-hole KY = Characteristic depth with the dimension length Kj = Flow intensity factor also including the effects of sediment gradation Kd = Sediment size factor, Ksh = Shape factor Kq , = Alignment factor Kg = Channel geometry factor

54 5. Scour and sediment transport

Curves, tables or equations for estimating the K values are given by Melville (1997). It should be noted that most are enveloping curves that result in an average overprediction of scour depth.

5.3.2 Scour at culvert outlets Large scour-holes may develop below culvert outlets and damage the culvert foundation. The development of a large scour-hole may also threaten the stability of the road embankment, resulting in the road embankment sliding into the hole. This section reviews methods of predicting scour depth below culvert outlets.

Evaluating scour generally involves an assessment of the riprap stability and, if the riprap is not considered stable, an assessment of the dimensions of the scour-hole that will develop. In the case of scour-holes below culverts the shape of the scour- hole and the stability of the riprap lining are very closely related. Large riprap is needed to protect a flat bed below a culvert outlet, but if a moderate scour-hole is allowed to form the riprap needed to protect it from further erosion will be considerably smaller than for a flat bed.

Most information on scour below culverts comes from small-scale experiments using narrowly graded sand. Some field data exist, but the hydraulic conditions (discharge, duration) that have caused the observed scour are often not reported.

D +

+

Figure 5-1: Culvert scour definition sketch

By using dimensional analysis and omitting viscous effects Lim (1995) expressed relative scour depth as:

where: Zs = Scour depth measured from culvert invert D = Diameter of culvert barrel

55 5. Scour and sediment transport

CTg = Geometric standard deviation of the grain size distribution W = Downstream channel width Ztw = Tail water elevation measured from culvert invert Fd = Densimetric Froude number (defined below) dso = Particle diameter for which 50 % by weight of sediment is finer

U (5-23) where: Fd = Densimetric Froude number U = Flow velocity Ss = Specific gravity of sediment dso = Particle diameter for which 50 % by weight of sediment is finer

An evaluation of the different parameters reveals that: • The densimetric Froude number expresses the flow strength and together with the relative sediment size is the most influential factor. • The influence of sediment grading still seems unclear. Breusers and Raudkivi (1991) concludes that gradation only influences scour depth at low outlet velocities. Investigating riprap on a flat bed, Shafai-Bajestan (1993) found well- graded riprap more stable than narrowly graded riprap with the same d50. In general, it should be expected that well-graded material would armour the hole and reduce scour depths as long as the threshold velocity for the armour is not exceeded. • Lim (1995) found that the relative downstream channel width had little influence on culvert scour. • The relative tailwater elevation defines the impact of the jet on the bed and is an important parameter.

Influence of the tailwater depth Rice and Kadavy (1994b; 1994a; 1995) found that four situations of tailwater elevation could be distinguished: 1. High plunge (Ztw/D<-1). The tailwater level is more than one culvert diameter below the culvert invert and the jet will attain a relatively large vertical velocity component before it reaches the tailwater surface. From the surface it will follow a straight line and impinge on the bed directly and at a steep angle. 2. Low plunge. (0> Ztw /D>-1) When the culvert invert is between the surface and one culvert diameter above, the jet will still plunge into the pool but with less vertical momentum.

56 5. Scour and sediment transport

3. Partly submerged outlet (0< Zxw /D<0.7). The jet will be partly supported by the water in the plunge pool, float for a greater distance and dissipate more energy close to the surface than in the previous cases. 4. Fully submerged outlet (Zrw/D>0.7) The jet is fully supported and the core velocity remains intact for a considerable distance, but does not impinge on the bed. However, turbulent mixing and energy dissipation may cause erosion.

Computing scour depth and riprap stability at culvert outlets The tailwater elevation must be taken into account when selecting a scour equation. Scour depth equations for a range of tailwater elevations are presented in the following paragraphs.

High plunge (Zrw/D<-1) Scour below a plunging jet was investigated by Blaisdell and Anderson (1991). The relative scour depth was found to approach -10.5 in an asymptotic manner as the densimetric Froude number increased. The best-fit relationship suggested by Blaisdell and Anderson is: (5-24) = -10.5[l - e~°3S(Fd~2) ] where: Ysc = Scour depth measured from water surface D = Diameter of culvert barrel Fa = Densimetric Froude number at the surface

Low plunge (-1.0< Zpw/D < 0) Rice and Kadavy (1995) investigated the stability of river gravel riprap for the low plungeoutlet condition and suggested an expression that encompassed most of the data: (5-25) where: Zs= S cour depth measured from culvert invert D = Diameter of culvert barrel Zrw = Tailwater elevation measured from culvert invert Q = Discharge in culvert dso = Particle diameter for which 50 % by weight of sediment is finer

57 5. Scour and sediment transport

Partly submerged outlet (0< Zm/D <0.7) This flow condition was investigated by Rice and Kadavy (1995) and the suggested equation for a safety factor = 1 was: Z f O2 ^ “50 \ z (5-26) +4.6 log + 2-™ D D where the variables are defined as for (5-25).

Lim (1995) compiled a large data set of scour depths below culverts. The data included both small and large-scale investigations with jet diameters ranging from 15 mm to 940 mm. An inspection of the data shows that the outlets were usually partly submerged and in some cases fully submerged. Lim found that the best-fit line could be expressed as a function of the densimetric Froude number: (5-27) Zs=032DFd Fa <10 (5-28) ZS=3.5D Fa >10 where: Zs = Scour depth measured from culvert invert D = Diameter of culvert barrel Fd = Densimetric Froude number at the culvert outlet

Fully submerged outlet (Zjy/D > 0.7) River gravel riprap stability on a plane bed below a submerged culvert outlet was investigated by Rice and Kadavy (1994b). The study revealed that the tailwater depth had little influence on the size of riprap required for stability. The most important depth parameter was the distance from the culvert invert to the ripped bed. The following equation was found to envelop the data: •tfl

II 0.23 + 0.06 ( Q2 ) D lD L where: dso = Particle diameter for which 50 % by weight of sediment is finer D = Diameter of culvert barrel Zs = Scour depth measured from culvert invert Q = Discharge in culvert

58 5. Scour and sediment transport

Rice and Kadavy (1994a) also investigated river gravel riprap protection of a plunge pool below a submerged culvert outlet. The following equation, which has a safety factor of 1.0, relates plunge pool depth to riprap diameter: n- r w„. xL18 " ^ = -3.75 (5-30) log -log 4.35-^- D gD 3 where the variables are defined as for (5-29).

5.3.3 Scour by overtopping flow

Overtopping granular materials Olivier (1967) investigated flow through and over rock fill and proposed a design method. For overtopping flow he distinguished three stages in the destruction of the riprap-protected slope: 1. At the point of incipient erosion many of the rocks were vibrating and a few would suddenly jump into the flow and be carried away. 2. If the flow increased more rock was removed and the flow would concentrate into the holes left. The concentrated flow scoured channels that rapidly progressed downstream to the toe. 3. If the flow was further increased beyond the threshold of destruction the whole riprap cover would rapidly disintegrate.

Abt and Johnson (1991) conducted riprap stability tests in a steep flume with slopes 0.01 - 0.2. In the tests they mainly used well-graded angular rock but they also carried out some tests with rounded rock. They tested both for incipient stone movement and riprap layer failure. Incipient movement occurred when the flow rate was 74 % of the failure flow. At 88 % of the failure flow rate channels stared to form in the riprap layer. When the riprap layer failed a catastrophic failure was observed on all slopes steeper than 0.02. Rounded stone would fail at a discharge rate of 60 % of the failure discharge rate of angular rock (d50 equal). The expression for the limit of riprap failure of angular rock proposed by Abt and Johnson (1991) and converted to metric units is: (5-31) d50=0.5S0OA3q056 where: dso = Particle diameter for which 50 % by weight of sediment is finer, m S0 = Slope of channel bottom, - q = Discharge per unit width, m3/sm

Robinson et al. (1993) did similar investigations with angular rock in a flume with slopes 0.1 - 0.4. The tests identified the discharge at which limited erosion occurred, but not the riprap failure flow. Their design equations was similar to that of Abt and

59 5. Scour and sediment transport

Johnson (1991) but resulted in relatively larger rock, especially for the steeper slopes. The enveloping equation for predicting the highest stable unit discharge in metric units is: (5-32) d50 = 0.45S0aiy55 where: dso = Particle diameter for which 50 % by weight of sediment is finer, m So = Slope of channel bottom, - q = Discharge per unit width, m3/sm

Temporal development of erosion in granular materials When flow that overtops an embankment that is constructed of granular material exceeds the stability threshold, scour will progress quickly. Abt and Johnson (1991) reported a catastrophic collapse of the riprap layer for slopes steeper than 0.02 and most embankment slopes are far steeper than this. Other tests have also shown a rapid erosion of granular embankments (Dodge 1988; Powledge et al. 1989b; Visser et al. 1990).

Tinney and Hsu (1961) investigatedovertopping of a 4 m-high model of a fuse plug mainly composed of gravel. The erosion was initiated by leading water over the crest in a pilot channel. One and a half minutes after the test had started the erosion had progressed down to the foundations, four metres below.

Flow overtopping cohesive materials Cohesive embankments are generally more resistant to erosion than granular fills. Case stories on overtopping mention many examples of levees and embankments constructed from cohesive soils that have withstood many hours of overtopping without damage (Powledge et al. 1989b). Embankments of sandy clay and earth seem to be more liable to failure.

Although some information on threshold velocities or shear stresses for cohesive soils exists erosion in cohesive soils is not well understood, and no universal governing equations for cohesive soil erosion exist. This makes extrapolation of data from small-scale models to prototypes extremely uncertain, and also prevents experience obtained at one large-scale situation from being used at another site (Powledge et al. 1989a).

5.3.4 Internal erosion When water flows through a granular soil the finer fractions may be eroded and transported through the voids between the grains. In a self-filtering material the voids are small enough to retain the coarser particles, which will in turn retain the finer particles. If the material is not self-filtering fine particles will be transported

60 5. Scour and sediment transport through the voids and out of the material. The loss of finer particles often starts locally and leads to the formation of pipes along areas with increased permeability. Large pressure gradients at the upstream end of the pipe will make erosion progress in the upstream' direction. Piping may lead to excessive leakage, the formation of sinkholes or breaching of the dam or levee.

Janbu (1970) discussed the piping hazard and relates the formation of piping to the pressure gradient. Using data from Lane (1935) he presents a table of critical gradients, Scr, for the formation of piping in different soils as shown in Table 5-2.

Table 5-2: Critical pressure gradients in different soils (Janbu 1970)

Soil Scr Silt 0.12 Fine sand 0.14 Medium sand 0.17 Coarse sand 0.20 Gravel — Cobbles 0.25 - 0.4

Sellmeijer (1988), who investigated piping below impermeable surfaces, found that relating the critical gradient to soil type does not explain Lane ’s data well. Sellmeijer suggests a method to establish the critical pressure gradient based on analytical evaluation of the grain stability. The method requires detailed soil data, and was not verified by tests.

Bartsch (1995) discusses criteria for evaluating the self-filtering ability of a granular material. If the material gradation curve is straight and the grading is not too wide the material is not liable to internal erosion. The self-filtering ability of a given material may be evaluated by dividing the gradation curve and considering the fine fraction as the base and the coarse fraction as filter. The coarse fraction should satisfy normal retention criteria for granular filters.

5.4 SCOUR - a program for scour calculations Flood hazard evaluations will involve a series of scour assessments: 1) investigation of riprap stability, 2) scour depths at bridge piers and abutments, 3) scour-hole depths at culvert outlets, and 4) embankment damage from overtopping flow or internal erosion.

A computer program was developed in order to evaluate a range of scouring situations effectively. Equations for estimating riprap/bed material stability and scour depths were programmed in a spreadsheet The program was used for a

61 5. Scour and sediment transport number of scour assessments during the case study. This section describes the main features of the program.

5.4.1 General stability of riprap and bed material. The general module uses three different equations to compute riprap stability on the bed and banks of a trapezoidal channel: 1) Shields' equation (5-1), 2) equation (5-7) (Escarameia and May 1995) and 3) equation (5-5) (Maynord 1993). Manning's friction factor is calculated by Stickler's formula (4-5). Average flow velocity is used instead of depth-averaged point velocity. For equation (5-1) and (5-7) reduced riprap stability on the bank is taken into account by using a stability chart (Lysne 1987). The effect of uneven shear stress distribution in bends is taken into account for by correction factors that must be calculated by the user. Stable rock sizes for the bed and the side slopes are calculated for a range of discharges specified by the user. Figure 5-2 shows an example.

Riprap stability in uniform flow

W = 10 m S0 = 0.01 n = 0.036 Side-slope 1:2

Discharge, Q (m3/s)

Eq. (5-1), on bed * Eq. (5-1), on side-slope Eq. (5-7), on bed Eq. (5-7), on side-slope

Figure 5-2: Results of riprap stability calculation

5.4.2 Riprap stability at piers The pier module uses three different approaches for assessing riprap stability at piers: 1) applies a ratio of limiting approach velocity to critical velocity, U/Us = 0.5 to equation (5-11), 2) applies a ratio, U/Us = 0.3 and correction factors (equation (5-12) (Chiew 1995)) to equation (5-11) and 3) equation (5-13) (Parola 1993) by using stability indices of 2.25 and 1.5 for rounded and square piers respectively. The stability indices were selected to give a probability of riprap failure of approximately 50 %.

62 5. Scour and sediment transport

Riprap size at incipient motion is calculated over a range of approach velocities specified by the user. Figure 5-3 shows an example for a 1-m wide pier in 4-m deep flow.

5.4.3 Scour depth at piers The pier module uses three equations to calculate scour depth: 1) Y$ = 2.3 BK« (Breusers and Raudkivi 1991), 2) equation (5-15) (Richardson and Davis 1995) and 3) equation (5-16) (Froehlich and Ameson 1995). The correction factors that are not directly available from tables are computed in SCOUR. Scour depths are computed over a range of bed material sizes as specified by the user. Figure 5-4 shows scour depths calculated for a 1-m wide pier in 4-m deep flow. The flow velocity is 3 m/s.

Riprap stability at piers

B = 1 m Y = 4m

« 0.6-

2 0.4-

Undlsturbed flow velocity, U (m/s)

-*-Eq, (5-11), U‘ = 0.5 -m-Eq. (5-11) and (5-12) Eq. (5-13), Nc = 225 (circular) -x- Eq. (5-13), Nc = 1.5 (square)

Figure 5-3: Results of pier riprap calculations

5.4.4 Riprap stability at bridge abutments Riprap stability at abutments is calculated using equations (5-18) and (5-19) (Atayee et al. 1993). By inspecting the data the equations were modified to yield also the riprap size with an approximately 50 % probability of failure. Riprap diameters are computed for the range of velocities that the user specifies. Figure 5-5 shows the design size and failure size of riprap at spill-through and vertical wall abutments in 3-m deep flow.

63 5. Scour and sediment transport

Scour depth at pier

—Ys=2.3B -*-Eq. (5-15) -±-Eq. (5-16)

Figure 5-4: Result of pier scour depth calculations

Riprap stability at abutments

Y, = 3 m

0.2 -

How velocity, Ua (m/s)

♦ Eq. (5-18) and (5-19), spill-through ■ Eq. (5-18) and (5-19), vertical wall a Eq. (5-18) and (5-19), spill-through, 50 % failure ---x-- Eq. (5-18) and (5-19), vertical wall, 50% failure

Figure 5-5: Results of abutment riprap calculations

5.4.5 Scour depth at culvert outlets The culvert scour module uses five equations to compute scour depths over the full range of tailwater elevations: 1) equation (5-24) (Blaisdell and Anderson 1991) for the high plunge, 2) equation (5-25) (Rice and Kadavy 1995) for the low plunge, 3) equation (5-26) (Rice and Kadavy 1995) for partly submerged outlets, 4) equation

64 5. Scour and sediment transport

(5-30) (Rice and Kadavy 1994a) for fully submerged outlets, and 5) equations (5-27) and (5-28) (Lim 1995) for a comparison of partly submerged and submerged outlets.

The user enters the minimum and maximum tailwater elevations and the sediment size. The program selects the appropriate equation and computes the expected scour depth. The results are then plotted in a graph. An example is shown in Figure 5-6. The culvert diameter is 1 m, the discharge is 2 m3/s and the sediment diameter is 0.05 m.

Scour depth below culvert outlet

0 = 2 nf/s -2.00 - D = 1 m

— -4.00 ■

q . -6.00 -

-8.00 •

-10.00 •

-12.00 -2.50 -2.00 -1.50 -1.00 -0.50 0.00 0.50 Tailwater elevation, Z™, (m)

-+-Eq. (5-30) -e-Eq. (5-27) and (5-28) -*-Eq. (5-26) -X-Eq. (5-25) -*-Eq. (5-24)

Figure 5-6: Results of culvert scour calculations

5.4.6 Scouring by overtopping flow Six equations are used for calculations of rock stability during overtopping flow: 1) stable angular rock (equation (5-31) (Abt and Johnson 1991) modified), 2) equation (5-31) (Abt and Johnson 1991) for imminent failure of angular rock, 3) stable rounded rock (equation (5-31) (Abt and Johnson 1991) modified), 4) imminent failure of rounded rock (equation (5-31) (Abt and Johnson 1991) modified), 5) equation (5-32) for stable angular rock (Robinson et al. 1993), and 6) equation (5-1) using T* c = 0.056. The rock sizes are calculated for a range of bed slopes specified by the user. The user can easily change the unit discharge rate and roughness in order to assess how parameter uncertainties affect the results. Figure 5-7 shows some results for an overtopping flow of 1 m3/sm.

65 5. Scour and sediment transport

Rock stability during overtopping flow

1.60

1.40 -

1.20 -

. 1.00 •

m 0.80 -

0.60 -

S 0.40

0.20 -

20% 30% 40% 50% Embankment slope, S0 (%)

Eq. (5-31) -x- Eq. (5-31), modified, failure of rounded rock -e- Eq. (5-32) Eq. (5-1)

Figure 5-7: Rock stability during overtopping flow

66 6. GIS as a tool for flood hazard assessment

6 GIS as a tool for flood hazard assessment The objective of this chapter is to introduce GIS in general, to present the Idrisi GIS used in the study, and to review some applications of GIS in floodplain and hazard analysis. The chapter also describes the use of GIS during the case study, including data acquisition and pre-processing.

6.1 An introduction to GIS A geographic information system (GIS) is an information system that is designed to work with data referenced by spatial co-ordinates. An information system is a chain of operations that takes us from planning the observation and collection of data via storage and analysis to the use of the information derived in a decision-making process. GIS is both a database system with specific capabilities for spatially referenced data and a set of operations for working with the data (Figure 6-1).

There are five essential elements that a GIS must contain: 1. Data acquisition. This is the process of identifying and gathering the data needed. This stage involves a number of processes: acquiring satellite or aerial photographs, acquiring maps, collecting demographic information or data on rainfall or runoff, and conducting field surveys. 2. Pre-processing is the manipulation of data so that it can be entered into the GIS. This involves data-format conversion and identifying the locations of objects. 3. Data management. Data management involves the access to the database itself. Typical functions are data entry, retrieval, update and deletion of data. 4. Manipulation and analysis. This involves analytical tools for working with the content of the database. Typical operations are deriving statistics from the data and combining data layers to produce new information. 5. Product generation. The final product from the GIS might be in the form of lists of data such as a statistical report, or in the form of maps.

67 6. GIS as a tool for flood hazard assessment

Images

Image Processing System / \ Statistical \ Reports Statistical // ' Map Analysis V* Digitizing System \ System

Spatial Attribute Data Data Base Base , .Geographic^ Database V Analysis Manage ­ \ System ment y System/ Statistics and Tabular Data Cartographic DisplaySystem

Figure 6-1: The main components of a GIS (after (Eastman 1995))

6.1.1 Data classes and data structures There are two classes of data in a GIS: 1) Spatial data that locate the position of an object and 2) attribute data that contain information about the object. For example, the location of a rain gauge is given by its co-ordinates, i.e. spatial data. The attribute data for the rain gauge may contain the year it was put into operation, the annual rainfall recorded or the whole time series of rainfall observations.

There are several ways of organising the spatial data within a GIS. Two main data structures exist: 1) the raster data structure and 2) the vector data structure (Figure 6-2): 1. Raster data are one of the simplest data structures. The data are organised in cells. Each cell contains an attribute value, much like the cells in a spreadsheet. The rows of the raster are often oriented parallel to the east-west direction. Raster systems often organise data in layers, with each layer containing all the data for a single attribute (Figure 6-3). 2. Vector data. Vector data structures are based on points. The points are combined to form lines, arcs and polygons. Attribute data may be stored with the point co-ordinates or in a separate database.

68 6. GIS as a tool for flood hazard assessment

\ \ 802\ ----- 812 X/ bOI

806 > X 810

x/ycjw / //XT 1J\ 809 805 \

* ± 0. 0.ioTo S ID LAND-USE AREA 0 z 0 0 0 loha4 z\ z\ z 801 201 6305 0 0. 0.\z\z 1sI 202 6412 802 0 0. 0. ag1& 0. 803 112 7221 M 804 201 12532 £0. 0. M o. 0. M 01 o 805 312 14638 s1£ 0. 806 201 6120 £££lips 0 E 0. $ 0 807 111 8914 Eunnnnxsnnn£i * 0 0 Vector Raster

Figure 6-2: Raster and vector data (Eastman 1995)

roads

soils

elevation Figure 2-3

Figure 6-3: The concept of data layers (Eastman 1995)

The digital elevation model (DEM) A DEM is an image that stores data that can be envisioned as heights on a surface. The value of each pixel in the raster represents the height of the surface above some

69 6. GIS as a tool for flood hazard assessment datum. Even if the grid structure breaks up the surface into uniform cells, the data are treated as belonging to an underlying continuous surface. A DEM for Norway is available from Statens kartverk (Government Mapping Agency). The grid resolution is approximately 90 • 90 m. Figure 6-4 shows a three-dim ensional view of the DEM of the study area.

Figure 6-4: Three-dimensional view of study area DEM

6.2 The Idrisi GIS Idrisi is a geographic information and image processing software package developed at Clark University (Eastman 1995). It is a raster-based GIS which runs on a micro-computer. The system comprises systems for a map digitisation, image processing, geographical analysis, statistical analysis, cartographic display and database management.

Image processing is largely concerned with four basic operations: 1) image restoration, 2) image enhancement, 3) image classification and 4) image transformation. The image processing system in Idrisi permits the import and 6. GIS as a tool for flood hazard assessment analysis of remotely sensed images such as aerial photographs and satellite imagery.

The database workshop in Idrisi provides an integrated relational database for managingattribute data. A large number of attribute data can be linked to spatial objects such as points or polygons. The database is linked to the map display so the results of queries to the database can be displayed directly on the map. Users can also query the database by clicking on the map layer.

The geographical analysis system is the heart of the GIS system. It has the ability to manipulate and analyse one or more images in order to produce new images or tabular data. The analysis system contains a large number of computational modules. A few of the modules used in the course of this project are listed below: 1. RECLASS produces a new image by reclassifying the values of an input image. 2. OVERLAY performs operations between two images, producing a new image as result. For example, an image with the flood water surface elevation may be overlain with a DEM to produce the flood zone. The concepts of reclassification and overlying are illustrated in Figure 6-5. 3. HISTO is used to display a histogram of the values in an image. For example HISTO can be used on a DEM to give a catchment hypsographic curve. 4. AREA is used to calculate the area of different classes of pixels. 5. SURFACE calculates the slope and aspect of cells in a DEM. 6. GROUP is used to identify contiguous groups of pixels having the same attribute. 7. WATRSHED calculates all cells belonging to the watershed of a group of target cells. 8. RESAMPLE is used to georegister an image to a reference system. For example, it may be used on an aerial photograph to adapt it to a reference system. 9. INTERCOM interpolates a surface from a set of digitised lines. It may be used to interpolate a DEM from digitised contour lines. 6. GIS as a tool for flood hazard assessment

Overlay

Figure 6-5: The concepts of reclassification and overlaying (Eastman 1995)

6.3 GIS and hydrological models Facilitated by the continuous development of cheaper and more powerful computers, hydrologic models are getting more complex, and lumped models are being replaced by advanced distributed models. Distributed modelling requires large amount of input data, and also produces large amounts of result data. A GIS is a natural tool for processing model inputs and results, but only limited hydrological modelling can be performed by the GIS itself.

6.3.1 Lumped hydrological models The level of interaction between the GIS and the hydrological model will depend on the model in use. In the case of lumped hydrological models the GIS can be used to extract confined parameters such as catchment size and hypsographic curves from a DEM. The number of parameters are few and only calculated once for each catchment, so the transfer from GIS to model is done manually.

For example, a flood study in the Au Sable River Basin used GIS to establish the Soil Conservation Service Runoff Curve Number (RCN) to be used (Mettel 1992).

72 6. GIS as a tool for flood hazard assessment

The RCN indicates the percentage of the rainfall that will run off from the catchment. RCNs are based on two factors: 1) ground cover and 2) soil. Data from the Thematic Mapper (TM) satellite was used to classify the ground cover. Infrared images from the TM were also used in conjunction with other data to classify the hydrologic soil group. RCN values for each cell were calculated by overlying images of ground cover and hydrologic soil group.

6.3.2 Distributed hydrological models In distributed models, the catchment is divided into a grid of cells, or into larger areas that are hydrologically homogeneous. The hydrological characteristics of each cell are calculated by combining layers of information. A cell’s response to rainfall is assessed from its hydrological characteristics, and may be calculated in the same manner as for a lumped model. The runoff from each cell is then routed to the catchment outlet. Some models use a simple overland flow method. In other models, the routing is done along a stream pattern derived from a DEM.

Several types of data may be needed for distributed modelling: data from a DEM are used to calculate flow directions for the overland flow and to delineate the river network. Soil and vegetation information is used to assess hydraulic conductivity and rainfall interception. Snow and soil moisture data may be used to define the model’s initial conditions, or to update the model. Time series of rainf all and temperature are main inputs in calibration and forecasting.

Most of the data are preferably handled in a GIS. River networks may be delineated in a GIS, and soil and vegetation data may be retrieved from special purpose maps or from satellite imagery. Snow and soil moisture may be assessed by remote sensing from an aircraft or a satellite. The spatial distribution of rainfall may be estimated by interpolation from point measurements and by means of elevation lapse rates.

6.4 The use of GIS in floodplain studies From a technical viewpoint, a traditional floodplain analysis involves five main steps: 1) data acquisition and pre-processing, 2) flood analysis, 3) hydraulic model simulation, 4) damage assessment and 5) presentation of results. The objective of the floodplain study is not only to assess flood damage but also to evaluate various mitigation measures such as channel improvement and the constructions of levees in order to find the best mix of measures. Therefore, the process will be iterative as indicated in Figure 6-6.

73 6. G1S as a tool for flood hazard assessment

Geographical Information System

Remote Other data Hydrological sensing retrieving and techniques hydraulic model

Imaging Mapping

Terrain

Figure 6-6: Integration of GIS and flood hazard analysis (Amighetti et al. 1994)

6.4.1 Data acquisition and pre-processing for floodplain studies The types and quality of data depend on the scope of the study. The data may be subdivided into three groups: 1) Data on flood probability and temporal development are needed in order to select a design flood, 2) Data on geometry and roughness of the river and surrounding floodplains are needed to run the hydraulic model. 3) Data on land use and developments and population along the river are needed to assess the consequences of flooding. The acquisition of geometric and land use data is briefly discussed in the following: 1. Geometrical data. Cross-sectional or surface data are normally extracted from a DEM, but in many cases the available OEMs are not sufficiently accurate. For example, the vertical resolution of the DEM available for Norway is not sufficiently for hydraulic computations. A DEM may be constructed from available maps, but its vertical accuracy will still be on the low side of acceptability. High quality DEMs may be constructed from points measured by ground surveys, from aerial photographs or by the use of aerial altimetry, but this involves relatively large costs. 2. Flood control structures. Weirs, dams, bridges and levees have important influences on the flood profile, and detailed geometrical data are needed to model their influence on the flood profile. Data may be collected from construction plans or by surveys, and stored in the GIS database. 3. Land use data. Land use data are required for two purposes: 1) they can be used to assess the roughness of the floodplains for use in hydraulic modelling and 2) they are needed for assessing the consequences of floods. Roughness

74 6. GIS as a tool for flood hazard assessment

parameters may be related to different land use and vegetation indexes which may be obtained from ground surveys, special-purpose maps, aerial photographs or satellite images. Maps of residential areas, areas developed for industry and commercial purposes and agricultural land use are required for assessing the consequences of flooding. The geographical data on the location of a building may be linked to databases with information about addresses, owner, building size, etc. 4. Important infrastructure. If important physical infrastructure is damaged during a flood this may have a considerable influence on the overall flood consequences. The availability of data depends on the type of infrastructure in question. Detailed information about road positions and road elevations exist for most of Norway and digital data describing the water supply and sewage system exist in many municipalities. Many power and telecommunication companies are starting to use GIS systems to maintain an inventory of their systems.

6.4.2 Preparing input data for the hydraulic model Although several hydraulic models can import and export GIS data, none of them form an integral part of a GIS so far. Several tools are being developed to provide means for effective transfer of data. Greenwood et al. (1994) describes a system for interaction between a one-dimensional hydraulic model and a GIS. The operator determines the location and extent of the cross-sections by drawing them on a map displayed on the computer screen. Station and elevation data for the cross-section are then extracted from the DEM and processed into a format suitable for the hydraulic model, but flow lengths and roughness have to be entered separately.

Two- and three-dimensional models require large amounts of data, and a GIS is a suitable tool for preparing and managing input data and results. Several authors have described the coupling of two-dimensional flood models and GIS (Amighetd et al. 1994; Bechteler et al. 1994; Di Giammarco et al. 1994; Estrela and Quintas 1994). Ground elevation and roughness data are prepared and managed in the GIS and exported to the model, and automatic grid-generation tools are used to prepare grids from OEMs.

6.4.3 Handling output data from hydraulic models The model outputs several hydraulic parameters such as water surface elevation and flow velocity. One-dimensional models report the parameter values at cross- sections and two- and three-dimensional models provide results for each cell. An unsteady flow model will produce even more results: data for the condition in each cell and at each time step.

75 6. GIS as a tool for flood hazard assessment

GIS may be used to manage and present the model results, and for further analysis of the consequences. Typical results are in the form of maps that show the extent of flooding, water depth or velocity distribution. Special maps may be constructed to show the temporal development of the flood, i.e. the extent of flooding at successive time steps, or maximum values obtained during the model run.

6.4.4 Flood damage assessment GIS is a very suitable tool for damage assessment because of its ability to combine results from the hydraulic model and land use information. The GIS may be used to delimit flood zones from computed flood profiles, to identify and enumerate flooded structures, to calculate flood depths, to assess flood damage at each structure and to find the aggregate flood damage costs within a given area.

De Jonge and Kok (1996) described how a GIS was used to assess flood damage and evaluate mitigation strategies for the river Meuse in The Netherlands. A one­ dimensional model was used to compute water surface elevations and the results were transferred to a GIS. The flooded area was determined in the GIS by searching the area around each cross-section until non-submerged ground was found. Four damage categories were employed: public authorities, private persons, industry and agriculture. A GIS was used to map the different categories and compute the depth of flooding. Stage-damage functions were used to compute the cost of flooding. Several flood mitigation strategies were investigated in this way.

Di Giammarco and Todini (1994) used a combined 1-dimensional and 2- dimensional hydraulic model, a raster GIS and a database to assess flood damage. Damage to agriculture and built-up areas, and traffic disruption were assessed. Damage to agriculture was taken to be a function of the duration of flooding, type of crop and season. The GIS and database was used to find the agricultural losses by combining images of crop types at the moment of flooding, flooding duration and duration-loss functions. Damage to buildings was assessed by overlaying the flood surface elevation and building locations. Losses were computed using a stage- damage function. Traffic disruption was analysed by first identifying flooded sections of the highway network. GIS was then used to analyse the redistribution of traffic flow and changes in travel time and travel length.

6.5 GIS applications in risk assessment and management Floodplain management is much more than mere assessment of the probabilities and extent of flooding. It involves a number of aspects concerning society ’s use of both floodplains and catchments, such as flood zone delineation, identification of groups and objects vulnerable to floods, assessments of the consequences of flooding, evaluation of flood mitigation measures, and decision-making.

76 6. GIS as a tool for flood hazard assessment

The ability of GIS to integrate data from different sources, analyse them, and present the results in a timely manner makes GIS a valuable tool in the management process. To provide the reader with a understanding of how GIS may be applied in the broad context of floodplain management some applications of GIS in environmental risk assessment and management are reviewed below. This treatment is largely based on a project at The Idrisi Project, Clark Labs for Cartographic Technology and Geographic Analysis: “Applications of GIS Technology in Environmental Risk Assessment and Management ” (Eastman et al. 1997), and “Explorations in Geographic Information Systems Technology, Applications in Hazard Assessment and Management ” (Emani 1996).

The environmental risk assessment and management process can be divided into four stages (Eastman et al. 1997): 1. Hazard assessment. A hazard is a potential source of harm to something that people value. Hazard assessment is concerned with the characterisation of the nature, magnitude, and timing of hazard events. 2. Vulnerability assessment Vulnerability is the susceptibility to suffer losses from hazards. There are three dimensions of vulnerability: 1) exposure, or the likelihood of suffering losses from a hazard, 2) resistance, or the ability to withstand the impacts of hazard, 3) resilience, or the ability to recover from the impacts of hazard. Vulnerability assessment is concerned with characterising the degree to which an individual, group or entity is susceptible to harm from a hazard. 3. Risk assessment. Risk assessment is concerned with the probabilities and consequences of a hazard. Risk assessment must integrate the characterisation of hazard and the vulnerability to hazard with the consequences of the harm caused. 4. Decision-making. The final stage of the risk management stage is decision ­ making. Data from the previous stages are used to decide how to cope with the hazard in question.

In addition to the four stages mentioned above, applications of GIS in monitoring and managing an emergency will also be reviewed. GIS and remote sensing are particularly useful for monitoring the development and consequences of natural hazards of large spatial and temporal extent

6.5.1 Application of GIS in hazard assessment GIS is highly suitable for the analysis of natural hazards as they often have a considerable spatial component. Data on potentially hazardous sites may be acquired by the use of a GIS, for example, by digitising data from maps or from remotely sensed images. Potentially hazardous sites may also be identified by using the analysis capabilities of the GIS. For example, data on rainfall, soil and slope can

77 6. GIS as a tool for flood hazard assessment be combined to identify areas at risk from landslides. The potential development of a hazard can be modelled within a GIS itself or by linking the GIS to external models. For example, GIS and ground-water flow models have been used to assess the potential spread of contaminants in an aquifer.

Several applications have been reported in the literature. Ellen and Mark (1993) used GIS to identify debris flow hazards in Honolulu. The New Year’s Eve storm in 1987 triggered more than 400 debris flows in the Honolulu area, where several struck homes and others contributed debris that diverted floodwaters.

Ellen and Mark (1993) used observations of past debris flows to characterise sites of initiation, volume at initiation and volume change during flow. It was found that the locations of slope failures are closely related to terrain slope and rock weathering. A GIS was used to overlay hill slope data extracted from a DEM and weathering data, producing an image that showed the long-term average frequency of slope failure for each cell.

Simulated debris flows were routed through the DEM from a set of starting points taken from the slope-failure frequency image. The routing procedure provided the expected debris-flow paths. Hazard zones were established by counting the number of debris flow paths to each cell. Approximately 800,000 simulations, representing a period of 10,000 years, were performed to create the debris flow hazard maps.

6.5.2 Applications of GIS in vulnerability analysis Vulnerability analysis is concerned with susceptibility to suffer losses from hazard. The groups or objects that may be exposed to hazard are analysed, rather than the hazard itself. GIS was used to explore the vulnerability to coastal storms and flooding of Revere, Massachusetts (Emani 1996). Exposure to hazard was determined by the types of land use (residential, industrial or agricultural) and the ability to withstand and recover from the impacts of hazard was associated with socio-economic factors.

Flood-zone maps were digitised to capture areas at risk from a 100-year flood. Socio-economic factors such as ethnicity, age and income were also entered into the GIS. GIS was then used to combine these dimensions to produce a composite image of community vulnerability. For example, flood data were combined with data on age to produce maps showing the spatial distribution of elderly population at risk from flooding.

78 6. GIS as a tool for flood hazard assessment

6.5.3 Applications of GIS in risk analysis Risk analysis deals with both hazards and consequences. A risk analysis attempts to identify possible hazards, their outcomes and the associated probabilities. Few examples have been found of GIS applied to risk analysis. The best examples are probably the use of GIS for flood damage assessment as described in section 6.4.4.

6.5.4 Applications of GIS in decision-making Few studies exist on the use of GIS for decision-making in hazard management. However, some decision-making processes are very suitable for the use of GIS. Overlaying techniques have traditionally been used to combine various siting factors and finding areas that meet all criteria. For example, for selecting suitable locations for a new residential area one may specify certain criteria: e.g. probability of flooding < 0.001/year, slope < 0.1, distance to a main road < 500 m, etc. For each criterion an image is made that shows the areas that meet that criterion, and suitable areas are found by overlaying the individual images.

An example of this approach is given by EarthSat (1998). During the Great Flood of 1993 the towns of Valmeyer and Hull in Illinois were substantially flooded, causing the destruction of a number of buildings. After the flood, the feasibility of moving the town out of harm ’s way was investigated. Land use maps were made by using Landsat TM images. From a classification based on the spectral classes five categories of land use were identified: 1) forest, 2) agriculture, 3) bare soil, 4) water, and 5) urban. Several infrastructure features were captured by digitising topographic maps: municipal zones, railroads, airfields, highways and power lines. Hazardous zones were created from flood-zone maps and by identifying and creating buffer zones around landfills, hazardous waste sites and toxic release sites. Ecologically sensitive areas were identified by capturing data from several sources. Potential relocation sites were determined by masking out critical infrastructure, ecologically sensitive areas and hazardous zones.

Simple overlaying does not allow for the incorporation of multiple and conflicting objectives. Complex decision-making can be accomplished with GIS by using multi-criteria evaluation (MCE) techniques. For example, different criteria concerning the choice of siting location may be weighted by the various groups involved in making the decision. GIS may then be used to create images that show area suitability and to identify the best compromise sites using different MCE techniques.

79 6. GIS as a tool for flood hazard assessment

6.5.5 The use of GIS in emergency management The use of GIS and remotely sensed data has at least two important fields of application in emergency management: 1. Monitoring. Remotely sensed data can be used to monitor situations or processes that may develop into an emergency or disaster. Monitoring can provide early warning, allowing time for effective mitigation measures. For example, data from weather satellites are used to monitor hurricanes and estimate their courses (Figure 6-7). The use of remotely sensed data may be the only feasible way of monitoring the development of a crisis affecting a large area. During severe floods, inundated roads and damaged telephone lines will make on-the-ground monitoring extremely difficult. Instead, satellite images and aerial photographs can be used to monitor flood development and identify damage and relief needs as the flood develops. 2. Management. GIS can be an effective tool in the management of relief work following major natural disasters. For example, after the Hurricane Andrew in 1993 in Florida, GIS was used to determine the co-ordinates of flooded neighbourhoods and to guide relief workers (Emani 1996). Gardner ((Gardner 1994) in (Emani 1996)) describes how remotely sensed data were used to assist the police in deciding which areas should be evacuated during the mid-west floods of 1993. Landsat imagery of the area was loaded into a GIS. Electronic maps showing normal river boundaries and building locations were superimposed on the images. The current extent of the flood was extracted from Thematic Mapper data. By combining these data with elevation data, the areas most likely to experience flooding could be identified, and the police could concentrate their evacuation efforts on these areas.

80 6. GIS as a tool for flood hazard assessment

Figure 6-7 Satellite image of Hurricane Felix (Copyright 1995-1997 Earth Watch Communications, Minnesota, USA)

6.6 Applicationsof GIS in the current study This section gives an overview of how GIS was used during the case study. First, the sources of data for the study and the process of data capturing are described. The practical applications of GIS during the study are then described. Finally, some experimental applications of GIS are given.

6.6.1 Data acquisition for the case study Digital map data were purchased from the government mapping agency Statens kartverk under agreement number LDS 61001-R29371. The layers included: 1) contour lines at 20 m intervals, 2) rivers and lakes, 3) coastal contours. The map layers were based on the map series M711 at a scale of 1:50 000. The data was in SOSI format, a Norwegian standard used by Statens kartverk. The reference system was UTM32 with EUREF 89 datum.

The SOSI format could not be directly imported into the Idrisi GIS. A computer program was developed in Visual Basic to extract the relevant data from the SOSI data files and convert it to Idrisi vector format. The program read text files with SOSI data and identified lines with the relevant attributes from the SOSI identification code. Line data needed for the case study were then extracted from the SOSI file, converted to Idrisi format and written to a new text file for use with Idrisi.

81

F 6. GIS as a tool for flood hazard assessment

A DEM of the study area was created by first converting the map layer with contour lines from SCSI to Idrisi format, then converting the data from vector to raster format. In order to create a continuous DEM surface intermediate pixel values were interpolated between the rasterized contours. The resulting surface was filtered several times to remove scatter created by the interpolation routine. The resulting DEM, part of it shown in Figure 6-4, was used as the basis for a number of analyses and maps which were created in the course of the study.

A raster layer of the river network was created from the SOSI rivers and lakes vector layer. The data was converted to Idrisi format and rasterized. A raster layer of the coastal contour was created in a similar manner.

Flood zones were captured by digitising from the flood zone map prepared by NVE and Orkdal municipality (Selboe 1997). The data were converted from the NGO reference system to UTM 32 by a rubber-sheet transformation. Cross-sections used for the flood profiles computations along Orkla were captured in a similar manner. The cross-section locations were digitised from maps prepared by NVE (Basvre 1996), resampled to the UTM32 reference system and rasterized.

Digital road data were acquired by purchasing VEBAS for S0r-Tr0ndelag county from Statens kartverk. VEBAS is a database of road information. Among other data it contains xyz co-ordinates for the centre lines of almost all roads throughout Norway. VEBAS uses the SOSI format, and a computer program was developed to extract data for the main roads in the study area and to convert the data to Idrisi format. The data were imported to Idrisi and rasterized.

Data on specific runoff for the study area were kindly provided by NVE in the form of vector points in a 90 m • 90 m grid. The data were rasterized to create an image of specific runoff.

Data on annual rainfall were digitised from maps (F0rland 1993), imported to Idrisi, georeferenced and converted to a raster image.

Several aerial photographs were bought from Fjellanger Wider0e AS and scanned. The co-ordinates of six easily recognisable objects were established both in the bitmap co-ordinate system of the scanned image and from M711 maps. The corresponding co-ordinates were used to georeference the images through a rubber- sheet transformation.

82 6. GIS as a tool for flood hazard assessment

6.6.2 An overview of GIS application of the case study The DEM was used to prepare data for rainfall-runoff modelling. The DEM was used to delimit the catchments for the flood studies and to extract the hypsographic curves. The use of GIS for flood assessment is described further in Chapter 7.

The DEM was also used to prepare base maps of the study area. Road layers from VEBAS, and river and lake layers and coastal contours were also used when creating the maps.

For display purpose, a background image was created from the DEM using analytical hill shading. Hill shading is a GIS technique that calculates highlights and shadows on a ground surface using a user-specified sun position.

Average rainfall and runoff for use in the flood assessment were computed by overlaying the rainfall and runoff images with the image of each catchment.

GIS was used to assess the consequences of flooding along the River Orkla. Results of the flood profile calculations were captured into the GIS. Continuous flood surfaces were created by interpolating between the cross-sections used by HEC- RAS. By overlaying the flood surface with an image showing elevations for the main roads it was possible to assess locations where the road would be inundated.

A map-linked database was created to organise and display the results obtained for the many objects investigated during the study. The location of each object, 88 in total, was digitised and given a unique identification number. A database of information on each object was created using the Database Workshop in Idrisi. By linking the information in the database to the geographic location of the objects the object features could be displayed directly on screen. This was particularly useful when preparing maps showing the results of the analysis.

6.6.3 Examples of experimental GIS applications GIS was used to identify objects vulnerable to flood damage. Two examples are described in the next section. The first example demonstrates the use of GIS to find stretches of road vulnerable to flooding. The second example demonstrates an attempt to identify stretches of road at hazard from debris flows.

Identification of road sections vulnerable to flooding An important part of the study was identification of parts of the road system vulnerable to flooding. In general, it was found that roads crossing rivers or streams, and roads with short horizontal or vertical distances to water were most susceptible to flood damage. This example shows how GIS can be used to identify road sections that meet these criteria.

83 6. GIS as a tool for flood hazard assessment

First, a raster image of all rivers and lakes in the area was created as described in the previous section. The layer is shown in Figure 6-8. Next, a raster image of all roads was created. A buffer zone of 25 m on each side was created around the roads on the image. The image of the buffered roads is shown in Figure 6-9. All rivers and lakes within the buffered region were found by overlaying the two images. Each pixel that met the road buffer and river criteria was converted to a vector point, representing a possible conflict.

The points of vulnerable stretches were displayed with the hill shade image as background as shown in Figure 6-10. The image was used when identifying the vulnerable objects during the case study.

The disadvantage of this technique is that it does not take into account the vertical distance between roads and rivers. The main river, Orkla, will flood large areas, far wider than the 25m buffer around the roads. This problem was dealt with by overlaying images of road elevations with images of flood-surface profiles. This is described in more detail in Chapter 9.

84 Figure 6-8: Rivers and lakes raster layer

Figure 6-9: Buffered main roads raster layer

85 6. GIS as a tool for flood hazard assessment

Locations found by overlaying roads and rivers

Meters Grid North 10000.00

Figure 6-10: Points of conflict found by overlaying rivers and roads

86 6. GIS as a tool for flood hazard assessment

6.6.4 Identification of road sections vulnerable to debris flows Debris flows, also called soil avalanches, mud flows or debris slides are rapidly sliding masses of soil, bedrock and vegetation, usually with a high water content. Intense rainfalls that saturate the soil often result in large numbers of debris flows. Jn 1982 an intense rainfall that lasted for 32 hours triggered more than 18,000 debris flows in the San Francisco Bay region (Wieczorek 1993). Fourteen people were killed and more than 100 homes destroyed.

During extreme floods there will usually be intense rainfalls that trigger debris flows and road blockages, and damage caused by debris flow may be as severe a problem as the floodwater itself. GIS was used in an attempt to identify stretches of road in the study area particularly vulnerable to debris flow damage. The assessment proceeded in three steps. First, the debris flow initiation areas were identified. Secondly, the flow receiving areas were identified. Finally, the image of receiving areas was overlain with the road image (Figure 6-9) to find vulnerable road reaches.

Debris flows will occur in most slopes steeper than 30° (Sandersen 1998). In view of the extreme floods being investigated in this study it was decided to use a slightly milder slope as a initiating criterion. An image of all areas with slopes of 25° or greater was created from the DEM, and this taken as the possible initiation areas for debris flows. The possible initiation areas are shown in Figure 6-11 as white areas bounded by black lines.

The DISPERSE module in Idrisi was used to assess the areas receiving the debris flow. The DISPERSE module calculates the cost of moving along a surface when acted on by force or friction. DISPERSE requires three images: 1) an image showing the starting point of the movement, in this case the image of slopes, (3, steeper than 25°, 2) an image showing the magnitude of the force and 3) an image showing the direction of the force. The pixel values in the resulting image reflect the cost of moving from the starting area to the pixel. Low values indicate that movement has followed a path parallel to a large acting force. An image of the hill slope aspect was taken as the force direction image, so that only downhill movement was possible. A force magnitude image was created by computing force as a function of slope. Each pixel was given a value calculated by the expression: (K cosines (3 - sinus (3) This image expresses the resultant of gravity force and friction force parallel to the hill slope. K may be interpreted as a friction factor. A value of K = 0.5 was used.

The image created with DISPERSE was overlam with the main roads image. The resulting image,Figure 6-12, clearly shows stretches of road at risk from debris

87 6. GIS as a tool for flood hazard assessment flows. It should be noted that this approach is based on simple assumptions. The method does not take into account the soil properties or the initial volume of debris, and does not model the dynamics of debris flow. However, it is believed that it gives a good indication of the areas most likely to receive debris flows.

Although debris flows will have important impacts on roads and traffic flow during severe flood episodes it was beyond the scope of this work to pursue this topic.

88 6. GIS as a tool for flood hazard assessment

Figure 6-11: Areas with slopes steeper than 25° (white bounded by black lines)

89 6. GIS as a tool for flood hazard assessment

Main roads and debris flow hazard zones

Meters 10000.00

Figure 6-12: Main roads and debris flow hazard zones

90 7. Methods of estimating floods

7 Methods of estimating floods To assess the consequences of a flood it is necessary to estimate the maximum flood discharge and preferably the flood volume. This chapter reviews various methods of flood assessment, discusses special needs related to flood hazard analysis and suggests methods to be used. The FASTELOOD program, which has been developed to facilitate the large number of rainfall-runoff analyses is presented. Finally, the procedure suggested is demonstrated using a case in Orkdal.

7.1 Frequency analysis Frequency analysis is a widely used method in catchments for which discharge measurements are available. Frequency analysis is based on the assumption that the discharges at any given time are realisations of underlying stochastic processes, and that the frequency function may be found from observations of the discharge. Two main groups of flood frequency analyses exist: 1) the single-series analysis and 2) the regional analysis.

Several important limitations of flood frequency analysis should be noted: 1. Frequency analysis is based on an assumption that the underlying stochastic processes are constant over time. Long-term changes in climate or in the catchment may violate this assumption. Observations of historic floods may therefore not be sufficient allow predictions of future floods. 2. When estimating large floods the recurrence intervals are often far longer than the data series. Extrapolations to recurrence intervals ten to twenty times longer than the observation period are not uncommon. Such extrapolation makes flood estimates highly unreliable. 3. An important practical problem is the lack of quality discharge measurements. Often the important flood peak discharge is not measured, but is merely estimated from the measured water level.

7.1.1 Single-series flood frequency analysis A data set is selected from a discharge time series to provide a sample. Two approaches are common: 1) the annual maximum series and 2) the peaks over threshold series. The annual maximum series consists of the largest flood every year. The peaks over threshold series consists of all floods with discharge above a given limiting value.

A probability (plotting position) is assigned to each observation in the sample based on the rank of the observation and the size of the sample. Several formulae exist for assigning plotting position. In Norway the Weibull plotting position is often used though it is biased and assigns excessively high probabilities to the largest values in the sample (Beran 1981).

91 7. Methods of estimating floods

Next, a frequency function is fitted to the data set. Frequently used probability functions are: log-normal, Pearson-III, log-Pearson HI and extreme value functions. The function may be fitted visually by plotting the observations on a special probability paper, but numerical methods are normally used to estimate the function parameters. Common methods are the method of moments, the maximum likelihood method and the method of probability weighted moments.

Where two flood seasons with different flood characteristics are dominant, e.g. a snow melt spring flood and an autumn rain flood, the two seasons should be analysed separately.

Detailed description of flood frequency analysis can be found in several books, e.g. “Applied Hydrology” (Chow et al. 1988), “Probability and Statistics in Hydrology” (Yevjevich 1982) and “Frequency and Risk Analysis in Hydrology” (Kite 1988).

7.1.2 Regional flood frequency analysis Regional frequency analysis is based on the assumption that climatically homogeneous regions exist, and that within a region the ratio of a flood with some fixed recurrence interval, Qr, to the average flood, Qavg, is constant. All flood data in a region can then be used to calculate the regional growth curve, which gives a much larger database than for single series. The results are often presented as curves showing the ratio Qr/Qavg as a function of the recurrence interval.

NVE has recently finished a new regional flood frequency study (Stelthun et al. 1997). The study report describes methods for estimating the Qr/Qavg ratio.

7.2 Rainfall - runoff methods An alternative to the statistical analysis of discharge is to use rainfall as a basis for calculating runoff. The simplest methods calculate runoff as a fixed fraction of rainfall. More advanced methods use computer programs to model hydrologic processes in the catchment. Whatever rainfall-runoff method is used a rainfall analysis will be needed to assess the appropriate amount of rainfall.

7.2.1 The rational method With the rational method the runoff is calculated as a fixed ratio of the rainfall: (7-1) Q = CiA where: Q = Discharge C = Runoff ratio i = Rainfall intensity A = Catchment area.

92 7. Methods of estimating floods

The runoff ratio will depend on the terrain surface, the catchment slope and the rainfall intensity. Steep catchments with impermeable surfaces will yield high runoffs. The runoff ratio also increases with rainfall intensity. The maximum rainfall intensity for a duration equal to the concentration time, Tc, of the catchment will yield the highest discharge.

The rational method is much used for small urban catchments. It should preferably be used in catchments with homogeneous surfaces. In (Myrab0 1991) NVE has evaluated the rational method for use in natural catchments and concludes that it may be used in catchments smaller than 5 km2. The report provides some information on estimating C and Tc. Additional information may be found in “Applied Hydrology ” (Chow et al. 1988). The discharge is sensitive to C, which is difficult to assess.

7.2.2 The unit hydrograph The unit hydrograph shows the discharge resulting from a unit rainfall over the catchment. The unit rainfall is a rainfall with defined depth and duration, e.g. 10 mm rainfall in one hour. The rainfall must fall with constant intensity and be evenly distributed over the catchment. If the catchment is assumed to have a linear response the response from any rainfall series may be constructed by subdividing it into unit rainfalls and adding the resulting unit hydrographs.

The unit hydrograph is found by analysing the catchment response to known rainfalls. Methods of finding the unit hydrograph from catchment parameters have also been developed. This is called a synthetic unit hydrograph. Information on deriving and using the unit hydrograph can be found in textbooks on hydrology e.g. “Applied Hydrology ” (Chow et al. 1988) or “Hydrology in Practice” (Shaw 1994). The unit hydrograph method is seldom used in Norway (Otnes and Rasstad 1978).

7.2.3 The rainfall-runoff model PQFLOM NVE has developed a simple rainfall-runoff model named PQFLOM, which is specially aimed at flood modelling (Andersen et al. 1983). The catchment is modelled as a linear reservoir with two outlets. Three parameters must be calibrated: 1) upper recession constant, 2) lower recession constant and 3) threshold level. Other inputs include catchment size, time step length, initial flow, rainfall time series and catchment concentration time.

The best way to calibrate the model is by using measurements of rainfall and runoff. For many catchments, rainfall and runoff measurements are not available. An empirical method of estimating the model parameters has been developed (Andersen et al. 1983). The method is based on calibrating the model for a series of

93 7. Methods of estimating floods catchments and then using regression analysis to relate the model parameters to catchment parameters. Fifty catchments in southern and central Norway were used. The catchments varied in size from 0.4 km2 to almost 800 km2.

PQFLOM may be used for a variety of catchment sizes and conditions and can be used in catchments for which no measurements are available. It should not be used for small floods. Contributions from snowmelt are not handled by the model but must be calculated separately and added to the rainfall. PQFLOM produces the whole flood hydrograph. A typical result is shown in Figure 7-1.

A master’s thesis at the University in Oslo (Mosebakken 1986) compared PQFLOM and the unit hydrograph method. The responses of six catchments varying in size from 0.4 km2 to 6275 km2 were compared. The unit hydrograph and the model parameters for PQFLOM were calibrated from observed rainfall and runoff. The unit hydrograph gave good results for large catchments but tended to underestimate the flood peaks for small catch ments. PQFLOM gave good results for all catchments. Catchment characteristics were also used to estimate the PQFLOM model parameters. This gave good results for the small catchments. For the large catchments, the outlet coefficients were overestimated.

Two problems concerning PQFLOM should be noted: 1. The catchment concentration time is a parameter used in the model. Tc has considerable effect on the results, but no guidelines are given for estimating Tc. Unfortunately, no information is given on how Tc was estimated for the 50 catchments used in the study described above (Andersen et al. 1983). Thus estimating Tc becomes rather arbitrary, and adds considerable uncertainty to the use of the model. 2. The model does not handle the conversion between different time-step lengths properly. The recession constants are varied linearly with the time-step length, which is not correct. Inappropriate treatment of time-step conversion during the parameter study (Andersen et al. 1983) may have resulted in systematic errors in the equations for predicting model parameters from catchment characteristics.

94 7. Methods of estimating floods

Viggja PQFLOM-Simulering for per Lode Tstart = 1 TIL Tslutt =36 100.0 Observert vann-f. • AREAL'\ 30.0 KM2 Slmu ! er i varirvf. TIDS$KRITT 1. TIMER NEDBK0RR-. 1.00 JERSKEL \ 13.6 MM 112 - ' TORE par : \ 0.140 T/TIME" 80.0 Observert nedboer to ORE PAR. 0.030 1/TIME-

84 -

56 - 40.0

20.0

'vio/y>/)Ay-y)/y-y>M

Tid i timer

Figure 7-1: Rainfall and runoff from PQFLOM

7.3 Assessing rainfall Rainfall is needed as input to all rainfall-runoff methods. Statistical analysis of rainfall is used to identify the relationship between intensity, duration and probability. Intensity-duration curves have been developed for man y continuous measurement rain-gauges, and are often used with the rational method. For flood assessment in larger catchments the temporal and spatial characteristics of rainfall are important, and rainfall time series are needed.

The Norwegian Meteorological Institute (DNMI) has developed a method of calculating extreme rainfall events (F0rland 1992). Statistical analysis of rainfall in Norway and other countries has been used to develop a growth curve for the ratio M5(24)/MT(24), where M5(24) is the 24-hour rainfall with a five-year recurrence interval and MT(24) is the 24-hour rainfall with a T-year recurrence interval. The same growth curve is used throughout Norway. The main steps in computing a T- year rainfall event are outlined below: 1. Estimate the average annual rainfall, PN. 2. Estimate the ratio M5(24)/PN. 3. Calculate M5(24). 4. Calculate the ratio M5(24)/MT(24). 5. Calculate MT(24)

1 95

if- 7. Methods of estimating floods

6. Adjust the amount of rainfall for duration that differ from 24 hours. 7. Convert the amount of rainfall from point value to catchment value. 8. Distribute the rainfall in time to create the design time series.

It is recommended that the M5(24)/PN ratio and the seasonal adjustment ratios should be established from statistical analysis of rainfall at neighbouring stations. A less exact but easier approach is to use ratio maps published by DNMI (F0rland 1984).

7.4 Recommendations A flood hazard analysis requires flood assessments to be made for a large number of catchments, most of which will be small. Discharge measurements will not be available for a large majority of the catchments. The flood assessment methods utilised should be easy to use, not require measurements of rainfall and runoff, and preferably provide the whole flood hydrograph. On the basis of the foregoing discussion it is suggested that: 1. A rainfall-runoff model should be used. 2. The rainfall should be estimated from the procedure described by F0rland (1984; 1992). 3. PQFLOM is the preferred model for calculating the runoff hydrograph, but the rational method may be used in small catchments. 4. The PQFLOM parameters can be estimated from the catchment characteristics. 5. Additional information should be utilised when available.

A large number of small catchments are often involved in flood vulnerability analyses. To reduce the time and effort needed for flood analysis it may be necessary to use the rational method for the smaller catchm ents. PQFLOM is believed to give better results but requires a much larger effort than the rational method.

PQFLOM should be used for all catchments larger than 5 km2. PQFLOM should also be used if there are lakes in the catchment. PQFLOM should be calibrated from discharge and rainfall measurements when these are available.

For catchments larger than approximately 20 km2 the results should be checked using the method described in “Regional Flood Frequency Analysis ” (Saelthun et al. 1997). If possible, frequency analysis should also be used as a supplement to PQFLOM.

7.5 The flood model FASTFLOOD The case study required estimates of flood sizes in a large number of small and medium-sized catchments. During the project a program was developed to

96 7. Methods of estimating floods facilitate rapid and efficient handling of flood analyses. The program has four modules: 1) rainfall time series preparation, 2) flood calculation using the rational method, 3) parameter estimation for PQFLOM, and 4) input file preparation for PQFLOM. The procedures were programmed into a spreadsheet using Visual Basic.

A separate spreadsheet was used to store data and prepare data for each catchment. After running PQFLOM the results were re-imported into the sheet. Thus, for each catchment the relevant spreadsheet provides full documentation of the rainfall and catchment data used, computational methods and flood modelling results.

The four modules of FASTFLOOD are described in the following paragraphs:

Rainfall time series preparation PN, M5(24)ZPN and the seasonal adjustment ratio are all entered by the user. The model computes the 24-hour rainfall with 50-, 100- and 1000-year recurrence intervals, called P50, P100 and P1000 respectively, and the probable maximum precipitation, PMP. The rainfall is adjusted for season and reduced according to the size of the catchment. A 36-hour rainfall series with one-hour resolution is constructed. The peak rainfall intensity is at 19 hours. The ratios of rainfall during n hours to the MT(24) is taken as a function of PN as shown in Figure 5 in F0rland (1992). A typical rainfall series is shown in Figure 7-2.

Flood estimates using the rational method The rainfall intensity calculated for the hour with the most intensive rainfall is used with the rational method. Strictly speaking the rainfall intensity should be selected to correspond to the catchment concentration time. The catchments calculated with the rational method are small (A < 5 km2) and most will have concentration times that are much shorter than one hour. It was felt that to include the concentration time when calculating the rainfall intensity would not significantly improve the results. Runoff ratio, C, of 0.2 - 0.5 is recommended for forest (Myrabp 1991). A runoff ratio = 0.3 was used for all catchments.

Parameter estimation for PQFLOM Model parameters for PQFLOM are estimated from catchment characteristics. The user enters the catchment area, catchment length, the 25 % and 75 % elevation on the hypsographic curve and the lake area. The model computes the recession constants, the threshold elevation and the concentration time. The concentration time is computed by assuming a flow velocity of 1 m/s along the axis of the catchment.

97 7. Methods of estimating floods

PQFLOM input file preparation Three input files to PQFLOM are prepared in the spreadsheet, one for each rainfall scenario: PI00, PI000 and PMP. The data are saved in a text file and used as input when running PQFLOM.

Rainfall series used for culvert 9-7

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Time (hours) ■ P100 DP1000 OPMP

Figure 7-2: Example rainfall series from FASTFLOOD

7.6 Flood analysis during the case study The case study included flood assessments of 23 catchments. This section gives examples of how the work was done.

First, the watershed was delimited from a digital elevation model (DEM) using the Watershed module in Idrisi. The Watershed module begins with a set of user- defined target cells in a raster layer and searches for surrounding cells that can flow into the target cells. The search continues until all cells that drain to the target cells, and thus the drainage catchment, have been found. The river network in the catchment was used as target cells. Figure 7-3 shows a river network used as target cells and the corresponding catchment. Because flow is considered possible in all directions in flat areas the method tends to slightlyoverestimate catchment size. Figure 7-4 shows the main catchments as delimited by Idrisi. The catchment size was calculated using the Area module.

The next step was to estimate the average rainfall in each catchment. A raster layer with annual rainfall distribution for the study area was created by scanning the corresponding section of a rainfall map (F0rland 1993), georegistering it and digitising the contours. A continuous rainfall depth raster layer was created by

98 7. Methods of estimating floods interpolating between the digitised contours using Idrisi. The average rainfall in each catchment was calculated by overlaying the catchment area layer with the rainfall layer and computing the average value.

Idrisi was also used to extract the catchment hypsographic curve. This was done by extracting the portion of the DEM that corresponds to the catchment area. The cumulative elevation distribution was found by running the Histo module on the catchment DEM.

Catchment boundary

Drainage network

Figure 7-3: River network and catchment boundary for Viggja

The annual average specific runoff was needed for all the catchments. Average runoff can be computed from runoff maps (NVE 1987), but this is time-consuming and cumbersome. NVE kindly provided a digital runoff-map for the study area. The original vector point format was converted to an Idrisi raster layer. Average runoff in each catchment was calculated by overlaying the catchment and runoff layer and computing the average.

Data extracted during the analysis of the catchment (area, length, elevations, lake area, average rainfall, average runoff) were entered in FASTFLOOD, which

99 7. Methods of estimating floods computed the rainfall time series, the model parameters and three input files for PQFLOM (P100, P1000, PMP). PQFLOM was used to compute the flood hydrographs for each scenario and the results were stored in FASTFLOOD. A typical flood hydrograph from PQFLOM is shown in Figure 7-1.

For the smallest catchm ents the rational method was used to estimate flood sizes and there was no need for detailed catchment data. The catchment boundaries were extracted manually and the area was found by using a planimeter. Average rainfall was found directly from the rainfall map. The peak flood values found by the analysis are shown in Table 7-1.

Table 7-1: Results of the Orkdal case flood studies

River/object Catchment area QlOO QlOOO PMF (km2) (m3/s) (m3/s) (m3/s) Skjenald/Bridge 9-3 162 110 150 280 Espa/Culvert 2-1 7.5 13 25 54 Folio/Culvert 2-3 31 23 35 80 Siken/Culvert 3-5 26 25 40 80 Viggja/Bridge 1-3 30 38 58 135 Vorma/Bridge 3-11 68 30 51 124 Gj0ta/Culvert 11-3 10 16 22 48 Sola/Culvert 12-1 30 40 62 140 Usd0ija/Culvert 13-5 10 18 26 54 Culvert 1-1 1.3 3 5 11 Culvert 1-2 0.5 1 2 5 Culvert 1-4 0.5 1 2 5 Culvert 1-5 0.5 1 2 5 Culvert 1-6 4 7 10 20 Culvert 1-7 0.8 2 3 7 Culvert 1-9 0.3 0.6 1 2 Culvert 1-10 0.6 1 2 5 Culvert 1-11 0.2 0.5 0.7 1.8 Culvert 3-9 4.7 13 19 45 Culvert 9-5 - 3 4 8 Culvert 9-7 3.2 10 14 28 Culvert 10-3 2 5 7 17

100 7. Methods of estimating floods

Figure 7-4: Catchments in the Orkdal case study 8. A general analysis of the flood vulnerability of roads

8 A general analysis of the flood vulnerability of roads This chapter describes a general analysis of the vulnerability of roads to flooding. The objective of the analysis is to determine which objects are vulnerable to flooding and the kinds of damage to expect, and to develop a procedure for evaluating vulnerable objects.

First, the parties that may have interests in a vulnerability study of the road system are identified and their need for information is assessed. Secondly, analyses of historical data and Preliminary Hazard Analysis are used to identify undesired events and vulnerable objects. As a third step, the findings are analysed and compiled into two lists: 1. Lists of undesired events 2. Lists of vulnerable objects

Finally, several checklists and an “Object evaluation form” are developed and a checklist-based evaluation procedure is suggested.

The findings from this chapter are used as a basis for analysing the road system in Orkdal municipality, which is described in the following chapter.

8.1 Involved partiesand their need for information The objective of a flood vulnerability analysis is to provide essential information to the concerned parties. The information can provide a basis for contingency planning and for planning new infrastructure. Different parties have different interests in the road system, and thus different needs for information. In order to ensure that the analysis will provide the relevant information the parties involved must be identified and their needs assessed.

Three main groups are involved in the road system: owners, users and others. These may in turn be subdivided into several subgroups. Table 8-1 shows the parties involved and their main tasks in relation to a flood.

102 8. A general analysis of the flood vulnerability of roads

Table 8-1: Parties involved in flood-related activities.

Before a flood During a flood After a flood Owners Planning and Maintenance Maintenance (state, county, design Surveillance Redirecting municipality, private) Building Closing unsafe roads traffic Maintenance Redirecting traffic Repairing and Contingency reconstruction plans

Users with tasks vital Contingency Access for surveillance, Protection of to the community plans relief work and evacuation. property (police, fire brigade, Access to important Traffic control ambulance service, structures (dams, power Information to hydropower plants, etc.) the public companies) Traffic control Information to the public Other users Usually no Transport in flooded area Transport in contingency plans flooded area .

The owners will require the most detailed flood performance information. They will want to know where to expect damages, the kind and extent of damages and the consequences.

Users with vital tasks may use flood impact data for contingency planning purposes. They are interested in road closures, but not in details about the cause of the closures.

Casual users do not plan to meet rare flood emergencies, and will not require information until a flood is imminent.

On the basis of the above discussion it is suggested that the following parties should be involved when analysing the vulnerability of the road infrastructure in an area: State Highway Department The local authorities The police department NVE (in Norway) Dam owners and regulating authorities The County Emergency Management Office

103 8. A general analysis of the flood vulnerability of roads

The parties concerned will have different interests in different stretches of road. Some may request detailed information about roads that are of no interest to others.

It is therefore suggested that the road system should be subdivided into stretches and to assess the need for information for each section. Based on the need for information and priorities of the interested parties it is suggested that each section should be allocated to one of the three categories: • Level 0: No information necessary. • Level 1: Assess whether the section will be open to traffic or not. • Level 2: Identify all locations where undesired evens are expected, assess the type and extent of damage and its immediate consequences.

8.2 Description of the road infrastructure For the purpose of this analysis the highway system was subdivided into four parts: 1. Roads 2. Culverts 3. Bridges 4. Other objects

This analysis only considers the parts of the highway inf rastructure in use by the public. Other structures or equipment that are a part of the road infrastructure, i.e. office buildings, workshops, production sites and stockpiles are not considered.

8.3 Assessing undesired events, their causesand consequences Two approaches are used to identify undesired events, vulnerable objects and typical damages. First, historical data on flood impacts on road infrastructure are reviewed. Second, a risk analysis is performed in order to assess road performance during severe floods.

8.3.1 Analysis of historical data on flood damage to roads Most of the information used here is based on the three flood events briefly described below. In addition, information has been taken from other flood reports, papers, articles and newspaper and television news items.

The flood in Jostedalen in 1979 During August 14th and 15th 1979, the River Josted0la experienced a large flood caused by intense rainfall and snowmelt. A hundred residential buildings, 30 - 40 farmhouses and much farmland were damaged. The flood recurrence interval was estimated at 100 years (Roland and Krog 1981).

104 8. A general analysis of the flood vulnerability of roads

“The road system was seriously damaged. Both the main road and several minor roads breached at many locations”.... ’’Six large bridges and a number of smaller bridges were totally destroyed” (Roland and Krog 1981).

Unfortunately, the State Highway Department has been unable to provide any systematic data on the damage. However, some information has been acquired from other sources (Roland and Krog 1981; Andersen 1996).

The large floods in the Mid-West during 1993 The large flood in Mississippi and Missouri during the summer of 1993 was one of the most destructive ever in the history of the USA. It affected an area of 670,000 km2 and lasted from April to late autumn. It resulted in very severe damage and serious obstructions to waterway, railway and road transport. Many roads and bridges were damaged and the total cost of highway repair was 500 million dollars (Changnon 1996). The total costs in the transport sector have been estimated at two billion dollars (Changnon 1996).

The information available was mainly of a general nature (Changnon 1996), but some specific technical information was also available (COE 1994; Parola et al. 1994).

The flood in the south east of Norway during the spring of 1995 The combination of snowmelt and rainfall in late spring 1995 caused major flood episodes in the Glomma catchment, particularly in the eastern part. Flooding seriously affected the road transport system. Roads were damaged at several hundred locations and there were more than 100 closures. The longest closure lasted for 121 days. The State Highway Department in Oppland and Hedmark drew up reports with detailed data on highway damage in each county (Statens vegvesen 1995b; Statens vegvesen 1995a). This author visited the area during and after the flood and inspected much of the damage. On-site inspections by the author and reports from the flood in 1995 provided the most important historical information for this analysis.

A form was designed to record and analyse the historical data. Undesired events, their causes and consequences were recorded separately for each object. Table 8-2 shows an example of how data were registered.

8.3.2 Preliminary Hazard Analysis A risk analysis was carried out in order to uncover undesired events not identified during the analysis of historical data. A Prelimin ary Hazard Analysis was used to

105 8. A general analysis of the flood vulnerability of roads investigate: 1) roads, 2) bridges, and 3) culverts. Table 8-3 shows an example, with some of the findings from the bridge analysis.

106 8. A general analysis of the flood vulnerability of roads

Table 8-2: Analysis of historic data of flood effects on roads Undesired event Cause Effect on object Effect on main function References

Reduced carrying High water level causes Subsidence, deformation and Load restrictions. capacity saturation of the cracking of the pavement Speed restrictions. embankment fill or road particularly if used by heavy Road closed until embankment is foundations. vehicles while saturated. dry. Seepage flow causes wash ­ Increased permeability, formation Load restrictions. out of the fine fractions of of sinks and hollows in the road Speed restrictions. the embankment fills. fill, holes in the asphalt. Road partially blocked or closed for traffic. Scouring of road High water levels in lakes Scouring of the road fill and Load restrictions. embankment and reservoir allow wind ­ damage to the asphalt. Speed restrictions. generated waves to attack Road partially blocked or closed above riprap protection. for traffic. Scouring by high-velocity The effects range from minor From no traffic effects to flow parallel to the road. scour damage to total destruction complete road blockage. of the road.

107 8. A general analysis of the flood vulnerability of roads

Table 8-3: Example of Preliminary Hazard Analysis applied to a bridge. Hazard Cause Effect on object Effect on main Other effects function High water level Serious flooding High water level creates Traffic speed restrictions Damage to pipes and cables Insufficient capacity uncertainty as to whether bridge Closed for traffic fitted to bridge is safe or not. Uplift dislocates the bridge Closed for traffic Damage to pipes and cables Bridge floats away fitted to bridge. Reduced load carrying capacity Load restrictions Damage to pipes and cables due to saturation of the Traffic speed restrictions in road fill. embankment fill Closed for traffic Water level Serious flooding Water flow across bridge deck Traffic speed restrictions Increased backwater effect. exceeds bridge Insufficient capacity Closed for traffic high chord Pier scour Insufficient riprap Pier subsidence Closed for traffic Damage to pipes and cables protection Bridge subsidence fitted to bridge. Pier foundations too Bridge failure. shallow Abutment scour Insufficient riprap Abutment subsidence Closed for traffic Damage to pipes and cables protection Bridge subsidence fitted to bridge. Abutment foundations Bridge failure. too shallow

108 8. A general analysis of the flood vulnerability of roads

8.4 Undesired events and vulnerable objects The finding s of the PHA and historical data revealed a number of undesired events and vulnerable objects. The findings were analysed and the results are presented as a list of undesired events and a list of vulnerable objects.

8.4.1 Undesired events identified during the study Table 8-4 shows the list of undesired events identified during the study. Each event is discussed in the following sections. Table 8-4: Undesired events identified by risk - and historical analysis

Undesired event Road Culvert Bridge Reduced load-bearing capacity X X X Road flooded X X X Internal erosion of road embankment X X X Overtopping of road embankment X X X Scouring of road embankment by parallel X (X) (x) flow Embankment scoured by wind-generated x (x) X waves Instability and slope failures X X X Road blocked due to flood mitigation X (x) X measures Sediment deposits on the road X X X Debris flow X (x) Flood tourism X (X) Fallen trees over road X Light embankment fills dislocated by uplift X Lateral river movement (x) X X Traffic stopped due to safety concerns (x) (X) X Scouring at foundations X Structural damage by impact from large floating debris Overloading of structure by uplift and x water pressure Debris accumulation obstructing flow X X Scouring below culvert outlets X Culvert scour progressing upstream X Scour around defective culvert barrels X Culvert collapse due to high external X pressure

109 8. A general analysis of the flood vulnerability of roads

Undesired events at roads 1. Reduced load bearing capacity. High water levels may saturate the road embankment and severely reduces its load-bearing capacity. Fine-grained fills such as silt and sand are particularly vulnerable. Subsidence and cracking of the pavement may result, especially if heavy vehicles use the road. 2. Road is flooded. A road will normally be closed for traffic even at small inundation depths. 3. Internal erosion of road embankment. Internal erosion involves the removal of fines from the embankment fill by seepage flow. Wash-out of fines may result in deformation of the embankment, formation of sinkholes and loss of load bearing capacity. In serious cases the wash-out may develop into piping and eventually breach the road embankment. 4. Overtopping of road. Overtopping flow results if the water level on one side of the embankment exceeds the road crest. High flow velocities and serious scour damage may result if the downstream slope is steep and the difference in water level is large. 5. Scour by parallel flow. High-velocity flow parallel to the road embankment may result in serious scour damage or total destruction of the road. Road embankments filled into steep rivers are particularly vulnerable. 6. Embankment scour by wind-generated waves. A riprap layer normally protects road embankments along the shoreline of lakes. During serious floods the water level will often rice beyond the riprap protection, allowing wave action to scour the unprotected fill. 7. Instability and slope failures. High pore pressure severely reduces the stability of highway embankments resulting in surface slips or sliding along surfaces situated deeper down in fill. This typically happens at embankments of fine ­ grained fills with high water level on one side. 8. Road blocked due to flood mitigation measures. Many roads act as flood levees and extending the protection level with sandbags may block the road for normal traffic. 9. Sediments deposited on road. Large floods will often lead to a massive transport of gravel, rocks and even boulders in steep rivers. When the slope of the river flattens out, or if there is a backwater, the sediments will be deposited. This often occurs at culverts, bridges and on alluvial fans and may result in rock and gravel being deposited across the road. 10. Debris flows. Heavy rainfall will saturate the soil and initiate a number of debris flows that may block or damage roads. 11. Flood tourism. Large crowds of spectators travel to locations with good views of the flood drama. Illegal parking and crowds of people may obstruct traffic and important rescue work. 12. Fallen trees over road. Saturation of the soil and high pore pressure make the ground surface unstable and may result in trees falling over the road.

110 8. A general analysis of the flood vulnerability of roads

13.Light embankment fills dislocated by uplift. In areas where the ground has poor load bearing capacity the road fill may be constructed from special low- density materials. When they are subjected to high water levels such fills will have extremely poor stability and may even float away.

Undesired events at bridges The undesired events identified for roads are also common at bridges. In addition, the following events were found typical for bridges: 1. Lateral river movement. Scouring of riverbanks or deposition of sediments in the river channel may cause the river to move laterally causing scour damage at unexpected locations. 2. Traffic stopped due to safety concerns. Exact data on the maximum safe water level for a specific bridge are not normally available. During serious floods, engineers from the Highway Department will have to decide if the bridge is to be kept open for traffic or not. Considerably uncertainty may be involved in the decision process and it is believed that bridges are often closed at lower flows than their actual safe capacity. 3. Scouring. Scouring at the bridge foundations is a common cause of bridge damage or failure. 4. Impact from heavy floating debris. Large objects such as boats, barges and tanks may come drifting with the flow. On impact, they may cause considerable damage to bridges. 5. Overloading of the bridge structure. If the water level exceeds the low chord level the bridge superstructure will be subjected to uplift and pressure. Most bridges are heavy and stiff constructions that can resist both uplift and large lateral forces. For small bridges constructed from light materials such as timber, and for bridges subjected to large flow velocities, the ability to withstand pressure and uplift forces should be considered. 6. Debris accumulation obstructs the flow. During large floods, in particular in steep forested catchments, large amount of woody debris may be transported by the flow and build up on bridge piers or on the superstructure. Debris accumulation has several negative effects. It constricts the flow, increases the headwater level and pressure differences across the bridge and raises flow velocities. As a result, the danger of piping, overtopping and scour damage increases. 7. Blocked due to flood mitigation measures. Bridges are high-cost structures and great efforts will be made to protect them from damage. Heavy loads placed on the bridge deck to prevent uplift or sliding and cranes and tracks to remove floating debris may obstruct traffic for long periods.

Ill 8. A general analysis of the flood vulnerability of roads

Undesired events at culverts Like bridges, culverts are vulnerable to many of the hazards discussed in the section on roads. Some additional events were identified as applicable only to culverts: 1. Scour below the culvert outlet. Serious scour damage may occur below culvert outlets that are not protected with riprap or energy dissipation basins. Large scour-holes may reduce the stability of the road embankment and result in part of the road sliding into the scour-hole. 2. Scour progressing upstream. If a large scour-hole forms it may undermine the culvert foundations. The outlet structure and the downstream culvert sections may cave into the scour-hole. The erosion will progress upstream and may result in the embankment being cut off. 3. Scour around defective culvert barrels. Many old culverts have dislocated pipe sections with large gaps between them. With high internal water pressure water will flow out through the gaps and into the embankment causing serious scour damage. 4. Culvert collapse. During serious floods, the discharge may be several times greater than the culvert capacity, resulting in excessive upstream water levels and high water pressure at the intake. At the same time low pressure may exist inside the culvert barrel due to free surface flow or large entrance losses. The culvert barrel may collapse, resulting in reduced flow capacity and water scouring of the fill on the outside of the collapsed barrel. 5. Debris blocking the culvert inlet. Floating debris, rocks and sediments may fill the front of the culvert entrance. This reduces the flow capacity of the culvert and raises the upstream water level.

8.4.2 Flood-vulnerable objects and their characteristics Road systems are large systems that cover vast areas. To analyse every part of the system is not feasible, and easily recognisable characteristics are needed to identify vulnerable objects. Based on the previous analysis the four general characteristics were used to identify vulnerable objects during the case study: 1. Locations where the road crosses water (bridge or culvert). 2. Road fills close to rivers and lakes. 3. Roads with low elevations compared to rivers and lakes. 4. Roads, rivers or bridges on alluvial fans.

No good characteristics were found for stretches of road subjected to flood tourism or trees falling over the road. An experimental approach to identifying stretches of road vulnerable to debris flow is discussed in Chapter 6.

112 8. A general analysis of the flood vulnerability of roads

8.4.3 Developing checklists for vulnerability assessment It is suggested that checklists should be used to evaluate vulnerable objects. This will help to ensure that all relevant undesired events are systematically evaluated, and will serve to document the results. Three checklists and an evaluation form have been developed for assessing the vulnerability of roads: 1. General checklist. This includes the most typical undesired events occurring at roads, but which are also common at culverts and bridges. The generalchecklist is shown in Figure 8-1. 2. Culvert checklist. The culvert checklist is shown in Figure 8-2. 3. Bridge checklist. The bridge checklist is shown in Figure 8-2. 4. Object evaluation form. This is used to evaluate the total object performance and is shown in Figure 8-3.

Using checklists to evaluate object performance during floods The checklist-based vulnerability analysis consist of four separate steps: 1. The object under investigation is described and relevant data recorded. 2. The probability and direct consequences of each undesired event on the checklist are evaluated. 3. The quality of the evaluation is assessed and a further investigation is made if necessary. 4. The overall performance of the object is evaluated.

Preparations for the evaluation include the collection of survey data, photographs, flood discharge hydrographs, etc. A brief description of the object, its location and object ID is entered in the object description field of the evaluation form.

The undesired events in the list are evaluated one by one. First, the probability of the event is evaluated and assigned a probability from 1 to 3. 1 indicates a low probability, 2 medium probability and 3 a high probability of occurrence.

Next, the undesired events are evaluated and expected damage is classified from 1 to 3. Class 1 involves damage that do not affect the function or safety of the object. Class 2 indicates damage that will prevent the object from functioning as intended, or threaten the safety of users. Typical types of damage are subsidence of the road fill, piping and sinkholes. Class 3 involves severe damage that will result in costly and time-consuming repair work. Typical examples are the breaching of road embankments and subsidence or failure of bridge foundations.

Finally, the immediate effect of the undesired event on the main function of the object is evaluated. Three classes of effects are used: Class 1 indicates zero or minor effects. Class 2 means that traffic flow is disrupted but the object is still

113 8. A general analysis of the flood vulnerability of roads passable. Restrictions on speed, axle loads or narrowing to a single lane are typical examples. Class 3 indicates that the road will be closed to traffic.

It is believed that three classes are sufficient to describe the probabilities and effects of undesired events. In most cases the evaluations are approximate and have to rely heavily on the judgement of the analyser. Using several classes would suggest that the results are more accurate than they really are.

After going through the checklist, the overall performance is assessed. The findings obtained from the checklists are compiled and summarised in the “Object evaluation form”. The expected damages, causes and effects are described for each flood scenario.

The checklists and the “Object evaluation form” provide documentation of the evaluation process, showing what hazards have been evaluated and how they were assessed.

In many cases the hazard evaluation must be performed in an iterative manner. The first evaluation may be inconclusive and show that more data are required. After new data have been prepared, a new analysis can be carried out. This process may continue until the analyser considers the results adequate for the kind of analysis being made.

114 8. A general analysis of the flood vulnerability of roads

CHECKLIST Scenario: Q100, Q1000, PMF Date: Signature:

OBJECT DESCRIPTION Object ID: | Road#: | Location: | Riven Description:

GENERAL CHECKLIST UNDESIRED EVENT Probability of Extent of Effect on main occurrence 1 damage1 function 1 Scenario: SI S2 S3 SI S2 S3 SI S2 S3 HIGH WATER LEVEL Road flooded Strong current across the road Subsidence of pavement due to saturation of fill Reduced load capacity due to saturation of fill Timber debris deposited on road Fine sediments deposited on road Rocks / boulders deposited on road HIGH WATER PRESSURE Downstream road fill slope not stable Road embankment Mis along deep slip circle Internal erosion of road fill Piping through the road embankment SCOURING Overtopping of the road Scouring of downstream embankment slope bv overtopping flow. Scour by parallel flow Scouring by wind-generated waves OTHER EVENTS Excess discharge will follow the road Overtopping along uncontrolled flow path Scour along uncontrolled flow path Uplift in light fills Flood tourism Flood mitigation measures 1 = none/low, 2 = medium, 3 = large Figure 8-1: Checklist for roads

115

I 8. A general analysis of the flood vulnerability of roads

CULVERT CHECKLIST UNDESIRED EVENT Probability of Extent of Effect on main occurrence' damage1 function' Scenario: SI S2 S3 SI S2 S3 SI S2 S3 SCOUR DAMAGE Scour damage at inlet Scour hole at outlet Scour damage to culvert exit section Scour progresses upstream OTHER EVENTS Culvert clogged by floating debris Culvert clogged by sediments Culvert collapses due to external pressure 1 - none / low, 2 — medium, 3 = large

BRIDGE CHECKLIST UNDESIRED EVENT Probability of Extent of Effect on main occurrence' damage' function' Scenario: SI S2 S3 SI S2 S3 SI S2 S3 APPROACH EMBANKMENT SCOUR Scour by impinging flow Scour bv contracting/accelerating flow Scour bv wake downstream of road ABUTMENT SCOUR Scouring of riprap protection Scour hole formation Scour damage to foundations PIER SCOUR Scouring of riprap protection Scour hole formation Scour damage to foundations OVERLOADING Uplift caused bv high water level Pressure against bridge superstructure Harmful vibrations Impact of large floating debris OTHER EVENTS Timber debris build-up on bridge Sediment build-up at bridge section Lateral river movement Bridge closed to prevent flood damage Bridge closed due to safety concerns Bridge closed by other flood mitigation measures 1 = none / low, 2 = medium, 3 = large

Figure 8-2: Checklist for culverts and bridges

116 8. A general analysis of the flood vulnerability of roads

OBJECT EVALUATION FORM Date: Signature:

OBJECT DESCRIPTION ______Object ID: | Road#: | Location: | Riven Description:

CONCLU SION Scenario Damage1 Effect1 Brief description of most important problems Qioo Qiooo PMF 1 — none / low, 2 — medium, 3 = large

SUMMA RYOF FINDINGS Scenario Undesired event Effect Qioo

Qiooo

PMF

MAINSH ORTCOMINGS /UNCERTAINTIES Scenario Uncertainties Suggested measures Qioo

Qiooo

PMF

RECOMMENDATIONS FOR FURTHER INVESTIGATIONS

COMMENTS

Figure 8-3: Object evaluation form

117 9. Analysis of roads in Orkdal

9 Analysis of roads in Orkdal This chapter describes the flood vulnerability analysis of the road system in Orkdal. It consists of four main parts. The first part describes organisation of the work, the flood scenarios and the road system in the study area. The second part is concerned with the identification and evaluation of vulnerable objects, in particular the methods used for assessing the physical impacts of flooding. Third, several detailed examples of flood vulnerability assessment of road objects are discussed. Finally, the overall results from the study are presented.

igure 9-1: General view of the study area

118 9. Analysis of roads in Orkdal

9.1 Objectives of the analysis The primary objective was to assess how major floods might affect the road system in Orkdal municipality. The secondary objective was to explore methods of identifying flood vulnerable objects and of assessing how they would be affected by flooding.

9.2 Organisation of the work This study started as a part of the risk and vulnerability study (ROS) of flooding that Orkdal municipality was performing in 1996 (Selboe 1997). A working group, of which the author was a member (Chapter 3) performed the ROS study. However, the working group was dissolved before the road analysis covered by this work had been finished and the major part of the present work was done without the support of the working group.

9.3 Selection of flood scenarios Three scenarios were selected for further study: 1. The 100-year rainfall scenario 2. The 1000-year rainfall scenario 3. The Probable Maximum Rainfall scenario

It was believed that these rainfall scenarios could be used to model floods with approximately the same recurrence interval as the rainfall event. Contribution due to snowmelt was not included.

9.4 Description of the road system in Orkdal Orkdal is a municipality in Spr-Trpndelag county in Norway. Its administrative centre is located in Orkanger where the valley Orkdalen meets the sea. There are several villages further south in the valley: Fannrem, Vormstad and Svorkmo. The main river Orkla flows through the municipality from south to north. Orkla’s catchment covers 3089 km2. A general view is shown in Figure 9-1.

The main road is Route 65, which comes from Trondheim and follows the valley in a north-south direction. In the north Route 65 follows the eastern side of Orkla. At Fannrem it crosses over to the west bank of Orkla. At Orkanger Route 714 branches off for Hitra and Route 710 for Agdenes. At Fannrem Route 71 branches off to the west to Kyrksseter0ra and at Svorkmo Route 700 branches off for L0kken.

9.4.1 Subdividing the road system and assigning priorities The study focused on the main north-south road, Route 65, which was studied from Bprsa to Svorkmo. The main highways to the northwest, Route 710 and Route 714 were also included in the study.

I 119

■’.A ■ 9. Analysis of roads in Orkdal

Several secondary roads exist in the area, some run parallel to Route 65 and others out of the valley to the west or east. If the main road is blocked the secondary roads may be the only transport arteries, and the most important of them were also included in the study.

The road system was divided into 14 stretches, which are described in Table 9-1. Two levels of analysis were employed: Level 2 analysis which involves an evaluation of each and every flood vulnerable object along the stretch, and Level 1 analysis which is carried out in order to determine whether the road stretch will be passable or not. Table 9-1: Highway system subdivided into stretches Stretch Route Start End Analysis number level 1 65 B0rsa Bardshaug 2 2 65 Bardshaug Fannrem 2 3 65 Fannrem Bridge, east Fannrem Bridge, west 2 4 65 Fannrem Bridge, west Vormstad 2 5 65 Vormstad Svorkmo (Tronvoll) 2 6 700 Svorkmo (Tronvoll) Svorkmo bridge, east 2 7 710 Bardshaug 0yan 2 8 710 0yan Gj0lme 2 9 710 Gjplme Rabygda 2 10 714 Gj0lme Gagnasvatnet 2 11 - Fannrem Solbu 1 12 - Solbu Svorkmo Bridge, west 1 13 - Solbu Vormstad 1 14 - 0yan Fannrem Bridge, west 1

9.5 Identification of vulnerable objects The objective of the identification phase was to identify all potentially vulnerable objects during the flood scenarios that were being considered. This includes objects that could be damaged by the flood and objects where traffic obstructions might occur.

Each stretch was investigated in the course of a desk study that used the vulnerable object characteristics discussed in Chapter 8 as a basis for identifying objects for further investigation. Several techniques were used to identify the objects: 1) maps at a scale of 1:50000 to 1:5000, 2) flood-zone maps (Selboe 1997), 3) aerial photographs and 4) GIS techniques.

120 9. Analysis of roads in Orkdal

A total of 88 objects were identified as vulnerable to floods. Each object identified was given an identification number and a database of all the objects was established using the database workshop in the Idrisi GIS. The database was linked to the digital map of the area, which made it easy to update the map to reflect changes in the database.

A table of objects that contains the object identification number, object type, the spatial co-ordinates and the name of the location was also composed for each stretch. A sample is shown in Table 9-2. Figure 9-2 shows where the objects are located. Appendix B has a complete list of objects and Appendix C contains maps that show the locations in detail.

Table 9-2: Potentially vulnerable objects in Stretch 1 Stretch: 1 Start: B0rsa End: Bardshaug Object Object Location name Co-ordinates ID type 1 (m) 1-1 C Vikan 552150 7024550 1-2 C Lundteigen 551450 7024600 1-3 B Viggja 549650 7024450 1-4 C Sildvaertangen 548800 7024700 1-5 C Trasavika, south 547550 7023800 1-6 C Storsanden (0sthusbekken) - 546850 7023425 1-7 C Litisanden 5453007022500 1-8 C Litisanden 545000 7022250 1-9 c Litisanden 544800 7022100 1-10 c Thamshavn 544200 7021550 1-11 c Thamshavn 543800 7021250 1-12 c Orkanger 543150 7020400 1-13 c vElilykkja 552950 7023750 1-14 c Stykkan 550750 7024550 1C: culvert, B: bridge, LR: low road, CR: close road, O: other objects

121 9. Analysis of roads in Orkdal

^Meters Grid North 10000.00

Figure 9-2: Objects identified as potentially vulnerable to floods

122 9. Analysis of roads in Orkdal

9.6 The evaluation of flood vulnerable objects In this phase all objects from the identification phase were evaluated to assess how they would be likely to perform during the flood scenarios. The main objectives were: 1) to assess how the main function of the object would be affected and 2) to assess what damage would be sustained.

The evaluation phase involved several steps. First, a preliminary screening was carried out in order to eliminate objects that are not vulnerable to flooding. This was done by the means of a desk study followed by a field investigation. Second, the objects that remained after the preliminary screening were evaluated in depth by means of checklists. To substantiate the evaluation it was often necessary to compute flood discharges, water surface profiles, flow velocities, scour depths etc. The evaluation procedure is outlined in Figure 9-3.

9.6.1 Preliminary screening of vulnerable objects The objective of the screening was to eliminate objects from the study. The approach that was taken depended on the stretch under investigation. For level 1 stretches the main objective was to determine whether the stretches would be passable or not. In this case the screening process attempted to identify the objects that are most susceptible to flood damage so that they could be studied further. For level 2 stretches the objective was to obtain an overview of all flood hazards, and all objects considered susceptible to flood damage were included for further study.

Each object was assessed using checklists as part of a desk study. Flood-zone maps, topographic maps at a scale of 1:5000, geological maps and aerial photograph stereoscopy were used in the screening. For some objects the desk study was not conclusive and a field inspection was carried out in order to determine whether the objects could be ruled out of the study or should be considered further. 9. Analysis of roads in Orkdal

For level 2 stretches all culverts and bridges were regarded as vulnerable to flooding. However, due to time constraints culverts with a catchment smaller than approximately 0.5 km2 were excluded from the study.

List of objects potentially vulnerable to floods

Initial screening 1. Desk study 2. Field inspection Rainfall assessment

Flood calculations General checklist Culvert capacity assessment Culvert checklist < Flood profile calculations Bridge checklist Riprap stability assessment Object evaluation form Scour depth assessment I : Object performance Slope stability analysis during floods

Figure 9-3: Object evaluation flow chart

Several objects along the Orkla river were eliminated from the study by using the flood-zone maps prepared for the ROS project (Selboe 1997). Along Skjenaldelv the water depths were estimated assuming unif orm flow, and several of the objects could be excluded as they were far above any flood levels that could possibly occur.

Along Skjenaldelv and Orkla several objects were initially regarded susceptible to scouring because of their proximity to the river. However, field inspections showed many of them to be safe because they were founded on bedrock or because the distance from the river was greater than estimated from the map.

For level 1 stretches the low lying areas along Orkla and the main culverts and bridges were selected for further analysis as they were considered to be the most vulnerable to flooding, as well as being easiest to evaluate.

124 9. Analysis of roads in Orkdal

9.6.2 In depth hazard evaluation of each object Objects still considered vulnerable after the preliminary screening were evaluated further in order to assess their performance during the selected flood scenarios.

The evaluation procedure used checklists for evaluating the possible hazards. It started with assessing general hazards, continued with culvert and bridge hazards, if relevant, and finally evaluated the overall performance of the object.

9.6.3 General hazard evaluation of roads The general evaluation included hazards common to all parts of the road system, of which inundation, piping and scouring are typical examples. The general hazard evaluation was always carried out before specific culvert or bridge hazards were evaluated

Methods used for the evaluation of general hazards The general hazards were divided into four main groups: 1) high water level, 2) high water pressure, 3) scouring, and 4) other hazards. The methods that were used to evaluate each group of hazards are discussed below.

Evaluation of hazards caused by high water levels Several methods were used to establish water levels for the three scenarios. Along Orkla the flood surface profile was estimated using HEC-RAS and by using the flood-zone map prepared during the ROS project (Selboe 1997). On tributaries and smaller rivers HEC-RAS was used to compute flood profiles at several bridges and culverts. Where it seemed reasonable to assume uniform flow the Manning formula was used to estimate the depth of flow.

In order to establish whether an object would be flooded the estimated water levels were compared to road elevations obtained from maps, site inspections and from VEBAS (Chapter 6). The flood profile form HEC-RAS was used to assess the probability of strong currents across the flooded road.

An attempt was made to account for the fill material, the foundation material and the expected duration of flooding when investigating the loss of load bearing capacity due to saturation. Fills of fine sand and silt were considered particularly vulnerable whereas fills of rock and gravel were not considered to be liable to saturation damage.

Evaluation of hazards caused by large pressure gradients Large pressure gradients through road embankments will result in seepage flow, which may considerably reduce slope stability and lead to washout of the fine fractions of the fill. Seepage may develop into piping and eventually to breaching of

125

'*jr~ *2 9. Analysis of roads in Orkdal the whole embankment. Large gradients typically occur at high embankments running parallel to rivers, and at river crossings where there are large pressure differences from upstream to downstream of the conveyance structure.

The safety factor against shallow slope failures may be found by considering the forces acting on a thi n slice of soil parallel to the slope. Assuming that the attraction = 0 and flow direction is parallel to the slope, the safety factor can be expressed as (Nordal and Grande 1989): c = Ys~Y tan(p (9-1) 7s tan/3 where: Cs = Safety factor y s = Specific gravity of soil y = Specific gravity of water P = Slope angle (p = Friction angle

For horizontal flow the safety factor is (Nordal and Grande 1989): y__ 2L_ (9-2) C, - ' 0082 1 tm’’

Ys tan The maximum stable slopes (Cs=l) for some soils (attraction = 0) are shown in Table 9-3. The attraction in several soils, in particular those containing clay, will result in much better short term stability and steeper slopes than indicated in Table 9-3.

Table 9-3: Side slope with a safety factor equal to 1 for different soils and different seepage situations (Nordal and Grande 1989). tan cp No seepage Seepage Horizontal parallel to seepage slope Loose silt 0.5 1:2.0 1:4.0 1:4.2 Silt/sand 0.7 1:1.4 1:2.8 1:3.7 Compact 0.9 1:1.1 1:2.2 1:2.6 sand

Seepage flow emerging on the downstream embankment slope will dramatically reduce slope stability and shallow slope failures should be expected in most road fill embankments that remain saturated for some time.

126 9. Analysis of roads in Orkdal

When subjected to high pore pressures and large pressure gradients the embankment may become unstable along planes located deeper in the fill. The pore water pressure will reduce the effective vertical stresses and horizontal pressure gradients will increase the shear stresses. The resulting failures are far more serious than the surface instabilities discussed in the previous paragraphs, because a much larger section of the embankment will be involved in a failure.

The embankments that would experience large pressure gradients were analysed in order to assess their stability. The “direct method ” (Hjeldnes 1989) for analysing the stability of circular shear surfaces was used. This is a semi-graphical method for both drained and undrained shear stress calculations where charts are used to assess safety factors and locate failure planes.

Seepage flow through a road fill may remove the fines if the material is not self- filtering, resulting in increased flow, formation of sink holes, subsidence and cracking of the road pavement. The following rule of thumb was used when evaluating the danger of piping: expect sink holes and boils to occur at gradients larger than 0.1 and serious piping or failure for gradients greater than 0.25.

Evaluation of scour hazards Two kinds of scouring were evaluated for roads: 1) scour by flow parallel to the road and 2) scour by overtopping flow.

Parallel flow scour typically occurs at road embankments runnin g parallel and close to steeply falling rivers. High rates of parallel flow may also occur along the upstream side of emba nkm ents at river crossings. If the capacity of the bridge or culvert is insufficient excess water may be forced to flow parallel to the embankment, for example in the ditch along the road. Flow that overtops embankments will typically occur at river crossings (bridges and culverts) and at high embankments parallel to the river.

The scour hazard evaluation was performed in two stages: first, it was evaluated if the threshold of scouring would be exceeded. Second, if scouring was expected, the amount of scour was assessed.

For parallel flow the threshold of scouring was evaluated using Eq. (5-1) and Eq. (5-7) as programmed into SCOUR. The COE method (5-5) which was also included in SCOUR was found to predict initiation of scouring at much lower velocities than the other methods and was not used further.

The amount of scour was estimated by considering the duration of scouring, the excess shear stress and the stability of dislocated riprap. Scour duration was

127 9. Analysis of roads in Orkdal estimated from the flood hydrographs. If scour occurred on a steep side slope it was considered if scoured rock could be moved by the flow once it had been displaced to the riverbed at the toe of the slope. If the rocks could not be transported by the flow they would accumulate at the toe of the slope and reduce scour development.

Scour by overtopping flow was evaluated using the overtopping module in SCOUR. The threshold of scouring was evaluated using Eq. (5-31) and Eq. (5-32). The main problem was to estimate the unit discharge. As the overtopped embankments were mostly quite flat a detailed survey of road crest elevations would be needed for precise estimates of the unit discharge at the crest. This could not be justified, as irregularities on the downstream slope will cause the flow to concentrate and drastically change the unit discharge rate. Instead, maximum and minimum unit discharge rates were estimated from the expected flow width at the crest and the rock sizes required for stability were calculated for the range of unit discharge rates.

For vegetated slopes the flow velocities on the downstream slope were calculated for the range of unit discharges and compared with the limitingvelocities for scouring on grass-covered slopes (Hewlett et al. 1987) in order to assess the probability of scouring.

Evaluation of other hazards The scour and overtopping by floodwater forced to flow parallel to the road were estimated using the techniques discussed above. Road embankments constructed from light fills were not considered. The probabilities and effects of “flood- tourism” and flood mitigation measures were evaluated using engineering judgement only.

9.6.4 Hazard evaluation at culverts In the course of the case study, culverts were found to be highly vulnerable to floods. Many culverts had been dimensioned for floods with recurrence intervals of 50 years or less, several suffer from poor maintenance and the culvert inlets were often partially blocked by debris. In many cases sections of the culvert barrels were cracked, dislocated or squeezed by the soil pressure, as shown in Figure 9-4.

The main dimensions of the culvert and the road embankment were measured by tape measure, and the culvert entrance, barrel and exit were inspected for damage. The scour resistance, rock size and vegetation of the downstream and upstream slopes were checked and the approach and exit flow conditions were evaluated.

Methods used for evaluating culvert hazards The spreadsheet programme discussed in Chapter 4 was used to compute the culvert discharge rating curve in the cases where the culvert exit was not expected to be

128 9. Analysis of roads in Orkdal submerged. If the downstream water level would affect the culvert capacity cross- sections were surveyed and HEC-RAS was used to calculate the capacity, upstream water level, discharge through the culvert and overtopping discharge for each flood scenario.

Flood hazards were assessed according to the checklist described in Chapter 8. The general hazards were evaluated as discussed in the previous section. In addition, two special culvert hazards were evaluated: 1) outlet scour and 2) parallel flow upstream of the culvert embankm ent. The culvert module in SCOUR was used to assess scour depths below the outlet. The relevant culvert dimensions, discharge and rock size data were entered, together with maximum and minimum tailwater levels. The program selected the appropriate scour equations and computed the scour depth between the limiting tailwater levels. Rock size and discharge were easily changed to assess how the uncertainty in the input variables affected the scour depths.

Flow along the upstream side of the road may result in considerable scour damage and SCOUR was used to evaluate scour susceptibility. The flow was assumed to occur in a trapezoidal channel where the bottom width, the bed slope, the side slopes and maximum and minimu m values of Mannin g’s n were entered by the user, and scour damage was assessed in the same mann er as for parallel flow.

Figure 9-4: Flat culvert (Object 1-1)

129 9. Analysis of roads in Orkdal

9.6.5 Hazard evaluation at bridges Norwegian and international experience has shown that bridges can be vulnerable to flooding, and abutment and pier scouring is the primary cause of damage. The large flood in Jostedalen (Roland and Krog 1981) damaged more than twenty bridges. However, few bridges were damaged during the considerably larger flood in Eastern Norway in 1995 and it may seem that scour protection on large-state owned bridges is far better than on the many smaller private or community-owned bridges.

In comparison with other riprap design formulae (Chapter 5) the design guidelines used by the State Highway Department (Statens vegvesen 1990) oversize the riprap protection for low flow velocities, but under-sizes the riprap for flow velocities above approximately 3 m/s. This means that only minor scour damage will occur at the large bridges that cross the relatively flat main rivers. However, scour damage may be expected at smaller bridges crossing the steeper tributaries.

Road embankments approaching the bridge are also highly flood vulnerable. The head loss through the bridge causes high-pressure gradients across the embankment. These may result in seepage, loss of fines, piping, overtopping and breaching.

The bridges were inspected and photographed during low flow. Special attention was paid to the riprap protection at piers and abutments. Cross-sections needed for hydraulic computations were surveyed and drawings of the bridges were obtained from the State Highway Department in S0r-Tr0ndelag.

Methods used for evaluating bridge hazards Flow parameters that were needed for the evaluation were computed by means of HEC-RAS. The flood hazards were evaluated using the general checklist and the bridge checklist.

Pier scour was evaluated in two steps. First, the stability of the riprap was assessed and if the riprap was not regarded as stable, the depth of the scour-hole was estimated. The pier module in SCOUR was used to assess riprap stability and scour depths.

Riprap stability at abutments was assessed with SCOUR, and scour depth was estimated using Eq. (5-20).

130 9. Analysis of roads in Orkdal

9.6.6 Assessment of overall object performance during selected flood scenarios After the relevant points on the checklist had been evaluated the expected overall performance during the flood scenarios was assessed using the Object Evaluation Form (Chapter 8). The expected damage and its effects were assessed, described in the form and classified from 1 to 3.

The uncertainty of the analysis was also evaluated and described in the Object Evaluation Form. If the uncertainty was regarded as unacceptable, measures to improve the analysis were suggested and, if necessary, a new analysis was performed. The results of the evaluation were entered in the Idrisi data-base and linked to an image of the area.

9.7 Examples Four examples are presented to demonstrate the hazard evaluation methods used. The analysis of culvert 9-7 is included in order to demonstrate capacity calculations, stability analysis, scouring by overtopping flow, scouring by excess flow in the road ditch and outlet scour. Object 9-4, which is a road embankment partly in the river, is used to demonstrate the analysis of scour due to parallel flow. Object 8-2, a bridge over Skjenaldelv, is used to demonstrate how pier and abutment scour was assessed. Finally, the method that was used to identify inundated road sections along Orkla is included to demonstrate one of the applications of GIS during the case study.

9.7.1 Hazard analysis of culvert 9-7 Storbekken The Storbekken brook crosses Route 710 through culvert 9-7. Storbekken drains a steep 3.2 km2 catchment and by using the rational method the peak floods were estimated to be: Qmo = 10 m3/s, Qiooo = 14 m3/s and PMF = 28 m3/s. The culvert barrel is a 2.3 m diameter corrugated steel pipe with a vertical concrete wing wall at the inlet. The steel pipe projects approximately 0.1 m beyond the wall. The culvert outlet is on a steep slope. Overtopping of the road fill will start when the headwater is 5 - 6 m above the culvert invert. The culvert is shown in Figure 9-5.

131 9. Analysis of roads in Orkdal

Figure 9-5: Object 9-7: Culvert at Storbekken

Culvert capacity calculations As it was evident that the culvert outlet would not be submerged, the culvert capacity was computed using CULVCAP and the capacity chart is shown in Figure 9-6. Qioo and Qiooo can be conveyed without the headwater level exceeding the height of the emb ankm ent. With a headwater of 5 m and 6 m the culvert capacity is 22 m3/s and 25 m3/s respectively and during PMF 3 m3/s to 6 m3/s can be expected to overtop the road embankment or to flow along the road side ditch.

Evaluation of outlet scour The culvert discharges onto a steep scree with a slope of approximately 1:1.7 and is covered with rocks 0.5 m - 1 m diameter. During the PMF situation, with a culvert discharge of 22 m3/s and an outlet velocity of 5.3 m/s the jet will impact approximately 3 m below the invert. A range of tailwater levels from -3 m to - 1.5 metres measured from the barrel invert, was therefore studied and SCOUR was used to calculate the scour depths for rock diameters of 0.5 m and 1 m respectively. The results, shown in Figure 9-7, indicate a maximum scour depth of - 8 to - 12 m.

132 9. Analysis of roads in Orkdal

Culvert capacity chart

«?; 25 --

O 20 --

Headwater or depth of flow in barrel, Y (m)

Free flow Inlet control Submerged inlet control, square edge Submerged Inlet control, rounded -x- Full flow outlet control -e-Uniform flow

Figure 9-6: Object 9-7: Culvert capacity chart

The steep scree at the outlet differs greatly from the flat-bed conditions usually employed in culvert scour experiments. The rock stability was therefore also assessed using methods developed for steep rock chutes (Abt and Johnson 1991; Robinson et al. 1993). The stability was evaluated for a range of slopes and for two unit discharges corresponding to flow widths of one and two culvert diameters. The results, shown in Figure 9-8 and Figure 9-9, indicate that the rocks at the outlet will not be stable and that a scour-hole will form.

In evaluating how the scour-hole will affect the stability of the embankment the maximum scour depth was assumed to occur along the free-fall jet trajectory. Side slopes flatter than 1:1 were assumed to be stable for a short time, slopes 1:1 to 1:0.8 were assumed to have medium to high probability of failure, and steeper slopes were assumed to fail. On this basis the probability of damaging the culvert barrel support during PMF was assumed to be medium to high.

Outlet scour was also evaluated for Qioo and Qiooq. For Qiooo the rocks at the outlet will be partly unstable and a scour-hole will form, but this was not expected to result in serious damage to the road. For Qioo only minor scour damage was expected.

133 9. Analysis of roads in Orkdal

Scour depth below culvert outlet

dso = 0.5 m

Tailwater elevation, Z-™, (m)

Eq. (5-25) Eq. (5-24) -e- Eq. (5-25) -B- Eq. (5-24)

Figure 9-7: Object 9-7: Scour depth at the culvert outlet

Rock stability below culvert outlet

= 4.8 rrr/sm 1.4 -

1.0 - o.a -

0.6 --

0.4 --

0.2 --

35% 70% Bed slope, S0 (%)

-•-Eq. (5-31) -B-Eq. (5-31) modified, failure of rounded rock -e-Eq. (5-32)

Figure 9-8: Object 9-7: Rock stability at the culvert outlet

134 9. Analysis of roads in Orkdal

Rock stability below culvert outlet

2.0 -

_ 1.5-- ■Q—e—9— O'

1.0 -

0.5

35 % 40 % 45 % 50 % 55 % 60 % 65 % 70 % Bed slope, S0 (%)

-a-Eq. (5-31) -e-Eq. (5-31) modified, failure of rounded rock-e-Eq. (5-32)

Figure 9-9: Object 9-7: Rock stability at the culvert outlet

Scour during overtopping flow

0.16-

0.14 < ►

_ 0.12 -

0.10 - Overtopplng width =20 m 0.08 - - Overtopping discharge = 3 m3/s

0.02 - -

55% Bed slope, S0 (%)

Eq. (5-31) -e-Eq. (5-31) modified, failure of rounded rock-e-Eq. (5-32)

Figure 9-10: Object 9-7: Rock stability during overtopping flow

Evaluation of scour by overtopping flow. Only at PMF will the water level rise high enough for the water to find an alternative flow path. A combination of overtopping flow and flow in the ditch

135 9. Analysis of roads in Orkdal along the upstream side of the road embankment, with discharges in the range of 3 - 6 m3/s, was expected. The downstream side of the embankment has a slope of 1:1.7 to 1:2 and consists of sand and gravel with a sparse cover of grass and bushes. A flow width in the range of 5 - 20 m and a Manning's n of 0.033 - 0.05 were assumed when SCOUR was used to assess the stability of the gravel surface. The results are shown in Figure 9-10. Even at the lowest discharge and the widest flow width the rocks on the embankment surface are not stable. The grass cover offers little protection and the flow velocity will rapidly exceed the limiting velocities. Severe scour damage was expected for overtopping flow.

Parallel flow in ditches A high proportion of the excess flow may follow the ditch along the upstream side of the embankment. The ditch is trapezoidal in shape, approximately 1 m deep and 1.5 m wide at the bottom, the side slope is 1:1.7 and the bed slope is approximately 0.05. The soil consists of gravel with a sparse cover of grass.

SCOUR was used to assess the flow parameters, shear stress and stable rock sizes at discharge rates of 2 m3/s and 6 m3/s. Some of the results are shown in Figure 9-11 and Figure 9-12. A 2 m3/s discharge rate results in flow velocities of 2 - 2.5 m/s, which is approximately the limit of what the grass cover can resist and the stable rock size of 0.15 - 0.2 m clearly exceeds the existing gravel size. Moderate to serious scour damage was expected to occur in this situation.

The maximum flow of 6 m3/s will give velocities in the range of 2.5 - 3.5 m/s, which clearly exceeds both the grass cover protection limit and the stability of the gravel. Flow in the ditch will scour the road fill and undermine the pavement for a distance of several hundred metres. Sediments will deposit where the slope flattens and the water flows across the road.

Evaluating seepage and piping Pressure gradients were estimated from the computed headwater levels and embankment dimensions. For Qiooo the gradient is 0.1 - 0.15, which indicates that excess seepage, boils, loss of fines and sinkholes must be expected. For the PMF the gradient is estimated to be 0.25 - 0.3 and serious piping and breaching of the embankment is probable.

Evaluating embankment slope stability The high water pressure during PMF may make the emb ankm ent unstable and the stability against sliding was evaluated using the direct method (Hjeldnes 1989). The fill material was assumed to be crushed rock and the headwater level to be at the road crest. An attraction of 12 kN/m2 resulted in a safety factor of 1.6, while an attraction of 0 gave a safety factor of 0.6. During PMF the safety factor is expected

136 9. Analysis of roads in Orkdal

to be somewhere between these limiting values. As the high water level will last for only a few hours, the probability of embankment failure during that period was considered to be low to moderate.

Parallel flow in ditch, Q = 2 m3/s

n = 0.033 3.0 - ( c 2.0;: lu )

osp

-- 0.10 n = 0.05

0.5 -- - - 0.05

Bed slope, S„ (%) Row velocity, U (n = 0.05) Row velocity, U(n = 0.033) -a-Limiting rock size, d50 (Eq. (5-1), n = 0.05) -m-Limiting rock size, d50 (Eq. (5-1), n = 0.033)

Figure 9-11: Object 9-7: Scour by parallel flow, Q = 2 m3/s

Parallel flow in ditch, Q = 6 m3/s

n = 0.033 4.0 ■-

- - 0.30 3.0 * -

x 2.5

o 2.0 n = 0.05 ■ - 0.15

E 1.0 -0.10

0.5 - - 0.05

Bed slope, S0 (%)

-e-Row velocity, U(n = 0.05) Row velocity, U(n = 0.033) -fi-Umlting rock size, d50 (Eq. (5-1), n = 0.05) Umiting rock size. d50 (Eq. (5-1), n = 0.033)

Figure 9-12: Object 9-7: Scour by parallel flow, Q = 6 m3/s

137 9. Analysis of roads in Orkdal

Object 9-7: Expected performance during flooding 1. Qioo: Minor scour damage below the culvert outlet. 2. Qiooo: Scour-hole formation at the outlet, which may also result in some damage to the culvert exit. High-pressure gradients will result in large seepage flow, so internal erosion and subsidence of the road are likely. The downstream slope will not be stable and shallow slides can be expected. 3. PMF: A large scour-hole will develop below the outlet and may damage the culvert outlet section. High pore pressure will result in an unstable downstream slope, shallow slides, seepage and piping that may breach the road. Excessive scour of the downstream slope of the embankment and along the ditch on the upstream side of the road is expected. The road will not be passable until considerable repair work has been done.

The checklist that was used during the evaluation is shown below in Figure 9-13.

138 9. Analysis of roads in Orkdai

CHECKLIST Scenario: Q100, Q1000, PMF Date: 8.8.97 Signature:

OBJECT DESCRIPTION Object ID: 9-7 1 Road#: 714 1 Location: - I Riven Storbekkcn Description:

GENERAL CHECKLIST UNDESIRED EVENT Probability of Extent of Effect on main occurrence 1 damage1 function 1 Scenario: SI S2 S3 SI S2 S3 SI S2 S3 HIGH WATER LEVEL Road flooded 1 1 3 - - - _ - - Strong current across road 1 1 3 ------

Subsidence of pavement due to saturation of 1 2 2 - 2 2 - 2 2 fill Reduced load capacity due to saturation of fill 1 2 2 - 2 2 - 2 2 Timber debris deposited onroad 1 1 2 - - 1 - - 2 Fine sediments deposited on road 1 1 3 - - 1 - - 2 Rocks / boulders deposited on road 1 1 1 ------HIGH WATER PRESSURE Downstream road fill slope not stable 1 2 3 - 2 2 - 2 2 Road embankment fails along deep slip circle 1 i 2 - - 2 - - - Internal erosion of road fill 1 2 3 - 2 2 - 2 2 Piping through road embankment 1 1 2 _ 2 - - - SCOURING

Overtopping of road 1 1 3 - - 1 - - 3 Scouring of downstream embankment slope 1 1 3 - 3 ~ by overtopping flow. Scour by parallel flow 1 1 1 - - - - . - Scouring by wind-generated waves 1 1 1 - - - _ _ - OTHER EVENTS Excess discharge will follow road 1 1 3 ------Overtopping along uncontrolled flow path 1 1 3 - 2 - - 3 Scour along uncontrolled flow path 1 1 3 - 3 - - 3 Uplift in light fills 1 1 1 - - - - - Flood tourism 1 1 1 ------Flood mitigation measures 1 1 1 ------1 = none / low, 2 = medium, 3 = large

CULVERT CHECKLIST UNDESIRED EVENT Probability of Extent of Effect on main occurrence 1 damage1 function 1 Scenario: SI S2 S3 SI S2 S3 SI S2 S3 SCOUR DAMAGE Scour damage at inlet 1 1 2 - - 2 - - 1 Scour hole at outlet 1 2 3 - 2 2 - 1 1 Scour damage to culvert exit section 1 2 3 - 2 2 - 1 1 Scour progresses upstream 1 1 2 - - 2 - 1 2 OTHER EVENTS Culvert clogged by floating debris 2 3 3 Culvert clogged bv sediments 1 2 2 Culvert collapses due to external pressure 1 1 1 1 = none / low, 2 = medium, 3 = large Figure 9-13: The checklist used for evaluating Object 9-7.

I

139

r -tv 9. Analysis of roads in Orkdal

9.7.2 Hazard analysis of Route 714 close to Skjenaldelv-Object 9-4

Figure 9-14: Object 9-4: Route 714 parallel to Skjenaldelv

Route 714 from Gj0lme to Gagnasvatnet follows the relatively steep river Skjenaldelv. At first, several locations of the road were regarded as vulnerable to scouring because of their proximity to the river. However, inspection revealed that most of the objects were too far away to be in danger so it was only necessary to perform a detailed investigation of two objects. The analysis of Object 9-4 is discussed in this section.

At Object 9-4 Route 714 passes very close to the outside of a bend in Skjenaldelv (Figure 9-14). For a couple of hundred metres, the toe of the road embankment is in the river. The lower part of the road fill is protected by riprap. PQFLOM was used to assess the floods from the 140 km2 catchment resulting in Qioo =110 m3/s, Qiooo = 150 m3/s and PMF = 280 m3/s. The large lakes in the catchment result in relatively low flood peaks but long flood durations. The river cross-section and slope were estimated from maps (1:5000) and field inspection. Manning’s n was estimated by using Eq. (4-8) and from pictures and tables (French 1987), which gave n = 0.032 and n = 0.04 respectively. The average value of n = 0.036 was used. Flow parameters were estimated assuming uniform flow in a trapezoidal channel and solved in SCOUR. The results are shown in Figure 9-15.

Stable rocks sizes both at the bed and on the side slope were computed at increments over the range of relevant discharges (Figure 9-16). Shear stresses that are considerably higher than average must be expected to occur along the outside portion of the bend. Based on the ratio of bend radius to river width a correction

140 9. Analysis of roads in Orkdal factor of 1.55 was applied to the average shear stress. The destabilising effect of the side slope was taken into consideration by using the diagram suggested by Lysne (Lysne 1987). The results are summarised in Table 9-4.

Stage-discharge chart for Skjenaldelv at Object 9-4

450 - 6.0

350 -5.0 (m/s)

300-1 U - - 4.0

200 -; - - 3.0 velocity,

150 -: Flow 100 -: --1.0 50 -:

Water depth, Y (m)

-a- Discharge, Q -e- Velocity, U

Figure 9-15: Object 9-4: Stage-discharge chart for Skjenaldelv

Incipient motion of rocks at riverbed, Skjenaldelv at Object 9-4

0.25 --

0.20 - -

0.15 -

200 Discharge, Q (m3/s)

Figure 9-16: Object 9-4: Riprap stability

141 9. Analysis of roads in Orkdal

Table 9-4: Evaluation of riprap stability at Object 9-4

QlOO Qiooo PMF Comments Q (m3/s) 110 150 280 Y(m) 1.8 2.15 3.1 U (m/s) 3.9 4.3 5.2 x (N/m2) 171 198 263 Limiting rock size using Eq. (5-1) d50 (m) = 0.14 0.17 0.26 Riverbed d50 (m) = 0.21 0.26 0.40 On bank (Lysne 1987) dso (m) = 0.33 0.40 0.62 On outer bank of river bend Limiting rock size using Eq. (5-7) dso (m) = 0.10 0.12 0.18 Riverbed dso (m) = 0.15 0.18 0.28 On bank side slope (Lysne 1987) dso (m) = 0.23 0.30 0.43 On outer bank of river bend

Object 9-4: Expected performance during flood The ground behind the road fill is almost at road level, and the area will gradually be filled through a drainpipe so that damage due to high pressure gradients and overtopping is not likely to occur. The area inside the road is so flat that flow velocities will be low. The serious hazard is from scouring of the road fill by Skjenaldelv: 1. Qioo-The water level will just exceed the riprap-protected zone. The riprap is generally stable but local scour damage is expected. The scoured riprap will remain stable at the bed and only min or damage to the road fill is expected. 2. Qiooo- The road will not be inundated but the water level clearly exceeds the riprap at several places. Severe scouring may occur above the riprap and locally where the riprap is weak. However, the main portion of the riprap is still stable, and much of the scoured material will be stable at the riverbed. Scour at the toe of the embankment may result in local sliding of the embankment fill. It is probable that only the inner part of the road will be passable, and it is possible that the road will be completely blocked. 3. PMF: It is probable that the lowest part of the road will be slightly inundated. The unprotected fill will be severely scoured and much of the riprap protection will also be unstable. Severe scour damage may be expected along several hundred metres of the road fill. The road will probably be blocked and extensive repair work will be necessary.

142 9. Analysis of roads in Orkdai

9.7.3 Hazard analysis of the bridge where Route 710 crosses Skjenaldelv - Object 8-2

The bridge where Route 710 crosses Skjenaldelv was selected to demonstrate the bridge analysis approach. The bridge is a two-span concrete bridge, of which each span is 15.3 m wide. The abutments and the pier are founded on wooden pillars, and the top of the pier foundation extends from the riverbed and is not riprap protected. The road rises as it approaches the bridge from the south and the minimum elevation of the road to the south is 1 - 2 m below the bridge deck. The bed slope of the river is approximately 0.01 upstream of the bridge and 0.006 downstream. The riverbed is covered with cobbles and stones ranging from 0.05 m- 0.3 m and djo was roughly estimated to be 0.15 - 0.25 m. The soils in the area are mainly fluvial deposits.

The bridges dimensions were measured and the bridge photographed. Cross- sections of the river were surveyed using a level. The bridge foundations were inspected to assess riprap dimensions and scour damage. A drawing of the bridge was obtained from the State Highway Department in S0r-Tr0ndelag.

143

A- i 9. Analysis of roads in Orkdal

Flood profile computations The peak flood values for Qioo, Qiooo and PMF were estimated to be 110 m3/s, 150 m3/s and 280 m3/s respectively. The flood profile for each discharge was computed using HEC-RAS. The roughness coefficient of the river channel was estimated using Eq. (4-8) and photographic examples (French 1987). The computations provided flood profiles, velocities, shear stresses and overtopping flow at the bridge and the nearby river reach. Figure 9-18 shows the PMF profile.

Bridge over Skjenaldelv PMF profile Legend

Energy line

Water surface

Critical depth

Ground

Main Channel Distance (m)

Figure 9-18; Object 8-2: Water surface profile during the PMF

Evaluation of contraction scouring Contraction scouring was evaluated using Shields ’ criterion for incipient movement, and Strickler’s formula, (4-5), to estimate the roughness. Contraction scouring was evaluated for two sediment sizes: d50 = 0.1 m and d50 = 0.2 m. The results are shown in Table 9-5. During PMF minor contraction scouring may take place but the duration of the scouring will be short, and armouring of the bed will limit the scour depth. Consequently, contraction scouring was not regarded as a problem for any of the flood scenarios.

144 9. Analysis of roads in Orkdal

Table 9-5: Evaluation of contraction scour Hood scenario Required cross-sectional area Area from profile based on Shields' criterion computations (m2) (m2) d5o = 0.10 m dso = 0.20 m QlOO 31 25 38 Qiooo 40 33 46 PMF 68 56 76

Evaluation of riprap stability at the pier The pier and abutments are not protected by riprap, but the materials of the river bed is coarse. The pier nose is rounded, but the pier foundation, with its top almost 0.8 m above the bed, is square-nosed. There is already evidence of scouring at the upstream face of the pier foundation. The pier module in SCOUR was used to assess the stability and the bed material was not considered to be stable for any flood scenario.

Evaluating scour depths at the pier The 0.5 m-wide pier was not considered to be significant in evaluating the scour depth because the 2.8 m-wide pile cap is already exposed to the flow. Further scouring will expose the 27 piles and for this case "HEC-18" (Richardson and Davis 1995) recommends using a width equal to the projected width of the piers, ignoring the clear space between them. Accordingly an effective width of 1.4 m was assumed. For this case the scour depth estimates showed the scour-hole to be rather shallow which indicates that the pile cap would be close to the bed and have a strong influence on scour development. For this reason an estimate of scour dept was also made using the cap width of 2.8 m. The pier module of SCOUR was used to estimate the scour depths for a range of bed sediment diameters. Results for the PMF situation are shown in Figure 9-19. Scour depths from 2 m to 4 m can be expected.

145 9. Analysis of roads in Orkdal

Scour depth at bridge pier, Object 8-2

U = 3 m/s Y = 4.3 m

Eq. (5-15), B = 1.4 m -o-Eq. (5-15), B = 2.8 m Eq. (5-16), B = 1.4 m Eq. (5-16), B = 2.8 m

Figure 9-19: Object 8-2: Scour depths at pier

Evaluating abutment riprap stability The stability of the river bed at the vertical wall abutment was evaluated using SCOUR. The results, shown in Table 9-6, indicate that abutment scour must be expected for all scenarios.

Table 9-6: Object 8-2: Stable riprap diameter at abutment

d50 (m) Method QlOO Qiooo PMF Comment Eqs. (5-18) and (5-19) 0.39 0.48 0.58 Design Eqs. (5-18) and (5-19) 0.22 0.27 0.32 50 % failure modified

Evaluating abutment scour depth Eq. (5-20) was used to estimate the scour depth. Two approaches were taken to calculate the scour depth for Qiooo and PMF. The largest depths were obtained by considering the short length of abutment projecting into the main flow. The lowest depth was computed using the total obstruction length and the corresponding low water depth and velocities on the floodplain. The results for the left abutment are shown in Table 9-7. Scour damage is not expected at the right abutment, as it is located at the inner bend, and is protected by a guide wall that directs the flow away from the abutment.

146 9. Analysis of roads in Orkdal

Table 9-7: Scour depths at left abutment Ys(m) Method Qioo Qiooo PMF Comment Eq. (5-20) 3.6 3-5 3-5 Design Eq. (5-20) modified 2.6 2-4 3-5 Best fit line

Object 8-2: Expected performance during floods. The flood hazards were evaluated on the basis of the bridge checklist. The main considerations are discussed below: 1. Qioo. In this situation there is free surface flow below the bridge, and the head loss is small. There is no danger of inundation, overtopping or damage caused by pressure gradients. However, the pier will be scoured well below the pile cap, exposing the piles to the flow. This is not believed to damage the bridge, but the load bearing capacity of the exposed piles has not been evaluated. Scour at the left abutment is also expected to expose the piers but it is not believed that this will damage the bridge. However, to prevent damage to the weakened foundations the bridge would have to be closed to heavy vehicles. 2. Qiooo- Profile calculations indicate that the bridge will be overtopped to a depth of 0.2 m to pass an excess flow of 7 m3/s. However, the road embankment is 1 — 2 m lower than the bridge to the south and this area will allow much of the excess flow to bypass the bridge. The overtopping flow is expected to cause considerable damage to the road fill, either at the bridge or further south. Compared to Qioo the degree of pier and abutment scour will increase, but is not expected to damage the bridge. 3. PMF. For this scenario an excess flow of more than 100 m3/s will overtop or bypass the bridge and extensive damage to the road is expected on both sides. Debris build up and pressure flow may increase scouring, but scouring and breaching of the approach fills may considerably increase the conveyance and lower the headwater level. The bridge would not be passable until extensive repairs had been carried out.

147 9. Analysis of roads in Orkdal

9.7.4 Assessing road flooding along the River Orkla Long road sections along the Orkla will be inundated during major floods. This example illustrates how road flooding was evaluated by using the Idiisi GIS to combine VEBAS and results from the flood profile calculations. The analysis was carried out in several steps: 1. A raster layer with the road centreline elevations was developed from VEBAS. 2. A raster layer of the flood profile elevations was developed for each flood scenario. 3. The layers were overlaid to find where the road would be below the water surface. 4. The inundation depths were calculated by subtracting the road elevation layer from the flood surface layer. 5. Flood damage and effects were assessed.

VEBAS is a database with xyz co-ordinates for the road system. The data are in SOSI format, a special format for vector data used by Statens kartverk. SCSI could not be read by Idrisi and a program that extracted data for the study area and converted SOSI data to Idrisi vector format was developed in Visual Basic. The centre-line elevation data were thereafter converted to a raster layer using the Pointras module in Idrisi.

The locations of cross-sections used in the flood profile computations were shown on 1:5000 maps provided by NVE (Bsevre 1996). The cross-section locations were manually transferred to maps on a scale of 1:20000, digitised and georegistered. Each cross-section line was given a value corresponding to the computed water- surface elevation. The cross-section vector data were converted to raster and a continuous surface was created by interpolating between the profiles using the Intercon module in Idrisi.

The road elevation and water-surface raster layer were overlaid in order to identify locations where the main road was below the water surface and to find the water depth. An example from 0yan during the PMF is shown in Figure 9-20. The black line shows the main road and the pixels show the places where the road will be flooded. The shade of the pixels indicates the flow depth. Using the GIS the flood depth at each pixel was available by cursor inquiry. Figure 9-21 shows all locations on the main road that will be flooded during the PMF. Damage at the flooded locations was assessed by using flow velocities from the profile calculations. Roads crossing the floodplain perpendicular to the flow were particularly exposed to damage.

148 9. Analysis of roads in Orkdal

Flooded

Road

Figure 9-20: Road inundation depths at 0yan

149 9. Analysis of roads in Orkdal

Meiers North 10000.00

Figure 9-21: Stretches of the main road that will be flooded during the PMF

150 9. Analysis of roads in Orkdal

9.8 Some experiencesfrom the flood vulnerability assessment This section describes some of the experiences from the vulnerability analysis.

9.8.1 Capacity calculations at culverts and bridges Unusual designs and damaged culverts made several of the capacity calculations difficult. By using CULVCAP it was easy to explore how the various parameters affected the results so that a educated guess could be made.

However, the main uncertainty concerning the capacities of culverts and bridges is caused by the build-up of woody debris or sediments. In many cases a large build ­ up of debris that would drastically reduce capacity seemed very probable. However, no method was found to estimate the amount of debris or the effect on capacity. For this reason, all capacity calculations were made without taking the effects of debris into account. It is therefore believed that damage at bridges, and even more so at culverts, have been underestimated by this study.

9.8.2 Trees falling over the road This is expected to be a problem during extreme rainfall, but no method of analysing this problem was identified. It was not considered further during the study.

9.8.3 Debris flows It is well known that heavy rainfall may initiate a number of debris flows, which will damage roads and disrupt traffic. In Chapter 6 the Idrisi GIS was used to identify stretches of road at risk from debris flows. However, as the approach used was rather experimental the results have not been incorporated into this study.

9.8.4 Sediment deposits and alluvial fans Sediments deposited where steep sediment-carrying rivers reach flatter slopes poses a special problem. The deposits may cause damages, block culverts and bridges and even force the river to take a new course. Maps and aerial photos were studied to identify alluvial fans and other areas where sediment build-up is likely but none were found in the proximity of the main roads. However, it is felt that this problem has not been sufficiently investigated and that such hazards may exist unnoticed within the study area.

151 9. Analysis of roads in Orkdal

9.9 Description of flood vulnerability in the study area Eighty-eight objects were identified as vulnerable to flooding and were included in the study. The objects that were still considered to be vulnerable to flooding after an initial screening were included for further study. Each object was classified according to expected damage and its effects on the main function. Three classes were used; class 1 indicates no or small effects, class 2 indicates medium effects and class 3 indicates severe effects.

Three flood scenarios were considered; Qioo, Qiooo and the PMF. The expected damage and its effects on the objects for each of the scenarios considered are presented in Figure 9-22, Figure 9-23 and Figure 9-24. A list of the results for each object is given in Appendix B.

9.9.1 The expected effects of Q10o Flooding along the river Orkla causes the most serious problems. The main road, Route 65, will be inundated at several locations, and so will the parallel roads. It will not be possible to travel through the valley from south to north on the primary roads. The capacity of several culverts will be exceeded and water will overtop the road embankment, resulting in moderate traffic disruption.

9.9.2 The expected effects of Q10oo The number of inundations along the Orkla increases. At a number of culverts, excess discharge will overtop the road, resulting in scour damage and traffic disruption. At some locations this will result in the road embankment being breached.

9.9.3 The expected effects of PMF The roads along Orkla are almost totally inundated. Water will overflow the road at almost every culvert resulting in numerous damage situations or breaches. There will be serious damage at several bridges. Road traffic is possible only on some short road sections.

152 9. Analysis of roads in Orkdal

Meters 10000.00

Figure 9-22: Estimated effects of Quo 9. Analysis of roads in Orkdal

Figure 9-23: Estimated effects of Qiooo

154 9. Analysis of roads in Orkdal

Figure 9-24: Estimated effects ofPMF

155 10. A method for assessing infrastructure flood vulnerability

10 A method for assessing infrastructureflood vulnerability In this chapter, a method for assessing the impact of large floods on a physical infrastructure or utility is suggested. It is based on the experience gained during the analysis of the road infrastructure, described in Chapter 8 and 9.

The method suggested is not specific to a particular area or kind of infrastructure. It is believed that the method will be useful for analysing a variety of physical infrastructures in different areas.

The method involves two stages. The first stage is general and is concerned with assessing which parts of the infrastructure are vulnerable to flooding. The second stage is concerned with analysing the flood vulnerability of a specific area.

This chapter consists of three sections. First, special problems related to the analysis of flood vulnerability are discussed. Secondly, the general vulnerability analysis is described. The procedure for analysing a specific infrastructure is then described. Figure 10-1 shows how the suggested method is organised.

10.1 Some important aspects of flood vulnerability analysis Knowing that risk analysis methods have successfully been applied to a variety of situations, ranging from the simple to the very complex, the question arises: does the analysis of serious floods call for a new approach? To answer this question it is necessary to consider the characteristics of flood impacts and of the physical infrastructure itself.

Several features of severe floods make impacts difficult to assess: 1. Large floods will adversely effect a majority of important items of infrastructure. 2. A large number of destructive mechanisms are involved, e.g. inundation, scouring, pollution transport, intense rainfall, debris flows etc. 3. The flood impacts are spread over a large area. 4. The flood impacts occur at the same time.

156 10. A method for assessing infrastructure flood vulnerability

General vulnerability analysis

Establish a working group

Describe the system

Identify involved parties

Analysis of Preliminary Synthetic historical hazard approach data analysis

Results: Undesired events Vulnerable objects Consequences Checklists Evaluation methods

Specific vulnerability analysis

Tool-kit: Study area 1 Flood size Flood profile Capacity calculations Scour damage

Figure 10-1: Organisation of the flood vulnerability analysis method

In addition, the physical infrastructure possesses features that are important when considering what methods are suitable for perfo rmin g the analysis: 1. The infrastructure is often spread over large areas. 2. A failure in one part of the infrastructure will often affect large areas. 3. Vulnerable objects in the infrastructure are often expensive and will take a long time to repair or replace, e.g. bridges, treatment plants, transformer stations, etc. 4. There is a large degree of interdependence between different utilities.

Assessing the flood impacts on an object in the physical infrastructure involves a number of special tasks. Hood severity, water levels, flow velocities, scour

157 10. A method for assessing infrastructure flood vulnerability potential, sediment transport, slope stability, etc. all have to be evaluated. This often requires special skills and methods not readily at hand.

Considering the impacts of serious floods, the characteristics of the physical infrastructure and the need for specialised knowledge it seems unlikely that traditional risk analysis methods can be directly employed in a flood vulnerability analysis.

10.1.1 Identifying vulnerable objects Some types of utility or physical infrastructure may be spread over large areas and it is an extremely complex process to assess every bit of the system. However, some parts of the system are much more vulnerable to flooding than other parts, and an analysis must focus on identifying and evaluating such objects. The effective and reliable identification of vulnerable objects within a study area is of great importance for any flood vulnerability study.

In order to identify vulnerable objects within an area it is necessary to know what characterises them. Vulnerability may be related to characteristic features of the object itself. For example, an object that severely constricts the flow of water is probably vulnerable during serious floods. In other cases however, the object itself has no characteristics that indicates that it is vulnerable. The vulnerability may depend solemnly on the features of the surroundings of the object. For example, a road that runs along the foot of a steep hill will very probably be exposed to debris flows during extreme rainfall, but analysing the road alone can not reveal this.

In most cases the vulnerability can be attributed both to the surroundings and the object itself. In many cases, the features of the surroundings determine the exposure to hazard while the ability to withstand and recover from the impacts is determined by the object itself. The characteristics must consider both the object, its surroundings and how they interact with each other.

The characteristics should meet the following criteria: 1. They must be broad enough to identify all objects that will be damaged or malfunction during floods. 2. They must be so specific that only a few non-vulnerable objects are identified as vulnerable. 3. They must be adapted to the information and methods that will be used to identify objects. For example, using the shape of the gradation curve to characterise a road embankment as vulnerable to piping is not useful for identifying such objects within an area unless gradation curves are readily available.

158 10. A method for assessinginfrastructure flood vulnerability

10.2 General flood vulnerability analysis This stage aims to find the characteristics of flood vulnerable objects and the typical types of damage that can be expected. The general analysis involves one kind of physical infrastructure, e.g. roads, water supply etc., but no specific study area. It is performed only once for each kind of infrastructure or utility. The findings obtained at this stage are the basis for analysing the same kind of infrastructure in all areas.

Three alternative methods are suggested: 1) a Preliminary Hazard Analysis, 2) using data from previous floods, and 3) a synthetic approach. The most important results of this stage are: • A list of undesired events. • A list of vulnerable objects and their characteristics. • Check lists for evaluating flood impacts. • A list of parties involved and their need for information. • A procedure for performing a specific vulnerability analysis.

10.2.1 Organisation of work The analysis should be done by a group with wide-ranging knowledge of the system under analysis, flood hydrology and hydraulics.

10.2.2 Description of the system The analysis begins with a description of the system for analysis, hi the course of its work with the description, the group will acquire a joint understanding of how the system works.

General requirements for the description are given in “Requirements for risk analyses ” (NSF 1991). The description should include the limitations and operating conditions of the system. All technical, organisational and human circumstances that are relevant to the analysis must be included.

Attention should be paid to describing the operation of the system under adverse or emergency conditions. It should include the description of emergency and contingency plans, and plans for co-operating with agencies that will be involved in the emergency (police, fire brigade).

The system’s dependence on other systems or organisations must be described. This should include power supply, water supply, telephone services, road transport, access routes etc.

10.2.3 Identify parties involved and assess their need for information The objective of the analysis is to provide background data for emergency planning. The analysis must be designed to provide relevant information only, at a level of

159 10. A method for assessing infrastructure flood vulnerability

detail suitable for the users. In order to assess the need for information the parties involved must be identified, and their need for information assessed.

The owners and operators of the infrastructure will require the most detailed data. Their needs will often be covered through participation in the work group that is analysing the flood impacts.

The analysis must also provide relevant data to organisations that depend on the infrastructure in question, and particular attention should be given to the needs of the emergency services and the municipality administration. As this analysis is not site-specific, the need for information is assessed on a general basis.

10.2.4 Methods for assessing vulnerable objects and typical damage Three approaches are suggested for identifying vulnerable objects and associated effects: 1. Using Preliminary Hazard Analysis. 2. By analysinghistorical data from large floods. 3. The synthetic approach.

Using Preliminary Hazard Analysis Preliminary Hazard Analysis (PHA) is a risk analysis method that may be used without expert knowledge of risk analysis. PHA focuses mainly on detecting hazards. It is often used at the early design stage. It is believed that this method is suitable for the general flood vulnerability analysis.

PHA is done by subdividing the system into its main components and identifying possible hazards. The possible causes and consequences are described of each hazard. The results of the analysis are documented on a special PHA form. PHA is briefly described in Chapter 3. Further inf ormation can be found in (Rausand 1991) or (Aven 1994).

Review of historical experience Historical data from large floods are an important source of information and are extremely important when attempting to understand future flood events. Large floods involve a number of mechanisms of destruction, both direct and indirect, that are extremely difficult to foresee. A systematic review of historical data will reveal which objects are liable to flood damage, the kind of damage to expect, the causes of damage and experience gained from repair and mitigation.

In practice, detailed and systematic data on the impacts of large floods are scarce. The situation itself, with high water levels, blocked roads and severe weather makes surveillance difficult. Much of the data must be gathered after the flood. However,

160 10. A method for assessing infrastructure flood vulnerability after the flood there will be a rush to clean up and repair. Resources are not spent on documenting the whys and wherefores of flood damage.

The kind of analysis to be undertaken on the historical data will depend on the type of infrastructure under investigation and on the scope of the study. The objective of the analysis is to find typical types of damage or performance failures (undesired events) and their associated causes and consequences. It is also important to identify which objects within the infrastructure are liable to damage, and typical characteristics of these objects.

A systematic review of historical data should be carried out in order to identify possible hazards. The method used will depend on the system to be analysed. A three-stage approach was used during the case study: 1) collect flood damage data, 2) review the data and identify relevant information, 3) analyse the data and document the results. The approach is outlined below.

Collection of flood damage information The consequences of floods are often poorly documented. Many of the authorities involved are surprisingly uninterested in evaluating their own performance during floods and in documenting flood damage to the structures for which they are responsible. However, some sources of information do exist. 1. Specialised performance reports. After serious floods some of the agencies or utilities affected may prepare reports that describe the damage. Written by professionals, these reports are often very useful. 2. General performance reports. General reports are sometimes drawn up as a result of investigations of how the authorities have handled their responsibilities before and during serious floods. They may provide background information on flood mitigation strategies, land use and the organisation of emergency response activities. 3. Newspaper and TV reports. Television and newspapers have many reports about floods. They do not normally provide any technical data, but may be a starting point for further investigation. 4. Interviews. Interviews with technical staff operating utilities that have recently been affected by floods may be very useful.

Review the collected material and identify relevant information This involves reading books, scientific papers, technical reports, and newspaper articles, and studying films, videos and photographs of flood and flood damage, and reviewing other sources of relevant information. The objective is to identify all information relevant to the infrastructure being analysed. Failures, near failure, damages, malfunctions and organisational problems are all of interest.

161 10. A method for assessing infrastructure flood vulnerability

Analyse the data and document the results. When a relevant incident has been identified the findings must be recorded and analysed. The event itself and its causes and consequences should be described in sufficient detail. The description should focus on the physical aspects of the event. Unusual or unexpected circumstances relating to the causes or the consequences should also be included.

A special form for recording the findings is suggested. For each object in the system, the findings are recorded on a separate form. The form as shown in Table 8-2 has been designed to closely reassemble the PHA form.

Cases in which the incident or its causes and consequences are not adequately described should be analysed further to fill in gaps in the information.

The synthetic approach The synthetic approach utilises lists with examples of undesired events, typical damage and typical situations in which it occurs. The lists may be used to assist the working group during the Preliminary Hazard Analysis. It should be helpful to them as it provides a database of undesired events and also data on the circumstances under which they occur. It may also be used as a checklist during a general evaluation of the infrastructure concerned. After subdividing the infrastructure each object is evaluated by going through the list, considering both the various undesired events, features of the object and the features of the surroundings that may contribute to its vulnerability.

The list was developed on the basis of experience gained when collecting and analysing flood impact data. It is shown in Table 10-1.

162 10. A method for assessing infrastructure flood vulnerability

Table 10-1: Checklist for identifying undesired events Undesired event Typical damage Object characteristics Characteristics of the surroundings Structure and Damage to electrical equipment Objects below ground level, in cellar or On floodplains equipment becomes Damage to mechanical equipment in first floor. Close to lakes wet Damage to archives and books Leakage through openings in the In backwater areas Structural damage structure • Upstream culverts through Back-flow through drainage systems high fills Structures that use pumps for drainage • Upstream bridges that may become clogged with debris In flat areas or hollows In areas drained through pipes Loss of load-bearing Deformation Foundations on fine-grained soils As above capacity Foundation subsidence Road fills Foundations on or near steep slopes Insufficient clearance Traffic can not pass under object Bridges Across rivers between water surface Minimum safety distance violated Electric power lines On floodplains and object 10. A method for assessing infrastructure flood vulnerability

Undesired event Typical damage Object characteristics Characteristics of the surroundings High external water Leakage Structures with water pressure on the On floodplains pressure Walls and floors crack outside and none on the inside Close to lakes Dam failures Structures with high water pressure on In backwater areas Levee failures one side. In flat areas or hollows In areas drained through pipes Uplift Structures dislocated by uplift Light or waterproof structures: As above Structures tom from foundations • Tanks and drift away • Pipes • Pumping stations • Light fills • Wooden structures Large horizontal force Structure is dislocated, slides, Structures with little ability to withstand Situations with high flow on structure - drag moves or is bent or cracks. horizontal forces or with a large area velocities: forces exposed to the flow. • Steep rivers • Buildings • Narrow constrictions • Bridges Vibrations Damage due to vibrations Light structures exposed to flow As above Wave action along rivers and lakes

164 10. A method for assessing infrastructure flood vulnerability

Undesired event Typical damage Object characteristics Characteristics of the surroundings Direct wave action Scouring of fills and foundations Fills without riprap protection or where Waves caused by high-velocity Structural damage the water level may exceed the water flow and critical flow level. Steep rivers Foundations Downstream of spillways Light structures unable to withstand Wind-generated waves along wave action. lakes Scouring Scour at bridge foundations Structures exposed to flowing water and High flow velocities: Scour around buildings without riprap protection or shallow • Steep rivers Scouring downstream of foundations • Narrow constrictions overtopped levees Scouring of river banks and road Structures that contract flow Founded on fine-grained soils fills Scouring at structures exposed to Embankments parallel to steep rivers Downstream overtopped or the flow: breached levees • Water intakes in rivers • Pipelines crossing the river Scouring downstream of spillways, sills and drops.

165 10. A method for assessing infrastructure flood vulnerability

Undesired event Typical damage Object characteristics Characteristics of the surroundings Large sediment Sediment deposits on fields, roads All structures in flooded areas Areas with large sediment yield transport and inside flooded structures. Structures that create a backwater and do Rivers with large carrying Sediment deposits fill intake not allow free passage of flow and capacity. ponds sediments: Sediment deposits clog water • Bridges Large deposits of coarse-grained intakes • Culverts sediments may build up where Pressure forces from large • Dams steep rivers reach flatter areas. sediment deposits may damage • Intake structures exposed structures High sediment content makes the All equipment used for treating raw water unsuitable for purpose: water. • Drinking water supply • Cooling water • Industrial processes

Sediments may damage pumps and turbines

166 10. A method for assessing infrastructure flood vulnerability

Undesired event Typical damage Object characteristics Characteristics of the surroundings Large concentration of Pollutants make the water All processes that treat or use water: Sources that may release toxic pollutants unsuited for the purpose. • Treatment plants substances if flooded: Common pollutants are: • Water supply • Waste dumps • Metals • Cooling water • Agricultural areas • Pesticides • Industrial processes • Mine tailings • Nitrate • Flooded industrial plants • Phosphor Facilities where people are in direct • Storage tanks for pesticides, • Humus contact with water. petrol, oil etc. • Bacteria • Flooded wastewater • Petroleum products treatment plants and untreated wastewater. High pore pressure due Landslides Structures founded on slopes that may Steep slopes to heavy rain Debris flows become unstable if saturated: Poor vegetation cover Slope failures • Fine-grained fills Fine-grained fills Fallen trees over road • Poor drainage Landforms that concentrate the • Steep slopes debris flow paths

Structures that may be in the path of debris flows.

167 10. A method for assessing infrastructure flood vulnerability

Undesired event Typical damage Object characteristics Characteristics of the surroundings Floating debris Floating debris blocks flow Structures that constrict the water flow Floating debris may originate Reduced flow capacity and high • Bridges from: water pressure results in increased • Culverts • steep forested catchments scouring and pressure forces. • Water intakes • flooded timber mills Flooding in backwater area. • Screens Intakes clogged • Intakes Damage caused by impact from large floating debris. Structures that will act as screens when flooded • Fences • Rails

168 10. A method for assessing infrastructure flood vulnerability

10.2.5 Compiling the results for the analysis of a specific infrastructure The Preliminary Hazard Analysis and analysis of historical data will provide large quantities of data concerning the flood performance of the infrastructure. The results must be compiled and presented so they will be useful when analysing a specific area. It is recommended to organise the results as follows: 1. List of parties involved. The parties that may use the results of the infrastructure should be listed along with their need for information. When analysing a specific area this list is used to ensure that all relevant parties will be involved in the analysis. 2. List of undesired events and associated consequences. A list of undesired events is needed when assessing how vulnerable objects will perform during floods. The undesired events should be listed along with the objects involved. References to detailed descriptions of the events should be included whenever possible. The consequences on the objects main function should be included. 3. List of vulnerable objects. Objects and the characteristics that identify them as flood vulnerable are listed. The level of detail should be adjusted to the information available for identifying the objects. 4. Checklists. It is suggested to use checklists for evaluating vulnerable objects. Checklists are developed based on the findings from the PHA and the historical data. The use of checklists will help the analyser to investigate all relevant hazards, and avoid overlooking important problems. The checklists should be designed to guide the analyser through the analysis in a systematic way. When it is filled in the checklist provides documentation of how the object was analysed and the results.

10.3 Flood vulnerability analysisof a specific infrastructure The general vulnerability analysis was concerned with providing background data for the vulnerability study. The specific analysis deals with the flood impacts on one kind of physical infrastructure in a defined area.

The analysis involves several activities, of which identifying vulnerable objects and assessing their performance during severe floods are the most important. The recommended procedure is outlined in the following: 1. Describe the objectives of the analysis. 2. Identify parties involved and their need for information. The scope and detail of the analysis must be adjusted to the requirements of those who will use the results of the analysis. Parties that have interests in the analysis must be identified and contacted. Their requirements must be specified. Several of the parties involved may want to participate in the working group. The list of

169 10. A method for assessing infrastructure flood vulnerability

parties involved developed in the course of the general analysis will provide a starting point for identifying whom to include. 3. Establish a working group. The choice of members will depend on the objective of the analysis, the system for analysis and the parties involved. The working group should include engineers with extensive knowledge of flood hydrology and hydraulics, and engineers with detailed knowledge of the system being analysed. A representative of NVE should be included to account for levees, river training works, scour protection measures etc. If the rivers in the area are regulated for hydropower or other purposes, a representative of the regulators should be included. An official of the community and a representative of the police should also participate. 4. Select flood scenarios. It is not feasible to evaluate all flood situations. Two or three scenarios should be selected to represent the range of possible situations. 5. Describe the subject for analysis and assign priorities. In many cases, the same level of detail is not required for all parts of the system. Priorities should be assigned to its various parts. The interests of the parties involved will be the basis for assigning priorities. 6. Identify flood vulnerable objects. The list of vulnerable objects and object characteristics obtained from the general analysis are used as a basis. Several methods can be used to identify the vulnerable objects: inspection of maps and aerial photographs, field inspections, various GIS techniques, interviews, construction drawings, etc. The appropriate method will depend on the characteristics of the objects to be identified. 7. Evaluate the flood vulnerable objects. The vulnerable objects must be evaluated to assess how they will perform during the flood scenarios. The evaluation is based on two main components: 1) the checklists developed during the general analysis and 2) the hydrological and hydraulic tool kit. 8. Describe flood vulnerability. Rood vulnerability is described for each object. For each flood scenario, the description should include the undesired event, the expected damage and its direct consequences for the object. 9. Present the results. The flood impacts on each object are documented in the checklist and in an evaluation form. The overall results are presented as tables and maps.

The procedure has been designed to conform to “Requirements for risk analysis ” (NSF 1991) which also provides extra information on several of the points listed.

170 10. A method for assessing infrastructure flood vulnerability

The suggested approach does not attempt to carry the assessment beyond the immediate and direct effects on the investigated objects. Assessing consequences must be the task for engineers familiar with the system under investigation. Once the direct flood impacts have been assessed, existing methods can be used to find the consequences.

If the system being analysed depends on other utilities, they must also be investigated. This also goes for other functions on which the system depends, e.g. transport, staff, supplies, etc. For this situation, an iterative holistic approach was outlined in Chapter 2. However, it is beyond the scope of this work to investigate the propagation of flood impacts within systems or from one system to another

171 11. Summary, discussion and recommendations

11 Summary, discussion and recommendations

11.1 Summary of the study The objective of this study was to develop a procedure for analysing the impacts of severe flooding on physical infrastructure.

In the first part of the study methods of flood assessment, hydraulic computations and scour assessment were reviewed in order to provide a basis for analysing vulnerability to flooding. Three computer programs were developed: • CULVCAP assesses culvert capacities in situations with low tail-water levels. • SCOUR assesses general scour and local scour by means of a variety of methods. • FASTFLOOD facilitates effective flood-size computations.

In the second part of the study, the flood vulnerability of the road infrastructure was investigated. First, flood vulnerability was analysed on a general basis by the use of historical data and Preliminary Hazard Analysis. The results of the general analysis were used to assess how the main roads in Orkdal will be affected during Qioo, Qiooo and PMF.

Finally, a method for analysing the flood vulnerability of physical infrastructure has been proposed. The method involves two stages: 1. A general stage that will provide: • Lists of undesired events. • Lists of objects that are vulnerable to flooding. • Checklists for evaluating the impact of undesired events. • Evaluation forms for assessing the vulnerability of the object considered. • A list of parties who ought to be involved in the analysis. 2. A specific stage which is concerned with analysing one particular kind of physical infrastructure in a study area. There are two main activities in this stage: • Identification of objects that are potentially vulnerable to flooding. • Evaluation of expected flood impacts on the objects regarded as vulnerable to flooding.

11.2 Discussion This part of the discussion concerns the method for assessing flood vulnerability. Three important aspects are considered: • Does the method provide the answers the involved parties request? • Can the method be verified? • Is the method feasible?

172 11. Summary, discussion and recommendations

Does the method provide the information the involved parties request? The general analysis provides comprehensive data on how the infrastructure considered will be affected by serious floods. These are important background data that can be used for several different purposes. It can be used when designing new components of the infrastructure. For example, a section of the road embankment at the approaches to a bridge can be designed to breach during a severe flood, reducing the probability of a costly bridge failure. Data from the general study can also be used when deciding where to locate vital structures, taking flood-zones, accessibility, debris flow hazards, etc., into account.

The suggested method provides a flexible method of assessing the impacts of flooding in an area. The scope and detail of the analysis can be tailored to suit the needs of the parties affected. The checklists can be used both to screen of objects in order to obtain an overview of the flood hazards and for an in-depth analysis of each object.

Can the suggested method be verified? Two questions concerning verification need to be answered: 1. Will the correct objects be identified as vulnerable to floods and thus be included in a detailed study? 2. How do the estimated impacts of flooding compare with true flood impacts?

The problem of verification is important but unsolved. Theoretically, the method can be tested by performing a flood vulnerability analysis in an area and then checking the predictions against observations once a major flood has occurred. The problems with this approach are obvious.

Is the suggested method feasible? This question has two important aspects: • Is flood vulnerability assessment feasible at all? • Will the suggested method provide information at a lower cost than other methods?

Data from a flood vulnerability analysis may be used for contingency planning, for land-use issues and when designing new infrastructure so that flood losses can be kept to a minimum. The feasibility of performing a flood vulnerability assessment can be calculated by comparing the cost of vulnerability assessment and contingency planning with the net present value of the potential reduction in flood losses. No general answer exists so the feasibility must be assessed in each individual case. In practice however, it is extremely difficult to assess the reduction

173 11. Summary, discussion and recommendations in total flood losses, particularly because improved contingency planning at utilities mainly reduces the indirect costs of floods.

If a flood vulnerability analysis is requested then the most efficient method should be used, i.e. the method that produces the data required at the lowest cost. The efficiency of the method suggested should be compared with other methods of flood vulnerability assessment. This has not been done since no comparable methods are known to the author.

11.2.1 Is there a demand for flood vulnerability analysis? The most important question in this discussion is probably: Will local authorities and managers of vital infrastructure be interested in assessing vulnerability to major floods at all?

This question is not easily answered. Considering current Norwegian practice in flood-plain management and flood awareness, the answer is probably no. Local authorities seem strangely uninterested in considering the danger of flooding when deciding on land use issues. Furthermore, during the planning of most kinds of utilities the question of flood vulnerability receives hardly any attention at all. In general, most of local and state authorities and utility managers seem quite uninterested in problems related to large floods.

On the other hand, it may seem that the large flood in 1995 has increased flood awareness in Norway to some extent. However, most experience from large floods indicates that the lessons learned are soon forgotten. Often it does not take many years from when an area has been devastated by a major flood until there is a demand for development in the same flood-prone area, without regard to the flood threat.

11.3 Recommendationsfor further work In general, both government and private utility owners are little interested in assessing flood vulnerability and preparing contingency plans for serious floods. In view of this situation, it may not be feasible to continue to develop methods for flood vulnerability analysis. However, there is a trend in society in the direction of increasing demand for risk assessment and contingency planning, and attitudes to flood preparedness may also be changing. For this situation two areas of further research are suggested below.

In a modem society the infrastructure is highly complex and if one part of the system fails it will have widespread effects. The impacts of major floods on an infrastructure utility are not merely the result of the direct effects of floodwaters, but also because the flood disrupts utilities on which the infrastructure in question

174 11. Summary, discussion and recommendations depends. Thus, an infrastructure should not be analysed alone, but as a part of a whole. Apart from a brief discussion in Chapter 2 this study has not explored the propagation of effects on flooding throughout a system of interdependent infrastructures. It is believed however, that this is important, and methods for including such effects in a flood vulnerability analysis should be developed.

Contingency planning for vital utilities and infr astructure is probably the most important application of the results of flood vulnerability analyses. This study investigated methods of assessing the immediate physical effects on objects subjected to flooding. However, as this is still a new field it is felt that there is still a considerable gap between the information on flood damages that the vulnerability analysis provides and a fully developed flood contingency plan. Methods for preparing flood contingency plans on the basis of flood vulnerability analyses and other data are needed.

175 References

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182 Appendix A: List of symbols

Appendix A: List of symbols

List of Symbols If a particular symbol is used for one concept in one chapter and for a different concept in another chapter, the chapters are noted in the list. A list of appropriate dimensions is included. A 1 in the dimensions column indicates a dimensionless quantity, a (-) means that the idea of dimension is irrelevant to the particular concept.

Roman Concept Dimensions Symbols A Cross-sectional area of culvert barrel (Chapter 4) L2 A Catchment area (Chapter 7) L2 B Pier width L C Expansion or contraction coefficient (Chapter 4) 1 C Coefficient (Chapter 5) 1 C Runoff ratio (Chapter 7) 1 cf Safety factor 1 CR Contraction ratio 1 Cs Stability factor (Chapter 5) 1 Cs Safety factor (Chapter 9) 1 Ct Blanket thickness coefficient 1 Cy Vertical velocity distribution coefficient 1 D Diameter of culvert barrel L d Characteristic diameter of sediment particle L dao Particle diameter for which 30 % by weight of L sediment is finer dso Particle diameter for which 50 % by weight of L sediment is finer dsoa Particle diameter for which 50 % by weight of L sediment in armour layer is finer dg4 Particle diameter for which 84 % by weight of L sediment is finer dmax Maximum particle diameter L d„ Size of a cube which has the same weight as d# L ER Expansion ratio 1 F Froude number 1 Fd Densimetric Froude number 1 f() Function - g Acceleration of gravity LT2 he Energy head loss L i Rainfall intensity LT1 Appendix A: List of symbols

Roman Concept Dimensions Symbols Js Relative ground structure number 1 K Tractive-force ratio (Chapter 5) 1 1 K Friction factor (Chapter 6) K* Skew angle/alignment factor 1 K, Factor for abutment shape (Chapter 5) 1 1 k 2 Factor for abutment angle (Chapter 5) 1 Ki, K2 Constants used for culvert capacity computations (Chapter 4) 1 k 3 Bed condition factor 1 K4 Factor for armouring of bed Kb Block/particle size number 1 Ka Sediment size factor 1 Kd Relative bed material size factor 1 Kd Discontinuity/inter-particle shear strength 1 number Kg Cannel geometry factor 1 Kb Erodibility index 1 Ki Flow intensity factor 1 Ks Side slope factor 1 Ksh Pier shape and orientation factor 1 Ku Clear-water condition factor 1 Ky Characteristic depth L Ky Relative depth factor/depth factor 1 k Constant used in Strickler's formula Tl-i/2 L Length L L Length of abutment projected normal to flow L U Length of contraction reach L U Length of expansion reach L M5(24) 24-hour rainfall with a five-year recurrence LT"1 interval Ms Mass strength number 1

MT(24) 24-hour rainfall with a T-year recurrence LT"1 interval Nc Stability number 1 n Manning's friction factor TL"1/3

P Stream power (energy dissipation per unit MLT'3 width)

PMF Probable Maximum Flood L3T-1

PN Average annual rainfall LT"1 Q Discharge L3T"‘ Appendix A: List of symbols

Roman Concept Dimensions Symbols Qz Hood with 2-year recurrence interval L3T1 Qio Hood with 10-year recurrence interval l3t4 Qso Hood with 50-year recurrence interval l3t-1 QlOO Hood with 100-year recurrence interval L3t-i QlOOO Hood with 1000-year recurrence interval l3t-1 Qavg Mean annual flood l3t-1 Q t Hood with T-year recurrence interval lV Qm Median annual peak discharge l3t1 q Discharge per unit width lV R Hydraulic radius L R* Particle Reynolds number 1 rc Radius of centreline of river bend L So Slope of culvert barrel (Chapter 4) 1 So Slope of channel bottom (Chapter 5, Chapter 9) 1 ScR Critical pressure gradient 1 sf Friction slope 1 Ss Specific gravity of sediment 1 Tc Concentration time T t Thickness of riprap layer L U How velocity LT1 u* Shear velocity LT1 U*ac Critical armour shear velocity LT1 U*c Critical shear velocity LT1 u* Critical U/Us for the initiation of pier scouring 1 Ua How velocity at abutment toe LT1 U= How velocity at critical depth LT1 Ucf Depth-averaged velocity on contracted LT1 floodplain Us Critical velocity for sediment entrainment in LT1 uniform flow Uy Local depth-averaged velocity LT1 Ub Point velocity 10 % of the depth above the bed LT1 V How velocity (VR method in Chapter 5) LT1 W Width of river L Y Depth of water L Ya How depth at abutment toe L Yc Critical depth L Ysc Scour depth below culvert measured from water L surface to bottom of scour-hole Yd Average flow depth on contracted floodplain L Appendix A: List of symbols

Roman Concept Dimensions Symbols Yf Average flow depth on floodplain L Ys Scour depth measured from bed to bottom of L scour-hole Z Elevation above specified datum L Zs Scour depth measured from culvert invert L Zjw Tailwater elevation measured from the pipe L invert

Greek Symbols Concept Dimensions a Velocity weighting coefficient (Chapter 4) 1 P Constants used for culvert capacity 1 computations (Chapter 4) P Exponent (Chapter 5) 1 P Slope angle (Chapter 6, Chapter 9) 1 Y Specific weight of water ML"2!"2 Ys Specific weight of sediment ML'2T'2 V Kinematic viscosity l2t1 P Density of water ML"3 Og Geometric standard deviation of the grain size 1 distribution X Shear stress ML"1T"2 T* c Critical dimensionless shear stress, Shields' 1 parameter Tc Critical shear stress ML"1T"2

Appendix B: List of objects

All objects that were identified as potentially vulnerable to floods during the object identification phase are listed below. Start and end is the start and endpoint of the road stretch. ID refers to the object identification number. Type defines the kind of object: C = culvert, B = bridge, LR = road with little elevation above a river or lake (low road), CL = road close to river or lake (close road), O = other object. Location means the name of the area where the object is located. UTM refers to the approximate co-ordinates (east north) of the object in the UTM system with EUREF 89 datum. Damage means the physical damage to the object that is expected to occur during the flood scenario. The effect is concerned with traffic flow at the object. The expected performance of the object is ranked from 1 to 3.1 indicate that only minor damage/effect is expected to occur, 3 indicate severe damage or the road being closed to traffic. A (-) means that this situation or object was not investigated.

Stretch: 1 Start: B0rsa End: Bardshaug ID Type Location UTM Qioo QlOOO PMF (m) Damage Effect Damage Effect Damage Effect 1-1 C Vikan 552150 7024550 1 1 2 3 3 3 1-2 C Lundteigen 551450 7024600 2 1-3 2 1-3 3 3 1-3 B Viggja 549650 7024450 1 1 2 1 3 3 1-4 C Sildvaertangen 548800 7024700 1 1 2 2 2 2 1-5 C Trasavika, south 547550 7023800 1 1 2 2 2 2 1-6 C Storsanden 546850 7023425 ? (0sthusbekken) 1-7 C Litlsanden 545300 7022500 2 2 3 3 3 3 1-8 C Litlsanden 545000 7022250 ------1-9 C Litlsanden 544800 7022100 1 1 2 2 2 2 1-10 C Thamshavn 544200 7021550 1 1 2 2 3 3 1-11 C Thamshavn 543800 7021250 1 1 1 1 2 2 Appendix B: List of objects

Stretch: 1 Start: Bprsa End: Bardshaug ID Type Location UTM Qioo Qiooo PMF (m) Damage Effect Damage Effect Damage Effect

1-12 C Orkanger 543150 7020400 - -

1-13 C jElilykkja 552950 7023750 - -

1-14 c Stykkan 550750 7024550 - -

Stretch: 2 Start: Bardshaug End: Fannrem ID Type Location UTM Qioo Qiooo PMF (m) Damage Effect Damage Effect Damage Effect 2-1 C Hospital 542700 7018250 2 3 3 3 3 3 2-2 CR Hospital 542700 7018000 ------2-3 C Sorenskriver- 542100 7016900 1 1 2 1 3 3 garden 2-4 CR Megarden 540592 7016470 1 3 1 3 1 3 2-5 LR Stretch 2 541700 7016904 1 3 1 3 1 3

Stretch: 3 Start: Fannrem End: Vormstad ID Type Location UTM Qioo Qiooo PMF (m) Damage Effect Damage Effect Damage Effect 3-1 B Fannrem 540205 7015444 2 1 2 1 3 3 3-2 CL Solhus 540037 7015248 1 1 1 1 2 3 3-3 LR Solhus 539867 7015107 1 1 1 1 1 3 3-4 LR Bakkmoen 538642 7014157 1 1 1 1 1 3 3-5 C Bakk (Siken) 538579 7013757 1 1 2 3 3 3 3-6 CL Kvale 538729 7012819 1 1 1 1 1 1 Appendix B: List of objects

Stretch: 3 Start: Fannrem End: Vormstad ID Type Location UTM Qioo QlOOO PMF (m) Damage Effect Damage Effect Damage Effect 3-7 LR Skoleby 538229 7012181 1 3 1 3 1 3

3-8 C Byakjela 538242 7011806 ------3-9 C Fjellmoen 538592 7010418 2 3 2 3 2 3 3-10 LR Lj0kel 538742 7009293 1 1 1 1 1 1 3-11 B Vormstad 538642 7008218 1 1 2 1 2 3

3-12 C Solhus 539551 7014785 ------

3-13 C Torshus 539426 7014691 ------

3-14 C Torshus 539314 7014616 ------

3-15 C Skoleby 538256 7012371 ------

Stretch: 4 Start: Vormstad End: Svorkmo (Tronvoll) ID Type Location UTM Qioo QlOOO PMF (m) Damage Effect Damage Effect Damage Effect 4-1 LR Vormstad, south 538642 7007743 1 1 1 3 1 3 4-2 LR Orkland 538690 7007020 1 1 1 1 1 3 4-3 CR Asppl 537764 7005887 1 1 1 1 1 1 4-4 LR Tronvoll 537481 7005503 1 1 1 1 1 1 Appendix B: List of objects

Stretch: 5 Start: Svorkmo (Tronvoll) End: Svorkmo Bridge (east) ID Type Location UTM QlOO QlOOO PMF (m) Damage Effect Damage Effect Damage Effect 5-1 LR Svorkmo (0ra) 537389 7004995 1 1 1 3 2 3 5-2 B Svorkmo Bridge 537406 7004478 1 1 2 3 3 3

Stretch: 6 Start: Bardshaug End: 0yan ID Type Location UTM QlOO QlOOO PMF (m) Damage Effect Damage Effect Damage Effect 6-1 LR Bardshaug 542589 7018917 - - - - - 6-2 B Bardshaug 542176 7018954 1 1 1 1 2 3 Bridge 6-3 LR 0yan 541764 7018998 3 3 3 3 3 3

Stretch: 7 Start: 0yan End: Gj0lme ID Type Location UTM Qioo QlOOO PMF (m) Damage Effect Damage Effect Damage Effect 7-1 C Feijemanns- 541490 7019055 - - - - stugu 7-2 C Motorbane 541207 7019497 7-3 c Gj0lme 540898 7019930 - - - - 7-4 c Gj0lme 540857 7020047 - - - - 7-5 LR 0yan 541015 7019714 2 3 2 3 2 3 Appendix B: List of objects

Stretch: 8 Start: Gj0lme End: Rabygda ID Type Location UTM Qioo Qiooo PMF (m) Damage Effect Damage Effect Damage Effect 8-1 LR Gj0lme 540623 7020606 1 1 2 3 2 3 8-2 B Skjenald Bridge 540582 7020922 2 2 2 3 3 3

Stretch: 9 Start: Gj0lme End: Gagnasvatnet ID Type Location UTM QlOO QlOOO PMF (m) Damage Effect Damage Effect Damage Effect 9-1 CR Dynald 540298 7020372 1 1 1 1 1 1 9-2 CR Dyndal 539731 7020139 1 1 2 1 2 1

9-3 B Kjellarenget 538915 7019947 ------9-4 CR Flaskog 538665 7019997 1 1 2 2 3 3 9-5 C Ann0l 537831 7019680 1 1 2 1 2 3 9-6 CR Ann0l, west 537539 7019530 1 1 1 1 1 1 9-7 C Fossgjerdet 536781 7018930 1 1 2 2 3 3 (Storbekken) 9-8 CR Stor0ra 539215 7019997 1 1 1 1 1 1

9-9 C Flaskog 538440 7019872 ------

9-10 C F0niks 537423 7019422 ------

9-11 C Kjellarenget 538534 7019950 - - - - - Appendix B: List of objects

Stretch: 10 Start: Fannrem End: Solbu ID Type Location UTM QlOO Q 1000 PMF (m) Damage Effect Damage Effect Damage Effect 10-1 LR Asheim 540605 7015019 1 1 1 1 1 3 10-2 CR Engan, SW 540055 7014119 ------10-3 C Prestmoen, NW 540067 7013869 2 1 2 2 3 3 10-4 CR Kleiva 539205 7011131 ------10-5 C Kleiva, SW 539730 7010806 ------10-6 C Solbu, N 539723 7010287 ------10-7 LR Blasmo - 540250 7014388 1 1 1 1 1 3 Prestmoen 10-8 LR Kleiva - Solbu 539774 7010636 1 1 1 3 1 3

Stretch: 11 Start: Solbu End: Svorkmo ID Typel Location UTM QlOO QlOOO PMF (m) Damage Effect Damage Effect Damage Effect

11-1 C Stubban 540525 7008761 ------

11-2 C Solem 540875 7008585 ------11-3 c Monset 541100 7008235 2 1 2 1 3 3

11-4 c Aspjeld 541100 7007560 ------

11-5 c Aspjeld 540675 7007360 ------

11-6 c Gumdal 539574 7005309 ------

11-7 B Svorka Bridge 537898 7004233 ------11-8 CL Svorkmo 537673 7004459 1 1 1 1 1 1 Appendix B: List of objects

Stretch: 12 Start: Solbu End: Vormstad ID Typel Location UTM QlOO QlOOO PMF (m) Damage Effect Damage Effect Damage Effect 12-1 C Haugen, S 539780 7009018 2 2 2 3 2 3 12-2 B Orkla Bridge 538904 7008193 2 3 3 3 3 3 12-3 LR 0yan -Haugen 539542 7008468 3 3 3 3 3 3

Stretch: 13 Start: 0yan End: Fannrem Bridge, west side ID Typel Location UTM QlOO QlOOO PMF (m) Damage Effect Damage Effect Damage Effect 13-1 LR 0yan 541530 7018633 2 3 2 3 2 3

13-2 C Ustsastra 541230 7018183 ------13-3 LR Trettpya - 540880 7017845 1 3 1 3 1 3 Vollen

13-4 C Vollmoen 540767 7017595 ------13-5 C Vollen 540580 7017032 2 2 3 3 3 3 13-6 C Batset, N 540092 7016032 ------13-7 CR Batset - 540126 7015616 1 1 1 1 2 3 Fannrem Bridge Appendix C: Maps

Appendix C: Maps

Meters Grid North 10000.00

Overview of the study area. The rectangles show the locations of the three following maps. Appendix C: Maps

Detail map of northern area. Appendix C: Maps

10-7 > &

Meters 5000.00

Detail map of central area Appendix C: Maps

Detail map of southern area,