Flood Severity and Magnitude in the Keisie R

DRIVERS OF FLOOD SEVERITY AND MAGNITUDE IN THE KEISIEKEISIE RIVER CACATHCMENT:THCMENT:

A CASE STUDY FROM THE NOVEMBER 2008 FLOOD EVENT IN MONTAGU, WESTERN

CAPE, SOUTH AFRICA

An Honours Thesis Submitted to the University of Cape Town in Fulfillment of the

Requirements of the Degree of

Bachelor of Science (Hons) in Environmental and Geographical Science with specialization

in Disaster Risk Science

In the

FACULTY of SCIENCE

PPPHINDILEPHINDILE TIYISELANI ZANELE SABELA

* * * * *

January 2010

Supervisor:

Dr. A Holloway

PLAGIARISM DECLARATION

I know that plagiarism is wrong. Plagiarism is to use another’s work and pretend that it is one’s own.

I have used the Harvard system for citation and referencing. Each contribution to and quotation in this thesis from the works of other people has been attributed, and has been cited and referenced.

This thesis is my own work.

I have not allowed, and will not allow anyone to copy with intention of passing it off as his or her own work.

Signature……………………

ABSTRACT

Floods and flood-related hazards have increased globally in past decades and are evident in both developed and less developed countries. However, people in the less developed countries are the most vulnerable due their close proximity to hazard prone areas along with their dependency on primary products which are more sensitive to weather related hazards.

This study explores the drivers of flood frequency and severity in the Keisie River Catchment by applying a disaster risk lens. It specifically examine the river flood hazard component of a potential flood risk through a case study of the November 2008 cut-off low that affected the town of Montagu in the Cape Winelands district in the Western Cape province.

The research method combined a spatial analysis of land-use/land-cover change over a 40 year period over catchment conditions for 1963, 1987 and 2007, and compared aerial photographs of the Keisie River catchment. The methods also involved modelling the design flood for 2008 by using the HdroCAD software.

Results indicated modest changes in catchment conditions at macro catchment scale and little difference in design flood outcomes. It also underlined the importance of other flood risk factors such as; decrease in vegetation cover, increase in open space and the effect of wild fires as important drivers of riverine flood loss.

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ACKNOWLEDGEMENTS

I would like to thank:

My supervisor Dr Ailsa Holloway of Disaster Mitigation for Sustainable Livelihoods

Programme (DiMP) for guidance, advice, motivation and support throughout;

Arthur Chapman, from, One World Sustainable Developments who helped with the generation of hydrologic data and with structure of my methods and research findings;

The Chief Directorate of Surveys and Mapping (CDSM) for supplying the Aerial photographs and maps of the study area;

The CSIR for providing the data used for the layers created by the GIS

Thomas Slingsby of UCT’s Geomatics Department for the guidance with spatial data

The Cape Higher Educational Consertion(CHEC) for proving financial support for field work.

Richard Donaldson for making it possible to undertake the field research required in this study.

My family for their support, interest and encouragement throughout.

TTTABLETABLE OF CONTENTS

PLAGIARISM DECLARATION ...... II

ABSTRACT ...... III

ACKNOWLEDGEMENTS ...... IV

LIST OF FIGURES ...... VIII

FIGURES : ...... VIII

TABLES : ...... VIII

GLOSSARY ...... IX

ABBREVIATIONS ...... XIII

1. INTRODUCTION ...... 14

1.1 BACKGROUND ...... 14

1.2 STUDY AIMS AND OBJECTIVES ...... 17

1.3 LIMITATIONS ...... 17 1.3 1 uneven quality of aerial photographs ...... 17 1.3.2 Uneven accuracy of rainfall data ...... 18 1.3.3 Complexity in land categorization ...... 18

1.4 ETHICAL CONSIDERATION ...... 18

1.6 ORGANISATION OF THE THESIS ...... 19

2 LITERATURE REVIEW AND CONCEPTUAL FRAMEWORK ...... 20

2.1 GLOBAL FLOOD CONTEXT ...... 20 2.1.1 Flood trends and losses ...... 20 2.1.2 Types of floods and associated characteristics ...... 20 2.1.3 Flooding and severe weather ...... 21

2.2 FLOODING IN SOUTH AFRICA AND THE WESTERN CAPE ...... 22 2.2.1 Historical overview of flood ...... 22 2.2.2 Recent flood events in the Western Cape ...... 22

2.3 RISK FACTORS INCREASING SEVERITY OF FLASH FLOOD EVENTS ...... 23 2.3.1 Overview ...... 23 2.3.2 Increase in impervious surface ...... 23

2.3.3 Land degradation ...... 24 2.3.4 Wild fires ...... 24

2.4 METHODS USED IN STORM HAZARD DETERMINATION ...... 25 2.4.1 Overview ...... 25 2.4.2 Storm Hydrographs ...... 25 2.4.3 HydroCAD flood estimation software ...... 26 2.4.4 Other design flood estimation procedures ...... 27

2.5 CONCEPTUAL FRAMEWORKS FOR THIS STUDY ...... 28

3. RESEARCH CONTEXT: KEISIE RIVER CATCHMENT, MONTAGU ...... 31

3.1 OVERVIEW OF MONTAGU ...... 31 3.1.1 History ...... 31 3.1.2 Socio-demographic and economic profile ...... 31

3.2 PHYSICAL CHARACTERISTICS OF THE CATCHMENT ...... 32

3.2.1 Study area ...... 32

3.2.2 Climate ...... 33

3.2.3 Geology and soils ...... 34 3.2.4 Vegetation in the Keisie River Catchment ...... 35 3.2.5 Hydrology ...... 35

3.3 EXPOSURE TO EXTREME WEATHER ...... 36 3.3.1 Flood history in Montagu ...... 36 3.3.2 November 2008 cut-off low ...... 39

4. METHODS ...... 42

4.1 INTRODUCTION ...... 42

4.2 SECONDARY DATA SOURCES ...... 43 4.2.1 Data Sources ...... 43 4.2.2 Rainfall data collection ...... 43 4. 3 Primary data collection ...... 44 4.3.1 Study area ...... 44 4.3.2 Spatial characteristics of the Keisie River Catchment ...... 45 4.3.3. Data consolidation ...... 46

4.4 DATA ANALYSIS ...... 46 4.4.1 Overview ...... 46 4.4.2 Determining the return period of the November 2008 storm ...... 47

4.4.3 General storm Hydrographs ...... 48

5. RESEARCH FINDINGS AND ANALYSIS ...... 49

5. 1 OVERVIEW OF THE CHAPTER ...... 49

5.2 CHANGES IN LAND -USE /LAND -COVER ...... 49 5.2. Changes in Land-cover over time and observed characteristics in the ...... 51 Keisie River Catchment ...... 51

5.3 CHARACTERISATION OF THE NOVEMBER 2008 STORM ...... 51 5.4 Storm hydrograph comparison of the Keisie River catchment conditions ...... 52

6: DISCUSSION AND CONCLUSION ...... 54

6.1 INTRODUCTION ...... 54

6.2 THE ANTHROPOGENIC DEVELOPMENTS IN THE FLOOD EXPOSED AREAS ...... 54

6.3 CONSISTENCY OF RESEARCH FINDINGS WITH EXISTING LITERATURE ...... 55

6.4 CONCLUSION AND DIRECTION FOR FUTURE RESEARCH ...... 55

REFERENCES ...... 57

APPENDIX ...... 60

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LIST OF FIGURES

Figures:

FIGURE 1: MAP INDICATING THE LOCATION OF THE CAPE WINELANDS DISTRICT MUNCIPALITY FROM THE

SOUTH AFRICAN MAP ...... 15

FIGURE 2: FLOODED SITES IN MONTAGU (PICTURE A : MONTAGU BRIDGE IN THE SOUTH ENTRANCE ,

PICTURE B : PARKING OF AVALON SPRINGS HOTEL PICTURE 6: DIE ERF FARMS , PICTURE D : BADEN

FARM ) ...... 16

FIGURE 3: ADOPTED CONCEPTUAL FRAMEWORK ...... 30

FIGURE 4: THE KEISIE RIVER CATCHMENT AREA ...... 32

FIGURE 5: MONTAGU ’S MONTHLY AVERAGE PRECIPITATION CURVE OF THE RAINFALL IN MARCH (1883-

1995) IS 19.43 MM /MONTH . APRIL INDICATES THE START OF THE WET WINTER SEASON , WITH A

LARGE INCREASE IN AVERAGE MONTHLY PRECIPITATION ...... 33

FIGURE 7: STORM HYDROGRAPH FOR THE 1963 CATCHMENT CONDITION FOR 1:40 YEAR RETURN PERIOD ...... 52

FIGURE 8: STORM HYDROGRAPH FOR THE 1987 CATCHMENT CONDITION FOR 1:40 YEAR ...... 52

FIGURE 9: STORM HYDROGRAPH FOR THE 2007 CATCHMENT CONDITION FOR 1:40 YEAR ...... 53

Tables:

TABLE 1: MONTAGU FLOOD HISTORY : FLOOD HISTORY : 1867-2008 37

TABLE 2: PRELIMINARY DAMAGE ASSESSMENT IN MONTAGU 38

TABLE 3: DAILY RAINFALL 10-15 NOVEMBER 2008 41

TABLE 4: METHOD ANALYSIS 42

TABLE 5: LAND -COVER CHANGE BETWEEN 1963 AND 2007 50

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GLOSSARY

Catchment. A catchment is all the land that drains into a particular river system (King 1988).

The topography of these drainage regions are such that all rainfall that falls in a specific catchment will eventually drain into the main river or stream flowing through the catchment

(DEAT, 2004)

Cut-off low. A cut-off low is a cold-cored depression, which starts as a trough in the upper westerlies and deepens into a closed circulation extending downward to the surface and which become displaced equator wards out of the basic westerly current (Singleton and

Reason, 2005).

Curve number (CN). The runoff curve number is an empirical parameter used in hydrology for predicting direct runoff or infiltration from rainfall excess. This parameter is expressed by a numerical value varying between 0 – 100 and determined according to the soil type and ground cover. A high CN (such as 98 for pavement) indicates minimum retention, while a low CN (such as 30 for certain wooded areas) indicates a large withholding capability. (Davies and Day, 1998).

Discharge. Also known as the outflow, it is defined as the peak flow of the unit hydrograph, measured in m3/s . Each hydrograph consists of flow values (ordinates) that occur at a given time increment throughout a certain time span (Alexander,1993).

Drainage region classification for South Africa. South Africa has been classified into 22 drainage regions. The South African drainage classification system assigns 4 levels of classification. At the primary level, each drainage region is assigned a letter of the alphabet, for example ‘H’ which represents the Breede River Basin. The secondary catchment is

assigned the letter of the primary catchment as well as the numerical number depending on how many secondary catchments exist within the primary catchment. For example, the

Kogmans River catchment is assigned the code ‘H3’. Using the same logic, the secondary catchments are subdivided into tertiary and quaternary catchment by assigning a ‘0’ and additional alphabetic symbol (A, B etc.) respectively, for example H3E04 is for Keisie drainage region in Montagu.

Flood frequency (return period). Flood frequency is the calculation of the statistical probability that a flood of a certain magnitude for a given river will occur in a certain period of time. These calculations are expressed as return periods, which are described in terms of the particular flood being a 2, 5,10, 20,50 100 and 200 year flood (DiMP,2003). A 2-year flood relates to a

50% probability of the estimated flood occurring in a given year (DiMP, 2003). A 10-year flood relates to a 10% probability, a 20-year flood relates to a 5% probability and so on (DiMP,

2003).

Hydrograph. A hydrograph is a graph that illustrates the stage flow and velocity of water with respect to time (ASCE, 1996 in Rogatshnig, 2005).

Hydrograph volume. This is the total flow volume attained by a storm generated runoff, represented in a storm hydrograph. (The volume includes flow only within the given time span, any flow before or after the span is excluded).

Hydrology. Hydrology is concerned with the basic physical processes governing the occurrence, distribution and movement of water on or below the Earth’s surface (Ward and

Robinson, 1990, in Rogatschnig, 2005).

Hydrological cycle. The hydrological cycle is the movement of water and its transformation between gaseous, liquid and solid forms (Mayhew, 1997 in Rogatschnig, 2005). The major

components of the cycle are condensation by which precipitation is formed, the movement and storage of water overland and underground, evaporation and the horizontal movement of water (Mayhew, 1997 in Rogatschnig, 2005).

Inflow depth. This is an average runoff depth generated from the upstream watershed. The inflow depth is based on the total inflow volume, including any base flow divided by the area of the catchment.

Land-cover. The term land-cover relates to the type of feature present on the surface of the earth e.g. corn fields, lakes, forests, and highways (Benjamin, 2008 ).

Land degradation. Land degradation is the reduction or loss in arid, semi-arid and dry sub- humid areas, of the biological or economic productivity and complexity and rain-fed cropland, irrigated cropland, pasture, forest and woodlands resulting from land use or from the combination of processes, including processes arising from human activities and habitation patterns such as: Soil erosion caused by wind or water; Deterioration of the physical, chemical and biological or economic properties of soil and Long-term loss of natural vegetation Viljoen and Booysen, 2006)

Land-use. The term land-use relates specifically to the human activity or economic function associated with a specific tract of land.

Peak volume. This is a peak volume of the unit hydrograph (Alexander, 2000).

Riparian zone. The riparian zone has been loosely defined as the area adjacent to a river or stream (Snaddon, 1999 in Rogatschnig, 2005). In the South African context, zones 20m wide on either side of the streams and rivers are defined as riparian.

Time to concentration. Time of concentration is the travel time from the hydraulically furthermost point in a watershed to the outlet. This is also defined as the time from the end of rainfall excess to the recession curve inflection point as illustrated on the accompanying hydrograph (Viljoen and Reimold,1999)

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Abbreviations

CD: SM Chief Directorate: Survey and Mapping South Africa

CSIR Council for Scientific and Industrial research

DEAT Department of Environmental Affairs and Tourism

DiMP Disaster Mitigation for sustainable Livelihoods Programme

DWAF Department of Water Affairs and Forestry

GIS Geographical Information Systems

HEE-HMS Hydrologic Engineering Center's Hydraulic Modeling System

NDMS National Disaster Management System

RMF Regional Maximum Flood

SAWS South African Weather service

SCS Soil Conservation Service

SES Search Engine Strategies

USACE United State Corps of Engineers

WCNC Western Cape Nature Conservation

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1. INTRODUCINTRODUCTIONTION

This study researches the drivers flood severity and magnitude in the Keisies River catchment: A case study of the November 2008 event in Montagu, Western Cape.

1.1.1.11. 111 Background

While riverine flooding plays an important protective role in flood-dependent ecosystem, it is increasingly associated with damaging losses. Recent assessment of disaster impacts globally underline this, by showing that more lives are lost or affected due to severe flooding than any other natural hazard (Alexander, 2000).

Upward trend in flood-losses has also been noted in South Africa. It is estimated that at least 50 000 people and possibly more than 100 000 people are living in the along rivers and streams below levels that has been reached by the previous floods (Alexander, 2000). Moreover most of these people live the unplanned settlements within the jurisdiction of local or regional authorities.

In the Western Cape for instance, significant flood-related losses have recently been recorded for

2003, 2004, 2005, 2006, 2007 and 2008 (DiMP, 2010 forth-coming). One area in the in the Western cape that is repeatedly affected by the flood events is the town of Montagu in the Cape Winelands

District Municipality.

Figure 111:1: map indicating the location of the Cape WinelandsWinelands District MMuuuuncipalityncipality from the South African Map

Source: http://www.capegateway.gov.za/image/2003/boland_e.gif

Although Montagu has been affected by numerous severe weather events, significant flood effects

were sustained following the cut-off low weather system of the 11 th to the 13 th of November 2008. This event resulted in heavy rainfall of 356-500mm in the mountainous area of the Langerberg, 130mm in

Montagu and 145mm in other areas close to Montagu (DiMp, 2008). Flood damage from the Keisie

River that is associated with heavy rainfall was reflected in direct municipal losses of R 8 166 250.00

(DiMP, 2008), although this excludes losses recorded by the provincial and national departments.

Figure 2a: Montagu Bridge in the South entrance Figure 2b: parking of Avalon springs

Figure 2c:Die Erf Farms. 13 th Nov 2008

Figure 222:2: flofloodedoded sites in Montagu in figure 2a, 2b and 2c

Source: Pictures acquired from the Disaster Cape

1.1.1.21. 222 Study aims and objectives

Recognising that climate change scenarios from the Western Cape foresee the possibility of increased rainfall in mountainous areas (Midgley, 2005) along with their associated impacts on development, this study therefore aims to examining the contribution of land-use and land-cover change and potential rivrine flood risk within the Keisie River catchment.

It specifically intends to:

• Examine the recent flood history of the Keisie River (1918 – 2008)

• Establish the nature and degree of land-use and land-cover change within the Keisie River

catchment that may have influenced the flood hydrograph in the 2008 flood event;

• Apply a simple hydrological model to the Keisie River catchment to examine the effect of

change in land-use and land-cover on the total discharge of the catchment.

• Identify other contributing risk factors for endangering floods within the Keisie River

Catchment

1.1.1.31. 3 L3 LimitationsL imitations

1.3 1 uneven quality of aerial photographs

Despite effort to address constraints in the data and analysis, several limitations must be acknowledged in the study. First, some of the aerial photographs did not exactly cover the study area, adjustments were necessary. This may have compromised the subsequent quality and accuracy of land-use / land-cover classifications and the digitalisation of these photographs. Moreover, as the

1963 and the 1987 photographs were printed in grey, and not orthophoto-rectified, this limited the

accuracy in identifying changes in land-use/land-cover. In addition to inadequate data, it was difficult to identify degraded areas and to differentiate between alien invasive species and indigenous vegetation. This resulted in all natural vegetation being classified onto one category.

1.3.2 Uneven accuracy of rainfall data

Although the Keisie River Catchment covers a relatively large area; the two rainfall stations used in

study this are located several kilometres away from the river. In addition the rainfall data collected by

the farmers from “Drie Berge” farm and other neighbouring farms were consolidated as monthly

averages and not daily rainfall totals, this data were applicable to this study

1.3.3 Complexity in land categorization

A section of the Keisie River catchment has been used as the proxy for the total catchment area.

This may limit the study relevance of the findings to other areas in the catchment.

1.1.1.41. 444 Ethical consideration

Conducting research in disaster affected areas requires careful and respectful planning. This was

enabled through consultation with the local disaster manager. In addition, the results of this study will

be shared amongst all the concerned stakeholders for transparency. To ensure confidentiality all

those interviewed are referred to by their titles. In addition, the study acknowledges the difficulties

associated with in catchments like the Keisie. To address this, an expert hydrologist was consulted for

advice throughout the flood modelling phases of this study to ensure that accurate information was

produced.

1.61.61.6 Organisation of the thesis

Chapter one introduces the background as well as the broad aims and objectives of this study.

Chapter two describes the literature relevant to the topic. Chapter three outlines the research context of the study area and concludes by describing the area exposure to extreme weather and associated flood experiences. Chapter four outlines the methods utilised to collect consolidate and analyse data, while chapter five present analysis of the results. Chapter six discusses the findings and concludes the study.

2 LITERATURE REVIEW AND CONCEPTUAL FRAMEWORK

2.12.12.1 Global flood context

2.1.1 Flood trends and losses

Floods can be defined as the height or stage of water above some given point, such as the banks of

the channel (Alexander, 1993); they commonly result from any place on land whereby the water is

introduced faster than it drains away.

Floods are a natural phenomenon, but damage and losses are commonly exacerbated consequence

of human action (.De Sherbinin, 2002), of the entire natural phenomenon capable of producing

disaster, flooding is by far the most significant in causing significant loss of life and property. The

severity of such disasters is often increased several folds by the after effects diseases and starvation

(Alexander, 2000).

The physical impacts associated with floods are; force loading and abrasional damage related to debris deposition, which results in the disruption to pedestrians, roads, railway lines and air traffic.

Contamination and deterioration of water sources, household objects and equipments are some of the other consequences of floods (Alexader, 2000). Secondary and tertiary damage comprise outbreaks of waterborne disease and multiplying of unwanted pests.

2.1.2 Types of floods and associated characteristics

Generally, floods have a tendency to be short-lived, threshold hazards that suggests a close temporal

and spatial relation between their frequency as hydrological events and the scope of human

responses to them (Viljoen and Booysen, 2006). However floods are also acknowledged for their

diverse characteristics.

The differing types of catchment, runoff regimes, flow processes and land uses all combine with physical geography to create various types of flood events. Generally, there are three main causes of

flood events in which nations show some or all of these different kinds of flooding namely; mountains

flash floods, freshwater flooding; river floods, and mountain catchments flash floods(Alexander, 2000).

Flash floods are an extreme; though short –lived, form of inundation. They usually occur under

stationary or slowly moving clusters of thunderstorms or result from motionless or slowly progressing

storms which have an unabated inflow of air that has high moisture content (Alexandra, 1999). The

storm usually lasts less than 24 hours, but the resulting rainfall intensity greatly exceeds infiltration

capacity (usually peak in the range 50-100mm/hr) (Alexandra, 1993).

It is undeniable that by far, the flash floods have the highest average mortality per event (Jonkman,

2005). According to Jonkman, ibid), the flood type and location indicate that average mortality is

comparatively constant for the different types of flood over various continents, while the magnitude of

the impacts (deaths) and affected people for a certain type of flood varies between different

continents (Jonkman, 2005).

2.1.3 Flooding and severe weather

Flooding is a very common environmental hazard with over 3 000 disasters recorded in the CRED

database since the 1900(Smith and Petley, 2009). This is generally because of the widespread

distribution of river flood plains and low lying coasts and their long-standing attraction for human

settlement (Smith and Petley, ibid).

An Increase in agricultural practices and cultivation mismanagement has played a great role on

increasing the risk of flooding. Local farmers have become more vulnerable to flood as they farm in

the flood line.

2.22.22.2 FFFloodingFlooding in South Africa and the Western Cape

South Africa, like many other nations demonstrates both the severity and diversity of these floods regardless of the fact that it is one of the driest countries of the world with the average rainfall of 500 mm per annum. The impacts and social vulnerability related to flood hazards in South Africa are also exacerbated by unsustainable development, expansion of poorly serviced urban areas and exhaustive agricultural practices in the country (Alexander,2000)

2.2.1 Historical overview of flood

Although South Africa is considered to be a disaster-prone, the level of documentation of the

Nationally declared disaster and significant events is very low (Montagu cut-off low Report, 2003).

Despite this poor level of documentation on average floods causes significant damage once every two years And larger and more extensive floods once every 10-15 years, with some of the famous floods occurring once on a 50- 100 years interval (Viljoen and Booysen, 2006).

The National Disaster Management Centre’s(NDMC) 2007 annual report noted the number of occurrences per hazard type is as follows 'Wet' events occurred in approximately 59% of cases (flood, hailstorm, cloud burst. snow, heavy rain, and torrential rain). It also reported that floods and flood related fatalities comprised 66% of t death attributed to single hazard event in South Africa.

2.2.2 Recent flood events in the Western Cape

Between 1800-1995, the provinces most frequently affected by flooding are those located on South

Africa’s coast .In descending order the most frequently flood affected Provinces are the Western

Cape and KwaZulu-Natal, followed by the Eastern Cape (NDMC annual report, 2007). The province of Western Cape has further shown this trend in 2003, 2004, 2005, 2006, 2007 and 2008 (DiMP, 2010

forth coming report). These events have shown different types of vulnerabilities, including social, economic and physical vulnerability as well loss of life.

In the Western Cape cut-off low weather systems particularly increase the severity of flood events. A

cut-off low is defined as a low pressure system which is recognised to be an important weather

system for two reasons; firstly, they are capable of stratosphere–troposphere exchange, and

secondly, they are often associated with deep moist convection, which can lead to significant amounts

of rainfall over short periods of time and therefore flash-flooding (Singleton and Reason, 2006).

2.32.32.3 Risk factors increasing severity of flash flood events.

2.3.1 Overview

In addition to severe weather exposure, numerous other factors can increase the severity of floods.

These include impervious surfaces, land degradation and wild fires.

2.3.2 Increase in impervious surface

An ideal catchment area is one with ground cover or vegetation still undamaged. Plants play a crucial

role on ensuring that runoff is slowed, allowing infiltration and recharge of groundwater stores. Land

cover and land use change is a vital constituent to signify the relationship between the state of a

river’s catchment and the quality of its water and its flow (Rabie and Day, 1999: in Rogatschnig,

2005). The condition of a catchment is positively influenced by the state of affairs of the soil, which in

turn is directly related to land-cover and land-use change.

Generally the removal of forest and other natural vegetation, and the conversion of land to agricultural

uses, as well as an enlargement in urbanised areas, compact the soil and reduces infiltration rates,

leading to higher flood peaks.

2.3.3 Land degradation

Land degradation issue relates to the change in plant species composition as a result of grazing or fire mismanagement (Hoffman and Ashwell, 1999 in Rogatschnig, 2005). This usually results in badlands with degradation predominantly found on foot-slopes and gullies in valley bottoms

(Alexander, 1993). Land degradation, like increase impervious surface increases runoff and hence the risk of flooding.

2.3.4 Wild fires

The regular occurrence of mountain and wild fires play a significant role on escalating the risk of flooding. According to the WCNC Board (2009) mountain fires have become more regular and the severity of these fires has increased from 1995 to recent. Increases in fire frequency and severity have been recognised to degrade top soil hence an increase on the formation of debris during flooding. In addition some of the alien vegetation produces chemicals that result in hydrophobic soil.

This decreases the rate of infiltration and increases runoff and resulting flood risk (Smith, 2007).

According to Forsyth and Van Wilgen, (2008), fire regimes are outlined through fire frequency, season, intensity and size that characterise a particular area. Ideal periods between veldfires are between 12 and 18 years. Recently the data from the Table Mountain National Park Fire Management indicate that the fires are becoming more frequent (Forsyth and Van Wilgen, 2008). Seasons also play a greater role in the changing this the fire period. Naturally, the fire seasons in the Western Cape are summer and autumn as these periods are generally dry and windy. However, Fynbos have the potential of occurring anytime of the year (Forsyth and Van Wilgen, 2008),.

2.2.2.42. 444 Methods used in storm hazard determination

2.4.1 Overview

An important aspect of flood risk management is determining flood severity for different storm occurrences .numerous methods exist to process. They include the use of storm hydrographs as well as specific flood modelling application.

2.4.2 Storm Hydrographs

In surface water hydrology, stream hydrograph is a graphical measure of changes in discharge over time, as recorded or predicted for a given measuring station in the river basin (Alexander, 1993). This represent how a catchment responds to rainfall. A catchment’s response to rainfall depends on a variety of factors which affect the shape of a hydrograph. Typically, rainfall is the main input to a catchment and the stream flow is often considered the output.

The critical elements of the catchment are topography and geology. The deeper the soil the more water can be absorbed. Soils which have larger particle sizes have larger infiltration capacities. The steeper the slopes, the lower the rate of infiltration and the faster the rate of run-off when the soil is saturated (saturated overland flow) or when rainfall intensity is high (infiltration excess over land flow)

(Drowley, 2007).

Land-use is another important factor which affects the storm hydrograph (e.g. agriculture, urban development, forestry operations). Impervious surfaces and drainage systems help transfer water in an urban area to rivers quickly. An increase in built environments on river flood-plains has contributed to the increase receptiveness of river systems.

Drainage density is also a crucial factor shapes the storm hydrograph. Generally, the larger the number of streams and rivers per area the shorter distance water has to flow and the faster the rate of

response. The duration of rainfall and precipitation intensity and the type affects the shape of the storm hydrograph. The rate and intensity of the rainfall will directly affect the amount and rate of overland flow. Furthermore, the season affects the storm hydrograph. In the summer, evapotranspiration rates are higher, reducing the amount of surface runoff. In addition, photosynthesis

in plants will be at a maximum longer spells of sunlight and higher temperatures will create more

opportunities for root systems to absorb water, and leaf systems to transpire water (Drowley, 2007).

Finally vegetation type and cover modify a storm hydrograph. A high amount of vegetation will capture

the rainfall, and reduce initial surface flow. Evapotranspiration will occur when water is on leaves and

branches, reducing the amount of water on the ground.

In general an increase in land-use/land-cover change such as hardening of the catchment area will

result in an increase in run-off and ultimately a higher river discharge. In terms of the storm

hydrograph a shorter lag time and a higher discharge peak will result (Alexandra, 2000). The storm

hydrograph peak or maximum discharge represents the most damaging aspect of flood waters.

Compaction of the catchment area through increased urbanisation will result in a more efficient, direct

route for water to reach streams and rivers. Storm water runoff tends to travel at greater velocities, and therefore has a much greater erosive potential than naturally occurring runoff (and as a result

causes more damage) (Alexandra, 1993).

2.4.3 HydroCAD flood estimation software

HydroCAD is chosen to model the flood hydrology of the catchment in this study. HydroCAD is a

Computer Aided Design tool used by Civil Engineers for modelling storm water runoff (Drowley,

2007). It generates complete runoff hydrographs using the SCS Unit Hydrograph procedure. The

software package HydroCAD produces weighted curve numbers (CN) and percentage

pervious/impervious area in a catchment area. The CN numbers provide an indication of how much

water is likely to pass through the hydrological system as run-off (or a catchment response index to rainfall). HydroCAD allows the integration of different types of storm and soil type, with changing land- use/land-cover, and calculates the effects of this land-use change on flood levels. It is a common, well-understood and supported method (based on the SCS method of the United States Department of Agriculture).

Hydrology is the amount of precipitation that reaches the land surface and what happens when it gets there (Alexander, 2000) .Historical flow, discharge and rainfall data give insignificant insight of the relationship between rainfall and runoff in a particular catchment. Design rainfall estimation is a way of understanding the statistical distribution of extreme rainfalls for the purpose of incorporating the results into hydraulic structures with specified most probable life spans Studies on design rainfall and long-term extreme value distributions have been done by Smithers and Schulze (2000) and developed into software.

In order to specify the location for the design rainfall estimate, a user rent input a location of a rainfall station. Having taken this option requires the use of the SAWS (South African Weather Services) station number or by entering the station name. The input of the duration of the design rainfall is achieved by selecting the appropriate the design rainfall is estimated for all durations. Similarly, the return period can also be selected. A “radius”, in minutes, from the point of interest and design rainfall will be estimated at each 1'x1' latitude and longitude point within the area. Thus the spatial variation of design rainfall within an area or catchment was evaluated.

2.4.4 Other design flood estimation procedures

2.2.2.42. 444.3.1.3.1 Hydrologic Engineering Center Hydrologic ModelModellingling System (HEC ---HMS)-HMS)

The HEC-HMS was developed by the United States Army Corps of Engineers, and designed to simulate the precipitation - run-off - routing process of dendritic watershed systems (USACE, 2000).

This programme is designed to be applicable in a wide range of geographic areas and is able to solve problems ranging from large river basin water supply and flood hydrology, to small urban or natural watershed runoff (USACE, 2000 in Drowley, 2007). The hydrographs produced by HEC-HMS can be used directly or in conjunction with other software for studies relating to water availability, urban drainage, flow forecasting, future urbanisation impact, flood damage reduction and floodplain regulation (USACE, 2000 in Drowley, 2007).

2.42.42.4.42.4 .4.4.4.2.2 USSCS method

The United States Department of Agriculture Soil Conservation Service (SCS) model has also developed for South African conditions by . The model was developed for use on small catchments of up to 82 square kilometres. SCS uses curve numbers to estimate runoff. The curve number method, also known as the hydrologic soil cover complex method, is a versatile and widely used procedure for runoff estimation (Schmidt and Schulze, 1987). This method includes several important properties of the catchment; namely the soil's permeability, land use and antecedent soil water conditions.

2.42.42.4.42.4 .4.4.4.3.3 Regional maximum flood (RMF)

The RMF approach is based on observed maximum floods, which in turn are based on estimated

maximum possible rainfalls derived from observed maximum rainfalls and maximised observed

storms. The RMF is an upper envelope of floods that have occurred in a region, and is consequently a

reasonable estimate of the maximum flood that could be expected to occur at a specific site

(Alexander, 2000).

2.2.2.52. 555 CCConceptualConceptual frameworks for tthishis study

Although there is considerable literature on flooding in fields such as freshwater ecology and flood

hydrology, the focus in this study will be on characterising the river flood hazard component of flood

risk. This applies a disaster risk approach in which flood hazard factors interact with conditions of vulnerability to increase risk. The adopted conceptual framework used focuses specifically on the flood hazard component of flood risk by examining the impact of land use/land-cover change on the magnitude of flood event. It also incorporates other risk factors that increase the damage potential of flood event (refer figure 3.below, adapted from Drowley 2007).

In this conceptualisation the interaction between land-use/land-cover and an extreme storm event influences peak volume, discharge and runoff; it further argues that when catchment conditions harden (i.e. as a result of land-cover change), this can result in a shorter time to peak discharge. It is also acknowledged that the rainfall intensity and antecedent catchment wetness can also influence runoff generation processes (Niehoff et al., 2002 in Drowley, 2007).

Extreme

(Precipitation) weather conditions Debris loading

Shorter time to Increase peak Infrastructure in farming in harm’s way Severe volume in flood weather- Changing risk areas exposed Discharge magnitude Lack of catchment of flood Decrease catchment event natural Increased management Increased vegetation run off severity of flood loss

Increased Antecedent Wild fires moisture

conditions

Increased

open space

Risk factors that increase the damage potential

of endangering flood event Figure 333:3: Adopted conceptual frameworframeworkkkk

Source: adapted from Drowley 2007

3. RESEARCH CONTEXTCONTEXT:: Keisie River Catchment, MontaguMontagu

3.1 Overview of Montagu

3.1.1 History

The town of Montagu was established in1850 and named after a colonial Secretary Sir John Montagu

(Sinske, 2007). The construction of the Kogmanskloof pass in 1877 resulted on the booming of

Montagu as the pass worked as direct access to the trading post of Ashton, which was then connected to the railway line; and thus opened up the Western Cape Colony (Bulpin, 2001 in

Rogatschnig, 2005). The fruit and wine industry became the central economy within the catchment and in 1940. The establishment of the canning factory in Ashton also boosted the Agricultural production in the Keisie River catchment (Bulpin, Rogatschnig, 2005).

3.1.2 Socio-demographic and economic profile

The Montagu economy relies heavily on agricultural activities specialising heavily on vineyards and peach and apricot orchards. In addition, private wine and jam manufacturing play a big role for generating income in Montagu. Overseas and local tourists are also the main contributor to the economy; major tourist’s attractions include the hot springs and the wineries in Montagu and the neighbouring towns. The population of Montagu is approximately 11 000 (Statistics South Africa,

2008) with a regular seasonal influx of people from all over Western Cape and the Eastern Cape to work in the farms. (Statistics South Africa, 2008)

3.2 PPhysicalhysical characteristics of the catchment

3.2.1 Study area

The Keisie River catchment is situated in the Klein Karoo region of the Western Cape, within the

Langeberg and the Waboomsberge mountains. This tertiary catchment is part of the greater Breede

River Catchment. The Keisie River is the western branch of the great Breede River, the longest water course of the Cogmanskloof River upstream of the confluence. The length of Keisie River is 65km.

Both the Keisie and the Kingna are Perennial Rivers drain into the primary catchment of the Breede

River (Sinske, 2007). In the North-West of the Keisie River is the Pitersfontein Dam which serves as one of the irrigation dams that provides water to the agricultural community within the catchment.

Figure 444:4: The Keisie River catchment area

Source: developed from the data provided by CD: SM (2007)

The Keisie River catchment incorporates the tourist town of Montagu, situated 170 km east of Cape

Town. The confluence of the Keisie River and the Kingna is at the South entrance of the town of

Montagu and the north end of the Kogmanskloof.

3.3.3.23. 222.2.2 Climate

The Keisie River catchment is situated in Mediterranean region in the winter rainfall region of the

Western Cape known as the Klein Karoo (SAWS, 2008). This region is characterised by strong

seasonal disparity. The summers are hot and dry whereas the winters are wet and humid. The rainfall

in this region is strongly seasonal, with approximately 80% of the annual rainfall falling between the

months if April and September due to frontal rain systems of this region (DWAF, 2003, refer to figure

3.1.2 below). The rainfall in this area further varies due to its topography. The mountainous area of

the Langeberg and the Waboomsberg receive the highest mean rainfall compared to the low-lying

area which receives the lowest (DWAF, 2004).

Figure 555:5: MontaguMontagu’’’’ss monthly average precipitation curve of the rainfarainfallll in March (1883-(1883 ---1995)1995) is 19.43 mm/month. April indicates the start of the Wet wiwinternter season, with a large increase in average monthmonthlyly precipitationprecipitation

Source: DiMP (2003)

The Keisie river catchment is characterised by the by a significant diurnal fluctuations in temperature

(Kotze, 2002 in Rogatschnig, 2005). During the summer months, temperatures regularly reach 38 degrees Celsius during the day and drops below freezing point in cold winter nights. The daily average minimum and maximum temperatures for summer and winter range from 15 to 42 degrees

Celsius and -3 to 18.5 degrees Celsius correspondingly(Kotze, 2002 in Rogatschnig, 2005).

Due to hot dry summer, evaporation is high in the catchments area. It is estimated to be 50% less between the months of April and September as compared to the summer months. Evapotranspiration values is therefore higher between October and March, this is reflected by a decrease in groundwater

(Kotze, 2002 in Rogatschnig, 2005).

3.2.3 Geology and soils

Most of the Western Cape geology encompasses the sedimentary rocks of the Cape Supergroup

made from wind and water erosion. The Keisie River catchment shows the same characteristics

because of the dominance of the Table Mountain and the Bokkeveld Cape Super Group. The

Langeberg Mountains and the Waboomsberge which enclose the catchment area are characterised

mainly by the Table Mountain Group Sandstone, and the base constitute mainly the Bokkeveld Group

Shales and siltstone. The yellow Malmesbury phylittes are dominant on the slopes of the

Kogmanskloof (Geographical Society of South Africa, 1999).

A significant percentage of the area consists of young shallow soils which are derived from the

Bokkeveld Group which dominates the geology of the study area. (Wakeys,1999 in Rogatschnig,

2005). Soils derived from the Table Mountain Super Group rocks are also shallow, quartzite and

generally with less nutrients, hence not suitable for cultivation (Wakeys, 1999 in Rogatschnig, 2005).

3.2.4 Vegetation in the Keisie River Catchment

The Keisie River Catchment is situated predominately within the Fynbos Biome of the Western Cape.

The vegetation type of the area comprises dwarf shrubs (chaemaphytes) and grasses

(hemicryptophytes) dominate the region. There are 2'147 species of which 377 are endemic (DEAT,

2008).

Within the Keisie River Catchment, the low lying areas are generally characterised by the vegetations belonging to the Succulent-Karoo biome, and the Little Succulent vegetation. The upper slopes are dominated by the Mountain Fynbos the Central Mountain Renosteveld.

Rather than the natural vegetation found in the catchment, there is also a percentage of Alien vegetation invasion. The term alien is used to define any species that is not naturally occurring in a specific area (Rogatschnig, 2005).

The riparian zones are reportedly the most invaded in the Catchment. They are also the most vulnerable to invasion as the alien species are consumptive water-uses with the potential to reduce river flows. In addition alien vegetation species that have invaded the South African River catchments are also associated with severe fire events (.Forsyth and Van Wilgen, 2008)

3.2.5 Hydrology

The Keisie River Catchment is a tertiary catchment of the greater Breede River catchment. As mentioned earlier the Keise River is one of the two rivers which drain the Kogmans River Catchment.

The Pietersfontein dam is built and maintained by the Department of Water Affairs and Forestry to serve much of the agricultural sector in the catchment with irrigation water. The Pietersfontein Dam is an Arch dam with a height of 29m (DWAF, 2003 in Rogatschnig, 2005). This dam is a major tributary to the Keisie River and lies 18km north-west of Montagu (DWAF, 2003). The construction of the dam was completed in 1968 on the Pietersfontein River with a maximum storage capacity of 2.097

million cubic meters and at full supply covers an area of 30.4 ha (DWAF,2003). The irrigation boards operating in this catchment area are the Cogmanskloof Irrigation Board. This board operate a pumping scheme that diverts water from the Breede River to Montagu. The Baden Irrigation Board also that manages groundwater supply in the Montagu area utilising the spring water from the

Pietersfontein River valley (DWAF, 2003 in Rogatschnig, 2005). The Keisie River is listed as one of the rivers that support the riverine wetlands in A Directory of South African Wetlands (Cowen and Van

Riet, 1998 in Rogatschnig, 2005).

3.3.3.33. 333 Exposure to extreme weather

3.3.1 Flood history in Montagu

The town of Montagu has experienced at least ten major floods since its establishment in the 1850s

(DWAF,nd). The first recorded flood occurred on 8 March 1867, when a powerful storm caused the

Keisie River to burst the banks, damaging vineyards and claiming the lives of at least twelve people

(Rogatschnig, 2005). Later that year in May, another flood followed and caused great damage to

property, completely washing away the road through the Kogmanskloof, there was fortunately no loss

of life in this event (Rogatschnig, 2005).

Table 111:1: Montagu flood History: Flood History: 18671867----20082008

Source: SAWS in Rogatschnig, 2005

Date Region/Location of floods Source

08-03-1867 Montagu Burman, 1970

05-1867 Montagu Burman, 1970

14-05-1885 Southern Cape DWAF*(Event**.92)

14-12-1906 Montagu Burman, 1970

11-10-1948 Southern Cape DWAF*(Event**.120)

25-01-1981 South-Western District DWAF*(Event**.260)

02-02-1981 Laingsburg DWAF*(Event**.566)

22-09-1983 Southern Cape DWAF*(Event**.568)

24-03-2003 Southern Cape DiMP,2003

11-11-2008 Montagu DiMP,2008

The great floods of the 19 th and the early 20 th century were devastating for Montagu. However the

flood event of 25 th of January 1981 was reported the most damaging prior to the event of the 11 th to the 13 th November 2008. On the 25 th January 1981, the banks of the Buffels River broke, submerging more than 367 houses and business premises and claiming the lives of 100 people (DiMP, 2003). In addition, flooding in the Keisie River caused the Pietersfontein Dam to spill for the first time since its

construction. This resulted in the Keisie River bursting its banks, washing away the Caravan Park and the “hot springs” and claiming the lives of 13 people in Montagu (Rogatschnig, 2005).

In February 1981, Montagu was struck by another flood that resulted in more damage to much of the rehabilitation done the previous month (DWAF,nd). A further flood struck Montagu in1983 and caused both the Kingna and the Keisie River to overflow.

TTTableTable 222:2: PPPreliminaryPreliminary damage assessment in Montagu

Source: DiMP, 2008

Reported Economic Losses (R)

Insured Losses Uninsured TOTAL VARIVARIAAAANCENCE or SECTOR Losses ECONOMIC SHOSHORRRRTFALLTFALL LOSSES (Rand)

Civil Engineering 240,000 6,565,000 6,805,000 6,565,000

Electrical Eng. (East 307,171 307,171 Montagu)

Electrical Eng. (West 318,877 20,600 Montagu)

Environmental 93,000 512,200 605,200 512,200 Services

130,000 130,000 Community Facilities

Totals 1,089,048 7,123,200 8,166,248 7,123,200

After 1983, the next flood to hit Montagu occurred in 2003. Although this event exacted significant

losses in the town itself (DiMP, 2003), farmers along the Keisie River reportedly view the 2008

flooding event as the most damaging to the infrastructure(DWAF,ND). The losses for this event are

also shown in the table above.

3.3.2 November 2008 cut-off low

3.2.2.1 Meteorological facts

Figure 66:: 500mb Geopotential heights (contours) and nearnear----surface winds (arrows) for various times during 111111-11 ---1313 November 2007. Shading depicts TRMM satellite estimated rainfall rratesates

Source: DiMP (2008)

A cut-off low in Montagu began forming on Tuesday 11 November 2008, with the severe weather occurring during the early evening. During the following 48 hours the system intensified as the upper- level atmosphere developed a cut-off low, and the South Atlantic High Pressure cell, ridged in below the Western Cape to help drive storm strength winds(figure 6) (DiMP, 2008).

This was a three day weather phenomenon that resulted in flash-flooding to the Western Cape but more intensely in Montagu and the nearby town. This extreme weather event resulted in damage to properties and posed risk to motorists with couple of vehicles blown off the roads by gust wind

(DiMP,2010 forthcoming report).

...

Figure 777: Daily rainfall at stations in Western Cape for 12 November 2008. Dot sizes and shading represent 24hr accumulated rainfall total Source:

Source: DiMP, 2010 forthcoming report.

Figure 7 clearly shows that the core region of the heavy rainfalls was in the region of the highest

topography of the central south-western Cape Mountains. This is also evident as the high lying area

of the Langeberg Mountains recorded between 350 mm and 500 mm in a period of 3 days, whereas

the low lying valley and the town of Montagu recorded about between 150mm and 180 mm over the

same period (DiMP, 2010).

Figure 7 shows the stations that have record rainfalls of above 25mm on any day during the three

day event. However, these stations were already experiencing heavy downpours during 11 November

with 24hr accumulated rainfall exceeding 50mm at many of these stations on the Tuesday (DiMP,

2008).The heaviest falls however, occurred on Wednesday 12 November with rainfall over 100mm

recorded at 4 of the stations presented in Fig.9. The highest 24hr total for these stations was 175 mm

in the Haweqwas State Forest (DiMP, 2010).

Table 333:3: Daily rainfall 101010-10 ---1515 November 2008

Source: DiMP, 2010

Town 11 Nov 12 th 13 th 14 th Total rainfall (mm)

Ashton 38 57.5 26 121.5

Ceres 19 24.5 0.1 43.6

De Doorns 134 134

Montagu 48 76 5 129

Robertson 4.1 38.5 74.2 144.3

Touws River 20 58 1 78

Tulbagh 14.5 20 35.5

The total rainfall that was recorded in this event is shown in table 3 above. This is how heavy rain falls over Ashton, De Doorns, Montagu and Robertson. It resulted in recorded direct losses of R 8 166

250.00 in Montagu (DiMP, 2010). However De Doorns resulted in the death of a matriculant who drowned while attempting to reach school for her exam.

4. METHODS

4.1 Introduction

This research applied a case study method to examine the relationship between land-use and land- cover change and the flood hydrograph within the Keisie river catchment. In this context, a range of qualitative and spatial methods were used involving both secondary and primary data sources. An overview of the steps applied in this study is below in represented in the figure below.

HydroCAD Rainfall Data

Extraction Utility

Primary data Change Hydrological collection ArcGIS in land- data: Peak Flow Keisie use/land Inflow Volume Spatial River cover Secondary catchment analysis since data 1963

collection

Figure 88:: method analysis

Source: adopted from Drowley (200

444.24.2.2.2 secondary data sources

4.2.1 Data Sources

A range of secondary data sources were used in this study. These included rainfall data sourced from the South African Weather Services for the rainfall stations in Montagu and Ashton from the year

1900 to 2008.

Spatial data in the form of aerial photograph of the Keisie River catchment for the year 1963 and 1987 were sourced from the Chief Directorate of Surveys and Mapping. 2007 imagery however was obtained from FUNDISADIS K CSIR, 2009.

Documented reports of the past floods and cut-off lows events were also sourced from the Disaster

Mitigation for Sustainable Livelihoods Programme. These included unpublished reports for 2007,

2008, 2009 and 2010. They also included past students theses related to provincial flood events (i.e.

Rogatshnig, Drowley and Smith).

4.2.2 Rainfall data collection

Daily rainfall data were obtained from three SAWS rain gauge stations, one in Montagu, and one in

Ashton, which is 16km away from the town of Montagu but still, reflects the rainfall data in the Keisie

River Catchment. The Concordia weather station is a few kilometres outside of Montagu but still provide necessary data for the study area.

4. 3 Primary data collection

4.3.1 Study area

Figure 999:9: the map outlining all the different landland----covercover categories in the Keisie River Catchment

Source: the map is developed from the data provided by CD: SM (2007)

A field visit was undertaken to Montagu from the 18th to the 20 th of November 2009 to observe the major land-use/ land-cover conditions of the catchment. Flood-affected sites were visited; in addition, catchment vegetation slope and soil types were observed.

Structured and semi-structured interviews and consultation were held with key informants, including disaster risk managers, the town planner, farmers and residents. These interviews were conducted to

“ground-truth” information derived from the aerial photographs.

Primary data collection also included the collection of observational and photographic data collection from flood damaged sites. These photographed sites were also georeferenced using GPS instrumentation.

4.3.2 Spatial characteristics of the Keisie River Catchment

a) Estimation of physical characteristics of the catchment

Generation of slopes

Using the ArcGIS “Terrain Model” feature, physical characteristics of the catchment were estimated

specifically 5m, 10m and 20m contours were used to generate the slopes using a five scale-resolution

spectral analysis.

Estimation of land-use

The percentage estimation was also estimated using ArcGIS. After the land cover layers were

created; the calculation was done by applying polygons for all the created layers. Summary tables for

land use categorisation were created for the layers and the percentage land-use for each category

was calculated and the percentage change over the years was produced.

b) Subdivision of the catchment

The Keisie River Catchment was divided into three distinctive land-cover categories. .The sub-division

of the catchment was necessary for this study as the HydroCAD modelling package is used

specifically to Model small –sized catchment and the required results is suppose to classified in such manner, and also the whole catchment have distinctive properties that would require special treatment for each different land-use c) Determination of land-cover over time

The Aerial photographs for 1963, 1987 and 2008 were Geo-referenced by using the method “rubber- sheeting”. There after the digitalisation of the images was done with the vector polygon layers by using the five predefined land-use/ land-cover classes. The method of classification implemented was a visual rather than a computer programmed The Aerial photographs for the years 1963, 1987, and

2008 were therefore used to trace the change in land-use and the fraction increase in cultivation and urbanisation within the Keisie basin.

4.3.3. Data consolidation

For the purposes of spatial data consolidation the ArcGIS images were refined using flood damage

georeferenced photographs along with and the observational data and field measurements.

4.4.4.44. 444 Data analysis

4.4.1 Overview

The consolidation of the spatial data for the Keisie River catchment, as well as rainfall data, allowed

for generation of three storm hydrographs for a variety of catchment conditions .Data analysis was

undertaken through several steps that involved;

a) Determining the return period of the November 2008 storm, using Design rainfall estimation tables

b) Generating three storm hydrographs over the Keisie River Catchment under land-use conditions

defined for 1963, 1987 and 2007.

c) Comparing the three storm hydrographs was necessary to identify the possible relationship with land-use and land-cover change.

4.4.2 Determining the return period of the November 2008 storm

With the use of the design rainfall software package a series of storm hydrographs were generated for

a variety of catchment conditions namely;

The current land-use pattern (2008)

The “intermediate” land-use pattern (1987)

For the pristine natural conditions

Also in different rainfall conditions, the model was created for 1:50 year storm event, ideally assuming that this event will occur under are extreme weather condition consistent with cut-off lows and assuming event duration of 5 days (Drowley, 2007).

The statistics created by the design rainfall software allowed comparing and predicting the future runoff conditions which resulted from extreme weather events. These statistics included; discharge, inflow depth and peak volume.

Prior to generating the storm hydrograph for the Keisie River catchment, it was necessary to determine the antecedent soil moisture condition. Rainfall records from October 2008 indicated that the surface was not too dry or very moist but just the right conditions that would allow a reasonable amount of infiltration and at the same time not causing exhaustive soil erosion due to soil dryness.

4.4.3 General storm Hydrographs

The rainfall data extracted from the design rainfall estimation package was inserted into HydroCAD software, where various storm scenarios were generated. The rainfall depths for these return periods were obtained from the utility program "Design Rainfall Estimation in South Africa" by Smithers and

Schulze (2002). The SCS model uses a range of different storm types in order to generate hydrological data. A type II 24-hr storm type was used for this study, as it corresponded the rainfall characteristics of Montagu area.

5. Research findings and analysis

5. 1 overview of the chapter

This chapter is divided into five subd ivisions . Section 5.1 begins by presenting findings on land-

use/land-cover change from 1963 to 2007 followed by a description of the physical features of the

Keisie River catchment in 2008. This chapter continues with a focus on the meteorological conditions

that generate endangering floods, as wel l as modelled storm scenarios over the catchment during the

12 th of November 2008 rainfall event .

5.2 Changes in landland----use/landuse/landuse/land----covercover

This section includes the anthropogenic changes in catchment which alter the geometry of the river

bed and banks. These results will explain the change in land-cover/ land-use. The table below shows

the change that occurred between 1963 and 2007. The positive number underlines a percentage

increase of that specific category of land cover over a period of time whereas the negative value

shows a decrease.

Table 444:4: LandLand----covercover change between 1963 and 2007

Source: CD: MS (1963, 1987, and 2007)

LandLand----covercover change between 1963 and 2007

Name 1963(ha) 1987(ha) 2007(ha) % % %

change(1963 change(1987 change(1963

-1987) -2007) -2007)

Agriculture 2,079.7 3,060.43 3,171.9 3.6 0.4 4

Natural 22,851 20,286.7 20,503.8 -9.4 0.8 -8.6

Open Space 556.3 1492.30 1131.8 5.5 -1.4 2.1

Water Body 667.04 746.07 618.8 0.3 -0.4 -0.1

Total pervious 26,154 25,585.5 25,426.4 Surface

Impervious 1148 1,716.55 1875.5 2.1 0.6 2.1 surface

Total Catchment 2,7302 27,302.0 27,302.0 Size

The impervious area of the Keisie River catchment comprises 5% of the total area of 27302.55

hectares. Analysis of the aerial photographs from 1963 and 1987 indicated a slight increase over

forty years. However, this was not significant enough to change the storm hydrograph of the

catchment (Alexander, 1993).

5.2. Changes in Land-cover over time and observed characteristics in the Keisie River Catchment

Natural environment cover was shown to be the category with the highest percentage relative to other

land-cover categories. However, it also decreases the most. Both observational and the ArcGIS data

indicate that Agricultural practices occupy a significant percentage of the catchment area although the

change rate appears decrease over the years.

According to the data extracted it is evident that there has been a slight decrease in the total area

occupied by the water bodies. This could be explained by changing weather systems as well as

intensive agricultural practices.

The open space category is recorded to have been decreasing for the past 20 years. The built

environment has shown to have increased over the years as the result of infrastructural development

in the catchment.

5.3 CCharacterisationharacterisation of the November 2008 storm

The November 2008 cut-off low accumulated 129 mm of rainfall over a period of 3 days. However the

maximum daily rainfall recorded over that period was 76.8 mm on the 12 th of November 2008. From table 1 , this years; 1910, 1918, 1993 are those with rainfall that approximate that of the 12 th of

November 2008.

5.4 Storm hydrograph comparison of the Keisie River catchment conditions

Hydrograph 79,931.34 cfs Runoff 80,000 Type II 24-hr 70,000 Rainfall=59.01" Runoff Area=6,746.500 ac Runoff Volume=26,507.850 af 60,000 Runoff Depth>47.15" Tc=180.0 min 50,000 CN=65 40,000

Flow (cfs) Flow 30,000 20,000 10,000 0 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Time (hours)

Figure 666:6: storm hydrograph for the 1963 catchment condition for 1:40 year return period

Hydrograph 90,000 82,118.31 cfs Runoff

80,000 Type II 24-hr Rainfall=59.01" 70,000 Runoff Area=6,746.500 ac Runoff Volume=30,143.141 af 60,000 Runoff Depth>53.62" Tc=180.0 min 50,000 CN=79 40,000

Flow (cfs) Flow 30,000 20,000 10,000 0 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Time (hours)

Figure 777:7: storm Hydrograph for the 1987 catchment conditioncondition for 1:40 year

Hydrograph Runoff 80,000 71,361.11 cfs Type II 24-hr 70,000 Rainfall=51.01" Runoff Area=6,746.500 ac Runoff Volume=26,400.357 af 60,000 Runoff Depth>46.96" Tc=180.0 min 50,000 CN=86 40,000

Flow (cfs) Flow 30,000 20,000 10,000 0 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Time (hours)

Figure 888:8: Storm Hydrograph for the 2007 catchment conditioncondition for 1:40 year

Comparing the three storm hydrographs was necessary to identify the possible relationship with land- use and land-cover change. However the results indicate that there was no significant difference in the shapes of the hydrgraphs for the three different catchment scenarios.. The similarities in the hydrographs under 40 year flood return conditions are not surprising, given the modest change in vegetative land-cover observed from historic aerial photographs since 1963. However, this does not adequately explain the disproportionately high losses that were observed and reported following the

November 2008 cut-off low. Additional factors are identified and described in the following chapter.

6:6:6: Discussion and Conclusion

6.1 Introduction

The inability of the flood hydrograph and land-use and land-cover analysis to provide clear

explanation for flood damage underlines the need for close investigation of the other risk factors that contributed to the flood loss. These include; anthropogenic developments (agricultural activities and infrastructural expansion) in the flood exposed areas, decrease in natural storage capacity and in addition the changing pattern in the distribution of open spaces and the role of wild fire in the mountain catchments

6.26.26.2 The anthropogenic developments in the flood exposedexposed areas

The spatial analysis indicates that agricultural activities have not changed significantly at a macro-

scale with the catchment. However, these activities with the riparian zone and poor farming practices

may play a major role in increasing the severity of flooding losses. This is due, on one hand, to

anthropogenic changes to the riparian zone that increase the hazardous nature of the flooding as it

also reflect the fact that there is now more development actually in “harm’s way” that is exposed to

flood processes.

In addition it is also evident that although the percentage area of the built environment have

increased over the years it did not increase the flood risk as it did in the November 2008 storm

event. The reason behind this is the fact that some of the recreational developments are occurring in

the riverine and runoff areas which are highly vulnerable to flooding.

Changing patterns in distribution of open space particularly along the slopes has increased runoff

and therefore debris loading and the severity of flooding in the catchment areas.

6.3 Consistency of research findings with existing literaturliteraturee

The literature for this study focuses on the flood hazard component of flood risk by examining the impact of catchment-scale land use/land-cover change on the magnitude of flood event. The research findings diverge somewhat from the literature described because they indicate the importance of localised changes in parts of the catchment that are highly vulnerable to flash floods. However, field observations did confirm published findings about the relationship between farming on catchment slopes and riparian zones and increased flood loss. The small incidents (farming on the catchment slope and in the riparian zones (refer to 6.2)), by observation of the agricultural activities in the catchment is consistent with the literature that incorporates other risk factors that increase the damage potential of flood event.

In addition, the literature of flood related hazards that underpins that; the substitution of natural forests with artificial surfaces increases the impervious area results in an increase in runoff diverged from the research findings. The research findings in the study area shows that an increase in impervious area in the harm’s way (steep slope and along the river banks and in the riparian zone) plays a greater role on increasing the flood severity.

6.4 Conclusion and dddirectiondirection for future research

This research intended to examine the recent flood history of the Keisie River from 1918 to 2008. The findings illustrate that the 2008 flood event was not the one with the highest flow rate according to the storm hydrographs (refer to figure 9). However, the 2008 event was the most damaging.

The study further intended to establish the nature and degree of land-use and land-cover change within the Keisie River catchment that may have influenced the flood hydrograph in the 2008 flood

event. The research findings identified fine scale contributing risk factors for endangering floods within the Keisie River Catchment.

The application of a simple hydrological model to the Keisie River catchment to examine the effect of change in land-use and land-cover on the total discharge of the catchment was performed. This concluded that this type of the methodology does not show the complexity of assessing flood risk in mountain catchments. A drawback identified in this research was the use of coarse spatial data at catchment scale.

The coarse scale used in this research also limited to show fine scale local characteristics of the catchment. This include for example, being unable to differentiate between alien and indigenous vegetation. In conclusion, the methodology applied in this study, ruled out the flood risk assessment that would have detailed my research.

A useful direction for future research would be to explore the flood risk assessment methods that can detail the characteristics of the catchment at a fine scale. This ideally would differentiate specific flood prone areas and to identify fine scale changes that increase the likeliness of flood loses associated with severe weather.

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Appendix

Source: CD:SM(1963)

Period 1 Month Plot Start00:00_01/11/2008 2008 Interval1 Hour Plot End 00:00_01/12/2008 H3H005 Keisie @ Keisiesdoor100.00 Max & MinLevel (Metres) 3

2.5

1.5

0.5

0 1 2 3 4 5 6 7 8 9 101112131415161718192021222324252627282930

Source: DWAF, 2009

Table showing daily rainfall data for 2009

DAY JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC

1 2

2 4

3 4 A

4 A

5 11 .0 C

6 5

7 5 5.5 2 33

8 2 3 19

10 3

11 2.5 1.5 6 6 48

12 5 76

13 5

14 3

18 0.5

19 8

20 4 8

22 5

23 5

24 4.5

25 15

26 8

27 2

28 6.5

30 2

TOT 0 11 1.5 19 15 13 34.5 13 21 53 129 11.5

Source: SAWS,2009

Source: http://www.beltramiswcd.org/Aquatic%20Biology/Hydrograph.jpg