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Risk assessment: The effect of flooding on the socio-ecological

system of the Irrawaddy river delta

Annabel Isarin, Laurens Beets, Thomas Hofman en Martin Vergouw 3-10-2017

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ABSTRACT

In this paper a risk assessment of floods in the Irrawaddy delta is proposed. This will be done through an interdisciplinary approach. Three different disciplines will be working together; Human Geography, Earth Sciences and Biology. The aim is to integrate knowledge from different disciplines and to assemble new insights regarding the complex system of the Irrawaddy delta. The risk assessment will consist of the probability of the flood hazard, the elements at risk and the vulnerability of the delta. Combining these three questions will result in a risk assessment of the floods in the delta.

Introduction

The Irrawaddy is the biggest river in Myanmar, stretching across the entire length of the country. It originates in the north of Myanmar in the Hengduan Shan mountains and debouches 2170 kilometers downstream in the Irrawaddy delta in Southern Myanmar. Myanmar’s climate is dominated by the dry and the wet season. The wet season, which is also referred to as the monsoon, takes place from June to October. A monsoon is a seasonal reversing wind accompanied by changes in

precipitation. During monsoon season, it is very likely that flooding will occur in the delta due to increases in precipitation (Brewin et Al., 2000). On July 22nd of 2017 a large flood displaced 100.000 people and killed two people in Myanmar. It caused enormous damage and wiped entire villages in the country (Lone, 2017). The Irrawaddy delta has a width of 115 kilometer and is of utmost

importance to Myanmar since it provides nearly 60% of the total rice production in the country (NASA, 2008). In the delta region, nearly 60% of the land is cultivated with rainfed rice and there are often concerns about drainage and flood protection (Giosan, 2014). The Irrawaddy delta is the largest, most dense agricultural area of Myanmar. Flooding in this area can cause serious damage. This paper will provide a risk assessment of flooding in the region. This means calculating the hazard probability, the elements at risk, and the vulnerability of the area. Calculating the risk is an important aspect in decision making regarding coastal protection. This research can also be useful in research regarding the damage of future flooding, since this paper provides a framework for calculating the damage of flooding in the delta.

An interdisciplinary approach was necessary in this research, as a risk assessment crosses the boundaries of different disciplines. The perspectives from the disciplines Human Geography, Earth Sciences and Biology will be integrated to achieve a more complete and less one-sided view of the complex system of the Irrawaddy Delta. To make a correct risk assessment the following sub question have been made: “What is the hazard probability of flooding in the Irrawaddy Delta?”, “What are the elements at risk?” and “What is the vulnerability of the Irrawaddy Delta?”. This to answer the main question: How does flooding affect the socio-ecological system of the Irrawaddy river delta?”.

For this research, the quantitative risk assessment will be used. This method comprises of the hazard probability, elements at risk and the vulnerability. The hazard probability will be measured by using the method of Smith & Petley (2008). In this method, historical data of flooding is studied and the events are ranked, after which the probability of flooding is calculated. The elements at risk are valued in monetary terms and measured by using valuation methodologies such as the TEEB, which can be used for measuring the value of a specific piece of land per hectare (Van der Ploef & de Groot, 2010). The vulnerability will be measured by using the Vulnerability-Resilience Indicators Model (VRIM).

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Theoretical framework

Risk assessment method selection

Providing absolute safety is impossible. However, there is great sense in determining the level of risk for any given situation. This paper aims to provide a quantitative risk assessment following the Krewski et Al. (1982) risk assessment method. This method calculates the risk of flooding by

multiplying the Hazard probability with the Elements at risk and the Vulnerability. This method reviews different, mutually exclusive, events (E1 .. En) (the hazard) and multiplies those with the probability and loss equivalents. Since flooding has different causations this is an appropriate way of measuring the risk of different floods and adding them up. The effectiveness of this method relies on a good database of the events. Hence, this method is not completely adequate for rare events, since less data on these events is available.

This method focusses on the objective risk and excludes the perceived risk. Distinctions are being made between objective and perceived risk because individuals often perceive risks intuitively and quite differently from objective assessments (Starr & Whipple, 1980). Perceived risk is seen as crucial in assessing risk, alongside objective research, because most people make decisions about hazards based on their perceived risk. Risk perception therefore has to be regarded as a valid component of risk management. Overcoming the gap between a perceived risk analysis or an objective risk assessment proves to be difficult. Rohrmann (1994) states that perceived risk varies between individuals and is affected by lifestyle, age, gender, occupation and other variables. Therefore, it is seen as impossible to include perceived risk in an quantitative risk assessment (Smith & Petley, 2008). The quantitative risk assessment comprises of three parts. Firstly, there is the Hazard

probability, secondly there has to be researched what elements are at risk. Lastly, the vulnerability of the river delta has to be investigated. each part of the risk assessment will be elaborated in the following section.

What is the hazard probability of flooding in the Irrawaddy Delta?

In order to calculate the probability of a hazard the probability based approach will be used as described by Smith & Petley (2008). The probability of a hazard is based on the probability that a hazard will occur. With this information the size of floods in this case can be determined, since magnitude and frequency of a hazard are closely related (Smith & Petley, 2008). A flood that has a probability of occurring once every 100 years results often in a bigger disaster than a flood that occurs every year. With this information correct measures can be taken, like building dams that can withstand an once in a 100 year flood. The next step is using the historical data, and ranking those events. Rank one is the largest flood with the highest water level, rank two is the second largest flood and so on. When looking at cyclones it can also be ranked by wind speed. Subsequently the return period (Tr)will be calculated with the formula: Tr = (n+1)/m, where n is the number of events in the period of the record and m is the rank of the event. Then the percentage probability will be calculated by dividing 100 by Tr. With this can a plot be made that can estimate the return period for any desired flood level or visa versa. The downside of using the method is that in order to determine the probability of the flooding hazard it must be assumed that the past processes and events can give an accurate representation of the future. This method also requires a correct database.

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What are the elements at risk?

The valuation elements at risk is a function if the value of the environment itself multiplied with the fraction of elements in the environment that are threatened to be lost by flood. The valuation of the elements at risk is actually a form of risk assessment in monetary units and the equation can be simplified to probability(p) * loss (L) (Smith & Petley, 2013). According to Smith & Petley (2013) the elements at risk in case of flooding are divided in primary and secondary elements. Primary elements of risk being deaths and diseases causing direct harm. The infrastructure and agriculture are

secondary elements and can harm the population on the long term.

The most effective way to determine the elements at risk is by monetary units (Meyer, Scheuer & Haase, 2009). This however becomes problematic when assessing primary elements at risk, for it is ethically challenging to put a value on human lives. Another way of determining the elements at risk is by a Multiple Criteria Analysis (MCA). Meyer, Scheuer & Haase (2009) made such an approach, capable of integrating the economical, environmental and social factors. The

identification of elements at risk is the most determining factor in this approach. As the identification of elements is location specific, the elements in this proposal will be based on previous events. This approach also requires a definition of risk for each of these aforementioned elements, a certain threshold value that, when surpassed will determine the element as being at risk.

The downside of using an MCA in comparison to monetary units is the information it provides for future research or decision making. The MCA provides information about the area’s prone to flooding, while monetary units give information about the damage that is done by flooding expressed in values that are more commonly understood. Thus to determine the value of the elements at risk required for our risk assessment, a monetary expression is prefered.

What is the vulnerability of the Irrawaddy delta?

Following the Vulnerability-Resilience Indicators Model (VRIM), socio-ecological sensitivity and resilience to flooding in the Irrawaddy river delta will be assessed. This method comprises of five sectors of sensitivity to flooding, and three sectors of coping capability that measure the resilience of the irrawaddy river delta to flooding. The five sectors of sensitivity are; settlement and infrastructure sensitivity, food security, ecosystem sensitivity, human health sensitivity and water resource sensitivity. The three sectors of coping capacity are; economic capacity, human and civic resources and environmental capacity. Indicators are aggregated and serve as proxies for their sectors. (Ibarrán et Al., 2008). The eight sectors have 18 indicators in total. Ibarrán et Al. (2008) states that the

selection of sectors and variables is based on a wide-ranged literature review and includes variables that can be measured, even though other more qualitative aspects are explicitly left out due to measurement issues or to a lack of a clear variable to represent specific concepts. Hence why a large dataset needs to be available for the use of the VRIM model. After gathering the data the ranges of data will be normalized. Subsequently the means of each sector will be computed. This makes the data comparable to other regions and countries by using comparative measurement (Brenkert and Malone, 2005). Measuring the vulnerability is a key part in a risk assessment as it shows what the strong and weak points are in relationship to the risk (Smith & Petley, 2008). The reason VRIM is useful is because it aims to compare and integrate impacts between different sectors and populations. The IPCC stated that this is an important feature that should be more integrated in impact

assessments (Watson et Al., 1996). Luers et al. (2003: 257) criticises the uses of proxy indicators to measure vulnerability, the paper states; “While the indicator approach is valuable for monitoring trends and exploring conceptual frameworks, indices are limited in their application by considerable subjectivity in the selection of variables and their relative weights, by the availability of data at various scales, and by the difficulty of testing or validating the different metrics”.

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Research problem and research questions:

It is clear that flooding in the Irrawaddy delta damages infrastructure, human lives, ecosystems and agriculture (Lone, 2017; Swe & Ando, 2016). However, no research has been done to the exact risk to these different elements in the delta. As this knowledge gap complicated the development of suitable adaptation and mitigation strategies it is important to assess this risk in the delta. Therefore, the research problem of this paper is defined as the risk of flooding for the socio-ecological system of the Irrawaddy river delta. From this research problem, the following research question has been derived: “How does flooding affect the socio-ecological system of the Irrawaddy river delta?”. This will be answered by answering the subquestions:

- What is the hazard probability of flooding in the Irrawaddy data? - What are the elements at risk?

- What is the vulnerability of the Irrawaddy delta?

The risk of flooding for the socio-ecological system of the Irrawaddy river delta is a complex problem. This can be concluded when comparing the properties of the problem with the different properties of a complex system as defined by Menken & Keestra (2016). Hereby a complex problem is described as problems occurring on different system levels, in which different factors are involved and there is no consensus about the problem definition and the most adequate way to solve the problem. One property of a complex problem that is applicable to this problem is connectivity. In this paper the socio-ecological system of the delta will be researched. This system is built up from infrastructure, human lives, ecosystems and agriculture which are four completely different parts of the system. However, these parts of the system are also interconnected as they influence each other through several feedback loops. For example, the state of the infrastructure in the delta influences the vulnerability of the other three parts of the system as better infrastructure may result in a better protecting of the socio-ecological system. Furthermore, changes in one part of the system may influence other parts of the system. For example, agriculture may influence the vulnerability of the ecosystems. In addition, this problem is nonlinear to some extent as flooding is caused by weather events and climate change. Weather events and climate change can be predicted but, there will always be a some degree of uncertainty as weather events are different every year and climate change may be reinforced or balanced by many factors. Climate change can be defined as emergent which is another property of complex systems. Moreover, robustness and resilience play an important role in this problem as ecosystems and agriculture will show robustness to flooding in a certain way and once damaged their resilience will determine part of the vulnerability of ecosystems and agriculture.

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Integration method

To integrate multiple disciplines in an interdisciplinary research, several integration techniques are available. This paper chooses to use a cross table to highlight the interconnections between the three disciplines, this table can be seen in figure 1. Other methods like the triangulation method and the scenario study are not suitable for this research. The triangulation method combines several methods to study one topic. This paper uses mostly literature research, in-depth or quantitative interviews will not be used. This makes triangulation irrelevant to integrate the different disciplines. The scenario study is also not optimal for this paper. In this method four scenarios will be made based on the outcomes of two variables. The scenario study could be implemented in the risk assessment because assumptions are made to get to the outcome of the risk. Different scenarios could give an overview of other outcomes of the risk assessment with the use of different assumptions. Even though this could be useful, this makes the risk assessment much more extensive, and not feasible within this course. This paper uses a risk assessment to integrate the different disciplines, and a cross table to highlight the interconnections between the different parts of the risk assessment. A schematic overview of the risk assessment can be seen in figure 2.

Methodology

This research will be conducted using secondary data as the timeframe and resources of the research do not allow for primary data to be collected in the Irrawaddy river delta. In addition, collecting primary data would not be necessary since much secondary data is already available. This secondary data is used because large data samples of the area are available which are needed in this research and can hardly be gathered in this research.

The information needed to calculate the hazard probability comes from historical data. The historical data of the hazards will be gathered from websites such as GDACS (Global Disaster Alert and Coordinate System), JAXA tropical cyclone database and the JPL Tropical Cyclone Information System. With this information a database will be made of the hazards and will subsequently be ranked. Using a combination of these sites should be enough to make a correct database on which a risk assessment could be made. It must be noted that the events in the database are drawn from the same statistical population and are independent.

The elements at risk consist of primary and secondary elements at risk. The primary elements are human deaths and diseases, the secondary elements are infrastructure, agriculture and

environment. As discussed in the theoretical framework, these elements must be expressed in monetary terms. This proves to be difficult for the primary elements, as these are not easily expressed in economic value. the question of how much a human life is worth cannot be answered in this paper. Due to the subjectivity of the loss of value per diseased person or death, these are not taken into account in this research.

The risk of flooding on infrastructure can be measured by the depth and velocity of the water (Smith & Petley, 2008). Water flowing at a speed of 2 meter per second and a depth of 0.5 meter can cause buildings and obstructions to fail. Below this depth and velocity cars and people can be washed away, but no direct damage to infrastructure is done. Hence why this paper takes a water flow of 2 meter per second and flooding depth of 0.5 meter as the threshold value for causing damage to infrastructure. The damage to infrastructure can be measured easily in monetary terms.

Reduced rice yield has a big impact on the population, in 1995 48.3% of the average population’s daily calorie intake consisted of rice (Kyaw & Routray, 2006). The salt sea water which floods the land is disastrous for the cultivation of rice. The rice yield will reduce due to the salinization, for it delays and reduces heading, along with growing processes in the plant and pollen viability of which being the most important for yield (Reddy et. al., 2017). Floodwater with a conductivity of 2dS/m decreases the rice yield up to 1t/hm2 (Reddy et al., 2017). To determine the worth of the elements at

risk, the worth of such a ricefield combined with the magnitude of the flood will then express the risk in monetary units. This method is particularly easy applicable on the loss of agricultural services for the amount of food loss is predictable and the food has an established worth. For environmental services

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however, this method does not apply in such a way as it consists of different services. To assess the value of these services it is important differentiate between these services. We can divide ecosystem services in four forms, provisioning, regulating, supporting and recreational services (Dempsey, Robertson, 2012). The provisioning value of ecosystems primarily focuses on products, acquirable form the environment such as food and medicine. The regulating and supporting value includes services such as coastal protection by mangroves, or the importance of sustained biodiversity for the ecosystem as a whole. The recreational value includes the services provided for future generations such as species extinction which can’t be undone. The Economics of Environment and Biodiversity (TEEB) project provides a way to express these services in monetary units (van der Ploeg & de Groot, 2010). The damage done to the environment and the effects on different aspects of the ecosystems by flooding need to be researched. The effects need to be multiplied by the value of such floods to express the risk in monetary units.

For the Vulnerability-Resilience Indicators Model (VRIM) most of the information will be included from the national population census and administrative data of organisations such as The World Bank, Myanmar’s government websites such as websites of the Ministry of Agriculture, Livestock and Irrigation and the Ministry of Natural Resources and Environmental Conservation, and the FAO. This is sufficient because most of the data needed in the VRIM model are measurable entities for the river delta that are already available. Examples of this is the population that is at risk from flooding in the delta, the protein consumption per capita, use of fertilizer, life expectancy, precipitation, GDP per capita, literacy and population density. 18 of these indicators will measure the vulnerability in a region as they represent characteristics relevant to human well being and can all be found in secondary data (Ibarrán et Al., 2008).

Conclusion and anticipated results

In conclusion of this research proposal, an interdisciplinary approach for a risk assessment has been conducted to answer the research question, “How does flooding affect the socio-ecological system of the Irrawaddy river delta?”. With the combination of hazard probability, elements at risk and

vulnerability a risk assessment has been made. The Irrawaddy delta is already affected by flooding. If flooding will occur more frequently and with a larger magnitude it is likely that more damage will be done to the elements at risk. Therefore, it is likely that the outcome of this research paper will be that the Irrawaddy Delta region is at high risk to flooding and action has to be taken to protect the delta against these floods to reduce damage. The resilience to flooding will most likely decrease in the future. Therefore, it is vital to take action in order to reduce the socio-ecological problems that will occur.

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Brenkert, Antoinette L., and Elizabeth L. Malone (2005), “Modeling Vulnerability and Resilience to Climate Change: A Case Study of India and Indian States”, Climatic Change 72, 57-102.

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Biology, 44(4), 581-594

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practice. Amsterdam University Press.

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Modeling and Data Assimilation Techniques for Tropical Cyclone Prediction (pp. 561-587).

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https://earthobservatory.nasa.gov/IOTD/view.php?id=8767 [Accessed 28 sep. 2017]. Rohrmann, B. (1994) Risk perception of different societal groups: Australian findings and crossnational comparisons. Australian Journal of Psychology 46: 150–63.

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Appendix

Data management Table

Theory Concept Underlying Assumptions

Insights to the problem

Hazard Probability

Hazard Probability is a theory that uses a formula to predict the probability of a hazard to occur. Hazard Probability measurements described techniques as described by Smith & Petley (2008)

Measures the probability of a risk, which is an integral part of a quantitative risk

assessment.

Climate Change

Climate change is a change in the usual weather patterns in an area. This can have a natural cause or an anthropogenic cause.

Uncertainty in the climate change models. The future events are not completely

predictable. So, it is based on not fully accurate models and scenario’s.

Gives an insight in the future magnitude and frequency of floods in the Irrawaddy Delta region.

Cyclone formation

A tropical cyclone is a rotating cloud formation that forms under six conditions (Montgomery, 2016).

The Assumptions of cyclone formation are based on the

information that is now available.

Unfortunately,

scientists do not have a full understanding of this process

(Montgomery, 2016).

Shows the possibility of forming a cyclone in the Indian ocean and therefore adds to the hazard

probability in the risk assessment.

Socio-ecological systems

SES: “All humanly used resources are

embedded in complex, social-ecological systems (SESs). SESs are composed of multiple subsystems and internal variables within these subsystems at multiple levels

The definition of what a socio-ecological system is inherently stays the same

The four core subsystems are resource systems, resource units, governance systems and users. Together they interact and produce outcomes on an SES level. (Ostrom, 2009)

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analogous to organisms composed of organs, organs of tissues, tissues of cells, cells of proteins” (Ostrom, 2009,1)

Risk

assessment Quantitative risk assessment: This method calculates the risk of flooding by multiplying the Hazard probability with the Elements at risk and the Vulnerability. (Krewski et al., 1982)

Non-quantifiable information such as variation to exposure of a risk are left out because they cannot be defined.

Method is flawed because it ignores the perceived risk. Kasperson et Al. (1988). Perceived risk varies between individuals and is affected by lifestyle, age, gender, occupation and other variables. Therefore, it is impossible to include perceived risk in a

quantitative risk assessment (Smith & Petley, 2008; Rohrmann 1994) Elements at

risk Smith & Petley (2008) divide Elements at risk between primary and secondary elements. Primary elements of risk being deaths and diseases causing direct harm. The infrastructure, environment and agriculture are

secondary elements and can harm the population on the long term.

Assessing the deaths and environmental elements at risk is impossible in monetary terms, as intrinsic value of these cannot be measured in money

Measuring risks with a Multiple-Criteria Analysis (MCA) is difficult. The identification of elements at risk is the most determining factor in this approach. As the identification of elements is location specific, the elements in this proposal will be based on previous events. This approach also requires a definition of risk for each of these elements, a certain threshold value that, when surpassed will determine the element as being at risk. (Meyer, Scheuer & Haase, 2009) Vulnerability vulnerability is often

defined as the function of exposure, sensitivity, adaptive capacity, manifested within the interactions of social and ecological systems”. (Luers et al.,2003: 256)

the selection of sectors and variables is based on a wide-ranged literature review and includes variables that can be measured, even though other more qualitative aspects are explicitly left out due to measurement issues or to a lack of a clear variable to represent specific concepts. (Ibarrán, 2008)

“While the indicator approach is valuable for monitoring trends and exploring conceptual frameworks, indices are limited in their application by considerable subjectivity in the selection of variables and their relative weights, by the availability of data at various scales, and by the difficulty of testing or validating the different metrics”. (Luers et al., 2003:257)

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understanding and valuation of ecosystems world wild and ability to determine the long term sustainable value. provide regulating and supporting services which benefit society. By destruction of these services in any way these services get lost. These services are measurable and the cost of replacing these services can be determined. As the services provided are present over a long period of time, this needs to be accounted for too. Often, the value of an ecosystem as a whole is provided. This could be a problem in the assessment of the elements at risk for this might not be the entire ecosystem. To determine the value of the elements at risk, the value of the elements at risk must be derived from the risk and the value of the ecosystem.

put a value on ecosystem services and this value is suitable for risk assessment and can help in future decision making. purpose of this paper is to present a way to evaluate a ecosystem’s supporting and regulating services, the MCA would be less sufficient than making use of the TEEB to construct a quantitative risk assessment as available in Smith (2013). For future research it would be of importance to assess a standardized ecosystem damage framework that can be used to combine the magnitude of floods with the damage being done to the ecosystem.

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Appendix

Earth Sciences Biology Human Geography Earth Sciences X The resilience of

ecosystems against coastal flooding.

Looking at the economic capability to determine the ability of prevent floods and dealing with flood damage.

Biology Floods leading to salinization causing a reduced agricultural yield and impacting mangrove forests.

X Fisheries depending

on freshwater bodies which are vulnerable to flooding.

Human Geography Floods leading to infrastructural damage, which must be measured in economic terms.

Reduced agricultural yield leading to changes in vulnerability (food security) for the people.

X

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