**Abstract**

Despite multiple challenges, floods remain the most frequently occurring hazard in Myanmar. Current developments of political instability, multidimensional insecurity, and associated economic crisis have burdened the existing vulnerabilities and inequalities of the Burmese people and their ecosystems. Diminishing adaptive capacities of degraded ecosystems, poor infrastructure, and extreme poverty, together with major livelihood dependency on climate-sensitive agriculture, will further increase flood risk. Moreover, other hazards such as COVID-19, heatwaves, and droughts may exacerbate flood impacts leading to compound disasters. Understanding how and which factors drive flood risk, and where they distribute are important to reduce flood risk, address its root causes, and prevent future flood damages by lessening exposures, vulnerabilities, and even hazards. We aim to compare the spatial-temporal distributions between dynamic pressures and flood risk, and identify the spatial relations on a national scale and within floodplains. We draw on socio-ecological risk assessment, systematic review, time-series analysis and modified t-test after testing spatial autocorrelations of dynamic pressures and flood risk. Our results show that many socioecological dynamic pressures driven by economic- and governance-related root causes had positive spatial relationships with flood risks. We recommend effective land use and environmental governance that consider compound and cascaded flood risk and investment in public services and infrastructure such as health and education to reduce vulnerabilities and increase resilience of Myanmar people.

**Keywords:** flood, risk, exposure, vulnerability, Myanmar, dynamic pressures, root causes, spatial-temporal relations, socio-ecological systems

### **1. Introduction**

The disproportionate rise in climate-related impacts, and losses and damage in countries of the Global South may attribute to differences in vulnerability to those climate and disaster impacts. Yet, the issue is treating disasters separately from their underlying root-causes in their disaster- and climate-related management and adaptation practices, especially in those vulnerable countries. For example, climate change adaptation through nature-based solutions is not possible without addressing root

causes of deforestation and forest degradation in those nations. There is a clear call for transformative change in dealing with vulnerabilities in those countries.

Disaster risk and impacts are increasingly becoming the products of more compound and complex causal mechanisms in today's interconnected world. Explanation of disaster risk needs to trace connections that join disaster impacts with a sequence of causal factors and processes. Cascading impacts are chains of disruptive disaster impacts on systems at different scales [1, 2]. This systemic nature of risk can be seen in the examples of the COVID-19 pandemic [3–6]. In other words, a disaster at the same time can be a driving factor to cause a larger and more calamitous compound disaster. This type of compound disaster can be especially worse in the incidence of social, economic, financial, health, and political crises, which are outside of the climate and disaster risk framing.

Here, root causes are defined as "an interrelated set of widespread and general processes within a society and the world economy" [7]. They are economic, demographic, and political processes that affect the distribution and allocation of resources among different social groups. Those causal mechanisms are spatially and temporally distant from those disastrous situations (unsafe conditions of vulnerability) to be clearly understandable at a glance [7–9]. They are usually "invisible" and "taken for granted" as they are embedded in socio-cultural beliefs and assumptions. For example, inadequate natural resource governance that leads to inequalities and deforestation, which in turn increases flood risk, cannot easily be mapped or easily visible as a causal factor. Therefore, they are difficult to express spatially and temporally. As a result, those root causes cannot be easily incorporated into the disaster risk management.

Therefore, it is essential to understand the spatial and temporal relations of risk drivers (root causes) and the places where risk occurs. Dynamic pressures are "processes and activities that translate the effects of root causes both temporally and spatially into unsafe conditions" [7]. Therefore, these pressures can be visualized over space and trends. In this chapter, we will explain spatial-temporal relations of dynamic pressures exercised by root causes and disaster risk using case study of Myanmar.

Myanmar provides a comprehensive case study to understand compound cascading risk driven by the interaction of deepened root causes. Myanmar has been experiencing multiple exogenous compound stressors and endogenous dynamic pressures driven by several root causes currently and dynamically over history. Myanmar is one of the countries, which is mostly affected by and is highly vulnerable to extreme climate events, according to GAR Report, Inform Risk Index 2017, and Global Climate Risk Index 2021 [10–12]. Given consistent inadequate governance, the dependency of Myanmar's economy on resource extraction and agriculture left Myanmar's forests, land, water, and environment in a seriously degraded condition [13–15]. This inadequate governance also deepens socioeconomic and class inequalities [13–15]. The fact that the majority of populations depend on their livelihoods in those degraded ecosystems and climate sensitive sectors results in limited capacities to cope and adapt to extreme climate events due to the degraded ecosystems. Long history of conflicts and the current development of political instabilities render already poor Myanmar population to face multidimensional insecurities and inequalities including food, job, and safety, to name a few [15, 16]. These recent developments disrupted humanitarian assistance, international development aid, food production, environmental management, and climate actions, resulting in conditions which can be extremely catastrophic in the face of extreme disasters [16]. Considering the increasing impacts of

climate change in the near future, those extreme disasters are likely to occur. Public services and infrastructure, such as education and health services, have received little priority and attention for investment in their development, which is now seriously disrupted due to the recent changes [15]. Last COVID-19 incidences and associated vast mortalities due to shortages in oxygen supplies and health facilities prove weakening health infrastructure. The associated economic and financial crisis put additional millions of Burmese people into poverty. Social security systems and climate insurance development are yet in the very early stage of development to support recovery from disasters and climate impacts and for the risk transfer [17]. Official Development Assistance from outside Myanmar can be difficult due to the ethical challenges, safety, and entry issues [17]. Therefore, in case of any disasters, already vulnerable Myanmar people can be helpless, seeing the examples of 2008 Nargis Cyclone.

Despite those multiple challenges in Myanmar, flood remains the most frequent and has the highest contribution to average annual loss compared to all other hazards in the country [18]. Winseminus et al. (2016) estimated that 1.24 billion out of 1.81 billion population exposed to 1 in 100-year floods live-in South East Asia [19]. In 2015, a riverine flood resulted in over US\$1 billion in damages, affected over 1.6 million people, and caused at least 149 deaths [20]. With climate change, Myanmar is likely to continue to experience river flood events at the scale of the 2015 floods or worse [21]. In Myanmar, some river flooding occurs almost every year during the monsoon season and communities now rely on these floods for nutrient deposition in their agricultural fields [22]. Communities have learnt to cope with and have adapted to these annual floods, harnessing their value [22]. However, as demonstrated by the impact of the 2015 flood, which was characterized to be of a 20–50-year return period [23], Myanmar has little capacity to cope and adapt with major flood events alone given the overlapping effects of different pressures.

Transformational risk reduction and adaptation require addressing root causes of flood risk to reduce its vulnerabilities and increase resilience. If only symptoms are addressed and root causes are not considered in the risk management, those root causes will be intensified in the future, enhancing compound pressures in a climatechanging world. The Sendai Framework for Disaster Risk Reduction calls for disaster risk management that considers all dimensions of disaster risk, including hazard, exposure, and vulnerability. To reduce flood risk, decision makers and stakeholders must have a holistic understanding of the underlying factors.

Studies have focused only on drivers that drive individual components of risk and any of the assessments have barely explored risk drivers that contribute all components of risk [24]. Unlike the Pressure and Release (PAR) model, this chapter will consider that root causes and dynamic pressures will not only lead to the vulnerabilities of the people, but they can also lead to all components of risks which are hazard, exposure, and vulnerability of socio-ecological systems.

Several studies attempted to understand drivers of flood risk. Flood risk was assumed to be caused by various factors: including physical factors such as river levees and river incision [25], climate-related factors such as Climate variations associated with Oscillations such as Pacific Decadal Oscillation (PDO) and El Niño Southern Oscillation (ENSO) [26], sea level rise [24, 27] and storm surges, typhoons and cyclones [24], social factors such as urbanization [24, 25, 28, 29], soil sealing [27], poverty, and limited education [28], environmental factors such as land use changes and deforestation [24], degraded wetlands and decreased drainage capacities [30], land subsidence [24, 27], governance-related factors such as failures of top-down

approaches in flood risk management, lack of risk communications, lack of local information, limited citizen involvement in flood risk management [31], and subjective factors such as risk perceptions in shaping flood risk in terms of developing insurance-based flood management and risk transfer [32]. Abbas and Routray (2014) identified exposure to vectors, inaccessibility, damaged, and non-operated health care facilities as major factors of flood-induced health risks [33]. Assessments have likely prioritized physical and environmental risk drivers over social, economic, and governance-related drivers [24].

However, spatial-temporal relations of disaster risk and driving factors were rarely explored. A few studies investigated spatial-temporal relations of flood-related losses and damages and their influencing factors [34, 35]. However, those studies have a focus on the hazard and impacts part with limited vulnerability considerations in assessing the spatial-temporal distribution of disaster risk. We will aim to fill this gap by exploring spatial-temporal relations of dynamic pressures and flood risk that is considered as a function of hazards, exposure, and vulnerability, driven by dynamic pressures and root causes. There are three main objectives of the chapter. First, this chapter will investigate root causes and driving pressures of flood risk in Myanmar, considering potential compound and cascading risk, while the focus is on the flood risk. The spatial and temporal evolutions of dynamic pressures in relation to flood plain areas will be assessed. Second, this analysis will show the spatial distribution of flood risk based on the IPCC framing of risk [36]. Third, spatial relations of dynamic pressures and flood risk will be examined. Understanding the spatial and temporal relations of dynamic pressures (that translate from root causes to unsafe conditions of flood vulnerability) and flood risk can be used for transformative change to effective flood risk reduction.
