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Scalar Politics in Flood Risk Management and Community Engagement  

Thomas Thaler

Recent extreme hydrological events (e.g., in the United States in 2005 or 2012, Pakistan in 2010, and Thailand in 2011) revealed increasing flood risks due to climate and societal change. Consequently, the roles of multiple stakeholders in flood risk management have transformed significantly. A central aspect here is the question of sharing responsibilities among global, national, regional, and local stakeholders in organizing flood risk management of all kinds. This new policy agenda of sharing responsibilities strives to delegate responsibilities and costs from the central government to local authorities, and from public administration to private citizens. The main reasons for this decentralization are that local authorities can deal more efficiently with public administration tasks concerned with risks and emergency management. Resulting locally based strategies for risk reduction are expected to tighten the feedback loops between complex environmental dynamics and human decision-making processes. However, there are a series of consequences to this rescaling process in flood risk management, regarding the development of new governance structures and institutions, like resilience teams or flood action groups in the United Kingdom. Additionally, downscaling to local-level tasks without additional resources is particularly challenging. This development has tightened further with fiscal and administrative cuts around the world resulting from the global economic crisis of 2007–2008, which tightening eventually causes budget restrictions for flood risk management. Managing local risks easily exceeds the technical and budgetary capacities of municipal institutions, and individual citizens struggle to carry the full responsibility of flood protection. To manage community engagement in flood risk management, emphasis should be given to the development of multi-level governance structures, so that multiple stakeholders share fairly the power, resources, and responsibility in disaster planning. If we fail to do so, some consequences would be: (1), “hollowing out” the government, including the downscaling of the responsibility towards local stakeholders; and (2), inability of the government to deal with the new tasks due to lack of resources transferred to local authorities.


Executive and Legislative Competition Over Natural Hazards Policies  

Deserai A. Crow

As with countless other policy areas, natural hazard policy can be viewed as a jurisdictional competition between executive and legislative branches. While policymaking supremacy is delegated to the legislative branch in constitutional democracies, the power over implementation, budgeting, and grant-making that executive agencies enjoy means that the executive branch wields considerable influence over outcomes in natural hazards policymaking. The rules that govern federal implementation of complex legislative policies put the implementing agency at the center of influence over how policy priorities play out in local, county, and state processes before, during, and after disasters hit. Examples abound related to this give-and-take between the legislative and executive functions of government within the hazards and disaster realm, but none more telling than the changes made to US disaster policy after September 11th, which profoundly affected natural hazards policy as well as security policy. The competition and potential for mismatch between legislative and executive priorities has been heightened since the Federal Emergency Management Agency (FEMA) was reorganized under the Department of Homeland Security. While this may appear uniquely American, the primacy of terrorism and other security-related threats not only dwarfs natural hazards issues in the United States, but also globally. Among the most professionalized and powerful natural hazards and disaster agencies prior to 9/11, FEMA has seen its influence diminished and its access to decision-makers reduced. This picture of legislative and executive actors within the natural hazards policy domain who compete for supremacy goes beyond the role of FEMA and post-9/11 policy. Power dynamics associated with budgets, oversight and accountability, and relative power among executive agencies are ongoing issues important to understanding the competition for policy influence as natural hazards policy competes for attention, funding, and power within the broader domain of all-hazards policy.


Scaling Theory of Floods for Developing a Physical Basis of Statistical Flood Frequency Relations  

Vijay Gupta

Prediction of floods at locations where no streamflow data exist is a global issue because most of the countries involved don’t have adequate streamflow records. The United States Geological Survey developed the regional flood frequency (RFF) analysis to predict annual peak flow quantiles, for example, the 100-year flood, in ungauged basins. RFF equations are pure statistical characterizations that use historical streamflow records and the concept of “homogeneous regions.” To supplement the accuracy of flood quantile estimates due to limited record lengths, a physical solution is required. It is further reinforced by the need to predict potential impacts of a changing hydro-climate system on flood frequencies. A nonlinear geophysical theory of floods, or a scaling theory for short, focused on river basins and abandoned the “homogeneous regions” concept in order to incorporate flood producing physical processes. Self-similarity in channel networks plays a foundational role in understanding the observed scaling, or power law relations, between peak flows and drainage areas. Scaling theory of floods offers a unified framework to predict floods in rainfall-runoff (RF-RO) events and in annual peak flow quantiles in ungauged basins. Theoretical research in the course of time clarified several key ideas: (1) to understand scaling in annual peak flow quantiles in terms of physical processes, it was necessary to consider scaling in individual RF-RO events; (2) a unique partitioning of a drainage basin into hillslopes and channel links is necessary; (3) a continuity equation in terms of link storage and discharge was developed for a link-hillslope pair (to complete the mathematical specification, another equation for a channel link involving storage and discharge can be written that gives the continuity equation in terms of discharge); (4) the self-similarity in channel networks plays a pivotal role in solving the continuity equation, which produces scaling in peak flows as drainage area goes to infinity (scaling is an emergent property that was shown to hold for an idealized case study); (5) a theory of hydraulic-geometry in channel networks is summarized; and (6) highlights of a theory of biological diversity in riparian vegetation along a network are given. The first observational study in the Goodwin Creek Experimental Watershed, Mississippi, discovered that the scaling slopes and intercepts vary from one RF-RO event to the next. Subsequently, diagnostic studies of this variability showed that it is a reflection of variability in the flood-producing mechanisms. It has led to developing a model that links the scaling in RF-RO events with the annual peak flow quantiles featured here. Rainfall-runoff models in engineering practice use a variety of techniques to calibrate their parameters using observed streamflow hydrographs. In ungagged basins, streamflow data are not available, and in a changing climate, the reliability of historic data becomes questionable, so calibration of parameters is not a viable option. Recent progress on developing a suitable theoretical framework to test RF-RO model parameterizations without calibration is briefly reviewed. Contributions to generalizing the scaling theory of floods to medium and large river basins spanning different climates are reviewed. Two studies that have focused on understanding floods at the scale of the entire planet Earth are cited. Finally, two case studies on the innovative applications of the scaling framework to practical hydrologic engineering problems are highlighted. They include real-time flood forecasting and the effect of spatially distributed small dams in a river network on real-time flood forecasting.


Vulnerability as Concept, Model, Metric, and Tool  

Benjamin Wisner

Vulnerability is complex because it involves many characteristics of people and groups that expose them to harm and limit their ability to anticipate, cope with, and recover from harm. The subject is also complex because workers in many disciplines such as public health, psychology, geography, and development studies (among others) have different ways of defining, measuring, and assessing vulnerability. Some of these practitioners focus on the short-term identification of vulnerability, so that maps and lists of people living “at risk” can be generated and used by authorities. Others are more concerned with reasons why some people are more vulnerable when facing a hazard or threat than others. Professionals working at the scale of localities are interested in methods that bring out residents’ own knowledge of hazards and help them to cooperate with each other to find ways of reducing risk. There are some interpretations of vulnerability that seek its root cause in the creation of risk by political and economic systems that make investment and locational decisions for the benefit of small elites without regard for how these decisions affect the majority. Finally, whatever success there may be in treating vulnerability in any of the ways just mentioned, it will always be a part of the human condition, and this fact in itself is puzzling.


Corruption and the Governance of Disaster Risk  

David Alexander

This article considers how corruption affects the management of disaster mitigation, relief, and recovery. Corruption is a very serious and pervasive issue that affects all countries and many operations related to disasters, yet it has not been studied to the degree that it merits. This is because it is difficult to define, hard to measure and difficult to separate from other issues, such as excessive political influence and economic mismanagement. Not all corruption is illegal, and not all of that which is against the law is vigorously pursued by law enforcement. In essence, corruption subverts public resources for private gain, to the damage of the body politic and people at large. It is often associated with political violence and authoritarianism and is a highly exploitative phenomenon. Corruption knows no boundaries of social class or economic status. It tends to be greatest where there are strong juxtapositions of extreme wealth and poverty. Corruption is intimately bound up with the armaments trade. The relationship between arms supply and humanitarian assistance and support for democracy is complex and difficult to decipher. So is the relationship between disasters and organized crime. In both cases, disasters are seen as opportunities for corruption and potentially massive gains, achieved amid the fear, suffering, and disruption of the aftermath. In humanitarian emergencies, black markets can thrive, which, although they support people by providing basic incomes, do nothing to reduce disaster risk. In counties in which the informal sector is very large, there are few, and perhaps insufficient, controls on corruption in business and economic affairs. Corruption is a major factor in weakening efforts to bring the problem of disasters under control. The solution is to reduce its impact by ensuring that transactions connected with disasters are transparent, ethically justifiable, and in line with what the affected population wants and needs. In this respect, the phenomenon is bound up with fundamental human rights. Denial or restriction of such rights can reduce a person’s access to information and freedom to act in favor of disaster reduction. Corruption can exacerbate such situations. Yet disasters often reveal the effects of corruption, for example, in the collapse of buildings that were not built to established safety codes.


Intersectionality as a Forward-Thinking Approach in Disaster Research  

Cassandra Jean, Tilly E. Hall, and Jamie Vickery

Disaster researchers, policymakers, and practitioners are confronted with the pressing need to understand and address how and why certain individuals and groups of individuals experience inequities leading up to, during, and postdisaster. These efforts must consider how to address such inequities through collaborative efforts toward intentional and systemic change. The use of intersectional approaches supports better analyze and critique of discriminatory and oppressive practices that disproportionately impact historically marginalized peoples, especially in the face of hazards and disasters. Intersectionality calls for understanding how different forms of privilege, power, and oppression interact and compound to create unequal socioeconomic outcomes across individuals and groups of individuals based on their identities (e.g., age, race, sexuality, and gender) and conditions (e.g., housing composition, immigration, and marital status). A review of inter- and multidisciplinary terrains of disaster studies shows that there are multifaceted utilities, capabilities, and advantages of adopting an intersectional approach. By considering historical discriminatory practices and the root causes of vulnerability, intersectionality highlights the systemic and institutionalized patterns that create precarious situations for some people while simultaneously protecting others. Intersectionality is also well suited to support insight into individuals’ capacities that affect their ability to prepare for, respond to, and recover from disastrous events, as well as assist them in avoiding or reducing risks that make them susceptible to disaster in the first place. However, intersectional approaches within disaster studies remain underutilized and, sometimes, superficially applied. Simplistic representations, the unequal attention given to certain intersections, and the domination of Western epistemologies must be attended to in order to challenge, disrupt, and diligently undo the interactions of systematic privilege, power, and oppression that render unequal disaster experiences and outcomes.


Earthquakes in Political, Economic, and Cultural History  

Andrew Robinson

The immediate aftermath of a great urban earthquake is a dramatic and terrible event, comparable to a massive terrorist attack. Yet the shocking impact soon fades from the public mind and receives surprisingly little attention from historians, unlike wars and human atrocities. In 1923, the Great Kanto earthquake and its subsequent fires demolished most of Tokyo and Yokohama and killed around 140,000 Japanese: a level of devastation and fatalities comparable with the atomic bombing of Hiroshima and Nagasaki in 1945. But the second event has infinitely more resonance in public consciousness and historical studies than the first. Indeed, most people would be challenged to name a single earthquake with an indisputable historical impact, including even the most famous of all earthquakes: the San Francisco earthquake and fire of 1906. In truth, however, great earthquakes, from ancient times—as recorded by Greek and biblical writers—to the present day, have had major cultural, economic, and political consequences—often a combination of all three—some of which were beneficial. Thus, the current prime minister of India owes his election in 2014 to an earthquake that devastated part of his home state of Gujarat in 2001, which led to its striking economic growth. The martial law imposed on Tokyo and Yokohama after the 1923 earthquake gave new authority to the Japanese army, which eventually took over the Japanese government and led Japan to war with China and the world. The destruction of San Francisco in 1906 produced a boom in rebuilding and financial and technological development of the surrounding area on the San Andreas Fault, including what became Silicon Valley. A great earthquake in Venezuela in 1812 was the principal cause of the temporary defeat of its leader Simon Bolivar by the Spanish colonial regime, but his subsequent exile led to his permanent freeing of Bolivia, Colombia, Ecuador, Peru, and Venezuela from Spanish rule. The catastrophic Lisbon earthquake of 1755—as well known in the early 19th century as the 1945 atomic bombings are today—was a pivotal factor in the freeing of Enlightenment science from Catholic religious orthodoxy, as epitomized by Voltaire’s satirical novel Candide, written in response to the earthquake. Even the minor earthquakes in Britain in 1750, the so-called Year of Earthquakes, produced the earliest scientific understanding of earthquakes, published by the Royal Society: the beginning of seismology. The long-term impact of a great earthquake depends on its epicenter, magnitude, and timing—and also on human factors: the political, social, intellectual, religious, and cultural resources specific to a region’s history. Each earthquake-struck society offers its own particular lesson, and yet, taken together, such earth-shattering events have important shared consequences for the history of the world.


Modeling Power Outage Risk From Natural Hazards  

Seth Guikema and Roshanak Nateghi

Natural disasters can have significant widespread impacts on society, and they often lead to loss of electric power for a large number of customers in the most heavily impacted areas. In the United States, severe weather and climate events have been the leading cause of major outages (i.e., more than 50,000 customers affected), leading to significant socioeconomic losses. Natural disaster impacts can be modeled and probabilistically predicted prior to the occurrence of the extreme event, although the accuracy of the predictive models will vary across different types of disasters. These predictions can help utilities plan for and respond to extreme weather and climate events, helping them better balance the costs of disaster responses with the need to restore power quickly. This, in turn, helps society recover from natural disasters such as storms, hurricanes, and earthquakes more efficiently. Modern Bayesian methods may provide an avenue to further improve the prediction of extreme event impacts by allowing first-principles structural reliability models to be integrated with field-observed failure data. Climate change and climate nonstationarity pose challenges for natural hazards risk assessment, especially for hydrometeorological hazards such as tropical cyclones and floods, although the link between these types of hazards and climate change remains highly uncertain and the topic of many research efforts. A sensitivity-based approach can be taken to understand the potential impacts of climate change-induced alterations in natural hazards such as hurricanes. This approach gives an estimate of the impacts of different potential changes in hazard characteristics, such as hurricane frequency, intensity, and landfall location, on the power system, should they occur. Further research is needed to better understand and probabilistically characterize the relationship between climate change and hurricane intensity, frequency, and landfall location, and to extend the framework to other types of hydroclimatological events. Underlying the reliability of power systems in the United States is a diverse set of regulations, policies, and rules governing electric power system reliability. An overview of these regulations and the challenges associated with current U.S. regulatory structure is provided. Specifically, high-impact, low-frequency events such as hurricanes are handled differently in the regulatory structure; there is a lack of consistency between bulk power and the distribution system in terms of how their reliability is regulated. Moreover, the definition of reliability used by the North American Reliability Corporation (NERC) is at odds with generally accepted definitions of reliability in the broader reliability engineering community. Improvements in the regulatory structure may have substantial benefit to power system customers, though changes are difficult to realize. Overall, broader implications are raised for modeling other types of natural hazards. Some of the key takeaway messages are the following: (1) the impacts natural hazard on infrastructure can be modeled with reasonable accuracy given sufficient data and modern risk analysis methods; (2) there are substantial data on the impacts of some types of natural hazards on infrastructure; and (3) appropriate regulatory frameworks are needed to help translate modeling advances and insights into decreased impacts of natural hazards on infrastructure systems.