Infrastructure systems around the world face immediate crises and smoldering long-term challenges. Consequently, system owners and managers must balance the need to repair and replace the aging and deteriorating systems already in place against the need for transformative investments in deep decarbonization, climate adaptation, and transportation that will enable long-term competitiveness. Complicating these decisions are deep uncertainties, finite resources, and competing objectives. These challenges motivate the integration of “hard” investments in physical infrastructure with “soft” instruments like insurance, land use policy, and ecosystem restoration that can improve service, shrink costs, scale up or down as future needs require, and reduce vulnerability to population loss and economic contraction. A critical advantage of soft instruments is that they enable planners to adjust, expand, or reduce them at regular intervals, unlike hard instruments which are difficult to modify once in place. As a result, soft instruments can be precisely tailored to meet near-term needs and conditions, including projections of the quasi-oscillatory, regime-like climate processes that dominate seasonal to decadal hydro-climate variability, thereby reducing the need to guess the needs and hazards of the distant future. The objective of this dissertation is to demonstrate how potentially predictable modes of structured climate variability can inform the design of soft instruments and the formulation of adaptive infrastructure system plans. Using climate information for sequential adaptation requires developing credible projections of climate variables at relevant time scales. PartI considers the drivers of river floods in large river basins, which is used throughout this dissertation as an example of a high-impact hydroclimate extreme. First, chapter 2 opens by exploring the strengths and limitations of existing methodologies, and by developing a statistical-dynamical causal chain framework within which to consider flood risk on interannual to secular time scales. Next, chapter 3 describes the physical mechanisms responsible for heavy rainfall (90th percentile exceedance)and flooding in the Lower Paraguay River Basin (LPRB), focusing on a November-February(NDJF) 2015-16 flood event that displaced over 170 000 people. This chapter shows that: 1. persistent large-scale conditions over the South American continent during NDJF 2015-16 strengthened the South American Low-Level Jet (SALLJ), bringing warm air and moisture to South East South America (SESA), and steered the jet towards the LPRB, leading to repeated heavy rainfall events and large-scale flooding; 2. while the observed El Niño event contributed to a stronger SALLJ, the Madden-JulienOscillation (MJO) and Atlantic ocean steered the jet over the LPRB; and 3. while numerical sub-seasonal to seasonal (S2S) and seasonal models projected an elevated risk of flooding consistent with the observed El Niño event, they had limited skill at lead times greater than two weeks, suggesting that improved representation of MJO and Atlantic teleconnections could improve regional forecast skill. Finally, chapter 4 shows how mechanistic understanding of the physical causal chain that leads to a particular hazard of interest – in this case heavy rainfall over a large area in the Ohio River Basin (ORB) – can inform future risks. Taking the GFDL coupled model, version 3 (CM3) as a representative general circulation model (GCM), this chapter shows that 1. the GCM simulates too many regional extreme precipitation (REP) events but under-simulates the occurrence of back to back REP days; 2. REP days show consistent large-scale climate anomalies leading up to the event; 3. indices describing these large-scale anomalies are well simulated by the GCM; and 4. a statistical model describing this causal chain and exploiting simulated large-scale in-dices from the GCM can be used to inform the future occurrence of REP days. Even the best climate projections must confront epistemic uncertainties. Part II of this dissertation explores how intrinsically flawed projections should inform sequential adaptation.First, chapter5reviews approaches for planning under uncertainty, considering the role of classical decision theory, optimization, probability, and non probabilistic approaches. Next, chapter 6 considers how different physical mechanisms impart predictability at different timescales and the implications of secular, low-frequency cyclical, and high-frequency cyclical variability for selection between instruments with long and short planning periods. In particular, this chapter builds from three assertions regarding the nature of climate risk: 1. different climate risk mitigation instruments have different project lifespans; 2. climate risk varies on many scales; and 3. the processes which dominate this risk over the planning period depend on the planning period itself. Defining M as the nominal design life of a structural or financial instrument and N as the length of the observational record (a proxy for total informational uncertainty), chapter 7 presents a series of stylized computational experiments to probe the implications of these premises. Key findings are that: 1. quasi-periodic and secular climate signals, with different identifiability and predictability, control future uncertainty and risk; 2. adaptation strategies need to consider how uncertainties in risk projections influence the success of decision pathways; and 3. stylized experiments reveal how bias and variance of climate risk projections influencerisk mitigation over a finite planning period. Chapter 7 elaborates these findings through a didactic case study of levee heightening in the Netherlands. Integrating a conceptual model of low-frequency variability with credible projections of sea level rise, chapter 7 uses dynamic programming to co-optimize hard (levee increase) and soft (insurance) instruments. Key findings are that 1. large but distant and uncertain changes (e.g., sea level rise) do not necessarily motivate immediate investment in structural risk protection; 2. soft adaptation strategies are robust to different model structures and assumptions while hard instruments perform poorly under conditions for which they were not de-signed; and 3. increasing the hypothetical predictability of near-term climate extremes significantly lowers long-term adaptation costs. Finally, part III seeks to unpack the conceptual experiments of parts I and II to inform policy and future research. Chapter 8 describes how constructive narratives about climate change can discourage climate fatalism. Instead, chapter 8 emphasizes that while climate change is and will be a critical stressor of infrastructure systems, individuals, communities, and regions have agency and can mitigate its consequences. Finally, chapter9concludes by discussing the key findings of this dissertation and exploring how future work on decision under uncertainty, technology, and earth systems science can aid the design and management of effective infrastructure services.

Indiana University-Purdue University Indianapolis (IUPUI) / The frequency and magnitude of floods in the midcontinental United States have increased in recent decades due to changing precipitation patterns as global temperatures rise. These trends pose major social and economic risks to the region, which is home to tens of millions of Americans and a global agricultural center. It is therefore critical to understand if current fluvial dynamics are within the scope of past fluvial-climate relationships, or if they represent a novel response to recent climate and land-use changes. Presented is a 1600-year-long flood frequency record for the moderately sized (~29,400 km2 watershed) White River, Indiana. Flood frequencies were determined using 14C-based sediment accumulation rates at Half Moon Pond, an oxbow lake on the lower White River’s floodplain. Comparison with regional paleoclimate data shows that White River flooding was frequent when atmospheric circulation resembled the negative mode of the Pacific-North American (PNA) teleconnection, particularly during the Medieval Climate Anomaly (950-1250 CE) and the Current Warm Period (last ~150 years). During these times, the regional climate was dominated by warm-season precipitation originating from the Gulf of Mexico. Conversely, White River flooding was less frequent during the Little Ice Age (1250-1800 CE) when cold-season precipitation from the North Pacific/Arctic dominated (+PNA-like conditions). The pre-1790 CE White River flood history was antiphased with reconstructed Ohio River flood frequencies from southern Illinois. This dynamic is consistent with discharge in small to moderate sized watersheds being sensitive to rainstorm runoff and large watersheds being sensitive to snowmelt runoff. After 1790 CE, flooding frequencies of both river systems increased to their highest levels, despite a shift to -PNA-like conditions. This change was likely due to extensive Euro-American land-clearance, which increased runoff/erosion by reducing evapotranspiration, interception, and infiltration. While the White River responded strongly to climatic conditions in the past that were similar to present conditions (-PNA-like conditions), recent land-use practices have amplified the effects of the current hydroclimate. Since a warming climate is expected to increase regional average precipitation and extreme rainfall events, and that landscape modifications have lowered surface resilience to hydroclimate events, flooding will likely become more frequent in the coming decades.

The development of the European water policy has been in a continuous improvement process during the last fifty years. The adoption of Water Framework Directive (WFD) enabled the consolidation of a fragmented policy to comprehensive approach with a focus on sustainability. The floods Directive was developed as acomplement to the WFD and promoted their integration. However, several opportunities have been identified in the implementation and in achieving integration. This paper identifies integration gaps faced by practitionersand develops an assessment framework which can be used by diverse stakeholders from policy makers to water users to understand the degree of integration in a systematic way. Indicators within the framework can shed light on the progress and optimize the development of action plans to address integration gaps and achieveefficiency gains. Although not a remedy for the complex challenges, establishing measuring systems is a first step to ensure integration of current and future directives.

Disaster risk reduction policies and practitioners alike emphasise the importance of vulnerability reduction. However, the concept of vulnerability is highly dynamic, and research still strives to understand and capture its complexity. The purpose of this study was to improve the understanding of flood vulnerability in rural disaster-prone communities in Mozambique. To explore previous experiences of floods, I conducted semi-structured interviews with local risk committee members and community members in the lower Limpopo river basin. The findings were analysed with an analytical framework consisting of the Disaster Pressure and Release (PAR) model, drawing on political ecology and the Access model. Disaster was studied as a process revealing important factors, capabilities and strains affecting peoples’ vulnerability. This paper illustrated that rural communities in the lower Limpopo river basin are vulnerable to floods in a variety of ways. The findings presented unsafe conditions such as the fragile local economy, unsafe natural resources, strained physical resources and limited access to human and social capital. Several factors deriving from political, social and economic structures were found to influence specific forms of vulnerability expressed in relation to floods. Therefore, this paper contributes to new insights of how flood vulnerability can be described and explained in Mozambique.

Abstract Flood disasters have been a challenge in Liberia for the past 15 years. The result has been hardship for residents, which has created major disruptions to social and economic services. Global warming, poor environmental conditions and weak disaster management policies among other factors are largely blamed for the floods. The conceptual framework for this study was Barton's collective stress theory and Edwards' varied response theory, which guided this exploration of how flood victims perceive the effectiveness of the Liberian government's flood disaster management strategies. A total of 25 participants were recruited for this grounded theory study. Twenty participants were victims of flooding and 5 participants were managers from government and non-governmental organizations (NGO) entities. Data were collected from open-ended semistructured interviews with the participants. Multiple sources such as individuals and group interviews, field notes were used to support the study. Data analysis utilized descriptive coding. Results suggest community and government needs include: (a) policies on zonal regulations to reduce the problem of flooded drainages, (b) funding and other support for disaster emergency management institutions, (c) decentralizing and empowering local government agencies for disaster emergency management, and (d) empowering communities themselves through funding and training to become the first line of defense when floods occur. This dissertation may support positive social change by highlighting the need for government to strengthen disaster management policies to include zoning and building permit regulations, funding for disaster emergency management institutions, and flood control.

Magister Philosophiae (Integrated Water Resource Management) / Rare-infrequent magnitude floods of shorter duration events are significant natural hazards and play a key role in shaping river channel and island geomorphology. For a given river or channel, there is a relationship between the magnitude of a flood, frequency of a flood and duration of a flood, once a flood exceeds a reach-averaged erosional threshold geomorphic change can begin to occur. Expansion of conceptual models for the response of mixed bedrock alluvial influenced dryland rivers to such floods is of increasing scientific importance. The Vaal River near Parys in the Free State Province is characterised by a variable degree of mixed bedrock-alluvial anabranching channels which divide and re-join around the islands. In this study the historical aerial images and flow data from 1938 to 2016 were used to determine the effects of flood dynamics on island geomorphology in a large mixed bedrock-alluvial anabranching river: Vaal River near Parys. The historical aerial images and flow data reveals some minor island geomorphological changes during flood of rare magnitude, infrequent and shorter duration. The highest flood in the record was the one which was found having a recurrence interval of 20-50 years. The changes observed in the mixed bedrock-alluvial anabranching river in the Vaal River near Parys, indicate some minor decrease in the island bar area during flood of rare magnitudes, infrequent and shorter duration with recurrence interval of 20-50 years. The findings in this study area also reveals that the island bars in the area of study shows some degree of stability, however for the past 78 years the islands bar have not change the position. The impact of flood dynamics on island geomorphology in a large, mixed bedrock-alluvial anabranching river is not yet researched in the area of study (Vaal River), these findings will contribute to enhanced analysis of the Vaal River, relatively the impacts of extreme floods in island and channel geomorphology.

In our region, heavy rains may occur virtually everywhere. Nowadays there are instruments to predict these events in sufficient advance, but without precise localisation, which is a problem. Present instruments for searching endangered watersheds are focused on operative evaluation of meteorological situation and actual precipitation forecast processing (nowcasting). The thesis brings quite different approach. Potentially endangered areas are detected with evaluation of long-term statistical variables (N-year discharges and rain characteristics) and properties of specific watershed. The whole issue is handled out of situation of actual danger, this attitude is so called off-line solution. The thesis describes a model based on selected artificial intelligence methods. The model forms the core of final map application. The use of model and final application is supposed to be used in area of preventive flood protection, and related investment decision-making. The model focuses on heavy rains and flash floods.

The aim of this thesis is to map an anti-flooding protection in locality Dobrá Voda near Hořice and to create suitable plan of a water retention reservoir. Retention reservoir works as a system for holding and transformation of flood wave and thus for dealing with floods. First part of this thesis covers general description of issues of floods, current legislature, anti-flooding measures and a description of flood wave transformation. Methods for determination of retention seepage of the reservoir are described in this part as well. Computer programmes (HEC-RAS, Transformwave) were used for the purpose of above mentioned determination. In the second part of this thesis the given locality is described including all the possible risks and plans of convenient anti-flooding measures. The results of appropriate software determinations are compared in this part of the thesis as well. A final plan of a suitable retention reservoir is based on the results of comparison.

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During intensive rainfall, the ground is at risk of flooding if the water has no opportunity to infiltrate into the ground or drain. Cities are most heavily affected by such pluvial floods due to their predominantly solid surfaces. An example of such a city is Umeå, which experienced extensive floods causing up to 40 million Swedish kronor in damages. During the period 1970 to 2020, the population of Umeå has increased from 70,000 to 130,000 inhabitants, which means that both housing demand and thus the proportion of hardened surfaces in the municipality increased rapidly. To avoid future flooding problems, studying intensive precipitation trends as well as factors that affect the risk of pluvial floods is of the utmost importance. The purpose of this research is thus to investigate heavy precipitation trends as well as study how climate change and hardened surfaces affect the risk of flooding in Umeå. This study shows that the frequency of intense rainfall in Umeå has increased compared to the mean of the period 1963-1987 and that climate change could lead to an even higher frequency. Increased frequency of intensive precipitation in combination with an increased proportion of hardened surfaces increases the risk of flooding problems. Furthermore, heavy rainfalls, defined as precipitation above ten millilitres a day, occurred eighteen times a year during the period 1996-2020, which is four days more than the 1963-1987 average. By the end of the twenty-first century, climate change is expected to increase these number of days by a further 20-30% (equivalent to 7-12 days) according to SMHI predictions. Intense rainfall is likely to become more common in the future and population growth in Umeå will likely lead to an increase in the number of paved areas. These changes, in combination, place high demands on Umeå municipality to work efficiently with urban planning and climate adaptation.