Chapter 3 - Disentangling drivers of change

Chapter 2 - Key drivers of flood risk change

Extreme floods are one of the most damaging natural hazards, accounting for the majority of all economic losses from natural hazards worldwide. Several intertwined natural and anthropogenic drivers influence flood risk and its change: global warming, precipitation patterns, flood triggering processes, river morphology, river engineering works, population and values at risk, and flood risk reduction strategies. Sustainable flood risk management requires understanding all aspects of flood risk and its change in space and time. Thus, flood risks must be analyzed from a dynamic rather than a static perspective. However, methods to analyze and quantify environmental and socio-economic changes related to flood risk, both in space and time, are nearly not existent. Within this cumulative habilitation thesis methods are examined and developed that allow the analysis of past and future changes in both the natural and human environment with a spatially explicit perspective, and methods that allow disentangling the different drivers of change that are mostly interwoven and have opposing effects on flood risk evolution. The habilitation extends the frontiers of research on flood risk changes with three main methodological approaches: (1) data-driven analyses of environmental and socio-economic change, (2) development of models for specific aspects of flood risk, and (3) model coupling. Coupled component models provide an interesting approach for analyzing flood risk change, for modelling feedback mechanisms between human activities and the natural environment, and for the regionalization of global environmental and socio-economic changes. The habilitation thesis gives an outlook for enabling coupled model frameworks to predict and evaluate the effects of different adaptation strategies on flood risk evolution. Finally a modelling framework that couples specialist models toward whole-system models offers the potential for obtaining an universalist view and unifying several approaches in geography. Such a holistic approach is supporting the search for sustainable solutions for the complex and interconnected problems we are facing today.

Using precipitation and temperature data for the 20th century in combination with a macroscale hydrologic model, we evaluate changes in flood risk in the western U.S. associated both with century‐scale warming and interannual climate variations. In addition, we examine the implications of apparent increases in precipitation variability over the region since the mid‐1970s. We use detrended temperature data representing early and late 20th century climate to force the variable infiltration capacity hydrologic model and show that spatially homogeneous temperature changes over the western U.S. in the 20th century on the order of +1°C per century have resulted in substantial changes in flood risks over much of the region. Although changes specific to particular geographic areas are apparent in some cases, the overall changes due to observed warming trends are well categorized by midwinter temperature regimes in each watershed. Cold river basins where snow processes dominate the annual hydrologic cycle (<−6°C average in midwinter) typically show reductions in flood risk due to overall reductions in spring snowpack. Relatively warm rain‐dominant basins (>5°C average in midwinter) show little systematic change. Intermediate or transient basins show a wide range of effects depending on competing factors such as the relative role of antecedent snow and contributing basin area during storms that cause flooding. Warmer transient basins along the coast in Washington, Oregon, and California, in particular, tend to show increased flood risk. While the absolute value of simulated changes in flood risk is affected by basin scale, the nature of the relationship of flood risk to basin temperatures in midwinter is largely scale‐independent. Climate variations associated with Pacific Decadal Oscillation (PDO) and El Niño Southern Oscillation (ENSO) also have strong effects on flood risks. In contrast to the effects associated with 20th century warming, the climate variability signal is characterized by regional scale patterns related to the geographic distribution of cool season precipitation also identified in many previous studies. In general, the largest changes in simulated flood risks are associated with years when PDO and ENSO are “in phase,” particularly in the southwest. Changes in the variability of cool season precipitation after about 1973, the causes of which are uncertain, are shown to result in increased flood risk over much of the western U.S. in the simulations.

Flood risk (d)evolution: Disentangling key drivers of flood risk change with a retro-model experiment

The economic stress and damage from natural hazards are escalating at an alarming rate, calling for anticipatory risk management. Yet few studies have projected flood and drought risk, owing to large uncertainties, strong non‐linearities, and complex spatial‐temporal dynamics. Here, we develop an integrative global risk analysis framework encapsulating future changes in flood and drought hazards as well as associated exposure and vulnerability dimensions. Flood characteristics are quantified by fitting a generalized extreme value distribution (GEV) to the annual flow maxima time series, while drought properties are characterized by the standardized precipitation evapotranspiration index (SPEI) and the standardized precipitation index (SPI). The drivers of drought and flood risk changes at the global and regional scales are explored, and the wide cascade of uncertainties in the risk assessment is decomposed. We find a substantial increase in both flood and drought risk towards the end of the century over most of the globe, driven by compounding changes in exposure, vulnerability, and hazard. A shift from a fossil‐fueled development to a sustainable one decreases the global area facing a risk doubling from 61% to 33% for flood and from 41% to 23% for drought. South America and Africa are identified as hotspot regions where a concomitant, large increase in both flood and drought risk are projected. The hazard quantification method is ubiquitously the dominant uncertainty source for drought risk changes, while the contribution of uncertainty sources for flood risk changes is highly variable in space.

Flood damage has increased significantly and is expected to rise further in many parts of the world. For assessing potential changes in flood risk, this paper presents an integrated model chain quantifying flood hazards and losses while considering climate and land use changes. In the case study region, risk estimates for the present and the near future illustrate that changes in flood risk by 2030 are relatively low compared to historic periods. While the impact of climate change on the flood hazard and risk by 2030 is slight or negligible, strong urbanisation associated with economic growth contributes to a remarkable increase in flood risk. Therefore, it is recommended to frequently consider land use scenarios and economic developments when assessing future flood risks. Further, an adapted and sustainable risk management is necessary to encounter rising flood losses, in which non-structural measures are becoming more and more important. The case study demonstrates that adaptation by non-structural measures such as stricter land use regulations or enhancement of private precaution is capable of reducing flood risk by around 30 %. Ignoring flood risks, in contrast, always leads to further increasing losses—with our assumptions by 17 %. These findings underline that private precaution and land use regulation could be taken into account as low cost adaptation strategies to global climate change in many flood prone areas. Since such measures reduce flood risk regardless of climate or land use changes, they can also be recommended as no-regret measures.

Changes in flood risk impacted by river training - case study of piedmont section of the Vistula river. Main problems concerning the flood risk in piedmont section of the Vistula, Southern Poland, are discussed. This stretch of the river is channelized since the middle of the 19th century. It is part of the mainstream discussion of the effectiveness of existing river channelization methods. The following problems are analysed: (1) current state of flood risk, (2) the rate of river flow, (3) changes in flood risk since the start of channelization efforts with respect to changing channel geometry and changing rates of river flow reflecting the effects of channelization work. Substantially increased bankfull discharge in a channelized river may be considered as a stable hydrologic feature of the river stretch analysed. This means that the river is effectively reducing the quantity of water available for flooding the inter-embankment zone. This statement is the basis for analysis of changes in flood risk in the river studied. An assessment of changes in flood risk for the piedmont section of the Vistula cannot be categorical. Some changes in discharge help reduce flood risk, while others increase it. The paper is based mainly on the State Hydrological Survey data over more than the last 100 years, a large-scale maps over the last 230 years, and fieldwork conducted by the author.

Our understanding of the key drivers of change in flood risk due to climate change remains incomplete. Here, to understand and quantify the key drivers of change in flood risk, we present a framework to undertake a ‘bottom-up’ (‘scenario-neutral’) climate change impact study on flood risk using an event-based flood model that considers non-stationarity in rainfall extremes and catchment wetness. A key advantage of this approach is that by using an event-based model, which explicitly represents key flood drivers, we can directly understand how changes in these drivers will influence changes in flood peaks. The utility of this modelling framework is demonstrated by applying it to one temperate and one tropical catchment in Australia, focusing on the sensitivity of frequent (1 in 5 annual exceedance probability, AEP) and rare (1 in 50 AEP) flood peaks to changes in thermodynamic and dynamic drivers of rainfall extremes, and changes in catchment processes, which are quantified by changes in rainfall losses.Response surfaces of the catchment sensitivity are first produced and demonstrate that increases in rainfall intensity drive increases in the flood peak. Smaller flood peaks in drier catchments are most sensitive to changes in rainfall losses, with the modulating impact of changes in losses decreasing as the runoff ratio increases. Climate model projections of these drivers are then superimposed on these surfaces to identify plausible shifts in flood risk under climate change. Several climate model ensemble members imply a decrease in future flood peaks, most notably 14 % of ensemble members suggest future decreases for the 1 in 5 AEP event for the temperate catchment. Despite large agreement on the direction of change, we found large variability in the expected magnitude of change for both frequent and rare events with flood peaks projected to increase between 0 % and 45 % for the tropical catchment and between −10 % to more than 50 % for the temperate catchment under RCP8.5 in 2085, highlighting the deep uncertainty associated with projecting flood risk under climate change. We believe this study acts as proof of concept for how a bottom-up climate change assessment can be undertaken within an event-based flood modelling framework, and provides insights to help us better understand and communicate the key drivers of changes to flood risk into the future.

We report on a regional flood and earthquake risk assessment for 33 countries in Eastern Europe and Central Asia. Flood and earthquake risk were defined in terms of affected population and affected gross domestic product (GDP). Earthquake risk was also quantified in terms of fatalities and capital loss. Estimates of future population and GDP affected by earthquakes vary significantly among five shared socioeconomic pathways that are used to represent population and GDP in 2030 and 2080. There is a linear relationship between the future relative change in a nation's exposure (population or GDP) and its future relative change in annual average population or GDP affected by earthquakes. The evolution of flood hazard was quantified using a flood model with boundary conditions derived from five different general circulation models and two representative concentration pathways, and changes in population and GDP were quantified using two shared socioeconomic pathways. There is a nonlinear relationship between the future relative change in a nation's exposure (population or GDP) and its future relative change in its annual average population or GDP affected by floods. Six regions can be defined for positive and negative relative change in population that designate whether climate change can temper, counter, or reinforce relative changes in flood risk produced by changes in population or exposure. The departure from the one‐to‐one relationship between a relative change in a nation's population or GDP and its relative change in flood risk could be used to inform further efforts at flood mitigation and adaptation.

Floodplains, as seen from the flood risk management perspective, are composed of co-evolving natural and human systems. Both flood processes (that is, the hazard) and the values at risk (that is, settlements and infrastructure built in hazardous areas) are dynamically changing over time and influence each other. These changes influence future risk pathways. The co-evolution of all of these drivers for changes in flood risk could lead to emergent behavior. Hence, complexity theory and systems science can provide a sound theoretical framework for flood risk management in the 21st century. This review aims at providing an entry point for modelers in flood risk research to consider floodplains as complex adaptive systems. For the systems science community, the actual problems and approaches in the flood risk research community are summarized. Finally, an outlook is given on potential future coupled component modeling approaches that aims at bringing together both disciplines.

There is growing evidence of coherent, global patterns of change in annual precipitation and runoff with high latitudes experiencing increases consistent with climate model projections. This paper describes a methodology for estimating detection times for changes in seasonal precipitation extremes. The approach is illustrated using changes in UK precipitation projected by the European Union PRUDENCE climate model ensemble. We show that because of high variability from year to year and confounding factors, detection of anthropogenic climate change at regional scales is not generally expected for decades to come. Overall, the earliest detection times were found for 10 day winter precipitation totals with 10 year return period in SW England. In this case, formal detection could be possible within a decade from now if the climate model projections are realized. The outlook for changes in summer flash flood risk is highly uncertain. Our analysis further demonstrates that existing precautionary allowances for climate change used for flood management may not be sufficiently robust in NE England and east Scotland. These findings imply that for certain types of flood mechanism, adaptation decisions might have to be taken in advance of formally detected changes in flood risk. This reinforces the case for long‐term environmental monitoring and reporting of climate change indices at “sentinel” locations.

<p>In the coming decades, climate change will likely become a complex issue affecting hydrological regimes and flood hazard conditions. According to the IPCC reports, significant changes in atmospheric temperature, precipitation, humidity, and circulation are expected which may lead to extreme events including flood, droughts, heatwaves, heavy precipitation, and more intense cyclones. Although the effects of climate change on flood hazard indices is subject to large uncertainty, the evaluation of high-flows plays a crucial role in flood risk planning and extreme event management. With the advent of the Coupled Model Intercomparison Project Phase 6 (CMIP6), flood managers are interested to know how changes in catchment flood risk are expected to alter relative to previous assessments. Here we examine catchment based projected changes in flood quantiles and extreme high flow events for Irish catchments, selected to be representative of the range of hydrological conditions on the island. Conceptual hydrological models, together with different downscaling techniques are used to examine changes in flood risk projected from the CMIP6 archive for mid and end of century. Results will inform the range of plausible changes expected for policy relevant flood indices, the sensitivity of findings to use of different climate model ensembles and inform the tailoring of adaptation plans to account for the new generation of climate model outputs.</p>

Abstract. The observed increase of direct flood damage over the last decades may be caused by changes in the meteorological drivers of floods, or by changing land-use patterns and socio-economic developments. It is still widely unknown to which extent these factors will contribute to future flood risk changes. We survey the change of flood risk in terms of expected annual damage for residential buildings in the lower part of the Mulde River basin (Vereinigte Mulde) between 1990 and 2020 in 10-yr time steps based on measurements and model projections. For this purpose we consider the complete risk chain from climate impact via hydrological and hydraulic modelling to damage and risk estimation. We analyse what drives the changes in flood risk and quantify the contributions of these drivers: flood hazard change due to climate change, land-use change and changes in building values. We estimate flood risk and building losses based on constant values and based on effective (inflation adjusted) values separately. For constant values, estimated building losses for the most extreme inundation scenario amount to more than 360 million € for all time steps. Based on effective values, damage estimates for the same inundation scenario decrease from 478 million € in 1990 to 361 million € in 2000 and 348 million € in 2020 (maximum land-use scenario). Using constant values, flood risk is 111% (effective values: 146%) of the 2000 estimate in 1990 and 121% (effective values: 115%) of the 2000 estimate for the maximum land-use scenario in 2020. The quantification of driver contributions reveals that land-use change in the form of urban sprawl in endangered areas is the main driver of flood risk in the study area. Climate induced flood hazard change is important but not a dominant factor of risk change in the study area. With the historical exception of the economic effects in Eastern Germany following the German reunification, value developments only have minor influence on the development of flood risk.

Natural disasters have become more frequent and intense over the last decade mainly as a result of poor water and land management. Cultural sites and monuments are extremely vulnerable to natural disasters, particularly floods, while mitigation measures and protective infrastructure are difficult to construct within such areas. In the present study, the precipitation trends of the recent past and over the next 80 years were analyzed for the old town of Corfu (UNESCO World Heritage Site) in order to identify potentially significant changes that may affect the flood risk of the area. Moreover, a multi-criteria analysis using GIS software was used to identify high flood hazard zones in this living monument in order to propose specific mitigation measures that are in line with the characteristics of the site. The main effort in this study was to find a methodological approach for a fast but reliable assessment of future changes in the flood risk of historic monuments without the need for a hydrodynamic model and with a limited amount of locally based data. With the selected approach, a good indication of the potential changes in flood risk was provided, according to climate scenarios and simple, physically-based geostatistical models. The results indicate that no significant changes in the flood risk were found for the future climatic conditions, and the identified flood-prone areas will remain approximately the same as today in this particular historic monument. The uncertainty that is included in this output originates mainly from the inherent errors in climate modeling and from the non-high temporal resolution of the data.

Flood risk under future climate in data sparse regions: Linking extreme value models and flood generating processes