Suchergebnisse

Cover -- Half Title -- Title Page -- Copyright Page -- Dedication -- Acknoledgments -- Summary -- Samenvatting -- Sommario -- Table of Contents -- 1: Introduction -- 1.1 Background -- 1.1.1 Flood forecasting and early warning systems -- 1.1.2 Hydrological and hydrodynamic modelling -- 1.1.3 Uncertainty in hydrological and hydrodynamic modelling -- 1.1.4 Data assimilation -- 1.1.5 Citizen Science -- 1.2 Motivation -- 1.3 Terminology -- 1.4 Research objectives -- 1.5 Outline of the thesis -- 2: Case studies and models -- 2.1 Introduction -- 2.2 Case 1 - Brue Catchment (UK) -- 2.2.1 Catchment description -- 2.2.2 Model description -- 2.3 Case 2 - Bacchiglione Catchment (Italy) -- 2.3.1 Catchment description -- 2.3.2 Model description -- 2.4 Case 3 - Trinity and Sabine Rivers (USA) -- 2.4.1 Rivers description -- 2.4.2 Model description -- 2.5 Case 4 - Synthetic river reach -- 3: Data assimilation methods -- 3.1 Introduction -- 3.2 Direct insertion -- 3.3 Nudging scheme -- 3.4 Kalman Filter -- 3.5 Ensemble Kalman Filter -- 3.6 Asynchronous Ensemble Kalman Filter -- 4: Assimilation of synchronous data in hydrological models -- 4.1 Introduction -- 4.2 Methodology -- 4.2.1 Assimilation of intermittent observations -- 4.2.2 Observation and model error -- 4.2.3 Generation of synthetic observations -- 4.3 Experimental setup -- 4.3.1 Experiment 4.1: Streamflow data from static physical (StPh) sensors -- 4.3.2 Experiment 4.2: Streamflow data from static social (StSc) sensors -- 4.3.3 Experiment 4.3: Intermittent streamflow data from static social (StSc) sensors -- 4.3.4 Experiment 4.4: Heterogeneous network of static physical (StPh) and static social (StSc) sensors -- 4.4 Results and discussion -- 4.4.1 Experiment 4.1 -- 4.4.2 Experiment 4.2 -- 4.4.3 Experiment 4.3 -- 4.4.4 Experiment 4.4 -- 4.5 Conclusions

Two-way interactions and feedback between hydrological and social processes in settled floodplains determine the complex human-flood system and change vulnerability over time. To focus on the dynamic role of individual and governmental decision making on flood-risk management, we developed and implemented a coupled agent-based and hydraulic modelling framework. Within this framework, household agents are located in a floodplain protected by a levee system. Individual behaviour is based on Protection Motivation Theory and includes the options to (1) not react to flood risk; (2) implement individual flood protection measures; or (3) file a complaint to the government. The government decides about reinforcing the levee system, compromising between a cost-benefit analysis and filed complaints from households. We found that individual decision making can significantly influence flood risk. In addition, the coupled agent-based and hydraulic modelling framework approach captures commonly observed socio-hydrological dynamics, namely levee and adaptation effects. It provides an explanatory tool for assessing spatial and temporal dynamics of flood risk in a socio-hydrological system.

Multi-hazard events can be associated with larger socio-economic impacts than single-hazard events. Understanding the spatio-temporal interactions that characterize the former is therefore of relevance to disaster risk reduction measures. Here, we consider two high-impact hazards, namely wet and dry hydrological extremes, and quantify their global co-occurrence. We define these using the monthly self-calibrated Palmer Drought Severity Index based on the Penman–Monteith model (sc_PDSI_pm), covering the period 1950–2014, at 2.5 ∘ horizontal resolution. We find that the land areas affected by extreme wet, dry, and wet–dry events (i.e. geographically remote yet temporally co-occurring wet or dry extremes) are all increasing with time, the trends of which in dry and wet–dry episodes are significant ( p value ≪ 0.01). The most geographically widespread wet–dry event was associated with the strong La Niña in 2010. This caused wet–dry anomalies across a land area of 21 million km 2 with documented high-impact flooding and drought episodes spanning diverse regions. To further elucidate the interplay of wet and dry extremes at a grid cell scale, we introduce two new metrics: the wet–dry (WD) ratio and the extreme transition (ET) time intervals. The WD ratio measures the relative occurrence of wet or dry extremes, whereas ET quantifies the average separation time of hydrological extremes with opposite signs. The WD ratio shows that the incidence of wet extremes dominates over dry extremes in the USA, northern and southern South America, northern Europe, north Africa, western China, and most of Australia. Conversely, dry extremes are more prominent in most of the remaining regions. The median ET for wet to dry is ∼27 months, while the dry-to-wet median ET is 21 months. We also evaluate correlations between wet–dry hydrological extremes and leading modes of climate variability, namely the El Niño–Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), and Atlantic Multi-decadal Oscillation (AMO). We find that ENSO and PDO have a similar influence globally, with the former significantly impacting ( p value < 0.05) a larger area (18.1 % of total sc_PDSI_pm area) compared to the latter (12.0 %), whereas the AMO shows an almost inverse pattern and significantly impacts the largest area overall (18.9 %). ENSO and PDO show the most significant correlations over northern South America, the central and western USA, the Middle East, eastern Russia, and eastern Australia. On the other hand, the AMO shows significant associations over Mexico, Brazil, central Africa, the Arabian Peninsula, China, and eastern Russia. Our analysis brings new insights on hydrological multi-hazards that are of relevance to governments and organizations with globally distributed interests. Specifically, the multi-hazard maps may be used to evaluate worst-case disaster scenarios considering the potential co-occurrence of wet and dry hydrological extremes.

Multi-hazard events can be associated with larger socio-economic impacts than single-hazard events. Understanding the spatio-temporal interactions characterising the former is, therefore, of relevance to disaster risk reduction measures. Here, we consider two high-impact hazards, namely wet and dry hydrological extremes, and quantify their global co-occurrence. We define these using the monthly self-calibrated Palmer Drought Severity Index based on the Penman-Monteith model (sc_PDSI_pm) covering the period 1950–2014, at 2.5° horizontal resolution. We find that the land areas affected by extreme wet, dry and wet-dry events (i.e. geographically remote, yet temporally co-occurring wet or dry extremes) all display increasing trends with time, of which changes in dry and wet-dry episodes are significant ( p -value « 0.01). The most geographically widespread wet-dry event covered a combined land area of 21 million km 2 , with documented high-impact flooding and drought episodes spanning diverse regions. To further elucidate the interplay of wet and dry extremes at a grid-point scale, we introduce two new metrics: the wet-dry (WD) ratio and the extreme transition (ET) time interval. The WD-ratio measures the relative occurrence of extreme wet or dry events, whereas ET quantifies the average separation time of hydrological extremes with opposite signs. The WD-ratio shows that the incidence of extreme wet episodes dominates over dry episodes in the USA, northern and southern south America, northern Europe, north Africa, western China and most of Australia. Conversely, extreme dry events are more prominent in most of the remaining regions. The median ET for wet to dry is ~ 27 months, while the dry to wet median ET is 21 months. We also evaluate correlations between wet-dry hydrological extremes and leading modes of large-scale variability, namely the: El Niño–Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO) and American Multi-decadal Oscillation (AMO). We find that ENSO and PDO have a similar influence globally, with the former significantly impacting ( p -value < 0.05) a larger area compared to the latter, whereas the AMO shows an almost inverse pattern, and significantly impacts a larger overall area. Our analysis brings new insights on hydrological multi-hazards and are of direct relevance to governments and organisations with globally distributed interests, such as (re)insurance companies. Specifically, the multi-hazard maps may be used to evaluate worst-case disaster scenarios considering the potential co-occurrence of wet and dry hydrological extremes.

What role can a speculative political ecology play in (re)imaging urban futures of climate extremes? In recent years, narratives of dystopian futures of climate extremes have proliferated in geosciences, and across the media and creative arts. These anxiety-fueled narratives often generate a sense of resignation and unavoidability, which contributes to foreclosing the possibility of radically different political projects. In this article, we argue that these narratives conceal the coproduction of nature and society and treat nature as the problem, thereby locking futures into dystopic configurations. Political ecology scholarship can contribute to generate a politics of possibility by reconceptualizing the relations that constitute urban futures under climate extremes as socionatural. This, we argue, calls for a more experimental political ecology and new forms of theorizing. To this aim, we develop a speculative political ecological approach grounded on a numerical model that examines the potential of transformative change in the aftermath of extreme flood events in a capitalist city. Analytically, this opens a unique possibility of exploring urban futures beyond current trajectories, and how these alternative futures might transform vulnerability and inequality across urban spaces. From a policy perspective, we lay the foundations for a new generation of models that apprehend the role of power and agency in shaping uneven urban futures of climate extremes.

Multi-hazard events can be associated with larger socio-economic impacts than single-hazard events. Understanding the spatio-temporal interactions that characterize the former is therefore of relevance to disaster risk reduction measures. Here, we consider two high-impact hazards, namely wet and dry hydrological extremes, and quantify their global co-occurrence. We define these using the monthly self-calibrated Palmer Drought Severity Index based on the Penman-Monteith model (sc_PDSI_pm), covering the period 1950-2014, at 2.5 degrees horizontal resolution. We find that the land areas affected by extreme wet, dry, and wet-dry events (i.e. geographically remote yet temporally co-occurring wet or dry extremes) are all increasing with time, the trends of which in dry and wet-dry episodes are significant (p value « 0.01). The most geographically widespread wet-dry event was associated with the strong La Nina in 2010. This caused wet-dry anomalies across a land area of 21 million km(2) with documented high-impact flooding and drought episodes spanning diverse regions. To further elucidate the interplay of wet and dry extremes at a grid cell scale, we introduce two new metrics: the wet-dry (WD) ratio and the extreme transition (ET) time intervals. The WD ratio measures the relative occurrence of wet or dry extremes, whereas ET quantifies the average separation time of hydrological extremes with opposite signs. The WD ratio shows that the incidence of wet extremes dominates over dry extremes in the USA, northern and southern South America, northern Europe, north Africa, western China, and most of Australia. Conversely, dry extremes are more prominent in most of the remaining regions. The median ET for wet to dry is similar to 27 months, while the dry-to-wet median ET is 21 months. We also evaluate correlations between wet-dry hydrological extremes and leading modes of climate variability, namely the El Nina-Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), and Atlantic Multi-decadal Oscillation (AMO). We find that ENSO and PDO have a similar influence globally, with the former significantly impacting (p value < 0.05) a larger area (18.1 % of total sc_PDSI_pm area) compared to the latter (12.0 %), whereas the AMO shows an almost inverse pattern and significantly impacts the largest area overall (18.9 %). ENSO and PDO show the most significant correlations over northern South America, the central and western USA, the Middle East, eastern Russia, and eastern Australia. On the other hand, the AMO shows significant associations over Mexico, Brazil, central Africa, the Arabian Peninsula, China, and eastern Russia. Our analysis brings new insights on hydrological multi-hazards that are of relevance to governments and organizations with globally distributed interests. Specifically, the multi-hazard maps may be used to evaluate worst-case disaster scenarios considering the potential co-occurrence of wet and dry hydrological extremes.

Multi-hazard events can be associated with larger socio-economic impacts than single-hazard events. Understanding the spatio-temporal interactions that characterize the former is therefore of relevance to disaster risk reduction measures. Here, we consider two high-impact hazards, namely wet and dry hydrological extremes, and quantify their global co-occurrence. We define these using the monthly self-calibrated Palmer Drought Severity Index based on the Penman-Monteith model (sc-PDSI-pm), covering the period 1950-2014, at 2.5° horizontal resolution. We find that the land areas affected by extreme wet, dry, and wet-dry events (i.e. geographically remote yet temporally co-occurring wet or dry extremes) are all increasing with time, the trends of which in dry and wet-dry episodes are significant (p value ≪ 0.01). The most geographically widespread wet-dry event was associated with the strong La Niña in 2010. This caused wet-dry anomalies across a land area of 21 million km 2 with documented high-impact flooding and drought episodes spanning diverse regions. To further elucidate the interplay of wet and dry extremes at a grid cell scale, we introduce two new metrics: the wet-dry (WD) ratio and the extreme transition (ET) time intervals. The WD ratio measures the relative occurrence of wet or dry extremes, whereas ET quantifies the average separation time of hydrological extremes with opposite signs. The WD ratio shows that the incidence of wet extremes dominates over dry extremes in the USA, northern and southern South America, northern Europe, north Africa, western China, and most of Australia. Conversely, dry extremes are more prominent in most of the remaining regions. The median ET for wet to dry is ∼27 months, while the dry-to-wet median ET is 21 months. We also evaluate correlations between wet-dry hydrological extremes and leading modes of climate variability, namely the El Niño-Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), and Atlantic Multi-decadal Oscillation (AMO). We find that ENSO and PDO have a similar influence globally, with the former significantly impacting (p value < 0.05) a larger area (18.1 % of total sc-PDSI-pm area) compared to the latter (12.0 %), whereas the AMO shows an almost inverse pattern and significantly impacts the largest area overall (18.9 %). ENSO and PDO show the most significant correlations over northern South America, the central and western USA, the Middle East, eastern Russia, and eastern Australia. On the other hand, the AMO shows significant associations over Mexico, Brazil, central Africa, the Arabian Peninsula, China, and eastern Russia. Our analysis brings new insights on hydrological multi-hazards that are of relevance to governments and organizations with globally distributed interests. Specifically, the multi-hazard maps may be used to evaluate worst-case disaster scenarios considering the potential co-occurrence of wet and dry hydrological extremes.

Multi-hazard events can be associated with larger socio-economic impacts than single-hazard events. Understanding the spatio-temporal interactions that characterize the former is therefore of relevance to disaster risk reduction measures. Here, we consider two high-impact hazards, namely wet and dry hydrological extremes, and quantify their global co-occurrence. We define these using the monthly self-calibrated Palmer Drought Severity Index based on the Penman–Monteith model (sc_PDSI_pm), covering the period 1950–2014, at 2.5∘ horizontal resolution. We find that the land areas affected by extreme wet, dry, and wet–dry events (i.e. geographically remote yet temporally co-occurring wet or dry extremes) are all increasing with time, the trends of which in dry and wet–dry episodes are significant (p value ≪ 0.01). The most geographically widespread wet–dry event was associated with the strong La Niña in 2010. This caused wet–dry anomalies across a land area of 21 million km2 with documented high-impact flooding and drought episodes spanning diverse regions. To further elucidate the interplay of wet and dry extremes at a grid cell scale, we introduce two new metrics: the wet–dry (WD) ratio and the extreme transition (ET) time intervals. The WD ratio measures the relative occurrence of wet or dry extremes, whereas ET quantifies the average separation time of hydrological extremes with opposite signs. The WD ratio shows that the incidence of wet extremes dominates over dry extremes in the USA, northern and southern South America, northern Europe, north Africa, western China, and most of Australia. Conversely, dry extremes are more prominent in most of the remaining regions. The median ET for wet to dry is ∼27 months, while the dry-to-wet median ET is 21 months. We also evaluate correlations between wet–dry hydrological extremes and leading modes of climate variability, namely the El Niño–Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), and Atlantic Multi-decadal Oscillation (AMO). We find that ENSO and PDO have a similar influence globally, with the former significantly impacting (p value < 0.05) a larger area (18.1 % of total sc_PDSI_pm area) compared to the latter (12.0 %), whereas the AMO shows an almost inverse pattern and significantly impacts the largest area overall (18.9 %). ENSO and PDO show the most significant correlations over northern South America, the central and western USA, the Middle East, eastern Russia, and eastern Australia. On the other hand, the AMO shows significant associations over Mexico, Brazil, central Africa, the Arabian Peninsula, China, and eastern Russia. Our analysis brings new insights on hydrological multi-hazards that are of relevance to governments and organizations with globally distributed interests. Specifically, the multi-hazard maps may be used to evaluate worst-case disaster scenarios considering the potential co-occurrence of wet and dry hydrological extremes.

This is an Open Access Article. It is published by Copernicus under the Creative Commons Attribution 4.0 Unported Licence (CC BY). Full details of this licence are available at: http://creativecommons.org/licenses/by/4.0/ ; Abstract. Multi-hazard events can be associated with larger socio-economic impacts than single-hazard events. Understanding the spatio-temporal interactions characterising the former is, therefore, of relevance to disaster risk reduction measures. Here, we consider two high-impact hazards, namely wet and dry hydrological extremes, and quantify their global co-occurrence. We define these using the monthly self-calibrated Palmer Drought Severity Index based on the Penman-Monteith model (sc_PDSI_pm) covering the period 1950–2014, at 2.5° horizontal resolution. We find that the land areas affected by extreme wet, dry and wet-dry events (i.e. geographically remote, yet temporally co-occurring wet or dry extremes) all display increasing trends with time, of which changes in dry and wet-dry episodes are significant (p-value «0.01). The most geographically widespread wet-dry event covered a combined land area of 21 million km 2 , with documented high-impact flooding and drought episodes spanning diverse regions. To further elucidate the interplay of wet and dry extremes at a grid-point scale, we introduce two new metrics: the wet-dry (WD) ratio and the extreme transition (ET) time interval. The WD-ratio measures the relative occurrence of extreme wet or dry events, whereas ET quantifies the average separation time of hydrological extremes with opposite signs. The WD-ratio shows that the incidence of extreme wet episodes dominates over dry episodes in the USA, northern and southern south America, northern Europe, north Africa, western China and most of Australia. Conversely, extreme dry events are more prominent in most of the remaining regions. The median ET for wet to dry is ~ 27 months, while the dry to wet median ET is 21 months. We also evaluate correlations between wet-dry hydrological extremes and leading modes of large-scale variability, namely the: El Niño–Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO) and American Multi-decadal Oscillation (AMO). We find that ENSO and PDO have a similar influence globally, with the former significantly impacting (p-value «0.01) a larger area compared to the latter, whereas the AMO shows an almost inverse pattern, and significantly impacts a larger overall area. Our analysis brings new insights on hydrological multi-hazards and are of direct relevance to governments and organisations with globally distributed interests, such as (re)insurance companies. Specifically, the multi-hazard maps may be used to evaluate worst-case disaster scenarios considering the potential co-occurrence of wet and dry hydrological extremes.

Predicting floods and droughts is essential to inform the development of policy in water management, climate change adaptation and disaster risk reduction. Yet, hydrological predictions are highly uncertain, while the frequency, severity and spatial distribution of extreme events are further complicated by the increasing impact of human activities on the water cycle. In this commentary, we argue that four main aspects characterizing the complexity of human-water systems should be explicitly addressed: feedbacks, scales, tradeoffs and inequalities. We propose the integration of multiple research methods as a way to cope with complexity and develop policy-relevant science. Plain Language Summary Several governments today claim to be following the science in addressing crises caused by the occurrence of extreme events, such as floods and droughts, or the emergence of global threats, such as climate change and COVID-19. In this commentary, we show that there are no universal answers to apparently simple questions such as: Do levees reduce flood risk? Do reservoirs alleviate droughts? We argue that the best science we have consists of a plurality of legitimate interpretations and a range of foresights, which can be enriched by integrating multiple disciplines and research methods.