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Hydrometric networks play a vital role in providing information for decision-making in water resource management. They should be set up optimally to provide as much information as possible that is as accurate as possible and, at the same time, be cost-effective. Although the design of hydrometric networks is a well-identified problem in hydrometeorology and has received considerable attention, there is still scope for further advancement. In this study, we use complex network analysis, defined as a collection of nodes interconnected by links, to propose a new measure that identifies critical nodes of station networks. The approach can support the design and redesign of hydrometric station networks. The science of complex networks is a relatively young field and has gained significant momentum over the last few years in different areas such as brain networks, social networks, technological networks, or climate networks. The identification of influential nodes in complex networks is an important field of research. We propose a new node-ranking measure – the weighted degree–betweenness (WDB) measure – to evaluate the importance of nodes in a network. It is compared to previously proposed measures used on synthetic sample networks and then applied to a real-world rain gauge network comprising 1229 stations across Germany to demonstrate its applicability. The proposed measure is evaluated using the decline rate of the network efficiency and the kriging error. The results suggest that WDB effectively quantifies the importance of rain gauges, although the benefits of the method need to be investigated in more detail.
In recent years, urban and rural flash floods in Europe and abroad have gained considerable attention because of their sudden occurrence, severe material damages and even danger to life of inhabitants. This contribution addresses questions about possibly changing environmental conditions which might have altered the occurrence frequencies of such events and their consequences. We analyze the following major fields of environmental changes.
Altered high intensity rain storm conditions, as a consequence of regionalwarming; Possibly altered runoff generation conditions in response to high intensity rainfall events; Possibly altered runoff concentration conditions in response to the usage and management of the landscape, such as agricultural, forest practices or rural roads; Effects of engineering measures in the catchment, such as retention basins, check dams, culverts, or river and geomorphological engineering measures.
We take the flash-flood in Braunsbach, SW-Germany, as an example, where a particularly concise flash flood event occurred at the end of May 2016. This extreme cascading natural event led to immense damage in this particular village. The event is retrospectively analyzed with regard to meteorology, hydrology, geomorphology and damage to obtain a quantitative assessment of the processes and their development.
The results show that it was a very rare rainfall event with extreme intensities, which in combination with catchment properties and altered environmental conditions led to extreme runoff, extreme debris flow and immense damages. Due to the complex and interacting processes, no single flood cause can be identified, since only the interplay of those led to such an event. We have shown that environmental changes are important, but-at least for this case study-even natural weather and hydrologic conditions would still have resulted in an extreme flash flood event.
Hydrometric networks play a vital role in providing information for decision-making in water resource management. They should be set up optimally to provide as much information as possible that is as accurate as possible and, at the same time, be cost-effective. Although the design of hydrometric networks is a well-identified problem in hydrometeorology and has received considerable attention, there is still scope for further advancement. In this study, we use complex network analysis, defined as a collection of nodes interconnected by links, to propose a new measure that identifies critical nodes of station networks. The approach can support the design and redesign of hydrometric station networks. The science of complex networks is a relatively young field and has gained significant momentum over the last few years in different areas such as brain networks, social networks, technological networks, or climate networks. The identification of influential nodes in complex networks is an important field of research. We propose a new node-ranking measure – the weighted degree–betweenness (WDB) measure – to evaluate the importance of nodes in a network. It is compared to previously proposed measures used on synthetic sample networks and then applied to a real-world rain gauge network comprising 1229 stations across Germany to demonstrate its applicability. The proposed measure is evaluated using the decline rate of the network efficiency and the kriging error. The results suggest that WDB effectively quantifies the importance of rain gauges, although the benefits of the method need to be investigated in more detail.
The flash-flood in Braunsbach in the north-eastern part of Baden-Wuerttemberg/Germany was a particularly strong and concise event which took place during the floods in southern Germany at the end of May/early June 2016. This article presents a detailed analysis of the hydro-meteorological forcing and the hydrological consequences of this event. A specific approach, the "forensic hydrological analysis" was followed in order to include and combine retrospectively a variety of data from different disciplines. Such an approach investigates the origins, mechanisms and course of such natural events if possible in a "near real time" mode, in order to follow the most recent traces of the event. The results show that it was a very rare rainfall event with extreme intensities which, in combination with catchment properties, led to extreme runoff plus severe geomorphological hazards, i.e. great debris flows, which together resulted in immense damage in this small rural town Braunsbach. It was definitely a record-breaking event and greatly exceeded existing design guidelines for extreme flood discharge for this region, i.e. by a factor of about 10. Being such a rare or even unique event, it is not reliably feasible to put it into a crisp probabilistic context. However, one can conclude that a return period clearly above 100 years can be assigned for all event components: rainfall, peak discharge and sediment transport. Due to the complex and interacting processes, no single flood cause or reason for the very high damage can be identified, since only the interplay and the cascading characteristics of those led to such an event. The roles of different human activities on the origin and/or intensification of such an extreme event are finally discussed. (C) 2018 Elsevier B.V. All rights reserved.
Frequent and intense rainfall events demand innovative techniques to better predict the extreme rainfall dynamics. This task requires essentially the assessment of the basic types of atmospheric processes that trigger extreme rainfall, and then to examine the differences between those processes, which may help to identify key patterns to improve predictive algorithms. We employ tools from network theory to compare the spatial features of extreme rainfall over the Japanese archipelago and surrounding areas caused by two atmospheric processes: the Baiu front, which occurs mainly in June and July (JJ), and the tropical storms from August to November (ASON). We infer from complex networks of satellite-derived rainfall data, which are based on the nonlinear correlation measure of event synchronization. We compare the spatial scales involved in both systems and identify different regions which receive rainfall due to the large spatial scale of the Baiu and tropical storm systems. We observed that the spatial scales involved in the Baiu driven rainfall extremes, including the synoptic processes behind the frontal development, are larger than tropical storms, which even have long tracks during extratropical transitions. We further delineate regions of coherent rainfall during the two seasons based on network communities, identifying the horizontal (east-west) rainfall bands during JJ over the Japanese archipelago, while during ASON these bands align with the island arc of Japan.
Im Graduiertenkolleg NatRiskChange der Universität Potsdam und anderen Forschungseinrichtungen werden beobachtete sowie zukünftig mögliche Veränderungen von Naturgefahren untersucht. Teil des strukturierten Doktorandenprogramms sind sogenannte Task-Force-Einsätze, bei denen die Promovierende zeitlich begrenzt ein aktuelles Ereignis auswerten. Im Zuge dieser Aktivität wurde die Sturzflut vom 29.05.2016 in Braunsbach (Baden-Württemberg) untersucht.
In diesem Bericht werden erste Auswertungen zur Einordnung der Niederschläge, zu den hydrologischen und geomorphologischen Prozessen im Einzugsgebiet des Orlacher Bachs sowie zu den verursachten Schäden beleuchtet.
Die Region war Zentrum extremer Regenfälle in der Größenordnung von 100 mm innerhalb von 2 Stunden. Das 6 km² kleine Einzugsgebiet hat eine sehr schnelle Reaktionszeit, zumal bei vorgesättigtem Boden. Im steilen Bachtal haben mehrere kleinere und größere Hangrutschungen über 8000 m³ Geröll, Schutt und Schwemmholz in das Gewässer eingetragen und möglicherweise kurzzeitige Aufstauungen und Durchbrüche verursacht. Neben den großen Wassermengen mit einer Abflussspitze in einer Größenordnung von 100 m³/s hat gerade die Geschiebefracht zu großen Schäden an den Gebäuden entlang des Bachlaufs in Braunsbach geführt.
The propagation of a seismic rupture on a fault introduces spatial variations in the seismic wave field surrounding the fault. This directivity effect results in larger shaking amplitudes in the rupture propagation direction. Its seismic radiation pattern also causes amplitude variations between the strike-normal and strike-parallel components of horizontal ground motion. We investigated the landslide response to these effects during the 2016 Kumamoto earthquake (M-w 7.1) in central Kyushu (Japan). Although the distribution of some 1500 earthquake-triggered landslides as a function of rupture distance is consistent with the observed Arias intensity, the landslides were more concentrated to the northeast of the southwest-northeast striking rupture. We examined several landslide susceptibility factors: hillslope inclination, the median amplification factor (MAF) of ground shaking, lithology, land cover, and topographic wetness. None of these factors sufficiently explains the landslide distribution or orientation (aspect), although the landslide head scarps have an elevated hillslope inclination and MAF. We propose a new physics-based ground-motion model (GMM) that accounts for the seismic rupture effects, and we demonstrate that the low-frequency seismic radiation pattern is consistent with the overall landslide distribution. Its spatial pattern is influenced by the rupture directivity effect, whereas landslide aspect is influenced by amplitude variations between the fault-normal and fault-parallel motion at frequencies < 2 Hz. This azimuth dependence implies that comparable landslide concentrations can occur at different distances from the rupture. This quantitative link between the prevalent landslide aspect and the low-frequency seismic radiation pattern can improve coseismic landslide hazard assessment.
Flash floods and debris flows are iconic hazards inmountainous regions with steep relief, high rainfall intensities, rapid snowmelt events, and abundant sediments. The cuesta landscapes of southern Germany hardly come to mind when dealing with such hazards. A series of heavy rainstorms dumping up to 140mm in 2 h caused destructive flash floods and debris flows in May 2016. The most severe damage occurred in the Braunsbach municipality, which was partly buried by 42,000 m(3) of boulders, gravel, mud, and anthropogenic debris from the small catchment of Orlacher Bach (similar to 6 km(2)). We analysed this event by combining rainfall patterns, geological conditions, and geomorphic impacts to estimate an average sediment yield of 14,000 t/km(2) that mostly (similar to 95%) came from some 50 riparian landslides and channel-bed incision of similar to 2 m. This specific sediment yield ranks among the top 20% globally, while the intensity-duration curve of the rainstormis similarly in the upper percentile range of storms that had triggered landslides. Compared to similar-sized catchments in the greater region hit by the rainstorms, we find that the Orlacher Bach is above the 95th percentile in terms of steepness, storm-rainfall intensity, and topographic curvatures. The flash flood transported a sediment volume equal to as much as 20-40% of the Pleistocene sediment volume stored in the Orlacher Bach fan, andmay have had several predecessors in the Holocene. River control structures from 1903 and records of a debris flow in the 1920s in a nearby catchment indicate that the local inhabitants may have been aware of the debris-flow hazards earlier. Such recurring and destructive events elude flood-hazard appraisals in humid landscapes of gentle relief, and broaden mechanistic views of how landslides and debris flows contribute to shaping small and deeply cut tributaries in the southern Germany cuesta landscape.
Quantitative estimates of sea-level rise in the Mediterranean Basin become increasingly accurate thanks to detailed satellite monitoring. However, such measuring campaigns cover several years to decades, while longer-term sea-level records are rare for the Mediterranean. We used a data archeological approach to reanalyze monthly mean sea-level data of the Antalya-I (1935–1977) tide gauge to fill this gap. We checked the accuracy and reliability of these data before merging them with the more recent records of the Antalya-II (1985–2009) tide gauge, accounting for an eight-year hiatus. We obtain a composite time series of monthly and annual mean sea levels spanning some 75 years, providing the longest record for the eastern Mediterranean Basin, and thus an essential tool for studying the region's recent sea-level trends. We estimate a relative mean sea-level rise of 2.2 ± 0.5 mm/year between 1935 and 2008, with an annual variability (expressed here as the standard deviation of the residuals, σresiduals = 41.4 mm) above that at the closest tide gauges (e.g., Thessaloniki, Greece, σresiduals = 29.0 mm). Relative sea-level rise accelerated to 6.0 ± 1.5 mm/year at Antalya-II; we attribute roughly half of this rate (~3.6 mm/year) to tectonic crustal motion and anthropogenic land subsidence. Our study highlights the value of data archeology for recovering and integrating historic tide gauge data for long-term sea-level and climate studies.
Reconciling the paths of extreme rainfall with those of typhoons remains difficult despite advanced forecasting techniques. We use complex networks defined by a nonlinear synchronization measure termed event synchronization to track extreme rainfall over the Japanese islands. Directed networks objectively record patterns of heavy rain brought by frontal storms and typhoons but mask out contributions of local convective storms. We propose a radial rank method to show that paths of extreme rainfall in the typhoon season (August-November, ASON) follow the overall southwest-northeast motion of typhoons and mean rainfall gradient of Japan. The associated eye-of-the-typhoon tracks deviate notably and may thus distort estimates of heavy typhoon rainfall. We mainly found that the lower spread of rainfall tracks in ASON may enable better hindcasting than for westerly-fed frontal storms in June and July.
