Svenja Fischer

Svenja Fischer
Ruhr-Universität Bochum | RUB · Department of Civil and Environmental Engineering

Dr. rer. nat.

About

39
Publications
8,116
Reads
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252
Citations
Introduction
After completing my M.Sc. in mathematics I decided to work in a more applied science and to find useful applications for my mathematical theory. This lead to me the field of hydrology, where I do research in flood statistics at the Institute of Hydrology in Bochum since 2013. Combining the methodological aspects and the application, I did my PhD in Statistics and now extend classical flood statistics by considering the origins of floods. In our research unit I develop new techniques for flood typology and stochastic-deterministic event generators.
Additional affiliations
July 2020 - present
Ruhr-Universität Bochum
Position
  • Project Manager
Description
  • Project Leader of DFG-funded research unit SPATE
October 2017 - June 2020
Ruhr-Universität Bochum
Position
  • PostDoc Position
Description
  • Post-Doc and coordinator of the DFG funded research group SPATE
July 2013 - September 2017
Ruhr-Universität Bochum
Position
  • Research Assistant
Education
January 2020 - November 2021
Ruhr-Universität Bochum
Field of study
  • Stochastic Hydrology
October 2016 - August 2017
Technische Universität Dortmund
Field of study
  • Statistics
October 2011 - September 2013
Ruhr-Universität Bochum
Field of study
  • Mathematics

Publications

Publications (39)
Article
Full-text available
Generalized linear (GL-) statistics are defined as functionals of an U-quantile process and unify different classes of statistics such as U-statistics and L-statistics. We derive a central limit theorem for GL- statistics of strongly mixing sequences and arbitrary dimension of the un- derlying kernel. For this purpose we establish a limit theorem f...
Article
When flood statistics are based on annual maximum series (AMS), the sample often contains flood peaks, which differ in their genesis. If the ratios among event types change over the range of observations, the extrapolation of a probability distribution function (pdf) can be dominated by a majority of events that belong to a certain flood type. If t...
Article
The flood peak is the dominating characteristic in nearly all flood-statistical analyses. Contrary to the general assumptions of design flood estimation, the peak is not closely related to other flood characteristics. Differentiation of floods into types provides a more realistic view. Often different parts of the probability distribution function...
Article
Full-text available
The classification of characteristics of flood events, like peak, volume, duration and baseflow components is essential for many hydrological applications such as multivariate flood statistics, the validation of rainfall-runoff models and comparative hydrology in general. The basis for estimations of these characteristics is formed by flood event s...
Article
Full-text available
In contrast to the basic assumption of a homogeneous population underlying common approaches to flood frequency analysis, flood events often arise from different runoff‐generating processes. In many large river basins, the diversity of these processes within tributary basins and the superposition of their flood waves increase the complexity of stat...
Conference Paper
Full-text available
Earth system processes have complex physics and are dynamically interlinked, making modelling and predictions difficult. In particular, current challenges for hydroclimatic systems are in understanding nonstationarity and heterogeneity driven by climatic and human influences. Hence, studying the spatial and temporal occurrences and dependencies of...
Article
Full-text available
Statistical distributions of flood peak discharge often show heavy tail behavior, that is, extreme floods are more likely to occur than would be predicted by commonly used distributions that have exponential asymptotic behavior. This heavy tail behavior may surprise flood managers and citizens, as human intuition tends to expect light tail behavior...
Conference Paper
Full-text available
Open and free data underpin a new way of thinking about what is required to advance scientific discoveries. The fourth paradigm for hydrology, i.e. data-intensive science, can only lead to transformative science and groundbreaking findings if data is freely accessible. Open datasets are available online, are accessible in machine-readable formats (...
Article
When using ordinal patterns, which describe the ordinal structure within a data vector, the problem of ties appears permanently. So far, model classes were used which do not allow for ties; randomization has been another attempt to overcome this problem. Often, time periods with constant values even have been counted as times of monotone increase....
Preprint
Full-text available
Extreme value analysis seeks to assign probabilities to events which deviate significantly from the mean and is thus widely employed in disciplines dealing with natural hazards. In terms of extreme sea levels (ESLs), these probabilities help to define coastal flood risk which guides the design of coastal protection measures. While tide gauge and ot...
Preprint
Full-text available
The use of the annual maximum series for flood frequency analyses limits the considered information to one event per year and one sample that is assumed to be homogeneous. However, flood may have different generating processes, such as snowmelt, heavy rainfall or long-duration rainfall, which makes the assumption of homogeneity questionable. Flood...
Article
Full-text available
The regionalisation of flood frequencies is a precondition for the estimation of flood statistics for ungauged basins. It is often based on either the concept of hydrological similarity of catchments or spatial proximity. Similarity is usually defined by comparing catchment attributes or distances. Here, we apply flood types in regionalisation dire...
Book
Full-text available
Eine HKC Projektgruppe hat praxisorientierte Hinweise zum Umgang mit hydrologischen Belastungsgrößen zur Ermittlung von Hochwassergefahren in einem Werkstattbericht erarbeitet. In Zeiten des Klimawandels nehmen die Starkniederschläge messbar zu. Somit verändern sich auch innerhalb von kurzer Zeit die Werte für die Wiederkehrwahrscheinlichkeiten. Da...
Article
Flood events may be caused by different runoff generating processes and can be differentiated in their genesis by the application of flood types. Additionally, the spatial interaction of catchments can play a crucial role in the flood generation. Flood wave superposition can increase the flood peak and volume downstream. The magnitude of increase a...
Article
The optimization and extension of existing gauging networks is a challenging task, which can be done under consideration of many different aspects. One possibility is to maximize the obtained information on regional hydrological characteristics by new gauges compared to existing ones. For this, information theory approaches are most suitable. Here,...
Article
Full-text available
This paper proposes a method from Scan statistics for identifying flood-rich and flood-poor periods (i.e., anomalies) in flood discharge records. Exceedances of quantiles with 2-, 5-, and 10-year return periods are used to identify periods with unusually many (or few) threshold exceedances with respect to the reference condition of independent and...
Article
Full-text available
Several factors have an impact on the generation of floods, for example, antecedent moisture conditions and the shape of the catchment. A very important factor is the event rainfall, especially its temporal distribution. However, the categorization of temporal distributions is riddled with uncertainty, due to a priori assumptions on distribution ty...
Article
Full-text available
Floods which affect several macro-scale river basins simultaneously can cause devastating damage. Future flood-risk assessment depends significantly on the knowledge about the atmospheric conditions leading to floods and external climate drivers. Nonetheless, only a few studies have investigated widespread floods, their occurrence frequency, and th...
Chapter
Hochwasser richten enorme Schäden an. Trotz jahrzehntelanger Forschung überraschen sie uns immer noch in ihrer Wirkung, und ein besseres Verständnis ist von hoher humanitärer und monetärer Bedeutung. Statistik hilft mit Modellen und Verfahren zur Analyse des Risikos von Hochwasser und allgemeiner extremer Naturereignisse. Wir berichten über den Sta...
Article
Flood events can have very different generating processes. Floods may originate from high intensity rainfall, long-duration rainfall or snowmelt. Other factors, e.g. initial soil moisture conditions, also affect the spatial and temporal characteristics of floods. Hence, a typology for floods is often used to classify floods according to their runof...
Article
Flood events can have very different generating processes. Floods may originate from high intensity rainfall, long-duration rainfall or snowmelt. Other factors, e.g. initial soil moisture conditions, also affect the spatial and temporal characteristics of floods. Hence, a typology for floods is often used to classify floods according to their runof...
Article
Full-text available
A wide variety of processes controls the time of occurrence, duration, extent, and severity of river floods. Classifying flood events by their causative processes may assist in enhancing the accuracy of local and regional flood frequency estimates and support the detection and interpretation of any changes in flood occurrence and magnitudes. This p...
Article
Full-text available
Classification of floods is often based on return periods of their peaks estimated from probability distributions and hence depends on assumptions. The choice of an appropriate distribution function and parameter estimation are often connected with high uncertainties. In addition, limited length of data series and the stochastic characteristic of t...
Article
Full-text available
Die Schätzung von Niederschlagsereignissen für gegebene Dauerstufen und Jährlichkeiten ist die Grundlage vieler wasserbaulicher Bemessungen der Kommunen, Länder und Verbände und ist durch das Merkblatt DWA A-531 geregelt. Dieses sieht eine Anpassung über die zweiparametrige Gumbel-Verteilung mit anschließendem Ausgleich über alle Dauerstufen vor. D...
Article
Full-text available
Flood events can be caused by several different meteorological circumstances. For example, heavy rain events often lead to short flood events with high peaks, whereas snowmelt normally results in events of very long duration with a high volume. Both event types have to be considered in the design of flood protection systems. Unfortunately, all thes...
Thesis
Full-text available
Robust statistics and the use of robust estimators have come more and more into focus during the last couple of years. In the context of flood statistics, robust estimation methods are used to obtain stable estimations of e.g. design floods. These are estimations that do not change from one year to another just because one large flood occurred. A...
Article
Full-text available
Driven by the EU-Flood Directive, flood risk management became one of the focusing points of water policy. Flood risk means the combination of the probability of a flood event with its adverse consequences. Unfortunately, the consequences of a changing environment on floods are hidden by high uncertainties about the stochastic behavior of flood ind...
Article
Full-text available
The class of Generalized $L$-statistics ($GL$-statistics) unifies a broad class of different estimators, for example scale estimators based on multivariate kernels. $GL$-statistics are functionals of $U$-quantiles and therefore the dimension of the kernel of the $U$-quantiles determines the kernel dimension of the estimator. Up to now only few resu...
Article
Ordinal patterns provide a method to measure dependencies between time series. In contrast to classical correlation measures like the Pearson correlation coefficient they are able to measure not only linear correlation but also non-linear correlation even in the presence of non-stationarity. Hence, they are a noteworthy alternative to the classical...
Article
Full-text available
In widely-used flood statistics, annual maximum discharges are generally used as the basis for the calculation of quantiles as design floods. These contain summer as well as winter events, each with a different genesis. Seasonal statistics offer one possibility of coping with this. It is the goal of this article to expand the classical seasonal sta...
Article
Full-text available
Ordinal patterns provide a method to measure correlation between time series. In contrast to classical correlation measures like the Pearson correlation coefficient they are able to measure not only linear correlation but also non-linear correlation even in the presence of non-stationarity. Hence, they are a noteworthy alternative to the classical...
Article
Full-text available
Summarizing a series of rainfall events for different duration levels by their annual maxima provides valuable information. These statistics are e.g. the design base of urban drainage systems. Investigating an entire set of duration levels, the dependence among them has to be taken into account. We propose an approach where a set of generalized ext...
Article
Flood quantile estimation based on partial duration series (peak over threshold, POT) represents a noteworthy alternative to the classical annual maximum approach since it enlarges the available information spectrum. Here the POT approach is discussed with reference to its benefits in increasing the robustness of flood quantile estimations. The cla...
Article
Full-text available
We compare several estimators, which are commonly used in hydrology, for the pa- rameters of the distribution of flood series, like the Maximum-Likelihood estimator or L-Moments, with the robust estimators Trimmed L-Moments and Minimum Distances. Our objective is estimation of the 99%- or 99.9%-quantile of an underlying Gumbel or Generalized Extrem...
Article
Full-text available
In German speaking countries, specific runoff values (quotients of discharge and belonging catchment areas) are widely used for regionalization. In many cases, a nonlinear regression is applied to describe the relationship between the specific runoff and the size of watersheds. The problem of this approach consists in the multiple use of the area:...
Article
Full-text available
In his article Willems (Clim Chang 120(4):931-944, 2013) proposed a methodology to analyse extremes in rainfall series. When applying it to artificially generated, non-cyclic random variables we were able to detect cyclic behavior. Therefor we had a closer look on the methodology. Here we discuss our considerations, why this method generates cycles...
Article
Full-text available
Generalized linear (GL-) statistics are defined as functionals of an U-quantile process and unify different classes of statistics such as U-statistics and L-statistics. We derive a central limit theorem for GL-statistics of strongly mixing sequences and arbitrary dimension of the underlying kernel. For this purpose we establish a limit theorem for...
Article
Full-text available
Partial duration series (peak over threshold) form a considerable alternative to the classical annual maximum approach since they enlarge the information spectrum. The classical POT approach is based on a Poisson distribution for the annual number of exceedances although this is can be questionable in some cases. Therefore two different distributio...

Projects

Projects (8)
Project
At EGU 2021, we will convene a new session that focus on clustering in hydrology. Please find the session description below. We are looking forward to many interesting abstracts and invite everyone to join us in the session. The abstract deadline is January 13th! https://meetingorganizer.copernicus.org/EGU21/session/38747 Clustering analysis is a well-known exploratory task for partitioning databases into smaller groups based on patterns or inherent similarity in data. Clustering methods have found many applications in many disciplines due to growing interest in unravelling the hidden and meaningful patterns that exist in large amounts of available data. Due to its unsupervised nature, clustering data is a complex task that requires attention to optimal choice alternatives regarding methods, model parameters and performance metrics. However, the suitability of clustering algorithms depends on their application. Different methods and approaches co-exist in a large pool. The challenge is to obtain application-specific insights while enabling a practical knowledge perspective for benchmarking. There are still research gaps in the wider clustering literature, and hydrology-specific knowledge is fragmented and difficult to find. In hydrology, unsupervised classification of multivariate data is often used but typically in rather basic forms and as an intermediate step. Recently, the number of studies using clustering methods has rapidly increased. However, a clear and integrative vision on clustering algorithms is currently missing. Despite advances in other fields, the scope of hydrological studies is limited. Knowledge exchange on hydrology-specific ways of dealing with the issues related to clustering is needed. The aim of this session is to explore theoretical and conceptual underpinnings of well-known clustering methods, offer fresh insights into applications of new clustering methods, gain thorough understanding of pearls and pitfalls in clustering algorithms, provide a critical overview of the main challenges associated with data clustering process, discuss major research trends and highlight open research issues. It is expected to improve scientific practice within the hydrology domain, and foster scientific debate on benchmarking in cluster analysis. We invite contributions (case studies, comparative analyses, theoretical experiments) on a wide range of topics including (but not limited to): hard vs fuzzy clustering; comparison of clustering algorithms; benchmarking in cluster analysis; clustering as an exploratory tool vs clustering as a hypothesis testing tool; determination of number of clusters; selecting variables to cluster upon; evaluation of clustering performance; alternative clustering methods (sequential, evolutionary, deep, ensemble, etc.) Share: https://meetingorganizer.copernicus.org/EGU21/session/38747
Project
Many environmental and hydrological problems are spatial or temporal, or both in nature. Spatio-temporal analysis allows identifying and explaining large-scale anomalies which are useful for understanding hydrological characteristics and subsequently predicting hydrological events. Temporal information is sometimes limited; spatial information, on the other hand has increased in recent years due technological advances including the availability of remote sensing data. This development has motivated new research efforts to include data in model representation and analysis. Statistics are in wide use in hydrology for example to estimate design events, forecast the risk and hazard of flood events, detect spatial or temporal clusters, model non-stationarity and changes and many more. Statistics are useful in the case when only few data are available but information for very rare events (extremes) or long time periods are needed. They are also helpful to detect changes and inconsistencies in the data and give a reliable statement on the significance. Moreover, temporal and spatial changes often lead to the violation of stationarity, a key assumption of many standard statistical approaches. This makes hydrological statistics interesting and challenging for so many researchers. Geostatistics is the discipline that investigates the statistics of spatially extended variables. Spatio-temporal analysis is at the forefront of geostatistical research these days, and its impact is expected to increase in the future. This trend will be driven by increasing needs to advance risk assessment and management strategies for extreme events such as floods and droughts, and to support both short and long-term water management planning. Current trends and variability of hydrological extremes call for spatio-temporal and/or geostatistical analysis to assess, predict, and manage water related and/or interlinked hazards. The aim of this session is to provide a platform and an opportunity to demonstrate and discuss innovative applications and methodologies of spatio-temporal analysis in a hydrological (hydrometeorological?) context. The session is targeted at both hydrologists and statisticians interested in the spatial and temporal analysis of hydrological events, extremes, and related hazards, and it aims to provide a forum for researchers from a variety of fields to effectively communicate their research. This session is co-sponsered by ICSH-STAHY (IAHS).
Project
Statistics are in wide use in hydrology for example to estimate design events, forecast the risk and hazard of flood events, detect spatial or temporal clusters, model non-stationarity and changes and many more. Statistics are useful in the case when only few data are available but information for very rare events (extremes) or long time periods are needed. They are also helpful to detect changes and inconsistencies in the data and give a reliable statement on the significance. The problems that statisticians in hydrology have to face are a very limited data base and the necessity to estimate quantiles that are up to now beyond the observation horizon. Moreover, temporal and spatial changes (e.g., in land use) often lead to the violation of stationarity, a key assumption of many standard statistical approaches. This makes hydrological statistics interesting and challenging for so many researchers. Although the origins of flood statistics now lie more than 70 years in the past, it is still a basic tool for many practitioners but also a field of many novel research and development. Especially changes in climate and/or anthropogenic circumstances demand new approaches to estimate floods, especially in providing stronger links between statistics and hydrological processes. But also the development of new techniques in the field of theoretical statistics and probability theory like new robust change-point tests or limit theorems on long-range dependent data give hydrologists the possibility to discover new applications. Moreover, the larger amount and better space and time resolution of hydrological data demand new models and techniques to handle the enlarged information. This session aims to bring together researchers and practitioners to discuss novel approaches and recent developments in flood statistics. Statisticians as well as hydrologists and meteorologists and every researcher interested in statistics is invited to present their theoretical results or a practical application of estimation methods, statistical models or test and detection methods focusing on the extremes of hydrological data. The topics are given in the following non-exclusive list: 1. New parametric and non-parametric estimation techniques 2. Seasonal and/or flood-type specific statistical models to estimate flood quantiles 3. Tests for non-stationarity and changes of flood series 4. Models to consider non-stationarity 5. Statistics for long- and short-range dependent data 6. Statistical approaches for clustering and detection of spatial dependence 7. Regionalisation of flood statistics 8. Links of flood statistics to hydrological processes