Search Results - "Fischer, Svenja"
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Snow-influenced floods are more strongly connected in space than purely rainfall-driven floods
Published in Environmental research letters (01-10-2022)“…Widespread floods that affect several catchments are associated with large damages and costs. To improve flood protection, a better understanding of the…”
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2
Temporal changes in the frequency of flood types and their impact on flood statistics
Published in Journal of hydrology: X (01-01-2024)“…[Display omitted] •Application of a change-point test to detect changes in the frequency of flood types.•Attribution of changes to flood-generating…”
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3
Regionalisation of flood frequencies based on flood type-specific mixture distributions
Published in Journal of hydrology: X (01-12-2021)“…•Derivation of flood-type-specific hydrologically similar regions.•Type-specific selection of catchment attributes to represent the flood-generation…”
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4
A statistics-based automated flood event separation
Published in Journal of hydrology: X (01-01-2021)“…•An automated event separation based on a moving-window variance is proposed.•The method delivers a reasonable number of flood events per year.•The method does…”
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5
On the temporal variability of widespread rain-on-snow floods
Published in Meteorologische Zeitschrift (Berlin, Germany : 1992) (04-08-2020)“…Floods which affect several macro-scale river basins simultaneously can cause devastating damage. Future flood-risk assessment depends significantly on the…”
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6
Impaired Immune Response to SARS-CoV-2 Vaccination in Dialysis Patients and in Kidney Transplant Recipients
Published in Kidney360 (30-09-2021)“…Patients with kidney failure on dialysis or after renal transplantation have a high risk for severe COVID-19 infection, and vaccination against SARS-CoV-2 is…”
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7
Incorporating historical flood events in type-based statistics
Published in Journal of hydrology (Amsterdam) (01-06-2024)“…•Incorporation of historical flood events in type-based statistics by considering the flood genesis.•Comparison of partial probability weighted moments and…”
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8
A seasonal mixed-POT model to estimate high flood quantiles from different event types and seasons
Published in Journal of applied statistics (18-11-2018)“…Flood events can be caused by several different meteorological circumstances. For example, heavy rain events often lead to short flood events with high peaks,…”
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9
A New Unsupervised Learning Method to Assess Clusters of Temporal Distribution of Rainfall and Their Coherence with Flood Types
Published in Water resources research (01-05-2020)“…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…”
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10
Generalized ordinal patterns allowing for ties and their applications in hydrology
Published in Computational statistics & data analysis (01-07-2022)“…When using ordinal patterns, which describe the ordinal structure within a data vector, the problem of ties appears permanently. So far, model classes were…”
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11
Impact of catchment and climate attributes on flood generating processes and their effect on flood statistics
Published in Journal of hydrology (Amsterdam) (01-01-2025)“…[Display omitted] •Flood events classified for New Zealand according to their hydrograph shape.•Key drivers determining flood types: rainfall variability and…”
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Spatio-temporal consideration of the impact of flood event types on flood statistic
Published in Stochastic environmental research and risk assessment (01-09-2020)“…Flood events can have very different generating processes. Floods may originate from high intensity rainfall, long-duration rainfall or snowmelt. Other…”
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13
A distribution-free ordinal classification of floods based on moments
Published in Hydrological sciences journal (18-08-2018)“…Classification of floods is often based on return periods of their peaks estimated from probability distributions and hence depends on assumptions. The choice…”
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14
Characterisation of seasonal flood types according to timescales in mixed probability distributions
Published in Journal of hydrology (Amsterdam) (01-08-2016)“…•Usage of flood timescale to distinguish between short and long flood events.•Development of a new mixing model to consider winter, short and long summer…”
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15
Robust flood statistics: comparison of peak over threshold approaches based on monthly maxima and TL-moments
Published in Hydrological sciences journal (17-02-2016)“…Flood quantile estimation based on partial duration series (peak over threshold, POT) represents a noteworthy alternative to the classical annual maximum…”
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Detecting Flood‐Rich and Flood‐Poor Periods in Annual Peak Discharges Across Europe
Published in Water resources research (01-07-2020)“…This paper proposes a method from Scan statistics for identifying flood‐rich and flood‐poor periods (i.e., anomalies) in flood discharge records. Exceedances…”
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17
Multivariate motion patterns and applications to rainfall radar data
Published in Stochastic environmental research and risk assessment (01-04-2024)“…The classification of movement in space is one of the key tasks in environmental science. Various geospatial data such as rainfall or other weather data, data…”
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18
Timescale-based flood typing to estimate temporal changes in flood frequencies
Published in Hydrological sciences journal (18-11-2019)“…The flood peak is the dominating characteristic in nearly all flood-statistical analyses. Contrary to the general assumptions of design flood estimation, the…”
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Comment on the paper of Willems, P.: Multidecadal oscillatory behaviour of rainfall extremes in Europe. Published in: Climatic Change 120 (4), p. 931–944
Published in Climatic change (01-05-2015)“…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…”
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Ordinal pattern dependence between hydrological time series
Published in Journal of hydrology (Amsterdam) (01-05-2017)“…•Uses the ordinal pattern approach to detect coherences between gauges.•Usage for the detection of homogeneous groups.•Relation to climate scenarios. Ordinal…”
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