57385
2022
2022
eng
1825
1831
7
4
112
article
Seismological Society of America
El Cerito, Calif.
1
2022-04-27
2022-04-27
--
A note on the estimation of the maximum possible earthquake magnitude based on extreme value theory for the Groningen Gas Field
Extreme value statistics is a popular and frequently used tool to model the occurrence of large earthquakes. The problem of poor statistics arising from rare events is addressed by taking advantage of the validity of general statistical properties in asymptotic regimes. In this note, I argue that the use of extreme value statistics for the purpose of practically modeling the tail of the frequency-magnitude distribution of earthquakes can produce biased and thus misleading results because it is unknown to what degree the tail of the true distribution is sampled by data. Using synthetic data allows to quantify this bias in detail. The implicit assumption that the true M-max is close to the maximum observed magnitude M-max,M-observed restricts the class of the potential models a priori to those with M-max = M-max,M-observed + Delta M with an increment Delta M approximate to 0.5... 1.2. This corresponds to the simple heuristic method suggested by Wheeler (2009) and labeled :M-max equals M-obs plus an increment." The incomplete consideration of the entire model family for the frequency-magnitude distribution neglects, however, the scenario of a large so far unobserved earthquake.
The bulletin of the Seismological Society of America : BSSA
10.1785/0120210307
0037-1106
1943-3573
outputup:dataSource:WoS:2022
WOS:000837068500003
Zoller, G (corresponding author), Univ Potsdam, Inst Math, Potsdam, Golm, Germany., zoeller@uni-potsdam.de
Collaborative Research Centre 1294 project, B04, of the German Research; Society (DFG)
Zöller, Gert
2023-01-09T10:09:21+00:00
sword
importub
filename=package.tar
995c3b14b5cbbbe57a692bdc84c18e6a
419141-9
2065447-9
false
true
Gert Zöller
Geowissenschaften
Institut für Mathematik
Referiert
Import
56417
2020
2020
eng
12
9
125
article
American Geophysical Union
Washington
1
2020-09-07
2020-09-07
--
Is Coulomb stress the best choice for aftershock forecasting?
The Coulomb failure stress (CFS) criterion is the most commonly used method for predicting spatial distributions of aftershocks following large earthquakes. However, large uncertainties are always associated with the calculation of Coulomb stress change. The uncertainties mainly arise due to nonunique slip inversions and unknown receiver faults; especially for the latter, results are highly dependent on the choice of the assumed receiver mechanism. Based on binary tests (aftershocks yes/no), recent studies suggest that alternative stress quantities, a distance-slip probabilistic model as well as deep neural network (DNN) approaches, all are superior to CFS with predefined receiver mechanism. To challenge this conclusion, which might have large implications, we use 289 slip inversions from SRCMOD database to calculate more realistic CFS values for a layered half-space and variable receiver mechanisms. We also analyze the effect of the magnitude cutoff, grid size variation, and aftershock duration to verify the use of receiver operating characteristic (ROC) analysis for the ranking of stress metrics. The observations suggest that introducing a layered half-space does not improve the stress maps and ROC curves. However, results significantly improve for larger aftershocks and shorter time periods but without changing the ranking. We also go beyond binary testing and apply alternative statistics to test the ability to estimate aftershock numbers, which confirm that simple stress metrics perform better than the classic Coulomb failure stress calculations and are also better than the distance-slip probabilistic model.
Journal of geophysical research : Solid earth
10.1029/2020JB019553
2169-9313
2169-9356
outputup:dataSource:WoS:2020
e2020JB019553
WOS:000577119500046
Sharma, S (corresponding author), Univ Potsdam, Inst Geosci, Potsdam, Germany.; Sharma, S (corresponding author), GFZ German Res Ctr Geosci, Potsdam, Germany., sharma@gfz-potsdam.de
DFG - Research Training Group "NatRiskChange"
Sharma, Shubham
2022-10-21T07:48:54+00:00
sword
importub
filename=package.tar
8ef1211d300c02d8f4c31113e9e8ce6a
161666-3
2016813-5
false
true
CC-BY - Namensnennung 4.0 International
Shubham Sharma
Sebastian Hainzl
Gert Zöller
Matthias Holschneider
Mathematik
Geowissenschaften
Institut für Mathematik
Institut für Geowissenschaften
Referiert
Import
Hybrid Open-Access
47397
2020
2020
eng
999
1023
27
968
postprint
1
2020-08-05
2020-08-05
--
Flash floods versus river floods
River floods are among the most damaging natural hazards that frequently occur in Germany. Flooding causes high economic losses and impacts many residents. In 2016, several southern German municipalities were hit by flash floods after unexpectedly severe heavy rainfall, while in 2013 widespread river flooding had occurred. This study investigates and compares the psychological impacts of river floods and flash floods and potential consequences for precautionary behaviour. Data were collected using computer-aided telephone interviews that were conducted among flood-affected households around 9 months after each damaging event. This study applies Bayesian statistics and negative binomial regressions to test the suitability of psychological indicators to predict the precaution motivation of individuals. The results show that it is not the particular flood type but rather the severity and local impacts of the event that are crucial for the different, and potentially negative, impacts on mental health. According to the used data, however, predictions of the individual precaution motivation should not be based on the derived psychological indicators – i.e. coping appraisal, threat appraisal, burden and evasion – since their explanatory power was generally low and results are, for the most part, non-significant. Only burden reveals a significant positive relation to planned precaution regarding weak flash floods. In contrast to weak flash floods and river floods, the perceived threat of strong flash floods is significantly lower although feelings of burden and lower coping appraisals are more pronounced. Further research is needed to better include psychological assessment procedures and to focus on alternative data sources regarding floods and the connected precaution motivation of affected residents.
Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe
a comparison of psychological impacts and implications for precautionary behaviour
10.25932/publishup-47397
urn:nbn:de:kobv:517-opus4-473974
1866-8372
Natural Hazards and Earth System Sciences 20 (2020) 999–1023 DOI:10.5194/nhess-20-999-2020
<a href="http://publishup.uni-potsdam.de/47396">Bibliographieeintrag der Originalveröffentlichung/Quelle</a>
CC-BY - Namensnennung 4.0 International
Jonas Laudan
Gert Zöller
Annegret Henriette Thieken
Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe
968
eng
uncontrolled
private households
eng
uncontrolled
risk perceptions
eng
uncontrolled
extreme rainfall
eng
uncontrolled
health
eng
uncontrolled
mitigation
eng
uncontrolled
Germany
eng
uncontrolled
people
eng
uncontrolled
damage
eng
uncontrolled
preparedness
eng
uncontrolled
residents
Geografie, Reisen
open_access
Referiert
Institut für Umweltwissenschaften und Geographie
Green Open-Access
Universität Potsdam
https://publishup.uni-potsdam.de/files/47397/pmnr968.pdf
47396
2020
2019
eng
999
1023
25
20
article
European Geophysical Society
Katlenburg-Lindau
1
2020-04-14
2019-12-31
--
Flash floods versus river floods
River floods are among the most damaging natural hazards that frequently occur in Germany. Flooding causes high economic losses and impacts many residents. In 2016, several southern German municipalities were hit by flash floods after unexpectedly severe heavy rainfall, while in 2013 widespread river flooding had occurred. This study investigates and compares the psychological impacts of river floods and flash floods and potential consequences for precautionary behaviour. Data were collected using computer-aided telephone interviews that were conducted among flood-affected households around 9 months after each damaging event. This study applies Bayesian statistics and negative binomial regressions to test the suitability of psychological indicators to predict the precaution motivation of individuals. The results show that it is not the particular flood type but rather the severity and local impacts of the event that are crucial for the different, and potentially negative, impacts on mental health. According to the used data, however, predictions of the individual precaution motivation should not be based on the derived psychological indicators – i.e. coping appraisal, threat appraisal, burden and evasion – since their explanatory power was generally low and results are, for the most part, non-significant. Only burden reveals a significant positive relation to planned precaution regarding weak flash floods. In contrast to weak flash floods and river floods, the perceived threat of strong flash floods is significantly lower although feelings of burden and lower coping appraisals are more pronounced. Further research is needed to better include psychological assessment procedures and to focus on alternative data sources regarding floods and the connected precaution motivation of affected residents.
Natural Hazards and Earth System Sciences
a comparison of psychological impacts and implications for precautionary behaviour
10.5194/nhess-20-999-2020
1684-9981
Universität Potsdam
PA 2020_047
2000.00
<a href="https://doi.org/10.25932/publishup-47397">Zweitveröffentlichung in der Schriftenreihe Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe ; 968</a>
CC-BY - Namensnennung 4.0 International
Jonas Laudan
Gert Zöller
Annegret Henriette Thieken
eng
uncontrolled
private households
eng
uncontrolled
risk perceptions
eng
uncontrolled
extreme rainfall
eng
uncontrolled
health
eng
uncontrolled
mitigation
eng
uncontrolled
Germany
eng
uncontrolled
people
eng
uncontrolled
damage
eng
uncontrolled
preparedness
eng
uncontrolled
residents
Geografie, Reisen
Referiert
Publikationsfonds der Universität Potsdam
Institut für Umweltwissenschaften und Geographie
Gold Open-Access
56406
2020
2020
eng
19
9
56
article
American Geophysical Union
Washington
1
2020-09-01
2020-09-01
--
Probabilistic flood loss models for companies
Flood loss modeling is a central component of flood risk analysis. Conventionally, this involves univariable and deterministic stage-damage functions. Recent advancements in the field promote the use of multivariable and probabilistic loss models, which consider variables beyond inundation depth and account for prediction uncertainty. Although companies contribute significantly to total loss figures, novel modeling approaches for companies are lacking. Scarce data and the heterogeneity among companies impede the development of company flood loss models. We present three multivariable flood loss models for companies from the manufacturing, commercial, financial, and service sector that intrinsically quantify prediction uncertainty. Based on object-level loss data (n = 1,306), we comparatively evaluate the predictive capacity of Bayesian networks, Bayesian regression, and random forest in relation to deterministic and probabilistic stage-damage functions, serving as benchmarks. The company loss data stem from four postevent surveys in Germany between 2002 and 2013 and include information on flood intensity, company characteristics, emergency response, private precaution, and resulting loss to building, equipment, and goods and stock. We find that the multivariable probabilistic models successfully identify and reproduce essential relationships of flood damage processes in the data. The assessment of model skill focuses on the precision of the probabilistic predictions and reveals that the candidate models outperform the stage-damage functions, while differences among the proposed models are negligible. Although the combination of multivariable and probabilistic loss estimation improves predictive accuracy over the entire data set, wide predictive distributions stress the necessity for the quantification of uncertainty.
Water resources research
10.1029/2020WR027649
0043-1397
1944-7973
outputup:dataSource:WoS:2020
e2020WR027649
WOS:000578452200019
Schoppa, L (corresponding author), GFZ German Res Ctr Geosci, Sect Hydrol 4 4, Potsdam, Germany.; Schoppa, L (corresponding author), Univ Potsdam, Inst Environm Sci & Geog, Potsdam, Germany., lukas.schoppa@gfz-potsdam.de
Deutsche Forschungsgemeinschaft (DFG)German Research Foundation (DFG); [GRK 2043]; German Ministry for Education and Research (BMBF)Federal; Ministry of Education & Research (BMBF) [DFNK 01SFR9969/5, Flood 2013; 13N13017]
Schoppa, Lukas
2022-10-21T06:16:14+00:00
sword
importub
filename=package.tar
38996806d97fe1e526565b4799f5b370
2029553-4
5564-5
false
true
CC-BY - Namensnennung 4.0 International
Lukas Schoppa
Tobias Sieg
Kristin Vogel
Gert Zöller
Heidi Kreibich
eng
uncontrolled
flood loss estimation
eng
uncontrolled
probabilistic modeling
eng
uncontrolled
companies
eng
uncontrolled
multivariable
eng
uncontrolled
models
Mathematik
Geowissenschaften
Institut für Mathematik
Institut für Geowissenschaften
Referiert
Import
Hybrid Open-Access
57770
2020
2020
eng
302
306
5
3
127
article
Wiley
Hoboken
1
2020-10-30
2020-10-30
--
Comment on: Wikelski, Martin; Müller, Uschi; Scocco, Paola; Catorci, Andrea; Desinov, Lev V.; Belyaev, Mikhail Y.; Keim, Daniel A.; Pohlmeier, Winfried; Fechteler, Gerhard; Mai, Martin P. : Potential short-term earthquake forecasting by farm animal monitoring. - Ethology. - 126 (2020), 9. - S. 931 - 941. -ISSN 0179-1613. - eISSN 1439-0310. - doi 10.1111/eth.13078
Based on an analysis of continuous monitoring of farm animal behavior in the region of the 2016 M6.6 Norcia earthquake in Italy, Wikelski et al., 2020; (Seismol Res Lett, 89, 2020, 1238) conclude that animal activity can be anticipated with subsequent seismic activity and that this finding might help to design a "short-term earthquake forecasting method." We show that this result is based on an incomplete analysis and misleading interpretations. Applying state-of-the-art methods of statistics, we demonstrate that the proposed anticipatory patterns cannot be distinguished from random patterns, and consequently, the observed anomalies in animal activity do not have any forecasting power.
Ethology
10.1111/eth.13105
0179-1613
1439-0310
outputup:dataSource:WoS:2021
WOS:000582961400001
Zoller, G (corresponding author), Univ Potsdam, Inst Math, Potsdam, Germany., zoeller@uni-potsdam.de
Zöller, Gert
2023-02-03T07:18:43+00:00
sword
importub
filename=package.tar
6272e0b17304081948490f651ea21ae2
2020221-0
false
true
CC-BY - Namensnennung 4.0 International
Gert Zöller
Sebastian Hainzl
Frederik Tilmann
Heiko Woith
Torsten Dahm
eng
uncontrolled
animal behavior
eng
uncontrolled
earthquake precursor
eng
uncontrolled
error diagram
eng
uncontrolled
prediction
eng
uncontrolled
randomness
eng
uncontrolled
statistics
Mathematik
Institut für Mathematik
Referiert
Import
Hybrid Open-Access
59120
2020
2020
eng
15
11
79
article
Springer
New York
1
2020-05-22
2020-05-22
--
Stress-based, statistical modeling of the induced seismicity at the Groningen gas field
Groningen is the largest onshore gas field under production in Europe. The pressure depletion of the gas field started in 1963. In 1991, the first induced micro-earthquakes have been located at reservoir level with increasing rates in the following decades. Most of these events are of magnitude less than 2.0 and cannot be felt. However, maximum observed magnitudes continuously increased over the years until the largest, significant event with ML=3.6 was recorded in 2014, which finally led to the decision to reduce the production. This causal sequence displays the crucial role of understanding and modeling the relation between production and induced seismicity for economic planing and hazard assessment. Here we test whether the induced seismicity related to gas exploration can be modeled by the statistical response of fault networks with rate-and-state-dependent frictional behavior. We use the long and complete local seismic catalog and additionally detailed information on production-induced changes at the reservoir level to test different seismicity models. Both the changes of the fluid pressure and of the reservoir compaction are tested as input to approximate the Coulomb stress changes. We find that the rate-and-state model with a constant tectonic background seismicity rate can reproduce the observed long delay of the seismicity onset. In contrast, so-called Coulomb failure models with instantaneous earthquake nucleation need to assume that all faults are initially far from a critical state of stress to explain the delay. Our rate-and-state model based on the fluid pore pressure fits the spatiotemporal pattern of the seismicity best, where the fit further improves by taking the fault density and orientation into account. Despite its simplicity with only three free parameters, the rate-and-state model can reproduce the main statistical features of the observed activity.
Environmental earth sciences
the Netherlands
10.1007/s12665-020-08941-4
1866-6280
1866-6299
outputup:dataSource:WoS:2020
252
WOS:000534881700001
Richter, G (corresponding author), Univ Potsdam, Inst Math, Potsdam, Germany.; Richter, G (corresponding author), GFZ German Res Ctr Geosci, Potsdam, Germany., gudrun@gfz-potsdam.de
BMBFFederal Ministry of Education & Research (BMBF) [03G0872D]; Deutsche; ForschungsgemeinschaftGerman Research Foundation (DFG) [SFB1294]
Richter, Gudrun
2023-05-03T06:07:01+00:00
sword
importub
filename=package.tar
56a29e30f8a23400b0f02111b1c20857
2493699-6
false
true
CC-BY - Namensnennung 4.0 International
Gudrun Richter
Sebastian Hainzl
Torsten Dahm
Gert Zöller
eng
uncontrolled
induced seismicity
eng
uncontrolled
modeling
eng
uncontrolled
statistical seismology
eng
uncontrolled
forecast
Geowissenschaften
Institut für Geowissenschaften
Referiert
Import
Hybrid Open-Access
48179
2019
2019
eng
11
10
article
Nature Publishing Group
London
1
--
2019-09-06
--
Forecasting the magnitude of the largest expected earthquake
The majority of earthquakes occur unexpectedly and can trigger subsequent sequences of events that can culminate in more powerful earthquakes. This self-exciting nature of seismicity generates complex clustering of earthquakes in space and time. Therefore, the problem of constraining the magnitude of the largest expected earthquake during a future time interval is of critical importance in mitigating earthquake hazard. We address this problem by developing a methodology to compute the probabilities for such extreme earthquakes to be above certain magnitudes. We combine the Bayesian methods with the extreme value theory and assume that the occurrence of earthquakes can be described by the Epidemic Type Aftershock Sequence process. We analyze in detail the application of this methodology to the 2016 Kumamoto, Japan, earthquake sequence. We are able to estimate retrospectively the probabilities of having large subsequent earthquakes during several stages of the evolution of this sequence.
Nature Communications
10.1038/s41467-019-11958-4
31492839
2041-1723
wos:2019
4051
WOS:000484599900001
Shcherbakov, R (reprint author), Univ Western Ontario, Dept Earth Sci, London, ON N6A 5B7, Canada.; Shcherbakov, R (reprint author), Univ Western Ontario, Dept Phys & Astron, London, ON N6A 3K7, Canada., rshcherb@uwo.ca
NSERCNatural Sciences and Engineering Research Council of Canada; Japan Society for the Promotion of ScienceMinistry of Education, Culture, Sports, Science and Technology, Japan (MEXT)Japan Society for the Promotion of Science [19H04073]; DFG Collaborative Research Centre 1294 (Data Assimilation-The seamless integration of data and models)
importub
2020-11-09T15:43:35+00:00
filename=package.tar
c4ad624ae4ad57426068059d649f4d6b
Robert Shcherbakov
Jiancang Zhuang
Gert Zöller
Yosihiko Ogata
Mathematik
Institut für Mathematik
Referiert
Open Access
Import
Gold Open-Access
DOAJ gelistet
48548
2019
2019
eng
3425
3438
14
8
176
article
Springer
Basel
1
--
2019-03-14
--
Prediction of the Maximum Expected Earthquake Magnitude in Iran:
This paper concerns the problem of predicting the maximum expected earthquake magnitude μ in a future time interval Tf given a catalog covering a time period T in the past. Different studies show the divergence of the confidence interval of the maximum possible earthquake magnitude m_{ max } for high levels of confidence (Salamat et al. 2017). Therefore, m_{ max } should be better replaced by μ (Holschneider et al. 2011). In a previous study (Salamat et al. 2018), μ is estimated for an instrumental earthquake catalog of Iran from 1900 onwards with a constant level of completeness ( {m0 = 5.5} ). In the current study, the Bayesian methodology developed by Zöller et al. (2014, 2015) is applied for the purpose of predicting μ based on the catalog consisting of both historical and instrumental parts. The catalog is first subdivided into six subcatalogs corresponding to six seismotectonic zones, and each of those zone catalogs is subsequently subdivided according to changes in completeness level and magnitude uncertainty. For this, broad and small error distributions are considered for historical and instrumental earthquakes, respectively. We assume that earthquakes follow a Poisson process in time and Gutenberg-Richter law in the magnitude domain with a priori unknown a and b values which are first estimated by Bayes' theorem and subsequently used to estimate μ. Imposing different values of m_{ max } for different seismotectonic zones namely Alborz, Azerbaijan, Central Iran, Zagros, Kopet Dagh and Makran, the results show considerable probabilities for the occurrence of earthquakes with Mw ≥ 7.5 in short Tf , whereas for long Tf, μ is almost equal to m_{ max }
Pure and applied geophysics
from a Catalog with Varying Magnitude of Completeness and Uncertain Magnitudes
10.1007/s00024-019-02141-3
0033-4553
1420-9136
wos:2019
WOS:000481435000009
Salamat, M (reprint author), IIEES, Tehran, Iran., salamat.mona@gmail.com
Deutsche ForschungsgemeinschaftGerman Research Foundation (DFG) [SFB 1294]
2020-12-07T18:48:44+00:00
sword
importub
filename=package.tar
dbd7df8dbd6d038cf8c265ff06d6f6c3
false
true
Mona Salamat
Gert Zöller
Morteza Amini
eng
uncontrolled
Maximum expected earthquake magnitude
eng
uncontrolled
completeness levels
eng
uncontrolled
magnitude errors
eng
uncontrolled
Bayesian method
eng
uncontrolled
Iran
Geowissenschaften
Institut für Mathematik
Referiert
Import
51875
2018
2018
eng
2778
2787
10
5A
108
article
Seismological Society of America
Albany
1
2018-08-21
--
--
Detection of Gutenberg-Richter b-Value Changes in Earthquake Time Series
The Gutenberg-Richter relation for earthquake magnitudes is the most famous empirical law in seismology. It states that the frequency of earthquake magnitudes follows an exponential distribution; this has been found to be a robust feature of seismicity above the completeness magnitude, and it is independent of whether global, regional, or local seismicity is analyzed. However, the exponent b of the distribution varies significantly in space and time, which is important for process understanding and seismic hazard assessment; this is particularly true because of the fact that the Gutenberg-Richter b-value acts as a proxy for the stress state and quantifies the ratio of large-to-small earthquakes. In our work, we focus on the automatic detection of statistically significant temporal changes of the b-value in seismicity data. In our approach, we use Bayes factors for model selection and estimate multiple change-points of the frequency-magnitude distribution in time. The method is first applied to synthetic data, showing its capability to detect change-points as function of the size of the sample and the b-value contrast. Finally, we apply this approach to examples of observational data sets for which b-value changes have previously been stated. Our analysis of foreshock and after-shock sequences related to mainshocks, as well as earthquake swarms, shows that only a portion of the b-value changes is statistically significant.
Bulletin of the Seismological Society of America
10.1785/0120180091
0037-1106
1943-3573
wos:2018
WOS:000445659100027
Fiedler, B (reprint author), Univ Potsdam, Inst Math, Karl Liebknecht Str 24-25, D-14476 Potsdam, Germany., bfiedler@uni-potsdam.de
Deutsche Forschungsgemeinschaft (DFG) Research Training Group "Natural hazards and risks in a changing world"(NatRiskChange); DFGGerman Research Foundation (DFG) [1294]
2021-09-22T07:44:47+00:00
sword
importub
filename=package.tar
462647ee3fd00f2d96f5fec7557b33ba
false
true
Bernhard Fiedler
Sebastian Hainzl
Gert Zöller
Matthias Holschneider
Geowissenschaften
Institut für Geowissenschaften
Referiert
Import
Green Open-Access