Classifying the 2021 'Ahrtal' flood event using hermeneutic
interpretation, natural language processing, and instrumental
data analyses

J 2022

Classifying the 2021 'Ahrtal' flood event using hermeneutic interpretation, natural language processing, and instrumental data analyses

KAHLE, Michael, Michael KEMPF, Martin BRICE a Glaser RÜDIGER

Základní údaje

Originální název

Classifying the 2021 'Ahrtal' flood event using hermeneutic interpretation, natural language processing, and instrumental data analyses

Autoři

KAHLE, Michael (276 Německo), Michael KEMPF (276 Německo, garant, domácí), Martin BRICE (250 Francie) a Glaser RÜDIGER (276 Německo)

Vydání

Environmental Research Communications, IOP PUBLISHING LTD, 2022, 2515-7620

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

60102 Archaeology

Stát vydavatele

Velká Británie a Severní Irsko

Utajení

není předmětem státního či obchodního tajemství

Odkazy

URL

Impakt faktor

Impact factor: 2.900

Kód RIV

RIV/00216224:14210/22:00132938

Organizační jednotka

Filozofická fakulta

DOI

http://dx.doi.org/10.1088/2515-7620/ac6657

UT WoS

000796722700001

Klíčová slova anglicky

Ahrtal flooding; Documentary sources; Machine learning; Natural language processing; Risk management

Štítky

rivok

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 10. 3. 2024 22:33, Mgr. Zuzana Matulíková

Anotace

V originále

Extreme weather events and severe flash floods during July 2021 caused numerous deaths and massive ecological disasters across Europe. The regionally overstrained environmental and socio-cultural resilience triggered an intensive discussion about cause and effect, responsibilities and public denouncement, and the financial consequences of climate-induced extreme events. In this article we analyze the flood event by four methodological approaches: (1) hermeneutics, with an analog interpretation of printed newspapers and sources; (2) text mining and natural language processing of digital newspaper articles available online; (3) precipitation and discharge models based on instrumental data; and (4) how the findings can be linked to the historical extreme floods of 1804 and 1910, based on documentary source analysis. These four approaches are used to compare and evaluate their consistency by tracking the course, consequences, and aftermaths of the flood disaster. The study shows a high consistency between the analog, digital, and instrumental data analysis. A combination of multidisciplinary methods and their application to historical events enables the evaluation of modern events. It enables to answer the question of return periods and intensities, which are indispensable for today's risk assessments and their social contextualization, a desideratum in historical and modern climatology.

Citovat

KAHLE, Michael, Michael KEMPF, Martin BRICE a Glaser RÜDIGER. Classifying the 2021 'Ahrtal' flood event using hermeneutic interpretation, natural language processing, and instrumental data analyses. Environmental Research Communications. IOP PUBLISHING LTD, 2022, roč. 4, č. 5, s. 1-15. ISSN 2515-7620. Dostupné z: https://dx.doi.org/10.1088/2515-7620/ac6657.

@article{2359448,
   author = {Kahle, Michael and Kempf, Michael and Brice, Martin and Rüdiger, Glaser},
   article_number = {5},
   doi = {http://dx.doi.org/10.1088/2515-7620/ac6657},
   keywords = {Ahrtal flooding; Documentary sources; Machine learning; Natural language processing; Risk management},
   language = {eng},
   issn = {2515-7620},
   journal = {Environmental Research Communications},
   title = {Classifying the 2021 'Ahrtal' flood event using hermeneutic interpretation, natural language processing, and instrumental data analyses},
   url = {https://iopscience.iop.org/article/10.1088/2515-7620/ac6657},
   volume = {4},
   year = {2022}
}

TY  - JOUR
ID  - 2359448
AU  - Kahle, Michael - Kempf, Michael - Brice, Martin - Rüdiger, Glaser
PY  - 2022
TI  - Classifying the 2021 'Ahrtal' flood event using hermeneutic interpretation, natural language processing, and instrumental data analyses
JF  - Environmental Research Communications
VL  - 4
IS  - 5
SP  - 1-15
EP  - 1-15
PB  - IOP PUBLISHING LTD
SN  - 25157620
KW  - Ahrtal flooding
KW  - Documentary sources
KW  - Machine learning
KW  - Natural language processing
KW  - Risk management
UR  - https://iopscience.iop.org/article/10.1088/2515-7620/ac6657
N2  - Extreme weather events and severe flash floods during July 2021 caused numerous deaths and massive ecological disasters across Europe. The regionally overstrained environmental and socio-cultural resilience triggered an intensive discussion about cause and effect, responsibilities and public denouncement, and the financial consequences of climate-induced extreme events. In this article we analyze the flood event by four methodological approaches: (1) hermeneutics, with an analog interpretation of printed newspapers and sources; (2) text mining and natural language processing of digital newspaper articles available online; (3) precipitation and discharge models based on instrumental data; and (4) how the findings can be linked to the historical extreme floods of 1804 and 1910, based on documentary source analysis. These four approaches are used to compare and evaluate their consistency by tracking the course, consequences, and aftermaths of the flood disaster. The study shows a high consistency between the analog, digital, and instrumental data analysis. A combination of multidisciplinary methods and their application to historical events enables the evaluation of modern events. It enables to answer the question of return periods and intensities, which are indispensable for today's risk assessments and their social contextualization, a desideratum in historical and modern climatology.
ER  -

KAHLE, Michael, Michael KEMPF, Martin BRICE a Glaser RÜDIGER. Classifying the 2021 'Ahrtal' flood event using hermeneutic interpretation, natural language processing, and instrumental data analyses. \textit{Environmental Research Communications}. IOP PUBLISHING LTD, 2022, roč.~4, č.~5, s.~1-15. ISSN~2515-7620. Dostupné z: https://dx.doi.org/10.1088/2515-7620/ac6657.

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