Flood Hazard Estimation under Nonstationarity Using the Particle Filter
The presence of the nonstationarity in flow datasets has challenged the flood hazard assessment. Nonstationary tools and evaluation metrics have been proposed to deal with the nonstationarity and guide the infrastructure design and mitigation measures. To date, the examination of how the flood hazar...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-12-01
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| Series: | Geosciences |
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| Online Access: | https://www.mdpi.com/2076-3263/11/1/13 |
| _version_ | 1827699084798984192 |
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| author | Cuauhtémoc Tonatiuh Vidrio-Sahagún Jianxun He |
| author_facet | Cuauhtémoc Tonatiuh Vidrio-Sahagún Jianxun He |
| author_sort | Cuauhtémoc Tonatiuh Vidrio-Sahagún |
| collection | DOAJ |
| description | The presence of the nonstationarity in flow datasets has challenged the flood hazard assessment. Nonstationary tools and evaluation metrics have been proposed to deal with the nonstationarity and guide the infrastructure design and mitigation measures. To date, the examination of how the flood hazards are affected by the nonstationarity is still very limited. This paper thus examined the association between the flood hazards and the nonstationary patterns and degrees of the underlying datasets. The Particle Filter, which allows for assessing the uncertainty of the point estimates, was adopted to conduct the nonstationary flood frequency analysis (NS-FFA) for subsequently estimating the flood hazards in three real study cases. The results suggested that the optimal and top NS-FFA models selected according to the fitting efficiency in general align with the pattern of nonstationarity, although they might not always be superior in terms of uncertainty. Moreover, the results demonstrated the association and the sensitivity of the flood hazards to the perceived patterns and degrees of nonstationarity. In particular, the variations of the flood hazards intensified with the increase in the degree of nonstationarity, which should be assessed in a more elaborate manner, i.e., considering multiple statistical moments. These advocate the potential of using the nonstationarity characteristics as a proxy for evaluating the evolutions of the flood hazards. |
| first_indexed | 2024-03-10T13:42:03Z |
| format | Article |
| id | doaj.art-ce5c1a42f6bb45dc9f4dbd6603f9ed3a |
| institution | Directory Open Access Journal |
| issn | 2076-3263 |
| language | English |
| last_indexed | 2024-03-10T13:42:03Z |
| publishDate | 2020-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Geosciences |
| spelling | doaj.art-ce5c1a42f6bb45dc9f4dbd6603f9ed3a2023-11-21T02:56:54ZengMDPI AGGeosciences2076-32632020-12-011111310.3390/geosciences11010013Flood Hazard Estimation under Nonstationarity Using the Particle FilterCuauhtémoc Tonatiuh Vidrio-Sahagún0Jianxun He1Civil Engineering, Schulich School of Engineering, University of Calgary, 2500 University Drive NW, Calgary, AB T2N 1N4, CanadaCivil Engineering, Schulich School of Engineering, University of Calgary, 2500 University Drive NW, Calgary, AB T2N 1N4, CanadaThe presence of the nonstationarity in flow datasets has challenged the flood hazard assessment. Nonstationary tools and evaluation metrics have been proposed to deal with the nonstationarity and guide the infrastructure design and mitigation measures. To date, the examination of how the flood hazards are affected by the nonstationarity is still very limited. This paper thus examined the association between the flood hazards and the nonstationary patterns and degrees of the underlying datasets. The Particle Filter, which allows for assessing the uncertainty of the point estimates, was adopted to conduct the nonstationary flood frequency analysis (NS-FFA) for subsequently estimating the flood hazards in three real study cases. The results suggested that the optimal and top NS-FFA models selected according to the fitting efficiency in general align with the pattern of nonstationarity, although they might not always be superior in terms of uncertainty. Moreover, the results demonstrated the association and the sensitivity of the flood hazards to the perceived patterns and degrees of nonstationarity. In particular, the variations of the flood hazards intensified with the increase in the degree of nonstationarity, which should be assessed in a more elaborate manner, i.e., considering multiple statistical moments. These advocate the potential of using the nonstationarity characteristics as a proxy for evaluating the evolutions of the flood hazards.https://www.mdpi.com/2076-3263/11/1/13flood hazardsnonstationary structureflood frequency analysisparticle filternonstationary pattern and degreepoint estimation |
| spellingShingle | Cuauhtémoc Tonatiuh Vidrio-Sahagún Jianxun He Flood Hazard Estimation under Nonstationarity Using the Particle Filter Geosciences flood hazards nonstationary structure flood frequency analysis particle filter nonstationary pattern and degree point estimation |
| title | Flood Hazard Estimation under Nonstationarity Using the Particle Filter |
| title_full | Flood Hazard Estimation under Nonstationarity Using the Particle Filter |
| title_fullStr | Flood Hazard Estimation under Nonstationarity Using the Particle Filter |
| title_full_unstemmed | Flood Hazard Estimation under Nonstationarity Using the Particle Filter |
| title_short | Flood Hazard Estimation under Nonstationarity Using the Particle Filter |
| title_sort | flood hazard estimation under nonstationarity using the particle filter |
| topic | flood hazards nonstationary structure flood frequency analysis particle filter nonstationary pattern and degree point estimation |
| url | https://www.mdpi.com/2076-3263/11/1/13 |
| work_keys_str_mv | AT cuauhtemoctonatiuhvidriosahagun floodhazardestimationundernonstationarityusingtheparticlefilter AT jianxunhe floodhazardestimationundernonstationarityusingtheparticlefilter |