Landslide hazard mapping of Wayanad District of Kerala, India, incorporating copula-based estimation of joint probability of rainfall
<p>The development and integration of the spatial and temporal probabilities of landslides are required for complete landslide hazard mapping at any location. Under changing climate, the computation of the temporal probability of landslides with rainfall magnitude alone is inaccurate. This res...
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Copernicus Publications
2024-11-01
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| Series: | Proceedings of the International Association of Hydrological Sciences |
| Online Access: | https://piahs.copernicus.org/articles/387/79/2024/piahs-387-79-2024.pdf |
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| author | S. Dilama Shamsudeen A. Sankaran |
| author_facet | S. Dilama Shamsudeen A. Sankaran |
| author_sort | S. Dilama Shamsudeen |
| collection | DOAJ |
| description | <p>The development and integration of the spatial and temporal probabilities of landslides are required for complete landslide hazard mapping at any location. Under changing climate, the computation of the temporal probability of landslides with rainfall magnitude alone is inaccurate. This research proposes a framework based on copula functions to develop a landslide probability map using multi-site rainfall data by accounting for the rainfall variables of intensity and duration using a joint-probability approach. The proposed technique is used for Wayanad District, Kerala, India, considering extreme rainfall events in 2018. Firstly, the landslide susceptibility map of the district was developed using a robust random forest (RF) model. Based on regional geology, geomorphology, and climate, different regions of Wayanad have varying rainfall thresholds assessed according to the intensity and duration of the rainfall. Then, the temporal probability of landslides was developed, accounting for the intensity and duration of rainfall events using the joint-probability estimation using copula. Through the integration of the landslide spatial probability map with the temporal probability, landslide hazard maps (LHMs) for Wayanad were developed for time periods ranging from 1 to 50 years. The results of the study indicate the need for bi- or multi-variate landslide probability modeling in studies on regional landslide hazard assessments.</p> |
| format | Article |
| id | doaj-art-a90e94ba30b94243bcb84b7b1ca4acc4 |
| institution | Kabale University |
| issn | 2199-8981 2199-899X |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Proceedings of the International Association of Hydrological Sciences |
| spelling | doaj-art-a90e94ba30b94243bcb84b7b1ca4acc42024-11-18T11:35:11ZengCopernicus PublicationsProceedings of the International Association of Hydrological Sciences2199-89812199-899X2024-11-01387798610.5194/piahs-387-79-2024Landslide hazard mapping of Wayanad District of Kerala, India, incorporating copula-based estimation of joint probability of rainfallS. Dilama Shamsudeen0A. Sankaran1Department of Civil Engineering, TKM College of Engineering Kollam-05, APJ Abdul Kalam Technological University, Kerala, IndiaDepartment of Civil Engineering, TKM College of Engineering Kollam-05, APJ Abdul Kalam Technological University, Kerala, India<p>The development and integration of the spatial and temporal probabilities of landslides are required for complete landslide hazard mapping at any location. Under changing climate, the computation of the temporal probability of landslides with rainfall magnitude alone is inaccurate. This research proposes a framework based on copula functions to develop a landslide probability map using multi-site rainfall data by accounting for the rainfall variables of intensity and duration using a joint-probability approach. The proposed technique is used for Wayanad District, Kerala, India, considering extreme rainfall events in 2018. Firstly, the landslide susceptibility map of the district was developed using a robust random forest (RF) model. Based on regional geology, geomorphology, and climate, different regions of Wayanad have varying rainfall thresholds assessed according to the intensity and duration of the rainfall. Then, the temporal probability of landslides was developed, accounting for the intensity and duration of rainfall events using the joint-probability estimation using copula. Through the integration of the landslide spatial probability map with the temporal probability, landslide hazard maps (LHMs) for Wayanad were developed for time periods ranging from 1 to 50 years. The results of the study indicate the need for bi- or multi-variate landslide probability modeling in studies on regional landslide hazard assessments.</p>https://piahs.copernicus.org/articles/387/79/2024/piahs-387-79-2024.pdf |
| spellingShingle | S. Dilama Shamsudeen A. Sankaran Landslide hazard mapping of Wayanad District of Kerala, India, incorporating copula-based estimation of joint probability of rainfall Proceedings of the International Association of Hydrological Sciences |
| title | Landslide hazard mapping of Wayanad District of Kerala, India, incorporating copula-based estimation of joint probability of rainfall |
| title_full | Landslide hazard mapping of Wayanad District of Kerala, India, incorporating copula-based estimation of joint probability of rainfall |
| title_fullStr | Landslide hazard mapping of Wayanad District of Kerala, India, incorporating copula-based estimation of joint probability of rainfall |
| title_full_unstemmed | Landslide hazard mapping of Wayanad District of Kerala, India, incorporating copula-based estimation of joint probability of rainfall |
| title_short | Landslide hazard mapping of Wayanad District of Kerala, India, incorporating copula-based estimation of joint probability of rainfall |
| title_sort | landslide hazard mapping of wayanad district of kerala india incorporating copula based estimation of joint probability of rainfall |
| url | https://piahs.copernicus.org/articles/387/79/2024/piahs-387-79-2024.pdf |
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