A Regional assessment on the influence of climate change on summer rainfall : an application to shallow landsliding in Wanzhou County, China
This study looks into the future of evolving triggering rainfall conditions in a changing climate, and aims to establish a link to tools in the present to assess shallow landslide susceptibility. Focus is given to the triggering rainfall conditions represented by extreme daily rainfall and mean seas...
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| Format: | master thesis |
| Publication Date: | 2021 |
| Country: | España |
| Institution: | Universitat Politècnica de Catalunya (UPC) |
| Repository: | UPCommons. Portal del coneixement obert de la UPC |
| Language: | English |
| OAI Identifier: | oai:upcommons.upc.edu:2117/360706 |
| Online Access: | https://hdl.handle.net/2117/360706 |
| Access Level: | Open access |
| Keyword: | Landslides Climatic changes Rain and rainfall Shallow landslides Climate Change Extreme Events Rainfall Bias Correction China Hydrology Esllavissades Canvis climàtics Pluja Àrees temàtiques de la UPC::Enginyeria civil::Geologia::Riscos geològics |
| Summary: | This study looks into the future of evolving triggering rainfall conditions in a changing climate, and aims to establish a link to tools in the present to assess shallow landslide susceptibility. Focus is given to the triggering rainfall conditions represented by extreme daily rainfall and mean seasonal rainfall. The study site selected in this research was Wanzhou County, China. This county lies in a region of China that receives 90% of its annual rainfall during the summer months. The effect of which is observed with 80% of shallow landslides occurring between June to August from 1995-2005. This research project delivered proof-of-concept for a methodological framework to derive shallow landslide triggering rainfall scenarios from climate model outputs. The presentation of the results and the identification of sources of uncertainties in this study demonstrated a viable link between for climate change projections to provide future rainfall scenarios as inputs for physically-based shallow landslide susceptibility models. |
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