Development of a QGIS model for Rockfall risk assessment

Development of a QGIS model for Rockfall risk assessment. Abstract: Characterized by their high velocity and substantial energy, rockfalls are among the most often occurring and dangerous natural events that seriously affect inhabited areas and important infrastructure. Ongoing changes in the weather and the environment have made it harder to accurately find and assess areas that are likely to have rockfalls. Even small changes can have a big effect on how much risk people are exposed to. So, for effective territorial management, it is important to have timely and reliable risk assessments that take into account how things change over time. This lets decision-makers plan their mitigation efforts in a strategic way. In this case, the current study presents a new, fully automated QGIS-based model that is specifically made to look at rockfall risk on a regional scale. Independent management of input data and integration of temporal parameters by the proposed approach helps to quantify risk over several occurrence intervals. You can use different GIS tools to do spatial hazard analysis, which is an important first step in preparing data. The QPROTO plugin was chosen for this thesis because it is easy to use, open-source, and works well with QGIS, which makes it easy to get reliable first estimates of rockfall runout and kinetic energies. The IMIRILAND method is used for a full risk assessment, which lets us look at all the risks in detail, including physical, social, and total risks. An exponential distribution model that uses historical rockfall events to cover different rockfall volume scenarios over different time periods is used to explicitly include temporal probability. this method is verified with a detailed case study in Sorba Valley, which is in Piemonte, northwestern Italy. We chose this area because it has unique landforms, a history of rockfalls, and access to public spatial datasets. The results show that this method works and can be used in real cases. It makes a big difference in land-use planning, risk reduction strategies, and deciding which high-risk areas need more in-depth studies and protective actions.