Flood risk assessment, as essential part of flood risk management, is a useful tool for the indication of economic damages and for the identification of the most vulnerable cities worldwide. In most cases, cities with a high concentration of people and goods are vulnerable to floods (Kubal et al., 2009). As a consequence there is a need to assess the flooding risk in all its entirety. Risk is the outcome of the interaction between a hazard phenomenon and the elements at risk within the community (e.g. people, buildings and infrastructure) that are vulnerable to such an impact (Jacks et al., 2010). In risk assessment, one has to consider the probabilities of hazardous events affecting the community and the consequent harm to the community. Probability is a concept and skill that most people have problems understanding, as many cannot handle statistical concepts or effectively factor probabilities into their decision-making (“PWS Guidelines on Communicating Forecast Uncertainty” (PWS-18), WMO/TD No. 1422). The flooding risk assessment consists on different phases: prevention, forecasting, real time monitoring and finally post-event. In the prevention phase, all the actions that allow to reduce the risk of flooding for the most sensitive areas are implemented. These actions are different and the mains are intended to: a) introduce advance flood warning and pre-planning can significantly reduce the impact of flooding; b) modify homes and business to help the population to withstand the floods; c) Construct buildings above flood levels; d) tackle climate change; e) protect wetlands and introduce trees strategically; f) restore rivers to their natural courses; g) introduce water storage areas; h) put up more flood barriers; and at least l) improve soil conditions. All these phenomena are investigated through post event flooding maps. However, because of the ongoing climate change these flooding maps based on past extreme events are obsolete. In fact, the return period (intended as an average time or an estimated average time between events such as floods) of such floods is completely different from the ones happened in the past and therefore there is a need to update these maps. The forecasting and nowcasting phases (the term forecast is referred to a very short time, generally from zero to six hours) are very important from the point of view of effective warnings and response in order to reduce the disaster risk. The forecast phase generally is based on four components: Observational Data and Monitoring Systems, Numerical Weather Prediction, Conceptual Models and Situational Awareness. For all of these components higher temporal and spatial resolution of the data (temperature, humidity pressure and wind data) are required to lead to a better weather diagnosis. These analyses allow to plan a better warning response. To date both these two phases are fundamental for the civil protection in providing information to the citizens (from e.g. media, governance institutions, etc.), understanding the hazard and, at least, in the emergency response plans. Especially the nowcasting phase, that is characterized by shorts times, requires a wide range of tools that allow to evaluate the hazard immediately. However, in some cases it is not possible to give these technologies to the civil protection and therefore, sometimes they entrust themself to the experiences of the operators or/and to their knowledge based on the experiences of past extreme events. The monitoring phase, instead, is managed by collecting information on the territory thanks to the ground-based systems linked to the local databases available or through the rescue teams. The ground stations (i.e. sensors measuring precipitation and / or water levels at relevant sites in local waterways) often are not available or capable to monitor well the extreme event. In fact, it is of extreme importance for this phase that the spatial disposition of the stations is such as to cover the whole area of interest. Because of this usually does not happen, the local rescue emergency team are employed, hence, exposing them at risk. Finally, the post-event phase deals with the using of flooding maps obtained with numerical models and / or via photographic evidence of the damages happened. These maps, as mentioned above, usually are obsolete considering the ongoing climate change and, often, do not make possible to localize all the area affected by the flood. Moreover, often these maps are implemented with hydraulic modelling using old input data (Digital Elevation Model, land cover, etc.) that do not represent the real status of the environment at the time of the extreme event of interest. Finally, usually these tools are validated considering maps based on past extreme events. As a consequence, this methodology is not useful for the reconstruction of post event maps with high accuracy, because of the land and climatic changings lead to consider new flooding areas that were safety in the past. Regarding the post event analysis with photographic evidences, the goodness of the maps depends directly from the area considered for the analysis. In fact, if the zone is in a developed city it is simple to find pictures that show the situation and that allow to rebuild a flooding map, while it is very difficult if the area is in a developing country. In flood risk assessment, satellite remote sensing constitutes a very useful tool in all above described phases. In fact, through the satellites it is possible to have, with regard to the prevention phase, a record of the floods that occurred in the past and the consequent location of the areas most exposed to the risk of flooding. For the forecast phase, information on the distribution and intensity of the rains that is about to fall can be obtained. In the monitoring phase, the satellites allow to follow the evolution of the extreme event and detect the flooding. Finally, in the post-event phase, satellites allow to a rebuilding of the flood maps and to the identification of flooded areas and to a consequently better organization of the securing of the areas most at risk. Remote sensing from satellite, therefore, for all the phases of flooding risk assessment, allows obtaining important information in the detection of soil moisture, subsidence, precipitation and the extent of flooding. Satellite technology is an excellent solution for obtaining information for flooding risk assessment for several reasons: a) allows analysis on a much larger scale compared to those made with ground instruments; b) involves less risk for rescue teams in action during floods; c) some sensors, such as radar, allows to get information in correspondence with any atmospheric configuration and during the night; finally d) in the near future satellites will be launched capable of providing ever better spatial resolutions and revisit time. At the same time, this technology also has some rather important limitations that lead us to integrate it with other existing techniques. Some of the most important limits are: a) of an instrumental nature (i.e. the radar is not able to capture flooding in the urban area); b) the spatial and temporal resolution not always able to capture the peak of flood during the extreme event; and finally c) that not all satellite missions are free and / or accessible; For this reason the satellite instrument alone is not sufficient and must necessarily be associated with other existing and compatible technologies for flooding risk assessment. Specifically, in this thesis we explore the possibility to improve flood risk assessment by the integration of hydraulic models with satellite data with reference at the two phases of post-event analysis and nowcasting. Regarding the post event, the aim was to understand if the remote sensing from satellite, considering its limitation, is a useful tool for the reconstruction of very accurate flooding maps that can perform the flooding risk assessment. Furthermore, also the possibility to integrate this technology with other available tools (social media marker and hydraulic modelling) was explored. Drawbacks arose about open source shallow water model (HEC-RAS) used in the case studies have suggested to develop a new 2D hydraulic model, that has been used in the carrying out of nowcasting phase. Concerning the nowcasting phase, the possibility to integrate data of precipitation measured by radar with real time flood forecast model was explored. A flood model, following an artificial intelligence approach, was carried out. Such model was trained by a number of simulations carried out by the 2D hydraulic model. The development of the thesis has seen three main moments: 1) Analysis of the capabilities of remote sensing in flooding risk assessment by applying it to real cases and other available tools (hydraulic modeling and social media markers); 2) Application to the post-event phases in which it was first rebuilt the extreme event of Hurricane Harvey in Houston and then an assessment of the need to build more flexible numerical models than the one used for the simulations was done; 3) Application to the analysis of flooding risk assessment in the nowcasting phase through the construction of a real time artificial intelligence model. In the first point, first of all was studied how remote sensing from satellite was used in the evaluation of flooding risk assessment for: detection of soil moisture and subsidence phenomenon; flood detection; and finally for estimating precipitation. For each of these applications the sensors and missions currently in orbit that are mostly used for these purposes have been presented. Such applications have been reported as case studies. Finally, other existing tools were investigated, such as hydraulic modeling and social media markers, useful for the flooding risk assessment. In the second point, instead, considering the applications developed in point 1, in particular that of the reconstruction of the flooding emerged in Greece (river Strymon) and in Vietnam (Quang Ngai), remote sensing techniques from satellite with hydraulic modeling and social media markers were integrated. The numerical code used in these simulations was HEC-RAS 5.0.3. This hydraulic model was considered because suggested by FEMA and because of its excellent results in terms of robustness. The peculiarity of this hydraulic model is that it exploits the subgrid approach (Casulli et al., 2008). This method allows using large meshes to perform hydraulic simulations in large areas with reasonable computational times. The Hurricane Harvey, occurred in Houston, was adopted as a test case. In this study the technique of remote sensing from satellite was integrated with hydraulic modeling and social media markers. This methodology allowed us to reconstruct, using the information obtained from ground stations, extremely accurate flood maps for all days of the extreme flood event. Subsequently, tests were carried out on the robustness of the HEC-RAS code on a portion of the urban area of Houston. These analysis, conducted in correspondence of complex geometries (such as buildings, roads, slope changes, etc.), have allowed us to understand the goodness of the approach to the subgrid in returning the results of depth and velocity of the flow to the different spatial resolutions of the computational grid. The results of the tests led to the creation of a new numerical code that was able to overcome the limitations found in HEC-RAS and, in general, those that afflict the various models present in the literature. The model created was first of all object of a bench marking test and then of an application to a real case study. Twelve extreme events occurred in correspondence of Saint Lucia Island were simulated and the results were validated with social media collected by the local population. Finally, the third and final point allowed us to explore the possibility of overcoming the main limitation in the application of hydraulic models in the nowcasting phase. In fact, the numerical codes for simulations require much longer times than those useful for the nowcasting phase (a few seconds). For this reason, an approach based on artificial intelligence has been used that allows, for a given atmospheric configurations that occurs, to obtain in a short time flooding maps based on past events similar to the extreme event that is coming. The surrogate model, in this thesis, has been trained with the simulated maps for the extreme events happened on Saint Lucia in past.
Development and validation of alluvial risk identification methodologies through the integrated use of remote sensing from satellite and hydraulic modeling with particular reference to post-event analysis and nowcasting phases / Scotti, Vincenzo. - (2020 Feb 27).
|Titolo:||Development and validation of alluvial risk identification methodologies through the integrated use of remote sensing from satellite and hydraulic modeling with particular reference to post-event analysis and nowcasting phases|
|Data di discussione:||27-feb-2020|
|Appartiene alla tipologia:||07a Tesi di Dottorato|