Delineating flood prone areas using a statistical approach
نویسندگان
چکیده
8 Floods are frequent and widespread in Italy and pose a severe risk for the population. Local administrations commonly use flow propagation models to delineate the flood prone areas. These modeling approaches require a detail geo-environmental data knowledge, intensive calculation and long computational times. Conversely, statistical methods can be used to asses flood hazard over large areas, or to extend the flood hazard zonation to the portion of the river networks where hydraulic models have still not been applied or can be applied with difficulties. In this paper, we describe a statistical approach to prepare flood hazard maps for the whole of Italy. The proposed method is based on a multivariate machine learning algorithm calibrated using in input flood hazard maps delineated by the local authorities and terrain elevation data. The preliminary results obtained in several major Italian catchments indicate good performances of the statistical algorithm in matching the training data. Results are promising giving the possibility to obtain reliable delineations of flood prone areas obtained in the rest of the Italian territory. 9
منابع مشابه
Mapping the flood-prone areas for developing a flood risk management system in the northeast of Iran
متن کامل
Simulation of floodplain zones in Tehran's metropolitan watershed (case study: Kaan basin)
Simulation of floodplain zones in Tehran's metropolitan watershed (case study: Kaan basin) Ezaatollah Ghanavati, Associate prof. Geographical science faculty, Kharzmi University Ali Ahmmadabadi. Assistance prof. Geographical science faculty, Kharzmi University Negar Gholami, MA in Geomorphology, Geographical science faculty, Kharzmi University Extended abstract Floodplains and adjacent riv...
متن کاملSimulation of floodplain zones in Tehran's metropolitan watershed (case study: Kaan basin)
Simulation of floodplain zones in Tehran's metropolitan watershed (case study: Kaan basin) Ezaatollah Ghanavati, Associate prof. Geographical science faculty, Kharzmi University Ali Ahmmadabadi. Assistance prof. Geographical science faculty, Kharzmi University Negar Gholami, MA in Geomorphology, Geographical science faculty, Kharzmi University Extended abstract Floodplains and adjacent riv...
متن کاملDetermination of flood-prone areas using Sentinel-1 Radar images (Case study: Flood on March 2019, Kashkan River, Lorestan Province)
Determination of flood-prone areas using Sentinel-1 Radar images (Case study: Flood on March 2019, Kashkan River, Lorestan Province) Introduction Although natural hazards occur in all parts of the world, their incidence is higher in Asia than in any other part of the world. Natural phenomena are considered as natural hazards when they cause damage or financial losses to human beings. Iran ...
متن کاملRunoff Production Potential Zoning Using Fuzzy GIS-MCDA Models (Case Study: Tajan River Basin)
Because in Iran, flood phenomenon has the highest financial losses and death tolls among the natural disasters, thus reducing the damage caused by it has been considered for a long time and it is regarded essential. The most urgent action to deal with this natural disaster is to make preparations and take measures to reduce its harmful effects. One of the basic measures in this regard is the re...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- PeerJ PrePrints
دوره 4 شماره
صفحات -
تاریخ انتشار 2016