Publication Details |
| Category | Text Publication |
| Reference Category | Journals |
| DOI | 10.1016/j.advwatres.2020.103785 |
| Document | accepted manuscript |
| Title (Primary) | Flood risk forecasting at weather to medium range incorporating weather model, topography, socio-economic information and land use exposure |
| Author | Tripathy, S.S.; Hari, V.; Karmakar, S.; Ghosh, S. |
| Source Titel | Advances in Water Resources |
| Year | 2020 |
| Department | CHS |
| Volume | 146 |
| Page From | art. 103785 |
| Language | englisch |
| Keywords | Extreme rainfall; Flood risk; Weather forecast; Hazard; Vulnerability; Exposure |
| Abstract | Non-structural mitigation measures to the globally increasing flood events include forecast based alert generation. However, the extreme rainfall forecasts are associated with low hit rate, high false alarm, and spatiotemporal bias; which makes it difficult to rely on them. Further, the losses due to flood in a region not only depend on rainfall severity but also on topography, socioeconomic conditions and exposure of the region to floods. Here, we introduce a new concept of spatial flood risk mapping and forecasting at weather to medium range based on forecasted hazard, embedded with vulnerability topographic and socioeconomic) and exposure information. Here, we define hazard as the probability of extreme rainfall event during upcoming days given an available weather forecast for the same days. As hindcast is used for computation of probabilities, hazard contains prior information about the false alarm, hit rate and spatiotemporal bias of the forecast. Vulnerability is calculated by averaging the topographic and socioeconomic indicators, and exposure is calculated using a land use land cover map. Topographic vulnerability is computed with digital elevation model using Height Above the Nearest Drainage method, whereas Data Envelopment Analysis is performed to derive the socioeconomic vulnerability based on the demographic census data. For a specific region and a specific event, the relative flood risk maps are generated at an administrative level (e.g., district, subdistrict or village level for India) and the high-risk areas can be identified from those maps for mitigation. The methodology is demonstrated for a very recent extremely severe flood event that happened in Kerala, India in August, 2018. It is evident from the results that the high-risk areas forecasted well in advance (as high lead time as 15 days) match fairly well with the areas, which suffered maximum losses because of direct flood. |
| Persistent UFZ Identifier | https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=23704 |
| Tripathy, S.S., Hari, V., Karmakar, S., Ghosh, S. (2020): Flood risk forecasting at weather to medium range incorporating weather model, topography, socio-economic information and land use exposure Adv. Water Resour. 146 , art. 103785 10.1016/j.advwatres.2020.103785 |
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