Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1002/2017WR020784 |
Tree-based flood damage modeling of companies: Damage processes and model performance | |
Sieg, Tobias1,2; Vogel, Kristin2; Merz, Bruno1,2; Kreibich, Heidi1 | |
2017-07-01 | |
发表期刊 | WATER RESOURCES RESEARCH |
ISSN | 0043-1397 |
EISSN | 1944-7973 |
出版年 | 2017 |
卷号 | 53期号:7 |
文章类型 | Article |
语种 | 英语 |
国家 | Germany |
英文摘要 | Reliable flood risk analyses, including the estimation of damage, are an important prerequisite for efficient risk management. However, not much is known about flood damage processes affecting companies. Thus, we conduct a flood damage assessment of companies in Germany with regard to two aspects. First, we identify relevant damage-influencing variables. Second, we assess the prediction performance of the developed damage models with respect to the gain by using an increasing amount of training data and a sector-specific evaluation of the data. Random forests are trained with data from two postevent surveys after flood events occurring in the years 2002 and 2013. For a sector-specific consideration, the data set is split into four subsets corresponding to the manufacturing, commercial, financial, and service sectors. Further, separate models are derived for three different company assets: buildings, equipment, and goods and stock. Calculated variable importance values reveal different variable sets relevant for the damage estimation, indicating significant differences in the damage process for various company sectors and assets. With an increasing number of data used to build the models, prediction errors decrease. Yet the effect is rather small and seems to saturate for a data set size of several hundred observations. In contrast, the prediction improvement achieved by a sector-specific consideration is more distinct, especially for damage to equipment and goods and stock. Consequently, sector-specific data acquisition and a consideration of sector-specific company characteristics in future flood damage assessments is expected to improve the model performance more than a mere increase in data. |
领域 | 资源环境 |
收录类别 | SCI-E |
WOS记录号 | WOS:000407895000048 |
WOS关键词 | ABSOLUTE ERROR MAE ; JUNE 2013 ; RISK ; GERMANY ; VALIDATION ; FLEMOCS ; RMSE ; BIAS |
WOS类目 | Environmental Sciences ; Limnology ; Water Resources |
WOS研究方向 | Environmental Sciences & Ecology ; Marine & Freshwater Biology ; Water Resources |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/22078 |
专题 | 资源环境科学 |
作者单位 | 1.GFZ German Res Ctr Geosci, Sect Hydrol 5 4, Potsdam, Germany; 2.Univ Potsdam, Inst Earth & Environm Sci, Potsdam, Germany |
推荐引用方式 GB/T 7714 | Sieg, Tobias,Vogel, Kristin,Merz, Bruno,et al. Tree-based flood damage modeling of companies: Damage processes and model performance[J]. WATER RESOURCES RESEARCH,2017,53(7). |
APA | Sieg, Tobias,Vogel, Kristin,Merz, Bruno,&Kreibich, Heidi.(2017).Tree-based flood damage modeling of companies: Damage processes and model performance.WATER RESOURCES RESEARCH,53(7). |
MLA | Sieg, Tobias,et al."Tree-based flood damage modeling of companies: Damage processes and model performance".WATER RESOURCES RESEARCH 53.7(2017). |
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