The results illustrate that: (i) Unprecedented uncertainty. Here we explore the impact of floods on the real-world highway network of China. Furthermore, we imposing simulated future floods into traffic simulation system and develop two measurements to evaluate the impact of floods on the railway system as the perspective of the entire system. The future floods was simulated by using CaMa-Flood model after inputting future runoff scenarios. Secondly, future runoff scenarios were produced by using five global climate models and three different representative concentration pathways. Firstly, A three layered traffic flow simulation model was constructed to study propagation and amplification effects of component failure after the event of flooding in the system. This study developed an integrated approach to explore the impact of large-scale future floods on railway system. The floods directly or indirectly disrupt the railway system and arise a significant negative impact on our social-economic system. Increasing flood risk was caused by expanding climate change. and Venkata Vemavarapu, S.: Probabilistic Flood Hazard Maps at Ungauged Locations Using Multivariate Extreme Values Approach, EGU General Assembly 2020, Online, 4–, EGU2020-732,, 2019. Coefficient of correlation and root mean squared error considered for performance evaluation indicated that the proposed approach is promising. Comparison is shown between flood hazard map obtained based on true at-site data and that derived based on the proposed MRFA approach by considering the respective sites to be pseudo-ungauged. Potential of the proposed approach is demonstrated through a case study on catchments in Mahanadi river basin of India, which extends over 141,600 km 2 and is frequently prone to floods. The approach alleviates several uncertainties found in conventional methods (based on conceptual, probabilistic or geomorphological approaches) which affect estimation of flood hazard. Thus, the synthetic flood hydrographs generated in river basins appear more realistic depicting the observed dependence structure among flood hydrograph characteristics. An advantage of the proposed approach is its ability to account for uncertainty in catchment regionalization and dependency between all the flood hydrograph related characteristics reliably. The MRFA approach is designed to predict flood hydrograph related characteristics (peak flow, volume and duration of flood) at target locations in ungauged basins by considering watershed related characteristics as predictor/explanatory variables. It involves (i) use of a newly proposed clustering methodology for regionalization of catchments, which accounts for uncertainty arising from ambiguity in choice of various potential clustering algorithms (which differ in underlying clustering strategies) and their initialization, (ii) fitting of a multivariate extremes model to information pooled from catchments in homogeneous region to generate synthetic flood hydrographs at ungauged target location(s), and (iii) routing of the hydrographs through the flood plain using LISFLOOD-FP model to derive probabilistic flood hazard map. To address this, a novel multivariate regional frequency analysis (MRFA) approach is proposed. In the case of ungauged catchments, however, there is a dearth of procedures for prediction of flood hazard maps. For gauged catchments, historical streamflow and/or rainfall data may be used to determine design flood hydrographs and the corresponding hazard maps using various strategies. Each of those hydrographs is routed through the flood plain and probability of inundation for all locations in the plain is estimated to derive the probabilistic flood hazard map. To arrive at a probabilistic flood hazard map, several flood hydrographs are generated, representing possible scenarios for flood events over a long period of time (e.g., 500 to 1000 years). A more informative way of representing flood risk is through probabilistic hazard maps, which additionally provide information on the uncertainty associated with the extent of inundation. A flood hydrograph corresponding to a specified return period is derived using a hydrologic model, which is then routed through flood plain of the study area to estimate water surface elevations and inundation extent with the aid of a hydraulic model. Conventionally, flood hazard assessment is based on deterministic approach which involves deriving inundation maps considering hydrologic and hydraulic models. Flood hazard maps are essential for development and assessment of flood risk management strategies.
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