 grid over Austria.
The sixth contribution authored by Tsung-Yi Pan, Lung-Yao Chang, Jihn-Sung Lai, Hsiang-Kuan Chang, Cheng-Shang Lee and Yih-Chi Tan is titled “Coupling typhoon rainfall forecasting with overland-flow modelling for early warning of inundation”. In Taiwan, potential inundation maps have been widely used as a non-structural risk mitigation strategy for floods. The authors point out that spatiotemporal rainfall distributions must be addressed to improve the accuracy of inundation forecasting for emergency response operations. Therefore, they present a system for 24-h forecast early warning system of inundation by coupling the forecasting of typhoon rainfall with the modelling of overland flow. The forecast of the typhoon rainfall is carried out by the climatology model (TRCM) in order to approximate dynamically the spatiotemporal rainfall distribution based on typhoon tracks. The scheme is superior to traditional early warning method that determines the maximum extent and depth of inundation from conditional uniform rainfall. It can forecast spatiotemporal rainfall patterns, leading to improved performance of inundation forecasting, which is critical for emergency response operations.
The final contribution by Desiree Hilbring, Tanja Titzschkau, Alfons Buchmann, Gottfried Bonn, Friedemann Wenzel and Eberhard Hohnecker deals with “Earthquake Early Warning for Transport Lines”. This interdisciplinary work focuses on the immediate production of an alert map during an ongoing earthquake. Furthermore, a damage map representing the consequences to the railway infrastructure is calculated immediately after the strong motion phase. The procedure is based on a service-oriented architecture applying geospatial standards. It is aimed that the system architecture can be used in different geographical regions and can be potentially transferred to other types of natural hazards and infrastructure systems. Besides the general description of the architecture, an online demonstrator has been applied to a test area in the Federal State of Baden-Württemberg, Germany. Furthermore, this system is coupled with the implementation of low-cost sensors in the railway track in order to provide a dense network directly on the railway infrastructure.
We strongly believe that the covered topics provide a range of interesting themes related to early warning systems and further our knowledge in this field. Indeed, there are many other aspects of early warning systems which deserve detailed attention. The provided manuscripts do, however, provide a sample of some of the work being carried out in the respective fields. The guest editors want to thank the authors for their submissions and their patience during the process of managing this special issue. We also want to acknowledge the hard work of numerous reviewers, who improved the quality of the manuscripts significantly. Finally, we deeply appreciate the guidance and support of the NHAZ editorial team, who helped us tremendously to finalize this special issue.