Hydro-meteorological risks are a growing issue for societies, economies and environments around the world. An effective, sustainable response to such risks and their future uncertainty requires a paradigm shift in our research and practical efforts. In this respect, Nature-Based Solutions (NBSs) offer the potential to achieve a more effective and flexible response to hydro-meteorological risks while also enhancing human well-being and biodiversity. The present paper describes a new methodology that incorporates stakeholders’ preferences into a multi-criteria analysis framework, as part of a tool for selecting risk mitigation measures. The methodology has been applied to Tamnava river basin in Serbia and Nangang river basin in Taiwan within the EC-funded RECONECT project. The results highlight the importance of involving stakeholders in the early stages of projects in order to achieve successful implementation of NBSs. The methodology can assist decision-makers in formulating desirable benefits and co-benefits and can enable a systematic and transparent NBSs planning process.

Abstract. Coastal floods are a consistent threat to oceanfront countries, causing major human suffering and substantial economic losses. Climate change is exacerbating the problem. An early warning system is essential to mitigate the loss of life and property from coastal flooding. The purpose of this study is to develop a coastal flooding early warning system (CoFEWs) by integrating existing sea-state monitoring technology, numerical ocean forecasting models, historical database and experiences, as well as computer science. The proposed system has capability of offering data for the past, information for the present and future. The system was developed for the Taiwanese coast due to its frequent threat by typhoons. An operational system without any manual work is the basic requirement of the system. Integration of various data sources is the system kernel. Numerical ocean models play an important role within the system because they provide data for assessment of possible flooding. The regional wave model (SWAN) that nested with the large domain wave model (NWW III) is operationally set up for coastal wave forecasting, in addition to the storm surge predicted by a POM model. Data assimilation technology is incorporated for enhanced accuracy. A warning signal is presented when the storm water level that accumulated from astronomical tide, storm surge, and wave-induced run-up exceeds the alarm sea level. This warning system has been in practical use for coastal flooding damage mitigation in Taiwan for years. An example of the system operation during the Typhoon Haitung which struck Taiwan in 2005 is illustrated in this study.

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Abstract.This paper presents modelling the wave conditions in Typhoon Krosa prior to touching Taiwan in October 2007, with third-generation wave models of SWAN and WWM. The accuracy of the extreme wave measurement H max = 32 m with significant wave height H s ≈ 24 m at the depth of h = 38 m is discussed first. It is concluded that the measurement does not appear faulty and is physically realistic. The numerical results are then analysed in order to examine the models' capability to reproduce the observed conditions. It is found that neither SWAN nor WWMII are able to hindcast the extreme measurement. Series of sensitivity tests are conducted for different numerical and diffraction schemes, and source functions. It is shown that, in the circumstances, the model performance only improves in response to the bottom-limited breaking formulation.

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