;Contents: A theory of urban floodplain protection benefits; Benefit determination theories in INTASA and Weisz studies; Empirical estimation methods in INTASA and Weisz-day--A critical analysis; A regression model of impact of flood risk on urban land values--A case study for St. Louis County.

Flood risk assessment usually focuses on damages to material objects (indirect tangible costs) and downplays the broader socio-economic aspects of flood-prone systems. Such aspects are crucial for an accurate assessment of risk to human receptors and of the benefits of non-structural measures. For example, an early warning system (EWS) that reduces the amount of direct tangible costs only partially could: (i) save lives (direct intangible costs); (ii) help avoid long-lasting trauma (indirect intangible costs); (iii) prevent post-disaster evacuation costs (indirect tangible costs). We present a methodology to assess flood risk to people, which integrates people's vulnerability and ability to cushion hazards by coping and adapting. The study area covers the lower part of the Sihl valley (Switzerland) including the city of Zurich. Flood risk to people is modelled using a spatially explicit Bayesian network model calibrated on expert opinions (25 experts were involved). Risk to people is assessed in terms of: (1) likelihood of non-fatal physical injury; (2) likelihood of post-traumatic stress disorder; (3) likelihood of death. The model is used to estimate the benefits of improving an existing EWS, taking into account reliability, lead-time and scope. The proposed approach can: (1) improve flood cost estimation by extending its scope beyond direct and tangible damages; (2) complement quantitative and semi-quantitative data with subjective and local knowledge, improving the use of commonly available information; and (3) produce estimates of model uncertainty by providing probability distributions for all its outputs.

Floods are the most frequent of all-natural hazards and responsible for causing more damages than any other disasters. Globally, floods are estimated to have affected more than 2 billion people between 1998 and 2018, accounting for 45 percent of all people affected by disasters during that period with an estimated 142,088 fatalities. The immediate impacts of flooding include the loss of human life, livelihoods, damage to property, destruction of crops, loss of livestock, disruption of services, and deterioration of health conditions owing to waterborne diseases, among others. The direct economic losses caused by flooding over the last decade are estimated at US656 billion dollars, although these are systematically under-reported and actual values are likely much higher. When accounting for intangible impacts on human well-being, natural disasters are thought to cost the global economy more than US520 billion dollars a year. This report outlines a comprehensive framework for valuing the benefits associated with NbS for IUFM to facilitate the identification of appropriate and sustainable financing mechanisms to realize those values. Traditional approaches of assessing the benefits of urban flood management have been focused on avoided losses due to reductions in the probability of flooding. A benefit to this approach is that it is simple to calculate and to explain to decision makers. It can also provide information regarding the optimal level of flood risk reduction associated to the direct intervention cost. However, such traditional approaches do not reflect the full range of social, environmental and economic benefits that can be realized by NbS for IUFM. Broader recognition of these benefits, and an evaluation of their value under different circumstances, provides the foundation for capturing non-market values and leveraging private sector and community financing options. The approach described herein builds on the 'Principles for Valuing Water' articulated by the High-Level Panel on Water convened by the United Nations and the World Bank Group and includes three common types of flooding (i.e. fluvial, pluvial and coastal) through a five step process.