Social vulnerability models are becoming increasingly important for hazard mitigation and recovery planning, but it remains unclear how well they explain disaster outcomes. Most studies using indicators and indices employ them to either describe vulnerability patterns or compare newly devised measures to existing ones. The focus of this article is construct validation, in which we investigate the empirical validity of a range of models of social vulnerability using outcomes from Hurricane Sandy. Using spatial regression, relative measures of assistance applicants, affected renters, housing damage, and property loss were regressed on four social vulnerability models and their constituent pillars while controlling for flood exposure. The indices best explained housing assistance applicants, while they poorly explained property loss. At the pillar level, themes related to access and functional needs, age, transportation, and housing were the most explanatory. Overall, social vulnerability models with weighted and profile configurations demonstrated higher construct validity than the prevailing social vulnerability indices. The findings highlight the need to expand the number and breadth of empirical validation studies to better understand relationships among social vulnerability models and disaster outcomes.

Research Impact Statement: Agricultural best management practices (BMPs) can reduce flood risk, providing a co-benefit to nutrient reduction.ABSTRACT: Best management practices (BMPs) play an important role in improving impaired water quality from conventional row crop agriculture. In addition to reducing nutrient and sediment loads, BMPs such as fertilizer management, reduced tillage, and cover crops could alter the hydrology of agricultural systems and reduce surface water runoff. While attention is devoted to the water quality benefits of BMPs, the potential cobenefits of flood loss reduction are often overlooked. This study quantifies the effects of selected commonly applied BMPs on expected flood loss to agricultural and urban areas in four Iowa watersheds. The analysis combines a watershed hydrologic model, hydraulic model outputs, and a loss estimation model to determine relationships between hydrologic changes from BMP implementations and annual economic flood loss. The results indicate a modest reduction in peak discharge and economic loss, although loss reduction is substantial when urban centers or other high-value assets are located downstream in the watershed. Among the BMPs, wetlands, and cover crops reduce losses the most. The research demonstrates that watershed-scale implementation of agricultural BMPs could provide benefits of flood loss reduction in addition to water quality improvements.(

Distributed attenuation in flood management relies on small and low-impact runoff attenuating features variously distributed within a catchment. Distributed systems of reservoirs, natural flood management, and green infrastructure are practical examples of distributed attenuation. The effectiveness of attenuating features lies in their ability to work in concert, by reducing and slowing runoff in strategic parts of the catchment, and desynchronizing flows. The spatial distribution of attenuating features plays an essential role in the process. This article proposes a framework to place features in a hydrologic network, group them into spatially distributed systems, and analyze their flood attenuation effects. The framework is applied to study distributed systems of reservoirs in a rural watershed in Iowa, USA. The results show that distributed attenuation can be an effective alternative to a single centralized flood mitigation approach. The different flow peak attenuation of considered distributed systems suggest that the spatial distribution of features significantly influences flood magnitude at the catchment scale. The proposed framework can be applied to examine the effectiveness of distributed attenuation, and its viability as a widespread flood attenuation strategy in different landscapes and at multiple scales.

We would like to thank the CDC colleagues for their Commentary in what constitutes the first comment on a paper published in the Annals in decades. We view critique as a strength of scientific exploration.The Commentary concludes with as statement agreeing with the findings and conclusions of our paper:"we recognize CDC SVI may not identify the most vulnerable populations in all applications and has not done so in the Rufat et al. study (…) we agree with the authors."

____________________________________________ Ricardo Mantilla ____________________________________________ David Bennett ii ACKNOWLEDGEMENTS I would like to acknowledge IIHR -Hydroscience and Engineering for involving me in the Iowa Watershed Projects, funded by the US Department of Housing and Urban Development. This has represented a decisive opportunity to conceive and develop the study hereby presented. Financial and conceptual supports have been continuous and made possible the deepening of the subject of this research. I would like to thank the Department of Geographical and Sustainability Sciences for giving me the opportunity to continue my studies and enhance my knowledge of the world, and of myself too. I have greatly appreciated the warm and sincere academic support of the Department, and the technical means that were made available to me for the successful processing of the modeling part of the study. iii ABSTRACT The use of a system of detention reservoirs distributed across a region has been gaining interest as an innovative way to manage riverine flooding. An open problem is the role played by the spatial configuration of detention projects in regulating the flow. Possible locations for reservoirs within a watershed are numerous, however methods used in literature to place reservoirs on real watersheds and couple them with realistic values of storage are not very detailed.This thesis presents a methodology for modeling dams and related reservoirs at high density, based on the analysis of a Digital Elevation Model (DEM) of the terrain, and extracting their geometric characteristics. Four indicators, based on the morphology of reservoirs and their position in the network, are proposed to classify them and identify which locations are more suitable for a detention project. These are the Horton order, the ratio between volume and extent of the reservoir, the ratio between volume and the expected inflow volume, and the volume itself.The study area of the analysis is the Turkey River watershed, in northeastern Iowa. The algorithm analyzed over 100,000 locations and successfully modeled more than 60%. Most of the failed attempts occurred in a region of the watershed where the terrain is generally flat and reservoirs, when feasible, tend to store water inundating a large area. Regional patterns of ratios are highlighted at the scale of the watershed, but no clear, recurring pattern is identified at the subwatershed level.The considered indicators have the purpose of narrowing down locations to a manageable number of candidates. Further criteria can also be adopted, based on land use and social and economic considerations. Selected reservoirs can be variously combined and entered, together with their geometric characteristics, in hydrological models and optimization processes to determine the best spatial configuration possible. iv PUBLIC ABSTRACTThe use of a system of detention ponds, or small reservoirs, distributed across a region has been gaining interest as an innovative way to manage riverine flooding...