Social and environmental vulnerability to flooding: Investigating cross-scale hypotheses

Flooding is a natural hazard that touches nearly all facets of the globe and is expected to become more frequent and intensified due to climate and land-use change. However, flooding does not impact all individuals equally. Therefore, understanding how flooding impacts distribute across populations of different socioeconomic and demographic backgrounds is vital. One approach to reducing flood risk on people is using indicators, such as social vulnerability indices and flood exposure metrics, to inform decision-making for flood risk management. However, such indicators can face the scale and zonal effect produced by the Modifiable Areal Unit Problem (MAUP). This study investigates how the U.S. Census block group, tract, and county scale selection impacts social vulnerability and flood exposure outcomes within coastal Virginia, USA. Here we show how (1) scale selection can obstruct our understanding of drivers of vulnerability, (2) increasingly aggregated scales significantly undercount highly vulnerable populations, and (3) hotspot clusters of social vulnerability and flood exposure can identify variable priority areas for current and future flood risk reduction. Study results present considerations about using such indicators, given the real-life consequences that can occur due to the MAUP. The results of this work warrant understanding the implications of scale selection on research methodological approaches and what this means for practitioners and policymakers that utilize such information to help guide flood mitigation strategies.

洪水是一种波及全球几乎所有领域的自然灾害，受气候变化与土地利用变化影响，其发生频率预计将持续提升、强度也将进一步加剧。但洪水对不同人群的影响并不均等。因此，厘清洪水影响在不同社会经济与人口特征群体间的分布规律，具有至关重要的意义。其中一种降低民众洪水风险的路径，是借助社会脆弱性指数（social vulnerability indices）、洪水暴露度指标（flood exposure metrics）等指标为洪水风险管理决策提供支撑。但此类指标往往会受到可修改面元问题（Modifiable Areal Unit Problem, MAUP）带来的尺度效应与分区效应的干扰。本研究以美国弗吉尼亚州沿海地区为研究区域，探讨美国人口普查街区组、普查区以及郡县这三种尺度的选择，会如何影响社会脆弱性与洪水暴露度的评估结果。研究结果显示：其一，尺度选择会阻碍我们对脆弱性驱动因素的认知；其二，尺度聚合程度越高，高度脆弱群体的统计漏算问题就越显著；其三，社会脆弱性与洪水暴露度的热点聚类分析，可识别出当前及未来洪水风险防控的差异化优先区域。鉴于可修改面元问题可能引发的现实后果，本研究结果可为此类指标的应用提供参考方向。本研究成果凸显了厘清尺度选择对研究方法论的影响的必要性，同时也阐明了这一因素对借助相关信息制定洪水减缓策略的从业者与政策制定者的实际意义。