First Street Foundation's National Flood Adaptation Database

In order to create a national model with complete coverage of the contiguous United States, the First Street Foundation Flood Model relies on nationally available data that consistently represents the hydrologic conditions of the United States. However, most of this data represents the natural environment better than the modifications made by human activity that impact hydrology and therefore flooding. To make this model as accurate a representation of actual flood risk as possible, First Street has spent considerable time and effort to build a database of “grey” and “green” infrastructure and adaptation projects that affect the flow of water and therefore flooding. Grey Flood control projects include a variety of traditional infrastructure solutions like levees, pump stations, and flood control channels. Many green infrastructure projects also contribute to flood reduction, such as wetland restoration, floodable open space, retention basins, and creek rehabilitation projects. The First Street Foundation Flood Model also records and accounts for climate adaptation projects such as beach renourishment projects that are designed to counteract the effects of rising seas. This data is collected from state, county, and city agencies across the United States. It is digitized by drawing the area for which a structure is providing flood protection and assigned a level of protection provided. These service areas can range in size from a few residential blocks to a small city. Each feature is associated with one or more sources of flooding for which it provides protection. Estimates of the level of protection are based on the return period to which it will continue to function. This data is accounted for in the hydraulic and hydrologic model in several different ways. In most places, water is blocked within the model from entering a service area. This is similar to how a levee operates in real life, blocking water from entering a given location and pushing it somewhere else. Importantly, water is not removed from the model. In other cases like various runoff reduction green infrastructure projects, the service area of the project represents a change in the underlying soil classification within the hydrologic model. This replicates the way green infrastructure projects reduce runoff from their service area. In still other projects such as pump stations, the service area represents an adjustment to the flow of water in an area. Just as a pump station has a certain flowrate at which it will continue to be effective, even in an event beyond its design standard, this is represented in the model by removing an amount of flooding from an area equivalent to the modeled flow in the project’s service area at the design standard. So a pump station designed for a 5 year event would always remove the equivalent of the 5 year event, even in a 100 year event. You can download a sample of the database through Zenodo. If you wish to acquire the adaptation database, you can do so by reaching out to First Street Foundation here.为构建覆盖美国本土全域的国家级洪水模型，第一街基金会洪水模型（First Street Foundation Flood Model）依托全国范围内可获取的、能够一致表征美国水文状况的数据集开展研发。然而，此类数据大多更能体现自然环境特征，却难以准确反映人类活动对水文及洪水过程造成的改造影响。为使模型尽可能精准还原实际洪水风险，第一街基金会投入大量时间与精力，构建了一套涵盖影响水流及洪水过程的灰色基础设施（grey infrastructure）与绿色基础设施（green infrastructure）及适应性改造项目的数据库。 灰色防洪工程包含各类传统基础设施解决方案，例如堤防、泵站及防洪河道等。诸多绿色基础设施项目同样可助力洪水消减，如湿地修复、可淹没开放空间、滞留塘及河道整治项目等。第一街基金会洪水模型还收录并考量了旨在缓解海平面上升影响的气候适应性项目，例如海滩养滩工程。 该数据集采集自美国各州、郡及市级政府机构，通过绘制结构物提供防洪保护的范围并标定其防护等级完成数字化处理。其服务区域规模跨度较大，可从数个居民街区延伸至小型城市。每个设施均对应一种或多种其可提供防护的洪水类型。 防护等级的估算基于该设施可持续发挥作用的重现期。此类数据将通过多种方式纳入水文水力学模型：在多数场景下，模型会阻止水流进入防护服务区域，这与现实中堤防的运作逻辑一致——阻挡水流进入指定区域并将其导至别处，需特别说明的是，模型不会将水流从系统中移除。 针对各类径流消减型绿色基础设施项目，项目服务区域对应水文模型中底层土壤分类的调整，以此复现绿色基础设施项目消减其服务区域内径流的实际效果。而在泵站等其他项目中，服务区域代表对区域内水流过程的调整。正如泵站在超出设计标准的极端事件中仍可维持一定流量效率，模型中通过移除服务区域内对应设计标准下模拟流量当量的洪水量来体现这一特性。例如，一座按5年一遇标准设计的泵站，即便在100年一遇的洪水事件中，仍可移除相当于5年一遇洪水当量的积水。 用户可通过Zenodo平台下载该数据库的样本数据。若需获取完整的适应性改造数据库，可通过指定渠道联系第一街基金会进行获取。