Science to Inform Management of Floodplain Conservation Lands under Non-Stationary Conditions

Within large-river ecosystems, floodplains serve a variety of important ecological functions. A recent survey of 80 managers of floodplain conservation lands along the Upper and Middle Mississippi and Lower Missouri Rivers in the central United States found that the most critical information needed to improve floodplain management centered on metrics for characterizing depth, extent, frequency, duration, and timing of inundation. These metrics can be delivered to managers efficiently through cloud-based interactive maps. To calculate these metrics, we interpolated an existing one-dimensional HEC-RAS hydraulic model for the Lower Missouri River, which simulated water surface elevations at cross sections spaced (<1 kilometer) to sufficiently characterize water surface profiles along an approximately 800 kilometer stretch upstream from the confluence with the Mississippi River over an 80-year record at a daily time step. To translate these water surface elevations to inundation depths, we subtracted a merged terrain model consisting of floodplain LIDAR and bathymetric surveys of the river channel. We completed these calculations for an 800 kilometer stretch of the Missouri River, spanning from Rulo, Nebraska to the river's confluence with the Mississippi River. This approach resulted in a 29,000+ day time series of inundation depths across the floodplain using grid cells with 30 meter spatial resolution. This dataset presents 17 metrics for each of two scenarios, one using a baseline timeseries of stages from the HEC-RAS simulation and one using a timeseries of stages adjusted to account for changes in discharge under one possible climate change scenario. These metrics are calculated on a per pixel basis and encompass a variety of temporal criteria generally relevant to flora and fauna of interest to floodplain managers, including, for example, the average number of days inundated per year within a growing season. We also include a series of maps of water depths across the floodplain by return interval for each scenario, and the minimum return interval at which each pixel is inundated. Lastly, we include the base elevation layer that we generated to calculate depth of inundation from interpolated water-surface elevations.

在大型河流生态系统中，河漫滩（floodplain）承担着诸多关键生态功能。近期一项针对美国中部密西西比河上游、中游以及密苏里河下游沿岸80名河漫滩保护用地管理者的调研显示，优化河漫滩管理所需的核心信息，集中于表征洪水淹没深度、范围、频次、持续时长及发生时机的各类指标。此类指标可通过基于云端的交互式地图高效传递给管理者。为计算此类指标，我们对密苏里河下游已有的一维HEC-RAS水力学模型进行插值处理：该模型以每日时间步长，基于80年的逐日观测数据，对密西西比河汇流点上游约800公里的河段内间距小于1公里的河道断面处的水面高程进行模拟，以充分刻画该河段的水面形态。为将水面高程转换为淹没水深，我们将水面高程减去由河漫滩激光雷达（LIDAR）与河道水深测量数据融合得到的地形模型高程，以此得到淹没水深。我们在内布拉斯加州鲁洛（Rulo）至密苏里河与密西西比河汇流点的800公里河段范围内完成了上述计算。本方法采用空间分辨率为30米的网格单元，生成了覆盖整个河漫滩的、时长超29000天的淹没水深时间序列数据集。本数据集包含两种情景下的17项指标：其一为基于HEC-RAS模拟得到的基准水位时间序列，其二为针对某一气候变化情景下的径流变化进行调整后的水位时间序列。此类指标以单个像素为单位计算，涵盖了河漫滩管理者关注的动植物相关的各类时间维度标准，例如生长季内年均淹没天数。本数据集还提供了两种情景下基于重现期的河漫滩水深分布图，以及各像素发生淹没的最小重现期。此外，数据集还包含我们为通过插值水面高程计算淹没水深而生成的基础高程图层。