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 surface elevation 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中游与密苏里河下游沿岸80名河漫滩保护地管理者的调研显示，优化河漫滩管理所需的核心信息，集中于表征淹没深度、淹没范围、淹没频次、淹没时长与淹没时机的量化指标。上述量化指标可通过基于云端的交互式地图高效传递给管理者。
为计算上述量化指标，我们针对密苏里河下游对现有一维HEC-RAS水力学模型开展插值处理：该模型以日时间步长完成了80年时长的模拟，对密西西比河汇流口上游约800公里河段内间距小于1公里的断面处的水面高程进行刻画，可充分表征该河段的水面剖面特征。为将模拟得到的水面高程转换为淹没水深，我们以融合河漫滩激光雷达（LIDAR）与河道水深测量数据的合并地形模型的高程值为基准，通过水面高程与该基准高程的差值计算得到淹没水深。
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口的800公里密苏里河河段上完成了上述计算。该方法生成了空间分辨率为30米的河漫滩淹没水深时间序列，时长超29000天。
本数据集包含两种情景下的共17项量化指标：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径流变化进行校正后的水位时间序列。上述指标均以逐像素为单位计算，涵盖了河漫滩管理者所关注的各类与目标动植物相关的时间维度评判标准，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面高程分布图，以及每个像素发生淹没的最小重现期。此外，本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。