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，洪泛平原承担着多种关键生态功能。近期一项针对美国中部密西西比河中上游及密苏里河下游沿岸80处洪泛平原保护用地管理者的调研显示，优化洪泛平原管理所需的核心信息，集中于表征淹没深度、范围、频次、持续时长与淹没时机的各类指标。此类指标可通过基于云端的交互式地图高效交付给管理者。为计算这些指标，我们针对密苏里河下游河段构建了现有一维HEC-RAS水力模型的插值版本，该模型以间距不足1千米的断面模拟水面高程，可在每日时间步长下，基于80年的逐日观测记录，充分表征从密西西比河汇流处上游约800千米河段的水面形态。为将水面高程转化为淹没深度，我们采用了融合洪泛平原激光雷达（LIDAR）与河道水深测量数据的合并地形模型，通过将水面高程与该合并地形模型相减得到淹没深度。我们针对内布拉斯加州鲁洛至密苏里河与密西西比河汇流处的800千米密苏里河河段完成了全部计算，最终生成了空间分辨率30米的网格单元对应的29000余天的洪泛平原淹没深度时间序列。本数据集包含两种情景下的17项指标：其一为基于HEC-RAS模拟水位的基准时间序列，其二为针对某一可能气候变化情景下径流变化调整后的水位时间序列。这些指标以逐像素为单位计算，涵盖了洪泛平原管理者所关注的各类目标动植物相关的时间维度标准，例如生长季内的年均淹没天数。我们还提供了两种情景下按重现期划分的洪泛平原水深分布图，以及每个像素首次被淹没的最小重现期。最后，我们附上了用于通过插值水面高程计算淹没深度的基础高程图层。