Spatial information on the distribution of ecosystem patterns and processes can be a critical component of designing and implementing effective management programs in river‐floodplain ecosystems. For example, translating how flood pulses detected within a stream gauge record are spatially manifested across a river‐valley bottom can be used to evaluate whether the current distribution of physical conditions has the potential to support priority habitats or if intervention is needed to meet desired goals. The size and complexity of large river‐floodplain systems can make mapping inundation dynamics a challenging task. We used a geospatial model to simulate 40 years (1972–2011) of daily surface‐water inundation depths for 11,331 km² of the Upper Mississippi River System floodplain. We identified discrete inundation events at each 4‐m × 4‐m pixel in the model as sequential days of submergence. We then quantified and mapped four aspects of inundation regime – event frequency, duration, magnitude, and timing – for each pixel. The spatial distribution of inundation regime attributes varied within and among multiple levels of river organization, including navigation pools and geomorphic reaches, but only event timing exhibited a strong down‐river trend. Non‐linear relations among inundation attributes and their geospatial distributions likely reflect complex interactions among topographic, hydrologic, and anthropogenic constraints on flooding dynamics. Together, our results reveal spatial gradients in inundation dynamics not captured by hydrologic data alone. Characterizing such diversity in inundation dynamics is important for testing hypotheses about ecological processes, developing models of ecosystem functions, and informing management actions.

中文翻译：

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量化和绘制大型河漫滩生态系统中的淹没状况，以进行生态和管理应用

有关生态系统模式和过程分布的空间信息可能是设计和实施河漫滩生态系统中有效管理计划的重要组成部分。例如，转换在水位计记录中检测到的洪水脉冲如何在空间上体现在河谷底部，可以用于评估当前的自然条件分布是否有潜力支持优先生境，或者是否需要干预才能达到预期目标。大型河漫滩系统的规模和复杂性会使地图淹没动力学成为一项艰巨的任务。我们使用地理空间模型模拟了11331 km ^2的40年（1972-2011年）每日地表水淹没深度密西西比河上游河流泛滥平原。我们将模型中每个4 m×4 m像素处的离散浸水事件确定为淹没的连续天数。然后，我们对每个像素的淹没状态的四个方面进行了量化和映射-事件发生频率，持续时间，大小和时序。淹没状态属性的空间分布在河流组织的多个层次之内和之中各不相同，包括导航池和地貌河段，但只有事件时机表现出强烈的下游趋势。淹没属性及其地理空间分布之间的非线性关系很可能反映了地形，水文和人为因素对洪水动力学的复杂影响。总之，我们的研究结果揭示了淹没动力学中的空间梯度不能仅由水文数据来捕获。