Native riparian vegetation communities have declined downstream of large water infrastructure like dams and diversions, owing to water management operations that prevent successful seedling colonization and recruitment. Altered timing and magnitude of reservoir releases to fulfill competing water demands often lead to reduced peak discharges and flow recession rates that do not support native riparian reproduction processes. To achieve short-term ecosystem function in highly regulated rivers an alternative method might be restoration planting, whereby success depends on identifying appropriate planting location and spatial extents. This study aims to provide a methodology to inform resource managers about the extent of possible natural seedling recruitment under average and wet hydrologic conditions, as well as constrain restoration planting operational uncertainties. Results from field surveys and simulations showed limited favorable areas for successful riparian seedling recruitment under regulated flows, regardless of hydrologic conditions in the basin. However, wet (11.4 ha) hydrologic conditions were more (approximately 11 times) favorable than average (1 ha) conditions for seedling recruitment. Furthermore, model results identified the location and spatial extent (25.6 ha) of favorable restoration planting areas during average flow. This extent is approximately 25 times larger than natural recruitment during an average (hydrological) year and even twice that for natural recruitment for a wet year. This suggests that ground operational activities guided by numerical modeling may effectively constrain planting uncertainties.

由于水管理活动阻止了幼苗的成功定居和募集，原生河岸植被群落在大型水利基础设施（如水坝和改道工程）的下游逐渐减少。为了满足竞争性水需求，改变储层释放的时间和幅度通常会导致峰值排放量减少和流量下降速率降低，这不支持原生河岸繁殖过程。为了在高度管制的河流中实现短期的生态系统功能，另一种方法可能是恢复种植，其中成功取决于确定适当的种植位置和空间范围。这项研究旨在提供一种方法，以告知资源管理者在平均和潮湿水文条件下可能招募的天然苗木的范围，以及限制恢复种植的操作不确定性。实地调查和模拟结果表明，无论流域的水文条件如何，在调节流量下，成功招募河岸苗的有利区域有限。但是，湿润（11.4公顷）的水文条件比幼苗募集的平均（1公顷）条件更有利（约11倍）。此外，模型结果确定了平均流量期间有利的恢复种植面积的位置和空间范围（25.6公顷）。这个程度大约是平均（水文）年自然招募的25倍，甚至是潮湿年份自然招募的两倍。这表明，以数值模型为指导的地面作业活动可能有效地限制了播种的不确定性。