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首页> 外文期刊>Journal of hydrologic engineering >Estimating Flood Discharges in Reservoir-Regulated River Basins by Integrating Synthetic SWOT Satellite Observations and Hydrologic Modeling
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Estimating Flood Discharges in Reservoir-Regulated River Basins by Integrating Synthetic SWOT Satellite Observations and Hydrologic Modeling

机译：综合SWOT卫星观测资料和水文模型估算水库调度流域的洪水流量

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摘要

Lakes and reservoirs are widely used for water supply and flood control, especially during large storm events. In hydrologic modeling applications, accounting for the regulated behavior of reservoirs distributed throughout a river system poses a significant challenge, especially during flood events, when detailed reservoir operation rules and strategies are implemented. Building on this problem, this study addresses this question: Can we model reservoir water storage changes and outlet discharges based on satellite measurements of river water surface elevation and inundated areas especially during the flood event? A method is presented and evaluated using synthetic observations as a proxy for measurements from the forthcoming surface water and ocean topography (SWOT) satellite mission. The May 2010 flood event in the Cumberland River Basin is used as a case study. Based on synthetic SWOT observation, time series of water storage changes are generated and evaluated for eight reservoirs. As expected, although SWOT will provide relatively high temporal resolution measurements (i.e., three or four times per repeat cycle) compared with current point-based satellite altimeters, it provides only a 5% chance of direct observation of the 2-day flash flood event. To overcome this limitation, a new algorithm using the continuity equation and ensemble Kalman filter is presented to augment SWOT-estimated water storage changes for times between SWOT overpasses at eight reservoirs located throughout the watershed. The algorithm provides accurate storage changes with a 9% normalized RMS error (NRMSE). SWOT-estimated storage changes and reservoir routing are integrated into the Hillslope River Routing model to estimate inflows and outflows for the reservoirs. The average NRMSE for reservoir outflow is 28%, which is a 64% improvement compared with not including reservoir routing. At the watershed outlet, which integrates all eight reservoirs, the NRMSE and peak discharge error (EQ_P) for discharge estimates are 9 and 28%, respectively. The approach, which is entirely based on remotely sensed data and is potentially applicable in global scale models, reduced NRMSE by 73% and EQ_P by 85% compared with the simulated discharges, without accounting for reservoir routing.
机译：湖泊和水库被广泛用于供水和防洪，特别是在暴风雨期间。在水文建模应用中，要考虑到分布在整个河流系统中的水库的调节行为，这是一个巨大的挑战，特别是在洪水事件期间，当实施详细的水库运行规则和策略时。在这个问题的基础上，本研究解决了这个问题：我们能否基于卫星对河流水面高程和淹没区域（尤其是在洪水事件期间）的测量来对水库蓄水量变化和出口流量建模？提出并评估了一种方法，使用合成观测值作为对即将到来的地表水和海洋地形（SWOT）卫星任务进行测量的代理。以坎伯兰河流域2010年5月的洪水事件为例。基于合成的SWOT观测结果，生成并评估了8个水库的储水量变化的时间序列。不出所料，尽管与当前的基于点的卫星高度计相比，SWOT将提供相对较高的时间分辨率测量（即，每个重复周期三至四次），但仅提供5％的机会直接观测2天的暴洪事件。为了克服这一限制，提出了一种使用连续性方程和集成卡尔曼滤波器的新算法，以在整个流域的八个水库的SWOT立交之间增加SWOT估计的储水量变化。该算法可提供准确的存储更改，并具有9％的RMS标准化误差（NRMSE）。 SWOT估计的存储量变化和水库调度已集成到Hillslope河调度模型中，以估算水库的流入和流出。油藏流出的平均NRMSE为28％，与不包括油藏布放的路线相比，提高了64％。在将所有八个水库整合在一起的流域出口处，用于排放估算的NRMSE和峰值排放误差（EQ_P）分别为9％和28％。该方法完全基于遥感数据，并且可能适用于全球规模模型，与模拟排放量相比，NRMSE降低了73％，EQ_P降低了85％，而无需考虑油藏路线。

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