Constraining coupled hydrological-hydraulic flood model by past storm events and post-event measurements in data-sparse regions
Constraining coupled hydrological-hydraulic flood model by past storm events and post-event measurements in data-sparse regions
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DOI：
10.1016/j.jhydrol.2018.08.008
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发表时间：
2018-10
影响因子：
6.4
通讯作者：
Rouya Hdeib;C. Abdallah;F. Colin;L. Brocca;R. Moussa
中科院分区：
文献类型：
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作者：
Rouya Hdeib;C. Abdallah;F. Colin;L. Brocca;R. Moussa
数据稀疏地区的洪水建模始终仅限于适合生成区域灾害地图的经验、统计或地貌方法。这种粗分辨率地图不适合流域规模的应用，中小型流域（<1000km2），特别是当需要对特定事件的流量和水位进行详细估计时，因此不能取代水文/水力模型。在数据稀疏的地区，后者是一项具有挑战性的任务，该地区的洪水通常持续时间为几个小时，传统雨量计网络、遥感或卫星成像几乎没有机会进行实时记录。这种数据稀疏性并不总是与水文和水力模型的空间和时间分辨率兼容。我们提出了一个洪水建模框架，使用来自过去风暴事件和空间事件后测量约束的耦合水文水力模型的稀疏数据。该方法适用于黎巴嫩阿瓦利河流域（301 平方公里），特别是模拟所调查的 2013 年 1 月上旬的极端洪水事件，该事件被认为是过去三十年来最大的事件之一。水文模型通过过去 12 次风暴事件进行了校准和评估，旨在定义狭窄的参数范围，并通过蒙特卡罗模拟对这些参数范围进行不确定性。该水力模型基于高分辨率 DEM，使用水文流出进行模拟，并通过高水位空间中的 27 次事件后测量进行验证。得到的流出值令人满意，并且与任意宽的参数范围相比，不确定性降低了。水文模型的性能变化很大，但对于水力模型来说，93% 的观测水位落在模拟的不确定性范围内，RMSE 误差为 0.26m。所提出的框架允许绘制可能的洪水图，并且可以与处理模型复杂性和相关性能的其他方法进行比较。
Flood modelling in data-sparse regions have been always limited to empirical, statistical or geomorphic approaches that are suitable to produce regional hazard maps. Such coarse resolution maps are not adapted for basin-scale applications, small to medium sized basins (<1000 km2), especially when detailed estimates of flows and water levels of a particular event is required and hence cannot replace the hydrological/hydraulic modelling. The latter is a challenging task in data-sparse regions characterized by floods of typical duration times of a few hours which offer little opportunity for real-time recording by traditional rain-gauge networks, remote sensing or satellite imaging. Such data sparseness is not always compatible with the resolution, in both space and time, of the hydrological and hydraulic models. We propose a framework for flood modelling using sparse data from a coupled hydrological-hydraulic model constrained by past storm events and post-event measurements in space. The approach is applied to the Awali river basin (301 km2), in Lebanon, particularly to simulate the investigated early January 2013 extreme flood event, which is considered one of the largest events in the last three decades. The hydrological model was calibrated and evaluated with 12 past storm events aiming at defining narrow parameter ranges and uncertainty was performed with Monte Carlo simulations for these parameter ranges. The hydraulic model, based on a fine resolution DEM, was simulated using hydrological outflows and validated with 27 post-event measurements in space of high water marks. The resulting outflow values were satisfactory, and uncertainty was reduced when compared with arbitrarily wide parameter ranges. The hydrological model performance was highly variable but for the hydraulic model, 93% of the observed water levels fall within the simulated uncertainty bounds with an RMSE error of 0.26 m. The proposed framework allows mapping the possible inundation and can be compared to other approaches dealing with model complexity and associated performances.