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Estimation of antecedent wetness conditions for flood modelling in northern Morocco

机译:摩洛哥北部洪水建模的前期湿润条件估算

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In northern Morocco are located most of the dams and reservoirs of the country, while this region is affected by severe rainfall events causing floods. To improve the management of the water regulation structures, there is a need to develop rainfall-runoff models to both maximize the storage capacity and reduce the risks caused by floods. In this study, a model is developed to reproduce the flood events for a 655 km2 catchment located upstream of the 6th largest dam in Morocco. Constrained by data availability, a standard event-based model combining a SCS-CN (Soil Conservation Service Curve Number) loss model and a Clark unit hydrograph was developed for hourly discharge simulation using 16 flood events that occurred between 1984 and 2008. The model was found satisfactory to reproduce the runoff and the temporal evolution of floods, even with limited rainfall data. Several antecedent wetness conditions estimators for the catchment were compared with the initial condition of the model. Theses estimators include an antecedent discharge index, an antecedent precipitation index and a continuous daily soil moisture accounting model (SMA), based on precipitation and evapotranspiration. The SMA model performed the best to estimate the initial conditions of the event-based hydrological model (R2 Combining double low line 0.9). Its daily output has been compared with ASCAT and AMSR-E remote sensing data products, which were both able to reproduce with accuracy the daily simulated soil moisture dynamics at the catchment scale. This same approach could be implemented in other catchments of this region for operational purposes. The Results of this study suggest that remote sensing data are potentially useful to estimate the soil moisture conditions in the case of ungauged catchments in Northern Africa.
机译:摩洛哥北部是该国大部分水坝和水库,而该地区受到严重降雨事件的影响,导致洪水泛滥。为了改善水调节结构的管理,需要开发降雨径流模型,以最大化存储容​​量并减少洪水带来的风险。在这项研究中,开发了一个模型来重现摩洛哥第六大水坝上游655 km2集水区的洪水事件。受数据可用性的约束,开发了一个基于事件的标准模型,该模型结合了SCS-CN(水土保持服务曲线编号)损失模型和Clark单位水位图,用于使用1984年至2008年之间发生的16次洪水事件进行小时流量模拟。即使降雨数据有限,也发现能够令人满意地再现洪水的径流和时间演变。流域的几个先前湿度条件估算器与模型的初始条件进行了比较。这些估算器包括基于降水量和蒸散量的前期排放指数,前期降水指数和连续的每日土壤水分核算模型(SMA)。 SMA模型在估计基于事件的水文模型( R 2组合双低线0.9)的初始条件方面表现最佳。它的日产量已与ASCAT和AMSR-E遥感数据产品进行了比较,它们都能够精确地再现流域尺度上的每日模拟土壤水分动态。出于业务目的,可以在该区域的其他流域实施相同的方法。这项研究的结果表明,在北非流域未开垦的情况下,遥感数据可能有助于估算土壤湿度状况。

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