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Distributed Hydrological Modeling: Determination of Theoretical Hydraulic Potential & Streamflow Simulation of Extreme Hydrometeorological Events

机译:分布式水文建模:理论水力势的确定和极端水文气象事件的水流模拟

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The progressive change in climatic conditions worldwide has increased frequency and severity of extreme hydrometeorological events (EHEs). México is an example that has been affected by the occurrence of EHE leading to economic, social, and environmental losses. The objective of this research was to apply a Canadian distributed hydrological model (DHM) to tropical conditions and to evaluate its capacity to simulate flows in a basin in the central Gulf of Mexico. In addition, the DHM (once calibrated and validated) was used to calculate the theoretical hydraulic power (THP) and the performance to predict streamflow before the presence of an EHE. The results of the DHM show that the goodness of fit indicators between the observed and simulated flows in the calibration process Nash-Sutcliffe efficiency ( NSE ) = 0.83, ratio of the root mean square error to the standard deviation of measured data ( RSR ) = 0.41, and percent bias ( PBIAS ) = ?4.3) and validation ( NSE = 0.775, RSR = 0.4735, and PBIAS = 2.45) are satisfactory. The DHM showed its applicability: determination of THP showed that the mean flows are in synchrony with the order of the river reaches and streamflow simulation of 13 EHEs ( NSE = 0.78 ± 0.13, RSR = 0.46 ± 0.14 and PBIAS = ?0.48 ± 7.5) confirmed a reliable efficiency. This work can serve as a tool for identifying vulnerabilities before floods and for the rational and sustainable management of water resources.
机译:世界范围内气候条件的逐步变化增加了极端水文气象事件(EHE)的频率和严重性。墨西哥就是受到EHE的影响而导致经济,社会和环境损失的一个例子。这项研究的目的是将加拿大分布式水文模型(DHM)应用于热带条件,并评估其模拟墨西哥中部海湾盆地水流的能力。此外,使用DHM(一旦经过校准和验证)就可以计算出EHE之前的理论水力(THP)和预测流量的性能。 DHM的结果表明,在校准过程中,观察到的流量与模拟流量之间的拟合指标良好。Nash-Sutcliffe效率(NSE)= 0.83,均方根误差与测量数据的标准偏差之比(RSR)= 0.41,百分比偏差(PBIAS)=?4.3)和验证(NSE = 0.775,RSR = 0.4735,PBIAS = 2.45)是令人满意的。 DHM显示出其适用性:THP的测定表明,平均流量与河段的顺序是同步的,并且模拟了13个EHE(NSE = 0.78±0.13,RSR = 0.46±0.14和PBIAS =α0.48±7.5)。确认了可靠的效率。这项工作可以作为一种工具,用于确定洪水前的脆弱性以及合理和可持续地管理水资源。

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