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首页> 外文期刊>Stochastic environmental research and risk assessment >Effect of single and multi-site calibration techniques on hydrological model performance, parameter estimation and predictive uncertainty: a case study in the Logone catchment, Lake Chad basin
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Effect of single and multi-site calibration techniques on hydrological model performance, parameter estimation and predictive uncertainty: a case study in the Logone catchment, Lake Chad basin

机译：单站点和多站点校准技术对水文模型性能，参数估计和预测不确定性的影响：以乍得湖盆地洛格内流域为例

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Understanding hydrological processes at catchment scale through the use of hydrological model parameters is essential for enhancing water resource management. Given the difficulty of using lump parameters to calibrate distributed catchment hydrological models in spatially heterogeneous catchments, a multiple calibration technique was adopted to enhance model calibration in this study. Different calibration techniques were used to calibrate the Soil and Water Assessment Tool (SWAT) model at different locations along the Logone river channel. These were: single-site calibration (SSC); sequential calibration (SC); and simultaneous multi-site calibration (SMSC). Results indicate that it is possible to reveal differences in hydrological behavior between the upstream and downstream parts of the catchment using different parameter values. Using all calibration techniques, model performance indicators were mostly above the minimum threshold of 0.60 and 0.65 for Nash Sutcliff Efficiency ( NSE ) and coefficient of determination ( R _(2)) respectively, at both daily and monthly time-steps. Model uncertainty analysis showed that more than 60% of observed streamflow values were bracketed within the 95% prediction uncertainty (95PPU) band after calibration and validation. Furthermore, results indicated that the SC technique out-performed the other two methods (SSC and SMSC). It was also observed that although the SMSC technique uses streamflow data from all gauging stations during calibration and validation, thereby taking into account the catchment spatial variability, the choice of each calibration method will depend on the application and spatial scale of implementation of the modelling results in the catchment.
机译：通过使用水文模型参数了解流域尺度的水文过程对于加强水资源管理至关重要。考虑到使用集总参数来校准空间异质集水区中的分布式集水区水文模型的困难，在这项研究中采用了多种标定技术来增强模型标定。在Logone河道的不同位置，使用了不同的校准技术来校准土壤和水评估工具（SWAT）模型。它们是：单站点校准（SSC）；顺序校准（SC）;以及同时多站点校准（SMSC）。结果表明，可以使用不同的参数值揭示流域上游和下游部分之间水文行为的差异。使用所有校准技术，在每日和每月的时间步长上，模型性能指标大多分别高于纳什·舒克利夫效率（NSE）和确定系数（R _（2））的最小阈值0.60和0.65。模型不确定性分析表明，经过校准和验证后，超过60％的观测流量被包围在95％预测不确定性（95PPU）范围内。此外，结果表明，SC技术优于其他两种方法（SSC和SMSC）。还观察到，尽管SMSC技术在校准和验证过程中使用了来自所有测量站的流量数据，从而考虑到流域的空间变异性，但是每种校准方法的选择将取决于建模结果的应用和空间规模在流域。

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