SWAT和HBV模型对埃塞俄比亚青尼罗河上游流域流量估算的响应

Belay B. Bizuneh , Mamaru A. Moges , Berhanu G. Sinshaw , Mulu S. Kerebih
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引用次数: 15

摘要

该研究旨在评估SWAT和HBV模型的响应,以估计埃塞俄比亚青尼罗河上游三个典型流域的流量。通过对位于埃塞俄比亚青尼罗河上游流域的Gilgel Abay、Anger和Maybar三个流域的径流模拟进行评价。每个流域模型都采用相同的校准和验证周期,并具有各自的历史记录。目标函数表明了模型参数在校准和验证过程中的优化范围,并给出了良好的模型响应结果,这是由推荐的性能指标和水文图决定的。对于Gilgel Abay, Anger和Maybar流域,HBV和SWAT模型的校准响应分别为(NSE = 0.81, NSE = 0.48和NSE = 0.46)和(NSE = 0.81, NSE = 0.63, NSE = 0.61)。将优化后的参数应用于独立历史数据验证模型。在验证期内,SWAT和HBV模型对NSE的反应分别为0.8、0.55和0.54,Gilgel Abay、Anger和Maybe流域的反应分别为0.63、0.45和0.34。另一种方法是在极端潮湿和干燥时期的刺激期间高估和低估径流。总体而言,经校准和验证的水文曲线输出结果表明,模型对过湿和过干条件的响应不令人满意。因此,建议进一步改进极端事件的模型,包括基于季节的模型评估,以改善降雨径流事件的过程表示。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

SWAT and HBV models’ response to streamflow estimation in the upper Blue Nile Basin, Ethiopia

SWAT and HBV models’ response to streamflow estimation in the upper Blue Nile Basin, Ethiopia

The study aimed to evaluate the SWAT and HBV model’s responses to estimate streamflow in three typical selected watersheds in the upper Blue Nile Basin, Ethiopia. The evaluation was carried out through simulation of runoff in three watersheds, namely: Gilgel Abay, Anger, and Maybar located in the upper Blue Nile Basin, Ethiopia. The same calibration and validation period were applied for each watershed model with their respective historical records. The objective function indicates the optimized range of model parameters during the calibration and validation procedure, and it gives a good model response result, which is determined by the recommended performance indicators and hydrograph plots. The HBV and SWAT model’s calibration responds with (NSE = 0.81, NSE = 0.48 and NSE = 0.46) and (NSE = 0.81, NSE = 0.63, NSE = 0.61), respectively for Gilgel Abay, Anger, and Maybar watersheds. The optimized parameters were applied to validate the model using independent historical data. The SWAT and HBV model responses for NSE during the validation period were 0.8, 0.55, and 0.54 and 0.63, 0.45, and 0.34, respectively, for Gilgel Abay, Anger, and Maybe watersheds. An alternative was observed to over and under estimate runoff during stimulation periods in extreme wet and dry periods. Generally, the calibrated and validated hydrograph output result indicates that the model’s responses to too wet and dry conditions were not satisfactory. Therefore, further model refinements for extreme events, including season-based model evaluations that could improve the process representation of rainfall-runoff events, are recommended.

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