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Investigating different methods of estimating annual flood discharge in basins and presenting a new regression model based on physiographic features
Applied Water Science ( IF 5.7 ) Pub Date : 2025-05-27 , DOI: 10.1007/s13201-025-02474-6
Yaser Hoseini

Due to the high cost of constructing a hydrometric station, it is not possible to measure water level on all rivers. Therefore, the estimation of water flow of these rivers is one of the basic needs of water resources projects. In this research, various experimental methods presented to estimate the annual flood discharge in the basins, including the regression, Inglis and De’Souza and the Indian Department of Irrigation (IDOI), Turc, Coutagine, Khosla, Indian Council of Agricultural Research (ICAR), Justin and Lacey methods were examined and evaluated in a number of sub-basins of the Dareh-Rood in Ardabil province. In this research, the discharge data of 7 hydrometric stations with a common statistical period of 15 years were collected during 1380–94 and the incomplete data related to the stations were completed using statistical methods. Then, using ArcGIS and WMS software, the physiographic characteristics of the sub-basins, including the area, slope, shape factor and average height of the sub-basins were extracted. The root mean square error, relative percentage error (ε), mean absolute error (MAE), Coefficient of residual mass and model efficiency (EF) were calculated to evaluate the models. The results showed that the order of the accuracy of the methods decreases from the regression method, Coutagine, Turc, IDOI, ICAR, Lacey, JUSTIN, Inglis and De’Souza and Khosla, respectively. For the regression model, these statistics were estimated as 21.9 21.09, 0.01 and 0.1, respectively. The results showed that except for the regression model, none of the experimental methods provided reliable results and amount of runoff estimated by the regression model for different basins is in good agreement with the observed runoff data.



中文翻译:

研究了估算流域年洪水流量的不同方法,并提出了一种基于地形特征的新回归模型

由于建造水文测量站的成本很高,因此无法测量所有河流的水位。因此,估算这些河流的水流量是水资源工程的基本需求之一。在这项研究中,提出了各种实验方法来估计流域的年洪水流量,包括回归法、Inglis 和 De'Souza 以及印度灌溉部 (IDOI)、Turc、Coutagine、Khosla、印度农业研究委员会 (ICAR)、Justin 和 Lacey 方法在阿尔达比勒省的 Dareh-Rood 的许多子流域中进行了检查和评估。在这项研究中,收集了 1380-94 年间 7 个共同统计周期为 15 的水文测量站的流量数据,并使用统计方法完成了与这些站相关的不完整数据。然后,利用 ArcGIS 和 WMS 软件提取子流域的地貌特征,包括子流域的面积、坡度、形状因子和平均高度。计算均方根误差、相对百分比误差 (ε )、平均绝对误差 (MAE) 、残余质量系数和模型效率 (EF) 以评估模型。结果表明,方法的准确性顺序分别从回归法、Coutagine、Turc、IDOI、ICAR、Lacey、JUSTIN、Inglis 和 De'Souza 和 Khosla 开始下降。对于回归模型,这些统计数据分别估计为 21.9 21.09 、 0.01 和 0.1。结果表明,除回归模型外,所有实验方法均未提供可靠的结果,回归模型估计的不同流域径流量与观测径流数据吻合较好。

更新日期:2025-05-27
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