基于CN05.1数据集驱动SWAT模型的玉龙喀什河流域径流模拟

Runoff Simulation of Yulong Kashi River Basin Based on CN05.1 Dataset Driven SWAT Model

为探究CN05.1数据集驱动下的SWAT模型在气象站稀缺地区模拟效果以及流域径流对气候变化的响应,选取玉龙喀什河流域为研究区,利用上述数据集驱动SWAT模型对该流域1991—2020年进行逐月径流模拟,在此基础上,设置了25种气候情景模式,通过模型导入25种气候情景下气象数据模拟径流。结果表明:CN05.1+SWAT模型适用于玉龙喀什河流域的径流模拟,模拟结果与实测数据吻合较好,率定期和验证期的决定系数(R^(2))、纳什系数(C_(NS))和百分比偏差(σ_(P))均达到模型评价标准,率定期(1991—2005)C_(NS)、R^(2)、σ_(P)分别为0.85、0.86、-10.35%,验证期(2006—2020)C_(NS)、R^(2)、σ_(P)分别为0.76、0.79、-14.75%;CN05.1数据集可以为无气象资料的玉龙喀什河流域水文模拟提供时间连续、时间序列长、高分辨的气象数据,可用作后续的研究与应用;CN05.1数据集能够准确反映玉河流域的下垫面和地表大气特征;玉龙喀什河流域年径流量与温度和降水皆呈正相关,2个因子中温度变化对径流的影响更为显著,降水-温度-径流量之间基本可以用平面函数表达,决定系数为0.9957,方差为0.0002,均方根误差为0.0123。

To investigate the simulation performance of the SWAT model driven by the CN05.1 dataset in areas lacking meteorological stations and the response of basin runoff to climate change,the Yulong Kashi River Basin is selected as the study area.This paper uses the aforementioned dataset to drive the SWAT model to conduct monthly runoff simulations of the basin from 1991 to 2020.On this basis,25 climate scenario models are set up,and runoff is simulated by importing meteorological data under these 25 climate scenarios into the models.The results show that the CN05.1+SWAT model is suitable for runoff simulation in the Yulong Kashi River Basin,with good agreement between the simulated results and the measured data.The coefficient of determination(R^(2)),Nash-Sutcliffe efficiency coefficient(C_(NS)),and percentage bias(σ_(P))of both calibration and validation period meet the evaluation criteria for runoff simulation.R^(2),C_(NS) andσ_(P) during the calibration period(1991—2005)are 0.85,0.86,and−10.35%,respectively.During the validation period(2006—2020),they are 0.76,0.79 and−14.75%,respectively.The CN05.1 dataset provides continuous meteorological data with high resolution in a long time series for hydrological simulations in the Yulong Kashi River Basin,which lacks meteorological observations.Therefore,this dataset can be used for future research and in other applications.The CN05.1 dataset can accurately reflect the underlying surface and surface atmospheric characteristics of the Basin.Annual runoff in the Basin shows a positive correlation with both precipitation and temperature,whose change has a more significant impact on runoff.The relationship among precipitation,temperature,and runoff can be expressed by a plane function,with an R^(2) of 0.9957,variance of 0.0002,and root mean square error of 0.0123.