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    基于MSWEP降水数据的缺资料小流域径流推求研究

    Study on Streamflow Estimation in a Data-Scarce Small Watershed Based on MSWEP Precipitation Data

    • 摘要: 由于小流域通常缺乏足够的径流观测乃至降水监测资料,长系列径流推求及设计值计算面临较大困难.近年兴起的卫星遥感与大气再分析等全球性降水数据提供了新的降水信息,也为小流域径流资料的获取提供了新途径.以浙江省温州市仰义水库流域为例,研究了全球性降水资料MSWEP的局地订正方法,并利用订正后MSWEP降水资料推求长系列径流过程及设计洪水.研究表明,特征增强型随机森林算法不仅可有效削减MSWEP日降水量的系统偏差,且改善了定量和分类精度,对各季节降水均具有较好订正效果.与传统邻近雨量站点移植方法相比,订正后MSWEP降水资料在小流域径流推求和设计洪水计算中具有一定应用潜力.当重现期处于1000年一遇至50年一遇时,MSWEP推求的设计洪峰流量较瞿溪站移植降水量推求值偏低8.51%~11.33%,3日洪量偏低4.95%~7.22%.

       

      Abstract: The scarcity of sufficient streamflow observations,and in some cases,ground-based precipitation measurements in small watersheds poses substantial challenges for reconstructing long-term streamflow series and estimating design floods.In recent years,the increasing availability of global precipitation products derived from satellite observations and atmospheric reanalysis has provided new opportunities for hydrological applications in data-scarce regions.This study investigated an ungauged small watershed—the Yangyi Reservoir watershed in Wenzhou,Zhejiang Province,China,and developed a local correction framework for the Multi-Source Weighted-Ensemble Precipitation (MSWEP) dataset.The corrected MSWEP precipitation was then applied to estimate long-term streamflow series and to calculate design floods in the ungauged small watershed.The results demonstrate that the Feature-Enhanced Random Forest (FERF) algorithm effectively improves the consistency between MSWEP and gauge-based precipitation at both daily and seasonal scales,leading to enhanced accuracy in local precipitation estimation.Compared with the traditional neighboring-gauge transplantation methods,the corrected MSWEP dataset shows some potential in streamflow estimation and design flood calculation.For return periods ranging from 1000 to 50 years,the design peak discharges derived from corrected MSWEP precipitation are 8.51%~11.33% lower than those obtained using Quxi Gauge-transplanted precipitation,while the corresponding 3-day flood volumes are underestimated by 4.95%~7.22%.

       

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