{"title":"水文观测与流域特征估算麝香草参数的比较分析","authors":"Y. M. Kim, C. S. Yoo, S. Yoon","doi":"10.36334/modsim.2023.kim371","DOIUrl":null,"url":null,"abstract":": The usefulness of the Muskingum model for flow routing has been widely recognized and made the model one of the most commonly used hydrologic channel flood routing models. Despite its wide application in hydrologic flood routing, the model is unsuitable for ungauged channel reaches due to its need for data from hydrologic observations for the estimation of its parameters. This paper uses a different method based on basin characteristics suggested by Yoo et al. (2013) at Chungju Dam basin to compare its results with the current hydrologic observation based parameter estimation method. The Chungju Dam basin was divided into subbasins and each subbasin’s exit was further divided into either upstream or downstream section of the channel reach. Rainfall data from 2010 to 2020 was used and a total of 55 rainfall events were selected from the entire data. 12 channel reaches were formed based on 15 water level stations within the study basin. The amount of storage was calculated using the inflow and outflow hydrographs for every channel reach, and then the Muskingum parameters were estimated by the graphical method. The time of concentration 𝑇𝑇 𝑐𝑐 and storage coefficient 𝐾𝐾 values were calculated by the difference between the times of concentration ( 𝑇𝑇 𝑐𝑐1 and 𝑇𝑇 𝑐𝑐2 ) and the storage coefficients ( 𝐾𝐾 1 and 𝐾𝐾 2 ) formed by two subbasins created according to Yoo and others’ method. The weighting factor 𝑥𝑥 was calculated by using the range of the time interval ∆ t . The 𝑇𝑇 𝑐𝑐 and storage coefficient 𝐾𝐾 values used in the parameter estimation process were calculated by empirical equations such as the ones proposed by Lee et al (2013) and Kraven II and Sabol. In order to obtain the ideal outflow hydrograph to be used in the graphical method, the lateral inflow was calculated using the effective rainfall obtained by the SCS-CN method and Clark unit hydrograph. The Muskingum parameters were estimated using the final outflow hydrograph derived after removing the upstream lateral inflow and base flow from the observed outflow hydrograph data at the downstream in graphical method. The Muskingum parameters estimated by Yoo and others’ method, which is based on Lee’s and Kraven II and Sabol empirical equations were compared with the estimations made by the graphical method. The results showed that the empirical equations proposed by Lee and others give values that are closer to the Muskingum parameters obtained by the graphical method. This suggests that the Lee’s empirical equations derived using the basin characteristics of the Chungju Dam basin yield more appropriate results.","PeriodicalId":390064,"journal":{"name":"MODSIM2023, 25th International Congress on Modelling and Simulation.","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Comparative analysis of Muskingum parameters estimated from hydrologic observations and basin characteristics\",\"authors\":\"Y. M. Kim, C. S. Yoo, S. Yoon\",\"doi\":\"10.36334/modsim.2023.kim371\",\"DOIUrl\":null,\"url\":null,\"abstract\":\": The usefulness of the Muskingum model for flow routing has been widely recognized and made the model one of the most commonly used hydrologic channel flood routing models. Despite its wide application in hydrologic flood routing, the model is unsuitable for ungauged channel reaches due to its need for data from hydrologic observations for the estimation of its parameters. This paper uses a different method based on basin characteristics suggested by Yoo et al. (2013) at Chungju Dam basin to compare its results with the current hydrologic observation based parameter estimation method. The Chungju Dam basin was divided into subbasins and each subbasin’s exit was further divided into either upstream or downstream section of the channel reach. Rainfall data from 2010 to 2020 was used and a total of 55 rainfall events were selected from the entire data. 12 channel reaches were formed based on 15 water level stations within the study basin. The amount of storage was calculated using the inflow and outflow hydrographs for every channel reach, and then the Muskingum parameters were estimated by the graphical method. The time of concentration 𝑇𝑇 𝑐𝑐 and storage coefficient 𝐾𝐾 values were calculated by the difference between the times of concentration ( 𝑇𝑇 𝑐𝑐1 and 𝑇𝑇 𝑐𝑐2 ) and the storage coefficients ( 𝐾𝐾 1 and 𝐾𝐾 2 ) formed by two subbasins created according to Yoo and others’ method. The weighting factor 𝑥𝑥 was calculated by using the range of the time interval ∆ t . The 𝑇𝑇 𝑐𝑐 and storage coefficient 𝐾𝐾 values used in the parameter estimation process were calculated by empirical equations such as the ones proposed by Lee et al (2013) and Kraven II and Sabol. In order to obtain the ideal outflow hydrograph to be used in the graphical method, the lateral inflow was calculated using the effective rainfall obtained by the SCS-CN method and Clark unit hydrograph. The Muskingum parameters were estimated using the final outflow hydrograph derived after removing the upstream lateral inflow and base flow from the observed outflow hydrograph data at the downstream in graphical method. The Muskingum parameters estimated by Yoo and others’ method, which is based on Lee’s and Kraven II and Sabol empirical equations were compared with the estimations made by the graphical method. The results showed that the empirical equations proposed by Lee and others give values that are closer to the Muskingum parameters obtained by the graphical method. This suggests that the Lee’s empirical equations derived using the basin characteristics of the Chungju Dam basin yield more appropriate results.\",\"PeriodicalId\":390064,\"journal\":{\"name\":\"MODSIM2023, 25th International Congress on Modelling and Simulation.\",\"volume\":\"32 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"MODSIM2023, 25th International Congress on Modelling and Simulation.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.36334/modsim.2023.kim371\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"MODSIM2023, 25th International Congress on Modelling and Simulation.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.36334/modsim.2023.kim371","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
Muskingum模型对水流走向的有用性已得到广泛认可,并使该模型成为最常用的水文河道洪水走向模型之一。尽管该模型在水文洪水路径中得到了广泛的应用,但由于其参数估计需要水文观测数据,因此不适用于未测量的河段。本文采用Yoo et al.(2013)在忠州坝流域提出的基于流域特征的不同方法,将其结果与目前基于水文观测的参数估计方法进行比较。忠州坝盆地被划分为多个子盆地,每个子盆地的出口被进一步划分为河道河段的上游或下游段。使用2010 - 2020年的降雨数据,从整个数据中选取55个降雨事件。根据研究流域内15个水位站,形成了12条河道。利用各河段的入流和出流曲线计算库存量,然后用图解法估计了Muskingum参数。浓缩时间𝑇𝑇𝑐𝑐和储存系数𝐾𝐾是根据Yoo等人的方法建立的两个子盆地的浓缩时间(𝑇𝑇𝑐𝑐1和𝑇𝑇𝑐𝑐2)和储存系数(𝐾𝐾1和𝐾𝐾2)的差值计算出来的。采用时间区间的取值范围∆t计算权重因子。参数估计过程中使用的𝑇𝑇𝑐𝑐和存储系数𝐾𝐾值由Lee et al(2013)和Kraven II和Sabol提出的经验方程计算。为了得到图解法中理想的流出线线,利用SCS-CN法和Clark单位线线得到的有效降雨量计算了侧向流入。Muskingum参数是用图形法从下游观测的流出线数据中去除上游侧向流入和基流后得到的最终流出线来估计的。将Yoo等人基于Lee’s和Kraven II以及Sabol经验方程估计的Muskingum参数与图解法估计的参数进行了比较。结果表明,由Lee等人提出的经验方程给出的值更接近于用图解法得到的Muskingum参数。这表明,利用忠州坝流域特征推导的Lee经验方程可以得到更合适的结果。
Comparative analysis of Muskingum parameters estimated from hydrologic observations and basin characteristics
: The usefulness of the Muskingum model for flow routing has been widely recognized and made the model one of the most commonly used hydrologic channel flood routing models. Despite its wide application in hydrologic flood routing, the model is unsuitable for ungauged channel reaches due to its need for data from hydrologic observations for the estimation of its parameters. This paper uses a different method based on basin characteristics suggested by Yoo et al. (2013) at Chungju Dam basin to compare its results with the current hydrologic observation based parameter estimation method. The Chungju Dam basin was divided into subbasins and each subbasin’s exit was further divided into either upstream or downstream section of the channel reach. Rainfall data from 2010 to 2020 was used and a total of 55 rainfall events were selected from the entire data. 12 channel reaches were formed based on 15 water level stations within the study basin. The amount of storage was calculated using the inflow and outflow hydrographs for every channel reach, and then the Muskingum parameters were estimated by the graphical method. The time of concentration 𝑇𝑇 𝑐𝑐 and storage coefficient 𝐾𝐾 values were calculated by the difference between the times of concentration ( 𝑇𝑇 𝑐𝑐1 and 𝑇𝑇 𝑐𝑐2 ) and the storage coefficients ( 𝐾𝐾 1 and 𝐾𝐾 2 ) formed by two subbasins created according to Yoo and others’ method. The weighting factor 𝑥𝑥 was calculated by using the range of the time interval ∆ t . The 𝑇𝑇 𝑐𝑐 and storage coefficient 𝐾𝐾 values used in the parameter estimation process were calculated by empirical equations such as the ones proposed by Lee et al (2013) and Kraven II and Sabol. In order to obtain the ideal outflow hydrograph to be used in the graphical method, the lateral inflow was calculated using the effective rainfall obtained by the SCS-CN method and Clark unit hydrograph. The Muskingum parameters were estimated using the final outflow hydrograph derived after removing the upstream lateral inflow and base flow from the observed outflow hydrograph data at the downstream in graphical method. The Muskingum parameters estimated by Yoo and others’ method, which is based on Lee’s and Kraven II and Sabol empirical equations were compared with the estimations made by the graphical method. The results showed that the empirical equations proposed by Lee and others give values that are closer to the Muskingum parameters obtained by the graphical method. This suggests that the Lee’s empirical equations derived using the basin characteristics of the Chungju Dam basin yield more appropriate results.