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基于全球气候模型和热带降雨测量任务(GCM-TRMM)的降雨径流模拟:以马来西亚丁加奴 Hulu 集水区为例

Rainfall-runoff modelling based on global climate model and tropical rainfall measuring mission (GCM -TRMM): A case study in Hulu Terengganu catchment, Malaysia.

作者信息

Che Wan Zanial Wan Norsyuhada, Malek Marlinda Abdul, Md Reba Mohd Nadzri, Zaini Nuratiah, Ahmed Ali Najah, Sherif Mohsen, Elshafie Ahmed

机构信息

Civil Engineering Department, College of Engineering, Universiti Tenaga Nasional, 43000 Kajang, Selangor, Malaysia.

Cataclysmic Management and Sustainable Development Research Group (CAMSDE), Department of Civil Engineering, Kulliyyah of Engineering, International Islamic University Malaysia, 53100, Selangor, Malaysia.

出版信息

Heliyon. 2023 Apr 23;9(5):e15740. doi: 10.1016/j.heliyon.2023.e15740. eCollection 2023 May.

Abstract

The hydropower Plant in Terengganu is one of the major hydroelectric dams currently operated in Malaysia. For better operating and scheduling, accurate modelling of natural inflow is vital for a hydroelectric dam. The rainfall-runoff model is among the most reliable models in predicting the inflow based on the rainfall events. Such a model's reliability depends entirely on the reliability and consistency of the rainfall events assessed. However, due to the hydropower plant's remote location, the cost associated with maintaining the installed rainfall stations became a burden. Therefore, the study aims to create a continuous set of rainfall data before, during, and after the construction of a hydropower plant and simulate a rainfall-runoff model for the area. It also examines the reliability of alternative methods by combining rainfall data from two sources: the general circulation model and tropical rainfall measuring mission. Rainfall data from ground stations and generated data using inverse distance weighted method will be compared. The statistical downscaling model will obtain regional rainfall from the general circulation model. The data will be divided into three stages to evaluate the accuracy of the models in capturing inflow changes. The results revealed that rainfall data from TRMM is more correlated to ground station data with R2 = 0.606, while SDSM data has R2 = 0.592. The proposed inflow model based on GCM-TRMM data showed higher precision compared to the model using ground station data. The proposed model consistently predicted inflow during three stages with R2 values ranging from 0.75 to 0.93.

摘要

登嘉楼的水电站是马来西亚目前运营的主要水电大坝之一。为了更好地运行和调度,对自然入流进行准确建模对于水电大坝至关重要。降雨径流模型是基于降雨事件预测入流的最可靠模型之一。这种模型的可靠性完全取决于所评估降雨事件的可靠性和一致性。然而,由于该水电站位置偏远,维护已安装降雨站的成本成为了一项负担。因此,本研究旨在创建一套在水电站建设之前、期间和之后的连续降雨数据,并模拟该地区的降雨径流模型。它还通过结合来自两个来源的降雨数据来检验替代方法的可靠性:全球环流模型和热带降雨测量任务。将比较地面站的降雨数据和使用反距离加权法生成的数据。统计降尺度模型将从全球环流模型中获取区域降雨。数据将分为三个阶段,以评估模型在捕捉入流变化方面的准确性。结果表明,热带降雨测量任务(TRMM)的降雨数据与地面站数据的相关性更强,R2 = 0.606,而统计降尺度模型(SDSM)数据的R2 = 0.592。与使用地面站数据的模型相比,基于全球环流模型 - 热带降雨测量任务(GCM - TRMM)数据提出的入流模型显示出更高的精度。所提出的模型在三个阶段持续预测入流,R2值范围为0.75至0.93。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/276e/10160519/dcc21b119d9e/gr1.jpg

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