通过 MMRC-copula 综合建模将降雨量从日尺度分解到 1 小时尺度

IF 5.9 1区 地球科学 Q1 ENGINEERING, CIVIL
Payel Biswas, Ujjwal Saha
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引用次数: 0

摘要

降雨强度是最关键的气象参数之一,被水资源规划人员、水文学家、灌溉专家、洪水和吃水监管部门广泛使用。特别是,亚日时降雨时间序列对城市排水设计和雨水管理的详细规划非常重要。然而,由于无法获得可靠的精细分辨率降雨数据,在当前情况下,使用各种随机技术对现有降雨记录进行时间分解正成为最受欢迎的选择之一。在本研究中,采用了微规范乘法随机级联(MMRC)模型将日降雨量值分解为 1 小时量级。虽然 MMRC 能够生成统计上可靠的降雨时间序列,但它不足以保留极端降雨的特征。本文提出了一个新模型,将 copula 理论与 MMRC 模型相结合,以捕捉粗时间步降雨量与其相应的细时间步之间的依赖结构。与通常会导致高估极端降雨量的 MMRC 模型相比,这种新的 MMRC-copula 集成模型更精确地考虑了级联发生器的随机分裂过程,因此能以更高的精度完成粗分辨率降雨序列的分解过程。与 MMRC 模型相比,MMRC-Copula 集成模型的整体性能有所提高,这证明了该模型在降雨时间分解领域的相关性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Disaggregation of rainfall from daily to 1-hour scale through integrated MMRC-copula modelling
Rainfall intensity is one of the most crucial meteorological parameters which is extensively used by water resource planners, hydrologists, irrigation experts, flood and draught regulatory authorities. Particularly, sub-daily temporal rainfall time series is quite essential for detailed planning of urban drainage design, storm water management. However, due to non-availability of reliable fine resolution rainfall data, under current scenario temporal disaggregation of existing rainfall record using various stochastic techniques is emerging as one of the most sought after option. In the present study, the Microcanonical Multiplicative Random Cascade (MMRC) model has been adopted for disaggregation of daily rainfall values to 1 h scale. Though MMRC is capable of generating statistically reliable rainfall time series, it is not competent enough to preserve the extreme rainfall characteristics.
In this paper, a new model has been presented where copula theory has been integrated with MMRC model to capture the dependence structure between coarse time step rainfall and its corresponding finer time steps. The procedure of disaggregation of coarse resolution rainfall series has been accomplished by this new Integrated MMRC-copula model with higher accuracy as it accounts for the random splitting procedure of cascade generator more precisely compared to MMRC model which generally leads to overestimation of extreme rainfall. An overall improved performance of the Integrated MMRC-Copula model in contrast to MMRC supports the model’s pertinence in the field of temporal disaggregation of rainfall.
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来源期刊
Journal of Hydrology
Journal of Hydrology 地学-地球科学综合
CiteScore
11.00
自引率
12.50%
发文量
1309
审稿时长
7.5 months
期刊介绍: The Journal of Hydrology publishes original research papers and comprehensive reviews in all the subfields of the hydrological sciences including water based management and policy issues that impact on economics and society. These comprise, but are not limited to the physical, chemical, biogeochemical, stochastic and systems aspects of surface and groundwater hydrology, hydrometeorology and hydrogeology. Relevant topics incorporating the insights and methodologies of disciplines such as climatology, water resource systems, hydraulics, agrohydrology, geomorphology, soil science, instrumentation and remote sensing, civil and environmental engineering are included. Social science perspectives on hydrological problems such as resource and ecological economics, environmental sociology, psychology and behavioural science, management and policy analysis are also invited. Multi-and interdisciplinary analyses of hydrological problems are within scope. The science published in the Journal of Hydrology is relevant to catchment scales rather than exclusively to a local scale or site.
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