{"title":"通过 MMRC-copula 综合建模将降雨量从日尺度分解到 1 小时尺度","authors":"Payel Biswas, Ujjwal Saha","doi":"10.1016/j.jhydrol.2024.132338","DOIUrl":null,"url":null,"abstract":"<div><div>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.</div><div>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.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"647 ","pages":"Article 132338"},"PeriodicalIF":5.9000,"publicationDate":"2024-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Disaggregation of rainfall from daily to 1-hour scale through integrated MMRC-copula modelling\",\"authors\":\"Payel Biswas, Ujjwal Saha\",\"doi\":\"10.1016/j.jhydrol.2024.132338\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>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.</div><div>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.</div></div>\",\"PeriodicalId\":362,\"journal\":{\"name\":\"Journal of Hydrology\",\"volume\":\"647 \",\"pages\":\"Article 132338\"},\"PeriodicalIF\":5.9000,\"publicationDate\":\"2024-11-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Hydrology\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0022169424017347\",\"RegionNum\":1,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, CIVIL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Hydrology","FirstCategoryId":"89","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0022169424017347","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, CIVIL","Score":null,"Total":0}
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.
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.