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Precipitation projection over Daqing River Basin (North China) considering the evolution of dependence structures
Understanding dynamic future changes in precipitation can provide prior information for nonpoint source pollution simulations under global warming. However, the evolution of the dependence structure and the unevenness characteristics of precipitation are rarely considered. This study applied a two-s...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8379070/ https://www.ncbi.nlm.nih.gov/pubmed/34417694 http://dx.doi.org/10.1007/s11356-021-16066-9 |
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author | Gao, Xueping Lv, Mingcong Liu, Yinzhu Sun, Bowen |
author_facet | Gao, Xueping Lv, Mingcong Liu, Yinzhu Sun, Bowen |
author_sort | Gao, Xueping |
collection | PubMed |
description | Understanding dynamic future changes in precipitation can provide prior information for nonpoint source pollution simulations under global warming. However, the evolution of the dependence structure and the unevenness characteristics of precipitation are rarely considered. This study applied a two-stage bias correction to daily precipitation and max/min temperature data in the Daqing River Basin (DQRB) with the HadGEM3-RA climate model. Validated from 1981 to 2015, future scenarios under two emission paths covering 2031–2065 and 2066–2100 were projected to assess variations in both the amount and unevenness of precipitation. The results suggested that, overall, the two-stage bias correction could reproduce the marginal distributions of variables and the evolution process of the dependence structure. In the future, the amount of precipitation in the plains is expected to increase more than that in the mountains, while precipitation unevenness, as measured by relative entropy, shows a slight increase in the mountains and a decrease in the plains, with enhanced seasonality. Conditioned on rising temperatures, high-/low-intensity precipitation tends to intensify/weaken precipitation unevenness. Additionally, the potential application of the bias correction method used herein and the possible impacts of uneven precipitation on nonpoint source pollution are given for further analyses. This study can provide useful information for future nonpoint source pollution simulations in the DQRB. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11356-021-16066-9. |
format | Online Article Text |
id | pubmed-8379070 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-83790702021-08-23 Precipitation projection over Daqing River Basin (North China) considering the evolution of dependence structures Gao, Xueping Lv, Mingcong Liu, Yinzhu Sun, Bowen Environ Sci Pollut Res Int Research Article Understanding dynamic future changes in precipitation can provide prior information for nonpoint source pollution simulations under global warming. However, the evolution of the dependence structure and the unevenness characteristics of precipitation are rarely considered. This study applied a two-stage bias correction to daily precipitation and max/min temperature data in the Daqing River Basin (DQRB) with the HadGEM3-RA climate model. Validated from 1981 to 2015, future scenarios under two emission paths covering 2031–2065 and 2066–2100 were projected to assess variations in both the amount and unevenness of precipitation. The results suggested that, overall, the two-stage bias correction could reproduce the marginal distributions of variables and the evolution process of the dependence structure. In the future, the amount of precipitation in the plains is expected to increase more than that in the mountains, while precipitation unevenness, as measured by relative entropy, shows a slight increase in the mountains and a decrease in the plains, with enhanced seasonality. Conditioned on rising temperatures, high-/low-intensity precipitation tends to intensify/weaken precipitation unevenness. Additionally, the potential application of the bias correction method used herein and the possible impacts of uneven precipitation on nonpoint source pollution are given for further analyses. This study can provide useful information for future nonpoint source pollution simulations in the DQRB. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11356-021-16066-9. Springer Berlin Heidelberg 2021-08-21 2022 /pmc/articles/PMC8379070/ /pubmed/34417694 http://dx.doi.org/10.1007/s11356-021-16066-9 Text en © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Research Article Gao, Xueping Lv, Mingcong Liu, Yinzhu Sun, Bowen Precipitation projection over Daqing River Basin (North China) considering the evolution of dependence structures |
title | Precipitation projection over Daqing River Basin (North China) considering the evolution of dependence structures |
title_full | Precipitation projection over Daqing River Basin (North China) considering the evolution of dependence structures |
title_fullStr | Precipitation projection over Daqing River Basin (North China) considering the evolution of dependence structures |
title_full_unstemmed | Precipitation projection over Daqing River Basin (North China) considering the evolution of dependence structures |
title_short | Precipitation projection over Daqing River Basin (North China) considering the evolution of dependence structures |
title_sort | precipitation projection over daqing river basin (north china) considering the evolution of dependence structures |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8379070/ https://www.ncbi.nlm.nih.gov/pubmed/34417694 http://dx.doi.org/10.1007/s11356-021-16066-9 |
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