Yang Liu , Jianming Chen , Jingyun Zheng , Zhixin Hao
{"title":"中国历史文献中的水文气候代表性和干湿指数重建降水预测能力的重新评估","authors":"Yang Liu , Jianming Chen , Jingyun Zheng , Zhixin Hao","doi":"10.1016/j.ejrh.2024.101883","DOIUrl":null,"url":null,"abstract":"<div><h3>Study region</h3><p>China</p></div><div><h3>Study focus</h3><p>The Dryness/Wetness Index (DWI) data from China is widely utilized in palaeohydroclimate research. The initial part of this data, covering the years 1470–1979 (original DWI), is primarily generated from records of droughts/floods in historical documents. However, the extended data over 1980–2000 (precipitation-based DWI) is derived entirely from instrumental precipitation measurements. To date, there is no research on the regional differences in hydroclimatic representativeness of the original DWI. Moreover, when reconstructing precipitation using the combined 1470–2000 DWI data as a proxy and calibrating it with instrumental precipitation data post-1950, the overestimated reconstruction skill has not been evaluated. Therefore, utilizing data on crop yield reductions due to drought/flood disasters from 1978 to 2008, we establish the disaster-based DWI following the same method as the original DWI and explore its representativeness and reconstruction skill.</p></div><div><h3>New hydrological insights for the region</h3><p>Disaster-based DWI is more sensitive to precipitation in East Central China, with the seasonal window primarily lasting for five months and distributed between April and September. In contrast, it reflects soil water in the Northeastern, Southeast coastal, and Western regions in China. Additionally, by comparing the average predicted R-Squared of summer precipitation reconstruction using precipitation-based DWI and disaster-based DWI (58.6 % and 45.0 %, respectively), we identify an average overestimation of 13.6 %. Even after excluding this inflated R-Squared, the disaster-based DWI remains a highly reliable proxy for precipitation.</p></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":null,"pages":null},"PeriodicalIF":4.7000,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2214581824002325/pdfft?md5=b118885aed4f8984dc4018d1e39d9296&pid=1-s2.0-S2214581824002325-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Hydroclimatic representativeness and reassessment of the predictive skill to reconstruct precipitation by the Dryness/Wetness Index from Chinese historical documents\",\"authors\":\"Yang Liu , Jianming Chen , Jingyun Zheng , Zhixin Hao\",\"doi\":\"10.1016/j.ejrh.2024.101883\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Study region</h3><p>China</p></div><div><h3>Study focus</h3><p>The Dryness/Wetness Index (DWI) data from China is widely utilized in palaeohydroclimate research. The initial part of this data, covering the years 1470–1979 (original DWI), is primarily generated from records of droughts/floods in historical documents. However, the extended data over 1980–2000 (precipitation-based DWI) is derived entirely from instrumental precipitation measurements. To date, there is no research on the regional differences in hydroclimatic representativeness of the original DWI. Moreover, when reconstructing precipitation using the combined 1470–2000 DWI data as a proxy and calibrating it with instrumental precipitation data post-1950, the overestimated reconstruction skill has not been evaluated. Therefore, utilizing data on crop yield reductions due to drought/flood disasters from 1978 to 2008, we establish the disaster-based DWI following the same method as the original DWI and explore its representativeness and reconstruction skill.</p></div><div><h3>New hydrological insights for the region</h3><p>Disaster-based DWI is more sensitive to precipitation in East Central China, with the seasonal window primarily lasting for five months and distributed between April and September. In contrast, it reflects soil water in the Northeastern, Southeast coastal, and Western regions in China. Additionally, by comparing the average predicted R-Squared of summer precipitation reconstruction using precipitation-based DWI and disaster-based DWI (58.6 % and 45.0 %, respectively), we identify an average overestimation of 13.6 %. Even after excluding this inflated R-Squared, the disaster-based DWI remains a highly reliable proxy for precipitation.</p></div>\",\"PeriodicalId\":48620,\"journal\":{\"name\":\"Journal of Hydrology-Regional Studies\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.7000,\"publicationDate\":\"2024-07-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2214581824002325/pdfft?md5=b118885aed4f8984dc4018d1e39d9296&pid=1-s2.0-S2214581824002325-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Hydrology-Regional Studies\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2214581824002325\",\"RegionNum\":2,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"WATER RESOURCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Hydrology-Regional Studies","FirstCategoryId":"89","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2214581824002325","RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"WATER RESOURCES","Score":null,"Total":0}
Hydroclimatic representativeness and reassessment of the predictive skill to reconstruct precipitation by the Dryness/Wetness Index from Chinese historical documents
Study region
China
Study focus
The Dryness/Wetness Index (DWI) data from China is widely utilized in palaeohydroclimate research. The initial part of this data, covering the years 1470–1979 (original DWI), is primarily generated from records of droughts/floods in historical documents. However, the extended data over 1980–2000 (precipitation-based DWI) is derived entirely from instrumental precipitation measurements. To date, there is no research on the regional differences in hydroclimatic representativeness of the original DWI. Moreover, when reconstructing precipitation using the combined 1470–2000 DWI data as a proxy and calibrating it with instrumental precipitation data post-1950, the overestimated reconstruction skill has not been evaluated. Therefore, utilizing data on crop yield reductions due to drought/flood disasters from 1978 to 2008, we establish the disaster-based DWI following the same method as the original DWI and explore its representativeness and reconstruction skill.
New hydrological insights for the region
Disaster-based DWI is more sensitive to precipitation in East Central China, with the seasonal window primarily lasting for five months and distributed between April and September. In contrast, it reflects soil water in the Northeastern, Southeast coastal, and Western regions in China. Additionally, by comparing the average predicted R-Squared of summer precipitation reconstruction using precipitation-based DWI and disaster-based DWI (58.6 % and 45.0 %, respectively), we identify an average overestimation of 13.6 %. Even after excluding this inflated R-Squared, the disaster-based DWI remains a highly reliable proxy for precipitation.
期刊介绍:
Journal of Hydrology: Regional Studies publishes original research papers enhancing the science of hydrology and aiming at region-specific problems, past and future conditions, analysis, review and solutions. The journal particularly welcomes research papers that deliver new insights into region-specific hydrological processes and responses to changing conditions, as well as contributions that incorporate interdisciplinarity and translational science.