Spatiotemporal characterization of the isotopic composition of meteoric waters in Cuba.

IF 5.8 2区综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES

Scientific Data Pub Date : 2024-12-19 DOI:10.1038/s41597-024-04178-z

Alejandro Garcia-Moya, Carlos Manuel Alonso-Hernández, Ricardo Sánchez-Murillo, Yasser Morera-Gómez, Minerva Sánchez-Llull, Oscar Díaz Rizo, Osvaldo Cuesta Santos, Rosemery López Lee, Osvaldo Brígido Flores, Enma Odalys Ramos Viltre, Lucia Ortega

{"title":"Spatiotemporal characterization of the isotopic composition of meteoric waters in Cuba.","authors":"Alejandro Garcia-Moya, Carlos Manuel Alonso-Hernández, Ricardo Sánchez-Murillo, Yasser Morera-Gómez, Minerva Sánchez-Llull, Oscar Díaz Rizo, Osvaldo Cuesta Santos, Rosemery López Lee, Osvaldo Brígido Flores, Enma Odalys Ramos Viltre, Lucia Ortega","doi":"10.1038/s41597-024-04178-z","DOIUrl":null,"url":null,"abstract":"The stable isotope composition of meteoric water has been widely used to understand hydrological processes worldwide. We present a unique dataset, with the isotopic composition (δ18O and δ2H) of meteoric waters, derived from a nationwide study in Cuba. It includes monthly composite and event-based precipitations, from January 2017 to December 2021 (N = 526 and N = 111 respectively). Monthly data showed minor seasonal trends (dry vs. rainy), with a notable influence of tropical cyclones. Event-based data demonstrated that precipitation associated with tropical cyclones exhibited lower isotopic compositions. The analysis of potential factors influencing the isotopic composition of precipitation showed a minor influence of the rainfall amount, but negligible influence of factors such are relative humidity, elevation, and air temperature. This data set can be used as a tool not only to understand hydrological processes at the country scale, but also to further improve and develop isotope-enabled modelling for assessing water balances and fluxes, understanding the impact of extreme events, and paleoreconstruction in the Intra-Americas Sea.","PeriodicalId":21597,"journal":{"name":"Scientific Data","volume":"11 1","pages":"1398"},"PeriodicalIF":5.8000,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scientific Data","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1038/s41597-024-04178-z","RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}

引用次数: 0

Abstract

The stable isotope composition of meteoric water has been widely used to understand hydrological processes worldwide. We present a unique dataset, with the isotopic composition (δ¹⁸O and δ²H) of meteoric waters, derived from a nationwide study in Cuba. It includes monthly composite and event-based precipitations, from January 2017 to December 2021 (N = 526 and N = 111 respectively). Monthly data showed minor seasonal trends (dry vs. rainy), with a notable influence of tropical cyclones. Event-based data demonstrated that precipitation associated with tropical cyclones exhibited lower isotopic compositions. The analysis of potential factors influencing the isotopic composition of precipitation showed a minor influence of the rainfall amount, but negligible influence of factors such are relative humidity, elevation, and air temperature. This data set can be used as a tool not only to understand hydrological processes at the country scale, but also to further improve and develop isotope-enabled modelling for assessing water balances and fluxes, understanding the impact of extreme events, and paleoreconstruction in the Intra-Americas Sea.

查看原文本刊更多论文

求助全文

约1分钟内获得全文求助全文

来源期刊

Scientific Data Social Sciences-Education

CiteScore

11.20

自引率

4.10%

发文量

689

审稿时长

16 weeks

期刊介绍： Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data. The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.