{"title":"阿尔及利亚西北部年最大降雨量趋势的时空分析:最新和旧非参数方法的比较分析","authors":"Benali Benzater, Abdelkader Elouissi, Sahnoun Fellah, Anouar Hachemaoui","doi":"10.1111/wej.12905","DOIUrl":null,"url":null,"abstract":"Abstract This article examines the spatial variability of extreme precipitation trends in northwestern Algeria (Macta) and compares the results obtained from the four recent and old non‐parametric methods. A dataset of annual maximum precipitation consisting of 41 observation years (1970–2010) and 41 rain gauges was used. The results of the four old and new methods used to detect trends, Mann–Kendall (MK), Bravais–Pearson (BP), Spearman (SR) and innovative trend analysis (ITA), show good agreement. They revealed that a decrease in the trend of annual maximum precipitation was detected during the first period (1970–1992) with −44% (MK), −61% (BP), −68% (SR) and −76% (ITA). On the other hand, in the second period (1993–2010), a total shift occurred in which a significant increase in annual maximum precipitation trends was observed with +63% (BP), +34% (MK and SR) and +93% (ITA). These results show the ability of ITA to detect partial trends that the other three tests do not allow. Our results allow decision‐makers to properly design adaptation strategies in the face of the intensification of these extreme events.","PeriodicalId":23753,"journal":{"name":"Water and Environment Journal","volume":"111 34","pages":"0"},"PeriodicalIF":1.7000,"publicationDate":"2023-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Spatio‐temporal analysis of trends in annual maximum rainfall in the North‐West of Algeria: Comparative analysis of recent and old non‐parametric methods\",\"authors\":\"Benali Benzater, Abdelkader Elouissi, Sahnoun Fellah, Anouar Hachemaoui\",\"doi\":\"10.1111/wej.12905\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract This article examines the spatial variability of extreme precipitation trends in northwestern Algeria (Macta) and compares the results obtained from the four recent and old non‐parametric methods. A dataset of annual maximum precipitation consisting of 41 observation years (1970–2010) and 41 rain gauges was used. The results of the four old and new methods used to detect trends, Mann–Kendall (MK), Bravais–Pearson (BP), Spearman (SR) and innovative trend analysis (ITA), show good agreement. They revealed that a decrease in the trend of annual maximum precipitation was detected during the first period (1970–1992) with −44% (MK), −61% (BP), −68% (SR) and −76% (ITA). On the other hand, in the second period (1993–2010), a total shift occurred in which a significant increase in annual maximum precipitation trends was observed with +63% (BP), +34% (MK and SR) and +93% (ITA). These results show the ability of ITA to detect partial trends that the other three tests do not allow. Our results allow decision‐makers to properly design adaptation strategies in the face of the intensification of these extreme events.\",\"PeriodicalId\":23753,\"journal\":{\"name\":\"Water and Environment Journal\",\"volume\":\"111 34\",\"pages\":\"0\"},\"PeriodicalIF\":1.7000,\"publicationDate\":\"2023-11-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Water and Environment Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1111/wej.12905\",\"RegionNum\":4,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Water and Environment Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1111/wej.12905","RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Spatio‐temporal analysis of trends in annual maximum rainfall in the North‐West of Algeria: Comparative analysis of recent and old non‐parametric methods
Abstract This article examines the spatial variability of extreme precipitation trends in northwestern Algeria (Macta) and compares the results obtained from the four recent and old non‐parametric methods. A dataset of annual maximum precipitation consisting of 41 observation years (1970–2010) and 41 rain gauges was used. The results of the four old and new methods used to detect trends, Mann–Kendall (MK), Bravais–Pearson (BP), Spearman (SR) and innovative trend analysis (ITA), show good agreement. They revealed that a decrease in the trend of annual maximum precipitation was detected during the first period (1970–1992) with −44% (MK), −61% (BP), −68% (SR) and −76% (ITA). On the other hand, in the second period (1993–2010), a total shift occurred in which a significant increase in annual maximum precipitation trends was observed with +63% (BP), +34% (MK and SR) and +93% (ITA). These results show the ability of ITA to detect partial trends that the other three tests do not allow. Our results allow decision‐makers to properly design adaptation strategies in the face of the intensification of these extreme events.
期刊介绍:
Water and Environment Journal is an internationally recognised peer reviewed Journal for the dissemination of innovations and solutions focussed on enhancing water management best practice. Water and Environment Journal is available to over 12,000 institutions with a further 7,000 copies physically distributed to the Chartered Institution of Water and Environmental Management (CIWEM) membership, comprised of environment sector professionals based across the value chain (utilities, consultancy, technology suppliers, regulators, government and NGOs). As such, the journal provides a conduit between academics and practitioners. We therefore particularly encourage contributions focussed at the interface between academia and industry, which deliver industrially impactful applied research underpinned by scientific evidence. We are keen to attract papers on a broad range of subjects including:
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-Integrated water management strategies
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-Climate change mitigation including management of impacts on agriculture, urban areas and infrastructure