Temesgen Tsehayeneh Mihret, Fasikaw A. Zemale, Abeyou W. Worqlul, Ayenew D. Ayalew, Nicola Fohrer
{"title":"埃塞俄比亚青尼罗河流域水文同源流域的确定和气候-植被动态变化","authors":"Temesgen Tsehayeneh Mihret, Fasikaw A. Zemale, Abeyou W. Worqlul, Ayenew D. Ayalew, Nicola Fohrer","doi":"10.2166/nh.2024.098","DOIUrl":null,"url":null,"abstract":"<div><div data- reveal-group-><div><img alt=\"graphic\" data-src=\"https://iwa.silverchair-cdn.com/iwa/content_public/journal/hr/55/3/10.2166_nh.2024.098/1/m_hydrology-d-23-00098gf01.png?Expires=1714755649&Signature=SS3PNqIlhHL6n70YLvsQcCpnfo9fH-~Rq2O8G0C5YBxWsPNlPH6L5dkj~vaCioKKKx3gpS0pfZRMugegwLqNmJtic~nMKo8MwjGXXhflpp-09aOy4p6VF4OwfAUUnG55pUJr7Ccu5ZcwvOkFH7qcoQrcus0HHmycVbt0yyJ-IIDsXHucRm-NkK1pB7XPLeESAFkFWJcoVk2XSMIowmDQRGSFFCfxWi2~4h4uKVs28y-NcnwpBNDfECNhQhsJeLBTEoaog4Plypn0lsFIBq52lMpHVEm2oZLxoc7aSeaoJvgmuqMONeQfsdZfanOXhP1IcchNScJjwWTU163Q1BB2cA__&Key-Pair-Id=APKAIE5G5CRDK6RD3PGA\" path-from-xml=\"hydrology-d-23-00098gf01.tif\" src=\"https://iwa.silverchair-cdn.com/iwa/content_public/journal/hr/55/3/10.2166_nh.2024.098/1/m_hydrology-d-23-00098gf01.png?Expires=1714755649&Signature=SS3PNqIlhHL6n70YLvsQcCpnfo9fH-~Rq2O8G0C5YBxWsPNlPH6L5dkj~vaCioKKKx3gpS0pfZRMugegwLqNmJtic~nMKo8MwjGXXhflpp-09aOy4p6VF4OwfAUUnG55pUJr7Ccu5ZcwvOkFH7qcoQrcus0HHmycVbt0yyJ-IIDsXHucRm-NkK1pB7XPLeESAFkFWJcoVk2XSMIowmDQRGSFFCfxWi2~4h4uKVs28y-NcnwpBNDfECNhQhsJeLBTEoaog4Plypn0lsFIBq52lMpHVEm2oZLxoc7aSeaoJvgmuqMONeQfsdZfanOXhP1IcchNScJjwWTU163Q1BB2cA__&Key-Pair-Id=APKAIE5G5CRDK6RD3PGA\"/><div>View largeDownload slide</div></div></div><div content- data-reveal=\"data-reveal\"><div><img alt=\"graphic\" data-src=\"https://iwa.silverchair-cdn.com/iwa/content_public/journal/hr/55/3/10.2166_nh.2024.098/1/m_hydrology-d-23-00098gf01.png?Expires=1714755649&Signature=SS3PNqIlhHL6n70YLvsQcCpnfo9fH-~Rq2O8G0C5YBxWsPNlPH6L5dkj~vaCioKKKx3gpS0pfZRMugegwLqNmJtic~nMKo8MwjGXXhflpp-09aOy4p6VF4OwfAUUnG55pUJr7Ccu5ZcwvOkFH7qcoQrcus0HHmycVbt0yyJ-IIDsXHucRm-NkK1pB7XPLeESAFkFWJcoVk2XSMIowmDQRGSFFCfxWi2~4h4uKVs28y-NcnwpBNDfECNhQhsJeLBTEoaog4Plypn0lsFIBq52lMpHVEm2oZLxoc7aSeaoJvgmuqMONeQfsdZfanOXhP1IcchNScJjwWTU163Q1BB2cA__&Key-Pair-Id=APKAIE5G5CRDK6RD3PGA\" path-from-xml=\"hydrology-d-23-00098gf01.tif\" src=\"https://iwa.silverchair-cdn.com/iwa/content_public/journal/hr/55/3/10.2166_nh.2024.098/1/m_hydrology-d-23-00098gf01.png?Expires=1714755649&Signature=SS3PNqIlhHL6n70YLvsQcCpnfo9fH-~Rq2O8G0C5YBxWsPNlPH6L5dkj~vaCioKKKx3gpS0pfZRMugegwLqNmJtic~nMKo8MwjGXXhflpp-09aOy4p6VF4OwfAUUnG55pUJr7Ccu5ZcwvOkFH7qcoQrcus0HHmycVbt0yyJ-IIDsXHucRm-NkK1pB7XPLeESAFkFWJcoVk2XSMIowmDQRGSFFCfxWi2~4h4uKVs28y-NcnwpBNDfECNhQhsJeLBTEoaog4Plypn0lsFIBq52lMpHVEm2oZLxoc7aSeaoJvgmuqMONeQfsdZfanOXhP1IcchNScJjwWTU163Q1BB2cA__&Key-Pair-Id=APKAIE5G5CRDK6RD3PGA\"/><div>View largeDownload slide</div></div><i> </i><span>Close modal</span></div></div><p>Identification of hydrologically homogenous watersheds in the Upper Blue Nile Basin of Ethiopia is challenging due to the large number of watersheds and the lack of consistent and reliable data. Traditional methods, such as expert-based classification, are time-consuming, subjective, and often not reproducible. Therefore, this study aims to identify homogenous gauged watersheds using hydrometeorological and remote sensing data. In this study 76 watersheds were delineated from a 30-m digital elevation model (SRTM-DEM). Twelve watershed characteristics were selected to aid the classification process. Three homogenous climate regions were identified using rainfall data from 42 stations, and for each homogeneous climate region, gauged watersheds were identified. Principal component analysis (PCA) and <em>K</em>-means clustering were used for classification. The PCA reduced 12 watershed characteristics into three principal components using a threshold of 80% accounted variance and eigenvalues greater than one. <em>K</em>-means clustering classified the 76 watersheds into nine homogenous clusters. In the classified regions, vegetation dynamics within three decades have also been analyzed. This helped identify trends in vegetation cover and its spatial and temporal dynamics. The results of the investigation will potentially be used for runoff prediction of ungauged watersheds and for water resource management models in the future.</p>","PeriodicalId":13096,"journal":{"name":"Hydrology Research","volume":"102 1","pages":""},"PeriodicalIF":2.6000,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Identification of hydrologically homogenous watersheds and climate-vegetation dynamics in the Blue Nile Basin of Ethiopia\",\"authors\":\"Temesgen Tsehayeneh Mihret, Fasikaw A. Zemale, Abeyou W. Worqlul, Ayenew D. Ayalew, Nicola Fohrer\",\"doi\":\"10.2166/nh.2024.098\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div data- reveal-group-><div><img alt=\\\"graphic\\\" data-src=\\\"https://iwa.silverchair-cdn.com/iwa/content_public/journal/hr/55/3/10.2166_nh.2024.098/1/m_hydrology-d-23-00098gf01.png?Expires=1714755649&Signature=SS3PNqIlhHL6n70YLvsQcCpnfo9fH-~Rq2O8G0C5YBxWsPNlPH6L5dkj~vaCioKKKx3gpS0pfZRMugegwLqNmJtic~nMKo8MwjGXXhflpp-09aOy4p6VF4OwfAUUnG55pUJr7Ccu5ZcwvOkFH7qcoQrcus0HHmycVbt0yyJ-IIDsXHucRm-NkK1pB7XPLeESAFkFWJcoVk2XSMIowmDQRGSFFCfxWi2~4h4uKVs28y-NcnwpBNDfECNhQhsJeLBTEoaog4Plypn0lsFIBq52lMpHVEm2oZLxoc7aSeaoJvgmuqMONeQfsdZfanOXhP1IcchNScJjwWTU163Q1BB2cA__&Key-Pair-Id=APKAIE5G5CRDK6RD3PGA\\\" path-from-xml=\\\"hydrology-d-23-00098gf01.tif\\\" src=\\\"https://iwa.silverchair-cdn.com/iwa/content_public/journal/hr/55/3/10.2166_nh.2024.098/1/m_hydrology-d-23-00098gf01.png?Expires=1714755649&Signature=SS3PNqIlhHL6n70YLvsQcCpnfo9fH-~Rq2O8G0C5YBxWsPNlPH6L5dkj~vaCioKKKx3gpS0pfZRMugegwLqNmJtic~nMKo8MwjGXXhflpp-09aOy4p6VF4OwfAUUnG55pUJr7Ccu5ZcwvOkFH7qcoQrcus0HHmycVbt0yyJ-IIDsXHucRm-NkK1pB7XPLeESAFkFWJcoVk2XSMIowmDQRGSFFCfxWi2~4h4uKVs28y-NcnwpBNDfECNhQhsJeLBTEoaog4Plypn0lsFIBq52lMpHVEm2oZLxoc7aSeaoJvgmuqMONeQfsdZfanOXhP1IcchNScJjwWTU163Q1BB2cA__&Key-Pair-Id=APKAIE5G5CRDK6RD3PGA\\\"/><div>View largeDownload slide</div></div></div><div content- data-reveal=\\\"data-reveal\\\"><div><img alt=\\\"graphic\\\" data-src=\\\"https://iwa.silverchair-cdn.com/iwa/content_public/journal/hr/55/3/10.2166_nh.2024.098/1/m_hydrology-d-23-00098gf01.png?Expires=1714755649&Signature=SS3PNqIlhHL6n70YLvsQcCpnfo9fH-~Rq2O8G0C5YBxWsPNlPH6L5dkj~vaCioKKKx3gpS0pfZRMugegwLqNmJtic~nMKo8MwjGXXhflpp-09aOy4p6VF4OwfAUUnG55pUJr7Ccu5ZcwvOkFH7qcoQrcus0HHmycVbt0yyJ-IIDsXHucRm-NkK1pB7XPLeESAFkFWJcoVk2XSMIowmDQRGSFFCfxWi2~4h4uKVs28y-NcnwpBNDfECNhQhsJeLBTEoaog4Plypn0lsFIBq52lMpHVEm2oZLxoc7aSeaoJvgmuqMONeQfsdZfanOXhP1IcchNScJjwWTU163Q1BB2cA__&Key-Pair-Id=APKAIE5G5CRDK6RD3PGA\\\" path-from-xml=\\\"hydrology-d-23-00098gf01.tif\\\" src=\\\"https://iwa.silverchair-cdn.com/iwa/content_public/journal/hr/55/3/10.2166_nh.2024.098/1/m_hydrology-d-23-00098gf01.png?Expires=1714755649&Signature=SS3PNqIlhHL6n70YLvsQcCpnfo9fH-~Rq2O8G0C5YBxWsPNlPH6L5dkj~vaCioKKKx3gpS0pfZRMugegwLqNmJtic~nMKo8MwjGXXhflpp-09aOy4p6VF4OwfAUUnG55pUJr7Ccu5ZcwvOkFH7qcoQrcus0HHmycVbt0yyJ-IIDsXHucRm-NkK1pB7XPLeESAFkFWJcoVk2XSMIowmDQRGSFFCfxWi2~4h4uKVs28y-NcnwpBNDfECNhQhsJeLBTEoaog4Plypn0lsFIBq52lMpHVEm2oZLxoc7aSeaoJvgmuqMONeQfsdZfanOXhP1IcchNScJjwWTU163Q1BB2cA__&Key-Pair-Id=APKAIE5G5CRDK6RD3PGA\\\"/><div>View largeDownload slide</div></div><i> </i><span>Close modal</span></div></div><p>Identification of hydrologically homogenous watersheds in the Upper Blue Nile Basin of Ethiopia is challenging due to the large number of watersheds and the lack of consistent and reliable data. Traditional methods, such as expert-based classification, are time-consuming, subjective, and often not reproducible. Therefore, this study aims to identify homogenous gauged watersheds using hydrometeorological and remote sensing data. In this study 76 watersheds were delineated from a 30-m digital elevation model (SRTM-DEM). Twelve watershed characteristics were selected to aid the classification process. Three homogenous climate regions were identified using rainfall data from 42 stations, and for each homogeneous climate region, gauged watersheds were identified. Principal component analysis (PCA) and <em>K</em>-means clustering were used for classification. The PCA reduced 12 watershed characteristics into three principal components using a threshold of 80% accounted variance and eigenvalues greater than one. <em>K</em>-means clustering classified the 76 watersheds into nine homogenous clusters. In the classified regions, vegetation dynamics within three decades have also been analyzed. This helped identify trends in vegetation cover and its spatial and temporal dynamics. The results of the investigation will potentially be used for runoff prediction of ungauged watersheds and for water resource management models in the future.</p>\",\"PeriodicalId\":13096,\"journal\":{\"name\":\"Hydrology Research\",\"volume\":\"102 1\",\"pages\":\"\"},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2024-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Hydrology Research\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://doi.org/10.2166/nh.2024.098\",\"RegionNum\":4,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"WATER RESOURCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Hydrology Research","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.2166/nh.2024.098","RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"WATER RESOURCES","Score":null,"Total":0}
Identification of hydrologically homogenous watersheds and climate-vegetation dynamics in the Blue Nile Basin of Ethiopia
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Identification of hydrologically homogenous watersheds in the Upper Blue Nile Basin of Ethiopia is challenging due to the large number of watersheds and the lack of consistent and reliable data. Traditional methods, such as expert-based classification, are time-consuming, subjective, and often not reproducible. Therefore, this study aims to identify homogenous gauged watersheds using hydrometeorological and remote sensing data. In this study 76 watersheds were delineated from a 30-m digital elevation model (SRTM-DEM). Twelve watershed characteristics were selected to aid the classification process. Three homogenous climate regions were identified using rainfall data from 42 stations, and for each homogeneous climate region, gauged watersheds were identified. Principal component analysis (PCA) and K-means clustering were used for classification. The PCA reduced 12 watershed characteristics into three principal components using a threshold of 80% accounted variance and eigenvalues greater than one. K-means clustering classified the 76 watersheds into nine homogenous clusters. In the classified regions, vegetation dynamics within three decades have also been analyzed. This helped identify trends in vegetation cover and its spatial and temporal dynamics. The results of the investigation will potentially be used for runoff prediction of ungauged watersheds and for water resource management models in the future.
期刊介绍:
Hydrology Research provides international coverage on all aspects of hydrology in its widest sense, and welcomes the submission of papers from across the subject. While emphasis is placed on studies of the hydrological cycle, the Journal also covers the physics and chemistry of water. Hydrology Research is intended to be a link between basic hydrological research and the practical application of scientific results within the broad field of water management.