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Trong nghiên cứu này, 12 chỉ số mưa cực đoan và phân bố giá trị cực đoan phù hợp nhất đã được sử dụng để phân tích đặc trưng không gian-thời gian của mưa cực đoan ở thượng lưu lưu vực sông Hồng Thủy (UHRB). Các mối liên hệ khả dĩ giữa mưa cực đoan và lưu thông quy mô lớn cũng được điều tra. Hầu hết các chỉ số mưa cực đoan tăng từ tây sang đông ở UHRB, cho thấy vùng đông là một khu vực ẩm ướt với lượng mưa phong phú. Các chỉ số cho số ngày ẩm ướt liên tiếp (CWD) và sự kiện mưa (R0.1) giảm đáng kể, cho thấy UHRB có xu hướng khô, với ít sự kiện mưa. Các hàm phân phối xác suất của hầu hết các chỉ số mưa cực đoan, đặc biệt là của R0.1, đã chuyển dịch đáng kể sang bên trái trong giai đoạn 1988–2016 so với 1959–1987, cho thấy UHRB đã trải qua một xu hướng khô hạn đáng kể trong những thập kỷ gần đây. Gió mùa hè Đông Á và dao động El Niño–Southern Oscillation\u002FĐổ mồ hôi Thái Bình Dương đã được xác nhận có ảnh hưởng đến mưa cực đoan ở UHRB. Những phát hiện này giúp hiểu rõ hơn về xu hướng biến động của mưa cực đoan ở UHRB và cung cấp các tài liệu tham khảo cho các nghiên cứu tiếp theo.\u003C\u002Fjats:p>","\u003Cjats:title>Abstract\u003C\u002Fjats:title>\u003Cjats:p>Understanding changes in the intensity and frequency of extreme precipitation is vital for flood control, disaster mitigation, and water resource management. In this study, 12 extreme precipitation indices and the best-fitting extreme value distribution were used to analyze the spatiotemporal characteristics of extreme precipitation in the upper reaches of the Hongshui River Basin (UHRB). The possible links between extreme precipitation and large-scale circulation were also investigated. Most extreme precipitation indices increased from west to east in the UHRB, indicating that the eastern region is a humid area with abundant precipitation. The indices for consecutive wet days (CWD) and precipitation events (R0.1) decreased significantly, indicating that the UHRB tends to be dry, with few precipitation events. The probability distribution functions of most extreme precipitation indices, especially that of R0.1, shifted significantly to the left in 1988–2016 compared with 1959–1987, further indicating that the UHRB has experienced a significant drying trend in recent decades. The East Asian summer monsoon and the El Niño–Southern Oscillation\u002FPacific Decadal Oscillation were confirmed to influence extreme precipitation in the UHRB. These findings are helpful for understanding extreme precipitation variation trends in the UHRB and provide references for further research.\u003C\u002Fjats:p>",{"VI":448,"EN":449},"Đặc trưng biến đổi không gian-thời gian của mưa cực đoan ở thượng lưu lưu vực sông Hồng Thủy trong giai đoạn 1959–2016","Spatiotemporal variation characteristics of extreme precipitation in the upper reaches of the Hongshui River Basin during 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Climate Research Division Atmospheric Science and Technology Directorate Science and Technology Branch",{},{"id":24,"text":807,"url":24,"identifiers":808},"10.1002\u002Fasl.221",{"doi":807},{"id":24,"text":810,"url":24,"identifiers":811},"10.1007\u002Fs11442-013-0989-7",{"doi":810},{"id":24,"text":813,"url":24,"identifiers":814},"10.1007\u002Fs00704-015-1470-6",{"doi":813},{"id":24,"text":816,"url":24,"identifiers":817},"10.1007\u002Fs00704-018-2371-2",{"doi":816},{"id":24,"text":819,"url":24,"identifiers":820},"10.1023\u002FA:1008119805106",{"doi":819},{"id":822,"createTime":823,"updateTime":824,"relativeEntities":825,"slug":826,"properties":827,"entityType":153,"verifyStatus":154,"verifyTime":823,"verifyNote":156,"syncStatus":23,"languages":842,"translateLanguages":843,"viewCount":25,"primaryUrl":844,"fullTextUrl":24,"authors":845,"publicationType":280,"publisherRelationship":973,"citationCount":128,"citationInfo":1011,"publishDate":1013,"publishYear":1014,"citationAnalyzeStatus":23,"lastCitationAnalyze":24,"indexDatabases":24,"openAccess":24,"references":1015,"isForceReanalyzing":430},"23e90a1e-21bc-4fcd-8137-dc46d275ee82","2024-10-08T20:02:15.739+00:00","2025-01-24T09:45:12.036+00:00",[],"Temporal-spatial-evolution-patterns-of-the-annual-precipitation-considering-the-climate-change-conditions-in-the-Sanjiang-Plain",{"mag":828,"keywords":830,"openalex":832,"abstract":834,"title":837,"doi":840},{"VOID":829},"2408232893",{"VI":831},"biến đổi khí hậu, lượng mưa hàng năm, nhiệt độ trung bình, phân tích không gian, Đồng bằng Sanjiang",{"VOID":833},"W2408232893",{"VI":835,"EN":836},"\u003Cjats:p>Teo thuyet wavelet, bài kiểm tra xu hướng Mann-Kendall và lý thuyết phân tích không gian ArcGIS đã được sử dụng để phân tích dữ liệu lượng mưa hàng năm và nhiệt độ trung bình được thu thập tại bảy trạm thời tiết quốc gia ở Đồng bằng Sanjiang từ năm 1956 đến năm 2013 nhằm xác định các mô hình tạm thời - không gian của sự thay đổi lượng mưa hàng năm do điều kiện biến đổi khí hậu. Kết quả cho thấy khí hậu ở Đồng bằng Sanjiang đã trải qua một xu hướng ấm lên đáng kể trong 50 năm qua, với nhiệt độ tăng 1.35 °C từ những năm 1960. Ngoài ra, lượng mưa cũng thể hiện một số đặc điểm xu hướng nhất định, cho thấy sự khác biệt lớn hơn ở các khu vực khác nhau. Lượng mưa hàng năm đã cho thấy các đặc điểm biến động theo chu kỳ 23 năm và 12 năm, và kỳ có mức lượng mưa hàng năm cao hơn mức trung bình dự kiến sẽ tiếp tục sau năm 2013. Sự phân bố không gian của lượng mưa trung bình hàng năm cho các năm khác nhau là khác nhau, trong khi sự phân bố không gian của lượng mưa trung bình nhiều năm có tính đồng nhất tương đối. Biên độ biến động lượng mưa hàng năm ở khu vực trung tâm lớn hơn so với khu vực phía nam. Biến động giữa các năm tổng thể của lượng mưa hàng năm là tương đối nhỏ với phần lớn có phân phối bình thường. Kết quả có thể cung cấp hướng dẫn cho các nghiên cứu khoa học và việc sử dụng hợp lý nguồn tài nguyên nước mưa ở Đồng bằng Sanjiang.\u003C\u002Fjats:p>","\u003Cjats:p>The wavelet theory, Mann-Kendall trend test and ArcGIS spatial analysis theory were used to analyze annual precipitation and mean temperature data that were collected at seven national weather stations in the Sanjiang Plain from 1956 to 2013 to identify the temporal-spatial patterns of annual precipitation changes caused by climate change conditions. The results showed that the climate in the Sanjiang Plain experienced a significant warming trend over the past 50 years, with the temperature increasing by 1.35 °C since the 1960s. Additionally, the precipitation also exhibited certain trend characteristics, which revealed a larger difference in different areas. The annual precipitation exhibited 23-year and 12-year periodic variation characteristics, and the period with above-average annual precipitation levels is expected to continue after 2013. The spatial distributions of the mean annual precipitation for different years were different, whereas the spatial distribution of the multi-year mean precipitation was relatively uniform. The annual variation amplitude of the annual precipitation in the central area was larger than that in the south. The overall inter-annual fluctuation of the annual precipitation was relatively small with a mostly normal distribution. The results can provide guidance for scientific investigations and the reasonable use of rainfall resources in the Sanjiang Plain.\u003C\u002Fjats:p>",{"VI":838,"EN":839},"Các mô hình tiến hóa tạm thời - không gian của lượng mưa hàng năm xem xét điều kiện biến đổi khí hậu tại Đồng bằng Sanjiang","Temporal-spatial evolution patterns of the annual precipitation considering the climate change conditions in the Sanjiang 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cây có mối liên hệ chặt chẽ với chu trình nước và các quá trình sinh thái. Ở quy mô lưu vực, cách dòng chảy của nước xanh\u002Flá cây thay đổi giữa các năm khí tượng điển hình (những năm khô, năm ẩm và năm bình thường) vẫn còn chưa được báo cáo nhiều. Để phân tích sự biến thiên không gian và thời gian của nước xanh\u002Flá cây trong các năm điển hình ở lưu vực sông Heihe, các năm khí tượng điển hình đã được xác định bằng cách sử dụng chỉ số lượng mưa tiêu chuẩn (SPI) và chỉ số bất thường về lượng mưa (H), và các dòng chảy của nước xanh\u002Flá cây đã được mô phỏng bằng cách sử dụng Công cụ Đánh giá Đất và Nước (SWAT). Các năm khí tượng điển hình thường không nhất quán từ thượng nguồn đến hạ nguồn trong lưu vực sông Heihe, ngoại trừ các năm 1978 và 1998. Hơn nữa, lượng nước xanh\u002Flá cây trong các năm ẩm (1998, 27.93 tỷ m3) cao hơn so với các năm khô (1978, 16.80 tỷ m3). Hệ số nước lá cây (GWC) lớn hơn 87.5% ở toàn bộ lưu vực sông. Có một mối tương quan tiêu cực giữa GWC và mức độ khô\u002Fẩm trong các năm khí tượng điển hình, khi khí hậu khô hơn, GWC lại cao hơn. Nghiên cứu này cung cấp hiểu biết về dòng chảy xanh\u002Flá cây trong các năm tham chiếu khác nhau nhằm quản lý tài nguyên nước xanh và nước lá cây của các sông nội địa.","\u003Cjats:p>Blue\u002Fgreen water closely links the water cycle and ecological processes. On the watershed scale, how blue\u002Fgreen water flows vary among different typical meteorological years (dry years, wet years, and normal years) remains poorly reported. To analyze the spatial and temporal variability of blue\u002Fgreen water in typical years in the Heihe River Basin, typical meteorological years were obtained by using the standardized precipitation index (SPI) and the precipitation anomaly index (H) and simulated blue\u002Fgreen water flows using the Soil and Water Assessment Tool (SWAT). The typical meteorological years are often not consistent from upstream to downstream in the Heihe River Basin, except in 1978 and 1998. Furthermore, the blue\u002Fgreen water quantities in wet years (1998, 27.93 billion m3) are higher than in dry years (1978, 16.80 billion m3). The green water coefficient (GWC) is more than 87.5% in the entire river basin. There was a negative correlation between the GWC and the degree of dry and wet in the typical meteorological years, as the drier the climate, the higher the GWC. This study provided an understanding of green\u002Fblue flows in different reference years to inland river green and blue water resource management.\u003C\u002Fjats:p>",{"VI":1203,"EN":1204},"Biến thiên không gian và thời gian của dòng nước xanh\u002Flá cây trong các năm khí tượng điển hình ở một lưu vực sông nội địa tại Trung Quốc","Spatial and temporal variability of blue\u002Fgreen water flows in typical meteorological years in an inland river basin in China",{"VOID":1206},"10.2166\u002Fwcc.2016.036",[158],[454],"https:\u002F\u002Fiwaponline.com\u002Fjwcc\u002Farticle\u002F8\u002F1\u002F165\u002F1826\u002FSpatial-and-temporal-variability-of-bluegreen",[1211],{"id":1212,"sortIndex":25,"researcher":24,"roles":1213,"affiliations":1214,"properties":1225},"ca8d3829-bc53-472c-ad8e-47d8fa6ba7eb",[],[1215],{"id":1216,"sortIndex":25,"affiliation":1217,"properties":24},"64f7d427-d4a7-475e-bc8c-502d9d039a51",{"id":1218,"createTime":1219,"updateTime":1219,"relativeEntities":1220,"slug":1221,"properties":1222,"entityType":69,"verifyStatus":23,"verifyTime":24,"verifyNote":24,"syncStatus":23,"languages":24,"translateLanguages":24,"viewCount":25},"fdc60635-fd3f-400a-9e0b-a4629550e887","2024-08-31T08:56:19.704+00:00",[],"National-Monitor-and-Scientific-Research-Station-of-Forest-Ecosystem-in-Greater-Xingan-Mountains-of-Inner-Mongolia-Forestry-College-of-Inner-Mongolia-Agricultural-University-Daxue-East-Road-Saihan-District-Huhehaote-010018-China",{"title":1223},{"EN":1224},"National Monitor and Scientific Research Station of Forest Ecosystem in Greater Xingan Mountains of Inner Mongolia, Forestry College of Inner Mongolia Agricultural University, Daxue East Road, Saihan District, Huhehaote 010018, China",{"openalex":1226,"orcid":1228,"title":1230},{"VOID":1227},"A5010586687",{"VOID":1229},"https:\u002F\u002Forcid.org\u002F0000-0002-0540-3496",{"EN":1231},"Chuanfu Zang",{"url":24,"publisher":1233,"properties":1263},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":1234,"slug":10,"properties":1235,"entityType":22,"verifyStatus":23,"verifyTime":24,"verifyNote":24,"syncStatus":23,"languages":24,"translateLanguages":24,"viewCount":25,"subjectFields":1241,"manageAffiliations":1242,"indexDatabases":1243,"url":114,"thumbnailPath":24,"statistic":1258,"gsStatistic":24,"type":24,"analyzePriority":24},[],{"country":1236,"issn":1237,"introduce":1238,"eissn":1239,"title":1240},{"VOID":13},{"VOID":15},{"EN":17},{"VOID":19},{"EN":21},[],[],[1244,1251],{"id":74,"indexDatabase":1245,"url":89,"indexYears":24,"academicFieldIds":1250,"indexDatabaseRanking":24},{"id":76,"createTime":77,"updateTime":78,"relativeEntities":1246,"label":1247,"description":1248,"key":85,"publicationTags":1249,"standard":24},[],{"EN":81,"VI":81},{"VI":83,"EN":84},[87,88],[91],{"id":93,"indexDatabase":1252,"url":106,"indexYears":107,"academicFieldIds":1257,"indexDatabaseRanking":113},{"id":95,"createTime":96,"updateTime":97,"relativeEntities":1253,"label":1254,"description":1255,"key":103,"publicationTags":1256,"standard":24},[],{"EN":100,"VI":100},{"EN":100,"VI":102},[105],[109,110,111,112],{"impactFactor":25,"impactFactorByYear":1259,"i10Index":120,"i10IndexLast5Year":122,"totalPublication":123,"totalPublicationByYear":1260,"totalCitation":125,"totalCitationByYear":1261,"totalCitationPerPublication":131,"totalCitationPerPublicationByYear":1262,"hindexLast5Year":70,"hindex":70},{"2015":117,"2017":117,"2018":118,"2020":70,"2021":119,"2022":120,"2023":121},{"2013":117,"2016":117,"2017":117,"2019":117,"2021":122,"2023":117,"2024":117},{"2013":127,"2016":128,"2017":123,"2019":129,"2021":130,"2023":70},{"2013":127,"2016":128,"2017":123,"2019":129,"2021":133,"2023":70},{"volume":1264,"pages":1266,"issue":1268},{"VOID":1265},"8",{"VOID":1267},"165-176",{"VOID":1010},{"total":123,"publishYear":24,"statisticByYear":1270},{"2018":122,"2021":122,"2023":122,"2024":122},"2017-03-01",2017,[1274,1277,1281,1284,1287,1291,1294,1298,1302,1305,1308,1311,1314,1317,1320,1324,1328,1332,1336,1340,1343,1347,1350,1354,1358,1362,1366,1370,1374,1378,1381,1385,1388,1392,1396,1400,1404],{"id":24,"text":1275,"url":24,"identifiers":1276},"Abbaspour, 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10.1016\u002Fj.catena.2015.09.018",{"doi":1407},"10.1016\u002Fj.catena.2015.09.018",{"id":1409,"createTime":1410,"updateTime":1411,"relativeEntities":1412,"slug":1413,"properties":1414,"entityType":153,"verifyStatus":154,"verifyTime":1410,"verifyNote":156,"syncStatus":23,"languages":1428,"translateLanguages":1429,"viewCount":25,"primaryUrl":1430,"fullTextUrl":24,"authors":1431,"publicationType":280,"publisherRelationship":1513,"citationCount":127,"citationInfo":1550,"publishDate":1552,"publishYear":1553,"citationAnalyzeStatus":23,"lastCitationAnalyze":24,"indexDatabases":24,"openAccess":24,"references":1554,"isForceReanalyzing":430},"817fdbd9-7a5e-4bae-9a4b-396c82c8b282","2024-11-27T20:29:35.138+00:00","2025-01-24T09:43:18.336+00:00",[],"Appraising-sustainable-flood-risk-management-in-the-Pearl-River-Delta-s-coastal-megacities-a-case-study-of-Hong-Kong-China",{"mag":1415,"keywords":1417,"openalex":1418,"abstract":1420,"title":1423,"doi":1426},{"VOID":1416},"2035545068",{"VI":441},{"VOID":1419},"W2035545068",{"VI":1421,"EN":1422},"\u003Cjats:p>Vùng Đồng bằng Sông Châu Giang (PRD) đã trải qua sự tăng trưởng kinh tế và dân số nhanh chóng trong ba thập kỷ qua. Delta này bao gồm các siêu đô thị ven biển, chẳng hạn như Hồng Kông. Những khu vực ven biển trũng thấp đô thị hóa ở PRD đang đối mặt với nguy cơ ngập lụt do điều kiện khí hậu khó lường. Những điều này có thể dẫn đến sóng bão tăng cường, mực nước biển dâng cao và những cơn mưa lớn tăng cường gây ra ngập lụt ven biển và nội địa, tất cả đều ảnh hưởng đến delta. Bài báo này tập trung vào siêu đô thị ven biển Hồng Kông như một trường hợp nghiên cứu, với hai địa điểm được chọn là sông Thâm Quyến và thị trấn Tai O, vì những vấn đề ngập lụt nội địa và ven biển cụ thể của chúng. Một mẫu đánh giá rủi ro lũ bền vững (SFRA) đã được phát triển để đối chiếu với các thực hành quản lý rủi ro lũ bền vững (FRM) tại các địa điểm này. Ba mươi tám bên liên quan đã được phỏng vấn trong nghiên cứu này để hiểu rõ các thực hành FRM hiện tại, những rào cản và hạn chế của chúng. Kết quả cho thấy FRM trong nghiên cứu trường hợp hiện tại tập trung vào kỹ thuật cứng, trong khi bỏ qua những chỉ số bền vững quan trọng khác. Một thực hành SFRA xem xét sự tham gia của công chúng, công bằng trong chuẩn bị ứng phó với lũ lụt và thân thiện với môi trường có thể hiệu quả trong việc đạt được các thực hành giảm thiểu rủi ro lũ bền vững ở Hồng Kông và các thành phố ven biển khác trong PRD.\u003C\u002Fjats:p>","\u003Cjats:p>The Pearl River Delta (PRD) region has experienced rapid economic and population growth in the last three decades. The delta includes coastal megacities, such as Hong Kong. These low-lying urbanised coastal regions in the PRD are vulnerable to flood risks from unpredictable climatic conditions. These can result in increasing storm surges, rising sea level and intensified rainstorms causing coastal and inland flooding, all of which impact the delta. This paper has taken the coastal megacity of Hong Kong as a case, focusing on two study sites: Shenzhen River and Tai O town, chosen for their peculiar inland and coastal flood problems. A sustainable flood risk appraisal (SFRA) template was developed against which sustainable flood risk management (FRM) practices in these sites were benchmarked. Thirty-eight stakeholders were interviewed during this research in order to understand the current FRM practices, their barriers and their constraints. It was found that FRM in the case study currently focuses on hard engineering, while neglecting other important sustainability indicators. A SFRA practice that takes public participation, equity of flood preparedness and environmental friendly into account could be effective in achieving sustainable flood risk mitigation practices in Hong Kong and other coastal cities in the PRD.\u003C\u002Fjats:p>",{"VI":1424,"EN":1425},"Đánh giá quản lý rủi ro lũ bền vững ở các siêu đô thị ven biển vùng Đồng bằng Sông Châu Giang: Nghiên cứu trường hợp của Hồng Kông, Trung Quốc","Appraising sustainable flood risk management in the Pearl River Delta's coastal megacities: a case study of Hong Kong, China",{"VOID":1427},"10.2166\u002Fwcc.2013.018",[158],[454],"https:\u002F\u002Fiwaponline.com\u002Fjwcc\u002Farticle\u002F4\u002F4\u002F390\u002F3643\u002FAppraising-sustainable-flood-risk-management-in",[1432,1454,1481,1496],{"id":1433,"sortIndex":117,"researcher":24,"roles":1434,"affiliations":1435,"properties":1447},"c896e8c6-54da-4274-b6a7-50a0c2769ece",[],[1436],{"id":1437,"sortIndex":25,"affiliation":1438,"properties":24},"6a72fd65-0717-4391-965e-76ff36d2f222",{"id":1439,"createTime":1440,"updateTime":1441,"relativeEntities":1442,"slug":1443,"properties":1444,"entityType":69,"verifyStatus":23,"verifyTime":24,"verifyNote":24,"syncStatus":23,"languages":24,"translateLanguages":24,"viewCount":25},"91de981c-237c-4e93-a9e6-97e14ed00861","2023-12-01T23:33:14.409+00:00","2024-11-27T20:29:35.154+00:00",[],"School-of-Geography-University-of-Leeds-Leeds-LS29JT-UK",{"title":1445},{"VI":1446},"School of Geography, University of Leeds, Leeds LS29JT, UK",{"openalex":1448,"orcid":1450,"title":1452},{"VOID":1449},"A5003162913",{"VOID":1451},"https:\u002F\u002Forcid.org\u002F0000-0001-9747-0583",{"EN":1453},"Olalekan Adekola",{"id":1455,"sortIndex":25,"researcher":24,"roles":1456,"affiliations":1457,"properties":1474},"5fc94bff-c69a-4325-b63d-97cf8363e4eb",[],[1458,1464],{"id":1459,"sortIndex":117,"affiliation":1460,"properties":24},"af4fe0ed-0b66-4e32-bdfa-d32d9b5c4b23",{"id":1439,"createTime":1440,"updateTime":1441,"relativeEntities":1461,"slug":1443,"properties":1462,"entityType":69,"verifyStatus":23,"verifyTime":24,"verifyNote":24,"syncStatus":23,"languages":24,"translateLanguages":24,"viewCount":25},[],{"title":1463},{"VI":1446},{"id":1465,"sortIndex":25,"affiliation":1466,"properties":24},"9e7c0d20-9fb4-4462-8719-b6d9ba0c8ba7",{"id":1467,"createTime":1468,"updateTime":1468,"relativeEntities":1469,"slug":1470,"properties":1471,"entityType":69,"verifyStatus":23,"verifyTime":24,"verifyNote":24,"syncStatus":23,"languages":24,"translateLanguages":24,"viewCount":25},"d0228917-8c41-4fb9-8f5b-e25e01da5ebf","2024-11-27T20:29:35.151+00:00",[],"Department-of-Geographical-Sciences-University-of-Nottingham-Ningbo-Campus-199-Taikang-East-Road-Ningbo-315100-China",{"title":1472},{"EN":1473},"Department of Geographical Sciences, University of Nottingham, Ningbo Campus, 199 Taikang East Road, Ningbo 315100, China",{"openalex":1475,"orcid":1477,"title":1479},{"VOID":1476},"A5025341348",{"VOID":1478},"https:\u002F\u002Forcid.org\u002F0000-0001-6091-6596",{"EN":1480},"Faith Ka Shun Chan",{"id":1482,"sortIndex":120,"researcher":24,"roles":1483,"affiliations":1484,"properties":1491},"83c227af-4d5a-48b5-94f2-f71bd51cffa1",[],[1485],{"id":1486,"sortIndex":25,"affiliation":1487,"properties":24},"cc066d90-20e0-4242-a31c-f7bb1abd8aea",{"id":1439,"createTime":1440,"updateTime":1441,"relativeEntities":1488,"slug":1443,"properties":1489,"entityType":69,"verifyStatus":23,"verifyTime":24,"verifyNote":24,"syncStatus":23,"languages":24,"translateLanguages":24,"viewCount":25},[],{"title":1490},{"VI":1446},{"openalex":1492,"title":1494},{"VOID":1493},"A5104594812",{"EN":1495},"A. 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Nghiên cứu đã sử dụng 13 Mô hình Khí hậu Toàn cầu (GCM) từ Dự án So sánh Mô hình Liên kết Giai đoạn 6 (CMIP6). Dựa trên việc đánh giá hiệu suất của 13 GCM-CMIP6, các GCM tốt nhất được chọn cho các dự đoán trong tương lai là EC-Earth3, MPI-ESM1-2-LR và MPI-ESM1-2-HR. SWAT-CUP (SWAT – Chương trình Hiệu chỉnh và Không chắc chắn) đã hiệu chỉnh và xác thực thành công mô hình SWAT. Mô hình SWAT đã mô phỏng các thành phần thủy văn của lưu vực cho giai đoạn tương lai dưới các kịch bản phát thải SSP245 và SSP585. Kết quả cho thấy lượng dòng chảy tăng lên trong giai đoạn dự đoán do lượng mưa tăng trong lưu vực. Lượng nước chảy bề mặt hàng năm biến đổi từ −20,41 đến −15,46%, −10,51 đến 18,34% và 73,88 đến 134,56% dưới kịch bản SSP585 cho các thập kỷ 2020, 2050 và 2080, tương ứng. Đối với tương lai thập kỷ 2020, sản lượng nước biến đổi từ −7,02 đến 11,36% và −1,41 đến 6,15% cho SSP245 và SSP585. Trong các thập kỷ 2050 và 2080, có sự gia tăng sản lượng nước (7,89–21,18% và 36,12–115,25%) dưới các kịch bản khí hậu tương lai SSP245 và SSP585. Nghiên cứu này có thể giúp các nhà lập chính sách và các bên liên quan phát triển các chiến lược thích ứng cho lưu vực sông Ponnaiyar.\u003C\u002Fjats:p>","\u003Cjats:title>Abstract\u003C\u002Fjats:title>\u003Cjats:p>This study aims to assess the climate change impacts on the hydrological components in the Ponnaiyar river basin using the Soil Water Assessment Tool (SWAT) model. This study used 13 Global Climate Models (GCM) from Coupled Model Inter-comparison Project Phase 6 (CMIP6). Based on the performance evaluation of 13 CMIP6-GCMs, the best GCMs selected for future projections were EC-Earth3, MPI-ESM1-2-LR and MPI-ESM1-2-HR. SWAT-CUP (SWAT – Calibration and Uncertainty Programs) successfully calibrated and validated the SWAT model. The SWAT model simulated the hydrological components of the basin for the future period under SSP245 and SSP585 emission scenarios. The results indicated increased streamflow over the projected period due to increased rainfall in the basin. The annual surface runoff varied from −20.41 to −15.46%, −10.51 to 18.34% and 73.88 to 134.56% under the SSP585 scenario for the 2020s, 2050s and 2080s, respectively. For the future 2020s, the water yield varied from −7.02 to 11.36% and −1.41 to 6.15% for SSP245 and SSP585. During the 2050s and 2080s, there was an increase in water yield (7.89–21.18% and 36.12–115.25%) under SSP245 and SSP585 future climate scenarios. This study could help policymakers and stakeholders to develop adaptive strategies for the Ponniyar river basin.\u003C\u002Fjats:p>",{"VI":1570,"EN":1571},"Đánh giá tác động của biến đổi khí hậu đến các thành phần thủy văn của lưu vực sông Ponnaiyar, Tamil Nadu sử dụng các mô hình CMIP6","Assessment of climate change impact on hydrological components of Ponnaiyar river basin, Tamil Nadu using CMIP6 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Assessment of climate change impacts on streamflow through hydrological model using SWAT model: a case study of Afghanistan, Modeling Earth Systems and Environment, 6, 1427, 10.1007\u002Fs40808-020-00759-0",{"doi":1678},"10.1007\u002Fs40808-020-00759-0",{"id":24,"text":1680,"url":24,"identifiers":1681},"2020, Assessment of climate change impact on flow regimes over the Gomti River basin under IPCC AR5 climate change scenarios, Journal of Water and Climate Change, 11, 303, 10.2166\u002Fwcc.2018.039",{"doi":1682},"10.2166\u002Fwcc.2018.039",{"id":24,"text":1684,"url":24,"identifiers":1685},"2019, Selection of multi-model ensemble of GCMs for the simulation of precipitation based on spatial assessment metrics, Hydrology and Earth System Sciences, 23, 4803, 10.5194\u002Fhess-23-4803-2019",{"doi":1686},"10.5194\u002Fhess-23-4803-2019",{"id":24,"text":1688,"url":24,"identifiers":1689},"2012, SWAT: Model use, calibration, and validation, Transactions of the ASABE, 55, 1491, 10.13031\u002F2013.42256",{"doi":1690},"10.13031\u002F2013.42256",{"id":24,"text":1692,"url":24,"identifiers":1693},"2012, Progress and challenges in urban climate adaptation planning: results of a global survey, 33",{},{"id":24,"text":1695,"url":24,"identifiers":1696},"CGWB 2017 Report on Aquifer Mapping for Sustainable Management of Groundwater Resources in Upper Ponnaiyar River Basin Aquifer System, Tamil Nadu. Central Ground Water Board, Ministry of Water Resources, River Development and Ganga Rejuvenation Government of India.",{},{"id":24,"text":1698,"url":24,"identifiers":1699},"2022, Effect of climate change on streamflow in the Gelana watershed, Rift valley basin, Ethiopia, Journal of Water and Climate Change, 13, 2205, 10.2166\u002Fwcc.2022.059",{"doi":1700},"10.2166\u002Fwcc.2022.059",{"id":24,"text":1702,"url":24,"identifiers":1703},"2016, Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization, Geoscientific Model Development, 9, 1937, 10.5194\u002Fgmd-9-1937-2016",{"doi":1704},"10.5194\u002Fgmd-9-1937-2016",{"id":24,"text":1706,"url":24,"identifiers":1707},"2010, Assessing hydrological impacts of climate change: modeling techniques and challenges, The Open Hydrology Journal, 4, 115, 10.2174\u002F1874378101004010115",{"doi":1708},"10.2174\u002F1874378101004010115",{"id":24,"text":1710,"url":24,"identifiers":1711},"2019, Global emissions pathways under different socioeconomic scenarios for use in CMIP6: a dataset of harmonized emissions trajectories through the end of the century, Geoscientific Model Development, 12, 1443, 10.5194\u002Fgmd-12-1443-2019",{"doi":1712},"10.5194\u002Fgmd-12-1443-2019",{"id":24,"text":1714,"url":24,"identifiers":1715},"2014, Evaluating three hydrological distributed watershed models: MIKE-SHE, APEX, SWAT, 20",{},{"id":24,"text":1717,"url":24,"identifiers":1718},"2022, Hydrologic characterization of the Upper Ayeyarwaddy River Basin and the impact of climate change, Journal of Water and Climate Change, 13, 2577, 10.2166\u002Fwcc.2022.407",{"doi":1719},"10.2166\u002Fwcc.2022.407",{"id":24,"text":1721,"url":24,"identifiers":1722},"2022, Hydrological impacts of climate and land-use change on flow regime variations in upper Indus basin, Journal of Water and Climate Change, 13, 758, 10.2166\u002Fwcc.2021.238",{"doi":1723},"10.2166\u002Fwcc.2021.238",{"id":24,"text":1725,"url":24,"identifiers":1726},"2022, Climate change impact on water balance and hydrological extremes in the Lower Mekong Basin : a case study of Prek Thnot River Basin, Cambodia, 00, 1",{},{"id":24,"text":1728,"url":24,"identifiers":1729},"IPCC, 2022",{},{"id":24,"text":1731,"url":24,"identifiers":1732},"IPCC, 2022, Technical Summary, The Ocean and Cryosphere in a Changing Climate, 39",{},{"id":24,"text":1734,"url":24,"identifiers":1735},"2021, Evaluation of CMIP6 GCM rainfall in mainland Southeast Asia, Atmospheric Research, 254, 105525, 10.1016\u002Fj.atmosres.2021.105525",{"doi":1736},"10.1016\u002Fj.atmosres.2021.105525",{"id":24,"text":1738,"url":24,"identifiers":1739},"2021, Water resources availability under different climate change scenarios in South East Iran, 12, 3976",{},{"id":24,"text":1741,"url":24,"identifiers":1742},"2005, Advances in the application of the SWAT model for water resources management, Hydrological Processes, 19, 749, 10.1002\u002Fhyp.5624",{"doi":1743},"10.1002\u002Fhyp.5624",{"id":24,"text":1745,"url":24,"identifiers":1746},"2007, Hydrogeochemistry and groundwater quality assessment of lower part of the Ponnaiyar River Basin, Cuddalore district, South India, Environmental Monitoring and Assessment, 132, 263",{},{"id":24,"text":1748,"url":24,"identifiers":1749},"2017, Spatial mapping of groundwater potential in Ponnaiyar River basin using probabilistic-based frequency ratio model, Modeling Earth Systems and Environment, 3, 1",{},{"id":24,"text":1751,"url":24,"identifiers":1752},"2021, Assessment of climate change impact on water availability in the Upper Dong Nai River Basin, Vietnam, Journal of Water and Climate Change, 12, 3851, 10.2166\u002Fwcc.2021.255",{"doi":1753},"10.2166\u002Fwcc.2021.255",{"id":24,"text":1755,"url":24,"identifiers":1756},"2010, Bias correction of monthly precipitation and temperature fields from Intergovernmental Panel on Climate Change AR4 models using equidistant quantile matching, 115",{},{"id":24,"text":1758,"url":24,"identifiers":1759},"2020, Assessment and ranking of CMIP5 GCMs performance based on observed statistics over Cauvery river basin – Peninsular India, Arabian Journal of Geosciences, 13",{},{"id":24,"text":1761,"url":24,"identifiers":1762},"2021, Evaluation of historical CMIP6 model simulations and future projections of temperature and precipitation in Paraguay, Climatic Change, 164, 1",{},{"id":24,"text":1764,"url":24,"identifiers":1765},"2020, Bias-corrected climate projections for South Asia from Coupled Model Intercomparison Project-6, Scientific Data, 7, 1",{},{"id":24,"text":1767,"url":24,"identifiers":1768},"2007, Model evaluation guidelines for systematic quantification of accuracy in watershed simulations, American Society of Agricultural and Biological Engineers, 50, 885",{},{"id":24,"text":1770,"url":24,"identifiers":1771},"2009, 1.1 Overview of soil and water assessment tool (SWAT) model, Tier B, 8, 3",{},{"id":24,"text":1773,"url":24,"identifiers":1774},"Neitsch S. L. , ArnoldJ. G., KiniryJ. R. & WilliamsJ. R.2011Theoretical Documentation SWAT.",{},{"id":24,"text":1776,"url":24,"identifiers":1777},"2021, Water resources of the Desna river basin under future climate, Journal of Water and Climate Change, 12, 3355, 10.2166\u002Fwcc.2021.034",{"doi":1778},"10.2166\u002Fwcc.2021.034",{"id":24,"text":1780,"url":24,"identifiers":1781},"2022, Modelling climate change impact on water resources of the Upper Indus Basin, Journal of Water and Climate Change, 13, 482, 10.2166\u002Fwcc.2021.233",{"doi":1782},"10.2166\u002Fwcc.2021.233",{"id":24,"text":1784,"url":24,"identifiers":1785},"2019, Prioritization of global climate models using fuzzy analytic hierarchy process and reliability index, Theoretical and Applied Climatology, 137, 2381, 10.1007\u002Fs00704-018-2707-y",{"doi":1786},"10.1007\u002Fs00704-018-2707-y",{"id":24,"text":1788,"url":24,"identifiers":1789},"2020, Review of approaches for selection and ensembling of GCMS, Journal of Water and Climate Change, 11, 577, 10.2166\u002Fwcc.2020.128",{"doi":1790},"10.2166\u002Fwcc.2020.128",{"id":24,"text":1792,"url":24,"identifiers":1793},"1990",{},{"id":24,"text":1795,"url":24,"identifiers":1796},"2022, Adaptation of satellite-based precipitation product to study runoff and sediment of Indian River watersheds, Arabian Journal of Geosciences, 15",{},{"id":24,"text":1798,"url":24,"identifiers":1799},"2022, Assessing streamflow modeling using single and multi-site calibration approach on Bharathpuzha catchment, India: a case study, Modeling Earth Systems and Environment, 0123456789",{},{"id":24,"text":1801,"url":24,"identifiers":1802},"2015, Global hydrological models: a review, Hydrological Sciences Journal, 60, 549, 10.1080\u002F02626667.2014.950580",{"doi":1803},"10.1080\u002F02626667.2014.950580",{"id":24,"text":1805,"url":24,"identifiers":1806},"2010, Soil and water assessment tool (Swat) model: current developments and applications, American Society of Agricultural and Biological Engineers, 53, 1423",{},{"id":24,"text":1808,"url":24,"identifiers":1809},"2012, SWAT: Model use, calibration, and validation, American Society of Agricultural and Biological Engineers, 55, 1491",{},{"id":24,"text":1811,"url":24,"identifiers":1812},"2015, Ranking general circulation models for India using TOPSIS, Journal of Water and Climate Change, 6, 288, 10.2166\u002Fwcc.2014.074",{"doi":1813},"10.2166\u002Fwcc.2014.074",{"id":24,"text":1815,"url":24,"identifiers":1816},"2017, Ranking of CMIP5-based global climate models for India using compromise programming, Theoretical and Applied Climatology, 128, 563",{},{"id":24,"text":1818,"url":24,"identifiers":1819},"2018, Application of storm water management model to an urban catchment, Hydrologic Modeling, 81, 175, 10.1007\u002F978-981-10-5801-1_13",{"doi":1820},"10.1007\u002F978-981-10-5801-1_13",{"id":24,"text":1822,"url":24,"identifiers":1823},"UNDESA, 2012, World Urbanization Prospects: The 2011 Revision",{},{"id":24,"text":1825,"url":24,"identifiers":1826},"UNDESA, 2014, UN. World Urbanization Prospects: The 2014 Revision-Highlights",{},{"id":24,"text":1828,"url":24,"identifiers":1829},"2011, The representative concentration pathways: an overview, Climatic Change, 109, 5",{},{"id":24,"text":1831,"url":24,"identifiers":1832},"2021, Future changes in precipitation and temperature over the Yangtze River Basin in China based on CMIP6 GCMs, Atmospheric Research, 264, 105828, 10.1016\u002Fj.atmosres.2021.105828",{"doi":1833},"10.1016\u002Fj.atmosres.2021.105828",{"id":1835,"createTime":1836,"updateTime":1837,"relativeEntities":1838,"slug":1839,"properties":1840,"entityType":153,"verifyStatus":154,"verifyTime":1836,"verifyNote":156,"syncStatus":23,"languages":1854,"translateLanguages":1855,"viewCount":25,"primaryUrl":1856,"fullTextUrl":24,"authors":1857,"publicationType":280,"publisherRelationship":1914,"citationCount":1950,"citationInfo":1951,"publishDate":1953,"publishYear":610,"citationAnalyzeStatus":23,"lastCitationAnalyze":24,"indexDatabases":24,"openAccess":24,"references":1954,"isForceReanalyzing":430},"3e310131-a862-4332-b495-59ce0592e6a4","2024-10-07T02:35:00.490+00:00","2025-01-24T09:41:23.820+00:00",[],"Spatio-temporal-variation-and-future-risk-assessment-of-projected-drought-events-in-the-Godavari-River-basin-using-regional-climate-models",{"mag":1841,"keywords":1843,"openalex":1844,"abstract":1846,"title":1849,"doi":1852},{"VOID":1842},"3188587262",{"VI":441},{"VOID":1845},"W3188587262",{"VI":1847,"EN":1848},"\u003Cjats:title>Tóm tắt\u003C\u002Fjats:title>\u003Cjats:p>Nghiên cứu tập trung vào lưu vực sông Godavari nhằm hiểu rõ sự thay đổi trong hiện tượng hạn hán cho các kịch bản tương lai. Chỉ số Tích hợp Khí hậu Kiểm soát Khô hạn Chuẩn hóa (SPEI)-3 được tính toán từ dữ liệu mưa của Đơn vị Nghiên cứu Khí hậu 4.03 và nhiệt độ tối thiểu cũng như tối đa. Cường độ và đặc điểm của hạn hán được xác định bằng cách sử dụng SPEI, xem xét cả dữ liệu về lượng mưa và nhiệt độ như là biến đầu vào. Phân tích xu hướng Mann–Kendall được thực hiện để xác định xu hướng liên quan đến các đặc điểm hạn hán. Lưu vực được chia thành sáu vùng đồng nhất bằng cách sử dụng thuật toán phân cụm K-means. Phương pháp trung bình hợp thành độ tin cậy được sử dụng cho việc trung bình hợp thành các mô hình khí hậu vùng (RCMs). Phân tích tần suất hạn hán được thực hiện bằng cách sử dụng copula ba biến cho các khoảng thời gian tham chiếu và tương lai. Sự biến đổi trong các đặc điểm hạn hán được quan sát thấy ở các kịch bản tương lai liên quan đến khoảng thời gian tham chiếu. Thời gian kéo dài, cường độ và đỉnh điểm của hạn hán cho các phân vùng khí hậu khác nhau cho thấy một xu hướng gia tăng trong khoảng thời gian tương lai, đặc biệt là trong các kịch bản RCP8.5. Thời gian quay trở lại của các đợt hạn hán trong tương lai dựa trên các mô hình RCM trung bình có trọng số dưới hai kịch bản cho thấy khả năng xảy ra hạn hán thường xuyên hơn trong tương lai (2053–2099) so với trong quá khứ (1971–2017).\u003C\u002Fjats:p>","\u003Cjats:title>Abstract\u003C\u002Fjats:title>\u003Cjats:p>The study focused on the Godavari River basin to understand the alteration in the drought phenomenon for future scenarios. The Standardized Precipitation Evapotranspiration Index (SPEI)-3 is calculated from Climate Research Unit 4.03 precipitation, and minimum and maximum temperatures. The drought magnitude and characteristics are determined using SPEI, which considers both precipitation and temperature data as input variables. The Mann–Kendall trend analysis is performed to identify the trend associated with drought characteristics. The basin is divided into six homogeneous regions using K-means clustering algorithm. The reliability ensemble averaging method is used for ensemble averaging of regional climate models (RCMs). The drought frequency analysis is carried out using trivariate copula for reference and future time periods. Variations in the drought characteristics are observed in the future scenarios with respect to the reference period. The drought duration, severity and peak for different climate divisions showed an increasing trend in future time period, especially in the case of RCP8.5 scenarios. The return periods of future droughts based on weighted-average RCMs under the two scenarios showed the possibility of more frequent droughts in the future (2053–2099) than in the past (1971–2017).\u003C\u002Fjats:p>",{"VI":1850,"EN":1851},"Biến động không gian-thời gian và đánh giá rủi ro tương lai của các sự kiện hạn hán dự báo tại lưu vực sông Godavari sử dụng các mô hình khí hậu vùng","Spatio-temporal variation and future risk assessment of projected drought events in the Godavari River basin using regional climate models",{"VOID":1853},"10.2166\u002Fwcc.2021.093",[158],[454],"https:\u002F\u002Fiwaponline.com\u002Fjwcc\u002Farticle\u002F12\u002F7\u002F3240\u002F82904\u002FSpatio-temporal-variation-and-future-risk",[1858,1880,1897],{"id":1859,"sortIndex":117,"researcher":24,"roles":1860,"affiliations":1861,"properties":1873},"c5e5905f-878c-448d-bfd7-597ae3766517",[],[1862],{"id":1863,"sortIndex":25,"affiliation":1864,"properties":24},"32740112-8dd9-4020-b25e-da086f95a37f",{"id":1865,"createTime":1866,"updateTime":1867,"relativeEntities":1868,"slug":1869,"properties":1870,"entityType":69,"verifyStatus":23,"verifyTime":24,"verifyNote":24,"syncStatus":23,"languages":24,"translateLanguages":24,"viewCount":25},"49adf35a-e79d-4689-bd09-f64d9c14a378","2024-04-06T16:35:55.437+00:00","2024-12-06T02:22:26.363+00:00",[],"Department-of-Civil-Engineering-National-Institute-of-Technology-Warangal-Warangal-India",{"title":1871},{"VI":1872},"Department of Civil Engineering, National Institute of Technology Warangal, Warangal, India",{"openalex":1874,"orcid":1876,"title":1878},{"VOID":1875},"A5028910108",{"VOID":1877},"https:\u002F\u002Forcid.org\u002F0000-0002-7049-0258",{"EN":1879},"Syed Tayyaba",{"id":1881,"sortIndex":122,"researcher":24,"roles":1882,"affiliations":1883,"properties":1890},"cd21dd74-8ae4-4559-a3d2-1f172a663bad",[],[1884],{"id":1885,"sortIndex":25,"affiliation":1886,"properties":24},"2b56f774-df38-44c7-ba00-b19b8b51e8e0",{"id":1865,"createTime":1866,"updateTime":1867,"relativeEntities":1887,"slug":1869,"properties":1888,"entityType":69,"verifyStatus":23,"verifyTime":24,"verifyNote":24,"syncStatus":23,"languages":24,"translateLanguages":24,"viewCount":25},[],{"title":1889},{"VI":1872},{"openalex":1891,"orcid":1893,"title":1895},{"VOID":1892},"A5107246725",{"VOID":1894},"https:\u002F\u002Forcid.org\u002F0000-0003-2602-1814",{"EN":1896},"K. 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M. 1967 Objective Approach to Definitions and Investigations of Continental Hydrologic Droughts. Doctoral Dissertation, Colorado State University. https:\u002F\u002Fdoi.org\u002F10.1016\u002F0022-1694(69)90110-3.",{"doi":2175},"10.1016\u002F0022-1694(69)90110-3",{"id":24,"text":2177,"url":24,"identifiers":2178},"10.1016\u002Fj.jhydrol.2014.09.071",{"doi":2177},{"id":24,"text":2180,"url":24,"identifiers":2181},"10.1016\u002Fj.jhydrol.2012.09.054",{"doi":2180},{"id":2183,"createTime":2184,"updateTime":2185,"relativeEntities":2186,"slug":2187,"properties":2188,"entityType":153,"verifyStatus":154,"verifyTime":2184,"verifyNote":156,"syncStatus":23,"languages":2202,"translateLanguages":2203,"viewCount":25,"primaryUrl":2204,"fullTextUrl":24,"authors":2205,"publicationType":280,"publisherRelationship":2309,"citationCount":2345,"citationInfo":2346,"publishDate":2348,"publishYear":1272,"citationAnalyzeStatus":23,"lastCitationAnalyze":24,"indexDatabases":24,"openAccess":24,"references":2349,"isForceReanalyzing":430},"493b0f6d-8dd6-4d13-be0f-5c594f6a9bd4","2025-01-03T07:11:33.197+00:00","2025-01-24T09:40:25.478+00:00",[],"Assessing-the-impacts-of-climate-change-on-water-resources-in-the-Srepok-watershed-Central-Highland-of-Vietnam",{"mag":2189,"keywords":2191,"openalex":2192,"abstract":2194,"title":2197,"doi":2200},{"VOID":2190},"2625093192",{"VI":441},{"VOID":2193},"W2625093192",{"VI":2195,"EN":2196},"\u003Cjats:p>Lưu vực sông Srepok ở Tây Nguyên Việt Nam đóng vai trò quan trọng trong sự phát triển kinh tế của vùng. Những tác động có hại của biến đổi khí hậu đối với tài nguyên thiên nhiên có thể gây khó khăn cho sự phát triển xã hội và kinh tế trong khu vực này. Nghiên cứu hiện tại nhằm mục đích dự đoán và đánh giá các thay đổi của tài nguyên nước trong lưu vực sông Srepok dưới tác động của các kịch bản biến đổi khí hậu bằng cách sử dụng mô hình đánh giá đất và nước (SWAT). Nghiên cứu đã sử dụng dữ liệu thời tiết quan trắc từ năm 1990 đến 2010 cho giai đoạn đầu tiên và các kịch bản biến đổi khí hậu A1B và A2 từ năm 2011 đến 2039 cho giai đoạn thứ hai và từ 2040 đến 2069 cho giai đoạn thứ ba. Theo các kịch bản biến đổi khí hậu của lưu vực nghiên cứu, nhiệt độ trung bình hàng ngày tối thiểu và tối đa trong tương lai sẽ tăng lên trong tất cả các kịch bản, và lượng mưa hàng năm sẽ giảm trong kịch bản A1B và tăng trong kịch bản A2. Dựa trên kết quả mô phỏng, lưu lượng nước hàng năm trong kịch bản A1B giảm 11,1% và 1,2% trong giai đoạn thứ hai và thứ ba, lần lượt, so với giai đoạn đầu tiên. Trong kịch bản A2, lưu lượng nước hàng năm tăng 2,4% trong giai đoạn thứ hai nhưng giảm 1,8% trong giai đoạn thứ ba.\u003C\u002Fjats:p>","\u003Cjats:p>The Srepok watershed in the Central Highland of Vietnam plays an important role in the economic development of the region. Any harmful effects of climate change on natural resources may cause difficulties for social and economic development in this area. The present study aims to predict and evaluate changes of water resources in the Srepok watershed under the impact of climate change scenarios by using the soil and water assessment tool (SWAT) model. The study used observed weather data from 1990 to 2010 for the first period and climate change scenarios A1B and A2 from 2011 to 2039 for the second period and from 2040 to 2069 for the third period. According to the climate change scenarios of the studied watershed, future minimum and maximum daily average temperature will rise in all climate change scenarios and the amount of annual precipitation will fall in scenario A1B and go up in scenario A2. Based on the simulation results, the annual water discharge in scenario A1B decreased by 11.1% and 1.2% during the second and third periods, respectively, compared with the first. In scenario A2, annual water discharge increased by 2.4% during the second period but decreased by 1.8% during the third period.\u003C\u002Fjats:p>",{"VI":2198,"EN":2199},"Đánh giá tác động của biến đổi khí hậu đối với tài nguyên nước tại lưu vực sông Srepok, Tây Nguyên Việt Nam","Assessing the impacts of climate change on water resources in the Srepok watershed, Central Highland of 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Res., 44, 10.1029\u002F2007WR006711",{"doi":2469},"10.1029\u002F2007WR006711",{"id":2471,"createTime":2472,"updateTime":2473,"relativeEntities":2474,"slug":2475,"properties":2476,"entityType":153,"verifyStatus":154,"verifyTime":2472,"verifyNote":156,"syncStatus":23,"languages":2490,"translateLanguages":2491,"viewCount":25,"primaryUrl":2492,"fullTextUrl":24,"authors":2493,"publicationType":280,"publisherRelationship":2585,"citationCount":129,"citationInfo":2622,"publishDate":2626,"publishYear":2627,"citationAnalyzeStatus":23,"lastCitationAnalyze":24,"indexDatabases":24,"openAccess":24,"references":2628,"isForceReanalyzing":430},"d9b2a5a7-5e90-4cd7-9707-238cf27c1c2f","2024-10-02T04:26:48.369+00:00","2025-01-24T09:39:09.728+00:00",[],"Investigating-the-effect-of-hydroclimatological-variables-on-Urmia-Lake-water-level-using-wavelet-coherence-measure",{"mag":2477,"keywords":2479,"openalex":2480,"abstract":2482,"title":2485,"doi":2488},{"VOID":2478},"2796147676",{"VI":441},{"VOID":2481},"W2796147676",{"VI":2483,"EN":2484},"\u003Cjats:title>Tóm tắt\u003C\u002Fjats:title>\n               \u003Cjats:p>Trong bài báo này, đồng nhất biến đổi wavelet được thực hiện để khảo sát tác động của các biến số thủy khí hậu đến sự dao động mức nước ở hai hồ nước mặn lớn tại Trung Đông có vị trí địa lý tương tự, đó là hồ Urmia ở phía tây bắc Iran, nơi có một hệ sinh thái rất nhạy cảm do kim tự tháp sinh thái đơn giản, cùng với hồ Van ở phía đông bắc Thổ Nhĩ Kỳ. Nghiên cứu hiện tại điều tra các xu hướng trong các bậc cao hơn của chuỗi thời gian thủy văn. Mục tiêu của bài báo này là điều tra tính phức tạp của chuỗi thời gian mức nước hồ Urmia, điều này có thể dẫn đến việc giảm dao động của chuỗi thời gian. Để đạt được điều này, độ mạnh và mối quan hệ giữa năm biến số thủy khí hậu, bao gồm lượng mưa, dòng chảy, nhiệt độ, độ ẩm tương đối, cũng như sự bốc hơi và dao động mức nước ở các hồ được xác định và thảo luận theo vùng công suất chung cao, mối quan hệ pha và tương quan đa quy mô tại chỗ. Kết quả cho thấy rằng trong số các biến số thủy khí hậu, dòng chảy có độ đồng nhất cao nhất (0.9–1) với sự dao động mức nước ở các hồ. Mặc dù cả hai hồ đều nằm trong một khu vực khí hậu tương tự, trong 15 năm gần đây, xu hướng bất lợi trong sự dao động mức nước của hồ Urmia cho thấy tình trạng nghiêm trọng cho hồ này.\u003C\u002Fjats:p>","\u003Cjats:title>Abstract\u003C\u002Fjats:title>\n               \u003Cjats:p>In this paper, wavelet transform coherence is implemented to examine the impacts of hydroclimatological variables on water level fluctuations in two large saline lakes in the Middle East with a similar geographical location, namely, Urmia Lake in north-west Iran, which has an extremely simple ecological pyramid where water level decrease produces a very sensitive ecosystem, and Van Lake in north-east Turkey. The present study investigates trends in higher order moments of hydrological time series. The aim of this paper is to investigate the complexity of Urmia Lake water level time series which could lead to decrease fluctuations of time series. To this end, the strength and relationships between five hydroclimatological variables, including rainfall, runoff, temperature, relative humidity, as well as evaporation and water level fluctuations in the lakes were determined and discussed in terms of high common power region, phase relationships, and local multi-scale correlations. The results showed that among the hydroclimatological variables, runoff has the most coherencies (0.9–1) with water level fluctuations in the lakes. Although both lakes are located in a similar climatic region, for the recent 15 years, adverse trend in water level fluctuations of Urmia Lake indicates a critical condition for this lake.\u003C\u002Fjats:p>",{"VI":2486,"EN":2487},"Nghiên cứu tác động của các biến số thủy khí hậu lên mức nước hồ Urmia sử dụng chỉ số đồng nhất sóng","Investigating the effect of hydroclimatological variables on Urmia Lake water level using wavelet coherence measure",{"VOID":2489},"10.2166\u002Fwcc.2018.261",[158],[454],"https:\u002F\u002Fiwaponline.com\u002Fjwcc\u002Farticle\u002F10\u002F1\u002F13\u002F39081\u002FInvestigating-the-effect-of-hydroclimatological",[2494,2514,2542,2568],{"id":2495,"sortIndex":117,"researcher":24,"roles":2496,"affiliations":2497,"properties":2509},"433cbb1b-6614-4f36-beef-6e22c3c7bacf",[],[2498],{"id":2499,"sortIndex":25,"affiliation":2500,"properties":24},"7abb75dd-5ba7-4067-aa60-0f24511928dd",{"id":2501,"createTime":2502,"updateTime":2503,"relativeEntities":2504,"slug":2505,"properties":2506,"entityType":69,"verifyStatus":23,"verifyTime":24,"verifyNote":24,"syncStatus":23,"languages":24,"translateLanguages":24,"viewCount":25},"cd15e130-b60b-425f-882a-a1483c2fa959","2023-12-28T16:33:32.360+00:00","2024-10-02T04:26:48.379+00:00",[],"Department-of-Water-Resources-Engineering-Faculty-of-Civil-Engineering-University-of-Tabriz-Tabriz-Iran",{"title":2507},{"VI":2508},"Department of Water Resources Engineering, Faculty of Civil Engineering, University of Tabriz, Tabriz, Iran",{"openalex":2510,"title":2512},{"VOID":2511},"A5024555422",{"EN":2513},"Mahsa Ghasemzade",{"id":2515,"sortIndex":25,"researcher":24,"roles":2516,"affiliations":2517,"properties":2535},"f0f861c1-4810-40ee-94cf-b3d3448d73bb",[],[2518,2524],{"id":2519,"sortIndex":117,"affiliation":2520,"properties":24},"89144d85-5545-40e1-9c0c-c1fbc7632c26",{"id":2501,"createTime":2502,"updateTime":2503,"relativeEntities":2521,"slug":2505,"properties":2522,"entityType":69,"verifyStatus":23,"verifyTime":24,"verifyNote":24,"syncStatus":23,"languages":24,"translateLanguages":24,"viewCount":25},[],{"title":2523},{"VI":2508},{"id":2525,"sortIndex":25,"affiliation":2526,"properties":24},"4147bdec-e578-4be8-894f-0f57e7f81726",{"id":2527,"createTime":2528,"updateTime":2529,"relativeEntities":2530,"slug":2531,"properties":2532,"entityType":69,"verifyStatus":23,"verifyTime":24,"verifyNote":24,"syncStatus":23,"languages":24,"translateLanguages":24,"viewCount":25},"be48b29e-a87e-44b6-ac32-70f53255dd50","2023-11-24T08:52:52.473+00:00","2024-10-13T15:46:42.151+00:00",[],"Department-of-Civil-Engineering-Near-East-University-P-O-Box-99138-Nicosia-North-Cyprus-Mersin-10-Turkey",{"title":2533},{"VI":2534},"Department of Civil Engineering, Near East University, P.O. Box: 99138, Nicosia, North Cyprus, Mersin 10, Turkey",{"openalex":2536,"orcid":2538,"title":2540},{"VOID":2537},"A5089882448",{"VOID":2539},"https:\u002F\u002Forcid.org\u002F0000-0002-6931-7060",{"EN":2541},"Vahid Nourani",{"id":2543,"sortIndex":122,"researcher":24,"roles":2544,"affiliations":2545,"properties":2563},"ca8ba28e-20f5-464a-b4d0-ddd0fbad5f6d",[],[2546,2557],{"id":2547,"sortIndex":25,"affiliation":2548,"properties":24},"2ccd61d8-0d38-4d90-95e0-12f0907cf597",{"id":2549,"createTime":2550,"updateTime":2551,"relativeEntities":2552,"slug":2553,"properties":2554,"entityType":69,"verifyStatus":23,"verifyTime":24,"verifyNote":24,"syncStatus":23,"languages":24,"translateLanguages":24,"viewCount":25},"96f3ddc4-ca3d-4481-8012-4c7417496d45","2023-12-02T19:08:35.903+00:00","2024-10-02T04:26:48.390+00:00",[],"Department-of-Civil-Engineering-Antalya-Bilim-University-Antalya-Turkey",{"title":2555},{"VI":2556},"Department of Civil Engineering, Antalya Bilim University. 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Hydrol., 529, 1754, 10.1016\u002Fj.jhydrol.2015.08.011",{"doi":2772},"10.1016\u002Fj.jhydrol.2015.08.011",{"id":2774,"createTime":2775,"updateTime":2776,"relativeEntities":2777,"slug":2778,"properties":2779,"entityType":153,"verifyStatus":154,"verifyTime":2775,"verifyNote":156,"syncStatus":23,"languages":2793,"translateLanguages":2794,"viewCount":25,"primaryUrl":2795,"fullTextUrl":24,"authors":2796,"publicationType":280,"publisherRelationship":2879,"citationCount":2916,"citationInfo":2917,"publishDate":2919,"publishYear":2920,"citationAnalyzeStatus":23,"lastCitationAnalyze":24,"indexDatabases":24,"openAccess":24,"references":2921,"isForceReanalyzing":430},"96024606-b6a9-464d-9219-bb76016794c1","2024-12-25T08:51:45.649+00:00","2025-01-24T09:38:12.766+00:00",[],"An-updated-hydrological-review-on-recent-advancements-in-soil-conservation-service-curve-number-technique",{"mag":2780,"keywords":2782,"openalex":2783,"abstract":2785,"title":2788,"doi":2791},{"VOID":2781},"1976482574",{"VI":441},{"VOID":2784},"W1976482574",{"VI":2786,"EN":2787},"\u003Cjats:p>Mặc dù có nhiều mô hình thủy văn có sẵn để ước tính dòng chảy trực tiếp từ mưa bão, hầu hết các mô hình đều bị giới hạn do yêu cầu về dữ liệu đầu vào và hiệu chỉnh cao. Kỹ thuật Số Đường Cong Dịch Vụ Bảo Tồn Đất (SCS-CN) đã được áp dụng thành công trong toàn bộ lĩnh vực thủy văn và tài nguyên nước, mặc dù ban đầu nó không được thiết kế để giải quyết và xử lý một số vấn đề như xói mòn và lắng đọng cũng như kỹ thuật môi trường. Bài viết này bao gồm một đánh giá cập nhật về kỹ thuật phổ biến này với phân tích hiệu suất quan trọng của nó dưới các ứng dụng thủy văn khác nhau. Nghiên cứu nhấn mạnh nguồn gốc của nó và các nền tảng khái niệm cùng thực nghiệm, sau đó là sự quan trọng tương đối của tham số CN và các phương pháp ước tính khác nhau cũng như các vấn đề liên quan đến mối quan hệ Ia và S. Cuối cùng, những tiến bộ đáng chú ý gần đây có sẵn trong tài liệu được thảo luận về sức mạnh cấu trúc và tính khả thi của chúng trong các vấn đề thực tế.","\u003Cjats:p>Although many hydrologic models are available for the estimation of direct runoff from storm rainfall, most models are limited because of their intensive input data and calibration requirements. The Soil Conservation Service-Curve Number (SCS-CN) technique has been applied successfully throughout the entire spectrum of hydrology and water resources, even though originally it was not intended to deal with and solve certain issues such as erosion and sedimentation and environmental engineering. This manuscript includes an updated review of this popular technique with its critical performance analysis under various hydrological applications. The study highlights its provenance and its conceptual and empirical foundations followed by relative significance of the parameter CN and various estimation methods and issues related to the Ia and S relationship. Finally, notable recent advancements available in the literature are discussed for their structural strengths and applicability in real world problems.\u003C\u002Fjats:p>",{"VI":2789,"EN":2790},"Một bài tổng quan về những tiến bộ gần đây trong kỹ thuật số bảo tồn số đường cong","An updated hydrological review on recent advancements in soil conservation service-curve number technique",{"VOID":2792},"10.2166\u002Fwcc.2010.022",[158],[454],"https:\u002F\u002Fiwaponline.com\u002Fjwcc\u002Farticle\u002F1\u002F2\u002F118\u002F3398\u002FAn-updated-hydrological-review-on-recent",[2797,2819,2841,2858],{"id":2798,"sortIndex":120,"researcher":24,"roles":2799,"affiliations":2800,"properties":2812},"3723883d-3461-4e15-a260-a886bbc5c1f8",[],[2801],{"id":2802,"sortIndex":25,"affiliation":2803,"properties":24},"bbaf0b73-9a8e-4814-8142-2d420e4108d4",{"id":2804,"createTime":2805,"updateTime":2806,"relativeEntities":2807,"slug":2808,"properties":2809,"entityType":69,"verifyStatus":23,"verifyTime":24,"verifyNote":24,"syncStatus":23,"languages":24,"translateLanguages":24,"viewCount":25},"67befcba-e072-43c6-b09b-c74b0d4cca9c","2023-12-31T11:44:16.382+00:00","2024-12-25T08:51:45.675+00:00",[],"Department-of-Water-Resources-Development-and-Management-Indian-Institute-of-Technology-Roorkee-247667-Uttarakhand-India",{"title":2810},{"VI":2811},"Department of Water Resources Development and Management, Indian Institute of Technology, Roorkee 247667, Uttarakhand, India",{"openalex":2813,"orcid":2815,"title":2817},{"VOID":2814},"A5034901806",{"VOID":2816},"https:\u002F\u002Forcid.org\u002F0000-0002-4351-3178",{"EN":2818},"Shraddha Rawat",{"id":2820,"sortIndex":25,"researcher":24,"roles":2821,"affiliations":2822,"properties":2834},"0c4fe165-5bf6-4a2f-9940-02bde679f492",[],[2823],{"id":2824,"sortIndex":25,"affiliation":2825,"properties":24},"c9eae94b-c9b3-4f98-b29a-353e51a6548f",{"id":2826,"createTime":2827,"updateTime":2828,"relativeEntities":2829,"slug":2830,"properties":2831,"entityType":69,"verifyStatus":23,"verifyTime":24,"verifyNote":24,"syncStatus":23,"languages":24,"translateLanguages":24,"viewCount":25},"b5267f82-0aaf-40ad-b610-a17cafe2ae04","2024-04-16T21:02:38.207+00:00","2024-12-25T08:51:45.661+00:00",[],"Department-of-Soil-and-Water-Engineering-College-of-Agricultural-Engineering-and-Technology-Anand-Agricultural-University-Godhra-389001-Gujarat-India",{"title":2832},{"EN":2833},"Department of Soil and Water Engineering, College of Agricultural Engineering and Technology, Anand Agricultural University, Godhra, 389001, Gujarat, India",{"openalex":2835,"orcid":2837,"title":2839},{"VOID":2836},"A5028236116",{"VOID":2838},"https:\u002F\u002Forcid.org\u002F0000-0002-7277-115X",{"EN":2840},"Pushpendra Singh",{"id":2842,"sortIndex":122,"researcher":24,"roles":2843,"affiliations":2844,"properties":2851},"0244b003-a171-4497-b00d-5a70e892ab45",[],[2845],{"id":2846,"sortIndex":25,"affiliation":2847,"properties":24},"889674f6-73ad-4c04-8a6b-49ec05a43899",{"id":2804,"createTime":2805,"updateTime":2806,"relativeEntities":2848,"slug":2808,"properties":2849,"entityType":69,"verifyStatus":23,"verifyTime":24,"verifyNote":24,"syncStatus":23,"languages":24,"translateLanguages":24,"viewCount":25},[],{"title":2850},{"VI":2811},{"openalex":2852,"orcid":2854,"title":2856},{"VOID":2853},"A5056470743",{"VOID":2855},"https:\u002F\u002Forcid.org\u002F0000-0002-1986-1228",{"EN":2857},"S. 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