Predicting Surface Runoff from Catchment to Large Region
Predicting surface runoff from catchment to large region is a fundamental and challenging task in hydrology. This paper presents a comprehensive review for various studies conducted for improving runoff predictions from catchment to large region in the last several decades. This review summarizes th...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Wiley
2015-01-01
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| Series: | Advances in Meteorology |
| Online Access: | http://dx.doi.org/10.1155/2015/720967 |
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| _version_ | 1832565080325095424 |
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| author | Hongxia Li Yongqiang Zhang Xinyao Zhou |
| author_facet | Hongxia Li Yongqiang Zhang Xinyao Zhou |
| author_sort | Hongxia Li |
| collection | DOAJ |
| description | Predicting surface runoff from catchment to large region is a fundamental and challenging task in hydrology. This paper presents a comprehensive review for various studies conducted for improving runoff predictions from catchment to large region in the last several decades. This review summarizes the well-established methods and discusses some promising approaches from the following four research fields: (1) modeling catchment, regional and global runoff using lumped conceptual rainfall-runoff models, distributed hydrological models, and land surface models, (2) parameterizing hydrological models in ungauged catchments, (3) improving hydrological model structure, and (4) using new remote sensing precipitation data. |
| format | Article |
| id | doaj-art-2788417209f94c8bb23ebbe8b2bf795e |
| institution | Kabale University |
| issn | 1687-9309 1687-9317 |
| language | English |
| publishDate | 2015-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Meteorology |
| spelling | doaj-art-2788417209f94c8bb23ebbe8b2bf795e2025-02-03T01:09:23ZengWileyAdvances in Meteorology1687-93091687-93172015-01-01201510.1155/2015/720967720967Predicting Surface Runoff from Catchment to Large RegionHongxia Li0Yongqiang Zhang1Xinyao Zhou2State Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University, Chengdu 610065, ChinaCSIRO Land Water Flagship, Clunies Ross Street, Acton, Canberra, ACT 2601, AustraliaKey Laboratory of Agricultural Water Resources, Center for Agricultural Resources Research, Chinese Academy of Sciences, Shijiazhuang 050021, ChinaPredicting surface runoff from catchment to large region is a fundamental and challenging task in hydrology. This paper presents a comprehensive review for various studies conducted for improving runoff predictions from catchment to large region in the last several decades. This review summarizes the well-established methods and discusses some promising approaches from the following four research fields: (1) modeling catchment, regional and global runoff using lumped conceptual rainfall-runoff models, distributed hydrological models, and land surface models, (2) parameterizing hydrological models in ungauged catchments, (3) improving hydrological model structure, and (4) using new remote sensing precipitation data.http://dx.doi.org/10.1155/2015/720967 |
| spellingShingle | Hongxia Li Yongqiang Zhang Xinyao Zhou Predicting Surface Runoff from Catchment to Large Region Advances in Meteorology |
| title | Predicting Surface Runoff from Catchment to Large Region |
| title_full | Predicting Surface Runoff from Catchment to Large Region |
| title_fullStr | Predicting Surface Runoff from Catchment to Large Region |
| title_full_unstemmed | Predicting Surface Runoff from Catchment to Large Region |
| title_short | Predicting Surface Runoff from Catchment to Large Region |
| title_sort | predicting surface runoff from catchment to large region |
| url | http://dx.doi.org/10.1155/2015/720967 |
| work_keys_str_mv | AT hongxiali predictingsurfacerunofffromcatchmenttolargeregion AT yongqiangzhang predictingsurfacerunofffromcatchmenttolargeregion AT xinyaozhou predictingsurfacerunofffromcatchmenttolargeregion |