Predicting Surface Runoff from Catchment to Large Region
This article is part of Special Issue:
Hongxia Li,
Yongqiang Zhang,
Xinyao Zhou,
Hongxia Li
State Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University, Chengdu 610065, China scu.edu.cn
Search for more papers by this authorCorresponding Author
Yongqiang Zhang
CSIRO Land Water Flagship, Clunies Ross Street, Acton, Canberra, ACT 2601, Australia csiro.au
Search for more papers by this authorXinyao Zhou
Key Laboratory of Agricultural Water Resources, Center for Agricultural Resources Research, Chinese Academy of Sciences, Shijiazhuang 050021, China cas.cn
Search for more papers by this authorHongxia Li,
Yongqiang Zhang,
Xinyao Zhou,
Hongxia Li
State Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University, Chengdu 610065, China scu.edu.cn
Search for more papers by this authorCorresponding Author
Yongqiang Zhang
CSIRO Land Water Flagship, Clunies Ross Street, Acton, Canberra, ACT 2601, Australia csiro.au
Search for more papers by this authorXinyao Zhou
Key Laboratory of Agricultural Water Resources, Center for Agricultural Resources Research, Chinese Academy of Sciences, Shijiazhuang 050021, China cas.cn
Search for more papers by this authorAcademic Editor: Enrico Ferrero
Abstract
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.
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