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Rainfall Spatial Estimations: A Review from Spatial Interpolation to Multi-Source Data Merging
Hu, Qingfang1; Li, Zhe2,3; Wang, Leizhi1; Huang, Yong1; Wang, Yintang1; Li, Lingjie1
2019-03-20
Source PublicationWATER
ISSN2073-4441
Volume11Issue:3Pages:30
Corresponding AuthorHu, Qingfang(huqf@nhri.com)
AbstractRainfall is one of the most basic meteorological and hydrological elements. Quantitative rainfall estimation has always been a common concern in many fields of research and practice, such as meteorology, hydrology, and environment, as well as being one of the most important research hotspots in various fields nowadays. Due to the development of space observation technology and statistics, progress has been made in rainfall quantitative spatial estimation, which has continuously deepened our understanding of the water cycle across different space-time scales. In light of the information sources used in rainfall spatial estimation, this paper summarized the research progress in traditional spatial interpolation, remote sensing retrieval, atmospheric reanalysis rainfall, and multi-source rainfall merging since 2000. However, because of the extremely complex spatiotemporal variability and physical mechanism of rainfall, it is still quite challenging to obtain rainfall spatial distribution with high quality and resolution. Therefore, we present existing problems that require further exploration, including the improvement of interpolation and merging methods, the comprehensive evaluation of remote sensing, and the reanalysis of rainfall data and in-depth application of non-gauge based rainfall data.
Keywordrainfall spatial interpolation radar satellite atmospheric reanalysis rainfall merging
DOI10.3390/w11030579
WOS KeywordMULTISATELLITE PRECIPITATION PRODUCTS ; SATELLITE PRECIPITATION ; HIGH-RESOLUTION ; CLIMATE DATA ; ERA-INTERIM ; INCORPORATING ELEVATION ; WEIGHTED REGRESSION ; HYDROLOGICAL MODEL ; BAYESIAN-ANALYSIS ; GLOBAL RAINFALL
Indexed BySCI
Language英语
Funding ProjectNational Key Research and Development Program of China[2016YFC0400902] ; National Key Research and Development Program of China[2016YFC0400910] ; National Natural Science Foundation of China[51479118] ; Consulting and Research Program of the Chinese Academy of Engineering[2015-ZD-07-02] ; Public Welfare Industry Scientific Research Special Fund of the Ministry of Water Resources[201501014]
Funding OrganizationNational Key Research and Development Program of China ; National Natural Science Foundation of China ; Consulting and Research Program of the Chinese Academy of Engineering ; Public Welfare Industry Scientific Research Special Fund of the Ministry of Water Resources
WOS Research AreaWater Resources
WOS SubjectWater Resources
WOS IDWOS:000464546700006
PublisherMDPI
Citation statistics
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/48193
Collection中国科学院地理科学与资源研究所
Corresponding AuthorHu, Qingfang
Affiliation1.Nanjing Hydraul Res Inst, State Key Lab Hydrol Water Resources & Hydraul En, Nanjing 210029, Jiangsu, Peoples R China
2.Chinese Acad Sci, Inst Geog Sci & Resources, Key Lab Terr Water Cycle & Surface Proc, Beijing 100101, Peoples R China
3.Univ Wisconsin, Dept Civil & Environm Engn, Madison, WI 53706 USA
4.Anhui Inst Meteorol Sci, Anhui Prov Key Lab Atmospher Sci & Satellite Remo, Hefei 230031, Anhui, Peoples R China
Recommended Citation
GB/T 7714
Hu, Qingfang,Li, Zhe,Wang, Leizhi,et al. Rainfall Spatial Estimations: A Review from Spatial Interpolation to Multi-Source Data Merging[J]. WATER,2019,11(3):30.
APA Hu, Qingfang,Li, Zhe,Wang, Leizhi,Huang, Yong,Wang, Yintang,&Li, Lingjie.(2019).Rainfall Spatial Estimations: A Review from Spatial Interpolation to Multi-Source Data Merging.WATER,11(3),30.
MLA Hu, Qingfang,et al."Rainfall Spatial Estimations: A Review from Spatial Interpolation to Multi-Source Data Merging".WATER 11.3(2019):30.
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