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Estimation of instantaneous peak flow from maximum mean daily flow by regionalization of catchment model parameters
Ding, J (Ding, Jie)1,2; Haberlandt, U (Haberlandt, Uwe)2; Ding, J
Source PublicationHYDROLOGICAL PROCESSES
2017
Volume31Issue:3Pages:612-626
DOI10.1002/hyp.11053
AbstractRegionalization methods have been effectively used in many hydrological studies, such as regional flood frequency analysis and low flows. However, there is no study to estimate the instantaneous peak flow (IPF) from maximum mean daily flow (MDF) using hydrological models with regionalized parameters. In this paper, the semidistributed conceptual hydrological model Hydrologiska Byrans Vattenbalansavdelning is operated on a daily time step for 18 catchments in the Aller-Leine basin, Germany. The model is calibrated on four different flow statistics, including winter/summer extremes distribution and flow duration curves. The model parameter values are predefined with the associated catchment descriptors by a transfer function. Two different regionalization schemes are investigated: one is carried out for all the catchments in the study area; the other one is only performed for several catchments within a cluster. The k-means algorithm is used to 12 different catchment characteristics from all 18 catchments as the partitional clustering algorithm. Subsequently, the general extreme value distributions are fitted to the modeled MDFs, which are then transferred into IPF quantiles using a multiple regression model. The results show that (a) the uncertainty resulted from model parameter regionalization for the estimation of IPFs is much smaller than the error when using MDFs instead of IPFs; (b) the hydrological responses of the clustered catchments located in the flat areas are, in general, not as homogeneous as the ones in high elevated regions; and (c) the model with the parameters derived from the same regionalization coefficients within a cluster performs better using the corresponding parameters estimated through all the catchments.
Subject Area自然地理学
WOS IDWOS:000393558900009
Language英语
Indexed BySCI
KeywordHYDROLOGICAL MODEL FREQUENCY-ANALYSIS UNGAUGED CATCHMENTS WATERSHED MODEL RIVER-BASIN RUNOFF PREDICTIONS CALIBRATION RAINFALL UNCERTAINTY
WOS Research AreaWater Resources
WOS SubjectWater Resources ; Water Resources ; Water Resources
Cooperation Status国际
Citation statistics
Cited Times:4[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.itpcas.ac.cn/handle/131C11/8398
Collection图书馆
Corresponding AuthorDing, J
Affiliation1.Chinese Acad Sci, Inst Tibetan Plateau Res, Key Lab Tibetan Plateau Environm Changes & Land S, Beijing, Peoples R China.
2.Leibniz Univ Hannover, Inst Water Resources Management Hydrol & Agr Hydr, Hannover, Germany.
Recommended Citation
GB/T 7714
Ding, J ,Haberlandt, U ,Ding, J. Estimation of instantaneous peak flow from maximum mean daily flow by regionalization of catchment model parameters[J]. HYDROLOGICAL PROCESSES,2017,31(3):612-626.
APA Ding, J ,Haberlandt, U ,&Ding, J.(2017).Estimation of instantaneous peak flow from maximum mean daily flow by regionalization of catchment model parameters.HYDROLOGICAL PROCESSES,31(3),612-626.
MLA Ding, J ,et al."Estimation of instantaneous peak flow from maximum mean daily flow by regionalization of catchment model parameters".HYDROLOGICAL PROCESSES 31.3(2017):612-626.
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