Analysis of the Influence of Rainfall Spatial Uncertainty on Hydrological Simulations Using the Bootstrap Method
1
State Key Laboratory of Hydroscience and Engineering, Tsinghua University, Beijing 100084, China
2
State Key Laboratory of Plateau Ecology and Agriculture, Qinghai University, Xining 810016, China
3
Sanjiangyuan Collaborative Innovation Center, Qinghai University, Xining 810016, China
4
Department of Civil Engineering, The University of Hong Kong, Hong Kong, China
*
Authors to whom correspondence should be addressed.
Atmosphere 2018, 9(2), 71; https://doi.org/10.3390/atmos9020071
Received: 18 January 2018 / Revised: 9 February 2018 / Accepted: 10 February 2018 / Published: 15 February 2018
(This article belongs to the Special Issue Integration of Advanced Soft Computing Techniques in Hydrological Predictions)
Rainfall stations of a certain number and spatial distribution supply sampling records of rainfall processes in a river basin. Uncertainty may be introduced when the station records are spatially interpolated for the purpose of hydrological simulations. This study adopts a bootstrap method to quantitatively estimate the uncertainty of areal rainfall estimates and its effects on hydrological simulations. The observed rainfall records are first analyzed using clustering and correlation methods and possible average basin rainfall amounts are calculated with a bootstrap method using various combinations of rainfall station subsets. Then, the uncertainty of simulated runoff, which is propagated through a hydrological model from the spatial uncertainty of rainfall estimates, is analyzed with the bootstrapped rainfall inputs. By comparing the uncertainties of rainfall and runoff, the responses of the hydrological simulation to the rainfall spatial uncertainty are discussed. Analyses are primarily performed for three rainfall events in the upstream of the Qingjian River basin, a sub-basin of the middle Yellow River; moreover, one rainfall event in the Longxi River basin is selected for the analysis of the areal representation of rainfall stations. Using the Digital Yellow River Integrated Model, the results show that the uncertainty of rainfall estimates derived from rainfall station network has a direct influence on model simulation, which can be conducive to better understand of rainfall spatial characteristic. The proposed method can be a guide to quantify an approximate range of simulated error caused by the spatial uncertainty of rainfall input and the quantified relationship between rainfall input and simulation performance can provide useful information about rainfall station network management in river basins.
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Keywords:
bootstrap method; hydrological simulation; rainfall spatial uncertainty; runoff simulation uncertainty; Digital Yellow River Integrated Model
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MDPI and ACS Style
Zhang, A.; Shi, H.; Li, T.; Fu, X. Analysis of the Influence of Rainfall Spatial Uncertainty on Hydrological Simulations Using the Bootstrap Method. Atmosphere 2018, 9, 71. https://doi.org/10.3390/atmos9020071
AMA Style
Zhang A, Shi H, Li T, Fu X. Analysis of the Influence of Rainfall Spatial Uncertainty on Hydrological Simulations Using the Bootstrap Method. Atmosphere. 2018; 9(2):71. https://doi.org/10.3390/atmos9020071
Chicago/Turabian StyleZhang, Ang; Shi, Haiyun; Li, Tiejian; Fu, Xudong. 2018. "Analysis of the Influence of Rainfall Spatial Uncertainty on Hydrological Simulations Using the Bootstrap Method" Atmosphere 9, no. 2: 71. https://doi.org/10.3390/atmos9020071
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