Predictions in ungauged basins (PUB) are widely considered to be one of the fundamentally challenging research topics in the hydrological sciences. This paper couples a regional parameter transfer module with a probabilistic prediction module in order to obtain probabilistic PUB. Steps in the proposed probabilistic PUB include: (1) variable infiltration capacity-three layers (VIC-3L) model description; (2) three regional parameter transfer schemes for ungauged basins, i.e., regression analysis, spatial proximity, and physical similarity; (3) probabilistic PUB using Bayesian model averaging (BMA); and (4) performance evaluation for probabilistic PUB. The study is performed on 12 sub-basins in the Hanjiang River basin, China. The results demonstrate that the mean prediction of BMA is much closer to the observed data compared with its associated individual parameter transfer scheme (physical similarity approach), and the probabilistic predictions of BMA can effectively reduce the uncertainty in runoff PUB better than any associated individual parameter transfer schemes for two ungauged sub-basins.
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Research Article|January 05 2016
Probabilistic prediction in ungauged basins (PUB) based on regional parameter estimation and Bayesian model averaging
Yanlai Zhou
Yanlai Zhou
1Changjiang River Scientific Research Institute, Wuhan 430010, China2State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China
E-mail: zyl23bulls@whu.edu.cn
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Shenglian Guo
Shenglian Guo
2State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China
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Chong-Yu Xu
Chong-Yu Xu
2State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China3Department of Geosciences, University of Oslo, N-0316 Oslo, Norway
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Hua Chen
Hua Chen
2State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China
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Jiali Guo
Jiali Guo
4Three Gorges University, Yichang 443002, China
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Kairong Lin
Kairong Lin
5School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, China
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Hydrology Research (2016) 47 (6): 1087-1103.
Article history
Received:
March 28 2015
Accepted:
November 20 2015
Citation
Yanlai Zhou, Shenglian Guo, Chong-Yu Xu, Hua Chen, Jiali Guo, Kairong Lin; Probabilistic prediction in ungauged basins (PUB) based on regional parameter estimation and Bayesian model averaging. Hydrology Research 1 December 2016; 47 (6): 1087–1103. doi: https://doi.org/10.2166/nh.2016.058
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