Climate models and hydrological parameter uncertainties in climate change impacts on monthly runoff and daily flow duration curve of a Mediterranean catchment

被引:24
作者
Sellami, Haykel [1 ]
Benabdallah, Sihem [2 ]
La Jeunesse, Isabelle [3 ,4 ]
Vanclooster, Marnik [1 ]
机构
[1] Catholic Univ Louvain, Earth & Life Inst, Louvain, Belgium
[2] Ctr Rech & Technol Eaux, Technopole Borj Cedria, Soliman, Tunisia
[3] Univ Tours, UMR CITERES 6173, Tours, France
[4] Univ Angers, Fac Sci, LETG Angers LEESA UMR CNRS 6554, Angers, France
关键词
model parameter; SWAT; climate models; uncertainty; climate change impacts; artificial neural network; ARTIFICIAL NEURAL-NETWORK; SWAT MODEL; WATER-RESOURCES; GLUE; EQUIFINALITY; PROJECTIONS; SCENARIOS; ENSEMBLE; FUTURE;
D O I
10.1080/02626667.2015.1040801
中图分类号
TV21 [水资源调查与水利规划];
学科分类号
081501 ;
摘要
Climate models and hydrological parameter uncertainties were quantified and compared while assessing climate change impacts on monthly runoff and daily flow duration curve (FDC) in a Mediterranean catchment. Simulations of the Soil and Water Assessment Tool (SWAT) model using an ensemble of behavioural parameter sets derived from the Generalized Likelihood Uncertainty Estimation (GLUE) method were approximated by feed-forward artificial neural networks (FF-NN). Then, outputs of climate models were used as inputs to the FF-NN models. Subsequently, projected changes in runoff and FDC were calculated and their associated uncertainty was partitioned into climate model and hydrological parameter uncertainties. Runoff and daily discharge of the Chiba catchment were expected to decrease in response to drier and warmer climatic conditions in the 2050s. For both hydrological indicators, uncertainty magnitude increased when moving from dry to wet periods. The decomposition of uncertainty demonstrated that climate model uncertainty dominated hydrological parameter uncertainty in wet periods, whereas in dry periods hydrological parametric uncertainty became more important.
引用
收藏
页码:1415 / 1429
页数:15
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