DOI: 10.5194/hess-20-1031-2016
Scopus记录号: 2-s2.0-84960444107
论文题名: Sensitivity analysis of runoff modeling to statistical downscaling models in the western Mediterranean
作者: Grouillet B ; , Ruelland D ; , Ayar P ; V ; , Vrac M
刊名: Hydrology and Earth System Sciences
ISSN: 10275606
出版年: 2016
卷: 20, 期: 3 起始页码: 1031
结束页码: 1047
语种: 英语
Scopus关键词: Climate change
; Distribution functions
; Hydrology
; Runoff
; Sensitivity analysis
; Stochastic models
; Stochastic systems
; Stream flow
; Climate change impact
; Cumulative distribution function
; General circulation model
; Hydrological indicators
; Hydrological modeling
; Statistical downscaling
; Stochastic weather generator
; Western Mediterranean basin
; Climate models
; climate forcing
; climate modeling
; downscaling
; general circulation model
; hydrograph
; hydrological modeling
; precipitation (climatology)
; runoff
; seasonal variation
; sensitivity analysis
; streamflow
; Mediterranean Region
英文摘要: This paper analyzes the sensitivity of a hydrological model to different methods to statistically downscale climate precipitation and temperature over four western Mediterranean basins illustrative of different hydro-meteorological situations. The comparison was conducted over a common 20-year period (1986-2005) to capture different climatic conditions in the basins. The daily GR4j conceptual model was used to simulate streamflow that was eventually evaluated at a 10-day time step. Cross-validation showed that this model is able to correctly reproduce runoff in both dry and wet years when high-resolution observed climate forcings are used as inputs. These simulations can thus be used as a benchmark to test the ability of different statistically downscaled data sets to reproduce various aspects of the hydrograph. Three different statistical downscaling models were tested: an analog method (ANALOG), a stochastic weather generator (SWG) and the cumulative distribution function-transform approach (CDFt). We used the models to downscale precipitation and temperature data from NCEP/NCAR reanalyses as well as outputs from two general circulation models (GCMs) (CNRM-CM5 and IPSL-CM5A-MR) over the reference period. We then analyzed the sensitivity of the hydrological model to the various downscaled data via five hydrological indicators representing the main features of the hydrograph. Our results confirm that using high-resolution downscaled climate values leads to a major improvement in runoff simulations in comparison to the use of low-resolution raw inputs from reanalyses or climate models. The results also demonstrate that the ANALOG and CDFt methods generally perform much better than SWG in reproducing mean seasonal streamflow, interannual runoff volumes as well as low/high flow distribution. More generally, our approach provides a guideline to help choose the appropriate statistical downscaling models to be used in climate change impact studies to minimize the range of uncertainty associated with such downscaling methods. © 2016 Author(s). Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/78895
Appears in Collections: 气候变化事实与影响
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作者单位: CNRS, Laboratoire HydroSciences, Place Eugene Bataillon, Montpellier, France; LSCE, Laboratoire des Sciences du Climat et de l'Environnement, UMR CEA-CNRS-UVSQ 1572, CE Saclay l'Orme des Merisiers, Gif-sur-Yvette, France
Recommended Citation:
Grouillet B,, Ruelland D,, Ayar P,et al. Sensitivity analysis of runoff modeling to statistical downscaling models in the western Mediterranean[J]. Hydrology and Earth System Sciences,2016-01-01,20(3)