气候变化领域集成服务门户(CCPortal): Monthly streamflow forecasting at varying spatial scales in the Rhine basin

CCPortal

DOI	10.5194/hess-22-929-2018
	Monthly streamflow forecasting at varying spatial scales in the Rhine basin
	Schick S.; Rössler O.; Weingartner R.
发表日期	2018
ISSN	1027-5606
起始页码	929
结束页码	942
卷号	22 期号:2
英文摘要	Model output statistics (MOS) methods can be used to empirically relate an environmental variable of interest to predictions from earth system models (ESMs). This variable often belongs to a spatial scale not resolved by the ESM. Here, using the linear model fitted by least squares, we regress monthly mean streamflow of the Rhine River at Lobith and Basel against seasonal predictions of precipitation, surface air temperature, and runoff from the European Centre for Medium-Range Weather Forecasts. To address potential effects of a scale mismatch between the ESM's horizontal grid resolution and the hydrological application, the MOS method is further tested with an experiment conducted at the subcatchment scale. This experiment applies the MOS method to 133 additional gauging stations located within the Rhine basin and combines the forecasts from the subcatchments to predict streamflow at Lobith and Basel. In doing so, the MOS method is tested for catchments areas covering 4 orders of magnitude. Using data from the period 1981-2011, the results show that skill, with respect to climatology, is restricted on average to the first month ahead. This result holds for both the predictor combination that mimics the initial conditions and the predictor combinations that additionally include the dynamical seasonal predictions. The latter, however, reduce the mean absolute error of the former in the range of 5 to 12 g, which is consistently reproduced at the subcatchment scale. An additional experiment conducted for 5-day mean streamflow indicates that the dynamical predictions help to reduce uncertainties up to about 20 days ahead, but it also reveals some shortcomings of the present MOS method.
语种	英语
scopus关键词	Catchments; Climatology; Forecasting; Stream flow; Additional experiments; Dynamical predictions; Environmental variables; European centre for medium-range weather forecasts; Model output statistics; Orders of magnitude; Streamflow forecasting; Surface air temperatures; Weather forecasting; catchment; climate modeling; numerical method; precipitation (climatology); river basin; runoff; streamflow; uncertainty analysis; Basel; Basel-Stadt; Gelderland; Lobith; Netherlands; Rhine River; Switzerland
来源期刊	Hydrology and Earth System Sciences
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/160171
作者单位	Schick, S., Institute of Geography, University of Bern, Bern, Switzerland, Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland; Rössler, O., Institute of Geography, University of Bern, Bern, Switzerland, Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland; Weingartner, R., Institute of Geography, University of Bern, Bern, Switzerland, Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland
推荐引用方式 GB/T 7714	Schick S.,Rössler O.,Weingartner R.. Monthly streamflow forecasting at varying spatial scales in the Rhine basin[J],2018,22(2).
APA	Schick S.,Rössler O.,&Weingartner R..(2018).Monthly streamflow forecasting at varying spatial scales in the Rhine basin.Hydrology and Earth System Sciences,22(2).
MLA	Schick S.,et al."Monthly streamflow forecasting at varying spatial scales in the Rhine basin".Hydrology and Earth System Sciences 22.2(2018).