Uncertainty of annual runoff projections in Lithuanian rivers under a future climate

被引:10
作者
Akstinas, V. [1 ]
Jakimavicius, D. [1 ]
Meilutyte-Lukauskiene, D. [1 ]
Kriauciuniene, J. [1 ]
Sarauskiene, D. [1 ]
机构
[1] Lithuanian Energy Inst, Breslaujos Str 3, LT-44403 Kaunas, Lithuania
来源
HYDROLOGY RESEARCH | 2020年 / 51卷 / 02期
关键词
climate change; GCM; RCP; statistical downscaling; uncertainty analysis; BIAS CORRECTION; CHANGE IMPACTS; PRECIPITATION; SIMULATIONS; CALIBRATION; MODELS;
D O I
10.2166/nh.2019.004
中图分类号
TV21 [水资源调查与水利规划];
学科分类号
081501 ;
摘要
Uncertainties of runoff projections arise from different sources of origin, such as climate scenarios (RCPs), global climate models (GCMs) and statistical downscaling (SD) methods. Assessment of uncertainties related to the mentioned sources was carried out for selected rivers of Lithuania (Minija, Nevezis and Sventoji). These rivers reflect conditions of different hydrological regions (western, central and southeastern). Using HBV software, hydrological models were created for river runoff projections in the near (2021-2040) and far (2081-2100) future. The runoff projections according to three RCP scenarios, three GCMs and three SD methods were created. In the Western hydrological region represented by the Minija River, the GCMs were the most dominant uncertainty source (41.0-44.5%) in the runoff projections. Meanwhile, uncertainties of runoff projections from central (Nevezis River) and southeastern (Sventoji River) regions of Lithuania were related to SD methods and the range of uncertainties fluctuates from 39.4% to 60.9%. In western Lithuania, the main source of rivers' supply is precipitation, where projections highly depend on selected GCMs. The rivers from central and southeastern regions are more sensitive to the SD methods, which not always precisely adjust the meteorological variables from a large grid cell of GCM into catchment scale.
引用
收藏
页码:257 / 271
页数:15
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