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DOI10.1007/s00704-017-2359-3
Quantifying the sources of uncertainty in an ensemble of hydrological climate-impact projections
Aryal, Anil; Shrestha, Sangam; Babel, Mukand S.
发表日期2019
ISSN0177-798X
EISSN1434-4483
卷号135期号:1-2页码:193-209
英文摘要

The objective of this paper is to quantify the various sources of uncertainty in the assessment of climate change impact on hydrology in the Tamakoshi River Basin, located in the north-eastern part of Nepal. Multiple climate and hydrological models were used to simulate future climate conditions and discharge in the basin. The simulated results of future climate and river discharge were analysed for the quantification of sources of uncertainty using two-way and three-way ANOVA. The results showed that temperature and precipitation in the study area are projected to change in near- (2010-2039), mid- (2040-2069) and far-future (2070-2099) periods. Maximum temperature is likely to rise by 1.75 degrees C under Representative Concentration Pathway (RCP) 4.5 and by 3.52 degrees C under RCP 8.5. Similarly, the minimum temperature is expected to rise by 2.10 degrees C under RCP 4.5 and by 3.73 degrees C under RCP 8.5 by the end of the twenty-first century. Similarly, the precipitation in the study area is expected to change by -2.15% under RCP 4.5 and -2.44% under RCP 8.5 scenarios. The future discharge in the study area was projected using two hydrological models, viz. Soil and Water Assessment Tool (SWAT) and Hydrologic Engineering Center's Hydrologic Modelling System (HEC-HMS). The SWAT model projected discharge is expected to change by small amount, whereas HEC-HMS model projected considerably lower discharge in future compared to the baseline period. The results also show that future climate variables and river hydrology contain uncertainty due to the choice of climate models, RCP scenarios, bias correction methods and hydrological models. During wet days, more uncertainty is observed due to the use of different climate models, whereas during dry days, the use of different hydrological models has a greater effect on uncertainty. Inter-comparison of the impacts of different climate models reveals that the REMO climate model shows higher uncertainty in the prediction of precipitation and, consequently, in the prediction of future discharge and maximum probable flood.


WOS研究方向Meteorology & Atmospheric Sciences
来源期刊THEORETICAL AND APPLIED CLIMATOLOGY
文献类型期刊论文
条目标识符http://gcip.llas.ac.cn/handle/2XKMVOVA/90188
作者单位Asian Inst Technol, Sch Engn & Technol, Water Engn & Management, POB 4, Klongluang 12120, Pathum Thani, Thailand
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Aryal, Anil,Shrestha, Sangam,Babel, Mukand S.. Quantifying the sources of uncertainty in an ensemble of hydrological climate-impact projections[J],2019,135(1-2):193-209.
APA Aryal, Anil,Shrestha, Sangam,&Babel, Mukand S..(2019).Quantifying the sources of uncertainty in an ensemble of hydrological climate-impact projections.THEORETICAL AND APPLIED CLIMATOLOGY,135(1-2),193-209.
MLA Aryal, Anil,et al."Quantifying the sources of uncertainty in an ensemble of hydrological climate-impact projections".THEORETICAL AND APPLIED CLIMATOLOGY 135.1-2(2019):193-209.
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