气候变化领域集成服务门户(CCPortal): Multi-model approach to quantify groundwater-level prediction uncertainty using an ensemble of global climate models and multiple abstraction scenarios

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DOI	10.5194/hess-23-2279-2019
	Multi-model approach to quantify groundwater-level prediction uncertainty using an ensemble of global climate models and multiple abstraction scenarios
	Mustafa S.M.T.; Moudud Hasan M.; Saha A.K.; Rannu R.P.; Van Uytven E.; Willems P.; Huysmans M.
发表日期	2019
ISSN	1027-5606
起始页码	2279
结束页码	2303
卷号	23 期号:5
英文摘要	Worldwide, groundwater resources are under a constant threat of overexploitation and pollution due to anthropogenic and climatic pressures. For sustainable management and policy making a reliable prediction of groundwater levels for different future scenarios is necessary. Uncertainties are present in these groundwater-level predictions and originate from greenhouse gas scenarios, climate models, conceptual hydro(geo)logical models (CHMs) and groundwater abstraction scenarios. The aim of this study is to quantify the individual uncertainty contributions using an ensemble of 2 greenhouse gas scenarios (representative concentration pathways 4.5 and 8.5), 22 global climate models, 15 alternative CHMs and 5 groundwater abstraction scenarios. This multi-model ensemble approach was applied to a drought-prone study area in Bangladesh. Findings of this study, firstly, point to the strong dependence of the groundwater levels on the CHMs considered. All groundwater abstraction scenarios showed a significant decrease in groundwater levels. If the current groundwater abstraction trend continues, the groundwater level is predicted to decline about 5 to 6 times faster for the future period 2026-2047 compared to the baseline period (1985-2006). Even with a 30% lower groundwater abstraction rate, the mean monthly groundwater level would decrease by up to 14m in the southwestern part of the study area. The groundwater abstraction in the northwestern part of Bangladesh has to decrease by 60% of the current abstraction to ensure sustainable use of groundwater. Finally, the difference in abstraction scenarios was identified as the dominant uncertainty source. CHM uncertainty contributed about 23% of total uncertainty. The alternative CHM uncertainty contribution is higher than the recharge scenario uncertainty contribution, including the greenhouse gas scenario and climate model uncertainty contributions. It is recommended that future groundwater-level prediction studies should use multi-model and multiple climate and abstraction scenarios. © 2019 Author(s).
语种	英语
scopus关键词	Abstracting; Forecasting; Greenhouse gases; Groundwater; Groundwater pollution; Groundwater resources; Uncertainty analysis; Global climate model; Groundwater abstraction; Individual uncertainties; Model uncertainties; Multi-model ensemble; Prediction uncertainty; Sustainable management; Uncertainty contributions; Climate models; climate modeling; exploitation; global climate; greenhouse gas; groundwater abstraction; groundwater resource; policy making; prediction; uncertainty analysis; water level; Bangladesh
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/159685
作者单位	Mustafa, S.M.T., Department of Hydrology and Hydraulic Engineering, Vrije Universiteit Brussel (VUB), Pleinlaan 2, Brussels, 1050, Belgium; Moudud Hasan, M., Department of Hydrology and Hydraulic Engineering, Vrije Universiteit Brussel (VUB), Pleinlaan 2, Brussels, 1050, Belgium; Saha, A.K., Department of Hydrology and Hydraulic Engineering, Vrije Universiteit Brussel (VUB), Pleinlaan 2, Brussels, 1050, Belgium; Rannu, R.P., Department of Hydrology and Hydraulic Engineering, Vrije Universiteit Brussel (VUB), Pleinlaan 2, Brussels, 1050, Belgium; Van Uytven, E., Department of Civil Engineering-Hydraulics Section, KU Leuven, Box-2448, Kasteelpark 40, Leuven, 3001, Belgium; Willems, P., Department of Hydrology and Hydraulic Engineering, Vrije Universiteit Brussel (VUB), Pleinlaan 2, Brussels, 1050, Belgium, Department of Civil Engineering-Hydraulics Section, KU Leuven, Box-2448, Kasteelpark 40, Leuven, 3001, Belgium; Huysmans, M., Department of Hydrology and Hydraulic Engineering, Vrije Universiteit Brussel ...
推荐引用方式 GB/T 7714	Mustafa S.M.T.,Moudud Hasan M.,Saha A.K.,et al. Multi-model approach to quantify groundwater-level prediction uncertainty using an ensemble of global climate models and multiple abstraction scenarios[J],2019,23(5).
APA	Mustafa S.M.T..,Moudud Hasan M..,Saha A.K..,Rannu R.P..,Van Uytven E..,...&Huysmans M..(2019).Multi-model approach to quantify groundwater-level prediction uncertainty using an ensemble of global climate models and multiple abstraction scenarios.Hydrology and Earth System Sciences,23(5).
MLA	Mustafa S.M.T.,et al."Multi-model approach to quantify groundwater-level prediction uncertainty using an ensemble of global climate models and multiple abstraction scenarios".Hydrology and Earth System Sciences 23.5(2019).