Articles | Volume 23, issue 5
https://doi.org/10.5194/hess-23-2279-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-23-2279-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Multi-model approach to quantify groundwater-level prediction uncertainty using an ensemble of global climate models and multiple abstraction scenarios
Syed M. Touhidul Mustafa
CORRESPONDING AUTHOR
Department of Hydrology and Hydraulic Engineering, Vrije Universiteit Brussel (VUB), Pleinlaan 2, 1050 Brussels, Belgium
M. Moudud Hasan
Department of Hydrology and Hydraulic Engineering, Vrije Universiteit Brussel (VUB), Pleinlaan 2, 1050 Brussels, Belgium
Ajoy Kumar Saha
Department of Hydrology and Hydraulic Engineering, Vrije Universiteit Brussel (VUB), Pleinlaan 2, 1050 Brussels, Belgium
Rahena Parvin Rannu
Department of Hydrology and Hydraulic Engineering, Vrije Universiteit Brussel (VUB), Pleinlaan 2, 1050 Brussels, Belgium
Els Van Uytven
Department of Civil Engineering – Hydraulics Section, KU Leuven, Kasteelpark 40 box 2448, 3001 Leuven, Belgium
Patrick Willems
Department of Hydrology and Hydraulic Engineering, Vrije Universiteit Brussel (VUB), Pleinlaan 2, 1050 Brussels, Belgium
Department of Civil Engineering – Hydraulics Section, KU Leuven, Kasteelpark 40 box 2448, 3001 Leuven, Belgium
Marijke Huysmans
Department of Hydrology and Hydraulic Engineering, Vrije Universiteit Brussel (VUB), Pleinlaan 2, 1050 Brussels, Belgium
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34 citations as recorded by crossref.
- The impact of irrigation return flow on seasonal groundwater recharge in northwestern Bangladesh S. Tulip et al. 10.1016/j.agwat.2022.107593
- Quantification of climate change sensitivity of shallow and deep groundwater in Denmark I. Seidenfaden et al. 10.1016/j.ejrh.2022.101100
- The impact of land use and land cover change on groundwater recharge in northwestern Bangladesh M. Siddik et al. 10.1016/j.jenvman.2022.115130
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- A critical review on groundwater level depletion monitoring based on GIS and data-driven models: Global perspectives and future challenges M. Monir et al. 10.1016/j.hydres.2024.05.001
- Development and Application of a Methodology for the Identification of Potential Groundwater Recharge Zones: A Case Study in the Virvini Micro-Basin, Tiraque, Bolivia I. Rodriguez-Levy et al. 10.3390/w15071268
- Groundwater Management in an Uncommon and Artificial Aquifer Based on Kc Approach and MODIS ET Products for Irrigation Assessment in a Subtropical Island Z. Yang et al. 10.3390/rs14246304
- Climate change and New Zealand’s groundwater resources: A methodology to support adaptation F. Mourot et al. 10.1016/j.ejrh.2022.101053
- Investigation of the consistency of changes in the wavelet phase characteristics of heliocosmic and climate variables and changes in the components of the world water balance. Part 1 V. Alekseev 10.18822/byusu202203121-136
- Inferences of Groundwater Response to Projected Hydroclimatic Changes in North Florida F. Gordu & M. Nachabe 10.1061/JHYEFF.HEENG-5827
- Assessment and prediction of regional climate based on a multimodel ensemble machine learning method Y. Fu et al. 10.1007/s00382-023-06787-7
- Intensified salinity intrusion in coastal aquifers due to groundwater overextraction: a case study in the Mekong Delta, Vietnam D. Tran et al. 10.1007/s11356-021-16282-3
- Climate change and its impact on the projected values of groundwater recharge: A review D. Atawneh et al. 10.1016/j.jhydrol.2021.126602
- Prediction of spatial saturated hydraulic conductivity at the upper soil layer using soil class and terrain attributes A. Saha et al. 10.1007/s40808-021-01317-y
- Review of approaches for selection and ensembling of GCMs K. Raju & D. Kumar 10.2166/wcc.2020.128
- Numerical simulation of groundwater in an unconfined aquifer with a novel hybrid model (case study: Birjand Aquifer, Iran) A. Mohtashami et al. 10.2166/hydro.2021.113
- Integrated Bayesian Multi-model approach to quantify input, parameter and conceptual model structure uncertainty in groundwater modeling S. Mustafa et al. 10.1016/j.envsoft.2020.104654
- Integrating of Bayesian model averaging and formal likelihood function to enhance groundwater process modeling in arid environments A. Jafarzadeh et al. 10.1016/j.asej.2024.103127
- Response of the Shabestar Plain aquifer to climate-change scenarios through statistical and hybrid soft computing techniques E. Jeihouni et al. 10.1016/j.gsd.2021.100649
- Modelling the impacts of climate change and management options on sustainable groundwater use in an irrigated agriculture landscape F. Karim et al. 10.1016/j.gsd.2023.100964
- Groundwater system and climate change: Present status and future considerations A. Amanambu et al. 10.1016/j.jhydrol.2020.125163
- Modelling groundwater level fluctuations by ELM merged advanced metaheuristic algorithms using hydroclimatic data R. Adnan et al. 10.1080/10106049.2022.2158951
- An overview of approaches for reducing uncertainties in hydrological forecasting: Progress and challenges A. Panchanathan et al. 10.1016/j.earscirev.2024.104956
- Uncertainty-based saltwater intrusion prediction using integrated Bayesian machine learning modeling (IBMLM) in a deep aquifer J. Yin et al. 10.1016/j.jenvman.2024.120252
- Development of a Multi-Scale Groundwater Drought Prediction Model Using Deep Learning and Hydrometeorological Data D. Kang & K. Byun 10.3390/w16142036
- A multimodel ensemble machine learning approach for CMIP6 climate model projections in an Indian River basin A. Dey et al. 10.1002/joc.7813
Discussed (preprint)
Latest update: 23 Nov 2024
Short summary
This study evaluates the effect of conceptual hydro(geo)logical model (CHM) structure, climate change and groundwater abstraction on future groundwater-level prediction uncertainty. If the current groundwater abstraction trend continues, groundwater level is predicted to decline quickly. Groundwater abstraction in NW Bangladesh should decrease by 60 % to ensure sustainable use. Abstraction scenarios are the dominant uncertainty source, followed by CHM uncertainty and climate model uncertainty.
This study evaluates the effect of conceptual hydro(geo)logical model (CHM) structure, climate...