Articles | Volume 18, issue 2
https://doi.org/10.5194/nhess-18-445-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/nhess-18-445-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
08 Feb 2018
Research article |
| 08 Feb 2018
Process-based modelling to evaluate simulated groundwater levels and frequencies in a Chalk catchment in south-western England
Simon Brenner
CORRESPONDING AUTHOR
Institute of Earth and Environmental Sciences, Freiburg
University, Freiburg, Germany
Gemma Coxon
School of Geographical Sciences, University of Bristol,
Bristol, UK
Cabot Institute, University of Bristol, Bristol, UK
Nicholas J. K. Howden
Department of Civil Engineering, University of Bristol,
Bristol, UK
Cabot Institute, University of Bristol, Bristol, UK
Jim Freer
School of Geographical Sciences, University of Bristol,
Bristol, UK
Cabot Institute, University of Bristol, Bristol, UK
Andreas Hartmann
Institute of Earth and Environmental Sciences, Freiburg
University, Freiburg, Germany
Department of Civil Engineering, University of Bristol,
Bristol, UK
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- Development of an integrated global sensitivity analysis strategy for evaluating process sensitivities across single- and multi-models J. Yang et al. 10.1016/j.jhydrol.2024.132014
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- Enhancing water management in Northern European lowland chalk streams: A parsimonious, high-resolution hydrological model using groundwater level as a proxy for baseflow T. Homan et al. 10.1016/j.ejrh.2024.102022
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28 citations as recorded by crossref.
- Towards integrated flood inundation modelling in groundwater-dominated catchments S. Collins et al. 10.1016/j.jhydrol.2020.125755
- A proposed modelling towards the potential impacts of climate change on a semi-arid, small-scaled aquifer: a case study of Iran H. Nassery et al. 10.1007/s10661-021-08955-w
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- Using Sobol’ sensitivity analysis to identify important model layers of a prediction model for simulating soil nitrogen transport in surface runoff and subsurface water S. Zhang et al. 10.1007/s00477-024-02894-x
- Revealing the positive influence of young water fractions derived from stable isotopes on the robustness of karst water resources predictions K. Çallı et al. 10.1016/j.jhydrol.2023.129549
- A new multi-model absolute difference-based sensitivity (MMADS) analysis method to screen non-influential processes under process model and parametric uncertainty J. Yang & M. Ye 10.1016/j.jhydrol.2022.127609
- Wavelet gated multiformer for groundwater time series forecasting V. Serravalle Reis Rodrigues et al. 10.1038/s41598-023-39688-0
- Groundwater Vulnerability in the Piedmont Region under Climate Change M. Nistor 10.3390/atmos11080779
- An introduction to the chalk aquifers of northern Europe L. West et al. 10.1144/SP517-2023-3
- A new process-based approach for defining karst aquifer vulnerability to contamination risks under global changes T. Leins et al. 10.1016/j.scitotenv.2025.178561
- Modeling the Effect of Global Warming on the Sustainable Groundwater Management: A Case Study in Bangladesh A. Islam & H. Biswas 10.37394/23206.2020.19.71
- Validating the KAGIS black‐box GIS‐based model in a Mediterranean karst aquifer: Case of study of Mela aquifer (SE Spain) J. Valdes‐Abellan et al. 10.1002/hyp.13215
- Impacts of climate change on groundwater flooding and ecohydrology in lowland karst P. Morrissey et al. 10.5194/hess-25-1923-2021
- Dynamic evolution of karst water levels and its controlling and influencing factors in Northern China: a case study in the Dawu water source area Z. Gao et al. 10.1007/s13146-020-00585-6
- An Improved Optimization Scheme for Representing Hillslopes and Depressions in Karst Hydrology C. Xu et al. 10.1029/2019WR026038
- Considering land cover and land use (LCLU) in lumped parameter modeling in forest dominated karst catchments V. Sivelle et al. 10.1016/j.jhydrol.2022.128264
- Graph neural network for groundwater level forecasting T. Bai & P. Tahmasebi 10.1016/j.jhydrol.2022.128792
- Hydrological modelling of large-scale karst-dominated basin using a grid-based distributed karst hydrological model L. Chen et al. 10.1016/j.jhydrol.2023.130459
- Modeling interbasin groundwater flow in karst areas: Model development, application, and calibration strategy V. Nguyen et al. 10.1016/j.envsoft.2019.104606
- Exploring AI approaches for predicting groundwater levels in coastal agro-climatic zones: a case study in Cuttack District, Odisha S. Panda et al. 10.1007/s44288-024-00021-5
- A data‐based approach to determining the optimal water ponding scale and zone for small urban wetland restoration N. Nakashima et al. 10.1111/rec.14154
- Climate Change Impacts on Groundwater Resources in the Coastal Karstic Adriatic Area: A Case Study from the Dinaric Karst J. Lukač Reberski et al. 10.1007/s11053-019-09558-6
- Development of an integrated global sensitivity analysis strategy for evaluating process sensitivities across single- and multi-models J. Yang et al. 10.1016/j.jhydrol.2024.132014
- A simulation model for estimating root zone saturation indices of agricultural crops in a shallow aquifer and canal system M. Zhang et al. 10.1016/j.agwat.2019.03.044
- Prediction of the karstic spring flow rates under climate change by climatic variables based on the artificial neural network: a case study of Iran N. Zeydalinejad et al. 10.1007/s10661-020-08332-z
- Spatial-temporal graph neural networks for groundwater data M. Taccari et al. 10.1038/s41598-024-75385-2
- Enhancing water management in Northern European lowland chalk streams: A parsimonious, high-resolution hydrological model using groundwater level as a proxy for baseflow T. Homan et al. 10.1016/j.ejrh.2024.102022
- Groundwater level prediction using an improved SVR model integrated with hybrid particle swarm optimization and firefly algorithm S. Samantaray et al. 10.1016/j.clwat.2024.100003
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Latest update: 24 Apr 2025
Short summary
In this study we simulate groundwater levels with a semi-distributed karst model. Using a percentile approach we can assess the number of days exceeding or falling below selected groundwater level percentiles. We show that our approach is able to predict groundwater levels across all considered timescales up to the 75th percentile. We then use our approach to assess future changes in groundwater dynamics and show that projected climate changes may lead to generally lower groundwater levels.
In this study we simulate groundwater levels with a semi-distributed karst model. Using a...
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