Articles | Volume 22, issue 11
https://doi.org/10.5194/hess-22-5675-2018
© Author(s) 2018. 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-22-5675-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
02 Nov 2018
Research article |
| 02 Nov 2018
| 02 Nov 2018
Stochastic hydrogeology's biggest hurdles analyzed and its big blind spot
Civil and Environmental Engineering, University of California, Berkeley, 94720, USA
Ching-Fu Chang
Civil and Environmental Engineering, University of California, Berkeley, 94720, USA
Jiancong Chen
Civil and Environmental Engineering, University of California, Berkeley, 94720, USA
Karina Cucchi
Civil and Environmental Engineering, University of California, Berkeley, 94720, USA
Bradley Harken
Civil and Environmental Engineering, University of California, Berkeley, 94720, USA
Falk Heße
Computational Hydrosystems, Helmholtz Centre for Environmental Research (UFZ), 04318 Leipzig, Germany
Heather Savoy
Civil and Environmental Engineering, University of California, Berkeley, 94720, USA
Viewed
Total article views: 3,840 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 14 Jun 2018)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 2,604 | 1,167 | 69 | 3,840 | 81 | 69 |
- HTML: 2,604
- PDF: 1,167
- XML: 69
- Total: 3,840
- BibTeX: 81
- EndNote: 69
Total article views: 3,046 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 02 Nov 2018)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 2,206 | 778 | 62 | 3,046 | 69 | 53 |
- HTML: 2,206
- PDF: 778
- XML: 62
- Total: 3,046
- BibTeX: 69
- EndNote: 53
Total article views: 794 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 14 Jun 2018)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 398 | 389 | 7 | 794 | 12 | 16 |
- HTML: 398
- PDF: 389
- XML: 7
- Total: 794
- BibTeX: 12
- EndNote: 16
Viewed (geographical distribution)
Total article views: 3,840 (including HTML, PDF, and XML)
Thereof 3,590 with geography defined
and 250 with unknown origin.
Total article views: 3,046 (including HTML, PDF, and XML)
Thereof 2,821 with geography defined
and 225 with unknown origin.
Total article views: 794 (including HTML, PDF, and XML)
Thereof 769 with geography defined
and 25 with unknown origin.
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
Cited
13 citations as recorded by crossref.
- A Snapshot of the World's Groundwater Challenges U. Lall et al. 10.1146/annurev-environ-102017-025800
- An effective multi-objective optimization approach for groundwater remediation considering the coexisting uncertainties of aquifer parameters Y. Yang et al. 10.1016/j.jhydrol.2022.127677
- Uncertainties in physical and tracer methods in actual groundwater recharge estimation in the thick loess deposits of China W. Wang et al. 10.1016/j.jhydrol.2024.131127
- Regionalization with hierarchical hydrologic similarity and ex situ data in the context of groundwater recharge estimation at ungauged watersheds C. Chang & Y. Rubin 10.5194/hess-23-2417-2019
- Application of upscaling methods for fluid flow and mass transport in multi-scale heterogeneous media: A critical review X. Zhang et al. 10.1016/j.apenergy.2021.117603
- Conceptual framework addressing timescale mismatch uncertainty: Nitrous-oxide (N2O) modeled and measured, Kansas, USA M. Arango et al. 10.1016/j.ecolmodel.2023.110536
- GSTools v1.3: a toolbox for geostatistical modelling in Python S. Müller et al. 10.5194/gmd-15-3161-2022
- Ensemble modeling of the two-dimensional stochastic confined groundwater flow through the evolution of the hydraulic head’s probability density function J. Meza & M. Levent Kavvas 10.1016/j.jhydrol.2025.132689
- A Critical Review of the Modelling Tools for the Reactive Transport of Organic Contaminants K. Samborska-Goik & M. Pogrzeba 10.3390/app14093675
- Ensemble-based stochastic permeability and flow simulation of a sparsely sampled hard-rock aquifer supported by high performance computing J. Bruckmann & C. Clauser 10.1007/s10040-020-02163-5
- Hydrological design in the HELPING decade – inspiring the community to innovate the hydrological design concept S. Fischer et al. 10.1080/02626667.2024.2436634
- Representing driver-response complexity in ecosystems using an improved conceptual model C. Bentley & A. Anandhi 10.1016/j.ecolmodel.2020.109320
- What We Talk About When We Talk About Uncertainty. Toward a Unified, Data-Driven Framework for Uncertainty Characterization in Hydrogeology F. Heße et al. 10.3389/feart.2019.00118
12 citations as recorded by crossref.
- A Snapshot of the World's Groundwater Challenges U. Lall et al. 10.1146/annurev-environ-102017-025800
- An effective multi-objective optimization approach for groundwater remediation considering the coexisting uncertainties of aquifer parameters Y. Yang et al. 10.1016/j.jhydrol.2022.127677
- Uncertainties in physical and tracer methods in actual groundwater recharge estimation in the thick loess deposits of China W. Wang et al. 10.1016/j.jhydrol.2024.131127
- Regionalization with hierarchical hydrologic similarity and ex situ data in the context of groundwater recharge estimation at ungauged watersheds C. Chang & Y. Rubin 10.5194/hess-23-2417-2019
- Application of upscaling methods for fluid flow and mass transport in multi-scale heterogeneous media: A critical review X. Zhang et al. 10.1016/j.apenergy.2021.117603
- Conceptual framework addressing timescale mismatch uncertainty: Nitrous-oxide (N2O) modeled and measured, Kansas, USA M. Arango et al. 10.1016/j.ecolmodel.2023.110536
- GSTools v1.3: a toolbox for geostatistical modelling in Python S. Müller et al. 10.5194/gmd-15-3161-2022
- Ensemble modeling of the two-dimensional stochastic confined groundwater flow through the evolution of the hydraulic head’s probability density function J. Meza & M. Levent Kavvas 10.1016/j.jhydrol.2025.132689
- A Critical Review of the Modelling Tools for the Reactive Transport of Organic Contaminants K. Samborska-Goik & M. Pogrzeba 10.3390/app14093675
- Ensemble-based stochastic permeability and flow simulation of a sparsely sampled hard-rock aquifer supported by high performance computing J. Bruckmann & C. Clauser 10.1007/s10040-020-02163-5
- Hydrological design in the HELPING decade – inspiring the community to innovate the hydrological design concept S. Fischer et al. 10.1080/02626667.2024.2436634
- Representing driver-response complexity in ecosystems using an improved conceptual model C. Bentley & A. Anandhi 10.1016/j.ecolmodel.2020.109320
Latest update: 14 Jan 2025
Short summary
This paper addresses questions related to the adoption of stochastic methods in hydrogeology, looking at factors such as environmental regulations, financial incentives, higher education, and the collective feedback loop involving these factors. We show that stochastic hydrogeology's blind spot is in focusing on risk while ignoring uncertainty, to the detriment of its potential clients. The imbalance between the treatments of risk and uncertainty is shown to be common to multiple disciplines.
This paper addresses questions related to the adoption of stochastic methods in hydrogeology,...
