Articles | Volume 13, issue 5
https://doi.org/10.5194/gmd-13-2433-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-13-2433-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
27 May 2020
Model description paper |
| 27 May 2020
| 27 May 2020
HydroMix v1.0: a new Bayesian mixing framework for attributing uncertain hydrological sources
Institute of Earth Surface Dynamics, University of Lausanne,
Lausanne, Switzerland
Joshua R. Larsen
School of Geography, Earth and Environmental Sciences, University
of Birmingham, Birmingham, UK
Anthony Michelon
Institute of Earth Surface Dynamics, University of Lausanne,
Lausanne, Switzerland
Natalie C. Ceperley
Institute of Earth Surface Dynamics, University of Lausanne,
Lausanne, Switzerland
now at: Institute of Geography, University of Berne, Bern, Switzerland
Bettina Schaefli
Institute of Earth Surface Dynamics, University of Lausanne,
Lausanne, Switzerland
now at: Institute of Geography, University of Berne, Bern, Switzerland
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Cited
18 citations as recorded by crossref.
- Estimation of Water-to-Cement Ratio in Cementitious Materials Using Electrochemical Impedance Spectroscopy and Artificial Neural Networks J. Park et al. 10.2139/ssrn.4144029
- Benefits from high-density rain gauge observations for hydrological response analysis in a small alpine catchment A. Michelon et al. 10.5194/hess-25-2301-2021
- Seasonal snow cover decreases young water fractions in high Alpine catchments N. Ceperley et al. 10.1002/hyp.13937
- The Spatiotemporal Variability of Snowpack and Snowmelt Water 18O and 2H Isotopes in a Subarctic Catchment K. Noor et al. 10.1029/2022WR033101
- Mixing Models With Multiple, Overlapping, or Incomplete End‐Members, Quantified Using Time Series of a Single Tracer J. Kirchner 10.1029/2023GL104147
- Incorporating Snowmelt into Daily Estimates of Recharge Using a State‐Space Model of Infiltration A. Shapiro et al. 10.1111/gwat.13206
- Stream water sourcing from high-elevation snowpack inferred from stable isotopes of water: a novel application of d-excess values M. Sprenger et al. 10.5194/hess-28-1711-2024
- A Framework for Untangling Transient Groundwater Mixing and Travel Times A. Popp et al. 10.1029/2020WR028362
- Estimation of water-to-cement ratio in cementitious materials using electrochemical impedance spectroscopy and artificial neural networks J. Park et al. 10.1016/j.conbuildmat.2022.128843
- Constraining Mountain Streamflow Constituents by Integrating Citizen Scientist Acquired Geochemical Samples and Sentinel‐1 SAR Wet Snow Time‐Series for the Shimshal Catchment in the Karakoram Mountains of Pakistan J. Lund et al. 10.1029/2022WR032171
- Hydrodynamics of a high Alpine catchment characterized by four natural tracers A. Michelon et al. 10.5194/hess-27-1403-2023
- Comparing Bayesian and traditional end-member mixing approaches for hydrograph separation in a glacierized basin Z. He et al. 10.5194/hess-24-3289-2020
- Investigation of factors controlling the runoff generation mechanism using isotope tracing in large-scale nested basins J. Fang et al. 10.1016/j.jhydrol.2022.128728
- Deep learning for water quality W. Zhi et al. 10.1038/s44221-024-00202-z
- A data-driven method for estimating the composition of end-members from stream water chemistry time series E. Xu Fei & C. Harman 10.5194/hess-26-1977-2022
- Snow sampling strategy can bias estimation of meltwater fractions in isotope hydrograph separation K. Noor et al. 10.1016/j.jhydrol.2023.130429
- End member and Bayesian mixing models consistently indicate near‐surface flowpath dominance in a pristine humid tropical rainforest C. Birkel et al. 10.1002/hyp.14153
- Stream water sourcing from high-elevation snowpack inferred from stable isotopes of water: a novel application of d-excess values M. Sprenger et al. 10.5194/hess-28-1711-2024
17 citations as recorded by crossref.
- Estimation of Water-to-Cement Ratio in Cementitious Materials Using Electrochemical Impedance Spectroscopy and Artificial Neural Networks J. Park et al. 10.2139/ssrn.4144029
- Benefits from high-density rain gauge observations for hydrological response analysis in a small alpine catchment A. Michelon et al. 10.5194/hess-25-2301-2021
- Seasonal snow cover decreases young water fractions in high Alpine catchments N. Ceperley et al. 10.1002/hyp.13937
- The Spatiotemporal Variability of Snowpack and Snowmelt Water 18O and 2H Isotopes in a Subarctic Catchment K. Noor et al. 10.1029/2022WR033101
- Mixing Models With Multiple, Overlapping, or Incomplete End‐Members, Quantified Using Time Series of a Single Tracer J. Kirchner 10.1029/2023GL104147
- Incorporating Snowmelt into Daily Estimates of Recharge Using a State‐Space Model of Infiltration A. Shapiro et al. 10.1111/gwat.13206
- Stream water sourcing from high-elevation snowpack inferred from stable isotopes of water: a novel application of d-excess values M. Sprenger et al. 10.5194/hess-28-1711-2024
- A Framework for Untangling Transient Groundwater Mixing and Travel Times A. Popp et al. 10.1029/2020WR028362
- Estimation of water-to-cement ratio in cementitious materials using electrochemical impedance spectroscopy and artificial neural networks J. Park et al. 10.1016/j.conbuildmat.2022.128843
- Constraining Mountain Streamflow Constituents by Integrating Citizen Scientist Acquired Geochemical Samples and Sentinel‐1 SAR Wet Snow Time‐Series for the Shimshal Catchment in the Karakoram Mountains of Pakistan J. Lund et al. 10.1029/2022WR032171
- Hydrodynamics of a high Alpine catchment characterized by four natural tracers A. Michelon et al. 10.5194/hess-27-1403-2023
- Comparing Bayesian and traditional end-member mixing approaches for hydrograph separation in a glacierized basin Z. He et al. 10.5194/hess-24-3289-2020
- Investigation of factors controlling the runoff generation mechanism using isotope tracing in large-scale nested basins J. Fang et al. 10.1016/j.jhydrol.2022.128728
- Deep learning for water quality W. Zhi et al. 10.1038/s44221-024-00202-z
- A data-driven method for estimating the composition of end-members from stream water chemistry time series E. Xu Fei & C. Harman 10.5194/hess-26-1977-2022
- Snow sampling strategy can bias estimation of meltwater fractions in isotope hydrograph separation K. Noor et al. 10.1016/j.jhydrol.2023.130429
- End member and Bayesian mixing models consistently indicate near‐surface flowpath dominance in a pristine humid tropical rainforest C. Birkel et al. 10.1002/hyp.14153
Latest update: 14 Dec 2024
Short summary
We develop a Bayesian mixing model to address the issue of small sample sizes to describe different sources in hydrological mixing applications. Using composite likelihood functions, the model accounts for an often overlooked bias arising due to unweighted mixing. We test the model efficacy using a series of statistical benchmarking tests and demonstrate its real-life applicability by applying it to a Swiss Alpine catchment to obtain the proportion of groundwater recharged from rain vs. snow.
We develop a Bayesian mixing model to address the issue of small sample sizes to describe...
