Articles | Volume 13, issue 5
Geosci. Model Dev., 13, 2433–2450, 2020
https://doi.org/10.5194/gmd-13-2433-2020
Geosci. Model Dev., 13, 2433–2450, 2020
https://doi.org/10.5194/gmd-13-2433-2020

Model description paper 27 May 2020

Model description paper | 27 May 2020

HydroMix v1.0: a new Bayesian mixing framework for attributing uncertain hydrological sources

Harsh Beria et al.

Related authors

Benefits from high-density rain gauge observations for hydrological response analysis in a small alpine catchment
Anthony Michelon, Lionel Benoit, Harsh Beria, Natalie Ceperley, and Bettina Schaefli
Hydrol. Earth Syst. Sci., 25, 2301–2325, https://doi.org/10.5194/hess-25-2301-2021,https://doi.org/10.5194/hess-25-2301-2021, 2021
Short summary
On the value of high density rain gauge observations for small Alpine headwater catchments
Anthony Michelon, Lionel Benoit, Harsh Beria, Natalie Ceperley, and Bettina Schaefli
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-683,https://doi.org/10.5194/hess-2019-683, 2020
Manuscript not accepted for further review
Short summary
Does the GPM mission improve the systematic error component in satellite rainfall estimates over TRMM? An evaluation at a pan-India scale
Harsh Beria, Trushnamayee Nanda, Deepak Singh Bisht, and Chandranath Chatterjee
Hydrol. Earth Syst. Sci., 21, 6117–6134, https://doi.org/10.5194/hess-21-6117-2017,https://doi.org/10.5194/hess-21-6117-2017, 2017
Short summary

Related subject area

Hydrology
Understanding each other's models: an introduction and a standard representation of 16 global water models to support intercomparison, improvement, and communication
Camelia-Eliza Telteu, Hannes Müller Schmied, Wim Thiery, Guoyong Leng, Peter Burek, Xingcai Liu, Julien Eric Stanislas Boulange, Lauren Seaby Andersen, Manolis Grillakis, Simon Newland Gosling, Yusuke Satoh, Oldrich Rakovec, Tobias Stacke, Jinfeng Chang, Niko Wanders, Harsh Lovekumar Shah, Tim Trautmann, Ganquan Mao, Naota Hanasaki, Aristeidis Koutroulis, Yadu Pokhrel, Luis Samaniego, Yoshihide Wada, Vimal Mishra, Junguo Liu, Petra Döll, Fang Zhao, Anne Gädeke, Sam S. Rabin, and Florian Herz
Geosci. Model Dev., 14, 3843–3878, https://doi.org/10.5194/gmd-14-3843-2021,https://doi.org/10.5194/gmd-14-3843-2021, 2021
Short summary
LISFLOOD-FP 8.0: the new discontinuous Galerkin shallow-water solver for multi-core CPUs and GPUs
James Shaw, Georges Kesserwani, Jeffrey Neal, Paul Bates, and Mohammad Kazem Sharifian
Geosci. Model Dev., 14, 3577–3602, https://doi.org/10.5194/gmd-14-3577-2021,https://doi.org/10.5194/gmd-14-3577-2021, 2021
Short summary
InundatEd-v1.0: a height above nearest drainage (HAND)-based flood risk modeling system using a discrete global grid system
Chiranjib Chaudhuri, Annie Gray, and Colin Robertson
Geosci. Model Dev., 14, 3295–3315, https://doi.org/10.5194/gmd-14-3295-2021,https://doi.org/10.5194/gmd-14-3295-2021, 2021
Short summary
Fluxes from soil moisture measurements (FluSM v1.0): a data-driven water balance framework for permeable pavements
Axel Schaffitel, Tobias Schuetz, and Markus Weiler
Geosci. Model Dev., 14, 2127–2142, https://doi.org/10.5194/gmd-14-2127-2021,https://doi.org/10.5194/gmd-14-2127-2021, 2021
Short summary
Parametrization of a lake water dynamics model MLake in the ISBA-CTRIP land surface system (SURFEX v8.1)
Thibault Guinaldo, Simon Munier, Patrick Le Moigne, Aaron Boone, Bertrand Decharme, Margarita Choulga, and Delphine J. Leroux
Geosci. Model Dev., 14, 1309–1344, https://doi.org/10.5194/gmd-14-1309-2021,https://doi.org/10.5194/gmd-14-1309-2021, 2021
Short summary

Cited articles

Allen, S. T., Kirchner, J. W., and Goldsmith, G. R.: Predicting spatial patterns in precipitation isotope (δ2H and δ18O) seasonality using sinusoidal isoscapes, Geophys. Res. Lett., 45, 4859–4868, https://doi.org/10.1029/2018GL077458, 2018. 
Barbeta, A. and Peñuelas, J.: Relative contribution of groundwater to plant transpiration estimated with stable isotopes, Sci. Rep., 7, 10580, https://doi.org/10.1038/s41598-017-09643-x, 2017. 
Benettin, P., Bailey, S. W., Rinaldo, A., Likens, G. E., McGuire, K. J., and Botter, G.: Young runoff fractions control streamwater age and solute concentration dynamics, Hydrol. Process., 31, 2982–2986, https://doi.org/10.1002/hyp.11243, 2017. 
Beria, H., Larsen, J. R., Ceperley, N. C., Michelon, A., Vennemann, T., and Schaefli, B.: Understanding snow hydrological processes through the lens of stable water isotopes, Wiley Interdiscip. Rev. Water, 5, e1311, https://doi.org/10.1002/wat2.1311, 2018. 
Beria, H., Larsen, J. R., Michelon, A., Ceperley, N. C., and Schaefli, B.: Data for the manuscript “HydroMix v1.0: a new Bayesian mixing framework for attributing uncertain hydrological sources” (Version 1.0), Zenodo, https://doi.org/10.5281/zenodo.3475429, 2019. 
Download
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.