HydroSight is a highly flexible statistical toolbox for quantitative hydrogeological insights. It comprises of a powerful groundwater hydrograph time-series modelling and simulation framework plus a data quality analysis module. Multiple models can be built for one bore, allowing statistical identification of the dominant processes, or 100’s of bores can be modelled to quantify aquifer heterogeneity. This flexibility allows many novel applications such as:
- Separations of the impacts from pumping and drought over time.
- Probabilistic estimation of aquifer hydraulic properties.
- Estimation of the impacts of re-vegetation on groundwater level.
- Exploration of groundwater management scenarios.
- Interpolation and extrapolation irregularly observed hydrograph at a daily time-step.
The toolbox can be used from a highly flexible and stand-alone graphical user interface (available here) or programmatically from within Matlab 2014b (or later).
What’s New
The next release of the stand alone application is out! It contains some exciting new features:
- Extend examination of calibrated and simulation model fluxes, eg rations such as monthly free drainage / precip.
- Details documentation of model construction and calibration status.
- Outlier detection analysis is significantly faster to run on 100s of bores.
- “Cite Project” menu item added to allow efficient referencing.
- Many bug and annoyances fixed making it more efficient to build and examine models.
How many use HydroSight?
The number of downloads per releases are availabe at Git Hub Release Statistics. As of August 2022, there had been >1,200 downloads. Also, 17 users have forked this project to make their only modifications.
Getting Started
To begin using the stand-alone application, simply download and install the above Windows 64bit executable (available here).
Next, visit the project wiki help to explore the graphical interface and types of models.
About the Researchers
HydroSight development was led by Dr Tim Peterson at Monash University, with contributons from colleagues and students at the University of Melbourne. To find out more see Tim’s Research Profile, Research Gate or Google Scholar
Alternatively, to stay connected with developments and new versions join us at LinkedIn or join the Google Groups discussion.
Acknowledgements
HydroSight has been generously supported by the following organisations:
- The Australian Research Council grants LP0991280, LP130100958.
- The Bureau of Meteorology (Aust.)
- The Department of Environment, Land, Water and Planning (Vic., Aust.)
- The Department of Economic Development, Jobs, Transport and Resources (Vic., Aust.)
- Power and Water Corporation, N. T., Aust.
References:
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Peterson, T. J. and Fulton, S. (2019), Joint estimation of gross recharge, groundwater usage and hydraulic properties within HydroSight. Groundwater. Accepted Author Manuscript. https://doi.org/10.1111/gwat.12946
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Peterson T. J and Western A. W., (2014), Nonlinear Groundwater time-series modeling of unconfined groundwater head, Water Resources Research, DOI: 10.1002/2013WR014800 PDF copy
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Peterson, T. J., & Western, A. W. (2018). Statistical interpolation of groundwater hydrographs. Water Resources Research, 54, 4663–4680. DOI: https://doi.org/10.1029/2017WR021838
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Peterson, T.J., Western, A.W. & Cheng, X. (2018). The good, the bad and the outliers: automated detection of errors and outliers from groundwater hydrographs. Hydrogeol J, 26: 371. https://doi.org/10.1007/s10040-017-1660-7
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Shapoori V., Peterson T.J. , Western A.W. and Costelloe J. F. (2015a). Decomposing groundwater head variations into meteorological and pumping components: a synthetic study, Hydrogeology Journal, DOI: 10.1007/s10040-015-1269-7 PDF copy
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Shapoori V., Peterson T.J. , Western A.W. and Costelloe J. F. (2015b). Top-down groundwater hydrograph time-series modeling for climate-pumping decomposition, Hydrogeology Journal, 23(4), 819-83, DOI: 10.1007/s10040-014-1223-0 PDF copy
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Shapoori V., Peterson T.J. , Western A.W. and Costelloe J. F. (2015c). Estimating aquifer properties using groundwater hydrograph modeling. Hydrological Processes, 29: 5424–5437. DOI: 10.1002/hyp.10583. PDF copy
