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HydroSight is a highly flexible statistical toolbox for getting more quantitative value from groundwater level monitoring data. It allows a wide range of data-driven time-series analysis to be efficiently undertaken at 100's of bores and comes with a powerful user interface.
HydroSight contains a highly flexible groundwater hydrograph time-series modeling framework can be used for the following analysis:
- decomposition of a groundwater hydrograph into individual drivers, such as climate and pumping or climate (Shapoori et al., 2015a) and landuse change (Peterson and Western, 2014).
- estimation of aquifer hydraulic properties from the hydrograph (Shapoori et al., 2015c) by building and calibrating a model that includes groundwater pumping.
- estimation of recharge over time (Peterson & Fulton, 2019) by building a model, ideally using the V2 soil models and a calibrated gamma parameter to ensure reliable modelled ET, and calibrating the model and then examining the recharge within the forcing data tab.
- statistical identification of the major groundwater processes (Shapoori et al., 2015b) by building and calibrating different possible drivers (e.g. pumping and climate vs only climate) and identifying the model with the lowest Akaike information criterion, as shown within the model calibration outputs table.
- interpolation of the observed hydrograph (Peterson et al., 2018) by building and calibration a model, and then running a model simulation with the Simulation Time Step set to, say, daily and the Krig Simulation Residuals? ticked to ensure the interpolated hydrograph honours the observed data..
- extrapolation of the observed hydrograph back in time by building and calibration a model, and then running a model simulation with the simulation start date set to before the first groundwater level observation but, ideally, some years after the start date of the forcing data.
- simulation of groundwater head under different climate or, say, pumping scenarios by building and calibration a model and then running a model simulation using an alternate Forcing Data File.
- numerical identification of hydrograph monitoring errors and outliers (Peterson et al., 2018) by running the Date Preparation tool.
Decades of groundwater level data is available in many regions of the world. It is primarily used only for graphical analysis of, say, trends and only very occasionally is the data used for calibration of numerical models. HydroSight was developed to provide a quantitative option between these two alternatives. Additionally, it was developed to allow the identification of sub-surface processes from the data - that is, allowing us learn from the data about the hydrological cycle.
HydroSight can be used in two ways:
- Programmatically: using a collection Matlab of object-oriented classes that provides enormous flexibility to built time-series models and develop new models and components. This option requires the user to have a copy of MatLab.
- Graphical User Interface: stand alone application that provides a highly flexible framework for the efficient construction, modelling and simulation of an unlimited number of models within a simple graphical environment. This option does not require the user to have a copy of MatLab.
This wiki focuses on the various modelling approaches and the GUI. It does not focus on the programmatic use, but which is documented within the header to most classes, methods and functions.
HydroSight can be run as a stand alone Windows executable program or from within Matlab. For installation details see https://github.com/peterson-tim-j/HydroSight/wiki/Installation
| Home | Graphical Interface | Model Details | Tutorials | Support & Collaboration |
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| Introduction to HydroSight | An overview of the HydroSight graphical interface | Technical details of the various model types and their components | Tutorials of example applications | About the open-source project, the user community and how to contribute |