Design and Development of an Open Source Software Application for the Characterization of Spatially Variable Fields

The characterization of the structural parameters of spatially variable fields (SVFs) is essential to understanding the variability of hydrological processes such as infiltration, evapotranspiration, groundwater contaminant transport, etc. SVFs can be characterized using a Bayesian inverse method called Method of Anchored Distributions (MAD). This method characterizes the structural parameters of SVFs using prior information of structural parameter fields, indirect measurements, and simulation models allowing the transfer of valuable information to a target variable field. An example SVF in hydrology is hydraulic conductivity, which may be characterized by head pressure measurements through a simulation model such as MODFLOW. This poster will present the design and development of a free and open source inverse modeling desktop software application and extension framework called MAD# for the characterization of the structural parameters of SVFs using MAD. The developed software is designed with a flexible architecture to support different simulation models and random field generators and includes geographic information system (GIS) interfaces for representing, analyzing, and understanding SVFs. This framework has also been made compatible with Mono, a cross-platform implementation of C#, for a wider usability.