Reengineering and optimization of GEOtop software package

The GEOtop hydrological scientific package is an integrated hydrological model that simulates the heat and water budgets at and below the soil sur-face (Rigon, Bertoldi, and Over, 2006). It describes the three-dimensional water flow in the soil and the energy exchange with the atmosphere, con-sidering the radiative and turbulent fluxes. Furthermore, it reproduces soil freezing and thawing processes, and it simulates the temporal evolution of snow cover, soil temperature and moisture. The model can be applied both at the plot and the catchment scale to study the long term water budget and runoff production. The model has been applied to a variety of scientific prob-lems, ranging from estimation of runoff and water budget in small - medium chatchments (< 1000 m2), studies related to the water-soil-vegetation interac-tions, snow cover in mountain areas, climate change impact assessment (for a full reference list see http://geotopmodel.github.io/geotop/materials/publication-list.html). One version of the model is currently used in an operational snow forecasting system (http://www.mysnowmaps.com). The core components of the package were presented in the 2.0 version (En-drizzi et al., 2014), which was released as Free Software Open-source project under GNU General Public License v3.0. The code was written in C lan-guage. However, despite the high scientific quality of the project, a modern software engineering approach was still missing. Such weakness hindered its computational efficiency, its scientific potential and its use both as a stan-dalone package and, more importantly, in an integrated way with other hy-drological software tools and earth system models. A poor engineering is typical issue of scientific softwares, whose goal is the creation of new scientific knowledge; the emphasis placed on software qual-ity (i.e., correctness of code, maintainability, and reliability) has been his-torically lower than seen in more traditional software engineering (Heaton and Carver, 2015). More in general, the scientific software community is fac-ing a crisis created by the confluence of disruptive changes in computing architectures and new opportunities for greatly improved data availability a simulation capabilities (See the scheme in Fig.1 taken from Ideas Produc-tivity project). There is therefore the need, in order to keep productive well established scientific softwares to perform a software refactoring to develop efficient codes for parallel architecture. A suitable test case is the GEOtop model, an integrated hydrological model which started to be developed in 2000, and, since them, continuously evolved to address a number of scien-tific and applied problems, but also increasing it complexity