Building a groundwater model is often essential to make accurate predictions about the evolution of groundwater resources. To this aim, a wide variety of data can be used, such as groundwater levels, geophysical measurements or pumping tests. However, integrating these data into a consistent groundwater modelling workflow is known to be difficult. In the last decade, open science has become widely accepted in geosciences with the emergence of many software, datasets and methodologies that are freely accessible and facilitate the development of more holistic approaches that better integrate different types of data. Within this philosophy, we have developed a set of geostatistical tools and modelling approaches to simplify the complex task of (hydro)-geological modelling and spatial predictions. First, we have a python library called GEONE which includes a large panel of geostatistical functions (random fields, indicator simulations, multiple point statistics). Second, around GEONE, we have ArchPy, a python module that allows the fast generation of hierarchical geological stochastic models that respect both geological concepts (stratigraphic relations, lithofacies, etc.) and geological data (geological maps, boreholes, cross-section). ArchPy is flexible and can be simply coupled with other open access software such as geophysical and groundwater forward models. Notably, there is the archpy2modflow submodule which allows to easily create a MODFLOW model directly from an Archpy model. It also integrates options for automatic simple upscaling of Archpy models, reducing the computational burden of hydrogeological modelling while preserving latent complex geology. This is even more critical for coastal aquifers, where seawater need to be considered, making the computation of groundwater heads difficult and computationally expensive. Finally, we have developed a web-interface, ArchPyOnline, that allows to generate a geological model on demand via an open access website. All of these tools facilitate the emergence of coupled and holistic workflows that allow better management of underground resources.