Core Ideas: OZCAR is a network of sites studying the critical zone. OZCAR covers various disciplines. OZCAR will help disciplines to work together for a better representation and modeling of the critical zone. The French critical zone initiative, called OZCAR (Observatoires de la Zone Critique–Application et Recherche or Critical Zone Observatories–Application and Research) is a National Research Infrastructure (RI). OZCAR‐RI is a network of instrumented sites, bringing together 21 pre‐existing research observatories monitoring different compartments of the zone situated between “the rock and the sky,” the Earth's skin or critical zone (CZ), over the long term. These observatories are regionally based and have specific initial scientific questions, monitoring strategies, databases, and modeling activities. The diversity of OZCAR‐RI observatories and sites is well representative of the heterogeneity of the CZ and of the scientific communities studying it. Despite this diversity, all OZCAR‐RI sites share a main overarching mandate, which is to monitor, understand, and predict (“earthcast”) the fluxes of water and matter of the Earth's near surface and how they will change in response to the “new climatic regime.” The vision for OZCAR strategic development aims at designing an open infrastructure, building a national CZ community able to share a systemic representation of the CZ, and educating a new generation of scientists more apt to tackle the wicked problem of the Anthropocene. OZCAR articulates around: (i) a set of common scientific questions and cross‐cutting scientific activities using the wealth of OZCAR‐RI observatories, (ii) an ambitious instrumental development program, and (iii) a better interaction between data and models to integrate the different time and spatial scales. Internationally, OZCAR‐RI aims at strengthening the CZ community by providing a model of organization for pre‐existing observatories and by offering CZ instrumented sites. OZCAR is one of two French mirrors of the European Strategy Forum on Research Infrastructure (eLTER‐ESFRI) project.

The self-potential method enables non-intrusive assessment and imaging of disturbances in electrical currents of conductive subsurface materials. It has an increasing number of applications, from mapping fluid flow in the subsurface of the Earth to detecting preferential flow paths in earth dams and embankments. This book provides the first full overview of the fundamental concepts of this method and its applications in the field. It discusses a historical perspective, laboratory investigations undertaken, the inverse problem and seismoelectric coupling, and concludes with the application of the self-potential method to geohazards, water resources and hydrothermal systems. Chapter exercises, online datasets and analytical software enable the reader to put the theory into practice. This book is a key reference for academic researchers and professionals working in the areas of geophysics, environmental science, hydrology and geotechnical engineering. It will also be valuable reading for related graduate courses.

An algorithm is developed to interpret self‐potential (SP) data in terms of distribution of Darcy velocity of the ground water. The model is based on the proportionality existing between the streaming current density and the Darcy velocity. Because the inverse problem of current density determination from SP data is underdetermined, we use Tikhonov regularization with a smoothness constraint based on the differential Laplacian operator and a prior model. The regularization parameter is determined by the L‐shape method. The distribution of the Darcy velocity depends on the localization and number of non‐polarizing electrodes and information relative to the distribution of the electrical resistivity of the ground. A priori hydraulic information can be introduced in the inverse problem. This approach is tested on two synthetic cases and on real SP data resulting from infiltration of water from a ditch.

We propose an algorithm to invert self‐potential signals measured at the ground surface of the Earth to localize hydromechanical disturbances or to the pattern of groundwater flow in geothermal systems. The self‐potential signals result from the divergence of the streaming current density. Groundwater flow can be either driven by topography of the water table, free convection, or deformation of the medium. The algorithm includes the electrical resistivity distribution of the medium obtained independently by DC resistance tomography or electromagnetic methods or by coding the assumed geology in terms of distribution of the electrical resistivity accounting for the effect of the temperature and salinity distributions and possibly constraints from borehole measurements. Inversion of the distribution of the source current density from ground surface and borehole self‐potential measurements is achieved by solving the inverse problem using Tikhonov regularization solutions that are compatible with the physics of the primary flow problem. By introducing assumptions regarding the smoothness or the compactness of the source and the three‐dimensional distribution of the electrical resistivity of the system, the inverse problem can be solved in obtaining the three‐dimensional distribution of the current source density in the ground. However, an annihilator can be added to the inverted source geometry without affecting the measured self‐potential field. Annihilators can be obtained from boundary conditions. Synthetic models and a sandbox experiment are discussed to demonstrate the validity of the algorithm. An application is presented to the geothermal field of Cerro Prieto, Baja California, Mexico, using literature data. Inversion of the self‐potential and resistivity data allows observing a plume of hot groundwater rising to the ground surface in the central part of the investigated area and discharging to the ground surface in the southwest part. The temperature anomaly associated with the existence of this plume is independently observed by interpolating borehole temperature measurements. We found a good agreement between the distribution of the temperature and the inverted source current density. The proposed method appears therefore as a noninvasive method for remote detection and three‐dimensional mapping of subsurface groundwater flow.