Based on a multi-scale and hydrostructural approach, this study presents the most relevant methodology to be applied to a karst hydrosystem in order to get a full understanding of underground water flow. It implies a complete structural analysis, from the hydrosystem scale to the outcrop scale, including the intermediate scale of the major geological structures. We illustrate the method in the Arcier hydrosystem, in the northwestern border of the Jura fold-and-thrust belt (Eastern France).Field mapping and structural analysis allow to update the geological vision of the hydrosystem with two kink-type fault propagation folds, including a trishear kinematic model, on either side of a plateau presenting a hollow-and-dome configuration. Fracturing analysis reveals a fault-fracture network that we infer governs the entire hydrosystem. A Riedel pattern is highlighted, characterized by a N-S-striking (N355°±5), sinistral strike-slip, regional shear zone. Then, two 3D geological models, at different scales, constructed with MOVE and Visual Karsys softwares are combined with water levels and artificial tracer tests. It reveals a multilayer aquifer and a redefinition of groundwater circulations for the Arcier hydrosystem.The results demonstrate a strong geological control of karstic hydrosystems on groundwater circulations, proving that classical hydrogeological methods, such as natural and/or artificial tracers, must be combined with rigorous geological analysis. Moreover, the multi-scale approach provides an explanation of groundwater circulation based on the intersection between 3D geometry of impervious layers delimiting the aquifers and their base water level, instead of the 2D view (section or map) requiring systematic recourse to inferred vertical faults to cross permeability barriers vertically or laterally. This study also brings a new vision to the local protection of the water resource.

Shallow groundwater resources, especially in hard rock environment, constitute an important part of urban water supply in developing countries, appropriate to the low level of economic development. However, increasing urban population and dependence on shallow groundwater systems make it imperative to evaluate the availability and the contamination of these resources, and define new strategies of water exploitation taking into accounts these findings and constrains. This study has been carried out on the shallow groundwater of Yaounde, Central Africa. Based on head slug-in tests, chemical and isotope analyses, we demonstrate the importance of geomorphological settings that constrain hydrogeology, urban occupation and therefore, water exploitation and contamination. Slug test results show spatial variability of well recovery rates with higher values recorded in the valleys compare to the hills, presenting saturated hydraulic conductivity of 10 –6 –10 –8 m/s. Groundwater evolves from recharge zone as Ca–HCO 3 in the hillside lateritic system to discharge zone in the slope/valley colluvium/alluvium system as NaK–NO 3 . The groundwater composition dominated by silicates/water interaction in the hillside lateritic system, and anthropogenic processes in the slopes and valleys. δ 15 N and δ 18 O of nitrates indicates that nitrate pollution of groundwater is mainly from sewage and human waste. Shallow groundwater resources in the hillside/new urban districts and to a lesser extent slopes should therefore be protected and prioritised for usability and sustainability. The proposed conceptual scheme for Yaounde can then be used as a guide in the development, exploitation and management of local wells in hard rocks system of Africa.

Unlike surface water reservoirs, that can be easily quantified and monitored, underground conduits in karst systems are often inaccessible, hence challenging to monitor. Seismic noise analysis was proved to be a reliable tool to monitor ground water storage in a fractured rock aquifer (Lecocq et al. 2017). In underground karstic environments, seismic noise monitoring was able to detect hydrological cycles and monitor the groundwater-content variations (Almagro Vidal et al. 2021). The following approach relies on coupling passive seismic wavefield with hydrological data in a machine learning algorithm in order to monitor underground water heights. The studied site is the Fourbanne karst aquifer (Jura Mountains, Eastern France, Jurassic Karst observatory). The underground conduit is accessible through a drilled shaft and instrumented by two 3-component seismological stations, one located underground and the other one at the surface, and a water height probe. We applied a new approach based on the machine learning random forest (RF) algorithm and continuous seismic records (Hibert et al., 2017), to find characteristic signals to predict the underground river water height. The method consists on the computation on a sliding window of seismic signal features (waveform, spectral and spectrogram features) and using the corresponding water height at the same time window to train the algorithm, and then apply it on new data. The RF algorithm is capable of accurately detecting flooding periods and reproduce the groundwater heights with an efficiency exceeding 95% and 53% using the Nash-Sutcliffe criterion for the seismic stations located in the underground conduit and at the surface respectively. The obtained results are a first promising outcome for the remote study of water circulation in karst aquifers using seismic noise.