## 3 Results
### Current Status, Challenges and Future Developments
#### 3.2.2 Renewable Hydrogen Storage  
Within the HVC, storage represents a key research focus, with 25 of the 177 reviewed papers dedicated to this stage. As a versatile energy vector, renewable hydrogen requires intermediate storage between production and end use to ensure availability during periods without renewable energy input. Two primary storage methods are identified, depending on capacity and temporal requirements. Short-term storage, typically lasting days or weeks (e.g., 10-day supply), is achieved using pressurized tanks designed to handle frequent charge/discharge cycles ([PERSON], 2018). For long-term or inter-seasonal storage, underground geological formations--such as salt domes and depleted gas reservoirs--offer significantly greater capacity, often in the multi-megawatt range ([PERSON], 2018). Due to their spatial efficiency and large-scale capacity, underground storage options have attracted greater research interest, accounting for 10 of the 25 papers in the storage cluster. GIS emerges as the predominant geospatial tool in this context, often integrated with advanced methods like Multi-Criteria Decision Making (MCDM). Interest in subsurface hydrogen storage has also led to studies on natural hydrogen reservoirs. A total of 11 papers focus on this area, including topics such as the formation mechanisms (4 papers), characterization of underground cavities (3 papers), and detection via surface leakages (4 papers). While GIS remains widely used, additional geospatial \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Application** & **Ref.** & **Main Geospatial** & **Primary Uses of the** & **Challenges** \\ \hline Resource mapping & [(54; 56; 78)] & GIS + Remote & Spatial assessment of solar irradiance, wind potential, terrain suitability & Cloud cover in imagery; inconsistent grain granularity \\ \hline IoT monitoring & [(55; 79; 80; 81; 82)] & GIS + IoT Sensors & Real-time performance tracking, system automation, predictive maintenance & Sensor calibration and failure; infrastructure cost in remote areas \\ \hline Clustering & [(55; 73; 83)] & GIS + Clustering Algorithms & Aggregation and mapping of high-potential production zones using big data & Need for harmonized cross-sectoral datasets \\ \hline Techno-economic modeling & [(84; 85; 86; 87; 88; 89; 90; 91; 92; 93)] & GIS + Economic Simulation Models & Spatialized cost analysis of hydrogen supply configurations & Lack of integration between spatial and financial models \\ \hline \hline \end{tabular}
\end{table} 
Table 5: _Cont._techniques--such as geophysics for subsurface imaging and IoT for monitoring thermophysical properties--have also been applied. Spatial analysis of the literature reveals geographic concentrations: Spain and France lead in studies on natural hydrogen, particularly in the Pyrenees region (3 papers). Poland features prominently due to the presence of salt domes suitable for underground storage (3 papers). Other studies are located in high solar potential regions (including Iran, Algeria, Australia, Portugal, and Italy) highlighting the prevalent view of solar energy surplus as a key driver for hydrogen production. A summary of the papers found regarding hydrogen storage is shown in Table 6.  
Table 6 provides a structured overview of the main geospatial techniques applied in various aspects of renewable hydrogen storage research and development. GIS, IoT, and advanced computational approaches (e.g., ML, CV) play a central role across different application domains. GIS-based multi-criteria decision-making is critical for identifying optimal storage locations by integrating diverse environmental, technical, and socio-economic factors. As an example, [PERSON], [PERSON] et al. [99] apply a convolutional neural network (CNN) to generate suitability maps for hydrogen storage in salt deposits. Twelve criteria were determined for the MCDM, classified as evaluation and exclusion criteria.