Geocarto International

Integrated Geospatial Intelligence for Sustainable Groundwater Assessment and Management Using Multi-Source Earth Observation, Geophysics, and Artificial Intelligence

Geocarto International is pleased to welcome you to submit your research to the Article Collection "Integrated Geospatial Intelligence for Sustainable Groundwater Assessment and Management Using Multi-Source Earth Observation, Geophysics, and Artificial Intelligence".

Groundwater is essential for water security, ecosystem stability, food production, and socioeconomic development, especially in arid and hyper-arid regions where surface-water availability is limited and highly variable. Many aquifers extend across national boundaries and are characterized by complex geological settings, sparse monitoring, and increasing pressure from agricultural expansion, urban growth, industrial activities, climate variability, and intensive groundwater abstraction. Advances in Earth observation, geographic information systems (GIS), satellite gravimetry, geophysical methods, cloud-based geospatial platforms, and artificial intelligence now offer powerful means of investigating groundwater systems beyond the constraints of conventional point-based measurements. The integration of these technologies enables improved assessment of groundwater-storage changes, aquifer architecture, recharge, groundwater potential, quality, and anthropogenic impacts across a range of spatial scales.

Sustainable groundwater management increasingly depends on integrated and spatially explicit assessments that link surface environmental conditions with subsurface hydrogeological processes. This is particularly critical in data-limited and transboundary aquifers, where sparse monitoring, geological heterogeneity, uncertain recharge, and competing demands make resource evaluation challenging. Geospatial methods can provide spatially continuous and temporally consistent information that complements field observations, geophysical investigations, hydrochemical analyses, and numerical modelling. The combined use of multi-source Earth observation, advanced spatial analysis, and machine learning can further support groundwater-potential assessment, depletion monitoring, vulnerability mapping, prediction, scenario evaluation, and decision-making. These capabilities are highly relevant to climate adaptation, water security, sustainable agriculture, ecosystem conservation, and progress toward the Sustainable Development Goals (SDGs).

This Article Collection seeks innovative contributions on the use of remote sensing, GIS, geophysics, geospatial artificial intelligence, and related technologies for groundwater assessment and sustainable management in arid, semi-arid, and transboundary settings. Relevant topics include:

• Satellite-based monitoring of groundwater and terrestrial water storage;
• Groundwater-potential and vulnerability mapping;
• Structural and hydrogeophysical characterization of aquifers;
• Satellite gravity and magnetic applications;
• Integration of optical, thermal, and radar observations;
• Hydrochemical and isotope investigations;
• Groundwater-quality assessment;
• Recharge estimation and flow-path characterization;
• Machine learning and deep learning for groundwater prediction;
• Cloud-based geospatial computing and Google Earth Engine;
• Coupling remote sensing with numerical groundwater models;
• Assessment of climatic and anthropogenic pressures;
• Geospatial decision-support tools for Integrated Water Resources Management.

Studies introducing new datasets, methodological advances, validation strategies, regional applications, comparative analyses, or transferable workflows are particularly encouraged. The Collection welcomes original research articles as well as scientific and technical review papers that fall within the journal’s scope.

Meet the Guest Advisors

Dr. Youssef M. Youssef is an Assistant Professor of Remote Sensing and Geoinformatics at Suez University, Egypt, with research interests spanning remote sensing, GIS, geophysics, hydrogeology, groundwater resources, environmental monitoring, and geospatial modelling. His research focuses on integrating Earth observation, geospatial analysis, machine learning, and hydrogeophysical techniques to investigate water resources and environmental challenges in arid and data scarce regions.

Dr. hab. Dominika Dąbrowska is an Associate Professor in the Institute of Earth Sciences at the University of Silesia in Katowice, Poland. A unique researcher with a highly interdisciplinary background, she holds master’s degrees in Geology and Mathematics, along with postgraduate qualifications in Computer Science and an MBA in Innovation and Data Analysis. Her work focuses primarily on groundwater protection, hydrogeology, and environmental risk assessment.

The Guest Advisors declare no conflict of interest regarding this work.