Earth Observation for Sustainable Agricultural Water Management
A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "New Sensors, New Technologies and Machine Learning in Water Sciences".
Deadline for manuscript submissions: 30 June 2026 | Viewed by 215
Special Issue Editors
Interests: geomatics; precision agriculture; remote sensing; irrigation management; environ-mental monitoring
Interests: UAV; precision agriculture; remote sensing; irrigation management; modelling of crop water demand
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Sustainable management of agricultural water resources represents one of the most pressing challenges for global food security and environmental resilience. Increasing pressures from climate variability, population growth, and intensified agricultural practices demand innovative approaches for monitoring and optimizing water use. In this context, Earth Observation (EO) and remote sensing technologies have emerged as powerful tools to support informed decision-making, improve irrigation efficiency, and enhance the sustainability of agricultural systems at multiple spatial and temporal scales.
This Special Issue aims to bring together cutting-edge research, methodological advances, and practical applications that leverage EO data and related technologies for sustainable agricultural water management. In particular, we welcome contributions that explore the integration of EO data with ground-based measurements, modeling frameworks, and data analytics techniques to assess and manage water use across diverse agroecosystems.
For this reason, we invite high-quality interdisciplinary studies that include (but are not limited to) the following areas:
- Applications of multispectral, hyperspectral, thermal, and SAR data for estimating crop evapotranspiration, plant water status, and irrigation performance;
- Mapping irrigated areas and assessing spatiotemporal dynamics of agricultural water demand;
- Soil moisture retrieval, land surface energy balance modeling, and soil–plant–atmosphere interactions in irrigated systems;
- Integration of EO data within situ sensors, meteorological records, and hydrological models for irrigation management and water allocation;
- Data fusion, artificial intelligence, and machine learning approaches for water-use monitoring and decision support;
- Development of operational tools, platforms, and services supporting precision irrigation and policy design for sustainable water governance.
We look forward to receiving your contributions.
Dr. Grazia Tosi
Dr. Alessandra Vinci
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Water is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- earth observation
- water demand
- precision agriculture
- remote sensing
- machine learning
- sustainable water management
- soil-plant-atmosphere interactions
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