Smart and Precision Farming for Climate-Resilient Water and Land Management

A special issue of Earth (ISSN 2673-4834).

Deadline for manuscript submissions: 1 October 2026 | Viewed by 924

Special Issue Editors


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Guest Editor
Department of Agriculture, University of Patras, 30200 Messolonghi, Greece
Interests: soil inorganic carbon (SIC); soil and water conservation engineering; soil spectroscopy; heavy metals accumulation; soil genesis; innovations and techniques in soil and plant analysis; non-destructive techniques for soil testing
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Guest Editor
Department of Agriculture, University of Patras, 30200 Messolonghi, Greece
Interests: fluid mechanics; computational fluid dynamics; porous media flow

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Guest Editor
Department of Surveying and Geoinformatics Engineering, University of West Attica, 28 Ag. Spiridonos, Egaleo, 12243 Athens, Greece
Interests: geographic information science; geoinformatics; geographic information systems; cartography; geodemography; VGI; geoarchaeology; spatial analysis in physical geography and human geography; modeling of natural phenomena and disasters; citizen science
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Special Issue Information

Dear Colleagues,

Climate variability is exacerbating drought, heat stress, desertification and freshwater availability in agricultural regions worldwide. In this scenario, the agricultural sector must increase productivity, reduce environmental impacts and ensure economic sustainability simultaneously. Technology-based smart and precision farming, using sensing, geospatial, decision support, automation and data-driven irrigation and fertilizer use, can offer solutions in this area.

The Special Issue, titled ‘Smart and Precision Farming for Climate-Resilient Water and Land Management,’ encourages original articles, review papers, methodological contributions and case studies that explore applications of digital agriculture, precision agronomy and smart monitoring/forecasting platforms that might serve for sustainable water resource management, soil preservation, carbon-efficient farming and more effective climate change resilience at the field scale, farm scale, basin scale and regional scale. Applications that connect technology to real-world problems in agronomy, the environment and policy are especially invited. Agriculture occupies the land–water–climate triangle. The unpredictability of rainfall, increasing occurrences of climate-related extremes, waterlogged conditions caused by over-irrigation, increasing soil salinization, and the acceleration of evapotranspiration rates are pushing the conventional management system beyond its limits.

“Average-year” planning on the usual traditional basis is no longer adequate. Here, there is a need for adaptive systems. The systems should be able to detect stress in near-real time, predict risk before a loss occurs and offer suggestions for actions that save water, protect soils and preserve yield. Technologies for smart and precision agriculture have developed at an incredible pace in the mentioned area. These include the following: proximal and remote sensing of crop conditions and soil water status; the carrying out of “Fert-irrigations” through “variable rating irrigations”; decision-support systems through Edge computing as well as through Cloud computing;  the conducting of “GNSS-guided” operations on the farm; the installation of “Internet of Things” sensors; “Climate, Hydrology and Crop Growth” blends through “AI/ML” techniques and the creation of “Digital Twin” models for the “Farms” as well as for the “Watershed”.

This Special Issue aims to showcase the science, technology and practice of cutting-edge science at this juncture. Of special interest are research that (i) estimate benefits (water saved, yield maintained, emissions reduced), (ii) address uncertainties explicitly (e.g., probabilistic seasonal forecasts, probabilistic drought alerts, climate scenarios) and/or (iii) demonstrate real-world scaling and deployment.

Dr. Dimitrios E. Tsesmelis
Prof. Dr. Pantelis E. Barouchas
Dr. Georgios Bourantas
Dr. Kleomenis Kalogeropoulos
Guest Editors

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Keywords

  • precision agriculture
  • smart farming
  • climate resilience in farming
  • carbon farming
  • remote sensing for crops
  • digital soil
  • decision support systems in agriculture
  • smart irrigation management

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Published Papers (1 paper)

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Research

27 pages, 22570 KB  
Article
Development of High-Resolution Agroclimatic Zoning Method to Determine Micro-Agroclimatic Zones in Greece
by Nikolaos-Fivos Galatoulas, Dimitrios E. Tsesmelis, Angeliki Kavga, Kleomenis Kalogeropoulos and Pantelis E. Barouchas
Earth 2026, 7(2), 61; https://doi.org/10.3390/earth7020061 - 9 Apr 2026
Viewed by 326
Abstract
Climate variability and rising water scarcity are major challenges to agricultural sustainability, particularly in Mediterranean climates with high spatial heterogeneity. Agroclimatic zoning is a fundamental analytical tool for digital agriculture and climate-resilient agriculture. The current effort proposes an integrated agroclimatic and micro-agroclimatic zoning [...] Read more.
Climate variability and rising water scarcity are major challenges to agricultural sustainability, particularly in Mediterranean climates with high spatial heterogeneity. Agroclimatic zoning is a fundamental analytical tool for digital agriculture and climate-resilient agriculture. The current effort proposes an integrated agroclimatic and micro-agroclimatic zoning approach for Greece, based on the Aridity Index (AI), CORINE Land Cover 2018 land-use data, and topographic factors. Daily precipitation and reference evapotranspiration data from 139 meteorological stations and 382 rain gauges were spatially interpolated using Empirical Bayesian Kriging, identifying eight agroclimatic classes adapted to the country’s specific conditions. The results indicate a high degree of variability in space, with most agricultural areas being classified as dry to sub-humid, suggesting higher irrigation requirements and sensitivity to drought. Micro-agroclimatic zones have been identified by combining agroclimatic classes, land use, and elevation. Consequently, the derived zones can be used as groundwork for designing methodologies towards more efficient agrometeorological monitoring through the improved localization of IoT agrometeorological stations. Validation with the Köppen–Geiger climate classification reveals high spatial and statistical agreement (χ2 = 248,454.09, df = 49, p < 0.001), proving the climatic validity of the proposed approach and its higher sensitivity to local water balance conditions. Full article
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