Climate Risk in Agriculture, Analysis, Modeling and Applications

A special issue of Climate (ISSN 2225-1154).

Deadline for manuscript submissions: 31 December 2025 | Viewed by 250

Special Issue Editors


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Guest Editor
Laboratory of General and Agricultural Meteorology, Department of Crop Science, Agricultural University of Athens, 11855 Athens, Greece
Interests: environment; environmental impact assessment

Special Issue Information

Dear Colleagues,

Climate risk in agriculture is one of the important issues determining the food security, livelihood of communities, and ecosystem sustenance throughout the world. Because temperature is rising, extreme events such as droughts, floods, and heat waves will further affect agriculture.

Climate risk analysis and modeling involve understanding the interdependency between complex climate parameters and agricultural systems. Similarly, some advanced modeling techniques for crop and climate impact assessment can help simulate and project the most likely impacts of strategic adaptation actions.

Applications of climate risk modeling in crop resilient practices and management, optimization of irrigation practices, and implementation of sustainable farming techniques will be worked out. Climate risk analysis can also serve as a very useful tool for effective and equitable agricultural insurance services. By incorporating climate risk analysis into agricultural planning, we can make farming communities more resilient and ensure food security in this era of climate change.

Dr. Ioannis Charalampopoulos
Dr. Fotoula Droulia
Guest Editors

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Keywords

  • agriculture
  • climate change
  • drought/flood
  • irrigation
  • food-water-energy nexus
  • pest management
  • organic farming
  • agro technology

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Published Papers (1 paper)

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Review

26 pages, 4911 KB  
Review
Hail Netting in Apple Orchards: Current Knowledge, Research Gaps, and Perspectives for Digital Agriculture
by Danielle Elis Garcia Furuya, Édson Luis Bolfe, Franco da Silveira, Jayme Garcia Arnal Barbedo, Tamires Lima da Silva, Luciana Alvim Santos Romani, Letícia Ferrari Castanheiro and Luciano Gebler
Climate 2025, 13(10), 203; https://doi.org/10.3390/cli13100203 (registering DOI) - 28 Sep 2025
Abstract
Hailstorms are a major climatic threat to apple production, causing substantial economic losses in orchards worldwide. Anti-hail nets have been increasingly adopted to mitigate this risk, but the scientific literature on their effectiveness and future applications remains scattered, especially considering advances in digital [...] Read more.
Hailstorms are a major climatic threat to apple production, causing substantial economic losses in orchards worldwide. Anti-hail nets have been increasingly adopted to mitigate this risk, but the scientific literature on their effectiveness and future applications remains scattered, especially considering advances in digital agriculture. This study synthesizes current knowledge on the use of anti-hail nets in apple orchards through a systematic review and explores future perspectives involving digital technologies. A PRISMA-based review was conducted using three databases, revealing information regarding the studied countries, netting colors, and apple varieties, among others. A clear research gap was identified in integrating anti-hail nets with remote sensing and Artificial Intelligence (AI). This paper also analyzes studies from Vacaria, Brazil, a key apple-producing region and part of the Semear Digital project, highlighting local efforts to use hail netting in commercial orchards. Potential applications of AI algorithms and remote sensing are proposed for hail netting assessment, orchard monitoring, and decision-making support. These technologies can improve predictive modeling, quantify areas, and enhance precision management. Findings suggest combining traditional protective methods with technological innovations to strengthen orchard resilience in regions exposed to extreme weather. Full article
(This article belongs to the Special Issue Climate Risk in Agriculture, Analysis, Modeling and Applications)
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