| Issue |
EPJ Web Conf.
Volume 369, 2026
4th International Conference on Artificial Intelligence and Applied Mathematics (JIAMA’26)
|
|
|---|---|---|
| Article Number | 02002 | |
| Number of page(s) | 13 | |
| Section | XAI and Data-Driven Optimization in Energy, Environment, and Economic Systems | |
| DOI | https://doi.org/10.1051/epjconf/202636902002 | |
| Published online | 13 May 2026 | |
https://doi.org/10.1051/epjconf/202636902002
Unlocking the potential of Explainable climate-risk economics for agriculture and water stress in Uzbekistan
1 Department of Economics. Tashkent institute of irrigation and agricultural mechanization engineers. National research university, 39, Kary Niyazi str., Tashkent, Uzbekistan
2 Department of HR and personnel development. Nordic International University. 290, Farabi str., Tashkent, Uzbekistan.
* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.
Published online: 13 May 2026
Abstract
This is a mixed-method research design aimed at investigating the role of explainable climate-risk assessment in agriculture and water management on the resilience outcomes for smallholder farmers among rural farming communities. The main objective of this study is to find out that the development of explainable climate-risk models needs no extra financial burden, but has a great role in improving adaptive decision-making. This study aimed at investigating the impact of a climate-risk prioritization framework on agricultural planning and water allocation in different levels of drought exposure in Uzbekistan. In addition, the AHP analysis showed that irrigation efficiency and crop diversification are the two major adaptation practice priorities that are statistically significant predictors of farm survival probability. The method of the study was quasi-experimental and the intervention action was performed in two treatment groups; conventional risk assessment was employed in one group and in the other group, the same method together with explainable climate-risk dashboards for farmers were employed. The results showed that AHP’s weighted index (β = 0.42, p ≤ 0.05) significantly improved the farmers’ adaptive capacity in drought-prone districts. Results from parametric survival analysis revealed a positive and statistically significant relationship between farmers’ risk beliefs and the probability for sustained agricultural productivity among irrigated farms. Overall, the research result can impact policymakers in regional water authorities to review and enhance their risk governance strategies and provide a better understanding of the importance of farmers’ risk perception mechanisms toward agriculture’s climate resilience that supports sustainable production and efficient water use in Uzbekistan.
Key words: Explainable Climate-Risk Assessment / Agricultural Adaptation / Water Stress Management / Smallholder Farmers / Analytic Hierarchy Process (AHP) / Parametric Survival Analysis / Climate Resilience in Uzbekistan
© The Authors, published by EDP Sciences, 2026
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.

