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トルコ農業部門におけるトリプル・サステナビリティ・ダイナミクス：温室効果ガス排出量、水強度、経済動態に関する2030年までの予測

The Triple Sustainability Dynamic in Türkiye's Agricultural Sector: Projections Until 2030 on Greenhouse Gas Emissions, Water Intensity, and Economic Dynamics (原題)

Erkin Cihangir Karataş

Selcuk Journal of Agriculture and Food Sciences📚 査読済 / ジャーナル2026-08-21#agriculture対象セクター: agriculture
DOI: 10.15316/selcukjafsci.1913181
原典: https://doi.org/10.15316/selcukjafsci.1913181

🤖 gxceed AI 要約

日本語

トルコ農業の持続可能性を、温室効果ガス排出量・水使用量・経済の3側面から2030年まで予測。Prophet時系列モデルと3シナリオを用い、国際機関予測が最も現実的と判明。水強度は29.9%減少し、排出量との逆相関を確認。政策提言として点滴灌漑、有機農業、スマート農業を提案。

English

This study projects Türkiye's agricultural sustainability to 2030, analyzing GHG emissions, water intensity, and economic dynamics. Using the Prophet model with three scenarios, it finds international projections most realistic, predicts a 29.9% decline in water intensity, and reveals inverse correlations with emissions. Recommends drip irrigation, organic farming, and smart agriculture.

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

📝 gxceed 編集解説 — Why this matters

日本のGX文脈において

日本では農業分野のGXは食料安全保障と関連し、スマート農業技術の導入が進む。本予測手法は日本の農業政策にも応用可能で、水資源管理と排出削減の両立に示唆を与える。

In the global GX context

This study contributes to global agricultural decarbonization literature by integrating water and economic dimensions. Its scenario-based forecasting approach offers a model for other countries, aligning with climate-smart agriculture goals under the Paris Agreement.

👥 読者別の含意

🔬研究者:Provides a data-driven framework for agricultural sustainability forecasting, useful for comparative studies.

🏢実務担当者:Offers policy recommendations (drip irrigation, organic farming) that can guide corporate sustainability strategies in agribusiness.

🏛政策担当者:Highlights the need for integrated water-emissions planning in agricultural policy, relevant for national climate strategies.

📄 Abstract（原文）

This study aims to make predictions for the sustainability dynamics of Türkiye's agricultural sector until 2030, considering agricultural water use, greenhouse gas emissions, and agricultural economics from a three-pronged perspective. Predictions were made using data covering the years 1992-2022 based on greenhouse gas emissions and water intensity. Emissions were used in carbon equivalent (Mt CO2e), and water intensity in km³/billion USD. The analysis was conducted using the Prophet time series model across three scenarios. The scenarios were defined as Prophet estimate, international organization estimate, and linear decline. The relationships between variables were evaluated using correlation-based network analysis, and then regressive effects were tested using sensitivity analysis. Based on the findings, the international projections used in Scenario 2 (3.5%) showed that the share of agriculture in GDP would be 78.75 Mt CO2e in 2030. It was determined that this gave the most realistic value compared to the other two scenarios. The analysis findings also predicted that Türkiye's agricultural water intensity will decrease by 29.9% to 0.0379 km³/billion USD by 2030. Correlation analysis also revealed a strong positive correlation between water intensity and the share of agriculture, with a value of 0.87. Furthermore, it showed inverse relationships with greenhouse gas emissions, with values of -0.70 and -0.55, respectively. Subsequent sensitivity analysis confirmed that the impact of water intensity on the model is limited. The study, which offers a data-driven framework for Türkiye's agricultural policies, suggests focusing on drip irrigation, organic farming, and smart farming technologies as policy recommendations.

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