Research on World Agricultural Economy

Building Resilience in Jordan’s Agriculture: Harnessing Climate Smart Practices and Predictive Models to Combat Climatic Variability

Anber Abraheem Shlash Mohammad

Digital Marketing Department, Faculty of Administrative and Financial Sciences, Petra University, Amman 961343, Jordan

Suleiman Mohammad

Electronic Marketing and Social Media, Economic and Administrative Sciences Zarqa University, Zarqa 13110, Jordan; University Department, INTI International University, Nilai 71800, Negeri Sembilan, Malaysia

Khaleel Ibrahim Al‑ Daoud

Department of Accounting, Business School Faculties, Al Ahilya Amman University, Amman 19111, Jordan

Badrea Al Oraini

Business Administration Department, Collage of Business and Economics, Qassim University, Buraydah 52571, Qassim, Saudi Arabia

Asokan Vasudevan

Faculty of Business and Communications, INTI International University, Nilai 71800, Negeri Sembilan, Malaysia

Zhidong Feng

Faculty of Liberal Arts, Shinawatra University, Pathum Thani 12160, Thailand

DOI: https://doi.org/10.36956/rwae.v6i2.1628

Received: 25 December 2024 | Revised: 6 January 2025 | Accepted: 24 January 2025 | Published Online: 3 April 2025

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Abstract

Agriculture in Jordan is increasingly vulnerable to climatic variability, including rising temperatures, erratic precipitation, and frequent extreme weather events, threatening crop yields and food security. This study assessed the impacts of climatic factors, evaluated the effectiveness of climatesmart agricultural practices, and explored future scenarios using predictive models. A mixedmethods approach was employed, combining quantitative regression analysis, ANOVA tests, qualitative content analysis, scenario modelling, and geospatial mapping. Regression analysis showed that climatic factors explain 83.2% of the variability in crop yields (R² = 0.832). Temperature and precipitation had positive and significant effects (coefficients: 0.421 and 0.206, p < 0.01), while extreme weather events significantly reduced yields (coefficient: 2.227, p < 0.01). ANOVA revealed no significant differences in crop yields across low, medium, and high adoption levels of climatesmart practices (F = 0.272, p = 0.762), suggesting suboptimal implementation. Qualitative analysis identified key barriers such as water scarcity, financial constraints, and knowledge gaps, alongside opportunities like drip irrigation and crop diversification. Scenario analysis projected yield variations ranging from 64.69 tons/ha in optimistic scenarios to 40.89 tons/ha in pessimistic ones, highlighting the importance of adaptive measures. Geospatial analysis identified regional hotspots with low yields, correlating with climatic stress. These findings emphasize the need for regionspecific interventions, enhanced capacity building, and financial support to optimize climatesmart practices. Predictive models proved valuable for planning under future climatic uncertainties. This study provides actionable insights for developing a resilient agricultural sector in Jordan, aligning with global food security and climate adaptation goals.

Keywords: Agriculture; Jordan; Climate Change; Resilience; ClimateSmart Practices; Predictive Models

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