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

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 fu- ture 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 sub-optimal 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 pro-jected 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 ca-pacity 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.