Sensitivity analysis and uncertainty quantification of climate change effects on Tanzanian banana crop yield

Concerns about the impact of climate change on agricultural systems have heightened, particularly in regions where crop cultivation is essential for economic stability and sustenance. This research addresses a critical gap in understanding by investigating how climate change influences Tanzania’s bananas, a vital component of the country’s agricultural sector. The study used a multiple regression model to analyze the correlation between bananas and key climate variables in Tanzania, the results showed gradual decrease in bananas. Specifically, the climate variables, including precipitation ( X 1 ), soil moisture ( X 2 ), minimum temperature ( X 3 ), maximum temperature ( X 4 ), and relative humidity ( X 5 ) have coefficients 0.0206, -0.0085, 4.8328, -1.6594, and -0.0991, respectively. In this case, a large positive coefficient and a negligible negative coefficient show that the independent variable greatly influences the yield of the bananas. Additionally, the study utilize two powerful global sensitivity analysis methods, Sobol’ Sensitivity Indices and Response Surface Methodology, to comprehensively explore the sensitivity of bananas to climate variables. So, these methods revealed that minimum temperature, precipitation and soil moisture have the most impact on bananas and affect the crop’s production variability. Uncertainty quantification was performed using Monte Carlo simulation, estimating uncertainties in model parameters to enhance the reliability of the findings. This research not only contributes to our broader understanding of how climate change impacts bananas but also offers practical policy suggestions tailored to Tanzania’s unique context, ensuring resilience and sustainability in the face of environmental changes. The outcomes of this study carry significance for policymakers, stakeholders, and farmers, providing actionable insights to shape adaptive agricultural strategies. By bridging the gap between climate change and bananas, this research offers valuable contributions to the broader field of agricultural sustainability.

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Publication Details

Journal
Results in Control and Optimization
Published
2025-01-09
DOI
https://doi.org/10.1016/j.rico.2025.100519
Citations
3
Primary Topic
Sustainable Agricultural Systems Analysis
Type
article
Field-Weighted Citation Impact
2.58

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article

Sensitivity analysis and uncertainty quantification of climate change effects on Tanzanian banana crop yield

Judith Leo, Isambi Sailon Mbalawata, Silas Mirau, Sabas Patrick
3 citations
Results in Control and Optimization
Sustainable Agricultural Systems Analysis
2.58
article

Sensitivity analysis and uncertainty quantification of climate change effects on Tanzanian banana crop yield

Judith Leo, Isambi Sailon Mbalawata, Silas Mirau, Sabas Patrick
article en
3 citations

Abstract

Concerns about the impact of climate change on agricultural systems have heightened, particularly in regions where crop cultivation is essential for economic stability and sustenance. This research addresses a critical gap in understanding by investigating how climate change influences Tanzania’s bananas, a vital component of the country’s agricultural sector. The study used a multiple regression model to analyze the correlation between bananas and key climate variables in Tanzania, the results showed gradual decrease in bananas. Specifically, the climate variables, including precipitation ( X 1 ), soil moisture ( X 2 ), minimum temperature ( X 3 ), maximum temperature ( X 4 ), and relative humidity ( X 5 ) have coefficients 0.0206, -0.0085, 4.8328, -1.6594, and -0.0991, respectively. In this case, a large positive coefficient and a negligible negative coefficient show that the independent variable greatly influences the yield of the bananas. Additionally, the study utilize two powerful global sensitivity analysis methods, Sobol’ Sensitivity Indices and Response Surface Methodology, to comprehensively explore the sensitivity of bananas to climate variables. So, these methods revealed that minimum temperature, precipitation and soil moisture have the most impact on bananas and affect the crop’s production variability. Uncertainty quantification was performed using Monte Carlo simulation, estimating uncertainties in model parameters to enhance the reliability of the findings. This research not only contributes to our broader understanding of how climate change impacts bananas but also offers practical policy suggestions tailored to Tanzania’s unique context, ensuring resilience and sustainability in the face of environmental changes. The outcomes of this study carry significance for policymakers, stakeholders, and farmers, providing actionable insights to shape adaptive agricultural strategies. By bridging the gap between climate change and bananas, this research offers valuable contributions to the broader field of agricultural sustainability.

Results in Control and OptimizationVol. 18
African Institute for Mathematical Sciences (RW), Nelson Mandela African Institution of Science and Technology (TZ)
West African Science Service Centre on Climate Change and Adapted Land Use
Climate action
Openalex Percentile: Top 14%
Sustainable Agricultural Systems Analysis
2.58
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