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 ba...
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| Language: | English |
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Elsevier
2025-03-01
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| Series: | Results in Control and Optimization |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666720725000050 |
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| author | Sabas Patrick Silas Mirau Isambi Mbalawata Judith Leo |
| author_facet | Sabas Patrick Silas Mirau Isambi Mbalawata Judith Leo |
| author_sort | Sabas Patrick |
| collection | DOAJ |
| description | 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 (X1), soil moisture (X2), minimum temperature (X3), maximum temperature (X4), and relative humidity (X5) 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. |
| format | Article |
| id | doaj-art-a564f09eeae74f239e8f95a5bcca52ee |
| institution | Kabale University |
| issn | 2666-7207 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Results in Control and Optimization |
| spelling | doaj-art-a564f09eeae74f239e8f95a5bcca52ee2025-01-12T05:26:08ZengElsevierResults in Control and Optimization2666-72072025-03-0118100519Sensitivity analysis and uncertainty quantification of climate change effects on Tanzanian banana crop yieldSabas Patrick0Silas Mirau1Isambi Mbalawata2Judith Leo3School of Computational and Communication Science and Engineering, Nelson Mandela African Institution of Science and Technology (NM-AIST), P.O. Box 447, Arusha, Tanzania; Correspondence to: The Nelson Mandela African Institution of Science and Technology, P.O. Box 447, Arusha, Tanzania.School of Computational and Communication Science and Engineering, Nelson Mandela African Institution of Science and Technology (NM-AIST), P.O. Box 447, Arusha, TanzaniaAfrican Institute for Mathematical Sciences, Kigali, RwandaSchool of Computational and Communication Science and Engineering, Nelson Mandela African Institution of Science and Technology (NM-AIST), P.O. Box 447, Arusha, TanzaniaConcerns 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 (X1), soil moisture (X2), minimum temperature (X3), maximum temperature (X4), and relative humidity (X5) 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.http://www.sciencedirect.com/science/article/pii/S2666720725000050Sensitivity analysisUncertainty quantificationClimate variablesBanana crop yieldRegression modelMonte Carlo simulation |
| spellingShingle | Sabas Patrick Silas Mirau Isambi Mbalawata Judith Leo Sensitivity analysis and uncertainty quantification of climate change effects on Tanzanian banana crop yield Results in Control and Optimization Sensitivity analysis Uncertainty quantification Climate variables Banana crop yield Regression model Monte Carlo simulation |
| title | Sensitivity analysis and uncertainty quantification of climate change effects on Tanzanian banana crop yield |
| title_full | Sensitivity analysis and uncertainty quantification of climate change effects on Tanzanian banana crop yield |
| title_fullStr | Sensitivity analysis and uncertainty quantification of climate change effects on Tanzanian banana crop yield |
| title_full_unstemmed | Sensitivity analysis and uncertainty quantification of climate change effects on Tanzanian banana crop yield |
| title_short | Sensitivity analysis and uncertainty quantification of climate change effects on Tanzanian banana crop yield |
| title_sort | sensitivity analysis and uncertainty quantification of climate change effects on tanzanian banana crop yield |
| topic | Sensitivity analysis Uncertainty quantification Climate variables Banana crop yield Regression model Monte Carlo simulation |
| url | http://www.sciencedirect.com/science/article/pii/S2666720725000050 |
| work_keys_str_mv | AT sabaspatrick sensitivityanalysisanduncertaintyquantificationofclimatechangeeffectsontanzanianbananacropyield AT silasmirau sensitivityanalysisanduncertaintyquantificationofclimatechangeeffectsontanzanianbananacropyield AT isambimbalawata sensitivityanalysisanduncertaintyquantificationofclimatechangeeffectsontanzanianbananacropyield AT judithleo sensitivityanalysisanduncertaintyquantificationofclimatechangeeffectsontanzanianbananacropyield |