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<p>Rainfall variability and prolonged wet or dry spells increasingly threaten rain-fed agriculture in tropical highland regions where microclimatic conditions strongly influence crop productivity. However, studies related to variability and trends of rainfall, consecutive wet and dry days at the microclimate level remains limited in most of the tropical regions, despite its critical importance in agricultural planning. In this study, we used daily rainfall and temperature data obtained from Rwanda Meteorology Agency (1983–2021) and delineated Nyaruguru District into four near-homogeneous zones using K-means clustering techniques. Thereafter, we analysed mean, variability and trends for rainfall, consecutive wet days (CWD) and consecutive dry days (CDD) in these four microclimate zones. Variability was assessed using the coefficient of variation, while trends were detected using the modified Mann–Kendall test and Theil–Sen slope estimator. Using Pearson correlation coefficient (r), linear regression and Bayesian regression model, we evaluated the relationships between four staple foods in the district (maize, beans, Irish potato and cassava) with rainfall, CWD and CDD variability. We found that highland zones (zone 2 and 4) are wetter and cooler, suitable for maize, beans and irish potatoes whereas eastern lowlands zones (Zone 1 and 3) are warmer and relatively drier, suitable for cassava. The March–May season has the most reliable rainfall with less variability (13–33%), while the June–August season is extremely dry and variable, with CDD reaching 77 days. Seasonal rainfall trends are generally weak, but localized annual increases occur in high-altitude areas (up to 26.9&#xa0;mm/ year). Pearson Correlation, regression and Bayesian regression model results indicate that variability in consecutive dry days, rainfall and consecutive wet days exhibits weak but statistically significant negative effect on crop productivity of maize, beans, Irish potato, and cassava. These findings underscore the urgent need to integrate microclimate-based analysis into agricultural planning through crop zoning, optimized planting calendars, and drought-tolerant varieties to strengthen climate resilience and food security.</p>

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Microclimate-based rainfall and consecutive wet and dry spells variability and trends for agricultural planning in a tropical highland: evidence from Nyaruguru District, Rwanda

  • 期刊论文

  • 发表日期：

    2026年6月24日

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  • Sylvere Kubwimana,
  • Nibizi Don Fleury

摘要

Rainfall variability and prolonged wet or dry spells increasingly threaten rain-fed agriculture in tropical highland regions where microclimatic conditions strongly influence crop productivity. However, studies related to variability and trends of rainfall, consecutive wet and dry days at the microclimate level remains limited in most of the tropical regions, despite its critical importance in agricultural planning. In this study, we used daily rainfall and temperature data obtained from Rwanda Meteorology Agency (1983–2021) and delineated Nyaruguru District into four near-homogeneous zones using K-means clustering techniques. Thereafter, we analysed mean, variability and trends for rainfall, consecutive wet days (CWD) and consecutive dry days (CDD) in these four microclimate zones. Variability was assessed using the coefficient of variation, while trends were detected using the modified Mann–Kendall test and Theil–Sen slope estimator. Using Pearson correlation coefficient (r), linear regression and Bayesian regression model, we evaluated the relationships between four staple foods in the district (maize, beans, Irish potato and cassava) with rainfall, CWD and CDD variability. We found that highland zones (zone 2 and 4) are wetter and cooler, suitable for maize, beans and irish potatoes whereas eastern lowlands zones (Zone 1 and 3) are warmer and relatively drier, suitable for cassava. The March–May season has the most reliable rainfall with less variability (13–33%), while the June–August season is extremely dry and variable, with CDD reaching 77 days. Seasonal rainfall trends are generally weak, but localized annual increases occur in high-altitude areas (up to 26.9 mm/ year). Pearson Correlation, regression and Bayesian regression model results indicate that variability in consecutive dry days, rainfall and consecutive wet days exhibits weak but statistically significant negative effect on crop productivity of maize, beans, Irish potato, and cassava. These findings underscore the urgent need to integrate microclimate-based analysis into agricultural planning through crop zoning, optimized planting calendars, and drought-tolerant varieties to strengthen climate resilience and food security.