The sustainable intensification of crop production in West Africa is constrained by soil degradation exacerbated by climatic factors such as excessive rainfall and high temperature. Adoption of climate-smart soil and crop management practices could buffer future extreme weather effects on maize yield. To test this hypothesis, the overarching aim of our study was to (i) calibrate and evaluation the DSSAT model for maize and parameterize the DSSAT tillage module for different tillage practices (contour ridge tillage and reduced tillage), and (ii) simulate the effects of different management options (tillage and crop residue incorporation) to buffer future extreme climate events on maize yield in four soil types (Lixisols and Plinthosols) located in two landscape positions (upslope and footslopes) of Benin and Burkina-Faso in West Africa, using two climate scenarios (baseline and 2 °C above pre-industrial period). Scenario analysis was performed using factorial combination of two tillage operations (contour ridge and reduced tillage), one crop residue treatment (with crop residue), and two N fertilizer rates (recommended N rate: 60 kg ha⁻¹ and double recommended N rate: 120 kg ha⁻¹) using HAPPI dataset.

Model performance (calibration, evaluation and tillage model parameterization) was good as indicated by the lower normalized root mean square error (nRMSE, 12 %–18 %) and mean root absolute error (MRAE, 10 %–16 %), and higher d-index (0.78−0.93) depending on tillage practices and soil types. Long term future climate simulations and cumulative probability distribution confirmed that with both fertilization cases (recommended and double recommended), contour ridge tillage along with crop residue application could enhance maize yield (4 %–7 %) at upslope field sites under a future 2 °C warming scenario, where soil erosion and loss of water and nutrients through runoff is a serious risk. Simultaneously, reduced tillage with crop residue application under both fertilization cases could be a valuable alternative to farmer’s practice in fields with deep soils at footslope position (St1 and St3), as it resulted in a higher increase of maize yield (14.5 %) under future 2 °C warming scenario compared to the baseline and could be preferred by risk-averse farmers. Maize production on gravelly soils with low water retention capacity (St1, 63−66 mm) may suffer (-11 %) from future 2 °C warming regardless of the tillage practice. However, despite the significant site-specific tillage effects, intensified N fertilizer application could reduce maize yield losses on St2, St3, and St4, irrespective of tillage practices by improving maize N uptake under elevated CO₂ during future warming period. Hence, the application of site-specific tillage operations and crop residue application has the potential to buffer future warming effects on maize yield as confirmed by DSSAT simulations.

西非农作物生产的可持续集约化受到土壤退化的影响，而土壤退化则是由于降雨过多和高温等气候因素而加剧的。采用气候智能型土壤和作物管理措施可以缓冲未来极端天气对玉米产量的影响。为了检验该假设，我们研究的总体目标是（i）校准和评估玉米的DSSAT模型，并针对不同耕作实践（等高垄耕和减耕）对DSSAT耕作模块进行参数设置，以及（ii）模拟效果在西非贝宁和布基纳法索的两个景观位置（上坡和下坡）的四种土壤类型（Lixisol和Plinthosols）中，采用不同的管理方案（耕作和作物残渣掺入）来缓冲未来极端气候事件对玉米产量的影响，使用两种气候情景（基线和比工业化前期高2°C）。使用两次耕作（轮廓垄和减少耕作），一种作物残渣处理（带有作物残渣）和两种氮肥用量（推荐氮肥用量：60 kg ha）的因子组合进行情景分析^-1，使用HAPPI数据集，建议的N倍增倍数：120 kg ha ^-1）。

模型性能（校准，评估和耕作模型参数设置）良好，这可以通过较低的归一化均方根误差（nRMSE，12％–18％）和均方根绝对误差（MRAE，10％–16％）以及更高的d来表明。-指数（0.78−0.93），具体取决于耕作方法和土壤类型。长期的未来气候模拟和累积概率分布证实，在两种施肥情况下（推荐和两次推荐），等高垄耕和作物残茬的应用都可以在未来2°C的上坡田地提高玉米产量（4％–7％）。在气候变暖的情况下，土壤侵蚀以及径流造成的水和养分流失是一个严重的风险。同时，在两个土壤肥力较高的土壤（St1和St3）上，在两种施肥情况下均施以农作物残茬来减少耕作可能是农民实践的一种有价值的替代方法，因为这将导致未来玉米的增产更高（14.5％）。与基线相比，温度升高了2°C，因此规避风险的农民可能更喜欢。无论耕作方式如何，在保水能力低（St1，63−66 mm）的砾石土壤上生产玉米，未来2°C的温度可能会升高（-11％）。然而，尽管特定的耕作效果显着，但加强氮肥的施用仍可以减少St2，St3和St4的玉米产量损失，而与耕作方式无关，可通过提高CO浓度下玉米对N的吸收来实现。₂在未来的升温期间。因此，如通过DSSAT模拟所证实的，特定地点的耕作操作和农作物残渣的施用具有缓冲未来变暖对玉米产量的影响的潜力。