Abstract/Summary

Trade-off studies effectively compare rational decisions when choosing alternatives. This study utilizes a Bayesian belief network (BBN) model to analyse land use tillage practices for flood management, considering climate, soilscape, slope, and farming systems. The BBN comprises three sub-models using soil samples, farm surveys, synthetic datasets, and literature review data. In one scenario, conventional tillage on a 3° slope increased the net value of crop yield (50.85 %) and positive farm effects (49.64 %) but increased surface runoff (66.24 %) and reduced flood alleviation benefits (58.56 %). On the other hand, conservational tillage on a 3 ° slope yielded lower crop yield increase (14.11 %) and farm production effects (13.80 %) but reduced surface runoff (51.05 %) and increased flood alleviation benefits (45.06 %). Similarly, conventional tillage on a 12 ° slope showed similar crop yield and farm production effects, with slightly higher surface runoff (66.88 %) and reduced flood alleviation benefits (59.13 %). Conversely, adopting conservational tillage on a 12 slope resulted same extent of reduction in crop yield increase band (14.11 %) and farm production effects (13.80 %) but effectively reduced surface runoff (50.42 %) and improved flood alleviation benefits (44.49 %). Therefore, a trade-off between farm production and flood alleviation was identified when tillage preference was applied as a natural flood management strategy. Results showed this trend was particularly pronounced amongst soils on slopes. The model can help users in informed decisions on tillage for sustainable farming, with the potential for improvement through additional variables and farm-specific data.