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 degrees 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 degrees 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 degrees 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.
机构:
South China Univ Technol, Inst Safety Sci & Engn, Guangzhou 510640, Peoples R China
Guangdong Prov Sci & Technol, Collaborat Innovat Ctr Work Safety, Guangzhou 510640, Peoples R China
Katholieke Univ Leuven, CEDON, Campus Brussels, B-1000 Brussels, BelgiumSouth China Univ Technol, Inst Safety Sci & Engn, Guangzhou 510640, Peoples R China
Men, Jinkun
Chen, Guohua
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South China Univ Technol, Inst Safety Sci & Engn, Guangzhou 510640, Peoples R China
Guangdong Prov Sci & Technol, Collaborat Innovat Ctr Work Safety, Guangzhou 510640, Peoples R China
South China Univ Technol, 381 Wushan Rd, Guangzhou 510640, Peoples R ChinaSouth China Univ Technol, Inst Safety Sci & Engn, Guangzhou 510640, Peoples R China
Chen, Guohua
Reniers, Genserik
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Katholieke Univ Leuven, CEDON, Campus Brussels, B-1000 Brussels, Belgium
Delft Univ Technol, Fac Technol Policy & Management, Safety & Secur Sci Grp S3G, NL-2628 BX Delft, Netherlands
Univ Antwerp, Fac Appl Econ, Antwerp Res Grp Safety & Secur ARGoSS, B-2000 Antwerp, BelgiumSouth China Univ Technol, Inst Safety Sci & Engn, Guangzhou 510640, Peoples R China