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Based on soil erosion and sediment transport processes, CAMF (Cellular Automata-based heuristic for Minimizing Flow) selects sites for afforestation to minimize sediment influx at a catchment's outlet. CAMF uses a raster representation of the catchment and a steepest ascent hill-climbing optimization heuristic, safeguarding spatial interaction. Its execution time can be prohibitively long for large data-sets. Parallelization results in a speedup of 20 to 24 on 28 cores. We present variants of the optimization method to reduce the number and cost of the iterations. We present a tuning algorithm for the meta-parameters of these variants. The results obtained for two contrasting catchments illustrate that the accelerations reduce the cost by a factor larger than 100, with negligible effect on the afforested cells and magnitude of the sediment reduction. The results indicate that higher levels of spatial interaction have a stronger impact on the accuracy of the results and/or the execution time. • An efficient method to select sites for afforestation to minimize sediment loss. • Modified steepest ascent hill climbing method reduces runtime with minor quality loss. • A parallel implementation achieves nearly optimal speedup on multi-core processors. • Application to two river catchments shows the impact of spatial interaction. [ABSTRACT FROM AUTHOR]

[Display omitted] • Erosion and hydrology were studied in small eucalyptus (EC) and grassland (GC) catchments. • Two-fold higher surface runoff and sediment yield in GC compared with EC. • In El Niño year, annual sediment yield was 4.2 times greater in GC than in EC. • Hysteresis patterns showed faster sediment delivery in GC than in EC. • Well-managed commercial forests produce less runoff and erosion. Land use change in the Southern Grasslands biome with the introduction of exotic, fast-growing forest species is a controversial topic, because of the potential effect on water and soil resources. The aim of this study was to assess the effects of afforesting degraded grassland on streamflow and sedimentation in subtropical headwater catchments. Two small, headwater catchments were studied, one planted with Eucalyptus saligna (EC: 0.83 km2) and another with grasslands and extensive livestock (GC: 1.10 km2). Rainfall, runoff, and sediment discharge were monitored from September 2013 to March 2017. The results show two-fold greater surface runoff and sediment yield occurred in GC than in EC. Maximum and mean runoff coefficients were, respectively, 45.5 and 10.2% in GC, and 12.4 and 2.2% in EC; suspended sediment yield was, respectively, 67.9 and 22.4 Mg km−2 in GC and EC; and bed load sediment yield was only 0.053 and 0.006 Mg km−2. El Niño year with high rainfall produced the greatest annual sediment yield, with values 4.2 times greater in GC (167.7 Mg km−2) than in EC (39.9 Mg km−2). Hydrographs/sedimentographs synchronization and hysteresis patterns suggest faster sediment delivery in GC than in EC, but further studies are needed to conciliate sediment sources results with sediment fingerprinting. Staggered forest harvest (21% of the planted eucalyptus) led to sediment yield comparable to the observed during the pre-harvest period, and lower than in grassland catchment. In conclusion, well‐managed forest plantations, including staggered forest harvesting and preservation of riparian forest, are less prone to sedimentation than degraded grassland under intensive grazing. Well-managed afforestation of degraded lands contributes to soil conservation in the studied region, whereas low ecological performance of degraded grassland calls for soil and pasture management practices to increase forage offer to grazing animals, while conserving soil and water resources in the catchments. [ABSTRACT FROM AUTHOR]