Where to Act in the Landscape to Minimize Sedimentation and Contamination of the River System: A Multi-Objective Heuristic Approach

Afforestation can mitigate the export of water, sediment, and dissolved or adsorbed contaminants to river systems, but identifying effective intervention sites requires accounting for multiple flow-related criteria and their spatial interactions. This paper presents a multi-criteria heuristic approach that extends CAMF (Cellular Automata-based Heuristic for Minimizing Flow), originally designed to select cells from a rasterized landscape for interventions that minimize sediment yield at target sites. We integrated the Distance-to-Ideal-Point (DIST2IP) algorithm in CAMF, enabling the selection of cells where intervention can minimize two or more flows simultaneously. The multi-criteria CAMF was applied ex post to the radioactively contaminated Niida river catchment, Fukushima Prefecture, Japan, to identify 1000 cells within decontaminated zones where the then immediate afforestation would have maximally reduced both sediment and residual 137Cs export. The 1000 best cells selected by DIST2IP, representing 4% of the decontaminated cells, would have reduced sediment export by 22% and 137Cs export by 6%. Selected cells are within the union of cells identified by the two single-criteria optimizations and are predominantly close to water bodies, confirming that blocking flow paths before they connect to the river system is most effective.