Selecting cells in a raster database for maximal impact intervention in the presence of spatial interaction: Computational complexity of a Multiple vs. a Single Flow Direction Method

TL;DR

This paper compares Single and Multiple Flow Direction algorithms within a cellular automata heuristic to optimize intervention sites in river catchments, highlighting the computational and practical differences for sediment reduction.

Contribution

It introduces and analyzes the integration of a Multiple Flow Direction algorithm into the CAMF method, enhancing flow simulation realism in raster-based interventions.

Findings

MFD provides more realistic flow modeling than SFD.

MFD increases computational complexity compared to SFD.

Both methods effectively identify intervention sites for sediment reduction.

Abstract

To minimize the sediment flowing to the outlet of a river catchment with minimal effort or cost, it is important to select the best areas to perform a certain intervention, e.g., afforestation. CAMF (Cellular Automata based heuristic for Minimizing Flow) is a method that performs this selection process iteratively in a raster geodatabase environment. To simulate the flow paths, the original CAMF uses a Single Flow Direction (SFD) algorithm. However, SFD fails to reflect the real nature of flow transport, especially in areas with low relief. This paper describes and analyzes the integration of a Multiple Flow Direction (MFD) algorithm in CAMF, in order to provide a more realistic flow simulation. We compare the computational complexity of CAMF-SFD and CAMF-MFD and we discuss the scalability w.r.t. the number of cells involved. We evaluate the behavior of both variants for sediment yield minimization by afforestation in two catchments with different properties.