Resuspension ofsediments in marine environments affects the exchange of water, nutrients, and organiccarbon between the seabed and the water column. Thus, it has a strong influenceon the biology and geochemistry of the benthic ecosystem and the overlyingwater. Resuspension results from physical stresses imposed by currents andwaves that form a nepheloid layer, and from the benthic activity of organisms (hereafter“biological resuspension”) such as fish that borrow for food, which typically generatesdistinct particle puffs. While physical resuspension is dominant in highcurrents and wavy coastal regions, biological resuspension is the dominant mechanismin low-energy environments. While low-energy environments are predominant inthe deep sea they are also common in closed basins. Despite its importance, lessthan a handful of estimates of the average fluxes that stem from biologicalresuspension are available. The main reason is the lack of methodologies thatcan quantify biological resuspension. In my research, I have developed afootprint model that estimates the vertical resuspension flux from measurementsof the horizontal advective flux. The footprint model is based on the integralmass conservation law and considers advection and settling of the sedimentparticles. A rigorous derivation of the model was followed by a theoretical sensitivityanalysis that was performed to identify which environmental parameters influencethe model accuracy. It was found that the grain size distribution, the medianheight of the particles within the puff, and the puffs’ median height arecrucial to accurately estimate the resuspension flux. To test the footprintmodel performance, a Lagrangian stochastic simulation program was developed.The program generates random puffs, follows the particles locations as they areadvected and settle, and measures their concentration at simulated detectors. Usingthe simulated concentrations, the resuspension flux calculated by the footprintmodel was compared to the flux generated by the simulation. While the resultsshow high accuracy for all the tested parameters, we found that the model’sprecision is influenced by the number of puffs in each measurement, thevariance of the vertical distribution of mass within the puff at the moment of resuspension,and by the variance of the puffs’ height. While the footprint model did not explicitlyaccount for the effect of turbulent dispersion, I found that for the commonturbulence intensity value of 10% the results were still accurate (mean error<15%) for particles with settling velocity greater than 1.9 cm/sec. Thus, itis concluded that the footprint model is highly accurate in areas of coarse sedimentor negligible turbulent dispersion.