This work presents a detailed computational study on the role of microstructural properties of a superhydrophobic granular coating on its drag reducing performance. More specifically, the effects of the Young-Laplace contact angle, particle diameter, and solid volume fraction on drag reduction are studied for submerged superhydrophobic granular coatings under negative (suction) and positive hydrostatic pressures. In addition, four different particle arrangements (square, staggered, reticulated, and random) are considered to investigate the effects of particle spatial distribution on coatings' drag reduction performance. This was accomplished by accurately predicting the 3-D shape and surface area of a coating's wetted area fraction, and then by using this information to solve the flow field over the coating in a Couette configuration to obtain its drag reduction efficiency. As expected, it was found that drag reduction performance of submerged superhydrophobic coatings decreases with increasing hydrostatic pressure. However, in contrast to coatings comprised of sharp-edged pores, it was found that drag reduction efficiency of granular coatings monotonically increases with decreasing the pressure when the pressure is negative. It was also found that spatial distribution of the particles has no significant effect on drag reduction. The only exception to this conclusion is the case of coatings with reticulated particle packing. Results of our simulations are compared with available data in the literature and discussed in detail. (C) 2017 Elsevier Ltd. All rights reserved.