© The Author(s), 2016. This is the author's version of the work and is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Earth and Planetary Science Letters 452 (2016): 204-214, doi:10.1016/j.epsl.2016.08.018. ; The typically single-threaded channels on wave-influenced deltas show striking differences in their orientations, with some channels oriented into the incoming waves (e.g., Ombrone, Krishna), and others oriented away from the waves (e.g., Godavari, Sao Francisco). Understanding the controls on channel orientation is important as the channel location greatly influences deltaic morphology and sedimentology, both subaerially and subaqueously. Here, we explore channel orientation and consequent feedbacks with local shoreline dynamics using a plan-form numerical model of delta evolution. The model treats fluvial sediment delivery to a wave-dominated coast in two ways: 1) channels are assumed to prograde in a direction perpendicular to the local shoreline orientation and 2) a controlled fraction of littoral sediment transport can bypass the river mouth. Model results suggest that channels migrate downdrift when there is a significant net littoral transport and alongshore transport bypassing of the river mouth is limited. In contrast, river channels tend to orient themselves into the waves when fluvial sediment flux is relatively large, causing the shoreline of the downdrift delta flank to attain the orientation of maximum potential sediment transport for the incoming wave climate. Using model results, we develop a framework to estimate channel orientations for wave-influenced deltas that shows good agreement with natural examples. An increase in fluvial sediment input can cause a channel to reorient itself into incoming waves, behavior observed, for example, in the Ombrone delta in Italy. Our results can inform paleoclimate studies by linking channel orientation to fluvial sediment flux and wave energy. In particular, our approach provides a means to quantify past wave directions, which are notoriously difficult to constrain. ; This study was supported by NSF grant EAR-0952146. ; 2017-08-10