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Abstract Precise point positioning (PPP) of ships using Global Navigation Satellite System (GNSS) data reveals the precise movements of marine vessels. This method may quantify anomalies in sea surface height with implications for oceanographic monitoring, exploration, and tsunami warning. The GNSS PPP data from theR/V Sikuliaq, a research ship of the University of Alaska Fairbanks, were processed to detect a small local tsunami generated by the Lowell Point landslide, which occurred near Seward, Alaska, on 8 May 2022 (UTC). The GNSS receiver aboard theR/V Sikuliaqrecorded the waves generated by the landslide, with a maximum wave amplitude of 6 cm and wave periods between 40 and 50 s. These results are consistent with simulations of the landslide event. 

Abstract Features of landscape morphology—including slope, curvature, and drainage dissection—are important controls on runoff generation in upland landscapes. Over long timescales, runoff plays an essential role in shaping these same features through surface erosion. This feedback between erosion and runoff generation suggests that modeling long‐term landscape evolution together with dynamic runoff generation could provide insight into hydrological function. Here we examine the emergence of variable source area runoff generation in a new coupled hydro‐geomorphic model that accounts for water balance partitioning between surface flow, subsurface flow, and evapotranspiration as landscapes evolve over millions of years. We derive a minimal set of dimensionless numbers that provide insight into how hydrologic and geomorphic parameters together affect landscapes. Across the parameter space we investigated, model results collapsed to a single inverse relationship between the dimensionless relief and the ratio of catchment quickflow to discharge. Furthermore, we found an inverse relationship between the Hillslope number, which describes topographic relief relative to aquifer thickness, and the proportion of the landscape that was variably saturated. While the model generally produces fluvial topography visually similar to simpler landscape evolution models, certain parameter combinations produce wide valley bottom wetlands and non‐dendritic, trellis‐like drainage networks, which may reflect real conditions in some landscapes where aquifer gradients become decoupled from topography. With these results, we demonstrate the power of hydro‐geomorphic models for generating new insights into hydrological processes, and also suggest that subsurface hydrology may be integral for modeling aspects of long‐term landscape evolution.