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Topographic models are widely used throughout the Earth Sciences to study physical processes and quantify geomorphic change. Fluvial geomorphology is no exception, with Digital Elevation Models commonly featuring in gravel-bed river research where they are used to quantify process dynamics such as sediment flux and bed level change. Error is inherently present in many of the datasets used to generate topographical models. A range of methods has been established to estimate error during creation and assessment of topographic models. This paper presents a case study from the Makaroro River in Hawke's Bay, New Zealand, to highlight the importance of error estimation. The freely available Geomorphic Change Detection (GCD) plugin for ArcGIS (also available as a stand-alone package) was used to generate Digital Elevation Models of a 2.2 km reach of the Makaroro River and estimate elevation and …