Landscape evolution models (LEMs) are an increasingly popular resource for geomorphologists as they can operate as virtual laboratories where the implications of hypotheses about processes over human to geological timescales can be visualized at spatial scales from catchments to mountain ranges. Hypothetical studies for idealized landscapes have dominated, although model testing in real landscapes has also been undertaken. So far however, numerical landscape evolution models have rarely been used to aid field-based reconstructions of the geomorphic evolution of actual landscapes. To help make this use more common, we review numerical landscape evolution models from the point of view of model use in field reconstruction studies. We first give a broad overview of the main assumptions and choices made in many LEMs to help prospective users select models appropriate to their field situation. We then summarize for various timescales which data are typically available and which models are appropriate. Finally, we provide guidance on how to set up a model study as a function of available data and the type of research question. Copyright

Landscape evolution models (LEMs) simulate the three‐dimensional development of landscapes over time. Different LEMs have different foci, e.g. erosional behaviour, river dynamics, the fluvial domain, hillslopes or a combination. LEM LAPSUS is a relatively simple cellular model operating on timescales of centuries to millennia and using annual timesteps that has had a hillslope focus. Our objective was to incorporate fluvial behaviour in LAPSUS without changing the existing model equations. The model should be able to reproduce alternating aggradation and incision in the floodplains of catchments, depending on simulated conditions. Testing was done using an artificial digital elevation model (DEM) and a demonstration of the ability for fluvial simulation was performed for a real landscape (Torrealvilla catchment, southeast Spain). Model equations to calculate sediment dynamics and water routing were similar for both hillslope and fluvial conditions, but different parameter values were used for these domains, defined based on annual discharge. Parameters changing between the domains are convergence factor p, which is used in the multiple flow algorithm to route water, and discharge and gradient exponents m and n, used in transport capacity calculations. Erodibility and ‘sedimentability’ factors K and P were changed between cold (little vegetation, high erodibility) and warm conditions (more vegetation, lower erodibility). Results show that the adapted parameters reproduced alternating aggradation – due to divergent flow in the floodplain and sediment supply under cold conditions – and incision due to reduced sediment supply and resulting clean water erosion during simulated warm conditions. The simulated results are due to interactions between hillslopes and floodplains, as the former provide the sediments that are deposited in the latter. Similar behaviour was demonstrated when using the real DEM. Sensitivity and resolution analysis showed that the model is sensitive to changes in m, n and p and that model behaviour is influenced by DEM resolution. Copyright © 2012 John Wiley & Sons, Ltd.

Additional information:Use policyThe full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-pro t purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details. ABSTRACTThe Gediz River, one of the principal rivers of Western Anatolia, has an extensive Pleistocene fluvial archive that potentially offers a unique window into fluvial system behaviour on the western margins of Asia during the Quaternary. In this paper we review our work on the Quaternary Gediz River Project (2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010) and present new data which leads to a revised stratigraphical model for the Early Pleistocene development of this fluvial system.In previous work we confirmed the preservation of eleven buried Early Pleistocene fluvial terraces of the Gediz River (designated GT11, the oldest and highest, to GT1, the youngest and lowest) which lie beneath the basalt-covered plateaux of the Kula Volcanic Province. Deciphering the information locked in this fluvial archive requires the construction of a robust geochronology. Fortunately, the Gediz archive provides ample opportunity for ageconstraint based upon age estimates derived from basaltic lava flows that repeatedly entered the palaeo-Gediz valley floors. In this paper we present, for the first time, our complete dataset of 40 Ar/ 39 Ar age estimates and associated palaeomagnetic measurements. These data, which can be directly related to the underlying fluvial deposits, provide age constraints critical to our understanding of this sequence.The new chronology establishes the onset of Quaternary volcanism at ~1320ka (MIS42). This volcanism, which is associated with GT6, confirms a pre-MIS42 age for terraces GT11-GT7. Evidence from the colluvial sequences directly overlying these early terraces suggests that they formed in response to hydrological and sediment budget changes forced by climatedriven vegetation change. The cyclic formation of terraces and their timing suggests they represent the obliquity-driven climate changes of the Early Pleistocene. By way of contrast the GT5-GT1 terrace sequence, constrained by a lava flow with an age estimate of ~1247ka, span the time-interval MIS42 -MIS38 and therefore do not match the frequency of climate change as previously suggested. The onset of volcanism breaks the simple linkage of terracing to climate-driven change. These younger terraces more likely reflect a localized terracing process triggered by base level changes forced by volcanic eruption and associated reactivation of pre-existing faults, lava dam construction, landsliding and subsequent lavadammed lake drainage.Establishing a firm stratigraphy a...

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Landscapes respond in complex ways to external drivers such as base level change due to damming events. In this study, landscape evolution modelling was used to understand and analyse long-term catchment response to lava damming events. PalaeoDEM reconstruction of a small Turkish catchment (45 km 2 ) that endured multiple lava damming events in the past 300 ka, was used to derive long-term net erosion rates. These erosion rates were used for parameter calibration and led to a best fit parameter set. This optimal parameter set was used to compare net erosion landscape time series of four scenarios: (i) no uplift and no damming events; (ii) no uplift and three damming events; (iii) uplift and no damming events; and (iv) uplift and three damming events. Spatial evolution of net erosion and sediment storage of scenario (iii) and (iv) were compared. Simulation results demonstrate net erosion differences after 250 000 years between scenarios with and without dams. Initially, trunk gullies show less net erosion in the scenario with damming events compared with the scenario without damming events. This effect of dampened erosion migrates upstream to smaller gullies and local slopes. Finally, an intrinsic incision pulse in the dam scenario results in a higher net erosion of trunk gullies while decoupled local slopes are still responding to the pre-incision landscape conditions. Sediment storage differences also occur on a 100 ka scale. These differences behaved in a complex manner owing to different timings of the migration of erosion and sediment waves along the gullies for each scenario. Although the specific spatial and temporal sequence of erosion and deposition events is sensitive to local parameters, this model study shows the manner in which past short-lived events like lava dams have long-lasting effects on catchment evolution.