Baartman, J.E.M.

Buis, E.

Schoorl, J.M.

Temme, A.J.A.M.

English

Wageningen Yield 

Landscape Evolution Modelling - LAPSUS 
 
J.E.M. Baartman, A.J.A.M. Temme, J.M. Schoorl, L. Claessens, W. Viveen, W. van 
Gorp and A. Veldkamp 
 
Wageningen University, Land Dynamics Group, P.O. Box 47, 6700 AA Wageningen, The 
Netherlands. E-mail: jantiene.baartman@wur.nl 
 
 
 
ABSTRACT 
Landscape evolution modeling can make the consequences of landscape evolution 
hypotheses explicit and theoretically allows for their falsification and improvement. Ideally, 
landscape evolution models (LEMs) combine the results of all relevant landscape forming 
processes into an ever-adapting digital landscape (e.g. DEM). These processes may act on 
different spatial and temporal scales. LAPSUS is such a LEM. Processes that have in 
different studies been included in LAPSUS are water erosion and deposition, landslide 
activity, creep, solifluction, weathering, tectonics and tillage. Process descriptions are as 
simple and generic as possible, ensuring wide applicability. Vegetation-effects can be 
included. Interactions between processes are turn-based: volumes of one process are 
calculated and used to update the DEM before another process starts. LAPSUS uses 
multiple flow techniques to model flows of water and sediment over the landscape. Though 
computationally costly, this gives a more natural result than steepest descent methods. In 
addition, the combination of different processes may create sinks during modelling. Since 
these sinks are not spurious, the model has been adapted to deal with them in natural ways. 
This is crucial for several purposes, for instance when studying damming of valleys by 
landslides, and subsequent infilling of the resulting lake with sediments from upstream. 
 
Keywords: Landscape Evolution Modelling, LAPSUS, soil redistribution, erosion 
 
INTRODUCTION 
 
This extended abstract is merely a review of the work undertaken and developments into the 
future with the LAPSUS model. LAPSUS is a landscape evolution model (e.g. LEM erosion 
model) that combines the results of multiple landscape forming processes into one dynamic 
landscape. Spatial and temporal extent and resolution may vary from slope, catchment to 
basins, grids from 1 to 1000 m2, timesteps of multiple events, seasons, years, decades and 
simulation periods from years to millennial. 
Interactions between processes are turn-based: volumes of one process are calculated and 
used to update the DEM before another process starts. Processes that have been included 
in LAPSUS are water erosion and deposition, landslide activity, creep, solifluction, physical 
weathering, frost weathering, tectonics and tillage (See Figure 1). 
Process descriptions are as simple and generic as possible, ensuring wide applicability. 
Vegetation-effects are included to different degrees in different case studies. LAPSUS uses 
multiple flow techniques to model the flow of water and sediment over the landscape. This is 
computationally costly, but yields a more natural result than steepest descent methods, 
especially when combining multiple processes over multiple timesteps. 
The combination of different processes may create sinks during modelling. Since these sinks 
are not spurious, the model has been adapted to deal with them in a natural way. This is 
crucial when studying damming of valleys by landslides, and subsequent infilling of the 
resulting lake with sediments from upstream. 
 
 
TOPIC 1: PHYSICAL GEOGRAPHY MODELLING
101
RESULTS AND DISCUSSION 
 
LAPSUS has been used for erosion and landscape evolution studies in many landscapes in 
many countries. LAPSUS has been founded in the year 2000 with the development, 
calibration and validation of the LAPSUS model and applications concerning land use in 
Spain and Ecuador (Schoorl et al., 2000, 2002, 2004, 2006; Schoorl and Veldkamp, 2001, 
2006). Firstly, the model has been extended in order to cover the process of landsliding in 
New Zealand and Taiwan (Claessens et al., 2005, 2006a, 2006b, 2007a, 2007b). Secondly, 
issues of DEM resolution and the treatment of sinks and pits in the landscape have been 
investigated (Temme et al., 2006, 2009) as well as stretching the models time scale to 
landscape evolution time spans in South Africa (Temme and Veldkamp, 2009). Thirdly, 
different applications with specific processes have been developed, for example, the model 
has been used in regional nutrient balance studies in Africa (Haileslassie et al., 2005, 2006, 
2007; Roy et al., 2004; Lesschen et al., 2005). aplying the model in desert environments of 
Israel (Buis and Veldkamp, 2008), using LAPSUS in combination with geostatistical tools and 
tillage in Canada (Heuvelink et al, 2006), investigating the faith of phosphor in the 
landscapes of the Netherlands (Sonneveld et al., 2006) and new developments concerning 
connectivity, agricultural terraces and land abandonment (Lesschen et al., 2007, 2009) and 
the processing of feedbacks between land use and soil redistribution (Claessens et al., 2009) 
 
 
Figure 1. Overview of processes incorporated within the Lapsus modelling framework (see 
also www.lapsusmodel.nl) 
 
CONCLUSIONS  
 
Landscape evolution modelling allows for falsification and improvement of landscape 
evolution hypotheses and can make the consequences temporal and spatial explicit. Ideally, 
landscape evolution models (LEMs) combine the results of all relevant landscape forming 
processes into an ever-adapting digital landscape (e.g. DEM). These processes may act and 
interact on different spatial and temporal scales. 
 
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ÁREA TEMÁTICA 1: MODELIZACIÓN EN GEOGRAFÍA FÍSICA
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A spatially explicit methodology to quantify soil nutrient balances and their uncertainties at the national level Nutrient Cycling in

Algorithm for dealing with depressions in dynamic landscape evolution models:

Assessment of soil nutrient depletion and its spatial variability on smallholders’ mixed farming systems in Ethiopia using partial versus full nutrient balances.

Chapter 5: Geostatistical simulation and error propagation in geomorphometry.

Contribution of topographical based landslide hazard Modelling to the analysis of the spatial distribution and ecology of Kauri (Agathis australis):

DEM resolution effects on shallow landslide hazard and soil redistribution modelling.

Evaluating The Fate Of Phosphorus In Apparent Homogeneous Landscapes Using a High-Resolution DEM.

Linking land use and landscape process modelling: a case study for the Alora region (South Spain): Agric.Ecosyst.Environ.,

Modelling dynamic water redistribution patterns in arid catchments in the Negev Desert of Israel.

Modelling interactions and feedback mechanisms between land use change and landscape processes.

Modelling landslide hazard, soil redistribution and sediment yield of landslides on the Ugandan footslopes of Mount Elgon.

Modelling runoff and erosion for a semi-arid catchment using a multi-scale approach based on hydrological connectivity.

Modelling the location of shallow landslides and their effects on landscape dynamics in large watersheds: an application for Northern New Zealand: Geomorphology, Volume 87, Issues 1-2, p 16

Modelling water and soil redistribution in a dynamic landscape context: Soil.Sci.Soc.Am.J.,

Multi-process Late Quaternary landscape evolution modelling reveals lags in climate response over small spatial scales.

Multi-Scale Soil-Landscape Process Modeling,

Nutrient flows and balances at the field and farm scale: Exploring effects of land-use strategies and access to resources.

Reconstructing high-magnitude/low-frequency landslide events based on soil redistribution modelling and a Late-Holocene sediment record from New Zealand:

Scaling Soil Nutrient Balances - Enabling mesoscale approaches for African realities. FAO Fertilizer and Plant Nutrition Bulletin 15, FAO,

Smallholders’ soil fertility management in the Central Highlands of Ethiopia: implications for nutrient stocks, balances and sustainability of agroecosystems.

Space-time Kalman filtering of soil redistribution.

The 137Cs technique on steep Mediterranean slopes (Part 2): landscape evolution and model calibration: Catena,

Three-dimensional landscape process modelling: the effect of DEM resolution: Earth Surf.Proc.Landforms,

Landscape evolution modeling - LAPSUS

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