Soil & Water Res., 2012, 7(2):52-63 | DOI: 10.17221/25/2011-SWR
Effects of soil depth spatial variation on runoff simulation, using the Limburg Soil Erosion Model (LISEM), a case study in Faucon catchment, FranceOriginal Paper
- Faculty of Geo-Information Science and Earth Observation, University of Twente, Enschede, Netherlands
Soil depth is an important parameter for models of surface runoff. Commonly used models require not only accurate estimates of the parameter but also its realistic spatial distribution. The objective of this study was to use terrain and environmental variables to map soil depth, comparing different spatial prediction methods by their effect on simulated runoff hydrographs. The study area is called Faucon, and it is located in the southeast of the French Alps. An additive linear model of "land cover class" and "overland flow distance to channel network" predicted the soil depth in the best way. Regression kriging (RK) used in this model gave better accuracy than ordinary kriging (OK). The soil depth maps, including conditional simulations, were exported to the hydrologic model of LISEM, where three synthetic rainfall scenarios were used. The hydrographs produced by RK and OK were significantly different only at rainfalls of low intensity or short duration.
Keywords: conditional simulation; Faucon; hydrograph; kriging; LISEM; soil depth
Published: June 30, 2012 Show citation
ACS | AIP | APA | ASA | Harvard | Chicago | Chicago Notes | IEEE | ISO690 | MLA | NLM | Turabian | Vancouver |
References
- Bagarello V., Sferlazza S. (2009): Comparing two methods of analysis of single-ring infiltrometer data for a sandy-loam soil. Geoderma, 149: 415-420.
Go to original source...
- Bhattacharjya R.K. (2004): Optimal design of unit hydrographs using probability distribution and genetic algorithms. Sadhana, 29: 499-508.
Go to original source...
- Bruin J. (2006): Newtest: Command to Compute New Test. UCLA: Academic Technology Services, Statistical Consulting Group. Available at http://www.ats.ucla.edu/stat/stata/ado/analysis/ (accessed September 2011).
- Cimmery V. (2010): User Guide for SAGA (version 2.0.5). Vol. 1 and 2. Available at http://www.saga-gis.org/en/about/references.html (accessed January 16, 2011).
- De Roo A.P.J. (1996a): The LISEM project: An introduction. Hydrological Processes, 10: 1021-1025.
Go to original source...
- Dietrich W.E., Reiss R., Hsu M.-L., Montgomery D.R. (1995): A process-based model for colluvial soil depth and shallow landsliding using digital elevation data. Hydrological Processes, 9: 383-400.
Go to original source...
- FAO (2006): Guidelines for Soil Description. 4th Ed. FAO, Rome.
- Farrell Z. (2010): Single Ring Falling Head Infiltrometer. Available at http://www.usyd.edu.au/agric/web04/Single%20ring%20final.htm (accessed October 2010).
- Florinsky I.V., Eilers R.G. (2002): Prediction of soil properties by digital terrain modelling. Environmental Modelling & Software, 17: 295-311.
Go to original source...
- Foth H.D. (1984): Fundamentals of Soil Sciences. 7th Ed. John Wiley and Sons, Inc., New York.
- Green W.H., Ampt G.A. (1911): Studies on soil physics. 1. The flow of air and water through soils. Journal of Agricultural Sciences, 4: 11-24.
Go to original source...
- Goovaerts P. (2000): Geostatistical approaches for incorporating elevation into the spatial interpolation of rainfall. Journal of Hydrology, 228: 113-129.
Go to original source...
- Grayson R., Bloschl G. (eds) (2001): Spatial Patterns in Catchment Hydrology; Observations and Modeling. University Press, Cambridge.
- Herbst M., Diekkrüger B. (2006a): Numerical experiments on the sensitivity of runoff generation to the spatial variation of soil hydraulic properties. Journal of Hydrology, 326: 43-58.
Go to original source...
- Herbst M., Diekkrüger B. (2006b): Geostatistical coregionalization of soil hydraulic properties in a microscale catchment using terrain attributes. Geoderma, 132: 206-221.
Go to original source...
- Hessel R. (2005): Effects of grid cell size and time step length on simulation results of the Limburg soil erosion model (LISEM). Hydrological Processes, 19: 3037-3049.
Go to original source...
- Hosein T. (2010): Alluvial Fan Flood Hazard Assessment based on DTM Uncertainty. [MSc Thesis.] ITC, Enschede.
- Jenny H. (1941): Factors of Soil Formation, a System of Quantitative Pedology. McGraw-Hill, New York.
Go to original source...
- Jetten V.G. (2002): LISEM User Manual. Utrecht Center for Environment and Landscape Dynamics, Utrecht University, Utrecht.
- Jetten V., Straatsma M., Alkema D. (2010): Spatial Modelling of Natural Hazard Processes, GH Module 8. ESA Department, ITC, Enschede.
- Kalivas D.P., Triantakonstantis D.P., Kollias V.J. (2002): Spatial prediction of two soil properties using topographic Information. Global Nest: the International Journal, 4: 41-49.
Go to original source...
- Kuriakose S.L., Sanjaya Devotka, Rossiter D.G., Jetten V.G. (2009): Prediction of soil depth using environmental variables in an anthropogenic landscape, a case study in the Western Ghats of Kerala, India. Catena, 79: 27-38.
Go to original source...
- Kutilek M., Nielsen D.R. (1994). Soil Hydrology. Catena Verlag Geoecology Publications, CremlingenDestedt.
- Malet J.-P., Remaitre A., Maquaire O. (2004): Runout modeling and extension of the threatened area associated with muddy debris flows. Géomorphologie: Relief, Processus, Environment, 10: 195-209.
Go to original source...
- McBratney A.B., Mendonça Santos M.L. (2003): On digital soil mapping. Geoderma, 117: 3-52.
Go to original source...
- McKenzie N.J., Ryan P.J. (1999): Spatial prediction of soil properties using environmental correlation. Geoderma, 89: 67-94.
Go to original source...
- Merz B., Bárdossy A. (1998): Effects of spatial variability on the rainfall runoff process in a small loess catchment. Journal of Hydrology, 212-213: 304-317.
Go to original source...
- Milevski I. (2007): Morphometric elements of terrain morphology in the Republic of Macedonia and their influence on soil erosion. In: Int. Conf. Erosion 2007. Belgrade.
- Minasny B., McBratney A.B. (1999): A rudimentary mechanistic model for soil production and landscape development. Geoderma, 90: 3-21.
Go to original source...
- Mountain Risks (2010): The Faucon watershed: the 2003 debris-flow even (part 1). Available at http://www.unicaen.fr/mountainrisks/spip/IMG/pdf/13_Faucon_pit_stop_1.pdf (accessed August 17, 2010).
- Mwendera E.J., Feyen J. (1992): Estimation of depression storage and Manning's resistance coefficient from random roughness measurements. Geoderma, 52: 235-250.
Go to original source...
- Neitsch S.L., Arnold J.G., Kiniry J.R., Williams J.R., King K.W. (2002): Soil and Water Assessment Tool. Theoretical Documentation. TWRI Report, Texas Water Resources Institute, Texas.
- Odeh I.O.A., McBratney A.B., Chittleborough D.J. (1995): Further results on prediction of soil properties from terrain attributes: heterotopic cokriging and regression-kriging. Geoderma, 67: 215-226.
Go to original source...
- OMIV-EOST (2010): Barcelonnette area, debris flows at Faucon. Services des Observatoires des instabilites de Versants. Available at http://eost.u-strasbg.fr/omiv/barcelo_area_faucon.html (accessed August 17, 2010).
- Penížek V., Borůvka L. (2006): Soil depth prediction supproted by primary terrain attributes: a comparison of methods. Plant, Soil and Environment, 52: 424-430.
Go to original source...
- Prachansri S. (2007): Analysis of soil and land cover parameters for flood hazard assessment: a case study of the Nam Chun watershed, Phetchabun, Thailand. [MSc Thesis.] ITC, Enschede.
- Remaitre A., Malet J.P. (2005): Morphology and Sedimentology of a complex Debris Flow in a clay-shale basin. Earth surface processes and landforms. The Journal of British Geomorphological Research Group, 30: 339-348.
Go to original source...
- Renard K.G., Foster G.R., Weesies G.A., McCool D.K., Yoder D.D. (2000): Predicting Soil Erosion by Water: A Guide to Conservation Planning with the Revised Universal Soil Loss Equation (RUSLE). The U.S. Department of Agriculture (USDA), Washington D.C.
- Rossiter D.G. (2010): Tutorial: Using the R Environment for Statistical Computing. An Example with the Mercel & Hall Wheat Yield Dataset. Faculty of Geo-Information Science & Earth Observation (ITC), University of Twente, Enschede.
- Shafique M., van der Meijde M., Rossiter D.G. (2011): Geophysical and remote sensing-based approach to model regolith thickness in a data-sparse environment. Catena, 87: 11-19.
Go to original source...
- Singh V.P. (1997): Effect of spatial and temporal variability in rainfall and watershed characteristics on stream flow hydrology. Hydrological Processes, 11: 1649-1669.
Go to original source...
- USDA (2010): Determining Soil Texture by Feel Method Handout. Available at http://www.mt.nrcs.usda.gov/about/lessons/Lessons_Soil/feelmethod.html (accessed October 17, 2010).
- Webster R., Oliver M.A. (2007): Geostatistics for Environmental Scientists. 2nd Ed. John Wiley and Sons, Ltd, Chichester.
Go to original source...
- Yamamoto J. (2005): Correcting the smoothing effect of ordinary kriging estimates. Mathematical Geology, 37: 69-94.
Go to original source...
- Ziadat F.M. (2010): Prediction of soil depth from digital terrain data by integrating statistical and visual approaches. Pedosphere, 20: 361-367.
Go to original source...
This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY NC 4.0), which permits non-comercial use, distribution, and reproduction in any medium, provided the original publication is properly cited. No use, distribution or reproduction is permitted which does not comply with these terms.