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Agriculture  2013 

Evaluating Alternative Methods of Soil Erodibility Mapping in the Mediterranean Island of Crete

DOI: 10.3390/agriculture3030362

Keywords: soil erodibility, K-factor, USDA formula, Crete, Kolymvari

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Abstract:

Soil erodibility is among the trickiest erosion factors to estimate. This is especially true for heterogeneous Mediterranean environments, where reliable and dense soil data are rarely available, and interpolation methods give very low accuracies. Towards estimating soil erodibility, research so far has resulted in several alternatives mainly based on empirical formulas, on physics-based equations or on inference with expertise. The aim of this work was to compare erodibility patterns derived by using the empirical United States Department of Agriculture (USDA) formula and by inference from a geological map in a Mediterranean agricultural site. The Kolymvari area, located in the western part of Crete, an area covered by olive groves and citrus orchards, was selected as the study site for this work. Comparison of the spatial patterns of soil erodibility derived from the two alternatives showed significant differences ( i.e., a mean normalized difference value of 0.52), while a test of the “inference” alternative indicated very low accuracies (0.1475 RMS error). A comparison, however, of the spatial patterns of erosion values derived from both alternatives indicated that dissimilarities of the two soil erodibility maps faded out. Moreover, the highly risky areas provided by both alternatives were found to be identical for 88% of the whole study site.

References

[1]  Foster, G.R.; Meyer, L.D. A Closed-form Soil Erosion Equation for Upland Areas. In Sedimentation Symposium in Honor Porf. H.A. Einstein; Sten, H.W., Ed.; Colorado State University: Ft. Collins, CO, USA, 1972; pp. 12:1–12:19.
[2]  Sanders, D.W. Sloping Land: Soil Erosion Problems and Soil Conservation Requirements. In Land Evaluation for Land-use Planning and Conservation in Sloping Areas; Siderius, W., Ed.; Institute for Land Reclamation and Improvement: Wageningen, The Netherlands, 1986; pp. 40–50.
[3]  Wischmeier, W.H.; Smith, D.D. Predicting Rainfall Erosion Losses from Cropland East of the Rocky Mountains; Agricultural Research Service, U. S. Department of Agriculture in Cooperation with Purdue Agricultural Experiment Station: Washington, DC, USA, 1978.
[4]  Kinnell, P.I.A. Raindrop-impact-induced erosion processes and prediction: A review. Hydrol. Process. 2005, 19, 2815–2844, doi:10.1002/hyp.5788.
[5]  Le Bissonnais, Y.; Cerdan, O.; Lecomte, V.; Benkhadra, H.; Souchere, V.; Martin, P. Variability of soil surface characteristics influencing runoff and interril erosion. Catena 2005, 62, 111–124, doi:10.1016/j.catena.2005.05.001.
[6]  Aksoy, H.; Kavvas, M.L. A review of hillslope and watershed scale erosion and sediment transport models. Catena 2005, 64, 247–271, doi:10.1016/j.catena.2005.08.008.
[7]  De Vente, J.; Poesen, J. Predicting soil erosion and sediment yield at the basin scale: Scale issues and semi-quantitative models. Earth Sci. Rev. 2005, 71, 95–125, doi:10.1016/j.earscirev.2005.02.002.
[8]  Garcia-Ruiz, J.M. The effect of land uses on soil erosion in Spain: A review. Catena 2010, doi:10.1016/j.catena.2010.01.001.
[9]  Boardman, J. Soil erosion science: Reflections on the limitations of current approaches. Catena 2006, 68, 73–86, doi:10.1016/j.catena.2006.03.007.
[10]  Proposal for a Directive of the European Parliament and of the Council Establishing a Framework for the Protection of Soil and Amending Directive 2004/35/EC; European Commission: Brussels, Belgium, 2006.
[11]  Integration of Environment into EU Agriculture Policy. The IRENA Indicator-Based Assessment Report; K?benhavn, K., Ed.; European Environment Agency: Copenhagen, Denmark, 2006.
[12]  Millington, A.C. Reconnaissance Scale Soil Erosion Mapping Using a Simple Geographic Information System in the Humid Tropics. In Land Evaluation for Land-use Planning and Conservation in Sloping Areas; Siderius, W., Ed.; Institute for Land Reclamation and Improvement: Wageningen, The Netherlands, 1986; pp. 64–81.
[13]  Merritt, W.S.; Letcher, R.A.; Jakeman, A.J. A review of erosion and sediment transport models. Environ. Model. Softw. 2003, 18, 761–799, doi:10.1016/S1364-8152(03)00078-1.
[14]  Karydas, C.G.; Panagos, P.; Gitas, I.Z. A classification of water erosion models according to their geospatial characteristics. Int. J. Dig. Earth 2002, 16, 663–680, doi:10.1080/17538947.2012.671380.
[15]  Van Rompaey, A.J.J.; Govers, G. Data quality and model complexity for regional scale soil erosion prediction. Int. J. Geogr. Inf. Sci. 2002, 16, 663–680.
[16]  Perez-Rodriguez, R.; Marques, M.J.; Bienes, R. Spatial variability of the soil erodibility parameters and their relation with the soil map at subgroup level. Sci. Total Environ. 2007, 378, 166–173.
[17]  Jetten, V.; de Roo, A.; Favis-Mortlock, D. Evaluation of field-scale and catchment-scale soil erosion models. Catena 1999, 37, 521–541.
[18]  IUSS Working Group WRB. World Reference Base for Soil Resources 2006, 2nd ed.. World Soil Resources Reports No. 103 ed.; FAO: Italy, 2006.
[19]  Beaufoy, G. The Environmental Impact of Olive Oil Production in European Union (Report); European Forum on Nature Conservation and Pastoralism: Madrid, Spain, 2000.
[20]  Renard, K.; Foster, G.R.; Weesies, G.A.; Porter, J.P. RUSLE Revised universal soil loss equation. J. Soil Water Conserv. 1991, 46, 30–33.
[21]  Desmet, P.; Grovers, G. A GIS procedure for automatically calculating the USLE LS factor on topographically complex landscape units. J. Soil Water Conserv. 1996, 51, 427–433.
[22]  Buol, S.W.; Southard, R.J.; Graham, R.C.; McDaniel, P.A. Soil Genesis and Classification, 5th ed. ed.; Iowa State University Press: Ames, IA, USA, 2003; p. 494.
[23]  Mueller, T.G.; Pusuluri, N.B.; Mathias, K.K.; Cornelius, P.L.; Barnhisel, R.I.; Shearer, S.A. Map quality for ordinary kriging and inverse distance weighted interpolation. Soil Sci. Soc. Am. 2001, 68, 2042–2047.
[24]  Schloeder, C.A.; Zimmerman, N.E.; Jacobs, M.J. Comparison of methods for interpolating soil properties using limited data. Soil Sci. Soc. Am. 2001, 65, 470–479, doi:10.2136/sssaj2001.652470x.
[25]  Daly, C.; Gibson, W.P.; Taylor, G.H.; Johnson, G.L.; Pasteris, P. A knowledge-based approach to the statistical mapping of climate. Climate Res. 2002, 22, 99–113, doi:10.3354/cr022099.
[26]  Gallant, J.C.; Wilson, J. TAPES-G: A grid-based terrain analysis program for the environmental sciences. Comput. Geosci. 1996, 22, 713–722, doi:10.1016/0098-3004(96)00002-7.
[27]  De Jong, S.M.; Paracchini, M.L.; Bertolo, F.; Folving, S.; Megier, J.; de Roo, A.P.J. Regional assessment of soil erosion using the distributed model SEMMED and remotely sensed data. Catena 1999, 37, 291–308, doi:10.1016/S0341-8162(99)00038-7.
[28]  Vrieling, A. Satellite remote sensing for water erosion assessment: A review. Catena 2006, 65, 2–18, doi:10.1016/j.catena.2005.10.005.
[29]  Karydas, C.G.; Sekuloska, T.; Silleos, G. Quantification and site-specification of the support practice factor when mapping soil erosion risk associated with olive plantations in the Mediterranean island of Crete. Environ. Monit. Assess. 2008, 149, 19–28, doi:10.1007/s10661-008-0179-8.
[30]  Sall, J.; Creighton, L.; Lehman, A. Jmp Start Statistics: A Guide to Statistics and Data Analysis Using Jmp and Jmp in Software, 3rd ed. ed.; Thomson: Cary, NC ,USA, 2007.
[31]  Torri, D.; Poesen, J.; Borselli, L. Predictability and uncertainty of the soil erodibility factor using a global dataset. Catena 1997, 31, 1–22, doi:10.1016/S0341-8162(97)00036-2.
[32]  ISOTEIA—Integrated System for the Promotion of Territorial & Environmental Impact Assessment in the Framework of Spatial Planning Digital Support Centre for Strategic Environmental Assessement (SEA). Available online: http://193.218.36.11:8012/ (accessed on 27 Jun 2013).

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