Hydrology and Earth System Sciences
www.hydrol-earth-syst-sci.net
1027-5606
1607-7938
13
10
2009
10.5194/hess-13-1907-2009
http://www.hydrol-earth-syst-sci.net/13/1907/2009/
http://www.hydrol-earth-syst-sci.net/13/1907/2009/hess-13-1907-2009.html
http://www.hydrol-earth-syst-sci.net/13/1907/2009/hess-13-1907-2009.pdf
1907
1920
2009-10-19
Mapping rainfall erosivity at a regional scale: a comparison of interpolation methods in the Ebro Basin (NE Spain)
M. Angulo-MartÃnez
M. López-Vicente
S. M. Vicente-Serrano
S. BeguerÃa
Department of Soil and Water, Aula Dei Experimental Station – CSIC, 1005 Avda. Montañana, 50080-Zaragoza, Spain
Department of Geo-environmental Processes and Global Change, Pyrenean Institute of Ecology – CSIC, 1005 Avda. Montañana, 50080-Zaragoza, Spain
Department of Earth and Environmental Sciences, Katholieke Universiteit Leuven, Celestijnenlaan 200E, 3001 Leuven-Heverlee, Belgium
Rainfall erosivity is a major causal factor of soil erosion, and it is
included in many prediction models. Maps of rainfall erosivity indices are
required for assessing soil erosion at the regional scale. In this study a
comparison is made between several techniques for mapping the rainfall
erosivity indices: i) the RUSLE R factor and ii) the average EI<sub>30</sub> index
of the erosive events over the Ebro basin (NE Spain). A spatially dense
precipitation data base with a high temporal resolution (15 min) was used.
Global, local and geostatistical interpolation techniques were employed to
produce maps of the rainfall erosivity indices, as well as mixed methods. To
determine the reliability of the maps several goodness-of-fit and error
statistics were computed, using a cross-validation scheme, as well as the
uncertainty of the predictions, modeled by Gaussian geostatistical
simulation. All methods were able to capture the general spatial pattern of
both erosivity indices. The semivariogram analysis revealed that spatial
autocorrelation only affected at distances of ~15 km around the
observatories. Therefore, local interpolation techniques tended to be better
overall considering the validation statistics. All models showed high
uncertainty, caused by the high variability of rainfall erosivity indices
both in time and space, what stresses the importance of having long data
series with a dense spatial coverage.
Ahmed, S. and De Marsily, G.: Comparison of geostatistical methods for estimating transmissivity using data on transmissivity and specific capacity, Water Resour. Res., 23, 1717–1737, 1987.
Arnoldus, H. M. J.: Methodology used to determine the maximum potential average annual soil loss due to sheet and rill erosion in Morocco, FAO Soils Bulletin, 34, 39–51, 1977.
BeguerÃa, S. and Vicente-Serrano, S. M.: Mapping the hazard of extreme rainfall by peaks over threshold extreme value analysis and spatial regression techniques, J. Appl. Meteorol., 45, 108–124, 2006.
BeguerÃa, S., Vicente-Serrano, S. M., López-Moreno, J. I., and GarcÃa-Ruiz, J. M.: Annual and seasonal mapping of peak intensity, magnitude and duration of extreme precipitation events across a climatic gradient, North-east Iberian Peninsula, Int. J. Climatol., 29(12), 1759–1779, doi:10.1002/joc.1808, 2009.
BeguerÃa, S. and Pueyo, Y.: A comparison of simultaneous autoregressive and generalized least squares models for dealing with spatial autocorrelation, Global Ecol. Biogeogr., 18(3), 273–279, 2009.
Boellstorff, D. and Benito, G.: Impacts of set-aside policy on the risk of soil erosion in central Spain, Agr. Ecosyst. Environ., 107, 231–243, 2005.
Borrough, P. A. and McDonnell, R. A.: Principles of geographical information systems, Oxford University Press, 1998.
Brown, D. P. and Comrie, A. C.: Spatial modelling of winter temperature and precipitation in Arizona and New Mexico, USA, Climate Res., 22, 115–128, 2002.
Brown, L. C. and Foster, G. R.: Storm erosivity using idealized intensity distributions, T ASAE, 30, 379–386, 1987.
Casas, M. C., Herrero, M., Ninyerola, M., Pons, X., RodrÃguez, R., Rius, A., and Redaño, A.: Analysis and objective mapping of extreme daily rainfall in Catalonia, Int. J. Climatol., 27, 399–409, 2007.
Chiles, J. and Delfiner, P.: Geostatistics: modelling spatial uncertainty, Wiley, New York, 1999.
Cressie, N. A. C.: Statistics for spatial data, rev. edn., John Wiley and Sons, 1993.
Creus, J.: Las sequÃas en el valle del Ebro, in: Causas y consecuencias de las sequÃas en España, edited by: Gil, A. and Morales, A., Universidad D'Alacant, 231–259, 2001.
Cuadrat, J. M.: Las sequÃas en el valle del Ebro. Aspectos climáticos y consecuencias económicas, Rev. Real Acad. Ciencias, 85, 537–545, 1991.
Curse, R., Flanagan, J., Frankenberger, B., Gelder, D., Herzmann, D., James, D., Krajenski, W., Kraszewski, M., Laflen, J., Opsomer, J., and Todey, D.: Daily estimates of rainfall, water runoff and soil erosion in Iowa, J. Soil Water Conserv., 61, 191–199, 2006.
Daly, C., Gibson, W. P., Taylor, G. H., Johnson, G. L., and Pasteris, P.: A knowledge-based approach to the statistical mapping of climate, Climate Res., 22, 99–113, 2002.
Deutsch, C. V. and Journel, A. G.: Gslib: Geostatistical software library and user's guide, Oxford university press, 1998.
Diggle, P. J., Ribero, P. J., an dCristensen, O. F.: An introduction to model basis geostatistics, in: Spatial statistics and computational methods. Lecture notes in statistics, edited by: Møller, J., Springer-Verlag, New York, 2002.
Diodato, N.: Estimating RUSLE’s rainfall factor in the part of Italy with a Mediterranean rainfall regime, Hydrol. Earth Syst. Sci., 8, 103–107, 2004.
Dirks, K. N., Hay, J. E., Stow, C. D., and Harris D.: High-resolution studies of rainfall on Norfolk Island. Part II: Interpolation of rainfall data, J. Hydrol., 208, 187–193, 1998.
DomÃnguez-Romero, L., Ayuso Muñoz, J. L., and GarcÃa MarÃn, A. P.: Annual distribution of rainfall erosivity in western Andalusia, southern Spain, J. Soil Water Conserv., 62, 390–401, 2007.
Dunkerley, D.: Rain event properties in nature and in rainfall simulation experiments: a comparative review with recommendations for increasingly systematic study and reporting, Hydrol. Process., 22(22), 4415–4435, doi:10.1002/hyp.7045, 2008.
Efron, B. and Tibshirani, R. J.: Improvements on cross-validation: the .632+ bootstrap method, J. Am. Stat. Assoc., 92, 548–560, 1997.
GarcÃa-Ruiz, J. M., Arnáez, J., White, S. M., Lorente, A., and BeguerÃa, S.: Uncertainty assessment in the predition of extreme rainfall events: an example from the Central Spanish Pyrenees, Hydrol. Process., 14, 887–898, 2000.
Garrido, J. and GarcÃa, J. A.: Periodic signals in Spanish monthly precipitation data, Theor. Appl. Climatol., 45, 97–106, 1992.
Gobin, A., Jones, R., Kirkby, M., Campling, P., Govers, G., Kosmas, C., and Gentile, A. R.: Indicators for pan-European assessment and monitoring of soil erosion by water, Environ. Sci. Policy, 7, 25–38, 2004.
González-Hidalgo, J. C., Peña-Monnè, J. L., and de Luis, M.: A review of daily soil erosion in western Mediterranean areas, Catena, 71, 193–199, 2007.
Goodale, C. L., Aber, J. D., and Ollinger, S. V.: Mapping monthly precipitation, temperature and solar radiation from Ireland with polynomial regression and a digital elevation model, Climate Res., 10, 35–49, 1998.
Goovaerts, P.: Geostatistics for natural resources evaluation, Oxford University Press, New York, 1997.
Goovaerts, P.: Using elevation to aid the geostatistical mapping of rainfall erosivity, Catena, 34, 227–242, 1999.
Goovaerts, P.: Geostatistical modelling of uncertainty in soil science, Geoderma, 103, 3–26, 2001.
Hengl, T., Heuvelink, G. B. M., and Stain, A.: A gereric framework for spatial prediction of soil variables based on regression-kriging, Geoderma, 120, 75–93, 2004.
Hoyos, N., Waylen, P. R., and Jaramillo, A.: Seasonal and spatial patterns of erosivity in a tropical watershed of the Colombian Andes, J. Hydrol., 314, 177–191, 2005.
Hudson, N.: Soil Conservation, Cornell University Press, Ithaca, 1971.
Kinnell, P. I. A. and Risse, L. M.: USLE-M: Empirical modelling rainfall erosion through runoff and sediment concentration, Soil Sci. Soc. Am. J., 62, 1667–1672, 1998.
ICONA: Agresividad de la lluvia en España. Valores del factor R de la Ecuación Universal de Pérdida de Suelo, Ministerio de Agricultura, pesca y alimentación, España, 1988.
Isaaks, E. H. and Strivastava, R. M.: An introduction to applied geostatistics, Oxford University Press, Oxford, 1989.
Lal, R.: Soil erosion on alfisols in Western Nigeria. III – Effects of rainfall characteristics, Geoderma, 16, 389–401, 1976.
Lana, X. and Burgueño, A.: Spatial and temporal characterization of annual extreme droughts in catalonia (Northeast Spain), Int. J. Climatol., 18, 93–110, 1998.
Lasanta, T.: Gestión agrÃcola y erosión del suelo en la cuenca del Ebro: el estado de la cuestión, ZubÃa, 21, 76–96, 2003.
Llasat, M. C. and Puigcerver, M.: Meteorological factors associated with floods in the north-eastern part of the Iberian Peninsula, Nat. Hazards, 5, 133–151, 1994.
Llasat, M. C.: An objective classification of rainfall events on the basis of their convective features: Application to rainfall intensity in the northeast of Spain, Int. J. Climatol., 21, 1385–1400, 2001.
Leek, R. and Olsen, P.: Modelling climatic erosivity as a factor for soil erosion in Denmark: changes and temporal trends, Soil Use Manage., 16, 61–65, 2000.
Lim, K. J., Sagong, M., Engel, B. A., Tang, Z., Choi, J., and Kim, K.: GIS-based sediment assessment tool, Catena, 64, 61–80, 2005.
López-Vicente, M., Navas, A., and MachÃn, J.: Identifying erosive periods by using RUSLE factors in mountain fields of the Central Spanish Pyrenees, Hydrol. Earth Syst. Sci., 12, 523–535, 2008.
MartÃn-Vide, J.: Diez caracterÃsticas de la pluviometrÃa española decisivas en el control de la demanda y el uso del agua, BoletÃn de la AGE, 18, 9–16, 1994.
McBratney, A. B. and Webster, R.: Chosing functions for semi-variograms of soil properties and fitting them to sampling estimates, J. Soil Sci., 37(4), 617–639, 1986.
McBratney, A., Mendoça-Santos, M., and Minasny, B.: On digital soil mapping, Geoderma, 117, 3–52, 2003.
Millward, A. A. and Mersey, J. E.: Adapting the RUSLE to model soil erosion potential in a mountainous tropical watershed, Catena, 38, 109–129, 1999.
Mitasova, H., Mitas, L., Brown, W. M., Gerdes, D. P., Kosinovsky, I., and Baker, T.: Modelling spatially and temporally distributed phenomena: new methods and tools for GRASS GIS, Int. J. Geogr. Inf. Syst., 9, 433–446, 1995.
Mutua, B. M., Klik, A., and Loiskandl, W.: Modeling soil erosion and sediment yield at a catchment scale: the case of masinga catchment, Kenya, Land Degrad. Dev., 17, 557–570, 2006.
Ninyerola, M., Pons, X., and Roure, J. M.: A methodological approach of climatological modelling of air temperature and precipitation through GIS techniques, Int. J. Climatol., 20, 1823–1841, 2000.
Ninyerola, M., Pons, X., and Roure, J. M.: Monthly precipitation mapping of the Iberian Peninsula using spatial interpolation tools implemented in a Geographic Information System, Theor. Appl. Climatol., 89, 195–209, 2007.
Ninyerola, M., Pons, X., and Roure, J. M.: Objective air temperature mapping for the Iberian Peninsula using spatial interpolation and GIS, Int. J. Climatol., 27, 1231–1242, 2007.
Odeh, I. O. A., McBratney, A. B., and Chittleborough, D. J.: Spatial prediction of soil properties from landform attributes derived from a digital elevation model, Geoderma, 63, 197–214, 1994.
Odeh, I. O. A., McBratney, A. B., and Chittleborough, D. J.: Further results on prediction of soil properties from terrain attributes: heterotopic cokriging and regression-kriging, Geoderma, 67(3–4), 215–226, 1995.
Onori, F., De Bonis, P., and Grauso, S.: Soil erosion prediction at the basin scale using the revised universal soil loss equation (RUSLE) in a catchment of Sicily (southern Italy), Environ. Geol., 50(8), 1129–1140, doi:10.1007/S00254-006-0286-1, 2006.
Peñarrocha, D., Estrela, M. J., and Millán, M.: Classification of daily rainfall patterns in a Mediterranean area with extreme intensity levels: the Valencia region, Int. J. Climatol., 22, 677–695, 2002.
Pons, X.: Manual of miramon, Geographic Information System and Remote Sensing Software, Centre de Recerca Ecològica i Aplicacions Forestals (CREAF): Bellaterra, available at: http://www.creaf.uab.es/miramon, 2006.
Pons, X. and Ninyerola, M.: Mapping a topographic global solar radiation model implemented in a GIS and calibrated with ground data, Int. J. Climatol., 28(13), 1821–1834, doi:10.1002/joc.1676, 2008.
Prudhome, C. and Reed, D. W.: Mapping extreme rainfall in a mountainous region using geostatistical techniques: A case study in Scotland, Int. J. Climatol., 19, 1337–1356, 1999.
R Development Core Team: $R$: A Language and Environment for Statistical Computing, Vienna (Austria), R Foundation for Statistical Computing, 2008.
Renard, K. G. and Freimund, J. R.: Using monthly precipitation data to estimate the $R$ factor in the revised USLE, J. Hydrol., 157, 287–306, 1994.
Renard, K. G., Foster, G. R., Weesies, G. A., McCool, D. K., and Yoder, D. C.: Predicting Soil Erosion by Water: A Guide to Conservation Planning with the Revised Universal Soil Loss Equation (RUSLE), Handbook #703, US Department of Agriculture, Washington, DC, 1997.
Romero, R., Guijarro, J. A., Ramis, C., and Alonso, S.: A 30-year (1964–1993) daily rainfall data base for the Spanish Mediterranean regions: first exploratory study, Int. J. Climatol., 18, 541–560, 1998.
De Santos Loureiro, N. and De Azevedo Coutinho, M.: A new procedure to estimate the RUSLE EI$_30$~index, based on monthly rainfall data and applied to the Algarve region, Portugal, J. Hydrol., 250, 12–18, doi:10.1016/S0022-1694(01)00387-0, 2001.
Shi, Z. H., Cai, C. F., Ding, S. W., Wang, T. W., and Chow, T. L.: Soil conservation planning at the small watershed level using RUSLE with GIS, Catena, 55, 33–48, 2004.
Tobler, W. R.: A computer movie simulating urban growth in Detroit region, Econ. Geogr., 46, 234–240, 1970.
Verstraeten, G., Poesen, J., Demarée, G., and Salles, C.: Long-term (105 years) variability in rain erosivity as derived from 10-min rainfall depth data for Ukkel (Brussels, Belgium): implications for assessing soil erosion rates, J. Geophys. Res., 111, D22109, doi:10.1029/2006JD007169, 2006.
Vicente-Serrano, S. M., Saz-Sánchez, M. A., and Cuadrat, J. S.: Comparative analysis of interpolation methods in the middle Ebro Valley (Spain): application to annual precipitation and temperature, Climate Res., 24, 161–180, 2003.
Vicente-Serrano, S. M.: Las sequÃas climáticas en el valle medio del Ebro: factores atmosféricos, evolución temporal y variabilidad espacial, Publicaciones del Consejo de Protección de la Naturaleza de Aragón, 2005.
Vicente-Serrano, S. M., Lanjeri, S., and López-Moreno, J. I.: Comparison of different procedures to map reference evapotranspiration using geographical information systems and regression-based techniques, Int. J. Climatol., 27, 1103–1118, 2007.
Vogt, J. V., Viau, A. A., and Paquet, F.: Mapping regional air temperature fields using satellite derived surface skin temperatures, Int. J. Climatol., 17, 1559–1579, 1997.
Wackernagel, H.: Multivariate Geostatistics: an introduction with applications, Springer, Berlin/London, XIV, 1998.
Weisse, A. K. and Bois, P.: A comparison of methods for mapping statistical characteristics of heavy rainfall in the French Alps: The use of daily information, Hydrolog. Sci. J., 47, 739–752, 2002.
Weiss, S. M. and Kulikowski, C. A.: Computer Systems That Learn, Morgan Kaufmann, 1991.
Willmott, C. J.: On the validation of models, Phys. Geogr., 2, 184–194, 1981.
Willmott, C. J. and Matsuura, K.: Advantages of the mean absolute error (MAE) over the root mean square error (RMSE) in assessing average model performance, Climate Res., 30, 79–82, 2005.
Winchell, M. F., Jackson, S. H., Wadley, A. M., and Srinivasan, R.: Extension and validation of a geographic information system-based method for calculating the Revised Universal Soil Loss Equation length-slope factor for erosion risk assessments in large watersheds, J. Soil Water Conserv., 63, 105–111, 2008.
Wischmeier, W. H.: A rainfall erosion index for a universal soil-loss equation, Soil Sci. Soc. Am. Pro., 23, 246–249, 1959.
Wischmeier, W. H. and Smith, D. D.: Predicting rainfall erosion losses: a guide to conservation planning, USDA Handbook 537, Washington, DC, 1978.