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Impact of climate change on soil erosion and the efficiency of soil conservation practices in Austria

Published online by Cambridge University Press:  30 March 2010

A. KLIK  and
J. EITZINGER
A. KLIK*
Affiliation:
Institute for Hydraulics and Rural Water Management, Department for Water, Atmosphere and Environment, University of Natural Resources and Applied Life Sciences, Muthgasse 18, A-1190Vienna, Austria
J. EITZINGER
Affiliation:
Institute of Meteorology, Department for Water, Atmosphere and Environment, University of Natural Resources and Applied Life Sciences, Peter Jordan Strasse 82, A-1190Vienna, Austria
*
*To whom all correspondence should be addressed. Email: [email protected]
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Summary

The goal of the present study was to assess the impact of selected soil protection measures on soil erosion and retention of rainwater in a 1·14 km2 watershed used for agriculture in the north-east of Austria. Watershed conditions under conventional tillage (CT), no-till (NT) and under grassland use were simulated using the Water Erosion Prediction Project (WEPP) soil erosion model. The period 1961–90 was used as a reference and results were compared to future Intergovernmental Panel on Climate Change (IPCC) scenarios A1B and A2 (2040–60).

The simulations for the NT and grassland options suggested runoff would decrease by 38 and 75%, respectively, under the current climatic conditions. The simulation results suggest that, under future climate scenarios, the effectiveness of the selected soil conservation measures with respect to runoff will be similar, or decreased by 16–53%.

The actual average net soil losses in the watershed varied from 2·57 t/ha/yr for conventional soil management systems to 0.01 t/ha/yr for grassland. This corresponds to a maximum average annual loss of about 0·2 mm, which is considered to be the average annual soil formation rate and therefore an acceptable soil loss. The current soil/land use does not exceed this limit, with most of the erosion occurring during spring time. Under future climate scenarios, the simulations suggested that CT would either decrease soil erosion by up to 55% or increase it by up to 56%. Under these conditions, the acceptable limits will partly be exceeded. The simulations of NT suggested this would reduce annual soil loss rates (compared to CT) to 0·2 and 1·4 t/ha, i.e. about the same or slightly higher than for NT under actual conditions. The simulation of conversion to grassland suggested soil erosion was almost completely prevented.

The selected soil conservation methods maintain their protective effect on soil resources, independent of the climate scenario. Therefore, with small adaptations, they can also be recommended as sustainable soil/land management systems under future climatic conditions.

However, based on the available climate scenarios, climate-induced changes in the frequency and intensity of heavy rainstorms were only considered in a limited way in the present work. As the general future trend indicates a strong increase of rainstorms with high intensity during summer months, the results of the present study may be too optimistic.

Type
Climate Change and Agriculture
Information
The Journal of Agricultural Science , Volume 148 , Issue 5 , October 2010 , pp. 529 - 541
Copyright
Copyright © Cambridge University Press 2010

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References

REFERENCES

Bundesministerium für Land- Und Forstwirtschaft, Umwelt und Wasserwirtschaft (BMLFUW). (2007). Sonderrichtlinie des BMLFUW für das Österreichische Programm zur Förderung einer umweltgerechten, extensiven und den natürlichen Lebensraum schützenden Landwirtschaft (ÖPUL 2007). GZ BMLFUW-LE.1.1.8/0073-II/8/2007. Vienna, Austria: BMLFUW.Google Scholar
Dubrovsky, M., Bichtele, J. & Zalud, Z. (2004). High-frequency and low-frequency variability in stochastic daily weather generator and its effect on agricultural and hydrologic modelling. Climatic Change 63, 145–179.CrossRefGoogle Scholar
European Environment Agency (EEA). (1999). Environment in the European Union at the Turn of the Century. Copenhagen, Denmark: European Environment Agency.Google Scholar
European Environment Agency (EEA). (2000). Down to Earth. Soil Degradation and Sustainable Development in Europe – A Challenge for the 21st Century. Environmental Issue Report No. 16. Copenhagen, Denmark: European Environment Agency.Google Scholar
Flanagan, D. C. & Nearing, M. A. (1995). USDA-Water Erosion Prediction Project. Hillslope Profile and Watershed Model Documentation. NSERL Report No. 10. West Lafayette, IN: U. S. National Soil Erosion Research Laboratory.Google Scholar
Formayer, J. H., Eitzinger, J., Nefzger, H., Simic, S. & Kromp-Kolb, H. (2001). Auswirkungen einer Klimaveränderung in Österreich. Was aus bisherigen Untersuchungen ableitbar ist. Vienna, Austria: Institut für Meteorologie und Physik; Universität für Bodenkultur Wien.Google Scholar
Harvey, L. D. D., Gregory, J., Hoffert, M., Jain, A., Lal, M., Leemans, R., Raper, S. B. C., Wigley, T. M. L. & de Wolde, J. (1997). An Introduction to Simple Climate Models used in the IPCC Second Assessment Report: IPCC Technical Paper 2. Geneva, Switzerland: Intergovernmental Panel on Climate Change.Google Scholar
Hofmann, J. (2005). Auswirkungen unterschiedlicher Bodenbearbeitungssysteme auf die Bodengesundheit. Ph.D. thesis, Institut für Hydraulik und Landeskulturelle Wasserwirtschaft der Universität für Bodenkultur, Wien.Google Scholar
Hulme, M., Wigley, T. M. L., Barrow, E. M., Raper, S. C. B., Centella, A., Smith, S. & Chipanshi, A. C. (2000). Using a Climate Scenario Generator for Vulnerability and Adaptation Assessments: MAGICC and SCENGEN Version 2.4 Workbook. Norwich, UK: Climatic Research Unit, University of East Anglia/NCSP.Google Scholar
IPCC (2000). Emission Scenarios 2000. Special Report of the Intergovernmental Panel on Climate Change. Cambridge, UK: Cambridge University Press.Google Scholar
IPCC (2001). Climate Change 2001: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Third Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, UK: Cambridge University Press.Google Scholar
Jones, R. J. A., Le Bissonnais, Y. L., Diaz, J. S., Düwel, O., Øygarden, L., Bazzoffi, P., Prasuhn, V., Yordanov, Y., Strauss, P., Rydell, B., Uveges, J. B., Loj, G., Lane, M. & Vandekerckhove, L. (2003). Work Package 2: Nature and Extent of Soil Erosion in Europe. Interim Report Version 3.31. EU Soil Thematic Strategy, Technical Working Group on Erosion. Brussels: European Commission – GD Environment.Google Scholar
Klik, A. (2003). Einfluss unterschiedlicher Bodenbearbeitung auf Oberflächenabfluss, Bodenabtrag sowie Nährstoff- und Pestizidausträge. Österreichische Wasser- und Abfallwirtschaft 55, 89–96.Google Scholar
Klik, A. & Zartl, A. S. (2001). Comparison of soil erosion simulations using WEPP and RUSLE with field measurements. In Proceedings of the International Symposium ‘Soil Erosion Research for the 21st Century’, 3–5 January 2001, Honolulu, Hawaii (Eds Ascough, J. C. & Flanagan, D. C.), pp. 350–353. St. Joseph, MI: ASAE.Google Scholar
Klik, A., Jester, W. & Rauter, C. (2005). Sediment transport in a small agricultural watershed – evaluation of WEPP simulations with measured data. In Sediment Budgets 2. Vol. 2 of the Proceedings of the International Symposium on Sediment Budgets, VIIth Scientific Assembly of the IAHS, Foz do Iguazu, Brazil, 3–9 April, 2005 (Eds Horowitz, A. J. & Walling, D. E.), pp. 127–135. IAHS Publication No. 292. Wallingford, UK: International Association of Hydrological Sciences Press, Centre for Ecology and Hydrology.Google Scholar
Nearing, M. A. (2001). Potential changes in rainfall erosivity in the U. S. with climate change during the 21st Century. Journal of Soil and Water Conservation 56, 220–232.Google Scholar
Nearing, M. A., Jetten, V., Baffaut, C., Cerdan, O., Couturier, A., Hernandez, M., Le Bissonnais, Y., Nichols, M. H., Nunes, J. P., Renschler, C. S., Souchère, V. & van Oost, K. (2005). Modeling response of soil erosion and runoff to changes in precipitation and cover. Catena 61, 131–154.CrossRefGoogle Scholar
Nicks, A. D., Lane, L. J. & Gander, G. A. (1995). Chapter 2: Weather generator. In USDA-Water Erosion Prediction Project Hillslope Profile and Watershed Model Documentation (Eds Flanagan, D. C. & Nearing, M. A.), pp. 2.1–2.22. NSERL Report No. 10. West Lafayette, IN: U. S. National Soil Erosion Research Laboratory.Google Scholar
OECD (2001). Environmental Indicators for Agriculture: Methods and Results. Vol. 3. Paris, France: OECD.Google Scholar
Österreichische Bodenkartierung (1995). Bodenkarte und Erläuterungen zur Bodenkarte 1:25·000, Kartierungsbereich Mistelbach. Bundesministerium für Land- und Forstwirtschaft, Wien.Google Scholar
Pruski, F. F. & Nearing, M. A. (2002 a). Runoff and soil-loss responses to changes in precipitation: a computer simulation study. Journal of Soil and Water Conservation 57, 7–16.Google Scholar
Pruski, F. F. & Nearing, M. A. (2002 b). Climate-induced changes in erosion during the 21st century for eight U. S. locations. Water Resources Research 38, 1298.CrossRefGoogle Scholar
Renard, K. R., Foster, G. R., Weesies, G. A., McCool, D. K. & Yoder, D. C. (1995). Predicting Soil Erosion by Water: A Guide to Conservation Planning with the Revised Universal Soil Loss Equation (RUSLE). Agricultural Handbook No. 703. Washington, DC: U. S. Department of Agriculture.Google Scholar
Renschler, C. S. (2003). Designing geo-spatial interfaces to scale process models: the GeoWEPP approach. Hydrological Processes 17, 1005–1017.CrossRefGoogle Scholar
Röckner, E., Arpe, K., Bengtsson, L., Christoph, M., Claussen, M., Dümenil, L., Esch, M., Giorgetta, M., Schlese, U. & Schulzweida, U. (1996). The Atmospheric General Circulation Model ECHAM4: Model Description and Simulation of Present-day Climate. Report No. 218. Hamburg, Germany: Max Planck Institut für Meteorologie.Google Scholar
Röckner, E., Bäuml, G., Bonaventura, L., Brokopf, R., Esch, M., Giorgetta, M., Hagemann, S., Kirchner, I., Kornblüh, L., Manzini, E., Rhodin, A., Schlese, U., Schulzweida, U. & Tompkins, A. (2003). The Atmospheric General Circulation Model ECHAM5. Report No. 349, Model description. Hamburg, Germany: Max-Planck-Institut für Meteorologie.Google Scholar
Santer, B. D., Wigley, T. M. L., Schlesinger, M. E. & Mitchell, J. F. B. (1990). Developing Climate Scenarios from Equilibrium GCM results. Report No. 47. Hamburg, Germany: Max-Planck-Institut-für-Meteorologie.Google Scholar
Schaap, M. G., Leij, F. J. & van Genuchten, M. Th. (1998). Neural network analysis for hierarchical prediction of soil water retention and saturated hydraulic conductivity. Soil Science Society of America Journal 62, 847–855.CrossRefGoogle Scholar
Scholz, G., Quinton, J. N. & Strauss, P. (2008). Soil erosion from sugar beet in Central Europe in response to climate change induced seasonal precipitation variations. Catena 72, 91–105.CrossRefGoogle Scholar
Semenov, V. A. & Bengtsson, L. (2002). Secular trends in daily precipitation characteristics: greenhouse gas simulation with a coupled AOGCM. Climate Dynamics 19, 123–140.Google Scholar
Statistix (1996). Statistix Version 1.0. Tallahassee, FL: Analytical Software.Google Scholar
Strauss, P. & Klaghofer, E. (2006). Austria. In Soil Erosion in Europe (Eds Boardman, J. & Poesen, J.), pp. 205–212. Chichester, UK: John Wiley and Sons Ltd.CrossRefGoogle Scholar
Strauss, P., Auerswald, K., Blum, W. E. H. & Klaghofer, E. (1995). Erosivität von Niederschlägen. Ein Vergleich Österreich-Bayern. Zeitschrift für Kulturtechnik und Landentwicklung 36, 304–309.Google Scholar
Trnka, M., Dubrovsky, M., Semeradova, D. & Zalud, Z. (2004). Projections of uncertainties in climate change scenarios into expected winter wheat yields. Theoretical and Applied Climatology 77, 229–249.CrossRefGoogle Scholar
U. S. Department of Agriculture, Soil Conservation Service (USDA-SCS) (1992). Soil Survey Laboratory Manual. Soil Survey Investigations Report No. 42. Version 2.0. National Soil Survey Center, Lincoln, NE, USA.Google Scholar
Williams, J. R., Jones, C. A., Kiniry, J. R. & Spanel, D. A. (1989). The EPIC crop growth model. Transactions of the ASAE 32, 497–511.CrossRefGoogle Scholar