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Soil erosion prediction using the Revised Universal Soil Loss Equation (RUSLE) in a GIS framework, Chania, Northwestern Crete, Greece

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Environmental Geology

Abstract

Soil erosion is a growing problem in southern Greece and particularly in the island of Crete, the biggest Greek island with great agricultural activity. Soil erosion not only decreases agricultural productivity, but also reduces the water availability. In the current study, an effort to predict potential annual soil loss has been conducted. For the prediction, the Revised Universal Soil Loss Equation (RUSLE) has been adopted in a Geographical Information System framework. The RUSLE factors were calculated (in the form of raster layers) for the nine major watersheds which cover the northern part of the Chania Prefecture. The R-factor was calculated from monthly and annual precipitation data. The K-factor was estimated using soil maps available from the Soil Geographical Data Base of Europe at a scale of 1:1,000,000. The LS-factor was calculated from a 30-m digital elevation model. The C-factor was calculated using Remote Sensing techniques. The P-factor in absence of data was set to 1. The results show that an extended part of the area is undergoing severe erosion. The mean annual soil loss is predicted up to ∼200 (t/ha year−1) for some watersheds showing extended erosion and demanding the attention of local administrators.

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Acknowledgments

The project is co-funded by the European Social Fund and National Resources in the framework of the project INTERREG III B ARCHIMED, sub-project A1.020 entitled “MILDMAP—Methodology Integration of EO techniques as operative tool for Land Degradation Management and planning in Mediterranean Areas”. The authors are grateful to the anonymous reviewers for their very helpful comments and valuable suggestions.

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  1. Institute of Natural Resources and Natural Hazards, Center of Technological Research of Crete (CTRC), 3 Romanou, Chalepa, 73133, Chania, Crete, Greece

    Maria Kouli, Pantelis Soupios & Filippos Vallianatos

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  1. Maria Kouli
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  2. Pantelis Soupios
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  3. Filippos Vallianatos
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Correspondence to Maria Kouli.

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Kouli, M., Soupios, P. & Vallianatos, F. Soil erosion prediction using the Revised Universal Soil Loss Equation (RUSLE) in a GIS framework, Chania, Northwestern Crete, Greece. Environ Geol 57, 483–497 (2009). https://doi.org/10.1007/s00254-008-1318-9

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