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Soil Erosion estimation for the Göta Älv river using remote sensing, GIS and the Revised Universal Soil Loss Equation (RUSLE) model
Stockholm University, Faculty of Science, Department of Physical Geography.
2019 (English)Independent thesis Advanced level (degree of Master (One Year)), 40 credits / 60 HE creditsStudent thesis
Abstract [en]

According to previous studies, the study area of Göta Älv river has high risk of landslides along the river banks due to the water flow. Soil erosion can affect the increase of the landslides in an area with unstable soils caused by the increase rainfall. The Swedish climate is getting more vulnerable thus there is a potential increased risk in erosion and landslides due to unpredictable rainfall intensity. This study aims to calculate soil erosion for the Göta Älv river using the Revised Universal Soil Loss Equation (RUSLE) where a comparison of data from remote sensing and meteorological and geological agencies were completed. Two research questions will be addressed, first if the different calculation of the soil erodibility (K) factor affects RUSLE result, and second how much soil erosion occurs and will potentially occur in the future. Factors including rainfall erosivity (R), soil erodibility (K), slope length and steepness (LS), land cover management (C) and conservation practices (P) were analyzed and used as inputs for the RUSLE model. Moreover, three scenarios were applied for the calculation of K factor in order to show how each one can affect the soil erosion result. The scenarios includes the K-scenario 1, 2 and 3, where the values were derived from a world soil database, a table with literature values and estimated field measurements, respectively. Also, three scenarios for R factor were applied for the periods 2000-2018, 2021-2050 and 2069-2098 (R-scenarios 1, 2 and 3) in order to show how future changes to rainfall patterns could affect soil erosion in the Göta Älv river and if it increases the risk of the landslides. The results suggest that the soil erosion varied between 0 – 0.5 t/ha for all the time periods with mean annual soil loss between 20 – 22 t/ha/yr and maximum soil loss between 2158- 5443 t/ha. The difference between the three K factor scenarios is almost 4%, which is pretty low thus, no influence on the soil erosion results. In conclusion, the different calculations of the K factor affected more the estimated maximum soil loss instead of the mean annual soil loss. The different calculations of R factor showed that more than 90% of the total area was not affected by the soil erosion when the soil loss will not be increased considerably in the future due to the rainfall increase.

Place, publisher, year, edition, pages
2019. , p. 47
National Category
Physical Geography
Identifiers
URN: urn:nbn:se:su:diva-175412OAI: oai:DiVA.org:su-175412DiVA, id: diva2:1365607
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Available from: 2019-11-12 Created: 2019-10-25 Last updated: 2019-11-12Bibliographically approved

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