Alteration of Revised Universal Soil Loss Equation (RUSLE) for application in mountainous, snowy regions

• Název v anglickém jazyce: Alteration of Revised Universal Soil Loss Equation (RUSLE) for application in mountainous, snowy regions
• Klíčová slova: Soil erosion, RUSLE, modeling, hydrology
• Klíčová slova anglicky: Soil erosion, RUSLE, modeling, hydrology
• Akademický rok vypsání: 2013/2014
• Typ práce: disertační práce
• Jazyk práce: angličtina
• Ústav: Katedra fyzické geografie a geoekologie (31-330)
• Vedoucí / školitel: prof. RNDr. Jakub Langhammer, Ph.D.
• Řešitel: skrytý - zadáno vedoucím/školitelem
• Datum přihlášení: 17.12.2013
• Datum zadání: 17.12.2013

Předběžná náplň práce

The dominant model applied worldwide to soil loss prediction is the Universal Soil Loss Equation or the Revised Universal Soil Loss Equation (Prasannakumar et al. 2011). These are empirical models that were initially developed to predict water-based erosion in temperate climates, and are more adaptable to tropical climates than other models (Prasannakumar et al. 2011, Angima et al. 2003). Erosion estimations are made through the combination of six biophysical factors: rainfall data (R), soil erodibility (K), slope length (L), slope steepness (S), cropping (C), and conservation practices (P), which are multiplied to result in the estimated average rate of soil loss in tons per hectare per year (Schwab et al. 1992).
The RUSLE has been adapted to particular areas, such as central Kenya, southeastern Ethopia, Rondônia in Brazil, Kerala in India, and others (Angima et al. 2003, Bouaziz et al. 2011, Lu et al. 2004, Prasannakumar et al. 2011). However, these adaptations have been for mid-latitude and tropical areas, and the RUSLE may not be as accurate in cases where soil is affected by freezing and thawing cycles, as the K factor is generally only estimated from frost-free days (Renard et al. 1991).
This is a major limitation, as processes such as cryoturbation, frost heaving, and other types of frost-related weathering can affect soil detachment, saturation, and water infiltration (Fontaine et al. 2002). While other models, such as EUROSEM, CREAMS, WEPP exist, they often assume a steady surface flow profile, en (Morgan et al. 1998), and thus would not be applicable to areas with significant differences across their flow profiles.
The Otava river basin in southern Bohemia has been assessed for runoff factors and landscape dynamics, including precipitation (Langhammer et al. 2008). As the Otava river basin experiences precipitation in the form of snow, it is essential to use a soil erosion prediction model that includes a factor for snow and ice impact on the movement of soil particles. By understanding these effects, soil erosion may be better predicted, preventing floods and reducing high-volume runoff through more specialized conservation practices.
Development of this factor would include determining the effects of the dynamics of cryoturbation on soils in the study area, impact of vegetation and urbanization, and differences in surface flow.

Předběžná náplň práce v anglickém jazyce

The dominant model applied worldwide to soil loss prediction is the Universal Soil Loss Equation or the Revised Universal Soil Loss Equation (Prasannakumar et al. 2011). These are empirical models that were initially developed to predict water-based erosion in temperate climates, and are more adaptable to tropical climates than other models (Prasannakumar et al. 2011, Angima et al. 2003). Erosion estimations are made through the combination of six biophysical factors: rainfall data (R), soil erodibility (K), slope length (L), slope steepness (S), cropping (C), and conservation practices (P), which are multiplied to result in the estimated average rate of soil loss in tons per hectare per year (Schwab et al. 1992).
The RUSLE has been adapted to particular areas, such as central Kenya, southeastern Ethopia, Rondônia in Brazil, Kerala in India, and others (Angima et al. 2003, Bouaziz et al. 2011, Lu et al. 2004, Prasannakumar et al. 2011). However, these adaptations have been for mid-latitude and tropical areas, and the RUSLE may not be as accurate in cases where soil is affected by freezing and thawing cycles, as the K factor is generally only estimated from frost-free days (Renard et al. 1991).
This is a major limitation, as processes such as cryoturbation, frost heaving, and other types of frost-related weathering can affect soil detachment, saturation, and water infiltration (Fontaine et al. 2002). While other models, such as EUROSEM, CREAMS, WEPP exist, they often assume a steady surface flow profile, en (Morgan et al. 1998), and thus would not be applicable to areas with significant differences across their flow profiles.
The Otava river basin in southern Bohemia has been assessed for runoff factors and landscape dynamics, including precipitation (Langhammer et al. 2008). As the Otava river basin experiences precipitation in the form of snow, it is essential to use a soil erosion prediction model that includes a factor for snow and ice impact on the movement of soil particles. By understanding these effects, soil erosion may be better predicted, preventing floods and reducing high-volume runoff through more specialized conservation practices.
Development of this factor would include determining the effects of the dynamics of cryoturbation on soils in the study area, impact of vegetation and urbanization, and differences in surface flow.