Son i oss PRFnim on

Si Ji /mir m-wa ferslwrl s

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Si Ji /mir m-wa ferslwrl s

Sml miHPivfliiínii nmii^Tfliiinii nf^ih/mírni xjuatvrflliiWlft

CP- FACTOR

Figure 6: Factors of USLE and model predicted erosional soil loss (Bhogabati Watershed, Kolhapur District, Maharashtra, India)

CP- FACTOR

Figure 6: Factors of USLE and model predicted erosional soil loss (Bhogabati Watershed, Kolhapur District, Maharashtra, India)

Qgis Python Flowchart

Figure 7: Flow diagram of methodology of soil erosion modeling using MMF model

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Figure 7: Flow diagram of methodology of soil erosion modeling using MMF model

Figure 8: MMF model parameters F & G and model predicted erosional soil loss (Dehra Dun District, Uttaranchal, India)

been its ineffectiveness in applications outside the range of conditions for which it was developed. The process models and physically-based model have an advantage over simple statistical empirical models when individual processes and components that affect erosion are described simply and effectively. The disadvantages of these models are that the mathematical representation of a natural process can only be approximate and there are difficulties in the parameter prediction procedures. RS and GIS techniques are very effective tools for soil erosion modeling and erosion risk assessment.

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