Reply to Comment on “determining soil erodibility for the USLE-MM rainfall erosion model by P.I.A. Kinnell”

P. I.A. Kinnell

Research output: Contribution to journalComment/debate

1 Citation (Scopus)

Abstract

In Kinnell (2018), I proposed that the soil erodibility factor KUMM used in the USLE-MM model could be replaced by the product of the soil erodibility factor KUM and a coefficient a1 that was given by the ratio of between KUMM and KUM. The theory was developed based on the well-known practice that for USLE based models, the erodibility factor is calculated as the ratio between the total soil loss for a set of erosion producing events and the total value of the erosivity index associated with those events. In their comment, Pampalone et al. (2018) used data for KUMM and KUM values for 12 plots at Sparacia determined by regression analysis to calculate a1 using a different method to show that the exponential equation I proposed in Kinnell (2018) between the power of the erosivity term and the a1 was demonstrated to be site dependent. In this reply, the approach adopted by Pampalone et al. is challenged for not using the well-known method for determining soil erodibilities in USLE based models and the consequences of power increasing with slope length while the runoff ratio decreases with slope length on the values of a1 is illustrated. At Sparacia, soil loss varies with KUM, slope length, and slope gradient, and, in addition, in the context of the USLE-MM, consideration has to be given to the fact that both b1 and the runoff ratio vary with slope length.

Original languageEnglish
Pages (from-to)444-447
Number of pages4
JournalCatena
Volume167
DOIs
Publication statusPublished - 1 Aug 2018

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Universal Soil Loss Equation
erodibility
erosion
rainfall
erosivity
soil
runoff
regression analysis

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title = "Reply to Comment on “determining soil erodibility for the USLE-MM rainfall erosion model by P.I.A. Kinnell”",
abstract = "In Kinnell (2018), I proposed that the soil erodibility factor KUMM used in the USLE-MM model could be replaced by the product of the soil erodibility factor KUM and a coefficient a1 that was given by the ratio of between KUMM and KUM. The theory was developed based on the well-known practice that for USLE based models, the erodibility factor is calculated as the ratio between the total soil loss for a set of erosion producing events and the total value of the erosivity index associated with those events. In their comment, Pampalone et al. (2018) used data for KUMM and KUM values for 12 plots at Sparacia determined by regression analysis to calculate a1 using a different method to show that the exponential equation I proposed in Kinnell (2018) between the power of the erosivity term and the a1 was demonstrated to be site dependent. In this reply, the approach adopted by Pampalone et al. is challenged for not using the well-known method for determining soil erodibilities in USLE based models and the consequences of power increasing with slope length while the runoff ratio decreases with slope length on the values of a1 is illustrated. At Sparacia, soil loss varies with KUM, slope length, and slope gradient, and, in addition, in the context of the USLE-MM, consideration has to be given to the fact that both b1 and the runoff ratio vary with slope length.",
keywords = "Runoff plots, Soil loss prediction",
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language = "English",
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Reply to Comment on “determining soil erodibility for the USLE-MM rainfall erosion model by P.I.A. Kinnell”. / Kinnell, P. I.A.

In: Catena, Vol. 167, 01.08.2018, p. 444-447.

Research output: Contribution to journalComment/debate

TY - JOUR

T1 - Reply to Comment on “determining soil erodibility for the USLE-MM rainfall erosion model by P.I.A. Kinnell”

AU - Kinnell, P. I.A.

PY - 2018/8/1

Y1 - 2018/8/1

N2 - In Kinnell (2018), I proposed that the soil erodibility factor KUMM used in the USLE-MM model could be replaced by the product of the soil erodibility factor KUM and a coefficient a1 that was given by the ratio of between KUMM and KUM. The theory was developed based on the well-known practice that for USLE based models, the erodibility factor is calculated as the ratio between the total soil loss for a set of erosion producing events and the total value of the erosivity index associated with those events. In their comment, Pampalone et al. (2018) used data for KUMM and KUM values for 12 plots at Sparacia determined by regression analysis to calculate a1 using a different method to show that the exponential equation I proposed in Kinnell (2018) between the power of the erosivity term and the a1 was demonstrated to be site dependent. In this reply, the approach adopted by Pampalone et al. is challenged for not using the well-known method for determining soil erodibilities in USLE based models and the consequences of power increasing with slope length while the runoff ratio decreases with slope length on the values of a1 is illustrated. At Sparacia, soil loss varies with KUM, slope length, and slope gradient, and, in addition, in the context of the USLE-MM, consideration has to be given to the fact that both b1 and the runoff ratio vary with slope length.

AB - In Kinnell (2018), I proposed that the soil erodibility factor KUMM used in the USLE-MM model could be replaced by the product of the soil erodibility factor KUM and a coefficient a1 that was given by the ratio of between KUMM and KUM. The theory was developed based on the well-known practice that for USLE based models, the erodibility factor is calculated as the ratio between the total soil loss for a set of erosion producing events and the total value of the erosivity index associated with those events. In their comment, Pampalone et al. (2018) used data for KUMM and KUM values for 12 plots at Sparacia determined by regression analysis to calculate a1 using a different method to show that the exponential equation I proposed in Kinnell (2018) between the power of the erosivity term and the a1 was demonstrated to be site dependent. In this reply, the approach adopted by Pampalone et al. is challenged for not using the well-known method for determining soil erodibilities in USLE based models and the consequences of power increasing with slope length while the runoff ratio decreases with slope length on the values of a1 is illustrated. At Sparacia, soil loss varies with KUM, slope length, and slope gradient, and, in addition, in the context of the USLE-MM, consideration has to be given to the fact that both b1 and the runoff ratio vary with slope length.

KW - Runoff plots

KW - Soil loss prediction

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JO - Catena

JF - Catena

SN - 0341-8162

ER -