Gully-head has been observed in a wide range of continuous and categorical conditioning factors in different countries. This study aimed to examine the association of gully-heads with the most effective hydrologic factors via univariate and bivariate analyses in the standard mode. A 2700 ha area in the loess-covered region of Iran was selected and the point map of 287 gully-heads prepared by unmanned aerial vehicle (UAV) images. The pattern of gully-heads was evaluated using univariate tests (O(r) &g(r)). The occurrence of gully-heads in relation to the linear features including road networks (RNS) and stream networks(SNS) was assessed using bivariate correlation tests(O12(r) g12(r)). The analysis mode in mark correlation function (kmm(r)) was applied for soil particles categorized into three groups by size including clay, sand, and silt content. The Mont Carlo simulation intervals were also conducted based on fifth highest and lowest values of the summary statistic of 199 simulated null model data sets. According to the results of the univariate spatial statistics, gully-heads had an aggregated distribution. The bivariate O-ring and pair correlation (g12(r)) test revealed that gully-heads had positive interactions with RNS and SNS. Based on mark correlation function kmm(r), clay content of nearby gully-heads was consistently smaller than the mean value of clay content (?2 = 22.93%) in the study area. However, the silt contents of nearby gully-heads were significantly larger than the mean value of silt content (?2 = 64.58%). The mean sand contents (?2 = 14.75%) do not differ from the mean sand contents taken over all pair gully-heads. Consequently, compared to other interoperation, the suggested approach prepares a proper technique to erosion research community which would be of interest to policy makers and geomorphologists.

Factors Affecting Gully-Head Activity in a Hilly Area Under a Semiarid Climate in Iran

Rossi;Mauro
2020

Abstract

Gully-head has been observed in a wide range of continuous and categorical conditioning factors in different countries. This study aimed to examine the association of gully-heads with the most effective hydrologic factors via univariate and bivariate analyses in the standard mode. A 2700 ha area in the loess-covered region of Iran was selected and the point map of 287 gully-heads prepared by unmanned aerial vehicle (UAV) images. The pattern of gully-heads was evaluated using univariate tests (O(r) &g(r)). The occurrence of gully-heads in relation to the linear features including road networks (RNS) and stream networks(SNS) was assessed using bivariate correlation tests(O12(r) g12(r)). The analysis mode in mark correlation function (kmm(r)) was applied for soil particles categorized into three groups by size including clay, sand, and silt content. The Mont Carlo simulation intervals were also conducted based on fifth highest and lowest values of the summary statistic of 199 simulated null model data sets. According to the results of the univariate spatial statistics, gully-heads had an aggregated distribution. The bivariate O-ring and pair correlation (g12(r)) test revealed that gully-heads had positive interactions with RNS and SNS. Based on mark correlation function kmm(r), clay content of nearby gully-heads was consistently smaller than the mean value of clay content (?2 = 22.93%) in the study area. However, the silt contents of nearby gully-heads were significantly larger than the mean value of silt content (?2 = 64.58%). The mean sand contents (?2 = 14.75%) do not differ from the mean sand contents taken over all pair gully-heads. Consequently, compared to other interoperation, the suggested approach prepares a proper technique to erosion research community which would be of interest to policy makers and geomorphologists.
2020
Istituto di Ricerca per la Protezione Idrogeologica - IRPI
978-3-030-23243-6
Gully-head
Spatial modeling
Road networks
Stream networks
Soil texture
Iran
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/404658
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