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2 Acta Geophysica

2 2020

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Multiscale comparison of LS factor calculation methods based on diferent fow direction algorithms in Susa Ancient landscape

Khanifar Javad, Khademalrasoul Ataallah

Acta Geophysica

2020

Vol. 68, no. 3

783--793

Topography (LS factor) is one of the most important controlling factors of soil characteristics and geomorphic processes in the landscape. This study was performed in the Susa Ancient site and aimed to compare the estimation of three diferent LS factor calculation methods in which the catchment area was calculated based on seven types of fow direction algorithms using DEM with fve spatial resolutions. For calculating the LS factor, the catchment area attribute was used to calculate the slope length based on the fow direction. Results showed that the catchment area is an entirely scale-dependent attribute and with decreasing the spatial resolution, the statistical values of catchment area increased. At high spatial resolution, the diferent fow direction algorithms despite the diference in the fow distribution to the neighboring cells, but the catchment area attributes calculated based on them, are statistically slightly diferent. By upscaling, the LS factor values calculated in Boehner and Selige and Moore et al. methods increase, whereas in Desmet and Govers method decrease and this change rate indicates that the LS factors calculated by these three methods have the lowest sensitivity to the slope length. At a same scale, the statistics of LS factors calculated based on diferent fow direction algorithms depicted no considerable diferent. The single fow direction algorithms of Rh and D8 cause to calculate the lowest mean values of LS factors at all spatial resolutions. The diference between frequency distributions of the LS factors calculated by these three methods increases with decreasing spatial resolution. The statistical analysis of this study confrms that estimating the LS factor scale and calculation method are more important than the type of fow direction algorithm.

Multi objective optimization of soil erosion parameters using response surface method (RSM) in the Emamzadeh watershed

Shirazi Mojtaba, Khademalrasoul Ataallah, Safeddin Ardebili Seyed Mohammad

Acta Geophysica

2020

Vol. 68, no. 2

505--517

Soil erosion is one of the most leading environmental and public health problems in the world which dislodges considerable volumes of soil annually. In order to control soil erosion, several soil factors should be taken into account. Regarding the importance of soil properties on erosion occurrence, it is necessary to focus on soil properties. The aim of this study is to evaluate the efect of physical parameters that consist of sand %, silt %, clay %, SP % and stone % along with hydraulic properties including theta s, theta r, alpha n and Ks (cm/day) on the amount of soil erosion in Emamzadeh watershed. The above-mentioned factors were optimized using response surface methodology. The soil texture in the study area is mostly silty clay loam, and the main soil orders are Entisols and Inceptisols. Moreover, the main land use in the study area is forest–rangeland. The results proved that both physical and hydraulic valuables illustrated a signifcant efect on all of the independent parameters. The optimized values of diferent physical parameters were 60.241 for sand, 14 for silt, 41.025 for clay, 58.729% for SP and 3.83% for stone. A theta r of 0.09, theta s of 0.457 alpha of 0.014, n of 1.3 and Ks of 46.01 were found to be optimal values. The results of this study indicated that at optimal studied parameters, the values of the soil erosion before and after application of management scenarios were found to be 11.537 and −2.253, respectively. Results show that both physical and hydraulic parameters have signifcant efects at the 1% level on the soil erosion before and after application of management scenarios. The obtained results could assist policy-makers with decisions aimed at minimizing soil erosion in this watershed. In summary, using the simulation–optimization techniques helps to evaluate the efect of management scenarios, then select and apply the best one to minimize the soil erosion outcomes.