干旱区生态环境知识资源中心(Arid): Digital mapping of Philip model parameters for prediction of water infiltration at the watershed scale in a semi-arid region of Iran

Arid

DOI	10.1016/j.geodrs.2020.e00301
	Digital mapping of Philip model parameters for prediction of water infiltration at the watershed scale in a semi-arid region of Iran
	Tashayo, Behnam; Honarbakhsh, Afshin; Akbari, Mohammad; Ostovari, Yaser
通讯作者	Honarbakhsh, A
来源期刊	GEODERMA REGIONAL
ISSN	2352-0094
出版年	2020
卷号	22
英文摘要	Modeling water infiltration rate at the regional scale with the ruler of calcareous conditions is important for a better understanding of infiltration processes and infiltration modeling development. The aim of the present study was to derive and evaluate a digital soil mapping of the Philip model parameters (sorptivity and hydraulic conductivity) to predict water infiltration using environmental data in calcareous soils in northwest Iran. The infiltration data was carried out at 92 locations at the field scale with three replications. At each location, the various basic soil properties were measured, and environmental data obtained from attributes was derived from digital elevation models and remote sensing data. The feed-forward multilayer perceptron artificial neural networks (ANN) model was used to estimate sorptivity (S) and hydraulic conductivity (K-s). For the first type of prediction models, the measured basic soil properties, and for the second type, the measured basic soil properties and principal components (PCs) based on the environmental data were used as input data. The results showed a higher performance of ANN models developed based on environmental data (soil plus PCs data) than that developed based on only soil data for predicting both Philip infiltration model parameters. The R-2 criteria was improved by 0.18 (from 39 to 57) for S-parameter and by 0.15 (from 0.44 to 0.59) for K-s-parameter prediction using ANN models developed based on environmental data. It was concluded that attributes derived from DEMs and remotely sensed information could be a potential environmental data for improving Philip infiltration model parameters and developing high quality infiltration data maps. That would be a first step in site-specific soil utilization, management and protection of the environment. (C) 2020 Elsevier B.V. All rights reserved.
英文关键词	Artificial neural network S and K-s parameters Infiltration model Entisols Inceptisols Mollisols
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:000568759000005
WOS关键词	ARTIFICIAL NEURAL-NETWORKS ; SURFACE SHEAR-STRENGTH ; CALCAREOUS SOILS ; HYDRAULIC CONDUCTIVITY ; PEDOTRANSFER FUNCTIONS ; SPATIAL VARIABILITY ; EROSION ; GIS
WOS类目	Soil Science
WOS研究方向	Agriculture
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/326226
作者单位	[Tashayo, Behnam; Honarbakhsh, Afshin] Univ Isfahan, Fac Civil Engn & Transportat, Azadi Sq, Esfahan, Iran; [Akbari, Mohammad] Univ Birjand, Dept Civil Engn, Birjand, Iran; [Ostovari, Yaser] Tech Univ Munich, TUM Sch Life Sci Weihenstephan, Res Dept Ecol & Ecosyst Management, Chair Soil Sci, Freising Weihenstephan, Germany
推荐引用方式 GB/T 7714	Tashayo, Behnam,Honarbakhsh, Afshin,Akbari, Mohammad,et al. Digital mapping of Philip model parameters for prediction of water infiltration at the watershed scale in a semi-arid region of Iran[J],2020,22.
APA	Tashayo, Behnam,Honarbakhsh, Afshin,Akbari, Mohammad,&Ostovari, Yaser.(2020).Digital mapping of Philip model parameters for prediction of water infiltration at the watershed scale in a semi-arid region of Iran.GEODERMA REGIONAL,22.
MLA	Tashayo, Behnam,et al."Digital mapping of Philip model parameters for prediction of water infiltration at the watershed scale in a semi-arid region of Iran".GEODERMA REGIONAL 22(2020).