干旱区生态环境知识资源中心(Arid): Predicting the infiltration characteristics for semi-arid regions using regression trees

Arid

DOI	10.2166/ws.2021.047
	Predicting the infiltration characteristics for semi-arid regions using regression trees
	Sihag, Parveen; Kumar, Munish; Sammen, Saad Sh.
通讯作者	Sammen, SS (corresponding author), Univ Diyala, Dept Civil Engn, Coll Engn, Diyala Governorate, Iraq.
来源期刊	WATER SUPPLY
ISSN	1606-9749
EISSN	1607-0798
出版年	2021
英文摘要	The study of the infiltration process is considered essential and necessary for all hydrology studies. Therefore, accurate predictions of infiltration characteristics are required to understand the behavior of the subsurface flow of water through the soil surface. The aim of the current study is to simulate and improve the prediction accuracy of the infiltration rate and cumulative infiltration of soil using regression tree methods. Experimental data recorded with a double ring infiltrometer for 17 different sites are used in this study. Three regression tree methods: random tree, random forest (RF) and M5 tree, are employed to model the infiltration characteristics using basic soil characteristics. The performance of the modelling approaches is compared in predicting the infiltration rate as well as cumulative infiltration, and the obtained results suggest that the performance of the RF model is better than the other applied models with coefficient of determination (R-2) = 0.97 and 0.97, root mean square error (RMSE) = 8.10 and 6.96 and mean absolute error (MAE) = 5.74 and 4.44 for infiltration rate and cumulative infiltration respectively. The RF model is used to represent the infiltration characteristics of the study area. Moreover, parametric sensitivity is adopted to study the significance of each input parameter in estimating the infiltration process. The results suggest that time (t) is the most influencing parameter in predicting the infiltration process using this data set.
英文关键词	cumulative infiltration infiltration rate M5 tree random forest random tree
类型	Article ; Early Access
语种	英语
开放获取类型	Other Gold
收录类别	SCI-E
WOS记录号	WOS:000634805100001
WOS关键词	HYDRAULIC CONDUCTIVITY ; WATER ; EQUATION ; ANN
WOS类目	Engineering, Environmental ; Environmental Sciences ; Water Resources
WOS研究方向	Engineering ; Environmental Sciences & Ecology ; Water Resources
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/352485
作者单位	[Sihag, Parveen] Shoolini Univ, Solan 173229, Himachal Prades, India; [Kumar, Munish] Natl Inst Technol, Kurukshetra, Haryana, India; [Sammen, Saad Sh.] Univ Diyala, Dept Civil Engn, Coll Engn, Diyala Governorate, Iraq
推荐引用方式 GB/T 7714	Sihag, Parveen,Kumar, Munish,Sammen, Saad Sh.. Predicting the infiltration characteristics for semi-arid regions using regression trees[J],2021.
APA	Sihag, Parveen,Kumar, Munish,&Sammen, Saad Sh..(2021).Predicting the infiltration characteristics for semi-arid regions using regression trees.WATER SUPPLY.
MLA	Sihag, Parveen,et al."Predicting the infiltration characteristics for semi-arid regions using regression trees".WATER SUPPLY (2021).