Enhancing Soil Water Prediction in Arid Climates Using Multipredictor Machine-Learning Models and SHAP-Based Interpretability

dc.contributor.author	Alsumaiei, Abdullah A.
dc.contributor.author	Alrumaidhi, Mubarak
dc.date.accessioned	2026-08-20T11:09:40Z
dc.date.available	2026-08-20T11:09:40Z
dc.date.copyright	2025/12/09
dc.date.issued	2026
dc.identifier.other	JIDEDH.IRENG-10619.pdf
dc.identifier.uri	http://yetl.yabesh.ir/yetl1/handle/yetl/4311775
dc.description.abstract	AbstractEfficient water management in irrigated watersheds requires the timely and precise application of water to optimize crop yields and sustain resources. Although machine-learning (ML) models have shown promise in capturing hydrological dynamics, ...
dc.publisher	American Society of Civil Engineers
dc.title	Enhancing Soil Water Prediction in Arid Climates Using Multipredictor Machine-Learning Models and SHAP-Based Interpretability
dc.type	Journal Article
dc.journal.volume	152
dc.journal.issue	1
dc.journal.title	Journal of Irrigation and Drainage Engineering
dc.identifier.doi	10.1061/JIDEDH.IRENG-10619
dc.journal.fristpage	04025049-1
dc.journal.lastpage	04025049-17
dc.page	17
dc.tree	Journal of Irrigation and Drainage Engineering:;2026:;Volume ( 152 ):;issue: 001
dc.contenttype	Fulltext