Integrating Hydrological, Physical, and Chemical Factors for Soil Moisture Prediction Using Advanced Machine Learning ModelsSource: Journal of Hydrologic Engineering:;2026:;Volume ( 031 ):;issue: 004::page 04026025-1Author:Al-Juaidi, Ahmed E. M.
DOI: 10.1061/JHYEFF.HEENG-6811Publisher: American Society of Civil Engineers
Abstract: AbstractAccurately predicting soil moisture content (SMC) is critical for effective water
management and sustainable agriculture. This study demonstrates that combining hydrological
factors, such as rainfall, with soil physical characteristics—including ...
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| contributor author | Al-Juaidi, Ahmed E. M. | |
| date accessioned | 2026-08-20T11:08:05Z | |
| date available | 2026-08-20T11:08:05Z | |
| date copyright | 2026/06/06 | |
| date issued | 2026 | |
| identifier other | JHYEFF.HEENG-6811.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4311738 | |
| description abstract | AbstractAccurately predicting soil moisture content (SMC) is critical for effective water management and sustainable agriculture. This study demonstrates that combining hydrological factors, such as rainfall, with soil physical characteristics—including ... | |
| publisher | American Society of Civil Engineers | |
| title | Integrating Hydrological, Physical, and Chemical Factors for Soil Moisture Prediction Using Advanced Machine Learning Models | |
| type | Journal Article | |
| journal volume | 31 | |
| journal issue | 4 | |
| journal title | Journal of Hydrologic Engineering | |
| identifier doi | 10.1061/JHYEFF.HEENG-6811 | |
| journal fristpage | 04026025-1 | |
| journal lastpage | 04026025-15 | |
| page | 15 | |
| tree | Journal of Hydrologic Engineering:;2026:;Volume ( 031 ):;issue: 004 | |
| contenttype | Fulltext |