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    Integrating Hydrological, Physical, and Chemical Factors for Soil Moisture Prediction Using Advanced Machine Learning Models 

    Source: Journal of Hydrologic Engineering:;2026:;Volume ( 031 ):;issue: 004:;page 04026025-1
    Author(s): Al-Juaidi, Ahmed E. M.
    Publisher: 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 ...
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    Flood Vulnerability Assessment of Wadi Numan, Makkah: Insights from Advanced Multicriteria Decision Analysis and Fuzzy Logic Techniques 

    Source: Journal of Hydrologic Engineering:;2026:;Volume ( 031 ):;issue: 003:;page 04026004-1
    Author(s): Al-Juaidi, Ahmed E. M.; Emam, Aly A.
    Publisher: American Society of Civil Engineers
    Abstract: AbstractThis work examines flood-prone areas in Wadi Numan, Makkah, Saudi Arabia, using an integrated geographic information system (GIS) approach combined with three multicriteria decision-making (MCDM) techniques [analytical ...
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
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