Sensitivity of Soil Moisture Simulations to Noah-MP Parameterization Schemes in a Semi-Arid Inland River Basin, China

Yuanhong You, Yanyu Lu (), Yu Wang, Houfu Zhou, Ying Hao, Weijing Chen and Zuo Wang
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Yuanhong You: Anhui Province Key Laboratory of Atmospheric Science and Satellite Remote Sensing, Anhui Institute of Meteorological Sciences, Hefei 230031, China
Yanyu Lu: Anhui Province Key Laboratory of Atmospheric Science and Satellite Remote Sensing, Anhui Institute of Meteorological Sciences, Hefei 230031, China
Yu Wang: School of Earth and Space Sciences, University of Science and Technology of China, Hefei 230031, China
Houfu Zhou: Anhui Province Key Laboratory of Atmospheric Science and Satellite Remote Sensing, Anhui Institute of Meteorological Sciences, Hefei 230031, China
Ying Hao: Huaihe River Basin Meteorological Center, Anhui Meteorological Bureau, Hefei 230031, China
Weijing Chen: School of Aeronautic Engineering, Changsha University of Science and Technology, Changsha 410000, China
Zuo Wang: School of Geography and Tourism, Anhui Normal University, Wuhu 241002, China

Agriculture, 2025, vol. 15, issue 21, 1-21

Abstract: Soil moisture simulations in semi-arid inland river basins remain highly uncertain due to complex land–atmosphere interactions and multiple parameterization schemes in land surface models. This study evaluated the ability of the Noah-Multiparameterization Land Surface Model (Noah-MP) to simulate soil moisture at meteorological sites representing the upstream, midstream and downstream regions of a semi-arid inland river basin with contrasting climates. A large physics-ensemble experiment (17,280 simulations per site) combining different parameterization schemes for 10 main physical processes was conducted. Natural selection, Tukey’s test and uncertainty contribution analysis were applied to identify sensitive processes and quantify their contributions to simulation uncertainty. Results indicate that Noah-MP captures soil moisture variability across the basin but with notable biases. Three physical processes—frozen soil permeability, supercooled liquid water in frozen soil and ground resistance to sublimation—were sensitive at all sites, whereas radiation transfer and surface albedo were consistently insensitive. At the upstream and midstream sites, supercooled liquid water contributed about half of the ensemble uncertainty, and at the downstream site ground resistance to sublimation contributed roughly 51%. These findings reveal which physical processes most strongly affect Noah-MP soil moisture simulations in semi-arid basins and provide guidance for improving parameterization schemes to reduce uncertainty.

Keywords: multi-parameterization scheme ensemble simulation; sensitivity analysis; uncertainty contribution rate; soil moisture (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2025
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