黑河上游高寒山区土壤水分模拟对Noah-MP模型参数化方案的敏感性评估 

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  • 1. 安徽师范大学地理与旅游学院,安徽 芜湖 241002
    2. 安徽省气象局气象科学研究所大气科学与卫星遥感安徽省重点实验室,安徽 合肥 230031
    3. 资源环境与地理信息工程安徽省工程技术研究中心,安徽 芜湖 241002
    4. 安徽省气象局淮河流域气象中心,安徽 合肥 230031

网络出版日期: 2025-02-24

基金资助

国家自然科学基金项目(42101361);安徽省重点研究与开发计划项目(2022m07020003);安徽省高等学校科学研究重点项目(2023AH050143);中 国 博 士 后 科 学 基 金 面 上 项 目(2024M753092);安 徽 师 范 大 学 大 学 生 创 新 创 业 训 练 计 划 项 目
202310370056202310370051202410370018

Sensitivity Analysis of Noah-MP Model Parameterization Schemes for Soil Moisture Simulation in the High-Cold Region of the Upper Heihe River Basin

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  • 1. College of Geography and TourismAnhui Normal UniversityWuhu 241002AnhuiChina
    2. Anhui Province Key Laboratory of Atmospheric Science and Satellite Remote SensingAnhui Institute of Meteorological SciencesHefei 230031AnhuiChina
    3. Resource environment and geographyInformation Engineering Anhui Province Engineering Technology Research CenterWuhu 241002AnhuiChina
    4. Huaihe River Basin Meteorological CenterAnhui Meteorological BureauHefei230031AnhuiChina

Online published: 2025-02-24

摘要

在气候变化的背景下,利用陆面过程模型准确模拟土壤水分对气象预报、农业生产和水文过程都具有重要意义。本文利用黑河上游阿柔站的气象观测资料作为 Noah-MP模型的驱动数据,开展了土壤水分模拟试验,评估了 Noah-MP模型在黑河上游高寒山区的土壤水分模拟性能。在不考虑模型参数和驱动数据不确定性的条件下,对 Noah-MP模型不同物理过程的参数化方案进行任意组合,设计了包含17280种不同组合方案的土壤水分多参数化方案集合模拟试验,选用Natural Selection敏感性分析方法分析了浅层土壤水分模拟结果对参数化方案的敏感性,并进一步量化了土壤水分多参数化方案集合模拟结果的不确定性范围。研究结果表明,Noah-MP模型可用于黑河上游高寒山区的土壤水分模拟,模型对浅层土壤水分的模拟精度较高,模拟的土壤水分变化趋势与观测资料基本一致;而深层土壤水分模拟结果精度较差,模拟的土壤水分变化趋势与观测资料偏差较大。浅层土壤水分模拟结果对冻结土壤中过冷液态水、冻结土壤渗透、雨雪分离和第一层积雪或土壤温度的时间方案4个物理过程的参数化方案敏感,其中对冻结土壤渗透物理过程的参数化方案特别敏感。上游高寒山区土壤冻融循环过程中,冻结时段内的土壤水分模拟结果对参数化方案更加敏感,使得土壤冻结物理过程参数化方案的选择是导致土壤水分多参数化方案集合模拟结果不确定性的主要因素。

本文引用格式

黄克秀, 尤元红, 卢燕宇, 郝 莹, 汪 左, 孙 京 . 黑河上游高寒山区土壤水分模拟对Noah-MP模型参数化方案的敏感性评估 [J]. 高原气象, 0 : 1 . DOI: 10. 7522/j. issn. 1000-0534. 2024. 00114

Abstract

In the context of climate changeaccurately simulating soil moisture using land surface process models holds significant importance for weather forecastingagricultural productionand hydrological processes. This study utilized meteorological observation data from the Arou site in the upper reaches of the Heihe River as the driving data for the Noah-MP model to conduct soil moisture simulation experimentsaiming to assess the soil moisture simulation performance of the Noah-MP model in the alpine mountainous area of the upper reaches of the Heihe River. Without considering uncertainties in model parameters and driving dataarbitrary combinations of the parameterization schemes for different physical processes of the Noah-MP model were made. A soil moisture multi-parameterization ensemble simulation experiment encompassing 17280 different combination schemes was designed. The Natural Selection sensitivity analysis method was employed to analyze the sensitivity of shallow soil moisture simulation results to the parameterization schemes and further quantify the uncertainty range of the simulation results of the soil moisture multi-parameterization ensemble. The results of this research indicate that the Noah-MP model can be applied to simulate soil moisture in the alpine mountainous area of the upper reaches of the Heihe river basin. The model demonstrates relatively high accuracy in simulating shallow soil moistureand the simulated soil moisture change trends are generally consistent with the observed data. This consistency suggests that the Noah-MP model is well-suited for capturing the dynamics of shallow soil moisture in these regions. Howeverthe simulation accuracy for deep soil moisture is relatively poorwith the simulated soil moisture change trends showing considerable deviations from the observed data. This suggests that there are still challenges in accurately modeling moisture dynamics at greater soil depthspotentially due to the complexity of subsurface hydrological processes in cold and mountainous environments. The analysis also reveals that shallow soil moisture simulation results are sensitive to the parameterization schemes of four physical processessupercooled liquid water in frozen soilfrozen soil permeabilitypartitioning precipitation into rainfall and snow‐ falland the first-layer snow or soil temperature time scheme. Among thesethe parameterization scheme of frozen soil permeability is particularly sensitiveindicating that it plays a crucial role in determining the accuracy of the simulation results. During the soil freeze-thaw cycle in the alpine mountainous area of the upper reaches of the Heihe Riverthe simulation results of soil moisture during the freezing period showed increased sensitivity to parameterization schemesmaking the selection of the parameterization scheme for the soil freezing process the main factor contributing to the uncertainty of the simulation results of the soil moisture multi-parameterization ensemble.

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