Systematic Hydrological Evaluation of the Noah-MP Land Surface Model over China

被引:0
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作者
Jingjing Liang
Zongliang Yang
Peirong Lin
机构
[1] Chinese Academy of Sciences,Institute of Atmospheric Physics
[2] University of Texas at Austin,Jackson School of Geosciences
[3] Princeton University,Department of Civil and Environmental Engineering
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关键词
hydrological evaluation; Noah-MP; multi-parameterization; China; 水文评估; Noah-MP; 多参数化方案; 中国;
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学科分类号
摘要
We evaluate water budget components—namely, soil moisture, runoff, evapotranspiration, and terrestrial water storage (TWS)—simulated by the Noah land surface model with multi-parameterization options (Noah-MP) in China, a large geographic domain challenging for hydrological modeling due to poor observational data and a lack of one single parameterization that can fit for complex hydrological processes. By comparing the model simulations with multi-source reference data, we show that Noah-MP can generally reproduce the overall spatiotemporal patterns of runoff and evapotranspiration over six major river basins, with the annual correlation coefficients generally greater than 0.8 and the Nash-Sutcliffe model efficiency coefficient exceeding 0.5. Among the six basins evaluated, the best model performance is seen over the Huaihe River basin. The temporal trend of the modeled TWS anomalies agrees well with GRACE (Gravity Recovery and Climate Experiment) observations, capturing major flood and drought events in different basins. Experiments with 12 selected physical parameterization options show that the runoff parameterization has a stronger impact on the simulated soil moisture-runoff-evapotranspiration relationships than the soil moisture factor for stomatal resistance schemes, a result consistent with previous studies. Overall, Noah-MP driven by GLDAS forcing simulates the hydrological variables well, except for the Songliao basin in northeastern China, likely because this is a transitional region with extensive freeze-thaw activity, while representations of human activities may also help improve the model performance.
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页码:1171 / 1187
页数:16
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