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Augmentations to the Noah Model Physics for Application to the Yellow River Source Area. Part I: Soil Water Flow

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  • 1 Faculty of Geo-Information Science and Earth Observation, and Faculty of Engineering Technology, University of Twente, Enschede, Netherlands
  • | 2 Faculty of Geo-Information Science and Earth Observation, University of Twente, Enschede, Netherlands
  • | 3 Key Laboratory of Land Surface Process and Climate Change in Cold and Arid Regions, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou, China
  • | 4 Faculty of Engineering Technology, University of Twente, Enschede, Netherlands
  • | 5 Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China
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Abstract

This is the first part of a study focusing on evaluating the performance of the Noah land surface model (LSM) in simulating surface water and energy budgets for the high-elevation source region of the Yellow River (SRYR). A comprehensive dataset is utilized that includes in situ micrometeorological and profile soil moisture and temperature measurements as well as laboratory soil property measurements of samples collected across the SRYR. Here, the simulation of soil water flow is investigated, while Part II concentrates on the surface heat flux and soil temperature simulations. Three augmentations are proposed: 1) to include the effect of organic matter on soil hydraulic parameterization via the additivity hypothesis, 2) to implement the saturated hydraulic conductivity as an exponentially decaying function with soil depth, and 3) to modify the vertical root distribution to represent the Tibetan conditions characterized by an abundance of roots in the topsoil. The diffusivity form of Richards’ equation is further revised to allow for the simulation of soil water flow across soil layers with different hydraulic properties. Usage of organic matter for calculating the porosity and soil suction improves the agreement between the estimates and laboratory measurements, and the exponential function together with the Kozeny–Carman equation best describes the in situ . Through implementation of the modified hydraulic parameterization alone, the soil moisture underestimation in the upper soil layer under wet conditions is resolved, while the soil moisture profile dynamics are better captured by also including the modified root distribution.

Corresponding author address: Donghai Zheng, University of Twente, P.O. Box 217, 7500 AE Enschede, Netherlands. E-mail: d.zheng@utwente.nl

Abstract

This is the first part of a study focusing on evaluating the performance of the Noah land surface model (LSM) in simulating surface water and energy budgets for the high-elevation source region of the Yellow River (SRYR). A comprehensive dataset is utilized that includes in situ micrometeorological and profile soil moisture and temperature measurements as well as laboratory soil property measurements of samples collected across the SRYR. Here, the simulation of soil water flow is investigated, while Part II concentrates on the surface heat flux and soil temperature simulations. Three augmentations are proposed: 1) to include the effect of organic matter on soil hydraulic parameterization via the additivity hypothesis, 2) to implement the saturated hydraulic conductivity as an exponentially decaying function with soil depth, and 3) to modify the vertical root distribution to represent the Tibetan conditions characterized by an abundance of roots in the topsoil. The diffusivity form of Richards’ equation is further revised to allow for the simulation of soil water flow across soil layers with different hydraulic properties. Usage of organic matter for calculating the porosity and soil suction improves the agreement between the estimates and laboratory measurements, and the exponential function together with the Kozeny–Carman equation best describes the in situ . Through implementation of the modified hydraulic parameterization alone, the soil moisture underestimation in the upper soil layer under wet conditions is resolved, while the soil moisture profile dynamics are better captured by also including the modified root distribution.

Corresponding author address: Donghai Zheng, University of Twente, P.O. Box 217, 7500 AE Enschede, Netherlands. E-mail: d.zheng@utwente.nl
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