Evaluation and improvement of the default soil hydraulic parameters for the Noah Land Surface Model

Abstract

Soil hydraulic parameters used in estimating soil water and energy fluxes are included in a lookup table in the Noah Land Surface Model (LSM). The purpose of the study was to examine the Noah default soil hydraulic parameters and compare them to soil measurements across Texas, USA. These default soil parameters were compared to measured soil properties from a soil database including 6,749 soil samples located within and around Texas. Mean differences between measured and default soil parameters were tested using a t-test (α = 0.05). To assess the proposed changes to default soil parameters, water retention curves were created using updated parameters and compared to measured soil moisture content at field capacity (θ fc) and permanent wilting point (θ wp). Spatial trends across major land resource areas in Texas were also demonstrated for water retention parameters. Our findings indicate that 95% of the default soil parameters were significantly different from the region-specific measured values. Measured soil water content at air-dry, θ wp , and θ fc are better replacements than default values. Consequent changes in θ wp and θ fc yielded a 35 to 76% decrease in plant available water compared to default. Updated water retention curves showed improved agreement between estimated soil water and measured values in 95% of cases. For three texture classes, the standard deviations of parameters for water retention parameters ranged 30% for the slope of the water retention curve and 65% for saturated hydraulic conductivity. These results indicate the importance of accounting for spatial variability of soil parameters rather than combining these parameters into texture classes alone. The revised parameter table improves modeling of soil hydraulic properties. Ultimately spatially distributed databases of hydraulic soil parameters will better capture variability and spatial structure of soil processes modeled by Noah LSM.

Comparison of Contemporary In Situ, Model, and Satellite Remote Sensing Soil Moisture With a Focus on Drought Monitoring

“…It is also important to note that future phases of NLDAS and the NCEP Unified Land Data Assimilation System (NULDAS) will contain operational data assimilation of soil moisture and snow. Problems with NLDAS model soil hydraulic parameters and model structure should be addressed, given that improved parameterizations result in more realistic soil moisture dynamics (Kishné et al, ).…”

Pedotransfer Functions in Earth System Science: Challenges and Perspectives

“…Most LSMs mainly use default soil parameters, oversimplifying their influence. Kishné et al () found that using measured and PTF‐estimated water content at field capacity and wilting point yielded a 35 to 76% decrease in plant available water compared to default model settings.…”

An Intercomparison of Noah Model Skills With Benefits of Assimilating SMOPS Blended and Individual Soil Moisture Retrievals

“…The hydraulic conductivity is largely nonlinear relying on the SM with sensitivity to SM fluctuations and soil properties (Cuenca et al, 1996). Yet the hydraulic conductivity associated with other soil variables is default defined in the Noah LSM as constants according to the soil texture map (Chen & Dudhia, 2001;Cosby et al, 1984;Ek et al, 2003), which indeed cannot provide optimal soil hydraulic properties (Kishné et al, 2017;Shellito et al, 2016). Besides, reasonable vertical soil hydrology in Noah model is also hampered by the layer soil texture used to represent the entire 2-m soil column (Xia et al, 2015).…”