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Accurate simulation of energy, water, and carbon fluxes exchanging between the land surface and the atmosphere is beneficial for improving terrestrial ecohydrological and climate predictions. We systematically assessed the Noah land surface model (LSM) with mutiparameterization options (Noah-MP) in simulating these fluxes and associated variations in terrestrial water storage (TWS) and snow cover fraction (SCF) against various reference products over 18 United States Geological Survey two-digital hydrological unit code regions of the continental United States (CONUS). In general, Noah-MP captures better the observed seasonal and interregional variability of net radiation, SCF, and runoff than other variables. With a dynamic vegetation model, it overestimates gross primary productivity by 40% and evapotranspiration (ET) by 22% over the whole CONUS domain; however, with a prescribed climatology of leaf area index, it greatly improves ET simulation with relative bias dropping to 4%. It accurately simulates regional TWS dynamics in most regions except those with large lakes or severely affected by irrigation and/or impoundments. Incorporating the lake water storage variations into the modeled TWS variations largely reduces the TWS simulation bias more obviously over the Great Lakes with model efficiency increasing from 0.18 to 0.76. Noah-MP simulates runoff well in most regions except an obvious overestimation (underestimation) in the Rio Grande and Lower Colorado (New England). Compared with North American Land Data Assimilation System Phase 2 (NLDAS-2) LSMs, Noah-MP shows a better ability to simulate runoff and a comparable skill in simulating Rn but a worse skill in simulating ET over most regions. This study suggests that future model developments should focus on improving the representations of vegetation dynamics, lake water storage dynamics, and human activities including irrigation and impoundments.

An accurate description of soil water vapour sorption isotherms (WSIs) is significant for modelling numerous soil processes. Soil clay content predictions from WSIs can be cost effective and convenient, although the approach has only been investigated on non‐saline soils. To investigate relationships among the clay content, water vapour sorption characteristics and salinity of soils, the WSIs of 35 soil samples were measured at four salinity levels. The characterization of the isotherms indicated that the double log polynomial (DLP) model was optimal for fitting the WSIs of soils with various salinity levels. Moreover, existing clay content prediction models based on WSIs had poor applicability to saline soils, and soil salinity had a greater influence than the soil clay content on the shape of the WSIs. Therefore, multiple linear regression (MLR) models were established to explain the relationships among the soil clay content, salt content and geometrical characteristics of the WSIs. Specifically, a significant correlation was observed between the soil salt content and the sub‐area at the end interval of the WSIs (relative vapour pressure (RH) = 0.83 to 0.93, coefficient of determination (R2) > 0.9) and the hysteresis sub‐area in the middle of the WSIs (RH = 0.53 to 0.63, R2 > 0.8). Furthermore, a strong linear relationship existed between the clay content and the sub‐areas of desorption and hysteresis at the end interval of the WSIs (RH = 0.73 to 0.83, R2 > 0.9) in the non‐saline soils only. Based on the investigated samples, the geometrical characteristics of WSIs were affected predominantly by the soil clay content when the salt content was low (electrical conductivity (EC) < 4.5 dS m−1), whereas salinity was the main influencing factor for samples that have high salt content (EC ≥ 4.5 dS m−1). Moreover, the WSIs' geometric characteristics had the potential to predict soil salt content and clay content under certain limited conditions. Isotherm models that accurately describe water sorption isotherms of saline soils were identified. Soil clay content and salinity affect water sorption isotherms differently depending on soil salinity level. Robust relationships between the soil salinity, clay content and WSI shape properties were established. Highlights: Isotherm models that accurately describe water sorption isotherms of saline soils were identified.Soil clay content and salinity affect water sorption isotherms differently depending on soil salinity level.Robust relationships between the soil salinity, clay content and WSI shape properties were established. [ABSTRACT FROM AUTHOR]