Improving soil moisture prediction of a high-resolution land surface model by parameterising pedotransfer functions through assimilation of SMAP satellite data

Abstract

Abstract. Pedotransfer functions are used to relate gridded databases of soil texture information to the soil hydraulic and thermal parameters of land surface models. The parameters within these pedotransfer functions are uncertain and calibrated through analyses of point soil samples. How these calibrations relate to the soil parameters at the spatial scale of modern land surface models is unclear because gridded databases of soil texture represent an area average. We present a novel approach for calibrating such pedotransfer functions to improve land surface model soil moisture prediction by using observations from the Soil Moisture Active Passive (SMAP) satellite mission within a data assimilation framework. Unlike traditional calibration procedures, data assimilation always takes into account the relative uncertainties given to both model and observed estimates to find a maximum likelihood estimate. After performing the calibration procedure, we find improved estimates of soil moisture and heat flux for the Joint UK Land Environment Simulator (JULES) land surface model (run at a 1 km resolution) when compared to estimates from a cosmic-ray soil moisture monitoring network (COSMOS-UK) and three flux tower sites. The spatial resolution of the COSMOS probes is much more representative of the 1 km model grid than traditional point-based soil moisture sensors. For 11 cosmic-ray neutron soil moisture probes located across the modelled domain, we find an average 22 % reduction in root mean squared error, a 16 % reduction in unbiased root mean squared error and a 16 % increase in correlation after using data assimilation techniques to retrieve new pedotransfer function parameters.

COSMOS-UK: national soil moisture and hydrometeorology data for environmental science research

“…COSMOS-UK data could also provide insight into alternative scientific research, such as the relationship between soil moisture and pest behaviour (Hertl et al, 2001), the impact of soil moisture on local infrastructure (Pritchard et al, 2013), investigation of ground-level cosmic ray events (Flückiger et al, 2005), and meteorological data with respect to bacterial infection seasonality (Djennad et al, 2019).…”

Local-scale evaluation of the simulated interactions between energy, water and vegetation in ISBA, ORCHIDEE and a diagnostic model

“…Substantial improvements to soil moisture have indeed been obtained by calibrating the pedotransfer functions or soil physical parameters. Yet, the impact thereof on the surface fluxes has been found to be relatively limited (Pinnington et al, 2021), or in some cases even negative (Raoult et al, 2021). Though many parameters in ISBA and ORCHIDEE are derived from databases (Delire et al, 2020), the LSMs have been calibrated to produce accurate surface fluxes using (amongst others) eddy covariance observations.…”

Sedimentation and Proposed Algorithms to Detect the Possible Existence of Vegetation and Humidity in the Landing Area of the Mars Exploration Rover-B (Opportunity)

“…As is well known, according to [17], soil moisture plays a fundamental role both in the hydrological cycle and in land-atmosphere interactions. However, there are several studies in which the importance of the soil has been analyzed in various scientific areas, such as in climate simulations and meteorological prediction [18], in precipitation and runoff models [19] or in evapotranspiration [20] among others.…”