This study provides results for the optimization strategy of highly parameterized models, especially with a high number of unknown input parameters and joint problems in terms of sufficient parameter space. Consequently, the uncertainty in model parameterization and measurements must be considered when highly variable nitrogen losses, e.g. N leaching, are to be predicted. The Bayesian calibrati...

The sensitivity of land surface model parameters is usually examined for one parameter at a time in response to changes in observation data and/or the model estimated output. This parameter independence approach assumes that there are limited interactions between model parameters a precondition which is highly unlikely for land surface models. Additionally, the model parameter values are widely...

Soil moisture is a key parameter controlling the exchanges at the surface/atmosphere interface. This parameter, very important for the weather and climate modelling, is not well monitored at a global scale. Because of its high spatial variability, a large number of point measurements is necessary to estimate an accurate value over an area. The SMOS (Soil Moisture and Ocean Salinity) mission was...

Synthetic Aperture Radar has shown its large potential for retrieving soil moisture maps at regional scales. However, since the backscattered signal is determined by several surface characteristics, the retrieval of soil moisture is an ill-posed problem when using single configuration imagery. Unless accurate surface roughness parameter values are available, retrieving soil moisture from radar ...

soil conservation service (scs) adjusted the kostiakovs infiltration model by adding a constant coefficient, for improvement of estimation. the improved model has three constant parameters, which are difficult to calculate. so scs has taken the third constant parameter as equal to 0.65-0.7 cm to simplify the estimation. this parameter varies in different soil and often outranges the scs estimat...

Data assimilation (DA) methods have been widely used to improve model state estimation by merging model outputs with observations. Traditionally, studies have focused on updating model state variables but recent studies have augmented model parameters alongside model state variables to improve the estimation procedure. The updated model ensemble members represent a compromised estimation betwee...

Soil moisture is a key parameter in different environmental applications, suchas hydrology and natural risk assessment. In this paper, surface soil moisture mappingwas carried out over a basin in France using satellite synthetic aperture radar (SAR)images acquired in 2006 and 2007 by C-band (5.3 GHz) sensors. The comparisonbetween soil moisture estimated from SAR data and in situ measurements s...

The SMOS satellite mission, launched in 2009, allows global soil moisture estimations to be made using the L-band Microwave Emission of the Biosphere (L-MEB) model, which simulates the L-band microwave emissions produced by the soil–vegetation layer. This model was calibrated using various sources of in situ and airborne data. In the present study, we propose to evaluate the L-MEB model on the ...

Surface soil moisture is important to understand environmental systems and dielectric constant is a convenient physical parameter to describe this. Dielectric Mixing models relate the effective dielectric constant of a heterogeneous medium with the properties of constituent materials. The dielectric properties of the soil is known to have dependence on Soil moisture content along with other fac...