This study presents a simple and efficient scheme for Bayesian estimation of uncertainty in soil moisture simulation by a Land Surface Model (LSM). The scheme is assessed within a Monte Carlo (MC) simulation framework based on the Generalized Likelihood Uncertainty Estimation (GLUE) methodology. A primary limitation of using the GLUE method is the prohibitive computational burden imposed by uni...

A digital moisture measuring instrument based on phase angle measuring technique with porous silicon (PSi) or porous alumina (PA) as capacitive moisture sensor is proposed. The proposed technique can measure digitally the phase angle change of capacitive impedance of porous silicon or porous alumina sensor due to change in moisture concentration in terms of clock pulses. Analysis shows that the...

[1] Climate model prediction skill is currently limited in response to poor land surface soil moisture state initialization. However, initial soil moisture state prediction skill can potentially be enhanced by the assimilation of remotely sensed near-surface soil moisture data in off-line simulation. This study is one of the first to evaluate such potential using actual remote sensing data toge...

A three-dimensional, nonhydrostatic, nested grid version of the Colorado State University Regional Atmospheric Modeling System (RAMS) was used to perform simulations of an actual dryline that was observed as part of the COPS-91 field experiment on 15 May 1991. A control run designed to reproduce the observed conditions as accurately as possible was generated and verified against standard Nation...

Modeling composting processes is the prerequisite to realize the process control of composting. In this paper, a simulation model for domestic solid waste composting processes was developed based on microbial process kinetics, mass conservation equation, energy conservation equation and water balance. Differential equations describing microbial, substrate, oxygen concentrations, moisture conten...

Improving the capability of land-surface process models to simulate soil moisture assists in better understanding the atmosphere-land interaction. In semi-arid regions, due to limited near-surface observational data and large errors in large-scale parameters obtained by the remote sensing method, there exist uncertainties in land surface parameters, which can cause large offsets between the sim...

A key state variable in land surface–atmosphere interactions is soil moisture, which affects surface energy fluxes, runoff and the radiation balance. Soil moisture modelling relies on parameter estimates that are inadequately measured at the necessarily fine model scales. Hence, model soil moisture estimates are imperfect and often drift away from reality through simulation time. Because of its...

The variance budget of land surface hydrological quantities is analyzed in the second Atmospheric Model Intercomparison Project (AMIP2) simulation made with the Canadian Centre for Climate Modelling and Analysis (CCCma) third-generation general circulation model (AGCM3). The land surface parameterization in this model is the comparatively sophisticated Canadian Land Surface Scheme (CLASS). Seco...