Related Papers
Review An Overview of the Use of the SimSphere Soil Vegetation Atmosphere Transfer (SVAT) Model for the Study of Land- Atmosphere Interactions
2009 •
Toby N. Carlson
Ecological Modelling
A global Bayesian sensitivity analysis of the 1d SimSphere soil–vegetation–atmospheric transfer (SVAT) model using Gaussian model emulation
2009 •
George P. Petropoulos
Sensitivity analysis consists of an integral and important validatory check of a computer simulation model before the code is used in performing any kind of analysis operation. The present paper demonstrates the use of a relatively new method and tool for conducting global sensitivity analysis (GSA) for environmental models, providing simultaneously the first GSA study of the widely used 1d soil–vegetation–atmospheric transfer (SVAT) model named SimSphere. A software platform called the Gaussian emulation machine for sensitivity analysis (GEM SA), which has been developed for performing a GSA via Bayesian theory, is applied to SimSphere model in order to identify the most responsive model inputs to the simulation of key model outputs, detect their interactions and derive absolute sensitivity measures concerning the model structure. This study is also very timely in that, use of this particular SVAT model is currently being considered to be used in a scheme being developed for the operational retrieval of the soil surface moisture content by National Polar-orbiting Operational Environmental Satellite System (NPOESS), in a series of satellite platforms that are due to be launched in the next 12 years starting from 2016. The employed GSA method was found capable of identifying the most responsive SimSphere inputs and also of capturing their key interactions for each of the simulated target quantities on which the GSA was conducted. The most sensitive model inputs were the topography parameters (slope, aspect) as well as the fractional vegetation cover and soil surface moisture availability. The implications of these findings for the future use of SimSphere are discussed.
Remote Sensing of Environment
Estimation of evapotranspiration and photosynthesis by assimilation of remote sensing data into SVAT models
1999 •
D. Courault
Addressing the ability of a land biosphere model to predict key biophysical vegetation characterisation parameters with Global Sensitivity Analysis
George P. Petropoulos
Sensitivity Analysis (SA) of the SimSphere Soil Vegetation Atmosphere Transfer (SVAT) model has been performed in this study using a cutting edge and robust Global Sensitivity Analysis (GSA) approach, based on the use of the Gaussian Emulation Machine for Sensitivity Analysis (GEM-SA) tool. The sensitivity of the following model outputs was evaluated: the ambient CO 2 concentration, the rate of CO 2 uptake by the plant, the ambient O 3 concentration, the flux of O 3 from the air to the plant/soil boundary and the flux of O 3 taken up by the plant alone. The most sensitive model inputs for the majority of outputs were: The Leaf Area Index (LAI), Fractional Vegetation Cover (Fr), Cuticle Resistance (CR) and Vegetation Height (VH). The influence of the external CO 2 on the leaf and O 3 concentration in the air as input parameters was also significant. Our study provides an important step forward in the global efforts towards SimSphere verification given the increasing interest in its use as an independent modelling or educational tool. Results of this study are also timely given the ongoing global efforts focused on deriving, at an operational level, spatio-temporal estimates of energy fluxes and soil moisture content using SimSphere synergistically with Earth Observation (EO) data.
Agricultural and Forest Meteorology
Monitoring water stress using time series of observed to unstressed surface temperature difference
2007 •
Rachid Hadria
Evapotranspiration - Remote Sensing and Modeling
Possibilities of Deriving Crop Evapotranspiration from Satellite Data with the Integration with Other Sources of Information
2012 •
GHEORGHE STANCALIE
Review on estimation of evapotranspiration from remote sensing data: From empirical to numerical modeling approaches
2005 •
albert olioso
Abstract Different methods have been developed to estimate evapotranspiration from remote sensing data, from empirical approaches such as the simplified relationship to complex methods based on remote sensing data assimilation along with SVAT models. The simplified relationship has been applied from small spatial scale using airborne TIR images to continental scale with NOAA data.
… on remote sensing of ET for …
Review to Estimate Evapotranspiration From Remote Sensing Data: Some Examples From the Simplified Relationship to the Use of Mesoscale Atmospheric Models
2003 •
Dominique Courault
Different methods have been developed to estimate evapotranspiration from remote sensing data. Among them direct methods based upon the energy balance equation and using thermal infrared (TIR) data like the simplified relationship. This method has been applied for ...
Hydrology and Earth System Sciences
Ability of a soil–vegetation–atmosphere transfer model and a two-source energy balance model to predict evapotranspiration for several crops and climate conditions
Benoit Coudert
Modification of DAISY SVAT model for potential use of remotely sensed data
2001 •
Anton Thomsen
