Add to ORKGA sequential Bayesian approach for joint assimilation of hydrological and geophysical data in a variably saturated flow model is presented. The study aims to improve simulation results and system understanding by assimilation of multiple type data using a Monte Carlo approach and avoiding the inversion of the geophysical measurements. A SIR based particle filter data assimilation is implemented in a 3D variably saturated flow model. Point measurements are directly assimilated in time while spatial information are blended in the simulation by assimilating Electrical Resistivity Tomography (ERT) measurements. To avoid the inversion of the latter, a forward 3D model of electrical current distribution is implemented as the measurements model in...
The ensemble Kalman filter (EnKF) is a powerful tool for assimilating data in earth system models. T...
The ensemble Kalman filter (EnKF) is a powerful tool for assimilating data in earth system models. T...
The ensemble Kalman filter (EnKF) is a powerful tool for assimilating data in earth system models. T...
A sequential Bayesian approach for joint assimilation of hydrological and geophysical data in a vari...
The modeling of unsaturated groundwater flow is affected by a high degree of uncertainty related to ...
The modeling of unsaturated groundwater flow is affected by a high degree of uncertainty related to ...
The modeling of unsaturated groundwater flow is affected by a high degree of uncertainty related to ...
The modeling of unsaturated groundwater flow is affected by a high degree of uncertainty related to ...
The modeling of unsaturated groundwater flow is affected by a high degree of uncertainty related to ...
Abstract. Coupled hydrogeophysical methods infer hydro-logical and petrophysical parameters directly...
Probabilistic risk assessment of groundwater contamination requires us to incorporate large and dive...
Recent advances in geophysical methods have been increasingly exploited as inverse modeling tools in...
Recent advances in geophysical methods have been increasingly exploited as inverse modeling tools in...
Recent advances in geophysical methods have been increasingly exploited as inverse modeling tools in...
There is increasing interest in the use of multiple measurement types, including indirect (geophysic...
The ensemble Kalman filter (EnKF) is a powerful tool for assimilating data in earth system models. T...
The ensemble Kalman filter (EnKF) is a powerful tool for assimilating data in earth system models. T...
The ensemble Kalman filter (EnKF) is a powerful tool for assimilating data in earth system models. T...
A sequential Bayesian approach for joint assimilation of hydrological and geophysical data in a vari...
The modeling of unsaturated groundwater flow is affected by a high degree of uncertainty related to ...
The modeling of unsaturated groundwater flow is affected by a high degree of uncertainty related to ...
The modeling of unsaturated groundwater flow is affected by a high degree of uncertainty related to ...
The modeling of unsaturated groundwater flow is affected by a high degree of uncertainty related to ...
The modeling of unsaturated groundwater flow is affected by a high degree of uncertainty related to ...
Abstract. Coupled hydrogeophysical methods infer hydro-logical and petrophysical parameters directly...
Probabilistic risk assessment of groundwater contamination requires us to incorporate large and dive...
Recent advances in geophysical methods have been increasingly exploited as inverse modeling tools in...
Recent advances in geophysical methods have been increasingly exploited as inverse modeling tools in...
Recent advances in geophysical methods have been increasingly exploited as inverse modeling tools in...
There is increasing interest in the use of multiple measurement types, including indirect (geophysic...
The ensemble Kalman filter (EnKF) is a powerful tool for assimilating data in earth system models. T...
The ensemble Kalman filter (EnKF) is a powerful tool for assimilating data in earth system models. T...
The ensemble Kalman filter (EnKF) is a powerful tool for assimilating data in earth system models. T...