This paper describes an innovative procedure that is able to simultaneously identify the release history and the source location of a pollutant injection in a groundwater aquifer (simultaneous release function and source location identification, SRSI). The methodology follows a geostatistical approach: it develops starting from a data set and a reliable numerical flow and transport model of the aquifer. Observations can be concentration data detected at a given time in multiple locations or a time series of concentration measurements collected at multiple locations. The methodology requires a preliminary delineation of a probably source area and results in the identification of both the sub-area where the pollutant injection has most likely...
The great interest in environmental issues has drawn the community to an attention to the quality of...
A methodology using a nonlinear optimization model is presented for estimating unknown magnitude, lo...
A methodology using a nonlinear optimization model is presented for estimating unknown magnitude, lo...
This paper describes an innovative procedure that is able to simultaneously identify the release his...
In this paper the problem of recovering the temporal release history of a pollutant is approached wi...
This work shows the application of an innovative procedure that is able to simultaneously identify t...
The interest in environmental issues has led great attention to the quality of groundwater. Since '9...
The pollutant release history in 2-D groundwater aquifer is obtained by means of a geostatistical ap...
The increasing interest in environmental issues has led to greater attention to the quality of groun...
The interest in environmental issues has led great attention to the quality of groundwater. Since '...
The increasing interest in environmental issues has led to greater attention to the quality of groun...
This work addresses the issue of recovering the release history of a pollutant injection in water di...
Inverse methods can be used to recover the pollutant source location from concentration data. In thi...
The great interest in environmental issues has led to an attention to the quality of groundwater. S...
The paper presents a new multi-step approach aiming at source identification and release history est...
The great interest in environmental issues has drawn the community to an attention to the quality of...
A methodology using a nonlinear optimization model is presented for estimating unknown magnitude, lo...
A methodology using a nonlinear optimization model is presented for estimating unknown magnitude, lo...
This paper describes an innovative procedure that is able to simultaneously identify the release his...
In this paper the problem of recovering the temporal release history of a pollutant is approached wi...
This work shows the application of an innovative procedure that is able to simultaneously identify t...
The interest in environmental issues has led great attention to the quality of groundwater. Since '9...
The pollutant release history in 2-D groundwater aquifer is obtained by means of a geostatistical ap...
The increasing interest in environmental issues has led to greater attention to the quality of groun...
The interest in environmental issues has led great attention to the quality of groundwater. Since '...
The increasing interest in environmental issues has led to greater attention to the quality of groun...
This work addresses the issue of recovering the release history of a pollutant injection in water di...
Inverse methods can be used to recover the pollutant source location from concentration data. In thi...
The great interest in environmental issues has led to an attention to the quality of groundwater. S...
The paper presents a new multi-step approach aiming at source identification and release history est...
The great interest in environmental issues has drawn the community to an attention to the quality of...
A methodology using a nonlinear optimization model is presented for estimating unknown magnitude, lo...
A methodology using a nonlinear optimization model is presented for estimating unknown magnitude, lo...