For visual interpretation, mapping or empirical modelling purposes, the amount of information contained in a full spatio-temporal description of the groundwater table dynamics is simply too large. For such purposes, the data has to be compressed without loosing too much information. Methods have been developed to visualise the groundwater regime in overall graphs, or statistically characterise the dynamics with a limited set of parameters. More recently, methods have been sought to identify the properties that determine the dynamics of a groundwater system. In such approaches, it is believed that the spatial differences in the groundwater dynamics are determined by the system properties, while its temporal variation is driven by the dynamic...
The flood-wave method is implemented within the framework of time-series analysis to estimate aquife...
The temporal scale effect is an important issue for groundwater system evolution research. The selec...
Time series analysis is a data-driven approach to analyze time series of heads measured in an observ...
For visual interpretation, mapping or empirical modelling purposes, the amount of information contai...
Groundwater, water in the ground. Although it is invisible, it is a vital resource for all terrestri...
Time series analysis is applied to identify and analyze a transition in the groundwater regime in th...
ABSTRACT Time series modelling applied to study water table depths monitoring data is an elegant wa...
Shallow groundwater interacts strongly with surface water across a quarter of global land area, affe...
The objective of this thesis is twofold: to develop time series analysis methods for the estimation ...
Large‐scale groundwater models are required to estimate groundwater availability and to inform water...
This study aims to identify common hydrogeological patterns and to gain a deeper understanding of th...
Groundwater is one of important water resources for the socio-economic development of a community. I...
Groundwater plays an important role in both urban and rural areas. It is therefore essential to moni...
© 2015 Dr. Vahid ShapooriGroundwater level dynamic is a complex phenomenon that results from several...
Existing groundwater table (GWT) class maps, available at full coverage for the Netherlands at 1:50,...
The flood-wave method is implemented within the framework of time-series analysis to estimate aquife...
The temporal scale effect is an important issue for groundwater system evolution research. The selec...
Time series analysis is a data-driven approach to analyze time series of heads measured in an observ...
For visual interpretation, mapping or empirical modelling purposes, the amount of information contai...
Groundwater, water in the ground. Although it is invisible, it is a vital resource for all terrestri...
Time series analysis is applied to identify and analyze a transition in the groundwater regime in th...
ABSTRACT Time series modelling applied to study water table depths monitoring data is an elegant wa...
Shallow groundwater interacts strongly with surface water across a quarter of global land area, affe...
The objective of this thesis is twofold: to develop time series analysis methods for the estimation ...
Large‐scale groundwater models are required to estimate groundwater availability and to inform water...
This study aims to identify common hydrogeological patterns and to gain a deeper understanding of th...
Groundwater is one of important water resources for the socio-economic development of a community. I...
Groundwater plays an important role in both urban and rural areas. It is therefore essential to moni...
© 2015 Dr. Vahid ShapooriGroundwater level dynamic is a complex phenomenon that results from several...
Existing groundwater table (GWT) class maps, available at full coverage for the Netherlands at 1:50,...
The flood-wave method is implemented within the framework of time-series analysis to estimate aquife...
The temporal scale effect is an important issue for groundwater system evolution research. The selec...
Time series analysis is a data-driven approach to analyze time series of heads measured in an observ...