scholarly journals The Quaternary aquifer system flow model by chemical and tritium isotope data: case of south-east Lithuania

Baltica ◽  
2012 ◽  
Vol 25 (2) ◽  
pp. 91-98 ◽  
Author(s):  
Anicetas Štuopis ◽  
Vytautas Juodkazis ◽  
Robert Mokrik
Keyword(s):  
Flow Model ◽  
Quaternary Aquifer ◽  
Aquifer System ◽  
Isotope Data ◽  
System Flow

Smart auction system flow model for Agro-Based sector farmers using blockchain technology

2021 ◽  
Author(s):  
P Sivalakshmi ◽  
K.G Shanthi ◽  
K Sangeethalakshmi ◽  
S SeshaVidhya ◽  
G Sandhiya
Keyword(s):  
Flow Model ◽  
Blockchain Technology ◽  
System Flow

scholarly journals Conceptual and Mathematical Modeling of a Coastal Aquifer in Eastern Delta of R. Nestos (N. Greece)

Hydrology ◽  
2021 ◽  
Vol 8 (1) ◽  
pp. 23
Author(s):  
Ioannis Gkiougkis ◽  
Christos Pouliaris ◽  
Fotios-Konstantinos Pliakas ◽  
Ioannis Diamantis ◽  
Andreas Kallioras
Keyword(s):  
Mathematical Modeling ◽  
Groundwater Flow ◽  
Coastal Aquifer ◽  
Flow Model ◽  
Meteorological Data ◽  
Field Measurements ◽  
Groundwater Flow Model ◽  
Aquifer System ◽  
Geophysical Surveys ◽  
The Mathematical Model

In this paper, the development of the conceptual and groundwater flow model for the coastal aquifer system of the alluvial plain of River Nestos (N. Greece), that suffers from seawater intrusion due to over-pumping for irrigation, is analyzed. The study area is a typical semi-arid hydrogeologic environment, composed of a multi-layer granular aquifers that covers the eastern coastal delta system of R. Nestos. This study demonstrates the results of a series of field measurements (such as geophysical surveys, hydrochemical and isotopical measurements, hydro-meteorological data, land use, irrigation schemes) that were conducted during the period 2009 to 2014. The synthesis of the above resulted in the development of the conceptual model for this aquifer system, that formed the basis for the application of the mathematical model for simulating groundwater flow. The mathematical modeling was achieved using the finite difference method after the application of the USGS code MODFLOW-2005.

The Coastal Modeling System Flow Model (CMS-Flow): Past and Present

2011 ◽  
Vol 59 ◽  
pp. 1-6 ◽  
Author(s):  
Christopher W. Reed ◽  
Mitchell E. Brown ◽  
Alejandro Sánchez ◽  
Weiming Wu ◽  
Adele M. Buttolph
Keyword(s):  
Flow Model ◽  
Coastal Modeling ◽  
Flow Past ◽  
System Flow

Modelling present and future Po river interactions with alluvial aquifers (Low Po River Plain, Italy)

2014 ◽  
Vol 5 (3) ◽  
pp. 457-471 ◽  
Author(s):  
M. Mastrocicco ◽  
N. Colombani ◽  
A. Gargini
Keyword(s):  
Groundwater Flow ◽  
Large Scale ◽  
Flow Model ◽  
Transient Flow ◽  
Scale Model ◽  
Groundwater Flow Model ◽  
Po River ◽  
Local Conditions ◽  
Aquifer System ◽  
Hydrological Conditions

A modelling study on a multi-layered confined/unconfined alluvial aquifer system was performed to quantify surface water/groundwater interactions. The calibrated groundwater flow model was used to forecast climate change impacts by implementing the results of a downscaled A1B model ensemble for the Po river valley. The modelled area is located in the north-western portion of the Ferrara Province (Northern Italy), along the eastern bank of the Po river. The modelling procedure started with a large scale steady state model followed by a transient flow model for the central portion of the domain, where a telescopic mesh refinement was applied. The calibration performance of both models was satisfactory, in both drought and flooding conditions. Subsequently, forecasted rainfall, evapotranspiration and Po river stage at 2050, were implemented in the calibrated large scale groundwater flow model and their uncertainties discussed. Three scenarios were run on the large scale model: the first simulating mean hydrological conditions and the other two simulating one standard deviation above and below the mean hydrological conditions. The forecasted variations in groundwater/Po river fluxes are relevant, with a general increase of groundwater levels due to local conditions, although there are large uncertainties in the predicted variables.

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