Coupled irrigation-system/groundwater flow modelling for groundwater resource assessment in agricultural areas: a case study in northern Italy

2018 ◽  
Vol 46 ◽  
pp. 94-100 ◽  
Author(s):  
Gabriele Oberto ◽  
Luca Alberti ◽  
Rodolfo Soncini Sessa ◽  
Loris Colombo
Keyword(s):  
Groundwater Flow ◽  
Irrigation System ◽  
Resource Assessment ◽  
Northern Italy ◽  
Groundwater Resource ◽  
Flow Modelling ◽  
Groundwater Flow Modelling ◽  
Groundwater Resource Assessment ◽  
Agricultural Areas

Groundwater Flow Modelling of the Aosta Plain in Northern Italy

2014 ◽  
pp. 227-230 ◽  
Author(s):  
Tullia Bonomi ◽  
Maria Letizia Fumagalli ◽  
Marco Rotiroti ◽  
Rodolfo Perego ◽  
Fulvio Simonetto ◽  
...  
Keyword(s):  
Groundwater Flow ◽  
Northern Italy ◽  
Flow Modelling ◽  
Groundwater Flow Modelling

scholarly journals Modelling Groundwater Flow with MIKE SHE Using Conventional Climate Data and Satellite Data as Model Forcing in Haihe Plain, China

Water ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 1295 ◽  
Author(s):  
Yunqiao Shu ◽  
Hongjun Li ◽  
Yuping Lei
Keyword(s):  
Remote Sensing ◽  
Spatial Variability ◽  
Groundwater Flow ◽  
Groundwater Level ◽  
Remote Sensing Data ◽  
Resource Assessment ◽  
Groundwater Resource ◽  
Mike She ◽  
Sensing Data ◽  
Groundwater Resource Assessment

In North China Plain, accurate spatial and temporal ET and precipitation pattern is very important in the groundwater resource assessment. This study demonstrated the potential for modelling ET and groundwater processes using remote sensing data for distributed hydrological modelling with MIKE SHE codes in the Haihe Plain, China. The model was successfully validated against independent groundwater level measurements following the calibration period and the model also provided a reasonable match of the lysimeter measurements of ET. The remote sensing data included ET derived from global radiation products of Fengyun-2C geostationary meteorological satellite (FY-2C) and FY-2C precipitation products. The comparisons show that precipitation is a critical factor for the hydrological response and for the spatial distribution of ET and groundwater flow. FY-2C precipitation products has a spatial resolution of about 11 km, which thus adds more spatial variability to the most important driving variable. The ET map based on FY-2C data has a higher spatial variability than that map based on conventional data, which are caused by higher resolution of ground information. The groundwater level changes in the aquifer system are shown in the quite different spatial patterns under two models, which is affected by the significant difference between two types of precipitation. In the Haihe Plain, accurate spatial and temporal ET pattern is very important in the groundwater resource assessment that determines the recharge to the saturated zone.

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