Evaluation of hydrogeologic conditions for groundwater heat pumps: analysis with data from national groundwater monitoring stations

2006 ◽  
Vol 10 (1) ◽  
pp. 91-99 ◽  
Author(s):  
Jin-Yong Lee ◽  
Jong-Ho Won ◽  
Jeong-Sang Hahn
2007 ◽  
Vol 55 (3) ◽  
pp. 97-105 ◽  
Author(s):  
R. Kunkel ◽  
F. Wendland ◽  
S. Hannappel ◽  
H.J. Voigt ◽  
R. Wolter

Commissioned by Germany's Working Group of the Federal States on Water Problems (LAWA) the authors developed a procedure to define natural groundwater conditions from groundwater monitoring data. The distribution pattern of a specific groundwater parameter observed by a number of groundwater monitoring stations within a petrographically comparable groundwater typology is reproduced by two statistical distribution functions, representing the “natural” and “influenced” component. The range of natural groundwater concentrations is characterized by confidence intervals of the distribution function of the natural component. The applicability of the approach was established for 17 hydrochemical different groundwater typologies occurring throughout Germany. Based on groundwater monitoring data from ca. 26,000 groundwater-monitoring stations, 40 different hydrochemical parameters were evaluated for each groundwater typology. For all investigated parameters the range of natural groundwater concentrations has been identified. According to the requirements of the EC Water Framework Directive (article 17) (WFD) this study is a basis for the German position to propose criteria for assessing a reference state for a “good groundwater chemical status”.


Energy ◽  
2021 ◽  
pp. 121607
Author(s):  
Smajil Halilovic ◽  
Leonhard Odersky ◽  
Thomas Hamacher

Geothermics ◽  
2009 ◽  
Vol 38 (3) ◽  
pp. 335-345 ◽  
Author(s):  
Stefano Lo Russo ◽  
Massimo Vincenzo Civita

2014 ◽  
Vol 905 ◽  
pp. 314-317
Author(s):  
Tzu Yi Pai ◽  
Ray Shyan Wu ◽  
Ching Ho Chen ◽  
Li Chen ◽  
Ching Yuan Lin ◽  
...  

In this study, seven types of first-order and one-variable grey differential equation model (abbreviated as GM (1, 1) model) were used to predict the hardness of four groundwater monitoring stations in Kaohsiung City of Taiwan. The mean absolute percentage error (MAPE) was used to evaluate the predicting performance. The results indicated the minimum MAPE of 4.71 %, 3.15 %, 2.66 %, and 16.63 % could be achieved when predicting hardness of Fonsi, Datung, Shaukang, and Chihsien stations, respectively. According to the results, it revealed that GM (1, 1) was an efficiently early warning tool for providing groundwater quality information to the competent authority.


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