Evaluation and optimisation of groundwater observation networks using the Kriging methodology

被引:130
作者
Theodossiou, Nicolaos [1 ]
Latinopoulos, Pericles [1 ]
机构
[1] Aristotle Univ Thessaloniki, Sch Technol, Fac Civil Engn, Div Hydraul & Environm Engn, Thessaloniki 54124, Greece
关键词
groundwater resources management; groundwater modelling; observation networks; Kriging methodology;
D O I
10.1016/j.envsoft.2005.05.001
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Groundwater simulation models have nowadays a decisive role in the development and application of rational water policies. Since the accuracy of the simulation depends strongly on the available data, the task of optimising the observation networks is of great importance. In this paper an application is presented aiming at the optimisation of groundwater level observation networks and the improvement of the quality rather than the quantity of the obtained data. This technique is based on the application of the Kriging methodology and the evaluation of its results in conjunction with the statistical analysis of the available groundwater level data. This procedure that involves different analysis methods of the available data, such as estimation of the interpolation error, data crossvalidation and time variation, is applied to a case study in order to demonstrate the potential of improvement of the quality of the observation network. (C) 2005 Elsevier Ltd. All rights reserved.
引用
收藏
页码:991 / 1000
页数:10
相关论文
共 18 条
[1]   Spatial sampling design for sediment quality assessment in estuaries [J].
Caeiro, S ;
Painho, M ;
Goovaerts, P ;
Costa, H ;
Sousa, S .
ENVIRONMENTAL MODELLING & SOFTWARE, 2003, 18 (10) :853-859
[2]  
DEMARSILY, 1986, QUANTITATIVE HYDROGE
[3]   On the kriging of water table elevations using collateral information from a digital elevation model [J].
Desbarats, AJ ;
Logan, CE ;
Hinton, MJ ;
Sharpe, DR .
JOURNAL OF HYDROLOGY, 2002, 255 (1-4) :25-38
[4]  
*GOLD SOFTW INC, 1999, SURF 7 US GUID
[5]  
GUERTIN K, 1990, MANUEL UTILISATION L
[6]  
HILL MC, 2000, 00184 USGS
[7]   A flexible, integrated system for generating meteorological surfaces derived from point sources across multiple geographic scales [J].
Jolly, WM ;
Graham, JM ;
Michaelis, A ;
Nemani, R ;
Running, SW .
ENVIRONMENTAL MODELLING & SOFTWARE, 2005, 20 (07) :873-882
[8]  
JOURNEL A.G., 1989, SHORT COURSE GEOLOGY, V8
[9]   Designing sampling grids from imprecise information on soil variability, an approach based on the fuzzy kriging variance [J].
Lark, RM .
GEODERMA, 2000, 98 (1-2) :35-59
[10]  
Latinopoulos P., 2001, INVESTIGATION EXPLOI