International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B7. Istanbul 2004 
Considering the geostatistical methodology presented, four 
main steps can be distinguished: a) obtaining spatial variability 
functions (variogram functions) for the hard data; b) estimation 
of average values of contaminant heavy metals by means of the 
ordinary kriging method, c) production of hazard maps based on 
simulated images of the spatial dispersion of heavy metals, 
using a stochastic simulation technique — direct sequential 
simulation and co-simulation, d) optimum sampling desing for 
the next campaigns. 
2. DATA SET 
The study area is a 2 km? region located approximately 10 km 
in the South of the Aznalcóllar mine. The information available 
was obtained through a soil sampling realized in August 1999, 
where 80 samples were collected. For the purpose of this study, 
only the samples located inside the study area, i.e. 40 samples, 
were used to characterize spatial dispersion of residual 
contamination with heavy metals (figure 3). Soil samples were 
collected from the topsoil and analytical results of Cu, Pb, Zn, 
Cd and As recorded in terms of total concentration (ppm). 
Figure 1 shows the position of the sampling locations and the 
basic statistics of the metal concentration are summarized in 
Table 1. 
X 
N * eo 
ros 
{ 
t 
e 
{ ; 
= J 
/ f 
/ e 
/ e 
4 
f ./ 
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Figure 3. Sampling locations 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
Cu Pb Zn Cd As 
Mean 242.53 | 686.43 | 1042.5 3.30 | 336.55 
0 
Std.Dev. | 184.03 | 848.17 | 820.40 2.98 | 448.00 
Minimum 47.0 116.0 146.0 0.5 24.0 
25" Perc. 104.5 203.5 362.5 1.0 77.0 
Median 220.5 | 403.0 | 1031.5 3.0 193.5 
75% Perc. 340.0 | 830.5 | 1421.5 40 | 415.0 
Maximum | 1074.0 | 5150.0 | 4460.0 17.0 | 2649.0 
Range 1027.0 | 5054.0 | 4314.0 16.5 | 2625.0 
  
  
Table 1. Basic statistics of the available data (in ppm) 
3. SPATIAL VARIABILITY CHARACTERIZATION 
The spatial variability characterization was one of the main 
objectives of this work. This characterization has been made 
374 
using the variogram functions. Variograms of the metal contents 
value were calculated (Figure 4). 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
h 
30000 0) : = 
25000 
20000 . 
wx] Lem : 
10000 / 
/ Variable Cu: 
500017 Struct 1: Exponential 
je Range: 450m; Sill: 16552 ppm2 
% 500 1000 1500 2000 2500 3000 
y (h) "e 
250000 
200000 . + 
150000| pe ten ^ 
4 . 
/ 
100000 / 
/ Variable Pb: 
50000 / Struct 1: Nugget effect. Sill: 50000 ppm’ 
Struct 2: Exponential 
Range: 300m; Sill: 111309 ppm“ 
0 ; 
0 500 1000 1500 2000 
h (m) 
y(h 
450000 ©) 
400000 . 
350000 : . 
300000 7777777 nn 
250000 m t ot 
^ 
200000 . / 
150000 / 
i 
/ 
109009): / Variable Zn: 
50000| / Struct 1: Exponential 
of Range: 750m; Sill: 307762 ppm’ 
0 500 1000 1500 2000 2500 3000 
h (m) 
6 v (h) 
5 . 
ab SPHERE I e Rt Te mal 
3 ZU : . 
] / 
/ Variable Cd: 
1 / Struct 1: Exponential 
/ Range: 340m; Sill: 4.20 ppm’ 
0 ——— 
0 200 400 600 800 1000 
h (m) 
y(h) 
60000 . 
50000 : : a 
40000 ER vs 
PA ? 
30000] / 
/ 
20000 Variable As: 
Struct 1: Nugget effect. Sill: 20000 ppm’ 
10000 Struct 2: Exponential 
Range: 500m; Sill: 23740 ppm’ 
© 500 1000 1500 2000 
h (m) 
Figure 4. Variogram of the experimental data 
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