gis-based assessment of groundwater vulnerability …
TRANSCRIPT
Proceedings, 6th International Conference on Cartography and GIS, 13-17 June 2016, Albena, Bulgaria
ISSN: 1314-0604, Eds: Bandrova T., Konecny M.
668
GIS-BASED ASSESSMENT OF GROUNDWATER
VULNERABILITY TO ARSENIC CONTAMINATION IN THE
FLOODPLAIN OF THE OGOSTA RIVER, NW BULGARIA
Velimira Stoyanova, Tsvetan Kotsev
Dr. Velimira Stoyanova
National Institute of Geophysics, Geodesy and Geography
Bulgarian Academy of Sciences
Acad. Georgi Bonchev Str., Bl. 3, 1113 Sofia, Bulgaria
Tel.: +3592 979 3396; GSM 0889885934
E-mail: [email protected]
Assoc. Prof. Dr.Tsvetan Kotsev
National Institute of Geophysics, Geodesy and Geography
Bulgarian Academy of Sciences
Acad. Georgi Bonchev Str., Bl. 3, 1113 Sofia, Bulgaria
GSM 0894413096
E-mail: [email protected]
Abstract
The aim of this study is to evaluate the specific groundwater vulnerability of arsenic contamination in the specific
environmental conditions of river floodplains. For this purpose DRESPI modification of DRASTIC index is elaborated
and tested in the arsenic polluted Ogosta Valley, NW Bulgaria. The assessment takes into account the following six
parameters: depth to groundwater table, net recharge, soil texture, impact of the thickness of soil, redox potential and
pH of soil. The respective layers are generated in ArcGIS (ESRI, 2015) and the DRESPI index is computed to generate
the final vulnerability map. The values of the vulnerability index for the floodplain of the Ogosta River are in the range
of 55 - 182 points. The most vulnerable areas are associated with the lowest sections of the floodplain close to the river,
while the less threatened are the lands of the high floodplain in the valley.
Keywords: DRASTIC index, DRESPI index, GIS, Map Algebra
INTRODUCTION
Economic activities, e.g. ore dressing and smelting, tend to concentrate in the river valleys due to their favorable
conditions for development of settlements and industrial infrastructure and this often results in chemical contamination
of soil, especially in the river floodplains. The problem of arsenic contamination of aquifers in the valleys and river
lowlands affects millions of people across the world: Asia – Bangladesh, China, India, Taiwan (Fazal et. аl 2001;
Тuinhof et. al 2006; Smedley, 2008); North America – Mexico; South America – Argentina, Chile (Berlin et al., 2001;
Rodriguez et al., 2002); Europa – Poland, Hungary and Spain (Jain et al., 2000) (Figure 1). Preconditions for
enrichment of groundwater with As exist also in the Ogosta Valley, NW Bulgaria, as a consequence of the historic
mining in the local area. The global significance of the ‘arsenic problem’ mobilizes huge resources and efforts by
international organizations, state governments, local authorities and scientists for research and remediation activities.
An accurate assessment of groundwater vulnerability of As pollution in the river floodplains would help the delineation
of the most threatened areas and prevent valuable water resources from degradation. The index method of DRASTIC
(Aller et al, 1987) and its variations GLA (Hölting et al., 2005), PI (Goldscheider et al., 2000), SINTACS (Civita,
1994), EPIK (Doerfliger and Zwahlen, 1998), REKS (Malik et al., 1999), GOD (Foster, 1987), AVI (van Stemproot et
al., 1993) are often used for evaluation of groundwater intrinsic vulnerability, but we were not able to find in the
literature an application specifically developed for arsenic under conditions of riparian environment.
Proceedings, 6th International Conference on Cartography and GIS, 13-17 June 2016, Albena, Bulgaria
ISSN: 1314-0604, Eds: Bandrova T., Konecny M.
669
Figure 1. Countries with established contamination of aquifers with arsenic (Source:Rahman et al., 2006; Mukherjee et
al., 2006)
1. Poland; 2. Brazil; 3. NewZealand; 4. Spain; 5. Hungary; 6. USA; 7. Argentina; 8. Mexico; 9. Taiwan; 10. Chile; 11.
Sri Lanka; 12. Canada; 13. China; 14. Bangladesh; 15. India; 16. Vietnam; 17. Afganistan; 18. Pakistan; 19. Egypt;
20. Ghana; 21. Cambodia; 22. Sweden; 23. Finland; 24. United Kingdom; 25. Germany; 26. Romania; 27. Bulgaria;
28. Greece; 29. Austria; 30. Myanmar; 31. Iran; 32. Japan; 33. Laos; 34. Nepal; 35. Switzerland; 36. Thailand
The latter is not taken into account by Guo et al. (2007) and Ckakraborty et al. (2007) though both research teams
studied aquifer vulnerability to As contamination with DRASTIC models.The PI method was applied for the basin of
the Ogosta River by Orehova et al. (2009) and the aquifer intrinsic suscptibility in the Ogosta Valley was rated as
medium. The results of this study does not show any differentiation of the estimates within the valley floor and the
specific vulnerability of groundwater to As pollution has not been considered also.
Given the foregoing, the aim of the current paper is to propose a modification of the DRASTIC index method for
assessment of groundwater vulnerability to arsenic pollution in river floodplain and to present the results of its
application for a stretch of the Ogosta Valley.
MATERIAL AND METHODS
Study Area
The study area is situated in the upper stretch of the Ogosta Valley, NW Bulgaria (Figure 2) and extends between the
parallels of latitude N43˚22 and N43˚25 and meridian of longitude E22˚48 and E23˚70. It covers an area of around 14,5
sq. km with mean elevation of 491 m and average inclination of slopes about 3˚. The valley extends over part of the
Western Balkan mountain range and Western Fore-Balkan. It includes parts of three municipalites: Chiprovtsi, Georgi
Damyanovo and Montana. Extraction and dressing of iron-ore and lead-ore took place near the town of Chiprovtsi in
the upper reach of the Ogosta River from 1951 to 1999. Due to the tailings dam failure in 1964 and to the mine waste
discharge into the Ogosta River in the period 1964-1979, the floodplain soil in the Ogosta Valley received significant
amounts of arsenic and heavy metals (Spectroteh, 1994; Kotsev, 2003; Mandaliev et al., 2013; Kotsev et al., 2015).
Proceedings, 6th International Conference on Cartography and GIS, 13-17 June 2016, Albena, Bulgaria
ISSN: 1314-0604, Eds: Bandrova T., Konecny M.
670
Figure 2. Study area
A - “Ogosta” Reservoir; B - Ogosta River; C, D – monitoring wells in the Ogosta Valley
Elevated As levels in the groundwater are registered for some sites in the valley (Kotsev et al., 2006), but the problem is
not well studied yet.
DRESPI index method
DRESPI is rather an modification of the DRASTIC model than a complete new index method. It is aimed at evaluation
of specific vulnerability to As pollution of groundwater in river floodplains. The acronym is created from the first letters
of the following six parameters integrated in the final assessment: Depth to groundwater table (D); net Recharge (R);
Eh - redox state of soil (E); Soil texture (S); pH - active soil reaction (P); Impact of the soil thickness (I). The indices of
DRESPI can be divided into two groups: (1) for evaluation of hydrogeological settings – D, R, S, I; (2) for assessment
of As mobility in the vadose zone – E, P. Compared with DRASTIC, the new application of the model does not include
the indices related to lithology and conductivity of the aquifer as well as the topography (inclination of slopes) because
of their poor spatial differentiation within the river floodplain, at least in the study area (table 1). Redox state and active
reaction (pH) are the major factors to control the solubility and water migration of chemical elements and they were
integrated in the DRESPI model to make the assessment more specific with regard to As. It is well known that under
reducing conditions arsenic tends to form AsIII
species which can be easily transported within the vadose zone (Nriagu,
1994). Under oxic conditions predominant are AsV species, which are strongly absorbed by iron oxide-hydroxides and
are mostly fixed in situ in soil (Nriagu, 1994; Wang et al., 2006; Pendias, 2011). Given the fact that information on
absolute values of Eh of soil solutes is rather scarce, this index is reduced to registration of lack or presence of
indications for periodic or permanent reduction of iron and manganese species in soil. Because of the lack of
information the two intervals for periodic and predominant reducing conditions are merged into one for this case study.
Soil pH intervals are borrowed from the USDA classification of soil active reaction (USDA, 1998). The rating of the
intervals is determined considering the decreasing adsorption of AsV species onto iron oxide-hydroxides with increasing
of pH (Raven et al., 1998; Amita et al., 1999; Dixit et al., 2003). DRESPI keeps the same weight ranking as DRASTIC
for the indices related with hydrological settings. Although the content of the I-index is altered in DRESPI, its weight
factor remains equal to 5 because of the significant protective role of soil cover against As penetration to the
groundwater. The maximum weight of the Eh parameter reflects the significant role of the redox state of soil for As
Proceedings, 6th International Conference on Cartography and GIS, 13-17 June 2016, Albena, Bulgaria
ISSN: 1314-0604, Eds: Bandrova T., Konecny M.
671
mobility and transport in the vadose zone. Arsenic mobility is less dependent on the soil reaction and this is the reason
pH to be considered less important than Eh.
The DRESPI index is calculated as the sum of product of ratings and weights assigned to each of the parameters.
Di = DR*DW + RR*RW + ER*EW +SR*SW + PR*PW + IR*IW (1)
Where: Di – DRESPI index, R – rating, W – weight.
The minimum DRESPI index value is 23 and the maximum is 219 and it is very close to the range of DRASTIC 26-
228. This allows DRESPI to use vulnerability classes identical to those of DRASTIC, which makes the perception of
results easier. The only difference is the merger of middle classes 4 and 5 of DRASTIC into one class in DRESPI. It
resulted in dividing the whole range into the following seven classes: 23-79 (no risk area), 80-99 (very low
vulnerability), 100-119 (low vulnerability), 120-159 (moderate vunerability), 160-179 (high vulnerability), 180-199
(very high vulnerability) and 200-219 (extremely high vulnerability). However, the estimates of the two models are not
comparable due to differences between content and intervals of the used parameters.
Table 1. DRASTIC and DRESPI Rating and Weighting Values for the Various Hydrogeological Parameter Settings
(Aller et al, 1987; Stoyanova, 2015)
DRASTIC (Aller et al., 1987) DRESPI (Stoyanova, 2015)
Parameters Range Rating R DRASTIC
Weight
W
Total
Score
Parameters Range Rating
R
DRESPI
Weight
W
Total
Score
D - Depth
to water
(m)
30,5>
22,9-30,5
15,2-22,9
9,1-15,2
4,6-9,1
1,5-4,6
0-1,5
1
2
3
5
7
9
10
5 5
10
15
25
35
45
50
D - Depth to
groundwater
tabel
(m)
5>
4-5
3,5-4
3-3,5
2,5-3
2-2,5
1,5-2
1-1,5
0,5-1,0
0-0,5
1
2
3
4
5
6
7
8
9
10
5 5
10
15
20
25
30
35
40
45
50
R - Net
recharge
(mm)
0-50,8
50,8-101,6
101,6-177,8
177,8-254
254>
1
3
6
8
9
4 4
12
24
32
36
R –
net
Recharge
(mm/y)
0-50
51-100
101-150
151-200
201-250
251-300
301-350
351-400
401-450
451>
1
2
3
4
5
6
7
8
9
10
4 4
8
12
16
20
24
28
32
36
40
A -
Aquifer
media
Massive Shale
Metamorphic
Weathered
Metamorphic
Glacial Till
Bedded Sandstone,
Limestone and
Shale Sequences
Massive Sandstone
Masive Limestone
Sand and Gravel
Basalt
Karst Limestone
2
3
4
5
6
6
6
8
9
10
3 6
9
12
15
18
18
18
24
27
30
Not
applicable
Not
applicable
E - Redox
state of the
soil – Eh
Predominant
oxic
conditions
Alternation
of oxic and
reducing
1
5
4 4
20
Proceedings, 6th International Conference on Cartography and GIS, 13-17 June 2016, Albena, Bulgaria
ISSN: 1314-0604, Eds: Bandrova T., Konecny M.
672
conditions
Predominant
reducing
conditions
10
40
S - Soil
media
Nonshrinking
Muck
Clay Loam
Silty Loam
Loam
Sandy Loam
Shrinking
Peat
Sand
Gravel
Thin ar absent
1
2
3
4
5
6
7
8
9
10
10
2 2
4
6
8
10
12
14
16
18
20
20
S – Soil
texture
Share of
particle size
fraction
<0,01mm
(%)
85>
75-85
60-75
45-60
30-45
20-30
10-20
5-10
<5
1
2
3
4
5
6
7
8
9
2 2
4
6
8
10
12
14
16
18
Not
applicable
P - Active
soil reaction
– pH
<5,5
5,6-6,0
6,1-6,5
6,6-7,3
7,4-7,8
7,9-8,4
8,4>
1
2
3
4
5
6
7
3 3
6
9
12
15
18
21
T -
Topograph
y (Slope)
(%)
18>
12-18
6-12
2-6
0-2
1
3
5
9
10
1 1
3
5
9
10
Not
applicable
I - Impact
of the
vadose
zone
media
Confining Layer
Silt/Clay
Shale
Limestone
Sandstone
Bedded
Limestone,
Sandstone, Shale
Sand and Gravel
wit Silt and Clay
Metamrphic/
Igneous
Sand and Gravel
Basalt
Karst Limestone
1
3
3
6
6
6
6
4
8
9
10
5 5
15
15
30
30
30
30
20
40
45
50
I - Impact of
the
thickness of
soil (m)
1,80>
1,61-1,80
1,41-1,60
1,21-1,40
1,01-1,20
0,81-1,00
0,61-0,80
0,41-0,60
0,21-0,40
0-0,20
1
2
3
4
5
6
7
8
9
10
5 5
10
15
20
25
30
35
40
45
50
C -
Conductivi
ty of the
aquifer
(GPD/FT2)
1-100
100-300
300-700
700-1000
1000-2000
2000>
1
2
4
6
8
10
3 3
6
12
18
24
30
Not
applicable
Spataial data processing in GIS
Assessment of groundwater vulnerability with DRESPI, as well as with DRASTIC, produces not only a numeric score,
but also maps for each index and an integrated vulnerability map. The whole process takes four major steps using ESRI
ArcGIS, ArcMap 10.3 (Figure 3). The first step produces files into raster format for each six parameters of DRESPI.
Depth to groundwater table is obtained by subtracting the values of altitude in the available hydrodynamic map from the
altitude of the detailed DTM 1x1 m. The limited number of sites with information on the soil texture and soil thickness
did not allow us to interpolate these data and average values were calculated for the main morphographic zones
delineated by using the morphographic map of the valley (Tcherkezova, 2015). The map of the zones is then
reclassified with the relevant mean values for each zone. Areas of low redox potential in soil are outlined to the sections
of shallow groundwater table with depth less than 50 cm from the surface. Locations of studied soil profiles with
described gleyic colour patterns fitted very well to these areas. The second step of data processing includes
reclassification of the resulted maps of the six indices considering the rating of the predefined intervals for each
parameter. The values of the rated maps are then multiplied with the relevant weight factors to produce the final maps
of each index of DRESPI (Figure 4). The third step uses the Spatial Analyst Tools - Map Algebra - Raster Calculator of
Proceedings, 6th International Conference on Cartography and GIS, 13-17 June 2016, Albena, Bulgaria
ISSN: 1314-0604, Eds: Bandrova T., Konecny M.
673
ArcMap to combine all the index maps into one preliminary vulnerability map. The latter is reclassified in the last step
of data processing taking into account the predefined vulnerability classes.
Figure 3. Flowchart of groundwater vulnerability analysis using DRESPI index in GIS
Figure 4. Evaluation maps of DRESPI indices
Proceedings, 6th International Conference on Cartography and GIS, 13-17 June 2016, Albena, Bulgaria
ISSN: 1314-0604, Eds: Bandrova T., Konecny M.
674
Each class is characterized by a different color: no risk area – dark green (RGB – 38/118/0); very low vulnerability –
green (RGB – 10/204/0); low vulnerability- light green (RGB – 170/255/0); moderate vunerability – yellow (RGB –
255/255/0); high vulnerability – orange (RGB – 255/209/15); very high vulnerability – red (RGB - 255/0/0); extremely
high vulnerability – violet (RGB – 194/0/187).
RESULTS AND DISCUSSION
The calculated values of DRESPI index for the Ogosta Valley are within the range 55-182 and fall into six classes of
vulnerability with different coverage of the study area (% of total area) : no risk area – 2.48; very low vulnerability -
11.05; low vulnerability – 33.76; moderate vulnerability – 29.54; high vulnerability – 23.13; very high vulnerability
0.03 (Figure 5).
Proceedings, 6th International Conference on Cartography and GIS, 13-17 June 2016, Albena, Bulgaria
ISSN: 1314-0604, Eds: Bandrova T., Konecny M.
675
Figure 5. Groundwater Vulnerability map
Results show that moderate and higher levels of vulnerability are considered for more than 50% of the Ogosta Valley
lands between the village of Beli Mel and the “Ogosta”reservoir. Groundwater in these areas is prone to significant
threat of arsenic pollution. Depth to groundwater table, net recharge, redox potential and soil thickness are the factors
with the greatest contribution to the vulnerability estimates. Sections with highest scores are associated with the lowest
parts of the floodplain along the Ogosta River channel due to the shallow groundwater table (0-1.5m), the higher
probability for reducing conditions in soil, its less thickness (0.4-0.8 m) and coarser texture. The aquifer is much better
protected from arsenic pollution in the higher floodplain where most of the indices show low scores. The DRESPI
groundwater vulnerability map clearly shows three areas of signifficant concern with regard to possible As pollution
where high vulnerability level (shades of orange) are registered. The biggest area is located close to the reservoir where
the low floodplain is wide spread. The other two areas are located in the lands of the villages of Beli Mel and Gorna
Kovatchitsa where low sections of the floodplain are also well developed.
CONCLUSIONS
The proposed DRESPI modification of the DRASTIC model integrates new indices to provide more accurate evaluation
of groundwater vulnerability to As contamination in river floodplains. The elaborated map shows significant spatial
differentiation of vulnerability within the study area of the Ogosta Valley, which is mostly due to the detailed DTM
used for preparation of some of the input data layers. The levels of vulnerability are closely associated with the
morphology of the river floodplain as a result of the fluvial genesis of the study area. The aquifer is most susceptive to
As contamination in the lowest sections of the floodplain where the highest levels of soil pollution in the valley can be
expected. The DRESPI estimates for the Ogosta Valley are dependant mostly on the indices Depth to groundwater, net
Recharge, Redox state of soil and the Impact of soil thickness. The evaluation elaborated with DRESPI can be
incorporated as a first step in the risk assessment of groundwater pollution with arsenic in riparian zones. The range and
intervals of the index of net Recharge take into account the hydro-climatic conditions of Bulgaria and for this reason the
current setting of DRESPI makes it most appropriate for the river valleys on its territory. Nevertheless, the model can be
easily adapted to the features of other regions.
ACKNOWLEDGEMENTS
This study has been accomplished in the frame of the research project ASCOR “Arsenic contamination of Ogosta River:
Linking biogeochemical processes in floodplain soils with river system dynamics”, № IZEBZO-142978, Bulgarian-
Swiss Research Programme (2011-2016).
Proceedings, 6th International Conference on Cartography and GIS, 13-17 June 2016, Albena, Bulgaria
ISSN: 1314-0604, Eds: Bandrova T., Konecny M.
676
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BIOGRAPHY
Dr. Velimira Stoyanova works at the National Institute of Geophysics, Geodesy and Geography –
Bulgarian Academy of Sciences, Department of Geography, section Physical Geography. She is a
member of Bulgarian Cartographic Association and Bulgarian Geographical Society. She received
a Doctoral degree in Physical Geography and Landscape Studies in 2015. Her PhD research is
related to vulnerability of arsenic contamination of groundwater in the floodplain of Ogosta River
between Martinovo Village and “Ogosta” Reservoir. She is Master's degree of Physical Geography
and Landscape Studies and Regional Development and Management at Sofia University “St.
Kliment Ohridski”, Faculty of Geology and Geography, 2011. Current research interests of Dr.
Stoyanova are in Environmental Geochemistry, Landscape Ecology, Hydrogeology, Geographic
Information Systems.
Assoc. Prof. Dr.Tsvetan Kotsev works at the National Institute of Geophysics, Geodesy and
Geography - Bulgarian Academy of Sciences, Department of Geography, section Physical
Geography. Dr. Kotsev received his Master Degree in Geography from Sofia University“St.
Kliment Ohridski” in 1998 and his Doctoral Degree in Physical Geography in 2003. Current
research interests of Dr. Kotsev are in the fields of Environmental Geochemistry, Environmental
Quality Assessment and Landscape Ecology.