Groundwater Vulnerability Mapping Optimized With Groundwater Quality Data: The Tahtalı Basin Example

Transcription

1 Groundwater Vulnerability Mapping Optimized With Groundwater Quality Data: The Tahtalı Basin Example Alper Elçi Dokuz Eylül University, Dept. of Environmental Engineering Izmir, TURKEY Abstract The concept of groundwater vulnerability assessment is a key component in integrated watershed management. Groundwater vulnerability is an intrinsic property of the groundwater system that defines the likelihood of breakthrough of any contaminant released at or near the land surface. A wide range of approaches for assessing groundwater vulnerability were developed based on identified factors affecting the transport of contaminants in the vadose zone. Many of the approaches are simple overlay-and-index methods, which are executed within a GIS framework. These methods involve assigning numerical ratings to hydrogeological and physiological attributes and subsequent weighted combination (overlaying) of various rating maps of these attributes to develop a range of final vulnerability classes. The DRASTIC method and its variants are widely used in the assessment of groundwater vulnerability. The main objective of this study was to optimize the conventional DRASTIC method and show the applicability of the optimized method with a case study. The Tahtalı stream basin, which is of utmost importance for the city of Izmir, was selected as the study site. Raster-based input layers were constructed that represent the factors contributing to surface-originated groundwater contamination. The vulnerability of the stream basin to groundwater contamination was mapped using weighted overlaying and index calculating approach as prescribed by the original DRASTIC method that was subsequently optimized with groundwater quality data. Nitrate concentration measurements, which represent surface-originated conservative contaminants for the basin, were used as groundwater quality data. Correlation coefficients between nitrate values and parameters affecting groundwater vulnerability were calculated to accordingly revise the conventional DRASTIC parameter weighting coefficients. The correlation coefficient between measured nitrate concentrations and corresponding vulnerability ratings increased from to by optimizing the layer weights. Optimized vulnerability maps were produced, interpreted and discussed. Keywords: GIS, groundwater, vulnerability, nitrate, optimization, DRASTIC, Turkey Introduction Groundwater is a relatively abundant water resource that can be exploited in most parts of the world. However, it is also a resource under continuous environmental stress due to many potential contamination sources originating from urbanization, industrial and agricultural activities. Furthermore, it is important to take preventive measures to protect groundwater since the remediation of polluted groundwater is a costly process. In this regard, preventive measures to protect groundwater imply the determination of aquifers that are more vulnerable to contamination. Therefore, groundwater vulnerability assessments have become recently more pronounced in water resources management. The concept of groundwater vulnerability can have different interpretations in different contexts; in the conventional sense it is a dimensionless and an intrinsic property of the groundwater system that defines the likelihood of breakthrough of any contaminant released at the land surface. Groundwater vulnerability cannot be measured directly and must be derived from information of various hydrogeological properties. The DRASTIC method (Aller et al., 1987) is a well-known vulnerability assessment method that can be implemented within a geographical information system (GIS) framework. It can be classified as an overlay and index method that is conceptually accepted by the hydrogeology community. In recent years, modifications and improvements of the method were published (e.g. Sinan and Razack, 2009; Antonakos and Lambrakis, 2007; Panagopoulos et al., 2006). BALWOIS Ohrid, Republic of Macedonia - 25, 29 May

2 The main objective of this study was to optimize the conventional DRASTIC method and show the applicability of the optimized method with a case study. The optimization of groundwater vulnerability maps was based on the systematic comparison of actual groundwater quality data with calculated groundwater vulnerability indices. The Tahtalı stream basin, which is of utmost importance for the city of Izmir, was selected as the study site. The vulnerability assessment with subsequent optimization to actual groundwater quality data was carried out and vulnerability maps were interpreted for the study site. Materials and methods Description of study site The Tahtalı dam reservoir (38 08 N; E) is located 40 km south of Izmir and meets about 36% of the city s total water demand (Fig. 1). The catchment has an area of 550 km 2 and it is a sub-basin of the larger K.Menderes river basin. The climate of the region is typical Mediterranean and the long-term mean annual precipitation over the area is recorded as 690 mm. Most of the precipitation occurs in the period between October and May, whereas the rest of the year is relatively dry. A total of 44 ephemeral creeks and their tributaries drain through the catchment area and feed the Tahtalı reservoir. The major inflows to the reservoir are from the north via Tahtalı and Şaşal streams. The Şaşal stream contributes 25% whereas the Tahtalı stream contributes 75% to the total inflow. The discharges of the other four inflowing streams are negligible (Çalışkan and Elçi, 2009). According to the 2008 census data (Turkstat, 2008), inhabitants live within the boundaries of the Tahtalı catchment. Based on analysis of satellite imagery, the land use distribution of the area is 42.1% forests, 31.8% agricultural areas, 3.1% water bodies, 1.8% residential and 0.2% industrial areas. Quaternary aged alluvial deposits, Neogene age flysch, clayey limestone, allochthonous limestone, conglomerate and tuff formations comprise the geological structure of the study area (Fig.2). Figure 1. The Tahtalı stream basin in Izmir-Turkey BALWOIS Ohrid, Republic of Macedonia - 25, 29 May

3 The catchment area is under environmental stress, in particular with respect to groundwater. Some small communities in the catchment rely on groundwater from supply wells. On the other hand, there are many wells drilled in the surficial aquifer, which provide the much needed irrigation water for agriculture. The groundwater in the catchment is prone to contamination originating from domestic and some industrial pollution sources located mostly in the medium- and long-distance buffer zones of the catchment. Furthermore, excessive withdrawal from the surficial aquifer due to increase in population and also periodic droughts that have become more pronounced and sustained due to climate change pose a serious threat to the quantity and quality of groundwater resources. Figure 2. Geological structure of the study site The groundwater vulnerability assessment process The main idea of the DRASTIC groundwater vulnerability assessment process is to calculate a raster map representing vulnerability index values by overlaying raster maps of parameters that affect groundwater vulnerability. Seven parameters are considered in this method: (1) Depth to water table; (2) net Recharge; (3) Aquifer media; (4) Soil media; (5) Topography; (6) Impact of the vadose zone media; and (7) hydraulic Conductivity of the aquifer. Descriptions of these factors and their relevance to groundwater contamination are presented in the original documentation of the method by Aller et al. (1987), and therefore will not be discussed here. For each of the seven parameters, a grid-based map in raster format is prepared which contains the spatial distribution of vulnerability rating values from 1 (least effective on vulnerability) to 10 (most effective on vulnerability). The assignment of rating values is a subjective process that is controlled by the expert performing the vulnerability assessment. The preparation of the parameter rating maps requires the analysis, synthesis and mapping of more or less raw data in different formats, sources and scales. This is accomplished within a GIS framework that enables the user to maintain databases, process, analyze and map the data. Furthermore, professional judgment and expertise in contaminant hydrology and GIS operations are essential in the preparation of these maps. BALWOIS Ohrid, Republic of Macedonia - 25, 29 May

4 In this study, information about the hydrogeology of the study area was obtained from various sources in the form of field data, reports, digital and hardcopy maps. The seven DRASTIC parameter map layers were prepared with a raster resolution of m. UTM coordinates (zone 35S) and the European 1950 datum was chosen for all map layers. The following raw data was used in this study: Seasonal groundwater level measurements at 51 monitoring points 76m resolution DEM from NASA s SRTM database 1:100,000 scaled geology map Soil texture map Land use map Well logs and well specific capacity data for over 100 drilling locations Miscellaneous reports about previous hydrogeological studies in the area Cartographic data such as highways, locations of residential areas and stream network The rating maps for each parameter were produced by reclassifying information of quantitative data (e.g. groundwater depth, hydraulic conductivity) or qualitative data (e.g. aquifer and soil type) based on a scale from 1 to 10, depending on the degree of groundwater vulnerability. They are shown in Figures 3 and 4. Groundwater depth was calculated using cokriging interpolation on seasonal groundwater levels at 31 monitoring points (Elçi et al. 2009). The collocated auxiliary data used in the cokriging process was selected as the ground surface elevation data from the DEM of the study area. It is important to note that due to seasonal fluctuation of the water table the least favorable situation with respect to vulnerability had to be taken into account. Since the water table is highest in the rainy winter months, measurements representative of the winter conditions were used in the preparation of the groundwater depth parameter map. Rating values were assigned to each class ranging from 1 (deep groundwater, thus minimum impact on vulnerability) to 10 (shallow groundwater, thus maximum impact on vulnerability). Net recharge used in the context of groundwater vulnerability assessment is the total amount of precipitation water that infiltrates from the ground surface to the water table. This parameter can be estimated using hydrological precipitation-runoff models, field experiments or simply by multiplying the difference of the spatial distribution of evapotranspiration and the spatial distribution for mean annual rainfall by an infiltration coefficient. However, the necessary data was not available to implement any of the mentioned methods. Instead the land use map was used as a surrogate parameter to derive the recharge map. Rating values were assigned to five distinct land use classes, ranging from 10 (agricultural areas) to 1 (highways, residential and industrial areas and water bodies). The aquifer media ratings map was primarily obtained from rigorous analysis of well log data and the digitized geology map. The latter was used in particular to delineate zones for the aquifer media ratings map. Rating values were assigned to seven aquifer media classes ranging from 10 (karstic limestone) to 2 (tuff). Similarly, the impact of vadose zone map was obtained by interpolating point data from well logs. The resulting raster surface was then classified into seven classes ranging from 10 (maximum impact on vulnerability due to absence of impermeable layers in the vadose zone) to 3 (least impact to vulnerability due to fractured formations or relatively permeable layers). The soil type parameter map was obtained directly from an available digital version of a soil texture map for the Tahtalı stream basin. The different soil types were assigned ratings based on the potential ability of the soil to filter out contaminants by sorption and biochemical removal processes. These processes are usually governed by the clay and organic matter contents of the soil, respectively. Assigned ratings ranged from 10 (bare rock, gravel) to 1 (clay). The impact of topography on vulnerability is related to the terrain slope. Slope was calculated in terms of percentage using the resampled version of the original digital elevation data. Resampling was necessary to be consistent with the selected m resolution since the DEM had a different resolution. The calculated slope was classified into seven classes based on the prescribed rating scheme of the original DRASTIC method. Hydraulic conductivities for the saturated aquifer were estimated using specific capacity data. This data is usually obtained after completion of a well drilling and is provided in the well log. The inverse distance weighted interpolation scheme was selected to generate the spatial distribution of hydraulic BALWOIS Ohrid, Republic of Macedonia - 25, 29 May

5 conductivity from point data. The resulting raster map is further classified into four classes based on typical rating values ranging from 1 to 4. Figure 3. Rating maps for groundwater depth, net recharge, aquifer media type and soil type In the conventional DRASTIC method, the seven vulnerability parameters are assigned weighting coefficients ranging from 1 to 5, which reflect their relative importance to the vulnerability of the aquifer. These weights are determined subjectively by the expert who performs the vulnerability assessment. However, these weights can be subsequently refined based on statistical correlation of actual groundwater quality data with the obtained vulnerability index values, which leads to the production of an optimized groundwater vulnerability map, as it was done in this study. The DRASTIC vulnerability index map was computed according to the linear addition of the parameters given in Equation 1 : DRASTIC index = D r D w + R r R w + A r A w + S r S w + T r T w + I r I w + C r C w (Equation 1) where D, R, A, S, T, I and C are the seven parameters affecting groundwater vulnerability and the subscripts r and w are the corresponding rating values and weight coefficients, respectively. Weight coefficients of the original DRASTIC method was used: D w =5; Rw=4; A w =3; S w =2; T w =1; I w =5; C w =3. BALWOIS Ohrid, Republic of Macedonia - 25, 29 May

6 Figure 4. Rating maps for topography, vadose zone impact and saturated aquifer hydraulic conductivity Optimization of groundwater vulnerability maps with nitrate data The raw, unoptimized groundwater vulnerability map for the study site was obtained by weighted overlaying of the seven parameter rating maps using original DRASTIC weighting coefficients. Following this step, the map was refined by optimizing the parameter weighting coefficients using groundwater quality data. Nitrate was selected as quality data which was considered to be representative of land surface (or near surface) originating, conservative contaminant. Nitrate concentrations measured at 31 sampling points in a related study (Ileri et al., 2007) was used for this purpose. Nitrate concentrations and sampling points are depicted in Figure 5. BALWOIS Ohrid, Republic of Macedonia - 25, 29 May

7 Figure 5. Raw groundwater vulnerability map with nitrate concentrations and sampling stations The modification of the parameter weighting factors was achieved first by calculating the Spearman s rho correlation coefficients of each parameter rating value with the nitrate concentration for the 31 sampling points. Consequently, seven correlation coefficients were determined. These coefficients were rescaled to a scale of one to five to obtain the modified and thus optimized parameter weighting coefficients for each vulnerability parameter. In the case when any correlation coefficient was statistically not significant, the related parameters was simply ignored and taken out of Equation 1. Using the modified parameter weighting coefficients, an optimized version of the groundwater vulnerability map was produced. As part of the performance evaluation of the process, the correlations of raw and optimized vulnerability index values with actual nitrate concentrations were used as criteria to verify the accuracy of the obtained vulnerability maps. Thereby, it was also possible to quantify the impact of the optimization process on the overall outcome. Results Correlation coefficients of vulnerability parameters with nitrate concentrations and the modified weighting factors are summarized in Table 1. Based on these results, all parameters had statistically meaningful correlations with nitrate data. The vadose zone impact parameter and the saturated hydraulic conductivity had the strongest and weakest correlation, respectively. The weightings of BALWOIS Ohrid, Republic of Macedonia - 25, 29 May

8 groundwater depth, net recharge and hydraulic conductivity were decreased in the overall vulnerability assessment process. The remaining parameters were assigned higher weightings and hence became more pronounced vulnerability factors. The unoptimized, raw and the optimized groundwater vulnerability map are provided in Figures 5 and 6, respectively. Table 1. Original and modified weighting coefficient and correlations of vulnerability parameters with nitrate data Vulnerability parameter Original weighting coefficient Spearman s rho correlation coefficient * Optimized weighting coefficient Groundwater depth (D) Net recharge (R) Aquifer type (A) Soil type (S) Topography (T) Impact of vadose zone (I) Hydraulic conductivity (C) Figure 6. Optimized groundwater vulnerability map of the Tahtalı stream basin using optimized DRASTIC weighting coefficients BALWOIS Ohrid, Republic of Macedonia - 25, 29 May

9 Groundwater vulnerability indices for both maps were normalized based on Equation 2 to attain comparability. X n = X X X X maks min min 100 (Equation 2) X min and X max represent the lowest and highest index values calculated for the map, respectively, X the raster index value and X n the normalized vulnerability index. Also, to facilitate the interpretation of the maps, index values were reclassified into five classes; the green color tones in the map depict the areas that are less susceptible to groundwater contamination and the red color tones the area where contamination should be expected, when a contamination source is present. Pearson correlation coefficients between measured nitrate concentrations and corresponding vulnerability ratings increased from to by optimizing the layer weights (Figure 7). It can be concluded that the optimization improved the correlation by 11%. Furthermore, it is noticeable in the optimized map (Figure 6) that on an aerial basis 44% of the watershed is vulnerable to groundwater contamination, whereas 30% and 26% is moderately and less vulnerable, respectively. In particular the central part of the catchment is dominated by high vulnerability index values. This is in part due to the fact that the water table is shallow in the alluvial plains around the town of Menderes. Also, the geology in the central part of the catchment area is dominated by alluvial deposits, another negative factor with respect to vulnerability. Higher elevations of the study area, e.g. the northeast, south and west, are generally classified as less vulnerable due in part by deep groundwater and high terrain slopes Original DRASTIC vulnerability index Correlation coefficient r =0,589 (p>0,005) Optimized vulnerability index Correlation coefficient r =0,653 (p>0,005) Nitrate concentration (ppm) Nitrate concentration (ppm) Figure 7. Correlation between vulnerability index and nitrate concentration; (left) original DRASTIC vulnerability index; (right) optimized vulnerability index Discussion The groundwater vulnerability assessment approach that forms the basis of the presented study is widely accepted in the literature and practice because it is conceptually simple and its application is fairly straightforward. Although the GIS operations during the execution of the assessment are not complicated, it should be noted that meticulous preparation of the parameter rating maps is important. The reliability of the vulnerability maps depends on data and parameter map accuracy and quality. It is necessary to analyze the quality of raw data and maps originating from various sources and then synthesize the information to produce the parameter maps that form the basis of the vulnerability assessment. BALWOIS Ohrid, Republic of Macedonia - 25, 29 May

10 Another important fact of the matter is that even with visual inspection of the final vulnerability map certain patterns of groundwater vulnerability can be revealed that can be easily justified with data and observations in the field. However, it should be also noted that this method gives the end user a vulnerability map that is relative in nature rather than absolute. Therefore, if possible, enhancement or optimization of the assessment process should be sought. GIS-based groundwater vulnerability assessment methods are viable and useful tools for decision makers who want to take measures to protect groundwater resources from contamination. It was shown in this paper that the subjectivity of the DRASTIC approach can be reduced by a simple optimization process which is tied to actual groundwater quality data. References Aller, L., T. Bennett, J.H. Lehr, R.J. Petty, G. Hackett, 1987: DRASTIC : a standardized system for evaluating ground water pollution potential using hydrogeologic settings. Robert S. Kerr Environmental Research Laboratory, Office of Research and Development, U.S. Environmental Protection Agency, Ada, OK. Antonakos, A.K., N.J. Lambrakis, 2007: Development and testing of three hybrid methods for the assessment of aquifer vulnerability to nitrates, based on the drastic model, an example from NE Korinthia, Greece. Journal of Hydrology 333, Çalışkan, A., Ş. Elçi, 2009: Effects of Selective Withdrawal on Hydrodynamics of a Stratified Reservoir. Water Resources Management 23, Elçi, A., D. Karadaş, O. Fıstıkoğlu, 2009: The combined use of MODFLOW and precipitation-runoff modeling to simulate groundwater flow in a diffuse-pollution prone watershed. 13th International Specialized Conference on Diffuse Pollution and Integrated Watershed Management, Seoul, South Korea. Ileri, B., O. Gündüz, A. Elçi, C. Şimşek, M.N. Alpaslan, 2007: GIS Integrated Assessment of Groundwater Quality in Tahtali Basin Izmir (in Turkish). 7th National Environmental Engineering Congress. Panagopoulos, G.P., A.K. Antonakos, N.J. Lambrakis, 2006: Optimization of the DRASTIC method for groundwater vulnerability assessment via the use of simple statistical methods and GIS. Hydrogeology Journal 14, Sinan, M., M. Razack, 2009: An extension to the DRASTIC model to assess groundwater vulnerability to pollution: application to the Haouz aquifer of Marrakech (Morocco). Environmental Geology 57, TURKSTAT, 2008: Databank for Population, Housing and Demography. Turkish Statistics Institution. Accessed 28 January 2009 on BALWOIS Ohrid, Republic of Macedonia - 25, 29 May