Aquifer Vulnerability Assessment for Sustainable Groundwater Management Using DRASTIC
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. DRASTIC to Estimate Aquifer Vulnerability
- Dr: Ratings to the depth to water table;
- Dw: Weight assigned to the depth to water table;
- Rr: Ratings for ranges of aquifer recharge;
- Rw: Weight for aquifer recharge;
- Ar: Ratings assigned to aquifer media;
- Aw: Weight assigned to aquifer media;
- Sr: Ratings for soil media;
- Sw: Weight for soil media;
- Tr: Ratings for topography;
- Tw: Weight assigned to topography;
- Ir: Ratings assigned to vadose zone;
- Iw: Weight assigned to vadose zone;
- Cr: Ratings for rates of hydraulic conductivity; and
- Cw: Weight given to hydraulic conductivity.
2.3. Sources of Data
2.4. Nitrate Measurements
2.5. Aquifer Vulnerability Mapping Using DRASTIC
2.5.1. Depth to Water
2.5.2. Recharge
- Qi: Depth of runoff (mm);
- P: Depth of rainfall (mm);
- Ia: Initial abstraction (mm);
- S: Maximum potential retention (mm); and
- CN: Curve number (dimensionless).
2.5.3. Aquifer Media
2.5.4. Soil Media and Topography
2.5.5. Impact of Vadose Zone Media
2.5.6. Hydraulic Conductivity
2.6. Model Calibration and Validation
- : Simulated nitrate concentration DRASTIC binary value; and
- : Observed nitrate concentration binary value.
2.7. Evaluation for Potential Groundwater Monitoring Sites
- : Getis–Ord local statistic;
- : Attribute value for feature j;
- : Spatial weight between feature i and j; and
- : Total number of features.
3. Results and Discussion
3.1. Calibration and Validation of DRASTIC Weights
3.2. Aquifer Vulnerability Mapping
3.3. Potential Groundwater Monitoring and Management Sites
4. Conclusions
- (1)
- About 79% of land uses (45.5% agricultural and 23.5% urban areas) are human-related areas, and most human-related areas cover very high and high vulnerability classes. Thus, DRASTIC in this study describes human impact. For more accurate estimation of human impact by DRASTIC or other overlay and index models, more human-impact-related factors such as land use, population density, and point sources should be considered as input data.
- (2)
- For a detailed vulnerability assessment, the aquifer vulnerability analysis of DRASTIC would need to be combined with predictive models for pollutant transport. This combination is required to evaluate the actual quantitative risk. For example, models such as SWAT which can estimate pollutant transport could be combined with DRASTIC. Further, pollutant transport should be considered beyond that on the land surface and consider subsurface transport. To do this, more detailed soil data that describe various soil components for the surface and subsurface soil layers should be used for future study.
- (3)
- The aquifer vulnerability index is a combination of data. Further, there are many pre-processes and post-processes to generate an aquifer vulnerability index. Thus, an aquifer vulnerability index includes some degree of uncertainty which might come from data, data processing errors by the modeler, and model structure. Future work would benefit from quantification of errors when using an overlay and index model.
Author Contributions
Conflicts of Interest
Appendix A
Depth to Water (m) | |
Range | Rating |
0–1.5 | 10 |
1.5–4.6 | 9 |
4.6–6.8 | 8 |
6.8–9.1 | 7 |
9.1–12.1 | 6 |
12.1–15.2 | 5 |
15.2–22.9 | 4 |
22.9–26.7 | 3 |
26.7–30.5 | 2 |
30.5+ | 1 |
Net Recharge (mm/year) | |
Range | Rating |
254+ | 10 |
235–254 | 9 |
216–235 | 8 |
178–216 | 7 |
147.6–178 | 6 |
117.2–147.6 | 5 |
91.8–117.2 | 4 |
71.4–91.8 | 3 |
51–71.4 | 2 |
0–51 | 1 |
Aquifer Media | |
Range | Rating |
Karst limestone | 10 |
Basalt | 9 |
Sand and gravel | 8 |
Massive sandstone Massive limestone | 7 |
7 | |
Bedded sandstone Limestone | 6 |
6 | |
Glacial till | 5 |
Weathered metamorphic igneous | 4 |
Metamorphic igneous | 3 |
Massive shale | 2 |
Soil Media | |
Range | Rating |
Thin or absent/Gravel | 10 |
Sand | 9 |
Peat | 8 |
Shrinking clay | 7 |
Loamy sand | 6 |
Sandy loam | 6 |
Loam | 5 |
Sandy clay | 4 |
Sandy clay loam | 4 |
Silt loam | 4 |
Silty clay | 3 |
Clay loam | 3 |
Silty clay loam | 3 |
Muck | 2 |
Non-shrinking clay | 1 |
Topography (%) | |
Range | Rating |
0–2 | 10 |
2–6 | 9 |
6–12 | 5 |
12–18 | 3 |
18+ | 1 |
Vadose Zone Media | |
Range | Rating |
Thin or absent/Gravel | 10 |
Sand | 9 |
Peat | 8 |
Shrinking clay | 7 |
Loamy sand | 6 |
Sandy loam | 6 |
Loam | 5 |
Sandy clay | 4 |
Sandy clay loam | 4 |
Silt loam | 4 |
Silty clay | 3 |
Clay loam | 3 |
Silty clay loam | 3 |
Muck | 2 |
Non-shrinking clay | 1 |
Hydraulic Conductivity (m/s) | |
Range | Rating |
0.00095+ | 10 |
0.0005–0.00095 | 8 |
0.00033–0.0005 | 6 |
0.00015–0.00033 | 4 |
0.00005–0.00015 | 2 |
0.00000015–0.00005 | 1 |
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Data Type | Source | Format | Scale | Date | Used to Produce |
---|---|---|---|---|---|
Water well | IDNR 1 | Point Shapefile | 1:24,000 | 1959–2010 | Depth to water |
Annual Precipitation | NCDC 2 | Tabular data | - | 1949–2013 | Recharge |
LULC | MRLC 3 | Raster | 1:250,000 | 2006 | Recharge |
Aquifer Systems | USGS 4 | Polygon Shapefile Text | 1:48,000 | 2003–2011 | Aquifer media |
SSURGO 5 | NRCS 6 | Polygon Shapefile | 1:12,000 | 2005 | Recharge Soil media Topography |
iLITH data | IGS 7 | Point Shapefile | 1:24,000 | 2001 | Impact of vadose |
Aquifer Transmissivity | IDNR 1 | Point Shapefile | 1:24,000 | 2011 | Conductivity |
DRASTIC Parameters | Description | Original Weight |
---|---|---|
Depth to water (D) | Depth from the ground surface to the water table. Deeper water table levels imply lesser contamination chances. | 5 |
Recharge (R) | Amount of water entering the aquifer. The amount of recharge is positively correlated with the vulnerability rating. | 4 |
Aquifer media (A) | Material property of the saturated zone, which controls pollutant attenuation processes based on the permeability of each layer of media. | 3 |
Soil media (S) | Soil media affects contaminant transport and water from soil surface to the aquifer. | 2 |
Topography (T) | Slope of the land surface. For low slope, contaminant is less likely to become runoff and more likely to infiltrate. | 1 |
Impact of vadose zone media (I) | Vadose zone is the typical soil horizon above the water table and below the ground surface. If vadose zone is highly permeable, this will lead to a high vulnerability rating. | 5 |
Hydraulic conductivity (C) | Hydraulic conductivity represents the ability of the aquifer to transmit water. Hydraulic conductivity is positively correlated with the vulnerability rating. | 3 |
Aquifer Media | |||
---|---|---|---|
Range | Rating (Typical) | Vulnerability (IDNR Report) | Rating (Modified) |
Karst limestone | 10 | Very high | 10 |
Basalt | 9 | High | 8 |
Sand and gravel | 8 | Moderate | 6 |
Massive sandstone Massive limestone | 7 | Low | 4 |
Bedded sandstone Limestone Shale | 6 | Very Low | 2 |
Glacial till | 5 | ||
Weathered metamorphic | 4 | ||
Metamorphic Igneous | 3 | ||
Massive shale | 2 |
GA Driving Variables | Values |
---|---|
Population size | 100 |
Max generation | 10,000 |
Initial random value | 1000 |
Min. value of parameters | 0 |
Max. value of parameters | 6 |
Crossover probability | 0.5 |
Mutation probability | 0.02 |
Calibration Methods | D | R | A | S | T | I | C | RMSE |
---|---|---|---|---|---|---|---|---|
No calibration | 5 | 4 | 3 | 2 | 1 | 5 | 3 | 0.70 |
Bi-GA 1 | 5.7 | 4.3 | 3 | 1.6 | 0.7 | 5.4 | 2.8 | 0.57 |
Uncalibrated DRASTIC | Calibrated DRASTIC | |||
---|---|---|---|---|
Reference Data | Reference Data | |||
Classification | >2 ppm | >2 ppm | ||
Very high + high 1 (>2 ppm) | 12 | Very high + high 1 (>2 ppm) | 16 | |
Others 2 (≤2 ppm) | 23 | Others 2 (≤2 ppm) | 19 |
Class | Area (%) | Number of Nitrate Detections >2 ppm |
---|---|---|
Very low | 10.6 | 1 (0.9%) |
Low | 60.4 | 4 (3.4%) |
Moderate | 25.8 | 70 (60.3%) |
High | 3.0 | 34 (29.3%) |
Very high | 0.2 | 7 (6%) |
Class | Area (%) | Number of Nitrate Detections >2 ppm |
---|---|---|
Very low | 9.6 | 0 (0%) |
Low | 60.1 | 5 (4.3%) |
Moderate | 26.9 | 62 (53.4%) |
High | 3.2 | 42 (36.2%) |
Very high | 0.2 | 7 (6%) |
Navulur (1996) | ||||
---|---|---|---|---|
DRASTIC | SEEPAGE | Combined DL 1 | DRASTIC 2 | |
HV-Area 3 (%) | 24.8 | 28.6 | 56.9 | 3.4 |
N-Detections 4 (%) | 80.7 | 60.5 | 91.8 | 42.2 |
Detection Ratio | 3.3 | 2.1 | 1.6 | 12.4 |
Calibration Methods | Potential Groundwater Monitoring and Management Sites (%) | ||
---|---|---|---|
Z-Scores | |||
1.65–1.96 | 1.96–2.58 | >2.58 | |
Bi-GA | 3.4 | 5.6 | 10.9 |
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Share and Cite
Jang, W.S.; Engel, B.; Harbor, J.; Theller, L. Aquifer Vulnerability Assessment for Sustainable Groundwater Management Using DRASTIC. Water 2017, 9, 792. https://doi.org/10.3390/w9100792
Jang WS, Engel B, Harbor J, Theller L. Aquifer Vulnerability Assessment for Sustainable Groundwater Management Using DRASTIC. Water. 2017; 9(10):792. https://doi.org/10.3390/w9100792
Chicago/Turabian StyleJang, Won Seok, Bernard Engel, Jon Harbor, and Larry Theller. 2017. "Aquifer Vulnerability Assessment for Sustainable Groundwater Management Using DRASTIC" Water 9, no. 10: 792. https://doi.org/10.3390/w9100792