GIS in the Estimation of Groundwater Recharge
A series of Annotated Bibliographies created for
GEO 565: Geographic Information Systems and Science
Winter 2009
Overview:
Advances in GIS technology are increasing its usefulness in water resource studies, especially in determining estimates and potential for groundwater recharge. GIS is a very useful tool for calculating recharge because it has the ability to produce quick estimates that would otherwise be labor and time intensive if determined through field measurement techniques. Another benefit of using a GIS models is that it allows for the production of cheap, multi-temporal estimates. Groundwater recharge estimates produced using GIS tend to correlate well with field measurements as indicated by the following research studies.
Batelaan, O., and De Smedt, F. (2007). "GIS-Based Recharge Estimation by Coupling Surface-Subsurface Water Balances." Journal of Hydrology, 337: 337-355.
Batelaan and De Smedt develop a method to simulate long-term average groundwater recharge in GIS by using the WetSpass water balance model which incorporates land cover, soil texture, topography and precipitation in conjunction with a groundwater model. This method was tested on 17 catchments which showed spatially complex discharge patterns attributed to soil texture and land cover. Further GIS analysis revealed significant groundwater recharge variance based on soil texture and land cover characteristics. Results produced by the model showed a correlation coefficient of 0.93 with field observed values. Possible errors were attributed to model concept, uncertainties in land cover, soil classifications, slope, and precipitation maps.
Bogena, H., Kunkel, R., Schobel, T., Schrey, H.P., and Wendland, F. (2005). "Distributed Modeling Of Groundwater Recharge at the Macroscale." Ecological Modelling, 187: 15-26.
The purpose of this research was to test the accuracy of a GIS raster-based calculation method's ability to calculate groundwater recharge values. The method used was the empirical GROWA model, which uses climate data, soil data, soil cover, geology, topographic, and validation data in estimating groundwater recharge. The GROWA method was modified for this research to include more sophisticated geology parameters as the model tends to overestimate recharge in solid rock. The model was applied to the entire Federal State of North Rhine-Westphalia, an area of approximately 34,000 square kilometers, using a grid resolution of 100 meters. Field runoff data was collected from 125 gauging stations to derive baseflow indices for the years 1979-1999. Based on the data collected from the gauging stations, most of the GIS-derived values were found to have a margin of error less than 15%.
Cherkauer, D.S., and Ansari, S.A. (2005). "Estimating Ground Water Recharge from Topography, Hydrogeology, and Land Cover." Ground Water, 43(1): 102-112.
This paper presents a method to estimate groundwater recharge using available ground surface information for the purpose of long term monitoring. Layers used by this method included: slope, depth to water table, soil conductivity, and land cover. The goal of this method is to provide a quick initial estimate that can later be fine tuned with other methods. The authors tested this method on 15 different watershed sites ranging in size from 3 to 48.7 square kilometers in southern Washington County, Wisconsin, on land primarily used for agriculture. To determine accuracy, stream baseflow separation from total stream discharge was measured as a proxy for recharge to compare to the GIS derived values. When measuring recharge, the value is normalized by factoring in annual precipitation, so the researchers focus on the recharge to precipitation ratio. The authors determined that recharge varies directly with the ratio of infiltration flux to surface runoff and with the total percentage of natural land cover. When comparing values calculated in ArcView to manually collected ones, it was found that the GIS tended to overestimate slope and landcover percentages while underestimating depth to water table. Recharge was found to vary inversely with the ration of representative vertical and lateral travel distance across a watershed. The GIS derived recharge rates were found to correlate to the manually measured rates within 15-20%.
Jasrotia, A.S., Kumar, R., and Saraf, A.K. (2007). "Delineation of Groundwater Recharge Sites Using Integrate Remote Sensing and GIS in Jammu District, India." International Journal of Remote Sensing, 28(22): 5019-5036.
This study combined remote sensing with GIS techniques to produce maps to aid in determining suitable locations for creating artificial recharge zones for the purpose of replenishing groundwater. Thematic maps of lithology, geomorphology, land cover, drainage and soil texture were produced by combining Linear Imaging Self Scanner (LISS)-III and panchromatic remote sensing data from the Indian Remote Sensing Satellite IRS-1D. A topographic map provided slope data. These maps were combined in ArcView with layers of aquifer data including depth to water table, transmissivity, permeability, storage, capacity, and infiltration which were produced from conventional field data to produce the potential for artificial recharge zones map. Ideal locations were those determined to have high storativity, shallow depth to the water level and good water holding capacity. The GIS generated maps were then verified for accuracy by making field observations. Incorporating drainage and terrain data allowed the researchers to identify the most suitable areas for installation of artificial recharge systems.
Minor, T.B., Russell, C.E., and Mizell, S.A. (2007). "Development of a GIS-based model for extrapolating mesoscale groundwater recharge estimates using integrated geospatial data sets." Hydrogeology Journal, 15: 183-195.
In this study, a GIS based model is used to estimate recharge using the elevation-dependent chloride massbalance (EDCMB) approach. The EDCMB approach uses precipitation, chloride flux, and chloride enrichment in groundwater to quantify recharge. Chloride enrichment is determined at springs at different elevations in the study area in order to correlate it to elevation. The research consisted of a 14 basin area located in southwestern Nevada. For each basin, a non-linear regression equation was derived to relate chloride enrichment to watershed elevation. These formulae were added to the GIS framework along with precipitation, elevation and geologic data to determine explicit recharge values. The final calculated recharge estimates were within 14% and 3% of two previous studies performed on the area, but varied by 31% from a third study.
Lin, Y., Wang, J., and Valocchi, A.J. (2009). "PRO-GRADE: GIS Toolkits for Ground Water Recharge and Discharge Estimation." Ground Water, 47(1): 122-128.
This paper introduces the new PRO-GRADE plug-in package for ArcGIS, a tool for estimating groundwater recharge and discharge, and compares this new tool to an older one using a control basin for validation. PRO-GRADE consists of two component toolkits: the pattern recognition organizer (PRO-GIS) and groundwater recharge and discharge estimator (GRADE-GIS). By taking hydraulic conductivity, water table, and bedrock elevation data, the GRADE-GIS software is able to produce the recharge and discharge data for two-dimensional steady state unconfined aquifers. PRO-GIS uses image processing algorithms on GRADE-GIS data to estimate the recharge and discharge rates and patterns. Both methods were found to produce comparable results, validating PRO-GRADE's computations.
Saraf, A.K., Choudhury, P.R., Roy, B., Sarma, B., Vijay, S., and Choudhury, S. (2004). "GIS Based Surface Hydrological Modelling in identification of groundwater recharge zones." International Journal of Remote Sensing, 25(24): 5759-5770.
In this study, Saraf et al. examined two Indian watersheds, the Dwarkeshwar and the Kethan to determine if groundwater recharge zones identified by using GIS techniques correlate with results produced by surveyed data. These watersheds are dominated by hard rock terrain which covers 65% of India's surface. DEMs were generated by digitizing contour maps and interpolating the data points. The researchers combined land use, vegetation, surface water remote sensing data with GIS data of water table and aquifer properties and DEM-derived terrain data to produce a map of groundwater recharge zones. Visual comparison of the final surveyed groundwater recharge zones and the GIS calculated map groundwater recharge zones show good correlation for both the watersheds examined.
Sen, P.K., and Gieske, A. (2005). "Use of GIS and Remote Sensing in Identifying Recharge Zones in an Arid Catchment: A Case Study Of Roxo River Basin, Portugal." Journal of Nepal Geological Society, 31: 25-32.
This article discusses the use of GIS and remote sensing in identifying recharge zones in arid regions. The researchers focused their study on the Roxo River basin in Portugal. While previous methods focused on calculating water balance for a single point, the authors used GIS to model water balance for the entire catchment. The model required the following layers: soil texture, land cover, and water holding capacity as determined by soil texture and vegetation. Using data from rainfall monitoring stations, point interpolation was used to determine its spatial and temporal distributions using the IL WIS GIS software. These data allowed the researchers to estimate the spatial and temporal distribution of groundwater recharge and flow in the watershed and thus isolate the recharge zones.
Shankar, M.N.R., and Mohan, G. (2005). "A GIS Based Hydrogeomorphic Approach for Identification of Site-Specific Artificial-Recharge Techniques in the Deccan Volcanic Province." Journal of Earth Systems Science, 114(5): 505-514.
This study used remote sensing and GIS techniques to identify site-specific watershed management techniques in order to enhance the groundwater potential in a region. Specifically, the authors are using GIS to identify zones favorable for the implementation of artificial recharge techniques. Input features include a basin's drainage density, slope, landforms, landuse/land cover, drainage patterns, lineament density, depth to bedrock, soil cover, and groundwater condition. These data are used to determine the region's groundwater potential and suitability for installation of an artificial recharge system. In the Bhatsa and Kalu basins examined by Shanhar and Mohan, they found that recharge structures such as percolation ponds, check dams, and echelon dams were suitable for certain zones in the environment based on the drainage morphology.
Tweed, S.O., Leblanc, M., Webb, J.A., and Lubczyski, M.W. (2007). "Remote Sensing and GIS for Mapping Groundwater Recharge and Discharge Areas in Salinity Prone Catchments, Southeastern Australia." Hydrogeology Journal, 15: 75-96.
In this study, Tweed et al. combine GIS and remote sensing techniques to map the recharge and discharge areas of an unconfined basalt aquifer in the Glenelg-Hopkins catchment in Southeastern Australia. The aquifer is approximately 11,500 square kilometers located in an agricultural region. Layers used included DEMs, soil type, groundwater electrical conductivity, flow, depth to water table, terrain, vegetation activity, and ground infiltration capacity. Vegetation activity was determined by calculation the vegetation indices using Landsat data. Based on their findings, they were able to match catchment features to recharge or discharge processes. Discharge areas were associated with stable vegetation, topographic depressions, breaks in slop, shallow depth to water table, groundwater flow direction, and permanent surface water bodies. Areas that were not associated as being a discharge area were considered recharge areas. Areas with high shallow zone infiltration rates were considered preferential recharge zones. The authors believe their findings will be useful for future studies on this aquifer, particularly numerical modeling and water-budget analysis.
Vijay, R., Panchbhai, N., and Gupta, A. (2007). "Spatio-Temporal Analysis of Groundwater Recharge and Mound Dynamics in an Unconfined Aquifer: A GIS-Based Approach." Hydrological Processes, 21: 2760-2764.
In this research, Vijay et al. study the effectiveness of a basin in terms of its hydrologic and hydraulic properties based on its geometry using a GIS-based approach. Basins of different geometries were examined for their recharge and mound growth effectiveness. The authors' GIS-based approach used a two phase algorithm. The first phase involved referencing the thematic maps and relative attribute data into the GIS environment. The second phase involved the computations using modules to determine recharge and mound growth. Results were compared with those obtained doing manual calculations and differences were found. The GIS-based approach also allows for the computation of recharge and mound growth of irregularly shaped basins, which was not possible with the manual equation they were using. The researchers determined that square shaped basins are the most effective in providing recharge.
Last Modified: March 13, 2009