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Delineating groundwater prospect zones using Multi Criteria Analysis ( MCA)

by Tejaswi Bhardwaj

Spatial decision problems typically involve a large set of feasible alternatives & multiple evaluation criteria most of the time, these are conflicting. Alternatives & criteria are often evaluated by a number of individuals (decision-makers, managers, stakeholders, interest groups). Most of the time, they also have conflicting ideas, preferences, objectives, etc.  GIS  techniques & procedures have an important role to play in analyzing decision problems and recognized as a decision support system involving the integration of spatially referenced data in a problem solving environment. Multi-Criteria Analysis (MCA) or Evaluation (MCE) is a technique used in decision making to analyze and compare how well different alternatives achieve different objectives and through this process identifying a preferred alternative. GIS based Multi-Criteria Decision Analysis is a process that transforms and combines geographical data and value judgments (decision-makers preferences) to obtain relevant information for decision making.

Multi-criteria analysis (MCA) is a technique used to consider many different criteria when making a decision. MCA gives a logical, well-structured process to follow so different factors can be clearly identified and prioritised. It allows the alternative solutions being considered to be ranked in order of suitability. Spatial MCA is used for decisions with a geographical element, most often in site selection processes where multiple factors need to be considered. Eg:

  • Site location
  • Land use
  • Distance to areas of population
  • Local area demographics
  • Proximity to transport and road infrastructure
  • Environmentally sensitive areas

Assessment of ground water resource using GIS & Multi-Criteria Analysis (MCA)
Assessment, planning and management of groundwater resource are becoming crucial and extremely urgent in recent time. In order to do assessment of groundwater availability, it is required to delineate groundwater potential zone using remote sensing, GIS and Multi-Criteria Analysis (MCA). Different thematic layers such as hydrogeomorphology slope and lineament density maps have been transformed to raster data. To assign weights and ranks to different input factor maps, multi-influencing factor (MIF) technique has been used. The weights assigned to each factor have been computed statistically. Weighted index overlay modeling technique is used to develop a groundwater potential zone map with three weighted and scored parameters. A groundwater development program requires a large volume of data from various sources. Remote sensing and GIS study with its advantages of spatial, spectral and temporal availability of data covering large and inaccessible areas within a short time has come out as an efficient tool to provide the appropriate platform for convergent analysis of large volumes of multi-disciplinary data and decision making for groundwater studies. Various thematic maps such as geomorphology, slope and lineament density maps have been generated to determine the groundwater potential zones.


  

                     Fig 1  Methodology Flowchart of Delineating Ground-Water Potential Zone Map

Hydrogeomorphology
Hydrogeomorphological studies include identification and mapping of different landforms that have a direct control on the occurrence of groundwater. Based on the interpretation of the satellite image and SOI Toposheet, different hydrogeomorphological units have been delineated. Remote sensing studies provide an opportunity for better observation and more systematic analysis of various hydrogeomorphic units/ landforms/lineaments, features following the multispectral repetitive coverage of the terrain. 


                                                    Fig 2  Map of Hydrogeomorphological Units

Lineament and lineament density
Lineaments are topography of the underlying linear structural features. Lineaments play an important role in groundwater recharge in hard rock terrains; groundwater potential is high near lineament zones. Lineament density is the total length of all the lineaments present in the basin/watershed divided by the area of basin/ watershed. Lineament density map was prepared by dividing the study area into 1 km/1 km grids, and the lineament density values of each grid was then obtained from the values of the ratio of total length of the lineaments in a single grid (L) and the area of that single grid (A). By calculating the value of L/A for each grid, the value is plotted at the centre of each grid. 


                                                               Fig 3  Lineament Length Density Map

Groundwater Potential Zones

Different thematic maps describing favourable sites for groundwater potentiality have been prepared. These maps were then integrated with the help of GIS software. All the thematic maps were converted into grid (raster format) and analyzed by weighted overlay method (rank and weightage wise thematic maps). As a result, four different zones have been identified i.e.

  • Excellent
  • Good
  • Moderate
  • Poor

                                                              Fig 4  Map showing groundwater potential zones

Summary
Geospatial technology is a rapid and cost-effective tool in producing valuable data on geology, geomorphology, lineaments and slope, etc., that plays a significant role in deciphering groundwater potential zone. The spatially complete and temporal nature of the remote sensing data provides excellent opportunities to hydrogeologists for improving the understanding of the hydrogeological system. Several factors such as geomorphology, land use/land cover, geological structures, fractures, groundwater table distribution, slope and drainage—all contribute in the movement and occurrence of groundwater in an area.


SATPALDA is a privately owned company and a leading provider of satellite imagery and GeoSpatial services to the user community. Established in 2002, SATPALDA has successfully completed wide range of photogrammetric and Remote Sensing Projects.

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