30 Applications of Remote Sensing and GIS in Groundwater and Water Pollution

Dr. Jitendra Kumar Pattanaik

CONTENTS

 

1.  Aim of the Module

 

2.  Introduction

 

3.  Remote sensing and GIS techniques for Groundwater studies

 

4.  Sensing of Ground Water Fluxes

 

5.  Ground water and Land Surface

 

6.  Image interpretation for ground water study

 

7.  Remote sensing and GIS in water pollution studies

 

8.  Conclusions

 

9.  References

 

 

1.  Aim of the Module

  • To explain conceptual model for groundwater flow system
  • To apply remote sensing and GIS techniques for hydraulic potential and flux Understand the interaction of groundwater and land surface
  • Understand the occurrence of ground water in different terrain
  • Applying remote sensing and GIS techniques for water pollution studies

 

2.  Introduction

 

This module is divided into two parts. The first part deals with the application of remote sensing and geographic information system (GIS) techniques for the groundwater studies and the second part (section 6) explains the application on water pollution studies.

 

Groundwater is a vital natural resource for mankind. This resource is extensively being used for drinking and household utilization; irrigation and industrial purpose. It plays an important role for the economic development and food security of the country. Only 2.5% of the earth’s water is available as freshwater. Groundwater comprises nearly 30% of freshwater resource of the world whereas glaciers and ice cap consist of 68.7% (http://water.usgs.gov/edu/earthwherewater.html) which is difficult to access for direct utilization. Remaining freshwater is present in lake, river, stream, atmosphere and wetland. Therefore groundwater is an important source of freshwater. The annual replenishable ground water resource of India is 431 billion cubic meters (bcm), net annual availability is 396 bcm whereas the annual ground water draft for irrigation, domestic and industrial use is 243 bcm (CGWB, 2009; Murry, 2013). In the country like India nearly 90% of rural population and 30 % of urban population depend up on the groundwater for drinking and domestic use (NRSA, 2008; Murry, 2013).

 

Demand of groundwater is increasing day by day due to rapid increase in population, urbanization, industrialization and agriculture. It leads to decline in groundwater level and anthropogenic activity deteriorating the quality. Similar problems are also prevailing for the useable surface water. Hence it is important to study the ground water potential and its quality of our country for a better sustainability.

 

Occurrence and distribution of groundwater is controlled by the lithology, structure, geomorphology and rainfall pattern of an area. So detail investigations of these controlling parameters are required for groundwater modeling and management. Groundwater modeling and management required reliable input data which is most of the time difficult to obtain. The standard point sampling methods for input parameter are biased because of heterogeneity in subsurface layers and structures, and restriction of sample from harsh terrain. Additionally this method is expensive and time consuming. So the remote sensing and GIS technique provided ample scope to generate input data to study groundwater and its quality of an area more efficiently at lower cost and time. However for validation ground verifications are required.

 

3.   Remote sensing and GIS techniques for Groundwater studies

 

Remote sensing provides information in space and time and GIS techniques helps to store, interpret and retrieve spatial data. It is very essential for an inaccessible area. This technique is very successful for surface hydrology, but for subsurface hydrology remotely sensed images such as airborne and space borne; passive or active microwave image; data from specific satellite sensor with different spatio-temporal or spectral resolutions can be analyzed to infer the groundwater behavior from surface expressions and its quality. Generally these data are combined with the numerical modeling, GIS and ground-based information. The basic principle for the remote sensing groundwater is to find out the shallow groundwater flow. These flows are driven by the surface forcing and other geological parameters which can be inferred from the surface data.

 

Based on the topographic driving force Tόth (1963) conceptualized a model (Fig. 1) of groundwater flow system for local and regional scale. This model shows that the ground water recharged at higher elevation in the regional scale tend to move deeper compare to local scale recharge. So based on the topographical information from remote sensing data predicting local or regional scale groundwater flow will be more effective (Becker, 2005). The rate and behavior of flow depend up on the geology and it can be expressed by the Darcy’s Law. Darcy’s law defines the flow of fluid in a porous medium and also states that there is a linear relationship between flow velocity and hydraulic gradient (I) for any given saturated soil or medium under steady laminar flow conditions. It can be stated as

 

q = K. I

 

Where ‘q’ is the specific discharge vector representing flow per unit area (flux of ground water), ‘K’ is the hydraulic conductivity which is a function of geology, ‘I’ is the hydraulic gradient which is a function of surface forcing (Becker, 2005). Geological maps prepared in combination with remotely sensing data and ground verification provides useful information about the hydraulic conductivity, water bearing formations, lineaments such as faults, fractures in the hard-rock terrain. This information is used for groundwater prospecting as evident from literature.

 

For preparation of groundwater model of an area, surface water treated as the boundary conditions for the subsurface flow equation which is based Darcy’s law. Remotely sensed imageries are used to define boundary conditions such as streams, lakes, wetlands, seepage areas, recharge zones, or evapotranspiration zones for prediction of ground water flow. The important mathematical boundary conditions are hydraulic head (Fig. 2), flux or discharge (Fig. 3), mixed (both head and discharge). So the remote sensing applications in ground water studies can be structured into the sensing of hydraulic potential (heads) and hydraulic flux (or discharge).

 

3.1 Sensing of Hydraulic Potential (heads)

 

To measure groundwater head sensors like visible, microwave and gravity sensors may be used. Ground water storage and hydraulic gradient can be deduced from hydraulic head.

 

3.2 Surface Water Elevations: Generally the elevation of surface water depicts the possible groundwater head of that region. Therefore the spring or first-order stream originates at an elevation where water table intersects the slope. In the catchment scale it provides an opportunity for dynamic monitoring of water table. Sometime it may be difficult if hydraulic conductivity changes considerably. Use of satellite based altimetry and interferometry for obtaining surface water elevations provides higher accuracy (Becker, 2005) compare to digital elevation models (DEMs) and topographic digital line graphs (DLGs).

Figure 1: Conceptual model (Tόth) of topographically driven ground water flow systems (after Becker, 2005; Fetter 2001).

 

Figure 2: Schematic illustration of the groundwater flow system, distribution of groundwater recharge and discharge in relation to surface topography and distribution of hydraulic head for a simple water-table aquifer (after Fleming and Rupp, 1994).

 

3.3 Water Column Mass: Water storage in the subsurface and hydraulic head in an aquifer can be estimated using satellite or aerial gravity surveys. This method is useful for studying very large aquifer system due to very coarse spatial resolution. Additionally this method does not have the vertical resolution; hence the influences from water present in the atmosphere and vegetation, and unsaturated water content i.e. soil moisture has to be removed to enhance the accuracy in estimates of saturated water mass (Becker, 2005). Determination of ground water potential gradient is difficult using this method because of coarse spatial resolution which requires aquifer to be continuous over hundreds of kilometer. Data obtained from the NASA Gravity Recovery and Climate Experiment (GRACE) satellite proved to be an asset for estimating ground water storage.

 

3.4 Heat Capacity: Heat capacity of saturated soil is higher than the dry soil. Using this property of soil, depth of water table can be estimated from remotely sensed thermal image. This technique is very useful to locate shallow water tables and this was proposed by Cartwright (1968) and Chase (1969) in the early days of remote sensing application. Some researchers have found that night time thermal images are more useful to predict depth of shallow water table compare to the day time thermal image. Annual variation in soil temperature like heat sink during summer and heat source in the winter should be taken into consideration for locating the depth of water table. This technique should be used cautiously in the snowpack areas where it amplify the heat signature of shallow ground water through heat of fusion during snow melt or heat change in the snowpack (Becker, 2005).

 

3.5 Land Subsidence: Ground water generally occupies the pore space of the sediments. In case of unconsolidated sediment, addition (recharge) or withdrawal (depletion) of water from the pore space will change the net volume. During recharge effective pressure will be high in the pore space hence it will increase the volume as well as water level (Becker, 2005). Withdrawal of water will cause reduction in the pore pressure which leads to decrease in volume and compaction of unconsolidated sediment. This will result in land subsidence. This volume change will be reflected as variation in the surface elevation. Although this variation is small, it can be measured by interferometric synthetic aperture radar (InSAR). For this analysis image of a location is taken from different angle and time. Accuracy of elevation change estimated by In SAR analysis is control by topography and concentration of water vapor in the atmosphere. This accuracy is different for humid (10cm) and dry (1mm) region (Galloway et al 1998). Using surface elevation change storativity of a porous medium can also be estimated with the help of other data such as geodetic controls from GPS, water level, hydrological flux and strain measurement of the study area. Integration of numeric model with InSAR analysis widens the application of this method and provides better resolution and spatial extent of land subsidence than ground base measurement (Becker, 2005).

 

3.6 Soil Moisture: Presence of shallow water table can be predicated based on the soil moisture content. Different remote sensing method has been applied extensively to delineate shallow water table from soil moisture content and vegetation stress or proliferation (Becker, 2005). Visible and near-infrared sensor is also used to monitor the change of vegetation cover/agricultural performance which can be linked with the water logging or change in the soil moisture content. Passive and active microwave sensor can be used to monitor flood and ground water recharge. Predicting water table depth from soil moisture content is conditional because it requires surface soil should be continuous as drying of surface soil may decouple from the subsurface soil moisture.

 

4. Sensing of Ground Water Fluxes

 

At many places ground water flow is driven by topography where it gets recharged at higher elevation and discharged at lower elevation (Becker, 2005). Different remote sensing methods are being applied effectively to find out the interface between ground water and surface water or land surface. These interfaces are manifested as lakes, stream, spring or seeps in the surface. Discharge of ground water transfer heat and chemical constituents to the surface which can be detected by the remote sensing method. This also reflected by the vegetation cover in the interface as water uptake of plant changes.

 

The nature of connection between ground water and surface water differ in the arid and humid climate or during wet and dry season. For example: water table is well separated from the surface water by a large vadose zone in the arid climate (Becker, 2005). Water deprived vegetation from dry season or arid climate regime indicates the position and flow of the ground water. During wet season or humid climate region the ground water perched below the surface water demarcating the interface and hence it can be used for inferring ground water condition. In this region shallow water tables are more common and generally it is easy to interpret ground water condition compare to arid region.

 

4.1 Spring and seep

 

Springs and seep develops at the interface of water table and surface (Fig. 3). These water tables or ground water layer is confined by an impervious (clay units) or low permeable rock or structural unit (fracture rock) which facilitate to form a focused discharge point. Using infrared thermal analysis springs or seep may be detected as it shows contrasting temperature with respect to surrounding area (Becker, 2005). At many instance the ground water is saturated with different mineral phase which leads to precipitation of secondary minerals and staining in the rock near spring and seep. These features are good indicator of spring or seep or to locate geothermal spring. Presences of different chemical dissolve species in the ground water also affect the vegetation cover. Mineral precipitation, staining or change in the vegetation cover are very local, hence it impose spatial limitation to the remote sensing analysis.

Figure 3: Development of springs (Source: http://www.kcse-online.info/geog/5.html)

 

4.2 Base flow of a stream

 

Base flow of a stream is mainly controlled by the discharge of ground water to stream. Quantifying the base flow of a stream is not possible from remote sensing method directly but field data from stream gauge network will help to estimate the base flow. In the absence of field data theoretical estimation of base flow from stream cross section and surface velocity can be obtained. Inflow of ground water to the stream varies widely with maximum inflow observed near bank and it is distributed spatially. Remote sensing method can be applied to characterize the ground water discharge based on the thermal signature of the area where stream bed temperatures are measured (Becker, 2005). Maps can be prepared for hydrological assessment of a region using average base flow index (BFI: the fraction of stream flow attribute to the base flow) of different watershed. The region with higher BFI is more feasible to assess the ground water flow using remote sensing method. Multiple remote sensing images and time series field data are being used to estimate the ground water flux and its flow.

 

4.3 Inflow to Surface water bodies

 

Estimation of inflow of ground water to the standing water bodies such as lake, estuaries or lake is more challenging than the above interaction between ground water and stream/spring/seep. It is important to perform the water balance of standing water bodies by identifying various possible inlets and outlets of surface water (Becker, 2005). Remote sensing methods can be applied to quantify the spatial distribution of ground water discharge to the standing water bodies based on the thermal, chemical (chemistry or salinity) or vegetation signature. Ground water discharge is maximum near the shoreline/bank of lake or estuary and this will change the water temperature due to mixing. This thermal signature can be detected from the Airborne Thermal Infrared Multispectral Scanner (TIMS) images. This also helps to identify whether the discharge is focused or distributed in an area.

 

5.   Ground water and Land Surface

 

Surplus water after evaporation infiltrates the surface and recharges the ground water table. In this case movement of water is reverse while comparing with the discharge of ground water discussed in the previous section. Vegetation cover is also control the infiltration of surface water hence it regulate the ground water recharge (Becker, 2005). Growth, speciation and abundance of vegetation of a region is depend up on the availability of water and nutrients, atmospheric moisture content, salinity and acidity/alkalinity. Different plant species provides clue to the occurrence of ground water but the link between them varies considerably in different climatic regime. In the arid environment ground water discharge or shallow water table is the only source of water for vegetation whereas in the humid climate region it is more complex. Soil chemistry also plays a major role to support selective plant species, hence while considering the vegetation species assemblage to study the ground water condition, data on soil chemistry should be taken into consideration (Becker, 2005). Distribution, growth and type of plant species are used as indicator in the remote sensing and GIS method to determine the ground water conditions. However, it is difficult to estimate the change of ground water flow from vegetation cover due to its late response to the flow change. Some researchers (Batelaan et al., 1998) classified vegetation cover using principal component analysis to study the ground water discharge in a wetland in Belgium. They also estimated the flow rates and travel time using combined data of remote sensing and hydrochemistry in a GIS GRASS environment. Although based on type of vegetation indicator classifying interaction of ground water with the surface i.e. recharge/ discharge area, appears simple but in practice it is tricky.

 

Vegetation moisture flux is an important parameter for developing a model to study the hydrological cycle. Understanding different component of hydrological cycle is a key research area for remote sensing community for appropriate application of this technique (Becker, 2005). A Model has been developed to consider the contributions from soil, vegetation and atmosphere transfer (SVAT) of moisture. SVAT models are being used for shallow subsurface study but it does not have much application directly on ground water study. However SVAT model has been coupled with ground water flow finite-difference model (MODFLOW) for understanding ground water (Salvucci and Entekhabi, 1995). Generally the residence time of ground water is longer than the soil and atmospheric water, hence changes in the ground water condition is also in the longer time scale compare to other two. Shallow subsurface water or soil water is subjected to differential drying or evapotranspiration locally but in the larger scale it is more or less uniform.

 

Different models have been used in sole or combination to predict movement of ground water. Combination of water table dependent vadose zone model and MODFLOW was used to delineate recharge and discharge zone, and to predict movement of net soil water (Levine and Salvucci, 1999). Simplified atmospheric model coupled with MODFLOW used to determine long term interactions between ground water and atmosphere (York et al., 2002).

 

6.   Image interpretation for ground water study

 

Remotely sensed images depict the terrain and sometime provide valuable information about the subsurface geology. Hence interpretation of these images for extracting information about the ground water required expertise and background knowledge about the terrain. Information about surficial feature which control the recharge, groundwater out flow and configuration of subsurface geology are targeted during interpretations of images. Same geological formation may appear differently in the images due to local weathering condition, erosion or accumulation of sediment/debris (Meijerink et al. 2007). Sometime vegetation cover masks the outcrop. Hence field verifications are required. Image interpretations are generally gets validated using field work, geological map, geophysical and drill hole data.

 

While interpreting surface features for ground water studies various topographic evidences are being examined based on the hydrogeological properties of outcrop or any geological formation (Meijerink et al. 2007). Some of them are a) permeable conditions such as thick sand/colluvial deposits or non-eroded thick soils over dipping rock sequences, b) type of surface runoff, c) presence of lineaments and its association with vegetation, d) presence of water in rivulets, e) disappearance of base flow in the river bed indicating infiltration or loss to the rock formation/larger fractures and f) reappearance of water further downstream indicates an alluvial fan aquifer (Meijerink et al. 2007). Hydrological properties will be depended up on the climate, geology and geomorphology. For ground water study geomorphological interpretation is very important. For example, drainage density can be directly link with the permeability of the region as low drainage density indicates high permeable condition, but it is not always true. Many instance (sheet wash dominant area over pediments, crystalline basement rock) presence of impermeable rock also leads to development of low drainage density. Hence it is tricky to interpret the image.

 

Hydrological image interpretation of different geological terrain required basic understanding of geology of that region. Terrains consisting of unconsolidated sediment mostly the quaternary deposits have been extensively studied for ground water exploration, withdrawal and management. Preliminary investigation of this deposits are to know the geomorphological process (fluvial, aeolian, coastal, lacustrine or glacial) responsible for development of this deposits and type of materials (Meijerink et al. 2007). Generally this deposit conceals the complex sub-surface features which has no or very little surface expressions. Such areas are investigated by different remote sensing images like thermal, infrared images, soil moisture study in combination with other field and geophysical data.

 

6.1 Alluvial Fan

 

Alluvial fans are formed in the mountain front where river loss its carrying capacity of sediment due to abrupt change in the slope. Due to aggradation river shift its channel to the lower area. These deposits are mainly consisting of poorly sorted river bedload (fanglomerates) which is permeable and it gets recharged easily by mountain front runoff. Upper reach of the fan has coarser grain compare to middle and lower reach. Middle part shows more sorted river deposits and lower part mainly consist of finer sediments.

 

Alluvial fan is considered to be a well-defined flow system and also forms much of the conceptual groundwater model. Upper reach of the fan act as a recharge area and runoff from the small river in the mountain front provides pressure head for the flow system developed in the fan. In the alluvial fan water intake is in the permeable upper part shows phreatic conditions and in the middle part lateral groundwater flow is dominant (Meijerink et al. 2007). Due to the presence of finer sediments (clay and silt) phreatic conditions makes for a semi-confined condition in the lower part of the fan (Fig. 4). In the lower part of fan upward groundwater flow causes appearance of water in riverbed, seepage zones or even marshy areas. In semi-arid region groundwater mainly recharged by rain fall and the phreatic groundwater level is generally deep. The remote sensing image of the fan or fan complex is analyzed to extract information about groundwater, transmission loss and mountain front recharge by inspecting hydraulic geometry of the channels.

Figure 4: A section of alluvial fan schematically representing change of facies from the upper to the lower fan and the groundwater flow system. Arrows indicate groundwater flow. (Modified after Meijerink et al. 2007)

 

In the arid climate, where annual rainfall is <200mm, occasional rainfall is responsible for groundwater recharge. Figure 5 shows the alluvial fan developed in the arid region of Death Valley, USA where different alluvial fans have been formed with distinct provenance. Left side fan has good flow system and fed from the range with elevation of 3000 m and shows ephemeral seepage line. Whereas Right side fan has weak flow system and recharge is insufficient to maintain permanent outflow, hence shows phreatophyte vegetation and this fan is slightly dissected.

 

Figure 5: Alluvial fans in an arid region of Death Valley, USA with distinct difference between upper (U), middle (M) and lower (L) parts, but with different provenance. Fans on the left: minor seepage on lower parts, Fans on the right: middle part of the fan slightly dissected and has pheareophyte vegetation. F.P.: flood plains. (Source: Meijerink et al. 2007)

 

Another case study from Tibet (Fig. 6) shows large fan complex developed in the tectonic regime where outflows are perennial and mainly recharged by the snowmelt and occasional flash flow. Fans are highly permeable hence surface runoff infiltrates and groundwater leaves the fan through few springs. In the head of the fan few channels with dense vegetation are found and differential upliftment along the southern flank of the area is evident of dissected older fans.

Figure 6: a) Alluvial fans in subsidence basin. At E groundwater emerges. Landsat TM b5. Recharge by snowmelt runoff and flash floods is sufficient to cause perennial outflow. Note tilted dissected old-fans and mud flow deposits. Scale: E-W is 55.7 km. b) Enraged part of a zone with springs with dense vegetation along river course and irrigated area (dark tone) Landsat TMb3. (Source: Meijerink et al. 2007)

 

6.2 Volcanic terrain

 

Image interpretation of volcanic terrain for hydrogeological analysis is focused on the type of volcanic formations based on geomorphology, demarcating of groundwater recharge and outflow areas, presence of spring and large fractures (Meijerink et al. 2007). Remotely sensed images are used to prepare preliminary hydrogeological mapping based on the information extracted from the image about the possible groundwater occurrence, groundwater flow systems and recharge area. In the flood basalt terrain groundwater occurrences are associated with weathered basalt, vesicular basalt and fractures (lineaments).

 

6.3 Karst landforms

 

Karst landforms are indicative of underground channel system with groundwater; hence it is important to analyze the landform. Remote sensing images are used to identify the different features such as large sinkhole, recent collapse and geological structure etc. Sometime it is difficult to recognize small scale features such as solution landforms, dolines, pseudo-relief impression due to shadows (Meijerink et al. 2007). Stereo images are more suitable to map karst topography by visual interpretation. Groundwater study on karst landforms requires information about the local and regional geological structure and appropriate image interpretation. For hydrological study of karst terrain remote sensing images are interpreted for mapping surficial feature related to underground karst network, tracing the lineaments associated with cavern/fissure conduits, orientation of cavernous conduits along the structural features, determining bedding planes for two dimensional flow for cave development and possible zone (fracture/fault) for high permeability and concentrated ground water flow. This observation is also take support from geophysical survey and the ground verification.

 

6.4 Crystalline Terrain

 

The crystalline rock does not have the primary porosity/permeability, but secondary porosity/ permeability may developed in the regolith (weathered zone) above the crystalline rock or due to the presence of fracture. Occurrence of groundwater in the crystalline basement rock terrain is controlled by properties of weathered zone and fracture zone. The development of weather zone the control of ground water recharge is again control by the climate (Meijerink et al. 2007). Studies show that the fracture zone found under the regolith appears to be more liable for groundwater than regolith. Sometime fractures are filled with mineral/ clay or the density and inter-connectivity is less within the fracture. Hence this affects the porosity and permeability of the rock. The complex interplay of types of fracture, development of regolith, climate and denudation history of an area affects the groundwater conditions of the crystalline rock. Therefore groundwater occurrence is highly site-specific. However, remote sensing method proved to an important tool to explore groundwater in the crystalline basement terrain with the help of local geological data. In India, hydro-geomorphological approach has been widely used. Based on remote sensing method and ground survey different aquifer system developed in the diverse terrain of India has been demarcated (Fig.7).

 

Using remotely sensed image interpretations of the various terrains with their specific flow model, recharge and storage properties can be distinguished and lineaments can be traced out. However, hydrogeological assessment relies mostly on geological and geophysical survey and on analysis using experiential data from the existing wells.

Figure 7: Principle aquifer system of India. (Source: CGWB, 2012)

 

7.   Remote sensing and GIS in water pollution studies

 

For sustainable management and development of water resource the monitoring water quality and quantity is very essential (Sharma et al. 2015). Remote sensing and GIS techniques are used directly or indirectly for studying water quality and quantity with temporal changes mainly for the river, lake, snow/glacier or ground water resources. Concentrations of specific parameters and specific properties of water are being monitored using suitable sensors for assessment of water quality.

 

Emitted energy (reflectance) of surface water will change due to turbidity, presence of phytoplankton/algae, specific chemical constituents or dissolve organic matter, oil spill etc. (Sharma et al., 2015). Based on the emitted energy from the water surface, which is recorded by different sensor, water quality is monitored and the change in the energy is studied by the remote sensing tools. In India water quality of river, lake and pond etc. has been analyzed by many researchers using remote sensing tool. Suspended materials are common pollutant in the surface water. Different sensors carried by satellite, aircraft or aerial images are helpful for estimating this pollutant. Following empirical equation for quantifying presence of suspended material or other dissolved organic/chemical constituents in water are used.

 

R = X + YZ or R = XYZ

 

Where R= reflectance, Z= water quality parameter, X & Y = empirically derived factors (Sharma et al., 2015; Ritchie et al., 1974). This equation can be rewritten (Sharma et al., 2015; Schiebe et al., 1992) based on the physical relationship model between spectral and physical properties of surface water.

 

Ri= Si[1 – ex], where x = Cs/Pi

 

Here Ri = reflectance of surface water for specific wave band i, Cs = concentration of suspended sediments, Si = reflectance saturation level at high suspended sediment concentration for wave band i, Pi = concentration parameter, which is equal to the concentration for reflectance of 63% of saturation level in wave band i (Sharma et al. 2015). Similar to turbidity presence of chlorophyll will change the reflectance of surface water hence various algorithm and wavelength are used to monitor surface water bodies and eutrophication of in lake. Seasonal change of chlorophyll concentration can be estimated using following equation (applied for Chesapeake Bay by Harding et al. 1995):

 

Log10 [Chlorophyll] = x + y (-Log10Z), where Z = [(R2)2/ (R1R3)]

 

Here, x & y = empirical value derived from in situ measurement, R1= radiance at 460 nm, R2 = radiance at 490 nm, R3 = radiance at 520 nm (Sharma et al. 2015). Now various satellite sensors like IKONOS, OCTS (ocean color and temperature scanner), MOS (Modular optical scanners) are used for measuring chlorophyll in the surface water (Sharma et al. 2015).

 

Remote sensing and GIS techniques are also used for preparing map showing spatial variation of groundwater quality parameter such as arsenic, fluoride, chloride, TDS (total dissolve solid), TH (total hardness) nitrate, iron, SAR (Sodium absorption ratio) and bacterial contamination to identify affected area and for risk assessment. In addition to this salt water intrusion is another issue in the coastal areas. For this study groundwater samples are collected from predetermined area followed by chemical analysis and then maps for different chemical constituents are prepared. Generally these maps carry the water quality index based on different national/international standard (BIS- Bureau of Indian standard, WHO – world health organization) for domestic use or irrigation purpose (Sharma et al. 2015). The flow chart for application of remote sensing and GIS technique for water pollution study is illustrated in the figure 8.

 

Figure 8: Flow chart for application of remote sensing and GIS technique for water pollution study

 

8.   Conclusions

 

The first part of this module deals with the application of remote sensing and geographic information system (GIS) techniques for the groundwater studies and the second part (section 6) explains the application on water pollution studies. In the first part (Section 1 -5) is written for those who are interested in applying these techniques for groundwater studies, be it exploration, evaluation of resources, management or required data processing. Inadequate experience in image interpretation and lack of knowledge will hinder the appropriate uses of satellite images and aerial photographs. Here emphasis is given on the interpretation of aerial photograph and satellite images of diverse geological terrain having different climatic settings for extraction of information about groundwater. Map of the principle aquifer system of India is given in the last part of the section 5. At last, this module discusses about the determination of water pollution using remote sensing and GIS techniques.

 

9.   References

 

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