SPATIO-TEMPORAL ASSESSMENT OF GROUNDWATER USING GEOSPATIAL TOOLS

Abstract

Groundwater is an important source of water supply throughout the World, but it becomes contaminated and its level is likely being declined day by day due to mismanagement of this resources. The decreasing water table and groundwater contaminations found to be are critical problems in a Loni and Morahi watersheds of UP State, India. To overcome this problem spatio-temporal analysis has been carried out with the help of Remote Sensing (RS) and Geographical Information System (GIS). Groundwater flow modeling was carried out and finally, a web enabled geoportal using open source GIS technology was created. The spatial and non-spatial (attribute data) database was created and designed in GIS environment using ArcGIS 9.3 and ERDAS Imagine 9.3 software. Spatial database contained different thematic maps that were represented in a vector format; RS images, field data and Global Positioning System (GPS) measurements were represented in ArcGIS compatible format. For physical implementation of the spatial database, a layer based approach was used. For its physical implementation, a relational structure was used and different relational tables were created within ArcGIS domain. To demonstrate the reliability of the developed database for a spatial decision-making as well as to extract some information to be needed for further studies, geographical data processing, in particular construction of DEM from the topographic maps entered into the GIS. The generated database was efficiently used for derivation of results and their analysis. In this study, groundwater potential zones map is delineated using RS, GIS and Multi Criteria Decision Making Technique (MCDM) techniques. Groundwater potential map is categorized into five zones, viz., 'very poor', 'poor', 'good', 'very good' and 'excellent'. The area falling in excellent category is about 150.93 km2 (7.06% of the total study area), that lies along Ganga river. However, the area having very poor category is about 372.03 km2 (17.42% of the total study area) which lies along Loni river, rest of the area falling poor, good and very good category is about 815.39, 594, 202.94 km2, respectively. Results have been validated using yield data of wells and found to be satisfactory. The developed groundwater potential zones map will be helpful to the decision makers in identifying suitable locations for drilling production wells and/or monitoring wells as well as in protecting the vital groundwater resources. The study also reveals that remotely sensed data and GIS based approach is more appropriate and effective than the conventional methods for evaluation of drainage iii morphometric parameters and their influence on landforms, soils and eroded land characteristics at sub-watershed level. Interpretation of multi-spectral satellite sensor data was of great help in analysis of drainage parameters and morphometric characteristics which could be used for accurate delineation of distinct geological and landform units. The results of morphometric analysis show that sub-watershed LSW6 is prone to relatively high erosion and soil loss. Hence, suitable control measures are urgently required in this sub-watershed to preserve the land from further degradation. Rainfall-runoff modeling was carried out in GIS environment where major inputs were derived from topographic maps, satellite images and field data. Fairly accurate classification of Land Use/Land Cover (LULC) types from satellite images helped in computing the Curve Number (CN) values distributed over the sub-watershed required for Soil Conservation Service curve number (SCS-CN) model. In this study, 22 suitable locations for artificial recharge sites were identified. During field visit, 4 sites were verified that match with the identified location using remote sensing and GIS technique. RS and GIS was found to be an effective tool for integrating hydrological, LULC and morphometric parameters as per user defined criteria to identify suitable artificial recharge sites. The study assesses the necessity of having a suitable type of water harvesting structure in each sub-watershed. It not only indicates the suitability of the structures, but also helps whether a particular sub-watershed requires treatment or not, in terms of water harvesting structures. On the basis of groundwater recharge modeling using GEC guidelines (MOWR, 2011); it was found that Sikandarpur Karan and Sareni blocks fall in critical category while the offer blocks have significantly decline in groundwater level. On the basis of Mann Kendall’s trend test and linear regression analysis, it was found that most of the wells have declining trend in pre- and post-monsoon season, and As per the results in pre-monsoon season, 58% wells showed falling trends which can be due to high pumpage of water and less recharge, while about 5% wells showed rising trends, most of which are located near pond and canal. In post-monsoon season, 63% wells showed falling trends and about 7% wells showed rising trends. However, 61% wells showed falling trends and 6% showed rising trend in both the pre- and post-monsoon seasons. These results provide useful information for groundwater analyses required to ensure sustainable groundwater development. For protecting groundwater from further depletion, the groundwater development needs to be taken up in a planned manner in order to prevent adverse impact on groundwater. The artificial recharge can be implemented to avoid the declining trend in groundwater levels. Water-logging iv and soil salinity problems, resulting from gradual rise of groundwater levels, are observed in study area. This is due to the surface water irrigation without environmental considerations. So, there is also a need to adopt conjunctive water use strategy in the areas experiencing water logging problem. The steady state calibration of the model shows a close agreement between the simulated and observed heads with the residual mean of -0.32 m, variance 1.27 m and correlation coefficient 0.975. In transient state calibration, the model shows a close agreement between simulated and observed heads with the residual mean of 0.01 m, variance 2.36 m and correlation coefficient 0.953. The calibrated and validated statistics for different time steps of RMS error has been found in the range of 1.24 m to 1.63 m throughout the calibration period, which is in acceptable range. Residual mean has been found to lie within -0.49 m and 0.49 m, absolute residual mean within a range of 0.9 m to 1.25 m throughout the calibration period. On the basis of calibration and validation of the model by observing the calibrated aquifer parameters, hydraulic conductivity was found to lie between 15.4 and 93.1 m/day in the area, and specific yield is in the range of 0.002 to 0.12 in different zones of area. Hydraulic conductivity, storage parameters (specific yield) and recharge were selected as the most uncertain parameters. On the basis of sensitivity analysis, it was found that recharge and hydraulic conductivity are most sensitive parameter as compared to specific yield, as indicated by the relative mobility in the mean errors between the mean error corresponding to calibrated values and errors. The RMS error has increased by 1.6 times with a decrease in hydraulic conductivity by 80%, whereas it has increased by 1.1 times with an increase in hydraulic conductivity by 80%. For recharge, the model is more sensitive as compared to hydraulic conductivity. RMS error has increased by 4.1 times with a decrease in recharge by 80%, whereas it has increased by 3.7 times with an increase in recharge by 80%. In case of specific yield, small change is observed as compared to recharge and hydraulic conductivity. The modified DRASTIC model DRASIC-LU has been used to investigate the groundwater vulnerable zones in study area. It uses six DRASTIC parameters and land use as an extra parameter in a GIS environment. The normalized DRASTIC index varied between 0.21 and 0.96, which was divided on the basis of histogram into four classes; low, moderate, high and very high, considering as the higher the index, the greater the relative pollution potential. It indicates that 13.44% area is categorized as very high vulnerable zone, while 32.56% and 19.95% of the areas are categorized as moderate and high vulnerable, respectively. Similarly, 34.05% of the total area is classified as low vulnerable zone. The result is validated using measured nitrate and fluoride data of 40 different locations collected from UP Jal Nigam, v Unnao. All the tested samples were overlaid on the groundwater vulnerability map using GIS in order to study the number of wells with high concentration of nitrate and fluoride is found within different vulnerable zones. Nevertheless, it was found that majority of sampled sources which violated BIS, 2011 limit value of nitrate and fluoride are located in high to very high vulnerable zones. A relationship between nitrate and groundwater depth was established, and found that concentration of nitrate was higher in shallow water table as compared to deeper water table. This confirms that model results are satisfactory. Groundwater quality index has been categorized into five classes namely; excellent, very good, good, poor and unfit for drinking. It was found that the area falling in excellent groundwater quality is about 240.6 km2 (11.2% of the total study area), which covers central portion of Bighapur block and Eastern south part of study area, that lies in Sumerpur and Khiron block. However the area unfit for drinking is about 117 km2 (5.46% of the total study area), which falls in western part of Sikandarpur block, and it is nearby the Unnao city and industrial area of Unnao district. Groundwater quality map for irrigation purpose has been categorized into four classes namely: excellent, good, permissible and doubtful. It was found that most of the area (about 99%) is suitable for irrigation except few area (about 1%) in Bichhiya block are in doubtful range. The web GIS based application using open source technology has been developed and demonstrated the groundwater resources. This tool provides a complete GIS solution in web browser environment. The advantage of web technology has also been derived i.e. through internet it can be used simultaneously by a large number of users as the knowledge of basic software is not necessary to handle web GIS based module. The software to develop Web GIS module are also available free of cost which is a great advantage in a developing country, like India