Keywords

Introduction

Groundwater is preferred source for drinking and irrigation purposes in rural as well as urban areas in India. Increasing population and their dependence on groundwater cause heavy stress on groundwater resources, leading to decline of groundwater levels (Chopra and Krishan 2014; MacDonald et al. 2013; Rodell et al. 2009). To prepare a sustainable management strategy for groundwater development, it is important to understand the fluctuation of groundwater levels (GWL) with reference to natural or artificial recharge and abstraction of groundwater in space and time domain. The spatial and temporal variations in the GWL were investigated by many researchers. Finke et al. (2004) and Ahmadi and Sedghamiz (2007) used kriging for mapping of groundwater level to identify critical area.

Geostatistical methods are good tools for water resource management and can be effectively used to derive the long-term trends of the groundwater (Raghunath et al. 2005). Statistical methods for trend analysis vary from simple linear regression to more advanced parametric and nonparametric methods (Helsel and Hirsch 2002). Many researchers (Arora et al. 2005; Dash et al. 2007) investigated rainfall and temperature trend analysis, but few studies have been done for GWL trend analysis. Few researchers (Shamsudduha et al. 2009; Hossein and Shifteh 2011) attempted to study trend analysis using statistical methods for analysing groundwater levels. Hossein and Shifteh (2011) investigated the temporal trends in annual, seasonal and monthly groundwater levels using Mann–Kendall test and the Sen’s slope estimator. Shamsudduha et al. (2009) studied recent trends in groundwater levels in highly seasonal hydrological system of Ganges–Brahmaputra–Meghna Delta of Bangladesh using nonparametric techniques. In the present study, spatio-temporal variations of groundwater level in Raipur city, Chhattisgarh, have been analysed. The monthly trend analyses using Mann–Kendall (MK) and Sen’s slope test have also been ascertained. The study will provide useful input to the engineers and water resource planners for development and management of groundwater resources.

Study Area

The study area (Fig. 1) comprised of Raipur city, the capital city of Chhattisgarh, along with its outgrowths lies between 21° 10′ and 21° 21′N latitudes and 81° 32′ to 81° 44′E longitudes and falls under Survey of India toposheets number 64G/11 and 64G/12. The present population of Raipur city is about 1,200,000. Water supply requirement of the city is mainly met from Kharun River—a tributary of Mahanadi River. Approximately 65% of the city’s drinking water supply is met from Kharun River, and the rest is supplied from groundwater resources developed through hand pumps and tube wells. In general, Raipur area features semi-arid tropical climate having hot long summer from March to mid-June followed by rainy season of about four months from mid-June to September. The winter season commences from December and continues till end of February. The annual rainfall varies from 831 to 1719 mm with average rainfall of 1207 mm (Saph 2013).

Fig. 1
figure 1

Study area (Raipur city) with observation wells in and around the city

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Data and Methodology

Monthly GWL of 30 observation wells (dug well) during the period of five years (2010–2014) of Raipur urban area collected from CGWB, Raipur, has been used for the analyses. Spatial and temporal variations have been analysed for observation wells to predict groundwater flow direction and fluctuations in the respective wells. The groundwater levels are available at the depth below ground surface; therefore, by collecting the RL of the respective well locations, these data were converted to groundwater level above msl and then georeferenced with respect to their latitude and longitude. Trend analysis, using MK test and Sen’s slope, has been performed for each wells based on monthly data. The MK test is one of the most commonly used nonparametric method, most of the literature significantly contains this approach for trend analysis. Magnitude of trend has been quantified by Theil–Sen’s estimator, and positive and negative values of magnitude showed increasing and decreasing trend, respectively. The minimum and maximum GWL observed in dug wells during five years period has been presented in Table 1. Dug wells are shallow-depth wells, and groundwater levels indicate the level of phreatic aquifer.

Table 1 Dug well identification and coordinates with minimum and maximum GWL
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Results and Discussion

The minimum depth to water (0.84 m bgl) has been observed in July 2010 at Kota, whereas maximum value (16.61 m bgl) observed in May 2012 at Tatibandh, based on five years GWL monthly data. The pre- and post-monsoon groundwater contours maps (Fig. 2a, b) depict the spatial variation of average groundwater level. The average groundwater level in pre-monsoon (month—May) varies from 1.74 to 13.80 m bgl (i.e. 279.92 m to 282.54 m amsl), whereas during post-monsoon (month-November) groundwater level varies from 1.05 to 6.75 m bgl. GWL is shallower in central part of the city, whereas deeper GWL can be observed in western and northern part of the city. Groundwater flow direction in the area helps us decide the location of abstraction wells and pollutant transport path. The directions of the groundwater flow are found similar for the pre- and post-monsoon periods (Fig. 3). The direction of groundwater flow is towards north and west.

Fig. 2
figure 2

DTW contour map for a pre-monsoon b post-monsoon

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Fig. 3
figure 3

GW flow direction during a pre-monsoon b post-monsoon

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Trend analysis was performed using Mann–Kendall test (at 5% significant level) and Sen’s slope estimator method for monthly groundwater level. The summarised results of trend analysis have been presented in Table 2. The negative S-statistics indicate a falling trend and vice versa. The computed Z-statistics less than the z-value corresponding to 5% significance level (1.96) indicate no significant trend. It can be observed from Table 2 that groundwater level is showing falling and rising trend, which are not significant except few locations. There are few locations viz. Telibandha, Shankar Nagar, Gogaon, where groundwater level shows significant rising trend, whereas Math Purena showing significant falling trend.

Table 2 Summarised results of trend analyses for each observation wells
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Magnitudes of above trends are calculated using Sen’s slope estimator method and have been presented in Table 2. A positive slope gives rising trend and vice versa. It is noticed that the trend pattern is same as detected using Mann–Kendall analysis.

The time series plot of GWL with linear trend for the locations showing significant rising or falling trend has been shown in Fig. 4. The rising trend of some wells maybe due to recharge from water bodies and less or no abstraction of groundwater from phreatic aquifer.

Fig. 4
figure 4

Time series plot for depth to water for a Telibandha area showing rising trend b Gogaon area showing rising trend c Shankar Nagar showing rising trend d Math Purena showing falling trend

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Conclusions

The present study has been carried out to study the spatio-temporal variation and trend analysis of groundwater level in the Raipur city, Chhattisgarh. For the study, monthly groundwater level of 30 observation wells (dug well) for the period of five years (2010–2014) have been used. The minimum depth to water (0.84 m bgl) has been observed in July 2010 at Kota, whereas maximum value (16.61 m bgl) observed in May 2012 at Tatibandh. The average groundwater level in pre-monsoon varies from 1.74 to 13.80 m bgl, whereas during post-monsoon it varies from 1.05 to 6.75 m bgl. The shallower GWL has been observed in central part of the city. The direction of groundwater flow is towards north and west. The trend analysis is carried out using the Mann–Kendall analysis and Sen’s slope estimator method. It may be concluded that no significant trend is detected at 5% significance level except four locations. Locations showing significant rising trend are Telibandha, Shankar Nagar, Gogaon, whereas Math Purena shows significant falling trend.