Andhra Pradesh the "Rice Bowl of India" is present in the south-eastern part of the Precambrian Shield of India. Andhra Pradesh is traversed by three major, many medium and minor rivers making it  a "Riverine" state. It is drained by the Godavari, Krishna and Penna rivers majorly which flow into the Bay of Bengal and few areas by Vamsadhara and Nagavali originating in the Eastern Ghats. Geology of Andhra Pradesh ranges from the oldest Archaean group of rocks to recent alluvium. State depicts the spatial variation of Rainfall. Both southwest monsoon and northeast monsoon bring rainfall in the state. Southwest monsoon extends from June - September accounting for two- thirds of the annual rainfall whereas northeast extends from October - November accounting for the remaining one-third of the annual rainfall. Normal rainfall is 966.0 mm.

Rajasthan also known as 'Rajputana'(Land of the kings) is situated in the northwest part of the country. Because 61% of the area is desert or semi-desert and is called India's desert. Rajasthan lies between latitudes 23°03'-30°12' N and longitudes 69°29'- 78°17'E. Rajasthan is characterized by a highly varied and complex geological sequence of rocks ranging from Archaean Bhilwara Supergroup to sub-recent alluvium as well as windblown sand. The Climate of Rajasthan varies with temperature and rainfall between West and East of Aravallis. The western part of Aravallis viz., Rajasthan Desert plains have extremely high range of temperatures in India compared to the eastern part of Aravallis. This peculiar characteristic of climate between east and west of Aravallis is termed the 'Climatic Divide'. Rajasthan’s rainfall is highly erratic and it varies as high as 50 to 70%. Rajasthan receives the lowest Rainfall in India. The Average Rainfall is 52.26 cm. Rajasthan gets two seasons of rainfall one in the months of July-Sept holding 75% -90% and the other in the months of December-Feburary holding 10% of Rainfall.

Telangana is strategically situated in the Deccan plateau of peninsular India. Telangana state was formed on June 2nd 2014 by the bifurcation of former Andhra Pradesh State and became the 29th state of India with Hyderabad city as its capital. It falls in the geographical coordinates of 15°46'N lat to 19°47'N  lat and 77°16'E long to 81°43'E long. Telangana is segregated into two parts by Telangana Plateau and Golconda Plateau occupying the major portions in the North and South. Geologically Telangana is characterized by rock formations belonging to Archean to Quaternary age. Telangana falls in a semi-arid zone.  South-west monsoon brings 80% of the annual rainfall and retreating monsoon accounts for 13% rainfall in Telangana. The average rainfall is 906.6 mm. The rainfall is uneven ranging 900-1500 mm in Northern 

The average annual rainfall in Andhra Pradesh varies between 558 m to 1200 m, depending on the region. Most districts in the north-eastern (Figure 2) coastline region receive high rainfall, whereas southern districts near Telangana receive comparatively less. The coefficient of variation, on the other hand, is relatively high in southern regions and continues to decrease as one moves north-eastern in the state. This variation in rainfall has an impact on groundwater depth across the state, which may be shown on a map (Figure 3). Districts with substantial yearly rainfall fall into the group of districts with very shallow groundwater depths. Districts with minimal annual rainfall, on the other hand, reveal that the depth is extremely high in most part of the district.

The average annual rainfall in Telangana varies between 650 m to 1200 m, depending on the region. Districts in the north and north-eastern (Figure 4) region receive high rainfall, whereas southern districts near receive comparatively less rainfall hence coming under the first category. The coefficient of variation, on the other hand, is relatively high in southern districts and continues to decrease as one moves north-eastern in the state. This variation in rainfall has an impact on groundwater depth across the state, which may be shown on a map (Figure 5). Districts with substantial yearly rainfall fall into the group of districts with very shallow groundwater depths. Districts with minimal annual rainfall, on the other hand, reveal that the depth is extremely high in most parts of the district.

The average annual rainfall in Rajasthan varies between 200 m to 1000 m, depending on the region. Districts in the south and south-eastern (Figure 6) region receive high rainfall, whereas western districts near receive comparatively less rainfall hence coming under the first category. The coefficient of variation, on the other hand, is relatively high in northern districts and continues to decrease as one moves south-eastern and western part of the state. This variation in rainfall has an impact on groundwater depth across the state, which may be shown on a map (Figure 6). Districts with substantial yearly rainfall fall into the group of districts with very shallow groundwater depths. Districts with minimal annual rainfall, on the other hand, reveal that the depth is extremely high in most parts of the district.

The above table (Table 1) obtained through a linear regression test in SPSS. It provides the basic characteristics of the model viz. level of groundwater depth as a dependent variable whereas mean annual rainfall as independent variable. The model summary table is as under.

The R-value represents the correlation between maximum groundwater depth, and amount of rainfall received; the value is greater than 0.4 or 40%, which is considered for further analysis; and the value is.664 or 66.4 percent(Table 2), which is very good for model fit. Because the R-squared value is larger than 0.4, the total variance explained by the variables is greater than 0.4, indicating that the model is successful and accurate enough to describe the water usage, which is 0.440 or 44.0 percent. The reduced R-square informs us how common the discoveries are.

The adjusted R-square indicates the generalisation of the results, or the variation in the sample results. It is essential to have a minimum difference between R-square and Adjusted R-square, and the same number is.390 or 39.0 percent, which is a little difference, therefore it is good. As a result, the model summary table is a great place to start.

In order to conduct this analysis, the P-value and 95% confidence level for this table were determined in advance. As a result, a p-value of less than 0.05 is considered statistically significant. As a result, the impact is significant. As a result, the findings are extremely important. Similarly, the F ratio is a measure of how well a model predicts a given variable after taking into account the model's inaccuracies. An efficient model can be created with a F ratio of 8.659, which is larger than 1. It explains the appropriateness of sample for carrying out the test. There is a chance to reject the null hypothesis that there is a significant difference in groundwater depth and rainfall received, based on these results because the ANOVA's p-value is below the tolerable significance level. There is a strong correlation between annual rainfall and groundwater depth (Table 3).

The estimated (predictors) of the independent variables and the dependent variable were shown to be related in this study. The anticipated value increases or decreases by the same percentage for each unit change in parameter estimates. The use of effect size and parameter estimates in univariate analysis of variance, which is also used in cross-sectional approaches, is still an option. Regression parameters like R square and adjusted R square value (0.440 and 0.390) are identical to those in the previous approach, which is fixed effects dummy variable (t values, significant levels), but the regression value of the dummy variable is different because it is coexisting with different dummy coexistence. This is shown in the tables above. As a result of this study, it is clear that depth of ground water and mean annual rainfall has a strong correlation with the factors examined (Table 4).   

The composite water index score is 68 out of 100 in Andhra Pradesh and 48 and 50 in Rajasthan and Telangana respectively the score of the Telangana is 50 (Figure 8)

Figure 8

Source: Based on NITI Aayog report on Composite Water Management Index June 2018

The linear regression analysis shows a high level of variation in the rainfall in three selected sample states, witnessing the change in climate since the last few decades. The diminishing trend of ground water level in three sample states reflects the criticality of ground water resource availability for near future.   Analysis of climate change and ground water both depends upon temporal variation of one to three decades. Study reveals that there is an increase in the source of surface water augmentation because of development of conservation techniques at all level. But the level of groundwater is declining in Rajasthan during last few decades that shows the impact of climate change on the state. Although the trend analysis of ground and surface water restoration has increased in Andhra Pradesh and Telangana compared to the base year but it is not sufficient as per the demand of water in respective states. Besides that the demographic increase in India is putting enormous pressure on the use of groundwater as it is not possible to cater the requirement of potable water during the non-monsoon season in the selected sample states. Majority of the population in respective states, still depends upon agricultural and other primary sectors. Paddy crops are the dominant crops and groundwater availability is an essential requirement in absence of surface water availability during the non-monsoon season. The study concludes that irregularity in rainfall is resulting in less percolation of water into the surface affecting the level of groundwater in all three states, as validated through the map of rainfall and groundwater depth. The impact of precipitation variability is affecting not only the socio-economic condition but also questioning the sustainability of groundwater resources in the region. Although, effort of water holders are praiseworthy in conserving the available surface and rainwater but it still requires to be implemented at macro level to bring a homogeneous development of rural and urban regions. There is considerable gap between the infrastructure created and service available at the household. Strengthening of mega projects through international collaborations for better sustainability of projects, the operations and maintenance of projects and capacity development programs, such as Asian Development Bank (ADB) and United Nation’s development funds for developing countries will strengthen the water resource development.