Globally, it is established that the partial lockdown system assists to improve the health of the total environment due to inadequate anthropogenic actions in different economic sectors. The ample research on fitness of environment has been proved that the strict imposition of lockdown was the blessings of environment. The river Damodar has historical significance and lifeline for huge population of Jharkhand and West Bengal state of India but in the recent years the water quality has been deteriorated due to untreated industrial effluents and urban sewage. The main objective of this study is to examine the water quality of river Damodar during and prelockdown phase for domestic use and restoration of river ecosystem. A total of eleven (11) effluent discharge sites were selected in prelockdown and during lockdown phase. A new approach of water quality assessment, i.e., water pollution index (WPI) has been applied in this study. WPI is weightage free, unbiased method to analysis of water quality. The result shows that the physical, chemical and heavy elements were found beyond the standard limit in prelockdown period. The cation and anion were arranged in an order of Na 2+ > K + > Ca 2+ > Mg 2+ and Cl − > So 4 − > No 3 − > F − in both the sessions. WPI of prelockdown showed that about 100% water samples are of highly polluted. WPI of lockdown period showed that around 90.90% samples improved to 'good quality' and 9.10% of samples are of 'moderately polluted.' Hypothesis testing by 't' test proved that there was a significant difference (ρ = 0.05%) in values of each parameter between two periods. Null hypothesis was rejected and indicated the improvement of river water quality statistically. Spatial mapping using Arc GIS 10.4 interpolation (IDW) helps to understand spatial intensity of pollution load in two periods. This research study should be helpful for further management and spatial diagnosis of water resource of river Damodar.

The sudden lockdown recovers the health of the total environment particularly air and water while the country's economic growth and socio-cultural tempo of people have been completely hampered due to the COVID-19 pandemic. Most of the industries within the catchment area of river Damodar have been closed; as a result, significant changes have been reflected throughout the stretch of river Damodar. The main objective of the study is to analyze the impact of lockdown on the water quality of river Damodar. A total of 55 samples was collected from eleven different confluence sites of nallas with the main river channel during and pre-lockdown period. The relevant methods like WQI, TSI, Pearson's correlation coefficient, and "t" test have been applied to evaluate the physical, chemical, and biological status of river water. The result of "t" test indicated that there are significant differences (α = 0.05) of each parameter between pre and during lockdown. Water quality index (WQI) is used for analysis of drinking water quality suitability followed by BIS. The values of WQI showed "very poor" (S1, S2, S3, S6, S7, and S11) to "unfit for drinking" (S4, S5, S8, S9, and S10) of river water during pre-monsoon season. The nutrient enrichment status of the river was analyzed by Trophic State Index (TSI) method and it shows the "High" eutrophic condition with a heavy concentration of algal blooms in almost an entire stretch. During lockdown, nutrient supplies like TN and TP have been reduced and is designated as "Low" (S1, S2) to "Moderate" (S3 to S11) eutrophic condition of middle stretch of Damodar. This research output of river Damodar will definitely assist to policy makers for sustainable environmental management despite the dilemma between development and conservation.

The exploration, exploitation, and unscientific management of groundwater resources in the National Capital Territory (NCT) of Delhi, India have posed a serious threat of reduction in quantity and deterioration of quality. The objective of the study is to determine the groundwater quality and to assess the risk of groundwater pollution at Najafgarh, NCT of Delhi. The groundwater quality parameters were analyzed from the existing wells of the Najafgarh and the thematic maps were generated using geostatistical concepts. Ordinary kriging and indicator kriging methods were used as geostatistical approach for preparation of thematic maps of the groundwater quality parameters such as bicarbonate, calcium, chloride, electrical conductivity (EC), magnesium, nitrate, sodium, and sulphate with concentrations equal or greater than their respective groundwater pollution cutoff value. Experimental semivariogram values were fitted well in spherical model for the water quality parameters, such as bicarbonate, chloride, EC, magnesium, sodium, and sulphate and in exponential model for calcium and nitrate. The thematic maps of all the groundwater quality parameters exhibited an increasing trend of pollution from the northern and western part of the study area towards the southern and eastern part. The concentration was highest at the southernmost part of the study area but it could not reflect correctly the groundwater pollution status. The indicator kriging method is useful to assess the risk of groundwater pollution by giving the conditional probability of concentrations of different chemical parameters exceeding their cutoff values. Thus, risk assessment of groundwater pollution is useful for proper management of groundwater resources and minimizing the pollution threat.

Most of the data pertaining to Indian soils are limited to the major soil separates, sand, silt, and clay. We examined the possibilities of using these parameters to describe the hydraulic characteristics of the soils of India. The final or steady-state infiltration rate, which is mainly profile-controlled, showed a power function relationship with the maximum and the average clay content in the soil profile. The saturated hydraulic conductivity also showed a similar relationship with the silt + clay content. The soil water content at a given suction could be satisfactorily predicted using the percentage of major soil separates, sand, silt, and clay. The coefficients in the soil water function ψ(θ) were linearly related to the sand content. Non-linear regression equations were developed to predict these coefficients using the percentages of sand and clay in soils. The equations proved to be quite satisfactory for a wide range of textures and provided reasonably accurate estimates of the soil water characteristic curve from a minimum of readily available data.

Accurate and reliable interpolation of groundwater depth over a region is a pre-requisite for efficient planning and management of water resources. The performance of two deterministic, such as inverse distance weighting (IDW) and radial basis function (RBF) and two stochastic, i.e., ordinary kriging (OK) and universal kriging (UK) interpolation methods was compared to predict spatio-temporal variation of groundwater depth. Pre-and postmonsoon groundwater level data for the year 2006 from 110 different locations over Delhi were used. Analyses revealed that OK and UK methods outperformed the IDW method, and UK performed better than OK. RBF also performed better than IDW and OK. IDW and RBF methods slightly underestimated and both the kriging methods slightly overestimated the prediction of water table depth. OK, RBF and UK yielded 27.52, 27.66 and 51.11 % lower RMSE, 27.49, 35.34 and 51.28 % lower MRE, and 14.21, 16.12 and 21.36 % higher R 2 over IDW. The isodepth-area curves indicated the possibility of exploitation of groundwater up to a depth of 20 m.

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The global economic activities were completely stopped during COVID-19 lockdown and continuous lockdown partially brought some positive effects for the health of the total environment. The multiple industries, cities, towns and rural people are completely depending on large tropical river Damodar (India) but in the last few decades the quality of the river water is being significantly deteriorated. The present study attempts to investigate the river water quality (RWQ) particularly for pre- lockdown, lockdown and unlock period. We considered 20 variables per sample of RWQ data and it was analyzed using novel Modified Water Quality Index (MWQI), Trophic State Index (TSI), Heavy Metal Index (HMI) and Potential Ecological Risk Index (RI). Principal component analysis (PCA) and Pearson’s correlation (r) analysis are applied to determine the influencing variables and relationship among the river pollutants. The results show that during lockdown 54.54% samples were brought significantly positive changes applying MWQI. During lockdown, HMI ranged from 33.96 to 117.33 with 27.27% good water quality which shows the low ecological risk of aquatic ecosystem due to low mixing of toxic metals in the river water. Lockdown effects brought river water to oligotrophic/meso-eutrophic condition from eutrophic/hyper-eutrophic stage. Rejuvenation of river health during lockdown offers ample scope to policymakers, administrators and environmentalists for restoration of river health from huge anthropogenic stress.

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