Alternate wetting and drying water management can reduce phosphorus availability under lowland rice cultivation irrespective of nitrogen level.

The limited availability of phosphorus (P) in the soil, which is affected by soil moisture, has a significant impact on crop production. However, we still do not fully understand how water management and nitrogen (N) addition affect the availability of P in paddy soil. An evaluation of the effects of two water management strategies that is continuous flooding (CF) and alternate wetting and drying (AWD) irrigation along with various nitrogenous fertilizer addition rates (equivalent to 0, 100%, 133%, and 166% recommended dose of N addition) on P availability in paddy soil took place over the course of a 2-year field experiment. The results showed that water management had a significant influence on ferrous iron, microbial biomass P, and soil-available P. However, the addition of N did not affect the availability of P in the soil. When N was added at various rates, AWD consistently reduced the amount of soil-available P compared to CF. This was primarily because AWD increased microbial biomass, which immobilized P and decreased the content of ferrous iron. As a result, the soil's ability to absorb P increased, leading to a decrease in the amount of P available. In conclusion, AWD decreases the amount of available P in paddy soil compared to CF.

Significant reduction of carbon stocks and changes of ecosystem service valuation of Indian Sundarban.

The Sundarban mangrove or tidal influenced natural ecosystem is extremely productive and providing multiple goods and services to millions of people. In the last few decades, the quality and quantity of mangrove ecosystem are being deteriorated. The main objectives of this current research are (i) to investigate the ecosystem service values (ESVs) using a time series satellite data (1975, 2000 and 2020) and different unit values (ii) to analyze the dynamic pattern of carbon sequestration through InVEST model and (iii) determination of ESVs change hotspots by Getis-Ord Gi* method. Here, mangrove forest has the highest ecosystem service value and highest carbon sinker. The total loss of ESVs was estimated 3310.79 million USD during last 45 years in Sundarban Biosphere Reserve (SBR) due to high natural and anthropogenic adversities. InVEST model also revealed that the total static carbon storage over the study area was 48.87, 46.65 and 43.33 Tg for the year 1975, 2000 and 2020 respectively. Total 6313944 mg/6.31Tg loss of carbon has been observed in the case of mangrove forest during the overall study period (1975-2020). So, illegal human encroachment should be strictly (through law and regulations) restricted within Sundarban mangrove ecosystem for the benefits of people.

Effects of COVID-19 lockdown and unlock on the health of tropical large river with associated human health risk.

River Damodar (India) is one of the most significant tropical large rivers and this river is carrying predominantly industrial effluents, urban sewage, and non-degradable chemical agricultural fertilizers. Several industries, cities, and townships directly depend on this important river throughout the year. It is highly essential to evaluate its surface water quality, characteristics, and improvement status during the COVID-19 lockdown and unlock phases. The major objectives of the present study are to analyse changing nature of heavy metals (Zn, Cd, Pb, Ni, Cr, and Fe) and microbial load (TVC, TC, and FC) of river water and to identify heavy metals impact on water quality and human health in pre, during, and after unlocking of COVID-19 lockdown. Here, a total of 33 water samples have been collected in the pre-lockdown, lockdown, and unlock phases. The results showed that decreasing trend of the microbial load was found in the lockdown phase. Heavy metal pollution index (HPI) illustrated that all samples are highly polluted (HPI > 150) during the pre-lockdown phase, while during the lockdown phase; HPI showed that around 54.54% of samples have been positively changed (low pollution level). During the unlock phase, 45.45% of samples were again amplified to the high pollution level. Pearson's correlation coefficient and hierarchical cluster analysis indicated strong relation among heavy metals with faecal coliform at a 0.05% level of significance. Noncarcinogenic hazard index (HI) shows the higher possibility of health risk (HI > 1) particularly for children in all the phases and during the lockdown phase, 36.36% of samples showed no possible health risk for adults (HI < 1). However, HI of dermal contact showed no possible health risk for children and adults in the assessment periods. This applied research can definitely assist planners and administrators in making effective solutions regarding public health.

Positive effects of COVID-19 lockdown on river water quality: evidence from River Damodar, India.

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.

Assessment of non-carcinogenic health risk of heavy metal pollution: evidences from coal mining region of eastern India.

Various developmental projects and economic actions such as mining, industries, urban expansion, and agricultural activities contribute toxic heavy metals into the soils and it adversely affects to human health and broadly the environment. For the scientific study (coal mining region of Eastern India) around 120 soil samples were collected from top (0 - 20 cm) and subsurface soil (20 - 50 cm) of coal mining, semi mining and non mining type of land use sites to assess ten heavy metals applying standard methods and indices for the assessment of pollution load and human health risk. Statistical analysis clearly indicated that Fe, Mn, Zr are the most dominantly distributed in the study region. Coefficient of variance (CV)showed that there was very less variation in the metal values among samples of any particular landuse site. Correlation coefficient (0.05% level of significance) depicts that metals were very strongly correlated with each other in every site of Neturia block. Igeo (Geo- accumulation index) values of Fe and As indicated moderate to low pollution in the topsoil of study area. It is because of their regional background value. Enrichment Factor (EF) also showed thatcontamination of Fe ismainly supplied by natural factors (EF < 2)i.e., weathering of parent rock in all over the study area. All other heavy metals indicated their anthropogenic sources (EF > 2)on top and subsurface soil both of three landuse site. Degree of contamination (Cdeg), modified degree of contamination (mCdeg), contamination factor (CF) and pollution load index (PLI) clearly suggest that topsoil of coal mining sites is most polluted than two other sites. Subsurface soil of mining sites also indicated comparatively higher pollution load than subsoil of semi mining or non mining sites. PLI values have been classified into four groups i.e., high pollution (> 6), medium pollution (6 -3), low pollution (3 - 1) and no pollution (< 1) zone. There was no PLI value < 1 in topsoil of the study area. But subsurface soil of non mining site indicated no pollution to the soil. Spatial mapping using Inverse Distance Weightage (IDW) on Arc GIS 10.4 software showed clear variation of metal concentration and pollution load to the top and subsoil of the study area. Human health risk of non - carcinogenic typeisdue to heavy metals intake of topsoil through three exposure pathwaywhich indicates the health risk of HI dermal> HI ingestion> HI inhalation for both the adult and children. Mean values of total HI showed that children are more prone to health risk in comparison with adult. There was no soil sample that exceeds its HI values > 1 for adults and thus no obvious health risk was found from soil heavy metals for adults.On the other hand, topsoil of mining sites indicated HI values >1;therefore, children are prone to health risk in this site. The present investigation suggests that coal mining region is highly polluted by their heavy metal burden on soil. Industrial and semi urban areas of semi mining region are also affected by heavy metal dust to its soil. Agricultural activities in non-mining region indicated lower pollution than other landuse sites. Remedial measures are highly needed to control heavy metal pollution of different landuse sites at colliery region to sustain environmental quality and human health as well. Modern scientific technologies and public awareness should be very useful on this way.

Eco-restoration of river water quality during COVID-19 lockdown in the industrial belt of eastern India.

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.

Cleaning the river Damodar (India): impact of COVID-19 lockdown on water quality and future rejuvenation strategies.

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 Na2+ > K+ > Ca2+ > Mg2+ and Cl- > So4 - > No3 - > 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.

Land use and land cover dynamics with special emphasis on shifting cultivation in Eastern Ghats Highlands of India using remote sensing data and GIS.

Continual, historical, and accurate information about the land use/land cover (LULC) changes of the earth's surface is extremely important for sustainable management of natural resources. In this study, historical topographic sheets, IRS P6 LISS-III, and LANDSAT TM images were used to provide recent and historical LULC conditions of the Eastern Ghats Highlands of east India. The supervised classification results were further improved by employing image enhancement and visual interpretation. Ratio Vegetation Index with fuzzy-based possibilistic c-means classification approach has improved the classification accuracy of the shifting cultivated area. Post-classification comparisons of the classified images indicated that the major change consisted of barren land and forestland changing into agricultural land and scrubland. Between 1931 and 2008, forest cover was decreased from 52.7% to 29.6% of total area. There was an increase in the scrub area from 874 (10.4%) to 1269 km2 (15.2%), and agricultural land from 978 (11.7%) to 2864 km2 (34.2%) during the same period. The rate of deforestation was found to be 0.65 km2 per year for reserve forest and 24.50 km2 per year for mixed forest. The shifting cultivated area in the district was 308.7 km2 during 2004, and that has been reduced since then and now is stabilized to 186.4 km2 area. Among this 186.4 km2 area, nearly half is covered by abandoned shifting cultivation. The decadal rate of decrease of shifting cultivated area is 0.15% per year. The shifting cultivated areas were mainly distributed at elevations 580-810 and 810-907 m and slopes 20-30 and 30-40%. Southeast and south facing slopes were preferred for shifting cultivation. Based on the identified causes of the change in shifting cultivation, policy recommendations for their better management were made.

Indicator and probability kriging methods for delineating Cu, Fe, and Mn contamination in groundwater of Najafgarh Block, Delhi, India.

Two non-parametric kriging methods such as indicator kriging and probability kriging were compared and used to estimate the probability of concentrations of Cu, Fe, and Mn higher than a threshold value in groundwater. In indicator kriging, experimental semivariogram values were fitted well in spherical model for Fe and Mn. Exponential model was found to be best for all the metals in probability kriging and for Cu in indicator kriging. The probability maps of all the metals exhibited an increasing risk of pollution over the entire study area. Probability kriging estimator incorporates the information about order relations which the indicator kriging does not, has improved the accuracy of estimating the probability of metal concentrations in groundwater being higher than a threshold value. Evaluation of these two spatial interpolation methods through mean error (ME), mean square error (MSE), kriged reduced mean error (KRME), and kriged reduced mean square error (KRMSE) showed 3.52% better performance of probability kriging over indicator kriging. The combined result of these two kriging method indicated that on an average 26.34%, 65.36%, and 99.55% area for Cu, Fe, and Mn, respectively, are coming under the risk zone with probability of exceedance from a cutoff value is 0.6 or more. The groundwater quality map pictorially represents groundwater zones as "desirable" or "undesirable" for drinking. Thus the geostatistical approach is very much helpful for the planners and decision makers to devise policy guidelines for efficient management of the groundwater resources so as to enhance groundwater recharge and minimize the pollution level.

Assessment of groundwater pollution in West Delhi, India using geostatistical approach.

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.

Statistical approaches for hydrogeochemical characterization of groundwater in West Delhi, India.

Parametric statistical approaches, correlations and multiple linear regressions were used to develop models for the interpretation of hydrogeochemical parameters in the Western part of Delhi state, India. The hydrogeochemical parameters indicated that the groundwater quality is not safe for consumption. The water is moderately saline and the salinity level is increasing over time. There is also the problem of nitrate pollution. The correlation between electrical conductivity (EC) and other water quality parameters except potassium (K(+)), nitrate (NO(3)(-)) and bicarbonate (HCO(3)(-)) is significantly positive and Ca(++)+ Mg(++)/Na(+)+ K(+) is significantly negative. In predicting EC, the multiple R(2) values of 0.996 and 0.985 indicate that 99.6% and 98.5% variability in the observed EC could be ascribed to the combined effect of Na(+), HCO(3)(-), Cl(-), SO(4)(--), NO(3)(-) and Ca(++)+ Mg(++) for the year of 2005 and 2006 respectively. Out of 99.6% of the variability in EC in 2005, 51.2% was due to Cl(-) alone, and 8.5%, 12.5%, 6.1%, 14.7% and 6.7% were due to Na(+), HCO(3)(-), SO(4)(--), NO(3)(-) and Ca(++) + Mg(++). Similarly in 2006, out of 98.5% of the variability in EC, 48.5% was due to Cl(-) alone, and 10.4%, 12.7%, 5.3%, 17.2% and 4.4% were due to Na(+), HCO(3)(-), SO(4)(--), NO(3)(-) and Ca(++)+ Mg(++). The analysis shows that a good correlation exists between EC, Cl(-) and SO(4)(--) either individually or in combination with other ions and the multiple regression models can predict EC at 5% level of significance.