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Is it true that rural areas, like urban areas, experience temperature changes over time? The aim of this mission was to find the season-wise trend associated with land surface thermal alteration based on satellite imagery from the last 30 years using the least square regression method, as well as to determine the stimulus of LST for the years 2027 and 2037 using Artificial Neural Network and Support Vector Machine techniques. The average temperature in the winter, summer, and Monsoon months has risen by 0.11 °C/year, 0.19 °C/year, and 0.07 °C/year, respectively, according to the analysis. Additionally, the simulated models reveal which extreme finish temperature group (>37.13 °C) may include more areas than the current one. For example, in 2017, a total area of 28.95 km2 was above the 37.13 °C temperature class, but this could increase to 37.91 km2 in 2027 and 42.67 km2 in 2037. Fragmentation analysis of the extreme temperature patches shows that the location of the high-temperature core steadily increases over time. The simulated water body, vegetation, built-up land, and bare land cover area show a decreasing trend in the first two parameters and an increasing trend in the last two, all of which influence temperature increase incident.
Susanta Mahato; Swades Pal. Land surface thermal alteration and pattern simulation based on influencing factors of rural landscape. Geocarto International 2021, 1 -29.
AMA StyleSusanta Mahato, Swades Pal. Land surface thermal alteration and pattern simulation based on influencing factors of rural landscape. Geocarto International. 2021; ():1-29.
Chicago/Turabian StyleSusanta Mahato; Swades Pal. 2021. "Land surface thermal alteration and pattern simulation based on influencing factors of rural landscape." Geocarto International , no. : 1-29.
Global temperature rises in response to accumulating greenhouse gases is a well-debated issue in the present time. Historical records show that greenhouse gases positively influence temperature. Lockdown incident has brought an opportunity to justify the relation between greenhouse gas centric air pollutants and climatic variables considering a concise period. The present work has intended to explore the trend of air quality parameters, and air quality induced risk state since pre to during the lockdown period in reference to India and justifies the influence of pollutant parameters on climatic variables. Results showed that after implementation of lockdown, about 70% area experienced air quality improvement during the lockdown. The hazardous area was reduced from 7.52% to 5.17%. The spatial association between air quality components and climatic variables were not found very strong in all the cases. Still, statistically, a significant relation was observed in the case of surface pressure and moisture. From this, it can be stated that pollutant components can control the climatic components. This study recommends that pollution source management could be a partially good step for bringing climatic resilience of a region.
Susanta Mahato; Swapan Talukdar; Swades Pal; Sandipta Debanshi. How far climatic parameters associated with air quality induced risk state (AQiRS) during COVID-19 persuaded lockdown in India. Environmental Pollution 2021, 280, 116975 .
AMA StyleSusanta Mahato, Swapan Talukdar, Swades Pal, Sandipta Debanshi. How far climatic parameters associated with air quality induced risk state (AQiRS) during COVID-19 persuaded lockdown in India. Environmental Pollution. 2021; 280 ():116975.
Chicago/Turabian StyleSusanta Mahato; Swapan Talukdar; Swades Pal; Sandipta Debanshi. 2021. "How far climatic parameters associated with air quality induced risk state (AQiRS) during COVID-19 persuaded lockdown in India." Environmental Pollution 280, no. : 116975.
Highly urbanized and industrialized Asansol Durgapur industrial belt of Eastern India is characterized by severe heat island effect and high pollution level leading to human discomfort and even health problems. However, COVID-19 persuaded lockdown emergency in India led to shut-down of the industries, traffic system, and day-to-day normal work and expectedly caused changes in air quality and weather. The present work intended to examine the impact of lockdown on air quality, land surface temperature (LST), and anthropogenic heat flux (AHF) of Asansol Durgapur industrial belt. Satellite images and daily data of the Central Pollution Control Board (CPCB) were used for analyzing the spatial scale and numerical change of air quality from pre to amid lockdown conditions in the study region. Results exhibited that, in consequence of lockdown, LST reduced by 4.02 °C, PM10 level decreased from 102 to 18 μg/m3 and AHF declined from 116 to 40W/m2 during lockdown period. Qualitative upgradation of air quality index (AQI) from poor to very poor state to moderate to satisfactory state was observed during lockdown period. To regulate air quality and climate change, many steps were taken at global and regional scales, but no fruitful outcome was received yet. Such lockdown (temporarily) is against economic growth, but it showed some healing effect of air quality standard.
Swades Pal; Priyanka Das; Indrajit Mandal; Rajesh Sarda; Susanta Mahato; Kim-Anh Nguyen; Yuei-An Liou; Swapan Talukdar; Sandipta Debanshi; Tamal Kanti Saha. Effects of lockdown due to COVID-19 outbreak on air quality and anthropogenic heat in an industrial belt of India. Journal of Cleaner Production 2021, 297, 126674 .
AMA StyleSwades Pal, Priyanka Das, Indrajit Mandal, Rajesh Sarda, Susanta Mahato, Kim-Anh Nguyen, Yuei-An Liou, Swapan Talukdar, Sandipta Debanshi, Tamal Kanti Saha. Effects of lockdown due to COVID-19 outbreak on air quality and anthropogenic heat in an industrial belt of India. Journal of Cleaner Production. 2021; 297 ():126674.
Chicago/Turabian StyleSwades Pal; Priyanka Das; Indrajit Mandal; Rajesh Sarda; Susanta Mahato; Kim-Anh Nguyen; Yuei-An Liou; Swapan Talukdar; Sandipta Debanshi; Tamal Kanti Saha. 2021. "Effects of lockdown due to COVID-19 outbreak on air quality and anthropogenic heat in an industrial belt of India." Journal of Cleaner Production 297, no. : 126674.
Recorded seasonal variation and uneven distribution of rainfall is one of the major issues to the agrarian society and the domestic water users today. For strategic planning of water use, scientific estimation of water balance in different spatio-temporal scale is necessary. For this, the present paper intends to investigate monthly and annual water balance state of Mayurakshi River basin (including 45 sub-basins) using precipitation (P), runoff (Q), evapotranspiration (ET) and recharge/soil moisture. P, Q, ET, respectively, vary from 1625.97 mm to 2037.93 mm, 182.19 mm to 1503.15 mm and 1050 mm to 1500 mm for the entire basin. The monthly pattern shows significant variation attributed to strong seasonality of P and temperature (T). Monsoon months recorded heavy maximum P, Q and actual ET and on the other hand, all these are very poor during pre-monsoon season. Groundwater recharge annually differs spatially, but annual average recharge is 307mmwith main contribution in monsoon months. Water deficit condition prevails in pre-monsoon season; strong groundwater lowering and drying of top soil are some explicit evidences of the same. This seasonal water scarcity withstands against multi-cropping strategies of the agrarian communities. To cope with this emerging situation, pressure on groundwater is mounting but it is the fact that this resource is also highly limited and precious. Quantification of monthly water balance and water deficit will be inputs to the strategy development for sustainable water resource management.
Swades Pal; Susanta Mahato; Biplab Giri; Deep Narayan Pandey; Pawan Kumar Joshi. Quantifying monthly water balance to estimate water deficit in Mayurakshi River basin of Eastern India. Environment, Development and Sustainability 2021, 1 -29.
AMA StyleSwades Pal, Susanta Mahato, Biplab Giri, Deep Narayan Pandey, Pawan Kumar Joshi. Quantifying monthly water balance to estimate water deficit in Mayurakshi River basin of Eastern India. Environment, Development and Sustainability. 2021; ():1-29.
Chicago/Turabian StyleSwades Pal; Susanta Mahato; Biplab Giri; Deep Narayan Pandey; Pawan Kumar Joshi. 2021. "Quantifying monthly water balance to estimate water deficit in Mayurakshi River basin of Eastern India." Environment, Development and Sustainability , no. : 1-29.
Although the impact of lockdown on Air Quality Index(AQI) was given enough attention but investigation on AQI during partial lockdown, change of the worst AQI hot spot pattern and its consistency, spatio-temporal dynamics of core-periphery divide of pollution over megacities were lacking. The present study explored the above mentioned issues along with monitoring of AQI of India during lockdown and partial lockdown based on the daily data of Central Pollution Control Board(CBCB). Gi-index, instability index, least squares regression and frequency approaches were used for analyzing AQI hot spot, spatial instability of AQI, trend of AQI and consistency of Pollution State Presence Frequency (PSPF). In result, clear improvement of AQI was observed since average AQI reduced from 110 in pre-lockdown to 73 in lockdown I and 93 in partial lockdown. The average AQI of the mega cities was improved up to 55%–75% in lockdown. However during partial lockdown, with restoration of economic activities the air quality was observed to degrade again. AQI hotspot and PSPF were identified high in and around Delhi and industrial hubs. Positive trend of AQI change, instability of AQI were found gradually high in partial lockdown period and these effects was observed greater in urban and industrial belts. Though all these facts signify anthropogenic activities as a major source of air pollution but shutting down economic activities lockdown couldn’t be a permanent solution to combat it. Hence, prioritizing green energy sources, improve technologies, utilize energy sustainably that could reduce the pollution level.
Priyanka Das; Indrajit Mandal; Sandipta Debanshi; Susanta Mahato; Swapan Talukdar; Biplab Giri; Swades Pal. Short term unwinding lockdown effects on air pollution. Journal of Cleaner Production 2021, 296, 126514 .
AMA StylePriyanka Das, Indrajit Mandal, Sandipta Debanshi, Susanta Mahato, Swapan Talukdar, Biplab Giri, Swades Pal. Short term unwinding lockdown effects on air pollution. Journal of Cleaner Production. 2021; 296 ():126514.
Chicago/Turabian StylePriyanka Das; Indrajit Mandal; Sandipta Debanshi; Susanta Mahato; Swapan Talukdar; Biplab Giri; Swades Pal. 2021. "Short term unwinding lockdown effects on air pollution." Journal of Cleaner Production 296, no. : 126514.
Damming over the river remarkably alters the downstream hydrological and ecological state of the river and riparian wetlands. Considering this, the present work intended to explore the habitat quality and the trophic state index (TSI) of the wetland in Tangan river basin of India and Bangladesh. The spatial linkages between habitat quality and TSI was also assessed. Random forest (RF), Radial basis function neural network (RBF) and Artificial neural network (ANN) algorithms based habitat vulnerability models were constructed based on eight proxy data layers, which are mainly related to hydrology. The ANN and RBF models were found as the best representative. In the pre-dam period, about 30% area was under high and very high habitat vulnerability, while it was increased to 54% after damming. TSI value in the post-dam period was found significantly higher (44–54) in comparison to pre-dam phase (18–22). It was also identified that vulnerable habitat areas were more susceptible to poorer water quality. Hence, in water quality and ecosystem related data sparse conditions, the proxy parameters can be used effectively for habitat vulnerability modelling. Furthermore, results clearly demonstrated that damming has deteriorated the habitability and trophic state of the wetland. To restrain the growing impact, ecological flow maintenance to the dam downstream river and riparian wetland is essential.
Swapan Talukdar; Swades Pal; Anamika Chakraborty; Susanta Mahato. Damming effects on trophic and habitat state of riparian wetlands and their spatial relationship. Ecological Indicators 2020, 118, 106757 .
AMA StyleSwapan Talukdar, Swades Pal, Anamika Chakraborty, Susanta Mahato. Damming effects on trophic and habitat state of riparian wetlands and their spatial relationship. Ecological Indicators. 2020; 118 ():106757.
Chicago/Turabian StyleSwapan Talukdar; Swades Pal; Anamika Chakraborty; Susanta Mahato. 2020. "Damming effects on trophic and habitat state of riparian wetlands and their spatial relationship." Ecological Indicators 118, no. : 106757.
Air pollution has happened to be one of the mounting alarms to be concerned with in many Indian cities. COVID-19 epidemic endow with a unique opportunity to report the degree of air quality improvement due to the nationwide lockdown in 10 most polluted cities across the country. National Air Quality Index (NAQI) based on continuous monitoring records of seven criteria pollutants (i.e. common air pollutants with known health impacts e.g. PM10, PM2.5, CO, NO2, SO2, NH3 and O3) for a total of 59 stations across the cities, satellite image derived Aerosol Optical Depth (AOD) and few statistical tools are employed to derive the outcomes. NAQI results convey that 8 cities out of the 10 air quality restored to good to satisfactory category during the lockdown period. Within week+1 of the lockdown period, PM10 and PM2.5 concentrations have suppressed below the permissible limit in all cities. CO and NO2 have reduced to about −30% and −57% respectively during the lockdown period. Diurnal concentrations of PM10 and PM2.5 have dropped drastically on the very 4th day of lockdown and become consistent with minor hourly vacillation. In April 2020 the AOD amount was reduced to about 36% and 18% in contrast to April 2018 and April 2019 respectively. This add-on reporting of the possible recovery extent in air quality may help to guide alternative policy intervention in form of short term lockdown so as to testify whether this type of unconventional policy decisions may be put forward to attain a green environment. Because, despite numerous restoration plans, air pollution levels have risen unabated in these cities. However, detailed inventory needs to be focused on identifying the localized pollution hotspots (i.e. source contribution).
Susanta Mahato; Krishna Gopal Ghosh. Short-term exposure to ambient air quality of the most polluted Indian cities due to lockdown amid SARS-CoV-2. Environmental Research 2020, 188, 109835 -109835.
AMA StyleSusanta Mahato, Krishna Gopal Ghosh. Short-term exposure to ambient air quality of the most polluted Indian cities due to lockdown amid SARS-CoV-2. Environmental Research. 2020; 188 ():109835-109835.
Chicago/Turabian StyleSusanta Mahato; Krishna Gopal Ghosh. 2020. "Short-term exposure to ambient air quality of the most polluted Indian cities due to lockdown amid SARS-CoV-2." Environmental Research 188, no. : 109835-109835.
Amid the COVID-19 pandemic, a nationwide lockdown is imposed in India initially for three weeks from 24th March to 14th April 2020 and extended up to 3rd May 2020. Due to the forced restrictions, pollution level in cities across the country drastically slowed down just within few days which magnetize discussions regarding lockdown to be the effectual alternative measures to be implemented for controlling air pollution. The present article eventually worked on this direction to look upon the air quality scenario amidst the lockdown period scientifically with special reference to the megacity Delhi. With the aid of air quality data of seven pollutant parameters (PM10, PM2.5, SO2, NO2, CO, O3 and NH3) for 34 monitoring stations spread over the megacity we have employed National Air Quality Index (NAQI) to show the spatial pattern of air quality in pre and during-lockdown phases. The results demonstrated that during lockdown air quality is significantly improved. Among the selected pollutants, concentrations of PM10 and PM2.5 have witnessed maximum reduction (>50%) in compare to the pre-lockdown phase. In compare to the last year (i.e. 2019) during the said time period the reduction of PM10 and PM2.5 is as high as about 60% and 39% respectively. Among other pollutants, NO2 (−52.68%) and CO (−30.35%) level have also reduced during-lockdown phase. About 40% to 50% improvement in air quality is identified just after four days of commencing lockdown. About 54%, 49%, 43%, 37% and 31% reduction in NAQI have been observed in Central, Eastern, Southern, Western and Northern parts of the megacity. Overall, the study is thought to be a useful supplement to the regulatory bodies since it showed the pollution source control can attenuate the air quality. Temporary such source control in a suitable time interval may heal the environment.
Susanta Mahato; Swades Pal; Krishna Gopal Ghosh. Effect of lockdown amid COVID-19 pandemic on air quality of the megacity Delhi, India. Science of The Total Environment 2020, 730, 139086 -139086.
AMA StyleSusanta Mahato, Swades Pal, Krishna Gopal Ghosh. Effect of lockdown amid COVID-19 pandemic on air quality of the megacity Delhi, India. Science of The Total Environment. 2020; 730 ():139086-139086.
Chicago/Turabian StyleSusanta Mahato; Swades Pal; Krishna Gopal Ghosh. 2020. "Effect of lockdown amid COVID-19 pandemic on air quality of the megacity Delhi, India." Science of The Total Environment 730, no. : 139086-139086.
Rapid and uncontrolled population growth along with economic and industrial development, especially in developing countries during the late twentieth and early twenty-first centuries, have increased the rate of land-use/land-cover (LULC) change many times. Since quantitative assessment of changes in LULC is one of the most efficient means to understand and manage the land transformation, there is a need to examine the accuracy of different algorithms for LULC mapping in order to identify the best classifier for further applications of earth observations. In this article, six machine-learning algorithms, namely random forest (RF), support vector machine (SVM), artificial neural network (ANN), fuzzy adaptive resonance theory-supervised predictive mapping (Fuzzy ARTMAP), spectral angle mapper (SAM) and Mahalanobis distance (MD) were examined. Accuracy assessment was performed by using Kappa coefficient, receiver operational curve (RoC), index-based validation and root mean square error (RMSE). Results of Kappa coefficient show that all the classifiers have a similar accuracy level with minor variation, but the RF algorithm has the highest accuracy of 0.89 and the MD algorithm (parametric classifier) has the least accuracy of 0.82. In addition, the index-based LULC and visual cross-validation show that the RF algorithm (correlations between RF and normalised differentiation water index, normalised differentiation vegetation index and normalised differentiation built-up index are 0.96, 0.99 and 1, respectively, at 0.05 level of significance) has the highest accuracy level in comparison to the other classifiers adopted. Findings from the literature also proved that ANN and RF algorithms are the best LULC classifiers, although a non-parametric classifier like SAM (Kappa coefficient 0.84; area under curve (AUC) 0.85) has a better and consistent accuracy level than the other machine-learning algorithms. Finally, this review concludes that the RF algorithm is the best machine-learning LULC classifier, among the six examined algorithms although it is necessary to further test the RF algorithm in different morphoclimatic conditions in the future.
Swapan Talukdar; Pankaj Singha; Susanta Mahato; Shahfahad; Swades Pal; Yuei-An Liou; Atiqur Rahman. Land-Use Land-Cover Classification by Machine Learning Classifiers for Satellite Observations—A Review. Remote Sensing 2020, 12, 1135 .
AMA StyleSwapan Talukdar, Pankaj Singha, Susanta Mahato, Shahfahad, Swades Pal, Yuei-An Liou, Atiqur Rahman. Land-Use Land-Cover Classification by Machine Learning Classifiers for Satellite Observations—A Review. Remote Sensing. 2020; 12 (7):1135.
Chicago/Turabian StyleSwapan Talukdar; Pankaj Singha; Susanta Mahato; Shahfahad; Swades Pal; Yuei-An Liou; Atiqur Rahman. 2020. "Land-Use Land-Cover Classification by Machine Learning Classifiers for Satellite Observations—A Review." Remote Sensing 12, no. 7: 1135.
Groundwater crisis across the world is a thought-provoking issue and for resolving the problem, it is highly necessary to identify the potential groundwater zones and estimate water yield. The present work intends to identify potential groundwater zone based on ensemble modeling assembling advance machine learning algorithm like Random Forest (RF), Radial Basis Function (RBFnn) and Artificial Neural Network (ANN) and set theories like union and intersection based modeling using 15proxyconditioning parameters for developing sustainable water resource management plan. The work is based on Tangon river basin of Barind tract of Eastern Indian and Bangladesh, suffers from water scarcity. Groundwater potentiality models have identified 34.93–35.67% area to total basin area (2388.88 km2) at the proximity of lower reach of the main river as very high to highly potential for groundwater. Among the employed parameters elevation, slope, land use/land cover, distance from perennial segment of stream are identified as the dominant in this case. For assessing the accuracy level of the models, Receiver operating characteristics (RoC), proximity test and aquifer breadth data are used. Both the ensemble models and set theory centric models show very good to excellent performances suitably identifying groundwater potentiality. However, the performance level of ensemble modeling is more satisfactory. As the groundwater potentiality zones of the study area are well delimitated, this study may be useful for adopting a suitable water resource management plan.
Swades Pal; Sonali Kundu; Susanta Mahato. Groundwater potential zones for sustainable management plans in a river basin of India and Bangladesh. Journal of Cleaner Production 2020, 257, 120311 .
AMA StyleSwades Pal, Sonali Kundu, Susanta Mahato. Groundwater potential zones for sustainable management plans in a river basin of India and Bangladesh. Journal of Cleaner Production. 2020; 257 ():120311.
Chicago/Turabian StyleSwades Pal; Sonali Kundu; Susanta Mahato. 2020. "Groundwater potential zones for sustainable management plans in a river basin of India and Bangladesh." Journal of Cleaner Production 257, no. : 120311.
The ecosystems provide a range of material as well as non-material services that contribute to human well-being as well as supply necessary resources for the organisms. The land use/ land cover (LU/LC) changes have been taken place due to several natural and anthropogenic reasons, which significantly influence the ecosystem services. Therefore, the present study aimed to explore the minor variations of ecosystem services provided by the particular land use types of the study area. Therefore, we have divided the study area into nine grids. The land use land cover classifications have been performed using support vector machine techniques (SVM) for 1999–2019. Based on the multi-temporal land use land cover maps, we have used the global coefficient value of 1997 and 2003 for valuation of ecosystem services for different land use types. Then we have employed elasticity techniques to analyse the response of land use land cover changes over the ecosystem service valuation. The findings showed that the overall built-up area has increased by 29.14% since 1999, while the overall water-body has decreased by 15.81%. Therefore, the ecosystem services provided by water-body have been decreased correspondingly and the 29.14% areas that converted to built-up area from others land use types do not able to provide any ecosystem services and the ecosystem service values become nil, which is not suitable for good health ecosystem. Therefore, the study can be the foundation to the planners and scientists to prepare sustainable plans for the management of local ecosystem based on minorly study on the impact of LULC changes on the ecosystem services.
Swapan Talukdar; Pankaj Singha; Shahfahad; Susanta Mahato; Bushra Praveen; Atiqur Rahman. Dynamics of ecosystem services (ESs) in response to land use land cover (LU/LC) changes in the lower Gangetic plain of India. Ecological Indicators 2020, 112, 106121 .
AMA StyleSwapan Talukdar, Pankaj Singha, Shahfahad, Susanta Mahato, Bushra Praveen, Atiqur Rahman. Dynamics of ecosystem services (ESs) in response to land use land cover (LU/LC) changes in the lower Gangetic plain of India. Ecological Indicators. 2020; 112 ():106121.
Chicago/Turabian StyleSwapan Talukdar; Pankaj Singha; Shahfahad; Susanta Mahato; Bushra Praveen; Atiqur Rahman. 2020. "Dynamics of ecosystem services (ESs) in response to land use land cover (LU/LC) changes in the lower Gangetic plain of India." Ecological Indicators 112, no. : 106121.
The magnitude and causes of changes in the land surface temperature of rural areas have not been extensively studied. The thermal band of Landsat imagery is taken to extract winter, summer, and monsoon season land surface temperature (LST) and relate it to surface parameters over a 30-year period. From the extracted parameters constructed a prospective surface temperature (PST) model using Multivariate Adaptive Regression Splines. The Chandrabhaga river basin in West Bengal of the lateritic Rarh Tract at the Chota Nagpur Plateau fringe was chosen as the study area because it is far from urban influences, to avoid the well-known heat island effect. Over the study period, summer and winter average LST increased linearly by 0.085°C/y and 0.016°C/y respectively. These results were validated with air temperature (RMSE= x and y, respectively). Over time more of the area is in the higher temperature zones, e.g., in April 2011, 4% area exceeded >32°, whereas in 2015 this proportion reached 52%. PST models of all the seasons were moderate to highly correlate (0.57 to 0.87) with actual LST, showing the value of this model. It also revealed the relative importance of the regional factors. Based on this information factor management is a scientific step to restrict or minimize the temperature rise effect.
Susanta Mahato; Swades Pal. Influence of land surface parameters on the spatio-seasonal land surface temperature regime in rural West Bengal, India. Advances in Space Research 2018, 63, 172 -189.
AMA StyleSusanta Mahato, Swades Pal. Influence of land surface parameters on the spatio-seasonal land surface temperature regime in rural West Bengal, India. Advances in Space Research. 2018; 63 (1):172-189.
Chicago/Turabian StyleSusanta Mahato; Swades Pal. 2018. "Influence of land surface parameters on the spatio-seasonal land surface temperature regime in rural West Bengal, India." Advances in Space Research 63, no. 1: 172-189.
Targeting groundwater in the river basin like Chandrabhaga with seasonal drought is a very urgent task especially for mitigating irrigation demand during the non-monsoon period. This paper delineated suitable groundwater potential zones based on the analytical hierarchy process (AHP), modified AHP, PCA-based weight and knowledge-based weight of multiple input parameters. For providing more certainty of the target zones in the derived models, union and intersection of all models were performed. A GIS-based multi-criteria approach using 13 relevant parameters has been adopted in this work. From the first four models, it is found that very suitable areas vary from 7.5 to 11% of the total basin area. The union and intersection models of the four individual models, respectively, delineated 13.91% and 3.69% suitable areas. Among the six models, the average yield of groundwater (5.96 L/s) is maximum in case of the intersection model, which is, therefore, more reliable than others. In case of the union model, the suitable area has 0.2 L/s less average yield than the intersection model. Therefore, for the harvesting more water, very good potential area delineated in the intersection model can be targeted. All these models will nevertheless help decision-makers to judge whether the existing groundwater harvesting structures are located properly or whether reorientation is needed.
Susanta Mahato; Swades Pal. Groundwater Potential Mapping in a Rural River Basin by Union (OR) and Intersection (AND) of Four Multi-criteria Decision-Making Models. Natural Resources Research 2018, 28, 523 -545.
AMA StyleSusanta Mahato, Swades Pal. Groundwater Potential Mapping in a Rural River Basin by Union (OR) and Intersection (AND) of Four Multi-criteria Decision-Making Models. Natural Resources Research. 2018; 28 (2):523-545.
Chicago/Turabian StyleSusanta Mahato; Swades Pal. 2018. "Groundwater Potential Mapping in a Rural River Basin by Union (OR) and Intersection (AND) of Four Multi-criteria Decision-Making Models." Natural Resources Research 28, no. 2: 523-545.
The rise of temperature and heat island effect is frequently found in the urban areas and this effect is also clearly exhibited when work on image-based land surface temperature (LST) Modeling in different phases is carried out in Chandrabhaga river basin of Chottanagpur plateau fringe within the rural background. The average rise of LST in last 25 years is about 3.5 °C with strong seasonality. Extension of agriculture land, built up area, change of building materials, fragmentation of water bodies, deforestation, seasonal crop practice emerge as major reasons behind such rising temperature. Temperature differs almost 3 °C over different the LULC units in each season. Relatively lower temperature is registered in water bodies and vegetation but these areas have also been experienced by 1.5 °C temperature rise in last 25 years. This rate is high in case of built-up areas. The intensity of built up area is positively and strongly correlated with LST (r = 0.46 to 0.91). Newly grown areas are highly susceptible to temperature change. Increasing vegetation canopy density decreases LST but the nature of influence is gradually declined over advancing of time (r-value in April is reduced from −0.86 to −0.25).
Susanta Mahato; Swades Pal. Changing land surface temperature of a rural Rarh tract river basin of India. Remote Sensing Applications: Society and Environment 2018, 10, 209 -223.
AMA StyleSusanta Mahato, Swades Pal. Changing land surface temperature of a rural Rarh tract river basin of India. Remote Sensing Applications: Society and Environment. 2018; 10 ():209-223.
Chicago/Turabian StyleSusanta Mahato; Swades Pal. 2018. "Changing land surface temperature of a rural Rarh tract river basin of India." Remote Sensing Applications: Society and Environment 10, no. : 209-223.
The present article intends to capture the impact of fly ash generated from Bakreswar Thermal Power Plant (BKTPP) on Chandrabhaga River of proximate location. Impacts have been captured giving emphasis on the morphological aspects of the channel and water quality standard. Chandrabhaga River (length: 26 km) of Birbhum district covers a mostly Rarh tract composed of coarse grain laterite soil. Field measurement of morphological parameters, water and soil samples collection from nine river sites and testing in laboratory reveal the following results: (1) In very proximate location of the fly ash pond, the river bed has raised up to 10–75 cm and the rate of aggradations declined downstream; (2) textural characteristics of bed materials have altered and become finer after huge influxing of fly ash; (3) leaching of finer fly ash particles in the pore space of the sand bed and consequent clogging has started which withstand the interaction between surface and subsurface flow; (4) suspended and dissolved load has increased by 62 % in comparison with the load before over spilling of fly ash from fly ash pond; (5) due to overloaded condition, more than 12,000 m3/year of fly ash is deposited over the river bed and it can defer the graded time of that river; (6) an analysis of physico-chemical properties of the collected water samples states that some of the parameters, e.g., turbidity, TDS, BOD, COD and DO, are not only beyond drinking standard but also beyond the standard of irrigation and aquatic life, specifically fishes; (7) fly ash contamination highly reduced carp fishes on which a troop of fishermen spend their livelihood and they are now in anxiety for the viability of their livelihood.
Swades Pal; Susanta Mahato; Samrat Sarkar. Impact of fly ash on channel morphology and ambient water quality of Chandrabhaga River of Eastern India. Environmental Earth Sciences 2016, 75, 1268 .
AMA StyleSwades Pal, Susanta Mahato, Samrat Sarkar. Impact of fly ash on channel morphology and ambient water quality of Chandrabhaga River of Eastern India. Environmental Earth Sciences. 2016; 75 (18):1268.
Chicago/Turabian StyleSwades Pal; Susanta Mahato; Samrat Sarkar. 2016. "Impact of fly ash on channel morphology and ambient water quality of Chandrabhaga River of Eastern India." Environmental Earth Sciences 75, no. 18: 1268.