Browsing by Author "Singh, Suraj Kumar"

Now showing 1 - 19 of 19

Assessing Sustainable Ecotourism Opportunities in Western Rajasthan, India, through Advanced Geospatial Technologies
(Multidisciplinary Digital Publishing Institute (MDPI), 2023-07-25T00:00:00) Chandel, Rajeev Singh; Kanga, Shruti; Singh, Suraj Kumar; �urin, Bojan; Or�uli?, Olga Bjelotomi?; Dogan?i?, Dragana; Hunt, Julian David
The present study focuses on finding potential sites for ecotourism development using GIS and remote-sensing-based weightage sum overlay techniques in Western Rajasthan, India. Ecotourism is one of the fastest growing and revenue-making sectors incorporating a sustainable future. Western Rajasthan has a broad scope to develop tourism-based activity in various ways, mainly through cultural heritage, historical and archaeological wonders, and rare wildlife. Weightage sum overlay analysis is a useful and simple tool to compare each thematic layer. These values are based on various factors and understanding taken during the study. For this purpose, different data types have been taken from the USGS website. Arc GIS 10.8 and ERDAS Imagine software 2015 have been utilized to process the data. This research incorporates seven thematic layers, i.e., elevation, proximity to streams, land use/cover, population density, road connectivity, proximity to protected areas, and heritage hotspots. Based on the physical and cultural characteristics of Western Rajasthan, the weightage of each thematic layer has been decided, which is finally overlaid using Arc GIS software. After processing all the thematic layers, we finally get an outcome in the form of a suitability map. The final suitability map represents five suitability classes that divide the total area into the following categories, very high (37.31%), high (26.85%), moderate (7.89%), low (0.83%), and very low (27.12%), which represents the potential of ecotourism in Western Rajasthan. � 2023 by the authors.
Assessing the Effects of Drought on Rice Yields in the Mekong Delta
(MDPI, 2023-01-04T00:00:00) Lavane, Kim; Kumar, Pankaj; Meraj, Gowhar; Han, Tran Gia; Ngan, Luong Hong Boi; Lien, Bui Thi Bich; Van Ty, Tran; Thanh, Nguyen Truong; Downes, Nigel K.; Nam, Nguyen Dinh Giang; Minh, Huynh Vuong Thu; Singh, Suraj Kumar; Kanga, Shruti
In contrast to other natural disasters, droughts may develop gradually and last for extended periods of time. The World Meteorological Organization advises using the Standardized Precipitation Index (SPI) for the early identification of drought and understanding of its characteristics over various geographical areas. In this study, we use long-term rainfall data from 14 rain gauge stations in the Vietnamese Mekong Delta (1979�2020) to examine correlations with changes in rice yields. Results indicate that in the winter�spring rice cropping season in both 2016 and 2017, yields declined, corresponding with high humidity levels. Excessive rainfall during these years may have contributed to waterlogging, which in turn adversely affected yields. The results highlight that not only drought, but also humidity has the potential to adversely affect rice yield. � 2023 by the authors.
Assessing the Impact of the 2004 Indian Ocean Tsunami on South Andaman�s Coastal Shoreline: A Geospatial Analysis of Erosion and Accretion Patterns
(MDPI, 2023-05-28T00:00:00) Singh, Saurabh; Singh, Suraj Kumar; Prajapat, Deepak Kumar; Pandey, Vikas; Kanga, Shruti; Kumar, Pankaj; Meraj, Gowhar
The 2004 Indian Ocean earthquake and tsunami significantly impacted the coastal shoreline of the Andaman and Nicobar Islands, causing widespread destruction of infrastructure and ecological damage. This study aims to analyze the short- and long-term shoreline changes in South Andaman, focusing on 2004�2005 (pre- and post-tsunami) and 1990�2023 (to assess periodic changes). Using remote sensing techniques and geospatial tools such as the Digital Shoreline Analysis System (DSAS), shoreline change rates were calculated in four zones, revealing the extent of the tsunami�s impact. During the pre- and post-tsunami periods, the maximum coastal erosion rate was ?410.55 m/year, while the maximum accretion was 359.07 m/year in zone A, the island�s east side. For the 1990�2023 period, the most significant coastal shoreline erosion rate was also recorded in zone A, which was recorded at ?2.3 m/year. After analyzing the result, it can be seen that the tsunami severely affected the island�s east side. To validate the coastal shoreline measurements, the root mean square error (RMSE) of Landsat-7 and Google Earth was 18.53 m, enabling comparisons of the accuracy of different models on the same dataset. The results demonstrate the extensive impact of the 2004 Indian Ocean Tsunami on South Andaman�s coastal shoreline and the value of analyzing shoreline changes to understand the short- and long-term consequences of such events on coastal ecosystems. This information can inform conservation efforts, management strategies, and disaster response plans to mitigate future damage and allocate resources more efficiently. By better understanding the impact of tsunamis on coastal shorelines, emergency responders, government agencies, and conservationists can develop more effective strategies to protect these fragile ecosystems and the communities that rely on them. � 2023 by the authors.
Assessment of Ground Water Quality of Lucknow City under GIS Framework Using Water Quality Index (WQI)
(Multidisciplinary Digital Publishing Institute (MDPI), 2023-08-28T00:00:00) Saqib, Nazmu; Rai, Praveen Kumar; Kanga, Shruti; Kumar, Deepak; ?urin, Bojan; Singh, Suraj Kumar
Continuous groundwater quality monitoring is crucial for ensuring safe drinking and irrigation by mitigating risks from geochemical contaminants through appropriate treatment methods. Therefore, the primary objective of this study was to assess the suitability of groundwater collected from Lucknow, India, for both drinking and irrigation. Forty samples were collected from different sites within the study area to evaluate groundwater quality. Various parameters such as pH, turbidity, total dissolved solids (TDS), chlorides ((Formula presented.)), total alkalinity, total hardness, sulphate ((Formula presented.)), nitrate ((Formula presented.)), fluorides ((Formula presented.)), iron (Fe), arsenic (As), magnesium ((Formula presented.)), and calcium ((Formula presented.)) were analyzed. The weighted arithmetic water quality index (WAWQI), a vital rating system representing overall water quality, was employed to classify the water into different categories, such as very good, good, moderate, poor, and unfit for drinking. This classification is invaluable for public awareness and decision-making to make informed decisions regarding effective management, treatment, and sustainable societal development on a broader scale. A correlation matrix was generated and analyzed to observe correlations between the various parameters. Additionally, spatial distribution maps for the analyzed parameters and WQI were prepared using the inverse distance weighted (IDW) method. The study found that WQI values in the area ranged from 2.64 to 168.68, indicating good water quality in most places except for the Kukrail region, where the water quality is unfit for drinking purposes. The water quality map shows that 86% of the area falls under the very good category, 14.63% under good to moderate quality, and 0.37% is categorized as unfit for drinking. Consequently, the findings suggest that the groundwater in the studied area is safe and suitable for drinking and irrigation purposes. � 2023 by the authors.
Cellular Automata-Based Artificial Neural Network Model for Assessing Past, Present, and Future Land Use/Land Cover Dynamics
(MDPI, 2022-11-08T00:00:00) Sajan, Bhartendu; Mishra, Varun Narayan; Kanga, Shruti; Meraj, Gowhar; Singh, Suraj Kumar; Kumar, Pankaj
Land use and land cover change (LULCC) is among the most apparent natural landscape processes impacted by anthropogenic activities, particularly in fast-growing regions. In India, at present, due to the impacts of anthropogenic climate change, supplemented by the fast pace of developmental activities, the areas providing the highest agricultural yields are facing the threat of either extinction or change in land use. This study assesses the LULCC in the fastest-changing landscape region of the Indian state of Bihar, District Muzaffarpur. This district is known for its litchi cultivation, which, over the last few years, has been observed to be increasing in acreage at the behest of a decrease in natural vegetation. In this study, we aim to assess the past, present and future changes in LULC of the Muzaffarpur district using support vector classification and CA-ANN (cellular automata-artificial neural network) algorithms. For assessing the present and past LULC of the study area, we used Landsat Satellite data for 1990, 2000, 2010, and 2020. It was observed that between 1990 and 2020, the area under vegetation, wetlands, water body, and fallow land decreased by 44.28%, 34.82%, 25.56%, and 5.63%, respectively. At the same time, the area under built-up, litchi plantation, and cropland increased by 1451.30%, 181.91%, and 5.66%, respectively. Extensive ground truthing was carried out to assess the accuracy of the LULC for 2020, whereas historical google earth images were used for 1990, 2000, and 2010, through the use of overall accuracy and kappa coefficient indices. The kappa coefficients for the final LULC for the years 1990, 2000, 2010, and 2020 were 0.79, 0.75, 0.87, and 0.85, respectively. For forecasting the future LULC, first, the LULC of 1990 and 2010 were used to predict the landscape for 2020 using the CA-ANN model. After calibrating and validating the CA-ANN outputs, LULC for 2030 and 2050 were generated. The generated future LULC scenarios were validated using kappa index statistics by comparing the forecast outcomes with the original LULC data for 2020. It was observed that in both 2030 and 2050, built-up and vegetation would be the major transitioning LULC. In 2030 and 2050, built-up will increase by 13.15% and 108.69%, respectively, compared to its area in 2020; whereas vegetation is expected to decrease by 14.30% in 2030 and 32.84% in 2050 compared to its area in 2020. Overall, this study depicted a decline in the natural landscape and a sudden increase in the built-up and cash-crop area. If such trends continue, the future scenario of LULC will also demonstrate the same pattern. This study will help formulate better land use management policy in the study area, and the overall state of Bihar, which is considered to be the poorest state of India and the most vulnerable to natural calamities. It also demonstrates the ability of the CA-ANN model to forecast future events and comprehend spatiotemporal LULC dynamics. � 2022 by the authors.
Correlation Between Volumetric Loading Rate and Removal Efficiency of Bio-chemical Oxygen Demand and Chemical Oxygen Demand for Waste Water Treatment by Improved Bio-tower Technology in Ganga River Basin (India)
(Springer International Publishing, 2023-05-19T00:00:00) Singh, Ankit; Singh, Anju; Karwariya, Sateesh; Pandey, Govind; Kanga, Shruti; Singh, Suraj Kumar
The most often utilised parameters for the characterisation of wastewaters are biochemical oxygen demand (BOD) and chemical oxygen demand (COD). Both parameters have advantages and disadvantages, and the choice is usually based on several factors, such as the amount of time it takes to determine each. To aid in the design and operation of wastewater treatment facilities, it is necessary to obtain a connection between BOD and COD for various wastewater treatment plants. The volumetric loading rate and removal effectiveness of BOD and COD of two wastew-ater treatment plants were compared in this article. The WWTPs chosen encompassed various areas of Prayagraj, located on the Ganga River. The association between BOD and COD discovered will aid in evaluating treatment processes. � The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.
Decoding Chambal River Shoreline Transformations: A Comprehensive Analysis Using Remote Sensing, GIS, and DSAS
(MDPI, 2023-05-08T00:00:00) Singh, Saurabh; Meraj, Gowhar; Kumar, Pankaj; Singh, Suraj Kumar; Kanga, Shruti; Johnson, Brian Alan; Prajapat, Deepak Kumar; Debnath, Jatan; Sahariah, Dhrubajyoti
Illegal sand mining has been identified as a significant cause of harm to riverbanks, as it leads to excessive removal of sand from rivers and negatively impacts river shorelines. This investigation aimed to identify instances of shoreline erosion and accretion at illegal sand mining sites along the Chambal River. These sites were selected based on a report submitted by the Director of the National Chambal Sanctuary (NCS) to the National Green Tribunal (NGT) of India. The digital shoreline analysis system (DSAS v5.1) was used during the elapsed period from 1990 to 2020. Three statistical parameters used in DSAS�the shoreline change envelope (SCE), endpoint rate (EPR), and net shoreline movement (NSM)�quantify the rates of shoreline changes in the form of erosion and accretion patterns. To carry out this study, Landsat imagery data (T.M., ETM+, and OLI) and Sentinel-2A/MSI from 1990 to 2020 were used to analyze river shoreline erosion and accretion. The normalized difference water index (NDWI) and modified normalized difference water index (MNDWI) were used to detect riverbanks in satellite images. The investigation results indicated that erosion was observed at all illegal mining sites, with the highest erosion rate of 1.26 m/year at the Sewarpali site. On the other hand, the highest accretion was identified at the Chandilpura site, with a rate of 0.63 m/year. We observed significant changes in river shorelines at illegal mining and unmined sites. Erosion and accretion at unmined sites are recorded at ?0.18 m/year and 0.19 m/year, respectively, which are minor compared to mining sites. This study�s findings on the effects of illegal sand mining on river shorelines will be helpful in the sustainable management and conservation of river ecosystems. These results can also help to develop and implement river sand mining policies that protect river ecosystems from the long-term effects of illegal sand mining. � 2023 by the authors.
Geospatial modeling to assess the past and future land use-land cover changes in the Brahmaputra Valley, NE India, for sustainable land resource management
(Springer Science and Business Media Deutschland GmbH, 2022-11-24T00:00:00) Debnath, Jatan; Sahariah, Dhrubajyoti; Lahon, Durlov; Nath, Nityaranjan; Chand, Kesar; Meraj, Gowhar; Farooq, Majid; Kumar, Pankaj; Kanga, Shruti; Singh, Suraj Kumar
Satellite remote sensing and geographic information system (GIS) have revolutionalized the mapping, quantifying, and assessing the land surface processes, particularly analyzing the past and future land use-land cover (LULC) change patterns. Worldwide river basins have observed enormous changes in the land system dynamics as a result of anthropogenic factors such as population, urbanization, development, and agriculture. As is the scenario of various other river basins, the Brahmaputra basin, which falls in China, Bhutan, India, and Bangladesh, is also witnessing the same environmental issues. The present study has been conducted on the Brahmaputra Valley in Assam, India (a sub-basin of the larger Brahmaputra basin) and assessed its LULC changes using a maximum likelihood classification algorithm. The study also simulated the changing LULC pattern for the years 2030, 2040, and 2050 using the GIS-based cellular automata Markov model (CA-Markov) to understand the implications of the ongoing trends in the LULC change for future land system dynamics. The current rate of change of the LULC in the region was assessed using the 48�years of earth observation satellite data from 1973 to 2021. It was observed that from 1973 to 2021, the area under vegetation cover and water body decreased by 19.48 and 47.13%, respectively. In contrast, cultivated land, barren land, and built-up area increased by 7.60, 20.28, and 384.99%, respectively. It was found that the area covered by vegetation and water body has largely been transitioned to cultivated land and built-up classes. The research predicted that, by the end of 2050, the area covered by vegetation, cultivated land, and water would remain at 39.75, 32.31, and 4.91%, respectively, while the area covered by built-up areas will increase by up to 18.09%. Using the kappa index (ki) as an accuracy indicator of the simulated future LULCs, the predicted LULC of 2021 was validated against the observed LULC of 2021, and the very high ki observed validated the generated simulation LULC products. The research concludes that significant LULC changes are taking place in the study area with a decrease in vegetation cover and water body and an increase of area under built-up. Such trends will continue in the future and shall have disastrous environmental consequences unless necessary land resource management strategies are not implemented. The main factors responsible for the changing dynamics of LULC in the study area are urbanization, population growth, climate change, river bank erosion and sedimentation, and intensive agriculture. This study is aimed at providing the policy and decision-makers of the region with the necessary what-if scenarios for better decision-making. It shall also be useful in other countries of the Brahmaputra basin for transboundary integrated river basin management of the whole region. � 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
Groundwater Potential Zone Mapping in the Ghaggar River Basin, North-West India, Using Integrated Remote Sensing and GIS Techniques
(MDPI, 2023-03-02T00:00:00) Upadhyay, Ritambhara K.; Tripathi, Gaurav; ?urin, Bojan; �amanovi?, Sanja; Cetl, Vlado; Kishore, Naval; Sharma, Mukta; Singh, Suraj Kumar; Kanga, Shruti; Wasim, Md; Rai, Praveen Kumar; Bhardwaj, Vinay
The immense dependence of the growing population on groundwater has resulted in depletion at a fast pace can be seen nowadays. Identifying a groundwater potential zone can be proved as an aid to provide insight to the decision-makers and local authorities for planning purposes. This study evaluated the delineation of groundwater potential zones using integrated remote sensing and GIS approach. Various thematic layers such as geology, geomorphology, lineament, slope, drainage, soil, land use/land cover, and rainfall were considered in this study as these have influence on the occurrence of groundwater and its cycle, and maps have been prepared in GIS domain. Afterward, appropriate weights were assigned to these layers based on multi-criteria decision analysis, i.e., Analytical Hierarchy Process (AHP). Groundwater potentiality has been delineated in different zones (low, moderate, high, and very high) in the study region based on weighted overlay analysis. The study reveals zones with different groundwater prospects viz. low (1.27%), moderate (15.65%), high (75.54%), and very high (7.29%). The ground survey data provided by CGWB (Central Ground Water Board) of nearly 100 wells/dug wells/borewells/piezometers have been used for validation purposes, showing comparable results with the groundwater prospects zones. It also confirms that the majority of these wells fall under very high or high groundwater potential zones. They were also found to be thereby indicating that there is the existence of a permeable reservoir with considerable water storage in the subsurface. One of the most important issues for users and governments is groundwater depletion. Planning for the available groundwater resource is made easier by identifying the potential for groundwater (low to high). � 2023 by the authors.
Land Use and Land Cover Change Monitoring and Prediction of a UNESCO World Heritage Site: Kaziranga Eco-Sensitive Zone Using Cellular Automata-Markov Model
(MDPI, 2023-01-02T00:00:00) Nath, Nityaranjan; Sahariah, Dhrubajyoti; Meraj, Gowhar; Debnath, Jatan; Kumar, Pankaj; Lahon, Durlov; Chand, Kesar; Farooq, Majid; Chandan, Pankaj; Singh, Suraj Kumar; Kanga, Shruti
The Kaziranga Eco-Sensitive Zone is located on the edge of the Eastern Himalayan biodiversity hotspot region. In 1985, the Kaziranga National Park (KNP) was declared a World Heritage Site by UNESCO. Nowadays, anthropogenic interference has created a significant negative impact on this national park. As a result, the area under natural habitat is gradually decreasing. The current study attempted to analyze the land use land cover (LULC) change in the Kaziranga Eco-Sensitive Zone using remote sensing data with CA-Markov models. Satellite remote sensing and the geographic information system (GIS) are widely used for monitoring, mapping, and change detection of LULC change dynamics. The changing rate was assessed using thirty years (1990�2020) of Landsat data. The study analyses the significant change in LULC, with the decrease in the waterbody, grassland and agricultural land, and the increase of sand or dry river beds, forest, and built-up areas. Between 1990 and 2020, waterbody, grassland, and agricultural land decreased by 18.4, 9.96, and 64.88%, respectively, while sand or dry river beds, forest, and built-up areas increased by 103.72, 6.96, and 89.03%, respectively. The result shows that the area covered with waterbodies, grassland, and agricultural land is mostly converted into built-up areas and sand or dry river bed areas. According to this study, by 2050, waterbodies, sand or dry river beds, and forests will decrease by 3.67, 3.91, and 7.11%, respectively; while grassland and agriculture will increase by up to 16.67% and 0.37%, respectively. The built-up areas are expected to slightly decrease during this period (up to 2.4%). The outcome of this study is expected to be useful for the long-term management of the Kaziranga Eco-Sensitive Zone. � 2023 by the authors.
Landslide Susceptibility Mapping of Tehri Reservoir Region Using Geospatial Approach
(Springer International Publishing, 2023-03-10T00:00:00) Tripathi, Gaurav; Shakya, Achala; Upadhyay, Ritambhara Kumari; Singh, Suraj Kumar; Kanga, Shruti; Pandey, Sandeep Kumar
Uttarakhand is one of the most landslide-susceptible states because of its geographical setting, which consists of 86% of the Himalayan terrain. However, in recent years, landslides have increased dramatically due to the large number of settlements, farms, road buildings, and a wide variety of hydroelectric projects. Therefore, this is a need to study the landslides scrupulously at a regional scale to rein the future developmental planning models. In the current work, a comprehensive study has been undertaken for the assessment of landslide susceptibility zones using the weight of evidence (WOE) and risk assessment for the Tehri region, specifically around the Tehri reservoir. Landslides are derived through remotesensing techniques and other sources such as slope, geology, aspect, geomorphology, land use/land cover, drainage, lineaments, and more. After that, the WOE method is applied to integrate causative factors for the mapping of susceptible landslide zones, where the weights have been assigned to each layer according to available literatures. Subsequently, vulnerability is prepared for the area by integrating layers through the weighted sum technique. Finally, a risk map was prepared by integrating a susceptibility and vulnerability map. All three maps, namely, vulnerability, landslide susceptibility, and risk maps, were classified into five zones: very low, low, moderate, high, and very high. The results obtained from final maps and plots indicate that approximately 8% of the area is in a high susceptible zone, 50% is in a moderate susceptible zone, 54% is in a very low-risk zone, 23% is in a moderaterisk zone, and 14% is in a very high-risk zone. This study identified and illustrated the causative factors, combined into a GIS environment to identify landslide-prone locations. Then, depending upon the potency of an element, suitable and effective preventive measures may be taken to reduce the impact of the disaster. The concerned government agencies can use the same map while mapping disaster management, developing future strategies, implementing rehabilitation programs, and environmental planning. � The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.
Predicting Future Land Use Utilizing Economic and Land Surface Parameters with ANN and Markov Chain Models
(Multidisciplinary Digital Publishing Institute (MDPI), 2023-09-18T00:00:00) Rani, Ankush; Gupta, Saurabh Kumar; Singh, Suraj Kumar; Meraj, Gowhar; Kumar, Pankaj; Kanga, Shruti; ?urin, Bojan; Dogan?i?, Dragana
The main aim of this study is to comprehensively analyze the dynamics of land use and land cover (LULC) changes in the Bathinda region of Punjab, India, encompassing historical, current, and future trends. To forecast future LULC, the Cellular Automaton�Markov Chain (CA) based on artificial neural network (ANN) concepts was used using cartographic variables such as environmental, economic, and cultural. For segmenting LULC, the study used a combination of ML models, such as support vector machine (SVM) and Maximum Likelihood Classifier (MLC). The study is empirical in nature, and it employs quantitative analyses to shed light on LULC variations through time. The result indicates that the barren land is expected to shrink from 55.2 km2 in 1990 to 5.6 km2 in 2050, signifying better land management or increasing human activity. Vegetative expanses, on the other hand, are expected to rise from 81.3 km2 in 1990 to 205.6 km2 in 2050, reflecting a balance between urbanization and ecological conservation. Agricultural fields are expected to increase from 2597.4 km2 in 1990 to 2859.6 km2 in 2020 before stabilizing at 2898.4 km2 in 2050. Water landscapes are expected to shrink from 13.4 km2 in 1990 to 5.6 km2 in 2050, providing possible issues for water resources. Wetland regions are expected to decrease, thus complicating irrigation and groundwater reservoir sustainability. These findings are confirmed by strong statistical indices, with this study�s high kappa coefficients of Kno (0.97), Kstandard (0.95), and Klocation (0.97) indicating a reasonable level of accuracy in CA prediction. From the result of the F1 score, a significant issue was found in MLC for segmenting vegetation, and the issue was resolved in SVM classification. The findings of this study can be used to inform land use policy and plans for sustainable development in the region and beyond. � 2023 by the authors.
Simulating Groundwater Potential Zones in Mountainous Indian Himalayas�A Case Study of Himachal Pradesh
(MDPI, 2023-03-13T00:00:00) Sud, Anshul; Kanga, Rahul; Singh, Suraj Kumar; Meraj, Gowhar; Kanga, Shruti; Kumar, Pankaj; Ramanathan, A.L.; Sudhanshu; Bhardwaj, Vinay
Groundwater resources are increasingly important as the main supply of fresh water for household, industrial, and agricultural activities. However, overuse and depletion of these resources can lead to water scarcity and resource deterioration. Therefore, assessing groundwater availability is essential for sustainable water management. This study aims to identify potential groundwater zones in the Bilaspur district of Himachal Pradesh using the Multi Influencing Factor (MIF) technique, a modern decision-making method widely used in various sectors. Geospatial models were integrated with the MIF technique to evaluate prospective groundwater areas. Grid layouts of all underground water influencing variables were given a predetermined score and weight in this decision-making strategy. The potential groundwater areas were then statistically assessed using graded data maps of slope, lithology, land-use, lineament, aspect, elevation, soil, drainage, geomorphology, and rainfall. These maps were converted into raster data using the raster converter tool in ArcGIS software, utilizing Survey of India toposheets, SRTM DEM data, and Resourcesat-2A satellite imageries. The prospective groundwater zones obtained were classified into five categories: nil�very low, covering 0.34% of the total area; very low�low (51.64%); low�moderate (4.92%); moderate�high (18%) and high�very high (25%). Scholars and policymakers can collaborate to develop systematic exploration plans for future developments and implement preservative and protective strategies by identifying groundwater recharge zones to reduce groundwater levels. This study provides valuable insights for long-term planning and management of water resources in the region. � 2023 by the authors.
Spatial and Temporal Analysis of Hydrological Modelling in the Beas Basin Using SWAT+ Model
(Multidisciplinary Digital Publishing Institute (MDPI), 2023-09-24T00:00:00) Singh, Suraj Kumar; Kanga, Shruti; Gulati, Bhavneet; Rai?, Mirna; Sajan, Bhartendu; ?urin, Bojan; Singh, Saurabh
In this research, the SWAT+ model was employed to elucidate hydrological dynamics within the Beas Basin. The primary objectives encompassed the calibration of the SWAT model for accurate water balance quantification, annual simulation of salient hydrological components, and a decadal analysis of trends in fluvial discharge and sediment transport. The methodology encompasses simulating hydrological data with the SWAT+ model, followed by calibration and validation using flow data from Larji and Mahadev hydroelectric plants. The model�s efficacy in depicting streamflow and other hydrological components is corroborated by statistical measures such as the Nash�Sutcliffe efficiency and PBIAS. The water balance analysis delivers insights into the basin�s hydrological characteristics, including surface flow, water yield, and evapotranspiration. The temporal analysis exposes intricate seasonal and interannual variability in flow and sediment discharge, while spatial distribution highlights heterogeneity across the basin. These findings have practical implications for water resource management, including optimizing water allocation, hydroelectric power generation, irrigation, and environmental concerns. Limitations, such as data quality and model simplifications, are acknowledged, and future data collection and observations are recommended for improved model performance. In essence, these researches enhance understanding of the Beas Basin�s hydrology, setting a course for future investigations to integrate more data sources, refine model parameters, and consider climate and land-use changes for a richer comprehension of the basin�s hydrological dynamics. � 2023 by the authors.
Spatial variations of LST and NDVI in Muzaffarpur district, Bihar using Google earth engine (GEE) during 1990-2020
(Association of Agrometeorologists, 2023-05-30T00:00:00) Sajan, Bhartendu; Kanga, Shruti; Singh, Suraj Kumar; Mishra, Varun Narayan; Durin, Bojan
The aim of this study is to analyze land cover changes and their effects on land surface temperature (LST) and normalized difference vegetation index (NDVI) in Muzaffarpur district, Bihar, India. The research utilized Landsat 5 and 8 satellite images taken every five years from 1990 to 2020 to classify seven land cover types, namely built-up areas, wetlands, fallow lands, croplands, vegetation, and water bodies, using the Artificial Neural Network technique in ENVI 5.1. The resulting land cover maps reveal a significant decrease in cropland area during the studied period, while fallow land area decreased from 48.06% to 35.79%. Analysis of LST and NDVI data showed a strong negative correlation (R2 <-0.0057) for all years, except for a weak positive correlation (R2 > 0.006). NDVI values were highest in agricultural lands with the lowest LST values, while fallow land areas showed the opposite trend. The study suggests that vegetation and fallow land are crucial determinants of the spatial and temporal variations in NDVI and LST, relative to urban and water cover categories. � 2023, Association of Agrometeorologists. All rights reserved.
Status of Air Pollution during COVID-19-Induced Lockdown in Delhi, India
(MDPI, 2022-12-13T00:00:00) Singh, Harikesh; Meraj, Gowhar; Singh, Sachchidanand; Shrivastava, Vaibhav; Sharma, Vishal; Farooq, Majid; Kanga, Shruti; Singh, Suraj Kumar; Kumar, Pankaj
To monitor the spread of the novel coronavirus (COVID-19), India, during the last week of March 2020, imposed national restrictions on the movement of its citizens (lockdown). Although India�s economy was shut down due to restrictions, the nation observed a sharp decline in particulate matter (PM) concentrations. In recent years, Delhi has experienced rapid economic growth, leading to pollution, especially in urban and industrial areas. In this paper, we explored the linkages between air quality and the nationwide lockdown of the city of Delhi using a geographic information system (GIS)-based approach. Data from 37 stations were monitored from 12 March, 2020 to 2 April, 2020 and it was found that the Air Quality Index for the city was almost reduced by 37% and 46% concerning PM2.5 and PM10, respectively. The study highlights that, in regular conditions, the atmosphere�s natural healing rate against anthropogenic activities is lower, as indicated by a higher AQI. However, during the lockdown, this sudden cessation of anthropogenic activities leads to a period in which the natural healing rate is greater than the induced disturbances, resulting in a lower AQI, and thus proving that this pandemic has given a small window for the environment to breathe and helped the districts of Delhi to recover from serious issues related to bad air quality. If such healing windows are incorporated into policy and decision-making, these can prove to be effective measures for controlling air pollution in heavily polluted regions of the World. � 2022 by the authors.
Uncovering the hydro-meteorological drivers responsible for forest fires utilizing geospatial techniques
(Springer, 2023-05-29T00:00:00) Gupta, Saurabh Kumar; Kanga, Shruti; Meraj, Gowhar; Kumar, Pankaj; Singh, Suraj Kumar
Forest fires have become a growing concern worldwide, with climate change exacerbating their frequency and intensity. In the Simlipal region of India, forest fires are relatively rare; however, in 2021, significant damage occurred in the buffer area�s forests. Understanding the driving factors behind these events is essential for developing effective management strategies. This study investigates the impact of hydro-meteorological conditions on forest fire causes in the Simlipal region by analyzing Terra climatic data and geo-statistics for the period of 1984 to 2021. Long-term trends were determined using non-parametric tests on the Google Earth Engine (GEE) cloud computing platform. Our findings reveal that the maximum burned area location has a decreasing trend in Land Surface Temperature (LST), with a small portion (<10%) showing an increasing trend (0.02 �C/year) near burned locations. Wind speed is decreasing at a rate of ?0.006 m/s/year. The sudden forest fires are caused by the combined effect of increasing LST and decreasing wind speed in some areas (<10% of the region). However, the major factor contributing to forest fires in the entire area is the rising trend of annual potential water deficit and actual evapotranspiration, as well as an increasing trend of minimum temperature. The soil moisture deficit during the summer season, especially between 2012 and 2021, contributed to forest fires in the burned area. The soil moisture deficit during the summer season, particularly from 2012 to 2021, played a significant role in the occurrence of forest fires in the affected area. The study emphasized the need for increased attention to this region in order to preserve biodiversity, which was assessed through an analysis of burned severity mapping in GEE (Google Earth Engine). These findings have important implications for future forest management strategies in the Simlipal region. Climate variability is likely to exacerbate the frequency and intensity of forest fires in the region, necessitating effective management strategies to mitigate their impact. Such strategies could involve improving fire prevention and control measures, such as creating fire breaks and increasing the availability of fire-fighting equipment, as well as enhancing forest monitoring systems to detect potential fires early. Additionally, efforts to address climate change, proper management of land use practices, and reduce greenhouse gas emissions could help to mitigate the future impacts of forest fires in the Simlipal region and elsewhere. � 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature.
Unveiling Nature�s Resilience: Exploring Vegetation Dynamics during the COVID-19 Era in Jharkhand, India, with the Google Earth Engine
(Multidisciplinary Digital Publishing Institute (MDPI), 2023-09-08T00:00:00) Ahmad, Tauseef; Gupta, Saurabh Kumar; Singh, Suraj Kumar; Meraj, Gowhar; Kumar, Pankaj; Kanga, Shruti
The Severe Acute Respiratory Syndrome Coronavirus Disease 2019 (COVID-19) pandemic has presented unprecedented challenges to global health and economic stability. Intriguingly, the necessary lockdown measures, while disruptive to human society, inadvertently led to environmental rejuvenation, particularly noticeable in decreased air pollution and improved vegetation health. This study investigates the lockdown�s impact on vegetation health in Jharkhand, India, employing the Google Earth Engine for cloud-based data analysis. MODIS-NDVI data were analyzed using spatio-temporal NDVI analyses and time-series models. These analyses revealed a notable increase in maximum vegetation greenery of 19% from April 2019 to 2020, with subsequent increases of 13% and 3% observed in March and May of the same year, respectively. A longer-term analysis from 2000 to 2020 displayed an overall 16.7% rise in vegetation greenness. While the maximum value remained relatively constant, it demonstrated a slight increment during the dry season. The Landsat data Mann�Kendall trend test reinforced these findings, displaying a significant shift from a negative NDVI trend (1984�2019) to a positive 17.7% trend (1984�2021) in Jharkhand�s north-west region. The precipitation (using NASA power and Merra2 data) and NDVI correlation were also studied during the pre- and lockdown periods. Maximum precipitation (350�400 mm) was observed in June, while July typically experienced around 300 mm precipitation, covering nearly 85% of Jharkhand. Interestingly, August 2020 saw up to 550 mm precipitation, primarily in Jharkhand�s southern region, compared to 400 mm in the same month in 2019. Peak changes in NDVI value during this period ranged between 0.6�0.76 and 0.76�1, observed throughout the state. Although the decrease in air pollution led to improved vegetation health, these benefits began to diminish post-lockdown. This observation underscores the need for immediate attention and intervention from scientists and researchers. Understanding lockdown-induced environmental changes and their impact on vegetation health can facilitate the development of proactive environmental management strategies, paving the way towards a sustainable and resilient future. � 2023 by the authors.
Urban Heat Island (UHI) Resilience Plan in Varying Climatic Conditions Using Geospatial Approach: A Case Study of Rajkot City
(Springer International Publishing, 2023-05-19T00:00:00) Kotecha, Mit J.; Kanga, Shruti; Pankhaniya, Sagar K.; Agrawal, Sneha; Meraj, Gowhar; Singh, Suraj Kumar
During the twenty-first century, urbanization and industrialization are rapidly growing in India, adversely destroying the climate. Urban Heat Island can be discerned in urban areas due to anthropogenic activities, industrialization, deforesta-tion, etc. The main peculiarity of the UHI effect is a rise in temperature in core urban areas than their rural surroundings, leading to excessive energy usage and putting the urban population at significant risk of morbidity and mortality. Therefore, the study of UHI is crucial for adaptation to climate change and making the city resilient. In this study, the LST and air temperature (ambient) of Rajkot city were assessed. We derived isotherm for Rajkot city for three locations: Trikon Baugh, Madhapar Chowk, and Atika industrial area having diverse typologies. The inconsistency between LST and ambient air temperature has been found out. Carbon dioxide and carbon monoxide, which contribute to the UHI effect, were also analyzed for these locations. From the analysis, UHI�s resilient strategies, effectiveness, and resilience were established to help provide recommendations for applying resilient strategies. The four central resilient systems are integrating reduction and response of UHI for existing policies and programs, strengthening and building green infrastructure, alleviating cool roofs, and creating cool road infrastructure. Detailed demonstration of resilient strategies was given through T.P. scheme-10 of Rajkot. � The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.