Department Of Geography
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Item 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, SaurabhIn 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.Item 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 KumarContinuous 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.Item 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, ShrutiThe 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.Item 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 DavidThe 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.Item 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?, DraganaThe 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.Item 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 KumarForest 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.Item 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, GowharThe 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.Item 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, BojanThe 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.Item 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 KumarThe 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.Item 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 KumarUttarakhand 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.