Department Of Geography
Permanent URI for this communityhttps://kr.cup.edu.in/handle/32116/89
Browse
6 results
Search Results
Item 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, VinayGroundwater 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.Item 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, VinayThe 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.Item Frontal Changes of Gangotri Glacier, Garhwal Himalaya, between 1935 and 2022(Springer, 2023-02-07T00:00:00) Bhambri, Rakesh; Sain, Kalachand; Chand, Pritam; Srivastava, Deepak; Tiwari, Sameer K.; Yadav, Jairam SinghGangotri Glacier is one of the most thoroughly investigated glaciers in the Indian Himalaya in terms of terminus monitoring. This study aims to update the frontal retreat of Gangotri Glacier between 1935 and 2022 using a large scale Geological Survey of India map, remote sensing images, and repeated photography. Gangotri Glacier�s retreat rate varied significantly during the study period. This glacier receded by 1727 � 51m (19.8 � 0.2 m a?1) between 1935 and 2022. The retreat of Gangotri Glacier decreased from 2001 to 2006 (7.0 � 4.0 m a?1) compared to the previous observation (1980�2001; 21.0 � 1.2 m a?1) but increased about three times between 2006 and 2017 (21.9 � 1.9 m a?1). Furthermore, from 2017 to 2022, the frontal retreat accelerated by about 1.5 times (33.8 � 6.7 m a?1) compared to the period between 2006 and 2017. The findings of the present study are consistent with ground based survey conducted by the Geological Survey of India. � 2023, Geological Society of India, Bengaluru, India.Item 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, PankajLand 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.Item Decadal terminus position changes and ice thickness measurement of Menthosa Glacier in Lahaul region of North-Western Himalaya(Taylor and Francis Ltd., 2021-06-05T00:00:00) Prakash, Satya; Sharma, Milap Chand; Sreekesh, S.; Chand, Pritam; Pandey, Vijendra Kumar; Latief, Syed Umer; Deswal, Sanjay; Manna, Ishita; Das, Suresh; Mandal, Sandip Tanu; Bahuguna, I.M.Glacier ice-thickness measurement and distribution is one of the essential variables to assess present status of glacier-water equivalent and its volumetric reserve as well as to model the future glacier dynamics under the climate changing scenario. Yet, substantial gaps in ice thickness information exist for the Himalayan glaciers. The present study provides a long-term assessment (1965�2016) of recessional and area change patterns, as well as the detailed field-based (2016�2017) Ground Penetrating Radar(GPR), derived ice-thickness measurement of the Menthosa Glacier, Lahaul Himalaya. Additionally, the study examines whether the modelled ice thickness from remote sensing data is consistent with the field-based GPR measurement and how can it be improved. The extensive field surveys coupled with the multi-temporal high (Corona KH-4A) to medium resolution (Landsat Enhanced Thematic Mapper+ (ETM+)/Operational Land Imager (OLI), Sentinel 2A-Multispectral Instrument (MSI)) remote sensing data and cross-sectional GPR surveyed profile measurements have been used to examine past half a century (1965�2016) glacier fluctuation and the recent ice-thickness estimations, respectively. The results show that the Menthosa Glacier receded by 301.5 � 19.2 m during the past half a century (1965�2016) with an average annual retreat of 5.9 � 0.4 m a?1, whereas glacier lost 0.09 km2 ice in the frontal section. Field measurement over the past one decade (2006�2017) also conforms to a continuous recessional pattern and substantial glacier degeneration particularly the extensive surface lowering and significant appearance of ice-cliffs in the ablation and lateral zones over this period. The GPR measurements (2017) show the minimum glacier ice thickness of 24 meters at 4691 m a.s.l. (in the lower part of ablation area) and maximum glacier ice thickness of 55 meters measured at 4758 m a.s.l. (in the upper left-side tributary part of ablation area). Moreover, the modelled ice thickness derived from remotely sensed data is having Root Mean Square Error (RMSE) between 38 to 72 � 10 m as compared with GPR measured ice thickness. � 2021 Informa UK Limited, trading as Taylor & Francis Group.Item Analyzing shoreline dynamicity and the associated socioecological risk along the Southern Odisha Coast of India using remote sensing-based and statistical approaches(Taylor and Francis Ltd., 2021-02-06T00:00:00) Mishra, Manoranjan; Acharyya, Tamoghna; Chand, Pritam; Santos, Celso Augusto Guimar�es; Kar, Dipika; Das, Prabhu Prasad; Pattnaik, Namita; Silva, Richarde Marques da; Nascimento, Thiago Victor Medeiros doThe coastal zone is an extremely volatile environment and is constantly changing. We assessed short- and long-term shoreline changes in the Ganjam district of Odisha on the eastern coast of India from 1990 to 2019 using Landsat satellite imagery and the Digital Shoreline Analysis System (DSAS) tool in a geographic information system. In addition, we have also projected the likely future coastline position for the 2030�2040 period and the possible impact on the socioecology of the shoreline. In this study, we used the endpoint rate (EPR) analysis, weighted linear regression (WLR) analysis, and trigonometric functions to analyze the shoreline from 1990 to 2019 and also forecasted for year 2030 and 2040. The shoreline of the Ganjam coastal zone is one of the most biologically productive ecosystems in the world, and it is well-known due to the breeding and mass nesting grounds of olive ridley turtles and the economically connected ports, famous beaches, and cyclone-prone areas. During the study period (1990�2019), the average erosion and accretion rates in the Ganjam shoreline were ?2.58 m/year and 11.63 m/year, respectively. The rate of shoreline erosion increased during years of cyclone landfall, which was revealed during the short-term shoreline analysis of the periods from 1995 to 2000 (1999 super cyclone) and 2015 to 2019 (2019 category�IV cyclone Fani). The short- to long-term analyses of the shoreline assisted in identifying erosion (Ramyapatna, Podampetta) and accretion (southern part of Gopalpur port, spits along the Bahuda and Rushikulya Rivers) hotspots within the Ganjam coastal zone. The identified erosion hotspots could submerge a significant number of coastal villages that serve as breeding and mass nesting grounds for olive ridley turtles. The dominant erosion along the Ganjam coastline are likely to enhance socioecological risk and further threaten coastal communities in the future. The output of the undertaken research will benefit coastal planners, policymakers, and conservationists by helping them to formulate the most suitable action plan for coastal zone management with consideration of all stakeholders. � 2021 Informa UK Limited, trading as Taylor & Francis Group.