http://localhost:8081/jspui/handle/123456789/15067 2026-05-21T18:48:56Z http://localhost:8081/jspui/handle/123456789/20433 Title: GEOSPATIAL MODELING OF GROUNDWATER DEPLETION AND ITS IMPACT IN PARTS OF NORTHWEST INDIA Authors: Sahoo, Sashikanta Abstract: Groundwater is a critical resource for agriculture, industrial growth, and domestic use, particularly in semi-arid and arid regions of Northwest India, where surface water is limited. However, in recent decades, over-extraction of groundwater, primarily for irrigation, has led to significant groundwater depletion in areas such as the Malwa region of Punjab. This research employs geospatial modeling, machine learning, and remote sensing techniques to assess groundwater depletion trends and predict future impacts, offering a systematic analysis over a 21-year period (1997–2018) using groundwater level (GWL) data from 90 wells in the region. The study aims to provide insight into spatial variations in depletion rates, the potential for groundwater recharge, and the implications of water resource management practices. The analysis reveals an alarming trend of groundwater decline, with over 30% of wells in Malwa experiencing depletion at an average rate of approximately 40 cm per year. Seasonal patterns of groundwater levels, influenced by monsoon variability, show that while most areas report consistent declines, certain regions in southwestern Malwa experience waterlogging during monsoon periods, resulting in localized groundwater rise. This dichotomy between groundwater depletion and localized waterlogging reflects the complex hydrological challenges faced in this region, emphasizing the need for tailored water management strategies. To quantify the spatial and temporal trends in groundwater levels, statistical tools such as the Modified Mann-Kendall (MMK) test and Sen’s slope estimator were applied, allowing for a more nuanced understanding of depletion patterns. Hierarchical cluster analysis further enabled classification of wells based on depletion rates, providing a clear spatial framework for targeted groundwater management interventions. To forecast groundwater trends under varying future scenarios, machine learning (ML) models, including Random Forest (RF), Bagging-REPTree, and Bagging-DSTree, were applied. Among these, RF emerged as the most robust model, demonstrating high predictive accuracy across multiple statistical metrics, including Root Mean Square Error (RMSE), Nash-Sutcliffe Efficiency (NSE), and correlation coefficient (CC). By offering reliable predictive capability, the RF model proves valuable for informing water resource policies and planning in high-demand agricultural zones. This study highlights the utility of ML techniques for groundwater forecasting, advocating for their broader application in resource-scarce and over-exploited regions. 2024-09-01T00:00:00Z http://localhost:8081/jspui/handle/123456789/20367 Title: PARTICIPATORY RISK RESILIENT PLANNING FRAMEWORK FOR SUSTAINABLE HILL HABITAT Authors: Chouhan, Shivani Abstract: The Indian Himalayas are one of the world's most significant and extensive mountain ecosystems. However, due to their tectonic activity, structural instability and mature nature, they are prone to multiple hazards, with huge loss of life and damage to property every year. Unrecognised practices, poor-engineering, and irresponsible development initiatives increase disaster risk and severity in the region, which turned many natural hazards into human-induced disasters. Such disasters further strain an economy already under stress, with devastating socio-economic consequences. Uttarakhand is an Indian Himalayan state located in the northern region of India. Being a Himalayan state, it experiences disasters every year with great losses. Among the most notable disasters in the state are the Uttarkashi earthquake (1991), Chamoli earthquake (1999), Malpa landslide (1998), the Himalayan tsunamis of Badrinath and Kedarnath (2013), and the recent sinking of Joshimath town (2023). Besides being in seismic zones V and IV, it is also susceptible to multiple hazards like floods, landslides, cloudbursts etc. Tourism is a major attraction in the state, and it is a popular destination for pilgrimages and leisure activities. It is estimated that over 25 million tourists visited the state in 2011, which has a population of about 10 million, despite the fact that the state faces frequent natural hazards especially during the monsoon season. While the state has abundant natural resources and tourism activities, most of its population lives on a survival level, making it vulnerable to disaster impacts and recovery. In this region, unscientific exploitation of natural resources has resulted in increased hazards and environmental degradation (Singh, 2006). For the aforementioned reasons, Uttarakhand state was chosen for this study as it desperately needs a prioritisation development decision framework for sustainable risk-resilient planning. The focus and overall aim of this study is to identify the parameters that are increasing the risk most significantly and slowing down the disaster recovery process in the Indian Himalayan Region. The Multi-hazard Risk Assessment (MHRA) component of the study will examine pre-disaster factors and the Disaster Recovery study will examine post-disaster factors. The significant parameters identified are connected with sustainable development goals and validated using a participatory approach. 2024-02-01T00:00:00Z http://localhost:8081/jspui/handle/123456789/20351 Title: DEVELOPMENT AND FLAMMABILITY BEHAVIOR OF FOREST/CROP RESIDUE-BASED POLYMERIC COMPOSITES Authors: Gairola, Sandeep Abstract: Throughout human civilization, the role of materials has been paramount, shaping technological advancements and driving progress. In this context, polymer matrix composites (PMCs) have emerged as versatile and promising materials, offering a unique blend of mechanical properties. However, their widespread adoption faces challenges, notably in terms of sustainability. To address these challenges, the incorporation of biobased fibers and fillers derived from forest and agricultural waste has gained substantial attention. Incorporating biobased fibers and fillers in biopolymers signifies a critical shift towards sustainable material development. Despite these advancements, one significant limitation that hinders the broader application of natural fiber reinforced polymer composites (NFRPCs) is their inherently poor flame retardancy. Natural fibers, while offering an array of advantages, tend to be highly flammable when exposed to heat or flame. This susceptibility to combustion poses a critical constraint on their potential utility across various industries, particularly in applications where fire resistance is an essential criterion. Conventional flame-retardant (FR) materials, typically based on halogenated compounds and other hazardous chemicals, have addressed this challenge effectively. However, they often counteract the sustainability goals sought using natural fibers. Consequently, developing flame-retardant biobased composites becomes a pressing imperative, as it aligns sustainability with fire safety. Hence, the current research endeavor aims to tackle the issue by exploring various underutilized agricultural/forest waste as potential filler/fibers for the development of polymer matrix composites via conventional routes, such as extrusion, injection, and compression molding techniques. It is followed by developing flame-retardant-based composites using non-halogenated flame retardants, thereby broadening the application spectrum of these sustainable materials. The present research investigation is divided into four broad areas. The first phase explores a feasibility check and process parameter optimization for processing NFRPCs using various forest/agricultural waste (such as, finger millet husk, barnyard millet husk, and corncob). The processing is followed by investigation of the mechanical, thermal, and morphological behavior of developed NFRPCs using standard characterization techniques. The tensile and flexural strength varies for all the composites in the range of 22-30 MPa and 45-63 MPa, respectively. The tensile and flexural modulus varies in the range of 550-900 MPa and 1700-2700 MPa, respectively. The results established the potential candidacy of the selected waste materials as a filler/reinforcement in developing composite materials for non-structural applications. The second phase explore the woven (continuous) fiber (such as, jute, sisal, and jute-sisal intra hybrid fabric) based polypropylene composites. The analysis involved the investigation of fiber orientation, hybridization, and stacking sequence and their effect on the static and dynamic mechanical behavior of the developed composites. The results revealed that the combined and alternative orientation of the jute and sisal fibers resulted in better stress transfer efficiency. Therefore, hybridization and orientation of the fibers significantly improved the static and dynamic mechanical properties of developed composites. The third phase explored the FR additives, treatment of fibers with FRs, and hybrid FR approaches to develop flame-resistant NFRPCs. The findings provide an in-depth analysis of the development and utilization of FR-based natural fibers for developing flame-resistant NFRPCs employing detailed characterization. The results revealed that the hybrid approach utilizing FR additives and treated fibers exhibited superior flame retardancy as compared to the additive and treated fiber approaches adopted independently. The fourth phase explored the detailed analysis of the degradation behavior of the jute-sisal fibers and their polypropylene based composites when exposed to three different environmental conditions. The results have been thoroughly analyzed and discussed in detail. The results revealed that the lowest durability was observed with alkali aging, followed by water and oil aging. The current experimental research gives insight into the importance of fiber hybridization, orientation, stacking sequence processing, flame retardancy behavior, and environment aging behavior of polymeric composites. The research findings from the current work can certainly help the industrial and research fraternity working in the broad area of sustainable composites. 2024-02-01T00:00:00Z http://localhost:8081/jspui/handle/123456789/19605 Title: EARTHQUAKE EARLY WARNING SYSTEM: SITE CLASSIFICATION, INTENSITY MAP AND ATTRIBUTES Authors: Kumar, Pankaj Abstract: The Himalaya is one of the most seismically active regions of the world. Many Indian states are in the Himalayan region, and Uttarakhand is one of them. This region lies in seismic zones IV and V of the seismic zone map of India (IS 1893 (Part1), 2016) and is prone to seismic hazards. Seismic gap studies carried out of the Indian Himalayan region (Srivastava et al., 2015) identify a central seismic gap, namely Uttarakhand-Dharchula between Kaurik fault in Himachal-Pradesh and Main Central Thrust (MCT) near Dharchula, Nepal. The major part of the Uttarakhand falls in this seismic gap region. Many researchers have envisaged that a large earthquake is impending in this region. Therefore, an Earthquake Early Warning (EEW) System for this region can serve as a foremost tool to reduce losses due to future earthquakes. An EEW System for Uttarakhand has been developed by EEW System Laboratory, Centre of Excellence in Disaster Mitigation & Management (CoEDMM), Indian Institute of Technology (IIT) Roorkee. Now, this system is full-fledged operational. A further research study that needs to be addressed is required to be carried out. In the present thesis, an attempt has been made to fill the identified gaps. In this study, all the prevalent EEW attributes and their formulation are presented in tabular form. The empirical relationships to estimate magnitude using EEW parameters developed by different authors are also presented in a tabular form. Several authors have formulated GMPEs for the Indian Himalayan region, which are described in the literature review. Various site classification schemes used by different authors are described in the tabular form. Studies carried out by different authors in the preparation of PGA and intensity maps are explained. The developed regression relationships between Modified Mercalli Intensity (MMI) and PGA by various authors are presented in a tabular form. Finally, the research gaps are identified to address the objective to enhance the potential of existing EEW System and carried out unwinding of complexities of the earthquakes in general. There is no regional attenuation model available for the Uttarakhand region; therefore, an attempt has been made to develop a regional GMPE for this region. A dataset of 116 records of 9 earthquakes having magnitudes ranges from 5.0 to 6.8 of this region, recorded by ‘U.P. array’ (Shrikhande, 2001), Indian National Strong Motion Instrumentation Network (NSMIN) accelerographs (Kumar et al., 2012), and presently operating EEW System for Uttarakhand has been used to develop attenuation relationship for peak ground acceleration (horizontal components) for Uttarakhand region. The hybrid (i.e. two step-stratified) regression analysis has been used in the modelling of a new relationship (equation 1). 𝑙𝑜𝑔10 𝐴 (𝑔) = −1.091 + 0.3245𝑀 − 1.0632 𝑙𝑜𝑔10(𝑋 + 𝑒𝑥𝑝0.4561𝑀) (1) The developed relationship has been compared with other developed relationships for the whole Himalayan region (Singh et al., 1996; Sharma, 1998; Kumar et al., 2017; Joshi et al., 2013), which at present, could be used for the Uttarakhand region also. However, the newly developed relationship for Uttarakhand region shows good results despite having small data set used in the development of this relationship. Thus, the developed GMPE can be considered to be more reliable for this region. The root mean square error (RMSE) of the present relationship is found to be comparable with other relationships, but much superior to the relationship developed by Joshi et al. (2013). The instrumentation of the EEW System for Uttarakhand comprises 167 sensors installed in the hilly region of the state. After processing of the data, only 97 stations qualified the eligibility criteria. The qualification criteria are signal to noise ratio (SNR) and preset threshold of PGA of the records. The horizontal by vertical (H/V) spectral ratio curves of all the stations are created by both Fourier amplitude spectra (FAS) and 5% damped response spectra. The effects of depth, distance, and magnitude of earthquakes on the H/V spectral ratio curves are discussed. The effect of change in percentage of damping ratio in response spectra method is also discussed. Four methods have been used for classification. In the first method, the predominant period is estimated by the H/V spectral ratio curve of FAS of the data. In the second method, the predominant period is estimated by the H/V spectral ratio curve of 5% damped response spectra of the data. The third method is based on an empirical approach, and a site classification index uses cumulative distribution function (Zhao et al., 2006). The fourth method is based on Spearman’s rank correlation coefficient and uses the site index for classification (Ghasemi et al., 2009). The present work of classification uses only strong ground motion of earthquakes recorded by the instrumented sensors of EEW System for Uttarakhand. Two classification schemes, namely the NEHRP scheme (Building Seismic Safety Council, 2003) in the first method and Japan Road Association (1980) scheme in the second method have been used to classify sites. Conclusively, the site class, which has the highest frequency of occurrence amongst the four methods has been selected the final site classification of that station. In the present study, the aggregate H/V spectral ratio curve of each site class is compared with the standard H/V spectral ratio curves given by Zhao et al. (2006).A server of the EEW System for Uttarakhand continuously processes the streamed ground motion data coming from the distant installed sensors. The complete records of the earthquake recorded by the triggered sensors become available in real-time. A computer program using python programming language has been developed to create PGA and intensity maps through the EEW System for Uttarakhand. The reason to choose python is its open-source nature and availability of required numerous in-built modules and packages. The computer program is written to read ground motion data to implement GMPE and MMI scaling models. This program reads ground motion data (acceleration) from the server and performs pre-processing operations (e.g. baseline correction, filtering etc.). Before creating PGA and intensity maps, code adaptively creates new GMPE using the records of the past earthquakes of the region augmented with the new earthquake records, and when RMSE of new GMPE is found to be less than the existing regional GMPE, then it uses modified GMPE; otherwise, it uses existing GMPE of the region. An opensource image and graph drawing software, namely Generic Mapping Tools (GMT) is used to draw the spatial variation of varying seismic intensity (Wessel and Smith, 1991) and variation of PGA in the region. The GMT tool plots high-quality images, graphs, and maps. A colour palette is used to show geospatial variation in PGA and intensities on the maps. For a regional EEW System, fast determination of the magnitude of the impending earthquake on the basis of the first few seconds of the P-wave record is more complex than the determination of EEW parameters. The scaling relationships between magnitude and EEW parameters have been developed and tested for many regions of the world. In the present study, Pd based magnitude does a good agreement with catalogue magnitude. As data is very limited and the highest magnitude in the catalogue used in this study is 5.5; therefore, the developed model would give a good approximation to the magnitude range from 3 to 5. The derived scaling relationship (equation 2) with RMSE 0.252 is a good fit for the Uttarakhand region for small earthquakes. Magnitude is estimated by inverting the model given in equation (2). 𝑙𝑜𝑔 (𝑃𝑑) = −2.6826 + 0.52258 × 𝑀𝑤 − 1.2011 × 𝑙𝑜𝑔 (𝑋) (2) This thesis contributes the research work useful to the professionals of diverse fields. The developed maps would be very useful to disaster management authorities, land-use planners, and professionals. Classification of the sites and developed GMPE model would help in seismic hazard analysis of the region. Pd based magnitude estimation would help professionals who are involved in the development and maintenance of the EEW Systems. 2020-05-01T00:00:00Z