BITS Faculty Publications

Permanent URI for this communityhttp://localhost:4000/handle/123456789/1867

Browse

Author: search.filters.author.Singh, Ajit PratapSubject: search.filters.subject.Civil engineering

Search Results

Now showing 1 - 6 of 6
  • No Thumbnail Available
    Item
    Decentralized faecal sludge management in rural India by integrating drying beds for dewatering and coagulation for leachate treatment: A sustainable, cost-effective, nature-based solution
    (Elsevier, 2025-11) Singh, Ajit Pratap
    Discharging untreated faecal sludge (FS) from on-site sanitation into the environment poses environmental and public health risks in semi-urban and rural areas of India. Therefore, designing a low-cost, resource-efficient, sustainable, and effective FS treatment system is crucial. This study investigated a hybrid treatment approach combining planted and unplanted drying beds for FS dewatering, followed by leachate treatment using natural coagulants, Moringa oleifera and chitosan. The planted and unplanted drying beds achieved removal efficiencies of 95.84 % and 94.47 % for total solids, 98.09 % and 97.71 % for chemical oxygen demand, 93.46 % and 91.17 % for biochemical oxygen demand, 95.09 % and 86.85 % for total phosphorus, 80.04 % and 71.71 % for total nitrogen, and 99 % and 97.71 % for E. coli, respectively. The macrophyte Nerium oleander, planted in the drying bed, exhibited healthy growth under FS loading conditions, with the plant height increasing from 0.75 m to 1.8 m, indicating its potential for phytoremediation and resilience. The natural coagulants M. oleifera and chitosan achieved 95.77 % and 96.29 % turbidity removal, and 81.67 % and 84.17 % COD removal, respectively. The dried FS exhibited C/N ratios of 8.56 (planted) and 7.16 (unplanted), alongside favourable organic matter and nutrient content, indicating its suitability for organic manure. The calorific value of the dried sludge was 14.76 MJ/ kg (planted) and 15.93 MJ/ kg (unplanted), suggesting potential for use as solid fuel. This treatment system can provide a sustainable FS management solution for rural areas of India, as it achieves overall treatment goals and enables resource recovery.
  • No Thumbnail Available
    Item
    A comparative analysis of composite and grab sampling methods for fecal sludge characterization: a case study from Pilani, India
    (Springer, 2025-08) Singh, Ajit Pratap
    Fecal sludge (FS) is biohazardous waste from on-site sanitation (OSS) containers like septic tanks and pit latrines, potentially harming the environment if discharged untreated. The design of the FS treatment system depends on its characteristic properties. Earlier and already existing characterization studies have shown that FS age, OSS type, water inclusion, and usage of additives significantly impact FS characteristics. There are various sampling methods to collect and characterize the sample. However, no study has compared the sampling methods of FS, which may potentially impact characterization. This study compares composite and grab sampling methods by analyzing 15 samples of each collected from the same FS discharge during a vacuum truck emptying vehicle in Pilani, a town in Rajasthan, India. The characterization of FS samples from OSS revealed variations between the two sampling methods, even though the samples were obtained from the same FS discharge. In composite sampling, total solids (TS) varied from 14.9 to 90 g/l (mean: 42.3 g/l, median: 33.4 g/l), and chemical oxygen demand (COD) varied from 16 g/l to 122.7 g/l (mean: 54.7 g/l, median: 42.7 g/l). While in grab sampling, TS varied from 12.1 to 91.5 g/l (mean: 36.2 g/l, median: 25.6 g/l), and COD varied from 8.7 g/l to 114.7 g/l (mean: 43.9 g/l, median: 29.3 g/l). A paired Wilcoxon signed-rank test shows that sampling methods significantly affect the TS (p = 0.041) and COD (p = 0.018) of FS samples.
  • No Thumbnail Available
    Item
    Spatiotemporal change analysis of urbanization in Gurugram district of Haryana, India, using a geospatial technique
    (Springer, 2024-07) Singh, Ajit Pratap
    Remote sensing and GIS play a very important role in monitoring, managing, and mapping the operation of natural resources. This study includes the Landsat 5 and Landsat 8 satellite imagery for the analysis of urban sprawl for the years 1999 and 2019, respectively, in the Gurugram (previously known as Gurgaon) district of Haryana, India. The methodology of the study follows by calculating the NDBI (normalized built-up index) spectral indices for extracting the built-up feature class from the Landsat time series data sets of 1999 and 2019. The aim of this study is to: (i). find out urbanization patterns in the area of interest and (ii). temporal change analysis, in particular, urban feature class from 1999–2019. The outcomes of the study illustrate a rapid urban sprawl in the region by the percent increase of 293%. In conclusion, the study findings suggest to secure a livable and resilient future for the residents of the region; policymakers and urban planners must embrace sustainable and integrated approaches to urban development that balance economic growth with environmental protection.
  • No Thumbnail Available
    Item
    Random tree classifier for land use classification in hilly terrain using sentinel 2 imagery: a case study of Almora town, Uttarakhand, India
    (Springer, 2024-07) Singh, Ajit Pratap
    Mountain landscapes are extremely complex and heterogeneous. These zones are highly sensitive and dynamic in nature. Rapid uncontrolled urbanization and population growth lead to severe environmental degradation in a hilly region. Due to the change in surface altitude and steep slopes, image processing in these regions is challenging. This study includes the sentinel 2B satellite imagery for classifying the Almora town situated in Uttarakhand state of India. The classification was performed by applying the object-based image analysis technique (OBIA) with a machine learning classifier. The study includes two scenarios of different image parameter training of the classifier using sentinel 2B satellite imagery. The major objectives of this study were to (1) define the optimal segmentation level for better image feature extraction using a multi-resolution segmentation approach, (2) find out the optimal image feature (mean, standard deviation (sd), and geometry) for better classification of LULC in the mountain region, and (3) evaluate the performance of a random tree (RT) machine learning (ML) classifier in assessing the land use land cover (LULC) analysis in Almora town of Uttarakhand, India. The study aims at exploring the potential of the RT algorithm with different parameter settings using different sets of image features to improve the overall accuracy of the classification. The results suggest that selecting proper sets of image features is essential for achieving high classification accuracy. The most satisfactory results have been obtained from scenario I, with an overall accuracy of 86.92. Overall, the study shows that the OBIA technique with ML classifier was effective and capable of achieving a high LULC classification accuracy in a mountainous landscape.
  • No Thumbnail Available
    Item
    Floating solar photovoltaic (FSPV) installations at varying heights: evaporation reduction estimation for major dams of the tropical region of Uttar Pradesh, India
    (IOP, 2025) Singh, Ajit Pratap; Jha, Shibani Khanra; Mittal, Ravi Kant
    Any tropical region is well known for its high levels of sunshine and is suitable for PV installations with the associated disadvantage of high evaporation rates. FSPV is an alternate approach for solar PV installations in such regions to harness maximum solar energy with the additional advantage of reducing evaporation from water bodies. The study on estimating the reduction in evaporation due to FSPV installations and associated panel height above the water surface is limited. This study aims to quantify the reduction in evaporation resulting from the deployment of floating solar photovoltaic (FSPV) systems above water surfaces. It also determines the panel height above water bodies to maximize evaporation reduction. These findings are then extended to evaluate the impact of FSPV installations on reducing evaporation over the major dams in the tropical region of Uttar Pradesh, India. The experimental results highlighted that the maximum evaporation reduction occurred from the water surface covered with a panel at a height of 300 mm above the water with an evaporation reduction of 23.44 %. The extrapolation of the study for 28 major dams of Uttar Pradesh, reveals an annual water saving of 92.56 million cubic meters (MCM) with FSPV coverage of 25%. Based on estimations, a 1 MWp FSPV installation considerable amount of water annually can fetch water for 67 individuals in a tropical region, assuming 100 lpcd. These research outcomes would provide valuable insights into FSPV technology and its potential to mitigate water evaporation, with implications for regional and national water and energy resource management policies.
  • No Thumbnail Available
    Item
    Developing strategic and staging optimization pathways for urban flood damage mitigation
    (Elsevier, 2025-10) Srinivas, Rallapalli; Singh, Ajit Pratap; Goonetilleke, Ashantha
    Despite significant advancements in flood risk assessment and damage monetization, research is lacking for simultaneously examining the impacts of the complexity of factors such as rising sea levels, changing rainfall patterns, and urbanization, on flood damage assessment. This study adopts an innovative staging procedure that progressively and strategically optimizes flood damage mitigation measures while addressing the uncertainties associated with the implementation of flood mitigation measures over three different time horizons (2040, 2070, and 2100), with each subsequent stage refined based on the constraints and optimal results of the previous stage. Using the Non-dominated Sorting Genetic Algorithm (NSGA II), the study compares 27 optimized pathways for mitigating flood damages, balancing investment costs and Average Annual Damage (AAD) reduction. The results demonstrate that the proposed approach achieves an AAD reduction of up to 2.89% in 2040, 4.03% in 2070, and 2.12% in 2100 under the most comprehensive mitigation pathways while balancing the costs. The study highlights cost-effective alternatives, such as combining dredging and permeable asphalt, achieving a 1.31% AAD reduction in 2040 with no additional costs. Compared to static single-stage mitigation policies, the proposed staging approach offers greater flexibility and efficiency in addressing dynamic urbanization and climate change scenarios. These results underline the trade-offs between cost and effectiveness, equipping policymakers with a robust decision-making framework to tailor flood mitigation strategies for diverse global contexts. Overall, this study significantly advances the strategic planning of urban flood damage mitigation, enabling adaptation to evolving environmental and socio-economic challenges.