Hydropower is a significant renewable energy source for Nepal, contributing to its electricity generation and economic development. However, climate change-induced fluctuations in river discharge concerns long-term hydropower sustainability. This study investigates the effects of climate change on the hydropower potential of Nepal’s Sunkoshi basin using a physically based hydrological approach (SWAT) compared with a machine-learning method (Bi-directional LSTM). In the face of increasing global energy consumption and calls for sustainable development, the paper utilizes long historical hydrological records (1980–2015) and future climates in the simulation of river flow for the period of 2024–2050. While the physically realistic data-driven SWAT approach captures physical watershed processes, the BiLSTM exploits the pattern of historical flow for future flow forecast. Both models forecast a nearly 48% reduction in the average flow in the historical period, with significant rises in the duration of low flow with total hydrological variability. Although the correlation coefficient (r = 0.99) for the relationship between the two approaches in predicting the yields of hydropower energy is very high, the results in the forecast of events at extremes conflict: while the SWAT overestimates the peak flows, the BiLSTM offers smoother curves. The paper emphasizes the contribution of multi-model approaches towards hydrological forecasting and highlights the importance of planning for adaptation in the face of changing climatic conditions, for the requirement of adaptation measures, investment in resilient infrastructure, as well as updating policies to maximize the utilization of hydropower in the face of changing climatic conditions. The SWAT model achieved strong calibration performance with R2 = 0.91 and Nash-Sutcliffe Efficiency (NSE) = 0.82, while the BiLSTM model demonstrated superior short-term accuracy with Test MSE = 0.0006, MAE = 0.0099, and RMSE = 0.0246. Energy output projections suggest hydropower generation could decline significantly, emphasizing the need for resilient infrastructure, adaptive policy reforms, and hybrid renewable energy integration. This study underscores the necessity of multi-model approaches for hydrological forecasting and provides critical insights for climate-resilient hydropower planning in Nepal. The findings are instrumental for policymakers, engineers, and researchers aiming to enhance energy security and sustainable development. In this study, the rationale for selecting SWAT lies in its strength to interpret physical watershed processes, while BiLSTM was chosen for its ability to capture short-term temporal dependencies in hydrological time series. The regional significance of this study is emphasized by Nepal’s reliance on hydropower for over 90% of electricity, making accurate discharge forecasting vital for national energy security.

Nepal’s high seismic vulnerability necessitates stringent design codes to mitigate infrastructure risks. This study compares a regular reinforced concrete frame under Nepal’s NBC 105:2020 and India’s IS 1893 (part 1):2016 using finite element modeling in ETABS and SAP2000 commercial software, incorporating stiffness modifiers prescribed in the codes. Seismic parameters are compared in both ETABS and SAP2000, and for design forces and reinforcement requirements, only ETABS is used. Seismic analyses employed Equivalent Static and Response Spectrum methods. Results reveal NBC 105:2020 mandates double the base shear compared to IS 1893:2016, with lateral displacements surging by 50.6–66.6% under static analysis and 106–108% under dynamic analysis. Drift patterns mirrored displacement trends, showing similar percentage increases. Double base shear, amplified lateral displacements and drifts, consistent across both software analysis approaches, underscore NBC 105:2020’s heightened design forces and reinforcement demands, particularly in lower floors. For beams, NBC 105:2020 required 12.7% more reinforcement, 11.6% higher moments, 110% lower torsion while maintaining comparable shear forces. Columns under NBC exhibited 79.78% higher axial forces, Floor-wise fluctuation in biaxial moments and 10.6% more reinforcement, with lower floors disproportionately impacted. This study suggests that municipalities and engineers in Nepal to follow the NBC code. While NBC 105:2020’s stricter seismic provisions—requiring more robust structural systems, amplified design forces, and higher reinforcement demands compared to IS 1893 (Part 1):2016—escalate construction costs, its conservative approach ensures enhanced seismic resilience, critical for high-seismic-risk regions like Nepal.

A 3-hinged stiffening girder is a structural element used in suspension bridges to provide additional stability and stiffness. It consists of a girder supported by three hinges typically at the two ends and at the centre allowing it to accommodate temperature variations, deflections, and dynamic loads while distributing stresses efficiently across the structure. This research aims to conduct a comprehensive comparative analysis of the equivalent uniform distributed load (UDL) transmitted through a 3-hinged stiffening girder cable with varying numbers of suspenders. The study has delved into the theories and definitions associated with the behaviors of suspended cables, exploring how different configurations of suspenders impact the distribution of loads and the overall structural performance of the system. The significance lies in achieving an optimal balance between load-bearing capacity, stability, and material efficiency. An insufficient number of suspenders may lead to uneven load distribution, potentially causing localized stress concentrations or overloading certain elements. On the other hand, an excessive number of suspenders may result in unnecessary complexity and increased construction costs without proportional benefits in load distribution. Understanding the influence of the number of suspenders on structural behaviors is essential for designing cost-effective and resilient suspended cable systems.