Journal of Geotechnical Studies

Revisiting Indigenous Wisdom for Sustainable Construction: A Conceptual and Analytical Examination of Khona’s Maxim in Contemporary Site Selection

Mian Md Jawad Ibne Iqbal — 2026-04-07

The increasing demand for sustainable construction has highlighted the critical importance of site selection in ensuring structural stability, environmental suitability, and long-term resilience. While contemporary approaches rely on geotechnical investigations, hydrological modelling, and Geographic Information Systems (GIS), these methods are often data-intensive and may not fully capture localised environmental variability, particularly in data-constrained regions. In this context, Traditional Ecological Knowledge (TEK) offers valuable, place-based insights derived from long-term human–environment interaction. This study examines the relevance of Khona’s maxim—an element of South Asian indigenous knowledge—in informing construction site selection. Adopting a qualitative-dominant conceptual research design, the study develops a multi-dimensional analytical framework that translates indigenous environmental guidance into engineering-relevant parameters, including soil stability, drainage efficiency, and water-related risk. A structured comparative analysis is conducted to evaluate the alignment between Khona’s principles and established geotechnical and hydrological criteria. The findings reveal a strong conceptual convergence between indigenous knowledge and modern engineering practices, particularly in promoting balanced terrain conditions, effective drainage, and reduced flood vulnerability. The study demonstrates that Khona’s maxim encodes empirically grounded environmental insights that align with scientific understanding, despite being expressed in qualitative terms. The research contributes by advancing beyond descriptive interpretations of TEK and proposing a structured framework for its integration into construction decision-making. However, the study is limited by its conceptual nature and lack of empirical validation. Future research should incorporate case studies, geotechnical field testing, and hydrological modelling to validate the proposed framework. Overall, the study highlights the potential of integrating indigenous knowledge with scientific approaches to support more holistic, context-sensitive, and resilient construction practices, particularly in data-scarce environments.

Integrated Hydrological and Groundwater Modelling for Sustainable Water Resource Management in the Kabini River Basin: A Comprehensive Review

Ramya B. — 2026-03-25

This review paper presents an integrated hydrological–groundwater modelling framework to evaluate surface-subsurface interactions in the Kabini River Basin. The synthesis highlights its role in sustainable water resource management under climate and anthropogenic pressures. An integrated surface water-groundwater modelling framework combining hydrological and groundwater models is reviewed to assess hydrological processes, groundwater dynamics, and sustainable water resource management strategies in the Kabini River Basin.” Integrated management of water resources in river basins needs a comprehensive understanding of surface water and groundwater interactions, especially in areas where water demand is increasing, land use patterns are changing, and the climate is fluctuating. The Kabini River Basin, a large sub-basin of the Cauvery River Basin in southern India, is of prime importance for irrigation, drinking water supply, hydropower, and sustainable ecosystems. But increasing human-induced pressures and spatial-temporal variability in water availability have accentuated the need for scientifically sound decision-support systems. This review provides a comprehensive synthesis of integrated hydrological and groundwater modelling techniques for water resource management in river basin scales, particularly in the Kabini River Basin. The review critically assesses the popular surface water models (such as SWAT, HEC-HMS, MIKE SHE, and VIC), groundwater models (such as MODFLOW and its derivatives), and fully or loosely coupled integrated models that couple surface and subsurface processes. The discussion focuses on the model structure, data requirements, calibration and validation procedures, and the ability of each modelling strategy to capture essential hydrological processes such as recharge, base flow contribution, river-aquifer exchange, and groundwater abstraction. Recent advances that incorporate remote sensing data, geographic information systems (GIS), climate model outputs, and machine learning algorithms are also reviewed to emphasise their importance in enhancing model accuracy and mitigating data uncertainties in data-scarce basins.

Machine Learning and Geospatial Specialist Mapping-based Severe Disease Prediction System

Eknath Patil — 2026-04-13

In the traditional healthcare system, early detection/diagnosis of diseases is a major concern, especially when it comes to chronic and life-threatening diseases. Although common disease conditions can be fluently diagnosed and treated on time, severe disease conditions need to be diagnosed earlier to ensure effective treatment. Recent advancements in Artificial Intelligence (AI) and Machine Learning (ML) have significantly improved the accuracy of disease prediction and supported better clinical decision-making. However, most existing ML-based predictive models are developed to detect or predict only a single specific disease profile. They cannot usually analyse and predict multiple diseases within a single integrated system. This study presents an advanced AI-ML integrated disease prediction platform that can diagnose both common and severe disease conditions on a single platform. The proposed platform integrates multiple machine learning models for different disease conditions into a single platform, divided into separate sections according to complaint types. The platform also enhances usability by recommending suitable medical specialists according to the complaint based on the user’s geographical location, therefore providing timely medical consultation. The proposed frame, which combines lifestyle, symptom and medical history-based diagnosing algorithms, is a scalable and doable result for the current digital healthcare system.

Failure Mechanisms, Design Optimization, and Performance Enhancement of Skirted Foundations

Prof. Samirsinh P Parmar — 2026-04-06

Skirted foundations have emerged as an efficient alternative to conventional shallow foundations due to their enhanced bearing capacity, improved resistance to lateral loads, and superior performance in weak and heterogeneous soils. This study presents a comprehensive investigation into the failure mechanisms, design optimization, and performance enhancement of skirted foundations, based on both analytical interpretation and the synthesis of existing experimental findings. The failure mechanisms are systematically classified into foundation failure and soil failure, including base footing failure (punching shear and settlement), skirt failure (separation and deflection), bearing failure, and soil movement. A modified analytical framework is proposed by extending classical bearing capacity theory to incorporate soil confinement and skirt–soil interaction effects. The derived formulation demonstrates that the ultimate bearing capacity is significantly influenced by skirt depth-to-width ratio, embedment depth, soil properties, and interface friction characteristics. Parametric analysis indicates that increasing skirt depth enhances confinement and shifts the failure mode from general shear to confined plug failure and, eventually, punching failure. The results further highlight that the friction angle plays a dominant role in capacity enhancement, while cohesion contributes linearly. Circular skirted foundations exhibit superior performance due to uniform stress distribution and the mobilisation of hoop stress. The study also outlines key design optimization strategies, including appropriate selection of skirt geometry, soil improvement techniques, and dynamic analysis for seismic and offshore conditions. The proposed mechanistic approach provides a rational basis for understanding failure evolution and offers practical guidance for the safe and efficient design of skirted foundations in complex geotechnical environments.

Seaport Decentralisation Policy and Regional Development: Lessons for Nigeria

U. J. Jimmy — 2026-02-24

This study investigates the strategic relationship between seaport decentralisation policies and balanced regional development, offering a critical analysis of its implications for the Nigerian maritime sector. Utilizing a robust theoretical framework anchored in Fiscal Federalism and New Economic Geography (NEG), the research explores how the devolution of port authority can dismantle “core-periphery” bottlenecks and foster new economic growth poles. The study demonstrates that centralisation leads to catastrophic diseconomies, such as the chronic congestion currently stifling the Lagos maritime corridor. Through a comparative analysis of international best practices, the paper highlights successful models from the United States, Germany, and China, where local autonomy has catalyzed specialization and competitive efficiency. A critical evaluation of Nigeria’s 2006 port concessioning reveals that while private-sector participation improved, the systemic reliance on a centralized administrative monopoly persists, leaving Eastern and Delta ports underutilized. The findings suggest that for Nigeria to leverage its 853km coastline effectively, it must transition toward a “Landlord” governance model. The paper concludes with specific policy recommendations, including comprehensive legislative reform of the Nigerian Ports Authority Act, strategic infrastructure investment in hinterland rail connectivity, and targeted incentives for private-sector participation. Implementing these reforms will unlock the dormant economic potential of sub-national regions, ensuring long-term maritime security and national prosperity.