Bøker i Springer Transactions in Civil and Environmental Engineering-serien

This book discusses design aspects of steel fiber-reinforced concrete (SFRC) members, including the behavior of the SFRC and its modeling.

This book intends to bring together and integrate the subject matter of water quality. The book covers aspects of water related to climate change, emerging aspects of engineering sciences, bio-geochemical sciences, hydro geochemistry, river management and morphology, social sciences, and public policy.

This book presents the proceedings of the International Conference on Health, Safety, Fire, Environment, and Allied Sciences. The volume comprises content from leading scientists, engineers, and policy makers discussing issues relating to industrial safety, fire hazards and their management in industry, forests and other settings.

On the other hand, Veerbhadraiah and Jain have provided a status on environmental management services at Maitri station Additionally Tiwari has provided details on the new Indian Research Base 'Bharti' at Larsemann Hills region.

This book presents the proceedings of the International Conference on Health, Safety, Fire, Environment, and Allied Sciences (HSFEA 2018).

This book comprises the proceedings of the International Conference on Green Buildings and Sustainable Engineering (GBSE 2019), which focused on the theme "Ecotechnological and Digital Solutions for Smart Cities".

This volume takes a multidisciplinary approach to study and evaluate the global human vulnerability to the exposure of contaminants of emerging concern (CECs) in the natural environment.

This book talks about the dynamics of the surface water-groundwater contaminant interactions under different environmental conditions across the world.

On the other hand, Veerbhadraiah and Jain have provided a status on environmental management services at Maitri station Additionally Tiwari has provided details on the new Indian Research Base 'Bharti' at Larsemann Hills region.

This book highlights cutting-edge applications of machine learning techniques for disaster management by monitoring, analyzing, and forecasting hydro-meteorological variables.