Zahra Kalantari - Böcker

This book catalogs the evidence based on the social, economic and environmental effectiveness of Nature based Solutions (NbS) to face environmental challenges and simultaneously provide a better understanding of associated social-ecological interactions.NbS are reframing discussion and policy responses worldwide to environmental challenges. The concept builds on and complements other closely related concepts, such as the ecosystem approach, ecosystem services, ecosystem-based adaptation/mitigation, disaster risk reduction, sponge cities, and green/blue infrastructures. The quantification of existing NbS' effectiveness, their operationalization and replication in different environmental settings are presented here in such a way that allows them to be both widely accepted and incorporated in policy development and in practical implementation.Explores the nexus between Nature-based Solutions (NbS) and global SDG, thus leading future research and practice worldwide.Presents novel conceptualizations, pathways, applications, evidence-based cases, and experiential assessmentsOffers best practice portfolios for practitioners (city managers, policy-makers, civil servants, environmental engineers) to guide the practices of NbS towards SDG.

Natural Disasters Under Changing Climate: Modeling Strategies, Predictions, and Management is an essential textbook within the natural disaster prediction domain, functioning as a comprehensive book on natural disasters, and focusing on floods, landslides, earthquakes, dust storms, land subsidence, wildfire, sea level rise, drought, snow avalanches, debris flow, desertification, sand dune migration, and heatwaves. In addition to taking a range of natural disasters into account, it covers novel approaches in artificial intelligence and remote sensing and provides an overview of the different concepts of natural disasters perception and how geo-environmental, topo-hydrological, and edaphic variables are connected with their occurrences.The initial chapters of the book shed light on the main principles and mechanisms of disasters prediction and the application of artificial intelligence algorithms in natural disasters domain. They discuss the applicability of the predictive models in the natural hazards domain and how the understanding of disaster management can happen with the help of disaster susceptibility maps. The book then pivots into landslide susceptibility modeling under climate change and details the use of DInSAR as a powerful tool for studying the effects of earthquakes in various regions. Following that, dust storm frequency and intensity, and how these are impacted by climatic factors, as well as water and land use management, is discussed at length.Functions as a comprehensive textbook on natural disasters, focusing on floods, landslides, earthquakes, dust storms, land subsidence, wildfire, sea level rise, drought, snow avalanches, debris flow, and desertificationProvides unique and cutting-edge research on natural disaster predictionExplores novel approaches in the field of artificial intelligence and remote sensingPresents scientific frameworks for the spatial prediction of a wide suite of natural disaster types, with a focus on their specific triggers and processesOffers study questions and case studies for students and instructors

This book provides an overview of the typical nature-based solutions (NBS) used for flood mitigation at different scales and in different areas (e.g. from catchment to hillslope scale; from urban to coastal areas). NBS can provide several ecosystem services, such as water regulation and water quality enhancement, and as such offer relevant technical solutions to complement typical grey infrastructures to mitigate flood hazard and water quality problems. In recent years, political awareness and interest from the scientific community have led to increasing implementation of NBS worldwide.In light of this trend, this book provides valuable insights into the environmental aspects of NBS, particularly their effectiveness for flood and pollution mitigation, and discusses socio-economic aspects related to the implementation of NBS, including regulatory aspects, cost, and citizens’ perceptions of NBS. Compiling the latest research, the book furthers our understanding of the role of NBS for flood mitigation and its relation to environmental aspects, to guide scientists and stakeholders in future NBS projects. It is intended for the scientific community and stakeholders, such as spatial planners and landscape managers.Chapter "Nature-based solutions for flood mitigation and resilience in urban areas" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

This book provides an overview of the typical nature-based solutions (NBS) used for flood mitigation at different scales and in different areas (e.g. from catchment to hillslope scale; from urban to coastal areas). NBS can provide several ecosystem services, such as water regulation and water quality enhancement, and as such offer relevant technical solutions to complement typical grey infrastructures to mitigate flood hazard and water quality problems. In recent years, political awareness and interest from the scientific community have led to increasing implementation of NBS worldwide.In light of this trend, this book provides valuable insights into the environmental aspects of NBS, particularly their effectiveness for flood and pollution mitigation, and discusses socio-economic aspects related to the implementation of NBS, including regulatory aspects, cost, and citizens’ perceptions of NBS. Compiling the latest research, the book furthers our understanding of the role of NBS for flood mitigation and its relation to environmental aspects, to guide scientists and stakeholders in future NBS projects. It is intended for the scientific community and stakeholders, such as spatial planners and landscape managers.Chapter "Nature-based solutions for flood mitigation and resilience in urban areas" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.