Hydro-meteorological extremes and disasters / / Manish Kumar Goyal, Anil Kumar Gupta and Akhilesh Gupta, editors

• Pubblicazione: Singapore : , : Springer, , [2022]; ©2022
• Descrizione fisica: 1 online resource (333 pages)
• Disciplina: 551.6
• Soggetto topico: Climatic changes; Emergency management; Natural disasters
• Persona (resp. second.): GoyalManish Kumar; GuptaAnil Kumar; GuptaAkhilesh
• Nota di bibliografia: Includes bibliographical references.
• Nota di contenuto: Intro -- Foreword -- Acknowledgments -- Introduction -- Contents -- About the Editors -- Part I: Overview and Strategies -- 1: Hydro-meteorological Extremes and Disasters: Integrated Risk, Remediation and Sustainability -- 1.1 Introduction -- 1.2 Integrated Disaster Management: Concept and Scope -- 1.3 Disaster Management Models -- 1.3.1 Integration in DRR -- 1.3.1.1 Challenges of Increasing Disasters -- 1.3.1.2 Framework of Integrated Disaster Management Strategies -- 1.4 Initiative Taken for Integrated Disaster Management in India and Globally -- 1.5 Suggestions for Integrated Disaster Management Strategies -- 1.5.1 Proposed Approach of Integration for City Resilience -- References -- 2: Public Policy in Environment and Sustainability Strategies: Global & -- National Scenario -- 2.1 Introduction -- 2.2 Policy Implementation -- 2.3 History of the International Environment Policy -- 2.4 Policy Initiatives by The Government of India -- 2.4.1 Indian Policies Towards Environmental Protection -- 2.5 Indian Policies Towards Disaster Management -- 2.5.1 Hydro-meteorological Domains and Public Policy -- 2.5.2 Climate Finance and India´s Nationally Determined Contribution -- 2.5.3 One Health Approach -- 2.5.4 Corporate Sustainability Policy -- 2.5.5 Policy Instruments in Environment Concerns -- 2.5.6 Present Policy Scenarios in India -- 2.5.7 Way Forward -- References -- 3: Climate Finance at International and National Level: Needs, Drivers and Sources -- 3.1 Introduction -- 3.2 An Overview of Climate Finance at Global Level -- 3.3 Allocation of Climate Finance -- 3.4 Climate Finance in India -- 3.4.1 Importance of Climate Finance in India -- 3.5 Climate Insurance -- 3.6 Way Forward -- References -- 4: Economic Impacts of Hydroclimatic Extremes and Disasters in India -- 4.1 Background -- 4.1.1 Objective of the Present Study. ; 4.2 Observations at National and Sub-National Levels -- 4.3 Evidence from Vulnerable Households -- 4.3.1 Poor Infrastructure Development -- 4.3.2 Agriculture Is the Main Occupation -- 4.3.3 Disaster-Induced Migration -- 4.3.4 Loss in Cropped Land -- 4.4 Conclusions and Policy Implications -- References -- Part II: Tools and Techniques -- 5: Remote Sensing Applications in Drought Monitoring and Prediction -- 5.1 Introduction -- 5.1.1 Remote Sensing -- 5.1.2 Drought Concept -- 5.2 Drought Monitoring and Prediction -- 5.2.1 Drought Prediction Approaches -- 5.2.1.1 Statistical Approach -- 5.2.1.2 Dynamical Approach -- 5.2.1.3 Hybrid Approach -- 5.3 Remote Sensing in Drought Monitoring and Prediction -- 5.3.1 Precipitation -- 5.3.2 Soil Moisture -- 5.3.3 Evapotranspiration -- 5.3.4 Surface Water -- 5.3.5 Ground Water -- 5.3.6 Vegetation -- 5.4 Challenges and Future Perspectives -- 5.5 Case Study -- 5.5.1 Background -- 5.5.2 Study Area -- 5.5.3 Data Used -- 5.5.4 Methodology -- 5.5.5 Results and Discussion -- 5.6 Summary -- References -- 6: Disaster Early Warning Communication Systems -- 6.1 Introduction -- 6.2 Disaster Management Scenario in India -- 6.3 Early Warnings for Disaster Risk Reduction -- 6.4 Early Warning Communication Procedures and Systems -- 6.5 Technological Tools for EWS -- 6.6 Geo-spatial Information Systems -- 6.7 Satellites for Remote Sensing and Earth Observation and EW Communication -- 6.8 Disruptive Technologies -- 6.9 Early Warning and Forecasting Networks in India -- 6.10 Early Warning Communication -- 6.11 Conclusion -- Further Readings -- 7: Spatial Data Infrastructure for Suitable Land Identification for Government Projects -- 7.1 Introduction -- 7.2 Related Work -- 7.3 Spatial Data Infrastructure (SDI) for Land, Rainfall and Temperature Detailing. ; 7.3.1 Spatial Data Infrastructure Architecture for Land, Rainfall and Temperature Detailing -- 7.3.2 LULC Detailing by Using Satellite Images (Landsat) -- 7.3.3 LULC Detailing by Using Topo-Sheets from Survey of India (SoI) -- 7.3.4 Rainfall Detailing by Using Indian Meteorological Department Data -- 7.3.5 Temperature Detailing by Using Indian Meteorological Department Data -- 7.3.6 Weighted Sum Overlay for Decision Making or Selection of Piece of Land -- 7.4 Verification, Accuracy and Use of this Research -- 7.4.1 Verification Using Actual Ground Control Points -- 7.4.2 LULC Accuracy Calculation (How Accurate Is Our Classification) -- 7.4.2.1 Overall Accuracy -- 7.4.2.2 Errors of Omission -- 7.4.2.3 Commission Error -- 7.4.2.4 Producer´s Accuracy -- 7.4.2.5 User´s Accuracy -- 7.4.2.6 Kappa Coefficient -- 7.4.3 Significance of This Research to Federal and Regional Government Agencies -- 7.5 Summary -- References -- 8: Role of Stable Isotopes in Climate Studies - A Multi-archive Approach Focusing on Holocene to Anthropocene Records -- 8.1 Introduction -- 8.2 Basics of Isotopes -- 8.2.1 Stable Isotopes of Carbon (δ13C), Oxygen (δ18O), Nitrogen (δ15N) and Hydrogen (δD) -- 8.3 Climate Extremities from Latest Pleistocene to Present -- 8.3.1 Younger Dryas (YD) -- 8.3.2 8.2 ka Cold Event -- 8.3.3 4.2 ka Cold Event -- 8.3.4 Roman Warm Period (RWP) -- 8.3.5 Dark Age Cold Period (DACP) -- 8.3.6 Medieval Climate Anomaly (MCA) -- 8.3.7 Little Ice Age (LIA) -- 8.4 Challenges and outlook -- 8.5 Conclusion -- References -- 9: Integration of Climate Model & -- Hydrology Model-Tools, Bias-Correction, Downscaling, & -- Future Focus -- 9.1 Introduction -- 9.2 Downscaling Techniques -- 9.3 Integration of GCM and Hydrological Model -- 9.4 Bias-Correction in Climate Change Impact Analysis -- 9.5 Uncertainty Analysis in Climate Change Impact Assessment. ; 9.6 Case Study -- 9.6.1 Study Area -- 9.6.2 Climate and Rainfall -- 9.6.3 Climate Model Data -- 9.6.4 Methodology -- 9.6.5 Multimodel Uncertainty Analysis -- 9.6.6 Bias-Correction -- 9.6.7 Hydrological Modelling -- 9.6.8 Climate Change Impact Analysis -- 9.7 Concluding Remarks and Future Focus -- References -- 10: Analysis of Precipitation Extremes at the Intra-seasonal Scale Using a Regional Climate Model -- 10.1 Introduction -- 10.2 Data and Methodology -- 10.2.1 Model and Data Used -- 10.2.2 Methodology -- 10.3 Results and Discussion -- 10.3.1 Intra-seasonal Variability of the Indian Summer Monsoon -- 10.3.2 Analysis of Low and High Frequency Modes -- 10.4 Conclusion -- References -- 11: Geospatial BigData and Its Applications -- 11.1 Introduction -- 11.2 Geospatial Data as a Big Data -- 11.2.1 Features of BigData -- 11.2.2 Gap Analysis of Geo-spatial Data -- 11.2.3 Categorization of Geospatial Big Data -- 11.2.3.1 Raster Data -- 11.2.3.2 Vector Data -- 11.2.4 Pre-processing -- 11.2.4.1 Pre-processing Architecture -- 11.2.5 Feature Extraction -- 11.2.5.1 Curse of Dimensionality -- 11.2.5.2 Dimensionality Reduction Techniques -- 11.2.5.3 Principal Component Analysis -- 11.2.5.4 Linear Discriminant Analysis -- 11.2.5.5 Independent Component Analysis Algorithm (ICA) -- 11.3 Applications of Geospatial Big Data for Monitoring Hazards -- 11.4 Case Study -- 11.4.1 Flood Change Detection Using Satellite Images -- 11.4.2 Wind Power Prediction -- 11.5 Summary -- References -- Part III: Case Studies -- 12: Quantitative Assessment of Impact of Climate Change on Crop Yield over Sikkim and Central Region of India -- 12.1 Introduction -- 12.2 Study Area and Data Utilized -- 12.2.1 Study Area Description -- 12.2.2 Meteorological Data Utilized -- 12.3 Methodology -- 12.3.1 Crop Yield Simulation Using Aquacrop Model. ; 12.3.2 Model Performance Evaluation Using RMSE and Coefficient of Determination (r2) -- 12.3.3 Evaluating Uncertainty of GCMs for Future Yield Simulation -- 12.3.4 Adaptation Strategy to Combat Impact of Climate Change on Crop Yield -- 12.4 Results and Discussion -- 12.4.1 Aquacrop Model Efficiency During Calibration and Validation for the Sikkim Region -- 12.4.2 Aquacrop Model Efficiency During Calibration and Validation for the Central Region of India -- 12.4.3 Future Simulated Yield of Crops -- 12.4.3.1 Sikkim Region -- 12.4.3.2 Central Region of India -- Adaptation Strategy by Shifting Sowing Dates -- 12.5 Conclusions -- References -- 13: Understanding of Future Water Challenges in a River Basin Under Ensemble of CORDEX Simulated Projections -- 13.1 Introduction -- 13.2 Study Area -- 13.3 Data Used -- 13.4 Methodology -- 13.5 Results and Discussion -- 13.5.1 Drought Occurrence and Temporal Extent -- 13.5.2 Drought Trend -- 13.5.3 Drought Concurrence -- 13.6 Conclusion -- References -- 14: Drought as a Disaster and Its Characterization over Central India -- 14.1 Introduction -- 14.2 Drought: The Creeping Hazard -- 14.2.1 Drought Types: Meteorological, Agricultural, and Hydrological Drought Types -- 14.2.1.1 Meteorological Drought -- 14.2.1.2 Agricultural Drought -- 14.2.1.3 Hydrological Drought -- 14.2.1.4 Socio-Economic Drought -- 14.2.2 Drought Indices -- 14.2.2.1 Standardized Precipitation Index (SPI) -- 14.2.2.2 Standardized Runoff Index (SRI) -- 14.2.2.3 Standardized Soil Moisture Index (SSI) -- 14.2.2.4 Vegetation Condition Index (VCI) -- 14.2.3 Impact of Droughts -- 14.2.3.1 Environmental Impact -- 14.2.3.2 Economic Impact -- 14.2.3.3 Social Impact -- 14.3 Case Study over Central India -- 14.3.1 Study Area and Data Used -- 14.3.2 Drought Frequency, Mean Areal Extent, and Mean Duration -- 14.3.3 Drought Trend -- 14.3.4 Drought Concurrence. ; 14.4 Drought Mitigation.
• Titolo autorizzato: Hydro-meteorological extremes and disasters
• ISBN: 981-19-0725-0
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910624398503321
• Lo trovi qui: Univ. Federico II
• Serie: Disaster resilience and green growth.