GLORIA

GEOMAR Library Ocean Research Information Access

feed icon rss

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    Online Resource
    Online Resource
    New York :Cambridge University Press,
    Keywords: Floods-Risk assessment. ; Electronic books.
    Description / Table of Contents: A comprehensive interdisciplinary exploration of climate risks to water security, for students of hydrology, resource management, climate change, and geography, and for researchers, civil and environmental engineers, and water management professionals concerned with water-related hazards, water cycles, and climate change.
    Type of Medium: Online Resource
    Pages: 1 online resource (504 pages)
    Edition: 1st ed.
    ISBN: 9781108847841
    DDC: 333.91
    Language: English
    Note: Cover -- Half-title -- Title page -- Copyright information -- Contents -- List of Contributors -- Preface -- Acknowledgements -- Part I Water-Related Risks under Climate Change -- 1 Pluvial, Fluvial and Coastal Flood Risks and Sustainable Flood Management in the Pearl River Delta under Climate Change -- 1.1 Introduction -- 1.2 Localized Precipitation Extremes and Pluvial Flood Risks in the PRD under Climate Change: Observations and Projections -- 1.2.1 Past Observations and Analyses -- 1.2.2 Future Projections -- 1.3 Upstream River Flow and Fluvial Flood Risks in the PRD under Climate Change: Observations and Projections -- 1.3.1 Past Observations and Analyses -- 1.3.2 Future Projections -- 1.4 Coastal Flood Hazards in the PRD under Climate Change: Observations and Projections -- 1.4.1 Past Observations and Analyses -- 1.4.2 Future Projections -- 1.5 Urbanization and Sustainable Flood Management in the PRD -- 1.5.1 Impacts of Urbanization on Flood Risks -- 1.5.2 Sustainable Flood Management -- 1.6 Summary -- References -- 2 Flooding Risk in the Lancang-Mekong River Basin under Global Change -- 2.1 Introduction -- 2.2 The Lancang-Mekong River Basin -- 2.3 Data and Methods -- 2.3.1 Data -- 2.3.2 SPI-3 -- 2.3.3 VIC Model -- 2.3.4 Definition of the Flood Events -- 2.4 Results -- 2.4.1 Changes of SPI-3 -- 2.4.2 VIC Model in the LMRB -- 2.4.3 Impact of Climate Change on Streamflow -- 2.4.4 Impact of Climate Change on Flood Events -- 2.5 Discussion -- 2.6 Conclusion -- Notes -- References -- 3 Spatial Drought Patterns in East Africa -- 3.1 Introduction -- 3.2 Materials and Methods -- 3.2.1 Research Area -- 3.2.2 Drought Index, Dataset and Study Period -- 3.2.3 Spatial Drought Analysis Procedures -- 3.2.3.1 Drought Characterization -- 3.2.3.2 Drought Severity Level Detection -- 3.3 Results and Discussion -- 3.3.1 Long-Term Analysis of Precipitation. , 3.3.2 Drought Characterization -- 3.3.2.1 Spatial Drought Duration -- 3.3.2.2 Spatial Drought Frequency -- 3.3.2.3 Spatial Drought Intensity -- 3.3.3 Long-Term Spatial Trends -- 3.3.4 Historical Severe Drought Events -- 3.3.4.1 The 1973-1974 Drought -- 3.3.4.2 The 1984-1985 Drought -- 3.3.4.3 The 2010-2011 Drought -- 3.3.5 Impacts of the Drought Events -- 3.4 Conclusion -- References -- 4 Assessment of Global Water Erosion Vulnerability under Climate Change -- 4.1 Introduction -- 4.2 Materials and Methods -- 4.2.1 RUSLE Model -- 4.2.1.1 Rainfall Erosivity Factor (R) -- 4.2.1.2 Soil Erodibility Factor (K) -- 4.2.1.3 The Slope Length and Steepness Factor (LS) -- 4.2.1.4 The Land Cover and Management Factor (C) -- 4.2.2 Data Analyses -- 4.2.2.1 Spatial Analyses -- 4.2.2.2 Ordinary Least Squares Linear Regression -- 4.3 Results -- 4.3.1 Model Validation -- 4.3.2 Spatial Characteristics of Global Water Erosion Vulnerability -- 4.3.3 Global Water Erosion Change Associated with Various Land Uses -- 4.3.4 Effects of SDII on Water Erosion -- 4.4 Discussion -- 4.4.1 Impacts of Rainfall Change on Water Erosion -- 4.4.2 Impacts of Other Factors Associated with Climate Change -- 4.4.3 Limitations of this Study -- 4.5 Conclusions -- References -- 5 Water Erosion and Its Controlling Factors in the Anthropocene -- 5.1 Introduction -- 5.2 Water Erosion Processes and their Relations to Climate Change -- 5.2.1 Raindrop Splash Erosion -- 5.2.2 Inter-rill and Rill Erosion Processes -- 5.2.3 Ephemeral Gully Erosion -- 5.2.4 Permanent Gully Erosion -- 5.2.5 From Hillslope to River System -- 5.2.6 Other Agents Coupled with the Water Erosion Process -- 5.3 Water Erosion Control Practices -- 5.3.1 Biological Techniques -- 5.3.2 Engineering Methods -- 5.3.3 Tillage Practices -- 5.4 Water Erosion under Future Climate Risk. , 5.4.1 Direct Impacts of Climate Change: Change in Rainfall Erosivity -- 5.4.2 Indirect Climate Change Impact: Change in Land Use and Land Cover -- 5.5 Future Research Needs -- References -- 6 Climate Change Impacts on Saltwater Intrusion into Coastal Aquifers -- 6.1 Introduction -- 6.2 Theory -- 6.3 Method -- 6.3.1 Finite-Difference Method -- 6.3.2 Finite-Element Method -- 6.4 Case Study -- 6.4.1 Study Area and Model Domain -- 6.4.2 Model Development -- 6.4.2.1 Spatial Discretization -- 6.4.2.2 Temporal Discretization -- 6.4.2.3 Parameters -- 6.4.2.4 Boundary Conditions -- 6.4.2.5 Initial Conditions -- 6.4.2.6 Calibration -- 6.4.3 Results and Discussion -- 6.4.3.1 Sea-Level Rise Impacts on Saltwater Intrusion -- 6.4.3.2 Storm Surge Impacts on Saltwater Intrusion -- 6.4.3.3 Uncertainty Analysis -- 6.5 Mitigation Processes -- References -- Part II Climate Risk to Human and Natural Systems -- 7 Observed Urban Effects on Temperature and Precipitation in Southeast China -- 7.1 Introduction -- 7.2 Data -- 7.3 Methodology -- 7.4 Trends and Mean Values of Temperature and Precipitation -- 7.5 Urban Effect on Temperature -- 7.6 Urban Effect on Precipitation -- 7.7 Discussion -- 7.8 Conclusions -- Notes -- References -- 8 Vegetation Dynamics, Land Use and Ecological Risk in Response to NDVI and Climate Change in Nepal -- 8.1 Introduction -- 8.2 Research Approach and Methods -- 8.2.1 Data -- 8.2.2 Methods -- 8.3 Results -- 8.3.1 Spatial and Temporal Vegetation Dynamics -- 8.3.1.1 Spatio-Temporal Trends and Net NDVI Changes -- 8.3.2 Land Use Land Cover Change and HFP -- 8.3.3 Ecological Risk based on NDVI and Climate -- 8.4 Discussion -- 8.5 Conclusion -- References -- 9 Climate Warming Induced Frozen Soil Changes and the Corresponding Environmental Effect on the Tibetan Plateau: A Review -- 9.1 Introduction -- 9.2 Climate Warming Influence on Frozen Ground. , 9.2.1 Ground Temperature Changes -- 9.2.2 Soil FT Cycles -- 9.2.3 Frozen Ground Distribution -- 9.2.4 Active Layer Thickness -- 9.3 Environmental Effects -- 9.3.1 Vegetation Degradation -- 9.3.2 Desertification -- 9.3.3 Soil Erosion -- 9.3.4 Carbon Emission -- 9.3.5 Infrastructure Project -- 9.4 Conclusion -- References -- 10 A Review of the Effects of Climate Extremes on Agriculture Production -- 10.1 Introduction -- 10.2 Climate Change and Climate Extremes -- 10.2.1 Heat Extremes -- 10.2.2 Droughts -- 10.2.3 Climate Models -- 10.2.4 Climate Data Sets -- 10.3 The Effects of Climate Extremes on Yields -- 10.3.1 The Effects of High Temperature on Crop Growth -- 10.3.2 The Effects of Drought on Crop Growth -- 10.3.3 Recent Research on the Effects of Climate Extremes on Yield -- 10.3.4 The Indices of Drought -- 10.3.5 Approaches to Assess the Impacts of Climate Extremes -- 10.4 Adaptation Measures to Mitigate Yield Loss -- 10.5 Conclusion -- Note -- References -- 11 Agricultural Water Use Estimation and Impact Assessment on the Water System in China -- 11.1 Introduction -- 11.2 Methodology -- 11.2.1 The Model -- 11.2.2 Green and Blue Water Uses Estimation -- 11.2.3 Temporal Variabilities and Spatial Patterns -- 11.2.4 Impact Assessment -- 11.3 Study Area and Data Sets -- 11.3.1 Study Area -- 11.3.2 Data Sets -- 11.4 Results -- 11.4.1 Temporal Variability of Green and Blue Water Uses -- 11.4.2 Spatial Patterns of Green and Blue Water Uses -- 11.4.3 Impact Assessment of Agricultural Water Use on the Water System -- 11.5 Discussion -- 11.5.1 Uncertainty -- 11.5.2 Implications for Agricultural Water Resources Management -- 11.6 Conclusions -- References -- 12 Impact of Inter-Basin Water Transfer on Water Scarcity in Water-Receiving Area under Global Warming: A Case Study of the South-to-North Water Diversion Project -- 12.1 Introduction. , 12.2 South-to-North Water Diversion Project: A Primer -- 12.3 Water-Receiving Area of SNWD: Huang-Huai-Hai Region -- 12.4 Data and Methods -- 12.4.1 Data -- 12.4.2 Methods -- 12.4.2.1 Bias-Adjustment for Runoff, Groundwater Recharge and Irrigation -- 12.4.2.2 Available Water Supply -- 12.4.2.3 Sectoral and Total Water Demand -- 12.4.2.4 Impact of the SNWD Project on Water Supply Risk -- 12.5 Results -- 12.5.1 Projected Changes of Water Supply -- 12.5.2 Projected Changes of Sectoral and Total Water Demand -- 12.5.3 Impact of the SNWD Project on Water Supply Risk -- 12.6 Discussions and Conclusions -- Note -- References -- 13 Broadening and Deepening the Rainfall-Induced Landslide Detection: Practices and Perspectives at a Global Scale -- 13.1 Introduction -- 13.2 Practices for Global Rainfall-Induced Landslide Detection -- 13.2.1 Landslide Datasets Compilation -- 13.2.2 Landslide Susceptibility Analysis -- 13.2.3 Triggering Threshold Identification -- 13.3 Data and Methods -- 13.3.1 Environmental Factors and Landslide Datasets -- 13.3.2 Triggering Rainfall Identification for Landslide Events -- 13.3.3 Modelling for Global Distributed Rainfall Thresholds -- 13.4 Results -- 13.4.1 Characteristics of Triggering Rainfall Events -- 13.4.2 Multiple Linear Regression Model for Global Distributed Rainfall Thresholds -- 13.4.3 Model Application -- 13.5 Discussions and Conclusion -- Notes -- References -- 14 Estimating Aquifer Depth in Arid and Semi-arid Watersheds using Statistical Modelling of Spectral MODIS Products -- 14.1 Introduction -- 14.2 Materials and Methods -- 14.2.1 Study Area -- 14.2.1.1 Sarvestan Plain -- 14.2.1.2 Lamerd Plain -- 14.2.2 Research Data -- 14.2.2.1 Field Data -- 14.2.2.2 Remotely-Sensed Data -- 14.2.3 The Method -- 14.2.3.1 Image Products of MODIS Data -- 14.2.3.2 Field Data Exploration -- 14.2.3.3 Statistical Modelling. , The Pearson Correlation Analysis.
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 2
    Online Resource
    Online Resource
    Newark :American Geophysical Union,
    Keywords: Floods. ; Droughts. ; Electronic books.
    Type of Medium: Online Resource
    Pages: 1 online resource (355 pages)
    ISBN: 9781119427209
    Series Statement: Geophysical Monograph Series
    DDC: 363.34929
    Language: English
    Note: Cover -- Title Page -- Copyright Page -- Contents -- List of Contributors -- Preface -- Part I Remote Sensing for Global Drought and Flood Observations -- Chapter 1 Progress, Challenges, and Opportunities in Remote Sensing of Drought -- 1.1. INTRODUCTION -- 1.2. PROGRESS IN REMOTE SENSING OF DRIVERS OF DROUGHT -- 1.3. MULTI-INDICATOR DROUGHT MODELING -- 1.4. DROUGHT AND HEATWAVES FEEDBACKS -- 1.5. REMAINING CHALLENGES AND OPPORTUNITIES -- 1.6. CONCLUSION -- REFERENCES -- Chapter 2 Remote Sensing of Evapotranspiration for Global Drought Monitoring -- 2.1. INTRODUCTION -- 2.2. HISTORICAL SKETCH OF ET REMOTE SENSING STUDIES AND ET DATA PRODUCTS -- 2.3. ESTIMATING ET AND MONITORING DROUGHT WITH GEOSTATIONARY SATELLITE THERMAL OBSERVATIONS -- 2.4. DROUGHT MONITORING PRODUCT SYSTEM BASED ON ET REMOTE SENSING -- 2.5. COMBINING ET REMOTE SENSING WITH MICROWAVE SOIL MOISTURE DATA FOR DROUGHT MONITORING -- 2.6. DISCUSSION -- ACKNOWLEDGMENTS -- REFERENCES -- Chapter 3 Drought Monitoring Using Reservoir Data Collected via Satellite Remote Sensing -- 3.1. INTRODUCTION -- 3.2. DROUGHT MONITORING USING REMOTELY SENSED RESERVOIR DATA -- 3.3. ADOPTING REMOTELY SENSED RESERVOIR DATA TO SUPPORT DROUGHT MODELING APPLICATIONS -- 3.4. FUTURE DIRECTIONS -- 3.5. DISCUSSION AND CONCLUSIONS -- ACKNOWLEDGMENTS -- REFERENCES -- Chapter 4 Automatic Near-Real-Time Flood Mapping from Geostationary Low Earth Orbiting Satellite Observations -- 4.1. INTRODUCTION -- 4.2. DATA USED -- 4.3. METHODS -- 4.4. APPLICATIONS -- 4.5. VALIDATION -- 4.6. DISCUSSION -- 4.7. SUMMARY -- ACKNOWLEDGMENTS -- REFERENCES -- Chapter 5 Global Flood Observation with Multiple Satellites: Applications in Rio Salado (Argentina) and the Eastern Nile Basin -- 5.1. INTRODUCTION: THE STATE OF THE SCIENCE AND NEED FOR GLOBAL SATELLITE FLOOD MAPPING -- 5.2. METHODS FOR GLOBAL FLOOD OBSERVATION. , 5.3. WATERSHED CASE STUDIES: ARGENTINA AND THE EASTERN NILE REGION -- 5.4. RESULTS FROM FLOOD MAPPING IN CASE STUDIES -- 5.5. LIMITATIONS AND FUTURE DIRECTIONS FOR THE UTILITY OF SATELLITE FLOOD-EVENT DATA -- 5.6. CONCLUSION -- ACKNOWLEDGMENTS -- REFERENCES -- Chapter 6 Integrating Earth Observation Data of Floods with Large-Scale Hydrodynamic Models -- 6.1. INTRODUCTION -- 6.2. EARTH OBSERVATION FLOOD DATA -- 6.3. INTEGRATION OF EO DATA AND FLOOD MODELS -- 6.4. OUTLOOK -- 6.5. CONCLUSION -- REFERENCES -- Part II Modeling and Prediction of Global Drought and Flood -- Chapter 7 Global Integrated Drought Monitoring with a Multivariate Framework -- 7.1. INTRODUCTION -- 7.2. METHOD -- 7.3. DATA -- 7.4. RESULTS -- 7.5. CONCLUSION -- REFERENCES -- Chapter 8 A Probabilistic Framework for Agricultural Drought Forecasting Using the Ensemble Data Assimilation and Bayesian Multivariate Modeling -- 8.1. INTRODUCTION -- 8.2. REVIEW OF CURRENT DROUGHT FORECASTING SYSTEMS -- 8.3. THE PROPOSED COUPLED DYNAMICAL-STATISTICAL DROUGHT FORECASTING SYSTEM -- 8.4. CASE STUDIES -- 8.5. CONCLUSIONS AND DISCUSSION -- REFERENCES -- Chapter 9 Integrating Soil Moisture Active/Passive Observations with Rainfall Data Using an Analytic Model for Drought Monitoring at the Continental Scale -- 9.1. INTRODUCTION -- 9.2. DATA AND METHOD -- 9.3. RESULTS -- 9.4. DISCUSSION AND CONCLUSIONS -- ACKNOWLEDGEMENTS -- REFERENCES -- Chapter 10 Global Flood Models -- 10.1. INTRODUCTION -- 10.2. TYPES OF GFM AND SPECIFIC EXAMPLES -- 10.3. APPLICATIONS OF GLOBAL FLOOD MODELS -- 10.4. INSURANCE CATASTROPHE MODELS -- 10.5. GFM CREDIBILITY -- 10.6. THE FUTURE OF GFMS -- REFERENCES -- Chapter 11 Calibration of Global Flood Models: Progress, Challenges, and Opportunities -- 11.1. INTRODUCTION -- 11.2. GLOBAL HYDROLOGICAL MODEL CALIBRATION. , 11.3. MAIN CHALLENGES OF CALIBRATING GLOBAL HYDROLOGICAL MODELS -- 11.4. EMERGING OPPORTUNITIES -- 11.5. SUMMARY -- REFERENCES -- Chapter 12 Digital Elevation Model and Drainage Network Data Sets for Global Flood and Drought Modeling -- 12.1. INTRODUCTION -- 12.2. GLOBAL BASELINE DIGITAL ELEVATION DATA FOR HYDROLOGICAL MODELING -- 12.3. GLOBAL HYDROGRAPHY DATA SETS -- 12.4. CHALLENGES AND OPPORTUNITIES -- 12.5. SUMMARY -- ACKNOWLEDGMENTS -- REFERENCES -- Chapter 13 Fundamental Data Set for Global Drought and Flood Modeling: Land Use and Land Cover -- 13.1. INTRODUCTION -- 13.2. GLOBAL LAND COVER DATA SETS -- 13.3. DISCUSSION -- REFERENCES -- Part III Global Drought and Flood Risk Assessment, Management, and Socioeconomic Response -- Chapter 14 Global River Flood Risk Under Climate Change -- 14.1. INTRODUCTION -- 14.2. MODELING GLOBAL RIVER FLOOD RISK: GENERAL CONCEPTS AND METHODS -- 14.3. THE GLOFRIS MODELING FRAMEWORK -- 14.4. CAMA-FLOOD AND ISIMIP MODELING FRAMEWORKS -- 14.5. THE GAR-2015 FLOOD RISK FRAMEWORK -- 14.6. THE JOINT RESEARCH CENTRE MODEL -- 14.7. OTHER FLOOD RISK MODELS -- 14.8. CONCLUSIONS -- REFERENCES -- Chapter 15 Direct Tangible Damage Classification and Exposure Analysis Using Satellite Images and Media Data -- 15.1. INTRODUCTION -- 15.2. DATA AND STUDY SITE -- 15.3. METHOD -- 15.4. RESULTS -- 15.5. DISCUSSION -- 15.6. CONCLUSIONS -- ACKNOWLEDGMENTS -- REFERENCES -- Chapter 16 Flood Risk and Monitoring Data for Preparedness and Response: From Availability to Use -- 16.1. INTRODUCTION -- 16.2. CHALLENGES IN UNDERSTANDING AND TRUSTING FLOOD DATA -- 16.3. TWO CASE STUDIES FRAMING THE DISCONNECT BETWEEN FLOOD DATA DEVELOPERS AND DECISION MAKERS -- 16.4. IDENTIFICATION OF COMMON THEMES FOUND IN THE QUESTIONS ASKED WITHIN THE CASE STUDIES -- 16.5. SUGGESTED OPPORTUNITIES TO MOVE TOWARDS NARROWING THE GAP -- 16.6. CONCLUSION. , ACKNOWLEDGMENTS -- REFERENCES -- Chapter 17 Global Flood Partnership* -- 17.1. INTRODUCTION -- 17.2. MODELS AND PRODUCTS -- 17.3. GFP ACTIVATIONS -- 17.4. DISCUSSION AND CONCLUSIONS -- REFERENCES -- Chapter 18 Drought and Flood Monitoring and Forecasting: Challenges and Opportunities Ahead -- 18.1. REMOTE SENSING FOR DROUGHT AND FLOOD MODELING -- 18.2. DROUGHT AND FLOOD MODELING -- 18.3. RISK ANALYSIS AND COLLABORATION -- 18.4. PERSPECTIVE -- Index -- EULA.
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 3
    Publication Date: 2023-06-14
    Description: Global Water Models (GWMs), which include Global Hydrological, Land Surface, and Dynamic Global Vegetation Models, present valuable tools for quantifying climate change impacts on hydrological processes in the data scarce high latitudes. Here we performed a systematic model performance evaluation in six major Pan-Arctic watersheds for different hydrological indicators (monthly and seasonal discharge, extremes, trends (or lack of), and snow water equivalent (SWE)) via a novel Aggregated Performance Index (API) that is based on commonly used statistical evaluation metrics. The machine learning Boruta feature selection algorithm was used to evaluate the explanatory power of the API attributes. Our results show that the majority of the nine GWMs included in the study exhibit considerable difficulties in realistically representing Pan-Arctic hydrological processes. Average APIdischarge (monthly and seasonal discharge) over nine GWMs is 〉 50% only in the Kolyma basin (55%), as low as 30% in the Yukon basin and averaged over all watersheds APIdischarge is 43%. WATERGAP2 and MATSIRO present the highest (APIdischarge 〉 55%) while ORCHIDEE and JULES-W1 the lowest (APIdischarge ≤ 25%) performing GWMs over all watersheds. For the high and low flows, average APIextreme is 35% and 26%, respectively, and over six GWMs APISWE is 57%. The Boruta algorithm suggests that using different observation-based climate data sets does not influence the total score of the APIs in all watersheds. Ultimately, only satisfactory to good performing GWMs that effectively represent cold-region hydrological processes (including snow-related processes, permafrost) should be included in multi-model climate change impact assessments in Pan-Arctic watersheds.
    Description: Bundesministerium für Bildung und Forschung http://dx.doi.org/10.13039/501100002347
    Keywords: ddc:551.48 ; Global Water Models ; Model performance ; Model evaluation ; Arctic watersheds ; Boruta feature selection
    Language: English
    Type: doc-type:article
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 4
    Publication Date: 2023-06-14
    Description: Importance of evaluation of global hydrological models (gHMs) before doing climate impact assessment was underlined in several studies. The main objective of this study is to evaluate the performance of six gHMs in simulating observed discharge for a set of 57 large catchments applying common metrics with thresholds for the monthly and seasonal dynamics and summarize them estimating an aggregated index of model performance for each model in each basin. One model showed a good performance, and other five showed a weak or poor performance in most of the basins. In 15 catchments, evaluation results of all models were poor. The model evaluation was supplemented by climate impact assessment for a subset of 12 representative catchments using (1) usual ensemble mean approach and (2) weighted mean approach based on model performance, and the outcomes were compared. The comparison of impacts in terms of mean monthly and mean annual discharges using two approaches has shown that in four basins, differences were negligible or small, and in eight catchments, differences in mean monthly, mean annual discharge or both were moderate to large. The spreads were notably decreased in most cases when the second method was applied. It can be concluded that for improving credibility of projections, the model evaluation and application of the weighted mean approach could be recommended, especially if the mean monthly (seasonal) impacts are of interest, whereas the ensemble mean approach could be applied for projecting the mean annual changes. The calibration of gHMs could improve their performance and, consequently, the credibility of projections.
    Description: BMBF
    Description: JSPS KAKENHI
    Description: NSFC
    Keywords: ddc:551.48 ; Climate change ; Global hydrological models ; River discharge projections ; Model evaluation ; Model performance ; Model weighting ; Credibility of projections
    Language: English
    Type: doc-type:article
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 5
    Publication Date: 2024-04-22
    Description: As the adverse impacts of hydrological extremes increase in many regions of the world, a better understanding of the drivers of changes in risk and impacts is essential for effective flood and drought risk management and climate adaptation. However, there is currently a lack of comprehensive, empirical data about the processes, interactions, and feedbacks in complex human-water systems leading to flood and drought impacts. Here we present a benchmark dataset containing socio-hydrological data of paired events, i.e. two floods or two droughts that occurred in the same area. The 45 paired events occurred in 42 different study areas and cover a wide range of socio-economic and hydro-climatic conditions. The dataset is unique in covering both floods and droughts, in the number of cases assessed and in the quantity of socio-hydrological data. The benchmark dataset comprises (1) detailed review-style reports about the events and key processes between the two events of a pair; (2) the key data table containing variables that assess the indicators which characterize management shortcomings, hazard, exposure, vulnerability, and impacts of all events; and (3) a table of the indicators of change that indicate the differences between the first and second event of a pair. The advantages of the dataset are that it enables comparative analyses across all the paired events based on the indicators of change and allows for detailed context- and location-specific assessments based on the extensive data and reports of the individual study areas. The dataset can be used by the scientific community for exploratory data analyses, e.g. focused on causal links between risk management; changes in hazard, exposure and vulnerability; and flood or drought impacts. The data can also be used for the development, calibration, and validation of socio-hydrological models. The dataset is available to the public through the GFZ Data Services (Kreibich et al., 2023, 10.5880/GFZ.4.4.2023.001).
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
    Format: application/pdf
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...