Techniques for Disaster Risk Management and Mitigation

 
 
Wiley (Verlag)
  • 1. Auflage
  • |
  • erschienen am 28. April 2020
  • |
  • 352 Seiten
 
E-Book | ePUB mit Adobe DRM | Systemvoraussetzungen
978-1-119-35919-7 (ISBN)
 
A comprehensive guide to managing and mitigating natural disasters

Recent years have seen a surge in the number, frequency, and severity of natural disasters, with further increases expected as the climate continues to change. However, advanced computational and geospatial technologies have enabled the development of sophisticated early warning systems and techniques to predict, manage, and mitigate disasters.Techniques for Disaster Risk Management and Mitigation explores different approaches to forecasting disasters and provides guidance on mitigation and adaptation strategies.

Volume highlights include:
* Review of current and emerging technologies for disaster prediction
* Different approaches to risk management and mitigation
* Strategies for implementing disaster plans and infrastructure improvements
* Guidance on integrating artificial intelligence with GIS and earth observation data
* Examination of the regional and global impacts of disasters under climate variability
weitere Ausgaben werden ermittelt
Edited by

Prashant K. Srivastava, Assistant Professor, Institute of Environment and Sustainable Development, Banaras Hindu University, Varanasi, India

Sudhir Kumar Singh, Assistant Professor, K. Banerjee Centre of Atmospheric & Ocean Studies, IIDS, Nehru Science Centre, University of Allahabad, Prayagraj, India

U. C. Mohanty, Visiting Professor, School of Earth Ocean and Climate Sciences, Indian Institute of Technology Bhubaneswar, Argul, India

Tad Murty, Formerly Adjunct Professor, Department of Civil Engineering and Earth Sciences, University of Ottawa, Ottawa, ON, Canada
Contributors ix

Preface xiii

Section I: Introduction

1. Concepts and Methodologies of Environmental Hazards and Disasters 3
Nicolas R. Dalezios, George P. Petropoulos, and Ioannis N. Faraslis

2. Indigenous Knowledge for Disaster Solutions in the Hilly State of Mizoram, Northeast India 23
Kewat Sanjay Kumar, Awadhesh Kumar, Vinod Prasad Khanduri, and Sudhir Kumar Singh

3. Urban Risk and Resilience to Climate Change and Natural Hazards: A Perspective from Million-Plus Cities on the Indian Subcontinent 33
Amit Kumar, Diksha, A. C. Pandey, and M. L. Khan

4. The Contribution of Earth Observation in Disaster Prediction, Management, and Mitigation: A Holistic View 47
Varsha Pandey, Prashant K. Srivastava, and George P. Petropoulos

Section II: Atmospheric Hazards and Disasters

5. Tropical Cyclones Over the North Indian Ocean in Changing Climate 65
R. Bhatla, Raveena Raj, R. K. Mall, and Shivani

6. Simulation of Intensity and Track of Tropical Cyclones Over the Arabian Sea Using the Weather Research and Forecast (WRF) Modeling System with Different Initial Conditions (ICs) 77
Sushil Kumar, Ashish Routray, Prabhjot Singh Chawla, and Shilpi Kalra

7. Development of a Soft Computing Model from the Reanalyzed Atmospheric Data to Detect Severe Weather Conditions 85
Devajyoti Dutta, Ashish Routray, and Prashant K. Srivastava

8. Lightning, the Global Electric Circuit, and Climate 93
N. Jeni Victor, Sagarika Chandra, and Devendraa Siingh

9. An Exploration of the Panther Mountain Crater Impact Using Spatial Data and GIS Spatial Correlation Analysis Techniques 111
Sawyer Reid Stippa, Konstantinos P. Ferentinos, and George P. Petropoulos

Section III: Land Hazards and Disasters

10. Satellite Radar Interferometry Processing and Elevation Change Analysis for Geoenvironmental Hazard Assessment 127
Sergey Stankevich, Iryna Piestova, Anna Kozlova, Olga Titarenko, and Sudhir Kumar Singh

11. Assessing the Use of Sentinel-2 in Burnt Area Cartography: Findings from a Case Study in Spain 141
Craig Amos, Konstantinos P. Ferentinos, George P. Petropoulos, and Prashant K. Srivastava

12. Assimilating SEVIRI Satellite Observation into the Name-III Dispersion Model to Improve Volcanic Ash Forecast 151
Prajakta Patil, I. M. Watson, Shona Mackie, Prashant K. Srivastava, Tanvir Islam, and Sourabh Sakhare

13. Geoinformation Technology for Drought Assessment 171
Arnab Kundu, D. M. Denis, N. R. Patel, R. K. Mall, and Dipanwita Dutta

14. Introduction to Landslides 181
H. K. Pandey

15. Probabilistic Landslide Hazard Assessment using Statistical Information Value (SIV) and GIS Techniques: A Case Study of Himachal Pradesh, India 197
Ankit Sharma, Ujjwal Sur, Prafull Singh, Praveen Kumar Rai, and Prashant K. Srivastava

16. One-Dimensional Hydrodynamic Modeling of the River Tapi: The 2006 Flood, Surat, India 209
Dhruvesh P. Patel, Prashant K. Srivastava, Sudhir Kumar Singh, Cristina Prieto, and Dawei Han

Section IV: Ocean Hazards and Disasters

17. Tropical Cyclone-Induced Storm Surges and Wind Waves in the Bay of Bengal 239
Prasad K. Bhaskaran, A. D. Rao, and Tad Murty

18. Space-Based Measurement of Rainfall Over India and Nearby Oceans Using Remote Sensing Application 295
Anoop Kumar Mishra and Kishan Singh Rawat

19. Modeling Tsunami Attenuation and Impacts on Coastal Communities 309
S. Piché, I. Nistor, and T. Murty

Index 325

1
Concepts and Methodologies of Environmental Hazards and Disasters


Nicolas R. Dalezios1, George P. Petropoulos2, and Ioannis N. Faraslis3

1 University of Thessaly, Department of Civil Engineering, Pedion Areos, Volos, Greece

2 School of Mineral & Resources Engineering, Technical University of Crete, Kounoupidiana Campus, Crete, Greece; Department of Soil & Water Resources, Institute of Industrial & Forage Crops, Hellenic Agricultural Organization "Demeter" (former NAGREF), Directorate General of Agricultural Research, Larissa, Greece

3 University of Thessaly, Department of Planning and Regional Development, Pedion Areos, Volos, Greece

ABSTRACT


Natural disasters have significant impact on several sectors of the economy, including agriculture. Moreover, under climate uncertainty, the role of several sectors of the economy, such as agriculture, as a provider of environmental and ecosystem services, is expected to further gain importance. Indeed, increasing climate variability and climate change lead to increases in climate extremes. The objective of this review is to present concepts and methodologies of environmental hazards and extremes that affect agriculture and agroecosystems, based on remote sensing data and methods, since this is a field gaining in potential and reliability. In this chapter, the relationship between environmental hazards and agriculture is presented; this is followed by concepts and quantitative methodologies of environmental hazards affecting agriculture, namely hydrometeorological hazards (floods and excess rain, droughts, hail, desertification) and biophysical hazards (frost, heat waves, wild fires). The emphasis is on concepts and the three stages of hazard development: forecasting-nowcasting (before), monitoring (during), and assessment (after). Examples and case studies are presented using recorded data sets, model simulations, and innovative methodologies.

1.1. INTRODUCTION


Agriculture faces several current and future challenges, such as international competition and further liberalization of trade policy. Additionally, environmental hazards play a major role in agriculture; this has resulted in a gradual and significant increase of the economic cost associated with all environmental hazards. Needless to say, agricultural production is highly dependent on climate, and is adversely affected by anthropogenic climate change and increasing climate variability, which have led to increases in climate extremes. During the 21st century, scientific projections, among others, point to changes in climate extremes, such as heat waves, heavy rainfall, and droughts, in many semiarid and arid regions around the world. Specifically, southern Europe and the entire Mediterranean basin are characterized as vulnerable regions due to the combined effect of temperature increases and reduced precipitation in areas already coping with water scarcity (Dalezios et al., 2018a; Srivastava et al., 2019). Agricultural production risks could become an issue in areas such as the entire Mediterranean basin, as mainly droughts and heat waves are likely to increase the incidence of crop failure. As yield variability increases, food supply is at increasing risk.

Under a changing climate, the role of agriculture as a provider of environmental and ecosystem services is expected to gain further importance. Improvement of water use efficiency in dry regions is an example of agricultural management. Vulnerability of agriculture can be reduced through adaptation measures and tools to increase climate variability (EU, 2007). Some farming systems may adapt more readily to climate pressures due to an inherent resilience. Other systems may need interventions for adaptation. However, besides traditional knowledge and technologies, more sophisticated technologies seem to be required due to increasing climate variability and change. Seasonal to interannual climate forecasting is a new branch of climate science that promises to reduce vulnerability in agriculture. Improved seasonal forecasts are now being linked to decision making for cropping. The application of climate knowledge to improving risk management is expected to increase the resilience of farming systems.

Environmental degradation is one of the major factors contributing to the vulnerability of agriculture because it directly magnifies the risk of environmental disasters. In order to ensure sustainability in agricultural production, a better understanding of the environmental hazards and disasters that impact agriculture is essential. A comprehensive assessment of impacts of natural disasters on agriculture requires a multidisciplinary, multisectoral, and integral approach involving several components and factors. Priority should be given to supporting applied research, since research is necessary to understand the physical and biological factors contributing to disasters. Community-wide awareness and capacity building on environmental hazards and disasters, mainly for farmers and stakeholders, should also be included in any research effort. Programs for improving prediction and early warning methods, as well as dissemination of warnings, should be expanded and intensified. Moreover, efforts are required to determine the impact of disasters on natural resources.

Recent research findings suggest that variability of climate, if encompassing more intense and frequent extremes, such as major large-scale hazards like droughts, heat waves, or floods, results in the occurrence of natural disasters that are beyond our socioeconomic planning levels. It is estimated that about 65% of the global damage from natural disasters has a meteorological origin. Also, meteorological factors contribute to 87% of people affected by natural disasters and 85% of relevant deaths (UN/ISDR, 2015; EM-DAT, 2009; WMO, 2004). This is expected to stretch regional response capabilities beyond their capacity and will require new adaptation and preparedness strategies (Salinger et al., 2005). Disaster prevention and preparedness should become a priority, and rapid response capacities to climate change need to be accompanied by a strategy for disaster prevention. Nevertheless, each type of extreme event has its own particular climatic, cultural, and environmental setting, and mitigation activities must use these settings as a foundation of proactive management. There is significant complexity involved in homogenizing and issuing global or regional statistics for disasters affecting agriculture, since this depends on the specific climatic zone and environment where the agricultural activity takes place, as well as the type, areal extent, and microclimatic and agronomic characteristics of the crops in that zone, including agroclimatic features. Nevertheless, international organizations, such as the Food and Agriculture Organization (FAO), the World Meteorological Organization (WMO), or the United Nations International Strategy for Disaster Reduction (UN/ISDR), issue statistics periodically that refer to environmental hazards and disasters that affect agriculture and agroecosystems. There is an urgent need to assess the forecasting skills for environmental hazards affecting agriculture in order to determine those where greater research is required. It is well known that lack of good forecast skill is a constraint to improve management, mitigation, and adaptation.

A holistic and integrated approach to environmental risks has gradually explored the use of common methodologies, such as risk analysis, including risk assessment and management. Indeed, through risk analysis, there are efforts to develop preventive measures and hazard processes before the crisis. It should be stated that current natural disaster management is crisis driven. It is thus realized that there is an urgent research need for a more risk-based management approach to natural disaster planning in agriculture, which would include a timely and user-oriented early warning system (Dalezios, 2017). Agricultural risk zoning is also an essential component of natural disaster mitigation and preparedness strategies. GIS and remote sensing and, in general, geoinformatics are increasingly employed due to the complex nature of databases to facilitate strategic and tactical applications at the farm and policy levels. Therefore, additional research is required to incorporate GIS, remote sensing, global positioning systems (GPS), simulation models, and other computational techniques into an integrated multihazard risk management framework for sustainable agriculture that includes early warnings of natural disasters (Sivakumar et al., 2005). There should also be more research attention to the potential impact of the increasing frequency and severity of extreme events associated with global change and appropriate mitigation strategies.

In general, risk assessment methodologies include three stages, or sectors, such as forecasting and early warnings before the phenomenon occurs, monitoring during a natural disaster, and estimating damage after the end of a disaster. In addition, risk identification involves quantifying, monitoring, and event risk, statistical inference, and database development, which should include records and historical information on disasters and their impacts. Risk assessment also entails reviewing the risk of these events, that is, the probability of occurrence, as well as the magnitude-duration-frequency and area-to-risk ratio. Finally, the risk assessment includes an environmental impact assessment and cost-benefit analysis of the adaptation options for the...

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