Global Drought and Flood. Группа авторов

and forecasting of the occurrence, intensity, and evolution of drought and flood events are considered to be more and more important by humanitarian and government agencies for issuing timely warnings, monitoring ongoing hazards, and developing short‐term and long‐term risk assessments and management plans. In the past two decades, there have been significant advances in both numerical modeling and remote sensing approaches. These complementary approaches have been critical components in producing integrated information for droughts and floods.

      This monograph reviews recent advances in the modeling and remote sensing of droughts and floods, covering many relevant topics including: (a) the currently available, widely used techniques and products for obtaining timely and accurate global‐scale or continental‐scale drought and flood information; (b) the features, strengths and weaknesses, and advances and challenges in each of these global products; (c) how these products have been used by humanitarian, government, and development sectors in recent natural disaster cases; and (d) discussions about the gaps between the products and end users, and insights for further improving the workflow in response activities from perspectives of both hazard information providers and users.

      This book is organized into three closely connected sections. Part I focuses on remote sensing approaches for global drought and flood mapping. It starts with an overview of progress, challenges, and opportunities in remote sensing of drought. As critical components for drought monitoring, two well recognized remote‐sensing‐based products for evapotranspiration measurement and reservoir parameters (elevation, storage, and area) are then introduced and discussed in the following two chapters. Two widely used remote‐sensing‐based flood mapping products are described in the next two chapters, respectively, followed by a thoughtful chapter proposing an integration of Earth Observation (EO) data and numerical models, with the latter as the focus of the next section.

      Part II summarizes current widely used modeling approaches and systems, including model physics, features, validation, strength, limitations, and challenges in their further improvement and applications. In this section, the first three chapters are focused on modeling of drought using statistical, process‐based or hybrid approaches. For flood modeling, an overview of the state‐of‐the‐art flood models is presented in a dedicated chapter. An open challenge for almost all global flood models, i.e., large‐scale calibration of models, is discussed in the following chapter. The rest of the section then focuses on two common data sets, i.e., derivations based on digital elevations model (DEM), and land use and land cover (LULC), which are fundamental for both drought and flood simulations.

      Part III provides a review of recent advances in drought and flood damage estimation and risk assessment, and in‐depth discussions on challenges in humanitarian response and management activities when integrating the hazard information from multiple products and data sources. Flood risk assessment under climate change is first introduced and discussed. Then practical activities in hazard response from national and international agencies are detailed in the next two chapters. The final chapter of this section describes the emerging role of the Global Flood Partnership (GFP), a network of scientists, users, and private and public organizations active in global flood response and risk management. The GFP shares flood information in near real‐time for national environmental agencies and humanitarian organizations to support emergency operations and to reduce the overall socioeconomic impacts of disasters. A conclusion summarizes the whole book, with a brief discussion on existing challenges and the strategies of improving the monitoring and prediction of drought and flood.

Drought and floods have unsurprisingly become the hot topics of several recently published books. The uniqueness of this book, however, lies in the fact that: (a) it represents most of the ongoing modeling efforts, including current widely used products, and as chapter contributors are the developers of these products, this allows them to describe in detail and depth the strengths, weaknesses, advances and challenges in their further development and integration; (b) it brings together contributors from humanitarian, government, and development sectors, describing how these products are used in risk assessment and catastrophe response activities from a users’ standpoint, shedding light on how to narrow the gap between product providers and users in both expectation and communication. As a result, this book should appeal to a broad community of researchers, engineers, practitioners, policy makers, and decision makers, from various national and international agencies and nongovernmental organizations (NGOs) working in drought and flood disaster management, and in sustainable and resilient construction. It should also be of interest to college students and teachers with interests in subjects including hydrology, remote sensing, meteorology, natural hazards, emergency management, and global change.

      Last, we note that many of the chapters on floods are born out of presentations given at recent American Geophysical Union’s Fall Meeting sessions on “Global Floods: Forecasting, Monitoring, Risk Assessment, and Socioeconomic Response” and the annual meetings of the Global Flood Partnership (GFP). These sessions and meetings foster global flood forecasting, monitoring, and impact assessment efforts with the aim to strengthen preparedness and response and to reduce global flood losses.

       Huan Wu Sun Yat‐sen University, China

       Dennis P. Lettenmaier University of California, Los Angeles, USA

       Qiuhong Tang Chinese Academy of Sciences, China

       Philip J. Ward Vrije Universiteit Amsterdam, The Netherlands

Part I Remote Sensing for Global Drought and Flood Observations

1 Progress, Challenges, and Opportunities in Remote Sensing of Drought

       Arash Modarresi Rad1, Amir AghaKouchak2, Mahdi Navari3, and Mojtaba Sadegh4

       1 Department of Computing, Boise State University, Boise, Idaho, USA

       2 Department of Civil and Environmental Engineering, and Department of Earth System Science, University of California Irvine, Irvine, California, USA

       3 NASA Goddard Space Flight Center, Greenbelt, Maryland, USA

       4 Department of Civil Engineering, Boise State University, Boise, Idaho, USA

      ABSTRACT

      Drought, one of the most daunting natural hazards, is linked to other hazards such as heatwaves and wildfires, and is related to global and regional food security. Given the severe environmental and socioeconomic ramifications of droughts, comprehensive and timely analysis of droughts’ onset, development, and recovery at proper spatial and temporal scales is of paramount importance. Droughts are categorized by different variables, such as precipitation, soil moisture, and streamflow, depending on the target of the analysis. The root cause of droughts, however, is sustained below‐average precipitation. Large‐scale oceanic and atmospheric circulations drive precipitation variability, and hence droughts should be analyzed from a continental to global perspective. Given the spatial scale of interest, as well as the poor spatial resolution and temporal inconsistency of ground observations, multisensor remotely sensed climatological, hydrological, and biophysical variables offer a unique opportunity to model droughts from different perspectives (meteorological, agricultural, hydrological, and socioeconomic) and at the global scale. It is also often required to model droughts using multiple indices and analyze feedbacks between droughts and other hazards, such as heatwaves. Multiple satellites, missions, and sensors offer invaluable information for multi‐indicator modeling of droughts and their feedbacks with other natural hazards in an era of big data. Remote sensing satellite data, however, are associated with major challenges including temporal limitations, consistency within and between multiple sensors and data sets, reliability, lack of uncertainty assessment, managing data volumes, and paucity of research on translating remote sensing