Studies of drought have increased in light of new data availability and advances in spatio-temporal analysis. However, the following gaps still need to be filled: 1) methods to characterise drought that explicitly consider its spatio-temporal features, such as spatial extent (area) and pathway; 2) methods to monitor and predict drought that include the above-mentioned characteristics and 3) approaches for visualising and analysing drought characteristics to facilitate interpretation of its variation. This research aims to explore, analyse and propose improvements to the spatio-temporal characterisation of drought. Outcomes provide new perspectives towards better prediction. The following objectives were proposed. 1) Improve the methodology for characterising drought based on the phenomenon’s spatial features. 2) Develop a visual approach to analysing drought variations. 3) Develop a methodology for spatial drought tracking. 4) Explore machine learning (ML) techniques to predict crop-yield responses to drought. The four objectives were addressed and results are presented. Finally, a scope was formulated for integrating ML and the spatio-temporal analysis of drought. Proposed scope opens a new area of potential for drought prediction (i.e. predicting spatial drought tracks and areas). It is expected that the drought tracking and prediction method will help populations cope with drought and its severe impacts.

Studies of drought have increased in light of new data availability and advances in spatio-temporal analysis. However, the following gaps still need to be filled: 1) methods to characterise drought that explicitly consider its spatio-temporal features, such as spatial extent (area) and pathway; 2) methods to monitor and predict drought that include the above-mentioned characteristics and 3) approaches for visualising and analysing drought characteristics to facilitate interpretation of its variation. This research aims to explore, analyse and propose improvements to the spatio-temporal characterisation of drought. Outcomes provide new perspectives towards better prediction. The following objectives were proposed. 1) Improve the methodology for characterising drought based on the phenomenon’s spatial features. 2) Develop a visual approach to analysing drought variations. 3) Develop a methodology for spatial drought tracking. 4) Explore machine learning (ML) techniques to predict crop-yield responses to drought. The four objectives were addressed and results are presented. Finally, a scope was formulated for integrating ML and the spatio-temporal analysis of drought. Proposed scope opens a new area of potential for drought prediction (i.e. predicting spatial drought tracks and areas). It is expected that the drought tracking and prediction method will help populations cope with drought and its severe impacts.

Hydrological Drought: Processes and Estimation Methods for Streamflow and Groundwater, Second Edition provides a comprehensive review of processes and estimation methods for streamflow and groundwater drought. It includes a qualitative conceptual understanding of drought features and processes, a detailed presentation of estimation methods and tools, practical examples and impacts relevant for operational practice. The drought phenomenon and its diversity across the world are illustrated using a global set of daily streamflow series, whereas regional and local aspects of drought are studied using a combination of hydrological time series and catchment information. Hydrological Drought: Processes and Estimation Methods for Streamflow and Groundwater, Second Edition concludes with human impacts, including climate change impacts on drought, drought forecasting and early warning and examples of procedures on how to manage water during drought. The majority of the examples are taken from regions where the rivers run most of the year, but not exclusively. The material presented ranges from well-established knowledge and analysing methods to recent developments in drought research. Its nature varies accordingly, from a more traditional textbook and clear overview to that of a research paper, which introduces recent approaches and methodologies for drought analysis. Includes a number of innovative tools (self-guided tours, worked examples and software) to support both the understanding and teaching of different methods for evaluating drought severity, human impacts, ecological effects of drought and regional methods that enable estimation Offers applications/demonstrations using a comprehensive database of streamflow and thematic data from a large number of national and international agencies, which illustrate how data are used when evaluating drought severity Presents the state of the art of hydrological drought, including well established knowledge as well as recent developments in drought research

Frequent drought events have recently occurred in different Mediterranean regions. These have highlighted a general inadequacy of the current strategies applied to mitigate negative impacts of such phenomenon. This book provides various methods of drought monitoring at different spatial scales, as well as innovative drought forecasting techniques based on stochastic approaches. Besides common drought indices (i.e. SPI), new agrometeorological indices are proposed.

The majority of the examples are taken from regions where the rivers run most of the year.

Agricultural droughts affect whole societies, leading to higher food costs, threatened economies, and even famine. In order to mitigate such effects, researchers must first be able to monitor them, and then predict them; however no book currently focuses on accurate monitoring or prediction of these devastating kinds of droughts. To fill this void, the editors of Monitoring and Predicting Agricultural Drought have assembled a team of expert contributors from all continents to make a global study, describing biometeorological models and monitoring methods for agricultural droughts. These models and methods note the relationships between precipitation, soil moisture, and crop yields, using data gathered from conventional and remote sensing techniques. The coverage of the book includes probabilistic models and techniques used in America, Europe and the former USSR, Africa, Asia, and Australia, and it concludes with coverage of climate change and resultant shifts in agricultural productivity, drought early warning systems, and famine mitigation. This will be an essential collection for those who must advise governments or international organizations on the current scope, likelihood, and impact of agricultural droughts. Sponsored by the World Meterological Organization

Recent advances in the modeling and remote sensing of droughts and floods Droughts and floods are causing increasing damage worldwide, often with devastating short- and long-term impacts on human society. Forecasting when they will occur, monitoring them as they develop, and learning from the past to improve disaster management is vital. Global Drought and Flood: Observation, Modeling, and Prediction presents recent advances in the modeling and remote sensing of droughts and floods. It also describes the techniques and products currently available and how they are being used in practice. Volume highlights include: Remote sensing approaches for mapping droughts and floods Physical and statistical models for monitoring and forecasting hydrologic hazards Features of various drought and flood systems and products Use by governments, humanitarian, and development stakeholders in recent disaster cases Improving the collaboration between hazard information provision and end users The American Geophysical Union promotes discovery in Earth and space science for the benefit of humanity. Its publications disseminate scientific knowledge and provide resources for researchers, students, and professionals.