Spatio Temporal Characterisation Of Drought Data Analytics Modelling Tracking Impact And Prediction
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Spatio-temporal characterisation of drought: data analytics, modelling, tracking, impact and prediction
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.
Spatio-temporal characterisation of drought: data analytics, modelling, tracking, impact and prediction
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
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