Imputation Methods for Missing Hydrometeorological Data Estimation
About This Book
Gaps in the records are a widespread problem in hydrometeorological datasets. Estimating the missing values calls for objective and robust spatial and temporal imputation methods, so that data are free of errors and gaps and continuous over time. This book is a comprehensive guide and reference to basic and advanced interpolation and data-driven approaches for filling such gaps. It covers spatial and temporal interpolation, universal function approximation, and imputation aided by data mining. It also presents new spatial deterministic and stochastic methods that emphasise the objective selection of control points and optimal spatial interpolation. Further chapters deal with emerging machine learning techniques for spatial and temporal interpolation schemes, and with error and performance measures for evaluating interpolation methods and validating imputed data. Practical applications to real-world hydrometeorological data illustrate the methods. The intended readership is broad. It includes graduate students and researchers in climatology, hydrology, and the earth sciences, as well as water engineering professionals in government agencies and private organisations that process and use hydrometeorological and climatological data.
ISBN: 9783031609459
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