Review of Hydroinformatics: Data Integrative Approaches in Computation, Analysis, and Modeling by Praveen Kumar, Jay Alameda, Peter Bajcsy, Mike Folk, and Momcilo Markus: Taylor and Francis Group, LLC, Boca Raton, FL, 2006; ISBN 9780-8493-2894-7

This book is unusual in two respects: First, it is attributed to 5 authors, but in reality 15 authors have contributed different chapters. Second, each chapter is written by one or more authors. The book includes 25 chapters and 6 appendixes. For an authored book, this arrangement seems unusual. When different authors write different chapters, there is bound to be a certain degree of nonuniformity in style and breadth of coverage. This outcome is less likely when the entire book is written by the authors.

Hydroinformatics is an area that is only a little over a decade old. During its short period of existence, it has witnessed phenomenal growth, fueled largely by unprecedented revolutions occurring in the information technology sector, as well as rapid advances in satellite technology, geographical information systems, data mining, database management systems, and data storage and retrieval systems. Applications of these technologies in civil, environmental, ecological, and water resources engineering have given birth to the newly emerging and rapidly expanding area called hydroinformatics. This healthy trend brings seemingly disparate areas closer. Hydroinformatics cuts across several disciplines—a point well emphasized in the book—and different disciplines now do not look so different after all. They indeed have a great deal in common—more than might appear at first sight. The book makes a real contribution in bridging different disciplines, and the authors are to be congratulated for preparing this book on hydroinformatics.

The subject matter of the book is divided into six sections. After the book introduces data integrative studies in Chapter 1, the following five sections contain 24 chapters, and the remaining section contains six appendixes. The first chapter sets the stage for the material to follow, develops a rationale for the book, and goes on to describe its scope.

The first section, comprising five chapters, deals with data-driven investigations and approaches in hydrology. The approaches described in these chapters have potential for application in other areas related to water and the environment. Chapter 2 deals with a unified modeling language (UML). After introducing the basic aspects of UML, it discusses the framework of UML, structural software objects, UML relationships, UML diagrams, object model diagrams, and database designs and development. This introduction to the material is excellent. Chapter 3 deals with digital library technology for hydrology. This technology has applicability beyond the frontiers of hydrology. After introducing a scholarly model for data publication by using digital libraries, it goes on to describe the building of a hydrologic information system digital library. The importance of this well-written chapter cannot be overemphasized, especially in light of growing databases and increased sharing of data across national borders. Chapter 4 discusses hydrologic metadata. After a short introduction to metadata and definition of metadata categories, the chapter describes problems and standardization of metadata and hydrologic metadata. The chapter concludes with a short remark on the future outlook. Hydrologic data models constitute the subject matter of Chapter 5. Data models, geodata models, and the arch-hydro data model are discussed in the chapter. The material described here will have particular appeal for distributed watershed modeling. The concluding chapter of Section 1 is Chapter 6, on the modelshed geodata model. The chapter describes a modelshed framework and the modelshed geodata model structure. It shows the power of data models for representing systems in three dimensions.

Section 2, which deals with the subject of managing and accessing large data sets, consists of three chapters. After providing a survey of different data types and uses of data, including remote sensing and common geospatial data, Chapter 7 goes on to discuss who the users are; gathering, using, and archiving data; and data management challenges. The chapter clearly illustrates the heterogeneity and challenging characteristics of data encountered in hydrology. This discussion is equally applicable in other areas of water and environment. Chapter 8 discusses data formats, including formats and abstraction layers, file access, structures, format options, and format examples. The last chapter in this section deals with HDF5 and encompasses the HDF5 data model and library, as well as an example problem involving a diffusion equation. The entire section is well-written with many diagrams and illustrative examples.

Section 3 discusses data communication and consists of four chapters. Chapter 10 deals with Web services. After beginning with a discussion of distributed object systems, objects and interfaces, and components of architectures, the chapter goes on to discuss Web service standards and application theory. Extensible markup language (XML) is the subject of Chapter 11. It discusses elements of XML and XML schema and provides data description and transformation from hydrology and task descriptions in XML. Grid computing is included in Chapter 12 and encompasses grid genesis, protocol-based grids, service grids, and application scenarios in atmospheric discovery and chemical engineering. Chapter 13 deals with integrated data management systems and encompasses metadata and integrated data management, metadata mechanisms for data management, data management systems using metadata mechanisms, and development of an integrated data management system. The material provided here is of great value in large-scale hydrologic and environmental modeling.

Data processing and analysis is the subject of section 4, which consists of eight chapters. Data processing is introduced in Chapter 14, which sets the stage for the material to follow in succeeding chapters of this section and provides a discussion of NSF-funded applications. Chapter 15 focuses on understanding data sources. It describes data sources from data producers and gives examples of data generation for modeling bidirectional reflectance distribution functions (BRDFs), examples of data acquisitions using wireless sensor networks, and a summary of implications of and issues about data sources. Data representation is discussed in Chapter 16. It discusses both vector data types and raster data types, as well as trade-offs. Chapter 17 deals with spatial registration. The treatment includes spatial registration steps and associated computational issues. Chapter 18 deals with georeferencing. The discussion includes georeferencing models, geographic transformations, and obtaining georeferencing information. Data integration is treated in Chapter 19, which discusses spatial interpolation with kriging, shallow integration of geospatial raster data, and deep integration of raster and vector data. Feature extraction is the subject of Chapter 20 which discusses feature extraction from point data and feature extraction from raster data. Chapter 21 discusses feature selection and analysis. It deals with the general feature selection problem and the spectral band selection problem and provides an overview of band selection methods and an example of feature analysis and decision support, in addition to discussing the evaluation of geographic territorial partitions and decision support.

Section 5, spanning four chapters, deals with soft computing. Statistical data mining is the subject of Chapter 22. It includes a discussion of both supervised learning and unsupervised learning. Artificial neural networks (ANNs) are described in Chapter 23. After introducing ANNs, the chapter treats back-propagation neural networks, synthetic data generation that is based on neural networks, and radial-basis neural networks. Chapter 24, which deals with genetic algorithms (GAs), discusses GA basics, a case study in groundwater monitoring design, GA theory, advanced GA theory, overcoming computational limitations, and design methodology for simple genetic algorithm (SGA) parameter setting and determining optimal solutions. The last chapter, Chapter 25, discusses fuzzy logic. It gives the essentials of fuzzy logic, fuzzy modeling, and a fuzzy-reasoning tutorial with an example.

The last section of the book is a suite of six appendixes. Appendix 1 is a tutorial for geodatabase and modelshed tools operation, Appendix 2 gives an XSL transformation file example, Appendix 3 discusses the universal transverse mercator (UTM) Northern Hemisphere projection, Appendix 4 deals with the Molodensky equations, Appendix 5 contains review questions for Section 4, and Appendix 6 provides a project assignment.

The book is well-written, is easy to follow, and comprehensive. It is extremely timely and sends a clear message that teaching hydrology must entail hydroinformatics if hydrology is to take full advantage of emerging technologies, which are heavily based on new information and computing tools. The book will serve as a good textbook for a course on hydroinformatics either at the senior undergraduate level or the beginning graduate level. It would also be a useful reference book on one’s bookshelf.