Hydroinformatics introduces the tools, approaches, and system considerations necessary to take full advantage of the abundant hydrological data available today.

Features:

• Provides the first comprehensive introduction to hydroinformatics
• Takes a pedagogical approach to the concepts that does not rely on research that will soon be outdated
• Integrates multidisciplinary information into a unified treatment
• Supplies ready-to-use software techniques for application
• Includes real-world examples and programs
• Offers downloadable companion software to implement the concepts and techniques outlined in the book

Contents

Data Integrative Studies in Hydroinformatics

• What is Hydroinformatics?
• Scope of the Book

Unified Modeling Language

• What is UML?
• The Framework of the UML
• Object Model Diagrams
• Database Design and Deployment

Digital Library Technology

• Building the Hydrologic Information System Digital Library

Hydrologic Metadata

• Introduction to Metadata.
• Definition of Metadata Categories
• Metadata: Problems and Standardization
• Hydrologic Metadata

Hydrologic Data Models

• Data Models
• Geodata Models
• The ArcHydro Data Model

Modelshed Data Model

• Modelshed Framework
• The Modelshed Geodata Model Structure

Data Models for Storage and Retrieval

• Survey of Different Types and Uses of Data
• Who are the Users?
• Gathering, Using, and Archiving Data
• Data Management Challenges

Data Formats

• Formats and Abstraction Layers
• Concepts of Data File Formats

HDF5

• What is HDF5?
• HDF5 Data Model: Drilling Down
• HDF5 Library
• Example Problem: Using the HDF5 File Format as IO for an Advection -Diffusion Model

Web Services

• Distributed Object Systems
• Web Services

XML

• Data Descriptions
• Task Descriptions in XML

Grid Computing

• Grid Genesis
• Protocol-Based Grids
• Service Grids
• Application Scenarios

Integrated Data Management

• Metadata and Integrated Data Management
• Metadata Mechanism for Data Management
• Data Management System Using Metadata Mechanism
• Development of an Integrated Data Management System

Introduction to Data Processing

• Motivation Example
• NSF Funded Applications

Understanding Data Sources

• Data Sources from Data Producers
• Example of Data Generation for Modeling BRDFs
• Example of Data Acquisitions Using Wireless Sensor Networks

Data Representation

• Vector Data Types
• Raster Data Types

Spatial Registration

• Spatial Registration Steps
• Computational Issues Related to Spatial Registration

Georeferencing

• Georeferencing Models
• Geographic Transformations
• Finding Georeferencing Information

Data Integration

• Spatial Interpolation with Kriging
• Shallow Integration of Geospatial Raster Data
• Deep Integration of Raster and Vector Data

Feature Extraction

• Feature Extraction from Point Data
• Feature Extraction from Raster Data

Feature Selection and Analysis

• General Feature Selection Problem
• Spectral Band Selection Problem
• Overview of Band Selection Methods
• Conducting Band Selection Studies
• Feature Analysis and Decision Support Example
• Evaluation of Geographic Territorial Partitions and Decision Support

Statistical Data Mining

• Supervised Learning
• Unsupervised Learning

Neural Networks

• Back-Propagation Neural Networks
• Synthetic Data Generation Based on Neural Networks
• Radial Basis Neural Networks: Minimal Resource Allocation Networks

Genetic Algorithms

• GA Basics
• Formulating Hydroinformatics Optimization Problems: A Case Study in Groundwater Monitoring Design
• GA Theory
• Design Methodology for SGA Parameter Setting and Finding the Optimal Solution
• Overcoming Computational Limitations
• Advanced GAs

Fuzzy Logic

• Fuzzy Sets Essentials
• Fuzzy Modeling
• Fuzzy Reasoning Tutorial: An Example

Index

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