Radar Hydrology : Principles, Models, and Applications book cover
1st Edition

Radar Hydrology
Principles, Models, and Applications

ISBN 9781466514614
Published December 19, 2014 by CRC Press
196 Pages 13 Color & 41 B/W Illustrations

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Book Description

Radar Hydrology: Principles, Models, and Applications provides graduate students, operational forecasters, and researchers with a theoretical framework and practical knowledge of radar precipitation estimation. The only text on the market solely devoted to radar hydrology, this comprehensive reference:

  • Begins with a brief introduction to radar
  • Focuses on the processing of radar data to arrive at accurate estimates of rainfall
  • Addresses advanced radar sensing principles and applications
  • Covers radar technologies for observing each component of the hydrologic cycle
  • Examines state-of-the-art hydrologic models and their inputs, parameters, state variables, calibration procedures, and outputs
  • Discusses contemporary approaches in data assimilation
  • Concludes with methods, case studies, and prediction system design
  • Includes downloadable MATLAB® content

Flooding is the #1 weather-related natural disaster worldwide. Radar Hydrology: Principles, Models, and Applications aids in understanding the physical systems and detection tools, as well as designing prediction systems.

Table of Contents


About the Authors

Introduction to Basic Radar Principles

Radar Components

The Radar Beam

The Radar Pulse

Signal Processing


Radar Quantitative Precipitation Estimation

Radar Calibration

Quality Control

Signal Processing

Fuzzy Logic

Precipitation Rate Estimation

Vertical Profile of Reflectivity

Rain Gauge Adjustment

Space-Time Aggregation

Remaining Challenges

Uncertainty Estimation


Polarimetric Radar Quantitative Precipitation Estimation

Polarimetric Radar Variables

Polarimetric Radar Data Quality Control

Noise Effect and Reduction

Clutter Detection and Removal

Attenuation Correction


Self-Consistency Check

Hydrometeor Classification

Polarimetric Characteristics of Radar Echoes

Classification Algorithms

Polarimetric Radar-Based QPE

Microphysical Retrievals

Raindrop Size Distribution Model

DSD Retrieval

Snowfall and Hail Estimation



Multi-Radar Multi-Sensor (MRMS) Algorithm

Single-Radar Processing

Dual-Polarization Quality Control

Vertical Profile of Reflectivity Correction

Product Generation

Precipitation Typology

Precipitation Estimation




Advanced Radar Technologies for Quantitative Precipitation Estimation

Mobile and Gap-Filling Radars

ARRC's Shared Mobile Atmospheric Research and Teaching Radar (SMART-R)

NSSL's X-Band Polarimetric Mobile Radar (NOXP)

ARRC's Atmospheric Imaging Radar (AIR)

ARRC's Polarimetric X-Band 1000 (PX-1000)

Collaborative Adaptive Sensing of the Atmosphere (CASA)

Spaceborne Radars

Precipitation Radar aboard TRMM

Dual-Frequency Precipitation Radar aboard NASA GPM

Phased-Array Radar

Design Aspects and Product Resolution

Dual Polarization

Impact on Hydrology


Radar Technologies for Observing the Water Cycle

The Hydrologic Cycle

Surface Water

Streamflow Radar

Surface Water Altimetry

Synthetic Aperture Radar

Subsurface Water

L-Band Radar

C-Band Radar

Ground-Penetrating Radar

Subsurface Water


Radar QPE for Hydrologic Modeling

Overview of Hydrological Models

Model Classes

Model Parameters

Model State Variables and Data Assimilation

Hydrological Model Evaluation

Hydrological Evaluation of Radar QPE

Case Study in Ft. Cobb Basin, Oklahoma

Evaluation with a Hydrologic Model Calibrated to a Reference QPE

Evaluation with Monte Carlo Simulations from a Hydrologic Model

Evaluation with a Hydrologic Model Calibrated to Individual QPEs


Flash Flood Forecasting

Flash Flood Guidance

Flash Flood Guidance: History

Lumped Flash Flood Guidance

Flash Flood Potential Index

Gridded Flash Flood Guidance

Comments on the Use of Flash Flood Guidance

Threshold Frequency Approach


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Yang Hong is a professor of hydrometeorology and remote sensing in the School of Civil Engineering and Environmental Sciences, adjunct faculty member with the School of Meteorology, co-director of the WaTER Center, faculty member with the Advanced Radar Research Center, and affiliated member of the Center for Analysis and Prediction of Storms at the University of Oklahoma. Dr. Hong also directs the HyDROS Lab at the National Weather Center. Previously, he was a research scientist at NASA's Goddard Space Flight Center and postdoctoral researcher at University of California, Irvine. He holds a BS and MS from Peking (Beijing) University, China and Ph.D from the University of Arizona.

Jonathan J. Gourley is a research hydrologist with the NOAA/National Severe Storms Laboratory and affiliate associate professor with the School of Meteorology at the University of Oklahoma. His research interests include hydrologic prediction across scales ranging from water resources management to early warning of extreme events. Dr. Gourley was the principal inventor of a multisensor rainfall algorithm that was expanded to encompass all radars in North America and deployed to several foreign countries for operational use. He also assembled a comprehensive database that is being used to develop FLASH—a real-time flash flood forecasting system. He holds a BS, MS, and Ph.D from the University of Oklahoma.


"This is the first book on radar hydrology written by hydrologists. Whereas the excellent knowledge of radar technology by the authors permits an adequate coverage of the principles of rainfall rate estimation by radar, their hydrological background allows them to provide a unique message on the benefits (and on the remaining challenges) in exploiting radar techniques in hydrology. … In a clear and concise manner, the book combines topics from different scientific disciplines into a unified approach aiming to guide the reader through the requirements, strengths, and pitfalls of the application of radar technology in hydrology—mostly for flood prediction. Chapters include excellent discussion of theory, data analysis, and applications, along with several cross references for further review and useful conclusions."
—Marco Borga, University of Padova, Italy