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Aug 18, 2017

Review of Hydrologic Remote Sensing:Capacity Building for Sustainability and Resilience by Yang Hong, Yu Zhang, and Sadiq Ibrahim Khan

Based on: CRC Press/Taylor & Francis Group, Boca Raton, FL 33487-2742; 2017; ISBN 978-1-4987-2666-5; 395 pp.; $127.95.
Publication: Journal of Hydrologic Engineering
Volume 22, Issue 11
Remote sensing is receiving increasing attention in hydrology these days. This is because in situ observations may be inadequate; spatial coverage over large areas may be needed; many areas are inaccessible or dangerous for in situ observations; observations during hazards, such as floods, are difficult; and existing observation networks may not be yielding the data that is needed and may not be optimal. Conversely, there are questions related to the accuracy and uncertainty associated with remote sensing estimates. This book addresses these questions and several other related aspects. The subject matter of the book containing 20 chapters is divided into three logical sections.
Section 1, comprising five chapters, deals with remote sensing observations and estimations. Chapter 1 discusses precipitation measurement from tropical to global. Beginning with global precipitation measurement (GPM) core observatory and constellation, it goes on to discuss the statistical validation of GPM precipitation products, hydrologic applications for both static and dynamic parameters, and concludes with an outlook. The chapter contains useful information. Chapter 2 is on evapotranspiration (ET) mapping with remote sensing data. Providing an overview of remote sensing-based ET mapping estimates, it first discusses the Penman-Monteith (PM) ET mapping methods and then global implementation of the PM ET mapping. The chapter summarizes limitations of the PM methods and future prospects.
Soil moisture estimation with both active and passive remote sensing is treated in Chapter 3. Microwave sensors, including radiative transfer process and radar backscatter, are discussed first. Satellite missions and microwave sensors are discussed next. The chapter then discusses soil moisture retrieval products, validation and uncertainty assessment, limitations, and applications. Chapter 4 deals with satellite remote sensing of lakes and wetlands. It first discusses estimates of surface elevation, surface area, and storage variations of lakes and reservoirs. Then it discusses estimates of surface elevation, inundated area, and storage change of wetlands. The chapter concludes with future vision. It also illustrates two useful practical applications. Drought and flood monitoring for a large karst plateau in southwest China with extended gravity recovery and climate experiment (GRACE) data is presented in Chapter 5. The chapter first discusses Yun-Gui Plateau and its individual basins, then discusses the evaluation of GRACE total water storage change using a water balance equation, artificial neural network (ANN), flood potential amount, and processing of hydrometeorologic and GRACE data, and finally discusses results obtained with these methods. The chapter concludes that ANN can be a powerful tool to reconstruct total water storage anomalies beyond the GRACE period, which can be useful for monitoring of floods and droughts.
Section 2, comprising eight chapters, is on modeling, data assimilation, and analysis. Chapter 6 deals with statistical and hydrologic evaluation of tropical rainfall measurement mission (TRMM)-based multisatellite precipitation analysis over the Wangchu basin of Bhutan. Starting with a discussion of the study area, it discusses in situ and satellite datasets. Then, using four statistical criteria, it compares precipitation inputs and streamflow simulation for two scenarios. An advanced distributed hydrologic framework—the development of coupled routing and excess water storage (CREST)—is described in Chapter 7. Beginning with a discussion of CREST versions 1.0 to 1.5, it goes on to discussing CREST version 2.0, the incoming version of CREST, and efficiency and convergence considerations. Assimilation of remotely sensed streamflow data to improve flood forecasting in an ungauged basin in Africa is discussed in Chapter 8. It first discusses streamflow estimation using remote sensing. Then, it illustrates the assimilation of remotely sensed information for improving hydrologic predictions and concludes with future prospects.
Chapter 9 deals with multisensor geospatial data for flood monitoring along Indus River, Pakistan. It first discusses satellite sensors for flood detection including optical sensors for flood mapping and microwave remote sensing based flood detection, and then satellite-based precipitation estimates for hydrologic modeling including space-based precipitation estimates and precipitation estimates for monsoon monitoring. It shows that satellite techniques are cost effective and hence can play a key role in hydrologic modeling at high resolution in space and time. Evaluation of the diurnal cycle of precipitation representation in west African monsoon region with different convection schemes is reported in Chapter 10. Beginning with precipitation observations from tropical rainfall measurement mission (TMPA), it discusses the regional spectral model and experimental set; analysis method; and precipitation characteristics, including amount, frequency, and intensity. Then it discusses simulation results with respect to amplitude; phase; land versus ocean in terms of amount, frequency, and intensity; and convective available energy. The chapter is concluded with a discussion of general behavior of the regional spectral model, convective parameterization schemes, and future work.
Chapter 11 deals with multiscale evaluation and applications of current global satellite-based precipitation products over the Yangtze River basin. It first discusses satellite-based precipitation products, ground gauge data, and a geomorphology-based hydrologic model. Then it presents annual scale comparison, seasonal estimation, and daily scale evaluation, and finally modeling-based evaluation of annual water balance simulation and streamflow simulation. It concludes that multisource precipitation information should be developed. Uncertainty analysis of five satellite-based precipitation products and evaluation of three optimally merged multialgorithm products over the Tibetan Plateau are presented in Chapter 12. The study area, data, and method are discussed first and then spatial distribution, snow cover fraction–dependent seasonal uncertainty, rain rate–dependent uncertainty, and topography-dependent uncertainty are discussed. Finally, uncertainty analysis of merged multialgorithm data ensembles is presented for statistical analysis and spatial distribution. Chapter 13 deals with the use of remote sensing–based precipitation data for flood frequency analysis in data poor regions. It first discusses the Blue Nile River basin, Ethiopia, then discusses flood frequency analysis (FFA), and finally compares simulated and observed flow quantiles. The reliability of the FFA model in predicting streamflow from satellite observations needs to be evaluated.
Section 3, containing seven chapters, is on hydrologic capacity building for improved societal resilience. Chapter 14 deals with real-time hydrologic prediction system in East Africa through a regional monitoring and visualization system (SERVIR). Introducing SERVIR Global and SERVIR Africa, it presents a case study of operational flood prediction system in Nzoia basin, East Africa, data used, and a conceptual physical distributed hydrological model. It shows that satellite-based rainfall and geospatial datasets are useful for cost-effective detection and early warning of natural hazards. Satellite remote sensing drought monitoring and predictions over the globe are discussed in Chapter 15. Providing an overview of drought indices, it presents satellite remote sensing drought indices, including indices from optical remote sensing, indices from thermal infrared remote sensing, indices from microwave remote sensing, and integrated indices; satellite remote sensing drought monitoring, including vegetation, precipitation, evapotranspiration, soil moisture, and groundwater; and finally satellite remote sensing drought prediction comprising an overview of drought prediction methods, satellite remote sensing drought prediction, and global meteorological drought prediction with remote sensing products.
Capacity building efforts in hydrologic modeling for Africa are presented in Chapter 16. The chapter first discusses capacity building with reference to coupled routing and excess storage (CREST). It then discusses efforts prior to 2015, including “2010: Kenya,” “2012: Namibia,” “2012: Kenya,” “2013: Namibia and Rwanda,” “2013: Nigeria,” “2014: Namibia,” and “2014 and Beyond: Lecture Videos.” Finally, current efforts and future efforts are detailed. Chapter 17 comprises an assessment of shallow landslides induced by Mitch using a physically based model with a case study in Honduras. Introducing landslides first, it discusses approaches for landslide forecast, available data and parameter initialization, and the slope infiltration distributed equilibrium (SLIDE) model. It then presents a case study.
Chapter 18 presents applied research and the future of flood monitoring in Indus River basin. Introducing the Indus basin, it discusses flood monitoring research in the basin, including geospatial data for flood monitoring, flood modeling research and development, and coupling of atmospheric forecast and hydrologic modeling. It then discusses capacity building in flood monitoring, and future improvements in hydrometeorological forecast and warning systems, including hydrometeorological observation stations and weather radar, flood early warning systems, hydraulic and hydrologic models, and hydrometeorological database systems and software systems. The chapter concludes with integrated water resources planning and management. Chapter 19 deals with the investigation of satellite-based observations for improving societal resilience to hydrometeorological hazard in Columbia. It begins with a pilot study on flood warning in the Bogota River basin and discusses hydrological modeling with satellite-based rainfall estimates from National Aeronautics and Space Administration’s (NASA’s) 3B42RT products and simulation of flooding events. It then provides a general evaluation of satellite-based rainfall estimates and flood detection skill. The last chapter, Chapter 20, is on cloud-based cyberinfrastructure for disaster monitoring and mitigation. Introducing cloudsourcing first, it discusses cyberinfrastructure design and application to a cyberflood case study containing data preparation and demonstration. It also discusses advantages, performance experiment, limitations and scalability, data sharing, and sustainability.
On the whole, this a very good and well written book. Chapters have been written by people who are well experienced in remote sensing and its applications. The editors of the book are known for their contributions in the remote sensing area and have done an excellent job at editing the chapters for preparing the book. They deserve a lot of applause for enriching the hydrologic literature. The book will be useful to students who are interested in remote sensing, faculty members who are interested in delving deeper into this emerging area and its applications, and the practitioners who are interested in applying the remote sensing technology to practical problems, especially in water resources management and disaster mitigation.

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Published In

Go to Journal of Hydrologic Engineering
Journal of Hydrologic Engineering
Volume 22Issue 11November 2017


Received: May 5, 2017
Accepted: May 16, 2017
Published online: Aug 18, 2017
Published in print: Nov 1, 2017
Discussion open until: Jan 18, 2018


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Vijay P. Singh, Ph.D., Dist.M.ASCE [email protected]
Distinguished Professor, Regents Professor and Caroline and William N. Lehrer Distinguished Chair in Water Engineering, Dept. of Biological and Agricultural Engineering, and Zachry Dept. of Civil Engineering, Texas A&M Univ., 321 Scoates Hall, TAMU 2117, College Station, TX 77843-2117. E-mail: [email protected]

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