Satellite Remote Sensing Of Terrestrial Hydrology

This book highlights several opportunities that exist in satellite remote sensing of large-scale terrestrial hydrology. It lays bare the novel concept of remote sensing hydrology and demonstrates key applications of advance satellite technology and new methods in advancing our fundamental understanding of environmental systems. This includes, using state-of-the-art satellite hydrology missions like the Gravity Recovery and Climate Experiment and other multi-mission satellite systems as important tools that underpin water resources planning and accounting. This book discusses and demonstrates how the efficacy, simplicity, and sophistication in novel computing platforms for big earth observation data can help facilitate environmental monitoring and improve contemporary understanding of climate change impacts on freshwater resources. It also provides opportunities for practitioners and relevant government agencies to leverage satellite-based information in a transdisciplinary context to address several environmental issues affecting society. This book provides a general framework and highlights methods to help improve our understanding of hydrological processes and impact analysis from extreme events (e.g., droughts, floods) and climate change.

Remote Sensing of the Terrestrial Water Cycle is an outcome of the AGU Chapman Conference held in February 2012. This is a comprehensive volume that examines the use of available remote sensing satellite data as well as data from future missions that can be used to expand our knowledge in quantifying the spatial and temporal variations in the terrestrial water cycle. Volume highlights include: - An in-depth discussion of the global water cycle - Approaches to various problems in climate, weather, hydrology, and agriculture - Applications of satellite remote sensing in measuring precipitation, surface water, snow, soil moisture, groundwater, modeling, and data assimilation - A description of the use of satellite data for accurately estimating and monitoring the components of the hydrological cycle - Discussion of the measurement of multiple geophysical variables and properties over different landscapes on a temporal and a regional scale Remote Sensing of the Terrestrial Water Cycle is a valuable resource for students and research professionals in the hydrology, ecology, atmospheric sciences, geography, and geological sciences communities.

This book is a collection of overview articles showing how space-based observations, combined with hydrological modeling, have considerably improved our knowledge of the continental water cycle and its sensitivity to climate change. Two main issues are highlighted: (1) the use in combination of space observations for monitoring water storage changes in river basins worldwide, and (2) the use of space data in hydrological modeling either through data assimilation or as external constraints. The water resources aspect is also addressed, as well as the impacts of direct anthropogenic forcing on land hydrology (e.g. ground water depletion, dam building on rivers, crop irrigation, changes in land use and agricultural practices, etc.). Remote sensing observations offer important new information on this important topic as well, which is highly useful for achieving water management objectives.Over the past 15 years, remote sensing techniques have increasingly demonstrated their capability to monitor components of the water balance of large river basins on time scales ranging from months to decades: satellite altimetry routinely monitors water level changes in large rivers, lakes and floodplains. When combined with satellite imagery, this technique can also measure surface water volume variations. Passive and active microwave sensors offer important information on soil moisture (e.g. the SMOS mission) as well as wetlands and snowpack. The GRACE space gravity mission offers, for the first time, the possibility of directly measuring spatio-temporal variations in the total vertically integrated terrestrial water storage. When combined with other space observations (e.g. from satellite altimetry and SMOS) or model estimates of surface waters and soil moisture, space gravity data can effectively measure groundwater storage variations. New satellite missions, planned for the coming years, will complement the constellation of satellites monitoring waters on land. This is particularly the case for the SWOT mission, which is expected to revolutionize land surface hydrology. Previously published in Surveys in Geophysics, Volume 37, No. 2, 2016

This book provides a practical introduction to remote sensing applications for detecting changes in the terrestrial water cycle and understanding the causes and consequences of these changes. Covering a wide range of innovative remote sensing approaches for hydrological study, this book contributes significantly to the knowledge base of hydrology in the Anthropocene, i.e., global change hydrology. It is an excellent reference for students and professionals in the fields of hydrology, climate change, and geography.

Traditional means of data gathering are inadequate for present purposes in hydrology and water management. Thus, hydrologists are urgently seeking new ways for supplementing their conventional data supplies. Satellite remote sensing is being explored increasingly as one possible answer to such data acquisition problems, both because of its perceived facility for providing greatly improved space and time coverage of key hydrological observation systems; and because the technologies of data acquisiton, transmission and processing have become more advanced and more capable. Although the use of remote sensing - especially from satellites - is currently less well developed in these contexts than in support of many other Earth resource and environmental sciences, much successful hydrological research has already been based upon satellite data and in limited but important ways satellite data have already begun to be used in water monitoring and management operations.

The book provides comprehensive information on possible applications of remote sensing data for hydrological monitoring and modelling as well as for water management decisions. Mathematical theory is provided only as far as it is necessary for understanding the underlying principles. The book is especially timely because of new programs and sensors that are or will be realised. ESA, NASA, NASDA as well as the Indian and the Brazilian Space Agency have recently launched satellites or developed plans for new sensor systems that will be especially pertinent to hydrology and water management. New techniques are presented whose structure differ from conventional hydrological models due to the nature of remotely sensed data.

Water resources are the most valuable resources of sustainable socio-economic development, which is significantly affected by climate change and human activities. Water resources assessment is an urgent need for implementation of the perfect water resources management, but it is difficult to accurately evaluate the quantity and quality of water resources, especially in arid regions and high-altitude regions with sparse gauged data. This book hosts 24 papers devoted to remote sensing in hydrology and water resources management, which summarizes the recent advancement in remote sensing technology for hydrology analysis such as satellite remote sensing for water resources management, water quality monitoring and evaluation using remote sensing data, remote sensing for detecting the global impact of climate extremes, the use of remote sensing data for improved calibration of hydrological models, and so on. In general, the book will contribute to promote the application of remote sensing technology in water resources.

This book presents the fundamentals of data assimilation and reviews the application of satellite remote sensing in hydrological data assimilation. Although hydrological models are valuable tools to monitor and understand global and regional water cycles, they are subject to various sources of errors. Satellite remote sensing data provides a great opportunity to improve the performance of models through data assimilation.