This paper describes a data assimilation method that uses observations of snow covered area (SCA) to update hydrologic model states in a mountainous catchment in Colorado. The assimilation method uses SCA information as part of an ensemble Kalman filter to alter the sub-basin distribution of snow as well as the basin water balance. This method permits an optimal combination of model simulations and observations, as well as propagation of information across model states. Sensitivity experiments are conducted with a fairly simple snowpack/water-balance model to evaluate effects of the data assimilation scheme on simulations of streamflow. The assimilation of SCA information results in minor improvements in the accuracy of streamflow simulations near the end of the snowmelt season. The small effect from SCA assimilation is initially surprising. It can be explained both because a substantial portion of snowmelts before any bare ground is exposed, and because the transition from 100% to 0% snow coverage occurs fairly quickly. Both of these factors are basin-dependent. Satellite SCA information is expected to be most useful in basins where snow cover is ephemeral. The data assimilation strategy presented in this study improved the accuracy of the streamflow simulation, indicating that SCA is a useful source of independent information that can be used as part of an integrated data assimilation strategy.

Published by the American Geophysical Union as part of the Water Science and Application Series, Volume 3. Land surface hydrology integrates various physical, chemical and biological processes that occur above, on, and below the surface of the Earth. As a result, it is critical to accurately account for land surface processes within predictive models of hydrology, meteorology, and climate. One of our main difficulties, however, concerns the broad range of spatial and temporal scales that characterize land surface hydrological processes. For example, we determine infiltration by pore scale physics, while soil hydraulic conductivity remains a field scale property. Photosynthesis, respiration, and transpiration occur at the leaf scale. Runoff is a catchment scale process, and the variability of groundwater storage is a regional scale issue. Turbulence in land-atmosphere exchanges of heat, moisture, and momentum occur on the order of seconds to minutes, while variations in land surface and air temperatures occur much more gradually: on the order of hours. The persistence of floods and droughts is seasonal to annual, and so is the effect of El Nino on regional hydrology. Long-term climate effects occur much more slowly, on the order of years to decades.

A comprehensive reference on data assimilation and inverse problems, and their applications across a broad range of geophysical disciplines, ideal for researchers and graduate students. It highlights the importance of data assimilation for understanding dynamical processes of the Earth and its space environment, and summarises recent advances.

The continental hydrological cycle is one of the least understood components of the climate system. The understanding of the different processes involved is important in the fields of hydrology and meteorology.In this volume the main applications for continental hydrology are presented, including the characterization of the states of continental surfaces (water state, snow cover, etc.) using active and passive remote sensing, monitoring the Antarctic ice sheet and land water surface heights using radar altimetry, the characterization of redistributions of water masses using the GRACE mission, the potential of GNSS-R technology in hydrology, and remote sensing data assimilation in hydrological models.This book, part of a set of six volumes, has been produced by scientists who are internationally renowned in their fields. It is addressed to students (engineers, Masters, PhD) , engineers and scientists, specialists in remote sensing applied to hydrology. Through this pedagogical work, the authors contribute to breaking down the barriers that hinder the use of Earth observation data. Provides clear and concise descriptions of modern remote sensing methods Explores the most current remote sensing techniques with physical aspects of the measurement (theory) and their applications Provides chapters on physical principles, measurement, and data processing for each technique described Describes optical remote sensing technology, including a description of acquisition systems and measurement corrections to be made

The reprint book of the “Remote Sensing of Snow and Its Applications” Special Issue provides recent studies on all aspects of remote sensing of snow, from retrieving the data to the application. These studies mainly address the following: (a) New opportunities (Copernicus Sentinels) and emerging remote sensing methods, (b) use of snow data in modeling, and (c) characterization of snowpack.

Principles of Snow Hydrology describes the factors that control the accumulation, melting and runoff of water from seasonal snowpacks over the surface of the earth. The book addresses not only the basic principles governing snow in the hydrologic cycle, but also the latest applications of remote sensing, and techniques for modeling streamflow from snowmelt across large mixed land-use river basins. Individual chapters are devoted to climatology and distribution of snow, snowpack energy exchange, snow chemistry, ground-based measurements and remote sensing of snowpack characteristics, snowpack management, and modeling snowmelt runoff. Many chapters have review questions and problems with solutions available online. This book is a reference book for practicing water resources managers and a text for advanced hydrology and water resources courses which span fields such as engineering, earth sciences, meteorology, biogeochemistry, forestry and range management, and water resources planning.

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