Note: Front Cover -- Satellite Soil Moisture Retrieval: Techniques and Applications -- Copyright -- Dedication -- Contents -- List of Contributors -- Author Biographies -- Preface -- Acknowledgments -- About the Cover -- Section I: Introduction -- Chapter 1: Soil Moisture from Space: Techniques and Limitations -- 1. Introduction -- 2. Means of Measuring Soil Moisture -- 2.1. Remotely Sensed Soil Moisture, The Main Approaches -- 2.2. Microwave as a Tool for Soil Moisture Monitoring: Current Status -- 3. Satellite Missions -- 4. Soil Moisture Retrieval From Space Using Passive Microwaves -- 4.1. Surface Soil Moisture -- 4.2. Root-Zone Soil Moisture -- 5. Way Forward -- 6. Caveats -- 7. Conclusions and Perspectives -- References -- Chapter 2: Available Data Sets and Satellites for Terrestrial Soil Moisture Estimation -- 1. Introduction -- 2. In Situ Data Sets for Soil Moisture -- 2.1. International Soil Moisture Network -- 2.2. Field Campaigns -- 2.2.1. Soil Moisture Experiments Series -- 2.2.1.1. Soil Moisture Experiment 2002 -- 2.2.1.2. Soil Moisture Experiment 2003 -- 2.2.1.3. Soil Moisture Experiment 2004 -- 2.2.1.4. Soil Moisture Experiment 2005 -- 2.2.2. Canadian Experiment for Soil Moisture in 2010 -- 2.2.3. Soil Moisture Active Passive Validation Experiment -- 2.2.3.1. SMAPVEX08 -- 2.2.3.2. SMAPVEX12 -- 2.2.4. Soil Moisture Active Passive Experiments -- 2.3. FLUXNET sites -- 3. Satellite Data Sets for Soil Moisture -- 3.1. The Scanning Multichannel Microwave Radiometer (SMMR) -- 3.2. Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E/2) -- 3.3. Advanced Scatterometer (ASCAT) -- 3.4. Soil Moisture and Ocean Salinity (SMOS) -- 3.5. Soil Moisture Active and Passive (SMAP) Mission -- 4. Conclusion -- References -- Section II: Optical and Infrared Techniques & -- Synergies Between them. , Chapter 3: Soil Moisture Retrievals Using Optical/TIR Methods -- 1. Introduction -- 2. Optical/TIR Model History and Concept -- 2.1. History -- 2.2. The Ts/VI Concept -- 3. Optical/TIR Models Used for SM Estimation -- 3.1. Direct Estimation of SM From Ts/VI Space -- 3.2. Models Based on Ts/VI and Empirical Equations -- 4. Case Study: Estimation of SM Using Optical/TIR RS in the Canadian Prairies -- 4.1. Introduction -- 4.2. Materials and Methods -- 4.2.1. Study Area and Data -- 4.2.2. Methodology -- 4.3. Results -- 4.3.1. Comparing EF Estimations Retrieved From Three Different Approaches -- 4.3.2. SM Estimation From Evaporative Fraction -- 4.3.3. Correlations Between Estimated SM and Field Data -- 5. Summary and Future Outlook -- References -- Chapter 4: Optical/Thermal-Based Techniques for Subsurface Soil Moisture Estimation -- 1. Introduction -- 2. Methodology -- 2.1. Study Area -- 2.2. Satellite Data, Estimation of TVDI, and Measurements -- 3. Results and Discussion -- 3.1. TVDI Parameters -- 3.2. Comparison of TVDI and Subsurface Soil Moisture Measurements -- 4. Conclusions -- References -- Chapter 5: Spatiotemporal Estimates of Surface Soil Moisture from Space Using the Ts/VI Feature Space -- 1. Introduction -- 2. The Ts/VI Domain -- 3. Experimental Set Up and Data Sets -- 3.1. CarboEurope In Situ Measurements -- 3.2. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Imagery -- 3.3. The Advanced Along Track Scanning Radiometer (AATSR) Imagery -- 3.4. The SimSphere Land Biosphere Model -- 4. Methodology -- 4.1. Preprocessing -- 4.2. ``Triangle´´ Implementation -- 4.3. Coupling EO With the SVAT Model to Retrieve SMC -- 5. Results -- 6. Discussion -- 7. Conclusions -- Acknowledgments -- References -- Chapter 6: Spatial Downscaling of Passive Microwave Data With Visible-to-Infrared Information for High-Resolution Soil Mo. , 1. Introduction -- 2. A Semiempirical Model to Capture the Synergy of Passive Microwaves With Optical Data at Different Spatial Scales -- 3. High-Resolution Soil Moisture Mapping From Space -- 3.1. Long-Term Validation Over the Central Part of the Duero Basin -- 3.2. Exploring the Use of SWIR-Based Vegetation Indices to Disaggregate SMOS Observations to 500m -- 4. Airborne Field Experiments -- 4.1. Airborne Platform for Simultaneous Thermal, VNIR Hyperspectral and Microwave L-Band Acquisions: Proof-of-Concept and... -- 4.2. Airborne GNSS-R and Landsat 8 for Soil Moisture Estimation -- 5. Future Lines and Recommendations -- Acknowledgments -- References -- Section III: Microwave Soil Moisture Retrieval Techniques -- Chapter 7: Soil Moisture Retrieved From a Combined Optical and Passive Microwave Approach: Theory and Applications -- 1. Introduction -- 2. Radiative Transfer Equation -- 2.1. Tau-Omega Model -- 2.2. Effective Temperature, Single Dispersion and Vegetation Optical Depth -- 2.3. A Combined Optical-Passive Microwave Approach -- 2.4. Case Study-Optical Passive Microwave at in-situ level -- 2.5. Case Study-Optical Passive Microwave at Regional Scale -- 2.5.1. Study Area -- 2.5.2. Data -- 2.5.3. Results -- 2.5.4. Discussion -- 2.6. Toward a Thermal Infrared Contribution in the Optical-Passive Microwave Approach -- 3. Conclusions -- Acknowledgments -- References -- Chapter 8: Nonparametric Model for the Retrieval of Soil Moisture by Microwave Remote Sensing -- 1. Introduction -- 2. Material and Methods -- 2.1. Instrumentation Setup and Observations -- 2.2. Radial Basis Function Artificial Neural Network -- 2.3. Performance Indices -- 3. Results and Discussion -- 3.1. Assessment of Data Sets -- 3.2. Estimation of Soil Moisture Using the RBFANN -- 4. Conclusions -- References. , Chapter 9: Temperature-Dependent Spectroscopic Dielectric Model at 0.05-16 GHz for a Thawed and Frozen Alaskan Organic Soil -- 1. Introduction -- 2. Soil Samples and Measurement Procedures -- 3. Concept of a Multirelaxation Spectroscopic Dielectric Model -- 4. Retrieving the Parameters of the Multirelaxation Spectroscopic Dielectric Model -- 5. The Temperature-Dependent Multirelaxation Spectroscopic Dielectric Model -- 6. Evaluation of the TD MRSDM -- 7. Conclusions -- References -- Chapter 10: Active and Passive Microwave Remote Sensing Synergy for Soil Moisture Estimation -- 1. Introduction -- 1.1. Measurement Spatial Resolution -- 1.2. Soil Moisture Sensitivity and Estimation Accuracy -- 2. SR CAP Soil Moisture Retrieval -- 3. MR CAP Soil Moisture Retrieval -- 3.1. Multi-Temporal and Multi-Scale Method -- 3.2. Probabilistic and Machine Learning Techniques -- 4. Forward Electromagnetic Scattering and Emission Model Considerations -- 5. Further Discussions -- References -- Chapter 11: Intercomparison of Soil Moisture Retrievals From In Situ, ASAR, and ECV SM Data Sets Over Different European ... -- 1. Introduction -- 2. Materials and Methods -- 2.1. In Situ Soil Moisture Observations -- 2.2. ECV Soil Moisture Observations -- 2.3. ASAR Soil Moisture Observations -- 2.4. Characterization of Errors -- 3. Results and Discussion -- 3.1. Time Series Temporal Analysis -- 3.2. Seasonal Analysis -- 4. Conclusions -- Acknowledgments -- References -- Section IV: Advanced Applications of Soil Moisture -- Chapter 12: Use of Satellite Soil Moisture Products for the Operational Mitigation of Landslides Risk in Central Italy -- 1. Introduction -- 2. PRESSCA Early Warning System -- 3. Case Study and Data Sets -- 3.1. Study Area and Ground Meteorological Observations -- 3.2. Satellite Soil Moisture Observations -- 4. Results and Discussion. , 4.1. Comparison Between Satellite, In Situ, and Modeled Soil Moisture Data -- 4.2. Impact of Soil Moisture Condition on Landslide Hazard -- 5. Conclusions and Future Perspectives -- Acknowledgments -- References -- Chapter 13: Remotely Sensed Soil Moisture as a Key Variable in Wildfires Prevention Services: Towards New Prediction Tool... -- 1. Introduction -- 2. Remotely Sensed Soil Moisture, Climate Change, and Fire Risk -- 2.1. Remote Sensing of the Earth's Soil Moisture -- 2.2. Remotely Sensed Soil Moisture, Climate Change, and Fire Risk -- 3. The Role of Soil Moisture in Forest Fires -- 3.1. Droughts and High Temperatures Lead to Extreme Forest Fires Events -- 3.2. Dead Fuels Moisture Is a Key Variable in Forest Fire Risk Indices -- 4. Linking Remotely Sensed Soil Moisture With Forest Fires Ignition and Propagation -- 5. Fire Risk Assessment in the Iberian Peninsula Using SMOS Data -- 5.1. New Fire Risk Maps Over the Iberian Peninsula Based on SMOS Data -- 5.2. Fire Risk Maps Availability and Operational Applications -- 6. Conclusions -- Acknowledgments -- References -- Chapter 14: Integrative Use of Near-Surface Satellite Soil Moisture and Precipitation for Estimation of Improved Irrigati... -- 1. Introduction -- 2. Material and Methods -- 2.1. Study Area -- 2.2. Ground Validation Data -- 2.3. Satellite Data -- 2.4. Numerical Modeling -- 2.4.1. Initial and Boundary Conditions -- 2.4.2. Soil Parameters -- 2.5. Evaluation Criteria -- 3. Results and Discussion -- 3.1. Comparison of TRMM Rainfall With Ground-Based Rainfall Measurements -- 3.2. Soil Hydraulic Parameters -- 3.3. Soil Moisture Calibration and Validation -- 4. Conclusions -- Acknowledgments -- References -- Chapter 15: A Comparative Study on SMOS and NLDAS-2 Soil Moistures Over a Hydrological Basin-With Continental Climate -- 1. Introduction -- 2. Data and Methodology. , 2.1. Study Area and Data Sets.

Note: Intro -- Contents -- Foreword: International Space Science Institute (ISSI) Workshop on the Earth's Hydrological Cycle -- References -- Review of Understanding of Earth's Hydrological Cycle: Observations, Theory and Modelling -- Abstract -- Introduction -- Clouds and Precipitation -- Soil Moisture -- Evapotranspiration -- Ground Water Observations -- Water Extent and Levels -- Vegetation Stage -- Water Vapour -- Snow -- Permafrost -- Glaciers and Ice Caps -- Ice Sheet -- Sea Ice -- Sea Level -- Sea-surface Salinity -- Freshwater Discharge for Large Mid-Latitude and Tropical Rivers -- Conclusions and Observational Needs for the Future -- Acknowledgments -- References -- Challenges and Opportunities in Water Cycle Research: WCRP Contributions -- Abstract -- Introduction -- The WCRP -- The Global Water Budget and Hydrological Cycle -- Grand Challenges -- Grand Challenge on Water Resources -- Grand Challenge on Water Extremes -- Conclusions -- Acknowledgments -- References -- Physically Consistent Responses of the Global Atmospheric Hydrological Cycle in Models and Observations -- Abstract -- Introduction -- Constraints upon Global Mean Precipitation Responses -- Simple Model of Global Precipitation -- Transient Response in Global Precipitation in CMIP5 Models -- Current Changes in the Global Atmospheric Water Cycle -- Water Vapor and Regional Constraints on Precipitation -- Moisture Flux into Tropical Wet Regions -- Precipitation Response in the Wet and Dry Regions of the Tropics -- Extremes of Precipitation -- Influence of Dynamical Changes on Precipitation and Its Extremes -- Conclusions -- Acknowledgments -- References -- Quantifying and Reducing Uncertainty in the Large-Scale Response of the Water Cycle -- Abstract -- Introduction -- Scientific Challenges in Modelling the Global Water Cycle -- Global Water Budget -- The Role of Model Resolution. , Influence of Resolution on Global Precipitation -- Resolved Versus Parametrised Processes in Models -- Representing Hydrological Processes and Phenomena -- Clouds, Humidity and Radiation -- Model Representations of Cloud and Precipitation and Their Evaluation -- Diurnal Cycle of Clouds and Precipitation -- Precipitation in Mid-latitude Cyclones -- Land--Atmosphere Interactions -- Ocean--Atmosphere Processes and Interactions -- The Role of the Cryosphere -- Global Monsoons -- Summary -- Acknowledgments -- References -- Connecting Satellite Observations with Water Cycle Variables Through Land Data Assimilation: Examples Using the NASA GEOS-5 LDAS -- Abstract -- Introduction -- Data and Methods -- GEOS-5 Land Data Assimilation System -- Assimilated Observations -- Validation Data and Approach -- Results -- Assimilation of Sparse and Coarse-Scale Observations -- Partitioning of Terrestrial Water Storage Observations -- Microwave Radiative Transfer Models for Radiance Data Assimilation -- Warm-Season, L-Band Radiative Transfer Modeling -- Predicting Microwave Brightness Temperatures over Snow -- Observation Selection for a Root Zone Soil Moisture Analysis -- Using Precipitation Observations -- Assimilating Surface Soil Moisture Retrievals -- Combining Precipitation Observations and Surface Soil Moisture Retrievals -- Summary and Discussion -- Conclusions and Outlook -- Acknowledgments -- References -- Initialisation of Land Surface Variables for Numerical Weather Prediction -- Abstract -- Introduction -- Snow Analysis -- Snow Forecast Models -- Snow Observations -- Snow Analysis Methods -- Results -- Soil Moisture Analysis -- History of Soil Moisture Analysis for NWP -- Comparison Between the OI and EKF Soil Moisture Analyses -- Use of Satellite Data to Analyse Soil Moisture -- Conclusion -- Acknowledgments -- References. , Closing the Gaps in Our Knowledge of the Hydrological Cycle over Land: Conceptual Problems -- Abstract -- Introduction -- Observations of the Hydrological Cycle -- Models of the Hydrological Cycle -- Data Assimilation of the Hydrological Cycle -- Introduction -- Data Assimilation Methods -- Representation of Errors -- Advantages and Disadvantages of Assimilation Methods -- Example of a Land Data Assimilation System -- Data Assimilation Research Applications -- Single-column Applications -- Distributed Applications -- Towards Operational Land Data Assimilation -- Conceptual Problems and Key Challenges -- Assimilated Observations -- Forward and Retrieval Models, with Particular Reference to Radiances and Backscatter Processes -- Land Surface Models -- Data Assimilation Challenges -- Validation -- Conclusions -- Acknowledgments -- Appendix: Sensor acronyms -- References -- Toward Improved Estimation of the Dynamic Topography and Ocean Circulation in the High Latitude and Arctic Ocean: The Importance of GOCE -- Abstract -- Introduction -- Ocean Dynamic Topography -- Surface Circulation -- Volume Transport -- Summary -- Acknowledgments -- References -- Sea Surface Salinity Observations from Space with the SMOS Satellite: A New Means to Monitor the Marine Branch of the Water Cycle -- Abstract -- Introduction -- Data -- SMOS SSS Data -- Ocean Surface Currents -- Rain, Evaporation and River Discharge Data -- Ocean Color Products -- In Situ Data -- SMOS Monitoring of the Major Tropical Atlantic River Plumes -- Amazon and Orinoco River Plume Monitoring -- Eastern Tropical Atlantic Freshwater Pools Monitoring -- Precipitation Signatures in SSS Data from Space -- SSS Temporal Variability Associated with Rain Events -- Systematically Fresher Skin SSS in Rainy Regions -- SSS as a Tracer of the Evaporation--Precipitation Budget in the Oceanic Mixed Layer. , Large-scale SSS Interannual Variability in Tropical Indian and Pacific Oceans -- Fresh Pool Interactions with Wind-driven Processes -- An Example of Fresh Pool Erosion by Wind-driven Upwelling -- Fresh Pool Interactions with Tropical Cyclones -- Conclusions and Perspectives -- Acknowledgments -- References -- Role of Ocean in the Variability of Indian Summer Monsoon Rainfall -- Abstract -- Introduction -- Monsoon Onset Over India -- Active--Break Cycle of Monsoon -- Inter-annual and Decadal Variability of Monsoon -- Rapid Warming of the Indian Ocean -- Summary and Conclusions -- References -- Perspectives in Modelling Climate--Hydrology Interactions -- Abstract -- Introduction -- Impact of Anthropogenic Land Use, Especially Irrigation, on Climate -- Impact of Irrigation on the South Asian Summer Monsoon (SASM) -- Conclusions and Perspectives for the Impact of Irrigation on Climate -- Permafrost -- Basic Hydrological Processes in Permafrost Areas -- Representation of Permafrost Processes in ESMs -- Wetlands -- Concluding Remark -- Acknowledgments -- References -- Downscaling Satellite Precipitation with Emphasis on Extremes: A Variational ell1-Norm Regularization in the Derivative Domain -- Abstract -- Introduction -- Precipitation Downscaling as a Regularized Inverse Problem -- Basic Concepts in the Continuous Space -- Discrete Representation -- Geometrical Versus Statistical Interpretation of the ell1-Norm Regularized Downscaling -- Working with an Unknown Downgrading Operator (H) -- Results from a Case Study -- Concluding Remarks -- Acknowledgments -- References -- Global Snow Mass Measurements and the Effect of Stratigraphic Detail on Inversion of Microwave Brightness Temperatures -- Abstract -- Introduction -- Current Snow Mass Estimation -- General Circulation Models and Reanalyses -- Products Which Prioritise Snow -- Surface Observations Only. , Land Surface Models Assimilating In Situ Observations -- Remote Sensing of Snow Mass -- Assimilation of Passive Microwave Observations to Improve Snow Mass Estimation -- Assimilation of Passive Microwave Brightness Temperatures -- Globsnow -- Methodology -- Limitations of Globsnow -- Methods -- The Cold Land Processes Experiment (CLPX) Resampled Snowpits -- Comparison: Layered HUT Scene Simulation Versus Observations -- Comparison: N-layer Versus Fewer Layers of Stratigraphic Information -- Results and Analysis -- Snow Properties at CLPX Sites -- Simulated Scene Brightness Temperatures -- Differences Due to Layering Detail -- Discussion and Conclusions -- Acknowledgments -- References -- Glaciers in the Earth's Hydrological Cycle: Assessments of Glacier Mass and Runoff Changes on Global and Regional Scales -- Abstract -- Introduction -- Assessing glacier mass balance on regional and global scales -- Assessments by in situ mass-balance measurements -- Assessments by geodetic method -- Assessments using satellite gravimetry -- Assessments by other approaches -- AAR method -- Multi-method approach -- Modeling glacier mass balance on regional and global scales -- Models based on mass-balance sensitivity -- Models of surface mass balance -- Model limitations -- Glacier runoff -- Effects of glaciers on streamflow -- What is glacier runoff? -- Assessing global-scale impacts of glaciers on the hydrological cycle -- Synthesis and discussion -- Conclusions -- Acknowledgments -- References -- Observing Global Surface Water Flood Dynamics -- Abstract -- Introduction: Surface Water Floods in the Earth System -- Observing Global Flood Dynamics -- Remote Measurements of Floodplain Topography -- Remote Measurements of Inundation Extent -- Remote Measurements of Water Elevation -- Remote Measurements of Water Storage -- The Proposed SWOT Satellite Mission. , Inferring Remaining Unknown Variables Using DA.