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John D. Hottenstein, Guillermo E. Ponce-Campos, Julio Moguel-Yanes, and M. Susan Moran

1. Introduction Soil moisture plays an integral role within the hydrologic cycle as a critical link between soils, climate, and biogeography ( Legates et al. 2011 ). Soil moisture has been shown to influence soil respiration ( Geng et al. 2012 ), act as a thermal reservoir that impacts cloud formation and wind fields ( Ek and Holtslag 2004 ; Findell and Eltahir 2003 ; Entekhabi et al. 1996 ), and directly influence precipitation formation ( Koster et al. 2004 ). As the understanding of the

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Catherine Champagne, Andrew Davidson, Patrick Cherneski, Jessika L’Heureux, and Trevor Hadwen

1. Introduction Agricultural risk assessment is a key tool for determining potential and actual losses in food production that result from climatic extremes such as deficits and excesses of moisture in the soil and at the surface. Soil moisture is a key determinant of crop production, impacting field accessibility for seeding, harvest, and field management; sustaining productive crop growth; and often determining vulnerability of crops to disease and pests. Characterizing soil moisture and soil

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Sujay V. Kumar, Kenneth W. Harrison, Christa D. Peters-Lidard, Joseph A. Santanello Jr., and Dalia Kirschbaum

1. Introduction The need for accurate estimates of soil moisture conditions is well established, as it is important for a variety of science and applications. Soil moisture influences the partitioning of heat and moisture at the land–atmosphere interface ( Cohen and Entekhabi 1999 ; Koster et al. 2004 ; Seneviratne et al. 2006 ) and in the redistribution of rainfall into infiltration and runoff. Root-zone soil moisture has been shown to influence subseasonal prediction of precipitation

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Fan Chen, Wade T. Crow, and Dongryeol Ryu

1. Introduction Surface soil moisture plays a key role in determining the partitioning of surface-incident rainfall between infiltration and surface runoff. As a result, the characterization of prestorm soil moisture states is an important component of most hydrologic prediction systems. With the growing availability of satellite-derived surface soil moisture retrievals ( Naeimi et al. 2009 ; Entekhabi et al. 2010 ; Kerr et al. 2010 ), the application of data assimilation techniques in

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Marco L. Carrera, Stéphane Bélair, and Bernard Bilodeau

1. Introduction It has become increasingly clear that an accurate initialization of the land surface is important for skillful weather and seasonal climate predictions (e.g., Koster et al. 2004 ; Drusch 2007 ; Drusch and Viterbo 2007 ; Gao et al. 2008 ; Mahfouf 2010 ; Douville 2010 ). Soil moisture, snow characteristics, surface temperature, and vegetation properties of the land surface influence both the water and energy budgets, exerting important controls on land

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Amy McNally, Gregory J. Husak, Molly Brown, Mark Carroll, Chris Funk, Soni Yatheendradas, Kristi Arsenault, Christa Peters-Lidard, and James P. Verdin

1. Introduction Soil moisture is a critical variable for weather and climate forecasting and early warning for natural disasters like drought, floods, landslides, and fire. Soil moisture also plays an important role in the early warning of human health concerns like hunger and malaria. The Soil Moisture Active Passive (SMAP) mission ( https://smap.jpl.nasa.gov/ ) aims to provide high-quality soil moisture data and enhance predictive models for many applications. However, new tools need to be

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Susan Frankenstein, Maria Stevens, and Constance Scott

and RCI have also been estimated based on other available data. Based on a large number of field and laboratory strength tests on soil collected from over 1000 sites, the Geotechnical Laboratory at WES developed a set of empirical equations to predict both CI and RCI as a function of soil moisture and Unified Soil Classification System (USCS; Sullivan et al. 1997 ). Unlike the U.S. Department of Agriculture (USDA) soil texture scheme that is based only on grain size distribution, the USCS also

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C. Albergel, W. Dorigo, R. H. Reichle, G. Balsamo, P. de Rosnay, J. Muñoz-Sabater, L. Isaksen, R. de Jeu, and W. Wagner

1. Introduction The importance of soil moisture in the global climate system has recently been underlined by the Global Climate Observing System (GCOS) Programme endorsing soil moisture as an Essential Climate Variable (ECV). It is a crucial variable for numerical weather prediction (NWP) and climate projections because it plays a key role in hydrological processes. A good representation of soil moisture conditions can therefore help improve the forecasting of precipitation, droughts, and

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Husayn El Sharif, Jingfeng Wang, and Aris P. Georgakakos

space–time distribution of soil moisture is critical for irrigation decisions and for more efficient use of water resources across multiple sectors. Agricultural models, such as Decision Support System for Agrotechnology Transfer cropping system model (DSSAT-CSM; Tsuji et al. 1994 ), have been developed to predict the yield of various crops at field and regional scales. Crop yield modeling and prediction provide essential information for water resources management. One key output of the

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Randal D. Koster, Gregory K. Walker, Sarith P. P. Mahanama, and Rolf H. Reichle

current state of a system (e.g., snow amount, soil moisture, and climate indices), calibrated regressions are applied that transform these quantities into streamflow forecasts. The historical use of these statistical techniques is arguably a reflection of historical limitations in our ability to model accurately the physical processes that generate streamflow—in particular our ability to provide the high-resolution forcing and boundary condition data needed to support the physical modeling. The advent

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