Spatial variability and its scale dependency of observed and modeled soil moisture over different climate regions

Abstract. Past studies on soil moisture spatial variability have been mainly conducted at catchment scales where soil moisture is often sampled over a short time period; as a result, the observed soil moisture often exhibited smaller dynamic ranges, which prevented the complete revelation of soil moisture spatial variability as a function of mean soil moisture. In this study, spatial statistics (mean, spatial variability and skewness) of in situ soil moisture, modeled and satellite-retrieved soil moisture obtained in a warm season (198 days) were examined over three large climate regions in the US. The study found that spatial moments of in situ measurements strongly depend on climates, with distinct mean, spatial variability and skewness observed in each climate zone. In addition, an upward convex shape, which was revealed in several smaller scale studies, was observed for the relationship between spatial variability of in situ soil moisture and its spatial mean when statistics from dry, intermediate, and wet climates were combined. This upward convex shape was vaguely or partially observable in modeled and satellite-retrieved soil moisture estimates due to their smaller dynamic ranges. Despite different environmental controls on large-scale soil moisture spatial variability, the correlation between spatial variability and mean soil moisture remained similar to that observed at small scales, which is attributed to the boundedness of soil moisture. From the smaller support (effective area or volume represented by a measurement or estimate) to larger ones, soil moisture spatial variability decreased in each climate region. The scale dependency of spatial variability all followed the power law, but data with large supports showed stronger scale dependency than those with smaller supports. The scale dependency of soil moisture variability also varied with climates, which may be linked to the scale dependency of precipitation spatial variability. Influences of environmental controls on soil moisture spatial variability at large scales are discussed. The results of this study should be useful for diagnosing large scale soil moisture estimates and for improving the estimation of land surface processes.

[1]  T. Jackson,et al.  Ground‐based investigation of soil moisture variability within remote sensing footprints During the Southern Great Plains 1997 (SGP97) Hydrology Experiment , 1999 .

[2]  Paul A. Dirmeyer,et al.  Precipitation, Recycling, and Land Memory: An Integrated Analysis , 2009 .

[3]  T. Jackson,et al.  III. Measuring surface soil moisture using passive microwave remote sensing , 1993 .

[4]  T. Jackson,et al.  The USDA Natural Resources Conservation Service Soil Climate Analysis Network (SCAN) , 2007 .

[5]  M. Watkins,et al.  GRACE Measurements of Mass Variability in the Earth System , 2004, Science.

[6]  Marco Borga,et al.  Hillslope scale soil moisture variability in a steep alpine terrain , 2009 .

[7]  S. Islam,et al.  Multiscaling properties of soil moisture images and decomposition of large- and small-scale features using wavelet transforms , 1998 .

[8]  A. Rinaldo,et al.  On the spatial organization of soil moisture fields , 1995 .

[9]  Luca Brocca,et al.  Soil moisture spatial variability in experimental areas of central Italy , 2007 .

[10]  S. Seneviratne,et al.  A new perspective on the spatio-temporal variability of soil moisture: temporal dynamics versus time-invariant contributions , 2012 .

[11]  Thomas J. Jackson,et al.  Soil moisture retrieval from AMSR-E , 2003, IEEE Trans. Geosci. Remote. Sens..

[12]  M. Ek,et al.  Comparative analysis of relationships between NLDAS‐2 forcings and model outputs , 2012 .

[13]  T. Jackson,et al.  Field observations of soil moisture variability across scales , 2008 .

[14]  Minha Choi,et al.  Scaled spatial variability of soil moisture fields , 2007 .

[15]  Dongryeol Ryu,et al.  Characterization of footprint‐scale surface soil moisture variability using Gaussian and beta distribution functions during the Southern Great Plains 1997 (SGP97) hydrology experiment , 2005 .

[16]  M. Univer.  Ground-based investigation of soil moisture variability within remote sensing footprints during the Southern Great Plains 1997 (SGP97) Hydrology Experiment , 1999 .

[17]  Günter Blöschl,et al.  On the spatial scaling of soil moisture , 1999 .

[18]  Bailing Li,et al.  Improving estimated soil moisture fields through assimilation of AMSR-E soil moisture retrievals with an ensemble Kalman filter and a mass conservation constraint , 2011 .

[19]  Xu Liang,et al.  A downscaling framework for L band radiobrightness temperature imagery , 2003 .

[20]  Luca Brocca,et al.  Catchment scale soil moisture spatial–temporal variability , 2012 .

[21]  Wade T. Crow,et al.  Multi‐scale dynamics of soil moisture variability observed during SGP'97 , 1999 .

[22]  Günter Blöschl,et al.  Spatial variability of soil moisture and its implications for scaling , 2003 .

[23]  J. D. Tarpley,et al.  Real‐time and retrospective forcing in the North American Land Data Assimilation System (NLDAS) project , 2003 .

[24]  J. D. Tarpley,et al.  The multi‐institution North American Land Data Assimilation System (NLDAS): Utilizing multiple GCIP products and partners in a continental distributed hydrological modeling system , 2004 .

[25]  S. Swenson,et al.  Post‐processing removal of correlated errors in GRACE data , 2006 .

[26]  Qiang Zuo,et al.  Estimating the necessary sampling size of surface soil moisture at different scales using a random combination method , 2008 .

[27]  Wade T. Crow,et al.  The Value of Coarse-Scale Soil Moisture Observations for Regional Surface Energy Balance Modeling , 2002 .

[28]  J. Famiglietti,et al.  Estimating groundwater storage changes in the Mississippi River basin (USA) using GRACE , 2007 .

[29]  Mark S. Seyfried,et al.  Dielectric Loss and Calibration of the Hydra Probe Soil Water Sensor , 2005 .