Spatial variability of shallow soil moisture and its stable isotope values on a karst hillslope

Geoderma ◽  
2016 ◽  
Vol 264 ◽  
pp. 61-70 ◽  
Author(s):  
Jing Yang ◽  
Hongsong Chen ◽  
Yunpeng Nie ◽  
Wei Zhang ◽  
Kelin Wang
Keyword(s):  
Soil Moisture ◽  
Stable Isotope ◽  
Spatial Variability ◽  
Shallow Soil ◽  
Karst Hillslope

scholarly journals Effects of micro-topography and vegetation type on soil moisture in a large gully on the Loess Plateau of China

2017 ◽  
Vol 49 (4) ◽  
pp. 1255-1270 ◽  
Author(s):  
Bowei Yu ◽  
Gaohuan Liu ◽  
Qingsheng Liu ◽  
Jiuliang Feng ◽  
Xiaoping Wang ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Spatial Variability ◽  
Loess Plateau ◽  
Root Zone ◽  
Plane Surface ◽  
Vegetation Type ◽  
Chinese Loess Plateau ◽  
Chinese Loess ◽  
Micro Topography ◽  
The Chinese Loess Plateau

Abstract Large gullies occur globally and can be classified into four main micro-topographic types: ridges, plane surfaces, pipes and cliffs. Afforestation is an effective method of controlling land degradation worldwide. However, the combined effects of afforestation and micro-topography on the variability of soil moisture remain poorly understood. The primary objectives of this study were to determine whether afforestation affects the spatial pattern of the root-zone (0–100 cm) soil moisture and whether soil moisture dynamics differ among the micro-topographic types in gully areas of the Chinese Loess Plateau. The results showed that in the woodland regions, the spatial mean moisture values decreased by an average of 6.2% and the spatial variability increased, as indicated by the standard deviation (17.1%) and the coefficient of variation (22.2%). In general, different micro-topographic types exerted different influences on soil moisture behavior. The plane surface presented the largest average soil moisture values and the smallest spatial variability. The lowest soil moisture values were observed in the ridge, mainly due to the rapid drainage of these areas. Although pipe woodland region can concentrate surface runoff during and after rainfall, the larger trees growing in these areas can lead to increased soil moisture evapotranspiration.

Statistical characterization of the spatial variability of soil moisture in a cutover peatland

2004 ◽  
Vol 18 (1) ◽  
pp. 41-52 ◽  
Author(s):  
Richard M. Petrone ◽  
J. S. Price ◽  
S. K. Carey ◽  
J. M. Waddington
Keyword(s):  
Soil Moisture ◽  
Spatial Variability ◽  
Statistical Characterization

Spatial dynamics of soil moisture and temperature in a black spruce boreal chronosequence

2006 ◽  
Vol 36 (11) ◽  
pp. 2794-2802 ◽  
Author(s):  
Ben Bond-Lamberty ◽  
Karen M Brown ◽  
Carol Goranson ◽  
Stith T Gower
Keyword(s):  
Soil Moisture ◽  
Spatial Variability ◽  
Sampling Design ◽  
Black Spruce ◽  
Structural Characteristics ◽  
Spatial Dynamics ◽  
Spherical Model ◽  
Local Scale ◽  
Spatial Dependencies ◽  
The Mean

This study analyzed the spatial dependencies of soil moisture and temperature in a six-stand chronosequence of boreal black spruce (Picea mariana (Mill.) BSP) stands. Spatial variability of soil temperature (TSOIL) was evaluated twice during the growing season using four transects in each stand, employing a cyclic sampling design with measurements spaced 2–92 m apart. Soil moisture (θg) was measured on one occasion. A spherical model was used to analyze the geostatistical correlation structure; θg and TSOIL at the 7- and 21-year-old stands did not exhibit stable ranges or sills. The fits with stable ranges and sills modeled the spatial patterns in the older stands reasonably well, although unexplained variability was high. Calculated ranges varied from 3 to 150 m for these stands, lengths probably related to structural characteristics influential in local-scale energy transfer. Transect-to-transect variability was significant and typically 5%–15% of the mean for TSOIL and 10%–70% for θg. TSOIL and θg were negatively correlated for most stands and depths, with TSOIL dropping 0.5–0.9 °C for every 1% rise in θg. The results reported here provide initial data to assess the spatial variability of TSOIL and θg in a variety of boreal forest stand ages.

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

2013 ◽  
Vol 17 (3) ◽  
pp. 1177-1188 ◽  
Author(s):  
B. Li ◽  
M. Rodell
Keyword(s):  
Soil Moisture ◽  
Spatial Variability ◽  
Land Surface ◽  
Large Scale ◽  
Warm Season ◽  
Scale Dependency ◽  
Convex Shape ◽  
Spatial Moments ◽  
Environmental Controls

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.

scholarly journals Estimating flow and transport parameters in the unsaturated zone with pore water stable isotopes

2015 ◽  
Vol 19 (6) ◽  
pp. 2617-2635 ◽  
Author(s):  
M. Sprenger ◽  
T. H. M. Volkmann ◽  
T. Blume ◽  
M. Weiler
Keyword(s):  
Soil Moisture ◽  
Stable Isotope ◽  
Solute Transport ◽  
Water Flow ◽  
Pore Water ◽  
Pedotransfer Functions ◽  
Transport Parameters ◽  
Soil Moisture Dynamics ◽  
Moisture Dynamics ◽  
Water Isotope

Abstract. Determining the soil hydraulic properties is a prerequisite to physically model transient water flow and solute transport in the vadose zone. Estimating these properties by inverse modelling techniques has become more common within the last 2 decades. While these inverse approaches usually fit simulations to hydrometric data, we expanded the methodology by using independent information about the stable isotope composition of the soil pore water depth profile as a single or additional optimization target. To demonstrate the potential and limits of this approach, we compared the results of three inverse modelling strategies where the fitting targets were (a) pore water isotope concentrations, (b) a combination of pore water isotope concentrations and soil moisture time series, and (c) a two-step approach using first soil moisture data to determine water flow parameters and then the pore water stable isotope concentrations to estimate the solute transport parameters. The analyses were conducted at three study sites with different soil properties and vegetation. The transient unsaturated water flow was simulated by solving the Richards equation numerically with the finite-element code of HYDRUS-1D. The transport of deuterium was simulated with the advection-dispersion equation, and a modified version of HYDRUS was used, allowing deuterium loss during evaporation. The Mualem–van Genuchten and the longitudinal dispersivity parameters were determined for two major soil horizons at each site. The results show that approach (a), using only the pore water isotope content, cannot substitute hydrometric information to derive parameter sets that reflect the observed soil moisture dynamics but gives comparable results when the parameter space is constrained by pedotransfer functions. Approaches (b) and (c), using both the isotope profiles and the soil moisture time series, resulted in good simulation results with regard to the Kling–Gupta efficiency and good parameter identifiability. However, approach (b) has the advantage that it considers the isotope data not only for the solute transport parameters but also for water flow and root water uptake, and thus increases parameter realism. Approaches (b) and (c) both outcompeted simulations run with parameters derived from pedotransfer functions, which did not result in an acceptable representation of the soil moisture dynamics and pore water stable isotope composition. Overall, parameters based on this new approach that includes isotope data lead to similar model performances regarding the water balance and soil moisture dynamics and better parameter identifiability than the conventional inverse model approaches limited to hydrometric fitting targets. If only data from isotope profiles in combination with textural information is available, the results are still satisfactory. This method has the additional advantage that it will not only allow us to estimate water balance and response times but also site-specific time variant transit times or solute breakthrough within the soil profile.

scholarly journals Sampling density and date influence spatial representation of tree ring reconstructions

2020 ◽  
Author(s):  
Justin T. Maxwell ◽  
Grant L. Harley ◽  
Trevis J. Matheus ◽  
Brandon M. Strange ◽  
Kayla Van Aken ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Spatial Variability ◽  
Tree Ring ◽  
Tree Rings ◽  
Large Scale ◽  
The United States ◽  
Severe Drought ◽  
Ring Network ◽  
Tree Ring Data ◽  
The Us

Abstract. Our understanding of the natural variability of hydroclimate before the instrumental period (ca. 1900 in the United States; US) is largely dependent on tree-ring-based reconstructions. Large-scale soil moisture reconstructions from a network of tree-ring chronologies have greatly improved our understanding of the spatial and temporal variability in hydroclimate conditions, particularly extremes of both drought and pluvial (wet) events. However, certain regions within these large-scale reconstructions in the US have a sparse network of tree-ring chronologies. Further, several chronologies were collected in the 1980s and 1990s, thus our understanding of the sensitivity of radial growth to soil moisture in the US is based on a period that experienced multiple extremely severe droughts and neglects the impacts of recent, rapid global change. In this study, we expanded the tree-ring network of the Ohio River Valley in the US, a region with sparse coverage. We used a total of 72 chronologies across 15 species to examine how increasing the density of the tree-ring network influences the representation of reconstructing the Palmer Meteorological Drought Index (PMDI). Further, we tested how the sampling date influenced the reconstruction models by creating reconstructions that ended in the year 1980 and compared them to reconstructions ending in 2010 from the same chronologies. We found that increasing the density of the tree-ring network resulted in reconstructed values that better matched the spatial variability of instrumentally recorded droughts and to a lesser extent, pluvials. By sampling tree in 2010 compared to 1980, the sensitivity of tree rings to PMDI decreased in the southern portion of our region where severe drought conditions have been absent over recent decades. We emphasize the need of building a high-density tree-ring network to better represent the spatial variability of past droughts and pluvials. Further, chronologies on the International Tree-Ring Data Bank need updating regularly to better understand how the sensitivity of tree rings to climate may vary through time.

scholarly journals Spatial variability and its scale dependency of observed and modeled soil moisture under different climate conditions

2012 ◽  
Vol 9 (9) ◽  
pp. 10245-10276 ◽  
Author(s):  
B. Li ◽  
M. Rodell
Keyword(s):  
Soil Moisture ◽  
Spatial Variability ◽  
Warm Season ◽  
Weather Conditions ◽  
Data Sets ◽  
Scale Dependency ◽  
Convex Shape ◽  
Climate Conditions ◽  
Spatial Moments

Abstract. Past studies on soil moisture spatial variability have been mainly conducted in catchment scales where soil moisture is often sampled over a short time period. Because of limited climate and weather conditions, 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 measurements (from a continuously monitored network across the US), modeled and satellite retrieved soil moisture obtained in a warm season (198 days) were examined at large extent scales (>100 km) over three different climate regions. The investigation on in situ measurements revealed that their spatial moments 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 across dry, intermediate, and wet climates. These climate specific features were vaguely or partially observable in modeled and satellite retrieved soil moisture estimates, which is attributed to the fact that these two data sets do not have climate specific and seasonal sensitive mean soil moisture values, in addition to lack of dynamic ranges. From the point measurements to satellite retrievals, soil moisture spatial variability decreased in each climate region. The three data sources all followed the power law in the scale dependency of spatial variability, with coarser resolution data showing stronger scale dependency than finer ones. The main findings from this study are: (1) the statistical distribution of soil moisture depends on spatial mean soil moisture values and thus need to be derived locally within any given area; (2) the boundedness of soil moisture plays a pivoting role in the dependency of soil moisture spatial variability/skewness on its mean (and thus climate conditions); (3) the scale dependency of soil moisture spatial variability changes with climate conditions.

Sign in / Sign up

Export Citation Format

Share Document