Spatial Distribution Of Soil Moisture Research Articles

Spatial Distribution of Soil Moisture and Fine Roots of Apple Trees under Water Storage Pit Irrigation

AbstractThis study was conducted to determine the spatial distribution of soil moisture and fine roots (white, diameter <2 mm) growth under water storage pit (WSP) irrigation of apple trees in an experimental apple orchard. Three irrigation treatments have been used since 2009—WSP60 (water storage pit irrigation, pit depth 60 cm), WSP40 (water storage pit irrigation, pit depth 40 cm), and CK (border irrigation)—in controlled trials. In the considered soil profile of a 0–2 m depth, the soil moisture was mostly distributed in the middle-deep soil layer (40–150 cm) of the rhizosphere of apple trees, yet this was lower at a depth of 0–40 cm under WSP (WSP60 or WSP40) irrigation. For CK, the soil moisture was mainly concentrated within a depth of 0–60 cm of the rhizosphere of apple trees. Compared with CK, the fine root length density (FRLD) in the surface soil (0–40 cm) was reduced by 7.52–7.56% under WSP (WSP60 and WSP40) irrigation, whereas in the middle-deep soil layer (40–110 cm), it increased by 10.32–1...

Potential soil moisture products from the aquarius radiometer and scatterometer using an observing system simulation experiment

Abstract. Using an observing system simulation experiment (OSSE), we investigate the potential soil moisture retrieval capability of the National Aeronautics and Space Administration (NASA) Aquarius radiometer (L-band 1.413 GHz) and scatterometer (L-band, 1.260 GHz). We estimate potential errors in soil moisture retrievals and identify the sources that could cause those errors. The OSSE system includes (i) a land surface model in the NASA Land Information System, (ii) a radiative transfer and backscatter model, (iii) a realistic orbital sampling model, and (iv) an inverse soil moisture retrieval model. We execute the OSSE over a 1000 × 2200 km2 region in the central United States, including the Red and Arkansas river basins. Spatial distributions of soil moisture retrieved from the radiometer and scatterometer are close to the synthetic truth. High root mean square errors (RMSEs) of radiometer retrievals are found over the heavily vegetated regions, while large RMSEs of scatterometer retrievals are scattered over the entire domain. The temporal variations of soil moisture are realistically captured over a sparely vegetated region with correlations 0.98 and 0.63, and RMSEs 1.28% and 8.23% vol/vol for radiometer and scatterometer, respectively. Over the densely vegetated region, soil moisture exhibits larger temporal variation than the truth, leading to correlation 0.70 and 0.67, respectively, and RMSEs 9.49% and 6.09% vol/vol respectively. The domain-averaged correlations and RMSEs suggest that radiometer is more accurate than scatterometer in retrieving soil moisture. The analysis also demonstrates that the accuracy of the retrieved soil moisture is affected by vegetation coverage and spatial aggregation.

Using HydroGeoSphere in a Forested Catchment: How does Spatial Resolution Influence the Simulation of Spatio-temporal Soil Moisture Variability?

Soil moisture is a key variable in the soil-plant-atmosphere system because it interacts with various system components. Both the measurement and the simulation of the soil moisture pattern and its spatio-temporal variability are current challenges in hydrology. This study applies the model HydroGeoSphere in a natural forest ecosystem to assess whether the model can simulate the spatio-temporal variability and pattern of soil moisture. The assessment is performed by comparing the simulation results with soil moisture measurements. The model is used at two different model resolutions to reveal the scale dependency of the calibrated model parameters, the water balance, the discharge components, and the spatial distribution of soil moisture and its variogram parameters. Discharge simulation results show that the model is capable of reproducing the discharge characteristics. A weak correlation is found between simulated and measured soil moisture dynamics in the topsoil, but the correlation is stronger in 20cm depth. In 50cm depth, the model is able to simulate the seasonal trend but not the short-term dynamics because preferential flow is not simulated. Furthermore, a decrease in soil moisture variance during continued drying is observed for both simulations and the measurements at both resolutions. In addition, the pattern of measured soil moisture shows a patchy character that does not show in the simulated pattern indicating that using uniform soil properties in the topsoil makes the soil moisture simulation inaccurate.

Spatial distribution of soil moisture, salinity and organic matter in Manas River watershed, Xinjiang, China

With the classical statistical and geostatistical methods, the study of the spatial distribution and its in- fluence factors of soil water, salinity and organic matter was carried out for 0-70 cm soil layers in Manas River watershed. The results showed that the soil moisture data from all soil layers exhibited a normal distribution, with average values of 14.08%-21.55%. Geostatistical analysis revealed that the content of soil moisture had a moder- ate spatial autocorrelation with the ratios of nugget/sill ranging from 0.500 to 0.718, which implies that the spatial pattern of soil moisture is influenced by the combined effects of structural factors and random factors. Remarkable spatial distributions with stripped and mottled features were found for soil moisture in all different soil layers. The landform and crop planting had a relatively big influence on the spatial distribution of soil moisture; total soil salinity was high in east but low in west, and non-salinized soil and lightly salinized soil appeared at the northwest and southwest of the study area. Under the effect of reservoir leakage, the heavily salinized soils are widely distributed in the middle of the study area. The areas of the non-salinized and lightly salinized soils decreased gradually with soil depth increment, which is contrary to the case for saline soils that reached a maximum of 245.67 km 2 at the layer of 50-70 cm. The types of soil salinization in Manas River watershed were classified into four classes: the sulfate, chloride-sulfate, sulfate-chloride and chloride. The sulfate salinized soil is most widely distributed in the surface layer. The areas of chloride-sulfate, sulfate-chloride, and chloride salinized soils increased gradually along with the increment of soil depth; the variation range of the average values of soil organic matter content was be- tween 7.48%-11.33%. The ratios of nugget/sill reduced gradually from 0.698 to 0.299 with soil depth increment, which shows that the content of soil organic matter has a moderate spatial autocorrelation. The soil organic matter in all soil layers met normal distribution after logarithmic transformation. The spatial distribution patterns of soil or- ganic matter and soil moisture were similar; the areas with high organic matter contents were mainly distributed in the south of the study area, with the lowest contents in the middle.

Contrasting physiological effects of partial root zone drying in field-grown grapevine (Vitis vinifera L. cv. Monastrell) according to total soil water availability.

Different spatial distributions of soil moisture were imposed on field-grown grapevines by applying the same irrigation volumes to the entire (DI; deficit irrigation) or part of the (PRD; partial root zone drying) root zone. Five treatments were applied: controls irrigated at 60% ETc (crop evapotranspiration) for the whole season (308 mm year−1); DI-1 and PRD-1 that received the same irrigation as controls before fruit set, 30% ETc from fruit set to harvest and 45% ETc post-harvest (192 mm year−1); and DI-2 and PRD-2 that were the same, except that 15% ETc was applied from fruit set to harvest (142 mm year−1). Compared with DI-1, PRD-1 maintained higher leaf area post-veraison and increased root water uptake, whole-plant hydraulic conductance, leaf transpiration, stomatal conductance, and photosynthesis, but decreased intrinsic gas exchange efficiency without causing differences in leaf xylem abscisic acid (ABA) concentration. Compared with DI-2, PRD-2 increased leaf xylem ABA concentration and decreased root water uptake, whole-plant hydraulic conductance, leaf transpiration, stomatal conductance, and photosynthesis, mainly at the beginning of PRD cycles. Distinctive PRD effects (e.g. greater stomatal closure) depended on the volumetric soil water content of the wet root zone, as predicted from a model of root-to-shoot ABA signalling.

Vegetation effects on soil moisture estimation from ERS-2 SAR images

The aim of this study was to map soil moisture from ERS-2 SAR images by minimizing the effect of vegetation on the backscatter coefficient. Detailed analysis was carried out to identify the prominent crop descriptor (i.e. crop height, h; leaf area index, LAI; and plant water content, PWC), and to minimize its effect on soil moisture estimation. A semi-empirical water cloud model was used to eliminate the vegetation effects on the backscatter coefficient. Our results showed that the water cloud model based on LAI as the canopy descriptor was able to estimate the crop-covered backscatter coefficient more accurately than the models based on either of the other two crop descriptors. Once the crop-covered backscatter coefficient was determined, a nonlinear least square method (LSM) was implemented to estimate the volumetric soil moisture. A significantly high correlation (R2 ≈ 0.94) between the estimated soil moisture and the corresponding observed soil moisture for barren land, as well as crop-covered surfaces, was obtained. Subsequently, individual soil moisture maps were generated from the three ERS-2 SAR images to depict the spatial distribution of soil moisture during the three seasons. Editor Z.W. Kundzewicz; Associate editor J. Simunek Citation Said, S., Kothyari, U.C. and Arora, M.K., 2012. Vegetation effects on soil moisture estimation from ERS-2 SAR images. Hydrological Sciences Journal, 57 (3), 517–534.

A novel multiple flow direction algorithm for computing the topographic wetness index

The topographic wetness index (TWI), frequently used in approximately characterizing the spatial distribution of soil moisture and surface saturation within a watershed, has been widely applied in topography-related geographical processes and hydrological models. However, it is still questionable whether the current algorithms of TWI can adequately model the spatial distribution of topographic characteristics. Based upon the widely-used multiple flow direction approach (MFD), a novel MFD algorithm (NMFD) is proposed for improving the TWI derivation using a Digital Elevation Model (DEM) in this study. Compared with MFD, NMFD improves the mathematical equations of the contributing area and more precisely calculates the effective contour length. Additionally, a varying exponent strategy is adopted to dynamically determine the downslope flow-partition exponent. Finally, a flow-direction tracking method is employed to address grid cells in flat terrain. The NMFD algorithm is first applied to a catchment located upstream of the Hanjiang River in China to demonstrate its accuracy and improvements. Then NMFD is quantitatively evaluated by using four types of artificial mathematical surfaces. The results indicate that the error generated by NMFD is generally lower than that computed by MFD, and NMFD is able to more accurately represent the hydrological similarity of watersheds.

Inferring soil moisture variability in the Mediterrean Sea area using infrared and passive microwave observations

The objective of this study was to infer soil moisture variability from a combination of passive microwave and infrared satellite observations. The proposed approach is mainly based on the concept of apparent thermal inertia (ATI) and makes use of the daily gradient in brightness temperature from MODIS AQUA to infer soil moisture at moderate spatial resolution. Soil moisture retrievals from optical polar orbiting satellites are affected by discontinuities due to the presence of clouds and spurious fluctuations because of low temporal sampling, which is not sufficient for a reliable daily cycle sampling. To mitigate these limitations, we propose using soil moisture temporal trend derived from passive microwave based product, namely the NASA AMSR-E soil moisture product, to filter estimates from MODIS observations. Passive microwave-based soil moisture products exhibit less fluctuation because of their coarse resolution and lower sensitivity to atmosphere. They can therefore be considered as natural “low pass filters” thus reducing the effect of noise in the infrared based estimates. A sensitivity test was conducted to identify to determine the contribution of various factors to the inferred soil moisture from ATI and the error that they may introduce in the estimates. The ATI-based approach was then applied to qualitatively describe the spatial distribution of soil moisture. The algorithm was validated over two different test areas in Italy and France where reference measurements are available. For the test site in Italy, the obtained ATI values were clustered around four different values corresponding to different levels of wetness. The determined four classes of soil moisture (low, medium, medium-high, and high) were compared to available in situ observations. An agreement with in situ observations of 81% was obtained. In densely vegetated areas, only three classes of soil moisture were instead distinguishable. The obtained agreement between observed and inferred soil moisture values was 88%. Also, in the second study area in France, where vegetation is more dominant, only three classes of soil moisture were determined with a lower agreement of 73%. In addition, the ATI trends are in agreement with thermal inertia values determined from physics-based formulation. This study showed that a combination of infrared and passive microwave observation may lead to a better mapping of soil moisture at the regional scale.

Time series modeling of the spatial distribution of soil moisture in a mountainous hillslope headwater

The spatial distribution of soil moisture depth profiles on a hillslope at the headwater of a mountainous forest watershed in Korea was obtained from time series measurements performed using a refined soil moisture monitoring system. Digital terrain analysis based on intensive field surveying was applied to configure the spatial distribution of soil moisture along the steep regolith. The upslope contributing area and topographic wetness index were employed to determine the optimal locations of sensors for time domain reflectometry (TDR) monitoring along two transects. In the early autumn of 2007, 37 time series were recorded over three weeks and used as data for modeling, accounting for the known reliability of the data and the preliminary evaluation of measured soil moisture histories in the context of time series modeling assumptions. A systematic modeling procedure involving pretreatment, investigation of stochastic structure, modeling practice with heuristic repetition, and diagnostic checking was applied to selected soil moisture time series. The two transects showed differences in the distribution of the explanatory models. Transect A, covering a region of relatively fine soil texture, showed a systematic model distribution in the context of soil depth, whereas transect B across coarser soil occasionally produced inconsistent depth profile modeling results. The predictability of the models tends to reduce substantially at the outlet of the hillslope region, possibly due to active subsurface runoff generation near the channel.

Spatial variability of remotely sensed soil moisture in a temperate‐humid grassland catchment

ABSTRACTKnowledge of the spatial distribution of soil moisture is very important for understanding eco‐hydrological processes, but monitoring of soil moisture over extensive areas remains a challenge because of its high spatial variability and temporal dynamics. This study, taking an Irish temperate‐humid catchment as an example, shows that the backscatter coefficient acquired from Environmental Satellite (ENVISAT) Advanced Synthetic Aperture Radar (ASAR) Wide Swath (WS) image (150 m resolution) is a good estimator of the surface (top 5 cm) soil moisture, leading us to propose an empirical model for soil moisture estimation. Statistical analysis of the remotely sensed soil moisture (produced from 35 ENVISAT/ASAR WS images spanning both wet and dry regimes in 2006) revealed that the spatial variation (standard deviation and coefficient of variance) mainly decreased with increasing mean soil moisture for this wet catchment. Geostatistical analysis showed that the spatial dependence of the soil moisture field was moderate with most of the nugget ratios ranging from 45% (25% percentile) to 55% (75% percentile), and the spatial correlation range was around 554–854 m. The exponential model was able to accurately fit the sample semivariograms and was a reliable estimator of the characteristics of the remotely sensed soil moisture field. This type of analysis can provide meaningful information for soil moisture monitoring at the catchment or regional scale. Copyright © 2011 John Wiley &amp; Sons, Ltd.

Pedotransfer functions in soil electrical resistivity estimation

Surface electrical resistivity tomography (ERT) is recognized as a powerful non-invasive soil survey and monitoring method. Relationships between electrical resistivity (ER) and soil water contents that are needed to infer the spatial distribution of soil moisture from the ERT results, are known to reflect soil properties. However, pedotransfer relationships that relate ER, water content, and basic soil properties other than clay content have not been developed. The objective of this work was to evaluate the improvement in the estimates of ER from soil water contents if soil basic properties are included in the pedotransfer equations. Soil — coarse-loamy, siliceous, mesic Typic (or Aquic) Hapludult — was sampled in 12 locations at ten depths across a 30 × 30-m experimental site. The resistivity was measured in disturbed samples in four-electrode cells. Water content, bulk density, texture, organic carbon, and pH were measured in these samples. The coefficient and the exponent in the power law-dependence of ER on volumetric water content were approximated with linear regressions that included any number of measured soil basic properties as inputs. A total of 1024 regressions were compared using the Akaike information criterion, and the best model was found that provided the best approximation with minimum number of regression terms. Six soil textural classes were encountered in the samples. When no pedotransfer relationships were included, the R 2 of the log-log relationships between ER and water content increased from 0.45 at 10 cm to 0.91 at 190 cm. Splitting the dataset into topsoil and subsoil subsets resulted in favorable pedotransfer relationships with R 2 about 0.85 both in topsoil and subsoil. Bulk density, clay content, sand content and pH appeared to be influential soil properties. Overall, accuracy of relationships between soil electrical resistivity and volumetric water content at ten depths in highly heterogeneous sandy soil could be substantially improved if pedotransfer relationships were established. Future work is needed on the applicability of data obtained on repacked samples to undisturbed soils and on the selection of input variables and evaluation methods for pedotransfer electrical resistivity pedotransfer functions.

Water demand and water use efficiency of winter barley in Hungary

The temporal and spatial variability of soil moisture, evapotranspiration and water use were investigated for winter barley. Evaluations were carried out on a database containing meteorological and yield data from 15 stations. The spatial distribution of soil moisture, evapotranspiration and water use efficiency (WUE) was evaluated from 1951 to 2000 and the moisture conditions during the growth period of winter barley were investigated. The water supply was found to be favourable, since the average values of soil moisture remained above the lower limit of favourable water content throughout the growth period, except for September–December and May–June. The actual evapotranspiration tended to be close to the potential evapotranspiration, so the water supplies were favourable throughout the vegetation period. The calculated values of WUE showed an increasing trend from 1960 to 1990, but the lower level of agricultural inputs caused a decline after 1990. The average values of WUE varied between 0.87 and 1.09 g/kg in different counties, with higher values in the northern part of the Great Hungarian Plain. The potential yield of winter barley can be calculated from the maximum value of WUE. Except in the cooler northern and western parts of the country, the potential yield of winter barley, based on the water supply, could exceed 10 t/ha.

Water-related ecological impacts of rill erosion processes in Mediterranean-dry reclaimed slopes

Soil moisture is considered the main limiting factor governing the structure and dynamics of vegetation in drylands. Soil erosion is perceived as a critical process affecting these systems, especially when rill formation occurs, as rill networks can condition the availability and spatial distribution of soil moisture. To assess the impact of soil erosion processes on the dynamics of Mediterranean-dry reclaimed systems, during the 2005–06 hydrological year we monitored the soil moisture regime (temporal availability and spatial distribution) and the associated responses describing vegetation performance (plant water status and potential seed germination) and vegetation structure in five coal-mining reclaimed slopes subjected to different rill erosion rates (from 0 to about 70 t ha − 1 year − 1 ). Rill network development leads to increased runoff connectivity and to concentration of water flow along the channeling network. As a result, water loss from the slope system is maximized. Simultaneously, the spatial distribution of soil moisture is ruled by the pattern of geomorphic forms (rill and interrill units). The ecological consequences are led by the intensification of water stress and the occurrence of unfavorable conditions for plant recruitment and natural colonization, causing a non-linear decline of species richness and aboveground biomass at the slope scale level. When dense rill networks are developed, long-term effects of erosion result in a sharp ecosystem transition to a very simple and low productive plant community spatially organized in downward spots adjacent to the rills, where plants minimize simultaneously water stress and the mechanical disturbance associated to concentrated flows. ► Rill erosion conditions the availability and spatial distribution of soil moisture ► Rill networks increase runoff connectivity, maximizing the loss of water from slopes ► Soil moisture is deprived from interril areas and concentrated in the rill beds ► Rill erosion reduces non-linearly the availability of water for vegetation ► The ecological consequences of rill erosion are led by the increase of water stress

An assessment of digital elevation models and their ability to capture geomorphic and hydrologic properties at the catchment scale*

Digital elevation model (DEM) data quality is paramount for accurate representation of the land surface and drainage network. This issue was investigated within a small agricultural catchment in the Upper Hunter Valley region of New South Wales, Australia for a DEM created by use of a Differential Global Positioning System (DGPS) and a 25 m DEM from the New South Wales Government's land mapping authority, Land and Property Information (LPI). A hierarchical scaling approach was used to investigate the effect of increasing DEM grid size on a number of geomorphic and hydrologic descriptors (i.e. area–slope relationship, cumulative area distribution, hypsometric curve, width function, Strahler stream order and stream network statistics), as well as addressing the issue of source data accuracy. Results of qualitative and quantitative assessments indicate that as DEM grid size increased, average slope gradients decreased and the drainage network became increasingly simplified. Geomorphic descriptors such as the width function, cumulative area distribution and hypsometric curve appear largely insensitive to DEM scale. The area–slope relationship loses definition in the diffusive region of the curve at large grid scales; however, the fluvial region appears largely insensitive to changes in DEM resolution. A comparison of long-term field soil moisture data with wetness indices derived from DEMs clearly demonstrates that high resolution DEM data are needed to model soil moisture distribution. A 5 m DEM was found to have the minimum resolution required for the current study site in order to accurately capture catchment geomorphology and hydrology and to model the spatial distribution of soil moisture.

The Synergistic Relationship between Soil Moisture and the Low-Level Jet and Its Role on the Prestorm Environment in the Southern Great Plains

Abstract Changes in low-level moisture alter the convective parameters [e.g., convective available potential energy (CAPE), lifted index (LI), and convective inhibition (CIN)] as a result of alterations in the latent and sensible heat energy exchange. Two sources for low-level moisture exist in the southern Great Plains: 1) moisture advection by the low-level jet (LLJ) from the Gulf of Mexico and 2) evaporation and transpiration from the soils and vegetation in the region. The primary focus of this study is to examine the spatial distribution of soil moisture on a daily basis and to determine the effect it has on the convective parameters. The secondary objective is to investigate how the relationship between soil moisture and convective parameters is altered by the presence of an LLJ. The soil moisture data were obtained through newly developed procedures and advances in technology aboard the Tropical Rainfall Measuring Mission Microwave Imager. The convective parameter data were obtained through the North American Regional Reanalysis dataset. The study examined seven warm seasons (April–September) from 1998 to 2004 and found that the convective environment is more unstable (CAPE &amp;gt; 900 J kg−1, LI &amp;lt; −2°C) but more strongly capped (CIN &amp;gt; 70 J kg−1) on days with an LLJ present. Spearman’s rank correlation analysis showed a less stable atmosphere with increased soil moisture, after soil moisture reached 5%, on most days. Additional analysis determined that on all synoptic-type days the probability of reaching various thresholds of convective intensity increased as soil moisture values increased. The probabilities were even greater on days with an LLJ present than on the days without an LLJ present. An examination of four days representing each synoptic-type day indicates that on the daily scale the intensity of the convective environment is closely related to the high soil moisture and the presence of an LLJ.

Development of a one-parameter variable source area runoff model for ungauged basins

This research develops a one-parameter model of saturated source area dynamics and the spatial distribution of soil moisture. The single required parameter is the maximum soil moisture deficit within the catchment. The concept behind the development of the model comes from the fact that the complexity of topographically-driven runoff generation can be reduced through the use of geomorphological scaling relations. The scaling formulation allows the prediction of the dynamics of saturated source areas as a function of basin-wide soil moisture state. This model offers a number of potential advantages. Firstly, the model parameter is independent of topographic index distribution and its associated scale effects. Secondly, it may be possible to measure this single parameter using field measurements or perhaps remote sensing, which gives the model significant potential for application in ungauged basins. Finally, the fact that this parameter is a physical characteristic of the basin, estimation of this parameter avoids regionalization and parameter transferability problems. The model is tested using rainfall–runoff data from the 10.4 ha experimental catchment known as Tarrawara in Australia, the 37 km 2 Town Creek catchment in U.S.A., and the 620 km 2 Balaphi and the 850 km 2 Likhu sub-catchments of the Koshi river in Nepal. In sub-catchments of Koshi river, the simulation results compare favorably against the calibrated TOPMODEL both in terms of direct runoff and the spatial distribution of soil moisture state. In the Tarrawara and Town Brook catchments, simulation results compare favorably against observed storm runoff using all observed data, without calibration.

An approach to computing topographic wetness index based on maximum downslope gradient

As an important topographic attribute widely-used in precision agriculture, topographic wetness index (TWI) is designed to quantify the effect of local topography on hydrological processes and for modeling the spatial distribution of soil moisture and surface saturation. This index is formulated as TWI = ln(a/tanβ), where a is the upslope contributing area per unit contour length (or Specific Catchment Area, SCA) and tanβ is the local slope gradient for estimating a hydraulic gradient. The computation of both a and tanβ need to reflect impacts of local terrain on local drainage. Many of the existing flow direction algorithms for computing a use global parameters, which lead to unrealistic partitioning of flow. β is often approximated by slope gradient around the pixel. In fact, the downslope gradient of the pixel is a better approximation of β. This paper examines how TWI is impacted by a multiple flow routing algorithm adaptive to local terrain and the employment of maximum downslope gradient as β. The adaptive multiple flow routing algorithm partitions flow by altering the flow partition parameter based on local maximum downslope gradient. The proposed approach for computing TWI is quantitatively evaluated using four types of artificial terrains constructed as DEMs with a series of resolutions (1, 5, 10, 20, and 30 m), respectively. The result shows that the error of TWI computed using the proposed approach is generally lower than that of TWI by the widely used approach. The new approach was applied to a low-relief agricultural catchment (about 60 km2) in the Nenjiang watershed, Northeastern China. The results of this application show that the distribution of TWI by the proposed approach reflects local terrain conditions better.

“Group Inversion Approach” for Detection of Soil Moisture Temporal-Invariant Locations

This paper presents an approach denominated Group Inversion Approach (GIA) which aims at detecting soil moisture temporal invariants, i.e., the stable temporal soil moisture locations, by using mainly remotely sensed data. The soil moisture temporal invariants are those locations where independently of the absolute value changes, the relative spatial distribution of soil moisture remains almost constant. In this procedure, the soil moisture values estimated from different inversion approaches and sensor configurations are compared among themselves and with the ground data. The procedure has been tested in a watershed of around 7,000 km2 with data collected during the SMEX’02 experiment in Iowa (USA). The results indicate that fields with inversion errors lower than five times the soil moisture variability detected with ground measurements represent well the mean watershed soil moisture values. The GIA technique has been also found in good agreement with the classical technique used to detect the stable soil moisture features, based exclusively on ground measurements.

Characteristics of soil water retention curve at macro-scale

Scale adaptable hydrological models have attracted more and more attentions in the hydrological modeling research community, and the constitutive relationship at the macro-scale is one of the most important issues, upon which there are not enough research activities yet. Taking the constitutive relationships of soil water movement—soil water retention curve (SWRC) as an example, this study extends the definition of SWRC at the micro-scale to that at the macro-scale, and aided by Monte Carlo method we demonstrate that soil property and the spatial distribution of soil moisture will affect the features of SWRC greatly. Furthermore, we assume that the spatial distribution of soil moisture is the result of self-organization of climate, soil, ground water and soil water movement under the specific boundary conditions, and we also carry out numerical experiments of soil water movement at the vertical direction in order to explore the relationship between SWRC at the macro-scale and the combinations of climate, soil, and groundwater. The results show that SWRCs at the macro-scale and micro-scale presents totally different features, e.g., the essential hysteresis phenomenon which is exaggerated with increasing aridity index and rising groundwater table. Soil property plays an important role in the shape of SWRC which will even lead to a rectangular shape under drier conditions, and power function form of SWRC widely adopted in hydrological model might be revised for most situations at the macro-scale.

Controls on the temporal and spatial variability of soil moisture in a mountainous landscape: the signature of snow and complex terrain

Abstract. The controls on the spatial distribution of soil moisture include static and dynamic variables. The superposition of static and dynamic controls can lead to different soil moisture patterns for a given catchment during wetting, draining, and drying periods. These relationships can be further complicated in snow-dominated mountain regions where soil water input by precipitation is largely dictated by the spatial variability of snow accumulation and melt. In this study, we assess controls on spatial and temporal soil moisture variability in a small (0.02 km2), snow-dominated, semi-arid catchment by evaluating spatial correlations between soil moisture and site characteristics through different hydrologic seasons. We assess the relative importance of snow with respect to other catchment properties on the spatial variability of soil moisture and track the temporal persistence of those controls. Spatial distribution of snow, distance from divide, soil texture, and soil depth exerted significant control on the spatial variability of moisture content throughout most of the hydrologic year. These relationships were strongest during the wettest period and degraded during the dry period. As the catchment cycled through wet and dry periods, the relative spatial variability of soil moisture tended to remain unchanged. We suggest that the static properties in complex terrain (slope, aspect, soils) impose first order controls on the spatial variability of snow and resulting soil moisture patterns, and that the interaction of dynamic (timing of water input) and static influences propagate that relative constant spatial variability through most of the hydrologic year. The results demonstrate that snow exerts significant influence on how water is retained within mid-elevation semi-arid catchments and suggest that reductions in annual snowpacks associated with changing climate regimes may strongly influence spatial and temporal soil moisture patterns and catchment physical and biological processes.