Spatial variation in solutional denudation and soil moisture over a hillslope hollow

A spatial pattern of relative solutional denudation is described for a hillslope hollow and adjacent spurs at Bicknoller Combe, Somerset. The pattern was obtained from a network of micro-weight loss rock tablets emplaced in the soil. The results show that the hollow is the main locus of solutional denudation. The soil moisture distribution over the hollow indicates that it is a transmission zone for acid soil water percolating from the adjacent spurs to the saturated wedge at the base of the hollow. The wetter acid soils in the hollow are responsible for the relatively higher solutional denudation taking place in the hollow.     

On the interrelations between topography,soil depth,soil moisture,transpiration rates and species distribution at the hillslope scale

Relations between the spatial patterns of soil moisture, soil depth, and transpiration and their influence on the hillslope water balance are not well understood. When determining a water balance for a hillslope, small scale variations in soil depth are often ignored. In this study we found that these variations in soil depth can lead to distinct patterns in transpiration rates across a hillslope. We measured soil moisture content at 0.05 and 0.10 m depth intervals between the soil surface and the soil–bedrock boundary on 64 locations across the trenched hillslope in the Panola Mountain Research Watershed, Georgia, USA. We related these soil moisture data to transpiration rates measured in 14 trees across the hillslope using 28 constant heat sapflow sensors. Results showed a lack of spatial structure in soil moisture across the hillslope and with depth when the hillslope was in either the wet or the dry state. However, during the short transition period between the wet and dry state, soil moisture did become spatially organized with depth and across the hillslope. Variations in soil depth and thus total soil water stored in the soil profile at the end of the wet season caused differences in soil moisture content and transpiration rates between upslope and midslope sections at the end of the summer. In the upslope section, which has shallower soils, transpiration became limited by soil moisture while in the midslope section with deeper soils, transpiration was not limited by soil moisture. These spatial differences in soil depth, total water available at the end of the wet season and soil moisture content during the summer appear responsible for the observed spatial differences in basal area and species distribution between the upslope and midslope sections of the hillslope.     

Scaling characteristics of spatial patterns of soil moisture from distributed modelling

Characterizing the spatial dynamics of soil moisture fields is a key issue in hydrology, offering an avenue to improve our understanding of complex land surface–atmosphere interactions. In this paper, the statistical structure of soil moisture patterns is examined using modelled soil moisture obtained from the North American Land Data Assimilation System (NLDAS) at 0.125° resolution. The study focuses on the vertically averaged soil moisture in the top 10 cm and 100 cm layers. The two variables display a weak dependence for lower values of surface soil moisture, with the strength of the relationship increasing with the water content of the top layer. In both cases, the variance of the soil moisture follows a power law decay as a function of the averaging area. The superficial layer shows a lower degree of spatial organization and higher temporal variability, which is reflected in rapid changes in time of the slope of the scaling functions of the soil moisture variance. Conversely, the soil moisture in the top 100 cm has lower variability in time and larger spatial correlation. The scaling of these patterns was found to be controlled by the changes in the soil water content. Results have implications for the downscaling of soil moisture to prevent model bias.     

Multivariate analysis of soil moisture history for a hillslope

In this study, the spatial distribution of measured soil moisture was analyzed on the platform of multivariate modeling. Soil moisture time series for two seasons were selected and used for analysis to reveal similarities and differences in soil moisture responses for a few rainfall events. The development of a soil moisture transport process that considers the representative element volume and uncertainty of soil media provides the hydrological basis for time series modeling. The systematic procedure of Box–Jenkins with noise modeling was used to delineate the final models for all monitoring points. The physical basis of mass balance and the continuity in inflow contribution, as well as statistical criteria, were used in the model selection procedure. Heuristic approaches provide the spatial distribution of selected models along the transect of a hillside. Comparative analysis for two different depths and seasons provide an understanding of the variation in soil moisture transfer processes at the hillslope scale. Differences in soil moisture models for both depths and seasons are associated with eco-hydrological processes. The relationships between distributed topographic features and modeling results were explored to configure dominant hydrological processes for each season.     

Complexity‐reduction modelling for assessing the macro‐scale patterns of historical soil moisture in the Euro‐Mediterranean region

Complexity‐reduction modelling can be useful for increasing the understanding of how the climate affects basin soil moisture response upon historical times not covered by detailed hydrological data. For this purpose, here is presented and assessed an empirical regression‐based model, the European Soil Moisture Empirical Downscaling (ESMED), in which different climatic variables, easily available on the web, are addressed for simplifying the inherent complexity in the long‐time studies. To accommodate this simplification, the Palmer Drought Severity Index, the precipitation, the elevation and the geographical location were used as input data in the ESMED model for predicting annual soil moisture budget. The test area was a large region including central Europe and Mediterranean countries, and the spatial resolution was initially set at 50 km. ESMED model calibration was made according to the soil moisture values retrieved from the Terrestrial Water Budget Data archive by selecting randomly 285 grid points (out of 2606). Once parameterized, ESMED model was performed at validation stage both spatially and temporally. The spatial validation was made for the grid points not selected in the calibration stage while the comparison with the soil moisture outputs of the Global Land Data Assimilation System–NOAH10 simulations upon the period 1950–2010 was carried out for the temporal validation. Moreover, ESMED results were found to be in good agreement with a root‐zone soil moisture product obtained from active and passive microwave sensors from various satellite missions. ESMED model was thus found to be reliable for both the temporal and spatial validations and, hence, it might represent a useful tool to characterize the long‐term dynamics of soil moisture–weather interaction. Copyright © 2013 John Wiley & Sons, Ltd.     

Spatial explicit soil moisture analysis: pattern and its stability at small catchment scale in the loess hilly region of China

Soil moisture is essential for plant growth and terrestrial ecosystems, especially in arid and semi‐arid regions. This study aims to quantify the variation of soil moisture content and its spatial pattern as well as the influencing factors. The experiment is conducted in a small catchment named Yangjuangou in the loess hilly region of China. Soil moisture to a depth of 1 m has been obtained by in situ sampling at 149 sites with different vegetation types before and after the rainy season. Elevation, slope position, slope aspect, slope gradient and vegetation properties are investigated synchronously. With the rainy season coming, soil moisture content increases and then reaches the highest value after the rainy season. Fluctuation range and standard deviation of soil moisture decrease after a 4‐month rainy season. Standard deviation of soil moisture increases with depth before the rainy season; after the rainy season, it decreases within the 0‐ to 40‐cm soil depth but then increases with depths below 40 cm. The stability of the soil moisture pattern at the small catchment scale increases with depth. The geographical position determines the framework of soil moisture pattern. Soil moisture content with different land‐use types is significantly increased after the rainy season, but the variances of land‐use types are significantly different. Landform and land‐use types can explain most of the soil moisture spatial variations. Soil moisture at all sample sites increases after the rainy season, but the spatial patterns of soil moisture are not significantly changed and display temporal stability despite the influence of the rainy season. Copyright © 2013 John Wiley & Sons, Ltd.     

Testing the influence of topography and material properties on catchment‐scale soil moisture patterns using remotely sensed vegetation patterns in a humid temperate catchment,northern Britain

In order to evaluate the relationship between the apparent complexity of hillslope soil moisture and the emergent patterns of catchment hydrological behaviour and water quality, we need fine‐resolution catchment‐wide data on soil moisture characteristics. This study proposes a methodology whereby vegetation patterns obtained from high‐resolution orthorectified aerial photographs are used as an indicator of soil moisture characteristics. This enables us to examine a set of hypotheses regarding what drives the spatial patterns of soil moisture at the catchment scale (material properties or topography). We find that the pattern of Juncus effusus vegetation is controlled largely by topography and mediated by the catchment's material properties. Characterizing topography using the topographic index adds value to the soil moisture predictions relative to slope or upslope contributing area (UCA). However, these predictions depart from the observed soil moisture patterns at very steep slopes or low UCAs. Copyright © 2012 John Wiley & Sons, Ltd.     

Responses of soil moisture at different topographic positions to rainfall events along a steep subtropical forested hillslope

Understanding the dynamic response of soil moisture to rainfall is crucial for describing hydrological processes at the hillslope scale. However, because of sparse monitoring coupled with the complexity of water movement and steep topography, the findings of rainfall-related soil moisture dynamics have not always been consistent, indicating a need for systematic investigations of soil moisture dynamics and infiltration patterns following rainfall inputs at multiple topographic positions along a hillslope. This study aimed to examine the nature of these responses by characterizing and quantifying the response amplitude, rate and time for 37 large rainfall events at 25 combinations of topographic positions and soil depths along a steep forested hillslope. Our results showed that soil moisture responses under different rainfall patterns could be attributed to one or the other rainfall characteristics, such as rainfall intensity and amount. However, soil moisture dynamics at different hillslope positions after rainfall varied widely due to the controls of soil properties, topography, and non-equilibrium flow. Preferential flow was more evident under dry initial soil conditions than under wet initial soil conditions. Findings of this study reveal that the dynamic response patterns of soil moisture to rainfall do not always follow topographic controls, which can improve our understanding of water cycling related to the infiltration process at the hillslope scale, and support water resources management in subtropical mountain ecosystems.     

Spatial and temporal predictions of soil moisture dynamics,runoff, variable source areas and evapotranspiration for plynlimon,mid-wales

For many years hydrologists have tried to build physically realistic models which are still simple enough to be fitted to a range of observations made in the field. This is an ongoing process which will become even more difficult as the quality and variety of field and remotely sensed data improves. Hence models must be able to predict soil moisture patterns in time and in space as well as the outflow hydrograph. The model presented here (TOPMODEL) aims to predict the nature of variable source areas in a way that reflects their dynamics over space and time. All component processes are described and shown in operation. As TOPMODEL and similar models have a growing popularity, this paper can be seen as a demonstration of the model's predictive capabilities. The model is applied to the catchments of Plynlimon, mid-Wales for 1984, 1985 and 1986 data sets. The model has been thoroughly tested and cross-validated against independent data sets for different time periods, for a separate catchment, for internal gauges and for wet and dry periods. The resulting predicted soil moisture patterns show a small, semi-permanent variable source area that has the ability during large storms to expand dynamically over short time periods. Spatial predictions of evapotranspiration are also shown which reflect the influence of soil moisture patterns on this process. The weakest component of the model is the representation of root zone evaporation and how this pre-sets the antecedent condition of the catchment during long dry periods.     

Stability of banded vegetation patterns under seasonal rainfall and limited soil moisture storage capacity

The delicate equilibrium of soil moisture and biomass may become unstable under water scarcity conditions causing banded vegetation patterns to form on hillsides of semi-arid catchments. Soil related processes that induce instability (namely: soil moisture advection and diffusion), have been evaluated numerically for different rainfall regimes. This study addresses the combined influence of some relevant soil characteristics, and the effect of seasonal precipitation on vegetation patterns, advancing the comprehension of those mechanisms that cause shifts toward banded vegetation patterns or bare states.     

Spatial patterns and temporal stability of soil moisture across a range of scales in a semi‐arid environment

The antecedent soil moisture status of a catchment is an important factor in hydrological modelling. Traditional Hortonian infiltration models assume that the initial moisture content is constant across the whole catchment, despite the fact that even in small catchments antecedent soil moisture exhibits tremendous spatial heterogeneity. Spatial patterns of soil water distribution across three transects (two in a burnt area and one in an unburnt area) in a semi‐arid area were studied. At the transect scale, when the factors affecting soil moisture were limited to topographical position or local topography, spatial patterns showed time stability, but when other factors, such as vegetation, were taken into account, the spatial patterns became time unstable. At the point scale, and in the same areas, topographical position was the main factor controlling time stability. Scale dependence of time stability was studied and local topography and vegetation presence were observed to play an important role for the correlation between consecutive measures depending on the scale. Copyright © 2000 John Wiley & Sons, Ltd.     

Regional scale spatial and temporal variability of soil moisture in a prairie region

Understanding the dynamics of spatial and temporal variability of soil moisture at the regional scale and daily interval, respectively, has important implications for remote sensing calibration and validation missions as well as environmental modelling applications. The spatial and temporal variability of soil moisture was investigated in an agriculturally dominated region using an in‐situ soil moisture network located in central Saskatchewan, Canada. The study site evaluated three depths (5, 20, 50 cm) through 139 days producing a high spatial and temporal resolution data set, which were analysed using statistical and geostatistical means. Processes affecting standard deviation at the 5‐cm depth were different from the 20‐cm and 50‐cm depths. Deeper soil measurements were well correlated through the field season. Further analysis demonstrated that lag time to maximum correlation between soil depths increased through the field season. Temporal autocorrelation was approximately twice as long at depth compared to surface soil moisture as measured by the e‐folding frequency. Spatial correlation was highest under wet conditions caused by uniform rainfall events with low coefficient of variation. Overall soil moisture spatial and temporal variability was explained well by rainfall events and antecedent soil moisture conditions throughout the Kenaston soil moisture network. It is expected that the results of this study will support future remote sensing calibration and validation missions, data assimilation, as well as hydrologic model parameterization for use in agricultural regions. Copyright © 2016 John Wiley & Sons, Ltd.     

Stochastic modelling of soil moisture dynamics in a grassland of Qilian Mountain at point scale

Stochastic modeling of soil moisture dynamics is crucial to the quantitative understanding of plant responses to water stresses,hydrological control of nutrient cycling processes,water competition among plants,and some other ecological dynamics,and thus has become a hotspot in ecohydrology at present.In this paper,we based on the continuously monitored data of soil moisture during 2002―2005 and daily precipitation date of 1992―2006,and tried to make a probabilistic analysis of soil moisture dynamics at point scale in a grassland of Qilian Mountain by integrating the stochastic model improved by Laio and the Monte Carlo method.The results show that the inter-annual variations for the soil moisture patterns at different depths are very significant,and that the coefficient of variance(CV) of surface soil moisture(20 cm) is almost continually kept at about 0.23 whether in the rich or poor rainy years.Interestingly,it has been found that the maximal CV of soil moisture has not always appeared at the surface layer.Comparison of the analytically derived soil moisture probability density function(PDF) with the statistical distribution of the observed soil moisture data suggests that the stochastic model can reasonably describe and predict the soil moisture dynamics of the grassland in Qilian Mountain at point scale.By extracting the statistical information of the historical precipitation data in 1994―2006,and inputting them into the stochastic model,we analytically derived the long-term soil moisture PDF without considering the inter-annual climate fluctuations,and then numerically derived the one when considering the inter-annual fluctuation effects in combination with a Monte-Carlo procedure.It was found that,though the peak position of the probability density distribution significantly moved towards drought when considering the disturbance forces,and its width was narrowed,accordingly its peak value was increased,no significant bimodality was observed in the soil moisture dynamics under the given intensity of random fluctuation disturbance.     

Controls of surface soil moisture spatial patterns and their temporal stability in a semi‐arid steppe

Temporal stability of soil moisture spatial patterns has important implications for optimal soil and water management and effective field monitoring. The aim of this study was to investigate the temporal stability of soil moisture spatial patterns over four plots of 105 m × 135 m in grid size with different grazing intensities in a semi‐arid steppe in China. We also examined whether a time‐stable location can be identified from causative factors (i.e. soil, vegetation, and topography). At each plot, surface soil moisture (0–6 cm) was measured about biweekly from 2004 to 2006 using 100 points in each grid. Possible controls of soil moisture, including soil texture, organic carbon, bulk density, vegetation coverage, and topographic indices, were determined at the same grid points. The results showed that the spatial patterns of soil moisture were considerably stable over the 3‐y monitoring period. Soil moisture under wet conditions (averaged volumetric moisture contents > 20%) was more stable than that under dry ( ) or moist ( ) conditions. The best representative point for the whole field identified in each plot was accurate in representing the field mean moisture over time (R² ≥ 0·97; p < 0·0001). The degree of temporal persistence varied with grazing intensity, which was partly related to grazing‐induced differences in soil and vegetation properties. The correlation analysis showed that soil properties, and to a lesser extent vegetation and topographic properties, were important in controlling the temporal stability of soil moisture spatial patterns in this relatively flat grassland. Response surface regression analysis was used to quantitatively identify representative monitoring locations a priori from available soil‐plant parameters. This allows appropriate selection of monitoring locations and enhances efficiency in managing soil and water resources in semi‐arid environments. Copyright © 2010 John Wiley & Sons, Ltd.     

基于Millstone Hill非相干散射雷达观测的电离层电子浓度剖面的经验正交函数分析

本文利用经验正交函数（Empirical Orthogonal Function,简称EOF）方法分析了Millstone Hill非相干散射雷达（Incoherent Scatter Radar,简称ISR）近三个太阳黑子周期（1976年2月～2006年4月）的实测电离层160～700 km的电子浓度剖面资料,并分别用Chapman-α函数拟合了平均电子浓度剖面和带有均值的前三阶EOF级数．结果表明：电子浓度剖面的EOF级数的第一阶项主要控制F2层峰值浓度NmF2,第二阶项同时控制F2层的峰高hmF2和等效标高Hm,第三阶项主要控制等效标高Hm．进一步分析了对应的EOF系数的周日变化、季节变化和太阳活动周期变化,这些变化反映了NmF2,hmF2,Hm的气候学变化规律,例如电离层的冬季异常、半年异常等．EOF方法在级数展开方面收敛速度快,很少数低阶项即能反映电子浓度剖面的主要变化,因此可用于提取出电子浓度剖面的主要分布特征及其周日变化与气候学变化特性,并可用于进一步构建相应的经验模式．     

The effects of scene heterogeneity on soil moisture retrieval from passive microwave data

The τ–ω model of microwave emission from soil and vegetation layers is widely used to estimate soil moisture content from passive microwave observations. Its application to prospective satellite-based observations aggregating several thousand square kilometres requires understanding of the effects of scene heterogeneity. The effects of heterogeneity in soil surface roughness, soil moisture, water area and vegetation density on the retrieval of soil moisture from simulated single- and multi-angle observing systems were tested. Uncertainty in water area proved the most serious problem for both systems, causing errors of a few percent in soil moisture retrieval. Single-angle retrieval was largely unaffected by the other factors studied here. Multiple-angle retrievals errors around one percent arose from heterogeneity in either soil roughness or soil moisture. Errors of a few percent were caused by vegetation heterogeneity. A simple extension of the model vegetation representation was shown to reduce this error substantially for scenes containing a range of vegetation types.     

Analysis of the contributions of topographic,soil, and vegetation features on the spatial distributions of surface soil moisture in a steep natural forested headwater catchment

Surface soil moisture has been extensively studied for various land uses and landforms. Although many studies have reported potential factors that control surface soil moisture over space or time, the findings have not always been consistent, indicating a need for identification of the main factors. This study focused on the static controls of topographic, soil, and vegetation features on surface soil moisture in a steep natural forested headwater catchment consisting of three hillslope units of a gully area, side slope, and valley‐head slope. Using a simple correlation analysis to investigate the effects of the static factors on surface soil moisture at depths of 0–20 cm at 470 points in 13 surveys, we addressed the characteristics of surface soil moisture and its main controlling factors. The results indicated that the mean of surface soil moisture was in the decreasing order of gully area > valley‐head slope > side slope. The relationship between the mean and standard deviation of surface soil moisture showed a convex‐upward shape in the headwater catchment, a negative curvilinear shape in the gully area, and positive curvilinear shapes at the side and valley‐head slopes. At the headwater catchment and valley‐head slope, positive contributions of soil porosity and negative contributions of slope gradient and saturated hydraulic conductivity were the main controlling factors of surface soil moisture under wetter conditions, whereas positive contributions of topographic wetness index and negative contributions of vegetation density were the main controlling factors of surface soil moisture under drier conditions. At the side slope underlain by fractured bedrocks, only saturated hydraulic conductivity and vegetation density were observed to be the controlling factors. Surface soil moisture in the gully area was mainly affected by runoff rather than were static features. Thus, using hillslope units is effective for approximately estimating the hydrological behaviours of surface moisture on a larger scale, whereas dependency between the main static factors and moisture conditions is helpful for estimating the spatial distributions of surface moisture on a smaller scale.     

An analysis of soil moisture dynamics using multi-year data from a network of micrometeorological observation sites

Soil moisture data, obtained from four AmeriFlux sites in the US, were examined using an ecohydrological framework. Sites were selected for the analysis to provide a range of plant functional type, climate, soil particle size distribution, and time series of data spanning a minimum of two growing seasons. Soil moisture trends revealed the importance of measuring water content at several depths throughout the rooting zone; soil moisture at the surface (0–10 cm) was approximately 20–30% less than that at 50–60 cm. A modified soil moisture dynamics model was used to generate soil moisture probability density functions at each site. Model calibration results demonstrated that the commonly used soil matric potential values for finding the vegetation stress point and field content may not be appropriate, particularly for vegetation adapted to a water-controlled environment. Projections of future soil moisture patterns suggest that two of the four sites will become severely stressed by climate change induced alterations to the precipitation regime.     

Spatial and temporal dynamics of soil moisture after rainfall events along a slope in Regosols of southwest China

High frequency seasonal drought in purple soils (Regosols in FAO taxonomy) of the hilly upland areas of Sichuan basin, China, is one of the key restrictive factors for crop production. In order to manage irrigation and fertilizer application in these soils effectively, the soil water content in a sloped plot with 60 cm soil depth was measured by neutron probe devices to investigate the soil moisture regime during the 1998 rainy season after various amounts of rainfall events. The results showed that variation of soil moisture along the slope positions was highest in the top soil layer during the period of sporadic rainfall that did not induce any runoff. The coefficients of variation of soil moisture at various slope positions (upper, middle, and lower) are 17·36%, 8·95%, 10·25%, 8·58%, 8·05% and 9·21% at the 10 cm, 20 cm, 30 cm, 40 cm, 50 cm and 60 cm soil depths respectively. When surface runoff occurred, the soil moisture dynamics at various positions on the plot were then very different. Soil water content decreased more rapidly on the upper slope than on the middle and lower slope positions. When both surface runoff and throughflow occurred, the soil moisture dynamics in the various layers showed a stable period (soil water content is near constant as time elapses) that lasted about 1 week. Also, the pattern of moisture dynamics is ‘decreasing–stabilization–decreasing’. Thus, irrigation and fertilization management according to the spatial and temporal features of soil moisture dynamics on sloped land can increase the water and fertilizer utilization efficacy by reducing their losses during the stable period. Copyright © 2006 John Wiley & Sons, Ltd.     

Evaluation of an empirical orthogonal function–based method to downscale soil moisture patterns based on topographical attributes

Soil moisture influences many hydrologic applications including agriculture, land management and flood prediction. Most remote‐sensing methods that estimate soil moisture produce coarse resolution patterns, so methods are required to downscale such patterns to the resolutions required by these applications (e.g. 10‐ to 30‐m grid cells). At such resolutions, topography is known to affect soil moisture patterns. Although methods have been proposed to downscale soil moisture based on topography, they usually require the availability of past high‐resolution soil moisture patterns from the application region. The objective of this article is to determine whether a single topographic‐based downscaling method can be used at multiple locations without relying on detailed local observations. The evaluated downscaling method is developed on the basis of empirical orthogonal function (EOF) analysis of space–time soil moisture data at a reference catchment. The most important EOFs are then estimated from topographic attributes, and the associated expansion coefficients are estimated on the basis of the spatial‐average soil moisture. To test the portability of this EOF‐based method, it is developed separately using four data sets (Tarrawarra, Tarrawarra 2, Cache la Poudre and Satellite Station), and the relationships that are derived from these data sets to estimate the EOFs and expansion coefficients are compared. In addition, each of these downscaling methods is applied not only for the catchment where it was developed but also to the other three catchments. The results suggest that the EOF downscaling method performs well for the location where it is developed, but its performance degrades when applied to other catchments. Copyright © 2011 John Wiley & Sons, Ltd.