Factors affecting channel infiltration of floodwaters in Nahal Zin basin,Negev desert,Israel

Although floods in arid environments have been documented, considerable uncertainties still exist as to the floodwater and in‐channel infiltration relationships. In desert alluvial channels, the prime cause of flood discharge attenuation is water loss by infiltration into the alluvium. The present study documents flows in Nahal Zin, Israel, their infiltration into the channel bed, and the resultant change in the alluvium moisture content. The study uses a systematic combination of two experimental scales, the cross‐section scale and the reach scale. Direct measurements of moisture distribution in the active channel during floods were made using time domain reflectometry. Twelve flow events were recorded. Flow patterns and their respective alluvium moisture content were analysed. A trench was dug in the alluvium for the study of alluvium properties and time domain reflectometry sensor installation. The alluvium was characterized in terms of size distribution and sediment stratigraphy, structure, and composition. Two main alluvial structures (closed and open) affected the advance of the wetting front and water losses. Alluvial units with an open structure (clast‐supported) reached their maximum moisture content faster than closed structure units (matrix‐supported). Small‐sized particles and matrix‐supported layers reduced infiltration rate. The measured velocities of the wetting front were 0.33 and 2.88 m h^?1 for small and large floods respectively. The wetting front moved downward. Lateral movement was negligible. Copyright © 2016 John Wiley & Sons, Ltd.     

Variability in surface moisture content along a hillslope transect: Rattlesnake Hill, Texas

Surface soil moisture content exhibits a high degree of spatial and temporal variability. The purpose of this study was (a) to characterize variations in moisture content in the 0–5 cm surface soil layer along a hillslope transect by means of intensive sampling in both space and time; and (b) to make inferences regarding the environmental factors that influence this variability. Over a period of seven months, soil moisture content was measured (gravimetric method) on a near-daily basis at 10 m intervals along a 200 m downslope transect at the Rattlesnake Hill field site in Austin, Texas. Results indicate that significant variability in soil moisture content exists along the length of the transect; that variability decreases with decreasing transect-mean moisture content as the hillslope dries down following rain events; and that the dominant influences on moisture content variability are dependent upon the moisture conditions on the hillslope. While topographic and soil attributes operate jointly to redistribute soil water following storm events, under wet conditions, variability in surface moisture content is most strongly influenced by porosity and hydraulic conductivity, and under dry conditions, correlations are strongest to relative elevation, aspect and clay content. Consequently, the dominant influence on soil moisture variability gradually changes from soil heterogeneity to joint control by topographic and soil properties as the transect dries following significant rain events.     

On the potential of MetOp ASCAT‐derived soil wetness indices as a new aperture for hydrological monitoring and prediction: a field evaluation over Luxembourg

In situ soil moisture data from the Bibeschbach experimental catchment in Luxembourg are used to evaluate relative surface soil moisture observed with the MetOp‐A Advanced Scatterometer (ASCAT). Filtered and bias‐corrected surface soil wetness indices (SWIs) derived from coarse‐resolution (25 km) C‐band scatterometer observations are shown to be highly correlated (r = 0.86) with catchment‐averaged soil moisture measured in the field. The combination of ASCAT and ENVISAT Advanced Synthetic Aperture Radar (ASAR) data sets yields high‐resolution (1 km) relative surface soil moisture that is equally well correlated with in situ measurements. It is concluded that for soil moisture monitoring applications at a catchment scale, the two soil moisture products are equivalent. The best correlation between the SWI derived from ASCAT and ASCAT‐ASAR with in situ soil moisture observations at ca. 5 cm depth is obtained with a characteristic time length parameter T equal to 288 h. These results suggest that satellite‐derived surface soil wetness may serve as proxy for soil storage that enables the monitoring of abrupt switches in river system dynamics to appear when an effective field capacity is exceeded and rapid subsurface stormflow is initiated. In catchments where soil moisture is the main controlling factor of rapid subsurface flow, MetOp ASCAT–derived SWI has the potential to monitor how a river system approaches a critical threshold. Copyright © 2011 John Wiley & Sons, Ltd.     

Determining hydrological regimes in an agriculturally used tropical inland valley wetland in Central Uganda using soil moisture,groundwater, and digital elevation data

Inadequate knowledge exists on the distribution of soil moisture and shallow groundwater in intensively cultivated inland valley wetlands in tropical environments, which are required for determining the hydrological regime. This study investigated the spatial and temporal variability of soil moisture along 4 hydrological positions segmented as riparian zone, valley bottom, fringe, and valley slope in an agriculturally used inland valley wetland in Central Uganda. The determined hydrological regimes of the defined hydrological positions are based on soil moisture deficit calculated from the depth to the groundwater table. For that, the accuracy and reliability of satellite‐derived surface models, SRTM‐30m and TanDEM‐X‐12m, for mapping microscale topography and hydrological regimes are evaluated against a 5‐m digital elevation model (DEM) derived from field measurements. Soil moisture and depth to groundwater table were measured using frequency domain reflectometry sensors and piezometers installed along the hydrological positions, respectively. Results showed that spatial and temporal variability in soil moisture increased significantly (p < .05) towards the riparian zone; however, no significant difference was observed between the valley bottom and riparian zone. The distribution of soil hydrological regimes, saturated, near‐saturated, and nonsaturated regimes does not correlate with the hydrological positions. This is due to high spatial and temporal variability in depth to groundwater and soil moisture content across the valley. Precipitation strongly controlled the temporal variability, whereas microscale topography, soil properties, distance from the stream, anthropogenic factors, and land use controlled the spatial variability in the inland valley. TanDEM‐X DEM reasonably mapped the microscale topography and thus soil hydrological regimes relative to the Shuttle Radar Topography Mission DEM. The findings of the study contribute to improved understanding of the distribution of hydrological regimes in an inland valley wetland, which is required for a better agricultural water management planning.     

Modelling soil moisture in a high‐latitude landscape using LiDAR and soil data

Soil moisture has a pronounced effect on earth surface processes. Global soil moisture is strongly driven by climate, whereas at finer scales, the role of non‐climatic drivers becomes more important. We provide insights into the significance of soil and land surface properties in landscape‐scale soil moisture variation by utilizing high‐resolution light detection and ranging (LiDAR) data and extensive field investigations. The data consist of 1200 study plots located in a high‐latitude landscape of mountain tundra in north‐western Finland. We measured the plots three times during growing season 2016 with a hand‐held time‐domain reflectometry sensor. To model soil moisture and its temporal variation, we used four statistical modelling methods: generalized linear models, generalized additive models, boosted regression trees, and random forests. The model fit of the soil moisture models were R² = 0.60 and root mean square error (RMSE) 8.04 VWC% on average, while the temporal variation models showed a lower fit of R² = 0.25 and RMSE 13.11 CV%. The predictive performances for the former were R² = 0.47 and RMSE 9.34 VWC%, and for the latter R² = 0.01 and RMSE 15.29 CV%. Results were similar across the modelling methods, demonstrating a consistent pattern. Soil moisture and its temporal variation showed strong heterogeneity over short distances; therefore, soil moisture modelling benefits from high‐resolution predictors, such as LiDAR based variables. In the soil moisture models, the strongest predictor was SAGA (System for Automated Geoscientific Analyses) wetness index (SWI), based on a 1 m² digital terrain model derived from LiDAR data, which outperformed soil predictors. Thus, our study supports the use of LiDAR based SWI in explaining fine‐scale soil moisture variation. In the temporal variation models, the strongest predictor was the field‐quantified organic layer depth variable. Our results show that spatial soil moisture predictions can be based on soil and land surface properties, yet the temporal models require further investigation. Copyright © 2017 John Wiley & Sons, Ltd.     

Soil moisture variability of root zone profiles within SMEX02 remote sensing footprints

Remote sensing of soil moisture effectively provides soil moisture at a large scale, but does not explain highly heterogeneous soil moisture characteristics within remote sensing footprints. In this study, field scale spatio-temporal variability of root zone soil moisture was analyzed. During the Soil Moisture Experiment 2002 (SMEX02), daily soil moisture profiles (i.e., 0–6, 5–11, 15–21, and 25–31 cm) were measured in two fields in Walnut Creek watershed, Ames, Iowa, USA. Theta probe measurements of the volumetric soil moisture profile data were used to analyze statistical moments and time stability and to validate soil moisture predicted by a simple physical model simulation. For all depths, the coefficient of variation of soil moisture is well explained by the mean soil moisture using an exponential relationship. The simple model simulated very similar variability patterns as those observed.As soil depth increases, soil moisture distributions shift from skewed to normal patterns. At the surface depth, the soil moisture during dry down is log-normally distributed, while the soil moisture is normally distributed after rainfall. At all depths below the surface, the normal distribution captures the soil moisture variability for all conditions. Time stability analyses show that spatial patterns of sampling points are preserved for all depths and that time stability of surface measurements is a good indicator of subsurface time stability. The most time stable sampling sites estimate the field average root zone soil moisture value within ±2.1% volumetric soil moisture.     

A top–down soil moisture and sap flux sampling design of a rain–snow transition mountain watershed

This paper presents a top–down approach for soil moisture and sap flux sampling design with the goal of understanding ecohydrologic response to interannual climate variation in the rain–snow transition watersheds. The design is based on a priori estimates of soil moisture and transpiration patterns using a physical distributed model, Regional Hydro‐Ecologic Simulation System (RHESSys). RHESSys was initially calibrated with existing snow depth and streamflow data. Calibrated model estimates of seasonal trajectories of snowmelt, root‐zone soil moisture storage, and transpiration were used to develop five hydrologic similarity indicators and map these at (30 m) patch scale across the study watershed. The partitioning around medoids‐clustering algorithm was then used to define six distinctive spatially explicit clusters based on the five hydrologic similarity indictors. A representative site within each cluster was identified for sampling. For each site, soil moisture sensors were installed at the 30‐ and 90‐cm depths and at the five soil pits and a sap flux sensor at the averaged‐size white fir tree for each site. The model‐based cluster analysis suggests that the elevation gradient and topographically driven flow drainage patterns are the dominant drivers of spatial patterns of soil moisture and transpiration. The comparison of model‐based calculated hydrological similarity indicators with measured‐data‐based values shows that spatial patterns of field‐sampled soil moisture data typically fell within uncertainty bounds of model‐based estimates for each cluster. There were however several notable exceptions. The model failed to capture the soil moisture and sap flux dynamics in a riparian zone site and in a site where lateral subsurface flow may not follow surface topography. Results highlight the utility of using a hypothesis driven sampling strategy, based on a physically based model, for efficiently providing new information that can drive both future measurements and strategic refinements to model inputs, parameters, or structure that might reduce these errors. Future research will focus on strategies for using of finer scale representations of microclimate, topography, vegetation, and soil properties to improve models.     

Evaluation of multiple surface soil moisture for Korean regional flux monitoring network sites: Advanced Microwave Scanning Radiometer E,land surface model,and ground measurements

In the past few decades, there have been great developments in remotely sensed soil moisture, with validation efforts using land surface models (LSMs) and ground‐based measurements, because soil moisture information is essential to understanding complex land surface–atmosphere interactions. However, the validation of remotely sensed soil moisture has been very limited because of the scarcity of the ground measurements in Korea. This study validated Advanced Microwave Scanning Radiometer E (AMSR‐E) soil moisture data with the Common Land Model (CLM), one of the most widely used LSMs, and ground‐based measurements at two Korean regional flux monitoring network sites. There was reasonable agreement regarding the different soil moisture products for monitoring temporal trends except National Snow and Ice Data Centre (NSIDC) AMSR‐E soil moisture, albeit there were essential comparison limitations by different spatial scales and soil depths. The AMSR‐E soil moisture data published by the National Aeronautics and Space Administration and Vrije Universiteit Amsterdam (VUA) showed potential to replicate temporal variability patterns (root‐mean‐square errors = 0·10–0·14 m³ m^?3 and wet BIAS = 0·09 ? 0·04 m³ m^?3) with the CLM and ground‐based measurements. However, the NSIDC AMSR‐E soil moisture was problematic because of the extremely low temporal variability and the VUA AMSR‐E soil moisture was relatively inaccurate in Gwangneung site characterized by complex geophysical conditions. Additional evaluations should be required to facilitate the use of recent and forthcoming remotely sensed soil moisture data from Soil Moisture and Ocean Salinity and Soil Moisture Active and Passive missions at representative future validation sites. Copyright © 2011 John Wiley & Sons, Ltd.     

Active microwave remote sensing for soil moisture measurement: a field evaluation using ERS‐2

Active microwave remote sensing observations of backscattering, such as C‐band vertically polarized synthetic aperture radar (SAR) observations from the second European remote sensing (ERS‐2) satellite, have the potential to measure moisture content in a near‐surface layer of soil. However, SAR backscattering observations are highly dependent on topography, soil texture, surface roughness and soil moisture, meaning that soil moisture inversion from single frequency and polarization SAR observations is difficult. In this paper, the potential for measuring near‐surface soil moisture with the ERS‐2 satellite is explored by comparing model estimates of backscattering with ERS‐2 SAR observations. This comparison was made for two ERS‐2 overpasses coincident with near‐surface soil moisture measurements in a 6 ha catchment using 15‐cm time domain reflectometry probes on a 20 m grid. In addition, 1‐cm soil moisture data were obtained from a calibrated soil moisture model. Using state‐of‐the‐art theoretical, semi‐empirical and empirical backscattering models, it was found that using measured soil moisture and roughness data there were root mean square (RMS) errors from 3·5 to 8·5 dB and r² values from 0·00 to 0·25, depending on the backscattering model and degree of filtering. Using model soil moisture in place of measured soil moisture reduced RMS errors slightly (0·5 to 2 dB) but did not improve r² values. Likewise, using the first day of ERS‐2 backscattering and soil moisture data to solve for RMS surface roughness reduced RMS errors in backscattering for the second day to between 0·9 and 2·8 dB, but did not improve r² values. Moreover, RMS differences were as large as 3·7 dB and r² values as low as 0·53 between the various backscattering models, even when using the same data as input. These results suggest that more research is required to improve the agreement between backscattering models, and that ERS‐2 SAR data may be useful for estimating fields‐scale average soil moisture but not variations at the hillslope scale. Copyright © 2004 John Wiley & Sons, Ltd.     

How soil moisture mediates the influence of transpiration on streamflow at hourly to interannual scales in a forested catchment

The water balance equation dictates that streamflow may be reduced by transpiration. Yet temporal disequilibrium weakens the relationship between transpiration and streamflow in many cases where inputs and outputs are unbalanced. We address two critical knowledge barriers in ecohydrology with respect to time, scale dependence and lags. Study objectives were to correlate components of the water balance equation at hourly to annual scales, quantify time lags, and simplify critical components of the water budget during wet and dry conditions. We tested interrelationships among precipitation, vapour pressure deficit, transpiration, soil moisture, and streamflow within the confines of a 60‐hectare forested watershed in the western Cascades of Oregon. The Pacific Northwest is an ideal location to compare wet and dry seasons because of its Mediterranean climate. Soil moisture explained more than 80% of the variation in streamflow at all temporal scales investigated. Streamflow was most strongly coupled to soil moisture in the wet season because of gravitational drainage patterns; strong coupling of transpiration to vapour pressure deficit was dominant in the dry season and driven by low humidity. We observed progressively longer hourly time lags between soil moisture and streamflow in the dry season, which relates to an increasing soil moisture deficit that took an average of 48 days to refill after the onset of winter rains. We propose that transpiration drives seasonal patterns in soil moisture that relate to patterns in streamflow only after long time lags. In other words, soil moisture mediates the influence of transpiration on streamflow. Copyright © 2011 John Wiley & Sons, Ltd.     

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.     

Physical controls on septic leachate movement in the vadose zone at the hillslope scale,Putnam County,New York,USA

The fate and transport of contaminants in the vicinity of septic fields remains poorly understood in many hydrogeomorphological environments. We report hydrometric data from an intensive hillslope‐scale experiment conducted between 29 August and 11 November 1998 at a residential leach field in New York State. The objective of our study was to characterize water flux within the vadose zone, understand the physical controls on the flux, and predict how this ultimately will affect subsurface water quality. Soil‐water flux was calculated using matric potential measurements from a network of 25 tensiometer nests, each nest consisting of three tensiometers installed to depths of 10, 50 and 130 cm. Unsaturated hydraulic conductivity curves were derived at each depth from field‐determined time‐domain reflectometry–tensiometry moisture‐release curves and borehole permeametry measurements. Flownets indicated that a strong upward flux of soil water occurred between rainstorms. Following the onset of (typically convective) rainfall, low near‐surface matric potentials were rapidly converted to near‐saturated and saturated conditions, promoting steep vertical gradients through the near‐surface horizons of the hillslope. Lateral hydraulic gradients were typically 10 times smaller than the vertical gradients. Resultant flow vectors showed that the flux was predominantly vertical through the vadose zone, and that the flux response to precipitation was short‐lived. The flux response was controlled primarily by the shape of the unsaturated hydraulic conductivity curves, which indicated a rapid loss of conductivity below saturation. Thus, soil water had a very high residence time in the vadose zone. The absence of rapid wetting at 130 cm and the delayed and small phreatic zone response to rainfall indicated that water movement through macropores did not occur on this hillslope. These results are consistent with a Cl tracing experiment, which demonstrated that the tracer was retained in the vadose zone for several months after injection to the system. Copyright © 2002 John Wiley & Sons, Ltd.     

Spatial prediction of temporal soil moisture dynamics using HYDRUS‐1D

This article investigates the soil moisture dynamics within two catchments (Stanley and Krui) in the Goulburn River in NSW during a 3‐year period (2005–2007) using the HYDRUS‐1D soil water model. Sensitivity analyses indicated that soil type, and leaf area index were the key parameters affecting model performance. The model was satisfactorily calibrated on the Stanley microcatchment sites with a single point rainfall record from this microcatchment for both surface 30 cm and full‐profile soil moisture measurements. Good correlations were obtained between observed and simulated soil water storage when calibrations for one site were applied to the other sites. We extended the predictions of soil moisture to a larger spatial scale using the calibrated soil and vegetation parameters to the sites in the Krui catchment where soil moisture measurement sites were up to 30 km distant from Stanley. Similarly good results show that it is possible to use a calibrated soil moisture model with measurements at a single site to extrapolate the soil moisture to other sites for a catchment with an area of up to 1000 km² given similar soils and vegetation and local rainfall data. Site predictions were effectively improved by our simple data assimilation method using only a few sample data collected from the site. This article demonstrates the potential usefulness of continuous time, point‐scale soil moisture data (typical of that measured by permanently installed TDR probes) and simulations for predicting the soil wetness status over a catchment of significant size (up to 1000 km²). Copyright © 2012 John Wiley & Sons, Ltd.     

卫星遥感数据评估黄土高原陆面干湿程度研究

卫星遥感数据具有估算时空尺度上地表参量的优势,在陆地环境状况评估和监测等方面有很大的应用潜力.本文利用美国地球观测系统卫星搭载中等分辨率成像光谱仪（EOS/MODIS）在黄土高原2002-2010年期间获取的每16天归一化植被指数（NDVI）和每日地表温度（LST）数据,分析了黄土高原地区LST-NDVI空间的基本特征.结果发现：当研究区域足够大且遥感数据时间序列足够长时,LST-NDVI空间中（NDVI,LST）散点并非呈三角形或梯形分布.为了能够利用EOS/MODIS的NDVI和LST数据正确地评估陆面的干湿状况,本文给出了利用数据集合法确定LST-NDVI空间中干边和湿边的数值,即在LST-NDVI空间中,利用NDVI等值区间内LST最大值和最小值的集合代表干边和湿边的数值,并进一步证明了在LST-NDVI空间中干边和湿边数值并非呈线性关系.在分析LST-NDVI空间特征的基础上,通过构建地表温度-植被干旱指数（TVDI）,探讨其在评估黄土高原地区陆面的干湿状况的应用潜力.结果表明：由TVDI距平表征的陆面的干湿程度与局地降水距平有很好的关联性,二者在时空分布上有较好的对应关系.在我国陇东黄土高原塬区,TDVI数值与地面观测的表层土壤湿度有很好的相关性,相关系数在0.67以上,并通过显著性为1%的检验.由此说明：如果合理选取干边和湿边的数值,TDVI可应用于区域陆面干湿程度的客观评估.     

Radar altimetry backscattering signatures at Ka,Ku, C,and S bands over West Africa

This study presents a comprehensive comparison of radar altimetry signatures at Ka-, Ku-, C-, and S-bands using SARAL, ENVISAT and Jason-2 data over the major bioclimatic zones, soil and vegetation types encountered in West-Africa, with an emphasis on the new information at Ka-band provided by the recently launched SARAL–Altika mission. Spatio-temporal variations of the radar altimetry responses were related to changes in surface roughness, land cover and soil wetness. Analysis of time series of backscattering coefficients along the West African bioclimatic gradient shows that radar echoes at nadir incidence are well correlated to soil moisture in semi-arid savannah environments. Radar altimeters are able to detect the presence of water even under a dense canopy cover at all frequencies. But only measurements at Ka-band are able to penetrate underneath the canopy of non-inundated tropical evergreen forests.     

Factors controlling the spatial variability of surface soil moisture within revegetated‐stabilized desert ecosystems of the Tengger Desert,Northern China

The spatial structure of surface soil moisture was investigated at a grid scale with 10 × 10 m intervals on a plot of 4500 m² in a re‐vegetated desert area in Shapotou, the Tengger Desert. The site topography varies from dune crest to dune hollow, and again to dune crest. Volumetric soil moisture contents were measured 21 times over 6 months in 2006 by using Delta‐T Theta‐Probes in the 0–6 cm surface soil layer before and after rainfall. At the same time, soil texture, relative elevation, and plant coverage were measured, to examine (i) the spatial variability of surface soil moisture; (ii) the main factors controlling the spatial variability patterns; and (iii) how the importance of these factors varies with the seasonal variations in soil moisture content. The results indicated that the normal distribution of surface soil moisture was more obvious in wet conditions than in dry conditions; the spatial variability of surface soil moisture was inherent and decreased with increased soil moisture content; and precipitation increased the spatial dependence of surface soil moisture. The relative elevation of the landscape, the shrub coverage of the community, and the soil texture were the main factors influencing surface soil moisture variability, while the effect of soil texture strengthened gradually following the heavy precipitation events. The correlation between the spatial variability of surface soil moisture and the environmental factors, such as, the dry and wet conditions, the landscape coverage and the relative elevation suggests that increasing stability of the soil moisture resulted in a significant increase of soil moisture. Copyright © 2009 John Wiley & Sons, Ltd.     

Soil moisture states,lateral flow,and streamflow generation in a semi‐arid,snowmelt‐driven catchment

Hydraulic connectivity on hillslopes and the existence of preferred soil moisture states in a catchment have important controls on runoff generation. In this study we investigate the relationships between soil moisture patterns, lateral hillslope flow, and streamflow generation in a semi‐arid, snowmelt‐driven catchment. We identify five soil moisture conditions that occur during a year and present a conceptual model based on field studies and computer simulations of how streamflow is generated with respect to the soil moisture conditions. The five soil moisture conditions are (1) a summer dry period, (2) a transitional fall wetting period, (3) a winter wet, low‐flux period, (4) a spring wet, high‐flux period, and (5) a transitional late‐spring drying period. Transitions between the periods are driven by changes in the water balance between rain, snow, snowmelt and evapotranspiration. Low rates of water input to the soil during the winter allow dry soil regions to persist at the soil–bedrock interface, which act as barriers to lateral flow. Once the dry‐soil flow barriers are wetted, whole‐slope hydraulic connectivity is established, lateral flow can occur, and upland soils are in direct connection with the near‐stream soil moisture. This whole‐slope connectivity can alter near‐stream hydraulics and modify the delivery of water, pressure, and solutes to the stream. Copyright © 2005 John Wiley & Sons, Ltd.     

Hydrological responses to climatic variability in a cold agricultural region

Extended severe dry and wet periods are frequently observed in the northern continental climate of the Canadian Prairies. Prairie streamflow is mainly driven by spring snowmelt of the winter snowpack, whilst summer rainfall is an important control on evapotranspiration and thus seasonality affects the hydrological response to drought and wet periods in complex ways. A field‐tested physically based model was used to investigate the influences of climatic variability on hydrological processes in this region. The model was set up to resolve agricultural fields and to include key cold regions processes. It was parameterized from local and regional measurements without calibration and run for the South Tobacco Creek basin in southern Manitoba, Canada. The model was tested against snow depth and streamflow observations at multiple scales and performed well enough to explore the impacts of wet and dry periods on hydrological processes governing the basin scale hydrological response. Four hydro‐climatic patterns with distinctive climatic seasonality and runoff responses were identified from differing combinations of wet/dry winter and summer seasons. Water balance analyses of these patterns identified substantive multiyear subsurface soil moisture storage depletion during drought (2001–2005) and recharge during a subsequent wet period (2009–2011). The fractional percentage of heavy rainfall days was a useful metric to explain the contrasting runoff volumes between dry and wet summers. Finally, a comparison of modeling approaches highlights the importance of antecedent fall soil moisture, ice lens formation during the snowmelt period, and peak snow water equivalent in simulating snowmelt runoff.     

Characteristics of soil moisture in permafrost observed in East Siberian taiga with stable isotopes of water

Soil moisture and its isotopic composition were observed at Spasskaya Pad experimental forest near Yakutsk, Russia, during summer in 1998, 1999, and 2000. The amount of soil water (plus ice) was estimated from volumetric soil water content obtained with time domain reflectometry. Soil moisture and its δ¹⁸O showed large interannual variation depending on the amount of summer rainfall. The soil water δ¹⁸O decreased with soil moisture during a dry summer (1998), indicating that ice meltwater from a deeper soil layer was transported upward. On the other hand, during a wet summer (1999), the δ¹⁸O of soil water increased due to percolation of summer rain with high δ¹⁸O values. Infiltration after spring snowmelt can be traced down to 15 cm by the increase in the amount of soil water and decrease in the δ¹⁸O because of the low δ¹⁸O of deposited snow. About half of the snow water equivalent (about 50 mm) recharged the surface soil. The pulse of the snow meltwater was, however, less important than the amount of summer rainfall for intra‐annual variation of soil moisture. Excess water at the time just before soil freezing, which is controlled by the amount of summer rainfall, was stored as ice during winter. This water storage stabilizes the rate of evapotranspiration. Soil water stored in the upper part of the active layer (surface to about 120 cm) can be a water source for transpiration in the following summer. On the other hand, once water was stored in the lower part of the active layer (deeper than about 120 cm), it would not be used by plants in the following summer, because the lower part of the active layer thaws in late summer after the plant growing season is over. Copyright © 2002 John Wiley & Sons, Ltd.     

Are spatial patterns of soil moisture at plot scales generalisable across catchments,climates, and other characteristics? A synthesis of synoptic soil moisture across the Mid-Atlantic

The spatial variation of soil moisture over very small areas (<100 m²) can have nonlinear impacts on cycling and flux rates resulting in bias if it is not considered, but measuring this variation is difficult over extensive temporal and spatial scales. Most studies examining spatial variation of soil moisture were conducted at hillslope (0.01 km²) to multi-catchment spatial scales (1000 km²). They found the greatest variation at mid wetness levels and the smallest variation at wet and dry wetness levels forming a concave down relationship. There is growing evidence that concave down relationships formed between spatial variation of soil moisture and average soil moisture are consistent across spatial scales spanning several orders of magnitude, but more research is needed at very small, plot scales (<100 m²). The goal of this study was to characterise spatial variation in shallow soil moisture at the plot scale by relating the mean of measurements collected in a plot to the standard deviation (SD). We combined data from a previous study with thousands of new soil moisture measurements from 212 plots in eight catchments distributed across the US Mid-Atlantic Region to (1) test for a generalisable mean–SD relationship at plot scales, (2) characterise how landcover, land use, season, and hillslope position contribute to differences in mean–SD relationships, and (3) use these generalised mean–SD relationships to quantify their impacts on catchment scale nitrification and denitrification potential. Our study found that 98% of all measurements formed a generalised mean–SD relationship like those observed at hillslope and catchment spatial scales. The remaining 2% of data comprised a mean–SD relationship with greater spatial variation that originated from two riparian plots reported in a previous study. Incorporating the generalised mean–SD relationship into estimates of nitrification and denitrification potential revealed strong bias that was even greater when incorporating mean–SD observations from the two riparian plots with significantly greater spatial variation.