Near-surface Soil Water Content Research Articles

Measurement and estimation of evapotranspiration in a maize field: A new method based on an analytical water flux model

Quantifying evapotranspiration (ET) in rainfed cropping systems can be challenging due to complicated interactions among site-specific soil, plant, and management factors. In Northeast China, ET and soil water status in maize fields often display strong spatial and temporal variations due to the changes in tillage practice, planting pattern, and maize plant density. Previous studies have shown that near-surface soil water content (θ) observations at multiple scales provide the potential to estimate surface soil water fluxes. In this study, we introduced a new method to estimate daily field ET by using a soil water flux model mainly based on the time-series of θ at a depth of 2.5 cm. The new method required a calibration of soil water diffusivity with maximum net water flux in the near-surface soil layer, which was related to precipitation redistribution below the canopy. Finally, the new method was evaluated using observed ET values over a 2-year period in a maize field, where independent measurements of soil water evaporation (E) and transpiration (T) were made with heat-pulse sensors and sap-flow gauges, respectively. Field observations showed that E dominated water loss during the seedling stage (16% of total ET). As the canopy was fully developed, E sharply decreased to a value of 0.4 mm d−1, and T accounted for about 89% of ET since the silking stage. The new method to estimate ET performed well in drying periods, while it tended to underestimate ET in wet periods with substantial infiltration into the surface layer. On rain-free days, the ET values estimated with the new method matched well with the measured E+T values, with R2 and RMSE values of 0.85 and 1.93 mm d−1. Therefore, the new approach provides an effective way to quantify maize ET.

Effects of Biomass and Soil Water Content Distribution on Cosmic Ray Neutron Probe Measurement

Cosmic ray neutron probes (CRNPs) provide continuous monitoring of average near-surface soil water content (SWC) on hectometer scales. However, the performance of CRNPs on surfaces of highly heterogeneous vegetation and SWC remains uncertain. This study evaluated three vegetation calibration methods with the correction of vegetation distribution developed for a CRNP on the Loess Plateau of China. Three plots with different vegetation distributions were selected and equipped with CRNPs and SWC sensors, and their biomass as well as distribution were measured by an unmanned aerial vehicle (UAV) equipped with a RedEdge multispectral camera. We found that the parameter N0, which is neutron flux in dry soil, was best represented by the biomass at average growth conditions of the monitoring period, yielding the lowest RMSE (0.068). The Veg–N0 vegetation calibration method reduced the RMSE the most between the CRNP SWC and the Kriging-weighted SWC, and the correction of the spatial distribution of the vegetation further reduced the RMSE. The cooperation between the CRNP and the UAV could obtain the regional averaged SWC accurately. This study makes up for the lack of vegetation calibration for the CRNP on the Loess Plateau, which should help develop sustainable vegetation management and ecohydrological management strategies on the Loess Plateau, so as to protect water security in the region.

Velocity analysis of a lateral wave

In practice, the reflected EM signal cannot be clearly observed in GPR data due to the high water content and other reasons. However, the antenna coupling signal through the ground interface is dominated in all the GPR measurements. This direct coupling signal that travels through the ground interface is called a lateral wave. The properties of the lateral wave directly depend on the subsurface properties, especially electrical parameters. We have numerically analyzed a lateral wave and its velocity. Subsequently, the relationship between lateral wave and dielectric permittivity was determined by polynomial regression. Analytically, it is challenging to analyze a lateral wave due to the parameters that can influence wave propagation. Antenna characteristics, surface roughness, etc need to be considered. Numerically, we designed a GPR system with a subsurface layer and observed a lateral wave. This numerical analysis can give a chance to use a lateral wave for near-surface soil water content. This analysis gives a more precise estimation of surface water content. Moreover, we analyze the antenna height effect that influences radar signals. We numerically observed that the GPR signal is highly affected by antenna height. The antenna height effect depended on the wavelength of the applied electromagnetic wave. By adjusting the antenna height, the unobservable GPR signal can be clearly detected.

Developing a novel geophysical tool to investigate the influence of vegetation on slope stability

Vegetation is important for managing shallow geotechnical assets. However, root water uptake-driven changes in slope hydrology and the near-surface (soil water content, matric suction, and hydraulic conductivity) are highly complex. Improved knowledge of these processes is increasingly important as society faces the threat of a greater prevalence of climate-driven extreme rainfall and drought events. Intrinsic factors affect slope stability, including geometry, soil properties, groundwater, and vegetation-driven matric suction. Field evidence shows that engineered slopes are susceptible to hydrometeorological instability mechanisms and pose a potential failure hazard to asset operation and public safety. This study considers the combination of a novel geophysical monitoring system and geotechnical point sensors for use in controlled laboratory conditions to assess the influence of vegetation on soil-water dynamics in the context of geotechnical infrastructure. The geophysical monitoring system, referred to here as PRIME (Proactive Infrastructure Monitoring and Evaluation system), uses electrical resistivity tomography (ERT) technology to non-invasively image changing subsurface moisture-driven processes. The PRIME system and point sensor arrays are being developed for near real-time data acquisition of transient soil moisture conditions in a suite of soil column experiments. Through addressing the challenges associated with designing integrated geophysical-geotechnical laboratory-scale monitoring experiments, this research aims to provide new tools and approaches to further our understanding of vegetation-driven soil moisture movement to better assess slope instability risk.

Increased annual methane uptake driven by warmer winters in an alpine meadow

Pronounced nongrowing season warming and changes in soil freeze-thaw (F-T) cycles can dramatically alter net methane (CH4 ) exchange rates between soils and the atmosphere. However, the magnitudes and drivers of warming impacts on CH4 uptake in different stages of the F-T cycle are poorly understood in cold alpine ecosystems, which have been found to be a net sink of atmospheric CH4 . Here, we reported a year-round ecosystem daily CH4 uptake in an alpine meadow on the Qinghai-Tibetan Plateau after a 5-year warming experiment that included a control, a low-level warming treatment (+2.4℃ at 5cm soil depth), and a high-level warming treatment (+4.5℃ at 5cm soil depth). We found that warming shortened the F-T cycle under the low-level warming and soils did not freeze under the high-level warming. Although both warming treatments increased the mean CH4 uptake rate, only the high-level warming significantly increased annual CH4 uptake compared to the control. The warming-induced stimulation of CH4 uptake mainly occurred in the cold season, which was mostly during spring thaw under low-level warming and during the frozen winter under high-level warming due to a longer period with thawed soil. We also found that warming significantly stimulated daily CH4 uptake mainly by reducing near-surface soil water content in the warm season, whereas both soil water content and temperature controlled daily CH4 uptake in different ways during the autumn freeze, frozen winter, and spring thaw periods of the control. Our study revealed a strong warming effect on CH4 uptake during the entire F-T cycle in the alpine meadow, especially the unfrozen winter. Our results also suggested the important roles of soil pH, available phosphorus, and methanotroph abundance in regulating annual CH4 uptake in response to warming, which should be incorporated into biogeochemical models for accurately forecasting CH4 fluxes under future climate scenarios.

Ground penetrating radar for soil-water measurement in a semi-arid climate in the Orkhon River basin, central Mongolia

In this paper, we present a velocity analysis technique using ground-penetrating radar (GPR) data to estimate near-surface soil-water content affected by topography and solar radiation on a mountain peak, mountain mid-slope, and alluvial plain sites in a semi-arid climate area in central Asia. By making precise measurements of reflected EM wave velocity, the water content in the near-surface soil was determined. The GPR experiments at several frequencies were carried out in two sequential phases (comprising common-offset and multi-offset methods) to obtain the soil-water content and illustrate the subsurface structure. We then tried to determine the relationship between near-surface moisture content and permafrost thawing. Therefore, we used several different methods including time-domain reflectometry and a resistivity survey. We also confirmed via the GPR data that vegetation cover indicates soil-water content in the near-surface soil. The results evaluated in this study provide meaningful information about soil water as well as subsurface structures. The GPR data acquired at the survey sites indicated a large range of near-surface water content due to the topography of the survey lines.

COSMOS-UK: national soil moisture and hydrometeorology data for environmental science research

Abstract. The COSMOS-UK observation network has been providing field-scale soil moisture and hydrometeorological measurements across the UK since 2013. At the time of publication a total of 51 COSMOS-UK sites have been established, each delivering high-temporal resolution data in near-real time. Each site utilizes a cosmic-ray neutron sensor, which counts epithermal neutrons at the land surface. These measurements are used to derive field-scale near-surface soil water content, which can provide unique insight for science, industry, and agriculture by filling a scale gap between localized point soil moisture and large-scale satellite soil moisture datasets. Additional soil physics and meteorological measurements are made by the COSMOS-UK network including precipitation, air temperature, relative humidity, barometric pressure, soil heat flux, wind speed and direction, and components of incoming and outgoing radiation. These near-real-time observational data can be used to improve the performance of hydrological models, validate remote sensing products, improve hydro-meteorological forecasting, and underpin applications across a range of other scientific fields. The most recent version of the COSMOS-UK dataset is publically available at https://doi.org/10.5285/b5c190e4-e35d-40ea-8fbe-598da03a1185 (Stanley et al., 2021).

Spatial heterogeneity of throughfall and its contributions to the variability in near-surface soil water-content in semiarid mountains of China

Throughfall (TF) is one of the most important factors affecting forest surface soil moisture. However, TF heterogeneity and its contributions to the variability in near-surface soil water-content (SWC) in a spruce forest in semiarid mountain ecosystems are poorly understood, and may determine plant survival. Here, we systematically investigated variability of TF in a Picea crassifolia stand within a protected semi-arid mountain ecosystem, and evaluated the contributions of TF to near-surface SWC variability obtained from TF gauges and SWC measurements at the plot level. Results showed that TF variability tended to decline with an increase in rainfall amount, intensity, and duration, and then tended to be stable after a value of 24.1 mm, 3.1 mm h−1 and 789.8 min, respectively. Both TF and surface SWC were highly spatially variable, but the spatial patterns appeared to be stable over time based on time-stability analysis. The mean SWC increment exhibited a strong positive power relationship with plot mean TF, and the percent of locations with SWC increments increased similarly to TF amount for individual rainfall events. TF, soil bulk density, and litter fall biomass can significantly (P < 0.05) affect the stability of SWC increments. Therefore, our research indicated that further research should consider the relative importance of, and interactions among precipitation characteristics, soil heterogeneity, and vegetation characteristics. Our results may be useful for land managers involved in enhancing the water conservation capacity of semi-arid mountain forest ecosystems, where climatic conditions, soil quality and vegetation characteristics will determine the supply of multiple forest ecosystem functions.

Variations in diurnal and seasonal net ecosystem carbon dioxide exchange in a semiarid sandy grassland ecosystem in China's Horqin Sandy Land

Abstract. Grasslands are major terrestrial ecosystems in arid and semiarid regions, and they play important roles in the regional carbon dioxide (CO2) balance and cycles. Sandy grasslands are sensitive to climate change, yet the magnitudes, patterns, and environmental controls of their CO2 flows are poorly understood for some regions (e.g., China's Horqin Sandy Land). Here, we report the results from continuous year-round CO2 flux measurements for 5 years from a sandy grassland in China's Horqin Sandy Land. The grassland was a net CO2 source at an annual scale with a mean annual net ecosystem CO2 exchange (NEE) of 49 ± 8 gCm-2yr-1 for the years for which a complete dataset was available (2015, 2016, and 2018). Annual precipitation had the strongest effect on annual NEE; grassland carbon sequestration increased with the increasing precipitation since NEE depended on annual precipitation. In the spring, NEE decreased (i.e., C sequestration increased) with increasing magnitude of effective precipitation pulses, total monthly precipitation, and soil temperature (Tsoil). In the summer, NEE was dominated by the total seasonal precipitation and high precipitation pulses (&gt; 20 mm). In the autumn, NEE increased (i.e., C sequestration decreased) with increasing effective precipitation pulses, Tsoil, and near-surface soil water content (SWC) but decreased with increased SWC deeper in the soil. In the winter, NEE decreased with increasing Tsoil and SWC. The sandy grassland was a net annual CO2 source because drought decreased carbon sequestration by the annual plants. Long-term observations will be necessary to reveal the true source or sink intensity and its response to environmental and biological factors.

Improving estimation of evapotranspiration during soil freeze-thaw cycles by incorporating a freezing stress index and a coupled heat and water transfer model into the FAO Penman-Monteith model

Evapotranspiration (ET) plays an important role in water and energy balance at the surface-atmosphere interface. It is widely reported that near-surface soil water content (SWC) or soil water potential (SWP) significantly affects ET and this parameter has been incorporated into the FAO Penman-Monteith (FAO-PM) model for prediction of ET during crop growth seasons. However, there is little information on the effect of SWC or SWP on prediction of ET during soil freeze-thaw cycles in winter. We present an experiment conducted at a demonstration farm with a crop of winter wheat, over two winters near Beijing, China. A lysimeter system equipped with a weather station was used to measure the ET flux and meteorological data. Unfrozen soil water content (USWC) and soil temperature (Tsoil) were measured using dielectric tube sensors (DTS) and digital temperature sensors, respectively. SWP was determined by measured USWC and a soil moisture characteristic (SMC) curve derived from the soil freezing characteristic (SFC) curve and the Clapeyron equation in frozen soil. Detailed measurements in year 1 showed that the FAO-PM model exhibited a complex error pattern, underestimating ET from unfrozen soil but overestimating ET from stable frozen soil. To address these errors, we define a freezing stress index (Ksf) as a function of SWP. Incorporation of Ksf as a modifier of the standard crop coefficient in the FAO-PM model improved prediction of ET (RMSE declined from 0.424 to 0.187 mm day−1, in year 1). These data revealed a correlation between SWP near the soil surface (<10 cm) and measured ET over freezing and thawing cycles. We incorporated a coupled heat and water transfer (CHWT) model into the improved FAO-PM model to predict USWC, SWP and ET throughout the winter of year 2 from current meteorological data as upper boundary conditions, initial measurements of ET, USWC and Tsoil as initial conditions, and Ksf and soil hydraulic properties optimized in year 1. The results showed that ET estimation was significantly improved, with RMSE reduced from 0.323 to 0.281 mm day−1 using the combined (FAOPM-Ksf-CHWT) model. Model error primarily derived from an underestimation of simulated SWP during soil freezing process. The combined model extends the utility of the FAO-PM model to non-cropping seasons including winter in temperate climates and reduces the data requirements for accurate prediction of ET from intermittently frozen soil.

Monitoring near-surface soil water content using an innovative perforated cylinder coaxial dielectric sensor

Near-surface soil water content (NSWC) is an important parameter for characterizing hydrological processes, water and vapor exchange at the soil-atmosphere boundary, and potential biological productivity. Here we develop a dielectric based frequency-domain (FD) impedance sensor operating at 100 MHz, with a novel coaxial probe design and a temperature sensor embedded in the circuit board. This perforated cylinder coaxial (PCC) sensor provides simultaneous measurements of volumetric soil water content (VSWC) and of temperature. The temperature measurement allows signal correction for the temperature response of the circuit board and of the permittivity of soil water. We characterize the performance of the PCC sensor and compare it with alternative 3-pin- and 2-pin-electrode FD impedance sensors each using a similarly performing circuit board. A series of theoretical analyses and experiments were conducted, including (i) sensors calibration, (ii) temperature effects and their correction, (iii) soil volume sensed by each sensor through simulation analysis and a stepwise soil removal (SSR) test and (iv) accuracy comparison of the three sensors when applied for the NSWC measurements. The calibration results verified that the PCC, 3-pin and 2-pin probes were suitable to measure VSWC (RMSE ≤ 0.0142 cm3 cm−3). The simulation analysis using High Frequency Structure Simulator software (HFSS) indicated that the novel PCC probe had a symmetrical distribution of the E-field, wholly contained within the cylinder, avoiding leakage of the E-Field into air at the soil-atmosphere interface and removing the dependency of sensed volume on VSWC. The results of the SSR test showed that the E-field distributed outside the receiving electrode of the PCC probe could be ignored whereas that of both pin-type electrodes was distributed outside of the receiving electrode to a distance that depended on VSWC (i.e. up to 8 mm for 3-pin and up to 11 mm for 2-pin designs when VSWC > 0.17 cm3 cm−3), which corresponds to the simulation analysis. Moreover, the new PCC probe provided more accurate NSWC measurement than 3-pin or 2-pin probes because the E-field was contained within the perforated cylinder, avoiding E-field leakage and fixing sensed soil volume independent of VSWC. The pin-structure probes appear to perform best when installed horizontally in the soil at least 11 mm below the surface.

Importance of soil organic carbon in near-surface soil water content estimation: A simple model comparison in dry-end Canadian Prairie soils

The relationship of soil organic carbon (SOC) to soil water content (SWC) is primarily included in hydrological models through porosity where SOC is known to influence soil structure. The Soil Moisture Active Passive Validation Experiment 2012 (SMAPVEX12) field sampling campaign in southern Manitoba provided both SWC and SOC data over three soil textural classes and a range of soil wetness conditions. Linear regressions were developed to predict time-averaged SWC from SOC in the surface 5 cm of 50 cropland fields during SMAPVEX12 when averaged across three wetness ranges. The prediction of SWC from SOC was tested on fields in the same vicinity as SMAPVEX12 that were sampled for SWC in 2008 when soils were very dry. The measured SWC on the five sampling dates in 2008 was compared to SWC estimated for those dates from (1) the single-parameter regression equation from SOC during SMAPVEX12 dry days (1pSOC); (2) a ‘decay’ formula (5% reduction of a declining balance) (2pDM); and (3) a model based on field mean SOC with daily computation (3pSOCM). Both daily iteration models (2 and 3) required initial field capacity and rainfall data from 1 April. Models were compared with root-mean-square error (RMSE) and delta Akaike information criterion (∆AIC). The two-parameter model (2pDM) had the lowest RMSE and most favorable ∆AIC scores for mean SWC of the five sampling dates over all fields. The single-variable SOC equation was equally viable in RMSE and ∆AIC to the other models on sand soils. On clay soils, 3pSOCM was advantageous on some sampling dates, demonstrating a benefit of including SOC with field capacity and precipitation. The predictive ability of SOC to explain time-averaged SWC variability in dry soils would be valuable for SWC model initialization and as a covariate for geostatistical downscaling from satellite SWC scales.

Advances in Heat-Pulse Methods: Measuring Near-Surface Soil Water Content

Advances in Heat-Pulse Methods: Measuring Near-Surface Soil Water Content

Kalman filters for assimilating near-surface observations into the Richards equation – Part 3: Retrieving states and parameters from laboratory evaporation experiments

Abstract. The purpose of this work is to evaluate the performance of a dual Kalman filter procedure in retrieving states and parameters of a one-dimensional soil water budget model based on the Richards equation, by assimilating near-surface soil water content values during evaporation experiments carried out under laboratory conditions. The experimental data set consists of simultaneously measured evaporation rates, soil water content and matric potential profiles. The parameters identified by assimilating the data measured at 1 and 2 cm soil depths are in very good agreement with those obtained by exploiting the observations carried out in the entire soil profiles. A reasonably good correspondence has been found between the parameter values obtained from the proposed assimilation technique and those identified by applying a non-sequential parameter estimation method. The dual Kalman filter also performs well in retrieving the water state in the porous system. Bias and accuracy of the predicted state profiles are affected by observation depth changes, particularly for the experiments involving low state vertical gradients. The assimilation procedure proved flexible and very stable in both experimental cases, independently from the selected initial conditions and the involved uncertainty.

Ground-penetrating radar for monitoring the distribution of near-surface soil water content in the Gurbantünggüt Desert

In the Gurbantunggut Desert, snowmelt-induced high soil water contents briefly create favorable conditions for the germination and growth of plants every spring. Monitoring the rapidly changing conditions in this time period demands fast and efficient methods for measuring soil water contents at the field scale. For this study, a series of ground-penetrating radar (GPR) measurements were carried out on sites characterized by semi-vegetated dunes both in April 2010 and 2011. We compare water contents calculated from the GPR direct ground wave signal to both point scale validation measurements by time-domain reflectometry (TDR) and gravimetric sampling. Our results show that GPR is an effective method to rapidly obtain a detailed image of the field scale soil water content distribution in the Gurbantunggut Desert with an accuracy similar to TDR. Observed large scale soil water content variations are dominated by dune topography: During snow melting, melt water was found to trickle slowly from the dune ridges to interdune valleys, increasing the soil water content there while the dune ridges quickly started to dry down. In dune valleys, smaller scale near-surface soil water content changes were dominated by variations in the vegetation coverage, leading to snowmelt funnels at distinct locations: The snowmelt initially occurred around the stems and branches of plants, forming funnel-shaped melt water induced holes through the snow cover and leading to an increasing amount of melt water collected around these plant roots. Our comparison of data from 2010 to 2011 furthermore suggests a temporally stable distribution of near-surface soil water content. This has important ecological significance for controlling desertification and for restoring and reconstructing vegetation in the Gurbantunggut Desert.

Chloride leaching in two Ontario soils: Measurement and prediction using HYDRUS-1D

Saso, J. K., Parkin, G. W., Drury, C. F., Lauzon, J. D. and Reynolds, W. D. 2012. Chloride leaching in two Ontario soils: Measurement and prediction using HYDRUS-1D. Can. J. Soil Sci. 92: 285–296. Deterministic numerical modelling can often be used to complement and extend field results, and to provide extra insight into the mechanisms of water and solute movement within the profile of agricultural soils. Chloride leaching and near-surface soil water content in a Guelph loam and a Maryhill loam cropped to corn (Zea mays L.) were measured over a 12-mo period (October 2007 to September 2008) and simulated using the HYDRUS-1D numerical model (version 4.12). Field measurements and prediction indicated that over 70% of the applied chloride (Cl) was lost to deep drainage (below 80 cm depth) during the winter months (November 2007 to April 2008) in both soils. Normalized root mean square error (NRMSE) values for HYDRUS-1D estimates of near-surface (0- to 30-cm depth interval) soil water content over the growing season (April to September, 2008) were 28% for Guelph loam and 42% for Maryhill loam. The NRMSE value for estimated versus measured Cl mass remaining in the soil profile (0–80 cm depth interval) over the winter months was 17% for both soils. It was concluded that the HYDRUS-1D model can provide reasonable predictions of near-surface soil water content and profile leaching losses of tracer solutes. Further work is required, however, to determine if the predictive ability of HYDRUS-1D might be improved by incorporating the effects of freeze-thaw cycles on soil hydraulic properties and solute leaching. Further study is also required to establish the model's ability to simulate the leaching behaviour of reactive solutes, such as nitrate, in agricultural soils.

Simulating water content, crop yield and nitrate-N loss under free and controlled tile drainage with subsurface irrigation using the DSSAT model

Abstract In southwestern Ontario, rain-fed crop production frequently fails to achieve its yield potential because of growing-season droughts and/or uneven rainfall distribution. The objective of this study was to determine if the Decision Support System for Agrotechnology Transfer (DSSAT) v4.5 model could adequately simulate corn and soybean yields, near-surface soil water contents, and cumulative nitrate-N losses associated with regular free tile drainage (TD) and controlled tile drainage with optional subsurface irrigation (CDS). The simulations were compared to observations collected between 2000 and 2004 from both TD and CDS field experiments on a Perth clay loam soil at the Essex Region Conservation Authority demonstration farm, Holiday Beach, Ontario, Canada. There was good model-data agreement for crop yields, near-surface (0–30 cm) soil water content and cumulative annual tile nitrate-N loss in both the calibration and validation years. For both TD and CDS, the CENTURY soil C/N model in DSSAT simulated water content and cumulative tile nitrate-N loss with normalized root mean square error (n-RMSE) values ranging from 9.9 to 14.8% and 17.8 to 25.2%, respectively. The CERES-Maize and CROPGRO-Soybean crop system models in the DSSAT simulated corn and soybean yields with n-RMSE values ranging from 4.3 to 14.0%. It was concluded that the DSSAT v4.5 model can be a useful tool for simulating near-surface soil water content, cumulative tile nitrate-N losses, and corn and soybean yields associated with CDS and TD water management systems.

Characterization of Soil Water Content Variability and Soil Texture using GPR Groundwave Techniques

Accurate characterization of near-surface soil water content is vital for guiding agricultural management decisions and for reducing the potential negative environmental impacts of agriculture. Characterizing the near-surface soil water content can be difficult, as this parameter is often both spatially and temporally variable, and obtaining sufficient measurements to describe the heterogeneity can be prohibitively expensive. Understanding the spatial correlation of near-surface soil water content can help optimize data acquisition and improve understanding of the processes controlling soil water content at the field scale. In this study, ground penetrating radar (GPR) methods were used to characterize the spatial correlation of water content in a three acre field as a function of sampling depth, season, vegetation, and soil texture. GPR data were acquired with [Formula: see text] and [Formula: see text] antennas, and measurements of the GPR groundwave were used to estimate soil water content at four different times. Additional water content estimates were obtained using time domain reflectometry measurements, and soil texture measurements were also acquired. Variograms were calculated for each set of measurements, and comparison of these variograms showed that the horizontal spatial correlation was greater for deeper water content measurements than for shallower measurements. Precipitation and irrigation were both shown to increase the spatial variability of water content, while shallowly-rooted vegetation decreased the variability. Comparison of the variograms of water content and soil texture showed that soil texture generally had greater small-scale spatial correlation than water content, and that the variability of water content in deeper soil layers was more closely correlated to soil texture than were shallower water content measurements. Lastly, cross-variograms of soil texture and water content were calculated, and co-kriging of water content estimates and soil texture measurements showed that geophysically-derived estimates of soil water content could be used to improve spatial estimation of soil texture.

SENSITIVITY ANALYSIS OF SOIL AND PM10 LOSS IN WEPS USING THE LHS-OAT METHOD

The Wind Erosion Prediction System (WEPS) was developed for the specific application of simulating erosionprocesses from agricultural lands. WEPS is a physically based model, with a moderate to large number of input parameters.Knowledge about model sensitivity is essential to both model developers and users in ascertaining those parameters mostinfluential to modeled object functions. A combined method of Latin hypercube sampling (LHS) and one-factor-at-a-time(OAT) parameter examination was used to assess the sensitivity of parameters in the WEPS erosion submodel in simulatingtotal soil loss, creep/saltation, suspension, and PM10 emission. The ranges of the parameters considered in this analysis wereobtained from the WEPS Users Manual and determined for the Columbia Plateau region of the U.S. Overall, the analysisindicated that the model was most sensitive to changes in biomass flat cover, near-surface soil water content, ridge height,wind speed, rock volume, soil wilting-point water content, field length and width, crust cover, aggregate and crust stability,and random roughness. The model was least sensitive to changes in bulk density, silt content, and aggregate and crust density.For the Columbia Plateau, erosion processes were more sensitive to surface soil water content and random roughness inspring than in autumn and more sensitive to residue cover and aggregate mean diameter in autumn than in spring. Thissensitivity analysis suggests that residue management, surface soil moisture conservation, aggregation, and field size caneffectively influence soil loss and PM10 emission.

Infiltration and soil water mixing on forested and harvested slopes during spring snowmelt, Turkey Lakes Watershed, central Ontario

Forest harvesting increases snow accumulation and water delivery to the soil surface relative to undisturbed forest; however, implications of these changes for water infiltration and storage in the soil profile are not well known. These processes were studied using a combined hydrometric and isotopic tracer approach in a harvested area and adjacent hardwood forest stand on a slope at the Turkey Lakes Watershed (TLW) in central Ontario. The slope had a mean gradient of 0.29 and a 0.5–1 m thick ablation till layer overlying compacted basal till. Pre-melt snow accumulation and daily water inputs in the harvested area and forest were measured during the 2000 and 2001 snowmelts. Soil water content in the ablation till was monitored at harvested and forest soil pits using time domain reflectometry. Isotopic signatures of input and soil water at the pits were sampled throughout melt. Total water inputs to the harvested soil surface exceeded that in the forest: 280 mm in the harvested area vs. 212 mm in the forest in 2000 and 526 mm in the harvested area vs. 409 mm in the forest in 2001. Near-surface soil water content, relative saturation of the ablation till and duration of soil saturation at 0.2 m depth were also greater in the harvested area compared to the forest for both years. Despite the absence of between-pit differences in soil properties influencing infiltration into the profile, a thinner ablation till layer at the harvested area pits would have contributed to greater soil saturation at 0.2 m depth in the harvested area. Greater soil wetness in the harvested area appeared to restrict mixing between inputs and pre-melt soil water relative to conditions in the forest during the 2000 melt, leading to longer water residence times at depth in the ablation till. This was partly supported by results from the 2001 melt. We suggest that harvesting of hardwoods on slopes in TLW may promote increased subsurface flow above the basal till contact and saturation overland flow during spring snowmelt, with implications for point-scale soil water chemistry as well as the quantity and quality of slope runoff to receiving streams.