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1.
Two ground penetrating radar (GPR) techniques were used to estimate the shallow soil water content at the field scale. The first technique is based on the ground wave velocity measured with a bistatic impulse radar connected to 450 MHz ground-coupled antennas. The second technique is based on inverse modeling of an off-ground monostatic TEM horn antenna in the 0.8–1.6 GHz frequency range. Data were collected on a 8 by 9 m partially irrigated intensive research plot and along four 148.5 m transects. Time domain reflectometry, capacitance sensors, and volumetric soil samples were used as reference measurements. The aim of the study was to test the applicability of the ground wave method and the off-ground inverse modeling approach at the field scale for a soil with a silt loam texture. The results for the ground wave technique were difficult to interpret due to the strong attenuation of the GPR signal, which is related to the silt loam texture at the test site. The root mean square error of the ground wave technique was 0.076 m3 m−3 when compared to the TDR measurements and 0.102 m3 m−3 when compared with the volumetric soil samples. The off-ground monostatic GPR measured less within-field soil water content variability than the reference measurements, resulting in a root mean square error of 0.053 m3 m−3 when compared with the TDR measurements and an error of 0.051 m3 m−3 when compared with the volumetric soil samples. The variability between the two GPR measurements was even larger with a RSME of 0.115 m3 m−3. In summary, both GPR methods did not provide adequate spatial information on soil water content variation at the field scale. The main reason for the deviating results of the ground wave method was the poor data quality due to high silt and clay content at the test site. Additional reasons were shallow reflections and the dry upper soil layer that cannot be detected by the ground wave method. In the case of off-ground GPR, the high sensitivity to the dry surface layer is the most likely reason for the observed deviations. The off-ground GPR results might be improved by using a different antenna that allows data acquisition in a lower frequency range.  相似文献   

2.
GPR study of pore water content and salinity in sand   总被引：5，自引：0，他引：5  
High‐resolution studies of hydrological problems of the near‐surface zone can be better accomplished by applying ground‐probing radar (GPR) and geoelectrical techniques. We report on GPR measurements (500 and 900 MHz antennae) which were carried out on a sorted, clean sand, both in the laboratory and at outdoor experimental sites. The outdoor sites include a full‐scale model measuring 5 × 3 × 2.4 m3 and a salinity site measuring 7.0 × 1.0 × 0.9 m3 with three buried sand bodies saturated with water of various salinities. Our studies investigate the capability of GPR to determine the pore water content and to estimate the salinity. These parameters are important for quantifying and evaluating the water quality of vadose zones and aquifers. The radar technique is increasingly applied in quantifying soil moisture but is still rarely used in studying the problems of water salinity and quality. The reflection coefficient at interfaces is obtained from the amplitude spectrum in the frequency and time domains and is confirmed by 1D wavelet modelling. In addition, the GPR velocity to a target at a known depth is determined using techniques of two‐way traveltime, CMP semblance analysis and fitting an asymptotic diffraction curve. The results demonstrate that the reflection coefficient increases with increasing salinity of the moisture. These results may open up a new approach for applications in environmental problems and groundwater prospecting, e.g. mapping and monitoring of contamination and evaluating of aquifer salinity, especially in coastal areas with a time‐varying fresh‐water lens. In addition, the relationship between GPR velocity and water content is established for the sand. Using this relationship, a subsurface velocity distribution for a full‐scale model of this sand is deduced and applied for migrated radargrams. Well‐focused diffractions separate single small targets (diameter of 2–3 cm, at a depth of 20–180 cm and a vertical interval of 20 cm). The results underscore the high potential of GPR for determining moisture content and its variation, flow processes and water quality, and even very small bodies inside the sand or soil.  相似文献   

3.
We evaluate the reliability of the joint use of Ground Penetrating Radar (GPR) and Time Domain Reflectometry (TDR) to map dry snow depth, layering, and density where the snowpack thickness is highly irregular and the use of classical survey methods (i.e., hand probes and snow sampling) is unsustainable.We choose a test site characterised by irregular ground morphology, slope, and intense wind action (about 3000 m a.s.l., Western Alps, northern Italy) in dry snow conditions and with a snow-depth ranging from 0.3 m to 3 m over a few tens of metres over the course of a season.The combined use of TDR and high-frequency GPR (at a nominal frequency of 900 MHz) allows for rapid high-resolution imaging of the snowpack. While the GPR data show the interface between the snowpack and the ground, the snow layering, and the presence of snow crusts, the TDR survey allows the local calibration of wave speed based on GPR measurements and the estimation of layer densities. From January to April, there was a slight increase in the average wave speed from 0.22 to 0.24 m/ns from the accumulation zone to the eroded zone. The values are consistent with density values in the range of 350–450 kg/m3, with peaks of 600 kg/m3, as gravimetrically measured from samples from snow pits at different times. The conversion of the electromagnetic wave speed into density agrees with the core samples, with an estimated uncertainty of about 10%.  相似文献   

4.
Soil moisture is widely recognized as a fundamental variable governing the mass and energy fluxes between the land surface and the atmosphere. In this study, the soil moisture modelling at sub‐daily timescale is addressed by using an accurate representation of the infiltration component. For that, the semi‐analytical infiltration model proposed by Corradini et al. (1997) has been incorporated into a soil water balance model to simulate the evolution in time of surface and profile soil moisture. The performances of this new soil moisture model [soil water balance module‐semi‐analytical (SWBM‐SA)] are compared with those of a precedent version [SWBM‐Green–Ampt (GA)] where the GA approach was employed. Their capability to reproduce in situ soil moisture observations at three sites in Italy, Spain and France is analysed. Hourly observations of quality‐checked rainfall, temperature and soil moisture data for a 2‐year period are used for testing the modelling approaches. Specifically, different configurations for the calibration and validation of the models are adopted by varying a single parameter, that is, the saturated hydraulic conductivity. Results indicate that both SWBMs are able to reproduce satisfactorily the hourly soil moisture temporal pattern for the three sites with root mean square errors lower than 0.024 m3/m3 both in the calibration and validation periods. For all sites, the SWBM‐SA model outperforms the SWBM‐GA with an average reduction of the root mean square error of ~20%. Specifically, the higher improvement is observed for the French site for which in situ observations are measured at 30 cm depth, and this is attributed to the capability of the SA infiltration model to simulate the time evolution of the whole soil moisture profile. The reasonable models performance coupled with the need to calibrate only a single parameter makes them useful tools for soil moisture simulation in different regions worldwide, also in scarcely gauged areas. Copyright © 2013 John Wiley & Sons, Ltd.  相似文献   

5.
The recent transformation of wetlands into farmland in East Africa is accelerating due to growing food-demand, land shortages, and an increasing unpredictability of climatic conditions for crop production in uplands. However, the conversion of pristine wetlands into sites of production may alter hydrological attributes with negative effects on production potential. Particularly the amount and the dynamics of plant available soil moisture in the rooting zone of crops determine to a large extent the agricultural production potential of wetlands. Various methods exist to assess soil moisture dynamics with Frequency Domain Reflectometry (FDR) being among the most prominent. However, the suitability of FDR sensors for assessing plant available soil moisture has to date not been confirmed for wetland soils in the region. We monitored the seasonal and spatial dynamics of water availability for crop growth in an inland valley wetland of the Kenyan highlands using a FDR sensor which was site-specifically calibrated. Access tubes were installed within different wetland use types and hydrological situations along valley transects and soil properties affecting soil moisture (organic C, texture, and bulk density) were investigated. There was little variation in soil attributes between physical positions in the valley, and also between topsoil and subsoil attributes with the exception of organic C contents. With a root mean squared error of 0.073 m3/m3, the developed calibration function of the FDR sensor allows for reasonably accurate soil moisture prediction for both within-site comparisons and the monitoring of temporal soil moisture variations. Applying the calibration equation to a time series of profile probe readings over a period of one year illustrated not only the temporal variation of soil moisture, but also effects of land use.  相似文献   

6.
With well-determined hydraulic parameters in a hydrologic model, a traditional data assimilation method (such as the Kalman filter and its extensions) can be used to retrieve root zone soil moisture under uncertain initial state variables (e.g., initial soil moisture content) and good simulated results can be achieved. However, when the key soil hydraulic parameters are incorrect, the error is non-Gaussian, as the Kalman filter will produce a persistent bias in its predictions. In this paper, we propose a method coupling optimal parameters and extended Kalman filter data assimilation (OP-EKF) by combining optimal parameter estimation, the extended Kalman filter (EKF) assimilation method, a particle swarm optimization (PSO) algorithm, and Richards’ equation. We examine the accuracy of estimating root zone soil moisture through the optimal parameters and extended Kalman filter data assimilation method by using observed in situ data at the Meiling experimental station, China. Results indicate that merely using EKF for assimilating surface soil moisture content to obtain soil moisture content in the root zone will produce a persistent bias between simulated and observed values. Using the OP-EKF assimilation method, estimates were clearly improved. If the soil profile is heterogeneous, soil moisture retrieval is accurate in the 0-50 cm soil profile and is inaccurate at 100 cm depth. Results indicate that the method is useful for retrieving root zone soil moisture over large areas and long timescales even when available soil moisture data are limited to the surface layer, and soil moisture content are uncertain and soil hydraulic parameters are incorrect.  相似文献   

7.
This paper presents an assessment of the relationship between near-surface soil moisture (SM) and SM at other depths in the root zone under three different land uses: irrigated corn, rainfed corn and grass. This research addresses the question whether or not near-surface SM can be used reliably to predict plant available root zone SM and SM at other depths. For this study, a realistic soil-water energy balance process model is applied to three locations in Nebraska representing an east-to-west hydroclimatic gradient in the Great Plains. The applications were completed from 1982 through to 1999 at a daily time scale. The simulated SM climatologies are developed for the root zone as a whole and for the five layers of the soil profile to a depth of 1·2 m. Over all, the relationship between near-surface SM (0–2·5 cm) and plant available root zone SM is not strong. This applies to all land uses and for all locations. For example, r estimates range from 0·02 to 0·33 for this relationship. Results for near-surface SM and SM of several depths suggest improvement in r estimates. For example, these estimates range from − 0·19 to 0·69 for all land uses and locations. It was clear that r estimates are the highest (0·49–0·69) between near-surface and the second layer (2·5–30·5 cm) of the root zone. The strength of this type of relationship rapidly declines for deeper depths. Cross-correlation estimates also suggest that at various time-lags the strength of the relationship between near-surface SM and plant available SM is not strong. The strength of the relationship between SM modulation of the near surface and second layer over various time-lags slightly improves over no lags. The results suggest that use of near-surface SM for estimating SM at 2·5–30 cm is most promising. Copyright © 2007 John Wiley & Sons, Ltd.  相似文献   

8.
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.  相似文献   

9.
A soil moisture retrieval method is proposed, in the absence of ground-based auxiliary measurements, by deriving the soil moisture content relationship from the satellite vegetation index-based evapotranspiration fraction and soil moisture physical properties of a soil type. A temperature–vegetation dryness index threshold value is also proposed to identify water bodies and underlying saturated areas. Verification of the retrieved growing season soil moisture was performed by comparative analysis of soil moisture obtained by observed conventional in situ point measurements at the 239-km2 Reynolds Creek Experimental Watershed, Idaho, USA (2006–2009), and at the US Climate Reference Network (USCRN) soil moisture measurement sites in Sundance, Wyoming (2012–2015), and Lewistown, Montana (2014–2015). The proposed method best represented the effective root zone soil moisture condition, at a depth between 50 and 100 cm, with an overall average R2 value of 0.72 and average root mean square error (RMSE) of 0.042.  相似文献   

10.
Soil moisture is highly variable both spatially and temporally. It is widely recognized that improving the knowledge and understanding of soil moisture and the processes underpinning its spatial and temporal distribution is critical. This paper addresses the relationship between near‐surface and root zone soil moisture, the way in which they vary spatially and temporally, and the effect of sampling design for determining catchment scale soil moisture dynamics. In this study, catchment scale near‐surface (0–50 mm) and root zone (0–300 mm) soil moisture were monitored over a four‐week period. Measurements of near‐surface soil moisture were recorded at various resolutions, and near‐surface and root zone soil moisture data were also monitored continuously within a network of recording sensors. Catchment average near‐surface soil moisture derived from detailed spatial measurements and continuous observations at fixed points were found to be significantly correlated (r2 = 0·96; P = 0·0063; n = 4). Root zone soil moisture was also found to be highly correlated with catchment average near‐surface, continuously monitored (r2 = 0·81; P < 0·0001; n = 26) and with detailed spatial measurements of near‐surface soil moisture (r2 = 0·84). The weaker relationship observed between near‐surface and root zone soil moisture is considered to be caused by the different responses to rainfall and the different factors controlling soil moisture for the soil depths of 0–50 mm and 0–300 mm. Aspect is considered to be the main factor influencing the spatial and temporal distribution of near‐surface soil moisture, while topography and soil type are considered important for root zone soil moisture. The ability of a limited number of monitoring stations to provide accurate estimates of catchment scale average soil moisture for both near‐surface and root zone is thus demonstrated, as opposed to high resolution spatial measurements. Similarly, the use of near‐surface soil moisture measurements to obtain a reliable estimate of deeper soil moisture levels at the small catchment scale was demonstrated. Copyright © 2007 John Wiley & Sons, Ltd.  相似文献   

11.
Rapidly depleting unconfined aquifers are the primary source of water for irrigation on the North China Plain. Yet, despite its critical importance, groundwater recharge to the Plain remains an enigma. We introduce a one‐dimensional soil‐water‐balance model to estimate precipitation‐ and irrigation‐generated areal recharge from commonly available crop and soil characteristics and climate data. To limit input data needs and to simplify calculations, the model assumes that water flows vertically downward under a unit gradient; infiltration and evapotranspiration are separate, sequential processes; evapotranspiration is allocated to evaporation and transpiration as a function of leaf‐area index and is limited by soil‐moisture content; and evaporation and transpiration are distributed through the soil profile as exponential functions of soil and root depth, respectively. For calibration, model‐calculated water contents of 11 soil‐depth intervals from 0 to 200 cm were compared with measured water contents of loam soil at four sites in Luancheng County, Hebei Province, over 3 years (1998–2001). Each 50‐m2 site was identically cropped with winter wheat and summer maize, but received a different irrigation treatment. Average root mean‐squared error between measured and model‐calculated water content of the top 180 cm was 4·2 cm, or 9·3% of average total water content. In addition, model‐calculated evapotranspiration compared well with that measured by a large‐scale lysimeter. To test the model, 12 additional sites were simulated successfully. Model results demonstrate that drainage from the soil profile is not a constant fraction of precipitation and irrigation inputs, but rather the fraction increases as the inputs increase. Because this drainage recharges the underlying aquifer, improving irrigation efficiency by reducing seepage will not reverse water‐table declines. Copyright © 2003 John Wiley & Sons, Ltd.  相似文献   

12.
Ground-penetrating radar (GPR) is a non-destructive geophysical technique to obtain information about shallow subsurface by transmitting electromagnetic waves into the ground and registering signals reflected from objects or layers with different dielectric properties. The present GPR study was conducted in Võhmuta limestone quarry in Estonia in order to describe the relationship between GRP responses to the variations in petrophysical properties. Sub-horizontally oriented cores for petrophysical measurements were drilled from the side wall of the quarry. The GPR profiles were run at the sloped trench floor and on the top of side wall in order to correlate traceable reflections with physical properties. Based on three techniques: (i) hyperbola fitting, (ii) wide angle reflection and refraction (WARR), and (iii) topographic, a mean electromagnetic wave velocity value of 9.25 cm ns?1 (corresponding to relative dielectric permittivity of 10.5) was found to describe the sequence and was used for time-to-depth conversion. Examination of radar images against petrophysical properties revealed that major reflections appear in levels where the changes in porosity occur.  相似文献   

13.
The objective of this study was to validate the soil moisture data derived from coarse‐resolution active microwave data (50 km) from the ERS scatterometer. The retrieval technique is based on a change detection method coupled with a data‐based modelling approach to account for seasonal vegetation dynamics. The technique is able to derive information about the soil moisture content corresponding to the degree of saturation of the topmost soil layer (∼5 cm). To estimate profile soil moisture contents down to 100 cm depth from the scatterometer data, a simple two‐layer water balance model is used, which generates a red noise‐like soil moisture spectrum. The retrieval technique had been successfully applied in the Ukraine in a previous study. In this paper, the performance of the model in a semi‐arid Mediterranean environment characterized by low annual precipitation (400 mm), hot dry summers and sandy soils is investigated. To this end, field measurements from the REMEDHUS soil moisture station network in the semi‐arid parts of the Duero Basin (Spain) were used. The results reveal a significant coefficient of determination (R2 = 0·75) for the averaged 0–100 cm soil moisture profile and a root mean square error (RMSE) of 2·2 vol%. The spatial arrangement of the REMEDHUS soil moisture stations also allowed us to study the influence of the small‐scale variability of soil moisture within the ERS scatterometer footprint. The results show that the small‐scale variability in the study area is modest and can be explained in terms of texture fraction distribution in the soil profiles. Copyright © 2004 John Wiley & Sons, Ltd.  相似文献   

14.
Water flow in the soil–root–stem system was studied in a flooded riparian hardwood forest in the upper Rhine floodplain. The study was undertaken to identify the vertical distribution of water uptake by trees in a system where the groundwater is at a depth of less than 1 m. The three dominant ligneous species (Quercus robur, Fraxinus excelsior and Populus alba) were investigated for root structure (vertical extension of root systems), leaf and soil water potential (Ψm), isotopic signal (18O) of soil water and xylem sap. The root density of oak and poplar was maximal at a depth of 20 to 60 cm, whereas the roots of the ash explored the surface horizon between 0 and 30 cm, which suggests a complementary tree root distribution in the hardwood forest. The flow density of oak and poplar was much lower than that of the ash. However, in the three cases the depth of soil explored by the roots reached 1·2 m, i.e. just above a bed of gravel. The oak roots had a large lateral distribution up to a distance of 15 m from the trunk. The water potential of the soil measured at 1 m from the trunk showed a zone of strong water potential between 20 and 60 cm deep. The vertical profile of soil water content varied from 0·40 to 0·50 cm3 cm?3 close to the water table, and 0·20 to 0·30 cm3 cm?3 in the rooting zone. The isotopic signal of stem water was constant over the whole 24‐h cycle, which suggested that the uptake of water by trees occurred at a relatively constant depth. By comparing the isotopic composition of water between soil and plant, it was concluded that the water uptake occurred at a depth of 20 to 60 cm, which was in good agreement with the root and soil water potential distributions. The riparian forest therefore did not take water directly from the water table but from the unsaturated zone through the effect of capillarity. Copyright © 2007 John Wiley & Sons, Ltd.  相似文献   

15.
ABSTRACT

In this study we analyzed two models commonly used in remote sensing-based root-zone soil moisture (SM) estimations: one utilizing the exponential decaying function and the other derived from the principle of maximum entropy (POME). We used both models to deduce root-zone (0–100 cm) SM conditions at 11 sites located in the southeastern USA for the period 2012–2017 and evaluated the strengths and weaknesses of each approach against ground observations. The results indicate that, temporally, at shallow depths (10 cm), both models performed similarly, with correlation coefficients (r) of 0.89 (POME) and 0.88 (exponential). However, with increasing depths, the models start to deviate: at 50 cm the POME resulted in r of 0.93 while the exponential filter (EF) model had r of 0.58. Similar trends were observed for unbiased root mean square error (ubRMSE) and bias. Vertical profile analysis suggests that, overall, the POME model had nearly 30% less ubRMSE compared to the EF model, indicating that the POME model was relatively better able to distribute the moisture content through the soil column.  相似文献   

16.
Hydraulic redistribution defined as the translocation of soil moisture by plant root systems in response to water potential gradients is a phenomenon widely documented in different climate, vegetation, and soil conditions. Past research has largely focused on hydraulic redistribution in deep tree roots with access to groundwater and/or winter rainfall, while the case of relatively shallow (i.e., ≈1–2 m deep) tree roots has remained poorly investigated. In fact, it is not clear how hydraulic redistribution in shallow root zones is affected by climate, vegetation, and soil properties. In this study, we developed a model to investigate the climate, vegetation, and soil controls on the net direction and magnitude of hydraulic redistribution in shallow tree root systems at the growing season to yearly timescale. We used the model to evaluate the effect of hydraulic redistribution on the water stress of trees and grasses. We found that hydraulic lift increases with decreasing rainfall frequency, depth of the rooting zone, root density in the deep soil and tree leaf area index; at the same time for a given rainfall frequency, hydraulic lift increases with increasing average rainstorm depth and soil hydraulic conductivity. We propose that water drainage into deeper soil layers can lead to the emergence of vertical water potential gradients sufficient to explain the occurrence of hydraulic lift in shallow tree roots without invoking the presence of a shallow water table or winter precipitation. We also found that hydraulic descent reduces the water stress of trees and hydraulic lift reduces the water stress of grass with important implications on tree–grass interactions.  相似文献   

17.
Seasonal soil water dynamics were measured on a hillslope transect in the jarrah forest of southwest Western Australia over the period 1984-86 using mercury manometer tensiometers, gypsum blocks, and a neutron moisture meter. The soil water potential gradients indicated downward vertical drainage flux through winter and spring. There was generally a change to an upwards flux in early summer which was sustained through to autumn. A shallow ephemeral saturation zone was identified in and above a duricrust layer, lasting up to three days after heavy, late winter rainfall. The annual maximum to minimum unsaturated soil water storage on the hillslope was approximately 400 mm to 6 m depth and 480 mm to 15 m depth. This did not change significantly in years of substantially different winter rainfall. The magnitude of seasonal soil water storage was similar to other forested areas with deep soil profiles. The depth of observable infiltration was dependent on annual rainfall. This was consistent with the observation that groundwater levels responded to rainfall over the whole hillslope in wet years but only responded on the lower slopes in dry years. The average summer drying rate of the soil profile to 6 m depth of 3.5 mm day?1 was within the range of values reported for forests elsewhere. In late summer, following an extended drought period, the drying rate decreased downslope but increased midslope.  相似文献   

18.
Root zone soil water content impacts plant water availability, land energy and water balances. Because of unknown hydrological model error, observation errors and the statistical characteristics of the errors, the widely used Kalman filter (KF) and its extensions are challenged to retrieve the root zone soil water content using the surface soil water content. If the soil hydraulic parameters are poorly estimated, the KF and its extensions fail to accurately estimate the root zone soil water. The H‐infinity filter (HF) represents a robust version of the KF. The HF is widely used in data assimilation and is superior to the KF, especially when the performance of the model is not well understood. The objective of this study is to study the impact of uncertain soil hydraulic parameters, initial soil moisture content and observation period on the ability of HF assimilation to predict in situ soil water content. In this article, we study seven cases. The results show that the soil hydraulic parameters hold a critical role in the course of assimilation. When the soil hydraulic parameters are poorly estimated, an accurate estimation of root soil water content cannot be retrieved by the HF assimilation approach. When the estimated soil hydraulic parameters are similar to actual values, the soil water content at various depths can be accurately retrieved by the HF assimilation. The HF assimilation is not very sensitive to the initial soil water content, and the impact of the initial soil water content on the assimilation scheme can be eliminated after about 5–7 days. The observation interval is important for soil water profile distribution retrieval with the HF, and the shorter the observation interval, the shorter the time required to achieve actual soil water content. However, the retrieval results are not very accurate at a depth of 100 cm. Also it is complex to determine the weighting coefficient and the error attenuation parameter in the HF assimilation. In this article, the trial‐and‐error method was used to determine the weighting coefficient and the error attenuation parameter. After the first establishment of limited range of the parameters, ‘the best parameter set’ was selected from the range of values. For the soil conditions investigated, the HF assimilation results are better than the open‐loop results. Copyright © 2010 John Wiley & Sons, Ltd.  相似文献   

19.
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20.
Sampling of soil pore moisture in the vadose zone underneath land disposal facilities (landfills and surface impoundments) for hazardous waste has been suggested as an "early warning system" to detect leakage from these facilities. Some states require vadose zone moisture sampling at such sites. Given a leak of a particular size, mathematical models can estimate the necessary moisture sample volume collection times and lysimeter spacings to guarantee detection of the leak in a homogeneous medium. Examination of 47 hazardous waste sites existing in 1984 indicated the most were located in areas with water tables too shallow to permit vadose zone detection monitoring. Several of the 47 sites had soils that could be described as loamy sand, silt loam or silty clay. Using these three soils as examples, the process of lysimeter leak-detector network design has been illustrated. For a particular loamy sand with a saturates hydraulic conductivity of 10-6 cm/ sec, the maximum ceramic lysimeter spacing is 15.5 feet at a depth of 30 feet to collec a moisture sample of 10 mL in one week from a 1 ft2 leak. For a silt loam, maximum lysimeter spacing would be 17 feet at depth of 15 feet. For silty clays, the maximum lysimeter spacing is 7 feet at a depth of 2 feet; maximum emplacement depth is about 9 feet. Calculations show that in some soils, suction lysimeters will not be able to collect usable moisture samples. Since soil properties vary widely and lysimeter spacing is strongly dependent on soil-moisture characteristics appropriate soil measurements and modeling must be performed at each disposal facility to estimate lysimete performance and to select locations for emplacement.  相似文献   

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