Water Retention Function Research Articles

Drywell infiltration and hydraulic properties in heterogeneous soil profiles

Drywells are increasingly used to capture stormwater runoff for surface infiltration and aquifer recharge, but little research has examined the role of ubiquitous subsurface heterogeneity in hydraulic properties on drywell performance. Numerical experiments were therefore conducted using the HYDRUS (2D/3D) software to systematically study the influence of subsurface heterogeneity on drywell infiltration. Subsurface heterogeneity was described deterministically by defining soil layers or lenses, or by generating stochastic realizations of soil hydraulic properties with selected variance (σ) and horizontal (X) and vertical (Z) correlation lengths. The infiltration rate increased when a high permeability layer/lens was located at the bottom of the drywell, and had larger vertical and especially horizontal dimensions. Furthermore, the average cumulative infiltration (I) for 100 stochastic realizations of a given subsurface heterogeneity increased with σ and X, but decreased with Z. This indicates that the presence of many highly permeable, laterally extending lenses provides a larger surface area for enhanced infiltration than the presence of isolated, highly permeable lenses. The ability to inversely determine soil hydraulic properties from numerical drywell infiltration results was also investigated. The hydraulic properties and the lateral extension of a highly permeable lens could be accurately determined for certain idealized situations (e.g., simple layered profiles) using constant head tests. However, variability in soil hydraulic properties could not be accurately determined for systems that exhibited more realistic stochastic heterogeneity. In this case, the heterogeneous profile could be replaced with an equivalent homogeneous profile and values of an effective isotropic saturated conductivity (Ks) and the shape parameter in the soil water retention function (α) could be inversely determined. The average value of Ksfor 100 stochastic realizations showed a similar dependency to I on σ, X, and Z. Whereas, the average value of α had large confidence interval for soil heterogeneity parameters and played a secondary role in drywell infiltration. This research provides valuable insight on the selection of site, design, installation, and long-term performance of a drywell.

SPorDyn: A Python code for modeling the evolution of soil pore size distribution after tillage

Surface soil structure is very responsive to natural and anthropogenic impacts and these changes alter soil hydraulic properties and the soil water budget. In the midst of a dearth of efforts to capture soil structural dynamics, an analytical solution to the Fokker-Planck Equation with physically-based coefficients has shown promising results in predicting the evolution of soil pore space in agricultural soils. In this study, the Python code for the analytical solution is shown along with steps to estimate coefficients leading towards obtaining the analytical solution.•Python code for modeling the evolution of soil pore space based on an existing model is shared.•The code for the estimation of physically-based coefficients of the model and parameter optimization are also shown.•The final output of the model may be used in estimation of soil water retention and hydraulic conductivity functions.

BEST‐2K Method for Characterizing Dual‐Permeability Unsaturated Soils with Ponded and Tension Infiltrometers

Core Ideas We present a new method for the hydraulic characterization of dual‐permeability soils. The BEST‐2K method was validated with synthetic soil data. The BEST‐2K method was also validated with real experimental data for contrasting soils. This study presents a new method (BEST‐2K) that extends the existing BEST methods for use in characterizing the water retention and hydraulic conductivity functions of matrix and fast‐flow regions in dual‐permeability soils. BEST‐2K requires input information from two water infiltration experiments that are performed under ponded (Beerkan) and unsaturated (tension infiltrometer) conditions at the surface. Other required inputs include water content measurements and the traditional BEST inputs (particle size distribution and bulk density). In this study, first, a flowchart of the BEST‐2K method was developed and illustrated with analytically generated data for a synthetic dual‐permeability soil. Next, a sensitivity analysis was performed to assess the accuracy of BEST‐2K and its sensitivity to the quality of the inputs (water contents and cumulative infiltrations, and the prior estimation of the volume ratio occupied by the fast‐flow region). Lastly, BEST‐2K was applied to real experimental data to characterize three soils that are prone to preferential flow. BEST‐2K was found to be a particularly useful tool that combines experimental and modeling approaches for characterizing dual‐permeability soils and, more generally, soils prone to preferential flows.

Development of a steady-state model to predict daily water table depth and root zone soil matric potential of a cranberry field with a subirrigation system

Maintaining a steady water table depth (WTD) to ensure an optimal soil matric potential in the root zone (RMAP) is vital when growing cranberry under a subirrigation system; owing to losses and other hydrological processes. The excessive rising or falling of the WTD may threaten the plant transpiration either by saturation or lack of moisture in the root soil. A steady-state model was developed for a uniform soil column to predict WTD and RMAP under different weather conditions. The model is based on van Genuchten (VG) and Brooks and Corey (BC) analytical soil water retention functions coupled with Mualem, Brooks and Corey, and Gardner hydraulic conductivity models. The results show that the model is capable of predicting satisfactorily both WTD and RMAP. The VG model performed with a 78.13% accuracy for the WTD and an 88.59% precision according to the Kling Gupta Efficiency coefficient (r2 = 0.90, β = 1.00, and γ = 0.99) for the field storage. Meanwhile for the RMAP the Mualem and Gardner hydraulic conductivity models, predictions were successful 71.87% and 75.00% of the time, respectively. The BC model had a 78.13% success for the WTD, 86.93% accuracy in estimating the field water storage according to Kling-Gupta efficiency coefficient (r2 = 0.89, β = 1.00, and γ = 1.00) and the BC and Gardner hydraulic conductivity models had 65.63% and 71.88% success, respectively. A sensitivity analysis of the model, by means of the Morris method, reveals that for both models, the lower boundary condition impacts significantly both variables which are, however, less affected by the field capacity and the residual soil moisture content. The lower boundary condition interacts with the slope of the soil water retention functions, the height of the capillary fringe, the saturated conductivity, and the saturation moisture content which have non-linear effects. An uncertainty analysis shows that both variables for both models are normally distributed.

An Alert Regarding a Common Misinterpretation of the Van Genuchten α Parameter

ABSTRACT Among the equations available to describe the relation between matric potential and soil water content, the soil water retention function, the most commonly used is the equation proposed by Van Genuchten in his 1980 landmark paper. In soil physics literature, especially in Brazil, several authors relate the inverse of the Van Genuchten parameter α to the air-entry pressure. This study aimed to show this common interpretation to be erroneous, as 1/α corresponds to water contents lower than saturation. The [...]

Temporal dynamics of subsurface soil water content estimated from surface measurement using wavelet transform

Temporal variation of water in the vadose zone is important to understand processes such as solute transport and nutrient cycling. Measurements of soil water content (SWC) in the subsurface are less common than those near the surface and predictions using numerical models are limited by data availability. Wavelet decomposition of surface measurements of SWC could improve modeling of subsurface SWC by segregating features at different temporal scales and projecting them to the subsurface. The objectives of this work were to: 1) predict subsurface SWC using surface SWC and a combination of wavelet analysis and linear regression, and 2) investigate relationships between soil properties and the movement of soil water at various temporal scales, s. Climate data and SWC at various depths were collected from eight sites in the Atlantic Coastal Plain of the USA. Soil water retention and hydraulic conductivity (k) functions of each horizon were optimized by comparing measured and predicted (using HYDRUS-1D) soil water contents. Each time series of SWC was decomposed into 50 scale components using the Mexican Hat wavelet and later reduced to 5 group components with minimal impact on the characteristics of the signal. Changes in the values of each group component with depth were represented with transfer coefficients that could be estimated with predictors derived from particle size distributions and optimized soil hydraulic functions. Prediction depth and saturated k were the two most important predictors for s < 256 h, while k at −10 kPa was the best predictor for 256 h < s < 724 h, and the median value of particle size diameters for s > 724 h. Subsurface soil water content can be reasonably predicted with the proposed approach, particularly when vertical movement of soil water is unrestricted.

Comparison of seven water retention functions used for modelling soil hydraulic conductivity due to film flow

AbstractThe unsaturated soil hydraulic conductivity accounting for film flow is important for understanding soil hydrological and biological processes, especially in arid and semi‐arid regions. Recently, a theoretically based hydraulic conductivity model was developed to describe the hydraulic conductivity as a function of water content. We have used this model to compare seven soil water retention functions commonly used for predicting soil hydraulic conductivity due to film flow. A total of 30 soils, varying in basic properties, were selected from the Unsaturated Soil Hydraulic Database to evaluate the seven functions. The Webb method was applied to identify the critical soil matric potential (hc) below which thin film flow controls water movement. Soil hydraulic conductivity measurements at matric potential below hc were then used for curve fitting according to the seven functions. Slight differences were observed among the functions in predicting soil hydraulic conductivity due to film flow. Six of the seven functions in combination with the hydraulic conductivity model described the hydraulic conductivity due to film flow well, according to the terms of the coefficient of efficiency. The relatively poor performance of the one exception was due to the fact that the linear shape of the function made it less flexible at low matric potentials. In addition, the effect of textural class on its performance was substantial, showing a poorer fit for the sand soil compared with the loam and clay soils. These findings have important applications related to soil and water resources conservation especially in arid and semi‐arid regions.

Numerical Simulation and Sensitivity Analysis for Nitrogen Dynamics Under Sewage Water Irrigation with Organic Carbon

This study is focused on investigating the impacts of organic carbon on the denitrification process of nitrogen transformation and transport. A numerical model, Nitrogen-2D, is modified by considering the impact of organic carbon in the denitrification equation. The modified model is used to simulate the soil nitrogen (including nitrate and ammonium) dynamics under the primary and secondary sewage water irrigation with different organic carbon concentrations. The simulated results of accumulated drainage water amount, soil nitrogen concentration, and nitrogen concentration in the drainage water show that the simulations and measurements are consistent. The comparison of results from the original and improved models shows the necessity to consider the impact of organic carbon. The nitrogen mass balance is calculated to analyze the nitrogen transformation processes quantitatively under different input organic carbon sources. Furthermore, the effect of different input organic carbon sources on the soil nitrogen dynamics is investigated by using the modified Nitrogen-2D model with the calibrated parameters. The input organic carbon source helps to speed up the mineralization and denitrification, which contributes to the slight increase of ammonium concentration and the decrease of nitrate concentration in the shallow soil. Since a large number of soil water and nitrogen transformation and transport parameters are needed when setting up the model, a local sensitivity method is conducted to evaluate the input parameters by the sewage water irrigation case. The results show that the drainage water amount is very sensitive to the exponent n and the coefficient α of the soil water retention function and that the ammonium concentration is very sensitive to the first-order nitrification rate constant, the decomposition rate coefficient in humus pool, and the soil ammonium adsorption coefficient. The nitrate concentration is sensitive to more parameters, especially to the exponent n and the coefficient α in the soil water retention function and to the denitrification rate constant.

Spatial prediction of near surface soil water retention functions using hydrogeophysics and empirical orthogonal functions

The hydrological community often turns to widely available spatial datasets such as the NRCS Soil Survey Geographic database (SSURGO) to characterize the spatial variability of soil properties. When used to spatially characterize and parameterize watershed models, this has served as a reasonable first approximation when lacking localized or incomplete soil data. Within agriculture, soil data has been left relatively coarse when compared to numerous other data sources measured. This is because localized soil sampling is both expensive and time intense, thus a need exists in better connecting spatial datasets with ground observations. Given that hydrogeophysics is data-dense, rapid, non-invasive, and relatively easy to adopt, it is a promising technique to help dovetail localized soil sampling with spatially exhaustive datasets. In this work, we utilize two common near surface geophysical methods, cosmic-ray neutron probe and electromagnetic induction, to identify temporally stable spatial patterns of measured geophysical properties in three 65 ha agricultural fields in western Nebraska. This is achieved by repeat geophysical observations of the same study area across a range of wet to dry field conditions in order to evaluate with an empirical orthogonal function. Shallow cores were then extracted within each identified zone and water retention functions were generated in the laboratory. Using EOF patterns as a covariate, we quantify the predictive skill of estimating soil hydraulic properties in areas without measurement using a bootstrap validation analysis. Results indicate that sampling locations informed via repeat hydrogeophysical surveys, required only five cores to reduce the cross-validation root mean squared error by an average of 64% as compared to soil parameters predicted by a commonly used benchmark, SSURGO and ROSETTA. The reduction to five strategically located samples within the 65 ha fields reduces sampling efforts by up to ∼90% as compared to the common practice of soil grid sampling every 1 ha.

Degradation of the urban ecosystem function due to soil sealing: involvement in the heat island phenomenon and hydrologic cycle in the Tokyo metropolitan area

ABSTRACT We reviewed the role of the soil function of urban green space in mitigating the heat island phenomenon and urban flood damage, which are important issues in the modern urban environment. Urban sprawl has progressed remarkably in the southern part of the Kanto District of Japan, especially since the 1960s. The grassland/bare land area ratio in the center of Tokyo was more than 70% in the 1930s but less than 40% in 1990. On the other hand, the paving area ratio was ~2% in the 1930s but more than 10 times that amount in 1990. Thus, cities, such as Tokyo, in the southern part of the Kanto District have been significantly sealed soil throughout time, and the heat island phenomenon has intensified. Urban green space helps to mitigate the heat island phenomenon based on the water retention and heat dissipation function of plants and unsealed soil. A cool island effect was reported during summer days in urban green spaces in Tokyo. The mitigation of the heat island effect seems to be large, even when conditions, such as the park area, land use, afforestation area ratio, and soil type, differ. Soil sealing and compaction affect urban flooding by hindering the penetration of rainwater and increasing surface runoff. According to a survey in the hilly basin (1 km2) of the western part of Tokyo, the proportion of farm- and forestland decreased due to development. The urban area increased from ~10% in the 1970s to ~60% in the 1980s. As a result, the flood arrival time shortened. Green spaces have a high rainwater permeability. The forest soil structure and presence of O horizons further increase the permeability. By promoting permeability to the underground, it is possible to reduce and delay the water runoff on the land surface. To develop urban green space as green infrastructure, it is necessary to accumulate more information on the current situation and agenda for the future of urban green space.

Predicting the Campbell Soil Water Retention Function: Comparing Visible–Near‐Infrared Spectroscopy with Classical Pedotransfer Function

Core Ideas The Campbell model was anchored at a soil water content of −1000 cm H2O matric potential. The two model parameters were predicted using either soil fines or vis–NIR spectroscopy. Both methods accurately predicted the soil water retention curve. The soil water retention curve (SWRC) is essential for the modeling of water flow and chemical transport in the vadose zone. The Campbell function and its b (pore‐size distribution index) parameter fitted to measured data is a simple method to quantify retention under relatively moist conditions. Measuring soil water retention is time consuming, and a method to accurately predict the Campbell relation from either typically available soil parameters such as bulk density, clay‐size fraction, and organic matter content (soil fines) or from visible–near‐infrared (vis–NIR) spectroscopy may provide a fast and inexpensive alternative. However, the traditional Campbell model has a reference point at saturated water content, and this soil‐structure‐dependent water content will typically be poorly related to basic texture properties and thus be poorly predicted from vis–NIR spectra. In this study, we anchor the Campbell model at the water content at −1000 cm H2O matric potential [log(1000)= pF 3]. Agricultural soil samples with a wide textural range from across Denmark were used. Soil water retention was measured at a number of matric potentials between pF 1 and 3. The soil water content at pF 3 and Campbell b were both well predicted using either a soil‐fines‐based pedotransfer function or vis–NIR spectroscopy. The resulting Campbell function anchored at pF 3 compared closely to measured water retention data for a majority of soils. The ability of the two methods to also predict field average SWRC was evaluated for three fields. Field average, predicted SWRC compared well with field average measured data, with vis–NIR overall performing better.

Water Flow Modeling with Dry Bulk Density Optimization to Determine Hydraulic Properties in Mountain Soils

Core Ideas The GEOtop model was used to calculate water flow in mountain soils. Dry soil bulk density was optimized to determine soil hydraulic properties. Soil water contents for two watersheds were used to test the optimization procedure. A new method for determining profile‐average and depth‐wise hydraulic properties in heterogeneous mountain soils is presented using the GEOtop watershed model in 1‐D vertical mode. Dry soil bulk density–converted volumetric soil water retention data are used to determine van Genuchten soil water retention parameters, and the Kozeny–Carman equation is used to determine saturated soil hydraulic conductivity. Optimum dry soil bulk densities are identified by minimizing the sum of squared error between measured and calculated soil water content time series. The new method was tested using soil moisture data from soil profiles at the Dry Creek Experimental Watershed, Boise, ID, and the Libby Creek Experimental Watershed, Laramie, WY. Results of different scenarios showed that the optimization of a single profile‐average dry soil bulk density is a good option for describing soil water flow in the heterogeneous mountain soils. Soil water content modeling efficiency (ME) values of 0.084 ≤ ME ≤ 0.745 and –2.443 ≤ ME ≤ 0.373 were found for the Dry Creek and Libby Creek sites, respectively. Relatively low ME values for the deepest sensor depths for some scenarios were attributed to the overestimation of soil water freezing and uncertainty in the soil water retention function near saturation. The resulting calibration procedure is computationally efficient because only one parameter (dry soil bulk density) is optimized.

The impact of late medieval deforestation and 20th century forest decline on extreme flood magnitudes in the Ore Mountains (Southeastern Germany)

Vegetation is one of the main controlling factors in the system of flood runoff formation in headwater areas. Especially the absence or presence of forests has a substantial influence on the development of surface runoff and peak discharge as well as on the water balance at the catchment scale. In Germany there is a long history of wood consumption, deforestation and forest recovery. In the Ore Mountains the modern forest distribution is the result of two important developments. The most remarkable deforestation period began with the increase of mining activities after the early 12th century. In modern times, i.e. from the 1950s until the political turn in Eastern Germany at the end of the 1990s forests of the Ore Mountains suffered from industrial SO2 emissions that caused a severe forest decline especially in headwater areas near the main ridge of the mountains. Since the Ore Mountains are one of the main flood generating regions in the Elbe basin the aim of the study is to reveal the influence of the deforestation history on the magnitude of extreme floods. The analysis is based on a rainfall-runoff modelling of the Upper Flöha River in the Ore Mountains (Free State of Saxony, South-eastern Germany) with the mainly physically-based modelling system WaSiM-ETH. Based on the assumption that the recent forest distribution is the result of all the historical developments an extreme flood event was simulated for land use conditions between 2000 and 2008 using statistical storm rainfall intensities with a return period of 100 years and a duration of 12 h (baseline scenario). Then two main scenarios with the forest distribution before the medieval deforestation in the 12th century and land cover before the onset of the SO2-related forest decline in the second half of the 20th century were implemented in the model. The simulation reveals a significant impact of large-scale deforestation and forest decline on the magnitude of flood events. In the scenarios the peak discharge was between 16.4 and 21% lower than in the baseline scenario. This result is mainly influenced by a reduction of surface runoff with an increasing percentage of forests and by a decreasing antecedent soil moisture. The data show clearly, that forest conservancy and land use management are essential to maintain and increase the water retention function of forests.

A global data set of soil hydraulic properties and sub-grid variability of soil water retention and hydraulic conductivity curves

Abstract. Agroecosystem models, regional and global climate models, and numerical weather prediction models require adequate parameterization of soil hydraulic properties. These properties are fundamental for describing and predicting water and energy exchange processes at the transition zone between solid earth and atmosphere, and regulate evapotranspiration, infiltration and runoff generation. Hydraulic parameters describing the soil water retention (WRC) and hydraulic conductivity (HCC) curves are typically derived from soil texture via pedotransfer functions (PTFs). Resampling of those parameters for specific model grids is typically performed by different aggregation approaches such a spatial averaging and the use of dominant textural properties or soil classes. These aggregation approaches introduce uncertainty, bias and parameter inconsistencies throughout spatial scales due to nonlinear relationships between hydraulic parameters and soil texture. Therefore, we present a method to scale hydraulic parameters to individual model grids and provide a global data set that overcomes the mentioned problems. The approach is based on Miller–Miller scaling in the relaxed form by Warrick, that fits the parameters of the WRC through all sub-grid WRCs to provide an effective parameterization for the grid cell at model resolution; at the same time it preserves the information of sub-grid variability of the water retention curve by deriving local scaling parameters. Based on the Mualem–van Genuchten approach we also derive the unsaturated hydraulic conductivity from the water retention functions, thereby assuming that the local parameters are also valid for this function. In addition, via the Warrick scaling parameter λ, information on global sub-grid scaling variance is given that enables modellers to improve dynamical downscaling of (regional) climate models or to perturb hydraulic parameters for model ensemble output generation. The present analysis is based on the ROSETTA PTF of Schaap et al. (2001) applied to the SoilGrids1km data set of Hengl et al. (2014). The example data set is provided at a global resolution of 0.25° at https://doi.org/10.1594/PANGAEA.870605.

A binary mixing model for characterizing stony-soil water retention

A century of research focused primarily on agricultural soils has largely ignored stony soils, which dominate some forests and are poorly understood in terms of the stone influence on soil hydraulic properties. Motivated by this knowledge gap, we quantified the influence of soil-containing stone fragments on bulk soil hydraulic properties by determining the water retention curve (WRC) of soil, stone and stone-soil mixtures with varied volumetric stone content. The measured WRC for seven different stone types based on their composition showed maximum and minimum saturated water contents of 0.55m3m−3 in pumice and 0.025m3m−3 in fine sandstone, respectively. The stony soil water retention function was measured using the simplified evaporation method. Contrasting scenarios were studied considering a broad range of stone inclusions; (i) negligibly porous, (ii) significantly porous but less porous than the background soil, (iii) more porous than the background soil. An averaging scheme to describe the WRC of stony soil was proposed based on the individual WRC of the background and stone inclusion which was in good agreement with the experimental data. The HYDRUS-3D model was also employed to simulate the evaporation experiment used for the WRC measurements. The model simulations supported the basic assumptions of the proposed averaging scheme.

Assessment of water retention function as tool to improve integrated watershed management (case study of Poprad river basin, Slovakia)

The presented study concentrates on assessing the ecosystem function of water retention. The water retention function is defined as the ability of the landscape to retain water, slow runoff and encourage water infiltration. The water retention function was expressed by calculating the hydric significance (HS) indicator. This method is based on scoring the individual input parameters according to their overall impact on watershed hydrology. The study was conducted on a sample area of Poprad River basin. The final results presented a spatial distribution of hydric function within the watershed classified according to its significance into four classes (from limited to excellent significance). A breakdown of the results on the level of elementary watersheds was used in order to examine those with low hydric function. The results showed a significant influence of land-use on retention function; however, this impact could be limited by extreme precipitation or high soil water saturation. The methodology of hydric significance represents an innovative approach towards assessment of ecosystem function of water retention on regional level.

Soil hydro-physical characteristics and water retention function of typical shrubbery stands in the Yellow River Delta of China

The shell ridge worldwide that presents a combination of old and new shell ridges is located in the Yellow River Delta of China. The water storage and retention capacities of the shell sand soil are key factors for the growth and development of vegetation and act as important indicators in evaluations of vegetation-related soil and water conservation. We investigated the hydrological and physical characteristics of the soil and the interactions of these characteristics for the following dominant shrubbery stands on the shell ridge: Tamarix chinensis Lour, Periploca sepium Bunge and Ziziphus jujuba var. Spinosa. The different shrubbery stands presented significantly different physical shell sand parameters, such as water storage capacity, permeability and water-holding capacity. Compared with the bare soil, the shrubbery-covered shell sand soils showed significantly reduced bulk densities; increased porosities, water storage capacities, infiltration rates and water-holding capacities; and reduced particle sizes. The shrubbery increased the amount of soil water-stable aggregates and reduced the amount of soil air-dried aggregates, and the fractal dimension of the soil water-stable aggregates was significantly higher than that of the air-dried aggregates. T. chinensis shrub growth yielded a better soil aggregate structure compared with that of Z. jujuba, whereas the P. sepium shrub yielded the poorest structure. The soil porosity and the mean weight diameter of the soil aggregates were the major factors that affected the water retention capability of the shell sand. The best water retention capability was observed with the T. chinensis shrub stand followed by the Z. jujuba and P. sepium stands, whereas the bare soil exhibited the poorest results. Our results indicate that T. chinensis seedlings are the best choice for planting to improve soil porosity and soil aggregates on the shell ridges of the Yellow River Delta.

Evaluating a sensor setup with respect to near-surface soil water monitoring and determination of in-situ water retention functions

Monitoring water status near the soil surface is a prerequisite for studying hydrological processes at the soil-atmosphere boundary and an option for calibrating remotely sensed water content data, for instance. As the water status of the uppermost soil layer is highly variable in space and time, adequate sensors are required to enable accurate measurements. Therefore, a sensor setup was tested and evaluated in the laboratory and in the field for such a purpose. The arrangement included Hydra Probe and MPS-2 sensors to measure water content and matric potential, respectively.Performance of the MPS-2 was validated in the laboratory by comparing sensor readings with the water potential of a soil, drained to equilibrium for certain pressure steps inside a pressure plate apparatus. Afterwards, six Hydra Probes and twelve MPS-2 sensors were installed in bare soil at a small field plot of about 9m2. The measurements represented soil water status to a depth of 6cm from surface. Core samples were repeatedly excavated around the measurement spots. Their water content was determined and the samples were further utilized to analyze water retention characteristics.The tested setup properly reflected changes of near-surface soil water status due to rainfall and evaporation. However, some shortcomings weakened the potential of the chosen arrangement. Site-specific calibration of the Hydra Probes – implemented by relating sensor readings to the water content values of the core samples – confirmed the applicability of the recommended standard calibration parameters for the respective soil texture. The derived user calibration enabled a measurement accuracy of 0.02cm3·cm−3. Further improvement was restrained by the spatial variability of soil moisture. In this context, spots that were permanently drier or wetter than the others were discovered by means of a temporal stability approach. Performance of MPS-2 sensors was more critical with respect to the objectives. Sensor-to-sensor variation was small at the applied pressure steps of −20, −50, and −100kPa, but the respective averaged readings were −18, −37, and −57kPa. At matric potentials of −200 and −300kPa, the MPS-2 revealed substantial sensor-to-sensor variation. The large deviation of the sensor readings in the field confirmed that the calibration of the MPS-2 should be improved. However, in spite of this inaccuracy, the wide measuring range of the MPS-2 offers suitability to a wide range of potential applications. As an example, water retention functions were calculated from the in-situ data and compared to retention data from the core samples.

Effects of Peach (Prunus persica)-Derived Glucosylceramide on the Human Skin

Background: Plant-derived ceramides are functional natural products with vari-ous physiological effects that improve water retention and skin permeability functions.Objective: Herein, we isolated peach (Prunus persica)-derived glucosylceramide with high purity and evaluated its effects on moisture and permeability of skin.Methods: Three separate experiments were performed: evaluations of the effect of peach-derived glucosylceramide application on the ceramide content in a three-dimensional hu-man cultured skin model, water retention effect of the oral administration of the peach-derived glucosylceramide on human skin functionality, and safety of the long-term admin-istration of the peach-derived glucosylceramide in human subjects.Results: Treatments of three-dimensional cultures of human skin with peach-derived gluco-sylceramide led to dose-dependent increases in human ceramide contents. Additionally, af-ter oral administration of ceramide to humans, dose-dependent improvements in water re-tention functions of skin, suppression of trans-epidermal water loss and improvements in skin texture were observed. Furthermore, no significant changes in subjective/objective symptoms, physical characteristics, or laboratory test values were observed in human sub-jects following long term oral administration of ceramide at doses that were 4.5-9-times greater than recommended. Taken together, the present data indicate the positive effects of peach ceramide on skin function and no adverse effects.

基于二元水循环的黄淮海平原耕地水源涵养功能研究

PDF HTML阅读 XML下载 导出引用 引用提醒 基于二元水循环的黄淮海平原耕地水源涵养功能研究 DOI: 10.5846/stxb201606011059 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家科技支撑计划项目（2015BAD06B01） Study on the water conservation function of cultivated land based on dualistic water cycle in Huang-Huai-Hai Plain Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:水源涵养功能是陆地生态系统的重要功能类型之一。黄淮海平原耕地数量巨大，耕地利用模式典型，研究其水源涵养功能，对于调控区域水资源，推动耕地可持续利用有重要作用。从耕地利用角度出发，基于整个系统二元水循环过程，构建了黄淮海平原耕地水源涵养功能研究基本框架，并应用SCS-CN模型，结合研究区耕地覆盖数据、气候数据、土壤数据对黄淮海平原耕地水源涵养功能进行了评价。研究结果表明：耕地利用过程中的耕地水源涵养功能认识，应从理想水源涵养能力、有效水源涵养能力和净水源涵养能力3个层次展开；黄淮海平原耕地水源涵养功能效应在上述各层级上均表现出正向性，耕地水源涵养能力分别为1890.74、1127.76、464.62亿m3；空间上，黄淮海平原耕地水源涵养功能具有明显的空间分异性，北部和东南部地区耕地水源涵养能力较强，中部和西南部地区耕地水源涵养能力较弱。研究结果不仅为耕地生态功能理论研究提供新思考点，同时也为耕地水资源有效调控以及耕地生态补偿制定提供参考和支撑。 Abstract:Water conservation as an important ecosystem function has caused a rising interests in the scientific community in recent years. Huang-Huai-Hai Plain has a substantial cultivated land area and typical cultivated land-use patterns. So, the research on water conservation function of cultivated land in this area is important for regulating the regional water resources and promoting the sustainable utilization of cultivated land. We constructed a basic research framework of the water conservation function of cultivated land in Huang-Huai-Hai Plain, which based on the dualistic water cycle process of cultivated land use systems. The water conservation function and spatial distribution of cultivated land in the Huang-Huai-Hai Plain was evaluated with cultivated land cover data, climate data, and soil data, by using the Soil Conservation Service Curve Number(SCS-CN) model. The results suggested that the water conservation function of cultivated land should be identified by the ideal water conservation ability, effective water conservation ability, and net water conservation ability, which were 1890.74×108, 1127.76×108, and 464.62×108 m3, respectively, in Huang-Huai-Hai Plain in 2012. And the water retention function of cultivated land showed obvious spatial heterogeneity:It was strong in the northern and southeastern regions of the study area, but it was weak in the central and southwestern regions of the study area. This study provides a new perspective on research of the ecological function theory of cultivated land, and a reference and support for regulating water resources effectively and formulating ecological compensation of cultivated land. 参考文献 相似文献 引证文献