Range Of Soil Moisture Research Articles

Assessment of modernized GPS L5 SNR for ground-based multipath reflectometry applications

Global Positioning System (GPS) signal-to-noise ratio (SNR) measurements can be employed to retrieve environmental variables in multipath reception conditions, whereby direct or line-of-sight transmission is received simultaneously with coherent reflections thereof. Previous GPS SNR multipath studies of soil moisture and snow depth have focused on the legacy GPS L1 and L2 bands. In the present paper, short-delay, near-grazing incidence multipath from the L5-band GPS SNR is assessed for its value in detecting soil moisture and snow depth. The L5 signal will become more important in the future because of compatibility and interoperability among the different global satellite navigation systems. The L5 results are compared with L2C estimates to determine whether the L2C–L5 differences (given their differing power budgets and their modulation properties) are significant. To address these questions, measurements and simulations were employed. A physically-based multipath simulator was enhanced to investigate the differences between parameter retrievals for the L2C and the L5 GPS signals. Parameter retrievals from synthetic observations for different scenarios were compared. Comparisons included varying reflector height, surface material, and surface roughness. Measurements from two GPS stations in Colorado, USA, were used to retrieve soil moisture and snow depth conditions. Over a 153-day period that encompassed the catastrophic 2013 Colorado flooding event, L2-derived volumetric soil moisture had an RMS difference of 0.042cm3/cm3 while the L5 RMS difference was 0.034cm3/cm3 with respect to in-situ data (values of volumetric soil moisture range between 0.04 and 0.34cm3/cm3). In a separate 483-day campaign, L5-derived snow depth estimates were compared to L2C-derived values and found strongly correlated, deviating from a one-to-one relationship by only 0.00001±0.0064cm/cm. These results indicate the absence of any detectable biases in L5 as compared to L2C for retrieving soil moisture and snow depth from GPS SNR multipath observations.

Soil water thermodynamic to unify water retention curve by pressure plates and tensiometer

The pressure plate method is a standard method for measuring the pF curves, also called soil water retention curves, in a large soil moisture range from saturation to a dry state corresponding to a tension pressure of near 1500 kPa. However, the pressure plate can only provide discrete water retention curves represented by a dozen measured points. In contrast, the measurement of the soil water retention curves by tensiometer is direct and continuous, but limited to the range of the tensiometer reading: from saturation to near 70-80 kPa. The two methods stem from two very different concepts of measurement and the compatibility of both methods has never been demonstrated. The recently established thermodynamic formulation of the pedostructure water retention curve, will allow the compatibility of the two curves to be studied, both theoretically and experimentally. This constitutes the object of the present article. We found that the pressure plate method provides accurate measurement points of the pedostructure water retention curve h(W), conceptually the same as that accurately measured by the tensiometer. However, contrarily to what is usually thought, h is not equal to the applied air pressure on the sample, but rather, is proportional to its logarithm, in agreement with the thermodynamic theory developed in the article. The pF curve and soil water retention curve, as well as their methods of measurement are unified in a same physical theory. It is the theory of the soil medium organization (pedostructure) and its interaction with water. We show also how the hydrostructural parameters of the theoretical curve equation can be estimated from any measured curve, whatever the method of measurement. An application example using published pF curves is given.

Remote monitoring of soil moisture using passive microwave-based techniques — Theoretical basis and overview of selected algorithms for AMSR-E

Satellite-based passive microwave remote sensing has been shown to be a valuable tool in mapping and monitoring global soil moisture. The Advanced Microwave Scanning Radiometer on the Aqua platform (AMSR-E) has made significant contributions to this application. As the result of agency and individual initiatives, several approaches for the retrieval of soil moisture from AMSR-E have been proposed and implemented. Although the majority of these are based on the same Radiative Transfer Equation, studies have shown that the resulting soil moisture estimates can differ significantly. A primary goal of this investigation is to understand these differences and develop a suitable approach to potentially improve the algorithm currently used by NASA in producing its operational soil moisture product. In order to achieve this goal, the theoretical basis of several alternative soil moisture retrieval algorithms are examined. Analysis has focused on five established approaches: the operational algorithm adopted by NASA, which is referred to as the Normalized Polarization Difference algorithm, the Single Channel Algorithm, the Land Parameter Retrieval Model, the University of Montana soil moisture algorithm, and the HydroAlgo Artificial Neural Network algorithm. Previous comparisons of these algorithms in the literature have typically focused on the retrieved soil moisture products, and employed different metrics and data sets, and have resulted in differing conclusions. In this investigation we attempt to provide a more thorough understanding of the fundamental differences between the algorithms and how these differences affect their performance in terms of range of soil moisture provided. The comparative overview presented in the paper is based on the operating versions of the source codes of the individual algorithms. Analysis has indicated that the differences between algorithms lie in the specific parameterizations and assumptions of each algorithm. The comparative overview of the theoretical basis of the approaches is linked to differences found in the soil moisture retrievals, leading to suggestions for improvements and increased reliability in these algorithms.

Effect of soil hydraulic properties on the relationship between the spatial mean and variability of soil moisture

Summary Knowledge of spatial mean soil moisture and its variability over time is needed in many environmental applications. We analyzed dependencies of soil moisture variability on average soil moisture contents in soils with and without root water uptake using ensembles of non-stationary water flow simulations by varying soil hydraulic properties under different climatic conditions. We focused on the dry end of the soil moisture range and found that the magnitude of soil moisture variability was controlled by the interplay of soil hydraulic properties and climate. The average moisture at which the maximum variability occurred depended on soil hydraulic properties and vegetation. A positive linear relationship was observed between mean soil moisture and its standard deviation and was controlled by the parameter defining the shape of soil water retention curves and the spatial variability of saturated hydraulic conductivity. The influence of other controls, such as variable weather patterns, topography or lateral flow processes needs to be studied further to see if such relationship persists and could be used for the inference of soil hydraulic properties from the spatiotemporal variation in soil moisture.

羊草和紫花苜蓿生长特征及光合特性对不同土壤水分的响应

PDF HTML阅读 XML下载 导出引用 引用提醒 羊草和紫花苜蓿生长特征及光合特性对不同土壤水分的响应 DOI: 10.5846/stxb201301290188 作者: 作者单位: 北京师范大学,北京师范大学资源学院,北京师范大学资源学院,北京师范大学,北京师范大学资源学院 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金资助项目(40871031, 41025001); 长江学者和创新团队发展计划(IRT1108); 中央高校基本科研业务费专项 Effects of soil moisture content on morphological and photosynthetic characteristics of Leymus chinensis and Medicago sativa Author: Affiliation: Beijing Normal University,,,Beijing Normal University, 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:采用人工控制实验,对12%(T1)、16%(T2)和20%(T3)3种土壤水分条件下羊草和紫花苜蓿的净光合速率Pn、实际光化学量子效率ФPSⅡ、光化学淬灭qP、非光化学淬灭qN、水分利用效率WUE、株高、分枝分蘖数、生物量等参数进行测定.结果表明,在实验范围内,(1)ФPSⅡ 和qP共同影响净光合速率,羊草和紫花苜蓿净光合速率对土壤水分的响应不同,紫花苜蓿的土壤水分生态幅要比羊草窄,羊草生长的最适土壤含水量为20%,随着土壤含水量的降低,净光合速率呈单调递减趋势;紫花苜蓿的最适土壤含水量为16%,其净光合速率与土壤含水量之间呈非线性关系,存在明显阈值.(2)适宜土壤含水量有助于羊草和紫花苜蓿株高和分枝分蘖的生长.(3) 在土壤水分低于适宜土壤含水量范围时,羊草和紫花苜蓿有相似的响应机制,都通过增加根系生物量来适应环境胁迫. Abstract:Leymus chinensis and Medicago sativa are the two most significant perennial artificial grasses of the farming-pastoral ecotone of north China and are crucial for the development of animal husbandry in this area. In this region, water is an important ecological factor that limits plant ecophysiology and the growth of L. chinensis and M. sativa. To maximize the productivity of artificial grassland in this area, it is necessary to explore the mechanisms of the morphological and photosynthetic response characteristics of L. chinensis and M. sativa to water stress. Response characteristics, including the fluorescence characteristics, water use efficiency, biomass and biomass allocation to drought, are studied in this paper. This was done in order to propose the optimum soil moisture content for the growth of, and high economic benefits from, L. chinensis and M. sativa in the chestnut soil of the farming-pastoral ecotone of north China. Data on the morphological and photosynthetic characteristics of L. chinensis and M. sativa were collected from a controlled field experiment in the Taipusi Banner in Inner Mongolia. A water control experiment was applied from the 9th week to the 13th week of the field experiment to evaluate leaf net photosynthetic rate (Pn), actual photochemical efficiency of photosystem Ⅱ complex in the light (ФPSⅡ), photochemical quenching (qP), non-photochemical quenching (qN), water use efficiency (WUE), plant height, branch number and tiller number per plant, biomass and biomass allocation in modules of L. chinensis and M. sativa. The experiment consisted of three soil moisture gradients of 12%, 16% and 20%. The results indicated that, within the soil moisture range of the experiment: (1) the responses of Pn to soil moisture content of L. chinensis and M. sativa were different from each other, and the highest Pn depended on the highest ФPSⅡ and qP. The most suitable soil moisture content for the growth of L. chinensis was 20% and with a decrease in soil moisture content, the Pn of L. chinensis also decreased in a linear relationship; conversely, the optimum soil moisture content of M. sativa was 16%, and as soil moisture decreased, the Pn of M. sativa showed a non-linear relationship with an obvious threshold value. To some extent, the ecological amplitude of soil moisture of M. sativa was narrower than that of L. chinensis. (2) The appropriate soil moisture content for plant growth was attributed to plant height, branching and tillering. (3) The adaptive strategies of L. chinensis and M. sativa were similar, in that they adapt to environmental stress through increased root biomass when the soil moisture content was below the appropriate range. Pn, ФPSⅡ, qP, qN, WUE, morphological characteristics, biomass and biomass allocation in modules of L. chinensis and M. sativa would be changed with the changed soil moisture, which indicates that an optimum soil moisture content should be created for maximizing the growth of M. sativa and L. chinensis during production to obtain high economic benefits for the farming-pastoral ecotone of north China. 参考文献 相似文献 引证文献

Influence of Electrical Double Layer in the Electrical Model for Capacitance- based Soil Moisture Sensor on Measuring Soil Moisture

The reasonable electrical model for Capacitance-Based Soil Moisture Sensor (CBSMS), namely relationship between soil moisture and sensor output voltage, is the basic requirement of soil moisture measurements. In the present study, two CBSMS (PA-1 for the self-developed CBSMS and EC-5 for decagon company’s CBSMS) were employed to assess influence of electrical double layer in the electrical model for CBSMS on measuring soil moisture based on 15 soil samples with moisture ranging from 2.6~30%. Results showed that significant deviations of experimental results and estimated values were determined mainly in dependence on the electrical models (Model-1: with electrical double layer, Model-2: without electrical double layer), soil moisture range and sensor itself. Significant deviations were observed in the moisture range of 2.6~6%, 22~30% for EC-5 and of 2.6~10%, 22~30% for PA-1 with Model-2, whereas the deviations did not exist for both CBSMS in the moisture range of 2.6~10% with Model-1. For both CBSMS, in the moisture range of 22~30%, the deviation between estimated values from Model-1 with experimental results was obviously less than that from Model-2. These results suggest that the electrical double layer should be considered in the electrical model for CBSMS, especially for measuring low soil moisture.

Costs and Benefits of Implementing Sensor-controlled Irrigation in a Commercial Pot-in-Pot Container Nursery

Irrigation scheduling in ornamental plant production is complex due to the large number of species grown by individual growers and the need to consider plant, environment, and substrate conditions to make correct irrigation decisions on a daily or more frequent basis. The engineering team in our project has developed a smart wireless sensor node that is capable of integrating outputs from a range of soil moisture and environmental sensors to schedule irrigation events. In addition, an advanced monitoring and control software enables growers to manage irrigation based on set-point or model-based protocols, which are then independently executed by the nodes, enhancing or replacing human decision making. During 2012, we implemented a sensor-controlled vs. grower-controlled irrigation study at a pot-in-pot nursery in Tennessee. Sensor networks were installed in two separate production blocks of 3-year-old dogwood (Cornus florida ‘Cherokee Brave’) and 2-year-old red maple (Acer rubrum ‘Autumn Blaze’) trees grown in 15- and 30-gal containers, respectively. One row of trees in each block was irrigated based on the average reading of soil moisture sensors inserted in individual trees using micropulse irrigation, i.e., sensor controlled. Trees in the adjacent row and the rest of the block were independently irrigated by the grower using standard practices, i.e., grower controlled. Sensor volumetric water content (VWC) readings and irrigation volumes were logged by nodes on a 15-min basis and were relayed to a base station on the farm. For the study period between Mar. 2012 and Nov. 2012, average daily water applied by the grower-controlled irrigation to the dogwood block was 0.92 gal/tree, compared with 0.34 gal/tree applied using sensor-controlled irrigation; for red maple, these values were 1.72 gal/tree and 1.13 gal/tree, respectively. No significant differences in tree caliper or quality were noted between the two irrigation treatments in either species over the year. The cost of water for this particular operation was negligible consisting only of pumping costs, as water is drawn from a perennial stream with excellent water quality. Consequently, a conservative return on investment for a wireless sensor network capable of covering the entire operation was 37.5%, corresponding to a payback period of 2.7 years, associated almost entirely from a reduction in irrigation management time. Pricing in a nominal cost for water of $326 per acre-foot ($1 per 1000 gal) increased annualized net savings 9-fold, reducing the payback period to less than 4 months. This analysis did not factor in additional economic benefits such as reductions in production time, losses due to disease, or increased plant quality, which have been associated with the use of sensor-based irrigation control in other studies.

Factors Affecting Nutrient Availability, Placement, Rate, and Application Timing of Controlled-release Fertilizers for Florida Vegetable Production Using Seepage Irrigation

This publication summarizes the factors influencing controlled-release fertilizer (CRF) nutrient release, CRF placement, CRF rate, and CRF application timing for the two major seepage-irrigated vegetable production systems (plasticulture and open-bed) in Florida. One of several best management practices for vegetable production, CRF helps growers achieve total maximum daily loads (TMDLs) established in Florida under the Federal Clean Water Act. Several factors intrinsic to CRF and to the vegetable production systems affect CRF nutrient release, making implementation of CRF fertility programs challenging. Increasing or decreasing soil temperature increases or decreases nutrient release from CRF. Soil moisture required for uninhibited plant growth is within the soil moisture range for optimum CRF nutrient release. CRF substrate affects nutrient release rate, which is inversely related to coating thickness and granule size. Soil microbes, soil texture, and soil pH do not influence nutrient release rate. Field placement of CRFs in seepage-irrigated, plasticulture, and open-bed production should be in the bottom mix at bed formation and soil incorporated or banded at planting, respectively. In plasticulture production systems, soil fumigation and delayed planting for continuous harvest may add a 14- to 21-day lag period between fertilization and planting, which along with different season lengths will influence CRF release length selected by growers. Using a hybrid fertilizer system in plasticulture production or incorporating CRF at planting in open-bed production allows for up to a 25% reduction in the nitrogen (N) rate needed.

Impacts of a new bare‐soil evaporation formulation on site, regional, and global surface energy and water budgets in CLM4

We describe the implementation of a new bare‐soil evaporation formulation in the Community Land Model‐version 4 (CLM4). This new formulation comprises two components: (1) a full‐range (desiccated to fully saturated) soil water retention curve (SWRC) parameterization that extends the classical Clapp‐Hornberger parameterization and (2) a mechanistically based formulation of soil resistance that considers the effects of water vapor diffusion and liquid mass flow. Predictions by the new SWRC parameterization matched measured soil matric pressure data across a wide soil moisture range for six very different soils. We assessed the revised bare‐soil evaporation formulation with two types of global simulations, one with prescribed satellite plant phenology and the other with bare‐soil conditions. Compared with the default CLM4 soil evaporation formulation, the revised model leads to (1) slightly lower (−0.2 ∼ 0 mm d−1 averaged annually) bare‐soil evaporation in moderately wet regions; (2) slightly higher (0 ∼ 0.2 mm d−1 averaged annually) bare‐soil evaporation in semiarid regions; (3) small changes in global surface energy and water balances across all temporal scales for both vegetated and nonvegetated simulations; and (4) a small reduction (−0.2 ∼ 0 mm d−1 averaged annually) in the current overestimation of evapotranspiration in densely vegetated regions such as the Amazon basin. However, contrary to expectation and consistent with the default CLM4, the simulated bare‐soil evapotranspiration remains higher than that of the vegetated soil in the same grid cells. We conclude that further studies are needed to identify the processes that lead to the overestimation of bare‐soil evaporation in CLM4.

Spatial and temporal variability of soil electrical conductivity related to soil moisture

Soil electrical conductivity (ECa) is a soil quality indicator associated to attributes interesting to site-specific soil management such as soil moisture and texture. Soil ECa provides information that helps guide soil management decisions, so we performed spatial evaluation of soil moisture in two experimental fields in two consecutive years and modeled its influence on soil ECa. Soil ECa, moisture and clay content were evaluated by statistical, geostatistical and regression analyses. Semivariogram models, adjusted for soil moisture, had strong spatial dependence, but the relationship between soil moisture and soil ECa was obtained only in one of the experimental fields, where soil moisture and clay content range was higher. In this same field, coefficients of determinations between soil moisture and clay content were above 0.70. In the second field, the low soil moisture and clay content range explain the absence of a relationship between soil ECa and soil moisture. Data repetition over the years, suggested that ECa is a qualitative indicator in areas with high spatial variability in soil texture.

Temperature Dependence of Thermal Properties of Sands across a Wide Range of Temperatures (30–70°C)

Due to the dynamic nature of the shallow subsurface, knowledge of soil thermal properties across a wide range of soil moisture and temperature conditions is necessary to accurately describe heat transport in many settings. Soil thermal properties are difficult to measure at high temperatures, however, due to the lack of suitable measurement devices and the potential for measurement‐induced changes. Therefore, thermal property data are often scarce and incomplete and very often limited to specific soils. Due to this scarcity of accurate experimental data, empirical relationships often do not accurately predict the thermal properties of soils as a function of both soil moisture and temperature. In this study, thermal conductivity and diffusivity were measured for silica sands under loose and tight packing conditions and a field sand under varied water saturation and temperature. Several recent sensor‐based technologies were integrated into a small cell modified to have a network of sampling ports, continuously monitoring water saturation, temperature, and soil thermal properties. For the test sands studied, data showed that the thermal conductivity and diffusivity increased noticeably for sample temperatures >50°C. At sample temperatures between 30 and 50°C, any change in thermal properties with temperature was small. Thermal conductivities measured in this study were compared with independent estimates made using empirical models from the literature. In general, good agreement was observed for most thermal conductivity data when proper fitting parameters were established, except at intermediate saturation values.

Emission and distribution of fumigants as affected by soil moistures in three different textured soils

Water application is a low-cost strategy to control emissions of soil fumigant to meet the requirements of the stringent environmental regulations and it is applicable for a wide range of commodity groups. Although it is known that an increase in soil moisture reduces emissions, the range of soil moisture for minimizing emissions without risking pest control, is not well defined for various types of soils. With two column studies, we determined the effect of different soil moisture levels on emission and distribution of 1,3-dichloropropene and chloropicrin in three different textured soils. Results on sandy loam and loam soils showed that by increasing soil moisture from 30% to 100% of field capacity (FC), peak fluxes were lowered by 77–88% and their occurrences were delayed 5–15h, and cumulative emissions were reduced 24–49%. For the sandy soil, neither peak fluxes nor the cumulative emissions were significantly different when soil moisture increased from 30% to 100% FC. Compared to the drier soils, the wetter soils retained consistently higher fumigant concentrations in the gas-phase, suggesting efficacy may not be impacted in these soils. The air-filled porosity positively and linearly correlated with the cumulative emission loss across all soil types indicating that it may serve as a good indicator for estimating emissions. These laboratory findings can be further tested under field conditions to conclude what irrigation regime should be used for increasing soil water content before fumigant application that can achieve maximum emission reduction and uniform fumigant distribution with high exposure index values.

Determination of Soil Pore Water Salinity Using an FDR Sensor Working at Various Frequencies up to 500 MHz

This paper presents the application of a frequency-domain reflectometry (FDR) sensor designed for soil salinity assessment of sandy mineral soils in a wide range of soil moisture and bulk electrical conductivity, through the determination of soil complex dielectric permittivity spectra in the frequency range 10–500 MHz. The real part of dielectric permittivity was assessed from the 380–440 MHz, while the bulk electrical conductivity was calculated from the 165–325 MHz range. The FDR technique allows determination of bulk electrical conductivity from the imaginary part of the complex dielectric permittivity, without disregarding the dielectric losses. The soil salinity status was determined using the salinity index, defined as a partial derivative of the soil bulk electrical conductivity with respect to the real part of the soil complex dielectric permittivity. The salinity index method enables determining the soil water electrical conductivity value. For the five sandy mineral soils that have been tested, the relationship between bulk electrical conductivity and the real part of dielectric permittivity is essentially linear. As a result, the salinity index method applied for FDR measurements may be adapted to field use after examination of loam and clayey soils.

Estimation of soil parameters over bare agriculture areas from C-band polarimetric SAR data using neural networks

Abstract. The purpose of this study was to develop an approach to estimate soil surface parameters from C-band polarimetric SAR data in the case of bare agricultural soils. An inversion technique based on multi-layer perceptron (MLP) neural networks was introduced. The neural networks were trained and validated on a noisy simulated dataset generated from the Integral Equation Model (IEM) on a wide range of surface roughness and soil moisture, as it is encountered in agricultural contexts for bare soils. The performances of neural networks in retrieving soil moisture and surface roughness were tested for several inversion cases using or not using a-priori knowledge on soil parameters. The inversion approach was then validated using RADARSAT-2 images in polarimetric mode. The introduction of expert knowledge on the soil moisture (dry to wet soils or very wet soils) improves the soil moisture estimates, whereas the precision on the surface roughness estimation remains unchanged. Moreover, the use of polarimetric parameters α1 and anisotropy were used to improve the soil parameters estimates. These parameters provide to neural networks the probable ranges of soil moisture (lower or higher than 0.30 cm3 cm−3) and surface roughness (root mean square surface height lower or higher than 1.0 cm). Soil moisture can be retrieved correctly from C-band SAR data by using the neural networks technique. Soil moisture errors were estimated at about 0.098 cm3 cm−3 without a-priori information on soil parameters and 0.065 cm3 cm−3 (RMSE) applying a-priori information on the soil moisture. The retrieval of surface roughness is possible only for low and medium values (lower than 2 cm). Results show that the precision on the soil roughness estimates was about 0.7 cm. For surface roughness lower than 2 cm, the precision on the soil roughness is better with an RMSE about 0.5 cm. The use of polarimetric parameters improves only slightly the soil parameters estimates.

Effect of Soil Temperature and Moisture on Survival of Eggs and First-Instar Larvae of Delia radicum

Edaphic factors such as soil temperature and moisture influence soil-dwelling insects, whose most vulnerable stages typically are eggs and young larvae. In this study, the survival of eggs and first-instar larvae of the cabbage maggot, Delia radicum L., was measured under laboratory conditions after exposure to a range of soil temperatures and moistures. When eggs were exposed to constant temperature (20-29°C) and humidity (5-200% [wt:wt]), temperature had no significant effect on survival, whereas humidity <25% [wt:wt] caused egg mortality. The gradual exposure of eggs to high temperatures resulted in low mortality below 33°C, but <5% of eggs survived at 40°C. When first-instar larvae were exposed to constant temperature (17-29°C) and humidity (5-100% [wt:wt]), both factors as well as their interaction had a significant effect on larval survival, which was nil at 5% (wt:wt) for all temperatures but increased from 21.9 to 42.8% at 17°C and from 34.1 to 55.0% at 29°C, for soil moisture contents of 15% and 100% (wt:wt), respectively. Eggs of D. radicum are resistant to low soil moisture and high temperature conditions. Larval survival tends to increase with an increase in soil temperature and moisture. It is suggested that soil temperature be integrated into insect development simulation models instead of air temperature, to build more effective models for cabbage maggot management.

A Model Analysis Using a Combined Active/Passive Microwave Remote Sensing Approach for Soil Moisture Retrieval

This study develops a new algorithm for estimating bare surface soil moisture using combined active/passive microwave remote sensing on the basis of TRMM(Tropical Rainfall Measuring Mission).To accurately estimate bare surface soil moisture,the algorithm simultaneously uses a precipitation radar(PR) and microwave imager(TMI) for observation.In this paper,through an analysis of the numerically simulated surface backscattering and emissivity database by Advanced Integral Equation Model(AIEM) with a wide range of soil moisture and surface roughness conditions,the authors have found that the surface roughness parameter has an important impact on both backscattering coefficient and emissivity.Based on the simulated database by AIEM,the authors use theoretical model(Geometrical Optical Model) and semi-empirical model(Qp Model) through the analysis of surface roughness as well as TRMM/PR and TMI data to develop the algorithm for estimating bare surface soil moisture.

Impact of soil hydraulic parameter uncertainty on soil moisture modeling

For simulations in basins where soil information is limited to soil type maps, a methodology is presented to quantify the uncertainty of soil hydraulic parameters arising from within‐soil‐class variability and to assess the impact of this uncertainty on soil moisture modeling. Continuous pedotransfer functions were applied to samples with different texture within each soil class to construct discrete probability distributions of the soil hydraulic parameters. When propagating the parameter distributions through a hydrologic model, a wide range of simulated soil moisture was generated within a single soil class. The pedotransfer function was found to play a crucial role in assessing the uncertainty in the modeled soil moisture, and the geographic origin of the pedotransfer function (region specific versus nonregion specific) highly affected the range and shape of the probability distribution of the soil hydraulic parameters. Furthermore, the modeled soil moisture distribution was found to be non‐Gaussian. An accurate uncertainty assessment therefore requires the characterization of its higher‐order moments. As an extension of this research, we have shown that applying continuous region‐specific pedotransfer functions to the central point of a soil class is a better alternative to standard (often nonregion‐specific) class pedotransfer functions for determining an average set of soil hydraulic parameters.

Soil properties related to potential particulate matter emissions (PM10) of sandy soils

Little information is available on the effect of properties of coarse textured soils on the emission of fine particulate matter (PM10). In this study was evaluated the effect of textural fractions (clay, silt and sand), organic matter contents (OM) and soil moisture of 7 sandy to loamy-sand soils on potential PM10 emissions by means of wind tunnel simulations. PM10 emissions decreases linearly along the whole soil moisture range in loess developed soils (Anguil and Santa Rosa), and above a given soil moisture in soils developed on sandy sediments (Villa Mercedes, Abra Pampa, Potrok Aike, Rio Mayo and Pilcaniyeu). Soils with higher PM10 emissions had high threshold moisture contents (TMC, soil moisture above which the PM10 emission was negligible) excepting for Potrok Aike (PA) that had low PM10 emissions and high TMC (8%) as a consequence of its relative high OM contents. Moisture effects on PM10 emissions decreased in a logarithmic way when OM contents increased in relation to soil silt contents (P < 0.01). In general, maximum PM10 emissions were higher in soils with higher silt contents, excepting PA which

Divergent Egg Physiologies in Two Closely Related Grasshopper Species:Taeniopoda equesversus Romalea microptera (Orthoptera: Romaleidae)

We compared egg survivorship and egg development time at different soil moistures for two closely related grasshopper species from divergent habitats: marsh-inhabiting Romalea microptera (Beauvois) versus desert-inhabiting Taeniopoda eques (Burmeister). These two species can interbreed and produce viable offspring. In nature, both species have a similar 8-9 mo subterranean egg stage, but their soil environments differ dramatically in water content. We predicted that the eggs of the two species would exhibit differential survivorship and development times under different moisture levels. Our laboratory results show that the eggs of both species survived a wide range of soil moistures (≈ 0.5 to 90%), maintained for 3 mo. However, the eggs of the marsh grasshopper, R. microptera, better tolerated the highest soil moistures (95 and 100%), whereas the eggs of the desert species, T. eques, better tolerated the lowest soil moistures (0.0 and 0.1%). Sixty-five percent of marsh-inhabiting R. microptera eggs, but no desert T. eques eggs, survived 3 mo submersion under water. In contrast, 49% of desert T. eques eggs, but only 3.5% of R. microptera eggs, survived after being laid into oven-dried sand and then maintained with no additional water until hatch. In the laboratory at 26 °C, the two species differed significantly in the mean length of the oviposition-to-hatch interval: 176 d for R. microptera versus 237 d for T. eques. These divergent traits presumably benefit these insects in their divergent habitats. Our results suggest the evolution of physiological divergence that is consistent with adaptations to local environments.

Agricultural PM10 emissions from cotton field disking in Las Cruces, NM

Various studies have shown a relationship between elevated levels of inhalable particulate matter (PM) and agricultural practices, especially in the vicinity of agricultural fields. Airborne particle concentrations and meteorological variables were measured during nine agricultural field events on a cotton field in Las Cruces, NM in March 2008. A variety of real-time and integrated PM10 and total suspended particles (TSP) samplers were used during sampling. The field events were designed to measure particle concentrations at different heights, near (4 m) and far (20–100 m) from a disking tractor. Particle concentrations decreased with increasing distance from the ground for near-source disking events, whereas particle concentrations were almost independent of height for background events. Near-source disking event particle concentrations were 4–7 times higher than those for far-source disking and background events. Near-source disking events had PM10 emission factors ranging from 78 to 239 mg m−2, while those for far-source disking events ranged from 8 to 89 mg m−2. PM10 plume heights for near-source disking events were between 4 and 5.7 m, whereas those for far-source disking events were between 12 and 15 m. Meteorological variables were found to influence emission factors, with wind speed showing a nonlinear relationship with emission factors. No clear relationship was found between soil moisture content and emission factors probably because the range of soil moisture was small. Impactor data indicated 10–40% of the total mass of agricultural PM collected was less than 1 μm in diameter for the clay loam soil type. Vertical PM10 concentration profiles showed maxima at sampling heights between 1 and 2 m above the ground.