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Sample records for affect soil moisture

  1. Sensitivity of Polygonum aviculare Seeds to Light as Affected by Soil Moisture Conditions

    PubMed Central

    Batlla, Diego; Nicoletta, Marcelo; Benech-Arnold, Roberto

    2007-01-01

    Background and Aims It has been hypothesized that soil moisture conditions could affect the dormancy status of buried weed seeds, and, consequently, their sensitivity to light stimuli. In this study, an investigation is made of the effect of different soil moisture conditions during cold-induced dormancy loss on changes in the sensitivity of Polygonum aviculare seeds to light. Methods Seeds buried in pots were stored under different constant and fluctuating soil moisture environments at dormancy-releasing temperatures. Seeds were exhumed at regular intervals during storage and were exposed to different light treatments. Changes in the germination response of seeds to light treatments during storage under the different moisture environments were compared in order to determine the effect of soil moisture on the sensitivity to light of P. aviculare seeds. Key Results Seed acquisition of low-fluence responses during dormancy release was not affected by either soil moisture fluctuations or different constant soil moisture contents. On the contrary, different soil moisture environments affected seed acquisition of very low fluence responses and the capacity of seeds to germinate in the dark. Conclusions The results indicate that under field conditions, the sensitivity to light of buried weed seeds could be affected by the soil moisture environment experienced during the dormancy release season, and this could affect their emergence pattern. PMID:17430979

  2. Soil Tillage Management Affects Maize Grain Yield by Regulating Spatial Distribution Coordination of Roots, Soil Moisture and Nitrogen Status

    PubMed Central

    Wang, Xinbing; Zhou, Baoyuan; Sun, Xuefang; Yue, Yang; Ma, Wei; Zhao, Ming

    2015-01-01

    The spatial distribution of the root system through the soil profile has an impact on moisture and nutrient uptake by plants, affecting growth and productivity. The spatial distribution of the roots, soil moisture, and fertility are affected by tillage practices. The combination of high soil density and the presence of a soil plow pan typically impede the growth of maize (Zea mays L.).We investigated the spatial distribution coordination of the root system, soil moisture, and N status in response to different soil tillage treatments (NT: no-tillage, RT: rotary-tillage, SS: subsoiling) and the subsequent impact on maize yield, and identify yield-increasing mechanisms and optimal soil tillage management practices. Field experiments were conducted on the Huang-Huai-Hai plain in China during 2011 and 2012. The SS and RT treatments significantly reduced soil bulk density in the top 0–20 cm layer of the soil profile, while SS significantly decreased soil bulk density in the 20–30 cm layer. Soil moisture in the 20–50 cm profile layer was significantly higher for the SS treatment compared to the RT and NT treatment. In the 0-20 cm topsoil layer, the NT treatment had higher soil moisture than the SS and RT treatments. Root length density of the SS treatment was significantly greater than density of the RT and NT treatments, as soil depth increased. Soil moisture was reduced in the soil profile where root concentration was high. SS had greater soil moisture depletion and a more concentration root system than RT and NT in deep soil. Our results suggest that the SS treatment improved the spatial distribution of root density, soil moisture and N states, thereby promoting the absorption of soil moisture and reducing N leaching via the root system in the 20–50 cm layer of the profile. Within the context of the SS treatment, a root architecture densely distributed deep into the soil profile, played a pivotal role in plants’ ability to access nutrients and water. An

  3. Soil Tillage Management Affects Maize Grain Yield by Regulating Spatial Distribution Coordination of Roots, Soil Moisture and Nitrogen Status.

    PubMed

    Wang, Xinbing; Zhou, Baoyuan; Sun, Xuefang; Yue, Yang; Ma, Wei; Zhao, Ming

    2015-01-01

    The spatial distribution of the root system through the soil profile has an impact on moisture and nutrient uptake by plants, affecting growth and productivity. The spatial distribution of the roots, soil moisture, and fertility are affected by tillage practices. The combination of high soil density and the presence of a soil plow pan typically impede the growth of maize (Zea mays L.).We investigated the spatial distribution coordination of the root system, soil moisture, and N status in response to different soil tillage treatments (NT: no-tillage, RT: rotary-tillage, SS: subsoiling) and the subsequent impact on maize yield, and identify yield-increasing mechanisms and optimal soil tillage management practices. Field experiments were conducted on the Huang-Huai-Hai plain in China during 2011 and 2012. The SS and RT treatments significantly reduced soil bulk density in the top 0-20 cm layer of the soil profile, while SS significantly decreased soil bulk density in the 20-30 cm layer. Soil moisture in the 20-50 cm profile layer was significantly higher for the SS treatment compared to the RT and NT treatment. In the 0-20 cm topsoil layer, the NT treatment had higher soil moisture than the SS and RT treatments. Root length density of the SS treatment was significantly greater than density of the RT and NT treatments, as soil depth increased. Soil moisture was reduced in the soil profile where root concentration was high. SS had greater soil moisture depletion and a more concentration root system than RT and NT in deep soil. Our results suggest that the SS treatment improved the spatial distribution of root density, soil moisture and N states, thereby promoting the absorption of soil moisture and reducing N leaching via the root system in the 20-50 cm layer of the profile. Within the context of the SS treatment, a root architecture densely distributed deep into the soil profile, played a pivotal role in plants' ability to access nutrients and water. An optimal

  4. Harvest residue and competing vegetation affect soil moisture, soil temperature, N availability, and Douglas-fir seedling growth.

    Treesearch

    Scott D. Roberts; Constance A. Harrington; Thomas A. Terry

    2005-01-01

    Decisions made during stand regeneration that affect subsequent levels of competing vegetation and residual biomass can have important short-term consequences for early stand growth, and may affect long-term site productivity. Competing vegetation clearly affects the availability of site resources such as soil moisture and nutrients. Harvest residues can also impact...

  5. Soil moisture

    Treesearch

    L. L. Boersma; D. Kirkham; D. Norum; R. Ziemer; J. C. Guitjens; J. Davidson; J. N. Luthin

    1971-01-01

    Infiltration continues to occupy the attention of soil physicists and engineers. A theoretical and experimental analysis of the effect of surface sealing on infiltration by Edwards and Larson [1969] showed that raindrops reduced the infiltration rate by as much as 50% for a two-hour period of infiltration. The effect of raindrops on the surface infiltration rate of...

  6. Understanding Soil Moisture

    USDA-ARS?s Scientific Manuscript database

    Understanding soil moisture is critical for landscape irrigation management. This landscaep irrigation seminar will compare volumetric and matric potential soil-moisture sensors, discuss the relationship between their readings and demonstrate how to use these data. Soil water sensors attempt to sens...

  7. Soil moisture modeling review

    NASA Technical Reports Server (NTRS)

    Hildreth, W. W.

    1978-01-01

    A determination of the state of the art in soil moisture transport modeling based on physical or physiological principles was made. It was found that soil moisture models based on physical principles have been under development for more than 10 years. However, these models were shown to represent infiltration and redistribution of soil moisture quite well. Evapotranspiration has not been as adequately incorporated into the models.

  8. Soil Moisture Workshop

    NASA Technical Reports Server (NTRS)

    Heilman, J. L. (Editor); Moore, D. G. (Editor); Schmugge, T. J. (Editor); Friedman, D. B. (Editor)

    1978-01-01

    The Soil Moisture Workshop was held at the United States Department of Agriculture National Agricultural Library in Beltsville, Maryland on January 17-19, 1978. The objectives of the Workshop were to evaluate the state of the art of remote sensing of soil moisture; examine the needs of potential users; and make recommendations concerning the future of soil moisture research and development. To accomplish these objectives, small working groups were organized in advance of the Workshop to prepare position papers. These papers served as the basis for this report.

  9. Soil Moisture Sensing

    USDA-ARS?s Scientific Manuscript database

    Soil moisture monitoring can be useful as an irrigation management tool for both landscapes and agriculture, sometimes replacing an evapotranspiration (ET) based approach or as a useful check on ET based approaches since the latter tend to drift off target over time. All moisture sensors, also known...

  10. Factors affecting temporal and spatial soil moisture variation in and adjacent to group selection openings

    Treesearch

    W.H. McNab

    1991-01-01

    Soil moisture content was intensively sampled in three, 1-acre blocks containing an opening and surrounding mature upland hardwoods. Openings covering 0.19-0.26 ac were created by group-selection cutting, and they were occupied by 1-year-old trees and shrubs.

  11. Soil moisture and fungi affect seed survival in California grassland annual plants.

    PubMed

    Mordecai, Erin A

    2012-01-01

    Survival of seeds in the seed bank is important for the population dynamics of many plant species, yet the environmental factors that control seed survival at a landscape level remain poorly understood. These factors may include soil moisture, vegetation cover, soil type, and soil pathogens. Because many soil fungi respond to moisture and host species, fungi may mediate environmental drivers of seed survival. Here, I measure patterns of seed survival in California annual grassland plants across 15 species in three experiments. First, I surveyed seed survival for eight species at 18 grasslands and coastal sage scrub sites ranging across coastal and inland Santa Barbara County, California. Species differed in seed survival, and soil moisture and geographic location had the strongest influence on survival. Grasslands had higher survival than coastal sage scrub sites for some species. Second, I used a fungicide addition and exotic grass thatch removal experiment in the field to tease apart the relative impact of fungi, thatch, and their interaction in an invaded grassland. Seed survival was lower in the winter (wet season) than in the summer (dry season), but fungicide improved winter survival. Seed survival varied between species but did not depend on thatch. Third, I manipulated water and fungicide in the laboratory to directly examine the relationship between water, fungi, and survival. Seed survival declined from dry to single watered to continuously watered treatments. Fungicide slightly improved seed survival when seeds were watered once but not continually. Together, these experiments demonstrate an important role of soil moisture, potentially mediated by fungal pathogens, in driving seed survival.

  12. Soil moisture variations affect short-term plant-microbial competition for ammonium, glycine, and glutamate

    PubMed Central

    Månsson, Katarina F; Olsson, Magnus O; Falkengren-Grerup, Ursula; Bengtsson, Göran

    2014-01-01

    We tested whether the presence of plant roots would impair the uptake of ammonium (), glycine, and glutamate by microorganisms in a deciduous forest soil exposed to constant or variable moisture in a short-term (24-h) experiment. The uptake of 15NH4 and dual labeled amino acids by the grass Festuca gigantea L. and soil microorganisms was determined in planted and unplanted soils maintained at 60% WHC (water holding capacity) or subject to drying and rewetting. The experiment used a design by which competition was tested in soils that were primed by plant roots to the same extent in the planted and unplanted treatments. Festuca gigantea had no effect on microbial N uptake in the constant moist soil, but its presence doubled the microbial uptake in the dried and rewetted soil compared with the constant moist. The drying and rewetting reduced by half or more the uptake by F. gigantea, despite more than 60% increase in the soil concentration of . At the same time, the amino acid and -N became equally valued in the plant uptake, suggesting that plants used amino acids to compensate for the lower acquisition. Our results demonstrate the flexibility in plant-microbial use of different N sources in response to soil moisture fluctuations and emphasize the importance of including transient soil conditions in experiments on resource competition between plants and soil microorganisms. Competition between plants and microorganisms for N is demonstrated by a combination of removal of one of the potential competitors, the plant, and subsequent observations of the uptake of N in the organisms in soils that differ only in the physical presence and absence of the plant during a short assay. Those conditions are necessary to unequivocally test for competition. PMID:24772283

  13. Soil moisture variations affect short-term plant-microbial competition for ammonium, glycine, and glutamate.

    PubMed

    Månsson, Katarina F; Olsson, Magnus O; Falkengren-Grerup, Ursula; Bengtsson, Göran

    2014-04-01

    We tested whether the presence of plant roots would impair the uptake of ammonium ([Formula: see text]), glycine, and glutamate by microorganisms in a deciduous forest soil exposed to constant or variable moisture in a short-term (24-h) experiment. The uptake of (15)NH4 and dual labeled amino acids by the grass Festuca gigantea L. and soil microorganisms was determined in planted and unplanted soils maintained at 60% WHC (water holding capacity) or subject to drying and rewetting. The experiment used a design by which competition was tested in soils that were primed by plant roots to the same extent in the planted and unplanted treatments. Festuca gigantea had no effect on microbial N uptake in the constant moist soil, but its presence doubled the microbial [Formula: see text] uptake in the dried and rewetted soil compared with the constant moist. The drying and rewetting reduced by half or more the [Formula: see text] uptake by F. gigantea, despite more than 60% increase in the soil concentration of [Formula: see text]. At the same time, the amino acid and [Formula: see text]-N became equally valued in the plant uptake, suggesting that plants used amino acids to compensate for the lower [Formula: see text] acquisition. Our results demonstrate the flexibility in plant-microbial use of different N sources in response to soil moisture fluctuations and emphasize the importance of including transient soil conditions in experiments on resource competition between plants and soil microorganisms. Competition between plants and microorganisms for N is demonstrated by a combination of removal of one of the potential competitors, the plant, and subsequent observations of the uptake of N in the organisms in soils that differ only in the physical presence and absence of the plant during a short assay. Those conditions are necessary to unequivocally test for competition.

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

    USDA-ARS?s Scientific Manuscript database

    Stringent environmental regulations are being developed to control the emission of soil fumigants to reduce air pollution. Water application is a low-cost strategy for fumigant emission control and applicable for a wide range of commodity groups, especially those with low profit margins. Although it...

  15. The soil carbon/nitrogen ratio and moisture affect microbial community structures in alkaline permafrost-affected soils with different vegetation types on the Tibetan plateau.

    PubMed

    Zhang, Xinfang; Xu, Shijian; Li, Changming; Zhao, Lin; Feng, Huyuan; Yue, Guangyang; Ren, Zhengwei; Cheng, Guogdong

    2014-01-01

    In the Tibetan permafrost region, vegetation types and soil properties have been affected by permafrost degradation, but little is known about the corresponding patterns of their soil microbial communities. Thus, we analyzed the effects of vegetation types and their covariant soil properties on bacterial and fungal community structure and membership and bacterial community-level physiological patterns. Pyrosequencing and Biolog EcoPlates were used to analyze 19 permafrost-affected soil samples from four principal vegetation types: swamp meadow (SM), meadow (M), steppe (S) and desert steppe (DS). Proteobacteria, Acidobacteria, Bacteroidetes and Actinobacteria dominated bacterial communities and the main fungal phyla were Ascomycota, Basidiomycota and Mucoromycotina. The ratios of Proteobacteria/Acidobacteria decreased in the order: SM>M>S>DS, whereas the Ascomycota/Basidiomycota ratios increased. The distributions of carbon and nitrogen cycling bacterial genera detected were related to soil properties. The bacterial communities in SM/M soils degraded amines/amino acids very rapidly, while polymers were degraded rapidly by S/DS communities. UniFrac analysis of bacterial communities detected differences among vegetation types. The fungal UniFrac community patterns of SM differed from the others. Redundancy analysis showed that the carbon/nitrogen ratio had the main effect on bacteria community structures and their diversity in alkaline soil, whereas soil moisture was mainly responsible for structuring fungal communities. Thus, microbial communities and their functioning are probably affected by soil environmental change in response to permafrost degradation. Copyright © 2014 Institut Pasteur. Published by Elsevier Masson SAS. All rights reserved.

  16. Soil Moisture or Groundwater?

    NASA Astrophysics Data System (ADS)

    Swenson, S. C.; Lawrence, D. M.

    2017-12-01

    Partitioning the vertically integrated water storage variations estimated from GRACE satellite data into the components of which it is comprised requires independent information. Land surface models, which simulate the transfer and storage of moisture and energy at the land surface, are often used to estimate water storage variability of snow, surface water, and soil moisture. To obtain an estimate of changes in groundwater, the estimates of these storage components are removed from GRACE data. Biases in the modeled water storage components are therefore present in the residual groundwater estimate. In this study, we examine how soil moisture variability, estimated using the Community Land Model (CLM), depends on the vertical structure of the model. We then explore the implications of this uncertainty in the context of estimating groundwater variations using GRACE data.

  17. Soil Moisture Project Evaluation Workshop

    NASA Technical Reports Server (NTRS)

    Gilbert, R. H. (Editor)

    1980-01-01

    Approaches planned or being developed for measuring and modeling soil moisture parameters are discussed. Topics cover analysis of spatial variability of soil moisture as a function of terrain; the value of soil moisture information in developing stream flow data; energy/scene interactions; applications of satellite data; verifying soil water budget models; soil water profile/soil temperature profile models; soil moisture sensitivity analysis; combinations of the thermal model and microwave; determing planetary roughness and field roughness; how crust or a soil layer effects microwave return; truck radar; and truck/aircraft radar comparison.

  18. Southern U.S. Soil Moisture Map

    NASA Image and Video Library

    2015-05-19

    Southern U.S. NASA's SMAP soil moisture retrievals from April 27, 2015, when severe storms were affecting Texas. Top: radiometer data alone. Bottom: combined radar and radiometer data with a resolution of 5.6 miles (9 kilometers). The combined product reveals more detailed surface soil moisture features. http://photojournal.jpl.nasa.gov/catalog/PIA19338

  19. Evaluation of soil moisture barrier.

    DOT National Transportation Integrated Search

    2000-06-01

    This report is an extension report and examines one of the measures being tried to stabilize the development : of pavement damage on expansive soils, which is the use of horizontal moisture barriers. The moisture barrier : will not stop horizontal fl...

  20. SOIL moisture data intercomparison

    NASA Astrophysics Data System (ADS)

    Kerr, Yann; Rodriguez-Frenandez, Nemesio; Al-Yaari, Amen; Parens, Marie; Molero, Beatriz; Mahmoodi, Ali; Mialon, Arnaud; Richaume, Philippe; Bindlish, Rajat; Mecklenburg, Susanne; Wigneron, Jean-Pierre

    2016-04-01

    The Soil Moisture and Ocean Salinity satellite (SMOS) was launched in November 2009 and started delivering data in January 2010. Subsequently, the satellite has been in operation for over 6 years while the retrieval algorithms from Level 1 to Level 2 underwent significant evolutions as knowledge improved. Other approaches for retrieval at Level 2 over land were also investigated while Level 3 and 4 were initiated. In this présentation these improvements are assessed by inter-comparisons of the current Level 2 (V620) against the previous version (V551) and new products either using neural networks or Level 3. In addition a global evaluation of different SMOS soil moisture (SM) products is performed comparing products with those of model simulations and other satellites (AMSR E/ AMSR2 and ASCAT). Finally, all products were evaluated against in situ measurements of soil moisture (SM). The study demonstrated that the V620 shows a significant improvement (including those at level1 improving level2)) with respect to the earlier version V551. Results also show that neural network based approaches can yield excellent results over areas where other products are poor. Finally, global comparison indicates that SMOS behaves very well when compared to other sensors/approaches and gives consistent results over all surfaces from very dry (African Sahel, Arizona), to wet (tropical rain forests). RFI (Radio Frequency Interference) is still an issue even though detection has been greatly improved while RFI sources in several areas of the world are significantly reduced. When compared to other satellite products, the analysis shows that SMOS achieves its expected goals and is globally consistent over different eco climate regions from low to high latitudes and throughout the seasons.

  1. Soil moisture: Some fundamentals. [agriculture - soil mechanics

    NASA Technical Reports Server (NTRS)

    Milstead, B. W.

    1975-01-01

    A brief tutorial on soil moisture, as it applies to agriculture, is presented. Information was taken from books and papers considered freshman college level material, and is an attempt to briefly present the basic concept of soil moisture and a minimal understanding of how water interacts with soil.

  2. Zeolite Soil Application Method Affects Inorganic Nitrogen, Moisture, and Corn Growth

    USDA-ARS?s Scientific Manuscript database

    Adoption of new management techniques which improve soil water storage and soil nitrogen plant availability yet limit nitrogen leaching may help improve environmental quality. A benchtop study was conducted to determine the influence of a single urea fertilizer rate (224 kilograms of Nitrogen per ...

  3. Microwave Remote Sensing of Soil Moisture

    NASA Technical Reports Server (NTRS)

    Schmugge, T. J.

    1985-01-01

    Because of the large contrast between the dielectric constant of liquid water and that of dry soil at microwave wavelength, there is a strong dependence of the thermal emission and radar backscatter from the soil on its moisture content. This dependence provides a means for the remote sensing of the moisture content in a surface layer approximately 5 cm thick. The feasibility of these techniques is demonstrated from field, aircraft and spacecraft platforms. The soil texture, surface roughness, and vegetative cover affect the sensitivity of the microwave response to moisture variations with vegetation being the most important. It serves as an attenuating layer which can totally obscure the surface. Research indicates that it is possible to obtain five or more levels of moisture discrimination and that a mature corn crop is the limiting vegetation situation.

  4. Diameter Growth of Loblolly Pine Trees as Affected by Soil-Moisture Availibility

    Treesearch

    John R. Bassett

    1964-01-01

    In a 30-year-old even-aged stand of loblolly pine on a site 90 loessial soil in southeast Arkansas during foul growing seasons, most trees on plots thinned to 125 square feet of basal area per acre increased in basal area continuously when, under the crown canopy, available water in the surface foot remained above 65 percent. Measurable diameter growth ceased when...

  5. FINAL REPORT: Temporal and Spatial Distribution of Soil Moisture in Heterogeneous Vadose Zone with Moisture Barriers as Affected by Atmospheric Boundary Conditions

    DTIC Science & Technology

    2015-12-07

    Wallen, B., K.M. Smits and S.E. Howington. Thermal conductivity of binary sand mixtures evaluated through the full range of saturation. Hydrology Days...and T.H. Illangasekare. 2011. Thermal conductivity of soils as affected by temperature, Proceedings from Hydrology Days. Colorado State University...is mixed with very fine soil). Although it is well known that the apparent thermal conductivity (λ) of partially wet soil is a function of water (θ

  6. Microstrip transmission line for soil moisture measurement

    NASA Astrophysics Data System (ADS)

    Chen, Xuemin; Li, Jing; Liang, Renyue; Sun, Yijie; Liu, C. Richard; Rogers, Richard; Claros, German

    2004-12-01

    Pavement life span is often affected by the amount of voids in the base and subgrade soils, especially moisture content in pavement. Most available moisture sensors are based on the capacitive sensing using planar blades. Since the planar sensor blades are fabricated on the same surface to reduce the overall size of the sensor, such structure cannot provide very high accuracy for moisture content measurement. As a consequence, a typical capacitive moisture sensor has an error in the range of 30%. A more accurate measurement is based on the time domain refelctometer (TDR) measurement. However, typical TDR system is fairly expensive equipment, very large in size, and difficult to operate, the moisture content measurement is limited. In this paper, a novel microstrip transmission line based moisture sensor is presented. This sensor uses the phase shift measurement of RF signal going through a transmission line buried in the soil to be measured. Since the amplitude of the transmission measurement is a strong function of the conductivity (loss of the media) and the imaginary part of dielectric constant, and the phase is mainly a strong function of the real part of the dielectric constant, measuring phase shift in transmission mode can directly obtain the soil moisture information. This sensor was designed and implemented. Sensor networking was devised. Both lab and field data show that this sensor is sensitive and accurate.

  7. Soil Moisture Retrieval from Aquarius

    USDA-ARS?s Scientific Manuscript database

    Aquarius observations over land offer an unprecedented opportunity to provide a value-added product, land surface soil moisture, which will contribute to a better understanding of the Earth’s climate and water cycle. Additionally, Aquarius will provide the first spaceborne data that can be used to a...

  8. Soil-moisture constants and their variation

    Treesearch

    Walter M. Broadfoot; Hubert D. Burke

    1958-01-01

    "Constants" like field capacity, liquid limit, moisture equivalent, and wilting point are used by most students and workers in soil moisture. These constants may be equilibrium points or other values that describe soil moisture. Their values under specific soil and cover conditions have been discussed at length in the literature, but few general analyses and...

  9. Soil moisture depletion patterns around scattered trees

    Treesearch

    Robert R. Ziemer

    1968-01-01

    Soil moisture was measured around an isolated mature sugar pine tree (Pinus lambertiana Dougl.) in the mixed conifer forest type of the north central Sierra Nevada, California, from November 1965 to October 1966. From a sequence of measurements, horizontal and vertical soil moisture profiles were developed. Estimated soil moisture depletion from the 61-foot radius plot...

  10. Soil moisture patterns in a northern coniferous forest

    Treesearch

    Thomas F. McLintock

    1959-01-01

    The trend of soil moisture during the growing season, the alternate wetting from rainfall and drying during clear weather, determines the amount of moisture available for tree growth and also fixes, in part, the environment for root growth. In much of the northern coniferous region both moisture content and root environment are in turn affected by the hummock-and-...

  11. Evaluation of Assimilated SMOS Soil Moisture Data for US Cropland Soil Moisture Monitoring

    NASA Technical Reports Server (NTRS)

    Yang, Zhengwei; Sherstha, Ranjay; Crow, Wade; Bolten, John; Mladenova, Iva; Yu, Genong; Di, Liping

    2016-01-01

    Remotely sensed soil moisture data can provide timely, objective and quantitative crop soil moisture information with broad geospatial coverage and sufficiently high resolution observations collected throughout the growing season. This paper evaluates the feasibility of using the assimilated ESA Soil Moisture Ocean Salinity (SMOS)Mission L-band passive microwave data for operational US cropland soil surface moisture monitoring. The assimilated SMOS soil moisture data are first categorized to match with the United States Department of Agriculture (USDA)National Agricultural Statistics Service (NASS) survey based weekly soil moisture observation data, which are ordinal. The categorized assimilated SMOS soil moisture data are compared with NASSs survey-based weekly soil moisture data for consistency and robustness using visual assessment and rank correlation. Preliminary results indicate that the assimilated SMOS soil moisture data highly co-vary with NASS field observations across a large geographic area. Therefore, SMOS data have great potential for US operational cropland soil moisture monitoring.

  12. Long-term nitrogen addition affects the phylogenetic turnover of soil microbial community responding to moisture pulse

    SciTech Connect

    Liu, Chi; Yao, Minjie; Stegen, James C.

    How press disturbance (long-term) influences the phylogenetic turnover of soil microbial communities responding to pulse disturbances (short-term) is not fully known. Understanding the complex connections between the history of environmental conditions, assembly processes and microbial community dynamics is necessary to predict microbial response to perturbation. Here, we started by investigating phylogenetic spatial turnover (based on DNA) of soil prokaryotic communities after long-term nitrogen (N) deposition and temporal turnover (based on RNA) of communities responding to pulse by conducting short-term rewetting experiments. The results showed that moderate N addition increased ecological stochasticity and phylogenetic diversity. In contrast, high N addition slightlymore » increased homogeneous selection and decreased phylogenetic diversity. Examining the system with higher phylogenetic resolution revealed a moderate contribution of variable selection across the whole N gradient. The moisture pulse experiment showed that high N soils had higher rates of phylogenetic turnover across short phylogenetic distances and significant changes in community compositions through time. Long-term N input history influenced spatial turnover of microbial communities, but the dominant community assembly mechanisms differed across different N deposition gradients. We further revealed an interaction between press and pulse disturbances whereby deterministic processes were particularly important following pulse disturbances in high N soils.« less

  13. Long-term nitrogen addition affects the phylogenetic turnover of soil microbial community responding to moisture pulse

    DOE PAGES

    Liu, Chi; Yao, Minjie; Stegen, James C.; ...

    2017-12-13

    How press disturbance (long-term) influences the phylogenetic turnover of soil microbial communities responding to pulse disturbances (short-term) is not fully known. Understanding the complex connections between the history of environmental conditions, assembly processes and microbial community dynamics is necessary to predict microbial response to perturbation. Here, we started by investigating phylogenetic spatial turnover (based on DNA) of soil prokaryotic communities after long-term nitrogen (N) deposition and temporal turnover (based on RNA) of communities responding to pulse by conducting short-term rewetting experiments. The results showed that moderate N addition increased ecological stochasticity and phylogenetic diversity. In contrast, high N addition slightlymore » increased homogeneous selection and decreased phylogenetic diversity. Examining the system with higher phylogenetic resolution revealed a moderate contribution of variable selection across the whole N gradient. The moisture pulse experiment showed that high N soils had higher rates of phylogenetic turnover across short phylogenetic distances and significant changes in community compositions through time. Long-term N input history influenced spatial turnover of microbial communities, but the dominant community assembly mechanisms differed across different N deposition gradients. We further revealed an interaction between press and pulse disturbances whereby deterministic processes were particularly important following pulse disturbances in high N soils.« less

  14. Long-term nitrogen addition affects the phylogenetic turnover of soil microbial community responding to moisture pulse.

    PubMed

    Liu, Chi; Yao, Minjie; Stegen, James C; Rui, Junpeng; Li, Jiabao; Li, Xiangzhen

    2017-12-13

    How press disturbance (long-term) influences the phylogenetic turnover of soil microbial communities responding to pulse disturbances (short-term) is not fully known. Understanding the complex connections between the history of environmental conditions, assembly processes and microbial community dynamics is necessary to predict microbial response to perturbation. We started by investigating phylogenetic spatial turnover (based on DNA) of soil prokaryotic communities after long-term nitrogen (N) deposition and temporal turnover (based on RNA) of communities responding to pulse by conducting short-term rewetting experiments. The results showed that moderate N addition increased ecological stochasticity and phylogenetic diversity. In contrast, high N addition slightly increased homogeneous selection and decreased phylogenetic diversity. Examining the system with higher phylogenetic resolution revealed a moderate contribution of variable selection across the whole N gradient. The moisture pulse experiment showed that high N soils had higher rates of phylogenetic turnover across short phylogenetic distances and significant changes in community compositions through time. Long-term N input history influenced spatial turnover of microbial communities, but the dominant community assembly mechanisms differed across different N deposition gradients. We further revealed an interaction between press and pulse disturbances whereby deterministic processes were particularly important following pulse disturbances in high N soils.

  15. Modeling soil moisture memory in savanna ecosystems

    NASA Astrophysics Data System (ADS)

    Gou, S.; Miller, G. R.

    2011-12-01

    Antecedent soil conditions create an ecosystem's "memory" of past rainfall events. Such soil moisture memory effects may be observed over a range of timescales, from daily to yearly, and lead to feedbacks between hydrological and ecosystem processes. In this study, we modeled the soil moisture memory effect on savanna ecosystems in California, Arizona, and Africa, using a system dynamics model created to simulate the ecohydrological processes at the plot-scale. The model was carefully calibrated using soil moisture and evapotranspiration data collected at three study sites. The model was then used to simulate scenarios with various initial soil moisture conditions and antecedent precipitation regimes, in order to study the soil moisture memory effects on the evapotranspiration of understory and overstory species. Based on the model results, soil texture and antecedent precipitation regime impact the redistribution of water within soil layers, potentially causing deeper soil layers to influence the ecosystem for a longer time. Of all the study areas modeled, soil moisture memory of California savanna ecosystem site is replenished and dries out most rapidly. Thus soil moisture memory could not maintain the high rate evapotranspiration for more than a few days without incoming rainfall event. On the contrary, soil moisture memory of Arizona savanna ecosystem site lasts the longest time. The plants with different root depths respond to different memory effects; shallow-rooted species mainly respond to the soil moisture memory in the shallow soil. The growing season of grass is largely depended on the soil moisture memory of the top 25cm soil layer. Grass transpiration is sensitive to the antecedent precipitation events within daily to weekly timescale. Deep-rooted plants have different responses since these species can access to the deeper soil moisture memory with longer time duration Soil moisture memory does not have obvious impacts on the phenology of woody plants

  16. Influence of soil moisture on soil respiration

    NASA Astrophysics Data System (ADS)

    Fer, Miroslav; Kodesova, Radka; Nikodem, Antonin; Klement, Ales; Jelenova, Klara

    2015-04-01

    The aim of this work was to describe an impact of soil moisture on soil respiration. Study was performed on soil samples from morphologically diverse study site in loess region of Southern Moravia, Czech Republic. The original soil type is Haplic Chernozem, which was due to erosion changed into Regosol (steep parts) and Colluvial soil (base slope and the tributary valley). Soil samples were collected from topsoils at 5 points of the selected elevation transect and also from the parent material (loess). Grab soil samples, undisturbed soil samples (small - 100 cm3, and large - 713 cm3) and undisturbed soil blocks were taken. Basic soil properties were determined on grab soil samples. Small undisturbed soil samples were used to determine the soil water retention curves and the hydraulic conductivity functions using the multiple outflow tests in Tempe cells and a numerical inversion with HYDRUS 1-D. During experiments performed in greenhouse dry large undisturbed soil samples were wetted from below using a kaolin tank and cumulative water inflow due to capillary rise was measured. Simultaneously net CO2 exchange rate and net H2O exchange rate were measured using LCi-SD portable photosynthesis system with Soil Respiration Chamber. Numerical inversion of the measured cumulative capillary rise data using the HYDRUS-1D program was applied to modify selected soil hydraulic parameters for particular conditions and to simulate actual soil water distribution within each soil column in selected times. Undisturbed soil blocks were used to prepare thin soil sections to study soil-pore structure. Results for all soil samples showed that at the beginning of soil samples wetting the CO2 emission increased because of improving condition for microbes' activity. The maximum values were reached for soil column average soil water content between 0.10 and 0.15 cm3/cm3. Next CO2 emission decreased since the pore system starts filling by water (i.e. aggravated conditions for microbes

  17. Irrigation scheduling using soil moisture sensors

    USDA-ARS?s Scientific Manuscript database

    Soil moisture sensors were evaluated and used for irrigation scheduling in humid region. Soil moisture sensors were installed in soil at depths of 15cm, 30cm, and 61cm belowground. Soil volumetric water content was automatically measured by the sensors in a time interval of an hour during the crop g...

  18. SMALT - Soil Moisture from Altimetry

    NASA Astrophysics Data System (ADS)

    Smith, Richard; Salloway, Mark; Berry, Philippa; Hahn, Sebastian; Wagner, Wolfgang; Egido, Alejandro; Dinardo, Salvatore; Lucas, Bruno Manuel; Benveniste, Jerome

    2014-05-01

    Soil surface moisture is a key scientific parameter; however, it is extremely difficult to measure remotely, particularly in arid and semi-arid terrain. This paper outlines the development of a novel methodology to generate soil moisture estimates in these regions from multi-mission satellite radar altimetry. Key to this approach is the development of detailed DRy Earth ModelS (DREAMS), which encapsulate the detailed and intricate surface brightness variations over the Earth's land surface, resulting from changes in surface roughness and composition. DREAMS have been created over a number of arid and semi-arid deserts worldwide to produce historical SMALT timeseries over soil moisture variation. These products are available in two formats - a high resolution track product which utilises the altimeter's high frequency content alongtrack and a multi-looked 6" gridded product at facilitate easy comparison/integeration with other remote sensing techniques. An overview of the SMALT processing scheme, covering the progression of the data from altimeter sigma0 through to final soil moisture estimate, is included along with example SMALT products. Validation has been performed over a number of deserts by comparing SMALT products with other remote sensing techniques, results of the comparison between SMALT and Metop Warp 5.5 are presented here. Comparisons with other remote sensing techniques have been limited in scope due to differences in the operational aspects of the instruments, the restricted geographical coverage of the DREAMS and the low repeat temporal sampling rate of the altimeter. The potential to expand the SMALT technique into less arid areas has been investigated. Small-scale comparison with in-situ and GNSS-R data obtained by the LEiMON experimental campaign over Tuscany, where historical trends exist within both SMALT and SMC probe datasets. A qualitative analysis of unexpected backscatter characteristics in dedicated dry environments is performed with

  19. Impacts of soil moisture content on visual soil evaluation

    NASA Astrophysics Data System (ADS)

    Emmet-Booth, Jeremy; Forristal, Dermot; Fenton, Owen; Bondi, Giulia; Creamer, Rachel; Holden, Nick

    2017-04-01

    Visual Soil Examination and Evaluation (VSE) techniques offer tools for soil quality assessment. They involve the visual and tactile assessment of soil properties such as aggregate size and shape, porosity, redox morphology, soil colour and smell. An increasing body of research has demonstrated the reliability and utility of VSE techniques. However a number of limitations have been identified, including the potential impact of soil moisture variation during sampling. As part of a national survey of grassland soil quality in Ireland, an evaluation of the impact of soil moisture on two widely used VSE techniques was conducted. The techniques were Visual Evaluation of Soil Structure (VESS) (Guimarães et al., 2011) and Visual Soil Assessment (VSA) (Shepherd, 2009). Both generate summarising numeric scores that indicate soil structural quality, though employ different scoring mechanisms. The former requires the assessment of properties concurrently and the latter separately. Both methods were deployed on 20 sites across Ireland representing a range of soils. Additional samples were taken for soil volumetric water (θ) determination at 5-10 and 10-20 cm depth. No significant correlation was observed between θ 5-10 cm and either VSE technique. However, VESS scores were significantly related to θ 10-20 cm (rs = 0.40, sig = 0.02) while VSA scores were not (rs = -0.33, sig = 0.06). VESS and VSA scores can be grouped into quality classifications (good, moderate and poor). No significant mean difference was observed between θ 5-10 cm or θ 10-20 cm according to quality classification by either method. It was concluded that VESS scores may be affected by soil moisture variation while VSA appear unaffected. The different scoring mechanisms, where the separate assessment and scoring of individual properties employed by VSA, may limit soil moisture effects. However, moisture content appears not to affect overall structural quality classification by either method. References

  20. Carbon use efficiency (CUE) and biomass turnover of soil microbial communities as affected by bedrock, land management and soil temperature and moisture

    NASA Astrophysics Data System (ADS)

    Zheng, Qing; Hu, Yuntao; Richter, Andreas; Wanek, Wolfgang

    2017-04-01

    Soil microbial carbon use efficiency (CUE), defined as the proportion of organic C taken up that is allocated to microbial growth, represents an important synthetic representation of microbial community C metabolism that describes the flux partitioning between microbial respiration and growth. Therefore, studying microbial CUE is critical for the understanding of soil C cycling. Microbial CUE is thought to vary with environmental conditions (e.g. temperature and soil moisture). Microbial CUE is thought to decrease with increasing temperature and declining soil moisture, as the latter may trigger stress responses (e.g. the synthesis of stress metabolites), which may consequently lower microbial community CUE. However, these effects on microbial CUE have not been adequately measured so far due to methodological restrictions. The most widely used methods for microbial CUE estimation are based on tracing 13C-labeled substrates into microbial biomass and respiratory CO2, approaches that are known to overestimate microbial CUE of native organic matter in soil. Recently, a novel substrate-independent approach based on the measurement of (i) respiration rates and (ii) the incorporation rates of 18O from labelled water into newly formed microbial DNA has been developed in our laboratory for measuring microbial CUE. This approach overcomes the shortcomings of previously used methods and has already been shown to yield realistic estimations of soil microbial CUE. This approach can also be applied to concurrently measure microbial biomass turnover rates, which also influence the sequestration of soil organic C. Microbial turnover rates are also thought to be impacted by environmental factors, but rarely have been directly measured so far. Here, we aimed at determining the short-term effects of environmental factors (soil temperature and soil moisture) on microbial CUE and microbial biomass turnover rates based on the novel 18O approach. Soils from three land-use types (arable

  1. Soil Moisture Memory in Climate Models

    NASA Technical Reports Server (NTRS)

    Koster, Randal D.; Suarez, Max J.; Zukor, Dorothy J. (Technical Monitor)

    2000-01-01

    Water balance considerations at the soil surface lead to an equation that relates the autocorrelation of soil moisture in climate models to (1) seasonality in the statistics of the atmospheric forcing, (2) the variation of evaporation with soil moisture, (3) the variation of runoff with soil moisture, and (4) persistence in the atmospheric forcing, as perhaps induced by land atmosphere feedback. Geographical variations in the relative strengths of these factors, which can be established through analysis of model diagnostics and which can be validated to a certain extent against observations, lead to geographical variations in simulated soil moisture memory and thus, in effect, to geographical variations in seasonal precipitation predictability associated with soil moisture. The use of the equation to characterize controls on soil moisture memory is demonstrated with data from the modeling system of the NASA Seasonal-to-Interannual Prediction Project.

  2. A microwave systems approach to measuring root zone soil moisture

    NASA Technical Reports Server (NTRS)

    Newton, R. W.; Paris, J. F.; Clark, B. V.

    1983-01-01

    Computer microwave satellite simulation models were developed and the program was used to test the ability of a coarse resolution passive microwave sensor to measure soil moisture over large areas, and to evaluate the effect of heterogeneous ground covers with the resolution cell on the accuracy of the soil moisture estimate. The use of realistic scenes containing only 10% to 15% bare soil and significant vegetation made it possible to observe a 60% K decrease in brightness temperature from a 5% soil moisture to a 35% soil moisture at a 21 cm microwave wavelength, providing a 1.5 K to 2 K per percent soil moisture sensitivity to soil moisture. It was shown that resolution does not affect the basic ability to measure soil moisture with a microwave radiometer system. Experimental microwave and ground field data were acquired for developing and testing a root zone soil moisture prediction algorithm. The experimental measurements demonstrated that the depth of penetration at a 21 cm microwave wavelength is not greater than 5 cm.

  3. Soil-moisture sensors and irrigation management

    USDA-ARS?s Scientific Manuscript database

    This agricultural irrigation seminar will cover the major classes of soil-moisture sensors; their advantages and disadvantages; installing and reading soil-moisture sensors; and using their data for irrigation management. The soil water sensor classes include the resistance sensors (gypsum blocks, g...

  4. Diffusion and emissions of 1,3-dichloro propene in Florida sandy soil in microplots affected by soil moisture, organic matter, and plastic film.

    PubMed

    Thomas, John E; Allen, L Hartwell; McCormack, Leslie A; Vu, Joseph C; Dickson, Donald W; Ou, Li-Tse

    2004-04-01

    The main objective of this study was to determine the influence of soil moisture, organic matter amendment and plastic cover (a virtually impermeable film, VIF) on diffusion and emissions of (Z)- and (E)-1,3-dichloropropene (1,3-D) in microplots of Florida sandy soil (Arredondo fine sand). Upward diffusion of the two isomers in the Arredondo soil without a plastic cover was greatly influenced by soil-water content and (Z)-1,3-D diffused faster than (E)-1,3-D. In less than 5 h after 1,3-D injection to 30 cm depth, (Z)- and (E)-1,3-D in air dry soil had diffused to a 10 cm depth, whereas diffusion for the two isomers was negligible in near-water-saturated soil, even 101 h after injection. The diffusion rate of (Z)- and (E)-1,3-D in near-field-capacity soil was between the rates in the two water regimes. Yard waste compost (YWC) amendment greatly reduced diffusion of (Z)- and (E)-1,3-D, even in air-dry soil. Although upward diffusion of (Z)- and (E)-1,3-D in soil with VIF cover was slightly less than in the corresponding bare soil; the cover promoted retention of vapors of the two isomers in soil pore air in the shallow subsurface. More (Z)-1,3-D vapor was found initially in soil pore air than (E)-1,3-D although the difference declined thereafter. As a result of rapid upward movement in air-dry bare soil, (Z)- and (E)-1,3-D were rapidly volatilized into the atmosphere, but emissions from the near-water-saturated soil were minimal. Virtually impermeable film and YWC amendment retarded emissions. This study indicated that adequate soil water in this sandy soil is needed to prevent rapid emissions, but excess soil water slows diffusion of (Z)- and (E)-1,3-D. Thus, management for optimum water in soil is critical for pesticidal efficacy and the environment.

  5. Assimilating soil moisture into an Earth System Model

    NASA Astrophysics Data System (ADS)

    Stacke, Tobias; Hagemann, Stefan

    2017-04-01

    Several modelling studies reported potential impacts of soil moisture anomalies on regional climate. In particular for short prediction periods, perturbations of the soil moisture state may result in significant alteration of surface temperature in the following season. However, it is not clear yet whether or not soil moisture anomalies affect climate also on larger temporal and spatial scales. In an earlier study, we showed that soil moisture anomalies can persist for several seasons in the deeper soil layers of a land surface model. Additionally, those anomalies can influence root zone moisture, in particular during explicitly dry or wet periods. Thus, one prerequisite for predictability, namely the existence of long term memory, is evident for simulated soil moisture and might be exploited to improve climate predictions. The second prerequisite is the sensitivity of the climate system to soil moisture. In order to investigate this sensitivity for decadal simulations, we implemented a soil moisture assimilation scheme into the Max-Planck Institute for Meteorology's Earth System Model (MPI-ESM). The assimilation scheme is based on a simple nudging algorithm and updates the surface soil moisture state once per day. In our experiments, the MPI-ESM is used which includes model components for the interactive simulation of atmosphere, land and ocean. Artificial assimilation data is created from a control simulation to nudge the MPI-ESM towards predominantly dry and wet states. First analyses are focused on the impact of the assimilation on land surface variables and reveal distinct differences in the long-term mean values between wet and dry state simulations. Precipitation, evapotranspiration and runoff are larger in the wet state compared to the dry state, resulting in an increased moisture transport from the land to atmosphere and ocean. Consequently, surface temperatures are lower in the wet state simulations by more than one Kelvin. In terms of spatial pattern

  6. Improving Water Level and Soil Moisture Over Peatlands in a Global Land Modeling System

    NASA Technical Reports Server (NTRS)

    Bechtold, M.; De Lannoy, G. J. M.; Roose, D.; Reichle, R. H.; Koster, R. D.; Mahanama, S. P.

    2017-01-01

    New model structure for peatlands results in improved skill metrics (without any parameter calibration) Simulated surface soil moisture strongly affected by new model, but reliable soil moisture data lacking for validation.

  7. Validation of soil moisture ocean salinity (SMOS) satellite soil moisture products

    USDA-ARS?s Scientific Manuscript database

    The surface soil moisture state controls the partitioning of precipitation into infiltration and runoff. High-resolution observations of soil moisture will lead to improved flood forecasts, especially for intermediate to large watersheds where most flood damage occurs. Soil moisture is also key in d...

  8. The international soil moisture network: A data hosting facility for global in situ soil moisture measurements

    USDA-ARS?s Scientific Manuscript database

    In situ measurements of soil moisture are invaluable for calibrating and validating land surface models and satellite-based soil moisture retrievals. In addition, long-term time series of in situ soil moisture measurements themselves can reveal trends in the water cycle related to climate or land co...

  9. Anthropogenic warming exacerbates European soil moisture droughts

    NASA Astrophysics Data System (ADS)

    Samaniego, L.; Thober, S.; Kumar, R.; Wanders, N.; Rakovec, O.; Pan, M.; Zink, M.; Sheffield, J.; Wood, E. F.; Marx, A.

    2018-05-01

    Anthropogenic warming is anticipated to increase soil moisture drought in the future. However, projections are accompanied by large uncertainty due to varying estimates of future warming. Here, using an ensemble of hydrological and land-surface models, forced with bias-corrected downscaled general circulation model output, we estimate the impacts of 1-3 K global mean temperature increases on soil moisture droughts in Europe. Compared to the 1.5 K Paris target, an increase of 3 K—which represents current projected temperature change—is found to increase drought area by 40% (±24%), affecting up to 42% (±22%) more of the population. Furthermore, an event similar to the 2003 drought is shown to become twice as frequent; thus, due to their increased occurrence, events of this magnitude will no longer be classified as extreme. In the absence of effective mitigation, Europe will therefore face unprecedented increases in soil moisture drought, presenting new challenges for adaptation across the continent.

  10. Soil moisture by extraction and gas chromatography

    NASA Technical Reports Server (NTRS)

    Merek, E. L.; Carle, G. C.

    1973-01-01

    To determine moisture content of soils rapidly and conveniently extract moisture with methanol and determine water content of methanol extract by gas chromatography. Moisture content of sample is calculated from weight of water and methanol in aliquot and weight of methanol added to sample.

  11. Electrical methods of determining soil moisture content

    NASA Technical Reports Server (NTRS)

    Silva, L. F.; Schultz, F. V.; Zalusky, J. T.

    1975-01-01

    The electrical permittivity of soils is a useful indicator of soil moisture content. Two methods of determining the permittivity profile in soils are examined. A method due to Becher is found to be inapplicable to this situation. A method of Slichter, however, appears to be feasible. The results of Slichter's method are extended to the proposal of an instrument design that could measure available soil moisture profile (percent available soil moisture as a function of depth) from a surface measurement to an expected resolution of 10 to 20 cm.

  12. Survey of methods for soil moisture determination

    NASA Technical Reports Server (NTRS)

    Schmugge, T. J.; Jackson, T. J.; Mckim, H. L.

    1979-01-01

    Existing and proposed methods for soil moisture determination are discussed. These include: (1) in situ investigations including gravimetric, nuclear, and electromagnetic techniques; (2) remote sensing approaches that use the reflected solar, thermal infrared, and microwave portions of the electromagnetic spectrum; and (3) soil physics models that track the behavior of water in the soil in response to meteorological inputs (precipitation) and demands (evapotranspiration). The capacities of these approaches to satisfy various user needs for soil moisture information vary from application to application, but a conceptual scheme for merging these approaches into integrated systems to provide soil moisture information is proposed that has the potential for meeting various application requirements.

  13. Multiscale soil moisture estimates using static and roving cosmic-ray soil moisture sensors

    NASA Astrophysics Data System (ADS)

    McJannet, David; Hawdon, Aaron; Baker, Brett; Renzullo, Luigi; Searle, Ross

    2017-12-01

    Soil moisture plays a critical role in land surface processes and as such there has been a recent increase in the number and resolution of satellite soil moisture observations and the development of land surface process models with ever increasing resolution. Despite these developments, validation and calibration of these products has been limited because of a lack of observations on corresponding scales. A recently developed mobile soil moisture monitoring platform, known as the rover, offers opportunities to overcome this scale issue. This paper describes methods, results and testing of soil moisture estimates produced using rover surveys on a range of scales that are commensurate with model and satellite retrievals. Our investigation involved static cosmic-ray neutron sensors and rover surveys across both broad (36 × 36 km at 9 km resolution) and intensive (10 × 10 km at 1 km resolution) scales in a cropping district in the Mallee region of Victoria, Australia. We describe approaches for converting rover survey neutron counts to soil moisture and discuss the factors controlling soil moisture variability. We use independent gravimetric and modelled soil moisture estimates collected across both space and time to validate rover soil moisture products. Measurements revealed that temporal patterns in soil moisture were preserved through time and regression modelling approaches were utilised to produce time series of property-scale soil moisture which may also have applications in calibration and validation studies or local farm management. Intensive-scale rover surveys produced reliable soil moisture estimates at 1 km resolution while broad-scale surveys produced soil moisture estimates at 9 km resolution. We conclude that the multiscale soil moisture products produced in this study are well suited to future analysis of satellite soil moisture retrievals and finer-scale soil moisture models.

  14. Soil moisture profile variability in land-vegetation- atmosphere continuum

    NASA Astrophysics Data System (ADS)

    Wu, Wanru

    Soil moisture is of critical importance to the physical processes governing energy and water exchanges at the land-air boundary. With respect to the exchange of water mass, soil moisture controls the response of the land surface to atmospheric forcing and determines the partitioning of precipitation into infiltration and runoff. Meanwhile, the soil acts as a reservoir for the storage of liquid water and slow release of water vapor into the atmosphere. The major motivation of the study is that the soil moisture profile is thought to make a substantial contribution to the climate variability through two-way interactions between the land-surface and the atmosphere in the coupled ocean-atmosphere-land climate system. The characteristics of soil moisture variability with soil depth may be important in affecting the atmosphere. The natural variability of soil moisture profile is demonstrated using observations. The 16-year field observational data of soil moisture with 11-layer (top 2.0 meters) measured soil depths over Illinois are analyzed and used to identify and quantify the soil moisture profile variability, where the atmospheric forcing (precipitation) anomaly propagates down through the land-branch of the hydrological cycle with amplitude damping, phase shift, and increasing persistence. Detailed statistical data analyses, which include application of the periodogram method, the wavelet method and the band-pass filter, are made of the variations of soil moisture profile and concurrently measured precipitation for comparison. Cross-spectral analysis is performed to obtain the coherence pattern and phase correlation of two time series for phase shift and amplitude damping calculation. A composite of the drought events during this time period is analyzed and compared with the normal (non-drought) case. A multi-layer land surface model is applied for modeling the soil moisture profile variability characteristics and investigating the underlying mechanisms. Numerical

  15. Converting Soil Moisture Observations to Effective Values for Improved Validation of Remotely Sensed Soil Moisture

    NASA Technical Reports Server (NTRS)

    Laymon, Charles A.; Crosson, William L.; Limaye, Ashutosh; Manu, Andrew; Archer, Frank

    2005-01-01

    We compare soil moisture retrieved with an inverse algorithm with observations of mean moisture in the 0-6 cm soil layer. A significant discrepancy is noted between the retrieved and observed moisture. Using emitting depth functions as weighting functions to convert the observed mean moisture to observed effective moisture removes nearly one-half of the discrepancy noted. This result has important implications in remote sensing validation studies.

  16. Logging effects on soil moisture losses

    Treesearch

    Robert R. Ziemer

    1978-01-01

    Abstract - The depletion of soil moisture within the surface 15 feet by an isolated mature sugar pine and an adjacent uncut forest in the California Sierra Nevada was measured by the neutron method every 2 weeks for 5 consecutive summers. Soil moisture recharge was measured periodically during the intervening winters. Groundwater fluctuations within the surface 50...

  17. Temporal transferability of soil moisture calibration equations

    USDA-ARS?s Scientific Manuscript database

    Several large-scale field campaigns have been conducted over the last 20 years that require accurate estimates of soil moisture conditions. These measurements are manually conducted using soil moisture probes which require calibration. The calibration process involves the collection of hundreds of...

  18. Measuring soil moisture with imaging radars

    NASA Technical Reports Server (NTRS)

    Dubois, Pascale C.; Vanzyl, Jakob; Engman, Ted

    1995-01-01

    An empirical model was developed to infer soil moisture and surface roughness from radar data. The accuracy of the inversion technique is assessed by comparing soil moisture obtained with the inversion technique to in situ measurements. The effect of vegetation on the inversion is studied and a method to eliminate the areas where vegetation impairs the algorithm is described.

  19. Summary: Remote sensing soil moisture research

    NASA Technical Reports Server (NTRS)

    Schmer, F. A.; Werner, H. D.; Waltz, F. A.

    1970-01-01

    During the 1969 and 1970 growing seasons research was conducted to investigate the relationship between remote sensing imagery and soil moisture. The research was accomplished under two completely different conditions: (1) cultivated cropland in east central South Dakota, and (2) rangeland in western South Dakota. Aerial and ground truth data are being studied and correlated in order to evaluate the moisture supply and water use. Results show that remote sensing is a feasible method for monitoring soil moisture.

  20. High-resolution soil moisture mapping in Afghanistan

    NASA Astrophysics Data System (ADS)

    Hendrickx, Jan M. H.; Harrison, J. Bruce J.; Borchers, Brian; Kelley, Julie R.; Howington, Stacy; Ballard, Jerry

    2011-06-01

    Soil moisture conditions have an impact upon virtually all aspects of Army activities and are increasingly affecting its systems and operations. Soil moisture conditions affect operational mobility, detection of landmines and unexploded ordinance, natural material penetration/excavation, military engineering activities, blowing dust and sand, watershed responses, and flooding. This study further explores a method for high-resolution (2.7 m) soil moisture mapping using remote satellite optical imagery that is readily available from Landsat and QuickBird. The soil moisture estimations are needed for the evaluation of IED sensors using the Countermine Simulation Testbed in regions where access is difficult or impossible. The method has been tested in Helmand Province, Afghanistan, using a Landsat7 image and a QuickBird image of April 23 and 24, 2009, respectively. In previous work it was found that Landsat soil moisture can be predicted from the visual and near infra-red Landsat bands1-4. Since QuickBird bands 1-4 are almost identical to Landsat bands 1- 4, a Landsat soil moisture map can be downscaled using QuickBird bands 1-4. However, using this global approach for downscaling from Landsat to QuickBird scale yielded a small number of pixels with erroneous soil moisture values. Therefore, the objective of this study is to examine how the quality of the downscaled soil moisture maps can be improved by using a data stratification approach for the development of downscaling regression equations for each landscape class. It was found that stratification results in a reliable downscaled soil moisture map with a spatial resolution of 2.7 m.

  1. SMAP Radiometer Captures Views of Global Soil Moisture

    NASA Image and Video Library

    2015-05-06

    These maps of global soil moisture were created using data from the radiometer instrument on NASA Soil Moisture Active Passive SMAP observatory. Evident are regions of increased soil moisture and flooding during April, 2015.

  2. Remote sensing of soil moisture using airborne hyperspectral data

    USGS Publications Warehouse

    Finn, M.; Lewis, M.; Bosch, D.; Giraldo, Mario; Yamamoto, K.; Sullivan, D.; Kincaid, R.; Luna, R.; Allam, G.; Kvien, Craig; Williams, M.

    2011-01-01

    Landscape assessment of soil moisture is critical to understanding the hydrological cycle at the regional scale and in broad-scale studies of biophysical processes affected by global climate changes in temperature and precipitation. Traditional efforts to measure soil moisture have been principally restricted to in situ measurements, so remote sensing techniques are often employed. Hyperspectral sensors with finer spatial resolution and narrow band widths may offer an alternative to traditional multispectral analysis of soil moisture, particularly in landscapes with high spatial heterogeneity. This preliminary research evaluates the ability of remotely sensed hyperspectral data to quantify soil moisture for the Little River Experimental Watershed (LREW), Georgia. An airborne hyperspectral instrument with a short-wavelength infrared (SWIR) sensor was flown in 2005 and 2007 and the results were correlated to in situ soil moisture values. A significant statistical correlation (R2 value above 0.7 for both sampling dates) for the hyperspectral instrument data and the soil moisture probe data at 5.08 cm (2 inches) was determined. While models for the 20.32 cm (8 inches) and 30.48 cm (12 inches) depths were tested, they were not able to estimate soil moisture to the same degree.

  3. Remote sensing of soil moisture using airborne hyperspectral data

    USGS Publications Warehouse

    Finn, Michael P.; Lewis, Mark (David); Bosch, David D.; Giraldo, Mario; Yamamoto, Kristina H.; Sullivan, Dana G.; Kincaid, Russell; Luna, Ronaldo; Allam, Gopala Krishna; Kvien, Craig; Williams, Michael S.

    2011-01-01

    Landscape assessment of soil moisture is critical to understanding the hydrological cycle at the regional scale and in broad-scale studies of biophysical processes affected by global climate changes in temperature and precipitation. Traditional efforts to measure soil moisture have been principally restricted to in situ measurements, so remote sensing techniques are often employed. Hyperspectral sensors with finer spatial resolution and narrow band widths may offer an alternative to traditional multispectral analysis of soil moisture, particularly in landscapes with high spatial heterogeneity. This preliminary research evaluates the ability of remotely sensed hyperspectral data to quantify soil moisture for the Little River Experimental Watershed (LREW), Georgia. An airborne hyperspectral instrument with a short-wavelength infrared (SWIR) sensor was flown in 2005 and 2007 and the results were correlated to in situ soil moisture values. A significant statistical correlation (R 2 value above 0.7 for both sampling dates) for the hyperspectral instrument data and the soil moisture probe data at 5.08 cm (2 inches) was determined. While models for the 20.32 cm (8 inches) and 30.48 cm (12 inches) depths were tested, they were not able to estimate soil moisture to the same degree.

  4. On-irrigator pasture soil moisture sensor

    NASA Astrophysics Data System (ADS)

    Eng-Choon Tan, Adrian; Richards, Sean; Platt, Ian; Woodhead, Ian

    2017-02-01

    In this paper, we presented the development of a proximal soil moisture sensor that measured the soil moisture content of dairy pasture directly from the boom of an irrigator. The proposed sensor was capable of soil moisture measurements at an accuracy of  ±5% volumetric moisture content, and at meter scale ground area resolutions. The sensor adopted techniques from the ultra-wideband radar to enable measurements of ground reflection at resolutions that are smaller than the antenna beamwidth of the sensor. An experimental prototype was developed for field measurements. Extensive field measurements using the developed prototype were conducted on grass pasture at different ground conditions to validate the accuracy of the sensor in performing soil moisture measurements.

  5. Soil moisture monitoring for crop management

    NASA Astrophysics Data System (ADS)

    Boyd, Dale

    2015-07-01

    The 'Risk management through soil moisture monitoring' project has demonstrated the capability of current technology to remotely monitor and communicate real time soil moisture data. The project investigated whether capacitance probes would assist making informed pre- and in-crop decisions. Crop potential and cropping inputs are increasingly being subject to greater instability and uncertainty due to seasonal variability. In a targeted survey of those who received regular correspondence from the Department of Primary Industries it was found that i) 50% of the audience found the information generated relevant for them and less than 10% indicted with was not relevant; ii) 85% have improved their knowledge/ability to assess soil moisture compared to prior to the project, with the most used indicator of soil moisture still being rain fall records; and iii) 100% have indicated they will continue to use some form of the technology to monitor soil moisture levels in the future. It is hoped that continued access to this information will assist informed input decisions. This will minimise inputs in low decile years with a low soil moisture base and maximise yield potential in more favourable conditions based on soil moisture and positive seasonal forecasts

  6. Effect of soil moisture on the temperature sensitivity of Northern soils

    NASA Astrophysics Data System (ADS)

    Minions, C.; Natali, S.; Ludwig, S.; Risk, D.; Macintyre, C. M.

    2017-12-01

    Arctic and boreal ecosystems are vast reservoirs of carbon and are particularly sensitive to climate warming. Changes in the temperature and precipitation regimes of these regions could significantly alter soil respiration rates, impacting atmospheric concentrations and affecting climate change feedbacks. Many incubation studies have shown that both temperature and soil moisture are important environmental drivers of soil respiration; this relationship, however, has rarely been demonstrated with in situ data. Here we present the results of a study at six field sites in Alaska from 2016 to 2017. Low-power automated soil gas systems were used to measure soil surface CO2 flux from three forced diffusion chambers and soil profile concentrations from three soil depth chambers at hourly intervals at each site. HOBO Onset dataloggers were used to monitor soil moisture and temperature profiles. Temperature sensitivity (Q10) was determined at each site using inversion analysis applied over different time periods. With highly resolved data sets, we were able to observe the changes in soil respiration in response to changes in temperature and soil moisture. Through regression analysis we confirmed that temperature is the primary driver in soil respiration, but soil moisture becomes dominant beyond a certain threshold, suppressing CO2 flux in soils with high moisture content. This field study supports the conclusions made from previous soil incubation studies and provides valuable insights into the impact of both temperature and soil moisture changes on soil respiration.

  7. Passive Microwave Remote Sensing of Soil Moisture

    NASA Technical Reports Server (NTRS)

    Njoku, Eni G.; Entekhabi, Dara

    1996-01-01

    Microwave remote sensing provides a unique capability for direct observation of soil moisture. Remote measurements from space afford the possibility of obtaining frequent, global sampling of soil moisture over a large fraction of the Earth's land surface. Microwave measurements have the benefit of being largely unaffected by cloud cover and variable surface solar illumination, but accurate soil moisture estimates are limited to regions that have either bare soil or low to moderate amounts of vegetation cover. A particular advantage of passive microwave sensors is that in the absence of significant vegetation cover soil moisture is the dominant effect on the received signal. The spatial resolutions of passive Microwave soil moisture sensors currently considered for space operation are in the range 10-20 km. The most useful frequency range for soil moisture sensing is 1-5 GHz. System design considerations include optimum choice of frequencies, polarizations, and scanning configurations, based on trade-offs between requirements for high vegetation penetration capability, freedom from electromagnetic interference, manageable antenna size and complexity, and the requirement that a sufficient number of information channels be available to correct for perturbing geophysical effects. This paper outlines the basic principles of the passive microwave technique for soil moisture sensing, and reviews briefly the status of current retrieval methods. Particularly promising are methods for optimally assimilating passive microwave data into hydrologic models. Further studies are needed to investigate the effects on microwave observations of within-footprint spatial heterogeneity of vegetation cover and subsurface soil characteristics, and to assess the limitations imposed by heterogeneity on the retrievability of large-scale soil moisture information from remote observations.

  8. Is soil moisture initialization important for seasonal to decadal predictions?

    NASA Astrophysics Data System (ADS)

    Stacke, Tobias; Hagemann, Stefan

    2014-05-01

    The state of soil moisture can can have a significant impact on regional climate conditions for short time scales up to several months. However, focusing on seasonal to decadal time scales, it is not clear whether the predictive skill of global a Earth System Model might be enhanced by assimilating soil moisture data or improving the initial soil moisture conditions with respect to observations. As a first attempt to provide answers to this question, we set up an experiment to investigate the life time (memory) of extreme soil moisture states in the coupled land-atmosphere model ECHAM6-JSBACH, which is part of the Max Planck Institute for Meteorology's Earth System Model (MPI-ESM). This experiment consists of an ensemble of 3 years simulations which are initialized with extreme wet and dry soil moisture states for different seasons and years. Instead of using common thresholds like wilting point or critical soil moisture, the extreme states were extracted from a reference simulation to ensure that they are within the range of simulated climate variability. As a prerequisite for this experiment, the soil hydrology in JSBACH was improved by replacing the bucket-type soil hydrology scheme with a multi-layer scheme. This new scheme is a more realistic representation of the soil, including percolation and diffusion fluxes between up to five separate layers, the limitation of bare soil evaporation to the uppermost soil layer and the addition of a long term water storage below the root zone in regions with deep soil. While the hydrological cycle is not strongly affected by this new scheme, it has some impact on the simulated soil moisture memory which is mostly strengthened due to the additional deep layer water storage. Ensemble statistics of the initialization experiment indicate perturbation lengths between just a few days up to several seasons for some regions. In general, the strongest effects are seen for wet initialization during northern winter over cold and humid

  9. Soil moisture sensors for continuous monitoring

    USGS Publications Warehouse

    Amer, Saud A.; Keefer, T. O.; Weltz, M.A.; Goodrich, David C.; Bach, Leslie

    1995-01-01

    Certain physical and chemical properties of soil vary with soil water content. The relationship between these properties and water content is complex and involves both the pore structure and constituents of the soil solution. One of the most economical techniques to quantify soil water content involves the measurement of electrical resistance of a dielectric medium that is in equilibrium with the soil water content. The objective of this research was to test the reliability and accuracy of fiberglass soil-moisture electrical resistance sensors (ERS) as compared to gravimetric sampling and Time Domain Reflectometry (TDR). The response of the ERS was compared to gravimetric measurements at eight locations on the USDA-ABS Walnut Gulch Experimental Watershed. The comparisons with TDR sensors were made at three additional locations on the same watershed. The high soil rock content (>45 percent) at seven locations resulted in consistent overestimation of soil water content by the ERS method. Where rock content was less than 10 percent, estimation of soil water was within 5 percent of the gravimetric soil water content. New methodology to calibrate the ERS sensors for rocky soils will need to be developed before soil water content values can be determined with these sensors. (KEY TERMS: soil moisture; soil water; infiltration; instrumentation; soil moisture sensors.)

  10. Quantifying soil moisture impacts on light use efficiency across biomes.

    PubMed

    Stocker, Benjamin D; Zscheischler, Jakob; Keenan, Trevor F; Prentice, I Colin; Peñuelas, Josep; Seneviratne, Sonia I

    2018-06-01

    Terrestrial primary productivity and carbon cycle impacts of droughts are commonly quantified using vapour pressure deficit (VPD) data and remotely sensed greenness, without accounting for soil moisture. However, soil moisture limitation is known to strongly affect plant physiology. Here, we investigate light use efficiency, the ratio of gross primary productivity (GPP) to absorbed light. We derive its fractional reduction due to soil moisture (fLUE), separated from VPD and greenness changes, using artificial neural networks trained on eddy covariance data, multiple soil moisture datasets and remotely sensed greenness. This reveals substantial impacts of soil moisture alone that reduce GPP by up to 40% at sites located in sub-humid, semi-arid or arid regions. For sites in relatively moist climates, we find, paradoxically, a muted fLUE response to drying soil, but reduced fLUE under wet conditions. fLUE identifies substantial drought impacts that are not captured when relying solely on VPD and greenness changes and, when seasonally recurring, are missed by traditional, anomaly-based drought indices. Counter to common assumptions, fLUE reductions are largest in drought-deciduous vegetation, including grasslands. Our results highlight the necessity to account for soil moisture limitation in terrestrial primary productivity data products, especially for drought-related assessments. © 2018 The Authors. New Phytologist © 2018 New Phytologist Trust.

  11. The soil moisture active passive experiments (SMAPEx): Towards soil moisture retrieval from the SMAP mission

    USDA-ARS?s Scientific Manuscript database

    NASA’s Soil Moisture Active Passive (SMAP) mission, scheduled for launch in 2014, will carry the first combined L-band radar and radiometer system with the objective of mapping near surface soil moisture and freeze/thaw state globally at near-daily time step (2-3 days). SMAP will provide three soil ...

  12. Space-time modeling of soil moisture

    NASA Astrophysics Data System (ADS)

    Chen, Zijuan; Mohanty, Binayak P.; Rodriguez-Iturbe, Ignacio

    2017-11-01

    A physically derived space-time mathematical representation of the soil moisture field is carried out via the soil moisture balance equation driven by stochastic rainfall forcing. The model incorporates spatial diffusion and in its original version, it is shown to be unable to reproduce the relative fast decay in the spatial correlation functions observed in empirical data. This decay resulting from variations in local topography as well as in local soil and vegetation conditions is well reproduced via a jitter process acting multiplicatively over the space-time soil moisture field. The jitter is a multiplicative noise acting on the soil moisture dynamics with the objective to deflate its correlation structure at small spatial scales which are not embedded in the probabilistic structure of the rainfall process that drives the dynamics. These scales of order of several meters to several hundred meters are of great importance in ecohydrologic dynamics. Properties of space-time correlation functions and spectral densities of the model with jitter are explored analytically, and the influence of the jitter parameters, reflecting variabilities of soil moisture at different spatial and temporal scales, is investigated. A case study fitting the derived model to a soil moisture dataset is presented in detail.

  13. NASA's Soil Moisture Active Passive (SMAP) Observatory

    NASA Technical Reports Server (NTRS)

    Kellogg, Kent; Thurman, Sam; Edelstein, Wendy; Spencer, Michael; Chen, Gun-Shing; Underwood, Mark; Njoku, Eni; Goodman, Shawn; Jai, Benhan

    2013-01-01

    The SMAP mission will produce high-resolution and accurate global maps of soil moisture and its freeze/thaw state using data from a non-imaging synthetic aperture radar and a radiometer, both operating at L-band.

  14. Radar for Measuring Soil Moisture Under Vegetation

    NASA Technical Reports Server (NTRS)

    Moghaddam, Mahta; Moller, Delwyn; Rodriguez, Ernesto; Rahmat-Samii, Yahya

    2004-01-01

    A two-frequency, polarimetric, spaceborne synthetic-aperture radar (SAR) system has been proposed for measuring the moisture content of soil as a function of depth, even in the presence of overlying vegetation. These measurements are needed because data on soil moisture under vegetation canopies are not available now and are necessary for completing mathematical models of global energy and water balance with major implications for global variations in weather and climate.

  15. Soil moisture variability across different scales in an Indian watershed for satellite soil moisture product validation

    NASA Astrophysics Data System (ADS)

    Singh, Gurjeet; Panda, Rabindra K.; Mohanty, Binayak P.; Jana, Raghavendra B.

    2016-05-01

    Strategic ground-based sampling of soil moisture across multiple scales is necessary to validate remotely sensed quantities such as NASA's Soil Moisture Active Passive (SMAP) product. In the present study, in-situ soil moisture data were collected at two nested scale extents (0.5 km and 3 km) to understand the trend of soil moisture variability across these scales. This ground-based soil moisture sampling was conducted in the 500 km2 Rana watershed situated in eastern India. The study area is characterized as sub-humid, sub-tropical climate with average annual rainfall of about 1456 mm. Three 3x3 km square grids were sampled intensively once a day at 49 locations each, at a spacing of 0.5 km. These intensive sampling locations were selected on the basis of different topography, soil properties and vegetation characteristics. In addition, measurements were also made at 9 locations around each intensive sampling grid at 3 km spacing to cover a 9x9 km square grid. Intensive fine scale soil moisture sampling as well as coarser scale samplings were made using both impedance probes and gravimetric analyses in the study watershed. The ground-based soil moisture samplings were conducted during the day, concurrent with the SMAP descending overpass. Analysis of soil moisture spatial variability in terms of areal mean soil moisture and the statistics of higher-order moments, i.e., the standard deviation, and the coefficient of variation are presented. Results showed that the standard deviation and coefficient of variation of measured soil moisture decreased with extent scale by increasing mean soil moisture.

  16. Soil moisture and temperature conditions affect survival and sporulation capacity of Rhododendron leaf disks infested with Phytophthora ramorum

    Treesearch

    Ebba K. Peterson; Niklaus J. Grünwald; Jennifer L. ParkeSoil

    2017-01-01

    Soilborne inoculum (infested leaf debris which has become incorporated into the soil) may be an important contributor to the persistence of the sudden oak death pathogen Phytophthora ramorum in recurrently positive nurseries. To initiate new epidemics, soilborne inoculum must not only be able to survive over time, but also be capable of...

  17. Soil moisture availability as a factor affecting valley oak (Quercus lobata Neé) seedling establishment and survival in a riparian habitat, Cosumnes River Preserve, Sacramento County, California

    Treesearch

    Virginia C. Meyer

    2002-01-01

    The lack of valley oak (Quercus lobata Neé) regeneration throughout much of its historical range appears to be related to both habitat destruction and soil moisture availability. The water relations, growth and survival of greenhouse potted seedlings, field-planted and natural seedlings were monitored through the growing season, 1989. The age...

  18. Utilization of point soil moisture measurements for field scale soil moisture averages and variances in agricultural landscapes

    USDA-ARS?s Scientific Manuscript database

    Soil moisture is a key variable in understanding the hydrologic processes and energy fluxes at the land surface. In spite of new technologies for in-situ soil moisture measurements and increased availability of remotely sensed soil moisture data, scaling issues between soil moisture observations and...

  19. Estimating Soil Moisture Using Polsar Data: a Machine Learning Approach

    NASA Astrophysics Data System (ADS)

    Khedri, E.; Hasanlou, M.; Tabatabaeenejad, A.

    2017-09-01

    Soil moisture is an important parameter that affects several environmental processes. This parameter has many important functions in numerous sciences including agriculture, hydrology, aerology, flood prediction, and drought occurrence. However, field procedures for moisture calculations are not feasible in a vast agricultural region territory. This is due to the difficulty in calculating soil moisture in vast territories and high-cost nature as well as spatial and local variability of soil moisture. Polarimetric synthetic aperture radar (PolSAR) imaging is a powerful tool for estimating soil moisture. These images provide a wide field of view and high spatial resolution. For estimating soil moisture, in this study, a model of support vector regression (SVR) is proposed based on obtained data from AIRSAR in 2003 in C, L, and P channels. In this endeavor, sequential forward selection (SFS) and sequential backward selection (SBS) are evaluated to select suitable features of polarized image dataset for high efficient modeling. We compare the obtained data with in-situ data. Output results show that the SBS-SVR method results in higher modeling accuracy compared to SFS-SVR model. Statistical parameters obtained from this method show an R2 of 97% and an RMSE of lower than 0.00041 (m3/m3) for P, L, and C channels, which has provided better accuracy compared to other feature selection algorithms.

  20. Comparing soil moisture memory in satellite observations and models

    NASA Astrophysics Data System (ADS)

    Stacke, Tobias; Hagemann, Stefan; Loew, Alexander

    2013-04-01

    latter in the deepest layer. From this we conclude that the seasonal soil moisture variations dominate the memory close to the surface but these are dampened in lower layers where the memory is mainly affected by longer term variations.

  1. Soil moisture and vegetation patterns in northern California forests

    Treesearch

    James R. Griffin

    1967-01-01

    Twenty-nine soil-vegetation plots were studied in a broad transect across the southern Cascade Range. Variations in soil moisture patterns during the growing season and in soil moisture tension values are discussed. Plot soil moisture values for 40- and 80-cm. depths in August and September are integrated into a soil drought index. Vegetation patterns are described in...

  2. Soil Moisture Estimation Using Hyperspectral SWIR Imagery

    NASA Astrophysics Data System (ADS)

    Lewis, D.

    2007-12-01

    The U.S. Geological Survey (USGS) is engaged with the U.S. Department of Agriculture's (USDA) Agricultural Research Service (ARS) and the University of Georgia's National Environmentally Sound Production Agriculture Laboratory (NESPAL) both in Tifton, Georgia, USA, to develop transformations for medium and high resolution remotely sensed images to generate moisture indicators for soil. The Institute for Technology Development (ITD) is located at the Stennis Space Center in southern Mississippi and has developed hyperspectral sensor systems that, when mounted in aircraft, collect electromagnetic reflectance data of the terrain. The sensor suite consists of sensors for three different sections of the electromagnetic spectrum; the Ultra-Violet (UV), Visible/Near InfraRed (VNIR) and Short Wave InfraRed (SWIR). The USDA/ ARS' Southeast Watershed Research Laboratory has probes that measure and record soil moisture. Data taken from the ITD SWIR sensor and the USDA/ARS soil moisture meters were analyzed to study the informatics relationships between SWIR data and measured soil moisture. The geographic locations of 29 soil moisture meters provided by the USDA/ARS are in the vicinity of Tifton, Georgia. Using USGS Digital Ortho Quads (DOQ), flightlines were drawn over the 29 soil moisture meters. The SWIR sensor was installed into an aircraft. The coordinates for the flightlines were also loaded into the navigational system of the aircraft. This airborne platform was used to collect the data over these flightlines. In order to prepare the data set for analysis, standard preprocessing was performed. These standard processes included sensor calibration, spectral subsetting, and atmospheric calibration. All 60 bands of the SWIR data were collected for each line in the image data, 15 bands of which were stripped from the data set leaving 45 bands of information in the wavelength range of 906 to 1705 nanometers. All the image files were calibrated using the regression equations

  3. Soil moisture in sessile oak forest gaps

    NASA Astrophysics Data System (ADS)

    Zagyvainé Kiss, Katalin Anita; Vastag, Viktor; Gribovszki, Zoltán; Kalicz, Péter

    2015-04-01

    By social demands are being promoted the aspects of the natural forest management. In forestry the concept of continuous forest has been an accepted principle also in Hungary since the last decades. The first step from even-aged stand to continuous forest can be the forest regeneration based on gap cutting, so small openings are formed in a forest due to forestry interventions. This new stand structure modifies the hydrological conditions for the regrowth. Without canopy and due to the decreasing amounts of forest litter the interception is less significant so higher amount of precipitation reaching the soil. This research focuses on soil moisture patterns caused by gaps. The spatio-temporal variability of soil water content is measured in gaps and in surrounding sessile oak (Quercus petraea) forest stand. Soil moisture was determined with manual soil moisture meter which use Time-Domain Reflectometry (TDR) technology. The three different sizes gaps (G1: 10m, G2: 20m, G3: 30m) was opened next to Sopron on the Dalos Hill in Hungary. First, it was determined that there is difference in soil moisture between forest stand and gaps. Second, it was defined that how the gap size influences the soil moisture content. To explore the short term variability of soil moisture, two 24-hour (in growing season) and a 48-hour (in dormant season) field campaign were also performed in case of the medium-sized G2 gap along two/four transects. Subdaily changes of soil moisture were performed. The measured soil moisture pattern was compared with the radiation pattern. It was found that the non-illuminated areas were wetter and in the dormant season the subdaily changes cease. According to our measurements, in the gap there is more available water than under the forest stand due to the less evaporation and interception loss. Acknowledgements: The research was supported by TÁMOP-4.2.2.A-11/1/KONV-2012-0004 and AGRARKLIMA.2 VKSZ_12-1-2013-0034.

  4. Soil moisture and properties estimation by assimilating soil temperatures using particle batch smoother: A new perspective for DTS

    NASA Astrophysics Data System (ADS)

    Dong, J.; Steele-Dunne, S. C.; Ochsner, T. E.; Van De Giesen, N.

    2015-12-01

    Soil moisture, hydraulic and thermal properties are critical for understanding the soil surface energy balance and hydrological processes. Here, we will discuss the potential of using soil temperature observations from Distributed Temperature Sensing (DTS) to investigate the spatial variability of soil moisture and soil properties. With DTS soil temperature can be measured with high resolution (spatial <1m, and temporal < 1min) in cables up to kilometers in length. Soil temperature evolution is primarily controlled by the soil thermal properties, and the energy balance at the soil surface. Hence, soil moisture, which affects both soil thermal properties and the energy that participates the evaporation process, is strongly correlated to the soil temperatures. In addition, the dynamics of the soil moisture is determined by the soil hydraulic properties.Here we will demonstrate that soil moisture, hydraulic and thermal properties can be estimated by assimilating observed soil temperature at shallow depths using the Particle Batch Smoother (PBS). The PBS can be considered as an extension of the particle filter, which allows us to infer soil moisture and soil properties using the dynamics of soil temperature within a batch window. Both synthetic and real field data will be used to demonstrate the robustness of this approach. We will show that the proposed method is shown to be able to handle different sources of uncertainties, which may provide a new view of using DTS observations to estimate sub-meter resolution soil moisture and properties for remote sensing product validation.

  5. Microstrip Ring Resonator for Soil Moisture Measurements

    NASA Technical Reports Server (NTRS)

    Sarabandi, Kamal; Li, Eric S.

    1993-01-01

    Accurate determination of spatial soil moisture distribution and monitoring its temporal variation have a significant impact on the outcomes of hydrologic, ecologic, and climatic models. Development of a successful remote sensing instrument for soil moisture relies on the accurate knowledge of the soil dielectric constant (epsilon(sub soil)) to its moisture content. Two existing methods for measurement of dielectric constant of soil at low and high frequencies are, respectively, the time domain reflectometry and the reflection coefficient measurement using an open-ended coaxial probe. The major shortcoming of these methods is the lack of accurate determination of the imaginary part of epsilon(sub soil). In this paper a microstrip ring resonator is proposed for the accurate measurement of soil dielectric constant. In this technique the microstrip ring resonator is placed in contact with soil medium and the real and imaginary parts of epsilon(sub soil) are determined from the changes in the resonant frequency and the quality factor of the resonator respectively. The solution of the electromagnetic problem is obtained using a hybrid approach based on the method of moments solution of the quasi-static formulation in conjunction with experimental data obtained from reference dielectric samples. Also a simple inversion algorithm for epsilon(sub soil) = epsilon'(sub r) + j(epsilon"(sub r)) based on regression analysis is obtained. It is shown that the wide dynamic range of the measured quantities provides excellent accuracy in the dielectric constant measurement. A prototype microstrip ring resonator at L-band is designed and measurements of soil with different moisture contents are presented and compared with other approaches.

  6. Soil moisture needs in earth sciences

    NASA Technical Reports Server (NTRS)

    Engman, Edwin T.

    1992-01-01

    The author reviews the development of passive and active microwave techniques for measuring soil moisture with respect to how the data may be used. New science programs such as the EOS, the GEWEX Continental-Scale International Project (GCIP) and STORM, a mesoscale meteorology and hydrology project, will have to account for soil moisture either as a storage in water balance computations or as a state variable in-process modeling. The author discusses future soil moisture needs such as frequency of measurement, accuracy, depth, and spatial resolution, as well as the concomitant model development that must proceed concurrently if the development in microwave technology is to have a major impact in these areas.

  7. The International Soil Moisture Network: a data hosting facility for global in situ soil moisture measurements

    NASA Astrophysics Data System (ADS)

    Dorigo, W. A.; Wagner, W.; Hohensinn, R.; Hahn, S.; Paulik, C.; Drusch, M.; Mecklenburg, S.; van Oevelen, P.; Robock, A.; Jackson, T.

    2011-02-01

    In situ measurements of soil moisture are invaluable for calibrating and validating land surface models and satellite-based soil moisture retrievals. In addition, long-term time series of in situ soil moisture measurements themselves can reveal trends in the water cycle related to climate or land cover change. Nevertheless, on a worldwide basis the number of meteorological networks and stations measuring soil moisture, in particular on a continuous basis, is still limited and the data they provide lack standardization of technique and protocol. To overcome many of these limitations, the International Soil Moisture Network (ISMN; http://www.ipf.tuwien.ac.at/insitu) was initiated to serve as a centralized data hosting facility where globally available in situ soil moisture measurements from operational networks and validation campaigns are collected, harmonized, and made available to users. Data collecting networks share their soil moisture datasets with the ISMN on a voluntary and no-cost basis. Incoming soil moisture data are automatically transformed into common volumetric soil moisture units and checked for outliers and implausible values. Apart from soil water measurements from different depths, important metadata and meteorological variables (e.g., precipitation and soil temperature) are stored in the database. These will assist the user in correctly interpreting the soil moisture data. The database is queried through a graphical user interface while output of data selected for download is provided according to common standards for data and metadata. Currently (status January 2011), the ISMN contains data of 16 networks and more than 500 stations located in the North America, Europe, Asia, and Australia. The time period spanned by the entire database runs from 1952 until the present, although most datasets have originated during the last decade. The database is rapidly expanding, which means that

  8. The International Soil Moisture Network: a data hosting facility for global in situ soil moisture measurements

    NASA Astrophysics Data System (ADS)

    Dorigo, W. A.; Wagner, W.; Hohensinn, R.; Hahn, S.; Paulik, C.; Xaver, A.; Gruber, A.; Drusch, M.; Mecklenburg, S.; van Oevelen, P.; Robock, A.; Jackson, T.

    2011-05-01

    In situ measurements of soil moisture are invaluable for calibrating and validating land surface models and satellite-based soil moisture retrievals. In addition, long-term time series of in situ soil moisture measurements themselves can reveal trends in the water cycle related to climate or land cover change. Nevertheless, on a worldwide basis the number of meteorological networks and stations measuring soil moisture, in particular on a continuous basis, is still limited and the data they provide lack standardization of technique and protocol. To overcome many of these limitations, the International Soil Moisture Network (ISMN; http://www.ipf.tuwien.ac.at/insitu) was initiated to serve as a centralized data hosting facility where globally available in situ soil moisture measurements from operational networks and validation campaigns are collected, harmonized, and made available to users. Data collecting networks share their soil moisture datasets with the ISMN on a voluntary and no-cost basis. Incoming soil moisture data are automatically transformed into common volumetric soil moisture units and checked for outliers and implausible values. Apart from soil water measurements from different depths, important metadata and meteorological variables (e.g., precipitation and soil temperature) are stored in the database. These will assist the user in correctly interpreting the soil moisture data. The database is queried through a graphical user interface while output of data selected for download is provided according to common standards for data and metadata. Currently (status May 2011), the ISMN contains data of 19 networks and more than 500 stations located in North America, Europe, Asia, and Australia. The time period spanned by the entire database runs from 1952 until the present, although most datasets have originated during the last decade. The database is rapidly expanding, which means that both the

  9. Gravity changes, soil moisture and data assimilation

    NASA Astrophysics Data System (ADS)

    Walker, J.; Grayson, R.; Rodell, M.; Ellet, K.

    2003-04-01

    Remote sensing holds promise for near-surface soil moisture and snow mapping, but current techniques do not directly resolve the deeper soil moisture or groundwater. The benefits that would arise from improved monitoring of variations in terrestrial water storage are numerous. The year 2002 saw the launch of NASA's Gravity Recovery And Climate Experiment (GRACE) satellites, which are mapping the Earth's gravity field at such a high level of precision that we expect to be able to infer changes in terrestrial water storage (soil moisture, groundwater, snow, ice, lake, river and vegetation). The project described here has three distinct yet inter-linked components that all leverage off the same ground-based monitoring and land surface modelling framework. These components are: (i) field validation of a relationship between soil moisture and changes in the Earth's gravity field, from ground- and satellite-based measurements of changes in gravity; (ii) development of a modelling framework for the assimilation of gravity data to constrain land surface model predictions of soil moisture content (such a framework enables the downscaling and disaggregation of low spatial (500 km) and temporal (monthly) resolution measurements of gravity change to finer spatial and temporal resolutions); and (iii) further refining the downscaling and disaggregation of space-borne gravity measurements by making use of other remotely sensed information, such as the higher spatial (25 km) and temporal (daily) resolution remotely sensed near-surface soil moisture measurements from the Advanced Microwave Scanning Radiometer (AMSR) instruments on Aqua and ADEOS II. The important field work required by this project will be in the Murrumbidgee Catchment, Australia, where an extensive soil moisture monitoring program by the University of Melbourne is already in place. We will further enhance the current monitoring network by the addition of groundwater wells and additional soil moisture sites. Ground

  10. Multispectral determination of soil moisture. [Guymon, Oklahoma

    NASA Technical Reports Server (NTRS)

    Estes, J. E.; Simonett, D. S. (Principal Investigator); Hajic, E. J.; Blanchard, B. J.

    1980-01-01

    The edited Guymon soil moisture data collected on August 2, 5, 14, 17, 1978 were grouped into four field cover types for statistical analysis. These are the bare, milo with rows parallel to field of view, milo with rows perpendicular to field of view and alfalfa cover groups. There are 37, 22, 24 and 14 observations respectively in each group for each sensor channel and each soil moisture layer. A subset of these data called the 'five cover set' (VEG5) limited the scatterometer data to the 15 deg look angle and was used to determine discriminant functions and combined group regressions.

  11. Soil Moisture Active Passive (SMAP) Media Briefing

    NASA Image and Video Library

    2015-01-09

    Dara Entekhabi, SMAP science team lead, Massachusetts Institute of Technology, center, speaks during a briefing about the upcoming launch of the Soil Moisture Active Passive (SMAP) mission, Thursday, Jan. 08, 2015, at NASA Headquarters in Washington DC. The mission is scheduled for a Jan. 29 launch from Vandenberg Air Force Base in California, and will provide the most accurate, highest-resolution global measurements of soil moisture ever obtained from space. The data will be used to enhance scientists' understanding of the processes that link Earth's water, energy and carbon cycles. Photo Credit: (NASA/Aubrey Gemignani)

  12. Soil Moisture Active Passive (SMAP) Media Briefing

    NASA Image and Video Library

    2015-01-09

    Dara Entekhabi, SMAP science team lead, Massachusetts Institute of Technology, speaks during a briefing about the upcoming launch of the Soil Moisture Active Passive (SMAP) mission, Thursday, Jan. 08, 2015, at NASA Headquarters in Washington DC. The mission is scheduled for a Jan. 29 launch from Vandenberg Air Force Base in California, and will provide the most accurate, highest-resolution global measurements of soil moisture ever obtained from space. The data will be used to enhance scientists' understanding of the processes that link Earth's water, energy and carbon cycles. Photo Credit: (NASA/Aubrey Gemignani)

  13. Soil Moisture Active Passive (SMAP) Media Briefing

    NASA Image and Video Library

    2015-01-09

    Brad Doorn, SMAP applications lead, Science Mission Directorate’s Applied Sciences Program at NASA Headquarters speaks during a briefing about the upcoming launch of the Soil Moisture Active Passive (SMAP) mission, Thursday, Jan. 08, 2015, at NASA Headquarters in Washington DC. The mission is scheduled for a Jan. 29 launch from Vandenberg Air Force Base in California, and will provide the most accurate, highest-resolution global measurements of soil moisture ever obtained from space. The data will be used to enhance scientists' understanding of the processes that link Earth's water, energy and carbon cycles. Photo Credit: (NASA/Aubrey Gemignani)

  14. Soil Moisture Active Passive (SMAP) Media Briefing

    NASA Image and Video Library

    2015-01-09

    Christine Bonniksen, SMAP program executive with the Science Mission Directorate’s Earth Science Division at NASA Headquarters speaks during a briefing about the upcoming launch of the Soil Moisture Active Passive (SMAP) mission, Thursday, Jan. 08, 2015, at NASA Headquarters in Washington DC. The mission is scheduled for a Jan. 29 launch from Vandenberg Air Force Base in California, and will provide the most accurate, highest-resolution global measurements of soil moisture ever obtained from space. The data will be used to enhance scientists' understanding of the processes that link Earth's water, energy and carbon cycles. Photo Credit: (NASA/Aubrey Gemignani)

  15. Soil Moisture Active Passive (SMAP) Media Briefing

    NASA Image and Video Library

    2015-01-09

    Kent Kellogg, SMAP project manager at NASA’s Jet Propulsion Laboratory (JPL) in Pasadena, CA, speaks during a briefing about the upcoming launch of the Soil Moisture Active Passive (SMAP) mission, Thursday, Jan. 08, 2015, at NASA Headquarters in Washington DC. The mission is scheduled for a Jan. 29 launch from Vandenberg Air Force Base in California, and will provide the most accurate, highest-resolution global measurements of soil moisture ever obtained from space. The data will be used to enhance scientists' understanding of the processes that link Earth's water, energy and carbon cycles. Photo Credit: (NASA/Aubrey Gemignani)

  16. Investigating local controls on soil moisture temporal stability using an inverse modeling approach

    NASA Astrophysics Data System (ADS)

    Bogena, Heye; Qu, Wei; Huisman, Sander; Vereecken, Harry

    2013-04-01

    A better understanding of the temporal stability of soil moisture and its relation to local and nonlocal controls is a major challenge in modern hydrology. Both local controls, such as soil and vegetation properties, and non-local controls, such as topography and climate variability, affect soil moisture dynamics. Wireless sensor networks are becoming more readily available, which opens up opportunities to investigate spatial and temporal variability of soil moisture with unprecedented resolution. In this study, we employed the wireless sensor network SoilNet developed by the Forschungszentrum Jülich to investigate soil moisture variability of a grassland headwater catchment in Western Germany within the framework of the TERENO initiative. In particular, we investigated the effect of soil hydraulic parameters on the temporal stability of soil moisture. For this, the HYDRUS-1D code coupled with a global optimizer (DREAM) was used to inversely estimate Mualem-van Genuchten parameters from soil moisture observations at three depths under natural (transient) boundary conditions for 83 locations in the headwater catchment. On the basis of the optimized parameter sets, we then evaluated to which extent the variability in soil hydraulic conductivity, pore size distribution, air entry suction and soil depth between these 83 locations controlled the temporal stability of soil moisture, which was independently determined from the observed soil moisture data. It was found that the saturated hydraulic conductivity (Ks) was the most significant attribute to explain temporal stability of soil moisture as expressed by the mean relative difference (MRD).

  17. Historical climate controls soil respiration responses to current soil moisture.

    PubMed

    Hawkes, Christine V; Waring, Bonnie G; Rocca, Jennifer D; Kivlin, Stephanie N

    2017-06-13

    Ecosystem carbon losses from soil microbial respiration are a key component of global carbon cycling, resulting in the transfer of 40-70 Pg carbon from soil to the atmosphere each year. Because these microbial processes can feed back to climate change, understanding respiration responses to environmental factors is necessary for improved projections. We focus on respiration responses to soil moisture, which remain unresolved in ecosystem models. A common assumption of large-scale models is that soil microorganisms respond to moisture in the same way, regardless of location or climate. Here, we show that soil respiration is constrained by historical climate. We find that historical rainfall controls both the moisture dependence and sensitivity of respiration. Moisture sensitivity, defined as the slope of respiration vs. moisture, increased fourfold across a 480-mm rainfall gradient, resulting in twofold greater carbon loss on average in historically wetter soils compared with historically drier soils. The respiration-moisture relationship was resistant to environmental change in field common gardens and field rainfall manipulations, supporting a persistent effect of historical climate on microbial respiration. Based on these results, predicting future carbon cycling with climate change will require an understanding of the spatial variation and temporal lags in microbial responses created by historical rainfall.

  18. Historical climate controls soil respiration responses to current soil moisture

    PubMed Central

    Waring, Bonnie G.; Rocca, Jennifer D.; Kivlin, Stephanie N.

    2017-01-01

    Ecosystem carbon losses from soil microbial respiration are a key component of global carbon cycling, resulting in the transfer of 40–70 Pg carbon from soil to the atmosphere each year. Because these microbial processes can feed back to climate change, understanding respiration responses to environmental factors is necessary for improved projections. We focus on respiration responses to soil moisture, which remain unresolved in ecosystem models. A common assumption of large-scale models is that soil microorganisms respond to moisture in the same way, regardless of location or climate. Here, we show that soil respiration is constrained by historical climate. We find that historical rainfall controls both the moisture dependence and sensitivity of respiration. Moisture sensitivity, defined as the slope of respiration vs. moisture, increased fourfold across a 480-mm rainfall gradient, resulting in twofold greater carbon loss on average in historically wetter soils compared with historically drier soils. The respiration–moisture relationship was resistant to environmental change in field common gardens and field rainfall manipulations, supporting a persistent effect of historical climate on microbial respiration. Based on these results, predicting future carbon cycling with climate change will require an understanding of the spatial variation and temporal lags in microbial responses created by historical rainfall. PMID:28559315

  19. Mode Decomposition Methods for Soil Moisture Prediction

    NASA Astrophysics Data System (ADS)

    Jana, R. B.; Efendiev, Y. R.; Mohanty, B.

    2014-12-01

    Lack of reliable, well-distributed, long-term datasets for model validation is a bottle-neck for most exercises in soil moisture analysis and prediction. Understanding what factors drive soil hydrological processes at different scales and their variability is very critical to further our ability to model the various components of the hydrologic cycle more accurately. For this, a comprehensive dataset with measurements across scales is very necessary. Intensive fine-resolution sampling of soil moisture over extended periods of time is financially and logistically prohibitive. Installation of a few long term monitoring stations is also expensive, and needs to be situated at critical locations. The concept of Time Stable Locations has been in use for some time now to find locations that reflect the mean values for the soil moisture across the watershed under all wetness conditions. However, the soil moisture variability across the watershed is lost when measuring at only time stable locations. We present here a study using techniques such as Dynamic Mode Decomposition (DMD) and Discrete Empirical Interpolation Method (DEIM) that extends the concept of time stable locations to arrive at locations that provide not simply the average soil moisture values for the watershed, but also those that can help re-capture the dynamics across all locations in the watershed. As with the time stability, the initial analysis is dependent on an intensive sampling history. The DMD/DEIM method is an application of model reduction techniques for non-linearly related measurements. Using this technique, we are able to determine the number of sampling points that would be required for a given accuracy of prediction across the watershed, and the location of those points. Locations with higher energetics in the basis domain are chosen first. We present case studies across watersheds in the US and India. The technique can be applied to other hydro-climates easily.

  20. Implementation of surface soil moisture data assimilation with watershed scale distributed hydrological model

    USDA-ARS?s Scientific Manuscript database

    This paper aims to investigate how surface soil moisture data assimilation affects each hydrologic process and how spatially varying inputs affect the potential capability of surface soil moisture assimilation at the watershed scale. The Ensemble Kalman Filter (EnKF) is coupled with a watershed scal...

  1. The Impact of Rainfall on Soil Moisture Dynamics in a Foggy Desert

    PubMed Central

    Li, Bonan; Wang, Lixin; Kaseke, Kudzai F.; Li, Lin; Seely, Mary K.

    2016-01-01

    Soil moisture is a key variable in dryland ecosystems since it determines the occurrence and duration of vegetation water stress and affects the development of weather patterns including rainfall. However, the lack of ground observations of soil moisture and rainfall dynamics in many drylands has long been a major obstacle in understanding ecohydrological processes in these ecosystems. It is also uncertain to what extent rainfall controls soil moisture dynamics in fog dominated dryland systems. To this end, in this study, twelve to nineteen months’ continuous daily records of rainfall and soil moisture (from January 2014 to August 2015) obtained from three sites (one sand dune site and two gravel plain sites) in the Namib Desert are reported. A process-based model simulating the stochastic soil moisture dynamics in water-limited systems was used to study the relationships between soil moisture and rainfall dynamics. Model sensitivity in response to different soil and vegetation parameters under diverse soil textures was also investigated. Our field observations showed that surface soil moisture dynamics generally follow rainfall patterns at the two gravel plain sites, whereas soil moisture dynamics in the sand dune site did not show a significant relationship with rainfall pattern. The modeling results suggested that most of the soil moisture dynamics can be simulated except the daily fluctuations, which may require a modification of the model structure to include non-rainfall components. Sensitivity analyses suggested that soil hygroscopic point (sh) and field capacity (sfc) were two main parameters controlling soil moisture output, though permanent wilting point (sw) was also very sensitive under the parameter setting of sand dune (Gobabeb) and gravel plain (Kleinberg). Overall, the modeling results were not sensitive to the parameters in non-bounded group (e.g., soil hydraulic conductivity (Ks) and soil porosity (n)). Field observations, stochastic modeling

  2. The Impact of Rainfall on Soil Moisture Dynamics in a Foggy Desert.

    PubMed

    Li, Bonan; Wang, Lixin; Kaseke, Kudzai F; Li, Lin; Seely, Mary K

    2016-01-01

    Soil moisture is a key variable in dryland ecosystems since it determines the occurrence and duration of vegetation water stress and affects the development of weather patterns including rainfall. However, the lack of ground observations of soil moisture and rainfall dynamics in many drylands has long been a major obstacle in understanding ecohydrological processes in these ecosystems. It is also uncertain to what extent rainfall controls soil moisture dynamics in fog dominated dryland systems. To this end, in this study, twelve to nineteen months' continuous daily records of rainfall and soil moisture (from January 2014 to August 2015) obtained from three sites (one sand dune site and two gravel plain sites) in the Namib Desert are reported. A process-based model simulating the stochastic soil moisture dynamics in water-limited systems was used to study the relationships between soil moisture and rainfall dynamics. Model sensitivity in response to different soil and vegetation parameters under diverse soil textures was also investigated. Our field observations showed that surface soil moisture dynamics generally follow rainfall patterns at the two gravel plain sites, whereas soil moisture dynamics in the sand dune site did not show a significant relationship with rainfall pattern. The modeling results suggested that most of the soil moisture dynamics can be simulated except the daily fluctuations, which may require a modification of the model structure to include non-rainfall components. Sensitivity analyses suggested that soil hygroscopic point (sh) and field capacity (sfc) were two main parameters controlling soil moisture output, though permanent wilting point (sw) was also very sensitive under the parameter setting of sand dune (Gobabeb) and gravel plain (Kleinberg). Overall, the modeling results were not sensitive to the parameters in non-bounded group (e.g., soil hydraulic conductivity (Ks) and soil porosity (n)). Field observations, stochastic modeling

  3. SMAP validation of soil moisture products

    USDA-ARS?s Scientific Manuscript database

    The Soil Moisture Active Passive (SMAP) satellite will be launched by the National Aeronautics and Space Administration in October 2014. SMAP will also incorporate a rigorous calibration and validation program that will support algorithm refinement and provide users with information on the accuracy ...

  4. Estimating Subcanopy Soil Moisture with RADAR

    NASA Technical Reports Server (NTRS)

    Moghaddam, M.; Saatchi, S.; Cuenca, R. H.

    1998-01-01

    The subcanopy soil moisture of a boreal old jack pine forest is estimated using polarimetric L- and P-band AIRSAR data. Model simulations have shown that for this stand, the principal scattering mechanism responsible for radar backscatter is the double-bounce mechanism between the tree trunks and the ground.

  5. Soil Moisture Remote Sensing: Status and Outlook

    USDA-ARS?s Scientific Manuscript database

    Satellite-based passive microwave sensors have been available for thirty years and provide the basis for soil moisture monitoring and mapping. The approach has reached a level of maturity that is now limited primarily by technology and funding. This is a result of extensive research and development ...

  6. Soil moisture and temperature algorithms and validation

    USDA-ARS?s Scientific Manuscript database

    Passive microwave remote sensing of soil moisture has matured over the past decade as a result of the Advanced Microwave Scanning Radiometer (AMSR) program of JAXA. This program has resulted in improved algorithms that have been supported by rigorous validation. Access to the products and the valida...

  7. High-Resolution Global Soil Moisture Map

    NASA Image and Video Library

    2015-05-19

    High-resolution global soil moisture map from NASA SMAP combined radar and radiometer instruments, acquired between May 4 and May 11, 2015 during SMAP commissioning phase. The map has a resolution of 5.6 miles (9 kilometers). The data gap is due to turning the instruments on and off during testing. http://photojournal.jpl.nasa.gov/catalog/PIA19337

  8. AMSR2 Soil Moisture Product Validation

    NASA Technical Reports Server (NTRS)

    Bindlish, R.; Jackson, T.; Cosh, M.; Koike, T.; Fuiji, X.; de Jeu, R.; Chan, S.; Asanuma, J.; Berg, A.; Bosch, D.; hide

    2017-01-01

    The Advanced Microwave Scanning Radiometer 2 (AMSR2) is part of the Global Change Observation Mission-Water (GCOM-W) mission. AMSR2 fills the void left by the loss of the Advanced Microwave Scanning Radiometer Earth Observing System (AMSR-E) after almost 10 years. Both missions provide brightness temperature observations that are used to retrieve soil moisture. Merging AMSR-E and AMSR2 will help build a consistent long-term dataset. Before tackling the integration of AMSR-E and AMSR2 it is necessary to conduct a thorough validation and assessment of the AMSR2 soil moisture products. This study focuses on validation of the AMSR2 soil moisture products by comparison with in situ reference data from a set of core validation sites. Three products that rely on different algorithms were evaluated; the JAXA Soil Moisture Algorithm (JAXA), the Land Parameter Retrieval Model (LPRM), and the Single Channel Algorithm (SCA). Results indicate that overall the SCA has the best performance based upon the metrics considered.

  9. Characterization of Soil Moisture Level for Rice and Maize Crops using GSM Shield and Arduino Microcontroller

    NASA Astrophysics Data System (ADS)

    Gines, G. A.; Bea, J. G.; Palaoag, T. D.

    2018-03-01

    Soil serves a medium for plants growth. One factor that affects soil moisture is drought. Drought has been a major cause of agricultural disaster. Agricultural drought is said to occur when soil moisture is insufficient to meet crop water requirements, resulting in yield losses. In this research, it aimed to characterize soil moisture level for Rice and Maize Crops using Arduino and applying fuzzy logic. System architecture for soil moisture sensor and water pump were the basis in developing the equipment. The data gathered was characterized by applying fuzzy logic. Based on the results, applying fuzzy logic in validating the characterization of soil moisture level for Rice and Maize crops is accurate as attested by the experts. This will help the farmers in monitoring the soil moisture level of the Rice and Maize crops.

  10. Soil Moisture-Atmosphere Feedbacks on Atmospheric Tracers: The Effects of Soil Moisture on Precipitation and Near-Surface Chemistry

    NASA Astrophysics Data System (ADS)

    Tawfik, Ahmed B.

    The atmospheric component is described by rapid fluctuations in typical state variables, such as temperature and water vapor, on timescales of hours to days and the land component evolves on daily to yearly timescales. This dissertation examines the connection between soil moisture and atmospheric tracers under varying degrees of soil moisture-atmosphere coupling. Land-atmosphere coupling is defined over the United States using a regional climate model. A newly examined soil moisture-precipitation feedback is identified for winter months extending the previous summer feedback to colder temperature climates. This feedback is driven by the freezing and thawing of soil moisture, leading to coupled land-atmosphere conditions near the freezing line. Soil moisture can also affect the composition of the troposphere through modifying biogenic emissions of isoprene (C5H8). A novel first-order Taylor series decomposition indicates that isoprene emissions are jointly driven by temperature and soil moisture in models. These compounds are important precursors for ozone formation, an air pollutant and a short-lived forcing agent for climate. A mechanistic description of commonly observed relationships between ground-level ozone and meteorology is presented using the concept of soil moisture-temperature coupling regimes. The extent of surface drying was found to be a better predictor of ozone concentrations than temperature or humidity for the Eastern U.S. This relationship is evaluated in a coupled regional chemistry-climate model under several land-atmosphere coupling and isoprene emissions cases. The coupled chemistry-climate model can reproduce the observed soil moisture-temperature coupling pattern, yet modeled ozone is insensitive to changes in meteorology due to the balance between isoprene and the primary atmospheric oxidant, the hydroxyl radical (OH). Overall, this work highlights the importance of soil moisture-atmosphere coupling for previously neglected cold climate

  11. Plan of research for integrated soil moisture studies. Recommendations of the Soil Moisture Working Group

    NASA Technical Reports Server (NTRS)

    1980-01-01

    Soil moisture information is a potentially powerful tool for applications in agriculture, water resources, and climate. At present, it is difficult for users of this information to clearly define their needs in terms of accuracy, resolution and frequency because of the current sparsity of data. A plan is described for defining and conducting an integrated and coordinated research effort to develop and refine remote sensing techniques which will determine spatial and temporal variations of soil moisture and to utilize soil moisture information in support of agricultural, water resources, and climate applications. The soil moisture requirements of these three different application areas were reviewed in relation to each other so that one plan covering the three areas could be formulated. Four subgroups were established to write and compile the plan, namely models, ground-based studies, aircraft experiments, and spacecraft missions.

  12. Effect of management and soil moisture regimes on wetland soils total carbon and nitrogen in Tanzania

    NASA Astrophysics Data System (ADS)

    Kamiri, Hellen; Kreye, Christine; Becker, Mathias

    2013-04-01

    Wetland soils play an important role as storage compartments for water, carbon and nutrients. These soils implies various conditions, depending on the water regimes that affect several important microbial and physical-chemical processes which in turn influence the transformation of organic and inorganic components of nitrogen, carbon, soil acidity and other nutrients. Particularly, soil carbon and nitrogen play an important role in determining the productivity of a soil whereas management practices could determine the rate and magnitude of nutrient turnover. A study was carried out in a floodplain wetland planted with rice in North-west Tanzania- East Africa to determine the effects of different management practices and soil water regimes on paddy soil organic carbon and nitrogen. Four management treatments were compared: (i) control (non weeded plots); (ii) weeded plots; (iii) N fertilized plots, and (iv) non-cropped (non weeded plots). Two soil moisture regimes included soil under field capacity (rainfed conditions) and continuous water logging compared side-by-side. Soil were sampled at the start and end of the rice cropping seasons from the two fields differentiated by moisture regimes during the wet season 2012. The soils differed in the total organic carbon and nitrogen between the treatments. Soil management including weeding and fertilization is seen to affect soil carbon and nitrogen regardless of the soil moisture conditions. Particularly, the padddy soils were higher in the total organic carbon under continuous water logged field. These findings are preliminary and a more complete understanding of the relationships between management and soil moisture on the temporal changes of soil properties is required before making informed decisions on future wetland soil carbon and nitrogen dynamics. Keywords: Management, nitrogen, paddy soil, total carbon, Tanzania,

  13. Spatio-temporal Root Zone Soil Moisture Estimation for Indo - Gangetic Basin from Satellite Derived (AMSR-2 and SMOS) Surface Soil Moisture

    NASA Astrophysics Data System (ADS)

    Sure, A.; Dikshit, O.

    2017-12-01

    Root zone soil moisture (RZSM) is an important element in hydrology and agriculture. The estimation of RZSM provides insight in selecting the appropriate crops for specific soil conditions (soil type, bulk density, etc.). RZSM governs various vadose zone phenomena and subsequently affects the groundwater processes. With various satellite sensors dedicated to estimating surface soil moisture at different spatial and temporal resolutions, estimation of soil moisture at root zone level for Indo - Gangetic basin which inherits complex heterogeneous environment, is quite challenging. This study aims at estimating RZSM and understand its variation at the level of Indo - Gangetic basin with changing land use/land cover, topography, crop cycles, soil properties, temperature and precipitation patterns using two satellite derived soil moisture datasets operating at distinct frequencies with different principles of acquisition. Two surface soil moisture datasets are derived from AMSR-2 (6.9 GHz - `C' Band) and SMOS (1.4 GHz - `L' band) passive microwave sensors with coarse spatial resolution. The Soil Water Index (SWI), accounting for soil moisture from the surface, is derived by considering a theoretical two-layered water balance model and contributes in ascertaining soil moisture at the vadose zone. This index is evaluated against the widely used modelled soil moisture dataset of GLDAS - NOAH, version 2.1. This research enhances the domain of utilising the modelled soil moisture dataset, wherever the ground dataset is unavailable. The coupling between the surface soil moisture and RZSM is analysed for two years (2015-16), by defining a parameter T, the characteristic time length. The study demonstrates that deriving an optimal value of T for estimating SWI at a certain location is a function of various factors such as land, meteorological, and agricultural characteristics.

  14. Surface Soil Moisture Estimates Across China Based on Multi-satellite Observations and A Soil Moisture Model

    NASA Astrophysics Data System (ADS)

    Zhang, Ke; Yang, Tao; Ye, Jinyin; Li, Zhijia; Yu, Zhongbo

    2017-04-01

    Soil moisture is a key variable that regulates exchanges of water and energy between land surface and atmosphere. Soil moisture retrievals based on microwave satellite remote sensing have made it possible to estimate global surface (up to about 10 cm in depth) soil moisture routinely. Although there are many satellites operating, including NASA's Soil Moisture Acitive Passive mission (SMAP), ESA's Soil Moisture and Ocean Salinity mission (SMOS), JAXA's Advanced Microwave Scanning Radiometer 2 mission (AMSR2), and China's Fengyun (FY) missions, key differences exist between different satellite-based soil moisture products. In this study, we applied a single-channel soil moisture retrieval model forced by multiple sources of satellite brightness temperature observations to estimate consistent daily surface soil moisture across China at a spatial resolution of 25 km. By utilizing observations from multiple satellites, we are able to estimate daily soil moisture across the whole domain of China. We further developed a daily soil moisture accounting model and applied it to downscale the 25-km satellite-based soil moisture to 5 km. By comparing our estimated soil moisture with observations from a dense observation network implemented in Anhui Province, China, our estimated soil moisture results show a reasonably good agreement with the observations (RMSE < 0.1 and r > 0.8).

  15. Soil moisture mapping for aquarius

    USDA-ARS?s Scientific Manuscript database

    Aquarius is the first satellite to provide both passive and active L-band observations of the Earth. In addition, the instruments on Satelite de Aplicaciones Cientificas-D (SAC-D) provide complementary information for analysis and retrieval algorithms. Our research focuses on the retrieval of soil m...

  16. SoilNet - A Zigbee based soil moisture sensor network

    NASA Astrophysics Data System (ADS)

    Bogena, H. R.; Weuthen, A.; Rosenbaum, U.; Huisman, J. A.; Vereecken, H.

    2007-12-01

    Soil moisture plays a key role in partitioning water and energy fluxes, in providing moisture to the atmosphere for precipitation, and controlling the pattern of groundwater recharge. Large-scale soil moisture variability is driven by variation of precipitation and radiation in space and time. At local scales, land cover, soil conditions, and topography act to redistribute soil moisture. Despite the importance of soil moisture, it is not yet measured in an operational way, e.g. for a better prediction of hydrological and surface energy fluxes (e.g. runoff, latent heat) at larger scales and in the framework of the development of early warning systems (e.g. flood forecasting) and the management of irrigation systems. The SoilNet project aims to develop a sensor network for the near real-time monitoring of soil moisture changes at high spatial and temporal resolution on the basis of the new low-cost ZigBee radio network that operates on top of the IEEE 802.15.4 standard. The sensor network consists of soil moisture sensors attached to end devices by cables, router devices and a coordinator device. The end devices are buried in the soil and linked wirelessly with nearby aboveground router devices. This ZigBee wireless sensor network design considers channel errors, delays, packet losses, and power and topology constraints. In order to conserve battery power, a reactive routing protocol is used that determines a new route only when it is required. The sensor network is also able to react to external influences, e.g. such as rainfall occurrences. The SoilNet communicator, routing and end devices have been developed by the Forschungszentrum Juelich and will be marketed through external companies. We will present first results of experiments to verify network stability and the accuracy of the soil moisture sensors. Simultaneously, we have developed a data management and visualisation system. We tested the wireless network on a 100 by 100 meter forest plot equipped with 25

  17. Distributed Soil Moisture Estimation in a Mountainous Semiarid Basin: Constraining Soil Parameter Uncertainty through Field Studies

    NASA Astrophysics Data System (ADS)

    Yatheendradas, S.; Vivoni, E.

    2007-12-01

    A common practice in distributed hydrological modeling is to assign soil hydraulic properties based on coarse textural datasets. For semiarid regions with poor soil information, the performance of a model can be severely constrained due to the high model sensitivity to near-surface soil characteristics. Neglecting the uncertainty in soil hydraulic properties, their spatial variation and their naturally-occurring horizonation can potentially affect the modeled hydrological response. In this study, we investigate such effects using the TIN-based Real-time Integrated Basin Simulator (tRIBS) applied to the mid-sized (100 km2) Sierra Los Locos watershed in northern Sonora, Mexico. The Sierra Los Locos basin is characterized by complex mountainous terrain leading to topographic organization of soil characteristics and ecosystem distributions. We focus on simulations during the 2004 North American Monsoon Experiment (NAME) when intensive soil moisture measurements and aircraft- based soil moisture retrievals are available in the basin. Our experiments focus on soil moisture comparisons at the point, topographic transect and basin scales using a range of different soil characterizations. We compare the distributed soil moisture estimates obtained using (1) a deterministic simulation based on soil texture from coarse soil maps, (2) a set of ensemble simulations that capture soil parameter uncertainty and their spatial distribution, and (3) a set of simulations that conditions the ensemble on recent soil profile measurements. Uncertainties considered in near-surface soil characterization provide insights into their influence on the modeled uncertainty, into the value of soil profile observations, and into effective use of on-going field observations for constraining the soil moisture response uncertainty.

  18. Preliminary assessment of soil moisture over vegetation

    NASA Technical Reports Server (NTRS)

    Carlson, T. N.

    1986-01-01

    Modeling of surface energy fluxes was combined with in-situ measurement of surface parameters, specifically the surface sensible heat flux and the substrate soil moisture. A vegetation component was incorporated in the atmospheric/substrate model and subsequently showed that fluxes over vegetation can be very much different than those over bare soil for a given surface-air temperature difference. The temperature signatures measured by a satellite or airborne radiometer should be interpreted in conjunction with surface measurements of modeled parameters. Paradoxically, analyses of the large-scale distribution of soil moisture availability shows that there is a very high correlation between antecedent precipitation and inferred surface moisture availability, even when no specific vegetation parameterization is used in the boundary layer model. Preparatory work was begun in streamlining the present boundary layer model, developing better algorithms for relating surface temperatures to substrate moisture, preparing for participation in the French HAPEX experiment, and analyzing aircraft microwave and radiometric surface temperature data for the 1983 French Beauce experiments.

  19. Downscaled soil moisture from SMAP evaluated using high density observations

    USDA-ARS?s Scientific Manuscript database

    Recently, a soil moisture downscaling algorithm based on a regression relationship between daily temperature changes and daily average soil moisture was developed to produce an enhanced spatial resolution on soil moisture product for the Advanced Microwave Scanning Radiometer–EOS (AMSR-E) satellite ...

  20. Soil moisture inferences from thermal infrared measurements of vegetation temperatures

    NASA Technical Reports Server (NTRS)

    Jackson, R. D. (Principal Investigator)

    1981-01-01

    Thermal infrared measurements of wheat (Triticum durum) canopy temperatures were used in a crop water stress index to infer root zone soil moisture. Results indicated that one time plant temperature measurement cannot produce precise estimates of root zone soil moisture due to complicating plant factors. Plant temperature measurements do yield useful qualitative information concerning soil moisture and plant condition.

  1. Data assimilation to extract soil moisture information from SMAP observations

    USDA-ARS?s Scientific Manuscript database

    This study compares different methods to extract soil moisture information through the assimilation of Soil Moisture Active Passive (SMAP) observations. Neural Network(NN) and physically-based SMAP soil moisture retrievals were assimilated into the NASA Catchment model over the contiguous United Sta...

  2. Measuring Soil Moisture in Skeletal Soils Using a COSMOS Rover

    NASA Astrophysics Data System (ADS)

    Medina, C.; Neely, H.; Desilets, D.; Mohanty, B.; Moore, G. W.

    2017-12-01

    The presence of coarse fragments directly influences the volumetric water content of the soil. Current surface soil moisture sensors often do not account for the presence of coarse fragments, and little research has been done to calibrate these sensors under such conditions. The cosmic-ray soil moisture observation system (COSMOS) rover is a passive, non-invasive surface soil moisture sensor with a footprint greater than 100 m. Despite its potential, the COSMOS rover has yet to be validated in skeletal soils. The goal of this study was to validate measurements of surface soil moisture as taken by a COSMOS rover on a Texas skeletal soil. Data was collected for two soils, a Marfla clay loam and Chinati-Boracho-Berrend association, in West Texas. Three levels of data were collected: 1) COSMOS surveys at three different soil moistures, 2) electrical conductivity surveys within those COSMOS surveys, and 3) ground-truth measurements. Surveys with the COSMOS rover covered an 8000-h area and were taken both after large rain events (>2") and a long dry period. Within the COSMOS surveys, the EM38-MK2 was used to estimate the spatial distribution of coarse fragments in the soil around two COSMOS points. Ground truth measurements included coarse fragment mass and volume, bulk density, and water content at 3 locations within each EM38 survey. Ground-truth measurements were weighted using EM38 data, and COSMOS measurements were validated by their distance from the samples. There was a decrease in water content as the percent volume of coarse fragment increased. COSMOS estimations responded to both changes in coarse fragment percent volume and the ground-truth volumetric water content. Further research will focus on creating digital soil maps using landform data and water content estimations from the COSMOS rover.

  3. Inference of soil hydrologic parameters from electronic soil moisture records

    USDA-ARS?s Scientific Manuscript database

    Soil moisture is an important control on hydrologic function, as it governs vertical fluxes from and to the atmosphere, groundwater recharge, and lateral fluxes through the soil. Historically, the traditional model parameters of saturation, field capacity, and permanent wilting point have been deter...

  4. [Characteristics of soil moisture in artificial impermeable layers].

    PubMed

    Suo, Gai-Di; Xie, Yong-Sheng; Tian, Fei; Chuai, Jun-Feng; Jing, Min-Xiao

    2014-09-01

    For the problem of low water and fertilizer use efficiency caused by nitrate nitrogen lea- ching into deep soil layer and soil desiccation in dryland apple orchard, characteristics of soil moisture were investigated by means of hand tamping in order to find a new approach in improving the water and fertilizer use efficiency in the apple orchard. Two artificial impermeable layers of red clay and dark loessial soil were built in soil, with a thickness of 3 or 5 cm. Results showed that artificial impermeable layers with the two different thicknesses were effective in reducing or blocking water infiltration into soil and had higher seepage controlling efficiency. Seepage controlling efficiency for the red clay impermeable layer was better than that for the dark loessial soil impermeable layer. Among all the treatments, the red clay impermeable layer of 5 cm thickness had the highest bulk density, the lowest initial infiltration rate (0.033 mm · min(-1)) and stable infiltration rate (0.018 mm · min(-1)) among all treatments. After dry-wet alternation in summer and freezing-thawing cycle in winter, its physiochemical properties changed little. Increase in years did not affect stable infiltration rate of soil water. The red clay impermeable layer of 5 cm thickness could effectively increase soil moisture content in upper soil layer which was conducive to raise the water and nutrient use efficiency. The approach could be applied to the apple production of dryland orchard.

  5. Microwave Soil Moisture Retrieval Under Trees

    NASA Technical Reports Server (NTRS)

    O'Neill, P.; Lang, R.; Kurum, M.; Joseph, A.; Jackson, T.; Cosh, M.

    2008-01-01

    Soil moisture is recognized as an important component of the water, energy, and carbon cycles at the interface between the Earth's surface and atmosphere. Current baseline soil moisture retrieval algorithms for microwave space missions have been developed and validated only over grasslands, agricultural crops, and generally light to moderate vegetation. Tree areas have commonly been excluded from operational soil moisture retrieval plans due to the large expected impact of trees on masking the microwave response to the underlying soil moisture. Our understanding of the microwave properties of trees of various sizes and their effect on soil moisture retrieval algorithms at L band is presently limited, although research efforts are ongoing in Europe, the United States, and elsewhere to remedy this situation. As part of this research, a coordinated sequence of field measurements involving the ComRAD (for Combined Radar/Radiometer) active/passive microwave truck instrument system has been undertaken. Jointly developed and operated by NASA Goddard Space Flight Center and George Washington University, ComRAD consists of dual-polarized 1.4 GHz total-power radiometers (LH, LV) and a quad-polarized 1.25 GHz L band radar sharing a single parabolic dish antenna with a novel broadband stacked patch dual-polarized feed, a quad-polarized 4.75 GHz C band radar, and a single channel 10 GHz XHH radar. The instruments are deployed on a mobile truck with an 19-m hydraulic boom and share common control software; real-time calibrated signals, and the capability for automated data collection for unattended operation. Most microwave soil moisture retrieval algorithms developed for use at L band frequencies are based on the tau-omega model, a simplified zero-order radiative transfer approach where scattering is largely ignored and vegetation canopies are generally treated as a bulk attenuating layer. In this approach, vegetation effects are parameterized by tau and omega, the microwave

  6. Estimating Soil Moisture from Satellite Microwave Observations

    NASA Technical Reports Server (NTRS)

    Owe, M.; VandeGriend, A. A.; deJeu, R.; deVries, J.; Seyhan, E.

    1998-01-01

    Cooperative research in microwave remote sensing between the Hydrological Sciences Branch of the NASA Goddard Space Flight Center and the Earth Sciences Faculty of the Vrije Universiteit Amsterdam began with the Botswana Water and Energy Balance Experiment and has continued through a series of highly successful International Research Programs. The collaboration between these two research institutions has resulted in significant scientific achievements, most notably in the area of satellite-based microwave remote sensing of soil moisture. The Botswana Program was the first joint research initiative between these two institutions, and provided a unique data base which included historical data sets of Scanning Multifrequency Microwave Radiometer (SN4NM) data, climate information, and extensive soil moisture measurements over several large experimental sites in southeast Botswana. These data were the basis for the development of new approaches in physically-based inverse modelling of soil moisture from satellite microwave observations. Among the results from this study were quantitative estimates of vegetation transmission properties at microwave frequencies. A single polarization modelling approach which used horizontally polarized microwave observations combined with monthly composites of Normalized Difference Vegetation Index was developed, and yielded good results. After more precise field experimentation with a ground-based radiometer system, a dual-polarization approach was subsequently developed. This new approach realized significant improvements in soil moisture estimation by satellite. Results from the Botswana study were subsequently applied to a desertification monitoring study for the country of Spain within the framework of the European Community science research programs EFEDA and RESMEDES. A dual frequency approach with only microwave data was used for this application. The Microwave Polarization Difference Index (MPDI) was calculated from 37 GHz data

  7. A comparative study of the SMAP passive soil moisture product with existing satellite-based soil moisture products

    USDA-ARS?s Scientific Manuscript database

    NASA Soil Moisture Active Passive (SMAP) satellite mission was launched on January 31, 2015 to provide global mapping of high-resolution soil moisture and freeze thaw state every 2-3 days using an L-band (active) radar and an L-band (passive) radiometer. The radiometer-only soil moisture product (L2...

  8. Method for evaluating moisture tensions of soils using spectral data

    NASA Technical Reports Server (NTRS)

    Peterson, John B. (Inventor)

    1982-01-01

    A method is disclosed which permits evaluation of soil moisture utilizing remote sensing. Spectral measurements at a plurality of different wavelengths are taken with respect to sample soils and the bidirectional reflectance factor (BRF) measurements produced are submitted to regression analysis for development therefrom of predictable equations calculated for orderly relationships. Soil of unknown reflective and unknown soil moisture tension is thereafter analyzed for bidirectional reflectance and the resulting data utilized to determine the soil moisture tension of the soil as well as providing a prediction as to the bidirectional reflectance of the soil at other moisture tensions.

  9. Enhanced simulations of CH4 and CO2 production in permafrost-affected soils address soil moisture controls on anaerobic decomposition

    NASA Astrophysics Data System (ADS)

    Graham, D. E.; Zheng, J.; Moon, J. W.; Painter, S. L.; Thornton, P. E.; Gu, B.; Wullschleger, S. D.

    2017-12-01

    Rapid warming of Arctic ecosystems exposes soil organic carbon (SOC) to accelerated microbial decomposition, leading to increased emissions of carbon dioxide (CO2) and methane (CH4) that have a positive feedback on global warming. The magnitude, timing, and form of carbon release will depend not only on changes in temperature, but also on biogeochemical and hydrological properties of soils. In this synthesis study, we assessed the decomposability of thawed organic carbon from active layer soils and permafrost from the Barrow Environmental Observatory across different microtopographic positions under anoxic conditions. The main objectives of this study were to (i) examine environmental conditions and soil properties that control anaerobic carbon decomposition and carbon release (as both CO2 and CH4); (ii) develop a common set of parameters to simulate anaerobic CO2 and CH4 production; and (iii) evaluate uncertainties generated from representations of pH and temperature effects in the current model framework. A newly developed anaerobic carbon decomposition framework simulated incubation experiment results across a range of soil water contents. Anaerobic CO2 and CH4 production have different temperature and pH sensitivities, which are not well represented in current biogeochemical models. Distinct dynamics of CH4 production at -2° C suggest methanogen biomass and growth rate limit activity in these near-frozen soils, compared to warmer temperatures. Anaerobic CO2 production is well constrained by the model using data-informed labile carbon pool and fermentation rate initialization to accurately simulate its temperature sensitivity. On the other hand, CH4 production is controlled by water content, methanogenesis biomass, and the presence of alternative electron acceptors, producing a high temperature sensitivity with large uncertainties for methanogenesis. This set of environmental constraints to methanogenesis is likely to undergo drastic changes due to permafrost

  10. Land-atmosphere coupling and soil moisture memory contribute to long-term agricultural drought

    NASA Astrophysics Data System (ADS)

    Kumar, S.; Newman, M.; Lawrence, D. M.; Livneh, B.; Lombardozzi, D. L.

    2017-12-01

    We assessed the contribution of land-atmosphere coupling and soil moisture memory on long-term agricultural droughts in the US. We performed an ensemble of climate model simulations to study soil moisture dynamics under two atmospheric forcing scenarios: active and muted land-atmosphere coupling. Land-atmosphere coupling contributes to a 12% increase and 36% decrease in the decorrelation time scale of soil moisture anomalies in the US Great Plains and the Southwest, respectively. These differences in soil moisture memory affect the length and severity of modeled drought. Consequently, long-term droughts are 10% longer and 3% more severe in the Great Plains, and 15% shorter and 21% less severe in the Southwest. An analysis of Coupled Model Intercomparsion Project phase 5 data shows four fold uncertainty in soil moisture memory across models that strongly affects simulated long-term droughts and is potentially attributable to the differences in soil water storage capacity across models.

  11. Soil Moisture Active Passive (SMAP) Media Briefing

    NASA Image and Video Library

    2015-01-09

    Christine Bonniksen, SMAP program executive with the Science Mission Directorate’s Earth Science Division, NASA Headquarters, left, Kent Kellogg, SMAP project manager, NASA Jet Propulsion Laboratory (JPL), second from left, Dara Entekhabi, SMAP science team lead, Massachusetts Institute of Technology, second from right, and Brad Doorn, SMAP applications lead, Science Mission Directorate’s Applied Sciences Program, NASA Headquarters, right, are seen during a briefing about the upcoming launch of the Soil Moisture Active Passive (SMAP) mission, Thursday, Jan. 08, 2015, at NASA Headquarters in Washington DC. The mission is scheduled for a Jan. 29 launch from Vandenberg Air Force Base in California, and will provide the most accurate, highest-resolution global measurements of soil moisture ever obtained from space. The data will be used to enhance scientists' understanding of the processes that link Earth's water, energy and carbon cycles. Photo Credit: (NASA/Aubrey Gemignani)

  12. An overview of the measurements of soil moisture and modeling of moisture flux in FIFE

    NASA Technical Reports Server (NTRS)

    Wang, J. R.

    1992-01-01

    Measurements of soil moisture and calculations of moisture transfer in the soil medium and at the air-soil interface were performed over a 15-km by 15-km test site during FIFE in 1987 and 1989. The measurements included intensive soil moisture sampling at the ground level and surveys at aircraft altitudes by several passive and active microwave sensors as well as a gamma radiation device.

  13. Uncertainty Assessment of Space-Borne Passive Soil Moisture Retrievals

    NASA Technical Reports Server (NTRS)

    Quets, Jan; De Lannoy, Gabrielle; Reichle, Rolf; Cosh, Michael; van der Schalie, Robin; Wigneron, Jean-Pierre

    2017-01-01

    The uncertainty associated with passive soil moisture retrieval is hard to quantify, and known to be underlain by various, diverse, and complex causes. Factors affecting space-borne retrieved soil moisture estimation include: (i) the optimization or inversion method applied to the radiative transfer model (RTM), such as e.g. the Single Channel Algorithm (SCA), or the Land Parameter Retrieval Model (LPRM), (ii) the selection of the observed brightness temperatures (Tbs), e.g. polarization and incidence angle, (iii) the definition of the cost function and the impact of prior information in it, and (iv) the RTM parameterization (e.g. parameterizations officially used by the SMOS L2 and SMAP L2 retrieval products, ECMWF-based SMOS assimilation product, SMAP L4 assimilation product, and perturbations from those configurations). This study aims at disentangling the relative importance of the above-mentioned sources of uncertainty, by carrying out soil moisture retrieval experiments, using SMOS Tb observations in different settings, of which some are mentioned above. The ensemble uncertainties are evaluated at 11 reference CalVal sites, over a time period of more than 5 years. These experimental retrievals were inter-compared, and further confronted with in situ soil moisture measurements and operational SMOS L2 retrievals, using commonly used skill metrics to quantify the temporal uncertainty in the retrievals.

  14. NASA Soil Moisture Active Passive (SMAP) Applications

    NASA Astrophysics Data System (ADS)

    Orr, Barron; Moran, M. Susan; Escobar, Vanessa; Brown, Molly E.

    2014-05-01

    The launch of the NASA Soil Moisture Active Passive (SMAP) mission in 2014 will provide global soil moisture and freeze-thaw measurements at moderate resolution (9 km) with latency as short as 24 hours. The resolution, latency and global coverage of SMAP products will enable new applications in the fields of weather, climate, drought, flood, agricultural production, human health and national security. To prepare for launch, the SMAP mission has engaged more than 25 Early Adopters. Early Adopters are users who have a need for SMAP-like soil moisture or freeze-thaw data, and who agreed to apply their own resources to demonstrate the utility of SMAP data for their particular system or model. In turn, the SMAP mission agreed to provide Early Adopters with simulated SMAP data products and pre-launch calibration and validation data from SMAP field campaigns, modeling, and synergistic studies. The applied research underway by Early Adopters has provided fundamental knowledge of how SMAP data products can be scaled and integrated into users' policy, business and management activities to improve decision-making efforts. This presentation will cover SMAP applications including weather and climate forecasting, vehicle mobility estimation, quantification of greenhouse gas emissions, management of urban potable water supply, and prediction of crop yield. The presentation will end with a discussion of potential international applications with focus on the ESA/CEOS TIGER Initiative entitled "looking for water in Africa", the United Nations (UN) Convention to Combat Desertification (UNCCD) which carries a specific mandate focused on Africa, the UN Framework Convention on Climate Change (UNFCCC) which lists soil moisture as an Essential Climate Variable (ECV), and the UN Food and Agriculture Organization (FAO) which reported a food and nutrition crisis in the Sahel.

  15. New Physical Algorithms for Downscaling SMAP Soil Moisture

    NASA Astrophysics Data System (ADS)

    Sadeghi, M.; Ghafari, E.; Babaeian, E.; Davary, K.; Farid, A.; Jones, S. B.; Tuller, M.

    2017-12-01

    The NASA Soil Moisture Active Passive (SMAP) mission provides new means for estimation of surface soil moisture at the global scale. However, for many hydrological and agricultural applications the spatial SMAP resolution is too low. To address this scale issue we fused SMAP data with MODIS observations to generate soil moisture maps at 1-km spatial resolution. In course of this study we have improved several existing empirical algorithms and introduced a new physical approach for downscaling SMAP data. The universal triangle/trapezoid model was applied to relate soil moisture to optical/thermal observations such as NDVI, land surface temperature and surface reflectance. These algorithms were evaluated with in situ data measured at 5-cm depth. Our results demonstrate that downscaling SMAP soil moisture data based on physical indicators of soil moisture derived from the MODIS satellite leads to higher accuracy than that achievable with empirical downscaling algorithms. Keywords: Soil moisture, microwave data, downscaling, MODIS, triangle/trapezoid model.

  16. NASA Soil Moisture Data Products and Their Incorporation in DREAM

    NASA Technical Reports Server (NTRS)

    Blonski, Slawomir; Holland, Donald; Henderson, Vaneshette

    2005-01-01

    NASA provides soil moisture data products that include observations from the Advanced Microwave Scanning Radiometer on the Earth Observing System Aqua satellite, field measurements from the Soil Moisture Experiment campaigns, and model predictions from the Land Information System and the Goddard Earth Observing System Data Assimilation System. Incorporation of the NASA soil moisture products in the Dust Regional Atmospheric Model is possible through use of the satellite observations of soil moisture to set initial conditions for the dust simulations. An additional comparison of satellite soil moisture observations with mesoscale atmospheric dynamics modeling is recommended. Such a comparison would validate the use of NASA soil moisture data in applications and support acceptance of satellite soil moisture data assimilation in weather and climate modeling.

  17. Methods of measuring soil moisture in the field

    USGS Publications Warehouse

    Johnson, A.I.

    1962-01-01

    For centuries, the amount of moisture in the soil has been of interest in agriculture. The subject of soil moisture is also of great importance to the hydrologist, forester, and soils engineer. Much equipment and many methods have been developed to measure soil moisture under field conditions. This report discusses and evaluates the various methods for measurement of soil moisture and describes the equipment needed for each method. The advantages and disadvantages of each method are discussed and an extensive list of references is provided for those desiring to study the subject in more detail. The gravimetric method is concluded to be the most satisfactory method for most problems requiring onetime moisture-content data. The radioactive method is normally best for obtaining repeated measurements of soil moisture in place. It is concluded that all methods have some limitations and that the ideal method for measurement of soil moisture under field conditions has yet to be perfected.

  18. The impact of non-isothermal soil moisture transport on evaporation fluxes in a maize cropland

    NASA Astrophysics Data System (ADS)

    Shao, Wei; Coenders-Gerrits, Miriam; Judge, Jasmeet; Zeng, Yijian; Su, Ye

    2018-06-01

    The process of evaporation interacts with the soil, which has various comprehensive mechanisms. Multiphase flow models solve air, vapour, water, and heat transport equations to simulate non-isothermal soil moisture transport of both liquid water and vapor flow, but are only applied in non-vegetated soils. For (sparsely) vegetated soils often energy balance models are used, however these lack the detailed information on non-isothermal soil moisture transport. In this study we coupled a multiphase flow model with a two-layer energy balance model to study the impact of non-isothermal soil moisture transport on evaporation fluxes (i.e., interception, transpiration, and soil evaporation) for vegetated soils. The proposed model was implemented at an experimental agricultural site in Florida, US, covering an entire maize-growing season (67 days). As the crops grew, transpiration and interception became gradually dominated, while the fraction of soil evaporation dropped from 100% to less than 20%. The mechanisms of soil evaporation vary depending on the soil moisture content. After precipitation the soil moisture content increased, exfiltration of the liquid water flow could transport sufficient water to sustain evaporation from soil, and the soil vapor transport was not significant. However, after a sufficient dry-down period, the soil moisture content significantly reduced, and the soil vapour flow significantly contributed to the upward moisture transport in topmost soil. A sensitivity analysis found that the simulations of moisture content and temperature at the soil surface varied substantially when including the advective (i.e., advection and mechanical dispersion) vapour transport in simulation, including the mechanism of advective vapour transport decreased soil evaporation rate under wet condition, while vice versa under dry condition. The results showed that the formulation of advective soil vapor transport in a soil-vegetation-atmosphere transfer continuum can

  19. Assimilation of Passive and Active Microwave Soil Moisture Retrievals

    NASA Technical Reports Server (NTRS)

    Draper, C. S.; Reichle, R. H.; DeLannoy, G. J. M.; Liu, Q.

    2012-01-01

    Root-zone soil moisture is an important control over the partition of land surface energy and moisture, and the assimilation of remotely sensed near-surface soil moisture has been shown to improve model profile soil moisture [1]. To date, efforts to assimilate remotely sensed near-surface soil moisture at large scales have focused on soil moisture derived from the passive microwave Advanced Microwave Scanning Radiometer (AMSR-E) and the active Advanced Scatterometer (ASCAT; together with its predecessor on the European Remote Sensing satellites (ERS. The assimilation of passive and active microwave soil moisture observations has not yet been directly compared, and so this study compares the impact of assimilating ASCAT and AMSR-E soil moisture data, both separately and together. Since the soil moisture retrieval skill from active and passive microwave data is thought to differ according to surface characteristics [2], the impact of each assimilation on the model soil moisture skill is assessed according to land cover type, by comparison to in situ soil moisture observations.

  20. SMALT - Soil Moisture from Altimetry project

    NASA Astrophysics Data System (ADS)

    Smith, Richard; Benveniste, Jérôme; Dinardo, Salvatore; Lucas, Bruno Manuel; Berry, Philippa; Wagner, Wolfgang; Hahn, Sebastian; Egido, Alejandro

    Soil surface moisture is a key scientific parameter; however, it is extremely difficult to measure remotely, particularly in arid and semi-arid terrain. This paper outlines the development of a novel methodology to generate soil moisture estimates in these regions from multi-mission satellite radar altimetry. Key to this approach is the development of detailed DRy Earth ModelS (DREAMS), which encapsulate the detailed and intricate surface brightness variations over the Earth’s land surface, resulting from changes in surface roughness and composition. DREAMS have been created over a number of arid and semi-arid deserts worldwide to produce historical SMALT timeseries over soil moisture variation. These products are available in two formats - a high resolution track product which utilises the altimeter’s high frequency content alongtrack and a multi-looked 6” gridded product at facilitate easy comparison/integeration with other remote sensing techniques. An overview of the SMALT processing scheme, covering the progression of the data from altimeter sigma0 through to final soil moisture estimate, is included along with example SMALT products. Validation has been performed over a number of deserts by comparing SMALT products with other remote sensing techniques, results of the comparison between SMALT and Metop Warp 5.5 are presented here. Comparisons with other remote sensing techniques have been limited in scope due to differences in the operational aspects of the instruments, the restricted geographical coverage of the DREAMS and the low repeat temporal sampling rate of the altimeter. The potential to expand the SMALT technique into less arid areas has been investigated. Small-scale comparison with in-situ and GNSS-R data obtained by the LEiMON experimental campaign over Tuscany, where historical trends exist within both SMALT and SMC probe datasets. A qualitative analysis of unexpected backscatter characteristics in dedicated dry environments is performed

  1. Using satellite image data to estimate soil moisture

    NASA Astrophysics Data System (ADS)

    Chuang, Chi-Hung; Yu, Hwa-Lung

    2017-04-01

    Soil moisture is considered as an important parameter in various study fields, such as hydrology, phenology, and agriculture. In hydrology, soil moisture is an significant parameter to decide how much rainfall that will infiltrate into permeable layer and become groundwater resource. Although soil moisture is a critical role in many environmental studies, so far the measurement of soil moisture is using ground instrument such as electromagnetic soil moisture sensor. Use of ground instrumentation can directly obtain the information, but the instrument needs maintenance and consume manpower to operation. If we need wide range region information, ground instrumentation probably is not suitable. To measure wide region soil moisture information, we need other method to achieve this purpose. Satellite remote sensing techniques can obtain satellite image on Earth, this can be a way to solve the spatial restriction on instrument measurement. In this study, we used MODIS data to retrieve daily soil moisture pattern estimation, i.e., crop water stress index (cwsi), over the year of 2015. The estimations are compared with the observations at the soil moisture stations from Taiwan Bureau of soil and water conservation. Results show that the satellite remote sensing data can be helpful to the soil moisture estimation. Further analysis can be required to obtain the optimal parameters for soil moisture estimation in Taiwan.

  2. Microbiology and Moisture Uptake of Desert Soils

    NASA Astrophysics Data System (ADS)

    Kress, M. E.; Bryant, E. P.; Morgan, S. W.; Rech, S.; McKay, C. P.

    2005-12-01

    We have initiated an interdisciplinary study of the microbiology and water content of desert soils to better understand microbial activity in extreme arid environments. Water is the one constituent that no organism can live without; nevertheless, there are places on Earth with an annual rainfall near zero that do support microbial ecosystems. These hyperarid deserts (e.g. Atacama and the Antarctic Dry Valleys) are the closest terrestrial analogs to Mars, which is the subject of future exploration motivated by the search for life beyond Earth. We are modeling the moisture uptake by soils in hyperarid environments to quantify the environmental constraints that regulate the survival and growth of micro-organisms. Together with the studies of moisture uptake, we are also characterizing the microbial population in these soils using molecular and culturing methods. We are in the process of extracting DNA from these soils using MoBio extraction kits. This DNA will be used as a template to amplify bacterial and eukaryotic ribosomal DNA to determine the diversity of the microbial population. We also have been attempting to determine the density of organisms by culturing on one-half strength R2A agar. The long-range goal of this research is to identify special adaptations of terrestrial life that allow them to inhabit extreme arid environments, while simultaneously quantifying the environmental parameters that enforce limits on these organisms' growth and survival.

  3. Contributions of Precipitation and Soil Moisture Observations to the Skill of Soil Moisture Estimates in a Land Data Assimilation System

    NASA Technical Reports Server (NTRS)

    Reichle, Rolf H.; Liu, Qing; Bindlish, Rajat; Cosh, Michael H.; Crow, Wade T.; deJeu, Richard; DeLannoy, Gabrielle J. M.; Huffman, George J.; Jackson, Thomas J.

    2011-01-01

    The contributions of precipitation and soil moisture observations to the skill of soil moisture estimates from a land data assimilation system are assessed. Relative to baseline estimates from the Modern Era Retrospective-analysis for Research and Applications (MERRA), the study investigates soil moisture skill derived from (i) model forcing corrections based on large-scale, gauge- and satellite-based precipitation observations and (ii) assimilation of surface soil moisture retrievals from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E). Soil moisture skill is measured against in situ observations in the continental United States at 44 single-profile sites within the Soil Climate Analysis Network (SCAN) for which skillful AMSR-E retrievals are available and at four CalVal watersheds with high-quality distributed sensor networks that measure soil moisture at the scale of land model and satellite estimates. The average skill (in terms of the anomaly time series correlation coefficient R) of AMSR-E retrievals is R=0.39 versus SCAN and R=0.53 versus CalVal measurements. The skill of MERRA surface and root-zone soil moisture is R=0.42 and R=0.46, respectively, versus SCAN measurements, and MERRA surface moisture skill is R=0.56 versus CalVal measurements. Adding information from either precipitation observations or soil moisture retrievals increases surface soil moisture skill levels by IDDeltaR=0.06-0.08, and root zone soil moisture skill levels by DeltaR=0.05-0.07. Adding information from both sources increases surface soil moisture skill levels by DeltaR=0.13, and root zone soil moisture skill by DeltaR=0.11, demonstrating that precipitation corrections and assimilation of satellite soil moisture retrievals contribute similar and largely independent amounts of information.

  4. Examining diel patterns of soil and xylem moisture using electrical resistivity imaging

    NASA Astrophysics Data System (ADS)

    Mares, Rachel; Barnard, Holly R.; Mao, Deqiang; Revil, André; Singha, Kamini

    2016-05-01

    The feedbacks among forest transpiration, soil moisture, and subsurface flowpaths are poorly understood. We investigate how soil moisture is affected by daily transpiration using time-lapse electrical resistivity imaging (ERI) on a highly instrumented ponderosa pine and the surrounding soil throughout the growing season. By comparing sap flow measurements to the ERI data, we find that periods of high sap flow within the diel cycle are aligned with decreases in ground electrical conductivity and soil moisture due to drying of the soil during moisture uptake. As sap flow decreases during the night, the ground conductivity increases as the soil moisture is replenished. The mean and variance of the ground conductivity decreases into the summer dry season, indicating drier soil and smaller diel fluctuations in soil moisture as the summer progresses. Sap flow did not significantly decrease through the summer suggesting use of a water source deeper than 60 cm to maintain transpiration during times of shallow soil moisture depletion. ERI captured spatiotemporal variability of soil moisture on daily and seasonal timescales. ERI data on the tree showed a diel cycle of conductivity, interpreted as changes in water content due to transpiration, but changes in sap flow throughout the season could not be interpreted from ERI inversions alone due to daily temperature changes.

  5. Capacitive Soil Moisture Sensor for Plant Watering

    NASA Astrophysics Data System (ADS)

    Maier, Thomas; Kamm, Lukas

    2016-04-01

    How can you realize a water saving and demand-driven plant watering device? To achieve this you need a sensor, which precisely detects the soil moisture. Designing such a sensor is the topic of this poster. We approached this subject with comparing several physical properties of water, e.g. the conductivity, permittivity, heat capacity and the soil water potential, which are suitable to detect the soil moisture via an electronic device. For our project we have developed a sensor device, which measures the soil moisture and provides the measured values for a plant watering system via a wireless bluetooth 4.0 network. Different sensor setups have been analyzed and the final sensor is the result of many iterative steps of improvement. In the end we tested the precision of our sensor and compared the results with theoretical values. The sensor is currently being used in the Botanical Garden of the Friedrich-Alexander-University in a long-term test. This will show how good the usability in the real field is. On the basis of these findings a marketable sensor will soon be available. Furthermore a more specific type of this sensor has been designed for the EU:CROPIS Space Project, where tomato plants will grow at different gravitational forces. Due to a very small (15mm x 85mm x 1.5mm) and light (5 gramm) realisation, our sensor has been selected for the space program. Now the scientists can monitor the water content of the substrate of the tomato plants in outer space and water the plants on demand.

  6. The Integration of SMOS Soil Moisture in a Consistent Soil Moisture Climate Record

    NASA Astrophysics Data System (ADS)

    de Jeu, Richard; Kerr, Yann; Wigneron, Jean Pierre; Rodriguez-Fernandez, Nemesio; Al-Yaari, Amen; van der Schalie, Robin; Dolman, Han; Drusch, Matthias; Mecklenburg, Susanne

    2015-04-01

    Recently, a study funded by the European Space Agency (ESA) was set up to provide guidelines for the development of a global soil moisture climate record with a special emphasis on the integration of SMOS. Three different data fusion approaches were designed and implemented on 10 year passive microwave data (2003-2013) from two different satellite sensors; the ESA Soil Moisture Ocean Salinity Mission (SMOS) and the NASA/JAXA Advanced Scanning Microwave Radiometer (AMSR-E). The AMSR-E data covered the period from January 2003 until Oct 2011 and SMOS data covered the period from June 2010 until the end of 2013. The fusion approaches included a neural network approach (Rodriguez-Fernandez et al., this conference session HS6.4), a regression approach (Wigneron et al., 2004), and an approach based on the baseline algorithm of ESAs current Climate Change Initiative soil moisture program, the Land Parameter Retrieval Model (Van der Schalie et al., this conference session HS6.4). With this presentation we will show the first results from this study including a description of the different approaches and the validation activities using both globally covered modeled datasets and ground observations from the international soil moisture network. The statistical validation analyses will give us information on the temporal and spatial performance of the three different approaches. Based on these results we will then discuss the next steps towards a seamless integration of SMOS in a consistent soil moisture climate record. References Wigneron J.-P., J.-C. Calvet, P. de Rosnay, Y. Kerr, P. Waldteufel, K. Saleh, M. J. Escorihuela, A. Kruszewski, 'Soil Moisture Retrievals from Bi-Angular L-band Passive Microwave Observations', IEEE Trans. Geosc. Remote Sens. Let., vol 1, no. 4, 277-281, 2004.

  7. Interpretation of in situ tests as affected by soil suction.

    DOT National Transportation Integrated Search

    2013-07-01

    Soil moisture conditions are subject to change depending on the season in which they are tested. In : unsaturated soils the moisture at which a soil is tested can directly affect strength and stiffness of the : material. In situ testing is commonly u...

  8. NASA Soil Moisture Mapper Takes First SMAPshots

    NASA Image and Video Library

    2015-03-09

    Fresh off the recent successful deployment of its 20-foot (6-meter) reflector antenna and associated boom arm, NASA's new Soil Moisture Active Passive (SMAP) observatory has successfully completed a two-day test of its science instruments. On Feb. 27 and 28, SMAP's radar and radiometer instruments were successfully operated for the first time with SMAP's antenna in a non-spinning mode. The test was a key step in preparation for the planned spin-up of SMAP's antenna to approximately 15 revolutions per minute in late March. The spin-up will be performed in a two-step process after additional tests and maneuvers adjust the observatory to its final science orbit over the next couple of weeks. Based on the data received, mission controllers at NASA's Jet Propulsion Laboratory, Pasadena, California; and NASA's Goddard Space Flight Center, Greenbelt, Maryland; concluded that the radar and radiometer performed as expected. SMAP launched Jan. 31 on a minimum three-year mission to map global soil moisture and detect whether soils are frozen or thawed. The mission will help scientists understand the links in Earth's water, energy and carbon cycles, help reduce uncertainties in predicting weather and climate, and enhance our ability to monitor and predict natural hazards such as floods and droughts The first test image illustrates the significance of SMAP's spinning instrument design. For this initial test with SMAP's antenna not yet spinning, the observatory's measurement swath width -- the strips observed on Earth in the image -- was limited to 25 miles (40 kilometers). When fully spun up and operating, SMAP's antenna will measure a 620-mile-wide (1,000-kilometer) swath of the ground as it flies above Earth at an altitude of 426 miles (685 kilometers). This will allow SMAP to map the entire globe with high-resolution radar data every two to three days, filling in all of the land surface detail that is not available in this first image. The radar data illustrated in the upper

  9. Determining soil volumetric moisture content using time domain reflectometry

    DOT National Transportation Integrated Search

    1998-02-01

    Time domain reflectometry (TDR) is a technique used to measure indirectly the in situ volumetric moisture content of soil. Current research provides a variety of prediction equations that estimate the volumetric moisture content using the dielectric ...

  10. Evaluation of soil and vegetation response to drought using SMOS soil moisture satellite observations

    NASA Astrophysics Data System (ADS)

    Piles, Maria; Sánchez, Nilda; Vall-llossera, Mercè; Ballabrera, Joaquim; Martínez, Justino; Martínez-Fernández, José; Camps, Adriano; Font, Jordi

    2014-05-01

    Soil moisture plays an important role in determining the likelihood of droughts and floods that may affect an area. Knowledge of soil moisture distribution as a function of time and space is highly relevant for hydrological, ecological and agricultural applications, especially in water-limited or drought-prone regions. However, measuring soil moisture is challenging because of its high variability; point-scale in-situ measurements are scarce being remote sensing the only practical means to obtain regional- and global-scale soil moisture estimates. The ESA's Soil Moisture and Ocean Salinity (SMOS) is the first satellite mission ever designed to measuring the Earth's surface soil moisture at near daily time scales with levels of accuracy previously not attained. Since its launch in November 2009, significant efforts have been dedicated to validate and fine-tune the retrieval algorithms so that SMOS-derived soil moisture estimates meet the standards required for a wide variety of applications. In this line, the SMOS Barcelona Expert Center (BEC) is distributing daily, monthly, and annual temporal averages of 0.25-deg global soil moisture maps, which have proved useful for assessing drought and water-stress conditions. In addition, a downscaling algorithm has been developed to combine SMOS and NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) data into fine-scale (< 1km) soil moisture estimates, which permits extending the applicability of the data to regional and local studies. Fine-scale soil moisture maps are currently limited to the Iberian Peninsula but the algorithm is dynamic and can be transported to any region. Soil moisture maps are generated in a near real-time fashion at BEC facilities and are used by Barcelona's fire prevention services to detect extremely dry soil and vegetation conditions posing a risk of fire. Recently, they have been used to explain drought-induced tree mortality episodes and forest decline in the Catalonia region. These

  11. Concerning the relationship between evapotranspiration and soil moisture

    NASA Technical Reports Server (NTRS)

    Wetzel, Peter J.; Chang, Jy-Tai

    1987-01-01

    The relationship between the evapotranspiration and soil moisture during the drying, supply-limited phase is studied. A second scaling parameter, based on the evapotranspirational supply and demand concept of Federer (1982), is defined; the parameter, referred to as the threshold evapotranspiration, occurs in vegetation-covered surfaces just before leaf stomata close and when surface tension restricts moisture release from bare soil pores. A simple model for evapotranspiration is proposed. The effects of natural soil heterogeneities on evapotranspiration computed from the model are investigated. It is observed that the natural variability in soil moisture, caused by the heterogeneities, alters the relationship between regional evapotranspiration and the area average soil moisture.

  12. Different rates of soil drying after rainfall are observed by the SMOS satellite and the South Fork In Situ Soil Moisture Network

    USDA-ARS?s Scientific Manuscript database

    Soil moisture affects the spatial variation of land–atmosphere interactions through its in'uence on the balance of latent and sensible heat 'ux. Wetter soils are more prone to 'ooding because a smaller fraction of rainfall can in'ltrate into the soil. The Soil Moisture and Oceanic Salinity (SMOS) sa...

  13. Ultrasound Algorithm Derivation for Soil Moisture Content Estimation

    NASA Technical Reports Server (NTRS)

    Belisle, W.R.; Metzl, R.; Choi, J.; Aggarwal, M. D.; Coleman, T.

    1997-01-01

    Soil moisture content can be estimated by evaluating the velocity at which sound waves travel through a known volume of solid material. This research involved the development of three soil algorithms relating the moisture content to the velocity at which sound waves moved through dry and moist media. Pressure and shear wave propagation equations were used in conjunction with soil property descriptions to derive algorithms appropriate for describing the effects of moisture content variation on the velocity of sound waves in soils with and without complete soil pore water volumes, An elementary algorithm was used to estimate soil moisture contents ranging from 0.08 g/g to 0.5 g/g from sound wave velocities ranging from 526 m/s to 664 m/s. Secondary algorithms were also used to estimate soil moisture content from sound wave velocities through soils with pores that were filled predominantly with air or water.

  14. Evaluation of gravimetric ground truth soil moisture data collected for the agricultural soil moisture experiment, 1978 Colby, Kansas, aircraft mission

    NASA Technical Reports Server (NTRS)

    Arya, L. M.; Phinney, D. E. (Principal Investigator)

    1980-01-01

    Soil moisture data acquired to support the development of algorithms for estimating surface soil moisture from remotely sensed backscattering of microwaves from ground surfaces are presented. Aspects of field uniformity and variability of gravimetric soil moisture measurements are discussed. Moisture distribution patterns are illustrated by frequency distributions and contour plots. Standard deviations and coefficients of variation relative to degree of wetness and agronomic features of the fields are examined. Influence of sampling depth on observed moisture content an variability are indicated. For the various sets of measurements, soil moisture values that appear as outliers are flagged. The distribution and legal descriptions of the test fields are included along with examinations of soil types, agronomic features, and sampling plan. Bulk density data for experimental fields are appended, should analyses involving volumetric moisture content be of interest to the users of data in this report.

  15. Use of Ultrasonic Technology for Soil Moisture Measurement

    NASA Technical Reports Server (NTRS)

    Choi, J.; Metzl, R.; Aggarwal, M. D.; Belisle, W.; Coleman, T.

    1997-01-01

    In an effort to improve existing soil moisture measurement techniques or find new techniques using physics principles, a new technique is presented in this paper using ultrasonic techniques. It has been found that ultrasonic velocity changes as the moisture content changes. Preliminary values of velocities are 676.1 m/s in dry soil and 356.8 m/s in 100% moist soils. Intermediate values can be calibrated to give exact values for the moisture content in an unknown sample.

  16. Dual frequency microwave radiometer measurements of soil moisture for bare and vegetated rough surfaces

    NASA Technical Reports Server (NTRS)

    Lee, S. L.

    1974-01-01

    Controlled ground-based passive microwave radiometric measurements on soil moisture were conducted to determine the effects of terrain surface roughness and vegetation on microwave emission. Theoretical predictions were compared with the experimental results and with some recent airborne radiometric measurements. The relationship of soil moisture to the permittivity for the soil was obtained in the laboratory. A dual frequency radiometer, 1.41356 GHz and 10.69 GHz, took measurements at angles between 0 and 50 degrees from an altitude of about fifty feet. Distinct surface roughnesses were studied. With the roughness undisturbed, oats were later planted and vegetated and bare field measurements were compared. The 1.4 GHz radiometer was less affected than the 10.6 GHz radiometer, which under vegetated conditions was incapable of detecting soil moisture. The bare surface theoretical model was inadequate, although the vegetation model appeared to be valid. Moisture parameters to correlate apparent temperature with soil moisture were compared.

  17. Effect of land-use practice on soil moisture variability for soils covered with dense forest vegetation of Puerto Rico

    NASA Technical Reports Server (NTRS)

    Tsegaye, T.; Coleman, T.; Senwo, Z.; Shaffer, D.; Zou, X.

    1998-01-01

    Little is known about the landuse management effect on soil moisture and soil pH distribution on a landscape covered with dense tropical forest vegetation. This study was conducted at three locations where the history of the landuse management is different. Soil moisture was measured using a 6-cm three-rod Time Domain Reflectometery (TDR) probe. Disturbed soil samples were taken from the top 5-cm at the up, mid, and foothill landscape position from the same spots where soil moisture was measured. The results showed that soil moisture varies with landscape position and depth at all three locations. Soil pH and moisture variability were found to be affected by the change in landuse management and landscape position. Soil moisture distribution usually expected to be relatively higher in the foothill (P3) area of these forests than the uphill (P1) position. However, our results indicated that in the Luquillo and Guanica site the surface soil moisture was significantly higher for P1 than P3 position. These suggest that the surface and subsurface drainage in these two sites may have been poor due to the nature of soil formation and type.

  18. Australian Soil Moisture Field Experiments in Support of Soil Moisture Satellite Observations

    NASA Technical Reports Server (NTRS)

    Kim, Edward; Walker, Jeff; Rudiger, Christopher; Panciera, Rocco

    2010-01-01

    Large-scale field campaigns provide the critical fink between our understanding retrieval algorithms developed at the point scale, and algorithms suitable for satellite applications at vastly larger pixel scales. Retrievals of land parameters must deal with the substantial sub-pixel heterogeneity that is present in most regions. This is particularly the case for soil moisture remote sensing, because of the long microwave wavelengths (L-band) that are optimal. Yet, airborne L-band imagers have generally been large, heavy, and required heavy-lift aircraft resources that are expensive and difficult to schedule. Indeed, US soil moisture campaigns, have been constrained by these factors, and European campaigns have used non-imagers due to instrument and aircraft size constraints. Despite these factors, these campaigns established that large-scale soil moisture remote sensing was possible, laying the groundwork for satellite missions. Starting in 2005, a series of airborne field campaigns have been conducted in Australia: to improve our understanding of soil moisture remote sensing at large scales over heterogeneous areas. These field data have been used to test and refine retrieval algorithms for soil moisture satellite missions, and most recently with the launch of the European Space Agency's Soil Moisture Ocean Salinity (SMOS) mission, to provide validation measurements over a multi-pixel area. The campaigns to date have included a preparatory campaign in 2005, two National Airborne Field Experiments (NAFE), (2005 and 2006), two campaigns to the Simpson Desert (2008 and 2009), and one Australian Airborne Cal/val Experiment for SMOS (AACES), just concluded in the austral spring of 2010. The primary airborne sensor for each campaign has been the Polarimetric L-band Microwave Radiometer (PLMR), a 6-beam pushbroom imager that is small enough to be compatible with light aircraft, greatly facilitating the execution of the series of campaigns, and a key to their success. An

  19. Moisture-strength-constructability guidelines for subgrade foundation soils found in Indiana.

    DOT National Transportation Integrated Search

    2016-09-01

    Soil moisture is an important indicator of constructability in the field. Construction activities become difficult when the soil moisture content is excessive, especially in fine-grained soils. Change orders caused by excessive soil moisture during c...

  20. Drought monitoring with soil moisture active passive (SMAP) measurements

    NASA Astrophysics Data System (ADS)

    Mishra, Ashok; Vu, Tue; Veettil, Anoop Valiya; Entekhabi, Dara

    2017-09-01

    Recent launch of space-borne systems to estimate surface soil moisture may expand the capability to map soil moisture deficit and drought with global coverage. In this study, we use Soil Moisture Active Passive (SMAP) soil moisture geophysical retrieval products from passive L-band radiometer to evaluate its applicability to forming agricultural drought indices. Agricultural drought is quantified using the Soil Water Deficit Index (SWDI) based on SMAP and soil properties (field capacity and available water content) information. The soil properties are computed using pedo-transfer function with soil characteristics derived from Harmonized World Soil Database. The SMAP soil moisture product needs to be rescaled to be compatible with the soil parameters derived from the in situ stations. In most locations, the rescaled SMAP information captured the dynamics of in situ soil moisture well and shows the expected lag between accumulations of precipitation and delayed increased in surface soil moisture. However, the SMAP soil moisture itself does not reveal the drought information. Therefore, the SMAP based SWDI (SMAP_SWDI) was computed to improve agriculture drought monitoring by using the latest soil moisture retrieval satellite technology. The formulation of SWDI does not depend on longer data and it will overcome the limited (short) length of SMAP data for agricultural drought studies. The SMAP_SWDI is further compared with in situ Atmospheric Water Deficit (AWD) Index. The comparison shows close agreement between SMAP_SWDI and AWD in drought monitoring over Contiguous United States (CONUS), especially in terms of drought characteristics. The SMAP_SWDI was used to construct drought maps for CONUS and compared with well-known drought indices, such as, AWD, Palmer Z-Index, sc-PDSI and SPEI. Overall the SMAP_SWDI is an effective agricultural drought indicator and it provides continuity and introduces new spatial mapping capability for drought monitoring. As an

  1. Downscaling SMAP Soil Moisture Using Geoinformation Data and Geostatistics

    NASA Astrophysics Data System (ADS)

    Xu, Y.; Wang, L.

    2017-12-01

    Soil moisture is important for agricultural and hydrological studies. However, ground truth soil moisture data for wide area is difficult to achieve. Microwave remote sensing such as Soil Moisture Active Passive (SMAP) can offer a solution for wide coverage. However, existing global soil moisture products only provide observations at coarse spatial resolutions, which often limit their applications in regional agricultural and hydrological studies. This paper therefore aims to generate fine scale soil moisture information and extend soil moisture spatial availability. A statistical downscaling scheme is presented that incorporates multiple fine scale geoinformation data into the downscaling of coarse scale SMAP data in the absence of ground measurement data. Geoinformation data related to soil moisture patterns including digital elevation model (DEM), land surface temperature (LST), land use and normalized difference vegetation index (NDVI) at a fine scale are used as auxiliary environmental variables for downscaling SMAP data. Generalized additive model (GAM) and regression tree are first conducted to derive statistical relationships between SMAP data and auxiliary geoinformation data at an original coarse scale, and residuals are then downscaled to a finer scale via area-to-point kriging (ATPK) by accounting for the spatial correlation information of the input residuals. The results from standard validation scores as well as the triple collocation (TC) method against soil moisture in-situ measurements show that the downscaling method can significantly improve the spatial details of SMAP soil moisture while maintain the accuracy.

  2. Stochastic Analysis and Probabilistic Downscaling of Soil Moisture

    NASA Astrophysics Data System (ADS)

    Deshon, J. P.; Niemann, J. D.; Green, T. R.; Jones, A. S.

    2017-12-01

    Soil moisture is a key variable for rainfall-runoff response estimation, ecological and biogeochemical flux estimation, and biodiversity characterization, each of which is useful for watershed condition assessment. These applications require not only accurate, fine-resolution soil-moisture estimates but also confidence limits on those estimates and soil-moisture patterns that exhibit realistic statistical properties (e.g., variance and spatial correlation structure). The Equilibrium Moisture from Topography, Vegetation, and Soil (EMT+VS) model downscales coarse-resolution (9-40 km) soil moisture from satellite remote sensing or land-surface models to produce fine-resolution (10-30 m) estimates. The model was designed to produce accurate deterministic soil-moisture estimates at multiple points, but the resulting patterns do not reproduce the variance or spatial correlation of observed soil-moisture patterns. The primary objective of this research is to generalize the EMT+VS model to produce a probability density function (pdf) for soil moisture at each fine-resolution location and time. Each pdf has a mean that is equal to the deterministic soil-moisture estimate, and the pdf can be used to quantify the uncertainty in the soil-moisture estimates and to simulate soil-moisture patterns. Different versions of the generalized model are hypothesized based on how uncertainty enters the model, whether the uncertainty is additive or multiplicative, and which distributions describe the uncertainty. These versions are then tested by application to four catchments with detailed soil-moisture observations (Tarrawarra, Satellite Station, Cache la Poudre, and Nerrigundah). The performance of the generalized models is evaluated by comparing the statistical properties of the simulated soil-moisture patterns to those of the observations and the deterministic EMT+VS model. The versions of the generalized EMT+VS model with normally distributed stochastic components produce soil-moisture

  3. Remote Sensing Soil Moisture Analysis by Unmanned Aerial Vehicles Digital Imaging

    NASA Astrophysics Data System (ADS)

    Yeh, C. Y.; Lin, H. R.; Chen, Y. L.; Huang, S. Y.; Wen, J. C.

    2017-12-01

    In recent years, remote sensing analysis has been able to apply to the research of climate change, environment monitoring, geology, hydro-meteorological, and so on. However, the traditional methods for analyzing wide ranges of surface soil moisture of spatial distribution surveys may require plenty resources besides the high cost. In the past, remote sensing analysis performed soil moisture estimates through shortwave, thermal infrared ray, or infrared satellite, which requires lots of resources, labor, and money. Therefore, the digital image color was used to establish the multiple linear regression model. Finally, we can find out the relationship between surface soil color and soil moisture. In this study, we use the Unmanned Aerial Vehicle (UAV) to take an aerial photo of the fallow farmland. Simultaneously, we take the surface soil sample from 0-5 cm of the surface. The soil will be baking by 110° C and 24 hr. And the software ImageJ 1.48 is applied for the analysis of the digital images and the hue analysis into Red, Green, and Blue (R, G, B) hue values. The correlation analysis is the result from the data obtained from the image hue and the surface soil moisture at each sampling point. After image and soil moisture analysis, we use the R, G, B and soil moisture to establish the multiple regression to estimate the spatial distributions of surface soil moisture. In the result, we compare the real soil moisture and the estimated soil moisture. The coefficient of determination (R2) can achieve 0.5-0.7. The uncertainties in the field test, such as the sun illumination, the sun exposure angle, even the shadow, will affect the result; therefore, R2 can achieve 0.5-0.7 reflects good effect for the in-suit test by using the digital image to estimate the soil moisture. Based on the outcomes of the research, using digital images from UAV to estimate the surface soil moisture is acceptable. However, further investigations need to be collected more than ten days (four

  4. BOREAS HYD-1 Volumetric Soil Moisture Data

    NASA Technical Reports Server (NTRS)

    Cuenca, Richard H.; Kelly, Shaun F.; Stangel, David E.; Hall, Forrest G. (Editor); Knapp, David E. (Editor); Smith, David E. (Technical Monitor)

    2000-01-01

    The Boreal Ecosystem-Atmosphere Study (BOREAS) Hydrology (HYD)-1 team made measurements of volumetric soil moisture at the Southern Study Area (SSA) and Northern Study Area (NSA) tower flux sites in 1994 and at selected tower flux sites in 1995-97. Different methods were used to collect these measurements, including neutron probe and manual and automated Time Domain Reflectometry (TDR). In 1994, the measurements were made every other day at the NSA-OJP (Old Jack Pine), NSA-YJP (Young Jack Pine), NSA-OBS (Old Black Spruce), NSA-Fen, SSA-OJP, SSA-YJP, SSA-Fen, SSA-YA (Young Aspen), and SSA-OBS sites. In 1995-97, when automated equipment was deployed at NSA-OJP, NSA-YJP, NSA-OBS, SSA-OBS, and SSA-OA (Old Aspen), the measurements were made as often as every hour. The data are stored in tabular ASCII files. The volumetric soil moisture data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884).

  5. EVALUATION OF RADON EMANATION FROM SOIL WITH VARYING MOISTURE CONTENT IN A SOIL CHAMBER

    EPA Science Inventory

    The paper describes measurements to quantitatively identify the extent to which moisture affects radon emanation and diffusive transport components of a sandy soil radon concentration gradient obtained in the EPA test chamber. The chamber (2X2X4 m long) was constructed to study t...

  6. Validation of the Soil Moisture Active Passive (SMAP) satellite soil moisture retrieval in an Arctic tundra environment

    NASA Astrophysics Data System (ADS)

    Wrona, Elizabeth; Rowlandson, Tracy L.; Nambiar, Manoj; Berg, Aaron A.; Colliander, Andreas; Marsh, Philip

    2017-05-01

    This study examines the Soil Moisture Active Passive soil moisture product on the Equal Area Scalable Earth-2 (EASE-2) 36 km Global cylindrical and North Polar azimuthal grids relative to two in situ soil moisture monitoring networks that were installed in 2015 and 2016. Results indicate that there is no relationship between the Soil Moisture Active Passive (SMAP) Level-2 passive soil moisture product and the upscaled in situ measurements. Additionally, there is very low correlation between modeled brightness temperature using the Community Microwave Emission Model and the Level-1 C SMAP brightness temperature interpolated to the EASE-2 Global grid; however, there is a much stronger relationship to the brightness temperature measurements interpolated to the North Polar grid, suggesting that the soil moisture product could be improved with interpolation on the North Polar grid.

  7. Soil Moisture under Different Vegetation cover in response to Precipitation

    NASA Astrophysics Data System (ADS)

    Liang, Z.; Zhang, J.; Guo, B.; Ma, J.; Wu, Y.

    2016-12-01

    The response study of soil moisture to different precipitation and landcover is significant in the field of Hydropedology. The influence of precipitation to soil moisture is obvious in addition to individual stable aquifer. With data of Hillsborough County, Florida, USA, the alluvial wetland forest and ungrazed Bahia grass that under wet and dry periods were chosen as the research objects, respectively. HYDRUS-3D numerical simulation method was used to simulate soil moisture dynamics in the root zone (10-50 cm) of those vegetation. The soil moisture response to precipitation was analyzed. The results showed that the simulation results of alluvial wetland forest by HYDRUS-3D were better than that of the Bahia grass, and for the same vegetation, the simulation results of soil moisture under dry period were better. Precipitation was more in June, 2003, the soil moisture change of alluvial wetland forest in 10-30 cm soil layer and Bahia grass in 10 cm soil layer were consistent with the precipitation change conspicuously. The alluvial wetland forest soil moisture declined faster than Bahia grass under dry period, which demonstrated that Bahia grass had strong ability to hold water. Key words: alluvial wetland forest; Bahia grass; soil moisture; HYDRUS-3D; precipitation

  8. Soil Moisture as an Estimator for Crop Yield in Germany

    NASA Astrophysics Data System (ADS)

    Peichl, Michael; Meyer, Volker; Samaniego, Luis; Thober, Stephan

    2015-04-01

    , phenological, geological, agronomic, and socio-economic variables are also considered to extend the model in order to reveal the proper causal relation. First results show that dry as well as wet extremes of SMI have a negative impact on crop yield for winter wheat. This indicates that soil moisture has at least a limiting affect on crop production.

  9. Response of deep soil moisture to land use and afforestation in the semi-arid Loess Plateau, China

    NASA Astrophysics Data System (ADS)

    Yang, Lei; Wei, Wei; Chen, Liding; Mo, Baoru

    2012-12-01

    SummarySoil moisture is an effective water source for plant growth in the semi-arid Loess Plateau of China. Characterizing the response of deep soil moisture to land use and afforestation is important for the sustainability of vegetation restoration in this region. In this paper, the dynamics of soil moisture were quantified to evaluate the effect of land use on soil moisture at a depth of 2 m. Specifically, the gravimetric soil moisture content was measured in the soil layer between 0 and 8 m for five land use types in the Longtan catchment of the western Loess Plateau. The land use types included traditional farmland, native grassland, and lands converted from traditional farmland (pasture grassland, shrubland and forestland). Results indicate that the deep soil moisture content decreased more than 35% after land use conversion, and a soil moisture deficit appeared in all types of land with introduced vegetation. The introduced vegetation decreased the soil moisture content to levels lower than the reference value representing no human impact in the entire 0-8 m soil profile. No significant differences appeared between different land use types and introduced vegetation covers, especially in deeper soil layers, regardless of which plant species were introduced. High planting density was found to be the main reason for the severe deficit of soil moisture. Landscape management activities such as tillage activities, micro-topography reconstruction, and fallowed farmland affected soil moisture in both shallow and deep soil layers. Tillage and micro-topography reconstruction can be used as effective countermeasures to reduce the soil moisture deficit due to their ability to increase soil moisture content. For sustainable vegetation restoration in a vulnerable semi-arid region, the plant density should be optimized with local soil moisture conditions and appropriate landscape management practices.

  10. Spatial and temporal variability of soil moisture on the field with and without plants*

    NASA Astrophysics Data System (ADS)

    Usowicz, B.; Marczewski, W.; Usowicz, J. B.

    2012-04-01

    moisture runs in particular objects and of precipitation distribution shows clearly that rainfall has an effect on the soil moisture. The amount of precipitation water that increased the soil moisture depended on the strength of the rainfall, on the hydrological properties of the soil (primarily the soil density), the status of the plant cover, and surface runoff. Basing on the precipitation distribution and on the soil moisture runs, an attempt was made at finding a temporal and spatial relationship between those variables, employing for the purpose the geostatistical methods which permit time and space to be included in the analysis. The geostatistical parameters determined showed the temporal dependence of moisture distribution in the soil profile, with the autocorrelation radius increasing with increasing depth in the profile. The highest values of the radius were observed in the plots with plant cover below the arable horizon, and the lowest in the arable horizon on the barley and fallow plots. The fractal dimensions showed a clear decrease in values with increasing depth in the plots with plant cover, while in the bare plots they were relatively constant within the soil profile under study. Therefore, they indicated that the temporal distribution of soil moisture within the soil profile in the bare field was more random in character than in the plots with plants. The results obtained and the analyses indicate that the moisture in the soil profile, its variability and determination, are significantly affected by the type and condition of plant canopy. The differentiation in moisture content between the plots studied resulted from different precipitation interception and different intensity of water uptake by the roots. * The work was financially supported in part by the ESA Programme for European Cooperating States (PECS), No.98084 "SWEX-R, Soil Water and Energy Exchange/Research", AO-3275.

  11. Divergent surface and total soil moisture projections under global warming

    USGS Publications Warehouse

    Berg, Alexis; Sheffield, Justin; Milly, Paul C.D.

    2017-01-01

    Land aridity has been projected to increase with global warming. Such projections are mostly based on off-line aridity and drought metrics applied to climate model outputs but also are supported by climate-model projections of decreased surface soil moisture. Here we comprehensively analyze soil moisture projections from the Coupled Model Intercomparison Project phase 5, including surface, total, and layer-by-layer soil moisture. We identify a robust vertical gradient of projected mean soil moisture changes, with more negative changes near the surface. Some regions of the northern middle to high latitudes exhibit negative annual surface changes but positive total changes. We interpret this behavior in the context of seasonal changes in the surface water budget. This vertical pattern implies that the extensive drying predicted by off-line drought metrics, while consistent with the projected decline in surface soil moisture, will tend to overestimate (negatively) changes in total soil water availability.

  12. An integrated GIS application system for soil moisture data assimilation

    NASA Astrophysics Data System (ADS)

    Wang, Di; Shen, Runping; Huang, Xiaolong; Shi, Chunxiang

    2014-11-01

    The gaps in knowledge and existing challenges in precisely describing the land surface process make it critical to represent the massive soil moisture data visually and mine the data for further research.This article introduces a comprehensive soil moisture assimilation data analysis system, which is instructed by tools of C#, IDL, ArcSDE, Visual Studio 2008 and SQL Server 2005. The system provides integrated service, management of efficient graphics visualization and analysis of land surface data assimilation. The system is not only able to improve the efficiency of data assimilation management, but also comprehensively integrate the data processing and analysis tools into GIS development environment. So analyzing the soil moisture assimilation data and accomplishing GIS spatial analysis can be realized in the same system. This system provides basic GIS map functions, massive data process and soil moisture products analysis etc. Besides,it takes full advantage of a spatial data engine called ArcSDE to effeciently manage, retrieve and store all kinds of data. In the system, characteristics of temporal and spatial pattern of soil moiture will be plotted. By analyzing the soil moisture impact factors, it is possible to acquire the correlation coefficients between soil moisture value and its every single impact factor. Daily and monthly comparative analysis of soil moisture products among observations, simulation results and assimilations can be made in this system to display the different trends of these products. Furthermore, soil moisture map production function is realized for business application.

  13. Misrepresentation and amendment of soil moisture in conceptual hydrological modelling

    NASA Astrophysics Data System (ADS)

    Zhuo, Lu; Han, Dawei

    2016-04-01

    Although many conceptual models are very effective in simulating river runoff, their soil moisture schemes are generally not realistic in comparison with the reality (i.e., getting the right answers for the wrong reasons). This study reveals two significant misrepresentations in those models through a case study using the Xinanjiang model which is representative of many well-known conceptual hydrological models. The first is the setting of the upper limit of its soil moisture at the field capacity, due to the 'holding excess runoff' concept (i.e., runoff begins on repletion of its storage to the field capacity). The second is neglect of capillary rise of water movement. A new scheme is therefore proposed to overcome those two issues. The amended model is as effective as its original form in flow modelling, but represents more logically realistic soil water processes. The purpose of the study is to enable the hydrological model to get the right answers for the right reasons. Therefore, the new model structure has a better capability in potentially assimilating soil moisture observations to enhance its real-time flood forecasting accuracy. The new scheme is evaluated in the Pontiac catchment of the USA through a comparison with satellite observed soil moisture. The correlation between the XAJ and the observed soil moisture is enhanced significantly from 0.64 to 0.70. In addition, a new soil moisture term called SMDS (Soil Moisture Deficit to Saturation) is proposed to complement the conventional SMD (Soil Moisture Deficit).

  14. Simulating soil moisture change in a semiarid rangeland watershed with a process-based water-balance model

    Treesearch

    Howard Evan Canfield; Vicente L. Lopes

    2000-01-01

    A process-based, simulation model for evaporation, soil water and streamflow (BROOK903) was used to estimate soil moisture change on a semiarid rangeland watershed in southeastern Arizona. A sensitivity analysis was performed to select parameters affecting ET and soil moisture for calibration. Automatic parameter calibration was performed using a procedure based on a...

  15. Typical moisture-density curves : part II : lime treated soils.

    DOT National Transportation Integrated Search

    1966-05-01

    The objective of the study covered by this report was to determine whether the family of curves developed for untreated soils, could be used for determining the optimum moisture and maximum density of lime treated soils. This investigation was initia...

  16. Remote sensing as a tool in assessing soil moisture

    NASA Technical Reports Server (NTRS)

    Carlson, C. W.

    1978-01-01

    The effects of soil moisture as it relates to agriculture is briefly discussed. The use of remote sensing to predict scheduling of irrigation, runoff and soil erosion which contributes to the prediction of crop yield is also discussed.

  17. Soil moisture-soil temperature interrelationships on a sandy-loam soil exposed to full sunlight

    Treesearch

    David A. Marquis

    1967-01-01

    In a study of birch regeneration in New Hampshire, soil moisture and temperature were found to be intimately related. Not only does low moisture lead to high temperature, but high temperature undoubtedly accelerates soil drying, setting up a vicious cycle of heating and drying that may prevent seed germination or kill seedlings.

  18. Joint microwave and infrared studies for soil moisture determination

    NASA Technical Reports Server (NTRS)

    Njoku, E. G.; Schieldge, J. P.; Kahle, A. B. (Principal Investigator)

    1980-01-01

    The feasibility of using a combined microwave-thermal infrared system to determine soil moisture content is addressed. Of particular concern are bare soils. The theoretical basis for microwave emission from soils and the transport of heat and moisture in soils is presented. Also, a description is given of the results of two field experiments held during vernal months in the San Joaquin Valley of California.

  19. Acclimation and soil moisture constrain sugar maple root respiration in experimentally warmed soil.

    PubMed

    Jarvi, Mickey P; Burton, Andrew J

    2013-09-01

    The response of root respiration to warmer soil can affect ecosystem carbon (C) allocation and the strength of positive feedbacks between climatic warming and soil CO2 efflux. This study sought to determine whether fine-root (<1 mm) respiration in a sugar maple (Acer saccharum Marsh.)-dominated northern hardwood forest would adjust to experimentally warmed soil, reducing C return to the atmosphere at the ecosystem scale to levels lower than that would be expected using an exponential temperature response function. Infrared heating lamps were used to warm the soil (+4 to +5 °C) in a mature sugar maple forest in a fully factorial design, including water additions used to offset the effects of warming-induced dry soil. Fine-root-specific respiration rates, root biomass, root nitrogen (N) concentration, soil temperature and soil moisture were measured from 2009 to 2011, with experimental treatments conducted from late 2010 to 2011. Partial acclimation of fine-root respiration to soil warming occurred, with soil moisture deficit further constraining specific respiration rates in heated plots. Fine-root biomass and N concentration remained unchanged. Over the 2011 growing season, ecosystem root respiration was not significantly greater in warmed soil. This result would not be predicted by models that allow respiration to increase exponentially with temperature and do not directly reduce root respiration in drier soil.

  20. Estimating Surface Soil Moisture in Simulated AVIRIS Spectra

    NASA Technical Reports Server (NTRS)

    Whiting, Michael L.; Li, Lin; Ustin, Susan L.

    2004-01-01

    Soil albedo is influenced by many physical and chemical constituents, with moisture being the most influential on the spectra general shape and albedo (Stoner and Baumgardner, 1981). Without moisture, the intrinsic or matrix reflectance of dissimilar soils varies widely due to differences in surface roughness, particle and aggregate sizes, mineral types, including salts, and organic matter contents. The influence of moisture on soil reflectance can be isolated by comparing similar soils in a study of the effects that small differences in moisture content have on reflectance. However, without prior knowledge of the soil physical and chemical constituents within every pixel, it is nearly impossible to accurately attribute the reflectance variability in an image to moisture or to differences in the physical and chemical constituents in the soil. The effect of moisture on the spectra must be eliminated to use hyperspectral imagery for determining minerals and organic matter abundances of bare agricultural soils. Accurate soil mineral and organic matter abundance maps from air- and space-borne imagery can improve GIS models for precision farming prescription, and managing irrigation and salinity. Better models of soil moisture and reflectance will also improve the selection of soil endmembers for spectral mixture analysis.

  1. The Value of SMAP Soil Moisture Observations For Agricultural Applications

    NASA Astrophysics Data System (ADS)

    Mladenova, I. E.; Bolten, J. D.; Crow, W.; Reynolds, C. A.

    2017-12-01

    Knowledge of the amount of soil moisture (SM) in the root zone (RZ) is critical source of information for crop analysts and agricultural agencies as it controls crop development and crop condition changes and can largely impact end-of-season yield. Foreign Agricultural Services (FAS), a subdivision of U.S. Department of Agriculture (USDA) that is in charge with providing information on current and expected global crop supply and demand estimates, has been relying on RZSM estimates generated by the modified two-layer Palmer model, which has been enhanced to allow the assimilation of satellite-based soil moisture data. Generally the accuracy of model-based soil moisture estimates is dependent on the precision of the forcing data that drives the model and more specifically, the accuracy of the precipitation data. Data assimilation gives the opportunity to correct for such precipitation-related inaccuracies and enhance the quality of the model estimates. Here we demonstrate the value of ingesting passive-based soil moisture observations derived from the Soil Moisture Active Passive (SMAP) mission. In terms of agriculture, general understanding is that the change in soil moisture conditions precede the change in vegetation status, suggesting that soil moisture can be used as an early indicator of expected crop conditions. Therefore, we assess the accuracy of the SMAP enhanced Palmer model by examining the lag rank cross-correlation coefficient between the model generated soil moisture observations and the Normalized Difference Vegetation Index (NDVI).

  2. Spatially enhanced passive microwave derived soil moisture: capabilities and opportunities

    USDA-ARS?s Scientific Manuscript database

    Low frequency passive microwave remote sensing is a proven technique for soil moisture retrieval, but its coarse resolution restricts the range of applications. Downscaling, otherwise known as disaggregation, has been proposed as the solution to spatially enhance these coarse resolution soil moistur...

  3. Soil moisture remote sensing: State of the science

    USDA-ARS?s Scientific Manuscript database

    Satellites (e.g., SMAP, SMOS) using passive microwave techniques, in particular at L band frequency, have shown good promise for global mapping of near-surface (0-5 cm) soil moisture at a spatial resolution of 25-40 km and temporal resolution of 2-3 days. C- and X-band soil moisture records date bac...

  4. Use of soil moisture sensors for irrigation scheduling

    USDA-ARS?s Scientific Manuscript database

    Various types of soil moisture sensing devices have been developed and are commercially available for water management applications. Each type of soil moisture sensors has its advantages and shortcomings in terms of accuracy, reliability, and cost. Resistive and capacitive based sensors, and time-d...

  5. Soil moisture and groundwater recharge under a mixed conifer forest

    Treesearch

    Robert R. Ziemer

    1978-01-01

    The depletion of soil moisture within the surface 7 m by a mixed conifer forest in the Sierra Nevada was measured by the neutron method every 2 weeks during 5 consecutive summers. Soil moisture recharge was measured periodically during the intervening winters. Groundwater fluctuations within the surface 17 m were continuously recorded during the same period.

  6. Recent advances in (soil moisture) triple collocation analysis

    USDA-ARS?s Scientific Manuscript database

    To date, triple collocation (TC) analysis is one of the most important methods for the global scale evaluation of remotely sensed soil moisture data sets. In this study we review existing implementations of soil moisture TC analysis as well as investigations of the assumptions underlying the method....

  7. A review of the applications of ASCAT soil moisture products

    USDA-ARS?s Scientific Manuscript database

    Remote sensing of soil moisture has reached a level of good maturity and accuracy for which the retrieved products are ready to use in real-world applications. Due to the importance of soil moisture in the partitioning of the water and energy fluxes between the land surface and the atmosphere, a wid...

  8. Evaluating ESA CCI Soil Moisture in East Africa

    NASA Technical Reports Server (NTRS)

    McNally, Amy; Shukla, Shraddhanand; Arsenault, Kristi R.; Wang, Shugong; Peters-Lidard, Christa D.; Verdin, James P.

    2016-01-01

    To assess growing season conditions where ground based observations are limited or unavailable, food security and agricultural drought monitoring analysts rely on publicly available remotely sensed rainfall and vegetation greenness. There are also remotely sensed soil moisture observations from missions like the European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) and NASAs Soil Moisture Active Passive (SMAP), however these time series are still too short to conduct studies that demonstrate the utility of these data for operational applications, or to provide historical context for extreme wet or dry events. To promote the use of remotely sensed soil moisture in agricultural drought and food security monitoring, we use East Africa as a case study to evaluate the quality of a 30+ year time series of merged active-passive microwave soil moisture from the ESA Climate Change Initiative (CCI-SM). Compared to the Normalized Difference Vegetation index (NDVI) and modeled soil moisture products, we found substantial spatial and temporal gaps in the early part of the CCI-SM record, with adequate data coverage beginning in 1992. From this point forward, growing season CCI-SM anomalies were well correlated (R greater than 0.5) with modeled, seasonal soil moisture, and in some regions, NDVI. We use correlation analysis and qualitative comparisons at seasonal time scales to show that remotely sensed soil moisture can add information to a convergence of evidence framework that traditionally relies on rainfall and NDVI in moderately vegetated regions.

  9. Assessment of the SMAP level 2 passive soil moisture product

    USDA-ARS?s Scientific Manuscript database

    The NASA Soil Moisture Active Passive (SMAP) satellite mission was launched on Jan 31, 2015. The observatory was developed to provide global mapping of high-resolution soil moisture and freeze-thaw state every 2–3 days using an L-band (active) radar and an L-band (passive) radiometer. SMAP provides ...

  10. Soil moisture retrival from Sentinel-1 and Modis synergy

    NASA Astrophysics Data System (ADS)

    Gao, Qi; Zribi, Mehrez; Escorihuela, Maria Jose; Baghdadi, Nicolas

    2017-04-01

    This study presents two methodologies retrieving soil moisture from SAR remote sensing data. The study is based on Sentinel-1 data in the VV polarization, over a site in Urgell, Catalunya (Spain). In the two methodologies using change detection techniques, preprocessed radar data are combined with normalized difference vegetation index (NDVI) auxiliary data to estimate the mean soil moisture with a resolution of 1km. By modeling the relationship between the backscatter difference and NDVI, the soil moisture at a specific NDVI value is retrieved. The first algorithm is already developed on West Africa(Zribi et al., 2014) from ERS scatterometer data to estimate soil water status. In this study, it is adapted to Sentinel-1 data and take into account the high repetitiveness of data in optimizing the inversion approach. Another new method is developed based on the backscatter difference between two adjacent days of Sentinel-1 data w.r.t. NDVI, with smaller vegetation change, the backscatter difference is more sensitive to soil moisture. The proposed methodologies have been validated with the ground measurement in two demonstrative fields with RMS error about 0.05 (in volumetric moisture), and the coherence between soil moisture variations and rainfall events is observed. Soil moisture maps at 1km resolution are generated for the study area. The results demonstrate the potential of Sentinel-1 data for the retrieval of soil moisture at 1km or even better resolution.

  11. The Soil Moisture Active/Passive Mission (SMAP)

    USDA-ARS?s Scientific Manuscript database

    The Soil Moisture Active/Passive (SMAP) mission will deliver global views of soil moisture content and its freeze/thaw state that are critical terrestrial water cycle state variables. Polarized measurements obtained with a shared antenna L-band radar and radiometer system will allow accurate estima...

  12. Evaluating ESA CCI soil moisture in East Africa.

    PubMed

    McNally, Amy; Shukla, Shraddhanand; Arsenault, Kristi R; Wang, Shugong; Peters-Lidard, Christa D; Verdin, James P

    2016-06-01

    To assess growing season conditions where ground based observations are limited or unavailable, food security and agricultural drought monitoring analysts rely on publicly available remotely sensed rainfall and vegetation greenness. There are also remotely sensed soil moisture observations from missions like the European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) and NASA's Soil Moisture Active Passive (SMAP), however these time series are still too short to conduct studies that demonstrate the utility of these data for operational applications, or to provide historical context for extreme wet or dry events. To promote the use of remotely sensed soil moisture in agricultural drought and food security monitoring, we use East Africa as a case study to evaluate the quality of a 30+ year time series of merged active-passive microwave soil moisture from the ESA Climate Change Initiative (CCI-SM). Compared to the Normalized Difference Vegetation index (NDVI) and modeled soil moisture products, we found substantial spatial and temporal gaps in the early part of the CCI-SM record, with adequate data coverage beginning in 1992. From this point forward, growing season CCI-SM anomalies were well correlated (R>0.5) with modeled, seasonal soil moisture, and in some regions, NDVI. We use correlation analysis and qualitative comparisons at seasonal time scales to show that remotely sensed soil moisture can add information to a convergence of evidence framework that traditionally relies on rainfall and NDVI in moderately vegetated regions.

  13. Challenges in Interpreting and Validating Satellite Soil Moisture Information

    USDA-ARS?s Scientific Manuscript database

    Global soil moisture products are now being generated routinely using microwave-based satellite observing systems. These include the NASA Soil Moisture Active Passive (SMAP) mission. In order to fully exploit these observations they must be integrated with both in situ measurements and model-based e...

  14. Combined radar-radiometer surface soil moisture and roughness estimation

    USDA-ARS?s Scientific Manuscript database

    A robust physics-based combined radar-radiometer, or Active-Passive, surface soil moisture and roughness estimation methodology is presented. Soil moisture and roughness retrieval is performed via optimization, i.e., minimization, of a joint objective function which constrains similar resolution rad...

  15. Long term observation and validation of windsat soil moisture data

    USDA-ARS?s Scientific Manuscript database

    The surface soil moisture controls surface energy budget. It is a key environmental variable in the coupled atmospheric and hydrological processes that are related to drought, heat waves and monsoon formation. Satellite remote sensing of soil moisture provides information that can contribute to unde...

  16. The global distribution and dynamics of surface soil moisture

    NASA Astrophysics Data System (ADS)

    McColl, Kaighin A.; Alemohammad, Seyed Hamed; Akbar, Ruzbeh; Konings, Alexandra G.; Yueh, Simon; Entekhabi, Dara

    2017-01-01

    Surface soil moisture has a direct impact on food security, human health and ecosystem function. It also plays a key role in the climate system, and the development and persistence of extreme weather events such as droughts, floods and heatwaves. However, sparse and uneven observations have made it difficult to quantify the global distribution and dynamics of surface soil moisture. Here we introduce a metric of soil moisture memory and use a full year of global observations from NASA's Soil Moisture Active Passive mission to show that surface soil moisture--a storage believed to make up less than 0.001% of the global freshwater budget by volume, and equivalent to an, on average, 8-mm thin layer of water covering all land surfaces--plays a significant role in the water cycle. Specifically, we find that surface soil moisture retains a median 14% of precipitation falling on land after three days. Furthermore, the retained fraction of the surface soil moisture storage after three days is highest over arid regions, and in regions where drainage to groundwater storage is lowest. We conclude that lower groundwater storage in these regions is due not only to lower precipitation, but also to the complex partitioning of the water cycle by the surface soil moisture storage layer at the land surface.

  17. Remote Sensing of Soil Moisture Using Airborne Hyperspectral Data

    DTIC Science & Technology

    2011-01-01

    the relationship between reflec- tance and soil moisture where there is ground cover and ascertain the Normalized Difference Vegetation Index ( NDVI ...in those areas. This could establish a minimum NDVI for ground cover that would allow for estimation of soil moisture. Alternatively, they could

  18. Soil moisture determination study. [Guymon, Oklahoma

    NASA Technical Reports Server (NTRS)

    Blanchard, B. J.

    1979-01-01

    Soil moisture data collected in conjunction with aircraft sensor and SEASAT SAR data taken near Guymon, Oklahoma are summarized. In order to minimize the effects of vegetation and roughness three bare and uniformly smooth fields were sampled 6 times at three day intervals on the flight days from August 2 through 17. Two fields remained unirrigated and dry. A similar pair of fields was irrigated at different times during the sample period. In addition, eighteen other fields were sampled on the nonflight days with no field being sampled more than 24 hours from a flight time. The aircraft sensors used included either black and white or color infrared photography, L and C band passive microwave radiometers, the 13.3, 4.75, 1.6 and .4 GHz scatterometers, the 11 channel modular microwave scanner, and the PRT5.

  19. A high resolution soil moisture radiometer

    NASA Technical Reports Server (NTRS)

    Dod, L. R.

    1980-01-01

    The design of an L-band high resolution soil moisture radiometer is described. The selected system is a planar slotted waveguide array at L-band frequencies. The square aperture is 74.75 m by 74.75 m subdivided into 8 tilted subarrays. The system has a 290 km circular orbit and provides a spatial resolution of 1 km. The aperture forms 230 simultaneous beams in a cross-track pattern which covers a swath 420 km wide. A revisit time of 6 days is provided for an orbit inclination of 50 deg. The 1 km resolution cell allows an integration time of 1/7 second and sharing this time period sequentially between two orthogonal polarization modes can provide a temperature resolution of 0.7 K.

  20. Drive by Soil Moisture Measurement: A Citizen Science Project

    NASA Astrophysics Data System (ADS)

    Senanayake, I. P.; Willgoose, G. R.; Yeo, I. Y.; Hancock, G. R.

    2017-12-01

    Two of the common attributes of soil moisture are that at any given time it varies quite markedly from point to point, and that there is a significant deterministic pattern that underlies this spatial variation and which is typically 50% of the spatial variability. The spatial variation makes it difficult to determine the time varying catchment average soil moisture using field measurements because any individual measurement is unlikely to be equal to the average for the catchment. The traditional solution to this is to make many measurements (e.g. with soil moisture probes) spread over the catchment, which is very costly and manpower intensive, particularly if we need a time series of soil moisture variation across a catchment. An alternative approach, explored in this poster is to use the deterministic spatial pattern of soil moisture to calibrate one site (e.g. a permanent soil moisture probe at a weather station) to the spatial pattern of soil moisture over the study area. The challenge is then to determine the spatial pattern of soil moisture. This poster will present results from a proof of concept project, where data was collected by a number of undergraduate engineering students, to estimate the spatial pattern. The approach was to drive along a series of roads in a catchment and collect soil moisture measurements at the roadside using field portable soil moisture probes. This drive was repeated a number of times over the semester, and the time variation and spatial persistence of the soil moisture pattern were examined. Provided that the students could return to exactly the same location on each collection day there was a strong persistent pattern in the soil moisture, even while the average soil moisture varied temporally as a result of preceding rainfall. The poster will present results and analysis of the student data, and compare these results with several field sites where we have spatially distributed permanently installed soil moisture probes. The

  1. The moisture response of soil heterotrophic respiration: Interaction with soil properties.

    USDA-ARS?s Scientific Manuscript database

    Soil moisture-respiration functions are used to simulate the various mechanisms determining the relations between soil moisture content and carbon mineralization. Soil models used in the simulation of global carbon fluxes often apply simplified functions assumed to represent an average moisture-resp...

  2. Soil moisture dynamics and smoldering combustion limits of pocosin soils in North Carolina, USA

    Treesearch

    James Reardon; Gary Curcio; Roberta Bartlette

    2009-01-01

    Smoldering combustion of wetland organic soils in the south-eastern USA is a serious management concern. Previous studies have reported smoldering was sensitive to a wide range of moisture contents, but studies of soil moisture dynamics and changing smoldering combustion potential in wetland communities are limited. Linking soil moisture measurements with estimates of...

  3. Soil Moisture and the Persistence of North American Drought.

    NASA Astrophysics Data System (ADS)

    Oglesby, Robert J.; Erickson, David J., III

    1989-11-01

    We describe numerical sensitivity experiments exploring the effects of soil moisture on North American summertime climate using the NCAR CCMI, a 12-layer global atmospheric general circulation model. In particular. the hypothesis that reduced soil moisture may help induce and amplify warm, dry summers over midlatitude continental interiors is examined. Equilibrium climate statistics are computed for the perpetual July model response to imposed soil moisture anomalies over North America between 36° and 49°N. In addition, the persistence of imposed soil moisture anomalies is examined through use of the seasonal cycle mode of operation with use of various initial atmospheric states both equilibrated and nonequilibrated to the initial soil moisture anomaly.The climate statistics generated by thew model simulations resemble in a general way those of the summer of 1988, when extensive heat and drought occurred over much of North America. A reduction in soil moisture in the model leads to an increase in surface temperature, lower surface pressure, increased ridging aloft, and a northward shift of the jet stream. Low-level moisture advection from the Gulf of Mexico is important in determining where persistent soil moisture deficits can be maintained. In seasonal cycle simulations, it lock longer for an initially unequilibrated atmosphere to respond to the imposed soil moisture anomaly, via moisture transport from the Gulf of Mexico, than when initially the atmosphere was in equilibrium with the imposed anomaly., i.e., the initial state was obtained from the appropriate perpetual July simulation. The results demonstrate the important role of soil moisture in prolonging and/or amplifying North American summertime drought.

  4. What is the philosophy of modelling soil moisture movement?

    NASA Astrophysics Data System (ADS)

    Chen, J.; Wu, Y.

    2009-12-01

    In laboratory, the soil moisture movement in the different soil textures has been analysed. From field investigation, at a spot, the soil moisture movement in the root zone, vadose zone and shallow aquifer has been explored. In addition, on ground slopes, the interflow in the near surface soil layers has been studied. Along the regions near river reaches, the expansion and shrink of the saturated area due to rainfall occurrences have been observed. From those previous explorations regarding soil moisture movement, numerical models to represent this hydrologic process have been developed. However, generally, due to high heterogeneity and stratification of soil in a basin, modelling soil moisture movement is rather challenging. Normally, some empirical equations or artificial manipulation are employed to adjust the soil moisture movement in various numerical models. In this study, we inspect the soil moisture movement equations used in a watershed model, SWAT (Soil and Water Assessment Tool) (Neitsch et al., 2005), to examine the limitations of our knowledge in such a hydrologic process. Then, we adopt the features of a topographic-information based on a hydrologic model, TOPMODEL (Beven and Kirkby, 1979), to enhance the representation of soil moisture movement in SWAT. Basically, the results of the study reveal, to some extent, the philosophy of modelling soil moisture movement in numerical models, which will be presented in the conference. Beven, K.J. and Kirkby, M.J., 1979. A physically based variable contributing area model of basin hydrology. Hydrol. Science Bulletin, 24: 43-69. Neitsch, S.L., Arnold, J.G., Kiniry, J.R., Williams, J.R. and King, K.W., 2005. Soil and Water Assessment Tool Theoretical Documentation, Grassland, soil and research service, Temple, TX.

  5. MODIS-based spatiotemporal patterns of soil moisture and evapotranspiration interactions in Tampa Bay urban watershed

    NASA Astrophysics Data System (ADS)

    Chang, Ni-Bin; Xuan, Zhemin; Wimberly, Brent

    2011-09-01

    Soil moisture and evapotranspiration (ET) is affected by both water and energy balances in the soilvegetation- atmosphere system, it involves many complex processes in the nexus of water and thermal cycles at the surface of the Earth. These impacts may affect the recharge of the upper Floridian aquifer. The advent of urban hydrology and remote sensing technologies opens new and innovative means to undertake eventbased assessment of ecohydrological effects in urban regions. For assessing these landfalls, the multispectral Moderate Resolution Imaging Spectroradiometer (MODIS) remote sensing images can be used for the estimation of such soil moisture change in connection with two other MODIS products - Enhanced Vegetation Index (EVI), Land Surface Temperature (LST). Supervised classification for soil moisture retrieval was performed for Tampa Bay area on the 2 kmx2km grid with MODIS images. Machine learning with genetic programming model for soil moisture estimation shows advances in image processing, feature extraction, and change detection of soil moisture. ET data that were derived by Geostationary Operational Environmental Satellite (GOES) data and hydrologic models can be retrieved from the USGS web site directly. Overall, the derived soil moisture in comparison with ET time series changes on a seasonal basis shows that spatial and temporal variations of soil moisture and ET that are confined within a defined region for each type of surfaces, showing clustered patterns and featuring space scatter plot in association with the land use and cover map. These concomitant soil moisture patterns and ET fluctuations vary among patches, plant species, and, especially, location on the urban gradient. Time series plots of LST in association with ET, soil moisture and EVI reveals unique ecohydrological trends. Such ecohydrological assessment can be applied for supporting the urban landscape management in hurricane-stricken regions.

  6. Upscaling sparse ground-based soil moisture observations for the validation of satellite surface soil moisture products

    USDA-ARS?s Scientific Manuscript database

    The contrast between the point-scale nature of current ground-based soil moisture instrumentation and the footprint resolution (typically >100 square kilometers) of satellites used to retrieve soil moisture poses a significant challenge for the validation of data products from satellite missions suc...

  7. Evaluation of Ku-Band Sensitivity To Soil Moisture: Soil Moisture Change Detection Over the NAFE06 Study Area

    USDA-ARS?s Scientific Manuscript database

    A very promising technique for spatial disaggregation of soil moisture is on the combination of radiometer and radar observations. Despite their demonstrated potential for long term large scale monitoring of soil moisture, passive and active have their disadvantages in terms of temporal and spatial ...

  8. Manipulative experiments demonstrate how long-term soil moisture changes alter controls of plant water use

    SciTech Connect

    Grossiord, Charlotte; Sevanto, Sanna Annika; Limousin, Jean -Marc

    Tree transpiration depends on biotic and abiotic factors that might change in the future, including precipitation and soil moisture status. Although short-term sap flux responses to soil moisture and evaporative demand have been the subject of attention before, the relative sensitivity of sap flux to these two factors under long-term changes in soil moisture conditions has rarely been determined experimentally. We tested how long-term artificial change in soil moisture affects the sensitivity of tree-level sap flux to daily atmospheric vapor pressure deficit ( VPD) and soil moisture variations, and the generality of these effects across forest types and environments usingmore » four manipulative sites in mature forests. Exposure to relatively long-term (two to six years) soil moisture reduction decreases tree sap flux sensitivity to daily VPD and relative extractable water ( REW) variations, leading to lower sap flux even under high soil moisture and optimal VPD. Inversely, trees subjected to long-term irrigation showed a significant increase in their sensitivity to daily VPD and REW, but only at the most water-limited site. The ratio between the relative change in soil moisture manipulation and the relative change in sap flux sensitivity to VPD and REW variations was similar across sites suggesting common adjustment mechanisms to long-term soil moisture status across environments for evergreen tree species. Altogether, our results show that long-term changes in soil water availability, and subsequent adjustments to these novel conditions, could play a critical and increasingly important role in controlling forest water use in the future.« less

  9. Manipulative experiments demonstrate how long-term soil moisture changes alter controls of plant water use

    SciTech Connect

    Grossiord, Charlotte; Sevanto, Sanna; Limousin, Jean-Marc

    Tree transpiration depends on biotic and abiotic factors that might change in the future, including precipitation and soil moisture status. Although short-term sap flux responses to soil moisture and evaporative demand have been the subject of attention before, the relative sensitivity of sap flux to these two factors under long-term changes in soil moisture conditions has rarely been determined experimentally. We tested how long-term artificial change in soil moisture affects the sensitivity of tree-level sap flux to daily atmospheric vapor pressure deficit (VPD) and soil moisture variations, and the generality of these effects across forest types and environments using fourmore » manipulative sites in mature forests. Exposure to relatively long-term (two to six years) soil moisture reduction decreases tree sap flux sensitivity to daily VPD and relative extractable water (REW) variations, leading to lower sap flux even under high soil moisture and optimal VPD. Inversely, trees subjected to long-term irrigation showed a significant increase in their sensitivity to daily VPD and REW, but only at the most water-limited site. The ratio between the relative change in soil moisture manipulation and the relative change in sap flux sensitivity to VPD and REW variations was similar across sites suggesting common adjustment mechanisms to long-term soil moisture status across environments for evergreen tree species. Overall, our results show that long-term changes in soil water availability, and subsequent adjustments to these novel conditions, could play a critical and increasingly important role in controlling forest water use in the future.« less

  10. Manipulative experiments demonstrate how long-term soil moisture changes alter controls of plant water use

    DOE PAGES

    Grossiord, Charlotte; Sevanto, Sanna Annika; Limousin, Jean -Marc; ...

    2017-12-14

    Tree transpiration depends on biotic and abiotic factors that might change in the future, including precipitation and soil moisture status. Although short-term sap flux responses to soil moisture and evaporative demand have been the subject of attention before, the relative sensitivity of sap flux to these two factors under long-term changes in soil moisture conditions has rarely been determined experimentally. We tested how long-term artificial change in soil moisture affects the sensitivity of tree-level sap flux to daily atmospheric vapor pressure deficit ( VPD) and soil moisture variations, and the generality of these effects across forest types and environments usingmore » four manipulative sites in mature forests. Exposure to relatively long-term (two to six years) soil moisture reduction decreases tree sap flux sensitivity to daily VPD and relative extractable water ( REW) variations, leading to lower sap flux even under high soil moisture and optimal VPD. Inversely, trees subjected to long-term irrigation showed a significant increase in their sensitivity to daily VPD and REW, but only at the most water-limited site. The ratio between the relative change in soil moisture manipulation and the relative change in sap flux sensitivity to VPD and REW variations was similar across sites suggesting common adjustment mechanisms to long-term soil moisture status across environments for evergreen tree species. Altogether, our results show that long-term changes in soil water availability, and subsequent adjustments to these novel conditions, could play a critical and increasingly important role in controlling forest water use in the future.« less

  11. The impact of fog on soil moisture dynamics in the Namib Desert

    NASA Astrophysics Data System (ADS)

    Li, Bonan; Wang, Lixin; Kaseke, Kudzai F.; Vogt, Roland; Li, Lin; Seely, Mary K.

    2018-03-01

    Soil moisture is a crucial component supporting vegetation dynamics in drylands. Despite increasing attention on fog in dryland ecosystems, the statistical characterization of fog distribution and how fog affects soil moisture dynamics have not been seen in literature. To this end, daily fog records over two years (Dec 1, 2014-Nov 1, 2016) from three sites within the Namib Desert were used to characterize fog distribution. Two sites were located within the Gobabeb Research and Training Center vicinity, the gravel plains and the sand dunes. The third site was located at the gravel plains, Kleinberg. A subset of the fog data during rainless period was used to investigate the effect of fog on soil moisture. A stochastic modeling framework was used to simulate the effect of fog on soil moisture dynamics. Our results showed that fog distribution can be characterized by a Poisson process with two parameters (arrival rate λ and average depth α (mm)). Fog and soil moisture observations from eighty (Aug 19, 2015-Nov 6, 2015) rainless days indicated a moderate positive relationship between soil moisture and fog in the Gobabeb gravel plains, a weaker relationship in the Gobabeb sand dunes while no relationship was observed at the Kleinberg site. The modeling results suggested that mean and major peaks of soil moisture dynamics can be captured by the fog modeling. Our field observations demonstrated the effects of fog on soil moisture dynamics during rainless periods at some locations, which has important implications on soil biogeochemical processes. The statistical characterization and modeling of fog distribution are of great value to predict fog distribution and investigate the effects of potential changes in fog distribution on soil moisture dynamics.

  12. Remotely sensed soil moisture input to a hydrologic model

    NASA Technical Reports Server (NTRS)

    Engman, E. T.; Kustas, W. P.; Wang, J. R.

    1989-01-01

    The possibility of using detailed spatial soil moisture maps as input to a runoff model was investigated. The water balance of a small drainage basin was simulated using a simple storage model. Aircraft microwave measurements of soil moisture were used to construct two-dimensional maps of the spatial distribution of the soil moisture. Data from overflights on different dates provided the temporal changes resulting from soil drainage and evapotranspiration. The study site and data collection are described, and the soil measurement data are given. The model selection is discussed, and the simulation results are summarized. It is concluded that a time series of soil moisture is a valuable new type of data for verifying model performance and for updating and correcting simulated streamflow.

  13. Pore-scale investigation on the response of heterotrophic respiration to moisture conditions in heterogeneous soils

    SciTech Connect

    Yan, Zhifeng; Liu, Chongxuan; Todd-Brown, Katherine E.

    The relationship between microbial respiration rate and soil moisture content is an important property for understanding and predicting soil organic carbon degradation, CO 2 production and emission, and their subsequent effects on climate change. This paper reports a pore-scale modeling study to investigate the response of heterotrophic respiration to moisture conditions in soils and to evaluate various factors that affect this response. X-ray computed tomography was used to derive soil pore structures, which were then used for pore-scale model investigation. The pore-scale results were then averaged to calculate the effective respiration rates as a function of water content in soils.more » The calculated effective respiration rate first increases and then decreases with increasing soil water content, showing a maximum respiration rate at water saturation degree of 0.75 that is consistent with field and laboratory observations. The relationship between the respiration rate and moisture content is affected by various factors, including pore-scale organic carbon bioavailability, the rate of oxygen delivery, soil pore structure and physical heterogeneity, soil clay content, and microbial drought resistivity. Simulations also illustrates that a larger fraction of CO 2 produced from microbial respiration can be accumulated inside soil cores under higher saturation conditions, implying that CO 2 flux measured on the top of soil cores may underestimate or overestimate true soil respiration rates under dynamic moisture conditions. Overall, this study provides mechanistic insights into the soil respiration response to the change in moisture conditions, and reveals a complex relationship between heterotrophic microbial respiration rate and moisture content in soils that is affected by various hydrological, geochemical, and biophysical factors.« less

  14. Value of Available Global Soil Moisture Products for Agricultural Monitoring

    NASA Astrophysics Data System (ADS)

    Mladenova, Iliana; Bolten, John; Crow, Wade; de Jeu, Richard

    2016-04-01

    The first operationally derived and publicly distributed global soil moil moisture product was initiated with the launch of the Advanced Scanning Microwave Mission on the NASA's Earth Observing System Aqua satellite (AMSR-E). AMSR-E failed in late 2011, but its legacy is continued by AMSR2, launched in 2012 on the JAXA Global Change Observation Mission-Water (GCOM-W) mission. AMSR is a multi-frequency dual-polarization instrument, where the lowest two frequencies (C- and X-band) were used for soil moisture retrieval. Theoretical research and small-/field-scale airborne campaigns, however, have demonstrated that soil moisture would be best monitored using L-band-based observations. This consequently led to the development and launch of the first L-band-based mission-the ESA's Soil Moisture Ocean Salinity (SMOS) mission (2009). In early 2015 NASA launched the second L-band-based mission, the Soil Moisture Active Passive (SMAP). These satellite-based soil moisture products have been demonstrated to be invaluable sources of information for mapping water stress areas, crop monitoring and yield forecasting. Thus, a number of agricultural agencies routinely utilize and rely on global soil moisture products for improving their decision making activities, determining global crop production and crop prices, identifying food restricted areas, etc. The basic premise of applying soil moisture observations for vegetation monitoring is that the change in soil moisture conditions will precede the change in vegetation status, suggesting that soil moisture can be used as an early indicator of expected crop condition change. Here this relationship was evaluated across multiple microwave frequencies by examining the lag rank cross-correlation coefficient between the soil moisture observations and the Normalized Difference Vegetation Index (NDVI). A main goal of our analysis is to evaluate and inter-compare the value of the different soil moisture products derived using L-band (SMOS

  15. Soil moisture and the persistence of North American drought

    NASA Technical Reports Server (NTRS)

    Oglesby, Robert J.; Erickson, David J., III

    1989-01-01

    Numerical sensitivity experiments on the effects of soil moisture on North American summertime climate are performed using a 12-layer global atmospheric general circulation model. Consideration is given to the hypothesis that reduced soil moisture may induce and amplify warm, dry summers of midlatitude continental interiors. The simulations resemble the conditions of the summer of 1988, including an extensive drought over much of North America. It is found that a reduction in soil moisture leads to an increase in surface temperature, lower surface pressure, increased ridging aloft, and a northward shift of the jet stream. It is shown that low-level moisture advection from the Gulf of Mexico is important in the maintenance of persistent soil moisture deficits.

  16. Investigation of remote sensing techniques of measuring soil moisture

    NASA Technical Reports Server (NTRS)

    Newton, R. W. (Principal Investigator); Blanchard, A. J.; Nieber, J. L.; Lascano, R.; Tsang, L.; Vanbavel, C. H. M.

    1981-01-01

    Major activities described include development and evaluation of theoretical models that describe both active and passive microwave sensing of soil moisture, the evaluation of these models for their applicability, the execution of a controlled field experiment during which passive microwave measurements were acquired to validate these models, and evaluation of previously acquired aircraft microwave measurements. The development of a root zone soil water and soil temperature profile model and the calibration and evaluation of gamma ray attenuation probes for measuring soil moisture profiles are considered. The analysis of spatial variability of soil information as related to remote sensing is discussed as well as the implementation of an instrumented field site for acquisition of soil moisture and meteorologic information for use in validating the soil water profile and soil temperature profile models.

  17. Soil moisture downscaling using a simple thermal based proxy

    NASA Astrophysics Data System (ADS)

    Peng, Jian; Loew, Alexander; Niesel, Jonathan

    2016-04-01

    Microwave remote sensing has been largely applied to retrieve soil moisture (SM) from active and passive sensors. The obvious advantage of microwave sensor is that SM can be obtained regardless of atmospheric conditions. However, existing global SM products only provide observations at coarse spatial resolutions, which often hamper their applications in regional hydrological studies. Therefore, various downscaling methods have been proposed to enhance the spatial resolution of satellite soil moisture products. The aim of this study is to investigate the validity and robustness of a simple Vegetation Temperature Condition Index (VTCI) downscaling scheme over different climates and regions. Both polar orbiting (MODIS) and geostationary (MSG SEVIRI) satellite data are used to improve the spatial resolution of the European Space Agency's Water Cycle Multi-mission Observation Strategy and Climate Change Initiative (ESA CCI) soil moisture, which is a merged product based on both active and passive microwave observations. The results from direct validation against soil moisture in-situ measurements, spatial pattern comparison, as well as seasonal and land use analyses show that the downscaling method can significantly improve the spatial details of CCI soil moisture while maintain the accuracy of CCI soil moisture. The application of the scheme with different satellite platforms and over different regions further demonstrate the robustness and effectiveness of the proposed method. Therefore, the VTCI downscaling method has the potential to facilitate relevant hydrological applications that require high spatial and temporal resolution soil moisture.

  18. Microwave remote sensing and its application to soil moisture detection

    NASA Technical Reports Server (NTRS)

    Newton, R. W. (Principal Investigator)

    1977-01-01

    The author has identified the following significant results. Experimental measurements were utilized to demonstrate a procedure for estimating soil moisture, using a passive microwave sensor. The investigation showed that 1.4 GHz and 10.6 GHz can be used to estimate the average soil moisture within two depths; however, it appeared that a frequency less than 10.6 GHz would be preferable for the surface measurement. Average soil moisture within two depths would provide information on the slope of the soil moisture gradient near the surface. Measurements showed that a uniform surface roughness similar to flat tilled fields reduced the sensitivity of the microwave emission to soil moisture changes. Assuming that the surface roughness was known, the approximate soil moisture estimation accuracy at 1.4 GHz calculated for a 25% average soil moisture and an 80% degree of confidence, was +3% and -6% for a smooth bare surface, +4% and -5% for a medium rough surface, and +5.5% and -6% for a rough surface.

  19. Retrieving pace in vegetation growth using precipitation and soil moisture

    NASA Astrophysics Data System (ADS)

    Sohoulande Djebou, D. C.; Singh, V. P.

    2013-12-01

    The complexity of interactions between the biophysical components of the watershed increases the challenge of understanding water budget. Hence, the perspicacity of the continuum soil-vegetation-atmosphere's functionality still remains crucial for science. This study targeted the Texas Gulf watershed and evaluated the behavior of vegetation covers by coupling precipitation and soil moisture patterns. Growing season's Normalized Differential Vegetation Index NDVI for deciduous forest and grassland were used over a 23 year period as well as precipitation and soil moisture data. The role of time scales on vegetation dynamics analysis was appraised using both entropy rescaling and correlation analysis. This resulted in that soil moisture at 5 cm and 25cm are potentially more efficient to use for vegetation dynamics monitoring at finer time scale compared to precipitation. Albeit soil moisture at 5 cm and 25 cm series are highly correlated (R2>0.64), it appeared that 5 cm soil moisture series can better explain the variability of vegetation growth. A logarithmic transformation of soil moisture and precipitation data increased correlation with NDVI for the different time scales considered. Based on a monthly time scale we came out with a relationship between vegetation index and the couple soil moisture and precipitation [NDVI=a*Log(% soil moisture)+b*Log(Precipitation)+c] with R2>0.25 for each vegetation type. Further, we proposed to assess vegetation green-up using logistic regression model and transinformation entropy using the couple soil moisture and precipitation as independent variables and vegetation growth metrics (NDVI, NDVI ratio, NDVI slope) as the dependent variable. The study is still ongoing and the results will surely contribute to the knowledge in large scale vegetation monitoring. Keywords: Precipitation, soil moisture, vegetation growth, entropy Time scale, Logarithmic transformation and correlation between soil moisture and NDVI, precipitation and

  20. The effect of row structure on soil moisture retrieval accuracy from passive microwave data.

    PubMed

    Xingming, Zheng; Kai, Zhao; Yangyang, Li; Jianhua, Ren; Yanling, Ding

    2014-01-01

    Row structure causes the anisotropy of microwave brightness temperature (TB) of soil surface, and it also can affect soil moisture retrieval accuracy when its influence is ignored in the inversion model. To study the effect of typical row structure on the retrieved soil moisture and evaluate if there is a need to introduce this effect into the inversion model, two ground-based experiments were carried out in 2011. Based on the observed C-band TB, field soil and vegetation parameters, row structure rough surface assumption (Q p model and discrete model), including the effect of row structure, and flat rough surface assumption (Q p model), ignoring the effect of row structure, are used to model microwave TB of soil surface. Then, soil moisture can be retrieved, respectively, by minimizing the difference of the measured and modeled TB. The results show that soil moisture retrieval accuracy based on the row structure rough surface assumption is approximately 0.02 cm(3)/cm(3) better than the flat rough surface assumption for vegetated soil, as well as 0.015 cm(3)/cm(3) better for bare and wet soil. This result indicates that the effect of row structure cannot be ignored for accurately retrieving soil moisture of farmland surface when C-band is used.

  1. Remote monitoring of soil moisture using airborne microwave radiometers

    NASA Technical Reports Server (NTRS)

    Kroll, C. L.

    1973-01-01

    The current status of microwave radiometry is provided. The fundamentals of the microwave radiometer are reviewed with particular reference to airborne operations, and the interpretative procedures normally used for the modeling of the apparent temperature are presented. Airborne microwave radiometer measurements were made over selected flight lines in Chickasha, Oklahoma and Weslaco, Texas. Extensive ground measurements of soil moisture were made in support of the aircraft mission over the two locations. In addition, laboratory determination of the complex permittivities of soil samples taken from the flight lines were made with varying moisture contents. The data were analyzed to determine the degree of correlation between measured apparent temperatures and soil moisture content.

  2. The Soil Moisture Active and Passive (SMAP) Mission

    NASA Technical Reports Server (NTRS)

    Entekhabi, Dara; Nijoku, Eni G.; ONeill, Peggy E.; Kellogg, Kent H.; Crow, Wade T.; Edelstein, Wendy N.; Entin, Jared K.; Goodman, Shawn D.; Jackson, Thomas J.; Johnson, Joel; hide

    2009-01-01

    The Soil Moisture Active and Passive (SMAP) Mission is one of the first Earth observation satellites being developed by NASA in response to the National Research Council s Decadal Survey. SMAP will make global measurements of the moisture present at Earth's land surface and will distinguish frozen from thawed land surfaces. Direct observations of soil moisture and freeze/thaw state from space will allow significantly improved estimates of water, energy and carbon transfers between land and atmosphere. Soil moisture measurements are also of great importance in assessing flooding and monitoring drought. SMAP observations can help mitigate these natural hazards, resulting in potentially great economic and social benefits. SMAP soil moisture and freeze/thaw timing observations will also reduce a major uncertainty in quantifying the global carbon balance by helping to resolve an apparent missing carbon sink on land over the boreal latitudes. The SMAP mission concept would utilize an L-band radar and radiometer. These instruments will share a rotating 6-meter mesh reflector antenna to provide high-resolution and high-accuracy global maps of soil moisture and freeze/thaw state every two to three days. The SMAP instruments provide direct measurements of surface conditions. In addition, the SMAP project will use these observations with advanced modeling and data assimilation to provide deeper root-zone soil moisture and estimates of land surface-atmosphere exchanges of water, energy and carbon. SMAP is scheduled for a 2014 launch date

  3. Vegetation Response to Rainfall and Soil Moisture Variability in Botswana

    DTIC Science & Technology

    1991-01-01

    Effects of Varying Soil Type on the NDVI /Rainfall and NDVI /Soil Moisture...examine the effects of different soil types on the vegetation growth/rainfall relationship. The goals are to determine whether differences in the water-use...34first step" in removing the soil effect (Huete et al., 1985). Indeed, no large-scale soil corrections have been attempted as yet on NDVI data.

  4. Core vs. Bulk Samples in Soil-Moisture Tension Analyses

    Treesearch

    Walter M. Broadfoot

    1954-01-01

    The usual laboratory procedure in determining soil-moisture tension values is to use "undisturbed" soil cores for tensions up to 60 cm. of water and bulk soil samples for higher tensions. Low tensions are usually obtained with a tension table and the higher tensions by use of pressure plate apparatus. In tension analysis at the Vicksburg Infiltration Project...

  5. Exploiting Soil Moisture, Precipitation, and Streamflow Observations to Evaluate Soil Moisture/Runoff Coupling in Land Surface Models

    NASA Astrophysics Data System (ADS)

    Crow, W. T.; Chen, F.; Reichle, R. H.; Xia, Y.; Liu, Q.

    2018-05-01

    Accurate partitioning of precipitation into infiltration and runoff is a fundamental objective of land surface models tasked with characterizing the surface water and energy balance. Temporal variability in this partitioning is due, in part, to changes in prestorm soil moisture, which determine soil infiltration capacity and unsaturated storage. Utilizing the National Aeronautics and Space Administration Soil Moisture Active Passive Level-4 soil moisture product in combination with streamflow and precipitation observations, we demonstrate that land surface models (LSMs) generally underestimate the strength of the positive rank correlation between prestorm soil moisture and event runoff coefficients (i.e., the fraction of rainfall accumulation volume converted into stormflow runoff during a storm event). Underestimation is largest for LSMs employing an infiltration-excess approach for stormflow runoff generation. More accurate coupling strength is found in LSMs that explicitly represent subsurface stormflow or saturation-excess runoff generation processes.

  6. Pupal development of Ceratitis capitata (Diptera: Tephritidae) and Diachasmimorpha longicaudata (Hymenoptera: Braconidae) at different moisture values in four soil types.

    PubMed

    Bento, F de M M; Marques, R N; Costa, M L Z; Walder, J M M; Silva, A P; Parra, J R P

    2010-08-01

    This study aimed to evaluate adult emergence and duration of the pupal stage of the Mediterranean fruit fly, Ceratitis capitata (Wiedemann), and emergence of the fruit fly parasitoid, Diachasmimorpha longicaudata (Ashmead), under different moisture conditions in four soil types, using soil water matric potential. Pupal stage duration in C. capitata was influenced differently for males and females. In females, only soil type affected pupal stage duration, which was longer in a clay soil. In males, pupal stage duration was individually influenced by moisture and soil type, with a reduction in pupal stage duration in a heavy clay soil and in a sandy clay, with longer duration in the clay soil. As matric potential decreased, duration of the pupal stage of C. capitata males increased, regardless of soil type. C. capitata emergence was affected by moisture, regardless of soil type, and was higher in drier soils. The emergence of D. longicaudata adults was individually influenced by soil type and moisture factors, and the number of emerged D. longicaudata adults was three times higher in sandy loam and lower in a heavy clay soil. Always, the number of emerged adults was higher at higher moisture conditions. C. capitata and D. longicaudata pupal development was affected by moisture and soil type, which may facilitate pest sampling and allow release areas for the parasitoid to be defined under field conditions.

  7. The Soil Moisture Active and Passive (SMAP) Mission

    USDA-ARS?s Scientific Manuscript database

    The Soil Moisture Active and Passive (SMAP) Mission is one of the first Earth observation satellites being developed by NASA in response to the National Research Council’s Decadal Survey. SMAP will make global measurements of the moisture present at Earth's land surface and will distinguish frozen f...

  8. Effects of neutron source type on soil moisture measurement

    Treesearch

    Irving Goldberg; Norman A. MacGillivray; Robert R. Ziemer

    1967-01-01

    A number of radioisotopes have recently become commercially available as alternatives to radium-225 in moisture gauging devices using alpha-neutron sources for determining soil moisture, for well logging, and for other industrial applications in which hydrogenous materials are measured.

  9. Soil moisture variation patterns observed in Hand County, South Dakota

    NASA Technical Reports Server (NTRS)

    Jones, E. B.; Owe, M.; Schmugge, T. J. (Principal Investigator)

    1981-01-01

    Soil moisture data were taken during 1976 (April, June, October), 1977 (April, May, June), and 1978 (May, June, July) Hand County, South Dakota as part of the ground truth used in NASA's aircraft experiments to study the use of microwave radiometers for the remote sensing of soil moisture. The spatial variability observed on the ground during each of the sampling events was studied. The data reported are the mean gravimetric soil moisture contained in three surface horizon depths: 0 to 2.5, 0 to 5 and 0 to 10 cm. The overall moisture levels ranged from extremely dry conditions in June 1976 to very wet in May 1978, with a relatively even distribution of values within that range. It is indicated that well drained sites have to be partitioned from imperfectly drained areas when attempting to characterize the general moisture profile throughout an area of varying soil and cover type conditions. It is also found that the variability in moisture content is greatest in the 0 to 2.5 cm measurements and decreases as the measurements are integrated over a greater depth. It is also determined that the sampling intensity of 10 measurements per km is adequate to estimate the mean moisture with an uncertainty of + or - 3 percent under average moisture conditions in areas of moderate to good drainage.

  10. Light, soil moisture, and tree reproduction in hardwood forest openings.

    Treesearch

    Leon S. Minckler; John D. Woerheide; Richard C. Schlesinger

    1973-01-01

    Light, soil moisture, and tree reproduction were measured at five positions in six openings on each of three aspects in southern Illinois. Amount of light received was clearly related to position in the light openings, opening size, and aspect. More moisture was available in the centers of the openings, although 4 years after openings were made the differences...

  11. Automated Quality Control of in Situ Soil Moisture from the North American Soil Moisture Database Using NLDAS-2 Products

    NASA Astrophysics Data System (ADS)

    Ek, M. B.; Xia, Y.; Ford, T.; Wu, Y.; Quiring, S. M.

    2015-12-01

    The North American Soil Moisture Database (NASMD) was initiated in 2011 to provide support for developing climate forecasting tools, calibrating land surface models and validating satellite-derived soil moisture algorithms. The NASMD has collected data from over 30 soil moisture observation networks providing millions of in situ soil moisture observations in all 50 states as well as Canada and Mexico. It is recognized that the quality of measured soil moisture in NASMD is highly variable due to the diversity of climatological conditions, land cover, soil texture, and topographies of the stations and differences in measurement devices (e.g., sensors) and installation. It is also recognized that error, inaccuracy and imprecision in the data set can have significant impacts on practical operations and scientific studies. Therefore, developing an appropriate quality control procedure is essential to ensure the data is of the best quality. In this study, an automated quality control approach is developed using the North American Land Data Assimilation System phase 2 (NLDAS-2) Noah soil porosity, soil temperature, and fraction of liquid and total soil moisture to flag erroneous and/or spurious measurements. Overall results show that this approach is able to flag unreasonable values when the soil is partially frozen. A validation example using NLDAS-2 multiple model soil moisture products at the 20 cm soil layer showed that the quality control procedure had a significant positive impact in Alabama, North Carolina, and West Texas. It had a greater impact in colder regions, particularly during spring and autumn. Over 433 NASMD stations have been quality controlled using the methodology proposed in this study, and the algorithm will be implemented to control data quality from the other ~1,200 NASMD stations in the near future.

  12. Modification of Soil Temperature and Moisture Budgets by Snow Processes

    NASA Astrophysics Data System (ADS)

    Feng, X.; Houser, P.

    2006-12-01

    Snow cover significantly influences the land surface energy and surface moisture budgets. Snow thermally insulates the soil column from large and rapid temperature fluctuations, and snow melting provides an important source for surface runoff and soil moisture. Therefore, it is important to accurately understand and predict the energy and moisture exchange between surface and subsurface associated with snow accumulation and ablation. The objective of this study is to understand the impact of land surface model soil layering treatment on the realistic simulation of soil temperature and soil moisture. We seek to understand how many soil layers are required to fully take into account soil thermodynamic properties and hydrological process while also honoring efficient calculation and inexpensive computation? This work attempts to address this question using field measurements from the Cold Land Processes Field Experiment (CLPX). In addition, to gain a better understanding of surface heat and surface moisture transfer process between land surface and deep soil involved in snow processes, numerical simulations were performed at several Meso-Cell Study Areas (MSAs) of CLPX using the Center for Ocean-Land-Atmosphere (COLA) Simplified Version of the Simple Biosphere Model (SSiB). Measurements of soil temperature and soil moisture were analyzed at several CLPX sites with different vegetation and soil features. The monthly mean vertical profile of soil temperature during October 2002 to July 2003 at North Park Illinois River exhibits a large near surface variation (<5 cm), reveals a significant transition zone from 5 cm to 25 cm, and becomes uniform beyond 25cm. This result shows us that three soil layers are reasonable in solving the vertical variation of soil temperature at these study sites. With 6 soil layers, SSiB also captures the vertical variation of soil temperature during entire winter season, featuring with six soil layers, but the bare soil temperature is

  13. Mapping surface soil moisture with L-band radiometric measurements

    NASA Technical Reports Server (NTRS)

    Wang, James R.; Shiue, James C.; Schmugge, Thomas J.; Engman, Edwin T.

    1989-01-01

    A NASA C-130 airborne remote sensing aircraft was used to obtain four-beam pushbroom microwave radiometric measurements over two small Kansas tall-grass prairie region watersheds, during a dry-down period after heavy rainfall in May and June, 1987. While one of the watersheds had been burned 2 months before these measurements, the other had not been burned for over a year. Surface soil-moisture data were collected at the time of the aircraft measurements and correlated with the corresponding radiometric measurements, establishing a relationship for surface soil-moisture mapping. Radiometric sensitivity to soil moisture variation is higher in the burned than in the unburned watershed; surface soil moisture loss is also faster in the burned watershed.

  14. Soil moisture and evapotranspiration predictions using Skylab data

    NASA Technical Reports Server (NTRS)

    Myers, V. I. (Principal Investigator); Moore, D. G.; Horton, M. L.; Russell, M. J.

    1975-01-01

    The author has identified the following significant results. Multispectral reflectance and emittance data from the Skylab workshop were evaluated for prediction of evapotranspiration and soil moisture for an irrigated region of southern Texas. Wavelengths greater than 2.1 microns were required to spectrally distinguish between wet and dry fallow surfaces. Thermal data provided a better estimate of soil moisture than did data from the reflective bands. Thermal data were dependent on soil moisture but not on the type of agricultural land use. The emittance map, when used in conjunction with existing models, did provide an estimate of evapotranspiration rates. Surveys of areas of high soil moisture can be accomplished with space altitude thermal data. Thermal data will provide a reliable input into irrigation scheduling.

  15. Airborne gamma radiation soil moisture measurements over short flight lines

    NASA Technical Reports Server (NTRS)

    Peck, Eugene L.; Carrol, Thomas R.; Lipinski, Daniel M.

    1990-01-01

    Results are presented on airborne gamma radiation measurements of soil moisture condition, carried out along short flight lines as part of the First International Satellite Land Surface Climatology Project Field Experiment (FIFE). Data were collected over an area in Kansas during the summers of 1987 and 1989. The airborne surveys, together with ground measurements, provide the most comprehensive set of airborne and ground truth data available in the U.S. for calibrating and evaluating airborne gamma flight lines. Analysis showed that, using standard National Weather Service weights for the K, Tl, and Gc radiation windows, the airborne soil moisture estimates for the FIFE lines had a root mean square error of no greater than 3.0 percent soil moisture. The soil moisture estimates for sections having acquisition time of at least 15 sec were found to be reliable.

  16. The NASA Soil Moisture Active Passive (SMAP) Mission: Overview

    NASA Technical Reports Server (NTRS)

    O'Neill, Peggy; Entekhabi, Dara; Njoku, Eni; Kellogg, Kent

    2011-01-01

    The Soil Moisture Active Passive (SMAP) mission is one of the first Earth observation satellites being developed by NASA in response to the National Research Council?s Decadal Survey [1]. Its mission design consists of L-band radiometer and radar instruments sharing a rotating 6-m mesh reflector antenna to provide high-resolution and high-accuracy global maps of soil moisture and freeze/thaw state every 2-3 days. The combined active/passive microwave soil moisture product will have a spatial resolution of 10 km and a mean latency of 24 hours. In addition, the SMAP surface observations will be combined with advanced modeling and data assimilation to provide deeper root zone soil moisture and net ecosystem exchange of carbon. SMAP is expected to launch in the late 2014 - early 2015 time frame.

  17. SMAP Level 4 Surface and Root Zone Soil Moisture

    NASA Technical Reports Server (NTRS)

    Reichle, R.; De Lannoy, G.; Liu, Q.; Ardizzone, J.; Kimball, J.; Koster, R.

    2017-01-01

    The SMAP Level 4 soil moisture (L4_SM) product provides global estimates of surface and root zone soil moisture, along with other land surface variables and their error estimates. These estimates are obtained through assimilation of SMAP brightness temperature observations into the Goddard Earth Observing System (GEOS-5) land surface model. The L4_SM product is provided at 9 km spatial and 3-hourly temporal resolution and with about 2.5 day latency. The soil moisture and temperature estimates in the L4_SM product are validated against in situ observations. The L4_SM product meets the required target uncertainty of 0.04 m(exp. 3)m(exp. -3), measured in terms of unbiased root-mean-square-error, for both surface and root zone soil moisture.

  18. A quantitative comparison of soil moisture inversion algorithms

    NASA Technical Reports Server (NTRS)

    Zyl, J. J. van; Kim, Y.

    2001-01-01

    This paper compares the performance of four bare surface radar soil moisture inversion algorithms in the presence of measurement errors. The particular errors considered include calibration errors, system thermal noise, local topography and vegetation cover.

  19. Aircraft active microwave measurements for estimating soil moisture

    NASA Technical Reports Server (NTRS)

    Jackson, T. J.; Chang, A.; Schmugge, T. J.

    1981-01-01

    Both active and passive microwave sensors are sensitive to variations in near-surface soil moisture. The principal advantage of active microwave systems for soil moisture applications is that high spatial resolution can be retained even at satellite attitudes. The considered investigation is concerned with the use of active microwave scatterometers for estimating near-surface soil moisture. Microwave scatterometer data were obtained during a series of three aircraft flights over a group of Oklahoma research watersheds during May 1978. Data were obtained for the C, L, and P bands at angles of incidence between 5 and 50 degrees. The best results were obtained using C band data at incidence angles of 10 and 15 degrees and soil moisture depth of 0 to 15 cm. These results were in excellent agreement with the conclusions of the truck-mounted scatterometer measurement program reported by Ulaby et al. (1978, 1979).

  20. Soil moisture monitoring in Candelaro basin, Southern Italy

    NASA Astrophysics Data System (ADS)

    Campana, C.; Gigante, V.; Iacobellis, V.

    2012-04-01

    The signature of the hydrologic regime can be investigated, in principle, by recognizing the main mechanisms of runoff generation that take place in the basin and affect the seasonal behavior or the rainfall-driven events. In this framework, besides the implementation of hydrological models, a crucial role should be played by direct observation of key state variables such as soil moisture at different depths and different distances from the river network. In fact, understanding hydrological systems is often limited by the frequency and spatial distribution of observations. Experimental catchments, which are field laboratories with long-term measurements of hydrological variables, are not only sources of data but also sources of knowledge. Wireless distributed sensing platforms are a key technology to address the need for overcoming field limitations such as conflicts between soil use and cable connections. A stand-alone wireless network system has been installed for continuous monitoring of soil water contents at multiple depths along a transect located in Celone basin (sub-basin of Candelaro basin in Puglia, Southern Italy). The transect consists of five verticals, each one having three soil water content sensors at multiple depths: 0,05 m, 0,6 m and 1,2 m below the ground level. The total length of the transect is 307 m and the average distance between the verticals is 77 m. The main elements of the instrumental system installed are: fifteen Decagon 10HS Soil Moisture Sensors, five Decagon Em50R Wireless Radio Data Loggers, one Rain gauge, one Decagon Data Station and one Campbell CR1000 Data Logger. Main advantages of the system as described and presented in this work are that installation of the wireless network system is fast and easy to use, data retrieval and monitoring information over large spatial scales can be obtained in (near) real-time mode and finally other type of sensors can be connected to the system, also offering wide potentials for future

  1. Predicting root zone soil moisture with soil properties and satellite near-surface moisture data across the conterminous United States

    NASA Astrophysics Data System (ADS)

    Baldwin, D.; Manfreda, S.; Keller, K.; Smithwick, E. A. H.

    2017-03-01

    Satellite-based near-surface (0-2 cm) soil moisture estimates have global coverage, but do not capture variations of soil moisture in the root zone (up to 100 cm depth) and may be biased with respect to ground-based soil moisture measurements. Here, we present an ensemble Kalman filter (EnKF) hydrologic data assimilation system that predicts bias in satellite soil moisture data to support the physically based Soil Moisture Analytical Relationship (SMAR) infiltration model, which estimates root zone soil moisture with satellite soil moisture data. The SMAR-EnKF model estimates a regional-scale bias parameter using available in situ data. The regional bias parameter is added to satellite soil moisture retrievals before their use in the SMAR model, and the bias parameter is updated continuously over time with the EnKF algorithm. In this study, the SMAR-EnKF assimilates in situ soil moisture at 43 Soil Climate Analysis Network (SCAN) monitoring locations across the conterminous U.S. Multivariate regression models are developed to estimate SMAR parameters using soil physical properties and the moderate resolution imaging spectroradiometer (MODIS) evapotranspiration data product as covariates. SMAR-EnKF root zone soil moisture predictions are in relatively close agreement with in situ observations when using optimal model parameters, with root mean square errors averaging 0.051 [cm3 cm-3] (standard error, s.e. = 0.005). The average root mean square error associated with a 20-fold cross-validation analysis with permuted SMAR parameter regression models increases moderately (0.082 [cm3 cm-3], s.e. = 0.004). The expected regional-scale satellite correction bias is negative in four out of six ecoregions studied (mean = -0.12 [-], s.e. = 0.002), excluding the Great Plains and Eastern Temperate Forests (0.053 [-], s.e. = 0.001). With its capability of estimating regional-scale satellite bias, the SMAR-EnKF system can predict root zone soil moisture over broad extents and has

  2. Soil Moisture Dynamics under Corn, Soybean, and Perennial Kura Clover

    NASA Astrophysics Data System (ADS)

    Ochsner, T.; Venterea, R. T.

    2009-12-01

    Rising global food and energy consumption call for increased agricultural production, whereas rising concerns for environmental quality call for farming systems with more favorable environmental impacts. Improved understanding and management of plant-soil water interactions are central to meeting these twin challenges. The objective of this research was to compare the temporal dynamics of soil moisture under contrasting cropping systems suited for the Midwestern region of the United States. Precipitation, infiltration, drainage, evapotranspiration, soil water storage, and freeze/thaw processes were measured hourly for three years in field plots of continuous corn (Zea mays L.), corn/soybean [Glycine max (L.) Merr.] rotation, and perennial kura clover (Trifolium ambiguum M. Bieb.) in southeastern Minnesota. The evapotranspiration from the perennial clover most closely followed the temporal dynamics of precipitation, resulting in deep drainage which was reduced up to 50% relative to the annual crops. Soil moisture utilization also continued later into the fall under the clover than under the annual crops. In the annual cropping systems, crop sequence influenced the soil moisture dynamics. Soybean following corn and continuous corn exhibited evapotranspiration which was 80 mm less than and deep drainage which was 80 mm greater than that of corn following soybean. These differences occurred primarily during the spring and were associated with differences in early season plant growth between the systems. In the summer, soil moisture depletion was up to 30 mm greater under corn than soybean. Crop residue also played an important role in the soil moisture dynamics. Higher amounts of residue were associated with reduced soil freezing. This presentation will highlight key aspects of the soil moisture dynamics for these contrasting cropping systems across temporal scales ranging from hours to years. The links between soil moisture dynamics, crop yields, and nutrient leaching

  3. Soil moisture at local scale: Measurements and simulations

    NASA Astrophysics Data System (ADS)

    Romano, Nunzio

    2014-08-01

    Soil moisture refers to the water present in the uppermost part of a field soil and is a state variable controlling a wide array of ecological, hydrological, geotechnical, and meteorological processes. The literature on soil moisture is very extensive and is developing so rapidly that it might be considered ambitious to seek to present the state of the art concerning research into this key variable. Even when covering investigations about only one aspect of the problem, there is a risk of some inevitable omission. A specific feature of the present essay, which may make this overview if not comprehensive at least of particular interest, is that the reader is guided through the various traditional and more up-to-date methods by the central thread of techniques developed to measure soil moisture interwoven with applications of modeling tools that exploit the observed datasets. This paper restricts its analysis to the evolution of soil moisture at the local (spatial) scale. Though a somewhat loosely defined term, it is linked here to a characteristic length of the soil volume investigated by the soil moisture sensing probe. After presenting the most common concepts and definitions about the amount of water stored in a certain volume of soil close to the land surface, this paper proceeds to review ground-based methods for monitoring soil moisture and evaluates modeling tools for the analysis of the gathered information in various applications. Concluding remarks address questions of monitoring and modeling of soil moisture at scales larger than the local scale with the related issue of data aggregation. An extensive, but not exhaustive, list of references is provided, enabling the reader to gain further insights into this subject.

  4. Development of an Objective High Spatial Resolution Soil Moisture Index

    NASA Astrophysics Data System (ADS)

    Zavodsky, B.; Case, J.; White, K.; Bell, J. R.

    2015-12-01

    Drought detection, analysis, and mitigation has become a key challenge for a diverse set of decision makers, including but not limited to operational weather forecasters, climatologists, agricultural interests, and water resource management. One tool that is heavily used is the United States Drought Monitor (USDM), which is derived from a complex blend of objective data and subjective analysis on a state-by-state basis using a variety of modeled and observed precipitation, soil moisture, hydrologic, and vegetation and crop health data. The NASA Short-term Prediction Research and Transition (SPoRT) Center currently runs a real-time configuration of the Noah land surface model (LSM) within the NASA Land Information System (LIS) framework. The LIS-Noah is run at 3-km resolution for local numerical weather prediction (NWP) and situational awareness applications at select NOAA/National Weather Service (NWS) forecast offices over the Continental U.S. (CONUS). To enhance the practicality of the LIS-Noah output for drought monitoring and assessing flood potential, a 30+-year soil moisture climatology has been developed in an attempt to place near real-time soil moisture values in historical context at county- and/or watershed-scale resolutions. This LIS-Noah soil moisture climatology and accompanying anomalies is intended to complement the current suite of operational products, such as the North American Land Data Assimilation System phase 2 (NLDAS-2), which are generated on a coarser-resolution grid that may not capture localized, yet important soil moisture features. Daily soil moisture histograms are used to identify the real-time soil moisture percentiles at each grid point according to the county or watershed in which the grid point resides. Spatial plots are then produced that map the percentiles as proxies to the different USDM categories. This presentation will highlight recent developments of this gridded, objective soil moisture index, comparison to subjective

  5. A Methodology for Soil Moisture Retrieval from Land Surface Temperature, Vegetation Index, Topography and Soil Type

    NASA Astrophysics Data System (ADS)

    Pradhan, N. R.

    2015-12-01

    Soil moisture conditions have an impact upon hydrological processes, biological and biogeochemical processes, eco-hydrology, floods and droughts due to changing climate, near-surface atmospheric conditions and the partition of incoming solar and long-wave radiation between sensible and latent heat fluxes. Hence, soil moisture conditions virtually effect on all aspects of engineering / military engineering activities such as operational mobility, detection of landmines and unexploded ordinance, natural material penetration/excavation, peaking factor analysis in dam design etc. Like other natural systems, soil moisture pattern can vary from completely disorganized (disordered, random) to highly organized. To understand this varying soil moisture pattern, this research utilized topographic wetness index from digital elevation models (DEM) along with vegetation index from remotely sensed measurements in red and near-infrared bands, as well as land surface temperature (LST) in the thermal infrared bands. This research developed a methodology to relate a combined index from DEM, LST and vegetation index with the physical soil moisture properties of soil types and the degree of saturation. The advantage in using this relationship is twofold: first it retrieves soil moisture content at the scale of soil data resolution even though the derived indexes are in a coarse resolution, and secondly the derived soil moisture distribution represents both organized and disorganized patterns of actual soil moisture. The derived soil moisture is used in driving the hydrological model simulations of runoff, sediment and nutrients.

  6. Galvanic Cell Type Sensor for Soil Moisture Analysis.

    PubMed

    Gaikwad, Pramod; Devendrachari, Mruthyunjayachari Chattanahalli; Thimmappa, Ravikumar; Paswan, Bhuneshwar; Raja Kottaichamy, Alagar; Makri Nimbegondi Kotresh, Harish; Thotiyl, Musthafa Ottakam

    2015-07-21

    Here we report the first potentiometric sensor for soil moisture analysis by bringing in the concept of Galvanic cells wherein the redox energies of Al and conducting polyaniline are exploited to design a battery type sensor. The sensor consists of only simple architectural components, and as such they are inexpensive and lightweight, making it suitable for on-site analysis. The sensing mechanism is proved to be identical to a battery type discharge reaction wherein polyaniline redox energy changes from the conducting to the nonconducting state with a resulting voltage shift in the presence of soil moisture. Unlike the state of the art soil moisture sensors, a signal derived from the proposed moisture sensor is probe size independent, as it is potentiometric in nature and, hence, can be fabricated in any shape or size and can provide a consistent output signal under the strong aberration conditions often encountered in soil moisture analysis. The sensor is regenerable by treating with 1 M HCl and can be used for multiple analysis with little read out hysteresis. Further, a portable sensor is fabricated which can provide warning signals to the end user when the moisture levels in the soil go below critically low levels, thereby functioning as a smart device. As the sensor is inexpensive, portable, and potentiometric, it opens up avenues for developing effective and energy efficient irrigation strategies, understanding the heat and water transfer at the atmosphere-land interface, understanding soil mechanics, forecasting the risk of natural calamities, and so on.

  7. Soil Moisture Sensing Using Spaceborne GNSS Reflections: Comparison of CYGNSS Reflectivity to SMAP Soil Moisture

    NASA Astrophysics Data System (ADS)

    Chew, C. C.; Small, E. E.

    2018-05-01

    This paper quantifies the relationship between forward scattered L-band Global Navigation Satellite System (GNSS) signals, recorded by the Cyclone Global Navigation Satellite System (CYGNSS) constellation and Soil Moisture Active Passive (SMAP) soil moisture (SM). Although designed for tropical ocean surface wind sensing, the CYGNSS receivers also record GNSS reflections over land. The CYGNSS observations of reflection power are compared to SMAP SM between March 2017 and February 2018. A strong, positive linear relationship exists between changes in CYGNSS reflectivity and changes in SMAP SM, but not between the absolute magnitudes of the two observations. The sensitivity of CYGNSS reflectivity to SM varies spatially and can be used to convert reflectivity to estimates of SM. The unbiased root-mean-square difference between daily averaged CYGNSS-derived SM and SMAP SM is 0.045 cm3/cm3 and is similarly low between CYGNSS and in situ SM. These results show that CYGNSS, and future GNSS reflection missions, could provide global SM observations.

  8. FDR Soil Moisture Sensor for Environmental Testing and Evaluation

    NASA Astrophysics Data System (ADS)

    Linmao, Ye; longqin, Xue; guangzhou, Zhang; haibo, Chen; likuai, Shi; zhigang, Wu; gouhe, Yu; yanbin, Wang; sujun, Niu; Jin, Ye; Qi, Jin

    To test the affect of environmental stresses on a adaptability of soil moisture capacitance sensor(FDR) a number of stresses were induced including vibrational shock as well as temperature and humidity through the use of a CH-I constant humidity chamber with variable temperature. A Vibrational platform was used to exam the resistance and structural integrity of the sensor after vibrations simulating the process of using, transporting and handling the sensor. A Impactive trial platform was used to test the resistance and structural integrity of the sensor after enduring repeated mechanical shocks. An CH-I constant humidity chamber with high-low temperature was used to test the adaptability of sensor in different environments with high temperature, low temperature and constant humidity. Otherwise, scope of magnetic force line of sensor was also tested in this paper. Test show:the capacitance type soil moisture sensor spread a feeling machine to bear heat, high wet and low temperature, at bear impact and vibration experiment in pass an examination, is a kind of environment to adapt to ability very strong instrument;Spread a feeling machine moreover electric field strength function radius scope 7 cms.

  9. Evaluation of the validated soil moisture product from the SMAP radiometer

    USDA-ARS?s Scientific Manuscript database

    In this study, we used a multilinear regression approach to retrieve surface soil moisture from NASA’s Soil Moisture Active Passive (SMAP) satellite data to create a global dataset of surface soil moisture which is consistent with ESA’s Soil Moisture and Ocean Salinity (SMOS) satellite retrieved sur...

  10. Effects of Recent Regional Soil Moisture Variability on Global Net Ecosystem CO2 Exchange

    NASA Astrophysics Data System (ADS)

    Jones, L. A.; Madani, N.; Kimball, J. S.; Reichle, R. H.; Colliander, A.

    2017-12-01

    Soil moisture exerts a major regional control on the inter-annual variability of the global land sink for atmospheric CO2. In semi-arid regions, annual biomass production is closely coupled to variability in soil moisture availability, while in cold-season-affected regions, summer drought offsets the effects of advancing spring phenology. Availability of satellite solar-induced fluorescence (SIF) observations and improvements in atmospheric inversions has led to unprecedented ability to monitor atmospheric sink strength. However, discrepancies still exist between such top-down estimates as atmospheric inversion and bottom-up process and satellite driven models, indicating that relative strength, mechanisms, and interaction of driving factors remain poorly understood. We use soil moisture fields informed by Soil Moisture Active Passive Mission (SMAP) observations to compare recent (2015-2017) and historic (2000-2014) variability in net ecosystem land-atmosphere CO2 exchange (NEE). The operational SMAP Level 4 Carbon (L4C) product relates ground-based flux tower measurements to other bottom-up and global top-down estimates to underlying soil moisture and other driving conditions using data-assimilation-based SMAP Level 4 Soil Moisture (L4SM). Droughts in coastal Brazil, South Africa, Eastern Africa, and an anomalous wet period in Eastern Australia were observed by L4C. A seasonal seesaw pattern of below-normal sink strength at high latitudes relative to slightly above-normal sink strength for mid-latitudes was also observed. Whereas SMAP-based soil moisture is relatively informative for short-term temporal variability, soil moisture biases that vary in space and with season constrain the ability of the L4C estimates to accurately resolve NEE. Such biases might be caused by irrigation and plant-accessible ground-water. Nevertheless, SMAP L4C daily NEE estimates connect top-down estimates to variability of effective driving factors for accurate estimates of regional

  11. Satellite Based Soil Moisture Product Validation Using NOAA-CREST Ground and L-Band Observations

    NASA Astrophysics Data System (ADS)

    Norouzi, H.; Campo, C.; Temimi, M.; Lakhankar, T.; Khanbilvardi, R.

    2015-12-01

    Soil moisture content is among most important physical parameters in hydrology, climate, and environmental studies. Many microwave-based satellite observations have been utilized to estimate this parameter. The Advanced Microwave Scanning Radiometer 2 (AMSR2) is one of many remotely sensors that collects daily information of land surface soil moisture. However, many factors such as ancillary data and vegetation scattering can affect the signal and the estimation. Therefore, this information needs to be validated against some "ground-truth" observations. NOAA - Cooperative Remote Sensing and Technology (CREST) center at the City University of New York has a site located at Millbrook, NY with several insitu soil moisture probes and an L-Band radiometer similar to Soil Moisture Passive and Active (SMAP) one. This site is among SMAP Cal/Val sites. Soil moisture information was measured at seven different locations from 2012 to 2015. Hydra probes are used to measure six of these locations. This study utilizes the observations from insitu data and the L-Band radiometer close to ground (at 3 meters height) to validate and to compare soil moisture estimates from AMSR2. Analysis of the measurements and AMSR2 indicated a weak correlation with the hydra probes and a moderate correlation with Cosmic-ray Soil Moisture Observing System (COSMOS probes). Several differences including the differences between pixel size and point measurements can cause these discrepancies. Some interpolation techniques are used to expand point measurements from 6 locations to AMSR2 footprint. Finally, the effect of penetration depth in microwave signal and inconsistencies with other ancillary data such as skin temperature is investigated to provide a better understanding in the analysis. The results show that the retrieval algorithm of AMSR2 is appropriate under certain circumstances. This validation algorithm and similar study will be conducted for SMAP mission. Keywords: Remote Sensing, Soil

  12. Effect of Soil Type and Moisture Availability on the Foraging Behavior of the Formosan Subterranean Termite (Isoptera: Rhinotermitidae)

    USDA-ARS?s Scientific Manuscript database

    This study examined the influence of soil type and moisture availability on termite foraging behavior. Physical properties of the soil affected both tunneling behavior and mud tube construction. Termites tunneled through sand faster than top soil and clay. In containers with top soil and clay, termi...

  13. Fiber Optic Thermo-Hygrometers for Soil Moisture Monitoring.

    PubMed

    Leone, Marco; Principe, Sofia; Consales, Marco; Parente, Roberto; Laudati, Armando; Caliro, Stefano; Cutolo, Antonello; Cusano, Andrea

    2017-06-20

    This work deals with the fabrication, prototyping, and experimental validation of a fiber optic thermo-hygrometer-based soil moisture sensor, useful for rainfall-induced landslide prevention applications. In particular, we recently proposed a new generation of fiber Bragg grating (FBGs)-based soil moisture sensors for irrigation purposes. This device was realized by integrating, inside a customized aluminum protection package, a FBG thermo-hygrometer with a polymer micro-porous membrane. Here, we first verify the limitations, in terms of the volumetric water content (VWC) measuring range, of this first version of the soil moisture sensor for its exploitation in landslide prevention applications. Successively, we present the development, prototyping, and experimental validation of a novel, optimized version of a soil VWC sensor, still based on a FBG thermo-hygrometer, but able to reliably monitor, continuously and in real-time, VWC values up to 37% when buried in the soil.

  14. Fiber Optic Thermo-Hygrometers for Soil Moisture Monitoring

    PubMed Central

    Leone, Marco; Principe, Sofia; Consales, Marco; Parente, Roberto; Laudati, Armando; Caliro, Stefano; Cutolo, Antonello; Cusano, Andrea

    2017-01-01

    This work deals with the fabrication, prototyping, and experimental validation of a fiber optic thermo-hygrometer-based soil moisture sensor, useful for rainfall-induced landslide prevention applications. In particular, we recently proposed a new generation of fiber Bragg grating (FBGs)-based soil moisture sensors for irrigation purposes. This device was realized by integrating, inside a customized aluminum protection package, a FBG thermo-hygrometer with a polymer micro-porous membrane. Here, we first verify the limitations, in terms of the volumetric water content (VWC) measuring range, of this first version of the soil moisture sensor for its exploitation in landslide prevention applications. Successively, we present the development, prototyping, and experimental validation of a novel, optimized version of a soil VWC sensor, still based on a FBG thermo-hygrometer, but able to reliably monitor, continuously and in real-time, VWC values up to 37% when buried in the soil. PMID:28632172

  15. Soil moisture dynamics modeling considering multi-layer root zone.

    PubMed

    Kumar, R; Shankar, V; Jat, M K

    2013-01-01

    The moisture uptake by plant from soil is a key process for plant growth and movement of water in the soil-plant system. A non-linear root water uptake (RWU) model was developed for a multi-layer crop root zone. The model comprised two parts: (1) model formulation and (2) moisture flow prediction. The developed model was tested for its efficiency in predicting moisture depletion in a non-uniform root zone. A field experiment on wheat (Triticum aestivum) was conducted in the sub-temperate sub-humid agro-climate of Solan, Himachal Pradesh, India. Model-predicted soil moisture parameters, i.e., moisture status at various depths, moisture depletion and soil moisture profile in the root zone, are in good agreement with experiment results. The results of simulation emphasize the utility of the RWU model across different agro-climatic regions. The model can be used for sound irrigation management especially in water-scarce humid, temperate, arid and semi-arid regions and can also be integrated with a water transport equation to predict the solute uptake by plant biomass.

  16. Reconciling spatial and temporal soil moisture effects on afternoon rainfall

    PubMed Central

    Guillod, Benoit P.; Orlowsky, Boris; Miralles, Diego G.; Teuling, Adriaan J.; Seneviratne, Sonia I.

    2015-01-01

    Soil moisture impacts on precipitation have been strongly debated. Recent observational evidence of afternoon rain falling preferentially over land parcels that are drier than the surrounding areas (negative spatial effect), contrasts with previous reports of a predominant positive temporal effect. However, whether spatial effects relating to soil moisture heterogeneity translate into similar temporal effects remains unknown. Here we show that afternoon precipitation events tend to occur during wet and heterogeneous soil moisture conditions, while being located over comparatively drier patches. Using remote-sensing data and a common analysis framework, spatial and temporal correlations with opposite signs are shown to coexist within the same region and data set. Positive temporal coupling might enhance precipitation persistence, while negative spatial coupling tends to regionally homogenize land surface conditions. Although the apparent positive temporal coupling does not necessarily imply a causal relationship, these results reconcile the notions of moisture recycling with local, spatially negative feedbacks. PMID:25740589

  17. Aircraft scatterometer observations of soil moisture on rangeland watersheds

    NASA Technical Reports Server (NTRS)

    Jackson, T. J.; Oneill, P. E.

    1983-01-01

    Extensive studies conducted by several researchers using truck-mounted active microwave sensors have shown the sensitivity of these sensors to soil moisture variations. The logical extension of these results is the evaluation of similar systems at lower resolutions typical of operational systems. Data collected during a series of aircraft flights in 1978 and 1980 over four rangeland watersheds located near Chickasha, Oklahoma, were analyzed in this study. These data included scatterometer measurements made at 1.6 and 4.75 GHz using a NASA aircraft and ground observations of soil moisture for a wide range of moisture conditions. Data were analyzed for consistency and compared to previous truck and aircraft results. Results indicate that the sensor system is capable of providing consistent estimates of soil moisture under the conditions tested.

  18. Creating soil moisture maps based on radar satellite imagery

    NASA Astrophysics Data System (ADS)

    Hnatushenko, Volodymyr; Garkusha, Igor; Vasyliev, Volodymyr

    2017-10-01

    The presented work is related to a study of mapping soil moisture basing on radar data from Sentinel-1 and a test of adequacy of the models constructed on the basis of data obtained from alternative sources. Radar signals are reflected from the ground differently, depending on its properties. In radar images obtained, for example, in the C band of the electromagnetic spectrum, soils saturated with moisture usually appear in dark tones. Although, at first glance, the problem of constructing moisture maps basing on radar data seems intuitively clear, its implementation on the basis of the Sentinel-1 data on an industrial scale and in the public domain is not yet available. In the process of mapping, for verification of the results, measurements of soil moisture obtained from logs of the network of climate stations NOAA US Climate Reference Network (USCRN) were used. This network covers almost the entire territory of the United States. The passive microwave radiometers of Aqua and SMAP satellites data are used for comparing processing. In addition, other supplementary cartographic materials were used, such as maps of soil types and ready moisture maps. The paper presents a comparison of the effect of the use of certain methods of roughening the quality of radar data on the result of mapping moisture. Regression models were constructed showing dependence of backscatter coefficient values Sigma0 for calibrated radar data of different spatial resolution obtained at different times on soil moisture values. The obtained soil moisture maps of the territories of research, as well as the conceptual solutions about automation of operations of constructing such digital maps, are presented. The comparative assessment of the time required for processing a given set of radar scenes with the developed tools and with the ESA SNAP product was carried out.

  19. Soil moisture and soil temperature variability among three plant communities in a High Arctic Lake Basin

    NASA Astrophysics Data System (ADS)

    Davis, M. L.; Konkel, J.; Welker, J. M.; Schaeffer, S. M.

    2017-12-01

    Soil moisture and soil temperature are critical to plant community distribution and soil carbon cycle processes in High Arctic tundra. As environmental drivers of soil biochemical processes, the predictability of soil moisture and soil temperature by vegetation zone in High Arctic landscapes has significant implications for the use of satellite imagery and vegetation distribution maps to estimate of soil gas flux rates. During the 2017 growing season, we monitored soil moisture and soil temperature weekly at 48 sites in dry tundra, moist tundra, and wet grassland vegetation zones in a High Arctic lake basin. Soil temperature in all three communities reflected fluctuations in air temperature throughout the season. Mean soil temperature was highest in the dry tundra community at 10.5±0.6ºC, however, did not differ between moist tundra and wet grassland communities (2.7±0.6 and 3.1±0.5ºC, respectively). Mean volumetric soil moisture differed significantly among all three plant communities with the lowest and highest soil moisture measured in the dry tundra and wet grassland (30±1.2 and 65±2.7%), respectively. For all three communities, soil moisture was highest during the early season snow melt. Soil moisture in wet grassland remained high with no significant change throughout the season, while significant drying occurred in dry tundra. The most significant change in soil moisture was measured in moist tundra, ranging from 61 to 35%. Our results show different gradients in soil moisture variability within each plant community where: 1) soil moisture was lowest in dry tundra with little change, 2) highest in wet grassland with negligible change, and 3) variable in moist tundra which slowly dried but remained moist. Consistently high soil moisture in wet grassland restricts this plant community to areas with no significant drying during summer. The moist tundra occupies the intermediary areas between wet grassland and dry tundra and experiences the widest range

  20. Soil moisture retrieval from Sentinel-1 satellite data

    NASA Astrophysics Data System (ADS)

    Benninga, Harm-Jan; van der Velde, Rogier; Su, Zhongbo

    2016-04-01

    Reliable up-to-date information on the current water availability and models to evaluate management scenarios are indispensable for skilful water management. The Sentinel-1 radar satellite programme provides an opportunity to monitor water availability (as surface soil moisture) from space on an operational basis at unprecedented fine spatial and temporal resolutions. However, the influences of soil roughness and vegetation cover complicate the retrieval of soil moisture states from radar data. In this contribution, we investigate the sensitivity of Sentinel-1 radar backscatter to soil moisture states and vegetation conditions. The analyses are based on 105 Sentinel-1 images in the period from October 2014 to January 2016 covering the Twente region in the Netherlands. This area is almost flat and has a heterogeneous landscape, including agricultural (mainly grass, cereal and corn), forested and urban land covers. In-situ measurements at 5 cm depth collected from the Twente soil moisture monitoring network are used as reference. This network consists of twenty measurement stations (most of them at agricultural fields) distributed across an area of 50 km × 40 km. The Normalized Difference Vegetation Index (NDVI) derived from optical images is adopted as proxy to represent seasonal variability in vegetation conditions. The results from this sensitivity study provide insight into the potential capability of Sentinel-1 data for the estimation of soil moisture states and they will facilitate the further development of operational retrieval methods. An operationally applicable soil moisture retrieval method requires an algorithm that is usable without the need for area specific model calibration with detailed field information (regarding roughness and vegetation). Because it is not yet clear which method provides the most reliable soil moisture retrievals from Sentinel-1 data, multiple soil moisture retrieval methods will be studied in which the fine spatiotemporal

  1. Synergistic method for boreal soil moisture and soil freeze retrievals using active and passive microwave instruments

    NASA Astrophysics Data System (ADS)

    Smolander, Tuomo; Lemmetyinen, Juha; Rautiainen, Kimmo; Schwank, Mike; Pulliainen, Jouni

    2017-04-01

    Soil moisture and soil freezing are important for diverse hydrological, biogeochemical, and climatological applications. They affect surface energy balance, surface and subsurface water flow, and exchange rates of carbon with the atmosphere. Soil freezing controls important biogeochemical processes, like photosynthetic activity of plants and microbial activity within soils. Permafrost covers approximately 24% of the land surface in the Northern Hemisphere and seasonal freezing occurs on approximately 51% of the area. The retrieval method presented is based on an inversion technique and applies a semiempirical backscattering model that describes the dependence of radar backscattering of forest as a function of stem volume, soil permittivity, the extinction coefficient of forest canopy, surface roughness, incidence angle, and radar frequency. It gives an estimate of soil permittivity using active microwave measurements. Applying a Bayesian assimilation scheme, it is also possible to use other soil permittivity retrievals to regulate this estimate to combine for example low resolution passive observations with high resolution active observations for a synergistic retrieval. This way the higher variance in the active retrieval can be constricted with the passive retrieval when at the same time the spatial resolution of the product is improved compared to the passive-only retrieval. The retrieved soil permittivity estimate can be used to detect soil freeze/thaw state by considering the soil to be frozen when the estimate is below a threshold value. The permittivity retrieval can also be used to estimate the relative moisture of the soil. The method was tested using SAR (Synthetic Aperture Radar) measurements from ENVISAT ASAR instrument for the years 2010-2012 and from Sentinel-1 satellite for the years 2015-2016 in Sodankylä area in Northern Finland. The synergistic method was tested combining the SAR measurements with a SMOS (Soil Moisture Ocean Salinity) radiometer

  2. NASA SMAPVEX 15 Field Campaign Measures Soil Moisture Over Arizona

    NASA Image and Video Library

    2015-09-09

    NASA's SMAP (Soil Moisture Active Passive) satellite observatory conducted a field experiment as part of its soil moisture data product validation program in southern Arizona on Aug. 2-18, 2015. The images here represent the distribution of soil moisture over the SMAPVEX15 (SMAP Validation Experiment 2015) experiment domain, as measured by the Passive Active L-band System (PALS) developed by NASA's Jet Propulsion Laboratory, Pasadena, California, which was installed onboard a DC-3 aircraft operated by Airborne Imaging, Inc. Blue and green colors denote wet conditions and dry conditions are marked by red and orange. The black lines show the nominal flight path of PALS. The measurements show that on the first day, the domain surface was wet overall, but had mostly dried down by the second measurement day. On the third day, there was a mix of soil wetness. The heterogeneous soil moisture distribution over the domain is typical for the area during the North American Monsoon season and provides excellent conditions for SMAP soil moisture product validation and algorithm enhancement. The images are based on brightness temperature measured by the PALS instrument gridded on a grid with 0.6-mile (1-kilometer) pixel size. They do not yet compensate for surface characteristics, such as vegetation and topography. That work is currently in progress. http://photojournal.jpl.nasa.gov/catalog/PIA19879

  3. Dependence of soil respiration on soil temperature and soil moisture in successional forests in Southern China

    USGS Publications Warehouse

    Tang, X.-L.; Zhou, G.-Y.; Liu, S.-G.; Zhang, D.-Q.; Liu, S.-Z.; Li, Ji; Zhou, C.-Y.

    2006-01-01

    The spatial and temporal variations in soil respiration and its relationship with biophysical factors in forests near the Tropic of Cancer remain highly uncertain. To contribute towards an improvement of actual estimates, soil respiration rates, soil temperature, and soil moisture were measured in three successional subtropical forests at the Dinghushan Nature Reserve (DNR) in southern China from March 2003 to February 2005. The overall objective of the present study was to analyze the temporal variations of soil respiration and its biophysical dependence in these forests. The relationships between biophysical factors and soil respiration rates were compared in successional forests to test the hypothesis that these forests responded similarly to biophysical factors. The seasonality of soil respiration coincided with the seasonal climate pattern, with high respiration rates in the hot humid season (April-September) and with low rates in the cool dry season (October-March). Soil respiration measured at these forests showed a clear increasing trend with the progressive succession. Annual mean (±SD) soil respiration rate in the DNR forests was (9.0 ± 4.6) Mg CO2-C/hm2per year, ranging from (6.1 ± 3.2) Mg CO2-C/hm2per year in early successional forests to (10.7 ± 4.9) Mg CO2-C/hm2 per year in advanced successional forests. Soil respiration was correlated with both soil temperature and moisture. The T/M model, where the two biophysical variables are driving factors, accounted for 74%-82% of soil respiration variation in DNR forests. Temperature sensitivity decreased along progressive succession stages, suggesting that advanced-successional forests have a good ability to adjust to temperature. In contrast, moisture increased with progressive succession processes. This increase is caused, in part, by abundant respirators in advanced-successional forest, where more soil moisture is needed to maintain their activities.

  4. Assessment of the SMAP Passive Soil Moisture Product

    NASA Technical Reports Server (NTRS)

    Chan, Steven K.; Bindlish, Rajat; O'Neill, Peggy E.; Njoku, Eni; Jackson, Tom; Colliander, Andreas; Chen, Fan; Burgin, Mariko; Dunbar, Scott; Piepmeier, Jeffrey; hide

    2016-01-01

    The National Aeronautics and Space Administration (NASA) Soil Moisture Active Passive (SMAP) satellite mission was launched on January 31, 2015. The observatory was developed to provide global mapping of high-resolution soil moisture and freeze-thaw state every two to three days using an L-band (active) radar and an L-band (passive) radiometer. After an irrecoverable hardware failure of the radar on July 7, 2015, the radiometer-only soil moisture product became the only operational Level 2 soil moisture product for SMAP. The product provides soil moisture estimates posted on a 36 kilometer Earth-fixed grid produced using brightness temperature observations from descending passes. Within months after the commissioning of the SMAP radiometer, the product was assessed to have attained preliminary (beta) science quality, and data were released to the public for evaluation in September 2015. The product is available from the NASA Distributed Active Archive Center at the National Snow and Ice Data Center. This paper provides a summary of the Level 2 Passive Soil Moisture Product (L2_SM_P) and its validation against in situ ground measurements collected from different data sources. Initial in situ comparisons conducted between March 31, 2015 and October 26, 2015, at a limited number of core validation sites (CVSs) and several hundred sparse network points, indicate that the V-pol Single Channel Algorithm (SCA-V) currently delivers the best performance among algorithms considered for L2_SM_P, based on several metrics. The accuracy of the soil moisture retrievals averaged over the CVSs was 0.038 cubic meter per cubic meter unbiased root-mean-square difference (ubRMSD), which approaches the SMAP mission requirement of 0.040 cubic meter per cubic meter.

  5. Using a soil moisture and precipitation network for satellite validation

    USDA-ARS?s Scientific Manuscript database

    A long term in situ network for the study of soil moisture and precipitation was deployed in north central Iowa, in cooperation between USDA and NASA. A total of 20 dual precipitation gages were established across a watershed landscape with an area of approximately 600 km2. In addition, four soil mo...

  6. Soil CO2 evolution and root respiration in 11 year-old Loblolly Pine (Pinus taeda) Plantations as Affected by Moisture and Nutrient Availability

    Treesearch

    Chris A. Maier; L.W. Kress

    2000-01-01

    We measured soil CO2 evolution rates with (Sff) and without (Sms) the forest floor litter and root respiration monthly in 11-year-old loblolly pine (Pinus taeda L.) plantations during the fourth year of fertilization and irrigation treatments. Values of Sff...

  7. ELEVATED TEMPERATURE, SOIL MOISTURE AND SEASONALITY BUT NOT CO2 AFFECT CANOPY ASSIMILATION AND SYSTEM RESPIRATION IN SEEDLING DOUGLAS-FIR ECOSYSTEMS

    EPA Science Inventory

    We investigated the effects of elevated atmospheric CO2 and air temperature on C cycling in trees and associated soil system, focusing on canopy CO2 assimilation (Asys) and system CO2 loss through respiration (Rsys). We hypothesized that both elevated CO2 and elevated temperature...

  8. Effect of soil moisture on seasonal variation in indoor radon concentration: modelling and measurements in 326 Finnish houses

    PubMed Central

    Arvela, H.; Holmgren, O.; Hänninen, P.

    2016-01-01

    The effect of soil moisture on seasonal variation in soil air and indoor radon is studied. A brief review of the theory of the effect of soil moisture on soil air radon has been presented. The theoretical estimates, together with soil moisture measurements over a period of 10 y, indicate that variation in soil moisture evidently is an important factor affecting the seasonal variation in soil air radon concentration. Partitioning of radon gas between the water and air fractions of soil pores is the main factor increasing soil air radon concentration. On two example test sites, the relative standard deviation of the calculated monthly average soil air radon concentration was 17 and 26 %. Increased soil moisture in autumn and spring, after the snowmelt, increases soil gas radon concentrations by 10–20 %. In February and March, the soil gas radon concentration is in its minimum. Soil temperature is also an important factor. High soil temperature in summer increased the calculated soil gas radon concentration by 14 %, compared with winter values. The monthly indoor radon measurements over period of 1 y in 326 Finnish houses are presented and compared with the modelling results. The model takes into account radon entry, climate and air exchange. The measured radon concentrations in autumn and spring were higher than expected and it can be explained by the seasonal variation in the soil moisture. The variation in soil moisture is a potential factor affecting markedly to the high year-to-year variation in the annual or seasonal average radon concentrations, observed in many radon studies. PMID:25899611

  9. Comparisons of Satellite Soil Moisture, an Energy Balance Model Driven by LST Data and Point Measurements

    NASA Astrophysics Data System (ADS)

    Laiolo, Paola; Gabellani, Simone; Rudari, Roberto; Boni, Giorgio; Puca, Silvia

    2013-04-01

    Soil moisture plays a fundamental role in the partitioning of mass and energy fluxes between land surface and atmosphere, thereby influencing climate and weather, and it is important in determining the rainfall-runoff response of catchments; moreover, in hydrological modelling and flood forecasting, a correct definition of moisture conditions is a key factor for accurate predictions. Different sources of information for the estimation of the soil moisture state are currently available: satellite data, point measurements and model predictions. All are affected by intrinsic uncertainty. Among different satellite sensors that can be used for soil moisture estimation three major groups can be distinguished: passive microwave sensors (e.g., SSMI), active sensors (e.g. SAR, Scatterometers), and optical sensors (e.g. Spectroradiometers). The last two families, mainly because of their temporal and spatial resolution seem the most suitable for hydrological applications In this work soil moisture point measurements from 10 sensors in the Italian territory are compared of with the satellite products both from the HSAF project SM-OBS-2, derived from the ASCAT scatterometer, and from ACHAB, an operative energy balance model that assimilate LST data derived from MSG and furnishes daily an evaporative fraction index related to soil moisture content for all the Italian region. Distributed comparison of the ACHAB and SM-OBS-2 on the whole Italian territory are performed too.

  10. Evaluation of Long-term Soil Moisture Proxies in the U.S. Great Plains

    NASA Astrophysics Data System (ADS)

    Yuan, S.; Quiring, S. M.

    2016-12-01

    Soil moisture plays an important role in land-atmosphere interactions through both surface energy and water balances. However, despite its importance, there are few long-term records of observed soil moisture for investigating long-term spatial and temporal variations of soil moisture. Hence, it is necessary to find suitable approximations of soil moisture observations. 5 drought indices will be compared with simulated and observed soil moisture over the U.S. Great Plains during two time periods (1980 - 2012 and 2003 - 2012). Standardized Precipitation Index (SPI), Standardized Precipitation-Evapotranspiration Index (SPEI), Palmer Z Index (zindex) and Crop Moisture Index (CMI) will be calculated by PRISM data. The soil moisture simulations will be derived from NLDAS. In situ soil moisture will be obtained from North American Soil Moisture Database. The evaluation will focus on three main aspects: trends, variations and persistence. The results will support further research investigating long-term variations in soil moisture-climate interactions.

  11. Soil Moisture: The Hydrologic Interface Between Surface and Ground Waters

    NASA Technical Reports Server (NTRS)

    Engman, Edwin T.

    1997-01-01

    A hypothesis is presented that many hydrologic processes display a unique signature that is detectable with microwave remote sensing. These signatures are in the form of the spatial and temporal distributions of surface soil moisture. The specific hydrologic processes that may be detected include groundwater recharge and discharge zones, storm runoff contributing areas, regions of potential and less than potential evapotranspiration (ET), and information about the hydrologic properties of soils. In basin and hillslope hydrology, soil moisture is the interface between surface and ground waters.

  12. Effect of soil type and moisture availability on the foraging behavior of the Formosan subterranean termite (Isoptera: Rhinotermitidae).

    PubMed

    Cornelius, Mary L; Osbrink, Weste L A

    2010-06-01

    This study examined the influence of soil type and moisture availability on termite foraging behavior. Physical properties of the soil affected both tunneling behavior and shelter tube construction. Termites tunneled through sand faster than top soil and clay. In containers with top soil and clay, termites built shelter tubes on the sides of the containers. In containers with sand, termites built shelter tubes directly into the air and covered the sides of the container with a layer of sand. The interaction of soil type and moisture availability affected termite movement, feeding, and survival. In assays with moist soils, termites were more likely to aggregate in top soil over potting soil and peat moss. However, termites were more likely to move into containers with dry peat moss and potting soil than containers with dry sand and clay. Termites were also significantly more likely to move into containers with dry potting soil than dry top soil. In the assay with dry soils, termite mortality was high even though termites were able to travel freely between moist sand and dry soil, possibly due to desiccation caused by contact with dry soil. Evaporation from potting soil and peat moss resulted in significant mortality, whereas termites were able to retain enough moisture in top soil, sand, and clay to survive for 25 d. The interaction of soil type and moisture availability influences the distribution of foraging termites in microhabitats.

  13. Assessment of SMOS Soil Moisture Retrieval Parameters Using Tau-Omega Algorithms for Soil Moisture Deficit Estimation

    NASA Technical Reports Server (NTRS)

    Srivastava, Prashant K.; Han, Dawei; Rico-Ramirez, Miguel A.; O'Neill, Peggy; Islam, Tanvir; Gupta, Manika

    2014-01-01

    Soil Moisture and Ocean Salinity (SMOS) is the latest mission which provides flow of coarse resolution soil moisture data for land applications. However, the efficient retrieval of soil moisture for hydrological applications depends on optimally choosing the soil and vegetation parameters. The first stage of this work involves the evaluation of SMOS Level 2 products and then several approaches for soil moisture retrieval from SMOS brightness temperature are performed to estimate Soil Moisture Deficit (SMD). The most widely applied algorithm i.e. Single channel algorithm (SCA), based on tau-omega is used in this study for the soil moisture retrieval. In tau-omega, the soil moisture is retrieved using the Horizontal (H) polarisation following Hallikainen dielectric model, roughness parameters, Fresnel's equation and estimated Vegetation Optical Depth (tau). The roughness parameters are empirically calibrated using the numerical optimization techniques. Further to explore the improvement in retrieval models, modifications have been incorporated in the algorithms with respect to the sources of the parameters, which include effective temperatures derived from the European Center for Medium-Range Weather Forecasts (ECMWF) downscaled using the Weather Research and Forecasting (WRF)-NOAH Land Surface Model and Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) while the s is derived from MODIS Leaf Area Index (LAI). All the evaluations are performed against SMD, which is estimated using the Probability Distributed Model following a careful calibration and validation integrated with sensitivity and uncertainty analysis. The performance obtained after all those changes indicate that SCA-H using WRF-NOAH LSM downscaled ECMWF LST produces an improved performance for SMD estimation at a catchment scale.

  14. Soil Texture Often Exerts a Stronger Influence Than Precipitation on Mesoscale Soil Moisture Patterns

    NASA Astrophysics Data System (ADS)

    Dong, Jingnuo; Ochsner, Tyson E.

    2018-03-01

    Soil moisture patterns are commonly thought to be dominated by land surface characteristics, such as soil texture, at small scales and by atmospheric processes, such as precipitation, at larger scales. However, a growing body of evidence challenges this conceptual model. We investigated the structural similarity and spatial correlations between mesoscale (˜1-100 km) soil moisture patterns and land surface and atmospheric factors along a 150 km transect using 4 km multisensor precipitation data and a cosmic-ray neutron rover, with a 400 m diameter footprint. The rover was used to measure soil moisture along the transect 18 times over 13 months. Spatial structures of soil moisture, soil texture (sand content), and antecedent precipitation index (API) were characterized using autocorrelation functions and fitted with exponential models. Relative importance of land surface characteristics and atmospheric processes were compared using correlation coefficients (r) between soil moisture and sand content or API. The correlation lengths of soil moisture, sand content, and API ranged from 12-32 km, 13-20 km, and 14-45 km, respectively. Soil moisture was more strongly correlated with sand content (r = -0.536 to -0.704) than with API for all but one date. Thus, land surface characteristics exhibit coherent spatial patterns at scales up to 20 km, and those patterns often exert a stronger influence than do precipitation patterns on mesoscale spatial patterns of soil moisture.

  15. Soil moisture - precipitation feedbacks in observations and models (Invited)

    NASA Astrophysics Data System (ADS)

    Taylor, C.

    2013-12-01

    There is considerable uncertainty about the strength, geographical extent, and even the sign of feedbacks between soil moisture and precipitation. Whilst precipitation trivially increases soil moisture, the impact of soil moisture, via surface fluxes, on convective rainfall is far from straight-forward, and likely depends on space and time scale, soil and synoptic conditions, and the nature of the convection itself. In considering how daytime convection responds to surface fluxes, large-scale models based on convective parameterisations may not necessarily provide reliable depictions, particularly given their long-standing inability to reproduce a realistic diurnal cycle of convection. On the other hand, long-term satellite data provide the potential to establish robust relationships between soil moisture and precipitation across the world, notwithstanding some fundamental weaknesses and uncertainties in the datasets. Here, results from regional and global satellite-based analyses are presented. Globally, using 3-hourly precipitation and daily soil moisture datasets, a methodology has been developed to compare the statistics of antecedent soil moisture in the region of localised afternoon rain events (Taylor et al 2012). Specifically the analysis tests whether there are any significant differences in pre-event soil moisture between rainfall maxima and nearby (50-100km) minima. The results reveal a clear signal across a number of semi-arid regions, most notably North Africa, indicating a preference for afternoon rain over drier soil. Analysis by continent and by climatic zone reveals that this signal (locally a negative feedback) is evident in other continents and climatic zones, but is somewhat weaker. This may be linked to the inherent geographical differences across the world, as detection of a feedback requires water-stressed surfaces coincident with frequent active convective initiations. The differences also reflect the quality and utility of the soil moisture

  16. Soil Moisture Controls the Thermal Habitat of Active Layer Soils in the McMurdo Dry Valleys, Antarctica

    NASA Astrophysics Data System (ADS)

    Wlostowski, A. N.; Gooseff, M. N.; Adams, B. J.

    2018-01-01

    Antarctic soil ecosystems are strongly controlled by abiotic habitat variables. Regional climate change in the McMurdo Dry Valleys is expected to cause warming over the next century, leading to an increase in frequency of freeze-thaw cycling in the soil habitat. Previous studies show that physiological stress associated with freeze-thaw cycling adversely affects invertebrate populations by decreasing abundance and positively selecting for larger body sizes. However, it remains unclear whether or not climate warming will indeed enhance the frequency of annual freeze-thaw cycling and associated physiological stresses. This research quantifies the frequency, rate, and spatial heterogeneity of active layer freezing to better understand how regional climate change may affect active layer soil thermodynamics, and, in turn, affect soil macroinvertebrate communities. Shallow active layer temperature, specific conductance, and soil moisture were observed along natural wetness gradients. Field observations show that the frequency and rate of freeze events are nonlinearly related to freezable soil moisture (θf). Over a 2 year period, soils at θf < 0.080 m3/m3 experienced between 15 and 35 freeze events and froze rapidly compared to soils with θf > 0.080 m3/m3, which experienced between 2 and 6 freeze events and froze more gradually. A numerical soil thermodynamic model is able to simulate observed freezing rates across a range of θf, reinforcing a well-known causal relationship between soil moisture and active layer freezing dynamics. Findings show that slight increases in soil moisture can potentially offset the effect of climate warming on exacerbating soil freeze-thaw cycling.

  17. Surface soil moisture retrieval using the L-band synthetic aperture radar onboard the Soil Moisture Active Passive satellite and evaluation at core validation sites

    USDA-ARS?s Scientific Manuscript database

    This paper evaluates the retrieval of soil moisture in the top 5-cm layer at 3-km spatial resolution using L-band dual-copolarized Soil Moisture Active Passive (SMAP) synthetic aperture radar (SAR) data that mapped the globe every three days from mid-April to early July, 2015. Surface soil moisture ...

  18. Soil Moisture Sensing Using Reflected GPS Signals: Description of the GPS Soil Moisture Product.

    NASA Astrophysics Data System (ADS)

    Larson, Kristine; Small, Eric; Chew, Clara

    2015-04-01

    As first demonstrated by the GPS reflections group in 2008, data from GPS networks can be used to monitor multiple parameters of the terrestrial water cycle. The GPS L-band signals take two paths: (1) the "direct" signal travels from the satellite to the antenna, which is typically located 2-3 meters above the ground; (2) the reflected signal interacts with the Earth's surface before traveling to the antenna. The direct signal is used by geophysicists and surveyors to measure the position of the antenna, while the effects of reflected signals are a source of error. If one focuses on the reflected signal rather than the positioning observables, one has a method that is sensitive to surface soil moisture (top 5 cm), vegetation water content, and snow depth. This method - known as GPS Interferometric Reflectometry (GPS-IR) - has a footprint of ~1000 m2 for most GPS sites. This is intermediate in scale to most in situ and satellite observations. A significant advantage of GPS-IR is that data from existing GPS networks can be used without any changes to the instrumentation. This means that there is a new source of cost-effective instrumentation for satellite validation and climate studies. This presentation will provide an overview of the GPS-IR methodology with an emphasis on the soil moisture product. GPS water cycle products are currently produced on a daily basis for a network of ~500 sites in the western United States; results are freely available at http://xenon.colorado.edu/portal. Plans to expand the GPS-IR method to the network of international GPS sites will also be discussed.

  19. Soil moisture retrieval by active/passive microwave remote sensing data

    NASA Astrophysics Data System (ADS)

    Wu, Shengli; Yang, Lijuan

    2012-09-01

    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). Tropical Rainfall Measurement Mission was jointly launched by NASA and NASDA in 1997, whose main task was to observe the precipitation of the area in 40 ° N-40 ° S. It was equipped with active microwave radar sensors (PR) and passive sensor microwave imager (TMI). To accurately estimate bare surface soil moisture, precipitation radar (PR) and microwave imager (TMI) are simultaneously used for observation. According to the frequency and incident angle setting of PR and TMI, we first need to establish a database which includes a large range of surface conditions; and then we use Advanced Integral Equation Model (AIEM) to calculate the backscattering coefficient and emissivity. Meanwhile, under the accuracy of resolution, we use a simplified theoretical model (GO model) and the semi-empirical physical model (Qp Model) to redescribe the process of scattering and radiation. There are quite a lot of parameters effecting backscattering coefficient and emissivity, including soil moisture, surface root mean square height, correlation length, and the correlation function etc. Radar backscattering is strongly affected by the surface roughness, which includes the surface root mean square roughness height, surface correlation length and the correlation function we use. And emissivity is differently affected by the root mean square slope under different polarizations. In general, emissivity decreases with the root mean square slope increases in V polarization, and increases with the root mean square slope increases in H polarization. For the GO model, we found that the backscattering coefficient is only related to the root mean square slope and soil moisture when the incident angle is fixed. And for Qp Model, through the analysis, we found that there is a quite good relationship

  20. Spatial variability of soil moisture retrieved by SMOS satellite

    NASA Astrophysics Data System (ADS)

    Lukowski, Mateusz; Marczewski, Wojciech; Usowicz, Boguslaw; Rojek, Edyta; Slominski, Jan; Lipiec, Jerzy

    2015-04-01

    Standard statistical methods assume that the analysed variables are independent. Since the majority of the processes observed in the nature are continuous in space and time, this assumption introduces a significant limitation for understanding the examined phenomena. In classical approach, valuable information about the locations of examined observations is completely lost. However, there is a branch of statistics, called geostatistics, which is the study of random variables, but taking into account the space where they occur. A common example of so-called "regionalized variable" is soil moisture. Using in situ methods it is difficult to estimate soil moisture distribution because it is often significantly diversified. Thanks to the geostatistical methods, by employing semivariance analysis, it is possible to get the information about the nature of spatial dependences and their lengths. Since the Soil Moisture and Ocean Salinity mission launch in 2009, the estimation of soil moisture spatial distribution for regional up to continental scale started to be much easier. In this study, the SMOS L2 data for Central and Eastern Europe were examined. The statistical and geostatistical features of moisture distributions of this area were studied for selected natural soil phenomena for 2010-2014 including: freezing, thawing, rainfalls (wetting), drying and drought. Those soil water "states" were recognized employing ground data from the agro-meteorological network of ground-based stations SWEX and SMUDP2 data from SMOS. After pixel regularization, without any upscaling, the geostatistical methods were applied directly on Discrete Global Grid (15-km resolution) in ISEA 4H9 projection, on which SMOS observations are reported. Analysis of spatial distribution of SMOS soil moisture, carried out for each data set, in most cases did not show significant trends. It was therefore assumed that each of the examined distributions of soil moisture in the adopted scale satisfies

  1. Using the Spatial Persistence of Soil Moisture Patterns to Estimate Catchment Soil Moisture in Semi-arid Areas

    NASA Astrophysics Data System (ADS)

    Willgoose, G. R.

    2006-12-01

    In humid catchments the spatial distribution of soil water is dominated by subsurface lateral fluxes, which leads to a persistent spatial pattern of soil moisture principally described by the topographic index. In contrast, semi-arid, and dryer, catchments are dominated by vertical fluxes (infiltration and evapotranspiration) and persistent spatial patterns, if they exist, are subtler. In the first part of this presentation the results of a reanalysis of a number of catchment-scale long-term spatially-distributed soil moisture data sets are presented. We concentrate on Tarrawarra and SASMAS, both catchments in Australia that are water-limited for at least part of the year and which have been monitored using a variety of technologies. Using the data from permanently installed instruments (neutron probe and reflectometry) both catchments show persistent patterns at the 1-3 year timescale. This persistent pattern is not evident in the field campaign data where field portable instruments (reflectometry) instruments were used. We argue, based on high-resolution soil moisture semivariograms, that high short-distance variability (100mm scale) means that field portable instrument cannot be replaced at the same location with sufficient accuracy to ensure deterministic repeatability of soil moisture measurements from campaign to campaign. The observed temporal persistence of the spatial pattern can be caused by; (1) permanent features of the landscape (e.g. vegetation, soils), or (2) long term memory in the soil moisture store. We argue that it is permanent in which case it is possible to monitor the soil moisture status of a catchment using a single location measurement (continuous in time) of soil moisture using a permanently installed reflectometry instrument. This instrument will need to be calibrated to the catchment averaged soil moisture but the temporal persistence of the spatial pattern of soil moisture will mean that this calibration will be deterministically

  2. Use of midlatitude soil moisture and meteorological observations to validate soil moisture simulations with biosphere and bucket models

    NASA Technical Reports Server (NTRS)

    Robock, Alan; Vinnikov, Konstantin YA.; Schlosser, C. Adam; Speranskaya, Nina A.; Xue, Yongkang

    1995-01-01

    Soil moisture observations in sites with natural vegetation were made for several decades in the former Soviet Union at hundreds of stations. In this paper, the authors use data from six of these stations from different climatic regimes, along with ancillary meteorological and actinometric data, to demonstrate a method to validate soil moisture simulations with biosphere and bucket models. Some early and current general circulation models (GCMs) use bucket models for soil hydrology calculations. More recently, the Simple Biosphere Model (SiB) was developed to incorporate the effects of vegetation on fluxes of moisture, momentum, and energy at the earth's surface into soil hydrology models. Until now, the bucket and SiB have been verified by comparison with actual soil moisture data only on a limited basis. In this study, a Simplified SiB (SSiB) soil hydrology model and a 15-cm bucket model are forced by observed meteorological and actinometric data every 3 h for 6-yr simulations at the six stations. The model calculations of soil moisture are compared to observations of soil moisture, literally 'ground truth,' snow cover, surface albedo, and net radiation, and with each other. For three of the stations, the SSiB and 15-cm bucket models produce good simulations of seasonal cycles and interannual variations of soil moisture. For the other three stations, there are large errors in the simulations by both models. Inconsistencies in specification of field capacity may be partly responsible. There is no evidence that the SSiB simulations are superior in simulating soil moisture variations. In fact, the models are quite similar since SSiB implicitly has a bucket embedded in it. One of the main differences between the models is in the treatment of runoff due to melting snow in the spring -- SSiB incorrectly puts all the snowmelt into runoff. While producing similar soil moisture simulations, the models produce very different surface latent and sensible heat fluxes, which

  3. Biological soil crust succession impact on soil moisture and temperature in the sub-surface along a rainfall gradient

    NASA Astrophysics Data System (ADS)

    Zaady, E.; Yizhaq, H.; Ashkenazy, Y.

    2012-04-01

    Biological soil crusts produce mucilage sheets of polysaccharides that cover the soil surface. This hydrophobic coating can seal the soil micro-pores and thus cause reduction of water permeability and may influence soil temperature. This study evaluates the impact of crust composition on sub-surface water and temperature over time. We hypothesized that the successional stages of biological soil crusts, affect soil moisture and temperature differently along a rainfall gradient throughout the year. Four experimental sites were established along a rainfall gradient in the western Negev Desert. At each site three treatments; crust removal, pure sand (moving dune) and natural crusted were monitored. Crust successional stage was measured by biophysiological and physical measurements, soil water permeability by field mini-Infiltrometer, soil moisture by neutron scattering probe and temperature by sensors, at different depths. Our main interim conclusions from the ongoing study along the rainfall gradient are: 1. the biogenic crust controls water infiltration into the soil in sand dunes, 2. infiltration was dependent on the composition of the biogenic crust. It was low for higher successional stage crusts composed of lichens and mosses and high with cyanobacterial crust. Thus, infiltration rate controlled by the crust is inverse to the rainfall gradient. Continuous disturbances to the crust increase infiltration rates, 3. despite the different rainfall amounts at the sites, soil moisture content below 50 cm is almost the same. We therefore predict that climate change in areas that are becoming dryer (desertification) will have a positive effect on soil water content and vice versa.

  4. Uncertain soil moisture feedbacks in model projections of Sahel precipitation

    NASA Astrophysics Data System (ADS)

    Berg, Alexis; Lintner, Benjamin R.; Findell, Kirsten; Giannini, Alessandra

    2017-06-01

    Given the uncertainties in climate model projections of Sahel precipitation, at the northern edge of the West African Monsoon, understanding the factors governing projected precipitation changes in this semiarid region is crucial. This study investigates how long-term soil moisture changes projected under climate change may feedback on projected changes of Sahel rainfall, using simulations with and without soil moisture change from five climate models participating in the Global Land Atmosphere Coupling Experiment-Coupled Model Intercomparison Project phase 5 experiment. In four out of five models analyzed, soil moisture feedbacks significantly influence the projected West African precipitation response to warming; however, the sign of these feedbacks differs across the models. These results demonstrate that reducing uncertainties across model projections of the West African Monsoon requires, among other factors, improved mechanistic understanding and constraint of simulated land-atmosphere feedbacks, even at the large spatial scales considered here.Plain Language SummaryClimate model projections of Sahel rainfall remain notoriously uncertain; understanding the physical processes responsible for this uncertainty is thus crucial. Our study focuses on analyzing the feedbacks of <span class="hlt">soil</span> <span class="hlt">moisture</span> changes on model projections of the West African Monsoon under global warming. <span class="hlt">Soil</span> <span class="hlt">moisture</span>-atmosphere interactions have been shown in prior studies to play an important role in this region, but the potential feedbacks of long-term <span class="hlt">soil</span> <span class="hlt">moisture</span> changes on projected precipitation changes have not been investigated specifically. To isolate these feedbacks, we use targeted simulations from five climate models, with and without <span class="hlt">soil</span> <span class="hlt">moisture</span> change. Importantly, we find that climate models exhibit <span class="hlt">soil</span> <span class="hlt">moisture</span>-precipitation feedbacks of different sign in this region: in some models <span class="hlt">soil</span> <span class="hlt">moisture</span> changes amplify precipitation changes</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19760025537','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19760025537"><span>Remote sensing of <span class="hlt">soil</span> <span class="hlt">moisture</span> with microwave radiometers</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Schmugge, T.; Wilheit, T.; Webster, W., Jr.; Gloerson, P.</p> <p>1976-01-01</p> <p>Results are presented that were derived from measurements made by microwave radiometers during the March 1972 and February 1973 flights of National Aeronautics and Space Administration (NASA) Convair-9900 aircraft over agricultural test sites in the southwestern part of United States. The purpose of the missions was to study the use of microwave radiometers for the remote sensing of <span class="hlt">soil</span> <span class="hlt">moisture</span>. The microwave radiometers covered the 0.8- to 21-cm wavelength range. The results show a good linear correlation between the observed microwave brightness temperature and <span class="hlt">moisture</span> content of the 0- to 1-cm layer of the <span class="hlt">soil</span>. The results at the largest wavelength (21 cm) show the greatest sensitivity to <span class="hlt">soil</span> <span class="hlt">moisture</span> variations and indicate the possibility of sensing these variations through a vegetative canopy. The effect of <span class="hlt">soil</span> texture on the emission from the <span class="hlt">soil</span> was also studied and it was found that this effect can be compensated for by expressing <span class="hlt">soil</span> <span class="hlt">moisture</span> as a percent of field capacity for the <span class="hlt">soil</span>. The results were compared with calculations based on a radiative transfer model for layered dielectrics and the agreement is very good at the longer wavelengths. At the shorter wavelengths, surface roughness effects are larger and the agreement becomes poorer.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..15.9120W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..15.9120W"><span><span class="hlt">Soil</span> <span class="hlt">Moisture</span> Extremes Observed by METOP ASCAT: Was 2012 an Exceptional Year?</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wagner, Wolfgang; Paulik, Christoph; Hahn, Sebastian; Melzer, Thomas; Parinussa, Robert; de Jeu, Richard; Dorigo, Wouter; Chung, Daniel; Enenkel, Markus</p> <p>2013-04-01</p> <p>In summer 2012 the international press reported widely about the severe drought that had befallen large parts of the United States. Yet, the US drought was only one of several major droughts that occurred in 2012: Southeastern Europe, Central Asia, Brazil, India, Southern Australia and several other regions suffered from similarly dry <span class="hlt">soil</span> conditions. This raises the question whether 2012 was an exceptionally dry year? In this presentation we will address this question by analyzing global <span class="hlt">soil</span> <span class="hlt">moisture</span> patterns as observed by the Advanced Scatterometer (ASCAT) flown on board of the METOP-A satellite. We firstly compare the 2012 ASCAT <span class="hlt">soil</span> <span class="hlt">moisture</span> data to all available ASCAT measurements acquired by the instrument since the launch of METOP-A in November 2006. Secondly, we compare the 2012 data to a long-term <span class="hlt">soil</span> <span class="hlt">moisture</span> data set derived by merging the ASCAT <span class="hlt">soil</span> <span class="hlt">moisture</span> data with other active and passive microwave <span class="hlt">soil</span> <span class="hlt">moisture</span> retrievals as described by Liu et al. (2012) and Wagner et al. (2012) (see also http://www.esa-soilmoisture-cci.org/). A first trend analysis of the latter long-term <span class="hlt">soil</span> <span class="hlt">moisture</span> data set carried out by Dorigo et al. (2012) has revealed that over the period 1988-2010 significant trends were observed over 27 % of the area covered by the data set, of which 73 % were negative (<span class="hlt">soil</span> drying) and only 27 % were positive (<span class="hlt">soil</span> wetting). In this presentation we will show how the inclusion of the years 2011 and 2012 <span class="hlt">affects</span> the areal extent and strengths of these significant trends. REFERENCES Dorigo, W., R. de Jeu, D. Chung, R. Parinussa, Y. Liu, W. Wagner, D. Fernández-Prieto (2012) Evaluating global trends (1988-2010) in harmonized multi-satellite surface <span class="hlt">soil</span> <span class="hlt">moisture</span>, Geophysical Research Letters, 39, L18405, 1-7. Liu, Y.Y., W.A. Dorigo, R.M. Parinussa, R.A.M. de Jeu, W. Wagner, M.F. McCabe, J.P. Evans, A.I.J.M. van Dijk (2012) Trend-preserving blending of passive and active microwave <span class="hlt">soil</span> <span class="hlt">moisture</span> retrievals, Remote Sensing of Environment</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20020054243&hterms=seasonal+forecast&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dseasonal%2Bforecast','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20020054243&hterms=seasonal+forecast&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dseasonal%2Bforecast"><span>The Impact of <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Initialization On Seasonal Precipitation Forecasts</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Koster, R. D.; Suarez, M. J.; Tyahla, L.; Houser, Paul (Technical Monitor)</p> <p>2002-01-01</p> <p>Some studies suggest that the proper initialization of <span class="hlt">soil</span> <span class="hlt">moisture</span> in a forecasting model may contribute significantly to the accurate prediction of seasonal precipitation, especially over mid-latitude continents. In order for the initialization to have any impact at all, however, two conditions must be satisfied: (1) the initial <span class="hlt">soil</span> <span class="hlt">moisture</span> anomaly must be "remembered" into the forecasted season, and (2) the atmosphere must respond in a predictable way to the <span class="hlt">soil</span> <span class="hlt">moisture</span> anomaly. In our previous studies, we identified the key land surface and atmospheric properties needed to satisfy each condition. Here, we tie these studies together with an analysis of an ensemble of seasonal forecasts. Initial <span class="hlt">soil</span> <span class="hlt">moisture</span> conditions for the forecasts are established by forcing the land surface model with realistic precipitation prior to the start of the forecast period. As expected, the impacts on forecasted precipitation (relative to an ensemble of runs that do not utilize <span class="hlt">soil</span> <span class="hlt">moisture</span> information) tend to be localized over the small fraction of the earth with all of the required land and atmosphere properties.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29124249','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29124249"><span>Relating coccidioidomycosis (valley fever) incidence to <span class="hlt">soil</span> <span class="hlt">moisture</span> conditions.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Coopersmith, E J; Bell, J E; Benedict, K; Shriber, J; McCotter, O; Cosh, M H</p> <p>2017-04-17</p> <p>Coccidioidomycosis (also called Valley fever) is caused by a soilborne fungus, Coccidioides spp. , in arid regions of the southwestern United States. Though some who develop infections from this fungus remain asymptomatic, others develop respiratory disease as a consequence. Less commonly, severe illness and death can occur when the infection spreads to other regions of the body. Previous analyses have attempted to connect the incidence of coccidioidomycosis to broadly available climatic measurements, such as precipitation or temperature. However, with the limited availability of long-term, in situ <span class="hlt">soil</span> <span class="hlt">moisture</span> data sets, it has not been feasible to perform a direct analysis of the relationships between <span class="hlt">soil</span> <span class="hlt">moisture</span> levels and coccidioidomycosis incidence on a larger temporal and spatial scale. Utilizing in situ <span class="hlt">soil</span> <span class="hlt">moisture</span> gauges throughout the southwest from the U.S. Climate Reference Network and a model with which to extend those estimates, this work connects periods of higher and lower <span class="hlt">soil</span> <span class="hlt">moisture</span> in Arizona and California between 2002 and 2014 to the reported incidence of coccidioidomycosis. The results indicate that in both states, coccidioidomycosis incidence is related to <span class="hlt">soil</span> <span class="hlt">moisture</span> levels from previous summers and falls. Stated differently, a higher number of coccidioidomycosis cases are likely to be reported if previous bands of months have been atypically wet or dry, depending on the location.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMEP41C0921A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMEP41C0921A"><span>Downscaling Coarse Scale Microwave <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Product using Machine Learning</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Abbaszadeh, P.; Moradkhani, H.; Yan, H.</p> <p>2016-12-01</p> <p><span class="hlt">Soil</span> <span class="hlt">moisture</span> (SM) is a key variable in partitioning and examining the global water-energy cycle, agricultural planning, and water resource management. It is also strongly coupled with climate change, playing an important role in weather forecasting and drought monitoring and prediction, flood modeling and irrigation management. Although satellite retrievals can provide an unprecedented information of <span class="hlt">soil</span> <span class="hlt">moisture</span> at a global-scale, the products might be inadequate for basin scale study or regional assessment. To improve the spatial resolution of SM, this work presents a novel approach based on Machine Learning (ML) technique that allows for downscaling of the satellite <span class="hlt">soil</span> <span class="hlt">moisture</span> to fine resolution. For this purpose, the SMAP L-band radiometer SM products were used and conditioned on the Variable Infiltration Capacity (VIC) model prediction to describe the relationship between the coarse and fine scale <span class="hlt">soil</span> <span class="hlt">moisture</span> data. The proposed downscaling approach was applied to a western US basin and the products were compared against the available SM data from in-situ gauge stations. The obtained results indicated a great potential of the machine learning technique to derive the fine resolution <span class="hlt">soil</span> <span class="hlt">moisture</span> information that is currently used for land data assimilation applications.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20170006035','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20170006035"><span>Combined Radar-Radiometer Surface <span class="hlt">Soil</span> <span class="hlt">Moisture</span> and Roughness Estimation</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Akbar, Ruzbeh; Cosh, Michael H.; O'Neill, Peggy E.; Entekhabi, Dara; Moghaddam, Mahta</p> <p>2017-01-01</p> <p>A robust physics-based combined radar-radiometer, or Active-Passive, surface <span class="hlt">soil</span> <span class="hlt">moisture</span> and roughness estimation methodology is presented. <span class="hlt">Soil</span> <span class="hlt">moisture</span> and roughness retrieval is performed via optimization, i.e., minimization, of a joint objective function which constrains similar resolution radar and radiometer observations simultaneously. A data-driven and noise-dependent regularization term has also been developed to automatically regularize and balance corresponding radar and radiometer contributions to achieve optimal <span class="hlt">soil</span> <span class="hlt">moisture</span> retrievals. It is shown that in order to compensate for measurement and observation noise, as well as forward model inaccuracies, in combined radar-radiometer estimation surface roughness can be considered a free parameter. Extensive Monte-Carlo numerical simulations and assessment using field data have been performed to both evaluate the algorithms performance and to demonstrate <span class="hlt">soil</span> <span class="hlt">moisture</span> estimation. Unbiased root mean squared errors (RMSE) range from 0.18 to 0.03 cm3cm3 for two different land cover types of corn and soybean. In summary, in the context of <span class="hlt">soil</span> <span class="hlt">moisture</span> retrieval, the importance of consistent forward emission and scattering development is discussed and presented.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29657350','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29657350"><span>Combined Radar-Radiometer Surface <span class="hlt">Soil</span> <span class="hlt">Moisture</span> and Roughness Estimation.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Akbar, Ruzbeh; Cosh, Michael H; O'Neill, Peggy E; Entekhabi, Dara; Moghaddam, Mahta</p> <p>2017-07-01</p> <p>A robust physics-based combined radar-radiometer, or Active-Passive, surface <span class="hlt">soil</span> <span class="hlt">moisture</span> and roughness estimation methodology is presented. <span class="hlt">Soil</span> <span class="hlt">moisture</span> and roughness retrieval is performed via optimization, i.e., minimization, of a joint objective function which constrains similar resolution radar and radiometer observations simultaneously. A data-driven and noise-dependent regularization term has also been developed to automatically regularize and balance corresponding radar and radiometer contributions to achieve optimal <span class="hlt">soil</span> <span class="hlt">moisture</span> retrievals. It is shown that in order to compensate for measurement and observation noise, as well as forward model inaccuracies, in combined radar-radiometer estimation surface roughness can be considered a free parameter. Extensive Monte-Carlo numerical simulations and assessment using field data have been performed to both evaluate the algorithm's performance and to demonstrate <span class="hlt">soil</span> <span class="hlt">moisture</span> estimation. Unbiased root mean squared errors (RMSE) range from 0.18 to 0.03 cm3/cm3 for two different land cover types of corn and soybean. In summary, in the context of <span class="hlt">soil</span> <span class="hlt">moisture</span> retrieval, the importance of consistent forward emission and scattering development is discussed and presented.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5672948','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5672948"><span>Relating coccidioidomycosis (valley fever) incidence to <span class="hlt">soil</span> <span class="hlt">moisture</span> conditions</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Coopersmith, E. J.; Bell, J. E.; Benedict, K.; Shriber, J.; McCotter, O.; Cosh, M. H.</p> <p>2017-01-01</p> <p>Coccidioidomycosis (also called Valley fever) is caused by a soilborne fungus, Coccidioides spp., in arid regions of the southwestern United States. Though some who develop infections from this fungus remain asymptomatic, others develop respiratory disease as a consequence. Less commonly, severe illness and death can occur when the infection spreads to other regions of the body. Previous analyses have attempted to connect the incidence of coccidioidomycosis to broadly available climatic measurements, such as precipitation or temperature. However, with the limited availability of long-term, in situ <span class="hlt">soil</span> <span class="hlt">moisture</span> data sets, it has not been feasible to perform a direct analysis of the relationships between <span class="hlt">soil</span> <span class="hlt">moisture</span> levels and coccidioidomycosis incidence on a larger temporal and spatial scale. Utilizing in situ <span class="hlt">soil</span> <span class="hlt">moisture</span> gauges throughout the southwest from the U.S. Climate Reference Network and a model with which to extend those estimates, this work connects periods of higher and lower <span class="hlt">soil</span> <span class="hlt">moisture</span> in Arizona and California between 2002 and 2014 to the reported incidence of coccidioidomycosis. The results indicate that in both states, coccidioidomycosis incidence is related to <span class="hlt">soil</span> <span class="hlt">moisture</span> levels from previous summers and falls. Stated differently, a higher number of coccidioidomycosis cases are likely to be reported if previous bands of months have been atypically wet or dry, depending on the location. PMID:29124249</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H21I1597B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H21I1597B"><span>Enhancing SMAP <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Retrievals via Superresolution Techniques</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Beale, K. D.; Ebtehaj, A. M.; Romberg, J. K.; Bras, R. L.</p> <p>2017-12-01</p> <p><span class="hlt">Soil</span> <span class="hlt">moisture</span> is a key state variable that modulates land-atmosphere interactions and its high-resolution global scale estimates are essential for improved weather forecasting, drought prediction, crop management, and the safety of troop mobility. Currently, NASA's <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Active/Passive (SMAP) satellite provides a global picture of <span class="hlt">soil</span> <span class="hlt">moisture</span> variability at a resolution of 36 km, which is prohibitive for some hydrologic applications. The goal of this research is to enhance the resolution of SMAP passive microwave retrievals by a factor of 2 to 4 using modern superresolution techniques that rely on the knowledge of high-resolution land surface models. In this work, we explore several super-resolution techniques including an empirical dictionary method, a learned dictionary method, and a three-layer convolutional neural network. Using a year of global high-resolution land surface model simulations as training set, we found that we are able to produce high-resolution <span class="hlt">soil</span> <span class="hlt">moisture</span> maps that outperform the original low-resolution observations both qualitatively and quantitatively. In particular, on a patch-by-patch basis we are able to produce estimates of high-resolution <span class="hlt">soil</span> <span class="hlt">moisture</span> maps that improve on the original low-resolution patches by on average 6% in terms of mean-squared error, and 14% in terms of the structural similarity index.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19820003640','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19820003640"><span>An evaluation of the spatial resolution of <span class="hlt">soil</span> <span class="hlt">moisture</span> information</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hardy, K. R.; Cohen, S. H.; Rogers, L. K.; Burke, H. H. K.; Leupold, R. C.; Smallwood, M. D.</p> <p>1981-01-01</p> <p>Rainfall-amount patterns in the central regions of the U.S. were assessed. The spatial scales of surface features and their corresponding microwave responses in the mid western U.S. were investigated. The usefulness for U.S. government agencies of <span class="hlt">soil</span> <span class="hlt">moisture</span> information at scales of 10 km and 1 km. was ascertained. From an investigation of 494 storms, it was found that the rainfall resulting from the passage of most types of storms produces patterns which can be resolved on a 10 km scale. The land features causing the greatest problem in the sensing of <span class="hlt">soil</span> <span class="hlt">moisture</span> over large agricultural areas with a radiometer are bodies of water. Over the mid-western portions of the U.S., water occupies less than 2% of the total area, the consequently, the water bodies will not have a significant impact on the mapping of <span class="hlt">soil</span> <span class="hlt">moisture</span>. Over most of the areas, measurements at a 10-km resolution would adequately define the distribution of <span class="hlt">soil</span> <span class="hlt">moisture</span>. Crop yield models and hydrological models would give improved results if <span class="hlt">soil</span> <span class="hlt">moisture</span> information at scales of 10 km was available.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H13I1518M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H13I1518M"><span>Compact polarimetric synthetic aperture radar for monitoring <span class="hlt">soil</span> <span class="hlt">moisture</span> condition</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Merzouki, A.; McNairn, H.; Powers, J.; Friesen, M.</p> <p>2017-12-01</p> <p>Coarse resolution <span class="hlt">soil</span> <span class="hlt">moisture</span> maps are currently operationally delivered by ESA's SMOS and NASA's SMAP passive microwaves sensors. Despite this evolution, operational <span class="hlt">soil</span> <span class="hlt">moisture</span> monitoring at the field scale remains challenging. A number of factors contribute to this challenge including the complexity of the retrieval that requires advanced SAR systems with enhanced temporal revisit capabilities. Since the launch of RADARSAT-2 in 2007, Agriculture and Agri-Food Canada (AAFC) has been evaluating the accuracy of these data for estimating surface <span class="hlt">soil</span> <span class="hlt">moisture</span>. Thus, a hybrid (multi-angle/multi-polarization) retrieval approach was found well suited for the planned RADARSAT Constellation Mission (RCM) considering the more frequent relook expected with the three satellite configuration. The purpose of this study is to evaluate the capability of C-band CP data to estimate <span class="hlt">soil</span> <span class="hlt">moisture</span> over agricultural fields, in anticipation of the launch of RCM. In this research we introduce a new CP approach based on the IEM and simulated RCM CP mode intensities from RADARSAT-2 images acquired at different dates. The accuracy of <span class="hlt">soil</span> <span class="hlt">moisture</span> retrieval from the proposed multi-polarization and hybrid methods will be contrasted with that from a more conventional quad-pol approach, and validated against in situ measurements by pooling data collected over AAFC test sites in Ontario, Manitoba and Saskatchewan, Canada.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20020066567','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20020066567"><span>Impact of <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Initialization on Seasonal Weather Prediction</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Koster, Randal D.; Suarez, Max J.; Houser, Paul (Technical Monitor)</p> <p>2002-01-01</p> <p>The potential role of <span class="hlt">soil</span> <span class="hlt">moisture</span> initialization in seasonal forecasting is illustrated through ensembles of simulations with the NASA Seasonal-to-Interannual Prediction Project (NSIPP) model. For each boreal summer during 1997-2001, we generated two 16-member ensembles of 3-month simulations. The first, "AMIP-style" ensemble establishes the degree to which a perfect prediction of SSTs would contribute to the seasonal prediction of precipitation and temperature over continents. The second ensemble is identical to the first, except that the land surface is also initialized with "realistic" <span class="hlt">soil</span> <span class="hlt">moisture</span> contents through the continuous prior application (within GCM simulations leading up to the start of the forecast period) of a daily observational precipitation data set and the associated avoidance of model drift through the scaling of all surface prognostic variables. A comparison of the two ensembles shows that <span class="hlt">soil</span> <span class="hlt">moisture</span> initialization has a statistically significant impact on summertime precipitation and temperature over only a handful of continental regions. These regions agree, to first order, with regions that satisfy three conditions: (1) a tendency toward large initial <span class="hlt">soil</span> <span class="hlt">moisture</span> anomalies, (2) a strong sensitivity of evaporation to <span class="hlt">soil</span> <span class="hlt">moisture</span>, and (3) a strong sensitivity of precipitation to evaporation. The degree to which the initialization improves forecasts relative to observations is mixed, reflecting a critical need for the continued development of model parameterizations and data analysis strategies.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.H31F1177M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.H31F1177M"><span>Agricultural Decision Support Through Robust Assimilation of Satellite Derived <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Estimates</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mishra, V.; Cruise, J.; Mecikalski, J. R.</p> <p>2012-12-01</p> <p><span class="hlt">Soil</span> <span class="hlt">Moisture</span> is a key component in the hydrological process, <span class="hlt">affects</span> surface and boundary layer energy fluxes and is the driving factor in agricultural production. Multiple in situ <span class="hlt">soil</span> <span class="hlt">moisture</span> measuring instruments such as Time-domain Reflectrometry (TDR), Nuclear Probes etc. are in use along with remote sensing methods like Active and Passive Microwave (PM) sensors. In situ measurements, despite being more accurate, can only be obtained at discrete points over small spatial scales. Remote sensing estimates, on the other hand, can be obtained over larger spatial domains with varying spatial and temporal resolutions. <span class="hlt">Soil</span> <span class="hlt">moisture</span> profiles derived from satellite based thermal infrared (TIR) imagery can overcome many of the problems associated with laborious in-situ observations over large spatial domains. An area where <span class="hlt">soil</span> <span class="hlt">moisture</span> observation and assimilation is receiving increasing attention is agricultural crop modeling. This study revolves around the use of the Decision Support System for Agrotechnology Transfer (DSSAT) crop model to simulate corn yields under various forcing scenarios. First, the model was run and calibrated using observed precipitation and model generated <span class="hlt">soil</span> <span class="hlt">moisture</span> dynamics. Next, the modeled <span class="hlt">soil</span> <span class="hlt">moisture</span> was updated using estimates derived from satellite based TIR imagery and the Atmospheric Land Exchange Inverse (ALEXI) model. We selected three climatically different locations to test the concept. Test Locations were selected to represent varied climatology. Bell Mina, Alabama - South Eastern United States, representing humid subtropical climate. Nabb, Indiana - Mid Western United States, representing humid continental climate. Lubbok, Texas - Southern United States, representing semiarid steppe climate. A temporal (2000-2009) correlation analysis of the <span class="hlt">soil</span> <span class="hlt">moisture</span> values from both DSSAT and ALEXI were performed and validated against the Land Information System (LIS) <span class="hlt">soil</span> <span class="hlt">moisture</span> dataset. The results clearly show strong</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H51R..02L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H51R..02L"><span>Four Decades of Microwave Satellite <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Observations: Product validation and inter-satellite comparisons</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lanka, K.; Pan, M.; Wanders, N.; Kumar, D. N.; Wood, E. F.</p> <p>2017-12-01</p> <p>. Although the retrievals from the SMOS mission are <span class="hlt">affected</span> by issues such as RFI, the accuracy is still comparable to or better than that of AMSR-E and ASCAT sensors. All <span class="hlt">soil</span> <span class="hlt">moisture</span> products have indicated better agreement with the ISMN data than the VICSM, which indicate that they produce <span class="hlt">soil</span> <span class="hlt">moisture</span> with better accuracy than the VICSM over the CONUS.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFM.H33F1385B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFM.H33F1385B"><span>Evaluation of the cosmic-ray neutron method for measuring integral <span class="hlt">soil</span> <span class="hlt">moisture</span> dynamics of a forested head water catchment</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bogena, H. R.; Metzen, D.; Baatz, R.; Hendricks Franssen, H.; Huisman, J. A.; Montzka, C.; Vereecken, H.</p> <p>2011-12-01</p> <p>Measurements of low-energy secondary neutron intensity above the <span class="hlt">soil</span> surface by cosmic-ray <span class="hlt">soil</span> <span class="hlt">moisture</span> probes (CRP) can be used to estimate <span class="hlt">soil</span> <span class="hlt">moisture</span> content. CRPs utilise the fact that high-energy neutrons initiated by cosmic rays are moderated (slowed to lower energies) most effectively by collisions with hydrogen atoms contained in water molecules in the <span class="hlt">soil</span>. The conversion of neutron intensity to <span class="hlt">soil</span> <span class="hlt">moisture</span> content can potentially be complicated because neutrons are also moderated by aboveground water storage (e.g. vegetation water content, canopy storage of interception). Recently, it was demonstrated experimentally that <span class="hlt">soil</span> <span class="hlt">moisture</span> content derived from CRP measurements agrees well with average <span class="hlt">moisture</span> content from gravimetric <span class="hlt">soil</span> samples taken within the footprint of the cosmic ray probe, which is proposed to be up to several hundred meters in size [1]. However, the exact extension and shape of the CRP integration footprint is still an open question and it is also unclear how CRP measurements are <span class="hlt">affected</span> by the <span class="hlt">soil</span> <span class="hlt">moisture</span> distribution within the footprint both in horizontal and vertical directions. In this paper, we will take advantage of an extensive wireless <span class="hlt">soil</span> <span class="hlt">moisture</span> sensor network covering most of the estimated footprint of the CRP. The network consists of 150 nodes and 900 <span class="hlt">soil</span> <span class="hlt">moisture</span> sensors which were installed in the small forested Wüstebach catchment (~27 ha) in the framework of the Transregio32 and the Helmholtz initiative TERENO (Terrestrial Environmental Observatories) [2]. This unique <span class="hlt">soil</span> <span class="hlt">moisture</span> data set provides a consistent picture of the hydrological status of the catchment in a high spatial and temporal resolution and thus the opportunity to evaluate the CRP measurements in a rigorous way. We will present first results of the comparison with a specific focus on the sensitivity of the CRP measurements to <span class="hlt">soil</span> <span class="hlt">moisture</span> variation in both the horizontal and vertical direction. Furthermore, the influence of forest</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24836136','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24836136"><span>Fate of 14C-labeled dissolved organic matter in paddy and upland <span class="hlt">soils</span> in responding to <span class="hlt">moisture</span>.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Chen, Xiangbi; Wang, Aihua; Li, Yang; Hu, Lening; Zheng, Hua; He, Xunyang; Ge, Tida; Wu, Jinshui; Kuzyakov, Yakov; Su, Yirong</p> <p>2014-08-01</p> <p><span class="hlt">Soil</span> organic matter (SOM) content in paddy <span class="hlt">soils</span> is higher than that in upland <span class="hlt">soils</span> in tropical and subtropical China. The dissolved organic matter (DOM) concentration, however, is lower in paddy <span class="hlt">soils</span>. We hypothesize that <span class="hlt">soil</span> <span class="hlt">moisture</span> strongly controls the fate of DOM, and thereby leads to differences between the two agricultural <span class="hlt">soils</span> under contrasting management regimens. A 100-day incubation experiment was conducted to trace the fate and biodegradability of DOM in paddy and upland <span class="hlt">soils</span> under three <span class="hlt">moisture</span> levels: 45%, 75%, and 105% of the water holding capacity (WHC). (14)C labeled DOM, extracted from the (14)C labeled rice plant material, was incubated in paddy and upland <span class="hlt">soils</span>, and the mineralization to (14)CO2 and incorporation into microbial biomass were analyzed. Labile and refractory components of the initial (14)C labeled DOM and their respective half-lives were calculated by a double exponential model. During incubation, the mineralization of the initial (14)C labeled DOM in the paddy <span class="hlt">soils</span> was more <span class="hlt">affected</span> by <span class="hlt">moisture</span> than in the upland <span class="hlt">soils</span>. The amount of (14)C incorporated into the microbial biomass (2.4-11.0% of the initial DOM-(14)C activity) was less <span class="hlt">affected</span> by <span class="hlt">moisture</span> in the paddy <span class="hlt">soils</span> than in the upland <span class="hlt">soils</span>. At any of the <span class="hlt">moisture</span> levels, 1) the mineralization of DOM to (14)CO2 within 100 days was 1.2-2.1-fold higher in the paddy <span class="hlt">soils</span> (41.9-60.0% of the initial DOM-(14)C activity) than in the upland <span class="hlt">soils</span> (28.7-35.7%), 2) (14)C activity remaining in solution was significantly lower in the paddy <span class="hlt">soils</span> than in the upland <span class="hlt">soils</span>, and 3) (14)C activity remaining in the same agricultural <span class="hlt">soil</span> solution was not significantly different among the three <span class="hlt">moisture</span> levels after 20 days. Therefore, <span class="hlt">moisture</span> strongly controls DOM fate, but <span class="hlt">moisture</span> was not the key factor in determining the lower DOM in the paddy <span class="hlt">soils</span> than in the upland <span class="hlt">soils</span>. The UV absorbance of DOM at 280 nm indicates less aromaticity of DOM from the paddy <span class="hlt">soils</span> than from the</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li class="active"><span>15</span></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_15 --> <div id="page_16" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li class="active"><span>16</span></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="301"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017JHyd..551..203K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JHyd..551..203K"><span>Automated general temperature correction method for dielectric <span class="hlt">soil</span> <span class="hlt">moisture</span> sensors</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kapilaratne, R. G. C. Jeewantinie; Lu, Minjiao</p> <p>2017-08-01</p> <p>An effective temperature correction method for dielectric sensors is important to ensure the accuracy of <span class="hlt">soil</span> water content (SWC) measurements of local to regional-scale <span class="hlt">soil</span> <span class="hlt">moisture</span> monitoring networks. These networks are extensively using highly temperature sensitive dielectric sensors due to their low cost, ease of use and less power consumption. Yet there is no general temperature correction method for dielectric sensors, instead sensor or site dependent correction algorithms are employed. Such methods become ineffective at <span class="hlt">soil</span> <span class="hlt">moisture</span> monitoring networks with different sensor setups and those that cover diverse climatic conditions and <span class="hlt">soil</span> types. This study attempted to develop a general temperature correction method for dielectric sensors which can be commonly used regardless of the differences in sensor type, climatic conditions and <span class="hlt">soil</span> type without rainfall data. In this work an automated general temperature correction method was developed by adopting previously developed temperature correction algorithms using time domain reflectometry (TDR) measurements to ThetaProbe ML2X, Stevens Hydra probe II and Decagon Devices EC-TM sensor measurements. The rainy day effects removal procedure from SWC data was automated by incorporating a statistical inference technique with temperature correction algorithms. The temperature correction method was evaluated using 34 stations from the International <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Monitoring Network and another nine stations from a local <span class="hlt">soil</span> <span class="hlt">moisture</span> monitoring network in Mongolia. <span class="hlt">Soil</span> <span class="hlt">moisture</span> monitoring networks used in this study cover four major climates and six major <span class="hlt">soil</span> types. Results indicated that the automated temperature correction algorithms developed in this study can eliminate temperature effects from dielectric sensor measurements successfully even without on-site rainfall data. Furthermore, it has been found that actual daily average of SWC has been changed due to temperature effects of dielectric sensors with a</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2007AGUFM.H53H..04S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2007AGUFM.H53H..04S"><span>Pathways of <span class="hlt">soil</span> <span class="hlt">moisture</span> controls on boundary layer dynamics</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Siqueira, M.; Katul, G.; Porporato, A.</p> <p>2007-12-01</p> <p><span class="hlt">Soil</span> <span class="hlt">moisture</span> controls on precipitation are now receiving significant attention in climate systems because the memory of their variability is much slower than the memory of the fast atmospheric processes. We propose a new model that integrates <span class="hlt">soil</span> water dynamics, plant hydraulics and stomatal responses to water availability to estimate root water uptake and available energy partitioning, as well as feedbacks to boundary layer dynamics (in terms of water vapor and heat input to the atmospheric system). Using a simplified homogenization technique, the model solves the intrinsically 3-D <span class="hlt">soil</span> water movement equations by two 1-D coupled Richards' equations. The first resolves the radial water flow from bulk <span class="hlt">soil</span> to <span class="hlt">soil</span>-root interface to estimate root uptake (assuming the vertical gradients in <span class="hlt">moisture</span> persist during the rapid lateral flow), and then it solves vertical water movement through the <span class="hlt">soil</span> following the radial <span class="hlt">moisture</span> adjustments. The coupling between these two equations is obtained by area averaging the <span class="hlt">soil</span> <span class="hlt">moisture</span> in the radial domain (i.e. homogenization) to calculate the vertical fluxes. For each vertical layer, the domain is discretized in axi-symmetrical grid with constant <span class="hlt">soil</span> properties. This is deemed to be appropriate given the fact that the root uptake occurs on much shorter time scales closely following diurnal cycles, while the vertical water movement is more relevant to the inter-storm time scale. We show that this approach was able to explicitly simulate known features of root uptake such as diurnal hysteresis of canopy conductance, water redistribution by roots (hydraulic lift) and downward shift of root uptake during drying cycles. The model is then coupled with an atmospheric boundary layer (ABL) growth model thereby permitting us to explore low-dimensional elements of the interaction between <span class="hlt">soil</span> <span class="hlt">moisture</span> and ABL states commensurate with the lifting condensation level.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110011773','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110011773"><span>NASA <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Active Passive (SMAP) Mission Formulation</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Entekhabi, Dara; Njoku, Eni; ONeill, Peggy; Kellogg, Kent; Entin, Jared</p> <p>2011-01-01</p> <p>The <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Active Passive (SMAP) Mission is one of the first Earth observation satellites being formulated by NASA in response to the 2007 National Research Council s Earth Science Decadal Survey [1]. SMAP s measurement objectives are high-resolution global measurements of near-surface <span class="hlt">soil</span> <span class="hlt">moisture</span> and its freeze-thaw state. These measurements would allow significantly improved estimates of water, energy and carbon transfers between the land and atmosphere. The <span class="hlt">soil</span> <span class="hlt">moisture</span> control of these fluxes is a key factor in the performance of atmospheric models used for weather forecasts and climate projections. <span class="hlt">Soil</span> <span class="hlt">moisture</span> measurements are also of great importance in assessing flooding and monitoring drought. Knowledge gained from SMAP s planned observations can help mitigate these natural hazards, resulting in potentially great economic and societal benefits. SMAP measurements would also yield high resolution spatial and temporal mapping of the frozen or thawed condition of the surface <span class="hlt">soil</span> and vegetation. Observations of <span class="hlt">soil</span> <span class="hlt">moisture</span> and freeze/thaw timing over the boreal latitudes will contribute to reducing a major uncertainty in quantifying the global carbon balance and help resolve an apparent missing carbon sink over land. The SMAP mission would utilize an L-band radar and radiometer sharing a rotating 6-meter mesh reflector antenna (see Figure 1) [2]. The radar and radiometer instruments would be carried onboard a 3-axis stabilized spacecraft in a 680 km polar orbit with an 8-day repeating ground track. The instruments are planned to provide high-resolution and high-accuracy global maps of <span class="hlt">soil</span> <span class="hlt">moisture</span> at 10 km resolution and freeze/thaw at 3 km resolution, every two to three days (see Table 1 for a list of science data products). The mission is adopting a number of approaches to identify and mitigate potential terrestrial radio frequency interference (RFI). These approaches are being incorporated into the radiometer and radar flight hardware and</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013JHyd..498...89K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013JHyd..498...89K"><span>Patterns and scaling properties of surface <span class="hlt">soil</span> <span class="hlt">moisture</span> in an agricultural landscape: An ecohydrological modeling study</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Korres, W.; Reichenau, T. G.; Schneider, K.</p> <p>2013-08-01</p> <p><span class="hlt">Soil</span> <span class="hlt">moisture</span> is a key variable in hydrology, meteorology and agriculture. <span class="hlt">Soil</span> <span class="hlt">moisture</span>, and surface <span class="hlt">soil</span> <span class="hlt">moisture</span> in particular, is highly variable in space and time. Its spatial and temporal patterns in agricultural landscapes are <span class="hlt">affected</span> by multiple natural (precipitation, <span class="hlt">soil</span>, topography, etc.) and agro-economic (<span class="hlt">soil</span> management, fertilization, etc.) factors, making it difficult to identify unequivocal cause and effect relationships between <span class="hlt">soil</span> <span class="hlt">moisture</span> and its driving variables. The goal of this study is to characterize and analyze the spatial and temporal patterns of surface <span class="hlt">soil</span> <span class="hlt">moisture</span> (top 20 cm) in an intensively used agricultural landscape (1100 km2 northern part of the Rur catchment, Western Germany) and to determine the dominant factors and underlying processes controlling these patterns. A second goal is to analyze the scaling behavior of surface <span class="hlt">soil</span> <span class="hlt">moisture</span> patterns in order to investigate how spatial scale <span class="hlt">affects</span> spatial patterns. To achieve these goals, a dynamically coupled, process-based and spatially distributed ecohydrological model was used to analyze the key processes as well as their interactions and feedbacks. The model was validated for two growing seasons for the three main crops in the investigation area: Winter wheat, sugar beet, and maize. This yielded RMSE values for surface <span class="hlt">soil</span> <span class="hlt">moisture</span> between 1.8 and 7.8 vol.% and average RMSE values for all three crops of 0.27 kg m-2 for total aboveground biomass and 0.93 for green LAI. Large deviations of measured and modeled <span class="hlt">soil</span> <span class="hlt">moisture</span> can be explained by a change of the infiltration properties towards the end of the growing season, especially in maize fields. The validated model was used to generate daily surface <span class="hlt">soil</span> <span class="hlt">moisture</span> maps, serving as a basis for an autocorrelation analysis of spatial patterns and scale. Outside of the growing season, surface <span class="hlt">soil</span> <span class="hlt">moisture</span> patterns at all spatial scales depend mainly upon <span class="hlt">soil</span> properties. Within the main growing season, larger scale</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1816968T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1816968T"><span><span class="hlt">Soil</span> <span class="hlt">moisture</span> sensitivity of autotrophic and heterotrophic forest floor respiration in boreal xeric pine and mesic spruce forests</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ťupek, Boris; Launiainen, Samuli; Peltoniemi, Mikko; Heikkinen, Jukka; Lehtonen, Aleksi</p> <p>2016-04-01</p> <p>Litter decomposition rates of the most process based <span class="hlt">soil</span> carbon models <span class="hlt">affected</span> by environmental conditions are linked with <span class="hlt">soil</span> heterotrophic CO2 emissions and serve for estimating <span class="hlt">soil</span> carbon sequestration; thus due to the mass balance equation the variation in measured litter inputs and measured heterotrophic <span class="hlt">soil</span> CO2 effluxes should indicate <span class="hlt">soil</span> carbon stock changes, needed by <span class="hlt">soil</span> carbon management for mitigation of anthropogenic CO2 emissions, if sensitivity functions of the applied model suit to the environmental conditions e.g. <span class="hlt">soil</span> temperature and <span class="hlt">moisture</span>. We evaluated the response forms of autotrophic and heterotrophic forest floor respiration to <span class="hlt">soil</span> temperature and <span class="hlt">moisture</span> in four boreal forest sites of the International Cooperative Programme on Assessment and Monitoring of Air Pollution Effects on Forests (ICP Forests) by a <span class="hlt">soil</span> trenching experiment during year 2015 in southern Finland. As expected both autotrophic and heterotrophic forest floor respiration components were primarily controlled by <span class="hlt">soil</span> temperature and exponential regression models generally explained more than 90% of the variance. <span class="hlt">Soil</span> <span class="hlt">moisture</span> regression models on average explained less than 10% of the variance and the response forms varied between Gaussian for the autotrophic forest floor respiration component and linear for the heterotrophic forest floor respiration component. Although the percentage of explained variance of <span class="hlt">soil</span> heterotrophic respiration by the <span class="hlt">soil</span> <span class="hlt">moisture</span> was small, the observed reduction of CO2 emissions with higher <span class="hlt">moisture</span> levels suggested that <span class="hlt">soil</span> <span class="hlt">moisture</span> response of <span class="hlt">soil</span> carbon models not accounting for the reduction due to excessive <span class="hlt">moisture</span> should be re-evaluated in order to estimate right levels of <span class="hlt">soil</span> carbon stock changes. Our further study will include evaluation of process based <span class="hlt">soil</span> carbon models by the annual heterotrophic respiration and <span class="hlt">soil</span> carbon stocks.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.H52E..04M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.H52E..04M"><span>ESA's <span class="hlt">Soil</span> <span class="hlt">Moisture</span> dnd Ocean Salinity Mission - Contributing to Water Resource Management</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mecklenburg, S.; Kerr, Y. H.</p> <p>2015-12-01</p> <p>The <span class="hlt">Soil</span> <span class="hlt">Moisture</span> and Ocean Salinity (SMOS) mission, launched in November 2009, is the European Space Agency's (ESA) second Earth Explorer Opportunity mission. The scientific objectives of the SMOS mission directly respond to the need for global observations of <span class="hlt">soil</span> <span class="hlt">moisture</span> and ocean salinity, two key variables used in predictive hydrological, oceanographic and atmospheric models. SMOS observations also provide information on the characterisation of ice and snow covered surfaces and the sea ice effect on ocean-atmosphere heat fluxes and dynamics, which <span class="hlt">affects</span> large-scale processes of the Earth's climate system. The focus of this paper will be on SMOS's contribution to support water resource management: SMOS surface <span class="hlt">soil</span> <span class="hlt">moisture</span> provides the input to derive root-zone <span class="hlt">soil</span> <span class="hlt">moisture</span>, which in turn provides the input for the drought index, an important monitoring prediction tool for plant available water. In addition to surface <span class="hlt">soil</span> <span class="hlt">moisture</span>, SMOS also provides observations on vegetation optical depth. Both parameters aid agricultural applications such as crop growth, yield forecasting and drought monitoring, and provide input for carbon and land surface modelling. SMOS data products are used in data assimilation and forecasting systems. Over land, assimilating SMOS derived information has shown to have a positive impact on applications such as NWP, stream flow forecasting and the analysis of net ecosystem exchange. Over ocean, both sea surface salinity and severe wind speed have the potential to increase the predictive skill on the seasonal and short- to medium-range forecast range. Operational users in particular in Numerical Weather Prediction and operational hydrology have put forward a requirement for <span class="hlt">soil</span> <span class="hlt">moisture</span> data to be available in near-real time (NRT). This has been addressed by developing a fast retrieval for a NRT level 2 <span class="hlt">soil</span> <span class="hlt">moisture</span> product based on Neural Networks, which will be available by autumn 2015. This paper will focus on presenting the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20170001399','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20170001399"><span>Correlation Between <span class="hlt">Soil</span> <span class="hlt">Moisture</span> and Dust Emissions: An Investigation for Global Climate Modeling</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Fredrickson, Carley; Tan, Qian</p> <p>2017-01-01</p> <p>This work is using the newly available NASA SMAP <span class="hlt">soil</span> <span class="hlt">moisture</span> measurement data to evaluate its impact on the atmospheric dust emissions. Dust is an important component of atmospheric aerosols, which <span class="hlt">affects</span> both climate and air quality. In this work, we focused on semi-desert regions, where dust emissions show seasonal variations due to <span class="hlt">soil</span> <span class="hlt">moisture</span> changes, i.e. in Sahel of Africa. We first identified three Aerosol Robotic Network (AERONET) sites in the Sahel (IER_Cinzana, Banizoumbou, and Zinder_Airport). We then utilized measurements of aerosol optical depth (AOD), fine mode fraction, size distribution, and single-scattering albedo and its wave-length dependence to select dust plumes from the available measurements We matched the latitude and longitude of the AERONET station to the corresponding SMAP data cell in the years 2015 and 2016, and calculated their correlation coefficient. Additionally, we looked at the correlation coefficient with a three-day and a five-day shift to check the impact of <span class="hlt">soil</span> <span class="hlt">moisture</span> on dust plumes with some time delay. Due to the arid nature of Banizoumbou and Zinder_Airport, no correlation was found to exist between local <span class="hlt">soil</span> <span class="hlt">moisture</span> and dust aerosol load. While IER_Cinzana had <span class="hlt">soil</span> <span class="hlt">moisture</span> levels above the satellite threshold of 0.02cm3/cm3, R-value approaching zero indicated no presence of a correlation. On the other hand, Ilorin demonstrated a significant negative correlation between aerosol optical depth and <span class="hlt">soil</span> <span class="hlt">moisture</span>. When isolating the analysis to Ilorin's dry season, a negative correlation of -0.593 was the largest dust-isolated R-value recorded, suggesting that <span class="hlt">soil</span> <span class="hlt">moisture</span> is driven the dust emission in this semi-desert region during transitional season.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H21I1587H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H21I1587H"><span>Surface <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Memory Estimated from Models and SMAP Observations</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>He, Q.; Mccoll, K. A.; Li, C.; Lu, H.; Akbar, R.; Pan, M.; Entekhabi, D.</p> <p>2017-12-01</p> <p><span class="hlt">Soil</span> <span class="hlt">moisture</span> memory(SMM), which is loosely defined as the time taken by <span class="hlt">soil</span> to forget an anomaly, has been proved to be important in land-atmosphere interaction. There are many metrics to calculate the SMM timescale, for example, the timescale based on the time-series autocorrelation, the timescale ignoring the <span class="hlt">soil</span> <span class="hlt">moisture</span> time series and the timescale which only considers <span class="hlt">soil</span> <span class="hlt">moisture</span> increment. Recently, a new timescale based on `Water Cycle Fraction' (Kaighin et al., 2017), in which the impact of precipitation on <span class="hlt">soil</span> <span class="hlt">moisture</span> memory is considered, has been put up but not been fully evaluated in global. In this study, we compared the surface SMM derived from SMAP observations with that from land surface model simulations (i.e., the SMAP Nature Run (NR) provided by the Goddard Earth Observing System, version 5) (Rolf et al., 2014). Three timescale metrics were used to quantify the surface SMM as: T0 based on the <span class="hlt">soil</span> <span class="hlt">moisture</span> time series autocorrelation, deT0 based on the detrending <span class="hlt">soil</span> <span class="hlt">moisture</span> time series autocorrelation, and tHalf based on the Water Cycle Fraction. The comparisons indicate that: (1) there are big gaps between the T0 derived from SMAP and that from NR (2) the gaps get small for deT0 case, in which the seasonality of surface <span class="hlt">soil</span> <span class="hlt">moisture</span> was removed with a moving average filter; (3) the tHalf estimated from SMAP is much closer to that from NR. The results demonstrate that surface SMM can vary dramatically among different metrics, while the memory derived from land surface model differs from the one from SMAP observation. tHalf, with considering the impact of precipitation, may be a good choice to quantify surface SMM and have high potential in studies related to land atmosphere interactions. References McColl. K.A., S.H. Alemohammad, R. Akbar, A.G. Konings, S. Yueh, D. Entekhabi. The Global Distribution and Dynamics of Surface <span class="hlt">Soil</span> <span class="hlt">Moisture</span>, Nature Geoscience, 2017 Reichle. R., L. Qing, D.L. Gabrielle, A. Joe. The "SMAP_Nature_v03" Data</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/46775','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/46775"><span>Sensitivity of <span class="hlt">soil</span> respiration to variability in <span class="hlt">soil</span> <span class="hlt">moisture</span> and temperature in a humid tropical forest</span></a></p> <p><a target="_blank" href="http://www.fs.usda.gov/treesearch/">Treesearch</a></p> <p>Tana Wood; M. Detto; W.L. Silver</p> <p>2013-01-01</p> <p>Precipitation and temperature are important drivers of <span class="hlt">soil</span> respiration. The role of <span class="hlt">moisture</span> and temperature are generally explored at seasonal or inter-annual timescales; however, significant variability also occurs on hourly to daily time-scales. We used small (1.54 m2), throughfall exclusion shelters to evaluate the role <span class="hlt">soil</span> <span class="hlt">moisture</span> and temperature as temporal...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017GeoRL..4411860L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017GeoRL..4411860L"><span>Irrigation Signals Detected From SMAP <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Retrievals</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lawston, Patricia M.; Santanello, Joseph A.; Kumar, Sujay V.</p> <p>2017-12-01</p> <p>Irrigation can influence weather and climate, but the magnitude, timing, and spatial extent of irrigation are poorly represented in models, as are the resulting impacts of irrigation on the coupled land-atmosphere system. One way to improve irrigation representation in models is to assimilate <span class="hlt">soil</span> <span class="hlt">moisture</span> observations that reflect an irrigation signal to improve model states. Satellite remote sensing is a promising avenue for obtaining these needed observations on a routine basis, but to date, irrigation detection in passive microwave satellites has proven difficult. In this study, results show that the new enhanced <span class="hlt">soil</span> <span class="hlt">moisture</span> product from the <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Active Passive satellite is able to capture irrigation signals over three semiarid regions in the western United States. This marks an advancement in Earth-observing satellite skill and the ability to monitor human impacts on the water cycle.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19760017595','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19760017595"><span>Results of <span class="hlt">soil</span> <span class="hlt">moisture</span> flights during April 1974</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Schmugge, T. J.; Blanchard, B. J.; Burke, W. J.; Paris, J. F.; Swang, J. R.</p> <p>1976-01-01</p> <p>The results presented here are derived from measurements made during the April 5 and 6, 1974 flights of the NASA P-3A aircraft over the Phoenix, Arizona agricultural test site. The purpose of the mission was to study the use of microwave techniques for the remote sensing of <span class="hlt">soil</span> <span class="hlt">moisture</span>. These results include infrared (10-to 12 micrometers) 2.8-cm and 21-cm brightness temperatures for approximately 90 bare fields. These brightness temperatures are compared with surface measurements of the <span class="hlt">soil</span> <span class="hlt">moisture</span> made at the time of the overflights. These data indicate that the combination of the sum and difference of the vertically and the horizontally polarized brightness temperatures yield information on both the <span class="hlt">soil</span> <span class="hlt">moisture</span> and surface roughness conditions.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20000116624','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20000116624"><span>BOREAS HYD-6 Ground Gravimetric <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Data</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Carroll, Thomas; Knapp, David E. (Editor); Hall, Forrest G. (Editor); Peck, Eugene L.; Smith, David E. (Technical Monitor)</p> <p>2000-01-01</p> <p>The Boreal Ecosystem-Atmosphere Study (BOREAS) Hydrology (HYD)-6 team collected several data sets related to the <span class="hlt">moisture</span> content of <span class="hlt">soil</span> and overlying humus layers. This data set contains percent <span class="hlt">soil</span> <span class="hlt">moisture</span> ground measurements. These data were collected on the ground along the various flight lines flown in the Southern Study Area (SSA) and Northern Study Area (NSA) during 1994 by the gamma ray instrument. The data are available in tabular ASCII files. The HYD-06 ground gravimetric <span class="hlt">soil</span> <span class="hlt">moisture</span> data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.H33K1729L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.H33K1729L"><span>Impact of Tropical Cyclones on <span class="hlt">Soil</span> <span class="hlt">Moisture</span> over East Asia</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Liess, S.</p> <p>2016-12-01</p> <p>A simulation of a series of three strong typhoons (Frankie, Gloria, and Herb) during the 1996 typhoon season shows that the Weather Research and Forecasting (WRF) model is representing the general characteristics of each typhoon, including sharp right turns by Gloria and Herb over the Philippine Sea. These sharp right turns can be attributed to tropical easterly waves and they are responsible for landfall over Taiwan, instead of following the general direction toward the Philippines. A second simulation where the typhoon signal is removed before landfall over East Asia shows that both rainfall and <span class="hlt">soil</span> <span class="hlt">moisture</span> is increased by up to 30% in coastal regions after landfall, mostly to the north of the landfall region. However, despite the noisier signal in rainfall, significant increases in <span class="hlt">soil</span> <span class="hlt">moisture</span> related to the paths of the simulated typhoons occur as far west as western China and Myanmar. Strong winds associated with the typhoons can also increase local evaporation and thus locally reduce <span class="hlt">soil</span> <span class="hlt">moisture</span>, especially south of the landfall region. Detailed observations of hydrologic variables such as <span class="hlt">soil</span> <span class="hlt">moisture</span> are needed to evaluate these model studies not only over coastal regions but also further inland where typhoon signals are weaker but local <span class="hlt">moisture</span> availability is still influenced by increased rainfall and stronger winds.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..1711428H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..1711428H"><span>Assessing seasonal backscatter variations with respect to uncertainties in <span class="hlt">soil</span> <span class="hlt">moisture</span> retrieval in Siberian tundra regions</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Högström, Elin; Trofaier, Anna Maria; Gouttevin, Isabella; Bartsch, Annett</p> <p>2015-04-01</p> <p>Data from the Advanced Scatterometer (ASCAT) instrument provide the basis of a near real-time, coarse scale, global <span class="hlt">soil</span> <span class="hlt">moisture</span> product. Numerous studies have shown the applicability of this product, including recent operational use for numerical weather forecasts. <span class="hlt">Soil</span> <span class="hlt">moisture</span> is a key element in the global cycles of water, energy and carbon. Among many application areas, it is essential for the understanding of permafrost development in a future climate change scenario. Dramatic climate changes are expected in the Arctic, where ca 25% of the land is underlain by permafrost, and it is to a large extent remote and inaccessible. The availability and applicability of satellite derived land-surface data relevant for permafrost studies, such as surface <span class="hlt">soil</span> <span class="hlt">moisture</span>, is thus crucial to landscape-scale analyses of climate-induced change. However, there are challenges in the <span class="hlt">soil</span> <span class="hlt">moisture</span> retrieval that are specific to the Arctic. This study investigates backscatter variability unrelated to <span class="hlt">soil</span> <span class="hlt">moisture</span> variations in order to understand the possible impact on the <span class="hlt">soil</span> <span class="hlt">moisture</span> retrieval. The focus is on tundra lakes, which are a common feature in the Arctic and are expected to <span class="hlt">affect</span> the retrieval. ENVISAT Advanced Synthetic Aperture Radar (ASAR) Wide Swath (120 m) data are used to resolve lakes and later understand and quantify their impacts on Metop ASCAT (25 km) <span class="hlt">soil</span> <span class="hlt">moisture</span> retrieval during the snow free period. Sites of interest are chosen according to high or low agreement between output from the land surface model ORCHIDEE and ASCAT derived SSM. The results show that in most cases low model agreement is related to high water fraction. The water fraction correlates with backscatter deviations (relative to a smooth water surface reference image) within the ASCAT footprint areas (R = 0.91-0.97). Backscatter deviations of up to 5 dB can occur in areas with less than 50% water fraction and an assumed <span class="hlt">soil</span> <span class="hlt">moisture</span> related range (sensitivity) of 7 dB in the ASCAT</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20170010214','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20170010214"><span>Version 3 of the SMAP Level 4 <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Product</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Reichle, Rolf; Liu, Qing; Ardizzone, Joe; Crow, Wade; De Lannoy, Gabrielle; Kolassa, Jana; Kimball, John; Koster, Randy</p> <p>2017-01-01</p> <p>The NASA <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Active Passive (SMAP) Level 4 <span class="hlt">Soil</span> <span class="hlt">Moisture</span> (L4_SM) product provides 3-hourly, 9-km resolution, global estimates of surface (0-5 cm) and root zone (0-100 cm) <span class="hlt">soil</span> <span class="hlt">moisture</span> as well as related land surface states and fluxes from 31 March 2015 to present with a latency of 2.5 days. The ensemble-based L4_SM algorithm is a variant of the Goddard Earth Observing System version 5 (GEOS-5) land data assimilation system and ingests SMAP L-band (1.4 GHz) Level 1 brightness temperature observations into the Catchment land surface model. The <span class="hlt">soil</span> <span class="hlt">moisture</span> analysis is non-local (spatially distributed), performs downscaling from the 36-km resolution of the observations to that of the model, and respects the relative uncertainties of the modeled and observed brightness temperatures. Prior to assimilation, a climatological rescaling is applied to the assimilated brightness temperatures using a 6 year record of SMOS observations. A new feature in Version 3 of the L4_SM data product is the use of 2 years of SMAP observations for rescaling where SMOS observations are not available because of radio frequency interference, which expands the impact of SMAP observations on the L4_SM estimates into large regions of northern Africa and Asia. This presentation investigates the performance and data assimilation diagnostics of the Version 3 L4_SM data product. The L4_SM <span class="hlt">soil</span> <span class="hlt">moisture</span> estimates meet the 0.04 m3m3 (unbiased) RMSE requirement. We further demonstrate that there is little bias in the <span class="hlt">soil</span> <span class="hlt">moisture</span> analysis. Finally, we illustrate where the assimilation system overestimates or underestimates the actual errors in the system.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25085217','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25085217"><span><span class="hlt">Soil</span> <span class="hlt">moisture</span>--a regulator of arbuscular mycorrhizal fungal community assembly and symbiotic phosphorus uptake.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Deepika, Sharma; Kothamasi, David</p> <p>2015-01-01</p> <p>Multiple species of arbuscular mycorrhizal fungi (AMF) can colonize roots of an individual plant species but factors which determine the selection of a particular AMF species in a plant root are largely unknown. The present work analysed the effects of drought, flooding and optimal <span class="hlt">soil</span> <span class="hlt">moisture</span> (15-20 %) on AMF community composition and structure in Sorghum vulgare roots, using PCR-RFLP. Rhizophagus irregularis (isolate BEG 21), and rhizosphere <span class="hlt">soil</span> (mixed inoculum) of Heteropogon contortus, a perennial C4 grass, collected from the semi-arid Delhi ridge, were used as AMF inocula. <span class="hlt">Soil</span> <span class="hlt">moisture</span> functioned as an abiotic filter and <span class="hlt">affected</span> AMF community assembly inside plant roots by regulating AMF colonization and phylotype diversity. Roots of plants in flooded <span class="hlt">soils</span> had lowest AMF diversity whilst root AMF diversity was highest under the <span class="hlt">soil</span> <span class="hlt">moisture</span> regime of 15-20 %. Although plant biomass was not <span class="hlt">affected</span>, root P uptake was significantly influenced by <span class="hlt">soil</span> <span class="hlt">moisture</span>. Plants colonized with R. irregularis or mixed AMF inoculum showed higher root P uptake than non-mycorrhizal plants in drought and control treatments. No differences in root P levels were found in the flooded treatment between plants colonized with R. irregularis and non-mycorrhizal plants, whilst under the same treatment, root P uptake was lower in plants colonized with mixed AMF inoculum than in non-mycorrhizal plants.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.6315G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.6315G"><span>Crop yield monitoring in the Sahel using root zone <span class="hlt">soil</span> <span class="hlt">moisture</span> anomalies derived from SMOS <span class="hlt">soil</span> <span class="hlt">moisture</span> data assimilation</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Gibon, François; Pellarin, Thierry; Alhassane, Agali; Traoré, Seydou; Baron, Christian</p> <p>2017-04-01</p> <p>West Africa is greatly vulnerable, especially in terms of food sustainability. Mainly based on rainfed agriculture, the high variability of the rainy season strongly impacts the crop production driven by the <span class="hlt">soil</span> water availability in the <span class="hlt">soil</span>. To monitor this water availability, classical methods are based on daily precipitation measurements. However, the raingauge network suffers from the poor network density in Africa (1/10000km2). Alternatively, real-time satellite-derived precipitations can be used, but they are known to suffer from large uncertainties which produce significant error on crop yield estimations. The present study proposes to use root <span class="hlt">soil</span> <span class="hlt">moisture</span> rather than precipitation to evaluate crop yield variations. First, a local analysis of the spatiotemporal impact of water deficit on millet crop production in Niger was done, from in-situ <span class="hlt">soil</span> <span class="hlt">moisture</span> measurements (AMMA-CATCH/OZCAR (French Critical Zone exploration network)) and in-situ millet yield survey. Crop yield measurements were obtained for 10 villages located in the Niamey region from 2005 to 2012. The mean production (over 8 years) is 690 kg/ha, and ranges from 381 to 872 kg/ha during this period. Various statistical relationships based on <span class="hlt">soil</span> <span class="hlt">moisture</span> estimates were tested, and the most promising one (R>0.9) linked the 30-cm <span class="hlt">soil</span> <span class="hlt">moisture</span> anomalies from mid-August to mid-September (grain filling period) to the crop yield anomalies. Based on this local study, it was proposed to derive regional statistical relationships using 30-cm <span class="hlt">soil</span> <span class="hlt">moisture</span> maps over West Africa. The selected approach was to use a simple hydrological model, the Antecedent Precipitation Index (API), forced by real-time satellite-based precipitation (CMORPH, PERSIANN, TRMM3B42). To reduce uncertainties related to the quality of real-time rainfall satellite products, SMOS <span class="hlt">soil</span> <span class="hlt">moisture</span> measurements were assimilated into the API model through a Particular Filter algorithm. Then, obtained <span class="hlt">soil</span> <span class="hlt">moisture</span> anomalies were</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ThApC.132....1L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ThApC.132....1L"><span>Evaluation of a simple, point-scale hydrologic model in simulating <span class="hlt">soil</span> <span class="hlt">moisture</span> using the Delaware environmental observing system</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Legates, David R.; Junghenn, Katherine T.</p> <p>2018-04-01</p> <p>Many local weather station networks that measure a number of meteorological variables (i.e. , mesonetworks) have recently been established, with <span class="hlt">soil</span> <span class="hlt">moisture</span> occasionally being part of the suite of measured variables. These mesonetworks provide data from which detailed estimates of various hydrological parameters, such as precipitation and reference evapotranspiration, can be made which, when coupled with simple surface characteristics available from <span class="hlt">soil</span> surveys, can be used to obtain estimates of <span class="hlt">soil</span> <span class="hlt">moisture</span>. The question is Can meteorological data be used with a simple hydrologic model to estimate accurately daily <span class="hlt">soil</span> <span class="hlt">moisture</span> at a mesonetwork site? Using a state-of-the-art mesonetwork that also includes <span class="hlt">soil</span> <span class="hlt">moisture</span> measurements across the US State of Delaware, the efficacy of a simple, modified Thornthwaite/Mather-based daily water balance model based on these mesonetwork observations to estimate site-specific <span class="hlt">soil</span> <span class="hlt">moisture</span> is determined. Results suggest that the model works reasonably well for most well-drained sites and provides good qualitative estimates of measured <span class="hlt">soil</span> <span class="hlt">moisture</span>, often near the accuracy of the <span class="hlt">soil</span> <span class="hlt">moisture</span> instrumentation. The model exhibits particular trouble in that it cannot properly simulate the slow drainage that occurs in poorly drained <span class="hlt">soils</span> after heavy rains and interception loss, resulting from grass not being short cropped as expected also adversely <span class="hlt">affects</span> the simulation. However, the model could be tuned to accommodate some non-standard siting characteristics.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23359920','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23359920"><span>[Relationships between <span class="hlt">soil</span> <span class="hlt">moisture</span> and needle-fall in Masson pine forests in acid rain region of Chongqing, Southwest China].</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Wang, Yi-Hao; Wang, Yan-Hui; Li, Zhen-Hua; Yu, Peng-Tao; Xiong, Wei; Hao, Jia; Duan, Jian</p> <p>2012-10-01</p> <p>From March 2009 to November 2011, an investigation was conducted on the spatiotemporal variation of <span class="hlt">soil</span> <span class="hlt">moisture</span> and its effects on the needle-fall in Masson pine (Pinus massoniana) forests in acid rain region of Chongqing, Southeast China, with the corresponding <span class="hlt">soil</span> <span class="hlt">moisture</span> thresholds determined. No matter the annual precipitation was abundant, normal or less than average, the seasonal variation of <span class="hlt">soil</span> <span class="hlt">moisture</span> in the forests could be obviously divided into four periods, i.e., sufficient (before May), descending (from June to July), drought (from August to September), and recovering (from October to November). With increasing <span class="hlt">soil</span> depth, the <span class="hlt">soil</span> <span class="hlt">moisture</span> content increased after an initial decrease, but the difference of the <span class="hlt">soil</span> <span class="hlt">moisture</span> content among different <span class="hlt">soil</span> layers decreased with decreasing annual precipitation. The amount of monthly needle-fall in the forests in growth season was significantly correlated with the water storage in root zone (0-60 cm <span class="hlt">soil</span> layer), especially in the main root zone (20-50 cm <span class="hlt">soil</span> layer). <span class="hlt">Soil</span> field capacity (or capillary porosity) and 82% of field capacity (or 80% of capillary porosity) were the main <span class="hlt">soil</span> <span class="hlt">moisture</span> thresholds <span class="hlt">affecting</span> the litter-fall. It was suggested that in acid rain region, Masson pine forest was easily to suffer from water deficit stress, especially in dry-summer period. The water deficit stress, together with already existed acid rain stress, would further threaten the health of the Masson forest.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70162540','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70162540"><span><span class="hlt">Soil</span> <span class="hlt">moisture</span> and biogeochemical factors influence the distribution of annual Bromus species</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Belnap, Jayne; Stark, John Thomas; Rau, Benjamin; Allen, Edith B.; Phillips, Sue</p> <p>2016-01-01</p> <p>Abiotic factors have a strong influence on where annual Bromus species are found. At the large regional scale, temperature and precipitation extremes determine the boundaries of Bromusoccurrence. At the more local scale, <span class="hlt">soil</span> characteristics and climate influence distribution, cover, and performance. In hot, dry, summer-rainfall-dominated deserts (Sonoran, Chihuahuan), little or noBromus is found, likely due to timing or amount of <span class="hlt">soil</span> <span class="hlt">moisture</span> relative to Bromus phenology. In hot, winter-rainfall-dominated deserts (parts of the Mojave Desert), Bromus rubens is widespread and correlated with high phosphorus availability. It also responds positively to additions of nitrogen alone or with phosphorus. On the Colorado Plateau, with higher <span class="hlt">soil</span> <span class="hlt">moisture</span> availability, factors limiting Bromus tectorum populations vary with life stage: phosphorus and water limit germination, potassium and the potassium/magnesium ratio <span class="hlt">affect</span> winter performance, and water and potassium/magnesium <span class="hlt">affect</span> spring performance. Controlling nutrients also change with elevation. In cooler deserts with winter precipitation (Great Basin, Columbia Plateau) and thus even greater <span class="hlt">soil</span> <span class="hlt">moisture</span> availability, B. tectorum populations are controlled by nitrogen, phosphorus, or potassium. Experimental nitrogen additions stimulate Bromus performance. The reason for different nutrients limiting in dissimilar climatic regions is not known, but it is likely that site conditions such as <span class="hlt">soil</span> texture (as it <span class="hlt">affects</span> water and nutrient availability), organic matter, and/or chemistry interact in a manner that regulates nutrient availability and limitations. Under future drier, hotter conditions,Bromus distribution is likely to change due to changes in the interaction between <span class="hlt">moisture</span> and nutrient availability.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li class="active"><span>16</span></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_16 --> <div id="page_17" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li class="active"><span>17</span></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="321"> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19850035350&hterms=watershed&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Dwatershed','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19850035350&hterms=watershed&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Dwatershed"><span>Implications of complete watershed <span class="hlt">soil</span> <span class="hlt">moisture</span> measurements to hydrologic modeling</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Engman, E. T.; Jackson, T. J.; Schmugge, T. J.</p> <p>1983-01-01</p> <p>A series of six microwave data collection flights for measuring <span class="hlt">soil</span> <span class="hlt">moisture</span> were made over a small 7.8 square kilometer watershed in southwestern Minnesota. These flights were made to provide 100 percent coverage of the basin at a 400 m resolution. In addition, three flight lines were flown at preselected areas to provide a sample of data at a higher resolution of 60 m. The low level flights provide considerably more information on <span class="hlt">soil</span> <span class="hlt">moisture</span> variability. The results are discussed in terms of reproducibility, spatial variability and temporal variability, and their implications for hydrologic modeling.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24889286','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24889286"><span>Short-term precipitation exclusion alters microbial responses to <span class="hlt">soil</span> <span class="hlt">moisture</span> in a wet tropical forest.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Waring, Bonnie G; Hawkes, Christine V</p> <p>2015-05-01</p> <p>Many wet tropical forests, which contain a quarter of global terrestrial biomass carbon stocks, will experience changes in precipitation regime over the next century. <span class="hlt">Soil</span> microbial responses to altered rainfall are likely to be an important feedback on ecosystem carbon cycling, but the ecological mechanisms underpinning these responses are poorly understood. We examined how reduced rainfall <span class="hlt">affected</span> <span class="hlt">soil</span> microbial abundance, activity, and community composition using a 6-month precipitation exclusion experiment at La Selva Biological Station, Costa Rica. Thereafter, we addressed the persistent effects of field <span class="hlt">moisture</span> treatments by exposing <span class="hlt">soils</span> to a controlled <span class="hlt">soil</span> <span class="hlt">moisture</span> gradient in the lab for 4 weeks. In the field, compositional and functional responses to reduced rainfall were dependent on initial conditions, consistent with a large degree of spatial heterogeneity in tropical forests. However, the precipitation manipulation significantly altered microbial functional responses to <span class="hlt">soil</span> <span class="hlt">moisture</span>. Communities with prior drought exposure exhibited higher respiration rates per unit microbial biomass under all conditions and respired significantly more CO2 than control <span class="hlt">soils</span> at low <span class="hlt">soil</span> <span class="hlt">moisture</span>. These functional patterns suggest that changes in microbial physiology may drive positive feedbacks to rising atmospheric CO2 concentrations if wet tropical forests experience longer or more intense dry seasons in the future.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AGUSM.H11C..02T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AGUSM.H11C..02T"><span>Assessment of Multi-frequency Electromagnetic Induction for Determining <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Patterns at the Hillslope Scale</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Tromp-van Meerveld, I.; McDonnell, J.</p> <p>2009-05-01</p> <p>We present an assessment of electromagnetic induction (EM) as a potential rapid and non-invasive method to map <span class="hlt">soil</span> <span class="hlt">moisture</span> patterns at the Panola (GA, USA) hillslope. We address the following questions regarding the applicability of EM measurements for hillslope hydrological investigations: (1) Can EM be used for <span class="hlt">soil</span> <span class="hlt">moisture</span> measurements in areas with shallow <span class="hlt">soils</span>?; (2) Can EM represent the temporal and spatial patterns of <span class="hlt">soil</span> <span class="hlt">moisture</span> throughout the year?; and (3) can multiple frequencies be used to extract additional information content from the EM approach and explain the depth profile of <span class="hlt">soil</span> <span class="hlt">moisture</span>? We found that the apparent conductivity measured with the multi-frequency GEM-300 was linearly related to <span class="hlt">soil</span> <span class="hlt">moisture</span> measured with an Aqua-pro capacitance sensor below a threshold conductivity and represented the temporal patterns in <span class="hlt">soil</span> <span class="hlt">moisture</span> well. During spring rainfall events that wetted only the surface <span class="hlt">soil</span> layers the apparent conductivity measurements explained the <span class="hlt">soil</span> <span class="hlt">moisture</span> dynamics at depth better than the surface <span class="hlt">soil</span> <span class="hlt">moisture</span> dynamics. All four EM frequencies (7290, 9090, 11250, and 14010 Hz) were highly correlated and linearly related to each other and could be used to predict <span class="hlt">soil</span> <span class="hlt">moisture</span>. This limited our ability to use the four different EM frequencies to obtain a <span class="hlt">soil</span> <span class="hlt">moisture</span> profile with depth. The apparent conductivity patterns represented the observed spatial <span class="hlt">soil</span> <span class="hlt">moisture</span> patterns well when the individually fitted relationships between measured <span class="hlt">soil</span> <span class="hlt">moisture</span> and apparent conductivity were used for each measurement point. However, when the same (master) relationship was used for all measurement locations, the <span class="hlt">soil</span> <span class="hlt">moisture</span> patterns were smoothed and did not resemble the observed <span class="hlt">soil</span> <span class="hlt">moisture</span> patterns very well. In addition, the range in calculated <span class="hlt">soil</span> <span class="hlt">moisture</span> values was reduced compared to observed <span class="hlt">soil</span> <span class="hlt">moisture</span>. Part of the smoothing was likely due to the much larger measurement area of the GEM-300 compared to the Aqua</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1332724','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1332724"><span><span class="hlt">Soil</span> Temperature and <span class="hlt">Moisture</span> Profile (STAMP) System Handbook</span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Cook, David R.</p> <p></p> <p>The <span class="hlt">soil</span> temperature and <span class="hlt">moisture</span> profile system (STAMP) provides vertical profiles of <span class="hlt">soil</span> temperature, <span class="hlt">soil</span> water content (<span class="hlt">soil</span>-type specific and loam type), plant water availability, <span class="hlt">soil</span> conductivity, and real dielectric permittivity as a function of depth below the ground surface at half-hourly intervals, and precipitation at one-minute intervals. The profiles are measured directly by in situ probes at all extended facilities of the SGP climate research site. The profiles are derived from measurements of <span class="hlt">soil</span> energy conductivity. Atmospheric scientists use the data in climate models to determine boundary conditions and to estimate the surface energy flux. The data are alsomore » useful to hydrologists, <span class="hlt">soil</span> scientists, and agricultural scientists for determining the state of the <span class="hlt">soil</span>. The STAMP system replaced the SWATS system in early 2016.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19990116494&hterms=atmosphere+wind+profile&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Datmosphere%2Bwind%2Bprofile','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19990116494&hterms=atmosphere+wind+profile&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Datmosphere%2Bwind%2Bprofile"><span>The Influence of <span class="hlt">Soil</span> <span class="hlt">Moisture</span> and Wind on Rainfall Distribution and Intensity in Florida</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Baker, R. David; Lynn, Barry H.; Boone, Aaron; Tao, Wei-Kuo</p> <p>1998-01-01</p> <p>Land surface processes play a key role in water and energy budgets of the hydrological cycle. For example, the distribution of <span class="hlt">soil</span> <span class="hlt">moisture</span> will <span class="hlt">affect</span> sensible and latent heat fluxes, which in turn may dramatically influence the location and intensity of precipitation. However, mean wind conditions also strongly influence the distribution of precipitation. The relative importance of <span class="hlt">soil</span> <span class="hlt">moisture</span> and wind on rainfall location and intensity remains uncertain. Here, we examine the influence of <span class="hlt">soil</span> <span class="hlt">moisture</span> distribution and wind distribution on precipitation in the Florida peninsula using the 3-D Goddard Cumulus Ensemble (GCE) cloud model Coupled with the Parameterization for Land-Atmosphere-Cloud Exchange (PLACE) land surface model. This study utilizes data collected on 27 July 1991 in central Florida during the Convection and Precipitation Electrification Experiment (CaPE). The idealized numerical experiments consider a block of land (the Florida peninsula) bordered on the east and on the west by ocean. The initial <span class="hlt">soil</span> <span class="hlt">moisture</span> distribution is derived from an offline PLACE simulation, and the initial environmental wind profile is determined from the CaPE sounding network. Using the factor separation technique, the precise contribution of <span class="hlt">soil</span> <span class="hlt">moisture</span> and wind to rainfall distribution and intensity is determined.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=347186','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=347186"><span>Hydrologic downscaling of <span class="hlt">soil</span> <span class="hlt">moisture</span> using global data without site-specific calibration</span></a></p> <p><a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>Numerous applications require fine-resolution (10-30 m) <span class="hlt">soil</span> <span class="hlt">moisture</span> patterns, but most satellite remote sensing and land-surface models provide coarse-resolution (9-60 km) <span class="hlt">soil</span> <span class="hlt">moisture</span> estimates. The Equilibrium <span class="hlt">Moisture</span> from Topography, Vegetation, and <span class="hlt">Soil</span> (EMT+VS) model downscales <span class="hlt">soil</span> moistu...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/19797','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/19797"><span>A comparison of <span class="hlt">soil-moisture</span> loss from forested and clearcut areas in West Virginia</span></a></p> <p><a target="_blank" href="http://www.fs.usda.gov/treesearch/">Treesearch</a></p> <p>Charles A. Troendle</p> <p>1970-01-01</p> <p><span class="hlt">Soil-moisture</span> losses from forested and clearcut areas were compared on the Fernow Experimental Forest. As expected, hardwood forest <span class="hlt">soils</span> lost most <span class="hlt">moisture</span> while revegetated clearcuttings, clearcuttings, and barren areas lost less, in that order. <span class="hlt">Soil-moisture</span> losses from forested <span class="hlt">soils</span> also correlated well with evapotranspiration and streamflow.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..1616875A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..1616875A"><span><span class="hlt">Soil</span> <span class="hlt">moisture</span> under contrasted atmospheric conditions in Eastern Spain</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Azorin-Molina, César; Cerdà, Artemi; Vicente-Serrano, Sergio M.</p> <p>2014-05-01</p> <p><span class="hlt">Soil</span> <span class="hlt">moisture</span> plays a key role on the recently abandoned agriculture land where determine the recovery and the erosion rates (Cerdà, 1995), on the <span class="hlt">soil</span> water repellency degree (Bodí et al., 2011) and on the hydrological cycle (Cerdà, 1999), the plant development (García Fayos et al., 2000) and the seasonality of the geomorphological processes (Cerdà, 2002). Moreover, <span class="hlt">Soil</span> <span class="hlt">moisture</span> is a key factor on the semiarid land (Ziadat and Taimeh, 2013), on the productivity of the land (Qadir et al., 2013) and <span class="hlt">soils</span> treated with amendments (Johnston et al., 2013) and on <span class="hlt">soil</span> reclamation on drained saline-sodic <span class="hlt">soils</span> (Ghafoor et al., 2012). In previous study (Azorin-Molina et al., 2013) we investigated the intraannual evolution of <span class="hlt">soil</span> <span class="hlt">moisture</span> in <span class="hlt">soils</span> under different land managements in the Valencia region, Eastern Spain, and concluded that <span class="hlt">soil</span> <span class="hlt">moisture</span> recharges are much controlled by few heavy precipitation events; 23 recharge episodes during 2012. Most of the <span class="hlt">soil</span> <span class="hlt">moisture</span> recharge events occurred during the autumn season under Back-Door cold front situations. Additionally, sea breeze front episodes brought isolated precipitation and <span class="hlt">moisture</span> to mountainous areas within summer (Azorin-Molina et al., 2009). We also evidenced that the intraanual evolution of <span class="hlt">soil</span> <span class="hlt">moisture</span> changes are positively and significatively correlated (at p<0.01) with the amount of measured precipitation. In this study we analyze the role of other crucial atmospheric parameters (i.e., temperature, relative humidity, global solar radiation, and wind speed and wind direction) in the intraanual evolution of <span class="hlt">soil</span> <span class="hlt">moisture</span>; focussing our analyses on the <span class="hlt">soil</span> <span class="hlt">moisture</span> discharge episodes. Here we present 1-year of <span class="hlt">soil</span> <span class="hlt">moisture</span> measurements at two experimental sites in the Valencia region, one representing rainfed orchard typical from the Mediterranean mountains (El Teularet-Sierra de Enguera), and a second site corresponding to an irrigated orange crop (Alcoleja). Key Words: <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Discharges</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=324790','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=324790"><span>Projected irrigation requirements for upland crops using <span class="hlt">soil</span> <span class="hlt">moisture</span> model under climate change in South Korea</span></a></p> <p><a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>An increase in abnormal climate change patterns and unsustainable irrigation in uplands cause drought and <span class="hlt">affect</span> agricultural water security, crop productivity, and price fluctuations. In this study, we developed a <span class="hlt">soil</span> <span class="hlt">moisture</span> model to project irrigation requirements (IR) for upland crops under cl...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016cosp...41E1188L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016cosp...41E1188L"><span><span class="hlt">Soil</span> <span class="hlt">Moisture</span> Remote Sensing with GNSS-R at the Valencia Anchor Station. The SOMOSTA (<span class="hlt">Soil</span> <span class="hlt">Moisture</span> Station) Experiment</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lopez-Baeza, Ernesto</p> <p>2016-07-01</p> <p>In this paper, the SOMOSTA (<span class="hlt">Soil</span> <span class="hlt">Moisture</span> Monitoring Station) experiment on <span class="hlt">soil</span> <span class="hlt">moisture</span> monitoring byGlobal Navigation Satellite System Reflected signals(GNSS-R) at the Valencia Anchor Station is introduced. L-band microwaves have very good advantages in <span class="hlt">soil</span> <span class="hlt">moisture</span> remote sensing, for being unaffected by clouds and the atmosphere, and for the ability to penetrate vegetation. During this experimental campaign, the ESA GNSS-R Oceanpal antenna was installed on the same tower as the ESA ELBARA-II passive microwave radiometer, both measuring instruments having similar field of view. This experiment is fruitfully framed within the ESA - China Programme of Collaboration on GNSS-R. The GNSS-R instrument has an up-looking antenna for receiving direct signals from satellites, and two down-looking antennas for receiving LHCP (left-hand circular polarisation) and RHCP (right-hand circular polarisation) reflected signals from the <span class="hlt">soil</span> surface. We could collect data from the three different antennas through the two channels of Oceanpal and, in addition, calibration could be performed to reduce the impact from the differing channels. Reflectivity was thus measured and <span class="hlt">soil</span> <span class="hlt">moisture</span> could be retrieved by the L- MEB (L-band Microwave Emission of the Biosphere) model considering the effect of vegetation optical thickness and <span class="hlt">soil</span> roughness. By contrasting GNSS-R and ELBARA-II radiometer data, a negative correlation existed between reflectivity measured by GNSS-R and brightness temperature measured by the radiometer. The two parameters represent reflection and absorption of the <span class="hlt">soil</span>. <span class="hlt">Soil</span> <span class="hlt">moisture</span> retrieved by both L-band remote sensing methods shows good agreement. In addition, correspondence with in-situ measurements and rainfall is also good.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.1134F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.1134F"><span>Effects of land preparation and artificial vegetation on <span class="hlt">soil</span> <span class="hlt">moisture</span> variation in a loess hilly catchment of China</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Feng, Tianjiao; Wei, Wei; Chen, Liding; Yu, Yang</p> <p>2017-04-01</p> <p>In the dryland regions, <span class="hlt">soil</span> <span class="hlt">moisture</span> is the main factor to determine vegetation growth and ecosystem restoration. Land preparation and vegetation restoration are the principal means for improving <span class="hlt">soil</span> water content(SWC). Thus, it is important to analyze the coupling role of these two means on <span class="hlt">soil</span> <span class="hlt">moisture</span>. In this study, <span class="hlt">soil</span> <span class="hlt">moisture</span> were monitored at a semi-arid loess hilly catchment of China, during the growing season of 2014 and 2015. Four different land preparation methods (level ditches, fish-scale pits, adverse grade tablelands and level benches)and vegetation types(Prunus armeniaca, Platycladus orientalis, Platycladus orientalis and Caragana microphylla) were included in the experimental design. Our results showed that: (1)<span class="hlt">Soil</span> <span class="hlt">moisture</span> content differed across land preparation types, which is higher for fish-scale pits and decreased in the order of level ditches and adverse grade tablelands.(2) Rainwater harvesting capacity of fish-scale pits is greater than adverse grade tablelands. However the water holding capacity is much higher at <span class="hlt">soils</span> prepared with the adverse grade tablelands method than the ones prepared by fish-scale pits methods. (3) When land preparation method is similar, vegetation play a key role in <span class="hlt">soil</span> <span class="hlt">moisture</span> variation. For example, the mean <span class="hlt">soil</span> <span class="hlt">moisture</span> under a Platycladus orientalis field is 26.72% higher than a Pinus tabulaeformis field, with the same land preparation methods. (4)<span class="hlt">Soil</span> <span class="hlt">moisture</span> in deeper <span class="hlt">soil</span> layers is more <span class="hlt">affected</span> by changes in the vegetation cover while <span class="hlt">soil</span> <span class="hlt">moisture</span> in the shallower layers is more <span class="hlt">affected</span> by the variation in the land preparation methods. Therefore, we suggest that vegetation types such as: Platycladus orientalisor as well as <span class="hlt">soil</span> preparation methods such as level ditch and fish-scale pit are the most appropriate vegetation cover and land preparation methods for landscape restoration in semi-arid loess hilly area. This conclusion was made based on the vegetation type and land preparation with the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://rosap.ntl.bts.gov/view/dot/20486','DOTNTL'); return false;" href="https://rosap.ntl.bts.gov/view/dot/20486"><span>Unsaturated <span class="hlt">soil</span> <span class="hlt">moisture</span> drying and wetting diffusion coefficient measurements in the laboratory.</span></a></p> <p><a target="_blank" href="http://ntlsearch.bts.gov/tris/index.do">DOT National Transportation Integrated Search</a></p> <p></p> <p>2009-09-01</p> <p>ABSTRACTTransient <span class="hlt">moisture</span> flow in an unsaturated <span class="hlt">soil</span> in response to suction changes is controlled by the unsaturated <span class="hlt">moisture</span> diffusion coefficient. The <span class="hlt">moisture</span> diffusion coefficient can be determined by measuring suction profiles over time. The l...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2002EGSGA..27.2574H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2002EGSGA..27.2574H"><span>Quantifying The Effects of Initial <span class="hlt">Soil</span> <span class="hlt">Moisture</span> On Seasonal Streamflow Forecasts In The Columbia River Basin</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hamlet, A. F.; Wood, A.; Lettenmaier, D. P.</p> <p></p> <p>The role of <span class="hlt">soil</span> <span class="hlt">moisture</span> storage in the hydrologic cycle is well understood at a funda- mental level. Antecedent conditions are known to have potentially significant effects on streamflow forecasts, especially for short (e.g., flood) lead times. For this reason, the U.S. Geological Survey defines its "water year" as extending from October through September, a time period selected because over most of the U.S., <span class="hlt">soil</span> <span class="hlt">moisture</span> is at a seasonal low at summer's end. The effects of carryover <span class="hlt">soil</span> <span class="hlt">moisture</span> storage in the Columbia River basin have usually been considered to be minimal when forecasts are made on a water year or seasonal basis. Our study demonstrates that the role of carry- over <span class="hlt">soil</span> <span class="hlt">moisture</span> storage can be important. Absent direct observations of ET and <span class="hlt">soil</span> <span class="hlt">moisture</span> that would permit a closing of the water balance from observations, we use a physically based hydrologic model to estimate the <span class="hlt">soil</span> <span class="hlt">moisture</span> state at the begin- ning of the forecast period (Oct 1). We then evaluate, in a self-consistent manner, the subsequent effects of interannual variations in fall <span class="hlt">soil</span> <span class="hlt">moisture</span> on streamflow during the subsequent spring and summer snowmelt season (April-September). We analyze the period from 1950-1999, and the subsequent effects to the seasonal water balance at The Dalles, OR for representative high, medium, and low water years. The effects of initial <span class="hlt">soil</span> state in fall are remarkably persistent, with significant effects occurring in the summer of the following water year. For a representative low flow year (1992), the simulated variability of the <span class="hlt">soil</span> <span class="hlt">moisture</span> state in September produces a range of summer streamflows (April-September mean) equivalent to about 16 percent of the mean summer flows for all initial <span class="hlt">soil</span> conditions, with analogous, but smaller, relative changes for medium and high flow years. Winter flows are also <span class="hlt">affected</span>, and the rel- ative intensity of effects in winter and summer is variable, an effect that is probably attributable to the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27337651','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27337651"><span><span class="hlt">Moisture</span> effect in prompt gamma measurements from <span class="hlt">soil</span> samples.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Naqvi, A A; Khiari, F Z; Liadi, F A; Khateeb-Ur-Rehman; Raashid, M A; Isab, A H</p> <p>2016-09-01</p> <p>The variation in intensity of 1.78MeV silicon, 6.13MeV oxygen, and 2.22MeV hydrogen prompt gamma rays from <span class="hlt">soil</span> samples due to the addition of 5.1, 7.4, 9.7, 11.9 and 14.0wt% water was studied for 14MeV incident neutron beams utilizing a LaBr3:Ce gamma ray detector. The intensities of 1.78MeV and 6.13MeV gamma rays from silicon and oxygen, respectively, decreased with increasing sample <span class="hlt">moisture</span>. The intensity of 2.22MeV hydrogen gamma rays increases with <span class="hlt">moisture</span>. The decrease in intensity of silicon and oxygen gamma rays with <span class="hlt">moisture</span> concentration indicates a loss of 14MeV neutron flux, while the increase in intensity of 2.22MeV gamma rays with <span class="hlt">moisture</span> indicates an increase in thermal neutron flux due to increasing concentration of <span class="hlt">moisture</span>. The experimental intensities of silicon, oxygen and hydrogen prompt gamma rays, measured as a function of <span class="hlt">moisture</span> concentration in the <span class="hlt">soil</span> samples, are in good agreement with the theoretical results obtained through Monte Carlo calculations. Copyright © 2016 Elsevier Ltd. All rights reserved.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..17..830S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..17..830S"><span>Assessment of <span class="hlt">soil</span> <span class="hlt">moisture</span> dynamics on an irrigated maize field using cosmic ray neutron sensing</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Scheiffele, Lena Maria; Baroni, Gabriele; Oswald, Sascha E.</p> <p>2015-04-01</p> <p>In recent years cosmic ray neutron sensing (CRS) developed as a valuable, indirect and non-invasive method to estimate <span class="hlt">soil</span> <span class="hlt">moisture</span> at a scale of tens of hectares, covering the gap between point scale measurements and large scale remote sensing techniques. The method is particularly promising in cropped and irrigated fields where invasive installation of belowground measurement devices could conflict with the agricultural management. However, CRS is <span class="hlt">affected</span> by all hydrogen pools in the measurement footprint and a fast growing biomass provides some challenges for the interpretation of the signal and application of the method for detecting <span class="hlt">soil</span> <span class="hlt">moisture</span>. For this aim, in this study a cosmic ray probe was installed on a field near Braunschweig (Germany) during one maize growing season (2014). The field was irrigated in stripes of 50 m width using sprinkler devices for a total of seven events. Three <span class="hlt">soil</span> sampling campaigns were conducted throughout the growing season to assess the effect of different hydrogen pools on calibration results. Additionally, leaf area index and biomass measurements were collected to provide the relative contribution of the biomass on the CRS signal. Calibration results obtained with the different <span class="hlt">soil</span> sampling campaigns showed some discrepancy well correlated with the biomass growth. However, after the calibration function was adjusted to account also for lattice water and <span class="hlt">soil</span> organic carbon, thus representing an equivalent water content of the <span class="hlt">soil</span>, the differences decreased. <span class="hlt">Soil</span> <span class="hlt">moisture</span> estimated with CRS responded well to precipitation and irrigation events, confirming also the effective footprint of the method (i.e., radius 300 m) and showing occurring water stress for the crop. Thus, the dynamics are in agreement with the <span class="hlt">soil</span> <span class="hlt">moisture</span> determined with point scale measurements but they are less <span class="hlt">affected</span> by the heterogeneous <span class="hlt">moisture</span> conditions within the field. For this reason, by applying a detailed calibration, CRS proves to be a</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20000038145&hterms=How+soil+form&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3DHow%2Bsoil%2Bform','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20000038145&hterms=How+soil+form&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3DHow%2Bsoil%2Bform"><span>Potential for Remotely Sensed <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Data in Hydrologic Modeling</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Engman, Edwin T.</p> <p>1997-01-01</p> <p>Many hydrologic processes display a unique signature that is detectable with microwave remote sensing. These signatures are in the form of the spatial and temporal distributions of surface <span class="hlt">soil</span> <span class="hlt">moisture</span> and portray the spatial heterogeneity of hydrologic processes and properties that one encounters in drainage basins. The hydrologic processes that may be detected include ground water recharge and discharge zones, storm runoff contributing areas, regions of potential and less than potential ET, and information about the hydrologic properties of <span class="hlt">soils</span> and heterogeneity of hydrologic parameters. Microwave remote sensing has the potential to detect these signatures within a basin in the form of volumetric <span class="hlt">soil</span> <span class="hlt">moisture</span> measurements in the top few cm. These signatures should provide information on how and where to apply <span class="hlt">soil</span> physical parameters in distributed and lumped parameter models and how to subdivide drainage basins into hydrologically similar sub-basins.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19830027190','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19830027190"><span>Advanced microwave <span class="hlt">soil</span> <span class="hlt">moisture</span> studies. [Big Sioux River Basin, Iowa</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Dalsted, K. J.; Harlan, J. C.</p> <p>1983-01-01</p> <p>Comparisons of low level L-band brightness temperature (TB) and thermal infrared (TIR) data as well as the following data sets: <span class="hlt">soil</span> map and land cover data; direct <span class="hlt">soil</span> <span class="hlt">moisture</span> measurement; and a computer generated contour map were statistically evaluated using regression analysis and linear discriminant analysis. Regression analysis of footprint data shows that statistical groupings of ground variables (<span class="hlt">soil</span> features and land cover) hold promise for qualitative assessment of <span class="hlt">soil</span> <span class="hlt">moisture</span> and for reducing variance within the sampling space. Dry conditions appear to be more conductive to producing meaningful statistics than wet conditions. Regression analysis using field averaged TB and TIR data did not approach the higher sq R values obtained using within-field variations. The linear discriminant analysis indicates some capacity to distinguish categories with the results being somewhat better on a field basis than a footprint basis.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28886067','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28886067"><span>A wireless <span class="hlt">soil</span> <span class="hlt">moisture</span> sensor powered by solar energy.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Jiang, Mingliang; Lv, Mouchao; Deng, Zhong; Zhai, Guoliang</p> <p>2017-01-01</p> <p>In a variety of agricultural activities, such as irrigation scheduling and nutrient management, <span class="hlt">soil</span> water content is regarded as an essential parameter. Either power supply or long-distance cable is hardly available within field scale. For the necessity of monitoring <span class="hlt">soil</span> water dynamics at field scale, this study presents a wireless <span class="hlt">soil</span> <span class="hlt">moisture</span> sensor based on the impedance transform of the frequency domain. The sensor system is powered by solar energy, and the data can be instantly transmitted by wireless communication. The sensor electrodes are embedded into the bottom of a supporting rod so that the sensor can measure <span class="hlt">soil</span> water contents at different depths. An optimal design with time executing sequence is considered to reduce the energy consumption. The experimental results showed that the sensor is a promising tool for monitoring <span class="hlt">moisture</span> in large-scale farmland using solar power and wireless communication.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015ESASP.729E..15J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015ESASP.729E..15J"><span>Estimation of <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Under Vegetation Cover at Multiple Frequencies</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Jadghuber, Thomas; Hajnsek, Irena; Weiß, Thomas; Papathanassiou, Konstantinos P.</p> <p>2015-04-01</p> <p><span class="hlt">Soil</span> <span class="hlt">moisture</span> under vegetation cover was estimated by a polarimetric, iterative, generalized, hybrid decomposition and inversion approach at multiple frequencies (X-, C- and L-band). Therefore the algorithm, originally designed for longer wavelength (L-band), was adapted to deal with the short wavelength scattering scenarios of X- and C-band. The Integral Equation Method (IEM) was incorporated together with a pedo-transfer function of Dobson et al. to account for the peculiarities of short wavelength scattering at X- and C-band. DLR's F-SAR system acquired fully polarimetric SAR data in X-, C- and L-band over the Wallerfing test site in Lower Bavaria, Germany in 2014. Simultaneously, <span class="hlt">soil</span> and vegetation measurements were conducted on different agricultural test fields. The results indicate a spatially continuous inversion of <span class="hlt">soil</span> <span class="hlt">moisture</span> in all three frequencies (inversion rates >92%), mainly due to the careful adaption of the vegetation volume removal including a physical constraining of the decomposition algorithm. However, for X- and C-band the inversion results reveal <span class="hlt">moisture</span> pattern inconsistencies and in some cases an incorrectly high inversion of <span class="hlt">soil</span> <span class="hlt">moisture</span> at X-band. The validation with in situ measurements states a stable performance of 2.1- 7.6vol.% at L-band for the entire growing period. At C- and X-band a reliable performance of 3.7-13.4vol.% in RMSE can only be achieved after distinct filtering (X- band) leading to a loss of almost 60% in spatial inversion rate. Hence, a robust inversion for <span class="hlt">soil</span> <span class="hlt">moisture</span> estimation under vegetation cover can only be conducted at L-band due to a constant availability of the <span class="hlt">soil</span> signal in contrast to higher frequencies (X- and C-band).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29076022','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29076022"><span>The impact of cerium oxide nanoparticles on the physiology of soybean (Glycine max (L.) Merr.) under different <span class="hlt">soil</span> <span class="hlt">moisture</span> conditions.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Cao, Zhiming; Rossi, Lorenzo; Stowers, Cheyenne; Zhang, Weilan; Lombardini, Leonardo; Ma, Xingmao</p> <p>2018-01-01</p> <p>The ongoing global climate change raises concerns over the decreasing <span class="hlt">moisture</span> content in agricultural <span class="hlt">soils</span>. Our research investigated the physiological impact of two types of cerium oxide nanoparticles (CeO 2 NPs) on soybean at different <span class="hlt">moisture</span> content levels. One CeO 2 NP was positively charged on the surface and the other negatively charged due to the polyvinylpyrrolidone (PVP) coating. The results suggest that the effect of CeO 2 NPs on plant photosynthesis and water use efficiency (WUE) was dependent upon the <span class="hlt">soil</span> <span class="hlt">moisture</span> content. Both types of CeO 2 NPs exhibited consistently positive impacts on plant photosynthesis at the <span class="hlt">moisture</span> content above 70% of field capacity (θ fc ). Similar positive impact of CeO 2 NPs was not observed at 55% θ fc , suggesting that the physiological impact of CeO 2 NPs was dependent upon the <span class="hlt">soil</span> <span class="hlt">moisture</span> content. The results also revealed that V Cmax (maximum carboxylation rate) was <span class="hlt">affected</span> by CeO 2 NPs, indicating that CeO 2 NPs <span class="hlt">affected</span> the Rubisco activity which governs carbon assimilation in photosynthesis. In conclusion, CeO 2 NPs demonstrated significant impacts on the photosynthesis and WUE of soybeans and such impacts were <span class="hlt">affected</span> by the <span class="hlt">soil</span> <span class="hlt">moisture</span> content. Graphical abstract <span class="hlt">Soil</span> <span class="hlt">moisture</span> content <span class="hlt">affects</span> plant cerium oxide nanoparticle interactions.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li class="active"><span>17</span></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_17 --> <div id="page_18" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li class="active"><span>18</span></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="341"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2007JGRD..112.3102D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2007JGRD..112.3102D"><span>Initializing numerical weather prediction models with satellite-derived surface <span class="hlt">soil</span> <span class="hlt">moisture</span>: Data assimilation experiments with ECMWF's Integrated Forecast System and the TMI <span class="hlt">soil</span> <span class="hlt">moisture</span> data set</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Drusch, M.</p> <p>2007-02-01</p> <p>Satellite-derived surface <span class="hlt">soil</span> <span class="hlt">moisture</span> data sets are readily available and have been used successfully in hydrological applications. In many operational numerical weather prediction systems the initial <span class="hlt">soil</span> <span class="hlt">moisture</span> conditions are analyzed from the modeled background and 2 m temperature and relative humidity. This approach has proven its efficiency to improve surface latent and sensible heat fluxes and consequently the forecast on large geographical domains. However, since <span class="hlt">soil</span> <span class="hlt">moisture</span> is not always related to screen level variables, model errors and uncertainties in the forcing data can accumulate in root zone <span class="hlt">soil</span> <span class="hlt">moisture</span>. Remotely sensed surface <span class="hlt">soil</span> <span class="hlt">moisture</span> is directly linked to the model's uppermost <span class="hlt">soil</span> layer and therefore is a stronger constraint for the <span class="hlt">soil</span> <span class="hlt">moisture</span> analysis. For this study, three data assimilation experiments with the Integrated Forecast System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF) have been performed for the 2-month period of June and July 2002: a control run based on the operational <span class="hlt">soil</span> <span class="hlt">moisture</span> analysis, an open loop run with freely evolving <span class="hlt">soil</span> <span class="hlt">moisture</span>, and an experimental run incorporating TMI (TRMM Microwave Imager) derived <span class="hlt">soil</span> <span class="hlt">moisture</span> over the southern United States. In this experimental run the satellite-derived <span class="hlt">soil</span> <span class="hlt">moisture</span> product is introduced through a nudging scheme using 6-hourly increments. Apart from the <span class="hlt">soil</span> <span class="hlt">moisture</span> analysis, the system setup reflects the operational forecast configuration including the atmospheric 4D-Var analysis. <span class="hlt">Soil</span> <span class="hlt">moisture</span> analyzed in the nudging experiment is the most accurate estimate when compared against in situ observations from the Oklahoma Mesonet. The corresponding forecast for 2 m temperature and relative humidity is almost as accurate as in the control experiment. Furthermore, it is shown that the <span class="hlt">soil</span> <span class="hlt">moisture</span> analysis influences local weather parameters including the planetary boundary layer height and cloud coverage.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2004AGUFMSF53A0723T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2004AGUFMSF53A0723T"><span><span class="hlt">Soil</span> <span class="hlt">Moisture</span> and Vegetation Effects on GPS Reflectivity From Land</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Torres, O.; Grant, M. S.; Bosch, D.</p> <p>2004-12-01</p> <p>While originally designed as a navigation system, the GPS signal has been used to achieve a number of useful scientific measurements. One of these measurements utilizes the reflection of the GPS signal from land to determine <span class="hlt">soil</span> <span class="hlt">moisture</span>. The study of GPS reflections is based on a bistatic configuration that utilizes forward reflection from the surface. The strength of the GPS signal varies in proportion to surface parameters such as <span class="hlt">soil</span> <span class="hlt">moisture</span>, <span class="hlt">soil</span> type, vegetation cover, and topography. This paper focuses on the effects of <span class="hlt">soil</span> water content and vegetation cover on the surface based around a reflectivity. A two-part method for calibrating the GPS reflectivity was developed that permits the comparison of the data with surface parameters. The first part of the method relieves the direct signal from any multipath effects, the second part is an over-water calibration that yields a reflectivity independent of the transmitting satellite. The sensitivity of the GPS signal to water in the <span class="hlt">soil</span> is shown by presenting the increase in reflectivity after rain as compared to before rain. The effect of vegetation on the reflected signal is also presented by the inclusion of leaf area index as a fading parameter in the reflected signal from corn and soy bean fields. The results are compared to extensive surface measurements made as part of the <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Experiment 2002 (SMEX 2002) in Iowa and SMEX 2003 in Georgia.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA426497','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA426497"><span>Scaling Properties and Spatial Interpolation of <span class="hlt">Soil</span> <span class="hlt">Moisture</span></span></a></p> <p><a target="_blank" href="http://www.dtic.mil/">DTIC Science & Technology</a></p> <p></p> <p>2004-08-24</p> <p>the sensitivities is useful not only for characterizing <span class="hlt">soil</span> <span class="hlt">moisture</span> but also for forecasting the vulnerability of a region’s water cycle to climate...regional water balance was presented that can be used to assess the impact of climatic fluctuations and changes on the water cycle of a region. In</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20050182714&hterms=gravimetric+methods&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Dgravimetric%2Bmethods','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20050182714&hterms=gravimetric+methods&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Dgravimetric%2Bmethods"><span>A comparison of <span class="hlt">soil</span> <span class="hlt">moisture</span> sensors for space flight applications</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Norikane, J. H.; Prenger, J. J.; Rouzan-Wheeldon, D. T.; Levine, H. G.</p> <p>2005-01-01</p> <p>Plants will be an important part of future long-term space missions. Automated plant growth systems require accurate and reliable methods of monitoring <span class="hlt">soil</span> <span class="hlt">moisture</span> levels. There are a number of different methods to accomplish this task. This study evaluated sensors using the capacitance method (ECH2O), the heat-pulse method (TMAS), and tensiometers, compared to <span class="hlt">soil</span> water loss measured gravimetrically in a side-by-side test. The experiment monitored evaporative losses from substrate compartments filled with 1- to 2-mm baked calcinated clay media. The ECH2O data correlated well with the gravimetric measurements, but over a limited range of <span class="hlt">soil</span> <span class="hlt">moisture</span>. The averaged TMAS sensor data overstated <span class="hlt">soil</span> <span class="hlt">moisture</span> content levels. The tensiometer data appeared to track evaporative losses in the 0.5- to 2.5-kPa range of matric potential that corresponds to the water content needed to grow plants. This small range is characteristic of large particle media, and thus high-resolution tensiometers are required to distinguish changing <span class="hlt">moisture</span> contents in this range.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=317084','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=317084"><span><span class="hlt">Soil</span> <span class="hlt">Moisture</span> Active Passive Satellite Status and Recent Validation Results</span></a></p> <p><a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>The <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Active Passive (SMAP) mission was launched in January, 2015 and began its calibration and validation (cal/val) phase in May, 2015. Cal/Val will begin with a focus on instrument measurements, brightness temperature and backscatter, and evolve to the geophysical products that include...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=315838','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=315838"><span>SMAP Validation and Accuracy Assessment of <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Products</span></a></p> <p><a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>Introduction: The <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Active Passive (SMAP) mission was launched in January, 2015 and will begin its calibration and validation (Cal/Val) phase in May, 2015. This will begin with a focus on instrument measurements, brightness temperature and backscatter, and evolve to the geophysical produ...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=323268','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=323268"><span>GCOM-W <span class="hlt">soil</span> <span class="hlt">moisture</span> and temperature algorithms and validation</span></a></p> <p><a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>Passive microwave remote sensing of <span class="hlt">soil</span> <span class="hlt">moisture</span> has matured over the past decade as a result of the Advanced Microwave Scanning Radiometer (AMSR) program of JAXA. This program has resulted in improved algorithms that have been supported by rigorous validation. Access to the products and the valida...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://images.nasa.gov/#/details-PIA18058.html','SCIGOVIMAGE-NASA'); return false;" href="https://images.nasa.gov/#/details-PIA18058.html"><span>NASA <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Mission Produces First Global Radar Map</span></a></p> <p><a target="_blank" href="https://images.nasa.gov/">NASA Image and Video Library</a></p> <p></p> <p>2015-04-21</p> <p>With its antenna now spinning at full speed, NASA new <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Active Passive SMAP observatory has successfully re-tested its science instruments and generated its first global maps, a key step to beginning routine science operations in May, 2015</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://images.nasa.gov/#/details-PIA18057.html','SCIGOVIMAGE-NASA'); return false;" href="https://images.nasa.gov/#/details-PIA18057.html"><span>NASA <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Mission Produces First Global Radiometer Map</span></a></p> <p><a target="_blank" href="https://images.nasa.gov/">NASA Image and Video Library</a></p> <p></p> <p>2015-04-21</p> <p>With its antenna now spinning at full speed, NASA new <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Active Passive SMAP observatory has successfully re-tested its science instruments and generated its first global maps, a key step to beginning routine science operations in May, 2015</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20170002761','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20170002761"><span>NASA <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Active Passive Mission Status and Science Performance</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Yueh, Simon H.; Entekhabi, Dara; O'Neill, Peggy; Njoku, Eni; Entin, Jared K.</p> <p>2016-01-01</p> <p>The <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Active Passive (SMAP) observatory was launched January 31, 2015, and its L-band radiometer and radar instruments became operational since mid-April 2015. The SMAP radiometer has been operating flawlessly, but the radar transmitter ceased operation on July 7. This paper provides a status summary of the calibration and validation of the SMAP instruments and the quality assessment of its <span class="hlt">soil</span> <span class="hlt">moisture</span> and freeze/thaw products. Since the loss of the radar in July, the SMAP project has been conducting two parallel activities to enhance the resolution of <span class="hlt">soil</span> <span class="hlt">moisture</span> products. One of them explores the Backus Gilbert optimum interpolation and de-convolution techniques based on the oversampling characteristics of the SMAP radiometer. The other investigates the disaggregation of the SMAP radiometer data using the European Space Agency's Sentinel-1 C-band synthetic radar data to obtain <span class="hlt">soil</span> <span class="hlt">moisture</span> products at about 1 to 3 kilometers resolution. In addition, SMAP's L-band data have found many new applications, including vegetation opacity, ocean surface salinity and hurricane ocean surface wind mapping. Highlights of these new applications will be provided.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=294399','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=294399"><span>U.S National cropland <span class="hlt">soil</span> <span class="hlt">moisture</span> monitoring using SMAP</span></a></p> <p><a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>Crop condition information is critical for public and private sector decision making that concerns agricultural policy, food production, food security, and food commodity prices. Crop conditions change quickly due to various growing condition events, such as temperature extremes, <span class="hlt">soil</span> <span class="hlt">moisture</span> defic...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19930053193&hterms=watershed+analysis&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dwatershed%2Banalysis','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19930053193&hterms=watershed+analysis&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dwatershed%2Banalysis"><span>Microwave <span class="hlt">soil</span> <span class="hlt">moisture</span> estimation in humid and semiarid watersheds</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>O'Neill, P. E.; Jackson, T. J.; Chauhan, N. S.; Seyfried, M. S.</p> <p>1993-01-01</p> <p>Land surface hydrologic-atmospheric interactions in humid and semi-arid watersheds were investigated. Active and passive microwave sensors were used to estimate the spatial and temporal distribution of <span class="hlt">soil</span> <span class="hlt">moisture</span> at the catchment scale in four areas. Results are presented and discussed. The eventual use of this information in the analysis and prediction of associated hydrologic processes is examined.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=268159','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=268159"><span>The <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Active Passive (SMAP) applications activity</span></a></p> <p><a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>The <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Active Passive (SMAP) mission is one of the first-tier satellite missions recommended by the U.S. National Research Council Committee on Earth Science and Applications from Space. The SMAP mission 1 is under development by NASA and is scheduled for launch late in 2014. The SMAP mea...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=286116','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=286116"><span>Overview of the NASA <span class="hlt">soil</span> <span class="hlt">moisture</span> active/passive mission</span></a></p> <p><a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>The NASA <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Active Passive (SMAP) Mission is currently in design Phase C and scheduled for launch in October 2014. Its mission concept is based on combined L-band radar and radiometry measurements obtained from a shared, rotating 6-meter antennae. These measurements will be used to retrie...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=337101','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=337101"><span>SMAP radiometer-based <span class="hlt">soil</span> <span class="hlt">moisture</span> products status and validation</span></a></p> <p><a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>The NASA <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Active Passive (SMAP) mission has been providing L-band brightness temperature measurements of the globe since 2015. These are used with retrieval algorithms to generate global products every 2-3 days. SMAP has recently implemented several new products to enhance both the spat...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=345327','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=345327"><span>Triple collocation based merging of satellite <span class="hlt">soil</span> <span class="hlt">moisture</span> retrievals</span></a></p> <p><a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>We propose a method for merging <span class="hlt">soil</span> <span class="hlt">moisture</span> retrievals from space borne active and passive microwave instruments based on weighted averaging taking into account the error characteristics of the individual data sets. The merging scheme is parameterized using error variance estimates obtained from u...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMEP41C0924C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMEP41C0924C"><span>Estimating <span class="hlt">soil</span> <span class="hlt">moisture</span> exceedance probability from antecedent rainfall</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Cronkite-Ratcliff, C.; Kalansky, J.; Stock, J. D.; Collins, B. D.</p> <p>2016-12-01</p> <p>The first storms of the rainy season in coastal California, USA, add <span class="hlt">moisture</span> to <span class="hlt">soils</span> but rarely trigger landslides. Previous workers proposed that antecedent rainfall, the cumulative seasonal rain from October 1 onwards, had to exceed specific amounts in order to trigger landsliding. Recent monitoring of <span class="hlt">soil</span> <span class="hlt">moisture</span> upslope of historic landslides in the San Francisco Bay Area shows that storms can cause positive pressure heads once <span class="hlt">soil</span> <span class="hlt">moisture</span> values exceed a threshold of volumetric water content (VWC). We propose that antecedent rainfall could be used to estimate the probability that VWC exceeds this threshold. A major challenge to estimating the probability of exceedance is that rain gauge records are frequently incomplete. We developed a stochastic model to impute (infill) missing hourly precipitation data. This model uses nearest neighbor-based conditional resampling of the gauge record using data from nearby rain gauges. Using co-located VWC measurements, imputed data can be used to estimate the probability that VWC exceeds a specific threshold for a given antecedent rainfall. The stochastic imputation model can also provide an estimate of uncertainty in the exceedance probability curve. Here we demonstrate the method using <span class="hlt">soil</span> <span class="hlt">moisture</span> and precipitation data from several sites located throughout Northern California. Results show a significant variability between sites in the sensitivity of VWC exceedance probability to antecedent rainfall.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26672277','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26672277"><span>[Bare <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Inversion Model Based on Visible-Shortwave Infrared Reflectance].</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Zheng, Xiao-po; Sun, Yue-jun; Qin, Qi-ming; Ren, Hua-zhong; Gao, Zhong-ling; Wu, Ling; Meng, Qing-ye; Wang, Jin-liang; Wang, Jian-hua</p> <p>2015-08-01</p> <p><span class="hlt">Soil</span> is the loose solum of land surface that can support plants. It consists of minerals, organics, atmosphere, <span class="hlt">moisture</span>, microbes, et al. Among its complex compositions, <span class="hlt">soil</span> <span class="hlt">moisture</span> varies greatly. Therefore, the fast and accurate inversion of <span class="hlt">soil</span> <span class="hlt">moisture</span> by using remote sensing is very crucial. In order to reduce the influence of <span class="hlt">soil</span> type on the retrieval of <span class="hlt">soil</span> <span class="hlt">moisture</span>, this paper proposed a normalized spectral slope and absorption index named NSSAI to estimate <span class="hlt">soil</span> <span class="hlt">moisture</span>. The modeling of the new index contains several key steps: Firstly, <span class="hlt">soil</span> samples with different <span class="hlt">moisture</span> level were artificially prepared, and <span class="hlt">soil</span> reflectance spectra was consequently measured using spectroradiometer produced by ASD Company. Secondly, the <span class="hlt">moisture</span> absorption spectral feature located at shortwave wavelengths and the spectral slope of visible wavelengths were calculated after analyzing the regular spectral feature change patterns of different <span class="hlt">soil</span> at different <span class="hlt">moisture</span> conditions. Then advantages of the two features at reducing <span class="hlt">soil</span> types' effects was synthesized to build the NSSAI. Thirdly, a linear relationship between NSSAI and <span class="hlt">soil</span> <span class="hlt">moisture</span> was established. The result showed that NSSAI worked better (correlation coefficient is 0.93) than most of other traditional methods in <span class="hlt">soil</span> <span class="hlt">moisture</span> extraction. It can weaken the influences caused by <span class="hlt">soil</span> types at different <span class="hlt">moisture</span> levels and improve the bare <span class="hlt">soil</span> <span class="hlt">moisture</span> inversion accuracy.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26087288','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26087288"><span>Changes in <span class="hlt">soil</span> <span class="hlt">moisture</span> drive <span class="hlt">soil</span> methane uptake along a fire regeneration chronosequence in a eucalypt forest landscape.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Fest, Benedikt; Wardlaw, Tim; Livesley, Stephen J; Duff, Thomas J; Arndt, Stefan K</p> <p>2015-11-01</p> <p>Disturbance associated with severe wildfires (WF) and WF simulating harvest operations can potentially alter <span class="hlt">soil</span> methane (CH4 ) oxidation in well-aerated forest <span class="hlt">soils</span> due to the effect on <span class="hlt">soil</span> properties linked to diffusivity, methanotrophic activity or changes in methanotrophic bacterial community structure. However, changes in <span class="hlt">soil</span> CH4 flux related to such disturbances are still rarely studied even though WF frequency is predicted to increase as a consequence of global climate change. We measured in-situ <span class="hlt">soil</span>-atmosphere CH4 exchange along a wet sclerophyll eucalypt forest regeneration chronosequence in Tasmania, Australia, where the time since the last severe fire or harvesting disturbance ranged from 9 to >200 years. On all sampling occasions, mean CH4 uptake increased from most recently disturbed sites (9 year) to sites at stand 'maturity' (44 and 76 years). In stands >76 years since disturbance, we observed a decrease in <span class="hlt">soil</span> CH4 uptake. A similar age dependency of potential CH4 oxidation for three <span class="hlt">soil</span> layers (0.0-0.05, 0.05-0.10, 0.10-0.15 m) could be observed on incubated <span class="hlt">soils</span> under controlled laboratory conditions. The differences in <span class="hlt">soil</span> CH4 uptake between forest stands of different age were predominantly driven by differences in <span class="hlt">soil</span> <span class="hlt">moisture</span> status, which <span class="hlt">affected</span> the diffusion of atmospheric CH4 into the <span class="hlt">soil</span>. The observed <span class="hlt">soil</span> <span class="hlt">moisture</span> pattern was likely driven by changes in interception or evapotranspiration with forest age, which have been well described for similar eucalypt forest systems in south-eastern Australia. Our results imply that there is a large amount of variability in CH4 uptake at a landscape scale that can be attributed to stand age and <span class="hlt">soil</span> <span class="hlt">moisture</span> differences. An increase in severe WF frequency in response to climate change could potentially increase overall forest <span class="hlt">soil</span> CH4 sinks. © 2015 John Wiley & Sons Ltd.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20180002232','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20180002232"><span>Improving <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Estimation through the Joint Assimilation of SMOS and GRACE Satellite Observations</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Girotto, Manuela</p> <p>2018-01-01</p> <p>Observations from recent <span class="hlt">soil</span> <span class="hlt">moisture</span> dedicated missions (e.g. SMOS or SMAP) have been used in innovative data assimilation studies to provide global high spatial (i.e., approximately10-40 km) and temporal resolution (i.e., daily) <span class="hlt">soil</span> <span class="hlt">moisture</span> profile estimates from microwave brightness temperature observations. These missions are only sensitive to near-surface <span class="hlt">soil</span> <span class="hlt">moisture</span> 0-5 cm). In contrast, the Gravity Recovery and Climate Experiment (GRACE) mission provides accurate measurements of the entire vertically integrated terrestrial water storage (TWS) column but, it is characterized by low spatial (i.e., 150,000 km2) and temporal (i.e., monthly) resolutions. Data assimilation studies have shown that GRACE-TWS primarily <span class="hlt">affects</span> (in absolute terms) deeper <span class="hlt">moisture</span> storages (i.e., groundwater). In this presentation I will review benefits and drawbacks associated to the assimilation of both types of observations. In particular, I will illustrate the benefits and drawbacks of their joint assimilation for the purpose of improving the entire profile of <span class="hlt">soil</span> <span class="hlt">moisture</span> (i.e., surface and deeper water storages).</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li class="active"><span>18</span></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_18 --> <div id="page_19" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li class="active"><span>19</span></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="361"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.B33E2116A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.B33E2116A"><span>2015-16 ENSO Drove Tropical <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Dynamics and Methane Fluxes</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Aronson, E. L.; Dierick, D.; Botthoff, J.; Swanson, A. C.; Johnson, R. F.; Allen, M. F.</p> <p>2017-12-01</p> <p>The El Niño/Southern Oscillation Event (ENSO) cycle drives large-scale climatic trends globally. Within the new world tropics, El Niño brings dryer weather than the counterpart La Niña. Atmospheric methane growth rates have shown extreme variability over the past three decades. One proposed driver is the proportion of tropical land surface saturated, <span class="hlt">affecting</span> methane production or consumption. We measured methane flux bimonthly through the transition of 2015-16 ENSO. The date of measurement, across El Niño and La Niña within the typical "rainy" and "dry" seasons, to be the most significant driver of methane flux. <span class="hlt">Soil</span> <span class="hlt">moisture</span> varied across this time period, and regulated methane flux. During the strong El Niño, extreme dry <span class="hlt">soil</span> conditions occurred in a typical "rainy" season month reducing <span class="hlt">soil</span> <span class="hlt">moisture</span>. Wetter than usual <span class="hlt">soil</span> conditions appeared during the "rainy" season month of the moderate La Niña. The dry El Niño <span class="hlt">soils</span> corresponded to greater methane consumption by tropical forest <span class="hlt">soils</span>, and a reduced local atmospheric column methane concentration. Conversely, the wet La Niña <span class="hlt">soils</span> had lower methane consumption and higher local atmospheric column methane concentrations. The ENSO cycle is a strong driver of tropical terrestrial and wetland <span class="hlt">soil</span> <span class="hlt">moisture</span> conditions, and can regulate global atmospheric methane dynamics.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=254216&keyword=Global+AND+warming&actType=&TIMSType=+&TIMSSubTypeID=&DEID=&epaNumber=&ntisID=&archiveStatus=Both&ombCat=Any&dateBeginCreated=&dateEndCreated=&dateBeginPublishedPresented=&dateEndPublishedPresented=&dateBeginUpdated=&dateEndUpdated=&dateBeginCompleted=&dateEndCompleted=&personID=&role=Any&journalID=&publisherID=&sortBy=revisionDate&count=50','EPA-EIMS'); return false;" href="https://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=254216&keyword=Global+AND+warming&actType=&TIMSType=+&TIMSSubTypeID=&DEID=&epaNumber=&ntisID=&archiveStatus=Both&ombCat=Any&dateBeginCreated=&dateEndCreated=&dateBeginPublishedPresented=&dateEndPublishedPresented=&dateBeginUpdated=&dateEndUpdated=&dateBeginCompleted=&dateEndCompleted=&personID=&role=Any&journalID=&publisherID=&sortBy=revisionDate&count=50"><span>Seasonal <span class="hlt">soil</span> <span class="hlt">moisture</span> patterns in contrasting habitats in the Willamette Valley, Oregon</span></a></p> <p><a target="_blank" href="http://oaspub.epa.gov/eims/query.page">EPA Science Inventory</a></p> <p></p> <p></p> <p>Changing seasonal <span class="hlt">soil</span> <span class="hlt">moisture</span> regimes caused by global warming may alter plant community composition in sensitive habitats such as wetlands and oak savannas. To evaluate such changes, an understanding of typical seasonal <span class="hlt">soil</span> <span class="hlt">moisture</span> regimes is necessary. The primary objective...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19760009508','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19760009508"><span>Ground truth report 1975 Phoenix microwave experiment. [Joint <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Experiment</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Blanchard, B. J.</p> <p>1975-01-01</p> <p>Direct measurements of <span class="hlt">soil</span> <span class="hlt">moisture</span> obtained in conjunction with aircraft data flights near Phoenix, Arizona in March, 1975 are summarized. The data were collected for the Joint <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Experiment.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110011762','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110011762"><span>Evaluation of SMAP Level 2 <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Algorithms Using SMOS Data</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Bindlish, Rajat; Jackson, Thomas J.; Zhao, Tianjie; Cosh, Michael; Chan, Steven; O'Neill, Peggy; Njoku, Eni; Colliander, Andreas; Kerr, Yann; Shi, J. C.</p> <p>2011-01-01</p> <p>The objectives of the SMAP (<span class="hlt">Soil</span> <span class="hlt">Moisture</span> Active Passive) mission are global measurements of <span class="hlt">soil</span> <span class="hlt">moisture</span> and land freeze/thaw state at 10 km and 3 km resolution, respectively. SMAP will provide <span class="hlt">soil</span> <span class="hlt">moisture</span> with a spatial resolution of 10 km with a 3-day revisit time at an accuracy of 0.04 m3/m3 [1]. In this paper we contribute to the development of the Level 2 <span class="hlt">soil</span> <span class="hlt">moisture</span> algorithm that is based on passive microwave observations by exploiting <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Ocean Salinity (SMOS) satellite observations and products. SMOS brightness temperatures provide a global real-world, rather than simulated, test input for the SMAP radiometer-only <span class="hlt">soil</span> <span class="hlt">moisture</span> algorithm. Output of the potential SMAP algorithms will be compared to both in situ measurements and SMOS <span class="hlt">soil</span> <span class="hlt">moisture</span> products. The investigation will result in enhanced SMAP pre-launch algorithms for <span class="hlt">soil</span> <span class="hlt">moisture</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.epa.gov/watersense/watersense-soil-moisture-based-control-technologies-notice-intent-noi','PESTICIDES'); return false;" href="https://www.epa.gov/watersense/watersense-soil-moisture-based-control-technologies-notice-intent-noi"><span>WaterSense <span class="hlt">Soil</span> <span class="hlt">Moisture</span>-Based Control Technologies Notice of Intent (NOI)</span></a></p> <p><a target="_blank" href="http://www.epa.gov/pesticides/search.htm">EPA Pesticide Factsheets</a></p> <p></p> <p></p> <p>By directly measuring the amount of <span class="hlt">moisture</span> in the <span class="hlt">soil</span>, <span class="hlt">soil</span> <span class="hlt">moisture</span>-based control technologies tailor irrigation schedules to meet landscape water needs based on seasonal patterns, as well as prevailing conditions in the landscape.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H11D1202Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H11D1202Y"><span>Aspect-related Vegetation Differences Amplify <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Variability in Semiarid Landscapes</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Yetemen, O.; Srivastava, A.; Kumari, N.; Saco, P. M.</p> <p>2017-12-01</p> <p><span class="hlt">Soil</span> <span class="hlt">moisture</span> variability (SMV) in semiarid landscapes is <span class="hlt">affected</span> by vegetation, <span class="hlt">soil</span> texture, climate, aspect, and topography. The heterogeneity in vegetation cover that results from the effects of microclimate, terrain attributes (slope gradient, aspect, drainage area etc.), <span class="hlt">soil</span> properties, and spatial variability in precipitation have been reported to act as the dominant factors modulating SMV in semiarid ecosystems. However, the role of hillslope aspect in SMV, though reported in many field studies, has not received the same degree of attention probably due to the lack of extensive large datasets. Numerical simulations can then be used to elucidate the contribution of aspect-driven vegetation patterns to this variability. In this work, we perform a sensitivity analysis to study on variables driving SMV using the CHILD landscape evolution model equipped with a spatially-distributed solar-radiation component that couples vegetation dynamics and surface hydrology. To explore how aspect-driven vegetation heterogeneity contributes to the SMV, CHILD was run using a range of parameters selected to reflect different scenarios (from uniform to heterogeneous vegetation cover). Throughout the simulations, the spatial distribution of <span class="hlt">soil</span> <span class="hlt">moisture</span> and vegetation cover are computed to estimate the corresponding coefficients of variation. Under the uniform spatial precipitation forcing and uniform <span class="hlt">soil</span> properties, the factors <span class="hlt">affecting</span> the spatial distribution of solar insolation are found to play a key role in the SMV through the emergence of aspect-driven vegetation patterns. Hence, factors such as catchment gradient, aspect, and latitude, define water stress and vegetation growth, and in turn <span class="hlt">affect</span> the available <span class="hlt">soil</span> <span class="hlt">moisture</span> content. Interestingly, changes in <span class="hlt">soil</span> properties (porosity, root depth, and pore-size distribution) over the domain are not as effective as the other factors. These findings show that the factors associated to aspect-related vegetation</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015HESS...19.3845T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015HESS...19.3845T"><span>Use of satellite and modeled <span class="hlt">soil</span> <span class="hlt">moisture</span> data for predicting event <span class="hlt">soil</span> loss at plot scale</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Todisco, F.; Brocca, L.; Termite, L. F.; Wagner, W.</p> <p>2015-09-01</p> <p>The potential of coupling <span class="hlt">soil</span> <span class="hlt">moisture</span> and a Universal <span class="hlt">Soil</span> Loss Equation-based (USLE-based) model for event <span class="hlt">soil</span> loss estimation at plot scale is carefully investigated at the Masse area, in central Italy. The derived model, named <span class="hlt">Soil</span> <span class="hlt">Moisture</span> for Erosion (SM4E), is applied by considering the unavailability of in situ <span class="hlt">soil</span> <span class="hlt">moisture</span> measurements, by using the data predicted by a <span class="hlt">soil</span> water balance model (SWBM) and derived from satellite sensors, i.e., the Advanced SCATterometer (ASCAT). The <span class="hlt">soil</span> loss estimation accuracy is validated using in situ measurements in which event observations at plot scale are available for the period 2008-2013. The results showed that including <span class="hlt">soil</span> <span class="hlt">moisture</span> observations in the event rainfall-runoff erosivity factor of the USLE enhances the capability of the model to account for variations in event <span class="hlt">soil</span> losses, the <span class="hlt">soil</span> <span class="hlt">moisture</span> being an effective alternative to the estimated runoff, in the prediction of the event <span class="hlt">soil</span> loss at Masse. The agreement between observed and estimated <span class="hlt">soil</span> losses (through SM4E) is fairly satisfactory with a determination coefficient (log-scale) equal to ~ 0.35 and a root mean square error (RMSE) of ~ 2.8 Mg ha-1. These results are particularly significant for the operational estimation of <span class="hlt">soil</span> losses. Indeed, currently, <span class="hlt">soil</span> <span class="hlt">moisture</span> is a relatively simple measurement at the field scale and remote sensing data are also widely available on a global scale. Through satellite data, there is the potential of applying the SM4E model for large-scale monitoring and quantification of the <span class="hlt">soil</span> erosion process.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19820016662','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19820016662"><span>Microwave <span class="hlt">soil</span> <span class="hlt">moisture</span> measurements and analysis</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Newton, R. W.; Howell, T. A.; Nieber, J. L.; Vanbavel, C. H. M. (Principal Investigator)</p> <p>1980-01-01</p> <p>An effort to develop a model that simulates the distribution of water content and of temperature in bare <span class="hlt">soil</span> is documented. The field experimental set up designed to acquire the data to test this model is described. The microwave signature acquisition system (MSAS) field measurements acquired in Colby, Kansas during the summer of 1978 are pesented.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=318456','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=318456"><span>Biochar can positively influence <span class="hlt">soil</span> <span class="hlt">moisture</span> relations</span></a></p> <p><a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>One major issue related to climate change is the potential to improve <span class="hlt">soil</span> water relations in light of changes in future precipitation patterns or reductions in water availability in drier portions of the world (such as the western US). It appears that biochar may play a positive role, but that rol...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1916428C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1916428C"><span>Observing and modeling links between <span class="hlt">soil</span> <span class="hlt">moisture</span>, microbes and CH4 fluxes from forest <span class="hlt">soils</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Christiansen, Jesper; Levy-Booth, David; Barker, Jason; Prescott, Cindy; Grayston, Sue</p> <p>2017-04-01</p> <p><span class="hlt">Soil</span> <span class="hlt">moisture</span> is a key driver of methane (CH4) fluxes in forest <span class="hlt">soils</span>, both of the net uptake of atmospheric CH4 and emission from the <span class="hlt">soil</span>. Climate and land use change will alter spatial patterns of <span class="hlt">soil</span> <span class="hlt">moisture</span> as well as temporal variability impacting the net CH4 exchange. The impact on the resultant net CH4 exchange however is linked to the underlying spatial and temporal distribution of the <span class="hlt">soil</span> microbial communities involved in CH4 cycling as well as the response of the <span class="hlt">soil</span> microbial community to environmental changes. Significant progress has been made to target specific CH4 consuming and producing <span class="hlt">soil</span> organisms, which is invaluable in order to understand the microbial regulation of the CH4 cycle in forest <span class="hlt">soils</span>. However, it is not clear as to which extent <span class="hlt">soil</span> <span class="hlt">moisture</span> shapes the structure, function and abundance of CH4 specific microorganisms and how this is linked to observed net CH4 exchange under contrasting <span class="hlt">soil</span> <span class="hlt">moisture</span> regimes. Here we report on the results from a research project aiming to understand how the CH4 net exchange is shaped by the interactive effects <span class="hlt">soil</span> <span class="hlt">moisture</span> and the spatial distribution CH4 consuming (methanotrophs) and producing (methanogens). We studied the growing season variations of in situ CH4 fluxes, microbial gene abundances of methanotrophs and methanogens, <span class="hlt">soil</span> hydrology, and nutrient availability in three typical forest types across a <span class="hlt">soil</span> <span class="hlt">moisture</span> gradient in a temperate rainforest on the Canadian Pacific coast. Furthermore, we conducted laboratory experiments to determine whether the net CH4 exchange from hydrologically contrasting forest <span class="hlt">soils</span> responded differently to changes in <span class="hlt">soil</span> <span class="hlt">moisture</span>. Lastly, we modelled the microbial mediation of net CH4 exchange along the <span class="hlt">soil</span> <span class="hlt">moisture</span> gradient using structural equation modeling. Our study shows that it is possible to link spatial patterns of in situ net exchange of CH4 to microbial abundance of CH4 consuming and producing organisms. We also show that the microbial</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19750018483','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19750018483"><span>Dielectric properties of <span class="hlt">soils</span> as a function of <span class="hlt">moisture</span> content</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Cihlar, J.; Ulaby, F. T.</p> <p>1974-01-01</p> <p><span class="hlt">Soil</span> dielectric constant measurements are reviewed and the dependence of the dielectric constant on various <span class="hlt">soil</span> parameters is determined. <span class="hlt">Moisture</span> content is given special attention because of its practical significance in remote sensing and because it represents the single most influential parameter as far as <span class="hlt">soil</span> dielectric properties are concerned. Relative complex dielectric constant curves are derived as a function of volumetric <span class="hlt">soil</span> water content at three frequencies (1.3 GHz, 4.0 GHz, and 10.0 GHz) for each of three <span class="hlt">soil</span> textures (sand, loam, and clay). These curves, presented in both tabular and graphical form, were chosen as representative of the reported experimental data. Calculations based on these curves showed that the power reflection coefficient and emissivity, unlike skin depth, vary only slightly as a function of frequency and <span class="hlt">soil</span> texture.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3960259','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3960259"><span>Effects of <span class="hlt">Soil</span> <span class="hlt">Moisture</span> on the Temperature Sensitivity of <span class="hlt">Soil</span> Heterotrophic Respiration: A Laboratory Incubation Study</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Zhou, Weiping; Hui, Dafeng; Shen, Weijun</p> <p>2014-01-01</p> <p>The temperature sensitivity (Q10) of <span class="hlt">soil</span> heterotrophic respiration (Rh) is an important ecological model parameter and may vary with temperature and <span class="hlt">moisture</span>. While Q10 generally decreases with increasing temperature, the <span class="hlt">moisture</span> effects on Q10 have been controversial. To address this, we conducted a 90-day laboratory incubation experiment using a subtropical forest <span class="hlt">soil</span> with a full factorial combination of five <span class="hlt">moisture</span> levels (20%, 40%, 60%, 80%, and 100% water holding capacity - WHC) and five temperature levels (10, 17, 24, 31, and 38°C). Under each <span class="hlt">moisture</span> treatment, Rh was measured several times for each temperature treatment to derive Q10 based on the exponential relationships between Rh and temperature. Microbial biomass carbon (MBC), microbial community structure and <span class="hlt">soil</span> nutrients were also measured several times to detect their potential contributions to the <span class="hlt">moisture</span>-induced Q10 variation. We found that Q10 was significantly lower at lower <span class="hlt">moisture</span> levels (60%, 40% and 20% WHC) than at higher <span class="hlt">moisture</span> level (80% WHC) during the early stage of the incubation, but became significantly higher at 20%WHC than at 60% WHC and not significantly different from the other three <span class="hlt">moisture</span> levels during the late stage of incubation. In contrast, <span class="hlt">soil</span> Rh had the highest value at 60% WHC and the lowest at 20% WHC throughout the whole incubation period. Variations of Q10 were significantly associated with MBC during the early stages of incubation, but with the fungi-to-bacteria ratio during the later stages, suggesting that changes in microbial biomass and community structure are related to the <span class="hlt">moisture</span>-induced Q10 changes. This study implies that global warming’s impacts on <span class="hlt">soil</span> CO2 emission may depend upon <span class="hlt">soil</span> <span class="hlt">moisture</span> conditions. With the same temperature rise, wetter <span class="hlt">soils</span> may emit more CO2 into the atmosphere via heterotrophic respiration. PMID:24647610</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24743980','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24743980"><span><span class="hlt">Soil</span> microbial community responses to antibiotic-contaminated manure under different <span class="hlt">soil</span> <span class="hlt">moisture</span> regimes.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Reichel, Rüdiger; Radl, Viviane; Rosendahl, Ingrid; Albert, Andreas; Amelung, Wulf; Schloter, Michael; Thiele-Bruhn, Sören</p> <p>2014-01-01</p> <p>Sulfadiazine (SDZ) is an antibiotic frequently administered to livestock, and it alters microbial communities when entering <span class="hlt">soils</span> with animal manure, but understanding the interactions of these effects to the prevailing climatic regime has eluded researchers. A climatic factor that strongly controls microbial activity is <span class="hlt">soil</span> <span class="hlt">moisture</span>. Here, we hypothesized that the effects of SDZ on <span class="hlt">soil</span> microbial communities will be modulated depending on the <span class="hlt">soil</span> <span class="hlt">moisture</span> conditions. To test this hypothesis, we performed a 49-day fully controlled climate chamber pot experiments with <span class="hlt">soil</span> grown with Dactylis glomerata (L.). Manure-amended pots without or with SDZ contamination were incubated under a dynamic <span class="hlt">moisture</span> regime (DMR) with repeated drying and rewetting changes of >20 % maximum water holding capacity (WHCmax) in comparison to a control <span class="hlt">moisture</span> regime (CMR) at an average <span class="hlt">soil</span> <span class="hlt">moisture</span> of 38 % WHCmax. We then monitored changes in SDZ concentration as well as in the phenotypic phospholipid fatty acid and genotypic 16S rRNA gene fragment patterns of the microbial community after 7, 20, 27, 34, and 49 days of incubation. The results showed that strongly changing water supply made SDZ accessible to mild extraction in the short term. As a result, and despite rather small SDZ effects on community structures, the PLFA-derived microbial biomass was suppressed in the SDZ-contaminated DMR <span class="hlt">soils</span> relative to the CMR ones, indicating that dynamic <span class="hlt">moisture</span> changes accelerate the susceptibility of the <span class="hlt">soil</span> microbial community to antibiotics.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H53J1615A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H53J1615A"><span>Downscaling SMAP Radiometer <span class="hlt">Soil</span> <span class="hlt">Moisture</span> over the CONUS using <span class="hlt">Soil</span>-Climate Information and Ensemble Learning</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Abbaszadeh, P.; Moradkhani, H.</p> <p>2017-12-01</p> <p><span class="hlt">Soil</span> <span class="hlt">moisture</span> contributes significantly towards the improvement of weather and climate forecast and understanding terrestrial ecosystem processes. It is known as a key hydrologic variable in the agricultural drought monitoring, flood modeling and irrigation management. While satellite retrievals can provide an unprecedented information on <span class="hlt">soil</span> <span class="hlt">moisture</span> at global-scale, the products are generally at coarse spatial resolutions (25-50 km2). This often hampers their use in regional or local studies, which normally require a finer resolution of the data set. This work presents a new framework based on an ensemble learning method while using <span class="hlt">soil</span>-climate information derived from remote-sensing and ground-based observations to downscale the level 3 daily composite version (L3_SM_P) of SMAP radiometer <span class="hlt">soil</span> <span class="hlt">moisture</span> over the Continental U.S. (CONUS) at 1 km spatial resolution. In the proposed method, a suite of remotely sensed and in situ data sets in addition to <span class="hlt">soil</span> texture information and topography data among others were used. The downscaled product was validated against in situ <span class="hlt">soil</span> <span class="hlt">moisture</span> measurements collected from a limited number of core validation sites and several hundred sparse <span class="hlt">soil</span> <span class="hlt">moisture</span> networks throughout the CONUS. The obtained results indicated a great potential of the proposed methodology to derive the fine resolution <span class="hlt">soil</span> <span class="hlt">moisture</span> information applicable for fine resolution hydrologic modeling, data assimilation and other regional studies.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.H43F1017B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.H43F1017B"><span><span class="hlt">Soil</span> <span class="hlt">moisture</span> dynamics and their effect on bioretention performance in Northeast Ohio</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bush, S. A.; Jefferson, A.; Jarden, K.; Kinsman-Costello, L. E.; Grieser, J.</p> <p>2014-12-01</p> <p> time and peak flow, are altered relative to a control street. This analysis suggests that street-scale implementation of bioretention can reduce the impact of impervious surface on stormflows, but more information is needed to fully understand how <span class="hlt">soil</span> <span class="hlt">moisture</span> of the bioretentions <span class="hlt">affects</span> inter-storm variability in performance.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27594213','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27594213"><span>The sensitivity of <span class="hlt">soil</span> respiration to <span class="hlt">soil</span> temperature, <span class="hlt">moisture</span>, and carbon supply at the global scale.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Hursh, Andrew; Ballantyne, Ashley; Cooper, Leila; Maneta, Marco; Kimball, John; Watts, Jennifer</p> <p>2017-05-01</p> <p><span class="hlt">Soil</span> respiration (Rs) is a major pathway by which fixed carbon in the biosphere is returned to the atmosphere, yet there are limits to our ability to predict respiration rates using environmental drivers at the global scale. While temperature, <span class="hlt">moisture</span>, carbon supply, and other site characteristics are known to regulate <span class="hlt">soil</span> respiration rates at plot scales within certain biomes, quantitative frameworks for evaluating the relative importance of these factors across different biomes and at the global scale require tests of the relationships between field estimates and global climatic data. This study evaluates the factors driving Rs at the global scale by linking global datasets of <span class="hlt">soil</span> <span class="hlt">moisture</span>, <span class="hlt">soil</span> temperature, primary productivity, and <span class="hlt">soil</span> carbon estimates with observations of annual Rs from the Global <span class="hlt">Soil</span> Respiration Database (SRDB). We find that calibrating models with parabolic <span class="hlt">soil</span> <span class="hlt">moisture</span> functions can improve predictive power over similar models with asymptotic functions of mean annual precipitation. <span class="hlt">Soil</span> temperature is comparable with previously reported air temperature observations used in predicting Rs and is the dominant driver of Rs in global models; however, within certain biomes <span class="hlt">soil</span> <span class="hlt">moisture</span> and <span class="hlt">soil</span> carbon emerge as dominant predictors of Rs. We identify regions where typical temperature-driven responses are further mediated by <span class="hlt">soil</span> <span class="hlt">moisture</span>, precipitation, and carbon supply and regions in which environmental controls on high Rs values are difficult to ascertain due to limited field data. Because <span class="hlt">soil</span> <span class="hlt">moisture</span> integrates temperature and precipitation dynamics, it can more directly constrain the heterotrophic component of Rs, but global-scale models tend to smooth its spatial heterogeneity by aggregating factors that increase <span class="hlt">moisture</span> variability within and across biomes. We compare statistical and mechanistic models that provide independent estimates of global Rs ranging from 83 to 108 Pg yr -1 , but also highlight regions of uncertainty</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.A33J0315K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.A33J0315K"><span>Sensitivity of <span class="hlt">soil</span> <span class="hlt">moisture</span> initialization for decadal predictions under different regional climatic conditions in Europe</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Khodayar, S.; Sehlinger, A.; Feldmann, H.; Kottmeier, C.</p> <p>2015-12-01</p> <p>The impact of <span class="hlt">soil</span> initialization is investigated through perturbation simulations with the regional climate model COSMO-CLM. The focus of the investigation is to assess the sensitivity of simulated extreme periods, dry and wet, to <span class="hlt">soil</span> <span class="hlt">moisture</span> initialization in different climatic regions over Europe and to establish the necessary spin up time within the framework of decadal predictions for these regions. Sensitivity experiments consisted of a reference simulation from 1968 to 1999 and 5 simulations from 1972 to 1983. The Effective Drought Index (EDI) is used to select and quantify drought status in the reference run to establish the simulation time period for the sensitivity experiments. Different <span class="hlt">soil</span> initialization procedures are investigated. The sensitivity of the decadal predictions to <span class="hlt">soil</span> <span class="hlt">moisture</span> initial conditions is investigated through the analysis of water cycle components' (WCC) variability. In an episodic time scale the local effects of <span class="hlt">soil</span> <span class="hlt">moisture</span> on the boundary-layer and the propagated effects on the large-scale dynamics are analysed. The results show: (a) COSMO-CLM reproduces the observed features of the drought index. (b) <span class="hlt">Soil</span> <span class="hlt">moisture</span> initialization exerts a relevant impact on WCC, e.g., precipitation distribution and intensity. (c) Regional characteristics strongly impact the response of the WCC. Precipitation and evapotranspiration deviations are larger for humid regions. (d) The initial <span class="hlt">soil</span> conditions (wet/dry), the regional characteristics (humid/dry) and the annual period (wet/dry) play a key role in the time that <span class="hlt">soil</span> needs to restore quasi-equilibrium and the impact on the atmospheric conditions. Humid areas, and for all regions, a humid initialization, exhibit shorter spin up times, also <span class="hlt">soil</span> reacts more sensitive when initialised during dry periods. (e) The initial <span class="hlt">soil</span> perturbation may markedly modify atmospheric pressure field, wind circulation systems and atmospheric water vapour distribution <span class="hlt">affecting</span> atmospheric stability</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015HESSD..12.2945T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015HESSD..12.2945T"><span>Use of satellite and modelled <span class="hlt">soil</span> <span class="hlt">moisture</span> data for predicting event <span class="hlt">soil</span> loss at plot scale</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Todisco, F.; Brocca, L.; Termite, L. F.; Wagner, W.</p> <p>2015-03-01</p> <p>The potential of coupling <span class="hlt">soil</span> <span class="hlt">moisture</span> and a~USLE-based model for event <span class="hlt">soil</span> loss estimation at plot scale is carefully investigated at the Masse area, in Central Italy. The derived model, named <span class="hlt">Soil</span> <span class="hlt">Moisture</span> for Erosion (SM4E), is applied by considering the unavailability of in situ <span class="hlt">soil</span> <span class="hlt">moisture</span> measurements, by using the data predicted by a <span class="hlt">soil</span> water balance model (SWBM) and derived from satellite sensors, i.e. the Advanced SCATterometer (ASCAT). The <span class="hlt">soil</span> loss estimation accuracy is validated using in situ measurements in which event observations at plot scale are available for the period 2008-2013. The results showed that including <span class="hlt">soil</span> <span class="hlt">moisture</span> observations in the event rainfall-runoff erosivity factor of the RUSLE/USLE, enhances the capability of the model to account for variations in event <span class="hlt">soil</span> losses, being the <span class="hlt">soil</span> <span class="hlt">moisture</span> an effective alternative to the estimated runoff, in the prediction of the event <span class="hlt">soil</span> loss at Masse. The agreement between observed and estimated <span class="hlt">soil</span> losses (through SM4E) is fairly satisfactory with a determination coefficient (log-scale) equal to of ~ 0.35 and a root-mean-square error (RMSE) of ~ 2.8 Mg ha-1. These results are particularly significant for the operational estimation of <span class="hlt">soil</span> losses. Indeed, currently, <span class="hlt">soil</span> <span class="hlt">moisture</span> is a relatively simple measurement at the field scale and remote sensing data are also widely available on a global scale. Through satellite data, there is the potential of applying the SM4E model for large-scale monitoring and quantification of the <span class="hlt">soil</span> erosion process.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=244275','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=244275"><span>Remote sensing of an agricultural <span class="hlt">soil</span> <span class="hlt">moisture</span> network in Walnut Creek, Iowa</span></a></p> <p><a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>The calibration and validation of <span class="hlt">soil</span> <span class="hlt">moisture</span> remote sensing products is complicated by the logistics of installing a <span class="hlt">soil</span> <span class="hlt">moisture</span> network for a long term period in an active landscape. Usually <span class="hlt">soil</span> <span class="hlt">moisture</span> sensors are added to existing precipitation networks which have as a singular requiremen...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=304546','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=304546"><span>Evaluation of SMOS <span class="hlt">soil</span> <span class="hlt">moisture</span> products over the CanEx-SM10 area</span></a></p> <p><a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>The <span class="hlt">Soil</span> <span class="hlt">Moisture</span> and Ocean Salinity (SMOS) Earth observation satellite was launched in November 2009 to provide global <span class="hlt">soil</span> <span class="hlt">moisture</span> and ocean salinity measurements based on L-Band passive microwave measurements. Since its launch, different versions of SMOS <span class="hlt">soil</span> <span class="hlt">moisture</span> products processors have be...</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li class="active"><span>19</span></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_19 --> <div id="page_20" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li class="active"><span>20</span></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="381"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=263658','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=263658"><span>SMOS <span class="hlt">soil</span> <span class="hlt">moisture</span> validation with U.S. in situ newworks</span></a></p> <p><a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>Estimation of <span class="hlt">soil</span> <span class="hlt">moisture</span> at large scale has been performed using several satellite-based passive microwave sensors using a variety of retrieval methods. The most recent source of <span class="hlt">soil</span> <span class="hlt">moisture</span> is the European Space Agency <span class="hlt">Soil</span> <span class="hlt">Moisture</span> and Ocean Salinity (SMOS) mission. Since it is a new sensor u...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=330724','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=330724"><span>Rainfall estimation by inverting SMOS <span class="hlt">soil</span> <span class="hlt">moisture</span> estimates: a comparison of different methods over Australia</span></a></p> <p><a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>Remote sensing of <span class="hlt">soil</span> <span class="hlt">moisture</span> has reached a level of maturity and accuracy for which the retrieved products can be used to improve hydrological and meteorological applications. In this study, the <span class="hlt">soil</span> <span class="hlt">moisture</span> product from the European Space Agency’s <span class="hlt">Soil</span> <span class="hlt">Moisture</span> and Ocean Salinity (SMOS) is used...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=320076','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=320076"><span>Estimating error cross-correlations in <span class="hlt">soil</span> <span class="hlt">moisture</span> data sets using extended collocation analysis</span></a></p> <p><a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>Consistent global <span class="hlt">soil</span> <span class="hlt">moisture</span> records are essential for studying the role of hydrologic processes within the larger earth system. Various studies have shown the benefit of assimilating satellite-based <span class="hlt">soil</span> <span class="hlt">moisture</span> data into water balance models or merging multi-source <span class="hlt">soil</span> <span class="hlt">moisture</span> retrievals int...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=328373','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=328373"><span>Precipitation estimation using L-Band and C-Band <span class="hlt">soil</span> <span class="hlt">moisture</span> retrievals</span></a></p> <p><a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>An established methodology for estimating precipitation amounts from satellite-based <span class="hlt">soil</span> <span class="hlt">moisture</span> retrievals is applied to L-band products from the <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Active Passive (SMAP) and <span class="hlt">Soil</span> <span class="hlt">Moisture</span> and Ocean Salinity (SMOS) satellite missions and to a C-band product from the Advanced Scatterome...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=265877','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=265877"><span>Field scale spatiotemporal analysis of surface <span class="hlt">soil</span> <span class="hlt">moisture</span> for evaluating point-scale in situ networks</span></a></p> <p><a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p><span class="hlt">Soil</span> <span class="hlt">moisture</span> is an intrinsic state variable that varies considerably in space and time. From a hydrologic viewpoint, <span class="hlt">soil</span> <span class="hlt">moisture</span> controls runoff, infiltration, storage and drainage. <span class="hlt">Soil</span> <span class="hlt">moisture</span> determines the partitioning of the incoming radiation between latent and sensible heat fluxes. Althou...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=318185','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=318185"><span>Potential of bias correction for downscaling passive microwave and <span class="hlt">soil</span> <span class="hlt">moisture</span> data</span></a></p> <p><a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>Passive microwave satellites such as SMOS (<span class="hlt">Soil</span> <span class="hlt">Moisture</span> and Ocean Salinity) or SMAP (<span class="hlt">Soil</span> <span class="hlt">Moisture</span> Active Passive) observe brightness temperature (TB) and retrieve <span class="hlt">soil</span> <span class="hlt">moisture</span> at a spatial resolution greater than most hydrological processes. Bias correction is proposed as a simple method to disag...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=330813','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=330813"><span>Validation of SMAP surface <span class="hlt">soil</span> <span class="hlt">moisture</span> products with core validation sites</span></a></p> <p><a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>The NASA <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Active Passive (SMAP) mission has utilized a set of core validation sites as the primary methodology in assessing the <span class="hlt">soil</span> <span class="hlt">moisture</span> retrieval algorithm performance. Those sites provide well-calibrated in situ <span class="hlt">soil</span> <span class="hlt">moisture</span> measurements within SMAP product grid pixels for diver...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=335031','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=335031"><span>Evaluating <span class="hlt">soil</span> <span class="hlt">moisture</span> retrievals from ESA's SMOS and NASA's SMAP brightness temperature datasets</span></a></p> <p><a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>Two satellites are currently monitoring surface <span class="hlt">soil</span> <span class="hlt">moisture</span> (SM) from L-band observations: SMOS (<span class="hlt">Soil</span> <span class="hlt">Moisture</span> and Ocean Salinity), a European Space Agency (ESA) satellite that was launched on November 2, 2009 and SMAP (<span class="hlt">Soil</span> <span class="hlt">Moisture</span> Active Passive), a National Aeronautics and Space Administration...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=301013','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=301013"><span>Calibration and validation of the COSMOS rover for surface <span class="hlt">soil</span> <span class="hlt">moisture</span></span></a></p> <p><a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>The mobile COsmic-ray <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Observing System (COSMOS) rover may be useful for validating satellite-based estimates of near surface <span class="hlt">soil</span> <span class="hlt">moisture</span>, but the accuracy with which the rover can measure 0-5 cm <span class="hlt">soil</span> <span class="hlt">moisture</span> has not been previously determined. Our objectives were to calibrate and va...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/5151','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/5151"><span>Using <span class="hlt">soil</span> temperature and <span class="hlt">moisture</span> to predict forest <span class="hlt">soil</span> nitrogen mineralization</span></a></p> <p><a target="_blank" href="http://www.fs.usda.gov/treesearch/">Treesearch</a></p> <p>Jennifer D. Knoepp; Wayne T. Swank</p> <p>2002-01-01</p> <p>Due to the importance of N in forest productivity ecosystem and nutrient cycling research often includes measurement of <span class="hlt">soil</span> N transformation rates as indices of potential availability and ecosystem losses of N. We examined the feasibility of using <span class="hlt">soil</span> temperature and <span class="hlt">moisture</span> content to predict <span class="hlt">soil</span> N mineralization rates (Nmin) at the Coweeta Hydrologic Laboratory...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=241335&keyword=square&actType=&TIMSType=+&TIMSSubTypeID=&DEID=&epaNumber=&ntisID=&archiveStatus=Both&ombCat=Any&dateBeginCreated=&dateEndCreated=&dateBeginPublishedPresented=&dateEndPublishedPresented=&dateBeginUpdated=&dateEndUpdated=&dateBeginCompleted=&dateEndCompleted=&personID=&role=Any&journalID=&publisherID=&sortBy=revisionDate&count=50','EPA-EIMS'); return false;" href="https://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=241335&keyword=square&actType=&TIMSType=+&TIMSSubTypeID=&DEID=&epaNumber=&ntisID=&archiveStatus=Both&ombCat=Any&dateBeginCreated=&dateEndCreated=&dateBeginPublishedPresented=&dateEndPublishedPresented=&dateBeginUpdated=&dateEndUpdated=&dateBeginCompleted=&dateEndCompleted=&personID=&role=Any&journalID=&publisherID=&sortBy=revisionDate&count=50"><span>Identification of optimal <span class="hlt">soil</span> hydraulic functions and parameters for predicting <span class="hlt">soil</span> <span class="hlt">moisture</span></span></a></p> <p><a target="_blank" href="http://oaspub.epa.gov/eims/query.page">EPA Science Inventory</a></p> <p></p> <p></p> <p>We examined the accuracy of several commonly used <span class="hlt">soil</span> hydraulic functions and associated parameters for predicting observed <span class="hlt">soil</span> <span class="hlt">moisture</span> data. We used six combined methods formed by three commonly used <span class="hlt">soil</span> hydraulic functions – i.e., Brooks and Corey (1964) (BC), Campbell (19...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27600157','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27600157"><span>Individual contributions of climate and vegetation change to <span class="hlt">soil</span> <span class="hlt">moisture</span> trends across multiple spatial scales.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Feng, Huihui</p> <p>2016-09-07</p> <p>Climate and vegetation change are two dominating factors for <span class="hlt">soil</span> <span class="hlt">moisture</span> trend. However, their individual contributions remain unknown due to their complex interaction. Here, I separated their contributions through a trajectory-based method across the global, regional and local scales. Our results demonstrated that climate change accounted for 98.78% and 114.64% of the global drying and wetting trend. Vegetation change exhibited a relatively weak influence (contributing 1.22% and -14.64% of the global drying and wetting) because it occurred in a limited area on land. Regionally, the impact of vegetation change cannot be neglected, which contributed -40.21% of the <span class="hlt">soil</span> <span class="hlt">moisture</span> change in the wetting zone. Locally, the contributions strongly correlated to the local environmental characteristics. Vegetation negatively <span class="hlt">affected</span> <span class="hlt">soil</span> <span class="hlt">moisture</span> trends in the dry and sparsely vegetated regions and positively in the wet and densely vegetated regions. I conclude that individual contributions of climate and vegetation change vary at the global, regional and local scales. Climate change dominates the <span class="hlt">soil</span> <span class="hlt">moisture</span> trends, while vegetation change acts as a regulator to drying or wetting the <span class="hlt">soil</span> under the changing climate.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..1715065F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..1715065F"><span>Upscaling of <span class="hlt">soil</span> <span class="hlt">moisture</span> measurements in NW Italy</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ferraris, Stefano; Canone, Davide; Previati, Maurizio; Brunod, Christian; Ratto, Sara; Cauduro, Marco</p> <p>2015-04-01</p> <p>There is large mismatch in spatial scale between the climate and meteorological model grid, and the scale of <span class="hlt">soil</span> and vegetation measurements. Remote sensing data can help to fit the model scale, but they cannot provide rootzone data. In this work some <span class="hlt">soil</span> <span class="hlt">moisture</span> datasets are analysed for the sake of providing larger scale estimation of <span class="hlt">soil</span> <span class="hlt">moisture</span> and water and energy fluxes. The first dataset refers to a plain site near Torino, where measurements are taken since 1997 (Baudena et al., 2012), and a mountain site close to the town. The second one is a dataset in the mountains of Valle d'Aosta (Brocca et al., 2013), where 4 years of data are available. The use of digital elevation models and vegetation maps is shown in this work. Some <span class="hlt">soil</span> processes (e.g. Whalley et al., 2012) are usually disregarded, but in this work their possible impact is considered. References L. Brocca, A. Tarpanelli, T. Moramarco, F. Melone, S.M. Ratto, M. Cauduro, S. Ferraris, N. Berni, F. Ponziani, W. Wagner, T. Melzer (2013). <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Estimation in Alpine Catchments through Modeling and Satellite Observations VADOSE ZONE JOURNAL, vol. 8-2, p. 1-10, doi:10.2136/vzj2012.0102 M. Baudena, I. Bevilacqua, D. Canone, S. Ferraris, M. Previati, A. Provenzale (2012). <span class="hlt">Soil</span> water dynamics at a midlatitude test site: Field measurements and box modeling approaches. JOURNAL OF HYDROLOGY, vol. 414-415, p. 329-340, ISSN: 0022-1694, doi: 10.1016/j.jhydrol.2011.11.009 W.R. Whalley, G.P. Matthews, S. Ferraris (2012). The effect of compaction and shear deformation of saturated <span class="hlt">soil</span> on hydraulic conductivity. <span class="hlt">SOIL</span> & TILLAGE RESEARCH, vol. 125, p. 23-29, ISSN: 0167-1987</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015BGeo...12.3655Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015BGeo...12.3655Z"><span><span class="hlt">Soil</span> <span class="hlt">moisture</span> influence on the interannual variation in temperature sensitivity of <span class="hlt">soil</span> organic carbon mineralization in the Loess Plateau</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhang, Y. J.; Guo, S. L.; Zhao, M.; Du, L. L.; Li, R. J.; Jiang, J. S.; Wang, R.; Li, N. N.</p> <p>2015-06-01</p> <p>Temperature sensitivity of <span class="hlt">soil</span> organic carbon (SOC) mineralization (i.e., Q10) determines how strong the feedback from global warming may be on the atmospheric CO2 concentration; thus, understanding the factors influencing the interannual variation in Q10 is important for accurately estimating local <span class="hlt">soil</span> carbon cycle. In situ SOC mineralization rate was measured using an automated CO2 flux system (Li-8100) in long-term bare fallow <span class="hlt">soil</span> in the Loess Plateau (35°12' N, 107°40' E) in Changwu, Shaanxi, China from 2008 to 2013. The results showed that the annual cumulative SOC mineralization ranged from 226 to 298 g C m-2 yr-1, with a mean of 253 g C m-2 yr-1 and a coefficient of variation (CV) of 13%, annual Q10 ranged from 1.48 to 1.94, with a mean of 1.70 and a CV of 10%, and annual <span class="hlt">soil</span> <span class="hlt">moisture</span> content ranged from 38.6 to 50.7% <span class="hlt">soil</span> water-filled pore space (WFPS), with a mean of 43.8% WFPS and a CV of 11%, which were mainly <span class="hlt">affected</span> by the frequency and distribution of precipitation. Annual Q10 showed a quadratic correlation with annual mean <span class="hlt">soil</span> <span class="hlt">moisture</span> content. In conclusion, understanding of the relationships between interannual variation in Q10, <span class="hlt">soil</span> <span class="hlt">moisture</span>, and precipitation are important to accurately estimate the local carbon cycle, especially under the changing climate.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29432925','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29432925"><span>Applicability of common stomatal conductance models in maize under varying <span class="hlt">soil</span> <span class="hlt">moisture</span> conditions.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Wang, Qiuling; He, Qijin; Zhou, Guangsheng</p> <p>2018-07-01</p> <p>In the context of climate warming, the varying <span class="hlt">soil</span> <span class="hlt">moisture</span> caused by precipitation pattern change will <span class="hlt">affect</span> the applicability of stomatal conductance models, thereby <span class="hlt">affecting</span> the simulation accuracy of carbon-nitrogen-water cycles in ecosystems. We studied the applicability of four common stomatal conductance models including Jarvis, Ball-Woodrow-Berry (BWB), Ball-Berry-Leuning (BBL) and unified stomatal optimization (USO) models based on summer maize leaf gas exchange data from a <span class="hlt">soil</span> <span class="hlt">moisture</span> consecutive decrease manipulation experiment. The results showed that the USO model performed best, followed by the BBL model, BWB model, and the Jarvis model performed worst under varying <span class="hlt">soil</span> <span class="hlt">moisture</span> conditions. The effects of <span class="hlt">soil</span> <span class="hlt">moisture</span> made a difference in the relative performance among the models. By introducing a water response function, the performance of the Jarvis, BWB, and USO models improved, which decreased the normalized root mean square error (NRMSE) by 15.7%, 16.6% and 3.9%, respectively; however, the performance of the BBL model was negative, which increased the NRMSE by 5.3%. It was observed that the models of Jarvis, BWB, BBL and USO were applicable within different ranges of <span class="hlt">soil</span> relative water content (i.e., 55%-65%, 56%-67%, 37%-79% and 37%-95%, respectively) based on the 95% confidence limits. Moreover, introducing a water response function, the applicability of the Jarvis and BWB models improved. The USO model performed best with or without introducing the water response function and was applicable under varying <span class="hlt">soil</span> <span class="hlt">moisture</span> conditions. Our results provide a basis for selecting appropriate stomatal conductance models under drought conditions. Copyright © 2018 Elsevier B.V. All rights reserved.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5981356','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5981356"><span>Design and Test of a <span class="hlt">Soil</span> Profile <span class="hlt">Moisture</span> Sensor Based on Sensitive <span class="hlt">Soil</span> Layers</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Liu, Cheng; Qian, Hongzhou; Cao, Weixing; Ni, Jun</p> <p>2018-01-01</p> <p>To meet the demand of intelligent irrigation for accurate <span class="hlt">moisture</span> sensing in the <span class="hlt">soil</span> vertical profile, a <span class="hlt">soil</span> profile <span class="hlt">moisture</span> sensor was designed based on the principle of high-frequency capacitance. The sensor consists of five groups of sensing probes, a data processor, and some accessory components. Low-resistivity copper rings were used as components of the sensing probes. Composable simulation of the sensor’s sensing probes was carried out using a high-frequency structure simulator. According to the effective radiation range of electric field intensity, width and spacing of copper ring were set to 30 mm and 40 mm, respectively. A parallel resonance circuit of voltage-controlled oscillator and high-frequency inductance-capacitance (LC) was designed for signal frequency division and conditioning. A data processor was used to process <span class="hlt">moisture</span>-related frequency signals for <span class="hlt">soil</span> profile <span class="hlt">moisture</span> sensing. The sensor was able to detect real-time <span class="hlt">soil</span> <span class="hlt">moisture</span> at the depths of 20, 30, and 50 cm and conduct online inversion of <span class="hlt">moisture</span> in the <span class="hlt">soil</span> layer between 0–100 cm. According to the calibration results, the degree of fitting (R2) between the sensor’s measuring frequency and the volumetric <span class="hlt">moisture</span> content of <span class="hlt">soil</span> sample was 0.99 and the relative error of the sensor consistency test was 0–1.17%. Field tests in different loam <span class="hlt">soils</span> showed that measured <span class="hlt">soil</span> <span class="hlt">moisture</span> from our sensor reproduced the observed <span class="hlt">soil</span> <span class="hlt">moisture</span> dynamic well, with an R2 of 0.96 and a root mean square error of 0.04. In a sensor accuracy test, the R2 between the measured value of the proposed sensor and that of the Diviner2000 portable <span class="hlt">soil</span> <span class="hlt">moisture</span> monitoring system was higher than 0.85, with a relative error smaller than 5%. The R2 between measured values and inversed <span class="hlt">soil</span> <span class="hlt">moisture</span> values for other <span class="hlt">soil</span> layers were consistently higher than 0.8. According to calibration test and field test, this sensor, which features low cost, good operability, and high integration, is qualified for</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29883420','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29883420"><span>Design and Test of a <span class="hlt">Soil</span> Profile <span class="hlt">Moisture</span> Sensor Based on Sensitive <span class="hlt">Soil</span> Layers.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Gao, Zhenran; Zhu, Yan; Liu, Cheng; Qian, Hongzhou; Cao, Weixing; Ni, Jun</p> <p>2018-05-21</p> <p>To meet the demand of intelligent irrigation for accurate <span class="hlt">moisture</span> sensing in the <span class="hlt">soil</span> vertical profile, a <span class="hlt">soil</span> profile <span class="hlt">moisture</span> sensor was designed based on the principle of high-frequency capacitance. The sensor consists of five groups of sensing probes, a data processor, and some accessory components. Low-resistivity copper rings were used as components of the sensing probes. Composable simulation of the sensor’s sensing probes was carried out using a high-frequency structure simulator. According to the effective radiation range of electric field intensity, width and spacing of copper ring were set to 30 mm and 40 mm, respectively. A parallel resonance circuit of voltage-controlled oscillator and high-frequency inductance-capacitance (LC) was designed for signal frequency division and conditioning. A data processor was used to process <span class="hlt">moisture</span>-related frequency signals for <span class="hlt">soil</span> profile <span class="hlt">moisture</span> sensing. The sensor was able to detect real-time <span class="hlt">soil</span> <span class="hlt">moisture</span> at the depths of 20, 30, and 50 cm and conduct online inversion of <span class="hlt">moisture</span> in the <span class="hlt">soil</span> layer between 0⁻100 cm. According to the calibration results, the degree of fitting ( R ²) between the sensor’s measuring frequency and the volumetric <span class="hlt">moisture</span> content of <span class="hlt">soil</span> sample was 0.99 and the relative error of the sensor consistency test was 0⁻1.17%. Field tests in different loam <span class="hlt">soils</span> showed that measured <span class="hlt">soil</span> <span class="hlt">moisture</span> from our sensor reproduced the observed <span class="hlt">soil</span> <span class="hlt">moisture</span> dynamic well, with an R ² of 0.96 and a root mean square error of 0.04. In a sensor accuracy test, the R ² between the measured value of the proposed sensor and that of the Diviner2000 portable <span class="hlt">soil</span> <span class="hlt">moisture</span> monitoring system was higher than 0.85, with a relative error smaller than 5%. The R ² between measured values and inversed <span class="hlt">soil</span> <span class="hlt">moisture</span> values for other <span class="hlt">soil</span> layers were consistently higher than 0.8. According to calibration test and field test, this sensor, which features low cost, good operability, and high integration</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009JHyd..368...56T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009JHyd..368...56T"><span>Assessment of multi-frequency electromagnetic induction for determining <span class="hlt">soil</span> <span class="hlt">moisture</span> patterns at the hillslope scale</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Tromp-van Meerveld, H. J.; McDonnell, J. J.</p> <p>2009-04-01</p> <p>SummaryHillslopes are fundamental landscape units, yet represent a difficult scale for measurements as they are well-beyond our traditional point-scale techniques. Here we present an assessment of electromagnetic induction (EM) as a potential rapid and non-invasive method to map <span class="hlt">soil</span> <span class="hlt">moisture</span> patterns at the hillslope scale. We test the new multi-frequency GEM-300 for spatially distributed <span class="hlt">soil</span> <span class="hlt">moisture</span> measurements at the well-instrumented Panola hillslope. EM-based apparent conductivity measurements were linearly related to <span class="hlt">soil</span> <span class="hlt">moisture</span> measured with the Aqua-pro capacitance sensor below a threshold conductivity and represented the temporal patterns in <span class="hlt">soil</span> <span class="hlt">moisture</span> well. During spring rainfall events that wetted only the surface <span class="hlt">soil</span> layers the apparent conductivity measurements explained the <span class="hlt">soil</span> <span class="hlt">moisture</span> dynamics at depth better than the surface <span class="hlt">soil</span> <span class="hlt">moisture</span> dynamics. All four EM frequencies (7.290, 9.090, 11.250, and 14.010 kHz) were highly correlated and linearly related to each other and could be used to predict <span class="hlt">soil</span> <span class="hlt">moisture</span>. This limited our ability to use the four different EM frequencies to obtain a <span class="hlt">soil</span> <span class="hlt">moisture</span> profile with depth. The apparent conductivity patterns represented the observed spatial <span class="hlt">soil</span> <span class="hlt">moisture</span> patterns well when the individually fitted relationships between measured <span class="hlt">soil</span> <span class="hlt">moisture</span> and apparent conductivity were used for each measurement point. However, when the same (master) relationship was used for all measurement locations, the <span class="hlt">soil</span> <span class="hlt">moisture</span> patterns were smoothed and did not resemble the observed <span class="hlt">soil</span> <span class="hlt">moisture</span> patterns very well. In addition the range in calculated <span class="hlt">soil</span> <span class="hlt">moisture</span> values was reduced compared to observed <span class="hlt">soil</span> <span class="hlt">moisture</span>. Part of the smoothing was likely due to the much larger measurement area of the GEM-300 compared to the <span class="hlt">soil</span> <span class="hlt">moisture</span> measurements.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFMGC53A1251T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFMGC53A1251T"><span>Reconstructions of <span class="hlt">Soil</span> <span class="hlt">Moisture</span> for the Upper Colorado River Basin Using Tree-Ring Chronologies</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Tootle, G.; Anderson, S.; Grissino-Mayer, H.</p> <p>2012-12-01</p> <p><span class="hlt">Soil</span> <span class="hlt">moisture</span> is an important factor in the global hydrologic cycle, but existing reconstructions of historic <span class="hlt">soil</span> <span class="hlt">moisture</span> are limited. Tree-ring chronologies (TRCs) were used to reconstruct annual <span class="hlt">soil</span> <span class="hlt">moisture</span> in the Upper Colorado River Basin (UCRB). Gridded <span class="hlt">soil</span> <span class="hlt">moisture</span> data were spatially regionalized using principal components analysis and k-nearest neighbor techniques. <span class="hlt">Moisture</span> sensitive tree-ring chronologies in and adjacent to the UCRB were correlated with regional <span class="hlt">soil</span> <span class="hlt">moisture</span> and tested for temporal stability. TRCs that were positively correlated and stable for the calibration period were retained. Stepwise linear regression was applied to identify the best predictor combinations for each <span class="hlt">soil</span> <span class="hlt">moisture</span> region. The regressions explained 42-78% of the variability in <span class="hlt">soil</span> <span class="hlt">moisture</span> data. We performed reconstructions for individual <span class="hlt">soil</span> <span class="hlt">moisture</span> grid cells to enhance understanding of the disparity in reconstructive skill across the regions. Reconstructions that used chronologies based on ponderosa pines (Pinus ponderosa) and pinyon pines (Pinus edulis) explained increased variance in the datasets. Reconstructed <span class="hlt">soil</span> <span class="hlt">moisture</span> was standardized and compared with standardized reconstructed streamflow and snow water equivalent from the same region. <span class="hlt">Soil</span> <span class="hlt">moisture</span> reconstructions were highly correlated with streamflow and snow water equivalent reconstructions, indicating reconstructions of <span class="hlt">soil</span> <span class="hlt">moisture</span> in the UCRB using TRCs successfully represent hydrologic trends, including the identification of periods of prolonged drought.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20120013141&hterms=kellogg&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dkellogg','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20120013141&hterms=kellogg&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dkellogg"><span>The NASA <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Active Passive (SMAP) Mission Formulation</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Entekhabi, Dara; Njoku, Eni; ONeill, Peggy; Kellogg, Kent; Entin, Jared</p> <p>2011-01-01</p> <p>The <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Active Passive (SMAP) mission is one of the first-tier projects recommended by the U.S. National Research Council Committee on Earth Science and Applications from Space. The SMAP mission is in formulation phase and it is scheduled for launch in 2014. The SMAP mission is designed to produce high-resolution and accurate global mapping of <span class="hlt">soil</span> <span class="hlt">moisture</span> and its freeze/thaw state using an instrument architecture that incorporates an L-band (1.26 GHz) radar and an L-band (1.41 GHz) radiometer. The simultaneous radar and radiometer measurements will be combined to derive global <span class="hlt">soil</span> <span class="hlt">moisture</span> mapping at 9 [km] resolution with a 2 to 3 days revisit and 0.04 [cm3 cm-3] (1 sigma) <span class="hlt">soil</span> water content accuracy. The radar measurements also allow the binary detection of surface freeze/thaw state. The project science goals address in water, energy and carbon cycle science as well as provide improved capabilities in natural hazards applications.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li class="active"><span>20</span></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_20 --> <div id="page_21" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li class="active"><span>21</span></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="401"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AtmEn..88...14B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AtmEn..88...14B"><span>Influence of spatial and temporal variability of subsurface <span class="hlt">soil</span> <span class="hlt">moisture</span> and temperature on vapour intrusion</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bekele, Dawit N.; Naidu, Ravi; Chadalavada, Sreenivasulu</p> <p>2014-05-01</p> <p>A comprehensive field study was conducted at a site contaminated with chlorinated solvents, mainly trichloroethylene (TCE), to investigate the influence of subsurface <span class="hlt">soil</span> <span class="hlt">moisture</span> and temperature on vapour intrusion (VI) into built structures. Existing approaches to predict the risk of VI intrusion into buildings assume homogeneous or discrete layers in the vadose zone through which TCE migrates from an underlying source zone. In reality, the subsurface of the majority of contaminated sites will be subject to significant variations in <span class="hlt">moisture</span> and temperature. Detailed site-specific data were measured contemporaneously to evaluate the impact of spatial and temporal variability of subsurface <span class="hlt">soil</span> properties on VI exposure assessment. The results revealed that indoor air vapour concentrations would be <span class="hlt">affected</span> by spatial and temporal variability of subsurface <span class="hlt">soil</span> <span class="hlt">moisture</span> and temperature. The monthly monitoring of <span class="hlt">soil</span>-gas concentrations over a period of one year at a depth of 3 m across the study site demonstrated significant variation in TCE vapour concentrations, which ranged from 480 to 629,308 μg/m3. <span class="hlt">Soil</span>-gas wells at 1 m depth exhibited high seasonal variability in TCE vapour concentrations with a coefficient of variation 1.02 in comparison with values of 0.88 and 0.74 in 2 m and 3 m wells, respectively. Contour plots of the <span class="hlt">soil</span>-gas TCE plume during wet and dry seasons showed that the plume moved across the site, hence locations of <span class="hlt">soil</span>-gas monitoring wells for human risk assessment is a site specific decision. Subsurface <span class="hlt">soil</span>-gas vapour plume characterisation at the study site demonstrates that assessment for VI is greatly influenced by subsurface <span class="hlt">soil</span> properties such as temperature and <span class="hlt">moisture</span> that fluctuate with the seasons of the year.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.B34B..01T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.B34B..01T"><span>Modeling the hysteretic <span class="hlt">moisture</span> and temperature responses of <span class="hlt">soil</span> carbon decomposition resulting from organo-mineral interactions</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Tang, J.; Riley, W. J.</p> <p>2017-12-01</p> <p>Most existing <span class="hlt">soil</span> carbon cycle models have modeled the <span class="hlt">moisture</span> and temperature dependence of <span class="hlt">soil</span> respiration using deterministic response functions. However, empirical data suggest abundant variability in both of these dependencies. We here use the recently developed SUPECA (Synthesizing Unit and Equilibrium Chemistry Approximation) theory and a published dynamic energy budget based microbial model to investigate how <span class="hlt">soil</span> carbon decomposition responds to changes in <span class="hlt">soil</span> <span class="hlt">moisture</span> and temperature under the influence of organo-mineral interactions. We found that both the temperature and <span class="hlt">moisture</span> responses are hysteretic and cannot be represented by deterministic functions. We then evaluate how the multi-scale variability in temperature and <span class="hlt">moisture</span> forcing <span class="hlt">affect</span> <span class="hlt">soil</span> carbon decomposition. Our results indicate that when the model is run in scenarios mimicking laboratory incubation experiments, the often-observed temperature and <span class="hlt">moisture</span> response functions can be well reproduced. However, when such response functions are used for model extrapolation involving more transient variability in temperature and <span class="hlt">moisture</span> forcing (as found in real ecosystems), the dynamic model that explicitly accounts for hysteresis in temperature and <span class="hlt">moisture</span> dependency produces significantly different estimations of <span class="hlt">soil</span> carbon decomposition, suggesting there are large biases in models that do not resolve such hysteresis. We call for more studies on organo-mineral interactions to improve modeling of such hysteresis.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70034418','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70034418"><span>Response of spectral vegetation indices to <span class="hlt">soil</span> <span class="hlt">moisture</span> in grasslands and shrublands</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Zhang, Li; Ji, Lei; Wylie, Bruce K.</p> <p>2011-01-01</p> <p>The relationships between satellite-derived vegetation indices (VIs) and <span class="hlt">soil</span> <span class="hlt">moisture</span> are complicated because of the time lag of the vegetation response to <span class="hlt">soil</span> <span class="hlt">moisture</span>. In this study, we used a distributed lag regression model to evaluate the lag responses of VIs to <span class="hlt">soil</span> <span class="hlt">moisture</span> for grasslands and shrublands at <span class="hlt">Soil</span> Climate Analysis Network sites in the central and western United States. We examined the relationships between Moderate Resolution Imaging Spectroradiometer (MODIS)-derived VIs and <span class="hlt">soil</span> <span class="hlt">moisture</span> measurements. The Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) showed significant lag responses to <span class="hlt">soil</span> <span class="hlt">moisture</span>. The lag length varies from 8 to 56 days for NDVI and from 16 to 56 days for NDWI. However, the lag response of NDVI and NDWI to <span class="hlt">soil</span> <span class="hlt">moisture</span> varied among the sites. Our study suggests that the lag effect needs to be taken into consideration when the VIs are used to estimate <span class="hlt">soil</span> <span class="hlt">moisture</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H51E1317N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H51E1317N"><span>Enhanced <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Initialization Using Blended <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Product and Regional Optimization of LSM-RTM Coupled Land Data Assimilation System.</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Nair, A. S.; Indu, J.</p> <p>2017-12-01</p> <p>Prediction of <span class="hlt">soil</span> <span class="hlt">moisture</span> dynamics is high priority research challenge because of the complex land-atmosphere interaction processes. <span class="hlt">Soil</span> <span class="hlt">moisture</span> (SM) plays a decisive role in governing water and energy balance of the terrestrial system. An accurate SM estimate is imperative for hydrological and weather prediction models. Though SM estimates are available from microwave remote sensing and land surface model (LSM) simulations, it is <span class="hlt">affected</span> by uncertainties from several sources during estimation. Past studies have generally focused on land data assimilation (DA) for improving LSM predictions by assimilating <span class="hlt">soil</span> <span class="hlt">moisture</span> from single satellite sensor. This approach is limited by the large time gap between two consequent <span class="hlt">soil</span> <span class="hlt">moisture</span> observations due to satellite repeat cycle of more than three days at the equator. To overcome this, in the present study, we have performed DA using ensemble products from the <span class="hlt">soil</span> <span class="hlt">moisture</span> operational product system (SMOPS) blended <span class="hlt">soil</span> <span class="hlt">moisture</span> retrievals from different satellite sensors into Noah LSM. Before the assimilation period, the Noah LSM is initialized by cycling through seven multiple loops from 2008 to 2010 forcing with Global data assimilation system (GDAS) data over the Indian subcontinent. We assimilated SMOPS into Noah LSM for a period of two years from 2010 to 2011 using Ensemble Kalman Filter within NASA's land information system (LIS) framework. Results show that DA has improved Noah LSM prediction with a high correlation of 0.96 and low root mean square difference of 0.0303 m3/m3 (figure 1a). Further, this study has also investigated the notion of assimilating microwave brightness temperature (Tb) as a proxy for SM estimates owing to the close proximity of Tb and SM. Preliminary sensitivity analysis show a strong need for regional parameterization of radiative transfer models (RTMs) to improve Tb simulation. Towards this goal, we have optimized the forward RTM using swarm optimization technique for direct Tb</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20000038130&hterms=soil+maps&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dsoil%2Bmaps','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20000038130&hterms=soil+maps&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dsoil%2Bmaps"><span>Application of Multitemporal Remotely Sensed <span class="hlt">Soil</span> <span class="hlt">Moisture</span> for the Estimation of <span class="hlt">Soil</span> Physical Properties</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Mattikalli, N. M.; Engman, E. T.; Jackson, T. J.; Ahuja, L. R.</p> <p>1997-01-01</p> <p>This paper demonstrates the use of multitemporal <span class="hlt">soil</span> <span class="hlt">moisture</span> derived from microwave remote sensing to estimate <span class="hlt">soil</span> physical properties. The passive microwave ESTAR instrument was employed during June 10-18, 1992, to obtain brightness temperature (TB) and surface <span class="hlt">soil</span> <span class="hlt">moisture</span> data in the Little Washita watershed, Oklahoma. Analyses of spatial and temporal variations of TB and <span class="hlt">soil</span> <span class="hlt">moisture</span> during the dry-down period revealed a direct relationship between changes in T and <span class="hlt">soil</span> <span class="hlt">moisture</span> and <span class="hlt">soil</span> physical (viz. texture) and hydraulic (viz. saturated hydraulic conductivity, K(sat)) properties. Statistically significant regression relationships were developed for the ratio of percent sand to percent clay (RSC) and K(sat), in terms of change components of TB and surface <span class="hlt">soil</span> <span class="hlt">moisture</span>. Validation of results using field measured values and <span class="hlt">soil</span> texture map indicated that both RSC and K(sat) can be estimated with reasonable accuracy. These findings have potential applications of microwave remote sensing to obtain quick estimates of the spatial distributions of K(sat), over large areas for input parameterization of hydrologic models.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.3702C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.3702C"><span>Spatial and temporal variability of throughfall and <span class="hlt">soil</span> <span class="hlt">moisture</span> in a deciduous forest in the low mountain ranges (Hesse, Germany)</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Chifflard, Peter; Weishaupt, Philipp; Reiss, Martin</p> <p>2017-04-01</p> <p>Spatial and temporal patterns of throughfall can <span class="hlt">affect</span> the heterogeneity of ecological, biogeochemical and hydrological processes at a forest floor and further the underlying <span class="hlt">soil</span>. Previous research suggests different factors controlling the spatial and temporal patterns of throughfall, but most studies focus on coniferous forest, where the vegetation coverage is more or less constant over time. In deciduous forests the leaf area index varies due to the leaf fall in autumn which implicates a specific spatial and temporal variability of throughfall and furthermore of the <span class="hlt">soil</span> <span class="hlt">moisture</span>. Therefore, in the present study, the measurements of throughfall and <span class="hlt">soil</span> <span class="hlt">moisture</span> in a deciduous forest in the low mountain ranges focused especially on the period of leaf fall. The aims of this study were: 1) to detect the spatial and temporal variability of both the throughfall and the <span class="hlt">soil</span> <span class="hlt">moisture</span>, 2) to examine the temporal stability of the spatial patterns of the throughfall and <span class="hlt">soil</span> <span class="hlt">moisture</span> and 3) relate the <span class="hlt">soil</span> <span class="hlt">moisture</span> patterns to the throughfall patterns and further to the canopy characteristics. The study was carried out in a small catchment on middle Hesse (Germany) which is covered by beech forest. Annual mean air temperature is 9.4°C (48.9˚F) and annual mean precipitation is 650 mm. Base materials for <span class="hlt">soil</span> genesis is greywacke and clay shale from Devonian deposits. The <span class="hlt">soil</span> type at the study plot is a shallow cambisol. The study plot covers an area of about 150 m2 where 77 throughfall samplers where installed. The throughfall and the <span class="hlt">soil</span> <span class="hlt">moisture</span> (FDR-method, 20 cm depth) was measured immediately after every rainfall event at the 77 measurement points. During the period of October to December 2015 altogether 7 events were investigated. The geostatistical method kriging was used to interpolate between the measurements points to visualize the spatial patterns of each investigated parameter. Time-stability-plots were applied to examine temporal scatters of each</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=1086955','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=1086955"><span>Internal Water Balance of Barley Under <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Stress 1</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Millar, Agustin A.; Duysen, Murray E.; Wilkinson, Guy E.</p> <p>1968-01-01</p> <p>Leaf water potential, leaf relative water content, and relative transpiration of barley were determined daily under greenhouse conditions at 3 growth stages: tillering to boot, boot to heading, and heading to maturity. The leaf <span class="hlt">moisture</span> characteristic curve (relative water content versus leaf water potential) was the same for leaves of the same age growing in the same environment for the first 2 stages of growth, but shifted at the heading to maturity stage to higher leaf relative water content for a given leaf water potential. Growth chamber experiments showed that the leaf <span class="hlt">moisture</span> characteristic curve was not the same for plants growing in different environments. Relative transpiration data indicated that barley stomates closed at a water potential of about −22 bars at the 3 stages studied. The water potential was measured for all the leaves on barley to determine the variation of water potential with leaf position. Leaf water potential increased basipetally with plant leaf position. In <span class="hlt">soil</span> with a <span class="hlt">moisture</span> content near field capacity a difference of about 16.5 bars was observed between the top and bottom leaves on the same plant, while in <span class="hlt">soil</span> with a <span class="hlt">moisture</span> content near the permanent wilting point the difference was only 5.6 bars between the same leaf positions. PMID:16656869</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/18808006','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/18808006"><span>[Response processes of Aralia elata photosynthesis and transpiration to light and <span class="hlt">soil</span> <span class="hlt">moisture</span>].</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Chen, Jian; Zhang, Guang-Can; Zhang, Shu-Yong; Wang, Meng-Jun</p> <p>2008-06-01</p> <p>By using CIRAS-2 portable photosynthesis system, the light response processes of Aralia elata photosynthesis and transpiration under different <span class="hlt">soil</span> <span class="hlt">moisture</span> conditions were studied, aimed to understand the adaptability of A. elata to different light and <span class="hlt">soil</span> <span class="hlt">moisture</span> conditions. The results showed that the response processes of A. elata net photosynthetic rate (Pn), transpiration rate (Tr), and water use efficiency (WUE) to photon flux density (PFD) were different. With the increasing PFD in the range of 800-1800 micromol x m2(-2) x s(-1), Pn changed less, Tr decreased gradually, while WUE increased obviously. The light saturation point (LSP) and light compensation point (LCP) were about 800 and 30 micromol m(-2) x s(-1), respectively, and less <span class="hlt">affected</span> by <span class="hlt">soil</span> water content; while the apparent photosynthetic quantum yield (Phi) and dark respiratory rate (Rd) were more <span class="hlt">affected</span> by the <span class="hlt">moisture</span> content. The Pn and WUE had evident threshold responses to the variations of <span class="hlt">soil</span> water content. When the <span class="hlt">soil</span> relative water content (RWC) was in the range of 44%-79%, A. elata could have higher levels of Pn and WUE.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20160009650&hterms=soil+environment&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dsoil%2Benvironment','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20160009650&hterms=soil+environment&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dsoil%2Benvironment"><span>Spacecraft Environmental Testing SMAP (<span class="hlt">Soil</span>, <span class="hlt">Moisture</span>, Active, Passive)</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Fields, Keith</p> <p>2014-01-01</p> <p>Testing a complete full up spacecraft to verify it will survive the environment, in which it will be exposed to during its mission, is a formidable task in itself. However, the ''test like you fly'' philosophy sometimes gets compromised because of cost, design and or time. This paper describes the thermal-vacuum and mass properties testing of the <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Active Passive (SMAP) earth orbiting satellite. SMAP will provide global observations of <span class="hlt">soil</span> <span class="hlt">moisture</span> and freeze/thaw state (the hydrosphere state). SMAP hydrosphere state measurements will be used to enhance understanding of processes that link the water, energy, and carbon cycles, and to extend the capabilities of weather and climate prediction models. It will explain the problems encountered, and the solutions developed, which minimized the risk typically associated with such an arduous process. Also discussed, the future of testing on expensive long lead-time spacecraft. Will we ever reach the ''build and shoot" scenario with minimal or no verification testing?</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2005AdAtS..22..337L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2005AdAtS..22..337L"><span>A nonlinear coupled <span class="hlt">soil</span> <span class="hlt">moisture</span>-vegetation model</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Liu, Shikuo; Liu, Shida; Fu, Zuntao; Sun, Lan</p> <p>2005-06-01</p> <p>Based on the physical analysis that the <span class="hlt">soil</span> <span class="hlt">moisture</span> and vegetation depend mainly on the precipitation and evaporation as well as the growth, decay and consumption of vegetation a nonlinear dynamic coupled system of <span class="hlt">soil</span> <span class="hlt">moisture</span>-vegetation is established. Using this model, the stabilities of the steady states of vegetation are analyzed. This paper focuses on the research of the vegetation catastrophe point which represents the transition between aridness and wetness to a great extent. It is shown that the catastrophe point of steady states of vegetation depends mainly on the rainfall P and saturation value v0, which is selected to balance the growth and decay of vegetation. In addition, when the consumption of vegetation remains constant, the analytic solution of the vegetation equation is obtained.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19930036633&hterms=manhattan+project&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dmanhattan%2Bproject','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19930036633&hterms=manhattan+project&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dmanhattan%2Bproject"><span>Active and passive microwave measurements of <span class="hlt">soil</span> <span class="hlt">moisture</span> in FIFE</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wang, J. R.; Gogineni, S. P.; Ampe, J.</p> <p>1992-01-01</p> <p>During the intensive field campaigns of the First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE) in May-October of 1987, several nearly simultaneous measurements were made with low-altitude flights of the L-band radiometer and C- and X-band scatterometers over two transects in the Konza Prairie Natural Research Area, some 8 km south of Manhattan, Kansas. These measurements showed that although the scatterometers were sensitive to <span class="hlt">soil</span> <span class="hlt">moisture</span> variations in most regions under the flight path, the L-band radiometer lost most of its sensitivity in regions unburned for many years. The correlation coefficient derived from the regression between the radar backscattering coefficient and the <span class="hlt">soil</span> <span class="hlt">moisture</span> was found to improve with the increase in antenna incidence angle. This is attributed to a steeper falloff of the backscattering coefficient as a function of local incidence at angles near nadir than at angles greater than 30 deg.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20020072723&hterms=erickson&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Derickson','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20020072723&hterms=erickson&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Derickson"><span><span class="hlt">Soil</span> <span class="hlt">Moisture</span> and Snow Cover: Active or Passive Elements of Climate</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Oglesby, Robert J.; Marshall, Susan; Erickson, David J., III; Robertson, Franklin R.; Roads, John O.; Arnold, James E. (Technical Monitor)</p> <p>2002-01-01</p> <p>A key question is the extent to which surface effects such as <span class="hlt">soil</span> <span class="hlt">moisture</span> and snow cover are simply passive elements or whether they can <span class="hlt">affect</span> the evolution of climate on seasonal and longer time scales. We have constructed ensembles of predictability studies using the NCAR CCM3 in which we compared the relative roles of initial surface and atmospheric conditions over the central and western U.S. in determining the subsequent evolution of <span class="hlt">soil</span> <span class="hlt">moisture</span> and of snow cover. Results from simulations with realistic <span class="hlt">soil</span> <span class="hlt">moisture</span> anomalies indicate that internal climate variability may be the strongest factor, with some indication that the initial atmospheric state is also important. Model runs with exaggerated <span class="hlt">soil</span> <span class="hlt">moisture</span> reductions (near-desert conditions) showed a much larger effect, with warmer surface temperatures, reduced precipitation, and lower surface pressures; the latter indicating a response of the atmospheric circulation. These results suggest the possibility of a threshold effect in <span class="hlt">soil</span> <span class="hlt">moisture</span>, whereby an anomaly must be of a sufficient size before it can have a significant impact on the atmospheric circulation and climate. Results from simulations with realistic snow cover anomalies indicate that the time of year can be crucial. When introduced in late winter, these anomalies strongly <span class="hlt">affected</span> the subsequent evolution of snow cover. When introduced in early winter, however, little or no effect is seen on the subsequent snow cover. Runs with greatly exaggerated initial snow cover indicate that the high reflectivity of snow is the most important process by which snow cover can impact climate, through lower surface temperatures and increased surface pressures. The results to date were obtained for model runs with present-day conditions. We are currently analyzing runs made with projected forcings for the 21st century to see if these results are modified in any way under likely scenarios of future climate change. An intriguing new statistical technique</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.H12B..08C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.H12B..08C"><span>Generating a global <span class="hlt">soil</span> evaporation dataset using SMAP <span class="hlt">soil</span> <span class="hlt">moisture</span> data to estimate components of the surface water balance</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Carbone, E.; Small, E. E.; Badger, A.; Livneh, B.</p> <p>2016-12-01</p> <p>Evapotranspiration (ET) is fundamental to the water, energy and carbon cycles. However, our ability to measure ET and partition the total flux into transpiration and evaporation from <span class="hlt">soil</span> is limited. This project aims to generate a global, observationally-based <span class="hlt">soil</span> evaporation dataset (E-SMAP): using SMAP surface <span class="hlt">soil</span> <span class="hlt">moisture</span> data in conjunction with models and auxiliary observations to observe or estimate each component of the surface water balance. E-SMAP will enable a better understanding of water balance processes and contribute to forecasts of water resource availability. Here we focus on the flux between the <span class="hlt">soil</span> surface and root zone layers (qbot), which dictates the proportion of water that is available for <span class="hlt">soil</span> evaporation. Any water that moves from the surface layer to the root zone contributes to transpiration or groundwater recharge. The magnitude and direction of qbot are driven by gravity and the gradient in matric potential. We use a highly discretized Richards Equation-type model (e.g. Hydrus 1D software) with meteorological forcing from the North American Land Data Assimilation System (NLDAS) to estimate qbot. We verify the simulations using SMAP L4 surface and root zone <span class="hlt">soil</span> <span class="hlt">moisture</span> data. These data are well suited for evaluating qbot because they represent the most advanced estimate of the surface to root zone <span class="hlt">soil</span> <span class="hlt">moisture</span> gradient at the global scale. Results are compared with similar calculations using NLDAS and in situ <span class="hlt">soil</span> <span class="hlt">moisture</span> data. Preliminary calculations show that the greatest amount of variability between qbot determined from NLDAS, in situ and SMAP occurs directly after precipitation events. At these times, uncertainties in qbot calculations significantly <span class="hlt">affect</span> E-SMAP estimates.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25576276','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25576276"><span>Screening variability and change of <span class="hlt">soil</span> <span class="hlt">moisture</span> under wide-ranging climate conditions: Snow dynamics effects.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Verrot, Lucile; Destouni, Georgia</p> <p>2015-01-01</p> <p><span class="hlt">Soil</span> <span class="hlt">moisture</span> influences and is influenced by water, climate, and ecosystem conditions, <span class="hlt">affecting</span> associated ecosystem services in the landscape. This paper couples snow storage-melting dynamics with an analytical modeling approach to screening basin-scale, long-term <span class="hlt">soil</span> <span class="hlt">moisture</span> variability and change in a changing climate. This coupling enables assessment of both spatial differences and temporal changes across a wide range of hydro-climatic conditions. Model application is exemplified for two major Swedish hydrological basins, Norrström and Piteälven. These are located along a steep temperature gradient and have experienced different hydro-climatic changes over the time period of study, 1950-2009. Spatially, average intra-annual variability of <span class="hlt">soil</span> <span class="hlt">moisture</span> differs considerably between the basins due to their temperature-related differences in snow dynamics. With regard to temporal change, the long-term average state and intra-annual variability of <span class="hlt">soil</span> <span class="hlt">moisture</span> have not changed much, while inter-annual variability has changed considerably in response to hydro-climatic changes experienced so far in each basin.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20000013621&hterms=curvature&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dcurvature','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20000013621&hterms=curvature&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dcurvature"><span><span class="hlt">Soil</span> <span class="hlt">Moisture</span>, Coastline Curvature, and Sea Breeze Initiated Precipitation Over Florida</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Baker, R. David; Lynn, Barry H.; Boone, Aaron; Tao, Wei-Kuo</p> <p>1999-01-01</p> <p>Land surface-atmosphere interaction plays a key role in the development of summertime convection and precipitation over the Florida peninsula. Land-ocean temperature contrasts induce sea-breeze circulations along both coasts. Clouds develop along sea-breeze fronts, and significant precipitation can occur during the summer months. However, other factors such as <span class="hlt">soil</span> <span class="hlt">moisture</span> distribution and coastline curvature may modulate the timing, location, and intensity of sea breeze initiated precipitation. Here, we investigate the role of <span class="hlt">soil</span> <span class="hlt">moisture</span> and coastline curvature on Florida precipitation using the 3-D Goddard Cumulus Ensemble (GCE) cloud model coupled with the Parameterization for Land-Atmosphere-Cloud Exchange (PLACE) land surface model. This study utilizes data from the Convection and Precipitation Electrification Experiment (CaPE) collected on 27 July 1991. Our numerical simulations suggest that a realistic distribution of <span class="hlt">soil</span> <span class="hlt">moisture</span> influences the location and intensity of precipitation but not the timing of precipitation. In contrast, coastline curvature <span class="hlt">affects</span> the timing and location of precipitation but has little influence on peak rainfall rates. However, both factors (<span class="hlt">soil</span> <span class="hlt">moisture</span> and coastline curvature) are required to fully account for observed rainfall amounts.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.2015H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.2015H"><span>Simultaneous Assimilation of AMSR-E Brightness Temperature and MODIS LST to Improve <span class="hlt">Soil</span> <span class="hlt">Moisture</span> with Dual Ensemble Kalman Smoother</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Huang, Chunlin; Chen, Weijin; Wang, Weizhen; Gu, Juan</p> <p>2017-04-01</p> <p>Uncertainties in model parameters can easily cause systematic differences between model states and observations from ground or satellites, which significantly <span class="hlt">affect</span> the accuracy of <span class="hlt">soil</span> <span class="hlt">moisture</span> estimation in data assimilation systems. In this paper, a novel <span class="hlt">soil</span> <span class="hlt">moisture</span> assimilation scheme is developed to simultaneously assimilate AMSR-E brightness temperature (TB) and MODIS Land Surface Temperature (LST), which can correct model bias by simultaneously updating model states and parameters with dual ensemble Kalman filter (DEnKS). The Common Land Model (CoLM) and a Q-h Radiative Transfer Model (RTM) are adopted as model operator and observation operator, respectively. The assimilation experiment is conducted in Naqu, Tibet Plateau, from May 31 to September 27, 2011. Compared with in-situ measurements, the accuracy of <span class="hlt">soil</span> <span class="hlt">moisture</span> estimation is tremendously improved in terms of a variety of scales. The updated <span class="hlt">soil</span> temperature by assimilating MODIS LST as input of RTM can reduce the differences between the simulated and observed brightness temperatures to a certain degree, which helps to improve the estimation of <span class="hlt">soil</span> <span class="hlt">moisture</span> and model parameters. The updated parameters show large discrepancy with the default ones and the former effectively reduces the states bias of CoLM. Results demonstrate the potential of assimilating both microwave TB and MODIS LST to improve the estimation of <span class="hlt">soil</span> <span class="hlt">moisture</span> and related parameters. Furthermore, this study also indicates that the developed scheme is an effective <span class="hlt">soil</span> <span class="hlt">moisture</span> downscaling approach for coarse-scale microwave TB.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19720021738','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19720021738"><span><span class="hlt">Soil</span> <span class="hlt">moisture</span> mapping by ground and airborne microwave radiometry</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Poe, G.; Edgerton, A. T.</p> <p>1972-01-01</p> <p>Extensive ground-based and airborne investigations were undertaken in conjunction with laboratory dielectric measurements of <span class="hlt">soils</span> and analytical modeling. Radiometric measurements were made in the vicinity of Phoenix, Arizona at observational wavelengths ranging from 0.81 to 21 cm. Ground experiments were conducted with a microwave field laboratory and airborne measurements were obtained from a CV-990 aircraft. Research activities were focused on establishing basic relationships between microwave emission and the distribution of <span class="hlt">moisture</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20020050922&hterms=erickson&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Derickson','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20020050922&hterms=erickson&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Derickson"><span><span class="hlt">Soil</span> <span class="hlt">Moisture</span> and Snow Cover: Active or Passive Elements of Climate?</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Oglesby, Robert J.; Marshall, Susan; Erickson, David J., III; Robertson, Franklin R.; Roads, John O.; Arnold, James E. (Technical Monitor)</p> <p>2002-01-01</p> <p>A key question in the study of the hydrologic cycle is the extent to which surface effects such as <span class="hlt">soil</span> <span class="hlt">moisture</span> and snow cover are simply passive elements or whether they can <span class="hlt">affect</span> the evolution of climate on seasonal and longer time scales. We have constructed ensembles of predictability studies using the NCAR CCM3 in which we compared the relative roles of initial surface and atmospheric conditions over the central and western U.S. in determining the subsequent evolution of <span class="hlt">soil</span> <span class="hlt">moisture</span> and of snow cover. We have also made sensitivity studies with exaggerated <span class="hlt">soil</span> <span class="hlt">moisture</span> and snow cover anomalies in order to determine the physical processes that may be important. Results from simulations with realistic <span class="hlt">soil</span> <span class="hlt">moisture</span> anomalies indicate that internal climate variability may be the strongest factor, with some indication that the initial atmospheric state is also important. The initial state of <span class="hlt">soil</span> <span class="hlt">moisture</span> does not appear important, a result that held whether simulations were started in late winter or late spring. Model runs with exaggerated <span class="hlt">soil</span> <span class="hlt">moisture</span> reductions (near-desert conditions) showed a much larger effect, with warmer surface temperatures, reduced precipitation, and lower surface pressures; the latter indicating a response of the atmospheric circulation. These results suggest the possibility of a threshold effect in <span class="hlt">soil</span> <span class="hlt">moisture</span>, whereby an anomaly must be of a sufficient size before it can have a significant impact on the atmospheric circulation and hence climate. Results from simulations with realistic snow cover anomalies indicate that the time of year can be crucial. When introduced in late winter, these anomalies strongly <span class="hlt">affected</span> the subsequent evolution of snow cover. When introduced in early winter, however, little or no effect is seen on the subsequent snow cover. Runs with greatly exaggerated initial snow cover indicate that the high reflectively of snow is the most important process by which snow cover cart impact climate, through lower</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20020022301&hterms=climate+change+deserts&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dclimate%2Bchange%2Bdeserts','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20020022301&hterms=climate+change+deserts&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dclimate%2Bchange%2Bdeserts"><span><span class="hlt">Soil</span> <span class="hlt">Moisture</span> and Snow Cover: Active or Passive Elements of Climate?</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Oglesby, Robert J.; Marshall, Susan; Robertson, Franklin R.; Roads, John O.; Arnold, James E. (Technical Monitor)</p> <p>2001-01-01</p> <p>A key question in the study of the hydrologic cycle is the extent to which surface effects such as <span class="hlt">soil</span> <span class="hlt">moisture</span> and snow cover are simply passive elements or whether they can <span class="hlt">affect</span> the evolution of climate on seasonal and longer time scales. We have constructed ensembles of predictability studies using the NCAR CCM3 in which we compared the relative roles of initial surface and atmospheric conditions over the central and western U.S. GAPP region in determining the subsequent evolution of <span class="hlt">soil</span> <span class="hlt">moisture</span> and of snow cover. We have also made sensitivity studies with exaggerated <span class="hlt">soil</span> <span class="hlt">moisture</span> and snow cover anomalies in order to determine the physical processes that may be important. Results from simulations with realistic <span class="hlt">soil</span> <span class="hlt">moisture</span> anomalies indicate that internal climate variability may be the strongest factor, with some indication that the initial atmospheric state is also important. The initial state of <span class="hlt">soil</span> <span class="hlt">moisture</span> does not appear important, a result that held whether simulations were started in late winter or late spring. Model runs with exaggerated <span class="hlt">soil</span> <span class="hlt">moisture</span> reductions (near-desert conditions) showed a much larger effect, with warmer surface temperatures, reduced precipitation, and lower surface pressures; the latter indicating a response of the atmospheric circulation. These results suggest the possibility of a threshold effect in <span class="hlt">soil</span> <span class="hlt">moisture</span>, whereby an anomaly must be of a sufficient size before it can have a significant impact on the atmospheric circulation and hence climate. Results from simulations with realistic snow cover anomalies indicate that the time of year can be crucial. When introduced in late winter, these anomalies strongly <span class="hlt">affected</span> the subsequent evolution of snow cover. When introduced in early winter, however, little or no effect is seen on the subsequent snow cover. Runs with greatly exaggerated initial snow cover indicate that the high reflectivity of snow is the most important process by which snow cover can impact climate</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012EGUGA..1412724Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012EGUGA..1412724Z"><span>Impact of SMOS <span class="hlt">soil</span> <span class="hlt">moisture</span> data assimilation on NCEP-GFS forecasts</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhan, X.; Zheng, W.; Meng, J.; Dong, J.; Ek, M.</p> <p>2012-04-01</p> <p><span class="hlt">Soil</span> <span class="hlt">moisture</span> is one of the few critical land surface state variables that have long memory to impact the exchanges of water, energy and carbon between the land surface and atmosphere. Accurate information about <span class="hlt">soil</span> <span class="hlt">moisture</span> status is thus required for numerical weather, seasonal climate and hydrological forecast as well as for agricultural production forecasts, water management and many other water related economic or social activities. Since the successful launch of ESA's <span class="hlt">soil</span> <span class="hlt">moisture</span> ocean salinity (SMOS) mission in November 2009, about 2 years of <span class="hlt">soil</span> <span class="hlt">moisture</span> retrievals has been collected. SMOS is believed to be the currently best satellite sensors for <span class="hlt">soil</span> <span class="hlt">moisture</span> remote sensing. Therefore, it becomes interesting to examine how the collected SMOS <span class="hlt">soil</span> <span class="hlt">moisture</span> data are compared with other satellite-sensed <span class="hlt">soil</span> <span class="hlt">moisture</span> retrievals (such as NASA's Advanced Microwave Scanning Radiometer -AMSR-E and EUMETSAT's Advanced Scatterometer - ASCAT)), in situ <span class="hlt">soil</span> <span class="hlt">moisture</span> measurements, and how these data sets impact numerical weather prediction models such as the Global Forecast System of NOAA-NCEP. This study implements the Ensemble Kalman filter in GFS to assimilate the AMSR-E, ASCAT and SMOS <span class="hlt">soil</span> <span class="hlt">moisture</span> observations after a quantitative assessment of their error rate based on in situ measurements from ground networks around contiguous United States. in situ <span class="hlt">soil</span> <span class="hlt">moisture</span> measurements from ground networks (such as USDA <span class="hlt">Soil</span> Climate Analysis network - SCAN and NOAA's U.S. Climate Reference Network -USCRN) are used to evaluate the GFS <span class="hlt">soil</span> <span class="hlt">moisture</span> simulations (analysis). The benefits and uncertainties of assimilating the satellite data products in GFS are examined by comparing the GFS forecasts of surface temperature and rainfall with and without the assimilations. From these examinations, the advantages of SMOS <span class="hlt">soil</span> <span class="hlt">moisture</span> data products over other satellite <span class="hlt">soil</span> <span class="hlt">moisture</span> data sets will be evaluated. The next step toward operationally assimilating <span class="hlt">soil</span> <span class="hlt">moisture</span></p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li class="active"><span>21</span></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_21 --> <div id="page_22" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li class="active"><span>22</span></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="421"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.B13D1794D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.B13D1794D"><span>Using Remotely Sensed <span class="hlt">Soil</span> <span class="hlt">Moisture</span> to Estimate Fire Risk in Tropical Peatlands</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Dadap, N.; Cobb, A.; Hoyt, A.; Harvey, C. F.; Konings, A. G.</p> <p>2017-12-01</p> <p>Tropical peatlands in Equatorial Asia have become more vulnerable to fire due to deforestation and peatland drainage over the last 30 years. In these regions, water table depth has been shown to play an important role in mediating fire risk as it serves as a proxy for peat <span class="hlt">moisture</span> content. However, water table depth observations are sparse and expensive. <span class="hlt">Soil</span> <span class="hlt">moisture</span> could provide a more direct indicator of fire risk than water table depth. In this study, we use new <span class="hlt">soil</span> <span class="hlt">moisture</span> retrievals from the <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Active Passive (SMAP) satellite to demonstrate that - contrary to popular wisdom - remotely sensed <span class="hlt">soil</span> <span class="hlt">moisture</span> observations are possible over most Southeast Asian peatlands. <span class="hlt">Soil</span> <span class="hlt">moisture</span> estimation in this region was previously thought to be impossible over tropical peatlands because of dense vegetation cover. We show that vegetation density is sufficiently low across most Equatorial Asian peatlands to allow <span class="hlt">soil</span> <span class="hlt">moisture</span> estimation, and hypothesize that deforestation and other anthropogenic changes in land cover have combined to reduce overall vegetation density sufficient to allow <span class="hlt">soil</span> <span class="hlt">moisture</span> estimation. We further combine burned area estimates from the Global Fire Emissions Database and SMAP <span class="hlt">soil</span> <span class="hlt">moisture</span> retrievals to show that <span class="hlt">soil</span> <span class="hlt">moisture</span> provides a strong signal for fire risk in peatlands, with fires occurring at a much greater rate over drier <span class="hlt">soils</span>. We will also develop an explicit fire risk model incorporating <span class="hlt">soil</span> <span class="hlt">moisture</span> with additional climatic, land cover, and anthropogenic predictor variables.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..17.1780M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..17.1780M"><span>Assimilating satellite <span class="hlt">soil</span> <span class="hlt">moisture</span> into rainfall-runoff modelling: towards a systematic study</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Massari, Christian; Tarpanelli, Angelica; Brocca, Luca; Moramarco, Tommaso</p> <p>2015-04-01</p> <p><span class="hlt">Soil</span> <span class="hlt">moisture</span> is the main factor for the repartition of the mass and energy fluxes between the land surface and the atmosphere thus playing a fundamental role in the hydrological cycle. Indeed, <span class="hlt">soil</span> <span class="hlt">moisture</span> represents the initial condition of rainfall-runoff modelling that determines the flood response of a catchment. Different initial <span class="hlt">soil</span> <span class="hlt">moisture</span> conditions can discriminate between catastrophic and minor effects of a given rainfall event. Therefore, improving the estimation of initial <span class="hlt">soil</span> <span class="hlt">moisture</span> conditions will reduce uncertainties in early warning flood forecasting models addressing the mitigation of flood hazard. In recent years, satellite <span class="hlt">soil</span> <span class="hlt">moisture</span> products have become available with fine spatial-temporal resolution and a good accuracy. Therefore, a number of studies have been published in which the impact of the assimilation of satellite <span class="hlt">soil</span> <span class="hlt">moisture</span> data into rainfall-runoff modelling is investigated. Unfortunately, data assimilation involves a series of assumptions and choices that significantly <span class="hlt">affect</span> the final result. Given a satellite <span class="hlt">soil</span> <span class="hlt">moisture</span> observation, a rainfall-runoff model and a data assimilation technique, an improvement or a deterioration of discharge predictions can be obtained depending on the choices made in the data assimilation procedure. Consequently, large discrepancies have been obtained in the studies published so far likely due to the differences in the implementation of the data assimilation technique. On this basis, a comprehensive and robust procedure for the assimilation of satellite <span class="hlt">soil</span> <span class="hlt">moisture</span> data into rainfall-runoff modelling is developed here and applied to six subcatchment of the Upper Tiber River Basin for which high-quality hydrometeorological hourly observations are available in the period 1989-2013. The satellite <span class="hlt">soil</span> <span class="hlt">moisture</span> product used in this study is obtained from the Advanced SCATterometer (ASCAT) onboard Metop-A satellite and it is available since 2007. The MISDc ("Modello Idrologico Semi</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20170007423','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20170007423"><span>NASA <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Active Passive Mission Status and Science Highlights</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Yueh, Simon; Entekhabi, Dara; O'Neill, Peggy; Entin, Jared</p> <p>2017-01-01</p> <p>The <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Active Passive (SMAP) observatory was launched January 31, 2015, and its L-band radiometer and radar instruments became operational during April 2015. This paper provides a summary of the quality assessment of its baseline <span class="hlt">soil</span> <span class="hlt">moisture</span> and freeze/thaw products as well as an overview of new products. The first new product explores the Backus Gilbert optimum interpolation based on the oversampling characteristics of the SMAP radiometer. The second one investigates the disaggregation of the SMAP radiometer data using the European Space Agency's Sentinel-1 C-band synthetic aperture radar (SAR) data to obtain <span class="hlt">soil</span> <span class="hlt">moisture</span> products at about 1 to 3 km resolution. In addition, SMAPs L-band data have been found useful for many scientific applications, including depictions of water cycles, vegetation opacity, ocean surface salinity and hurricane ocean surface wind mapping. Highlights of these new applications will be provided.The SMAP <span class="hlt">soil</span> <span class="hlt">moisture</span>, freeze/taw state and SSSprovide a synergistic view of water cycle. For example, Fig.7 illustrates the transition of freeze/thaw state, change of soilmoisture near the pole and SSS in the Arctic Ocean fromApril to October in 2015 and 2016. In April, most parts ofAlaska, Canada, and Siberia remained frozen. Melt onsetstarted in May. Alaska, Canada, and a big part of Siberia havebecome thawed at the end of May; some freshwater dischargecould be found near the mouth of Mackenzie in 2016, but notin 2015. The <span class="hlt">soil</span> <span class="hlt">moisture</span> appeared to be higher in the Oband Yenisei river basins in Siberia in 2015. As a result,freshwater discharge was more widespread in the Kara Seanear the mouths of both rivers in June 2015 than in 2016. TheNorth America and Siberia have become completely thawedin July. After June, the freshwater discharge from other riversinto the Arctic, indicated by blue, also became visible. Thefreeze-up started in September and the high latitude regionsin North America and Eurasia became frozen. Comparing</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19820017729','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19820017729"><span>Orbiting passive microwave sensor simulation applied to <span class="hlt">soil</span> <span class="hlt">moisture</span> estimation</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Newton, R. W. (Principal Investigator); Clark, B. V.; Pitchford, W. M.; Paris, J. F.</p> <p>1979-01-01</p> <p>A sensor/scene simulation program was developed and used to determine the effects of scene heterogeneity, resolution, frequency, look angle, and surface and temperature relations on the performance of a spaceborne passive microwave system designed to estimate <span class="hlt">soil</span> water information. The ground scene is based on classified LANDSAT images which provide realistic ground classes, as well as geometries. It was determined that the average sensitivity of antenna temperature to <span class="hlt">soil</span> <span class="hlt">moisture</span> improves as the antenna footprint size increased. Also, the precision (or variability) of the sensitivity changes as a function of resolution.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19960025274','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19960025274"><span>Inflatable Antenna Microwave Radiometer for <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Measurement</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Bailey, M. C.; Kendall, Bruce M.; Schroeder, Lyle C.; Harrington, Richard F.</p> <p>1993-01-01</p> <p>Microwave measurements of <span class="hlt">soil</span> <span class="hlt">moisture</span> are not being obtained at the required spatial Earth resolution with current technology. Recently, new novel designs for lightweight reflector systems have been developed using deployable inflatable antenna structures which could enable lightweight real-aperture radiometers. In consideration of this, a study was conducted at the NASA Langley Research Center (LaRC) to determine the feasibility of developing a microwave radiometer system using inflatable reflector antenna technology to obtain high spatial resolution radiometric measurements of <span class="hlt">soil</span> <span class="hlt">moisture</span> from low Earth orbit and which could be used with a small and cost effective launch vehicle. The required high resolution with reasonable swath width coupled with the L-band measurement frequency for <span class="hlt">soil</span> <span class="hlt">moisture</span> dictated the use of a large (30 meter class) real aperture antenna in conjunction with a pushbroom antenna beam configuration and noise-injection type radiometer designs at 1.4 and 4.3 GHz to produce a 370 kilometer cross-track swath with a 10 kilometer resolution that could be packaged for launch with a Titan 2 class vehicle. This study includes design of the inflatable structure, control analysis, structural and thermal analysis, antenna and feed design, radiometer design, payload packaging, orbital analysis, and electromagnetic losses in the thin membrane inflatable materials.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20170010213','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20170010213"><span>Data Assimilation to Extract <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Information From SMAP Observations</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Kolassa, J.; Reichle, R. H.; Liu, Q.; Alemohammad, S. H.; Gentine, P.</p> <p>2017-01-01</p> <p>Statistical techniques permit the retrieval of <span class="hlt">soil</span> <span class="hlt">moisture</span> estimates in a model climatology while retaining the spatial and temporal signatures of the satellite observations. As a consequence, they can be used to reduce the need for localized bias correction techniques typically implemented in data assimilation (DA) systems that tend to remove some of the independent information provided by satellite observations. Here, we use a statistical neural network (NN) algorithm to retrieve SMAP (<span class="hlt">Soil</span> <span class="hlt">Moisture</span> Active Passive) surface <span class="hlt">soil</span> <span class="hlt">moisture</span> estimates in the climatology of the NASA Catchment land surface model. Assimilating these estimates without additional bias correction is found to significantly reduce the model error and increase the temporal correlation against SMAP CalVal in situ observations over the contiguous United States. A comparison with assimilation experiments using traditional bias correction techniques shows that the NN approach better retains the independent information provided by the SMAP observations and thus leads to larger model skill improvements during the assimilation. A comparison with the SMAP Level 4 product shows that the NN approach is able to provide comparable skill improvements and thus represents a viable assimilation approach.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20160006707&hterms=walker&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAuthor-Name%26N%3D0%26No%3D50%26Ntt%3Dwalker','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20160006707&hterms=walker&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAuthor-Name%26N%3D0%26No%3D50%26Ntt%3Dwalker"><span>Interactive Vegetation Phenology, <span class="hlt">Soil</span> <span class="hlt">Moisture</span>, and Monthly Temperature Forecasts</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Koster, R. D.; Walker, G. K.</p> <p>2015-01-01</p> <p>The time scales that characterize the variations of vegetation phenology are generally much longer than those that characterize atmospheric processes. The explicit modeling of phenological processes in an atmospheric forecast system thus has the potential to provide skill to subseasonal or seasonal forecasts. We examine this possibility here using a forecast system fitted with a dynamic vegetation phenology model. We perform three experiments, each consisting of 128 independent warm-season monthly forecasts: 1) an experiment in which both <span class="hlt">soil</span> <span class="hlt">moisture</span> states and carbon states (e.g., those determining leaf area index) are initialized realistically, 2) an experiment in which the carbon states are prescribed to climatology throughout the forecasts, and 3) an experiment in which both the carbon and <span class="hlt">soil</span> <span class="hlt">moisture</span> states are prescribed to climatology throughout the forecasts. Evaluating the monthly forecasts of air temperature in each ensemble against observations, as well as quantifying the inherent predictability of temperature within each ensemble, shows that dynamic phenology can indeed contribute positively to subseasonal forecasts, though only to a small extent, with an impact dwarfed by that of <span class="hlt">soil</span> <span class="hlt">moisture</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19750034484&hterms=alfalfa&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Dalfalfa','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19750034484&hterms=alfalfa&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Dalfalfa"><span>Radar response to vegetation. [<span class="hlt">soil</span> <span class="hlt">moisture</span> mapping via microwave backscattering</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Ulaby, F. T.</p> <p>1975-01-01</p> <p>Active microwave measurements of vegetation backscatter were conducted to determine the utility of radar in mapping <span class="hlt">soil</span> <span class="hlt">moisture</span> through vegetation and mapping crop types. Using a truck-mounted boom, spectral response data were obtained for four crop types (corn, milo, soybeans, and alfalfa) over the 4-8 GHz frequency band, at incidence angles of 0 to 70 degrees in 10-degree steps, and for all four linear polarization combinations. Based on a total of 125 data sets covering a wide range of <span class="hlt">soil</span> <span class="hlt">moisture</span>, content, system design criteria are proposed for each of the aforementioned objectives. Quantitative <span class="hlt">soil</span> <span class="hlt">moisture</span> determination was best achieved at the lower frequency end of the 4-8 GHz band using HH polarized waves in the 5- to 15-degree incidence angle range. A combination of low and high frequency measurements are suggested for classifying crop types. For crop discrimination, a dual-frequency dual-polarization (VV and cross) system operating at incidence angles above 40 degrees is suggested.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H21I1589R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H21I1589R"><span>The potential of SMAP <span class="hlt">soil</span> <span class="hlt">moisture</span> data for analyzing droughts</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Rajasekaran, E.; Das, N. N.; Entekhabi, D.; Yueh, S. H.</p> <p>2017-12-01</p> <p>Identification of the onset and the end of droughts are important for socioeconomic planning. Different datasets and tools are either available or being generated for drought analysis to recognize the status of drought. The aim of this study is to understand the potential of the SMAP <span class="hlt">soil</span> <span class="hlt">moisture</span> (SM) data for identification of onset, persistence and withdrawal of droughts over the Contiguous United States. We are using the SMAP-passive level 3 <span class="hlt">soil</span> <span class="hlt">moisture</span> observations and the United States Drought Monitor (http://droughtmonitor.unl.edu) data for understanding the relation between change in SM and drought severity. The daily observed SM data are temporally averaged to match the weekly drought monitor data and subsequently the weekly, monthly, 3 monthly and 6 monthly change in SM and drought severity were estimated. The analyses suggested that the change in SM and drought severity are correlated especially over the mid-west and west coast of USA at monthly and longer time scales. The spatial pattern of the SM change maps clearly indicated the regions that are moving between different levels of drought severity. Further, the time series of effective saturation [Se =(θ-θr)/(θs-θr)] indicated the temporal dynamics of drought conditions over California which is recovering from a long-term drought. Additional analyses are being carried out to develop statistics between drought severity and <span class="hlt">soil</span> <span class="hlt">moisture</span> level.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/15093293','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/15093293"><span>Determination of chemical availability of cadmium and zinc in <span class="hlt">soils</span> using inert <span class="hlt">soil</span> <span class="hlt">moisture</span> samplers.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Knight, B P; Chaudri, A M; McGrath, S P; Giller, K E</p> <p>1998-01-01</p> <p>A rapid method for extracting <span class="hlt">soil</span> solutions using porous plastic <span class="hlt">soil-moisture</span> samplers was combined with a cation resin equilibration based speciation technique to look at the chemical availability of metals in <span class="hlt">soil</span>. Industrially polluted, metal sulphate amended and sewage sludge treated <span class="hlt">soils</span> were used in our study. Cadmium sulphate amended and industrially contaminated <span class="hlt">soils</span> all had > 65% of the total <span class="hlt">soil</span> solution Cd present as free Cd2+. However, increasing total <span class="hlt">soil</span> Cd concentrations by adding CdSO4 resulted in smaller total <span class="hlt">soil</span> solution Cd. Consequently, the free Cd2+ concentrations in <span class="hlt">soil</span> solutions extracted from these <span class="hlt">soils</span> were smaller than in the same <span class="hlt">soil</span> contaminated by sewage sludge addition. Amendment with ZnSO4 gave much greater concentrations of free Zn2+ in <span class="hlt">soil</span> solutions compared with the same <span class="hlt">soil</span> after long-term Zn contamination via sewage sludge additions. Our results demonstrate the difficulty in comparing total <span class="hlt">soil</span> solution and free metal ion concentrations for <span class="hlt">soils</span> from different areas with different physiochemical properties and sources of contamination. However, when comparing the same Woburn <span class="hlt">soil</span>, Cd was much less available as Cd2+ in <span class="hlt">soil</span> solution from the CdSO4 amended <span class="hlt">soils</span> compared with <span class="hlt">soil</span> contaminated by about 36 years of sewage sludge additions. In contrast, much more Zn was available in <span class="hlt">soil</span> solution as free Zn2+ in the ZnSO4 amended <span class="hlt">soils</span> compared with the sewage sludge treated <span class="hlt">soils</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018JARS...12a6030Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018JARS...12a6030Z"><span>On the relationship between land surface infrared emissivity and <span class="hlt">soil</span> <span class="hlt">moisture</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhou, Daniel K.; Larar, Allen M.; Liu, Xu</p> <p>2018-01-01</p> <p>The relationship between surface infrared (IR) emissivity and <span class="hlt">soil</span> <span class="hlt">moisture</span> content has been investigated based on satellite measurements. Surface <span class="hlt">soil</span> <span class="hlt">moisture</span> content can be estimated by IR remote sensing, namely using the surface parameters of IR emissivity, temperature, vegetation coverage, and <span class="hlt">soil</span> texture. It is possible to separate IR emissivity from other parameters <span class="hlt">affecting</span> surface <span class="hlt">soil</span> <span class="hlt">moisture</span> estimation. The main objective of this paper is to examine the correlation between land surface IR emissivity and <span class="hlt">soil</span> <span class="hlt">moisture</span>. To this end, we have developed a simple yet effective scheme to estimate volumetric <span class="hlt">soil</span> <span class="hlt">moisture</span> (VSM) using IR land surface emissivity retrieved from satellite IR spectral radiance measurements, assuming those other parameters impacting the radiative transfer (e.g., temperature, vegetation coverage, and surface roughness) are known for an acceptable time and space reference location. This scheme is applied to a decade of global IR emissivity data retrieved from MetOp-A infrared atmospheric sounding interferometer measurements. The VSM estimated from these IR emissivity data (denoted as IR-VSM) is used to demonstrate its measurement-to-measurement variations. Representative 0.25-deg spatially-gridded monthly-mean IR-VSM global datasets are then assembled to compare with those routinely provided from satellite microwave (MW) multisensor measurements (denoted as MW-VSM), demonstrating VSM spatial variations as well as seasonal-cycles and interannual variability. Initial positive agreement is shown to exist between IR- and MW-VSM (i.e., R2 = 0.85). IR land surface emissivity contains surface water content information. So, when IR measurements are used to estimate <span class="hlt">soil</span> <span class="hlt">moisture</span>, this correlation produces results that correspond with those customarily achievable from MW measurements. A decade-long monthly-gridded emissivity atlas is used to estimate IR-VSM, to demonstrate its seasonal-cycle and interannual variation, which is spatially</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/biblio/1336979-temperature-moisture-effects-greenhouse-gas-emissions-from-deep-active-layer-boreal-soils','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1336979-temperature-moisture-effects-greenhouse-gas-emissions-from-deep-active-layer-boreal-soils"><span>Temperature and <span class="hlt">moisture</span> effects on greenhouse gas emissions from deep active-layer boreal <span class="hlt">soils</span></span></a></p> <p><a target="_blank" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p>Bond-Lamberty, Ben; Smith, A. Peyton; Bailey, Vanessa L.</p> <p></p> <p>Rapid climatic changes, rising air temperatures, and increased fires are expected to drive permafrost degradation and alter <span class="hlt">soil</span> carbon (C) cycling in many high-latitude ecosystems. How these <span class="hlt">soils</span> will respond to changes in their temperature, <span class="hlt">moisture</span>, and overlying vegetation is uncertain but critical to understand given the large <span class="hlt">soil</span> C stocks in these regions. We used a laboratory experiment to examine how temperature and <span class="hlt">moisture</span> control CO 2 and CH 4 emissions from mineral <span class="hlt">soils</span> sampled from the bottom of the annual active layer, i.e., directly above permafrost, in an Alaskan boreal forest. Gas emissions from 30 cores, subjected tomore » two temperatures and either field <span class="hlt">moisture</span> conditions or experimental drought, were tracked over a 100-day incubation; we also measured a variety of physical and chemical characteristics of the cores. Gravimetric water content was 0.31 ± 0.12 (unitless) at the beginning of the incubation; cores at field <span class="hlt">moisture</span> were unchanged at the end, but drought cores had declined to 0.06 ± 0.04. Daily CO 2 fluxes were positively correlated with incubation chamber temperature, core water content, and percent <span class="hlt">soil</span> nitrogen. They also had a temperature sensitivity ( Q 10) of 1.3 and 1.9 for the field <span class="hlt">moisture</span> and drought treatments, respectively. Daily CH 4 emissions were most strongly correlated with percent nitrogen, but neither temperature nor water content was a significant first-order predictor of CH 4 fluxes. The cumulative production of C from CO 2 was over 6 orders of magnitude higher than that from CH 4; cumulative CO 2 was correlated with incubation temperature and <span class="hlt">moisture</span> treatment, with drought cores producing 52–73 % lower C. Cumulative CH 4 production was unaffected by any treatment. These results suggest that deep active-layer <span class="hlt">soils</span> may be sensitive to changes in <span class="hlt">soil</span> <span class="hlt">moisture</span> under aerobic conditions, a critical factor as discontinuous permafrost thaws in interior Alaska. Furthermore, deep but unfrozen high</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1336979-temperature-moisture-effects-greenhouse-gas-emissions-from-deep-active-layer-boreal-soils','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1336979-temperature-moisture-effects-greenhouse-gas-emissions-from-deep-active-layer-boreal-soils"><span>Temperature and <span class="hlt">moisture</span> effects on greenhouse gas emissions from deep active-layer boreal <span class="hlt">soils</span></span></a></p> <p><a target="_blank" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Bond-Lamberty, Ben; Smith, A. Peyton; Bailey, Vanessa L.</p> <p>2016-12-21</p> <p>Rapid climatic changes, rising air temperatures, and increased fires are expected to drive permafrost degradation and alter <span class="hlt">soil</span> carbon (C) cycling in many high-latitude ecosystems. How these <span class="hlt">soils</span> will respond to changes in their temperature, <span class="hlt">moisture</span>, and overlying vegetation is uncertain but critical to understand given the large <span class="hlt">soil</span> C stocks in these regions. We used a laboratory experiment to examine how temperature and <span class="hlt">moisture</span> control CO 2 and CH 4 emissions from mineral <span class="hlt">soils</span> sampled from the bottom of the annual active layer, i.e., directly above permafrost, in an Alaskan boreal forest. Gas emissions from 30 cores, subjected tomore » two temperatures and either field <span class="hlt">moisture</span> conditions or experimental drought, were tracked over a 100-day incubation; we also measured a variety of physical and chemical characteristics of the cores. Gravimetric water content was 0.31 ± 0.12 (unitless) at the beginning of the incubation; cores at field <span class="hlt">moisture</span> were unchanged at the end, but drought cores had declined to 0.06 ± 0.04. Daily CO 2 fluxes were positively correlated with incubation chamber temperature, core water content, and percent <span class="hlt">soil</span> nitrogen. They also had a temperature sensitivity ( Q 10) of 1.3 and 1.9 for the field <span class="hlt">moisture</span> and drought treatments, respectively. Daily CH 4 emissions were most strongly correlated with percent nitrogen, but neither temperature nor water content was a significant first-order predictor of CH 4 fluxes. The cumulative production of C from CO 2 was over 6 orders of magnitude higher than that from CH 4; cumulative CO 2 was correlated with incubation temperature and <span class="hlt">moisture</span> treatment, with drought cores producing 52–73 % lower C. Cumulative CH 4 production was unaffected by any treatment. These results suggest that deep active-layer <span class="hlt">soils</span> may be sensitive to changes in <span class="hlt">soil</span> <span class="hlt">moisture</span> under aerobic conditions, a critical factor as discontinuous permafrost thaws in interior Alaska. Furthermore, deep but unfrozen high</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016BGeo...13.6669B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016BGeo...13.6669B"><span>Temperature and <span class="hlt">moisture</span> effects on greenhouse gas emissions from deep active-layer boreal <span class="hlt">soils</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bond-Lamberty, Ben; Smith, A. Peyton; Bailey, Vanessa</p> <p>2016-12-01</p> <p>Rapid climatic changes, rising air temperatures, and increased fires are expected to drive permafrost degradation and alter <span class="hlt">soil</span> carbon (C) cycling in many high-latitude ecosystems. How these <span class="hlt">soils</span> will respond to changes in their temperature, <span class="hlt">moisture</span>, and overlying vegetation is uncertain but critical to understand given the large <span class="hlt">soil</span> C stocks in these regions. We used a laboratory experiment to examine how temperature and <span class="hlt">moisture</span> control CO2 and CH4 emissions from mineral <span class="hlt">soils</span> sampled from the bottom of the annual active layer, i.e., directly above permafrost, in an Alaskan boreal forest. Gas emissions from 30 cores, subjected to two temperatures and either field <span class="hlt">moisture</span> conditions or experimental drought, were tracked over a 100-day incubation; we also measured a variety of physical and chemical characteristics of the cores. Gravimetric water content was 0.31 ± 0.12 (unitless) at the beginning of the incubation; cores at field <span class="hlt">moisture</span> were unchanged at the end, but drought cores had declined to 0.06 ± 0.04. Daily CO2 fluxes were positively correlated with incubation chamber temperature, core water content, and percent <span class="hlt">soil</span> nitrogen. They also had a temperature sensitivity (Q10) of 1.3 and 1.9 for the field <span class="hlt">moisture</span> and drought treatments, respectively. Daily CH4 emissions were most strongly correlated with percent nitrogen, but neither temperature nor water content was a significant first-order predictor of CH4 fluxes. The cumulative production of C from CO2 was over 6 orders of magnitude higher than that from CH4; cumulative CO2 was correlated with incubation temperature and <span class="hlt">moisture</span> treatment, with drought cores producing 52-73 % lower C. Cumulative CH4 production was unaffected by any treatment. These results suggest that deep active-layer <span class="hlt">soils</span> may be sensitive to changes in <span class="hlt">soil</span> <span class="hlt">moisture</span> under aerobic conditions, a critical factor as discontinuous permafrost thaws in interior Alaska. Deep but unfrozen high-latitude <span class="hlt">soils</span> have been shown to be</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017WRR....53.1553C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017WRR....53.1553C"><span>Impacts of precipitation and potential evapotranspiration patterns on downscaling <span class="hlt">soil</span> <span class="hlt">moisture</span> in regions with large topographic relief</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Cowley, Garret S.; Niemann, Jeffrey D.; Green, Timothy R.; Seyfried, Mark S.; Jones, Andrew S.; Grazaitis, Peter J.</p> <p>2017-02-01</p> <p><span class="hlt">Soil</span> <span class="hlt">moisture</span> can be estimated at coarse resolutions (>1 km) using satellite remote sensing, but that resolution is poorly suited for many applications. The Equilibrium <span class="hlt">Moisture</span> from Topography, Vegetation, and <span class="hlt">Soil</span> (EMT+VS) model downscales coarse-resolution <span class="hlt">soil</span> <span class="hlt">moisture</span> using fine-resolution topographic, vegetation, and <span class="hlt">soil</span> data to produce fine-resolution (10-30 m) estimates of <span class="hlt">soil</span> <span class="hlt">moisture</span>. The EMT+VS model performs well at catchments with low topographic relief (≤124 m), but it has not been applied to regions with larger ranges of elevation. Large relief can produce substantial variations in precipitation and potential evapotranspiration (PET), which might <span class="hlt">affect</span> the fine-resolution patterns of <span class="hlt">soil</span> <span class="hlt">moisture</span>. In this research, simple methods to downscale temporal average precipitation and PET are developed and included in the EMT+VS model, and the effects of spatial variations in these variables on the surface <span class="hlt">soil</span> <span class="hlt">moisture</span> estimates are investigated. The methods are tested against ground truth data at the 239 km2 Reynolds Creek watershed in southern Idaho, which has 1145 m of relief. The precipitation and PET downscaling methods are able to capture the main features in the spatial patterns of both variables. The space-time Nash-Sutcliffe coefficients of efficiency of the fine-resolution <span class="hlt">soil</span> <span class="hlt">moisture</span> estimates improve from 0.33 to 0.36 and 0.41 when the precipitation and PET downscaling methods are included, respectively. PET downscaling provides a larger improvement in the <span class="hlt">soil</span> <span class="hlt">moisture</span> estimates than precipitation downscaling likely because the PET pattern is more persistent through time, and thus more predictable, than the precipitation pattern.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015JGRD..12010915G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015JGRD..12010915G"><span>Dust emission parameterization scheme over the MENA region: Sensitivity analysis to <span class="hlt">soil</span> <span class="hlt">moisture</span> and <span class="hlt">soil</span> texture</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Gherboudj, Imen; Beegum, S. Naseema; Marticorena, Beatrice; Ghedira, Hosni</p> <p>2015-10-01</p> <p>The mineral dust emissions from arid/semiarid <span class="hlt">soils</span> were simulated over the MENA (Middle East and North Africa) region using the dust parameterization scheme proposed by Alfaro and Gomes (2001), to quantify the effect of the <span class="hlt">soil</span> <span class="hlt">moisture</span> and clay fraction in the emissions. For this purpose, an extensive data set of <span class="hlt">Soil</span> <span class="hlt">Moisture</span> and Ocean Salinity <span class="hlt">soil</span> <span class="hlt">moisture</span>, European Centre for Medium-Range Weather Forecasting wind speed at 10 m height, Food Agricultural Organization <span class="hlt">soil</span> texture maps, MODIS (Moderate Resolution Imaging Spectroradiometer) Normalized Difference Vegetation Index, and erodibility of the <span class="hlt">soil</span> surface were collected for the a period of 3 years, from 2010 to 2013. Though the considered data sets have different temporal and spatial resolution, efforts have been made to make them consistent in time and space. At first, the simulated sandblasting flux over the region were validated qualitatively using MODIS Deep Blue aerosol optical depth and EUMETSAT MSG (Meteosat Seciond Generation) dust product from SEVIRI (Meteosat Spinning Enhanced Visible and Infrared Imager) and quantitatively based on the available ground-based measurements of near-surface particulate mass concentrations (PM10) collected over four stations in the MENA region. Sensitivity analyses were performed to investigate the effect of <span class="hlt">soil</span> <span class="hlt">moisture</span> and clay fraction on the emissions flux. The results showed that <span class="hlt">soil</span> <span class="hlt">moisture</span> and <span class="hlt">soil</span> texture have significant roles in the dust emissions over the MENA region, particularly over the Arabian Peninsula. An inversely proportional dependency is observed between the <span class="hlt">soil</span> <span class="hlt">moisture</span> and the sandblasting flux, where a steep reduction in flux is observed at low friction velocity and a gradual reduction is observed at high friction velocity. Conversely, a directly proportional dependency is observed between the <span class="hlt">soil</span> clay fraction and the sandblasting flux where a steep increase in flux is observed at low friction velocity and a gradual increase is</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016IJAEO..45..187W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016IJAEO..45..187W"><span>Evaluation of AMSR2 <span class="hlt">soil</span> <span class="hlt">moisture</span> products over the contiguous United States using in situ data from the International <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Network</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wu, Qiusheng; Liu, Hongxing; Wang, Lei; Deng, Chengbin</p> <p>2016-03-01</p> <p>High quality <span class="hlt">soil</span> <span class="hlt">moisture</span> datasets are required for various environmental applications. The launch of the Advanced Microwave Scanning Radiometer 2 (AMSR2) on board the Global Change Observation Mission 1-Water (GCOM-W1) in May 2012 has provided global near-surface <span class="hlt">soil</span> <span class="hlt">moisture</span> data, with an average revisit frequency of two days. Since AMSR2 is a new passive microwave system in operation, it is very important to evaluate the quality of AMSR2 products before widespread utilization of the data for scientific research. In this paper, we provide a comprehensive evaluation of the AMSR2 <span class="hlt">soil</span> <span class="hlt">moisture</span> products retrieved by the Japan Aerospace Exploration Agency (JAXA) algorithm. The evaluation was performed for a three-year period (July 2012-June 2015) over the contiguous United States. The AMSR2 <span class="hlt">soil</span> <span class="hlt">moisture</span> products were evaluated by comparing ascending and descending overpass products to each other as well as comparing them to in situ <span class="hlt">soil</span> <span class="hlt">moisture</span> observations of 598 monitoring stations obtained from the International <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Network (ISMN). The accuracy of AMSR2 <span class="hlt">soil</span> <span class="hlt">moisture</span> product was evaluated against several types of monitoring networks, and for different land cover types and ecoregions. Three performance metrics, including mean difference (MD), root mean squared difference (RMSD), and correlation coefficient (R), were used in our accuracy assessment. Our evaluation results revealed that AMSR2 <span class="hlt">soil</span> <span class="hlt">moisture</span> retrievals are generally lower than in situ measurements. The AMSR2 <span class="hlt">soil</span> <span class="hlt">moisture</span> retrievals showed the best agreement with in situ measurements over the Great Plains and the worst agreement over forested areas. This study offers insights into the suitability and reliability of AMSR2 <span class="hlt">soil</span> <span class="hlt">moisture</span> products for different ecoregions. Although AMSR2 <span class="hlt">soil</span> <span class="hlt">moisture</span> retrievals represent useful and effective measurements for some regions, further studies are required to improve the data accuracy.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ACP....18.6413H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ACP....18.6413H"><span>Assessing the uncertainty of <span class="hlt">soil</span> <span class="hlt">moisture</span> impacts on convective precipitation using a new ensemble approach</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Henneberg, Olga; Ament, Felix; Grützun, Verena</p> <p>2018-05-01</p> <p><span class="hlt">Soil</span> <span class="hlt">moisture</span> amount and distribution control evapotranspiration and thus impact the occurrence of convective precipitation. Many recent model studies demonstrate that changes in initial <span class="hlt">soil</span> <span class="hlt">moisture</span> content result in modified convective precipitation. However, to quantify the resulting precipitation changes, the chaotic behavior of the atmospheric system needs to be considered. Slight changes in the simulation setup, such as the chosen model domain, also result in modifications to the simulated precipitation field. This causes an uncertainty due to stochastic variability, which can be large compared to effects caused by <span class="hlt">soil</span> <span class="hlt">moisture</span> variations. By shifting the model domain, we estimate the uncertainty of the model results. Our novel uncertainty estimate includes 10 simulations with shifted model boundaries and is compared to the effects on precipitation caused by variations in <span class="hlt">soil</span> <span class="hlt">moisture</span> amount and local distribution. With this approach, the influence of <span class="hlt">soil</span> <span class="hlt">moisture</span> amount and distribution on convective precipitation is quantified. Deviations in simulated precipitation can only be attributed to <span class="hlt">soil</span> <span class="hlt">moisture</span> impacts if the systematic effects of <span class="hlt">soil</span> <span class="hlt">moisture</span> modifications are larger than the inherent simulation uncertainty at the convection-resolving scale. We performed seven experiments with modified <span class="hlt">soil</span> <span class="hlt">moisture</span> amount or distribution to address the effect of <span class="hlt">soil</span> <span class="hlt">moisture</span> on precipitation. Each of the experiments consists of 10 ensemble members using the deep convection-resolving COSMO model with a grid spacing of 2.8 km. Only in experiments with very strong modification in <span class="hlt">soil</span> <span class="hlt">moisture</span> do precipitation changes exceed the model spread in amplitude, location or structure. These changes are caused by a 50 % <span class="hlt">soil</span> <span class="hlt">moisture</span> increase in either the whole or part of the model domain or by drying the whole model domain. Increasing or decreasing <span class="hlt">soil</span> <span class="hlt">moisture</span> both predominantly results in reduced precipitation rates. Replacing the <span class="hlt">soil</span> <span class="hlt">moisture</span> with realistic</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=330164','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=330164"><span>SMAP <span class="hlt">soil</span> <span class="hlt">moisture</span> drying more rapid than observed in situ following rainfall events</span></a></p> <p><a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>We examine <span class="hlt">soil</span> drying rates by comparing observations from the NASA <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Active Passive (SMAP) mission to surface <span class="hlt">soil</span> <span class="hlt">moisture</span> from in situ probes during drydown periods at SMAP validation sites. SMAP and in situ probes record different <span class="hlt">soil</span> drying dynamics after rainfall. We modeled this...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1915197R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1915197R"><span>Assimilation of neural network <span class="hlt">soil</span> <span class="hlt">moisture</span> in land surface models</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Rodriguez-Fernandez, Nemesio; de Rosnay, Patricia; Albergel, Clement; Aires, Filipe; Prigent, Catherine; Kerr, Yann; Richaume, Philippe; Muñoz-Sabater, Joaquin; Drusch, Matthias</p> <p>2017-04-01</p> <p>In this study a set of land surface data assimilation (DA) experiments making use of satellite derived <span class="hlt">soil</span> <span class="hlt">moisture</span> (SM) are presented. These experiments have two objectives: (1) to test the information content of satellite remote sensing of <span class="hlt">soil</span> <span class="hlt">moisture</span> for numerical weather prediction (NWP) models, and (2) to test a simplified assimilation of these data through the use of a Neural Network (NN) retrieval. Advanced Scatterometer (ASCAT) and <span class="hlt">Soil</span> <span class="hlt">Moisture</span> and Ocean Salinity (SMOS) data were used. The SMOS <span class="hlt">soil</span> <span class="hlt">moisture</span> dataset was obtained specifically for this project training a NN using SMOS brightness temperatures as input and using as reference for the training European Centre for Medium-Range Weather Forecasts (ECMWF) H-TESSEL SM fields. In this way, the SMOS NN SM dataset has a similar climatology to that of the model and it does not present a global bias with respect to the model. The DA experiments are computed using a surface-only Land Data Assimilation System (so-LDAS) based on the HTESSEL land surface model. This system is very computationally efficient and allows to perform long surface assimilation experiments (one whole year, 2012). SMOS NN SM DA experiments are compared to ASCAT SM DA experiments. In both cases, experiments with and without 2 m air temperature and relative humidity DA are discussed using different observation errors for the ASCAT and SMOS datasets. Seasonal, geographical and <span class="hlt">soil</span>-depth-related differences between the results of those experiments are presented and discussed. The different SM analysed fields are evaluated against a large number of in situ measurements of SM. On average, the SM analysis gives in general similar results to the model open loop with no assimilation even if significant differences can be seen for specific sites with in situ measurements. The sensitivity to observation errors to the SM dataset slightly differs depending on the networks of in situ measurements, however it is relatively low for the tests</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li class="active"><span>22</span></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_22 --> <div id="page_23" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li class="active"><span>23</span></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li><a href="#" onclick='return showDiv("page_25");'>25</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="441"> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27078970','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27078970"><span>[Effect of Biochar Application on <span class="hlt">Soil</span> Aggregates Distribution and <span class="hlt">Moisture</span> Retention in Orchard <span class="hlt">Soil</span>].</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>An, Yan; Ji, Qiang; Zhao, Shi-xiang; Wang, Xu-dong</p> <p>2016-01-15</p> <p>Applying biochar to <span class="hlt">soil</span> has been considered to be one of the important practices in improving <span class="hlt">soil</span> properties and increasing carbon sequestration. In order to investigate the effects of biochar application on <span class="hlt">soil</span> aggregates distribution and its organic matter content and <span class="hlt">soil</span> <span class="hlt">moisture</span> constant in different size aggregates, various particle-size fractions of <span class="hlt">soil</span> aggregates were obtained with the dry-screening method. The results showed that, compared to the treatment without biochar (CK), the application of biochar reduced the mass content of 5-8 mm and < 0.25 mm <span class="hlt">soil</span> aggregates at 0-10 cm <span class="hlt">soil</span> horizon, while increased the content of 1-2 mm and 2-5 mm <span class="hlt">soil</span> aggregates at this horizon, and the content of 1-2 mm aggregates significantly increased along with the rates of biochar application. The mean diameter of <span class="hlt">soil</span> aggregates was reduced by biochar application at 0-10 cm <span class="hlt">soil</span> horizon. However, the effect of biochar application on the mean diameter of <span class="hlt">soil</span> aggregates at 10-20 cm <span class="hlt">soil</span> horizon was not significant. Compared to CK, biochar application significantly increased <span class="hlt">soil</span> organic carbon content in aggregates, especially in 1-2 mm aggregates which was increased by > 70% compared to CK. Both the water holding capacity and <span class="hlt">soil</span> porosity were significantly increased by biochar application. Furthermore, the neutral biochar was more effective than alkaline biochar in increasing <span class="hlt">soil</span> <span class="hlt">moisture</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20160008107','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20160008107"><span><span class="hlt">Soil</span> <span class="hlt">Moisture</span> Active Passive (SMAP) Mission Level 4 Surface and Root Zone <span class="hlt">Soil</span> <span class="hlt">Moisture</span> (L4_SM) Product Specification Document</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Reichle, Rolf H.; Ardizzone, Joseph V.; Kim, Gi-Kong; Lucchesi, Robert A.; Smith, Edmond B.; Weiss, Barry H.</p> <p>2015-01-01</p> <p>This is the Product Specification Document (PSD) for Level 4 Surface and Root Zone <span class="hlt">Soil</span> <span class="hlt">Moisture</span> (L4_SM) data for the Science Data System (SDS) of the <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Active Passive (SMAP) project. The L4_SM data product provides estimates of land surface conditions based on the assimilation of SMAP observations into a customized version of the NASA Goddard Earth Observing System, Version 5 (GEOS-5) land data assimilation system (LDAS). This document applies to any standard L4_SM data product generated by the SMAP Project. The <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Active Passive (SMAP) mission will enhance the accuracy and the resolution of space-based measurements of terrestrial <span class="hlt">soil</span> <span class="hlt">moisture</span> and freeze-thaw state. SMAP data products will have a noteworthy impact on multiple relevant and current Earth Science endeavors. These include: Understanding of the processes that link the terrestrial water, the energy and the carbon cycles, Estimations of global water and energy fluxes over the land surfaces, Quantification of the net carbon flux in boreal landscapes Forecast skill of both weather and climate, Predictions and monitoring of natural disasters including floods, landslides and droughts, and Predictions of agricultural productivity. To provide these data, the SMAP mission will deploy a satellite observatory in a near polar, sun synchronous orbit. The observatory will house an L-band radiometer that operates at 1.40 GHz and an L-band radar that operates at 1.26 GHz. The instruments will share a rotating reflector antenna with a 6 meter aperture that scans over a 1000 km swath.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/16345610','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/16345610"><span>Variation in microbial activity in histosols and its relationship to <span class="hlt">soil</span> <span class="hlt">moisture</span>.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Tate, R L; Terry, R E</p> <p>1980-08-01</p> <p>Microbial biomass, dehydrogenase activity, carbon metabolism, and aerobic bacterial populations were examined in cropped and fallow Pahokee muck (a lithic medisaprist) of the Florida Everglades. Dehydrogenase activity was two- to sevenfold greater in <span class="hlt">soil</span> cropped to St. Augustinegrass (Stenotaphrum secundatum (Walt) Kuntz) compared with uncropped <span class="hlt">soil</span>, whereas biomass ranged from equivalence in the two <span class="hlt">soils</span> to a threefold stimulation in the cropped <span class="hlt">soil</span>. Biomass in <span class="hlt">soil</span> cropped to sugarcane (Saccharum spp. L) approximated that from the grass field, whereas dehydrogenase activities of the cane <span class="hlt">soil</span> were nearly equivalent to those of the fallow <span class="hlt">soil</span>. Microbial biomass, dehydrogenase activity, aerobic bacterial populations, and salicylate oxidation rates all correlated with <span class="hlt">soil</span> <span class="hlt">moisture</span> levels. These data indicate that within the <span class="hlt">moisture</span> ranges detected in the surface <span class="hlt">soils</span>, increased <span class="hlt">moisture</span> stimulated microbial activity, whereas within the <span class="hlt">soil</span> profile where <span class="hlt">moisture</span> ranges reached saturation, increased <span class="hlt">moisture</span> inhibited aerobic activities and stimulated anaerobic processes.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=291573','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=291573"><span>Variation in Microbial Activity in Histosols and Its Relationship to <span class="hlt">Soil</span> <span class="hlt">Moisture</span> †</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Tate, Robert L.; Terry, Richard E.</p> <p>1980-01-01</p> <p>Microbial biomass, dehydrogenase activity, carbon metabolism, and aerobic bacterial populations were examined in cropped and fallow Pahokee muck (a lithic medisaprist) of the Florida Everglades. Dehydrogenase activity was two- to sevenfold greater in <span class="hlt">soil</span> cropped to St. Augustinegrass (Stenotaphrum secundatum (Walt) Kuntz) compared with uncropped <span class="hlt">soil</span>, whereas biomass ranged from equivalence in the two <span class="hlt">soils</span> to a threefold stimulation in the cropped <span class="hlt">soil</span>. Biomass in <span class="hlt">soil</span> cropped to sugarcane (Saccharum spp. L) approximated that from the grass field, whereas dehydrogenase activities of the cane <span class="hlt">soil</span> were nearly equivalent to those of the fallow <span class="hlt">soil</span>. Microbial biomass, dehydrogenase activity, aerobic bacterial populations, and salicylate oxidation rates all correlated with <span class="hlt">soil</span> <span class="hlt">moisture</span> levels. These data indicate that within the <span class="hlt">moisture</span> ranges detected in the surface <span class="hlt">soils</span>, increased <span class="hlt">moisture</span> stimulated microbial activity, whereas within the <span class="hlt">soil</span> profile where <span class="hlt">moisture</span> ranges reached saturation, increased <span class="hlt">moisture</span> inhibited aerobic activities and stimulated anaerobic processes. PMID:16345610</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ESSD...10...61B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ESSD...10...61B"><span>The Raam regional <span class="hlt">soil</span> <span class="hlt">moisture</span> monitoring network in the Netherlands</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Benninga, Harm-Jan F.; Carranza, Coleen D. U.; Pezij, Michiel; van Santen, Pim; van der Ploeg, Martine J.; Augustijn, Denie C. M.; van der Velde, Rogier</p> <p>2018-01-01</p> <p>We have established a <span class="hlt">soil</span> <span class="hlt">moisture</span> profile monitoring network in the Raam region in the Netherlands. This region faces water shortages during summers and excess of water during winters and after extreme precipitation events. Water management can benefit from reliable information on the <span class="hlt">soil</span> water availability and water storing capacity in the unsaturated zone. In situ measurements provide a direct source of information on which water managers can base their decisions. Moreover, these measurements are commonly used as a reference for the calibration and validation of <span class="hlt">soil</span> <span class="hlt">moisture</span> content products derived from earth observations or obtained by model simulations. Distributed over the Raam region, we have equipped 14 agricultural fields and 1 natural grass field with <span class="hlt">soil</span> <span class="hlt">moisture</span> and <span class="hlt">soil</span> temperature monitoring instrumentation, consisting of Decagon 5TM sensors installed at depths of 5, 10, 20, 40 and 80 cm. In total, 12 stations are located within the Raam catchment (catchment area of 223 km2), and 5 of these stations are located within the closed sub-catchment Hooge Raam (catchment area of 41 km2). <span class="hlt">Soil</span>-specific calibration functions that have been developed for the 5TM sensors under laboratory conditions lead to an accuracy of 0.02 m3 m-3. The first set of measurements has been retrieved for the period 5 April 2016-4 April 2017. In this paper, we describe the Raam monitoring network and instrumentation, the <span class="hlt">soil</span>-specific calibration of the sensors, the first year of measurements, and additional measurements (<span class="hlt">soil</span> temperature, phreatic groundwater levels and meteorological data) and information (elevation, <span class="hlt">soil</span> physical characteristics, land cover and a geohydrological model) available for performing scientific research. The data are available at <a href="https://doi.org/10.4121/uuid:dc364e97-d44a-403f-82a7-121902deeb56" target="_blank">https://doi.org/10.4121/uuid:dc364e97-d44a-403f-82a7-121902deeb56</a>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018AdAtS..35..445Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018AdAtS..35..445Z"><span>Evaluating the Capabilities of <span class="hlt">Soil</span> Enthalpy, <span class="hlt">Soil</span> <span class="hlt">Moisture</span> and <span class="hlt">Soil</span> Temperature in Predicting Seasonal Precipitation</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhao, Changyu; Chen, Haishan; Sun, Shanlei</p> <p>2018-04-01</p> <p><span class="hlt">Soil</span> enthalpy ( H) contains the combined effects of both <span class="hlt">soil</span> <span class="hlt">moisture</span> ( w) and <span class="hlt">soil</span> temperature ( T) in the land surface hydrothermal process. In this study, the sensitivities of H to w and T are investigated using the multi-linear regression method. Results indicate that T generally makes positive contributions to H, while w exhibits different (positive or negative) impacts due to <span class="hlt">soil</span> ice effects. For example, w negatively contributes to H if <span class="hlt">soil</span> contains more ice; however, after <span class="hlt">soil</span> ice melts, w exerts positive contributions. In particular, due to lower w interannual variabilities in the deep <span class="hlt">soil</span> layer (i.e., the fifth layer), H is more sensitive to T than to w. Moreover, to compare the potential capabilities of H, w and T in precipitation ( P) prediction, the Huanghe-Huaihe Basin (HHB) and Southeast China (SEC), with similar sensitivities of H to w and T, are selected. Analyses show that, despite similar spatial distributions of H-P and T-P correlation coefficients, the former values are always higher than the latter ones. Furthermore, H provides the most effective signals for P prediction over HHB and SEC, i.e., a significant leading correlation between May H and early summer (June) P. In summary, H, which integrates the effects of T and w as an independent variable, has greater capabilities in monitoring land surface heating and improving seasonal P prediction relative to individual land surface factors (e.g., T and w).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017WRR....53.5320H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017WRR....53.5320H"><span>Near-surface turbulence as a missing link in modeling evapotranspiration-<span class="hlt">soil</span> <span class="hlt">moisture</span> relationships</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Haghighi, Erfan; Kirchner, James W.</p> <p>2017-07-01</p> <p>Despite many efforts to develop evapotranspiration (ET) models with improved parametrizations of resistance terms for water vapor transfer into the atmosphere, estimates of ET and its partitioning remain prone to bias. Much of this bias could arise from inadequate representations of physical interactions near nonuniform surfaces from which localized heat and water vapor fluxes emanate. This study aims to provide a mechanistic bridge from land-surface characteristics to vertical transport predictions, and proposes a new physically based ET model that builds on a recently developed bluff-rough bare <span class="hlt">soil</span> evaporation model incorporating coupled <span class="hlt">soil</span> <span class="hlt">moisture</span>-atmospheric controls. The newly developed ET model explicitly accounts for (1) near-surface turbulent interactions <span class="hlt">affecting</span> <span class="hlt">soil</span> drying and (2) <span class="hlt">soil-moisture</span>-dependent stomatal responses to atmospheric evaporative demand that influence leaf (and canopy) transpiration. Model estimates of ET and its partitioning were in good agreement with available field-scale data, and highlight hidden processes not accounted for by commonly used ET schemes. One such process, nonlinear vegetation-induced turbulence (as a function of vegetation stature and cover fraction) significantly influences ET-<span class="hlt">soil</span> <span class="hlt">moisture</span> relationships. Our results are particularly important for water resources and land use planning of semiarid sparsely vegetated ecosystems where <span class="hlt">soil</span> surface interactions are known to play a critical role in land-climate interactions. This study potentially facilitates a mathematically tractable description of the strength (i.e., the slope) of the ET-<span class="hlt">soil</span> <span class="hlt">moisture</span> relationship, which is a core component of models that seek to predict land-atmosphere coupling and its feedback to the climate system in a changing climate.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25397977','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25397977"><span>Role of extrinsic arbuscular mycorrhizal fungi in heavy metal-contaminated wetlands with various <span class="hlt">soil</span> <span class="hlt">moisture</span> levels.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Zheng, S; Wang, C; Shen, Z; Quan, Y; Liu, X</p> <p>2015-01-01</p> <p>This study presents an efficient heavy metal (HM) control method in HM-contaminated wetlands with varied <span class="hlt">soil</span> <span class="hlt">moisture</span> levels through the introduction of extrinsic arbuscular mycorrhizal fungi (AMF) into natural wetland <span class="hlt">soil</span> containing indigenous AMF species. A pot culture experiment was designed to determine the effect of two <span class="hlt">soil</span> water contents (5-8% and 25-30%), five extrinsic AMF inoculants (Glomus mosseae, G. clarum, G. claroideum, G. etunicatum, and G. intraradices), and HM contamination on root colonization, plant growth, and element uptake of common reed (Phragmites australis (Cav.) Trin. ex Steudel) plantlets in wetland <span class="hlt">soils</span>. This study showed the prevalence of mycorrhizae in the roots of all P. australis plantlets, regardless of extrinsic AMF inoculations, varied <span class="hlt">soil</span> <span class="hlt">moisture</span> or HM levels. It seems that different extrinsic AMF inoculations effectively lowered HM concentrations in the aboveground tissues of P. australis at two <span class="hlt">soil</span> <span class="hlt">moisture</span> levels. However, metal species, metal concentrations, and <span class="hlt">soil</span> <span class="hlt">moisture</span> should also be very important factors influencing the elemental uptake performance of plants in wetland ecosystems. Besides, the <span class="hlt">soil</span> <span class="hlt">moisture</span> level significantly influenced plant growth (including height, and shoot and root dry weight (DW)), and extrinsic AMF inoculations differently <span class="hlt">affected</span> shoot DW.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5087863','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5087863"><span>Effects of <span class="hlt">Soil</span> Temperature and <span class="hlt">Moisture</span> on <span class="hlt">Soil</span> Respiration on the Tibetan Plateau</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Chang, Xiaofeng; Wang, Shiping; Xu, Burenbayin; Luo, Caiyun; Zhang, Zhenhua; Wang, Qi; Rui, Yichao; Cui, Xiaoying</p> <p>2016-01-01</p> <p>Understanding of effects of <span class="hlt">soil</span> temperature and <span class="hlt">soil</span> <span class="hlt">moisture</span> on <span class="hlt">soil</span> respiration (Rs) under future warming is critical to reduce uncertainty in predictions of feedbacks to atmospheric CO2 concentrations from grassland <span class="hlt">soil</span> carbon. Intact cores with roots taken from a full factorial, 5-year alpine meadow warming and grazing experiment in the field were incubated at three different temperatures (i.e. 5, 15 and 25°C) with two <span class="hlt">soil</span> <span class="hlt">moistures</span> (i.e. 30 and 60% water holding capacity (WHC)) in our study. Another experiment of glucose-induced respiration (GIR) with 4 h of incubation was conducted to determine substrate limitation. Our results showed that high temperature increased Rs and low <span class="hlt">soil</span> <span class="hlt">moisture</span> limited the response of Rs to temperature only at high incubation temperature (i.e. 25°C). Temperature sensitivity (Q10) did not significantly decrease over the incubation period, suggesting that substrate depletion did not limit Rs. Meanwhile, the carbon availability index (CAI) was higher at 5°C compared with 15 and 25°C incubation, but GIR increased with increasing temperature. Therefore, our findings suggest that warming-induced decrease in Rs in the field over time may result from a decrease in <span class="hlt">soil</span> <span class="hlt">moisture</span> rather than from <span class="hlt">soil</span> substrate depletion, because warming increased root biomass in the alpine meadow. PMID:27798671</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=215525&keyword=bond&actType=&TIMSType=+&TIMSSubTypeID=&DEID=&epaNumber=&ntisID=&archiveStatus=Both&ombCat=Any&dateBeginCreated=&dateEndCreated=&dateBeginPublishedPresented=&dateEndPublishedPresented=&dateBeginUpdated=&dateEndUpdated=&dateBeginCompleted=&dateEndCompleted=&personID=&role=Any&journalID=&publisherID=&sortBy=revisionDate&count=50','EPA-EIMS'); return false;" href="https://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=215525&keyword=bond&actType=&TIMSType=+&TIMSSubTypeID=&DEID=&epaNumber=&ntisID=&archiveStatus=Both&ombCat=Any&dateBeginCreated=&dateEndCreated=&dateBeginPublishedPresented=&dateEndPublishedPresented=&dateBeginUpdated=&dateEndUpdated=&dateBeginCompleted=&dateEndCompleted=&personID=&role=Any&journalID=&publisherID=&sortBy=revisionDate&count=50"><span><span class="hlt">Soil</span> <span class="hlt">moisture</span> effects on the carbon isotopic composition of <span class="hlt">soil</span> respiration</span></a></p> <p><a target="_blank" href="http://oaspub.epa.gov/eims/query.page">EPA Science Inventory</a></p> <p></p> <p></p> <p>The carbon isotopic composition ( 13C) of recently assimilated plant carbon is known to depend on water-stress, caused either by low <span class="hlt">soil</span> <span class="hlt">moisture</span> or by low atmospheric humidity. Air humidity has also been shown to correlate with the 13C of <span class="hlt">soil</span> respiration, which suggests indir...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/24835','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/24835"><span>Lodgepole pine site index in relation to synoptic measures of climate, <span class="hlt">soil</span> <span class="hlt">moisture</span> and <span class="hlt">soil</span> nutrients.</span></a></p> <p><a target="_blank" href="http://www.fs.usda.gov/treesearch/">Treesearch</a></p> <p>G. Geoff Wang; Shongming Huang; Robert A. Monserud; Ryan J. Klos</p> <p>2004-01-01</p> <p>Lodgepole pine site index was examined in relation to synoptic measures of topography, <span class="hlt">soil</span> <span class="hlt">moisture</span>, and <span class="hlt">soil</span> nutrients in Alberta. Data came from 214 lodgepole pine-dominated stands sampled as a part of the provincial permanent sample plot program. Spatial location (elevation, latitude, and longitude) and natural subregions (NSRs) were topographic variables that...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/39672','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/39672"><span><span class="hlt">Soil</span> <span class="hlt">moisture</span> effects on the carbon isotope composition of <span class="hlt">soil</span> respiration</span></a></p> <p><a target="_blank" href="http://www.fs.usda.gov/treesearch/">Treesearch</a></p> <p>Claire L. Phillips; Nick Nickerson; David Risk; Zachary E. Kayler; Chris Andersen; Alan Mix; Barbara J. Bond</p> <p>2010-01-01</p> <p>The carbon isotopic composition (δ13C) of recently assimilated plant carbon is known to depend on water-stress, caused either by low <span class="hlt">soil</span> <span class="hlt">moisture</span> or by low atmospheric humidity. Air humidity has also been shown to correlate with the δ13C of <span class="hlt">soil</span> respiration, which suggests indirectly that recently fixed photosynthates...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA615121','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA615121"><span><span class="hlt">Soil</span> Temperature and <span class="hlt">Moisture</span> Effects on <span class="hlt">Soil</span> Respiration and Microbial Community Abundance</span></a></p> <p><a target="_blank" href="http://www.dtic.mil/">DTIC Science & Technology</a></p> <p></p> <p>2015-04-13</p> <p>highest abundance of bacteria and archaea. Across all <span class="hlt">soils</span>, if the <span class="hlt">moisture</span> content was optimal but the temperature was around 5°C, the respiration...9 3.3 Abundance of <span class="hlt">soil</span> bacteria and archaea ..................................................................... 10 4...ARTEMIS Army Terrestrial-Environmental Modeling and Intelligence System ATCC American Type Culture Collection Ca Calcium CEC Cation Exchange Capacity</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFMIN53B1742Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFMIN53B1742Z"><span>A Combined <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Product of the Tibetan Plateau using Different Sensors Simultaneously</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zeng, Y.; Dente, L.; Su, B.; Wang, L.</p> <p>2012-12-01</p> <p>It is always challenging to find a single satellite-derived <span class="hlt">soil</span> <span class="hlt">moisture</span> product that has complete coverage of the Tibetan Plateau for a long time period and is suitable for climate change studies at sub-continental scale. Meanwhile, having a number of independent satellite-derived <span class="hlt">soil</span> <span class="hlt">moisture</span> data sets does not mean that it is straightforward to create long-term consistent time series, due to the differences among the data sets related to the different retrieval approaches. Therefore, this study is focused on the development and validation of a simple Bayesian based method to merge/blend different satellite-derived <span class="hlt">soil</span> <span class="hlt">moisture</span> data. The merging method was firstly tested over the Maqu region (north-eastern fringe of the Tibetan Plateau), where in situ <span class="hlt">soil</span> <span class="hlt">moisture</span> data were collected, for the period from May 2008 to December 2010. The in situ data provided by the 20 monitoring stations in the Maqu region were compared to the AMSR-E <span class="hlt">soil</span> <span class="hlt">moisture</span> products by VUA-NASA and the ASCAT <span class="hlt">soil</span> <span class="hlt">moisture</span> products by TU Wien, in order to determine bias and standard deviation. It was found that the bias between the satellite and the in situ data varies with seasons. The satellite-derived products were first corrected for the bias and then merged. This is generally caused by notable differences in the represented depth, spatial extent and so on. The systematic bias is <span class="hlt">affected</span> by the spatial variability and the temporal stability (Dente et al. 2012). The dependence of the bias on season was investigated and identified as the monsoon season only (May-September), in winter only (December - February), and in the period between the monsoon season and winter (March-April, October-November, called the transition season) (Dente et al. 2012, Su et al. 2011). After the date merging procedure, the standard deviations between the satellite and the in situ data reduced from 0.0839 to 0.0622 for ASCAT data, and from 0.0682 to 0.0593 for AMSR-E data. The developed merging method is</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..15.1089A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..15.1089A"><span>Ground Albedo Neutron Sensing (GANS) method for measurements of <span class="hlt">soil</span> <span class="hlt">moisture</span> in cropped fields</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Andres Rivera Villarreyes, Carlos; Baroni, Gabriele; Oswald, Sascha E.</p> <p>2013-04-01</p> <p>Measurement of <span class="hlt">soil</span> <span class="hlt">moisture</span> at the plot or hill-slope scale is an important link between local vadose zone hydrology and catchment hydrology. However, so far only few methods are on the way to close this gap between point measurements and remote sensing. This study evaluates the applicability of the Ground Albedo Neutron Sensing (GANS) for integral quantification of seasonal <span class="hlt">soil</span> <span class="hlt">moisture</span> in the root zone at the scale of a field or small watershed, making use of the crucial role of hydrogen as neutron moderator relative to other landscape materials. GANS measurements were performed at two locations in Germany under different vegetative situations and seasonal conditions. Ground albedo neutrons were measured at (i) a lowland Bornim farmland (Brandenburg) cropped with sunflower in 2011 and winter rye in 2012, and (ii) a mountainous farmland catchment (Schaefertal, Harz Mountains) since middle 2011. At both sites depth profiles of <span class="hlt">soil</span> <span class="hlt">moisture</span> were measured at several locations in parallel by frequency domain reflectometry (FDR) for comparison and calibration. Initially, calibration parameters derived from a previous study with corn cover were tested under sunflower and winter rye periods at the same farmland. GANS <span class="hlt">soil</span> <span class="hlt">moisture</span> based on these parameters showed a large discrepancy compared to classical <span class="hlt">soil</span> <span class="hlt">moisture</span> measurements. Therefore, two new calibration approaches and four different ways of integration the <span class="hlt">soil</span> <span class="hlt">moisture</span> profile to an integral value for GANS were evaluated in this study. This included different sets of calibration parameters based on different growing periods of sunflower. New calibration parameters showed a good agreement with FDR network during sunflower period (RMSE = 0.023 m3 m-3), but they underestimated <span class="hlt">soil</span> <span class="hlt">moisture</span> in the winter rye period. The GANS approach resulted to be highly <span class="hlt">affected</span> by temporal changes of biomass and crop types which suggest the need of neutron corrections for long-term observations with crop rotation. Finally</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015BGD....12.1453Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015BGD....12.1453Z"><span><span class="hlt">Soil</span> <span class="hlt">moisture</span> influenced the interannual variation in temperature sensitivity of <span class="hlt">soil</span> organic carbon mineralization in the Loess Plateau</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhang, Y.; Guo, S.; Zhao, M.; Du, L.; Li, R.; Jiang, J.; Wang, R.; Li, N.</p> <p>2015-01-01</p> <p>Temperature sensitivity of SOC mineralization (Q10) determines how strong the feedback from global warming may be on the atmospheric CO2 concentration, thus understanding the factors influencing the interannual variation in Q10 is important to accurately estimate the local <span class="hlt">soil</span> carbon cycle. In situ SOC mineralization was measured using an automated CO2 flux system (Li-8100) in long-term bare fallow <span class="hlt">soil</span> in the Loess Plateau (35° 12' N, 107° 40' E) in Changwu, Shaanxi, China form 2008 to 2013. The results showed that the annual cumulative SOC mineralization ranged from 226 to 298 g C m-2 y-1 (mean =253 g C m-2 y-1; CV =13%), annual Q10 ranged from 1.48 to 1.94 (mean =1.70; CV =10%), and annual <span class="hlt">soil</span> <span class="hlt">moisture</span> content ranged from 38.6 to 50.7% WFPS (mean =43.8% WFPS; CV =11%), which were mainly <span class="hlt">affected</span> by the frequency and distribution of precipitation. Annual Q10 showed a negative quadratic correlation with <span class="hlt">soil</span> <span class="hlt">moisture</span>. In conclusion, understanding of the relationships between interannual variation in Q10 of SOC mineralization, <span class="hlt">soil</span> <span class="hlt">moisture</span> and precipitation is important to accurately estimate the local carbon cycle, especially under the changing climate.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=301780','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=301780"><span>Inter-comparison of <span class="hlt">soil</span> <span class="hlt">moisture</span> sensors from the <span class="hlt">soil</span> <span class="hlt">moisture</span> active passive marena Oklahoma in situ sensor testbed (SMAP-MOISST)</span></a></p> <p><a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>The diversity of in situ <span class="hlt">soil</span> <span class="hlt">moisture</span> network protocols and instrumentation led to the development of a testbed for comparing in situ <span class="hlt">soil</span> <span class="hlt">moisture</span> sensors. Located in Marena, Oklahoma on the Oklahoma State University Range Research Station, the testbed consists of four base stations. Each station ...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=285459','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=285459"><span>Improving long-term global precipitation dataset using multi-sensor surface <span class="hlt">soil</span> <span class="hlt">moisture</span> retrievals and the <span class="hlt">soil</span> <span class="hlt">moisture</span> analysis rainfall tool (SMART)</span></a></p> <p><a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>Using multiple historical satellite surface <span class="hlt">soil</span> <span class="hlt">moisture</span> products, the Kalman Filtering-based <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Analysis Rainfall Tool (SMART) is applied to improve the accuracy of a multi-decadal global daily rainfall product that has been bias-corrected to match the monthly totals of available rain g...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=331098','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=331098"><span>On the temporal and spatial variability of near-surface <span class="hlt">soil</span> <span class="hlt">moisture</span> for the identification of representative in situ <span class="hlt">soil</span> <span class="hlt">moisture</span> monitoring stations</span></a></p> <p><a target="_blank" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>The high spatio-temporal variability of <span class="hlt">soil</span> <span class="hlt">moisture</span> complicates the validation of remotely sensed <span class="hlt">soil</span> <span class="hlt">moisture</span> products using in-situ monitoring stations. Therefore, a standard methodology for selecting the most repre- sentative stations for the purpose of validating satellites and land surface ...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20180000706','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20180000706"><span>Local Versus Remote Contributions of <span class="hlt">Soil</span> <span class="hlt">Moisture</span> to Near-Surface Temperature Variability</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Koster, R.; Schubert, S.; Wang, H.; Chang, Y.</p> <p>2018-01-01</p> <p><span class="hlt">Soil</span> <span class="hlt">moisture</span> variations have a straightforward impact on overlying air temperatures, wetter <span class="hlt">soils</span> can induce higher evaporative cooling of the <span class="hlt">soil</span> and thus, locally, cooler temperatures overall. Not known, however, is the degree to which <span class="hlt">soil</span> <span class="hlt">moisture</span> variations can <span class="hlt">affect</span> remote air temperatures through their impact on the atmospheric circulation. In this talk we describe a two-pronged analysis that addresses this question. In the first segment, an extensive ensemble of NASA/GSFC GEOS-5 atmospheric model simulations is analyzed statistically to isolate and quantify the contributions of various <span class="hlt">soil</span> <span class="hlt">moisture</span> states, both local and remote, to the variability of air temperature at a given local site. In the second segment, the relevance of the derived statistical relationships is evaluated by applying them to observations-based data. Results from the second segment suggest that the GEOS-5-based relationships do, at least to first order, hold in nature and thus may provide some skill to forecasts of air temperature at subseasonal time scales, at least in certain regions.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li class="active"><span>23</span></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li><a href="#" onclick='return showDiv("page_25");'>25</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_23 --> <div id="page_24" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li class="active"><span>24</span></li> <li><a href="#" onclick='return showDiv("page_25");'>25</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="461"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2006AGUFM.H23E1559D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2006AGUFM.H23E1559D"><span>On the assimilation of satellite derived <span class="hlt">soil</span> <span class="hlt">moisture</span> in numerical weather prediction models</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Drusch, M.</p> <p>2006-12-01</p> <p>Satellite derived surface <span class="hlt">soil</span> <span class="hlt">moisture</span> data sets are readily available and have been used successfully in hydrological applications. In many operational numerical weather prediction systems the initial <span class="hlt">soil</span> <span class="hlt">moisture</span> conditions are analysed from the modelled background and 2 m temperature and relative humidity. This approach has proven its efficiency to improve surface latent and sensible heat fluxes and consequently the forecast on large geographical domains. However, since <span class="hlt">soil</span> <span class="hlt">moisture</span> is not always related to screen level variables, model errors and uncertainties in the forcing data can accumulate in root zone <span class="hlt">soil</span> <span class="hlt">moisture</span>. Remotely sensed surface <span class="hlt">soil</span> <span class="hlt">moisture</span> is directly linked to the model's uppermost <span class="hlt">soil</span> layer and therefore is a stronger constraint for the <span class="hlt">soil</span> <span class="hlt">moisture</span> analysis. Three data assimilation experiments with the Integrated Forecast System (IFS) of the European Centre for Medium-range Weather Forecasts (ECMWF) have been performed for the two months period of June and July 2002: A control run based on the operational <span class="hlt">soil</span> <span class="hlt">moisture</span> analysis, an open loop run with freely evolving <span class="hlt">soil</span> <span class="hlt">moisture</span>, and an experimental run incorporating bias corrected TMI (TRMM Microwave Imager) derived <span class="hlt">soil</span> <span class="hlt">moisture</span> over the southern United States through a nudging scheme using 6-hourly departures. Apart from the <span class="hlt">soil</span> <span class="hlt">moisture</span> analysis, the system setup reflects the operational forecast configuration including the atmospheric 4D-Var analysis. <span class="hlt">Soil</span> <span class="hlt">moisture</span> analysed in the nudging experiment is the most accurate estimate when compared against in-situ observations from the Oklahoma Mesonet. The corresponding forecast for 2 m temperature and relative humidity is almost as accurate as in the control experiment. Furthermore, it is shown that the <span class="hlt">soil</span> <span class="hlt">moisture</span> analysis influences local weather parameters including the planetary boundary layer height and cloud coverage. The transferability of the results to other satellite derived <span class="hlt">soil</span> <span class="hlt">moisture</span> data sets will be discussed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H23B1649J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H23B1649J"><span>Effects of Afforestation and Natural Revegetation on <span class="hlt">Soil</span> <span class="hlt">Moisture</span> Dynamics in Paired Watersheds in the Loess Plateau of China</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Jin, Z.; Guo, L.; Lin, H.; Wang, Y.; Chu, G.</p> <p>2017-12-01</p> <p>In this study, a paired of small watersheds, which are artificial forestland and natural grassland, respectively, were selected. The two watersheds have been set up since 1954 and the time of revegetation is more than 60 years. Their differences in event and seasonal dynamics of <span class="hlt">soil</span> <span class="hlt">moisture</span> were investigated and the effects of vegetation and landform were analyzed. Results showed that consecutive small events higher than 22 mm and single events higher than 16.6 mm could recharge the <span class="hlt">soil</span> <span class="hlt">moisture</span> of the two watersheds, but no rainfall event was observed to recharge the <span class="hlt">soil</span> <span class="hlt">moisture</span> of 100 cm within 2 weeks after rainfall initiation. Moreover, the two contrasting watersheds showed no difference in rainfall threshold for effective <span class="hlt">soil</span> <span class="hlt">moisture</span> replenishment and also had similar patterns of <span class="hlt">soil</span> water increment with the increase of initial <span class="hlt">soil</span> water content and rainfall intensity. The changing vegetation cover and coverage at different landforms (uphill slope land and downhill gully) showed the most significant impact on event and seasonal dynamics of <span class="hlt">soil</span> <span class="hlt">moisture</span>. The strong interception, evaporation and transpiration of tree canopy and understory vegetation in the gully of the forestland showed the most negative impacts on <span class="hlt">soil</span> <span class="hlt">moisture</span> replenishment. Moreover, dense surface grass biomass (living and dead) in the grassland also showed negative impacts on effective <span class="hlt">soil</span> <span class="hlt">moisture</span> recharge. Landform itself showed no significant impact on event <span class="hlt">soil</span> <span class="hlt">moisture</span> dynamics through changing the initial <span class="hlt">soil</span> water content and <span class="hlt">soil</span> texture, while site differences in slope gradient and <span class="hlt">soil</span> temperature could <span class="hlt">affect</span> the seasonal <span class="hlt">soil</span> water content. During the growing season of May-October, the forestland showed 1.3% higher <span class="hlt">soil</span> water content than that of the grassland in the landform of uphill slope land; while in the landform of downhill gully, the grassland showed 4.3% higher <span class="hlt">soil</span> water content than that of the forestland. Many studies have predicted that there will be</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018PApGe.175.1187V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018PApGe.175.1187V"><span>Relation Between the Rainfall and <span class="hlt">Soil</span> <span class="hlt">Moisture</span> During Different Phases of Indian Monsoon</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Varikoden, Hamza; Revadekar, J. V.</p> <p>2018-03-01</p> <p><span class="hlt">Soil</span> <span class="hlt">moisture</span> is a key parameter in the prediction of southwest monsoon rainfall, hydrological modelling, and many other environmental studies. The studies on rel