WorldWideScience

Sample records for spatial soil moisture

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

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    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...

  2. Spatial variability of soil moisture retrieved by SMOS satellite

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    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

  3. Spatial Variation of Soil Type and Soil Moisture in the Regional Atmospheric Modeling System

    Energy Technology Data Exchange (ETDEWEB)

    Buckley, R.

    2001-06-27

    Soil characteristics (texture and moisture) are typically assumed to be initially constant when performing simulations with the Regional Atmospheric Modeling System (RAMS). Soil texture is spatially homogeneous and time-independent, while soil moisture is often spatially homogeneous initially, but time-dependent. This report discusses the conversion of a global data set of Food and Agriculture Organization (FAO) soil types to RAMS soil texture and the subsequent modifications required in RAMS to ingest this information. Spatial variations in initial soil moisture obtained from the National Center for Environmental Predictions (NCEP) large-scale models are also introduced. Comparisons involving simulations over the southeastern United States for two different time periods, one during warmer, more humid summer conditions, and one during cooler, dryer winter conditions, reveals differences in surface conditions related to increases or decreases in near-surface atmospheric moisture con tent as a result of different soil properties. Three separate simulation types were considered. The base case assumed spatially homogeneous soil texture and initial soil moisture. The second case assumed variable soil texture and constant initial soil moisture, while the third case allowed for both variable soil texture and initial soil moisture. The simulation domain was further divided into four geographically distinct regions. It is concluded there is a more dramatic impact on thermodynamic variables (surface temperature and dewpoint) than on surface winds, and a more pronounced variability in results during the summer period. While no obvious trends in surface winds or dewpoint temperature were found relative to observations covering all regions and times, improvement in surface temperatures in most regions and time periods was generally seen with the incorporation of variable soil texture and initial soil moisture.

  4. Seedling establishment and physiological responses to temporal and spatial soil moisture changes

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    Jeremy Pinto; John D. Marshall; Kas Dumroese; Anthony S. Davis; Douglas R. Cobos

    2016-01-01

    In many forests of the world, the summer season (temporal element) brings drought conditions causing low soil moisture in the upper soil profile (spatial element) - a potentially large barrier to seedling establishment. We evaluated the relationship between initial seedling root depth, temporal and spatial changes in soil moisture during drought after...

  5. Linking Spatial and Temporal Patterns of Soil Moisture with Upland Soil Iron Reduction

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    Hodges, C. A.; Markewitz, D.; Thompson, A.

    2015-12-01

    Iron minerals play important roles in governing soil nutrient availability and carbon dynamics. Periods of intermittent anoxia (low-oxygen) in upland soils can drive microbial reduction and dissolution of iron minerals. However, quantifying ecosystem-scale iron reduction in upland soils is challenging. The key condition necessary for soil iron reduction is water saturation of soil micropores, even if the entire soil profile is not flooded. We assessed soil moisture and texture across three first-order watersheds at the Calhoun Critical Zone Observatory in South Carolina, USA over one year using electromagnetic induction (EMI). From these point measurements, we have created monthly maps of interpolated soil moisture. From the EMI data, we found that locations that remain relatively wet or dry throughout the year are not related to hill-slope position but to differences in soil texture along a catena. Across a gradient of soil moisture and texture (based on soil conductivity from the EMI probe) we installed passive redox sensors and conducted in situ iron reduction experiments. This data will be presented and the relationships between iron reduction, the spatial distribution of soil moisture/clay content, and the significance of these data with respect to soil carbon cycling will be discussed.

  6. Spatial Variability of Soil Properties and its Impact on Simulated Surface Soil Moisture Patterns

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    Korres, W.; Bothe, T.; Reichenau, T. G.; Schneider, K.

    2015-12-01

    The spatial variability of soil properties (particle size distribution, PSD, and bulk density, BD) has large effects on the spatial variability of soil moisture and therefore on plant growth and surface exchange processes. In model studies, soil properties from soil maps are considered homogeneous over mapping units, which neglects the small scale variability of soil properties and leads to underestimated small scale variability of simulated soil moisture. This study focuses on the validation of spatial variability of simulated surface soil moisture (SSM) in a winter wheat field in Western Germany using the eco-hydrological simulation system DANUBIA. SSM measurements were conducted at 20 different sampling points and nine different dates in 2008. Frequency distributions of BD and PSD were derived from an independent dataset (n = 486) of soil physical properties from Germany and the USA. In the simulations, BD and PSD were parameterized according to these frequency distributions. Mean values, coefficients of variation and frequency distributions of simulated SSM were compared to the field measurements. Using the heterogeneous model parameterization, up to 76 % of the frequency distribution of the measured SSM can be explained. Furthermore, the results show that BD has a larger impact on the variability of SSM than PSD. The introduced approach can be used for simulating mean SSM and SSM variability more accurately and can form the basis for a spatially heterogeneous parameterization of soil properties in mesoscale models.

  7. Spatial variations of shallow and deep soil moisture in the semi-arid Loess Plateau, China

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    L. Yang

    2012-09-01

    Full Text Available Soil moisture in deep soil layers is an important relatively stable water resource for vegetation growth in the semi-arid Loess Plateau of China. Characterizing the spatial variations of deep soil moisture with respect to the topographic conditions has significant importance for vegetation restoration. In this study, we focused on analyzing the spatial variations and factors influencing soil moisture content (SMC in shallow (0–2 m and deep (2–8 m soil layers, based on soil moisture observations in the Longtan watershed, Dingxi, Gansu province. The vegetation type of each sampling site for each comparison is same and varies by different positions, gradients, or aspects. The following discoveries were captured: (1 in comparison with shallow SMC, slope position and slope aspect may affect shallow soil moisture more than deep layers, while slope gradient affects both shallow and deep soil moisture significantly. This indicates that a great difference in deep soil hydrological processes between shallow and deep soil moisture remains that can be attributed to the introduced vegetation and topography. (2 A clear negative relationship exists between vegetation growth condition and deep soil moisture, which indicates that plants under different growing conditions may differ in consuming soil moisture, thus causing higher spatial variations in deep soil moisture. (3 The dynamic role of slope position and slope aspect on deep soil moisture has been changed due to large-scale plantation in semi-arid environment. Consequently, vegetation growth conditions and slope gradients may become the key factors dominating the spatial variations in deep soil moisture.

  8. Spatial patterns of soil moisture from two regional monitoring networks in the United States

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    Wang, Tiejun; Liu, Qin; Franz, Trenton E.; Li, Ruopu; Lang, Yunchao; Fiebrich, Christopher A.

    2017-09-01

    Understanding soil moisture spatial variability (SMSV) at regional scales is of great value for various purposes; however, relevant studies are still limited and have yielded inconsistent findings about the primary controls on regional SMSV. To further address this issue, long-term soil moisture data were retrieved from two large scale monitoring networks located in the continental United States, including the Michigan Automated Weather Network and the Oklahoma Mesonet. To evaluate different controls on SMSV, supporting datasets, which contained data on climate, soil, topography, and vegetation, were also compiled from various sources. Based on temporal stability analysis, the results showed that the mean relative difference (MRD) of soil moisture was more correlated with soil texture (e.g., negative correlations between MRD and sand fraction, and positive ones between MRD and silt and clay fractions) than with meteorological forcings in both regions, which differed from the traditional notion that meteorological forcings were the dominant controls on regional SMSV. Moreover, the results revealed that contrary to the previous conjecture, the use of soil moisture temporal anomaly did not reduce the impacts of static properties (e.g., soil properties) on soil moisture temporal dynamics. Instead, it was found that the magnitude of soil moisture temporal anomaly was mainly negatively correlated with sand fraction and positively with silt and clay fractions in both regions. Finally, the relationship between the spatial average and standard deviation of soil moisture as well as soil moisture temporal anomaly was investigated using the data from both networks. The field data showed that the relationship for both soil moisture and soil moisture temporal anomaly was more affected by soil texture than by climatic conditions (e.g., precipitation). The results of this study provided strong field evidence that local factors (e.g., soil properties) might outweigh regional

  9. The Relationship between an Invasive Shrub and Soil Moisture: Seasonal Interactions and Spatially Covarying Relations

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    Yuhong He

    2014-09-01

    Full Text Available Recent studies indicate that positive relationships between invasive plants and soil can contribute to further plant invasions. However, it remains unclear whether these relations remain unchanged throughout the growing season. In this study, spatial sequences of field observations along a transect were used to reveal seasonal interactions and spatially covarying relations between one common invasive shrub (Tartarian Honeysuckle, Lonicera tatarica and soil moisture in a tall grassland habitat. Statistical analysis over the transect shows that the contrast between soil moisture in shrub and herbaceous patches vary with season and precipitation. Overall, a negatively covarying relationship between shrub and soil moisture (i.e., drier surface soils at shrub microsites exists during the very early growing period (e.g., May, while in summer a positively covarying phenomenon (i.e., wetter soils under shrubs is usually evident, but could be weakened or vanish during long precipitation-free periods. If there is sufficient rainfall, surface soil moisture and leaf area index (LAI often spatially covary with significant spatial oscillations at an invariant scale (which is governed by the shrub spatial pattern and is about 8 m, but their phase relation in space varies with season, consistent with the seasonal variability of the co-varying phenomena between shrub invasion and soil water content. The findings are important for establishing a more complete picture of how shrub invasion affects soil moisture.

  10. Assimilation of Spatially Sparse In Situ Soil Moisture Networks into a Continuous Model Domain

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    Gruber, A.; Crow, W. T.; Dorigo, W. A.

    2018-02-01

    Growth in the availability of near-real-time soil moisture observations from ground-based networks has spurred interest in the assimilation of these observations into land surface models via a two-dimensional data assimilation system. However, the design of such systems is currently hampered by our ignorance concerning the spatial structure of error afflicting ground and model-based soil moisture estimates. Here we apply newly developed triple collocation techniques to provide the spatial error information required to fully parameterize a two-dimensional (2-D) data assimilation system designed to assimilate spatially sparse observations acquired from existing ground-based soil moisture networks into a spatially continuous Antecedent Precipitation Index (API) model for operational agricultural drought monitoring. Over the contiguous United States (CONUS), the posterior uncertainty of surface soil moisture estimates associated with this 2-D system is compared to that obtained from the 1-D assimilation of remote sensing retrievals to assess the value of ground-based observations to constrain a surface soil moisture analysis. Results demonstrate that a fourfold increase in existing CONUS ground station density is needed for ground network observations to provide a level of skill comparable to that provided by existing satellite-based surface soil moisture retrievals.

  11. Stemflow affects spatial soil moisture fields differently in summer and winter

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    Hildebrandt, Anke; Friesen, Jan; Kögler, Simon

    2014-05-01

    Stemflow is only a minor component of net precipitation, but because it acts as a point input, it has the potential to strongly shape the soil moisture patterns below trees and induce vertical fluxes as well as groundwater recharge. However, there is little research on the evolution of soil moisture patterns around trees over prolonged periods of time. In this paper we investigate in a beech dominated forest in central Germany the dynamics of surface soil moisture in proximal (radius around the tree trunks. Data were collected over a nine months period, including 10 weeks of intensive event based throughfall and stemflow monitoring. During the growing season, water content near the tree trunks was almost always lower compared to greater distance from the tree, which may be related to both lower root water uptake and higher throughfall in regions with thinner crowns at mid-distance between trees. During the growing season, soil water content near the beech trees only exceeded levels at greater distance during few rain events with substantial stemflow (15-20% of rain). However, during the wintertime, soil moisture near the trees was higher than at greater distances, in particular in response to rain events after leaf senescence. The variance of soil moisture at tree-distant locations is highest at intermediate mean moisture levels, while variance is low at both very high and very low mean soil water content. No such pattern is evident for the region near the trees, where both the highest and lowest variances occur at intermediate soil water contents. Our results indicate that the areas near tree trunks are a source of substantial spatial variation in the soil moisture field below trees. The elevated soil moisture in fall and early winter suggests a strong role of stemflow for shaping soil moisture patterns during mild winter periods.

  12. MAPPING SPATIAL MOISTURE CONTENT OF UNSATURATED AGRICULTURAL SOILS WITH GROUND-PENETRATING RADAR

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    O. Shamir

    2016-06-01

    Full Text Available Soil subsurface moisture content, especially in the root zone, is important for evaluation the influence of soil moisture to agricultural crops. Conservative monitoring by point-measurement methods is time-consuming and expensive. In this paper we represent an active remote-sensing tool for subsurface spatial imaging and analysis of electromagnetic physical properties, mostly water content, by ground-penetrating radar (GPR reflection. Combined with laboratory methods, this technique enables real-time and highly accurate evaluations of soils' physical qualities in the field. To calculate subsurface moisture content, a model based on the soil texture, porosity, saturation, organic matter and effective electrical conductivity is required. We developed an innovative method that make it possible measures spatial subsurface moisture content up to a depth of 1.5 m in agricultural soils and applied it to two different unsaturated soil types from agricultural fields in Israel: loess soil type (Calcic haploxeralf, common in rural areas of southern Israel with about 30% clay, 30% silt and 40% sand, and hamra soil type (Typic rhodoxeralf, common in rural areas of central Israel with about 10% clay, 5% silt and 85% sand. Combined field and laboratory measurements and model development gave efficient determinations of spatial moisture content in these fields. The environmentally friendly GPR system enabled non-destructive testing. The developed method for measuring moisture content in the laboratory enabled highly accurate interpretation and physical computing. Spatial soil moisture content to 1.5 m depth was determined with 1–5% accuracy, making our method useful for the design of irrigation plans for different interfaces.

  13. Can the ASAR Global Monitoring Mode Product Adequately Capture Spatial Soil Moisture Variability?

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    Mladenova, I.; Lakshmi, V.; Walker, J.; Panciera, R.; Wagner, W.; Doubkova, M.

    2008-12-01

    Global soil moisture (SM) monitoring in the past several decades has been undertaken mainly at coarse spatial resolution, which is not adequate for addressing small-scale phenomena and processes. The currently operational Advanced Microwave Scanning Radiometer (NASA) and future planned missions such as the Soil Moisture and Ocean Salinity (ESA) and the Soil Moisture Active Passive (NASA) will remain resolution limited. Finer scale soil moisture estimates can be achieved either by down-scaling the available coarse resolution radiometer and scatterometer (i.e. ERS1/2, ASCAT) observations or by using high resolution active microwave SAR type systems (typical resolution is in the order of meters). Considering the complex land surface - backscatter signal interaction, soil moisture inversion utilizing active microwave observations is difficult and generally needs supplementary data. Algorithms based on temporal change detection offer an alternative less complex approach for deriving (and disaggregating coarse) soil moisture estimates. Frequent monitoring and low frequency range along with a high pixel resolution are essential preconditions when characterizing spatial and temporal soil moisture variability. An alternative active system that meets these requirements is the Advance Synthetic Aperture Radar (ASAR) on ENVISAT [C-band, global, 1 km in Global Monitoring (GM) Mode]. The Vienna University of Technology (TU Wien) has developed a 1 km soil moisture product using the temporal change detection approach and the ASAR GM. The TU Wien SM product sensitivity was evaluated at two scales: point (using in situ data from permanent soil moisture stations) and regional [using ground measured data and aircraft estimates derived from the Polarimetric L-band Microwave Radiometer (PLMR)] over the National Airborne Field Experiment (NAFE'05) area located in the Goulburn catchment, SE Australia. The month long (November 2005) campaign was undertaken in a region predominantly covered

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

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    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

  15. Integration of GIS, Geostatistics, and 3-D Technology to Assess the Spatial Distribution of Soil Moisture

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    Betts, M.; Tsegaye, T.; Tadesse, W.; Coleman, T. L.; Fahsi, A.

    1998-01-01

    The spatial and temporal distribution of near surface soil moisture is of fundamental importance to many physical, biological, biogeochemical, and hydrological processes. However, knowledge of these space-time dynamics and the processes which control them remains unclear. The integration of geographic information systems (GIS) and geostatistics together promise a simple mechanism to evaluate and display the spatial and temporal distribution of this vital hydrologic and physical variable. Therefore, this research demonstrates the use of geostatistics and GIS to predict and display soil moisture distribution under vegetated and non-vegetated plots. The research was conducted at the Winfred Thomas Agricultural Experiment Station (WTAES), Hazel Green, Alabama. Soil moisture measurement were done on a 10 by 10 m grid from tall fescue grass (GR), alfalfa (AA), bare rough (BR), and bare smooth (BS) plots. Results indicated that variance associated with soil moisture was higher for vegetated plots than non-vegetated plots. The presence of vegetation in general contributed to the spatial variability of soil moisture. Integration of geostatistics and GIS can improve the productivity of farm lands and the precision of farming.

  16. A spatial Coherent Global Soil Moisture Product with Improved Temporal Resolution

    NARCIS (Netherlands)

    de Jeu, R.A.M.; Holmes, T.R.H.; Parinussa, R.M.; Owe, M.

    2014-01-01

    Global soil moisture products that are completely independent of any type of ancillary data and solely rely on satellite observations are presented. Additionally, we further develop an existing downscaling technique that enhances the spatial resolution of such products to approximately 11. km. These

  17. An intercomparison of remotely sensed soil moisture products at various spatial scales over the Iberian Peninsula

    NARCIS (Netherlands)

    Parinussa, R.M.; Yilmaz, M.T.; Anderson, M.; Hain, C.; de Jeu, R.A.M.

    2013-01-01

    Soil moisture (SM) can be retrieved from active microwave (AM), passive microwave (PM) and thermal infrared (TIR) observations, each having unique spatial and temporal coverages. A limitation of TIR-based retrievals is a dependence on cloud-free conditions, whereas microwave retrievals are almost

  18. Spatial and temporal monitoring of soil moisture using surface electrical resistivity tomography in Mediterranean soils

    NARCIS (Netherlands)

    Alamry, Abdulmohsen S.; van der Meijde, Mark; Noomen, Marleen; Addink, Elisabeth A.|info:eu-repo/dai/nl/224281216; van Benthem, Rik; de Jong, Steven M.|info:eu-repo/dai/nl/120221306

    2017-01-01

    ERT techniques are especially promising in (semi-arid) areas with shallow and rocky soils where other methods fail to produce soil moisture maps and to obtain soil profile information. Electrical Resistivity Tomography (ERT) was performed in the Peyne catchment in southern France at four sites

  19. Quantifying the heterogeneity of soil compaction, physical soil properties and soil moisture across multiple spatial scales

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    Coates, Victoria; Pattison, Ian; Sander, Graham

    2016-04-01

    England's rural landscape is dominated by pastoral agriculture, with 40% of land cover classified as either improved or semi-natural grassland according to the Land Cover Map 2007. Since the Second World War the intensification of agriculture has resulted in greater levels of soil compaction, associated with higher stocking densities in fields. Locally compaction has led to loss of soil storage and an increased in levels of ponding in fields. At the catchment scale soil compaction has been hypothesised to contribute to increased flood risk. Previous research (Pattison, 2011) on a 40km2 catchment (Dacre Beck, Lake District, UK) has shown that when soil characteristics are homogeneously parameterised in a hydrological model, downstream peak discharges can be 65% higher for a heavy compacted soil than for a lightly compacted soil. However, at the catchment scale there is likely to be a significant amount of variability in compaction levels within and between fields, due to multiple controlling factors. This research focusses in on one specific type of land use (permanent pasture with cattle grazing) and areas of activity within the field (feeding area, field gate, tree shelter, open field area). The aim was to determine if the soil characteristics and soil compaction levels are homogeneous in the four areas of the field. Also, to determine if these levels stayed the same over the course of the year, or if there were differences at the end of the dry (October) and wet (April) periods. Field experiments were conducted in the River Skell catchment, in Yorkshire, UK, which has an area of 120km2. The dynamic cone penetrometer was used to determine the structural properties of the soil, soil samples were collected to assess the bulk density, organic matter content and permeability in the laboratory and the Hydrosense II was used to determine the soil moisture content in the topsoil. Penetration results show that the tree shelter is the most compacted and the open field area

  20. L-band HIgh Spatial Resolution Soil Moisture Mapping using SMALL UnManned Aerial Systems

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    Dai, E.; Venkitasubramony, A.; Gasiewski, A. J.; Stachura, M.; Elston, J. S.; Walter, B.; Lankford, D.; Corey, C.

    2017-12-01

    Soil moisture is of fundamental importance to many hydrological, biological and biogeochemical processes, plays an important role in the development and evolution of convective weather and precipitation, water resource management, agriculture, and flood runoff prediction. The launch of NASA's Soil Moisture Active/Passive (SMAP) mission in 2015 provided new passive global measurements of soil moisture and surface freeze/thaw state at fixed crossing times and spatial resolutions of 36 km. However, there exists a need for measurements of soil moisture on much smaller spatial scales and arbitrary diurnal times for SMAP validation, precision agriculture and evaporation and transpiration studies of boundary layer heat transport. The Lobe Differencing Correlation Radiometer (LDCR) provides a means of mapping soil moisture on spatial scales as small as several meters. Compared with other methods of validation based on either in-situ measurements [1,2] or existing airborne sensors suitable for manned aircraft deployment [3], the integrated design of the LDCR on a lightweight small UAS (sUAS) is capable of providing sub-watershed ( km scale) coverage at very high spatial resolution ( 15 m) suitable for scaling studies, and at comparatively low operator cost. To demonstrate the LDCR several flights had been performed during field experiments at the Canton Oklahoma Soilscape site and Yuma Colorado Irrigation Research Foundation (IRF) site in 2015 and 2016, respectively, using LDCR Revision A and Tempest sUAS. The scientific intercomparisons of LDCR retrieved soil moisture and in-situ measurements will be presented. LDCR Revision B has been built and integrated into SuperSwift sUAS and additional field experiments will be performed at IRF in 2017. In Revision B the IF signal is sampled at 80 MS/s to enable digital correlation and RFI mitigation capabilities, in addition to analog correlation. [1] McIntyre, E.M., A.J. Gasiewski, and D. Manda D, "Near Real-Time Passive C

  1. Spatial Scaling Assessment of Surface Soil Moisture Estimations Using Remotely Sensed Data for Precision Agriculture

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    Hassan Esfahani, L.; Torres-Rua, A. F.; Jensen, A.; McKee, M.

    2014-12-01

    Airborne and Landsat remote sensing are promising technologies for measuring the response of agricultural crops to variations in several agricultural inputs and environmental conditions. Of particular significance to precision agriculture is surface soil moisture, a key component of the soil water balance, which addresses water and energy exchanges at the surface/atmosphere interface and affects vegetation health. Its estimation using the spectral reflectance of agricultural fields could be of value to agricultural management decisions. While top soil moisture can be estimated using radiometric information from aircraft or satellites and data mining techniques, comparison of results from two different aerial platforms might be complicated because of the differences in spatial scales (high resolution of approximately 0.15m versus coarser resolutions of 30m). This paper presents a combined modeling and scale-based approach to evaluate the impact of spatial scaling in the estimation of surface soil moisture content derived from remote sensing data. Data from Landsat 7 ETM+, Landsat 8 OLI and AggieAirTM aerial imagery are utilized. AggieAirTM is an airborne remote sensing platform developed by Utah State University that includes an autonomous Unmanned Aerial System (UAS) which captures radiometric information at visual, near-infrared, and thermal wavebands at spatial resolutions of 0.15 m or smaller for the optical cameras and about 0.6 m or smaller for the thermal infrared camera. Top soil moisture maps for AggieAir and Landsat are developed and statistically compared at different scales to determine the impact in terms of quantitative predictive capability and feasibility of applicability of results in improving in field management.

  2. Geophysical characterization of soil moisture spatial patterns in a tillage experiment

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    Martinez, G.; Vanderlinden, K.; Giráldez, J. V.; Muriel, J. L.

    2009-04-01

    Knowledge on the spatial soil moisture pattern can improve the characterisation of the hydrological response of either field-plots or small watersheds. Near-surface geophysical methods, such as electromagnetic induction (EMI), provide a means to map such patterns using non-invasive and non-destructive measurements of the soil apparent electrical conductivity (ECa. In this study ECa was measured using an EMI sensor and used to characterize spatially the hydrologic response of a cropped field to an intense shower. The study site is part of a long-term tillage experiment in Southern Spain in which Conventional Tillage (CT), Direct Drilling (DD) and Minimum Tillage (MT) are being evaluated since 1982. Soil ECa was measured before and after a rain event of 115 mm, near the soil surface and at deeper depth (ECas and ECad, respectively) using the EM38-DD EMI sensor. Simultaneously, elevation data were collected at each sampling point to generate a Digital Elevation Model (DEM). Soil moisture during the first survey was close to permanent wilting point and near field capacity during the second survey. For the first survey, both ECas and ECad, were higher in the CT and MT than in the DD plots. After the rain event, rill erosion appeared only in CT and MT plots were soil was uncovered, matching the drainage lines obtained from the DEM. Apparent electrical conductivity increased all over the field plot with higher increments in the DD plots. These plots showed the highest ECas and ECad values, in contrast to the spatial pattern found during the first sampling. Difference maps obtained from the two ECas and ECad samplings showed a clear difference between DD plots and CT and MT plots due to their distinct hydrologic response. Water infiltration was higher in the soil of the DD plots than in the MT and CT plots, as reflected by their ECad increment. Higher ECa increments were observed in the depressions of the terrain, where water and sediments accumulated. On the contrary, the

  3. A High-Temporal and Spatial Resolution Soil Moisture and Soil Temperature Network In Iowa Using Wireless Links

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    Niemeier, J. J.; Kruger, A.; Krajewki, W. F.; Eichinger, W. E.; Hornbuckle, B. K.; Cunha, L.

    2007-12-01

    Over the past year we have created an in-situ soil moisture and soil temperature network in a 200 acre agricultural plot at Ames, Iowa. This work is part of a collaborative effort between researchers at The University of Iowa, and Iowa State University. The purpose of the network is to provide high temporal and spatial resolution soil moisture and soil temperature data to validate remotely-sensed observations of the terrestrial water cycle. This is part of a larger effort by the authors and collaborators to improve the quantitative value of remotely-sensed observations of the water cycle. In addition to the soil moisture and soil temperature measurements, detailed precipitation data, and atmospheric data such as air temperature, humidity, pressure, wind direction and velocity, and solar radiation data are collected. The current soil moisture network consists of 10 Iowa and Iowa State stations, each equipped with seven pairs of soil moisture and soil temperature sensors. In the future, the network will be expanded to 15 stations. At each of the 10 station the sensors pairs are deployed at depths of 1.5, 4.5, 15, 30, and 60 cm to provide a vertical profile of soil moisture and soil temperature. Prior to installation we calibrated the soil temperature sensors to within 0.1 degree Celsius. The time-domain reflectometry soil moisture measurements are adjusted for local soil conditions. At each of the 10 stations, data are collected every 10 minutes. The data are transmitted wirelessly with low power radio links to a central location. The system started collecting data at the beginning of July, 2007. One of the challenges we faced is how to provide reliable solar power to the wireless nodes, since the current crop, corn, grows up to 3 m tall, and casts dense shadows. The corn also significantly attenuates the radios signals, and the radios fell far short of their advertized ranges. Consequently, we had to use high-gain antennas, and robust retransmit communication modes

  4. Modeling spatial and seasonal soil moisture in a semi arid hillslope: The impact of integrating soil surface seal parameters

    Science.gov (United States)

    Sela, Shai; Svoray, Tal; Assouline, Shmuel

    2010-05-01

    Modeling hillslope hydrology and the complex and coupled reaction of runoff processes to rainfall, lies in the focus of a growing number of research studies. The ability to characterize and understand the mechanisms underlying the complex hillslope soil moisture patterns, which trigger spatially variable non linear runoff initiation, still remains a current hydrological challenge especially in ungauged catchments. In humid climates, connectivity of transient moisture patches was suggested as a unifying concept for studying thresholds for subsurface flow and redistribution of soil moisture at the hillslope scale. In semiarid areas, however, transient moisture patches control also the differentiation between evaporation and surface runoff and the ability to identify a unifying concept controlling the large variability of soil moisture at the hillslope scale remains an open research gap. At the LTER Lehavim site in the center of Israel (31020' N, 34045' E) a typical hillslope (0.115 km2) was chosen offering different aspects and a classic geomorphologic banding. The annual rainfall is 290 mm, the soils are brown lithosols and arid brown loess and the dominant rock formations are Eocenean limestone and chalk with patches of calcrete. The vegetation is characterised by scattered dwarf shrubs (dominant species Sarcopoterium spinosum) and patches of herbaceous vegetation, mostly annuals, are spread between rocks and dwarf shrubs. An extensive spatial database of soil hydraulic and environmental parameters (e.g. slope, radiation, bulk density) was measured in the field and interpolated to continuous maps using geostatistical techniques and physically based modelling. To explore the effect of soil surface sealing, Mualem and Assouline (1989) equations describing the change in hydraulic parameters resulting from soil seal formation were applied. Two simple indices were developed to describe local evaporation values and contribution of water from rock outcrops to the soil

  5. Spatial and temporal variability of soil moisture in a restored reach of an Alpine river

    Science.gov (United States)

    Luster, Jörg

    2010-05-01

    In order to assess the effects of river restoration on water quality, the biogeochemical functions of restored river reaches have to be quantified, and soil moisture is a key environmental variable controlling this functionality. Restored sections of rivers often are characterized by a dynamic mosaic of riparian zones with varying exposure to flooding. In this presentation, the spatial and temporal variability of soil moisture in riparian soils of a restored reach of the Alpine river Thur in northeastern Switzerland is shown. The study was part of the interdisciplinary project cluster RECORD, which was initiated to advance the mechanistic understanding of coupled hydrological and ecological processes in river corridors. The studied river reach comprised the following three functional processing zones (FPZ) representing a lateral successional gradient with decreasing hydrological connectivity (i.e. decreasing flooding frequency and duration). (i) The grass zone developed naturally on a gravel bar after restoration of the channelized river section (mainly colonized by canary reed grass Phalaris arundinacae). The soil is loamy sand to sandy loam composed of up to 80 cm thick fresh sediments trapped and stabilized by the grass roots. (ii) The bush zone is composed of young willow trees (Salix viminalis) planted during restoration to stabilize older overbank deposits with a loamy fine earth. (iii) The mixed forest is a mature riparian hardwood forest with ash and maple as dominant trees developed on older overbank sediments with a silty loamy fine earth. The study period was between spring 2009 and winter 2009/2010 including three flood events in June, July and December 2009. The first and third flood inundated the grass zone and lower part of the bush zone while the second flood was bigger and swept through all the FPZs. Water contents in several soil depths were measured continuously in 30 minute intervals using Decagon EC-5 and EC-TM sensors. There were six spatial

  6. Spatial downscaling of SMAP soil moisture using MODIS land surface temperature and NDVI during SMAPVEX15

    Science.gov (United States)

    The SMAP (Soil Moisture Active Passive) mission provides global surface soil moisture product at 36 km resolution from its L-band radiometer. While the coarse resolution is satisfactory to many applications there are also a lot of applications which would benefit from a higher resolution soil moistu...

  7. On the Critical Behaviour of Observed and Simulated Spatial Soil Moisture Fields during SGP97

    Directory of Open Access Journals (Sweden)

    Mekonnen Gebremichael

    2010-09-01

    Full Text Available The aircraft-based ESTAR soil moisture fields from the Southern Great Plains 1997 (SGP97 Hydrology Experiment are compared to the simulated ones obtained by Bertoldi et al. [1] with the GEOtop model [2], with a particular focus on their capability in capturing the critical point behaviour in their space-time dynamics (see [3]. The critical point behaviour should denote the transition of soil moisture spatial patterns from an unorganized to organized appearance, as conditions become wetter. The study region is the Little Washita watershed, located in the southwest Oklahoma, in the Southern Great Plains region of the USA. The case study takes place from June 27 to July 16 and encompasses wetting and drying cycles allowing for exploring the behaviour under transient conditions. Results show that the critical probability value is 0.85 for GEOtop, and 0.80 for ESTAR. The GEOtop patterns appear more fragmented, being more reluctant to organization, as confirmed by the higher value of critical probability. Such behaviour is probably inherited by the model’s parameterization: land use and soil classes impose additional spatial structures to those related to the meteorological forcings and the hillslope morphology, driving to higher degrees of heterogeneity.

  8. Spatial patterns of preconsolidation pressure and soil moisture along transects in two directions under coffee

    Directory of Open Access Journals (Sweden)

    Ivoney Gontijo

    2011-08-01

    Full Text Available Information on the spatial structure of soil physical and structural properties is needed to evaluate the soil quality. The purpose of this study was to investigate the spatial behavior of preconsolidation pressure and soil moisture in six transects, three selected along and three across coffee rows, at three different sites under different tillage management systems. The study was carried out on a farm, in Patrocinio, state of Minas Gerais, in the Southeast of Brazil (18 º 59 ' 15 '' S; 46 º 56 ' 47 '' W; 934 m asl. The soil type is a typic dystrophic Red Latosol (Acrustox and consists of 780 g kg-1 clay; 110 g kg-1 silt and 110 g kg-1 sand, with an average slope of 3 %. Undisturbed soil cores were sampled at a depth of 0.10-0.13 m, at three different points within the coffee plantation: (a from under the wheel track, where equipment used in farm operations passes; (b in - between tracks and (c under the coffee canopy. Six linear transects were established in the experimental area: three transects along and three across the coffee rows. This way, 161 samples were collected in the transect across the coffee rows, from the three locations, while 117 samples were collected in the direction along the row. The shortest sampling distance in the transect across the row was 4 m, and 0.5 m for the transect along the row. No clear patterns of the preconsolidation pressure values were observed in the 200 m transect. The results of the semivariograms for both variables indicated a high nugget value and short range for the studied parameters of all transects. A cyclic pattern of the parameters was observed for the across-rows transect. An inverse relationship between preconsolidation pressure and soil moisture was clearly observed in the samples from under the track, in both directions.

  9. Spatial and temporal variability of soil temperature, moisture and surface soil properties

    Science.gov (United States)

    Hajek, B. F.; Dane, J. H.

    1993-01-01

    The overall objectives of this research were to: (l) Relate in-situ measured soil-water content and temperature profiles to remotely sensed surface soil-water and temperature conditions; to model simultaneous heat and water movement for spatially and temporally changing soil conditions; (2) Determine the spatial and temporal variability of surface soil properties affecting emissivity, reflectance, and material and energy flux across the soil surface. This will include physical, chemical, and mineralogical characteristics of primary soil components and aggregate systems; and (3) Develop surface soil classes of naturally occurring and distributed soil property assemblages and group classes to be tested with respect to water content, emissivity and reflectivity. This document is a report of studies conducted during the period funded by NASA grants. The project was designed to be conducted over a five year period. Since funding was discontinued after three years, some of the research started was not completed. Additional publications are planned whenever funding can be obtained to finalize data analysis for both the arid and humid locations.

  10. Spatial modelling of the variability of the soil moisture regime at the landscape scale in the southern Qilian Mountains, China

    Science.gov (United States)

    Zhao, C.-Y.; Qi, P.-C.; Feng, Z.-D.

    2009-10-01

    The spatial and temporal variability of the soil moisture status gives an important base for the assessment of ecological (for restoration) and economic (for agriculture) conditions at micro- and meso-scales. It is also an essential input into many hydrological processes models. However, there has been a lack of effective methods for its estimation in the study area. The aim of this study was to determine the relationship between the soil moisture status and precipitation and topographic factors. First, this study compared a linear regression model with interpolating models for estimating monthly mean precipitation and selected the linear regression model to simulate the temporal-spatial variability of precipitation in the southern Qilian Mountainous areas of the Heihe River Basin. Combining topographic index with the distribution of precipitation, we calculated the soil moisture regime in the Pailugou catchment, one representative comprehensive research catchment. The modeled results were tested by the observed soil water content for different times. The correlation coefficient between the modeled soil moisture status and the observed soil water content is quite high (e.g. R2=0.76 in June), assuring our confidence in the spatially-modeled results of the soil moisture status. The method was applied to the southern Qilian Mountainous regions. The results showed that the modelled distribution of the soil moisture status reflected the interplay of the local and landscape climate processes. The driest sites occur on some ridges in northern part and western part of the study area, which are very small catchment areas and of low precipitation rates; the wettest are registered in the low river valley of the Heihe River and its major tributaries are in the eastern part due to large accumulating flow areas and higher precipitation rates. Temporally, the bigger variation of the soil moisture status in the study occurs in July and smaller difference appears in May.

  11. Spatial Heterogeneity of Soil Moisture and the Scale Variability of Its Influencing Factors: A Case Study in the Loess Plateau of China

    OpenAIRE

    Feng, Qiang; Zhao, Wenwu; Qiu, Yang; Zhao, Mingyue; Zhong, Lina

    2013-01-01

    Soil moisture is an important factor for vegetation restoration and ecosystem sustainability in the Loess Plateau of China. The strong spatial heterogeneity of soil moisture is controlled by many environmental factors, including topography and land use. Moreover, the spatial patterns and soil hydrological processes depend on the scale of the site being investigated, which creates a challenge for soil moisture forecasts. This study was conducted at two scales: watershed and small watershed. Th...

  12. Spatial Variability of Soil Moisture and the Validation of Remote Sensing Products in a Unique Beach Environment

    Science.gov (United States)

    Rogers, J.; Berg, A. A.

    2010-12-01

    Soil water conditions are crucial for understanding the exchange of energy and mass at the earth's surface. The need for a better description of the heterogeneity of surface soil moisture in both space and time has garnered interest from areas including agricultural management and drought monitoring, water resources and flood prediction, and more recently climate modeling. Soil moisture has also been identified as a critical parameter in the initiation of particle entrainment by wind due to the alteration of physical properties such as aggregate structure and inter-particle cohesion. Therefore the dynamics of soil moisture are of great interest for regional wind erosion modeling as well as for the development of agricultural productivity and soil loss models. In this study, a unique environment for the study of soil moisture was investigated at Williston Reservoir in Northern British Columbia, Canada. For a period of a month or more before the reservoir is filled by the spring melt, several thousand hectares of fine-grained sediments are exposed to wind causing significant erosion and therefore potential air quality concerns. Here we present a study of the spatial and temporal patterning of surface soil moisture in exposed sediments. Measurements at small scales are used in the validation of remote sensing products at large scales and these estimates have been implemented into blowing dust models. Active microwave (RADARSAT-2) and optical (LandSAT-5) scenes were obtained between May 24th - June 2nd, 2009. On the ground, point measurements using capacitance based probes were performed over 4 test plots coincident with satellite overpass. Areal averages of soil moisture collected on the ground are used in the validation of soil moisture estimates from four backscatter inversion models (microwave) and a thermal band mono-window brightness temperature algorithm (optical). The studied environment represents an important validity test because backscatter inversion models

  13. Spatial and temporal variability of soil moisture-temperature coupling in current and future climate

    Science.gov (United States)

    Schwingshackl, Clemens; Hirschi, Martin; Seneviratne, Sonia Isabelle

    2017-04-01

    While climate models generally agree on a future global mean temperature increase, the exact rate of change is still uncertain. The uncertainty is even higher for regional temperature trends that can deviate substantially from the projected global temperature increase. Several studies tried to constrain these regional temperature projections. They found that over land areas soil moisture is an important factor that influences the regional response. Due to the limited knowledge of the influence of soil moisture on atmospheric conditions on global scale the constraint remains still weak, though. Here, we use a framework that is based on the dependence of evaporative fraction (i.e. the fraction of net radiation that goes into latent heat flux) on soil moisture to distinguish between different soil moisture regimes (Seneviratne et al., 2010). It allows to estimate the influence of soil moisture on near-surface air temperature in the current climate and in future projections. While in the wet soil moisture regime, atmospheric conditions and related land surface fluxes can be considered as mostly driven by available energy, in the transitional regime - where evaporative fraction and soil moisture are essentially linearly coupled - soil moisture has an impact on turbulent heat fluxes, air humidity and temperature: Decreasing soil moisture and concomitant decreasing evaporative fraction cause increasing sensible heat flux, which might further lead to higher surface air temperatures. We investigate the strength of the single couplings (soil moisture → latent heat flux → sensible heat flux → air temperature) in order to quantify the influence of soil moisture on surface air temperature in the transitional regime. Moreover, we take into account that the coupling strength can change in the course of the year due to seasonal climate variations. The relations between soil moisture, evaporative fraction and near-surface air temperature in re-analysis and observation

  14. Estimating Soil Moisture at High Spatial Resolution with Three Radiometric Satellite Products: A Study from a South-Eastern Australian Catchment

    Science.gov (United States)

    Senanayake, I. P.; Yeo, I. Y.; Tangdamrongsub, N.; Willgoose, G. R.; Hancock, G. R.; Wells, T.; Fang, B.; Lakshmi, V.

    2017-12-01

    Long-term soil moisture datasets at high spatial resolution are important in agricultural, hydrological, and climatic applications. The soil moisture estimates can be achieved using satellite remote sensing observations. However, the satellite soil moisture data are typically available at coarse spatial resolutions ( several tens of km), therefore require further downscaling. Different satellite soil moisture products have to be conjointly employed in developing a consistent time-series of high resolution soil moisture, while the discrepancies amongst different satellite retrievals need to be resolved. This study aims to downscale three different satellite soil moisture products, the Soil Moisture and Ocean Salinity (SMOS, 25 km), the Soil Moisture Active Passive (SMAP, 36 km) and the SMAP-Enhanced (9 km), and to conduct an inter-comparison of the downscaled results. The downscaling approach is developed based on the relationship between the diurnal temperature difference and the daily mean soil moisture content. The approach is applied to two sub-catchments (Krui and Merriwa River) of the Goulburn River catchment in the Upper Hunter region (NSW, Australia) to estimate soil moisture at 1 km resolution for 2015. The three coarse spatial resolution soil moisture products and their downscaled results will be validated with the in-situ observations obtained from the Scaling and Assimilation of Soil Moisture and Streamflow (SASMAS) network. The spatial and temporal patterns of the downscaled results will also be analysed. This study will provide the necessary insights for data selection and bias corrections to maintain the consistency of a long-term high resolution soil moisture dataset. The results will assist in developing a time-series of high resolution soil moisture data over the south-eastern Australia.

  15. Spatial variation and driving factors of soil moisture at multi-scales: a case study in Loess Plateau of China

    Science.gov (United States)

    Zhao, W.; Zhang, X.; Liu, Y.; Fang, X.

    2017-12-01

    Currently, the ecological restoration of the Loess Plateau has led to significant achievements such as increases in vegetation coverage, decreases in soil erosion, and enhancement of ecosystem services. Soil moisture shortages, however, commonly occur as a result of limited rainfall and strong evaporation in this semiarid region of China. Since soil moisture is critical in regulating plant growth in these semiarid regions, it is crucial to identify the spatial variation and factors affecting soil moisture at multi-scales in the Loess Plateau of China. In the last several years, extensive studies on soil moisture have been carried out by our research group at the plot, small watershed, watershed, and regional scale in the Loess Plateau, providing some information for vegetation restoration in the region. The main research results are as follows: (1) the highest soil moisture content was in the 0-0.1 m layer with a large coefficient of variation; (2) in the 0-0.1m layer, soil moisture content was negatively correlated with relative elevation, slope and vegetation cover, the correlations among slope, aspect and soil moisture increased with depth increased; (3) as for the deep soil moisture content, the higher spatial variation of deep SMC occurred at 1.2-1.4 m and 4.8-5.0m; (4) the deep soil moisture content in native grassland and farmland were significant higher than that of introduced vegetation; (5) at regional scale, the soil water content under different precipitation zones increased following the increase of precipitation, while, the influencing factors of deep SMC at watershed scale varied with land management types; (6) in the areas with multi-year precipitation of 370 - 440mm, natural grass is more suitable for restoration, and this should be treated as the key areas in vegetation restoration; (7) appropriate planting density and species selection should be taken into account for introduced vegetation management; (8) it is imperative to take the local

  16. Controls on the temporal and spatial variability of soil moisture in a mountainous landscape: the signature of snow and complex terrain

    Directory of Open Access Journals (Sweden)

    J. P. McNamara

    2009-07-01

    Full Text Available The controls on the spatial distribution of soil moisture include static and dynamic variables. The superposition of static and dynamic controls can lead to different soil moisture patterns for a given catchment during wetting, draining, and drying periods. These relationships can be further complicated in snow-dominated mountain regions where soil water input by precipitation is largely dictated by the spatial variability of snow accumulation and melt. In this study, we assess controls on spatial and temporal soil moisture variability in a small (0.02 km2, snow-dominated, semi-arid catchment by evaluating spatial correlations between soil moisture and site characteristics through different hydrologic seasons. We assess the relative importance of snow with respect to other catchment properties on the spatial variability of soil moisture and track the temporal persistence of those controls. Spatial distribution of snow, distance from divide, soil texture, and soil depth exerted significant control on the spatial variability of moisture content throughout most of the hydrologic year. These relationships were strongest during the wettest period and degraded during the dry period. As the catchment cycled through wet and dry periods, the relative spatial variability of soil moisture tended to remain unchanged. We suggest that the static properties in complex terrain (slope, aspect, soils impose first order controls on the spatial variability of snow and resulting soil moisture patterns, and that the interaction of dynamic (timing of water input and static influences propagate that relative constant spatial variability through most of the hydrologic year. The results demonstrate that snow exerts significant influence on how water is retained within mid-elevation semi-arid catchments and suggest that reductions in annual snowpacks associated with changing climate regimes may strongly influence spatial and temporal soil moisture patterns and

  17. Spatial Variability of Near-surface Soil Moisture for Bioenergy Crops at the Great Lakes Bioenergy Research Center

    Science.gov (United States)

    van Dam, R. L.; Diker, K.; Bhardwaj, A. K.; Hamilton, S. K.

    2009-12-01

    We used time-lapse electrical resistivity imaging (ERI) to monitor spatial and temporal soil moisture variability below ten different potential bioenergy cropping systems at the Great Lakes Bioenergy Research Center’s sustainability research site in Michigan, U.S.A. These crops range from high-diversity, low-input grasses and poplars to low-diversity, high-input corn-soybean-canola rotations. We equipped the 28x40m vegetation plots with permanent 2D resistivity arrays, each consisting of 40 graphite electrodes at 30cm spacing. Other permanent equipment in each plot includes multi-depth temperature and time domain reflectometry (TDR) based moisture sensors, and two tension soil water samplers. The material at the site consists of coarse sandy glacial tills in which a soil with an approximately 50cm thick A-Bt horizon has developed. ERI data were collected using a dipole-dipole configuration every four weeks since early May 2009. After removal of bad points, the data were inverted and translated into 2D images of water content using lab-derived petrophysical relationships, including corrections for soil temperature and salinity. The results show significant seasonal variation within and between vegetation plots. We compare our results to high-temporal resolution point-based measurements of soil moisture from TDR probes and present statistical analysis of the variability of soil moisture within and between plots.

  18. Impact of rainfall spatial distribution on rainfall-runoff modelling efficiency and initial soil moisture conditions estimation

    Directory of Open Access Journals (Sweden)

    Y. Tramblay

    2011-01-01

    Full Text Available A good knowledge of rainfall is essential for hydrological operational purposes such as flood forecasting. The objective of this paper was to analyze, on a relatively large sample of flood events, how rainfall-runoff modeling using an event-based model can be sensitive to the use of spatial rainfall compared to mean areal rainfall over the watershed. This comparison was based not only on the model's efficiency in reproducing the flood events but also through the estimation of the initial conditions by the model, using different rainfall inputs. The initial conditions of soil moisture are indeed a key factor for flood modeling in the Mediterranean region. In order to provide a soil moisture index that could be related to the initial condition of the model, the soil moisture output of the Safran-Isba-Modcou (SIM model developed by Météo-France was used. This study was done in the Gardon catchment (545 km2 in South France, using uniform or spatial rainfall data derived from rain gauge and radar for 16 flood events. The event-based model considered combines the SCS runoff production model and the Lag and Route routing model. Results show that spatial rainfall increases the efficiency of the model. The advantage of using spatial rainfall is marked for some of the largest flood events. In addition, the relationship between the model's initial condition and the external predictor of soil moisture provided by the SIM model is better when using spatial rainfall, in particular when using spatial radar data with R2 values increasing from 0.61 to 0.72.

  19. Hysteresis of soil temperature under different soil moisture and ...

    African Journals Online (AJOL)

    Jane

    2011-10-17

    Oct 17, 2011 ... Soil temperature is one of the important variables in spatial prediction of soil energy balance in a solar greenhouse. ... temperature under three soil moisture and two fertilizer levels in solar greenhouse conditions with tomato crop ... pertains to the soil itself (thermal properties, moisture content, type of soil, ...

  20. CPC Soil Moisture

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The monthly data set consists of a file containing 1/2 degree monthly averaged soil moisture water height equivalents for the globe from 1948 onwards. Values are...

  1. Physically-based modeling of topographic effects on spatial evapotranspiration and soil moisture patterns through radiation and wind

    Directory of Open Access Journals (Sweden)

    M. Liu

    2012-02-01

    Full Text Available In this paper, simulations with the Soil Water Atmosphere Plant (SWAP model are performed to quantify the spatial variability of both potential and actual evapotranspiration (ET, and soil moisture content (SMC caused by topography-induced spatial wind and radiation differences. To obtain the spatially distributed ET/SMC patterns, the field scale SWAP model is applied in a distributed way for both pointwise and catchment wide simulations. An adapted radiation model from r.sun and the physically-based meso-scale wind model METRAS PC are applied to obtain the spatial radiation and wind patterns respectively, which show significant spatial variation and correlation with aspect and elevation respectively. Such topographic dependences and spatial variations further propagate to ET/SMC. A strong spatial, seasonal-dependent, scale-relevant intra-catchment variability in daily/annual ET and less variability in SMC can be observed from the numerical experiments. The study concludes that topography has a significant effect on ET/SMC in the humid region where ET is a energy limited rather than water availability limited process. It affects the spatial runoff generation through spatial radiation and wind, therefore should be applied to inform hydrological model development. In addition, the methodology used in the study can serve as a general method for physically-based ET estimation for data sparse regions.

  2. SMAP Radiometer Soil Moisture Downscaling in CONUS

    Science.gov (United States)

    Fang, B.; Lakshmi, V.; Bindlish, R.; Jackson, T. J.

    2017-12-01

    Remote sensing technology has been providing soil moisture observations for the study of the global hydrological cycle for land-air interactions, ecology and agriculture. Passive microwave sensors that have provided operational products include AMSR-E (Advanced Microwave Scanning Radiometer for the Earth Observing System), AMSR2 (Advanced Microwave Scanning Radiometer 2), SMOS (Soil Moisture and Ocean Salinity), as and SMAP (Soil Moisture Active/Passive). The SMAP radiometer provides soil moisture with a grid resolution of 9 km. However, higher spatial resolution soil moisture is still required for various applications in weather, agriculture and watershed studies. This study focuses on providing a higher resolution product by downscaling the SMAP soil moisture over CONUS (Contiguous United States). This algorithm is based on the long term thermal inertia relationship between daily temperature variation and average soil moisture modulated by vegetation. This relationship is modeled using the variables from the NLDAS (North America Land Data Assimilation System) and LTDR (Land Long Term Data Record) from 1981-2016 and is applied to calculate 1 km soil moisture from MODIS land data products and then used to downscale SMAP Level-3 9 km radiometer soil moisture to 1 km over CONUS. The downscaled results are evaluated by comparison with in situ observations from ISMN (International Soil Moisture Network), SMAPVEX (SMAP Validation Experiment), MESONET (Mesoscale Network), Soil Climate Analysis Network (SCAN) and other established networks.

  3. Spatial variability and its main controlling factors of the permafrost soil-moisture on the northern-slope of Bayan Har Mountains in Qinghai-Tibet Plateau

    Science.gov (United States)

    Cao, W.; Sheng, Y.

    2017-12-01

    The soil moisture movement is an important carrier of material cycle and energy flow among the various geo-spheres in the cold regions. It is very critical to protect the alpine ecology and hydrologic cycle in Qinghai-Tibet Plateau. Especially, it becomes one of the key problems to reveal the spatial-temporal variability of soil moisture movement and its main influence factors in earth system science. Thus, this research takes the north slope of Bayan Har Mountains in Qinghai-Tibet Plateau as a case study. The present study firstly investigates the change of permafrost moisture in different slope positions and depths. Based on this investigation, this article attempts to investigate the spatial variability of permafrost moisture and identifies the key influence factors in different terrain conditions. The method of classification and regression tree (CART) is adopted to identify the main controlling factors influencing the soil moisture movement. And the relationships between soil moisture and environmental factors are revealed by the use of the method of canonical correspondence analysis (CCA). The results show that: 1) the change of the soil moisture on the permafrost slope is divided into 4 stages, including the freezing stability phase, the rapid thawing phase, the thawing stability phase and the fast freezing phase; 2) this greatly enhances the horizontal flow in the freezing period due to the terrain slope and the freezing-thawing process. Vertical migration is the mainly form of the soil moisture movement. It leads to that the soil-moisture content in the up-slope is higher than that in the down-slope. On the contrary, the soil-moisture content in the up-slope is lower than that in the down-slope during the melting period; 3) the main environmental factors which affect the slope-permafrost soil-moisture are elevation, soil texture, soil temperature and vegetation coverage. But there are differences in the impact factors of the soil moisture in different

  4. Synergic Use of Sentinel-1 and Sentinel-2 Images for Operational Soil Moisture Mapping at High Spatial Resolution over Agricultural Areas

    Directory of Open Access Journals (Sweden)

    Mohammad El Hajj

    2017-12-01

    Full Text Available Soil moisture mapping at a high spatial resolution is very important for several applications in hydrology, agriculture and risk assessment. With the arrival of the free Sentinel data at high spatial and temporal resolutions, the development of soil moisture products that can better meet the needs of users is now possible. In this context, the main objective of the present paper is to develop an operational approach for soil moisture mapping in agricultural areas at a high spatial resolution over bare soils, as well as soils with vegetation cover. The developed approach is based on the synergic use of radar and optical data. A neural network technique was used to develop an operational method for soil moisture estimates. Three inversion SAR (Synthetic Aperture Radar configurations were tested: (1 VV polarization; (2 VH polarization; and (3 both VV and VH polarization, all in addition to the NDVI information extracted from optical images. Neural networks were developed and validated using synthetic and real databases. The results showed that the use of a priori information on the soil moisture condition increases the precision of the soil moisture estimates. The results showed that VV alone provides better accuracy on the soil moisture estimates than VH alone. In addition, the use of both VV and VH provides similar results, compared to VV alone. In conclusion, the soil moisture could be estimated in agricultural areas with an accuracy of approximately 5 vol % (volumetric unit expressed in percent. Better results were obtained for soil with a moderate surface roughness (for root mean surface height between 1 and 3 cm. The developed approach could be applied for agricultural plots with an NDVI lower than 0.75.

  5. Spatial Soil Temperature and Moisture Monitoring Across the Transylvanian Plain, in Romania

    Science.gov (United States)

    Rusu, Teodor; Weindorf, David; Haggard, Beatrix; Moraru, Paula Ioana; Sopterean, Mara Lucia

    2011-01-01

    The Transylvanian Plain, Romania is an important region for agronomic productivity. However, limited soils data and adoption of best management practices hinder land productivity. Soil temperatures of the Transylvanian Plain were evaluated using a set of twenty datalogging stations positioned throughout the plain. Soil temperatures were monitored at the surface and at 10, 30, and 50 cm depths, and soil moisture was monitored at 10 cm. Preliminary results indicate that most soils of the Transylvanian Plain will have a mesic temperature regime. However, differences in seasonal warming and cooling trends across the plain were noted. These have important implications for planting recommendations. Growing degree days (GDDs) are preferred over maturity ratings, because they can account for temperature anomalies. The crop being considered for this study was corn. The base temperature (BT) was set at 10oC, and the upper threshold was 30oC. Two methods were used to calculate GDDs; 1) minimum and maximum daily temperatures, and 2) 24 h of averaged temperature data. Growing degree days were run from 110-199 day of year (DOY) to represent approximate planting date to tasseling. The DOY that 694 accumulated growing degree days (AGDDs) was reached at each site was then analyzed to identify differences across the TP. Three sites failed to reach 694 AGDDs by DOY 199, and were excluded from comparisons to other results. Averaged values were used to create spline interpolation maps with ArcMap 9.2 (ESRI, Redlands, CA, USA). The southeastern portion of the TP was found to tassel a month earlier assuming a planting date of 109 DOY. Four DeKalb® corn hybrids were then selected based on GDDs to tasseling, drydown, drought tolerance, and insect resistance. With a better understanding of the GDD trends across the TP, more effective planting and harvesting could be accomplished by Romanian farmers to maximize agronomic production.

  6. Temporal and spatial variability of soil hydraulic properties with implications on soil moisture simulations and irrigation scheduling

    Science.gov (United States)

    Feki, Mouna; Ravazzani, Giovanni; Mancini, Marco

    2017-04-01

    The increase in consumption of water resources, combined with climate change impacts, calls for new sources of water supply and/or different managements of available resources in agriculture. One way to increase the quality and quantity of agricultural production is using modern technology to make farms more "intelligent", the so-called "precision agriculture" also known as 'smart farming'. To this aim hydrological models play crucial role for their ability to simulate water movement from soil surface to groundwater and to predict onset of stress condition. However, optimal use of mathematical models requires intensive, time consuming and expensive collection of soil related parameters. Typically, soils to be characterized, exhibit large variations in space and time as well during the cropping cycle, due to biological processes and agricultural management practices: tillage, irrigation, fertilization and harvest. Soil properties are subjected to diverse physical and chemical changes that lead to a non-stability in terms of water and chemical movements within the soil and to the groundwater as well. The aim of this study is to assess the variability of soil hydraulic properties over a cropping cycle. The study site is a surface irrigated Maize field located in Secugnago (45◦13'31.70" N, 9 ◦36'26.82 E), in Northern Italy-Lombardy region. The field belongs to the Consortium Muzza Bassa Lodigiana, within which meteorological data together with soil moisture were monitored during the cropping season of 2015. To investigate soil properties variations, both measurements in the field and laboratory tests on both undisturbed and disturbed collected samples were performed. Soil samples were taken from different locations within the study area and at different depths (surface, 20cm and 40cm) at the beginning and in the middle of the cropping cycle and after the harvest. During three measuring campaigns, for each soil samples several parameters were monitored (Organic

  7. Using Actively Heated Fibre Optics (AHFO) to determine soil thermal conductivity and soil moisture content at high spatial and temporal resolution

    Science.gov (United States)

    Ciocca, Francesco; Abesser, Corinna; Hannah, David; Blaen, Philip; Chalari, Athena; Mondanos, Michael; Krause, Stefan

    2017-04-01

    Optical fibre distributed temperature sensing (DTS) is increasingly used in environmental monitoring and for subsurface characterisation, e.g. to obtain precise measurements of soil temperature at high spatio-temporal resolution, over several kilometres of optical fibre cable. When combined with active heating of metal elements embedded in the optical fibre cable (active-DTS), the temperature response of the soil to heating provides valuable information from which other important soil parameters, such as thermal conductivity and soil moisture content, can be inferred. In this presentation, we report the development of an Actively Heated Fibre Optics (AHFO) method for the characterisation of soil thermal conductivity and soil moisture dynamics at high temporal and spatial resolutions at a vegetated hillslope site in central England. The study site is located within a juvenile forest adjacent to the Birmingham Institute of Forest Research (BIFoR) experimental site. It is instrumented with three loops of a 500m hybrid-optical cable installed at 10cm, 25cm and 40cm depths. Active DTS surveys were undertaken in June and October 2016, collecting soil temperature data at 0.25m intervals along the cable, prior to, during and after the 900s heating phase. Soil thermal conductivity and soil moisture were determined according to Ciocca et al. 2012, applied to both the cooling and the heating phase. Independent measurements of soil thermal conductivity and soil moisture content were collected using thermal needle probes, calibrated capacitance-based probes and laboratory methods. Results from both the active DTS survey and independent in-situ and laboratory measurements will be presented, including the observed relationship between thermal conductivity and moisture content at the study site and how it compares against theoretical curves used by the AHFO methods. The spatial variability of soil thermal conductivity and soil moisture content, as observed using the different

  8. Spatial Heterogeneity of Soil Moisture and the Scale Variability of Its Influencing Factors: A Case Study in the Loess Plateau of China

    Directory of Open Access Journals (Sweden)

    Mingyue Zhao

    2013-08-01

    Full Text Available Soil moisture is an important factor for vegetation restoration and ecosystem sustainability in the Loess Plateau of China. The strong spatial heterogeneity of soil moisture is controlled by many environmental factors, including topography and land use. Moreover, the spatial patterns and soil hydrological processes depend on the scale of the site being investigated, which creates a challenge for soil moisture forecasts. This study was conducted at two scales: watershed and small watershed. The goal of the study was to investigate the spatial variability in soil moisture and the scale effect of its controlling factors, as well as to provide references for soil moisture forecasting and studies of scale transformation. We took samples at 76 sites in the Ansai watershed and at 34 sites in a typical small watershed within the Ansai watershed in August. Next, we measured the soil moisture in five equal layers from a depth of 0–100 cm and recorded the land use type, location on the hill slope, slope, aspect, elevation and vegetation cover at the sampling sites. The results indicated that soil moisture was negatively correlated with relative elevation, slope and vegetation cover. As depth increased, the correlations among slope, aspect and soil moisture increased. At the small watershed and watershed scales, the soil moisture was highest in cultivated land, followed by wild grassland and lowest in garden plots, woodland and shrubland. The soil moisture was distributed similarly with respect to the location on the hill slope at both scales: upper slope < middle-upper slope < middle slope < middle-lower slope < lower slope. The deep layer soil moisture value of the slope top was high, being close to the soil moisture in the lower slope. Therefore, wild grassland or low-density woodland should be prioritized for farmland recovery in the Ansai watershed, and the locations on the hill slope, slope and elevation should be combined to configure different

  9. Estimation of improved resolution soil moisture in vegetated areas ...

    Indian Academy of Sciences (India)

    Mina Moradizadeh

    2018-03-06

    Mar 6, 2018 ... main goal of this study is to develop a downscaling approach to improve the spatial resolution of soil moisture estimates with ... illustrated that the soil moisture variability is effectively captured at 5 km spatial scales without a significant degradation .... the ability of Vis/IR sensors in soil moisture sensing and ...

  10. Radar Mapping of Surface Soil Moisture

    Science.gov (United States)

    Ulaby, F. T.; Dubois, P. C.; van Zyl, J.

    1997-01-01

    Intended as an overview aimed at potential users of remotely sensed spatial distributions and temporal variations of soil moisture, this paper begins with an introductory section on the fundamentals of radar imaging and associated attributes.

  11. The soil moisture velocity equation

    Science.gov (United States)

    Ogden, Fred L.; Allen, Myron B.; Lai, Wencong; Zhu, Jianting; Seo, Mookwon; Douglas, Craig C.; Talbot, Cary A.

    2017-06-01

    Numerical solution of the one-dimensional Richards' equation is the recommended method for coupling groundwater to the atmosphere through the vadose zone in hyperresolution Earth system models, but requires fine spatial discretization, is computationally expensive, and may not converge due to mathematical degeneracy or when sharp wetting fronts occur. We transformed the one-dimensional Richards' equation into a new equation that describes the velocity of moisture content values in an unsaturated soil under the actions of capillarity and gravity. We call this new equation the Soil Moisture Velocity Equation (SMVE). The SMVE consists of two terms: an advection-like term that accounts for gravity and the integrated capillary drive of the wetting front, and a diffusion-like term that describes the flux due to the shape of the wetting front capillarity profile divided by the vertical gradient of the capillary pressure head. The SMVE advection-like term can be converted to a relatively easy to solve ordinary differential equation (ODE) using the method of lines and solved using a finite moisture-content discretization. Comparing against analytical solutions of Richards' equation shows that the SMVE advection-like term is >99% accurate for calculating infiltration fluxes neglecting the diffusion-like term. The ODE solution of the SMVE advection-like term is accurate, computationally efficient and reliable for calculating one-dimensional vadose zone fluxes in Earth system and large-scale coupled models of land-atmosphere interaction. It is also well suited for use in inverse problems such as when repeat remote sensing observations are used to infer soil hydraulic properties or soil moisture.type="synopsis">type="main">Plain Language SummarySince its original publication in 1922, the so-called Richards' equation has been the only rigorous way to couple groundwater to the land surface through the unsaturated zone that lies between the water table and land surface. The soil

  12. Multi-Timescale Analysis of the Spatial Representativeness of In Situ Soil Moisture Data within Satellite Footprints

    Science.gov (United States)

    Molero, B.; Leroux, D. J.; Richaume, P.; Kerr, Y. H.; Merlin, O.; Cosh, M. H.; Bindlish, R.

    2018-01-01

    We conduct a novel comprehensive investigation that seeks to prove the connection between spatial scales and timescales in surface soil moisture (SM) within the satellite footprint ( 50 km). Modeled and measured point series at Yanco and Little Washita in situ networks are first decomposed into anomalies at timescales ranging from 0.5 to 128 days, using wavelet transforms. Then, their degree of spatial representativeness is evaluated on a per-timescale basis by comparison to large spatial scale data sets (the in situ spatial average, SMOS, AMSR2, and ECMWF). Four methods are used for this: temporal stability analysis (TStab), triple collocation (TC), percentage of correlated areas (CArea), and a new proposed approach that uses wavelet-based correlations (WCor). We found that the mean of the spatial representativeness values tends to increase with the timescale but so does their dispersion. Locations exhibit poor spatial representativeness at scales below 4 days, while either very good or poor representativeness at seasonal scales. Regarding the methods, TStab cannot be applied to the anomaly series due to their multiple zero-crossings, and TC is suitable for week and month scales but not for other scales where data set cross-correlations are found low. In contrast, WCor and CArea give consistent results at all timescales. WCor is less sensitive to the spatial sampling density, so it is a robust method that can be applied to sparse networks (one station per footprint). These results are promising to improve the validation and downscaling of satellite SM series and the optimization of SM networks.

  13. Spatial and Temporal Distribution of Soil Moisture at the Catchment Scale Using Remotely-Sensed Energy Fluxes

    Directory of Open Access Journals (Sweden)

    Thomas K. Alexandridis

    2016-01-01

    Full Text Available Despite playing a critical role in the division of precipitation between runoff and infiltration, soil moisture (SM is difficult to estimate at the catchment scale and at frequent time steps, as is required by many hydrological, erosion and flood simulation models. In this work, an integrated methodology is described to estimate SM at the root zone, based on the remotely-sensed evaporative fraction (Λ and ancillary information on soil and meteorology. A time series of Terra MODIS satellite images was used to estimate SM maps with an eight-day time step at a 250-m spatial resolution for three diverse catchments in Europe. The study of the resulting SM maps shows that their spatial variability follows the pattern of land cover types and the main geomorphological features of the catchment, and their temporal pattern follows the distribution of rain events, with the exception of irrigated land. Field surveys provided in situ measurements to validate the SM maps’ accuracy, which proved to be variable according to site and season. In addition, several factors were analyzed in order to explain the variation in the accuracy, and it was shown that the land cover type, the soil texture class, the temporal difference between the datasets’ acquisition and the presence of rain events during the measurements played a significant role, rather than the often referred to scale difference between in situ and satellite observations. Therefore, the proposed methodology can be used operationally to estimate SM maps at the catchment scale, with a 250-m spatial resolution and an eight-day time step.

  14. Development of an Aquarius Soil Moisture Product

    Science.gov (United States)

    Bindlish, R.; Jackson, T. J.; Zhao, T.; Cosh, M. H.

    2013-12-01

    Aquarius observations over land offer a new resource for measuring soil moisture from space. Our objective in this investigation is to exploit the large amount of land observations that Aquarius acquires and extend the mission scope to land applications through the retrieval of soil moisture. This research increases the value and impact of the Aquarius mission by including a broader scientific community, allowing the exploration of new algorithm approaches that exploit the active-passive observations, and will contribute to a better understanding of the Earth's climate and water cycle. The first stage of our Aquarius soil moisture research focused on the use of the radiometer data because of the extensive heritage that this type of observations has in soil moisture applications. The calibration of the Aquarius radiometer over the entire dynamic range is a key element for the successful implementation of the soil moisture algorithm. Results to date indicate that the Aquarius observations are well calibrated for ocean targets but have a warm bias over land. This bias needed to be addressed if the Aquarius observations are to be used in land applications. Our approach was to use the gain and offsets computed using the Soil Moisture Ocean Salinity (SMOS) comparisons to adjust the Aquarius brightness temperatures. The Single Channel Algorithm (SCA) was implemented using the Aquarius observations. SCA is also the baseline algorithm for the SMAP radiometer-only soil moisture product. Aquarius radiometer observations from the three beams (after bias/gain modification) along with the National Centers for Environmental Prediction (NCEP) surface temperature model forecast were then used to estimate soil moisture. Ancillary data inputs required for using the SCA are vegetation water content, land surface temperature, and several soil and vegetation parameters derived based on land cover. The spatial patterns of the soil moisture estimates are consistent with the climatology

  15. Modeling soil moisture-reflectance

    OpenAIRE

    Muller, Etienne; Decamps, Henri

    2001-01-01

    International audience; Spectral information on soil is not easily available as vegetation and farm works prevent direct observation of soil responses. However, there is an increasing need to include soil reflectance values in spectral unmixing algorithms or in classification approaches. In most cases, the impact of soil moisture on the reflectance is unknown and therefore ignored. The objective of this study was to model reflectance changes due to soil moisture in a real field situation usin...

  16. Local- and Plot-Scale Measurements of Soil Moisture: Time and Spatially Resolved Field Techniques in Plain, Hill and Mountain Sites

    Directory of Open Access Journals (Sweden)

    Giulia Raffelli

    2017-09-01

    Full Text Available Soil moisture measurement is essential to validate hydrological models and satellite data. In this work we provide an overview of different local and plot scale soil moisture measurement techniques applied in three different conditions in terms of altitude, land use, and soil type, namely a plain, a mountain meadow and a hilly vineyard. The main goal is to provide a synoptic view of techniques supported by practical case studies to show that in such different conditions it is possible to estimate a time and spatially resolved soil moisture by the same combination of instruments: contact-based methods (i.e., Time Domain Reflectometry—TDR, and two low frequency probes for the time resolved, and hydro-geophysical minimally-invasive methods (i.e., Electromagnetic Induction—EMI, Ground Penetrating Radar—GPR, and the Electrical Resistivity Tomography—ERT for the spatially resolved. Both long-term soil moisture measurements and spatially resolved measurement campaigns are discussed. Technical and operational measures are detailed to allow critical factors to be identified.

  17. Passive microwave remote sensing of soil moisture

    International Nuclear Information System (INIS)

    Jackson, T.J.; Schmugge, T.J.

    1986-01-01

    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

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

    KAUST Repository

    Singh, Gurjeet

    2016-05-05

    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. © (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

  19. New Physical Algorithms for Downscaling SMAP Soil Moisture

    Science.gov (United States)

    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.

  20. [Spatial heterogeneity of soil moisture of mountain apple orchards with rainwater collection and infiltration (RWCI) system in the Loess Plateau, China].

    Science.gov (United States)

    Song, Xiao Lin; Zhao, Xi Ning; Gao, Xiao Dong; Wu, Pu Te; Ma, Wen; Yao, Jie; Jiang, Xiao Li; Zhang, Wei

    2017-11-01

    Water scarcity is a critical factor influencing rain-fed agricultural production on the Loess Plateau, and the exploitation of rainwater is an effective avenue to alleviate water scarcity in this area. This study was conducted to investigate the spatial and temporal distribution of soil moisture in the 0-300 cm under a 21-year-old apple orchard with the rainwater collection and infiltration (RWCI) system by using a time domain reflectometer (TDR) probe on the Loess Plateau. The results showed that there was a low soil moisture zone in the 40-80 cm under the CK, and the RWCI system significantly increased soil moisture in this depth interval. Over this depth, the annual average soil moisture under RWCI 40 , RWCI 60 and RWCI 80 was 39.2%, 47.2% and 29.1% higher than that of bare slope (BS) and 75.3%, 85.4% and 62.7% higher than that of CK, respectively. The maximum infiltration depth of water under RWCI 40 , RWCI 60 and RWCI 80 was 80 cm, 120 cm and 180 cm, respectively, and the soil moisture in the 0-60, 0-100 and 0-120 cm was more affected by RWCI 40 , RWCI 60 and RWCI 80 , respectively. Over the whole growth period of apple tree, the maximum value of soil moisture content in the 0-300 cm existed in the RWCI 80 treatment, followed by the RWCI 40 and RWCI 60 treatments. Overall, the RWCI system is an effective meaning of transforming rainwater to available water resources and realizing efficient use of agricultural water on the Loess Plateau.

  1. Root-zone soil moisture estimation from assimilation of downscaled Soil Moisture and Ocean Salinity data

    Science.gov (United States)

    Dumedah, Gift; Walker, Jeffrey P.; Merlin, Olivier

    2015-10-01

    The crucial role of root-zone soil moisture is widely recognized in land-atmosphere interaction, with direct practical use in hydrology, agriculture and meteorology. But it is difficult to estimate the root-zone soil moisture accurately because of its space-time variability and its nonlinear relationship with surface soil moisture. Typically, direct satellite observations at the surface are extended to estimate the root-zone soil moisture through data assimilation. But the results suffer from low spatial resolution of the satellite observation. While advances have been made recently to downscale the satellite soil moisture from Soil Moisture and Ocean Salinity (SMOS) mission using methods such as the Disaggregation based on Physical And Theoretical scale Change (DisPATCh), the assimilation of such data into high spatial resolution land surface models has not been examined to estimate the root-zone soil moisture. Consequently, this study assimilates the 1-km DisPATCh surface soil moisture into the Joint UK Land Environment Simulator (JULES) to better estimate the root-zone soil moisture. The assimilation is demonstrated using the advanced Evolutionary Data Assimilation (EDA) procedure for the Yanco area in south eastern Australia. When evaluated using in-situ OzNet soil moisture, the open loop was found to be 95% as accurate as the updated output, with the updated estimate improving the DisPATCh data by 14%, all based on the root mean square error (RMSE). Evaluation of the root-zone soil moisture with in-situ OzNet data found the updated output to improve the open loop estimate by 34% for the 0-30 cm soil depth, 59% for the 30-60 cm soil depth, and 63% for the 60-90 cm soil depth, based on RMSE. The increased performance of the updated output over the open loop estimate is associated with (i) consistent estimation accuracy across the three soil depths for the updated output, and (ii) the deterioration of the open loop output for deeper soil depths. Thus, the

  2. Integrating Real-time and Manual Monitored Soil Moisture Data to Predict Hillslope Soil Moisture Variations with High Temporal Resolutions

    Science.gov (United States)

    Zhu, Qing; Lv, Ligang; Zhou, Zhiwen; Liao, Kaihua

    2016-04-01

    Spatial-temporal variability of soil moisture 15 has been remaining an challenge to be better understood. A trade-off exists between spatial coverage and temporal resolution when using the manual and real-time soil moisture monitoring methods. This restricted the comprehensive and intensive examination of soil moisture dynamics. In this study, we aimed to integrate the manual and real-time monitored soil moisture to depict the hillslope dynamics of soil moisture with good spatial coverage and temporal resolution. Linear (stepwise multiple linear regression-SMLR) and non-linear models (support vector machines-SVM) were used to predict soil moisture at 38 manual sites (collected 1-2 times per month) with soil moisture automatically collected at three real-time monitoring sites (collected every 5 mins). By comparing the accuracies of SMLR and SVM for each manual site, optimal soil moisture prediction model of this site was then determined. Results show that soil moisture at these 38 manual sites can be reliably predicted (root mean square errorsindex, profile curvature, and relative difference of soil moisture and its standard deviation influenced the selection of prediction model since they related to the dynamics of soil water distribution and movement. By using this approach, hillslope soil moisture spatial distributions at un-sampled times and dates were predicted after a typical rainfall event. Missing information of hillslope soil moisture dynamics was then acquired successfully. This can be benefit for determining the hot spots and moments of soil water movement, as well as designing the proper soil moisture monitoring plan at the field scale.

  3. Local root abscisic acid (ABA) accumulation depends on the spatial distribution of soil moisture in potato: implications for ABA signalling under heterogeneous soil drying.

    Science.gov (United States)

    Puértolas, Jaime; Conesa, María R; Ballester, Carlos; Dodd, Ian C

    2015-04-01

    Patterns of root abscisic acid (ABA) accumulation ([ABA]root), root water potential (Ψroot), and root water uptake (RWU), and their impact on xylem sap ABA concentration ([X-ABA]) were measured under vertical partial root-zone drying (VPRD, upper compartment dry, lower compartment wet) and horizontal partial root-zone drying (HPRD, two lateral compartments: one dry, the other wet) of potato (Solanum tuberosum L.). When water was withheld from the dry compartment for 0-10 d, RWU and Ψroot were similarly lower in the dry compartment when soil volumetric water content dropped below 0.22cm(3) cm(-3) for both spatial distributions of soil moisture. However, [ABA]root increased in response to decreasing Ψroot in the dry compartment only for HPRD, resulting in much higher ABA accumulation than in VPRD. The position of the sampled roots (~4cm closer to the surface in the dry compartment of VPRD than in HPRD) might account for this difference, since older (upper) roots may accumulate less ABA in response to decreased Ψroot than younger (deeper) roots. This would explain differences in root ABA accumulation patterns under vertical and horizontal soil moisture gradients reported in the literature. In our experiment, these differences in root ABA accumulation did not influence [X-ABA], since the RWU fraction (and thus ABA export to shoots) from the dry compartment dramatically decreased simultaneously with any increase in [ABA]root. Thus, HPRD might better trigger a long-distance ABA signal than VPRD under conditions allowing simultaneous high [ABA]root and relatively high RWU fraction. © The Author 2014. Published by Oxford University Press on behalf of the Society for Experimental Biology.

  4. Analysis of soil moisture memory from observations in Europe

    Science.gov (United States)

    Orth, R.; Seneviratne, S. I.

    2012-08-01

    Soil moisture is known to show distinctive persistence characteristics compared to other quantities in the climate system. As soil moisture is governing land-atmosphere feedbacks to a large extent, its persistence can provide potential to improve seasonal climate predictions. So far, many modeling studies have investigated the nature of soil moisture memory, with consistent, but model-dependent results. This study investigates soil moisture memory in long-term observational records based on data from five stations across Europe. We investigate spatial and seasonal variations in soil moisture memory and identify their main climatic drivers. Also, we test an existing framework and introduce an extension thereof to approximate soil moisture memory and evaluate the contributions of its driving processes. At the analyzed five sites, we identify the variability of initial soil moisture divided by that of the accumulated forcing over the considered time frame as a main driver of soil moisture memory that reflects the impact of the precipitation regime and of soil and vegetation characteristics. Another important driver is found to be the correlation of initial soil moisture with subsequent forcing that captures forcing memory as it propagates to the soil and also land-atmosphere interactions. Thereby, the role of precipitation is found to be dominant for the forcing. In contrast to results from previous modeling studies, the runoff and evapotranspiration sensitivities to soil moisture are found to have only a minor influence on soil moisture persistence at the analyzed sites. For the central European sites, the seasonal cycles of soil moisture memory display a maximum in late summer and a minimum in spring. An opposite seasonal cycle is found at the analyzed site in Italy. High soil moisture memory is shown to last up to 40 days in some seasons at most sites. Extremely dry or wet states of the soil tend to increase soil moisture memory, suggesting enhanced prediction

  5. Downscaling SMAP Soil Moisture Using Geoinformation Data and Geostatistics

    Science.gov (United States)

    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.

  6. A Study of Spatial Soil Moisture Estimation Using a Multiple Linear Regression Model and MODIS Land Surface Temperature Data Corrected by Conditional Merging

    Directory of Open Access Journals (Sweden)

    Chunggil Jung

    2017-08-01

    Full Text Available This study attempts to estimate spatial soil moisture in South Korea (99,000 km2 from January 2013 to December 2015 using a multiple linear regression (MLR model and the Terra moderate-resolution imaging spectroradiometer (MODIS land surface temperature (LST and normalized distribution vegetation index (NDVI data. The MODIS NDVI was used to reflect vegetation variations. Observed precipitation was measured using the automatic weather stations (AWSs of the Korea Meteorological Administration (KMA, and soil moisture data were recorded at 58 stations operated by various institutions. Prior to MLR analysis, satellite LST data were corrected by applying the conditional merging (CM technique and observed LST data from 71 KMA stations. The coefficient of determination (R2 of the original LST and observed LST was 0.71, and the R2 of corrected LST and observed LST was 0.95 for 3 selected LST stations. The R2 values of all corrected LSTs were greater than 0.83 for total 71 LST stations. The regression coefficients of the MLR model were estimated seasonally considering the five-day antecedent precipitation. The p-values of all the regression coefficients were less than 0.05, and the R2 values were between 0.28 and 0.67. The reason for R2 values less than 0.5 is that the soil classification at each observation site was not completely accurate. Additionally, the observations at most of the soil moisture monitoring stations used in this study started in December 2014, and the soil moisture measurements did not stabilize. Notably, R2 and root mean square error (RMSE in winter were poor, as reflected by the many missing values, and uncertainty existed in observations due to freezing and mechanical errors in the soil. Thus, the prediction accuracy is low in winter due to the difficulty of establishing an appropriate regression model. Specifically, the estimated map of the soil moisture index (SMI can be used to better understand the severity of droughts with the

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

    Science.gov (United States)

    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

  8. Variabilidad espacial y diaria del contenido de humedad en el suelo en tres sistemas agroforestales Spatial and daily variability of soil moisture content in three agroforestry systems

    Directory of Open Access Journals (Sweden)

    Mariela Rivera Peña

    2009-04-01

    Full Text Available En seis puntos de tres transectos (102 m paralelos (9 m en tres sistemas de uso del terreno (Quesungual menor de dos años, SAQThe objective of this study was to determine the level of soil spatial variability in an area consisting of the land uses: Quesungual slash and mulch agroforestry system with less than two years (QSMAS<2, Slash-and-burn traditional system (SB and Secondary forest (SF. Soil samples were taken in three parallel transects of 102 m in length, separated 9 meters. The profile was sampled in the depths from 0 to 5 cm, 5 to 10 cm, 10 to 20 cm and 20 to 40 cm in 6 points (09, 11 am and 05 during 9 days. Coefficient of variation for soil properties varied for bulk density (0.76 and 15.1%, organic carbon (30.4 and 54.3%, volumetric moisture (9.5 and 23.5%, sand (12.8 and 22.5% and clay (14.0 and 29.2%. The geo-statistical analysis showed that the random component of the spatial dependence was predominant over the nugget effect. The functions of semivariograms, structured for each variable were used to generate maps of interpolated contours at a fine scale. The Moran (I autocorrelation indicated that sampling ranges less than 9 m would be adequate to detect spatial structure of the volumetric moisture variable.

  9. Spatial distribution of tree species governs the spatio-temporal interaction of leaf area index and soil moisture across a forested landscape.

    Directory of Open Access Journals (Sweden)

    Kusum J Naithani

    Full Text Available Quantifying coupled spatio-temporal dynamics of phenology and hydrology and understanding underlying processes is a fundamental challenge in ecohydrology. While variation in phenology and factors influencing it have attracted the attention of ecologists for a long time, the influence of biodiversity on coupled dynamics of phenology and hydrology across a landscape is largely untested. We measured leaf area index (L and volumetric soil water content (θ on a co-located spatial grid to characterize forest phenology and hydrology across a forested catchment in central Pennsylvania during 2010. We used hierarchical Bayesian modeling to quantify spatio-temporal patterns of L and θ. Our results suggest that the spatial distribution of tree species across the landscape created unique spatio-temporal patterns of L, which created patterns of water demand reflected in variable soil moisture across space and time. We found a lag of about 11 days between increase in L and decline in θ. Vegetation and soil moisture become increasingly homogenized and coupled from leaf-onset to maturity but heterogeneous and uncoupled from leaf maturity to senescence. Our results provide insight into spatio-temporal coupling between biodiversity and soil hydrology that is useful to enhance ecohydrological modeling in humid temperate forests.

  10. Modelling field scale spatial variation in water run-off, soil moisture, N2O emissions and herbage biomass of a grazed pasture using the SPACSYS model.

    Science.gov (United States)

    Liu, Yi; Li, Yuefen; Harris, Paul; Cardenas, Laura M; Dunn, Robert M; Sint, Hadewij; Murray, Phil J; Lee, Michael R F; Wu, Lianhai

    2018-04-01

    In this study, we evaluated the ability of the SPACSYS model to simulate water run-off, soil moisture, N 2 O fluxes and grass growth using data generated from a field of the North Wyke Farm Platform. The field-scale model is adapted via a linked and grid-based approach (grid-to-grid) to account for not only temporal dynamics but also the within-field spatial variation in these key ecosystem indicators. Spatial variability in nutrient and water presence at the field-scale is a key source of uncertainty when quantifying nutrient cycling and water movement in an agricultural system. Results demonstrated that the new spatially distributed version of SPACSYS provided a worthy improvement in accuracy over the standard (single-point) version for biomass productivity. No difference in model prediction performance was observed for water run-off, reflecting the closed-system nature of this variable. Similarly, no difference in model prediction performance was found for N 2 O fluxes, but here the N 2 O predictions were noticeably poor in both cases. Further developmental work, informed by this study's findings, is proposed to improve model predictions for N 2 O. Soil moisture results with the spatially distributed version appeared promising but this promise could not be objectively verified.

  11. Soil moisture remote sensing: State of the science

    Science.gov (United States)

    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...

  12. Nematode survival in relation to soil moisture

    NARCIS (Netherlands)

    Simons, W.R.

    1973-01-01

    Established nematode populations are very persistent in the soil. It is known that they need sufficient soil moisture for movement, feeding and reproduction (fig. 5), and that there are adverse soil moisture conditions which they cannot survive. The influence of soil moisture on survival

  13. Estimation of soil moisture and its effect on soil thermal ...

    Indian Academy of Sciences (India)

    Soil moisture is an important parameter of the earth's climate system. Regression model for estimation of soil moisture at various depths has been developed using the amount of moisture near the surface layer. The estimated values of soil moisture are tested with the measured moisture values and it is found that the ...

  14. SMEX03 Little Washita Micronet Soil Moisture Data: Oklahoma

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set contains volumetric soil moisture, soil temperature, soil conductivity, soil salinity, and surface temperature data collected during the Soil Moisture...

  15. Modeling Spatial and Temporal Variability of Soil Moisture in Shallow Depths of the Vadose Zone: A Comparison of two and Three Dimensional Simulations to Capture Relevant Physical Processes

    Science.gov (United States)

    Smits, K. M.; Frippiat, C.; Sakaki, T.; Illangasekare, T. H.

    2008-12-01

    The distribution of water saturation of soils near the ground surface is of interest in various applications involving soil moisture variations due to land-atmospheric interaction, evaporation from soils and land mine detection. Natural soil heterogeneity in combination with water flux conditions at the soil surface creates complex spatial and temporal distributions of soil moisture in the near-surface vadose zone. Validation of numerical models that are designed to capture these processes is difficult due to the inherent complexities of the problem and the scarcity of laboratory data with accurately known hydraulic parameters. A few 3-D experimental studies have been performed in attempts to generate such data. However, these experiments are tedious to setup and many challenges exist in getting accurate spatially and temporally varying measurements of water saturation and pressure. As a result, most of the experimental studies simulating multiphase flow processes in the heterogeneous vadose zone are carried out in 1-D or 2-D test systems. The issue is then to determine whether results obtained in such simplified conditions capture the relevant physical processes occurring in real 3-D heterogeneous situations. A numerical study was conducted to compare the spatial and temporal variability of soil moisture in a 3-D heterogeneous synthetic aquifer with the predictions of simplified 2-D models of vertical slices of the aquifer. The heterogeneous medium is composed of five different sandy materials, with air entry pressures ranging from 9.7 to 81.8 cm and saturated hydraulic conductivities ranging from 0.597 to 0.0067 cm/s. The numerical experiment designed around a synthetic 3-D aquifer consists of (1) simulating the drainage of the synthetic aquifer, starting from a fully saturated situation, and (2) inducing evaporation at the surface after liquid drainage has ceased. We compare results from 3-D and 2-D numerical simulations at several point locations, representing

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

    Science.gov (United States)

    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.

  17. Use of Soil Moisture Variability in Artificial Neural Network Retrieval of Soil Moisture

    Directory of Open Access Journals (Sweden)

    Bert Veenendaal

    2009-12-01

    Full Text Available Passive microwave remote sensing is one of the most promising techniques for soil moisture retrieval. However, the inversion of soil moisture from brightness temperature observations is not straightforward, as it is influenced by numerous factors such as surface roughness, vegetation cover, and soil texture. Moreover, the relationship between brightness temperature, soil moisture and the factors mentioned above is highly non-linear and ill-posed. Consequently, Artificial Neural Networks (ANNs have been used to retrieve soil moisture from microwave data, but with limited success when dealing with data different to that from the training period. In this study, an ANN is tested for its ability to predict soil moisture at 1 km resolution on different dates following training at the same site for a specific date. A novel approach that utilizes information on the variability of soil moisture, in terms of its mean and standard deviation for a (sub region of spatial dimension up to 40 km, is used to improve the current retrieval accuracy of the ANN method. A comparison between the ANN with and without the use of the variability information showed that this enhancement enables the ANN to achieve an average Root Mean Square Error (RMSE of around 5.1% v/v when using the variability information, as compared to around 7.5% v/v without it. The accuracy of the soil moisture retrieval was further improved by the division of the target site into smaller regions down to 4 km in size, with the spatial variability of soil moisture calculated from within the smaller region used in the ANN. With the combination of an ANN architecture of a single hidden layer of 20 neurons and the dual-polarized brightness temperatures as input, the proposed use of variability and sub-region methodology achieves an average retrieval accuracy of 3.7% v/v. Although this accuracy is not the lowest as comparing to the research in this field, the main contribution is the ability of ANN in

  18. Propagation of soil moisture memory into the climate system

    Science.gov (United States)

    Orth, R.; Seneviratne, S. I.

    2012-04-01

    Soil moisture is known for its integrative behaviour and resulting memory characteristics. Associated anomalies can persist for weeks or even months into the future, making initial soil moisture an important potential component in weather forecasting. This is particularly crucial given the role of soil moisture for land-atmosphere interactions and its impacts on the water and energy balances on continents. We present here an analysis of the characteristics of soil moisture memory and of its propagation into runoff and evapotranspiration in Europe, based on available measurements from several sites across the continent and expanding a previous analysis focused on soil moisture [1]. We identify the main drivers of soil moisture memory at the analysed sites, as well as their role for the propagation of soil moisture persistence into runoff and evapotranspiration memory characteristics. We focus on temporal and spatial variations in these relationships and identify seasonal and latitudinal differences in the persistence of soil moisture, evapotranspiration and runoff. Finally, we assess the role of these persistence characteristics for the development of agricultural and hydrological droughts. [1] Orth and Seneviratne: Analysis of soil moisture memory from observations in Europe; submitted to J. Geophysical Research.

  19. Measurement of soil moisture using gypsum blocks

    DEFF Research Database (Denmark)

    Friis Dela, B.

    For the past 50 years, gypsum blocks have been used to determine soil moisture content. This report describes a method for calibrating gypsum blocks for soil moisture measurements. Moisture conditions inside a building are strongly influenced by the moisture conditions in the soil surrounding...... the building. Consequently, measuring the moisture of the surrounding soil is of great importance for detecting the source of moisture in a building. Up till now, information has been needed to carry out individual calibrations for the different types of gypsum blocks available on the market and to account...

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

    Science.gov (United States)

    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.

  1. Remotely sensed soil moisture input to a hydrologic model

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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

  3. Assimilating soil moisture into an Earth System Model

    Science.gov (United States)

    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

  4. Local- and plot-scale measurements of soil moisture: time and spatially resolved field techniques in plain, hill and mountain sites

    OpenAIRE

    Raffelli, Giulia; Previati, Maurizio; Canone, Davide; Gisolo, Davide; Bevilacqua, Ivan; Capello, Giorgio; Biddoccu, Marcella; Cavallo, Eugenio; Deiana, Rita; Cassiani, Giorgio; Ferraris, Stefano

    2017-01-01

    Soil moisture measurement is essential to validate hydrological models and satellite data. In this work we provide an overview of different local and plot scale soil moisture measurement techniques applied in three different conditions in terms of altitude, land use, and soil type, namely a plain, a mountain meadow and a hilly vineyard. The main goal is to provide a synoptic view of techniques supported by practical case studies to show that in such different conditions it is possible to esti...

  5. Evaluating ESA CCI Soil Moisture in East Africa

    Science.gov (United States)

    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.

  6. A Novel Bias Correction Method for Soil Moisture and Ocean Salinity (SMOS Soil Moisture: Retrieval Ensembles

    Directory of Open Access Journals (Sweden)

    Ju Hyoung Lee

    2015-12-01

    Full Text Available Bias correction is a very important pre-processing step in satellite data assimilation analysis, as data assimilation itself cannot circumvent satellite biases. We introduce a retrieval algorithm-specific and spatially heterogeneous Instantaneous Field of View (IFOV bias correction method for Soil Moisture and Ocean Salinity (SMOS soil moisture. To the best of our knowledge, this is the first paper to present the probabilistic presentation of SMOS soil moisture using retrieval ensembles. We illustrate that retrieval ensembles effectively mitigated the overestimation problem of SMOS soil moisture arising from brightness temperature errors over West Africa in a computationally efficient way (ensemble size: 12, no time-integration. In contrast, the existing method of Cumulative Distribution Function (CDF matching considerably increased the SMOS biases, due to the limitations of relying on the imperfect reference data. From the validation at two semi-arid sites, Benin (moderately wet and vegetated area and Niger (dry and sandy bare soils, it was shown that the SMOS errors arising from rain and vegetation attenuation were appropriately corrected by ensemble approaches. In Benin, the Root Mean Square Errors (RMSEs decreased from 0.1248 m3/m3 for CDF matching to 0.0678 m3/m3 for the proposed ensemble approach. In Niger, the RMSEs decreased from 0.14 m3/m3 for CDF matching to 0.045 m3/m3 for the ensemble approach.

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

    Science.gov (United States)

    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

    Science.gov (United States)

    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. Estimation of soil moisture and its effect on soil thermal ...

    Indian Academy of Sciences (India)

    clay loam. The clay increase in subsurface layers qualifies these soils to be placed under ultisols. The experimental site belongs to soils of laterite landscape .... simulation models. Studies on some of the charac- teristics of soil moisture variations in the surface layer and the movement of moisture through the soil have been ...

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

    Science.gov (United States)

    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.

  11. Nitric oxide (NO) emissions from N-saturated subtropical forest soils are strongly affected by spatial and temporal variability in soil moisture

    Science.gov (United States)

    Kang, Ronghua; Dörsch, Peter; Mulder, Jan

    2016-04-01

    Subtropical forests in Southwest China have chronically high nitrogen (N) deposition. This results in high emission rates of N gasses, including N2O, NO and N2. In contrast to N2O, NO emission in subtropical China has received little attention, partly because its quantification is challenging. Here we present NO fluxes in a Masson pine-dominated headwater catchment with acrisols on mesic, well-drained hill slopes at TieShanPing (Chongqing, SW China). Measurements were conducted from July to September in 2015, using a dynamic chamber technique and a portable and highly sensitive chemiluminesence NOx analyzer (LMA-3M, Drummond Technology Inc, Canada). Mean NO fluxes as high as 120 μg N m-2 h-1 (± 56 μg N m-2 h-1) were observed at the foot of the hill slope. Mid-slope positions had intermediate NO emission rates (47 ± 17 μg N m-2 h-1), whereas the top of the hill slope showed the lowest NO fluxes (3 ± 3 μg N m-2 h-1). The magnitude of NO emission seemed to be controlled mainly by site-specific soil moisture, which was on average lower at the foot of the hill slope and in mid-slope positions than at the top of the hill slope. Rainfall episodes caused a pronounced decline in NO emission fluxes in all hill slope positions, whereas the subsequent gradual drying of the soil resulted in an increase. NO fluxes were negatively correlated with soil moisture (r2 = 0.36, p ˂ 0.05). The NO fluxes increased in the early morning, and decreased in the late afternoon, with peak emissions occurring between 2 and 3 pm. The diurnal variation of NO fluxes on mid-slope positions was positively correlated with soil temperature (r2 = 0.9, p ˂ 0.05). Our intensive measurements indicate that NO-N emissions in N-saturated subtropical forests are significant and strongly controlled by local hydrological conditions.

  12. Soil moisture from operational meteorological satellites

    NARCIS (Netherlands)

    Wagner, W; Naeimi, V.; Scipal, K.; De Jeu, R.A.M.; Fernandez, M.

    2007-01-01

    In recent years, unforeseen advances in monitoring soil moisture from operational satellite platforms have been made, mainly due to improved geophysical retrieval methods. In this study, four recently published soil-moisture datasets are compared with in-situ observations from the REMEDHUS

  13. Soil moisture from Operational Meteorological Satellites

    NARCIS (Netherlands)

    Wagner, W.; Naeimi, V.; Scipal, K.; de Jeu, R.A.M.; Martinez-Fernandez, J.

    2007-01-01

    In recent years, unforeseen advances in monitoring soil moisture from operational satellite platforms have been made, mainly due to improved geophysical retrieval methods. In this study, four recently published soil-moisture datasets are compared with in-situ observations from the REMEDHUS

  14. Soil Moisture Measurement System For An Improved Flood Warning

    Science.gov (United States)

    Schaedel, W.; Becker, R.

    Precipitation-runoff processes are correlated with the catchment's hydrological pre- conditions that are taken into account in some hydrological models, e.g. by pre- precipitation index. This statistically generated variable is unsuitable in case of ex- treme flood events. Thus a non-statistical estimation of the catchment's preconditions is of tremendous importance for an improvement in reliability of flood warning. This can be achieved by persistent operational observation of the catchment's soil mois- ture condition. The soil moisture acts as a state variable controlling the risk of surface runoff, which is assumed to provoke critical floods. Critical soil moisture conditions can be identified by measurements in certain areas representative for the catchment. Therefore a measurement arrangement that does not effect the structure of soils is realised with twin rod probes. Spatial resolution algorithms result in soil moisture profiles along the probe rods. In this set up a quasi three dimensional soil moisture distribution can be interpolated with point measurements of up to 47 twin rod probes per cluster, connected via multiplexer. The large number of probes per cluster is of use for detailed observation of small-scaled moisture variability. As regionalized grid cell moisture the cluster information calibrates the default, state depending soil moisture distribution of the catchment. This distribution is explained by diverse soil moisture influencing properties, which are found by Landsat satellite image. Therefore the im- age is processed with principal component analysis to extract the soil moisture distri- bution. The distribution is calibrated by the detailed measurements, acting as ground based truth. Linear multiple regression operated on the calibrated distribution identi- fies the mentioned properties. In this fashion the catchment status can be determined and combined with precipitation forecasts, thus allowing for the comprehensive risk calculation of

  15. NOAA Soil Moisture Products System (SMOPS) Daily Blended Products

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Soil Moisture Operational Products System (SMOPS) combines soil moisture retrievals from multiple satellite sensors to provide a global soil moisture map with...

  16. Testing of a conceptualisation of catchment scale surface soil moisture in a hydrologic model

    Science.gov (United States)

    Komma, J.; Parajka, J.; Naeimi, V.; Blöschl, G.; Wagner, W.

    2009-04-01

    In this study the simulated surface soil moisture of a dual layer conceptual hydrologic model is tested against ERS scatterometer top soil moisture observations. The study catchment at the Kamp river with a size of 1550 km² is located in north-eastern Austria. The hydrologic simulations in this study are based on a well calibrated hydrologic model. The model consists of a spatially distributed soil moisture accounting scheme and a flood routing component. The spatial and temporal resolutions of the model are 1 x 1 km² and 15 minutes. The soil moisture accounting scheme simulates the mean moisture state over the entire vertical soil column. To get additional information about moisture states in a thin surface soil layer from the continuous rainfall-runoff model, the soil moisture accounting scheme is extended by a thin skin soil storage sitting at the top of the main soil reservoir. The skin soil storage is filled by rain and snow melt. The skin soil reservoir and the main soil reservoir are connected by a bidirectional moisture flux which is assumed to be a linear function of the vertical soil moisture gradient. The calibration of the additional dual layer component is based on hydrologic reasoning and the incorporation of measured soil water contents close to the study catchment. The comparison of the simulated surface soil moisture with the ERS scatterometer top soil moisture observations is performed in the period 1993-2005. On average, about 3 scatterometer images per month with a mean spatial coverage of about 82% are available at the Kamp catchment. The correlation between the catchment mean values of the two top soil moisture estimates changes with the season. The differences tend to be smaller due the summer month from July to October. The results indicate a good agreement between the modelled and remote sensed spatial moisture patterns in the study area.

  17. Time series modeling of soil moisture dynamics on a steep mountainous hillside

    Science.gov (United States)

    Kim, Sanghyun

    2016-05-01

    The response of soil moisture to rainfall events along hillslope transects is an important hydrologic process and a critical component of interactions between soil vegetation and the atmosphere. In this context, the research described in this article addresses the spatial distribution of soil moisture as a function of topography. In order to characterize the temporal variation in soil moisture on a steep mountainous hillside, a transfer function, including a model for noise, was introduced. Soil moisture time series with similar rainfall amounts, but different wetness gradients were measured in the spring and fall. Water flux near the soil moisture sensors was modeled and mathematical expressions were developed to provide a basis for input-output modeling of rainfall and soil moisture using hydrological processes such as infiltration, exfiltration and downslope lateral flow. The characteristics of soil moisture response can be expressed in terms of model structure. A seasonal comparison of models reveals differences in soil moisture response to rainfall, possibly associated with eco-hydrological process and evapotranspiration. Modeling results along the hillslope indicate that the spatial structure of the soil moisture response patterns mainly appears in deeper layers. Similarities between topographic attributes and stochastic model structures are spatially organized. The impact of temporal and spatial discretization scales on parameter expression is addressed in the context of modeling results that link rainfall events and soil moisture.

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

    Science.gov (United States)

    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.

  19. On-irrigator pasture soil moisture sensor

    International Nuclear Information System (INIS)

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

    2017-01-01

    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. (paper)

  20. Transient soil moisture profile of a water-shedding soil cover in north Queensland, Australia

    Science.gov (United States)

    Gonzales, Christopher; Baumgartl, Thomas; Scheuermann, Alexander

    2014-05-01

    In current agricultural and industrial applications, soil moisture determination is limited to point-wise measurements and remote sensing technologies. The former has limitations on spatial resolution while the latter, although has greater coverage in three dimensions, but may not be representative of real-time hydrologic conditions of the substrate. This conference paper discusses the use of elongated soil moisture probes to describe the transient soil moisture profile of water-shedding soil cover trial plots in north Queensland, Australia. Three-metre long flat ribbon cables were installed at designed depths across a soil cover with substrate materials from mining activities comprising of waste rocks and blended tailings. The soil moisture measurement is analysed using spatial time domain reflectometry (STDR) (Scheuermann et al., 2009) Calibration of the flat ribbon cable's soil moisture measurement in waste rocks is undertaken in a glasshouse setting. Soil moisture retention and outflows are monitored at specific time interval by mass balance and water potential measurements. These data sets together with the soil hydrologic properties derived from laboratory and field measurements are used as input in the numerical code on unsaturated flow, Hydrus2D. The soil moisture calculations of the glasshouse calibration using this numerical method are compared with results from the STDR soil moisture data sets. In context, the purpose of the soil cover is to isolate sulphide-rich mine wastes from atmospheric interaction as oxidation and leaching of these materials may result to acid and metalliferous drainage. The long term performance of a soil cover will be described in terms of the quantities and physico-chemical characteristics of its outflows. With the soil moisture probes set at automated and pre-determined measurement time intervals, it is expected to distinguish between macropore and soil moisture flows during high intensity rainfall events and, also continuously

  1. Hysteresis of soil temperature under different soil moisture and ...

    African Journals Online (AJOL)

    ... in a solar greenhouse. The objective of this study was to find a simple method to estimate the hysteresis of soil temperature under three soil moisture and two fertilizer levels in solar greenhouse conditions with tomato crop (Lycopersicon esculentum Mill). The results show that the soil moisture had no significant effects on ...

  2. Soil moisture content with global warming

    International Nuclear Information System (INIS)

    Vinnikov, K.Ya.

    1990-01-01

    The potential greenhouse-gas-induced changes in soil moisture, particularly the desiccation of the Northern Hemisphere contents in summer, are discussed. To check the conclusions based on climate models the authors have used long-term measurements of contemporary soil moisture in the USSR and reconstructions of soil moisture for the last two epochs that were warmer than the present, namely, the Holocene optimum, 5,000-6,000 years ago, and the last interglacial, about 125,000 years ago. The analysis shows that there is a considerable disagreement between the model results and the empirical data

  3. SMEX03 Little River Micronet Soil Moisture Data: Georgia

    Data.gov (United States)

    National Aeronautics and Space Administration — Parameters for this data set include precipitation, soil temperature, volumetric soil moisture, soil conductivity, and soil salinity measured in the Little River...

  4. Multi-scale analysis of the impact of increased spatial resolution of soil moisture and atmospheric water vapour on convective precipitation

    Science.gov (United States)

    Khodayar, S.; Schaedler, G.; Kalthoff, N.

    2010-09-01

    The distribution of water vapour in the planetary boundary layer (PBL) and its development over time is one of the most important factors affecting precipitation processes. Despite the dense radiosonde network deployed during the Convective and Orographically-induced Precipitation Study (COPS), the high spatial variability of the water vapour field was not well resolved with respect to the detection of the initiation of convection. The first part of this investigation focuses on the impact of an increased resolution of the thermodynamics and dynamics of the PBL on the detection of the initiation of convection. The high spatial resolution was obtained using the synergy effect of data from the networks of radiosondes, automatic weather stations, synoptic stations, and especially Global Positioning Systems (GPSs). A method is introduced to combine GPS and radiosonde data to obtain a higher resolution representation of atmospheric water vapour. The gained spatial resolution successfully improved the representations of the areas where deep convection likelihood was high. Location and timing of the initiation of convection were critically influenced by the structure of the humidity field in the boundary-layer. The availability of moisture for precipitation is controlled by a number of processes including land surface processes, the latter are strongly influenced by spatially variable fields of soil moisture (SM) and land use. Therefore, an improved representation of both fields in regional model systems can be expected to produce better agreement between modelled and measured surface energy fluxes, boundary layer structure and precipitation. SM is currently one of the least assessed quantities with almost no data from operational monitoring networks available. However, during COPS an innovative measurement approach using a very high number of different SM sensors was introduced. The network consisted of newly developed low-cost SM sensors installed at 43 stations. Each

  5. Error Characterization of Multiple Sensor Soil Moisture Data for Improved Long-Term Global Soil Moisture Records

    Science.gov (United States)

    Dorigo, Wouter; Scipal, Klaus; de Jeu, Richard; Parinussa, Robert; Wagner, Wolfgang; Naeimi, Vahid

    2009-11-01

    In the framework of the Water Cycle Multi-mission Observation Strategy (WACMOS) project of ESA, a first multi-decadal (30+ years) global soil moisture record is generated by merging data sets from various active and passive microwave sensors. Combining multiple data sets brings many advantages in terms of enhanced temporal and spatial coverage and temporal resolution. Nevertheless, to benefit from this strategy, error budgets of the individual data sets have to be well characterized, and apt strategies for reducing the errors in the final product need to be developed.This study exploits the triple collocation error estimation technique to assess the error and systematic biases between three different independent soil moisture data sets: soil moisture data derived from the AMSR-E radiometer, scatterometer based estimates from MetOp- ASCAT, and modelled soil moisture from the ECMWF ERA Interim reanalysis program. The results suggest that the method provides realistic error estimates and allow us to identify systematic differences between the active and passive microwave derived soil moisture products, e.g. with respect to varying land cover or climatological zones. This in turn will help us in developing adequate strategies for merging active and passive observations for the generation of an accurate long-term soil moisture data set.

  6. Estimating Regional Scale Hydroclimatic Risk Conditions from the Soil Moisture Active-Passive (SMAP Satellite

    Directory of Open Access Journals (Sweden)

    Catherine Champagne

    2018-04-01

    Full Text Available Satellite soil moisture is a critical variable for identifying susceptibility to hydroclimatic risks such as drought, dryness, and excess moisture. Satellite soil moisture data from the Soil Moisture Active/Passive (SMAP mission was used to evaluate the sensitivity to hydroclimatic risk events in Canada. The SMAP soil moisture data sets in general capture relative moisture trends with the best estimates from the passive-only derived soil moisture and little difference between the data at different spatial resolutions. In general, SMAP data sets overestimated the magnitude of moisture at the wet extremes of wetting events. A soil moisture difference from average (SMDA was calculated from SMAP and historical Soil Moisture and Ocean Salinity (SMOS data showed a relatively good delineation of hydroclimatic risk events, although caution must be taken due to the large variability in the data within risk categories. Satellite soil moisture data sets are more sensitive to short term water shortages than longer term water deficits. This was not improved by adding “memory” to satellite soil moisture indices to improve the sensitivity of the data to drought, and there is a large variability in satellite soil moisture values with the same drought severity rating.

  7. SMEX02 Soil Moisture and Temperature Profiles, Walnut Creek, Iowa

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set contains rainfall, soil moisture, and soil temperature data collected for the Soil Moisture Experiment 2002 (SMEX02). The parameters measured are soil...

  8. Effects of natural and synthetic soil conditioners on soil moisture ...

    African Journals Online (AJOL)

    The efficacy of a natural soil conditioner, Coco-Peat (C-P), and synthetic soil conditioners, Terawet (T-200) and Teraflow (T-F), in improving soil moisture content were examined on five Ghanaian soil series (Akroso, Akuse, Amo, Hake and Oyarifa). In general, the water retention of T-200 and C-P treated soils were similar ...

  9. Site Averaged Neutron Soil Moisture: 1988 (Betts)

    Data.gov (United States)

    National Aeronautics and Space Administration — ABSTRACT: Site averaged product of the neutron probe soil moisture collected during the 1987-1989 FIFE experiment. Samples were averaged for each site, then averaged...

  10. CLPX-Ground: ISA Soil Moisture Measurements

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set consists of in-situ point measurements of soil moisture within three 25-km by 25-km Meso-cell Study Areas (MSAs) in northern Colorado (Fraser, North...

  11. Site Averaged Gravimetric Soil Moisture: 1989 (Betts)

    Data.gov (United States)

    National Aeronautics and Space Administration — Site averaged product of the gravimetric soil moisture collected during the 1987-1989 FIFE experiment. Samples were averaged for each site, then averaged for each...

  12. Site Averaged Gravimetric Soil Moisture: 1988 (Betts)

    Data.gov (United States)

    National Aeronautics and Space Administration — Site averaged product of the gravimetric soil moisture collected during the 1987-1989 FIFE experiment. Samples were averaged for each site, then averaged for each...

  13. Site Averaged Gravimetric Soil Moisture: 1987 (Betts)

    Data.gov (United States)

    National Aeronautics and Space Administration — ABSTRACT: Site averaged product of the gravimetric soil moisture collected during the 1987-1989 FIFE experiment. Samples were averaged for each site, then averaged...

  14. Site Averaged Gravimetric Soil Moisture: 1987 (Betts)

    Data.gov (United States)

    National Aeronautics and Space Administration — Site averaged product of the gravimetric soil moisture collected during the 1987-1989 FIFE experiment. Samples were averaged for each site, then averaged for each...

  15. Overview of soil moisture measurements with neutrons

    Science.gov (United States)

    Hendriks, Aagje; Steele-Dunne, Susan; van de Giesen, Nick

    2014-05-01

    Soil moisture measurements are useful for hydrological and agricultural applications. Soil moisture can be measured with a range of in-situ sensors in the soil, such as probes based on the difference in dielectric permittivity of wet and dry soil. At a large scale of tenths of kilometres, soil moisture can be measured with microwave remote sensing from satellites. At the intermediate scale, detection methods such as GPS reflectometry and the use of cosmic rays have been developed recently. One of the principles that can be used to measure soil moisture, is the difference in behaviour of neutrons in wet and dry soil. Neutrons are massive, electrically neutral particles that transfer their energy easily to light atoms, such as hydrogen. Therefore, in wet soil, neutrons lose their energy quickly. In dry soil, they scatter elastically from the heavy atoms and can be detected. The amount of detected neutrons is therefore inversely correlated with the amount of hydrogen in the soil. In this research we look for an overview of the possibilities to measure soil moisture with neutrons and how neutrons can be detected. Neutrons can be used to measure at the point scale and at a larger scale of approximately 1 km. We discuss in-situ measurements, in which a neutron source is put into the soil. Immediately next to the source is a detector, that counts the amount of neutrons that scatters back if the soil is dry. At a larger scale or measurement volume, we discuss the measurement of soil moisture with neutrons from cosmic rays. Cosmic rays are charged particles, accelerated by astrophysical sources (such as a Supernova). When the particles enter the atmosphere, they interact with the atmospheric atoms and form a shower. At sea level, we find several types of particles, such as muons and neutrons. We discuss why neutrons would be more useful for soil moisture measurements than other particles and how the use of cosmic-ray neutrons influences the measurement volume. Here we

  16. Collective Impacts of Orography and Soil Moisture on the Soil Moisture-Precipitation Feedback

    Science.gov (United States)

    Imamovic, Adel; Schlemmer, Linda; Schär, Christoph

    2017-11-01

    Ensembles of convection-resolving simulations with a simplified land surface are conducted to dissect the isolated and combined impacts of soil moisture and orography on deep-convective precipitation under weak synoptic forcing. In particular, the deep-convective precipitation response to a uniform and a nonuniform soil moisture perturbation is investigated both in settings with and without orography. In the case of horizontally uniform perturbations, we find a consistently positive soil moisture-precipitation feedback, irrespective of the presence of low orography. On the other hand, a negative feedback emerges with localized perturbations: a dry soil heterogeneity substantially enhances rain amounts that scale linearly with the dryness of the soil, while a moist heterogeneity suppresses rain amounts. If the heterogeneity is located in a mountainous region, the relative importance of soil moisture heterogeneity decreases with increasing mountain height: A mountain 500 m in height is sufficient to neutralize the local soil moisture-precipitation feedback.

  17. development and testing of a capacitive digital soil moisture metre

    African Journals Online (AJOL)

    The digital soil moisture meter developed was compared with gravimetric method for soil moisture determination on fifteen soil samples added different level of water during calibration process. The results revealed a relatively linear relationship between the moisture content process and the digital soil moisture meter.

  18. Creating soil moisture maps based on radar satellite imagery

    Science.gov (United States)

    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. Estimation of improved resolution soil moisture in vegetated areas using passive AMSR-E data

    Science.gov (United States)

    Moradizadeh, Mina; Saradjian, Mohammad R.

    2018-03-01

    Microwave remote sensing provides a unique capability for soil parameter retrievals. Therefore, various soil parameters estimation models have been developed using brightness temperature (BT) measured by passive microwave sensors. Due to the low resolution of satellite microwave radiometer data, the main goal of this study is to develop a downscaling approach to improve the spatial resolution of soil moisture estimates with the use of higher resolution visible/infrared sensor data. Accordingly, after the soil parameters have been obtained using Simultaneous Land Parameters Retrieval Model algorithm, the downscaling method has been applied to the soil moisture estimations that have been validated against in situ soil moisture data. Advance Microwave Scanning Radiometer-EOS BT data in Soil Moisture Experiment 2003 region in the south and north of Oklahoma have been used to this end. Results illustrated that the soil moisture variability is effectively captured at 5 km spatial scales without a significant degradation of the accuracy.

  20. Intercomparisons between passive and active microwave remote sensing, and hydrological modeling for soil moisture

    Science.gov (United States)

    Wood, E. F.; Lin, D.-S.; Mancini, M.; Thongs, D.; Troch, P. A.; Jackson, T. J.; Famiglietti, J. S.; Engman, E. T.

    1993-01-01

    Soil moisture estimations from a distributed hydrological model and two microwave sensors were compared with ground measurements collected during the MAC-HYDRO'90 experiment. The comparison was done with the purpose of evaluating the performance of the hydrological model and examining the limitations of remote sensing techniques used in soil moisture estimation. An image integration technique was used to integrate and analyze rainfall, soil properties, land cover, topography, and remote sensing imagery. Results indicate that the hydrological model and microwave sensors successfully picked up temporal variations of soil moisture and that the spatial soil moisture pattern may be remotely sensed with reasonable accuracy using existing algorithms.

  1. Irrigation Signals Detected From SMAP Soil Moisture Retrievals

    Science.gov (United States)

    Lawston, Patricia M.; Santanello, Joseph A.; Kumar, Sujay V.

    2017-12-01

    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 soil moisture 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 soil moisture product from the Soil Moisture 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.

  2. Relating coccidioidomycosis (valley fever) incidence to soil moisture conditions.

    Science.gov (United States)

    Coopersmith, E J; Bell, J E; Benedict, K; Shriber, J; McCotter, O; Cosh, M H

    2017-04-17

    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 soil moisture data sets, it has not been feasible to perform a direct analysis of the relationships between soil moisture levels and coccidioidomycosis incidence on a larger temporal and spatial scale. Utilizing in situ soil moisture 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 soil moisture 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 soil moisture 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.

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

    Science.gov (United States)

    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).

  4. Microwave Remote Sensing of Soil Moisture for Estimation of Soil Properties

    Science.gov (United States)

    Mattikalli, Nandish M.; Engman, Edwin T.; Jackson, Thomas J.

    1997-01-01

    Surface soil moisture dynamics was derived using microwave remote sensing, and employed to estimate soil physical and hydraulic properties. The L-band ESTAR radiometer was employed in an airborne campaign over the Little Washita watershed, Oklahoma during June 10-18, 1992. Brightness temperature (TB) data were employed in a soil moisture inversion algorithm which corrected for vegetation and soil effects. Analyses of spatial TB and soil moisture dynamics during the dry-down period revealed a direct relationship between changes in TB, soil moisture and soil texture. Extensive regression analyses were carried out which yielded statistically significant quantitative relationships between ratio of percent sand to percent clay (RSC, a term derived to quantify soil texture) and saturated hydraulic conductivity (Ksat) in terms of change components of TB and surface soil moisture. Validation of results indicated that both RSC and Ksat can be estimated with reasonable accuracy. These findings have potential applications for deriving spatial distributions of RSC and Ksat over large areas.

  5. Horizontal and vertical variability of soil moisture in savanna ecosystems

    Science.gov (United States)

    Caylor, K.; D'Odorico, P.; Rodriguez-Iturbe, I.

    2004-12-01

    Soil moisture is a key hydrological variable that mediates the interactions between climate, soil, and vegetation dynamics in water-limited ecosystems. Because of the importance of water limitation in savannas, a number of theoretical models of tree-grass coexistence have been developed which differ in their underlying assumptions about the ways in which trees and grasses access and use soil moisture. However, clarification of the mechanisms that allow savanna vegetation to persist as a mixture of grasses and trees remains a vexing problem in both hydrological and vegetation science. A particular challenge is the fact that the spatial pattern of vegetation is both a cause and effect of variation in water availability in semiarid ecosystems. At landscape to regional scales, climatic and geologic constraints on soil moisture availability are primary determinants of vegetation structural pattern. However, at local to landscape scales the patchy vegetation structural mosaic serves to redistribute the availability of soil moisture in ways that have important consequences for structural dynamics and community composition. In this regard, the emerging field of ecohydrology is well suited to investigate questions concerning couplings between the patchy structural mosaic of savanna vegetation and the kinds self-organizing dynamics known to exist in other light and nutrient-limited vegetation systems. Here we address the role of patchy vegetation structure through the use of a lumped model of soil moisture dynamics that accounts for the effect of tree canopy on the lateral and vertical distribution of soil moisture. The model includes mechanisms for the drying of the ground surface due to soil evaporation in the sites with no tree cover, and for the lateral water uptake due to root invading areas with no canopy cover located in the proximity of trees. The model, when applied to a series of sites along a rainfall gradient in southern Africa, is able to explain the cover

  6. SMEX03 Regional Ground Soil Moisture Data: Georgia, Version 1

    Data.gov (United States)

    National Aeronautics and Space Administration — The parameters for this data set include gravimetric soil moisture, volumetric soil moisture, bulk density, and surface and soil temperature for the Georgia study...

  7. SMEX03 Regional Ground Soil Moisture Data: Alabama, Version 1

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set comprises gravimetric soil moisture and soil bulk density data collected during the Soil Moisture Experiment 2003 (SMEX03), which was conducted during...

  8. SMEX03 Regional Ground Soil Moisture Data: Alabama

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set comprises gravimetric soil moisture and soil bulk density data collected during the Soil Moisture Experiment 2003 (SMEX03), which was conducted during...

  9. SMEX03 Regional Ground Soil Moisture Data: Oklahoma

    Data.gov (United States)

    National Aeronautics and Space Administration — The parameters for this data set include gravimetric soil moisture, volumetric soil moisture, bulk density, and surface and soil temperature for the Oklahoma study...

  10. SMEX02 Iowa Regional Ground Soil Moisture Data

    Data.gov (United States)

    National Aeronautics and Space Administration — The parameters for this data set include gravimetric and volumetric soil moisture, bulk density, and soil temperature. This data set is part of the Soil Moisture...

  11. SMEX03 Regional Ground Soil Moisture Data: Georgia

    Data.gov (United States)

    National Aeronautics and Space Administration — The parameters for this data set include gravimetric soil moisture, volumetric soil moisture, bulk density, and surface and soil temperature for the Georgia study...

  12. Effects of soil moisture content and temperature on methane uptake by grasslands on sandy soils.

    NARCIS (Netherlands)

    Pol-Van Dasselaar, van den A.; Beusichem, van M.L.; Oenema, O.

    1998-01-01

    Aerobic grasslands may consume significant amounts of atmospheric methane (CH4). We aimed (i) to assess the spatial and temporal variability of net CH4 fluxes from grasslands on aerobic sandy soils, and (ii) to explain the variability in net CH4 fluxes by differences in soil moisture content and

  13. A method to downscale soil moisture to fine-resolutions using topographic, vegetation, and soil data

    Science.gov (United States)

    Soil moisture can be estimated over large regions with spatial resolutions greater than 500 m, but many applications require finer resolutions (10 – 100 m grid cells). Several methods use topographic data to downscale, but vegetation and soil patterns can also be important. In this paper, a downsc...

  14. Global response of the growing season to soil moisture and topography

    Science.gov (United States)

    Guevara, M.; Arroyo, C.; Warner, D. L.; Equihua, J.; Lule, A. V.; Schwartz, A.; Taufer, M.; Vargas, R.

    2017-12-01

    Soil moisture has a direct influence in plant productivity. Plant productivity and its greenness can be inferred by remote sensing with higher spatial detail than soil moisture. The objective was to improve the coarse scale of currently available satellite soil moisture estimates and identify areas of strong coupling between the interannual variability soil moisture and the maximum greenness vegetation fraction (MGVF) at the global scale. We modeled, cross-validated and downscaled remotely sensed soil moisture using machine learning and digital terrain analysis across 23 years (1991-2013) of available data. Improving the accuracy (0.69-0.87 % of cross-validated explained variance) and the spatial detail (from 27 to 15km) of satellite soil moisture, we filled temporal gaps of information across vegetated areas where satellite soil moisture does not work properly. We found that 7.57% of global vegetated area shows strong correlation with our downscaled product (R2>0.5, Fig. 1). We found a dominant positive response of vegetation greenness to topography-based soil moisture across water limited environments, however, the tropics and temperate environments of higher latitudes showed a sparse negative response. We conclude that topography can be used to effectively improve the spatial detail of globally available remotely sensed soil moisture, which is convenient to generate unbiased comparisons with global vegetation dynamics, and better inform land and crop modeling efforts.

  15. development and testing of a capacitive digital soil moisture metre

    African Journals Online (AJOL)

    user

    moisture meter developed was compared with gravimetric method for soil moisture determination on fifteen soil samples added different level of water during calibration process. The results revealed a relatively linear relationship between the moisture content process and the digital soil moisture meter. The regression ...

  16. Soil moisture in sessile oak forest gaps

    Science.gov (United States)

    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.

  17. Application of Multitemporal Remotely Sensed Soil Moisture for the Estimation of Soil Physical Properties

    Science.gov (United States)

    Mattikalli, N. M.; Engman, E. T.; Jackson, T. J.; Ahuja, L. R.

    1997-01-01

    This paper demonstrates the use of multitemporal soil moisture derived from microwave remote sensing to estimate soil physical properties. The passive microwave ESTAR instrument was employed during June 10-18, 1992, to obtain brightness temperature (TB) and surface soil moisture data in the Little Washita watershed, Oklahoma. Analyses of spatial and temporal variations of TB and soil moisture during the dry-down period revealed a direct relationship between changes in T and soil moisture and soil 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 soil moisture. Validation of results using field measured values and soil 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.

  18. Soil moisture estimation in cereal fields using multipolarized SAR data

    Science.gov (United States)

    Alvarez-Mozos, J.; Izagirre, A.; Larrañaga, A.

    2012-04-01

    The retrieval of soil moisture from remote sensing data is an extremely active research topic with applications on a wide range of disciplines. Microwave observations represent the most viable approach due to the influence of soils' dielectric constant (and thus soil moisture) on both the emission and backscatter of waves in this region of the spectrum. Passive observations provide higher temporal resolutions, whereas active (SAR) observations have a higher spatial detail. Even if operational moisture products, based on passive data, exist, retrieval algorithms using active observations still face several problems. Surface roughness and vegetation cover are probably the disturbing factors most affecting the accuracy of soil moisture retrievals. In this communication the influence of vegetation cover is investigated and a retrieval technique based on multipolarized C band SAR observations is proposed. With this aim a dedicated field campaign was carried out in La Tejería watershed (north of Spain) from January to August 2010. Eight RADARSAT-2 Fine-Quadpol scenes were acquired in order to investigate the role of vegetation cover on the retrieval of soil moisture, as well as the sensitivity of different polarimetric parameters to vegetation cover condition. Coinciding with image acquisitions soil moisture, plant density and crop height measurements were acquired in eight control fields (cultivated with barley and wheat crops). The sensitivity of backscatter coefficients (in HH, HV and VV polarizations) and backscatter ratios (p=HH/VV and q=HV/VV) to soil moisture and crop condition were evaluated and the semi-empirical Water Cloud Model was fitted to the observations. The results obtained showed that the contribution of the cereal vegetation cover was minimal in HH and HV polarizations, whereas the VV channel appeared to be significantly attenuated by the cereal cover, so its value decreased as the crops grew. As a result, the ratios p and q showed a very good

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

    Science.gov (United States)

    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 soil moisture changes on model projections of the West African Monsoon under global warming. Soil moisture-atmosphere interactions have been shown in prior studies to play an important role in this region, but the potential feedbacks of long-term soil moisture 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 soil moisture change. Importantly, we find that climate models exhibit soil moisture-precipitation feedbacks of different sign in this region: in some models soil moisture changes amplify precipitation changes (positive feedback), in others they dampen them

  20. Small-scale soil moisture determination with GPR

    Science.gov (United States)

    Igel, Jan; Preetz, Holger

    2010-05-01

    The knowledge of topsoil moisture distribution is an important input for modelling water flow and evapotranspiration which are essential processes in hydrology, meteorology, and agriculture. All these processes involve non-linear effects and thus the small-scale variability of input parameters play an important role. Using smoothed interpolations instead can cause significant biases. Lateral soil moisture distribution can be sensed by different techniques at various scales whereby geophysical methods provide spatial information which closes the gap between point measurements by classical soil scientific methods and measurements on the field or regional scale by remote sensing. Ground-penetrating radar (GPR) can be used to explore soil moisture on the field scale as propagation of electromagnetic waves is correlated to soil water content. By determining the velocity of the ground wave, which is a guided wave travelling along the soil surface, we can sense soil water content. This method has been applied to determine topsoil moisture for several years. We present a new groundwave technique which determines the velocity in between two receiving antennas which enables a higher lateral resolution (approx. 10 cm) compared to classical groundwave technique (half meter and more). We present synthetic data from finite-differences (FD) calculations as well as data from a sandbox experiment carried out under controlled conditions to demonstrate the performance of this method. Further, we carried out field measurements on two sites on a sandy soil which is used as grassland. The measurements were carried out in late summer at dry soil conditions. Soil moisture on the first site shows an isotropic pattern with correlation lengths of approx. 35 cm. We think this natural pattern is governed by rout distribution within the soil and the water uptake of vegetation. On the second site, soil moisture distribution shows a regular stripe pattern. As the land has been used as

  1. Role of subsurface physics in the assimilation of surface soil moisture observations

    Science.gov (United States)

    Soil moisture controls the exchange of water and energy between the land surface and the atmosphere and exhibits memory that may be useful for climate prediction at monthly time scales. Though spatially distributed observations of soil moisture are increasingly becoming available from remotely sense...

  2. Merging thermal and microwave satellite observations for a high-resolution soil moisture data product

    Science.gov (United States)

    Many societal applications of soil moisture data products require high spatial resolution and numerical accuracy. Current thermal geostationary satellite sensors (GOES Imager and GOES-R ABI) could produce 2-16km resolution soil moisture proxy data. Passive microwave satellite radiometers (e.g. AMSR...

  3. Relation Between the Rainfall and Soil Moisture During Different Phases of Indian Monsoon

    Science.gov (United States)

    Varikoden, Hamza; Revadekar, J. V.

    2017-12-01

    Soil moisture is a key parameter in the prediction of southwest monsoon rainfall, hydrological modelling, and many other environmental studies. The studies on relationship between the soil moisture and rainfall in the Indian subcontinent are very limited; hence, the present study focuses the association between rainfall and soil moisture during different monsoon seasons. The soil moisture data used for this study are the ESA (European Space Agency) merged product derived from four passive and two active microwave sensors spanning over the period 1979-2013. The rainfall data used are India Meteorological Department gridded daily data. Both of these data sets are having a spatial resolution of 0.25° latitude-longitude grid. The study revealed that the soil moisture is higher during the southwest monsoon period similar to rainfall and during the pre-monsoon period, the soil moisture is lower. The annual cycle of both the soil moisture and rainfall has the similitude of monomodal variation with a peak during the month of August. The interannual variability of soil moisture and rainfall shows that they are linearly related with each other, even though they are not matched exactly for individual years. The study of extremes also exhibits the surplus amount of soil moisture during wet monsoon years and also the regions of surplus soil moisture are well coherent with the areas of high rainfall.

  4. Relation Between the Rainfall and Soil Moisture During Different Phases of Indian Monsoon

    Science.gov (United States)

    Varikoden, Hamza; Revadekar, J. V.

    2018-03-01

    Soil moisture is a key parameter in the prediction of southwest monsoon rainfall, hydrological modelling, and many other environmental studies. The studies on relationship between the soil moisture and rainfall in the Indian subcontinent are very limited; hence, the present study focuses the association between rainfall and soil moisture during different monsoon seasons. The soil moisture data used for this study are the ESA (European Space Agency) merged product derived from four passive and two active microwave sensors spanning over the period 1979-2013. The rainfall data used are India Meteorological Department gridded daily data. Both of these data sets are having a spatial resolution of 0.25° latitude-longitude grid. The study revealed that the soil moisture is higher during the southwest monsoon period similar to rainfall and during the pre-monsoon period, the soil moisture is lower. The annual cycle of both the soil moisture and rainfall has the similitude of monomodal variation with a peak during the month of August. The interannual variability of soil moisture and rainfall shows that they are linearly related with each other, even though they are not matched exactly for individual years. The study of extremes also exhibits the surplus amount of soil moisture during wet monsoon years and also the regions of surplus soil moisture are well coherent with the areas of high rainfall.

  5. Data assimilation of soil water flow via ensemble Kalman filter: Infusing soil moisture data at different scales

    Science.gov (United States)

    Zhu, Penghui; Shi, Liangsheng; Zhu, Yan; Zhang, Qiuru; Huang, Kai; Williams, Mathew

    2017-12-01

    This paper assesses the value of multi-scale near-surface (0∼5 cm) soil moisture observations to improve state-only or state-parameter estimation based on the ensemble Kalman filter (EnKF). To the best of our knowledge, studies on assimilating multi-scale soil moisture data into a distributed hydrological model with a series of detailed vertical soil moisture profiles are rare. Our analysis factors include spatial measurement scales, soil spatial heterogeneity, multi-scale data with contrasting information and systematic measurement errors. Results show that coarse-scale soil moisture data are also very useful for identifying finer-scale parameters and states given biased initial parameter fields, but it becomes increasingly difficult to recover the finer-scale spatial heterogeneity of soil property as the observation grids become coarser. In state-only estimation, near-surface soil moisture data result in improvement for shallow soil moisture profiles and degradation for deeper soil moisture profiles, with stronger influences from finer-scale data. With the decrease of background spatial heterogeneity of soil property, the value of coarse-scale data increases notably. Soil moisture data at two scales with contrasting information are found to be both useful. By updating spatially correlated soil hydraulic parameters, deviated observations still contain considerably useful information for finer-scale state-parameter estimation. Eventually, by presenting a difference information assimilation method based on EnKF we successfully extract useful information from soil moisture data containing systematic measurement errors. The current study can be extended to consider more complex atmosphere input and topography, etc.

  6. McMaster Mesonet soil moisture dataset: description and spatio-temporal variability analysis

    Directory of Open Access Journals (Sweden)

    K. C. Kornelsen

    2013-04-01

    Full Text Available This paper introduces and describes the hourly, high-resolution soil moisture dataset continuously recorded by the McMaster Mesonet located in the Hamilton-Halton Watershed in Southern Ontario, Canada. The McMaster Mesonet consists of a network of time domain reflectometer (TDR probes collecting hourly soil moisture data at six depths between 10 cm and 100 cm at nine locations per site, spread across four sites in the 1250 km2 watershed. The sites for the soil moisture arrays are designed to further improve understanding of soil moisture dynamics in a seasonal climate and to capture soil moisture transitions in areas that have different topography, soil and land cover. The McMaster Mesonet soil moisture constitutes a unique database in Canada because of its high spatio-temporal resolution. In order to provide some insight into the dominant processes at the McMaster Mesonet sites, a spatio-temporal and temporal stability analysis were conducted to identify spatio-temporal patterns in the data and to suggest some physical interpretation of soil moisture variability. It was found that the seasonal climate of the Great Lakes Basin causes a transition in soil moisture patterns at seasonal timescales. During winter and early spring months, and at the meadow sites, soil moisture distribution is governed by topographic redistribution, whereas following efflorescence in the spring and summer, soil moisture spatial distribution at the forested site was also controlled by vegetation canopy. Analysis of short-term temporal stability revealed that the relative difference between sites was maintained unless there was significant rainfall (> 20 mm or wet conditions a priori. Following a disturbance in the spatial soil moisture distribution due to wetting, the relative soil moisture pattern re-emerged in 18 to 24 h. Access to the McMaster Mesonet data can be provided by visiting www.hydrology.mcmaster.ca/mesonet.

  7. The sensitivity of soil respiration to soil temperature, moisture, and carbon supply at the global scale.

    Science.gov (United States)

    Hursh, Andrew; Ballantyne, Ashley; Cooper, Leila; Maneta, Marco; Kimball, John; Watts, Jennifer

    2017-05-01

    Soil 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, moisture, carbon supply, and other site characteristics are known to regulate soil 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 soil moisture, soil temperature, primary productivity, and soil carbon estimates with observations of annual Rs from the Global Soil Respiration Database (SRDB). We find that calibrating models with parabolic soil moisture functions can improve predictive power over similar models with asymptotic functions of mean annual precipitation. Soil 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 soil moisture and soil carbon emerge as dominant predictors of Rs. We identify regions where typical temperature-driven responses are further mediated by soil moisture, precipitation, and carbon supply and regions in which environmental controls on high Rs values are difficult to ascertain due to limited field data. Because soil moisture 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 moisture 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

  8. Estimation of Soil Moisture Under Vegetation Cover at Multiple Frequencies

    Science.gov (United States)

    Jadghuber, Thomas; Hajnsek, Irena; Weiß, Thomas; Papathanassiou, Konstantinos P.

    2015-04-01

    Soil moisture 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, soil and vegetation measurements were conducted on different agricultural test fields. The results indicate a spatially continuous inversion of soil moisture 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 moisture pattern inconsistencies and in some cases an incorrectly high inversion of soil moisture 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 soil moisture estimation under vegetation cover can only be conducted at L-band due to a constant availability of the soil signal in contrast to higher frequencies (X- and C-band).

  9. Variability of soil moisture and its relationship with surface albedo ...

    Indian Academy of Sciences (India)

    30 N latitude) are used to study the diurnal, monthly and seasonal soil moisture variations. The effect of rainfall on diurnal and seasonal soil moisture is discussed. We have investigated relationships of soil moisture with sur- face albedo and soil thermal diffusivity. The diurnal variation of surface albedo appears as a.

  10. A soil moisture network for SMOS validation in Western Denmark

    DEFF Research Database (Denmark)

    Bircher, Simone; Skou, N.; Jensen, Karsten Høgh

    2012-01-01

    The Soil Moisture and Ocean Salinity Mission (SMOS) acquires surface soil moisture data of global coverage every three days. Product validation for a range of climate and environmental conditions across continents is a crucial step. For this purpose, a soil moisture and soil temperature sensor...

  11. FASST Soil Moisture, Soil Temperature: Original Versus New

    National Research Council Canada - National Science Library

    Frankenstein, Susan

    2008-01-01

    .... In determining the new soil temperatures and moistures, the original model first achieved convergence in the temperature profile followed by the moisture profile at a given time step. The new version of FASST solves both of these sets of equations simultaneously. No changes have been made to the equations describing the canopy physical state except to allow for mixed precipitation.

  12. Soil moisture under contrasted atmospheric conditions in Eastern Spain

    Science.gov (United States)

    Azorin-Molina, César; Cerdà, Artemi; Vicente-Serrano, Sergio M.

    2014-05-01

    Soil moisture plays a key role on the recently abandoned agriculture land where determine the recovery and the erosion rates (Cerdà, 1995), on the soil 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, Soil moisture is a key factor on the semiarid land (Ziadat and Taimeh, 2013), on the productivity of the land (Qadir et al., 2013) and soils treated with amendments (Johnston et al., 2013) and on soil reclamation on drained saline-sodic soils (Ghafoor et al., 2012). In previous study (Azorin-Molina et al., 2013) we investigated the intraannual evolution of soil moisture in soils under different land managements in the Valencia region, Eastern Spain, and concluded that soil moisture recharges are much controlled by few heavy precipitation events; 23 recharge episodes during 2012. Most of the soil moisture recharge events occurred during the autumn season under Back-Door cold front situations. Additionally, sea breeze front episodes brought isolated precipitation and moisture to mountainous areas within summer (Azorin-Molina et al., 2009). We also evidenced that the intraanual evolution of soil moisture changes are positively and significatively correlated (at pGeoderma, 160, 599-607. 10.1016/j.geoderma.2010.11.009 Cerdà, A. 1995. Soil moisture regime under simulated rainfall in a three years abandoned field in Southeast Spain. Physics and Chemistry of The Earth, 20 (3-4), 271-279. Cerdà, A. 1999. Seasonal and spatial variations in infiltration rates in badland surfaces under Mediterranean climatic conditions. Water Resources Research, 35 (1) 319-328. Cerdà, A. 2002. The effect of season and parent material on water erosion on highly eroded soils in eastern Spain. Journal of Arid Environments, 52, 319-337. García-Fayos, P. García-Ventoso, B. Cerdà, A. 2000. Limitations to Plant establishment

  13. Downscaling soil moisture over East Asia through multi-sensor data fusion and optimization of regression trees

    Science.gov (United States)

    Park, Seonyoung; Im, Jungho; Park, Sumin; Rhee, Jinyoung

    2017-04-01

    Soil moisture is one of the most important keys for understanding regional and global climate systems. Soil moisture is directly related to agricultural processes as well as hydrological processes because soil moisture highly influences vegetation growth and determines water supply in the agroecosystem. Accurate monitoring of the spatiotemporal pattern of soil moisture is important. Soil moisture has been generally provided through in situ measurements at stations. Although field survey from in situ measurements provides accurate soil moisture with high temporal resolution, it requires high cost and does not provide the spatial distribution of soil moisture over large areas. Microwave satellite (e.g., advanced Microwave Scanning Radiometer on the Earth Observing System (AMSR2), the Advanced Scatterometer (ASCAT), and Soil Moisture Active Passive (SMAP)) -based approaches and numerical models such as Global Land Data Assimilation System (GLDAS) and Modern- Era Retrospective Analysis for Research and Applications (MERRA) provide spatial-temporalspatiotemporally continuous soil moisture products at global scale. However, since those global soil moisture products have coarse spatial resolution ( 25-40 km), their applications for agriculture and water resources at local and regional scales are very limited. Thus, soil moisture downscaling is needed to overcome the limitation of the spatial resolution of soil moisture products. In this study, GLDAS soil moisture data were downscaled up to 1 km spatial resolution through the integration of AMSR2 and ASCAT soil moisture data, Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM), and Moderate Resolution Imaging Spectroradiometer (MODIS) data—Land Surface Temperature, Normalized Difference Vegetation Index, and Land cover—using modified regression trees over East Asia from 2013 to 2015. Modified regression trees were implemented using Cubist, a commercial software tool based on machine learning. An

  14. Soil moisture sensors based on metamaterials

    Directory of Open Access Journals (Sweden)

    Goran Kitić

    2012-12-01

    Full Text Available In this paper novel miniature metamaterial-based soil moisture sensors are presented. The sensors are based on resonant-type metamaterials and employ split-ring resonators (SRR, spiral resonators and fractal SRRs to achieve small dimensions, high sensitivity, and compatibility with standard planar fabrication technologies. All these features make the proposedsensors suitable for deployment in agriculture for precise mapping of soil humidity.

  15. AMSR2 Soil Moisture Product Validation

    Science.gov (United States)

    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.

  16. Soil moisture and temperature algorithms and validation

    Science.gov (United States)

    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...

  17. A Method for Downscaling FengYun-3B Soil Moisture Based on Apparent Thermal Inertia

    Directory of Open Access Journals (Sweden)

    Chengyun Song

    2016-08-01

    Full Text Available FengYun-3B (FY-3B soil moisture product, retrieved from passive microwave brightness temperature data based on the Qp model, has rarely been applied at the catchment and region scale. One of the reasons for this is its coarse spatial resolution (25-km. The study in this paper presented a new method to obtain a high spatial resolution soil moisture product by downscaling FY-3B soil moisture product from 25-km to 1-km spatial resolution  using the theory of Apparent Thermal Inertia (ATI under bare surface or sparse vegetation covered land surface. The relationship between soil moisture and ATI was first constructed, and the coefficients were obtained directly from 25-km FY-3B soil moisture product and ATI derived from MODIS data, which is different from previous studies often assuming the same set of coefficients applicable at different spatial resolutions. The method was applied to Naqu area on the Tibetan Plateau to obtain the downscaled 1-km resolution soil moisture product, the latter was validated using ground measurements collected from Soil Moisture/Temperature Monitoring Network on the central Tibetan Plateau (TP-STMNS in 2012. The downscaled soil moisture showed promising results with a coefficient of determination R2 higher than 0.45 and a root mean-square error (RMSE less than 0.11 m3/m3 when comparing with the ground measurements at 5 sites out of the 9 selected sites. It was found that the accuracy of downscaled soil moisture was largely influenced by the accuracy of the FY-3B soil moisture product. The proposed method could be applied for both bare soil surface and sparsely vegetated surface.

  18. SMEX03 ThetaProbe Soil Moisture Data: Alabama

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set includes soil moisture data measured with Delta-T Devices’ ThetaProbe ML2 sensors for the Soil Moisture Experiment 2003 (SMEX03), conducted during June...

  19. Soil moisture mapping for aquarius

    Science.gov (United States)

    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...

  20. Statistical techniques to extract information during SMAP soil moisture assimilation

    Science.gov (United States)

    Kolassa, J.; Reichle, R. H.; Liu, Q.; Alemohammad, S. H.; Gentine, P.

    2017-12-01

    Statistical techniques permit the retrieval of soil moisture estimates in a model climatology while retaining the spatial and temporal signatures of the satellite observations. As a consequence, the need for bias correction prior to an assimilation of these estimates is reduced, which could result in a more effective use of the independent information provided by the satellite observations. In this study, a statistical neural network (NN) retrieval algorithm is calibrated using SMAP brightness temperature observations and modeled soil moisture estimates (similar to those used to calibrate the SMAP Level 4 DA system). Daily values of surface soil moisture are estimated using the NN and then assimilated into the NASA Catchment model. The skill of the assimilation estimates is assessed based on a comprehensive comparison to in situ measurements from the SMAP core and sparse network sites as well as the International Soil Moisture Network. The NN retrieval assimilation is found to significantly improve the model skill, particularly in areas where the model does not represent processes related to agricultural practices. Additionally, the NN method is compared to assimilation experiments using traditional bias correction techniques. The NN retrieval assimilation is found to more effectively use the independent information provided by SMAP resulting in larger model skill improvements than assimilation experiments using traditional bias correction techniques.

  1. Global Soil Moisture from the Aquarius/SAC-D Satellite: Description and Initial Assessment

    Science.gov (United States)

    Bindlish, Rajat; Jackson, Thomas; Cosh, Michael; Zhao, Tianjie; O'Neil, Peggy

    2015-01-01

    Aquarius satellite observations over land offer a new resource for measuring soil moisture from space. Although Aquarius was designed for ocean salinity mapping, our objective in this investigation is to exploit the large amount of land observations that Aquarius acquires and extend the mission scope to include the retrieval of surface soil moisture. The soil moisture retrieval algorithm development focused on using only the radiometer data because of the extensive heritage of passive microwave retrieval of soil moisture. The single channel algorithm (SCA) was implemented using the Aquarius observations to estimate surface soil moisture. Aquarius radiometer observations from three beams (after bias/gain modification) along with the National Centers for Environmental Prediction model forecast surface temperatures were then used to retrieve soil moisture. Ancillary data inputs required for using the SCA are vegetation water content, land surface temperature, and several soil and vegetation parameters based on land cover classes. The resulting global spatial patterns of soil moisture were consistent with the precipitation climatology and with soil moisture from other satellite missions (Advanced Microwave Scanning Radiometer for the Earth Observing System and Soil Moisture Ocean Salinity). Initial assessments were performed using in situ observations from the U.S. Department of Agriculture Little Washita and Little River watershed soil moisture networks. Results showed good performance by the algorithm for these land surface conditions for the period of August 2011-June 2013 (rmse = 0.031 m(exp 3)/m(exp 3), Bias = -0.007 m(exp 3)/m(exp 3), and R = 0.855). This radiometer-only soil moisture product will serve as a baseline for continuing research on both active and combined passive-active soil moisture algorithms. The products are routinely available through the National Aeronautics and Space Administration data archive at the National Snow and Ice Data Center.

  2. Neutron moisture gaging of agricultural soil

    International Nuclear Information System (INIS)

    Pospisil, S.; Janout, Z.; Kovacik, M.

    1987-01-01

    The design is described of a neutron moisture gage which consists of a measuring probe, neutron detector, small electronic recording device and a 241 Am-Be radionuclide source. The neutron detector consists of a surface barrier semiconductor silicon detector and a conversion layer of lithium fluoride. The detection of triton which is the reaction product of lithium with neutrons by the silicon detector is manifested as a voltage pulse. The detector has low sensitivity for fast neutrons and for gamma radiation and is suitable for determining moisture values in large volume samples. Verification and calibration measurements were carried out of chernozem, brown soil and podzolic soils in four series. The results are tabulated. Errors of measurement range between 0.8 to 1.0%. The precision of measurement could be improved by the calibration of the device for any type of soil. (E.S.). 4 tabs., 6 refs., 5 figs

  3. Using repeat electrical resistivity surveys to assess heterogeneity in soil moisture dynamics under contrasting vegetation types

    Science.gov (United States)

    Dick, Jonathan; Tetzlaff, Doerthe; Bradford, John; Soulsby, Chris

    2018-04-01

    As the relationship between vegetation and soil moisture is complex and reciprocal, there is a need to understand how spatial patterns in soil moisture influence the distribution of vegetation, and how the structure of vegetation canopies and root networks regulates the partitioning of precipitation. Spatial patterns of soil moisture are often difficult to visualise as usually, soil moisture is measured at point scales, and often difficult to extrapolate. Here, we address the difficulties in collecting large amounts of spatial soil moisture data through a study combining plot- and transect-scale electrical resistivity tomography (ERT) surveys to estimate soil moisture in a 3.2 km2 upland catchment in the Scottish Highlands. The aim was to assess the spatio-temporal variability in soil moisture under Scots pine forest (Pinus sylvestris) and heather moorland shrubs (Calluna vulgaris); the two dominant vegetation types in the Scottish Highlands. The study focussed on one year of fortnightly ERT surveys. The surveyed resistivity data was inverted and Archie's law was used to calculate volumetric soil moisture by estimating parameters and comparing against field measured data. Results showed that spatial soil moisture patterns were more heterogeneous in the forest site, as were patterns of wetting and drying, which can be linked to vegetation distribution and canopy structure. The heather site showed a less heterogeneous response to wetting and drying, reflecting the more uniform vegetation cover of the shrubs. Comparing soil moisture temporal variability during growing and non-growing seasons revealed further contrasts: under the heather there was little change in soil moisture during the growing season. Greatest changes in the forest were in areas where the trees were concentrated reflecting water uptake and canopy partitioning. Such differences have implications for climate and land use changes; increased forest cover can lead to greater spatial variability, greater

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

    Science.gov (United States)

    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...

  5. Estimation of soil moisture and its effect on soil thermal ...

    Indian Academy of Sciences (India)

    −1, respectively. The magnitudes of the diurnal soil thermal parameters showed strong association with the levels of the water content. The thermal diffusivity was found to increase with the amount of soil moisture, up to about 22% of the volumetric water content, but fell as the water content further increases. Similar patterns ...

  6. A Technical Design Approach to Soil Moisture Content Measurement

    African Journals Online (AJOL)

    Soil moisture is an important type of data in many fields; ranging from agriculture to environmental monitoring. Three soil samples were collected at definite proportions to represent the three basic soil types (sandy, loamy and clay soils). The moisture contents of these soil samples were analyzed using the thermogravimetric ...

  7. Soil Moisture Experiments 2004 (SMEX04) Polarimetric Scanning Radiometer, AMSR-E and Heterogeneous Landscapes

    National Research Council Canada - National Science Library

    Jackson, T. J; Bindlish, R; Cosh, M; Gasiewski, A; Stankov, B; Klein, M; Weber, B; Zavorotny, V

    2005-01-01

    An unresolved issue in global soil moisture retrieval using passive microwave sensors is the spatial integration of heterogeneous landscape features to the nominal 50 km footprint observed by most satellite systems...

  8. Error characterisation of global active and passive microwave soil moisture data sets

    NARCIS (Netherlands)

    Dorigo, W.; Scipal, K.; Parinussa, R.M.; Liu, Y.Y.; Wagner, W.; de Jeu, R.A.M.; Naeimi, V.

    2010-01-01

    Understanding the error structures of remotely sensed soil moisture observations is essential for correctly interpreting observed variations and trends in the data or assimilating them in hydrological or numerical weather prediction models. Nevertheless, a spatially coherent assessment of the

  9. Soil Moisture Profiles and Temperature Data from SoilSCAPE Sites, USA

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set contains in-situ soil moisture profile and soil temperature data collected at 20-minute intervals at SoilSCAPE (Soil moisture Sensing Controller and...

  10. Observation of soil moisture variability in agricultural and grassland field soils using a wireless sensor network

    Science.gov (United States)

    Priesack, Eckart; Schuh, Max

    2014-05-01

    Soil moisture dynamics is a key factor of energy and matter exchange between land surface and atmosphere. Therefore long-term observation of temporal and spatial soil moisture variability is important in studying impacts of climate change on terrestrial ecosystems and their possible feedbacks to the atmosphere. Within the framework of the network of terrestrial environmental observatories TERENO we installed at the research farm Scheyern in soils of two fields (of ca. 5 ha size each) the SoilNet wireless sensor network (Biogena et al. 2010). The SoilNet in Scheyern consists of 94 sensor units, 45 for the agricultural field site and 49 for the grassland site. Each sensor unit comprises 6 SPADE sensors, two sensors placed at the depths 10, 30 and 50 cm. The SPADE sensor (sceme.de GmbH, Horn-Bad Meinberg Germany) consists of a TDT sensor to estimate volumetric soil water content from soil electrical permittivity by sending an electromagnetic signal and measuring its propagation time, which depends on the soil dielectric properties and hence on soil water content. Additionally the SPADE sensor contains a temperature sensor (DS18B20). First results obtained from the SoilNet measurements at both fields sites will be presented and discussed. The observed high temporal and spatial variability will be analysed and related to agricultural management and basic soil properties (bulk density, soil texture, organic matter content and soil hydraulic characteristics).

  11. Comparison of Multiple Satellite Soil Moisture Products Using In-Situ Soil Moisture Observations Over the Continental United States

    Science.gov (United States)

    Chavez, N.; Galvan, J., III; McRoberts, D. B.; Quiring, S. M.; Ford, T.

    2015-12-01

    We evaluate the skill of multiple satellite-derived soil moisture products using in-situ soil moisture observations from over 50 long-record stations in the continental United States. The satellite products compared include AMSR-E, ASCAT, SMOS, TMI, ESA CCI, and SMAP. Daily volumetric water content and percentiles of volumetric water content from each satellite product is compared with the observations from the corresponding station. We evaluate the similarity between the satellite and in-situ products with regard to the climate and biome conditions of the area as well as the representativeness of the in-situ station for the satellite footprint. We find moderate-to-strong correspondence between all satellite products and in-situ soil moisture observations. Differences between the satellite and observation datasets are attributed to varying land cover conditions, snow cover, and the spatial mismatch of the point observation with the satellite product grid cell. In general, our results suggest that the satellite products evaluated can accurately capture temporal variability of soil moisture near the surface, but do show systematic offsets at several stations across the study region.

  12. De-noising of microwave satellite soil moisture time series

    Science.gov (United States)

    Su, Chun-Hsu; Ryu, Dongryeol; Western, Andrew; Wagner, Wolfgang

    2013-04-01

    The use of satellite soil moisture data for scientific and operational hydrologic, meteorological and climatological applications is advancing rapidly due to increasing capability and temporal coverage of current and future missions. However evaluation studies of various existing remotely-sensed soil moisture products from these space-borne microwave sensors, which include AMSR-E (Advanced Microwave Scanning Radiometer) on Aqua satellite, SMOS (Soil Moisture and Ocean Salinity) mission and ASCAT (Advanced Scatterometer) on MetOp-A satellite, found them to be significantly different from in-situ observations, showing large biases and different dynamic ranges and temporal patterns (e.g., Albergel et al., 2012; Su et al., 2012). Moreover they can have different error profiles in terms of bias, variance and correlations and their performance varies with land surface characteristics (Su et al., 2012). These severely impede the effort to use soil moisture retrievals from multiple sensors concurrently in land surface modelling, cross-validation and multi-satellite blending. The issue of systematic errors present in data sets should be addressed prior to renormalisation of the data for blending and data assimilation. Triple collocation estimation technique has successfully yielded realistic error estimates (Scipal et al., 2008), but this method relies on availability of large number of coincident data from multiple independent satellite data sets. In this work, we propose, i) a conceptual framework for distinguishing systematic periodic errors in the form of false spectral resonances from non-systematic errors (stochastic noise) in remotely-sensed soil moisture data in the frequency domain; and ii) the use of digital filters to reduce the variance- and correlation-related errors in satellite data. In this work, we focus on the VUA-NASA (Vrije Universiteit Amsterdam with NASA) AMSR-E, CATDS (Centre National d'Etudes Spatiales, CNES) SMOS and TUWIEN (Vienna University of

  13. Modeling Transient Root-zone Soil Moisture Dichotomies in Landscapes with Intermixed Land Covers

    Science.gov (United States)

    Patrignani, A.; Ochsner, T. E.

    2015-12-01

    Although large-scale in situ soil moisture monitoring networks are becoming increasingly valuable research tools, deficiencies of many existing networks include the small spatial support of each station, the low spatial density of stations, and the almost exclusive deployment of stations in grassland vegetation. These grassland soil moisture observations may not adequately represent the real soil moisture patterns in landscapes with intermixed land cover types. The objectives of this study were i) to compare root-zone soil moisture dynamics of two dominant vegetation types across Oklahoma, grassland (observed) and winter wheat cropland (simulated); ii) to relate the soil moisture dynamics of grassland and cropland vegetation using an artificial neural network (ANN) as a transfer function; and iii) to use the resulting ANN to estimate the soil moisture spatial patterns for a landscape of intermixed grassland and wheat cropland. Root-zone soil moisture was represented by plant available water (PAW) in the top 0.8 m of the soil profile. PAW under grassland was calculated from 18 years of soil moisture observations at 78 stations of the Oklahoma Mesonet, whereas PAW under winter wheat was simulated for the same 78 locations using a soil water balance model. Then, we trained an ANN to reproduce the simulated PAW under winter wheat using only seven inputs: day of the year, latitude and longitude, measured PAW under grassland, and percent sand, silt, and clay. The resulting ANN was used, along with grassland soil moisture observations, to estimate the detailed soil moisture pattern for a 9x9 km2 Soil Moisture Active Passive (SMAP) grid cell. The seasonal dynamics of root-zone PAW for grassland and winter wheat were strongly asynchronous, so grassland soil moisture observations rarely reflect cropland soil moisture conditions in the region. The simple ANN approach facilitated efficient and accurate prediction of the simulated PAW under winter wheat, RMSE = 24 mm, using

  14. Calibration of neutron moisture meters on stony soils

    International Nuclear Information System (INIS)

    Stocker, R.V.

    1984-01-01

    Laboratory methods (Greacen, 1981), as well as field methods (Watt and Jackson, 1981) for calibrating neutron moisture meters in stone-free soils have been described. None of these methods is practical in soils stony enough to prevent augering or repacking of the soil. This note describes a technique to calibrate neutron moisture meters in soils with stone content up to 60%. The slope of the relationship between neutron count ratio and soil water content of a neutron moisture meter varies by up to 10% for a range of Canterbury stony-soil types. This variation means that calibrations are site specific. The method of calibration is to measure the count ratio on an in situ soil and then to determine the volumetric moisture content of the measured soil.This is repeated over a range of soil moistures to derive a linear regression between soil moisture and count ratio

  15. Inferring Soil Moisture Memory from Streamflow Observations Using a Simple Water Balance Model

    Science.gov (United States)

    Orth, Rene; Koster, Randal Dean; Seneviratne, Sonia I.

    2013-01-01

    Soil moisture is known for its integrative behavior and resulting memory characteristics. Soil moisture anomalies can persist for weeks or even months into the future, making initial soil moisture a potentially important contributor to skill in weather forecasting. A major difficulty when investigating soil moisture and its memory using observations is the sparse availability of long-term measurements and their limited spatial representativeness. In contrast, there is an abundance of long-term streamflow measurements for catchments of various sizes across the world. We investigate in this study whether such streamflow measurements can be used to infer and characterize soil moisture memory in respective catchments. Our approach uses a simple water balance model in which evapotranspiration and runoff ratios are expressed as simple functions of soil moisture; optimized functions for the model are determined using streamflow observations, and the optimized model in turn provides information on soil moisture memory on the catchment scale. The validity of the approach is demonstrated with data from three heavily monitored catchments. The approach is then applied to streamflow data in several small catchments across Switzerland to obtain a spatially distributed description of soil moisture memory and to show how memory varies, for example, with altitude and topography.

  16. SMOS validation of soil moisture and ocen salinity (SMOS) soil moisture over watershed networks in the U.S.

    Science.gov (United States)

    Estimation of soil moisture at large scale has been performed using several satellite-based passive microwave sensors and a variety of retrieval methods. The most recent source of soil moisture is the European Space Agency Soil Moisture and Ocean Salinity (SMOS) mission. A thorough validation must b...

  17. Spatio-temporal variation of surface soil moisture over the Yellow River basin during 1961–2012

    Directory of Open Access Journals (Sweden)

    R. Tong

    2015-05-01

    Full Text Available Soil moisture plays a significant role in agricultural and ecosystem development. However, in the real world soil moisture data are very limited due to many factors. VIC-3L model, as a semi-distribution hydrological model, can potentially provide valuable information regarding soil moisture. In this study, daily soil moisture contents in the surface soil layer (0–10 cm of 1500 grids at 0.25 × 0.25 degree were simulated by the VIC-3L model. The Mann-Kendall trend test and Morlet wavelet analysis methods were used for the analysis of annual and monthly average surface soil moisture series. Results showed that the trend of surface soil moisture was not obvious on the basin scale, but it varied with spatial and temporal conditions. Different fluctuation amplitudes and periods of surface soil moisture were also discovered on the Yellow River basin during 1961 to 2012.

  18. Impacts of soil moisture content on visual soil evaluation

    Science.gov (United States)

    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

  19. NASA Soil Moisture Active Passive (SMAP) Applications

    Science.gov (United States)

    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.

  20. Automated Greenhouse : Temperature and soil moisture control

    OpenAIRE

    Attalla, Daniela; Tannfelt Wu, Jennifer

    2015-01-01

    In this thesis an automated greenhouse was built with the purpose of investigating the watering system’s reliability and if a desired range of temperatures can be maintained. The microcontroller used to create the automated greenhouse was an Arduino UNO. This project utilizes two different sensors, a soil moisture sensor and a temperature sensor. The sensors are controlling the two actuators which are a heating fan and a pump. The heating fan is used to change the temperature and the pump is ...

  1. The SMOS Validation Campaign 2010 in the Upper Danube Catchment: A Data Set for Studies of Soil Moisture, Brightness Temperature, and Their Spatial Variability Over a Heterogeneous Land Surface

    DEFF Research Database (Denmark)

    T. dall' Amico, Johanna; Schlenz, Florian; Loew, Alexander

    2013-01-01

    The Soil Moisture and Ocean Salinity mission has been launched by the European Space Agency (ESA) in November 2009. It is the worldwide first satellite dedicated to retrieve soil moisture information at the global scale, with a high temporal resolution, and from spaceborne L-band radiometry...

  2. Near Surface Soil Moisture Controls Beyond the Darcy Support Scale: A Remote Sensing Perspective

    Science.gov (United States)

    Mohanty, B.; Gaur, N.

    2014-12-01

    Variability observed in near-surface soil moisture is a function of spatial and temporal scale and an understanding of the same is required in numerous environmental and hydrological applications. Past literature has focused largely on the Darcy support scale of measurement for generating knowledge about soil moisture variability and the factors causing it. With the advent of a remote sensing era, it is essential to develop a comprehensive understanding of soil moisture variability and the factors creating it at the remote sensing footprint scale. This understanding will facilitate knowledge transfer between scales which remains an area of active research. In this study, we have presented the hierarchy of controls that physical factors namely, soil, vegetation and topography exert on soil moisture distributions from airborne remote sensor footprint scale (~800 m) to a satellite footprint scale (12800 m) across 3 hydro-climates- humid (Iowa), sub-humid (Oklahoma) and semi-arid (Arizona). We evaluated the effect of physical factors on soil moisture variability at coarse spatial support scales but fine (daily) temporal spacing scales which are typical of remotely sensed soil moisture data. The hierarchy or ranking scheme defined in the study is a function of the areal extent of controls of the different physical factors and the magnitude of their effect in creating spatial variability of soil moisture. We found that even though the areal influence of soil on soil moisture variability remained significant at all scales, it decreased as we went from airborne scale to coarser scales whereas the influence of topography and vegetation increased for all three hydro-climates. The magnitude of the effect of these factors, however, was dependent on antecedent soil moisture conditions and hydro-climate.

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

    Science.gov (United States)

    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. Hydrologic responses to restored wildfire regimes revealed by soil moisture-vegetation relationships

    Science.gov (United States)

    Boisramé, Gabrielle; Thompson, Sally; Stephens, Scott

    2018-02-01

    Many forested mountain watersheds worldwide evolved with frequent fire, which Twentieth Century fire suppression activities eliminated, resulting in unnaturally dense forests with high water demand. Restoration of pre-suppression forest composition and structure through a variety of management activities could improve forest resilience and water yields. This study explores the potential for "managed wildfire", whereby naturally ignited fires are allowed to burn, to alter the water balance. Interest in this type of managed wildfire is increasing, yet its long-term effects on water balance are uncertain. We use soil moisture as a spatially-distributed hydrologic indicator to assess the influence of vegetation, fire history and landscape position on water availability in the Illilouette Creek Basin in Yosemite National Park. Over 6000 manual surface soil moisture measurements were made over a period of three years, and supplemented with continuous soil moisture measurements over the top 1m of soil in three sites. Random forest and linear mixed effects models showed a dominant effect of vegetation type and history of vegetation change on measured soil moisture. Contemporary and historical vegetation maps were used to upscale the soil moisture observations to the basin and infer soil moisture under fire-suppressed conditions. Little change in basin-averaged soil moisture was inferred due to managed wildfire, but the results indicated that large localized increases in soil moisture had occurred, which could have important impacts on local ecology or downstream flows.

  5. A simple model to predict soil moisture: Bridging Event and Continuous Hydrological (BEACH) modelling

    NARCIS (Netherlands)

    Sheikh, V.; Visser, S.M.; Stroosnijder, L.

    2009-01-01

    This paper introduces a simple two-layer soil water balance model developed to Bridge Event And Continuous Hydrological (BEACH) modelling. BEACH is a spatially distributed daily basis hydrological model formulated to predict the initial condition of soil moisture for event-based soil erosion and

  6. Soil carbon inventories and d 13C along a moisture gradient in Botswana

    NARCIS (Netherlands)

    Bird, M.I.; Veenendaal, E.M.; Lloyd, J.

    2004-01-01

    We present a study of soil organic carbon (SOC) inventories and d 13C values for 625 soil cores collected from well-drained, coarse-textured soils in eight areas along a 1000 km moisture gradient from Southern Botswana, north into southern Zambia. The spatial distribution of trees and grass in the

  7. Shrub encroachment alters sensitivity of soil respiration to temperature and moisture 2115

    Science.gov (United States)

    Shrub encroachment into grasslands creates a mosaic of different soil microsites ranging from open spaces to well-developed shrub canopies, and it is unclear how this affects the spatial variability in soil respiration characteristics, such as the sensitivity to soil temperature and moisture. This i...

  8. Effects Of Irrigation Frequency On Soil Moisture Potential And ...

    African Journals Online (AJOL)

    Irrigation frequency affects soil properties with a residual influence on soil moisture potential, crop performance and shoot yield of vegetables. This study investigated the effect of irrigation frequency on the growth, shoot yield of large green, soil moisture potential, and soil chemical properties based on ramdomised complete ...

  9. Variability of soil moisture and its relationship with surface albedo ...

    Indian Academy of Sciences (India)

    system, soil moisture has a long memory (Pielke et al 1999; Wu et al 2002). The climatic anom- alies persist because the memory of soil moisture .... The colour of the soil at the experimental site varies from dark brown to dark reddish brown as we go to the deeper layers. Correspondingly the soil texture varies from grav-.

  10. Mapping high-resolution soil moisture and properties using distributed temperature sensing data and an adaptive particle batch smoother

    Science.gov (United States)

    This study demonstrated a new method for mapping high-resolution (spatial: 1 m, and temporal: 1 h) soil moisture by assimilating distributed temperature sensing (DTS) observed soil temperatures at intermediate scales. In order to provide robust soil moisture and property estimates, we first proposed...

  11. SMALT - Soil Moisture from Altimetry project

    Science.gov (United States)

    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

  12. Analysis of observed soil moisture patterns under different land covers in Western Ghats, India

    Science.gov (United States)

    Venkatesh, B.; Lakshman, Nandagiri; Purandara, B. K.; Reddy, V. B.

    2011-02-01

    SummaryAn understanding of the soil moisture variability is necessary to characterize the linkages between a region's hydrology, ecology and physiography. In the changing land use scenario of Western Ghats, India, where deforestation along with extensive afforestation with exotic species is being undertaken, there is an urgent need to evaluate the impacts of these changes on regional hydrology. The objectives of the present study were: (a) to understand spatio-temporal variability of soil water potential and soil moisture content under different land covers in the humid tropical Western Ghats region and (b) to evaluate differences if any in spatial and temporal patterns of soil moisture content as influenced by nature of land cover. To this end, experimental watersheds located in the Western Ghats of Uttara Kannada District, Karnataka State, India, were established for monitoring of soil moisture. These watersheds possessed homogenous land covers of acacia plantation, natural forest and degraded forest. In addition to the measurements of hydro-meteorological parameters, soil matric potential measurements were made at four locations in each watershed at 50 cm, 100 cm and 150 cm depths at weekly time intervals during the period October 2004-December 2008. Soil moisture contents derived from potential measurements collected were analyzed to characterize the spatial and temporal variations across the three land covers. The results of ANOVA ( p < 0.01, LSD) test indicated that there was no significant change in the mean soil moisture across land covers. However, significant differences in soil moisture with depth were observed under forested watershed, whereas no such changes with depth were noticed under acacia and degraded land covers. Also, relationships between soil moisture at different depths were evaluated using correlation analysis and multiple linear regression models for prediction of soil moisture from climatic variables and antecedent moisture condition were

  13. Tree root systems competing for soil moisture in a 3D soil-plant model

    Science.gov (United States)

    Manoli, Gabriele; Bonetti, Sara; Domec, Jean-Christophe; Putti, Mario; Katul, Gabriel; Marani, Marco

    2014-04-01

    Competition for water among multiple tree rooting systems is investigated using a soil-plant model that accounts for soil moisture dynamics and root water uptake (RWU), whole plant transpiration, and leaf-level photosynthesis. The model is based on a numerical solution to the 3D Richards equation modified to account for a 3D RWU, trunk xylem, and stomatal conductances. The stomatal conductance is determined by combining a conventional biochemical demand formulation for photosynthesis with an optimization hypothesis that selects stomatal aperture so as to maximize carbon gain for a given water loss. Model results compare well with measurements of soil moisture throughout the rooting zone, of total sap flow in the trunk xylem, as well as of leaf water potential collected in a Loblolly pine forest. The model is then used to diagnose plant responses to water stress in the presence of competing rooting systems. Unsurprisingly, the overlap between rooting zones is shown to enhance soil drying. However, the 3D spatial model yielded transpiration-bulk root-zone soil moisture relations that do not deviate appreciably from their proto-typical form commonly assumed in lumped eco-hydrological models. The increased overlap among rooting systems primarily alters the timing at which the point of incipient soil moisture stress is reached by the entire soil-plant system.

  14. Improving Simulated Soil Moisture Fields Through Assimilation of AMSR-E Soil Moisture Retrievals with an Ensemble Kalman Filter and a Mass Conservation Constraint

    Science.gov (United States)

    Li, Bailing; Toll, David; Zhan, Xiwu; Cosgrove, Brian

    2011-01-01

    Model simulated soil moisture fields are often biased due to errors in input parameters and deficiencies in model physics. Satellite derived soil moisture estimates, if retrieved appropriately, represent the spatial mean of soil moisture in a footprint area, and can be used to reduce model bias (at locations near the surface) through data assimilation techniques. While assimilating the retrievals can reduce model bias, it can also destroy the mass balance enforced by the model governing equation because water is removed from or added to the soil by the assimilation algorithm. In addition, studies have shown that assimilation of surface observations can adversely impact soil moisture estimates in the lower soil layers due to imperfect model physics, even though the bias near the surface is decreased. In this study, an ensemble Kalman filter (EnKF) with a mass conservation updating scheme was developed to assimilate the actual value of Advanced Microwave Scanning Radiometer (AMSR-E) soil moisture retrievals to improve the mean of simulated soil moisture fields by the Noah land surface model. Assimilation results using the conventional and the mass conservation updating scheme in the Little Washita watershed of Oklahoma showed that, while both updating schemes reduced the bias in the shallow root zone, the mass conservation scheme provided better estimates in the deeper profile. The mass conservation scheme also yielded physically consistent estimates of fluxes and maintained the water budget. Impacts of model physics on the assimilation results are discussed.

  15. Improving estimated soil moisture fields through assimilation of AMSR-E soil moisture retrievals with an ensemble Kalman filter and a mass conservation constraint

    Directory of Open Access Journals (Sweden)

    B. Li

    2012-01-01

    Full Text Available Model simulated soil moisture fields are often biased due to errors in input parameters and deficiencies in model physics. Satellite derived soil moisture estimates, if retrieved appropriately, represent the spatial mean of near surface soil moisture in a footprint area, and can be used to reduce bias of model estimates (at locations near the surface through data assimilation techniques. While assimilating the retrievals can reduce bias, it can also destroy the mass balance enforced by the model governing equation because water is removed from or added to the soil by the assimilation algorithm. In addition, studies have shown that assimilation of surface observations can adversely impact soil moisture estimates in the lower soil layers due to imperfect model physics, even though the bias near the surface is decreased. In this study, an ensemble Kalman filter (EnKF with a mass conservation updating scheme was developed to assimilate Advanced Microwave Scanning Radiometer (AMSR-E soil moisture retrievals, as they are without any scaling or pre-processing, to improve the estimated soil moisture fields by the Noah land surface model. Assimilation results using the conventional and the mass conservation updating scheme in the Little Washita watershed of Oklahoma showed that, while both updating schemes reduced the bias in the shallow root zone, the mass conservation scheme provided better estimates in the deeper profile. The mass conservation scheme also yielded physically consistent estimates of fluxes and maintained the water budget. Impacts of model physics on the assimilation results are discussed.

  16. The neutronic method for measuring soil moisture

    International Nuclear Information System (INIS)

    Couchat, Ph.

    1967-01-01

    The three group diffusion theory being chosen as the most adequate method for determining the response of the neutron soil moisture probe, a mathematical model is worked out using a numerical calculation programme with Fortran IV coding. This model is fitted to the experimental conditions by determining the effect of different parameters of measuring device: channel, fast neutron source, detector, as also the soil behaviour under neutron irradiation: absorbers, chemical binding of elements. The adequacy of the model is tested by fitting a line through the image points corresponding to the couples of experimental and theoretical values, for seven media having different chemical composition: sand, alumina, line stone, dolomite, kaolin, sandy loam, calcareous clay. The model chosen gives a good expression of the dry density influence and allows α, β, γ and δ constants to be calculated for a definite soil according to the following relation which gives the count rate of the soil moisture probe: N = (α ρ s +β) H v +γ ρ s + δ. (author) [fr

  17. Soil moisture memory at sub-monthly time scales

    Science.gov (United States)

    Mccoll, K. A.; Entekhabi, D.

    2017-12-01

    For soil moisture-climate feedbacks to occur, the soil moisture storage must have `memory' of past atmospheric anomalies. Quantifying soil moisture memory is, therefore, essential for mapping and characterizing land-atmosphere interactions globally. Most previous studies estimate soil moisture memory using metrics based on the autocorrelation function of the soil moisture time series (e.g., the e-folding autocorrelation time scale). This approach was first justified by Delworth and Manabe (1988) on the assumption that monthly soil moisture time series can be modelled as red noise. While this is a reasonable model for monthly soil moisture averages, at sub-monthly scales, the model is insufficient due to the highly non-Gaussian behavior of the precipitation forcing. Recent studies have shown that significant soil moisture-climate feedbacks appear to occur at sub-monthly time scales. Therefore, alternative metrics are required for defining and estimating soil moisture memory at these shorter time scales. In this study, we introduce metrics, based on the positive and negative increments of the soil moisture time series, that can be used to estimate soil moisture memory at sub-monthly time scales. The positive increments metric corresponds to a rapid drainage time scale. The negative increments metric represents a slower drying time scale that is most relevant to the study of land-atmosphere interactions. We show that autocorrelation-based metrics mix the two time scales, confounding physical interpretation. The new metrics are used to estimate soil moisture memory at sub-monthly scales from in-situ and satellite observations of soil moisture. Reference: Delworth, Thomas L., and Syukuro Manabe. "The Influence of Potential Evaporation on the Variabilities of Simulated Soil Wetness and Climate." Journal of Climate 1, no. 5 (May 1, 1988): 523-47. doi:10.1175/1520-0442(1988)0012.0.CO;2.

  18. MONITORING SOIL MOISTURE IN A COAL MINING AREA WITH MULTI-PHASE LANDSAT IMAGES

    Directory of Open Access Journals (Sweden)

    J. L. Kong

    2016-06-01

    Full Text Available The coal development zone of Northern Shaanxi, China is one of the eight largest coal mines in the world, also the national energy and chemical bases. However, the coal mining leads to ground surface deformation and previous studies show that in collapse fissure zone soil water losses almost 50% compared with non-fissure zone. The main objective of this study is to develop a retrieval model that is reliable and sensitive to soil moisture in the whole coal mining zone of Northern Shaanxi based upon the soil sample parameters collected from in situ site investigation, spectral data gathered simultaneously and the images of Landsat7 ETM. The model uses different phases of Landsat data to retrieve soil moisture and analyze the patterns of spatial and temporal variations of soil moisture caused by ground deformation in the coal mining areas. The study indicated that band4 of Landsat7 ETM is the most sensitive band for soil moisture retrieval using the spectrum method. The quadratic model developed by remote sensing reflectance (Rrs4 (corresponding to the band4 is the best pattern with the correlation coefficient of 0.858 between the observed and the estimated soil moisture. Two-phase Landsat7 ETM data of 2002 and 2009 and one phase Landsat8 OLI data of 2015 for the study area were selected to retrieve soil moisture information. The result showed that the mean relative error was 35.16% and the root-mean-squared error (RMSE was 0.58%. The changes of the spatial distribution of inversed soil moisture revealed that the trend of soil moisture contents of the study area was in general being gradually reduced from 2002 to 2015. The study results can serve as the baseline for monitoring environmental impacts on soil moisture in the regions due to coal mining.

  19. Spatiotemporal Distribution of Soil Moisture and Salinity in the Taklimakan Desert Highway Shelterbelt

    Directory of Open Access Journals (Sweden)

    Yuan Huang

    2015-08-01

    Full Text Available Salinization and secondary salinization often appear after irrigation with saline water. The Taklimakan Desert Highway Shelterbelt has been irrigated with saline ground water for more than ten years; however, soil salinity in the shelterbelt has not been evaluated. The objective of this study was to analyze the spatial and temporal distribution of soil moisture and salinity in the shelterbelt system. Using a non-uniform grid method, soil samples were collected every two days during one ten-day irrigation cycle in July 2014 and one day in spring, summer, and autumn. The results indicated that soil moisture declined linearly with time during the irrigation cycle. Soil moisture was greatest in the southern and eastern sections of the study area. In contrast to soil moisture, soil electrical conductivity increased from 2 to 6 days after irrigation, and then gradually decreased from 6 to 8 days after irrigation. Soil moisture was the greatest in spring and the least in summer. In contrast, soil salinity increased from spring to autumn. Long time drip-irrigation with saline groundwater increased soil salinity slightly. The soil salt content was closely associated with soil texture. The current soil salt content did not affect plant growth, however, the soil in the shelterbelt should be continuously monitored to prevent salinization in the future.

  20. Remote Sensing of Surface Soil Moisture using Semi-Concurrent Radar and Radiometer Observations

    Science.gov (United States)

    Li, L.; Ouellette, J. D.; Colliander, A.; Cosh, M. H.; Caldwell, T. G.; Walker, J. P.

    2017-12-01

    Radar backscatter and radiometer brightness temperature both have well-documented sensitivity to surface soil moisture, particularly in the microwave regime. While radiometer-derived soil moisture retrievals have been shown to be stable and accurate, they are only available at coarse spatial resolutions on the order of tens of kilometers. Backscatter from Synthetic Aperture Radar (SAR) is similarly sensitive to soil moisture but can yield higher spatial resolutions, with pixel sizes about an order of magnitude smaller. Soil moisture retrieval from radar backscatter is more difficult, however, due to the combined sensitivity of radar scattering to surface roughness, vegetation structure, and soil moisture. The algorithm uses a time-series of SAR data to retrieval soil moisture information, constraining the SAR-derived soil moisture estimates with radiometer observations. This effectively combines the high spatial resolution offered by SAR with the precision offered by passive radiometry. The algorithm is a change detection approach which maps changes in the radar backscatter to changes in surface soil moisture. This new algorithm differs from existing retrieval techniques in that it does not require ancillary vegetation information, but assumes vegetation and surface roughness are stable between pairs of consecutive radar overpasses. Furthermore, this method does not require a radar scattering model for the vegetation canopy, nor the use of a training data set. The algorithm works over a long time series, and is constrained by hard bounds which are defined using a coarse-resolution radiometer soil moisture product. The presentation will include soil moisture retrievals from Soil Moisture Active/Passive (SMAP) SAR data. Two sets of optimization bounds will constrain the radar change detection algorithm: one defined by SMAP radiometer retrievals and one defined by WindSat radiometer retrievals. Retrieved soil moisture values will be presented on a world map and will

  1. Influence of moisture content on radon diffusion in soil

    International Nuclear Information System (INIS)

    Singh, M.; Ramola, R.C.; Singh, S.; Virk, H.S.

    1990-01-01

    Radon diffusion from soil has been studied as a function of the moisture content of the soil. A few simple experiments showed that up to a certain moisture content the radon diffusion increased with increasing moisture. A sharp rise in radon concentration occurred as the moisture was increased from the completely dry state to 13% water by weight. The radon flux was measured for columns of dry, moist and water saturated soil. The highest flux came from the column filled with moist soil. Water saturated soil gave the lowest flux because of the much lower diffusion coefficient of radon through water. (author)

  2. Capability of meteorological drought indices for detecting soil moisture droughts

    Directory of Open Access Journals (Sweden)

    Devanmini Halwatura

    2017-08-01

    New hydrological insights for the region: For three typical soil types and climate zones in Eastern Australia, and for two soil profiles, we have found a significant correlation between the indices and soil moisture droughts detected by Hydrus-1D. The failure rates and false alarm rates for detecting the simulated soil moisture droughts were generally below 50% for both indices and both soil profiles (the Reconnaissance Drought Index at Melbourne was the only exception. However, the complexity of Hydrus-1D and the uncertainty associated with the available, regionalised soil water retention curves encourage using the indices over Hydrus-1D in absence of appropriate soil moisture monitoring data.

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

    Science.gov (United States)

    Berg, A. M.; Lintner, B. R.; Findell, K. L.; Giannini, A.

    2017-12-01

    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. In other words, we show, over a subset of climate models, how land-atmosphere interactions may be a cause of uncertainty in model projections of precipitation. 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.

  4. Spatial variability of total porosity, moisture and soil resistance to penetration of a yellow ultisol Variabilidade espacial da porosidade total, umidade e resistência do solo à penetração de um Argissolo amarelo

    Directory of Open Access Journals (Sweden)

    Renildo Luiz Mion

    2012-12-01

    Full Text Available The study of spatial variability of soil attributes is important in areas under different uses and management. The moisture and soil resistance to penetration are considered an indicative parameter of soil physical quality. The objective of this work to study the spatial variability of total porosity, soil resistance to penetration and moisture in an area of rotational grazing sheep. The experiment was conducted in a Yellow Ultisol with a sandy texture in the layers of 0- 0.1, 0.1-0.2 and 0.2-0.3 m. For the determination of properties and soil resistance to penetration was defined a grid, with regular intervals of 30 m, total of 13 points. The total porosity (TP and the gravimetric soil moisture (SU were obtained by collecting undisturbed samples (Uhland soil sampler and disturbed samples, respectively. The soil resistance to penetration (PR was determined at each point using an electronic georeferenced penetrometer. The results showed that TP had a low variation coefficient in all studied layers. The SU in all evaluated layers and the PR in layers 0-0.1 and 0.1-0.2 m showed a medium variation coefficient. The PR in layer 0.2-0.3 m showed a high variation coefficient showing the average distribution with a high heterogeneity in the data. The attributes TP, PR and SU showed a weak spatial dependency index (SDI in all evaluated layers. The PR increases as the TP and the SU has a smaller influence on the soil. O estudo da variabilidade espacial de atributos do solo é importante em áreas sob diferentes usos e manejos. A umidade e a resistência do solo à penetração são consideradas um parâmetro indicativo da qualidade física do solo. Objetivou-se com este trabalho estudar a variabilidade espacial da porosidade total, resistência do solo à penetração e da umidade em uma área de pastejo rotacionado de ovinos. O experimento foi conduzido em um Argissolo Amarelo de textura arenosa nas camadas de 0-0,1, 0,1-0,2 e 0,2-0,3m. Para a determina

  5. Wireless soil moisture sensor networks for environmental monitoring and irrigation

    Science.gov (United States)

    Hübner, Christof; Cardell-Oliver, Rachel; Becker, Rolf; Spohrer, Klaus; Jotter, Kai; Wagenknecht, Tino

    2010-05-01

    Dependable spatial-temporal soil parameter data is required for informed decision making in precision farming and hydrological applications. Wireless sensor networks are seen as a key technology to satisfy these demands. Hence, research and development focus is on reliable outdoor applications. This comprises sensor design improvement, more robust communication protocols, less power consumption as well as better deployment strategies and tools. Field trials were performed to investigate and iteratively improve wireless sensor networks in the above-mentioned areas. They accounted for different climate conditions, soil types and salinity, irrigation practices, solar power availability and also for different radio spectrum use which affects the reliability of the wireless links. E.g. 868 MHz and 2.4 GHz wireless nodes were compared in the field with regard to range. Furthermore a low-cost soil moisture sensor was developed to allow for large-scale field experiments. It is based on the measurement of the high frequency dielectric properties of the soil. Two agricultural sites were equipped with 80 sensors and 20 wireless nodes each. The soil moisture data is collected in regular intervals, aggregated in a base station and visualized through a web-based geographical information system. The complete system and results of field experiments are presented.

  6. DEVELOPMENT OF NEW HYPERSPECTRAL ANGLE INDEX FOR ESTIMATION OF SOIL MOISTURE USING IN SITU SPECTRAL MEASURMENTS

    Directory of Open Access Journals (Sweden)

    M. R. Mobasheri

    2013-10-01

    Full Text Available Near-surface soil moisture is one of the crucial variables in hydrological processes, which influences the exchange of water and energy fluxes at the land surface/atmosphere interface. Accurate estimate of the spatial and temporal variations of soil moisture is critical for numerous environmental studies. On the other hand, information of distributed soil moisture at large scale with reasonable spatial and temporal resolution is required for improving climatic and hydrologic modeling and prediction. The advent of hyperspectral imagery has allowed examination of continuous spectra not possible with isolated bands in multispectral imagery. In addition to high spectral resolution for individual band analyses, the contiguous narrow bands show characteristics of related absorption features, such as effects of strong absorptions on the band depths of adjacent absorptions. Our objective in this study was to develop a new spectral angle index to estimate soil moisture based on spectral region (350 and 2500 nm. In this paper, using spectral observations made by ASD Spectroradiometer for predicting soil moisture content, two soil indices were also investigated involving the Perpendicular Drought Index (PDI, NMDI (Normalized Multi-band Drought Index indices. Correlation and regression analysis showed a high relationship between PDI and the soil moisture percent (R2 = 0.9537 and NMDI (R2 = 0.9335. Furthermore, we also simulated these data according to the spectral range of some sensors such as MODIS, ASTER, ALI and ETM+. Indices relevant these sensors have high correlation with soil moisture data. Finally, we proposed a new angle index which shows significant relationship between new angle index and the soil moisture percentages (R2 = 0.9432.angle index relevant bands 3, 4, 5, 6, 7 MODIS also showing high accuracy in estimation of soil moisture (R2 = 0.719.

  7. Implementing a physical soil water flow model with minimal soil characteristics and added value offered by surface soil moisture measurements assimilation.

    Science.gov (United States)

    Chanzy, André

    2010-05-01

    Soil moisture is a key variable for many soil physical and biogeochemical processes. Its dynamic results from water fluxes in soil and at its boundaries, as well as soil water storage properties. If the water flows are dominated by diffusive processes, modelling approaches based on the Richard's equation or the Philip and de Vries coupled heat and water flow equations lead to a satisfactory representation of the soil moisture dynamic. However, It requires the characterization of soil hydraulic functions, the initialisation and the boundary conditions, which are expensive to obtain. The major problem to assess soil moisture for decision making or for representing its spatiotemporal evolution over complex landscape is therefore the lack of information to run the models. The aim of the presentation is to analyse how a soil moisture model can be implemented when only climatic data and basic soil information are available (soil texture, organic matter) and what would be the added of making a few soil moisture measurements. We considered the field scale, which is the key scale for decision making application (the field being the management unit for farming system) and landscape modelling (field size being comparable to the computation unit of distributed hydrological models). The presentation is limited to the bare soil case in order to limit the complexity of the system and the TEC model based on Philip and De Vries equations is used in this study. The following points are addressed: o the within field spatial variability. This spatial variability can be induced by the soil hydraulic properties and/or by the amount of infiltrated water induced by water rooting towards infiltration areas. We analyse how an effective parameterization of soil properties and boundary conditions can be used to simulate the field average moisture. o The model implementation with limited information. We propose strategies that can be implemented when information are limited to soil texture and

  8. A study of soil moisture variability for landmine detection by the neutron technique

    Directory of Open Access Journals (Sweden)

    Avdić Senada

    2007-01-01

    Full Text Available This paper is focused on the space and temporal variability of soil moisture experimental data acquired at a few locations near landmine fields in the Tuzla Canton, as well as on the quantification of the statistical nature of soil moisture data on a small spatial scale. Measurements of soil water content at the surface were performed by an electro-magnetic sensor over 1 25, and 100 m2 grids, at intervals of 0.2, 0.5, and 1 m, respectively. The sampling of soil moisture at different spatial resolutions and over different grid sizes has been investigated in order to achieve the quantification of the statistical nature of soil moisture distribution. The statistical characterization of spatial variability was performed through variogram and correlogram analysis of measurement results. The temporal variability of the said samples was examined over a two-season period. For both sampling periods, the spatial correlation length is about 1 to 2 m, respectively, or less. Thus, sampling should be done on a larger spatial scale, in order to capture the variability of the investigated areas. Since the characteristics of many landmine sensors depend on soil moisture, the results of this study could form a useful data base for multisensor landmine detection systems with a promising performance.

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

    Science.gov (United States)

    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.

  10. A sensor array system for monitoring moisture dynamics inunsaturated soil

    Energy Technology Data Exchange (ETDEWEB)

    Salve, R.; Cook, P.J.

    2007-05-15

    To facilitate investigations of moisture dynamics inunsaturated soil, we have developed a technique to qualitatively monitorpatterns of saturation changes. Field results suggest that this device,the sensor array system (SAS), is suitable for determining changes inrelative wetness along vertical soil profiles. The performance of theseprobes was compared with that of the time domain reflectometry (TDR)technique under controlled and field conditions. Measurements from bothtechniques suggest that by obtaining data at high spatial and temporalresolution, the SAS technique was effective in determining patterns ofsaturation changes along a soil profile. In addition, hardware used inthe SAS technique was significantly cheaper than the TDR system, and thesensor arrays were much easier to install along a soilprofile.

  11. Continuous data assimilation for downscaling large-footprint soil moisture retrievals

    KAUST Repository

    Altaf, M. U.

    2016-09-01

    Soil moisture is a crucial component of the hydrologic cycle, significantly influencing runoff, infiltration, recharge, evaporation and transpiration processes. Models characterizing these processes require soil moisture as an input, either directly or indirectly. Better characterization of the spatial variability of soil moisture leads to better predictions from hydrologic/climate models. In-situ measurements have fine resolution, but become impractical in terms of coverage over large extents. Remotely sensed data have excellent spatial coverage extents, but suffer from poorer spatial and temporal resolution. We present here an innovative approach to downscaling coarse resolution soil moisture data by combining data assimilation and physically based modeling. In this approach, we exploit the features of Continuous Data Assimilation (CDA). A nudging term, estimated as the misfit between interpolants of the assimilated coarse grid measurements and the fine grid model solution, is added to the model equations to constrain the model’s large scale variability by available measurements. Soil moisture fields generated at a fine resolution by a physically-based vadose zone model (e.g., HYDRUS) are subjected to data assimilation conditioned upon the coarse resolution observations. This enables nudging of the model outputs towards values that honor the coarse resolution dynamics while still being generated at the fine scale. The large scale features of the model output are constrained to the observations, and as a consequence, the misfit at the fine scale is reduced. The advantage of this approach is that fine resolution soil moisture maps can be generated across large spatial extents, given the coarse resolution data. The data assimilation approach also enables multi-scale data generation which is helpful to match the soil moisture input data to the corresponding modeling scale. Application of this approach is likely in generating fine and intermediate resolution soil

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

    Science.gov (United States)

    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

  13. Using lagged dependence to identify (de)coupled surface and subsurface soil moisture values

    Science.gov (United States)

    Carranza, Coleen D. U.; van der Ploeg, Martine J.; Torfs, Paul J. J. F.

    2018-04-01

    Recent advances in radar remote sensing popularized the mapping of surface soil moisture at different spatial scales. Surface soil moisture measurements are used in combination with hydrological models to determine subsurface soil moisture values. However, variability of soil moisture across the soil column is important for estimating depth-integrated values, as decoupling between surface and subsurface can occur. In this study, we employ new methods to investigate the occurrence of (de)coupling between surface and subsurface soil moisture. Using time series datasets, lagged dependence was incorporated in assessing (de)coupling with the idea that surface soil moisture conditions will be reflected at the subsurface after a certain delay. The main approach involves the application of a distributed-lag nonlinear model (DLNM) to simultaneously represent both the functional relation and the lag structure in the time series. The results of an exploratory analysis using residuals from a fitted loess function serve as a posteriori information to determine (de)coupled values. Both methods allow for a range of (de)coupled soil moisture values to be quantified. Results provide new insights into the decoupled range as its occurrence among the sites investigated is not limited to dry conditions.

  14. Propagation of soil moisture memory to runoff and evapotranspiration

    Science.gov (United States)

    Orth, R.; Seneviratne, S. I.

    2012-10-01

    As a key variable of the land-climate system soil moisture is a main driver of runoff and evapotranspiration under certain conditions. Soil moisture furthermore exhibits outstanding memory (persistence) characteristics. Also for runoff many studies report distinct low frequency variations that represent a memory. Using data from over 100 near-natural catchments located across Europe we investigate in this study the connection between soil moisture memory and the respective memory of runoff and evapotranspiration on different time scales. For this purpose we use a simple water balance model in which dependencies of runoff (normalized by precipitation) and evapotranspiration (normalized by radiation) on soil moisture are fitted using runoff observations. The model therefore allows to compute memory of soil moisture, runoff and evapotranspiration on catchment scale. We find considerable memory in soil moisture and runoff in many parts of the continent, and evapotranspiration also displays some memory on a monthly time scale in some catchments. We show that the memory of runoff and evapotranspiration jointly depend on soil moisture memory and on the strength of the coupling of runoff and evapotranspiration to soil moisture. Furthermore we find that the coupling strengths of runoff and evapotranspiration to soil moisture depend on the shape of the fitted dependencies and on the variance of the meteorological forcing. To better interpret the magnitude of the respective memories across Europe we finally provide a new perspective on hydrological memory by relating it to the mean duration required to recover from anomalies exceeding a certain threshold.

  15. Calibration of Soil Moisture Measurement Using Pr2 Moisture Meter and Gravimetric-Based Approaches

    Directory of Open Access Journals (Sweden)

    Olotu Yahaya

    2016-10-01

    Full Text Available The research study strongly focused on creating strong mechanism for measuring and evaluating soil moisture content comparing PR2 capacitance moisture meter and gravimetric approach. PR2 moisture meter shows a better performance accuracy of ± 6%; 0.06 m 3 /m 3 and intercept a0 =1.8; indicating the field is heavy clay. It measures to 1000 mm depth with high precision; while realistic result could not be obtained from gravimetric method at this measuring depth. Therefore, effective soil moisture measuring, monitoring and evaluation can be achieved with PR2 moisture meter.

  16. Evaluating the Capabilities of Soil Enthalpy, Soil Moisture and Soil Temperature in Predicting Seasonal Precipitation

    Science.gov (United States)

    Zhao, Changyu; Chen, Haishan; Sun, Shanlei

    2018-04-01

    Soil enthalpy ( H) contains the combined effects of both soil moisture ( w) and soil 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 soil ice effects. For example, w negatively contributes to H if soil contains more ice; however, after soil ice melts, w exerts positive contributions. In particular, due to lower w interannual variabilities in the deep soil 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).

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

    Science.gov (United States)

    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.

  18. Estimation of Soil Moisture in an Alpine Catchment with RADARSAT2 Images

    Directory of Open Access Journals (Sweden)

    L. Pasolli

    2011-01-01

    Full Text Available Soil moisture retrieval is one of the most challenging problems in the context of biophysical parameter estimation from remotely sensed data. Typically, microwave signals are used thanks to their sensitivity to variations in the water content of soil. However, especially in the Alps, the presence of vegetation and the heterogeneity of topography may significantly affect the microwave signal, thus increasing the complexity of the retrieval. In this paper, the effectiveness of RADARSAT2 SAR images for the estimation of soil moisture in an alpine catchment is investigated. We first carry out a sensitivity analysis of the SAR signal to the moisture content of soil and other target properties (e.g., topography and vegetation. Then we propose a technique for estimating soil moisture based on the Support Vector Regression algorithm and the integration of ancillary data. Preliminary results are discussed both in terms of accuracy over point measurements and effectiveness in handling spatially distributed data.

  19. The Use of Sentinel-1 for Monitoring of Soil Moisture within the Copernicus Global Land Service

    Science.gov (United States)

    Doubkova, M.; Wagner, W.; Naeimi, V.; Cao, S.; Bauer-Marschallinger, B.; Kidd, R.; Hasenauer, Stefan; Dostalova, A.; Paulik, Christopher

    2016-08-01

    Within the Copernicus Global Land Service (CGLS), a global Soil Water Index (SWI) product is available on an operational basis, derived from the Metop Advanced Scatterometer (ASCAT) with a spatial sampling of 0.1°. The SWI quantifies the moisture condition at various depths in the soil. To match the spatial resolution of the SWI data with the rest of the CGLS data products, the 1 km Sentinel-1 (S-1) surface soil moisture (SSM) product can be used. The S-1 SSM is retrieved by inverting a backscatter model trained using historic SAR observations. Here, the progress made in delivering the 1 km fused SWI as well as the 1 km S-1 SSM products at the Earth Observation Data Centre for Water Resources Monitoring (https://www.eodc.eu/) is reported. The first validation results of the 1 km fused SWI are satisfying demonstrating well the added fine- scale spatial soil moisture signal.

  20. Soil moisture calibration of TDR multilevel probes

    Directory of Open Access Journals (Sweden)

    Serrarens Daniel

    2000-01-01

    Full Text Available Time domain reflectometry (TDR probes are increasingly used for field estimation of soil water content. The objective of this study was to evaluate the accuracy of the multilevel TDR probe under field conditions. For this purpose, eight such TDR probes were installed in small plots that were seeded with beans and sorghum. Data collection from the probes was such that soil moisture readings were automated and logged using a standalone field unit. Neutron probe measurements were used to calibrate the TDR probes. Soil-probe contact and soil compaction were critical to the accuracy of the TDR, especially when a number of TDR probes are combined for a single calibration curve. If each probe is calibrated individually, approximate measurement errors were between 0.005 and 0.015 m³ m-3. However, measurement errors doubled to approximately 0.025 to 0.03 m³ m-3, when TDR probes were combined to yield a single calibration curve.

  1. Predicting root zone soil moisture with satellite near-surface moisture data in semiarid environments

    Science.gov (United States)

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

    2015-12-01

    One of the most critical variables in semiarid environment is the soil water content that represents a controlling factor for both ecological and hydrological processes. Soil moisture monitoring over large scales may be extremely useful, but it is limited by the fact that most of the available tools provides only surface measurements not representative of the effective amount of water stored in the subsurface. Therefore, a methodology able to infer root-zone soil moisture starting from surface measurements is highly desirable. Recently a new simplified formulation has been introduced to provide a formal description of the mathematical relationship between surface measurements and root-zone soil moisture (Manfreda et al., HESS 2014). This is a physically based approach derived from the soil water balance equation, where different soil water loss functions have been explored in order to take into account for the non-linear processes governing soil water fluxes. The study highlighted that the soil loss function is the key for such relationship that is therefore strongly influenced by soil type and physiological plant types. The new formulation has been tested on soil moisture based on measurements taken from the African Monsoon Multidisciplinary Analysis (AMMA) and the Soil Climate Analysis Network (SCAN) databases. The method sheds lights on the physical controls for soil moisture dynamics and on the possibility to use such a simplified method for the description of root-zone soil moisture. Furthermore, the method has been also couple with an Enasamble Kalman Filter (EnKF) in order to optimize its performances for the large scale monitoring based the new satellite near-surface moisture data (SMAP). The optimized SMAR-EnKF model does well in both wet and dry climates and across many different soil types (51 SCAN locations) providing a strategy for real-time soil moisture monitoring.

  2. Regional scale spatio-temporal variability of soil moisture and its relationship with meteorological factors over the Korean peninsula

    Science.gov (United States)

    Cho, Eunsang; Choi, Minha

    2014-08-01

    An understanding soil moisture spatio-temporal variability is essential for hydrological and meteorological research. This work aims at evaluating the spatio-temporal variability of near surface soil moisture and assessing dominant meteorological factors that influence spatial variability over the Korean peninsula from May 1 to September 29, 2011. The results of Kolmogorov-Smirnov tests for goodness of fit showed that all applied distributions (normal, log-normal and generalized extreme value: GEV) were appropriate for the datasets and the GEV distribution described best spatial soil moisture patterns. The relationship between the standard deviation and coefficient of variation (CV) of soil moisture with mean soil moisture contents showed an upper convex shape and an exponentially negative pattern, respectively. Skewness exhibited a decreasing pattern with increasing mean soil moisture contents and kurtosis exhibited the U-shaped relationship. In this regional scale (99,720 km2), we found that precipitation indicated temporally stable features through an ANOVA test considering the meteorological (i.e. precipitation, insolation, air temperature, ground temperature and wind speed) and physical (i.e. soil texture, elevation, topography, and land use) factors. Spatial variability of soil moisture affected by the meteorological forcing is shown as result of the relationship between the meteorological factors (precipitation, insolation, air temperature and ground temperature) and the standard deviation of relative difference of soil moisture contents (SDRDt) which implied the spatial variability of soil moisture. The SDRDt showed a positive relationship with the daily mean precipitation, while a negative relationship with insolation, air temperature and ground temperature. The variation of spatial soil moisture pattern is more sensitive to change in ground temperature rather than air temperature changes. Therefore, spatial variability of soil moisture is greatly affected

  3. Modelling soil moisture under different land covers in a sub-humid ...

    Indian Academy of Sciences (India)

    cipitation/irrigation and yields output of evapo- transpiration and drainage. Spatial (vertical and lateral) variations in properties and processes are ignored and soil moisture content for the layer as a whole is modelled. Accordingly, application of water balance equation to the soil layer under these assumptions for time period ...

  4. Assimilation of microwave brightness temperatures for soil moisture estimation using particle filter

    International Nuclear Information System (INIS)

    Bi, H Y; Ma, J W; Qin, S X; Zeng, J Y

    2014-01-01

    Soil moisture plays a significant role in global water cycles. Both model simulations and remote sensing observations have their limitations when estimating soil moisture on a large spatial scale. Data assimilation (DA) is a promising tool which can combine model dynamics and remote sensing observations to obtain more precise ground soil moisture distribution. Among various DA methods, the particle filter (PF) can be applied to non-linear and non-Gaussian systems, thus holding great potential for DA. In this study, a data assimilation scheme based on the residual resampling particle filter (RR-PF) was developed to assimilate microwave brightness temperatures into the macro-scale semi-distributed Variance Infiltration Capacity (VIC) Model to estimate surface soil moisture. A radiative transfer model (RTM) was used to link brightness temperatures with surface soil moisture. Finally, the data assimilation scheme was validated by experimental data obtained at Arizona during the Soil Moisture Experiment 2004 (SMEX04). The results show that the estimation accuracy of soil moisture can be improved significantly by RR-PF through assimilating microwave brightness temperatures into VIC model. Both the overall trends and specific values of the assimilation results are more consistent with ground observations compared with model simulation results

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

    Science.gov (United States)

    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.

  6. Downscaling near-surface soil moisture from field to plot scale: A comparative analysis under different environmental conditions

    Science.gov (United States)

    Nasta, Paolo; Penna, Daniele; Brocca, Luca; Zuecco, Giulia; Romano, Nunzio

    2018-02-01

    Indirect measurements of field-scale (hectometer grid-size) spatial-average near-surface soil moisture are becoming increasingly available by exploiting new-generation ground-based and satellite sensors. Nonetheless, modeling applications for water resources management require knowledge of plot-scale (1-5 m grid-size) soil moisture by using measurements through spatially-distributed sensor network systems. Since efforts to fulfill such requirements are not always possible due to time and budget constraints, alternative approaches are desirable. In this study, we explore the feasibility of determining spatial-average soil moisture and soil moisture patterns given the knowledge of long-term records of climate forcing data and topographic attributes. A downscaling approach is proposed that couples two different models: the Eco-Hydrological Bucket and Equilibrium Moisture from Topography. This approach helps identify the relative importance of two compound topographic indexes in explaining the spatial variation of soil moisture patterns, indicating valley- and hillslope-dependence controlled by lateral flow and radiative processes, respectively. The integrated model also detects temporal instability if the dominant type of topographic dependence changes with spatial-average soil moisture. Model application was carried out at three sites in different parts of Italy, each characterized by different environmental conditions. Prior calibration was performed by using sparse and sporadic soil moisture values measured by portable time domain reflectometry devices. Cross-site comparisons offer different interpretations in the explained spatial variation of soil moisture patterns, with time-invariant valley-dependence (site in northern Italy) and hillslope-dependence (site in southern Italy). The sources of soil moisture spatial variation at the site in central Italy are time-variant within the year and the seasonal change of topographic dependence can be conveniently

  7. SCAT/ASCAT Soil Moisture Data: Enhancements in the TU Wien Method for Soil Moisture Retrieval From ERS and METOP Scatterometer Observations

    Science.gov (United States)

    Naeimi, V.; Wagner, W.; Bartalis, Z.

    2009-05-01

    Active microwave remote sensing observations of the scatterometers onboard the European Remote Sensing (ERS) and METeorological OPerational (METOP) satellites have been proven to be valuable for monitoring surface soil moisture globally using the so-called TU Wien change detection method. The METOP satellite series carrying ASCAT (Advanced Scatteromer) instrument for the next 15 years will ensure the continuity of soil moisture retrieval from scatterometers' data for more than 30 years considering the available ERS-1&2 Scatterometer (SCAT) observations dataset. With the aim of implementing a near real-time system for operational soil moisture remote sensing at EUMETSAT, the Institute of Photogrammetry and Remote Sensing at Vienna University of Technology (TU Wien) has developed an improved soil moisture retrieval algorithm to cope with some of the limitations found in the earlier method. The new algorithm has been implemented on a discrete global grid with 12.5 km quasi-equal grid spacing and includes a correction method to reduce azimuthal anisotropy of backscatter signal, new techniques for calculation of the model parameters and incorporates a comprehensive error modeling. The error analysis provides not only the quality information about the product but also facilitates accurate determination of historically driest/wettest conditions during the retrieval process. Enhancements made in the TU Wien retrieval algorithm result in a more uniform performance of the model and, consequently, a spatially consistent soil moisture product with a better spatial resolution.

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

    Science.gov (United States)

    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.

  9. Variability of soil moisture and its relationship with surface albedo

    Indian Academy of Sciences (India)

    Continuous observation data collected over the year 2008 at Astronomical Observatory, Thiruvananthapuram in south Kerala (76° 59′E longitude and 8° 30′N latitude) are used to study the diurnal, monthly and seasonal soil moisture variations. The effect of rainfall on diurnal and seasonal soil moisture is discussed.

  10. development and testing of a capacitive digital soil moisture metre

    African Journals Online (AJOL)

    user

    This paper presents a low cost, simple digital soil moisture meter, working on the principle of dielectric. A digital soil moisture meter using the NE555 timer and micro controller as a major electronic component was developed and tested, which display its output in a range of 0.0 to 99% on the 7-segment displayed unit.

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

    Science.gov (United States)

    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).

  12. Feasibility of soil moisture estimation using passive distributed temperature sensing

    NARCIS (Netherlands)

    Steele-Dunne, S.C.; Rutten, M.M.; Krzeminska, D.M.; Hausner, M.; Tyler, S.W.; Selker, J.; Bogaard, T.A.; Van de Giesen, N.C.

    2010-01-01

    Through its role in the energy and water balances at the land surface, soil moisture is a key state variable in surface hydrology and land?atmosphere interactions. Point observations of soil moisture are easy to make using established methods such as time domain reflectometry and gravimetric

  13. Managing soil moisture on waste burial sites

    International Nuclear Information System (INIS)

    Anderson, J.E.; Ratzlaff, T.D.

    1991-11-01

    Shallow land burial is a common method of disposing of industrial, municipal, and low-level radioactive waste. The exclusion of water from buried wastes is a primary objective in designing and managing waste disposal sites. If wastes are not adequately isolated, water from precipitation may move through the landfill cover and into the wastes. The presence of water in the waste zone may promote the growth of plant roots to that depth and result in the transport of toxic materials to above-ground foliage. Furthermore, percolation of water through the waste zone may transport contaminants into ground water. This report presents results from a field study designed to assess the the potential for using vegetation to deplete soil moisture and prevent water from reaching buried wastes at the Idaho National Engineering Laboratory (INEL). Our results show that this approach may provide an economical means of limiting the intrusion of water on waste sites

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

    Science.gov (United States)

    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...

  15. Evaluation of a method to downscale intermediate-resolution soil moisture to a fine-resolution using topographic, vegetation, and soil data

    Science.gov (United States)

    Knowledge of soil moisture patterns and dynamics is important for many land and watershed management applications. Remote sensing methods can estimate soil moisture over large regions, but the spatial resolution of these estimates is very coarse (~ 1 km grid cells or larger). In order to be applicab...

  16. Soil moisture responses to vapour pressure deficit in polytunnel-grown tomato under soil moisture triggered irrigation control

    Science.gov (United States)

    Goodchild, Martin; Kühn, Karl; Jenkins, Dick

    2014-05-01

    The aim of this work has been to investigate soil-to-atmosphere water transport in potted tomato plants by measuring and processing high-resolution soil moisture data against the environmental driver of vapour pressure deficit (VPD). Whilst many researchers have successfully employed sap flow sensors to determine water uptake by roots and transport through the canopy, the installation of sap flow sensors is non-trivial. This work presents an alternative method that can be integrated with irrigation controllers and data loggers that employ soil moisture feedback which can allow water uptake to be evaluated against environmental drivers such as VPD between irrigation events. In order to investigate water uptake against VPD, soil moisture measurements were taken with a resolution of 2 decimal places - and soil moisture, air temperature and relative humidity measurements were logged every 2 minutes. Data processing of the soil moisture was performed in an Excel spread sheet where changes in water transport were derived from the rate of change of soil moisture using the Slope function over 5 soil moisture readings. Results are presented from a small scale experiment using a GP2-based irrigation controller and data logger. Soil moisture feedback is provided from a single SM300 soil moisture sensor in order to regulate the soil moisture level and to assess the water flow from potted tomato plants between irrigation events. Soil moisture levels were set to avoid drainage water losses. By determining the rate of change in soil moisture between irrigation events, over a 16 day period whilst the tomato plant was in flower, it has been possible to observe very good correlation between soil water uptake and VPD - illustrating the link between plant physiology and environmental conditions. Further data is presented for a second potted tomato plant where the soil moisture level is switched between the level that avoids drainage losses and a significantly lower level. This data

  17. Impacts of Irrigation on Soil Moisture Scaling Properties and Downscaling

    Science.gov (United States)

    Ko, A.; Mascaro, G.; Vivoni, E. R.

    2015-12-01

    Soil moisture (θ) exhibits high spatial variability due to the combined effect of natural and anthropogenic factors. Among the latter group, irrigation can introduce significant heterogeneity in the spatial variability of θ, thus modifying the statistical properties typically observed in natural landscapes. This, in turn, can affect the application of downscaling models of coarse satellite θ products based on the hypothesis of spatial homogeneity of θ distribution. In this study, the impact of irrigation on the scale invariance properties of θ and the application of a multifractal downscaling algorithm are analyzed using ground- and aircraft-based θ measurements from the National Airborne Field Experiments 2005 (NAFE05) and 2006 (NAFE06) campaigns conducted in two sites in Australia. After identifying irrigated areas through vegetation indices derived from Landsat 5 Thematic Mapper scenes, we investigate the presence of scale invariance from 32 km to 1 km in three scenarios, including (1) the original θ fields and in cases where θ in irrigated pixels was (2) replaced with missing data or (3) interpolated from neighboring pixels. We found that irrigation has a larger impact on the scale invariance properties in a large and compact agricultural district in the NAFE06 region, while it has a negligible influence on the sparser districts of NAFE05. The θ fields of scenario 3 are then used to calibrate a downscaling model based on spatially-homogeneous multifractal cascades as a function of coarse predictors. The model capability to reproduce the θ variability across scales is assessed by comparing ensembles of disaggregated field with the small-scale θ airborne observations and, for the first time, with ground θ measurements. Model performances are adequate in most cases in both experiments, although some deficiencies are found in regions with a larger presence of irrigated fields, suggesting the need to further refine the technique for detection of

  18. Agricultural Drought Assessment In Latin America Based On A Standardized Soil Moisture Index

    Science.gov (United States)

    Carrao, Hugo; Russo, Simone; Sepulcre, Guadalupe; Barbosa, Paulo

    2013-12-01

    We propose a relatively simple, spatially invariant and probabilistic year-round Standardized Soil Moisture Index (SSMI) that is designed to estimate drought conditions from satellite imagery data. The SSMI is based on soil moisture content alone and is defined as the number of standard deviations that the observed moisture at a given location and timescale deviates from the long- term normal conditions. Specifically, the SSMI is computed by fitting a non-parametric probability distribution function to historical soil moisture records and then trans- forming it into a normal distribution with a mean of zero and standard deviation of one. Negative standard normal values indicate dry conditions and positive values indicate wet conditions. To evaluate the applicability of the SSMI, we fitted empirical and normal cumulative distribution functions (ECDF and nCDF) to 32-years of averaged soil moisture amounts derived from the Essential Climate Variable (ECV) Soil Moisture (SM) dataset, and compared the root-mean-squared errors of residuals. SM climatology was calculated on a 0.25° grid over Latin America at timescales of 1, 3, 6, and 12 months for the long-term period of 1979-2010. Results show that the ECDF fits better the soil moisture data than the nCDF at all timescales and that the negative SSMI values computed with the non-parametric estimator accurately identified the temporal and geographic distribution of major drought events that occurred in the study area.

  19. Soil moisture monitoring in Candelaro basin, Southern Italy

    Science.gov (United States)

    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

  20. COSMOS: the COsmic-ray Soil Moisture Observing System

    Directory of Open Access Journals (Sweden)

    M. Zreda

    2012-11-01

    Full Text Available The newly-developed cosmic-ray method for measuring area-average soil moisture at the hectometer horizontal scale is being implemented in the COsmic-ray Soil Moisture Observing System (or the COSMOS. The stationary cosmic-ray soil moisture probe measures the neutrons that are generated by cosmic rays within air and soil and other materials, moderated by mainly hydrogen atoms located primarily in soil water, and emitted to the atmosphere where they mix instantaneously at a scale of hundreds of meters and whose density is inversely correlated with soil moisture. The COSMOS has already deployed more than 50 of the eventual 500 cosmic-ray probes, distributed mainly in the USA, each generating a time series of average soil moisture over its horizontal footprint, with similar networks coming into existence around the world. This paper is written to serve a community need to better understand this novel method and the COSMOS project. We describe the cosmic-ray soil moisture measurement method, the instrument and its calibration, the design, data processing and dissemination used in the COSMOS project, and give example time series of soil moisture obtained from COSMOS probes.

  1. Validation of Distributed Soil Moisture: Airborne Polarimetric SAR vs. Ground-based Sensor Networks

    Science.gov (United States)

    Jagdhuber, T.; Kohling, M.; Hajnsek, I.; Montzka, C.; Papathanassiou, K. P.

    2012-04-01

    The knowledge of spatially distributed soil moisture is highly desirable for an enhanced hydrological modeling in terms of flood prevention and for yield optimization in combination with precision farming. Especially in mid-latitudes, the growing agricultural vegetation results in an increasing soil coverage along the crop cycle. For a remote sensing approach, this vegetation influence has to be separated from the soil contribution within the resolution cell to extract the actual soil moisture. Therefore a hybrid decomposition was developed for estimation of soil moisture under vegetation cover using fully polarimetric SAR data. The novel polarimetric decomposition combines a model-based decomposition, separating the volume component from the ground components, with an eigen-based decomposition of the two ground components into a surface and a dihedral scattering contribution. Hence, this hybrid decomposition, which is based on [1,2], establishes an innovative way to retrieve soil moisture under vegetation. The developed inversion algorithm for soil moisture under vegetation cover is applied on fully polarimetric data of the TERENO campaign, conducted in May and June 2011 for the Rur catchment within the Eifel/Lower Rhine Valley Observatory. The fully polarimetric SAR data were acquired in high spatial resolution (range: 1.92m, azimuth: 0.6m) by DLR's novel F-SAR sensor at L-band. The inverted soil moisture product from the airborne SAR data is validated with corresponding distributed ground measurements for a quality assessment of the developed algorithm. The in situ measurements were obtained on the one hand by mobile FDR probes from agricultural fields near the towns of Merzenhausen and Selhausen incorporating different crop types and on the other hand by distributed wireless sensor networks (SoilNet clusters) from a grassland test site (near the town of Rollesbroich) and from a forest stand (within the Wüstebach sub-catchment). Each SoilNet cluster

  2. Soil Moisture Memory in Karst and Non-Karst Landscapes

    Science.gov (United States)

    Sobocinski-Norton, H. E.; Dirmeyer, P.

    2016-12-01

    Underlying geology plays an important role in soil column hydrology that is largely overlooked within the land surface model (LSM) parameterizations used in weather and climate models. LSMs typically treat the soil column as a set of horizontally homogeneous layers through which liquid water diffuses. These models parameterize the flow of water out of the bottom of the active soil column as "baseflow" that is typically a function of mean surface slope and the soil moisture in the lowest model layer. However, roughly 25% of the United States is underlain by karst systems that are characterized by heavily fractured bedrock or unconsolidated materials. These heavily fractured systems allow for more rapid drainage, increasing "baseflow" and reducing the amount of soil moisture available for surface fluxes. This increased drainage can also affect soil moisture memory, which is key to determining the strength of land-atmosphere coupling. We examine lagged autocorrelations of in-situ soil moisture data from climatologically similar stations over different substrates, to determine the extent to which karst affects soil moisture memory. These results are compared to simulations with the NCEP Noah LSM with both default parameters and setting all soil types to sand to enhance drainage in a crude approximation of karst macropores. Given the importance of soil moisture in surface fluxes and in turn land-atmospheric coupling, we will demonstrate the importance of representing shallow geology as realistically as possible, and develop better parameterizations of these processes for LSMs.

  3. Validation and Scaling of Soil Moisture in a Semi-Arid Environment: SMAP Validation Experiment 2015 (SMAPVEX15)

    Science.gov (United States)

    Colliander, Andreas; Cosh, Michael H.; Misra, Sidharth; Jackson, Thomas J.; Crow, Wade T.; Chan, Steven; Bindlish, Rajat; Chae, Chun; Holifield Collins, Chandra; Yueh, Simon H.

    2017-01-01

    The NASA SMAP (Soil Moisture Active Passive) mission conducted the SMAP Validation Experiment 2015 (SMAPVEX15) in order to support the calibration and validation activities of SMAP soil moisture data products. The main goals of the experiment were to address issues regarding the spatial disaggregation methodologies for improvement of soil moisture products and validation of the in situ measurement upscaling techniques. To support these objectives high-resolution soil moisture maps were acquired with the airborne PALS (Passive Active L-band Sensor) instrument over an area in southeast Arizona that includes the Walnut Gulch Experimental Watershed (WGEW), and intensive ground sampling was carried out to augment the permanent in situ instrumentation. The objective of the paper was to establish the correspondence and relationship between the highly heterogeneous spatial distribution of soil moisture on the ground and the coarse resolution radiometer-based soil moisture retrievals of SMAP. The high-resolution mapping conducted with PALS provided the required connection between the in situ measurements and SMAP retrievals. The in situ measurements were used to validate the PALS soil moisture acquired at 1-km resolution. Based on the information from a dense network of rain gauges in the study area, the in situ soil moisture measurements did not capture all the precipitation events accurately. That is, the PALS and SMAP soil moisture estimates responded to precipitation events detected by rain gauges, which were in some cases not detected by the in situ soil moisture sensors. It was also concluded that the spatial distribution of the soil moisture resulted from the relatively small spatial extents of the typical convective storms in this region was not completely captured with the in situ stations. After removing those cases (approximately10 of the observations) the following metrics were obtained: RMSD (root mean square difference) of0.016m3m3 and correlation of 0.83. The

  4. Evaluation of random cascade hierarchical and statistical arrangement model in disaggregation of SMOS soil moisture

    Science.gov (United States)

    Hosseini, M.; Magagi, R.; Goita, K.

    2013-12-01

    Soil moisture is an important parameter in hydrology that can be derived from remote sensing. In different studies, it was shown that optical-thermal, active and passive microwave remote sensing data can be used for soil moisture estimation. However, the most promising approach to estimate soil moisture in large areas is passive microwave radiometry. Global estimation of soil moisture is now operational by using remote sensing techniques. The Advanced Microwave Scanning Radiometer-Earth Observing System Sensor (AMSR-E) and Soil Moisture and Ocean Salinity (SMOS) passive microwave radiometers that were lunched on 2002 and 2009 respectively along with the upcoming Soil Moisture Active-Passive (SMAP) satellite that was planned to be lunched in the time frame of 2014-2015 make remote sensing to be more useful in soil moisture estimation. However, the spatial resolutions of AMSR-E, SMOS and SMAP are 60 km, 40 km and 10 km respectively. These very low spatial resolutions can not show the temporal and spatial variability of soil moisture in field or small scales. So, using disaggregation methods is required to efficiently using the passive microwave derived soil moisture information in different scales. The low spatial resolutions of passive microwave satellites can be improved by using disaggregation methods. Random Cascade (RC) model (Over and Gupta, 1996) is used in this research to downscale the 40 km resolution of SMOS satellite. By using this statistical method, the SMOS soil moisture resolutions are improved to 20 km, 10 km, 5 km and 2.5 km, respectively. The data that were measured during Soil Moisture Active Passive Validation Experiment 2012 (SMAPVEX12) field campaign are used to do the experiments. Totally the ground data and SMOS images that were obtained during 13 different days from 7-June-2012 to 13-July-2012 are used. By comparison with ground soil moisture, it is observed that the SMOS soil moisture is underestimated for all the images and so bias amounts

  5. The impact of land surface temperature on soil moisture anomaly detection from passive microwave observations

    Directory of Open Access Journals (Sweden)

    R. M. Parinussa

    2011-10-01

    Full Text Available For several years passive microwave observations have been used to retrieve soil moisture from the Earth's surface. Low frequency observations have the most sensitivity to soil moisture, therefore the current Soil Moisture and Ocean Salinity (SMOS and future Soil Moisture Active and Passive (SMAP satellite missions observe the Earth's surface in the L-band frequency. In the past, several satellite sensors such as the Advanced Microwave Scanning Radiometer-EOS (AMSR-E and WindSat have been used to retrieve surface soil moisture using multi-channel observations obtained at higher microwave frequencies. While AMSR-E and WindSat lack an L-band channel, they are able to leverage multi-channel microwave observations to estimate additional land surface parameters. In particular, the availability of Ka-band observations allows AMSR-E and WindSat to obtain coincident surface temperature estimates required for the retrieval of surface soil moisture. In contrast, SMOS and SMAP carry only a single frequency radiometer and therefore lack an instrument suited to estimate the physical temperature of the Earth. Instead, soil moisture algorithms from these new generation satellites rely on ancillary sources of surface temperature (e.g. re-analysis or near real time data from weather prediction centres. A consequence of relying on such ancillary data is the need for temporal and spatial interpolation, which may introduce uncertainties. Here, two newly-developed, large-scale soil moisture evaluation techniques, the triple collocation (TC approach and the Rvalue data assimilation approach, are applied to quantify the global-scale impact of replacing Ka-band based surface temperature retrievals with Modern Era Retrospective-analysis for Research and Applications (MERRA surface temperature output on the accuracy of WindSat and AMSR-E based surface soil moisture retrievals. Results demonstrate that under sparsely vegetated conditions, the use of

  6. Ensemble based Assimilation of SMOS Surface Soil Moisture into the Surfex 11-layer Diffusion Scheme

    Science.gov (United States)

    Blyverket, Jostein; Hamer, Paul; Svendby, Tove; Lahoz, William

    2017-04-01

    The Soil Moisture and Ocean Salinity (SMOS) satellite samples soil moisture at a spatial scale of ˜40 km and in the top ˜5 cm of the soil, depending on land cover and soil type. Remote sensing products have a limited spatial and temporal cover, with a re-visit time of 3 days close to the Equator for SMOS. These factors make it difficult to monitor the hydrological cycle over e.g., Northern Areas where there is a strong topography, fractal coastline and long periods of snow cover, all of which affect the SMOS soil moisture retrieval. Until now simple 3-layer force and restore models have been used to close the spatial (vertical/horizontal) and temporal gaps of soil moisture from remote sensing platforms. In this study we have implemented the Ensemble Transform Kalman Filter (ETKF) into the Surfex land surface model, and used the ISBA diffusion scheme with 11-vertical layers. In contrast to the rapid changing surface layer, the slower changing root zone soil moisture is important for long term evapotranspiration and water supply. By combining a land surface model with satellite observations using data assimilation we can provide a better estimate of the root zone soil moisture at regional scales. The Surfex model runs are done for a European domain, from 1 July 2012 to 1 August 2013. For validation of our model setup, we compare with in situ stations from the International Soil Moisture Network (ISMN) and the Norwegian Water and Energy Authorities (NVE); we also compare against the ESA CCI soil moisture product v02.2, which does not include SMOS soil moisture data. SMOS observations and open loop model runs are shown to exhibit large biases, these are removed before assimilation by a linear rescaling technique. Information from the satellite is transferred into deeper layers of the model using data assimilation, improving the root zone product when validated against in situ stations. The improved correlation between the assimilated product and the in situ values

  7. Errors in the calculation of sub-soil moisture probe by equivalent moisture content technique

    International Nuclear Information System (INIS)

    Lakshmipathy, A.V.; Gangadharan, P.

    1982-01-01

    The size of the soil sample required to obtain the saturation response, with a neutron moisture probe is quite large and this poses practical problems of handling and mixing large amounts of samples for absolute laboratory calibration. Hydrogenous materials are used as a substitute for water in the equivalent moisture content technique, for calibration of soil moisture probes. In this it is assumed that only hydrogen of the bulk sample is responsible for the slowing down of fast neutrons and the slow neutron countrate is correlated to equivalent water content by considering the hydrogen density of sample. It is observed that the higher atomic number elements present in water equivalent media also affect the response of the soil moisture probe. Hence calculations, as well as experiments, were undertaken to know the order of error introduced by this technique. The thermal and slow neutron flux distribution around the BF 3 counter of a sub-soil moisture probe is calculated using three group diffusion theory. The response of the probe corresponding to different equivalent moisture content of hydrogenous media, is calculated taking into consideration the effective length of BF 3 counter. Soil with hydrogenous media such as polyethylene, sugar and water are considered for calculation, to verify the suitability of these materials as substitute for water during calibration of soil moisture probe. Experiments were conducted, to verify the theoretically calculated values. (author)

  8. Quality Improvement of the Satellite Soil Moisture Products by Fusing In Situ and GNSS-R Observation

    Science.gov (United States)

    Yuan, Q.; Xu, H.; Li, T.; Shen, H.; Zhang, L.

    2017-12-01

    Soil moisture plays a fundamental role in the hydrological cycle as well as in the energy partitioning. On this basis, it is of great concern to derive a long-term soil moisture time series on a global scale and monitor its temporal and spatial variations for practical applications. Although passive and active microwave satellites have been shown to provide useful retrievals of near-surface soil moisture at regional and global scales, the limitations in retrieval accuracy prevent them from high-quality applications in specific areas. On the other hand, measuring soil moisture straightly through in situdevices, such as soil moisture probes, is high accuracy, but is not able to derive global soil moisture maps. Recently, the ground-based GNSS-R method is emerging in monitoring near-surface soil moisture variations but still over limited spatial scales. In this paper, a multi-source data fusion method was applied to synthesize regional high-quality soil moisture products from 2015 to 2017 in western parts of the continental United States. Firstly, we put all the three soil moisture datasets into the generalized regression neural network (GRNN) model. The input signals of the model are SMOS and SMAP satellite-derived passive level 3 soil moisture daily products combined with date and latitude and longitude information, while the in situ measured and GNSS-R retrieved soil moisture are used as target. Finally, we apply the model to all the soil moisture time series in the experiment area and obtain two high-quality regional soil moisture products for SMOS and SMAP, respectively. The results before fusion show that the correlation coefficients between site-specific soil moisture and satellite-derived soil moisture are 0.39 for SMOS and 0.27 for SMAP and that unbiased root-mean-square errors (ubRMSE) are 0.113 for SMOS and 0.128 for SMAP, respectively. After applying the GRNN-R, the model fitted correlation coefficients have reached 0.72 for SMOS and 0.75 for SMAP and the

  9. Evaluating near-surface soil moisture using Heat Capacity Mapping Mission data

    Science.gov (United States)

    Heilman, J. L.; Moore, D. G.

    1982-01-01

    Four dates of Heat Capacity Mapping Mission (HCMM) data were analyzed in order to evaluate HCMM thermal data use in estimating near-surface soil moisture in a complex agricultural landscape. Because of large spatial and temporal ground cover variations, HCMM radiometric temperatures alone did not correlate with soil water content. The radiometric temperatures consisted of radiance contributions from different canopies and their respective soil backgrounds. However, when surface soil temperatures were empirically estimated from HCMM temperatures and percent cover of each pixel, a highly significant correlation was obtained between the estimated soil temperatures and near-surface soil water content.

  10. SMEX02 Watershed Vitel Network Soil Moisture Data, Walnut Creek, Iowa

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set contains several parameters measured for the Soil Moisture Experiment 2002 (SMEX02). The parameters include soil moisture, temperature, conductivity,...

  11. Development of a Scaling Algorithm for Remotely Sensed and In-situ Soil Moisture Data across Complex Terrain

    Science.gov (United States)

    Shin, Y.; Mohanty, B. P.

    2012-12-01

    Spatial scaling algorithms have been developed/improved for increasing the availability of remotely sensed (RS) and in-situ soil moisture data for hydrologic applications. Existing approaches have their own drawbacks such as application in complex terrains, complexity of coupling downscaling and upscaling approaches, etc. In this study, we developed joint downscaling and upscaling algorithm for remotely sensed and in-situ soil moisture data. Our newly developed algorithm can downscale RS soil moisture footprints as well as upscale in-situ data simultaneously in complex terrains. This scheme is based on inverse modeling with a genetic algorithm. Normalized digital elevation model (NDEM) and normalized difference vegetation index (NDVI) that represent the heterogeneity of topography and vegetation covers, were used to characterize the variability of land surface. Our approach determined soil hydraulic parameters from RS and in-situ soil moisture at the airborne-/satellite footprint scales. Predicted soil moisture estimates were driven by derived soil hydraulic properties using a hydrological model (Soil-Water-Atmosphere-Plant, SWAP). As model simulated soil moisture predictions were generated for different elevations and NDVI values across complex terrains at a finer-scale (30 m 30 m), downscaled and upscaled soil moisture estimates were obtained. We selected the Little Washita watershed in Oklahoma for validating our proposed methodology at multiple scales. This newly developed joint downscaling and upscaling algorithm performed well across topographically complex regions and improved the availability of RS and in-situ soil moisture at appropriate scales for agriculture and water resources management efficiently.

  12. Integrating soil moisture measurements into pasture growth forecasting in New Zealand's hill country

    OpenAIRE

    Hajdu, I; Yule, I; Bretherton, M; Singh, R; Grafton, M; Hedley, C

    2017-01-01

    Forecasting pasture growth in hill country landscapes requires information about soil water retention characteristics, which will help to quantify both water uptake, and its percolation below the root zone. Despite the importance of soil moisture data in pasture productivity predictions, current models use low-resolution estimates of water input into their soil water balance equations and plant growth simulations. As a result, they frequently fail to capture the spatial and temporal variabili...

  13. SMOS CATDS Level 3 products, Soil Moisture and Brightness Temperature: Presentation and results

    Science.gov (United States)

    Berthon, Lucie; Mialon, Arnaud; Bitar, Ahmad Al; Cabot, François; Bircher, Simone; Jacquette, Elsa; Quesney, Arnaud; Kerr, Yann H.

    2013-04-01

    The ESA's (European Space Agency) SMOS (Soil Moisture and Ocean Salinity) mission, operating since November 2009, is the first satellite dedicated to measuring surface soil moisture and ocean salinity. The CNES (Centre National d'Etudes Spatiales) has developed the CATDS (Centre Aval de Traitement des Données SMOS) ground segment. It provides spatial and temporal synthesis products (referred to as Level 3) of soil moisture, which are now covering the whole SMOS operation period since January 2010. These products have different time resolutions: daily products, 3-day global products (insuring a complete coverage of the Earth's surface), 10-day composite products, and monthly averaged products. Moreover, a new product provides brightness temperatures at H and V polarizations which are computed at fixed incidence angles every 5 degrees. All the CATDS products are presented in the NetCDF format on the EASE grid (Equal Area Scalable Earth grid) with a spatial resolution of ~ 25*25 km². The soil moisture Level 3 algorithm is based on ESA's Level 2 retrieval scheme with the improvement of using several overpasses (3 at most) over a 7-day window. Using many revisits is expected to improve the quality of the retrieved soil moisture. This communication aims at presenting the CATDS soil moisture and brightness temperature products as well as other geophysical parameters retrieved on the side, such as the vegetation optical depth or the dielectric constant of the surface. Furthermore, we illustrate the validation of this database, including the comparison of the Level 3 soil moisture to in-situ measurements available from various sites (Australia, US, southwest of France, Spain, Denmark, West Africa, French Alps), spanning different surface conditions.

  14. Response of grassland ecosystems to prolonged soil moisture deficit

    Science.gov (United States)

    Ross, Morgan A.; Ponce-Campos, Guillermo E.; Barnes, Mallory L.; Hottenstein, John D.; Moran, M. Susan

    2014-05-01

    Soil moisture is commonly used for predictions of plant response and productivity. Climate change is predicted to cause an increase in the frequency and duration of droughts over the next century, which will result in prolonged periods of below-normal soil moisture. This, in turn, is expected to impact regional plant production, erosion and air quality. In fact, the number of consecutive months of soil moisture content below the drought-period mean has recently been linked to regional tree and shrub mortality in the southwest United States. This study investigated the effects of extended periods of below average soil moisture on the response of grassland ANPP to precipitation. Grassland ecosystems were selected for this study because of their ecological sensitivity to precipitation patterns. It has been postulated that the quick ecological response of grasslands to droughts can provide insight to large scale functional responses of regions to predicted climate change. The study sites included 21 grassland biomes throughout arid-to-humid climates in the United States with continuous surface soil moisture records for 2-13 years during the drought period from 2000-2013. Annual net primary production (ANPP) was estimated from the 13-year record of NASA MODIS Enhanced Vegetation Index extracted for each site. Prolonged soil moisture deficit was defined as a period of at least 10 consecutive months during which soil moisture was below the drought-period mean. ANPP was monitored before, during and after prolonged soil moisture deficit to quantify shifts in the functional response of grasslands to precipitation, and in some cases, new species assemblages that included invasive species. Preliminary results indicated that when altered climatic conditions on grasslands led to an increase in the duration of soil water deficit, then the precipitation-to-ANPP relation became non-linear. Non-linearity was associated with extreme grassland dieback and changes in the historic

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

    Science.gov (United States)

    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

  16. Parameter estimation of a two-horizon soil profile by combining crop canopy and surface soil moisture observations using GLUE

    Science.gov (United States)

    Sreelash, K.; Sekhar, M.; Ruiz, L.; Tomer, S. K.; Guérif, M.; Buis, S.; Durand, P.; Gascuel-Odoux, C.

    2012-08-01

    SummaryEstimation of soil parameters by inverse modeling using observations on either surface soil moisture or crop variables has been successfully attempted in many studies, but difficulties to estimate root zone properties arise when heterogeneous layered soils are considered. The objective of this study was to explore the potential of combining observations on surface soil moisture and crop variables - leaf area index (LAI) and above-ground biomass for estimating soil parameters (water holding capacity and soil depth) in a two-layered soil system using inversion of the crop model STICS. This was performed using GLUE method on a synthetic data set on varying soil types and on a data set from a field experiment carried out in two maize plots in South India. The main results were (i) combination of surface soil moisture and above-ground biomass provided consistently good estimates with small uncertainity of soil properties for the two soil layers, for a wide range of soil paramater values, both in the synthetic and the field experiment, (ii) above-ground biomass was found to give relatively better estimates and lower uncertainty than LAI when combined with surface soil moisture, especially for estimation of soil depth, (iii) surface soil moisture data, either alone or combined with crop variables, provided a very good estimate of the water holding capacity of the upper soil layer with very small uncertainty whereas using the surface soil moisture alone gave very poor estimates of the soil properties of the deeper layer, and (iv) using crop variables alone (else above-ground biomass or LAI) provided reasonable estimates of the deeper layer properties depending on the soil type but provided poor estimates of the first layer properties. The robustness of combining observations of the surface soil moisture and the above-ground biomass for estimating two layer soil properties, which was demonstrated using both synthetic and field experiments in this study, needs now to

  17. Microbial destruction of chitin in soils under different moisture conditions

    Science.gov (United States)

    Yaroslavtsev, A. M.; Manucharova, N. A.; Stepanov, A. L.; Zvyagintsev, D. G.; Sudnitsyn, I. I.

    2009-07-01

    The most favorable moisture conditions for the microbial destruction of chitin in soils are close to the total water capacity. The water content has the most pronounced effect on chitin destruction in soils in comparison with other studied substrates. It was found using gas-chromatographic and luminescent-microscopic methods that the maximum specific activity of the respiration of the chitinolytic community was at a rather low redox potential with the soil moisture close to the total water capacity. The range of moisture values under which the most intense microbial transformation of chitin occurred was wider in clayey and clay loamy soils as compared with sandy ones. The increase was observed due to the contribution of mycelial bacteria and actinomycetes in the chitinolytic complex as the soil moisture increased.

  18. Estimating Root Mean Square Errors in Remotely Sensed Soil Moisture over Continental Scale Domains

    Science.gov (United States)

    Draper, Clara S.; Reichle, Rolf; de Jeu, Richard; Naeimi, Vahid; Parinussa, Robert; Wagner, Wolfgang

    2013-01-01

    Root Mean Square Errors (RMSE) in the soil moisture anomaly time series obtained from the Advanced Scatterometer (ASCAT) and the Advanced Microwave Scanning Radiometer (AMSR-E; using the Land Parameter Retrieval Model) are estimated over a continental scale domain centered on North America, using two methods: triple colocation (RMSETC ) and error propagation through the soil moisture retrieval models (RMSEEP ). In the absence of an established consensus for the climatology of soil moisture over large domains, presenting a RMSE in soil moisture units requires that it be specified relative to a selected reference data set. To avoid the complications that arise from the use of a reference, the RMSE is presented as a fraction of the time series standard deviation (fRMSE). For both sensors, the fRMSETC and fRMSEEP show similar spatial patterns of relatively highlow errors, and the mean fRMSE for each land cover class is consistent with expectations. Triple colocation is also shown to be surprisingly robust to representativity differences between the soil moisture data sets used, and it is believed to accurately estimate the fRMSE in the remotely sensed soil moisture anomaly time series. Comparing the ASCAT and AMSR-E fRMSETC shows that both data sets have very similar accuracy across a range of land cover classes, although the AMSR-E accuracy is more directly related to vegetation cover. In general, both data sets have good skill up to moderate vegetation conditions.

  19. Evaluation of NLDAS-2 Multi-Model Simulated Soil Moisture Using the Observations from North American Soil Moisture Dataset (NASMD)

    Science.gov (United States)

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

    2014-12-01

    The North American Land Data Assimilation System phase 2 (NLDAS-2, http://www.emc.ncep.noaa.gov/mmb/nldas/) has generated 35-years (1979-2013) of hydrometeorological products from four state-of-the-art land surface models (Noah, Mosaic, SAC, VIC). These products include energy fluxes, water fluxes, and state variables. Soil moisture is one of the most important state variables in NLDAS-2 as it plays a key role in land-atmosphere interaction, regional climate and ecological model simulation, water resource management, and other study areas. The soil moisture data from these models have been used for US operational drought monitoring activities, water resources management and planning, initialization of regional weather and climate models, and other meteorological and hydrological research purposes. However, these data have not yet been comprehensively evaluated due to the lack of extensive soil moisture observations. In this study, observations from over 1200 sites in the North America compiled from 27 observational networks in the North American Soil Moisture Database (NASMD, http://soilmoisture.tamu.edu/) were used to evaluate the model-simulated daily soil moisture for different vegetation cover varying from grassland to forest, and different soil texture varying from sand to clay. Seven states in the United States from NASMD were selected based on known measurement error estimates for the evaluation. Statistical metrics, such as anomaly correlation, root-mean-square errors (RMSE), and bias are computed to assess NLDAS-2 soil moisture products. Three sensitivity tests were performed using the Noah model to examine the effect of soil texture and vegetation type mismatch on NLDAS-2 soil moisture simulation. In the first test, site observed soil texture was used. In the second test, site observed vegetation type/land cover was used. In the third test, both site observed soil texture and vegetation type were used. The results from three sensitivity tests will be

  20. Impact of a Merged Precipitation Data on Global Soil Moisture Variability

    Science.gov (United States)

    Yang, Runhua; Houser, Paul R.

    1999-01-01

    Accurate soil moisture information has proved to be important to climate simulations and climate and weather forecasts. However, many difficulties exist that limit our understanding of soil moisture distribution and variability. One of them is the lack of accurate precipitation with appropriate spatial and temporal resolution. Precipitation as an input forcing to the land surface greatly influences soil moisture characteristics and variability. To improve precipitation data quality, an algorithm has been developed to generate a spatially and temporally continuous 3-hourly global precipitation data for the period of 1987 to present. This precipitation product is a combination of the precipitation from Special Sensor Microwave Imager (SSMI) with the Goddard Earth Observing System-1 Data Assimilation System (GEOS-1 DAS) employing a Physical-space Statistical Analysis System (PSAS). In this study we investigate the impact of this merged/analyzed precipitation data on the global soil moisture variability using an Off-line Land-surface GEOS Assimilation (OLGA) system. Two OLGA integrations starting from 1987 to 1993 are performed forced with the analyzed and GEOS-1 DAS precipitation respectively. We examine the spatial and temporal characteristics of soil moisture variability in response to the analyzed precipitation. The influence of this merged precipitation on the soil moisture variability and regional hydrological budget is estimated throughout the comparison with the results forced with the GEOS-1 DAS precipitation only. In the OLGA the sut@-grid scale horizontal heterogeneity is explicitly represented on the tile space. This provides a means to assess the role of the surface moisture heterogeneity in the interaction with the surface atmosphere and surface hydrological budget, and to validate OLGA results at tile space with in situ observation. ABRACOS (Anglo-Brazilian Amazonian Climate Observation Study), FIFE (First ISLSCP Field Experiment) I and HAPEX data will

  1. Effect of soil moisture on trace elements concentrations using ...

    African Journals Online (AJOL)

    Portable X-ray fluorescence (PXRF) technology can offer rapid and cost-effective determination of the trace elements concentrations in soils. The aim of this study was to assess the influence of soil moisture content under different condition on PXRF measurement quality. For this purpose, PXRF was used to evaluate the soil ...

  2. Estimating runoff and soil moisture deficit in guinea savannah region ...

    African Journals Online (AJOL)

    The estimation ofrunoff and soil moisture deficit in Guinea Savannah region using semi arid model based on soil water balance technique (SAMBA) was carried out. The input to the SAMBA model are daily rainfall, daily evapotranspiration. type and date of planting of crop, and soil parameters. The estimated runoff was ...

  3. Large scale evaluation of soil moisture retrievals from passive microwave observations

    Science.gov (United States)

    Parinussa, R.; Holmes, T. R.; Crow, W. T.; De Jeu, R. A.

    2011-12-01

    For several years passive microwave observations have been used to retrieve surface soil moisture from the Earth's surface. Several satellite sensors such as the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) and WindSat have been used for this purpose using multi-channel observations. Large scale validation of these retrievals is generally hampered by a lack of ground-based observation networks with sufficient spatial density to be accurately up-scaled to the resolution of satellite-based soil moisture retrievals. In response to this challenge, two new global evaluation techniques have been proposed which circumvent the need for extensive ground-based soil moisture observations. The first technique (Rvalue) is based on calculating the correlation coefficient between known rainfall errors and Kalman filter analysis increments realized during the assimilation of remotely sensed soil moisture into an antecedent precipitation index. The second technique is based on a so-called Triple Collocation (TC) analysis, which is a statistical tool for estimating the root mean square error (RMSE) of a set of three linearly related data sources with independent error structures. These two newly-developed, large-scale soil moisture evaluation techniques are applied for cross-verification on a global scale. Both techniques are also used to determine the sensitivity of soil moisture retrievals to land surface temperature estimates by artificially degrading the satellite signal used for the retrieval of this important parameter. Instead of coincident land surface temperature observations from the same satellite, external sources for land surface temperature are also evaluated using the same evaluation techniques. Finally, both day- and night-time observations are evaluated separately to determine the impact of the different physical conditions during day- and night-time. The evaluation results produced by the Rvalue and TC soil moisture verification approaches show a high mutual

  4. Improving simulation of soil moisture in China using a multiple meteorological forcing ensemble approach

    Directory of Open Access Journals (Sweden)

    J.-G. Liu

    2013-09-01

    Full Text Available The quality of soil-moisture simulation using land surface models depends largely on the accuracy of the meteorological forcing data. We investigated how to reduce the uncertainty arising from meteorological forcings in a simulation by adopting a multiple meteorological forcing ensemble approach. Simulations by the Community Land Model version 3.5 (CLM3.5 over mainland China were conducted using four different meteorological forcings, and the four sets of soil-moisture data related to the simulations were then merged using simple arithmetical averaging and Bayesian model averaging (BMA ensemble approaches. BMA is a statistical post-processing procedure for producing calibrated and sharp predictive probability density functions (PDFs, which is a weighted average of PDFs centered on the bias-corrected forecasts from a set of individual ensemble members based on their probabilistic likelihood measures. Compared to in situ observations, the four simulations captured the spatial and seasonal variations of soil moisture in most cases with some mean bias. They performed differently when simulating the seasonal phases in the annual cycle, the interannual variation and the magnitude of observed soil moisture over different subregions of mainland China, but no individual meteorological forcing performed best for all subregions. The simple arithmetical average ensemble product outperformed most, but not all, individual members over most of the subregions. The BMA ensemble product performed better than simple arithmetical averaging, and performed best for all fields over most of the subregions. The BMA ensemble approach applied to the ensemble simulation reproduced anomalies and seasonal variations in observed soil-moisture values, and simulated the mean soil moisture. It is presented here as a promising way for reproducing long-term, high-resolution spatial and temporal soil-moisture data.

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

    Science.gov (United States)

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

    2018-03-31

    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.

  6. Sensitivity of convective precipitation to soil moisture and vegetation during break spell of Indian summer monsoon

    Science.gov (United States)

    Kutty, Govindan; Sandeep, S.; Vinodkumar; Nhaloor, Sreejith

    2017-07-01

    Indian summer monsoon rainfall is characterized by large intra-seasonal fluctuations in the form of active and break spells in rainfall. This study investigates the role of soil moisture and vegetation on 30-h precipitation forecasts during the break monsoon period using Weather Research and Forecast (WRF) model. The working hypothesis is that reduced rainfall, clear skies, and wet soil condition during the break monsoon period enhance land-atmosphere coupling over central India. Sensitivity experiments are conducted with modified initial soil moisture and vegetation. The results suggest that an increase in antecedent soil moisture would lead to an increase in precipitation, in general. The precipitation over the core monsoon region has increased by enhancing forest cover in the model simulations. Parameters such as Lifting Condensation Level, Level of Free Convection, and Convective Available Potential Energy indicate favorable atmospheric conditions for convection over forests, when wet soil conditions prevail. On spatial scales, the precipitation is more sensitive to soil moisture conditions over northeastern parts of India. Strong horizontal gradient in soil moisture and orographic uplift along the upslopes of Himalaya enhanced rainfall over the east of Indian subcontinent.

  7. A methodology for the evaluation of global warming impact on soil moisture and runoff

    International Nuclear Information System (INIS)

    Valdes, J.B.; Seoane, R.S.; North, G.R.

    1993-01-01

    Global warming is expected to increase the intensity of the global hydrologic cycle. Precipitation and temperature patterns, soil moisture requirements, and the physical structure of the vegetation canopy play important roles in the hydrologic system of drainage basins. Changes in these phenomena, because of a buildup Of CO 2 and other trace gases, have the potential to affect the quantity, quality, timing, and spatial distribution of water available to satisfy the many demands placed on the resource by society. In this work a methodology for the evaluation of impact on soil moisture concentration and direct surface runoff is presented. The methodology integrates stochastic models of hydroclimatic input variables with a model of water balance in the soil. This allows the derivation of the probability distribution of soil moisture concentration and direct surface runoff for different combinations of climate and soil characteristics, ranging from humid to semi-arid and arid. These PDFs asses, in a comprehensive manner, the impact that climate change have on soil moisture and runoff and allow the water resources planner to make more educated decisions in the planning and design of water resources systems. The methodology was applied to three sites in Texas. To continue in the line of research suggested by Delworth and Manabe the authors computed the autocorrelation function (ACF) and the spectra of both precipitation inputs and soil moisture concentration outputs for all scenarios of climate change

  8. Soil Moisture and Temperature Measuring Networks in the Tibetan Plateau and Their Hydrological Applications

    Science.gov (United States)

    Yang, Kun; Chen, Yingying; Qin, Jun; Lu, Hui

    2017-04-01

    Multi-sphere interactions over the Tibetan Plateau directly impact its surrounding climate and environment at a variety of spatiotemporal scales. Remote sensing and modeling are expected to provide hydro-meteorological data needed for these process studies, but in situ observations are required to support their calibration and validation. For this purpose, we have established two networks on the Tibetan Plateau to measure densely two state variables (soil moisture and temperature) and four soil depths (0 5, 10, 20, and 40 cm). The experimental area is characterized by low biomass, high soil moisture dynamic range, and typical freeze-thaw cycle. As auxiliary parameters of these networks, soil texture and soil organic carbon content are measured at each station to support further studies. In order to guarantee continuous and high-quality data, tremendous efforts have been made to protect the data logger from soil water intrusion, to calibrate soil moisture sensors, and to upscale the point measurements. One soil moisture network is located in a semi-humid area in central Tibetan Plateau (Naqu), which consists of 56 stations with their elevation varying over 4470 4950 m and covers three spatial scales (1.0, 0.3, 0.1 degree). The other is located in a semi-arid area in southern Tibetan Plateau (Pali), which consists of 25 stations and covers an area of 0.25 degree. The spatiotemporal characteristics of the former network were analyzed, and a new spatial upscaling method was developed to obtain the regional mean soil moisture truth from the point measurements. Our networks meet the requirement for evaluating a variety of soil moisture products, developing new algorithms, and analyzing soil moisture scaling. Three applications with the network data are presented in this paper. 1. Evaluation of Current remote sensing and LSM products. The in situ data have been used to evaluate AMSR-E, AMSR2, SMOS and SMAP products and four modeled outputs by the Global Land Data

  9. Global Assessment of the SMAP Level-4 Soil Moisture Product Using Assimilation Diagnostics

    Science.gov (United States)

    Reichle, Rolf; Liu, Qing; De Lannoy, Gabrielle; Crow, Wade; Kimball, John; Koster, Randy; Ardizzone, Joe

    2018-01-01

    The Soil Moisture Active Passive (SMAP) mission Level-4 Soil Moisture (L4_SM) product provides 3-hourly, 9-km resolution, global estimates of surface (0-5 cm) and root-zone (0-100 cm) soil moisture and related land surface variables from 31 March 2015 to present with approx. 2.5-day latency. The ensemble-based L4_SM algorithm assimilates SMAP brightness temperature (Tb) observations into the Catchment land surface model. This study describes the spatially distributed L4_SM analysis and assesses the observation-minus-forecast (O-F) Tb residuals and the soil moisture and temperature analysis increments. Owing to the climatological rescaling of the Tb observations prior to assimilation, the analysis is essentially unbiased, with global mean values of approx. 0.37 K for the O-F Tb residuals and practically zero for the soil moisture and temperature increments. There are, however, modest regional (absolute) biases in the O-F residuals (under approx. 3 K), the soil moisture increments (under approx. 0.01 cu m/cu m), and the surface soil temperature increments (under approx. 1 K). Typical instantaneous values are approx. 6 K for O-F residuals, approx. 0.01 (approx. 0.003) cu m/cu m for surface (root-zone) soil moisture increments, and approx. 0.6 K for surface soil temperature increments. The O-F diagnostics indicate that the actual errors in the system are overestimated in deserts and densely vegetated regions and underestimated in agricultural regions and transition zones between dry and wet climates. The O-F auto-correlations suggest that the SMAP observations are used efficiently in western North America, the Sahel, and Australia, but not in many forested regions and the high northern latitudes. A case study in Australia demonstrates that assimilating SMAP observations successfully corrects short-term errors in the L4_SM rainfall forcing.

  10. Using Data Assimilation Diagnostics to Assess the SMAP Level-4 Soil Moisture Product

    Science.gov (United States)

    Reichle, Rolf; Liu, Qing; De Lannoy, Gabrielle; Crow, Wade; Kimball, John; Koster, Randy; Ardizzone, Joe

    2018-01-01

    The Soil Moisture Active Passive (SMAP) mission Level-4 Soil Moisture (L4_SM) product provides 3-hourly, 9-km resolution, global estimates of surface (0-5 cm) and root-zone (0-100 cm) soil moisture and related land surface variables from 31 March 2015 to present with approx.2.5-day latency. The ensemble-based L4_SM algorithm assimilates SMAP brightness temperature (Tb) observations into the Catchment land surface model. This study describes the spatially distributed L4_SM analysis and assesses the observation-minus-forecast (O-F) Tb residuals and the soil moisture and temperature analysis increments. Owing to the climatological rescaling of the Tb observations prior to assimilation, the analysis is essentially unbiased, with global mean values of approx. 0.37 K for the O-F Tb residuals and practically zero for the soil moisture and temperature increments. There are, however, modest regional (absolute) biases in the O-F residuals (under approx. 3 K), the soil moisture increments (under approx. 0.01 cu m/cu m), and the surface soil temperature increments (under approx. 1 K). Typical instantaneous values are approx. 6 K for O-F residuals, approx. 0.01 (approx. 0.003) cu m/cu m for surface (root-zone) soil moisture increments, and approx. 0.6 K for surface soil temperature increments. The O-F diagnostics indicate that the actual errors in the system are overestimated in deserts and densely vegetated regions and underestimated in agricultural regions and transition zones between dry and wet climates. The O-F auto-correlations suggest that the SMAP observations are used efficiently in western North America, the Sahel, and Australia, but not in many forested regions and the high northern latitudes. A case study in Australia demonstrates that assimilating SMAP observations successfully corrects short-term errors in the L4_SM rainfall forcing.

  11. Effects of neutron source type on soil moisture measurement

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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...

  13. response of three forage legumes to soil moisture stress

    African Journals Online (AJOL)

    MR PRINCE

    The cover crop x soil moisture interaction sig- nificantly (P = 0.05) influenced the forage pro- duction of nodules with numbers at the various moisture regimes following a trend of Stylosan- thes > Centrosema > Lablab with interaction means ranging from 32 to 132 (Table 3). Al- though, Stylosanthes significantly produced the.

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

    Science.gov (United States)

    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.

  15. [Priming Effects of Soil Moisture on Soil Respiration Under Different Tillage Practices].

    Science.gov (United States)

    Zhang, Yan; Liang, Ai-zhen; Zhang, Xiao-ping; Chen, Sheng-long; Sun, Bing-jie; Liu, Si-yi

    2016-03-15

    In the early stage of an incubation experiment, soil respiration has a sensitive response to different levels of soil moisture. To investigate the effects of soil moisture on soil respiration under different tillage practices, we designed an incubation trial using air-dried soil samples collected from tillage experiment station established on black soils in 2001. The tillage experiment consisted of no-tillage (NT), ridge tillage (RT), and conventional tillage (CT). According to field capacity (water-holding capacity, WHC), we set nine moisture levels including 30%, 60%, 90%, 120%, 150%, 180%, 210%, 240%, 270% WHC. During the 22-day short-term incubation, soil CO₂ emission was measured. In the early stage of incubation, the priming effects occurred under all tillage practices. There were positive correlations between soil respiration and soil moisture. In addition to drought and flood conditions, soil CO₂ fluxes followed the order of NT > RT > CT. We fitted the relationship between soil moisture and soil CO₂ fluxes under different tillage practices. In the range of 30%-270% WHC, soil CO₂ fluxes and soil moisture fitted a quadratic regression equation under NT, and linear regression equations under RT and CT. Under the conditions of 30%-210% WHC of both NT and RT, soil CO₂ fluxes and soil moisture were well fitted by the logarithmic equation with fitting coefficient R² = 0.966 and 0.956, respectively.

  16. Site Averaged Neutron Soil Moisture: 1987-1989 (Betts)

    Data.gov (United States)

    National Aeronautics and Space Administration — ABSTRACT: Site averaged product of the neutron probe soil moisture collected during the 1987-1989 FIFE experiment. Samples were averaged for each site, then averaged...

  17. Site Averaged Gravimetric Soil Moisture: 1987-1989 (Betts)

    Data.gov (United States)

    National Aeronautics and Space Administration — Site averaged product of the gravimetric soil moisture collected during the 1987-1989 FIFE experiment. Samples were averaged for each site, then averaged for each...

  18. Site Averaged Gravimetric Soil Moisture: 1987-1989 (Betts)

    Data.gov (United States)

    National Aeronautics and Space Administration — ABSTRACT: Site averaged product of the gravimetric soil moisture collected during the 1987-1989 FIFE experiment. Samples were averaged for each site, then averaged...

  19. A comparison of soil moisture relations between standing and ...

    African Journals Online (AJOL)

    A comparison of soil moisture relations between standing and clearfelled plots with burnt and unburnt harvest residue treatments of a clonal eucalypt plantation on the Zululand Coastal Plain, South Africa.

  20. SMEX02 Watershed Soil Moisture Data, Walnut Creek, Iowa

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set combines data for several parameters measured for the Soil Moisture Experiment 2002 (SMEX02). The parameters include bulk density, gravimetric and...

  1. Estimating soil moisture using the Danish polarimetric SAR

    DEFF Research Database (Denmark)

    Jiankang, Ji; Thomsen, A.; Skriver, Henning

    1995-01-01

    The results of applying data from the Danish polarimetric SAR (EMISAR) to estimate soil moisture for bare fields are presented. Fully calibrated C-band SAR images for hh, vv and cross polarizations have been used in this study. The measured surface roughness data showed that classical roughness...... autocorrelation functions (Gaussian and Exponential) were not able to fit natural surfaces well. A Gauss-Exp hybrid model which agreed better with the measured data has been proposed. Theoretical surface scattering models (POM, IEM), as well as an empirical model for retrieval of soil moisture and surface rms...... height from coand cross-polarized ratio, have been examined, but the results are less satisfactory. As soil moisture response to backscattering coefficient σo is mainly coupled to surface roughness effect for bare fields, a bilinear model coupling volumetric soil moisture mv and surface rms height σ...

  2. Aquarius L2 Swath Single Orbit Soil Moisture V004

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set contains Level-2 global soil moisture estimates derived from the NASA Aquarius passive microwave radiometer on the Satélite de Aplicaciones Científicas...

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

    Science.gov (United States)

    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.

  4. CLPX-Ground: ISA Soil Moisture Measurements, Version 1

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set consists of in-situ point measurements of soil moisture within three 25-km by 25-km Meso-cell Study Areas (MSAs) in northern Colorado (Fraser, North...

  5. SMAPVEX12 PALS Soil Moisture Data V001

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set contains soil moisture data obtained by the Passive Active L-band System (PALS) aircraft instrument. The data were collected as part of SMAPVEX12, the...

  6. SMEX03 Watershed Ground Soil Moisture Data: Oklahoma

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set combines data for several parameters measured for the Soil Moisture Experiment 2003 (SMEX03). The parameters include bulk density, gravimetric and...

  7. Soil Moisture for Western Russia and The Ukraine

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset, DSI-6411 is comprised of soil moisture data and the accompanying information for the agricultural regions of Western Russia (west of ~ 60E) and The...

  8. The sensitivity of US wildfire occurrence to pre-season soil moisture conditions across ecosystems.

    Science.gov (United States)

    Jensen, Daniel; Reager, John T; Zajic, Brittany; Rousseau, Nick; Rodell, Matthew; Hinkley, Everett

    2018-01-01

    It is generally accepted that year-to-year variability in moisture conditions and drought are linked with increased wildfire occurrence. However, quantifying the sensitivity of wildfire to surface moisture state at seasonal lead-times has been challenging due to the absence of a long soil moisture record with the appropriate coverage and spatial resolution for continental-scale analysis. Here we apply model simulations of surface soil moisture that numerically assimilate observations from NASA's Gravity Recovery and Climate Experiment (GRACE) mission with the US Forest Service's historical Fire-Occurrence Database over the contiguous United States. We quantify the relationships between pre-fire-season soil moisture and subsequent-year wildfire occurrence by land-cover type and produce annual probable wildfire occurrence and burned area maps at 0.25-degree resolution. Cross-validated results generally indicate a higher occurrence of smaller fires when months preceding fire season are wet, while larger fires are more frequent when soils are dry. This result is consistent with the concept of increased fuel accumulation under wet conditions in the pre-season. These results demonstrate the fundamental strength of the relationship between soil moisture and fire activity at long lead-times and are indicative of that relationship's utility for the future development of national-scale predictive capability.

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

    Science.gov (United States)

    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. The sensitivity of US wildfire occurrence to pre-season soil moisture conditions across ecosystems

    Science.gov (United States)

    Jensen, Daniel; Reager, John T.; Zajic, Brittany; Rousseau, Nick; Rodell, Matthew; Hinkley, Everett

    2018-01-01

    It is generally accepted that year-to-year variability in moisture conditions and drought are linked with increased wildfire occurrence. However, quantifying the sensitivity of wildfire to surface moisture state at seasonal lead-times has been challenging due to the absence of a long soil moisture record with the appropriate coverage and spatial resolution for continental-scale analysis. Here we apply model simulations of surface soil moisture that numerically assimilate observations from NASA’s Gravity Recovery and Climate Experiment (GRACE) mission with the USDA Forest Service’s historical Fire-Occurrence Database over the contiguous United States. We quantify the relationships between pre-fire-season soil moisture and subsequent-year wildfire occurrence by land-cover type and produce annual probable wildfire occurrence and burned area maps at 0.25 degree resolution. Cross-validated results generally indicate a higher occurrence of smaller fires when months preceding fire season are wet, while larger fires are more frequent when soils are dry. This is consistent with the concept of increased fuel accumulation under wet conditions in the pre-season. These results demonstrate the fundamental strength of the relationship between soil moisture and fire activity at long lead-times and are indicative of that relationship’s utility for the future development of national-scale predictive capability.

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

    Science.gov (United States)

    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

  12. SMOS/SMAP Synergy for SMAP Level 2 Soil Moisture Algorithm Evaluation

    Science.gov (United States)

    Bindlish, Rajat; Jackson, Thomas J.; Zhao, Tianjie; Cosh, Michael; Chan, Steven; O'Neill, Peggy; Njoku, Eni; Colliander, Andreas; Kerr, Yann

    2011-01-01

    Soil Moisture Active Passive (SMAP) satellite has been proposed to provide global measurements of soil moisture and land freeze/thaw state at 10 km and 3 km resolutions, respectively. SMAP would also provide a radiometer-only soil moisture product at 40-km spatial resolution. This product and the supporting brightness temperature observations are common to both SMAP and European Space Agency's Soil Moisture and Ocean Salinity (SMOS) mission. As a result, there are opportunities for synergies between the two missions. These include exploiting the data for calibration and validation and establishing longer term L-band brightness temperature and derived soil moisture products. In this investigation we will be using SMOS brightness temperature, ancillary data, and soil moisture products to develop and evaluate a candidate SMAP L2 passive soil moisture retrieval algorithm. This work will begin with evaluations based on the SMOS product grids and ancillary data sets and transition to those that will be used by SMAP. An important step in this analysis is reprocessing the multiple incidence angle observations provided by SMOS to a global brightness temperature product that simulates the constant 40 degree incidence angle observations that SMAP will provide. The reprocessed brightness temperature data provide a basis for evaluating different SMAP algorithm alternatives. Several algorithms are being considered for the SMAP radiometer-only soil moisture retrieval. In this first phase, we utilized only the Single Channel Algorithm (SCA), which is based on the radiative transfer equation and uses the channel that is most sensitive to soil moisture (H-pol). Brightness temperature is corrected sequentially for the effects of temperature, vegetation, roughness (dynamic ancillary data sets) and soil texture (static ancillary data set). European Centre for Medium-Range Weather Forecasts (ECMWF) estimates of soil temperature for the top layer (as provided as part of the SMOS

  13. Volatilization of EPTC as affected by soil moisture

    Science.gov (United States)

    Fu, Liqun

    Volatilization is an important process that controls the dissipation of pesticides after field application. Soil moisture plays an important role in controlling the volatilization of pesticides. However, the extent of this role is unclear. This study was conducted to determine how soil moisture affects the sorption capacity and vapor loss of EPTC (S-ethyl dipropyl carbamothioate) from two soils, Weswood clay loam (fine- silty, mixed, thermic fluventic ustochrepts) and Padina loamy sand (loamy, siliceous, thermic grossarenic paleustalfs). Soil samples with different moisture contents were exposed to saturated EPTC vapor for 1, 2, 5, or 12 days and sorbed concentrations were measured. Sorption capacity of Weswood after 12 days exposure was about 12 times higher with air-dry soil than at the wilting point (-1500 kPa). For Padina, after 12 days exposure, the sorption capacity was about 18 times higher at air- dry than at -1500 kPa. The maximum sorption extrapolated from the partitioning coefficients determined with an equilibrium batch system and Henry's law were similar to the sorption capacities when moisture content was close to the wilting point for both soils. Desorption of EPTC vapor from soils with different moistures was determined by a purge and trap method. EPTC vapor losses strongly depended on the soil moisture and/or the humidity of the air. If the air was dry, volatilization of EPTC was much larger when the soil was wet. If humidity of the air was high, the effect of soil moisture on volatilization was not as great. No significant correlation at a confidence level of 95% was found between water and EPTC vapor losses for either soil when water saturated air was used as a purge gas. When purged with dry air, losses of water and EPTC vapor were strongly correlated at a confidence level of 99%. This study indicates that decreasing soil moisture significantly increases EPTC sorption and decreases volatilization. Simulation of volatilization with a one

  14. Potential of ASCAT Soil Moisture Product to Improve Runoff Prediction

    Science.gov (United States)

    Brocca, L.; Melone, F.; Moramarco, T.; Wagner, W.; Naeimi, V.; Bartalis, Z.; Hasenauer, S.

    2009-11-01

    The role and the importance of soil moisture for meteorological, agricultural and hydrological applications is widely known. Remote sensing offers the unique capability to monitor soil moisture over large areas (catchment scale) with, nowadays, a temporal resolution suitable for hydrological purposes. However, the accuracy of the remotely sensed soil moisture estimates have to be carefully checked. Therefore, the assessment of the effects of assimilating satellite- derived soil moisture estimates into rainfall-runoff models at different scales and over different regions represents an important scientific and operational issue. In this context, the soil wetness index (SWI) product derived from the Advanced Scatterometer (ASCAT) sensor was tested in this study. The SWI was firstly compared with the soil moisture temporal pattern derived from a continuous rainfall-runoff model (MISDc). Then, by using a simple data assimilation technique, the SWI was assimilated into MISDc and the model performance on flood estimation was analyzed. Moreover, three synthetic experiments considering errors on rainfall, model parameters and initial soil wetness conditions were carried out. These experiments allowed to further investigate the SWI potential when uncertain conditions take place.The most significant flood events, which occurred in the period 2000-2009 for five subcatchments of the Upper Tiber River in central Italy, ranging in extension between 100 and 650 km2, were used as case studies. Results reveal that the SWI derived from the ASCAT sensor can be conveniently used to improve runoff prediction in the study area, mainly if the initial soil wetness conditions are unknown.

  15. Aspect-related Vegetation Differences Amplify Soil Moisture Variability in Semiarid Landscapes

    Science.gov (United States)

    Yetemen, O.; Srivastava, A.; Kumari, N.; Saco, P. M.

    2017-12-01

    Soil moisture variability (SMV) in semiarid landscapes is affected by vegetation, soil 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.), soil 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 soil moisture and vegetation cover are computed to estimate the corresponding coefficients of variation. Under the uniform spatial precipitation forcing and uniform soil properties, the factors affecting 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 affect the available soil moisture content. Interestingly, changes in soil 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

  16. Soil Moisture Content in Hill-Filed Side Slope

    OpenAIRE

    A. Aboufayed

    2013-01-01

    The soil moisture content is an important property of the soil. The results of mean weekly gravimetric soil moisture content, measured for the three soil layers within the A horizon, showed that it was higher for the top 5 cm over the whole period of monitoring (15/7/2004 up to 10/11/05) with the variation becoming greater during winter time. This reflects the pattern of rainfall in Ireland which is spread over the whole year and shows that light rainfall events during su...

  17. THE CLAY CONTENT EFFECT ON THE FORMATION OF SHALLOW MOLE DRAINAGE AND THE RATE OF LOWERING SOIL MOISTURE CONTENT

    Directory of Open Access Journals (Sweden)

    Siti Suharyatun

    2014-10-01

    loam soil did not infl uence the rate of lowering soil moisture content. Contrary, the mole drainage installed in clay soil has effected to increase the rate of lowering soil moisture content. Keywords: Mole drainage, soil moisture content, clay content

  18. Quality Assessment of the CCI ECV Soil Moisture Product Using ENVISAT ASAR Wide Swath Data over Spain, Ireland and Finland

    Directory of Open Access Journals (Sweden)

    Chiara Pratola

    2015-11-01

    Full Text Available During the last decade, great progress has been made by the scientific community in generating satellite-derived global surface soil moisture products, as a valuable source of information to be used in a variety of applications, such as hydrology, meteorology and climatic modeling. Through the European Space Agency Climate Change Initiative (ESA CCI, the most complete and consistent global soil moisture (SM data record based on active and passive microwaves sensors is being developed. However, the coarse spatial resolution characterizing such data may be not sufficient to accurately represent the moisture conditions. The objective of this work is to assess the quality of the CCI Essential Climate Variable (ECV SM product by using finer spatial resolution Advanced Synthetic Aperture Radar (ASAR Wide Swath and in situ soil moisture data taken over three regions in Europe. Ireland, Spain, and Finland have been selected with the aim of assessing the spatial and temporal representativeness of the ECV SM product over areas that differ in climate, topography, land cover and soil type. This approach facilitated an understanding of the extent to which geophysical factors, such as soil texture, terrain composition and altitude, affect the retrieved ECV SM product values. A good temporal and spatial agreement has been observed between the three soil moisture datasets for the Irish and Spanish sites, while poorer results have been found at the Finnish sites. Overall, the two different satellite derived products capture the soil moisture temporal variations well and are in good agreement with each other.

  19. Evaluation of uncertainty in field soil moisture estimations by cosmic-ray neutron sensing

    Science.gov (United States)

    Scheiffele, Lena Maria; Baroni, Gabriele; Schrön, Martin; Ingwersen, Joachim; Oswald, Sascha E.

    2017-04-01

    Cosmic-ray neutron sensing (CRNS) has developed into a valuable, indirect and non-invasive method to estimate soil moisture at the field scale. It provides continuous temporal data (hours to days), relatively large depth (10-70 cm), and intermediate spatial scale measurements (hundreds of meters), thereby overcoming some of the limitations in point measurements (e.g., TDR/FDR) and of remote sensing products. All these characteristics make CRNS a favorable approach for soil moisture estimation, especially for applications in cropped fields and agricultural water management. Various studies compare CRNS measurements to soil sensor networks and show a good agreement. However, CRNS is sensitive to more characteristics of the land-surface, e.g. additional hydrogen pools, soil bulk density, and biomass. Prior to calibration the standard atmospheric corrections are accounting for the effects of air pressure, humidity and variations in incoming neutrons. In addition, the standard calibration approach was further extended to account for hydrogen in lattice water and soil organic material. Some corrections were also proposed to account for water in biomass. Moreover, the sensitivity of the probe was found to decrease with distance and a weighting procedure for the calibration datasets was introduced to account for the sensors' radial sensitivity. On the one hand, all the mentioned corrections showed to improve the accuracy in estimated soil moisture values. On the other hand, they require substantial additional efforts in monitoring activities and they could inherently contribute to the overall uncertainty of the CRNS product. In this study we aim (i) to quantify the uncertainty in the field soil moisture estimated by CRNS and (ii) to understand the role of the different sources of uncertainty. To this end, two experimental sites in Germany were equipped with a CRNS probe and compared to values of a soil moisture network. The agricultural fields were cropped with winter

  20. Assessing Landscape-Scale Soil Moisture Distribution Using Auxiliary Sensing Technologies and Multivariate Geostatistics

    Science.gov (United States)

    Landrum, C.; Castrignanò, A.; Mueller, T.; Zourarakis, D.; Zhu, J.

    2013-12-01

    It is important to assess soil moisture to develop strategies to better manage its availability and use. At the landscape scale, soil moisture distribution derives from an integration of hydrologic, pedologic and geomorphic processes that cause soil moisture variability (SMV) to be time, space, and scale-dependent. Traditional methods to assess SMV at this scale are often costly, labor intensive, and invasive, which can lead to inadequate sampling density and spatial coverage. Fusing traditional sampling techniques with georeferenced auxiliary sensing technologies, such as geoelectric sensing and LiDAR, provide an alternative approach. Because geoelectric and LiDAR measurements are sensitive to soil properties and terrain features that affect soil moisture variation, they are often employed as auxiliary measures to support less dense direct sampling. Georeferenced proximal sensing acquires rapid, real-time, high resolution data over large spatial extents that is enriched with spatial, temporal and scale-dependent information. Data fusion becomes important when proximal sensing is used in tandem with more sparse direct sampling. Multicollocated factorial cokriging (MFC) is one technique of multivariate geostatistics to fuse multiple data sources collected at different sampling scales to study the spatial characteristics of environmental properties. With MFC sparse soil observations are supported by more densely sampled auxiliary attributes to produce more consistent spatial descriptions of scale-dependent parameters affecting SMV. This study uses high resolution geoelectric and LiDAR data as auxiliary measures to support direct soil sampling (n=127) over a 40 hectare Central Kentucky (USA) landscape. Shallow and deep apparent electrical resistivity (ERa) were measured using a Veris 3100 in tandem with soil moisture sampling on three separate dates with ascending soil moisture contents ranging from plant wilting point to field capacity. Terrain features were produced

  1. MAPSM: A Spatio-Temporal Algorithm for Merging Soil Moisture from Active and Passive Microwave Remote Sensing

    Directory of Open Access Journals (Sweden)

    Sat Kumar Tomer

    2016-12-01

    Full Text Available Availability of soil moisture observations at a high spatial and temporal resolution is a prerequisite for various hydrological, agricultural and meteorological applications. In the current study, a novel algorithm for merging soil moisture from active microwave (SAR and passive microwave is presented. The MAPSM algorithm—Merge Active and Passive microwave Soil Moisture—uses a spatio-temporal approach based on the concept of the Water Change Capacity (WCC which represents the amplitude and direction of change in the soil moisture at the fine spatial resolution. The algorithm is applied and validated during a period of 3 years spanning from 2010 to 2013 over the Berambadi watershed which is located in a semi-arid tropical region in the Karnataka state of south India. Passive microwave products are provided from ESA Level 2 soil moisture products derived from Soil Moisture and Ocean Salinity (SMOS satellite (3 days temporal resolution and 40 km nominal spatial resolution. Active microwave are based on soil moisture retrievals from 30 images of RADARSAT-2 data (24 days temporal resolution and 20 m spatial resolution. The results show that MAPSM is able to provide a good estimate of soil moisture at a spatial resolution of 500 m with an RMSE of 0.025 m3/m3 and 0.069 m3/m3 when comparing it to soil moisture from RADARSAT-2 and in-situ measurements, respectively. The use of Sentinel-1 and RISAT products in MAPSM algorithm is envisioned over other areas where high number of revisits is available. This will need an update of the algorithm to take into account the angle sampling and resolution of Sentinel-1 and RISAT data.

  2. The effect of surface sealing on soil moisture dynamics in a semiarid hillslope

    Science.gov (United States)

    Sela, S.; Svoray, T.; Assouline, S.

    2010-12-01

    Understanding the mechanisms underlying hillslope soil moisture dynamics and vegetation patchiness remains a current challenge in hydrology, especially in ungauged watersheds. In dry areas, these mechanisms include the formation of surface seals, that although directly affects infiltration and evaporation fluxes, researchers usually disregard its development when predicting soil moisture patterns. The role of these seals in shaping spatial and temporal patterns of soil moisture, considered as the primary limiting factor for dry area plant distribution, is still an open research gap. At the LTER Lehavim site, in the center of Israel (31020' N, 34045' E), a typical hillslope (0.115 Km2) was chosen offering different aspects and a classic geomorphologic banding. Annual rainfall is 290 mm, the soils are brown lithosols and arid brown loess and the dominant rock formations are Eocenean limestone and chalk with patches of calcrete. The vegetation is characterised by scattered dwarf shrubs (dominant species Sarcopoterium spinosum) and patches of herbaceous vegetation, mostly annuals, are spread between rocks and dwarf shrubs. An extensive spatial database of soil hydraulic and environmental parameters (e.g. slope, radiation, bulk density) was measured in the field and was interpolated to continuous maps using geostatistical techniques and physically-based models. To explore the effect of soil surface sealing, the Mualem and Assouline (1989) equations, describing the change in hydraulic parameters resulting from soil seal formation, were applied explicitly in space to the entire hillslope. Two simple indices were developed to describe local evaporation rates and the contribution of water from rock outcrops to the downslope soil patches. This spatio-temporal database was used to characterise 1187 cells serving as an input to a numeric model (Hydrus 1D) solving the flow equations to predict soil water content at the single storm and the seasonal scales. Predictions were

  3. Estimating Surface Soil Moisture in a Mixed-Landscape using SMAP and MODIS/VIIRS Data

    Science.gov (United States)

    Tang, J.; Di, L.; Xiao, J.

    2017-12-01

    Soil moisture, a critical parameter of earth ecosystem linking land surface and atmosphere, has been widely applied in many application (Di, 1991; Njoku et al. 2003; Western 2002; Zhao et al. 2014; McColl et al. 2017) from regional to continental or even global scale. The advent of satellite-based remote sensing, particular in the last two decades, has proven successful for mapping the surface soil moisture (SSM) from space (Petropoulos et al. 2015; Kim et al. 2015; Molero et al. 2016). The current soil moisture products, however, is not able to fully characterize the spatial and temporal variability of soil moisture at mixed landscape types (Albergel et al. 2013; Zeng et al. 2015). In this research, we derived the SSM at 1-km spatial resolution by using sensor observation and high-level products from SMAP and MODIS/VIIRS as well as metrorological, landcover, and soil data. Specifically, we proposed a practicable method to produce the originally planned SMAP L3_SM_A with comparable quality by downscaling the SMAP L3_SM_P product through a proved method, the geographically weighted regression method at mixed landscape in southern New Hampshire. This estimated SSM was validated using the Soil Climate Analysis Network (SCAN) from Natural Resources Conservation Service (NRCS) of United States Department of Agriculture (USDA).

  4. Evaluating the Potential Use of Remotely-Sensed and Model-Simulated Soil Moisture for Agricultural Drought Risk Monitoring

    Science.gov (United States)

    Yan, Hongxiang; Moradkhani, Hamid

    2016-04-01

    Current two datasets provide spatial and temporal resolution of soil moisture at large-scale: the remotely-sensed soil moisture retrievals and the model-simulated soil moisture products. Drought monitoring using remotely-sensed soil moisture is emerging, and the soil moisture simulated using land surface models (LSMs) have been used operationally to monitor agriculture drought in United States. Although these two datasets yield important drought information, their drought monitoring skill still needs further quantification. This study provides a comprehensive assessment of the potential of remotely-sensed and model-simulated soil moisture data in monitoring agricultural drought over the Columbia River Basin (CRB), Pacific Northwest. Two satellite soil moisture datasets were evaluated, the LPRM-AMSR-E (unscaled, 2002-2011) and ESA-CCI (scaled, 1979-2013). The USGS Precipitation Runoff Modeling System (PRMS) is used to simulate the soil moisture from 1979-2011. The drought monitoring skill is quantified with two indices: drought area coverage (the ability of drought detection) and drought severity (according to USDM categories). The effects of satellite sensors (active, passive), multi-satellite combined, length of climatology, climate change effect, and statistical methods are also examined in this study.

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

    Science.gov (United States)

    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.

  6. Analyzing and Visualizing Precipitation and Soil Moisture in ArcGIS

    Science.gov (United States)

    Yang, Wenli; Pham, Long; Zhao, Peisheng; Kempler, Steve; Wei, Jennifer

    2016-01-01

    Precipitation and soil moisture are among the most important parameters in many land GIS (Geographic Information System) research and applications. These data are available globally from NASA GES DISC (Goddard Earth Science Data and Information Services Center) in GIS-ready format at 10-kilometer spatial resolution and 24-hour or less temporal resolutions. In this presentation, well demonstrate how rainfall and soil moisture data are used in ArcGIS to analyze and visualize spatiotemporal patterns of droughts and their impacts on natural vegetation and agriculture in different parts of the world.

  7. Four Decades of Microwave Satellite Soil Moisture Observations: Product validation and inter-satellite comparisons

    Science.gov (United States)

    Lanka, K.; Pan, M.; Wanders, N.; Kumar, D. N.; Wood, E. F.

    2017-12-01

    The satellite based passive and active microwave sensors enhanced our ability to retrieve soil moisture at global scales. It has been almost four decades since the first passive microwave satellite sensor was launched in 1978. Since then soil moisture has gained considerable attention in hydro-meteorological, climate, and agricultural research resulting in the deployment of two dedicated missions in the last decade, SMOS and SMAP. Signifying the four decades of microwave remote sensing of soil moisture, this work aims to present an overview of how our knowledge in this field has improved in terms of the design of sensors and their accuracy of retrieving soil moisture. We considered daily coverage, temporal performance, and spatial performance to assess the accuracy of products corresponding to eight passive sensors (SMMR, SSM/I, TMI, AMSR-E, WindSAT, AMSR2, SMOS and SMAP), two active sensors (ERS-Scatterometer, MetOp-ASCAT), and one active/passive merged soil moisture product (ESA-CCI combined product), using 1058 ISMN in-situ stations and the VIC LSM soil moisture simulations (VICSM) over the CONUS. Our analysis indicated that the daily coverage has increased from 30 % during 1980s to 85 % (during non-winter months) with the launch of dedicated soil moisture missions SMOS and SMAP. The temporal validation of passive and active soil moisture products with the ISMN data place the range of median RMSE as 0.06-0.10 m3/m3 and median correlation as 0.20-0.68. When TMI, AMSR-E and WindSAT are evaluated, the AMSR-E sensor is found to have produced the brightness temperatures with better quality, given that these sensors are paired with same retrieval algorithm (LPRM). The ASCAT product shows a significant improvement during the temporal validation of retrievals compared to its predecessor ERS, thanks to enhanced sensor configuration. The SMAP mission, through its improved sensor design and RFI handling, shows a high retrieval accuracy under all-topography conditions

  8. Improving Soil Moisture Estimation through the Joint Assimilation of SMOS and GRACE Satellite Observations

    Science.gov (United States)

    Girotto, Manuela

    2018-01-01

    Observations from recent soil moisture 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) soil moisture profile estimates from microwave brightness temperature observations. These missions are only sensitive to near-surface soil moisture 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 affects (in absolute terms) deeper moisture 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 soil moisture (i.e., surface and deeper water storages).

  9. Improving runoff prediction through the assimilation of the ASCAT soil moisture product

    Science.gov (United States)

    Brocca, L.; Melone, F.; Moramarco, T.; Wagner, W.; Naeimi, V.; Bartalis, Z.; Hasenauer, S.

    2010-10-01

    The role and the importance of soil moisture for meteorological, agricultural and hydrological applications is widely known. Remote sensing offers the unique capability to monitor soil moisture over large areas (catchment scale) with, nowadays, a temporal resolution suitable for hydrological purposes. However, the accuracy of the remotely sensed soil moisture estimates has to be carefully checked. The validation of these estimates with in-situ measurements is not straightforward due the well-known problems related to the spatial mismatch and the measurement accuracy. The analysis of the effects deriving from assimilating remotely sensed soil moisture data into hydrological or meteorological models could represent a more valuable method to test their reliability. In particular, the assimilation of satellite-derived soil moisture estimates into rainfall-runoff models at different scales and over different regions represents an important scientific and operational issue. In this study, the soil wetness index (SWI) product derived from the Advanced SCATterometer (ASCAT) sensor onboard of the Metop satellite was tested. The SWI was firstly compared with the soil moisture temporal pattern derived from a continuous rainfall-runoff model (MISDc) to assess its relationship with modeled data. Then, by using a simple data assimilation technique, the linearly rescaled SWI that matches the range of variability of modelled data (denoted as SWI*) was assimilated into MISDc and the model performance on flood estimation was analyzed. Moreover, three synthetic experiments considering errors on rainfall, model parameters and initial soil wetness conditions were carried out. These experiments allowed to further investigate the SWI potential when uncertain conditions take place. The most significant flood events, which occurred in the period 2000-2009 on five subcatchments of the Upper Tiber River in central Italy, ranging in extension between 100 and 650 km2, were used as case studies

  10. Validation of remotely-sensed soil moisture in the absence of in situ soil moisture: the case of the Yankin Basin, a tributary of the Niger River basin

    CSIR Research Space (South Africa)

    Badou, DF

    2017-10-01

    Full Text Available Soil moisture is known to be important in hydrology, agronomy, floods and drought forecasting. Acquisition of in situ soil moisture data is time consuming, costly, and does not cover the scale required for basin analysis. The consideration...

  11. Mapping Surface Heat Fluxes by Assimilating SMAP Soil Moisture and GOES Land Surface Temperature Data

    Science.gov (United States)

    Lu, Yang; Steele-Dunne, Susan C.; Farhadi, Leila; van de Giesen, Nick

    2017-12-01

    Surface heat fluxes play a crucial role in the surface energy and water balance. In situ measurements are costly and difficult, and large-scale flux mapping is hindered by surface heterogeneity. Previous studies have demonstrated that surface heat fluxes can be estimated by assimilating land surface temperature (LST) and soil moisture to determine two key parameters: a neutral bulk heat transfer coefficient (CHN) and an evaporative fraction (EF). Here a methodology is proposed to estimate surface heat fluxes by assimilating Soil Moisture Active Passive (SMAP) soil moisture data and Geostationary Operational Environmental Satellite (GOES) LST data into a dual-source (DS) model using a hybrid particle assimilation strategy. SMAP soil moisture data are assimilated using a particle filter (PF), and GOES LST data are assimilated using an adaptive particle batch smoother (APBS) to account for the large gap in the spatial and temporal resolution. The methodology is implemented in an area in the U.S. Southern Great Plains. Assessment against in situ observations suggests that soil moisture and LST estimates are in better agreement with observations after assimilation. The RMSD for 30 min (daytime) flux estimates is reduced by 6.3% (8.7%) and 31.6% (37%) for H and LE on average. Comparison against a LST-only and a soil moisture-only assimilation case suggests that despite the coarse resolution, assimilating SMAP soil moisture data is not only beneficial but also crucial for successful and robust flux estimation, particularly when the uncertainties in the model estimates are large.

  12. Assimilation of SMOS Brightness Temperatures or Soil Moisture Retrievals into a Land Surface Model

    Science.gov (United States)

    De Lannoy, Gabrielle J. M.; Reichle, Rolf H.

    2016-01-01

    Three different data products from the Soil Moisture Ocean Salinity (SMOS) mission are assimilated separately into the Goddard Earth Observing System Model, version 5 (GEOS-5) to improve estimates of surface and root-zone soil moisture. The first product consists of multi-angle, dual-polarization brightness temperature (Tb) observations at the bottom of the atmosphere extracted from Level 1 data. The second product is a derived SMOS Tb product that mimics the data at a 40 degree incidence angle from the Soil Moisture Active Passive (SMAP) mission. The third product is the operational SMOS Level 2 surface soil moisture (SM) retrieval product. The assimilation system uses a spatially distributed ensemble Kalman filter (EnKF) with seasonally varying climatological bias mitigation for Tb assimilation, whereas a time-invariant cumulative density function matching is used for SM retrieval assimilation. All assimilation experiments improve the soil moisture estimates compared to model-only simulations in terms of unbiased root-mean-square differences and anomaly correlations during the period from 1 July 2010 to 1 May 2015 and for 187 sites across the US. Especially in areas where the satellite data are most sensitive to surface soil moisture, large skill improvements (e.g., an increase in the anomaly correlation by 0.1) are found in the surface soil moisture. The domain-average surface and root-zone skill metrics are similar among the various assimilation experiments, but large differences in skill are found locally. The observation-minus-forecast residuals and analysis increments reveal large differences in how the observations add value in the Tb and SM retrieval assimilation systems. The distinct patterns of these diagnostics in the two systems reflect observation and model errors patterns that are not well captured in the assigned EnKF error parameters. Consequently, a localized optimization of the EnKF error parameters is needed to further improve Tb or SM retrieval

  13. Investigation of (de)coupling between surface and subsurface soil moisture using a Distributed Lag Non-linear Model (DNLM)

    Science.gov (United States)

    Carranza, Coleen; van der Ploeg, Martine

    2017-04-01

    Accurate estimates of water content in the soil profile are essential for environmental and climate modeling studies. Current trends for estimating profile soil moisture incorporate remote sensing methods for mapping soil moisture at greater spatial coverage but is limited to the upper soil layers (e.g. 5cm for radar satellites). Data assimilation methods offer promising computational techniques to translate mapped surface soil moisture to estimates of profile soil moisture, in conjunction with physical models. However, a variety of factors, such as differences in the drying rates, can lead to "decoupling" (Capehart and Carlson, 1997) of surface and subsurface soil moisture. In other words, surface soil moisture conditions no longer reflect or represent subsurface conditions. In this study, we investigated the relation and observed decoupling between surface and subsurface soil moisture from 15-minute interval time series datasets in four selected Dutch agricultural fields (SM_05, SM_09, SM_13, SM_20) from the soil moisture network in Twente region. The idea is that surface soil moisture conditions will be reflected in the subsurface after a certain time lag because of its movement or flow from the surface. These lagged associations were analysed using distributed lag non-linear model (DLNM). This statistical technique provides a framework to simultaneously represent non-linear exposure-response dependencies and delayed effects. DNLM was applied to elucidate which surface soil moisture conditions resulted in a high association to subsurface values, indicating good correlation between the two zones. For example, initial results for this ongoing study from SM_13 show an overall low but increasing association from dry to intermediate soil moisture values (0 to 25%). At this range of values, we say that the two zones are decoupled. Above these values towards near saturated conditions ( 40%), associations between the two zones remain high. For predictor

  14. Influence of Soil Moisture on Soil Gas Vapor Concentration for Vapor Intrusion.

    Science.gov (United States)

    Shen, Rui; Pennell, Kelly G; Suuberg, Eric M

    2013-10-01

    Mathematical models have been widely used in analyzing the effects of various environmental factors in the vapor intrusion process. Soil moisture content is one of the key factors determining the subsurface vapor concentration profile. This manuscript considers the effects of soil moisture profiles on the soil gas vapor concentration away from any surface capping by buildings or pavement. The "open field" soil gas vapor concentration profile is observed to be sensitive to the soil moisture distribution. The van Genuchten relations can be used for describing the soil moisture retention curve, and give results consistent with the results from a previous experimental study. Other modeling methods that account for soil moisture are evaluated. These modeling results are also compared with the measured subsurface concentration profiles in the U.S. EPA vapor intrusion database.

  15. The moisture response of soil heterotrophic respiration: interaction with soil properties

    DEFF Research Database (Denmark)

    Moyano, F E; Vasilyeva, N; Bouckaert, L

    2012-01-01

    -driven analysis of soil moisture-respiration relations based on 90 soils. With the use of linear models we show how the relationship between soil heterotrophic respiration and different measures of soil moisture is consistently affected by soil properties. The empirical models derived include main effects......Soil moisture is of primary importance for predicting the evolution of soil carbon stocks and fluxes, both because it strongly controls organic matter decomposition and because it is predicted to change at global scales in the following decades. However, the soil functions used to model...... the heterotrophic respiration response to moisture have limited empirical support and introduce an uncertainty of at least 4% in global soil carbon stock predictions by 2100. The necessity of improving the representation of this relationship in models has been highlighted in recent studies. Here we present a data...

  16. Assessment of the SMAP Passive Soil Moisture Product

    Science.gov (United States)

    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.

  17. Advances, experiences, and prospects of the International Soil Moisture Network

    Science.gov (United States)

    Dorigo, W.; van Oevelen, P. J.; Drusch, M.; Wagner, W.; Scipal, K.; Mecklenburg, S.

    2012-12-01

    In 2009, the International Soil Moisture Network (ISMN; http:www.ipf.tuwien.ac.at) was initiated as a platform to support calibration and validation of soil moisture products from remote sensing and land surface models, and to advance studies on the behavior of soil moisture over space and time. This international initiative is fruit of continuing coordinative efforts of the Global Energy and Water Cycle Experiment (GEWEX) in cooperation with the Group of Earth Observation (GEO) and the Committee on Earth Observation Satellites (CEOS). The decisive financial incentive was given by the European Space Agency (ESA) who considered the establishment of the network critical for optimizing the soil moisture products from the Soil Moisture and Ocean Salinity (SMOS) mission. The ISMN collects and harmonizes ground-based soil moisture data sets from a large variety of individually operating networks and makes them available through a centralized data portal. Meanwhile, almost 6000 soil moisture data sets from over 1300 sites, distributed among 34 networks worldwide, are contained in the database. The steadily increasing number of organizations voluntarily contributing to the ISMN, and the rapidly increasing number of studies based on the network show that the portal has been successful in reaching its primary goal to promote easy data accessibility to a wide variety of users. Recently, several updates of the system were performed to keep up with the increasing data amount and traffic, and to meet the requirements of many advanced users. Many datasets from operational networks (e.g., SCAN, the US Climate Reference Network, COSMOS, and ARM) are now assimilated and processed in the ISMN on a fully automated basis in near-real time. In addition, a new enhanced quality control system is currently being implemented. This presentation gives an overview of these recent developments, presents some examples of important scientific results based on the ISMN, and sketches an outlook for

  18. Effect of soil moisture on trace elements concentrations using

    African Journals Online (AJOL)

    H. Sahraoui and M. Hachicha

    2017-01-01

    Jan 1, 2017 ... ABSTRACT. Portable X-ray fluorescence (PXRF) technology can offer rapid and cost-effective determination of the trace elements concentrations in soils. The aim of this study was to assess the influence of soil moisture content under different condition on PXRF measurement quality. For this purpose ...

  19. The Raam regional soil moisture monitoring network in the Netherlands

    NARCIS (Netherlands)

    Benninga, H.F.; Carranza, C.D.U.; Pezij, M.; Santen, van Pim; Ploeg, van der M.J.; Augustijn, Denie C.M.; Velde, van der Rogier

    2018-01-01

    We have established a soil moisture 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 soil water

  20. Variability of soil moisture and its relationship with surface albedo ...

    Indian Academy of Sciences (India)

    Home; Journals; Journal of Earth System Science; Volume 119; Issue 4. Variability of soil moisture and its relationship with surface albedo and soil thermal ... The diurnal variation of surface albedo appears as a U-shaped curve on sunny days. Surface albedo decreases with the increase of solar elevation angle, and it tends ...

  1. Short-term precipitation exclusion alters microbial responses to soil moisture in a wet tropical forest.

    Science.gov (United States)

    Waring, Bonnie G; Hawkes, Christine V

    2015-05-01

    Many wet tropical forests, which contain a quarter of global terrestrial biomass carbon stocks, will experience changes in precipitation regime over the next century. Soil 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 affected soil 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 moisture treatments by exposing soils to a controlled soil moisture 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 soil moisture. Communities with prior drought exposure exhibited higher respiration rates per unit microbial biomass under all conditions and respired significantly more CO2 than control soils at low soil moisture. 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.

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

    Science.gov (United States)

    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.

  3. Microwave radiometric measurements of soil moisture in Italy

    Directory of Open Access Journals (Sweden)

    G. Macelloni

    2003-01-01

    Full Text Available Within the framework of the MAP and RAPHAEL projects, airborne experimental campaigns were carried out by the IFAC group in 1999 and 2000, using a multifrequency microwave radiometer at L, C and X bands (1.4, 6.8 and 10 GHz. The aim of the experiments was to collect soil moisture and vegetation biomass information on agricultural areas to give reliable inputs to the hydrological models. It is well known that microwave emission from soil, mainly at L-band (1.4 GHz, is very well correlated to its moisture content. Two experimental areas in Italy were selected for this project: one was the Toce Valley, Domodossola, in 1999, and the other, the agricultural area of Cerbaia, close to Florence, where flights were performed in 2000. Measurements were carried out on bare soils, corn and wheat fields in different growth stages and on meadows. Ground data of soil moisture (SMC were collected by other research teams involved in the experiments. From the analysis of the data sets, it has been confirmed that L-band is well related to the SMC of a rather deep soil layer, whereas C-band is sensitive to the surface SMC and is more affected by the presence of surface roughness and vegetation, especially at high incidence angles. An algorithm for the retrieval of soil moisture, based on the sensitivity to moisture of the brightness temperature at C-band, has been tested using the collected data set. The results of the algorithm, which is able to correct for the effect of vegetation by means of the polarisation index at X-band, have been compared with soil moisture data measured on the ground. Finally, the sensitivity of emission at different frequencies to the soil moisture profile was investigated. Experimental data sets were interpreted by using the Integral Equation Model (IEM and the outputs of the model were used to train an artificial neural network to reproduce the soil moisture content at different depths. Keywords: microwave radiometry, soil moisture

  4. Using Plant Temperature to Evaluate the Response of Stomatal Conductance to Soil Moisture Deficit

    Directory of Open Access Journals (Sweden)

    Ming-Han Yu

    2015-10-01

    Full Text Available Plant temperature is an indicator of stomatal conductance, which reflects soil moisture stresses. We explored the relationship between plant temperature and soil moisture to optimize irrigation schedules in a water-stress experiment using Firmiana platanifolia (L. f. Marsili in an incubator. Canopy temperature, leaf temperature, and stomatal conductance were measured using thermal imaging and a porometer. The results indicated that (1 stomatal conductance decreased with declines in soil moisture, and reflected average canopy temperature; (2 the variation of the leaf temperature distribution was a reliable indicator of soil moisture stress, and the temperature distribution in severely water-stressed leaves exhibited greater spatial variation than that in the presence of sufficient irrigation; (3 thermal indices (Ig and crop water stress index (CWSI were theoretically proportional to stomatal conductance (gs, Ig was certified to have linearity relationship with gs and CWSI have a logarithmic relationship with gs, and both of the two indices can be used to estimate soil moisture; and (4 thermal imaging data can reflect water status irrespective of long-term water scarcity or lack of sudden rainfall. This study applied thermal imaging methods to monitor plants and develop adaptable irrigation scheduling, which are important for the formulation of effective and economical agriculture and forestry policy.

  5. Clustering of soil moisture time series pattern for selecting representative point on mountainous hillslopes in South Korea

    Science.gov (United States)

    Lee, E.; Cho, M.; Kim, S.

    2016-12-01

    A method was proposed to find the representative soil moisture measurement points for a steep hillslope located on northeastern part of South Korea. We had analyzed time series data of soil moisture for 49 points between May and November 2013 in the study area to characterize temporal and spatial variation pattern characteristics. The factor analysis showed monthly characteristics of Index of temporal stability (ITS) which can be classified into 3 distinct characteristics. Dendrogram was useful to characterize spatial and topographic patterns of soil moisture. The performance of the proposed method was compared with existing ITS approach in terms of the coefficient of determination showing better representing potential for soil moisture measurements. The results of this pattern approach can be used to interpolate the missing data with high accuracy which was made it possible through addressing characteristics of topography and rainfall events depending on seasonal classification.

  6. Soil moisture assessed by digital mapping techniques and its field validation

    Directory of Open Access Journals (Sweden)

    Bruno Montoani Silva

    2014-04-01

    Full Text Available Digital techniques and tools can assist not only in the prediction of soil properties, such as soil moisture, but also in planning the use and management of areas for agriculture and, or, environmental purposes. In this sense, this work aimed to study wetness indexes methods, defining the spatial resolution and selecting the estimation method that best correlates with water content data measured in the field, evaluating even moisture at different soil depths and seasons. This study was developed in a landscape with strongly undulated relief and covered with Nitosols at the summit and upper middle third, and Argisols at the low middle third, ranging in altitude from 845 to 890 m, located in the southern state of Minas Gerais, Brazil. It were performed analyses of Pearson linear correlation between soil moisture determined in the field, at depths of 10, 20, 30, 40, 60 and 100 cm and the water storage in 0-100 cm depth, and the topographic and SAGA wetness indexes, TWI and SWI, respectively, obtained from digital elevation models at different spatial resolutions. In most studied conditions, the TWI with resolution of 10 m provided better results, particularly for the dry season. In this study, only the depth of 100 cm resulted in a significant and positive correlation, suggesting that the moisture levels are suitable for water dynamic studies in the subsurface, assisting in studies of hydrological dynamics and planning the soil use and management, especially for perennial plants with deeper root systems.

  7. Sensitivity Analysis of Distributed Soil Moisture Profiles by Active Distributed Temperature Sensing

    Science.gov (United States)

    Ciocca, F.; Van De Giesen, N.; Assouline, S.; Huwald, H.; Lunati, I.

    2012-12-01

    Monitoring and measuring the fluctuations of soil moisture at large scales in the filed remains a challenge. Although sensors based on measurement of dielectric properties such as Time Domain Reflectometers (TDR) and capacity-based probes can guarantee reasonable responses, they always operate on limited spatial ranges. On the other hand optical fibers, attached to a Distribute Temperature Sensing (DTS) system, can allow for high precision soil temperature measurements over distances of kilometers. A recently developed technique called Active DTS (ADTS) and consisting of a heat pulse of a certain duration and power along the metal sheath covering the optical fiber buried in the soil, has proven a promising alternative to spatially-limited probes. Two approaches have been investigated to infer distributed soil moisture profiles in the region surrounding the optic fiber cable by analyzing the temperature variations during the heating and the cooling phases. One directly relates the change of temperature to the soil moisture (independently measured) to develop specific calibration curve for the soil used; the other requires inferring the thermal properties and then obtaining the soil moisture by inversion of known relationships. To test and compare the two approaches over a broad range of saturation conditions a large lysimeter has been homogeneously filled with loamy soil and 52 meters of fiber optic cable have been buried in the shallower 0.8 meters in a double coil rigid structure of 15 loops along with a series of capacity-based sensors (calibrated for the soil used) to provide independent soil moisture measurements at the same depths of the optical fiber. Thermocouples have also been wrapped around the fiber to investigate the effects of the insulating cover surrounding the cable, and in between each layer in order to monitor heat diffusion at several centimeters. A high performance DTS has been used to measure the temperature along the fiber optic cable. Several

  8. Joint Sentinel-1 and SMAP data assimilation to improve soil moisture estimates

    Science.gov (United States)

    Lievens, H.; Reichle, R. H.; Liu, Q.; De Lannoy, G.; Dunbar, R. S.; Kim, S.; Das, N. N.; Cosh, M. H.; Walker, J. P.; Wagner, W.

    2017-12-01

    SMAP (Soil Moisture Active and Passive) radiometer observations at 40 km resolution are routinely assimilated into the NASA Catchment Land Surface Model (CLSM) to generate the SMAP Level 4 Soil Moisture product. The use of C-band radar backscatter observations from Sentinel-1 has the potential to add value to the radiance assimilation by increasing the level of spatial detail. The specifications of Sentinel-1 are appealing, particularly its high spatial resolution (5 by 20 m in interferometric wide swath mode) and frequent revisit time (6 day repeat cycle for the Sentinel-1A and Sentinel-1B constellation). However, the shorter wavelength of Sentinel-1 observations implies less sensitivity to soil moisture. This study investigates the value of Sentinel-1 data for hydrologic simulations by assimilating the radar observations into CLSM, either separately from or simultaneously with SMAP radiometer observations. To facilitate the assimilation of the radar observations, CLSM is coupled to the water cloud model, simulating the radar backscatter as observed by Sentinel-1. The innovations, i.e. differences between observations and simulations, are converted into increments to the model soil moisture state through an Ensemble Kalman Filter. The assimilation impact is assessed by comparing 3-hourly, 9 km surface and root-zone soil moisture simulations with in situ measurements from 9 km SMAP core validation sites and sparse networks, from May 2015 to 2017. The Sentinel-1 assimilation consistently improves surface soil moisture, whereas root-zone impacts are mostly neutral. Relatively larger improvements are obtained from SMAP assimilation. The joint assimilation of SMAP and Sentinel-1 observations performs best, demonstrating the complementary value of radar and radiometer observations.

  9. Trends in soil moisture and real evapotranspiration in Douro River for the period 1980-2010

    Science.gov (United States)

    García-Valdecasas-Ojeda, Matilde; de Franciscis, Sebastiano; Raquel Gámiz-Fortis, Sonia; Castro-Díez, Yolanda; Jesús Esteban-Parra, María

    2017-04-01

    This study analyzes the evolution of different hydrological variables, such as soil moisture and real evapotranspiration, for the last 30 years, in the Douro Basin, the most extensive basin in the Iberian Peninsula. The different components of the real evaporation, connected to the soil moisture content, can be important when analyzing the intensity of droughts and heat waves, and particularly relevant for the study of the climate change impacts. The real evapotranspiration and soil moisture data are provided by simulations obtained using the Variable Infiltration Capacity (VIC) hydrological model. This model is a large-scale hydrologic model and allows estimates of different variables in the hydrological system of a basin. Land surface is modeled as a grid of large and uniform cells with sub-grid heterogeneity (e.g. land cover), while water influx is local, only depending from the interaction between grid cells and local atmosphere environment. Observational data of temperature and precipitation from Spain02 dataset are used as input variables for VIC model. The simulations have a spatial resolution of about 9 km, and the analysis is carried out on a seasonal time-scale. Additionally, we compare these results with those obtained from a dynamical downscaling driven by ERA-Interim data using the Weather Research and Forecasting (WRF) model, with the same spatial resolution. The results obtained from Spain02 data show a decrease in soil moisture at different parts of the basin during spring and summer, meanwhile soil moisture seems to be increased for autumn. No significant changes are found for real evapotranspiration. Keywords: real evapotranspiration, soil moisture, Douro Basin, trends, VIC, WRF. Acknowledgements: This work has been financed by the projects P11-RNM-7941 (Junta de Andalucía-Spain) and CGL2013-48539-R (MINECO-Spain, FEDER).

  10. Spatiotemporal Interaction of Near-Surface Soil Moisture Content and Frost Table Depth in a Discontinuous Permafrost Environment

    Science.gov (United States)

    Guan, X.; Spence, C.; Westbrook, C. J.

    2009-05-01

    The ubiquitous presence of frozen ground in cold regions creates a unique dynamic boundary issue for subsurface water movement and storage. We examined the relationship between ground thaw and spatiotemporal soil moisture patterns at three sites (peatland, wetland and valley) near Yellowknife NT. Thaw depth and near-surface soil moisture were measured along a systematic grid at each site. Energy and water budgets were computed for each site to explain the soil moisture patterns. At the peatland, overall soil moisture decreased through the summer and became more spatially homogeneous with deepened thaw, increased subsurface storage capacity, and drying from evapotranspiration. In the peatland and wetland, accumulated water in depressions maintained soils at higher soil moistures for a longer duration than the hummock tops. The depressions had deeper frost tables than the drier hummock tops because the organic mats covering the hummocks insulated the ground and retarded ground thaw. The wettest soils were often locations of deepest thaw depth due to surface ponding and the transfer of latent heat accompanying surface runoff from upslopes. For example, the 3.3 ha wetland received 3.08x105 m3 of surface inflow from a lake with 2.32 kJm-2 of convective heat available to be transferred into the frozen ground over the study period. Soil moisture patterns also revealed preferential surface and subsurface flow routes. The findings indicate that the presence of frozen ground and differential thawing have a diverse and dynamic relationship with near-surface soil moisture content. When the impermeable boundary is dynamic, and controlled by water and energy fluxes, thicker soil layers are associated with higher moisture. This contrasts findings from temperate regions with a fixed impermeable boundary which show that surface soil moisture content can be lower in areas with thick soil.

  11. Physically plausible prescription of land surface model soil moisture

    Science.gov (United States)

    Hauser, Mathias; Orth, René; Thiery, Wim; Seneviratne, Sonia

    2016-04-01

    Land surface hydrology is an important control of surface weather and climate, especially under extreme dry or wet conditions where it can amplify heat waves or floods, respectively. Prescribing soil moisture in land surface models is a valuable technique to investigate this link between hydrology and climate. It has been used for example to assess the influence of soil moisture on temperature variability, mean and extremes (Seneviratne et al. 2006, 2013, Lorenz et al., 2015). However, perturbing the soil moisture content artificially can lead to a violation of the energy and water balances. Here we present a new method for prescribing soil moisture which ensures water and energy balance closure by using only water from runoff and a reservoir term. If water is available, the method prevents soil moisture decrease below climatological values. Results from simulations with the Community Land Model (CLM) indicate that our new method allows to avoid soil moisture deficits in many regions of the world. We show the influence of the irrigation-supported soil moisture content on mean and extreme temperatures and contrast our findings with that of earlier studies. Additionally, we will assess how long into the 21st century the new method will be able to maintain present-day climatological soil moisture levels for different regions. Lorenz, R., Argüeso, D., Donat, M.G., Pitman, A.J., den Hurk, B.V., Berg, A., Lawrence, D.M., Chéruy, F., Ducharne, A., Hagemann, S. and Meier, A., 2015. Influence of land-atmosphere feedbacks on temperature and precipitation extremes in the GLACE-CMIP5 ensemble. Journal of Geophysical Research: Atmospheres. Seneviratne, S.I., Lüthi, D., Litschi, M. and Schär, C., 2006. Land-atmosphere coupling and climate change in Europe. Nature, 443(7108), pp.205-209. Seneviratne, S.I., Wilhelm, M., Stanelle, T., Hurk, B., Hagemann, S., Berg, A., Cheruy, F., Higgins, M.E., Meier, A., Brovkin, V. and Claussen, M., 2013. Impact of soil moisture

  12. Hydrological connectivity drives microbial responses to soil moisture (Invited)

    Science.gov (United States)

    Schimel, J.

    2013-12-01

    Biogeochemical models generally fit microbial responses to moisture with smooth functions--as soils dry, processes slow. Microbial physiology, in contrast, has focused on how cells synthesize organic solutes to remain hydrated. Increasingly, however, we recognize that drying affects soil processes through resource constraints that develop when hydrological connection breaks down and organisms and resources become isolated in disconnected water pockets. Thus, microbial activity is regulated by abrupt breaks in connectivity and resources become unavailable to synthesize organic osmolytes; i.e. both biogeochemical models and pure-culture physiology perspectives are flawed. Hydrological connectivity fails before microbes become substantially stressed and before extracellular enzymes become inactive. Thus, resources can accumulate in dry soils, even as microbial activity shuts down because of resource limitation. The differential moisture responses of enzymes, organisms, and transport explains why microbial biomass and extractable C pools increase through the dry summer in California annual grasslands, why the size of the respiration pulse on rewetting increases with the length of drought, and even why soils from a wide range of biomes show the same relative response to soil moisture. I will discuss the evidence that supports the hydrological connectivity hypothesis for soil microbial moisture responses, how it affects a range of ecosystem processes, and how we can use it to develop simple, yet mechanistically rich, models of soil dynamics.

  13. Thresholds and interactive effects of soil moisture on the temperature response of soil respiration

    DEFF Research Database (Denmark)

    Lellei-Kovács, Eszter; Kovács-Láng, Edit; Botta-Dukát, Zoltán

    2011-01-01

    Ecosystem carbon exchange is poorly understood in low-productivity, semiarid habitats. Here we studied the controls of soil temperature and moisture on soil respiration in climate change field experiment in a sandy forest-steppe. Soil CO2 efflux was measured monthly from April to November in 2003......–2008 on plots receiving either rain exclusion or nocturnal warming, or serving as ambient control. Based on this dataset, we developed and compared empirical models of temperature and moisture effects on soil respiration. Results suggest that in this semiarid ecosystem the main controlling factor for soil CO2...... efflux is soil temperature, while soil moisture has less, although significant effect on soil respiration. Clear thresholds for moisture effects on temperature sensitivity were identified at 0.6, 4.0 and 7.0vol% by almost each model, which relate well to other known limits for biological activity...

  14. Monthly Summaries of Soil Temperature and Soil Moisture at Oil Contamination Sites in Antarctica, Version 1

    Data.gov (United States)

    National Aeronautics and Space Administration — To determine the effects of oil spills on soil temperature and moisture, soil climate stations were built at existing contamination sites -- Scott Base, Marble...

  15. Monthly Summaries of Soil Temperature and Soil Moisture in Mongolia, Version 1

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set contains soil temperature and soil moisture data from the Delger (White Bloom) site in Mongolia. Other variables include wind speed, wind direction,...

  16. Use of digital images to estimate soil moisture

    Directory of Open Access Journals (Sweden)

    João F. C. dos Santos

    Full Text Available ABSTRACT The objective of this study was to analyze the relation between the moisture and the spectral response of the soil to generate prediction models. Samples with different moisture contents were prepared and photographed. The photographs were taken under homogeneous light condition and with previous correction for the white balance of the digital photograph camera. The images were processed for extraction of the median values in the Red, Green and Blue bands of the RGB color space; Hue, Saturation and Value of the HSV color space; and values of the digital numbers of a panchromatic image obtained from the RGB bands. The moisture of the samples was determined with the thermogravimetric method. Regression models were evaluated for each image type: RGB, HSV and panchromatic. It was observed the darkening of the soil with the increase of moisture. For each type of soil, a model with best fit was observed and to use these models for prediction purposes, it is necessary to choose the model with best fit in advance, according to the soil characteristics. Soil moisture estimation as a function of its spectral response by digital image processing proves promising.

  17. Impact of Soil Moisture Initialization on Seasonal Weather Prediction

    Science.gov (United States)

    Koster, Randal D.; Suarez, Max J.; Houser, Paul (Technical Monitor)

    2002-01-01

    The potential role of soil moisture 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" soil moisture 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 soil moisture 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 soil moisture anomalies, (2) a strong sensitivity of evaporation to soil moisture, 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.

  18. Land surface model performance using cosmic-ray and point-scale soil moisture measurements for calibration

    Directory of Open Access Journals (Sweden)

    J. Iwema

    2017-06-01

    Full Text Available At very high resolution scale (i.e. grid cells of 1 km2, land surface model parameters can be calibrated with eddy-covariance flux data and point-scale soil moisture data. However, measurement scales of eddy-covariance and point-scale data differ substantially. In our study, we investigated the impact of reducing the scale mismatch between surface energy flux and soil moisture observations by replacing point-scale soil moisture data with observations derived from Cosmic-Ray Neutron Sensors (CRNSs made at larger spatial scales. Five soil and evapotranspiration parameters of the Joint UK Land Environment Simulator (JULES were calibrated against point-scale and Cosmic-Ray Neutron Sensor soil moisture data separately. We calibrated the model for 12 sites in the USA representing a range of climatic, soil, and vegetation conditions. The improvement in latent heat flux estimation for the two calibration solutions was assessed by comparison to eddy-covariance flux data and to JULES simulations with default parameter values. Calibrations against the two soil moisture products alone did show an advantage for the cosmic-ray technique. However, further analyses of two-objective calibrations with soil moisture and latent heat flux showed no substantial differences between both calibration strategies. This was mainly caused by the limited effect of calibrating soil parameters on soil moisture dynamics and surface energy fluxes. Other factors that played a role were limited spatial variability in surface fluxes implied by soil moisture spatio-temporal stability, and data quality issues.

  19. Synergistic soil moisture observation - an interdisciplinary multi-sensor approach to yield improved estimates across scales

    Science.gov (United States)

    Schrön, M.; Fersch, B.; Jagdhuber, T.

    2017-12-01

    The representative determination of soil moisture across different spatial ranges and scales is still an important challenge in hydrology. While in situ measurements are trusted methods at the profile- or point-scale, cosmic-ray neutron sensors (CRNS) are renowned for providing volume averages for several hectares and tens of decimeters depth. On the other hand, airborne remote-sensing enables the coverage of regional scales, however limited to the top few centimeters of the soil.Common to all of these methods is a challenging data processing part, often requiring calibration with independent data. We investigated the performance and potential of three complementary observational methods for the determination of soil moisture below grassland in an alpine front-range river catchment (Rott, 55 km2) of southern Germany.We employ the TERENO preAlpine soil moisture monitoring network, along with additional soil samples taken throughout the catchment. Spatial soil moisture products have been generated using surveys of a car-mounted mobile CRNS (rover), and an aerial acquisition of the polarimetric synthetic aperture radar (F-SAR) of DLR.The study assesses (1) the viability of the different methods to estimate soil moisture for their respective scales and extents, and (2) how either method could support an improvement of the others. We found that in situ data can provide valuable information to calibrate the CRNS rover and to train the vegetation removal part of the polarimetric SAR (PolSAR) retrieval algorithm. Vegetation correction is mandatory to obtain the sub-canopy soil moisture patterns. While CRNS rover surveys can be used to evaluate the F-SAR product across scales, vegetation-related PolSAR products in turn can support the spatial correction of CRNS products for biomass water. Despite the different physical principles, the synthesis of the methods can provide reasonable soil moisture information by integrating from the plot to the landscape scale. The

  20. Gravitational and capillary soil moisture dynamics for distributed hydrologic models

    Directory of Open Access Journals (Sweden)

    A. Castillo

    2015-04-01

    Full Text Available Distributed and continuous catchment models are used to simulate water and energy balance and fluxes across varied topography and landscape. The landscape is discretized into computational plan elements at resolutions of 101–103 m, and soil moisture is the hydrologic state variable. At the local scale, the vertical soil moisture dynamics link hydrologic fluxes and provide continuity in time. In catchment models these local-scale processes are modeled using 1-D soil columns that are discretized into layers that are usually 10−3–10−1 m in thickness. This creates a mismatch between the horizontal and vertical scales. For applications across large domains and in ensemble mode, this treatment can be a limiting factor due to its high computational demand. This study compares continuous multi-year simulations of soil moisture at the local scale using (i a 1-pixel version of a distributed catchment hydrologic model and (ii a benchmark detailed soil water physics solver. The distributed model uses a single soil layer with a novel dual-pore structure and employs linear parameterization of infiltration and some other fluxes. The detailed solver uses multiple soil layers and employs nonlinear soil physics relations to model flow in unsaturated soils. Using two sites with different climates (semiarid and sub-humid, it is shown that the efficient parameterization in the distributed model captures the essential dynamics of the detailed solver.

  1. Automated general temperature correction method for dielectric soil moisture sensors

    Science.gov (United States)

    Kapilaratne, R. G. C. Jeewantinie; Lu, Minjiao

    2017-08-01

    An effective temperature correction method for dielectric sensors is important to ensure the accuracy of soil water content (SWC) measurements of local to regional-scale soil moisture 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 soil moisture monitoring networks with different sensor setups and those that cover diverse climatic conditions and soil 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 soil 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 Soil Moisture Monitoring Network and another nine stations from a local soil moisture monitoring network in Mongolia. Soil moisture monitoring networks used in this study cover four major climates and six major soil 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

  2. Disaggregation of remotely sensed soil moisture under all sky condition using machine learning approach in Northeast Asia

    Science.gov (United States)

    Kim, S.; Kim, H.; Choi, M.; Kim, K.

    2016-12-01

    Estimating spatiotemporal variation of soil moisture is crucial to hydrological applications such as flood, drought, and near real-time climate forecasting. Recent advances in space-based passive microwave measurements allow the frequent monitoring of the surface soil moisture at a global scale and downscaling approaches have been applied to improve the spatial resolution of passive microwave products available at local scale applications. However, most downscaling methods using optical and thermal dataset, are valid only in cloud-free conditions; thus renewed downscaling method under all sky condition is necessary for the establishment of spatiotemporal continuity of datasets at fine resolution. In present study Support Vector Machine (SVM) technique was utilized to downscale a satellite-based soil moisture retrievals. The 0.1 and 0.25-degree resolution of daily Land Parameter Retrieval Model (LPRM) L3 soil moisture datasets from Advanced Microwave Scanning Radiometer 2 (AMSR2) were disaggregated over Northeast Asia in 2015. Optically derived estimates of surface temperature (LST), normalized difference vegetation index (NDVI), and its cloud products were obtained from MODerate Resolution Imaging Spectroradiometer (MODIS) for the purpose of downscaling soil moisture in finer resolution under all sky condition. Furthermore, a comparison analysis between in situ and downscaled soil moisture products was also conducted for quantitatively assessing its accuracy. Results showed that downscaled soil moisture under all sky condition not only preserves the quality of AMSR2 LPRM soil moisture at 1km resolution, but also attains higher spatial data coverage. From this research we expect that time continuous monitoring of soil moisture at fine scale regardless of weather conditions would be available.

  3. Monitoring hillslope moisture dynamics with surface ERT for enhancing spatial significance of hydrometric point measurements

    Science.gov (United States)

    Hübner, R.; Heller, K.; Günther, T.; Kleber, A.

    2015-01-01

    Besides floodplains, hillslopes are basic units that mainly control water movement and flow pathways within catchments of subdued mountain ranges. The structure of their shallow subsurface affects water balance, e.g. infiltration, retention, and runoff. Nevertheless, there is still a gap in the knowledge of the hydrological dynamics on hillslopes, notably due to the lack of generalization and transferability. This study presents a robust multi-method framework of electrical resistivity tomography (ERT) in addition to hydrometric point measurements, transferring hydrometric data into higher spatial scales to obtain additional patterns of distribution and dynamics of soil moisture on a hillslope. A geoelectrical monitoring in a small catchment in the eastern Ore Mountains was carried out at weekly intervals from May to December 2008 to image seasonal moisture dynamics on the hillslope scale. To link water content and electrical resistivity, the parameters of Archie's law were determined using different core samples. To optimize inversion parameters and methods, the derived spatial and temporal water content distribution was compared to tensiometer data. The results from ERT measurements show a strong correlation with the hydrometric data. The response is congruent to the soil tension data. Water content calculated from the ERT profile shows similar variations as that of water content from soil moisture sensors. Consequently, soil moisture dynamics on the hillslope scale may be determined not only by expensive invasive punctual hydrometric measurements, but also by minimally invasive time-lapse ERT, provided that pedo-/petrophysical relationships are known. Since ERT integrates larger spatial scales, a combination with hydrometric point measurements improves the understanding of the ongoing hydrological processes and better suits identification of heterogeneities.

  4. The neutron probe and the detection of soil moisture

    International Nuclear Information System (INIS)

    Luft, G.; Morgenschweis, G.

    1981-01-01

    The authors present a brief outline of the direct and indirect field methods used at present in soil moisture measurement; particularly the advantages and disadvantages of neutron diffusion measurement are illustrated by means of various types of instruments available. The recently developed Wellingford Neutron Moisture Probe IH II, used for hydrological and pedohydrological fieldwork respectively, is presented and the first test results concerning the handling, measuring time, measured volume and layer thickness are discussed. (orig.) [de

  5. Using electromagnetic conductivity imaging to generate time-lapse soil moisture estimates.

    Science.gov (United States)

    Huang, Jingyi; Scuderio, Elia; Corwin, Dennis; Triantafilis, John

    2015-04-01

    Irrigated agriculture is crucial to the agricultural productivity of the Moreno valley. To maintain profitability, more will need to be done by irrigators with less water, owing to competing demands from rapidly expanding urbanisation in southern California. In this regard, irrigators need to understand the spatial and temporal variation of soil moisture to discern inefficiencies. However, soil moisture is difficult to measure and monitor, unless a large bank of soil sensors are installed and at various depths in the profile. In order to value add to the limited amount of information, geophysical techniques, such as direct current resisivity (DCR) arrays are used to develop electrical resistivity images (ERI). Whilst successful the approach is time consuming and labour intensive. In this research we describe how equivalent data can be collected using a proximal sensing electromagnetic (EM) induction instrument (i.e. DUALEM-421) and inversion software (EM4Soil) to generate EM conductivity images (EMCI). Figure 1 shows the EMCI generated from DUALEM-421 data acquired at various days of a time-lapse experiment and including; day a) 0, b) 1, c) 2, d) 3, e) 5, f) 7 and g) 11. We calibrate the estimates of true electrical conductivity (sigma - mS/m) with volumetric moisture content and show with good accuracy the spatial and temporal variation of soil moisture status and over 12 day period. The results show clearly that the pivot sprinkler irrigation system is effective at providing sufficient amounts of water to the top 0.5 m of a Lucerne crop (i.e. red shaded areas of high sigma). However, in some places faulty sprinklers are evident owing to the lack of wetting (i.e. blue shaded areas of low sigma). In addition, and over time, our approach shows clearly the effect the Lucerne crop has in drying the soil profile and using the soil moisture.

  6. Multivariate assimilation of coarse scale soil moisture, cosmic-ray soil moisture, land surface temperature and leaf area index in CLM4.5

    Science.gov (United States)

    Han, Xujun; Hendricks Franssen, Harrie-Jan; Schalge, Bernd; Baroni, Gabriele; Rihani, Jehan; Kollet, Stefan; Vereecken, Harry; Simmer, Clemens

    2017-04-01

    The land surface plays a central role in the atmosphere - land surface - subsurface continuum. Surface soil moisture for instance impacts the partitioning of absorbed radiation in heating ground and atmosphere and thus impacts resulting evapotranspiration. The land surface also drives partitioning of rainfall between infiltration which ends up as groundwater recharge and surface runoff contributing to stream discharge. It is therefore expected that the use of observations for characterizing and predicting the land surface state also leads to improved state estimations and predictions in all the other sub-compartments of the system we consider: groundwater, stream discharge and atmosphere. To test this hypothesis requires efficient data assimilation schemes that are capable to take up specific requirements of different compartments, such as different time windows of observations. In this study we will derive such data assimilation methods and quantify the improvement of predictions in the different compartments due to assimilation of multiple observations, and evaluate to what extent assimilation of land surface observations will also improve predictions of land surface states and fluxes for atmosphere and groundwater. We argue that improvements can be achieved by implementing a data assimilation methodology that is capable of simultaneous assimilation of many data sources (remote sensing soil moisture, cosmic-ray measurement for soil moisture, land surface temperature and leaf area index) at different spatial scales ranging from 102 m to 104 m. The multivariate data assimilation system for the land-surface component will be developed and extended to assimilate the coarse scale remote sensing soil moisture, cosmic-ray soil moisture, land surface temperature and leaf area index, and their different combinations using the local ensemble transform Kalman filter. The multivariate data assimilation will be evaluated using a synthetic study which mimics the Neckar

  7. Estimating surface soil moisture from SMAP observations using a Neural Network technique.

    Science.gov (United States)

    Kolassa, J; Reichle, R H; Liu, Q; Alemohammad, S H; Gentine, P; Aida, K; Asanuma, J; Bircher, S; Caldwell, T; Colliander, A; Cosh, M; Collins, C Holifield; Jackson, T J; Martínez-Fernández, J; McNairn, H; Pacheco, A; Thibeault, M; Walker, J P

    2018-01-01

    A Neural Network (NN) algorithm was developed to estimate global surface soil moisture for April 2015 to March 2017 with a 2-3 day repeat frequency using passive microwave observations from the Soil Moisture Active Passive (SMAP) satellite, surface soil temperatures from the NASA Goddard Earth Observing System Model version 5 (GEOS-5) land modeling system, and Moderate Resolution Imaging Spectroradiometer-based vegetation water content. The NN was trained on GEOS-5 soil moisture target data, making the NN estimates consistent with the GEOS-5 climatology, such that they may ultimately be assimilated into this model without further bias correction. Evaluated against in situ soil moisture measurements, the average unbiased root mean square error (ubRMSE), correlation and anomaly correlation of the NN retrievals were 0.037 m 3 m -3 , 0.70 and 0.66, respectively, against SMAP core validation site measurements and 0.026 m 3 m -3 , 0.58 and 0.48, respectively, against International Soil Moisture Network (ISMN) measurements. At the core validation sites, the NN retrievals have a significantly higher skill than the GEOS-5 model estimates and a slightly lower correlation skill than the SMAP Level-2 Passive (L2P) product. The feasibility of the NN method was reflected by a lower ubRMSE compared to the L2P retrievals as well as a higher skill when ancillary parameters in physically-based retrievals were uncertain. Against ISMN measurements, the skill of the two retrieval products was more comparable. A triple collocation analysis against Advanced Microwave Scanning Radiometer 2 (AMSR2) and Advanced Scatterometer (ASCAT) soil moisture retrievals showed that the NN and L2P retrieval errors have a similar spatial distribution, but the NN retrieval errors are generally lower in densely vegetated regions and transition zones.

  8. Event-scale soil moisture dynamics in open evergreen woodlands of southwest Spain

    Science.gov (United States)

    Lozano-Parra, F. J.; Schnabel, S.; Gómez-Gutiérrez, Á.

    2012-04-01

    Rangelands with a disperse tree cover occupy large areas in the southwestern part of the Iberian Pensinsula and are also found in other parts of the Mediterranean. In these grazed, savannah-like ecosystems water constitutes an important limiting factor for vegetation growth because of the strong summer dry period, being annual potential evapotranspiration nearly twice the annual rainfall amount. Previous studies by other authors have found lower values of soil water content below the tree canopy as compared to the open spaces, covered only by herbaceous vegetation. The differences of soil moisture between tree covered and open areas vary along the year, commonly being highest during autumn, low when water content is close to saturation and the inverse during summer. Our studies indicate that the spatial variation of soil moisture is more complex. The main objective of this study is to analyze soil moisture dynamics at the event scale below tree canopies (Quercus ilex) and in the open spaces. Because soils are commonly very shallow (Cambisols) and a high concentration of grass roots is found in the upper five centimetres, soil moisture measurements were carried out at 5, 10, 15 and 30 cm depth. The study area is located in Extremadura. Soil moisture is measured continuously with a time resolution of 30 minutes using capacitive sensors and rainfall is registered in 5-minute intervals. Data from the hydrological year 2010-11 are presented here. The main factors which produced variations in soil moisture in the upper 5 cm were amount and duration of the rainfall event. Rainfall intensity was also significantly related with an increase of the water content. At greater depth (30 cm) soil moisture was more related with antecedent rainfall, as for example the amount of precipitation registered 30 and 45 days prior to the event. Maximum increases produced by a rainstorm were approximately 0.20 m3m-3 in grasslands and 0.17 m3m-3 below tree canopy. However, in the uppermost

  9. Influence of soil moisture content on surface albedo and soil thermal ...

    Indian Academy of Sciences (India)

    The large variability in the soil moisture content is attributed to the rainfall during all the seasons and also to the evaporation/movement of water to deeper layers. The relationship of surface albedo on soil moisture content on different time scales are studied and the influence of solar elevation angle and cloud cover are also ...

  10. Sensitivity of soil respiration to variability in soil moisture and temperature in a humid tropical forest

    Science.gov (United States)

    Tana Wood; M. Detto; W.L. Silver

    2013-01-01

    Precipitation and temperature are important drivers of soil respiration. The role of moisture 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 soil moisture and temperature as temporal...

  11. Design and Fabrication of a Soil Moisture Meter Using Thermal Conductivity Properties of Soil

    Directory of Open Access Journals (Sweden)

    Subir DAS

    2011-09-01

    Full Text Available Study of soil for agricultural purposes is one of the main focuses of research since the beginning of civilization as food related requirements is closely linked with the soil. The study of soil has generated an interest among the researchers for very similar other reasons including understanding of soil water dynamics, evolution of agricultural water stress and validation of soil moisture modeling. In this present work design of a soil moisture measurement meter using thermal conductivity properties of soil has been proposed and experimental results are reported.

  12. Assessment of Surface Soil Moisture Using High-Resolution Multi-Spectral Imagery and Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Leila Hassan-Esfahani

    2015-03-01

    Full Text Available Many crop production management decisions can be informed using data from high-resolution aerial images that provide information about crop health as influenced by soil fertility and moisture. Surface soil moisture is a key component of soil water balance, which addresses water and energy exchanges at the surface/atmosphere interface; however, high-resolution remotely sensed data is rarely used to acquire soil moisture values. In this study, an artificial neural network (ANN model was developed to quantify the effectiveness of using spectral images to estimate surface soil moisture. The model produces acceptable estimations of surface soil moisture (root mean square error (RMSE = 2.0, mean absolute error (MAE = 1.8, coefficient of correlation (r = 0.88, coefficient of performance (e = 0.75 and coefficient of determination (R2 = 0.77 by combining field measurements with inexpensive and readily available remotely sensed inputs. The spatial data (visual spectrum, near infrared, infrared/thermal are produced by the AggieAir™ platform, which includes an unmanned aerial vehicle (UAV that enables users to gather aerial imagery at a low price and high spatial and temporal resolutions. This study reports the development of an ANN model that translates AggieAir™ imagery into estimates of surface soil moisture for a large field irrigated by a center pivot sprinkler system.

  13. Water consumption and soil moisture distribution in melon crop with mulching and in a protected environment

    Directory of Open Access Journals (Sweden)

    Rodrigo Otávio Câmara Monteiro

    2013-06-01

    Full Text Available Mulching has become an important technique for land cover, but there are some technical procedures which should be adjusted for these new modified conditions to establish optimum total water depth. It is also important to observe the soil-water relations as soil water distribution and wetted volume dimensions. The objective of the present study was to estimate melon evapotranspiration under mulching in a protected environment and to verify the water spatial distribution around the melon root system in two soil classes. Mulching provided 27 mm water saving by reducing water evaporation. In terms of volume each plant received, on average, the amount of 175.2 L of water in 84 days of cultivation without mulching, while when was used mulching the water requirement was 160.2 L per plant. The use of mulching reduced the soil moisture variability throughout the crop cycle and allowed a greater distribution of soil water that was more intense in the clay soil. The clayey soil provided on average 43 mm more water depth retention in 0.50 m soil deep relative to the sandy loam soil, and reduced 5.6 mm the crop cycle soil moisture variation compared to sandy loam soil.

  14. Downscaling of Surface Soil Moisture Retrieval by Combining MODIS/Landsat and In Situ Measurements

    Directory of Open Access Journals (Sweden)

    Chenyang Xu

    2018-02-01

    Full Text Available Soil moisture, especially surface soil moisture (SSM, plays an important role in the development of various natural hazards that result from extreme weather events such as drought, flooding, and landslides. There have been many remote sensing methods for soil moisture retrieval based on microwave or optical thermal infrared (TIR measurements. TIR remote sensing has been popular for SSM retrieval due to its fine spatial and temporal resolutions. However, because of limitations in the penetration of optical TIR radiation and cloud cover, TIR methods can only be used under clear sky conditions. Microwave SSM retrieval is based on solid physical principles, and has advantages in cases of cloud cover, but it has low spatial resolution. For applications at the local scale, SSM data at high spatial and temporal resolutions are important, especially for agricultural management and decision support systems. Current remote sensing measurements usually have either a high spatial resolution or a high temporal resolution, but not both. This study aims to retrieve SSM at both high spatial and temporal resolutions through the fusion of Moderate Resolution Imaging Spectroradiometer (MODIS and Land Remote Sensing Satellite (Landsat data. Based on the universal triangle trapezoid, this study investigated the relationship between land surface temperature (LST and the normalized difference vegetation index (NDVI under different soil moisture conditions to construct an improved nonlinear model for SSM retrieval with LST and NDVI. A case study was conducted in Iowa, in the United States (USA (Lat: 42.2°~42.7°, Lon: −93.6°~−93.2°, from 1 May 2016 to 31 August 2016. Daily SSM in an agricultural area during the crop-growing season was downscaled to 120-m spatial resolution by fusing Landsat 8 with MODIS, with an R2 of 0.5766, and RMSE from 0.0302 to 0.1124 m3/m3.

  15. Crop yield monitoring in the Sahel using root zone soil moisture anomalies derived from SMOS soil moisture data assimilation

    Science.gov (United States)

    Gibon, François; Pellarin, Thierry; Alhassane, Agali; Traoré, Seydou; Baron, Christian

    2017-04-01

    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 soil water availability in the soil. 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 soil moisture 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 soil moisture 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 soil moisture estimates were tested, and the most promising one (R>0.9) linked the 30-cm soil moisture 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 soil moisture 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 soil moisture measurements were assimilated into the API model through a Particular Filter algorithm. Then, obtained soil moisture anomalies were

  16. Inter-Comparison of Retrieved and Modelled Soil Moisture and Coherency of Remotely Sensed Hydrology Data

    Science.gov (United States)

    Kolassa, Jana; Aires, Filipe

    2013-04-01

    A neural network algorithm has been developed for the retrieval of Soil Moisture (SM) from global satellite observations. The algorithm estimates soil moisture from a synergy of passive and active microwave, infrared and visible satellite observations in order to capture the different SM variabilities that the individual sensors are sensitive to. The advantages and drawbacks of each satellite observation have been analysed and the information type and content carried by each observation have been determined. A global data set of monthly mean soil moisture for the 1993-2000 period has been computed with the neural network algorithm (Kolassa et al., in press, 2012). The resulting soil moisture retrieval product has then been used in an inter-comparison study including soil moisture from (1) the HTESSEL model (Balsamo et al., 2009), (2) the WACMOS satellite product (Liu et al., 2011), and (3) in situ measurements from the International Soil Moisture Network (Dorigo et al., 2011). The analysis showed that the satellite remote sensing products are well-suited to capture the spatial variability of the in situ data and even show the potential to improve the modelled soil moisture. Both satellite retrievals also display a good agreement with the temporal structures of the in situ data, however, HTESSEL appears to be more suitable for capturing the temporal variability (Kolassa et al., in press, 2012). The use of this type of neural network approach is currently being investigated as a retrieval option for the SMOS mission. Our soil moisture retrieval product has also been used in a coherence study with precipitation data from GPCP (Adler et al., 2003) and inundation estimates from GIEMS (Prigent et al., 2007). It was investigated on a global scale whether the three observation-based datasets are coherent with each other and show the expected behaviour. For most regions of the Earth, the datasets were consistent and the behaviour observed could be explained with the known

  17. Application of Cosmic-ray Soil Moisture Sensing to Understand Land-atmosphere Interactions in Three North American Monsoon Ecosystems

    Science.gov (United States)

    Schreiner-McGraw, A.; Vivoni, E. R.; Franz, T. E.; Anderson, C.

    2013-12-01

    Human impacts on desert ecosystems have wide ranging effects on the hydrologic cycle which, in turn, influence interactions between the critical zone and the atmosphere. In this contribution, we utilize cosmic-ray soil moisture sensors at three human-modified semiarid ecosystems in the North American monsoon region: a buffelgrass pasture in Sonora, Mexico, a woody-plant encroached savanna ecosystem in Arizona, and a woody-plant encroached shrubland ecosystem in New Mexico. In each case, landscape heterogeneity in the form of bare soil and vegetation patches of different types leads to a complex mosaic of soil moisture and land-atmosphere interactions. Historically, the measurement of spatially-averaged soil moisture at the ecosystem scale (on the order of several hundred square meters) has been problematic. Thus, new advances in measuring cosmogenically-produced neutrons present an opportunity for observational and modeling studies in these ecosystems. We discuss the calibration of the cosmic-ray soil moisture sensors at each site, present comparisons to a distributed network of in-situ measurements, and verify the spatially-aggregated observations using the watershed water balance method at two sites. We focus our efforts on the summer season 2013 and its rainfall period during the North American monsoon. To compare neutron counts to the ground sensors, we utilized an aspect-elevation weighting algorithm to compute an appropriate spatial average for the in-situ measurements. Similarly, the water balance approach utilizes precipitation, runoff, and evapotranspiration measurements in the footprint of the cosmic-ray sensors to estimate a spatially-averaged soil moisture field. Based on these complementary approaches, we empirically determined a relationship between cosmogenically-produced neutrons and the spatially-aggregated soil moisture. This approach may improve upon existing methods used to calculate soil moisture from neutron counts that typically suffer from

  18. Soil Temperature and Moisture Profile (STAMP) System Handbook

    Energy Technology Data Exchange (ETDEWEB)

    Cook, David R. [Argonne National Lab. (ANL), Argonne, IL (United States)

    2016-11-01

    The soil temperature and moisture profile system (STAMP) provides vertical profiles of soil temperature, soil water content (soil-type specific and loam type), plant water availability, soil 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 soil energy conductivity. Atmospheric scientists use the data in climate models to determine boundary conditions and to estimate the surface energy flux. The data are also useful to hydrologists, soil scientists, and agricultural scientists for determining the state of the soil. The STAMP system replaced the SWATS system in early 2016.

  19. Impact of soil moisture on land-atmosphere interaction - a study on stemflow

    Science.gov (United States)

    Kuo, T.; Chen, J.

    2013-12-01

    Hydrological cycle inside a forest ecosystem is complicated. Rainfall entering the forest is redistributed via several pathways before reaching the forest floor. Some of the rainwater is intercepted by the canopy and some become throughfall. Water intercepted by the canopy and branches can flow to the forest floor as stemflow. Furthermore, in contrast to the slow penetration through the top soil, the stemflow can quickly reach deep soil and water table via the root system. Stemflow has been found to vary as a function of plant species, seasonality, meteorological conditions, rainfall intensity and canopy structure (Levia and Frost, 2003). It can significantly influence runoff generation (Neave and Abrahams, 2002), groundwater recharge (Taniguchi et al., 1996), and spatial pattern of soil moisture (Chang and Matzner, 2000; Liang et al., 2007). The stemflow mechanism has not been considered as part of the land-surface processes in most atmospheric models. So, in this effort we parameterize the stemflow effect into a land-surface module -- the Simplified Simple Biosphere (SSiB) model, and analyze how it affects soil moisture, and if this effect is significant enough to influence atmospheric processes. We first applied the SSiB model to simulate offline the sensitivity of soil moisture to stemflow under different rainfall intensity. Then the SSiB with stemflow effect is incorporated into the Weather Research and Forecasting (WRF) model to simulate stemflow effect on moisture exchange between soil and the atmosphere. The case selected is a summer convection event which lasted for five consecutive days, under weak synoptic weather conditions. The results indicated that stemflow acts like a bypass highway which allows soil water to quickly enter deep layer. As a result, upper layer soil moisture is decreased, leading to a stronger surface heating and thus atmospheric instability, consequently more intense rainfall.

  20. Espacialização da umidade do solo por meio da temperatura da superfície e índice de vegetação Spatial distribution of soil moisture using land surface temperature and vegetation indices

    Directory of Open Access Journals (Sweden)

    Helio L. Lopes

    2011-09-01

    Full Text Available O estudo da umidade do solo é fundamental não só para a determinação da resiliência de ecossistemas e sua recuperação, mas também na modelagem da relação água-vegetação-atmosfera. Na aquisição dessas informações o sensoriamento remoto perfaz uma ferramenta importante e de potencial adequado para monitoramento e mapeamento. Visando à espacialização de índices relacionados à umidade, vários métodos têm sido propostos, embora sua aplicação ainda seja limitada. Neste trabalho se aplicou o modelo de índice de umidade do solo (IUS cujos objetivos foram: espacializar o IUS, estabelecer graus de desertificação, delimitar a área em processo de desertificação e verificar possíveis relações do IUS com parâmetros de água no solo. Na aplicação deste modelo se utilizaram, como dados de entrada, o NDVI (índice de vegetação da diferença normalizada e a LST (temperatura da superfície e se observou que o IUS representado pela média dos valores desses índices pode ser empregado na determinação do grau de degradação da superfície e para gerar classificação legendada, discriminando vários níveis de degradação ambiental. Constatou-se também que não houve relação direta do IUS com parâmetros físicos de retenção de umidade do solo. Desta forma, o sensoriamento remoto mostrou ser uma ferramenta significativa na avaliação de índices de umidade do solo em áreas degradadas tal como para delinear a dinâmica de borda em núcleo de desertificação.The study of soil moisture is important in determining the resilience of ecosystems and their recovery, as well as in the modeling of water-vegetation-atmosphere relationship. Remote sensing is an important tool for the acquisition, mapping and monitoring soil moisture through the surface temperature and vegetation indices. For the soil moisture content assessment, several methods have been proposed, however its application is still limited. In this work the

  1. Evapotranspiration Estimates for a Stochastic Soil-Moisture Model

    Science.gov (United States)

    Chaleeraktrakoon, Chavalit; Somsakun, Somrit

    2009-03-01

    Potential evapotranspiration is information that is necessary for applying a widely used stochastic model of soil moisture (I. Rodriguez Iturbe, A. Porporato, L. Ridolfi, V. Isham and D. R. Cox, Probabilistic modelling of water balance at a point: The role of climate, soil and vegetation, Proc. Roy. Soc. London A455 (1999) 3789-3805). An objective of the present paper is thus to find a proper estimate of the evapotranspiration for the stochastic model. This estimate is obtained by comparing the calculated soil-moisture distribution resulting from various techniques, such as Thornthwaite, Makkink, Jensen-Haise, FAO Modified Penman, and Blaney-Criddle, with an observed one. The comparison results using five sequences of daily soil-moisture for a dry season from November 2003 to April 2004 (Udornthani Province, Thailand) have indicated that all methods can be used if the weather information required is available. This is because their soil-moisture distributions are alike. In addition, the model is shown to have its ability in approximately describing the phenomenon at a weekly or biweekly time scale which is desirable for agricultural engineering applications.

  2. A Polarimetric First-Order Model of Soil Moisture Effects on the DInSAR Coherence

    Directory of Open Access Journals (Sweden)

    Simon Zwieback

    2015-06-01

    Full Text Available Changes in soil moisture between two radar acquisitions can impact the observed coherence in differential interferometry: both coherence magnitude |Υ| and phase Φ are affected. The influence on the latter potentially biases the estimation of deformations. These effects have been found to be variable in magnitude and sign, as well as dependent on polarization, as opposed to predictions by existing models. Such diversity can be explained when the soil is modelled as a half-space with spatially varying dielectric properties and a rough interface. The first-order perturbative solution achieves–upon calibration with airborne L band data–median correlations ρ at HH polarization of 0.77 for the phase Φ, of 0.50 for |Υ|, and for the phase triplets ≡ of 0.56. The predictions are sensitive to the choice of dielectric mixing model, in particular the absorptive properties; the differences between the mixing models are found to be partially compensatable by varying the relative importance of surface and volume scattering. However, for half of the agricultural fields the Hallikainen mixing model cannot reproduce the observed sensitivities of the phase to soil moisture. In addition, the first-order expansion does not predict any impact on the HV coherence, which is however empirically found to display similar sensitivities to soil moisture as the co-pol channels HH and VV. These results indicate that the first-order solution, while not able to reproduce all observed phenomena, can capture some of the more salient patterns of the effect of soil moisture changes on the HH and VV DInSAR signals. Hence it may prove useful in separating the deformations from the moisture signals, thus yielding improved displacement estimates or new ways for inferring soil moisture.

  3. 4.4 Development of a 30-Year Soil Moisture Climatology for Situational Awareness and Public Health Applications

    Science.gov (United States)

    Case, Jonathan L.; Zavodsky, Bradley T.; White, Kristopher D.; Bell, Jesse E.

    2015-01-01

    This paper provided a brief background on the work being done at NASA SPoRT and the CDC to create a soil moisture climatology over the CONUS at high spatial resolution, and to provide a valuable source of soil moisture information to the CDC for monitoring conditions that could favor the development of Valley Fever. The soil moisture climatology has multi-faceted applications for both the NOAA/NWS situational awareness in the areas of drought and flooding, and for the Public Health community. SPoRT plans to increase its interaction with the drought monitoring and Public Health communities by enhancing this testbed soil moisture anomaly product. This soil moisture climatology run will also serve as a foundation for upgrading the real-time (currently southeastern CONUS) SPoRT-LIS to a full CONUS domain based on LIS version 7 and incorporating real-time GVF data from the Suomi-NPP Visible Infrared Imaging Radiometer Suite (Vargas et al. 2013) into LIS-Noah. The upgraded SPoRT-LIS run will serve as a testbed proof-of-concept of a higher-resolution NLDAS-2 modeling member. The climatology run will be extended to near real-time using the NLDAS-2 meteorological forcing from 2011 to present. The fixed 1981-2010 climatology shall provide the soil moisture "normals" for the production of real-time soil moisture anomalies. SPoRT also envisions a web-mapping type of service in which an end-user could put in a request for either an historical or real-time soil moisture anomaly graph for a specified county (as exemplified by Figure 2) and/or for local and regional maps of soil moisture proxy percentiles. Finally, SPoRT seeks to assimilate satellite soil moisture data from the current Soil Moisture Ocean Salinity (SMOS; Blankenship et al. 2014) and the recently-launched NASA Soil Moisture Active Passive (SMAP; Entekhabi et al. 2010) missions, using the EnKF capability within LIS. The 9-km combined active radar and passive microwave retrieval product from SMAP (Das et al. 2011

  4. Unsaturated soil moisture drying and wetting diffusion coefficient measurements in the laboratory.

    Science.gov (United States)

    2009-09-01

    ABSTRACTTransient moisture flow in an unsaturated soil in response to suction changes is controlled by the unsaturated moisture diffusion coefficient. The moisture diffusion coefficient can be determined by measuring suction profiles over time. The l...

  5. Determining soil moisture and soil properties in vegetated areas by assimilating soil temperatures

    NARCIS (Netherlands)

    Dong, J.; Steele-Dunne, S.C.; Ochsner, Tyson E.; van de Giesen, N.C.

    2016-01-01

    This study addresses two critical barriers to the use of Passive Distributed Temperature Sensing (DTS) for large-scale, high-resolution monitoring of soil moisture. In recent research, a particle batch smoother (PBS) was developed to assimilate sequences of temperature data at two depths into

  6. Soil moisture applications of the heat capacity mapping mission

    Science.gov (United States)

    Heilman, J. L.; Moore, D. G.

    1981-01-01

    Results are presented of ground, aircraft and satellite investigations conducted to evaluate the potential of the Heat Capacity Mapping Mission (HCMM) to monitor soil moisture and the depth of shallow ground water. The investigations were carried out over eastern South Dakota to evaluate the relation between directly measured soil temperatures and water content at various stages of canopy development, aircraft thermal scanner measurements of apparent canopy temperature and the reliability of actual HCMM data. The results demonstrate the possibility of evaluating soil moisture on the basis of HCMM apparent canopy temperature and day-night soil temperature difference measurements. Limitations on the use of thermal data posed by environmental factors which influence energy balance interactions, including phase transformations, wind patterns, topographic variations and atmospheric constituents are pointed out.

  7. Analysis of soil moisture probability in a tree cropped watershed

    Science.gov (United States)

    Espejo-Perez, Antonio Jesus; Giraldez Cervera, Juan Vicente; Pedrera, Aura; Vanderlinden, Karl

    2015-04-01

    Probability density functions (pdfs) of soil moisture were estimated for an experimental watershed in Southern Spain, cropped with olive trees. Measurements were made using a capacitance sensors network from June 2011 until May 2013. The network consisted of 22 profiles of sensors, installed close to the tree trunk under the canopy and in the adjacent inter-row area, at 11 locations across the watershed to assess the influence of rain interception and root-water uptake on the soil moisture distribution. A bimodal pdf described the moisture dynamics at the 11 sites, both under and in-between the trees. Each mode represented the moisture status during either the dry or the wet period of the year. The observed histograms could be decomposed into a Lognormal pdf for dry period and a Gaussian pdf for the wet period. The pdfs showed a larger variation among the different locations at inter-row positions, as compared to under the canopy, reflecting the strict control of the vegetation on soil moisture. At both positions this variability was smaller during the wet season than during the dry period.

  8. PRELIMINARY RESULTS OF ESTIMATING SOIL MOISTURE OVER BARE SOIL USING FULL-POLARIMETRIC ALOS-2 DATA

    Directory of Open Access Journals (Sweden)

    A. Sekertekin

    2016-10-01

    Full Text Available Synthetic Aperture Radar (SAR imaging system is one of the most effective way for Earth observation. The aim of this study is to present the preliminary results about estimating soil moisture using L-band Synthetic Aperture Radar (SAR data. Full-polarimetric (HH, HV, VV, VH ALOS-2 data, acquired on 22.04.2016 with the incidence angle of 30.4o, were used in the study. Simultaneously with the SAR acquisition, in-situ soil moisture samples over bare agricultural lands were collected and evaluated using gravimetric method. Backscattering coefficients for all polarizations were obtained and linear regression analysis was carried out with in situ moisture measurements. The best correlation coefficient was observed with VV polarization. Cross-polarized backscattering coefficients were not so sensitive to soil moisture content. In the study, it was observed that soil moisture maps can be retrieved with the accuracy about 14% (RMSE.

  9. Contributions of Soil Moisture and Vegetation Components to Polarized Emission Based on the Soil Moisture Active Passive (SMAP) Mission Measurements

    Science.gov (United States)

    Zhao, T.; Talebi, S.; Li, S.; Entekhabi, D.; Lu, H.; Shi, J.; Akbar, R.; Wang, Z.; Weng, H.; Mccoll, K. A.

    2016-12-01

    The Soil Moisture Active Passive (SMAP) is an Earth satellite mission providing polarized L-band brightness temperature measurements with 6AM and 6PM equatorial crossing times. The brightness temperature measurements over land respond to land and water mixing across the landscape. Over land the soil dielectric constant and the vegetation structure and biomass cause variations in brightness temperature. The physical temperature of the landscape components and their emissivity determine the polarized brightness temperature. During the morning crossing when the physical temperature of the components are nearly equal, the difference of the polarizations normalized by the sum is independent of physical temperature. In this study, we use the Polarization Ratio (PR) as a measurement of surface emission because it does not depend on physical temperature and potentially is also a signature of soil moisture and vegetation. To decompose the PR signal into vegetation and soil components, SMAP Level 2 radiometer-only soil moisture products at 36-km are directly used. Radar observations are used as a measurement of vegetation, including cross-polarized backscattering coefficients and the Radar Vegetation Index (RVI). Regressions between these satellite observations are conducted. The regression coefficients are used to estimate percentage variance explained. Results show there is a positive correlation between PR and soil moisture and an inverse correlation exists between PR and the cross polarization of radar signal or RVI that corresponds to vegetation. In light to moderate vegetation regions, there is a substantial explained-variance between PR and soil moisture. But in dense vegetation the correlation is weak because the vegetation causes depolarization and reduces the dynamic range of the PR.

  10. Revealing plot scale heterogeneity in soil moisture dynamics under contrasting vegetation assemblages using 3D electrical resistivity tomography (ERT) surveys

    Science.gov (United States)

    Dick, Jonathan; Tetzlaff, Doerthe; Bradford, John; Soulsby, Chris

    2016-04-01

    Soil moisture is a fundamental component of the water cycle that influences many hydrological processes, such as flooding, solute transport, biogeochemical processes, and land-atmosphere interactions. The relationship between vegetation and soil moisture is complex and reciprocal. Soil moisture may affect vegetation distribution due to its function as the primary source of water, in turn the structure of vegetation canopies regulate water partitioning into interception, throughfall and steam flow. Such spatial differences in inputs, together with complex patterns of water uptake from distributed root networks can create marked heterogeneity in soil moisture dynamics at small scales. Traditional methods of monitoring soil moisture have revolved around limited point measurements, but improved geophysical techniques have facilitated a trend towards more spatially distributed measurements to help understand this heterogeneity. Here, we present a study using 3D ERT surveys in a 3.2km upland catchment in the Scottish Highlands where increasing afforestation (for climate change adaptation, biofuels and conservation) has the potential to increase interception losses and reduce soil moisture storage. The study combined 3D surveys, traditional point measurements and laboratory analysis of soil cores to assess the plot scale soil moisture dynamics in podzolic soils under forest stands of 15m high Scots pine (Pinus sylvestris) and adjacent non-forest plots dominated by heather (Calluna vulgaris) shrubs (maintain water content in the soils below. These results are important as the point to potential water stresses with planned increased afforestation which may be compounded by climate change projections of decreasing precipitation during the growing season.

  11. High resolution soil moisture radiometer. [large space structures

    Science.gov (United States)

    Wilheit, T. T.

    1978-01-01

    An electrically scanned pushbroom phased antenna array is described for a microwave radiometer which can provide agriculturally meaningful measurements of soil moisture. The antenna size of 100 meters at 1400 MHz or 230 meters at 611 MHz requires several shuttle launches and orbital assembly. Problems inherent to the size of the structure and specific instrument problems are discussed as well as the preliminary design.

  12. Response of maize and cucumber intercrop to soil moisture control ...

    African Journals Online (AJOL)

    GREGO

    2007-03-05

    Mar 5, 2007 ... Replicate field plots were used in experiments aimed at evaluating the yield potentials of maize and cucumber intercrop resulting from the control of soil moisture through irrigation and mulching, for a period of eleven weeks. Three irrigation depths, 2.5, 3.5 and 4.5 mm; and two mulch levels, zero mulch.

  13. Effects of soil moisture stress on floral and pods abortion ...

    African Journals Online (AJOL)

    Experiments were conducted at Ilorin, Nigeria to evaluate the effects of soil moisture stress at different growth stages (vegetative, flowering and pod filling) on floral and pods abortion, reproductive efficiency and grain yields of ten soybean genotypes (TGX 923-2E, TGX 1440-1E, Samsoy- 2, TGX 536 02D, TGX 1019-2E, TGX ...

  14. Response of maize and cucumber intercrop to soil moisture control ...

    African Journals Online (AJOL)

    Replicate field plots were used in experiments aimed at evaluating the yield potentials of maize and cucumber intercrop resulting from the control of soil moisture through irrigation and mulching, for a period of eleven weeks. Three irrigation depths, 2.5, 3.5 and 4.5 mm; and two mulch levels, zero mulch and 10 ton/ha of oil ...

  15. NASA Soil Moisture Active Passive Mission Status and Science Performance

    Science.gov (United States)

    Yueh, Simon H.; Entekhabi, Dara; O'Neill, Peggy; Njoku, Eni; Entin, Jared K.

    2016-01-01

    The Soil Moisture 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 soil moisture 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 soil moisture 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 soil moisture 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.

  16. A Preliminary Study toward Consistent Soil Moisture from AMSR2

    NARCIS (Netherlands)

    Parinussa, R.M.; Holmes, T.R.H.; Wanders, N.; Dorigo, W.A.; de Jeu, R.A.M.

    2015-01-01

    A preliminary study toward consistent soil moisture products from the Advanced Microwave Scanning Radiometer 2 (AMSR2) is presented. Its predecessor, the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E), has providedEarth scientists with a consistent and continuous global

  17. Remote Sensing of Soil Moisture Using Airborne Hyperspectral Data

    Science.gov (United States)

    2011-01-01

    Soil Moisture Retrievals for Forecasting Rainfall-Runoff Partitioning ," Geophysical Research Letters, 32(18):L 18401 [doi: 10.1029/2005GL023543...Influences on the Remote Estimation of Evapotranspiration Using Multiple Satellite Sensors," Remote Sensing of Envi- ronment, 105(4):271-285. Milfred, C

  18. Effect of Soil Moisture on Chlorine Deposition (POSTPRINT)

    Science.gov (United States)

    2014-01-01

    distribution unlimited. 13. SUPPLEMENTARY NOTES The original document contains color images. 14. ABSTRACT The effect of soil moisture on chlorine (Cl2...conditions but additional experimental investi- ations were needed [4]. Experimental measurements of Cl2 uptake n aerosol particles [5,6], alfalfa grass [7

  19. GCOM-W soil moisture and temperature algorithms and validation

    Science.gov (United States)

    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...

  20. [Bare Soil Moisture Inversion Model Based on Visible-Shortwave Infrared Reflectance].

    Science.gov (United States)

    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

    2015-08-01

    Soil is the loose solum of land surface that can support plants. It consists of minerals, organics, atmosphere, moisture, microbes, et al. Among its complex compositions, soil moisture varies greatly. Therefore, the fast and accurate inversion of soil moisture by using remote sensing is very crucial. In order to reduce the influence of soil type on the retrieval of soil moisture, this paper proposed a normalized spectral slope and absorption index named NSSAI to estimate soil moisture. The modeling of the new index contains several key steps: Firstly, soil samples with different moisture level were artificially prepared, and soil reflectance spectra was consequently measured using spectroradiometer produced by ASD Company. Secondly, the moisture 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 soil at different moisture conditions. Then advantages of the two features at reducing soil types' effects was synthesized to build the NSSAI. Thirdly, a linear relationship between NSSAI and soil moisture was established. The result showed that NSSAI worked better (correlation coefficient is 0.93) than most of other traditional methods in soil moisture extraction. It can weaken the influences caused by soil types at different moisture levels and improve the bare soil moisture inversion accuracy.

  1. Optimizing Soil Moisture Sampling Locations for Validation Networks for SMAP

    Science.gov (United States)

    Roshani, E.; Berg, A. A.; Lindsay, J.

    2013-12-01

    Soil Moisture Active Passive satellite (SMAP) is scheduled for launch on Oct 2014. Global efforts are underway for establishment of soil moisture monitoring networks for both the pre- and post-launch validation and calibration of the SMAP products. In 2012 the SMAP Validation Experiment, SMAPVEX12, took place near Carman Manitoba, Canada where nearly 60 fields were sampled continuously over a 6 week period for soil moisture and several other parameters simultaneous to remotely sensed images of the sampling region. The locations of these sampling sites were mainly selected on the basis of accessibility, soil texture, and vegetation cover. Although these criteria are necessary to consider during sampling site selection, they do not guarantee optimal site placement to provide the most efficient representation of the studied area. In this analysis a method for optimization of sampling locations is presented which combines the state-of-art multi-objective optimization engine (non-dominated sorting genetic algorithm, NSGA-II), with the kriging interpolation technique to minimize the number of sampling sites while simultaneously minimizing the differences between the soil moisture map resulted from the kriging interpolation and soil moisture map from radar imaging. The algorithm is implemented in Whitebox Geospatial Analysis Tools, which is a multi-platform open-source GIS. The optimization framework is subject to the following three constraints:. A) sampling sites should be accessible to the crew on the ground, B) the number of sites located in a specific soil texture should be greater than or equal to a minimum value, and finally C) the number of sampling sites with a specific vegetation cover should be greater than or equal to a minimum constraint. The first constraint is implemented into the proposed model to keep the practicality of the approach. The second and third constraints are considered to guarantee that the collected samples from each soil texture categories

  2. The NAFE’06 data set: Towards soil moisture retrieval at intermediate resolution

    Science.gov (United States)

    Merlin, Olivier; Walker, Jeffrey P.; Kalma, Jetse D.; Kim, Edward J.; Hacker, Jorg; Panciera, Rocco; Young, Rodger; Summerell, Gregory; Hornbuckle, John; Hafeez, Mohsin; Jackson, Thomas

    2008-11-01

    The National Airborne Field Experiment 2006 (NAFE'06) was conducted during a three week period of November 2006 in the Murrumbidgee River catchment, located in southeastern Australia. One objective of NAFE'06 was to explore the suitability of the area for SMOS (Soil Moisture and Ocean Salinity) calibration/validation and develop downscaling and assimilation techniques for when SMOS does come on line. Airborne L-band brightness temperature was mapped at 1 km resolution 11 times (every 1-3 days) over a 40 by 55 km area in the Yanco region and 3 times over a 40 by 50 km area that includes Kyeamba Creek catchment. Moreover, multi-resolution, multi-angle and multi-spectral airborne data including surface temperature, surface reflectance (green, read and near infrared), lidar data and aerial photos were acquired over selected areas to develop downscaling algorithms and test multi-angle and multi-spectral retrieval approaches. The near-surface soil moisture was measured extensively on the ground in eight sampling areas concurrently with aircraft flights, and the soil moisture profile was continuously monitored at 41 sites. Preliminary analyses indicate that (i) the uncertainty of a single ground measurement was typically less than 5% vol. (ii) the spatial variability of ground measurements at 1 km resolution was up to 10% vol. and (iii) the validation of 1 km resolution L-band data is facilitated by selecting pixels with a spatial soil moisture variability lower than the point-scale uncertainty. The sensitivity of passive microwave and thermal data is also compared at 1 km resolution to illustrate the multi-spectral synergy for soil moisture monitoring at improved accuracy and resolution. The data described in this paper are available at www.nafe.unimelb.edu.au.

  3. Synergistic use of ENVISAT ASAR Global Mode Soil Moisture Products in the Okavango Delta: Runoff & Wetland Monitoring

    Science.gov (United States)

    Bartsch, A.; Doubkova, M.; Pathe, C.; Sabel, D.; Wagner, W.

    2007-12-01

    The Okavango Delta of northern Botswana is a fast-changing system of canals and floodplains which serves as an important wetland habitat. The area of the wetland is highly dependent on local source of precipitation as well as on external inflow from the upper Okavango River. The Advanced Synthetic Aperture Radar (ASAR) is an active remote sensing instrument onboard ENVISAT platform operating at C-band. The data from the ASAR Global ScanSAR Mode (GM) have amply demonstrated the ability for inland wetland monitoring as well as for near surface soil moisture derivation. The processing chain for ENVISAT derived soil moisture was setup within the ESA Tiger DUE Innovator project SHARE for hydrometeorological applications in the Southern African Development Community (SADC). The ASAR GM provides up to weekly samples of the Okavango delta with 1 km spatial resolution. The extent of the Okavango Delta wetlands is derived from the ENVISAT ASAR GM data applying threshold of absolute backscatter values. The relations of the wetland size, river discharge, and the relative mean soil moisture in the upper Okavango catchment are studied. Correlation above 0.9 can be observed between the relative mean soil moisture and river discharge. High dependence of the wetland extent on the relative mean soil moisture in the upper Okavango is also clearly evident. With this work we demonstrate that the relative soil moisture derived from the ENVISAT ASAR GM data can be clearly related to the river discharge measurements in subtropic environments. Additionally, we show the ability of ENVISAT ASAR Global Mode to monitor dynamics of wetland areas as a response to the relative soil moisture in the upper Okavango catchment. This allows for prediction of the wetland extent up to six months in advance. An incorporation of spatially improved soil moisture and wetland products may improve prediction models for the wetland region.

  4. Effects of land preparation and plantings of vegetation on soil moisture in a hilly loess catchment in China

    NARCIS (Netherlands)

    Tianjiao, Feng; Wei, Wei; Liding, Chen; Keesstra, Saskia D.; Yang, Yu

    2018-01-01

    In the dryland and degraded regions, soil moisture is the primary factor determining ecological restoration. Proper land preparations and vegetation restoration can improve soil moisture and benefit land restoration. Identifying their effects on soil moisture is thus essential for developing

  5. Seasonal soil moisture patterns in contrasting habitats in the Willamette Valley, Oregon

    Science.gov (United States)

    Changing seasonal soil moisture 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 soil moisture regimes is necessary. The primary objective...

  6. SMEX02 Sliced Core Soil Moisture Data, Walnut Creek Watershed, Iowa

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set includes sliced soil core moisture data collected during the Soil Moisture Experiment 2002 (SMEX02), conducted during June and July 2002 in the Walnut...

  7. Spatial and temporal structure within moisture measurements of a stormwater control system

    Science.gov (United States)

    Moisture sensing is a mature soil research technology commonly applied to agriculture. Such sensors may be appropriated for use in novel stormwater research applications. Knowledge of moisture (with respect to space and time) in infiltration based stormwater control measures (SCM...

  8. Quantifying the effects of soil temperature, moisture and sterilization on elemental mercury formation in boreal soils.

    Science.gov (United States)

    Pannu, Ravinder; Siciliano, Steven D; O'Driscoll, Nelson J

    2014-10-01

    Soils are a source of elemental mercury (Hg(0)) to the atmosphere, however the effects of soil temperature and moisture on Hg(0) formation is not well defined. This research quantifies the effect of varying soil temperature (278-303 K), moisture (15-80% water filled pore space (WFPS)) and sterilization on the kinetics of Hg(0) formation in forested soils of Nova Scotia, Canada. Both, the logarithm of cumulative mass of Hg(0) formed in soils and the reduction rate constants (k values) increased with temperature and moisture respectively. Sterilizing soils significantly (p soils and our results highlight two key processes: (i) a fast abiotic process that peaks at 45% WFPS and depletes a small pool of Hg(0) and; (ii) a slower, rate limiting biotic process that generates a large pool of reducible Hg(II). Copyright © 2014 Elsevier Ltd. All rights reserved.

  9. Effects of Soil Moisture on the Temperature Sensitivity of Soil Heterotrophic Respiration: A Laboratory Incubation Study

    Science.gov (United States)

    Zhou, Weiping; Hui, Dafeng; Shen, Weijun

    2014-01-01

    The temperature sensitivity (Q10) of soil heterotrophic respiration (Rh) is an important ecological model parameter and may vary with temperature and moisture. While Q10 generally decreases with increasing temperature, the moisture effects on Q10 have been controversial. To address this, we conducted a 90-day laboratory incubation experiment using a subtropical forest soil with a full factorial combination of five moisture levels (20%, 40%, 60%, 80%, and 100% water holding capacity - WHC) and five temperature levels (10, 17, 24, 31, and 38°C). Under each moisture 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 soil nutrients were also measured several times to detect their potential contributions to the moisture-induced Q10 variation. We found that Q10 was significantly lower at lower moisture levels (60%, 40% and 20% WHC) than at higher moisture 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 moisture levels during the late stage of incubation. In contrast, soil 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 moisture-induced Q10 changes. This study implies that global warming’s impacts on soil CO2 emission may depend upon soil moisture conditions. With the same temperature rise, wetter soils may emit more CO2 into the atmosphere via heterotrophic respiration. PMID:24647610

  10. Confronting Weather and Climate Models with Observational Data from Soil Moisture Networks over the United States

    Science.gov (United States)

    Dirmeyer, Paul A.; Wu, Jiexia; Norton, Holly E.; Dorigo, Wouter A.; Quiring, Steven M.; Ford, Trenton W.; Santanello, Joseph A., Jr.; Bosilovich, Michael G.; Ek, Michael B.; Koster, Randal Dean; hide

    2016-01-01

    Four land surface models in uncoupled and coupled configurations are compared to observations of daily soil moisture from 19 networks in the conterminous United States to determine the viability of such comparisons and explore the characteristics of model and observational data. First, observations are analyzed for error characteristics and representation of spatial and temporal variability. Some networks have multiple stations within an area comparable to model grid boxes; for those we find that aggregation of stations before calculation of statistics has little effect on estimates of variance, but soil moisture memory is sensitive to aggregation. Statistics for some networks stand out as unlike those of their neighbors, likely due to differences in instrumentation, calibration and maintenance. Buried sensors appear to have less random error than near-field remote sensing techniques, and heat dissipation sensors show less temporal variability than other types. Model soil moistures are evaluated using three metrics: standard deviation in time, temporal correlation (memory) and spatial correlation (length scale). Models do relatively well in capturing large-scale variability of metrics across climate regimes, but poorly reproduce observed patterns at scales of hundreds of kilometers and smaller. Uncoupled land models do no better than coupled model configurations, nor do reanalyses out perform free-running models. Spatial decorrelation scales are found to be difficult to diagnose. Using data for model validation, calibration or data assimilation from multiple soil moisture networks with different types of sensors and measurement techniques requires great caution. Data from models and observations should be put on the same spatial and temporal scales before comparison.

  11. Soil microbial community responses to antibiotic-contaminated manure under different soil moisture regimes.

    Science.gov (United States)

    Reichel, Rüdiger; Radl, Viviane; Rosendahl, Ingrid; Albert, Andreas; Amelung, Wulf; Schloter, Michael; Thiele-Bruhn, Sören

    2014-01-01

    Sulfadiazine (SDZ) is an antibiotic frequently administered to livestock, and it alters microbial communities when entering soils 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 soil moisture. Here, we hypothesized that the effects of SDZ on soil microbial communities will be modulated depending on the soil moisture conditions. To test this hypothesis, we performed a 49-day fully controlled climate chamber pot experiments with soil grown with Dactylis glomerata (L.). Manure-amended pots without or with SDZ contamination were incubated under a dynamic moisture regime (DMR) with repeated drying and rewetting changes of >20 % maximum water holding capacity (WHCmax) in comparison to a control moisture regime (CMR) at an average soil moisture 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 soils relative to the CMR ones, indicating that dynamic moisture changes accelerate the susceptibility of the soil microbial community to antibiotics.

  12. The Raam regional soil moisture monitoring network in the Netherlands

    Science.gov (United States)

    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

    2018-01-01

    We have established a soil moisture 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 soil 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 soil moisture 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 soil moisture and soil 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). Soil-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 soil-specific calibration of the sensors, the first year of measurements, and additional measurements (soil temperature, phreatic groundwater levels and meteorological data) and information (elevation, soil physical characteristics, land cover and a geohydrological model) available for performing scientific research. The data are available at https://doi.org/10.4121/uuid:dc364e97-d44a-403f-82a7-121902deeb56.

  13. A Smart Irrigation Approach Aided by Monitoring Surface Soil Moisture using Unmanned Aerial Vehicles

    Science.gov (United States)

    Wienhold, K. J.; Li, D.; Fang, N. Z.

    2017-12-01

    Soil moisture is a critical component in the optimization of irrigation scheduling in water resources management. Unmanned Aerial Vehicles (UAV) equipped with multispectral sensors represent an emerging technology capable of detecting and estimating soil moisture for irrigation and crop management. This study demonstrates a method of using a UAV as an optical and thermal remote sensing platform combined with genetic programming to derive high-resolution, surface soil moisture (SSM) estimates. The objective is to evaluate the feasibility of spatially-variable irrigation management for a golf course (about 50 acres) in North Central Texas. Multispectral data is collected over the course of one month in the visible, near infrared and longwave infrared spectrums using a UAV capable of rapid and safe deployment for daily estimates. The accuracy of the model predictions is quantified using a time domain reflectometry (TDR) soil moisture sensor and a holdout validation test set. The model produces reasonable estimates for SSM with an average coefficient of correlation (r) = 0.87 and coefficient of determination of (R2) = 0.76. The study suggests that the derived SSM estimates be used to better inform irrigation scheduling decisions for lightly vegetated areas such as the turf or native roughs found on golf courses.

  14. Soil Moisture Initialization Error and Subgrid Variability of Precipitation in Seasonal Streamflow Forecasting

    Science.gov (United States)

    Koster, Randal D.; Walker, Gregory K.; Mahanama, Sarith P.; Reichle, Rolf H.

    2013-01-01

    Offline simulations over the conterminous United States (CONUS) with a land surface model are used to address two issues relevant to the forecasting of large-scale seasonal streamflow: (i) the extent to which errors in soil moisture initialization degrade streamflow forecasts, and (ii) the extent to which a realistic increase in the spatial resolution of forecasted precipitation would improve streamflow forecasts. The addition of error to a soil moisture initialization field is found to lead to a nearly proportional reduction in streamflow forecast skill. The linearity of the response allows the determination of a lower bound for the increase in streamflow forecast skill achievable through improved soil moisture estimation, e.g., through satellite-based soil moisture measurements. An increase in the resolution of precipitation is found to have an impact on large-scale streamflow forecasts only when evaporation variance is significant relative to the precipitation variance. This condition is met only in the western half of the CONUS domain. Taken together, the two studies demonstrate the utility of a continental-scale land surface modeling system as a tool for addressing the science of hydrological prediction.

  15. Investigating soil moisture-climate interactions with prescribed soil moisture experiments: an assessment with the Community Earth System Model (version 1.2)

    Science.gov (United States)

    Hauser, Mathias; Orth, René; Seneviratne, Sonia I.

    2017-04-01

    Land surface hydrology is an important control of surface weather and climate. A valuable technique to investigate this link is the prescription of soil moisture in land surface models, which leads to a decoupling of the atmosphere and land processes. Diverse approaches to prescribe soil moisture, as well as different prescribed soil moisture conditions have been used in previous studies. Here, we compare and assess four methodologies to prescribe soil moisture and investigate the impact of two different estimates of the climatological seasonal cycle used to prescribe soil moisture. Our analysis shows that, though in appearance similar, the different approaches require substantially different long-term moisture inputs and lead to different temperature signals. The smallest influence on temperature and the water balance is found when prescribing the median seasonal cycle of deep soil liquid water, whereas the strongest signal is found when prescribing soil liquid and soil ice using the mean seasonal cycle. These results indicate that induced net water-balance perturbations in experiments investigating soil moisture-climate coupling are important contributors to the climate response, in addition to the intended impact of the decoupling. These results help to guide the set-up of future experiments prescribing soil moisture, as for instance planned within the Land Surface, Snow and Soil Moisture Model Intercomparison Project (LS3MIP).

  16. Intercomparison of AMSR2 and AMSR-E Soil Moisture Retrievals with MERRA-L data set over Australia

    Science.gov (United States)

    Cho, E.; Choi, M.; Su, C. H.; Ryu, D.; Kim, H.; Jacobs, J. M.

    2015-12-01

    Soil moisture is an important variable in the hydrological cycle on the land surface and plays an essential role in hydrological and meteorological processes. The Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) sensor on board the Aqua satellite offered valuable soil moisture data set from June 2002 and October 2011 and has been used in a wide range of applications. However, the AMSR-E sensor stopped operation from 4 October 2011 due to a problem with its antenna. AMSR-E was replaced by the Advanced Microwave Scanning Radiometer 2 (AMSR2) on the Global Climate Change Observation Mission 1 - Water (GCOM-W1) satellite in May 2012. Assessment of AMSR2 soil moisture retrievals as compared to AMSR-E has not yet been extensively evaluated. This task is critical if AMSR2 soil moisture products are used as a continuous dataset continuing the legacy of AMSR-E. The purpose of this study is to inter-compare AMSR2 and AMSR-E microwave based soil moisture over Australia, mediated by using model-based soil moisture data set to determine statistically similar inter-comparison periods from time periods of the individual sensors. This work use NASA-VUA AMSR2 and AMSR-E based soil moisture products derived by the Land Parameter Retrieval Model (LPRM) and the modelled soil moisture from NASA's MERRA-L (Modern Era Retrospective-analysis for Research and Applications-Land) re-analysis. The satellite soil moisture products are compared against the MERRA-L using traditional metrics, and the random errors in individual products are estimated using lagged instrumental variable regression analysis. Generally, the results demonstrate that the two satellite-based soil moisture retrievals have reasonable agreement with MERRA-L soil moisture data set. The error differences are notable, with the zonal error statistics are higher for AMSR2 in all climate zones, though the error maps of AMSR2 and AMSR-E are spatially similar over the Australia regions. This study leads

  17. Examining the relationship between intermediate scale soil moisture and terrestrial evaporation within a semi-arid grassland

    KAUST Repository

    Jana, Raghavendra Belur

    2016-05-17

    Interactions between soil moisture and terrestrial evaporation affect water cycle behaviour and responses between the land surface and the atmosphere across scales. With strong heterogeneities at the land surface, the inherent spatial variability in soil moisture makes its representation via point-scale measurements challenging, resulting in scale-mismatch when compared to coarser-resolution satellite-based soil moisture or evaporation estimates. The Cosmic Ray Soil Moisture Observing System (COSMOS) was developed to address such issues in the measurement and representation of soil moisture at intermediate scales. Here we present an examination of the links observed between COSMOS soil moisture retrievals and evaporation estimates over a pasture in the semi-arid central-west region of New South Wales, Australia. The COSMOS soil moisture product was compared to evaporation derived from three distinct approaches, including the Priestley-Taylor (PT-JPL), Penman-Monteith (PM-Mu) and Surface Energy Balance System (SEBS) models, driven by forcing data from local meteorological station data and remote sensing retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. Pearson’s Correlations, Quantile-Quantile (Q-Q) plots, and Analysis of Variance (ANOVA) were used to qualitatively and quantitatively evaluate the temporal distributions of soil moisture and evaporation over the study site. The relationships were examined against nearly two years of observation data, as well as for different seasons and for defined periods of analysis. Results highlight that while direct correlations of raw data were not particularly instructive, the Q-Q plots and ANOVA illustrate that the root-zone soil moisture represented by the COSMOS measurements and the modelled evaporation estimates reflect similar distributions under most meteorological conditions. The PT-JPL and PM-Mu model estimates performed contrary to expectation when high soil moisture and cold

  18. Examining the relationship between intermediate-scale soil moisture and terrestrial evaporation within a semi-arid grassland

    KAUST Repository

    Jana, Raghavendra B.

    2016-09-30

    Interactions between soil moisture and terrestrial evaporation affect water cycle behaviour and responses between the land surface and the atmosphere across scales. With strong heterogeneities at the land surface, the inherent spatial variability in soil moisture makes its representation via point-scale measurements challenging, resulting in scale mismatch when compared to coarser-resolution satellite based soil moisture or evaporation estimates. The Cosmic Ray Neutron Probe (CRNP) was developed to address such issues in the measurement and representation of soil moisture at intermediate scales. Here, we present a study to assess the utility of CRNP soil moisture observations in validating model evaporation estimates. The CRNP soil moisture product from a pasture in the semi-arid central west region of New South Wales, Australia, was compared to evaporation derived from three distinct approaches, including the Priestley–Taylor (PT-JPL), Penman–Monteith (PM-Mu), and Surface Energy Balance System (SEBS) models, driven by forcing data from local meteorological station data and remote sensing retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. Pearson’s correlations, quantile–quantile (Q–Q) plots, and analysis of variance (ANOVA) were used to qualitatively and quantitatively evaluate the temporal distributions of soil moisture and evaporation over the study site. The relationships were examined against nearly 2 years of observation data, as well as for different seasons and for defined periods of analysis. Results highlight that while direct correlations of raw data were not particularly instructive, the Q–Q plots and ANOVA illustrate that the root-zone soil moisture represented by the CRNP measurements and the modelled evaporation estimates reflect similar distributions under most meteorological conditions. The PT-JPL and PM-Mu model estimates performed contrary to expectation when high soil moisture and cold temperatures were

  19. Examining the relationship between intermediate-scale soil moisture and terrestrial evaporation within a semi-arid grassland

    Directory of Open Access Journals (Sweden)

    R. B. Jana

    2016-09-01

    Full Text Available Interactions between soil moisture and terrestrial evaporation affect water cycle behaviour and responses between the land surface and the atmosphere across scales. With strong heterogeneities at the land surface, the inherent spatial variability in soil moisture makes its representation via point-scale measurements challenging, resulting in scale mismatch when compared to coarser-resolution satellite-based soil moisture or evaporation estimates. The Cosmic Ray Neutron Probe (CRNP was developed to address such issues in the measurement and representation of soil moisture at intermediate scales. Here, we present a study to assess the utility of CRNP soil moisture observations in validating model evaporation estimates. The CRNP soil moisture product from a pasture in the semi-arid central west region of New South Wales, Australia, was compared to evaporation derived from three distinct approaches, including the Priestley–Taylor (PT-JPL, Penman–Monteith (PM-Mu, and Surface Energy Balance System (SEBS models, driven by forcing data from local meteorological station data and remote sensing retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS sensor. Pearson's correlations, quantile–quantile (Q–Q plots, and analysis of variance (ANOVA were used to qualitatively and quantitatively evaluate the temporal distributions of soil moisture and evaporation over the study site. The relationships were examined against nearly 2 years of observation data, as well as for different seasons and for defined periods of analysis. Results highlight that while direct correlations of raw data were not particularly instructive, the Q–Q plots and ANOVA illustrate that the root-zone soil moisture represented by the CRNP measurements and the modelled evaporation estimates reflect similar distributions under most meteorological conditions. The PT-JPL and PM-Mu model estimates performed contrary to expectation when high soil moisture and cold

  20. Development of long-wave microwave satellite systems for measuring soil moisture

    Science.gov (United States)

    Engman, Edwin T.

    1998-12-01

    The science need for remotely sensed soil moisture has been well established in the hydrologic, climate change and weather forecasting communities. There also have been a number of programs that have demonstrated the feasibility of using long wave microwave sensors for estimating soil moisture. These have ranged from truck mounted sensors, to intensive airborne campaigns with science objectives. Based on this history of truck and aircraft experiments, the science community has settled on a soil moisture product that meets the following criteria: a two day global repeat, a measured layer of 5 cm of soil, a footprint of 20 to 30 km, and an absolute accuracy of plus or minus 4% volumetric soil moisture. The principal sensor to accomplish this is an L-band passive microwave radiometer. A soil moisture mission is being proposed for the NASA Earth Systems Science Pathfinder (ESSP) mission which has very real constraints of a limited budget which includes the launch vehicle, and a three year award to launch time schedule. Within the past few years there have been a number of mission concepts proposed that meet the challenge of getting a very large antenna in space in order to realize a spatial resolution on the ground that meets the science and applications needs. This paper describes some of the alternative concepts considered to meet these unusual requirements and the ways to solve the very large antenna challenge, and the criteria used to choose the final design for an ESSP proposal. The paper also discusses the alternatives considered to obtain the necessary ancillary data for characterizing the surface roughness, the surface temperature and the attenuation affects of vegetation.

  1. Regulation of Microbial Herbicide Transformation by Coupled Moisture and Oxygen Dynamics in Soil

    Science.gov (United States)

    Marschmann, G.; Pagel, H.; Uksa, M.; Streck, T.; Milojevic, T.; Rezanezhad, F.; Van Cappellen, P.

    2017-12-01

    The key processes of herbicide fate in agricultural soils are well-characterized. However, most of these studies are from batch experiments that were conducted under optimal aerobic conditions. In order to delineate the processes controlling herbicide (i.e., phenoxy herbicide 2-methyl-4-chlorophenoxyacetic acid, MCPA) turnover in soil under variable moisture conditions, we conducted a state-of-the-art soil column experiment, with a highly instrumented automated soil column system, under constant and oscillating water table regimes. In this system, the position of the water table was imposed using a computer-controlled, multi-channel pump connected to a hydrostatic equilibrium reservoir and a water storage reservoir. The soil samples were collected from a fertilized, arable and carbon-limited agricultural field site in Germany. The efflux of CO2 was determined from headspace gas measurements as an integrated signal of microbial respiration activity. Moisture and oxygen profiles along the soil column were monitored continuously using high-resolution moisture content probes and luminescence-based Multi Fiber Optode (MuFO) microsensors, respectively. Pore water and solid-phase samples were collected periodically at 8 depths and analyzed for MCPA, dissolved inorganic and organic carbon concentrations as well as the abundance of specific MCPA-degrading bacteria. The results indicated a clear effect of the water table fluctuations on CO2 fluxes, with lower fluxes during imbibition periods and enhanced CO2 fluxes after drainage. In this presentation, we focus on the results of temporal changes in the vertical distribution of herbicide, specific herbicide degraders, organic carbon concentration, moisture content and oxygen. We expect that the high spatial and temporal resolution of measurements from this experiment will allow robust calibration of a reactive transport model for the soil columns, with subsequent identification and quantification of rate limiting processes of

  2. Identification of optimal soil hydraulic functions and parameters for predicting soil moisture

    Science.gov (United States)

    We examined the accuracy of several commonly used soil hydraulic functions and associated parameters for predicting observed soil moisture data. We used six combined methods formed by three commonly used soil hydraulic functions – i.e., Brooks and Corey (1964) (BC), Campbell (19...

  3. Influence of soil moisture content on surface albedo and soil thermal ...

    Indian Academy of Sciences (India)

    atively longer memory of soil moisture in com- parison with the variation of controlling parame- ters often leads to climatic ... and vegetation cover changes the soil colour and thus varies the surface albedo (Todd and Hoffer. 1998). .... The colour of the soil at the experimental site varied from dark brown to dark reddish brown.

  4. Using soil temperature and moisture to predict forest soil nitrogen mineralization

    Science.gov (United States)

    Jennifer D. Knoepp; Wayne T. Swank

    2002-01-01

    Due to the importance of N in forest productivity ecosystem and nutrient cycling research often includes measurement of soil N transformation rates as indices of potential availability and ecosystem losses of N. We examined the feasibility of using soil temperature and moisture content to predict soil N mineralization rates (Nmin) at the Coweeta Hydrologic Laboratory...

  5. Rainfall estimation by inverting SMOS soil moisture estimates: a comparison of different methods over Australia

    Science.gov (United States)

    Remote sensing of soil moisture 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 soil moisture product from the European Space Agency’s Soil Moisture and Ocean Salinity (SMOS) is used...

  6. A soil moisture and temperature network for SMOS validation in Western Denmark

    DEFF Research Database (Denmark)

    Bircher, Simone; Skou, Niels; Jensen, K. H.

    2011-01-01

    The Soil Moisture and Ocean Salinity Mission (SMOS) acquires surface soil moisture data globally, and thus product validation for a range of climate and environmental conditions across continents is a crucial step. For this purpose, a soil moisture and temperature network of Decagon ECH2O 5TE...

  7. Evaluation of SMOS soil moisture products over the CanEx-SM10 area

    Science.gov (United States)

    The Soil Moisture and Ocean Salinity (SMOS) Earth observation satellite was launched in November 2009 to provide global soil moisture and ocean salinity measurements based on L-Band passive microwave measurements. Since its launch, different versions of SMOS soil moisture products processors have be...

  8. A simple interpretation of the surface tenperature/vegetation index space for assessment of soil moisture status

    DEFF Research Database (Denmark)

    Sandholt, Inge; Andersen, J.; Rasmussen, Kjeld

    2002-01-01

    Remote Sensing, soil moisture, surface temperature, vegetation index, hydrology, Africa, Senegal, semiarid......Remote Sensing, soil moisture, surface temperature, vegetation index, hydrology, Africa, Senegal, semiarid...

  9. Microwave brightness temperature and thermal inertia - towards synergistic method of high-resolution soil moisture retrieval

    Science.gov (United States)

    Lukowski, Mateusz; Usowicz, Boguslaw; Sagan, Joanna; Szlazak, Radoslaw; Gluba, Lukasz; Rojek, Edyta

    2017-04-01

    Soil moisture is an important parameter in many environmental studies, as it influences the exchange of water and energy at the interface between the land surface and the atmosphere. Accurate assessment of the soil moisture spatial and temporal variations is crucial for numerous studies; starting from a small scale of single field, then catchment, mesoscale basin, ocean conglomeration, finally ending at the global water cycle. Despite numerous advantages, such as fine accuracy (undisturbed by clouds or daytime conditions) and good temporal resolution, passive microwave remote sensing of soil moisture, e.g. SMOS and SMAP, are not applicable to a small scale - simply because of too coarse spatial resolution. On the contrary, thermal infrared-based methods of soil moisture retrieval have a good spatial resolution, but are often disturbed by clouds and vegetation interferences or night effects. The methods that base on point measurements, collected in situ by monitoring stations or during field campaigns, are sometimes called "ground truth" and may serve as a reference for remote sensing, of course after some up-scaling and approximation procedures that are, unfortunately, potential source of error. Presented research concern attempt to synergistic approach that join two remote sensing methods: passive microwave and thermal infrared, supported by in situ measurements. Microwave brightness temperature of soil was measured by ELBARA, the radiometer at 1.4 GHz frequency, installed at 6 meters high tower at Bubnow test site in Poland. Thermal inertia around the tower was modelled using the statistical-physical model whose inputs were: soil physical properties, its water content, albedo and surface temperatures measured by an infrared pyrometer, directed at the same footprint as ELBARA. The results coming from this method were compared to in situ data obtained during several field campaigns and by the stationary agrometeorological stations. The approach seems to be

  10. Soil Moisture Estimation Using MODIS Images (Case Study: Mashhad Plain Area

    Directory of Open Access Journals (Sweden)

    M. Fashaee

    2016-09-01

    area is selected in the Mashhad plain in Khorasan Razavi province of I.R. Iran. Study area is about 1,200 square kilometers and is located around the Golmakan center of agricultural research. In this study, water deficit index (WDI was zoning by MODIS images in subset of Mashhad plain during water year of 2011-2012. Then, based on the close relationship between WDI and soil moisture parameter, a linear relationship between these two parameters were fitted. Soil moisture is measured by the TDR and every 7 days at 5 depths of 5, 10, 20, 30 and 50 cm from the surface. Remote Sensing (RS technology used as a tool for providing some of the data that is required. The moderate resolution imaging spectroradiometer (MODIS instrument is popular for monitoring soil moisture because of its high spectral (36 bands resolution, moderate spatial (250–1000 m resolution and various products for land surface properties. MODIS products used in the present study include: MOD09A1 land surface albedo data, MOD11A1 land surface temperature data, and MOD13A1 vegetation data. Using ArcMap 9.2 and ERDAS IMAGINE 2010 softwares, WDI was calculated pixel by pixel for 18 days (non-cloudy days and simultaneous with measurement of soil moisture at the station. Results and Discussion: The results showed that the northeastern region is predominantly rainfed and irrigated farmlands are under water stress. Conversely, the southwestern part of the area is mountainous with less water stress. Based on NDVI, there is also less crop cover in the southwestern part of the region during the year. The results showed that about 44% of the index values are in the range of 0.2-0.3. Then about 22% of the index values are in the range of 0.3-0.4. Thus it can be concluded that over 66% of the index values are in the range of 0.2-0.4. According to the maximum index value (WDI=0.59 on the 201th day of year and the minimum values (WDI=0.0004 on the 129th day of year during the time period of study, it seems that water

  11. Soil moisture effects during bioventing in fuel-contaminated arid soils

    International Nuclear Information System (INIS)

    Zwick, T.C.; Leeson, A.; Hinchee, R.E.; Hoeppel, R.E.; Bowling, L.

    1995-01-01

    This study evaluated the effects of soil moisture addition on microbial activity during bioventing of dry, sandy soils at the Marine Corps Air Ground Combat Center (MCAGCC), Twentynine Palms, California. Soils at the site have been contaminated to a depth of approximately 80 ft (24 m) with gasoline, JP-5 jet fuel, and diesel fuel. Based on the low soil moisture measured at the site (2 to 3% by weight), it was determined that soil moisture may be limiting biodegradation. To evaluate the effect that moisture addition had on microbial activity under field conditions, a subsurface drip irrigation system was installed above the fuel hydrocarbon plume. Irrigation water was obtained from two monitoring wells on the site, where groundwater was approximately 192 ft (59 m) below ground surface. Advancement of the wetting front was monitored. In situ respiration rates increased significantly after moisture addition. The results of this study provide evidence for the potential applicability of moisture addition in conjunction with bioventing for site remediation in arid environments. Further work is planned to investigate optimization of moisture addition

  12. Data Assimilation to Extract Soil Moisture Information from SMAP Observations

    Directory of Open Access Journals (Sweden)

    Jana Kolassa

    2017-11-01

    Full Text Available 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 National Aeronautics and Space Administration (NASA Catchment model over the contiguous United States for April 2015 to March 2017. By construction, the NN retrievals are consistent with the global climatology of the Catchment model soil moisture. Assimilating the NN retrievals without further bias correction improved the surface and root zone correlations against in situ measurements from 14 SMAP core validation sites (CVS by 0.12 and 0.16, respectively, over the model-only skill, and reduced the surface and root zone unbiased root-mean-square error (ubRMSE by 0.005 m 3 m − 3 and 0.001 m 3 m − 3 , respectively. The assimilation reduced the average absolute surface bias against the CVS measurements by 0.009 m 3 m − 3 , but increased the root zone bias by 0.014 m 3 m − 3 . Assimilating the NN retrievals after a localized bias correction yielded slightly lower surface correlation and ubRMSE improvements, but generally the skill differences were small. The assimilation of the physically-based SMAP Level-2 passive soil moisture retrievals using a global bias correction yielded similar skill improvements, as did the direct assimilation of locally bias-corrected SMAP brightness temperatures within the SMAP Level-4 soil moisture algorithm. The results show that global bias correction methods may be able to extract more independent information from SMAP observations compared to local bias correction methods, but without accurate quality control and observation error characterization they are also more vulnerable to adverse effects from retrieval errors related to uncertainties in the retrieval inputs and algorithm. Furthermore, the results show that using global bias correction approaches without a

  13. Seasonal soil moisture and drought occurrence in Europe in CMIP5 projections for the 21st century

    Science.gov (United States)

    Ruosteenoja, Kimmo; Markkanen, Tiina; Venäläinen, Ari; Räisänen, Petri; Peltola, Heli

    2018-02-01

    Projections for near-surface soil moisture content in Europe for the 21st century were derived from simulations performed with 26 CMIP5 global climate models (GCMs). Two Representative Concentration Pathways, RCP4.5 and RCP8.5, were considered. Unlike in previous research in general, projections were calculated separately for all four calendar seasons. To make the moisture contents simulated by the various GCMs commensurate, the moisture data were normalized by the corresponding local maxima found in the output of each individual GCM. A majority of the GCMs proved to perform satisfactorily in simulating the geographical distribution of recent soil moisture in the warm season, the spatial correlation with an satellite-derived estimate varying between 0.4 and 0.8. In southern Europe, long-term mean soil moisture is projected to decline substantially in all seasons. In summer and autumn, pronounced soil drying also afflicts western and central Europe. In northern Europe, drying mainly occurs in spring, in correspondence with an earlier melt of snow and soil frost. The spatial pattern of drying is qualitatively similar for both RCP scenarios, but weaker in magnitude under RCP4.5. In general, those GCMs that simulate the largest decreases in precipitation and increases in temperature and solar radiation tend to produce the most severe soil drying. Concurrently with the reduction of time-mean soil moisture, episodes with an anomalously low soil moisture, occurring once in 10 years in the recent past simulations, become far more common. In southern Europe by the late 21st century under RCP8.5, such events would be experienced about every second year.

  14. Soil moisture mapping at Bubnow Wetland using L-band radiometer (ELBARA III)

    Science.gov (United States)

    Łukowski, Mateusz; Schwank, Mike; Szlązak, Radosław; Wiesmann, Andreas; Marczewski, Wojciech; Usowicz, Bogusław; Usowicz, Jerzy; Rojek, Edyta; Werner, Charles

    2016-04-01

    The study of soil moisture is a scientific challenge. Not only because of large diversity of soils and differences in their water content, but also due to the difficulty of measuring, especially in large scale. On this field of interest several methods to determine the content of water in soil exists. The basic and referential is gravimetric method, which is accurate, but suitable only for small spatial scales and time-consuming. Indirect methods are faster, but need to be validated, for example those based on dielectric properties of materials (e.g. time domain reflectometry - TDR) or made from distance (remote), like brightness temperature measurements. Remote sensing of soil moisture can be performed locally (from towers, drones, planes etc.) or globally (satellites). These techniques can complement and help to verify different models and assumptions. In our studies, we applied spatial statistics to local soil moisture mapping using ELBARA III (ESA L-band radiometer, 1.4 GHz) mounted on tower (6.5 meter height). Our measurements were carried out in natural Bubnow Wetland, near Polesie National Park (Eastern Poland), during spring time. This test-site had been selected because it is representative for one of the biggest wetlands in Europe (1400 km2), called "Western Polesie", localized in Ukraine, Poland and Belarus. We have investigated Bubnow for almost decade, using meteorological and soil moisture stations, conducting campaigns of hand-held measurements and collecting soil samples. Now, due to the possibility of rotation at different incidence angles (as in previous ELBARA systems) and the new azimuth tracking capabilities, we obtained brightness temperature data not only at different distances from the tower, but also around it, in footprints containing different vegetation and soil types. During experiment we collected data at area about 450 m2 by rotating ELBARA's antenna 5-175° in horizontal and 30-70° in vertical plane. This type of approach allows

  15. Rainfall estimation by inverting SMOS soil moisture estimates: A comparison of different methods over Australia

    Science.gov (United States)

    Brocca, Luca; Pellarin, Thierry; Crow, Wade T.; Ciabatta, Luca; Massari, Christian; Ryu, Dongryeol; Su, Chun-Hsu; Rüdiger, Christoph; Kerr, Yann

    2016-10-01

    Remote sensing of soil moisture 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 soil moisture product from the Soil Moisture and Ocean Salinity (SMOS) satellite is used for improving satellite rainfall estimates obtained from the Tropical Rainfall Measuring Mission multisatellite precipitation analysis product (TMPA) using three different "bottom up" techniques: SM2RAIN, Soil Moisture Analysis Rainfall Tool, and Antecedent Precipitation Index Modification. The implementation of these techniques aims at improving the well-known "top down" rainfall estimate derived from TMPA products (version 7) available in near real time. Ground observations provided by the Australian Water Availability Project are considered as a separate validation data set. The three algorithms are calibrated against the gauge-corrected TMPA reanalysis product, 3B42, and used for adjusting the TMPA real-time product, 3B42RT, using SMOS soil moisture data. The study area covers the entire Australian continent, and the analysis period ranges from January 2010 to November 2013. Results show that all the SMOS-based rainfall products improve the performance of 3B42RT, even at daily time scale (differently from previous investigations). The major improvements are obtained in terms of estimation of accumulated rainfall with a reduction of the root-mean-square error of more than 25%. Also, in terms of temporal dynamic (correlation) and rainfall detection (categorical scores) the SMOS-based products provide slightly better results with respect to 3B42RT, even though the relative performance between the methods is not always the same. The strengths and weaknesses of each algorithm and the spatial variability of their performances are identified in order to indicate the ways forward for this promising research activity. Results show that the integration of bottom up and top down approaches

  16. Assimilation of ASCAT near-surface soil moisture into the French SIM hydrological model

    Science.gov (United States)

    Draper, C.; Mahfouf, J.-F.; Calvet, J.-C.; Martin, E.; Wagner, W.

    2011-06-01

    The impact of assimilating near-surface soil moisture into the SAFRAN-ISBA-MODCOU (SIM) hydrological model over France is examined. Specifically, the root-zone soil moisture in the ISBA land surface model is constrained over three and a half years, by assimilating the ASCAT-derived surface degree of saturation product, using a Simplified Extended Kalman Filter. In this experiment ISBA is forced with the near-real time SAFRAN analysis, which analyses the variables required to force ISBA from relevant observations available before the real time data cut-off. The assimilation results are tested against ISBA forecasts generated with a higher quality delayed cut-off SAFRAN analysis. Ideally, assimilating the ASCAT data will constrain the ISBA surface state to correct for errors in the near-real time SAFRAN forcing, the most significant of which was a substantial dry bias caused by a dry precipitation bias. The assimilation successfully reduced the mean root-zone soil moisture bias, relative to the delayed cut-off forecasts, by close to 50 % of the open-loop value. The improved soil moisture in the model then led to significant improvements in the forecast hydrological cycle, reducing the drainage, runoff, and evapotranspiration biases (by 17 %, 11 %, and 70 %, respectively). When coupled to the MODCOU hydrogeological model, the ASCAT assimilation also led to improved streamflow forecasts, increasing the mean discharge ratio, relative to the delayed cut off forecasts, from 0.68 to 0.76. These results demonstrate that assimilating near-surface soil moisture observations can effectively constrain the SIM model hydrology, while also confirming the accuracy of the ASCAT surface degree of saturation product. This latter point highlights how assimilation experiments can contribute towards the difficult issue of validating remotely sensed land surface observations over large spatial scales.

  17. Improving runoff prediction through the assimilation of the ASCAT soil moisture product

    Directory of Open Access Journals (Sweden)

    L. Brocca

    2010-10-01

    Full Text Available The role and the importance of soil moisture for meteorological, agricultural and hydrological applications is widely known. Remote sensing offers the unique capability to monitor soil moisture over large areas (catchment scale with, nowadays, a temporal resolution suitable for hydrological purposes. However, the accuracy of the remotely sensed soil moisture estimates has to be carefully checked. The validation of these estimates with in-situ measurements is not straightforward due the well-known problems related to the spatial mismatch and the measurement accuracy. The analysis of the effects deriving from assimilating remotely sensed soil moisture data into hydrological or meteorological models could represent a more valuable method to test their reliability. In particular, the assimilation of satellite-derived soil moisture estimates into rainfall-runoff models at different scales and over different regions represents an important scientific and operational issue.

    In this study, the soil wetness index (SWI product derived from the Advanced SCATterometer (ASCAT sensor onboard of the Metop satellite was tested. The SWI was firstly compared with the soil moisture temporal pattern derived from a continuous rainfall-runoff model (MISDc to assess its relationship with modeled data. Then, by using a simple data assimilation technique, the linearly rescaled SWI that matches the range of variability of modelled data (denoted as SWI* was assimilated into MISDc and the model performance on flood estimation was analyzed. Moreover, three synthetic experiments considering errors on rainfall, model parameters and initial soil wetness conditions were carried out. These experiments allowed to further investigate the SWI potential when uncertain conditions take place. The most significant flood events, which occurred in the period 2000–2009 on five subcatchments of the Upper Tiber River in central Italy, ranging in extension between 100 and 650 km

  18. The impact of soil moisture extremes and their spatiotemporal variability on Zambian maize yields

    Science.gov (United States)

    Zhao, Y.; Estes, L. D.; Vergopolan, N.

    2017-12-01

    Food security in sub-Saharan Africa is highly sensitive to climate variability. While it is well understood that extreme heat has substantial negative impacts on crop yield, the impacts of precipitation extremes, particularly over large spatial extents, are harder to quantify. There are three primary reasons for this difficulty, which are (1) lack of high quality, high resolution precipitation data, (2) rainfall data provide incomplete information on plant water availability, the variable that most directly affects crop performance, and (3) the type of rainfall extreme that most affects crop yields varies throughout the crop development stage. With respect to the first reason, the spatial and temporal variation of precipitation is much greater than that of temperature, yet the spatial resolution of rainfall data is typically even coarser than it is for temperature, particularly within Africa. Even if there were high-resolution rainfall data, the amount of water available to crops also depends on other physical factors that affect evapotranspiration, which are strongly influenced by heterogeneity in the land surface related to topography, soil properties, and land cover. In this context, soil moisture provides a better measure of crop water availability than rainfall. Furthermore, soil moisture has significantly different influences on crop yield depending on the crop's growth stage. The goal of this study is to understand how the spatiotemporal scales of soil moisture extremes interact with crops, more specifically, the timing and the spatial scales of extreme events like droughts and flooding. In this study, we simulate daily-1km soil moisture using HydroBlocks - a physically based land surface model - and compare it with precipitation and remote sensing derived maize yields between 2000 and 2016 in Zambia. We use a novel combination of the SCYM (scalable satellite-based yield mapper) method with DSSAT crop model, which is a mechanistic model responsive to water

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

    Science.gov (United States)

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

    2015-04-01

    Annual crop yield depends on various factors such as soil properties, management decisions, and meteorological conditions. Unfavorable weather conditions, e.g. droughts, have the potential to drastically diminish crop yield in rain-fed agriculture. For example, the drought in 2003 caused direct losses of 1.5 billion EUR only in Germany. Predicting crop yields allows to mitigate negative effects of weather extremes which are assumed to occur more often in the future due to climate change. A standard approach in economics is to predict the impact of climate change on agriculture as a function of temperature and precipitation. This approach has been developed further using concepts like growing degree days. Other econometric models use nonlinear functions of heat or vapor pressure deficit. However, none of these approaches uses soil moisture to predict crop yield. We hypothesize that soil moisture is a better indicator to explain stress on plant growth than estimations based on precipitation and temperature. This is the case because the latter variables do not explicitly account for the available water content in the root zone, which is the primary source of water supply for plant growth. In this study, a reduced form panel approach is applied to estimate a multivariate econometric production function for the years 1999 to 2010. Annual crop yield data of various crops on the administrative district level serve as depending variables. The explanatory variable of major interest is the Soil Moisture Index (SMI), which quantifies anomalies in root zone soil moisture. The SMI is computed by the mesoscale Hydrological Model (mHM, www.ufz.de/mhm). The index represents the monthly soil water quantile at a 4 km2 grid resolution covering entire Germany. A reduced model approach is suitable because the SMI is the result of a stochastic weather process and therefore can be considered exogenous. For the ease of interpretation a linear functionality is preferred. Meteorological

  20. Validation of SMAP Surface Soil Moisture Products with Core Validation Sites

    Science.gov (United States)

    Colliander, A.; Jackson, T. J.; Bindlish, R.; Chan, S.; Das, N.; Kim, S. B.; Cosh, M. H.; Dunbar, R. S.; Dang, L.; Pashaian, L.; hide

    2017-01-01

    The NASA Soil Moisture Active Passive (SMAP) mission has utilized a set of core validation sites as the primary methodology in assessing the soil moisture retrieval algorithm performance. Those sites provide well calibrated in situ soil moisture measurements within SMAP product grid pixels for diverse conditions and locations.The estimation of the average soil moisture within the SMAP product grid pixels based on in situ measurements is more reliable when location specific calibration of the sensors has been performed and there is adequate replication over the spatial domain, with an up-scaling function based on analysis using independent estimates of the soil moisture distribution. SMAP fulfilled these requirements through a collaborative CalVal Partner program.This paper presents the results from 34 candidate core validation sites for the first eleven months of the SMAP mission. As a result of the screening of the sites prior to the availability of SMAP data, out of the 34 candidate sites 18 sites fulfilled all the requirements at one of the resolution scales (at least). The rest of the sites are used as secondary information in algorithm evaluation. The results indicate that the SMAP radiometer-based soil moisture data product meets its expected performance of 0.04 cu m/cu m volumetric soil moisture (unbiased root mean square error); the combined radar-radiometer product is close to its expected performance of 0.04 cu m/cu m, and the radar-based product meets its target accuracy of 0.06 cu m/cu m (the lengths of the combined and radar-based products are truncated to about 10 weeks because of the SMAP radar failure). Upon completing the intensive CalVal phase of the mission the SMAP project will continue to enhance the products in the primary and extended geographic domains, in co-operation with the CalVal Partners, by continuing the comparisons over the existing core validation sites and inclusion of candidate sites that can address shortcomings.

  1. Shrub encroachment alters sensitivity of soil respiration to temperature and moisture

    Science.gov (United States)

    Cable, Jessica M.; Barron-Gafford, Greg A.; Ogle, Kiona; Pavao-Zuckerman, Mitchell; Scott, Russell L.; Williams, David G.; Huxman, Travis E.

    2012-03-01

    A greater abundance of shrubs in semiarid grasslands affects the spatial patterns of soil temperature, moisture, and litter, resulting in fertile islands with potentially enhanced soil metabolic activity. The goal of this study was to quantify the microsite specificity of soil respiration in a semiarid riparian ecosystem experiencing shrub encroachment. We quantified the response of soil respiration to different microsite conditions created by big mesquite shrubs (near the trunk and the canopy edge), medium-sized mesquite, sacaton bunchgrasses, and open spaces. We hypothesized that soil respiration would be more temperature sensitive and less moisture sensitive and have a greater magnitude in shrub microsites compared with grass and open microsites. Field and incubation soil respiration data were simultaneously analyzed in a Bayesian framework to quantify the microsite-specific temperature and moisture sensitivities and magnitude of respiration. The analysis showed that shrub expansion increases the heterogeneity of respiration. Respiration has greater temperature sensitivity near the shrub canopy edge, and respiration rates are higher overall under big mesquite compared with those of the other microsites. Respiration in the microsites beneath medium-sized mesquites does not behave like a downscaled version of big mesquite microsites. The grass microsites show more similarity to big mesquite microsites than medium-sized shrubs. This study shows there can be a great deal of fine-scale spatial heterogeneity that accompanies shifts in vegetation structure. Such complexity presents a challenge in scaling soil respiration fluxes to the landscape for systems experiencing shrub encroachment, but quantifying this complexity is significantly important in determining overall ecosystem metabolic behavior.

  2. The influence of soil moisture on magnetic susceptibility measurements

    Science.gov (United States)

    Maier, G.; Scholger, R.; Schön, J.

    2006-06-01

    An important methodological question for magnetic susceptibility measurements is if a variation of the soil conductivity, as a result of a change in soil moisture, influences the measured susceptibility values. An answer to this question is essential because an accurate magnetic susceptibility mapping requires a grid of comparable magnetic susceptibility values, which indicate the magnetic iron-mineral contents of the soils. Therefore, in the framework of the MAGPROX project (EU-Project EVK2-CT-1999-00019), the study aims at investigating the influence of soil moisture and the possible correlation between magnetic susceptibility and electric conductivity. This approach was realised by model experiments in the laboratory and a field monitoring experiment, which was performed in an analogical manner as the model. For the laboratory experiment, a plastic tub with a water in- and outflow system and installed lines of electrodes was used. The measurements were carried out with layers of different magnetic material within the experimental sand formation under varying water saturation conditions. For the field experiment, which was carried out from July to December 2003, two test sites were selected. The magnetic susceptibility was measured by means of the recently developed vertical soil profile kappa meter SM400 and a commonly used Bartington MS2D probe. The electric resistivity was recorded using a 4-point light system (laboratory) and a ground conductivity meter EM38 (field). The knowledge of the resistivity of the sand formation enabled an estimation of porosity and water saturation in consideration of the Archie equations. The laboratory experiment results showed a very slight variation of measured magnetic susceptibility under different degrees of moisture, indicating mainly the influence from the diamagnetic contribution of the water volume. A measurement error in connection with the measurement method, for example caused by an interfering effect of soil

  3. MoistureMap: A soil moisture monitoring, prediction and reporting system for sustainable land and water management

    Science.gov (United States)

    Rudiger, C.; Walker, J. P.; Barrett, D. J.; Gurney, R. J.; Kerr, Y. H.; Kim, E. J.; Lemarshall, J.

    2009-12-01

    A prototype soil moisture monitoring, prediction and reporting system is being developed for Australia, with the Murrumbidgee catchment as the demonstration catchment. The system will provide current and future soil moisture information and its uncertainty at 1km resolution, by combining weather, climate and land surface model predictions with soil moisture data from ESA's Soil Moisture and Ocean Salinity (SMOS) satellite; the first-ever dedicated microwave soil moisture mission. A major aspect of this project is developing and testing the soil moisture retrieval algorithms to be used for SMOS and verifying SMOS data for Australian conditions, through a number of airborne campaigns. The key elements of this project will develop and test innovative techniques for monitoring, prediction and reporting of 1km resolution soil moisture content from ground-, air- and space-based measurements for Australian conditions. The ground based and air-borne data will be used for: (i) calibration/validation of the SMOS satellite; (ii) development and verification of surface soil moisture retrieval algorithm components of the SMOS Simulator; (iii) development and verification of soil hydraulic property estimation; and (iv) verification of 1km moisture from MoistureMap. The Murrumbidgee catchment is an 80,000km2 watershed located in south-eastern Australia, with a large diversity in climatic, topographic and land cover characteristics making it an excellent demonstration test-bed for SMOS Simulator and MoistureMap developments. The Murrumbidgee River Catchment has been instrumented and monitored for soil moisture and supporting data for more than 7 years. The existing network of monitoring sites, data management systems, data sets, and detailed knowledge of the catchment provide an ideal basis for the field work and data requirements of this study. The soil moisture prediction model to be used is CSIRO Atmosphere Biosphere Land Exchange (CABLE), a column model based on Richards

  4. Multifractal and Singularity Maps of soil surface moisture distribution derived from 2D image analysis.

    Science.gov (United States)

    Cumbrera, Ramiro; Millán, Humberto; Martín-Sotoca, Juan Jose; Pérez Soto, Luis; Sanchez, Maria Elena; Tarquis, Ana Maria

    2016-04-01

    Soil moisture distribution usually presents extreme variation at multiple spatial scales. Image analysis could be a useful tool for investigating these spatial patterns of apparent soil moisture at multiple resolutions. The objectives of the present work were (i) to describe the local scaling of apparent soil moisture distribution and (ii) to define apparent soil moisture patterns from vertical planes of Vertisol pit images. Two soil pits (0.70 m long × 0.60 m width × 0.30 m depth) were excavated on a bare Mazic Pellic Vertisol. One was excavated in April/2011 and the other pit was established in May/2011 after 3 days of a moderate rainfall event. Digital photographs were taken from each Vertisol pit using a Kodak™ digital camera. The mean image size was 1600 × 945 pixels with one physical pixel ≈373 μm of the photographed soil pit. For more details see Cumbrera et al. (2012). Geochemical exploration have found with increasingly interests and benefits of using fractal (power-law) models to characterize geochemical distribution, using the concentration-area (C-A) model (Cheng et al., 1994; Cheng, 2012). This method is based on the singularity maps of a measure that at each point define areas with self-similar properties that are shown in power-law relationships in Concentration-Area plots (C-A method). The C-A method together with the singularity map ("Singularity-CA" method) define thresholds that can be applied to segment the map. We have applied it to each soil image. The results show that, in spite of some computational and practical limitations, image analysis of apparent soil moisture patterns could be used to study the dynamical change of soil moisture sampling in agreement with previous results (Millán et al., 2016). REFERENCES Cheng, Q., Agterberg, F. P. and Ballantyne, S. B. (1994). The separation of geochemical anomalies from background by fractal methods. Journal of Geochemical Exploration, 51, 109-130. Cheng, Q. (2012). Singularity theory and

  5. Soil Moisture Sensing via Swept Frequency Based Microwave Sensors

    Directory of Open Access Journals (Sweden)

    Greg A. Holt

    2012-01-01

    Full Text Available There is a need for low-cost, high-accuracy measurement of water content in various materials. This study assesses the performance of a new microwave swept frequency domain instrument (SFI that has promise to provide a low-cost, high-accuracy alternative to the traditional and more expensive time domain reflectometry (TDR. The technique obtains permittivity measurements of soils in the frequency domain utilizing a through transmission configuration, transmissometry, which provides a frequency domain transmissometry measurement (FDT. The measurement is comparable to time domain transmissometry (TDT with the added advantage of also being able to separately quantify the real and imaginary portions of the complex permittivity so that the measured bulk permittivity is more accurate that the measurement TDR provides where the apparent permittivity is impacted by the signal loss, which can be significant in heavier soils. The experimental SFI was compared with a high-end 12 GHz TDR/TDT system across a range of soils at varying soil water contents and densities. As propagation delay is the fundamental measurement of interest to the well-established TDR or TDT technique; the first set of tests utilized precision propagation delay lines to test the accuracy of the SFI instrument’s ability to resolve propagation delays across the expected range of delays that a soil probe would present when subjected to the expected range of soil types and soil moisture typical to an agronomic cropping system. The results of the precision-delay line testing suggests the instrument is capable of predicting propagation delays with a RMSE of +/−105 ps across the range of delays ranging from 0 to 12,000 ps with a coefficient of determination of r2 = 0.998. The second phase of tests noted the rich history of TDR for prediction of soil moisture and leveraged this history by utilizing TDT measured with a high-end Hewlett Packard TDR/TDT instrument to directly benchmark the

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

    Science.gov (United States)

    1991-01-01

    only surface water is found in the Okavango Delta , which covers approximately 15,000 km2 in the northern part of Botswana. It is fed by the Okavango ...exogeneous water is evident around the Okavango Delta , with relatively higher values present year-round. This is also indicative of the more persis... Okavango River and Delta . NDVI values are probably larger than the calculated soil moisture would indicate (recall that the model does not account for

  7. Soil moisture simulations using two different modelling approaches

    Czech Academy of Sciences Publication Activity Database

    Šípek, Václav; Tesař, Miroslav

    2013-01-01

    Roč. 64, 3-4 (2013), s. 99-103 ISSN 0006-5471 R&D Projects: GA AV ČR IAA300600901; GA ČR GA205/08/1174 Institutional research plan: CEZ:AV0Z20600510 Keywords : soil moisture modelling * SWIM model * box modelling approach Subject RIV: DA - Hydrology ; Limnology http://www.boku.ac.at/diebodenkultur/volltexte/sondernummern/band-64/heft-3-4/sipek.pdf

  8. MISTRALE: Soil moisture mapping service based on a UAV-embedded GNSS-Reflectometry sensor

    Science.gov (United States)

    Van de Vyvere, Laura; Desenfans, Olivier

    2016-04-01

    Around 70 percent of worldwide freshwater is used by agriculture. To be able to feed an additional 2 billion people by 2030, water demand is expected to increase tremendously in the next decades. Farmers are challenged to produce "more crop per drop". In order to optimize water resource management, it is crucial to improve soil moisture situation awareness, which implies both a better temporal and spatial resolution. To this end, the objective of the MISTRALE project (Monitoring soIl moiSture and waTeR-flooded Areas for agricuLture and Environment) is to provide UAV-based soil moisture maps that could complement satellite-based and field measurements. In addition to helping farmers make more efficient decisions about where and when to irrigate, MISTRALE moisture maps are an invaluable tool for risk management and damage evaluation, as they provide highly relevant information for wetland and flood-prone area monitoring. In order to measure soil water content, a prototype of a new sensor, called GNSS-Reflectometry (GNSS-R), is being developed in MISTRALE. This approach consists in comparing the direct signal, i.e. the signal travelling directly from satellite to receiver (in this case, embedded in the UAV), with its ground-reflected equivalent. Since soil dielectric properties vary with moisture content, the reflected signal's peak power is affected by soil moisture, unlike the direct one. In order to mitigate the effect of soil surface roughness on measurements, both left-hand and right-hand circular polarization reflected signals have to be recorded and processed. When it comes to soil moisture, using GNSS signals instead of traditional visible/NIR imagery has many advantages: it is operational under cloud cover, during the night, and also under vegetation (bushes, grass, trees). In addition, compared to microwaves, GNSS signal (which lies in L-band, between 1.4 and 1.8 GHz) is less influenced by variation on thermal background. GNSS frequencies are then ideal

  9. Assimilation of SMOS observations to improve soil moisture and streamflow simulations in the Murray Darling Basin, Australia

    Science.gov (United States)

    Lievens, Hans; Bitar, Ahmad Al; Cabot, Francois; De Lannoy, Gabrielle; Drusch, Matthias; Dumedah, Gift; Hendricks Franssen, Harrie-Jan; Kerr, Yann; Tomer, Sat Kumar; Martens, Brecht; Merlin, Olivier; Pan, Ming; Roundy, Joshua; van den Berg, Martinus Johannes; Vereecken, Harry; Verhoest, Niko; Walker, Jeff; Wood, Eric; Pauwels, Valentijn

    2015-04-01

    Soil Moisture and Ocean Salinity (SMOS) retrievals hold a large potential for improving hydrologic model simulations through data assimilation. However, the soil moisture retrievals are often provided at coarser spatial resolution than the model grid. To resolve the mismatch in spatial resolution between SMOS retrievals and simulations by VIC (i.e. the Variable Infiltration Capacity model), two approaches are investigated. The first approach is to downscale the remote sensing data prior to their use in the model. This renders the development of the data assimilation algorithm more straightforward, but requires a significant amount of satellite data processing. In the second approach, this processing is circumvented by directly assimilating the coarse scale satellite soil moisture retrievals into the model through the use of the observation operator. Recently, an increasing interest has also been drawn to the assimilation of level 1 data, i.e. the satellite-observed brightness temperatures. To accommodate for the assimilation of SMOS brightness temperature data, VIC is coupled with the Community Microwave Emission Model (CMEM), which allows the forward simulation of TOA brightness temperatures observed by SMOS. The main advantage of this approach is that it allows for using consistent parameter sets in the land surface and radiative transfer model. The objectives of this study are to investigate the potential of assimilating SMOS data, either as downscaled soil moisture, coarse scale soil moisture or brightness temperature products, into a coupled land surface and radiative transfer model for improving flood forecasts, and to provide recommendations on the optimal assimilation strategy. The merit of SMOS data assimilation for water management applications is studied by comparing simulated soil moisture and streamflow predictions with in situ measurements of soil moisture from OzNet and stream gauge data from 169 stations across the Murray Darling Basin. The study

  10. NASA Soil Moisture Active Passive Mission Status and Science Highlights

    Science.gov (United States)

    Yueh, Simon; Entekhabi, Dara; O'Neill, Peggy; Entin, Jared

    2017-01-01

    The Soil Moisture 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 soil moisture 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 soil moisture 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 soil moisture, 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 soil moisture 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

  11. Interactive Vegetation Phenology, Soil Moisture, and Monthly Temperature Forecasts

    Science.gov (United States)

    Koster, R. D.; Walker, G. K.

    2015-01-01

    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 soil moisture 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 soil moisture 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 soil moisture.

  12. Effects of soil moisture variations on deposition velocities above vegetation.

    Energy Technology Data Exchange (ETDEWEB)

    Wesely, M. L.; Song, J.; McMillen, R. T.; Meyers, T. P.; Environmental Research; Northern Illinois Univ.; National Oceanic and Atmospheric Administration

    2001-01-01

    The parameterized subgrid-scale surface flux (PASS) model provides a simplified means of using remote sensing data from satellites and limited surface meteorological information to estimate the influence of soil moisture on bulk canopy stomatal resistances to the uptake of gases over extended areas. PASS-generated estimates of bulk canopy stomatal resistance were used in a dry deposition module to compute gas deposition velocities with a horizontal resolution of 200 m for approximately 5000 km{sup 2} of agricultural crops and rangeland. Results were compared with measurements of O{sub 3} flux and concentrations made during April and May 1997 at two surface stations and from an aircraft. The trend in simulated O{sub 3} deposition velocity during soil moisture drydown over a period of a few days matched the trend observed at the two surface stations. For areas under the aircraft flight paths, the variability in simulated O{sub 3} deposition velocity was substantially smaller than the observed variability, while the averages over tens of kilometers were usually in agreement within 0.1 cm s{sup -1}. Model results indicated that soil moisture can have a major role in deposition of O{sub 3} and other substances strongly affected by canopy stomatal resistance.

  13. Use of microwave remote sensing data to monitor spatio temporal characteristics of surface soil moisture at local and regional scales

    Directory of Open Access Journals (Sweden)

    A. Löw

    2005-01-01

    Full Text Available Hydrologic processes, such as runoff production or evapotranspiration, largely depend on the variation of soil moisture and its spatial pattern. The interaction of electromagnetic waves with the land surface can be dependant on the water content of the uppermost soil layer. Especially in the microwave domain of the electromagnetic spectrum, this is the case. New sensors as e.g. ENVISAT ASAR, allow for frequent, synoptically and homogeneous image acquisitions over larger areas. Parameter inversion models are therefore developed to derive bio- and geophysical parameters from the image products. The paper presents a soil moisture inversion model for ENVISAT ASAR data for local and regional scale applications. The model is validated against in situ soil moisture measurements. The various sources of uncertainties, being related to the inversion process are assessed and quantified.

  14. Soil moisture and wild olive tree transpiration relationship in a water-limited Mediterranean ecosystem.

    Science.gov (United States)

    Curreli, M.; Montaldo, N.; Oren, R.

    2016-12-01

    Typically, during the dry summers, Mediterranean ecosystems are characterized by a simple dual PFTs system with strong-resistant woody vegetation and bare soil, since grass died. In these conditions the combined use of sap flow measurements, based on Granier's thermo-dissipative probes, eddy covariance technique and soil water content measurements provides a robust estimation of evapotranspiration (ET). An eddy covariance micrometeorological tower, thermo-dissipative probes based on the Granier technique and TDR sensors have been installed in the Orroli site in Sardinia (Italy). The site landscape is a mixture of Mediterranean patchy vegetation types: wild olives, different shrubs and herbaceous species, which died during the summer. 33 sap flow sensors have been installed at the Orroli site into 15 wild olives clumps with different characteristics (tree size, exposition to wind, solar radiation and soil depth). Sap flow measurements show the significantly impacts on transpiration of soil moisture, radiation and vapor pressure deficit (VPD). In addition ET is strongly influenced by the tree position into the clump. Results show a significant difference in sap flow rate for the south exposed trees compared to inside clump and north exposed trees. Using an innovative scaling procedure, the transpiration calculated from sap flow measurements have been compared to the eddy covariance ET. Sap flow measurements show night time uptake allows the recharge of the stem capacity, depleted during the day before due to transpiration. The night uptake increases with increasing VPD and transpiration but surprisingly it is independent to soil water content. Soil moisture probes allow monitoring spatial and temporal dynamics of water content at different soil depth and distance to the trees, and estimating its correlation with hydraulic lift. During the light hours soil moisture is depleted by roots to provide the water for transpiration and during night time the lateral roots

  15. Comparative estimation and assessment of initial soil moisture conditions for Flash Flood warning in Saxony

    Science.gov (United States)

    Luong, Thanh Thi; Kronenberg, Rico; Bernhofer, Christian; Janabi, Firas Al; Schütze, Niels

    2017-04-01

    Flash Floods are known as highly destructive natural hazards due to their sudden appearance and severe consequences. In Saxony/Germany flash floods occur in small and medium catchments of low mountain ranges which are typically ungauged. Besides rainfall and orography, pre-event moisture is decisive, as it determines the available natural retention in the catchment. The Flash Flood Guidance concept according to WMO and Prof. Marco Borga (University of Padua) will be adapted to incorporate pre-event moisture in real-time flood forecast within the ESF EXTRUSO project (SAB-Nr. 100270097). To arrive at pre-event moisture for the complete area of the low mountain range with flash flood potential, a widely applicable, accurate but yet simple approach is needed. Here, we use radar precipitation as input time series, detailed orographic, land-use and soil information and a lumped parameter model to estimate the overall catchment soil moisture and potential retention. When combined with rainfall forecast and its intrinsic uncertainty, the approach allows to find the point in time when precipitation exceeds the retention potential of the catchment. Then, spatially distributed and complex hydrological modeling and additional measurements can be initiated. Assuming reasonable rainfall forecasts of 24 to 48hrs, this part can start up to two days in advance of the actual event. The lumped-parameter model BROOK90 is used and tested for well observed catchments. First, physical meaningful parameters (like albedo or soil porosity) a set according to standards and second, "free" parameters (like percentage of lateral flow) were calibrated objectively by PEST (Model-Independent Parameter Estimation and Uncertainty Analysis) with the target on evapotranspiration and soil moisture which both have been measured at the study site Anchor Station Tharandt in Saxony/Germany. Finally, first results are presented for the Wernersbach catchment in Tharandt forest for main flood events in the 50

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

    Science.gov (United States)

    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

  17. Soil Organic Matter Accumulation and Carbon Fractions along a Moisture Gradient of Forest Soils

    Directory of Open Access Journals (Sweden)

    Ewa Błońska

    2017-11-01

    Full Text Available The aim of the study was to present effects of soil properties, especially moisture, on the quantity and quality of soil organic matter. The investigation was performed in the Czarna Rózga Reserve in Central Poland. Forty circular test areas were located in a regular grid of points (100 × 300 m. Each plot was represented by one soil profile located at the plot’s center. Sample plots were located in the area with Gleysols, Cambisols and Podzols with the water table from 0 to 100 cm. In each soil sample, particle size, total carbon and nitrogen content, acidity, base cations content and fractions of soil organic matter were determined. The organic carbon stock (SOCs was calculated based on its total content at particular genetic soil horizons. A Carbon Distribution Index (CDI was calculated from the ratio of the carbon accumulation in organic horizons and the amount of organic carbon accumulation in the mineral horizons, up to 60 cm. In the soils under study, in the temperate zone, moisture is an important factor in the accumulation of organic carbon in the soil. The highest accumulation of carbon was observed in soils of swampy variant, while the lowest was in the soils of moist variant. Large accumulation of C in the soils with water table 80–100 cm results from the thick organic horizons that are characterized by lower organic matter decomposition and higher acidity. The proportion of carbon accumulation in the organic horizons to the total accumulation in the mineral horizons expresses the distribution of carbon accumulated in the soil profile, and is a measure of quality of the organic matter accumulated. Studies have confirmed the importance of moisture content in the formation of the fractional organic matter. With greater soil moisture, the ratio of humic to fulvic acids (HA/FA decreases, which may suggest an increase in carbon mobility in soils.