WorldWideScience

Sample records for soil moisture variability

  1. 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.

  2. 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

  3. 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 ...

  4. Spatial variability of soil moisture retrieved by SMOS satellite

    Science.gov (United States)

    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

  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. 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.

  7. 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-.

  8. 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...

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

    Science.gov (United States)

    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.

  11. Year-round estimation of soil moisture content using temporally variable soil hydraulic parameters

    Czech Academy of Sciences Publication Activity Database

    Šípek, Václav; Tesař, Miroslav

    2017-01-01

    Roč. 31, č. 6 (2017), s. 1438-1452 ISSN 0885-6087 R&D Projects: GA ČR GA16-05665S Institutional support: RVO:67985874 Keywords : hydrological modelling * pore-size distribution * saturated hydraulic conductivity * seasonal variability * soil hydraulic parameters * soil moisture Subject RIV: DA - Hydrology ; Limnology OBOR OECD: Hydrology Impact factor: 3.014, year: 2016

  12. Year-round estimation of soil moisture content using temporally variable soil hydraulic parameters

    Czech Academy of Sciences Publication Activity Database

    Šípek, Václav; Tesař, Miroslav

    2017-01-01

    Roč. 31, č. 6 (2017), s. 1438-1452 ISSN 0885-6087 R&D Projects: GA ČR GA16-05665S Institutional support: RVO:67985874 Keywords : hydrological modelling * pore-size distribution * saturated hydraulic conductivity * seasonal variability * soil hydraulic parameters * soil moisture Subject RIV: DA - Hydrology ; Limnology Impact factor: 3.014, year: 2016

  13. 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).

  14. 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

  15. 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.

  16. 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.

  17. 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

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

    Science.gov (United States)

    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

  19. 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

  20. Using SMAP Data to Investigate the Role of Soil Moisture Variability on Realtime Flood Forecasting

    Science.gov (United States)

    Krajewski, W. F.; Jadidoleslam, N.; Mantilla, R.

    2017-12-01

    The Iowa Flood Center has developed a regional high-resolution flood-forecasting model for the state of Iowa that decomposes the landscape into hillslopes of about 0.1 km2. For the model to benefit, through data assimilation, from SMAP observations of soil moisture (SM) at scales of approximately 100 km2, we are testing a framework to connect SMAP-scale observations to the small-scale SM variability calculated by our rainfall-runoff models. As a step in this direction, we performed data analyses of 15-min point SM observations using a network of about 30 TDR instruments spread throughout the state. We developed a stochastic point-scale SM model that captures 1) SM increases due to rainfall inputs, and 2) SM decay during dry periods. We use a power law model to describe soil moisture decay during dry periods, and a single parameter logistic curve to describe precipitation feedback on soil moisture. We find that the parameters of the models behave as time-independent random variables with stationary distributions. Using data-based simulation, we explore differences in the dynamical range of variability of hillslope and SMAP-scale domains. The simulations allow us to predict the runoff field and streamflow hydrographs for the state of Iowa during the three largest flooding periods (2008, 2014, and 2016). We also use the results to determine the reduction in forecast uncertainty from assimilation of unbiased SMAP-scale soil moisture observations.

  1. 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

  2. Local Versus Remote Contributions of Soil Moisture to Near-Surface Temperature Variability

    Science.gov (United States)

    Koster, R.; Schubert, S.; Wang, H.; Chang, Y.

    2018-01-01

    Soil moisture variations have a straightforward impact on overlying air temperatures, wetter soils can induce higher evaporative cooling of the soil and thus, locally, cooler temperatures overall. Not known, however, is the degree to which soil moisture variations can affect remote air temperatures through their impact on the atmospheric circulation. In this talk we describe a two-pronged analysis that addresses this question. In the first segment, an extensive ensemble of NASA/GSFC GEOS-5 atmospheric model simulations is analyzed statistically to isolate and quantify the contributions of various soil moisture states, both local and remote, to the variability of air temperature at a given local site. In the second segment, the relevance of the derived statistical relationships is evaluated by applying them to observations-based data. Results from the second segment suggest that the GEOS-5-based relationships do, at least to first order, hold in nature and thus may provide some skill to forecasts of air temperature at subseasonal time scales, at least in certain regions.

  3. 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

  4. Compensating for environmental variability in the thermal inertia approach to remote sensing of soil moisture

    Science.gov (United States)

    Idso, S. B.; Jackson, R. D.; Reginato, R. J.

    1976-01-01

    A procedure is developed for removing data scatter in the thermal-inertia approach to remote sensing of soil moisture which arises from environmental variability in time and space. It entails the utilization of nearby National Weather Service air temperature measurements to normalize measured diurnal surface temperature variations to what they would have been for a day of standard diurnal air temperature variation, arbitrarily assigned to be 18 C. Tests of the procedure's basic premise on a bare loam soil and a crop of alfalfa indicate it to be conceptually sound. It is possible that the technique could also be useful in other thermal-inertia applications, such as lithographic mapping.

  5. Variability of parameters for modelling soil moisture conditions : studies on loamy to silty soils on marly bedrock in the Ardeche drainage basin (France)

    NARCIS (Netherlands)

    Berg, van den J.A.

    1989-01-01

    Field experiments and additional measurements on undisturbed soil samples in the laboratory were done to investigate the variability of the parameters used in modelling soil moisture conditions.

    The conditions of soil water control the amount of moisture available for the

  6. 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

  7. Assessing Climate Change Impacts on Large-Scale Soil Moisture, its Temporal Variability and Associated Drought-Flood Risks

    Science.gov (United States)

    Destouni, G.; Verrot, L.

    2015-12-01

    Soil moisture is a dynamic variable of great importance for water cycling and climate, as well as for ecosystems and societal sectors such as agriculture. Model representation of soil moisture and its temporal variability is, for instance, central for assessing the impacts of hydro-climatic change on drought and flood risks. However, our ability to assess such impacts and guide appropriate mitigation and adaptation measures is challenged by the need to link data and modeling across a range of spatiotemporal scales of relevance for the variability and change of soil moisture in long-term time series. This paper synthesizes recent advances for meeting this challenge by a relatively simple, analytical, data-driven approach to modeling the variability and change of large-scale soil moisture under long-term hydro-climatic change. Model application to two major Swedish drainage basins, and model-data comparison for ten study catchments across the United States shows the model ability to reproduce variability dynamics in long-term data series of the key soil-moisture variables: unsaturated water content and groundwater table position. The Swedish application shows that human-driven hydro-climatic shifts may imply increased risk for hydrological drought (runoff-related) and agricultural drought (soil moisture-related), even though meteorological drought risk (precipitation-related) is unchanged or lowered. The direct model-data comparison for ten U.S. catchments further shows good model representation of seasonal and longer-term fluctuation timings and frequencies for water content and groundwater level, along with physically reasonable model tendency to underestimate the local fluctuation magnitudes. Overall, the tested modeling approach can fulfill its main aim of screening long-term time series of large-scale hydro-climatic data (historic or projected for the future by climate modeling) for relatively simple, unexaggerated assessment of variability and change in key

  8. 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.

  9. Hill slope unsaturated flowpaths and soil moisture variability in a Forested Catchment in Southwest China

    OpenAIRE

    Sørbotten, Lars-Erik

    2011-01-01

    Forested catchments in subtropical southwest China are important sites for nitrogen, primarily due to denitrification. Denitrification depends strongly on soil moisture content and the residence time of soil water. Both depend on the hydrological properties of the soils. In this study we investigated the soil hydrological properties and water flow paths on a hill slope in the TieShanPing catchment around 25 kilometres north-east of Chongqing. Soils were sampled for analyses of water retention...

  10. 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

  11. 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.

  12. 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

  13. Variability of soil moisture proxies and hot days across the climate regimes of Australia

    Science.gov (United States)

    Holmes, A.; Rüdiger, C.; Mueller, B.; Hirschi, M.; Tapper, N.

    2017-07-01

    The frequency of extreme events such as heat waves are expected to increase due to the effect of climate change, particularly in semiarid regions of Australia. Recent studies have indicated a link between soil moisture deficits and heat extremes, focusing on the coupling between the two. This study investigates the relationship between the number of hot days (Tx90) and four soil moisture proxies (Standardized Precipitation Index, Antecedent Precipitation Index, Mount's Soil Dryness Index, and Keetch-Byram Drought Index), and how the strength of this relationship changes across various climate regimes within Australia. A strong anticorrelation between Tx90 and each moisture index is found, particularly for tropical savannas and temperate regions. However, the magnitude of the increase in Tx90 with decreasing moisture is strongest in semiarid and arid regions. It is also shown that the Tx90-soil moisture relationship strengthens during the El Niño phases of El Niño-Southern Oscillation in regions which are more sensitive to changes in soil moisture.

  14. 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.

  15. 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.

  16. 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...

  17. 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

  18. 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, ...

  19. Landscape-scale soil moisture heterogeneity and its influence on surface fluxes at the Jornada LTER site: Evaluating a new model parameterization for subgrid-scale soil moisture variability

    Science.gov (United States)

    Baker, I. T.; Prihodko, L.; Vivoni, E. R.; Denning, A. S.

    2017-12-01

    Arid and semiarid regions represent a large fraction of global land, with attendant importance of surface energy and trace gas flux to global totals. These regions are characterized by strong seasonality, especially in precipitation, that defines the level of ecosystem stress. Individual plants have been observed to respond non-linearly to increasing soil moisture stress, where plant function is generally maintained as soils dry down to a threshold at which rapid closure of stomates occurs. Incorporating this nonlinear mechanism into landscape-scale models can result in unrealistic binary "on-off" behavior that is especially problematic in arid landscapes. Subsequently, models have `relaxed' their simulation of soil moisture stress on evapotranspiration (ET). Unfortunately, these relaxations are not physically based, but are imposed upon model physics as a means to force a more realistic response. Previously, we have introduced a new method to represent soil moisture regulation of ET, whereby the landscape is partitioned into `BINS' of soil moisture wetness, each associated with a fractional area of the landscape or grid cell. A physically- and observationally-based nonlinear soil moisture stress function is applied, but when convolved with the relative area distribution represented by wetness BINS the system has the emergent property of `smoothing' the landscape-scale response without the need for non-physical impositions on model physics. In this research we confront BINS simulations of Bowen ratio, soil moisture variability and trace gas flux with soil moisture and eddy covariance observations taken at the Jornada LTER dryland site in southern New Mexico. We calculate the mean annual wetting cycle and associated variability about the mean state and evaluate model performance against this variability and time series of land surface fluxes from the highly instrumented Tromble Weir watershed. The BINS simulations capture the relatively rapid reaction to wetting

  20. Ground-based investigation of soil moisture variability within remote sensing footprints during the Southern Great Plains 1997 (SGP97) Hydrology Experiment

    NARCIS (Netherlands)

    Famiglietti, J.S.; Devereaux, J.A.; Laymon, C.A.; Tsegaye, T.; Houser, P.R.; Jackson, T.J.; Graham, S.T.; Rodell, M.; Oevelen, van P.J.

    1999-01-01

    Surface soil moisture content is highly variable in both space and time. While remote sensing provides an effective methodology for mapping surface moisture content over large areas, it averages within-pixel variability thereby masking the underlying heterogeneity observed at the land surface. This

  1. Reference Evapotranspiration Retrievals from a Mesoscale Model Based Weather Variables for Soil Moisture Deficit Estimation

    Directory of Open Access Journals (Sweden)

    Prashant K. Srivastava

    2017-10-01

    Full Text Available Reference Evapotranspiration (ETo and soil moisture deficit (SMD are vital for understanding the hydrological processes, particularly in the context of sustainable water use efficiency in the globe. Precise estimation of ETo and SMD are required for developing appropriate forecasting systems, in hydrological modeling and also in precision agriculture. In this study, the surface temperature downscaled from Weather Research and Forecasting (WRF model is used to estimate ETo using the boundary conditions that are provided by the European Center for Medium Range Weather Forecast (ECMWF. In order to understand the performance, the Hamon’s method is employed to estimate the ETo using the temperature from meteorological station and WRF derived variables. After estimating the ETo, a range of linear and non-linear models is utilized to retrieve SMD. The performance statistics such as RMSE, %Bias, and Nash Sutcliffe Efficiency (NSE indicates that the exponential model (RMSE = 0.226; %Bias = −0.077; NSE = 0.616 is efficient for SMD estimation by using the Observed ETo in comparison to the other linear and non-linear models (RMSE range = 0.019–0.667; %Bias range = 2.821–6.894; NSE = 0.013–0.419 used in this study. On the other hand, in the scenario where SMD is estimated using WRF downscaled meteorological variables based ETo, the linear model is found promising (RMSE = 0.017; %Bias = 5.280; NSE = 0.448 as compared to the non-linear models (RMSE range = 0.022–0.707; %Bias range = −0.207–−6.088; NSE range = 0.013–0.149. Our findings also suggest that all the models are performing better during the growing season (RMSE range = 0.024–0.025; %Bias range = −4.982–−3.431; r = 0.245–0.281 than the non−growing season (RMSE range = 0.011–0.12; %Bias range = 33.073–32.701; r = 0.161–0.244 for SMD estimation.

  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. Capability of crop water content for revealing variability of winter wheat grain yield and soil moisture under limited irrigation.

    Science.gov (United States)

    Zhang, Chao; Liu, Jiangui; Shang, Jiali; Cai, Huanjie

    2018-03-11

    Winter wheat (Triticum aestivum L.) is a major crop in the Guanzhong Plain, China. Understanding its water status is important for irrigation planning. A few crop water indicators, such as the leaf equivalent water thickness (EWT: g cm -2 ), leaf water content (LWC: %) and canopy water content (CWC: kg m -2 ), have been estimated using remote sensing techniques for a wide range of crops, yet their suitability and utility for revealing winter wheat growth and soil moisture status have not been well studied. To bridge this knowledge gap, field-scale irrigation experiments were conducted over two consecutive years (2014 and 2015) to investigate relationships of crop water content with soil moisture and grain yield, and to assess the performance of four spectral process methods for retrieving these three crop water indicators. The result revealed that the water indicators were more sensitive to soil moisture variation before the jointing stage. All three water indicators were significantly correlated with soil moisture during the reviving stage, and the correlations were stronger for leaf water indicators than that of the canopy water indicator at the jointing stage. No correlation was observed after the heading stage. All three water indicators showed good capabilities of revealing grain yield variability in jointing stage, with R 2 up to 0.89. CWC had a consistent relationship with grain yield over different growing seasons, but the performances of EWT and LWC were growing-season specific. The partial least squares regression was the most accurate method for estimating LWC (R 2 =0.72; RMSE=3.6%) and comparable capability for EWT and CWC. Finally, the work highlights the usefulness of crop water indicators to assess crop growth, productivity, and soil water status and demonstrates the potential of various spectral processing methods for retrieving crop water contents from canopy reflectance spectrums. Copyright © 2018 Elsevier B.V. All rights reserved.

  4. 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

  5. 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.

  6. 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

  7. Soil Moisture Controls on Rainfall and Temperature Variability: A Modeler Searches Through Observational Data

    Science.gov (United States)

    Koster, Randal

    2010-01-01

    The degree to which atmospheric processes respond to variations in soil moisture - a potentially important but largely untapped element of subseasonal to seasonal prediction - can be determined easily and directly for an atmospheric model but cannot be determined directly for nature through an analysis of observations. In atmospheric models) directions of causality can be artificially manipulated; we can avoid difficulties associated with the fact that atmospheric variations have a much larger impact on land state variations than vice-versa. In nature) on the other hand) the dominant direction of causality (the atmosphere forcing the ground) cannot be artificially "turned off") and the statistics associated with this dominant direction overwhelm those of the feedback signal. Observational data) however) do allow a number of indirect measures of landatmosphere feedback. This seminar reports on a series of joint analyses of observational and model data designed to illuminate the degree of land-atmosphere feedback present in the real world. The indirect measures do in fact suggest that feedback in nature, though small) is significant - enough to warrant the development of realistic land initialization strategies for subseasonal and seasonal forecasts.

  8. 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...

  9. Role of the Soil Thermal Inertia in the short term variability of the surface temperature and consequences for the soil-moisture temperature feedback

    Science.gov (United States)

    Cheruy, Frederique; Dufresne, Jean-Louis; Ait Mesbah, Sonia; Grandpeix, Jean-Yves; Wang, Fuxing

    2017-04-01

    A simple model based on the surface energy budget at equilibrium is developed to compute the sensitivity of the climatological mean daily temperature and diurnal amplitude to the soil thermal inertia. It gives a conceptual framework to quantity the role of the atmospheric and land surface processes in the surface temperature variability and relies on the diurnal amplitude of the net surface radiation, the sensitivity of the turbulent fluxes to the surface temperature and the thermal inertia. The performances of the model are first evaluated with 3D numerical simulations performed with the atmospheric (LMDZ) and land surface (ORCHIDEE) modules of the Institut Pierre Simon Laplace (IPSL) climate model. A nudging approach is adopted, it prevents from using time-consuming long-term simulations required to account for the natural variability of the climate and allow to draw conclusion based on short-term (several years) simulations. In the moist regions the diurnal amplitude and the mean surface temperature are controlled by the latent heat flux. In the dry areas, the relevant role of the stability of the boundary layer and of the soil thermal inertia is demonstrated. In these regions, the sensitivity of the surface temperature to the thermal inertia is high, due to the high contribution of the thermal flux to the energy budget. At high latitudes, when the sensitivity of turbulent fluxes is dominated by the day-time sensitivity of the sensible heat flux to the surface temperature and when this later is comparable to the thermal inertia term of the sensitivity equation, the surface temperature is also partially controlled by the thermal inertia which can rely on the snow properties; In the regions where the latent heat flux exhibits a high day-to-day variability, such as transition regions, the thermal inertia has also significant impact on the surface temperature variability . In these not too wet (energy limited) and not too dry (moisture-limited) soil moisture (SM

  10. Extracting Archaeological Feautres from GPR Surveys Conducted with Variable Soil Moisture Conditions

    Science.gov (United States)

    Morris, I. M.; Glisic, B.; Gonciar, A.

    2017-12-01

    As a common tool for subsurface archaeological prospection, ground penetrating radar (GPR) is a useful method for increasing the efficiency of archaeological excavations. Archaeological sites are often temporally and financially constrained, therefore having limited ability to reschedule surveys compromised by weather. Furthermore, electromagnetic GPR surveys are especially sensitive to variations in water content, soil type, and site-specific interference. In this work, GPR scans of a partially excavated Roman villa consisting of different construction materials and phases (limestone, andesite, brick) in central Romania are compared. Surveys were conducted with a 500 MHz GPR antenna in both dry (pre-rain event) and wet (post-rain event) conditions. Especially in time or depth slices, wet surveys present additional archaeological features that are not present or clear in the standard dry conditions, while simultaneously masking the clutter present in those scans. When dry, the limestone has a similar dielectric constant to the soil and does not provide enough contrast in electromagnetic properties for strong reflections despite the significant difference in their physical properties. Following precipitation, however, the electromagnetic properties of these two materials is dominated by their respective water content and the contrast is enhanced. For this reason, the wet surveys are particularly necessary for revealing reflections from the limestone features often invisible in dry surveys. GPR surveys conducted in variable environmental conditions provide unique archaeological information, with potential near-surface geophysical applications in nondestructive material characterization and identification.

  11. 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

  12. 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 ...

  13. The impact of soil moisture variability on seasonal convective precipitation simulations. Part I: validation, feedbacks, and realistic initialisation

    Directory of Open Access Journals (Sweden)

    Samiro Khodayar

    2013-08-01

    Full Text Available To assess how well and with what uncertainties the components of the regional water cycle, such as soil moisture, evapotranspiration, and precipitation, can be modelled especially in complex orographic areas and to investigate possible relationships among these parameters, numerical experiments were performed using the COSMO-CLM model in climate mode and observations from the field campaign 'Convective and Orographically-induced Precipitation Study' (COPS, including a unique soil moisture monitoring network. Additionally, the soil moisture observations were utilised for the initialisation of model simulations to investigate the impact on the precipitation field. The simulated summer season showed a clear relation of the different parameters of the process chain between soil moisture and precipitation. Deficiencies in the external model data, such as the soil type inventory, were pointed out. The simulated precipitation field showed an overestimation mainly in the valley and at lower altitudes. However, the analysis of the soil moisture distribution revealed a major underestimation in the valley and windward Black Forest areas, i.e. (a too much rain was converted into runoff and (b the forcing data were too dry. Differences in the surface fluxes could be attributed to a wrong soil type and an inappropriate land use type. The atmospheric water vapour content was overestimated in the valley and at windward sites, but underestimated in the high orographic areas, probably because thermally induced circulation systems were not represented well by the model. These model discrepancies may partly explain the biases observed in the precipitation field. Using COPS soil moisture observations for a model initialisation, an impact on precipitation was observed until the first strong precipitation event occurred.

  14. Global atmospheric moisture variability

    Science.gov (United States)

    Robertson, Franklin R.; James, Bonnie F.; Chi, Kay; Huang, Huo-Jin

    1989-01-01

    Research efforts during FY-88 have focused on completion of several projects relating to analysis of FGGE data during SOP-1 and on expanded studies of global atmospheric moisture. In particular, a revised paper on the relationship between diabatic heating and baroclinicity in the South Pacific Convergence Zone (SPCZ) was submitted. A summary of completed studies on diagnostic convective parameterization was presented at the Satellite Meteorology and Oceanography Convergence last February. These investigations of diabatic heating in the SPCZ have demonstrated the requirement for a more quantitative description of atmospheric moisture. As a result, efforts were directed toward use of passive remote microwave measurements from the Nimbus-7 SMMR and the DOD's Special Sensor Microwave Imager (SSMI/I) as critical sources of moisture data. Activities this year are summarized.

  15. 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

  16. Ground and surface temperature variability for remote sensing of soil moisture in a heterogeneous landscape

    Science.gov (United States)

    At the Little River Watershed (LRW) heterogeneous landscape near Tifton Georgia US an in situ network of stations operated by the US Department of Agriculture-Agriculture Research Service (USDA-ARS-SEWRL) was established in 2003 for the long term study of climatic and soil biophysical processes. To ...

  17. Intradiurnal and seasonal variability of soil temperature, heat flux, soil moisture content, and thermal properties under forest and pasture in Rondonia.

    NARCIS (Netherlands)

    Alvala, R.C.S.; Gielow, R.; Rocha, H.R.; Freitas, H.C.; Lopes, J.M.; Manzi, A.O.; von Rondow, C.; Dias, M.A.F.S.; Cabral, O.M.R.; Waterloo, M.J.

    2002-01-01

    Soil temperatures depend on the soil heat flux, an important parameter in meteorological and plant growth-energy balance models. Thus, they were measured, together with soil moisture contents, within the LBA program at forest (Reserva Jaru) and pasture (Fazenda Nossa Senhora) sites in Rondônia,

  18. 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

  19. 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

  20. 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.

  1. 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.

  2. 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

  3. 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 ...

  4. 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...

  5. 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...

  6. 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.

  7. 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.

  8. 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

  9. Short-term variability in labile soil phosphorus is positively related to soil moisture in a humid tropical forest in Puerto Rico

    Science.gov (United States)

    Tana E. Wood; Danielle Matthews; Karen Vandecar; Deborah Lawrence

    2016-01-01

    Primary productivity in tropical forests is often considered limited by phosphorus (P) availability. Microbial activity is a key regulator of available P through organic matter decomposition (supply) as well as microbial immobilization (depletion). Environmental conditions, such as soil moisture and temperature can fluctuate...

  10. 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

  11. 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...

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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,...

  18. 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

  19. 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

  20. 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.

  1. 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

  2. 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...

  3. 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...

  4. 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

  5. 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

  6. 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 ...

  7. 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

  8. 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

  9. 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

  10. 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

  11. 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 ...

  12. 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...

  13. 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.

  14. 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)

  15. Ground water level, Water storage, Soil moisture, Precipitation Variability Using Multi Satellite Data during 2003-2016 Associated with California Drought

    Science.gov (United States)

    Li, J. W.; Singh, R. P.

    2017-12-01

    The agricultural market of California is a multi-billion-dollar industry, however in the recent years, the state is facing severe drought. It is important to have a deeper understanding of how the agriculture is affected by the amount of rainfall as well as the ground conditions in California. We have considered 5 regions (each 2 degree by 2 degree) covering whole of California. Multi satellite (MODIS Terra, GRACE, GLDAS) data through NASA Giovanni portal were used to study long period variability 2003 - 2016 of ground water level and storage, soil moisture, root zone moisture level, precipitation and normalized vegetation index (NDVI) in these 5 regions. Our detailed analysis of these parameters show a strong correlation between the NDVI and some of these parameters. NDVI represents greenness showing strong drought conditions during the period 2011-2016 due to poor rainfall and recharge of ground water in the mid and southern parts of California. Effect of ground water level and underground storage will be also discussed on the frequency of earthquakes in five regions of California. The mid and southern parts of California show increasing frequency of small earthquakes during drought periods.

  16. 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.

  17. 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.

  18. 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 ...

  19. 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

  20. 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...

  1. 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.

  2. 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).

  3. 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...

  4. 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 ...

  5. 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...

  6. 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...

  7. 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...

  8. 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...

  9. 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...

  10. 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...

  11. 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.

  12. 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

  13. 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.

  14. 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.

  15. 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.

  16. 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

  17. 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

    update data sets on soil moisture retention, especially during long periods of drought. As such, description of the soil cover water balance will be more elaborate as the soil moisture profile will be described in terms of temporal and spatial variability. Moreover, this field data set can lend support on the evaluation of the potential use of mine wastes as cover materials with respect to their hydrologic and geochemical properties.

  18. 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...

  19. 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...

  20. 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...

  1. 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...

  2. 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...

  3. 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...

  4. State of the Art in Large-Scale Soil Moisture Monitoring

    Science.gov (United States)

    Ochsner, Tyson E.; Cosh, Michael Harold; Cuenca, Richard H.; Dorigo, Wouter; Draper, Clara S.; Hagimoto, Yutaka; Kerr, Yan H.; Larson, Kristine M.; Njoku, Eni Gerald; Small, Eric E.; hide

    2013-01-01

    Soil moisture is an essential climate variable influencing land atmosphere interactions, an essential hydrologic variable impacting rainfall runoff processes, an essential ecological variable regulating net ecosystem exchange, and an essential agricultural variable constraining food security. Large-scale soil moisture monitoring has advanced in recent years creating opportunities to transform scientific understanding of soil moisture and related processes. These advances are being driven by researchers from a broad range of disciplines, but this complicates collaboration and communication. For some applications, the science required to utilize large-scale soil moisture data is poorly developed. In this review, we describe the state of the art in large-scale soil moisture monitoring and identify some critical needs for research to optimize the use of increasingly available soil moisture data. We review representative examples of 1) emerging in situ and proximal sensing techniques, 2) dedicated soil moisture remote sensing missions, 3) soil moisture monitoring networks, and 4) applications of large-scale soil moisture measurements. Significant near-term progress seems possible in the use of large-scale soil moisture data for drought monitoring. Assimilation of soil moisture data for meteorological or hydrologic forecasting also shows promise, but significant challenges related to model structures and model errors remain. Little progress has been made yet in the use of large-scale soil moisture observations within the context of ecological or agricultural modeling. Opportunities abound to advance the science and practice of large-scale soil moisture monitoring for the sake of improved Earth system monitoring, modeling, and forecasting.

  5. Evaluation of Soil Moisture Derived from Passive Microwave Remote Sensing Over Agricultural Sites in Canada using ground-based Soil Moisture Monitoring Networks

    NARCIS (Netherlands)

    Champagne, C.; Berg, A; Belanger, J.; McNairn, H.; de Jeu, R.A.M.

    2010-01-01

    Passive microwave soil moisture datasets can be used as an input to provide an integrated assessment of climate variability as it relates to agricultural production. The objective of this research was to examine three passive microwave derived soil moisture datasets over multiple growing seasons in

  6. Modeling the contributions of global air temperature, synoptic-scale phenomena and soil moisture to near-surface static energy variability using artificial neural networks

    Science.gov (United States)

    Pryor, Sara C.; Sullivan, Ryan C.; Schoof, Justin T.

    2017-12-01

    The static energy content of the atmosphere is increasing on a global scale, but exhibits important subglobal and subregional scales of variability and is a useful parameter for integrating the net effect of changes in the partitioning of energy at the surface and for improving understanding of the causes of so-called warming holes (i.e., locations with decreasing daily maximum air temperatures (T) or increasing trends of lower magnitude than the global mean). Further, measures of the static energy content (herein the equivalent potential temperature, θe) are more strongly linked to excess human mortality and morbidity than air temperature alone, and have great relevance in understanding causes of past heat-related excess mortality and making projections of possible future events that are likely to be associated with negative human health and economic consequences. New nonlinear statistical models for summertime daily maximum and minimum θe are developed and used to advance understanding of drivers of historical change and variability over the eastern USA. The predictor variables are an index of the daily global mean temperature, daily indices of the synoptic-scale meteorology derived from T and specific humidity (Q) at 850 and 500 hPa geopotential heights (Z), and spatiotemporally averaged soil moisture (SM). SM is particularly important in determining the magnitude of θe over regions that have previously been identified as exhibiting warming holes, confirming the key importance of SM in dictating the partitioning of net radiation into sensible and latent heat and dictating trends in near-surface T and θe. Consistent with our a priori expectations, models built using artificial neural networks (ANNs) out-perform linear models that do not permit interaction of the predictor variables (global T, synoptic-scale meteorological conditions and SM). This is particularly marked in regions with high variability in minimum and maximum θe, where more complex models

  7. 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 ...

  8. 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.

  9. 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.

  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 estimation in cereal fields using multipolarized SAR data

    Science.gov (United States)

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

    2012-04-01

    correlation with vegetation condition and resulted to be almost insensitive to soil moisture variations. These ratios were next used to parameterize cereal vegetation cover on a retrieval scheme based on the Water Cloud Model. Results were best on VV polarization where the correlation coefficients obtained were above 0.7. The approach proposed is very promising from an operational point of view since it corrects the influence of vegetation cover in the retrieval without requiring external information to describe it. Besides, the low variability of the empirical coefficients obtained for different fields, suggests that differences in surface roughness at this stage do not significantly affect soil moisture retrievals.

  13. 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

  14. A meta-analysis of the response of soil moisture to experimental warming

    International Nuclear Information System (INIS)

    Xu, Wenfang; Yuan, Wenping; Dong, Wenjie; Xia, Jiangzhou; Liu, Dan; Chen, Yang

    2013-01-01

    Soil moisture is an important variable for regulating carbon, water and energy cycles of terrestrial ecosystems. However, numerous inconsistent conclusions have been reported regarding the responses of soil moisture to warming. In this study, we conducted a meta-analysis for examination of the response of soil moisture to experimental warming across global warming sites including several ecosystem types. The results showed that soil moisture decreased in response to warming treatments when compared with control treatments in most ecosystem types. The largest reduction of soil moisture was observed in forests, while intermediate reductions were observed in grassland and cropland, and they were both larger than the reductions observed in shrubland and tundra ecosystems. Increases (or no change) in soil moisture also occurred in some ecosystems. Taken together, these results showed a trend of soil drying in most ecosystems, which may have exerted profound impacts on a variety of terrestrial ecosystem processes as well as feedbacks to the climate system. (letter)

  15. 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

  16. 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

  17. 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.

  18. 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.

  19. 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. 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

  1. 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.

  2. 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.

  3. 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...

  4. 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

  5. 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...

  6. 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.

  7. 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

  8. 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.

  9. 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...

  10. 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 ...

  11. 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 ...

  12. 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.

  13. 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...

  14. Error characterization of microwave satellite soil moisture data sets using fourier analysis

    Science.gov (United States)

    Abstract: Soil moisture is a key geophysical variable in hydrological and meteorological processes. Accurate and current observations of soil moisture over mesoscale to global scales as inputs to hydrological, weather and climate modelling will benefit the predictability and understanding of these p...

  15. Retrieving near surface soil moisture from microwave radiometric observations: current status and future plans.

    NARCIS (Netherlands)

    Wigneron, J.P.; Calvet, J.C.; Pellarin, T.; vd Griend, A.A.; Berger, M.; Ferrazzoli, P.

    2003-01-01

    Surface soil moisture is a key variable used to describe water and energy exchanges at the land surface/atmosphere interface. Passive microwave remotely sensed data have great potential for providing estimates of soil moisture with good temporal repetition on a daily basis and on a regional scale (∼

  16. Hydrological response variability in a small vineyard catchment (D.O. Penedès, NE Spain): effects of rainfall intensity and soil moisture conditions

    Science.gov (United States)

    Carles Balasch Solanes, Josep; Concepción Ramos Martín, M.; Martínez Casasnovas, José Antonio

    2013-04-01

    The catchment of Hostalets de Pierola, a small tributary of the low course of the Anoia river (Llobregat basin), is located in the Catalan Prelitoral Depression (Penedès Depression) on Pliocene gravels and detritic Miocene substratum. The catchment size is 0.46 km2 with an average slope of 7.2 %. The main land use in the catchment is vineyards (62.3 %), with other crops and land uses with minor occupation: olive trees 4.8 %, winter cereals 9.5 %, alfalfa 8.5 %, among other). In order to carry out a research on the hydrological response and sediment transport in a representative catchment of vineyard areas in the Spanish Mediterranean region, the catchment was equipped with pluviographs to measure rainfall amount and intensity, soil moisture content sensors and a flume (HL 4" type) to measure water flow in the outlet. This water gauging allows to measure flows up to 3400 l•s-1, and it is equipped with two ultrasonic level sensors and a data-logger for data register. In parallel, monitoring of subsurface water flow of the catchment was carried out in the natural source called Can Flaquer. During the springs of 2011 and 2012 several rainfall events occurred, which allow a preliminary analysis of the hydrological response of the catchment, in comparison with rainfall characteristics (depth and intensity) and the antecedent soil moisture content. The spring events include episodes up to 27 mm, with maximum intensities of 50 mm•h-1 and peak flows up to 1100 l•s-1. The surface runoff of the catchment ceases very quickly, in a few hours after the end of rainfall events, indicating a limited role of soils in water retention and a very active percolation into the aquifer of the Pleistocene gravels. The runoff rates of the analyzed events were relatively low (between 1 - 12 %), depending on the rainfall characteristics and the antecedent soil moisture, indicating a high soil permeability. An important part of the infiltrated water follows a slow subsuperficial way to

  17. Soil surface moisture estimation over a semi-arid region using ENVISAT ASAR radar data for soil evaporation evaluation

    Directory of Open Access Journals (Sweden)

    M. Zribi

    2011-01-01

    Full Text Available The present paper proposes a method for the evaluation of soil evaporation, using soil moisture estimations based on radar satellite measurements. We present firstly an approach for the estimation and monitoring of soil moisture in a semi-arid region in North Africa, using ENVISAT ASAR images, over two types of vegetation covers. The first mapping process is dedicated solely to the monitoring of moisture variability related to rainfall events, over areas in the "non-irrigated olive tree" class of land use. The developed approach is based on a simple linear relationship between soil moisture and the backscattered radar signal normalised at a reference incidence angle. The second process is proposed over wheat fields, using an analysis of moisture variability due to both rainfall and irrigation. A semi-empirical model, based on the water-cloud model for vegetation correction, is used to retrieve soil moisture from the radar signal. Moisture mapping is carried out over wheat fields, showing high variability between irrigated and non-irrigated wheat covers. This analysis is based on a large database, including both ENVISAT ASAR and simultaneously acquired ground-truth measurements (moisture, vegetation, roughness, during the 2008–2009 vegetation cycle. Finally, a semi-empirical approach is proposed in order to relate surface moisture to the difference between soil evaporation and the climate demand, as defined by the potential evaporation. Mapping of the soil evaporation is proposed.

  18. 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

  19. 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...

  20. Using soil moisture forecasts for sub-seasonal summer temperature predictions in Europe

    Science.gov (United States)

    Orth, René; Seneviratne, Sonia I.

    2014-12-01

    Soil moisture exhibits outstanding memory characteristics and plays a key role within the climate system. Especially through its impacts on the evapotranspiration of soils and plants, it may influence the land energy balance and therefore surface temperature. These attributes make soil moisture an important variable in the context of weather and climate forecasting. In this study we investigate the value of (initial) soil moisture information for sub-seasonal temperature forecasts. For this purpose we employ a simple water balance model to infer soil moisture from streamflow observations in 400 catchments across Europe. Running this model with forecasted atmospheric forcing, we derive soil moisture forecasts, which we then translate into temperature forecasts using simple linear relationships. The resulting temperature forecasts show skill beyond climatology up to 2 weeks in most of the considered catchments. Even if forecasting skills are rather small at longer lead times with significant skill only in some catchments at lead times of 3 and 4 weeks, this soil moisture-based approach shows local improvements compared to the monthly European Centre for Medium Range Weather Forecasting (ECMWF) temperature forecasts at these lead times. For both products (soil moisture-only forecast and ECMWF forecast), we find comparable or better forecast performance in the case of extreme events, especially at long lead times. Even though a product based on soil moisture information alone is not of practical relevance, our results indicate that soil moisture (memory) is a potentially valuable contributor to temperature forecast skill. Investigating the underlying soil moisture of the ECMWF forecasts we find good agreement with the simple model forecasts, especially at longer lead times. Analyzing the drivers of the temperature forecast skills we find that they are mainly controlled by the strengths of (1) the soil moisture-temperature coupling and (2) the soil moisture memory. We

  1. 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

  2. Predicting Soil Salinity with Vis-NIR Spectra after Removing the Effects of Soil Moisture Using External Parameter Orthogonalization.

    Science.gov (United States)

    Liu, Ya; Pan, Xianzhang; Wang, Changkun; Li, Yanli; Shi, Rongjie

    2015-01-01

    Robust models for predicting soil salinity that use visible and near-infrared (vis-NIR) reflectance spectroscopy are needed to better quantify soil salinity in agricultural fields. Currently available models are not sufficiently robust for variable soil moisture contents. Thus, we used external parameter orthogonalization (EPO), which effectively projects spectra onto the subspace orthogonal to unwanted variation, to remove the variations caused by an external factor, e.g., the influences of soil moisture on spectral reflectance. In this study, 570 spectra between 380 and 2400 nm were obtained from soils with various soil moisture contents and salt concentrations in the laboratory; 3 soil types × 10 salt concentrations × 19 soil moisture levels were used. To examine the effectiveness of EPO, we compared the partial least squares regression (PLSR) results established from spectra with and without EPO correction. The EPO method effectively removed the effects of moisture, and the accuracy and robustness of the soil salt contents (SSCs) prediction model, which was built using the EPO-corrected spectra under various soil moisture conditions, were significantly improved relative to the spectra without EPO correction. This study contributes to the removal of soil moisture effects from soil salinity estimations when using vis-NIR reflectance spectroscopy and can assist others in quantifying soil salinity in the future.

  3. Predicting Soil Salinity with Vis–NIR Spectra after Removing the Effects of Soil Moisture Using External Parameter Orthogonalization

    Science.gov (United States)

    Liu, Ya; Pan, Xianzhang; Wang, Changkun; Li, Yanli; Shi, Rongjie

    2015-01-01

    Robust models for predicting soil salinity that use visible and near-infrared (vis–NIR) reflectance spectroscopy are needed to better quantify soil salinity in agricultural fields. Currently available models are not sufficiently robust for variable soil moisture contents. Thus, we used external parameter orthogonalization (EPO), which effectively projects spectra onto the subspace orthogonal to unwanted variation, to remove the variations caused by an external factor, e.g., the influences of soil moisture on spectral reflectance. In this study, 570 spectra between 380 and 2400 nm were obtained from soils with various soil moisture contents and salt concentrations in the laboratory; 3 soil types × 10 salt concentrations × 19 soil moisture levels were used. To examine the effectiveness of EPO, we compared the partial least squares regression (PLSR) results established from spectra with and without EPO correction. The EPO method effectively removed the effects of moisture, and the accuracy and robustness of the soil salt contents (SSCs) prediction model, which was built using the EPO-corrected spectra under various soil moisture conditions, were significantly improved relative to the spectra without EPO correction. This study contributes to the removal of soil moisture effects from soil salinity estimations when using vis–NIR reflectance spectroscopy and can assist others in quantifying soil salinity in the future. PMID:26468645

  4. 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.

  5. 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

  6. 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 ...

  7. 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.

  8. 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.

  9. 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.

  10. A Mulitivariate Statistical Model Describing the Compound Nature of Soil Moisture Drought

    Science.gov (United States)

    Manning, Colin; Widmann, Martin; Bevacqua, Emanuele; Maraun, Douglas; Van Loon, Anne; Vrac, Mathieu

    2017-04-01

    Soil moisture in Europe acts to partition incoming energy into sensible and latent heat fluxes, thereby exerting a large influence on temperature variability. Soil moisture is predominantly controlled by precipitation and evapotranspiration. When these meteorological variables are accumulated over different timescales, their joint multivariate distribution and dependence structure can be used to provide information of soil moisture. We therefore consider soil moisture drought as a compound event of meteorological drought (deficits of precipitation) and heat waves, or more specifically, periods of high Potential Evapotraspiration (PET). We present here a statistical model of soil moisture based on Pair Copula Constructions (PCC) that can describe the dependence amongst soil moisture and its contributing meteorological variables. The model is designed in such a way that it can account for concurrences of meteorological drought and heat waves and describe the dependence between these conditions at a local level. The model is composed of four variables; daily soil moisture (h); a short term and a long term accumulated precipitation variable (Y1 and Y_2) that account for the propagation of meteorological drought to soil moisture drought; and accumulated PET (Y_3), calculated using the Penman Monteith equation, which can represent the effect of a heat wave on soil conditions. Copula are multivariate distribution functions that allow one to model the dependence structure of given variables separately from their marginal behaviour. PCCs then allow in theory for the formulation of a multivariate distribution of any dimension where the multivariate distribution is decomposed into a product of marginal probability density functions and two-dimensional copula, of which some are conditional. We apply PCC here in such a way that allows us to provide estimates of h and their uncertainty through conditioning on the Y in the form h=h|y_1,y_2,y_3 (1) Applying the model to various

  11. 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 ...

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

    Science.gov (United States)

    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

  13. 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

  14. 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

  15. Investigating the Effect of Soil Moisture on Net Ecosystem Exchange in Shale Hills

    Science.gov (United States)

    Griffiths, Z. G.; Davis, K. J.; He, Y.

    2016-12-01

    Carbon sinks have the ability to absorb more carbon dioxide than what they emit. The terrestrial biome acts as a huge carbon sink, however, this ability is dependent on different environmental factors. This study focused on the effects of soil moisture on net ecosystem exchange(NEE) in the Shale Hills Critical Zone Observatory, PA. It was hypothesized that the strength of the carbon sink would grow with wetter soils. Data was collected from the eddy-covariance flux tower, a COSMOS soil moisture probe, automated soil respiration chambers and sap flow probes for May to August between the years 2011-2016. Since temperature and photosynthetically active radiation(PAR) also have an effect on carbon fluxes, these variables were isolated to properly study soil moisture and carbon fluxes. Generally, less carbon dioxide was absorbed with increasing soil moisture. Since NEE is a combination of photosynthesis and respiration, the effect of soil moisture was studied separately for each process. The sap flow data showed a decrease in activity with increasing soil moisture, hence photosynthesis was most likely reduced. Additionally, more carbon dioxide was emitted from respiration with increasing soil moisture. These findings could possibly explain why the forest at Shale Hills tends to release more carbon dioxide with increasing soil moisture.

  16. Potential and limitations of multidecadal satellite soil moisture observations for selected climate model evaluation studies

    Directory of Open Access Journals (Sweden)

    A. Loew

    2013-09-01

    Full Text Available Soil moisture is an essential climate variable (ECV of major importance for land–atmosphere interactions and global hydrology. An appropriate representation of soil moisture dynamics in global climate models is therefore important. Recently, a first multidecadal, observation-based soil moisture dataset has become available that provides information on soil moisture dynamics from satellite observations (ECVSM, essential climate variable soil moisture. The present study investigates the potential and limitations of this new dataset for several applications in climate model evaluation. We compare soil moisture data from satellite observations, reanalysis and simulations from a state-of-the-art land surface model and analyze relationships between soil moisture and precipitation anomalies in the different dataset. Other potential applications like model parameter optimization or model initialization are not investigated in the present study. In a detailed regional study, we show that ECVSM is capable to capture well the interannual and intraannual soil moisture and precipitation dynamics in the Sahelian region. Current deficits of the new dataset are critically discussed and summarized at the end of the paper to provide guidance for an appropriate usage of the ECVSM dataset for climate studies.

  17. 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

  18. 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

  19. 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...

  20. 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.

  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. 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.

  3. 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.

  4. Effects of antecedent soil moisture on runoff modeling in small semiarid watersheds of southeastern Arizona

    Directory of Open Access Journals (Sweden)

    Y. Zhang

    2011-10-01

    Full Text Available This study presents unique data on the effects of antecedent soil moisture on runoff generation in a semi-arid environment, with implications for process-based modeling of runoff. The data were collected from four small watersheds measured continuously from 2002 through 2010 in an environment where evapo-transpiration approaches 100% of the infiltrated water on the hillslopes. Storm events were generally intense and of short duration, and antecedent volumetric moisture conditions were dry, with an average in the upper 5 cm soil layer over the nine year period of 8% and a standard deviation of 3%. Sensitivity analysis of the model showed an average of 0.05 mm change in runoff for each 1% change in soil moisture, indicating an approximate 0.15 mm average variation in runoff accounted for by the 3% standard deviation of measured antecedent soil moisture. This compared to a standard deviation of 4.7 mm in the runoff depths for the measured events. Thus the low variability of soil moisture in this environment accounts for a relative lack of importance of storm antecedent soil moisture for modeling the runoff. Runoff characteristics simulated with a nine year average of antecedent soil moisture were statistically identical to those simulated with measured antecedent soil moisture, indicating that long term average antecedent soil moisture could be used as a substitute for measured antecedent soil moisture for runoff modeling of these watersheds. We also found no significant correlations between measured runoff ratio and antecedent soil moisture in any of the four watersheds.

  5. Role of soil moisture versus recent climate change for the 2010 heat wave in western Russia

    Science.gov (United States)

    Hauser, Mathias; Orth, René; Seneviratne, Sonia I.

    2016-03-01

    The severe 2010 heat wave in western Russia was found to be influenced by anthropogenic climate change. Additionally, soil moisture-temperature feedbacks were deemed important for the buildup of the exceptionally high temperatures. We quantify the relative role of both factors by applying the probabilistic event attribution framework and analyze ensemble simulations to distinguish the effect of climate change and the 2010 soil moisture conditions for annual maximum temperatures. The dry 2010 soil moisture alone has increased the risk of a severe heat wave in western Russia sixfold, while climate change from 1960 to 2000 has approximately tripled it. The combined effect of climate change and 2010 soil moisture yields a 13 times higher heat wave risk. We conclude that internal climate variability causing the dry 2010 soil moisture conditions formed a necessary basis for the extreme heat wave.

  6. Regional amplification of projected changes in extreme temperatures strongly controlled by soil moisture-temperature feedbacks

    Science.gov (United States)

    Vogel, M. M.; Orth, R.; Cheruy, F.; Hagemann, S.; Lorenz, R.; Hurk, B. J. J. M.; Seneviratne, S. I.

    2017-02-01

    Regional hot extremes are projected to increase more strongly than global mean temperature, with substantially larger changes than 2°C even if global warming is limited to this level. We investigate the role of soil moisture-temperature feedbacks for this response based on multimodel experiments for the 21st century with either interactive or fixed (late 20th century mean seasonal cycle) soil moisture. We analyze changes in the hottest days in each year in both sets of experiments, relate them to the global mean temperature increase, and investigate processes leading to these changes. We find that soil moisture-temperature feedbacks significantly contribute to the amplified warming of the hottest days compared to that of global mean temperature. This contribution reaches more than 70% in Central Europe and Central North America. Soil moisture trends are more important for this response than short-term soil moisture variability. These results are relevant for reducing uncertainties in regional temperature projections.

  7. Assimilating the cosmic-ray soil moisture observing system measurements for understanding watershed hydrodynamics

    Science.gov (United States)

    Xiao, D.; Cai, Z.; Shi, Y.; Li, L.

    2016-12-01

    Soil moisture is an essential variable in hydrologic, land-surface and reactive transport processes. The intermediate-scale cosmic-ray soil moisture observing system (COSMOS) provides average soil water content measurement over a footprint of 0.34 km2 with depths up to 70 cm and an innovative means to understand watershed water dynamics. Compared with point measurements at the scale of centimeters, the COSMOS data represent averaged soil moisture at the scale of hundreds of meters. In this study, we test the use of COSMOS observations in constraining parameters in a physics-based hydrology model Flux-PIHM via the ensemble Kalman filter (EnKF). We aim to investigate 1) how COSMOS data can be used to predict soil moisture in a low-order watershed by Flux-PIHM, 2) which parameters are critical in predicting areal averaged soil moisture, and 3) how changes in data availability of the COSMOS influence prediction of watershed hydrodynamics. Synthetic data experiments are performed at the Shale Hills Susquehanna Critical Zone Observatory in central Pennsylvania. The COSMOS data is assimilated into Flux-PIHM using the EnKF, in addition to discharge and land surface temperature observations. The assimilation of COSMOS measurements can improve the model prediction of top layer soil moisture, and the soil parameters like van Genuchten β and porosity are critical in reproducing areal averaged soil moisture. The accuracy of EnKF estimated parameters and water and energy flux predictions is evaluated, reflecting the sensitivity of the observation to the corresponding parameter related hydrologic processes. In addition, the results are compared with assimilating point soil moisture measurement to assess the effects of soil moisture measurements at different scales in calibrating Flux-PIHM. The data retrieval frequency experiments evaluate the consequence of data availability on the hydrodynamics of simulated soil moisture profiles. We found that there exists an optimal data

  8. The use of remotely sensed soil moisture data in large-scale models of the hydrological cycle

    Science.gov (United States)

    Salomonson, V. V.; Gurney, R. J.; Schmugge, T. J.

    1985-01-01

    Manabe (1982) has reviewed numerical simulations of the atmosphere which provided a framework within which an examination of the dynamics of the hydrological cycle could be conducted. It was found that the climate is sensitive to soil moisture variability in space and time. The challenge arises now to improve the observations of soil moisture so as to provide up-dated boundary condition inputs to large scale models including the hydrological cycle. Attention is given to details regarding the significance of understanding soil moisture variations, soil moisture estimation using remote sensing, and energy and moisture balance modeling.

  9. 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

  10. 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

  11. Soil gas radon response to environmental and soil physics variables

    International Nuclear Information System (INIS)

    Thomas, D.M.; Chen, C.; Holford, D.

    1991-01-01

    During the last three years a field study of soil gas radon activities conducted at Poamoho, Oahu, has shown that the primary environmental variables that control radon transport in shallow tropical soils are synoptic and diurnal barometric pressure changes and soil moisture levels. Barometric pressure changes drive advective transport and mixing of soil gas with atmospheric air; soil moisture appears to control soil porosity and permeability to enhance or inhibit advective and diffusive radon transport. An advective barrier test/control experiment has shown that advective exchange of soil gas and air may account for a substantial proportion of the radon loss from shallow soils but does not significantly affect radon activities at depths greater than 2.3 m. An irrigation test/control experiment also suggests that, at soil moisture levels approaching field capacity, saturation of soil macroporosity can halt all advective transport of radon and limit diffusive mobility to that occurring in the liquid phase. The results of the authors field study have been used to further refine and extend a numerical model, RN3D, that has been developed by Pacific Northwest Laboratories to simulate subsurface transport of radon. The field data have allowed them to accurately simulate the steady state soil gas radon profile at their field site and to track transient radon activities under the influence of barometric pressure changes and in response to changes in soil permeability that result from variations in soil moisture levels. Further work is continuing on the model to enable it to properly account for the relative effects of advective transport of soil gas through cracks and diffusive mobility in the bulk soils

  12. 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).

  13. 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...

  14. 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

  15. 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

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. Regional amplification of projected changes in extreme temperatures strongly controlled by soil moisture-temperature feedbacks

    Science.gov (United States)

    Vogel, Martha Marie; Orth, René; Cheruy, Frederique; Hagemann, Stefan; Lorenz, Ruth; van den Hurk, Bart; Seneviratne, Sonia Isabelle

    2017-04-01

    Regional hot extremes are projected to increase more strongly than global mean temperature, with substantially larger changes than 2°C even if global warming is limited to this level. We investigate here the role of soil moisture-temperature feedbacks for this response based on multi-model experiments for the 21st century with either interactive or fixed (late 20th century mean seasonal cycle) soil moisture. We analyze changes in the hottest days in each year in both sets of experiments, relate them to the global mean temperature increase, and investigate physical processes leading to these changes. We find that soil moisture-temperature feedbacks significantly contribute to the amplified warming of hottest days compared to that of global mean temperature. This contribution reaches more than 70% in Central Europe and Central North America and between 42%-52% in Amazonia, Northern Australia and Southern Africa. Soil moisture trends (multi-decadal soil moisture variability) are more important for this response than short-term (e.g. seasonal, interannual) soil moisture variability. These results are relevant for reducing uncertainties in regional temperature projections. Vogel, M.M. et al.,2017. Regional amplification of projected changes in extreme temperatures strongly controlled by soil moisture-temperature feedbacks. Geophysical Research Letters, accepted.

  1. Improving terrestrial evaporation estimates over continental Australia through assimilation of SMOS soil moisture

    Science.gov (United States)

    Martens, B.; Miralles, D.; Lievens, H.; Fernández-Prieto, D.; Verhoest, N. E. C.

    2016-06-01

    Terrestrial evaporation is an essential variable in the climate system that links the water, energy and carbon cycles over land. Despite this crucial importance, it remains one of the most uncertain components of the hydrological cycle, mainly due to known difficulties to model the constraints imposed by land water availability on terrestrial evaporation. The main objective of this study is to assimilate satellite soil moisture observations from the Soil Moisture and Ocean Salinity (SMOS) mission into an existing evaporation model. Our over-arching goal is to find an optimal use of satellite soil moisture that can help to improve our understanding of evaporation at continental scales. To this end, the Global Land Evaporation Amsterdam Model (GLEAM) is used to simulate evaporation fields over continental Australia for the period September 2010-December 2013. SMOS soil moisture observations are assimilated using a Newtonian Nudging algorithm in a series of experiments. Model estimates of surface soil moisture and evaporation are validated against soil moisture probe and eddy-covariance measurements, respectively. Finally, an analogous experiment in which Advanced Microwave Scanning Radiometer (AMSR-E) soil moisture is assimilated (instead of SMOS) allows to perform a relative assessment of the quality of both satellite soil moisture products. Results indicate that the modelled soil moisture from GLEAM can be improved through the assimilation of SMOS soil moisture: the average correlation coefficient between in situ measurements and the modelled soil moisture over the complete sample of stations increased from 0.68 to 0.71 and a statistical significant increase in the correlations is achieved for 17 out of the 25 individual stations. Our results also suggest a higher accuracy of the ascending SMOS data compared to the descending data, and overall higher quality of SMOS compared to AMSR-E retrievals over Australia. On the other hand, the effect of soil moisture data

  2. Propagation of soil moisture memory to streamflow and evapotranspiration in Europe

    Directory of Open Access Journals (Sweden)

    R. Orth

    2013-10-01

    Full Text Available As a key variable of the land-climate system soil moisture is a main driver of streamflow and evapotranspiration under certain conditions. Soil moisture furthermore exhibits outstanding memory (persistence characteristics. Many studies also report distinct low frequency variations for streamflow, which are likely related to soil moisture 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 streamflow and evapotranspiration on different time scales. For this purpose we use a simple water balance model in which dependencies of runoff (normalised by precipitation and evapotranspiration (normalised by radiation on soil moisture are fitted using streamflow observations. The model therefore allows us to compute the memory characteristics of soil moisture, streamflow and evapotranspiration on the catchment scale. We find considerable memory in soil moisture and streamflow in many parts of the continent, and evapotranspiration also displays some memory at monthly time scale in some catchments. We show that the memory of streamflow and evapotranspiration jointly depend on soil moisture memory and on the strength of the coupling of streamflow and evapotranspiration to soil moisture. Furthermore, we find that the coupling strengths of streamflow 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.

  3. Propagation of soil moisture memory to streamflow and evapotranspiration in Europe

    Science.gov (United States)

    Orth, R.; Seneviratne, S. I.

    2013-10-01

    As a key variable of the land-climate system soil moisture is a main driver of streamflow and evapotranspiration under certain conditions. Soil moisture furthermore exhibits outstanding memory (persistence) characteristics. Many studies also report distinct low frequency variations for streamflow, which are likely related to soil moisture 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 streamflow and evapotranspiration on different time scales. For this purpose we use a simple water balance model in which dependencies of runoff (normalised by precipitation) and evapotranspiration (normalised by radiation) on soil moisture are fitted using streamflow observations. The model therefore allows us to compute the memory characteristics of soil moisture, streamflow and evapotranspiration on the catchment scale. We find considerable memory in soil moisture and streamflow in many parts of the continent, and evapotranspiration also displays some memory at monthly time scale in some catchments. We show that the memory of streamflow and evapotranspiration jointly depend on soil moisture memory and on the strength of the coupling of streamflow and evapotranspiration to soil moisture. Furthermore, we find that the coupling strengths of streamflow 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.

  4. Upscaling of Surface Soil Moisture Using a Deep Learning Model with VIIRS RDR

    Directory of Open Access Journals (Sweden)

    Dongying Zhang

    2017-04-01

    Full Text Available In current upscaling of in situ surface soil moisture practices, commonly used novel statistical or machine learning-based regression models combined with remote sensing data show some advantages in accurately capturing the satellite footprint scale of specific local or regional surface soil moisture. However, the performance of most models is largely determined by the size of the training data and the limited generalization ability to accomplish correlation extraction in regression models, which are unsuitable for larger scale practices. In this paper, a deep learning model was proposed to estimate soil moisture on a national scale. The deep learning model has the advantage of representing nonlinearities and modeling complex relationships from large-scale data. To illustrate the deep learning model for soil moisture estimation, the croplands of China were selected as the study area, and four years of Visible Infrared Imaging Radiometer Suite (VIIRS raw data records (RDR were used as input parameters, then the models were trained and soil moisture estimates were obtained. Results demonstrate that the estimated models captured the complex relationship between the remote sensing variables and in situ surface soil moisture with an adjusted coefficient of determination of R ¯ 2 = 0.9875 and a root mean square error (RMSE of 0.0084 in China. These results were more accurate than the Soil Moisture Active Passive (SMAP active radar soil moisture products and the Global Land data assimilation system (GLDAS 0–10 cm depth soil moisture data. Our study suggests that deep learning model have potential for operational applications of upscaling in situ surface soil moisture data at the national scale.

  5. Long-term predictability of soil moisture dynamics at the global scale: Persistence versus large-scale drivers

    Science.gov (United States)

    Nicolai-Shaw, Nadine; Gudmundsson, Lukas; Hirschi, Martin; Seneviratne, Sonia I.

    2016-08-01

    Here we investigate factors that influence the long lead time predictability of soil moisture variability using standard statistical methods. As predictors we first consider soil moisture persistence only, using two independent global soil moisture data sets. In a second step we include three teleconnection indices indicative of the main northern, tropical, and southern atmospheric modes, i.e., the North Atlantic Oscillation (NAO), the Southern Oscillation Index (SOI), and the Antarctic Oscillation (AAO). For many regions results show significant skill in predicting soil moisture variability with lead times up to 5 months. Soil moisture persistence plays a key role at monthly to subseasonal time scales. With increasing lead times large-scale atmospheric drivers become more important, and areas influenced by teleconnection indices show higher predictability. This long lead time predictability of soil moisture may help to improve early warning systems for important natural hazards, such as heat waves, droughts, wildfires, and floods.

  6. 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.

  7. 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.

  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. 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.

  10. 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.

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

    Science.gov (United States)

    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...

  12. 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).

  13. 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...

  14. 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

  15. 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

  16. 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...

  17. 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

  18. Assessing the effect of soil use changes on soil moisture regimes in mountain regions. (Catalan Pre-Pyrenees NE Spain)

    International Nuclear Information System (INIS)

    Loaiza Usuga, Juan Carlos; Jarauta Bragulat, Eusebio; Porta Casanellas, Jaume; Poch Claret, Rosa Maria

    2010-01-01

    Soil moisture regimes under different land uses were observed and modeled in a representative forest basin in the Catalonian Pre-Pyrenees, more specifically in the Ribera Salada catchment (222.5 km2). The vegetation cover in the catchment consists of pasture, tillage and forest. A number of representative plots for each of these land cover types were intensely monitored during the study period. The annual precipitation fluctuates between 516 and 753 mm, while the soil moisture content oscillates between 14 and 26% in the middle and low lying areas of the basin, and between 21 and 48% in shady zones near the river bed, and in the higher parts of the basin. Soil moisture and rainfall are controlled firstly by altitude, with the existence of two climatic types in the basin (sub-Mediterranean and sub-alpine), and further, by land use. Two models were applied to the estimated water moisture regimes: the Jarauta Simulation Newhall model (JSM) and the Newhall simulation model (NSM) were found to be able to predict the soil moisture regimes in the basin in the different combinations of local abiotic and biotic factors. The JSM results are more precise than the results obtained using another frequently used method, more specifically the Newhall Simulation Model (NSM), which has been developed to simulate soil moisture regimes. NSM was found to overestimate wet soil moisture regimes. The results show the importance of the moisture control section size and Available Water Capacity (AWC) of the profile, in the moisture section control state and variability. The mountain soils are dominated by rustic and occasionally xeric regimes. Land use changes leading to an increase in forest areas would imply drier soil conditions and therefore drier soil water regimes. These effects are most evident in degraded shallow and stony soils with low AWC.

  19. A global validation of the ASCAT Soil Water Index (SWI) with in situ data from the International Soil Moisture Network.

    Science.gov (United States)

    Paulik, C.; Naeimi, V.; Dorigo, W.; Wagner, W.; Kidd, R.

    2012-04-01

    Soil Moisture is an Essential Climate Variable and a key parameter in hydrology, meteorology and agriculture. Surface Soil Moisture (SSM) can be estimated from measurements taken by ASCAT onboard Metop-A and have been successfully validated by several studies (C. Albergel et.al. 2009 and 2012, M.Parrens et.al. 2012). Profile soil moisture, while equally important, can not be measured directly by remote sensing. The near real-time Soil Water Index (SWI) product, developed within the framework of the GMES project geoland2 aims to close this gap. It is produced from ASCAT SSM estimates using a two-layer water balance model which describes the relationship between surface and profile soil moisture as a function of time. It provides daily global data about moisture conditions for 8 characteristic time lengths representing different depths. The objective of this work was to assess the quality of the SWI data for different measurement depths. SWI data from January 1st 2007 until the end of 2010 was compared to in situ soil moisture data from 420 stations belonging to 22 observation networks which are available through the International Soil Moisture Network. These stations delivered 1331 station/depth combinations which were compared to the SWI values. After excluding observations made during frozen conditions the average significant correlation coefficients were 0.564 (min -0.684, max 0.955) while being greater than 0.3 for 88% of all station/depth combinations.

  20. 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.

  1. 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.

  2. A comparison of methods for a priori bias correction in soil moisture data assimilation

    Science.gov (United States)

    Kumar, Sujay V.; Reichle, Rolf H.; Harrison, Kenneth W.; Peters-Lidard, Christa D.; Yatheendradas, Soni; Santanello, Joseph A.

    2012-03-01

    Data assimilation is increasingly being used to merge remotely sensed land surface variables such as soil moisture, snow, and skin temperature with estimates from land models. Its success, however, depends on unbiased model predictions and unbiased observations. Here a suite of continental-scale, synthetic soil moisture assimilation experiments is used to compare two approaches that address typical biases in soil moisture prior to data assimilation: (1) parameter estimation to calibrate the land model to the climatology of the soil moisture observations and (2) scaling of the observations to the model's soil moisture climatology. To enable this research, an optimization infrastructure was added to the NASA Land Information System (LIS) that includes gradient-based optimization methods and global, heuristic search algorithms. The land model calibration eliminates the bias but does not necessarily result in more realistic model parameters. Nevertheless, the experiments confirm that model calibration yields assimilation estimates of surface and root zone soil moisture that are as skillful as those obtained through scaling of the observations to the model's climatology. Analysis of innovation diagnostics underlines the importance of addressing bias in soil moisture assimilation and confirms that both approaches adequately address the issue.

  3. 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

  4. 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

  5. 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.

  6. Seasonality in ENSO-related precipitation, river discharges, soil moisture, and vegetation index in Colombia

    Science.gov (United States)

    Poveda, GermáN.; Jaramillo, Alvaro; Gil, Marta MaríA.; Quiceno, Natalia; Mantilla, Ricardo I.

    2001-08-01

    An analysis of hydrologic variability in Colombia shows different seasonal effects associated with El Niño/Southern Oscillation (ENSO) phenomenon. Spectral and cross-correlation analyses are developed between climatic indices of the tropical Pacific Ocean and the annual cycle of Colombia's hydrology: precipitation, river flows, soil moisture, and the Normalized Difference Vegetation Index (NDVI). Our findings indicate stronger anomalies during December-February and weaker during March-May. The effects of ENSO are stronger for streamflow than for precipitation, owing to concomitant effects on soil moisture and evapotranspiration. We studied time variability of 10-day average volumetric soil moisture, collected at the tropical Andes of central Colombia at depths of 20 and 40 cm, in coffee growing areas characterized by shading vegetation ("shaded coffee"), forest, and sunlit coffee. The annual and interannual variability of soil moisture are highly intertwined for the period 1997-1999, during strong El Niño and La Niña events. Soil moisture exhibited greater negative anomalies during 1997-1998 El Niño, being strongest during the two dry seasons that normally occur in central Colombia. Soil moisture deficits were more drastic at zones covered by sunlit coffee than at those covered by forest and shaded coffee. Soil moisture responds to wetter than normal precipitation conditions during La Niña 1998-1999, reaching maximum levels throughout that period. The probability density function of soil moisture records is highly skewed and exhibits different kinds of multimodality depending upon land cover type. NDVI exhibits strong negative anomalies throughout the year during El Niños, in particular during September-November (year 0) and June-August (year 0). The strong negative relation between NDVI and El Niño has enormous implications for carbon, water, and energy budgets over the region, including the tropical Andes and Amazon River basin.

  7. 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.

  8. An Arduino Based Citizen Science Soil Moisture Sensor in Support of SMAP and GLOBE

    Science.gov (United States)

    Podest, E.; Das, N. N.; Rajasekaran, E.; Jeyaram, R.; Lohrli, C.; Hovhannesian, H.; Fairbanks, G.

    2017-12-01

    Citizen science allows individuals anywhere in the world to engage in science by collecting environmental variables. One of the longest running platforms for the collection of in situ variables is the GLOBE program, which is international in scope and encourages students and citizen scientists alike to collect in situ measurements. NASA's Soil Moisture Active Passive (SMAP) satellite mission, which has been acquiring global soil moisture measurements every 3 days of the top 5 cm of the soil since 2015, has partnered with the GLOBE program to engage students from around the world to collect in situ soil moisture and help validate SMAP measurements. The current GLOBE SMAP soil moisture protocol consists in collecting a soil sample, weighing, drying and weighing it again in order to determine the amount of water in the soil. Preparation and soil sample collection can take up to 20 minutes and drying can take up to 3 days. We have hence developed a soil moisture measurement device based on Arduino- microcontrollers along with off-the-shelf and homemade sensors that are accurate, robust, inexpensive and quick and easy to use so that they can be implemented by the GLOBE community and citizen scientists alike. In addition, we have developed a phone app, which interfaces with the Arduino, displays the soil moisture value and send the measurement to the GLOBE database. This talk will discuss building, calibration and validation of the soil moisture measuring device and assessing the quality of the measurements collected. This work was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration.

  9. Improving Long-term Global Precipitation Dataset Using Multi-sensor Surface Soil Moisture Retrievals and the Soil Moisture Analysis Rainfall Tool (SMART)

    Science.gov (United States)

    Chen, F.; Crow, W. T.; Holmes, T. R.

    2012-12-01

    Using multiple historical satellite surface soil moisture products, the Kalman Filtering-based Soil Moisture Analysis Rainfall Tool (SMART) is applied to improve the accuracy of a multi-decadal global daily rainfall product that has been bias-corrected to match the monthly totals of available rain gauge observations. In order to adapt to the irregular retrieval frequency of heritage soil moisture products, a new variable correction window method is developed which allows for better efficiency in leveraging temporally sparse satellite soil moisture retrievals. Results confirm the advantage of using this variable window method relative to an existing fixed-window version of SMART over a range of accumulation periods. Using this modified version of SMART, and heritage satellite surface soil moisture products, a 1.0-degree, 1979-1998 global rainfall dataset over land is corrected and validated. Relative to the original precipitation product, the updated correction scheme demonstrates improved root-mean-square-error and correlation accuracy and provides a higher probability of detection and lower false alarm rates for 3-day rainfall accumulation estimates, except for the heaviest (99th percentile) cases. This corrected rainfall dataset is expected to provide improved rainfall forcing data for the land surface modeling community.

  10. Improving long-term, retrospective precipitation datasets using satellite-based surface soil moisture retrievals and the Soil Moisture Analysis Rainfall Tool

    Science.gov (United States)

    Chen, Fan; Crow, Wade T.; Holmes, Thomas R. H.

    2012-01-01

    Using historical satellite surface soil moisture products, the Soil Moisture Analysis Rainfall Tool (SMART) is applied to improve the submonthly scale accuracy of a multi-decadal global daily rainfall product that has been bias-corrected to match the monthly totals of available rain gauge observations. In order to adapt to the irregular retrieval frequency of heritage soil moisture products, a new variable correction window method is developed that allows for better efficiency in leveraging temporally sparse satellite soil moisture retrievals. Results confirm the advantage of using this variable window method relative to an existing fixed-window version of SMART over a range of one- to 30-day accumulation periods. Using this modified version of SMART and heritage satellite surface soil moisture products, a 1.0-deg, 20-year (1979 to 1998) global rainfall dataset over land is corrected and validated. Relative to the original precipitation product, the corrected dataset demonstrates improved correlation with a global gauge-based daily rainfall product, lower root-mean-square-error (-13%) on a 10-day scale and provides a higher probability of detection (+5%) and lower false alarm rates (-3.4%) for five-day rainfall accumulation estimates. This corrected rainfall dataset is expected to provide improved rainfall forcing data for the land surface modeling community.

  11. 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)

  12. 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,...

  13. 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.

  14. The effect of soil moisture anomalies on maize yield in Germany

    Science.gov (United States)

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

    2018-03-01

    Crop models routinely use meteorological variations to estimate crop yield. Soil moisture, however, is the primary source of water for plant growth. The aim of this study is to investigate the intraseasonal predictability of soil moisture to estimate silage maize yield in Germany. We also evaluate how approaches considering soil moisture perform compare to those using only meteorological variables. Silage maize is one of the most widely cultivated crops in Germany because it is used as a main biomass supplier for energy production in the course of the German Energiewende (energy transition). Reduced form fixed effect panel models are employed to investigate the relationships in this study. These models are estimated for each month of the growing season to gain insights into the time-varying effects of soil moisture and meteorological variables. Temperature, precipitation, and potential evapotranspiration are used as meteorological variables. Soil moisture is transformed into anomalies which provide a measure for the interannual variation within each month. The main result of this study is that soil moisture anomalies have predictive skills which vary in magnitude and direction depending on the month. For instance, dry soil moisture anomalies in August and September reduce silage maize yield more than 10 %, other factors being equal. In contrast, dry anomalies in May increase crop yield up to 7 % because absolute soil water content is higher in May compared to August due to its seasonality. With respect to the meteorological terms, models using both temperature and precipitation have higher predictability than models using only one meteorological variable. Also, models employing only temperature exhibit elevated effects.

  15. Assessment Of Backscatter Variations In Tundra Regions With Respect To Uncertainties In Soil Moisture Retrieval

    Science.gov (United States)

    Hogstrom, Elin; Bartsch, Annett; Gouttevin, Isabelle

    2013-12-01

    Knowledge of surface hydrology is relevant for many applications, including improving our understanding of permafrost response and feedback in a changing climate. Advances in remote-sensing techniques and retrieval algorithms can provide a range of land surface parameters, such as radar backscatter derived surface soil moisture. It has previously been pointed out that soil moisture retrieval can be challenging in high latitudes. This study investigates backscatter variability other than associated with changing soil moisture with focus on issues specific to the arctic, notably on variations related to water bodies. ENVISAT ASAR data are utilized for quantification of potential impacts on Metop ASCAT soil moisture retrieval during the snow free period. Ice cover on lakes is identified as a mayor contributor of impact.

  16. Four decades of microwave satellite soil moisture observations : Part 2. Product validation and inter-satellite comparisons

    NARCIS (Netherlands)

    Karthikeyan, L.; Pan, Ming; Wanders, Niko; Kumar, D. Nagesh; Wood, Eric F.

    2017-01-01

    Soil moisture is widely recognized as an important land surface variable that provides a deeper knowledge of land-atmosphere interactions and climate change. Space-borne passive and active microwave sensors have become valuable and essential sources of soil moisture observations at global scales.

  17. 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

  18. Quantifying the effect of nighttime interactions between roots and canopy physiology and their control of water and carbon cycling on feedbacks between soil moisture and terrestrial climatology under variable environmental conditions

    Energy Technology Data Exchange (ETDEWEB)

    Domec, Jean-Christophe [North Carolina State Univ., Raleigh, NC (United States); Palmroth, Sari [Duke Univ., Durham, NC (United States); Oren, Ram [Duke Univ., Durham, NC (United States); Swenson, Jennifer [Duke Univ., Durham, NC (United States); King, John S. [North Carolina State Univ., Raleigh, NC (United States); Noormets, Asko [North Carolina State Univ., Raleigh, NC (United States)

    2016-04-01

    The primary objective of this project is to characterize and quantify how the temporal variability of hydraulic redistribution (HR) and its physiological regulation in unmanaged and complex forests is affecting current water and carbon exchange and predict how future climate scenarios will affect these relationships and potentially feed back to the climate. Specifically, a detailed study of ecosystem water uptake and carbon exchange in relation to root functioning was proposed in order to quantify the mechanisms controlling temporal variability of soil moisture dynamic and HR in three active AmeriFlux sites, and to use published data of two other inactive AmeriFlux sites. Furthermore, data collected by our research group at the Duke Free Air CO2 enrichment (FACE) site was also being utilized to further improve our ability to forecast future environmental impacts of elevated CO2 concentration on soil moisture dynamic and its effect on carbon sequestration and terrestrial climatology. The overarching objective being to forecast, using a soil:plant:atmosphere model coupled with a biosphere:atmosphere model, the impact of root functioning on land surface climatology. By comparing unmanaged sites to plantations, we also proposed to determine the effect of land use change on terrestrial carbon sequestration and climatology through its effect on soil moisture dynamic and HR. Our simulations of HR by roots indicated that in some systems HR is an important mechanism that buffers soil water deficit, affects energy and carbon cycling; thus having significant implications for seasonal climate. HR maintained roots alive and below 70% loss of conductivity and our simulations also showed that the increased vapor pressure deficit at night under future conditions was sufficient to drive significant nighttime transpiration at all sites, which reduced HR. This predicted reduction in HR under future climate conditions played an important regulatory role in land atmosphere interactions

  19. 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

  20. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  2. SMAP Soil Moisture Data To Improve Remotely Sensed Global Estimates of Evapotranspiration

    Science.gov (United States)

    Purdy, A. J.; Fisher, J.; Goulden, M.; Famiglietti, J. S.

    2016-12-01

    Surface water availability limits plant productivity and the ability to transport water from the soil to the atmosphere in over 1/3rd of earth's vegetated land. Quantifying evapotranspiration (ET) across large areas requires the integration of satellite-observed land surface variables into physical or empirical equations that govern the transfer of mass and energy from land to the atmosphere. Many satellite ET algorithms have been developed to compute ET globally, but the current methods of two widely-used ET algorithms rely on implicit representation of soil moisture, limiting their capacity to impose proper physical constraints on ET under water limiting conditions. The successful launch of the Soil Moisture Active Passive (SMAP) satellite provides the first space-based soil moisture observations with the fidelity and the necessary spatio-temporal resolution to integrate directly into remote sensing ET algorithms and compare to in situ observations. Here we incorporate SMAP soil moisture observations into two widely used ET algorithms, the Priestley Taylor Jet Propulsion Laboratory (PT-JPL) ET model and the Penman Monteith MOD16. We present new soil moisture stress formulation and parameterization for each algorithm and evaluate model performance before and after soil moisture integration across a suite of in situ observations spanning a range of plant functional types and climates.

  3. Comparison of soil moisture products obtained from active and passive microwave data

    Science.gov (United States)

    Dente, L.; Vekerdy, Z.; de Jeu, R.

    2009-04-01

    Forty years of research on passive and active microwave observations have led so far to a better understanding of the sensitivity of satellite microwave observations to soil moisture and to a higher confidence in the possibility to retrieve reliable soil moisture from these sensors at small as well as large scale. This research forms the basis of two important new satellite missions: ESA's Soil Moisture and Ocean Salinity mission (SMOS) and NASA's Soil Moisture Active and Passive mission (SMAP) whose main goal is the retrieval of soil moisture at global scale. In view of these missions, the research has been recently focussed more on the development of soil moisture retrieval methods which can be applied at global scale and on their application over the existing scatterometer (ERS scatterometer and Metop ASCAT) and radiometer (SMMR and AMSR-E) data to obtain long time series of global products. In this work, two global soil moisture products, one obtained from radiometer data and the other from scatterometer data, have been compared. The main objective of this comparison is to better understand the potential and limitations for soil moisture retrieval of both the data and the applied method and to investigate the possible complementarity of the different datasets. The two surface soil moisture datasets employed in this study are: the product obtained from AQUA AMSR-E data by the Department of Hydrology and Geo-Environmental Sciences of the Vrije Universiteit of Amsterdam and the product retrieved from ERS-2 scatterometer data by the Institute of Photogrammetry and Remote Sensing of the Vienna University of Technology. The temporal variability from 2003 to 2007, the seasonal trends, the anomalies, the autocorrelations and the correlation between the two global datasets have been analysed. Two in-situ datasets collected by large soil moisture monitoring networks in Oklahoma (Oklahoma Mesonet) and in Australia (OzNet) have been also included in this comparison

  4. 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 ...

  5. 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 ...

  6. 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.

  7. Measurements of soil respiration and simple models dependent on moisture and temperature for an Amazonian southwest tropical forest

    NARCIS (Netherlands)

    Zanchi, F.B.; Rocha, Da H.R.; Freitas, De H.C.; Kruijt, B.; Waterloo, M.J.; Manzi, A.O.

    2009-01-01

    Soil respiration plays a significant role in the carbon cycle of Amazonian tropical forests, although in situ measurements have only been poorly reported and the dependence of soil moisture and soil temperature also weakly understood. This work investigates the temporal variability of soil

  8. 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.

  9. 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

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

    Science.gov (United States)

    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

  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. [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.

  15. 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...

  16. 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...

  17. 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...

  18. 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.

  19. 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...

  20. 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...

  1. 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...

  2. 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.

  3. 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...

  4. 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...

  5. 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...

  6. 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...

  7. 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

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

    Science.gov (United States)

    Altaf, Muhammad U.; Jana, Raghavendra B.; Hoteit, Ibrahim; McCabe, Matthew F.

    2016-10-01

    Soil moisture is a key component of the hydrologic cycle, influencing processes leading to runoff generation, infiltration and groundwater recharge, evaporation and transpiration. Generally, the measurement scale for soil moisture is found to be different from the modeling scales for these processes. Reducing this mismatch between observation and model scales in necessary for improved hydrological modeling. An innovative approach to downscaling coarse resolution soil moisture data by combining continuous data assimilation and physically based modeling is presented. In this approach, we exploit the features of Continuous Data Assimilation (CDA) which was initially designed for general dissipative dynamical systems and later tested numerically on the incompressible Navier-Stokes equation, and the Benard equation. 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 (HYDRUS) are subjected to data assimilation conditioned upon 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. Results show that the approach is feasible to generate fine scale soil moisture fields across large extents, based on coarse scale observations. Application of this approach is likely in generating fine and intermediate resolution soil moisture fields conditioned on the radiometerbased, coarse resolution products from remote sensing satellites.

  9. Role of Soil Moisture vs. Recent Climate Change for the 2010 Heat Wave in Western Russia

    Science.gov (United States)

    Hauser, Mathias; Orth, René; Seneviratne, Sonia

    2016-04-01

    Extreme event attribution statements are often conditional on increased greenhouse gas concentrations or a particular ocean state, but not on other physical factors of the climate system. Here we extend the classical framework and assess the influence of soil moisture on a heat wave to obtain a physical attribution statement. In particular, we test the role of soil-moisture-temperature feedbacks which have been shown to be generally relevant for the build-up of exceptionally high temperatures. As a case study we investigate the severe 2010 heat wave in western Russia, which was previously found to be influenced by anthropogenic climate change. We quantify the relative role of climate change and that of soil moisture-temperature feedbacks with the event attribution framework and analyze ensemble simulations to distinguish the effect of climate change and the 2010 soil moisture conditions for annual maximum temperatures. We find that climate change from 1960 to 2000 alone has approximately tripled the risk of a severe heat wave in western Russia. The combined effect of climate change and the dry 2010 soil moisture yields a 13 times higher heat wave risk. We conclude that internal climate variability causing the dry 2010 soil moisture conditions formed the basis for this extreme heatwave.

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

    KAUST Repository

    Altaf, Muhammad

    2016-01-01

    Soil moisture is a key component of the hydrologic cycle, influencing processes leading to runoff generation, infiltration and groundwater recharge, evaporation and transpiration. Generally, the measurement scale for soil moisture is found to be different from the modeling scales for these processes. Reducing this mismatch between observation and model scales in necessary for improved hydrological modeling. An innovative approach to downscaling coarse resolution soil moisture data by combining continuous data assimilation and physically based modeling is presented. In this approach, we exploit the features of Continuous Data Assimilation (CDA) which was initially designed for general dissipative dynamical systems and later tested numerically on the incompressible Navier-Stokes equation, and the Benard equation. 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 (HYDRUS) are subjected to data assimilation conditioned upon 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. Results show that the approach is feasible to generate fine scale soil moisture fields across large extents, based on coarse scale observations. Application of this approach is likely in generating fine and intermediate resolution soil moisture fields conditioned on the radiometerbased, coarse resolution products from remote sensing satellites.

  11. 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

  12. 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.

  13. 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...

  14. 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

  15. Impact of soil moisture on extreme maximum temperatures in Europe

    Directory of Open Access Journals (Sweden)

    Kirien Whan

    2015-09-01

    Full Text Available Land-atmosphere interactions play an important role for hot temperature extremes in Europe. Dry soils may amplify such extremes through feedbacks with evapotranspiration. While previous observational studies generally focused on the relationship between precipitation deficits and the number of hot days, we investigate here the influence of soil moisture (SM on summer monthly maximum temperatures (TXx using water balance model-based SM estimates (driven with observations and temperature observations. Generalized extreme value distributions are fitted to TXx using SM as a covariate. We identify a negative relationship between SM and TXx, whereby a 100 mm decrease in model-based SM is associated with a 1.6 °C increase in TXx in Southern-Central and Southeastern Europe. Dry SM conditions result in a 2–4 °C increase in the 20-year return value of TXx compared to wet conditions in these two regions. In contrast with SM impacts on the number of hot days (NHD, where low and high surface-moisture conditions lead to different variability, we find a mostly linear dependency of the 20-year return value on surface-moisture conditions. We attribute this difference to the non-linear relationship between TXx and NHD that stems from the threshold-based calculation of NHD. Furthermore the employed SM data and the Standardized Precipitation Index (SPI are only weakly correlated in the investigated regions, highlighting the importance of evapotranspiration and runoff for resulting SM. Finally, in a case study for the hot 2003 summer we illustrate that if 2003 spring conditions in Southern-Central Europe had been as dry as in the more recent 2011 event, temperature extremes in summer would have been higher by about 1 °C, further enhancing the already extreme conditions which prevailed in that year.

  16. 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.

  17. 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.

  18. 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

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. Evaluation of a simple, point-scale hydrologic model in simulating soil moisture using the Delaware environmental observing system

    Science.gov (United States)

    Legates, David R.; Junghenn, Katherine T.

    2018-04-01

    Many local weather station networks that measure a number of meteorological variables (i.e. , mesonetworks) have recently been established, with soil moisture occasionally being part of the suite of measured variables. These mesonetworks provide data from which detailed estimates of various hydrological parameters, such as precipitation and reference evapotranspiration, can be made which, when coupled with simple surface characteristics available from soil surveys, can be used to obtain estimates of soil moisture. The question is Can meteorological data be used with a simple hydrologic model to estimate accurately daily soil moisture at a mesonetwork site? Using a state-of-the-art mesonetwork that also includes soil moisture measurements across the US State of Delaware, the efficacy of a simple, modified Thornthwaite/Mather-based daily water balance model based on these mesonetwork observations to estimate site-specific soil moisture is determined. Results suggest that the model works reasonably well for most well-drained sites and provides good qualitative estimates of measured soil moisture, often near the accuracy of the soil moisture instrumentation. The model exhibits particular trouble in that it cannot properly simulate the slow drainage that occurs in poorly drained soils after heavy rains and interception loss, resulting from grass not being short cropped as expected also adversely affects the simulation. However, the model could be tuned to accommodate some non-standard siting characteristics.

  4. 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.

  5. 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...

  6. Rainfall estimation from soil moisture data: crash test for SM2RAIN algorithm

    Science.gov (United States)

    Brocca, Luca; Albergel, Clement; Massari, Christian; Ciabatta, Luca; Moramarco, Tommaso; de Rosnay, Patricia

    2015-04-01

    Soil moisture governs the partitioning of mass and energy fluxes between the land surface and the atmosphere and, hence, it represents a key variable for many applications in hydrology and earth science. In recent years, it was demonstrated that soil moisture observations from ground and satellite sensors contain important information useful for improving rainfall estimation. Indeed, soil moisture data have been used for correcting rainfall estimates from state-of-the-art satellite sensors (e.g. Crow et al., 2011), and also for improving flood prediction through a dual data assimilation approach (e.g. Massari et al., 2014; Chen et al., 2014). Brocca et al. (2013; 2014) developed a simple algorithm, called SM2RAIN, which allows estimating rainfall directly from soil moisture data. SM2RAIN has been applied successfully to in situ and satellite observations. Specifically, by using three satellite soil moisture products from ASCAT (Advanced SCATterometer), AMSR-E (Advanced Microwave Scanning Radiometer for Earth Observation) and SMOS (Soil Moisture and Ocean Salinity); it was found that the SM2RAIN-derived rainfall products are as accurate as state-of-the-art products, e.g., the real-time version of the TRMM (Tropical Rainfall Measuring Mission) product. Notwithstanding these promising results, a detailed study investigating the physical basis of the SM2RAIN algorithm, its range of applicability and its limitations on a global scale has still to be carried out. In this study, we carried out a crash test for SM2RAIN algorithm on a global scale by performing a synthetic experiment. Specifically, modelled soil moisture data are obtained from HTESSEL model (Hydrology Tiled ECMWF Scheme for Surface Exchanges over Land) forced by ERA-Interim near-surface meteorology. Afterwards, the modelled soil moisture data are used as input into SM2RAIN algorithm for testing weather or not the resulting rainfall estimates are able to reproduce ERA-Interim rainfall data. Correlation, root

  7. 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.

  8. Data Assimilation using observed streamflow and remotely-sensed soil moisture for improving sub-seasonal-to-seasonal forecasting

    Science.gov (United States)

    Arumugam, S.; Mazrooei, A.; Lakshmi, V.; Wood, A.

    2017-12-01

    Subseasonal-to-seasonal (S2S) forecasts of soil moisture and streamflow provides critical information for water and agricultural systems to support short-term planning and mangement. This study evaluates the role of observed streamflow and remotely-sensed soil moisture from SMAP (Soil Moisture Active Passive) mission in improving S2S streamflow and soil moisture forecasting using data assimilation (DA). We first show the ability to forecast soil moisture at monthly-to-seaasonal time scale by forcing climate forecasts with NASA's Land Information System and then compares the developed soil moisture forecast with the SMAP data over the Southeast US. Our analyses show significant skill in forecasting real-time soil moisture over 1-3 months using climate information. We also show that the developed soil moisture forecasts capture the observed severe drought conditions (2007-2008) over the Southeast US. Following that, we consider both SMAP data and observed streamflow for improving S2S streamflow and soil moisture forecasts for a pilot study area, Tar River basin, in NC. Towards this, we consider variational assimilation (VAR) of gauge-measured daily streamflow data in improving initial hydrologic conditions of Variable Infiltration Capacity (VIC) model. The utility of data assimilation is then assessed in improving S2S forecasts of streamflow and soil moisture through a retrospective analyses. Furthermore, the optimal frequency of data assimilation and optimal analysis window (number of past observations to use) are also assessed in order to achieve the maximum improvement in S2S forecasts of streamflow and soil moisture. Potential utility of updating initial conditions using DA and providing skillful forcings are also discussed.

  9. 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...

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

    Science.gov (United States)

    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.

  11. 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.

  12. 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

  13. 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 ...

  14. 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

  15. 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

  16. 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).

  17. The significance of soil moisture in forecasting characteristics of flood events. A statistical analysis in two nested catchments

    Directory of Open Access Journals (Sweden)

    Chifflard Peter

    2018-03-01

    Full Text Available We examine the feasibility and added value of upscaling point data of soil moisture from a small- to a mesoscale catchment for the purpose of single-event flood prediction. We test the hypothesis that in a given catchment, the present soil moisture status is a key factor governing peak discharge, flow volume and flood duration. Multiple regression analyses of rainfall, pre-event discharge, single point soil moisture profiles from representative locations and peak discharge, discharge duration, discharge volume are discussed. The soil moisture profiles are selected along a convergent slope connected to the groundwater in flood plain within the small-scale catchment Husten (2.6 km², which is a headwater catchment of the larger Hüppcherhammer catchment (47.2 km², Germany. Results show that the number of explanatory variables in the regression models is higher in summer (up to 8 variables than in winter (up to 3 variables and higher in the meso-scale catchment than in the small-scale catchment (up to 2 variables. Soil moisture data from selected key locations in the small catchment improves the quality of regression models established for the meso-scale catchment. For the different target variables peak discharge, discharge duration and discharge volume the adding of the soil moisture from the flood plain and the lower slope as explanatory variable improves the quality of the regression model by 15%, 20% and 10%, respectively, especially during the summer season. In the winter season the improvement is smaller (up to 6% and the regression models mainly include rainfall characteristics as explanatory variables. The appearance of the soil moisture variables in the stepwise regression indicates their varying importance, depending on which characteristics of the discharge are focused on. Thus, we conclude that point data for soil moisture in functional landscape elements describe the catchments’ initial conditions very well and may yield valuable

  18. 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.

  19. 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

  20. Development of a Drought Severity Assessment Framework using Remotely Sensed Soil Moisture Products under Climate Change Scenario

    Science.gov (United States)

    Mohanty, B. P.; Shin, Y.

    2012-12-01

    Evaluating drought severity based on future climate scenarios plays an important role for water resources management. In this study we assessed drought severity based on soil moisture for individual soil-crop combinations. Based on the historical data, pixel-scale hydraulic parameters at finer-scales were estimated from remotely sensed (RS) soil moisture using a newly developed algorithm EMOGA (Ensemble Multiple Operators Genetic Algorithm) coupled with Soil-Water-Atmosphere-Plant (SWAP) hydrological model. These estimated hydraulic parameters along with meteorological variables obtained from general circulation models (GCMs) were used to predict soil moisture using the SWAP model. Further, drought severity was calculated using a soil moisture deficit index (SMDI) based on the projected soil moisture obtained from the SWAP model. The proposed model was evaluated based on synthetic and field data under different hydro-climates (Lubbock, Texas; Little Washita watershed, Oklahoma; Walnut Creek watershed, Iowa). Finer-scale root zone soil moisture predictions were considerably influenced by various combinations of environmental factors (soils, crops, groundwater table, etc.) along with GCM scenarios. However, these local environmental factors had relatively limited impacts (compared to precipitation dynamics) on reducing drought severity in the study region. The absolute SMDI values do indicate the occurrence of agricultural drought during 2010-2020. Thus, our proposed approach can be used to assess drought severity at finer-scales using a RS soil moisture product for efficient agricultural/water resources management.

  1. 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

  2. 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

  3. 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.

  4. 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...

  5. 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...

  6. 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.

  7. 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.

  8. Spatial Variability of Soil Morphorlogical and Physico- Chemical ...

    African Journals Online (AJOL)

    user

    The available moisture of soil was very low thus water holding capacity (WHC) and wilting point (WP) of ... cover crops, planting legumes, mulching ..... can thrive well if the field capacity can supply the required plant available water to the planted crops. 142. Variability of Soil Morphorlogical and Physico-Chemical Properties ...

  9. Evaluation of Soil Moisture Retrieval from the ERS and Metop Scatterometers in the Lower Mekong Basin

    Directory of Open Access Journals (Sweden)

    Heiko Apel

    2013-03-01

    Full Text Available The natural environment and livelihoods in the Lower Mekong Basin (LMB are significantly affected by the annual hydrological cycle. Monitoring of soil moisture as a key variable in the hydrological cycle is of great interest in a number of Hydrological and agricultural applications. In this study we evaluated the quality and spatiotemporal variability of the soil moisture product retrieved from C-band scatterometers data across the LMB sub-catchments. The soil moisture retrieval algorithm showed reasonable performance in most areas of the LMB with the exception of a few sub-catchments in the eastern parts of Laos, where the land cover is characterized by dense vegetation. The best performance of the retrieval algorithm was obtained in agricultural regions. Comparison of the available in situ evaporation data in the LMB and the Basin Water Index (BWI, an indicator of the basin soil moisture condition, showed significant negative correlations up to R = −0.85. The inter-annual variation of the calculated BWI was also found corresponding to the reported extreme hydro-meteorological events in the Mekong region. The retrieved soil moisture data show high correlation (up to R = 0.92 with monthly anomalies of precipitation in non-irrigated regions. In general, the seasonal variability of soil moisture in the LMB was well captured by the retrieval method. The results of analysis also showed significant correlation between El Niño events and the monthly BWI anomaly measurements particularly for the month May with the maximum correlation of R = 0.88.

  10. 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

  11. 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

  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. Influence of soil properties and soil moisture on the efficacy of indaziflam and flumioxazin on Kochia scoparia L.

    Science.gov (United States)

    Sebastian, Derek J; Nissen, Scott J; Westra, Phil; Shaner, Dale L; Butters, Greg

    2017-02-01

    Kochia (Kochia scoparia L.) is a highly competitive, non-native weed found throughout the western United States. Flumioxazin and indaziflam are two broad-spectrum pre-emergence herbicides that can control kochia in a variety of crop and non-crop situations; however, under dry conditions, these herbicides sometimes fail to control this important weed. There is very little information describing the effect of soil properties and soil moisture on the efficacy of these herbicides. Soil organic matter (SOM) explained the highest proportion of variability in predicting the herbicide dose required for 80% kochia growth reduction (GR 80 ) for flumioxazin and indaziflam (R 2 = 0.72 and 0.79 respectively). SOM had a greater impact on flumioxazin phytotoxicity compared to indaziflam. Flumioxazin and indaziflam kochia phytotoxicity was greatly reduced at soil water potentials below -200 kPa. Kochia can germinate at soil moisture potentials below the moisture required for flumioxazin and indaziflam activation, which means that kochia control is greatly influenced by the complex interaction between soil physical properties and soil moisture. This research can be used to gain a better understanding of how and why some weeds, like kochia, are so difficult to manage even with herbicides that normally provide excellent control. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

  14. A time series based method for estimating relative soil moisture with ERS wind scatterometer data

    NARCIS (Netherlands)

    Wen, J.; Su, Z.

    2003-01-01

    The radar backscattering coefficient is mainly determined by surface soil moisture, vegetation and land surface roughness under a given configuration of the satellite sensor. It is observed that the temporal variations of the three variables are different, the variation of vegetation and roughness

  15. Updated global soil map for the Weather Research and Forecasting model and soil moisture initialization for the Noah land surface model

    Science.gov (United States)

    DY, C. Y.; Fung, J. C. H.

    2016-08-01

    A meteorological model requires accurate initial conditions and boundary conditions to obtain realistic numerical weather predictions. The land surface controls the surface heat and moisture exchanges, which can be determined by the physical properties of the soil and soil state variables, subsequently exerting an effect on the boundary layer meteorology. The initial and boundary conditions of soil moisture are currently obtained via National Centers for Environmental Prediction FNL (Final) Operational Global Analysis data, which are collected operationally in 1° by 1° resolutions every 6 h. Another input to the model is the soil map generated by the Food and Agriculture Organization of the United Nations - United Nations Educational, Scientific and Cultural Organization (FAO-UNESCO) soil database, which combines several soil surveys from around the world. Both soil moisture from the FNL analysis data and the default soil map lack accuracy and feature coarse resolutions, particularly for certain areas of China. In this study, we update the global soil map with data from Beijing Normal University in 1 km by 1 km grids and propose an alternative method of soil moisture initialization. Simulations of the Weather Research and Forecasting model show that spinning-up the soil moisture improves near-surface temperature and relative humidity prediction using different types of soil moisture initialization. Explanations of that improvement and improvement of the planetary boundary layer height in performing process analysis are provided.

  16. 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

  17. 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.

  18. Assimilation of SMOS Retrieved Soil Moisture into the Land Information System

    Science.gov (United States)

    Blankenship, Clay B.; Case, Jonathan L.; Zavodsky, Bradley T.

    2014-01-01

    Soil moisture is a crucial variable for weather prediction because of its influence on evaporation and surface heat fluxes. It is also of critical importance for drought and flood monitoring and prediction and for public health applications such as monitoring vector-borne diseases. Land surface modeling benefits greatly from regular updates with soil moisture observations via data assimilation. Satellite remote sensing is the only practical observation type for this purpose in most areas due to its worldwide coverage. The newest operational satellite sensor for soil moisture is the Microwave Imaging Radiometer using Aperture Synthesis (MIRAS) instrument aboard the Soil Moisture and Ocean Salinity (SMOS) satellite. The NASA Short-term Prediction Research and Transition Center (SPoRT) has implemented the assimilation of SMOS soil moisture observations into the NASA Land Information System (LIS), an integrated modeling and data assimilation software platform. We present results from assimilating SMOS observations into the Noah 3.2 land surface model within LIS. The SMOS MIRAS is an L-band radiometer launched by the European Space Agency in 2009, from which we assimilate Level 2 retrievals [1] into LIS-Noah. The measurements are sensitive to soil moisture concentration in roughly the top 2.5 cm of soil. The retrievals have a target volumetric accuracy of 4% at a resolution of 35-50 km. Sensitivity is reduced where precipitation, snowcover, frozen soil, or dense vegetation is present. Due to the satellite's polar orbit, the instrument achieves global coverage twice daily at most mid- and low-latitude locations, with only small gaps between swaths.

  19. 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.

  20. Modeling the hysteretic moisture and temperature responses of soil carbon decomposition resulting from organo-mineral interactions

    Science.gov (United States)

    Tang, J.; Riley, W. J.

    2017-12-01

    Most existing soil carbon cycle models have modeled the moisture and temperature dependence of soil respiration using deterministic response functions. However, empirical data suggest abundant variability in both of these dependencies. We here use the recently developed SUPECA (Synthesizing Unit and Equilibrium Chemistry Approximation) theory and a published dynamic energy budget based microbial model to investigate how soil carbon decomposition responds to changes in soil moisture and temperature under the influence of organo-mineral interactions. We found that both the temperature and moisture responses are hysteretic and cannot be represented by deterministic functions. We then evaluate how the multi-scale variability in temperature and moisture forcing affect soil carbon decomposition. Our results indicate that when the model is run in scenarios mimicking laboratory incubation experiments, the often-observed temperature and moisture response functions can be well reproduced. However, when such response functions are used for model extrapolation involving more transient variability in temperature and moisture forcing (as found in real ecosystems), the dynamic model that explicitly accounts for hysteresis in temperature and moisture dependency produces significantly different estimations of soil carbon decomposition, suggesting there are large biases in models that do not resolve such hysteresis. We call for more studies on organo-mineral interactions to improve modeling of such hysteresis.

  1. 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.

  2. 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

  3. 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.

  4. 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

  5. Soil moisture dynamics and their effect on bioretention performance in Northeast Ohio

    Science.gov (United States)

    Bush, S. A.; Jefferson, A.; Jarden, K.; Kinsman-Costello, L. E.; Grieser, J.

    2014-12-01

    Urban impervious surfaces lead to increases in stormwater runoff. Green infrastructure, like bioretention cells, is being used to mitigate negative impacts of runoff by disconnecting impervious surfaces from storm water systems and redirecting flow to decentralized treatment areas. While bioretention soil characteristics are carefully designed, little research is available on soil moisture dynamics within the cells and how these might relate to inter-storm variability in performance. Bioretentions have been installed along a residential street in Parma, Ohio to determine the impact of green infrastructure on the West Creek watershed, a 36 km2 subwatershed of the Cuyahoga River. Bioretentions were installed in two phases (Phase I in 2013 and Phase II in 2014); design and vegetation density vary slightly between the two phases. Our research focuses on characterizing soil moisture dynamics of multiple bioretentions and assessing their impact on stormwater runoff at the street scale. Soil moisture measurements were collected in transects for eight bioretentions over the course of one summer. Vegetation indices of canopy height, percent vegetative cover, species richness and NDVI were also measured. A flow meter in the storm drain at the end of the street measured storm sewer discharge. Precipitation was recorded from a meteorological station 2 km from the research site. Soil moisture increased in response to precipitation and decreased to relatively stable conditions within 3 days following a rain event. Phase II bioretentions exhibited greater soil moisture and less vegetation than Phase I bioretentions, though the relationship between soil moisture and vegetative cover is inconclusive for bioretentions constructed in the same phase. Data from five storms suggest that pre-event soil moisture does not control the runoff-to-rainfall ratio, which we use as a measure of bioretention performance. However, discharge data indicate that hydrograph characteristics, such as lag

  6. 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

  7. 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).

  8. 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...

  9. 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

  10. 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.

  11. A universal calibration function for determination of soil moisture with cosmic-ray neutrons

    Directory of Open Access Journals (Sweden)

    T. E. Franz

    2013-02-01

    Full Text Available A cosmic-ray soil moisture probe is usually calibrated locally using soil samples collected within its support volume. But such calibration may be difficult or impractical, for example when soil contains stones, in presence of bedrock outcrops, in urban environments, or when the probe is used as a rover. Here we use the neutron transport code MCNPx with observed soil chemistries and pore water distribution to derive a universal calibration function that can be used in such environments. Reasonable estimates of pore water content can be made from neutron intensity measurements and by using measurements of the other hydrogen pools (water vapor, soil lattice water, soil organic carbon, and biomass. Comparisons with independent soil moisture measurements at one cosmic-ray probe site and, separately, at 35 sites, show that the universal calibration function explains more than 79% of the total variability within each dataset, permitting accurate isolation of the soil moisture signal from the measured neutron intensity signal. In addition the framework allows for any of the other hydrogen pools to be separated from the neutron intensity measurements, which may be useful for estimating changes in biomass, biomass water, or exchangeable water in complex environments.

  12. 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.

  13. Detection of soil moisture impact in convective initiation in the central region of Mexico

    Science.gov (United States)

    Dolores, Edgar; Caetano, Ernesto

    2017-04-01

    Soil moisture is important for understanding hydrological cycle variability in many regions. Local surface heat and moisture fluxes represent a major source of convective rainfall in Mexico during the summer, driven by positive evaporation-precipitation feedback. The effects of soil moisture are directly reflected in the limitation of evapotranspiration, affecting the development of the planetary boundary layer and, therefore, the initiation and intensity of convective precipitation. This study presents preliminary analysis of the role of soil moisture in convective initiations in central Mexico, for which a methodology for the detection of convective initiations similar to Taylor (2015) has been considered. The results show that the moisture fluxes from the surface influence the development of convection favored by mesoscale circulations at low levels. Initiations are more frequent in regions less humid than their surroundings with the very strong signal during the month of September. The knowledge of the soil predisposition to allow the development of deep convection suggests an alternative tool for the prediction of convective rains in Mexico.

  14. 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).

  15. 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.

  16. 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.

  17. 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

  18. 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.

  19. 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.

  20. 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 ...

  1. 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.

  2. 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 ...

  3. 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.

  4. 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

  5. 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

  6. 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

  7. 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...

  8. [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.

  9. Soil animal responses to moisture availability are largely scale, not ecosystem dependent: insight from a cross-site study.

    Science.gov (United States)

    Sylvain, Zachary A; Wall, Diana H; Cherwin, Karie L; Peters, Debra P C; Reichmann, Lara G; Sala, Osvaldo E

    2014-08-01

    Climate change will result in reduced soil water availability in much of the world either due to changes in precipitation or increased temperature and evapotranspiration. How communities of mites and nematodes may respond to changes in moisture availability is not well known, yet these organisms play important roles in decomposition and nutrient cycling processes. We determined how communities of these organisms respond to changes in moisture availability and whether common patterns occur along fine-scale gradients of soil moisture within four individual ecosystem types (mesic, xeric and arid grasslands and a polar desert) located in the western United States and Antarctica, as well as across a cross-ecosystem moisture gradient (CEMG) of all four ecosystems considered together. An elevation transect of three sampling plots was monitored within each ecosystem and soil samples were collected from these plots and from existing experimental precipitation manipulations within each ecosystem once in fall of 2009 and three times each in 2010 and 2011. Mites and nematodes were sorted to trophic groups and analyzed to determine community responses to changes in soil moisture availability. We found that while both mites and nematodes increased with available soil moisture across the CEMG, within individual ecosystems, increases in soil moisture resulted in decreases to nematode communities at all but the arid grassland ecosystem; mites showed no responses at any ecosystem. In addition, we found changes in proportional abundances of mite and nematode trophic groups as soil moisture increased within individual ecosystems, which may result in shifts within soil food webs with important consequences for ecosystem functioning. We suggest that communities of soil animals at local scales may respond predictably to changes in moisture availability regardless of ecosystem type but that additional factors, such as climate variability, vegetation composition, and soil properties may

  10. 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

  11. Accuracy and Stability Requirements of ERS and MetOp Scatterometer Soil Moisture for Climate Change Assessment

    Science.gov (United States)

    Bartalis, Zoltan; Wagner, Wolfgang; Dorigo, Wouter; Naeimi, Vahid

    2010-12-01

    Soil moisture is one of the Essential Climate Variables (ECVs) urgently required for assessing impacts and feedbacks of global warming on the land surface. Recent advances in algorithm development have made it possible to retrieve soil moisture from operational microwave radiometers (SMMR, SSM/I, AMSR-E, Wind-sat, etc.) and scatterometers (ERS Scatterometer, Metop ASCAT). Thus it is now for the first time possible to construct multi-decadal soil moisture time series, whereas the accuracy and the spatio-temporal resolution of the retrieved soil moisture data improve in general over time. In this article we will discuss the long-term stability of soil moisture data derived using the C-band scatterometer on board the two ERS satellites (1991-present) and the Advanced Scatterometer (AS- CAT) on board the three Metop platforms (2006-2020). The usefulness of scatterometer soil moisture time series for registering geophysically meaningful long-term trends is highly dependent on the calibration stability of the backscattering coefficient measurements from which they originate. We also revisit the presumably perfect volume scattering properties of tropical forests and thus their suitability for radar sensor vicarious calibration. We discuss the effects of the calibration differences between the two scatterometer generations and make some recommendations to improve the long-term consistency of the combined soil moisture data set.

  12. The COsmic-ray Soil Moisture Interaction Code (COSMIC for use in data assimilation

    Directory of Open Access Journals (Sweden)

    J. Shuttleworth

    2013-08-01

    Full Text Available Soil moisture status in land surface models (LSMs can be updated by assimilating cosmic-ray neutron intensity measured in air above the surface. This requires a fast and accurate model to calculate the neutron intensity from the profiles of soil moisture modeled by the LSM. The existing Monte Carlo N-Particle eXtended (MCNPX model is sufficiently accurate but too slow to be practical in the context of data assimilation. Consequently an alternative and efficient model is needed which can be calibrated accurately to reproduce the calculations made by MCNPX and used to substitute for MCNPX during data assimilation. This paper describes the construction and calibration of such a model, COsmic-ray Soil Moisture Interaction Code (COSMIC, which is simple, physically based and analytic, and which, because it runs at least 50 000 times faster than MCNPX, is appropriate in data assimilation applications. The model includes simple descriptions of (a degradation of the incoming high-energy neutron flux with soil depth, (b creation of fast neutrons at each depth in the soil, and (c scattering of the resulting fast neutrons before they reach the soil surface, all of which processes may have parameterized dependency on the chemistry and moisture content of the soil. The site-to-site variability in the parameters used in COSMIC is explored for 42 sample sites in the COsmic-ray Soil Moisture Observing System (COSMOS, and the comparative performance of COSMIC relative to MCNPX when applied to represent interactions between cosmic-ray neutrons and moist soil is explored. At an example site in Arizona, fast-neutron counts calculated by COSMIC from the average soil moisture profile given by an independent network of point measurements in the COSMOS probe footprint are similar to the fast-neutron intensity measured by the COSMOS probe. It was demonstrated that, when used within a data assimilation framework to assimilate COSMOS probe counts into the Noah land surface

  13. 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.

  14. 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

  15. 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...

  16. 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...

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

    Science.gov (United States)

    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.

  18. 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.

  19. 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

  20. 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

  1. 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

  2. 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

  3. 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.

  4. 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.

  5. 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.

  6. 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).

  7. Soil moisture storage estimation based on steady vertical fluxes under equilibrium

    Science.gov (United States)

    Amvrosiadi, Nino; Bishop, Kevin; Seibert, Jan

    2017-10-01

    Soil moisture is an important variable for hillslope and catchment hydrology. There are various computational methods to estimate soil moisture and their complexity varies greatly: from one box with vertically constant volumetric soil water content to fully saturated-unsaturated coupled physically-based models. Different complexity levels are applicable depending on the simulation scale, computational time limitations, input data and knowledge about the parameters. The Vertical Equilibrium Model (VEM) is a simple approach to estimate the catchment-wide soil water storage at a daily time-scale on the basis of water table level observations, soil properties and an assumption of hydrological equilibrium without vertical fluxes above the water table. In this study VEM was extended by considering vertical fluxes, which allows conditions with evaporation and infiltration to be represented. The aim was to test the hypothesis that the simulated volumetric soil water content significantly depends on vertical fluxes. The water content difference between the no-flux, equilibrium approach and the new constant-flux approach greatly depended on the soil textural class, ranging between ∼1% for silty clay and ∼44% for sand at an evapotranspiration rate of 5 mm·d-1. The two approaches gave a mean volumetric soil water content difference of ∼1 mm for two case studies (sandy loam and organic rich soils). The results showed that for many soil types the differences in estimated storage between the no-flux and the constant flux approaches were relatively small.

  8. Evaluation of remotely sensed and modelled soil moisture products using global ground-based in situ observations

    Science.gov (United States)

    Albergel, C.; de Rosnay, P.; Gruhier, C.; Munoz-Sabater, J.; Hasenauer, S.; Isaksen, L.; Kerr, Y.; Wagner, W.

    2012-04-01

    In situ soil moisture data collected from more than 200 stations located in various biomes and climate (Africa, Australia, Europe and the United States) are used to determine the reliability of three soil moisture products, (i) one analysis from the ECMWF (European Centre for Medium-Range Weather Forecasts) numerical weather prediction system (SM-DAS-2) and two remotely sensed soil moisture products, namely (ii) ASCAT (Advanced Scatterometer) and (iii) SMOS (Soil Moisture Ocean Salinity). SM-DAS-2 is produced offline at ECMWF and relies on an advanced surface data assimilation system Extended Kalman Filter) used to optimally combine conventional observations with satellite measurements. ASCAT remotely sensed surface soil moisture is provided in near real time by EUMETSAT. At ECMWF, ASCAT is used for soil moisture analyses in SM-DAS-2, also. Finally the SMOS remotely sensed soil moisture data level two product developed at CESBIO is used. Evaluation of the times series as well as of the anomaly values, shows good performances of the three products to capture surface soil moisture annual cycle as well as its short term variability. Correlation values with in situ data are very satisfactory over most of the investigated sites located in contrasted biomes and climate conditions with averaged values of 0.70 for SM-DAS-2, 0.53 for ASCAT and 0.54 for SMOS. Although radio frequency interference disturbs the natural microwave emission of the Earth observed by SMOS in several parts of the world, hence the soil moisture retrieval, performances of SMOS over Australia are very encouraging.

  9. 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...

  10. 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

  11. 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.

  12. 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...

  13. 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...

  14. 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...

  15. 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...

  16. 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...

  17. 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.

  18. Complex terrain alters temperature and moisture limitations of forest soil respiration across a semiarid to subalpine gradient

    Science.gov (United States)

    Berryman, Erin Michele; Barnard, H.R.; Adams, H.R.; Burns, M.A.; Gallo, E.; Brooks, P.D.

    2015-01-01

    Forest soil respiration is a major carbon (C) flux that is characterized by significant variability in space and time. We quantified growing season soil respiration during both a drought year and a nondrought year across a complex landscape to identify how landscape and climate interact to control soil respiration. We asked the following questions: (1) How does soil respiration vary across the catchments due to terrain-induced variability in moisture availability and temperature? (2) Does the relative importance of moisture versus temperature limitation of respiration vary across space and time? And (3) what terrain elements are important for dictating the pattern of soil respiration and its controls? Moisture superseded temperature in explaining watershed respiration patterns, with wetter yet cooler areas higher up and on north facing slopes yielding greater soil respiration than lower and south facing areas. Wetter subalpine forests had reduced moisture limitation in favor of greater seasonal temperature limitation, and the reverse was true for low-elevation semiarid forests. Coincident climate poorly predicted soil respiration in the montane transition zone; however, antecedent precipitation from the prior 10 days provided additional explanatory power. A seasonal trend in respiration remained after accounting for microclimate effects, suggesting that local climate alone may not adequately predict seasonal variability in soil respiration in montane forests. Soil respiration climate controls were more strongly related to topography during the drought year highlighting the importance of landscape complexity in ecosystem response to drought.

  19. 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

  20. 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.

  1. Assessing Seasonal Backscatter Variations with Respect to Uncertainties in Soil Moisture Retrieval in Siberian Tundra Regions

    Directory of Open Access Journals (Sweden)

    Elin Högström

    2014-09-01

    Full Text Available Knowledge of surface hydrology is essential for many applications, including studies that aim to understand permafrost response to changing climate and the associated feedback mechanisms. Advanced remote sensing techniques make it possible to retrieve a range of land-surface variables, including radar retrieved soil moisture (SSM. It has been pointed out before that soil moisture retrieval from satellite data can be challenging at high latitudes, which correspond to remote areas where ground data are scarce and the applicability of satellite data of this type is essential. This study investigates backscatter variability other than associated with changing soil moisture in order to examine the possible impact on soil moisture retrieval. It focuses on issues specific to SSM retrieval in the Arctic, notably variations related to tundra lakes. ENVISAT Advanced Synthetic Aperture Radar (ASAR Wide Swath (WS, 120 m data are used to understand and quantify impacts on Metop (AAdvanced Scatterometer (ASCAT, 25 km soil moisture retrieval during the snow free period. Sites of interest are chosen according to ASAR WS availability, high or low agreement between output from the land surface model ORCHIDEE and ASCAT derived SSM. Backscatter variations are analyzed with respect to the ASCAT footprint area. It can be shown that the low model agreement is related to water fraction in most cases. No difference could be detected between periods with floating ice (in snow off situation and ice free periods at the chosen sites. The mean footprint backscatter is however impacted by partial short term surface roughness change. The water fraction correlates with backscatter deviations (relative to a smooth water surface reference image within the ASCAT footprint areas (R = 0.91

  2. Reducing the Influence of Soil Moisture on the Estimation of Clay from Hyperspectral Data: A Case Study Using Simulated PRISMA Data

    Directory of Open Access Journals (Sweden)

    Fabio Castaldi

    2015-11-01

    Full Text Available Soil moisture hampers the estimation of soil variables such as clay content from remote and proximal sensing data, reducing the strength of the relevant spectral absorption features. In the present study, two different strategies have been evaluated for their ability to minimize the influence of soil moisture on clay estimation by using soil spectra acquired in a laboratory and by simulating satellite hyperspectral data. Simulated satellite data were obtained according to the spectral characteristics of the forthcoming hyperspectral imager on board of the Italian PRISMA satellite mission. The soil datasets were split into four groups according to the water content. For each soil moisture level a prediction model was applied, using either spectral indices or partial least squares regression (PLSR. Prediction models were either specifically developed for the soil moisture level or calibrated using synthetically dry soil spectra, generated from wet soil data. Synthetically dry spectra were obtained using a new technique based on the effects caused by soil moisture on the optical spectrum from 400 to 2400 nm. The estimation of soil clay content, when using different prediction models according to soil moisture, was slightly more accurate as compared to the use of synthetically dry soil spectra, both employing clay indices and PLSR models. The results obtained in this study demonstrate that the a priori knowledge of the soil moisture class can reduce the error of clay estimation when using hyperspectral remote sensing data, such as those that will be provided by the PRISMA satellite mission in the near future.

  3. 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

  4. How do peat type, sand addition and soil moisture influence the soil organic matter mineralization in anthropogenically disturbed organic soils?

    Science.gov (United States)

    Säurich, Annelie; Tiemeyer, Bärbel; Don, Axel; Burkart, Stefan

    2017-04-01

    Drained peatlands are hotspots of carbon dioxide (CO2) emissions from agriculture. As a consequence of both drainage induced mineralization and anthropogenic sand mixing, large areas of former peatlands under agricultural use contain soil organic carbon (SOC) at the boundary between mineral and organic soils. Studies on SOC dynamics of such "low carbon organic soils" are rare as the focus of previous studies was mainly either on mineral soils or "true" peat soil. However, the variability of CO2 emissions increases with disturbance and therefore, we have yet to understand the reasons behind the relatively high CO2 emissions of these soils. Peat properties, soil organic matter (SOM) quality and water content are obviously influencing the rate of CO2 emissions, but a systematic evaluation of the hydrological and biogeochemical drivers for mineralization of disturbed peatlands is missing. With this incubation experiment, we aim at assessing the drivers of the high variability of CO2 emissions from strongly anthropogenically disturbed organic soil by systematically comparing strongly degraded peat with and without addition of sand under different moisture conditions and for different peat types. The selection of samples was based on results of a previous incubation study, using disturbed samples from the German Agricultural Soil Inventory. We sampled undisturbed soil columns from topsoil and subsoil (three replicates of each) of ten peatland sites all used as grassland. Peat types comprise six fens (sedge, Phragmites and wood peat) and four bogs (Sphagnum peat). All sites have an intact peat horizon that is permanently below groundwater level and a strongly disturbed topsoil horizon. Three of the fen and two of the bog sites have a topsoil horizon altered by sand-mixing. In addition the soil profile was mapped and samples for the determination of soil hydraulic properties were collected. All 64 soil columns (including four additional reference samples) will be installed

  5. 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.

  6. 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.

  7. Attribution of soil moisture dynamics - Initial conditions vs. atmospheric forcing and the role of climate change

    Science.gov (United States)

    Orth, Rene; Seneviratne, Sonia I.

    2014-05-01

    The world's climate has started to change more quickly in recent decades and a stronger and faster shift is expected in the future. Even if the public perception is mostly limited to a widespread warming, climate change is a complex phenomenon impacting numerous variables of the climate system in different ways, also depending on time and location. Furthermore, extreme events may change more drastically than the mean climate. There is growing evidence that climate change is mostly man-made. However, it is still a matter of debate to which extent changes of the mean climate but also of particular (extreme) events are due to human impact. These questions are addressed by the growing science of climate attribution. Pointing out the anthropogenic influence on extreme events such as the 2010 Russian heatwave or the 2002 floods in Central Europe may help to support adaptation to climate change. This study investigates soil moisture in Europe in the context of climate change, because of its role as a key variable of the land-climate system and its practical importance for instance to agriculture. To derive soil moisture dynamics from 1984-2007 we use E-OBS forcing data together with SRB radiation data and employ an observation-based approach where soil moisture is computed from a water balance equation in which runoff (normalized with precipitation) and ET (normalized with net radiation) are simple functions of soil moisture. The constant runoff function is prescribed for the whole continent, and the ET function is calibrated using temperature data. After performing a validation of the inferred soil moisture data we use it in order to analyze changes in the likelihood of droughts. Our results show increased drought risk especially in north-eastern Europe and the Mediterranean, whereby the probability of extreme droughts increases stronger as for mild dryness episodes. To assess the potential for drought forecasting we furthermore study the importance of the initial

  8. 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.

  9. 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

  10. 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

  11. 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

  12. GLEAM v3: satellite-based land evaporation and root-zone soil moisture

    Science.gov (United States)

    Martens, Brecht; Miralles, Diego G.; Lievens, Hans; van der Schalie, Robin; de Jeu, Richard A. M.; Fernández-Prieto, Diego; Beck, Hylke E.; Dorigo, Wouter A.; Verhoest, Niko E. C.

    2017-05-01

    The Global Land Evaporation Amsterdam Model (GLEAM) is a set of algorithms dedicated to the estimation of terrestrial evaporation and root-zone soil moisture from satellite data. Ever since its development in 2011, the model has been regularly revised, aiming at the optimal incorporation of new satellite-observed geophysical variables, and improving the representation of physical processes. In this study, the next version of this model (v3) is presented. Key changes relative to the previous version include (1) a revised formulation of the evaporative stress, (2) an optimized drainage algorithm, and (3) a new soil moisture data assimilation system. GLEAM v3 is used to produce three new data sets of terrestrial evaporation and root-zone soil moisture, including a 36-year data set spanning 1980-2015, referred to as v3a (based on satellite-observed soil moisture, vegetation optical depth and snow-water equivalent, reanalysis air temperature and radiation, and a multi-source precipitation product), and two satellite-based data sets. The latter share most of their forcing, except for the vegetation optical depth and soil moisture, which are based on observations from different passive and active C- and L-band microwave sensors (European Space Agency Climate Change Initiative, ESA CCI) for the v3b data set (spanning 2003-2015) and observations from the Soil Moisture and Ocean Salinity (SMOS) satellite in the v3c data set (spanning 2011-2015). Here, these three data sets are described in detail, compared against analogous data sets generated using the previous version of GLEAM (v2), and validated against measurements from 91 eddy-covariance towers and 2325 soil moisture sensors across a broad range of ecosystems. Results indicate that the quality of the v3 soil moisture is consistently better than the one from v2: average correlations against in situ surface soil moisture measurements increase from 0.61 to 0.64 in the case of the v3a data set and the representation of soil

  13. Variability of Phenology and Fluxes of Water and Carbon with Observed and Simulated Soil Moisture in the Ent Terrestrial Biosphere Model (Ent TBM Version 1.0.1.0.0)

    Science.gov (United States)

    Kim, Y.; Moorcroft, P. R.; Aleinov, Igor; Puma, M. J.; Kiang, N. Y.

    2015-01-01

    The Ent Terrestrial Biosphere Model (Ent TBM) is a mixed-canopy dynamic global vegetation model developed specifically for coupling with land surface hydrology and general circulation models (GCMs). This study describes the leaf phenology submodel implemented in the Ent TBM version 1.0.1.0.0 coupled to the carbon allocation scheme of the Ecosystem Demography (ED) model. The phenology submodel adopts a combination of responses to temperature (growing degree days and frost hardening), soil moisture (linearity of stress with relative saturation) and radiation (light length). Growth of leaves, sapwood, fine roots, stem wood and coarse roots is updated on a daily basis. We evaluate the performance in reproducing observed leaf seasonal growth as well as water and carbon fluxes for four plant functional types at five Fluxnet sites, with both observed and prognostic hydrology, and observed and prognostic seasonal leaf area index. The phenology submodel is able to capture the timing and magnitude of leaf-out and senescence for temperate broadleaf deciduous forest (Harvard Forest and Morgan- Monroe State Forest, US), C3 annual grassland (Vaira Ranch, US) and California oak savanna (Tonzi Ranch, US). For evergreen needleleaf forest (Hyytiäla, Finland), the phenology submodel captures the effect of frost hardening of photosynthetic capacity on seasonal fluxes and leaf area. We address the importance of customizing parameter sets of vegetation soil moisture stress response to the particular land surface hydrology scheme. We identify model deficiencies that reveal important dynamics and parameter needs.

  14. 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.

  15. 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

  16. 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

  17. Shallow soil moisture - ground thaw interactions and controls - Part 2: Influences of water and energy fluxes

    Science.gov (United States)

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

    2010-07-01

    The companion paper (Guan et al., 2010) demonstrated variable interactions and correlations between shallow soil moisture and ground thaw in soil filled areas along a wetness spectrum in a subarctic Canadian Precambrian Shield landscape. From wetter to drier, these included a wetland, peatland and soil filled valley. Herein, water and energy fluxes were examined for these same subarctic study sites to discern the key controlling processes on the found patterns. Results showed the presence of surface water was the key control in variable soil moisture and frost table interactions among sites. At the peatland and wetland sites, accumulated water in depressions and flow paths maintained soil moisture for a longer duration than at the hummock tops. These wet areas were often locations of deepest thaw depth due to the transfer of latent heat accompanying lateral surface runoff. Although the peatland and wetland sites had large inundation extent, modified Péclet numbers indicated the relative influence of external and internal hydrological and energy processes at each site were different. Continuous inflow from an upstream lake into the wetland site caused advective and conductive thermal energies to be of equal importance to ground thaw. The absence of continuous surface flow at the peatland and valley sites led to dominance of conductive thermal energy over advective energy for ground thaw. The results suggest that the modified Péclet number could be a very useful parameter to differentiate landscape components in modeling frost table heterogeneity. The calculated water and energy fluxes, and the modified Péclet number provide quantitative explanations for the shallow soil moisture-ground thaw patterns by linking them with hydrological processes and hillslope storage capacity.

  18. The aggregate description of semi-arid vegetation with precipitation-generated soil moisture heterogeneity

    Directory of Open Access Journals (Sweden)

    C. B. White

    1997-01-01

    Full Text Available Meteorological measurements in the Walnut Gulch catchment in Arizona were used to synthesize a distributed, hourly-average time series of data across a 26.9 by 12.5 km area with a grid resolution of 480 m for a continuous 18-month period which included two seasons of monsoonal rainfall. Coupled surface-atmosphere model runs established the acceptability (for modelling purposes of assuming uniformity in all meteorological variables other than rainfall. Rainfall was interpolated onto the grid from an array of 82 recording rain gauges. These meteorological data were used as forcing variables for an equivalent array of stand-alone Biosphere-Atmosphere Transfer Scheme (BATS models to describe the evolution of soil moisture and surface energy fluxes in response to the prevalent, heterogeneous pattern of convective precipitation. The calculated area-average behaviour was compared with that given by a single aggregate BATS simulation forced with area-average meteorological data. Heterogeneous rainfall gives rise to significant but partly compensating differences in the transpiration and the intercepted rainfall components of total evaporation during rain storms. However, the calculated area-average surface energy fluxes given by the two simulations in rain-free conditions with strong heterogeneity in soil moisture were always close to identical, a result which is independent of whether default or site-specific vegetation and soil parameters were used. Because the spatial variability in soil moisture throughout the catchment has the same order of magnitude as the amount of rain falling in a typical convective storm (commonly 10% of the vegetation's root zone saturation in a semi-arid environment, non-linearity in the relationship between transpiration and the soil moisture available to the vegetation has limited influence on area-average surface fluxes.

  19. Prediction of Soil Organic Matter by VIS–NIR Spectroscopy Using Normalized Soil Moisture Index as a Proxy of Soil Moisture

    Directory of Open Access Journals (Sweden)

    Yongsheng Hong

    2017-12-01

    Full Text Available Soil organic matter (SOM is an important parameter of soil fertility, and visible and near-infrared (VIS–NIR spectroscopy combined with multivariate modeling techniques have provided new possibilities to estimate SOM. However, the spectral signal is strongly influenced by soil moisture (SM in the field. Interest in using spectral classification to predict soils in the moist conditions to minimize the influence of SM is growing. The objective of this study was to investigate the transferability of two approaches, SM–based cluster method with known SM (classifying the VIS–NIR spectra into different SM clusters to develop models separately, the normalized soil moisture index (NSMI–based cluster method with unknown SM (utilizing NSMI to indicate the SM and establish models separately, to predict SOM directly in moist soil spectra. One hundred and twenty one soil samples were collected from Central China, and eight SM levels were obtained for each sample through rewetting experiments. Their reflectance spectra and SOM concentrations were measured in the laboratory. Partial least square-support vector machine (PLS-SVM was employed to construct SOM prediction models. Specifically, prediction models were developed for NSMI–based clusters with unknown SM data. The models were assessed through three statistics in the processes of calibration and validation: the coefficient of determination (R2, root mean square error (RMSE and the ratio of the performance to deviation (RPD. Results showed that the variable SM led to reduced VIS–NIR reflectance nonlinearly across the entire spectral range. NSMI was an effective spectral index to indicate the SM. Classifying the VIS–NIR spectra into different SM clusters in known SM states could improve the performance of PLS-SVM models to acceptable prediction accuracies (R2cv = 0.69–0.77, RPD = 1.79–2.08. The estimation of SOM, when using the NSMI–based cluster method with unknown SM (RPD = 1.95–2

  20. 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

  1. 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.

  2. 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.

  3. 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.

  4. 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

  5. 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

  6. 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.

  7. 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.

  8. Evaporational losses under different soil moisture regimes and atmospheric evaporativities using tritium

    International Nuclear Information System (INIS)

    Saxena, P.; Chaudhary, T.N.; Mookerji, P.

    1991-01-01

    Tritium as tracer was used in a laboratory study to estimate the contribution of moisture from different soil depths towards actual soil water evaporation. Results indicated that for comparable amounts of free water evaporation (5 cm), contribution of moisture from 70-80 cm soil layer towards total soil moisture loss through evaporation increased nearly 1.5 to 3 folds for soils with water table at 90 cm than without water table. Identical initial soil moistures were exposed to different atmospheric evaporativities. Similarly, for a given initial soil moisture status, upward movement of moisture from 70-80 cm soil layer under low evaporativity was nearly 8 to 12 times that of under high evaporativity at 5 cm free water evaporation value. (author). 6 refs., 4 tabs., 2 figs

  9. Soil Moisture Active Passive (SMAP) Mission Level 4 Surface and Root Zone Soil Moisture (L4_SM) Product Specification Document

    Science.gov (United States)

    Reichle, Rolf H.; Ardizzone, Joseph V.; Kim, Gi-Kong; Lucchesi, Robert A.; Smith, Edmond B.; Weiss, Barry H.

    2015-01-01

    This is the Product Specification Document (PSD) for Level 4 Surface and Root Zone Soil Moisture (L4_SM) data for the Science Data System (SDS) of the Soil Moisture Active Passive (SMAP) project. The L4_SM data product provides estimates of land surface conditions based on the assimilation of SMAP observations into a customized version of the NASA Goddard Earth Observing System, Version 5 (GEOS-5) land data assimilation system (LDAS). This document applies to any standard L4_SM data product generated by the SMAP Project. The Soil Moisture Active Passive (SMAP) mission will enhance the accuracy and the resolution of space-based measurements of terrestrial soil moisture and freeze-thaw state. SMAP data products will have a noteworthy impact on multiple relevant and current Earth Science endeavors. These include: Understanding of the processes that link the terrestrial water, the energy and the carbon cycles, Estimations of global water and energy fluxes over the land surfaces, Quantification of the net carbon flux in boreal landscapes Forecast skill of both weather and climate, Predictions and monitoring of natural disasters including floods, landslides and droughts, and Predictions of agricultural productivity. To provide these data, the SMAP mission will deploy a satellite observatory in a near polar, sun synchronous orbit. The observatory will house an L-band radiometer that operates at 1.40 GHz and an L-band radar that operates at 1.26 GHz. The instruments will share a rotating reflector antenna with a 6 meter aperture that scans over a 1000 km swath.

  10. 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...

  11. Soil moisture effects on the carbon isotope composition of soil respiration

    Science.gov (United States)

    Claire L. Phillips; Nick Nickerson; David Risk; Zachary E. Kayler; Chris Andersen; Alan Mix; Barbara J. Bond

    2010-01-01

    The carbon isotopic composition (δ13C) of recently assimilated plant carbon is known to depend on water-stress, caused either by low soil moisture or by low atmospheric humidity. Air humidity has also been shown to correlate with the δ13C of soil respiration, which suggests indirectly that recently fixed photosynthates...

  12. Effects of Soil Temperature and Moisture on Soil Respiration on the Tibetan Plateau.

    Science.gov (United States)

    Bao, Xiaoying; Zhu, Xiaoxue; Chang, Xiaofeng; Wang, Shiping; Xu, Burenbayin; Luo, Caiyun; Zhang, Zhenhua; Wang, Qi; Rui, Yichao; Cui, Xiaoying

    2016-01-01

    Understanding of effects of soil temperature and soil moisture on soil respiration (Rs) under future warming is critical to reduce uncertainty in predictions of feedbacks to atmospheric CO2 concentrations from grassland soil carbon. Intact cores with roots taken from a full factorial, 5-year alpine meadow warming and grazing experiment in the field were incubated at three different temperatures (i.e. 5, 15 and 25°C) with two soil moistures (i.e. 30 and 60% water holding capacity (WHC)) in our study. Another experiment of glucose-induced respiration (GIR) with 4 h of incubation was conducted to determine substrate limitation. Our results showed that high temperature increased Rs and low soil moisture limited the response of Rs to temperature only at high incubation temperature (i.e. 25°C). Temperature sensitivity (Q10) did not significantly decrease over the incubation period, suggesting that substrate depletion did not limit Rs. Meanwhile, the carbon availability index (CAI) was higher at 5°C compared with 15 and 25°C incubation, but GIR increased with increasing temperature. Therefore, our findings suggest that warming-induced decrease in Rs in the field over time may result from a decrease in soil moisture rather than from soil substrate depletion, because warming increased root biomass in the alpine meadow.

  13. Effects of Soil Temperature and Moisture on Soil Respiration on the Tibetan Plateau.

    Directory of Open Access Journals (Sweden)

    Xiaoying Bao

    Full Text Available Understanding of effects of soil temperature and soil moisture on soil respiration (Rs under future warming is critical to reduce uncertainty in predictions of feedbacks to atmospheric CO2 concentrations from grassland soil carbon. Intact cores with roots taken from a full factorial, 5-year alpine meadow warming and grazing experiment in the field were incubated at three different temperatures (i.e. 5, 15 and 25°C with two soil moistures (i.e. 30 and 60% water holding capacity (WHC in our study. Another experiment of glucose-induced respiration (GIR with 4 h of incubation was conducted to determine substrate limitation. Our results showed that high temperature increased Rs and low soil moisture limited the response of Rs to temperature only at high incubation temperature (i.e. 25°C. Temperature sensitivity (Q10 did not significantly decrease over the incubation period, suggesting that substrate depletion did not limit Rs. Meanwhile, the carbon availability index (CAI was higher at 5°C compared with 15 and 25°C incubation, but GIR increased with increasing temperature. Therefore, our findings suggest that warming-induced decrease in Rs in the field over time may result from a decrease in soil moisture rather than from soil substrate depletion, because warming increased root biomass in the alpine meadow.

  14. 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.

  15. Soil Moisture Anomaly as Predictor of Crop Yield Deviation in Germany

    Science.gov (United States)

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

    2016-04-01

    Natural hazards, such as 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 (COPA-COGECA 2003). Predicting crop yields allows to economize the mitigation of risks of weather extremes. Economic approaches for quantifying agricultural impacts of natural hazards mainly rely on temperature and related concepts. For instance extreme heat over the growing season is considered as best predictor of corn yield (Auffhammer and Schlenker 2014). However, those measures are only able to provide a proxy for the available water content in the root zone that ultimately determines plant growth and eventually crop yield. The aim of this paper is to analyse whether soil moisture has a causal effect on crop yield that can be exploited in improving adaptation measures. For this purpose, reduced form fixed effect panel models are developed with yield as dependent variable for both winter wheat and silo maize crops. The explanatory variables used are soil moisture anomalies, precipitation and temperature. The latter two are included to estimate the current state of the water balance. On the contrary, soil moisture provides an integrated signal over several months. It is also the primary source of water supply for plant growth. For each crop a single model is estimated for every month within the growing period to study the variation of the effects over time. Yield data is available for Germany as a whole on the level of administrative districts from 1990 to 2010. Station data by the German Weather Service are obtained for precipitation and temperature and are aggregated to the same spatial units. Simulated soil moisture computed by the mesoscale Hydrologic Model (mHM, www.ufz.de/mhm) is transformed into Soil Moisture Index (SMI), which represents the monthly soil water quantile and hence accounts directly for the water content available to plants. The results

  16. Desert grassland responses to climate and soil moisture suggest divergent vulnerabilities across the southwestern United States.

    Science.gov (United States)

    Gremer, Jennifer R; Bradford, John B; Munson, Seth M; Duniway, Michael C

    2015-11-01

    Climate change predictions include warming and drying trends, which are expected to be particularly pronounced in the southwestern United States. In this region, grassland dynamics are tightly linked to available moisture, yet it has proven difficult to resolve what aspects of climate drive vegetation change. In part, this is because it is unclear how heterogeneity in soils affects plant responses to climate. Here, we combine climate and soil properties with a mechanistic soil water model to explain temporal fluctuations in perennial grass cover, quantify where and the degree to which incorporating soil water dynamics enhances our ability to understand temporal patterns, and explore the potential consequences of climate change by assessing future trajectories of important climate and soil water variables. Our analyses focused on long-term (20-56 years) perennial grass dynamics across the Colorado Plateau, Sonoran, and Chihuahuan Desert regions. Our results suggest that climate variability has negative effects on grass cover, and that precipitation subsidies that extend growing seasons are beneficial. Soil water metrics, including the number of dry days and availability of water from deeper (>30 cm) soil layers, explained additional grass cover variability. While individual climate variables were ranked as more important in explaining grass cover, collectively soil water accounted for 40-60% of the total explained variance. Soil water conditions were more useful for understanding the responses of C3 than C4 grass species. Projections of water balance variables under climate change indicate that conditions that currently support perennial grasses will be less common in the future, and these altered conditions will be more pronounced in the Chihuahuan Desert and Colorado Plateau. We conclude that incorporating multiple aspects of climate and accounting for soil variability can improve our ability to understand patterns, identify areas of vulnerability, and predict

  17. 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.

  18. Collective impacts of soil moisture and orography on deep convective thunderstorms

    Science.gov (United States)

    Imamovic, Adel; Schlemmer, Linda; Schär, Christoph

    2017-04-01

    Thunderstorm activity in many land regions peaks in summer, when surface heat fluxes and the atmospheric moisture content reach an annual maximum. Studies using satellite and ground-based observations have shown that the timing and vigor of summer thunderstorms are influenced by the presence of triggering mechanisms such as soil-moisture heterogeneity or orography. In the current process-based study we aim to dissect the combined impact of soil-moisture and orography on moist convection by using convection-resolving climate simulations with idealized landsurface and orographic conditions. First we systematically investigate the sensitivity of moist convection in absence of orography to a mesoscale soil-moisture anomaly, i.e. a region with drier or moister soil. Consistent with previous studies, a high sensitivity of total rain to soil-moisture anomalies over flat terrain is found. The total rain in the presence of a dry soil-moisture anomaly increases linearly if the soil-moisture anomaly is dried: an anomaly that is 50 % dryer than the reference case with a homogeneous soil-moisture distribution produces up to 40 % more rain. The amplitude of this negative response to the dry soil-moisture anomaly cannot be reproduced by either drying or moistening the soil in the whole domain, even when using unrealistic soil-moisture values. A moist soil anomaly showed little impact on total rain. The triggering effects of the soil-moisture anomalies can be reproduced by an isolated mountain of 250 m height. In order to test to what extent the impact of the soil-moisture anomaly and the mountain are additive, the soil-moisture perturbation method is applied to soil-moisture over the isolated mountain. A 250 m high mountain with drier (moister) soil than its surrounding is found to enhance (suppress) rain amounts. However, the sensitivity of rain amount to the soil-moisture anomaly decreases with the mountain height: A 500 m high mountain is already sufficient to eliminate the

  19. Influence of physical and chemical properties of different soil types on optimal soil moisture for tillage

    Directory of Open Access Journals (Sweden)

    Vladimir Zebec

    2017-01-01

    Full Text Available Soil plasticity is the area of soil consistency, i.e. it represents a change in soil condition due to different soil moisture influenced by external forces activity. Consistency determines soil resistance in tillage, therefore, the aim of the research was to determine the optimum soil moisture condition for tillage and the influence of the chemical and physical properties of the arable land horizons on the soil plasticity on three different types of soil (fluvisol, luvisol and humic glaysol. Statistically significant differences were found between all examined soil types, such as the content of clay particles, the density of packaging and the actual and substitution acidity, the cation exchange capacity and the content of calcium. There were also statistically significant differences between the examined types of soil for the plasticity limit, liquid limit and the plasticity index. The average established value of plasticity limit as an important element for determining the optimal moment of soil tillage was 18.9% mass on fluvisol, 24.0% mass on luvisol and 28.6% mass on humic glaysol. Very significant positive direction correlation with plasticity limits was shown by organic matter, clay, fine silt, magnesium, sodium and calcium, while very significant negative direction correlation was shown by hydrolytic acidity, coarse sand, fine sand and coarse silt. Created regression models can estimate the optimal soil moisture condition for soil cultivation based on the basic soil properties. The model precision is significantly increased by introducing a greater number of agrochemical and agrophysical soil properties, and the additional precision of the model can be increased by soil type data.

  20. Monitoring soil moisture from middle to high elevation in Switzerland: set-up and first results from the SOMOMOUNT network

    Science.gov (United States)

    Pellet, Cécile; Hauck, Christian

    2017-06-01

    Besides its important role in the energy and water balance at the soil-atmosphere interface, soil moisture can be a particular important factor in mountain environments since it influences the amount of freezing and thawing in the subsurface and can affect the stability of slopes. In spite of its importance, the technical challenges and its strong spatial variability usually prevents soil moisture from being measured operationally at high and/or middle altitudes. This study describes the new Swiss soil moisture monitoring network SOMOMOUNT (soil moisture in mountainous terrain) launched in 2013. It consists of six entirely automated soil moisture stations distributed along an altitudinal gradient between the Jura Mountains and the Swiss Alps, ranging from 1205 to 3410 m a.s.l. in elevation. In addition to the standard instrumentation comprising frequency domain sensor and time domain reflectometry (TDR) sensors along vertical profiles, soil probes and meteorological data are available at each station. In this contribution we present a detailed description of the SOMOMOUNT instrumentation and calibration procedures. Additionally, the liquid soil moisture (LSM) data collected during the first 3 years of the project are discussed with regard to their soil type and climate dependency as well as their altitudinal distribution. The observed elevation dependency of LSM is found to be non-linear, with an increase of the mean annual values up to ˜ 2000 m a.s.l. followed by a decreasing trend towards higher elevations. This altitude threshold marks the change between precipitation-/evaporation-controlled and frost-affected LSM regimes. The former is characterized by high LSM throughout the year and minimum values in summer, whereas the latter typically exhibits long-lasting winter minimum LSM values and high variability during the summer.

  1. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  3. 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.

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

    Science.gov (United States)

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

    2018-03-01

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

  5. Soil nutrient content, soil moisture and yield of Katumani maize in a ...

    African Journals Online (AJOL)

    Administrator

    Sci. Technol. Table 1. Correlations (r) of soil moisture content (SMC) and clay content (CC) with total soil organic carbon (TSOC), total soil nitrogen (TSN) and available phosphorus (AP) at the 0 – 20 cm depth. SMC (%) Clay (%) TSOC r CC rSMC TSN. rCC rSMC. AP. rCC rSMC. Treatment. Season 1 (0 –20 cm) depth. NE.

  6. 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.

  7. Soil moisture gradients and controls on a southern Appalachian hillslope from drought through recharge

    Directory of Open Access Journals (Sweden)

    J. A. Yeakley

    1998-01-01

    Full Text Available Soil moisture gradients along hillslopes in humid watersheds, although indicated by vegetation gradients and by studies using models, have been difficult to confirm empirically. While soil properties and topographic features are the two general physio-graphic factors controlling soil moisture on hillslopes, studies have shown conflicting results regarding which factor is more important. The relative importance of topographic and soil property controls was examined in an upland forested watershed at the Coweeta Hydrologic Laboratory in the southern Appalachian mountains. Soil moisture was measured along a hillslope transect with a mesic-to-xeric forest vegetation gradient over a period spanning precipitation extremes. The hillslope was transect instrumented with a time domain reflectometry (TDR network at two depths. Soil moisture was measured during a severe autumn drought and subsequent winter precipitation recharge. In the upper soil depth (0-30 cm, moisture gradients persisted throughout the measurement period, and topography exerted dominant control. For the entire root zone (0-90 cm, soil moisture gradients were found only during drought. Control on soil moisture was due to both topography and storage before drought. During and after recharge, variations in soil texture and horizon distribution exerted dominant control on soil moisture content in the root zone (0-90 cm. These results indicate that topographic factors assert more control over hillslope soil moisture during drier periods as drainage progresses, while variations in soil water storage properties are more important during wetter periods. Hillslope soil moisture gradients in southern Appalachian watersheds appear to be restricted to upper soil layers, with deeper hillslope soil moisture gradients occurring only with sufficient drought.

  8. 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

    increasing errors for higher soil moisture content. We also examined the effects of sub-footprint variability in soil moisture on the neutron readings by comparing two of the sites with large variations in topographically-mediated surface flows. Our work also synthesizes seasonal soil moisture dynamics across the desert ecosystems and attempts to tease out differences due to land cover alterations, including the seasonal greening in each study site occurring during the North American monsoon.

  9. Intercomparison of the JULES and CABLE land surface models through assimilation of remotely sensed soil moisture in southeast Australia

    Science.gov (United States)

    Dumedah, Gift; Walker, Jeffrey P.

    2014-12-01

    Numerous land surface models exist for predicting water and energy fluxes in the terrestrial environment. These land surface models have different conceptualizations (i.e., process or physics based), together with structural differences in representing spatial variability, alternate empirical methods, mathematical formulations and computational approach. These inherent differences in modeling approach, and associated variations in outputs make it difficult to compare and contrast land surface models in a straight-forward manner. While model intercomparison studies have been undertaken in the past, leading to significant progress on the improvement of land surface models, additional framework towards identification of model weakness is needed. Given that land surface models are increasingly being integrated with satellite based estimates to improve their prediction skill, it is practical to undertake model intercomparison on the basis of soil moisture data assimilation. Consequently, this study compares two land surface models: the Joint UK Land Environment Simulator (JULES) and the Community Atmosphere Biosphere Land Exchange (CABLE) for soil moisture estimation and associated assessment of model uncertainty. A retrieved soil moisture data set from the Soil Moisture and Ocean Salinity (SMOS) mission was assimilated into both models, with their updated estimates validated against in-situ soil moisture in the Yanco area, Australia. The findings show that the updated estimates from both models generally provided a more accurate estimate of soil moisture than the open loop estimate based on calibration alone. Moreover, the JULES output was found to provide a slightly better estimate of soil moisture than the CABLE output at both near-surface and deeper soil layers. An assessment of the updated membership in decision space also showed that the JULES model had a relatively stable, less sensitive, and more highly convergent internal dynamics than the CABLE model.

  10. Optimizing operational water management with soil moisture data from Sentinel-1 satellites

    Science.gov (United States)

    Pezij, Michiel; Augustijn, Denie; Hendriks, Dimmie; Hulscher, Suzanne

    2016-04-01

    In the Netherlands, regional water authorities are responsible for management and maintenance of regional water bodies. Due to socio-economic developments (e.g. agricultural intensification and on-going urbanisation) and an increase in climate variability, the pressure on these water bodies is growing. Optimization of water availability by taking into account the needs of different users, both in wet and dry periods, is crucial for sustainable developments. To support timely and well-directed operational water management, accurate information on the current state of the system as well as reliable models to evaluate water management optimization measures are essential. Previous studies showed that the use of remote sensing data (for example soil moisture data) in water management offers many opportunities (e.g. Wanders et al. (2014)). However, these data are not yet used in operational applications at a large scale. The Sentinel-1 satellites programme offers high spatiotemporal resolution soil moisture data (1 image per 6 days with a spatial resolution of 10 by 10 m) that are freely available. In this study, these data will be used to improve the Netherlands Hydrological Instrument (NHI). The NHI consists of coupled models for the unsaturated zone (MetaSWAP), groundwater (iMODFLOW) and surface water (Mozart and DM). The NHI is used for scenario analyses and operational water management in the Netherlands (De Lange et al., 2014). Due to the lack of soil moisture data, the unsaturated zone model is not yet thoroughly validated and its output is not used by regional water authorities for decision-making. Therefore, the newly acquired remotely sensed soil moisture data will be used to improve the skill of the MetaSWAP-model and the NHI as whole. The research will focus among other things on the calibration of soil parameters by comparing model output (MetaSWAP) with the remotely sensed soil moisture data. Eventually, we want to apply data-assimilation to improve

  11. NASA's Soil Moisture Active and Passive (SMAP) Mission

    Science.gov (United States)

    Kellogg, Kent; Njoku, Eni; Thurman, Sam; Edelstein, Wendy; Jai, Ben; Spencer, Mike; Chen, Gun-Shing; Entekhabi, Dara; O'Neill, Peggy; Piepmeier, Jeffrey; hide

    2010-01-01

    The Soil Moisture Active-Passive (SMAP) Mission is one of the first Earth observation satellites being formulated by NASA in response to the 2007 National Research Council s Decadal Survey. SMAP will make global measurements of soil moisture at the Earth's land surface and its freeze-thaw state. These measurements will allow significantly improved estimates of water, energy and carbon transfers between the land and atmosphere. Soil moisture measurements are also of great importance in assessing flooding and monitoring drought. Knowledge gained from SMAP observations can help mitigate these natural hazards, resulting in potentially great economic and social benefits. SMAP observations of soil moisture and freeze/thaw timing over the boreal latitudes will also reduce a major uncertainty in quantifying the global carbon balance and help to resolve an apparent missing carbon sink over land. The SMAP mission concept will utilize an L-band radar and radiometer sharing a rotating 6-meter mesh reflector antenna flying in a 680 km polar orbit with an 8-day exact ground track repeat aboard a 3-axis stabilized spacecraft to provide high-resolution and high-accuracy global maps of soil moisture and freeze/thaw state every two to three days. In addition, the SMAP project will use these surface observations with advanced modeling and data assimilation to provide estimates of deeper root-zone soil moisture and net ecosystem exchange of carbon. SMAP recently completed its Phase A Mission Concept Study Phase for NASA and transitioned into Phase B (Formulation and Detailed Design). A number of significant accomplishments occurred during this initial phase of mission development. The SMAP project held several open meetings to solicit community feedback on possible science algorithms, prepared preliminary draft Algorithm Theoretical Basis Documents (ATBDs) for each mission science product, and established a prototype algorithm testbed to enable testing and evaluation of the

  12. Monitoring soil moisture from middle to high elevation in Switzerland: set-up and first results from the SOMOMOUNT network

    Directory of Open Access Journals (Sweden)

    C. Pellet

    2017-06-01

    Full Text Available Besides its important role in the energy and water balance at the soil–atmosphere interface, soil moisture can be a particular important factor in mountain environments since it influences the amount of freezing and thawing in the subsurface and can affect the stability of slopes. In spite of its importance, the technical challenges and its strong spatial variability usually prevents soil moisture from being measured operationally at high and/or middle altitudes. This study describes the new Swiss soil moisture monitoring network SOMOMOUNT (soil moisture in mountainous terrain launched in 2013. It consists of six entirely automated soil moisture stations distributed along an altitudinal gradient between the Jura Mountains and the Swiss Alps, ranging from 1205 to 3410 m a.s.l. in elevation. In addition to the standard instrumentation comprising frequency domain sensor and time domain reflectometry (TDR sensors along vertical profiles, soil probes and meteorological data are available at each station. In this contribution we present a detailed description of the SOMOMOUNT instrumentation and calibration procedures. Additionally, the liquid soil moisture (LSM data collected during the first 3 years of the project are discussed with regard to their soil type and climate dependency as well as their altitudinal distribution. The observed elevation dependency of LSM is found to be non-linear, with an increase of the mean annual values up to  ∼  2000 m a.s.l. followed by a decreasing trend towards higher elevations. This altitude threshold marks the change between precipitation-/evaporation-controlled and frost-affected LSM regimes. The former is characterized by high LSM throughout the year and minimum values in summer, whereas the latter typically exhibits long-lasting winter minimum LSM values and high variability during the summer.

  13. 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.

  14. Comparing the ensemble and extended Kalman filters for in situ soil moisture assimilation with contrasting conditions

    Directory of Open Access Journals (Sweden)

    D. Fairbairn

    2015-12-01

    Full Text Available Two data assimilation (DA methods are compared for their ability to produce an accurate soil moisture analysis using the Météo-France land surface model: (i SEKF, a simplified extended Kalman filter, which uses a climatological background-error covariance, and (ii EnSRF, the ensemble square root filter, which uses an ensemble background-error covariance and approximates random rainfall errors stochastically. In situ soil moisture observations at 5 cm depth are assimilated into the surface layer and 30 cm deep observations are used to evaluate the root-zone analysis on 12 sites in south-western France (SMOSMANIA network. These sites differ in terms of climate and soil texture. The two methods perform similarly and improve on the open loop. Both methods suffer from incorrect linear assumptions which are particularly degrading to the analysis during water-stressed conditions: the EnSRF by a dry bias and the SEKF by an over-sensitivity of the model Jacobian between the surface and the root-zone layers. These problems are less severe for the sites with wetter climates. A simple bias correction technique is tested on the EnSRF. Although this reduces the bias, it modifies the soil moisture fluxes and suppresses the ensemble spread, which degrades the analysis performance. However, the EnSRF flow-dependent background-error covariance evidently captures seasonal variability in the soil moisture errors and should exploit planned improvements in the model physics. Synthetic twin experiments demonstrate that when there is only a random component in the precipitation forcing errors, the correct stochastic representation of these errors enables the EnSRF to perform better than the SEKF. It might therefore be possible for the EnSRF to perform better than the SEKF with real data, if the rainfall uncertainty was accurately captured. However, the simple rainfall error model is not advantageous in our real experiments. More realistic rainfall error models are

  15. 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...

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

    Science.gov (United States)

    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...

  17. Soil moisture retrieval in mining-disturbed areas with temporal high resolution SAR

    Science.gov (United States)

    Ma, Wei; Liu, Weiwei; Ma, Chao

    2018-02-01

    Using 12 periods RADARSAT-2 HH polarization data and combining with the Alpha approximation model, the soil moisture of the study area was retrieved and then compared with the MODIS retrieval results. Then, the DInSAR results of RADARSAT-2 were used to investigate the effect of high intensity underground mining activities on surface soil moisture. The study found that the soil moisture values of RADARSAT-2 had a good correlation with MODIS retrieval results. In the four comparison groups, the maximum correlation coefficient was 0.599 (p<0.01). The comparison among the 72 soil moisture values of the six mining subsidence areas and the non-subsidence areas in the study area in 2012 showed that there were 38 soil moisture values of the non-subsidence area was higher than that of the subsidence area, which indicated that the high-intensity mining activity had a certain negative impact on the surface soil moisture.

  18. Comparison of Soil Moisture in Switzerland Using In-Situ Measurements and Model Output

    Science.gov (United States)

    Mittelbach, H.; Orth, R.; Seneviratne, S. I.

    2011-01-01

    Soil moisture is an essential contributor to land surface- atmosphere interactions. In this study we evaluate the two Land surface models CLM3.5 and SIB3 regarding their performance in simulating soil moisture and its anomalies for the one year period 01.09.2009 to 31.08.2010. Four grassland sites from the SwissSMEX/- Veg project were used as reference soil moisture data. In general, both models represent the soil moisture anomalies and their distribution better than the absolute soil moisture. Furthermore, both models show a seasonal dependence of the correlation and root mean square error. In contrast to the SIB3 model, the CLM3.5 model shows stronger seasonal variation of the root mean square error and a larger interquantile range for soil moisture anomalies.

  19. Assimilating scatterometer soil moisture data into conceptual hydrologic models at the regional scale

    Directory of Open Access Journals (Sweden)

    J. Parajka

    2006-01-01

    Full Text Available This paper examines the potential of scatterometer data from ERS satellites for improving hydrological simulations in both gauged and ungauged catchments. We compare the soil moisture dynamics simulated by a semidistributed hydrologic model in 320 Austrian catchments with the soil moisture dynamics inferred from the satellite data. The most apparent differences occur in the Alpine areas. Assimilating the scatterometer data into the hydrologic model during the calibration phase improves the relationship between the two soil moisture estimates without any significant decrease in runoff model efficiency. For the case of ungauged catchments, assimilating scatterometer data does not improve the daily runoff simulations but does provide more consistent soil moisture estimates. If the main interest is in obtaining estimates of catchment soil moisture, reconciling the two sources of soil moisture information seems to be of value because of the different error structures.

  20. 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

  1. Use of a combined penetrometer-TDR moisture probe for soil compaction studies

    International Nuclear Information System (INIS)

    Pedro Vaz, C.M.

    2004-01-01

    Soil mechanical strength is an important soil parameter that affects root growth and water movement, and controls nutrient and contaminant transport below the rooting zone. The most common way to assess soil strength is by using a soil penetrometer, which characterizes the force needed to drive a cone of specific size into the soil. The measured penetration resistance (PR) depends on such soil properties as bulk density, water content and potential, texture, aggregation, cementation and mineralogy. Soil scientists have related changes in PR as caused by tillage, traffic or soil genetic pans to root growth, crop yields and soil physical properties. For example, correlation between PR and crop root growth and water and nutrient exploration have been obtained, and cone penetrometers have been used extensively in soil science studies to identify natural and induced compacted layers or to predict related soil properties. Many studies have been conducted to understand the influence of bulk density and water content on PR in the laboratory and, from which both empirical and theoretical relationships were obtained. From the many different models that have been introduced to test these relationships (polynomial, exponential, power and linear equations), it is suggested that either the power or exponential equations are the most adequate. Using dimensional analysis techniques, it was suggested a power exponential equation for prediction of the PR for a silt loam soil, but also suggested additional experimental work for its validation. However, many referenced studies lack accurate and representative data, because PR is a highly variable soil property, whereas it is usually determined from local small-scale measurements. Hence, difficulties in relating PR with other soil parameters can be attributed mostly to soil spatial variability, because available measurement techniques prevent determination of the different soil attributes at the same spatial location. To improve on the

  2. Surprisingly robust projections of soil temperature and moisture for North American drylands in the 21st century

    Science.gov (United States)

    Bradford, J. B.; Schlaepfer, D.; Palmquist, K. A.; Lauenroth, W.

    2017-12-01

    Climate projections for western North America suggest temperature increases that are relatively consistent across climate models. However, precipitation projections are less consistent, especially in the Southwest, promoting uncertainty about the future of soil moisture and drought. We utilized a daily time-step ecosystem water balance model to characterize soil temperature and moisture patterns at a 10-km resolution across western North America for historical (1980-2010), mid-century (2020-2050), and late century (2070-2100). We simulated soil moisture and temperature under two representative concentration pathways and eleven climate models (selected strategically to represent the range of variability in projections among the full set of models in the CMIP5 database and perform well in hind-cast comparisons for the region), and we use the results to identify areas with robust projections, e.g. areas where the large majority of models agree in the direction of change in long-term average soil moisture or temperature. Rising air temperatures will increase average soil temperatures across western North America and expand the area of mesic and thermic soil temperature regimes while decreasing the area of cryic and frigid regimes. Future soil moisture conditions are relatively consistent across climate models for much of the region, including many areas with variable precipitation trajectories. Consistent projections for drier soils are expected in most of Arizona and New Mexico, similar to previous studies. Other regions with projections for declining soil moisture include the central and southern U.S. Great Plains and large parts of southern British Columbia. By contrast, areas with robust projections for increasing soil moisture include northeastern Montana, southern Alberta and Saskatchewan, and many areas in the intermountain west dominated by big sagebrush. In addition, seasonal moisture patterns in much of the western US drylands are expected to shift toward

  3. Impact of stone content on soil moisture measurement with capacitive sensors 10HS (Decagon)

    Science.gov (United States)

    Deraedt, Deborah; Bernard, Julien; Bietlot, Louise; Clerbois, Laura; Rosière, Clément; Starren, Amandine; Colinet, Gilles; Mercatoris, Benoit; Degré, Aurore

    2015-04-01

    Lot of soil survey focused on agricultural soils. For practical reasons, those soils have a low stone content. So, most of the soil water content sensors are placed on low stone content soils and the calibration equations are developed for them. Yet some researches take an interest in forest soils that are often much different from the previous ones. The differences lie in their stone content and their slope. Lots of studies have proved the importance of making soil specific calibration of the soil water content sensor. As our lab use regularly the 10HS sensors (Decagon Devices, United States) in forested soil, we decided to evaluate the importance of the stone content in the soil moisture measurement. The soil used for this experimentation comes from Gembloux (50°33'54.9''N, 4°42'11.3''E). It is silt that has been sieved at 2 mm to remove the gravel. The stones used to form the samples come from an experimental site located in the Belgian Ardennes (50°1'52.6''N, 4°53'22.5''E). They are mainly composed of schist with some quartz and sandstone elements. Initially, only five samples were constructed with three replications each. The size and the proportion of stones were the variables. Stones were classified in two groups, the first contains gravels whose size is less than 1,5 cm and a the second contains gravels whose size is comprised between 2 and 3 cm. The proportions of stone selected for the experiment are 0, 20 and 40%. In order to generate validation data, two more samples were constructed with intermediate proportion of stone content (30%). The samples were built in PVC container which dimensions are slightly bigger than the sensor volume of influence (1.1-1.3l). The soil samples were saturated and then dried on a thermal chamber set at about 32°C. During at least 14 days, the samples soil water content was determined by the sensor measurement with the Procheck read-out system (Decagon Devices, United State) and by weighting the samples thrice a day

  4. Empirical Soil Moisture Estimation with Spaceborne L-band Polarimetric Radars: Aquarius, SMAP, and PALSAR-2

    Science.gov (United States)

    Burgin, M. S.; van Zyl, J. J.

    2017-12-01

    Traditionally, substantial ancillary data is needed to parametrize complex electromagnetic models to estimate soil moisture from polarimetric radar data. The Soil Moisture Active Passive (SMAP) baseline radar soil moisture retrieval algorithm uses a data cube approach, where a cube of radar backscatter values is calculated using sophisticated models. In this work, we utilize the empirical approach by Kim and van Zyl (2009) which is an optional SMAP radar soil moisture retrieval algorithm; it expresses radar backscatter of a vegetated scene as a linear function of soil moisture, hence eliminating the need for ancillary data. We use 2.5 years of L-band Aquarius radar and radiometer derived soil moisture data to determine two coefficients of a linear model function on a global scale. These coefficients are used to estimate soil moisture with 2.5 months of L-band SMAP and L-band PALSAR-2 data. The estimated soil moisture is compared with the SMAP Level 2 radiometer-only soil moisture product; the global unbiased RMSE of the SMAP derived soil moisture corresponds to 0.06-0.07 cm3/cm3. In this study, we leverage the three diverse L-band radar data sets to investigate the impact of pixel size and pixel heterogeneity on soil moisture estimation performance. Pixel sizes range from 100 km for Aquarius, over 3, 9, 36 km for SMAP, to 10m for PALSAR-2. Furthermore, we observe seasonal variation in the radar sensitivity to soil moisture which allows the identification and quantification of seasonally changing vegetation. Utilizing this information, we further improve the estimation performance. The research described in this paper is supported by the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. Copyright 2017. All rights reserved.

  5. Preliminary Evaluation of the SMAP Radiometer Soil Moisture Product over China Using In Situ Data

    Directory of Open Access Journals (Sweden)

    Yayong Sun

    2017-03-01

    Full Text Available The Soil Moisture Active Passive (SMAP satellite makes coincident global measurements of soil moisture using an L-band radar instrument and an L-band radiometer. It is crucial to evaluate the errors in the newest L-band SMAP satellite-derived soil moisture products, before they are routinely used in scientific research and applications. This study represents the first evaluation of the SMAP radiometer soil moisture product over China. In this paper, a preliminary evaluation was performed using sparse in situ measurements from 655 China Meteorological Administration (CMA monitoring stations between 1 April 2015 and 31 August 2016. The SMAP radiometer-derived soil moisture product was evaluated against two schemes of original soil moisture and the soil moisture anomaly in different geographical zones and land cover types. Four performance metrics, i.e., bias, root mean square error (RMSE, unbiased root mean square error (ubRMSE, and the correlation coefficient (R, were used in the accuracy evaluation. The results indicated that the SMAP radiometer-derived soil moisture product agreed relatively well with the in situ measurements, with ubRMSE values of 0.058 cm3·cm−3 and 0.039 cm3·cm−3 based on original data and anomaly data, respectively. The values of the SMAP radiometer-based soil moisture product were overestimated in wet areas, especially in the Southwest China, South China, Southeast China, East China, and Central China zones. The accuracies over croplands and in Northeast China were the worst. Soil moisture, surface roughness, and vegetation are crucial factors contributing to the error in the soil moisture product. Moreover, radio frequency interference contributes to the overestimation over the northern portion of the East China zone. This study provides guidelines for the application of the SMAP-derived soil moisture product in China and acts as a reference for improving the retrieval algorithm.

  6. Correlation of spacecraft passive microwave system data with soil moisture indices (API). [great plains corridor

    Science.gov (United States)

    Blanchard, B. J.; Mcfarland, M. J.; Theis, S.; Richter, J. G.

    1981-01-01

    Electrical scanning microwave radiometer brightness temperature, meteorological data, climatological data, and winter wheat crop information were used to estimate that soil moisture content in the Great Plains region. Results over the predominant winter wheat areas indicate that the best potential to infer soil moisture occurs during fall and spring. These periods encompass the growth stages when soil</