7 CFR 801.6 - Tolerances for moisture meters.
Code of Federal Regulations, 2010 CFR
2010-01-01
... moisture, mean deviation from National standard moisture meter using Hard Red Winter wheat Mid ±0.05 percent moisture, mean deviation from National standard moisture meter using Hard Red Winter wheat High ±0.05 percent moisture, mean deviation from National standard moisture meter using Hard Red Winter wheat...
Electric moisture meters for wood
William L. James
1988-01-01
Electric moisture meters for wood measure electric conductance (resistance) or dielectric properties, which vary fairly consistently with moisture content when it is less than 30 percent. The two major classes of electric moisture meters are the conductance (resistance) type and the dielectric type. Conductance-t ype meters use penetrating electrodes that measure in a...
7 CFR 801.6 - Tolerances for moisture meters.
Code of Federal Regulations, 2011 CFR
2011-01-01
... 7 Agriculture 7 2011-01-01 2011-01-01 false Tolerances for moisture meters. 801.6 Section 801.6... FOR GRAIN INSPECTION EQUIPMENT § 801.6 Tolerances for moisture meters. (a) The maintenance tolerances for Motomco 919 moisture meters used in performing official inspection services shall be: (1...
7 CFR 801.6 - Tolerances for moisture meters.
Code of Federal Regulations, 2014 CFR
2014-01-01
... 7 Agriculture 7 2014-01-01 2014-01-01 false Tolerances for moisture meters. 801.6 Section 801.6... FOR GRAIN INSPECTION EQUIPMENT § 801.6 Tolerances for moisture meters. (a) The maintenance tolerances for Motomco 919 moisture meters used in performing official inspection services shall be: (1...
7 CFR 801.6 - Tolerances for moisture meters.
Code of Federal Regulations, 2012 CFR
2012-01-01
... 7 Agriculture 7 2012-01-01 2012-01-01 false Tolerances for moisture meters. 801.6 Section 801.6... FOR GRAIN INSPECTION EQUIPMENT § 801.6 Tolerances for moisture meters. (a) The maintenance tolerances for Motomco 919 moisture meters used in performing official inspection services shall be: (1...
7 CFR 801.6 - Tolerances for moisture meters.
Code of Federal Regulations, 2013 CFR
2013-01-01
... 7 Agriculture 7 2013-01-01 2013-01-01 false Tolerances for moisture meters. 801.6 Section 801.6... FOR GRAIN INSPECTION EQUIPMENT § 801.6 Tolerances for moisture meters. (a) The maintenance tolerances for Motomco 919 moisture meters used in performing official inspection services shall be: (1...
7 CFR 801.12 - Design requirements incorporated by reference.
Code of Federal Regulations, 2011 CFR
2011-01-01
... by reference. (a) Moisture meters. All moisture meters approved for use in official grain moisture determination and certification shall meet applicable requirements contained in the FGIS Moisture Handbook and the General Code and Grain Moisture Meters Code of the 1991 edition of the National Institute of...
7 CFR 801.12 - Design requirements incorporated by reference.
Code of Federal Regulations, 2013 CFR
2013-01-01
... by reference. (a) Moisture meters. All moisture meters approved for use in official grain moisture determination and certification shall meet applicable requirements contained in the FGIS Moisture Handbook and the General Code and Grain Moisture Meters Code of the 1991 edition of the National Institute of...
7 CFR 801.12 - Design requirements incorporated by reference.
Code of Federal Regulations, 2014 CFR
2014-01-01
... by reference. (a) Moisture meters. All moisture meters approved for use in official grain moisture determination and certification shall meet applicable requirements contained in the FGIS Moisture Handbook and the General Code and Grain Moisture Meters Code of the 1991 edition of the National Institute of...
7 CFR 801.12 - Design requirements incorporated by reference.
Code of Federal Regulations, 2012 CFR
2012-01-01
... by reference. (a) Moisture meters. All moisture meters approved for use in official grain moisture determination and certification shall meet applicable requirements contained in the FGIS Moisture Handbook and the General Code and Grain Moisture Meters Code of the 1991 edition of the National Institute of...
Space-time modeling of soil moisture
NASA Astrophysics Data System (ADS)
Chen, Zijuan; Mohanty, Binayak P.; Rodriguez-Iturbe, Ignacio
2017-11-01
A physically derived space-time mathematical representation of the soil moisture field is carried out via the soil moisture balance equation driven by stochastic rainfall forcing. The model incorporates spatial diffusion and in its original version, it is shown to be unable to reproduce the relative fast decay in the spatial correlation functions observed in empirical data. This decay resulting from variations in local topography as well as in local soil and vegetation conditions is well reproduced via a jitter process acting multiplicatively over the space-time soil moisture field. The jitter is a multiplicative noise acting on the soil moisture dynamics with the objective to deflate its correlation structure at small spatial scales which are not embedded in the probabilistic structure of the rainfall process that drives the dynamics. These scales of order of several meters to several hundred meters are of great importance in ecohydrologic dynamics. Properties of space-time correlation functions and spectral densities of the model with jitter are explored analytically, and the influence of the jitter parameters, reflecting variabilities of soil moisture at different spatial and temporal scales, is investigated. A case study fitting the derived model to a soil moisture dataset is presented in detail.
Embedded solution for a microwave moisture meter
USDA-ARS?s Scientific Manuscript database
In this paper, the conversion of a PC or laptop-controlled microwave moisture meter to a stand-alone meter hosting its own embedded system is discussed. The moisture meter is based on the free-space transmission measurement technique and uses low-intensity microwaves to measure the attenuation and p...
Integrating an embedded system in a microwave moisture meter
USDA-ARS?s Scientific Manuscript database
The conversion of a PC- or laptop-controlled microwave moisture meter to a stand-alone meter hosting its own embedded system is discussed. The moisture meter measures the attenuation and phase shift of low power microwaves traversing the sample, from which the dielectric properties are calculated. T...
Integrating an Embedded System within a Microwave Moisture Meter
USDA-ARS?s Scientific Manuscript database
In this paper, the conversion of a PC or laptop-controlled microwave moisture meter to a stand-alone meter hosting its own embedded system is discussed. The moisture meter uses low-power microwaves to measure the attenuation and phase shift of the sample, from which the dielectric properties are cal...
Electric moisture meters for wood
William L. James
1963-01-01
Common methods of measuring the moisture content of wood are described briefly, and a short historical account of the development of electric moisture meters is given. Electrical properties of wood are discussed briefly, and the basic operation of the resistance type and the radio- frequency types of moisture meter is outlined. Data relating the electrical resistance...
Moisture meter calibration for untreated and ACQ-treated southern yellow pine plywood
Samuel V. Glass; Charles G. Carll
2009-01-01
Conductance moisture meter readings using stainless steel screws as electrodes were compared with gravimetric moisture content for 1) southern yellow pine (SYP) dimensioned lumber, 2) untreated (underlayment grade) SYP plywood, and 3) SYP plywood treated with alkaline copper quaternary. Meter readings were taken with the meter set to the manufacturer-provided species...
COMPARING MOISTURE METER READINGS WITH MEASURED EQUILIBRIUM MOISTURE CONTENT OF GYPSUM BOARD
Moisture meters routinely used in the field to determine the moisture content in gypsum wallboard are primarily designed and manufactured to measure the moisture content of wood. Often they are used to decide whether to replace wallboard by determining if moisture is qualitativel...
Microwave moisture meter for in-shell peanut kernels
USDA-ARS?s Scientific Manuscript database
. A microwave moisture meter built with off-the-shelf components was developed, calibrated and tested in the laboratory and in the field for nondestructive and instantaneous in-shell peanut kernel moisture content determination from dielectric measurements on unshelled peanut pod samples. The meter ...
A Redesigned DFA Moisture Meter
USDA-ARS?s Scientific Manuscript database
The DFA moisture meter has been internationally recognized as the standard for determining moisture content of dried fruit in general and is AOAC Official Method 972.2 for measuring moisture in prunes and raisins since 1972. The device has remained virtually unchanged since its inception, with its o...
NASA Technical Reports Server (NTRS)
Wetzel, Peter J.; Chang, Jy-Tai
1988-01-01
Observations of surface heterogeneity of soil moisture from scales of meters to hundreds of kilometers are discussed, and a relationship between grid element size and soil moisture variability is presented. An evapotranspiration model is presented which accounts for the variability of soil moisture, standing surface water, and vegetation internal and stomatal resistance to moisture flow from the soil. The mean values and standard deviations of these parameters are required as input to the model. Tests of this model against field observations are reported, and extensive sensitivity tests are presented which explore the importance of including subgrid-scale variability in an evapotranspiration model.
Moisture meter calibrations for untreated and ACQ-treated southern yellow pine lumber and plywood
C.R. Boardman; Samuel V. Glass; Charles G. Carll
2011-01-01
This study investigates the effects of alkaline copper quaternary (ACQ) preservative treatment and of plywood glue lines on resistance-based moisture content (MC) measurements. Moisture meter readings using stainless steel screws as electrodes were acquired over a range of moisture conditions in Southern Yellow Pine (SYP) lumber and plywood. Calibration equations are...
Performance of a Microwave Bale Moisture Content Meter
USDA-ARS?s Scientific Manuscript database
Measuring the moisture content of cotton bales has been a topic of intense interest in the last few years. A non-contact microwave-based bale moisture meter, Vomax 851-B (Vomax Instrumentation through Samuel Jackson, Lubbock, TX) has been commercially available but independent verification of these...
Improving the accuracy of electronic moisture meters for runner-type peanuts
USDA-ARS?s Scientific Manuscript database
Runner-type peanut kernel moisture content (MC) is measured periodically during curing and post harvest processing with electronic moisture meters for marketing and quality control. MC is predicted for 250 g samples of kernels with a mathematical function from measurements of various physical prope...
Development of a method to relate the moisture content of a building material to its water activity.
Macher, J M; Mendell, M J; Chen, W; Kumagai, K
2017-05-01
Subjective indicators of building dampness consistently have been linked to health, but they are, at best, semi-quantitative, and objective and quantitative assessments of dampness are also needed to study dampness-related health effects. Investigators can readily and non-destructively measure the "moisture content" (MC) of building materials with hand-held moisture meters. However, MC does not indicate the amount of the water in a material that is available to microorganisms for growth, that is, the "water activity" (A w ). Unfortunately, A w has not been readily measurable in the field and is not relatable to MC unless previously determined experimentally, because for the same moisture meter reading, A w can differ across materials as well as during moisture adsorption vs desorption. To determine the A w s that correspond to MC levels, stable air relative humidities were generated in a glove box above saturated, aqueous salt solutions, and the A w of gypsum board and the relative humidity of the chamber air were tracked until they reached equilibrium. Strong correlations were observed between meter readings and gravimetrically determined MC (r=.91-1.00), among readings with three moisture meters (r=.87-.98), and between meter readings and gypsum board A w (r=.77-.99). © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Measurement of Moisture in Wood for Application in the Restoration of Old Buildings.
Moron, Carlos; Garcia-Fuentevilla, Luisa; Garcia, Alfonso; Moron, Alberto
2016-05-14
There are many historic buildings whose construction is based on timber frame walls. Most buildings built during the nineteenth and early twentieth centuries were based on timber frame walls with vertical support elements. These timber frame elements are affected by their moisture content and by the passage of time. If the interaction of the timber frame walls with hygrothermal fluctuations were known, the maintenance of these buildings could be improved significantly. To determine the moisture content of wood there are two types of meters on the market: on the one hand, capacitance meters which consist of two side ends and where the moisture content is measured locally between two peaks. On the other hand, there are meters based on the variation of electromagnetic transmittance of timber, which depends on the moisture of timber. The second ones are very expensive and difficult to handle. This work presents a new non-intrusive capacitive sensor that measures the global moisture content in a section of the timber frame walls and therefore its accuracy is similar to the accuracy that can be obtained with electromagnetic transmittance meters. Additionally, as it is a capacitive sensor, it is low cost and easy to operate.
Measurement of Moisture in Wood for Application in the Restoration of Old Buildings
Moron, Carlos; Garcia-Fuentevilla, Luisa; Garcia, Alfonso; Moron, Alberto
2016-01-01
There are many historic buildings whose construction is based on timber frame walls. Most buildings built during the nineteenth and early twentieth centuries were based on timber frame walls with vertical support elements. These timber frame elements are affected by their moisture content and by the passage of time. If the interaction of the timber frame walls with hygrothermal fluctuations were known, the maintenance of these buildings could be improved significantly. To determine the moisture content of wood there are two types of meters on the market: on the one hand, capacitance meters which consist of two side ends and where the moisture content is measured locally between two peaks. On the other hand, there are meters based on the variation of electromagnetic transmittance of timber, which depends on the moisture of timber. The second ones are very expensive and difficult to handle. This work presents a new non-intrusive capacitive sensor that measures the global moisture content in a section of the timber frame walls and therefore its accuracy is similar to the accuracy that can be obtained with electromagnetic transmittance meters. Additionally, as it is a capacitive sensor, it is low cost and easy to operate. PMID:27187410
NASA Technical Reports Server (NTRS)
Joseph, A. T.; Deshpande, M.; O'Neill, P. E.; Miles, L.
2017-01-01
A goal of this research is to test deployable VHF antennas for 6U Cubesat platforms to enable validation of root zone soil moisture (RZSM) estimation algorithms for signal of opportunity (SoOp) remote sensing over the 240-270 MHz frequency band. The proposed work provides a strong foundation for establishing a technology development path for maturing a global direct surface soil moisture (SM) and RZSM measurement system over a variety of land covers. Knowledge of RZSM up to a depth of 1 meter and surface SM up to a depth of 0.05 meter on a global scale, at a spatial resolution of 1-10 km through moderate-to-heavy vegetation, is critical to understanding global water resources and the vertical moisture gradient in the Earths surface layer which controls moisture interactions between the soil, vegetation, and atmosphere. Current observations of surface SM from space by L-band radiometers (1.4 GHz) and radars (1.26 GHz) are limited to measurements of surface SM up to a depth of 0.05 meter through moderate amounts of vegetation. This limitation is mainly due to the inability of L-band signals to penetrate through dense vegetation and deep into the soil column. Satellite observations of the surface moisture conditions are coupled to sophisticated models which extrapolate the surface SM into the root zone, thus providing an indirect estimate rather than a direct measurement of RZSM. To overcome this limitation, low-frequency airborne radars operating at 435 MHz and 118 MHz have been investigated, since these lower frequencies should penetrate denser vegetation and respond to conditions deeper in the soil.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Brownell, L.E.; Backer, J.G.; Isaacson, R.E.
1975-07-01
Data are presented from measurements of soil moisture at the Hanford Reservation. Possible mechanisms for moisture transport in arid and semi-arid climates were studied. Measurements for the lysimeter experiment and the thermocouple psychrometer experiment were continued with a new series of measurements using closely spaced sensors installed to a depth of 1.52 meters. During the 1973-1974 water year the percolation envelope of higher moisture content penetrated to a depth of four meters in the closed-bottom lysimeter and then was eliminated by upward transport of water in late summer. Precipitation during the 1973-1974 water year percolated to a depth of aboutmore » six meters in the open-bottom lysimeter and remains as a residual perched envelope. The increase over normal percolation was due in part to a residual envelope of higher moisture content from the previous water year. Results obtained indicate the advantages of Hanford as a site for a national repository for radioactive waste. (CH)« less
NASA Astrophysics Data System (ADS)
Korres, W.; Reichenau, T. G.; Schneider, K.
2012-12-01
Soil moisture is one of the fundamental variables in hydrology, meteorology and agriculture, influencing the partitioning of solar energy into latent and sensible heat flux as well as the partitioning of precipitation into runoff and percolation. Numerous studies have shown that in addition to natural factors (rainfall, soil, topography etc.) agricultural management is one of the key drivers for spatio-temporal patterns of soil moisture in agricultural landscapes. Interactions between plant growth, soil hydrology and soil nitrogen transformation processes are modeled by using a dynamically coupled modeling approach. The process-based ecohydrological model components of the integrated decision support system DANUBIA are used to identify the important processes and feedbacks determining soil moisture patterns in agroecosystems. Integrative validation of plant growth and surface soil moisture dynamics serves as a basis for a spatially distributed modeling analysis of surface soil moisture patterns in the northern part of the Rur catchment (1100 sq km), Western Germany. An extensive three year dataset (2007-2009) of surface soil moisture-, plant- (LAI, organ specific biomass and N) and soil- (texture, N, C) measurements was collected. Plant measurements were carried out biweekly for winter wheat, maize, and sugar beet during the growing season. Soil moisture was measured with three FDR soil moisture stations. Meteorological data was measured with an eddy flux station. The results of the model validation showed a very good agreement between the modeled plant parameters (biomass, green LAI) and the measured parameters with values between 0.84 and 0.98 (Willmotts index of agreement). The modeled surface soil moisture (0 - 20 cm) showed also a very favorable agreement with the measurements for winter wheat and sugar beet with an RMSE between 1.68 and 3.45 Vol.-%. For maize, the RMSE was less favorable particularly in the 1.5 months prior to harvest. The modeled soil moisture remained in contrast to the measurements very responsive to precipitation with high soil moisture after precipitation events. This behavior indicates that the soil properties might have changed due to the formation of a surface crust or seal towards the end of the growing season. Spatial soil moisture patterns were investigated using a grid resolution of 150 meter. Spatial autocorrelation was computed on a daily basis using patterns of soil texture as well as transpiration and precipitation indices as co-variables. Spatial patterns of surface soil moisture are mostly determined by the structure of the soil properties (soil type) during winter, early growing season and after harvest of all crops. Later in the growing season, after establishment of a closed canopy the dependence of the soil moisture patterns on soil texture patterns becomes smaller and diminishes quickly after precipitation events, due to differences of the transpiration rate of the different crops. When changing the spatial scale of the analysis, the highest autocorrelation values can be found on a grid cell size between 450 and 1200 meters. Thus, small scale variability of transpiration induced by the land use pattern almost averages out, leaving the larger scale structure of soil properties to explain the soil moisture patterns.
Assessment of the SMAP Passive Soil Moisture Product
NASA Technical Reports Server (NTRS)
Chan, Steven K.; Bindlish, Rajat; O'Neill, Peggy E.; Njoku, Eni; Jackson, Tom; Colliander, Andreas; Chen, Fan; Burgin, Mariko; Dunbar, Scott; Piepmeier, Jeffrey;
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.
Code of Federal Regulations, 2010 CFR
2010-01-01
... Governing Application of Standards § 868.258 Moisture. Water content in brown rice for processing as... purpose of this paragraph, “approved device” shall include the Motomco Moisture Meter and any other...
Sensing the Moisture Content of Dry Cherries - A Rapid and Nondestructive Method
USDA-ARS?s Scientific Manuscript database
Impedance (Z), and phase angle (') of a parallel-plate capacitor with a single cherry fruit between the plates was measured using a CI meter (Chari’s Impedance meter), at 1 and 9 MHz . Capacitance C, was derived from Z and ', and using the C, ', and Z values of a set of cherries whose moisture cont...
Soil Moisture Estimation Using Hyperspectral SWIR Imagery
NASA Astrophysics Data System (ADS)
Lewis, D.
2007-12-01
The U.S. Geological Survey (USGS) is engaged with the U.S. Department of Agriculture's (USDA) Agricultural Research Service (ARS) and the University of Georgia's National Environmentally Sound Production Agriculture Laboratory (NESPAL) both in Tifton, Georgia, USA, to develop transformations for medium and high resolution remotely sensed images to generate moisture indicators for soil. The Institute for Technology Development (ITD) is located at the Stennis Space Center in southern Mississippi and has developed hyperspectral sensor systems that, when mounted in aircraft, collect electromagnetic reflectance data of the terrain. The sensor suite consists of sensors for three different sections of the electromagnetic spectrum; the Ultra-Violet (UV), Visible/Near InfraRed (VNIR) and Short Wave InfraRed (SWIR). The USDA/ ARS' Southeast Watershed Research Laboratory has probes that measure and record soil moisture. Data taken from the ITD SWIR sensor and the USDA/ARS soil moisture meters were analyzed to study the informatics relationships between SWIR data and measured soil moisture. The geographic locations of 29 soil moisture meters provided by the USDA/ARS are in the vicinity of Tifton, Georgia. Using USGS Digital Ortho Quads (DOQ), flightlines were drawn over the 29 soil moisture meters. The SWIR sensor was installed into an aircraft. The coordinates for the flightlines were also loaded into the navigational system of the aircraft. This airborne platform was used to collect the data over these flightlines. In order to prepare the data set for analysis, standard preprocessing was performed. These standard processes included sensor calibration, spectral subsetting, and atmospheric calibration. All 60 bands of the SWIR data were collected for each line in the image data, 15 bands of which were stripped from the data set leaving 45 bands of information in the wavelength range of 906 to 1705 nanometers. All the image files were calibrated using the regression equations generated by using radiometer data collected over calibration tarps. Regions of Interest (ROI) were drawn over the image data set corresponding with the location of the soil moisture meters. Scripts written in ENVI's Interactive Data Language (IDL) were developed to extract the spectra from each of the processed hyperspectral image data over each soil moisture meter from its corresponding ROI. The informatics relationship between soil moisture and SWIR spectra was identified by using the resulting data set.
Soil Moisture Active Passive Mission L4_SM Data Product Assessment (Version 2 Validated Release)
NASA Technical Reports Server (NTRS)
Reichle, Rolf Helmut; De Lannoy, Gabrielle J. M.; Liu, Qing; Ardizzone, Joseph V.; Chen, Fan; Colliander, Andreas; Conaty, Austin; Crow, Wade; Jackson, Thomas; Kimball, John;
2016-01-01
During the post-launch SMAP calibration and validation (Cal/Val) phase there are two objectives for each science data product team: 1) calibrate, verify, and improve the performance of the science algorithm, and 2) validate the accuracy of the science data product as specified in the science requirements and according to the Cal/Val schedule. This report provides an assessment of the SMAP Level 4 Surface and Root Zone Soil Moisture Passive (L4_SM) product specifically for the product's public Version 2 validated release scheduled for 29 April 2016. The assessment of the Version 2 L4_SM data product includes comparisons of SMAP L4_SM soil moisture estimates with in situ soil moisture observations from core validation sites and sparse networks. The assessment further includes a global evaluation of the internal diagnostics from the ensemble-based data assimilation system that is used to generate the L4_SM product. This evaluation focuses on the statistics of the observation-minus-forecast (O-F) residuals and the analysis increments. Together, the core validation site comparisons and the statistics of the assimilation diagnostics are considered primary validation methodologies for the L4_SM product. Comparisons against in situ measurements from regional-scale sparse networks are considered a secondary validation methodology because such in situ measurements are subject to up-scaling errors from the point-scale to the grid cell scale of the data product. Based on the limited set of core validation sites, the wide geographic range of the sparse network sites, and the global assessment of the assimilation diagnostics, the assessment presented here meets the criteria established by the Committee on Earth Observing Satellites for Stage 2 validation and supports the validated release of the data. An analysis of the time average surface and root zone soil moisture shows that the global pattern of arid and humid regions are captured by the L4_SM estimates. Results from the core validation site comparisons indicate that "Version 2" of the L4_SM data product meets the self-imposed L4_SM accuracy requirement, which is formulated in terms of the ubRMSE: the RMSE (Root Mean Square Error) after removal of the long-term mean difference. The overall ubRMSE of the 3-hourly L4_SM surface soil moisture at the 9 km scale is 0.035 cubic meters per cubic meter requirement. The corresponding ubRMSE for L4_SM root zone soil moisture is 0.024 cubic meters per cubic meter requirement. Both of these metrics are comfortably below the 0.04 cubic meters per cubic meter requirement. The L4_SM estimates are an improvement over estimates from a model-only SMAP Nature Run version 4 (NRv4), which demonstrates the beneficial impact of the SMAP brightness temperature data. L4_SM surface soil moisture estimates are consistently more skillful than NRv4 estimates, although not by a statistically significant margin. The lack of statistical significance is not surprising given the limited data record available to date. Root zone soil moisture estimates from L4_SM and NRv4 have similar skill. Results from comparisons of the L4_SM product to in situ measurements from nearly 400 sparse network sites corroborate the core validation site results. The instantaneous soil moisture and soil temperature analysis increments are within a reasonable range and result in spatially smooth soil moisture analyses. The O-F residuals exhibit only small biases on the order of 1-3 degrees Kelvin between the (re-scaled) SMAP brightness temperature observations and the L4_SM model forecast, which indicates that the assimilation system is largely unbiased. The spatially averaged time series standard deviation of the O-F residuals is 5.9 degrees Kelvin, which reduces to 4.0 degrees Kelvin for the observation-minus-analysis (O-A) residuals, reflecting the impact of the SMAP observations on the L4_SM system. Averaged globally, the time series standard deviation of the normalized O-F residuals is close to unity, which would suggest that the magnitude of the modeled errors approximately reflects that of the actual errors. The assessment report also notes several limitations of the "Version 2" L4_SM data product and science algorithm calibration that will be addressed in future releases. Regionally, the time series standard deviation of the normalized O-F residuals deviates considerably from unity, which indicates that the L4_SM assimilation algorithm either over- or under-estimates the actual errors that are present in the system. Planned improvements include revised land model parameters, revised error parameters for the land model and the assimilated SMAP observations, and revised surface meteorological forcing data for the operational period and underlying climatological data. Moreover, a refined analysis of the impact of SMAP observations will be facilitated by the construction of additional variants of the model-only reference data. Nevertheless, the “Version 2” validated release of the L4_SM product is sufficiently mature and of adequate quality for distribution to and use by the larger science and application communities.
Code of Federal Regulations, 2010 CFR
2010-01-01
... Application of Standards § 868.207 Moisture. Water content in rough rice as determined by an approved device..., “approved device” shall include the Motomco Moisture Meter and any other equipment that is approved by the...
USDA-ARS?s Scientific Manuscript database
Impedance (Z), and phase angle (') of a cylindrical parallel-plate capacitor with dry fruits between the plates was measured using a CI meter (Chari’s Impedance meter), at 1 and 9 MHz . Capacitance, C was derived from Z and ', and using the C, ', and Z values of a set of cherries whose moisture con...
USDA-ARS?s Scientific Manuscript database
Storage bags are common in Africa, Asia and many other less developed countries therefore a grain probing method is well-suited for moisture content (MC) measurement. A low cost meter was developed as part of a USAID project to reduce the post-harvest loss (PHL). The meter measures the MC of maize a...
Peter R. Robichaud; D. S. Gasvoda; Roger D. Hungerford; J. Bilskie; Louise E. Ashmun; J. Reardon
2004-01-01
Duff water content is an important consideration for fire managers when determining favourable timing for prescribed fire ignition. The duff consumption during burning depends largely on the duff water content at the time of ignition. A portable duff moisture meter was developed for real-time water content measurements of nonhomogenous material such as forest duff....
A new tool for fire managers: An electronic duff moisture meter
Peter R. Robichaud; Jim Bilskie
2004-01-01
Prescribed fires are increasingly being used to reduce hazardous fuels, a major objective of the National Fire Plan. Despite advancing technology and ever-improving models, fire managers still find it challenging to determine the right time for a prescribed burn.
Code of Federal Regulations, 2013 CFR
2013-01-01
... 7 Agriculture 7 2013-01-01 2013-01-01 false Moisture. 868.258 Section 868.258 Agriculture... Governing Application of Standards § 868.258 Moisture. Water content in brown rice for processing as... purpose of this paragraph, “approved device” shall include the Motomco Moisture Meter and any other...
Code of Federal Regulations, 2012 CFR
2012-01-01
... 7 Agriculture 7 2012-01-01 2012-01-01 false Moisture. 868.258 Section 868.258 Agriculture... Governing Application of Standards § 868.258 Moisture. Water content in brown rice for processing as... purpose of this paragraph, “approved device” shall include the Motomco Moisture Meter and any other...
Code of Federal Regulations, 2014 CFR
2014-01-01
... 7 Agriculture 7 2014-01-01 2014-01-01 false Moisture. 868.258 Section 868.258 Agriculture... Governing Application of Standards § 868.258 Moisture. Water content in brown rice for processing as... purpose of this paragraph, “approved device” shall include the Motomco Moisture Meter and any other...
Code of Federal Regulations, 2012 CFR
2012-01-01
... 7 Agriculture 7 2012-01-01 2012-01-01 false Moisture. 868.207 Section 868.207 Agriculture... Application of Standards § 868.207 Moisture. Water content in rough rice as determined by an approved device..., “approved device” shall include the Motomco Moisture Meter and any other equipment that is approved by the...
Code of Federal Regulations, 2014 CFR
2014-01-01
... 7 Agriculture 7 2014-01-01 2014-01-01 false Moisture. 868.207 Section 868.207 Agriculture... Application of Standards § 868.207 Moisture. Water content in rough rice as determined by an approved device..., “approved device” shall include the Motomco Moisture Meter and any other equipment that is approved by the...
Code of Federal Regulations, 2013 CFR
2013-01-01
... 7 Agriculture 7 2013-01-01 2013-01-01 false Moisture. 868.207 Section 868.207 Agriculture... Application of Standards § 868.207 Moisture. Water content in rough rice as determined by an approved device..., “approved device” shall include the Motomco Moisture Meter and any other equipment that is approved by the...
New DEMs may stimulate significant advancements in remote sensing of soil moisture
NASA Astrophysics Data System (ADS)
Nolan, Matt; Fatland, Dennis R.
From Napoleon's defeat at Waterloo to increasing corn yields in Kansas to greenhouse gas flux in the Arctic, the importance of soil moisture is endemic to world affairs and merits the considerable attention it receives from the scientific community. This importance can hardly be overstated, though it often goes unstated.Soil moisture is one of the key variables in a variety of broad areas critical to the conduct of societies' economic and political affairs and their well-being; these include the health of agricultural crops, global climate dynamics, military trafficability planning, and hazards such as flooding and forest fires. Unfortunately the in situ measurement of the spatial distribution of soil moisture on a watershed-scale is practically impossible. And despite decades of international effort, a satellite remote sensing technique that can reliably measure soil moisture with a spatial resolution of meters has not yet been identified or implemented. Due to the lack of suitable measurement techniques and, until recently digital elevation models (DEMs), our ability to understand and predict soil moisture dynamics through modeling has largely remained crippled from birth [Grayson and Bloschl, 200l].
Microwave moisture meter for in-shell almonds.
USDA-ARS?s Scientific Manuscript database
Determining almond kernel moisture content while still in the shell is important for both almond growers and processors. A dielectric method was developed for almond kernel moisture determination from dielectric measurements on in-shell almonds at a single microwave frequency. A sample holder was fi...
USDA-ARS?s Scientific Manuscript database
Microwave Sensing provides a means for nondestructively determining the amount of moisture in materials by sensing the dielectric properties of the material. In this study, dielectric properties of Vidalia onions were analyzed for moisture dependence at 13.36 GHz and 23°C for moisture content betwee...
NASA Astrophysics Data System (ADS)
Troch, Peter A.; Niu, Guo-Yue; Gevaert, Anouk; Teuling, Adriaan; Uijlenhoet, Remko; Pasetto, Damiano; Paniconi, Claudio; Putti, Mario
2014-05-01
The Landscape Evolution Observatory (LEO) at Biosphere 2-The University of Arizona consists of three identical, sloping, 333 m2 convergent landscapes inside a 5,000 m2 environmentally controlled facility. These engineered landscapes contain 1-meter depth of basaltic tephra, ground to homogenous loamy sand. Each landscape contains a spatially dense sensor and sampler network capable of resolving meter-scale lateral heterogeneity and sub-meter scale vertical heterogeneity in moisture, energy and carbon states and fluxes. The density of sensors and frequency at which they can be polled allows for data collection at spatial and temporal scales that are impossible in natural field settings. Each ~600 metric ton landscape has load cells embedded into the structure to measure changes in total system mass with 0.05% full-scale repeatability (equivalent to less than 1 cm of precipitation). This facilitates the real time accounting of hydrological partitioning at the hillslope scale. Each hillslope is equipped with an engineered rain system capable of raining at rates between 3 and 45 mm/hr in a range of spatial patterns. We observed the spatial and temporal evolution of the soil moisture content at 496 5-TM Decagon sensors distributed over 5 different depths during a low-intensity long-duration rainfall experiment in February 2013. This presentation will focus on our modeling efforts to reveal subsurface hydraulic heterogeneity required to explain observed rainfall-runoff dynamics at the hillslope scale.
ERT to aid in WSN based early warning system for landslides
NASA Astrophysics Data System (ADS)
T, H.
2017-12-01
Amrita University's landslide monitoring and early warning system using Wireless Sensor Networks (WSN) consists of heterogeneous sensors like rain gauge, moisture sensor, piezometer, geophone, inclinometer, tilt meter etc. The information from the sensors are accurate and limited to that point. In order to monitor a large area, ERT can be used in conjunction with WSN technology. To accomplish the feasibility of ERT in landslide early warning along with WSN technology, we have conducted experiments in Amrita's landslide laboratory setup. The experiment was aimed to simulate landslide, and monitor the changes happening in the soil using moisture sensor and ERT. Simulating moisture values from resistivity measurements to a greater accuracy can help in landslide monitoring for large areas. For accomplishing the same we have adapted two mathematical approaches, 1) Regression analysis between resistivity measurements and actual moisture values from moisture sensor, and 2) Using Waxman Smith model to simulate moisture values from resistivity measurements. The simulated moisture values from Waxman Smith model is compared with the actual moisture values and the Mean Square Error (MSE) is found to be 46.33. Regression curve is drawn for the resistivity vs simulated moisture values from Waxman model, and it is compared with the regression curve of actual model, which is shown in figure-1. From figure-1, it is clear that there the regression curve from actual moisture values and the regression curve from simulated moisture values, follow the similar pattern and there is a small difference between them. Moisture values can be simulated to a greater accuracy using actual regression equation, but the limitation is that, regression curves will differ for different sites and different soils. Regression equation from actual moisture values can be used, if we have conducted experiment in the laboratory for a particular soil sample, otherwise with the knowledge of soil properties, Waxman model can be used to simulate moisture values. The promising results assure that, ERT measurements when used in conjunction with WSN technique, vital paramters triggering landslides like moisture can be simulated for a large area, which will help in providing early warning for large areas.
NASA Astrophysics Data System (ADS)
Sellers, Piers J.; Heiser, Mark D.; Hall, Forrest G.; Verma, Shashi B.; Desjardins, Raymond L.; Schuepp, Peter M.; Ian MacPherson, J.
1997-03-01
It is commonly assumed that biophysically based soil-vegetation-atmosphere transfer (SVAT) models are scale-invariant with respect to the initial boundary conditions of topography, vegetation condition and soil moisture. In practice, SVAT models that have been developed and tested at the local scale (a few meters or a few tens of meters) are applied almost unmodified within general circulation models (GCMs) of the atmosphere, which have grid areas of 50-500 km 2. This study, which draws much of its substantive material from the papers of Sellers et al. (1992c, J. Geophys. Res., 97(D17): 19033-19060) and Sellers et al. (1995, J. Geophys. Res., 100(D12): 25607-25629), explores the validity of doing this. The work makes use of the FIFE-89 data set which was collected over a 2 km × 15 km grassland area in Kansas. The site was characterized by high variability in soil moisture and vegetation condition during the late growing season of 1989. The area also has moderate topography. The 2 km × 15 km 'testbed' area was divided into 68 × 501 pixels of 30 m × 30 m spatial resolution, each of which could be assigned topographic, vegetation condition and soil moisture parameters from satellite and in situ observations gathered in FIFE-89. One or more of these surface fields was area-averaged in a series of simulation runs to determine the impact of using large-area means of these initial or boundary conditions on the area-integrated (aggregated) surface fluxes. The results of the study can be summarized as follows: 1. analyses and some of the simulations indicated that the relationships describing the effects of moderate topography on the surface radiation budget are near-linear and thus largely scale-invariant. The relationships linking the simple ratio vegetation index ( SR), the canopy conductance parameter (▽ F) and the canopy transpiration flux are also near-linear and similarly scale-invariant to first order. Because of this, it appears that simple area-averaging operations can be applied to these fields with relatively little impact on the calculated surface heat flux. 2. The relationships linking surface and root-zone soil wetness to the soil surface and canopy transpiration rates are non-linear. However, simulation results and observations indicate that soil moisture variability decreases significantly as an area dries out, which partially cancels out the effects of these non-linear functions.In conclusion, it appears that simple averages of topographic slope and vegetation parameters can be used to calculate surface energy and heat fluxes over a wide range of spatial scales, from a few meters up to many kilometers at least for grassland sites and areas with moderate topography. Although the relationships between soil moisture and evapotranspiration are non-linear for intermediate soil wetnesses, the dynamics of soil drying act to progressively reduce soil moisture variability and thus the impacts of these non-linearities on the area-averaged surface fluxes. These findings indicate that we may be able to use mean values of topography, vegetation condition and soil moisture to calculate the surface-atmosphere fluxes of energy, heat and moisture at larger length scales, to within an acceptable accuracy for climate modeling work. However, further tests over areas with different vegetation types, soils and more extreme topography are required to improve our confidence in this approach.
Evaluating Metal Probe Meters for Soil Testing.
ERIC Educational Resources Information Center
Hershey, David R.
1992-01-01
Inexpensive metal probe meters that are sold by garden stores can be evaluated by students for their accuracy in measuring soil pH, moisture, fertility, and salinity. The author concludes that the meters are inaccurate and cannot be calibrated in standard units. However, the student evaluations are useful in learning the methods of soil analysis…
NASA Astrophysics Data System (ADS)
Noh, Seong Jin; An, Hyunuk; Kim, Sanghyun
2015-04-01
Soil moisture, a critical factor in hydrologic systems, plays a key role in synthesizing interactions among soil, climate, hydrological response, solute transport and ecosystem dynamics. The spatial and temporal distribution of soil moisture at a hillslope scale is essential for understanding hillslope runoff generation processes. In this study, we implement Monte Carlo simulations in the hillslope scale using a three-dimensional surface-subsurface integrated model (3D model). Numerical simulations are compared with multiple soil moistures which had been measured using TDR(Mini_TRASE) for 22 locations in 2 or 3 depths during a whole year at a hillslope (area: 2100 square meters) located in Bongsunsa Watershed, South Korea. In stochastic simulations via Monte Carlo, uncertainty of the soil parameters and input forcing are considered and model ensembles showing good performance are selected separately for several seasonal periods. The presentation will be focused on the characterization of seasonal variations of model parameters based on simulations with field measurements. In addition, structural limitations of the contemporary modeling method will be discussed.
USDA-ARS?s Scientific Manuscript database
NASA’s Soil Moisture Active Passive (SMAP) Mission is scheduled for launch in early November 2014. The objective of the mission is global mapping of soil moisture and landscape freeze/thaw state. SMAP utilizes L-band radar and radiometer measurements sharing a rotating 6-meter mesh reflector antenna...
Measuring soil moisture near soil surface ... minor differences due to neutron source type
Robert R. Ziemer; Irving Goldberg; Norman A. MacGillivray
1967-01-01
Abstract - Moisture measurements were made in three media--paraffin, water, saturated sand--with four neutron moisture meters, each containing 226-radium-beryllium, 227-actinium-beryllium, 239-plutonium-beryllium, or 241-americium-beryllium neutron sources. Variability in surface detection by the different sources may be due to differences in neutron sources, in...
NASA Technical Reports Server (NTRS)
Kim, E. J.; Walker, J. P.; Panciera, R.; Kalma, J. D.
2006-01-01
Spatially-distributed soil moisture observations have applications spanning a wide range of spatial resolutions from the very local needs of individual farmers to the progressively larger areas of interest to weather forecasters, water resource managers, and global climate modelers. To date, the most promising approach for space-based remote sensing of soil moisture makes use of passive microwave emission radiometers at L-band frequencies (1-2 GHz). Several soil moisture-sensing satellites have been proposed in recent years, with the European Space Agency's Soil Moisture Ocean Salinity (SMOS) mission scheduled to be launched first in a couple years. While such a microwave-based approach has the advantage of essentially allweather operation, satellite size limits spatial resolution to 10's of km. Whether used at this native resolution or in conjunction with some type of downscaling technique to generate soil moisture estimates on a finer-scale grid, the effects of subpixel spatial variability play a critical role. The soil moisture variability is typically affected by factors such as vegetation, topography, surface roughness, and soil texture. Understanding and these factors is the key to achieving accurate soil moisture retrievals at any scale. Indeed, the ability to compensate for these factors ultimately limits the achievable spatial resolution and/or accuracy of the retrieval. Over the last 20 years, a series of airborne campaigns in the USA have supported the development of algorithms for spaceborne soil moisture retrieval. The most important observations involved imagery from passive microwave radiometers. The early campaigns proved that the retrieval worked for larger and larger footprints, up to satellite-scale footprints. These provided the solid basis for proposing the satellite missions. More recent campaigns have explored other aspects such as retrieval performance through greater amounts of vegetation. All of these campaigns featured extensive ground truth collection over a range of grid spacings, to provide a basis for examining the effects of subpixel variability. However, the native footprint size of the airborne L-band radiometers was always a few hundred meters. During the recently completed (November, 2005) National Airborne Field Experiment (NAFE) campaign in Australia, a compact L-band radiometer was deployed on a small aircraft. This new combination permitted routine observations at native resolutions as high as 60 meters, substantially finer than in previous airborne soil moisture campaigns, as well as satellite footprint areal coverage. The radiometer, the Polarimetric L-band Microwave Radiometer (PLMR) performed extremely well and operations included extensive calibration-related observations. Thus, along with the extensive fine-scale ground truth, the NAFE dataset includes all the ingredients for the first scaling studies involving very-high-native resolution soil moisture observations and the effects of vegetation, roughness, etc. A brief overview of the NAFE will be presented, then examples of the airborne observations with resolutions from 60 m to 1 km will be shown, and early results from scaling studies will be discussed.
Plant moisture stress: a portable freezing-point meter compared with the psychrometer
DOE Office of Scientific and Technical Information (OSTI.GOV)
Cary, J.W.; Fisher, H.D.
A small portable instrument for measuring the freezing-point depression of plant tissue has been developed for field use. The instrument is easy to operate and can be constructed from materials costing less than $100. Moisture stress measurements made with the freezing-point meter on a variety of plants were compared with vapor pressure psychrometer measurements. Variation between duplicates in the freezing point averaged 1.2 bars, but differences between stress measurements made with the psychrometer and freezing-point instrument averaged 2.6 bars. 11 references, 5 figures, 2 tables.
Bayesian Hierarchical Modeling for Big Data Fusion in Soil Hydrology
NASA Astrophysics Data System (ADS)
Mohanty, B.; Kathuria, D.; Katzfuss, M.
2016-12-01
Soil moisture datasets from remote sensing (RS) platforms (such as SMOS and SMAP) and reanalysis products from land surface models are typically available on a coarse spatial granularity of several square km. Ground based sensors on the other hand provide observations on a finer spatial scale (meter scale or less) but are sparsely available. Soil moisture is affected by high variability due to complex interactions between geologic, topographic, vegetation and atmospheric variables. Hydrologic processes usually occur at a scale of 1 km or less and therefore spatially ubiquitous and temporally periodic soil moisture products at this scale are required to aid local decision makers in agriculture, weather prediction and reservoir operations. Past literature has largely focused on downscaling RS soil moisture for a small extent of a field or a watershed and hence the applicability of such products has been limited. The present study employs a spatial Bayesian Hierarchical Model (BHM) to derive soil moisture products at a spatial scale of 1 km for the state of Oklahoma by fusing point scale Mesonet data and coarse scale RS data for soil moisture and its auxiliary covariates such as precipitation, topography, soil texture and vegetation. It is seen that the BHM model handles change of support problems easily while performing accurate uncertainty quantification arising from measurement errors and imperfect retrieval algorithms. The computational challenge arising due to the large number of measurements is tackled by utilizing basis function approaches and likelihood approximations. The BHM model can be considered as a complex Bayesian extension of traditional geostatistical prediction methods (such as Kriging) for large datasets in the presence of uncertainties.
Development of in-orbit refocusing mechanism for SpaceEye-1 electro-optical payload
NASA Astrophysics Data System (ADS)
Lee, Minwoo; Kim, Jongun; Chang, Jin-Soo; Kang, Myung-Seok
2016-09-01
SpaceEye-1 earth observation satellite, developed by Satrec Initiative Co. Ltd., is a 300 kg scale spacecraft with high resolution electro-optical payload (EOS-D) which performs 1 m GSD, 12 km swath in low earth orbit. Metering structure of EOS-D is manufactured with Carbon Fiber Reinforced Plastic (CFRP). Due to the moisture emission from CFRP metering structure, this spaceborne electro-optical payload undergoes shrinkage after orbit insertion. The shrinkage of metering structure causes change of the distance between primary and secondary mirror. In order to compensate the moisture shrinkage effect, two types of thermal refocusing mechanism were developed, analyzed and applied to EOS-D. Thermal analysis simulating in-orbit thermal condition and thermo-elastic displacement analysis was conducted to calculate the performance of refocusing mechanism. For each EOS-D telescope, analytical refocusing range (displacement change between primary and secondary mirror) was 2.5 um and 3.6 um. Thus, the refocusing mechanism can compensate the dimensional instability of metering structure caused by moisture emission. Furthermore, modal, static and wavefront error analysis was conducted in order to evaluate natural frequency, structural stability and optical performance. As a result, it can be concluded that the refocusing system of EOS-D payload can perform its function in orbit.
A Portable Solid-State Moisture Meter For Agricultural And Food Products
NASA Astrophysics Data System (ADS)
Bull, C. R.; Stafford, J. V.; Weaving, G. S.
1988-10-01
This paper reports on the development of a small, robust, battery operated near infra-red (NIR) reflectance device, designed for rapid on-farm measurement of the moisture content of forage crops without prior sample preparation. It has potential application to other agricultural or food materials. The instrument is based on two light emitting diodes (LEDs), a germanium detector and a control CMOS single chip microcomputer. The meter has been calibrated to give a direct read out of moisture content for 4 common grass varieties at 3 stages of development. The accuracy of a single point measurement on a grass sample is approximately +/- 6% over a range of 40-80% (wet basis). However, the potential accuracy on a homogeous sample may be as goon as 0.15%.
Predicting Fire Susceptibility in the Forests of Amazonia
NASA Technical Reports Server (NTRS)
Nepstad, Daniel C.; Brown, I. Foster; Setzer, Alberto
2000-01-01
Although fire is the single greatest threat to the ecological integrity of Amazon forests, our ability to predict the occurrence of Amazon forest fires is rudimentary. Part of the difficulty encountered in making such predictions is the remarkable capacity of Amazon forests to tolerate drought by tapping moisture stored in deep soil. These forests can avoid drought-induced leaf shedding by withdrawing moisture to depths of 8 meters and more. Hence, the absorption of deep soil moisture allows these forests to maintain their leaf canopies following droughts of several months duration, thereby maintaining the deep shade and high relative humidity of the forest interior that prevents these ecosystems from burning. But the drought- and fire-avoidance that is conferred by this deep-rooting phenomenon is not unlimited. During successive years of drought, such as those provoked by El Nino episodes, deep soil moisture can be depleted, and drought-induced leaf shedding begins. The goal of this project was to incorporate this knowledge of Amazon forest fire ecology into a predictive model of forest flammability.
NASA Astrophysics Data System (ADS)
Kaleita, A. L.
2013-12-01
Identifying field-scale soil moisture patterns, and quantifying their impact on hydrology and nutrient flux, is currently limited by the time and resources required to do sufficient monitoring. A small number of monitoring locations or occasions may not be sufficient to capture the true spatial and temporal dynamics of these patterns. While process models can help to fill in data gaps, it is often difficult if not impossible to effectively parameterize them at the field and sub-field scale. Thus, empirical methods that can optimize sampling and mapping of soil moisture by using a minimal amount of readily available data may be of significant value. LiDAR is one source of such readily available data. Various topographic indices, including relative elevation, land slope, curvature, and slope aspect are known to influence soil moisture patterns, though the exact nature of that relationship appears to vary from study to study. The objective of this study was to use these data to identify critical sampling locations for mapping soil moisture, and to upscale point measurements at those locations to both a single field-average value, and to a high-resolution pattern map for the field. This study analyzed in-situ soil moisture measurements from the working agricultural field in Story County, Iowa. Theta probe soil moisture measurement values were taken every 50 meters on a 300 x 250 meter grid (~18 acres) during the summer growing seasons of 2004, 2005, 2007, and 2008. The elevation in the field varies by approximately 5 meters and the grid covers six different soil types and a variety of different landscape positions throughout the field. We used self-organizing maps (SOMs) and K-means clustering algorithms to split apart the field study area into distinct categories of similarly-characterized locations. We then used the SOM and clustering metrics to identify locations within each group that were representative of the behavior of that group of locations. We developed a weighted upscaling process to estimate a whole-field average soil moisture content from these few critical samples, and we compared the results to those obtained through the more traditional 'temporal stability' approach. The cluster-based approach was as good as and often better than the temporal stability approach, with the significant advantage that the former does not require any initial period of exhaustive soil moisture monitoring, whereas the latter does. A second objective was to use the classification results of the landscape data to interpolate these sparse critical sampling point data over the whole field. Using what we term 'feature-space interpolation' we were able to re-create a high-resolution soil moisture map for the field using only three measurements, by giving locations with similar landscape characteristics similar soil moisture values. The results showed a small but significant statistical improvement over traditional distance-based interpolation methods, and the resulting patterns also had stronger correlation with end-of-season yield, suggesting this approach may have valuable applications in production agriculture decision-making and assessment.
Using electrical resistance probes for moisture determination in switchgrass windrows
USDA-ARS?s Scientific Manuscript database
Determining moisture levels in windrowed biomass is important for both forage producers and researchers. Energy crops such as switchgrass have been troublesome when using the standard methods set for electrical resistance meters. The objectives of this study were to i) develop the methodologies need...
NASA Astrophysics Data System (ADS)
Naylor, S.; Gustin, A. R.; Ellett, K. M.
2012-12-01
Weather stations that collect reliable, sustained meteorological data sets are becoming more widely distributed because of advances in both instrumentation and data server technology. However, sites collecting soil moisture and soil temperature data remain sparse with even fewer locations where complete meteorological data are collected in conjunction with soil data. Thanks to the advent of sensors that collect continuous in-situ thermal properties data for soils, we have gone a step further and incorporated thermal properties measurements as part of hydrologic instrument arrays in central and northern Indiana. The coupled approach provides insights into the variability of soil thermal conductivity and diffusivity attributable to geologic and climatological controls for various hydrogeologic settings. These data are collected to facilitate the optimization of ground-source heat pumps (GSHPs) in the glaciated Midwest by establishing publicly available data that can be used to parameterize system design models. A network of six monitoring sites was developed in Indiana. Sensors that determine thermal conductivity and diffusivity using radial differential temperature measurements around a heating wire were installed at 1.2 meters below ground surface— a typical depth for horizontal GSHP systems. Each site also includes standard meteorological sensors for calculating reference evapotranspiration following the methods by the Food and Agriculture Organization (FAO) of the United Nations. Vadose zone instrumentation includes time domain reflectometry soil-moisture and temperature sensors installed at 0.3-meter depth intervals down to a 1.8-meter depth, in addition to matric potential sensors at 0.15, 0.3, 0.6, and 1.2 meters. Cores collected at 0.3-meter intervals were analyzed in a laboratory for grain size distribution, bulk density, thermal conductivity, and thermal diffusivity. Our work includes developing methods for calibrating thermal properties sensors based on known standards and comparing measurements from transient line heat source devices. Transform equations have been developed to correct in-situ measurements of thermal conductivity and comparing these results with soil moisture data indicates that thermal conductivity can increase by as much as 25 percent during wetting front propagation. Thermal dryout curves have also been modeled based on laboratory conductivity data collected from core samples to verify field measurements, and alternatively, temperature profile data are used to calibrate near-surface temperature gradient models. We compare data collected across various spatial scales to assess the potential for upscaling near-surface thermal regimes based on available soils data. A long-term goal of the monitoring effort is to establish continuous data sets that determine the effect of climate variability on soil thermal properties such that expected ranges in thermal conductivity can be used to determine optimal ground-coupling loop lengths for GSHP systems.
Use of Satellite Data Assimilation to Infer Land Surface Thermal Inertia
NASA Technical Reports Server (NTRS)
Lapenta, William; McNider, Richard T.; Biazar, Arastoo; Suggs, Ron; Jedlovec, Gary; Dembek, Scott
2002-01-01
There are two important but observationally uncertain parameters in the grid averaged surface energy budgets of mesoscale models - surface moisture availability and thermal heat capacity. A technique has been successfully developed for assimilating Geostationary Operational Environmental Satellite (GOES) skin temperature tendencies during the mid-morning time frame to improve specification of surface moisture. In a new application of the technique, the use of satellite skin temperature tendencies in early evening is explored to improve specification of the surface thermal heat capacity. Together, these two satellite assimilation constraints have been shown to significantly improve the characterization of the surface energy budget of a mesoscale model on fine spatial scales. The GOES assimilation without the adjusted heat capacity was run operationally during the International H2O Project on a 12-km grid. This paper presents the results obtained when using both the moisture availability and heat capacity retrievals in concert. Preliminary results indicate that retrieved moisture availability alone improved the verification statistics of 2-meter temperature and dew point forecasts. Results from the 1.5 month long study period using the bulk heat capacity will be presented at the meeting.
Bates-Jensen, Barbara M; McCreath, Heather E; Patlan, Anabel
2017-05-01
We examined the relationship between subepidermal moisture measured using surface electrical capacitance and visual skin assessment of pressure ulcers at the trunk location (sacral, ischial tuberosities) in 417 nursing home residents residing in 19 facilities. Participants were on average older (mean age of 77 years), 58% were female, over half were ethnic minorities (29% African American, 12% Asian American, and 21% Hispanic), and at risk for pressure ulcers (mean score for Braden Scale for Predicting Pressure Ulcer Risk of 15.6). Concurrent visual assessments and subepidermal moisture were obtained at the sacrum and right and left ischium weekly for 16 weeks. Visual assessment was categorized as normal, erythema, stage 1 pressure ulcer, Deep Tissue Injury or stage 2+ pressure ulcer using the National Pressure Ulcer Advisory Panel 2009 classification system. Incidence of any skin damage was 52%. Subepidermal moisture was measured with a dermal phase meter where higher readings indicate greater moisture (range: 0-70 tissue dielectric constant), with values increasing significantly with the presence of skin damage. Elevated subepidermal moisture values co-occurred with concurrent skin damage in generalized multinomial logistic models (to control for repeated observations) at the sacrum, adjusting for age and risk. Higher subepidermal moisture values were associated with visual damage 1 week later using similar models. Threshold values for subepidermal moisture were compared to visual ratings to predict skin damage 1 week later. Subepidermal moisture of 39 tissue dielectric constant units predicted 41% of future skin damage while visual ratings predicted 27%. Thus, this method of detecting early skin damage holds promise for clinicians, especially as it is objective and equally valid for all groups of patients. © 2017 by the Wound Healing Society.
Okamoto, A; Miyachi, H; Tanaka, K; Chikazu, D; Miyaoka, H
2016-12-01
Patients with schizophrenia are most commonly treated with antipsychotic medications, often with the addition of anxiolytics. This study used an oral moisture meter to evaluate xerostomia in patients with schizophrenia taking typical and atypical antipsychotics, anxiolytics and non-psychotropic medications. Patients diagnosed with schizophrenia according to ICD-10 criteria in the Department of Psychiatry, Kitasato University East, and affiliated hospitals were studied. All patients were on psychotropic medications. Patients with diseases associated with xerostomia, such as Sjögren's syndrome I, were excluded. A total of 127 patients were enrolled. Mean oral moisture was 27·81 ± 2·27% (normal, ≥30·0%). A significant association was observed between objective oral moisture and the subjective sense of dry mouth. Multivariate analysis revealed a negative correlation between the number of antipsychotics and, especially, anxiolytics, and the degree of oral moisture. Drug dosages themselves were not significantly correlated with dry mouth. These findings suggest that objective oral moisture measurements show decreased moisture in patients on these medications and that the degree of moisture shows a greater negative correlation with the number, as opposed to the dosages, of psychotropic drugs administered. When patients with schizophrenia visit a dental clinic, it is important for the dentist to accurately assess the degree of oral moisture and to determine the medications being taken. Based on these findings of the association of polypharmacy with xerostomia, dentists are encouraged to inform the psychiatrist of the need to actively manage patients' xerostomia. © 2016 John Wiley & Sons Ltd.
Overview of the NASA soil moisture active/passive mission
USDA-ARS?s Scientific Manuscript database
The NASA Soil Moisture Active Passive (SMAP) Mission is currently in design Phase C and scheduled for launch in October 2014. Its mission concept is based on combined L-band radar and radiometry measurements obtained from a shared, rotating 6-meter antennae. These measurements will be used to retrie...
NASA Astrophysics Data System (ADS)
Li, Y.; Epifanio, C.
2017-12-01
In numerical prediction models, the interaction between the Earth's surface and the atmosphere is typically accounted for in terms of surface layer parameterizations, whose main job is to specify turbulent fluxes of heat, moisture and momentum across the lower boundary of the model domain. In the case of a domain with complex geometry, implementing the flux conditions (particularly the tensor stress condition) at the boundary can be somewhat subtle, and there has been a notable history of confusion in the CFD community over how to formulate and impose such conditions generally. In the atmospheric case, modelers have largely been able to avoid these complications, at least until recently, by assuming that the terrain resolved at typical model resolutions is fairly gentle, in the sense of having relatively shallow slopes. This in turn allows the flux conditions to be imposed as if the lower boundary were essentially flat. Unfortunately, while this flat-boundary assumption is acceptable for coarse resolutions, as grids become more refined and the geometry of the resolved terrain becomes more complex, the appproach is less justified. With this in mind, the goal of our present study is to explore the implementation and usage of the full, unapproximated version of the turbulent flux/stress conditions in atmospheric models, thus taking full account of the complex geometry of the resolved terrain. We propose to implement the conditions using a semi-idealized model developed by Epifanio (2007), in which the discretized boundary conditions are reduced to a large, sparse-matrix problem. The emphasis will be on fluxes of momentum, as the tensor nature of this flux makes the associated stress condition more difficult to impose, although the flux conditions for heat and moisture will be considered as well. With the resulotion of 90 meters, some of the results show that the typical differences between flat-boundary cases and full/stress cases are on the order of 10%, with extreme cases reaching as high as 30% based on typical disturbance wind speeds. And this difference dropping by a factor of six between grid spacings of 90 meters and 240 meters. It would thus appear that the need to apply the full stress condition is limited to relatively high-resolution modeling, with grid spacings on the order of 250 meters or less.
Meter scale variation in shrub dominance and soil moisture structure Arctic arthropod communities
Hansen, Oskar Liset Pryds; Bowden, Joseph J.; Treier, Urs A.; Normand, Signe; Høye, Toke
2016-01-01
The Arctic is warming at twice the rate of the rest of the world. This impacts Arctic species both directly, through increased temperatures, and indirectly, through structural changes in their habitats. Species are expected to exhibit idiosyncratic responses to structural change, which calls for detailed investigations at the species and community level. Here, we investigate how arthropod assemblages of spiders and beetles respond to variation in habitat structure at small spatial scales. We sampled transitions in shrub dominance and soil moisture between three different habitats (fen, dwarf shrub heath, and tall shrub tundra) at three different sites along a fjord gradient in southwest Greenland, using yellow pitfall cups. We identified 2,547 individuals belonging to 47 species. We used species richness estimation, indicator species analysis and latent variable modeling to examine differences in arthropod community structure in response to habitat variation at local (within site) and regional scales (between sites). We estimated species responses to the environment by fitting species-specific generalized linear models with environmental covariates. Species assemblages were segregated at the habitat and site level. Each habitat hosted significant indicator species, and species richness and diversity were significantly lower in fen habitats. Assemblage patterns were significantly linked to changes in soil moisture and vegetation height, as well as geographic location. We show that meter-scale variation among habitats affects arthropod community structure, supporting the notion that the Arctic tundra is a heterogeneous environment. To gain sufficient insight into temporal biodiversity change, we require studies of species distributions detailing species habitat preferences. PMID:27478709
The Soil Moisture Active and Passive (SMAP) Mission
NASA Technical Reports Server (NTRS)
Entekhabi, Dara; Nijoku, Eni G.; ONeill, Peggy E.; Kellogg, Kent H.; Crow, Wade T.; Edelstein, Wendy N.; Entin, Jared K.; Goodman, Shawn D.; Jackson, Thomas J.; Johnson, Joel;
2009-01-01
The Soil Moisture Active and Passive (SMAP) Mission is one of the first Earth observation satellites being developed by NASA in response to the National Research Council s Decadal Survey. SMAP will make global measurements of the moisture present at Earth's land surface and will distinguish frozen from thawed land surfaces. Direct observations of soil moisture and freeze/thaw state from space will allow significantly improved estimates of water, energy and carbon transfers between land and atmosphere. Soil moisture measurements are also of great importance in assessing flooding and monitoring drought. SMAP observations can help mitigate these natural hazards, resulting in potentially great economic and social benefits. SMAP soil moisture and freeze/thaw timing observations will also reduce a major uncertainty in quantifying the global carbon balance by helping to resolve an apparent missing carbon sink on land over the boreal latitudes. The SMAP mission concept would utilize an L-band radar and radiometer. These instruments will share a rotating 6-meter mesh reflector antenna to provide high-resolution and high-accuracy global maps of soil moisture and freeze/thaw state every two to three days. The SMAP instruments provide direct measurements of surface conditions. In addition, the SMAP project will use these observations with advanced modeling and data assimilation to provide deeper root-zone soil moisture and estimates of land surface-atmosphere exchanges of water, energy and carbon. SMAP is scheduled for a 2014 launch date
On-irrigator pasture soil moisture sensor
NASA Astrophysics Data System (ADS)
Eng-Choon Tan, Adrian; Richards, Sean; Platt, Ian; Woodhead, Ian
2017-02-01
In this paper, we presented the development of a proximal soil moisture sensor that measured the soil moisture content of dairy pasture directly from the boom of an irrigator. The proposed sensor was capable of soil moisture measurements at an accuracy of ±5% volumetric moisture content, and at meter scale ground area resolutions. The sensor adopted techniques from the ultra-wideband radar to enable measurements of ground reflection at resolutions that are smaller than the antenna beamwidth of the sensor. An experimental prototype was developed for field measurements. Extensive field measurements using the developed prototype were conducted on grass pasture at different ground conditions to validate the accuracy of the sensor in performing soil moisture measurements.
1km Soil Moisture from Downsampled Sentinel-1 SAR Data: Harnessing Assets and Overcoming Obstacles.
NASA Astrophysics Data System (ADS)
Bauer-Marschallinger, Bernhard; Cao, Senmao; Schaufler, Stefan; Paulik, Christoph; Naeimi, Vahid; Wagner, Wolfgang
2017-04-01
Radars onboard Earth observing satellites allow estimating Surface Soil Moisture (SSM) regularly and globally. The use of coarse-scale measurements from active or passive radars for SSM retrieval is well established and in operational use. Thanks to the Sentinel-1 mission, launched in 2014 and deploying Synthetic Aperture Radars (SAR), high-resolution radar imagery is routinely available at the scale of 20 meters, with a high revisit frequency of 3-6 days and with unprecedented radiometric accuracy. However, the direct exploitation of high-resolution SAR data for SSM retrieval is complicated by several problems: Small-scaled contributions to the radar backscatter from individual ground features often obscure the soil moisture signal, rendering common algorithms insensitive to SSM. Furthermore, the influence of vegetation dynamics on the radar signal is less understood than in the coarse-scale case, leading to biases during the vegetation period. Finally, the large data volumes of high-resolution remote sensing data present a great load on hardware systems. Consequently, a spatial resampling of the high-resolution SAR data to a 500 meters sampling is done, allowing the exploitation of information at 10 meter sampling, but reducing effectively the inherent uncertainties. The thereof retrieved 1km SSM product aims to describe the soil moisture dynamics at medium scale with high quality. We adopted the TU-Wien Change Detection algorithm to the Sentinel-1 data, which was already successfully used for retrieving SSM from ERS-1/2 and Envisat-ASAR observations. The adoption entails a new method for SAR image resampling, including a masking for pixels that do not carry soil moisture signals, preventing them to spread during downsampling. Furthermore, the observation angle between the radar sensors and the ground is treated in a different way, as Sentinel-1 sensors observe from fixed orbit paths (in contrast to other radar sensors). Here, a regression model is developed that successfully estimates the dependency of radar backscatter to observation angle with statistical parameters from the Sentinel-1 SAR time series archive. We present the Sentinel-1 1km-SSM product generated by the adopted change detection algorithm. The dataset covers the European continent and holds data from October 2014 ongoing. In addition to a validation of the SSM product, the statistical SAR parameters used during SSM retrieval are examined.
Direct observations of rock moisture, a hidden component of the hydrologic cycle.
Rempe, Daniella M; Dietrich, William E
2018-03-13
Recent theory and field observations suggest that a systematically varying weathering zone, that can be tens of meters thick, commonly develops in the bedrock underlying hillslopes. Weathering turns otherwise poorly conductive bedrock into a dynamic water storage reservoir. Infiltrating precipitation typically will pass through unsaturated weathered bedrock before reaching groundwater and running off to streams. This invisible and difficult to access unsaturated zone is virtually unexplored compared with the surface soil mantle. We have proposed the term "rock moisture" to describe the exchangeable water stored in the unsaturated zone in weathered bedrock, purposely choosing a term parallel to, but distinct from, soil moisture, because weathered bedrock is a distinctly different material that is distributed across landscapes independently of soil thickness. Here, we report a multiyear intensive campaign of quantifying rock moisture across a hillslope underlain by a thick weathered bedrock zone using repeat neutron probe measurements in a suite of boreholes. Rock moisture storage accumulates in the wet season, reaches a characteristic upper value, and rapidly passes any additional rainfall downward to groundwater. Hence, rock moisture storage mediates the initiation and magnitude of recharge and runoff. In the dry season, rock moisture storage is gradually depleted by trees for transpiration, leading to a common lower value at the end of the dry season. Up to 27% of the annual rainfall is seasonally stored as rock moisture. Significant rock moisture storage is likely common, and yet it is missing from hydrologic and land-surface models used to predict regional and global climate.
Federal Register 2010, 2011, 2012, 2013, 2014
2012-08-30
...'' (Russian Federation); R75, ``Heat meters'' (Germany); R80, ``Road and rail tankers with level gauging...)'' (Russian Federation); R92, ``Wood moisture meters--Verification methods and equipment: general provisions... liquids other than water'' (Switzerland); R124, ``Refractometers for the measurement of the sugar content...
NASA Astrophysics Data System (ADS)
Harmon, T. C.; Fernandez Bou, A. S.; Dierick, D.; Oberbauer, S. F.; Schwendenmann, L.; Swanson, A. C.; Zelikova, T. J.
2016-12-01
This project focuses on the role of leaf cutter ants (LCA) Atta cepholotes in carbon cycling in neotropical wet forests. LCA are abundant in these forests and workers cut and carry vegetation fragments to their nests, where symbiotic fungi break down the plant material and produce the fungal hyphae on which the ants feed. LCA are the dominant herbivores in tropical forest ecosystems, removing 10-50% of vegetation annually. Their nests can achieve large sizes, extending several meters belowground and covering 50 square meters or more of the forest floor. We monitored soil moisture, temperature, and soil CO2 concentrations continuously in nest and control sites at La Selva Biological Station, Costa Rica. Intermittently, we also assessed soil respiration and LCA nest vent fluxes. Observed soil CO2 concentrations varied markedly with soil moisture conditions, ranging from a few thousand to over 60,000 ppm(v). Accordingly, soil CO2 surface efflux varied temporally by an order of magnitude or more (typical range 0.5 to 5 mmol CO2 m-2 s-1) for the same location as a consequence of soil moisture fluctuations. LCA nest vents equivalent CO2 efflux rates (accounting for vent diameter) can be substantially greater than soil surface values, with observed values ranging from about 1 to 50 mmol m-2 s-1 (it is worth noting that correcting for vent diameters yields equivalent CO2 efflux rates greater than 1000 mmol m-2 s-1). Similar to the soil surface efflux, vent efflux varied temporally by factors of 3 or more, suggesting a potential link between the vent productivity and nest activity, moisture content of surrounding soil, and atmospheric conditions (e.g., air temperature, wind). Using a soil model (Hydrus-1D) to account for unsaturated flow, heat transfer, CO2 production and diffusive transport, we captured moisture and temperature dynamics and the order of magnitude of observed CO2 concentration. Modelled surface fluxes also agreed well with observed soil surface CO2 efflux. These results contribute to our understanding of CO2 production and transport in tropical soils, and the role played by the LCA in the soil carbon cycle.
Proceedings of the 66th National Conference on Weights and Measures, 1981
NASA Astrophysics Data System (ADS)
Wollin, H. F.; Barbrow, L. E.; Heffernan, A. P.
1981-12-01
Major issues discussed included measurement science education, enforcement uniformly, national type approval, inch pound and metric labeling provisions, new design and performance requirements for weighing and measuring technology, metric conversion of retail gasoline dispensers, weights and measures program evaluation studies of model State laws and regulations and their adoption by citation or other means by State and local jurisdictions, and report of States conducting grain moisture meter testing programs.
Measuring soil moisture near soil surface...minor differences due to neutron source type
Robert R. Ziemer; Irving Goldberg; Norman A. MacGillivray
1967-01-01
Moisture measurements were made in three media?paraffin, water, saturated sand?with four neutron miusture meters, each containing 226-radium-beryllium, 227-actinium-beryllium, 238-plutonium-beryllium, or 241-americium-beryllium neutron sources. Variability in surface detection by the different sources may be due to differences in neutron sources, in length of source,...
A LOW-COST IMPEDANCE METER FOR SENSING THE MOISTURE CONTENT OF IN-SHELL PEANUTS
USDA-ARS?s Scientific Manuscript database
A low cost impedance meter developed at the National Peanut Research Laboratory described here was used to generate RF signals at frequencies of 1, 5 and 9 MHz. The RF signals were applied to a parallel-plate capacitor holding a sample of peanuts and the capacitance (C), phase angle (') and impedanc...
Moisture Determination of Nuts and Dry Fruits using a Capacitance Sensor
USDA-ARS?s Scientific Manuscript database
Impedance (Z), and phase angle (') of a cylindrical parallel-plate capacitor with in-shell peanuts between the plates was measured earlier, using a CI meter (Chari’s Impedance meter), at 1 and 5 MHz . Capacitance C, was derived from Z and ', and using the C, ', and Z values of a set of peanuts whos...
1983-09-28
approximately isokinetic sampling conditions. The blower motor for the hi-vol was separated from the filter holder unit by a one- meter length of flexible...bridge bulkhead about 15 m above sea level and within 3 meters of the ARCAS inlet. The flow rate through the 20 cm x 25 cm glass fiber filters was...materials, atmospheric pressure, soil moisture and vegetative cover (Larson and Bressan, 1980). Radon concentrations measured a few meters above
Towards Novel Techniques for Root Phenotyping Using GPR
NASA Astrophysics Data System (ADS)
Kobylinski, C.; Neely, H.; Everett, M. E.; Hays, D. B.; Lewis, K.
2017-12-01
The ability to phenotype roots in situ would provide information for carbon sequestration potential through increased root mass, possible water-seeking strategies by plants, and generate data for plant breeders. One technique for root phenotyping is to measure differences in soil moisture and use this data to infer root presence or absence. Current technologies for soil moisture detection include electromagnetic induction and neutron moisture meters; however, ground penetrating radar (GPR) has been suggested to monitor root phenotypes. The objective of this study is to use GPR as a novel technique for detecting roots and classifying root phenotypes based on the detection of differences in dielectric permittivity in response to changes in soil water content. The study will be conducted at two sites in Texas: Thrall, TX (Burleson clay) and Lubbock, TX (Olton clay loam). Three root types will be investigated: fibrous (grain sorghum), tap root (cowpea), and mixed (9-species). Data will be collected along a 10 m linear transect in each plot with a PulseEkko GPR bi-static unit operating at a radio frequency of 500 MHz. Additionally, an EM38-MK2 survey will be performed along each transect. Soil surface moisture readings will be collected with a ML3 ThetaProbe soil moisture sensor and a neutron moisture meter will be used to obtain soil moisture measurements down to 1.2 m. Measurements will be collected every two weeks throughout the growing season. Soil properties including particle size distribution, cation exchange capacity, and bulk density will also be measured. GPR's ability to distinguish root types across soils will be assessed.
Testing the regionalization of a SVAT model for a region with high observation density
NASA Astrophysics Data System (ADS)
Eiermann, Sven; Thies, Boris; Bendix, Jörg
2014-05-01
The variable soil moisture is an important quantity in weather and climate investigations, because it has an essential influence on the energy exchange between the land surface and the atmosphere. However the recording of soil moisture in high spatio-temporal resolution is problematic. The planned Tandem-L mission of the German Aerospace Center (DLR) with an innovative L-band radar on board provides the opportunity to get daily soil moisture data at a spatial resolution of 50 meters. Within the Helmholtz Alliance Remote Sensing and Earth System Dynamics this data is planned to be used to regionalize a Soil Vegetation Atmosphere Transfer Model, in order to analyze the energy flux and the gas exchange and to improve the prediction of the water exchange between soil, vegetation and atmosphere. As investigation areas selected regions of the TERENO (TERrestrial ENviromental Observatoria) test sites and, later on, a region in South Ecuador will be used, for which data for the model initialization and validation are available. The reason for testing the method for the TERENO test sites first is the good data basis as a result of the already established high observation density there. The poster will present the methods being used for the model adaptation for the TERENO test sites and discuss the improvements achieved by these methods.
Where did my wifi go? Measuring soil moisture using wifi signal strength
NASA Astrophysics Data System (ADS)
Hut, Rolf; de Jeu, Richard
2015-04-01
Soil moisture is tricky to measure. Currently soil moisture is measured at small footprints using probes and other field devices, or at large footprints using satellites. Promising developments in measuring soil moisture are using fiber optic cables for measurements along a line, or using cosmos rays for field scale measurements. In this demonstration we present a low cost alternative to measure soil moisture at footprints of a few square meters. We use a wifi hotspot and a wifi dongle, both mounted in a cantenna for beam forming. We aim the hotspot on a piece of soil and put the dongle in the path of the reflection. By logging the signal strength of the wifi netwerk, we have a proxy for soil moisture. A first proof of concept is presented.
An example of nighttime drying in the Santa Ana mountains
Michael A. Fosberg; Mark J. Schroeder
1965-01-01
Humidity patterns near the 500- to 1,000-meter level on California's coastal mountains often show an anomolous decrease in the moisture content at night and early morning. A study in the Santa Ana mountains suggests that nighttime downslope winds provide the most satisfactory explanation for the decrease in moisture because of their effect on the marine layer....
Direct observations of rock moisture, a hidden component of the hydrologic cycle
NASA Astrophysics Data System (ADS)
Rempe, Daniella M.; Dietrich, William E.
2018-03-01
Recent theory and field observations suggest that a systematically varying weathering zone, that can be tens of meters thick, commonly develops in the bedrock underlying hillslopes. Weathering turns otherwise poorly conductive bedrock into a dynamic water storage reservoir. Infiltrating precipitation typically will pass through unsaturated weathered bedrock before reaching groundwater and running off to streams. This invisible and difficult to access unsaturated zone is virtually unexplored compared with the surface soil mantle. We have proposed the term “rock moisture” to describe the exchangeable water stored in the unsaturated zone in weathered bedrock, purposely choosing a term parallel to, but distinct from, soil moisture, because weathered bedrock is a distinctly different material that is distributed across landscapes independently of soil thickness. Here, we report a multiyear intensive campaign of quantifying rock moisture across a hillslope underlain by a thick weathered bedrock zone using repeat neutron probe measurements in a suite of boreholes. Rock moisture storage accumulates in the wet season, reaches a characteristic upper value, and rapidly passes any additional rainfall downward to groundwater. Hence, rock moisture storage mediates the initiation and magnitude of recharge and runoff. In the dry season, rock moisture storage is gradually depleted by trees for transpiration, leading to a common lower value at the end of the dry season. Up to 27% of the annual rainfall is seasonally stored as rock moisture. Significant rock moisture storage is likely common, and yet it is missing from hydrologic and land-surface models used to predict regional and global climate.
AGE Bio Diesel Emissions Evaluation
2003-12-01
329 44 788 Vratd) Standard Meter Volume, m° 1.336 1.214 1.255 1,268 am Average Sampling Rate, dscfm 0786 0 714 0 739 0 746 P, Stack Pressure, inches...sat) Moisture (at saturation), % by volume 70864 248 8 36676 V.d Standard Water Vapor Volume, ft’ 2.198 1 624 1 911 1-B• Dry Mole Fraction 0 941 0946...Clock Meter Dry Gas Sample Time, Volume, Rotameter Meter Temp., Vacuum, Probe Time (min) (24-hr) (liter) Setting (OF) (in.Hg) jTpr, OF /o5 f / 52 / 6 14V_
Interaction Between Ecohydrologic Dynamics and Microtopographic Variability Under Climate Change
NASA Astrophysics Data System (ADS)
Le, Phong V. V.; Kumar, Praveen
2017-10-01
Vegetation acclimation resulting from elevated atmospheric CO2 concentration, along with response to increased temperature and altered rainfall pattern, is expected to result in emergent behavior in ecologic and hydrologic functions. We hypothesize that microtopographic variability, which are landscape features typically of the length scale of the order of meters, such as topographic depressions, will play an important role in determining this dynamics by altering the persistence and variability of moisture. To investigate these emergent ecohydrologic dynamics, we develop a modeling framework, Dhara, which explicitly incorporates the control of microtopographic variability on vegetation, moisture, and energy dynamics. The intensive computational demand from such a modeling framework that allows coupling of multilayer modeling of the soil-vegetation continuum with 3-D surface-subsurface flow processes is addressed using hybrid CPU-GPU parallel computing framework. The study is performed for different climate change scenarios for an intensively managed agricultural landscape in central Illinois, USA, which is dominated by row-crop agriculture, primarily soybean (Glycine max) and maize (Zea mays). We show that rising CO2 concentration will decrease evapotranspiration, thus increasing soil moisture and surface water ponding in topographic depressions. However, increased atmospheric demand from higher air temperature overcomes this conservative behavior resulting in a net increase of evapotranspiration, leading to reduction in both soil moisture storage and persistence of ponding. These results shed light on the linkage between vegetation acclimation under climate change and microtopography variability controls on ecohydrologic processes.
Temperature changes in an initially frozen wood chip pile.
George R. Sampson; Jenifer H. McBeath
1987-01-01
White spruce trees and tops were chipped and placed in a pile near Fairbanks, Alaska, in February 1983. The pile was 6 meters in diameter and 6 meters high in a cylindrical shape. Thermocouples were placed at 25 locations within the pile so that temperatures could be tracked over time. Gypsum blocks were placed at 10 locations to determine changes in moisture content....
[Development and test of a wheat chlorophyll, nitrogen and water content meter].
Yu, Bo; Sun, Ming; Han, Shu-Qing; Xia, Jin-Wen
2011-08-01
A portable meter was developed which can detect chlorophyll, nitrogen and moisture content of wheat leaf simultaneously, and can supply enough data for guiding fertilization and irrigation. This meter is composed of light path and electronic circuit. And this meter uses 660, 940 and 1450 nm LED together with narrow band filters as the active light source. The hardware circuit consists of micro-controller, LED drive circuit, detector, communication circuit, keyboard and LCD circuit. The meter was tested in the field and performed well with good repeatability and accuracy. The relative errors of chlorophyll and nitrogen test were about 10%, relative error for water content was 4%. The coefficients of variation of the three indices were all below 1.5%. All of these prove that the meter can be applied under the field condition to guide the wheat production.
Gonçalves, Giovana M; Brianezi, Gabrielli; Miot, Hélio Amante
2017-01-01
The pH of the skin is slightly acidic (4.6 to 5.8) which is important for appropriate antibacterial, antifungal, constitution of barrier function, as well as structuring and maturation of the stratum corneum. This study aimed to evaluate the pH of the main commercial moisturizers and liquid soaps in Brazil. Thus, pH of the products was quantified by pH meter in three measurements. A total of 38 moisturizers and six commercial liquid soaps were evaluated. Mean pH of 63% and 50% of the moisturizing and liquid soaps presented results above 5.5, disfavoring repair, function, and synthesis of dermal barrier.
Soil moisture profile variability in land-vegetation- atmosphere continuum
NASA Astrophysics Data System (ADS)
Wu, Wanru
Soil moisture is of critical importance to the physical processes governing energy and water exchanges at the land-air boundary. With respect to the exchange of water mass, soil moisture controls the response of the land surface to atmospheric forcing and determines the partitioning of precipitation into infiltration and runoff. Meanwhile, the soil acts as a reservoir for the storage of liquid water and slow release of water vapor into the atmosphere. The major motivation of the study is that the soil moisture profile is thought to make a substantial contribution to the climate variability through two-way interactions between the land-surface and the atmosphere in the coupled ocean-atmosphere-land climate system. The characteristics of soil moisture variability with soil depth may be important in affecting the atmosphere. The natural variability of soil moisture profile is demonstrated using observations. The 16-year field observational data of soil moisture with 11-layer (top 2.0 meters) measured soil depths over Illinois are analyzed and used to identify and quantify the soil moisture profile variability, where the atmospheric forcing (precipitation) anomaly propagates down through the land-branch of the hydrological cycle with amplitude damping, phase shift, and increasing persistence. Detailed statistical data analyses, which include application of the periodogram method, the wavelet method and the band-pass filter, are made of the variations of soil moisture profile and concurrently measured precipitation for comparison. Cross-spectral analysis is performed to obtain the coherence pattern and phase correlation of two time series for phase shift and amplitude damping calculation. A composite of the drought events during this time period is analyzed and compared with the normal (non-drought) case. A multi-layer land surface model is applied for modeling the soil moisture profile variability characteristics and investigating the underlying mechanisms. Numerical experiments are conducted to examine the impacts of some potential controlling factors, which include atmospheric forcing (periodic and pulse) at the upper boundary, the initial soil moisture profile, the relative root abundance and the soil texture, on the variability of soil moisture profile and the corresponding evapotranspiration. Similar statistical data analyses are performed for the experimental data. Observations from the First International Satellite Land Surface Climatological Project (ISLSCP) Field Experiment (FIFE) are analyzed and used for the testing of model. The integration of the observational and modeling approaches makes it possible to better understand the mechanisms by which the soil moisture profile variability is generated with phase shift, fluctuation amplitude damping and low-pass frequency filtering with soil depth, to improve the strategies of parameterizations in land surface schemes, and furthermore, to assess its contribution to climate variability.
NASA Astrophysics Data System (ADS)
Moreno, H. A.; Basara, J. B.; Thompson, E.; Bertrand, D.; Johnston, C. S.
2017-12-01
Soil moisture measurements using satellite information can benefit from a land data assimilation model Goddard Earth Observing System (GEOS-5) and land data assimilation system (LDAS) to improve the representation of fine-scale dynamics and variability. This work presents some advances to understand the predictive skill of L4-SM product across different land-cover types, topography and precipitation totals, by using a dense network of multi-level soil moisture sensors (i.e. Mesonet and Micronet) in Oklahoma. 130 soil moisture stations are used across different precipitation gradients (i.e. arid vs wet), land cover (e.g. forest, shrubland, grasses, crops), elevation (low, mid and high) and slope to assess the improvements by the L4_SM product relative to the raw SMAP L-band brightness temperatures. The comparisons are conducted between July 2015 and July 2016 at the daily time scale. Results show the highest L4-SM overestimations occur in pastures and cultivated crops, during the rainy season and at higher elevation lands (over 800 meters asl). The smallest errors occur in low elevation lands, low rainfall and developed lands. Forested area's soil moisture biases lie in between pastures (max biases) and low intensity/developed lands (min biases). Fine scale assessment of L4-SM should help GEOS-5 and LDAS teams refine model parameters in light of observed differences and improve assimilation techniques in light of land-cover, topography and precipitation regime. Additionally, regional decision makers could have a framework to weight the utility of this product for water resources applications.
Gonçalves, Giovana M; Brianezi, Gabrielli; Miot, Hélio Amante
2017-01-01
The pH of the skin is slightly acidic (4.6 to 5.8) which is important for appropriate antibacterial, antifungal, constitution of barrier function, as well as structuring and maturation of the stratum corneum. This study aimed to evaluate the pH of the main commercial moisturizers and liquid soaps in Brazil. Thus, pH of the products was quantified by pH meter in three measurements. A total of 38 moisturizers and six commercial liquid soaps were evaluated. Mean pH of 63% and 50% of the moisturizing and liquid soaps presented results above 5.5, disfavoring repair, function, and synthesis of dermal barrier. PMID:29166523
Influence of boundary-layer dynamics on pollen dispersion and viability
NASA Astrophysics Data System (ADS)
Arritt, Raymond W.; Viner, Brian J.; Westgate, Mark E.
2013-04-01
Adoption of genetically modified (GM) crops has raised concerns that GM traits can accidentally cross into conventional crops or wild relatives through the transport of wind-borne pollen. In order to evaluate this risk it is necessary to account both for dispersion of the pollen grains and environmental influences on pollen viability. The Lagrangian approach is suited to this problem because it allows tracking the environmental temperature and moisture that pollen grains experience as they travel. Taking advantage of this capability we have combined a high-resolution version of the WRF meteorological model with a Lagrangian particle dispersion model to predict maize pollen dispersion and viability. WRF is used to obtain fields of wind, turbulence kinetic energy, temperature, and humidity which are then used as input to the Lagrangian dispersion model. The dispersion model in turn predicts transport of a statistical sample of a pollen cloud from source plants to receptors. We also use the three-dimensional temperature and moisture fields from WRF to diagnose changes in moisture content of the pollen grains and consequent loss of viability. Results show that turbulent motions in the convective boundary layer counteract the large terminal velocity of maize pollen grains and lift them to heights of several hundred meters, so that they can be transported long distances before settling to the ground. We also found that pollen lifted into the upper part of the boundary layer remains more viable than has been inferred using surface observations of temperature and humidity. This is attributed to the thermal and moisture structure that typifies the daytime atmospheric boundary layer, producing an environment of low vapor pressure deficit in the upper boundary layer which helps maintain pollen viability.
Subsurface material identification and sensor selection
NASA Astrophysics Data System (ADS)
T, H.; Reghunadh, R.; Ramesh, M. V.
2017-12-01
In India, most of the landslides occur during monsoon season and causes huge loss of life and property. Design of an early warning system for highly landslide prone area will reduce losses to a great extent. The in-situ monitoring systems needs deployment of several sensors inside a borehole for monitoring a particular slope. Amrita Center for Wireless Networks and Applications (AmritaWNA), Amrita University has designed, developed and deployed a Wireless Sensor Network (WSN) for real time landslide monitoring using geotechnical instruments and sensors like rain gauge, moisture sensor, piezometer, strain gauge, tilt meter and geophone inside a Deep Earth Probe (DEP) at different locations. These sensors provide point measurements of the subsurface at a higher accuracy. Every landslide prone terrain is unique with respect to its geology, hydrological conditions, meteorological conditions, velocity of movement etc. The decision of installing different geotechnical instruments in a landslide prone terrain is a crucial step to be considered. Rain gauge, moisture sensor, and piezometer are usually used in clay rich areas to sense the moisture and pore pressure values. Geophone and Crack meter are instruments used in rocky areas to monitor cracks and vibrations associated with a movement. Inclinometer and Strain gauge are usually placed inside a casing and can be used in both rocky and soil areas. In order to place geotechnical instruments and sensors at appropriate places Electrical Resistivity Tomography (ERT) method can be used. Variation in electrical resistivity values indicate the changes in composition, layer thickness, or contaminant levels. The derived true resistivity image can be used for identifying the type of materials present in the subsurface at different depths. We have used this method for identifying the type of materials present in our site at Chandmari (Sikkim). Fig 1 shows the typical resistivity values of a particular area in Chandmari site. The results shows that the area has more clay so the placement of moisture sensor and piezometer are required instead of placing geophone, crack meter etc.
Moisture Monitoring at Area G, Technical Area 54, Los Alamos National Laboratory, 2016 Status Report
DOE Office of Scientific and Technical Information (OSTI.GOV)
Levitt, Daniel Glenn; Birdsell, Kay Hanson; Jennings, Terry L.
Hydrological characterization and moisture monitoring activities provide data required for evaluating the transport of subsurface contaminants in the unsaturated and saturated zones beneath Area G, and for the Area G Performance Assessment and Composite Analysis. These activities have been ongoing at Area G, Technical Area 54 of the Los Alamos National Laboratory since waste disposal operations began in 1957. This report summarizes the hydrological characterization and moisture monitoring activities conducted at Area G. It includes moisture monitoring data collected from 1986 through 2016 from numerous boreholes and access tubes with neutron moisture meters, as well as data collected by automatedmore » dataloggers for water content measurement sensors installed in a waste disposal pit cover, and buried beneath the floor of a waste disposal pit. This report is an update of a nearly identical report by Levitt et al., (2015) that summarized data collected through early 2015; this report includes additional moisture monitoring data collected at Pit 31 and the Pit 38 extension through December, 2016. It also includes information from the Jennings and French (2009) moisture monitoring report and includes all data from Jennings and French (2009) and the Draft 2010 Addendum moisture monitoring report (Jennings and French, 2010). For the 2015 version of this report, all neutron logging data, including neutron probe calibrations, were investigated for quality and pedigree. Some data were recalculated using more defensible calibration data. Therefore, some water content profiles are different from those in the Jennings and French (2009) report. All of that information is repeated in this report for completeness. Monitoring and characterization data generally indicate that some areas of the Area G vadose zone are consistent with undisturbed conditions, with water contents of less than five percent by volume in the top two layers of the Bandelier tuff at Area G. These data also indicate that other areas of the vadose zone are affected by waste disposal activities that have been ongoing at Area G since 1957, a period of nearly 60 years. In some areas, water content profiles indicate increases in water content to depths of tens of meters, especially in areas covered by asphalt and structures.« less
NASA Astrophysics Data System (ADS)
Maples, S.; Fogg, G. E.; Harter, T.
2015-12-01
Accurate estimation of groundwater (GW) budgets and effective management of agricultural GW pumping remains a challenge in much of California's Central Valley (CV) due to a lack of irrigation well metering. CVHM and C2VSim are two regional-scale integrated hydrologic models that provide estimates of historical and current CV distributed pumping rates. However, both models estimate GW pumping using conceptually different agricultural water models with uncertainties that have not been adequately investigated. Here, we evaluate differences in distributed agricultural GW pumping and recharge estimates related to important differences in the conceptual framework and model assumptions used to simulate surface water (SW) and GW interaction across the root zone. Differences in the magnitude and timing of GW pumping and recharge were evaluated for a subregion (~1000 mi2) coincident with Yolo County, CA, to provide similar initial and boundary conditions for both models. Synthetic, multi-year datasets of land-use, precipitation, evapotranspiration (ET), and SW deliveries were prescribed for each model to provide realistic end-member scenarios for GW-pumping demand and recharge. Results show differences in the magnitude and timing of GW-pumping demand, deep percolation, and recharge. Discrepancies are related, in large part, to model differences in the estimation of ET requirements and representation of soil-moisture conditions. CVHM partitions ET demand, while C2VSim uses a bulk ET rate, resulting in differences in both crop-water and GW-pumping demand. Additionally, CVHM assumes steady-state soil-moisture conditions, and simulates deep percolation as a function of irrigation inefficiencies, while C2VSim simulates deep percolation as a function of transient soil-moisture storage conditions. These findings show that estimates of GW-pumping demand are sensitive to these important conceptual differences, which can impact conjunctive-use water management decisions in the CV.
Differential atmospheric tritium sampler
Griesbach, O.A.; Stencel, J.R.
1987-10-02
An atmospheric tritium sampler is provided which uses a carrier gas comprised of hydrogen gas and a diluting gas, mixed in a nonexplosive concentration. Sample air and carrier gas are drawn into and mixed in a manifold. A regulator meters the carrier gas flow to the manifold. The air sample/carrier gas mixture is pulled through a first moisture trap which adsorbs water from the air sample. The moisture then passes through a combustion chamber where hydrogen gas in the form of H/sub 2/ or HT is combusted into water. The manufactured water is transported by the air stream to a second moisture trap where it is adsorbed. The air is then discharged back into the atmosphere by means of a pump.
Kinoshita, Kensuke; Hattori, Kazuya; Ota, Yoshio; Kanai, Takao; Shimizu, Miyuki; Kobayashi, Hiroyuki; Tokuda, Yasuharu
2013-02-01
Dry axilla can sometimes be found among dehydrated older patients. In this study, we measured the axillary moisture and assessed it as possible marker for dehydration. Twenty-nine older patients admitted with acute medical conditions participated in this study. Dehydration was diagnosed by the calculated serum osmolality of greater than 295 mOsm/L. The moisture of axilla was measured by a skin moisture impedance meter which was applied at the center of axilla of patients. 11 patients (7 males and 4 females) were diagnosed as dehydrated and 18 patients (10 males and 8 females) were diagnosed as non-dehydrated. The mean axillary moisture (33%) in the dehydrated group was significantly lower than that (42%) in the non-dehydrated group (p<0.05). The axillary moisture ≥50% showed the sensitivity of 88%. The axillary moisture <30% showed the specificity of 91%. Use of a single cutoff value of 40% moisture produced the sensitivity of 59% and the specificity of 9%. As for the physical signs, dry axilla had also moderate sensitivity and excellent specificity to detect dehydration. The measurement of the axillary moisture could help assess dehydration. Dehydration could be ruled out when the axillary moisture ≥50%, while it could be ruled-in when the axillary moisture is <30%. Copyright © 2012 Elsevier Inc. All rights reserved.
Report of the 67th National Conference on Weights and Measures 1982
NASA Astrophysics Data System (ADS)
Tholen, A. D.; Barbrow, L. E.; Heffernan, A. P.
1982-10-01
Reports by the several standing and annual committees of the Conference comprise the major portion of the publication. Included also are papers presented by Conference officials and others. Major issues discussed at the National Conference included long range plans for training, enforcement uniformity, national type evaluation programs and a new publication on type evaluation examinations, new design and performance requirements for commercial weighing and measuring instruments, cash and credit sales at retail motor fuel outlets, studies of model State laws and regulations, a tentative code for grain moisture meters, and adoption of several NBS Handbooks by NCWM.
NASA Astrophysics Data System (ADS)
Cumming, William Frank Preston
Fine scale studies are rarely performed to address landscape level responses to microclimatic variability. Is it the timing, distribution, and magnitude of soil temperature and moisture that affects what species emerge each season and, in turn, their resilience to fluctuations in microclimate. For this dissertation research, I evaluated the response of vegetation change to microclimatic variability within two communities over a three year period (2009-2012) utilizing 25 meter transects at two locations along the Front Range of Colorado near Boulder, CO and Golden, CO respectively. To assess microclimatic variability, spatial and temporal autocorrelation analyses were performed with soil temperature and moisture. Species cover was assessed along several line transects and correlated with microclimatic variability. Spatial and temporal autocorrelograms are useful tools in identifying the degree of dependency of soil temperature and moisture on the distance and time between pairs of measurements. With this analysis I found that a meter spatial resolution and two-hour measurements are sufficient to capture the fine scale variability in soil properties throughout the year. By comparing this to in situ measurements of soil properties and species percent cover I found that there are several plant functional types and/or species origin in particular that are more sensitive to variations in temperature and moisture than others. When all seasons, locations, correlations, and regional climate are looked at, it is the month of March that stands out in terms of significance. Additionally, of all of the vegetation types represented at these two sites C4, C3, native, non-native, and forb species seem to be the most sensitive to fluctuations in soil temperature, moisture, and regional climate in the spring season. The steady decline in percent species cover the study period and subsequent decrease in percent species cover and size at both locations may indicate that certain are unable to respond to continually higher temperatures and lower moisture availability that is inevitable with future climatic variability.
NASA Technical Reports Server (NTRS)
Allison, D. E.
1984-01-01
A model is developed for the estimation of the surface fluxes of momentum, heat, and moisture of the cloud topped marine atmospheric boundary layer by use of satellite remotely sensed parameters. The parameters chosen for the problem are the integrated liquid water content, q sub li, the integrated water vapor content, q sub vi, the cloud top temperature, and either a measure of the 10 meter neutral wind speed or the friction velocity at the surface. Under the assumption of a horizontally homogeneous, well-mixed boundary layer, the model calculates the equivalent potential temperature and total water profiles of the boundary layer along with the boundary layer height from inputs of q sub li, q sub vi, and cloud top temperature. These values, along with the 10m neutral wind speed or friction velocity and the sea surface temperature are then used to estimate the surface fluxes. The development of a scheme to parameterize the integrated water vapor outside of the boundary layer for the cases of cold air outbreak and California coastal stratus is presented.
How well can regional fluxes be derived from smaller-scale estimates?
NASA Technical Reports Server (NTRS)
Moore, Kathleen E.; Fitzjarrald, David R.; Ritter, John A.
1992-01-01
Regional surface fluxes are essential lower boundary conditions for large scale numerical weather and climate models and are the elements of global budgets of important trace gases. Surface properties affecting the exchange of heat, moisture, momentum and trace gases vary with length scales from one meter to hundreds of km. A classical difficulty is that fluxes have been measured directly only at points or along lines. The process of scaling up observations limited in space and/or time to represent larger areas was done by assigning properties to surface classes and combining estimated or calculated fluxes using an area weighted average. It is not clear that a simple area weighted average is sufficient to produce the large scale from the small scale, chiefly due to the effect of internal boundary layers, nor is it known how important the uncertainty is to large scale model outcomes. Simultaneous aircraft and tower data obtained in the relatively simple terrain of the western Alaska tundra were used to determine the extent to which surface type variation can be related to fluxes of heat, moisture, and other properties. Surface type was classified as lake or land with aircraft borne infrared thermometer, and flight level heat and moisture fluxes were related to surface type. The magnitude and variety of sampling errors inherent in eddy correlation flux estimation place limits on how well any flux can be known even in simple geometries.
NASA Technical Reports Server (NTRS)
Wiesnet, D. R.; Mcginnis, D. F., Jr.; Matson, M. (Principal Investigator)
1978-01-01
The author has identified the following significant results. Estimates of soil moisture were obtained from visible, near-IR gamma ray and microwave data. Attempts using GOES thermal-IR were unsuccessful due to resolutions (8 km). Microwaves were the most effective at soil moisture estimates, with and without vegetative cover. Gamma rays provided only one value for the test site, produced by many data points obtained from overlapping 150 meter diameter circles. Even though the resulting averaged value was near the averaged field moisture value, this method suffers from atmospheric contaminants, the need to fly at low altitudes, and the necessity of prior calibration of a given site. Visible and near-IR relationships are present for bare fields but appear to be limited to soil moisture levels between 5 and 20%. The densely vegetated alfalfa fields correlated with near-IR reflectance only; soil moisture values from wheat fields showed no relation to either or near-IR MSS data.
NASA's Soil Moisture Active and Passive (SMAP) Mission
NASA Technical Reports Server (NTRS)
Kellogg, Kent; Njoku, Eni; Thurman, Sam; Edelstein, Wendy; Jai, Ben; Spencer, Mike; Chen, Gun-Shing; Entekhabi, Dara; O'Neill, Peggy; Piepmeier, Jeffrey;
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 performance of candidate algorithms. SMAP conducted an Applications Workshop in September 2009 to coordinate with potential application users interested in the mission data. A draft Applications Plan describing the Project s planned outreach to potential applications users has been prepared and will be updated during Phase B. SMAP made a significant evaluation of the potential terrestrial radio frequency interference (RFI) source environment and established radiometer and radar flight hardware and ground processing mitigation approaches. SMAP finalized its science orbit and orbit injection approach to optimize launch mass and prepared launch and commissioning scenarios and timeline. A science data communications approach was developed to maximize available science data volume to improve science margins while maintaining moderately short data product latencies to support many potential applications using existing ground assets and with minimum impact to the flight system. SMAP developed rigid multi-body and flexible body dynamics and control models and system designs for the 6-meter rotating instrument reflector-boom assembly (RBA) and flight system to confirm pointing and control performance, and devised strategies to efficiently implement on-orbit balancing if needed. Industry partners were selected for the spin mechanism assembly (SMA) and RBA. Preliminary designs for the radar and radiometer were initiated, including constructing breadboards of key assemblies.
Sun, Tian-Yong; Wang, Li-Hai; Sun, Mo-Long
2013-07-01
Standing trees decay often causes vast loss of timber resources. To investigate the correlations between the standing trees decay and the site conditions is of importance to scientifically and reasonably manage forests and to decrease wood resources loss. By using Resistograph and meter ruler, a measurement was made on the decay degree of the trunk near root and the diameter at breast height (DBH) of 15 mature Korean pine standing trees in a Korean pine-broadleaved mixed forest in Xiao Xing' an Mountains in May, 2011. In the meantime, soil samples were collected from the root zones of standing trees and the upslope and downslope 5 meters away from the trunks, respectively. Five physical-chemical properties including moisture content, bulk density, total porosity, pH value, and organic matter content of the soil samples were tested. The regression equations concerning the trunk decay degree of the standing trees, their DBH, and the 5 soil properties were established. The results showed that the trunk decay degree of the mature Korean pine standing trees had higher correlations with the bulk density, total porosity, pH value, and organic matter content (R = 0.687), and significant positive correlation with the moisture content (R = 0.507) of the soils at the root zones of standing trees, but less correlation with the 5 properties of the soils at both upslope and downslope 5 meters away from the trunks. The trunk decay degree was decreased when the soil moisture content was below 18.4%. No significant correlation was observed between the trunk decay degree of mature Korean pine standing trees and the tree age.
The NASA Soil Moisture Active Passive (SMAP) Mission - Science and Data Product Development Status
NASA Technical Reports Server (NTRS)
Nloku, E.; Entekhabi, D.; O'Neill, P.
2012-01-01
The Soil Moisture Active Passive (SMAP) mission, planned for launch in late 2014, has the objective of frequent, global mapping of near-surface soil moisture and its freeze-thaw state. The SMAP measurement system utilizes an L-band radar and radiometer sharing a rotating 6-meter mesh reflector antenna. The instruments will operate on a spacecraft in a 685 km polar orbit with 6am/6pm nodal crossings, viewing the surface at a constant 40-degree incidence angle with a 1000-km swath width, providing 3-day global coverage. Data from the instruments will yield global maps of soil moisture and freeze/thaw state at 10 km and 3 km resolutions, respectively, every two to three days. The 10-km soil moisture product will be generated using a combined radar and radiometer retrieval algorithm. SMAP will also provide a radiometer-only soil moisture product at 40-km spatial resolution and a radar-only soil moisture product at 3-km resolution. The relative accuracies of these products will vary regionally and will depend on surface characteristics such as vegetation water content, vegetation type, surface roughness, and landscape heterogeneity. The SMAP soil moisture and freeze/thaw measurements will enable significantly improved estimates of the fluxes of water, energy and carbon between the land and atmosphere. Soil moisture and freeze/thaw controls of these fluxes are key factors in the performance of models used for weather and climate predictions and for quantifYing the global carbon balance. Soil moisture measurements are also of importance in modeling and predicting extreme events such as floods and droughts. The algorithms and data products for SMAP are being developed in the SMAP Science Data System (SDS) Testbed. In the Testbed algorithms are developed and evaluated using simulated SMAP observations as well as observational data from current airborne and spaceborne L-band sensors including data from the SMOS and Aquarius missions. We report here on the development status of the SMAP data products. The Testbed simulations are designed to capture various sources of errors in the products including environment effects, instrument effects (nonideal aspects of the measurement system), and retrieval algorithm errors. The SMAP project has developed a Calibration and Validation (Cal/Val) Plan that is designed to support algorithm development (pre-launch) and data product validation (post-launch). A key component of the Cal/Val Plan is the identification, characterization, and instrumentation of sites that can be used to calibrate and validate the sensor data (Level l) and derived geophysical products (Level 2 and higher).
Homogeneity of a Global Multisatellite Soil Moisture Climate Data Record
NASA Technical Reports Server (NTRS)
Su, Chun-Hsu; Ryu, Dongryeol; Dorigo, Wouter; Zwieback, Simon; Gruber, Alexander; Albergel, Clement; Reichle, Rolf H.; Wagner, Wolfgang
2016-01-01
Climate Data Records (CDR) that blend multiple satellite products are invaluable for climate studies, trend analysis and risk assessments. Knowledge of any inhomogeneities in the CDR is therefore critical for making correct inferences. This work proposes a methodology to identify the spatiotemporal extent of the inhomogeneities in a 36-year, global multisatellite soil moisture CDR as the result of changing observing systems. Inhomogeneities are detected at up to 24 percent of the tested pixels with spatial extent varying with satellite changeover times. Nevertheless, the contiguous periods without inhomogeneities at changeover times are generally longer than 10 years. Although the inhomogeneities have measurable impact on the derived trends, these trends are similar to those observed in ground data and land surface reanalysis, with an average error less than 0.003 cubic meters per cubic meter per year. These results strengthen the basis of using the product for long-term studies and demonstrate the necessity of homogeneity testing of multisatellite CDRs in general.
NASA Astrophysics Data System (ADS)
He, L.; Ivanov, V. Y.; Bohrer, G.; Maurer, K.; Vogel, C. S.; Moghaddam, M.
2011-12-01
Vegetation is heterogeneous at different scales, influencing spatially variable energy and water exchanges between land-surface and atmosphere. Current land surface parameterizations of large-scale models consider spatial variability at a scale of a few kilometers and treat vegetation cover as aggregated patches with uniform properties. However, the coupling mechanisms between fine-scale soil moisture, vegetation, and energy fluxes such as evapotranspiration are strongly nonlinear; the aggregation of surface variations may produce biased energy fluxes. This study aims to improve the understanding of the scale impact in atmosphere-biosphere-hydrosphere interactions, which affects predictive capabilities of land surface models. The study uses a high-resolution, physically-based ecohydrological model tRIBS + VEGGIE as a data integration tool to upscale the heterogeneity of canopy distribution resolved at a few meters to the watershed scale. The study was carried out for a spatially heterogeneous, temperate mixed forest environment of Northern Michigan located near the University of Michigan Biological Station (UMBS). Energy and soil water dynamics were simulated at the tree-canopy resolution in the horizontal plane for a small domain (~2 sq. km) located within a footprint of the AmeriFlux tower. A variety of observational data were used to constrain and confirm the model, including a 3-m profile continuous soil moisture dataset and energy flux data (measured at the AmeriFlux tower footprint). A scenario with a spatially uniform canopy, corresponding to the commonly used 'big-leaf' scheme in land surface parameterizations was used to infer the effects of coarse-scale averaging. To gain insights on how heterogeneous canopy and soil moisture interact and contribute to the domain-averaged transpiration, several scenarios of tree-scale leaf area and soil moisture spatial variability were designed. Specifically, for the same mean states, the scenarios of variability of canopy biomass account for the spatial distribution of photosynthesis (and thus the stomatal resistance), the aerodynamic and leaf boundary layer resistances as well as the differential radiation forcing due to tall tree exposure and lateral shading of short trees. The numerical experiments show that by transpiring spatially varying amounts of water, heterogeneous canopies adjust the spatial soil water state to the scaled inverse of the canopy biomass regardless of the initial moisture state. Such a spatial distribution can be further wiped out because of the differential water stress. The aggregation of canopy-scale atmosphere-biosphere-hydrosphere interactions demonstrates non-linear relationship between soil moisture and evapotranspiration, influencing domain-averaged energy fluxes.
Soil Moisture fusion across scales using a multiscale nonstationary Spatial Hierarchical Model
NASA Astrophysics Data System (ADS)
Kathuria, D.; Mohanty, B.; Katzfuss, M.
2017-12-01
Soil moisture (SM) datasets from remote sensing (RS) platforms (such as SMOS and SMAP) and reanalysis products from land surface models are typically available on a coarse spatial granularity of several square km. Ground based sensors, on the other hand, provide observations on a finer spatial scale (meter scale or less) but are sparsely available. SM is affected by high variability due to complex interactions between geologic, topographic, vegetation and atmospheric variables and these interactions change dynamically with footprint scales. Past literature has largely focused on the scale specific effect of these covariates on soil moisture. The present study proposes a robust Multiscale-Nonstationary Spatial Hierarchical Model (MN-SHM) which can assimilate SM from point to RS footprints. The spatial structure of SM across footprints is modeled by a class of scalable covariance functions whose nonstationary depends on atmospheric forcings (such as precipitation) and surface physical controls (such as topography, soil-texture and vegetation). The proposed model is applied to fuse point and airborne ( 1.5 km) SM data obtained during the SMAPVEX12 campaign in the Red River watershed in Southern Manitoba, Canada with SMOS ( 30km) data. It is observed that precipitation, soil-texture and vegetation are the dominant factors which affect the SM distribution across various footprint scales (750 m, 1.5 km, 3 km, 9 km,15 km and 30 km). We conclude that MN-SHM handles the change of support problems easily while retaining reasonable predictive accuracy across multiple spatial resolutions in the presence of surface heterogeneity. The MN-SHM can be considered as a complex non-stationary extension of traditional geostatistical prediction methods (such as Kriging) for fusing multi-platform multi-scale datasets.
NASA Soil Moisture Active Passive (SMAP) Mission Formulation
NASA Technical Reports Server (NTRS)
Entekhabi, Dara; Njoku, Eni; ONeill, Peggy; Kellogg, Kent; Entin, Jared
2011-01-01
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 Earth Science Decadal Survey [1]. SMAP s measurement objectives are high-resolution global measurements of near-surface soil moisture and its freeze-thaw state. These measurements would allow significantly improved estimates of water, energy and carbon transfers between the land and atmosphere. The soil moisture control of these fluxes is a key factor in the performance of atmospheric models used for weather forecasts and climate projections. Soil moisture measurements are also of great importance in assessing flooding and monitoring drought. Knowledge gained from SMAP s planned observations can help mitigate these natural hazards, resulting in potentially great economic and societal benefits. SMAP measurements would also yield high resolution spatial and temporal mapping of the frozen or thawed condition of the surface soil and vegetation. Observations of soil moisture and freeze/thaw timing over the boreal latitudes will contribute to reducing a major uncertainty in quantifying the global carbon balance and help resolve an apparent missing carbon sink over land. The SMAP mission would utilize an L-band radar and radiometer sharing a rotating 6-meter mesh reflector antenna (see Figure 1) [2]. The radar and radiometer instruments would be carried onboard a 3-axis stabilized spacecraft in a 680 km polar orbit with an 8-day repeating ground track. The instruments are planned to provide high-resolution and high-accuracy global maps of soil moisture at 10 km resolution and freeze/thaw at 3 km resolution, every two to three days (see Table 1 for a list of science data products). The mission is adopting a number of approaches to identify and mitigate potential terrestrial radio frequency interference (RFI). These approaches are being incorporated into the radiometer and radar flight hardware and ground processing designs.
Terrestrial Ecosystems - Topographic Moisture Potential of the Conterminous United States
Cress, Jill J.; Sayre, Roger G.; Comer, Patrick; Warner, Harumi
2009-01-01
As part of an effort to map terrestrial ecosystems, the U.S. Geological Survey has generated topographic moisture potential classes to be used in creating maps depicting standardized, terrestrial ecosystem models for the conterminous United States, using an ecosystems classification developed by NatureServe. A biophysical stratification approach, developed for South America and now being implemented globally, was used to model the ecosystem distributions. Substrate moisture regimes strongly influence the differentiation and distribution of terrestrial ecosystems, and therefore topographic moisture potential is one of the key input layers in this biophysical stratification. The method used to produce these topographic moisture potential classes was based on the derivation of ground moisture potential using a combination of computed topographic characteristics (CTI, slope, and aspect) and mapped National Wetland Inventory (NWI) boundaries. This method does not use climate or soil attributes to calculate relative topographic moisture potential since these characteristics are incorporated into the ecosystem model though other input layers. All of the topographic data used for this assessment were derived from the USGS 30-meter National Elevation Dataset (NED ) including the National Compound Topographic Index (CTI). The CTI index is a topographically derived measure of slope for a raster cell and the contributing area from upstream raster cells, and thus expresses potential for water flow to a point. In other words CTI data are 'a quantification of the position of a site in the local landscape', where the lowest values indicate ridges and the highest values indicate stream channels, lakes and ponds. These CTI values were compared to independent estimates of water accumulation by obtaining geospatial data from a number of sample locations representing two types of NWI boundaries: freshwater emergent wetlands and freshwater forested/shrub wetlands. Where these shorelines (the interface between the NWI wetlands and adjacent land) occurred, the CTI values were extracted and a histogram of their statistical distributions was calculated. Based on an evaluation of these histograms, CTI thresholds were developed to separate periodically saturated or flooded land, mesic uplands (moderately moist), and uplands. After the range of CTI values for these three different substrate moisture regimes was determined, the CTI values were grouped into three initial topographic moisture potential classes. As a final step in the generation of this national data layer, the uplands classification was subdivided into either very dry uplands or dry uplands. Very dry uplands were defined as uplands with relatively steep, south-facing slopes, and identification of this class was based on the slope and aspect datasets derived from the NED. The remaining uplands that did not meet these additional criteria were simply re-classified as dry uplands. The final National Topographic Moisture Potential dataset for the conterminous United States contains four classes: periodically saturated or flooded land (CTI = 18.5), mesic uplands (12 = 24 degrees and 91 degrees =< Aspect =< 314 degrees). This map shows a smoothed and generalized image of the four topographic moisture potential classes. Additional information about this map and any of the data developed for the ecosystems modeling of the conterminous United States is available online at http://rmgsc.cr.usgs.gov/ecosystems/.
NASA Astrophysics Data System (ADS)
Schreiner-McGraw, A.; Vivoni, E. R.; Franz, T. E.; Anderson, C.
2013-12-01
Human impacts on desert ecosystems have wide ranging effects on the hydrologic cycle which, in turn, influence interactions between the critical zone and the atmosphere. In this contribution, we utilize cosmic-ray soil moisture sensors at three human-modified semiarid ecosystems in the North American monsoon region: a buffelgrass pasture in Sonora, Mexico, a woody-plant encroached savanna ecosystem in Arizona, and a woody-plant encroached shrubland ecosystem in New Mexico. In each case, landscape heterogeneity in the form of bare soil and vegetation patches of different types leads to a complex mosaic of soil moisture and land-atmosphere interactions. Historically, the measurement of spatially-averaged soil moisture at the ecosystem scale (on the order of several hundred square meters) has been problematic. Thus, new advances in measuring cosmogenically-produced neutrons present an opportunity for observational and modeling studies in these ecosystems. We discuss the calibration of the cosmic-ray soil moisture sensors at each site, present comparisons to a distributed network of in-situ measurements, and verify the spatially-aggregated observations using the watershed water balance method at two sites. We focus our efforts on the summer season 2013 and its rainfall period during the North American monsoon. To compare neutron counts to the ground sensors, we utilized an aspect-elevation weighting algorithm to compute an appropriate spatial average for the in-situ measurements. Similarly, the water balance approach utilizes precipitation, runoff, and evapotranspiration measurements in the footprint of the cosmic-ray sensors to estimate a spatially-averaged soil moisture field. Based on these complementary approaches, we empirically determined a relationship between cosmogenically-produced neutrons and the spatially-aggregated soil moisture. This approach may improve upon existing methods used to calculate soil moisture from neutron counts that typically suffer from 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.
Western juniper drying project summaries, 1993-96.
Scott Leavengood; Larry Swan
1999-01-01
Drying tests and trials for western juniper (Juniperus occidentalis Hook.) were conducted between 1993 and 1996 to (1) test and refine existing dry kiln schedules; (2) develop moisture meter correction factors; (3) test dry western juniper in different types of kilns, both by itself and with ponderosa pine (Pinus ponderosa...
Active nursery projects at the Missoula Technology and Development Center
Brian Vachowski
2005-01-01
The USDA Forest Service Missoula Technology and Development Center (MTDC) provides technical expertise, new equipment prototypes, and technology transfer services to Federal, State, and cooperator forest tree seedling nursery managers. Current projects at MTDC include a nursery soil moisture meter, remote data collection systems, low cost weather stations, soil...
Station for spatially distributed measurements of soil moisture and ambient temperature
NASA Astrophysics Data System (ADS)
Jankovec, Jakub; Šanda, Martin; Haase, Tomáš; Sněhota, Michal; Wild, Jan
2013-04-01
Third generation of combined thermal and soil moisture standalone field station coded TMS3 with wireless communication is presented. The device combines three thermometers (MAXIM/DALLAS Semiconductor DS7505U with -55 to +125°C range and 0.0625°C resolution, 0.5°C precision in 0 to +70°C range and 2°C precision out of this range). Soil moisture measurement is performed based on time domain transmission (TDT) principle for the full range of soil moisture with 0.025% resolution within the full possible soil moisture span for the most typical conditions of dry to saturated soils with safe margins to enable measurements in freezing, hot or saline soils. Principal compact version is designed for temperature measurements approximately at heights -10, 0 and +15 cm relative to soil surface when installed vertically and soil moisture measurements between 0 and 12 cm below surface. Set of buriable/subsurface stations each with 2.2 meter extension cord with soil and surface temperature measurement provides possibility to scan vertical soil profile for soil moisture and temperature at desired depths. USB equipped station is designed for streamed direct data acquisition in laboratory use in 1s interval. Station is also equipped with the shock sensor indicating the manipulation. Presented version incorporates life time permanent data storage (0.5 million logs). Current sensor design aims towards improved durability in harsh outdoor environment with reliable functioning in wet conditions withstanding mechanical or electric shock destruction. Insertion into the soil is possible by pressing with the use of a simple plastic cover. Data are retrieved by contact portable pocket collector (second generation) or by RFID wireless communication for hundreds meter distance (third generation) in either star pattern of GSM hub to stations or lined up GSM to station to another station both in comprised data packets. This option will allow online data harvesting and real time process control (e.g. optimized irrigation) by the end of 2013. User selected regimes of scanning in the field standalone model is 1,5 or 15 minutes for soil moisture and 1, 5, 10 or 15 minutes for the temperature (in their practical combinations) with a battery and datastorage lifetime ranging 1 - 10 years. Basic station diagnostics is recorded daily, comprehensive check is performed monthly. The TMS2 undergoes calibration on sets of soils. Disturbed and packed cylindrical soil samples (approx. 20 liter) were subject to forced bottom air ventilation to distribute the moisture evenly along vertical axis during drying the sample with increased intensity. Database of soil-specific calibration curves is being built for various soil samples. TMS2 station has been calibrated for soil materials: sandy loam, quartz sand and peat. Calibration on selected undisturbed 7 liter samples, previously CT scanned for correct sensor placement, is in the progress. Temperature and salinity influence on the soil moisture results in drift of 0.05%/°C and 7%/(in full range of 0 to 10 miliSiemens/cm) and additional 2%/(in the range of 10 to 20 miliSiemens/cm) as found in 100% moisture solution. Extended testing of TMS1 generation, predecessor of current design, is successfully performed in variety of field locations (central Europe, central Africa, Himalaya region). Results of long-term measurement at hundreds of localities are successfully used for i) evaluation of species-specific environmental requirements (for different species of plants, bryophytes and fungi) and ii) extrapolation of microclimatic conditions over large areas of rugged sandstone relief with assistance of accurate, LiDAR based, digital terrain model. TMS1 units are e.g. also applied for continuous measurement of temperature and moisture of coarse woody debris, which serves as an important substrate for establishment and growth of seedlings and is thus crucial for natural regeneration of many forest ecosystems. The research is supported by the Technology Agency of the Czech Republic projects No. TA01021283 and SGS12/130/OHK1/2T/11.
NASA Astrophysics Data System (ADS)
Darnault, C. J. G.; Daniel, T. J.; Billy, G.; Hopkins, I.; Guo, L.; Jin, Z.; Gall, H. E.; Lin, H.
2017-12-01
The permeability of the upper meter of soils in frozen conditions, commonly referred to as the active layer, can vary exponentially given the time of year. Variable moisture contents along with temperature, radiation, and slope angle of the soil surface can result in variable depths of frozen soils, which can cause the formation of low permeability ice lenses well into the spring thaw period. The wastewater irrigation site known as the "Living Filter" located in State College, PA has been in continuous operation since 1962. On average 5500 m3/day of wastewater is applied to the site annually, even in the winter months when average temperatures can dip as low as -7 °C during the month of January. The Living Filter is not permitted to discharge to surface water and is intended to recharge the Spring Creek basin that directly underlies the site, therefore runoff from the site is not permitted. We hypothesize that water infiltrates the upper meter of the subsurface during the winter in several different ways such as preferential pathways in the ice layer created by plant stems and weak patches of ice thawed by the warm wastewater. 2D conceptual models of the phase change between ice and water in the soil were created in order to predict soil permeability and its change in temperature. The 2D conceptual models can be correlated between observed soil moisture content and soil temperature data in order to validate the model given spray irrigation and weather patterns. By determining the permeability of the frozen soils, irrigation practices can be adjusted for the winter months so as to reduce the risk of any accidental wastewater runoff. The impact of this study will result in a better understanding of the multiphase dynamics of the active layer and their implication on soil hydrology at the Living Filter and other seasonally frozen sites.
NASA Astrophysics Data System (ADS)
Matos, K.; Alves Meira Neto, A.; Troch, P. A. A.; Volkmann, T.
2017-12-01
Hydrological processes at the hillslope scale are complex and heterogeneous, but monitoring hillslopes with a large number of sensors or replicate experimental designs is rarely feasible. The Landscape Evolution Observatory (LEO) at Biosphere 2 consists of three replicated, large (330 m2) artificial hillslopes (East, Center and West) packed with 1-m depth of initially homogeneous, basaltic soil. Each landscape contains a spatially dense network of sensors capable of resolving meter-scale lateral heterogeneity and sub-meter scale vertical heterogeneity in moisture content and water potential, as well as the hillslope-integrated water balance components. A sophisticated irrigation system allows performing controlled forcing experiments. The three hillslopes are thought to be nearly identical, however recent data showed significant differences in discharge and storage behavior. A 45-day periodic-steady-state tracer experiment was conducted in November and December of 2016, where a 3.5-day long, identical irrigation sequence was repeated 15 times. Each sequence's rainfall, runoff, and storage dynamics were recorded, and distributed moisture characteristics were derived using paired moisture content and matric potential data from 496 positions in each hillslope. In order to understand why the three hillslopes behave hydrologically different, we analyzed soil water retention characteristics at various scales ranging from individually paired moisture and matric potential to whole-hillslope soil water retention characteristics. The results confirm the distinct hydrological behavior between the three hillslopes. The East and West hillslopes behave more similar with respect to the release of water. In contrast, the East and Center hillslopes are more similar with respect to their storage behavior. The differences in hillslope behavior arising from three identically built hillslopes are a surprising and beneficial opportunity to explore how differences in small-scale heterogeneity can impact hydrological dynamics at the hillslope scale.
Combining SAR with LANDSAT for Change Detection of Riparian Buffer Zone in a Semi-arid River Basin
NASA Astrophysics Data System (ADS)
Chang, N.
2006-12-01
A combination of RADARSAT-1 and Landsat 5 TM satellite images linking the soil moisture variation with Normalized Difference Vegetation Index (NDVI) measurements were used to accomplish remotely sensed change detection of riparian buffer zone in the Choke Canyon Reservoir Watershed (CCRW), South Texas. The CCRW was selected as the study area contributing to the reservoir, which is mostly agricultural and range land in a semi-arid coastal environment. This makes the study significant due to the interception capability of non-point source impact within the riparian buffer zone and the maintenance of ecosystem integrity region wide. First of all, an estimation of soil moisture using RADARSAT-1 Synthetic Aperture Radar (SAR) satellite imagery was conducted. With its all-weather capability, the RADARSAT-1 is a promising tool for measuring the surface soil moisture over seasons. The time constraint is almost negligible since the RADARSAT-1 is able to capture surface soil moisture over a large area in a matter of seconds, if the area is within its swath. RADARSAT-1 images presented at here were captured in two acquisitions, including April and September 2004. With the aid of five corner reflectors deployed by Alaska Satellite Facility (ASF), essential radiometric and geometric calibrations were performed to improve the accuracy of the SAR imagery. The horizontal errors were reduced from initially 560 meter down to less than 5 meter at the best try. Then two Landsat 5 TM satellite images were summarized based on its NDVI. The combination of and NDVI and SAR data obviously show that soil moisture and vegetation biomass wholly varies in space and time in the CCRW leading to identify the riparian buffer zone evolution over seasons. It is found that the seasonal soil moisture variation is highly tied with the NDVI values and the change detection of buffer zone is technically feasible. It will contribute to develop more effective management strategies for non-point source pollution control, bird habitat monitoring, and grazing and live stock handlings in the future. Future research focuses on comparison of soil moisture variability within RADARSAT-1 footprints and NDVI variations against interferometric SAR for studying riparian ecosystem functioning on a seasonal basis.
USDA-ARS?s Scientific Manuscript database
Since the late 1980s, electromagnetic (EM) sensors for determination on of soil water content from within nonmetallic access tubes have been marketed as replacements for the neutron moisture meter (NMM); however, the accuracy, variability and physical significance of EM sensor field measurements hav...
Brian Vachowski
2006-01-01
The USDA Forest Service Missoula Technology and Development Center (MTDC) offers technical expertise, technology transfer, and new equipment development to Federal, State, and private forest nurseries. Current and recently completed projects at MTDC include a nursery soil moisture meter, remote data collection systems, low cost weather stations, electronic soil...
Moisture sources of the Mono Lake deglacial pluvial events
NASA Astrophysics Data System (ADS)
Wang, X.; Liang, M. C.; Ali, G.; Shen, C. C.; Cai, Y.; Ke, L.; Hemming, S. R.
2016-12-01
Enormously expanded lakes existed in the today's dry western US Great Basin during the last glacial period. The ancient shorelines located well above modern lake levels suggest that precipitation in lake basins must have been substantially higher in the past. It is however under debate whether the subtropical North Pacific or the tropical Pacific is the major moisture source that contributed to the pluvial events, particularly during the deglaciation. Here, we collected a suite of tufa carbonate samples deposited at the 2,080 meter terrace ( 135 meters above today's lake level) in the Mono Basin, California, a closed lake basin for the last 130 thousand years (kyr). At Goat Ranch, we discovered white, shiny, laminated botryoidal carbonate coatings on tufa mounds. Most of these coatings present two generations of formation separated by a hiatus, which indicates lake level fluctuations. Using high-precision U-Th dating techniques, we found that the lower layer was formed 14.1-14.4 kyr BP (corresponding to the North Atlantic Bølling warming period). The upper layer of the coating was formed 11.9-12.3 kyr BP (within the Younger Dryas event). We then obtained d18O, d13C, D47 and 17O-excess values for the two carbonate layers. The upper part is characterized by low d18O values, -8 to -12 ‰ VPDB, whereas the lower one has higher d18O values, -5 to -6 ‰ VPDB. Both share similar d13C values ( 1-2‰ VPDB). D47 analysis on the carbonates suggests that both layers were deposited in a water temperature of 9±2 oC (1s, n = 4 and 8, respectively). The two generations of carbonates present 17O-excess of moisture in values of 50±5 (1s, n=4) and 25±5 (1s, n=8) per meg VSMOW-SLAP, respectively. The large difference in 17O-excess of parent meteoric water points to different origins of moisture for the tufa carbonate formations. The high 17O-excess values during YD suggest a moisture source with a low relative humidity, consistent with the conventional view that the moisture was brought from the subtropical North Pacific, aided by a strong southward shift of the jet stream. In contrast, the lower 17O-excess values during Bølling indicate a moisture source with a high relative humidity or strong continental recycling; each suggests a southern moisture source in the tropical Pacific.
COSMOS: COsmic-ray Soil Moisture Observing System planned for the United States
NASA Astrophysics Data System (ADS)
Zweck, C.; Zreda, M.; Shuttleworth, J.; Zeng, X.
2008-12-01
Because soil water exerts a critical control on weather, climate, ecosystem, and water cycle, understanding soil moisture changes in time and space is crucial for many fields within natural sciences. A serious handicap in soil moisture measurements is the mismatch between limited point measurements using contact methods and remote sensing estimates over large areas. We present a novel method to measure soil moisture non- invasively at an intermediate spatial scale that will alleviate this problem. The method takes advantage of the dependence of cosmic-ray neutron intensity on the hydrogen content of soils (Zreda et al., Geophysical Research Letters, accepted). Low-energy cosmic-ray neutrons are produced and moderated in the soil, transported from the soil into the atmosphere where they are measured with a cosmic-ray neutron probe to provide integrated soil moisture content over a footprint of several hundred meters and a depth of a few decimeters. The method and the instrument are intended for deployment in the continental-scale COSMOS network that is designed to cover the contiguous region of the USA. Fully deployed, the COSMOS network will consist of up to 500 probes, and will provide continuous soil moisture content (together with atmospheric pressure, temperature and relative humidity) measured and reported hourly. These data will be used for initialization and assimilation of soil moisture conditions in weather and short-term (seasonal) climate forecasting, and for other land-surface applications.
L-band Soil Moisture Mapping using Small UnManned Aerial Systems
NASA Astrophysics Data System (ADS)
Dai, E.
2015-12-01
Soil moisture is of fundamental importance to many hydrological, biological and biogeochemical processes, plays an important role in the development and evolution of convective weather and precipitation, and impacts water resource management, agriculture, and flood runoff prediction. The launch of NASA's Soil Moisture Active/Passive (SMAP) mission in 2015 promises to provide global measurements of soil moisture and surface freeze/thaw state at fixed crossing times and spatial resolutions as low as 5 km for some products. However, there exists a need for measurements of soil moisture on smaller spatial scales and arbitrary diurnal times for SMAP validation, precision agriculture and evaporation and transpiration studies of boundary layer heat transport. The Lobe Differencing Correlation Radiometer (LDCR) provides a means of mapping soil moisture on spatial scales as small as several meters (i.e., the height of the platform) .Compared with various other proposed methods of validation based on either situ measurements [1,2] or existing airborne sensors suitable for manned aircraft deployment [3], the integrated design of the LDCR on a lightweight small UAS (sUAS) is capable of providing sub-watershed (~km scale) coverage at very high spatial resolution (~15 m) suitable for scaling scale studies, and at comparatively low operator cost. The LDCR on Tempest unit can supply the soil moisture mapping with different resolution which is of order the Tempest altitude.
NASA Astrophysics Data System (ADS)
Dong, J.; Steele-Dunne, S. C.; Ochsner, T. E.; Van De Giesen, N.
2015-12-01
Soil moisture, hydraulic and thermal properties are critical for understanding the soil surface energy balance and hydrological processes. Here, we will discuss the potential of using soil temperature observations from Distributed Temperature Sensing (DTS) to investigate the spatial variability of soil moisture and soil properties. With DTS soil temperature can be measured with high resolution (spatial <1m, and temporal < 1min) in cables up to kilometers in length. Soil temperature evolution is primarily controlled by the soil thermal properties, and the energy balance at the soil surface. Hence, soil moisture, which affects both soil thermal properties and the energy that participates the evaporation process, is strongly correlated to the soil temperatures. In addition, the dynamics of the soil moisture is determined by the soil hydraulic properties.Here we will demonstrate that soil moisture, hydraulic and thermal properties can be estimated by assimilating observed soil temperature at shallow depths using the Particle Batch Smoother (PBS). The PBS can be considered as an extension of the particle filter, which allows us to infer soil moisture and soil properties using the dynamics of soil temperature within a batch window. Both synthetic and real field data will be used to demonstrate the robustness of this approach. We will show that the proposed method is shown to be able to handle different sources of uncertainties, which may provide a new view of using DTS observations to estimate sub-meter resolution soil moisture and properties for remote sensing product validation.
Data on the chemical properties of commercial fish sauce products.
Nakano, Mitsutoshi; Sagane, Yoshimasa; Koizumi, Ryosuke; Nakazawa, Yozo; Yamazaki, Masao; Watanabe, Toshihiro; Takano, Katsumi; Sato, Hiroaki
2017-12-01
This data article reports on the chemical properties of commercial fish sauce products associated with the fish sauce taste and flavor. All products were analyzed in triplicate. Dried solid content was analyzed by moisture analyzer. Fish sauce salinity was determined by a salt meter. pH was measured using a pH meter. The acidity was determined using a titration assay. Amino nitrogen and total nitrogen were evaluated using a titration assay and Combustion-type nitrogen analyzer, respectively. The analyzed products originated from Japan, Thailand, Vietnam, China, the Philippines, and Italy. Data on the chemical properties of the products are provided in table format in the current article.
A chemical light meter for forest research
David A. Marquis; George Yelenosky
1961-01-01
Light is one of the most important factors that influence the growth and development of forest trees. Not only is light necessary for the basic process of photosynthesis; light also regulates and modifies other factors of the environment such as temperature and moisture. Yet despite the importance of light, few investigators have succeeded in measuring it adequately in...
NASA Astrophysics Data System (ADS)
Azza, Gorrab; Zribi, Mehrez; Baghdadi, Nicolas; Mougenot, Bernard; Boulet, Gilles; Lili-Chabaane, Zohra
2015-04-01
Mapping surface soil moisture with meter-scale spatial resolution is appropriate for multi- domains particularly hydrology and agronomy. It allows water resources and irrigation management decisions, drought monitoring and validation of multi-hydrological water balance models. In the last years, various studies have demonstrated the large potential of radar remote sensing data, mainly from C frequency band, to retrieve soil moisture. However, the accuracy of the soil moisture estimation, by inversing backscattering radar coefficients (σ°), is affected by the influence of surface roughness and vegetation biomass contributions. In recent years, different empirical, semi empirical and physical approaches are developed for bare soil conditions, to estimate accurately spatial soil moisture variability. In this study, we propose an approach based on the change detection method for the retrieval of surface soil moisture at a higher spatial resolution. The proposal algorithm combines multi-temporal X-band SAR images (TerraSAR-X) with different continuous thetaprobe measurements. Seven thetaprobe stations are installed at different depths over the central semi arid region of Tunisia (9°23' - 10°17' E, 35° 1'-35°55' N). They cover approximately the entire of our study site and provide regional scale information. Ground data were collected over agricultural bare soil fields simultaneously to various TerraSAR-X data acquired during 2013-2014 and 2014-2015. More than fourteen test fields were selected for each spatial acquisition campaign, with variations in soil texture and in surface soil roughness. For each date, we considered the volumetric water content with thetaprobe instrument and gravimetric sampling; we measured also the roughness parameters with pin profilor. To retrieve soil moisture from X-band SAR data, we analyzed statistically the sensitivity between radar measurements and ground soil moisture derived from permanent thetaprobe stations. Our analyses are applied over bare soil class identified from an optical image SPOT / HRV acquired in the same period of the measurements. Results have shown linear relationship for the radar signals as a function of volumetric soil moisture with high sensitivity about 0.21 dB/vol%. For estimation of change in soil moisture, we considered two options: On the first one, we applied the change detection approach between successive radar images (∆σ°) assuming unchanged soil roughness effects. Our soil moisture retrieval algorithm was validated on the basis of comparisons between estimated and in situ soil moisture measurements over test fields. Using this option, results have shown an accuracy (RMSE) of about 4.8 %. Secondly, we corrected the sensitivity of the radar backscatter images to the surface roughness variability. Results have shown a reduction of the difference between the retrieved soil moisture and ground measurements with an RMSE about 3.7%.
NASA Astrophysics Data System (ADS)
Cassiani, G.; Gallotti, L.; Ventura, V.; Andreotti, G.
2003-04-01
The identification of flow and transport characteristics in the vadose zone is a fundamental step towards understanding the dynamics of contaminated sites and the resulting risk of groundwater pollution. Borehole radar has gained popularity for the monitoring of moisture content changes, thanks to its apparent simplicity and its high resolution characteristics. However, cross-hole radar requires closely spaced (a few meters), plastic-cased boreholes, that are rarely available as a standard feature in sites of practical interest. Unlike cross-hole applications, Vertical Radar Profiles (VRP) require only one borehole, with practical and financial benefits. High-resolution, time-lapse VRPs have been acquired at a crude oil contaminated site in Trecate, Northern Italy, on a few existing boreholes originally developed for remediation via bioventing. The dynamic water table conditions, with yearly oscillations of roughly 5 m from 6 to 11 m bgl, offers a good opportunity to observe via VRP a field scale drainage-imbibition process. Arrival time inversion has been carried out using a regularized tomographic algorithm, in order to overcome the noise introduced by first arrival picking. Interpretation of the vertical profiles in terms of moisture content has been based on standard models (Topp et al., 1980; Roth et al., 1990). The sedimentary sequence manifests itself as a cyclic pattern in moisture content over most of the profiles. We performed preliminary Richards' equation simulations with time varying later table boundary conditions, in order to estimate the unsaturated flow parameters, and the results have been compared with laboratory evidence from cores.
NASA Technical Reports Server (NTRS)
O'Neill, P.; Podest, E.
2011-01-01
The planned Soil Moisture Active Passive (SMAP) mission is one of the first Earth observation satellites being developed by NASA in response to the National Research Council's Decadal Survey, Earth Science and Applications from Space: National Imperatives for the Next Decade and Beyond [1]. Scheduled to launch late in 2014, the proposed SMAP mission would provide high resolution and frequent revisit global mapping of soil moisture and freeze/thaw state, utilizing enhanced Radio Frequency Interference (RFI) mitigation approaches to collect new measurements of the hydrological condition of the Earth's surface. The SMAP instrument design incorporates an L-band radar (3 km) and an L band radiometer (40 km) sharing a single 6-meter rotating mesh antenna to provide measurements of soil moisture and landscape freeze/thaw state [2]. These observations would (1) improve our understanding of linkages between the Earth's water, energy, and carbon cycles, (2) benefit many application areas including numerical weather and climate prediction, flood and drought monitoring, agricultural productivity, human health, and national security, (3) help to address priority questions on climate change, and (4) potentially provide continuity with brightness temperature and soil moisture measurements from ESA's SMOS (Soil Moisture Ocean Salinity) and NASA's Aquarius missions. In the planned SMAP mission prelaunch time frame, baseline algorithms are being developed for generating (1) soil moisture products both from radiometer measurements on a 36 km grid and from combined radar/radiometer measurements on a 9 km grid, and (2) freeze/thaw products from radar measurements on a 3 km grid. These retrieval algorithms need a variety of global ancillary data, both static and dynamic, to run the retrieval models, constrain the retrievals, and provide flags for indicating retrieval quality. The choice of which ancillary dataset to use for a particular SMAP product would be based on a number of factors, including its availability and ease of use, its inherent error and resulting impact on the overall soil moisture or freeze/thaw retrieval accuracy, and its compatibility with similar choices made by the SMOS mission. All decisions regarding SMAP ancillary data sources would be fully documented by the SMAP Project and made available to the user community.
Comparing SMAP to Macro-scale and Hyper-resolution Land Surface Models over Continental U. S.
NASA Astrophysics Data System (ADS)
Pan, Ming; Cai, Xitian; Chaney, Nathaniel; Wood, Eric
2016-04-01
SMAP sensors collect moisture information in top soil at the spatial resolution of ~40 km (radiometer) and ~1 to 3 km (radar, before its failure in July 2015). Such information is extremely valuable for understanding various terrestrial hydrologic processes and their implications on human life. At the same time, soil moisture is a joint consequence of numerous physical processes (precipitation, temperature, radiation, topography, crop/vegetation dynamics, soil properties, etc.) that happen at a wide range of scales from tens of kilometers down to tens of meters. Therefore, a full and thorough analysis/exploration of SMAP data products calls for investigations at multiple spatial scales - from regional, to catchment, and to field scales. Here we first compare the SMAP retrievals to the Variable Infiltration Capacity (VIC) macro-scale land surface model simulations over the continental U. S. region at 3 km resolution. The forcing inputs to the model are merged/downscaled from a suite of best available data products including the NLDAS-2 forcing, Stage IV and Stage II precipitation, GOES Surface and Insolation Products, and fine elevation data. The near real time VIC simulation is intended to provide a source of large scale comparisons at the active sensor resolution. Beyond the VIC model scale, we perform comparisons at 30 m resolution against the recently developed HydroBloks hyper-resolution land surface model over several densely gauged USDA experimental watersheds. Comparisons are also made against in-situ point-scale observations from various SMAP Cal/Val and field campaign sites.
Progress in the Phase 0 Model Development of a STAR Concept for Dynamics and Control Testing
NASA Technical Reports Server (NTRS)
Woods-Vedeler, Jessica A.; Armand, Sasan C.
2003-01-01
The paper describes progress in the development of a lightweight, deployable passive Synthetic Thinned Aperture Radiometer (STAR). The spacecraft concept presented will enable the realization of 10 km resolution global soil moisture and ocean salinity measurements at 1.41 GHz. The focus of this work was on definition of an approximately 1/3-scaled, 5-meter Phase 0 test article for concept demonstration and dynamics and control testing. Design requirements, parameters and a multi-parameter, hybrid scaling approach for the dynamically scaled test model were established. The El Scaling Approach that was established allows designers freedom to define the cross section of scaled, lightweight structural components that is most convenient for manufacturing when the mass of the component is small compared to the overall system mass. Static and dynamic response analysis was conducted on analytical models to evaluate system level performance and to optimize panel geometry for optimal tension load distribution.
NASA Technical Reports Server (NTRS)
Brown, Todd S.
2016-01-01
The NASA Soil Moisture Active Passive (SMAP) spacecraft was designed to use radar and radiometer measurements to produce global soil moisture measurements every 2-3 days. The SMAP spacecraft is a complicated dual-spinning design with a large 6 meter deployable mesh reflector mounted on a platform that spins at 14.6 rpm while the Guidance Navigation and Control algorithms maintain precise nadir pointing for the de-spun portion of the spacecraft. After launching in early 2015, the Guidance Navigation and Control software and hardware aboard the SMAP spacecraft underwent an intensive spacecraft checkout and commissioning period. This paper describes the activities performed by the Guidance Navigation and Control team to confirm the health and phasing of subsystem hardware and the functionality of the guidance and control modes and algorithms. The operations tasks performed, as well as anomalies that were encountered during the commissioning, are explained and results are summarized.
Arthur, Jonathan M.; Johnson, Michael J.; Mayers, C. Justin; Andraski, Brian J.
2012-11-13
This report describes micrometeorological, evapotranspiration, and soil-moisture data collected since 2006 at the Amargosa Desert Research Site adjacent to a low-level radio-active waste and hazardous chemical waste facility near Beatty, Nevada. Micrometeorological data include precipitation, solar radiation, net radiation, air temperature, relative humidity, saturated and ambient vapor pressure, wind speed and direction, barometric pressure, near-surface soil temperature, soil-heat flux, and soil-water content. Evapotranspiration (ET) data include latent-heat flux, sensible-heat flux, net radiation, soil-heat flux, soil temperature, air temperature, vapor pressure, and other principal energy-budget data. Soil-moisture data include periodic measurements of volumetric water-content at experimental sites that represent vegetated native soil, devegetated native soil, and simulated waste disposal trenches - maximum measurement depths range from 5.25 to 29.25 meters. All data are compiled in electronic spreadsheets that are included with this report.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Snyder, M.A.; Kueppers, L.M.; Sloan, L.C.
In the western United States, more than 30,500 square miles has been converted to irrigated agriculture and urban areas. This study compares the climate responses of four regional climate models (RCMs) to these past land-use changes. The RCMs used two contrasting land cover distributions: potential natural vegetation, and modern land cover that includes agriculture and urban areas. Three of the RCMs represented irrigation by supplementing soil moisture, producing large decreases in August mean (-2.5 F to -5.6 F) and maximum (-5.2 F to -10.1 F) 2-meter temperatures where natural vegetation was converted to irrigated agriculture. Conversion to irrigated agriculture alsomore » resulted in large increases in relative humidity (9 percent 36 percent absolute change). Only one of the RCMs produced increases in summer minimum temperature. Converting natural vegetation to urban land cover produced modest but discernable climate effects in all models, with the magnitude of the effects dependent upon the preexisting vegetation type. Overall, the RCM results indicate that land use change impacts are most pronounced during the summer months, when surface heating is strongest and differences in surface moisture between irrigated land and natural vegetation are largest. The irrigation effect on summer maximum temperatures is comparable in magnitude (but opposite in sign) to predicted future temperature change due to increasing greenhouse gas concentrations.« less
Rathgeber, J; Züchner, K; Kietzmann, D; Weyland, W
1995-04-01
Heat and moisture exchangers (HME) are used as artificial noses for intubated patients to prevent tracheo-bronchial or pulmonary damage resulting from dry and cold inspired gases. HME are mounted directly on the tracheal tube, where they collect a large fraction of the heat and moisture of the expired air, adding this to the subsequent inspired breath. The effective performance depends on the water-retention capacity of the HME: the amount of water added to the inspired gas cannot exceed the stored water uptake of the previous breath. This study evaluates the efficiency of four different HME under laboratory and clinical conditions using a new moisture-measuring device. METHODS. In a first step, the absolute efficiency of four different HME (DAR Hygrobac, Gibeck Humid-Vent 2P, Pall BB 22-15 T, and Pall BB 100) was evaluated using a lung model simulating physiological heat and humidity conditions of the upper airways. The model was ventilated with tidal volumes of 500, 1,000, and 1,500 ml and different flow rates. The water content of the ventilated air was determined between tracheal tube and HME using a new high-resolution humidity meter and compared with the absolute water loss of the exhaled air at the gas outlet of a Siemens Servo C ventilator measured with a dew-point hygrometer. Secondly, the moisturizing efficiency was evaluated under clinical conditions in an intensive care unit with 25 intubated patients. Maintaining the ventilatory conditions for each patient, the HME were randomly changed. The humidity data were determined as described above and compared with the laboratory findings. RESULTS AND DISCUSSION. The water content at the respirator outlet is inversely equivalent to the humidity of the inspired gases and represents the water loss from the respiratory tract if the patient is ventilated with dry gases. Moisture retention and heating capacity decreased with higher volumes and higher flow rates. These data are simple to obtain without affecting the patient and can easily be interpreted. It was demonstrated that, compared to physiological conditions, the DAR Hygrobac and Gibeck Humid Vent 2P-HME coated with hygroscopic salts-were able to maintain sufficient inspiratory humidity and heat. The Pall-HME, solely a condensation humidifier, did not meet the physiological requirements.
Principal Components of Thermography analyses of the Silk Tomb, Petra (Jordan)
NASA Astrophysics Data System (ADS)
Gomez-Heras, Miguel; Alvarez de Buergo, Monica; Fort, Rafael
2015-04-01
This communication presents the results of an active thermography survey of the Silk Tomb, which belongs to the Royal Tombs compound in the archaeological city of Petra in Jordan. The Silk Tomb is carved in the variegated Palaeozoic Umm Ishrin sandstone and it is heavily backweathered due to surface runoff from the top of the cliff where it is carved. Moreover, the name "Silk Tomb" was given because of the colourful display of the variegated sandstone due to backweathering. A series of infrared images were taken as the façade was heated by sunlight to perform a Principal Component of Thermography analyses with IR view 1.7.5 software. This was related to indirect moisture measurements (percentage of Wood Moisture Equivalent) taken across the façade, by means of a Protimeter portable moisture meter. Results show how moisture retention is deeply controlled by lithological differences across the façade. Research funded by Geomateriales 2 S2013/MIT-2914 and CEI Moncloa (UPM, UCM, CSIC) through a PICATA contract and the equipment from RedLAbPAt Network
Grain quality inspection system
NASA Technical Reports Server (NTRS)
Flood, C. A., Jr.; Singletow, D. P.; James, S. N.
1979-01-01
A review of grain quality indicators and measurement methods was conducted in order to assess the feasibility of using remote sensing technology to develop a continuous monitoring system for use during grain transfer operations. Most detection methods were found to be too slow or too expensive to be incorporated into the normal inspection procedure of a grain elevator on a continuous basis. Two indicators, moisture content and broken corn and foreign material, show potential for automation and are of an economic value. A microprocessor based system which utilizes commercially available electronic moisture meter was developed and tested. A method for automating BCFM measurement is described. A complete system description is presented along with performance test results.
Differential atmospheric tritium sampler
Griesbach, Otto A.; Stencel, Joseph R.
1990-01-01
An atmospheric tritium sampler is provided which uses a carrier gas comprised of hydrogen gas and a diluting gas, mixed in a nonexplosive concentration. Sample air and carrier gas are drawn into and mixed in a manifold. A regulator meters the carrier gas flow to the manifold. The air sample/carrier gas mixture is pulled through a first moisture trap which adsorbs water from the air sample. The mixture then passes through a combustion chamber where hydrogen gas in the form of H.sub.2 or HT is combusted into water. The manufactured water is transported by the air stream to a second moisture trap where it is adsorbed. The air is then discharged back into the atmosphere by means of a pump.
Passive Microwave Measurements Over Conifer Forests at L-Band and C-Band
NASA Technical Reports Server (NTRS)
LeVine, D. M.; Lang, R.; Chauhan, N.; Kim, E.; Bidwell, S.; Goodberlet, M.; Haken, M.; deMatthaeis, P.
2000-01-01
Measurements have been made at L-band and C-band over conifer forests in Virginia to study the response of passive microwave instruments to biomass and soil moisture. A series of aircraft measurements were made in July, August and November, 1999 over relatively homogenous conifer forests of varying biomass. Three radiometers participated in these measurements. These were: 1) the L-band radiometer ESTAR, a horizontally polarized synthetic aperture radiometer which has been used extensively in past measurements of soil moisture; 2) the L-band radiometer SLFMR, a vertically polarized cross-track scanner which has been used successfully in the past for mapping sea surface salinity; and 3) The ACMR, a new C-band radiometer which operates at V- and H-polarization and in the configuration for these experiments did not scan. All three radiometers were flown on the NASA P-3 aircraft based at the Goddard Space Flight Center's Wallops Flight Facility. The ESTAR and SLFMR were mounted in the bomb bay of the P-3 and imaged across track whereas the ACMR was mounted to look aft at 54 degrees up from nadir. Data was collected at altitudes of 915 meters and 457 meters. The forests consisted of relatively homogeneous "managed" stands of conifer located near Waverly, Virginia. This is a relatively flat area about 30 miles southeast of Richmond, VA with numerous stands of trees being grown for the forestry industry. The stands selected for study consisted of areas of regrowth and mature stands of pine. In addition, a small stand of very large trees was observed. Soil moisture sampling was done in each stand during the aircraft over flights. Data was collected on July 7, August 27, November 15 and November 30, 1999. Measurements were made with ESTAR on all days. The ACMR flew on the summer missions and the SLFMR was present only on the August 27 flight. Soil moisture varied from quite dry on July 7 to quite moist on November 30 (which was shortly after a period of rain). The microwave images clearly distinguish between the different forest stands. Research is continuing to seek a quantitative correlation with biomass and surface soil moisture.
Brandburg Prominance, Namibia, Africa
1993-01-19
STS054-151-009 (13-19 Jan 1993) --- This large format camera's view shows the circular volcanic structure of the Brandberg mountain, which at 2630 meters (8,550 feet) is the highest point in the new nation of Namibia. The Brandberg is a major feature in the very arid Namib Desert on Africa's southwest coast. Coastal fog brings some moisture to the driest parts of the desert.
Code of Federal Regulations, 2010 CFR
2010-07-01
....5 sample collection filter is weighed (after moisture and temperature conditioning) before and after... ambient temperature and pressure and the sampling time. The mass concentrations of both PM10c and PM2.5 in... in micrograms per cubic meter (µg/m3)at local temperature and pressure conditions. The mass...
USDA-ARS?s Scientific Manuscript database
Vera et al. (2009) compared estimates of soil profile water content (mm) to a depth of 0.8 m made with the neutron moisture meter (NMM) and a multi-depth capacitance probe (MDCP), using measurements replicated in four drainage lysimeters (5 m x 5 m x 1.5-m deep). The NMM estimates of water content w...
Zundel, J; Ansari, S A; Trivedi, H M; Masters, J G; Mascaro, S
2018-05-07
The purpose of this research is to characterize the effects of mouthwash solutions on oral friction and moisture using a quantitative in vitro approach. The frictional coefficient of in vitro porcine tongue samples was measured using a magnetic levitation haptic device equipped with a custom tactor designed to mimic human skin. A commercially available moisture meter was used to measure moisture content of the samples. Tongue samples were first tested before treatment, then after application of saliva (either human or artificial), and again after application of 1 of 11 different mouthwash solutions. The data indicate that the samples treated with artificial saliva vs real saliva have comparable friction coefficient and moisture content. Furthermore, the moisture and friction coefficient remain relatively constant for up to 60 minutes after exposure to ambient conditions. Samples treated with artificial saliva have an average friction coefficient in the range of 0.70-0.80. Application of mouthwash solutions produced an average friction coefficient of 0.39-0.49 but retained the high moisture content of the artificial salivary layer. Several mouthwash solutions resulted in statistically significant differences in the friction coefficient relative to each other. The results of this study demonstrate that a magnetic levitation device can be an effective tool for in vitro oral tribology and that artificial saliva is an effective substitute for real saliva in extended in vitro experiments. The application of mouthwash generally reduces the coefficient of friction of the tongue samples while preserving a relatively high moisture level, and some mouthwashes reduce friction significantly more than others. © 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
NASA Astrophysics Data System (ADS)
Troch, Peter A.; Pangle, Luke; Niu, Guo-Yue; Dontsova, Katerina; Barron-Gafford, Greg; van Haren, Joost; Pavao-Zuckerman, Mitch
2014-05-01
The Landscape Evolution Observatory (LEO) at Biosphere 2-The University of Arizona consists of three identical, sloping, 333 m2 convergent landscapes inside a 5,000 m2 environmentally controlled facility. These engineered landscapes contain 1-meter depth of basaltic tephra, ground to homogenous loamy sand that will undergo physical, chemical, and mineralogical changes over many years. Each landscape contains a spatially dense sensor and sampler network capable of resolving meter-scale lateral heterogeneity and sub-meter scale vertical heterogeneity in moisture, energy and carbon states and fluxes. The density of sensors and frequency at which they can be polled allows for data collection at spatial and temporal scales that are impossible in natural field settings. Embedded solution and gas samplers allow for quantification of biogeochemical processes, and facilitate the use of chemical tracers to study water movement at very high spatial resolutions. Each ~600 metric ton landscape has load cells embedded into the structure to measure changes in total system mass with 0.05% full-scale repeatability (equivalent to less than 1 cm of precipitation). This facilitates the real time accounting of hydrological partitioning at the hillslope scale. Each hillslope is equipped with an engineered rain system capable of raining at rates between 3 and 45 mm/hr in a range of spatial patterns. The rain systems are capable of creating long-term steady state conditions or running complex simulations. The precipitation water supply storage system is flexibly designed to facilitate addition of tracers at constant or time-varying rates for any of the three hillslopes. This presentation will discuss detection of early landscape evolution in terms of hydrological, geochemical and microbial processes through controlled experimentation, data analysis, and numerical modeling during the commissioning phase of the first hillslope at LEO.
NASA Astrophysics Data System (ADS)
Vun, R. Y.; Hoover, K.; Janowiak, J.; Bhardwaj, M.
2008-01-01
Numerous handheld moisture meters are available for measuring moisture levels of wood and building materials for a vast range of quality control and moisture diagnosis applications. However, many methods currently available require physical contact of a probe with the test material to operate. The contact requirement of such devices has limited applications for these purposes. There is a tremendous demand for dynamic online quality assessment of in-process materials for moisture content (MC) measurements. In this paper, a non-destructive non-contact ultrasound technology was used to evaluate the effects of increasing temperature in two MC levels and of increasing MC in lumber. The results show that the ultrasonic absolute transmittance and velocity parameters are directly correlated very well (R2≥0.87) with temperature for the two moisture levels in wood. At constant temperature, however, the velocity is inversely correlated with MC. It was also found that the distribution of MC along the length is marginally insignificant to both ultrasonic measurements. The transmittance measurement along the orthogonal thickness direction is insignificant above the fiber saturation MC; similarly, the velocity measurement is marginally insignificant. The study concludes a positive correlation and a good fit for this technology to advance into the development of an automated device for determining wood moisture levels, which will in turn be used to control the dynamics of wood drying/sterilization processes. Further calibration research is recommended to ascertain the constraints and limitations of the technology to specific wood species and dimension.
NASA Astrophysics Data System (ADS)
Percy, M.; Singha, K.; Benninger, L. K.; Riveros-Iregui, D. A.; Mirus, B. B.
2015-12-01
The spatial and temporal distribution of soil moisture in tropical critical zones depends upon a number of variables including topographic position, soil texture, overlying vegetation, and local microclimates. We investigate the influences on soil moisture on a tropical basaltic island (San Cristóbal, Galápagos) across a variety of microclimates during the transition from the wetter to the drier season. We used multiple approaches to characterize spatial and temporal patterns in soil moisture at four sites across microclimates ranging from arid to very humid. The microclimates on San Cristóbal vary with elevation, so our monitoring includes two sites in the transitional zone at lower elevations, one in the humid zone at moderate elevations, and one in the very humid zone in higher elevations. We made over 250 near-surface point measurements per site using a Hydrosense II probe, and estimated the lateral variability in soil moisture across each site with an EM-31 electrical conductivity meter. We also monitored continuous time-series of in-situ soil moisture dynamics using three nested TDR probes collocated with meteorological stations at each of the sites. Preliminary analysis indicates that soils in the very humid zone have lower electrical conductivities across all the hillslopes as compared to the humid and transitional zones, which suggests that additional factors beyond climate and slope position are important. While soil texture across the very humid site is fairly uniform, variations in vegetation have a strong control on soil moisture patterns. At the remaining sites the vegetation patterns also have a very strong local influence on soil moisture, but correlation between the depth to clay layers and soil moisture patterns suggests that mineralogy is also important. Our findings suggest that the microclimatic setting is a crucial consideration for understanding relations between vegetation, soil texture, and soil-moisture dynamics in tropical critical zones.
In situ soil moisture and matrix potential - what do we measure?
NASA Astrophysics Data System (ADS)
Jackisch, Conrad; Durner, Wolfgang
2017-04-01
Soil moisture and matric potential are often regarded as state variables that are simple to monitor at the Darcy-scale. At the same time unproven believes about the capabilities and reliabilities of specific sensing methods or sensor systems exist. A consortium of ten institutions conducted a comparison study of currently available sensors for soil moisture and matrix potential at a specially homogenised field site with sandy loam soil, which was kept free of vegetation. In total 57 probes of 15 different systems measuring soil moisture, and 50 probes of 14 different systems measuring matric potential have been installed in a 0.5 meter grid to monitor the moisture state in 0.2 meter depth. The results give rise to a series of substantial questions about the state of the art in hydrological monitoring, the heterogeneity problem and the meaning of soil water retention at the field scale: A) For soil moisture, most sensors recorded highly plausible data. However, they do not agree in absolute values and reaction timing. For matric potential, only tensiometers were able to capture the quick reactions during rainfall events. All indirect sensors reacted comparably slowly and thus introduced a bias with respect to the sensing of soil water state under highly dynamic conditions. B) Under natural field conditions, a better homogeneity than in our setup can hardly be realised. While the homogeneity assumption held for the first weeks, it collapsed after a heavy storm event. The event exceeded the infiltration capacity, initiated the generation of redistribution networks at the surface, which altered the local surface properties on a very small scale. If this is the reality at a 40 m2 plot, what representativity have single point observations referencing the state of whole basins? C) A comparison of in situ and lab-measured retention curves marks systematic differences. Given the general practice of soil water retention parameterisation in almost any hydrological model this poses quite some concern about deriving field parameters from lab measurements. We will present some insights from the comparison study and highlight the conceptual concerns arising from it. Through this we hope to stimulate a discussion towards more critical revision of measurement assumptions and towards the development of alternative techniques to monitor subsurface states. The sensor comparison study consortium is a cooperation of Wolfgang Durner2, Ines Andrä2, Kai Germer2, Katrin Schulz2, Marcus Schiedung2, Jaqueline Haller-Jans2, Jonas Schneider2, Julia Jaquemotte2, Philipp Helmer2, Leander Lotz2, Thomas Graeff3, Andreas Bauer3, Irene Hahn3, Conrad Jackisch1, Martin Sanda4, Monika Kumpan5, Johann Dorner5, Gerrit de Rooij6, Stephan Wessel-Bothe7, Lorenz Kottmann8, and Siegfried Schittenhelm8. The great support by the team and the Thünen Institute Braunschweig is gratefully acknowledged. 1 Karlsruhe Institute of Technology, 2 Technical University of Braunschweig, 3 University of Potsdam, 4 Technical University of Prague, 5 Federal Department for Water Management Petzenkirchen, 6 Helmholtz Centre for Environmental Research Halle, 7 ecoTech GmbH Bonn, 8 Julius Kühn Institute Braunschweig
Rapid Intensification of Hurricane Irma Seen in New SMAP Wind Images
2017-09-05
This pair of images shows ocean surface wind speeds for Hurricane Irma as observed at 5:26 a.m. EDT on Sept. 4, 2017 (top) and 24.5 hours later at 6:02 a.m. EDT on September 5th (bottom) by the radiometer instrument on NASA's Soil Moisture Active Passive (SMAP) satellite. Color indicates wind speed, with red being highest and blue lowest. Irma intensified from a Category 2 hurricane on Sept. 4 with observed wind speed of 106 miles per hour (47.5 meters per second) to a Category 5 hurricane on Sept. 5 with a maximum observed wind speed of 160 miles per hour (71.4 meters per second). https://photojournal.jpl.nasa.gov/catalog/PIA21939
NASA Astrophysics Data System (ADS)
Zhu, Qing; Liao, Kaihua; Doolittle, James; Lin, Henry
2014-05-01
Hydropedological dynamics including soil moisture variation, subsurface flow, and spatial distributions of different soil properties are important parameters in ecological, environmental, hydrological, and agricultural modeling and applications. However, technical gap exists in mapping these dynamics at intermediate spatial scale (e.g., farm and catchment scales). At intermediate scales, in-situ monitoring provides detailed data, but is restricted in number and spatial coverage; while remote sensing provides more acceptable spatial coverage, but has comparatively low spatial resolution, limited observation depths, and is greatly influenced by the surface condition and climate. As a non-invasive, fast, and convenient geophysical tool, electromagnetic induction (EMI) measures soil apparent electrical conductivity (ECa) and has great potential to bridge this technical gap. In this presentation, principles of different EMI meters are briefly introduced. Then, case studies of using repeated EMI to detect spatial distributions of subsurface convergent flow, soil moisture dynamics, soil types and their transition zones, and different soil properties are presented. The suitability, effectiveness, and accuracy of EMI are evaluated for mapping different hydropedological dynamics. Lastly, contributions of different hydropedological and terrain properties on soil ECa are quantified under different wetness conditions, seasons, and land use types using Classification and Regression Tree model. Trend removal and residual analysis are then used for further mining of EMI survey data. Based on these analyses, proper EMI survey designs and data processing are proposed.
NASA Astrophysics Data System (ADS)
Pribulick, C. E.; Maxwell, R. M.; Williams, K. H.; Carroll, R. W. H.
2014-12-01
Prediction of environmental response to global climate change is paramount for regions that rely upon snowpack for their dominant water supply. Temperature increases are anticipated to be greater at higher elevations perturbing hydrologic systems that provide water to millions of downstream users. In this study, the relationships between large-scale climatic change and the corresponding small-scale hydrologic processes of mountainous terrain are investigated in the East River headwaters catchment near Gothic, CO. This catchment is emblematic of many others within the upper Colorado River Basin and covers an area of 250 square kilometers, has a topographic relief of 1420 meters, an average elevation of 3266 meters and has varying stream characteristics. This site allows for the examination of the varying effect of climate-induced changes on the hydrologic response of three different characteristic components of the catchment: a steep high-energy mountain system, a medium-grade lower-energy system and a low-grade low-energy meandering floodplain. To capture the surface and subsurface heterogeneity of this headwaters system the basin has been modeled at a 10-meter resolution using ParFlow, a parallel, integrated hydrologic model. Driven by meteorological forcing, ParFlow is able to capture land surface processes and represents surface and subsurface interactions through saturated and variably saturated heterogeneous flow. Data from Digital Elevation Models (DEMs), land cover, permeability, geologic and soil maps, and on-site meteorological stations, were prepared, analyzed and input into ParFlow as layers with a grid size comprised of 1403 by 1685 cells to best represent the small-scale, high resolution model domain. Water table depth, soil moisture, soil temperature, snowpack, runoff and local energy budget values provide useful insight into the catchments response to the Intergovernmental Panel on Climate Change (IPCC) temperature projections. In the near term, coupling this watershed model with one describing a diverse suite of subsurface elemental cycling pathways, including carbon and nitrogen, will provide an improved understanding of the response of the subsurface ecosystems to hydrologic transitions induced as a result of global climate change.
Ryan, Barbara J.
1989-01-01
Ten years of hydrologic research have been conducted by the U.S. Geological Survey at a commercial low-level radioactive-waste disposal site near Sheffield, Illinois. Research included studies of microclimate, evapotranspiration, and tritium release by plants; runoff and land modification; water movement through a trench cover; water and tritium movement in the unsaturated zone; gases in the unsaturated zone; water and tritium movement in the saturated zone; and water chemistry. Implications specific to each research topic and those based on overlapping research topics are summarized as to their potential effect on the selection, characterization, design, operation, and decommissioning processes of future low-level radioactive-waste disposal sites. Unconsolidated deposits at the site are diverse in lithologic character and are spatially and stratigraphically complex. Thickness of these Quaternary deposits ranges from 3 to 27 meters and averages 17 meters. The unconsolidated deposits overlay 140 meters of Pennsylvanian shale, mudstone, siltstone, and coal. Approximately 90,500 cubic meters of waste were buried from August 1967 through August 1978, in 21 trenches that were constructed in glacial materials by using a cut-and-fill process. Trenches generally were constructed below grade and ranged from 11 to 180 meters long, 2.4 to 21 meters wide, and 2.4 to about 7.9 meters deep. Research on microclimate and evapotranspiration at the site was conducted from July 1982 through June 1984. Continuous measurements were made of precipitation, incoming and reflected solar (shortwave) radiation, incoming and emitted terrestrial (longwave) radiation, horizontal windspeed and direction, wet- and dry-bulb air temperature, barometric pressure, soil-heat fluxes, and soil temperature. Soil-moisture content, for this research phase, was measured approximately biweekly. Evapotranspiration rates were estimated by using three techniques--energy budget, aerodynamic profile, and water budget. Although monthly totals for each method differed, estimated annual evapotranspiration averages ranged from 630 to 693 millimeters or about 70 percent of precipitation. Tritium concentrations in leaf water from on-site plants were determined for 125 vegetation samples collected during the summers of 1982 through 1986. Concentrations varied significantly among some locations and plant types. Tritium concentrations ranged from the detection limit of 0 .2 to 1,330 nanocuries per liter, with alfalfa (Medicago sativa) having the highest concentrations, followed by brome grass (Bromus inermis), and then red clover (Trifoleum pratense); these variations in concentration are most likely a result of root depth. Runoff and sediment transport were measured from July 1982 through December 1985 in four basins--three comprising almost two-thirds of the 8.1-hectare site and one comprising a 1.4-hectare undisturbed area. Volumes and equivalent weights of collapses were estimated from records of site surficial conditions from October 1978 through December 1985. Runoff showed a direct relation to degree of land modification; lowest mean yields were measured at the undisturbed area, and highest mean yields were measured from the basin composed wholly of trench and intertrench areas. Sediment yield measured onsite averaged 3.4 megagrams per hectare. A total of 315 collapse cavities, corresponding to a cumulative volume of about 500 cubic meters, were documented. Most collapses were recorded after periods of rainfall or snowmelt when soil moisture was near maximum. Almost two-thirds of the collapses, corresponding to 63 percent of the cumulative cavity volume, occurred during February through April. Data for the study of water movement through a trench cover were collected from July 1982 through June 1934. Pressure-head data were collected at four different clusters at depths ranging from 50 to 1,850 millimeters within a selected trench cover. Soil-moisture content f
NASA Astrophysics Data System (ADS)
Lukowski, Mateusz; Usowicz, Boguslaw; Sagan, Joanna; Szlazak, Radoslaw; Gluba, Lukasz; Rojek, Edyta
2017-04-01
Soil moisture is an important parameter in many environmental studies, as it influences the exchange of water and energy at the interface between the land surface and the atmosphere. Accurate assessment of the soil moisture spatial and temporal variations is crucial for numerous studies; starting from a small scale of single field, then catchment, mesoscale basin, ocean conglomeration, finally ending at the global water cycle. Despite numerous advantages, such as fine accuracy (undisturbed by clouds or daytime conditions) and good temporal resolution, passive microwave remote sensing of soil moisture, e.g. SMOS and SMAP, are not applicable to a small scale - simply because of too coarse spatial resolution. On the contrary, thermal infrared-based methods of soil moisture retrieval have a good spatial resolution, but are often disturbed by clouds and vegetation interferences or night effects. The methods that base on point measurements, collected in situ by monitoring stations or during field campaigns, are sometimes called "ground truth" and may serve as a reference for remote sensing, of course after some up-scaling and approximation procedures that are, unfortunately, potential source of error. Presented research concern attempt to synergistic approach that join two remote sensing methods: passive microwave and thermal infrared, supported by in situ measurements. Microwave brightness temperature of soil was measured by ELBARA, the radiometer at 1.4 GHz frequency, installed at 6 meters high tower at Bubnow test site in Poland. Thermal inertia around the tower was modelled using the statistical-physical model whose inputs were: soil physical properties, its water content, albedo and surface temperatures measured by an infrared pyrometer, directed at the same footprint as ELBARA. The results coming from this method were compared to in situ data obtained during several field campaigns and by the stationary agrometeorological stations. The approach seems to be reasonable, as both variables, brightness temperature and thermal inertia, strongly depend on soil moisture. Despite the fact that the presented research focused on modelling in the small size, 4 ha test site, the method is promising for larger scales as well, due to similarities between ELBARA and SMOS and between pyrometer and satellite imaging spectrometers (Landsat, Sentinel etc.). The approach will merge advantages: high accuracy of passive microwave sensing with a good spatial resolution of thermal infrared methods. The work was partially funded under two ESA projects: 1) "ELBARA_PD (Penetration Depth)" No. 4000107897/13/NL/KML, funded by the Government of Poland through an ESA-PECS contract (Plan for European Cooperating States). 2) "Technical Support for the fabrication and deployment of the radiometer ELBARA-III in Bubnow, Poland" No. 4000113360/15/NL/FF/gp.
Radar systems for the water resources mission. Volume 4: Appendices E-I
NASA Technical Reports Server (NTRS)
Moore, R. K.; Claassen, J. P.; Erickson, R. L.; Fong, R. K. T.; Hanson, B. C.; Komen, M. J.; Mcmillan, S. B.; Parashar, S. K.
1976-01-01
The use of a scanning antenna beam for a synthetic aperture system was examined. When the resolution required was modest, the radar did not use all the time the beam was passing a given point on the ground to build a synthetic aperture, so time was available to scan the beam to other positions and build several images at different ranges. The scanning synthetic-aperture radar (SCANSAR) could achieve swathwidths of well over 100 km with modest antenna size. Design considerations for a SCANSAR for hydrologic parameter observation are presented. Because of the high sensitivity to soil moisture at angles of incidence near vertical, a 7 to 22 deg swath was considered for that application. For snow and ice monitoring, a 22 to 37 deg scan was used. Frequencies from X-band to L-band were used in the design studies, but the proposed system operated in C-band at 4.75 GHz. It achieved an azimuth resolution of about 50 meters at all angles, with a range resolution varying from 150 meters at 7 deg to 31 meters at 37 deg. The antenna required an aperture of 3 x 4.16 meters, and the average transmitter power was under 2 watts.
NASA Technical Reports Server (NTRS)
Palm, Stephen P.; Miller, David O.; Schwemmer, Geary
2000-01-01
A new technique combining active and passive remote sensing instruments for the estimation of surface latent heat flux over the ocean is presented. This synergistic method uses aerosol lidar backscatter data, multi-channel infrared radiometer data and microwave scatterometer data acquired onboard the NASA P-3B research aircraft during an extended field campaign over the Atlantic ocean in support of the Lidar In-space Technology Experiment (LITE) in September of 1994. The 10 meter wind speed derived from the scatterometers and the lidar-radiometer inferred near-surface moisture are used to obtain an estimate of the surface flux of moisture via bulk aerodynamic formulae. The results are compared with the Special Sensor Microwave Imager (SSM/I) daily average latent heat flux and show reasonable agreement with an rms error and bias of about 50 and 25 W per square meters, respectively. In addition, the MABL height, entrainment zone thickness and integrated lidar backscatter intensity are computed from the lidar data and compared with the magnitude of the surface fluxes. The results show that the surface latent heat flux is most strongly correlated with entrainment zone top, bottom and the integrated MABL lidar backscatter, with corresponding correlation coefficients of 0.62, 0.67 and 0.61, respectively.
NASA Astrophysics Data System (ADS)
Zhang, Y.; Schaap, M. G.
2012-12-01
Over the past fifteen years, the University of Arizona has carried out four controlled infiltration experiments in a 3600 m2, 15 meter deep vadose zone (Maricopa, Arizona) in which the evolution of moisture content (9 wells, 25 cm resolution), and matric potential (27 locations) was monitored and the subsurface stratigraphy, texture (1042 samples), and bulk density (251 samples) was characterized. In order to simulate the subsurface moisture dynamics it is necessary to define the 3D structure of the subsurface hydraulic characteristics (i.e. moisture retention and hydraulic functions). Several simple to complex strategies are possible ranging from stratigraphy based layering using hydraulic parameters derived from core samples to sophisticated numerical inversions based on 3D geostatistics and site-specific pedotransfer functions. A range of approaches will be evaluated on objective metrics that quantify how well the observed moisture dynamics are matched by simulations. We will evaluate the worth of auxiliary data such as observed matric potentials and quantity the number of texture samples needed to arrive at effective descriptions of subsurface structure. In addition, we will discuss more subjective metrics that evaluate the relative effort involved and estimate monetary cost of each method. While some of the results will only be valid for the studied site, some general conclusions will be possible about the effectiveness of particular methods for other semi-arid sites.
NASA Astrophysics Data System (ADS)
Mallet, Florian; Marc, Vincent; Douvinet, Johnny; Rossello, Philippe; Le Bouteiller, Caroline; Malet, Jean-Philippe
2016-04-01
Soil moisture is a key parameter that controls runoff processes at the watershed scale. It is characterized by a high area and time variability, controlled by site properties such as soil texture, topography, vegetation cover and climate. Several recent studies showed that changes in water storage was a key variable to understand the distribution of water residence time and the shape of flood's hydrograph (McDonnell and Beven, 2014; Davies and Beven, 2015). Knowledge of high frequency soil moisture variation across scales is a prerequisite for better understanding the areal distribution of runoff generation. The present study has been carried out in the torrential Draix-Bléone's experimental catchments, where water storage processes are expected to occur mainly on the first meter of soil. The 0,86 km2 Laval marly torrential watershed has a peculiar hydrological behavior during flood events with specific discharge among the highest in the world. To better understand the Laval internal behavior and to identify explanatory parameters of runoff generation, additional field equipment has been setup in sub-basins with various land use and morphological characteristics. From fall 2015 onwards this new instrumentation helped to supplement the routine measurements (rainfall rate, streamflow) and to develop a network of high frequency soil water content sensors (moisture probes, mini lysimeter). Data collected since early May and complementary measurement campaigns (itinerant soil moisture measurements, geophysical measurements) make it now possible to propose a soil water content mapping procedure. We use the LISDQS spatial extrapolation model based on a local interpolation method (Joly et. al, 2008). The interpolation is carried out from different geographical variables which are derived from a high resolution DEM (1m LIDAR) and a land cover image. Unlike conventional interpolation procedure, this method takes into account local forcing parameters such as slope, aspect, soil type or land use. Eventually, the model gives insight into a catchment scale distributed high frequency soil moisture dynamics. This analysis is also used to identify the relative impacts of the morphological determinants on soil moisture content. References : McDonnell, J.J. and K. Beven, 2014. The future of hydrological science: A (common) path forward ? A call to action aimed at understanding velocities, celerities and residence time distributions of the headwater hydrograph. Water Resources Research, 50, 5342-5350. Davies A. C. Davies and K. Beven, 2015. Hysteresis and scale in catchment storage, flow and transport. Hydrological Processes, Volume 29, Issue 16 : 3604-3615. Joly D., Brossard T., Cardot H., Cavailhes J., Hilal M., Wavresky P., 2008. Interpolation par recherche d'information locale. Climatologie, Volume 5 : 27-47.
Stochastic Analysis and Probabilistic Downscaling of Soil Moisture
NASA Astrophysics Data System (ADS)
Deshon, J. P.; Niemann, J. D.; Green, T. R.; Jones, A. S.
2017-12-01
Soil moisture is a key variable for rainfall-runoff response estimation, ecological and biogeochemical flux estimation, and biodiversity characterization, each of which is useful for watershed condition assessment. These applications require not only accurate, fine-resolution soil-moisture estimates but also confidence limits on those estimates and soil-moisture patterns that exhibit realistic statistical properties (e.g., variance and spatial correlation structure). The Equilibrium Moisture from Topography, Vegetation, and Soil (EMT+VS) model downscales coarse-resolution (9-40 km) soil moisture from satellite remote sensing or land-surface models to produce fine-resolution (10-30 m) estimates. The model was designed to produce accurate deterministic soil-moisture estimates at multiple points, but the resulting patterns do not reproduce the variance or spatial correlation of observed soil-moisture patterns. The primary objective of this research is to generalize the EMT+VS model to produce a probability density function (pdf) for soil moisture at each fine-resolution location and time. Each pdf has a mean that is equal to the deterministic soil-moisture estimate, and the pdf can be used to quantify the uncertainty in the soil-moisture estimates and to simulate soil-moisture patterns. Different versions of the generalized model are hypothesized based on how uncertainty enters the model, whether the uncertainty is additive or multiplicative, and which distributions describe the uncertainty. These versions are then tested by application to four catchments with detailed soil-moisture observations (Tarrawarra, Satellite Station, Cache la Poudre, and Nerrigundah). The performance of the generalized models is evaluated by comparing the statistical properties of the simulated soil-moisture patterns to those of the observations and the deterministic EMT+VS model. The versions of the generalized EMT+VS model with normally distributed stochastic components produce soil-moisture patterns with more realistic statistical properties than the deterministic model. Additionally, the results suggest that the variance and spatial correlation of the stochastic soil-moisture variations do not vary consistently with the spatial-average soil moisture.
Satellite Based Soil Moisture Product Validation Using NOAA-CREST Ground and L-Band Observations
NASA Astrophysics Data System (ADS)
Norouzi, H.; Campo, C.; Temimi, M.; Lakhankar, T.; Khanbilvardi, R.
2015-12-01
Soil moisture content is among most important physical parameters in hydrology, climate, and environmental studies. Many microwave-based satellite observations have been utilized to estimate this parameter. The Advanced Microwave Scanning Radiometer 2 (AMSR2) is one of many remotely sensors that collects daily information of land surface soil moisture. However, many factors such as ancillary data and vegetation scattering can affect the signal and the estimation. Therefore, this information needs to be validated against some "ground-truth" observations. NOAA - Cooperative Remote Sensing and Technology (CREST) center at the City University of New York has a site located at Millbrook, NY with several insitu soil moisture probes and an L-Band radiometer similar to Soil Moisture Passive and Active (SMAP) one. This site is among SMAP Cal/Val sites. Soil moisture information was measured at seven different locations from 2012 to 2015. Hydra probes are used to measure six of these locations. This study utilizes the observations from insitu data and the L-Band radiometer close to ground (at 3 meters height) to validate and to compare soil moisture estimates from AMSR2. Analysis of the measurements and AMSR2 indicated a weak correlation with the hydra probes and a moderate correlation with Cosmic-ray Soil Moisture Observing System (COSMOS probes). Several differences including the differences between pixel size and point measurements can cause these discrepancies. Some interpolation techniques are used to expand point measurements from 6 locations to AMSR2 footprint. Finally, the effect of penetration depth in microwave signal and inconsistencies with other ancillary data such as skin temperature is investigated to provide a better understanding in the analysis. The results show that the retrieval algorithm of AMSR2 is appropriate under certain circumstances. This validation algorithm and similar study will be conducted for SMAP mission. Keywords: Remote Sensing, Soil Moisture, AMSR2, SMAP, L-Band.
Soil moisture in sessile oak forest gaps
NASA Astrophysics Data System (ADS)
Zagyvainé Kiss, Katalin Anita; Vastag, Viktor; Gribovszki, Zoltán; Kalicz, Péter
2015-04-01
By social demands are being promoted the aspects of the natural forest management. In forestry the concept of continuous forest has been an accepted principle also in Hungary since the last decades. The first step from even-aged stand to continuous forest can be the forest regeneration based on gap cutting, so small openings are formed in a forest due to forestry interventions. This new stand structure modifies the hydrological conditions for the regrowth. Without canopy and due to the decreasing amounts of forest litter the interception is less significant so higher amount of precipitation reaching the soil. This research focuses on soil moisture patterns caused by gaps. The spatio-temporal variability of soil water content is measured in gaps and in surrounding sessile oak (Quercus petraea) forest stand. Soil moisture was determined with manual soil moisture meter which use Time-Domain Reflectometry (TDR) technology. The three different sizes gaps (G1: 10m, G2: 20m, G3: 30m) was opened next to Sopron on the Dalos Hill in Hungary. First, it was determined that there is difference in soil moisture between forest stand and gaps. Second, it was defined that how the gap size influences the soil moisture content. To explore the short term variability of soil moisture, two 24-hour (in growing season) and a 48-hour (in dormant season) field campaign were also performed in case of the medium-sized G2 gap along two/four transects. Subdaily changes of soil moisture were performed. The measured soil moisture pattern was compared with the radiation pattern. It was found that the non-illuminated areas were wetter and in the dormant season the subdaily changes cease. According to our measurements, in the gap there is more available water than under the forest stand due to the less evaporation and interception loss. Acknowledgements: The research was supported by TÁMOP-4.2.2.A-11/1/KONV-2012-0004 and AGRARKLIMA.2 VKSZ_12-1-2013-0034.
NASA Astrophysics Data System (ADS)
Bogena, H. R.; Metzen, D.; Baatz, R.; Hendricks Franssen, H.; Huisman, J. A.; Montzka, C.; Vereecken, H.
2011-12-01
Measurements of low-energy secondary neutron intensity above the soil surface by cosmic-ray soil moisture probes (CRP) can be used to estimate soil moisture content. CRPs utilise the fact that high-energy neutrons initiated by cosmic rays are moderated (slowed to lower energies) most effectively by collisions with hydrogen atoms contained in water molecules in the soil. The conversion of neutron intensity to soil moisture content can potentially be complicated because neutrons are also moderated by aboveground water storage (e.g. vegetation water content, canopy storage of interception). Recently, it was demonstrated experimentally that soil moisture content derived from CRP measurements agrees well with average moisture content from gravimetric soil samples taken within the footprint of the cosmic ray probe, which is proposed to be up to several hundred meters in size [1]. However, the exact extension and shape of the CRP integration footprint is still an open question and it is also unclear how CRP measurements are affected by the soil moisture distribution within the footprint both in horizontal and vertical directions. In this paper, we will take advantage of an extensive wireless soil moisture sensor network covering most of the estimated footprint of the CRP. The network consists of 150 nodes and 900 soil moisture sensors which were installed in the small forested Wüstebach catchment (~27 ha) in the framework of the Transregio32 and the Helmholtz initiative TERENO (Terrestrial Environmental Observatories) [2]. This unique soil moisture data set provides a consistent picture of the hydrological status of the catchment in a high spatial and temporal resolution and thus the opportunity to evaluate the CRP measurements in a rigorous way. We will present first results of the comparison with a specific focus on the sensitivity of the CRP measurements to soil moisture variation in both the horizontal and vertical direction. Furthermore, the influence of forest biomass and shallow groundwater table fluctuations on the attenuation of cosmic-ray neutrons will be considered.
1-Meter Digital Elevation Model specification
Arundel, Samantha T.; Archuleta, Christy-Ann M.; Phillips, Lori A.; Roche, Brittany L.; Constance, Eric W.
2015-10-21
In January 2015, the U.S. Geological Survey National Geospatial Technical Operations Center began producing the 1-Meter Digital Elevation Model data product. This new product was developed to provide high resolution bare-earth digital elevation models from light detection and ranging (lidar) elevation data and other elevation data collected over the conterminous United States (lower 48 States), Hawaii, and potentially Alaska and the U.S. territories. The 1-Meter Digital Elevation Model consists of hydroflattened, topographic bare-earth raster digital elevation models, with a 1-meter x 1-meter cell size, and is available in 10,000-meter x 10,000-meter square blocks with a 6-meter overlap. This report details the specifications required for the production of the 1-Meter Digital Elevation Model.
NASA Technical Reports Server (NTRS)
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.
Model Performance of Water-Current Meters
Fulford, J.M.; ,
2002-01-01
The measurement of discharge in natural streams requires hydrographers to use accurate water-current meters that have consistent performance among meters of the same model. This paper presents the results of an investigation into the performance of four models of current meters - Price type-AA, Price pygmy, Marsh McBirney 2000 and Swoffer 2100. Tests for consistency and accuracy for six meters of each model are summarized. Variation of meter performance within a model is used as an indicator of consistency, and percent velocity error that is computed from a measured reference velocity is used as an indicator of meter accuracy. Velocities measured by each meter are also compared to the manufacturer's published or advertised accuracy limits. For the meters tested, the Price models werer found to be more accurate and consistent over the range of test velocities compared to the other models. The Marsh McBirney model usually measured within its accuracy specification. The Swoffer meters did not meet the stringent Swoffer accuracy limits for all the velocities tested.
The BlueSky Smoke Modeling Framework: Recent Developments
NASA Astrophysics Data System (ADS)
Sullivan, D. C.; Larkin, N.; Raffuse, S. M.; Strand, T.; ONeill, S. M.; Leung, F. T.; Qu, J. J.; Hao, X.
2012-12-01
BlueSky systems—a set of decision support tools including SmartFire and the BlueSky Framework—aid public policy decision makers and scientific researchers in evaluating the air quality impacts of fires. Smoke and fire managers use BlueSky systems in decisions about prescribed burns and wildland firefighting. Air quality agencies use BlueSky systems to support decisions related to air quality regulations. We will discuss a range of recent improvements to the BlueSky systems, as well as examples of applications and future plans. BlueSky systems have the flexibility to accept basic fire information from virtually any source and can reconcile multiple information sources so that duplication of fire records is eliminated. BlueSky systems currently apply information from (1) the National Oceanic and Atmospheric Administration's (NOAA) Hazard Mapping System (HMS), which represents remotely sensed data from the Moderate Resolution Imaging Spectroradiometer (MODIS), Advanced Very High Resolution Radiometer (AVHRR), and Geostationary Operational Environmental Satellites (GOES); (2) the Monitoring Trends in Burn Severity (MTBS) interagency project, which derives fire perimeters from Landsat 30-meter burn scars; (3) the Geospatial Multi-Agency Coordination Group (GeoMAC), which produces helicopter-flown burn perimeters; and (4) ground-based fire reports, such as the ICS-209 reports managed by the National Wildfire Coordinating Group. Efforts are currently underway to streamline the use of additional ground-based systems, such as states' prescribed burn databases. BlueSky systems were recently modified to address known uncertainties in smoke modeling associated with (1) estimates of biomass consumption derived from sparse fuel moisture data, and (2) models of plume injection heights. Additional sources of remotely sensed data are being applied to address these issues as follows: - The National Aeronautics and Space Administration's (NASA) Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis Real-Time (TMPA-RT) data set is being used to improve dead fuel moisture estimates. - EastFire live fuel moisture estimates, which are derived from NASA's MODIS direct broadcast, are being used to improve live fuel moisture estimates. - NASA's Multi-angle Imaging Spectroradiometer (MISR) stereo heights are being used to improve estimates of plume injection heights. Further, the Fire Location and Modeling of Burning Emissions (FLAMBÉ) model was incorporated into the BlueSky Framework as an alternative means of calculating fire emissions. FLAMBÉ directly estimates emissions on the basis of fire detections and radiance measures from NASA's MODIS and NOAA's GOES satellites. (The authors gratefully acknowledge NASA's Applied Sciences Program [Grant Nos. NN506AB52A and NNX09AV76G)], the USDA Forest Service, and the Joint Fire Science Program for their support.)
NASA Astrophysics Data System (ADS)
Henneberg, Olga; Ament, Felix; Grützun, Verena
2018-05-01
Soil moisture amount and distribution control evapotranspiration and thus impact the occurrence of convective precipitation. Many recent model studies demonstrate that changes in initial soil moisture content result in modified convective precipitation. However, to quantify the resulting precipitation changes, the chaotic behavior of the atmospheric system needs to be considered. Slight changes in the simulation setup, such as the chosen model domain, also result in modifications to the simulated precipitation field. This causes an uncertainty due to stochastic variability, which can be large compared to effects caused by soil moisture variations. By shifting the model domain, we estimate the uncertainty of the model results. Our novel uncertainty estimate includes 10 simulations with shifted model boundaries and is compared to the effects on precipitation caused by variations in soil moisture amount and local distribution. With this approach, the influence of soil moisture amount and distribution on convective precipitation is quantified. Deviations in simulated precipitation can only be attributed to soil moisture impacts if the systematic effects of soil moisture modifications are larger than the inherent simulation uncertainty at the convection-resolving scale. We performed seven experiments with modified soil moisture amount or distribution to address the effect of soil moisture on precipitation. Each of the experiments consists of 10 ensemble members using the deep convection-resolving COSMO model with a grid spacing of 2.8 km. Only in experiments with very strong modification in soil moisture do precipitation changes exceed the model spread in amplitude, location or structure. These changes are caused by a 50 % soil moisture increase in either the whole or part of the model domain or by drying the whole model domain. Increasing or decreasing soil moisture both predominantly results in reduced precipitation rates. Replacing the soil moisture with realistic fields from different days has an insignificant influence on precipitation. The findings of this study underline the need for uncertainty estimates in soil moisture studies based on convection-resolving models.
NASA Astrophysics Data System (ADS)
Argus, D. F.; Fu, Y.; Landerer, F. W.; Farr, T.; Watkins, M. M.; Famiglietti, J. S.
2014-12-01
Changes in total water thickness in most of California are being estimated using GPS measurements of vertical ground displacement. The Sierra Nevada each year subsides about 12 mm in the fall and winter due to the load of rain and snow, then rises about the same amount in the spring and summer when the snow melts, water runs off, and soil moisture evaporates. Earth's elastic response to a surface load is well known (except at thick sedimentary basins). Changes in equivalent water thickness can thus be inferred [Argus Fu Landerer 2014]. The average seasonal change in total water thickness is found to be 0.5 meters in the Sierra Nevada and Klamath Mountains and 0.1 meters in the Great Basin. The average seasonal change in the Sierra Nevada Mountains estimated with GPS is 35 Gigatons. GPS vertical ground displacements are furthermore being used to estimate changes in water in consecutive years of either drought or heavy precipitation. Changes in the sum of snow and soil moisture during California's drought from June 2011 to June 2014 are estimated from GPS in this study. Changes in water in California's massive reservoirs are well known and removed, yielding an estimate of change in the thickness of snow plus soil moisture. Water loss is found to be largest near the center of the southern Sierra Nevada (0.8 m equivalent water thickness) and smaller in the northern Sierra Nevada and southern Klamath Mountains (0.3 m). The GPS estimates of changes in the sum of snow and soil moisture complement GRACE observations of water change in the Sacramento-San Joaquin River basin. Whereas GPS provides estimates of water change at high spatial resolution in California's mountains, GRACE observes changes in groundwater in the Central Valley. We will further compare and contrast the GPS and GRACE measurements, and also evaluate the finding of Amos et al. [2014] that groundwater loss in the southern Central Valley (Tulare Basin) is causing the mountains on either side to rise at 1 to 3 mm/yr.
Johnson, Michael J.; Mayers, Charles J.; Andraski, Brian J.
2002-01-01
Selected micrometeorological and soil-moisture data were collected at the Amargosa Desert Research Site adjacent to a low-level radioactive waste and hazardous chemical waste facility near Beatty, Nev., 1998-2000. Data were collected in support of ongoing research studies to improve the understanding of hydrologic and contaminant-transport processes in arid environments. Micrometeorological data include precipitation, air temperature, solar radiation, net radiation, relative humidity, ambient vapor pressure, wind speed and direction, barometric pressure, soil temperature, and soil-heat flux. All micrometeorological data were collected using a 10-second sampling interval by data loggers that output daily mean, maximum, and minimum values, and hourly mean values. For precipitation, data output consisted of daily, hourly, and 5-minute totals. Soil-moisture data included periodic measurements of soil-water content at nine neutron-probe access tubes with measurable depths ranging from 5.25 to 29.75 meters. The computer data files included in this report contain the complete micrometeorological and soil-moisture data sets. The computer data consists of seven files with about 14 megabytes of information. The seven files are in tabular format: (1) one file lists daily mean, maximum, and minimum micrometeorological data and daily total precipitation; (2) three files list hourly mean micrometeorological data and hourly precipitation for each year (1998-2000); (3) one file lists 5-minute precipitation data; (4) one file lists mean soil-water content by date and depth at four experimental sites; and (5) one file lists soil-water content by date and depth for each neutron-probe access tube. This report highlights selected data contained in the computer data files using figures, tables, and brief discussions. Instrumentation used for data collection also is described. Water-content profiles are shown to demonstrate variability of water content with depth. Time-series data are plotted to illustrate temporal variations in micrometeorological and soil-water content data. Substantial precipitation at the end of an El Ni?o cycle in early 1998 resulted in measurable water penetration to a depth of 1.25 meters at one of the four experimental soil-monitoring sites.
A comparison of 3 models of 1-hr timelag fuel moisture in Hawaii
D.R. Weise; F.M. Fujioka; R.M. Nelson
2005-01-01
The U.S. National Fire Danger Rating System currently uses a moisture diffusion model developed by Fosberg to predict fine fuel moisture in woody fuels. Nelson recently developed a fuel moisture model that includes functions for both heat and moisture transfer. Fuel moisture samples were collected in Hawaii hourly for up to 96 h for three litter, one herbaceous, and...
Inflatable Antenna Microwave Radiometer for Soil Moisture Measurement
NASA Technical Reports Server (NTRS)
Bailey, M. C.; Kendall, Bruce M.; Schroeder, Lyle C.; Harrington, Richard F.
1993-01-01
Microwave measurements of soil moisture are not being obtained at the required spatial Earth resolution with current technology. Recently, new novel designs for lightweight reflector systems have been developed using deployable inflatable antenna structures which could enable lightweight real-aperture radiometers. In consideration of this, a study was conducted at the NASA Langley Research Center (LaRC) to determine the feasibility of developing a microwave radiometer system using inflatable reflector antenna technology to obtain high spatial resolution radiometric measurements of soil moisture from low Earth orbit and which could be used with a small and cost effective launch vehicle. The required high resolution with reasonable swath width coupled with the L-band measurement frequency for soil moisture dictated the use of a large (30 meter class) real aperture antenna in conjunction with a pushbroom antenna beam configuration and noise-injection type radiometer designs at 1.4 and 4.3 GHz to produce a 370 kilometer cross-track swath with a 10 kilometer resolution that could be packaged for launch with a Titan 2 class vehicle. This study includes design of the inflatable structure, control analysis, structural and thermal analysis, antenna and feed design, radiometer design, payload packaging, orbital analysis, and electromagnetic losses in the thin membrane inflatable materials.
Relationship between moisture content and electrical impedance of carrot slices during drying
NASA Astrophysics Data System (ADS)
Kertész, Ákos; Hlaváčová, Zuzana; Vozáry, Eszter; Staroňová, Lenka
2015-01-01
Electrical properties of food materials can give information about the inner structure and physiological state of biological tissues. Generally, the process of drying of fruits and vegetables is followed by weight loss. The aim of this study was to measure the impedance spectra of carrot slices during drying and to correlate impedance parameters to moisture content in different drying periods. Cylindrical slices were cut out from the carrot root along the axis. The slices were dried in a Venticell 111 air oven at 50°C. The weight of the slices was measured with a Denver SI-603 electronic analytical and precision balance. The weighing of the samples was performed every 30 min at the beginning of drying and every 60 min after the process. The moisture content of the samples was calculated on wet basis. The magnitude and phase angle of electrical impedance of the slices were measured with HP 4284A and 4285A precision LCR meters in the frequency range from 30 Hz to 1 MHz and from 75 kHz to 30 MHz, respectively, at voltage 1 V. The impedance measurement was performed after weighting. The change in the magnitude of impedance during drying showed a good correlation with the change in the moisture content.
SoilNet - A Zigbee based soil moisture sensor network
NASA Astrophysics Data System (ADS)
Bogena, H. R.; Weuthen, A.; Rosenbaum, U.; Huisman, J. A.; Vereecken, H.
2007-12-01
Soil moisture plays a key role in partitioning water and energy fluxes, in providing moisture to the atmosphere for precipitation, and controlling the pattern of groundwater recharge. Large-scale soil moisture variability is driven by variation of precipitation and radiation in space and time. At local scales, land cover, soil conditions, and topography act to redistribute soil moisture. Despite the importance of soil moisture, it is not yet measured in an operational way, e.g. for a better prediction of hydrological and surface energy fluxes (e.g. runoff, latent heat) at larger scales and in the framework of the development of early warning systems (e.g. flood forecasting) and the management of irrigation systems. The SoilNet project aims to develop a sensor network for the near real-time monitoring of soil moisture changes at high spatial and temporal resolution on the basis of the new low-cost ZigBee radio network that operates on top of the IEEE 802.15.4 standard. The sensor network consists of soil moisture sensors attached to end devices by cables, router devices and a coordinator device. The end devices are buried in the soil and linked wirelessly with nearby aboveground router devices. This ZigBee wireless sensor network design considers channel errors, delays, packet losses, and power and topology constraints. In order to conserve battery power, a reactive routing protocol is used that determines a new route only when it is required. The sensor network is also able to react to external influences, e.g. such as rainfall occurrences. The SoilNet communicator, routing and end devices have been developed by the Forschungszentrum Juelich and will be marketed through external companies. We will present first results of experiments to verify network stability and the accuracy of the soil moisture sensors. Simultaneously, we have developed a data management and visualisation system. We tested the wireless network on a 100 by 100 meter forest plot equipped with 25 end devices each consisting of 6 vertically arranged soil moisture sensors. The next step will be the instrumentation of two small catchments (~30 ha) with a 30 m spacing of the end devices. juelich.de/icg/icg-4/index.php?index=739
Vegetation Water Content Mapping for Agricultural Regions in SMAPVEX16
NASA Astrophysics Data System (ADS)
White, W. A.; Cosh, M. H.; McKee, L.; Berg, A. A.; McNairn, H.; Hornbuckle, B. K.; Colliander, A.; Jackson, T. J.
2017-12-01
Vegetation water content impacts the ability of L-band radiometers to measure surface soil moisture. Therefore it is necessary to quantify the amount of water held in surface vegetation for an accurate soil moisture remote sensing retrieval. A methodology is presented for generating agricultural vegetation water content maps using Landsat 8 scenes for agricultural fields of Iowa and Manitoba for the Soil Moisture Active Passive Validation Experiments in 2016 (SMAPVEX16). Manitoba has a variety of row crops across the region, and the study period encompasses the time frame from emergence to reproduction, as well as a forested region. The Iowa study site is dominated by corn and soybeans, presenting an easier challenge. Ground collection of vegetation biomass and water content were also collected to provide a ground truth data source. Errors for the resulting vegetation water content maps ranged depending upon crop type, but generally were less than 15% of the total plant water content per crop type. Interpolation is done between Landsat overpasses to produce daily vegetation water content maps for the summer of 2016 at a 30 meter resolution.
Microwave emission measurements of sea surface roughness, soil moisture, and sea ice structure
NASA Technical Reports Server (NTRS)
Gloersen, P.; Wilheit, T. T.; Schmugge, T. J.
1972-01-01
In order to demonstrate the feasibility of the microwave radiometers to be carried aboard the Nimbus 5 and 6 satellites and proposed for one of the earth observatory satellites, remote measurements of microwave radiation at wavelengths ranging from 0.8 to 21 cm have been made of a variety of the earth's surfaces from the NASA CV-990 A/C. Brightness temperatures of sea water surfaces of varying roughness, of terrain with varying soil moisture, and of sea ice of varying structure were observed. In each case, around truth information was available for correlation with the microwave brightness temperature. The utility of passive microwave radiometry in determining ocean surface wind speeds, at least for values higher than 7 meters/second has been demonstrated. In addition, it was shown that radiometric signatures can be used to determine soil moisture in unvegetated terrain to within five percentage points by weight. Finally, it was demonstrated that first year thick, multi-year, and first year thin sea ice can be distinguished by observing their differing microwave emissivities at various wavelengths.
NASA Soil Moisture Data Products and Their Incorporation in DREAM
NASA Technical Reports Server (NTRS)
Blonski, Slawomir; Holland, Donald; Henderson, Vaneshette
2005-01-01
NASA provides soil moisture data products that include observations from the Advanced Microwave Scanning Radiometer on the Earth Observing System Aqua satellite, field measurements from the Soil Moisture Experiment campaigns, and model predictions from the Land Information System and the Goddard Earth Observing System Data Assimilation System. Incorporation of the NASA soil moisture products in the Dust Regional Atmospheric Model is possible through use of the satellite observations of soil moisture to set initial conditions for the dust simulations. An additional comparison of satellite soil moisture observations with mesoscale atmospheric dynamics modeling is recommended. Such a comparison would validate the use of NASA soil moisture data in applications and support acceptance of satellite soil moisture data assimilation in weather and climate modeling.
NASA Astrophysics Data System (ADS)
Weiss, S. B.; Bunn, A. G.; Tran, T. J.; Bruening, J. M.; Salzer, M. W.; Hughes, M. K.
2016-12-01
The interpretation of ring-width patterns in high elevation Great Basin bristlecone pine is hampered by the presence of sharp ecophysiological gradients that can lead to mixed growth signals depending on topographic setting of individual trees. We have identified a temperature threshold near the upper forest border above which trees are limited more strongly by temperature, and below which trees tend to be moisture limited. We combined temperature loggers and GIS modeling at a scale of tens of meters to examine trees with different limiting factors. We found that the dual-signal patterns in radial growth can be partially explained by the topoclimate setting of individual trees, with trees in locations where growing season mean temperatures below about 7.4°C to 8°C were more strongly associated with temperature variability than with moisture availability. Using this threshold we show that it is possible to build both temperature and drought reconstructions over the common era from bristlecone pine near the alpine treeline. While our findings might allow for a better physiological understanding of bristlecone pine growth, they also raise questions about the interpretation of temperature reconstructions given the threshold nature of the growth response and the dynamic nature of the treeline ecotone over past millennia.
Liao, C M; Liang, H M
2000-05-01
Two models for evaluating the contents and advection of manure moisture on odor causing volatile organic compounds (VOC-odor) volatilization from stored swine manure were studied for their ability to predict the volatilization rate (indoor air concentration) and cumulative exposure dose: a MJ-I model and a MJ-II model. Both models simulating depletion of source contaminant via volatilization and degradation based on an analytical model adapted from the behavior assessment model of Jury et al. In the MJ-I model, manure moisture movement was negligible, whereas in the MJ-II model, time-dependent indoor air concentrations was a function of constant manure moisture contents and steady-state moisture advection. Predicted indoor air concentrations and inhaled doses for the study VOC-odors of p-cresol, toluene, and p-xylene varied by up to two to three orders of magnitude depending on the manure moisture conditions. The sensitivity analysis of both models suggests that when manure moisture movement exists, simply MJ-I model is inherently not sufficient to represent a more generally volatilization process, which can even become stringent as moisture content increases. The conclusion illustrates how one needs to include a wide variety of manure moisture values in order to fully assess the complex volatilization mechanisms that are present in a real situation.
Examination of Soil Moisture Retrieval Using SIR-C Radar Data and a Distributed Hydrological Model
NASA Technical Reports Server (NTRS)
Hsu, A. Y.; ONeill, P. E.; Wood, E. F.; Zion, M.
1997-01-01
A major objective of soil moisture-related hydrological-research during NASA's SIR-C/X-SAR mission was to determine and compare soil moisture patterns within humid watersheds using SAR data, ground-based measurements, and hydrologic modeling. Currently available soil moisture-inversion methods using active microwave data are only accurate when applied to bare and slightly vegetated surfaces. Moreover, as the surface dries down, the number of pixels that can provide estimated soil moisture by these radar inversion methods decreases, leading to less accuracy and, confidence in the retrieved soil moisture fields at the watershed scale. The impact of these errors in microwave- derived soil moisture on hydrological modeling of vegetated watersheds has yet to be addressed. In this study a coupled water and energy balance model operating within a topographic framework is used to predict surface soil moisture for both bare and vegetated areas. In the first model run, the hydrological model is initialized using a standard baseflow approach, while in the second model run, soil moisture values derived from SIR-C radar data are used for initialization. The results, which compare favorably with ground measurements, demonstrate the utility of combining radar-derived surface soil moisture information with basin-scale hydrological modeling.
Evapotranspiration measurement and modeling without fitting parameters in high-altitude grasslands
NASA Astrophysics Data System (ADS)
Ferraris, Stefano; Previati, Maurizio; Canone, Davide; Dematteis, Niccolò; Boetti, Marco; Balocco, Jacopo; Bechis, Stefano
2016-04-01
Mountain grasslands are important, also because one sixth of the world population lives inside watershed dominated by snowmelt. Also, grasslands provide food to both domestic and selvatic animals. The global warming will probably accelerate the hydrological cycle and increase the drought risk. The combination of measurements, modeling and remote sensing can furnish knowledge in such faraway areas (e.g.: Brocca et al., 2013). A better knowledge of water balance can also allow to optimize the irrigation (e.g.: Canone et al., 2015). This work is meant to build a model of water balance in mountain grasslands, ranging between 1500 and 2300 meters asl. The main input is the Digital Terrain Model, which is more reliable in grasslands than both in the woods and in the built environment. It drives the spatial variability of shortwave solar radiation. The other atmospheric forcings are more problematic to estimate, namely air temperature, wind and longwave radiation. Ad hoc routines have been written, in order to interpolate in space the meteorological hourly time variability. The soil hydraulic properties are less variable than in the plains, but the soil depth estimation is still an open issue. The soil vertical variability has been modeled taking into account the main processes: soil evaporation, root uptake, and fractured bedrock percolation. The time variability latent heat flux and soil moisture results have been compared with the data measured in an eddy covariance station. The results are very good, given the fact that the model has no fitting parameters. The space variability results have been compared with the results of a model based on Landsat 7 and 8 data, applied over an area of about 200 square kilometers. The spatial correlation is quite in agreement between the two models. Brocca et al. (2013). "Soil moisture estimation in alpine catchments through modelling and satellite observations". Vadose Zone Journal, 12(3), 10 pp. Canone et al. (2015). "Field measurements based model for surface irrigation efficiency assessment". Agric. Water Manag., 156(1) pp. 30-42
NASA Astrophysics Data System (ADS)
Hazreek, Z. A. M.; Rosli, S.; Fauziah, A.; Wijeyesekera, D. C.; Ashraf, M. I. M.; Faizal, T. B. M.; Kamarudin, A. F.; Rais, Y.; Dan, M. F. Md; Azhar, A. T. S.; Hafiz, Z. M.
2018-04-01
The efficiency of civil engineering structure require comprehensive geotechnical data obtained from site investigation. In the past, conventional site investigation was heavily related to drilling techniques thus suffer from several limitations such as time consuming, expensive and limited data collection. Consequently, this study presents determination of soil moisture content using laboratory experimental and field electrical resistivity values (ERV). Field and laboratory electrical resistivity (ER) test were performed using ABEM SAS4000 and Nilsson400 soil resistance meter. Soil sample used for resistivity test was tested for characterization test specifically on particle size distribution and moisture content test according to BS1377 (1990). Field ER data was processed using RES2DINV software while laboratory ER data was analyzed using SPSS and Excel software. Correlation of ERV and moisture content shows some medium relationship due to its r = 0.506. Moreover, coefficient of determination, R2 analyzed has demonstrate that the statistical correlation obtain was very good due to its R2 value of 0.9382. In order to determine soil moisture content based on statistical correlation (w = 110.68ρ-0.347), correction factor, C was established through laboratory and field ERV given as 19.27. Finally, this study has shown that soil basic geotechnical properties with particular reference to water content was applicably determined using integration of laboratory and field ERV data analysis thus able to compliment conventional approach due to its economic, fast and wider data coverage.
NASA Astrophysics Data System (ADS)
Pratsenka, S. V.; Voropai, E. S.; Belkin, V. G.
2018-01-01
Rapid measurement of the moisture content of dehydrated residues is a critical problem, the solution of which will increase the efficiency of treatment facilities and optimize the process of applying flocculants. The ability to determine the moisture content of dehydrated residues using a meter operating on the IR reflectance principle was confirmed experimentally. The most suitable interference filters were selected based on an analysis of the obtained diffuse reflectance spectrum of the dehydrated residue in the range 1.0-2.7 μm. Calibration curves were constructed and compared for each filter set. A measuring filter with a transmittance maximum at 1.19 μm and a reference filter with a maximum at 1.3 μm gave the best agreement with the laboratory measurements.
A Probabilistic Model of Meter Perception: Simulating Enculturation.
van der Weij, Bastiaan; Pearce, Marcus T; Honing, Henkjan
2017-01-01
Enculturation is known to shape the perception of meter in music but this is not explicitly accounted for by current cognitive models of meter perception. We hypothesize that the induction of meter is a result of predictive coding: interpreting onsets in a rhythm relative to a periodic meter facilitates prediction of future onsets. Such prediction, we hypothesize, is based on previous exposure to rhythms. As such, predictive coding provides a possible explanation for the way meter perception is shaped by the cultural environment. Based on this hypothesis, we present a probabilistic model of meter perception that uses statistical properties of the relation between rhythm and meter to infer meter from quantized rhythms. We show that our model can successfully predict annotated time signatures from quantized rhythmic patterns derived from folk melodies. Furthermore, we show that by inferring meter, our model improves prediction of the onsets of future events compared to a similar probabilistic model that does not infer meter. Finally, as a proof of concept, we demonstrate how our model can be used in a simulation of enculturation. From the results of this simulation, we derive a class of rhythms that are likely to be interpreted differently by enculturated listeners with different histories of exposure to rhythms.
Multiscale soil moisture estimates using static and roving cosmic-ray soil moisture sensors
NASA Astrophysics Data System (ADS)
McJannet, David; Hawdon, Aaron; Baker, Brett; Renzullo, Luigi; Searle, Ross
2017-12-01
Soil moisture plays a critical role in land surface processes and as such there has been a recent increase in the number and resolution of satellite soil moisture observations and the development of land surface process models with ever increasing resolution. Despite these developments, validation and calibration of these products has been limited because of a lack of observations on corresponding scales. A recently developed mobile soil moisture monitoring platform, known as the rover
, offers opportunities to overcome this scale issue. This paper describes methods, results and testing of soil moisture estimates produced using rover surveys on a range of scales that are commensurate with model and satellite retrievals. Our investigation involved static cosmic-ray neutron sensors and rover surveys across both broad (36 × 36 km at 9 km resolution) and intensive (10 × 10 km at 1 km resolution) scales in a cropping district in the Mallee region of Victoria, Australia. We describe approaches for converting rover survey neutron counts to soil moisture and discuss the factors controlling soil moisture variability. We use independent gravimetric and modelled soil moisture estimates collected across both space and time to validate rover soil moisture products. Measurements revealed that temporal patterns in soil moisture were preserved through time and regression modelling approaches were utilised to produce time series of property-scale soil moisture which may also have applications in calibration and validation studies or local farm management. Intensive-scale rover surveys produced reliable soil moisture estimates at 1 km resolution while broad-scale surveys produced soil moisture estimates at 9 km resolution. We conclude that the multiscale soil moisture products produced in this study are well suited to future analysis of satellite soil moisture retrievals and finer-scale soil moisture models.
Global and Regional Real-time Systems for Flood and Drought Monitoring and Prediction
NASA Astrophysics Data System (ADS)
Hong, Y.; Gourley, J. J.; Xue, X.; Flamig, Z.
2015-12-01
A Hydrometeorological Extreme Mapping and Prediction System (HyXtreme-MaP), initially built upon the Coupled Routing and Excess STorage (CREST) distributed hydrological model, is driven by real-time quasi-global TRMM/GPM satellites and by the US Multi-Radar Multi-Sensor (MRMS) radar network with dual-polarimetric upgrade to simulate streamflow, actual ET, soil moisture and other hydrologic variables at 1/8th degree resolution quasi-globally (http://eos.ou.edu) and at 250-meter 2.5-mintue resolution over the Continental United States (CONUS: http://flash.ou.edu). Multifaceted and collaborative by-design, this end-to-end research framework aims to not only integrate data, models, and applications but also brings people together (i.e., NOAA, NASA, University researchers, and end-users). This presentation will review the progresses, challenges and opportunities of such HyXTREME-MaP System used to monitor global floods and droughts, and also to predict flash floods over the CONUS.
Study of a dry room in a battery manufacturing plant using a process model
NASA Astrophysics Data System (ADS)
Ahmed, Shabbir; Nelson, Paul A.; Dees, Dennis W.
2016-09-01
The manufacture of lithium ion batteries requires some processing steps to be carried out in a dry room, where the moisture content should remain below 100 parts per million. The design and operation of such a dry room adds to the cost of the battery. This paper studied the humidity management of the air to and from the dry room to understand the impact of design and operating parameters on the energy demand and the cost contribution towards the battery manufacturing cost. The study was conducted with the help of a process model for a dry room with a volume of 16,000 cubic meters. For a defined base case scenario it was found that the dry room operation has an energy demand of approximately 400 kW. The paper explores some tradeoffs in design and operating parameters by looking at the humidity reduction by quenching the make-up air vs. at the desiccant wheel, and the impact of the heat recovery from the desiccant regeneration cycle.
Soil moisture dynamics modeling considering multi-layer root zone.
Kumar, R; Shankar, V; Jat, M K
2013-01-01
The moisture uptake by plant from soil is a key process for plant growth and movement of water in the soil-plant system. A non-linear root water uptake (RWU) model was developed for a multi-layer crop root zone. The model comprised two parts: (1) model formulation and (2) moisture flow prediction. The developed model was tested for its efficiency in predicting moisture depletion in a non-uniform root zone. A field experiment on wheat (Triticum aestivum) was conducted in the sub-temperate sub-humid agro-climate of Solan, Himachal Pradesh, India. Model-predicted soil moisture parameters, i.e., moisture status at various depths, moisture depletion and soil moisture profile in the root zone, are in good agreement with experiment results. The results of simulation emphasize the utility of the RWU model across different agro-climatic regions. The model can be used for sound irrigation management especially in water-scarce humid, temperate, arid and semi-arid regions and can also be integrated with a water transport equation to predict the solute uptake by plant biomass.
Li, Ming Ze; Gao, Yuan Ke; Di, Xue Ying; Fan, Wen Yi
2016-03-01
The moisture content of forest surface soil is an important parameter in forest ecosystems. It is practically significant for forest ecosystem related research to use microwave remote sensing technology for rapid and accurate estimation of the moisture content of forest surface soil. With the aid of TDR-300 soil moisture content measuring instrument, the moisture contents of forest surface soils of 120 sample plots at Tahe Forestry Bureau of Daxing'anling region in Heilongjiang Province were measured. Taking the moisture content of forest surface soil as the dependent variable and the polarization decomposition parameters of C band Quad-pol SAR data as independent variables, two types of quantitative estimation models (multilinear regression model and BP-neural network model) for predicting moisture content of forest surface soils were developed. The spatial distribution of moisture content of forest surface soil on the regional scale was then derived with model inversion. Results showed that the model precision was 86.0% and 89.4% with RMSE of 3.0% and 2.7% for the multilinear regression model and the BP-neural network model, respectively. It indicated that the BP-neural network model had a better performance than the multilinear regression model in quantitative estimation of the moisture content of forest surface soil. The spatial distribution of forest surface soil moisture content in the study area was then obtained by using the BP neural network model simulation with the Quad-pol SAR data.
NASA Technical Reports Server (NTRS)
Hildreth, W. W.
1978-01-01
A determination of the state of the art in soil moisture transport modeling based on physical or physiological principles was made. It was found that soil moisture models based on physical principles have been under development for more than 10 years. However, these models were shown to represent infiltration and redistribution of soil moisture quite well. Evapotranspiration has not been as adequately incorporated into the models.
NASA Technical Reports Server (NTRS)
Njoku, Eni; Entekhabi, Dara; O'Neill, Peggy; Jackson, Tom; Kellogg, Kent; Entin, Jared
2011-01-01
NASA's Soil Moisture Active Passive (SMAP) mission, planned for launch in late 2014, has as its key measurement objective the frequent, global mapping of near-surface soil moisture and its freeze-thaw state. SMAP soil moisture and freeze/thaw measurements at 10 km and 3 km resolutions respectively, would enable significantly improved estimates of water, energy and carbon transfers between the land and atmosphere. Soil moisture control of these fluxes is a key factor in the performance of atmospheric models used for weather forecasts and climate projections Soil moisture measurements are also of great importance in assessing floods and for monitoring drought. In addition, observations of soil moisture and freeze/thaw timing over the boreal latitudes can help reduce uncertainties in quantifying the global carbon balance. The SMAP measurement concept utilizes an L-band radar and radiometer sharing a rotating 6-meter mesh reflector antenna. The SMAP radiometer and radar flight hardware and ground processing designs are incorporating approaches to identify and mitigate potential terrestrial radio frequency interference (RFI). The radar and radiometer instruments are planned to operate in a 680 km polar orbit, viewing the surface at a constant 40-degree incidence angle with a 1000-km swath width, providing 3-day global coverage. Data from the instruments would yield global maps of soil moisture and freeze/thaw state to be provided at 10 km and 3 km resolutions respectively, every two to three days. Plans are to provide also a radiometer-only soil moisture product at 40-km spatial resolution. This product and the underlying brightness temperatures have characteristics similar to those provided by the Soil Moisture and Ocean Salinity (SMOS) mission. As a result, there are unique opportunities for common data product development and continuity between the two missions. SMAP also has commonalities with other satellite missions having L-band radiometer and/or radar sensors applicable to soil moisture measurement, such as Aquarius, SAO COM, and ALOS-2. The algorithms and data products for SMAP are being developed in the SMAP Science Data System (SDS) Testbed. The algorithms are developed and evaluated in the SDS Testbed using simulated SMAP observations as well as observational data from current airborne and spaceborne L-band sensors including SMOS. The SMAP project is developing a Calibration and Validation (Cal/Val) Plan that is designed to support algorithm development (pre-launch) and data product validation (post-launch). A key component of the Cal/Val Plan is the identification, characterization, and instrumentation of sites that can be used to calibrate and validate the sensor data (Level I) and derived geophysical products (Level 2 and higher). In this presentation we report on the development status of the SMAP data product algorithms, and the planning and implementation of the SMAP Cal/Val program. Several components of the SMAP algorithm development and Cal/Val plans have commonality with those of SMOS, and for this reason there are shared activities and resources that can be utilized between the missions, including in situ networks, ancillary data sets, and long-term monitoring sites.
NASA Astrophysics Data System (ADS)
Manning, J. E.; Schulz, M. S.; Lambrecht, D. S.
2016-12-01
Species imbalance within many California plant assemblages may arise due to more intense wildfires as well as climate warming. Given this, coyote brush (Baccharis pilularis DC), a native evergreen shrub known as a ready colonizer of disturbed soil, may become more dominant. While prolonged spring soil moisture is required for seedling establishment, 1+ year-old coyote brush can withstand low soil water potentials (-1.2 MPa). Beyond this, little is known about its soil-water dynamics. Hydraulic redistribution of water within the soil profile by plant roots has been established in numerous species in the past 20 years. Recent quantification of the water quantity re-distributed by root systems are beginning to provide detail that could inform ET, weathering, and carbon cycling models. Electrical resistivity tomography (ERT) has been used to study soil hydraulics in natural as well as cropland settings. This study is the first known to use ERT to investigate hydraulic redistribution in coyote brush. One mid-size shrub surrounded by open grassland was selected at the study site, located on a coastal marine terrace west of Santa Cruz, CA. The soil profile, previously characterized with ERT and auger-based soil-water sampling, includes a clay-rich B horizon and is texturally non-uniform due to bioturbation to 0.6 meter. The 12-m ERT survey transect had 48 semi-permanent electrodes, with the 4-m wide shrub canopy at probes 16 to 32. Five repeats of evening and morning surveys were conducted. Heterogeneous texture and severe soil drying necessitated qualitative comparison across time. Overnight resistivity changes using differences plots of the modelled data revealed increased moisture beneath the shrub canopy during the night. Areas beyond the canopy—presumably outside the root zone—experienced variable overnight changes, with moisture increasing in the clay-rich horizon. Preliminary analysis suggests that coyote brush roots redistribute water upward within the soil profile.
High resolution change estimation of soil moisture and its assimilation into a land surface model
NASA Astrophysics Data System (ADS)
Narayan, Ujjwal
Near surface soil moisture plays an important role in hydrological processes including infiltration, evapotranspiration and runoff. These processes depend non-linearly on soil moisture and hence sub-pixel scale soil moisture variability characterization is important for accurate modeling of water and energy fluxes at the pixel scale. Microwave remote sensing has evolved as an attractive technique for global monitoring of near surface soil moisture. A radiative transfer model has been tested and validated for soil moisture retrieval from passive microwave remote sensing data under a full range of vegetation water content conditions. It was demonstrated that soil moisture retrieval errors of approximately 0.04 g/g gravimetric soil moisture are attainable with vegetation water content as high as 5 kg/m2. Recognizing the limitation of low spatial resolution associated with passive sensors, an algorithm that uses low resolution passive microwave (radiometer) and high resolution active microwave (radar) data to estimate soil moisture change at the spatial resolution of radar operation has been developed and applied to coincident Passive and Active L and S band (PALS) and Airborne Synthetic Aperture Radar (AIRSAR) datasets acquired during the Soil Moisture Experiments in 2002 (SMEX02) campaign with root mean square error of 10% and a 4 times enhancement in spatial resolution. The change estimation algorithm has also been used to estimate soil moisture change at 5 km resolution using AMSR-E soil moisture product (50 km) in conjunction with the TRMM-PR data (5 km) for a 3 month period demonstrating the possibility of high resolution soil moisture change estimation using satellite based data. Soil moisture change is closely related to precipitation and soil hydraulic properties. A simple assimilation framework has been implemented to investigate whether assimilation of surface layer soil moisture change observations into a hydrologic model will potentially improve it performance. Results indicate an improvement in model prediction of near surface and deep layer soil moisture content when the update is performed to the model state as compared to free model runs. It is also seen that soil moisture change assimilation is able to mitigate the effect of erroneous precipitation input data.
NASA Technical Reports Server (NTRS)
Soman, Vishwas V.; Crosson, William L.; Laymon, Charles; Tsegaye, Teferi
1998-01-01
Soil moisture is an important component of analysis in many Earth science disciplines. Soil moisture information can be obtained either by using microwave remote sensing or by using a hydrologic model. In this study, we combined these two approaches to increase the accuracy of profile soil moisture estimation. A hydrologic model was used to analyze the errors in the estimation of soil moisture using the data collected during Huntsville '96 microwave remote sensing experiment in Huntsville, Alabama. Root mean square errors (RMSE) in soil moisture estimation increase by 22% with increase in the model input interval from 6 hr to 12 hr for the grass-covered plot. RMSEs were reduced for given model time step by 20-50% when model soil moisture estimates were updated using remotely-sensed data. This methodology has a potential to be employed in soil moisture estimation using rainfall data collected by a space-borne sensor, such as the Tropical Rainfall Measuring Mission (TRMM) satellite, if remotely-sensed data are available to update the model estimates.
Soil moisture dynamics and their effect on bioretention performance in Northeast Ohio
NASA Astrophysics Data System (ADS)
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 time and peak flow, are altered relative to a control street. This analysis suggests that street-scale implementation of bioretention can reduce the impact of impervious surface on stormflows, but more information is needed to fully understand how soil moisture of the bioretentions affects inter-storm variability in performance.
Application of IEM model on soil moisture and surface roughness estimation
NASA Technical Reports Server (NTRS)
Shi, Jiancheng; Wang, J. R.; Oneill, P. E.; Hsu, A. Y.; Engman, E. T.
1995-01-01
Monitoring spatial and temporal changes of soil moisture are of importance to hydrology, meteorology, and agriculture. This paper reports a result on study of using L-band SAR imagery to estimate soil moisture and surface roughness for bare fields. Due to limitations of the Small Perturbation Model, it is difficult to apply this model on estimation of soil moisture and surface roughness directly. In this study, we show a simplified model derived from the Integral Equation Model for estimation of soil moisture and surface roughness. We show a test of this model using JPL L-band AIRSAR data.
The Impact of Microwave-Derived Surface Soil Moisture on Watershed Hydrological Modeling
NASA Technical Reports Server (NTRS)
ONeill, P. E.; Hsu, A. Y.; Jackson, T. J.; Wood, E. F.; Zion, M.
1997-01-01
The usefulness of incorporating microwave-derived soil moisture information in a semi-distributed hydrological model was demonstrated for the Washita '92 experiment in the Little Washita River watershed in Oklahoma. Initializing the hydrological model with surface soil moisture fields from the ESTAR airborne L-band microwave radiometer on a single wet day at the start of the study period produced more accurate model predictions of soil moisture than a standard hydrological initialization with streamflow data over an eight-day soil moisture drydown.
Spatial variability in water-balance model performance in the conterminous United States
Hay, L.E.; McCabe, G.J.
2002-01-01
A monthly water-balance (WB) model was tested in 44 river basins from diverse physiographic and climatic regions across the conterminous United States (U.S.). The WB model includes the concepts of climatic water supply and climatic water demand, seasonality in climatic water supply and demand, and soil-moisture storage. Exhaustive search techniques were employed to determine the optimal set of precipitation and temperature stations, and the optimal set of WB model parameters to use for each basin. It was found that the WB model worked best for basins with: (1) a mean elevation less than 450 meters or greater than 2000 meters, and/or (2) monthly runoff that is greater than 5 millimeters (mm) more than 80 percent of the time. In a separate analysis, a multiple linear regression (MLR) was computed using the adjusted R-square values obtained by comparing measured and estimated monthly runoff of the original 44 river basins as the dependent variable, and combinations of various independent variables [streamflow gauge latitude, longitude, and elevation; basin area, the long-term mean and standard deviation of annual precipitation; temperature and runoff; and low-flow statistics (i.e., the percentage of months with monthly runoff that is less than 5 mm)]. Results from the MLR study showed that the reliability of a WB model for application in a specific region can be estimated from mean basin elevation and the percentage of months with gauged runoff less than 5 mm. The MLR equations were subsequently used to estimate adjusted R-square values for 1,646 gauging stations across the conterminous U.S. Results of this study indicate that WB models can be used reliably to estimate monthly runoff in the eastern U.S., mountainous areas of the western U.S., and the Pacific Northwest. Applications of monthly WB models in the central U.S. can lead to uncertain estimates of runoff.
Carbon Cycling Studies in Forest and Rangeland Ecosystems of Northern and Central Coastal California
NASA Astrophysics Data System (ADS)
Potter, C.; Klooster, S.; Gross, P.; Hiatt, S.; Genovese, V.
2008-12-01
The varied topography and micro-climates of northern and central coastal California result in high biodiversity and many different levels of primary production driving regional carbon cycles. Coastal mountains trap moisture from low clouds and fog in summer to supplement rainfall in winter. This creates a favorable micro-environment for coniferous forests, including the southernmost habitat of the coast redwood (Sequoia sempervirens), which grows mainly on lower north-facing slopes in Big Sur. In rain shadows, forests transition to open oak woodland, and then into the more fire-tolerant chaparral and coast scrub. Field sites for our on-going climate change studies on the California northern and central coasts currently include the University of California Santa Cruz Campus Natural Reserve, the US Forest Service Brazil Ranch, and the University of California Big Creek Reserve. We are conducting research at each of these sites to better understand possible impacts of climate change, including: (1) biological and physical capacity of soils to capture carbon and retain plant-essential nutrients; (2) rates of plant-soil water and carbon cycling and energy flow; and (3) recovery mechanisms for disturbances such as invasive weed species, grazing, and wildfire. The NASA-CASA simulation model based on satellite observations of monthly vegetation cover from the Moderate Resolution Imaging Spectroradiometer (MODIS) was used to estimate carbon cycling for much of the central coast as far north as Mendocino County. Net primary production (NPP) of all vegetation cover was mapped at 30-meter resolution for selected years by combining MODIS and Landsat images across the region. Results show annual NPP predictions of between 200-400 grams C per square meter for coastal scrub and 800-1200 grams C per square meter for coastal evergreen forests, Net ecosystem fluxes of carbon will be presented for the region based on NASA-CASA modeling and field measurements of soil respiration fluxes.
Project Fog Drops. Part 1: Investigations of warm fog properties
NASA Technical Reports Server (NTRS)
Pilie, R. J.; Eadie, W.; Mack, E. J.; Rogers, C.; Kocmond, W. C.
1972-01-01
A detailed study was made of the micrometeorological and microphysical characteristics of eleven valley fogs occurring near Elmira, New York. Observations were made of temperature, dew point, wind speed and direction, dew deposition, vertical wind velocity, and net radiative flux. In fog, visibility was continuously recorded and periodic measurements were made of liquid water content and drop-size distribution. The observations were initiated in late evening and continued until the time of fog dissipation. The vertical distribution of temperature in the lowest 300 meters and cloud nucleus concentration at several heights were measured from an aircraft before fog nucleus concentrations at several heights were measured from an aircraft before fog formation. A numerical model was developed to investigate the life cycle of radiation fogs. The model predicts the temporal evolution of the vertical distributions of temperature, water vapor, and liquid water as determined by the turbulent transfer of heat and moisture. The model includes the nocturnal cooling of the earth's surface, dew formation, fog drop sedimentation, and the absorption of infrared radiation by fog.
A Comparison of Methods for a Priori Bias Correction in Soil Moisture Data Assimilation
NASA Technical Reports Server (NTRS)
Kumar, Sujay V.; Reichle, Rolf H.; Harrison, Kenneth W.; Peters-Lidard, Christa D.; Yatheendradas, Soni; Santanello, Joseph A.
2011-01-01
Data assimilation is being increasingly 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: (i) parameter estimation to calibrate the land model to the climatology of the soil moisture observations, and (ii) 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.
Modeling moisture content of fine dead wildland fuels: Input to the BEHAVE fire prediction system
Richard C. Rothermel; Ralph A. Wilson; Glen A. Morris; Stephen S. Sackett
1986-01-01
Describes a model for predicting moisture content of fine fuels for use with the BEHAVE fire behavior and fuel modeling system. The model is intended to meet the need for more accurate predictions of fine fuel moisture, particularly in northern conifer stands and on days following rain. The model is based on the Canadian Fine Fuel Moisture Code (FFMC), modified to...
NASA Astrophysics Data System (ADS)
Zhang, Ke; Yang, Tao; Ye, Jinyin; Li, Zhijia; Yu, Zhongbo
2017-04-01
Soil moisture is a key variable that regulates exchanges of water and energy between land surface and atmosphere. Soil moisture retrievals based on microwave satellite remote sensing have made it possible to estimate global surface (up to about 10 cm in depth) soil moisture routinely. Although there are many satellites operating, including NASA's Soil Moisture Acitive Passive mission (SMAP), ESA's Soil Moisture and Ocean Salinity mission (SMOS), JAXA's Advanced Microwave Scanning Radiometer 2 mission (AMSR2), and China's Fengyun (FY) missions, key differences exist between different satellite-based soil moisture products. In this study, we applied a single-channel soil moisture retrieval model forced by multiple sources of satellite brightness temperature observations to estimate consistent daily surface soil moisture across China at a spatial resolution of 25 km. By utilizing observations from multiple satellites, we are able to estimate daily soil moisture across the whole domain of China. We further developed a daily soil moisture accounting model and applied it to downscale the 25-km satellite-based soil moisture to 5 km. By comparing our estimated soil moisture with observations from a dense observation network implemented in Anhui Province, China, our estimated soil moisture results show a reasonably good agreement with the observations (RMSE < 0.1 and r > 0.8).
NASA Astrophysics Data System (ADS)
Daminov, Ildar; Tarasova, Ekaterina; Andreeva, Tatyana; Avazov, Artur
2016-02-01
This paper presents the comparison of smart meter deployment business models to determine the most suitable option providing smart meters deployment. Authors consider 3 main business model of companies: distribution grid company, energy supplier (energosbyt) and metering company. The goal of the article is to compare the business models of power companies from massive smart metering roll out in power system of Russian Federation.
NASA Astrophysics Data System (ADS)
Bastola, S.; Dialynas, Y. G.; Arnone, E.; Bras, R. L.
2014-12-01
The spatial variability of soil, vegetation, topography, and precipitation controls hydrological processes, consequently resulting in high spatio-temporal variability of most of the hydrological variables, such as soil moisture. Limitation in existing measuring system to characterize this spatial variability, and its importance in various application have resulted in a need of reconciling spatially distributed soil moisture evolution model and corresponding measurements. Fully distributed ecohydrological model simulates soil moisture at high resolution soil moisture. This is relevant for range of environmental studies e.g., flood forecasting. They can also be used to evaluate the value of space born soil moisture data, by assimilating them into hydrological models. In this study, fine resolution soil moisture data simulated by a physically-based distributed hydrological model, tRIBS-VEGGIE, is compared with soil moisture data collected during the field campaign in Turkey river basin, Iowa. The soil moisture series at the 2 and 4 inch depth exhibited a more rapid response to rainfall as compared to bottom 8 and 20 inch ones. The spatial variability in two distinct land surfaces of Turkey River, IA, reflects the control of vegetation, topography and soil texture in the characterization of spatial variability. The comparison of observed and simulated soil moisture at various depth showed that model was able to capture the dynamics of soil moisture at a number of gauging stations. Discrepancies are large in some of the gauging stations, which are characterized by rugged terrain and represented, in the model, through large computational units.
Soil Moisture Project Evaluation Workshop
NASA Technical Reports Server (NTRS)
Gilbert, R. H. (Editor)
1980-01-01
Approaches planned or being developed for measuring and modeling soil moisture parameters are discussed. Topics cover analysis of spatial variability of soil moisture as a function of terrain; the value of soil moisture information in developing stream flow data; energy/scene interactions; applications of satellite data; verifying soil water budget models; soil water profile/soil temperature profile models; soil moisture sensitivity analysis; combinations of the thermal model and microwave; determing planetary roughness and field roughness; how crust or a soil layer effects microwave return; truck radar; and truck/aircraft radar comparison.
NASA Astrophysics Data System (ADS)
Kaushik, A.; Noone, D.
2016-12-01
The continental boundary layer moisture balance plays an important role in regulating water and energy exchange between the surface and the atmosphere, yet the mechanisms associated with moistening and drying are both poorly observed and modeled. Stable water isotope ratio measurements can provide insights into air mass origins, convection dynamics and mechanisms dominating atmosphere-land surface water fluxes. Profiles can be exploited to improve estimates of boundary layer moistening associated with evaporation of falling precipitation and contributions from surface evapotranspiration. We present two years of in situ tower-based measurements of isotope ratios of water vapor and precipitation (δD and δ18O) and raindrop size distributions from the Boulder Atmospheric Observatory (BAO) tall-tower site in Erie, Colorado. Isotope vapor measurements were made at 1 Hz with a full cycle from the surface to 300 meters recorded every 80 minutes. At the surface and 300m, water samples were collected during precipitation events and raindrop sizes were measured continuously using Parsivel instruments. We use this unique suite of measurements and, in particular, exploit the differences between the surface and 300m observations to constrain the surface layer hydrological mass balance during and after rain events, and evaluate parameterization choices for rain evaporation and moisture recycling in current isotope-enabled climate models. Aggregate raindrop size measurements showed shifts from populations of smaller raindrops at 300m to larger raindrops at the surface, contrary to what is expected for rain evaporation. Convective storms resulted in more uniform signatures between the surface and 300m, as well as longer isotope equilibration and adjustment time scales, whereas low Dexcess signatures (<9 to negative) during stratiform drizzle events were indicative of a greater degree of rain evaporation. Our observational results suggest that water vapor-rain equilibration is rarely achieved, and modification of the kinetic fractionation factor is necessary to better capture drop-size related isotope changes. This has implications not only for refining current global climate models, but also for interpreting proxy records connected to rainfall signatures that aid in understanding past hydrology.
NASA Astrophysics Data System (ADS)
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.
State of the Art in Large-Scale Soil Moisture Monitoring
NASA Technical Reports Server (NTRS)
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.;
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.
Field measurement of moisture-buffering model inputs for residential buildings
Woods, Jason; Winkler, Jon
2016-02-05
Moisture adsorption and desorption in building materials impact indoor humidity. This effect should be included in building-energy simulations, particularly when humidity is being investigated or controlled. Several models can calculate this moisture-buffering effect, but accurate ones require model inputs that are not always known to the user of the building-energy simulation. This research developed an empirical method to extract whole-house model inputs for the effective moisture penetration depth (EMPD) model. The experimental approach was to subject the materials in the house to a square-wave relative-humidity profile, measure all of the moisture-transfer terms (e.g., infiltration, air-conditioner condensate), and calculate the onlymore » unmeasured term—the moisture sorption into the materials. We validated this method with laboratory measurements, which we used to measure the EMPD model inputs of two houses. After deriving these inputs, we measured the humidity of the same houses during tests with realistic latent and sensible loads and demonstrated the accuracy of this approach. Furthermore, these results show that the EMPD model, when given reasonable inputs, is an accurate moisture-buffering model.« less
Misrepresentation and amendment of soil moisture in conceptual hydrological modelling
NASA Astrophysics Data System (ADS)
Zhuo, Lu; Han, Dawei
2016-04-01
Although many conceptual models are very effective in simulating river runoff, their soil moisture schemes are generally not realistic in comparison with the reality (i.e., getting the right answers for the wrong reasons). This study reveals two significant misrepresentations in those models through a case study using the Xinanjiang model which is representative of many well-known conceptual hydrological models. The first is the setting of the upper limit of its soil moisture at the field capacity, due to the 'holding excess runoff' concept (i.e., runoff begins on repletion of its storage to the field capacity). The second is neglect of capillary rise of water movement. A new scheme is therefore proposed to overcome those two issues. The amended model is as effective as its original form in flow modelling, but represents more logically realistic soil water processes. The purpose of the study is to enable the hydrological model to get the right answers for the right reasons. Therefore, the new model structure has a better capability in potentially assimilating soil moisture observations to enhance its real-time flood forecasting accuracy. The new scheme is evaluated in the Pontiac catchment of the USA through a comparison with satellite observed soil moisture. The correlation between the XAJ and the observed soil moisture is enhanced significantly from 0.64 to 0.70. In addition, a new soil moisture term called SMDS (Soil Moisture Deficit to Saturation) is proposed to complement the conventional SMD (Soil Moisture Deficit).
Modeling soil moisture memory in savanna ecosystems
NASA Astrophysics Data System (ADS)
Gou, S.; Miller, G. R.
2011-12-01
Antecedent soil conditions create an ecosystem's "memory" of past rainfall events. Such soil moisture memory effects may be observed over a range of timescales, from daily to yearly, and lead to feedbacks between hydrological and ecosystem processes. In this study, we modeled the soil moisture memory effect on savanna ecosystems in California, Arizona, and Africa, using a system dynamics model created to simulate the ecohydrological processes at the plot-scale. The model was carefully calibrated using soil moisture and evapotranspiration data collected at three study sites. The model was then used to simulate scenarios with various initial soil moisture conditions and antecedent precipitation regimes, in order to study the soil moisture memory effects on the evapotranspiration of understory and overstory species. Based on the model results, soil texture and antecedent precipitation regime impact the redistribution of water within soil layers, potentially causing deeper soil layers to influence the ecosystem for a longer time. Of all the study areas modeled, soil moisture memory of California savanna ecosystem site is replenished and dries out most rapidly. Thus soil moisture memory could not maintain the high rate evapotranspiration for more than a few days without incoming rainfall event. On the contrary, soil moisture memory of Arizona savanna ecosystem site lasts the longest time. The plants with different root depths respond to different memory effects; shallow-rooted species mainly respond to the soil moisture memory in the shallow soil. The growing season of grass is largely depended on the soil moisture memory of the top 25cm soil layer. Grass transpiration is sensitive to the antecedent precipitation events within daily to weekly timescale. Deep-rooted plants have different responses since these species can access to the deeper soil moisture memory with longer time duration Soil moisture memory does not have obvious impacts on the phenology of woody plants, as these can maintain transpiration for a longer time even through the top soil layer dries out.
Hurricane Harvey's Rapid Wind Intensification seen by NASA's SMAP
2017-08-28
The rapid intensification of Hurricane Harvey is seen in this pair of images of ocean surface wind speeds as observed by the radiometer instrument aboard NASA's Soil Moisture Active Passive (SMAP) satellite at 7:29 a.m. CDT Aug. 24th, 2017 (left) and at 7 p.m. CDT Aug. 26th (right). Color indicates wind speed, with red being highest and blue lowest. The images show Harvey's maximum wind speeds increased from approximately 56 miles per hour (25 meters per second) to about 107 miles per hour (47.8 meters per second) in the 36 hours just before landfall. The higher wind speeds estimated near the mouth of the Mississippi River are erroneous and are due to errors in the ancillary sea-surface-salinity data product used by SMAP to estimate extreme wind speeds. https://photojournal.jpl.nasa.gov/catalog/PIA21884
Soil Moisture Memory in Climate Models
NASA Technical Reports Server (NTRS)
Koster, Randal D.; Suarez, Max J.; Zukor, Dorothy J. (Technical Monitor)
2000-01-01
Water balance considerations at the soil surface lead to an equation that relates the autocorrelation of soil moisture in climate models to (1) seasonality in the statistics of the atmospheric forcing, (2) the variation of evaporation with soil moisture, (3) the variation of runoff with soil moisture, and (4) persistence in the atmospheric forcing, as perhaps induced by land atmosphere feedback. Geographical variations in the relative strengths of these factors, which can be established through analysis of model diagnostics and which can be validated to a certain extent against observations, lead to geographical variations in simulated soil moisture memory and thus, in effect, to geographical variations in seasonal precipitation predictability associated with soil moisture. The use of the equation to characterize controls on soil moisture memory is demonstrated with data from the modeling system of the NASA Seasonal-to-Interannual Prediction Project.
NASA Technical Reports Server (NTRS)
Robock, Alan; Vinnikov, Konstantin YA.; Schlosser, C. Adam; Speranskaya, Nina A.; Xue, Yongkang
1995-01-01
Soil moisture observations in sites with natural vegetation were made for several decades in the former Soviet Union at hundreds of stations. In this paper, the authors use data from six of these stations from different climatic regimes, along with ancillary meteorological and actinometric data, to demonstrate a method to validate soil moisture simulations with biosphere and bucket models. Some early and current general circulation models (GCMs) use bucket models for soil hydrology calculations. More recently, the Simple Biosphere Model (SiB) was developed to incorporate the effects of vegetation on fluxes of moisture, momentum, and energy at the earth's surface into soil hydrology models. Until now, the bucket and SiB have been verified by comparison with actual soil moisture data only on a limited basis. In this study, a Simplified SiB (SSiB) soil hydrology model and a 15-cm bucket model are forced by observed meteorological and actinometric data every 3 h for 6-yr simulations at the six stations. The model calculations of soil moisture are compared to observations of soil moisture, literally 'ground truth,' snow cover, surface albedo, and net radiation, and with each other. For three of the stations, the SSiB and 15-cm bucket models produce good simulations of seasonal cycles and interannual variations of soil moisture. For the other three stations, there are large errors in the simulations by both models. Inconsistencies in specification of field capacity may be partly responsible. There is no evidence that the SSiB simulations are superior in simulating soil moisture variations. In fact, the models are quite similar since SSiB implicitly has a bucket embedded in it. One of the main differences between the models is in the treatment of runoff due to melting snow in the spring -- SSiB incorrectly puts all the snowmelt into runoff. While producing similar soil moisture simulations, the models produce very different surface latent and sensible heat fluxes, which would have large effects on GCM simulations.
25. CURRENT METERS: GURLEY MODEL NO. 665 AT CENTER, GURLEY ...
25. CURRENT METERS: GURLEY MODEL NO. 665 AT CENTER, GURLEY MODEL NO. 625 'PYGMY' CURRENT METER AT LEFT, AND WES MINIATURE PRICE-TYPE CURRENT METER AT RIGHT. - Waterways Experiment Station, Hydraulics Laboratory, Halls Ferry Road, 2 miles south of I-20, Vicksburg, Warren County, MS
Relationship between peatland hydrology and biogeochemistry
NASA Astrophysics Data System (ADS)
Roulet, N. T.
2012-04-01
The 'boreal forest' landscape is composed of upland forests, peatlands, some of which are treed, lakes, streams, and in North America, beaver ponds. Each of these landscapes present quite different biogeochemical environments due to differences in both abiotic and biotic processes and conditions. A significant amount of the carbon (C) in the boreal landscape is stored in peatlands, in part, due to the effect of the water storage on C cycling. The near saturated conditions affect the plants that can grow in peatlands and over the shorter term moisture variability controls the rate of C input to the peat. In the peat water limits the supply of electron donors and this has a profound effect on the C biogeochemistry. Near peat surface the moisture storage can be quite dynamic and mostly oxic conditions prevail, but redox conditions change significantly within a few tenth of a meter below the surface where water residence times increase orders of magnitude. This limits the supply of electron donors and other substrates that control the rate of C mineralization. Understanding the links among the moisture dynamics, the chemical thermodynamics of temporally variable saturated environments, and the quality of C is critical to determining the sensitivity of the C stored in peatlands to environmental change.
NASA Astrophysics Data System (ADS)
Wanders, N.; Bierkens, M. F. P.; de Jong, S. M.; de Roo, A.; Karssenberg, D.
2014-08-01
Large-scale hydrological models are nowadays mostly calibrated using observed discharge. As a result, a large part of the hydrological system, in particular the unsaturated zone, remains uncalibrated. Soil moisture observations from satellites have the potential to fill this gap. Here we evaluate the added value of remotely sensed soil moisture in calibration of large-scale hydrological models by addressing two research questions: (1) Which parameters of hydrological models can be identified by calibration with remotely sensed soil moisture? (2) Does calibration with remotely sensed soil moisture lead to an improved calibration of hydrological models compared to calibration based only on discharge observations, such that this leads to improved simulations of soil moisture content and discharge? A dual state and parameter Ensemble Kalman Filter is used to calibrate the hydrological model LISFLOOD for the Upper Danube. Calibration is done using discharge and remotely sensed soil moisture acquired by AMSR-E, SMOS, and ASCAT. Calibration with discharge data improves the estimation of groundwater and routing parameters. Calibration with only remotely sensed soil moisture results in an accurate identification of parameters related to land-surface processes. For the Upper Danube upstream area up to 40,000 km2, calibration on both discharge and soil moisture results in a reduction by 10-30% in the RMSE for discharge simulations, compared to calibration on discharge alone. The conclusion is that remotely sensed soil moisture holds potential for calibration of hydrological models, leading to a better simulation of soil moisture content throughout the catchment and a better simulation of discharge in upstream areas. This article was corrected on 15 SEP 2014. See the end of the full text for details.
NASA Astrophysics Data System (ADS)
Moghaddam, M.; Silva, A.; Clewley, D.; Akbar, R.; Entekhabi, D.
2013-12-01
Soil Moisture Sensing Controller and oPtimal Estimator (SoilSCAPE) is a wireless in-situ sensor network technology, developed under the support of NASA ESTO/AIST program, for multi-scale validation of soil moisture retrievals from the Soil Moisture Active and Passive (SMAP) mission. The SMAP sensor suite is expected to produce soil moisture retrievals at 3 km scale from the radar instrument, at 36 km from the radiometer, and at 10 km from the combination of the two sensors. To validate the retrieved soil moisture maps at any of these scales, it is necessary to perform in-situ observations at multiple scales (ten, hundreds, and thousands of meters), representative of the true spatial variability of soil moisture fields. The most recent SoilSCAPE network, deployed in the California central valley, has been designed, built, and deployed to accomplish this goal, and is expected to become a core validation site for SMAP. The network consists of up to 150 sensor nodes, each comprised of 3-4 soil moisture sensors at various depths, deployed over a spatial extent of 36 km by 36 km. The network contains multiple sub-networks, each having up to 30 nodes, whose location is selected in part based on maximizing the land cover diversity within the 36 km cell. The network has achieved unprecedented energy efficiency, longevity, and spatial coverage using custom-designed hardware and software protocols. The network architecture utilizes a nested strategy, where a number of end devices (EDs) communicate to a local coordinator (LC) using our recently developed hardware with ultra-efficient circuitry and best-effort-timeslot allocation communication protocol. The LCs in turn communicates with the base station (BS) via text messages and a new compression scheme. The hardware and software technologies required to implement this latest deployment of the SoilSCAPE network will be presented in this paper, and several data sets resulting from the measurements will be shown. The data are available publicly in near-real-time from the project web site, and are also available and searchable via an extensive set of metadata fields through the ORNL-DAAC.
L-band Soil Moisture Mapping using Small UnManned Aerial Systems
NASA Astrophysics Data System (ADS)
Dai, E.; Gasiewski, A. J.; Stachura, M.; Elston, J.; Venkitasubramony, A.
2016-12-01
1. IntroductionSoil moisture is of fundamental importance to many hydrological, biological and biogeochemical processes, plays an important role in the development and evolution of convective weather and precipitation, and impacts water resource management, agriculture, and flood runoff prediction. The launch of NASA's Soil Moisture Active/Passive (SMAP) mission in 2015 promises to provide global measurements of soil moisture and surface freeze/thaw state at fixed crossing times and spatial resolutions as low as 5 km for some products. However, there exists a need for measurements of soil moisture on smaller spatial scales and arbitrary diurnal times for SMAP validation, precision agriculture and evaporation and transpiration studies of boundary layer heat transport. The Lobe Differencing Correlation Radiometer (LDCR) provides a means of mapping soil moisture on spatial scales as small as several meters (i.e., the height of the platform). Compared with various other proposed methods of validation based on either in-situ measurements [1,2] or existing airborne sensors suitable for manned aircraft deployment [3], the integrated design of the LDCR on a lightweight small UAS (sUAS) is capable of providing sub-watershed ( km scale) coverage at very high spatial resolution ( 15 m) suitable for scaling scale studies, and at comparatively low operator cost. To demonstrate the LDCR several flights had been performed during field experiments at the Canton Oklahoma Soilscape site on September 8th and 9th, 2015 and Yuma Colorado Irrigation Research Foundation (IRF) site from June to August, 2016. These tests were flown at 25-50 m altitude to obtain differing spatial resolutions. The scientific intercomparisons of LDCR retrieved soil moisture and in-situ measurements will be presented. 2. References[1] McIntyre, E.M., A.J. Gasiewski, and D. Manda D, "Near Real-Time Passive C-Band Microwave Soil Moisture Retrieval During CLASIC 2007," Proc. IGARSS, 2008. [2] Robock, A., S. Steele-Dunne, J. Basara, W. Crow, and M. Moghaddam M, "In Situ Network and Scaling," SMAP Algorithm and Cal/Val Workshop, 2009. [3] Walker, A., "Airborne Microwave Radiometer Measurements During CanEx-SM10," Second SMAP Cal/Val Workshop, 2011.
Improving Water Level and Soil Moisture Over Peatlands in a Global Land Modeling System
NASA Technical Reports Server (NTRS)
Bechtold, M.; De Lannoy, G. J. M.; Roose, D.; Reichle, R. H.; Koster, R. D.; Mahanama, S. P.
2017-01-01
New model structure for peatlands results in improved skill metrics (without any parameter calibration) Simulated surface soil moisture strongly affected by new model, but reliable soil moisture data lacking for validation.
Evaluation of a Soil Moisture Data Assimilation System Over West Africa
NASA Astrophysics Data System (ADS)
Bolten, J. D.; Crow, W.; Zhan, X.; Jackson, T.; Reynolds, C.
2009-05-01
A crucial requirement of global crop yield forecasts by the U.S. Department of Agriculture (USDA) International Production Assessment Division (IPAD) is the regional characterization of surface and sub-surface soil moisture. However, due to the spatial heterogeneity and dynamic nature of precipitation events and resulting soil moisture, accurate estimation of regional land surface-atmosphere interactions based sparse ground measurements is difficult. IPAD estimates global soil moisture using daily estimates of minimum and maximum temperature and precipitation applied to a modified Palmer two-layer soil moisture model which calculates the daily amount of soil moisture withdrawn by evapotranspiration and replenished by precipitation. We attempt to improve upon the existing system by applying an Ensemble Kalman filter (EnKF) data assimilation system to integrate surface soil moisture retrievals from the NASA Advanced Microwave Scanning Radiometer (AMSR-E) into the USDA soil moisture model. This work aims at evaluating the utility of merging satellite-retrieved soil moisture estimates with the IPAD two-layer soil moisture model used within the DBMS. We present a quantitative analysis of the assimilated soil moisture product over West Africa (9°N- 20°N; 20°W-20°E). This region contains many key agricultural areas and has a high agro- meteorological gradient from desert and semi-arid vegetation in the North, to grassland, trees and crops in the South, thus providing an ideal location for evaluating the assimilated soil moisture product over multiple land cover types and conditions. A data denial experimental approach is utilized to isolate the added utility of integrating remotely-sensed soil moisture by comparing assimilated soil moisture results obtained using (relatively) low-quality precipitation products obtained from real-time satellite imagery to baseline model runs forced with higher quality rainfall. An analysis of root-zone anomalies for each model simulation suggests that the assimilation of AMSR-E surface soil moisture retrievals can add significant value to USDA root-zone predictions derived from real-time satellite precipitation products.
The use of remotely sensed soil moisture data in large-scale models of the hydrological cycle
NASA Technical Reports Server (NTRS)
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.
A semi-mechanistic model of dead fine fuel moisture for Temperate and Mediterranean ecosystems
NASA Astrophysics Data System (ADS)
Resco de Dios, Víctor; Fellows, Aaron; Boer, Matthias; Bradstock, Ross; Nolan, Rachel; Goulden, Michel
2014-05-01
Fire is a major disturbance in terrestrial ecosystems globally. It has an enormous economic and social cost, and leads to fatalities in the worst cases. The moisture content of the vegetation (fuel moisture) is one of the main determinants of fire risk. Predicting the moisture content of dead and fine fuel (< 2.5 cm in diameter) is particularly important, as this is often the most important component of the fuel complex for fire propagation. A variety of drought indices, empirical and mechanistic models have been proposed to model fuel moisture. A commonality across these different approaches is that they have been neither validated across large temporal datasets nor validated across broadly different vegetation types. Here, we present the results of a study performed at 6 locations in California, USA (5 sites) and New South Wales, Australia (1 site), where 10-hours fuel moisture content was continuously measured every 30 minutes during one full year at each site. We observed that drought indices did not accurately predict fuel moisture, and that empirical and mechanistic models both needed site-specific calibrations, which hinders their global application as indices of fuel moisture. We developed a novel, single equation and semi-mechanistic model, based on atmospheric vapor-pressure deficit. Across sites and years, mean absolute error (MAE) of predicted fuel moisture was 4.7%. MAE dropped <1% in the critical range of fuel moisture <10%. The high simplicity, accuracy and precision of our model makes it suitable for a wide range of applications: from operational purposes, to global vegetation models.
Hydrologic downscaling of soil moisture using global data without site-specific calibration
USDA-ARS?s Scientific Manuscript database
Numerous applications require fine-resolution (10-30 m) soil moisture patterns, but most satellite remote sensing and land-surface models provide coarse-resolution (9-60 km) soil moisture estimates. The Equilibrium Moisture from Topography, Vegetation, and Soil (EMT+VS) model downscales soil moistu...
NASA Astrophysics Data System (ADS)
Tuttle, S. E.; Salvucci, G.
2012-12-01
Soil moisture influences many hydrological processes in the water and energy cycles, such as runoff generation, groundwater recharge, and evapotranspiration, and thus is important for climate modeling, water resources management, agriculture, and civil engineering. Large-scale estimates of soil moisture are produced almost exclusively from remote sensing, while validation of remotely sensed soil moisture has relied heavily on ground truthing, which is at an inherently smaller scale. Here we present a complementary method to determine the information content in different soil moisture products using only large-scale precipitation data (i.e. without modeling). This study builds on the work of Salvucci [2001], Saleem and Salvucci [2002], and Sun et al. [2011], in which precipitation was conditionally averaged according to soil moisture level, resulting in moisture-outflow curves that estimate the dependence of drainage, runoff, and evapotranspiration on soil moisture (i.e. sigmoidal relations that reflect stressed evapotranspiration for dry soils, roughly constant flux equal to potential evaporation minus capillary rise for moderately dry soils, and rapid drainage for very wet soils). We postulate that high quality satellite estimates of soil moisture, using large-scale precipitation data, will yield similar sigmoidal moisture-outflow curves to those that have been observed at field sites, while poor quality estimates will yield flatter, less informative curves that explain less of the precipitation variability. Following this logic, gridded ¼ degree NLDAS precipitation data were compared to three AMSR-E derived soil moisture products (VUA-NASA, or LPRM [Owe et al., 2001], NSIDC [Njoku et al., 2003], and NSIDC-LSP [Jones & Kimball, 2011]) for a period of nine years (2001-2010) across the contiguous United States. Gaps in the daily soil moisture data were filled using a multiple regression model reliant on past and future soil moisture and precipitation, and soil moisture was then converted to a ranked wetness index, in order to reconcile the wide range and magnitude of the soil moisture products. Generalized linear models were employed to fit a polynomial model to precipitation, given wetness index. Various measures of fit (e.g. log likelihood) were used to judge the amount of information in each soil moisture product, as indicated by the amount of precipitation variability explained by the fitted model. Using these methods, regional patterns appear in soil moisture product performance.
NASA Astrophysics Data System (ADS)
Schrön, Martin; Köhli, Markus; Scheiffele, Lena; Iwema, Joost; Bogena, Heye R.; Lv, Ling; Martini, Edoardo; Baroni, Gabriele; Rosolem, Rafael; Weimar, Jannis; Mai, Juliane; Cuntz, Matthias; Rebmann, Corinna; Oswald, Sascha E.; Dietrich, Peter; Schmidt, Ulrich; Zacharias, Steffen
2017-10-01
In the last few years the method of cosmic-ray neutron sensing (CRNS) has gained popularity among hydrologists, physicists, and land-surface modelers. The sensor provides continuous soil moisture data, averaged over several hectares and tens of decimeters in depth. However, the signal still may contain unidentified features of hydrological processes, and many calibration datasets are often required in order to find reliable relations between neutron intensity and water dynamics. Recent insights into environmental neutrons accurately described the spatial sensitivity of the sensor and thus allowed one to quantify the contribution of individual sample locations to the CRNS signal. Consequently, data points of calibration and validation datasets are suggested to be averaged using a more physically based weighting approach. In this work, a revised sensitivity function is used to calculate weighted averages of point data. The function is different from the simple exponential convention by the extraordinary sensitivity to the first few meters around the probe, and by dependencies on air pressure, air humidity, soil moisture, and vegetation. The approach is extensively tested at six distinct monitoring sites: two sites with multiple calibration datasets and four sites with continuous time series datasets. In all cases, the revised averaging method improved the performance of the CRNS products. The revised approach further helped to reveal hidden hydrological processes which otherwise remained unexplained in the data or were lost in the process of overcalibration. The presented weighting approach increases the overall accuracy of CRNS products and will have an impact on all their applications in agriculture, hydrology, and modeling.
A new model for predicting moisture uptake by packaged solid pharmaceuticals.
Chen, Y; Li, Y
2003-04-14
A novel mathematical model has been developed for predicting moisture uptake by packaged solid pharmaceutical products during storage. High density polyethylene (HDPE) bottles containing the tablet products of two new chemical entities and desiccants are investigated. Permeability of the bottles is determined at different temperatures using steady-state data. Moisture sorption isotherms of the two model drug products and desiccants at the same temperatures are determined and expressed in polynomial equations. The isotherms are used for modeling the time-humidity profile in the container, which enables the prediction of the moisture content of individual component during storage. Predicted moisture contents agree well with real time stability data. The current model could serve as a guide during packaging selection for moisture protection, so as to reduce the cost and cycle time of screening study.
The Impact of Rainfall on Soil Moisture Dynamics in a Foggy Desert.
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 results as well as sensitivity analyses provide soil moisture baseline information for future monitoring and the prediction of soil moisture patterns in the Namib Desert.
The Impact of Rainfall on Soil Moisture Dynamics in a Foggy Desert
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 results as well as sensitivity analyses provide soil moisture baseline information for future monitoring and the prediction of soil moisture patterns in the Namib Desert. PMID:27764203
NASA Astrophysics Data System (ADS)
Mishra, V.; Cruise, J. F.; Mecikalski, J. R.
2015-12-01
Developing accurate vertical soil moisture profiles with minimum input requirements is important to agricultural as well as land surface modeling. Earlier studies show that the principle of maximum entropy (POME) can be utilized to develop vertical soil moisture profiles with accuracy (MAE of about 1% for a monotonically dry profile; nearly 2% for monotonically wet profiles and 3.8% for mixed profiles) with minimum constraints (surface, mean and bottom soil moisture contents). In this study, the constraints for the vertical soil moisture profiles were obtained from remotely sensed data. Low resolution (25 km) MW soil moisture estimates (AMSR-E) were downscaled to 4 km using a soil evaporation efficiency index based disaggregation approach. The downscaled MW soil moisture estimates served as a surface boundary condition, while 4 km resolution TIR based Atmospheric Land Exchange Inverse (ALEXI) estimates provided the required mean root-zone soil moisture content. Bottom soil moisture content is assumed to be a soil dependent constant. Mulit-year (2002-2011) gridded profiles were developed for the southeastern United States using the POME method. The soil moisture profiles were compared to those generated in land surface models (Land Information System (LIS) and an agricultural model DSSAT) along with available NRCS SCAN sites in the study region. The end product, spatial soil moisture profiles, can be assimilated into agricultural and hydrologic models in lieu of precipitation for data scarce regions.Developing accurate vertical soil moisture profiles with minimum input requirements is important to agricultural as well as land surface modeling. Previous studies have shown that the principle of maximum entropy (POME) can be utilized with minimal constraints to develop vertical soil moisture profiles with accuracy (MAE = 1% for monotonically dry profiles; MAE = 2% for monotonically wet profiles and MAE = 3.8% for mixed profiles) when compared to laboratory and field data. In this study, vertical soil moisture profiles were developed using the POME model to evaluate an irrigation schedule over a maze field in north central Alabama (USA). The model was validated using both field data and a physically based mathematical model. The results demonstrate that a simple two-constraint entropy model under the assumption of a uniform initial soil moisture distribution can simulate most soil moisture profiles within the field area for 6 different soil types. The results of the irrigation simulation demonstrated that the POME model produced a very efficient irrigation strategy with loss of about 1.9% of the total applied irrigation water. However, areas of fine-textured soil (i.e. silty clay) resulted in plant stress of nearly 30% of the available moisture content due to insufficient water supply on the last day of the drying phase of the irrigation cycle. Overall, the POME approach showed promise as a general strategy to guide irrigation in humid environments, with minimum input requirements.
A Mulitivariate Statistical Model Describing the Compound Nature of Soil Moisture Drought
NASA Astrophysics Data System (ADS)
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 Fluxnet sites across Europe, we find the model has good skill and can particularly capture periods of low soil moisture well. We illustrate the relevance of the dependence structure of these Y variables to soil moisture and show how it may be generalised to offer information of soil moisture on a widespread scale where few observations of soil moisture exist. We then present results from a validation study of a selection of EURO CORDEX climate models where we demonstrate the skill of these models in representing these dependencies and so offer insight into the skill seen in the representation of soil moisture in these models.
NASA Astrophysics Data System (ADS)
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 assimilation on the evaporation fields is very mild, and difficult to assess due to the limited availability of eddy-covariance data. Nonetheless, our continental-scale simulations indicate that the assimilation of soil moisture can have a substantial impact on the estimated dynamics of evaporation in water-limited regimes. Progressing towards our goal of using satellite soil moisture to increase understanding of global land evaporation, future research will focus on the global application of this methodology and the consideration of multiple evaporation models.
NASA Astrophysics Data System (ADS)
Zhu, Fanglong; Zhou, Yu; Liu, Suyan
2013-10-01
In this paper, we propose a new fractal model to determine the moisture effective diffusivity of porous membrane such as expanded polytetrafluorethylene membrane, by taking account of both parallel and perpendicular channels to diffusion flow direction. With the consideration of both the Knudsen and bulk diffusion effect, a relationship between micro-structural parameters and effective moisture diffusivity is deduced. The effective moisture diffusivities predicted by the present fractal model are compared with moisture diffusion experiment data and calculated values obtained from other theoretical models.
Uncertain soil moisture feedbacks in model projections of Sahel precipitation
NASA Astrophysics Data System (ADS)
Berg, Alexis; Lintner, Benjamin R.; Findell, Kirsten; Giannini, Alessandra
2017-06-01
Given the uncertainties in climate model projections of Sahel precipitation, at the northern edge of the West African Monsoon, understanding the factors governing projected precipitation changes in this semiarid region is crucial. This study investigates how long-term soil moisture changes projected under climate change may feedback on projected changes of Sahel rainfall, using simulations with and without soil moisture change from five climate models participating in the Global Land Atmosphere Coupling Experiment-Coupled Model Intercomparison Project phase 5 experiment. In four out of five models analyzed, soil moisture feedbacks significantly influence the projected West African precipitation response to warming; however, the sign of these feedbacks differs across the models. These results demonstrate that reducing uncertainties across model projections of the West African Monsoon requires, among other factors, improved mechanistic understanding and constraint of simulated land-atmosphere feedbacks, even at the large spatial scales considered here.
On the assimilation of satellite derived soil moisture in numerical weather prediction models
NASA Astrophysics Data System (ADS)
Drusch, M.
2006-12-01
Satellite derived surface soil moisture data sets are readily available and have been used successfully in hydrological applications. In many operational numerical weather prediction systems the initial soil moisture conditions are analysed from the modelled background and 2 m temperature and relative humidity. This approach has proven its efficiency to improve surface latent and sensible heat fluxes and consequently the forecast on large geographical domains. However, since soil moisture is not always related to screen level variables, model errors and uncertainties in the forcing data can accumulate in root zone soil moisture. Remotely sensed surface soil moisture is directly linked to the model's uppermost soil layer and therefore is a stronger constraint for the soil moisture analysis. Three data assimilation experiments with the Integrated Forecast System (IFS) of the European Centre for Medium-range Weather Forecasts (ECMWF) have been performed for the two months period of June and July 2002: A control run based on the operational soil moisture analysis, an open loop run with freely evolving soil moisture, and an experimental run incorporating bias corrected TMI (TRMM Microwave Imager) derived soil moisture over the southern United States through a nudging scheme using 6-hourly departures. Apart from the soil moisture analysis, the system setup reflects the operational forecast configuration including the atmospheric 4D-Var analysis. Soil moisture analysed in the nudging experiment is the most accurate estimate when compared against in-situ observations from the Oklahoma Mesonet. The corresponding forecast for 2 m temperature and relative humidity is almost as accurate as in the control experiment. Furthermore, it is shown that the soil moisture analysis influences local weather parameters including the planetary boundary layer height and cloud coverage. The transferability of the results to other satellite derived soil moisture data sets will be discussed.
Inferring Soil Moisture Memory from Streamflow Observations Using a Simple Water Balance Model
NASA Technical Reports Server (NTRS)
Orth, Rene; Koster, Randal Dean; Seneviratne, Sonia I.
2013-01-01
Soil moisture is known for its integrative behavior and resulting memory characteristics. Soil moisture anomalies can persist for weeks or even months into the future, making initial soil moisture a potentially important contributor to skill in weather forecasting. A major difficulty when investigating soil moisture and its memory using observations is the sparse availability of long-term measurements and their limited spatial representativeness. In contrast, there is an abundance of long-term streamflow measurements for catchments of various sizes across the world. We investigate in this study whether such streamflow measurements can be used to infer and characterize soil moisture memory in respective catchments. Our approach uses a simple water balance model in which evapotranspiration and runoff ratios are expressed as simple functions of soil moisture; optimized functions for the model are determined using streamflow observations, and the optimized model in turn provides information on soil moisture memory on the catchment scale. The validity of the approach is demonstrated with data from three heavily monitored catchments. The approach is then applied to streamflow data in several small catchments across Switzerland to obtain a spatially distributed description of soil moisture memory and to show how memory varies, for example, with altitude and topography.
NASA Astrophysics Data System (ADS)
Baldwin, D.; Manfreda, S.; Keller, K.; Smithwick, E. A. H.
2017-03-01
Satellite-based near-surface (0-2 cm) soil moisture estimates have global coverage, but do not capture variations of soil moisture in the root zone (up to 100 cm depth) and may be biased with respect to ground-based soil moisture measurements. Here, we present an ensemble Kalman filter (EnKF) hydrologic data assimilation system that predicts bias in satellite soil moisture data to support the physically based Soil Moisture Analytical Relationship (SMAR) infiltration model, which estimates root zone soil moisture with satellite soil moisture data. The SMAR-EnKF model estimates a regional-scale bias parameter using available in situ data. The regional bias parameter is added to satellite soil moisture retrievals before their use in the SMAR model, and the bias parameter is updated continuously over time with the EnKF algorithm. In this study, the SMAR-EnKF assimilates in situ soil moisture at 43 Soil Climate Analysis Network (SCAN) monitoring locations across the conterminous U.S. Multivariate regression models are developed to estimate SMAR parameters using soil physical properties and the moderate resolution imaging spectroradiometer (MODIS) evapotranspiration data product as covariates. SMAR-EnKF root zone soil moisture predictions are in relatively close agreement with in situ observations when using optimal model parameters, with root mean square errors averaging 0.051 [cm3 cm-3] (standard error, s.e. = 0.005). The average root mean square error associated with a 20-fold cross-validation analysis with permuted SMAR parameter regression models increases moderately (0.082 [cm3 cm-3], s.e. = 0.004). The expected regional-scale satellite correction bias is negative in four out of six ecoregions studied (mean = -0.12 [-], s.e. = 0.002), excluding the Great Plains and Eastern Temperate Forests (0.053 [-], s.e. = 0.001). With its capability of estimating regional-scale satellite bias, the SMAR-EnKF system can predict root zone soil moisture over broad extents and has applications in drought predictions and other operational hydrologic modeling purposes.
Soil moisture mapping at Bubnow Wetland using L-band radiometer (ELBARA III)
NASA Astrophysics Data System (ADS)
Łukowski, Mateusz; Schwank, Mike; Szlązak, Radosław; Wiesmann, Andreas; Marczewski, Wojciech; Usowicz, Bogusław; Usowicz, Jerzy; Rojek, Edyta; Werner, Charles
2016-04-01
The study of soil moisture is a scientific challenge. Not only because of large diversity of soils and differences in their water content, but also due to the difficulty of measuring, especially in large scale. On this field of interest several methods to determine the content of water in soil exists. The basic and referential is gravimetric method, which is accurate, but suitable only for small spatial scales and time-consuming. Indirect methods are faster, but need to be validated, for example those based on dielectric properties of materials (e.g. time domain reflectometry - TDR) or made from distance (remote), like brightness temperature measurements. Remote sensing of soil moisture can be performed locally (from towers, drones, planes etc.) or globally (satellites). These techniques can complement and help to verify different models and assumptions. In our studies, we applied spatial statistics to local soil moisture mapping using ELBARA III (ESA L-band radiometer, 1.4 GHz) mounted on tower (6.5 meter height). Our measurements were carried out in natural Bubnow Wetland, near Polesie National Park (Eastern Poland), during spring time. This test-site had been selected because it is representative for one of the biggest wetlands in Europe (1400 km2), called "Western Polesie", localized in Ukraine, Poland and Belarus. We have investigated Bubnow for almost decade, using meteorological and soil moisture stations, conducting campaigns of hand-held measurements and collecting soil samples. Now, due to the possibility of rotation at different incidence angles (as in previous ELBARA systems) and the new azimuth tracking capabilities, we obtained brightness temperature data not only at different distances from the tower, but also around it, in footprints containing different vegetation and soil types. During experiment we collected data at area about 450 m2 by rotating ELBARA's antenna 5-175° in horizontal and 30-70° in vertical plane. This type of approach allows combining multiple independent measurements (performed nearly simultaneously) to one consistent soil moisture map. Spatial statistics helps with correcting blind spots or distortions causes by assembly elements, especially on corners of ELBARA's tower. Moreover, using this technique we can observe distribution of soil moisture with time dependency. In order to validate our data, the results were compared with measurements obtained by means of the TDR method. The presented approach enables better understanding the soil moisture spatial distribution over a particular local area of interests, before extending soil water assessments on larger areas. The work was partially funded under two ESA projects: 1) "ELBARA_PD (Penetration Depth)" No. 4000107897/13/NL/KML, funded by the Government of Poland through an ESA-PECS contract (Plan for European Cooperating States) 2) "Technical Support for the fabrication and deployment of the radiometer ELBARA-III in Bubnow, Poland" No. 4000113360/15/NL/FF/gp
Qi, Sheng; Belton, Peter; McAuley, William; Codoni, Doroty; Darji, Neerav
2013-04-01
Gelucire 50/13, a polyoxyethylene glycol glyceride mixture, has been widely used in drug delivery, but its moisture uptake behaviour is still poorly understood. In this study, the effects of relative humidity, temperature, and drug incorporation on the moisture uptake of Gelucire are reported in relation to their practical implications for preparation of solid dispersions using this material. DVS combined with kinetics modelling was used as the main experimental method to study the moisture uptake behaviour of Gelucire. Thermal and microscopic methods were employed to investigate the effect of moisture uptake on the physical properties of the material and drug loaded solid dispersions. The moisture uptake by Gelucire 50/13 is temperature and relative humidity dependent. At low temperatures and low relative humidities, moisture sorption follows a GAB model. The model fitting indicated that at high relative humidities the sorption is a complex process, potentially involving PEG being dissolved and the PEG solution acting as solvent to dissolve other components. Careful control of the storage and processing environmental conditions are required when using Gelucire 50/13. The incorporation of model drugs not only influences the moisture uptake capacity of Gelucire 50/13 but also the solidification behaviour.
Land-atmosphere coupling and soil moisture memory contribute to long-term agricultural drought
NASA Astrophysics Data System (ADS)
Kumar, S.; Newman, M.; Lawrence, D. M.; Livneh, B.; Lombardozzi, D. L.
2017-12-01
We assessed the contribution of land-atmosphere coupling and soil moisture memory on long-term agricultural droughts in the US. We performed an ensemble of climate model simulations to study soil moisture dynamics under two atmospheric forcing scenarios: active and muted land-atmosphere coupling. Land-atmosphere coupling contributes to a 12% increase and 36% decrease in the decorrelation time scale of soil moisture anomalies in the US Great Plains and the Southwest, respectively. These differences in soil moisture memory affect the length and severity of modeled drought. Consequently, long-term droughts are 10% longer and 3% more severe in the Great Plains, and 15% shorter and 21% less severe in the Southwest. An analysis of Coupled Model Intercomparsion Project phase 5 data shows four fold uncertainty in soil moisture memory across models that strongly affects simulated long-term droughts and is potentially attributable to the differences in soil water storage capacity across models.
Assimilation of Passive and Active Microwave Soil Moisture Retrievals
NASA Technical Reports Server (NTRS)
Draper, C. S.; Reichle, R. H.; DeLannoy, G. J. M.; Liu, Q.
2012-01-01
Root-zone soil moisture is an important control over the partition of land surface energy and moisture, and the assimilation of remotely sensed near-surface soil moisture has been shown to improve model profile soil moisture [1]. To date, efforts to assimilate remotely sensed near-surface soil moisture at large scales have focused on soil moisture derived from the passive microwave Advanced Microwave Scanning Radiometer (AMSR-E) and the active Advanced Scatterometer (ASCAT; together with its predecessor on the European Remote Sensing satellites (ERS. The assimilation of passive and active microwave soil moisture observations has not yet been directly compared, and so this study compares the impact of assimilating ASCAT and AMSR-E soil moisture data, both separately and together. Since the soil moisture retrieval skill from active and passive microwave data is thought to differ according to surface characteristics [2], the impact of each assimilation on the model soil moisture skill is assessed according to land cover type, by comparison to in situ soil moisture observations.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhu, Chunmei; Leung, Lai R.; Gochis, David
2009-11-29
The influence of antecedent soil moisture on North American monsoon system (NAMS) precipitation variability was explored using the MM5 mesoscale model coupled with the Variable Infiltration Capacity (VIC) land surface model. Sensitivity experiments were performed with extreme wet and dry initial soil moisture conditions for both the 1984 wet monsoon year and the 1989 dry year. The MM5-VIC model reproduced the key features of NAMS in 1984 and 1989 especially over northwestern Mexico. Our modeling results indicate that the land surface has memory of the initial soil wetness prescribed at the onset of the monsoon that persists over most ofmore » the region well into the monsoon season (e.g. until August). However, in contrast to the classical thermal contrast concept, where wetter soils lead to cooler surface temperatures, less land-sea thermal contrast, weaker monsoon circulations and less precipitation, the coupled model consistently demonstrated a positive soil moisture – precipitation feedback. Specifically, anomalously wet premonsoon soil moisture always lead to enhanced monsoon precipitation, and the reverse was also true. The surface temperature changes induced by differences in surface energy flux partitioning associated with pre-monsoon soil moisture anomalies changed the surface pressure and consequently the flow field in the coupled model, which in turn changed moisture convergence and, accordingly, precipitation patterns. Both the largescale circulation change and local land-atmospheric interactions in response to premonsoon soil moisture anomalies play important roles in the coupled model’s positive soil moisture monsoon precipitation feedback. However, the former may be sensitive to the strength and location of the thermal anomalies, thus leaving open the possibility of both positive and negative soil moisture precipitation feedbacks.« less
NASA Technical Reports Server (NTRS)
Bolten, John D.; Crow, Wade T.; Zhan, Xiwu; Jackson, Thomas J.; Reynolds,Curt
2010-01-01
Soil moisture is a fundamental data source used by the United States Department of Agriculture (USDA) International Production Assessment Division (IPAD) to monitor crop growth stage and condition and subsequently, globally forecast agricultural yields. Currently, the USDA IPAD estimates surface and root-zone soil moisture using a two-layer modified Palmer soil moisture model forced by global precipitation and temperature measurements. However, this approach suffers from well-known errors arising from uncertainty in model forcing data and highly simplified model physics. Here we attempt to correct for these errors by designing and applying an Ensemble Kalman filter (EnKF) data assimilation system to integrate surface soil moisture retrievals from the NASA Advanced Microwave Scanning Radiometer (AMSR-E) into the USDA modified Palmer soil moisture model. An assessment of soil moisture analysis products produced from this assimilation has been completed for a five-year (2002 to 2007) period over the North American continent between 23degN - 50degN and 128degW - 65degW. In particular, a data denial experimental approach is utilized to isolate the added utility of integrating remotely-sensed soil moisture by comparing EnKF soil moisture results obtained using (relatively) low-quality precipitation products obtained from real-time satellite imagery to baseline Palmer model runs forced with higher quality rainfall. An analysis of root-zone anomalies for each model simulation suggests that the assimilation of AMSR-E surface soil moisture retrievals can add significant value to USDA root-zone predictions derived from real-time satellite precipitation products.
Prediction of moisture variation during composting process: A comparison of mathematical models.
Wang, Yongjiang; Ai, Ping; Cao, Hongliang; Liu, Zhigang
2015-10-01
This study was carried out to develop and compare three models for simulating the moisture content during composting. Model 1 described changes in water content using mass balance, while Model 2 introduced a liquid-gas transferred water term. Model 3 predicted changes in moisture content without complex degradation kinetics. Average deviations for Model 1-3 were 8.909, 7.422 and 5.374 kg m(-3) while standard deviations were 10.299, 8.374 and 6.095, respectively. The results showed that Model 1 is complex and involves more state variables, but can be used to reveal the effect of humidity on moisture content. Model 2 tested the hypothesis of liquid-gas transfer and was shown to be capable of predicting moisture content during composting. Model 3 could predict water content well without considering degradation kinetics. Copyright © 2015 Elsevier Ltd. All rights reserved.
[How much does partially hydrolyzed guar gum affect the weight, moisture and hardness of feces?].
Sakata, Yukiko; Shimbo, Shinichiro
2006-04-01
The ministry of Health, Labor and Welfare recommends Japanese people to intake a certain amount of dietary fiber, believing that incorporating more dietary fiber into our diet can reduce the risk of colorectal cancer. The present study aimed to demonstrate and confirm the theory's validity by applying it to reality-to what extent is the intake of partially hydrolyzed guar gum (PHGG) useful in promoting bowel movements, and what problems are involved? We therefore investigated to what extent PHGG affects the weight, moisture and hardness of feces when healthy female students consumed PHGG as a supplement. During two fourteen-day sessions in spring and autumn, 9 healthy female students took the same diets. During the first session, the students were provided a strict dietary formula, while during the second session, they were administered an amount of 12.5 g/day PHGG (purity 80%, equivalent to 10 g of dietary fiber) dissolved in adequate amount of water at the end of each meal. Feces of the subjects were collected and weighted just after defection. A moisture meter was used to measure fecal moisture and a rheometer was used to measure fecal hardness. Fecal conditions and intestinal motility were also examined. (1) Due to the PHGG intake, the fecal bulk increased in 4 subjects and decreased in 2 subjects, significantly, out of 9. (2) Due to the PHGG intake, the fecal condition softened in 3 subjects while significantly hardening in 4 subjects. (3) The PHGG intake induced an increased of fecal moisture in 5 subjects, while moisture decreased in 2 subjects. (4) Fecal hardness measured more than 150 g/cm when it is classified as "frozen hard". (5) A significant inverse correlation could be seen between fecal hardness and fecal bulk, and between fecal hardness and its moisture. When PHGG was administered a significant inverse correlation could be seen between fecal hardness and its moisture. The conclusion is that the PHGG intake resulted in increase of the fecal bulk for 4 subjects and fecal moisture for 5 out of 9 subjects, but decrease of fecal hardness in 3 subjects; the benefit of bowel movements provided by the PHGG intake, however, varied greatly among the subjects.
What is the philosophy of modelling soil moisture movement?
NASA Astrophysics Data System (ADS)
Chen, J.; Wu, Y.
2009-12-01
In laboratory, the soil moisture movement in the different soil textures has been analysed. From field investigation, at a spot, the soil moisture movement in the root zone, vadose zone and shallow aquifer has been explored. In addition, on ground slopes, the interflow in the near surface soil layers has been studied. Along the regions near river reaches, the expansion and shrink of the saturated area due to rainfall occurrences have been observed. From those previous explorations regarding soil moisture movement, numerical models to represent this hydrologic process have been developed. However, generally, due to high heterogeneity and stratification of soil in a basin, modelling soil moisture movement is rather challenging. Normally, some empirical equations or artificial manipulation are employed to adjust the soil moisture movement in various numerical models. In this study, we inspect the soil moisture movement equations used in a watershed model, SWAT (Soil and Water Assessment Tool) (Neitsch et al., 2005), to examine the limitations of our knowledge in such a hydrologic process. Then, we adopt the features of a topographic-information based on a hydrologic model, TOPMODEL (Beven and Kirkby, 1979), to enhance the representation of soil moisture movement in SWAT. Basically, the results of the study reveal, to some extent, the philosophy of modelling soil moisture movement in numerical models, which will be presented in the conference. Beven, K.J. and Kirkby, M.J., 1979. A physically based variable contributing area model of basin hydrology. Hydrol. Science Bulletin, 24: 43-69. Neitsch, S.L., Arnold, J.G., Kiniry, J.R., Williams, J.R. and King, K.W., 2005. Soil and Water Assessment Tool Theoretical Documentation, Grassland, soil and research service, Temple, TX.
Remotely sensed soil moisture input to a hydrologic model
NASA Technical Reports Server (NTRS)
Engman, E. T.; Kustas, W. P.; Wang, J. R.
1989-01-01
The possibility of using detailed spatial soil moisture maps as input to a runoff model was investigated. The water balance of a small drainage basin was simulated using a simple storage model. Aircraft microwave measurements of soil moisture were used to construct two-dimensional maps of the spatial distribution of the soil moisture. Data from overflights on different dates provided the temporal changes resulting from soil drainage and evapotranspiration. The study site and data collection are described, and the soil measurement data are given. The model selection is discussed, and the simulation results are summarized. It is concluded that a time series of soil moisture is a valuable new type of data for verifying model performance and for updating and correcting simulated streamflow.
Subsurface Temperature, Moisture, Thermal Conductivity and Heat Flux, Barrow, Area A, B, C, D
Cable, William; Romanovsky, Vladimir
2014-03-31
Subsurface temperature data are being collected along a transect from the center of the polygon through the trough (and to the center of the adjacent polygon for Area D). Each transect has five 1.5m vertical array thermistor probes with 16 thermistors each. This dataset also includes soil pits that have been instrumented for temperature, water content, thermal conductivity, and heat flux at the permafrost table. Area C has a shallow borehole of 2.5 meters depth is instrumented in the center of the polygon.
US Steel Gary Works land based pushing emissions control
DOE Office of Scientific and Technical Information (OSTI.GOV)
Randolph, R.A.; Price, C.A.
1983-01-01
To meet air quality standards at its Gary Works Coke Plant in Gary, Indiana, US Steel Corporation has installed pushing emission control systems for its five (77) oven, three meter coke batteries. The pushing emission control system consists of a hooded coke guide, single spot catch car, stationary emission capture ducts and remote gas cleaning baghouse with precoat capabilities. The system is providing effective emission control. In addition, there are corollary benefits. The operation of the single spot catch cars is easier and safer and coke moisture variables have been reduced.
2010-02-01
the flue gas was measured with an S-type Pitot tube connected to an inclined oil manometer, and the temperature of the flue gas was measured with a...umbilical line, a vacuum pump, a dry gas meter, and a calibrated orifice connected to an inclined oil manometer. The moisture content was less than 2% so...flue gas was measured with an S-type Pitot tube connected to an inclined oil manometer, and the temperature of the flue gas was measured with a chromel
NASA Astrophysics Data System (ADS)
Wiß, Felix; Stacke, Tobias; Hagemann, Stefan
2014-05-01
Soil moisture and its memory can have a strong impact on near surface temperature and precipitation and have the potential to promote severe heat waves, dry spells and floods. To analyze how soil moisture is simulated in recent general circulation models (GCMs), soil moisture data from a 23 model ensemble of Atmospheric Model Intercomparison Project (AMIP) type simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5) are examined for the period 1979 to 2008 with regard to parameterization and statistical characteristics. With respect to soil moisture processes, the models vary in their maximum soil and root depth, the number of soil layers, the water-holding capacity, and the ability to simulate freezing which all together leads to very different soil moisture characteristics. Differences in the water-holding capacity are resulting in deviations in the global median soil moisture of more than one order of magnitude between the models. In contrast, the variance shows similar absolute values when comparing the models to each other. Thus, the input and output rates by precipitation and evapotranspiration, which are computed by the atmospheric component of the models, have to be in the same range. Most models simulate great variances in the monsoon areas of the tropics and north western U.S., intermediate variances in Europe and eastern U.S., and low variances in the Sahara, continental Asia, and central and western Australia. In general, the variance decreases with latitude over the high northern latitudes. As soil moisture trends in the models were found to be negligible, the soil moisture anomalies were calculated by subtracting the 30 year monthly climatology from the data. The length of the memory is determined from the soil moisture anomalies by calculating the first insignificant autocorrelation for ascending monthly lags (insignificant autocorrelation folding time). The models show a great spread of autocorrelation length from a few months in the tropics, north western Canada, eastern U.S. and northern Europe up to few years in the Sahara, the Arabian Peninsula, continental Eurasia and central U.S. Some models simulate very long memory all over the globe. This behavior is associated with differences between the models in the maximum root and soil depth. Models with shallow roots and deep soils exhibit longer memories than models with similar soil and root depths. Further analysis will be conducted to clearly divide models into groups based on their inter-model spatial correlation of simulated soil moisture characteristics.
SBIR Phase II Final Report: Low cost Autonomous NMR and Multi-sensor Soil Monitoring Instrument
DOE Office of Scientific and Technical Information (OSTI.GOV)
Walsh, David O.
In this 32-month SBIR Phase 2 program, Vista Clara designed, assembled and successfully tested four new NMR instruments for soil moisture measurement and monitoring: An enhanced performance man-portable Dart NMR logging probe and control unit for rapid, mobile measurement in core holes and 2” PVC access wells; A prototype 4-level Dart NMR monitoring probe and prototype multi-sensor soil monitoring control unit for long-term unattended monitoring of soil moisture and other measurements in-situ; A non-invasive 1m x 1m Discus NMR soil moisture sensor with surface based magnet/coil array for rapid measurement of soil moisture in the top 50 cm of themore » subsurface; A non-invasive, ultra-lightweight Earth’s field surface NMR instrument for non-invasive measurement and mapping of soil moisture in the top 3 meters of the subsurface. The Phase 2 research and development achieved most, but not all of our technical objectives. The single-coil Dart in-situ sensor and control unit were fully developed, demonstrated and successfully commercialized within the Phase 2 period of performance. The multi-level version of the Dart probe was designed, assembled and demonstrated in Phase 2, but its final assembly and testing were delayed until close to the end of the Phase 2 performance period, which limited our opportunities for demonstration in field settings. Likewise, the multi-sensor version of the Dart control unit was designed and assembled, but not in time for it to be deployed for any long-term monitoring demonstrations. The prototype ultra-lightweight surface NMR instrument was developed and demonstrated, and this result will be carried forward into the development of a new flexible surface NMR instrument and commercial product in 2018.« less
We have developed a coupled land-surface and dry deposition model for realistic treatment of surface fluxes of heat, moisture, and chemical dry deposition within a comprehensive air quality modeling system. A new land-surface model (LSM) with explicit treatment of soil moisture...
The Value of SMAP Soil Moisture Observations For Agricultural Applications
NASA Astrophysics Data System (ADS)
Mladenova, I. E.; Bolten, J. D.; Crow, W.; Reynolds, C. A.
2017-12-01
Knowledge of the amount of soil moisture (SM) in the root zone (RZ) is critical source of information for crop analysts and agricultural agencies as it controls crop development and crop condition changes and can largely impact end-of-season yield. Foreign Agricultural Services (FAS), a subdivision of U.S. Department of Agriculture (USDA) that is in charge with providing information on current and expected global crop supply and demand estimates, has been relying on RZSM estimates generated by the modified two-layer Palmer model, which has been enhanced to allow the assimilation of satellite-based soil moisture data. Generally the accuracy of model-based soil moisture estimates is dependent on the precision of the forcing data that drives the model and more specifically, the accuracy of the precipitation data. Data assimilation gives the opportunity to correct for such precipitation-related inaccuracies and enhance the quality of the model estimates. Here we demonstrate the value of ingesting passive-based soil moisture observations derived from the Soil Moisture Active Passive (SMAP) mission. In terms of agriculture, general understanding is that the change in soil moisture conditions precede the change in vegetation status, suggesting that soil moisture can be used as an early indicator of expected crop conditions. Therefore, we assess the accuracy of the SMAP enhanced Palmer model by examining the lag rank cross-correlation coefficient between the model generated soil moisture observations and the Normalized Difference Vegetation Index (NDVI).
NASA Astrophysics Data System (ADS)
DeLong, S.; Troch, P. A.; Barron-Gafford, G. A.; Huxman, T. E.; Pelletier, J. D.; Dontsova, K.; Niu, G.; Chorover, J.; Zeng, X.
2012-12-01
To meet the challenge of predicting landscape-scale changes in Earth system behavior, the University of Arizona has designed and constructed a new large-scale and community-oriented scientific facility - the Landscape Evolution Observatory (LEO). The primary scientific objectives are to quantify interactions among hydrologic partitioning, geochemical weathering, ecology, microbiology, atmospheric processes, and geomorphic change associated with incipient hillslope development. LEO consists of three identical, sloping, 333 m2 convergent landscapes inside a 5,000 m2 environmentally controlled facility. These engineered landscapes contain 1 meter of basaltic tephra ground to homogenous loamy sand and contains a spatially dense sensor and sampler network capable of resolving meter-scale lateral heterogeneity and sub-meter scale vertical heterogeneity in moisture, energy and carbon states and fluxes. Each ~1000 metric ton landscape has load cells embedded into the structure to measure changes in total system mass with 0.05% full-scale repeatability (equivalent to less than 1 cm of precipitation), to facilitate better quantification of evapotraspiration. Each landscape has an engineered rain system that allows application of precipitation at rates between3 and 45 mm/hr. These landscapes are being studied in replicate as "bare soil" for an initial period of several years. After this initial phase, heat- and drought-tolerant vascular plant communities will be introduced. Introduction of vascular plants is expected to change how water, carbon, and energy cycle through the landscapes, with potentially dramatic effects on co-evolution of the physical and biological systems. LEO also provides a physical comparison to computer models that are designed to predict interactions among hydrological, geochemical, atmospheric, ecological and geomorphic processes in changing climates. These computer models will be improved by comparing their predictions to physical measurements made in LEO. The main focus of our iterative modeling and measurement discovery cycle is to use rapid data assimilation to facilitate validation of newly coupled open-source Earth systems models. LEO will be a community resource for Earth system science research, education, and outreach. The LEO project operational philosophy includes 1) open and real-time availability of sensor network data, 2) a framework for community collaboration and facility access that includes integration of new or comparative measurement capabilities into existing facility cyberinfrastructure, 3) community-guided science planning and 4) development of novel education and outreach programs.Artistic rendering of the University of Arizona Landscape Evolution Observatory
Assimilation of SMOS Retrieved Soil Moisture into the Land Information System
NASA Technical Reports Server (NTRS)
Blankenship, Clay; Case, Jonathan; Zavodsky, Bradley; Jedlovec, Gary
2014-01-01
Soil moisture retrievals from the Soil Moisture and Ocean Salinity (SMOS) instrument are assimilated into the Noah land surface model (LSM) within the NASA Land Information System (LIS). Before assimilation, SMOS retrievals are bias-corrected to match the model climatological distribution using a Cumulative Distribution Function (CDF) matching approach. Data assimilation is done via the Ensemble Kalman Filter. The goal is to improve the representation of soil moisture within the LSM, and ultimately to improve numerical weather forecasts through better land surface initialization. We present a case study showing a large area of irrigation in the lower Mississippi River Valley, in an area with extensive rice agriculture. High soil moisture value in this region are observed by SMOS, but not captured in the forcing data. After assimilation, the model fields reflect the observed geographic patterns of soil moisture. Plans for a modeling experiment and operational use of the data are given. This work helps prepare for the assimilation of Soil Moisture Active/Passive (SMAP) retrievals in the near future.
Soil Moisture and the Persistence of North American Drought.
NASA Astrophysics Data System (ADS)
Oglesby, Robert J.; Erickson, David J., III
1989-11-01
We describe numerical sensitivity experiments exploring the effects of soil moisture on North American summertime climate using the NCAR CCMI, a 12-layer global atmospheric general circulation model. In particular. the hypothesis that reduced soil moisture may help induce and amplify warm, dry summers over midlatitude continental interiors is examined. Equilibrium climate statistics are computed for the perpetual July model response to imposed soil moisture anomalies over North America between 36° and 49°N. In addition, the persistence of imposed soil moisture anomalies is examined through use of the seasonal cycle mode of operation with use of various initial atmospheric states both equilibrated and nonequilibrated to the initial soil moisture anomaly.The climate statistics generated by thew model simulations resemble in a general way those of the summer of 1988, when extensive heat and drought occurred over much of North America. A reduction in soil moisture in the model leads to an increase in surface temperature, lower surface pressure, increased ridging aloft, and a northward shift of the jet stream. Low-level moisture advection from the Gulf of Mexico is important in determining where persistent soil moisture deficits can be maintained. In seasonal cycle simulations, it lock longer for an initially unequilibrated atmosphere to respond to the imposed soil moisture anomaly, via moisture transport from the Gulf of Mexico, than when initially the atmosphere was in equilibrium with the imposed anomaly., i.e., the initial state was obtained from the appropriate perpetual July simulation. The results demonstrate the important role of soil moisture in prolonging and/or amplifying North American summertime drought.
NASA Astrophysics Data System (ADS)
Zhang, Shuwen; Li, Haorui; Zhang, Weidong; Qiu, Chongjian; Li, Xin
2005-11-01
The paper investigates the ability to retrieve the true soil moisture profile by assimilating near-surface soil moisture into a soil moisture model with an ensemble Kaiman filter (EnKF) assimilation scheme, including the effect of ensemble size, update interval and nonlinearities in the profile retrieval, the required time for full retrieval of the soil moisture profiles, and the possible influence of the depth of the soil moisture observation. These questions are addressed by a desktop study using synthetic data. The “true” soil moisture profiles are generated from the soil moisture model under the boundary condition of 0.5 cm d-1 evaporation. To test the assimilation schemes, the model is initialized with a poor initial guess of the soil moisture profile, and different ensemble sizes are tested showing that an ensemble of 40 members is enough to represent the covariance of the model forecasts. Also compared are the results with those from the direct insertion assimilation scheme, showing that the EnKF is superior to the direct insertion assimilation scheme, for hourly observations, with retrieval of the soil moisture profile being achieved in 16 h as compared to 12 days or more. For daily observations, the true soil moisture profile is achieved in about 15 days with the EnKF, but it is impossible to approximate the true moisture within 18 days by using direct insertion. It is also found that observation depth does not have a significant effect on profile retrieval time for the EnKF. The nonlinearities have some negative influence on the optimal estimates of soil moisture profile but not very seriously.
Study of a dry room in a battery manufacturing plant using a process model
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ahmed, Shabbir; Nelson, Paul A.; Dees, Dennis W.
The manufacture of lithium ion batteries requires some processing steps to be carried out in a dry room, where the moisture content should remain below 100 parts per million. The design and operation of such a dry room adds to the cost of the battery. This paper studies the humidity management of the air to and from the dry room to understand the impact of design and operating parameters on the energy demand and the cost contribution towards the battery manufacturing cost. The study is conducted with the help of a process model for a dry room with a volumemore » of 16000 cubic meters. For a defined base case scenario it is found that the dry room operation has an energy demand of approximately 400 kW. The paper explores some tradeoffs in design and operating parameters by looking at the humidity reduction by quenching the make-up air vs. at the desiccant wheel, and the impact of the heat recovery from the desiccant regeneration cycle.« less
NASA Astrophysics Data System (ADS)
Drusch, M.
2007-02-01
Satellite-derived surface soil moisture data sets are readily available and have been used successfully in hydrological applications. In many operational numerical weather prediction systems the initial soil moisture conditions are analyzed from the modeled background and 2 m temperature and relative humidity. This approach has proven its efficiency to improve surface latent and sensible heat fluxes and consequently the forecast on large geographical domains. However, since soil moisture is not always related to screen level variables, model errors and uncertainties in the forcing data can accumulate in root zone soil moisture. Remotely sensed surface soil moisture is directly linked to the model's uppermost soil layer and therefore is a stronger constraint for the soil moisture analysis. For this study, three data assimilation experiments with the Integrated Forecast System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF) have been performed for the 2-month period of June and July 2002: a control run based on the operational soil moisture analysis, an open loop run with freely evolving soil moisture, and an experimental run incorporating TMI (TRMM Microwave Imager) derived soil moisture over the southern United States. In this experimental run the satellite-derived soil moisture product is introduced through a nudging scheme using 6-hourly increments. Apart from the soil moisture analysis, the system setup reflects the operational forecast configuration including the atmospheric 4D-Var analysis. Soil moisture analyzed in the nudging experiment is the most accurate estimate when compared against in situ observations from the Oklahoma Mesonet. The corresponding forecast for 2 m temperature and relative humidity is almost as accurate as in the control experiment. Furthermore, it is shown that the soil moisture analysis influences local weather parameters including the planetary boundary layer height and cloud coverage.
SMERGE: A multi-decadal root-zone soil moisture product for CONUS
NASA Astrophysics Data System (ADS)
Crow, W. T.; Dong, J.; Tobin, K. J.; Torres, R.
2017-12-01
Multi-decadal root-zone soil moisture products are of value for a range of water resource and climate applications. The NASA-funded root-zone soil moisture merging project (SMERGE) seeks to develop such products through the optimal merging of land surface model predictions with surface soil moisture retrievals acquired from multi-sensor remote sensing products. This presentation will describe the creation and validation of a daily, multi-decadal (1979-2015), vertically-integrated (both surface to 40 cm and surface to 100 cm), 0.125-degree root-zone product over the contiguous United States (CONUS). The modeling backbone of the system is based on hourly root-zone soil moisture simulations generated by the Noah model (v3.2) operating within the North American Land Data Assimilation System (NLDAS-2). Remotely-sensed surface soil moisture retrievals are taken from the multi-sensor European Space Agency Climate Change Initiative soil moisture data set (ESA CCI SM). In particular, the talk will detail: 1) the exponential smoothing approach used to convert surface ESA CCI SM retrievals into root-zone soil moisture estimates, 2) the averaging technique applied to merge (temporally-sporadic) remotely-sensed with (continuous) NLDAS-2 land surface model estimates of root-zone soil moisture into the unified SMERGE product, and 3) the validation of the SMERGE product using long-term, ground-based soil moisture datasets available within CONUS.
NASA Astrophysics Data System (ADS)
Chen, M.; Willgoose, G. R.; Saco, P. M.
2009-12-01
This paper investigates the soil moisture dynamics over two subcatchments (Stanley and Krui) in the Goulburn River in NSW during a three year period (2005-2007) using the Hydrus 1-D unsaturated soil water flow model. The model was calibrated to the seven Stanley microcatchment sites (1 sqkm site) using continuous time surface 30cm and full profile soil moisture measurements. Soil type, leaf area index and soil depth were found to be the key parameters changing model fit to the soil moisture time series. They either shifted the time series up or down, changed the steepness of dry-down recessions or determined the lowest point of soil moisture dry-down respectively. Good correlations were obtained between observed and simulated soil water storage (R=0.8-0.9) when calibrated parameters for one site were applied to the other sites. Soil type was also found to be the main determinant (after rainfall) of the mean of modelled soil moisture time series. Simulations of top 30cm were better than those of the whole soil profile. Within the Stanley microcatchment excellent soil moisture matches could be generated simply by adjusting the mean of soil moisture up or down slightly. Only minor modification of soil properties from site to site enable good fits for all of the Stanley sites. We extended the predictions of soil moisture to a larger spatial scale of the Krui catchment (sites up to 30km distant from Stanley) using soil and vegetation parameters from Stanley but the locally recorded rainfall at the soil moisture measurement site. The results were encouraging (R=0.7~0.8). These results show that it is possible to use a calibrated soil moisture model to extrapolate the soil moisture to other sites for a catchment with an area of up to 1000km2. This paper demonstrates the potential usefulness of continuous time, point scale soil moisture (typical of that measured by permanently installed TDR probes) in predicting the soil wetness status over a catchment of significant size.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Woods, Jason; Winkler, Jon
Moisture adsorption and desorption in building materials impact indoor humidity. This effect should be included in building-energy simulations, particularly when humidity is being investigated or controlled. Several models can calculate this moisture-buffering effect, but accurate ones require model inputs that are not always known to the user of the building-energy simulation. This research developed an empirical method to extract whole-house model inputs for the effective moisture penetration depth (EMPD) model. The experimental approach was to subject the materials in the house to a square-wave relative-humidity profile, measure all of the moisture-transfer terms (e.g., infiltration, air-conditioner condensate), and calculate the onlymore » unmeasured term—the moisture sorption into the materials. We validated this method with laboratory measurements, which we used to measure the EMPD model inputs of two houses. After deriving these inputs, we measured the humidity of the same houses during tests with realistic latent and sensible loads and demonstrated the accuracy of this approach. Furthermore, these results show that the EMPD model, when given reasonable inputs, is an accurate moisture-buffering model.« less
NASA Astrophysics Data System (ADS)
Chen, Zhuowei; Shi, Liangsheng; Ye, Ming; Zhu, Yan; Yang, Jinzhong
2018-06-01
Nitrogen reactive transport modeling is subject to uncertainty in model parameters, structures, and scenarios. By using a new variance-based global sensitivity analysis method, this paper identifies important parameters for nitrogen reactive transport with simultaneous consideration of these three uncertainties. A combination of three scenarios of soil temperature and two scenarios of soil moisture creates a total of six scenarios. Four alternative models describing the effect of soil temperature and moisture content are used to evaluate the reduction functions used for calculating actual reaction rates. The results show that for nitrogen reactive transport problem, parameter importance varies substantially among different models and scenarios. Denitrification and nitrification process is sensitive to soil moisture content status rather than to the moisture function parameter. Nitrification process becomes more important at low moisture content and low temperature. However, the changing importance of nitrification activity with respect to temperature change highly relies on the selected model. Model-averaging is suggested to assess the nitrification (or denitrification) contribution by reducing the possible model error. Despite the introduction of biochemical heterogeneity or not, fairly consistent parameter importance rank is obtained in this study: optimal denitrification rate (Kden) is the most important parameter; reference temperature (Tr) is more important than temperature coefficient (Q10); empirical constant in moisture response function (m) is the least important one. Vertical distribution of soil moisture but not temperature plays predominant role controlling nitrogen reaction. This study provides insight into the nitrogen reactive transport modeling and demonstrates an effective strategy of selecting the important parameters when future temperature and soil moisture carry uncertainties or when modelers face with multiple ways of establishing nitrogen models.
NASA Astrophysics Data System (ADS)
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.
Klinzing, Gerard R; Zavaliangos, Antonios
2016-08-01
This work establishes a predictive model that explicitly recognizes microstructural parameters in the description of the overall mass uptake and local gradients of moisture into tablets. Model equations were formulated based on local tablet geometry to describe the transient uptake of moisture. An analytical solution to a simplified set of model equations was solved to predict the overall mass uptake and moisture gradients with the tablets. The analytical solution takes into account individual diffusion mechanisms in different scales of porosity and diffusion into the solid phase. The time constant of mass uptake was found to be a function of several key material properties, such as tablet relative density, pore tortuosity, and equilibrium moisture content of the material. The predictions of the model are in excellent agreement with experimental results for microcrystalline cellulose tablets without the need for parameter fitting. The model presented provides a new method to analyze the transient uptake of moisture into hydrophilic materials with the knowledge of only a few fundamental material and microstructural parameters. In addition, the model allows for quick and insightful predictions of moisture diffusion for a variety of practical applications including pharmaceutical tablets, porous polymer systems, or cementitious materials. Copyright © 2016 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Wanders, N.; Karssenberg, D.; Bierkens, M. F. P.; Van Dam, J. C.; De Jong, S. M.
2012-04-01
Soil moisture is a key variable in the hydrological cycle and important in hydrological modelling. When assimilating soil moisture into flood forecasting models, the improvement of forecasting skills depends on the ability to accurately estimate the spatial and temporal patterns of soil moisture content throughout the river basin. Space-borne remote sensing may provide this information with a high temporal and spatial resolution and with a global coverage. Currently three microwave soil moisture products are available: AMSR-E, ASCAT and SMOS. The quality of these satellite-based products is often assessed by comparing them with in-situ observations of soil moisture. This comparison is however hampered by the difference in spatial and temporal support (i.e., resolution, scale), because the spatial resolution of microwave satellites is rather low compared to in-situ field measurements. Thus, the aim of this study is to derive a method to assess the uncertainty of microwave satellite soil moisture products at the correct spatial support. To overcome the difference in support size between in-situ soil moisture observations and remote sensed soil moisture, we used a stochastic, distributed unsaturated zone model (SWAP, van Dam (2000)) that is upscaled to the support of different satellite products. A detailed assessment of the SWAP model uncertainty is included to ensure that the uncertainty in satellite soil moisture is not overestimated due to an underestimation of the model uncertainty. We simulated unsaturated water flow up to a depth of 1.5m with a vertical resolution of 1 to 10 cm and on a horizontal grid of 1 km2 for the period Jan 2010 - Jun 2011. The SWAP model was first calibrated and validated on in-situ data of the REMEDHUS soil moisture network (Spain). Next, to evaluate the satellite products, the model was run for areas in the proximity of 79 meteorological stations in Spain, where model results were aggregated to the correct support of the satellite product by averaging model results from the 1 km2 grid within the remote sensing footprint. Overall 440 (AMSR-E, SMOS) to 680 (ASCAT) timeseries were compared to the aggregated SWAP model results, providing valuable information on the uncertainty of satellite soil moisture at the proper support. Our results show that temporal dynamics are best captured by ASCAT resulting in an average correlation of 0.72 with the model, while ASMR-E (0.41) and SMOS (0.42) are less capable of representing these dynamics. Standard deviations found for ASCAT and SMOS are low, 0.049 and 0.051m3m-3 respectively, while AMSR-E has a higher value of 0.062m3m-3. All standard deviations are higher than the average model uncertainty of 0.017m3m-3. All satellite products show a negative bias compared to the model results, with the largest value for SMOS. Satellite uncertainty is not found to be significantly related to topography, but is found to increase in densely vegetated areas. In general AMSR-E has most difficulties capturing soil moisture dynamics in Spain, while SMOS and mainly ASCAT have a fair to good performance. However, all products contain valuable information about the near-surface soil moisture over Spain. Van Dam, J.C., 2000, Field scale water flow and solute transport. SWAP model concepts, parameter estimation and case studies. Ph.D. thesis, Wageningen University
Evaluation of uncertainty in field soil moisture estimations by cosmic-ray neutron sensing
NASA Astrophysics Data System (ADS)
Scheiffele, Lena Maria; Baroni, Gabriele; Schrön, Martin; Ingwersen, Joachim; Oswald, Sascha E.
2017-04-01
Cosmic-ray neutron sensing (CRNS) has developed into a valuable, indirect and non-invasive method to estimate soil moisture at the field scale. It provides continuous temporal data (hours to days), relatively large depth (10-70 cm), and intermediate spatial scale measurements (hundreds of meters), thereby overcoming some of the limitations in point measurements (e.g., TDR/FDR) and of remote sensing products. All these characteristics make CRNS a favorable approach for soil moisture estimation, especially for applications in cropped fields and agricultural water management. Various studies compare CRNS measurements to soil sensor networks and show a good agreement. However, CRNS is sensitive to more characteristics of the land-surface, e.g. additional hydrogen pools, soil bulk density, and biomass. Prior to calibration the standard atmospheric corrections are accounting for the effects of air pressure, humidity and variations in incoming neutrons. In addition, the standard calibration approach was further extended to account for hydrogen in lattice water and soil organic material. Some corrections were also proposed to account for water in biomass. Moreover, the sensitivity of the probe was found to decrease with distance and a weighting procedure for the calibration datasets was introduced to account for the sensors' radial sensitivity. On the one hand, all the mentioned corrections showed to improve the accuracy in estimated soil moisture values. On the other hand, they require substantial additional efforts in monitoring activities and they could inherently contribute to the overall uncertainty of the CRNS product. In this study we aim (i) to quantify the uncertainty in the field soil moisture estimated by CRNS and (ii) to understand the role of the different sources of uncertainty. To this end, two experimental sites in Germany were equipped with a CRNS probe and compared to values of a soil moisture network. The agricultural fields were cropped with winter wheat (Pforzheim, 2013) and maize (Braunschweig, 2014) and differ in soil type and management. The results confirm a general good agreement between soil moisture estimated by CRNS and the soil moisture network. However, several sources of uncertainty were identified i.e., overestimation of dry conditions, strong effects of the additional hydrogen pools and an influence of the vertical soil moisture profile. Based on that, a global sensitivity analysis based on Monte Carlo sampling can be performed and evaluated in terms of soil moisture and footprint characteristics. The results allow quantifying the role of the different factors and identifying further improvements in the method.
Measuring Moisture Levels in Graphite Epoxy Composite Sandwich Structures
NASA Technical Reports Server (NTRS)
Nurge, Mark; Youngquist, Robert; Starr, Stanley
2011-01-01
Graphite epoxy composite (GEC) materials are used in the construction of rocket fairings, nose cones, interstage adapters, and heat shields due to their high strength and light weight. However, they absorb moisture depending on the environmental conditions they are exposed to prior to launch. Too much moisture absorption can become a problem when temperature and pressure changes experienced during launch cause the water to vaporize. The rapid state change of the water can result in structural failure of the material. In addition, heat and moisture combine to weaken GEC structures. Diffusion models that predict the total accumulated moisture content based on the environmental conditions are one accepted method of determining if the material strength has been reduced to an unacceptable level. However, there currently doesn t exist any field measurement technique to estimate the actual moisture content of a composite structure. A multi-layer diffusion model was constructed with Mathematica to predict moisture absorption and desorption from the GEC sandwich structure. This model is used in conjunction with relative humidity/temperature sensors both on the inside and outside of the material to determine the moisture levels in the structure. Because the core materials have much higher diffusivity than the face sheets, a single relative humidity measurement will accurately reflect the moisture levels in the core. When combined with an external relative humidity measurement, the model can be used to determine the moisture levels in the face sheets. Since diffusion is temperaturedependent, the temperature measurements are used to determine the diffusivity of the face sheets for the model computations.
Modeling Recharge - can it be Done?
NASA Astrophysics Data System (ADS)
Verburg, K.; Bond, W. J.; Smith, C. J.; Dunin, F. X.
2001-12-01
In sub-humid areas where rainfall is relatively low and sporadic, recharge (defined as water movement beyond the active root zone) is the small difference between the much larger numbers rainfall and evapotranspiration. It is very difficult to measure and often modeling is resorted to instead. But is modeling this small number any less difficult than measurement? In Australia there is considerable debate over the magnitude of recharge under different agricultural systems because of its contribution to rising saline groundwater levels following the clearing of native vegetation in the last 100 years. Hence the adequacy of measured and modeled estimates of recharge is under close scrutiny. Results will be presented for the water balance of an intensively monitored 8 year sequence of crops and pastures. Measurements included meteorological inputs, evapotranspiration measured with a pair of weighing lysimeters, and soil water content was measured with TDR and neutron moisture meter. Recharge was estimated from the percolate removed from the lysimeters as well as, when conditions were suitable, from soil water measurements and combined soil water and evapotranspiration measurements. This data was simulated using a comprehensive soil-plant-atmosphere model (APSIM). Comparison with field measurements shows that the recharge can be simulated with an accuracy similar to that with which it can be measured. However, is either sufficiently accurate for the applications for which they are required?
NASA Technical Reports Server (NTRS)
Maggioni, V.; Anagnostou, E. N.; Reichle, R. H.
2013-01-01
The contribution of rainfall forcing errors relative to model (structural and parameter) uncertainty in the prediction of soil moisture is investigated by integrating the NASA Catchment Land Surface Model (CLSM), forced with hydro-meteorological data, in the Oklahoma region. Rainfall-forcing uncertainty is introduced using a stochastic error model that generates ensemble rainfall fields from satellite rainfall products. The ensemble satellite rain fields are propagated through CLSM to produce soil moisture ensembles. Errors in CLSM are modeled with two different approaches: either by perturbing model parameters (representing model parameter uncertainty) or by adding randomly generated noise (representing model structure and parameter uncertainty) to the model prognostic variables. Our findings highlight that the method currently used in the NASA GEOS-5 Land Data Assimilation System to perturb CLSM variables poorly describes the uncertainty in the predicted soil moisture, even when combined with rainfall model perturbations. On the other hand, by adding model parameter perturbations to rainfall forcing perturbations, a better characterization of uncertainty in soil moisture simulations is observed. Specifically, an analysis of the rank histograms shows that the most consistent ensemble of soil moisture is obtained by combining rainfall and model parameter perturbations. When rainfall forcing and model prognostic perturbations are added, the rank histogram shows a U-shape at the domain average scale, which corresponds to a lack of variability in the forecast ensemble. The more accurate estimation of the soil moisture prediction uncertainty obtained by combining rainfall and parameter perturbations is encouraging for the application of this approach in ensemble data assimilation systems.
Adeeb A. Rahman; Thomas J. Urbanik; Mustafa Mahamid
2002-01-01
This research develops a model using finite element to study the response of a panel made of a typical commercial corrugated fireboard due to an induced moisture function at one side of the fiberboard. The model predicts how the moisture diffusion will permeate through the fiberboard's layers (medium and liners) providing information on moisture content at any...
A 3D moisture-stress FEM analysis for time dependent problems in timber structures
NASA Astrophysics Data System (ADS)
Fortino, Stefania; Mirianon, Florian; Toratti, Tomi
2009-11-01
This paper presents a 3D moisture-stress numerical analysis for timber structures under variable humidity and load conditions. An orthotropic viscoelastic-mechanosorptive material model is specialized on the basis of previous models. Both the constitutive model and the equations needed to describe the moisture flow across the structure are implemented into user subroutines of the Abaqus finite element code and a coupled moisture-stress analysis is performed for several types of mechanical loads and moisture changes. The presented computational approach is validated by analyzing some wood tests described in the literature and comparing the computational results with the reported experimental data.
Using SMAP to identify structural errors in hydrologic models
NASA Astrophysics Data System (ADS)
Crow, W. T.; Reichle, R. H.; Chen, F.; Xia, Y.; Liu, Q.
2017-12-01
Despite decades of effort, and the development of progressively more complex models, there continues to be underlying uncertainty regarding the representation of basic water and energy balance processes in land surface models. Soil moisture occupies a central conceptual position between atmosphere forcing of the land surface and resulting surface water fluxes. As such, direct observations of soil moisture are potentially of great value for identifying and correcting fundamental structural problems affecting these models. However, to date, this potential has not yet been realized using satellite-based retrieval products. Using soil moisture data sets produced by the NASA Soil Moisture Active/Passive mission, this presentation will explore the use of the remotely-sensed soil moisture data products as a constraint to reject certain types of surface runoff parameterizations within a land surface model. Results will demonstrate that the precision of the SMAP Level 4 Surface and Root-Zone soil moisture product allows for the robust sampling of correlation statistics describing the true strength of the relationship between pre-storm soil moisture and subsequent storm-scale runoff efficiency (i.e., total storm flow divided by total rainfall both in units of depth). For a set of 16 basins located in the South-Central United States, we will use these sampled correlations to demonstrate that so-called "infiltration-excess" runoff parameterizations under predict the importance of pre-storm soil moisture for determining storm-scale runoff efficiency. To conclude, we will discuss prospects for leveraging this insight to improve short-term hydrologic forecasting and additional avenues for SMAP soil moisture products to provide process-level insight for hydrologic modelers.
NASA Astrophysics Data System (ADS)
Karssenberg, D.; Wanders, N.; de Roo, A.; de Jong, S.; Bierkens, M. F.
2013-12-01
Large-scale hydrological models are nowadays mostly calibrated using observed discharge. As a result, a large part of the hydrological system that is not directly linked to discharge, in particular the unsaturated zone, remains uncalibrated, or might be modified unrealistically. Soil moisture observations from satellites have the potential to fill this gap, as these provide the closest thing to a direct measurement of the state of the unsaturated zone, and thus are potentially useful in calibrating unsaturated zone model parameters. This is expected to result in a better identification of the complete hydrological system, potentially leading to improved forecasts of the hydrograph as well. Here we evaluate this added value of remotely sensed soil moisture in calibration of large-scale hydrological models by addressing two research questions: 1) Which parameters of hydrological models can be identified by calibration with remotely sensed soil moisture? 2) Does calibration with remotely sensed soil moisture lead to an improved calibration of hydrological models compared to approaches that calibrate only with discharge, such that this leads to improved forecasts of soil moisture content and discharge as well? To answer these questions we use a dual state and parameter ensemble Kalman filter to calibrate the hydrological model LISFLOOD for the Upper Danube area. Calibration is done with discharge and remotely sensed soil moisture acquired by AMSR-E, SMOS and ASCAT. Four scenarios are studied: no calibration (expert knowledge), calibration on discharge, calibration on remote sensing data (three satellites) and calibration on both discharge and remote sensing data. Using a split-sample approach, the model is calibrated for a period of 2 years and validated for the calibrated model parameters on a validation period of 10 years. Results show that calibration with discharge data improves the estimation of groundwater parameters (e.g., groundwater reservoir constant) and routing parameters. Calibration with only remotely sensed soil moisture results in an accurate calibration of parameters related to land surface process (e.g., the saturated conductivity of the soil), which is not possible when calibrating on discharge alone. For the upstream area up to 40000 km2, calibration on both discharge and soil moisture results in a reduction by 10-30 % in the RMSE for discharge simulations, compared to calibration on discharge alone. For discharge in the downstream area, the model performance due to assimilation of remotely sensed soil moisture is not increased or slightly decreased, most probably due to the longer relative importance of the routing and contribution of groundwater in downstream areas. When microwave soil moisture is used for calibration the RMSE of soil moisture simulations decreases from 0.072 m3m-3 to 0.062 m3m-3. The conclusion is that remotely sensed soil moisture holds potential for calibration of hydrological models leading to a better simulation of soil moisture content throughout and a better simulation of discharge in upstream areas, particularly if discharge observations are sparse.
Mechanisms of northeastern Brazil rainfall anomalies due to Southern Tropical Atlantic variability
NASA Astrophysics Data System (ADS)
Neelin, J.; Su, H.
2004-05-01
Observational studies have shown that the rainfall anomalies in eastern equatorial South America, including Nordeste Brazil, have a positive correlation with tropical southern Atlantic sea surface temperature (SST) anomalies. Such relationships are reproduced in model simulations with the quasi-equilibrium tropical circulation model (QTCM), which includes a simple land model. A suite of model ensemble experiments is analysed using observed SST over the tropical oceans, the tropical Atlantic and the tropical southern Atlantic (30S-0), respectively (with climatological SST in the remainder of the oceans). Warm tropical south Atlantic SST anomalies yield positive precipitation anomalies over the Nordeste and the southern edge of the Atlantic marine intertropical convergence zone (ITCZ). Mechanisms associated with moisture variations are responsible for the land precipitation changes. Increases in moisture over the Atlantic cause positive anomalies in moisture advection, spreading increased moisture downwind. Where the basic state is far from the convective stability threshold, moisture changes have little effect, but the margins of the climatological convection zone are affected. The increased moisture supply due to advection is enhanced by increases in low-level convergence required by moist static energy balances. The moisture convergence term is several times larger, but experiments altering the moisture advection confirm that the feedback is initiated by wind acting on moisture gradient. This mechanism has several features in common with the recently published "upped-ante" mechanism for El Nino impacts on this region. In that case, the moisture gradient is initiated by warm free tropospheric temperature anomalies increasing the typical value of low-level moisture required to sustain convection in the convection zones. Both mechanisms suggest the usefulness of coordinating ocean and land in situ observations of boundary layer moisture.
Using Whole-House Field Tests to Empirically Derive Moisture Buffering Model Inputs
DOE Office of Scientific and Technical Information (OSTI.GOV)
Woods, J.; Winkler, J.; Christensen, D.
2014-08-01
Building energy simulations can be used to predict a building's interior conditions, along with the energy use associated with keeping these conditions comfortable. These models simulate the loads on the building (e.g., internal gains, envelope heat transfer), determine the operation of the space conditioning equipment, and then calculate the building's temperature and humidity throughout the year. The indoor temperature and humidity are affected not only by the loads and the space conditioning equipment, but also by the capacitance of the building materials, which buffer changes in temperature and humidity. This research developed an empirical method to extract whole-house model inputsmore » for use with a more accurate moisture capacitance model (the effective moisture penetration depth model). The experimental approach was to subject the materials in the house to a square-wave relative humidity profile, measure all of the moisture transfer terms (e.g., infiltration, air conditioner condensate) and calculate the only unmeasured term: the moisture absorption into the materials. After validating the method with laboratory measurements, we performed the tests in a field house. A least-squares fit of an analytical solution to the measured moisture absorption curves was used to determine the three independent model parameters representing the moisture buffering potential of this house and its furnishings. Follow on tests with realistic latent and sensible loads showed good agreement with the derived parameters, especially compared to the commonly-used effective capacitance approach. These results show that the EMPD model, once the inputs are known, is an accurate moisture buffering model.« less
NASA Technical Reports Server (NTRS)
Li, Bailing; Toll, David; Zhan, Xiwu; Cosgrove, Brian
2011-01-01
Model simulated soil moisture fields are often biased due to errors in input parameters and deficiencies in model physics. Satellite derived soil moisture estimates, if retrieved appropriately, represent the spatial mean of soil moisture in a footprint area, and can be used to reduce model bias (at locations near the surface) through data assimilation techniques. While assimilating the retrievals can reduce model bias, it can also destroy the mass balance enforced by the model governing equation because water is removed from or added to the soil by the assimilation algorithm. In addition, studies have shown that assimilation of surface observations can adversely impact soil moisture estimates in the lower soil layers due to imperfect model physics, even though the bias near the surface is decreased. In this study, an ensemble Kalman filter (EnKF) with a mass conservation updating scheme was developed to assimilate the actual value of Advanced Microwave Scanning Radiometer (AMSR-E) soil moisture retrievals to improve the mean of simulated soil moisture fields by the Noah land surface model. Assimilation results using the conventional and the mass conservation updating scheme in the Little Washita watershed of Oklahoma showed that, while both updating schemes reduced the bias in the shallow root zone, the mass conservation scheme provided better estimates in the deeper profile. The mass conservation scheme also yielded physically consistent estimates of fluxes and maintained the water budget. Impacts of model physics on the assimilation results are discussed.
NASA Technical Reports Server (NTRS)
Arya, L. M.; Richter, J. C.; Davidson, S. A. (Principal Investigator)
1982-01-01
Soil moisture characteristics predicted by the Arya-Paris model were compared with the laboratory measured data for 181 New Jersey soil horizons. For a number of soil horizons, the predicted and the measured moisture characteristic curves are almost coincident; for a large number of other horizons, despite some disparity, their shapes are strikingly similar. Uncertainties in the model input and laboratory measurement of the moisture characteristic are indicated, and recommendations for additional experimentation and testing are made.
Assimilating soil moisture into an Earth System Model
NASA Astrophysics Data System (ADS)
Stacke, Tobias; Hagemann, Stefan
2017-04-01
Several modelling studies reported potential impacts of soil moisture anomalies on regional climate. In particular for short prediction periods, perturbations of the soil moisture state may result in significant alteration of surface temperature in the following season. However, it is not clear yet whether or not soil moisture anomalies affect climate also on larger temporal and spatial scales. In an earlier study, we showed that soil moisture anomalies can persist for several seasons in the deeper soil layers of a land surface model. Additionally, those anomalies can influence root zone moisture, in particular during explicitly dry or wet periods. Thus, one prerequisite for predictability, namely the existence of long term memory, is evident for simulated soil moisture and might be exploited to improve climate predictions. The second prerequisite is the sensitivity of the climate system to soil moisture. In order to investigate this sensitivity for decadal simulations, we implemented a soil moisture assimilation scheme into the Max-Planck Institute for Meteorology's Earth System Model (MPI-ESM). The assimilation scheme is based on a simple nudging algorithm and updates the surface soil moisture state once per day. In our experiments, the MPI-ESM is used which includes model components for the interactive simulation of atmosphere, land and ocean. Artificial assimilation data is created from a control simulation to nudge the MPI-ESM towards predominantly dry and wet states. First analyses are focused on the impact of the assimilation on land surface variables and reveal distinct differences in the long-term mean values between wet and dry state simulations. Precipitation, evapotranspiration and runoff are larger in the wet state compared to the dry state, resulting in an increased moisture transport from the land to atmosphere and ocean. Consequently, surface temperatures are lower in the wet state simulations by more than one Kelvin. In terms of spatial pattern, the largest differences between both simulations are seen for continental areas, while regions with a maritime climate are least sensitive to soil moisture assimilation.
NASA Astrophysics Data System (ADS)
Fahim, A. M.; Shen, R.; Yue, Z.; Di, W.; Mushtaq Shah, S.
2015-12-01
Moisture in the upper most layer of soil column from 14 different models under Coupled Model Intercomparison Project Phase-5 (CMIP5) project were analyzed for four seasons of the year. Aim of this study was to explore variability in soil moisture over south Asia using multi model ensemble and relationship between summer rainfall and soil moisture for spring and summer season. GLDAS (Global Land Data Assimilation System) dataset set was used for comparing CMIP5 ensemble mean soil moisture in different season. Ensemble mean represents soil moisture well in accordance with the geographical features; prominent arid regions are indicated profoundly. Empirical Orthogonal Function (EOF) analysis was applied to study the variability. First component of EOF explains 17%, 16%, 11% and 11% variability for spring, summer, autumn and winter season respectively. Analysis reveal increasing trend in soil moisture over most parts of Afghanistan, Central and north western parts of Pakistan, northern India and eastern to south eastern parts of China, in spring season. During summer, south western part of India exhibits highest negative trend while rest of the study area show minute trend (increasing or decreasing). In autumn, south west of India is under highest negative loadings. During winter season, north western parts of study area show decreasing trend. Summer rainfall has very week (negative or positive) spatial correlation, with spring soil moisture, while possess higher correlation with summer soil moisture. Our studies have significant contribution to understand complex nature of land - atmosphere interactions, as soil moisture prediction plays an important role in the cycle of sink and source of many air pollutants. Next level of research should be on filling the gaps between accurately measuring the soil moisture using satellite remote sensing and land surface modelling. Impact of soil moisture in tracking down different types of pollutant will also be studied.
NASA Astrophysics Data System (ADS)
Willgoose, G. R.; Chen, M.; Cohen, S.; Saco, P. M.; Hancock, G. R.
2013-12-01
In humid areas it is generally considered that soil moisture scales spatially according to the wetness index of the landscape. This scaling arises from lateral flow downslope of ground water within the soil zone. However, in semi-arid and drier regions, this lateral flow is small and fluxes are dominated by vertical flows driven by infiltration and evapotranspiration. Thus, in the absence of runon processes, soil moisture at a location is more driven by local factors such as soil and vegetation properties at that location rather than upstream processes draining to that point. The 'apparent' spatial randomness of soil and vegetation properties generally suggests that soil moisture for semi-arid regions is spatially random. In this presentation a new analysis of neutron probe data during summer from the Tarrawarra site near Melbourne, Australia shows persistent spatial organisation of soil moisture over several years. This suggests a link between permanent features of the catchment (e.g. soil properties) and soil moisture distribution, even though the spatial pattern of soil moisture during the 4 summers monitored appears spatially random. This and other data establishes a prima facie case that soil variations drive spatial variation in soil moisture. Accordingly, we used a previously published spatial scaling relationship for soil properties derived using the mARM pedogenesis model to simulate the spatial variation of soil grading. This soil grading distribution was used in the Rosetta pedotransfer model to derive a spatial distribution of soil functional properties (e.g. saturated hydraulic conductivity, porosity). These functional properties were then input into the HYDRUS-1D soil moisture model and soil moisture simulated for 3 years at daily resolution. The HYDRUS model used had previously been calibrated to field observed soil moisture data at our SASMAS field site. The scaling behaviour of soil moisture derived from this modelling will be discussed and compared with observed data from our SASMAS field sites.
NASA Astrophysics Data System (ADS)
Sanchez-Mejia, Z. M.; Papuga, S. A.
2013-12-01
In semiarid regions, where water resources are limited and precipitation dynamics are changing, understanding land surface-atmosphere interactions that regulate the coupled soil moisture-precipitation system is key for resource management and planning. We present a modeling approach to study soil moisture and albedo controls on planetary boundary layer height (PBLh). We used data from the Santa Rita Creosote Ameriflux site and Tucson Airport atmospheric sounding to generate empirical relationships between soil moisture, albedo and PBLh. We developed empirical relationships and show that at least 50% of the variation in PBLh can be explained by soil moisture and albedo. Then, we used a stochastically driven two-layer bucket model of soil moisture dynamics and our empirical relationships to model PBLh. We explored soil moisture dynamics under three different mean annual precipitation regimes: current, increase, and decrease, to evaluate at the influence on soil moisture on land surface-atmospheric processes. While our precipitation regimes are simple, they represent future precipitation regimes that can influence the two soil layers in our conceptual framework. For instance, an increase in annual precipitation, could impact on deep soil moisture and atmospheric processes if precipitation events remain intense. We observed that the response of soil moisture, albedo, and the PBLh will depend not only on changes in annual precipitation, but also on the frequency and intensity of this change. We argue that because albedo and soil moisture data are readily available at multiple temporal and spatial scales, developing empirical relationships that can be used in land surface - atmosphere applications are of great value.
Snyder, Charles T.; Frickel, D.G.; Hadley, R.F.; Miller, R.F.
1976-01-01
Two widely separated sites in California used for motorcycle hill-climbing were studied to evaluate the impact on the landscape and hydrology. At Panoche Hills in central California, an area formerly used by motorcycles together with an adjacent unused area were monitored from 1971 to 1975. Observations in both areas included measurements of precipitation, runoff, soil moisture, soil bulk density, plant cover, and erosion surveys. At Dove Spring Canyon in souther California erosion was measured on a site that is currently being used for motorcycle hill-climbing. At the Panoche Hills site, the area used by motorcycles produced about eight times as nuch runoff as the unused area. Similarly, sediment yield from the used areas was 857 cubic meters/sq km, while the quantity of sediment from the unused area was not measurable by standard methods. At the Dove Spring Canyon site, which is still being used for hill-climbing, erosion surveys show that degradation in trails has been as much as 0.3 m in the period 1973-75. Compaction of soils and reduction of permeability appears to be the most serious hydrologic impact of motorcycle use at Panoche Hills. Increased bulk density of soils reduces depth of moisture penetration which deprives plants of moisture needed for growth. (Woodard-USGS)
Moisture origin and transport processes in Colombia, northern South America
NASA Astrophysics Data System (ADS)
Hoyos, I.; Dominguez, F.; Cañón-Barriga, J.; Martínez, J. A.; Nieto, R.; Gimeno, L.; Dirmeyer, P. A.
2018-02-01
We assess the spatial structure of moisture flux divergence, regional moisture sources and transport processes over Colombia, in northern South America. Using three independent methods the dynamic recycling model (DRM), FLEXPART and the Quasi-isentropic back-trajectory (QIBT) models we quantify the moisture sources that contribute to precipitation over the region. We find that moisture from the Atlantic Ocean and terrestrial recycling are the most important sources of moisture for Colombia, highlighting the importance of the Orinoco and Amazon basins as regional providers of atmospheric moisture. The results show the influence of long-range cross-equatorial flow from the Atlantic Ocean into the target region and the role of the study area as a passage of moisture into South America. We also describe the seasonal moisture transport mechanisms of the well-known low-level westerly and Caribbean jets that originate in the Pacific Ocean and Caribbean Sea, respectively. We find that these dynamical systems play an important role in the convergence of moisture over western Colombia.
Assimilation of SMOS (and SMAP) Retrieved Soil Moisture into the Land Information System
NASA Technical Reports Server (NTRS)
Blankenship, Clay; Zavodsky, Bradley; Case, Jonathan; Stano, Geoffrey
2016-01-01
Goal: Accurate, high-resolution (approx.3 km) soil moisture in near-real time. Situational awareness (drought assessment, flood and fire threat). Local modeling applications (to improve sfc-PBL exchanges) Method: Assimilate satellite soil moisture retrievals into a land surface model. Combines high-resolution geophysical model data with latest satellite observations.
NASA Astrophysics Data System (ADS)
Ek, M. B.; Yang, R.
2016-12-01
Skillful short-term weather forecasts, which rely heavily on quality atmospheric initial conditions, have a fundamental limit of about two weeks owing to the chaotic nature of the atmosphere. Useful forecasts at sub-seasonal to seasonal time scales, on the other hand, require well-simulated large-scale atmospheric response to slowly varying lower boundary forcings from both the ocean and land surface. The critical importance of ocean has been recognized, where the ocean indices have been used in a variety of climate applications. In contrast, the impact of land surface anomalies, especially soil moisture and associated evaporation, has been proven notably difficult to demonstrate. The Noah Land Surface Model (LSM) is the land component of NCEP CFS version 2 (CFSv2) used for seasonal predictions. The Noah LSM originates from the Oregon State University (OSU) LSM. The evaporation control in the Noah LSM is based on the Penman-Monteith equation, which takes into account the solar radiation, relative humidity, air temperature, and soil moisture effects. The Noah LSM is configured with four soil layers with a fixed depth of 2 meters and free drainage at the bottom soil layer. This treatment assumes that the soil water table depth is well within the specified range, and also potentially misrepresents the soil moisture memory effects at seasonal time scales. To overcome the limitation, an unconfined aquifer is attached to the bottom of the soil to allow the water table to move freely up and down. In addition, in conjunction with the water table, an alternative Ball-Berry photosynthesis-based evaporation parameterization is examined to evaluate the impact from using a different evaporation control methodology. Focusing on the 2011 and 2012 intense summer droughts in the central US, seasonal ensemble forecast experiments with early May initial conditions are carried out for the two years using an enhanced version of CFSv2, where the atmospheric component of the CFSv2 is coupled to the Noah Multiple-Parameterization (Noah-MP) land model. The Noah-MP has different options for ground water and evaporation control parameterizations. The differences will be presented and results will be discussed.
Nolet, Corjan; Poortinga, Ate; Roosjen, Peter; Bartholomeus, Harm; Ruessink, Gerben
2014-01-01
Surface moisture is an important supply limiting factor for aeolian sand transport, which is the primary driver of coastal dune development. As such, it is critical to account for the control of surface moisture on available sand for dune building. Optical remote sensing has the potential to measure surface moisture at a high spatio-temporal resolution. It is based on the principle that wet sand appears darker than dry sand: it is less reflective. The goals of this study are (1) to measure and model reflectance under controlled laboratory conditions as function of wavelength () and surface moisture () over the optical domain of 350–2500 nm, and (2) to explore the implications of our laboratory findings for accurately mapping the distribution of surface moisture under natural conditions. A laboratory spectroscopy experiment was conducted to measure spectral reflectance (1 nm interval) under different surface moisture conditions using beach sand. A non-linear increase of reflectance upon drying was observed over the full range of wavelengths. Two models were developed and tested. The first model is grounded in optics and describes the proportional contribution of scattering and absorption of light by pore water in an unsaturated sand matrix. The second model is grounded in soil physics and links the hydraulic behaviour of pore water in an unsaturated sand matrix to its optical properties. The optical model performed well for volumetric moisture content 24% ( 0.97), but underestimated reflectance for between 24–30% ( 0.92), most notable around the 1940 nm water absorption peak. The soil-physical model performed very well ( 0.99) but is limited to 4% 24%. Results from a field experiment show that a short-wave infrared terrestrial laser scanner ( = 1550 nm) can accurately relate surface moisture to reflectance (standard error 2.6%), demonstrating its potential to derive spatially extensive surface moisture maps of a natural coastal beach. PMID:25383709
J. D. Carlson; Larry S. Bradshaw; Ralph M. Nelson; Randall R Bensch; Rafal Jabrzemski
2007-01-01
The application of a next-generation dead-fuel moisture model, the 'Nelson model', to four timelag fuel classes using an extensive 21-month dataset of dead-fuel moisture observations is described. Developed by Ralph Nelson in the 1990s, the Nelson model is a dead-fuel moisture model designed to take advantage of frequent automated weather observations....
26. CURRENT METERS WITH FOLDING SCALE (MEASURED IN INCHES) IN ...
26. CURRENT METERS WITH FOLDING SCALE (MEASURED IN INCHES) IN FOREGROUND: GURLEY MODEL NO. 665 AT CENTER, GURLEY MODEL NO. 625 'PYGMY' CURRENT METER AT LEFT, AND WES MINIATURE PRICE-TYPE CURRENT METER AT RIGHT. - Waterways Experiment Station, Hydraulics Laboratory, Halls Ferry Road, 2 miles south of I-20, Vicksburg, Warren County, MS
Inversion of Farmland Soil Moisture in Large Region Based on Modified Vegetation Index
NASA Astrophysics Data System (ADS)
Wang, J. X.; Yu, B. S.; Zhang, G. Z.; Zhao, G. C.; He, S. D.; Luo, W. R.; Zhang, C. C.
2018-04-01
Soil moisture is an important parameter for agricultural production. Efficient and accurate monitoring of soil moisture is an important link to ensure the safety of agricultural production. Remote sensing technology has been widely used in agricultural moisture monitoring because of its timeliness, cyclicality, dynamic tracking of changes in things, easy access to data, and extensive monitoring. Vegetation index and surface temperature are important parameters for moisture monitoring. Based on NDVI, this paper introduces land surface temperature and average temperature for optimization. This article takes the soil moisture in winter wheat growing area in Henan Province as the research object, dividing Henan Province into three main regions producing winter wheat and dividing the growth period of winter wheat into the early, middle and late stages on the basis of phenological characteristics and regional characteristics. Introducing appropriate correction factor during the corresponding growth period of winter wheat, correcting the vegetation index in the corresponding area, this paper establishes regression models of soil moisture on NDVI and soil moisture on modified NDVI based on correlation analysis and compare models. It shows that modified NDVI is more suitable as a indicator of soil moisture because of the better correlation between soil moisture and modified NDVI and the higher prediction accuracy of the regression model of soil moisture on modified NDVI. The research in this paper has certain reference value for winter wheat farmland management and decision-making.
Friedel, Michael J.
2001-01-01
This report describes a model for simulating transient, Variably Saturated, coupled water-heatsolute Transport in heterogeneous, anisotropic, 2-Dimensional, ground-water systems with variable fluid density (VST2D). VST2D was developed to help understand the effects of natural and anthropogenic factors on quantity and quality of variably saturated ground-water systems. The model solves simultaneously for one or more dependent variables (pressure, temperature, and concentration) at nodes in a horizontal or vertical mesh using a quasi-linearized general minimum residual method. This approach enhances computational speed beyond the speed of a sequential approach. Heterogeneous and anisotropic conditions are implemented locally using individual element property descriptions. This implementation allows local principal directions to differ among elements and from the global solution domain coordinates. Boundary conditions can include time-varying pressure head (or moisture content), heat, and/or concentration; fluxes distributed along domain boundaries and/or at internal node points; and/or convective moisture, heat, and solute fluxes along the domain boundaries; and/or unit hydraulic gradient along domain boundaries. Other model features include temperature and concentration dependent density (liquid and vapor) and viscosity, sorption and/or decay of a solute, and capability to determine moisture content beyond residual to zero. These features are described in the documentation together with development of the governing equations, application of the finite-element formulation (using the Galerkin approach), solution procedure, mass and energy balance considerations, input requirements, and output options. The VST2D model was verified, and results included solutions for problems of water transport under isohaline and isothermal conditions, heat transport under isobaric and isohaline conditions, solute transport under isobaric and isothermal conditions, and coupled water-heat-solute transport. The first three problems considered in model verification were compared to either analytical or numerical solutions, whereas the coupled problem was compared to measured laboratory results for which no known analytic solutions or numerical models are available. The test results indicate the model is accurate and applicable for a wide range of conditions, including when water (liquid and vapor), heat (sensible and latent), and solute are coupled in ground-water systems. The cumulative residual errors for the coupled problem tested was less than 10-8 cubic centimeter per cubic centimeter, 10-5 moles per kilogram, and 102 calories per cubic meter for liquid water content, solute concentration and heat content, respectively. This model should be useful to hydrologists, engineers, and researchers interested in studying coupled processes associated with variably saturated transport in ground-water systems.
NASA Astrophysics Data System (ADS)
Wu, Mousong; Sholze, Marko
2017-04-01
We investigated the importance of soil moisture data on assimilation of a terrestrial biosphere model (BETHY) for a long time period from 2010 to 2015. Totally, 101 parameters related to carbon turnover, soil respiration, as well as soil texture were selected for optimization within a carbon cycle data assimilation system (CCDAS). Soil moisture data from Soil Moisture and Ocean Salinity (SMOS) product was derived for 10 sites representing different plant function types (PFTs) as well as different climate zones. Uncertainty of SMOS soil moisture data was also estimated using triple collocation analysis (TCA) method by comparing with ASCAT dataset and BETHY forward simulation results. Assimilation of soil moisture to the system improved soil moisture as well as net primary productivity(NPP) and net ecosystem productivity (NEP) when compared with soil moisture derived from in-situ measurements and fluxnet datasets. Parameter uncertainties were largely reduced relatively to prior values. Using SMOS soil moisture data for assimilation of a terrestrial biosphere model proved to be an efficient approach in reducing uncertainty in ecosystem fluxes simulation. It could be further used in regional an global assimilation work to constrain carbon dioxide concentration simulation by combining with other sources of measurements.
NASA Astrophysics Data System (ADS)
Srivastava, Prashant K., ,, Dr.; O'Neill, Peggy, ,, Dr.
2014-05-01
Soil moisture is an important element for weather and climate prediction, hydrological sciences, and applications. Hence, measurements of this hydrologic variable are required to improve our understanding of hydrological processes, ecosystem functions, and the linkages between the Earth's water, energy, and carbon cycles (Srivastava et al. 2013). The retrieval of soil moisture depends not only on parameterizations in the retrieval algorithm but also on the soil dielectric mixing models used (Behari 2005). Although a number of soil dielectric mixing models have been developed, testing these models for soil moisture retrieval has still not been fully explored, especially with SMAP-like simulators. The main objective of this work focuses on testing different dielectric models for soil moisture retrieval using the Combined Radar/Radiometer (ComRAD) ground-based L-band simulator developed jointly by NASA/GSFC and George Washington University (O'Neill et al., 2006). The ComRAD system was deployed during a field experiment in 2012 in order to provide long active/passive measurements of two crops under controlled conditions during an entire growing season. L-band passive data were acquired at a look angle of 40 degree from nadir at both horizontal & vertical polarization. Currently, there are many dielectric models available for soil moisture retrieval; however, four dielectric models (Mironov, Dobson, Wang & Schmugge and Hallikainen) were tested here and found to be promising for soil moisture retrieval (some with higher performances). All the above-mentioned dielectric models were integrated with Single Channel Algorithms using H (SCA-H) and V (SCA-V) polarizations for the soil moisture retrievals. All the ground-based observations were collected from test site-United States Department of Agriculture (USDA) OPE3, located a few miles away from NASA GSFC. Ground truth data were collected using a theta probe and in situ sensors which were then used for validation. Analysis indicated a higher performance in terms of soil moisture retrieval accuracy for the Mironov dielectric model (RMSE of 0.035 m3/m3), followed by Dobson, Wang & Schmugge, and Hallikainen. This analysis indicates that Mironov dielectric model is promising for passive-only microwave soil moisture retrieval and could be a useful choice for SMAP satellite soil moisture retrieval. Keywords: Dielectric models; Single Channel Algorithm, Combined Radar/Radiometer, Soil moisture; L band References: Behari, J. (2005). Dielectric Behavior of Soil (pp. 22-40). Springer Netherlands O'Neill, P. E., Lang, R. H., Kurum, M., Utku, C., & Carver, K. R. (2006), Multi-Sensor Microwave Soil Moisture Remote Sensing: NASA's Combined Radar/Radiometer (ComRAD) System. In IEEE MicroRad, 2006 (pp. 50-54). IEEE. Srivastava, P. K., Han, D., Rico Ramirez, M. A., & Islam, T. (2013), Appraisal of SMOS soil moisture at a catchment scale in a temperate maritime climate. Journal of Hydrology, 498, 292-304. USDA OPE3 web site at http://www.ars.usda.gov/Research/.
Continuous data assimilation for downscaling large-footprint soil moisture retrievals
NASA Astrophysics Data System (ADS)
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.
A simple nudging scheme to assimilate ASCAT soil moisture data in the WRF model
NASA Astrophysics Data System (ADS)
Capecchi, V.; Gozzini, B.
2012-04-01
The present work shows results obtained in a numerical experiment using the WRF (Weather and Research Forecasting, www.wrf-model.org) model. A control run where soil moisture is constrained by GFS global analysis is compared with a test run where soil moisture analysis is obtained via a simple nudging scheme using ASCAT data. The basic idea of the assimilation scheme is to "nudge" the first level (0-10 cm below ground in NOAH model) of volumetric soil moisture of the first-guess (say θ(b,1) derived from global model) towards the ASCAT derived value (say ^θ A). The soil moisture analysis θ(a,1) is given by: { θ + K (^θA - θ ) l = 1 θ(a,1) = θ(b,l) (b,l) l > 1 (b,l) (1) where l is the model soil level. K is a constant scalar value that is user specified and in this study it is equal to 0.2 (same value as in similar studies). Soil moisture is critical for estimating latent and sensible heat fluxes as well as boundary layer structure. This parameter is, however, poorly assimilated in current global and regional numerical models since no extensive soil moisture observation network exists. Remote sensing technologies offer a synoptic view of the dynamics and spatial distribution of soil moisture with a frequent temporal coverage and with a horizontal resolution similar to mesoscale NWP model. Several studies have shown that measurements of normalized backscatter (surface soil wetness) from the Advanced Scatterometer (ASCAT) operating at microwave frequencies and boarded on the meteorological operational (Metop) satellite, offer quality information about surface soil moisture. Recently several studies deal with the implementation of simple assimilation procedures (nudging, Extended Kalman Filter, etc...) to integrate ASCAT data in NWP models. They found improvements in screen temperature predictions, particularly in areas such as North-America and in the Tropics, where it is strong the land-atmosphere coupling. The ECMWF (Newsletter No. 127) is currently implementing and testing an EKF for combining conventional observations and remote sensed soil moisture data in order to produce a more accurate analysis. In the present work verification skills (RMSE, BIAS, correlation) of both control and test run are presented using observed data collected by International Soil Moisture Network. Moreover improvements in temperature predictions are evaluated.
NASA Astrophysics Data System (ADS)
Ajami, H.; Sharma, A.
2016-12-01
A computationally efficient, semi-distributed hydrologic modeling framework is developed to simulate water balance at a catchment scale. The Soil Moisture and Runoff simulation Toolkit (SMART) is based upon the delineation of contiguous and topologically connected Hydrologic Response Units (HRUs). In SMART, HRUs are delineated using thresholds obtained from topographic and geomorphic analysis of a catchment, and simulation elements are distributed cross sections or equivalent cross sections (ECS) delineated in first order sub-basins. ECSs are formulated by aggregating topographic and physiographic properties of the part or entire first order sub-basins to further reduce computational time in SMART. Previous investigations using SMART have shown that temporal dynamics of soil moisture are well captured at a HRU level using the ECS delineation approach. However, spatial variability of soil moisture within a given HRU is ignored. Here, we examined a number of disaggregation schemes for soil moisture distribution in each HRU. The disaggregation schemes are either based on topographic based indices or a covariance matrix obtained from distributed soil moisture simulations. To assess the performance of the disaggregation schemes, soil moisture simulations from an integrated land surface-groundwater model, ParFlow.CLM in Baldry sub-catchment, Australia are used. ParFlow is a variably saturated sub-surface flow model that is coupled to the Common Land Model (CLM). Our results illustrate that the statistical disaggregation scheme performs better than the methods based on topographic data in approximating soil moisture distribution at a 60m scale. Moreover, the statistical disaggregation scheme maintains temporal correlation of simulated daily soil moisture while preserves the mean sub-basin soil moisture. Future work is focused on assessing the performance of this scheme in catchments with various topographic and climate settings.
L-band HIgh Spatial Resolution Soil Moisture Mapping using SMALL UnManned Aerial Systems
NASA Astrophysics Data System (ADS)
Dai, E.; Venkitasubramony, A.; Gasiewski, A. J.; Stachura, M.; Elston, J. S.; Walter, B.; Lankford, D.; Corey, C.
2017-12-01
Soil moisture is of fundamental importance to many hydrological, biological and biogeochemical processes, plays an important role in the development and evolution of convective weather and precipitation, water resource management, agriculture, and flood runoff prediction. The launch of NASA's Soil Moisture Active/Passive (SMAP) mission in 2015 provided new passive global measurements of soil moisture and surface freeze/thaw state at fixed crossing times and spatial resolutions of 36 km. However, there exists a need for measurements of soil moisture on much smaller spatial scales and arbitrary diurnal times for SMAP validation, precision agriculture and evaporation and transpiration studies of boundary layer heat transport. The Lobe Differencing Correlation Radiometer (LDCR) provides a means of mapping soil moisture on spatial scales as small as several meters. Compared with other methods of validation based on either in-situ measurements [1,2] or existing airborne sensors suitable for manned aircraft deployment [3], the integrated design of the LDCR on a lightweight small UAS (sUAS) is capable of providing sub-watershed ( km scale) coverage at very high spatial resolution ( 15 m) suitable for scaling studies, and at comparatively low operator cost. To demonstrate the LDCR several flights had been performed during field experiments at the Canton Oklahoma Soilscape site and Yuma Colorado Irrigation Research Foundation (IRF) site in 2015 and 2016, respectively, using LDCR Revision A and Tempest sUAS. The scientific intercomparisons of LDCR retrieved soil moisture and in-situ measurements will be presented. LDCR Revision B has been built and integrated into SuperSwift sUAS and additional field experiments will be performed at IRF in 2017. In Revision B the IF signal is sampled at 80 MS/s to enable digital correlation and RFI mitigation capabilities, in addition to analog correlation. [1] McIntyre, E.M., A.J. Gasiewski, and D. Manda D, "Near Real-Time Passive C-Band Microwave Soil Moisture Retrieval During CLASIC 2007," Proc. IGARSS, 2008. [2] Robock, A., S. Steele-Dunne, J. Basara, W. Crow, and M. Moghaddam M, "In Situ Network and Scaling," SMAP Algorithm and Cal/Val Workshop, 2009. [3] Walker, A., "Airborne Microwave Radiometer Measurements During CanEx-SM10," Second SMAP Cal/Val Workshop, 2011.
Evaluation of a microwave resonator for predicting grain moisture independent of bulk density
USDA-ARS?s Scientific Manuscript database
This work evaluated the ability of a planar whispering mode resonator to predict moisture considering moisture and densities expected in an on-harvester application. A calibration model was developed to accurately predict moisture over the moisture, density and temperature ranges evaluated. This mod...
Calculating moisture content for 1000-hour timelag fuels in western Washington and western Oregon.
Roger D. Ottmar; David V. Sandberg
1985-01-01
A predictive model is presented to calculate moisture content of 1000-hour timelag fuels in Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) and western hemlock (Tsuga heterophylla (Raf.) Sarg.) logging slash in western Washington and western Oregon. The model is a modification of the 1000-hour fuel moisture model of the...
NASA Technical Reports Server (NTRS)
Blankenship, Clay B.; Crosson, William L.; Case, Jonathan L.; Hale, Robert
2010-01-01
Improve simulations of soil moisture/temperature, and consequently boundary layer states and processes, by assimilating AMSR-E soil moisture estimates into a coupled land surface-mesoscale model Provide a new land surface model as an option in the Land Information System (LIS)
NASA Technical Reports Server (NTRS)
Blankenship, Clay; Case, Jonathan L.; Zavodsky, Bradley
2015-01-01
Land surface models are important components of numerical weather prediction (NWP) models, partitioning incoming energy into latent and sensitive heat fluxes that affect boundary layer growth and destabilization. During warm-season months, diurnal heating and convective initiation depend strongly on evapotranspiration and available boundary layer moisture, which are substantially affected by soil moisture content. Therefore, to properly simulate warm-season processes in NWP models, an accurate initialization of the land surface state is important for accurately depicting the exchange of heat and moisture between the surface and boundary layer. In this study, soil moisture retrievals from the Soil Moisture and Ocean Salinity (SMOS) satellite radiometer are assimilated into the Noah Land Surface Model via an Ensemble Kalman Filter embedded within the NASA Land Information System (LIS) software framework. The output from LIS-Noah is subsequently used to initialize runs of the Weather Research and Forecasting (WRF) NWP model. The impact of assimilating SMOS retrievals is assessed by initializing the WRF model with LIS-Noah output obtained with and without SMOS data assimilation. The southeastern United States is used as the domain for a preliminary case study. During the summer months, there is extensive irrigation in the lower Mississippi Valley for rice and other crops. The irrigation is not represented in the meteorological forcing used to drive the LIS-Noah integration, but the irrigated areas show up clearly in the SMOS soil moisture retrievals, resulting in a case with a large difference in initial soil moisture conditions. The impact of SMOS data assimilation on both Noah soil moisture fields and on short-term (0-48 hour) WRF weather forecasts will be presented.
A model of the CO2 exchanges between biosphere and atmosphere in the tundra
NASA Technical Reports Server (NTRS)
Labgaa, Rachid R.; Gautier, Catherine
1992-01-01
A physical model of the soil thermal regime in a permafrost terrain has been developed and validated with soil temperature measurements at Barrow, Alaska. The model calculates daily soil temperatures as a function of depth and average moisture contents of the organic and mineral layers using a set of five climatic variables, i.e., air temperature, precipitation, cloudiness, wind speed, and relative humidity. The model is not only designed to study the impact of climate change on the soil temperature and moisture regime, but also to provide the input to a decomposition and net primary production model. In this context, it is well known that CO2 exchanges between the terrestrial biosphere and the atmosphere are driven by soil temperature through decomposition of soil organic matter and root respiration. However, in tundra ecosystems, net CO2 exchange is extremely sensitive to soil moisture content; therefore it is necessary to predict variations in soil moisture in order to assess the impact of climate change on carbon fluxes. To this end, the present model includes the representation of the soil moisture response to changes in climatic conditions. The results presented in the foregoing demonstrate that large errors in soil temperature and permafrost depth estimates arise from neglecting the dependence of the soil thermal regime on soil moisture contents. Permafrost terrain is an example of a situation where soil moisture and temperature are particularly interrelated: drainage conditions improve when the depth of the permafrost increases; a decrease in soil moisture content leads to a decrease in the latent heat required for the phase transition so that the heat penetrates faster and deeper, and the maximum depth of thaw increases; and as excepted, soil thermal coefficients increase with moisture.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Woods, Jason; Winkler, Jon
Moisture buffering of building materials has a significant impact on the building's indoor humidity, and building energy simulations need to model this buffering to accurately predict the humidity. Researchers requiring a simple moisture-buffering approach typically rely on the effective-capacitance model, which has been shown to be a poor predictor of actual indoor humidity. This paper describes an alternative two-layer effective moisture penetration depth (EMPD) model and its inputs. While this model has been used previously, there is a need to understand the sensitivity of this model to uncertain inputs. In this paper, we use the moisture-adsorbent materials exposed to themore » interior air: drywall, wood, and carpet. We use a global sensitivity analysis to determine which inputs are most influential and how the model's prediction capability degrades due to uncertainty in these inputs. We then compare the model's humidity prediction with measured data from five houses, which shows that this model, and a set of simple inputs, can give reasonable prediction of the indoor humidity.« less
Woods, Jason; Winkler, Jon
2018-01-31
Moisture buffering of building materials has a significant impact on the building's indoor humidity, and building energy simulations need to model this buffering to accurately predict the humidity. Researchers requiring a simple moisture-buffering approach typically rely on the effective-capacitance model, which has been shown to be a poor predictor of actual indoor humidity. This paper describes an alternative two-layer effective moisture penetration depth (EMPD) model and its inputs. While this model has been used previously, there is a need to understand the sensitivity of this model to uncertain inputs. In this paper, we use the moisture-adsorbent materials exposed to themore » interior air: drywall, wood, and carpet. We use a global sensitivity analysis to determine which inputs are most influential and how the model's prediction capability degrades due to uncertainty in these inputs. We then compare the model's humidity prediction with measured data from five houses, which shows that this model, and a set of simple inputs, can give reasonable prediction of the indoor humidity.« less
Adeeb A. Rahman; Thomas J. Urbanik; Mustafa Mahamid
2006-01-01
This paper presents a model using finite element method to study the response of a typical commercial corrugated fiberboard due to an induced moisture function at one side of the fiberboard. The model predicts how the moisture diffusion will permeate through the fiberboardâs layers(medium and liners) providing information on moisture content at any given point...
NASA Astrophysics Data System (ADS)
Hu, Z.; Xu, L.; Yu, B.
2018-04-01
A empirical model is established to analyse the daily retrieval of soil moisture from passive microwave remote sensing using convolutional neural networks (CNN). Soil moisture plays an important role in the water cycle. However, with the rapidly increasing of the acquiring technology for remotely sensed data, it's a hard task for remote sensing practitioners to find a fast and convenient model to deal with the massive data. In this paper, the AMSR-E brightness temperatures are used to train CNN for the prediction of the European centre for medium-range weather forecasts (ECMWF) model. Compared with the classical inversion methods, the deep learning-based method is more suitable for global soil moisture retrieval. It is very well supported by graphics processing unit (GPU) acceleration, which can meet the demand of massive data inversion. Once the model trained, a global soil moisture map can be predicted in less than 10 seconds. What's more, the method of soil moisture retrieval based on deep learning can learn the complex texture features from the big remote sensing data. In this experiment, the results demonstrates that the CNN deployed to retrieve global soil moisture can achieve a better performance than the support vector regression (SVR) for soil moisture retrieval.
Assimilation of ASCAT near-surface soil moisture into the SIM hydrological model over France
NASA Astrophysics Data System (ADS)
Draper, C.; Mahfouf, J.-F.; Calvet, J.-C.; Martin, E.; Wagner, W.
2011-12-01
This study examines whether the assimilation of remotely sensed near-surface soil moisture observations might benefit an operational hydrological model, specifically Météo-France's SAFRAN-ISBA-MODCOU (SIM) model. Soil moisture data derived from ASCAT backscatter observations are assimilated into SIM using a Simplified Extended Kalman Filter (SEKF) over 3.5 years. The benefit of the assimilation is tested by comparison to a delayed cut-off version of SIM, in which the land surface is forced with more accurate atmospheric analyses, due to the availability of additional atmospheric observations after the near-real time data cut-off. However, comparing the near-real time and delayed cut-off SIM models revealed that the main difference between them is a dry bias in the near-real time precipitation forcing, which resulted in a dry bias in the root-zone soil moisture and associated surface moisture flux forecasts. While assimilating the ASCAT data did reduce the root-zone soil moisture dry bias (by nearly 50%), this was more likely due to a bias within the SEKF, than due to the assimilation having accurately responded to the precipitation errors. Several improvements to the assimilation are identified to address this, and a bias-aware strategy is suggested for explicitly correcting the model bias. However, in this experiment the moisture added by the SEKF was quickly lost from the model surface due to the enhanced surface fluxes (particularly drainage) induced by the wetter soil moisture states. Consequently, by the end of each winter, during which frozen conditions prevent the ASCAT data from being assimilated, the model land surface had returned to its original (dry-biased) climate. This highlights that it would be more effective to address the precipitation bias directly, than to correct it by constraining the model soil moisture through data assimilation.
NASA Astrophysics Data System (ADS)
Nasta, Paolo; Penna, Daniele; Brocca, Luca; Zuecco, Giulia; Romano, Nunzio
2018-02-01
Indirect measurements of field-scale (hectometer grid-size) spatial-average near-surface soil moisture are becoming increasingly available by exploiting new-generation ground-based and satellite sensors. Nonetheless, modeling applications for water resources management require knowledge of plot-scale (1-5 m grid-size) soil moisture by using measurements through spatially-distributed sensor network systems. Since efforts to fulfill such requirements are not always possible due to time and budget constraints, alternative approaches are desirable. In this study, we explore the feasibility of determining spatial-average soil moisture and soil moisture patterns given the knowledge of long-term records of climate forcing data and topographic attributes. A downscaling approach is proposed that couples two different models: the Eco-Hydrological Bucket and Equilibrium Moisture from Topography. This approach helps identify the relative importance of two compound topographic indexes in explaining the spatial variation of soil moisture patterns, indicating valley- and hillslope-dependence controlled by lateral flow and radiative processes, respectively. The integrated model also detects temporal instability if the dominant type of topographic dependence changes with spatial-average soil moisture. Model application was carried out at three sites in different parts of Italy, each characterized by different environmental conditions. Prior calibration was performed by using sparse and sporadic soil moisture values measured by portable time domain reflectometry devices. Cross-site comparisons offer different interpretations in the explained spatial variation of soil moisture patterns, with time-invariant valley-dependence (site in northern Italy) and hillslope-dependence (site in southern Italy). The sources of soil moisture spatial variation at the site in central Italy are time-variant within the year and the seasonal change of topographic dependence can be conveniently correlated to a climate indicator such as the aridity index.
Large-area Soil Moisture Surveys Using a Cosmic-ray Rover: Approaches and Results from Australia
NASA Astrophysics Data System (ADS)
Hawdon, A. A.; McJannet, D. L.; Renzullo, L. J.; Baker, B.; Searle, R.
2017-12-01
Recent improvements in satellite instrumentation has increased the resolution and frequency of soil moisture observations, and this in turn has supported the development of higher resolution land surface process models. Calibration and validation of these products is restricted by the mismatch of scales between remotely sensed and contemporary ground based observations. Although the cosmic ray neutron soil moisture probe can provide estimates soil moisture at a scale useful for the calibration and validation purposes, it is spatially limited to a single, fixed location. This scaling issue has been addressed with the development of mobile soil moisture monitoring systems that utilizes the cosmic ray neutron method, typically referred to as a `rover'. This manuscript describes a project designed to develop approaches for undertaking rover surveys to produce soil moisture estimates at scales comparable to satellite observations and land surface process models. A custom designed, trailer-mounted rover was used to conduct repeat surveys at two scales in the Mallee region of Victoria, Australia. A broad scale survey was conducted at 36 x 36 km covering an area of a standard SMAP pixel and an intensive scale survey was conducted over a 10 x 10 km portion of the broad scale survey, which is at a scale equivalent to that used for national water balance modelling. We will describe the design of the rover, the methods used for converting neutron counts into soil moisture and discuss factors controlling soil moisture variability. We found that the intensive scale rover surveys produced reliable soil moisture estimates at 1 km resolution and the broad scale at 9 km resolution. We conclude that these products are well suited for future analysis of satellite soil moisture retrievals and finer scale soil moisture models.
NASA Astrophysics Data System (ADS)
Huang, Chunlin; Chen, Weijin; Wang, Weizhen; Gu, Juan
2017-04-01
Uncertainties in model parameters can easily cause systematic differences between model states and observations from ground or satellites, which significantly affect the accuracy of soil moisture estimation in data assimilation systems. In this paper, a novel soil moisture assimilation scheme is developed to simultaneously assimilate AMSR-E brightness temperature (TB) and MODIS Land Surface Temperature (LST), which can correct model bias by simultaneously updating model states and parameters with dual ensemble Kalman filter (DEnKS). The Common Land Model (CoLM) and a Q-h Radiative Transfer Model (RTM) are adopted as model operator and observation operator, respectively. The assimilation experiment is conducted in Naqu, Tibet Plateau, from May 31 to September 27, 2011. Compared with in-situ measurements, the accuracy of soil moisture estimation is tremendously improved in terms of a variety of scales. The updated soil temperature by assimilating MODIS LST as input of RTM can reduce the differences between the simulated and observed brightness temperatures to a certain degree, which helps to improve the estimation of soil moisture and model parameters. The updated parameters show large discrepancy with the default ones and the former effectively reduces the states bias of CoLM. Results demonstrate the potential of assimilating both microwave TB and MODIS LST to improve the estimation of soil moisture and related parameters. Furthermore, this study also indicates that the developed scheme is an effective soil moisture downscaling approach for coarse-scale microwave TB.
[Bare Soil Moisture Inversion Model Based on Visible-Shortwave Infrared Reflectance].
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.
Mass Conservation in Modeling Moisture Diffusion in Multi-Layer Carbon Composite Structures
NASA Technical Reports Server (NTRS)
Nurge, Mark A.; Youngquist, Robert C.; Starr, Stanley O.
2009-01-01
Moisture diffusion in multi-layer carbon composite structures is difficult to model using finite difference methods due to the discontinuity in concentrations between adjacent layers of differing materials. Applying a mass conserving approach at these boundaries proved to be effective at accurately predicting moisture uptake for a sample exposed to a fixed temperature and relative humidity. Details of the model developed are presented and compared with actual moisture uptake data gathered over 130 days from a graphite epoxy composite sandwich coupon with a Rohacell foam core.
New Physical Algorithms for Downscaling SMAP Soil Moisture
NASA Astrophysics Data System (ADS)
Sadeghi, M.; Ghafari, E.; Babaeian, E.; Davary, K.; Farid, A.; Jones, S. B.; Tuller, M.
2017-12-01
The NASA Soil Moisture Active Passive (SMAP) mission provides new means for estimation of surface soil moisture at the global scale. However, for many hydrological and agricultural applications the spatial SMAP resolution is too low. To address this scale issue we fused SMAP data with MODIS observations to generate soil moisture maps at 1-km spatial resolution. In course of this study we have improved several existing empirical algorithms and introduced a new physical approach for downscaling SMAP data. The universal triangle/trapezoid model was applied to relate soil moisture to optical/thermal observations such as NDVI, land surface temperature and surface reflectance. These algorithms were evaluated with in situ data measured at 5-cm depth. Our results demonstrate that downscaling SMAP soil moisture data based on physical indicators of soil moisture derived from the MODIS satellite leads to higher accuracy than that achievable with empirical downscaling algorithms. Keywords: Soil moisture, microwave data, downscaling, MODIS, triangle/trapezoid model.
NASA Astrophysics Data System (ADS)
Wrona, Elizabeth; Rowlandson, Tracy L.; Nambiar, Manoj; Berg, Aaron A.; Colliander, Andreas; Marsh, Philip
2017-05-01
This study examines the Soil Moisture Active Passive soil moisture product on the Equal Area Scalable Earth-2 (EASE-2) 36 km Global cylindrical and North Polar azimuthal grids relative to two in situ soil moisture monitoring networks that were installed in 2015 and 2016. Results indicate that there is no relationship between the Soil Moisture Active Passive (SMAP) Level-2 passive soil moisture product and the upscaled in situ measurements. Additionally, there is very low correlation between modeled brightness temperature using the Community Microwave Emission Model and the Level-1 C SMAP brightness temperature interpolated to the EASE-2 Global grid; however, there is a much stronger relationship to the brightness temperature measurements interpolated to the North Polar grid, suggesting that the soil moisture product could be improved with interpolation on the North Polar grid.
NASA Astrophysics Data System (ADS)
Barron-Gafford, G. A.; Minor, R. L.; Braun, Z.; Potts, D. L.
2012-12-01
Woody encroachment into grasslands alters ecosystem structure and function both above- and belowground. Aboveground, woody plant canopies increase leaf area index and alter patterns of interception, infiltration and runoff. Belowground, woody plants alter root distribution and increase maximum rooting depth with the effect of accessing deeper pools of soil moisture and shifting the timing and duration of evapotranspiration. In turn, these woody plants mediate hydrological changes that influence patterns of ecosystem CO2 exchange and productivity. Given projections of more variable precipitation and increased temperatures for many semiarid regions, differences in physiological performance are likely to drive changes in ecosystem-scale carbon and water flux depending on the degree of woody cover. Ultimately, as soil moisture declines with decreased precipitation, differential patterns of environmental sensitivity among growth-forms and their dependence on groundwater will only become more important in determining ecosystem resilience to future change. Here, we created a series of 1-meter deep mesocosms that housed either a woody mesquite shrub, a bunchgrass, or was left as bare soil. Five replicates of each were maintained under current ambient air temperatures, and five replicates were maintained under projected (+4oC) air temperatures. Each mesocosm was outfitted with an array of soil moisture, temperature, water potential, and CO2 exchange concentration sensors at the near-surface, 30, 55, and 80cm depths to quantify patterns of soil moisture and respiratory CO2 exchange efflux in response to rainfall events of varying magnitude and intervening dry periods of varying duration. In addition, we used minirhizotrons to quantify the response of roots to episodic rainfall. During the first year, bunchgrasses photosynthetically outperformed mesquite saplings across a wider range of temperatures under dry conditions, regardless of growth temperature (ambient or +4oC). Both growth forms were similarly responsive to episodic rainfall, regardless of event magnitude, though mesquite were able to maintain photosynthetic function for a longer period in response to each rain. However, in the second year of the experiment a new pattern of response to moisture and high temperature stress emerged. Under dry conditions, mesquite sustained high photosynthetic rates across a wider range of atmospheric temperatures and were less responsive to rainfall, regardless of event magnitude. In contrast, the limiting effect of high temperatures on bunchgrass photosynthesis was soil moisture dependent. In this case, the effects of high temperature limitation were exaggerated under dry conditions and relaxed when soil moisture was more abundant. Together, these trends yielded a significantly greater photosynthetic assimilation by deeper-rooted mesquite shrubs than shallow-rooted bunchgrasses under both temperature regimes. Combining these aboveground measurements of carbon uptake with belowground estimates of carbon efflux will allow us to make much more informed projections of net carbon balance within mixed vegetation shrublands across a range of global climate change projections.
NASA Technical Reports Server (NTRS)
Lapenta, William M.; Crosson, William; Dembek, Scott; Lakhtakia, Mercedes
1998-01-01
It is well known that soil moisture is a characteristic of the land surface that strongly affects the partitioning of outgoing radiation into sensible and latent heat which significantly impacts both weather and climate. Detailed land surface schemes are now being coupled to mesoscale atmospheric models in order to represent the effect of soil moisture upon atmospheric simulations. However, there is little direct soil moisture data available to initialize these models on regional to continental scales. As a result, a Soil Hydrology Model (SHM) is currently being used to generate an indirect estimate of the soil moisture conditions over the continental United States at a grid resolution of 36 Km on a daily basis since 8 May 1995. The SHM is forced by analyses of atmospheric observations including precipitation and contains detailed information on slope soil and landcover characteristics.The purpose of this paper is to evaluate the utility of initializing a detailed coupled model with the soil moisture data produced by SHM.
Uncertainty in Ecohydrological Modeling in an Arid Region Determined with Bayesian Methods
Yang, Junjun; He, Zhibin; Du, Jun; Chen, Longfei; Zhu, Xi
2016-01-01
In arid regions, water resources are a key forcing factor in ecosystem circulation, and soil moisture is the critical link that constrains plant and animal life on the soil surface and underground. Simulation of soil moisture in arid ecosystems is inherently difficult due to high variability. We assessed the applicability of the process-oriented CoupModel for forecasting of soil water relations in arid regions. We used vertical soil moisture profiling for model calibration. We determined that model-structural uncertainty constituted the largest error; the model did not capture the extremes of low soil moisture in the desert-oasis ecotone (DOE), particularly below 40 cm soil depth. Our results showed that total uncertainty in soil moisture prediction was improved when input and output data, parameter value array, and structure errors were characterized explicitly. Bayesian analysis was applied with prior information to reduce uncertainty. The need to provide independent descriptions of uncertainty analysis (UA) in the input and output data was demonstrated. Application of soil moisture simulation in arid regions will be useful for dune-stabilization and revegetation efforts in the DOE. PMID:26963523
Impact of moisture variations on the circulation of the south-west monsoon
NASA Astrophysics Data System (ADS)
Kishtawal, C. M.; Pal, P. K.; Narayanan, M. S.; Manna, S. K.; Sharma, O. P.; Agarwal, Sangeeta; Upadhyaya, H. C.
1993-12-01
The impact of moisture anomalies on the circulation of the south-west Indian monsoon has been studied with a general circulation model. Newtonian relaxation is adopted to subject the model atmosphere under sustained moisture anomalies. The impact of negative anomalies of moisture was seen as a divergent circulation anomaly, while the positive anomaly was a stronger convergent anomaly. Although the humidity fields display a resilient behaviour, and relax back to normal patterns 1-2 days after the forcing terms in humidity are withdrawn, the circulation anomalies created by the moisture variation keeps growing. A feedback between positive moisture anomalies and low level convergence exists, which is terminated in the absence of external forcings.
NASA Astrophysics Data System (ADS)
Singh, G.; Panda, R. K.; Mohanty, B.
2015-12-01
Prediction of root zone soil moisture status at field level is vital for developing efficient agricultural water management schemes. In this study, root zone soil moisture was estimated across the Rana watershed in Eastern India, by assimilation of near-surface soil moisture estimate from SMOS satellite into a physically-based Soil-Water-Atmosphere-Plant (SWAP) model. An ensemble Kalman filter (EnKF) technique coupled with SWAP model was used for assimilating the satellite soil moisture observation at different spatial scales. The universal triangle concept and artificial intelligence techniques were applied to disaggregate the SMOS satellite monitored near-surface soil moisture at a 40 km resolution to finer scale (1 km resolution), using higher spatial resolution of MODIS derived vegetation indices (NDVI) and land surface temperature (Ts). The disaggregated surface soil moisture were compared to ground-based measurements in diverse landscape using portable impedance probe and gravimetric samples. Simulated root zone soil moisture were compared with continuous soil moisture profile measurements at three monitoring stations. In addition, the impact of projected climate change on root zone soil moisture were also evaluated. The climate change projections of rainfall were analyzed for the Rana watershed from statistically downscaled Global Circulation Models (GCMs). The long-term root zone soil moisture dynamics were estimated by including a rainfall generator of likely scenarios. The predicted long term root zone soil moisture status at finer scale can help in developing efficient agricultural water management schemes to increase crop production, which lead to enhance the water use efficiency.
USDA-ARS?s Scientific Manuscript database
In situ measurements of soil moisture are invaluable for calibrating and validating land surface models and satellite-based soil moisture retrievals. In addition, long-term time series of in situ soil moisture measurements themselves can reveal trends in the water cycle related to climate or land co...
The Effects of Alkali and Temperature on the Hydrolysis Rate of N-methylpyrrolidone
NASA Astrophysics Data System (ADS)
Ou, Yu Jing; Wang, Xiao Mei; Lei Li, Chun; Zhu, Ya Long; Li, Xiao Long
2017-12-01
By studying the hydrolysis of N-methylpyrrolidone, it was found that the effects of NaOH concentration and temperature on N-methylpyrrolidone's hydrolysis were remarkable. Fourier transform infrared (FTIR) and Gel Permeation Chromatography (GPC) detected that the mainly hydrolyzate was 4-(methylamino)butyric acid, and the hydrolyzate can generate polymers, which of molecular weight increases with temperature rising. The results of Gas Chromatography (GC) and moisture meter test showed that adding alkaline and raising temperature can aggravate hydrolysis of NMP. This study provide theoretical basis for recycling solvent (NMP) in the production of polyphenylene sulfide (PPS).
Hurricane Maria's Strengthening Winds Seen in NASA SMAP Image
2017-09-19
The radiometer instrument on NASA's Soil Moisture Active Passive (SMAP) spacecraft captured this image of Hurricane Maria at 6:27 a.m. EDT on Sept. 19, 2017 (10:27 UTC), showing an estimated maximum surface wind speed of 126.6 miles per hour (56.6 meters per second). While Maria was already a Category 5 hurricane at the time of this observation, it is an extremely tightly organized hurricane and SMAP cannot fully resolve its highest winds due to the 25-mile (40-kilometer) resolution of SMAP. https://photojournal.jpl.nasa.gov/catalog/PIA21960
NASA Astrophysics Data System (ADS)
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.
USDA-ARS?s Scientific Manuscript database
The FASST (Fast All Season Strength model, US Army Corps of Engineers), one-dimensional hydrologic model was used to evaluate soil moisture across the USDA-ARS-SEWRL Little River Watershed in south Georgia US. The ultimate goal of this research is to assess the spatial variation of soil moisture acr...
NASA Technical Reports Server (NTRS)
Reichle, Rolf H.; De Lannoy, Gabrielle J. M.
2012-01-01
The Soil Moisture and Ocean Salinity (SMOS) satellite mission provides global measurements of L-band brightness temperatures at horizontal and vertical polarization and a variety of incidence angles that are sensitive to moisture and temperature conditions in the top few centimeters of the soil. These L-band observations can therefore be assimilated into a land surface model to obtain surface and root zone soil moisture estimates. As part of the observation operator, such an assimilation system requires a radiative transfer model (RTM) that converts geophysical fields (including soil moisture and soil temperature) into modeled L-band brightness temperatures. At the global scale, the RTM parameters and the climatological soil moisture conditions are still poorly known. Using look-up tables from the literature to estimate the RTM parameters usually results in modeled L-band brightness temperatures that are strongly biased against the SMOS observations, with biases varying regionally and seasonally. Such biases must be addressed within the land data assimilation system. In this presentation, the estimation of the RTM parameters is discussed for the NASA GEOS-5 land data assimilation system, which is based on the ensemble Kalman filter (EnKF) and the Catchment land surface model. In the GEOS-5 land data assimilation system, soil moisture and brightness temperature biases are addressed in three stages. First, the global soil properties and soil hydraulic parameters that are used in the Catchment model were revised to minimize the bias in the modeled soil moisture, as verified against available in situ soil moisture measurements. Second, key parameters of the "tau-omega" RTM were calibrated prior to data assimilation using an objective function that minimizes the climatological differences between the modeled L-band brightness temperatures and the corresponding SMOS observations. Calibrated parameters include soil roughness parameters, vegetation structure parameters, and the single scattering albedo. After this climatological calibration, the modeling system can provide L-band brightness temperatures with a global mean absolute bias of less than 10K against SMOS observations, across multiple incidence angles and for horizontal and vertical polarization. Third, seasonal and regional variations in the residual biases are addressed by estimating the vegetation optical depth through state augmentation during the assimilation of the L-band brightness temperatures. This strategy, tested here with SMOS data, is part of the baseline approach for the Level 4 Surface and Root Zone Soil Moisture data product from the planned Soil Moisture Active Passive (SMAP) satellite mission.
Comparing soil moisture memory in satellite observations and models
NASA Astrophysics Data System (ADS)
Stacke, Tobias; Hagemann, Stefan; Loew, Alexander
2013-04-01
A major obstacle to a correct parametrization of soil processes in large scale global land surface models is the lack of long term soil moisture observations for large parts of the globe. Currently, a compilation of soil moisture data derived from a range of satellites is released by the ESA Climate Change Initiative (ECV_SM). Comprising the period from 1978 until 2010, it provides the opportunity to compute climatological relevant statistics on a quasi-global scale and to compare these to the output of climate models. Our study is focused on the investigation of soil moisture memory in satellite observations and models. As a proxy for memory we compute the autocorrelation length (ACL) of the available satellite data and the uppermost soil layer of the models. Additional to the ECV_SM data, AMSR-E soil moisture is used as observational estimate. Simulated soil moisture fields are taken from ERA-Interim reanalysis and generated with the land surface model JSBACH, which was driven with quasi-observational meteorological forcing data. The satellite data show ACLs between one week and one month for the greater part of the land surface while the models simulate a longer memory of up to two months. Some pattern are similar in models and observations, e.g. a longer memory in the Sahel Zone and the Arabian Peninsula, but the models are not able to reproduce regions with a very short ACL of just a few days. If the long term seasonality is subtracted from the data the memory is strongly shortened, indicating the importance of seasonal variations for the memory in most regions. Furthermore, we analyze the change of soil moisture memory in the different soil layers of the models to investigate to which extent the surface soil moisture includes information about the whole soil column. A first analysis reveals that the ACL is increasing for deeper layers. However, its increase is stronger in the soil moisture anomaly than in its absolute values and the first even exceeds the latter in the deepest layer. From this we conclude that the seasonal soil moisture variations dominate the memory close to the surface but these are dampened in lower layers where the memory is mainly affected by longer term variations.
NASA Astrophysics Data System (ADS)
Crow, W. T.; Chen, F.; Reichle, R. H.; Xia, Y.; Liu, Q.
2018-05-01
Accurate partitioning of precipitation into infiltration and runoff is a fundamental objective of land surface models tasked with characterizing the surface water and energy balance. Temporal variability in this partitioning is due, in part, to changes in prestorm soil moisture, which determine soil infiltration capacity and unsaturated storage. Utilizing the National Aeronautics and Space Administration Soil Moisture Active Passive Level-4 soil moisture product in combination with streamflow and precipitation observations, we demonstrate that land surface models (LSMs) generally underestimate the strength of the positive rank correlation between prestorm soil moisture and event runoff coefficients (i.e., the fraction of rainfall accumulation volume converted into stormflow runoff during a storm event). Underestimation is largest for LSMs employing an infiltration-excess approach for stormflow runoff generation. More accurate coupling strength is found in LSMs that explicitly represent subsurface stormflow or saturation-excess runoff generation processes.
Divergent surface and total soil moisture projections under global warming
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.
NASA Astrophysics Data System (ADS)
Massman, W. J.
2012-10-01
Heating any soil during a sufficiently intense wildfire or prescribed burn can alter it irreversibly, causing many significant, long-term biological, chemical, and hydrological effects. Given the climate-change-driven increasing probability of wildfires and the increasing use of prescribed burns by land managers, it is important to better understand the dynamics of the coupled heat and moisture transport in soil during these extreme heating events. Furthermore, improved understanding and modeling of heat and mass transport during extreme conditions should provide insights into the associated transport mechanisms under more normal conditions. The present study describes a numerical model developed to simulate soil heat and moisture transport during fires where the surface heating often ranges between 10,000 and 100,000 W m-2 for several minutes to several hours. Basically, the model extends methods commonly used to model coupled heat flow and moisture evaporation at ambient conditions into regions of extreme dryness and heat. But it also incorporates some infrequently used formulations for temperature dependencies of the soil specific heat, thermal conductivity, and the water retention curve, as well as advective effects due to the large changes in volume that occur when liquid water is rapidly volatilized. Model performance is tested against laboratory measurements of soil temperature and moisture changes at several depths during controlled heating events. Qualitatively, the model agrees with the laboratory observations, namely, it simulates an increase in soil moisture ahead of the drying front (due to the condensation of evaporated soil water at the front) and a hiatus in the soil temperature rise during the strongly evaporative stage of the soil drying. Nevertheless, it is shown that the model is incapable of producing a physically realistic solution because it does not (and, in fact, cannot) represent the relationship between soil water potential and soil moisture at extremely low soil moisture contents (i.e., residual or bound water: θ < 0.01 m3 m-3, for example). Diagnosing the model's performance yields important insights into how to make progress on modeling soil evaporation and heating under conditions of high temperatures and very low soil moisture content.
Rasmussen, A; Frimodt-Møller, N; Espersen, F; Roed, M; Frimodt-Møller, C
1996-08-01
To compare three different urine metering systems for their ability to prevent retrograde contamination in an in vitro model of a closed urinary drainage system and for qualities important to their practical handling in a clinical setting. Using three urine-meters (the Braun Ureofix 511, the Kendall Curity 4000 and the Unoplast Unometer 500) the in vitro model was constantly flushed with a solution of Mueller-Hinton broth diluted with saline. On the first day, the urine collecting bag was inoculated with 10(8) cells of Pseudomonas aeruginosa. The system was operated for 12 days with daily sampling of the model bladder to detect any contamination. After 12 days the experiment was stopped and sampling performed at various locations, including the urine-meter and the tubing. Nine of each type of urine-meter were tested, i.e. three in three different experiments. In the clinical study, 45 patients were randomized to each of the three urine-meters and the nurses attending them were asked to complete a questionnaire on the practical handling of the urine-meters. When the urine-meters was omitted from the model system, the 'bladder' became contaminated with the test bacteria within 3 days. None of the nine Unometer 500 systems became contaminated, compared with four of each of the other two systems (P < 0.05). In clinical use, the Unometer 500 and Ureofix 511 were easier to suspend and empty than was the Curity 4000. The Unometer 500 was significantly easier to handle when the collecting bag was emptied. Urine-meters can prevent retrograde contamination in a closed bladder-drainage model, but the degree of prevention depends upon the type of urine-meter. In daily practice, there were differences in the ease of suspension of the systems and in the emptying of the urine-meter and collecting bag.
Application of Terrestrial Microwave Remote Sensing to Agricultural Drought Monitoring
NASA Astrophysics Data System (ADS)
Crow, W. T.; Bolten, J. D.
2014-12-01
Root-zone soil moisture information is a valuable diagnostic for detecting the onset and severity of agricultural drought. Current attempts to globally monitor root-zone soil moisture are generally based on the application of soil water balance models driven by observed meteorological variables. Such systems, however, are prone to random error associated with: incorrect process model physics, poor parameter choices and noisy meteorological inputs. The presentation will describe attempts to remediate these sources of error via the assimilation of remotely-sensed surface soil moisture retrievals from satellite-based passive microwave sensors into a global soil water balance model. Results demonstrate the ability of satellite-based soil moisture retrieval products to significantly improve the global characterization of root-zone soil moisture - particularly in data-poor regions lacking adequate ground-based rain gage instrumentation. This success has lead to an on-going effort to implement an operational land data assimilation system at the United States Department of Agriculture's Foreign Agricultural Service (USDA FAS) to globally monitor variations in root-zone soil moisture availability via the integration of satellite-based precipitation and soil moisture information. Prospects for improving the performance of the USDA FAS system via the simultaneous assimilation of both passive and active-based soil moisture retrievals derived from the upcoming NASA Soil Moisture Active/Passive mission will also be discussed.
Assimilation of Spatially Sparse In Situ Soil Moisture Networks into a Continuous Model Domain
NASA Astrophysics Data System (ADS)
Gruber, A.; Crow, W. T.; Dorigo, W. A.
2018-02-01
Growth in the availability of near-real-time soil moisture observations from ground-based networks has spurred interest in the assimilation of these observations into land surface models via a two-dimensional data assimilation system. However, the design of such systems is currently hampered by our ignorance concerning the spatial structure of error afflicting ground and model-based soil moisture estimates. Here we apply newly developed triple collocation techniques to provide the spatial error information required to fully parameterize a two-dimensional (2-D) data assimilation system designed to assimilate spatially sparse observations acquired from existing ground-based soil moisture networks into a spatially continuous Antecedent Precipitation Index (API) model for operational agricultural drought monitoring. Over the contiguous United States (CONUS), the posterior uncertainty of surface soil moisture estimates associated with this 2-D system is compared to that obtained from the 1-D assimilation of remote sensing retrievals to assess the value of ground-based observations to constrain a surface soil moisture analysis. Results demonstrate that a fourfold increase in existing CONUS ground station density is needed for ground network observations to provide a level of skill comparable to that provided by existing satellite-based surface soil moisture retrievals.
The effect of soil moisture anomalies on maize yield in Germany
NASA Astrophysics Data System (ADS)
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.
Vegetation function and non-uniqueness of the hydrological response
NASA Astrophysics Data System (ADS)
Ivanov, V. Y.; Fatichi, S.; Kampf, S. K.; Caporali, E.
2012-04-01
Through local moisture uptake vegetation exerts seasonal and longer-term impacts on the watershed hydrological response. However, the role of vegetation may go beyond the conventionally implied and well-understood "sink" function in the basin soil moisture storage equation. We argue that vegetation function imposes a "homogenizing" effect on pre-event soil moisture spatial storage, decreasing the likelihood that a rainfall event will result in a topographically-driven redistribution of soil water and the consequent formation of variable source areas. In combination with vegetation temporal dynamics, this may lead to the non-uniqueness of the hydrological response with respect to the mean basin wetness. This study designs a set of relevant numerical experiments carried out with two physically-based models; one of the models, HYDRUS, resolves variably saturated subsurface flow using a fully three-dimensional formulation, while the other model, tRIBS+VEGGIE, uses a one-dimensional formulation applied in a quasi-three-dimensional framework in combination with the model of vegetation dynamics. We demonstrate that (1) vegetation function modifies spatial heterogeneity in moisture spatial storage by imposing different degrees of subsurface flow connectivity; explore mechanistically (2) how and why a basin with the same mean soil moisture can have distinctly different spatial soil moisture distributions; and demonstrate (2) how these distinct moisture distributions result in a hysteretic runoff response to precipitation. Furthermore, the study argues that near-surface soil moisture is an insufficient indicator of the initial moisture state of a catchment with the implication of its limited effect on hydrological predictability.
Study of moisture absorption by an organoplastic
NASA Astrophysics Data System (ADS)
Aniskevich, A. N.; Yanson, Yu. O.
1991-07-01
A complex experimental study of the state of sorbed moisture in a unidirectionally reinforced organoplastic was conducted. The methods of TG, DSC, DTA, and NMR showed that moisture absorption in OP is reversible up to 8%, the sorbed moisture does not crystallize in the temperature range from -70 to 0 °C, it is finely dispersely distributed and is in the strongly and weakly bound state, and there is almost no free moisture. The results of the sorption experiments conducted on OP and its structural components: microplastic and EDT-10 binder, in a wide range of temperature-humidity conditions and the data from physical studies showed that moisture absorption in the materials basically takes place by diffusion and is satisfactorily described by a phenomenological model based on the Fick equation. A method of accelerated determination of the sorption characteristics of anisotropic composite materials was developed, using the introduced concept of the fictitious diffusion coefficient and the extrapolation method of determining the limiting moisture content. The features of migration of moisture on the interface in a multiphase system were investigated, and the possibility of successive calculation estimation of the sorption characteristics of an organoplastic at different structural levels was demonstrated: components—unidirectionally reinforced composite—model laminated article. The tested phenomenological model of the sorption process and the experimentally obtained values of the characteristics of the material were the basis for a method of calculation determination of the resource of moisture-proofing properties of a model multilayer article of CM in nonstationary external conditions.
Assessment of initial soil moisture conditions for event-based rainfall-runoff modelling
NASA Astrophysics Data System (ADS)
Tramblay, Yves; Bouvier, Christophe; Martin, Claude; Didon-Lescot, Jean-François; Todorovik, Dragana; Domergue, Jean-Marc
2010-06-01
Flash floods are the most destructive natural hazards that occur in the Mediterranean region. Rainfall-runoff models can be very useful for flash flood forecasting and prediction. Event-based models are very popular for operational purposes, but there is a need to reduce the uncertainties related to the initial moisture conditions estimation prior to a flood event. This paper aims to compare several soil moisture indicators: local Time Domain Reflectometry (TDR) measurements of soil moisture, modelled soil moisture through the Interaction-Sol-Biosphère-Atmosphère (ISBA) component of the SIM model (Météo-France), antecedent precipitation and base flow. A modelling approach based on the Soil Conservation Service-Curve Number method (SCS-CN) is used to simulate the flood events in a small headwater catchment in the Cevennes region (France). The model involves two parameters: one for the runoff production, S, and one for the routing component, K. The S parameter can be interpreted as the maximal water retention capacity, and acts as the initial condition of the model, depending on the antecedent moisture conditions. The model was calibrated from a 20-flood sample, and led to a median Nash value of 0.9. The local TDR measurements in the deepest layers of soil (80-140 cm) were found to be the best predictors for the S parameter. TDR measurements averaged over the whole soil profile, outputs of the SIM model, and the logarithm of base flow also proved to be good predictors, whereas antecedent precipitations were found to be less efficient. The good correlations observed between the TDR predictors and the S calibrated values indicate that monitoring soil moisture could help setting the initial conditions for simplified event-based models in small basins.
Spatial Estimation of Soil Moisture Using Synthetic Aperture Radar in Alaska
NASA Astrophysics Data System (ADS)
Meade, N. G.; Hinzman, L. D.; Kane, D. L.
1999-01-01
A spatially distributed Model of Arctic Thermal and Hydrologic processes (MATH) has been developed. One of the attributes of this model is the spatial and temporal prediction of soil moisture in the active layer. The spatially distributed output from this model required verification data obtained through remote sensing to assess performance at the watershed scale independently. Therefore, a neural network was trained to predict soil moisture contents near the ground surface. The input to train the neural network is synthetic aperture radar (SAR) pixel value, and field measurements of soil moisture, and vegetation, which were used as a surrogate for surface roughness. Once the network was trained, soil moisture predictions were made based on SAR pixel value and vegetation. These results were then used for comparison with results from the hydrologic model. The quality of neural network input was less than anticipated. Our digital elevation model (DEM) was not of high enough resolution to allow exact co-registration with soil moisture measurements; therefore, the statistical correlations were not as good as hoped. However, the spatial pattern of the SAR derived soil moisture contents compares favorably with the hydrologic MATH model results. Primary surface parameters that effect SAR include topography, surface roughness, vegetation cover and soil texture. Single parameters that are considered to influence SAR include incident angle of the radar, polarization of the radiation, signal strength and returning signal integration, to name a few. These factors influence the reflectance, but if one adequately quantifies the influences of terrain and roughness, it is considered possible to extract information on soil moisture from SAR imagery analysis and in turn use SAR imagery to validate hydrologic models
Should precipitation influence dust emission in global dust models?
NASA Astrophysics Data System (ADS)
Okin, Gregory
2016-04-01
Soil moisture modulates the threshold shear stress required to initiate aeolian transport and dust emission. Most of the theoretical and laboratory work that has confirmed the impact of soil moisture has appropriately acknowledged that it is the soil moisture of a surface layer a few grain diameters thick that truly controls threshold shear velocity. Global and regional models of dust emission include the effect of soil moisture on transport threshold, but most ignore the fact that only the moisture of the very topmost "active layer" matters. The soil moisture in the active layer can differ greatly from that integrated through the top 2, 5, 10, or 100 cm (surface layers used by various global models) because the top 2 mm of heavy texture soils dries within ~1/2 day while sandy soils dry within less than 2 hours. Thus, in drylands where dust emission occurs, it is likely that this top layer is drier than the underlying soil in the days and weeks after rain. This paper explores, globally, the time between rain events in relation to the time for the active layer to dry and the timing of high wind events. This analysis is carried out using the same coarse reanalyses used in global dust models and is intended to inform the soil moisture controls in these models. The results of this analysis indicate that the timing between events is, in almost all dust-producing areas, significantly longer than the drying time of the active layer, even when considering soil texture differences. Further, the analysis shows that the probability of a high wind event during the period after a rain where the surface is wet is small. Therefore, in coarse global models, there is little reason to include rain-derived soil moisture in the modeling scheme.
NASA Astrophysics Data System (ADS)
Yan, Hongxiang; Moradkhani, Hamid; Abbaszadeh, Peyman
2017-04-01
Assimilation of satellite soil moisture and streamflow data into hydrologic models using has received increasing attention over the past few years. Currently, these observations are increasingly used to improve the model streamflow and soil moisture predictions. However, the performance of this land data assimilation (DA) system still suffers from two limitations: 1) satellite data scarcity and quality; and 2) particle weight degeneration. In order to overcome these two limitations, we propose two possible solutions in this study. First, the general Gaussian geostatistical approach is proposed to overcome the limitation in the space/time resolution of satellite soil moisture products thus improving their accuracy at uncovered/biased grid cells. Secondly, an evolutionary PF approach based on Genetic Algorithm (GA) and Markov Chain Monte Carlo (MCMC), the so-called EPF-MCMC, is developed to further reduce weight degeneration and improve the robustness of the land DA system. This study provides a detailed analysis of the joint and separate assimilation of streamflow and satellite soil moisture into a distributed Sacramento Soil Moisture Accounting (SAC-SMA) model, with the use of recently developed EPF-MCMC and the general Gaussian geostatistical approach. Performance is assessed over several basins in the USA selected from Model Parameter Estimation Experiment (MOPEX) and located in different climate regions. The results indicate that: 1) the general Gaussian approach can predict the soil moisture at uncovered grid cells within the expected satellite data quality threshold; 2) assimilation of satellite soil moisture inferred from the general Gaussian model can significantly improve the soil moisture predictions; and 3) in terms of both deterministic and probabilistic measures, the EPF-MCMC can achieve better streamflow predictions. These results recommend that the geostatistical model is a helpful tool to aid the remote sensing technique and the EPF-MCMC is a reliable and effective DA approach in hydrologic applications.
The effect of row structure on soil moisture retrieval accuracy from passive microwave data.
Xingming, Zheng; Kai, Zhao; Yangyang, Li; Jianhua, Ren; Yanling, Ding
2014-01-01
Row structure causes the anisotropy of microwave brightness temperature (TB) of soil surface, and it also can affect soil moisture retrieval accuracy when its influence is ignored in the inversion model. To study the effect of typical row structure on the retrieved soil moisture and evaluate if there is a need to introduce this effect into the inversion model, two ground-based experiments were carried out in 2011. Based on the observed C-band TB, field soil and vegetation parameters, row structure rough surface assumption (Q p model and discrete model), including the effect of row structure, and flat rough surface assumption (Q p model), ignoring the effect of row structure, are used to model microwave TB of soil surface. Then, soil moisture can be retrieved, respectively, by minimizing the difference of the measured and modeled TB. The results show that soil moisture retrieval accuracy based on the row structure rough surface assumption is approximately 0.02 cm(3)/cm(3) better than the flat rough surface assumption for vegetated soil, as well as 0.015 cm(3)/cm(3) better for bare and wet soil. This result indicates that the effect of row structure cannot be ignored for accurately retrieving soil moisture of farmland surface when C-band is used.
Soil moisture retrieval by active/passive microwave remote sensing data
NASA Astrophysics Data System (ADS)
Wu, Shengli; Yang, Lijuan
2012-09-01
This study develops a new algorithm for estimating bare surface soil moisture using combined active / passive microwave remote sensing on the basis of TRMM (Tropical Rainfall Measuring Mission). Tropical Rainfall Measurement Mission was jointly launched by NASA and NASDA in 1997, whose main task was to observe the precipitation of the area in 40 ° N-40 ° S. It was equipped with active microwave radar sensors (PR) and passive sensor microwave imager (TMI). To accurately estimate bare surface soil moisture, precipitation radar (PR) and microwave imager (TMI) are simultaneously used for observation. According to the frequency and incident angle setting of PR and TMI, we first need to establish a database which includes a large range of surface conditions; and then we use Advanced Integral Equation Model (AIEM) to calculate the backscattering coefficient and emissivity. Meanwhile, under the accuracy of resolution, we use a simplified theoretical model (GO model) and the semi-empirical physical model (Qp Model) to redescribe the process of scattering and radiation. There are quite a lot of parameters effecting backscattering coefficient and emissivity, including soil moisture, surface root mean square height, correlation length, and the correlation function etc. Radar backscattering is strongly affected by the surface roughness, which includes the surface root mean square roughness height, surface correlation length and the correlation function we use. And emissivity is differently affected by the root mean square slope under different polarizations. In general, emissivity decreases with the root mean square slope increases in V polarization, and increases with the root mean square slope increases in H polarization. For the GO model, we found that the backscattering coefficient is only related to the root mean square slope and soil moisture when the incident angle is fixed. And for Qp Model, through the analysis, we found that there is a quite good relationship between Qpparameter and root mean square slope. So here, root mean square slope is a parameter that both models shared. Because of its big influence to backscattering and emissivity, we need to throw it out during the process of the combination of GO model and Qp model. The result we obtain from the combined model is the Fresnel reflection coefficient in the normal direction gama(0). It has a good relationship with the soil dielectric constant. In Dobson Model, there is a detailed description about Fresnel reflection coefficient and soil moisture. With the help of Dobson model and gama(0) that we have obtained, we can get the soil moisture that we want. The backscattering coefficient and emissivity data used in combined model is from TRMM/PR, TMI; with this data, we can obtain gama(0); further, we get the soil moisture by the relationship of the two parameters-- gama(0) and soil moisture. To validate the accuracy of the retrieval soil moisture, there is an experiment conducted in Tibet. The soil moisture data which is used to validate the retrieval algorithm is from GAME-Tibet IOP98 Soil Moisture and Temperature Measuring System (SMTMS). There are 9 observing sites in SMTMS to validate soil moisture. Meanwhile, we use the SMTMS soil moisture data obtained by Time Domain Reflectometer (TDR) to do the validation. And the result shows the comparison of retrieval and measured results is very good. Through the analysis, we can see that the retrieval and measured results in D66 is nearly close; and in MS3608, the measured result is a little higher than retrieval result; in MS3637, the retrieval result is a little higher than measured result. According to the analysis of the simulation results, we found that this combined active and passive approach to retrieve the soil moisture improves the retrieval accuracy.
NASA Astrophysics Data System (ADS)
Bonfante, A.; Basile, A.; de Mascellis, R.; Manna, P.; Terribile, F.
2009-04-01
Soil classification according to Soil Taxonomy include, as fundamental feature, the estimation of soil moisture regime. The term soil moisture regime refers to the "presence or absence either of ground water or of water held at a tension of less than 1500 kPa in the soil or in specific horizons during periods of the year". In the classification procedure, defining of the soil moisture control section is the primary step in order to obtain the soil moisture regimes classification. Currently, the estimation of soil moisture regimes is carried out through simple calculation schemes, such as Newhall and Billaux models, and only in few cases some authors suggest the use of different more complex models (i.e., EPIC) In fact, in the Soil Taxonomy, the definition of the soil moisture control section is based on the wetting front position in two different conditions: the upper boundary is the depth to which a dry soil will be moistened by 2.5 cm of water within 24 hours and the lower boundary is the depth to which a dry soil will be moistened by 7.5 cm of water within 48 hours. Newhall, Billaux and EPIC models don't use physical laws to describe soil water flows, but they use a simple bucket-like scheme where the soil is divided into several compartments and water moves, instantly, only downward when the field capacity is achieved. On the other side, a large number of one-dimensional hydrological simulation models (SWAP, Cropsyst, Hydrus, MACRO, etc..) are available, tested and successfully used. The flow is simulated according to pressure head gradients through the numerical solution of the Richard's equation. These simulation models can be fruitful used to improve the study of soil moisture regimes. The aims of this work are: (i) analysis of the soil moisture control section concept by a physically based model (SWAP); (ii) comparison of the classification obtained in five different Italian pedoclimatic conditions (Mantova and Lodi in northern Italy; Salerno, Benevento and Caserta in southern Italy) applying the classical models (Newhall e Billaux) and the physically-based models (CropSyst e SWAP), The results have shown that the Soil Taxonomy scheme for the definition of the soil moisture regime is unrealistic for the considered Mediterranean soil hydrological conditions. In fact, the same classifications arise irrespective of the soil type. In this respect some suggestions on how modified the section control boundaries were formulated. Keywords: Soil moisture regimes, Newhall, Swap, Soil Taxonomy
Evaluating Vertical Moisture Structure of the Madden-Julian Oscillation in Contemporary GCMs
NASA Astrophysics Data System (ADS)
Guan, B.; Jiang, X.; Waliser, D. E.
2013-12-01
The Madden-Julian Oscillation (MJO) remains a major challenge in our understanding and modeling of the tropical convection and circulation. Many models have troubles in realistically simulating key characteristics of the MJO, such as the strength, period, and eastward propagation. For models that do simulate aspects of the MJO, it remains to be understood what parameters and processes are the most critical in determining the quality of the simulations. This study focuses on the vertical structure of moisture in MJO simulations, with the aim to identify and understand the relationship between MJO simulation qualities and key parameters related to moisture. A series of 20-year simulations conducted by 26 GCMs are analyzed, including four that are coupled to ocean models and two that have a two-dimensional cloud resolving model embedded (i.e., superparameterized). TRMM precipitation and ERA-Interim reanalysis are used to evaluate the model simulations. MJO simulation qualities are evaluated based on pattern correlations of lead/lag regressions of precipitation - a measure of the model representation of the eastward propagating MJO convection. Models with strongest and weakest MJOs (top and bottom quartiles) are compared in terms of differences in moisture content, moisture convergence, moistening rate, and moist static energy. It is found that models with strongest MJOs have better representations of the observed vertical tilt of moisture. Relative importance of convection, advection, boundary layer, and large scale convection/precipitation are discussed in terms of their contribution to the moistening process. The results highlight the overall importance of vertical moisture structure in MJO simulations. The work contributes to the climatological component of the joint WCRP-WWRP/THORPEX YOTC MJO Task Force and the GEWEX Atmosphere System Study (GASS) global model evaluation project focused on the vertical structure and diabatic processes of the MJO.
Modelling soil water repellency at the daily scale in Portuguese burnt and unburnt eucalypt stands
NASA Astrophysics Data System (ADS)
Nunes, João Pedro; van der Slik, Bart; Marisa Santos, Juliana; Malvar Cortizo, Maruxa; Keizer, Jan Jacob
2014-05-01
Soil water repellency can impact soil hydrology, especially soil wetting. This creates a challenge for hydrological modelling in repellency-prone regions, since current models are generally unable to take it into account. This communication focuses on the development and evaluation of a daily water balance model which takes repellency into account, adapted for eucalypt forest plantations in the north-western Iberian Peninsula. The model was developed and tested using data from three eucalypt stands. Two were burnt in 2005, and the data included bi-weekly measurements of soil moisture and water repellency along a transect, during two years. The third was not burnt, and the data included both weekly measurements of soil water repellency and soil moisture along transects, and continuous measurements of soil moisture at one point, performed for one year between 2011 and 2012. All sites showed low repellency during the wet winter season (although less in the unburnt site, as the winter of 2011/12 was comparatively dry) and high repellency during the dry summer season; this seasonal pattern was strongly related with soil moisture fluctuations. The water balance model was based on the Thornthwaite-Mather method. Interception and tree potential evapotranspiration were estimated using satellite imagery (MODIS NDVI), the first by estimating LAI and applying the Gash interception model, and the second using the SAMIR approach. The model itself was modified by first estimating soil water repellency from soil moisture, using an empirical relation taking into account repellent and non-repellent moisture thresholds for each site; and afterwards using soil water repellency as a limiting factor on soil wettability, by limiting the fraction of infiltration which could replenish soil moisture. Results indicate that this simple approach to simulate repellency can provide adequate model performance and can be easily included in hydrological models.
NASA Astrophysics Data System (ADS)
Troch, P. A.; Gevaert, A.; Smit, Y.; Niu, G.; Nakolan, L.; Kyzivat, E.
2013-12-01
The Landscape Evolution Observatory (LEO) at Biosphere 2-The University of Arizona consists of three identical, sloping, 333 m2 convergent landscapes inside a 5,000 m2 environmentally controlled facility. These engineered landscapes contain 1-meter depth of basaltic tephra, ground to homogenous loamy sand that will undergo physical, chemical, and mineralogical changes over many years. Each landscape contains a spatially dense sensor and sampler network capable of resolving meter-scale lateral heterogeneity and sub-meter scale vertical heterogeneity in moisture, energy and carbon states and fluxes. The density of sensors and frequency at which they can be polled allows for data collection at spatial and temporal scales that are impossible in natural field settings. Embedded solution and gas samplers allow for quantification of biogeochemical processes, and facilitate the use of chemical tracers to study water movement at very high spatial resolutions. Each ~600 metric ton landscape has load cells embedded into the structure to measure changes in total system mass with 0.05% full-scale repeatability (equivalent to less than 1 cm of precipitation). This facilitates the real time accounting of hydrological partitioning at the hillslope scale. Each hillslope is equipped with an engineered rain system capable of raining at rates between 3 and 45 mm/hr in a range of spatial patterns. The rain systems are capable of creating long-term steady state conditions or running complex simulations. The precipitation water supply storage system is flexibly designed to facilitate addition of tracers at constant or time-varying rates for any of the three hillslopes. Six trenches measure subsurface flow via tipping bucket gauges and electromagnetic flowmeters. This presentation will give an overview of lessons learned during the commissioning phase of the first hillslope of LEO, and will indicate several opportunities for collaborative research at Biosphere 2.
NASA Astrophysics Data System (ADS)
Lorenz, Ruth; Argüeso, Daniel; Donat, Markus G.; Pitman, Andrew J.; van den Hurk, Bart; Berg, Alexis; Lawrence, David M.; Chéruy, Frédérique; Ducharne, Agnès.; Hagemann, Stefan; Meier, Arndt; Milly, P. C. D.; Seneviratne, Sonia I.
2016-01-01
We examine how soil moisture variability and trends affect the simulation of temperature and precipitation extremes in six global climate models using the experimental protocol of the Global Land-Atmosphere Coupling Experiment of the Coupled Model Intercomparison Project, Phase 5 (GLACE-CMIP5). This protocol enables separate examinations of the influences of soil moisture variability and trends on the intensity, frequency, and duration of climate extremes by the end of the 21st century under a business-as-usual (Representative Concentration Pathway 8.5) emission scenario. Removing soil moisture variability significantly reduces temperature extremes over most continental surfaces, while wet precipitation extremes are enhanced in the tropics. Projected drying trends in soil moisture lead to increases in intensity, frequency, and duration of temperature extremes by the end of the 21st century. Wet precipitation extremes are decreased in the tropics with soil moisture trends in the simulations, while dry extremes are enhanced in some regions, in particular the Mediterranean and Australia. However, the ensemble results mask considerable differences in the soil moisture trends simulated by the six climate models. We find that the large differences between the models in soil moisture trends, which are related to an unknown combination of differences in atmospheric forcing (precipitation, net radiation), flux partitioning at the land surface, and how soil moisture is parameterized, imply considerable uncertainty in future changes in climate extremes.
NASA Technical Reports Server (NTRS)
De Lannoy, Gabrielle; Reichle, Rolf; Gruber, Alexander; Bechtold, Michel; Quets, Jan; Vrugt, Jasper; Wigneron, Jean-Pierre
2018-01-01
The SMOS and SMAP missions have collected a wealth of global L-band Brightness temperature (Tb) observations. The retrieval of surface Soil moisture estimates, and the estimation of other geophysical Variables, such as root-zone soil moisture and temperature, via data Assimilation into land surface models largely depends on accurate Radiative transfer modeling (RTM). This presentation will focus on various configuration aspects of the RTM (i) for the inversion of SMOS Tb to surface soil moisture, and (ii) for the forward modeling as part of a SMOS Tb data assimilation System to estimate a consistent set of geophysical land surface Variables, using the GEOS-5 Catchment Land Surface Model.
Soil moisture observations using L-, C-, and X-band microwave radiometers
NASA Astrophysics Data System (ADS)
Bolten, John Dennis
The purpose of this thesis is to further the current understanding of soil moisture remote sensing under varying conditions using L-, C-, and X-band. Aircraft and satellite instruments are used to investigate the effects of frequency and spatial resolution on soil moisture sensitivity. The specific objectives of the research are to examine multi-scale observed and modeled microwave radiobrightness, evaluate new EOS Aqua Advanced Microwave Scanning Radiometer (AMSR-E) brightness temperature and soil moisture retrievals, and examine future satellite-based technologies for soil moisture sensing. The cycling of Earth's water, energy and carbon is vital to understanding global climate. Over land, these processes are largely dependent on the amount of moisture within the top few centimeters of the soil. However, there are currently no methods available that can accurately characterize Earth's soil moisture layer at the spatial scales or temporal resolutions appropriate for climate modeling. The current work uses ground truth, satellite and aircraft remote sensing data from three large-scale field experiments having different land surface, topographic and climate conditions. A physically-based radiative transfer model is used to simulate the observed aircraft and satellite measurements using spatially and temporally co-located surface parameters. A robust analysis of surface heterogeneity and scaling is possible due to the combination of multiple datasets from a range of microwave frequencies and field conditions. Accurate characterization of spatial and temporal variability of soil moisture during the three field experiments is achieved through sensor calibration and algorithm validation. Comparisons of satellite observations and resampled aircraft observations are made using soil moisture from a Numerical Weather Prediction (NWP) model in order to further demonstrate a soil moisture correlation where point data was unavailable. The influence of vegetation, spatial scaling, and surface heterogeneity on multi-scale soil moisture prediction is presented. This work demonstrates that derived soil moisture using remote sensing provides a better coverage of soil moisture spatial variability than traditional in-situ sensors. Effects of spatial scale were shown to be less significant than frequency on soil moisture sensitivity. Retrievals of soil moisture using the current methods proved inadequate under some conditions; however, this study demonstrates the need for concurrent spaceborne frequencies including L-, C, and X-band.
The impact of fog on soil moisture dynamics in the Namib Desert
NASA Astrophysics Data System (ADS)
Li, Bonan; Wang, Lixin; Kaseke, Kudzai F.; Vogt, Roland; Li, Lin; Seely, Mary K.
2018-03-01
Soil moisture is a crucial component supporting vegetation dynamics in drylands. Despite increasing attention on fog in dryland ecosystems, the statistical characterization of fog distribution and how fog affects soil moisture dynamics have not been seen in literature. To this end, daily fog records over two years (Dec 1, 2014-Nov 1, 2016) from three sites within the Namib Desert were used to characterize fog distribution. Two sites were located within the Gobabeb Research and Training Center vicinity, the gravel plains and the sand dunes. The third site was located at the gravel plains, Kleinberg. A subset of the fog data during rainless period was used to investigate the effect of fog on soil moisture. A stochastic modeling framework was used to simulate the effect of fog on soil moisture dynamics. Our results showed that fog distribution can be characterized by a Poisson process with two parameters (arrival rate λ and average depth α (mm)). Fog and soil moisture observations from eighty (Aug 19, 2015-Nov 6, 2015) rainless days indicated a moderate positive relationship between soil moisture and fog in the Gobabeb gravel plains, a weaker relationship in the Gobabeb sand dunes while no relationship was observed at the Kleinberg site. The modeling results suggested that mean and major peaks of soil moisture dynamics can be captured by the fog modeling. Our field observations demonstrated the effects of fog on soil moisture dynamics during rainless periods at some locations, which has important implications on soil biogeochemical processes. The statistical characterization and modeling of fog distribution are of great value to predict fog distribution and investigate the effects of potential changes in fog distribution on soil moisture dynamics.
Retrieval of Soil Moisture and Roughness from the Polarimetric Radar Response
NASA Technical Reports Server (NTRS)
Sarabandi, Kamal; Ulaby, Fawwaz T.
1997-01-01
The main objective of this investigation was the characterization of soil moisture using imaging radars. In order to accomplish this task, a number of intermediate steps had to be undertaken. In this proposal, the theoretical, numerical, and experimental aspects of electromagnetic scattering from natural surfaces was considered with emphasis on remote sensing of soil moisture. In the general case, the microwave backscatter from natural surfaces is mainly influenced by three major factors: (1) the roughness statistics of the soil surface, (2) soil moisture content, and (3) soil surface cover. First the scattering problem from bare-soil surfaces was considered and a hybrid model that relates the radar backscattering coefficient to soil moisture and surface roughness was developed. This model is based on extensive experimental measurements of the radar polarimetric backscatter response of bare soil surfaces at microwave frequencies over a wide range of moisture conditions and roughness scales in conjunction with existing theoretical surface scattering models in limiting cases (small perturbation, physical optics, and geometrical optics models). Also a simple inversion algorithm capable of providing accurate estimates of soil moisture content and surface rms height from single-frequency multi-polarization radar observations was developed. The accuracy of the model and its inversion algorithm is demonstrated using independent data sets. Next the hybrid model for bare-soil surfaces is made fully polarimetric by incorporating the parameters of the co- and cross-polarized phase difference into the model. Experimental data in conjunction with numerical simulations are used to relate the soil moisture content and surface roughness to the phase difference statistics. For this purpose, a novel numerical scattering simulation for inhomogeneous dielectric random surfaces was developed. Finally the scattering problem of short vegetation cover above a rough soil surface was considered. A general scattering model for grass-blades of arbitrary cross section was developed and incorporated in a first order random media model. The vegetation model and the bare-soil model are combined and the accuracy of the combined model is evaluated against experimental observations from a wheat field over the entire growing season. A complete set of ground-truth data and polarimetric backscatter data were collected. Also an inversion algorithm for estimating soil moisture and surface roughness from multi-polarized multi-frequency observations of vegetation-covered ground is developed.
Weather Impact on Airport Arrival Meter Fix Throughput
NASA Technical Reports Server (NTRS)
Wang, Yao
2017-01-01
Time-based flow management provides arrival aircraft schedules based on arrival airport conditions, airport capacity, required spacing, and weather conditions. In order to meet a scheduled time at which arrival aircraft can cross an airport arrival meter fix prior to entering the airport terminal airspace, air traffic controllers make regulations on air traffic. Severe weather may create an airport arrival bottleneck if one or more of airport arrival meter fixes are partially or completely blocked by the weather and the arrival demand has not been reduced accordingly. Under these conditions, aircraft are frequently being put in holding patterns until they can be rerouted. A model that predicts the weather impacted meter fix throughput may help air traffic controllers direct arrival flows into the airport more efficiently, minimizing arrival meter fix congestion. This paper presents an analysis of air traffic flows across arrival meter fixes at the Newark Liberty International Airport (EWR). Several scenarios of weather impacted EWR arrival fix flows are described. Furthermore, multiple linear regression and regression tree ensemble learning approaches for translating multiple sector Weather Impacted Traffic Indexes (WITI) to EWR arrival meter fix throughputs are examined. These weather translation models are developed and validated using the EWR arrival flight and weather data for the period of April-September in 2014. This study also compares the performance of the regression tree ensemble with traditional multiple linear regression models for estimating the weather impacted throughputs at each of the EWR arrival meter fixes. For all meter fixes investigated, the results from the regression tree ensemble weather translation models show a stronger correlation between model outputs and observed meter fix throughputs than that produced from multiple linear regression method.
The Contribution of Soil Moisture Information to Forecast Skill: Two Studies
NASA Technical Reports Server (NTRS)
Koster, Randal
2010-01-01
This talk briefly describes two recent studies on the impact of soil moisture information on hydrological and meteorological prediction. While the studies utilize soil moisture derived from the integration of large-scale land surface models with observations-based meteorological data, the results directly illustrate the potential usefulness of satellite-derived soil moisture information (e.g., from SMOS and SMAP) for applications in prediction. The first study, the GEWEX- and ClIVAR-sponsored GLACE-2 project, quantifies the contribution of realistic soil moisture initialization to skill in subseasonal forecasts of precipitation and air temperature (out to two months). The multi-model study shows that soil moisture information does indeed contribute skill to the forecasts, particularly for air temperature, and particularly when the initial local soil moisture anomaly is large. Furthermore, the skill contributions tend to be larger where the soil moisture initialization is more accurate, as measured by the density of the observational network contributing to the initialization. The second study focuses on streamflow prediction. The relative contributions of snow and soil moisture initialization to skill in streamflow prediction at seasonal lead, in the absence of knowledge of meteorological anomalies during the forecast period, were quantified with several land surface models using uniquely designed numerical experiments and naturalized streamflow data covering mUltiple decades over the western United States. In several basins, accurate soil moisture initialization is found to contribute significant levels of predictive skill. Depending on the date of forecast issue, the contributions can be significant out to leads of six months. Both studies suggest that improvements in soil moisture initialization would lead to increases in predictive skill. The relevance of SMOS and SMAP satellite-based soil moisture information to prediction are discussed in the context of these studies.
NASA Astrophysics Data System (ADS)
Sure, A.; Dikshit, O.
2017-12-01
Root zone soil moisture (RZSM) is an important element in hydrology and agriculture. The estimation of RZSM provides insight in selecting the appropriate crops for specific soil conditions (soil type, bulk density, etc.). RZSM governs various vadose zone phenomena and subsequently affects the groundwater processes. With various satellite sensors dedicated to estimating surface soil moisture at different spatial and temporal resolutions, estimation of soil moisture at root zone level for Indo - Gangetic basin which inherits complex heterogeneous environment, is quite challenging. This study aims at estimating RZSM and understand its variation at the level of Indo - Gangetic basin with changing land use/land cover, topography, crop cycles, soil properties, temperature and precipitation patterns using two satellite derived soil moisture datasets operating at distinct frequencies with different principles of acquisition. Two surface soil moisture datasets are derived from AMSR-2 (6.9 GHz - `C' Band) and SMOS (1.4 GHz - `L' band) passive microwave sensors with coarse spatial resolution. The Soil Water Index (SWI), accounting for soil moisture from the surface, is derived by considering a theoretical two-layered water balance model and contributes in ascertaining soil moisture at the vadose zone. This index is evaluated against the widely used modelled soil moisture dataset of GLDAS - NOAH, version 2.1. This research enhances the domain of utilising the modelled soil moisture dataset, wherever the ground dataset is unavailable. The coupling between the surface soil moisture and RZSM is analysed for two years (2015-16), by defining a parameter T, the characteristic time length. The study demonstrates that deriving an optimal value of T for estimating SWI at a certain location is a function of various factors such as land, meteorological, and agricultural characteristics.
NASA Astrophysics Data System (ADS)
Hüsami Afşar, M.; Bulut, B.; Yilmaz, M. T.
2017-12-01
Soil moisture is one of the fundamental parameters of the environment that plays a major role in carbon, energy, and water cycles. Spatial distribution and temporal changes of soil moisture is one of the important components in climatic, ecological and natural hazards at global, regional and local levels scales. Therefore retrieval of soil moisture datasets has a great importance in these studies. Given soil moisture can be retrieved through different platforms (i.e., in-situ measurements, numerical modeling, and remote sensing) for the same location and time period, it is often desirable to evaluate these different datasets to assign the most accurate estimates for different purposes. During last decades, efforts have been given to provide evaluations about different soil moisture products based on various statistical analysis of the soil moisture time series (i.e., comparison of correlation, bias, and their error standard deviation). On the other hand, there is still need for the comparisons of the soil moisture products in drought analysis context. In this study, LPRM and NOAH Land Surface Model soil moisture datasets are investigated in drought analysis context using station-based watershed average datasets obtained over four USDA ARS watersheds as ground truth. Here, the drought analysis are performed using the standardized soil moisture datasets (i.e., zero mean and one standard deviation) while the droughts are defined as consecutive negative anomalies less than -1 for longer than 3 months duration. Accordingly, the drought characteristics (duration and severity) and false alarm and hit/miss ratios of LPRM and NOAH datasets are validated using station-based datasets as ground truth. Results showed that although the NOAH soil moisture products have better correlations, LPRM based soil moisture retrievals show better consistency in drought analysis. This project is supported by TUBITAK Project number 114Y676.
Lavado Contador, J F; Maneta, M; Schnabel, S
2006-10-01
The capability of Artificial Neural Network models to forecast near-surface soil moisture at fine spatial scale resolution has been tested for a 99.5 ha watershed located in SW Spain using several easy to achieve digital models of topographic and land cover variables as inputs and a series of soil moisture measurements as training data set. The study methods were designed in order to determining the potentials of the neural network model as a tool to gain insight into soil moisture distribution factors and also in order to optimize the data sampling scheme finding the optimum size of the training data set. Results suggest the efficiency of the methods in forecasting soil moisture, as a tool to assess the optimum number of field samples, and the importance of the variables selected in explaining the final map obtained.
NASA Technical Reports Server (NTRS)
Rose, F. G.
1983-01-01
Modeled temperature data from a one-dimensional, time-dependent, initial value, planetary boundary layer model for 16 separate model runs with varying initial values of moisture availability are applied, by the use of a regression equation, to longwave infrared GOES satellite data to infer moisture availability over a regional area in the central U.S. This was done for several days during the summers of 1978 and 1980 where a large gradient in the antecedent precipitation index (API) represented the boundary between a drought area and a region of near normal precipitation. Correlations between satellite derived moisture availability and API were found to exist. Errors from the presence of clouds, water vapor and other spatial inhomogeneities made the use of the measurement for anything except the relative degree of moisture availability dubious.
NASA Technical Reports Server (NTRS)
Hancock, G. D.; Waite, W. P.
1984-01-01
Two experiments were performed employing swept frequency microwaves for the purpose of investigating the reflectivity from soil volumes containing both discontinuous and continuous changes in subsurface soil moisture content. Discontinuous moisture profiles were artificially created in the laboratory while continuous moisture profiles were induced into the soil of test plots by the environment of an agricultural field. The reflectivity for both the laboratory and field experiments was measured using bi-static reflectometers operated over the frequency ranges of 1.0 to 2.0 GHz and 4.0 to 8.0 GHz. Reflectivity models that considered the discontinuous and continuous moisture profiles within the soil volume were developed and compared with the results of the experiments. This comparison shows good agreement between the smooth surface models and the measurements. In particular the comparison of the smooth surface multi-layer model for continuous moisture profiles and the yield experiment measurements points out the sensitivity of the specular component of the scattered electromagnetic energy to the movement of moisture in the soil.
Toward improving the representation of the water cycle at High Northern Latitudes
NASA Astrophysics Data System (ADS)
Lahoz, William; Svendby, Tove; Hamer, Paul; Blyverket, Jostein; Kristiansen, Jørn; Luijting, Hanneke
2016-04-01
The rapid warming at northern latitude regions in recent decades has resulted in a lengthening of the growing season, greater photosynthetic activity and enhanced carbon sequestration by the ecosystem. These changes are likely to intensify summer droughts, tree mortality and wildfires. A potential major climate change feedback is the release of carbon-bearing compounds from soil thawing. These changes make it important to have information on the land surface (soil moisture and temperature) at high northern latitude regions. The availability of soil moisture measurements from several satellite platforms provides an opportunity to address issues associated with the effects of climate change, e.g., assessing multi-decadal links between increasing temperatures, snow cover, soil moisture variability and vegetation dynamics. The relatively poor information on water cycle parameters for biomes at northern high latitudes make it important that efforts are expended on improving the representation of the water cycle at these latitudes. In a collaboration between NILU and Met Norway, we evaluate the soil moisture observations over Norway from the ESA satellite SMOS (Soil Moisture and Ocean Salinity) using in situ ground based soil moisture measurements, with reference to drought and flood episodes. We will use data assimilation of the quality-controlled SMOS soil moisture observations into a land surface model and a numerical weather prediction model to assess the added value from satellite observations of soil moisture for improving the representation of the water cycle at high northern latitudes. This presentation provides first results from this work. We discuss the evaluation of SMOS soil moisture data (and from other satellites) against ground-based in situ data over Norway; the performance of the SMOS soil moisture data for selected drought and flood conditions over Norway; and the first results from data assimilation experiments with land surface models and numerical weather prediction models. Analyses include information on root zone soil moisture. We provide evidence of the value of satellite soil measurements over Norway, including their fidelity, and their impact at improving the representation of the hydrological cycle over northern high latitudes. We indicate benefits from these results for multi-decadal soil moisture datasets such as that from the ESA CCI for soil moisture.
Modeling Heat and Moisture Transport in Steam-Cured Mortar: Application to Aashto Type Vi Beams.
Hernández-Bautista, E; Sandoval-Torres, S; de J Cano-Barrita, P F; Bentz, D P
2017-10-01
During steam curing of concrete, temperature and moisture gradients are developed, which are difficult to measure experimentally and can adversely affect the durability of concrete. In this research, a model of cement hydration coupled to moisture and heat transport was used to simulate the process of steam curing of mortars with water-to-cement ( w/c ) ratios by mass of 0.30 and 0.45, considering natural convection boundary conditions in mortar and concrete specimens of AASHTO Type VI beams. The primary variables of the model were moisture content, temperature, and degree of hydration. Moisture content profiles of mortar specimens (40 mm in diameter and 50 mm in height) were measured by magnetic resonance imaging. The degree of hydration was obtained by mass-based measurements of loss on ignition to 1000 °C. The results indicate that the model correctly simulates the moisture distribution and degree of hydration in mortar specimens. Application of the model to the steam curing of an AASHTO Type VI beam indicates temperature differences (between the surface and the center) higher than 20 °C during the cooling stage, and internal temperatures higher than 70 °C that may compromise the durability of the concrete.
A simulation study of scene confusion factors in sensing soil moisture from orbital radar
NASA Technical Reports Server (NTRS)
Ulaby, F. T. (Principal Investigator); Dobson, M. C.; Moezzi, S.; Roth, F. T.
1983-01-01
Simulated C-band radar imagery for a 124-km by 108-km test site in eastern Kansas is used to classify soil moisture. Simulated radar resolutions are 100 m by 100 m, 1 km by 1km, and 3 km by 3 km. Distributions of actual near-surface soil moisture are established daily for a 23-day accounting period using a water budget model. Within the 23-day period, three orbital radar overpasses are simulated roughly corresponding to generally moist, wet, and dry soil moisture conditions. The radar simulations are performed by a target/sensor interaction model dependent upon a terrain model, land-use classification, and near-surface soil moisture distribution. The accuracy of soil-moisture classification is evaluated for each single-date radar observation and also for multi-date detection of relative soil moisture change. In general, the results for single-date moisture detection show that 70% to 90% of cropland can be correctly classified to within +/- 20% of the true percent of field capacity. For a given radar resolution, the expected classification accuracy is shown to be dependent upon both the general soil moisture condition and also the geographical distribution of land-use and topographic relief. An analysis of cropland, urban, pasture/rangeland, and woodland subregions within the test site indicates that multi-temporal detection of relative soil moisture change is least sensitive to classification error resulting from scene complexity and topographic effects.
USDA-ARS?s Scientific Manuscript database
Soil moisture plays an integral role in various aspects ranging from multi-scale hydrologic modeling to agricultural decision analysis to multi-scale hydrologic modeling, from climate change assessments to drought prediction and prevention. The broad availability of soil moisture estimates has only...
USDA-ARS?s Scientific Manuscript database
Although there have been efforts to improve existing soil moisture retrieval algorithms, the ability to estimate soil moisture from passive microwave observations is still hampered by problems in accurately modeling the observed microwave signal. This paper focuses on the estimation of effective sur...
Hamzalıoğlu, Aytül; Gökmen, Vural
2018-02-01
In this study, reactions of hydroxymethylfurfural (HMF) with selected amino acids (arginine, cysteine and lysine) were investigated in HMF-amino acid (high moisture) and Coffee-amino acid (low moisture) model systems at 5, 25 and 50°C. The results revealed that HMF reacted efficiently and effectively with amino acids in both high and low moisture model systems. High-resolution mass spectrometry (HRMS) analyses of the reaction mixtures confirmed the formations of Michael adduct and Schiff base of HMF with amino acids. Calculated pseudo-first order reaction rate constants were in the following order; k Cysteine >k Arginine >k Lysine for high moisture model systems. Comparing to these rate constants, the k Cysteine decreased whereas, k Arginine and k Lysine increased under the low moisture conditions of Coffee-amino acid model systems. The temperature dependence of the rate constants was found to obey the Arrhenius law in a temperature range of 5-50°C under both low and high moisture conditions. Copyright © 2017 Elsevier Ltd. All rights reserved.
NASA Technical Reports Server (NTRS)
Paris, J. F.; Arya, L. M.; Davidson, S. A.; Hildreth, W. W.; Richter, J. C.; Rosenkranz, W. A.
1982-01-01
The NASA/JSC ground scatterometer system was used in a row structure and row direction effects experiment to understand these effects on radar remote sensing of soil moisture. Also, a modification of the scatterometer system was begun and is continuing, to allow cross-polarization experiments to be conducted in fiscal years 1982 and 1983. Preprocessing of the 1978 agricultural soil moisture experiment (ASME) data was completed. Preparations for analysis of the ASME data is fiscal year 1982 were completed. A radar image simulation procedure developed by the University of Kansas is being improved. Profile soil moisture model outputs were compared quantitatively for the same soil and climate conditions. A new model was developed and tested to predict the soil moisture characteristic (water tension versus volumetric soil moisture content) from particle-size distribution and bulk density data. Relationships between surface-zone soil moisture, surface flux, and subsurface moisture conditions are being studied as well as the ways in which measured soil moisture (as obtained from remote sensing) can be used for agricultural applications.
The moisture response of soil heterotrophic respiration: Interaction with soil properties.
USDA-ARS?s Scientific Manuscript database
Soil moisture-respiration functions are used to simulate the various mechanisms determining the relations between soil moisture content and carbon mineralization. Soil models used in the simulation of global carbon fluxes often apply simplified functions assumed to represent an average moisture-resp...
Data assimilation to extract soil moisture information from SMAP observations
USDA-ARS?s Scientific Manuscript database
This study compares different methods to extract soil moisture information through the assimilation of Soil Moisture Active Passive (SMAP) observations. Neural Network(NN) and physically-based SMAP soil moisture retrievals were assimilated into the NASA Catchment model over the contiguous United Sta...
Elevated moisture stimulates carbon loss from mineral soils by releasing protected organic matter.
Huang, Wenjuan; Hall, Steven J
2017-11-24
Moisture response functions for soil microbial carbon (C) mineralization remain a critical uncertainty for predicting ecosystem-climate feedbacks. Theory and models posit that C mineralization declines under elevated moisture and associated anaerobic conditions, leading to soil C accumulation. Yet, iron (Fe) reduction potentially releases protected C, providing an under-appreciated mechanism for C destabilization under elevated moisture. Here we incubate Mollisols from ecosystems under C 3 /C 4 plant rotations at moisture levels at and above field capacity over 5 months. Increased moisture and anaerobiosis initially suppress soil C mineralization, consistent with theory. However, after 25 days, elevated moisture stimulates cumulative gaseous C-loss as CO 2 and CH 4 to >150% of the control. Stable C isotopes show that mineralization of older C 3 -derived C released following Fe reduction dominates C losses. Counter to theory, elevated moisture may significantly accelerate C losses from mineral soils over weeks to months-a critical mechanistic deficiency of current Earth system models.
Pu, Yuan-Yuan; Sun, Da-Wen
2015-12-01
Mango slices were dried by microwave-vacuum drying using a domestic microwave oven equipped with a vacuum desiccator inside. Two lab-scale hyperspectral imaging (HSI) systems were employed for moisture prediction. The Page and the Two-term thin-layer drying models were suitable to describe the current drying process with a fitting goodness of R(2)=0.978. Partial least square (PLS) was applied to correlate the mean spectrum of each slice and reference moisture content. With three waveband selection strategies, optimal wavebands corresponding to moisture prediction were identified. The best model RC-PLS-2 (Rp(2)=0.972 and RMSEP=4.611%) was implemented into the moisture visualization procedure. Moisture distribution map clearly showed that the moisture content in the central part of the mango slices was lower than that of other parts. The present study demonstrated that hyperspectral imaging was a useful tool for non-destructively and rapidly measuring and visualizing the moisture content during drying process. Copyright © 2015 Elsevier Ltd. All rights reserved.
Investigation of the Moisture Recycling Ratio over South America: A Modelling Approach using HadCM3
NASA Astrophysics Data System (ADS)
Charan Pattnayak, Kanhu; Gloor, Emanuel; Tindall, Julia; Briener, Roel
2017-04-01
It is a well-known fact that precipitation relies on terrestrial evaporation (moisture recycling). This study makes use of new definitions of moisture recycling from van der Ent, et al. 2010 to study the complete process of continental moisture feedback. Earlier studies have shown that there exist many regions over the globe that relies heavily on recycled moisture as well as that supplies moisture. In South America, the Río de la Plata basin depends on evaporation from the Amazon forest for 70% of its water resources. Stable water isotope (δ18O) can be used, as a good proxy for precipitation and it is a better tool to study convective processes and hydrological cycle. Analysing the δ18O would help to identify the moisture source for precipitation. In this study, we try to explain to the relation between δ18O and the moisture recycling ratio using atmospheric component of Hadley Centre Coupled Climate Model (HadCM3). And also we analyse the impact of land cover change on δ18O and the moisture recycling ratio. Further, we will analyse the changes of moisture recycling pattern from pre-industrial to the present scenario.
Preliminary assessment of soil moisture over vegetation
NASA Technical Reports Server (NTRS)
Carlson, T. N.
1986-01-01
Modeling of surface energy fluxes was combined with in-situ measurement of surface parameters, specifically the surface sensible heat flux and the substrate soil moisture. A vegetation component was incorporated in the atmospheric/substrate model and subsequently showed that fluxes over vegetation can be very much different than those over bare soil for a given surface-air temperature difference. The temperature signatures measured by a satellite or airborne radiometer should be interpreted in conjunction with surface measurements of modeled parameters. Paradoxically, analyses of the large-scale distribution of soil moisture availability shows that there is a very high correlation between antecedent precipitation and inferred surface moisture availability, even when no specific vegetation parameterization is used in the boundary layer model. Preparatory work was begun in streamlining the present boundary layer model, developing better algorithms for relating surface temperatures to substrate moisture, preparing for participation in the French HAPEX experiment, and analyzing aircraft microwave and radiometric surface temperature data for the 1983 French Beauce experiments.
NASA Astrophysics Data System (ADS)
Ťupek, Boris; Launiainen, Samuli; Peltoniemi, Mikko; Heikkinen, Jukka; Lehtonen, Aleksi
2016-04-01
Litter decomposition rates of the most process based soil carbon models affected by environmental conditions are linked with soil heterotrophic CO2 emissions and serve for estimating soil carbon sequestration; thus due to the mass balance equation the variation in measured litter inputs and measured heterotrophic soil CO2 effluxes should indicate soil carbon stock changes, needed by soil carbon management for mitigation of anthropogenic CO2 emissions, if sensitivity functions of the applied model suit to the environmental conditions e.g. soil temperature and moisture. We evaluated the response forms of autotrophic and heterotrophic forest floor respiration to soil temperature and moisture in four boreal forest sites of the International Cooperative Programme on Assessment and Monitoring of Air Pollution Effects on Forests (ICP Forests) by a soil trenching experiment during year 2015 in southern Finland. As expected both autotrophic and heterotrophic forest floor respiration components were primarily controlled by soil temperature and exponential regression models generally explained more than 90% of the variance. Soil moisture regression models on average explained less than 10% of the variance and the response forms varied between Gaussian for the autotrophic forest floor respiration component and linear for the heterotrophic forest floor respiration component. Although the percentage of explained variance of soil heterotrophic respiration by the soil moisture was small, the observed reduction of CO2 emissions with higher moisture levels suggested that soil moisture response of soil carbon models not accounting for the reduction due to excessive moisture should be re-evaluated in order to estimate right levels of soil carbon stock changes. Our further study will include evaluation of process based soil carbon models by the annual heterotrophic respiration and soil carbon stocks.
Why the predictions for monsoon rainfall fail?
NASA Astrophysics Data System (ADS)
Lee, J.
2016-12-01
To be in line with the Global Land/Atmosphere System Study (GLASS) of the Global Energy and Water Cycle Experiment (GEWEX) international research scheme, this study discusses classical arguments about the feedback mechanisms between land surface and precipitation to improve the predictions of African monsoon rainfall. In order to clarify the impact of antecedent soil moisture on subsequent rainfall evolution, several data sets will be presented. First, in-situ soil moisture field measurements acquired by the AMMA field campaign will be shown together with rain gauge data. This data set will validate various model and satellite data sets such as NOAH land surface model, TRMM rainfall, CMORPH rainfall and HadGEM climate models, SMOS soil moisture. To relate soil moisture with precipitation, two approaches are employed: one approach makes a direct comparison between the spatial distributions of soil moisture as an absolute value and rainfall, while the other measures a temporal evolution of the consecutive dry days (i.e. a relative change within the same soil moisture data set over time) and rainfall occurrences. Consecutive dry days shows consistent results of a negative feedback between soil moisture and rainfall across various data sets, contrary to the direct comparison of soil moisture state. This negative mechanism needs attention, as most climate models usually focus on a positive feedback only. The approach of consecutive dry days takes into account the systematic errors in satellite observations, reminding us that it may cause the misinterpretation to directly compare model with satellite data, due to their difference in data retrievals. This finding is significant, as the climate indices employed by the Intergovernmental Panel on Climate Change (IPCC) modelling archive are based on the atmospheric variable rathr than land.
NASA Astrophysics Data System (ADS)
Markewitz, D.; Sutter, L.; Richter, D. D., Jr.
2017-12-01
Soil Electrical Resistivity Tomography (ERT) was measured across the Calhoun Critical Zone Observatory in relation to land use cover. ERT can help identify patterns in soil and saprolite physical attributes and moisture content through multiple meters. ERT data were generated with an AGI Supersting R8 with a 28 probe dipole-dipole array on a 1.5 meter spacing providing information through the upper 9 m. In Nov/Dec 2016 ten soil pits were dug to 3m depth in agricultural fields, pine forests, and hardwood forests across the CCZO and ERT measures were taken centered on these pits. ERT values ranged from 200 to 2500 Ohm-m. ERT patterns in the agricultural field demonstrated a limited resistivity gradient (200-700 Ohm-m) appearing moist throughout. In contrast, research areas under pine and hardwood forest had stronger resistivity gradients reflecting both moisture and physical attributes (i.e., texture or rock content). For example, research area 2 under pine had an area of higher resistivity that correlated with a band of saprolite that was readily visible in the exposed profile. In research area 7 and 8 that included both pine and hardwood forest resistivity gradients had contradictory patterns of high to low resistivity from top to bottom. In research area 7 resistivity was highest at the surface and decreased with depth, a common pattern when water table is at depth. In research area 8 the inverse was observed with low resistivity above and resistivity increasing with depth, a pattern observed in upper landscape positions on ridges with moist clay above dry saprolite. ERT patterns did reflect a large difference in the measured agricultural fields compared to forest while other difference appeared to reflect landscape position.
Breast oedema following free flap breast reconstruction.
Greenhowe, Jennifer; Stephen, Christopher; McClymont, Liusaidh; Munnoch, D Alex
2017-08-01
Breast oedema causes significant morbidity and is historically difficult to quantify. The aim of this study was to identify changes in breast tissue water content from pre-operative levels in the native breast to post-operative levels in mastectomy skin flaps and free flaps in the reconstructed breast. One hundred patients undergoing unilateral mastectomy and immediate free flap breast reconstruction were examined pre-operatively and at three post-operative appointments. A validated moisture meter was used to record dermal water percentages of each breast quadrant and areola in both breasts pre-operatively, then four quadrants of both breasts plus the unaffected areola and free flap at each post-operative review. Native skin of the reconstructed breast showed significant, persistent increase in MWC from 45.6% ± 0.5% to 72.8% ± 0.9% at 1st follow up (p < 0.001), decreasing only to 67.6% ± 0.8% by 3rd follow up. There was a marked difference (p < 0.001) in the mean water content (MWC) of the initial free flap (39.7% ± 0.6%) compared to 61.8% ± 1.7% at 1st follow up, then 55.1% ± 1.4% at 2nd and 53.7% ± 1.3% at 3rd follow ups. The unaffected breast showed a small but significant increase in MWC of all quadrants at subsequent follow up (greatest difference 3.1% at 1st follow up). This patient group demonstrates significant, persistent oedema of the reconstructed breast, which can be monitored using a non-invasive moisture meter. Crown Copyright © 2017. Published by Elsevier Ltd. All rights reserved.
Economic characteristics of the peat deposits of Costa Rica: preliminary study
DOE Office of Scientific and Technical Information (OSTI.GOV)
Cohen, A.D. Malavassi, L.; Raymond, R. Jr.; Mora, S.
1985-01-01
Recent field and laboratory studies have established the presence of numerous extensive peat deposits in Costa Rica. Three of these were selected for initial investigation: (1) the cloud-forest histosols of the Talamanca Mountain Range; (2) the Rio Medio Queso flood plain deposits near the northern Costa Rican border; and (3) a tropical jungle swamp deposit on the northeastern coastal plain. In the Talamanca area, 29 samples were collected from eight sites. Due to the high moisture and cool temperatures of the cloud forest, the peats in this area form blanket-like deposits (generally <1 meter thick) over a wide area (>150more » km/sup 2/). These peats are all highly decomposed (avg. 28% fiber), high in ash (avg. 21%), and extensively bioturbated. Relative to all other sites visited, these peats are lowest in moisture (avg. 84%), pH (avg. 4.4), fixed carbon (avg. 23%), and sulfur (avg. 0.2%). However, they have the highest bulk densities (avg. 0.22 g/cc), volatile matter contents (avg. 55%), and nitrogen. Their heating value averaged 7700 BTUs/lb., dry. In the Rio Medio Queso area, 28 samples were collected, representing one transect of the 70 km/sup 2/ flood plain. The peats here occurred in several layers (each <1-1/2 meters thick), interfingering with river flood plain sediments. These peats have the highest calorific values (avg. 8000 BTUs/lb., dry), fixed carbon (avg. 30%), and ash (avg. 22%) and have an average pH of 5.4 and a bulk density of 0.20 g/cc. These results represent only the first part of a long-term, extensive survey of Costa Rica's peat resources. However, they suggest that large, economically-significant peat deposits may be present in this country. 5 refs., 8 figs., 4 tabs.« less
Advances in modeling sorption and diffusion of moisture in porous reactive materials.
Harley, Stephen J; Glascoe, Elizabeth A; Lewicki, James P; Maxwell, Robert S
2014-06-23
Water-vapor-uptake experiments were performed on a silica-filled poly(dimethylsiloxane) (PDMS) network and modeled by using two different approaches. The data was modeled by using established methods and the model parameters were used to predict moisture uptake in a sample. The predictions are reasonably good, but not outstanding; many of the shortcomings of the modeling are discussed. A high-fidelity modeling approach is derived and used to improve the modeling of moisture uptake and diffusion. Our modeling approach captures the physics and kinetics of diffusion and adsorption/desorption, simultaneously. It predicts uptake better than the established method; more importantly, it is also able to predict outgassing. The material used for these studies is a filled-PDMS network; physical interpretations concerning the sorption and diffusion of moisture in this network are discussed. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
William Massman
2015-01-01
Increased use of prescribed fire by land managers and the increasing likelihood of wildfires due to climate change require an improved modeling capability of extreme heating of soils during fires. This issue is addressed here by developing and testing the soil (heat-moisture-vapor) HMVmodel, a 1-D (one-dimensional) non-equilibrium (liquid- vapor phase change)...
Concerning the relationship between evapotranspiration and soil moisture
NASA Technical Reports Server (NTRS)
Wetzel, Peter J.; Chang, Jy-Tai
1987-01-01
The relationship between the evapotranspiration and soil moisture during the drying, supply-limited phase is studied. A second scaling parameter, based on the evapotranspirational supply and demand concept of Federer (1982), is defined; the parameter, referred to as the threshold evapotranspiration, occurs in vegetation-covered surfaces just before leaf stomata close and when surface tension restricts moisture release from bare soil pores. A simple model for evapotranspiration is proposed. The effects of natural soil heterogeneities on evapotranspiration computed from the model are investigated. It is observed that the natural variability in soil moisture, caused by the heterogeneities, alters the relationship between regional evapotranspiration and the area average soil moisture.
Wagner, Wolfgang; Pathe, Carsten; Doubkova, Marcela; Sabel, Daniel; Bartsch, Annett; Hasenauer, Stefan; Blöschl, Günter; Scipal, Klaus; Martínez-Fernández, José; Löw, Alexander
2008-01-01
The high spatio-temporal variability of soil moisture is the result of atmospheric forcing and redistribution processes related to terrain, soil, and vegetation characteristics. Despite this high variability, many field studies have shown that in the temporal domain soil moisture measured at specific locations is correlated to the mean soil moisture content over an area. Since the measurements taken by Synthetic Aperture Radar (SAR) instruments are very sensitive to soil moisture it is hypothesized that the temporally stable soil moisture patterns are reflected in the radar backscatter measurements. To verify this hypothesis 73 Wide Swath (WS) images have been acquired by the ENVISAT Advanced Synthetic Aperture Radar (ASAR) over the REMEDHUS soil moisture network located in the Duero basin, Spain. It is found that a time-invariant linear relationship is well suited for relating local scale (pixel) and regional scale (50 km) backscatter. The observed linear model coefficients can be estimated by considering the scattering properties of the terrain and vegetation and the soil moisture scaling properties. For both linear model coefficients, the relative error between observed and modelled values is less than 5 % and the coefficient of determination (R2) is 86 %. The results are of relevance for interpreting and downscaling coarse resolution soil moisture data retrieved from active (METOP ASCAT) and passive (SMOS, AMSR-E) instruments. PMID:27879759
NASA Astrophysics Data System (ADS)
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 events and more prolonged response to drying cycles, as opposed to binary behavior in the control.
Phase Sensitiveness to Soil Moisture in Controlled Anechoic Chamber: Measurements and First Results
NASA Astrophysics Data System (ADS)
Ben Khadhra, K.; Nolan, M.; Hounam, D.; Boerner, T.
2005-12-01
To date many radar methods and models have been reported for the estimation of soil moisture, such as the Oh-model or the Dubois model. Those models, which use only the magnitude of the backscattered signal, show results with 5 to 10 % accuracy. In the last two decades SAR Interferometry (InSAR) and differential InSAR (DInSAR), which uses the phase of the backscattered signal, has been shown to be a useful tool for the creation of Digital Elevation Models (DEMs), and temporal changes due to earthquakes, subsidence, and other ground motions. Nolan (2003) also suggested the possibility to use DINSAR penetration depth as a proxy to estimate the soil moisture. The principal is based on the relationship between the penetration depth and the permittivity, which varies as a function of soil moisture. In this paper we will present new interferometric X-band laboratory measurements, which have been carried out in the Bistatic Measurement Facility at the DLR Oberpfaffenhofen, Microwaves and Radar Institute in Germany. The bistatic geometry enables us to have interferometric pairs with different baseline and different soil moistures controlled by a TDR (Time Domain Reflectivity) system. After calibration of the measuring system using a large metal plate, the sensitivity of phase and reflectivity with regard to moisture variation and therefore the penetration depth was evaluated. The effect of the surface roughness has been also reported. Current results demonstrate a non-linear relationship between the signal phase and the soil moisture, as expected, confirming the possibility of using DInSAR to measure variations in soil moisture.
A mechanistic model for the prediction of in-use moisture uptake by packaged dosage forms.
Remmelgas, Johan; Simonutti, Anne-Laure; Ronkvist, Asa; Gradinarsky, Lubomir; Löfgren, Anders
2013-01-30
A mechanistic model for the prediction of in-use moisture uptake of solid dosage forms in bottles is developed. The model considers moisture transport into the bottle and moisture uptake by the dosage form both when the bottle is closed and when it is open. Experiments are carried out by placing tablets and desiccant canisters in bottles and monitoring their moisture content. Each bottle is opened once a day to remove one tablet or desiccant canister. Opening the bottle to remove a tablet or canister also causes some exchange of air between the bottle headspace and the environment. In order to ascertain how this air exchange might depend on the customer, tablets and desiccant canisters are removed from the bottles by either carefully removing only one or by pouring all of the tablets or desiccant canisters out of the bottle, removing one, and pouring the remaining ones back into the bottle. The predictions of the model are found to be in good agreement with experimental data for moisture sorption by desiccant canisters. Moreover, it is found experimentally that the manner in which the tablets or desiccant canisters were removed does not appreciably affect their moisture content. Copyright © 2012 Elsevier B.V. All rights reserved.
NASA Technical Reports Server (NTRS)
Jones, Jeffrey A.; Hoffman, Ronald B.; Harvey, C. M.; Bowen, C. K.; Hudy, C. E.; Gernhardt, M. L.
2007-01-01
During Neutral Buoyancy Lab (NBL) training sessions, a large amount of moisture accumulates in the EVA gloves. The glove design restricts the extension of the EVA suit s ventilation/cooling system to the hand. Subungual redness and fingernail pain develops for many astronauts following their NBL training sessions with subsequent oncholysis occurring over succeeding weeks. Various attempts have been made to reduce or avoid this problem. The causal role of moisture has yet to be defined. Methods: To determine the contribution that moisture plays in the injury to the fingers and fingernails during EVA training operations in NBL, the current Extravehicular Mobility Unit (EMU), with a Portable Life Support System (PLSS) was configured with a ventilation tube that extended down a single arm of the crewmember during the test and compared with the unventilated contralateral arm; with the ventilated hand serving as the experimental condition (E) and the opposite arm as the control (C). A cross-over design was used with opposite handedness for the vent tube on a subsequent NBL training run. Moisture content measures were conducted at six points on each hand with three types of moisture meters. A questionnaire was administered to determine subjective thermal hand discomfort, skin moisture perception, and hand and nail discomfort. Photographs and video were recorded. Measures were applied to six astronauts pre- and post-run in the NBL. Results: The consistent trends in relative hydration ratios at the dorsum, from 3.34 for C to 2.11 for E, and first ring finger joint locations, from 2.46 for C to 1.96 for E, indicated the extended vent tube promoted skin drying. The experimental treatment appeared to be more effective on the left hand versus the right hand, implying an interaction with hand anthropometry and glove fit. Video analyses differentiated fine and gross motor training tasks during runs and will be discussed. Conclusions: This potential countermeasure was effective in reducing the risks of hand and nail discomfort symptoms from moderate to low in two of six subjects. Improved design in the ventilation pattern of such a countermeasure is expected to improve the countermeasure s efficiency.
Portable Dew Point Mass Spectrometry System for Real-Time Gas and Moisture Analysis
NASA Technical Reports Server (NTRS)
Arkin, C.; Gillespie, Stacey; Ratzel, Christopher
2010-01-01
A portable instrument incorporates both mass spectrometry and dew point measurement to provide real-time, quantitative gas measurements of helium, nitrogen, oxygen, argon, and carbon dioxide, along with real-time, quantitative moisture analysis. The Portable Dew Point Mass Spectrometry (PDP-MS) system comprises a single quadrupole mass spectrometer and a high vacuum system consisting of a turbopump and a diaphragm-backing pump. A capacitive membrane dew point sensor was placed upstream of the MS, but still within the pressure-flow control pneumatic region. Pressure-flow control was achieved with an upstream precision metering valve, a capacitance diaphragm gauge, and a downstream mass flow controller. User configurable LabVIEW software was developed to provide real-time concentration data for the MS, dew point monitor, and sample delivery system pressure control, pressure and flow monitoring, and recording. The system has been designed to include in situ, NIST-traceable calibration. Certain sample tubing retains sufficient water that even if the sample is dry, the sample tube will desorb water to an amount resulting in moisture concentration errors up to 500 ppm for as long as 10 minutes. It was determined that Bev-A-Line IV was the best sample line to use. As a result of this issue, it is prudent to add a high-level humidity sensor to PDP-MS so such events can be prevented in the future.
NASA Technical Reports Server (NTRS)
Reichle, Rolf H.; Liu, Qing; Bindlish, Rajat; Cosh, Michael H.; Crow, Wade T.; deJeu, Richard; DeLannoy, Gabrielle J. M.; Huffman, George J.; Jackson, Thomas J.
2011-01-01
The contributions of precipitation and soil moisture observations to the skill of soil moisture estimates from a land data assimilation system are assessed. Relative to baseline estimates from the Modern Era Retrospective-analysis for Research and Applications (MERRA), the study investigates soil moisture skill derived from (i) model forcing corrections based on large-scale, gauge- and satellite-based precipitation observations and (ii) assimilation of surface soil moisture retrievals from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E). Soil moisture skill is measured against in situ observations in the continental United States at 44 single-profile sites within the Soil Climate Analysis Network (SCAN) for which skillful AMSR-E retrievals are available and at four CalVal watersheds with high-quality distributed sensor networks that measure soil moisture at the scale of land model and satellite estimates. The average skill (in terms of the anomaly time series correlation coefficient R) of AMSR-E retrievals is R=0.39 versus SCAN and R=0.53 versus CalVal measurements. The skill of MERRA surface and root-zone soil moisture is R=0.42 and R=0.46, respectively, versus SCAN measurements, and MERRA surface moisture skill is R=0.56 versus CalVal measurements. Adding information from either precipitation observations or soil moisture retrievals increases surface soil moisture skill levels by IDDeltaR=0.06-0.08, and root zone soil moisture skill levels by DeltaR=0.05-0.07. Adding information from both sources increases surface soil moisture skill levels by DeltaR=0.13, and root zone soil moisture skill by DeltaR=0.11, demonstrating that precipitation corrections and assimilation of satellite soil moisture retrievals contribute similar and largely independent amounts of information.
NASA Astrophysics Data System (ADS)
McNally, Amy L.
Agricultural drought is characterized by shortages in precipitation, large differences between actual and potential evapotranspiration, and soil water deficits that impact crop growth and pasture productivity. Rainfall and other agrometeorological gauge networks in Sub-Saharan Africa are inadequate for drought early warning systems and hence, satellite-based estimates of rainfall and vegetation greenness provide the main sources of information. While a number of studies have described the empirical relationship between rainfall and vegetation greenness, these studies lack a process based approach that includes soil moisture storage. In Chapters I and II, I modeled soil moisture using satellite rainfall inputs and developed a new method for estimating soil moisture with NDVI calibrated to in situ and microwave soil moisture observations. By transforming both NDVI and rainfall into estimates of soil moisture I was able to easily compare these two datasets in a physically meaningful way. In Chapter II, I also show how the new NDVI derived soil moisture can be assimilated into a water balance model that calculates an index of crop water stress. Compared to the analogous rainfall derived estimates of soil moisture and crop stress the NDVI derived estimates were better correlated with millet yields. In Chapter III, I developed a metric for defining growing season drought events that negatively impact millet yields. This metric is based on the data and models used in the Chapters I and II. I then use this metric to evaluate the ability of a sophisticated land surface model to detect drought events. The analysis showed that this particular land surface model's soil moisture estimates do have the potential to benefit the food security and drought early warning communities. With a focus on soil moisture, this dissertation introduced new methods that utilized a variety of data and models for agricultural drought monitoring applications. These new methods facilitate a more quantitative, transparent `convergence of evidence' approach to identifying agricultural drought events that lead to food insecurity. Ideally, these new methods will contribute to better famine early warning and the timely delivery of food aid to reduce the human suffering caused by drought.
NASA Technical Reports Server (NTRS)
McKay, Christopher P.; Friedmann, E. Imre; Gomez-Silva, Benito; Caceres-Villanueva, Luis; Andersen, Dale T.; Landheim, Ragnhild
2003-01-01
The Atacama along the Pacific Coast of Chile and Peru is one of the driest and possibly oldest deserts in the world. It represents an extreme habitat for life on Earth and is an analog for life in dry conditions on Mars. We report on four years (September 1994-October 1998) of climate and moisture data from the extreme arid region of the Atacama. Our data are focused on understanding moisture sources and their role in creating suitable environments for photosynthetic microorganisms in the desert surface. The average air temperature was 16.5 degrees C and 16.6 degrees C in 1995 and 1996, respectively. The maximum air temperature recorded was 37.9 degrees C, and the minimum was -5.7 degrees C. Annual average sunlight was 336 and 335 W m(-2) in 1995 and 1996, respectively. Winds averaged a few meters per second, with strong fohn winds coming from the west exceeding 12 m s(-1). During our 4 years of observation there was only one significant rain event of 2.3 mm, which occurred near midnight local time. We suggest that this event was a rainout of a heavy fog. It is of interest that the strong El Nino of 1997-1998 brought heavy rainfall to the deserts of Peru, but did not bring significant rain to the central Atacama in Chile. Dew occurred at our station frequently following high nighttime relative humidity, but is not a significant source of moisture in the soil or under stones. Groundwater also does not contribute to surface moisture. Only the one rain event of 2.3 mm resulted in liquid water in the soil and beneath stones for a total of only 65-85 h over 4 years. The paucity of liquid water under stones is consistent with the apparent absence of hypolithic (under-stone) cyanobacteria, the only known primary producers in such extreme deserts.
NASA Astrophysics Data System (ADS)
Inmaculada Martínez Garrido, María; Gómez Heras, Miguel; Fort González, Rafael; Valles Iriso, Javier; José Varas Muriel, María
2015-04-01
This work presents a case study developed in San Juan Bautista church in Talamanca de Jarama (12th -16th Century), which have been selected as an example of a historical church with a complex construction with subsequent combination of architectural styles and building techniques and materials. These materials have a differential behavior under the influence of external climatic conditions and constructive facts. Many decay processes related to humidity are affecting the building's walls and also have influence in the environmental dynamics inside the building. A methodology for monitoring moisture distribution on stone and masonry walls and floors was performed with different non-invasive techniques as thermal imaging, wireless sensor networks (WSN), portable moisture meter, electrical resistivity tomography (ERT) and ground-penetrating radar (GPR), in order to the evaluate the effectiveness of these techniques for the knowledge of moisture distribution inside the walls and the humidity origin. North and south oriented sections, both on walls and floors, were evaluated and also a general inspection in the church was carried out with different non-invasive techniques. This methodology implies different monitoring stages for a complete knowledge of the implication of outdoors and indoors conditions on the moisture distribution. Each technique is evaluated according to its effectiveness in the detection of decay processes and maintenance costs. Research funded by Geomateriales (S2013/MIT-2914) and Deterioration of stone materials in the interior of historic buildings as a result induced variation of its microclimate (CGL2011-27902) projects. The cooperation received from the Complutense University of Madrid's Research Group Alteración y Conservación de los Materiales Pétreos del Patrimonio (ref. 921349), the Laboratory Network in Science and Technology for Heritage Conservation (RedLabPat, CEI Moncloa) and the Diocese of Alcalá is gratefully acknowledged. MI Martínez-Garrido and M. Gomez-Heras are funded by Moncloa Campus of International Excellence (UPM-UCM, CSIC) PICATA fellowships.
NASA Astrophysics Data System (ADS)
Zhao, M.; A, G.; Velicogna, I.; Kimball, J. S.
2016-12-01
Drought is one of the major drivers of the reduction in terrestrial ecosystem productivity. Ecosystem productivity may not primarily be driven by present moisture conditions. Instead, earlier drought conditions may have the largest impact on vegetation growth. We investigate this time-lag effect in Australia by comparing MODIS NDVI data with multiple drought metrics that are sensitive to water deficits at different soil depths. These metrics include 1) soil moisture (SM) from microwave satellite-retrievals that is sensitive to top-centimeter SM variations; 2) the Palmer drought severity index (PDSI) which is sensitive to atmosphere moisture demand and shallow-depth ( 1 meter) SM changes; 3) the newly developed GRACE drought severity index (GRACE-DSI) that is sensitive to changes in overall terrestrial water storage component of the hydrologic cycle and complements satellite SM observations and the PDSI by providing information about deep groundwater storage changes. We quantify the temporal lags between NDVI and these drought metrics during 2002-2014. We find that the NDVI closely evolves with the GRACE-DSI but lags 1-3 months behind the PDSI and satellite-retrievals of SM in western Australia. This pattern however is reverse in eastern Australia. These contrasting NDVI response patterns indicate that vegetation in western Australia is more sensitive to water storage in relatively deeper soil depths than vegetation in the east. This suggests that, in western Australia, vegetation might experience a protracted recovery period after extreme drought since, usually, moisture recharge in deeper soil depths takes a relatively longer period. We conclude that the time-lag effect in Australia is associated with the relative depth of SM to which vegetation is most sensitive. We suggest that characterizing the relative vegetation moisture sensitive depth at the global scale is important for understanding the nature and pace of terrestrial ecosystem recovery from extreme drought events under the background of global climate change.
Modelling of Space-Time Soil Moisture in Savannas and its Relation to Vegetation Patterns
NASA Astrophysics Data System (ADS)
Rodriguez-Iturbe, I.; Mohanty, B.; Chen, Z.
2017-12-01
A physically derived space-time representation of the soil moisture field is presented. It includes the incorporation of a "jitter" process acting over the space-time soil moisture field and accounting for the short distance heterogeneities in topography, soil, and vegetation characteristics. The modelling scheme allows for the representation of spatial random fluctuations of soil moisture at small spatial scales and reproduces quite well the space-time correlation structure of soil moisture from a field study in Oklahoma. It is shown that the islands of soil moisture above different thresholds have sizes which follow power distributions over an extended range of scales. A discussion is provided about the possible links of this feature with the observed power law distributions of the clusters of trees in savannas.
NASA Technical Reports Server (NTRS)
Vandegriend, A. A.; Oneill, P. E.
1986-01-01
Using the De Vries models for thermal conductivity and heat capacity, thermal inertia was determined as a function of soil moisture for 12 classes of soil types ranging from sand to clay. A coupled heat and moisture balance model was used to describe the thermal behavior of the top soil, while microwave remote sensing was used to estimate the soil moisture content of the same top soil. Soil hydraulic parameters are found to be very highly correlated with the combination of soil moisture content and thermal inertia at the same moisture content. Therefore, a remotely sensed estimate of the thermal behavior of the soil from diurnal soil temperature observations and an independent remotely sensed estimate of soil moisture content gives the possibility of estimating soil hydraulic properties by remote sensing.
Evaluation of Crops Moisture Provision by Space Remote Sensing Data
NASA Astrophysics Data System (ADS)
Ilienko, Tetiana
2016-08-01
The article is focused on theoretical and experimental rationale for the use of space data to determine the moisture provision of agricultural landscapes and agricultural plants. The improvement of space remote sensing methods to evaluate plant moisture availability is the aim of this research.It was proved the possibility of replacement of satellite imagery of high spatial resolution on medium spatial resolution which are freely available to determine crop moisture content at the local level. The mathematical models to determine the moisture content of winter wheat plants by spectral indices were developed based on the results of experimental field research and satellite (Landsat, MODIS/Terra, RapidEye, SICH-2) data. The maps of the moisture content in winter wheat plants in test sites by obtained models were constructed using modern GIS technology.
The COsmic-ray Soil Moisture Interaction Code (COSMIC) for use in data assimilation
NASA Astrophysics Data System (ADS)
Shuttleworth, J.; Rosolem, R.; Zreda, M.; Franz, T.
2013-08-01
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 model at the Santa Rita Experimental Range field site, the calibrated COSMIC model provided an effective mechanism for translating model-calculated soil moisture profiles into aboveground fast-neutron count when applied with two radically different approaches used to remove the bias between data and model.
Investigation of remote sensing techniques of measuring soil moisture
NASA Technical Reports Server (NTRS)
Newton, R. W. (Principal Investigator); Blanchard, A. J.; Nieber, J. L.; Lascano, R.; Tsang, L.; Vanbavel, C. H. M.
1981-01-01
Major activities described include development and evaluation of theoretical models that describe both active and passive microwave sensing of soil moisture, the evaluation of these models for their applicability, the execution of a controlled field experiment during which passive microwave measurements were acquired to validate these models, and evaluation of previously acquired aircraft microwave measurements. The development of a root zone soil water and soil temperature profile model and the calibration and evaluation of gamma ray attenuation probes for measuring soil moisture profiles are considered. The analysis of spatial variability of soil information as related to remote sensing is discussed as well as the implementation of an instrumented field site for acquisition of soil moisture and meteorologic information for use in validating the soil water profile and soil temperature profile models.
Interactions between drought and soil biogeochemistry: scaling from molecules to meters
NASA Astrophysics Data System (ADS)
Schimel, J.; Schaeffer, S. M.
2011-12-01
Water is the perhaps the single most critical resource for life, yet most terrestrial ecosystems experience regular drought. Reduced water potential causes physiological stress; reduced diffusion limits resource availability when microbes may need resources to acclimate. Most biogeochemical models, however, have assumed that soil processes either slow down or stop during drought. But organisms survive and enzymes remain viable. In California, as soils stay dry through the long summer drought, microbial biomass actually increases and pools of extractable organic C increase, probably because extracellular enzymes continue to break down plant detritus (notably roots). Yet 14C suggests that in deeper soils, the pulse of C released on rewetting comes from pools with turnover times of as long as 800 years. What are the mechanisms that regulate these complex dynamics? They appear to involve differential moisture sensitivity for the activity of extracellular enzymes, substrate diffusion, and microbial metabolism. Rewetting not only redistributes materials made available during the drought, but it also disrupts aggregates and may make previously-protected substrates available as well. We have used several methods to simply capture these linkages between water and carbon in models that are applicable at the ecosystem scale and that could improve our ability to model biogeochemical cycles in arid and semi-arid ecosystems. One is a simple empirical modification to the DAYCENT model while the other is a mechanistic model that incorporates microbial dry-season processes.
NASA Astrophysics Data System (ADS)
Rajesh, P. V.; Pattnaik, S.; Mohanty, U. C.; Rai, D.; Baisya, H.; Pandey, P. C.
2017-12-01
Monsoon depressions (MDs) constitute a large fraction of the total rainfall during the Indian summer monsoon season. In this study, the impact of high-resolution land state is addressed by assessing the evolution of inland moving depressions formed over the Bay of Bengal using a mesoscale modeling system. Improved land state is generated using High Resolution Land Data Assimilation System employing Noah-MP land-surface model. Verification of soil moisture using Soil Moisture and Ocean Salinity (SMOS) and soil temperature using tower observations demonstrate promising results. Incorporating high-resolution land state yielded least root mean squared errors with higher correlation coefficient in the surface and mid tropospheric parameters. Rainfall forecasts reveal that simulations are spatially and quantitatively in accordance with observations and provide better skill scores. The improved land surface characteristics have brought about the realistic evolution of surface, mid-tropospheric parameters, vorticity and moist static energy that facilitates the accurate MDs dynamics in the model. Composite moisture budget analysis reveals that the surface evaporation is negligible compared to moisture flux convergence of water vapor, which supplies moisture into the MDs over land. The temporal relationship between rainfall and moisture convergence show high correlation, suggesting a realistic representation of land state help restructure the moisture inflow into the system through rainfall-moisture convergence feedback.
NASA Technical Reports Server (NTRS)
Spar, J.; Cohen, C.
1981-01-01
The effects of terrain elevation, soil moisture, and zonal variations in sea/surface temperature on the mean daily precipitation rates over Australia, Africa, and South America in January were evaluated. It is suggested that evaporation of soil moisture may either increase or decrease the model generated precipitation, depending on the surface albedo. It was found that a flat, dry continent model best simulates the January rainfall over Australia and South America, while over Africa the simulation is improved by the inclusion of surface physics, specifically soil moisture and albedo variations.
Automatic pattern identification of rock moisture based on the Staff-RF model
NASA Astrophysics Data System (ADS)
Zheng, Wei; Tao, Kai; Jiang, Wei
2018-04-01
Studies on the moisture and damage state of rocks generally focus on the qualitative description and mechanical information of rocks. This method is not applicable to the real-time safety monitoring of rock mass. In this study, a musical staff computing model is used to quantify the acoustic emission signals of rocks with different moisture patterns. Then, the random forest (RF) method is adopted to form the staff-RF model for the real-time pattern identification of rock moisture. The entire process requires only the computing information of the AE signal and does not require the mechanical conditions of rocks.
Agero, Anna Liza C; Verallo-Rowell, Vermén M
2004-09-01
Xerosis is a common skin condition (1) characterized by dry, rough, scaly, and itchy skin, (2) associated with a defect in skin barrier function, and (3) treated with moisturizers. People in the tropics have effectively used coconut oil as a traditional moisturizer for centuries. Recently, the oil also has been shown to have skin antiseptic effects. A moisturizer with antiseptic effects has value, but there are no clinical studies to document the efficacy and safety of coconut oil as a skin moisturizer. This study aimed to determine the effectivity and safety of virgin coconut oil compared with mineral oil as a therapeutic moisturizer for mild to moderate xerosis. A randomized double-blind controlled clinical trial was conducted on mild to moderate xerosis in 34 patients with negative patch-test reactions to the test products. These patients were randomized to apply either coconut oil or mineral oil on the legs twice a day for 2 weeks. Quantitative outcome parameters for effectivity were measured at baseline and on each visit with a Corneometer CM825 to measure skin hydration and a Sebumeter SM 810 to measure skin lipids. For safety, transepidermal water loss (TEWL) was measured with a Tewameter TM210, and skin surface hydrogen ion concentration (pH) was measured with a Skin pH Meter PH900. Patients and the investigator separately evaluated, at baseline and at each weekly visit, skin symptoms of dryness, scaling, roughness, and pruritus by using a visual analogue scale and grading of xerosis. Coconut oil and mineral oil have comparable effects. Both oils showed effectivity through significant improvement in skin hydration and increase in skin surface lipid levels. Safety was demonstrated through no significant difference in TEWL and skin pH. Subjective grading of xerosis by the investigators and visual analogue scales used by the patients showed a general trend toward better (though not statistically evident) improvement with coconut oil than with mineral oil. Safety for both was further demonstrated by negative patch-test results prior to the study and by the absence of adverse reactions during the study. Coconut oil is as effective and safe as mineral oil when used as a moisturizer.
NASA Astrophysics Data System (ADS)
Tawfik, Ahmed B.
The atmospheric component is described by rapid fluctuations in typical state variables, such as temperature and water vapor, on timescales of hours to days and the land component evolves on daily to yearly timescales. This dissertation examines the connection between soil moisture and atmospheric tracers under varying degrees of soil moisture-atmosphere coupling. Land-atmosphere coupling is defined over the United States using a regional climate model. A newly examined soil moisture-precipitation feedback is identified for winter months extending the previous summer feedback to colder temperature climates. This feedback is driven by the freezing and thawing of soil moisture, leading to coupled land-atmosphere conditions near the freezing line. Soil moisture can also affect the composition of the troposphere through modifying biogenic emissions of isoprene (C5H8). A novel first-order Taylor series decomposition indicates that isoprene emissions are jointly driven by temperature and soil moisture in models. These compounds are important precursors for ozone formation, an air pollutant and a short-lived forcing agent for climate. A mechanistic description of commonly observed relationships between ground-level ozone and meteorology is presented using the concept of soil moisture-temperature coupling regimes. The extent of surface drying was found to be a better predictor of ozone concentrations than temperature or humidity for the Eastern U.S. This relationship is evaluated in a coupled regional chemistry-climate model under several land-atmosphere coupling and isoprene emissions cases. The coupled chemistry-climate model can reproduce the observed soil moisture-temperature coupling pattern, yet modeled ozone is insensitive to changes in meteorology due to the balance between isoprene and the primary atmospheric oxidant, the hydroxyl radical (OH). Overall, this work highlights the importance of soil moisture-atmosphere coupling for previously neglected cold climate regimes, controlling isoprene emissions variability, and providing a processed-based description of observed ozone-meteorology relationships. From the perspective of ozone air quality, the lack of sensitivity of ozone to meteorology suggests a systematic deficiency in chemistry models in high isoprene emission regions. This shortcoming must be addressed to better estimate tropospheric ozone radiative forcing and to understanding how ozone air quality may respond to future warming.
NASA Astrophysics Data System (ADS)
Mishra, V.; Cruise, J.; Mecikalski, J. R.
2012-12-01
Soil Moisture is a key component in the hydrological process, affects surface and boundary layer energy fluxes and is the driving factor in agricultural production. Multiple in situ soil moisture measuring instruments such as Time-domain Reflectrometry (TDR), Nuclear Probes etc. are in use along with remote sensing methods like Active and Passive Microwave (PM) sensors. In situ measurements, despite being more accurate, can only be obtained at discrete points over small spatial scales. Remote sensing estimates, on the other hand, can be obtained over larger spatial domains with varying spatial and temporal resolutions. Soil moisture profiles derived from satellite based thermal infrared (TIR) imagery can overcome many of the problems associated with laborious in-situ observations over large spatial domains. An area where soil moisture observation and assimilation is receiving increasing attention is agricultural crop modeling. This study revolves around the use of the Decision Support System for Agrotechnology Transfer (DSSAT) crop model to simulate corn yields under various forcing scenarios. First, the model was run and calibrated using observed precipitation and model generated soil moisture dynamics. Next, the modeled soil moisture was updated using estimates derived from satellite based TIR imagery and the Atmospheric Land Exchange Inverse (ALEXI) model. We selected three climatically different locations to test the concept. Test Locations were selected to represent varied climatology. Bell Mina, Alabama - South Eastern United States, representing humid subtropical climate. Nabb, Indiana - Mid Western United States, representing humid continental climate. Lubbok, Texas - Southern United States, representing semiarid steppe climate. A temporal (2000-2009) correlation analysis of the soil moisture values from both DSSAT and ALEXI were performed and validated against the Land Information System (LIS) soil moisture dataset. The results clearly show strong correlation (R = 73%) between ALEXI and DSSAT at Bell Mina. At Nabb and Lubbock the correlation was 50-60%. Further, multiple experiments were conducted for each location: a) a DSSAT rain-fed 10 year sequential run forced with daymet precipitation; b) a DSSAT sequential run with no precipitation data; and c) a DSSAT run forced with ALEXI soil moisture estimates alone. The preliminary results of all the experiments are quantified through soil moisture correlations and yield comparisons. In general, the preliminary results strongly suggest that DSSAT forced with ALEXI can provide significant information especially at locations where no significant precipitation data exists.
USDA-ARS?s Scientific Manuscript database
Soil moisture measurements are required to improve our understanding of hydrological processes, ecosystem functions, and linkages between the Earth’s water, energy, and carbon cycles. The efficient retrieval of soil moisture depends on various factors in which soil dielectric mixing models are consi...
Estimating error cross-correlations in soil moisture data sets using extended collocation analysis
USDA-ARS?s Scientific Manuscript database
Consistent global soil moisture records are essential for studying the role of hydrologic processes within the larger earth system. Various studies have shown the benefit of assimilating satellite-based soil moisture data into water balance models or merging multi-source soil moisture retrievals int...
Applicability of common stomatal conductance models in maize under varying soil moisture conditions.
Wang, Qiuling; He, Qijin; Zhou, Guangsheng
2018-07-01
In the context of climate warming, the varying soil moisture caused by precipitation pattern change will affect the applicability of stomatal conductance models, thereby affecting the simulation accuracy of carbon-nitrogen-water cycles in ecosystems. We studied the applicability of four common stomatal conductance models including Jarvis, Ball-Woodrow-Berry (BWB), Ball-Berry-Leuning (BBL) and unified stomatal optimization (USO) models based on summer maize leaf gas exchange data from a soil moisture consecutive decrease manipulation experiment. The results showed that the USO model performed best, followed by the BBL model, BWB model, and the Jarvis model performed worst under varying soil moisture conditions. The effects of soil moisture made a difference in the relative performance among the models. By introducing a water response function, the performance of the Jarvis, BWB, and USO models improved, which decreased the normalized root mean square error (NRMSE) by 15.7%, 16.6% and 3.9%, respectively; however, the performance of the BBL model was negative, which increased the NRMSE by 5.3%. It was observed that the models of Jarvis, BWB, BBL and USO were applicable within different ranges of soil relative water content (i.e., 55%-65%, 56%-67%, 37%-79% and 37%-95%, respectively) based on the 95% confidence limits. Moreover, introducing a water response function, the applicability of the Jarvis and BWB models improved. The USO model performed best with or without introducing the water response function and was applicable under varying soil moisture conditions. Our results provide a basis for selecting appropriate stomatal conductance models under drought conditions. Copyright © 2018 Elsevier B.V. All rights reserved.
Lorenz, Ruth; Argueso, Daniel; Donat, Markus G.; Pitman, Andrew J.; van den Hurk, Bart; Berg, Alexis; Lawrence, David M.; Cheruy, Frederique; Ducharne, Agnes; Hagemann, Stefan; Meier, Arndt; Milly, Paul C.D.; Seneviratne, Sonia I
2016-01-01
We examine how soil moisture variability and trends affect the simulation of temperature and precipitation extremes in six global climate models using the experimental protocol of the Global Land-Atmosphere Coupling Experiment of the Coupled Model Intercomparison Project, Phase 5 (GLACE-CMIP5). This protocol enables separate examinations of the influences of soil moisture variability and trends on the intensity, frequency, and duration of climate extremes by the end of the 21st century under a business-as-usual (Representative Concentration Pathway 8.5) emission scenario. Removing soil moisture variability significantly reduces temperature extremes over most continental surfaces, while wet precipitation extremes are enhanced in the tropics. Projected drying trends in soil moisture lead to increases in intensity, frequency, and duration of temperature extremes by the end of the 21st century. Wet precipitation extremes are decreased in the tropics with soil moisture trends in the simulations, while dry extremes are enhanced in some regions, in particular the Mediterranean and Australia. However, the ensemble results mask considerable differences in the soil moisture trends simulated by the six climate models. We find that the large differences between the models in soil moisture trends, which are related to an unknown combination of differences in atmospheric forcing (precipitation, net radiation), flux partitioning at the land surface, and how soil moisture is parameterized, imply considerable uncertainty in future changes in climate extremes.
NASA Astrophysics Data System (ADS)
Qi, J.; Markewitz, D.; Radcliffe, D. E.
2016-12-01
Forests in the southeastern U.S. are predicted to experience a moderate decrease in water availability that will result in soil water deficiency during the growing season. The potential impact of drier climate on the productivity of managed loblolly pine plantations in the Southeast US is uncertain. Access to water reserves in deep soil during drought periods helps the forest buffer the effects of water deficits. To better understand the potential impact of drought on deep soil hydrology, we studied the combined effects of throughfall reduction and soil fertility on soil hydrology to the depth of 3 m in a 10-year-old loblolly pine plantation by applying a throughfall reduction treatment (ambient versus 30% throughfall reduction) and a fertilization treatment (no fertilization versus fertilization). Fertilization lowered soil moisture for all depths and differences were significant at 30-60 cm and 300 cm. Throughfall reduction also lowered soil moisture for all depths and differences were significant in the surface soils (0-30 cm) and deep soils (below 2m). Fertilization significantly decreased 10-90 cm soil water when combined with throughfall reduction treatment. HYDRUS 1-D model was used to simulate changes in the vertical distribution of soil water and to enhance our understanding of hydrologic processes. The model was accurately calibrated using 914 days of data under ambient rainfall (R2=0.84 and RMSE = 0.04). Using data under throughfall reduction treatment, the model validation showed R2=0.67 and RMSE = 0.04, suggesting that this model captures the hydrological processes of this study site. The difference in the rates of simulated cumulative actual evapotranspiration between ambient and throughfall reduction were only 10%; however, water yield as lower boundary flux decreased 64%. These empirical and simulated results suggested that when evapotranspiration exceeded precipitation, the soil water in the upper 90 cm did not satisfy the demand for AET, soil below 90 cm constantly contribute to plant water uptake. With 30% less throughfall, the water in the 3 meter soil profile can satisfy the demand of evapotranspiration before water yield.
Spatial and temporal variability of soil moisture on the field with and without plants*
NASA Astrophysics Data System (ADS)
Usowicz, B.; Marczewski, W.; Usowicz, J. B.
2012-04-01
Spatial and temporal variability of the natural environment is its inherent and unavoidable feature. Every element of the environment is characterized by its own variability. One of the kinds of variability in the natural environment is the variability of the soil environment. To acquire better and deeper knowledge and understanding of the temporal and spatial variability of the physical, chemical and biological features of the soil environment, we should determine the causes that induce a given variability. Relatively stable features of soil include its texture and mineral composition; examples of those variables in time are the soil pH or organic matter content; an example of a feature with strong dynamics is the soil temperature and moisture content. The aim of this study was to identify the variability of soil moisture on the field with and without plants using geostatistical methods. The soil moisture measurements were taken on the object with plant canopy and without plants (as reference). The measurements of soil moisture and meteorological components were taken within the period of April-July. The TDR moisture sensors covered 5 cm soil layers and were installed in the plots in the soil layers of 0-0.05, 0.05-0.1, 0.1-0.15, 0.2-0.25, 0.3-0.35, 0.4-0.45, 0.5-0.55, 0.8-0.85 m. Measurements of soil moisture were taken once a day, in the afternoon hours. For the determination of reciprocal correlation, precipitation data and data from soil moisture measurements with the TDR meter were used. Calculations of reciprocal correlation of precipitation and soil moisture at various depths were made for three objects - spring barley, rye, and bare soil, at the level of significance of p<0.05. No significant reciprocal correlation was found between the precipitation and soil moisture in the soil profile for any of the objects studied. Although the correlation analysis indicates a lack of correlation between the variables under consideration, observation of the soil moisture runs in particular objects and of precipitation distribution shows clearly that rainfall has an effect on the soil moisture. The amount of precipitation water that increased the soil moisture depended on the strength of the rainfall, on the hydrological properties of the soil (primarily the soil density), the status of the plant cover, and surface runoff. Basing on the precipitation distribution and on the soil moisture runs, an attempt was made at finding a temporal and spatial relationship between those variables, employing for the purpose the geostatistical methods which permit time and space to be included in the analysis. The geostatistical parameters determined showed the temporal dependence of moisture distribution in the soil profile, with the autocorrelation radius increasing with increasing depth in the profile. The highest values of the radius were observed in the plots with plant cover below the arable horizon, and the lowest in the arable horizon on the barley and fallow plots. The fractal dimensions showed a clear decrease in values with increasing depth in the plots with plant cover, while in the bare plots they were relatively constant within the soil profile under study. Therefore, they indicated that the temporal distribution of soil moisture within the soil profile in the bare field was more random in character than in the plots with plants. The results obtained and the analyses indicate that the moisture in the soil profile, its variability and determination, are significantly affected by the type and condition of plant canopy. The differentiation in moisture content between the plots studied resulted from different precipitation interception and different intensity of water uptake by the roots. * The work was financially supported in part by the ESA Programme for European Cooperating States (PECS), No.98084 "SWEX-R, Soil Water and Energy Exchange/Research", AO-3275.
NASA Astrophysics Data System (ADS)
Swenson, S. C.; Lawrence, D. M.
2017-12-01
Partitioning the vertically integrated water storage variations estimated from GRACE satellite data into the components of which it is comprised requires independent information. Land surface models, which simulate the transfer and storage of moisture and energy at the land surface, are often used to estimate water storage variability of snow, surface water, and soil moisture. To obtain an estimate of changes in groundwater, the estimates of these storage components are removed from GRACE data. Biases in the modeled water storage components are therefore present in the residual groundwater estimate. In this study, we examine how soil moisture variability, estimated using the Community Land Model (CLM), depends on the vertical structure of the model. We then explore the implications of this uncertainty in the context of estimating groundwater variations using GRACE data.
NASA Astrophysics Data System (ADS)
Flores, Alejandro N.; Bras, Rafael L.; Entekhabi, Dara
2012-08-01
Soil moisture information is critical for applications like landslide susceptibility analysis and military trafficability assessment. Existing technologies cannot observe soil moisture at spatial scales of hillslopes (e.g., 100 to 102 m) and over large areas (e.g., 102 to 105 km2) with sufficiently high temporal coverage (e.g., days). Physics-based hydrologic models can simulate soil moisture at the necessary spatial and temporal scales, albeit with error. We develop and test a data assimilation framework based on the ensemble Kalman filter for constraining uncertain simulated high-resolution soil moisture fields to anticipated remote sensing products, specifically NASA's Soil Moisture Active-Passive (SMAP) mission, which will provide global L band microwave observation approximately every 2-3 days. The framework directly assimilates SMAP synthetic 3 km radar backscatter observations to update hillslope-scale bare soil moisture estimates from a physics-based model. Downscaling from 3 km observations to hillslope scales is achieved through the data assimilation algorithm. Assimilation reduces bias in near-surface soil moisture (e.g., top 10 cm) by approximately 0.05 m3/m3and expected root-mean-square errors by at least 60% in much of the watershed, relative to an open loop simulation. However, near-surface moisture estimates in channel and valley bottoms do not improve, and estimates of profile-integrated moisture throughout the watershed do not substantially improve. We discuss the implications of this work, focusing on ongoing efforts to improve soil moisture estimation in the entire soil profile through joint assimilation of other satellite (e.g., vegetation) and in situ soil moisture measurements.
NASA Astrophysics Data System (ADS)
Ruotsalainen, Hannu
2018-05-01
A modern third-generation interferometric water level tilt meter was developed at the Finnish Geodetic Institute in 2000. The tilt meter has absolute scale and can do high-precision tilt measurements on earth tides, ocean tide loading and atmospheric loading. Additionally, it can be applied in various kinds of geodynamic and geophysical research. The principles and results of the historical 100-year-old Michelson-Gale tilt meter, as well as the development of interferometric water tube tilt meters of the Finnish Geodetic Institute, Finland, are reviewed. Modern Earth tide model tilt combined with Schwiderski ocean tide loading model explains the uncertainty in historical tilt observations by Michelson and Gale. Earth tide tilt observations in Lohja2 geodynamic station, southern Finland, are compared with the combined model earth tide and four ocean tide loading models. The observed diurnal and semidiurnal harmonic constituents do not fit well with combined models. The reason could be a result of the improper harmonic modelling of the Baltic Sea tides in those models.
Land surface dynamics monitoring using microwave passive satellite sensors
NASA Astrophysics Data System (ADS)
Guijarro, Lizbeth Noemi
Soil moisture, surface temperature and vegetation are variables that play an important role in our environment. There is growing demand for accurate estimation of these geophysical parameters for the research of global climate models (GCMs), weather, hydrological and flooding models, and for the application to agricultural assessment, land cover change, and a wide variety of other uses that meet the needs for the study of our environment. The different studies covered in this dissertation evaluate the capabilities and limitations of microwave passive sensors to monitor land surface dynamics. The first study evaluates the 19 GHz channel of the SSM/I instrument with a radiative transfer model and in situ datasets from the Illinois stations and the Oklahoma Mesonet to retrieve land surface temperature and surface soil moisture. The surface temperatures were retrieved with an average error of 5 K and the soil moisture with an average error of 6%. The results show that the 19 GHz channel can be used to qualitatively predict the spatial and temporal variability of surface soil moisture and surface temperature at regional scales. In the second study, in situ observations were compared with sensor observations to evaluate aspects of low and high spatial resolution at multiple frequencies with data collected from the Southern Great Plains Experiment (SGP99). The results showed that the sensitivity to soil moisture at each frequency is a function of wavelength and amount of vegetation. The results confirmed that L-band is more optimal for soil moisture, but each sensor can provide soil moisture information if the vegetation water content is low. The spatial variability of the emissivities reveals that resolution suffers considerably at higher frequencies. The third study evaluates C- and X-bands of the AMSR-E instrument. In situ datasets from the Soil Moisture Experiments (SMEX03) in South Central Georgia were utilized to validate the AMSR-E soil moisture product and to derive surface soil moisture with a radiative transfer model. The soil moisture was retrieved with an average error of 2.7% at X-band and 6.7% at C-band. The AMSR-E demonstrated its ability to successfully infer soil moisture during the SMEX03 experiment.
NASA Astrophysics Data System (ADS)
Yoshida, N.; Oki, T.
2016-12-01
Appropriate initial condition of soil moisture and water table depth are important factors to reduce uncertainty in hydrological simulations. Approaches to determine the initial water table depth have been developed because of difficulty to get information on global water table depth and soil moisture distributions. However, how is equilibrium soil moisture determined by climate conditions? We try to discuss this issue by using land surface model with representation of water table dynamics (MAT-GW). First, the global pattern of water table depth at equilibrium soil moisture in MAT-GW was verified. The water table depth in MAT-GW was deeper than the previous one at fundamentally arid region because the negative recharge and continuous baseflow made water table depth deeper. It indicated that the hydraulic conductivity used for estimating recharge and baseflow need to be reassessed in MAT-GW. In soil physics field, it is revealed that proper hydraulic property models for water retention and unsaturated hydraulic conductivity should be selected for each soil type. So, the effect of selecting hydraulic property models on terrestrial soil moisture and water table depth were examined.Clapp and Hornburger equation(CH eq.) and Van Genuchten equation(VG eq.) were used as representative hydraulic property models. Those models were integrated on MAT-GW and equilibrium soil moisture and water table depth with using each model were compared. The water table depth and soil moisture at grids which reached equilibrium in both simulations were analyzed. The equilibrium water table depth were deeper in VG eq. than CH eq. in most grids due to shape of hydraulic property models. Then, total soil moisture were smaller in VG eq. than CH eq. at almost all grids which water table depth reached equilibrium. It is interesting that spatial patterns which water table depth reached equilibrium or not were basically similar in both simulations but reverse patterns were shown in east and west part of America. Selection of each hydraulic property model based on soil types may compensate characteristic of models in initialization.
NASA Technical Reports Server (NTRS)
Crosson, William L.; Laymon, Charles A.; Inguva, Ramarao; Schamschula, Marius; Caulfield, John
1998-01-01
Knowledge of the amount of water in the soil is of great importance to many earth science disciplines. Soil moisture is a key variable in controlling the exchange of water and energy between the land surface and the atmosphere. Thus, soil moisture information is valuable in a wide range of applications including weather and climate, runoff potential and flood control, early warning of droughts, irrigation, crop yield forecasting, soil erosion, reservoir management, geotechnical engineering, and water quality. Despite the importance of soil moisture information, widespread and continuous measurements of soil moisture are not possible today. Although many earth surface conditions can be measured from satellites, we still cannot adequately measure soil moisture from space. Research in soil moisture remote sensing began in the mid 1970s shortly after the surge in satellite development. Recent advances in remote sensing have shown that soil moisture can be measured, at least qualitatively, by several methods. Quantitative measurements of moisture in the soil surface layer have been most successful using both passive and active microwave remote sensing, although complications arise from surface roughness and vegetation type and density. Early attempts to measure soil moisture from space-borne microwave instruments were hindered by what is now considered sub-optimal wavelengths (shorter than 5 cm) and the coarse spatial resolution of the measurements. L-band frequencies between 1 and 3 GHz (10-30 cm) have been deemed optimal for detection of soil moisture in the upper few centimeters of soil. The Electronically Steered Thinned Array Radiometer (ESTAR), an aircraft-based instrument operating a 1,4 GHz, has shown great promise for soil moisture determination. Initiatives are underway to develop a similar instrument for space. Existing space-borne synthetic aperture radars (SARS) operating at C- and L-band have also shown some potential to detect surface wetness. The advantage of radar is its much higher resolution than passive microwave systems, but it is currently hampered by surface roughness effects and the lack of a good algorithm based on a single frequency and single polarization. In addition, its repeat frequency is generally low (about 40 days). In the meantime, two new radiometers offer some hope for remote sensing of soil moisture from space. The Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), launched in November 1997, possesses a 10.65 GHz channel and the Advanced Microwave Scanning Radiometer (AMSR) on both the ADEOS-11 and Earth Observing System AM-1 platforms to be launched in 1999 possesses a 6.9 GHz channel. Aside from issues about interference from vegetation, the coarse resolution of these data will provide considerable challenges pertaining to their application. The resolution of TMI is about 45 km and that of AMSR is about 70 km. These resolutions are grossly inconsistent with the scale of soil moisture processes and the spatial variability of factors that control soil moisture. Scale disparities such as these are forcing us to rethink how we assimilate data of various scales in hydrologic models. Of particular interest is how to assimilate soil moisture data by reconciling the scale disparity between what we can expect from present and future remote sensing measurements of soil moisture and modeling soil moisture processes. It is because of this disparity between the resolution of space-based sensors and the scale of data needed for capturing the spatial variability of soil moisture and related properties that remote sensing of soil moisture has not met with more widespread success. Within a single footprint of current sensors at the wavelengths optimal for this application, in most cases there is enormous heterogeneity in soil moisture created by differences in landcover, soils and topography, as well as variability in antecedent precipitation. It is difficult to interpret the meaning of 'mean' soil moisture under such conditions and even more difficult to apply such a value. Because of the non-linear relationships between near-surface soil moisture and other variables of interest, such as surface energy fluxes and runoff, mean soil moisture has little applicability at such large scales. It is for these reasons that the use of remote sensing in conjunction with a hydrologic model appears to be of benefit in capturing the complete spatial and temporal structure of soil moisture. This paper is Part I of a four-part series describing a method for intermittently assimilating remotely-sensed soil moisture information to improve performance of a distributed land surface hydrology model. The method, summarized in section II, involves the following components, each of which is detailed in the indicated section of the paper or subsequent papers in this series: Forward radiative transfer model methods (section II and Part IV); Use of a Kalman filter to assimilate remotely-sensed soil moisture estimates with the model profile (section II and Part IV); Application of a soil hydrology model to capture the continuous evolution of the soil moisture profile within and below the root zone (section III); Statistical aggregation techniques (section IV and Part II); Disaggregation techniques using a neural network approach (section IV and Part III); and Maximum likelihood and Bayesian algorithms for inversely solving for the soil moisture profile in the upper few cm (Part IV).
NASA Astrophysics Data System (ADS)
Mishra, V.; Cruise, J.; Mecikalski, J. R.
2017-12-01
Much effort has been expended recently on the assimilation of remotely sensed soil moisture into operational land surface models (LSM). These efforts have normally been focused on the use of data derived from the microwave bands and results have often shown that improvements to model simulations have been limited due to the fact that microwave signals only penetrate the top 2-5 cm of the soil surface. It is possible that model simulations could be further improved through the introduction of geostationary satellite thermal infrared (TIR) based root zone soil moisture in addition to the microwave deduced surface estimates. In this study, root zone soil moisture estimates from the TIR based Atmospheric Land Exchange Inverse (ALEXI) model were merged with NASA Soil Moisture Active Passive (SMAP) based surface estimates through the application of informational entropy. Entropy can be used to characterize the movement of moisture within the vadose zone and accounts for both advection and diffusion processes. The Principle of Maximum Entropy (POME) can be used to derive complete soil moisture profiles and, fortuitously, only requires a surface boundary condition as well as the overall mean moisture content of the soil column. A lower boundary can be considered a soil parameter or obtained from the LSM itself. In this study, SMAP provided the surface boundary while ALEXI supplied the mean and the entropy integral was used to tie the two together and produce the vertical profile. However, prior to the merging, the coarse resolution (9 km) SMAP data were downscaled to the finer resolution (4.7 km) ALEXI grid. The disaggregation scheme followed the Soil Evaporative Efficiency approach and again, all necessary inputs were available from the TIR model. The profiles were then assimilated into a standard agricultural crop model (Decision Support System for Agrotechnology, DSSAT) via the ensemble Kalman Filter. The study was conducted over the Southeastern United States for the growing seasons from 2015-2017. Soil moisture profiles compared favorably to in situ data and simulated crop yields compared well with observed yields.
Soil Moisture Sensing Using Reflected GPS Signals: Description of the GPS Soil Moisture Product.
NASA Astrophysics Data System (ADS)
Larson, Kristine; Small, Eric; Chew, Clara
2015-04-01
As first demonstrated by the GPS reflections group in 2008, data from GPS networks can be used to monitor multiple parameters of the terrestrial water cycle. The GPS L-band signals take two paths: (1) the "direct" signal travels from the satellite to the antenna, which is typically located 2-3 meters above the ground; (2) the reflected signal interacts with the Earth's surface before traveling to the antenna. The direct signal is used by geophysicists and surveyors to measure the position of the antenna, while the effects of reflected signals are a source of error. If one focuses on the reflected signal rather than the positioning observables, one has a method that is sensitive to surface soil moisture (top 5 cm), vegetation water content, and snow depth. This method - known as GPS Interferometric Reflectometry (GPS-IR) - has a footprint of ~1000 m2 for most GPS sites. This is intermediate in scale to most in situ and satellite observations. A significant advantage of GPS-IR is that data from existing GPS networks can be used without any changes to the instrumentation. This means that there is a new source of cost-effective instrumentation for satellite validation and climate studies. This presentation will provide an overview of the GPS-IR methodology with an emphasis on the soil moisture product. GPS water cycle products are currently produced on a daily basis for a network of ~500 sites in the western United States; results are freely available at http://xenon.colorado.edu/portal. Plans to expand the GPS-IR method to the network of international GPS sites will also be discussed.
Flexible Ultra Moisture Barrier Film for Thin-Film Photovoltaic Applications
DOE Office of Scientific and Technical Information (OSTI.GOV)
David M. Dean
2012-10-30
Flexible Thin-film photovoltaic (TFPV) is a low cost alternative to incumbent c-Si PV products as it requires less volume of costly semiconductor materials and it can potentially reduce installation cost. Among the TFPV options, copper indium gallium diselenide (CIGS) has the highest efficiency and is believed to be one of the most attractive candidates to achieve PV cost reduction. However, CIGS cells are very moisture sensitive and require module water vapor transmission rate (WVTR) of less than 1x10-4 gram of water per square meter per day (g-H2O/m2/day). Successful development and commercialization of flexible transparent ultra moisture barrier film is themore » key to enable flexible CIGS TFPV products, and thus enable ultimate PV cost reduction. At DuPont, we have demonstrated at lab scale that we can successfully make polymer-based flexible transparent ultra moisture barrier film by depositing alumina on polymer films using atomic layer deposition (ALD) technology. The layer by layer ALD approach results in uniform and amorphous structure which effectively reduces pinhole density of the inorganic coating on the polymer, and thus allow the fabrication of flexible barrier film with WVTR of 10-5 g-H2O/m2/day. Currently ALD is a time-consuming process suitable only for high-value, relatively small substrates. To successfully commercialize the ALD-on-plastic technology for the PV industry, there is the need to scale up this technology and improve throughput. The goal of this contract work was to build a prototype demonstrating that the ALD technology could be scaled-up for commercial use. Unfortunately, the prototype failed to produce an ultra-barrier film by the close of the project.« less
Noda, Yasuhiro; Saito, Mika; Watanabe, Kazuya; Sanagawa, Akimasa; Sobajima, Yu; Fujii, Satoshi
2013-01-01
Maintenance of proper moisture and regulation of infection are simultaneously required to promote healing of pressure ulcers. Continuous use of water-rich ointment may often lead to excess moisture and induce edematous granulation tissue. Use of water soluble ointment may excessively absorb exudates and induce dry granulation tissue. Selection of appropriate topical ointment is desired to avoid worse clinical outcomes. For adjustment of wound moisture a novel blended ointment (tretinoin tocoferil-povidone-iodine (TR-PI)) was developed consisting of emulsion base, tretinoin tocoferil oil-in-water (o/w) emulsion (TR-cream), and sugar base, povidone-iodine and sugar (PI-sugar). For the characterization of TR-PI water absorption was tested using Franz diffusion cell with cellulose membrane. For rheological characteristics spreadability was tested using spread meter and yield value was calculated. Iodine permeation was tested using a permeation cell with silicon membrane. Water absorption rate constant of TR-PI with combination ratio of PI-sugar at 75% (TR-PI75, 18.5 mg cm(-2) min(-0.5)) was equivalent to that of TR-cream alone (16.4 mg cm(-2) min(-0.5)). The yield value of TR-PI75 (26.1 Pa) exhibited intermediate values as compared to those of TR-PI with combination ratio of PI-sugar at 50% (11.3 Pa) and TR-cream alone (46.8 Pa). The amount of released free-iodine from TR-PI75 was similar to that released from PI-sugar alone. TR-PI75 may have superior performance in keeping the moist environment in wounds and in preventing infection. TR-PI75 can be used to promote formation of favorable granulation tissue in pressure ulcers with moderate exudates.
Harrow, Jeffrey John; Mayrovitz, Harvey N.
2014-01-01
Objective Characterization of a non-invasive method of quantifying subepidermal moisture (SEM) surrounding stages III and IV pressure ulcers (PrUs) in spinal cord injury (SCI). Design Prospective, single-visit, single-rater, observational study, using repeated-measures analysis. Method Setting-inpatient units of one VA SCI Center. Participants Convenience sample of 16 subjects with SCI with stage III or IV PrUs over sacrum or ischium. Interventions Measurement with the MoistureMeter-D, a hand-held device using 300 MHz electromagnetic waves. Outcome measures Dielectric constant, a dimensionless number which increases with the moisture content. Each subject had a PrU site and a control site. Measurements were made at each site, on intact skin, at four points spaced angularly around the site, in triplicate. Results (1) Short-term, single-rater relative error was 2.5%. (2) Order effect: first readings were higher than second readings in 55 of 64 measurement sets. Order effect was significant for control sites (P < 0.0001) but not for PrU sites. (3) Angular effect: SEM varied by angle at the PrU sites (P < 0.01); 12 o'clock position the highest and 6 o'clock the lowest. (4) Ability to differentiate PrUs from intact skin: SEM at PrU sites was greater by 9.0% than control sites (P < 0.05). (5) Site effect: SEM was higher at sacral locations than ischial at control sites by 20% (P < 0.005). Conclusions SEM differentiates PrUs from intact skin. Future study designs must take into account order, angular, and site effects on this measure. This information will inform designers of future studies of SEM in healing of PrUs. PMID:25398030
Remote Sensing of Soil Moisture: A Comparison of Optical and Thermal Methods
NASA Astrophysics Data System (ADS)
Foroughi, H.; Naseri, A. A.; Boroomandnasab, S.; Sadeghi, M.; Jones, S. B.; Tuller, M.; Babaeian, E.
2017-12-01
Recent technological advances in satellite and airborne remote sensing have provided new means for large-scale soil moisture monitoring. Traditional methods for soil moisture retrieval require thermal and optical RS observations. In this study we compared the traditional trapezoid model parameterized based on the land surface temperature - normalized difference vegetation index (LST-NDVI) space with the recently developed optical trapezoid model OPTRAM parameterized based on the shortwave infrared transformed reflectance (STR)-NDVI space for an extensive sugarcane field located in Southwestern Iran. Twelve Landsat-8 satellite images were acquired during the sugarcane growth season (April to October 2016). Reference in situ soil moisture data were obtained at 22 locations at different depths via core sampling and oven-drying. The obtained results indicate that the thermal/optical and optical prediction methods are comparable, both with volumetric moisture content estimation errors of about 0.04 cm3 cm-3. However, the OPTRAM model is more efficient because it does not require thermal data and can be universally parameterized for a specific location, because unlike the LST-soil moisture relationship, the reflectance-soil moisture relationship does not significantly vary with environmental variables (e.g., air temperature, wind speed, etc.).
NASA Technical Reports Server (NTRS)
Koster, Randal D.; Mahanama, P. P.
2012-01-01
Key to translating soil moisture memory into subseasonal precipitation and air temperature forecast skill is a realistic treatment of evaporation in the forecast system used - in particular, a realistic treatment of how evaporation responds to variations in soil moisture. The inherent soil moisture-evaporation relationships used in today's land surface models (LSMs), however, arguably reflect little more than guesswork given the lack of evaporation and soil moisture data at the spatial scales represented by regional and global models. Here we present a new approach for evaluating this critical aspect of LSMs. Seasonally averaged precipitation is used as a proxy for seasonally-averaged soil moisture, and seasonally-averaged air temperature is used as a proxy for seasonally-averaged evaporation (e.g., more evaporative cooling leads to cooler temperatures) the relationship between historical precipitation and temperature measurements accordingly mimics in certain important ways nature's relationship between soil moisture and evaporation. Additional information on the relationship is gleaned from joint analysis of precipitation and streamflow measurements. An experimental framework that utilizes these ideas to guide the development of an improved soil moisture-evaporation relationship is described and demonstrated.
Lewis Jordon; Richard F. Daniels; Alexander Clark; Rechun He
2005-01-01
Earlywood and latewood microfibril angle (MFA) was determined at I-millimeter intervals from disks at 1.4 meters, then at 3-meter intervals to a height of 13.7 meters, from 18 loblolly pine (Pinus taeda L.) trees grown in southeastern Texas. A modified three-parameter logistic function with mixed effects is used for modeling earlywood and latewood...
Towards soil property retrieval from space: Proof of concept using in situ observations
NASA Astrophysics Data System (ADS)
Bandara, Ranmalee; Walker, Jeffrey P.; Rüdiger, Christoph
2014-05-01
Soil moisture is a key variable that controls the exchange of water and energy fluxes between the land surface and the atmosphere. However, the temporal evolution of soil moisture is neither easy to measure nor monitor at large scales because of its high spatial variability. This is mainly a result of the local variation in soil properties and vegetation cover. Thus, land surface models are normally used to predict the evolution of soil moisture and yet, despite their importance, these models are based on low-resolution soil property information or typical values. Therefore, the availability of more accurate and detailed soil parameter data than are currently available is vital, if regional or global soil moisture predictions are to be made with the accuracy required for environmental applications. The proposed solution is to estimate the soil hydraulic properties via model calibration to remotely sensed soil moisture observation, with in situ observations used as a proxy in this proof of concept study. Consequently, the feasibility is assessed, and the level of accuracy that can be expected determined, for soil hydraulic property estimation of duplex soil profiles in a semi-arid environment using near-surface soil moisture observations under naturally occurring conditions. The retrieved soil hydraulic parameters were then assessed by their reliability to predict the root zone soil moisture using the Joint UK Land Environment Simulator model. When using parameters that were retrieved using soil moisture observations, the root zone soil moisture was predicted to within an accuracy of 0.04 m3/m3, which is an improvement of ∼0.025 m3/m3 on predictions that used published values or pedo-transfer functions.
Impact of the assimilation of satellite soil moisture and LST on the hydrological cycle
NASA Astrophysics Data System (ADS)
Laiolo, Paola; Gabellani, Simone; Delogu, Fabio; Silvestro, Francesco; Rudari, Roberto; Campo, Lorenzo; Boni, Giorgio
2014-05-01
The reliable estimation of hydrological variables (e.g. soil moisture, evapotranspiration, surface temperature) in space and time is of fundamental importance in operational hydrology to improve the forecast of the rainfall-runoff response of catchments and, consequently, flood predictions. Nowadays remote sensing can offer a chance to provide good space-time estimates of several hydrological variables and then improve hydrological model performances especially in environments with scarce ground based data. The aim of this work is to investigate the impacts on the performances of a distributed hydrological model (Continuum) of the assimilation of satellite-derived soil moisture products and Land Surface (LST). In this work three different soil moisture (SM) products, derived by ASCAT sensor, are used. These data are provided by the EUMETSAT's H-SAF (Satellite Application Facility on Support to Operational Hydrology and Water Management) program. The considered soil moisture products are: large scale surface soil moisture (SM OBS 1 - H07), small scale surface soil moisture (SM OBS 2 - H08) and profile index in the roots region (SM DAS 2 - H14). These data are compared with soil moisture estimated by Continuum model on the Orba catchment (800 km2), in the northern part of Italy, for the period July 2012-June 2013. Different assimilation experiments have been performed. The first experiment consists in the assimilation of the SM products by using a simple Nudging technique; the second one is the assimilation of only LST data, derived from MSG satellite, and the third is the assimilation of both SM products and LST. The benefits on the model predictions of discharge, LST and soil moisture dynamics were tested.
NASA Technical Reports Server (NTRS)
Srivastava, Prashant K.; Han, Dawei; Rico-Ramirez, Miguel A.; O'Neill, Peggy; Islam, Tanvir; Gupta, Manika
2014-01-01
Soil Moisture and Ocean Salinity (SMOS) is the latest mission which provides flow of coarse resolution soil moisture data for land applications. However, the efficient retrieval of soil moisture for hydrological applications depends on optimally choosing the soil and vegetation parameters. The first stage of this work involves the evaluation of SMOS Level 2 products and then several approaches for soil moisture retrieval from SMOS brightness temperature are performed to estimate Soil Moisture Deficit (SMD). The most widely applied algorithm i.e. Single channel algorithm (SCA), based on tau-omega is used in this study for the soil moisture retrieval. In tau-omega, the soil moisture is retrieved using the Horizontal (H) polarisation following Hallikainen dielectric model, roughness parameters, Fresnel's equation and estimated Vegetation Optical Depth (tau). The roughness parameters are empirically calibrated using the numerical optimization techniques. Further to explore the improvement in retrieval models, modifications have been incorporated in the algorithms with respect to the sources of the parameters, which include effective temperatures derived from the European Center for Medium-Range Weather Forecasts (ECMWF) downscaled using the Weather Research and Forecasting (WRF)-NOAH Land Surface Model and Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) while the s is derived from MODIS Leaf Area Index (LAI). All the evaluations are performed against SMD, which is estimated using the Probability Distributed Model following a careful calibration and validation integrated with sensitivity and uncertainty analysis. The performance obtained after all those changes indicate that SCA-H using WRF-NOAH LSM downscaled ECMWF LST produces an improved performance for SMD estimation at a catchment scale.
Use of satellite and modeled soil moisture data for predicting event soil loss at plot scale
NASA Astrophysics Data System (ADS)
Todisco, F.; Brocca, L.; Termite, L. F.; Wagner, W.
2015-09-01
The potential of coupling soil moisture and a Universal Soil Loss Equation-based (USLE-based) model for event soil loss estimation at plot scale is carefully investigated at the Masse area, in central Italy. The derived model, named Soil Moisture for Erosion (SM4E), is applied by considering the unavailability of in situ soil moisture measurements, by using the data predicted by a soil water balance model (SWBM) and derived from satellite sensors, i.e., the Advanced SCATterometer (ASCAT). The soil loss estimation accuracy is validated using in situ measurements in which event observations at plot scale are available for the period 2008-2013. The results showed that including soil moisture observations in the event rainfall-runoff erosivity factor of the USLE enhances the capability of the model to account for variations in event soil losses, the soil moisture being an effective alternative to the estimated runoff, in the prediction of the event soil loss at Masse. The agreement between observed and estimated soil losses (through SM4E) is fairly satisfactory with a determination coefficient (log-scale) equal to ~ 0.35 and a root mean square error (RMSE) of ~ 2.8 Mg ha-1. These results are particularly significant for the operational estimation of soil losses. Indeed, currently, soil moisture is a relatively simple measurement at the field scale and remote sensing data are also widely available on a global scale. Through satellite data, there is the potential of applying the SM4E model for large-scale monitoring and quantification of the soil erosion process.
Use of satellite and modelled soil moisture data for predicting event soil loss at plot scale
NASA Astrophysics Data System (ADS)
Todisco, F.; Brocca, L.; Termite, L. F.; Wagner, W.
2015-03-01
The potential of coupling soil moisture and a~USLE-based model for event soil loss estimation at plot scale is carefully investigated at the Masse area, in Central Italy. The derived model, named Soil Moisture for Erosion (SM4E), is applied by considering the unavailability of in situ soil moisture measurements, by using the data predicted by a soil water balance model (SWBM) and derived from satellite sensors, i.e. the Advanced SCATterometer (ASCAT). The soil loss estimation accuracy is validated using in situ measurements in which event observations at plot scale are available for the period 2008-2013. The results showed that including soil moisture observations in the event rainfall-runoff erosivity factor of the RUSLE/USLE, enhances the capability of the model to account for variations in event soil losses, being the soil moisture an effective alternative to the estimated runoff, in the prediction of the event soil loss at Masse. The agreement between observed and estimated soil losses (through SM4E) is fairly satisfactory with a determination coefficient (log-scale) equal to of ~ 0.35 and a root-mean-square error (RMSE) of ~ 2.8 Mg ha-1. These results are particularly significant for the operational estimation of soil losses. Indeed, currently, soil moisture is a relatively simple measurement at the field scale and remote sensing data are also widely available on a global scale. Through satellite data, there is the potential of applying the SM4E model for large-scale monitoring and quantification of the soil erosion process.
NASA Astrophysics Data System (ADS)
Shi, Y.; Davis, K. J.; Eissenstat, D. M.; Kaye, J. P.; Duffy, C.; Yu, X.; He, Y.
2014-12-01
Belowground carbon processes are affected by soil moisture and soil temperature, but current biogeochemical models are 1-D and cannot resolve topographically driven hill-slope soil moisture patterns, and cannot simulate the nonlinear effects of soil moisture on carbon processes. Coupling spatially-distributed physically-based hydrologic models with biogeochemical models may yield significant improvements in the representation of topographic influence on belowground C processes. We will couple the Flux-PIHM model to the Biome-BGC (BBGC) model. Flux-PIHM is a coupled physically-based land surface hydrologic model, which incorporates a land-surface scheme into the Penn State Integrated Hydrologic Model (PIHM). The land surface scheme is adapted from the Noah land surface model. Because PIHM is capable of simulating lateral water flow and deep groundwater, Flux-PIHM is able to represent the link between groundwater and the surface energy balance, as well as the land surface heterogeneities caused by topography. The coupled Flux-PIHM-BBGC model will be tested at the Susquehanna/Shale Hills critical zone observatory (SSHCZO). The abundant observations, including eddy covariance fluxes, soil moisture, groundwater level, sap flux, stream discharge, litterfall, leaf area index, above ground carbon stock, and soil carbon efflux, make SSHCZO an ideal test bed for the coupled model. In the coupled model, each Flux-PIHM model grid will couple a BBGC cell. Flux-PIHM will provide BBGC with soil moisture and soil temperature information, while BBGC provides Flux-PIHM with leaf area index. Preliminary results show that when Biome- BGC is driven by PIHM simulated soil moisture pattern, the simulated soil carbon is clearly impacted by topography.
NASA Astrophysics Data System (ADS)
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.
Simulation of the modern arctic climate by the NCAR CCM1
NASA Technical Reports Server (NTRS)
Bromwich, David H.; Tzeng, Ren-Yow; Parish, Thomas, R.
1994-01-01
The National Center of Atmospheric Research (NCAR) Community Climate Model Version 1 (CCM1's) simulation of the modern arctic climate is evaluated by comparing a five-year seasonal cycle simulation with the European Center for Medium-Range Weather Forecasts (ECMWF) global analyses. The sea level pressure (SLP), storm tracks, vertical cross section of height, 500-hPa height, total energy budget, and moisture budget are analyzed to investigate the biases in the simulated arctic climate. The results show that the model simulates anomalously low SLP, too much storm activity, and anomalously strong baroclinicity to the west of Greenland and vice versa to the east of Greenland. This bias is mainly attributed to the model's topographic representation of Greenland. First, the broadened Greenland topography in the model distorts the path of cyclone waves over the North Atlantic Ocean. Second, the model oversimulates the ridge over Greenland, which intensifies its blocking effect and steers the cyclone waves clockwise around it and hence produces an artificial circum-Greenland trough. These biases are significantly alleviated when the horizontal resolution increases to T42. Over the Arctic basin, the model simulates large amounts of low-level (stratus) clouds in winter and almost no stratus in summer, which is opposite to the observations. This bias is mainly due to the location of the simulated SLP features and the negative anomaly of storm activity, which prevent the transport of moisture into this region during summer but favor this transport in winter. The moisture budget analysis shows that the model's net annual precipitation (P-E) between 70 deg N and the North Pole is 6.6 times larger than the observations and the model transports six times more moisture into this region. The bias in the advection term is attributed to the positive moisture fixer scheme and the distorted flow pattern. However, the excessive moisture transport into the Arctic basin does not solely result from the advection term. The contribution by the moisture fixer is as large as from advection. By contrast, the semi-Lagrangian transport scheme used in the CCM2 significantly improves the moisture simulation for this region; however, globally the error is as serious as for the positive moisture fixer scheme. Finally, because the model has such serious problems in simulating the present arctic climate, its simulations of past and future climate change for this region are questionable.
Soil Moisture Estimate under Forest using a Semi-empirical Model at P-Band
NASA Astrophysics Data System (ADS)
Truong-Loi, M.; Saatchi, S.; Jaruwatanadilok, S.
2013-12-01
In this paper we show the potential of a semi-empirical algorithm to retrieve soil moisture under forests using P-band polarimetric SAR data. In past decades, several remote sensing techniques have been developed to estimate the surface soil moisture. In most studies associated with radar sensing of soil moisture, the proposed algorithms are focused on bare or sparsely vegetated surfaces where the effect of vegetation can be ignored. At long wavelengths such as L-band, empirical or physical models such as the Small Perturbation Model (SPM) provide reasonable estimates of surface soil moisture at depths of 0-5cm. However for densely covered vegetated surfaces such as forests, the problem becomes more challenging because the vegetation canopy is a complex scattering environment. For this reason there have been only few studies focusing on retrieving soil moisture under vegetation canopy in the literature. Moghaddam et al. developed an algorithm to estimate soil moisture under a boreal forest using L- and P-band SAR data. For their studied area, double-bounce between trunks and ground appear to be the most important scattering mechanism. Thereby, they implemented parametric models of radar backscatter for double-bounce using simulations of a numerical forest scattering model. Hajnsek et al. showed the potential of estimating the soil moisture under agricultural vegetation using L-band polarimetric SAR data and using polarimetric-decomposition techniques to remove the vegetation layer. Here we use an approach based on physical formulation of dominant scattering mechanisms and three parameters that integrates the vegetation and soil effects at long wavelengths. The algorithm is a simplification of a 3-D coherent model of forest canopy based on the Distorted Born Approximation (DBA). The simplified model has three equations and three unknowns, preserving the three dominant scattering mechanisms of volume, double-bounce and surface for three polarized backscattering coefficients: σHH, σVV and σHV. The inversion process, which is not an ill-posed problem, uses the non-linear optimization method of Levenberg-Marquardt and estimates the three model parameters: vegetation aboveground biomass, average soil moisture and surface roughness. The model analytical formulation will be first recalled and sensitivity analyses will be shown. Then some results obtained with real SAR data will be presented and compared to ground estimates.
NASA Astrophysics Data System (ADS)
Bircher, Simone; Richaume, Philippe; Mahmoodi, Ali; Mialon, Arnaud; Fernandez-Moran, Roberto; Wigneron, Jean-Pierre; Demontoux, François; Jonard, François; Weihermüller, Lutz; Andreasen, Mie; Rautiainen, Kimmo; Ikonen, Jaakko; Schwank, Mike; Drusch, Mattias; Kerr, Yann H.
2017-04-01
From the passive L-band microwave radiometer onboard the Soil Moisture and Ocean Salinity (SMOS) space mission global surface soil moisture data is retrieved every 2 - 3 days. Thus far, the empirical L-band Microwave Emission of the Biosphere (L-MEB) radiative transfer model applied in the SMOS soil moisture retrieval algorithm is exclusively calibrated over test sites in dry and temperate climate zones. Furthermore, the included dielectric mixing model relating soil moisture to relative permittivity accounts only for mineral soils. However, soil moisture monitoring over the higher Northern latitudes is crucial since these regions are especially sensitive to climate change. A considerable positive feedback is expected if thawing of these extremely organic soils supports carbon decomposition and release to the atmosphere. Due to differing structural characteristics and thus varying bound water fractions, the relative permittivity of organic material is lower than that of the most mineral soils at a given water content. This assumption was verified by means of L-band relative permittivity laboratory measurements of organic and mineral substrates from various sites in Denmark, Finland, Scotland and Siberia using a resonant cavity. Based on these data, a simple empirical dielectric model for organic soils was derived and implemented in the SMOS Soil Moisture Level 2 Prototype Processor (SML2PP). Unfortunately, the current SMOS retrieved soil moisture product seems to show unrealistically low values compared to in situ soil moisture data collected from organic surface layers in North America, Europe and the Tibetan Plateau so that the impact of the dielectric model for organic soils cannot really be tested. A simplified SMOS processing scheme yielding higher soil moisture levels has recently been proposed and is presently under investigation. Furthermore, recalibration of the model parameters accounting for vegetation and roughness effects that were thus far only evaluated using the default dielectric model for mineral soils is ongoing for the "organic" L-MEB version. Additionally, in order to decide where a soil moisture retrieval using the "organic" dielectric model should be triggered, information on soil organic matter content in the soil surface layer has to be considered in the retrieval algorithm. For this purpose, SoilGrids (www.soilgrids.org) providing soil organic carbon content (SOCC) in g/kg is under study. A SOCC threshold based on the relation between the SoilGrids' SOCC and the presence of organic soil surface layers (relevant to alter the microwave L-band emissions from the land surface) in the SoilGrids' source soil profile information has to be established. In this communication, we present the current status of the above outlined studies with the objective to advance towards an improved soil moisture retrieval for organic-rich soils from SMOS passive microwave L-band observations.
Sensitivity of transpiration to subsurface properties: Exploration with a 1-D model
NASA Astrophysics Data System (ADS)
Vrettas, Michail D.; Fung, Inez Y.
2017-06-01
The amount of moisture transpired by vegetation is critically tied to the moisture supply accessible to the root zone. In a Mediterranean climate, integrated evapotranspiration (ET) is typically greater in the dry summer when there is an uninterrupted period of high insolation. We present a 1-D model to explore the subsurface factors that may sustain ET through the dry season. The model includes a stochastic parameterization of hydraulic conductivity, root water uptake efficiency, and hydraulic redistribution by plant roots. Model experiments vary the precipitation, the magnitude and seasonality of ET demand, as well as rooting profiles and rooting depths of the vegetation. The results show that the amount of subsurface moisture remaining at the end of the wet winter is determined by the competition among abundant precipitation input, fast infiltration, and winter ET demand. The weathered bedrock retains ˜30% of the winter rain and provides a substantial moisture reservoir that may sustain ET of deep-rooted (>8 m) trees through the dry season. A small negative feedback exists in the root zone, where the depletion of moisture by ET decreases hydraulic conductivity and enhances the retention of moisture. Hence, hydraulic redistribution by plant roots is impactful in a dry season, or with a less conductive subsurface. Suggestions for implementing the model in the CESM are discussed.
Stream Flow Prediction by Remote Sensing and Genetic Programming
NASA Technical Reports Server (NTRS)
Chang, Ni-Bin
2009-01-01
A genetic programming (GP)-based, nonlinear modeling structure relates soil moisture with synthetic-aperture-radar (SAR) images to present representative soil moisture estimates at the watershed scale. Surface soil moisture measurement is difficult to obtain over a large area due to a variety of soil permeability values and soil textures. Point measurements can be used on a small-scale area, but it is impossible to acquire such information effectively in large-scale watersheds. This model exhibits the capacity to assimilate SAR images and relevant geoenvironmental parameters to measure soil moisture.
NASA Astrophysics Data System (ADS)
Polcher, Jan; Barella-Ortiz, Anaïs; Aires, Filipe; Balsamo, Gianpaolo; Gelati, Emiliano; Rodríguez-Fernández, Nemesio
2015-04-01
Soil moisture is a key state variable of the hydrological cycle. It conditions runoff, infiltration and evaporation over continental surfaces, and is key for forecasting droughts and floods. It plays thus an important role in surface-atmosphere interactions. Surface Soil Moisture (SSM) can be measured by in situ measurements, by satellite observations or modelled using land surface models. As a complementary tool, data assimilation can be used to combine both modelling and satellite observations. The work presented here is an inter-comparison of retrieved and modelled SSM data, for the 2010 - 2012 period, over the Iberian Peninsula. The region has been chosen because its vegetation cover is not very dense and includes strong contrasts in the rainfall regimes and thus a diversity of behaviours for SSM. Furthermore this semi-arid region is strongly dependent on a good management of its water resources. Satellite observations correspond to the Soil Moisture and Ocean Salinity (SMOS) retrievals: the L2 product from an optimal interpolation retrieval, and 3 other products using Neural Network retrievals with different input information: SMOS time indexes, purely SMOS data, or addition of the European Advanced Scaterometer (ASCAT) backscattering, and the Moderate-Resolution Imaging Spectrometer (MODIS) surface temperature information. The modelled soil moistures have been taken from the ORCHIDEE (ORganising Carbon and Hydrology In Dynamic EcosystEms) and the HTESSEL (Hydrology-Tiled ECMWF Scheme for Surface Exchanges over Land) land surface models. Both models are forced with the same atmospheric conditions (as part of the Earth2Observe FP7 project) over the period but they represent the surface soil moisture with very different degrees of complexity. ORCHIDEE has 5 levels in the top 5 centimetres of soil while in HTESSEL this variable is part of the top soil moisture level. The two types of SMOS retrievals are compared to the model outputs in their spatial and temporal characteristics. The comparison with the model helps to identify which retrieval configuration is most consistent with our understanding of surface soil moisture in this region. In particular we have determined how each of the soil moisture products is related to the spatio-temporal variations of rainfall. In large parts of the Iberian Peninsula the co-variance of remote sensed SSM and rainfall is consistent with that of the models. But for some regions questions are raised. The variability of SSM observed by SMOS in the North West of the Iberian Peninsula is similar to that of rainfall, at least this relation of SSM and rainfall is closer than suggested by the two models.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sun, Rui, E-mail: Sunsr@hit.edu.cn; Ismail, Tamer M., E-mail: temoil@aucegypt.edu; Ren, Xiaohan
Highlights: • The effects of moisture content on the burning process of MSW are investigated. • A two-dimensional mathematical model was built to simulate the combustion process. • Temperature distributions, process rates, gas species were measured and simulated. • The The conversion ratio of C/CO and N/NO in MSW are inverse to moisture content. - Abstract: In order to reveal the features of the combustion process in the porous bed of a waste incinerator, a two-dimensional unsteady state model and experimental study were employed to investigate the combustion process in a fixed bed of municipal solid waste (MSW) on themore » combustion process in a fixed bed reactor. Conservation equations of the waste bed were implemented to describe the incineration process. The gas phase turbulence was modeled using the k–ε turbulent model and the particle phase was modeled using the kinetic theory of granular flow. The rate of moisture evaporation, devolatilization rate, and char burnout was calculated according to the waste property characters. The simulation results were then compared with experimental data for different moisture content of MSW, which shows that the incineration process of waste in the fixed bed is reasonably simulated. The simulation results of solid temperature, gas species and process rate in the bed are accordant with experimental data. Due to the high moisture content of fuel, moisture evaporation consumes a vast amount of heat, and the evaporation takes up most of the combustion time (about 2/3 of the whole combustion process). The whole bed combustion process reduces greatly as MSW moisture content increases. The experimental and simulation results provide direction for design and optimization of the fixed bed of MSW.« less
NASA Astrophysics Data System (ADS)
Blyverket, J.; Hamer, P.; Bertino, L.; Lahoz, W. A.
2017-12-01
The European Space Agency Climate Change Initiative for soil moisture (ESA CCI SM) was initiated in 2012 for a period of six years, the objective for this period was to produce the most complete and consistent global soil moisture data record based on both active and passive sensors. The ESA CCI SM products consist of three surface soil moisture datasets: The ACTIVE product and the PASSIVE product were created by fusing scatterometer and radiometer soil moisture data, respectively. The COMBINED product is a blended product based on the former two datasets. In this study we assimilate globally both the ACTIVE and PASSIVE product at a 25 km spatial resolution. The different satellite platforms have different overpass times, an observation is mapped to the hours 00.00, 06.00, 12.00 or 18.00 if it falls within a 3 hour window centred at these times. We use the SURFEX land surface model with the ISBA diffusion scheme for the soil hydrology. For the assimilation routine we apply the Ensemble Transform Kalman Filter (ETKF). The land surface model is driven by perturbed MERRA-2 atmospheric forcing data, which has a temporal resolution of one hour and is mapped to the SURFEX model grid. Bias between the land surface model and the ESA CCI product is removed by cumulative distribution function (CDF) matching. This work is a step towards creating a global root zone soil moisture product from the most comprehensive satellite surface soil moisture product available. As a first step we consider the period from 2010 - 2016. This allows for comparison against other global root zone soil moisture products (SMAP Level 4, which is independent of the ESA CCI SM product).
Geologic Controls on Geophysics for Tunnel Detection
NASA Astrophysics Data System (ADS)
Kelley, J. R.; Wakeley, L. D.; McKenna, J. R.; Ketcham, S. A.; Weiss, C. A.; Curtis, J. O.
2006-05-01
Properties of soils are critical to using near-surface geophysical techniques to search for clandestine tunnels. We have constructed a database of soils sampled at sites on the northern (N) and southern (S) US borders and at sites in Iraq in conjunction with tunnel searches. Geologic materials at these sites consist of glacial gravels (N), volcanic tuff (S), and alluvial sands interbedded with marine clays (Iraq). The depth of interest for detecting clandestine tunneling is < 30m, and as shallow as 2m at some locations. Mineral composition, grain size, moisture content, conductivity, permittivity, and magnetic susceptibility are critical for assessing the effectiveness of near-surface geophysical techniques. Values for these properties are consistent with soil stratigraphy and with vertical and lateral geologic variability. In some environments, in situ moisture content and the arrangement of conductive and resistive materials in the upper few meters limit significantly the depth of investigation using traditional near-surface techniques (electromagnetic induction, ground-penetrating radar). Geologic factors plus the small physical size of the targets limit the usefulness of commercial off-the-shelf techniques, and warrant an investment in new approaches.
Howard Evan Canfield; Vicente L. Lopes
2000-01-01
A process-based, simulation model for evaporation, soil water and streamflow (BROOK903) was used to estimate soil moisture change on a semiarid rangeland watershed in southeastern Arizona. A sensitivity analysis was performed to select parameters affecting ET and soil moisture for calibration. Automatic parameter calibration was performed using a procedure based on a...
One-dimensional simulation of temperature and moisture in atmospheric and soil boundary layers
NASA Technical Reports Server (NTRS)
Bornstein, R. D.; Santhanam, K.
1981-01-01
Meteorologists are interested in modeling the vertical flow of heat and moisture through the soil in order to better simulate the vertical and temporal variations of the atmospheric boundary layer. The one dimensional planetary boundary layer model of is modified by the addition of transport equations to be solved by a finite difference technique to predict soil moisture.
NASA Astrophysics Data System (ADS)
Boisserie, Marie
The goal of this dissertation research is to produce empirical soil moisture initial conditions (soil moisture analysis) and investigate its impact on the short-term (2 weeks) to subseasonal (2 months) forecasting skill of 2-m air temperature and precipitation. Because of soil moisture has a long memory and plays a role in controlling the surface water and energy budget, an accurate soil moisture analysis is today widely recognized as having the potential to increase summertime climate forecasting skill. However, because of a lack of global observations of soil moisture, there has been no scientific consensus on the importance of the contribution of a soil moisture initialization as close to the truth as possible to climate forecasting skill. In this study, the initial conditions are generated using a Precipitation Assimilation Reanalysis (PAR) technique to produce a soil moisture analysis. This technique consists mainly of nudging precipitation in the atmosphere component of a land-atmosphere model by adjusting the vertical air humidity profile based on the difference between the rate of the model-derived precipitation rate and the observed rate. The unique aspects of the PAR technique are the following: (1) based on the PAR technique, the soil moisture analysis is generated using a coupled land-atmosphere forecast model; therefore, no bias between the initial conditions and the forecast model (spinup problem) is encountered; and (2) the PAR technique is physically consistent; the surface and radiative fluxes remains in conjunction with the soil moisture analysis. To our knowledge, there has been no attempt to use a physically consistent soil moisture land assimilation system into a land-atmosphere model in a coupled mode. The effect of the PAR technique on the model soil moisture estimates is evaluated using the Global Soil Wetness Project Phase 2 (GSWP-2) multimodel analysis product (used as a proxy for global soil moisture observations) and actual in-situ observations from the state of Illinois. The results show that overall the PAR technique is effective; across most of the globe, the seasonal and anomaly variability of the model soil moisture estimates well reproduce the values of GSWP-2 in the top 1.5 m soil layer; by comparing to in-situ observations in Illinois, we find that the seasonal and anomaly soil moisture variability is also well represented deep into the soil. Therefore, in this study, we produce a new global soil moisture analysis dataset that can be used for many land surface studies (crop modeling, water resource management, soil erosion, etc.). Then, the contribution of the resulting soil moisture analysis (used as initial conditions) on air temperature and precipitation forecasts are investigated. For this, we follow the experimental set up of a model intercomparison study over the time period 1986-1995, the Global Land-Atmosphere Coupling Experiment second phase (GLACE-2), in which the FSU/COAPS climate model has participated. The results of the summertime air temperature forecasts show a significant increase in skill across most of the U.S. at short-term to subseasonal time scales. No increase in summertime precipitation forecasting skill is found at short-term to subseasonal time scales between 1986 and 1995, except for the anomalous drought year of 1988. We also analyze the forecasts of two extreme hydrological events, the 1988 U.S. drought and the 1993 U.S. flood. In general, the comparison of these two extreme hydrological event forecasts shows greater improvement for the summertime of 1988 than that of 1993, suggesting that soil moisture contributes more to the development of a drought than a flood. This result is consistent with Dirmeyer and Brubaker [1999] and Weaver et al. [2009]. By analyzing the evaporative sources of these two extreme events using the back-trajectory methodology of Dirmeyer and Brubaker [1999], we find similar results as this latter paper; the soil moisture-precipitation feedback mechanism seems to play a greater role during the drought year of 1988 than the flood year of 1993. Finally, the accuracy of this soil moisture initialization depends upon the quality of the precipitation dataset that is assimilated. Because of the lack of observed precipitation at a high temporal resolution (3-hourly) for the study period (1986-1995), a reanalysis product is used for precipitation assimilation in this study. It is important to keep in mind that precipitation data in reanalysis sometimes differ significantly from observations since precipitation is often not assimilated into the reanalysis model. In order to investigate that aspect, a similar analysis to that we performed in this study could be done using the 3-hourly Tropical Rainfall Measuring Mission (TRMM) dataset available for a the time period 1998-present. Then, since the TRMM dataset is a fully observational dataset, we expect the soil moisture initialization to be improved over that obtained in this study, which, in turn, may further increase the forecast skill.
NASA Astrophysics Data System (ADS)
Kempe, Michael D.
2016-09-01
Photovoltaic devices are often sensitive to moisture and must be packaged in such a way as to limit moisture ingress for 25 years or more. Typically, this is accomplished through the use of impermeable front and backsheets (e.g., glass sheets or metal foils). However, this will still allow moisture ingress between the sheets from the edges. Attempts to hermetically seal with a glass frit or similarly welded bonds at the edge have had problems with costs and mechanical strength. Because of this, low diffusivity polyisobutylene materials filled with desiccant are typically used. Although it is well known that these materials will substantially delay moisture ingress, correlating that to outdoor exposure has been difficult. Here, we use moisture ingress measurements at different temperatures and relative humidities to find fit parameters for a moisture ingress model for an edge-seal material. Then, using meteorological data, a finite element model is used to predict the moisture ingress profiles for hypothetical modules deployed in different climates and mounting conditions, assuming no change in properties of the edge-seal as a function of aging.
Effect of clothing material on thermal responses of the human body
NASA Astrophysics Data System (ADS)
Fengzhi, Li; Yi, Li
2005-09-01
The influence of clothing material on thermal responses of the human body are investigated by using an integrated model of a clothed thermoregulatory human body. A modified 25-nodes model considering the sweat accumulation on the skin surface is applied to simulate the human physiological regulatory responses. The heat and moisture coupled transfer mechanisms, including water vapour diffusion, the moisture evaporation/condensation, the moisture sorbtion/desorption by fibres, liquid sweat transfer under capillary pressure, and latent heat absorption/release due to phase change, are considered in the clothing model. On comparing prediction results with the experimental data in the literature, the proposed model seems able to predict dynamic heat and moisture transfer between the human body and the clothing system. The human body's thermal responses and clothing temperature and moisture variations are compared for different clothing materials during transient periods. We concluded that the hygroscopicity of clothing materials influences the human thermoregulation process significantly during environmental transients.
NASA Astrophysics Data System (ADS)
Yang, Yang; Dou, Yanxing; Liu, Dong; An, Shaoshan
2017-07-01
Spatial pattern and heterogeneity of soil moisture is important for the hydrological process on the Loess Plateau. This study combined the classical and geospatial statistical techniques to examine the spatial pattern and heterogeneity of soil moisture along a transect scale (e.g. land use types and topographical attributes) on the Loess Plateau. The average values of soil moisture were on the order of farmland > orchard > grassland > abandoned land > shrubland > forestland. Vertical distribution characteristics of soil moisture (0-500 cm) were similar among land use types. Highly significant (p < 0.01) negative correlations were found between soil moisture and elevation (h) except for shrubland (p > 0.05), whereas no significant correlations were found between soil moisture and plan curvature (Kh), stream power index (SPI), compound topographic index (CTI) (p > 0.05), indicating that topographical attributes (mainly h) have a negative effect on the soil moisture spatial heterogeneity. Besides, soil moisture spatial heterogeneity decreased from forestland to grassland and farmland, accompanied by a decline from 15° to 1° alongside upper to lower slope position. This study highlights the importance of land use types and topographical attributes on the soil moisture spatial heterogeneity from a combined analysis of the structural equation model (SEM) and generalized additive models (GAMs), and the relative contribution of land use types to the soil moisture spatial heterogeneity was higher than that of topographical attributes, which provides insights for researches focusing on soil moisture varitions on the Loess Plateau.
Spatial-temporal variability of soil moisture and its estimation across scales
NASA Astrophysics Data System (ADS)
Brocca, L.; Melone, F.; Moramarco, T.; Morbidelli, R.
2010-02-01
The soil moisture is a quantity of paramount importance in the study of hydrologic phenomena and soil-atmosphere interaction. Because of its high spatial and temporal variability, the soil moisture monitoring scheme was investigated here both for soil moisture retrieval by remote sensing and in view of the use of soil moisture data in rainfall-runoff modeling. To this end, by using a portable Time Domain Reflectometer, a sequence of 35 measurement days were carried out within a single year in seven fields located inside the Vallaccia catchment, central Italy, with area of 60 km2. Every sampling day, soil moisture measurements were collected at each field over a regular grid with an extension of 2000 m2. The optimization of the monitoring scheme, with the aim of an accurate mean soil moisture estimation at the field and catchment scale, was addressed by the statistical and the temporal stability. At the field scale, the number of required samples (NRS) to estimate the field-mean soil moisture within an accuracy of 2%, necessary for the validation of remotely sensed soil moisture, ranged between 4 and 15 for almost dry conditions (the worst case); at the catchment scale, this number increased to nearly 40 and it refers to almost wet conditions. On the other hand, to estimate the mean soil moisture temporal pattern, useful for rainfall-runoff modeling, the NRS was found to be lower. In fact, at the catchment scale only 10 measurements collected in the most "representative" field, previously determined through the temporal stability analysis, can reproduce the catchment-mean soil moisture with a determination coefficient, R2, higher than 0.96 and a root-mean-square error, RMSE, equal to 2.38%. For the "nonrepresentative" fields the accuracy in terms of RMSE decreased, but similar R2 coefficients were found. This insight can be exploited for the sampling in a generic field when it is sufficient to know an index of soil moisture temporal pattern to be incorporated in conceptual rainfall-runoff models. The obtained results can address the soil moisture monitoring network design from which a reliable soil moisture temporal pattern at the catchment scale can be derived.
The impact of non-isothermal soil moisture transport on evaporation fluxes in a maize cropland
NASA Astrophysics Data System (ADS)
Shao, Wei; Coenders-Gerrits, Miriam; Judge, Jasmeet; Zeng, Yijian; Su, Ye
2018-06-01
The process of evaporation interacts with the soil, which has various comprehensive mechanisms. Multiphase flow models solve air, vapour, water, and heat transport equations to simulate non-isothermal soil moisture transport of both liquid water and vapor flow, but are only applied in non-vegetated soils. For (sparsely) vegetated soils often energy balance models are used, however these lack the detailed information on non-isothermal soil moisture transport. In this study we coupled a multiphase flow model with a two-layer energy balance model to study the impact of non-isothermal soil moisture transport on evaporation fluxes (i.e., interception, transpiration, and soil evaporation) for vegetated soils. The proposed model was implemented at an experimental agricultural site in Florida, US, covering an entire maize-growing season (67 days). As the crops grew, transpiration and interception became gradually dominated, while the fraction of soil evaporation dropped from 100% to less than 20%. The mechanisms of soil evaporation vary depending on the soil moisture content. After precipitation the soil moisture content increased, exfiltration of the liquid water flow could transport sufficient water to sustain evaporation from soil, and the soil vapor transport was not significant. However, after a sufficient dry-down period, the soil moisture content significantly reduced, and the soil vapour flow significantly contributed to the upward moisture transport in topmost soil. A sensitivity analysis found that the simulations of moisture content and temperature at the soil surface varied substantially when including the advective (i.e., advection and mechanical dispersion) vapour transport in simulation, including the mechanism of advective vapour transport decreased soil evaporation rate under wet condition, while vice versa under dry condition. The results showed that the formulation of advective soil vapor transport in a soil-vegetation-atmosphere transfer continuum can affect the simulated evaporation fluxes, especially under dry condition.
Estimating Soil Moisture Using Polsar Data: a Machine Learning Approach
NASA Astrophysics Data System (ADS)
Khedri, E.; Hasanlou, M.; Tabatabaeenejad, A.
2017-09-01
Soil moisture is an important parameter that affects several environmental processes. This parameter has many important functions in numerous sciences including agriculture, hydrology, aerology, flood prediction, and drought occurrence. However, field procedures for moisture calculations are not feasible in a vast agricultural region territory. This is due to the difficulty in calculating soil moisture in vast territories and high-cost nature as well as spatial and local variability of soil moisture. Polarimetric synthetic aperture radar (PolSAR) imaging is a powerful tool for estimating soil moisture. These images provide a wide field of view and high spatial resolution. For estimating soil moisture, in this study, a model of support vector regression (SVR) is proposed based on obtained data from AIRSAR in 2003 in C, L, and P channels. In this endeavor, sequential forward selection (SFS) and sequential backward selection (SBS) are evaluated to select suitable features of polarized image dataset for high efficient modeling. We compare the obtained data with in-situ data. Output results show that the SBS-SVR method results in higher modeling accuracy compared to SFS-SVR model. Statistical parameters obtained from this method show an R2 of 97% and an RMSE of lower than 0.00041 (m3/m3) for P, L, and C channels, which has provided better accuracy compared to other feature selection algorithms.
Moisture sorption isotherms and thermodynamic properties of mexican mennonite-style cheese.
Martinez-Monteagudo, Sergio I; Salais-Fierro, Fabiola
2014-10-01
Moisture adsorption isotherms of fresh and ripened Mexican Mennonite-style cheese were investigated using the static gravimetric method at 4, 8, and 12 °C in a water activity range (aw) of 0.08-0.96. These isotherms were modeled using GAB, BET, Oswin and Halsey equations through weighed non-linear regression. All isotherms were sigmoid in shape, showing a type II BET isotherm, and the data were best described by GAB model. GAB model coefficients revealed that water adsorption by cheese matrix is a multilayer process characterized by molecules that are strongly bound in the monolayer and molecules that are slightly structured in a multilayer. Using the GAB model, it was possible to estimate thermodynamic functions (net isosteric heat, differential entropy, integral enthalpy and entropy, and enthalpy-entropy compensation) as function of moisture content. For both samples, the isosteric heat and differential entropy decreased with moisture content in exponential fashion. The integral enthalpy gradually decreased with increasing moisture content after reached a maximum value, while the integral entropy decreased with increasing moisture content after reached a minimum value. A linear compensation was found between integral enthalpy and entropy suggesting enthalpy controlled adsorption. Determination of moisture content and aw relationship yields to important information of controlling the ripening, drying and storage operations as well as understanding of the water state within a cheese matrix.
NASA Astrophysics Data System (ADS)
Laiolo, Paola; Gabellani, Simone; Rudari, Roberto; Boni, Giorgio; Puca, Silvia
2013-04-01
Soil moisture plays a fundamental role in the partitioning of mass and energy fluxes between land surface and atmosphere, thereby influencing climate and weather, and it is important in determining the rainfall-runoff response of catchments; moreover, in hydrological modelling and flood forecasting, a correct definition of moisture conditions is a key factor for accurate predictions. Different sources of information for the estimation of the soil moisture state are currently available: satellite data, point measurements and model predictions. All are affected by intrinsic uncertainty. Among different satellite sensors that can be used for soil moisture estimation three major groups can be distinguished: passive microwave sensors (e.g., SSMI), active sensors (e.g. SAR, Scatterometers), and optical sensors (e.g. Spectroradiometers). The last two families, mainly because of their temporal and spatial resolution seem the most suitable for hydrological applications In this work soil moisture point measurements from 10 sensors in the Italian territory are compared of with the satellite products both from the HSAF project SM-OBS-2, derived from the ASCAT scatterometer, and from ACHAB, an operative energy balance model that assimilate LST data derived from MSG and furnishes daily an evaporative fraction index related to soil moisture content for all the Italian region. Distributed comparison of the ACHAB and SM-OBS-2 on the whole Italian territory are performed too.
Role of Subsurface Physics in the Assimilation of Surface Soil Moisture Observations
NASA Technical Reports Server (NTRS)
Reichle, R. H.
2010-01-01
Root zone soil moisture controls the land-atmosphere exchange of water and energy and exhibits memory that may be useful for climate prediction at monthly scales. Assimilation of satellite-based surface soil moisture observations into a land surface model is an effective way to estimate large-scale root zone soil moisture. The propagation of surface information into deeper soil layers depends on the model-specific representation of subsurface physics that is used in the assimilation system. In a suite of experiments we assimilate synthetic surface soil moisture observations into four different models (Catchment, Mosaic, Noah and CLM) using the Ensemble Kalman Filter. We demonstrate that identical twin experiments significantly overestimate the information that can be obtained from the assimilation of surface soil moisture observations. The second key result indicates that the potential of surface soil moisture assimilation to improve root zone information is higher when the surface to root zone coupling is stronger. Our experiments also suggest that (faced with unknown true subsurface physics) overestimating surface to root zone coupling in the assimilation system provides more robust skill improvements in the root zone compared with underestimating the coupling. When CLM is excluded from the analysis, the skill improvements from using models with different vertical coupling strengths are comparable for different subsurface truths. Finally, the skill improvements through assimilation were found to be sensitive to the regional climate and soil types.
NASA Astrophysics Data System (ADS)
Kreutz, K. J.; Campbell, S. W.; Winski, D.; Osterberg, E. C.; Kochtitzky, W. H.; Copland, L.; Dixon, D.; Introne, D.; Medrzycka, D.; Main, B.; Bernsen, S.; Wake, C. P.
2017-12-01
A growing array of high-resolution paleoclimate records from the terrestrial region bordering the Gulf of Alaska (GoA) continues to reveal details about ocean-atmosphere variability in the region during the Common Era. Ice core records from high-elevation ranges in proximity to the GoA provide key information on extratropical hydroclimate, and potential teleconnections to low latitude regions. In particular, stable water isotope and snow accumulation reconstructions from ice cores collected in high precipitation locations are uniquely tied to regional water cycle changes. Here we present new data collected in 2016 and 2017 from the St. Elias Mountains (Eclipse Icefield, Yukon Territories, Canada), including a range of ice core and geophysical measurements. Low- and high-frequency ice penetrating radar data enable detailed mapping of icefield bedrock topography and internal reflector stratigraphy. The 1911 Katmai eruption layer can be clearly traced across the icefield, and tied definitively to the coeval ash layer found in the 345 meter ice core drilled at Eclipse Icefield in 2002. High-resolution radar data are used to map spatial variability in 2015/16 and 2016/17 snow accumulation. Ice velocity data from repeat GPS stake measurements and remote sensing feature tracking reveal a clear divide flow regime on the icefield. Shallow firn/ice cores (20 meters in 2017 and 65 meters in 2016) are used to update the 345 meter ice core drilled at Eclipse Icefield in 2002. We use new algorithm-based layer counting software to improve and provide error estimates on the new ice core chronology, which extends from 2017 to 1450AD. 3D finite element modeling, incorporating all available geophysical data, is used to refine the reconstructed accumulation rate record and account for vertical and horizontal ice flow. Together with high-resolution stable water isotope data, the updated Eclipse record provides detailed, sub-annual resolution data on several aspects of the regional water cycle (e.g., accumulation/precipitation, moisture source and trajectory, coupled ocean/atmosphere variability). We compare the updated Eclipse record with other data in the North Pacific region, including the new Denali 1200-year ice core datasets, to assess regional hydroclimate variability during the Common Era.
Modeling heat and moisture transport in firefighter protective clothing during flash fire exposure
NASA Astrophysics Data System (ADS)
Chitrphiromsri, Patirop; Kuznetsov, Andrey V.
2005-01-01
In this paper, a model of heat and moisture transport in firefighter protective clothing during a flash fire exposure is presented. The aim of this study is to investigate the effect of coupled heat and moisture transport on the protective performance of the garment. Computational results show the distribution of temperature and moisture content in the fabric during the exposure to the flash fire as well as during the cool-down period. Moreover, the duration of the exposure during which the garment protects the firefighter from getting second and third degree burns from the flash fire exposure is numerically predicted. A complete model for the fire-fabric-air gap-skin system is presented.
Pan, Hongyang; Jiang, Bo; Chen, Jie; Jin, Zhengyu
2014-11-04
Multi-component substances made through direct blending or blending with co-drying can form films on the surfaces of intermediate moisture foods (IMFs), which help retain moisture and protect food texture and flavor. An IMF film system based on pullulan, with glycerol serving as the plasticizer, was studied using alginate and four different types of polysaccharides (propyleneglycol alginate, pectin, carrageenan, and aloe polysaccharide) as the blend-modified substances. The physical, mechanical, color, transparency, and moisture-retention properties of the co-blended films with the polysaccharides were assessed. A new formula was established for the average moisture retention property, water barrier, tensile strength, elongation at break, and oxygen barrier property of the ternary co-blended films using the Design Expert software. The new model established for moisture content measurement used an indirect method of film formation on food surfaces by humectants, which should expedite model validation and allow a better comprehension of moisture transfer through edible films. Copyright © 2014 Elsevier Ltd. All rights reserved.
Muiti-Sensor Historical Climatology of Satellite-Derived Global Land Surface Moisture
NASA Technical Reports Server (NTRS)
Owe, Manfred; deJeu, Richard; Holmes, Thomas
2007-01-01
A historical climatology of continuous satellite derived global land surface soil moisture is being developed. The data set consists of surface soil moisture retrievals from observations of both historical and currently active satellite microwave sensors, including Nimbus-7 SMMR, DMSP SSM/I, TRMM TMI, and AQUA AMSR-E. The data sets span the period from November 1978 through the end of 2006. The soil moisture retrievals are made with the Land Parameter Retrieval Model, a physically-based model which was developed jointly by researchers from the above institutions. These data are significant in that they are the longest continuous data record of observational surface soil moisture at a global scale. Furthermore, while previous reports have intimated that higher frequency sensors such as on SSM/I are unable to provide meaningful information on soil moisture, our results indicate that these sensors do provide highly useful soil moisture data over significant parts of the globe, and especially in critical areas located within the Earth's many arid and semi-arid regions.
Design, analysis, and test verification of advanced encapsulation systems
NASA Technical Reports Server (NTRS)
Garcia, A.; Minning, C.
1981-01-01
Thermal, optical, structural, and electrical isolation analyses are decribed. Major factors in the design of terrestrial photovoltaic modules are discussed. Mechanical defects in the different layers of an encapsulation system, it was found, would strongly influence the minimum pottant thickness required for electrical isolation. Structural, optical, and electrical properties, a literature survey indicated, are hevily influenced by the presence of moisture. These items, identified as technology voids, are discussed. Analyses were based upon a 1.2 meter square module using 10.2 cm (4-inch) square cells placed 1.3 mm apart as shown in Figure 2-2. Sizing of the structural support member of a module was determined for a uniform, normal pressure load of 50 psf, corresponding to the pressure difference generated between the front and back surface of a module by a 100 mph wind. Thermal and optical calculations were performed for a wind velocity of 1 meter/sec parallel to the ground and for module tilt (relative to the local horizontal) of 37 deg. Placement of a module in a typical array field is illustrated.
Schaefer, Donald H.; Welch, Alan H.; Mauzer, Douglas K.
1983-01-01
Studies of the geothermal potential of the western arm of the Black Rock Desert in northwestern Nevada included a compilation of existing geologic data on a detailed map, a temperature survey at 1-meter depth, a thermal-scanner survey, and gravity and seismic surveys to determine basin geometry. The temperature survey showed the effects of heating at shallow depths due to rising geothermal fluids near the known hot spring areas. Lower temperatures were noted in areas of probable near-surface ground-water movement. The thermal-scanner survey verified the known geothermal areas and showed relatively high-temperature areas of standing water and ground-water discharge. The upland areas of the desert were found to be distinctly warmer than the playa area, probably due to low thermal diffusivity resulting from low moisture content. The surface geophysical surveys indicated that the maximum thickness of valley-fill deposits in the desert is about 3,200 meters. Gravity data further showed that changes in the trend of the desert axis occurred near thermal areas. (USGS)
Design, analysis, and test verification of advanced encapsulation systems
NASA Astrophysics Data System (ADS)
Garcia, A.; Minning, C.
1981-11-01
Thermal, optical, structural, and electrical isolation analyses are decribed. Major factors in the design of terrestrial photovoltaic modules are discussed. Mechanical defects in the different layers of an encapsulation system, it was found, would strongly influence the minimum pottant thickness required for electrical isolation. Structural, optical, and electrical properties, a literature survey indicated, are hevily influenced by the presence of moisture. These items, identified as technology voids, are discussed. Analyses were based upon a 1.2 meter square module using 10.2 cm (4-inch) square cells placed 1.3 mm apart as shown in Figure 2-2. Sizing of the structural support member of a module was determined for a uniform, normal pressure load of 50 psf, corresponding to the pressure difference generated between the front and back surface of a module by a 100 mph wind. Thermal and optical calculations were performed for a wind velocity of 1 meter/sec parallel to the ground and for module tilt (relative to the local horizontal) of 37 deg. Placement of a module in a typical array field is illustrated.
A model of the thermal-spike mechanism in graphite/epoxy laminates
NASA Technical Reports Server (NTRS)
Adamson, M. J.
1982-01-01
The influence of a thermal spike on a moisture-saturated graphite/epoxy composite was studied in detail. A single thermal spike from 25 C to 132 C was found to produce damage as evidenced by a significant increase in the level of moisture saturation in the composite. Approximately half of this increase remained after a vacuum anneal at 150 C for 7 days, suggesting the presence of an irreversible damage component. Subsequent thermal spikes created less and less additional moisture absorption, with the cumulative effect being a maximum or limiting moisture capacity of the composite. These observations are explained in terms of a model previously developed to explain the reverse thermal effect of moisture absorption in epoxy and epoxy matrix composites. This model, based on the inverse temperature dependence of free volume, contributes an improved understanding of thermal-spike effects in graphite/epoxy composites.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Staliulionis, Ž.; Jabbari, M.; Hattel, J. H.
The number of electronics used in outdoor environment is constantly growing. The humidity causes about 19 % of all electronics failures and, especially, moisture increases these problems due to the ongoing process of miniaturization and lower power consumption of electronic components. Moisture loads are still not understood well by design engineers, therefore this field has become one of the bottlenecks in the electronics system design. The objective of this paper is to model moisture ingress into an electronics enclosure under isothermal conditions. The moisture diffusion model is based on a 1D quasi-steady state (QSS) approximation for Fick’s second law. Thismore » QSS approach is also described with an electrical analogy which gives a fast tool in modelling of the moisture response. The same QSS method is applied to ambient water vapour variations. The obtained results are compared to an analytical solution and very good agreement is found.« less
FPL roof temperature and moisture model : description and verification
A. TenWolde
This paper describes a mathematical model developed by the Forest Products Laboratory to predict attic temperatures, relative humidities, and roof sheathing moisture content. Comparison of data from model simulation and measured data provided limited validation of the model and led to the following conclusions: (1) the model can...
Mesoscale research activities with the LAMPS model
NASA Technical Reports Server (NTRS)
Kalb, M. W.
1985-01-01
Researchers achieved full implementation of the LAMPS mesoscale model on the Atmospheric Sciences Division computer and derived balanced and real wind initial states for three case studies: March 6, April 24, April 26, 1982. Numerical simulations were performed for three separate studies: (1) a satellite moisture data impact study using Vertical Atmospheric Sounder (VAS) precipitable water as a constraint on model initial state moisture analyses; (2) an evaluation of mesoscale model precipitation simulation accuracy with and without convective parameterization; and (3) the sensitivity of model precipitation to mesoscale detail of moisture and vertical motion in an initial state.
NASA Astrophysics Data System (ADS)
Kearney, Michael R.; Maino, James L.
2018-06-01
Accurate models of soil moisture are vital for solving core problems in meteorology, hydrology, agriculture and ecology. The capacity for soil moisture modelling is growing rapidly with the development of high-resolution, continent-scale gridded weather and soil data together with advances in modelling methods. In particular, the GlobalSoilMap.net initiative represents next-generation, depth-specific gridded soil products that may substantially increase soil moisture modelling capacity. Here we present an implementation of Campbell's infiltration and redistribution model within the NicheMapR microclimate modelling package for the R environment, and use it to assess the predictive power provided by the GlobalSoilMap.net product Soil and Landscape Grid of Australia (SLGA, ∼100 m) as well as the coarser resolution global product SoilGrids (SG, ∼250 m). Predictions were tested in detail against 3 years of root-zone (3-75 cm) soil moisture observation data from 35 monitoring sites within the OzNet project in Australia, with additional tests of the finalised modelling approach against cosmic-ray neutron (CosmOz, 0-50 cm, 9 sites from 2011 to 2017) and satellite (ASCAT, 0-2 cm, continent-wide from 2007 to 2009) observations. The model was forced by daily 0.05° (∼5 km) gridded meteorological data. The NicheMapR system predicted soil moisture to within experimental error for all data sets. Using the SLGA or the SG soil database, the OzNet soil moisture could be predicted with a root mean square error (rmse) of ∼0.075 m3 m-3 and a correlation coefficient (r) of 0.65 consistently through the soil profile without any parameter tuning. Soil moisture predictions based on the SLGA and SG datasets were ≈ 17% closer to the observations than when using a chloropleth-derived soil data set (Digital Atlas of Australian Soils), with the greatest improvements occurring for deeper layers. The CosmOz observations were predicted with similar accuracy (r = 0.76 and rmse of ∼0.085 m3 m-3). Comparisons at the continental scale to 0-2 cm satellite data (ASCAT) showed that the SLGA/SG datasets increased model fit over simulations using the DAAS soil properties (r ∼ 0.63 &rmse 15% vs. r 0.48 &rmse 18%, respectively). Overall, our results demonstrate the advantages of using GlobalSoilMap.net products in combination with gridded weather data for modelling soil moisture at fine spatial and temporal resolution at the continental scale.
Subsurface valleys and geoarcheology of the Eastern Sahara revealed by shuttle radar
McCauley, J.F.; Schaber, G.G.; Breed, C.S.; Grolier, M.J.; Haynes, C.V.; Issawi, B.; Elachi, C.; Blom, R.
1982-01-01
The shuttle imaging radar (SIR-A) carried on the space shuttle Columbia in November 1981 penetrated the extremely dry Selima Sand Sheet, dunes, and drift sand of the eastern Sahara, revealing previously unknown buried valleys, geologic structures, and possible Stone Age occupation sites. Radar responses from bedrock and gravel surfaces beneath windblown sand several centimeters to possibly meters thick delineate sand- and alluvium-filled valleys, some nearly as wide as the Nile Valley and perhaps as old as middle Tertiary. The nov-vanished maijor river systems that carved these large valleys probably accomplished most of the erosional stripping of this extraordinarily flat, hyperarid region. Underfit and incised dry wadis, many superimposed on the large valleys, represent erosion by intermittent running water, probably during Quaternary pluvials. Stone Age artifacts associated with soils in the alluvium suggest that areas near the wadis may have been sites of early human occupation. The presence of old drainage networks beneath the sand sheet provides a geologic explanation for the locations of many playas and present-day oases which have been centers of episodic human habitation. Radar penetration of dry sand and soils varies with the wavelength of the incident signals (24 centimeters for the SIR-A system), incidence angle, and the electrical properties of the materials, which are largely determined by moisture content. The calculated depth of radar penetration of dry sand and granules, based on laboratory measurements of the electrical properties of samples from the Selima Sand Sheet, is at least 5 meters. Recent (September 1982) field studies in Egypt verified SIR-A signal penetration depths of at least 1 meter in the Selima Sand Sheet and in drift sand and 2 or more meters in sand dunes. Copyright ?? 1982 AAAS.
Sensitivity of Land Surface Parameters on Thunderstorm Simulation through HRLDAS-WRF Coupling Mode
NASA Astrophysics Data System (ADS)
Kumar, Dinesh; Kumar, Krishan; Mohanty, U. C.; Kisore Osuri, Krishna
2016-07-01
Land surface characteristics play an important role in large scale, regional and mesoscale atmospheric process. Representation of land surface characteristics can be improved through coupling of mesoscale atmospheric models with land surface models. Mesoscale atmospheric models depend on Land Surface Models (LSM) to provide land surface variables such as fluxes of heat, moisture, and momentum for lower boundary layer evolution. Studies have shown that land surface properties such as soil moisture, soil temperature, soil roughness, vegetation cover, have considerable effect on lower boundary layer. Although, the necessity to initialize soil moisture accurately in NWP models is widely acknowledged, monitoring soil moisture at regional and global scale is a very tough task due to high spatial and temporal variability. As a result, the available observation network is unable to provide the required spatial and temporal data for the most part of the globe. Therefore, model for land surface initializations rely on updated land surface properties from LSM. The solution for NWP land-state initialization can be found by combining data assimilation techniques, satellite-derived soil data, and land surface models. Further, it requires an intermediate step to use observed rainfall, satellite derived surface insolation, and meteorological analyses to run an uncoupled (offline) integration of LSM, so that the evolution of modeled soil moisture can be forced by observed forcing conditions. Therefore, for accurate land-state initialization, high resolution land data assimilation system (HRLDAS) is used to provide the essential land surface parameters. Offline-coupling of HRLDAS-WRF has shown much improved results over Delhi, India for four thunder storm events. The evolution of land surface variables particularly soil moisture, soil temperature and surface fluxes have provided more realistic condition. Results have shown that most of domain part became wetter and warmer after assimilation of soil moisture and soil temperature at the initial condition which helped to improve the exchange fluxes at lower atmospheric level. Mixing ratio were increased along with elevated theta-e at lower level giving a signature of improvement in LDAS experiment leading to a suitable condition for convection. In the analysis, moisture convergence, mixing ratio and vertical velocities have improved significantly in terms of intensity and time lag. Surface variables like soil moisture, soil temperature, sensible heat flux and latent heat flux have progressed in a possible realistic pattern. Above discussion suggests that assimilation of soil moisture and soil temperature improves the overall simulations significantly.
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
Effects of moisture controlled charcoal on indoor thermal and air environments
NASA Astrophysics Data System (ADS)
Matsumoto, Hiroshi; Yokogoshi, Midori; Nabeshima, Yuki
2017-10-01
It is crucial to remove and control indoor moisture in Japan, especially in hot and humid summers, in order to improve thermal comfort and save energy in buildings. Charcoal for moisture control made from the waste of wood material has attracted attention among many control strategies to control indoor moisture, and it is beginning to be used in houses. However, the basic characteristics of the charcoal to control moisture and remove chemical compounds in indoor air have not been investigated sufficiently. The objective of this study is to clarify the effect of moisture control charcoal on indoor thermal and air environments by a long-term field measurement using two housing scale models with/without charcoal in Toyohashi, Japan. The comparative experiments to investigate the effect of the charcoal on air temperature and humidity for two models with/without charcoal were conducted from 2015 to 2016. Also, the removal performance of volatile organic compound (VOCs) was investigated in the summer of 2015. Four bags of packed charcoal were set on the floor in the attic for one model during the experiment. As a result of the experiments, a significant effect of moisture control was observed in hot and humid season, and the efficient effect of moisture adsorption was obtained by the periodic humidification experiment using a humidifier. Furthermore, the charcoal showed a remarkable performance of VOC removal from indoor air by the injection experiment of formaldehyde.
An overview of the measurements of soil moisture and modeling of moisture flux in FIFE
NASA Technical Reports Server (NTRS)
Wang, J. R.
1992-01-01
Measurements of soil moisture and calculations of moisture transfer in the soil medium and at the air-soil interface were performed over a 15-km by 15-km test site during FIFE in 1987 and 1989. The measurements included intensive soil moisture sampling at the ground level and surveys at aircraft altitudes by several passive and active microwave sensors as well as a gamma radiation device.
NASA Astrophysics Data System (ADS)
Seo, Eunkyo; Lee, Myong-In; Jeong, Jee-Hoon; Koster, Randal D.; Schubert, Siegfried D.; Kim, Hye-Mi; Kim, Daehyun; Kang, Hyun-Suk; Kim, Hyun-Kyung; MacLachlan, Craig; Scaife, Adam A.
2018-05-01
This study uses a global land-atmosphere coupled model, the land-atmosphere component of the Global Seasonal Forecast System version 5, to quantify the degree to which soil moisture initialization could potentially enhance boreal summer surface air temperature forecast skill. Two sets of hindcast experiments are performed by prescribing the observed sea surface temperature as the boundary condition for a 15-year period (1996-2010). In one set of the hindcast experiments (noINIT), the initial soil moisture conditions are randomly taken from a long-term simulation. In the other set (INIT), the initial soil moisture conditions are taken from an observation-driven offline Land Surface Model (LSM) simulation. The soil moisture conditions from the offline LSM simulation are calibrated using the forecast model statistics to minimize the inconsistency between the LSM and the land-atmosphere coupled model in their mean and variability. Results show a higher boreal summer surface air temperature prediction skill in INIT than in noINIT, demonstrating the potential benefit from an accurate soil moisture initialization. The forecast skill enhancement appears especially in the areas in which the evaporative fraction—the ratio of surface latent heat flux to net surface incoming radiation—is sensitive to soil moisture amount. These areas lie in the transitional regime between humid and arid climates. Examination of the extreme 2003 European and 2010 Russian heat wave events reveal that the regionally anomalous soil moisture conditions during the events played an important role in maintaining the stationary circulation anomalies, especially those near the surface.
Comparison of experimental data with results of some drying models for regularly shaped products
NASA Astrophysics Data System (ADS)
Kaya, Ahmet; Aydın, Orhan; Dincer, Ibrahim
2010-05-01
This paper presents an experimental and theoretical investigation of drying of moist slab, cylinder and spherical products to study dimensionless moisture content distributions and their comparisons. Experimental study includes the measurement of the moisture content distributions of slab and cylindrical carrot, slab and cylindrical pumpkin and spherical blueberry during drying at various temperatures (e.g., 30, 40, 50 and 60°C) at specific constant velocity ( U = 1 m/s) and the relative humidity φ = 30%. In theoretical analysis, two moisture transfer models are used to determine drying process parameters (e.g., drying coefficient and lag factor) and moisture transfer parameters (e.g., moisture diffusivity and moisture transfer coefficient), and to calculate the dimensionless moisture content distributions. The calculated results are then compared with the experimental moisture data. A considerably high agreement is obtained between the calculations and experimental measurements for the cases considered. The effective diffusivity values were evaluated between 0.741 × 10-5 and 5.981 × 10-5 m2/h for slab products, 0.818 × 10-5 and 6.287 × 10-5 m2/h for cylindrical products and 1.213 × 10-7 and 7.589 × 10-7 m2/h spherical products using the Model-I and 0.316 × 10-5-5.072 × 10-5 m2/h for slab products, 0.580 × 10-5-9.587 × 10-5 m2/h for cylindrical products and 1.408 × 10-7-13.913 × 10-7 m2/h spherical products using the Model-II.
NASA Technical Reports Server (NTRS)
Baker, David R.; Lynn, Barry H.; Boone, Aaron; Tao, Wei-Kuo; Simpson, Joanne
2000-01-01
Idealized numerical simulations are performed with a coupled atmosphere/land-surface model to identify the roles of initial soil moisture, coastline curvature, and land breeze circulations on sea breeze initiated precipitation. Data collected on 27 July 1991 during the Convection and Precipitation Electrification Experiment (CAPE) in central Florida are used. The 3D Goddard Cumulus Ensemble (GCE) cloud resolving model is coupled with the Goddard Parameterization for Land-Atmosphere-Cloud Exchange (PLACE) land surface model, thus providing a tool to simulate more realistically land-surface/atmosphere interaction and convective initiation. Eight simulations are conducted with either straight or curved coast-lines, initially homogeneous soil moisture or initially variable soil moisture, and initially homogeneous horizontal winds or initially variable horizontal winds (land breezes). All model simulations capture the diurnal evolution and general distribution of sea-breeze initiated precipitation over central Florida. The distribution of initial soil moisture influences the timing, intensity and location of subsequent precipitation. Soil moisture acts as a moisture source for the atmosphere, increases the connectively available potential energy, and thus preferentially focuses heavy precipitation over existing wet soil. Strong soil moisture-induced mesoscale circulations are not evident in these simulations. Coastline curvature has a major impact on the timing and location of precipitation. Earlier low-level convergence occurs inland of convex coastlines, and subsequent precipitation occurs earlier in simulations with curved coastlines. The presence of initial land breezes alone has little impact on subsequent precipitation. however, simulations with both coastline curvature and initial land breezes produce significantly larger peak rain rates due to nonlinear interactions.
Western US high June 2015 temperatures and their relation to global warming and soil moisture
NASA Astrophysics Data System (ADS)
Philip, Sjoukje Y.; Kew, Sarah F.; Hauser, Mathias; Guillod, Benoit P.; Teuling, Adriaan J.; Whan, Kirien; Uhe, Peter; Oldenborgh, Geert Jan van
2018-04-01
The Western US states Washington (WA), Oregon (OR) and California (CA) experienced extremely high temperatures in June 2015. The temperature anomalies were so extreme that they cannot be explained with global warming alone. We investigate the hypothesis that soil moisture played an important role as well. We use a land surface model and a large ensemble from the weather@home modelling effort to investigate the coupling between soil moisture and temperature in a warming world. Both models show that May was anomalously dry, satisfying a prerequisite for the extreme heat wave, and they indicate that WA and OR are in a wet-to-dry transitional soil moisture regime. We use two different land surface-atmosphere coupling metrics to show that there was strong coupling between temperature, latent heat flux and the effect of soil moisture deficits on the energy balance in June 2015 in WA and OR. June temperature anomalies conditioned on wet/dry conditions show that both the mean and extreme temperatures become hotter for dry soils, especially in WA and OR. Fitting a Gaussian model to temperatures using soil moisture as a covariate shows that the June 2015 temperature values fit well in the extrapolated empirical temperature/drought lines. The high temperature anomalies in WA and OR are thus to be expected, given the dry soil moisture conditions and that those regions are in the transition from a wet to a dry regime. CA is already in the dry regime and therefore the necessity of taking soil moisture into account is of lower importance.
Modeling of the Assiniboine Delta Aquifer (ADA) of Manitoba using the Groundwater Storage from GRACE
NASA Astrophysics Data System (ADS)
Yirdaw-Zeleke, S.; Snelgrove, K.
2007-12-01
This paper investigates the use of GRACE (Gravity Recovery and Climate Experiment) moisture storages for modeling of the Assiniboine Delta Aquifer (ADA) of Manitoba, Canada. There are great promises from GRACE in capturing regional groundwater storages that are potentially used for modeling application. However, it is well known that these storages are difficult to measure over the scales needed for hydrological model applications. Therefore, prior to modeling the aquifer using GRACE moisture storages, the storages need to be downscaled in to regional groundwater storages using the measured groundwater head data available in the area. Previous studies in the ADA have shown that the downscaled moisture storage estimates compared favorably with the measured groundwater storage over the area. This study focuses on the modeling of the ADA aquifer using the downscaled GRACE moisture storages. These storages will be used to initialize, calibration and potentially steer the hydrologic simulation. The calibrated model then will be validated independently using the measured data. These validations will hopefully provide better explanations for the underlying reasons for the differences in model predictions and measurements. This will identify some of the key assumptions and uncertainties in predicting moisture storage, and so highlight topics for further discussion and research.
Seasonal-to-Interannual Variability and Land Surface Processes
NASA Technical Reports Server (NTRS)
Koster, Randal
2004-01-01
Atmospheric chaos severely limits the predictability of precipitation on subseasonal to interannual timescales. Hope for accurate long-term precipitation forecasts lies with simulating atmospheric response to components of the Earth system, such as the ocean, that can be predicted beyond a couple of weeks. Indeed, seasonal forecasts centers now rely heavily on forecasts of ocean circulation. Soil moisture, another slow component of the Earth system, is relatively ignored by the operational seasonal forecasting community. It is starting, however, to garner more attention. Soil moisture anomalies can persist for months. Because these anomalies can have a strong impact on evaporation and other surface energy fluxes, and because the atmosphere may respond consistently to anomalies in the surface fluxes, an accurate soil moisture initialization in a forecast system has the potential to provide additional forecast skill. This potential has motivated a number of atmospheric general circulation model (AGCM) studies of soil moisture and its contribution to variability in the climate system. Some of these studies even suggest that in continental midlatitudes during summer, oceanic impacts on precipitation are quite small relative to soil moisture impacts. The model results, though, are strongly model-dependent, with some models showing large impacts and others showing almost none at all. A validation of the model results with observations thus naturally suggests itself, but this is exceedingly difficult. The necessary contemporaneous soil moisture, evaporation, and precipitation measurements at the large scale are virtually non-existent, and even if they did exist, showing statistically that soil moisture affects rainfall would be difficult because the other direction of causality - wherein rainfall affects soil moisture - is unquestionably active and is almost certainly dominant. Nevertheless, joint analyses of observations and AGCM results do reveal some suggestions of land-atmosphere feedback in the observational record, suggestions that soil moisture can affect precipitation over seasonal timescales and across certain large continental areas. The strength of this observed feedback in nature is not large but is still significant enough to be potentially useful, e.g., for forecasts. This talk will address all of these issues. It will begin with a brief overview of land surface modeling in atmospheric models but will then focus on recent research - using both observations and models - into the impact of land surface processes on variability in the climate system.
Simha, H V Vikram; Pushpadass, Heartwin A; Franklin, Magdaline Eljeeva Emerald; Kumar, P Arun; Manimala, K
2016-06-01
Moisture sorption isotherms of spray-dried milk-foxtail millet powder were determined at 10, 25 and 40 °C. Sorption data was fitted using classical and soft-computing approaches. The isotherms were of type II, and equilibrium moisture content (EMC) was temperature dependent. The BET monolayer moisture content decreased from 3.30 to 2.67 % as temperature increased from 10 to 40 °C. Amongst the classical models, Ferro-Fontan gave the best fit of EMC-aw data. However, the Sugeno-type adaptive neuro-fuzzy inference system (ANFIS) with generalized bell-shaped membership function performed better than artificial neural network and classical models with RMSE as low as 0.0099. The isosteric heat of sorption decreased from 150.32 kJ mol(-1) at 1 % moisture content to 44.11 kJ mol(-1) at 15 % moisture. The enthalpy-entropy compensation theory was validated, and the isokinetic and harmonic mean temperatures were determined as 333.1 and 297.5 K, respectively.
Experimental evidence and modelling of drought induced alternative stable soil moisture states
NASA Astrophysics Data System (ADS)
Robinson, David; Jones, Scott; Lebron, Inma; Reinsch, Sabine; Dominguez, Maria; Smith, Andrew; Marshal, Miles; Emmett, Bridget
2017-04-01
The theory of alternative stable states in ecosystems is well established in ecology; however, evidence from manipulation experiments supporting the theory is limited. Developing the evidence base is important because it has profound implications for ecosystem management. Here we show evidence of the existence of alternative stable soil moisture states induced by drought in an upland wet heath. We used a long-term (15 yrs) climate change manipulation experiment with moderate sustained drought, which reduced the ability of the soil to retain soil moisture by degrading the soil structure, reducing moisture retention. Moreover, natural intense droughts superimposed themselves on the experiment, causing an unexpected additional alternative soil moisture state to develop, both for the drought manipulation and control plots; this impaired the soil from rewetting in winter. Our results show the coexistence of three stable states. Using modelling with the Hydrus 1D software package we are able to show the circumstances under which shifts in soil moisture states are likely to occur. Given the new understanding it presents a challenge of how to incorporate feedbacks, particularly related to soil structure, into soil flow and transport models?
NASA Astrophysics Data System (ADS)
Kara, Cem; Doymaz, İbrahim
2015-07-01
Drying of apple pomace representing by-products from apple juice processing was studied. The results obtained show that moisture content of the pomace decreases with time and temperature. The Midilli et al. model was selected as the best mathematical model for describing the drying kinetics of the apple pomace. The effective moisture diffusivity varied from 1.73 × 10-10 to 4.40 × 10-10 m2/s and the activation energy was calculated to be 29.65 kJ/mol.
Adeeb A. Rahman; Thomas J. Urbanik; Mustafa Mahamid
2003-01-01
Collapse of fiberboard packaging boxes, in the shipping industry, due to rise in humidity conditions is common and very costly. A 3D FE nonlinear model is developed to predict the moisture flow throughout a corrugated packaging fiberboard sandwich structure. The model predicts how the moisture diffusion will permeate through the layers of a fiberboard (medium and...
Validation of SMAP soil moisture for the SMAPVEX15 field campaign using a hyper-resolution model
USDA-ARS?s Scientific Manuscript database
Accurate global mapping of soil moisture is the goal of the Soil Moisture Active Passive (SMAP) mission, which is expected to improve the estimation of water, energy, and carbon exchanges between the land and the atmosphere. Like other satellite products, the SMAP soil moisture retrievals need to be...
NASA Astrophysics Data System (ADS)
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 cool-season water availability, with potentially important consequences for ecosystem structure and function. These results provide a framework for coping with variability in climate projections and assessing climate change impacts on dryland ecosystems.
Evaluation of a Soil Moisture Data Assimilation System Over the Conterminous United States
NASA Astrophysics Data System (ADS)
Bolten, J. D.; Crow, W. T.; Zhan, X.; Reynolds, C. A.; Jackson, T. J.
2008-12-01
A data assimilation system has been designed to integrate surface soil moisture estimates from the EOS Advanced Microwave Scanning Radiometer (AMSR-E) with an online soil moisture model used by the USDA Foreign Agriculture Service for global crop estimation. USDA's International Production Assessment Division (IPAD) of the Office of Global Analysis (OGA) ingests global soil moisture within a Crop Assessment Data Retrieval and Evaluation (CADRE) Decision Support System (DSS) to provide nowcasts of crop conditions and agricultural-drought. This information is primarily used to derive mid-season crop yield estimates for the improvement of foreign market access for U.S. agricultural products. The CADRE is forced by daily meteorological observations (precipitation and temperature) provided by the Air Force Weather Agency (AFWA) and World Meteorological Organization (WMO). The integration of AMSR-E observations into the two-layer soil moisture model employed by IPAD can potentially enhance the reliability of the CADRE soil moisture estimates due to AMSR-E's improved repeat time and greater spatial coverage. Assimilation of the AMSR-E soil moisture estimates is accomplished using a 1-D Ensemble Kalman filter (EnKF) at daily time steps. A diagnostic calibration of the filter is performed using innovation statistics by accurately weighting the filter observation and modeling errors for three ranges of vegetation biomass density estimated using historical data from the Advanced Very High Resolution Radiometer (AVHRR). Assessment of the AMSR-E assimilation has been completed for a five year duration over the conterminous United States. To evaluate the ability of the filter to compensate for incorrect precipitation forcing into the model, a data denial approach is employed by comparing soil moisture results obtained from separate model simulations forced with precipitation products of varying uncertainty. An analysis of surface and root-zone anomalies is presented for each model simulation over the conterminous United States, as well as statistical assessments for each simulation over various land cover types.
NASA Astrophysics Data System (ADS)
Dominguez, Francina
This study is the first to analyze the mechanisms that drive precipitation recycling variability at the daily to intraseasonal timescale. A new Dynamic Precipitation Recycling model is developed which, unlike previous models, includes the moisture storage term in the equation of conservation of atmospheric moisture. As shown using scaling analysis, the moisture storage term is non-negligible at small time scales, so the new model enables us to analyze precipitation recycling variability at shorter timescales than traditional models. The daily to intraseasonal analysis enables us to uncover key relationships between recycling and the moisture and energy fluxes. In the second phase of this work, a spatiotemporal analysis of daily precipitation recycling is performed over two regions of North America: the Midwestern United States, and the North American Monsoon System (NAMS) region. These regions were chosen because they present contrasting land-atmosphere interactions. Different physical mechanisms drive precipitation recycling in each region. In the Midwestern United States, evapotranspiration is not significantly affected by soil moisture anomalies, and there is a high recycling ratio during periods of reduced total precipitation. The reason is that, during periods of drier atmospheric conditions, transpiration will continue to provide moisture to the overlying atmosphere and contribute to total rainfall. Consequently, precipitation recycling variability in not driven by changes in evapotranspiration. Precipitable water, sensible heat and moisture fluxes are the main drivers of recycling variability in the Midwest. However, the drier soil moisture conditions over the NAMS region limit evapotranspiration, which will drive recycling variability. In this region, evapotranspiration becomes an important contribution to precipitation after Monsoon onset when total precipitation and evapotranspiration are highest. The precipitation recycling process in the NAMS region relocates moisture from regions of high evapotranspiration like the seasonally dry tropical forests of Mexico to drier regions downwind. During long monsoons, when soil moisture is abundant for a prolonged period of time, precipitation recycling significantly contributes to precipitation during periods of reduced total rainfall. In both the moisture abundant Midwestern region and the drier NAMS region, precipitation recycling plays an important role in maintaining a favorable hydroclimatological environment for vegetation.
NASA Astrophysics Data System (ADS)
Khedun, C. P.; Mishra, A. K.; Bolten, J. D.; Giardino, J. R.; Singh, V. P.
2010-12-01
Soil moisture is an important component of the hydrological cycle. Climate variability patterns, such as the Pacific Decadal Oscillation (PDO), El Niño Southern Oscillation (ENSO), and Atlantic Multidecadal Oscillation (AMO) are determining factors on surface water availability and soil moisture. Understanding this complex relationship and the phase and lag times between climate events and soil moisture variability is important for agricultural management and water planning. In this study we look at the effect of these climate teleconnection patterns on the soil moisture across the Rio Grande/Río Bravo del Norte basin. The basin is transboundary between the US and Mexico and has a varied climatology - ranging from snow dominated in its headwaters in Colorado, to an arid and semi-arid region in its middle reach and a tropical climate in the southern section before it discharges into the Gulf of Mexico. Agricultural activities in the US and in northern Mexico are highly dependent on the Rio Grande and are extremely vulnerable to climate extremes. The treaty between the two countries does not address climate related events. The soil moisture is generated using the community NOAH land surface model (LSM). The LSM is a 1-D column model that runs in coupled or uncoupled mode, and it simulates soil moisture, soil temperature, skin temperature, snowpack depth, snow water equivalent, canopy water content, and energy flux and water flux of the surface energy and water balance. The North American Land Data Assimilation Scheme 2 (NLDAS2) is used to drive the model. The model is run for the period 1979 to 2009. The soil moisture output is validated against measured values from the different Soil Climate Analysis Network (SCAN) sites within the basin. The spatial and temporal variability of the modeled soil moisture is then analyzed using marginal entropy to investigate monthly, seasonal, and annual variability. Wavelet transform is used to determine the relation, phase difference, and lag times between climate teleconnection events and soil moisture. The results from this study will help agricultural scientists and water planners in both the US and Mexico in better managing the dwindling water resources of this transboundary basin.
Inherent limitations of nondestructive chlorophyll meters: a comparison of two types of meters
NASA Technical Reports Server (NTRS)
Monje, O. A.; Bugbee, B.
1992-01-01
Two types of nondestructive chlorophyll meters were compared with a standard, destructive chlorophyll measurement technique. The nondestructive chlorophyll meters were 1) a custom built, single-wavelength meter, and 2) the recently introduced, dual-wavelengh, chlorophyll meter from Minolta (model SPAD-502). Data from both meters were closely correlated with destructive measurements of chlorophyll (r2 = 0.90 and 0.93; respectively) for leaves with chlorophyll concentrations ranging from 100 to 600 mg m-2, but both meters consistently overestimated chlorophyll outside this range. Although the dual-wavelength meter was slightly more accurate than the single-wavelength meter (higher r2), the light-scattering properties of leaf cells and the nonhomogeneous distribution of chlorophyll in leaves appear to limit the ability of all meters to estimate in vivo chlorophyll concentration.
Accuracy of Cycling Power Meters against a Mathematical Model of Treadmill Cycling.
Maier, Thomas; Schmid, Lucas; Müller, Beat; Steiner, Thomas; Wehrlin, Jon Peter
2017-06-01
The aim of this study was to compare the accuracy among a high number of current mobile cycling power meters used by elite and recreational cyclists against a first principle-based mathematical model of treadmill cycling. 54 power meters from 9 manufacturers used by 32 cyclists were calibrated. While the cyclist coasted downhill on a motorised treadmill, a back-pulling system was adjusted to counter the downhill force. The system was then loaded 3 times with 4 different masses while the cyclist pedalled to keep his position. The mean deviation (trueness) to the model and coefficient of variation (precision) were analysed. The mean deviations of the power meters were -0.9±3.2% (mean±SD) with 6 power meters deviating by more than±5%. The coefficients of variation of the power meters were 1.2±0.9% (mean±SD), with Stages varying more than SRM (p<0.001) and PowerTap (p<0.001). In conclusion, current power meters used by elite and recreational cyclists vary considerably in their trueness; precision is generally high but differs between manufacturers. Calibrating and adjusting the trueness of every power meter against a first principle-based reference is advised for accurate measurements. © Georg Thieme Verlag KG Stuttgart · New York.
Developing a model for moisture in saltcake waste tanks: Progress report
DOE Office of Scientific and Technical Information (OSTI.GOV)
Simmons, C.S.; Aimo, N.; Fayer, M.J.
1997-07-01
This report describes a modeling effort to provide a computer simulation capability for estimating the distribution and movement of moisture in the saltcake-type waste contained in Hanford`s single-shell radioactive waste storage tanks. This moisture model goes beyond an earlier version because it describes water vapor movement as well as the interstitial liquid held in a saltcake waste. The work was performed by Pacific Northwest National Laboratory to assist Duke Engineering and Services Hanford with the Organic Tank Safety Program. The Organic Tank Safety Program is concerned whether saltcake waste, when stabilized by jet pumping, will retain sufficient moisture near themore » surface to preclude any possibility of an accidental ignition and propagation of burning. The nitrate/nitrite saltcake, which might also potentially include combustible organic chemicals might not always retain enough moisture near the surface to preclude any such accident. Draining liquid from a tank by pumping, coupled with moisture evaporating into a tank`s head space, may cause a dry waste surface that is not inherently safe. The moisture model was devised to help examine this safety question. The model accounts for water being continually cycled by evaporation into the head space and returned to the waste by condensation or partly lost through venting to the external atmosphere. Water evaporation occurs even in a closed tank, because it is driven by the transfer to the outside of the heat load generated by radioactivity within the waste. How dry a waste may become over time depends on the particular hydraulic properties of a saltcake, and the model uses those properties to describe the capillary flow of interstitial liquid as well as the water vapor flow caused by thermal differences within the porous waste.« less
Trends in soil moisture and real evapotranspiration in Douro River for the period 1980-2010
NASA Astrophysics Data System (ADS)
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).
Patz, J A; Strzepek, K; Lele, S; Hedden, M; Greene, S; Noden, B; Hay, S I; Kalkstein, L; Beier, J C
1998-10-01
While malaria transmission varies seasonally, large inter-annual heterogeneity of malaria incidence occurs. Variability in entomological parameters, biting rates and entomological inoculation rates (EIR) have been strongly associated with attack rates in children. The goal of this study was to assess the weather's impact on weekly biting and EIR in the endemic area of Kisian, Kenya. Entomological data collected by the U.S. Army from March 1986 through June 1988 at Kisian, Kenya was analysed with concurrent weather data from nearby Kisumu airport. A soil moisture model of surface-water availability was used to combine multiple weather parameters with landcover and soil features to improve disease prediction. Modelling soil moisture substantially improved prediction of biting rates compared to rainfall; soil moisture lagged two weeks explained up to 45% of An. gambiae biting variability, compared to 8% for raw precipitation. For An. funestus, soil moisture explained 32% variability, peaking after a 4-week lag. The interspecies difference in response to soil moisture was significant (P < 0.00001). A satellite normalized differential vegetation index (NDVI) of the study site yielded a similar correlation (r = 0.42 An. gambiae). Modelled soil moisture accounted for up to 56% variability of An. gambiae EIR, peaking at a lag of six weeks. The relationship between temperature and An. gambiae biting rates was less robust; maximum temperature r2 = -0.20, and minimum temperature r2 = 0.12 after lagging one week. Benefits of hydrological modelling are compared to raw weather parameters and to satellite NDVI. These findings can improve both current malaria risk assessments and those based on El Niño forecasts or global climate change model projections.
NASA Technical Reports Server (NTRS)
Carlson, Toby N.
1988-01-01
Using model development, image analysis and micrometeorological measurements, the object is to push beyond the present limitations of using the infrared temperature method for remotely determining surface energy fluxes and soil moisture over vegetation. Model development consists of three aspects: (1) a more complex vegetation formulation which is more flexible and realistic; (2) a method for modeling the fluxes over patchy vegetation cover; and (3) a method for inferring a two-layer soil vertical moisture gradient from analyses of horizontal variations in surface temperatures. HAPEX and FIFE satellite data will be used along with aircraft thermal infrared and solar images as input for the models. To test the models, moisture availability and bulk canopy resistances will be calculated from data collected locally at the Rock Springs experimental field site and, eventually, from the FIFE project.
NASA Astrophysics Data System (ADS)
van Wesemael, Bas; Nocita, Marco
2016-04-01
One of the problems for mapping of soil organic carbon (SOC) at large-scale based on visible - near and short wave infrared (VIS-NIR-SWIR) remote sensing techniques is the spatial variation of topsoil moisture when the images are collected. Soil moisture is certainly an aspect causing biased SOC estimations, due to the problems in discriminating reflectance differences due to either variations in organic matter or soil moisture, or their combination. In addition, the difficult validation procedures make the accurate estimation of soil moisture from optical airborne a major challenge. After all, the first millimeters of the soil surface reflect the signal to the airborne sensor and show a large spatial, vertical and temporal variation in soil moisture. Hence, the difficulty of assessing the soil moisture of this thin layer at the same moment of the flight. The creation of a soil moisture proxy, directly retrievable from the hyperspectral data is a priority to improve the large-scale prediction of SOC. This paper aims to verify if the application of the normalized soil moisture index (NSMI) to Airborne Prima Experiment (APEX) hyperspectral images could improve the prediction of SOC. The study area was located in the loam region of Wallonia, Belgium. About 40 samples were collected from bare fields covered by the flight lines, and analyzed in the laboratory. Soil spectra, corresponding to the sample locations, were extracted from the images. Once the NSMI was calculated for the bare fields' pixels, spatial patterns, presumably related to within field soil moisture variations, were revealed. SOC prediction models, built using raw and pre-treated spectra, were generated from either the full dataset (general model), or pixels belonging to one of the two classes of NSMI values (NSMI models). The best result, with a RMSE after validation of 1.24 g C kg-1, was achieved with a NSMI model, compared to the best general model, characterized by a RMSE of 2.11 g C kg-1. These results confirmed the advantage to controlling the effect of soil moisture on the detection of SOC. The NSMI proved to be a flexible concept, due to the possible use of different SWIR wavelengths, and ease of use, because measurements of soil moisture by other techniques are not needed. However, in the future, it will be important to assess the effectiveness of the NSMI for different soil types, and other hyperspectral sensors.
Further experimentation on bubble generation during transformer overload
DOE Office of Scientific and Technical Information (OSTI.GOV)
Oommen, T.V.
1992-03-01
This report covers additional work done during 1990 and 1991 on gas bubble generation under overload conditions. To improve visual bubble detection, a single disc coil was used. To further improve detection, a corona device was also used which signaled the onset of corona activity in the early stages of bubble formation. A total of fourteen model tests were conducted, half of which used the Inertaire system, and the remaining, a conservator (COPS). Moisture content of paper in the coil varied from 1.0% to 8.0%; gas (nitrogen) content varied from 1.0% to 8.8%. The results confirmed earlier observations that themore » mathematical bubble prediction model was not valid for high gas content model with relatively low moisture levels in the coil. An empirical relationship was formulated to accurately predict bubble evolution temperatures from known moisture and gas content values. For low moisture content models (below 2%), the simple Piper relationship was sufficient to predict bubble evolution temperatures, regardless of gas content. Moisture in the coil appears to be the key factor in bubble generation. Gas blanketed (Inertaire) systems do not appear to be prone to premature bubble generation from overloads as previously thought. The new bubble prediction model reveals that for a coil with 2% moisture, the bubble evolution temperature would be about 140{degrees}C. Since old transformers in service may have as much as 2% moisture in paper, the 140{degrees}C bubble evolution temperature may be taken as the lower limit of bubble evolution temperature under overload conditions for operating transformers. Drier insulation would raise the bubble evolution temperature.« less
SMAP Data Assimilation at NASA SPoRT
NASA Technical Reports Server (NTRS)
Blankenship, Clay B.; Case, Jonathan L.; Zavodsky, Bradley T.
2016-01-01
The NASA Short-Term Prediction Research and Transition (SPoRT) Center maintains a near-real- time run of the Noah Land Surface Model within the Land Information System (LIS) at 3-km resolution. Soil moisture products from this model are used by several NOAA/National Weather Service Weather Forecast Offices for flood and drought situational awareness. We have implemented assimilation of soil moisture retrievals from the Soil Moisture Ocean Salinity (SMOS) and Soil Moisture Active/ Passive (SMAP) satellites, and are now evaluating the SMAP assimilation. The SMAP-enhanced LIS product is planned for public release by October 2016.
Downscaling SMAP Soil Moisture Using Geoinformation Data and Geostatistics
NASA Astrophysics Data System (ADS)
Xu, Y.; Wang, L.
2017-12-01
Soil moisture is important for agricultural and hydrological studies. However, ground truth soil moisture data for wide area is difficult to achieve. Microwave remote sensing such as Soil Moisture Active Passive (SMAP) can offer a solution for wide coverage. However, existing global soil moisture products only provide observations at coarse spatial resolutions, which often limit their applications in regional agricultural and hydrological studies. This paper therefore aims to generate fine scale soil moisture information and extend soil moisture spatial availability. A statistical downscaling scheme is presented that incorporates multiple fine scale geoinformation data into the downscaling of coarse scale SMAP data in the absence of ground measurement data. Geoinformation data related to soil moisture patterns including digital elevation model (DEM), land surface temperature (LST), land use and normalized difference vegetation index (NDVI) at a fine scale are used as auxiliary environmental variables for downscaling SMAP data. Generalized additive model (GAM) and regression tree are first conducted to derive statistical relationships between SMAP data and auxiliary geoinformation data at an original coarse scale, and residuals are then downscaled to a finer scale via area-to-point kriging (ATPK) by accounting for the spatial correlation information of the input residuals. The results from standard validation scores as well as the triple collocation (TC) method against soil moisture in-situ measurements show that the downscaling method can significantly improve the spatial details of SMAP soil moisture while maintain the accuracy.
Global response of the growing season to soil moisture and topography
NASA Astrophysics Data System (ADS)
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.
Lai, K P K; Dolan, K D; Ng, P K W
2009-06-01
Thermal and moisture effects on grape anthocyanin degradation were investigated using solid media to simulate processing at temperatures above 100 degrees C. Grape pomace (anthocyanin source) mixed with wheat pastry flour (1: 3, w/w dry basis) was used in both isothermal and nonisothermal experiments by heating the same mixture at 43% (db) initial moisture in steel cells in an oil bath at 80, 105, and 145 degrees C. To determine the effect of moisture on anthocyanin degradation, the grape pomace-wheat flour mixture was heated isothermally at 80 degrees C at constant moisture contents of 10%, 20%, and 43% (db). Anthocyanin degradation followed a pseudo first-order reaction with moisture. Anthocyanins degraded more rapidly with increasing temperature and moisture. The effects of temperature and moisture on the rate constant were modeled according to the Arrhenius and an exponential relationship, respectively. The nonisothermal reaction rate constant and activation energy (mean +/- standard error) were k(80 degrees C, 43% (db) moisture) = 2.81 x 10(-4)+/- 1.1 x 10(-6) s(-1) and DeltaE = 75273 +/- 197 J/g mol, respectively. The moisture parameter for the exponential model was 4.28 (dry basis moisture content)(-1). One possible application of this study is as a tool to predict the loss of anthocyanins in nutraceutical products containing grape pomace. For example, if the process temperature history and moisture history in an extruded snack fortified with grape pomace is known, the percentage anthocyanin loss can be predicted.
NASA Astrophysics Data System (ADS)
Goodchild, Martin; Janes, Stuart; Jenkins, Malcolm; Nicholl, Chris; Kühn, Karl
2015-04-01
The aim of this work is to assess the use of temperature corrected substrate moisture data to improve the relationship between environmental drivers and the measurement of substrate moisture content in high porosity soil-free growing environments such as coir. Substrate moisture sensor data collected from strawberry plants grown in coir bags installed in a table-top system under a polytunnel illustrates the impact of temperature on capacitance-based moisture measurements. Substrate moisture measurements made in our coir arrangement possess the negative temperature coefficient of the permittivity of water where diurnal changes in moisture content oppose those of substrate temperature. The diurnal substrate temperature variation was seen to range from 7° C to 25° C resulting in a clearly observable temperature effect in substrate moisture content measurements during the 23 day test period. In the laboratory we measured the ML3 soil moisture sensor (ThetaProbe) response to temperature in Air, dry glass beads and water saturated glass beads and used a three-phase alpha (α) mixing model, also known as the Complex Refractive Index Model (CRIM), to derive the permittivity temperature coefficients for glass and water. We derived the α value and estimated the temperature coefficient for water - for sensors operating at 100MHz. Both results are good agreement with published data. By applying the CRIM equation with the temperature coefficients of glass and water the moisture temperature coefficient of saturated glass beads has been reduced by more than an order of magnitude to a moisture temperature coefficient of
NASA Astrophysics Data System (ADS)
Cowley, Garret S.; Niemann, Jeffrey D.; Green, Timothy R.; Seyfried, Mark S.; Jones, Andrew S.; Grazaitis, Peter J.
2017-02-01
Soil moisture can be estimated at coarse resolutions (>1 km) using satellite remote sensing, but that resolution is poorly suited for many applications. The Equilibrium Moisture from Topography, Vegetation, and Soil (EMT+VS) model downscales coarse-resolution soil moisture using fine-resolution topographic, vegetation, and soil data to produce fine-resolution (10-30 m) estimates of soil moisture. The EMT+VS model performs well at catchments with low topographic relief (≤124 m), but it has not been applied to regions with larger ranges of elevation. Large relief can produce substantial variations in precipitation and potential evapotranspiration (PET), which might affect the fine-resolution patterns of soil moisture. In this research, simple methods to downscale temporal average precipitation and PET are developed and included in the EMT+VS model, and the effects of spatial variations in these variables on the surface soil moisture estimates are investigated. The methods are tested against ground truth data at the 239 km2 Reynolds Creek watershed in southern Idaho, which has 1145 m of relief. The precipitation and PET downscaling methods are able to capture the main features in the spatial patterns of both variables. The space-time Nash-Sutcliffe coefficients of efficiency of the fine-resolution soil moisture estimates improve from 0.33 to 0.36 and 0.41 when the precipitation and PET downscaling methods are included, respectively. PET downscaling provides a larger improvement in the soil moisture estimates than precipitation downscaling likely because the PET pattern is more persistent through time, and thus more predictable, than the precipitation pattern.
NASA Astrophysics Data System (ADS)
Hamed Alemohammad, Seyed; Kolassa, Jana; Prigent, Catherine; Aires, Filipe; Gentine, Pierre
2017-04-01
Knowledge of root zone soil moisture is essential in studying plant's response to different stress conditions since plant photosynthetic activity and transpiration rate are constrained by the water available through their roots. Current global root zone soil moisture estimates are based on either outputs from physical models constrained by observations, or assimilation of remotely-sensed microwave-based surface soil moisture estimates with physical model outputs. However, quality of these estimates are limited by the accuracy of the model representations of physical processes (such as radiative transfer, infiltration, percolation, and evapotranspiration) as well as errors in the estimates of the surface parameters. Additionally, statistical approaches provide an alternative efficient platform to develop root zone soil moisture retrieval algorithms from remotely-sensed observations. In this study, we present a new neural network based retrieval algorithm to estimate surface and root zone soil moisture from passive microwave observations of SMAP satellite (L-band) and AMSR2 instrument (X-band). SMAP early morning observations are ideal for surface soil moisture retrieval. AMSR2 mid-night observations are used here as an indicator of plant hydraulic properties that are related to root zone soil moisture. The combined observations from SMAP and AMSR2 together with other ancillary observations including the Solar-Induced Fluorescence (SIF) estimates from GOME-2 instrument provide necessary information to estimate surface and root zone soil moisture. The algorithm is applied to observations from the first 18 months of SMAP mission and retrievals are validated against in-situ observations and other global datasets.
Transpiration-driven aridification of the American West in 21st-Century model projections
NASA Astrophysics Data System (ADS)
Mankin, J. S.; Smerdon, J. E.; Cook, B.; Williams, P.; Seager, R.
2016-12-01
Climate models project significant 21st-Century declines in soil moisture and runoff over the American West from anthropogenic climate change, but the associated physical mechanisms are poorly characterized. In particular, there are significant uncertainties regarding the modulation of evaporative losses by vegetation and how the physical determinants (i.e., changes in moisture supply and demand) of future surface moisture balance will vary in time, space, and depth in the soil. Using 35-members of the NCAR CESM large ensemble (LENS) and 1800 years of its pre-industrial control simulation, we examine the response of Western surface moisture balance (soil moisture and runoff) to anthropogenic forcing. Declines in runoff and soil moisture are forced primarily by robust increases in evapotranspiration (from increased plant transpiration and canopy evaporation from leaf area index increases), rather than more uncertain changes in total precipitation. This increased water loss occurs even with significant and widespread increases in plant water-use efficiency. Additionally, snowpack reductions in the Rockies and the Pacific Northwest contribute to reductions in summer-season deep soil moisture, while increased transpiration dries out near surface soil moisture even in regions where total precipitation increases. When coupled with a warming- and CO2-induced shift in phenology and increase in net primary production, these vegetation changes reduce peak summer soil moisture and runoff considerably. Our results thus point to a large role for simulated vegetation responses in determining future Western aridity, highlighting the importance of reducing the substantial extant uncertainties in vegetation processes simulated within climate models.
Measurement of heat and moisture exchanger efficiency.
Chandler, M
2013-09-01
Deciding between a passive heat and moisture exchanger or active humidification depends upon the level of humidification that either will deliver. Published international standards dictate that active humidifiers should deliver a minimum humidity of 33 mg.l(-1); however, no such requirement exists, for heat and moisture exchangers. Anaesthetists instead have to rely on information provided by manufacturers, which may not allow comparison of different devices and their clinical effectiveness. I suggest that measurement of humidification efficiency, being the percentage moisture returned and determined by measuring the temperature of the respired gases, should be mandated, and report a modification of the standard method that will allow this to be easily measured. In this study, different types of heat and moisture exchangers for adults, children and patients with a tracheostomy were tested. Adult and paediatric models lost between 6.5 mg.l(-1) and 8.5 mg.l(-1) moisture (corresponding to an efficiency of around 80%); however, the models designed for patients with a tracheostomy lost between 16 mg.l(-1) and 18 mg.l(-1) (60% efficiency). I propose that all heat and moisture exchangers should be tested in this manner and percentage efficiency reported to allow an informed choice between different types and models. © 2013 The Association of Anaesthetists of Great Britain and Ireland.
Scaling an in situ network for high resolution modeling during SMAPVEX15
NASA Astrophysics Data System (ADS)
Coopersmith, E. J.; Cosh, M. H.; Jacobs, J. M.; Jackson, T. J.; Crow, W. T.; Holifield Collins, C.; Goodrich, D. C.; Colliander, A.
2015-12-01
Among the greatest challenges within the field of soil moisture estimation is that of scaling sparse point measurements within a network to produce higher resolution map products. Large-scale field experiments present an ideal opportunity to develop methodologies for this scaling, by coupling in situ networks, temporary networks, and aerial mapping of soil moisture. During the Soil Moisture Active Passive Validation Experiments in 2015 (SMAPVEX15) in and around the USDA-ARS Walnut Gulch Experimental Watershed and LTAR site in southeastern Arizona, USA, a high density network of soil moisture stations was deployed across a sparse, permanent in situ network in coordination with intensive soil moisture sampling and an aircraft campaign. This watershed is also densely instrumented with precipitation gages (one gauge/0.57 km2) to monitor the North American Monsoon System, which dominates the hydrologic cycle during the summer months in this region. Using the precipitation and soil moisture time series values provided, a physically-based model is calibrated that will provide estimates at the 3km, 9km, and 36km scales. The results from this model will be compared with the point-scale gravimetric samples, aircraft-based sensor, and the satellite-based products retrieved from NASA's Soil Moisture Active Passive mission.