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1

Long term analysis of PALS soil moisture campaign measurements for global soil moisture algorithm development  

Technology Transfer Automated Retrieval System (TEKTRAN)

An important component of satellite-based soil moisture algorithm development and validation is the comparison of coincident remote sensing and in situ observations that are typically provided by intensive field campaigns. The planned NASA Soil Moisture Active Passive (SMAP) mission has unique requi...

2

Microwave soil moisture measurements and analysis  

NASA Technical Reports Server (NTRS)

An effort to develop a model that simulates the distribution of water content and of temperature in bare soil is documented. The field experimental set up designed to acquire the data to test this model is described. The microwave signature acquisition system (MSAS) field measurements acquired in Colby, Kansas during the summer of 1978 are pesented.

Newton, R. W.; Howell, T. A.; Nieber, J. L.; Vanbavel, C. H. M. (principal investigators)

1980-01-01

3

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

NASA Astrophysics Data System (ADS)

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

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

2013-12-01

4

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

NASA Astrophysics Data System (ADS)

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

Kornelsen, K. C.; Coulibaly, P.

2012-12-01

5

Improving long-term, retrospective precipitation datasets using satellite-based surface soil moisture retrievals and the soil moisture analysis rainfall tool (SMART)  

Technology Transfer Automated Retrieval System (TEKTRAN)

Using historical satellite surface soil moisture products, the Soil Moisture Analysis Rainfall Tool (SMART) is applied to improve the accuracy of a multi-decadal global daily rainfall product that has been bias-corrected to match the monthly totals of available ground observations. In order to adapt...

6

Multi-scale analysis of bias correction of soil moisture  

NASA Astrophysics Data System (ADS)

Remote sensing, in situ networks and models are now providing unprecedented information for environmental monitoring. To conjunctively use multi-source data nominally representing an identical variable, one must resolve biases existing between these disparate sources, and the characteristics of the biases can be non-trivial due to spatio-temporal variability of the target variable, inter-sensor differences with variable measurement supports. One such example is of soil moisture (SM) monitoring. Triple collocation (TC) based bias correction is a powerful statistical method that is increasingly being used to address this issue, but is only applicable to the linear regime, whereas the non-linear method of statistical moment matching is susceptible to unintended biases originating from measurement error. Since different physical processes that influence SM dynamics may be distinguishable by their characteristic spatio-temporal scales, we propose a multi-timescale linear bias model in the framework of a wavelet-based multi-resolution analysis (MRA). The joint MRA-TC analysis was applied to demonstrate scale-dependent biases between in situ, remotely sensed and modelled SM, the influence of various prospective bias correction schemes on these biases, and lastly to enable multi-scale bias correction and data-adaptive, non-linear de-noising via wavelet thresholding.

Su, C.-H.; Ryu, D.

2015-01-01

7

Spatio-temporal soil moisture patterns - A meta-analysis using plot to catchment scale data  

NASA Astrophysics Data System (ADS)

Soil moisture is a key variable in hydrology, meteorology and agriculture. It is influenced by many factors, such as topography, soil properties, vegetation type, management, and meteorological conditions. The role of these factors in controlling the spatial patterns and temporal dynamics is often not well known. The aim of the current study is to analyze spatio-temporal soil moisture patterns acquired across a variety of land use types, on different spatial scales (plot to meso-scale catchment) and with different methods (point measurements, remote sensing, and modeling). We apply a uniform set of tools to determine method specific effects, as well as site and scale specific controlling factors. Spatial patterns of soil moisture and their temporal development were analyzed using nine different datasets from the Rur catchment in Western Germany. For all datasets we found negative linear relationships between the coefficient of variation and the mean soil moisture, indicating lower spatial variability at higher mean soil moisture. For a forest sub-catchment compared to cropped areas, the offset of this relationship was larger, with generally larger variability at similar mean soil moisture values. Using a geostatistical analysis of the soil moisture patterns we identified three groups of datasets with similar values for sill and range of the theoretical variogram: (i) modeled and measured datasets from the forest sub-catchment (patterns mainly influenced by soil properties and topography), (ii) remotely sensed datasets from the cropped part of the Rur catchment (patterns mainly influenced by the land-use structure of the cropped area), and (iii) modeled datasets from the cropped part of the Rur catchment (patterns mainly influenced by large scale variability of soil properties). A fractal analysis revealed that all analyzed soil moisture patterns showed a multifractal behavior, with at least one scale break and generally high fractal dimensions. Corresponding scale breaks were found between different datasets. The factors causing these scale breaks are consistent with the findings of the geostatistical analysis. Furthermore, the joined analysis of the different datasets showed that small differences in soil moisture dynamics, especially at the upper and lower bounds of soil moisture (at maximum porosity and wilting point of the soils) can have a large influence on the soil moisture patterns and their autocorrelation structure. Depending on the prevalent type of land use and the time of year, vegetation causes a decrease or an increase of spatial variability in the soil moisture pattern.

Korres, W.; Reichenau, T. G.; Fiener, P.; Koyama, C. N.; Bogena, H. R.; Cornelissen, T.; Baatz, R.; Herbst, M.; Diekkrüger, B.; Vereecken, H.; Schneider, K.

2015-01-01

8

Continental satellite soil moisture data assimilation improves root-zone moisture analysis for water resources assessment  

NASA Astrophysics Data System (ADS)

A framework was developed for the continental assimilation of satellite soil moisture (SM) into an operational water balance modelling system. The ensemble Kalman filter (EnKF) was implemented to assimilate AMSR-E and ASCAT-derived SM products into the landscape model of the Australian Water Resources Assessment system (AWRA-L) and generate ensembles of daily top-layer and shallow root-zone soil moisture analyses for the continent at 0.05° resolution. We evaluated the AWRA-L SM estimates with and without assimilation against in situ moisture measurements in southeast Australia (OzNet), as well as against a new network of cosmic-ray moisture probes (CosmOz) spread across the country. Results show that AWRA-L root-zone moisture estimates are improved though the assimilation of satellite SM: model estimates of 0-30 cm moisture content improved for more than 90% of OzNet sites, with an increase in average correlation from 0.68 (before assimilation) to 0.73 (after assimilation); while estimates 0-90 cm moisture improved for 60% of sites with increased average correlation from 0.56 to 0.65. The assimilation of AMSR-E and ASCAT appeared to yield similar performance gains for the top-layer, however ASCAT data assimilation improved root-zone estimation for more sites. Poor performance of one data set was compensated by the other through joint assimilation. The most significant improvements in AWRA-L root-zone moisture estimation (with increases in correlation as high as 90%) occurred for sites where both the assimilation of satellite soil moisture improved top-layer SM accuracy and the open-loop deep-layer storage estimates were reasonably good. CosmOz SM measurements exhibited highest correlation with AWRA-L estimates for modelled root-zones layer thicknesses ranging from 20 cm to 1 m. Slight improvements through satellite data assimilation were observed for only 2 of 7 CosmOz sites, but the comparison was affected by a short data overlap period. The location of some of the CosmOz probes was not optimal for evaluation of satellite SM assimilation, but their utility is demonstrated and the observations may become suitable for assimilation themselves in future.

Renzullo, L. J.; van Dijk, A. I. J. M.; Perraud, J.-M.; Collins, D.; Henderson, B.; Jin, H.; Smith, A. B.; McJannet, D. L.

2014-11-01

9

A case study on variational soil moisture analysis from atmospheric observations  

Microsoft Academic Search

Using a stand-alone 1-dim soil and atmospheric boundary layer model, the feasibility of off-line variational soil moisture analysis by assimilation of near-surface atmospheric observations is investigated. The experiments are performed using the soil module and boundary layer formulation taken from the regional forecast model of the German Weather Service. Assimilation experiments indicate that atmospheric information allows to initialize soil humidity

Ulrich Callies; Andreas Rhodin; Dieter P Eppel

1998-01-01

10

A Causality Analysis of Soil Moisture Measurements at a Steep Hillslope  

NASA Astrophysics Data System (ADS)

The vertical and lateral profiles of temporal variations in soil moisture are important for understanding the hydrological process along hillside transects. In this study the relationship between measured soil moistures was explored aiming to configure the hydrologic contributions of different flowpaths. All measured soil moistures include a common stochastic structure, because the hydrometeological driver, rainfall, mainly determines the soil moisture response feature. The infiltration process through the topsoil at a shallow depth is also common in all measured soil moisture histories, and relationships between measured series are also affected by both rainfall and topsoil infiltration. The common stochastic structure of soil moisture series was removed via the pre-whitening procedure. Therefore, a systematic analysis procedure is presented to delineate the exclusive causal relationships among multiple soil moisture measurements. A monitoring system based on multiplexed time domain reflectometry (TDR) was used to obtain time series of soil moisture along two transects for a steep hillslope during the rainy season. Application of the proposed method for monitoring points of two adjacent locations provided 8, 12, 14, and 13, 16, 22 causal relationships for vertical and, lateral in parallel and diagonal directions, respectively, along the two transects. The point-based contributions of the internal flowpath could be evaluated as the correlation is normalized in the context of inflow and outflow. The hydrological processes in the soil layer, vertical flow, lateral flow, downslope recharge, and return flow were quantified, and the relative importance of each hydrological component is presented to improve our understanding of hydrological processes along the two transects of the study area.

Kim, S.

2011-12-01

11

Correcting rainfall using satellite-based surfae soil moisture retrievals: The soil moisture analysis rainfall tool(SMART)  

Technology Transfer Automated Retrieval System (TEKTRAN)

Recent work in Crow et al. (2009) developed an algorithm for enhancing satellite-based land rainfall products via the assimilation of remotely-sensed surface soil moisture retrievals into a water balance model. As a follow-up, this paper describes the benefits of modifying their approach to incorpor...

12

Fluctuation regimes of soil moisture in ERA-40 re-analysis data  

NASA Astrophysics Data System (ADS)

Soil moisture variability is analysed in the re-analysis data ERA-40 of the European Centre for Medium-Range Weather Forecasts (ECMWF) which includes four layers within 189 cm depth. Short-term correlations are characterised by an e-folding time scale assuming an exponential decay, whilst long-term memory is described by power law decays with exponents determined by detrended fluctuation analysis. On a global scale, the short-term variability varies congruently with long-term memory in the surface layer. Key climatic regions (Europe, Amazon and Sahara) reveal that soil moisture time series are non-stationary in arid regions and in deep layers within the time horizon of ERA-40. The physical processes leading to soil moisture variability are linear according to an analysis of volatility (the absolute differences), which is substantiated by surrogate data analysis preserving the long-term memory.

Wang, Guojie; Dolman, Albertus Johannes; Blender, Richard; Fraedrich, Klaus

2010-01-01

13

A soil moisture budget analysis of Texas using basic climatic data  

E-print Network

A SOIL MOISTURE BUDGET ANALYSIS OF TEXAS USING BASIC CLIMATIC DATA A Thesis by RONALD PAUL LO~ Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE... May 1989 Major Subject: Meteorology A SOIL MOISTURE BUDGET ANALYSIS OF TEXAS USING BASIC CLIMATIC DATA A Thesis RONALD PAUL LOWTHER Approved as to style and content by: John F. Gn iIIts (Chair of Committee) Gerald R. North (Member) Ru If J...

Lowther, Ronald Paul

1989-01-01

14

Modeling soil moisture using passive remote sensing  

NASA Astrophysics Data System (ADS)

Soil moisture is an important component of analysis in many Earth science and related disciplines. Information about the entire profile can find a wide range of applications in many disciplines. Hydrological models can simulate soil moisture profiles, but there is usually limited subsurface information to constrain the models. Emerging science and technology to measure soil moisture with remote sensing offers a potential source of additional information from which to constrain soil hydrology models. Because passive remote sensing can provide soil moisture information for a thin surface layer of soil, the question becomes one of how to use this information to improve estimates of the soil moisture profile. This study attempts to shed light on this question by using a simple hydrology model (SHM) and with data collected during a microwave remote sensing experiment in Huntsville, Alabama during July 1996 (Huntsville '96). This study shows how the errors in the estimation of soil moisture increase as the sampling interval of meteorological data increases. The root mean square error (RMSE) from the baseline almost triples (i.e. from 0.0352 to 0.0810), as the sampling interval is increased from 6 hr to 12 hr. These errors can be reduced by half if we periodically update the modeled soil moisture estimates with a method that assimilates microwave remote sensing soil moisture estimates with the SHM soil moisture profile. Thus, this study attempts to extend the soil moisture information on the surface layer by microwave remote sensing to the entire profile using SHM.

Soman, Vishwas V.; Crosson, William L.; Laymon, Charles A.

1997-12-01

15

GLOBE Videos: Soil Characterization - Soil Moisture (18:23 min)  

NSDL National Science Digital Library

This video describes how to select a soil moisture study site and sampling strategy, and identifies what laboratory instruments will be needed to complete a soil moisture analysis. Students are shown collecting soil moisture data and asking questions about what soil moisture data might tell them about the environment. The resource includes a video and a written transcript, and is supported by the Soil Moisture Protocol in the GLOBE Teacher's Guide. This is one of five videos about soils in the 24-part instructional video series describing scientific protocols used by GLOBE (Global Learning and Observation to Benefit the Environment), a worldwide, hands-on, K-12 school-based science education program.

16

Catchment scale validation of SMOS and ASCAT soil moisture products using hydrological modeling and temporal stability analysis  

NASA Astrophysics Data System (ADS)

Since soil moisture is an important influencing factor of the hydrological cycle, knowledge of its spatio-temporal dynamics is crucial for climate and hydrological modeling. In recent years several soil moisture data products from satellite information have become available with global coverage and sub-monthly resolution. Since the remote sensing of soil moisture is an indirect measurement method and influenced by a large number of factors (e.g. atmospheric correction, vegetation, soil roughness, etc.), a comprehensive validation of the resulting soil moisture products is required. However, the coarse spatial resolution of these products hampers the comparison with point-scale in situ measurements. Therefore, upscaling of in situ to the scale of the satellite data is needed. We present the validation results of the soil moisture products of the years 2010-2012 retrieved from the Soil Moisture and Ocean Salinity (SMOS) and the Advanced Scatterometer (ASCAT) for the Rur and Erft catchments in western Germany. For the upscaling of in situ data obtained from three test sites of the Terrestrial Environmental Observatories (TERENO) initiative we used the hydrological model WaSiM ETH. Correlation of the SMOS product to modeled and upscaled soil moisture resulted in a mean correlation coefficient of 0.28 whereas for ASCAT a correlation coefficient of 0.50 was obtained. However, for specific regions the SMOS product showed similar correlation coefficients as the ASCAT product. While for ASCAT correlation was mainly dependent on topography and vegetation, SMOS was also influenced by radiofrequency interferences in our study area. Both products show dry biases as compared to the soil moisture reference. However, while SMOS showed relatively constant bias values, ASCAT bias is variable throughout the year. As an additional validation method we performed a temporal stability analysis of the retrieved spatio-temporal soil moisture data. Through investigation of mean relative differences of soil moisture for every pixel, their standard deviations and their rankings, we analyzed the temporal persistence of spatial patterns. Our results show high standard deviations for both SMOS and ASCAT soil moisture products as compared to modeled soil moisture, indicating a lower temporal persistence. The consistence of ranks of mean relative differences was low for SMOS and relative ASCAT soil moisture compared to modeled soil moisture, while ASCAT soil moisture, converted to absolute values, showed higher rank consistence.

Rötzer, K.; Montzka, C.; Bogena, H.; Wagner, W.; Kerr, Y. H.; Kidd, R.; Vereecken, H.

2014-11-01

17

Optional Soil Moisture Sensor Protocol  

NSDL National Science Digital Library

The purpose of this resource is to measure the water content of soil based on the electrical resistance of soil moisture sensors. Students install soil moisture sensors in holes that are 10 cm, 30 cm, 60 cm, and 90 cm deep. They take daily readings of soil moisture data by connecting a meter to the sensors and using a calibration curve to determine the soil water content at each depth.

The GLOBE Program, University Corporation for Atmospheric Research (UCAR)

2003-08-01

18

Evaluation of the Optimum Interpolation and Nudging Techniques for Soil Moisture Analysis Using FIFE Data  

Microsoft Academic Search

ABSTRACT Initialization of land surface prognostic variables is a crucial issue for short- and medium-range,forecasting as well as at seasonal timescales. In this study, two sequential soil moisture analysis schemes are tested, both based on the comparison,between,observed,and predicted 2-m parameters: the nudging,technique used opera- tionally at the European Centre for Medium-Range Weather Forecasts (ECMWF) and the optimum,interpolation technique proposed,by J.

Hervé Douville; Pedro Viterbo; Jean-François Mahfouf; Anton C. M. Beljaars

2000-01-01

19

Soil-moisture ground truth, Hand County, South Dakota  

NASA Technical Reports Server (NTRS)

Soil samples were taken in the field and carefully preserved in taped metal containers for later laboratory gravimetric analysis to determine soil-moisture content. The typical sampling pattern used in this mission is illustrated, and the soil types encountered on the soil-moisture lines are summarized. The actual soil-moisture data were tabulated by range, township and section. Soil-moisture data obtained in fields of winter wheat and spring wheat are briefly summarized.

Jones, E. B.

1976-01-01

20

Soil moisture analysis combining screen-level parameters and microwave brightness temperature: A test with field data  

Microsoft Academic Search

To improve the soil moisture initial conditions for numerical weather prediction models the potential of assimilating both screen-level parameters (2m-temperature T2m, 2m-relative humidity RH2m) and 1.4 GHz TB is investigated. A soil moisture analysis system based on the Extended Kalman Filter theory is applied to the single column version of the ECMWF numerical weather prediction model for 130 summer days

G. Seuffert; H. Wilker; P. Viterbo; J.-F. Mahfouf; M. Drusch; J.-C. Calvet

2003-01-01

21

Impact of elevated atmospheric CO2 on soil moisture: a meta-analysis  

NASA Astrophysics Data System (ADS)

The dynamics of soil moisture and vegetation productivity interact with and affect each other in many ecosystems. Therefore understanding soil moisture changes and the underlying mechanisms under climate change is important to predict future plant-water interactions and consequent hydrological responses. In this study, we aim to quantify and compare soil moisture under ambient and elevated CO2 treatment in different ecosystems. We used meta-analytic techniques to test the responses under different climate regimes, vegetation types, soil textures, and management types. We found a consistent increase in soil moisture under elevated CO2 treatment, and the effect is stronger in water-limited systems. The results suggest that CO2 enrichment may stimulate a decrease in stomatal conductance in plants, hence lead to a decrease of transpiration rate and higher soil water content.

Lu, X.; Wang, L.; McCabe, M. F.; Leung, M.

2013-12-01

22

Soil moisture: Some fundamentals. [agriculture - soil mechanics  

NASA Technical Reports Server (NTRS)

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

Milstead, B. W.

1975-01-01

23

Analysis of soil moisture extraction algorithm using data from aircraft experiments  

NASA Technical Reports Server (NTRS)

A soil moisture extraction algorithm is developed using a statistical parameter inversion method. Data sets from two aircraft experiments are utilized for the test. Multifrequency microwave radiometric data surface temperature, and soil moisture information are contained in the data sets. The surface and near surface ( or = 5 cm) soil moisture content can be extracted with accuracy of approximately 5% to 6% for bare fields and fields with grass cover by using L, C, and X band radiometer data. This technique is used for handling large amounts of remote sensing data from space.

Burke, H. H. K.; Ho, J. H.

1981-01-01

24

meeting summary: GEWEX\\/BAHC International Workshop on Soil Moisture Monitoring, Analysis, and Prediction for Hydrometeorological and Hydroclimatological Applications  

Microsoft Academic Search

The International Workshop on Soil Moisture Monitoring, Analysis, and Prediction for Hydrometeorological and Hydroclimatological Applications considered the potential for implementing a global system during this decade and for identifying the priorities for the research needed to achieve such a global system. The workshop attendees advised that a global system should provide measurements and\\/or estimates of volumetric soil water content on

J. Leese; T. Jackson; A. Pitman; P. Dirmeyer

2001-01-01

25

Analysis of soil moisture retrieval from airborne passive/active L-band sensor measurements in SMAPVEX 2012  

NASA Astrophysics Data System (ADS)

Soil moisture is a key component in the hydrologic cycle and climate system. It is an important input parameter for many hydrologic and meteorological models. NASA'S upcoming Soil Moisture Active Passive (SMAP) mission, to be launched in October 2014, will address this need by utilizing passive and active microwave measurements at L-band, which will penetrate moderately dense canopies. In preparation for the SMAP mission, the Soil Moisture Validation Experiment 2012 (SMAPVEX12) was conducted from 6 June to 17 July 2012 in the Carment-Elm Creek area in Manitoba, Canada. Over a period of six weeks diverse land cover types ranging from agriculture over pasture and grassland to forested sites were re-visited several times a week. The Passive/Active L-band Sensor (PALS) provides radiometer products, vertically and horizontally polarized brightness temperatures, and radar products. Over the past two decades, successful estimation of soil moisture has been accomplished using passive and active L-band data. However, remaining uncertainties related to surface roughness and the absorption, scattering, and emission by vegetation must be resolved before soil moisture retrieval algorithms can be applied with known and acceptable accuracy using satellite observations. This work focuses on analyzing the Passive/Active L-band Sensor observations of sites covered during SMAPVEX12, investigating the observed data, parameterizing vegetation covered surface model, modeling inversion algorithm and analyzing observed soil moisture changes over the time period of six weeks. The data and analysis results from this study are aimed at increasing the accuracy and range of validity of SMAP soil moisture retrievals via enhancing the accuracy for soil moisture retrieval.

Chen, Liang; Song, Hongting; Tan, Lei; Li, Yinan; Li, Hao

2014-11-01

26

SMALT - Soil Moisture from Altimetry  

NASA Astrophysics Data System (ADS)

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

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

2014-05-01

27

Preliminary analysis of the sensitivity of AIRSAR images to soil moisture variations  

NASA Technical Reports Server (NTRS)

Synthetic Aperture Radar (SAR) images acquired from various sources such as Shuttle Imaging Radar B (SIR-B) and airborne SAR (AIRSAR) have been analyzed for signatures of soil moisture. The SIR-B measurements have shown a strong correlation between measurements of surface soil moisture (0-5 cm) and the radar backscattering coefficient sigma(sup o). The AIRSAR measurements, however, indicated a lower sensitivity. In this study, an attempt has been made to investigate the causes for this reduced sensitivity.

Pardipuram, Rajan; Teng, William L.; Wang, James R.; Engman, Edwin T.

1993-01-01

28

Assimilation of screen-level observations by variational soil moisture analysis  

Microsoft Academic Search

Summary   Inaccurate specification of soil moisture contents can result in forecast errors up to several degrees centigrade. Since\\u000a direct measurements are rarely available, a variational method has been developed that assimilates synoptic measurements of\\u000a 2?m-temperature in order to specify the moisture contents of the two soil layers of the Local Model at Deutscher Wetterdienst.\\u000a The analyzed values minimize a cost

R. Hess

2001-01-01

29

Teleconnection analysis of runoff and soil moisture over the Pearl River basin in South China  

NASA Astrophysics Data System (ADS)

This study explores the teleconnection of two climatic patterns, namely the El Niño-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD), with hydrological processes over the Pearl River basin in South China. The Variable Infiltration Capacity (VIC) model is used to simulate the daily hydrological processes over the basin for the study period 1952-2000, and then, using the simulation results, the time series of the monthly runoff and soil moisture anomalies for its ten sub-basins are aggregated. Wavelet analysis is performed to explore the variability properties of these time series at 49 timescales ranging from 2 months to 9 yr. Use of wavelet coherence and rank correlation method reveals that the dominant variabilities of the time series of runoff and soil moisture are basically correlated with IOD. The influences of ENSO on the terrestrial hydrological processes are mainly found in the eastern sub-basins. The teleconnections between climatic patterns and hydrological variability also serve as a reference basis for inferences on the occurrence of extreme hydrological events (e.g. floods and droughts).

Niu, J.; Chen, J.; Sivakumar, B.

2013-09-01

30

An empirical approach towards improved spatial estimates of soil moisture for vegetation analysis  

Microsoft Academic Search

Landscape-level spatial estimates of soil water content are critical to understanding ecological processes and predicting watershed response to environmental change. Because soil moisture influences are highly variable at the landscape scale, most meteorological datasets are not detailed enough to depict spatial trends in the water balance at these extents. We propose a tactical approach to gather high-resolution field data for

Todd Lookingbill; Dean Urban

2004-01-01

31

Retrieving Soil Moisture States Using Streamflow Assimilation  

Microsoft Academic Search

It has been shown that soil moisture has an important impact on seasonal to interannual climate prediction through evapotranspiration controls, especially in heavily forested areas like the Amazon. Hence, it is important that the land surface component of climate models have an accurate initialisation of soil moisture. While remote sensing of soil moisture holds much promise for near-surface soil moisture

C. Rüdiger; J. P. Walker; J. D. Kalma; G. R. Willgoose; P. R. Houser

2004-01-01

32

Sensitivity of LISEM predicted catchment discharge to initial soil moisture content of soil profile  

E-print Network

Sensitivity of LISEM predicted catchment discharge to initial soil moisture content of soil profile: Soil moisture Infiltration Rainfall-runoff Sensitivity analysis LISEM s u m m a r y This study conducts a broad sensitivity analysis, taking into account the influence of initial soil moisture content in two

Loon, E. Emiel van

33

Method for evaluating moisture tensions of soils using spectral data  

NASA Technical Reports Server (NTRS)

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

Peterson, John B. (Inventor)

1982-01-01

34

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

NASA Astrophysics Data System (ADS)

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

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

2012-12-01

35

Spatio-temporal analysis of surface and subsurface soil moisture for remote sensing applications within the Upper Cedar Creek Watershed  

Technology Transfer Automated Retrieval System (TEKTRAN)

Soil moisture is an intrinsic state variable that varies considerably in space and time. From a hydrologic viewpoint, soil moisture controls runoff, infiltration, storage and drainage. Soil moisture determines the partitioning of the incoming radiation between latent and sensible heat fluxes. Althou...

36

Analysis of impact of heterogeneity at landscape level in retrieval of soil moisture from low-frequency radars  

NASA Astrophysics Data System (ADS)

Knowledge of soil moisture dynamics on a global scale is key in understanding the water and energy cycles. This understanding has critical impact on predicting future water resources and sustainability, and is invaluable across many disciplines such as hydrology, meteorology, and ecology, as well as in weather and climate prediction. To accommodate this need for global observations of surface soil moisture, NASA is developing the soil moisture active passive (SMAP) spaceborne mission carrying an L-band radar and radiometer to be launched in late 2014. The SMAP mission will carry both a radar and a radiometer allowing synergistic use of the two data types for soil moisture retrieval. Radar data are delivered at higher resolution (3 km) than the radiometer data (36 km), and allow finer analysis of the connection between land cover type and soil moisture. Most satellite resolution pixels contain highly heterogeneous scenes with small scale variability of soil moisture, soil texture, topography, and vegetation cover types. Traditional algorithms for radar soil moisture retrieval assume a homogeneous scene within each satellite resolution cell, which is not a reasonable assumption even for the 3 km resolution radar data from SMAP. This illuminates the need to develop spatial aggregation and disaggregation techniques using radar forward scattering models that assume homogeneity over finer scale sub-pixels and derive tailor-made models for their contribution to the coarse-scale satellite pixel for effective soil moisture retrieval. A physics-based remote sensing (radar) landscape simulator to analyze potentially large groups of georeferenced pixels by utilizing ancillary data has been developed. The inversion capability to compare different scaled retrieval results has been separately developed and shown to be suitable for retrieval of soil moisture values over a monospecies boreal forest in Canada. These tools facilitate the analysis of heterogeneity at landscape level by enabling the investigation of spatial aggregation and joint aggregation and disaggregation techniques. In this work, we build on preliminary findings and will further investigate and present results of a physics-based spatial aggregation strategy for a forested area. We will focus on retrieving soil moisture based on active radar measurements, which although at much finer resolution than a radiometer of the same frequency, is still at a coarse enough resolution to suffer from the effects of landscape heterogeneity. The total measured coarse-scale radar backscattering coefficient of a scene can be expressed as a weighted linear sum of the contributions of the fine-scale subpixels; these weights are functions of landscape parameters. By aggregating the radar backscattering coefficients of the simulated subpixels and disaggregating the measured radar backscattering coefficient of the coarse-scale pixel, we aim to find the total soil moisture of the satellite pixel. We adopt a block kriging strategy for radar backscattering coefficients using available ancillary data, followed by the development of an inversion strategy that takes into account the non-uniform contribution of different regions of the landscape. Thorough validation and error analysis will be shown through simulations as well as with the use of airborne radar data and ground-based observations.

Burgin, M.; Tabatabaeenejad, A.; Moghaddam, M.

2012-12-01

37

Soil Moisture from Altimetry - SMALT  

NASA Astrophysics Data System (ADS)

Soil surface moisture is a key scientific parameter; however, it is extremely difficult to measure remotely, particularly in arid and semi-arid terrain. This paper outlines the development of a novel methodology to generate soil moisture estimates in these regions from multi-mission satellite radar altimetry. Key to this approach is the development of detailed DRy Earth ModelS (DREAMS), which encapsulate the detailed and intricate surface brightness variations over the Earth's land surface, resulting from changes in surface roughness and composition. These models are created by cross-calibrating and reconciling multi-mission altimeter sigma0 measurements from ERS-1, ERS-2, EnviSat and Jason-2. This approach is made possible because altimeters are nadir-pointing, and most of the available radar altimeter datasets are from instruments operating in Ku band. These DREAMS are complicated to build and require multiple stages of processing and manual intervention. However, this approach obviates the requirement for detailed ground truth to populate theoretical models, facilitating derivation of surface soil moisture estimates over arid regions, where detailed survey data are generally not available. This paper presents results using the DREAMS over desert surfaces, and showcases the model outcomes over the Arabian and Tenere deserts. A global assessment is presented of areas where DREAMS are currently being generated, and an outline of the required processing to obtain soil surface moisture estimates is given. Results for altimeter derived soil moisture validation with ground truth are presented together with comparisons with other remotely sensed soil estimates. Soil moisture product from ERS-2 radar altimetry in arid regions is presented, and the temporal and spatial resolutions of these data are reported. The results generated by this ESA encouraged initiative will be made freely available to the global scientific community. First products are planned for release within the next few months. Further information can be found at http://tethys.eaprs.cse.dmu.ac.uk/SMALT.

Berry, Philippa; Smith, Richard; Salloway, Mark; Lucas, Bruno Manuel; Dinardo, Salvatore; Benveniste, Jérôme

2013-04-01

38

Gravimetric Soil Moisture Protocols  

NSDL National Science Digital Library

The purpose of this resource is to measure soil water content by mass. Students collect soil samples with a trowel or auger and weigh them, dry them, and then weigh them again. The soil water content is determined by calculating the difference between the wet sample mass and the dry sample mass.

The GLOBE Program, University Corporation for Atmospheric Research (UCAR)

2003-08-01

39

The determination of soil moisture by extraction and gas chromatography  

NASA Technical Reports Server (NTRS)

Soil moisture content was determined by extracting soil with methanol and subsequently analyzing the extract for water by gas chromatography. With air-dried mineral soils, this method gave slightly higher moisture content values than those obtained by the oven-dry method. Moisture content was determined quantitatively in soils to which various amounts of water had been added. The complete procedure, including extraction and analysis, requires less than one hour and gives results that closely compare to the oven-dry method.

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

1974-01-01

40

Davis Soil Moisture and Temperature Station Protocol  

NSDL National Science Digital Library

The purpose of this resource is to log soil data using a Davis soil moisture and temperature station. Soil moisture and temperature sensors are installed at multiple depths and a station is set up to measure and record measurements at 15 minute intervals. These measurements are transferred to your school.s computer and then submitted to GLOBE via email data entry. Gravimetric soil moisture measurements must be taken to develop calibration curves for the soil moisture sensors.

The GLOBE Program, University Corporation for Atmospheric Research (UCAR)

2003-08-01

41

Large Scale Evaluation of AMSR-E Soil Moisture Products Based on Ground Soil Moisture Network Measurements  

NASA Astrophysics Data System (ADS)

This paper presents an evaluation of AMSR-E (Advanced Microwave Scanning Radiometer for EOS) soil moisture products, based on a comparison with three ground soil moisture networks. The selected ground sites are representative of various climatic, hydrologic and environmental conditions in temperate and semi-arid areas. They are located in the south-west of France, south-east of Australia and the Gourma region of the Sahel. These sites were respectively implemented in the framework of the projects SMOSREX (Surface Monitoring Of Soil Reservoir Experiment), SASMAS/GoREx (Scaling and Assimilation of Soil Moisture and Streamflow in the Goulburn River Experimental catchment) and AMMA (African Monsoon Multidisciplinary Analysis). In all cases, the arrangement of the soil moisture measuring sites was specifically designed to address the validation of remotely sensed soil moisture in the context of the preparation of the SMOS (Soil Moisture and Ocean Salinity) project. For the purpose of this study, 25km AMSR-E products were used, including brightness temperatures at 6.9 and 10.7 GHz, and derived soil moisture. The study is focused on the year 2005. It is based on ground soil moisture network measurements from 4 stations for SMOSREX extended to the SUDOUEST project of CESBIO, 12 stations for GoRex, and 4 stations for AMMA. Temporal and spatial features of soil moisture variability and stability is a critical issue to be addressed for remotely sensed soil moisture validation. While ground measurements provide information on soil moisture dynamics at local scale and high temporal resolution (hourly), satellite measurements are sparser in time (up to several days), but cover a larger region (25km x 25km for AMSR-E). First, a statistical analysis, including mean relative difference and Spearman rank, is conducted for the three soil moisture networks. This method is mainly based on the approach proposed by Cosh et al. (2004) for the purpose of the use of ground networks for satellite remote sensing validation. It allows to capture soil moisture variability features and to identify for each site the most representative station. Second, a comparison of AMSR-E derived and in-situ soil moisture measurements was conducted. Volumetric soil moisture obtained from ground and satellite measurements are compared for both absolute and normalized values. For the three sites, results suggest that although AMSR-E soil moisture products are not able to capture the same range of soil moisture values as in-situ measurements, they provide reliable information on surface soil moisture temporal variability over the three sites. It is shown, however, that the use of radiometric products such as polarization ratio provide better agreement with ground stations, than the derived soil moisture products.

Gruhier, C.; de Rosnay, P.; Richaume, P.; Kerr, Y.; Rudiger, C.; Boulet, G.; Walker, J. P.; Mougin, E.; Ceschia, E.; Calvet, J.

2007-05-01

42

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

NASA Technical Reports Server (NTRS)

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.

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

43

Evaluation of Reanalysis Soil Moisture Simulations Using Updated Chinese Soil Moisture Observations  

Microsoft Academic Search

Using 19 yr of Chinese soil moisture data from 1981 to 1999, the authors evaluate soil moisture in three reanalysis outputs: the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re- Analysis (ERA-40); the National Centers for Environmental Prediction-National Center for Atmospheric Research (NCEP-NCAR) reanalysis 1 (R-1); and the NCEP-Department of Energy (DOE) reanalysis 2 (R-2) over China. R-2 shows

Haibin Li; Alan Robock; Suxia Liu; Xingguo Mo; Pedro Viterbo

2005-01-01

44

Soil Moisture Retrieval from Aquarius  

Technology Transfer Automated Retrieval System (TEKTRAN)

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

45

A soil moisture budget analysis of Texas using basic climatic data while assuming a possible warming trend across the state  

E-print Network

of record and compare it with a predicted soil moisture regime based on a possible warming trend. A statistical analysis was performed to investigate for possible relationships between mean monthly precipitation (MMP) and temperature (MMT) for each... division during all months of the year, Regression statistics revealed that a statistically significant linear relationship existed between MMP and MMT in just over half the cases (63 out of 120). The relationship worked best in relatively dry regions...

Bjornson, Brian Matthew

2012-06-07

46

An integrated GIS application system for soil moisture data assimilation  

NASA Astrophysics Data System (ADS)

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

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

2014-11-01

47

Interplay of climate seasonality and soil moisture-rainfall feedback  

NASA Astrophysics Data System (ADS)

The soil moisture-rainfall feedback (SMRF) may significantly impact hydro-climatic dynamics, inducing persistent weather conditions that are responsible for prolonged droughts or abnormally wet states. However, externally driven seasonal variability in rainfall and potential evapotranspiration, with the associated patterns of wet and dry conditions, may both interact with such an SMRF. In this study, seasonal variations in radiation and precipitation forcing are included in a stochastic SMRF model with the assumption of a soil moisture-dependent average rainfall frequency to explore their effects on the soil moisture probabilistic structure. The theoretical model results, based on a parameterization using data for soil moisture and climate in Illinois, show that average rainfall frequency peaks in late spring when both the soil condition and the SMRF strength favor convective rainfall triggering. Under such conditions, the soil moisture tends to exhibit bimodal behavior until the SMRF strength becomes weak again toward the end of the growing season. Such a behavior is reminiscent of the dynamics of a system undergoing a periodic, stochastically forced pitchfork bifurcation. The presence of bimodal soil moisture behavior is also verified using nonparametric statistical tests on soil moisture data. The analysis of wet-to-wet and dry-to-dry soil moisture transitions in the joint probability distribution of soil moisture further corroborates the presence of hydro-climatic persistence in the spring-to-summer transition.

Yin, Jun; Porporato, Amilcare; Albertson, John

2014-07-01

48

Relating Soil Moisture to TRMMPR Backscatter in Southern United States  

NASA Astrophysics Data System (ADS)

Soil Moisture is an important variable in hydrological cycle. It plays a vital role in agronomy, meteorology, and hydrology. In spite of being an important variable, soil moisture measuring stations are sparse. This is due to high cost involved in the installation of dense network of measuring stations required to map a comprehensive spatio-temporal behavior of soil moisture. Hence, there is a need to develop an alternate method to measure soil moisture. This research relates soil moisture (SM) to backscatter (?°) obtained from Tropical Rainfall Measuring Mission Precipitation Radar (TRMMPR) and Normalized Difference Vegetation Index (NDVI) obtained from Advanced Very High Resolution Radiometer. SM data is obtained from Soil Climate Analysis Network (SCAN). ?° measurements are normalized at an incidence angle of 10° at which it has the highest sensitivity to SM. An empirical model that relates SM to normalized ?° and NDVI is developed. NDVI takes into account the different vegetation densities. The relationship between model variables is approximated to be linear. The model is applied to data from 1998 to 2008 where 75% of the data is used for calibration and the remaining 25% for validation. Figure 1 shows the comparison of observed and modeled soil moisture for a site with low vegetation. Even though the model underestimates the soil moisture content, it captures the signal well and produces peaks similar to the observed soil moisture. The model performs well with a correlation of 0.71 and root mean square error of 4.0%. The accuracy of the model depends on vegetation density. Table 1 summarizes the model performance for different vegetation densities. The model performance decreases with the increase in vegetation as the leaves in the vegetation canopy attenuate the incident microwaves which reduces the penetration depth and subsequently the sensitivity to soil moisture. This research provides a new insight into the microwave remote sensing of soil moisture. Figure 1. Plot of observed vs. modeled soil moisture. Table 1. Soil moisture model performance based on different vegetation densities.

Puri, S.; Stephen, H.; Ahmad, S.

2009-12-01

49

IMPROVING HYDROLOGICAL FORECASTING USING SPACEBORNE SOIL MOISTURE RETRIEVALS  

Technology Transfer Automated Retrieval System (TEKTRAN)

Using existing data sets of passive microwave spaceborne soil moisture retrievals, streamflow, and precipitation for 26 basins in the United States Southern Great Plains, a 5-year analysis is performed to quantify the value of soil moisture retrievals derived from the Tropical Rainfall Mission (TRMM...

50

ALOS PALSAR and UAVSAR Soil Moisture in Field Campaigns  

Technology Transfer Automated Retrieval System (TEKTRAN)

As part of our ongoing analysis of L-band radar mapping of soil moisture we are evaluating the role that ALOS PALSAR data can play in the development of radar retrieval algorithms for the future NASA Soil Moisture Active Passive (SMAP) satellite. Differences in configurations must be assessed to det...

51

Soil temperature and soil moisture induced spatio-temporal variability of soil respiration in winter wheat  

NASA Astrophysics Data System (ADS)

Soil respiration is the major transfer of CO2 from the soil to the atmosphere and is characterized by a high spatio-temporal variability depending, among others, on variations in soil temperature and soil moisture. We simultaneously measured soil respiration, soil temperature (3 cm depth) and soil moisture (0-5 cm depth) in winter wheat from April to September 2008 at a 50x50 m plot at a site near Jülich, Germany. The average soil respiration rate over the whole sampling period was 3.8 ±1.5 mol m-2 s-1. Spatial variations of soil respiration, represented by the coefficient of variation (CV), were in average more than 5 times higher than the spatial variations of soil temperature and soil moisture, respectively. Concerning soil respiration, considerably higher spatial variations were observed during the growth period of winter wheat. Semivariogram analysis revealed a strong spatial autocorrelation of soil temperature, whereas a moderate spatial autocorrelation of soil respiration and soil moisture was detected. However, the range of spatial autocorrelation was nearly similar for all three variables, on average 20 m. For the given temporal and spatial scale, a large proportion in temporal changing of the spatial structure of soil respiration could be explained by the spatial distribution of soil moisture.

Prolingheuer, N.; Herbst, M.; Graf, A.; Vanderborght, J.; Vereecken, H.

2009-04-01

52

New Approaches for Soil Moisture Analysis over Complex Arctic Environments with PALSAR/ALOS  

NASA Astrophysics Data System (ADS)

Frozen ground is a sensitive indicator of how our home planet is changing. In this study, the relevance of L-band Synthetic Aperture Radar (SAR) data for extracting information on frozen ground is presented. Specifically, the study focused on the characterization of a permafrost active layer using polarimetric ALOS PALSAR imagery in two locations in Alaska: the Kobuk river valley and the Arctic National Wildlife Refuge. The adequacy between polarimetric EM model and radar data has been studied for a long time, especially over bare agricultural fields (Oh et al., 1992). The assessment of residual liquid water can be realized by means of a bare soil EM backscattering model. Over natural wild land areas such as the Arctic tundra, new approaches have to be proposed in order to tackle the effect of the vegetation and other irrelevant effects (sensor calibration, multiple scattering terms, etc.). As a result, traditional soil moisture retrieval has shown limited accuracy for operational use, even though promising methods have been recently investigated (Mattia et al., 2006; Verhoest et al., 2007). Two methodologies based on multi-temporal acquisitions are proposed in this study. In regards to the uncertainties of the vegetation effect or other irrelevant mechanisms, a first methodology is proposed in this study. An optimization on the Oh’s weights (Oh, 2004) and full-polarimetric PALSAR data is carried out by using priori information provided by the Advanced Microwave Scanning Radiometer (AMSR-E) onboard the Aqua satellite. By tuning PALSAR data and Oh’s weights, the effects of vegetation are counterbalanced. This method was tested over the Arctic National Wildlife Refuge (ANWR). The optimization results are found to be in good agreement with theoretical aspects: vegetation induces an increase of cross-polarized channel (anisotropic effect) and a decrease of co-polarized channels (attenuation mechanism). The soil moisture variation can be then retrieved in a consistent manner. The second methodology does not use any priori information from AMSR-E sensor to reduce the uncertainties. Over the second test site, the Kobuk river valley, nine single-polarized HH PALSAR scenes were used, four being acquired during the thawing period and five during the frozen period. Since the soil moisture content during the frozen events is close to zero, the roughness was estimated through the inversion of Oh’s model, assuming also some effects (e.g., Fresnel refraction) due to the overlying snow cover. In this assessment, the uncertainties about the snow densities and the soil moistures were modeled and integrated into the retrieval approach. The retrieved soil roughness and its associated uncertainty estimates based on the data acquired during the frozen season were further used to derive moisture variation during the thawing period.

Longépé, N.; Necsoiu, M.; Tadono, T.; Shimada, M.

2010-12-01

53

Retrieving Soil Moisture States Using Streamflow Assimilation  

NASA Astrophysics Data System (ADS)

It has been shown that soil moisture has an important impact on seasonal to interannual climate prediction through evapotranspiration controls, especially in heavily forested areas like the Amazon. Hence, it is important that the land surface component of climate models have an accurate initialisation of soil moisture. While remote sensing of soil moisture holds much promise for near-surface soil moisture measurement, and root zone soil moisture retrieval when assimilated into a land surface model, its application to such heavily forested areas is limited. This is due to the masking effect of dense vegetation canopies on remote sensing signals. However, soil moisture also has a strong impact on streamflow, through its control on baseflow and partitioning of rainfall into infiltration and runoff. Thus the use of streamflow data to constrain model predicted soil moisture is a potentially viable alternative to near-surface soil moisture remote sensing. This research demonstrates this potential using a synthetic twin-experiment. The study is based on typical conditions for both a semiarid and humid environment, using the catchment-based land surface model used by NSIPP (NASA Seasonal to Interannual Climate Prediction Project). First we produce a "truth" dataset which provides the streamflow observations and soil moisture validation data. Second, we make an "openloop" simulation where only the initial soil moisture states have been degraded to represent our lack of knowledge on soil moisture. We then assimilate streamflow observations from the truth run into the degraded simulation, in order to retrieve back the true initial soil moisture states. The results shown from this demonstration are for single subcatchments of much larger catchments, so that runoff routing could be ignored. Future research will include larger nested catchments interconnected via a routing model.

Rüdiger, C.; Walker, J. P.; Kalma, J. D.; Willgoose, G. R.; Houser, P. R.

2004-05-01

54

Soil Type Dependent Moisture-Respiration Relations Derived from Soil Incubation Data  

NASA Astrophysics Data System (ADS)

One of the most important factors affecting soil carbon mineralization is soil moisture. Moisture affects soil respiration either by being a limiting factor itself (affecting mobility and osmotic potential) or by limiting oxygen diffusion. The general relation between soil moisture and the production of CO2, integrated into all major soil carbon models, can vary largely between soils. However, a lack of information concerning its variation across soil types has led to most models applying simple moisture functions not validated by data. The uncertainties associated to such simplifications may result in wrong predictions of soil carbon stock changes. Soil incubations in the laboratory are well suited for obtaining precise relationships between variables, avoiding the problem of confounded or uncontrolled variables common in the field. Using multiple datasets from soil incubation studies, we performed an analysis with the aim of uncovering relations between moisture effects on soil respiration and a range of soil characteristics. We compiled data from multiple sources where soil moisture varied and was monitored along with respiration. Using, as a common unit, the relative increase in soil respiration for each per cent increase in moisture, we were able to calculate means and confidence intervals along the moisture axis and, most importantly, to relate the relative respiration change to soil physical characteristics. We found significant relations between soil characteristics (bulk density, pore space, organic carbon and texture) and the moisture effect on soil respiration, with such relations being strongly dependent on the moisture range and the type of measure used (gravimetric, volumetric, water potential, etc.). Most soil properties showed both fixed effects and interactions with moisture when fitting linear regression models. The relations obtained from regression analysis deviate significantly from those used currently in many soil carbon models, indicating the possibility of considerable errors in current soil carbon predictions.

Moyano, F. E.; Vasilyeva, N.; Chenu, C.

2011-12-01

55

The prototype SMOS soil moisture Algorithm  

NASA Astrophysics Data System (ADS)

The Soil Moisture and Ocean Salinity (SMOS) mission is ESA's (European Space Agency ) second Earth Explorer Opportunity mission, to be launched in September 2007. It is a joint programme between ESA CNES (Centre National d'Etudes Spatiales) and CDTI (Centro para el Desarrollo Tecnologico Industrial). SMOS carries a single payload, an L-band 2D interferometric radiometer in the 1400-1427 MHz protected band. This wavelength penetrates well through the atmosphere and hence the instrument probes the Earth surface emissivity. Surface emissivity can then be related to the moisture content in the first few centimeters of soil, and, after some surface roughness and temperature corrections, to the sea surface salinity over ocean. In order to prepare the data use and dissemination, the ground segment will produce level 1 and 2 data. Level 1 will consists mainly of angular brightness temperatures while level 2 will consist of geophysical products. In this context, a group of institutes prepared the soil moisture and ocean salinity Algorithm Theoretical Basis documents (ATBD) to be used to produce the operational algorithm. The consortium of institutes preparing the Soil moisture algorithm is led by CESBIO (Centre d'Etudes Spatiales de la BIOsphère) and Service d'Aéronomie and consists of the institutes represented by the authors. The principle of the soil moisture retrieval algorithm is based on an iterative approach which aims at minimizing a cost function given by the sum of the squared weighted differences between measured and modelled brightness temperature (TB) data, for a variety of incidence angles. This is achieved by finding the best suited set of the parameters which drive the direct TB model, e.g. soil moisture (SM) and vegetation characteristics. Despite the simplicity of this principle, the main reason for the complexity of the algorithm is that SMOS "pixels" can correspond to rather large, inhomogeneous surface areas whose contribution to the radiometric signal is difficult to model. Moreover, the exact description of pixels, given by a weighting function which expresses the directional pattern of the SMOS interferometric radiometer, depends on the incidence angle. The goal is to retrieve soil moisture over fairly large and thus inhomogeneous areas. The retrieval is carried out at nodes of a fixed Earth surface grid. To achieve this purpose, after checking input data quality and ingesting auxiliary data, the retrieval process per se can be initiated. This cannot be done blindly as the direct model will be dependent upon surface characteristics. It is thus necessary to first assess what is the dominant land use of a node. For this, an average weighing function (MEAN_WEF) which takes into account the "antenna" pattern is run over the high resolution land use map to assess the dominant cover type. This is used to drive the decision tree which, step by step, selects the type of model to be used as per surface conditions. All this being said and done the retrieval procedure starts if all the conditions are satisfied, ideally to retrieve 3 parameters over the dominant class (the so-called rich retrieval). If the algorithm does not converge satisfactorily, a new trial is made with less floating parameters ("poorer retrieval") until either results are satisfactory or the algorithm is considered to fail. The retrieval algorithm also delivers whenever possible a dielectric constant parameter (using the-so called cardioid approach). Finally, once the retrieval converged, it is possible to compute the brightness temperature at a given fixed angle (42.5°) using the selected forward models applied to the set of parameters obtained at the end of the retrieval process. So the output product of the level 2 soil moisture algorithm should be node position, soil moisture, dielectric constants, computed brightness temperature at 42.5°, flags and quality indices. The work around the ATBD also encompasses the making of breadboards and prototype, analysis of specific cases (snow, frozen soil, topography, flo

Kerr, Y.; Waldteufel, P.; Richaume, P.; Cabot, F.; Wigneron, J. P.; Ferrazzoli, P.; Mahmoodi, A.; Delwart, S.

2009-04-01

56

Space-time soil moisture variability for two different land use types: analysis at the plot scale  

NASA Astrophysics Data System (ADS)

Understanding space-time soil moisture variability at various scales is a key issue in hydrological research. At the plot scale soil moisture variability is expected to be explained by physical factors such as soil hydraulic properties, local topography and vegetation cover. This study aims to: i) characterize the spatial and temporal variability of soil moisture at the plot scale at two soil depths and for two different types of land use (meadow and vineyard); ii) investigate the role of vegetation cover on the seasonal variability of soil moisture; iii) assess the capability of a dynamic model to explain soil moisture variability and the control exerted by land use. The work is based on soil moisture data collected on a plot (about 200 m2) in Grugliasco (Po River basin, Northern Italy) by means of Time Domain Reflectometry (TDR) measurements. The plot is divided into two subplots: one covered by grapevine plants, the other covered homogeneously by grass. The soil is sandy, the slope is about 1%, and there is a buffer grass area about 20 m wide around the measurement field. The characteristics of the site allow to isolate the contribution of soil hydraulic properties and land use to space-time soil moisture variability. We used the data of 40 probes distributed in the two subplots, vertically inserted into the soil at 0-30 cm and 0-60 cm depths. Precipitation and temperature are recorded continuously on site. Statistics were computed based on soil moisture measurements collected continuously at daily time step over three years (2006-2008). Results show that soil moisture spatial patterns at the two sampling depths are highly correlated for both land uses. Higher values of mean soil moisture at 0-60 cm depth with respect to 0-30 cm for both types of land use likely reflect the evaporation processes affecting more the surface layer. Spatial mean soil moisture is always higher in the vineyard than in the meadow (especially at 0-30 cm depth), implying the influence of vegetation cover during the growing season. An exponential equation fits well the relationship between the spatial coefficient of variation and the mean soil moisture. An increasing variability of the coefficient of variation is observed during periods with high potential evapotranspiration rates (June-August). This is more evident for the grass site at 0-30 cm depth, highlighting again the important shading effect performed by the grapevine leaves. The application of a simple soil moisture dynamic model reveals a general good capability to capture soil moisture temporal dynamics at the plot scale. Moreover, the model reproduces consistently the observed relationships between soil moisture spatial mean and variability. Thus, the model provides a preliminary link between physical processes and statistical variability patterns. Keywords: soil moisture, plot scale, space-time variability, land use.

Zuecco, Giulia; Borga, Marco; Penna, Daniele; Canone, Davide; Ferraris, Stefano

2013-04-01

57

Estimating Surface Soil Moisture in Simulated AVIRIS Spectra  

NASA Technical Reports Server (NTRS)

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

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

2004-01-01

58

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

Technology Transfer Automated Retrieval System (TEKTRAN)

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

59

Soil moisture by extraction and gas chromatography  

NASA Technical Reports Server (NTRS)

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

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

1973-01-01

60

Electrical methods of determining soil moisture content  

NASA Technical Reports Server (NTRS)

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

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

1975-01-01

61

Survey of methods for soil moisture determination  

NASA Technical Reports Server (NTRS)

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

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

1979-01-01

62

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

NASA Technical Reports Server (NTRS)

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

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

2005-01-01

63

Development of an Aquarius Soil Moisture Product  

NASA Astrophysics Data System (ADS)

Aquarius observations over land offer a new resource for measuring soil moisture from space. Our objective in this investigation is to exploit the large amount of land observations that Aquarius acquires and extend the mission scope to land applications through the retrieval of soil moisture. This research increases the value and impact of the Aquarius mission by including a broader scientific community, allowing the exploration of new algorithm approaches that exploit the active-passive observations, and will contribute to a better understanding of the Earth's climate and water cycle. The first stage of our Aquarius soil moisture research focused on the use of the radiometer data because of the extensive heritage that this type of observations has in soil moisture applications. The calibration of the Aquarius radiometer over the entire dynamic range is a key element for the successful implementation of the soil moisture algorithm. Results to date indicate that the Aquarius observations are well calibrated for ocean targets but have a warm bias over land. This bias needed to be addressed if the Aquarius observations are to be used in land applications. Our approach was to use the gain and offsets computed using the Soil Moisture Ocean Salinity (SMOS) comparisons to adjust the Aquarius brightness temperatures. The Single Channel Algorithm (SCA) was implemented using the Aquarius observations. SCA is also the baseline algorithm for the SMAP radiometer-only soil moisture product. Aquarius radiometer observations from the three beams (after bias/gain modification) along with the National Centers for Environmental Prediction (NCEP) surface temperature model forecast were then used to estimate soil moisture. Ancillary data inputs required for using the SCA are vegetation water content, land surface temperature, and several soil and vegetation parameters derived based on land cover. The spatial patterns of the soil moisture estimates are consistent with the climatology and with the other satellite missions (Advanced Microwave Scanning Radiometer-E and SMOS). The soil moisture and temperature products were validated using in situ observations from the Little Washita and Little River watershed soil moisture networks. Results show good performance by the algorithm for these land surface conditions for the period of August 2011-June-2013 (RMSE=0.031 m3/m3, Bias=0.007 m3/m3, and R=0.855). The validated radiometer soil moisture product will serve as a baseline for continuing research on both active and combined passive-active soil moisture algorithms. The soil moisture product was implemented as part of the routine Aquarius data processing and will be available from National Snow and Ice Data Center both in swath and gridded formats in the near future. Acknowledgement: USDA is an equal opportunity employer.

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

2013-12-01

64

Measuring soil moisture with imaging radars  

NASA Technical Reports Server (NTRS)

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

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

1995-01-01

65

Sensitivity of Soil Respiration to Variability in Soil Moisture and Temperature in a Humid Tropical Forest  

PubMed Central

Precipitation and temperature are important drivers of soil respiration. The role of moisture and temperature are generally explored at seasonal or inter-annual timescales; however, significant variability also occurs on hourly to daily time-scales. We used small (1.54 m2), throughfall exclusion shelters to evaluate the role soil moisture and temperature as temporal controls on soil CO2 efflux from a humid tropical forest in Puerto Rico. We measured hourly soil CO2 efflux, temperature and moisture in control and exclusion plots (n?=?6) for 6-months. The variance of each time series was analyzed using orthonormal wavelet transformation and Haar-wavelet coherence. We found strong negative coherence between soil moisture and soil respiration in control plots corresponding to a two-day periodicity. Across all plots, there was a significant parabolic relationship between soil moisture and soil CO2 efflux with peak soil respiration occurring at volumetric soil moisture of approximately 0.375 m3/m3. We additionally found a weak positive coherence between CO2 and temperature at longer time-scales and a significant positive relationship between soil temperature and CO2 efflux when the analysis was limited to the control plots. The coherence between CO2 and both temperature and soil moisture were reduced in exclusion plots. The reduced CO2 response to temperature in exclusion plots suggests that the positive effect of temperature on CO2 is constrained by soil moisture availability. PMID:24312508

Wood, Tana E.; Detto, Matteo; Silver, Whendee L.

2013-01-01

66

SMALT - Soil Moisture from Altimetry project  

NASA Astrophysics Data System (ADS)

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

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

67

SOIL MOISTURE STRUCTURE FOR DIFFERENT SOIL DEPTHS FROM FIELD TO WATERSHED SCALE DURING THE SOIL MOISTURE EXPERIMENT 2005 (SMEX05)  

Technology Transfer Automated Retrieval System (TEKTRAN)

Surface soil moisture characteristics are varied due to physical factors such as vegetation, soil type, and topography as well as climatologic factors such as precipitation. Soil moisture was measured daily at depth of 0, 5, 10, 15, 25, and 50 cm using dielectric probes during the Soil Moisture Expe...

68

Contribution of Soil Moisture Information to Streamflow Prediction in the Snowmelt Season: A Continental-Scale Analysis  

NASA Technical Reports Server (NTRS)

In areas dominated by winter snowcover, the prediction of streamflow during the snowmelt season may benefit from three pieces of information: (i) the accurate prediction of weather variability (precipitation, etc.) leading up to and during the snowmelt season, (ii) estimates of the amount of snow present during the winter season, and (iii) estimates of the amount of soil moisture underlying the snowpack during the winter season. The importance of accurate meteorological predictions and wintertime snow estimates is obvious. The contribution of soil moisture to streamflow prediction is more subtle yet potentially very important. If the soil is dry below the snowpack, a significant fraction of the snowmelt may be lost to streamflow and potential reservoir storage, since it may infiltrate the soil instead for later evaporation. Such evaporative losses are presumably smaller if the soil below the snowpack is wet. In this paper, we use a state-of-the-art land surface model to quantify the contribution of wintertime snow and soil moisture information -- both together and separately -- to skill in forecasting springtime streamflow. We find that soil moisture information indeed contributes significantly to streamflow prediction skill.

Reichle, Rolf; Mahanama, Sarith; Koster, Randal; Lettenmaier, Dennis

2009-01-01

69

Passive Microwave Soil Moisture Disaggregation radar data and relationship between soil moisture, vegetation and surface temperature  

NASA Astrophysics Data System (ADS)

Soil moisture is an important variable in weather and climate. The passive microwave sensors have provided soil moisture of various spatial resolutions and are available for all-weather conditions, including AMSR-E (Advanced Microwave Scanning Radiometer- Earth Observing System), AMSR2 (Advanced Microwave Scanning Radiometer 2) and SMOS (Soil Moisture and Ocean Salinity). However, the spatial resolution of passive microwave soil moisture product is restricted at tens of kilometers level and needs to be improved. Toward this issue, the SMAP (Soil Moisture Active Passive) is set to be launched in October 2014 will be the first mission to provide L-band radar/radiometer soil moisture retrievals at three resolutions. In this paper we present two distinct methods to obtain higher spatial resolution soil moisture. The first one is use of active radar data to downscale soil moisture obtained by passive radiometers. The SMAP Validation Experiment 2012 (SMAPVEX12) was taken place and provided Passive/Active L-band Sensor (PALS) observations of two along-track resolutions (650 m and 1590 m), as well as ground soil moisture measurements. Consequently the PALS data can be used for disaggregating coarse resolution passive soil moisture retrievals. Based on a change detection theory, the relationships between change in radar backscatter and change in soil moisture at both coarse and fine resolutions are examined and used for calculating high spatial resolution soil moisture from AMSR-E and SMOS. Using SMAPVEX12 ground measurements validates the disaggregation results. The second method is use of the relationship between vegetation and surface temperature to downscale soil moisture obtained from passive radiometers. The physical relationships amongst soil moisture, land surface temperature and vegetation index (Normalized Difference Vegetation Index, NDVI), the historic soil moisture data of recent 30 years at 1/8 degree NLDAS (North America Land Data Assimilation Systems) scale were studied and modeled by using the long term records of land surface model and remote sensing products, NLDAS, MODIS (Moderate Resolution Imaging Spectroradiometer) and AVHRR (Advanced Very High Resolution Radiometer). This modeled relationship was then applied to the 1 km MODIS land surface temperature for disaggregating the microwave soil moisture estimates AMSR-E and SMOS in Oklahoma. Two sets of in-situ measurements Oklahoma Mesonet and Little Washita watershed Micronet were used for validating the disaggregated soil moisture.

Lakshmi, Venkat; Fang, Bin

2014-05-01

70

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

Technology Transfer Automated Retrieval System (TEKTRAN)

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

71

Estimating root zone soil moisture using near-surface observations from SMOS  

NASA Astrophysics Data System (ADS)

Satellite-derived soil moisture provides more spatially and temporally extensive data than in situ observations. However, satellites can only measure water in the top few centimeters of the soil. Root zone soil moisture is more important, particularly in vegetated regions. Therefore estimates of root zone soil moisture must be inferred from near-surface soil moisture retrievals. The accuracy of this inference is contingent on the relationship between soil moisture in the near-surface and the soil moisture at greater depths. This study uses cross correlation analysis to quantify the association between near-surface and root zone soil moisture using in situ data from the United States Great Plains. Our analysis demonstrates that there is generally a strong relationship between near-surface (5-10 cm) and root zone (25-60 cm) soil moisture. An exponential decay filter is used to estimate root zone soil moisture using near-surface soil moisture derived from the Soil Moisture and Ocean Salinity (SMOS) satellite. Root zone soil moisture derived from SMOS surface retrievals is compared to in situ soil moisture observations in the United States Great Plains. The SMOS-based root zone soil moisture had a mean R2 of 0.57 and a mean Nash-Sutcliffe score of 0.61 based on 33 stations in Oklahoma. In Nebraska, the SMOS-based root zone soil moisture had a mean R2 of 0.24 and a mean Nash-Sutcliffe score of 0.22 based on 22 stations. Although the performance of the exponential filter method varies over space and time, we conclude that it is a useful approach for estimating root zone soil moisture from SMOS surface retrievals.

Ford, T. W.; Harris, E.; Quiring, S. M.

2014-01-01

72

Soil moisture estimation with limited soil characterization for decision making  

NASA Astrophysics Data System (ADS)

Many decisions in agriculture are conditional to soil moisture. For instance in wet conditions, farming operations as soil tillage, organic waste spreading or harvesting may lead to degraded results and/or induce soil compaction. The development of a tool that allows the estimation of soil moisture is useful to help farmers to organize their field work in a context where farm size tends to increase as well as the need to optimize the use of expensive equipments. Soil water transfer models simulate soil moisture vertical profile evolution. These models are highly sensitive to site dependant parameters. A method to implement the mechanistic soil water and heat flow model (the TEC model) in a context of limited information (soil texture, climatic data, soil organic carbon) is proposed [Chanzy et al., 2008]. In this method the most sensitive model inputs were considered i.e. soil hydraulic properties, soil moisture profile initialization and the lower boundary conditions. The accuracy was estimated by implementing the method on several experimental cases covering a range of soils. Simulated soil moisture results were compared to soil moisture measurements. The obtained accuracy in surface soil moisture (0-30 cm) was 0.04 m3/m3. When a few soil moisture measurements are available (collected for instance by the farmer using a portable moisture sensor), significant improvement in soil moisture accuracy is obtained by assimilating the results into the model. Two assimilation strategies were compared and led to comparable results: a sequential approach, where the measurement were used to correct the simulated moisture profile when measurements are available and a variational approach which take moisture measurements to invert the TEC model and so retrieve soil hydraulic properties of the surface layer. The assimilation scheme remains however heavy in terms of computing time and so, for operational purposed fast code should be taken to simulate the soil moisture as with the Ross model [Ross, 2003, Crevoisier et al, 2009]. To meet the decision support context, we evaluated the model ability of evaluating the soil moisture level in comparison to a moisture threshold that splits soil conditions into desirable and undesirable cases. This threshold depends on soil properties, the farming operation and equipment characteristics. We evaluate the rate of making good decisions using either the TEC model with and without soil moisture measurements or an empirical algorithm that simulate the decision processes followed by farmers, currently. This later is a reference case that allows appreciating the adding value of using soil water transfer models. We found a significant improvement with a rate of success, which increases from 65% with the reference case to 90% when using the model with soil moisture assimilation. Chanzy, A., Mumen M., Richard, G.. (2008), Accuracy of top soil moisture simulation using a mechanistic model with limited soil characterization, Water Resources Research, 44(3), W03432. Crevoisier, D., Chanzy, A., Voltz M. (2009), Evaluation of the Ross Fast Solution of Richards' Equation in Unfavourable Conditions for Standard Finite Element Methods, Advances in Water Ressources, In revision. Ross, P. J. (2003). Modeling soil water and solute transport - Fast, simplified numerical solutions. Agronomy Journal 95:1352-1361.

Chanzy, A.; Richard, G.; Boizard, H.; Défossez, P.

2009-04-01

73

Soil-moisture ground truth, Hand County, South Dakota  

NASA Technical Reports Server (NTRS)

Soil types were determined from the Soil Survey of Hand County, South Dakota. The soil types encountered on the soil moisture lines are summarized. The actual soil moisture data are presented. The data have been divided by range, township and section. The soil moisture data obtained in fields of winter wheat and spring wheat are briefly summarized.

Jones, E. B.

1976-01-01

74

Using Polarimetric SAR Data to Infer Soil Moisture from Surfaces with Varying Subsurface Moisture Profiles  

NASA Technical Reports Server (NTRS)

A time-series approach is used to estimate the moisture content-based on polarimetric SAR data. It is found that under the assumption of constant soil moisture, empirically observed relationships between radar backscatter and moisture are only half as sensitive to moisture as compared to actual radar data. A numerical finite element method is used to calculate the radar backscatter for rough soils with arbitrarily varying soil moisture as a function of depth. Several instance of drying and wetting moisture profiles are considered and the radar backscatter is calculated in each case. Radar backscatter is found to crucially depend on the soil moisture variation in the top half wavelength of soil.

Khankhoje, Uday K.; van Zyl, Jakob; Kim, Yunjin; Cwik, Thomas

2012-01-01

75

Response of spectral vegetation indices to soil moisture in grasslands and shrublands  

USGS Publications Warehouse

The relationships between satellite-derived vegetation indices (VIs) and soil moisture are complicated because of the time lag of the vegetation response to soil moisture. In this study, we used a distributed lag regression model to evaluate the lag responses of VIs to soil moisture for grasslands and shrublands at Soil Climate Analysis Network sites in the central and western United States. We examined the relationships between Moderate Resolution Imaging Spectroradiometer (MODIS)-derived VIs and soil moisture measurements. The Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) showed significant lag responses to soil moisture. The lag length varies from 8 to 56 days for NDVI and from 16 to 56 days for NDWI. However, the lag response of NDVI and NDWI to soil moisture varied among the sites. Our study suggests that the lag effect needs to be taken into consideration when the VIs are used to estimate soil moisture. ?? 2011 Taylor & Francis.

Zhang, L.; Ji, L.; Wylie, B.K.

2011-01-01

76

Remote sensing applications to hydrology: soil moisture  

Microsoft Academic Search

Passive and active microwave remote sensing instruments are capable of measuring the surface soil moisture (0-5 cm) and can be implemented on high altitude platforms, e.g. spacecraft, for repetitive large area observations. The amount of water present in a soil affects its dielectric properties. The dielectric properties, along with several other physical characteristics, determine the microwave measurement. In addi­ tion,

T. J. JACKSON; J. SCHMUGGE; E. T. ENGMAN

1997-01-01

77

Reconstructions of Soil Moisture for the Upper Colorado River Basin Using Tree-Ring Chronologies  

NASA Astrophysics Data System (ADS)

Soil moisture is an important factor in the global hydrologic cycle, but existing reconstructions of historic soil moisture are limited. Tree-ring chronologies (TRCs) were used to reconstruct annual soil moisture in the Upper Colorado River Basin (UCRB). Gridded soil moisture data were spatially regionalized using principal components analysis and k-nearest neighbor techniques. Moisture sensitive tree-ring chronologies in and adjacent to the UCRB were correlated with regional soil moisture and tested for temporal stability. TRCs that were positively correlated and stable for the calibration period were retained. Stepwise linear regression was applied to identify the best predictor combinations for each soil moisture region. The regressions explained 42-78% of the variability in soil moisture data. We performed reconstructions for individual soil moisture grid cells to enhance understanding of the disparity in reconstructive skill across the regions. Reconstructions that used chronologies based on ponderosa pines (Pinus ponderosa) and pinyon pines (Pinus edulis) explained increased variance in the datasets. Reconstructed soil moisture was standardized and compared with standardized reconstructed streamflow and snow water equivalent from the same region. Soil moisture reconstructions were highly correlated with streamflow and snow water equivalent reconstructions, indicating reconstructions of soil moisture in the UCRB using TRCs successfully represent hydrologic trends, including the identification of periods of prolonged drought.

Tootle, G.; Anderson, S.; Grissino-Mayer, H.

2012-12-01

78

Comparing soil moisture memory in satellite observations and models  

NASA Astrophysics Data System (ADS)

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.

Stacke, Tobias; Hagemann, Stefan; Loew, Alexander

2013-04-01

79

Soil Moisture Experiments 2003 (SMEX03)  

NASA Astrophysics Data System (ADS)

A series of large-scale soil moisture field experiments have been conducted over the past decade. These have been successful at addressing a broad range of science question, focusing technology development and demonstration, and providing educational experiences for undergraduate and graduate students. Soil Moisture Experiments 2003 (SMEX03) will focus on satellite based soil moisture products. The NASA Aqua and Japanese ADEOS-II Advanced Microwave Scanning Radiometer (AMSR) Programs are committed to developing and providing daily soil moisture products. This is the first time that this challenging task has ever been attempted. The wide range of vegetation conditions that have to be dealt with, due to the global coverage and multi-temporal observations, exceed those that have been evaluated in previous investigations. For these reasons, validation is critical to the AMSR soil moisture product development and acceptance. SMEX03 will provide validation data for a wide range of vegetation conditions ranging from well-understood grass and wheat in Oklahoma to new observations of the Amazon rainforests. In addition it will provide a test bed for other new satellite instruments such as the Envisat ASAR and aircraft based prototype satellite instruments. SMEX03 will be conducted at U.S. sites in Oklahoma, Georgia and Alabama in June and July and Brazil in September.

Jackson, T. J.

2002-12-01

80

Soil moisture needs in earth sciences  

NASA Technical Reports Server (NTRS)

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

Engman, Edwin T.

1992-01-01

81

Advanced microwave soil moisture studies. [Big Sioux River Basin, Iowa  

NASA Technical Reports Server (NTRS)

Comparisons of low level L-band brightness temperature (TB) and thermal infrared (TIR) data as well as the following data sets: soil map and land cover data; direct soil moisture measurement; and a computer generated contour map were statistically evaluated using regression analysis and linear discriminant analysis. Regression analysis of footprint data shows that statistical groupings of ground variables (soil features and land cover) hold promise for qualitative assessment of soil moisture and for reducing variance within the sampling space. Dry conditions appear to be more conductive to producing meaningful statistics than wet conditions. Regression analysis using field averaged TB and TIR data did not approach the higher sq R values obtained using within-field variations. The linear discriminant analysis indicates some capacity to distinguish categories with the results being somewhat better on a field basis than a footprint basis.

Dalsted, K. J.; Harlan, J. C.

1983-01-01

82

Spatial and temporal variability of modeled and remotely sensed soil moisture products  

NASA Astrophysics Data System (ADS)

Improving numerical weather prediction, as well as hydrological and climate modeling requires reliable information about soil moisture and its spatial and temporal variability, because soil moisture is an essential variable in energy and water balance. Furthermore, knowledge about the spatio-temporal variability of soil moisture is important for up- and downscaling of soil moisture products and for data assimilation. For many applications representative soil moisture time series from large areas or even a global coverage are necessary. While in situ measurements cannot satisfy these criteria, soil moisture products from models and remote sensing are able to provide this data on large scale and in reasonable temporal and spatial resolution. Nevertheless, these products are constrained by the characteristics of the respective model or sensor and retrieval method. In this study, we investigated the temporal and spatial variability of several soil moisture products on a global scale. Two of them are remotely sensed products, the Soil Moisture and Ocean Salinity (SMOS) Level 2 soil moisture product and the Advanced Scatterometer (ASCAT) surface soil moisture product. To include a product with different characteristics than those inherent to remotely sensed products, we also used the modeled ERA Interim soil moisture product from the ECMWF (European Centre for Medium-Range Weather Forecast). Where available, we also included in situ data from the Global Soil Moisture database in our study. We used the following approaches: (1) With a temporal stability analysis the differences in the products were assessed. Mean relative differences were calculated and ranked from low to high on basis of different soil types of the USDA soil classification. The rankings of the different products were compared. Similar rankings show similar spatio-temporal behavior of the products. (2) We analyzed the relationship between spatial mean soil moisture content and spatial variance of soil moisture to characterize the spatial variability of soil moisture for different soil types and climate zones of the Koeppen-Geiger classification. (3) For the identification and quantification of influence factors on soil moisture distribution, the spatial variance of soil moisture was decomposed into time-varying and time-invariant components. This allows distinguishing between 'stable' factors like topography or land use and changing factors, for example seasonal weather changes or vegetation phenology. Through differences of spatio-temporal variability of the soil moisture products, we assessed the characteristics of the different products and thus determined their usefulness for different applications in different regions. Furthermore, we identified influencing factors on the temporal and spatial variability of soil moisture on large scale.

Rötzer, K.; Montzka, C.; Vereecken, H.

2013-12-01

83

Soil moisture-temperature coupling: revisited using remote sensing soil moisture  

NASA Astrophysics Data System (ADS)

Hot extremes have been shown to be induced by antecedent soil moisture deficits and drought conditions in several regions (e.g., Mueller and Seneviratne, 2012). While most previous studies on this topic relied on modeling results or precipitation-based soil moisture information (in particular the standardized precipitation index, SPI), we use here a new merged remote sensing (RS) soil moisture product combining data from active and passive microwave sensors to investigate the relation between the number of hot days (NHD) and preceding soil moisture deficits. Overall, the global patterns of soil moisture-NHD correlations from RS data and from SPI as used in previous studies agree relatively well, suggesting that these patterns are partly independent of the chosen dataset. Nonetheless, the strength of the relationship appears underestimated with RS-based soil mois- ture data compared to SPI-based estimates, in particular in previously iden- tified regions of strong soil moisture-temperature coupling. This is mainly due to the fact that the temporal hydrological variability is less pronounced in the RS data than the SPI estimates in these regions, and that pronounced (dry or wet) anomalies appear underestimated. Further, complementary anal- yses with data from the Global Land Data Assimilation System (GLDAS) suggest that the differences between the RS-based soil moisture-NHD and the precipitation-based SPI-NHD coupling estimates are not primarily due to the use of soil moisture instead of SPI, or to the shallow depth of the RS- based soil moisture retrievals. Mueller, B., and S. I. Seneviratne (2012). Hot days induced by precipitation deficits at the global scale. Proceedings of the National Academy of Sciences, doi: 10.1073/pnas.1204330109.

Hirschi, Martin; Mueller, Brigitte; Dorigo, Wouter; Seneviratne, Sonia I.

2013-04-01

84

Modeling soil moisture patterns in a microscale forest catchment  

NASA Astrophysics Data System (ADS)

The study investigates the spatial variability of the soil moisture on the microscale forest Wüstebach (27 ha) basin. A fully-integrated surface-subsurface flow model is applied to the Wüstebach headwater catchment in Germany which is a tributary to the Erkensruhr river and has a catchment size of about 27 ha. The catchment which is part of the Eifel national park is completely covered by spruce. The catchment is well characterized and monitored. In addition to the discharge data measured since 2007, soil moisture were measured discontinuously at a number of points. In summer 2009 a wireless sensor network was implemented which collects soil moisture data in three different depths at 150 points with an hourly resolution. Spatial patterns of soil moisture provide powerful information for testing distributed models and can provide independent information that are complementary to more traditional data as point discharge measurements. The 3-D fully coupled flow simulation model HydroGeoSphere was applied to this headwater catchment in two spatial resolutions (25 and 100 m). The distributed hydrological model produces spatially explicit predictions that allow more detailed analysis in decision-making than lumped models. With the model the importance of the spatial features of soil moisture patterns is quantified. We will present simulation results as well as a comparison of the predicted spatial patterns of soil moisture with those observed by the wireless sensor network. The comparison will be done using cell-by-cell method, which allows expressing the strength of agreement between simulated and observed soil moisture patterns through measures of similarity between two maps based on a contingency table and expressed in terms of Kappa statistics.

Sciuto, G.; Diekkrüger, B.; Bogena, H.; Rosenbaum, U.; Dwersteg, D.

2010-05-01

85

Towards an integrated soil moisture drought monitor for East Africa  

NASA Astrophysics Data System (ADS)

East Africa contains a number of highly drought prone regions, and the humanitarian consequences of drought in those regions can be severe. The severity of these drought impacts combined with a paucity of in situ monitoring networks has given rise to numerous efforts to develop reliable remote drought monitoring systems based on satellite data, physically-based models, or a combination of the two. Here we present the results of a cross-comparison and preliminary integration of three soil moisture monitoring methodologies that, combined, offer the potential for a soil moisture based drought monitoring system that is robust across the diverse climatic and ecological zones of East Africa. Three independent methods for estimating soil moisture anomalies, the AMSR-E microwave based satellite sensor, the ALEXI thermal infrared based model and the Noah land surface model, are evaluated using triple collocation error analysis (TCEA). TCEA is used to estimate the reliability of each soil moisture anomaly methodology through statistical cross-comparison-a particularly useful approach given the virtual absence of in situ soil moisture data in this region. While AMSR-E, ALEXI, and Noah each appear to produce reliable soil moisture anomaly estimates over some areas within East Africa, many areas posed significant challenges to one or more methods. These challenges include seasonal cloud cover that hinders ALEXI estimates, dense vegetation that impedes AMSR-E retrievals, and complex hydrology that tests the limits of Noah model assumptions. TCEA allows for assessment of the reliability of each method across seasonal and geographic gradients and provides systematic criteria for merging the three methods into an integrated estimate of spatially distributed soil moisture anomalies for all of East Africa. Results for the period 2007-2011 demonstrate the potential and the limitations of this approach in application to real time drought monitoring.

Anderson, W. B.; Hain, C.; Zaitchik, B. F.; Anderson, M. C.; Alo, C. A.; Yilmaz, M. T.

2011-12-01

86

Gravity changes, soil moisture and data assimilation  

NASA Astrophysics Data System (ADS)

Remote sensing holds promise for near-surface soil moisture and snow mapping, but current techniques do not directly resolve the deeper soil moisture or groundwater. The benefits that would arise from improved monitoring of variations in terrestrial water storage are numerous. The year 2002 saw the launch of NASA's Gravity Recovery And Climate Experiment (GRACE) satellites, which are mapping the Earth's gravity field at such a high level of precision that we expect to be able to infer changes in terrestrial water storage (soil moisture, groundwater, snow, ice, lake, river and vegetation). The project described here has three distinct yet inter-linked components that all leverage off the same ground-based monitoring and land surface modelling framework. These components are: (i) field validation of a relationship between soil moisture and changes in the Earth's gravity field, from ground- and satellite-based measurements of changes in gravity; (ii) development of a modelling framework for the assimilation of gravity data to constrain land surface model predictions of soil moisture content (such a framework enables the downscaling and disaggregation of low spatial (500 km) and temporal (monthly) resolution measurements of gravity change to finer spatial and temporal resolutions); and (iii) further refining the downscaling and disaggregation of space-borne gravity measurements by making use of other remotely sensed information, such as the higher spatial (25 km) and temporal (daily) resolution remotely sensed near-surface soil moisture measurements from the Advanced Microwave Scanning Radiometer (AMSR) instruments on Aqua and ADEOS II. The important field work required by this project will be in the Murrumbidgee Catchment, Australia, where an extensive soil moisture monitoring program by the University of Melbourne is already in place. We will further enhance the current monitoring network by the addition of groundwater wells and additional soil moisture sites. Ground-based gravity measurements will also be made on a monthly basis at each monitoring site. There will be two levels of modelling and monitoring; regional across the entire Murrumbidgee Catchment (100,000 km2), and local across a small sub-catchment (150 km2).

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

2003-04-01

87

Conservation and Utilization of Soil Moisture.  

E-print Network

by evaporation will be less than from clay loam soils (8). Farming practices that prevent rapid runoff, leave the surface cloddy to permit rapid penetration (6) and maintain a good cover of crop residues on the surface (4) aid deeper penetration of moisture... significantly increased the amount of available moisture in the soil and the yield of cotton from it. The use of flood waters, crop residues and tillage offer additional means of increasing the amount of water that is stored for plant use. Preseasonal...

Burnett, Earl; Fisher, C. E.

1953-01-01

88

Impact of Soil Moisture Initialization on Seasonal Weather Prediction  

NASA Technical Reports Server (NTRS)

The potential role of soil moisture initialization in seasonal forecasting is illustrated through ensembles of simulations with the NASA Seasonal-to-Interannual Prediction Project (NSIPP) model. For each boreal summer during 1997-2001, we generated two 16-member ensembles of 3-month simulations. The first, "AMIP-style" ensemble establishes the degree to which a perfect prediction of SSTs would contribute to the seasonal prediction of precipitation and temperature over continents. The second ensemble is identical to the first, except that the land surface is also initialized with "realistic" soil moisture contents through the continuous prior application (within GCM simulations leading up to the start of the forecast period) of a daily observational precipitation data set and the associated avoidance of model drift through the scaling of all surface prognostic variables. A comparison of the two ensembles shows that soil moisture initialization has a statistically significant impact on summertime precipitation and temperature over only a handful of continental regions. These regions agree, to first order, with regions that satisfy three conditions: (1) a tendency toward large initial soil moisture anomalies, (2) a strong sensitivity of evaporation to soil moisture, and (3) a strong sensitivity of precipitation to evaporation. The degree to which the initialization improves forecasts relative to observations is mixed, reflecting a critical need for the continued development of model parameterizations and data analysis strategies.

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

2002-01-01

89

Absolute versus temporal anomaly and percent of saturation soil moisture spatial variability for six networks worldwide  

NASA Astrophysics Data System (ADS)

analysis of the spatial-temporal variability of soil moisture can be carried out considering the absolute (original) soil moisture values or relative values, such as the percent of saturation or temporal anomalies. Over large areas, soil moisture data measured at different sites can be characterized by large differences in their minimum, mean, and maximum absolute values, even though in relative terms their temporal patterns are very similar. In these cases, the analysis considering absolute compared with percent of saturation or temporal anomaly soil moisture values can provide very different results with significant consequences for their use in hydrological applications and climate science. In this study, in situ observations from six soil moisture networks in Italy, Spain, France, Switzerland, Australia, and United States are collected and analyzed to investigate the spatial soil moisture variability over large areas (250-150,000 km2). Specifically, the statistical and temporal stability analyses of soil moisture have been carried out for absolute, temporal anomaly, and percent of saturation values (using two different formulations for temporal anomalies). The results highlight that the spatial variability of the soil moisture dynamic (i.e., temporal anomalies) is significantly lower than that of the absolute soil moisture values. The spatial variance of the time-invariant component (temporal mean of each site) is the predominant contribution to the total spatial variance of absolute soil moisture data. Moreover, half of the networks show a minimum in the spatial variability for intermediate conditions when the temporal anomalies are considered, in contrast with the widely recognized behavior of absolute soil moisture data. The analyses with percent saturation data show qualitatively similar results as those for the temporal anomalies because of the applied normalization which reduces spatial variability induced by differences in mean absolute soil moisture only. Overall, we find that the analysis of the spatial-temporal variability of absolute soil moisture does not apply to temporal anomalies or percent of saturation values.

Brocca, L.; Zucco, G.; Mittelbach, H.; Moramarco, T.; Seneviratne, S. I.

2014-07-01

90

Soil moisture modeling and scaling using passive microwave remote sensing  

E-print Network

Soil moisture in the shallow subsurface is a primary hydrologic state governing land-atmosphere interaction at various scales. The primary objectives of this study are to model soil moisture in the root zone in a distributed manner and determine...

Das, Narendra N.

2007-04-25

91

SOIL MOISTURE EXPERIMENTS IN 2002 AND 2003  

Technology Transfer Automated Retrieval System (TEKTRAN)

Soil moisture field experiments have been very successful at addressing a broad range of science question, focusing technology development and demonstration, and providing educational experiences for undergraduate and graduate students. The data have been used in studies that went well beyond the a...

92

Soil moisture ground truth, Lafayette, Indiana, site; St. Charles Missouri, site; Centralia, Missouri, site  

NASA Technical Reports Server (NTRS)

The soil moisture ground-truth measurements and ground-cover descriptions taken at three soil moisture survey sites located near Lafayette, Indiana; St. Charles, Missouri; and Centralia, Missouri are given. The data were taken on November 10, 1975, in connection with airborne remote sensing missions being flown by the Environmental Research Institute of Michigan under the auspices of the National Aeronautics and Space Administration. Emphasis was placed on the soil moisture in bare fields. Soil moisture was sampled in the top 0 to 1 in. and 0 to 6 in. by means of a soil sampling push tube. These samples were then placed in plastic bags and awaited gravimetric analysis.

Jones, E. B.

1975-01-01

93

SMOS CATDS level 3 Soil Moisture products  

NASA Astrophysics Data System (ADS)

The ESA's (European Space Agency) SMOS (Soil Moisture and Ocean Salinity) mission, operating since november 2009, is the first satellite dedicated to measuring surface soil moisture and ocean salinity. The CNES (Centre National d'Etudes Spatiales) has developed a ground segment for the SMOS data, known as the CATDS (Centre Aval de Traitement des Données SMOS). Operational since June 2011, it provides data referred to as level 3 products at different time resolutions: daily products, 3 days global products insuring a complete coverage of the Earth surface, 10-days composite products, and monthly averages products. These products are presented in the NetCDF format on the EASE grid (Equal Area Scalable Earth grid) with a spatial resolution of ~ 25*25 km2. Having global maps at different time resolutions is of interest for different applications such as agriculture, water management, climatic events (especially droughts and floods) or climatology. The soil moisture level 3 algorithm is based on ESA's (European Space Agency) level 2 retrieval scheme with the improvement of using several overpasses (3 at most) over a 7-days window. The benefit of using many revisits is expected to improve the retrieved soil moisture. Along with the surface soil moisture, other geophysical parameters are retrieved such as the vegetation optical depth or the dielectric constant of the surface. The aim of this communication is to present the first results from the CATDS dataset and all the different data available. Comparisons with in situ data at different sites will be presented to assess the quality of these data. A comparison with the ESA level 2 SMOS products will also be shown to better understand the difference between these dataset, in terms of quality, coverage, applications and use. We will also present how the CATDS data can capture some special events. For instance, the dataset will be compared with meteorological events (rain events), or extreme events such as droughts or floods.

Berthon, L.; Mialon, A.; Bitar, A. Al; Cabot, F.; Kerr, Y. H.

2012-04-01

94

Soil moisture inferences from thermal infrared measurements of vegetation temperatures  

NASA Technical Reports Server (NTRS)

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

Jackson, R. D. (principal investigator)

1981-01-01

95

Dry-end surface soil moisture variability during NAFE'06  

Microsoft Academic Search

Characterization of the space-time variability of soil moisture is important for land surface and climate studies. Here we develop an analytical model to investigate how, at the dry-end of the soil moisture range, the main characteristics of the soil moisture field (spatial mean and variability, steady state distribution) depend on the intermittent character of low intensity rain storms. Our model

A. J. Teuling; R. Uijlenhoet; R. T. W. L. Hurkmans; O. Merlin; R. Panciera; J. P. Walker; P. A. Troch

2007-01-01

96

Validation of Advanced Microwave Scanning Radiometer Soil Moisture Products  

Technology Transfer Automated Retrieval System (TEKTRAN)

Validation is an important and particularly challenging task for remote sensing of soil moisture. The key issue in the validation of soil moisture products is the disparity in spatial scales between satellite and in situ observations. Conventional measurements of soil moisture are made at a point wh...

97

Feasibility of Soil Moisture Estimation using Passive Distributed Temperature Sensing  

E-print Network

and land-atmosphere interactions. Point observations of soil moisture are easy to make using established at the land surface, soil moisture has been identified as a key state variable in surface hydrology and land-atmosphere Aeronautics and Space Administration (NASA) will launch the first dedicated satellite missions (Soil Moisture

Selker, John

98

A microwave scattering model for soil moisture movement  

Microsoft Academic Search

A microwave scattering model for soil moisture movement is developed by integrating three models: a moisture profile model, a dielectric constant model, and a soil surface electromagnetic scattering model. As an application, the model is used to assess the impact of moisture infiltration on soil scattering characteristics

Mostafa A. Karam; GenCorp Aerojet

1998-01-01

99

Estimating Soil Moisture With the Support Vector Regression Technique  

Microsoft Academic Search

This letter presents an experimental analysis of the application of the ?-insensitive support vector regression (SVR) technique to soil moisture content estimation from remotely sensed data at field\\/basin scale. SVR has attractive properties, such as ease of use, good intrinsic generalization capability, and robustness to noise in the training data, which make it a valid candidate as an alternative to

Luca Pasolli; Claudia Notarnicola; Lorenzo Bruzzone

2011-01-01

100

Microwave soil moisture estimation in humid and semiarid watersheds  

NASA Technical Reports Server (NTRS)

Land surface hydrologic-atmospheric interactions in humid and semi-arid watersheds were investigated. Active and passive microwave sensors were used to estimate the spatial and temporal distribution of soil moisture at the catchment scale in four areas. Results are presented and discussed. The eventual use of this information in the analysis and prediction of associated hydrologic processes is examined.

O'Neill, P. E.; Jackson, T. J.; Chauhan, N. S.; Seyfried, M. S.

1993-01-01

101

Preliminary assessment of soil moisture over vegetation  

NASA Technical Reports Server (NTRS)

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.

Carlson, T. N.

1986-01-01

102

Analysis of ASAR Wide Swath Mode time series for the retrieval of soil moisture in mountainous areas  

NASA Astrophysics Data System (ADS)

Soil moisture is a key element in the global cycles of water, energy, and carbon. Knowledge on the spatial and temporal distribution of the soil moisture content (SMC) is therefore essential for a number of hydrological applications as well as earth sciences like meteorology or climatology (Heathman et al., 2003). In the last few years there has been an increasing interest towards the estimation of SMC at local scales using active microwave sensors (Barret et al., 2009). Compared to passive microwave sensors, SAR offers the potential to provide data at high spatial resolution (modern sensors can acquire images with up to approximately 1 m), which is particularly important in mountainous areas. So far, these areas have been considered only marginally in research and only pioneer studies can be found in the literature (Brocca et al., 2012; Bertoldi et al. 2013). In this work we analyzed the temporal and spatial dynamics of the surface SMC (0 - 5 cm depth) on the basis of ground data collected by fixed meteorological stations located in the emerging Long-Term Ecological Research (LTER) site Mazia Valley (Province of Bolzano, South Tyrol, Italy), SAR data from ENVISATs ASAR sensor, wide swath (WS) mode (acquired between 2005 and 2012), and SMC estimates from the hydrological model GEOtop (Endrizzi et al., 2013). The SMC retrieval process was based on the support vector regression (SVR) method introduced by Pasolli et al. (2011). The training of the algorithm was based on data acquired in 2010. Furthermore, the SAR backscatter and derived SMC have been compared with time-series derived from the distributed hydrological model GEOtop. The differences in terms of temporal and spatial dynamic have been analyzed. The main goal of this work is to evaluate the spatial and temporal patterns of SAR derived SMC at field scale and to correlate them with ground information. This is a preparatory study to establish a methodology for the retrieval of SMC with high spatial and temporal sampling and to improve retrieval accuracies by integrating temporal information from different sources of ancillary data and from SAR time-series. It was found that the dynamics of both, temporal and spatial SMC patterns obtained from various data sources (ASAR, GEOtop and meteorological stations), show a similar general temporal behaviour that indicates the robustness of the retrieval algorithm with ASAR WS. However, depending on land cover, soil type and local topographic conditions different spatial patters can be found between SMC estimations coming from ASAR and from the GEOtop model. Introducing information on the temporal behaviour of the SAR signal proves to be a promising method for increasing the confidence and accuracy in estimating SMC, complementing hydrological model predictions. Following steps were identified as critical for the retrieval process: the topographic correction and geocoding of SAR data and the calibration of the meteorological stations. Both factors can have significant influence on the quality of SMC estimation. The accuracy of meteorological input and soil parameterization were identified as the most crucial challenges for SMC derived from hydrological modeling. References Barrett, B. W., E. Dwyer, and P. Whelan. "Soil moisture retrieval from active spaceborne microwave observations: An evaluation of current techniques." Remote Sensing 1, no. 3 (2009): 210-242. Bertoldi, G., S. Della Chiesa, C. Notarnicola, L. Pasolli, G. Niedrist, and U. Tappeiner. "Estimation of soil moisture patterns in mountain grasslands by means of SAR RADARSAT 2 images and hydrological modeling." Journal of Hydrology (2014). under revision. Brocca, L., A. Tarpanelli, T. Moramarco, F. Melone, S. M. Ratto, M. Cauduro, S. Ferraris et al. "Soil Moisture Estimation in Alpine Catchments through Modeling and Satellite Observations." Vadose Zone Journal (2013). Endrizzi, S., S. Gruber, M. Dall'Amico, and R. Rigon. "GEOtop 2.0: simulating the combined energy and water balance at and below the land surface accounting for soil fr

Greifeneder, Felix; Notarnicola, Claudia; Cuozzo, Giovanni; Spindler, Nadine; Bertoldi, Giacomo; Della Chiesa, Stefano; Niedrist, Georg; Stamenkovic, Jelena; Wagner, Wolgang

2014-05-01

103

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

Technology Transfer Automated Retrieval System (TEKTRAN)

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

104

Soil Moisture from Satellite Radar Altimetry (SMALT)  

NASA Astrophysics Data System (ADS)

Soil surface moisture is a key scientific parameter; however, it is extremely difficult to measure remotely, particularly in arid and semi-arid terrain. This paper outlines the development of a novel methodology to generate soil moisture estimates in these regions from multi-mission satellite radar altimetry. Key to this approach is the development of detailed DRy EArth ModelS (DREAMS) which encapsulate the detailed and intricate surface brightness variations over the Earth's land surface resulting from changes in surface roughness and composition. These models are made by cross-calibrating and reconciling multi-mission altimeter sigma0 measurements from ERS1, ERS2, EnviSat and Jason2. This approach is made possible because altimeters are nadir-pointing, and most of the available radar altimeter datasets are from instruments operating in Ku band. These DREAMS are complicated to build and require multiple stages of processing and manual intervention. However this approach obviates the requirement for detailed ground truth to populate theoretical models, facilitating derivation of surface soil moisture estimates over arid regions, where detailed survey data are generally not available. This paper presents results from the creation of the DREAMS over desert surfaces, and showcases the model development over the Simpson desert, the Sahara, and the Kalahari desert. A global assessment is given of areas where DREAMS may successfully be generated, and an outline of the required processing to obtain soil surface moisture estimates is given. Results for altimeter derived soil moisture validation are presented for the Simpson desert, assessed against the Queensland Climate Change Centre AussieGRASS model outputs. First soil moisture products from ERS2 and EnviSat radar altimetry in arid regions are presented, and the temporal and spatial resolution of these data are analysed. The results generated by this ESA sponsored initiative will be made freely available to the global scientific community. First products are planned for release within the next twelve months. Further information can be found at http://tethys.eaprs.cse.dmu.ac.uk/SMALT.

Berry, P. A. M.; Dowson, M.; Smith, R. G.; Carter, J.; Benveniste, J.; Witheridge, S.

2012-04-01

105

Microwave Soil Moisture Retrieval Under Trees  

NASA Technical Reports Server (NTRS)

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

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

2008-01-01

106

Assessing Soil Moisture Regimes with Traditional and New Methods  

Microsoft Academic Search

individual precipitation events, but shallow enough to show seasonal variations. Soil moisture regime classes are required by U.S. soil taxonomy The lack of data on the actual long-term daily soil and other classification systems. Soil moisture regimes are based on long-term daily data of soil water content, which are as a rule estimated moisture requires the characterization of the pedoclimate

Edoardo A. C. Costantini; Fabio Castelli; Salvatore Raimondi; Paolo Lorenzoni

2002-01-01

107

Improving Estimates of Root-zone Soil Water Content Using Soil Hydrologic Properties and Remotely Sensed Soil Moisture  

NASA Astrophysics Data System (ADS)

Newly defined relationships between remotely sensed soil moisture and soil hydraulic parameters were used to develop fine-scale (100 m) maps of root-zone soil moisture (RZSM) content at the regional scale on a daily time-step. There are several key outcomes from our research: (1) the first multi-layer regional dataset of soil hydraulic parameters developed from gSSURGO data for hydrologic modeling efforts in the Chequemegon Ecosystem Atmospheric Study (ChEAS) region, (2) the operation and calibration of a new model for estimating soil moisture flow through the root-zone at eddy covariance towers across the U.S. using remotely sensed active and passive soil moisture products, and (3) region-wide maps of estimated root-zone soil moisture content. The project links soil geophysical analytical approaches (pedotransfer functions) to new applications in remote sensing of soil moisture that detect surface moisture (~5 cm depth). We answer two key questions in soil moisture observation and prediction: (1) How do soil hydrologic properties of U.S. soil types quantitatively relate to surface-to-subsurface water loss? And (2) Does incorporation of fine-scale soil hydrologic parameters with remotely sensed soil moisture data provide improved hindcasts of in situ RZSM content? The project meets several critical research needs in estimation of soil moisture from remote sensing. First, soil moisture is known to vary spatially with soil texture and soil hydraulic properties that do not align well with the spatial resolution of current remote sensing products of soil moisture (~ 50 km2). To address this, we leveraged new advances in gridded soil parameter information (gSSURGO) together with existing remotely sensed estimates of surface soil moisture into a newly emerging semi-empirical modeling approach called SMAR (Soil Moisture Analytical Relationship). The SMAR model was calibrated and cross-validated using existing soil moisture data from a portion of AMERIFLUX tower sites and the NRCS Soil Climate Analysis Network (SCAN). Our preliminary results show good performance of the SMAR model for predicting RZSM at the site level (root mean square error = 0.04). Second, a calibrated SMAR parameter governing the surface to subsurface rate of water flow was related to soil hydraulic properties at the AMERIFLUX tower sites, and region-wide maps of SMAR parameters were developed for the ChEAS region using gSSURGO information. Finally, region-wide maps of RZSM were developed and validated for the ChEAS region. The RZSM products can be directly incorporated with regional CO2 flux modeling, and the results inform - but are not dependent on - efforts that integrate observed soil moisture data with planned NASA missions (e.g., SMAP).

Baldwin, D. C.; Miller, D. A.; Singha, K.; Davis, K. J.; Smithwick, E. A.

2013-12-01

108

Predicting Soil Moisture in the Southern Appalachians1  

Microsoft Academic Search

ABSTRACT Soil moisture was measured for 3.5 years on forested slopes in the mountains of western North Carolina to develop equations for predicting soil moisture content of watersheds. Predictors used were precipitation and easily measured topo- graphic, seasonal, and soil physical factors; among these, sand content and moisture'^etention at 1-bar suction were the best predictors of moisture icontent. Position on

J. D. Helvey; J. D. Hewlett; J. E. Douglass

1972-01-01

109

Quantifying Shrink Swell Capacity of Soil Using Soil Moisture Isotherms  

NASA Astrophysics Data System (ADS)

Vertisols, soils instinctively known for their expansive clays that cause them to have a high shrink swell potential, cover 2.4% of the earths ice-free land. In the United States these expansive soils can cause upwards of 6 billion in damages to pavements, foundations, and utility lines annually (Brady & Weil, 2010). Because of this, it is especially important that a soils ability to shrink and swell is well characterized when making engineering decisions. One traditional method for measuring a soil's expansive potential, the Coefficient of Linear Extensibility (COLE), can take weeks to months to complete (Grossman et al., 1968; Schafer and Singer, 1976b). Use of soil moisture isotherms, or the Soil Moisture Characteristic Curve (SMCC), in recent research has shown that the slope of the SMCC is related to a soils swelling potential (McKeen, 1992). The goal of this research is to evaluate the robustness of the relationship between the SMCC and COLE for a set of well-characterized test soils with COLE ranging from 0 to 0.176. If expansive potential can be reliably predicted from the SMCC, then data from recently developed automatic soil moisture isotherm generators could be used to characterize expansive potential with a fraction of the time and effort necessary for traditional techniques.

Rivera, L. D.; Cobos, D. R.; Campbell, C. S.; Morgan, C.

2013-12-01

110

Root-zone soil moisture estimation using data-driven methods  

NASA Astrophysics Data System (ADS)

soil moisture state partitions both mass and energy fluxes and is important for many hydro-geochemical cycles, but is often only measured within the surface layer. Estimating the amount of soil moisture in the root-zone from this information is difficult due to the nonlinear and heterogeneous nature of the various processes which alter the soil moisture state. Data-driven methods, such as artificial neural networks (ANN), mine data for nonlinear interdependencies and have potential for estimating root-zone soil moisture from surface soil moisture observations. To create an ANN root-zone model that was nonsite-specific and physically constrained, a training set was generated by forcing HYDRUS-1D with meteorological observations for different soil profiles from the unsaturated soil hydraulic database. Ensemble ANNs were trained to provide soil moisture at depths of 10, 20, and 50 cm below the surface using surface soil moisture observations and local meteorological information. Insights into the processes represented by the ANNs were derived from a clamping sensitivity analysis and by changing the ANNs input data. Further model testing based on synthetic soil moisture profiles from three McMaster Mesonet and three USDA soil climate analysis network sites suggests that ANNs are a flexible tool capable of predicting root-zone soil moisture with good accuracy. It was found that ANNs could well represent soil moisture as estimated by HYDRUS-1D, but performance was reduced in comparison to in situ soil moisture observations outside the training conditions. The transferability of the model appears limited to the same geographic region.

Kornelsen, Kurt C.; Coulibaly, Paulin

2014-04-01

111

Soil moisture at watershed scale: Remote sensing techniques  

NASA Astrophysics Data System (ADS)

Soil moisture at high spatial resolution is required for various land processes related studies. However, currently the resolution of passive microwave retrieved soil moisture is low - around 25 km. To solve this problem, a soil moisture disaggregation algorithm based on thermal inertia relationship between daily temperature change and average soil moisture modulated by vegetation conditions has been formulated. This algorithm was applied to the AMSR-E (Advanced Microwave Scanning Radiometer - Earth Observing System) as well as SMOS (Soil Moisture and Ocean Salinity satellite) to produce the 1 km downscaled soil moisture over the Little Washita Watershed in Oklahoma for the growing season in 2010 and 2011.The disaggregated soil moisture has been compared to in situ observations. The results of this approach are very encouraging.

Fang, Bin; Lakshmi, Venkat

2014-08-01

112

A method for estimating soil moisture availability  

NASA Technical Reports Server (NTRS)

A method for estimating values of soil moisture based on measurements of infrared surface temperature is discussed. A central element in the method is a boundary layer model. Although it has been shown that soil moistures determined by this method using satellite measurements do correspond in a coarse fashion to the antecedent precipitation, the accuracy and exact physical interpretation (with respect to ground water amounts) are not well known. This area of ignorance, which currently impedes the practical application of the method to problems in hydrology, meteorology and agriculture, is largely due to the absence of corresponding surface measurements. Preliminary field measurements made over France have led to the development of a promising vegetation formulation (Taconet et al., 1985), which has been incorporated in the model. It is necessary, however, to test the vegetation component, and the entire method, over a wide variety of surface conditions and crop canopies.

Carlson, T. N.

1985-01-01

113

Evolution of physical controls for soil moisture in humid and subhumid watersheds  

NASA Astrophysics Data System (ADS)

The covariability of soil moisture with soil, vegetation, topography, and precipitation is linked by physical relationships. The influence of each of these interdependent physical controls on soil moisture spatial distribution depends on the nature of heterogeneity present in the domain and evolves with time and scale. This paper investigates the effect of three physical controls, i.e., topography (slope), vegetation (type), and soil (texture), on soil moisture spatial distribution in the Little Washita and Walnut Creek watersheds in Oklahoma and Iowa, respectively, at two support scales. Point-support-scale data collected from four soil moisture campaigns (SMEX02, SMEX03, SMEX05, and CLASIC07) and airborne-scale data from three soil moisture campaigns (SGP97, SGP99, and SMEX02) were used in this analysis. The effect of different physical controls on the spatial mean and variability of soil moisture was assessed using Kruskal-Wallis and Shannon entropy respectively. It was found that at both (point and airborne) support scales, nonuniform precipitation (forcing) across the domain can mask the effect of the dominant physical controls on the soil moisture distribution. In order to isolate land-surface controls from the impact of forcing, the effect of precipitation variability was removed. After removing the effect of precipitation variability, it was found that for most soil moisture conditions, soil texture as opposed to vegetation and topography is the dominant physical control at both the point and airborne scales in Iowa and Oklahoma. During a very wet year (2007), however, the effect of topography on the soil moisture spatial variability overrides the effect of soil texture at the point support scale. These findings are valuable for developing any physically based scaling algorithms to upscale or downscale soil moisture between the point and watershed scales in the studied watersheds in humid and subhumid regions of the Great Plains of USA. These results may also be used in designing effective soil moisture field campaigns.

Gaur, Nandita; Mohanty, Binayak P.

2013-03-01

114

Effects of land cover on water table, soil moisture, evapotranspiration, and groundwater recharge: A Field observation and analysis  

USGS Publications Warehouse

The effects of land cover on water table, soil moisture, evapotranspiration, and groundwater recharge were studied with water level measurements collected from two monitoring wells over a period of 122 days. The two wells were installed under similar conditions except that one was drilled on the east side of a creek which was covered with grass, and the other on the west side of the creek which was burned into a bare ground. Substantial differences in water level fluctuations were observed at these two wells. The water level in the east grass (EG) well was generally lower and had much less response to rainfall events than the west no-grass (WNG) well. Grass cover lowered the water table, reduced soil moisture through ET losses, and thus reduced groundwater recharge. The amount of ET by the grass estimated with a water table recession model decreased exponentially from 7.6 mm/day to zero as the water table declined from near the ground surface to 1.42 m below the ground surface in 33 days. More groundwater recharge was received on the WNG side than on the EG side following large rainfall events and by significant slow internal downward drainage which may last many days after rainfall. Because of the decreased ET and increased R, significantly more baseflow and chemical loads may be generated from a bare ground watershed compared to a vegetated watershed. ?? 2005 Elsevier Ltd All rights reserved.

Zhang, Y.-K.; Schilling, K.E.

2006-01-01

115

Measuring soil moisture with imaging radars  

Microsoft Academic Search

An empirical algorithm for the retrieval of soil moisture content and surface root mean square (RMS) height from remotely sensed radar data was developed using scatterometer data. The algorithm is optimized for bare surfaces and requires two copolarized channels at a frequency between 1.5 and 11 GHz. It gives best results for kh⩽2.5, ?υ⩽35%, and ?⩾30°. Omitting the usually weaker

Pascale C. Dubois; Jakob van Zyl; Ted Engman

1995-01-01

116

Feasibility of soil moisture estimation using passive distributed temperature sensing  

E-print Network

(DTS) will be introduced as an experimental method of measuring soil moisture on the basis of DTS in length, and DTS equipment allows measurement of temperatures every 1 m. The passive soil DTS concept study demonstrate that passive soil DTS can detect changes in thermal properties. Deriving soil moisture

Selker, John

117

Spatial and temporal soil moisture and drought variability in the Upper Colorado River Basin  

NASA Astrophysics Data System (ADS)

SummaryThis research investigates the interannual variability of soil moisture as related to large-scale climate variability and also evaluates the spatial and temporal variability of modeled deep layer (40-140 cm) soil moisture in the Upper Colorado River Basin (UCRB). A three layers hydrological model VIC-3L (Variable Infiltration Capacity Model - 3 layers) was used to generate soil moisture in the UCRB over a 50-year period. By using wavelet analysis, deep layer soil moisture was compared to the Palmer Drought Severity Index (PDSI), precipitation, and streamflow to determine whether deep soil moisture is an indicator of climate extremes. Wavelet and coherency analysis for the UCRB indicated a strong relationship between the PDSI, climate variability and the deep soil moisture. The spatial variability of soil moisture during drought, normal, and wet years was analyzed by using map analysis. Distinct regions showing higher vulnerability to drought and wet conditions were identified in the spatial analysis. The temporal variation in soil moisture was performed by utilizing map analysis in pre-drought, drought, and post-drought years for four drought events, 1953-1956, 1959-1964, 1974-1977, and 1988-1992. Less than 50% of the basin had dry conditions (soil moisture anomaly below -10 mm) for the pre-drought years. Soil moisture anomalies were lower than -10 mm for more than 50% of the basin in 15 out of 19 drought years. Generally, droughts did not end until the average soil moisture anomalies increased to positive values for two consecutive years.

Tang, Chunling; Piechota, Thomas C.

2009-12-01

118

Assimilation of Passive and Active Microwave Soil Moisture Retrievals  

NASA Technical Reports Server (NTRS)

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.

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

2012-01-01

119

Direct soil moisture controls of future global soil carbon changes: An important source of uncertainty  

NASA Astrophysics Data System (ADS)

The nature of the climate-carbon cycle feedback depends critically on the response of soil carbon to climate, including changes in moisture. However, soil moisture-carbon feedback responses have not been investigated thoroughly. Uncertainty in the response of soil carbon to soil moisture changes could arise from uncertainty in the relationship between soil moisture and heterotrophic respiration. We used twelve soil moisture-respiration functions (SMRFs) with a soil carbon model (RothC) and data from a coupled climate-carbon cycle general circulation model to investigate the impact of direct heterotrophic respiration dependence on soil moisture on the climate-carbon cycle feedback. Global changes in soil moisture acted to oppose temperature-driven decreases in soil carbon and hence tended to increase soil carbon storage. We found considerable uncertainty in soil carbon changes due to the response of soil respiration to soil moisture. The use of different SMRFs resulted in both large losses and small gains in future global soil carbon stocks, whether considering all climate forcings or only moisture changes. Regionally, the greatest range in soil carbon changes across SMRFs was found where the largest soil carbon changes occurred. Further research is needed to constrain the soil moisture-respiration relationship and thus reduce uncertainty in climate-carbon cycle feedbacks. There may also be considerable uncertainty in the regional responses of soil carbon to soil moisture changes since climate model predictions of regional soil moisture changes are less coherent than temperature changes.

Falloon, Pete; Jones, Chris D.; Ades, Melanie; Paul, Keryn

2011-09-01

120

Optimizing Soil Moisture Sampling Locations for Validation Networks for SMAP  

NASA Astrophysics Data System (ADS)

Soil Moisture Active Passive satellite (SMAP) is scheduled for launch on Oct 2014. Global efforts are underway for establishment of soil moisture monitoring networks for both the pre- and post-launch validation and calibration of the SMAP products. In 2012 the SMAP Validation Experiment, SMAPVEX12, took place near Carman Manitoba, Canada where nearly 60 fields were sampled continuously over a 6 week period for soil moisture and several other parameters simultaneous to remotely sensed images of the sampling region. The locations of these sampling sites were mainly selected on the basis of accessibility, soil texture, and vegetation cover. Although these criteria are necessary to consider during sampling site selection, they do not guarantee optimal site placement to provide the most efficient representation of the studied area. In this analysis a method for optimization of sampling locations is presented which combines the state-of-art multi-objective optimization engine (non-dominated sorting genetic algorithm, NSGA-II), with the kriging interpolation technique to minimize the number of sampling sites while simultaneously minimizing the differences between the soil moisture map resulted from the kriging interpolation and soil moisture map from radar imaging. The algorithm is implemented in Whitebox Geospatial Analysis Tools, which is a multi-platform open-source GIS. The optimization framework is subject to the following three constraints:. A) sampling sites should be accessible to the crew on the ground, B) the number of sites located in a specific soil texture should be greater than or equal to a minimum value, and finally C) the number of sampling sites with a specific vegetation cover should be greater than or equal to a minimum constraint. The first constraint is implemented into the proposed model to keep the practicality of the approach. The second and third constraints are considered to guarantee that the collected samples from each soil texture categories or vegetation cover types are statistically meaningful. The proposed model is applied to the radar images from the Passive Active L-band System (PALS) collected during (SMAPVEX12). SMAPVEX12 lasted for 47 days, during which soil moisture varied significantly. The proposed model was applied to all of the collected images (17 images) during this time span. Optimized sampling site characteristics will be analyzed with surface characteristics and the trade off between the number of samples and estimated sampling error examined.

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

2013-12-01

121

Ultrasonic Velocity Variations with Soil Composition for Moisture Measurement  

NASA Technical Reports Server (NTRS)

Soil moisture content may be measured by many methods, but the presently available techniques all have drawbacks when used in ground truth measurements for remote sensing. Ultrasonic velocity varies with soil moisture content, and may be used as the basis of a new measurement technique. In order to characterize a sensor capable of field use, soil particle size distribution data are compared to ultrasonic velocity in a variety of soils over a wide moisture range.

Metzl, R.; Choi, J.; Aggarwal, M. D.; Manu, A.

1998-01-01

122

Comparison of deep soil moisture in two re-vegetation watersheds in semi-arid regions  

NASA Astrophysics Data System (ADS)

Soil moisture stored below rainfall infiltration depth is a reliable water resource for plant growth in semi-arid ecosystems. Along with the large-scale ecological restoration in Chinese Loess Plateau, identifying the ecohydrological response to human-introduced vegetation restoration has become an important issue in current research. In this study, soil moisture data in depth of 0-5 m was obtained by field observation and geostatistical method in two neighboring re-vegetation watersheds. Profile characteristics and spatial pattern of soil moisture was compared between different land use types, transects, and watersheds. The results showed that: (1) Introduced vegetation drastically decreased deep soil moisture when compared with farmland and native grassland. No significant differences in deep soil moisture were found between different introduced vegetation types. (2) An analysis of differences in soil moisture for different land use patterns indicated that land use had significant influence on deep soil moisture spatial variability. Land use structure determined the soil moisture condition and its spatial variation. (3) Vegetation restoration with introduced plants diminished the spatial heterogeneity of deep soil moisture on watershed scale. The improvement of land use management was suggested to improve the water management and maintain the sustainability of vegetation restoration.

Yang, Lei; Chen, Liding; Wei, Wei; Yu, Yang; Zhang, Handan

2014-05-01

123

Predictability of soil moisture and runoff in Switzerland  

NASA Astrophysics Data System (ADS)

Hydrological forecasts are an important tool in water resource management, especially in case of extreme events. This study investigates the potential predictability of soil moisture and runoff in Switzerland using a conceptual simple water balance model. We validate and add a snow module to the model to capture impacts of snow melting. Our results show that soil moisture and runoff are well predictable until lead times of approximately one week and 2-3 days, respectively, when using only initial soil moisture information. Using also initial snow information and seasonal weather forecasts the predictable time scales double in case of soil moisture and triple for runoff. The skill contributions of the additional information vary with altitude; at low levels the precipitation forecast is most important whereas in mountainous areas the temperature forecast and the initial snow information are the most valuable contributors. We find furthermore that information about initial soil moisture lead to better soil moisture and runoff forecasts the more anomalous the initial soil moisture content is. We show that a realistic initial soil moisture content is more important for a soil moisture forecast than a good forcing forecast because inaccurate initial soil moisture values deteriorate the forecast much stronger than atmospheric forcing with zero skill. For runoff forecasts we find the opposite; due to its strong relation with precipitation the forcing forecasts are more important.

Orth, Rene; Seneviratne, Sonia I.

2013-04-01

124

A simulation study of scene confusion factors in sensing soil moisture from orbital radar  

NASA Technical Reports Server (NTRS)

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.

Ulaby, F. T. (principal investigator); Dobson, M. C.; Moezzi, S.; Roth, F. T.

1983-01-01

125

Impacts of soil moisture in different layers on soil moisture-evapotranspiration interactions over the U.S. Great Plains  

NASA Astrophysics Data System (ADS)

Soil moisture plays an important role in land-atmosphere interactions through both surface energy and water balances. Evapotranspiration is a key factor that contributes to both soil moisture-temperature, and soil moisture-precipitation interactions. However, total evapotranspiration is too general to reflect the impacts of soil moisture to latent and sensible heat fluxes, because evaporation/transpiration occur at different near surface layers. It is necessary to focus on the interactions between soil moisture and each component of evapotranspiration. This project aims to analyze the impacts of soil moisture in different soil layers to each component of evapotranspiration combining with vegetation scheme over the U.S. Great Plains. Observed soil moisture will be derived from the North American Soil Moisture Database. Two-source PET model will be applied to partition evapotranspiration into canopy evaporation, transpiration and soil evaporation. This project will provide reliable results for calibrating and validating vegetation and soil hydrology parameterizations in land surface models and climate models at regional scale and also develop a more exhaustive understanding on soil moisture-precipitation interactions.

Yuan, S.

2013-12-01

126

Ultrasound Algorithm Derivation for Soil Moisture Content Estimation  

NASA Technical Reports Server (NTRS)

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

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

1997-01-01

127

Soil Moisture and the Drought in Texas Todd Caldwell  

E-print Network

Soil Moisture and the Drought in Texas Todd Caldwell Bridget Scanlon Michael Young Di Long Water Forum III: Droughts and Other Extreme Weather Events October 14, 2013 Photo by TPWD Photo by TWDB #12;Soil Moisture and the Drought in Texas I. How is drought linked to water resources? II. Where does soil

Yang, Zong-Liang

128

Temporal heterogeneity of soil moisture in grassland and forest  

Microsoft Academic Search

Summary 1 Differences between growth forms in the spatial heterogeneity of associated soil resources, such as water, are well-documented. We tested for differences in the temporal heterogeneity of soil moisture between natural grassland, shrubland and Populus tremuloides forest at the northern edge of the Great Plains. 2 Weekly measurements of soil moisture over a year, and daily measurements during a

Sarah E. James; Meelis Pärtel; Scott D. Wilson; Duane A. Peltzer

2003-01-01

129

Inferring Land Surface Model Parameters for the Assimilation of Satellite-Based L-Band Brightness Temperature Observations into a Soil Moisture Analysis System  

NASA Technical Reports Server (NTRS)

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.

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

2012-01-01

130

Relating TRMM precipitation radar land surface backscatter response to soil moisture in the Southern United States  

NASA Astrophysics Data System (ADS)

SummarySoil moisture is an important variable in the hydrological cycle and plays a vital role in agronomy, meteorology, and hydrology. It regulates the exchange of water and heat between land surface and atmosphere and thus plays an important role in the development of weather patterns. It is difficult to obtain a comprehensive spatio-temporal map of soil moisture because of expensive installation of soil moisture measuring instruments. In this paper, a model to estimate soil moisture ( m s) using Tropical Rainfall Measuring Mission Precipitation Radar (TRMMPR) backscatter ( ?°) and Normalized Difference Vegetation Index (NDVI) is developed for the Southern United States. Soil moisture data from Soil and Climate Analysis Network (SCAN) stations is used to calibrate and validate the model. The estimated values of m s compare well with the ground measurements of soil moisture. The model works well for various landcovers but works best for low density vegetated areas (closed shrubland). All the soil moisture estimates in this landcover have an absolute error of less than 8%. The model performance deteriorates with increase in vegetation density (crops and forest). Overall, the model performance is satisfactory for all landcover types with RMSE less than 6.3% and absolute error of 10% or less for 90% of the estimates. Estimation of soil moisture over a large area with low error provides another use of TRMMPR data.

Puri, Sumit; Stephen, Haroon; Ahmad, Sajjad

2011-05-01

131

Use of Ultrasonic Technology for Soil Moisture Measurement  

NASA Technical Reports Server (NTRS)

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

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

1997-01-01

132

UNCORRECTEDPROOF 1 Towards deterministic downscaling of SMOS soil moisture using MODIS derived soil  

E-print Network

UNCORRECTEDPROOF 1 Towards deterministic downscaling of SMOS soil moisture using MODIS derived soil online xxxx Keywords: Downscaling Disaggregation Soil moisture Evaporative fraction NAFE SMOS MODIS 10 11 A deterministic approach for downscaling 40 km resolution Soil Moisture and Ocean Salinity (SMOS) 12 observations

Boyer, Edmond

133

Understanding tree growth in response to moisture variability: Linking 32 years of satellite based soil moisture observations with tree rings  

NASA Astrophysics Data System (ADS)

Climate change induced drought variability impacts global forest ecosystems and forest carbon cycle dynamics. Physiological drought stress might even become an issue in regions generally not considered water-limited. The water balance at the soil surface is essential for forest growth. Soil moisture is a key driver linking precipitation and tree development. Tree ring based analyses are a potential approach to study the driving role of hydrological parameters for tree growth. However, at present two major research gaps are apparent: i) soil moisture records are hardly considered and ii) only a few studies are linking tree ring chronologies and satellite observations. Here we used tree ring chronologies obtained from the International Tree ring Data Bank (ITRDB) and remotely sensed soil moisture observations (ECV_SM) to analyze the moisture-tree growth relationship. The ECV_SM dataset, which is being distributed through ESA's Climate Change Initiative for soil moisture covers the period 1979 to 2010 at a spatial resolution of 0.25°. First analyses were performed for Mongolia, a country characterized by a continental arid climate. We extracted 13 tree ring chronologies suitable for our analysis from the ITRDB. Using monthly satellite based soil moisture observations we confirmed previous studies on the seasonality of soil moisture in Mongolia. Further, we investigated the relationship between tree growth (as reflected by tree ring width index) and remotely sensed soil moisture records by applying correlation analysis. In terms of correlation coefficient a strong response of tree growth to soil moisture conditions of current April to August was observed, confirming a strong linkage between tree growth and soil water storage. The highest correlation was found for current April (R=0.44), indicating that sufficient water supply is vital for trees at the beginning of the growing season. To verify these results, we related the chronologies to reanalysis precipitation and temperature datasets. Precipitation was important during both the current and previous growth season. Temperature showed the strongest correlation for previous (R=0.12) and current October (R=0.21). Hence, our results demonstrated that water supply is most likely limiting tree growth during the growing season, while temperature is determining its length. We are confident that long-term satellite based soil moisture observations can bridge spatial and temporal limitations that are inherent to in situ measurements, which are traditionally used for tree ring research. Our preliminary results are a foundation for further studies linking remotely sensed datasets and tree ring chronologies, an approach that has not been widely investigated among the scientific community.

Albrecht, Franziska; Dorigo, Wouter; Gruber, Alexander; Wagner, Wolfgang; Kainz, Wolfgang

2014-05-01

134

Soil Moisture Experiments 2005 (SMEX05): Passive Microwave Polarimetric Signature Of Soil Moisture and Vegetation  

Technology Transfer Automated Retrieval System (TEKTRAN)

Microwave remote sensing provides a direct measurement of soil moisture; however, there have been many challenges in algorithm science and technology that we have faced on the path to providing global measurements. Field experiments, especially those involving both ground and aircraft measurements, ...

135

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

NASA Technical Reports Server (NTRS)

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

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

2010-01-01

136

Evaluation and Application of Remotely Sensed Soil Moisture Products  

NASA Technical Reports Server (NTRS)

Whereas in-situ measurements of soil moisture are very accurate, achieving accurate regional soil moisture estimates derived solely from point measurements is difficult because of the dependence upon the density of the gauge network and the proper upkeep of these instruments, which can be costly. Microwave remote sensing is the only technology capable of providing timely direct measurements of regional soil moisture in areas that are lacking in-situ networks. Soil moisture remote sensing technology is well established has been successfully applied in many fashions to Earth Science applications. Since the microwave emission from the soil surface has such a high dependency upon the moisture content within the soil, we can take advantage of this relationship and combined with physically-based models of the land surface, derive accurate regional estimates of the soil column water content from the microwave brightness temperature observed from satellite-based remote sensing instruments. However, there still remain many questions regarding the most efficient methodology for evaluating and applying satellite-based soil moisture estimates. As discussed below, we to use satellite-based estimates of soil moisture dynamics to improve the predictive capability of an optimized hydrologic model giving more accurate root-zone soil moisture estimates.

Bolten, J.; Crow, W.; Zhan, X.; Jackson, T.; Reynolds, C.; Rodell, Matt

2010-01-01

137

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

NASA Astrophysics Data System (ADS)

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.

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

2012-04-01

138

BOREAS HYD-1 Volumetric Soil Moisture Data  

NASA Technical Reports Server (NTRS)

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

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

2000-01-01

139

Passive microwaves for soil moisture monitoring  

NASA Astrophysics Data System (ADS)

Since SMMR launched in 1978) to SMOS (launched in 2009) several missions have attempted describing the soil moisture, an important component of the water cycle. This could be a unique data set to see climatic trends, if coupled with other means as all the sensors (namely SMMR, SSM/I, ERS SCAT, Envisat ASCAT, AMSR, and now SMOS) have different times of over pass, different frequencies and possibluy even different measurement approaches. The rationale here is to inter-calibrate all the sensors available and try to operate a seamless transition correcting all the artifacts. The paper presents our two prong approach. On one hand we intercalibrate using reference targets the SMMR - SSM/I - AMSR series, deriving an empirical adjustment law for time of over pass and slight frequency differences, while, on the other hand we inter-compare over well monitored sites the behaviour of all available sensors and possibly algorithms. Finally, in the framework of the preparation of the SMOS mission we analyse over a reference site different ways to spatialise point information of a smos like pixel. During the oral presentation we will give the results gained through this approach and the problems encountered as well as potential ways to solve them. The results are intercompared with other similar approaches and long term soil moisture evolution shown on different areas.

Kerr, Yann; Leroux, Delphine; Juglea, Silvia; Gruhier, Claire; Mialon, Arnaud; Cabot, François

2010-05-01

140

Examining the relationship between soil moisture and summer extreme temperatures in East China  

NASA Astrophysics Data System (ADS)

Soil moisture conditions affect energy partitioning between sensible and latent heat fluxes, resulting in a change in surface temperatures. In this study, relationship between antecedent soil moisture conditions (as indicated by the 6-month Standardized Precipitation Index (SPI)) and several temperature indices are statistically quantified using the quantile regression analysis across East China to investigate the influence of soil moisture on summer surface temperatures. These temperature indices include percentage of hot-degree days (%HD), hot wave duration (HWD), daily temperature range (DTR), and daily minimum temperature (Tmin). Our results demonstrate that soil moisture had a significant impact on %HD and HWD at higher quantiles in all regions except East, suggesting that drier soil moisture conditions tend to intensity summer hot extremes. It was also found that hot extremes (%HD and HWD at higher quantiles) had increased substantially from 1958 to 2010. Soil moisture also significantly affected the DTR in all regions, but tended to have more impacts on the DTR in soil moisture-limited regimes than in energy-limited regimes. This study provides observational evidence of soil moisture influences on hot extremes in East China.

Meng, Lei

2014-05-01

141

A Multi-Scale Soil Moisture and Freeze-Thaw Monitoring Network on the Third Pole  

NASA Astrophysics Data System (ADS)

Multi-sphere interactions over the Tibetan Plateau directly impact its surrounding climate and environment at a variety of spatial/temporal scales. Remote sensing and modeling are expected to provide hydro-meteorological data needed for these process studies, but in situ observations are required to support their calibration and validation. For this purpose, we established a dense monitoring network on central Tibetan Plateau to measure two state variables (soil moisture and temperature) at three spatial scales (1.0, 0.3, 0.1 degree) and four soil depths (0~5cm, 10cm, 20cm, and 40cm). The experimental area is characterized by low biomass, large soil moisture dynamic range and typical freeze-thaw cycle. The network consists of 56 stations with their elevation varying over 4470 ~ 4950 m. Soil texture and soil organic matters are measured at each station, as auxiliary parameters of this network. In order to guarantee continuous and high-quality data, tremendous efforts have been made to protect the data logger from soil water intrusion, to calibrate soil moisture sensors, and to upscale the point measurements. As the highest soil moisture network in the world, our network meets the requirement for evaluating a variety of soil moisture products and for soil moisture scaling. It also directly contributes to the "water-ice-air-ecosystem-human" interaction theme of the "Third Pole Environment" Program. The data will be publicized via the International Soil Moisture Network. Publication: Zhao, L., K. Yang, J. Qin, Y-Y Chen, W-J Tang, C. Montzka, H. Wu, C-G Lin, M-L Han, and H. Vereecken., 2012: Spatiotemporal analysis of soil moisture observations within a Tibetan mesoscale area and its implication to regional soil moisture measurements, Journal of Hydrology DOI: 10.1016/j.jhydrol.2012.12.033.

Yang, Kun; Qin, Jun; Zhao, Long; Chen, Yingying; Han, Menglei

2013-04-01

142

Remote sensing as a tool in assessing soil moisture  

NASA Technical Reports Server (NTRS)

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

Carlson, C. W.

1978-01-01

143

Soil potassium mobility and uptake by corn under differential soil moisture regimes  

Microsoft Academic Search

This study examined the effects of soil moisture on soil K mobility, dynamics of soil K, soil K fixation, plant growth and\\u000a K uptake. A pot experiment, with and without corn (Zea maysL.), was conducted over a 16-d duration using a Yolo silt loam treated with two soil moisture regimes, i.e. constant moisture\\u000a vs. wetting–drying (W–D) cycles. Soil K dynamics

Qiupeng Zeng; Patrick H. Brown

2000-01-01

144

Phosphorus depletion in the rhizosphere as influenced by soil moisture  

Microsoft Academic Search

To study the influence of soil moisture on phosphorus (P) depletion in the rhizosphere, maize (Zea mays cv. Trak) was pre-grown in vermiculite filled-PVC tubes for 9 days and then the plants with the tubes were transplanted into soil columns maintained at two soil moisture levels (?) of 0.14 and 0.20 cm3 cm?3 for 10 days. The soil columns were

Tara Singh Gahoonia; Sherow Raza; Niels Erik Nielsen

1994-01-01

145

Multi-scale assimilation of surface soil moisture data for robust root zone moisture predictions  

NASA Astrophysics Data System (ADS)

In the presence of uncertain initial conditions and soil hydraulic properties land surface model performance can be significantly improved by the assimilation of periodic observations of certain state variables, such as the near surface soil moisture as observed from a remote platform. Recently, Montaldo et al. [Water Resour Res 37 (2001) 2889] derived a framework that uses biases between observed and modeled time rates of change of surface soil moisture to quantify biases between modeled and actual root-zone-average soil moisture contents. For very large errors in the saturated conductivity the soil moisture assimilation procedure is continuously working against the drainage errors, resulting in a persistent bias in its predictions. In this paper, we adopt this persistent (directional) bias in soil moisture as evidence of an error in the saturated conductivity. From manipulations of soil water balance equations we derived an expression that quantitatively relates the persistent bias in soil moisture to the estimated error in the saturated hydraulic conductivity. We combined this result with the approach of Montaldo et al. [Water Resour Res 37 (2001) 2889] to form a multi-scale assimilation approach. The multi-scale assimilation system is shown to provide marked improvements in the prediction of root zone soil moisture for a case study using data taken from an experimental catchment near Cork, Ireland. In effect, the root zone moisture is updated to provide a temporal trajectory of the near surface moisture that follows the trajectory of the observed surface moisture, and the hydraulic conductivity is adjusted on the basis of the time averaged corrections applied to the root zone water content. It is anticipated that this approach would be useful in operational forecasting models over large domains, where system parameters would be uncertain and occasional distributed observations would be limited to the near surface zone.

Montaldo, Nicola; Albertson, John D.

146

Soil Moisture and Drought Variability in the Upper Colorado River Basin  

NASA Astrophysics Data System (ADS)

This research investigates the interannual variability of soil moisture as related to large-scale climate variability. In addition, a study of the spatial and temporal soil moisture in the Upper Colorado River Basin is presented. A three layer hydrological model VIC-3L (Variable Infiltration Capacity Model C 3 layers) was used in the Upper Colorado River Basin over a 50-year period. Model calibration was conducted between the VIC-3L modeled streamflow and observed streamflow from five stations. Model verification was analyzed by comparing calculated soil moisture from the VIC-3L model with that from the Climate Prediction Center (CPC). Using wavelet analysis, deep soil moisture was compared to the Palmer Drought Severity Index (PDSI), precipitation, and streamflow to determine whether deep soil moisture is an indicator of climate extremes. Wavelet and coherency analysis for the Upper Colorado River Basin indicated a strong relationship between the PDSI, climate variability and the deep soil moisture. Lastly, the spatial and temporal soil moisture were analyzed by GIS map analysis, linear correlation, and t-test methods.

Tang, C.; Piechota, T.

2006-12-01

147

Variability in Corn Response to Nitrogen – Influence of Soil Moisture  

Technology Transfer Automated Retrieval System (TEKTRAN)

Corn yield response to N fertilizer applications has been observed to co-vary with soil moisture as related to topographic position. The objective of this study was to evaluate the variability in corn response to N under relatively wet and dry soil moisture regimes as determined by topography. A fie...

148

Timescales of Soil Moisture Anomalies: Results from Two GCMs  

NASA Technical Reports Server (NTRS)

Soil moisture anomalies dissipate over timescales that may span weeks to months. Characterizing the geographical and seasonal variations in these timescales can have important practical benefit; significant soil moisture "memory" allows long-lead forecasts of soil moisture, which have been found in recent studies to be essential for useful Ion--lead forecasts of precipitation in many regions. In this talk, we will present and compare the soil moisture timescales derived in two separate general circulation model (GCM) studies. Both studies employ multiple ensembles of short-term climate simulations. Timescales at a given point are effectively estimated by determining how quickly the soil moisture distribution generated in one ensemble of simulations (characterized by a unique set of initial soil moisture conditions) approaches that produced by another ensemble (characterized by a different set of initial soil moisture conditions). The talk will include a discussion of why the timescales produced by the two GCMs differ in some regions, and it will also describe the impact of soil moisture memory on simulated precipitation.

Koster, Randal D.; Milly, P. C. D.; Schlosser, C. Adam; Suarez, Max J.

1999-01-01

149

VALIDATION OF SATELLITE-BASED SOIL MOISTURE ALGORITHMS  

Technology Transfer Automated Retrieval System (TEKTRAN)

Validation is an important but particularly challenging task for passive microwave remote sensing of soil moisture from Earth orbit. The key issue is spatial scale; conventional measurements of soil moisture are made at a point whereas satellite sensors provide an integrated area/volume value for a ...

150

Soil Moisture Algorithm Validation with Ground Based Networks  

Technology Transfer Automated Retrieval System (TEKTRAN)

Validation satellite-based soil moisture algorithms and products is particularly challenging due to the disparity of scales of the two observation methods, conventional measurements of soil moisture are made at a point whereas satellite sensors provide an integrated area/volume value over a large ar...

151

Estimating soil moisture based on image processing technologies  

Microsoft Academic Search

Soil moisture is a critical factor to crop growth. Due to the facts of drought and less rain in northern China, it is necessary to introduce water controlled irrigating. Therefore, estimating soil moisture distribution rapidly and accurately is very important for decision making of water saving irrigating. This study took a farmland in Beijing as the experiment field. The aerial

Lihua Zheng; Minzan Li; Jianying Sun; Xijie Zhang; Peng Zhao

2005-01-01

152

SMOS Soil Moisture Validation with Dense and Sparse Networks  

Technology Transfer Automated Retrieval System (TEKTRAN)

Validation is an important but particularly challenging task for passive microwave remote sensing of soil moisture from Earth orbit. The key issue is spatial scale; conventional measurements of soil moisture are made at a point whereas satellite sensors provide an integrated area/volume value for a ...

153

The Soil Moisture Active/Passive Mission (SMAP)  

Technology Transfer Automated Retrieval System (TEKTRAN)

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

154

Soil moisture levels and mycorrhizal infection in black walnut seedlings  

Microsoft Academic Search

The influence of soil moisture on endomycorrhizal infection in black walnut was studied using four groups of potted seedlings watered at different time intervals. Seedlings watered every day or every second day had much longer lateral roots but fewer infected root segments than seedlings watered every third or fourth day. These results suggest that controlling the soil moisture level may

Filex Ponder Jr

1983-01-01

155

A spatial scaling relationship for soil moisture in a semiarid landscape, using spatial scaling relationships for pedology  

NASA Astrophysics Data System (ADS)

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.

Willgoose, G. R.; Chen, M.; Cohen, S.; Saco, P. M.; Hancock, G. R.

2013-12-01

156

Analysis of the hydrological response of a distributed physically-based model using post-assimilation (EnKF) diagnostics of streamflow and in situ soil moisture observations  

NASA Astrophysics Data System (ADS)

Data assimilation techniques not only enhance model simulations and forecast, they also provide the opportunity to obtain a diagnostic of both the model and observations used in the assimilation process. In this research, an ensemble Kalman filter was used to assimilate streamflow observations at a basin outlet and at interior locations, as well as soil moisture at two different depths (15 and 45 cm). The simulation model is the distributed physically-based hydrological model CATHY (CATchment HYdrology) and the study site is the Des Anglais watershed, a 690 km2 river basin located in southern Quebec, Canada. Use of Latin hypercube sampling instead of a conventional Monte Carlo method to generate the ensemble reduced the size of the ensemble, and therefore the calculation time. Different post-assimilation diagnostics, based on innovations (observation minus background), analysis residuals (observation minus analysis), and analysis increments (analysis minus background), were used to evaluate assimilation optimality. An important issue in data assimilation is the estimation of error covariance matrices. These diagnostics were also used in a calibration exercise to determine the standard deviation of model parameters, forcing data, and observations that led to optimal assimilations. The analysis of innovations showed a lag between the model forecast and the observation during rainfall events. Assimilation of streamflow observations corrected this discrepancy. Assimilation of outlet streamflow observations improved the Nash-Sutcliffe efficiencies (NSE) between the model forecast (one day) and the observation at both outlet and interior point locations, owing to the structure of the state vector used. However, assimilation of streamflow observations systematically increased the simulated soil moisture values.

Trudel, Mélanie; Leconte, Robert; Paniconi, Claudio

2014-06-01

157

The Use of Multispectral Imagery to Detect Variations in Soil Moisture Associated Shallow Soil Slumps  

Microsoft Academic Search

Spatial variations in soil moisture have previously been linked to the process of soil aging and can contribute to mass wasting in slopes rich in clay. We use remote sensing imagery to assess variation in soil moisture. Our investigation includes compacted clay soils of the levees along the Mississippi River maintained by the Mississippi Levee Board. Shallow soil slumps are

J. S. Kuszmaul; J. A. Neuner; A. A. Hossain; G. L. Easson

2004-01-01

158

Estimating soil moisture distribution using polarimetric airborne SAR  

NASA Astrophysics Data System (ADS)

The goal of this study is to develop an algorithm for estimating the surface soil moisture and surface roughness using polarimetric Synthetic Aperture Radar (SAR) data. In this study, an algorithm was applied to polarimetric airborne SAR data to estimate distributions of surface soil moisture and roughness. To validate the estimated soil moisture, we simultaneously conducted an experiment in October 1999 in Tsukuba Science City, Ibaragi Prefecture of Japan. Surface soil moisture was obtained by the Time- Domain Reflectometry (TDR) method, and the horizontal profiles of the land surface height were measured by a comb- style instrument for calculating the surface roughness parameters in test sites. Because the problem is site- specific and depends upon the measurement accuracy of both the ground truth data, the SAR system including speckle noise, and the effects of vegetation and artificial constructions, such as buildings, houses, roads, and roadside trees, the comparison results did not agree well with measured and inferred soil moisture.

Tadono, Takeo; Qong, Muhtar; Wakabayashi, Hiroyuki; Shimada, Masanobu; Shi, Jiancheng

2000-12-01

159

Dry-end surface soil moisture variability during NAFE'06  

NASA Astrophysics Data System (ADS)

Characterization of the space-time variability of soil moisture is important for land surface and climate studies. Here we develop an analytical model to investigate how, at the dry-end of the soil moisture range, the main characteristics of the soil moisture field (spatial mean and variability, steady state distribution) depend on the intermittent character of low intensity rain storms. Our model is in good agreement with data from the recent National Airborne Field Experiment (NAFE'06) held in the semiarid Australian Murrumbidgee catchment. We find a positive linear relationship between mean soil moisture and its associated variability, and a strong dependency of the temporal soil moisture distribution to the amount and structure of precipitation.

Teuling, A. J.; Uijlenhoet, R.; Hurkmans, R.; Merlin, O.; Panciera, R.; Walker, J. P.; Troch, P. A.

2007-09-01

160

Soil moisture determination study. [Guymon, Oklahoma  

NASA Technical Reports Server (NTRS)

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

Blanchard, B. J.

1979-01-01

161

Assimilation of soil moisture using Ensemble Kalman Filter  

NASA Astrophysics Data System (ADS)

In this work, a soil moisture data assimilation scheme was developed based on the Community Land Model Version 3.0 (hereafter CLM) and Ensemble Kalman Filter. Soil moisture in the 1st soil layer was assimilated into CLM to evaluate the improvements of land surface process simulation. The results indicated that the assimilation system could improve the model accuracy effectively. It can transfer the variations of shallow soil layer's moisture to the deep soil and make great improvements to the soil water and heat status in an overall level. The system could improve the soil moisture accuracy from the 1st soil layer to the 6th soil layer by 50%. According to this experiment, the transfer depth of soil moisture was from 40 cm to 60 cm. After assimilation, the correlation coefficient of latent heat flux observation and simulation increased from 0.68 to 0.91 and the RMSE dropped from 86.7 W/m2 to 45.7 W/m2. For the sensible heat flux, the correlation coefficient increased from 0.69 to 0.80 and the RMSE reduced from 105.1 W/m2 to 71.3 W/m2. It was feasible and significant to assimilate soil moisture remote sensing products.

Du, Juan; Liu, Chaoshun; Gao, Wei

2014-10-01

162

Soil moisture retrieval from space: the Soil Moisture and Ocean Salinity (SMOS) mission  

Microsoft Academic Search

Microwave radiometry at low frequencies (L-band: 1.4 GHz, 21 cm) is an established technique for estimating surface soil moisture and sea surface salinity with a suitable sensitivity. However, from space, large antennas (several meters) are required to achieve an adequate spatial resolution at L-band. So as to reduce the problem of putting into orbit a large filled antenna, the possibility

Yann H. Kerr; Philippe Waldteufel; Jean-Pierre Wigneron; Jean-Michel Martinuzzi; Michael Berger

2001-01-01

163

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

Technology Transfer Automated Retrieval System (TEKTRAN)

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

164

SOIL MOISTURE CHARACTERISTICS IN UPPER PART OF HINDON RIVER CATCHMENT  

E-print Network

1 SOIL MOISTURE CHARACTERISTICS IN UPPER PART OF HINDON RIVER CATCHMENT C. P. Kumar* Vijay Kumar** Vivekanand Singh*** ABSTRACT Knowledge of the physics of soil water movement is crucial to the solution for estimating the soil hydraulic properties are required for prediction of soil water flow. This paper presents

Kumar, C.P.

165

The GLOBE Soil Moisture Campaign's Light Bulb Oven  

NASA Astrophysics Data System (ADS)

The GLOBE Soil Moisture Campaign (SMC) (www.hwr.arizona.edu/globe/sci/SM/SMC) has developed a light bulb oven to provide a low budget, low-technology method for drying soil samples. Three different soils were used to compare the ability of the light bulb oven to dry soils against a standard laboratory convection oven. The soils were: 1) a very fine sandy loam (the "Gila" soil); 2) a silty clay (the "Pima" soil); and 3) a sandy soil (the "Sonoran" soil). A large batch of each soil was wetted uniformly in the laboratory. Twelve samples of each soil were placed in the light bulb oven and twelve samples were placed in the standard oven. The average gravimetric soil moisture of the Gila soil was 0.214 g/cm3 for both ovens; the average Pima soil moisture was 0.332 g/cm3 and 0.331 g/cm3 for the traditional and light bulb ovens, respectively; and the Sonoran soil moisture was 0.077 g/cm3 for both ovens. These results demonstrate that the low technology light-bulb oven was able to dry the soil samples as well as a standard laboratory oven, offering the ability to make gravimetric water content measurements when a relatively expensive drying oven is not available.

Whitaker, M. P.; Tietema, D.; Ferre, T. P.; Nijssen, B.; Washburne, J.

2003-12-01

166

Evaluating the Utility of Remotely-Sensed Soil Moisture Retrievals for Operational Agricultural Drought Monitoring  

NASA Technical Reports Server (NTRS)

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.

Bolten, John D.; Crow, Wade T.; Zhan, Xiwu; Jackson, Thomas J.; Reynolds,Curt

2010-01-01

167

Effects of soil moisture and temperature on overwintering survival of Curculio larvae (Coleoptera : Curculionidae)  

USGS Publications Warehouse

Few studies to date have investigated factors, other than mast crop size, that influence the dynamics of Curculio populations.W e examined the effects of varying levels of soil moisture (0.35, 0.4 and 0.5 g water/g soil) and temperature (8, 14 and 20 C) on over wintering survival of Curculio larvae collected from Quercus michauxii acorns. Survival of larvae, analyzed using log-linear analysis, was adversely affected by soil moisture but not by soil temperature. Larvae that overwinter in drier soil may have higher probabilities of successfully metamorphosing.

Ricca, M.A.; Weckerly, F.W.; Semlitsch, R.D.

1996-01-01

168

Is Regional Root Reinforcement Controlled by Soil Moisture Variability?  

NASA Astrophysics Data System (ADS)

Climate change will alter the amount, type (i.e., snow vs. rain), and timing of precipitation that controls many hazardous Earth surface processes, including debris flows. Most GCMs agree that as climate warms the frequency of extreme precipitation will increase across the globe. Debris flow events triggered by heavy precipitation will likely also increase. Precipitation also affects the resistance to debris flow initiation by controlling belowground plant hydraulic architecture (e.g. root frequency, diameter distribution, tensile strength). Quantifying the links between precipitation, below ground properties, and the processes that initiate debris flows are therefore critical to understanding future hazard. To explore these links, we conducted a field experiment in the Coweeta Hydrologic Laboratory by excavating 12 soil pits (~1 m3), from two topographies (noses, hollows), and two tree species (Liriodendron tulipifera and Betula lenta). For each species and topography, we collected all biomass from five soil depths and measured soil moisture at 30, 60, and 90cm depth. For each depth we also measured root tensile strength, root cellulose content. Where we collected soil moisture data, we also measured root and soil hydraulic conductivity. Our data show a link between soil moisture content and root biomass distribution; root biomass is more evenly distributed through the soil column in hollows compared to noses. This relationship is consistent with the hypothesis that more consistent soil moisture in hollows allows plant roots to access resources from deeper within the soil column. This physiologic control has a significant effect on root cohesion, with trees on noses (or lower average soil moisture) providing greater root cohesion close to the surface, but considerably less cohesion at depth. Root tensile strength correlated with local daily soil moisture rather than the long term differences represented by noses and hollows. Daily soil moisture affected the amount of "bound water" (water present in the cell wall), which in turn affected the strength of the cellulose fibrils that provide tensile strength. This phenomenon, which is the reason any wet wood is weaker than dry wood, results in a 50% difference in root tensile strength within the range of soil moisture measured in the field. We used a one-dimensional finite difference model to explore the effects of soil moisture on root cohesion. Our model shows that changes in the distribution of root biomass represent the primary control on root cohesion (representing up to 50% of intra-specific variability in root cohesion). Local changes in soil moisture result in ~20% change in the overall root cohesion. Our work suggest a feed-forward process in precipitation (and thus soil moisture), root strength changes, and debris flow hazard.

Hales, T.; Ford, C. R.

2011-12-01

169

A Comparison of Methods for a Priori Bias Correction in Soil Moisture Data Assimilation  

NASA Technical Reports Server (NTRS)

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.

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

2011-01-01

170

Estimation of Soil Moisture Profile using a Simple Hydrology Model and Passive Microwave Remote Sensing  

NASA Technical Reports Server (NTRS)

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.

Soman, Vishwas V.; Crosson, William L.; Laymon, Charles; Tsegaye, Teferi

1998-01-01

171

Soil moisture tendencies into the next century for the conterminous United States  

USGS Publications Warehouse

A monthly snow-pack and soil- moisture accounting model is formulated for application to each of the climate divisions of the conterminous United States for use in climate impacts-assessment studies. Statistical downscaling and bias-adjustment components complement the model for the assimilation of large-scale global climate model data. Simulations of the formulated model driven by precipitation and temperature for the period 1931-1998 produce streamflows that are broadly consistent with observed data from several drainage basins in the US. Simulated historical soil moisture fields reproduce several features of the available observed soil moisture in the Midwest. The simulations produce large-scale coherent seasonal patterns of soil moisture field- moments over the conterminous US, with high soil moisture means over divisions in the Ohio Valley, the northeastern US and the Pacific Northwest, and with pronounced low means in most of the western US climate divisions. Characteristically low field-standard- deviations are produced for the Ohio Valley and northeastern US, and the Pacific Northwest in winter, and the southwestern US in summer. Differences in extreme standardized anomalies of soil moisture over the historical record range possess high values (2.5 - 3) in the central US where the available water capacity of the soils is high. An application of the model to exemplify the methodology for determining projected US monthly soil moisture fields under control and greenhouse gas forcing is also documented. Climate simulations of the coupled global climate model from the Canadian Centre for Climate Modeling and Analysis were used for these sensitivity examples. The climatology of the control-run soil moisture fields reproduces several characteristic features of the historical soil moisture climatology. Simulations with forcing by a 1% greenhouse-gas- increase scenario show that for at least the first few decades of the 21 st Century somewhat drier-than-present soil conditions are projected, with highest drying trends found in the southeastern US. The soil moisture deficits in most areas are of the same order of magnitude as the soil moisture field-standard- deviations aris ing from historical natural variability. In a companion paper (Brumbelow and A. Georgakakos, 2000), the monthly soil moisture fields for the historical, control and greenhouse-gas-increase runs are used to initialize a site-specific daily crop yield model at the start of the growing season. Assessments of potential impacts of climate variability and trends on irrigation requirements and crop yield across the conterminous US are made.

Georgakakos, Konstantine P.; Smith, Diane E.

2000-01-01

172

Growth response to different constant soil moisture levels in maize ( Zea mays L.) during the vegetative phase  

Microsoft Academic Search

The effect of different constant soil moisture levels (90, 60, 30% and 90, 60, 40% respectively, of the maximum capillary\\u000a capacity) on the vegetative growth of maize was studied by the methods of growth analysis. The constant soil moisture in vegetation\\u000a pots was maintained by means of the injection method. The constantly decreased soil moisture was applied in one experiment

J. Václavík

1967-01-01

173

A Time Series Approach for Soil Moisture Estimation  

NASA Technical Reports Server (NTRS)

Soil moisture is a key parameter in understanding the global water cycle and in predicting natural hazards. Polarimetric radar measurements have been used for estimating soil moisture of bare surfaces. In order to estimate soil moisture accurately, the surface roughness effect must be compensated properly. In addition, these algorithms will not produce accurate results for vegetated surfaces. It is difficult to retrieve soil moisture of a vegetated surface since the radar backscattering cross section is sensitive to the vegetation structure and environmental conditions such as the ground slope. Therefore, it is necessary to develop a method to estimate the effect of the surface roughness and vegetation reliably. One way to remove the roughness effect and the vegetation contamination is to take advantage of the temporal variation of soil moisture. In order to understand the global hydrologic cycle, it is desirable to measure soil moisture with one- to two-days revisit. Using these frequent measurements, a time series approach can be implemented to improve the soil moisture retrieval accuracy.

Kim, Yunjin; vanZyl, Jakob

2006-01-01

174

Response of grassland ecosystems to prolonged soil moisture deficit  

NASA Astrophysics Data System (ADS)

Soil moisture is commonly used for predictions of plant response and productivity. Climate change is predicted to cause an increase in the frequency and duration of droughts over the next century, which will result in prolonged periods of below-normal soil moisture. This, in turn, is expected to impact regional plant production, erosion and air quality. In fact, the number of consecutive months of soil moisture content below the drought-period mean has recently been linked to regional tree and shrub mortality in the southwest United States. This study investigated the effects of extended periods of below average soil moisture on the response of grassland ANPP to precipitation. Grassland ecosystems were selected for this study because of their ecological sensitivity to precipitation patterns. It has been postulated that the quick ecological response of grasslands to droughts can provide insight to large scale functional responses of regions to predicted climate change. The study sites included 21 grassland biomes throughout arid-to-humid climates in the United States with continuous surface soil moisture records for 2-13 years during the drought period from 2000-2013. Annual net primary production (ANPP) was estimated from the 13-year record of NASA MODIS Enhanced Vegetation Index extracted for each site. Prolonged soil moisture deficit was defined as a period of at least 10 consecutive months during which soil moisture was below the drought-period mean. ANPP was monitored before, during and after prolonged soil moisture deficit to quantify shifts in the functional response of grasslands to precipitation, and in some cases, new species assemblages that included invasive species. Preliminary results indicated that when altered climatic conditions on grasslands led to an increase in the duration of soil water deficit, then the precipitation-to-ANPP relation became non-linear. Non-linearity was associated with extreme grassland dieback and changes in the historic species assemblage. The magnitude of change was related to the precipitation regime, where grasslands in hyper-arid and humid regimes were least likely to be affected by prolonged soil moisture deficit, and semiarid and mesic grasslands were most likely to be impacted, depending on the duration of the deficit. These results were applied to a large grassland region in Australia with soil moisture estimates from the European Space Agency (ESA) Soil Moisture Ocean Salinity (SMOS) sensor to demonstrate the continental-scale potential of this application with satellite measurements. These results are even more relevant for application with the higher-resolution NASA Soil Moisture Active Passive (SMAP) products to be available in 2015.

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

2014-05-01

175

Validation of Satellite Soil Moisture Retrievals using Precipitation Records in India  

NASA Astrophysics Data System (ADS)

Soil moisture plays crucial role in influencing the components of hydrologic cycle and thus used for large range of applications such as climate predictions, agriculture management and flood/drought modelling. The current work focuses on establishing a measure to check the performance of passive microwave satellite soil moisture data using rainfall information over India. The measure is developed based on the concepts of information theory and copulas. Two soil moisture products developed by, VUA-NASA (jointly by Vrije Universiteit Amsterdam and NASA) and university of Montana are tested with the proposed measure using IMD rainfall data at 0.25° latitude-longitude spatial resolution. The measure conveyed that soil moisture product by university of Montana has outperformed over its counterpart. Further analysis concluded that under moderate climate conditions, Montana product could be used for analysis whereas for study in extreme weather conditions it may be necessary to check the usefulness of VUA-NASA product.

Karthikeyan, L.; Nagesh Kumar, D.

2014-11-01

176

The Murrumbidgee soil moisture monitoring network data set  

NASA Astrophysics Data System (ADS)

This paper describes a soil moisture data set from the 82,000 km2 Murrumbidgee River Catchment in southern New South Wales, Australia. Data have been archived from the Murrumbidgee Soil Moisture Monitoring Network (MSMMN) since its inception in September 2001. The Murrumbidgee Catchment represents a range of conditions typical of much of temperate Australia, with climate ranging from semiarid to humid and land use including dry land and irrigated agriculture, remnant native vegetation, and urban areas. There are a total of 38 soil moisture-monitoring sites across the Murrumbidgee Catchment, with a concentration of sites in three subareas. The data set is composed of 0-5 (or 0-8), 0-30, 30-60, and 60-90 cm average soil moisture, soil temperature, precipitation, and other land surface model forcing at all sites, together with other ancillary data. These data are available on the World Wide Web at http://www.oznet.org.au.

Smith, A. B.; Walker, J. P.; Western, A. W.; Young, R. I.; Ellett, K. M.; Pipunic, R. C.; Grayson, R. B.; Siriwardena, L.; Chiew, F. H. S.; Richter, H.

2012-07-01

177

Long-term soil moisture variability from a new P-E water budget method  

NASA Astrophysics Data System (ADS)

Basin-scale soil moisture is traditionally estimated using either land-surface model forced by observed meteorological variables or atmospheric moisture convergence from atmospheric analysis and observed runoff. Interannual variability from such methods suffer from major uncertainties due to the sensitivity to small imperfections in the land-surface model or the atmospheric analysis. Here we introduce a novel P-E method in estimating basin-scale soil moisture, or more precisely apparent land water storage (AWS). The key input variables are observed precipitation and runoff, and reconstructed evaporation. We show the results for the tropics using the example of the Amazon basin. The seasonal cycle of diagnosed soil moisture over the Amazon is about 200mm, compares favorably with satellite estimate from the GRACE mission, thus lending confidence both in this method and the usefulness of space gravity based large-scale soil moisture estimate. This is about twice as large as estimates from several traditional methods, suggesting that current models tend to under estimate the soil moisture variability. One of the advantage of the P-E method is to retrive long-term variability of the basin-scale soil moisture (including interannual and decadal time scales), which can provide valuable information to understand climate variability and to predict future climate condition. However, validation on reconstructed evaporation is very difficult due to lack of observation. The interannual variability in AWS in the Amazon basin is about 150mm, also consistent with GRACE data, but much larger than model results. We also apply this P-E method to the midlatitude Mississippi basin and discuss the impact of major 20th century droughts such as the dust bowl period on the long-term soil moisture variability. The results suggest the existence of soil moisture memories on decadal time scales, significantly longer than typically assumed seasonal timescales.

Zeng, N.; Yoon, J.; Mariotti, A.; Swenson, S. C.

2006-05-01

178

Remote monitoring of soil moisture using airborne microwave radiometers  

NASA Technical Reports Server (NTRS)

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

Kroll, C. L.

1973-01-01

179

A statistical retrieval algorithm for root zone soil moisture  

NASA Astrophysics Data System (ADS)

An algorithm for the estimation of root zone soil moisture is presented. Global fields of the soil moisture within the uppermost metre of soil are derived with a temporal resolution of 10 days. For calibration, long-term soil moisture observations from the former Soviet Union are used. The variance of the measurements is largely dominated by the spatial variability of the long-term mean soil moisture, while the temporal variability gives comparatively small contribution. Consequently, the algorithm is organised into two steps. The first step concentrates on the retrieval of the spatial variance of the long-term means, which comprises more than 85% of the total soil moisture variability. A major part of the spatial variance can be explained by four easily available fields: the climatological precipitation, land use, soil texture, and terrain slope. The second step of the algorithm is dedicated to the local temporal variability. This part of variability is recovered by using passive microwave data from scanning multichannel microwave radiometre (SMMR) supported by monthly averaged fields of air temperature and precipitation. The 6-GHz channel of SMMR is shown to be severely disturbed by radio frequency interference, so that information from the 10-GHz channel is used instead. The algorithm provides reasonable soil moisture fields which is confirmed by a comparison with independent measurements from Illinois.

Lindau, Ralf; Simmer, Clemens

2014-11-01

180

Improved understanding of hillslope-scale hydrological processes using high-resolution soil moisture measurements  

NASA Astrophysics Data System (ADS)

Soil moisture is a key variable that controls e.g. matter and energy fluxes, slope stability, occurence of flood events and soil-vegetation-atmosphere exchange processes. Deriving detailed process understanding at the hillslope scale is not trivial, because of the non-linearity of hillslope response to rainfall due to local soil moisture dynamics. Characterizing this variability is one of the major challenges in hillslope hydrology. Long-term monitoring of surface and subsurfce soil moisture at various depths can provide a comprehensive picture of the spatial and temporal pattern of soil moisture dynamics, and facilitate understanding the controlling factors of underlying hydrological processes. In the Schäfertal catchment (located in the Harz Mountains, in Central Germany) a 2.5 ha hillslope area was permanently instrumented with a wireless soil moisture and soil temperature monitoring network. Ground-based electromagnetic induction (EMI) measurements and topographic data were included into a geostatistical sampling strategy in order to optimize the placement of the network nodes. In total, 240 sensors were distributed to create 40 pairs of instrumented soil profiles, providing hourly measurements of soil water content and soil temperature at 5, 25 and 50 cm depth. The soil spatial variability was mapped and the soil texture was determined for each node location and each soil horizon. For the selected monitoring period of 14 months, the soil moisture pattern and its variability through time were analyzed. Seasonal and event-based analysis shows the varying relevance of topography and soil properties in determining several near-surface processes such as preferential flow, subsurface lateral flow and dynamics of the groundwater table.

Martini, Edoardo; Kögler, Simon; Wollschläger, Ute; Werban, Ulrike; Behrens, Thorsten; Schmidt, Karsten; Dietrich, Peter; Zacharias, Steffen

2014-05-01

181

The Soil Moisture Active and Passive (SMAP) Mission  

NASA Technical Reports Server (NTRS)

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

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; Kimball, John; Piepmeier, Jeffrey R.; Koster, Randal D.; McDonald, Kyle C.; Moghaddam, Mahta; Moran, Susan; Reichle, Rolf; Shi, J. C.; Spencer, Michael W.; Thurman, Samuel W.; Tsang, Leung; VanZyl, Jakob

2009-01-01

182

SOIL MOISTURE RETENTION CHARACTERISTICS AND HYDRAULIC CONDUCTIVITY FOR DIFFERENT AREAS IN INDIA IN SELECTED STATES  

E-print Network

SOIL MOISTURE RETENTION CHARACTERISTICS AND HYDRAULIC CONDUCTIVITY FOR DIFFERENT AREAS IN INDIA systems require knowledge of the relationships between soil moisture content (), soil water pressure (h) and unsaturated hydraulic conductivity (K). This study involved field and laboratory determination of soil

Kumar, C.P.

183

The GLOBE Soil Moisture Campaign and SMEX03: Making it Real for Teachers  

NASA Astrophysics Data System (ADS)

The GLOBE Soil Moisture Campaign (SMC) (http://www.hwr.arizona.edu/globe/sci/SM/SMC) is an effort to mobilize students worldwide to collect near-surface (i.e. 0-5 cm and 8-12 cm deep) gravimetric soil moisture data twice a year: once during World Space Week/U.S Earth Science Week (early October) and again during Earth Day Week (mid-April). As part of our teacher-training and recruitment strategy, the SMC actively seeks event-oriented scientific campaigns, with which to collaborate and make the science relevant and "real" for the teachers and, subsequently, their students. One specific success has been the SMC collaboration with the Soil Moisture Experiment 2003 (SMEX03) that took place in June-July in Georgia and Alabama. SMEX03 was a soil moisture data collection campaign whose objectives were to collect soil moisture in a large-scale field experiment that used ground, aircraft and spacecraft observations over multiple field sites during the summer of 2003. The GLOBE SMC participated in SMEX03 by collaborating with a GLOBE soils training workshop in Huntsville, AL that was scheduled for dates and locations that overlapped with SMEX03. Fifty teachers were trained in the SMC soil moisture protocol, and were asked to collect soil moisture samples at or near their homes in the communities surrounding Huntsville. Of the fifty teachers, 41 returned with soil samples that were ultimately submitted for use in the SMEX03 campaign. The training workshop's collaboration with SMEX03 proved a successful means of hands-on training with an immediate connection between schools and scientists. An analysis of the teacher-collected soil moisture data used in SMEX03 will be presented, along with a discussion of the specific successes of the SMC involvement.

Whitaker, M. P.; Washburne, J.; Ferre, T. P.; Nijssen, B.

2003-12-01

184

The Soil Moisture Active and Passive (SMAP) Mission  

Technology Transfer Automated Retrieval System (TEKTRAN)

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

185

Soil moisture active/passive (SMAP) mission concept  

Technology Transfer Automated Retrieval System (TEKTRAN)

Soil Moisture Active/Passive (SMAP) Mission is one of the first 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. ...

186

New insights in catchment processes via distributed soil moisture measurements and 3D hydrological modeling  

NASA Astrophysics Data System (ADS)

Hydrological analysis is often limited by the number of data available. Usually, discharge data and only little point information concerning soil moisture status are available. This might give a good representation of the temporal variability of runoff, but it does not provide insights into the spatial dynamics of soil moisture and water fluxes within the catchment. The small forested Wüstebach catchment (~27 ha) has been instrumented with a wireless sensor network consisting of 150 nodes and more than 1200 soil moisture sensors in the framework of the Transregio32 and the Helmholtz initiative TERENO (Terrestrial Environmental Observatories) [1]. This unique data set provides a consistent picture of the hydrological status of the catchment in a high spatial and temporal resolution. We present first results of a geostatistical analysis of the data and an application of the integrated surface/subsurface 3D finite element model HydroGeoSphere model to investigate the scale dependency of the temporal dynamics of soil moisture patterns. A variogram analysis showed that the sum of the sub-scale variability and the measurement error is close to time-invariant. Wet situations showed smaller spatial variability, which is attributed to saturated soil moisture, which poses an upper limit and is typically not strongly variable in headwater catchments with relatively homogeneous soil. The spatiotemporal variability in soil moisture at 50 cm depth was significantly lower than at 5 and 20 cm. This finding indicates that the considerable variability of the top soil is buffered deeper in the soil due to root water uptake, lateral and vertical water fluxes. Topographic features showed the strongest correlation with soil moisture during dry periods, indicating that the control of topography on the soil moisture pattern depends on the soil water status. The temporal patterns of runoff discharge were reproduced by the HydroGeoSphere model in a satisfying way. The observed soil moisture patterns were used to analyze the simulation quality. Generally, the model accuracy increased with decreasing spatial discretisation. The spatial discretisation of the model also had a larger effect on the water balance than the scaling of soil properties, which was attributed to the model equation describing transpiration dependency on water status and was not considered to be related to the scale dependency of hydrological processes. These findings demonstrate that the conceptual model (deciding on equations) is as important as the perceptual model (deciding on the processes). References: [1] Bogena, H.R., M. Herbst, J.A. Huisman, U. Rosenbaum, A. Weuthen, and H. Vereecken (2010): Potential of wireless sensor networks for measuring soil water content variability. Vadose Zone J., doi:10.2136/vzj2009.0173.

Bogena, H. R.; Sciuto, G.; Rosenbaum, U.; Herbst, M.; Huisman, J. A.; Vereecken, H.; Diekkrueger, B.

2010-12-01

187

Effects of climate change on soil moisture over China from 1960-2006  

USGS Publications Warehouse

Soil moisture is an important variable in the climate system and it has sensitive impact on the global climate. Obviously it is one of essential components in the climate change study. The Integrated Biosphere Simulator (IBIS) is used to evaluate the spatial and temporal patterns of soil moisture across China under the climate change conditions for the period 1960-2006. Results show that the model performed better in warm season than in cold season. Mean errors (ME) are within 10% for all the months and root mean squared errors (RMSE) are within 10% except winter season. The model captured the spatial variability higher than 50% in warm seasons. Trend analysis based on the Mann-Kendall method indicated that soil moisture in most area of China is decreased especially in the northern China. The areas with significant increasing trends in soil moisture mainly locate at northwestern China and small areas in southeastern China and eastern Tibet plateau. ?? 2009 IEEE.

Zhu, Q.; Jiang, H.; Liu, J.

2009-01-01

188

The NASA Soil Moisture Active Passive (SMAP) mission: Overview  

E-print Network

The Soil Moisture Active Passive (SMAP) mission is one of the first Earth observation satellites being developed by NASA in response to the National Research Council's Decadal Survey. Its mission design consists of L-band ...

O'Neill, Peggy

189

Mapping surface soil moisture with L-band radiometric measurements  

NASA Technical Reports Server (NTRS)

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

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

1989-01-01

190

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

NASA Technical Reports Server (NTRS)

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

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

2011-01-01

191

Modification of Soil Temperature and Moisture Budgets by Snow Processes  

NASA Astrophysics Data System (ADS)

Snow cover significantly influences the land surface energy and surface moisture budgets. Snow thermally insulates the soil column from large and rapid temperature fluctuations, and snow melting provides an important source for surface runoff and soil moisture. Therefore, it is important to accurately understand and predict the energy and moisture exchange between surface and subsurface associated with snow accumulation and ablation. The objective of this study is to understand the impact of land surface model soil layering treatment on the realistic simulation of soil temperature and soil moisture. We seek to understand how many soil layers are required to fully take into account soil thermodynamic properties and hydrological process while also honoring efficient calculation and inexpensive computation? This work attempts to address this question using field measurements from the Cold Land Processes Field Experiment (CLPX). In addition, to gain a better understanding of surface heat and surface moisture transfer process between land surface and deep soil involved in snow processes, numerical simulations were performed at several Meso-Cell Study Areas (MSAs) of CLPX using the Center for Ocean-Land-Atmosphere (COLA) Simplified Version of the Simple Biosphere Model (SSiB). Measurements of soil temperature and soil moisture were analyzed at several CLPX sites with different vegetation and soil features. The monthly mean vertical profile of soil temperature during October 2002 to July 2003 at North Park Illinois River exhibits a large near surface variation (<5 cm), reveals a significant transition zone from 5 cm to 25 cm, and becomes uniform beyond 25cm. This result shows us that three soil layers are reasonable in solving the vertical variation of soil temperature at these study sites. With 6 soil layers, SSiB also captures the vertical variation of soil temperature during entire winter season, featuring with six soil layers, but the bare soil temperature is underestimated and root-zone soil temperature is overestimated during snow melting; which leads to overestimated temperature variations down to 20 cm. This is caused by extra heat loss from upper soil level and insufficient heat transport from the deep soil. Further work will need to verify if soil temperature displays similar vertical thermal structure for different vegetation and soil types during snow season. This study provides insight to the surface and subsurface thermodynamic and hydrological processes involved in snow modeling which is important for accurate snow simulation.

Feng, X.; Houser, P.

2006-12-01

192

Sensitivity of seasonal weather prediction and extreme precipitation events to soil moisture initialization uncertainty using SMOS soil moisture products  

NASA Astrophysics Data System (ADS)

Sensitivity of seasonal weather prediction and extreme precipitation events to soil moisture initialization uncertainty using SMOS soil moisture products (1) S. Khodayar, (2) A. Coll, (2) E. Lopez-Baeza (1) Institute for Meteorology and Climate Research, Karlsruhe Institute of Technology (KIT), Karlsruhe Germany (2) University of Valencia. Earth Physics and Thermodynamics Department. Climatology from Satellites Group Soil moisture is an important variable in agriculture, hydrology, meteorology and related disciplines. Despite its importance, it is complicated to obtain an appropriate representation of this variable, mainly because of its high temporal and spatial variability. SVAT (Soil-Vegetation-Atmosphere-Transfer) models can be used to simulate the temporal behaviour and spatial distribution of soil moisture in a given area and/or state of the art products such as the soil moisture measurements from the SMOS (Soil Moisture and Ocean Salinity) space mission may be also convenient. The potential role of soil moisture initialization and associated uncertainty in numerical weather prediction is illustrated in this study through sensitivity numerical experiments using the SVAT SURFEX model and the non-hydrostatic COSMO model. The aim of this investigation is twofold, (a) to demonstrate the sensitivity of model simulations of convective precipitation to soil moisture initial uncertainty, as well as the impact on the representation of extreme precipitation events, and (b) to assess the usefulness of SMOS soil moisture products to improve the simulation of water cycle components and heavy precipitation events. Simulated soil moisture and precipitation fields are compared with observations and with level-1(~1km), level-2(~15 km) and level-3(~35 km) soil moisture maps generated from SMOS over the Iberian Peninsula, the SMOS validation area (50 km x 50 km, eastern Spain) and selected stations, where in situ measurements are available covering different vegetation cover and soil types. Additionally, measurements from an L-band radiometer from ESA (European Space Agency), ELBARA-II, installed in the area to monitor SMOS validation conditions over a vineyard crop are available. Furthermore, MODIS, LANDSAF and SMOS products are used to define realistic initial conditions for sensitivity simulations. The results of these simulations are investigated, compared and conclusions drawn. The investigation covers the autumn period of 2012, September to November, and we will particularly focus on selected stages where extreme rain events occurred in our study area.

Khodayar-Pardo, Samiro; Lopez-Baeza, Ernesto; Coll Pajaron, M. Amparo

193

Temperature and moisture analysis in composites  

NASA Technical Reports Server (NTRS)

Advanced fiber-reinforced polymeric matric composites have emerged as strong candidate materials for airframe applications. Favorable aspects include high strength, stiffness, and low density. Temperature and Moisture Analysis in Composites (TMAC) program was developed to study effect of variations in diffusion coefficients, surface properties, panel tilt, ground reflection, and geographical location on moisture-concentration profiles and average moisture contents of composite laminates.

Tenney, D. R.; Tompkins, S. S.; Unnam, J.

1980-01-01

194

Inverse Method for Estimating the Spatial Variability of Soil Particle Size Distribution from Observed Soil Moisture  

SciTech Connect

Soil particle size distribution (PSD) (i.e., clay, silt, sand, and rock contents) information is one of critical factors for understanding water cycle since it affects almost all of water cycle processes, e.g., drainage, runoff, soil moisture, evaporation, and evapotranspiration. With information about soil PSD, we can estimate almost all soil hydraulic properties (e.g., saturated soil moisture, field capacity, wilting point, residual soil moisture, saturated hydraulic conductivity, pore-size distribution index, and bubbling capillary pressure) based on published empirical relationships. Therefore, a regional or global soil PSD database is essential for studying water cycle regionally or globally. At the present stage, three soil geographic databases are commonly used, i.e., the Soil Survey Geographic database, the State Soil Geographic database, and the National Soil Geographic database. Those soil data are map unit based and associated with great uncertainty. Ground soil surveys are a way to reduce this uncertainty. However, ground surveys are time consuming and labor intensive. In this study, an inverse method for estimating mean and standard deviation of soil PSD from observed soil moisture is proposed and applied to Throughfall Displacement Experiment sites in Walker Branch Watershed in eastern Tennessee. This method is based on the relationship between spatial mean and standard deviation of soil moisture. The results indicate that the suggested method is feasible and has potential for retrieving soil PSD information globally from remotely sensed soil moisture data.

Pan, Feifei [University of Texas; Peters-lidard, Christa D. [NASA Goddard Space Flight Center; King, Anthony Wayne [ORNL

2010-11-01

195

Mapping Field Surface Soil Moisture for Hydrological Modeling  

Microsoft Academic Search

Soil moisture is a major control variable on hydrological processes both at the storm event scale and in the long term. The\\u000a aggregate effect on the mean water balance over an area can be quantified successfully using hydrological models. However,\\u000a determination of soil moisture distribution for semi or fully distributed models is difficult. In some types of landscape,\\u000a the distribution

Mustafa Tombul

2007-01-01

196

Tibetan Plateau Soil moisture products Intercomparison and the field observations  

Microsoft Academic Search

It is well known that soil moisture plays an important role in hydrological and climate modeling. With an average elevation exceeding 4,000, Tibetan Plateau land-surface water and energy cycles greatly influence the Asian Monsoon, and global atmosphere general circulations. A set of accurate soil moisture data of Tibetan Plateau can provide observational information for the studies of land-atmosphere interaction. In

Y. Qi; L. Lu; L. Jiang; J. Tao; J. Du; J. Shi

2010-01-01

197

SMOS CATDS Level 3 products, Soil Moisture and Brightness Temperature  

NASA Astrophysics Data System (ADS)

The ESA's (European Space Agency) SMOS (Soil Moisture and Ocean Salinity) mission, operating since november 2009, is the first satellite dedicated to measuring the surface soil moisture and the ocean salinity. The CNES (Centre National d'Etudes Spatiales) has developed the CATDS (Centre Aval de Traitement des Données SMOS) ground segment. The CATDS provides temporal synthesis products (referred to as level 3) of soil moisture, which are now covering the whole SMOS period, i.e. since January 2010. These products have different time resolutions: daily products, 3-day global products (insuring a complete coverage of the Earth surface), 10-day composite products, and monthly averaged products. Moreover, a new product provides brightness temperatures at H and V polarizations which are computed at fixed incidence angles every 5 degrees. As the instrument measures L-band brightness temperatures at the antenna frame (X/Y polarizations), a rotation is applied to transform the observations to V/H polarizations. All the CATDS products are presented in the NetCDF format and on the EASE grid (Equal Area Scalable Earth grid) with a spatial resolution of ~ 25*25 km2 The soil moisture level 3 algorithm is based on ESA's (European Space Agency) level 2 retrieval scheme with the improvement of using several overpasses (3 at most) over a 7-day window. The use of many revisits is expected to improve the retrieved soil moisture. This communication aims at presenting the soil moisture and brightness temperature products from the CATDS as well as the other geophysical parameters retrieved, such as the vegetation optical depth or the dielectric constant of the surface. SMOS Level 3 soil moisture. 3-days aggregation product, the best estimation of soil moisture is chosen.

Berthon, L.; Mialon, A.; Al Bitar, A.; Cabot, F.; Kerr, Y. H.

2012-12-01

198

Temporal and spatial scales of observed soil moisture variations in the extratropics  

Microsoft Academic Search

Scales of soil moisture variations are important for understanding patterns of climate change, for developing and evaluating land surface models, for designing surface soil moisture observation networks, and for determining the appropriate resolution for satellite-based remote sensing instruments for soil moisture. Here we take advantage of a new archive of in situ soil moisture observations from Illinois and Iowa in

Jared K. Entin; Alan Robock; Konstantin Y. Vinnikov; Steven E. Hollinger; Suxia Liu; A. Namkhai

2000-01-01

199

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

NASA Astrophysics Data System (ADS)

Forty years of research on passive and active microwave observations have led so far to a better understanding of the sensitivity of satellite microwave observations to soil moisture and to a higher confidence in the possibility to retrieve reliable soil moisture from these sensors at small as well as large scale. This research forms the basis of two important new satellite missions: ESA's Soil Moisture and Ocean Salinity mission (SMOS) and NASA's Soil Moisture Active and Passive mission (SMAP) whose main goal is the retrieval of soil moisture at global scale. In view of these missions, the research has been recently focussed more on the development of soil moisture retrieval methods which can be applied at global scale and on their application over the existing scatterometer (ERS scatterometer and Metop ASCAT) and radiometer (SMMR and AMSR-E) data to obtain long time series of global products. In this work, two global soil moisture products, one obtained from radiometer data and the other from scatterometer data, have been compared. The main objective of this comparison is to better understand the potential and limitations for soil moisture retrieval of both the data and the applied method and to investigate the possible complementarity of the different datasets. The two surface soil moisture datasets employed in this study are: the product obtained from AQUA AMSR-E data by the Department of Hydrology and Geo-Environmental Sciences of the Vrije Universiteit of Amsterdam and the product retrieved from ERS-2 scatterometer data by the Institute of Photogrammetry and Remote Sensing of the Vienna University of Technology. The temporal variability from 2003 to 2007, the seasonal trends, the anomalies, the autocorrelations and the correlation between the two global datasets have been analysed. Two in-situ datasets collected by large soil moisture monitoring networks in Oklahoma (Oklahoma Mesonet) and in Australia (OzNet) have been also included in this comparison. However the analysis has been also extended to other areas characterised by different vegetation cover. In these cases, temporal variability and trends have been compared with GPCC precipitation data. The analysis shows a general good agreement between the two global soil moisture datasets and with in-situ and precipitation data. Comparable temporal variability, trends and autocorrelations have been observed between AMSR-E and ERS soil moisture products over OzNet test site, confirmed also by the analysis of the soil moisture measured in-situ at a depth of 5 cm. As expected, the soil moisture measured at deeper layer shows trends shifted in time and longer autocorrelation than the satellite products. The obtained results can support the possibility to integrate the two soil moisture products and to synergistically use active and passive microwave data for soil moisture monitoring at global scale.

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

2009-04-01

200

NASA Giovanni: A Tool for Visualizing, Analyzing, and Inter-comparing Soil Moisture Data  

NASA Technical Reports Server (NTRS)

There are many existing satellite soil moisture algorithms and their derived data products, but there is no simple way for a user to inter-compare the products or analyze them together with other related data. An environment that facilitates such inter-comparison and analysis would be useful for validation of satellite soil moisture retrievals against in situ data and for determining the relationships between different soil moisture products. As part of the NASA Giovanni (Geospatial Interactive Online Visualization ANd aNalysis Infrastructure) family of portals, which has provided users worldwide with a simple but powerful way to explore NASA data, a beta prototype Giovanni Inter-comparison of Soil Moisture Products portal has been developed. A number of soil moisture data products are currently included in the prototype portal. More will be added, based on user requirements and feedback and as resources become available. Two application examples for the portal are provided. The NASA Giovanni Soil Moisture portal is versatile and extensible, with many possible uses, for research and applications, as well as for the education community.

Teng, William; Rui, Hualan; Vollmer, Bruce; deJeu, Richard; Fang, Fan; Lei, Guang-Dih; Parinussa, Robert

2014-01-01

201

Soil moisture measurement techniques for remote sensing ground truth: evaluation and performance test of soil moisture sensors  

NASA Astrophysics Data System (ADS)

Remote sensing technology requires fast and sufficiently accurate devices to take repetitive and less destructive soil moisture measurement techniques for validation of remotely sensed data. This study was conducted at Winfred Thomas Agricultural Research Station (WTARS) in Hazel Green, Alabama. The objectives of this study were to compare volumetric water content values measured with the time domain reflectometry (TDR) and water content reflectometry (WCR) instruments to the values obtained by the standard gravimetric technique for the upper soil depth and to examine the performance of the different types of soil moisture sensors and the effect of the probe length on the accuracy of soil moisture determination. From Huntsville '96 field research, we found that the emitting depth is 5 cm or less, possibly as low as 1 cm. This suggests that, in order to validate remotely sensed data, it is necessary to have fast and sufficiently accurate instruments to take repetitive and non-destructive soil moisture measurement to measure soil moisture. Our results indicated no significance difference between the Delta-T 6 cm probe output with GSM, MESA 10 cm probe output with GSM, and WCR30 and 20 cm probe output with GSM measurements. Even though the standard gravimetric technique is very reliable to measure soil moisture content, it is relatively time consuming and very destructive. Therefore, it may not be used for repetitive measurement at exactly the same location. The different types of TDR and WCR probes we tested can be used for measuring the moisture content. Except the WCR 5 and 10 cm probes, all probes tested in this experiment provided similar results. Therefore, this probe can replace the traditional gravimetric technique as long as the proper calibration is performed for a range of soil moisture and soil types.

Tsegaye, Teferi D.; Laymon, Charles A.; Crosson, William L.; Coleman, Tommy L.; Rajbhandari, Narayan B.

1997-12-01

202

Impact of the soil hydrology scheme on simulated soil moisture memory  

NASA Astrophysics Data System (ADS)

Soil moisture-atmosphere feedback effects play an important role in several regions of the globe. For some of these regions, soil moisture memory may contribute significantly to the state and temporal variation of the regional climate. Identifying those regions can help to improve predictability in seasonal to decadal climate forecasts. In order to accurately simulate soil moisture memory and associated soil moisture-atmosphere interactions, an adequate representation of soil hydrology is required. The present study investigates how different setups of a soil hydrology scheme affect soil moisture memory simulated by the global climate model of the Max Planck Institute for Meteorology, ECHAM6/JSBACH. First, the standard setup is applied in which soil water is represented by a single soil moisture reservoir corresponding to the root zone. Second, a new five layer soil hydrology scheme is introduced where not only the root zone is differentiated into several layers but also layers below are added. Here, three variants of the new scheme are utilized to analyse how different characteristics of the soil hydrology and the associated fluxes influence soil moisture memory. Soil moisture memory of the different setups is analysed from global ECHAM6/JSBACH simulations forced by observed SST. Areas are highlighted where the regional climate seems to be sensitive to the improved representation of soil hydrology in the new setup and its variants. Results indicate that soil moisture memory is generally enlarged in regions during the dry season where a soil moisture buffer is present below the root zone due to the 5-layer scheme. This effect is usually enhanced when this buffer is increased. Memory tends to be weakened (strengthened) where bare soil evaporation is increased (decreased), especially in semi-arid regions and wet seasons. For some areas, this effect is compensated by a decreased (increased) transpiration.

Hagemann, Stefan; Stacke, Tobias

2014-06-01

203

Preliminary results of SAR soil moisture experiment, November 1975  

NASA Technical Reports Server (NTRS)

The experiment was performed using the Environmental Research Institute of Michigan's (ERIM) dual-frequency and dual-polarization side-looking SAR system on board a C-46 aircraft. For each frequency, horizontally polarized pulses were transmitted and both horizontally and vertically polarized return signals were recorded on the signal film simultaneously. The test sites were located in St. Charles, Missouri; Centralia, Missouri; and Lafayette, Indiana. Each test site was a 4.83 km by 8.05 km (3 mile by 5 mile) rectangular strip of terrain. Concurrent with SAR overflight, ground soil samples of 0-to-2.5 cm and 0-to-15 cm layers were collected for soil moisture estimation. The surface features were also noted. Hard-copy image films and the digital data produced via optical processing of the signal films are analyzed in this report to study the relationship of radar backscatter to the moisture content and the surface roughness. Many difficulties associated with processing and analysis of the SAR imagery are noted. In particular, major uncertainty in the quantitative analysis appeared due to the difficulty of quality reproduction of digital data from the signal films.

Choudhury, B. J.; Chang, A. T. C.; Schmugge, T. J.; Salomonson, V. V.; Wang, J. R.

1979-01-01

204

The role of vegetation and soil properties on the spatio-temporal variability of the surface soil moisture in a maize-cropped field  

NASA Astrophysics Data System (ADS)

Soil moisture dynamics are affected by complex interactions among several factors. Understanding the relative importance of these factors is still an important challenge in the study of water fluxes and solute transport in unsaturated media. In this study, the spatio-temporal variability of surface soil moisture was investigated in a 10 ha flat cropped field located in northern Italy. Soil moisture was measured on a regular 50 × 50 m grid on seven dates during the growing season. For each measurement campaign, the spatial variability of the soil moisture was compared with the spatial variability of the soil texture and crop properties. In particular, to better understand the role of the vegetation, the spatio-temporal variability of two different parameters - leaf area index and crop height - was monitored on eight dates at different crop development stages. Statistical and geostatistical analysis was then applied to explore the interactions between these variables. In agreement with other studies, the results show that the soil moisture variability changes according to the average value within the field, with the standard deviation reaching a maximum value under intermediate mean soil moisture conditions and the coefficient of variation decreasing exponentially with increasing mean soil moisture. The controls of soil moisture variability change according to the average soil moisture within the field. Under wet conditions, the spatial distribution of the soil moisture reflects the variability of the soil texture. Under dry conditions, the spatial distribution of the soil moisture is affected mostly by the spatial variability of the vegetation. The interaction between these two factors is more important under intermediate soil moisture conditions. These results confirm the importance of considering the average soil moisture conditions within a field when investigating the controls affecting the spatial variability of soil moisture. This study highlights the importance of considering the spatio-temporal variability of the vegetation in investigating soil moisture dynamics, especially under intermediate and dry soil moisture conditions. The results of this study have important implications in different hydrological applications, such as for sampling design, ranking stability application, indirect measurements of soil properties and model parameterisation.

Baroni, G.; Ortuani, B.; Facchi, A.; Gandolfi, C.

2013-05-01

205

Soil moisture determination by means of the data driven models  

NASA Astrophysics Data System (ADS)

Information's about soil water content are in the planning of water resources and management very valuable. Modeling and predicting soil water transfer is very important in agriculture or hydrology - e.g. for purposes of the effective irrigation management. Many tried and proven methods of estimating or measuring soil moisture are available. The choice of the method which in particular case is eligible, depends on a variety of factors such as accuracy, cost, and ease of use. One of the most important hydro physical characteristics of soil is water retention curve (WRC), which is input to various hydraulic and hydrological models and reflects the energy dependence of soil water and the water content, e.g. the relationship between soil moisture and moisture potential. The method of determining the water retention curve points in laboratory conditions is very expensive, time consuming and labor intensive. In soil physics, therefore, were developed methods for determining soil hydro physical characteristics from easier obtained characteristics - soil granularity composition, organic matter content and bulk density. For these models (or relations) have been established title pedotransfer functions (PTF). These functions specify different soil characteristics and properties from relationship with another. The submitted work compares the creation of such functional dependencies using neural networks, hybrid self-organizing map (SOM) and support vector machines (SVM) model and standard multi-linear regression method. The SVMs formulate a quadratic optimization problem that avoids local minima problems, which makes them often superior to traditional (iterative) learning algorithms such as multi-layer perceptron (MLP) type of neural network. Input data are taken from Zahorská lowland in Slovakia. It was taken 140 soil samples from various localities of Zahorská lowland on finding soil characteristics and on the expression of water retention curve points. Sandy soils are prevailing in this area. Main input data were percentage of granularity categories I to IV according to Kopecky method, reduced volume weight (?d) and measured humidity for potentials hw = -2.5; -56, -209, -558, -976, -3060, -15300 cm specified in laboratory in the overpressure equipment for testing the regression made with abovementioned methods. To compare the results between measured and modeled data by various data driven methods, was accomplished an analysis using correlation coefficient and other statistical characteristics. This evaluation revealed most accurate results by using hybrid SOM-SVM model, in comparison with a conventional multi-layer artificial neural networks, multi-linear regression and standalone SVM model. Greater stability and need of less time devoted to calculations was observed in computation using SVM methodology, since the MLP training sometimes stuck in a local minimum so the training process has to be reset and run many times. This work was supported by the Slovak Research and Development Agency under the contract No. LPP-0319-09.

Cisty, Milan; Suchar, Martin; Bajtek, Zbynek

2010-05-01

206

Effect of Surface Soil Moisture Assimilation on SWAT Model Output  

NASA Astrophysics Data System (ADS)

The Ensemble Kalman Filter(EnKF) was coupled with a watershed scale distributed hydrologic model, the Soil and Water Assessment Tool (SWAT) to improve predictions of soil water content and thus enhance overall model performance of the hydrologic system by assimilating spatially distributed measured surface soil moisture. The SWAT model is based on the concept of Hydrologic Response Units (HRU) and has been widely applied to many different areas of watershed scale modeling. However, there is a lack of investigative research as to how the spatial variability of inputs, especially from remotely sensed surface soil moisture data, affects the potential capability of data assimilation techniques with SWAT. In this study, a synthetic experiment is performed to better understand how soil moisture data assimilation affects various hydrologic processes in the model at the watershed scale. The study area for this work is the Upper Cedar Creek Watershed (UCCW) which is located in northeastern Indiana. There are two sources of rainfall data available for the UCCW: the National Climatic Data Center (NCDC) and hydrometerological network maintained by the USDA, Agricultural Research Service National Soil Erosion Research Laboratory (NSERL) to measure precipitation and soil moisture data. First, the “true” state is implemented by running the model with all available rainfall data from the NCDC and the NSERL raingauge network. To represent our imperfect knowledge of the true hydrologic processes, subsequently the model is run with an intentionally poor set of initial conditions and “limited” forcing data from only NCDC raingauges for the same time period. By limiting precipitation input, which is the driving force of soil moisture and streamflow, while keeping other model parameters unchanged, we determine how the updated soil water condition with surface measured soil moisture influences model predictions of profile soil water content, runoff and streamflow. Results show that daily assimilation of surface soil moisture for each HRU improves model predictions especially by reducing the overestimated streamflow due to the errors associated with insufficient spatially distributed rainfall input. Improved daily streamflow exceedance curve and statistical measures (the coefficient of determination and the Nash-Sutcliffe efficiency) demonstrate that better representation of soil water content through surface soil moisture assimilation can enhance the rainfall-runoff processes in the SWAT model. Distributed errors of the soil water content are also illustrated to show the influences of spatial variability.

Han, E.; Merwade, V.; Heathman, G. C.

2010-12-01

207

Assimilation of Satellite Based Soil Moisture Data in the National Weather Service's Flash Flood Guidance System  

NASA Astrophysics Data System (ADS)

Climate change and variability increases the probability of frequency, timing, intensity, and duration of flood events. After rainfall, soil moisture is the most important factor dictating flash flooding, since rainfall infiltration and runoff are based on the saturation of the soil. It is difficult to conduct ground-based measurements of soil moisture consistently and regionally. As such, soil moisture is often derived from models and agencies such as the National Oceanic and Atmospheric Administration's National Weather Service (NOAA/NWS) use proxy estimates of soil moisture at the surface in order support operational flood forecasting. In particular, a daily national map of Flash Flood Guidance (FFG) is produced that is based on surface soil moisture deficit and threshold runoff estimates. Flash flood warnings are issued by Weather Forecast Offices (WFOs) and are underpinned by information from the Flash Flood Guidance (FFG) system operated by the River Forecast Centers (RFCs). This study analyzes the accuracy and limitations of the FFG system using reported flash flood cases in 2010 and 2011. The flash flood reports were obtained from the NWS Storm Event database for the Arkansas-Red Basin RFC (ABRFC). The current FFG system at the ABRFC provides gridded flash flood guidance (GFFG) System using the NWS Hydrology Laboratory-Research Distributed Hydrologic Model (HL-RDHM) to translate the upper zone soil moisture to estimates of Soil Conservation Service Curve Numbers. Comparison of the GFFG and real-time Multi-sensor Precipitation Estimator derived Quantitative Precipitation Estimate (QPE) for the same duration and location were used to analyze the success of the system. Improved flash flood forecasting requires accurate and high resolution soil surface information. The remote sensing observations of soil moisture can improve the flood forecasting accuracy. The Soil Moisture Active and Passive (SMAP) and Soil Moisture and Ocean Salinity (SMOS) satellites are two potential sources of remotely sensed soil moisture data. SMOS measures the microwave radiation emitted from the Earth's surface operating at L-band (1.20-1.41 GHz) to measure surface soil moisture directly. Microwave radiation at this wavelength offers relatively deeper penetration and has lower sensitivity to vegetation impacts. The main objective of this research is to evaluate the contribution of remote sensing technology to quantifiable improvements in flash flood applications as well as adding a remote sensing component to the NWS FFG Algorithm. The challenge of this study is employing the direct soil moisture data from SMOS to replace the model-calculated soil moisture state which is based on the soil water balance in 4 km x 4 km Hydrologic Rainfall Analysis Project (HRAP) grid cells. In order to determine the value of the satellite data to NWS operations, the streamflow generated by HL-RDHM with and without soil moisture assimilation will be compared to USGS gauge data. Furthermore, we will apply the satellite-based soil moisture data with the FFG algorithm to evaluate how many hits, misses and false alarms are generated. This study will evaluate the value of remote sensing data in constraining the state of the system for main-stem and flash flood forecasting.

Seo, D.; Lakhankar, T.; Cosgrove, B.; Khanbilvardi, R.

2012-12-01

208

Soil Moisture Drought in China, 19502006 Nansen-Zhu International Research Centre, Institute of Atmospheric Physics, Beijing, China  

E-print Network

Soil Moisture Drought in China, 1950­2006 AIHUI WANG Nansen-Zhu International Research Centre from which agricultural drought severities and durations were estimated. A cluster analysis method and severity­area­duration (SAD) algorithm were applied to the soil moisture data to characterize drought

209

A physically based approach for the estimation of root-zone soil moisture from surface measurements  

NASA Astrophysics Data System (ADS)

In the present work, we developed a new formulation for the estimation of the soil moisture in the root zone based on the measured value of soil moisture at the surface. It was derived from a simplified soil water balance equation for semiarid environments that provides a closed form of the relationship between the root zone and the surface soil moisture with a limited number of physically consistent parameters. The method sheds lights on the mentioned relationship with possible applications in the use of satellite remote sensing retrievals of soil moisture. The proposed approach was used on soil moisture measurements taken from the African Monsoon Multidisciplinary Analysis (AMMA) and the Soil Climate Analysis Network (SCAN) databases. The AMMA network was designed with the aim to monitor three so-called mesoscale sites (super sites) located in Benin, Mali, and Niger using point measurements at different locations. Thereafter the new formulation was tested on three additional stations of SCAN in the state of New Mexico (US). Both databases are ideal for the application of such method, because they provide a good description of the soil moisture dynamics at the surface and the root zone using probes installed at different depths. The model was first applied with parameters assigned based on the physical characteristics of several sites. These results highlighted the potential of the methodology, providing a good description of the root-zone soil moisture. In the second part of the paper, the model performances were compared with those of the well-known exponential filter. Results show that this new approach provides good performances after calibration with a set of parameters consistent with the physical characteristics of the investigated areas. The limited number of parameters and their physical interpretation makes the procedure appealing for further applications to other regions.

Manfreda, S.; Brocca, L.; Moramarco, T.; Melone, F.; Sheffield, J.

2014-03-01

210

Potential Soil Moisture Products from the Aquarius Radiometer and Scatterometer Using an Observing System Simulation Experiment  

SciTech Connect

Using an observing system simulation experiment (OSSE), we investigate the potential soil moisture retrieval capability of the National Aeronautics and Space Administration (NASA) Aquarius radiometer (L-band 1.413 GHz) and scatterometer (L-band, 1.260 GHz). We estimate potential errors in soil moisture retrievals and identify the sources that could cause those errors. The OSSE system includes (i) a land surface model in the NASA Land Information System, (ii) a radiative transfer and backscatter model, (iii) a realistic orbital sampling model, and (iv) an inverse soil moisture retrieval model. We execute the OSSE over a 1000 2200 km2 region in the central United States, including the Red and Arkansas river basins. Spatial distributions of soil moisture retrieved from the radiometer and scatterometer are close to the synthetic truth. High root mean square errors (RMSEs) of radiometer retrievals are found over the heavily vegetated regions, while large RMSEs of scatterometer retrievals are scattered over the entire domain. The temporal variations of soil moisture are realistically captured over a sparely vegetated region with correlations 0.98 and 0.63, and RMSEs 1.28% and 8.23% vol/vol for radiometer and scatterometer, respectively. Over the densely vegetated region, soil moisture exhibits larger temporal variation than the truth, leading to correlation 0.70 and 0.67, respectively, and RMSEs 9.49% and 6.09% vol/vol respectively. The domain-averaged correlations and RMSEs suggest that radiometer is more accurate than scatterometer in retrieving soil moisture. The analysis also demonstrates that the accuracy of the retrieved soil moisture is affected by vegetation coverage and spatial aggregation.

Luo, Yan [I.M. Systems Group at NOAA/NCEP/EMC; Feng, Xia [George Mason University; Houser, Paul [George Mason University; Anantharaj, Valentine G [ORNL; Fan, Xingang [Western Kentucky University, Bowling Green; De Lannoy, Gabrielle [Ghent University, Belgium; Zhan, Xiwu [NOAA/NESDIS Center for Satellite Applications and Research; Dabbiru, Lalitha [Mississippi State University (MSU)

2013-01-01

211

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

NASA Astrophysics Data System (ADS)

Global soil moisture (SM) monitoring in the past several decades has been undertaken mainly at coarse spatial resolution, which is not adequate for addressing small-scale phenomena and processes. The currently operational Advanced Microwave Scanning Radiometer (NASA) and future planned missions such as the Soil Moisture and Ocean Salinity (ESA) and the Soil Moisture Active Passive (NASA) will remain resolution limited. Finer scale soil moisture estimates can be achieved either by down-scaling the available coarse resolution radiometer and scatterometer (i.e. ERS1/2, ASCAT) observations or by using high resolution active microwave SAR type systems (typical resolution is in the order of meters). Considering the complex land surface - backscatter signal interaction, soil moisture inversion utilizing active microwave observations is difficult and generally needs supplementary data. Algorithms based on temporal change detection offer an alternative less complex approach for deriving (and disaggregating coarse) soil moisture estimates. Frequent monitoring and low frequency range along with a high pixel resolution are essential preconditions when characterizing spatial and temporal soil moisture variability. An alternative active system that meets these requirements is the Advance Synthetic Aperture Radar (ASAR) on ENVISAT [C-band, global, 1 km in Global Monitoring (GM) Mode]. The Vienna University of Technology (TU Wien) has developed a 1 km soil moisture product using the temporal change detection approach and the ASAR GM. The TU Wien SM product sensitivity was evaluated at two scales: point (using in situ data from permanent soil moisture stations) and regional [using ground measured data and aircraft estimates derived from the Polarimetric L-band Microwave Radiometer (PLMR)] over the National Airborne Field Experiment (NAFE'05) area located in the Goulburn catchment, SE Australia. The month long (November 2005) campaign was undertaken in a region predominantly covered by grasslands and partly by forests and croplands. Point scale analysis revealed high ASAR sensitivity and adequate response to changes in moisture conditions (R = 0.69 and RMSE = 0.08 v/v). Regional analysis was performed at several different spatial resolutions (1 km to 25 km). ASAR exhibited high noise level and significant wet bias. Increase in pixel size resulted in improving R and RMSE from R = 0.59 and RMSE = 0.14 to R = 0.91 and RMSE = 0.05 at 1 km and 25 km respectively; however, despite the reasonable statistical agreement at 1 km, the soil moisture spatial patterns clearly visible in the PLMR images, the later were verified with ground data, were lacking in the ASAR product.

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

2008-12-01

212

Aircraft scatterometer observations of soil moisture on rangeland watersheds  

NASA Technical Reports Server (NTRS)

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

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

1983-01-01

213

Does soil moisture overrule temperature dependence of soil respiration in Mediterranean riparian forests?  

NASA Astrophysics Data System (ADS)

Soil respiration (SR) is a major component of ecosystems' carbon cycles and represents the second largest CO2 flux in the terrestrial biosphere. Soil temperature is considered to be the primary abiotic control on SR, whereas soil moisture is the secondary control factor. However, soil moisture can become the dominant control on SR in very wet or dry conditions. Determining the trigger that makes soil moisture as the primary control factor of SR will provide a deeper understanding on how SR changes under the projected future increase in droughts. Specific objectives of this study were (1) to investigate the seasonal variations and the relationship between SR and both soil temperature and moisture in a Mediterranean riparian forest along a groundwater level gradient; (2) to determine soil moisture thresholds at which SR is controlled by soil moisture rather than by temperature; (3) to compare SR responses under different tree species present in a Mediterranean riparian forest (Alnus glutinosa, Populus nigra and Fraxinus excelsior). Results showed that the heterotrophic soil respiration rate, groundwater level and 30 cm integral soil moisture (SM30) decreased significantly from the riverside moving uphill and showed a pronounced seasonality. SR rates showed significant differences between tree species, with higher SR for P. nigra and lower SR for A. glutinosa. The lower threshold of soil moisture was 20 and 17% for heterotrophic and total SR, respectively. Daily mean SR rate was positively correlated with soil temperature when soil moisture exceeded the threshold, with Q10 values ranging from 1.19 to 2.14; nevertheless, SR became decoupled from soil temperature when soil moisture dropped below these thresholds.

Chang, C. T.; Sabaté, S.; Sperlich, D.; Poblador, S.; Sabater, F.; Gracia, C.

2014-11-01

214

Does soil moisture overrule temperature dependency of soil respiration in Mediterranean riparian forests?  

NASA Astrophysics Data System (ADS)

Soil respiration (SR) is a major component of ecosystem's carbon cycle and represents the second largest CO2 flux of the terrestrial biosphere. Soil temperature is considered to be the primary control on SR whereas soil moisture as the secondary control factor. However, soil moisture can become the dominant control on SR in very wet or dry conditions. Determining the trigger that switches-on soil moisture as the primary control factor of SR will provide a deeper understanding on how SR changes under projected future increased droughts. Specific objectives of this study were (1) to investigate the seasonal variations and the relationship between SR and both soil temperature and moisture in a Mediterranean riparian forest along a groundwater level gradient; (2) to determine soil moisture thresholds at which SR is rather controlled by soil moisture than by temperature; (3) to compare SR responses under different tree species present in a Mediterranean riparian forest (Alnus, glutinosa, Populus nigra and Fraxinus excelsior). Results showed that the heterotrophic soil respiration rate, groundwater level and 30 cm integral soil moisture (SM30) decreased significantly from riverside to uphill and showed a pronounced seasonality. SR rates showed significant differences among tree species, with higher SR for P. nigra and lower SR for A. glutinosa. The lower threshold of soil moisture was 20 and 17% for heterotrophic and total SR respectively. Daily mean SR rate was positively correlated with soil temperature when soil moisture exceeded the threshold, with Q10 values ranging from 1.19 to 2.14; nevertheless, SR became decoupled from soil temperature when soil moisture dropped below these thresholds.

Chang, C.-T.; Sabaté, S.; Sperlich, D.; Poblador, S.; Sabater, F.; Gracia, C.

2014-06-01

215

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

PubMed Central

Abstract Mathematical models have been widely used in analyzing the effects of various environmental factors in the vapor intrusion process. Soil moisture content is one of the key factors determining the subsurface vapor concentration profile. This manuscript considers the effects of soil moisture profiles on the soil gas vapor concentration away from any surface capping by buildings or pavement. The “open field” soil gas vapor concentration profile is observed to be sensitive to the soil moisture distribution. The van Genuchten relations can be used for describing the soil moisture retention curve, and give results consistent with the results from a previous experimental study. Other modeling methods that account for soil moisture are evaluated. These modeling results are also compared with the measured subsurface concentration profiles in the U.S. EPA vapor intrusion database. PMID:24170970

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

2013-01-01

216

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

PubMed

Mathematical models have been widely used in analyzing the effects of various environmental factors in the vapor intrusion process. Soil moisture content is one of the key factors determining the subsurface vapor concentration profile. This manuscript considers the effects of soil moisture profiles on the soil gas vapor concentration away from any surface capping by buildings or pavement. The "open field" soil gas vapor concentration profile is observed to be sensitive to the soil moisture distribution. The van Genuchten relations can be used for describing the soil moisture retention curve, and give results consistent with the results from a previous experimental study. Other modeling methods that account for soil moisture are evaluated. These modeling results are also compared with the measured subsurface concentration profiles in the U.S. EPA vapor intrusion database. PMID:24170970

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

2013-10-01

217

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

NASA Technical Reports Server (NTRS)

Soil Moisture Active Passive (SMAP) satellite has been proposed to provide global measurements of soil moisture and land freeze/thaw state at 10 km and 3 km resolutions, respectively. SMAP would also provide a radiometer-only soil moisture product at 40-km spatial resolution. This product and the supporting brightness temperature observations are common to both SMAP and European Space Agency's Soil Moisture and Ocean Salinity (SMOS) mission. As a result, there are opportunities for synergies between the two missions. These include exploiting the data for calibration and validation and establishing longer term L-band brightness temperature and derived soil moisture products. In this investigation we will be using SMOS brightness temperature, ancillary data, and soil moisture products to develop and evaluate a candidate SMAP L2 passive soil moisture retrieval algorithm. This work will begin with evaluations based on the SMOS product grids and ancillary data sets and transition to those that will be used by SMAP. An important step in this analysis is reprocessing the multiple incidence angle observations provided by SMOS to a global brightness temperature product that simulates the constant 40 degree incidence angle observations that SMAP will provide. The reprocessed brightness temperature data provide a basis for evaluating different SMAP algorithm alternatives. Several algorithms are being considered for the SMAP radiometer-only soil moisture retrieval. In this first phase, we utilized only the Single Channel Algorithm (SCA), which is based on the radiative transfer equation and uses the channel that is most sensitive to soil moisture (H-pol). Brightness temperature is corrected sequentially for the effects of temperature, vegetation, roughness (dynamic ancillary data sets) and soil texture (static ancillary data set). European Centre for Medium-Range Weather Forecasts (ECMWF) estimates of soil temperature for the top layer (as provided as part of the SMOS ancillary data) were used to correct for surface temperature effects and to derive microwave emissivity. ECMWF data were also used for precipitation forecasts, presence of snow, and frozen ground. Vegetation options are described below. One year of soil moisture observations from a set of four watersheds in the U.S. were used to evaluate four different retrieval methodologies: (1) SMOS soil moisture estimates (version 400), (2) SeA soil moisture estimates using the SMOS/SMAP data with SMOS estimated vegetation optical depth, which is part of the SMOS level 2 product, (3) SeA soil moisture estimates using the SMOS/SMAP data and the MODIS-based vegetation climatology data, and (4) SeA soil moisture estimates using the SMOS/SMAP data and actual MODIS observations. The use of SMOS real-world global microwave observations and the analyses described here will help in the development and selection of different land surface parameters and ancillary observations needed for the SMAP soil moisture algorithms. These investigations will greatly improve the quality and reliability of this SMAP product at launch.

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

2011-01-01

218

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

USGS Publications Warehouse

The spatial and temporal variations in soil respiration and its relationship with biophysical factors in forests near the Tropic of Cancer remain highly uncertain. To contribute towards an improvement of actual estimates, soil respiration rates, soil temperature, and soil moisture were measured in three successional subtropical forests at the Dinghushan Nature Reserve (DNR) in southern China from March 2003 to February 2005. The overall objective of the present study was to analyze the temporal variations of soil respiration and its biophysical dependence in these forests. The relationships between biophysical factors and soil respiration rates were compared in successional forests to test the hypothesis that these forests responded similarly to biophysical factors. The seasonality of soil respiration coincided with the seasonal climate pattern, with high respiration rates in the hot humid season (April-September) and with low rates in the cool dry season (October-March). Soil respiration measured at these forests showed a clear increasing trend with the progressive succession. Annual mean (?? SD) soil respiration rate in the DNR forests was (9.0 ?? 4.6) Mg CO2-C/hm2per year, ranging from (6.1 ?? 3.2) Mg CO2-C/hm2per year in early successional forests to (10.7 ?? 4.9) Mg CO2-C/hm2 per year in advanced successional forests. Soil respiration was correlated with both soil temperature and moisture. The T/M model, where the two biophysical variables are driving factors, accounted for 74%-82% of soil respiration variation in DNR forests. Temperature sensitivity decreased along progressive succession stages, suggesting that advanced-successional forests have a good ability to adjust to temperature. In contrast, moisture increased with progressive succession processes. This increase is caused, in part, by abundant respirators in advanced-successional forest, where more soil moisture is needed to maintain their activities. ?? 2006 Institute of Botany, Chinese Academy of Sciences.

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

2006-01-01

219

Development of a Satellite Systems for Measuring Soil Moisture  

NASA Technical Reports Server (NTRS)

The science need for remotely sensed soil moisture has been well established in the hydrologic, climate change and weather forecasting communities. There also have been a number of programs that have demonstrated the feasibility of using long wave microwave sensors for estimating soil moisture. These have ranged from truck mounted sensors, to intensive airborne campaigns with science objectives. Based on this history of truck and aircraft experiments, the science community has settled on a soil moisture product that meets the following criteria: a two day global repeat, a measured layer of 5 cm of soil, a footprint of 20 to 30 km, and an absolute accuracy of +/- 4% volumetric soil moisture. The principal sensor to accomplish this is an L-band passive microwave radiometer. A soil moisture mission is being proposed for the NASA Earth Systems Science Pathfinder (ESSP) mission which has very real constraints of a limited budget which includes the launch vehicle, and a three year award to launch time schedule. This paper describes ways to solve the very large antenna challenge, and the criteria used to choose the final design for an ESSP proposal. The paper also discusses the alternatives considered to obtain the necessary ancillary data for characterizing the surface roughness, the surface temperature and the attenuation affects of vegetation.

Engman, Edwin T.

1998-01-01

220

Sensitivity of Severe Convective Storms to Soil Moisture and Lower Atmospheric Water Vapor  

NASA Astrophysics Data System (ADS)

Numerous studies have examined the sensitivity of the atmospheric state to soil moisture on time scales of up to a day. Dry line intensity, lower tropospheric water vapor content, and precipitation have all been shown through modeling studies to be affected by modest perturbations to upstream soil moisture content and subsequent lower atmospheric water vapor. Since all of these aspects could be associated with convection, a high-impact forecast event that exhibits rapid nonlinear error growth, it is reasonable to expect that irrigation practices might influence severe convective storms. Understanding the link between soil moisture and specific convective elements could have broad implications for severe weather forecasting, and could reveal the degree to which irrigation-induced storm-scale inadvertent weather modification exists. This work examines the sensitivity to soil moisture and lower atmospheric water vapor content of a severe convective storm that struck Moore, Oklahoma, USA on May 20th, 2013, killing 24 people. While adjoint sensitivity analysis that employs the tangent linear version of a numerical weather prediction model might be used to examine convective sensitivities to soil moisture, the strong nonlinearity associated with these events likely renders this technique inaccurate. Alternatively, the approach here utilizes backward trajectory analysis to identify the regions up to a day prior to which the storm might be sensitive. Once the regions are identified, an ensemble of model forecasts is created by varying initial soil moisture to reveal the degree to which perturbations must be made to influence the downstream storm. Subsequent comparisons are made between the required soil moisture perturbations and realistic soil water values added through irrigation.

Ancell, Brian; Nauert, Christian

2014-05-01

221

Soil Moisture Measurement in Heterogeneous Terrain Merlin, O.1  

E-print Network

, salinity and conductivity. A direct comparison between the factory calibration and gravimetric soilSoil Moisture Measurement in Heterogeneous Terrain Merlin, O.1 , J.P. Walker1 , R. Panciera1 , R of Melbourne, Australia 2 School of Engineering, The University of Newcastle, Australia 3 NASA Goddard Space

Walker, Jeff

222

NASA's Soil Moisture Active Passive (SMAP) Mission and Opportunities for Applications Users  

E-print Network

Water in the soil—both its amount (soil moisture) and its state (freeze/thaw)—plays a key role in water and energy cycles, in weather and climate, and in the carbon cycle. Additionally, soil moisture touches upon human ...

Brown, Molly E.

223

A soil moisture availability model for crop stress prediction  

E-print Network

-Chairmen of Advisory Committee: Dr. Peter J. H. Sharpe Dr. Hs1n-i Wu This thesis presents three 1mportant components of a soil- moisture accounting method--evaporat1on, transpiration, and root water uptake--that have been developed for crop water stress predict1on... root 10 water uptake is not restricted by horizontal moisture gradients in the soil. The average root and water content of a compartment (soil layer) are the variables determining the rate of water withdrawal. When part of the root system...

Gay, Roger Franklin

2012-06-07

224

Determination of Soil Moisture by the Method of Multiple Electrodes.  

E-print Network

measurements of soil resistivity to. the determination of soil moisture, and the results obtained during the summer of 1930 at Substation No. 7, located near Spur, Dickens County. Comparison of soil-moisture measurements by the auger method...- tudicd, in ' th samplings required b. th auger metholl would nt r a. an ro ?ion factor. To this end the project lead r,-Mr. A. B. onn r Mr. H. B. Dickson, and :Mr. D. , ' ?oat - initiated a. plan to u th el' tri n 1 c ll - cluctivity method for m a...

McCorkle, W. H.

1931-01-01

225

Soil Moisture: The Hydrologic Interface Between Surface and Ground Waters  

NASA Technical Reports Server (NTRS)

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

Engman, Edwin T.

1997-01-01

226

A Multi-Scale Soil Moisture and Freeze-Thaw Monitoring Network on the Tibetan Plateau and Its Applications  

NASA Astrophysics Data System (ADS)

In situ measurements are required to support the calibration and validation of satellite remote sensing of soil moisture. For this purpose, we established a dense monitoring network on central Tibetan Plateau to measure two state variables (soil moisture and temperature) at three spatial scales (1.0, 0.3, 0.1 degree) and four soil depths (0~5cm, 10cm, 20cm, and 40cm). The experimental area is characterized by low biomass, large soil moisture dynamic range and typical freeze-thaw cycle. The network consists of 56 stations with their elevation varying over 4470 ~ 4950 m. Soil texture and soil organic matters are measured at each station, as auxiliary parameters of this network. In order to guarantee continuous and high-quality data, tremendous efforts have been made to protect the data logger from soil water intrusion, to calibrate soil moisture sensors, and to upscale the point measurements. As the highest soil moisture network in the world, our network meets the requirement for evaluating a variety of soil moisture products and for soil moisture scaling. The data is being publicized via the International Soil Moisture Network. Based on the soil moisture data, we have conducted studies to evaluate GLDAS output and remotes sensing products, and to develop soil moisture upscaling and data assimilation algorithms. References: Yang, K., J. Qin, L. Zhao, Y. Y. Chen, W. J. Tang, M. L. Han, Lazhu, Z. Q. Chen, N. Lv, B. H. Ding, H. Wu, C. G. Lin, 2013: A Multi-Scale Soil Moisture and Freeze-Thaw Monitoring Network on the Third Pole, Bulletin of the American Meteorological Society, doi: 10.1175/BAMS-D-12-00203.1, in press Chen, Y. Y., K. Yang, J. Qin, L. Zhao, W. J. Tang and M. L. Han, 2013: Evaluation of AMSR-E retrievals and GLDAS simulations against observations of a soil moisture network on the central Tibetan Plateau, J. Geophys. Res. Atmos., 118, doi:10.1002/jgrd.50301. Zhao, L., K. Yang, J. Qin, Y. Y. Chen, W. J. Tang, C. Montzka, H. Wu, C. G. Lin, M. L. Han, and H. Vereecken., 2013: Spatiotemporal analysis of soil moisture observations within a Tibetan mesoscale area and its implication to regional soil moisture measurements, Journal of Hydrology, 482, 92-104 doi:10.1016/j.jhydrol.2012.12.033.

Yang, K.

2013-12-01

227

Soil electromagnetic parameters as functions of frequency, soil density, and soil moisture  

Microsoft Academic Search

Measurements are made to determine the conductivity and dielectric constants of a gray clay loam and a reddish-brown clay loam. The measurements are made as a function of soil density (from 1.2 g\\/cm3to 1.8 g\\/cm3), soil moisture (from 0 percent to 20 percent of the dry soil weight), and excitation frequency (from 30 MHz to 4 GHz), using standard transmission

J. E. Hipp

1974-01-01

228

Poor Soil Wettability: Does moisture alter measurement results?  

NASA Astrophysics Data System (ADS)

Poor soil wettability is a global problem, creating challenges to agriculture by plant drought stress and to soil stability in natural environments. Events that lead to poor soil wettability are varied, including natural and manmade events such as forest fires, hot dry environments, poor soil management or the application of post-consumer materials. Even though options offered in the literature for amelioration of the symptoms of hydrophobicity greatly differ, the basic techniques used to identify hydrophobic soil have changed very little over the past half-century. Recently, however, scientists have begun to question what these traditional techniques are actually measuring. One of the areas of interest is the relationship of hydrophobicity to moisture content, also termed reversible or seasonal hydrophobicity. Many studies suggest that changes in the organic matter structure as it is exposed to soil moisture leads to a reduction of the surface energy of particle surfaces. This study further complements that work by investigating how testing methods and soil-sample treatment impact water sorption of hydrophobic media, so as to make it appear that the surface energy has changed. The understanding of this phenomenon can lead to improved techniques for testing of hydrophobicity soil and also for soil management in agricultural areas by understanding the impact of soil moisture regimes on wettability.

Dragila, M. I.; Woolverton, P.; Horneck, D.; Kleber, M.

2013-12-01

229

Determination of soil moisture distribution from impedance and gravimetric measurements  

NASA Technical Reports Server (NTRS)

Daily measurements of the soil dielectric properties at 5 and 10 cm were obtained at five locations throughout the First ISLSCP Field Experiment (FIFE) test site during the 1987 intensive field campaigns (IFCs). An automated vector voltmeter was used to monitor the complex electrical impedance, at 10 MHz, of cylindrical volumes of soil delineated by specially designed soil moisture probes buried at these locations. The objective of this exercise was to test the hypothesis that the soil impedance is sensitive to the moisture content of the soil and that the imaginary part (that is, capacitive reactance) can be used to calculate the volumetric water content of the soil. These measurements were compared with gravimetric samples collected at these locations by the FIFE staff science team.

Ungar, Stephen G.; Layman, Robert; Campbell, Jeffrey E.; Walsh, John; Mckim, Harlan J.

1992-01-01

230

Determination of soil moisture distribution from impedance and gravimetric measurements  

NASA Astrophysics Data System (ADS)

Daily measurements of the soil dielectric properties at 5 and 10 cm were obtained at five locations throughout the First ISLSCP Field Experiment (FIFE) test site during the 1987 intensive field campaigns (IFCs). An automated vector voltmeter was used to monitor the complex electrical impedance, at 10 MHz, of cylindrical volumes of soil delineated by specially designed soil moisture probes buried at these locations. The objective of this exercise was to test the hypothesis that the soil impedance is sensitive to the moisture content of the soil and that the imaginary part (that is, capacitive reactance) can be used to calculate the volumetric water content of the soil. These measurements were compared with gravimetric samples collected at these locations by the FIFE staff science team.

Ungar, Stephen G.; Layman, Robert; Campbell, Jeffrey E.; Walsh, John; McKim, Harlan J.

1992-11-01

231

Remote sensing of soil moisture with microwave radiometers  

NASA Technical Reports Server (NTRS)

Results are presented that were derived from measurements made by microwave radiometers during the March 1972 and February 1973 flights of National Aeronautics and Space Administration (NASA) Convair-9900 aircraft over agricultural test sites in the southwestern part of United States. The purpose of the missions was to study the use of microwave radiometers for the remote sensing of soil moisture. The microwave radiometers covered the 0.8- to 21-cm wavelength range. The results show a good linear correlation between the observed microwave brightness temperature and moisture content of the 0- to 1-cm layer of the soil. The results at the largest wavelength (21 cm) show the greatest sensitivity to soil moisture variations and indicate the possibility of sensing these variations through a vegetative canopy. The effect of soil texture on the emission from the soil was also studied and it was found that this effect can be compensated for by expressing soil moisture as a percent of field capacity for the soil. The results were compared with calculations based on a radiative transfer model for layered dielectrics and the agreement is very good at the longer wavelengths. At the shorter wavelengths, surface roughness effects are larger and the agreement becomes poorer.

Schmugge, T.; Wilheit, T.; Webster, W., Jr.; Gloerson, P.

1976-01-01

232

An evaluation of the spatial resolution of soil moisture information  

NASA Technical Reports Server (NTRS)

Rainfall-amount patterns in the central regions of the U.S. were assessed. The spatial scales of surface features and their corresponding microwave responses in the mid western U.S. were investigated. The usefulness for U.S. government agencies of soil moisture information at scales of 10 km and 1 km. was ascertained. From an investigation of 494 storms, it was found that the rainfall resulting from the passage of most types of storms produces patterns which can be resolved on a 10 km scale. The land features causing the greatest problem in the sensing of soil moisture over large agricultural areas with a radiometer are bodies of water. Over the mid-western portions of the U.S., water occupies less than 2% of the total area, the consequently, the water bodies will not have a significant impact on the mapping of soil moisture. Over most of the areas, measurements at a 10-km resolution would adequately define the distribution of soil moisture. Crop yield models and hydrological models would give improved results if soil moisture information at scales of 10 km was available.

Hardy, K. R.; Cohen, S. H.; Rogers, L. K.; Burke, H. H. K.; Leupold, R. C.; Smallwood, M. D.

1981-01-01

233

Spatial Estimation of Soil Moisture Using Synthetic Aperture Radar in Alaska  

NASA Astrophysics Data System (ADS)

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

Meade, N. G.; Hinzman, L. D.; Kane, D. L.

1999-01-01

234

Influence of soil moisture and microbial activity on pendimethalin degradation  

Microsoft Academic Search

)-3,4-dimethyl-2,6-dinitroaniline, is a selective pre-emergence herbicide used extensively for control of large variety of grasses and broadleaf weeds in several crops including wheat (Triticum aestivum L.), soybean (Glycin max(L) Marr), peas (Pisum sativum) and various vegetable crops (Sprankle 1974). Persistence of herbicides, in general, is influenced by soil type, soil temperature, soil moisture and cultivation practices. It was observed (Zimdahl

G. Kulshrestha; S. B. Singh

1992-01-01

235

Soil Moisture Extremes Observed by METOP ASCAT: Was 2012 an Exceptional Year?  

NASA Astrophysics Data System (ADS)

In summer 2012 the international press reported widely about the severe drought that had befallen large parts of the United States. Yet, the US drought was only one of several major droughts that occurred in 2012: Southeastern Europe, Central Asia, Brazil, India, Southern Australia and several other regions suffered from similarly dry soil conditions. This raises the question whether 2012 was an exceptionally dry year? In this presentation we will address this question by analyzing global soil moisture patterns as observed by the Advanced Scatterometer (ASCAT) flown on board of the METOP-A satellite. We firstly compare the 2012 ASCAT soil moisture data to all available ASCAT measurements acquired by the instrument since the launch of METOP-A in November 2006. Secondly, we compare the 2012 data to a long-term soil moisture data set derived by merging the ASCAT soil moisture data with other active and passive microwave soil moisture retrievals as described by Liu et al. (2012) and Wagner et al. (2012) (see also http://www.esa-soilmoisture-cci.org/). A first trend analysis of the latter long-term soil moisture data set carried out by Dorigo et al. (2012) has revealed that over the period 1988-2010 significant trends were observed over 27 % of the area covered by the data set, of which 73 % were negative (soil drying) and only 27 % were positive (soil wetting). In this presentation we will show how the inclusion of the years 2011 and 2012 affects the areal extent and strengths of these significant trends. REFERENCES Dorigo, W., R. de Jeu, D. Chung, R. Parinussa, Y. Liu, W. Wagner, D. Fernández-Prieto (2012) Evaluating global trends (1988-2010) in harmonized multi-satellite surface soil moisture, Geophysical Research Letters, 39, L18405, 1-7. Liu, Y.Y., W.A. Dorigo, R.M. Parinussa, R.A.M. de Jeu, W. Wagner, M.F. McCabe, J.P. Evans, A.I.J.M. van Dijk (2012) Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297. Wagner, W., W. Dorigo, R. de Jeu, D. Fernandez, J. Benveniste, E. Haas, M. Ertl (2012) Fusion of active and passive microwave observations to create an Essential Climate Variable data record on soil moisture, ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences (ISPRS Annals), Volume I-7, XXII ISPRS Congress, Melbourne, Australia, 25 August-1 September 2012, 315-321.

Wagner, Wolfgang; Paulik, Christoph; Hahn, Sebastian; Melzer, Thomas; Parinussa, Robert; de Jeu, Richard; Dorigo, Wouter; Chung, Daniel; Enenkel, Markus

2013-04-01

236

NASA Soil Moisture Active Passive (SMAP) Mission Formulation  

NASA Technical Reports Server (NTRS)

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.

Entekhabi, Dara; Njoku, Eni; ONeill, Peggy; Kellogg, Kent; Entin, Jared

2011-01-01

237

Patterns and scaling properties of surface soil moisture in an agricultural landscape: An ecohydrological modeling study  

NASA Astrophysics Data System (ADS)

Soil moisture is a key variable in hydrology, meteorology and agriculture. Soil moisture, and surface soil moisture in particular, is highly variable in space and time. Its spatial and temporal patterns in agricultural landscapes are affected by multiple natural (precipitation, soil, topography, etc.) and agro-economic (soil management, fertilization, etc.) factors, making it difficult to identify unequivocal cause and effect relationships between soil moisture and its driving variables. The goal of this study is to characterize and analyze the spatial and temporal patterns of surface soil moisture (top 20 cm) in an intensively used agricultural landscape (1100 km2 northern part of the Rur catchment, Western Germany) and to determine the dominant factors and underlying processes controlling these patterns. A second goal is to analyze the scaling behavior of surface soil moisture patterns in order to investigate how spatial scale affects spatial patterns. To achieve these goals, a dynamically coupled, process-based and spatially distributed ecohydrological model was used to analyze the key processes as well as their interactions and feedbacks. The model was validated for two growing seasons for the three main crops in the investigation area: Winter wheat, sugar beet, and maize. This yielded RMSE values for surface soil moisture between 1.8 and 7.8 vol.% and average RMSE values for all three crops of 0.27 kg m-2 for total aboveground biomass and 0.93 for green LAI. Large deviations of measured and modeled soil moisture can be explained by a change of the infiltration properties towards the end of the growing season, especially in maize fields. The validated model was used to generate daily surface soil moisture maps, serving as a basis for an autocorrelation analysis of spatial patterns and scale. Outside of the growing season, surface soil moisture patterns at all spatial scales depend mainly upon soil properties. Within the main growing season, larger scale patterns that are induced by soil properties are superimposed by the small scale land use pattern and the resulting small scale variability of evapotranspiration. However, this influence decreases at larger spatial scales. Most precipitation events cause temporarily higher surface soil moisture autocorrelation lengths at all spatial scales for a short time even beyond the autocorrelation lengths induced by soil properties. The relation of daily spatial variance to the spatial scale of the analysis fits a power law scaling function, with negative values of the scaling exponent, indicating a decrease in spatial variability with increasing spatial resolution. High evapotranspiration rates cause an increase in the small scale soil moisture variability, thus leading to large negative values of the scaling exponent. Utilizing a multiple regression analysis, we found that 53% of the variance of the scaling exponent can be explained by a combination of an independent LAI parameter and the antecedent precipitation.

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

2013-08-01

238

Design of a global soil moisture initialization procedure for the simple biosphere model  

NASA Technical Reports Server (NTRS)

Global soil moisture and land-surface evapotranspiration fields are computed using an analysis scheme based on the Simple Biosphere (SiB) soil-vegetation-atmosphere interaction model. The scheme is driven with observed precipitation, and potential evapotranspiration, where the potential evapotranspiration is computed following the surface air temperature-potential evapotranspiration regression of Thomthwaite (1948). The observed surface air temperature is corrected to reflect potential (zero soil moisture stress) conditions by letting the ratio of actual transpiration to potential transpiration be a function of normalized difference vegetation index (NDVI). Soil moisture, evapotranspiration, and runoff data are generated on a daily basis for a 10-year period, January 1979 through December 1988, using observed precipitation gridded at a 4 deg by 5 deg resolution.

Liston, G. E.; Sud, Y. C.; Walker, G. K.

1993-01-01

239

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

SciTech Connect

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

Buckley, R.

2001-06-27

240

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

NASA Astrophysics Data System (ADS)

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

Gonzales, Christopher; Baumgartl, Thomas; Scheuermann, Alexander

2014-05-01

241

Accomplishments of the NASA Johnson Space Center portion of the soil moisture project in fiscal year 1981  

NASA Technical Reports Server (NTRS)

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.

Paris, J. F.; Arya, L. M.; Davidson, S. A.; Hildreth, W. W.; Richter, J. C.; Rosenkranz, W. A.

1982-01-01

242

Soils âField Characterization, Collection, and Laboratory Analysis  

NSDL National Science Digital Library

Field characterization of soil profiles in coniferous and deciduous settings; sample collection of soils from different horizons; laboratory analysis of soil moisture, soil organic carbon (by loss on ignition), and grain size distribution (by sieving)

Biswas, Abir

243

BOREAS HYD-6 Ground Gravimetric Soil Moisture Data  

NASA Technical Reports Server (NTRS)

The Boreal Ecosystem-Atmosphere Study (BOREAS) Hydrology (HYD)-6 team collected several data sets related to the moisture content of soil and overlying humus layers. This data set contains percent soil moisture ground measurements. These data were collected on the ground along the various flight lines flown in the Southern Study Area (SSA) and Northern Study Area (NSA) during 1994 by the gamma ray instrument. The data are available in tabular ASCII files. The HYD-06 ground gravimetric soil moisture data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884).

Carroll, Thomas; Knapp, David E. (Editor); Hall, Forrest G. (Editor); Peck, Eugene L.; Smith, David E. (Technical Monitor)

2000-01-01

244

Results of soil moisture flights during April 1974  

NASA Technical Reports Server (NTRS)

The results presented here are derived from measurements made during the April 5 and 6, 1974 flights of the NASA P-3A aircraft over the Phoenix, Arizona agricultural test site. The purpose of the mission was to study the use of microwave techniques for the remote sensing of soil moisture. These results include infrared (10-to 12 micrometers) 2.8-cm and 21-cm brightness temperatures for approximately 90 bare fields. These brightness temperatures are compared with surface measurements of the soil moisture made at the time of the overflights. These data indicate that the combination of the sum and difference of the vertically and the horizontally polarized brightness temperatures yield information on both the soil moisture and surface roughness conditions.

Schmugge, T. J.; Blanchard, B. J.; Burke, W. J.; Paris, J. F.; Swang, J. R.

1976-01-01

245

Influence of land use on soil moisture spatial-temporal variability and monitoring  

NASA Astrophysics Data System (ADS)

In this study, the influence of land use on soil moisture dynamics is investigated for monitoring purposes. To this end, 23 measurement campaigns were carried out during a period of 8 months at 5 sites located in central Italy, within a catchment of ?6 km2. The sites are characterized by different land uses: grassland, woodland (holm oak and hornbeam) olive grove and cropland. Soil moisture was measured with a portable Time Domain Reflectometer for a layer depth of 15 cm under the soil surface. The optimization of the monitoring scheme was addressed through a statistical and temporal stability analysis. Notwithstanding the significant differences in the land use, the temporal patterns of the field-mean soil moisture of the different sites were very similar while the spatial variability, expressed through the coefficient of variation, was found slightly higher (average value equal to 0.27) than that obtained from previous sampling campaigns on the same area but on sites characterized by a homogeneous soil use. The maximum number of required samples, to estimate the areal mean soil moisture within an accuracy of 2% vol/vol, was found ranging between 7 and 11 at the field scale and equal to 20 at the catchment scale. The temporal stability analysis allowed to identify the grassland site as the most representative of the catchment-mean soil moisture behavior (coefficient of determination, R2 = 0.96). Therefore, even though the heterogeneity of the land use increases the spatial variability (as expected), soil moisture exhibits a significant temporal stability and its large scale monitoring from few observations is still feasible.

Zucco, G.; Brocca, L.; Moramarco, T.; Morbidelli, R.

2014-08-01

246

ESTAR - A synthetic aperture microwave radiometer for measuring soil moisture  

NASA Technical Reports Server (NTRS)

The measurement of soil moisture from space requires putting relatively large microwave antennas in orbit. Aperture synthesis, an interferometric technique for reducing the antenna aperture needed in space, offers the potential for a practical means of meeting these requirements. An aircraft prototype, electronically steered thinned array L-band radiometer (ESTAR), has been built to develop this concept and to demonstrate its suitability for the measurement of soil moisture. Recent flights over the Walnut Gulch Watershed in Arizona show good agreement with ground truth and with measurements with the Pushbroom Microwave Radiometer (PBMR).

Le Vine, D. M.; Griffis, A.; Swift, C. T.; Jackson, T. J.

1992-01-01

247

Implications of complete watershed soil moisture measurements to hydrologic modeling  

NASA Technical Reports Server (NTRS)

A series of six microwave data collection flights for measuring soil moisture were made over a small 7.8 square kilometer watershed in southwestern Minnesota. These flights were made to provide 100 percent coverage of the basin at a 400 m resolution. In addition, three flight lines were flown at preselected areas to provide a sample of data at a higher resolution of 60 m. The low level flights provide considerably more information on soil moisture variability. The results are discussed in terms of reproducibility, spatial variability and temporal variability, and their implications for hydrologic modeling.

Engman, E. T.; Jackson, T. J.; Schmugge, T. J.

1983-01-01

248

Soil moisture effects on the carbon isotope composition of soil respiration  

E-print Network

Soil moisture effects on the carbon isotope composition of soil respiration Claire L. Phillips1 respiration, which suggests indirectly that recently fixed photosynthates comprise a substantial component of substrates consumed by soil respiration. However, there are other reasons why the d13 CO2 of soil efflux may

249

Effect of Soil Moisture on Fumigant Emissions from a Loam Soil  

Technology Transfer Automated Retrieval System (TEKTRAN)

Emissions of soil fumigants must be minimized in order to protect air quality in California. Soil moisture is an important factor that can be managed at a relatively low cost prior to soil fumigation to reduce emissions. A previous study indicated that increasing soil water content up to field capac...

250

Trajectory based detection of forest-change impacts on surface soil moisture at a basin scale [Poyang Lake Basin, China  

NASA Astrophysics Data System (ADS)

Surface soil moisture plays a critical role in hydrological processes, but varies with both natural and anthropogenic influences. Land cover change unavoidably alters surface property and subsequent soil moisture, and its contribution is yet hard to isolate from the mixed influences. In combination with trajectory analysis, this paper proposes a novel approach for detection of forest-change impacts on surface soil moisture variation with an examination over the Poyang Lake Basin, China from 2003 to 2009. Soil moisture in permanent forest trajectory represents a synthetic result of natural influences and serves as a reference for isolating soil moisture alternation due to land cover change at a basin scale. Our results showed that soil moisture decreased in all forest trajectories, while the absolute decrease was lower for permanent forest trajectory (2.53%) than the whole basin (2.61%), afforestation trajectories (2.70%) and deforestation trajectories (2.81%). Moreover, afforestation has a high capacity to hold more soil moisture, but may take more than 6 years to reach its maximum capacity. Soil moisture increased from 14.09% to 14.94% for the afforestation trajectories with tree aging from 1 to 6 years. Finally, land cover change may affect soil moisture alternation toward different transformation directions. Absolute soil moisture decreases by 0.08% for the whole basin, 0.17% for afforestation and 0.28% for deforestation trajectories, accounting for 3.13%, 6.47% and 10.07% of the total decrease in soil moisture. More specifically, the transformation from woody Savannas, cropland and other lands to forest generated absolute soil moisture deceases of 0.20%, -0.08% and 0.27%, accounting for 7.26%, -3.52% and 9.57% of the decreases. On the other hand, the reverse transformation generated soil moisture deceases of 0.29%, 0.21% and 0.35%, accounting for 10.43%, 7.69% and 12.14% of the total decrease. Our findings should be valuable for evaluating the impacts of land cover change on soil moisture alternation and promoting effective management of water resources.

Feng, Huihui; Liu, Yuanbo

2014-06-01

251

De-noising of microwave satellite soil moisture time series  

NASA Astrophysics Data System (ADS)

The use of satellite soil moisture data for scientific and operational hydrologic, meteorological and climatological applications is advancing rapidly due to increasing capability and temporal coverage of current and future missions. However evaluation studies of various existing remotely-sensed soil moisture products from these space-borne microwave sensors, which include AMSR-E (Advanced Microwave Scanning Radiometer) on Aqua satellite, SMOS (Soil Moisture and Ocean Salinity) mission and ASCAT (Advanced Scatterometer) on MetOp-A satellite, found them to be significantly different from in-situ observations, showing large biases and different dynamic ranges and temporal patterns (e.g., Albergel et al., 2012; Su et al., 2012). Moreover they can have different error profiles in terms of bias, variance and correlations and their performance varies with land surface characteristics (Su et al., 2012). These severely impede the effort to use soil moisture retrievals from multiple sensors concurrently in land surface modelling, cross-validation and multi-satellite blending. The issue of systematic errors present in data sets should be addressed prior to renormalisation of the data for blending and data assimilation. Triple collocation estimation technique has successfully yielded realistic error estimates (Scipal et al., 2008), but this method relies on availability of large number of coincident data from multiple independent satellite data sets. In this work, we propose, i) a conceptual framework for distinguishing systematic periodic errors in the form of false spectral resonances from non-systematic errors (stochastic noise) in remotely-sensed soil moisture data in the frequency domain; and ii) the use of digital filters to reduce the variance- and correlation-related errors in satellite data. In this work, we focus on the VUA-NASA (Vrije Universiteit Amsterdam with NASA) AMSR-E, CATDS (Centre National d'Etudes Spatiales, CNES) SMOS and TUWIEN (Vienna University of Technology) ASCAT data sets to identify two types of errors that are spectrally distinct. Based on a semi-empirical model of soil moisture dynamics, we consider possible digital filter designs to improve the accuracy of their soil moisture products by reducing systematic periodic errors and stochastic noise. We describe a methodology to design bandstop filters to remove artificial resonances, and a Wiener filter to remove stochastic white noise present in the satellite data. Utility of these filters is demonstrated by comparing de-noised data against in-situ observations from ground monitoring stations in the Murrumbidgee Catchment (Smith et al., 2012), southeast Australia. Albergel, C., de Rosnay, P., Gruhier, C., Muñoz Sabater, J., Hasenauer, S., Isaksen, L., Kerr, Y. H., & Wagner, W. (2012). Evaluation of remotely sensed and modelled soil moisture products using global ground-based in situ observations. Remote Sensing of Environment, 118, 215-226. Scipal, K., Holmes, T., de Jeu, R., Naeimi, V., & Wagner, W. (2008), A possible solution for the problem of estimating the error structure of global soil moisture data sets. Geophysical Research Letters, 35, L24403. Smith, A. B., Walker, J. P., Western, A. W., Young, R. I., Ellett, K. M., Pipunic, R. C., Grayson, R. B., Siriwardena, L., Chiew, F. H. S., & Richter, H. (2012). The Murrumbidgee soil moisture network data set. Water Resources Research, 48, W07701. Su, C.-H., Ryu, D., Young, R., Western, A. W., & Wagner, W. (2012). Inter-comparison of microwave satellite soil moisture retrievals over Australia. Submitted to Remote Sensing of Environment.

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

2013-04-01

252

Analysis of surface moisture variations within large field sites  

NASA Technical Reports Server (NTRS)

A statistical analysis was made on ground soils to define the general relationship and ranges of values of the field moisture relative to both the variance and coefficient of variation for a given test site and depth increment. The results of the variability study show that: (1) moisture variations within any given large field area are inherent and can either be controlled nor reduced; (2) neither a single value of the standard deviation nor coefficient of variation uniquely define the variability over the complete range of mean field moisture contents examined; and (3) using an upper bound standard deviation parameter clearly defines the maximum range of anticipated moisture variability. 87 percent of all large field moisture content standard deviations were less than 3 percent while about 96 percent of all the computed values had an upper bound of sigma=4 percent for these intensively sampled fields. The limit of accuracy curves of mean soil moisture measurements for large field sites relative to the required number of samples were determined.

Bell, K. R.; Blanchard, B. J.; Witczak, M. W.; Schmugge, T. J.

1979-01-01

253

Evaluation of SMOS soil moisture products over the CanEx-SM10 area  

NASA Astrophysics Data System (ADS)

The Soil Moisture and Ocean Salinity (SMOS) Earth observation satellite was launched in November 2009 to provide global soil moisture and ocean salinity measurements based on L-band passive microwave measurements. Since its launch, different versions of SMOS soil moisture products processors have been developed. The purpose of this study is to evaluate the processor versions 309, 400, 501 and 551 by comparing them to (a) soil moisture measurements from the Canadian Experiment for Soil Moisture in 2010 (CanEx-SM10) and from networks of permanent and temporary stations, and (b) other existing satellite-based soil moisture products (AMSR-E/NSIDC, AMSR-E/VUA, and ASCAT). Rainfall data were used during the analysis in order to understand the episodic variability of soil moisture. The analysis included both agricultural site (Canadian Prairies) and forested site (Boreal Ecosystem Research and Monitoring Sites; BERMS), and considered separately the SMOS ascending and descending modes. An improvement in SMOS soil moisture estimation was observed from the processor versions 309 to 551. We observed a little difference between the processor versions 400, 501, and particularly between the processor versions 501 and 551. These later versions were more correlated to ground measurements than the previous processor versions. For the agricultural site, all the four SMOS processor versions underestimated the soil moisture, but to varying degrees depending on the overpasses mode. For the ascending overpass, the four processor versions have a high bias with respect to the measured ground data (from -0.10 m3/m3 to -0.12 m3/m3). For the descending overpass, however, a good improvement in the algorithms was observed. Thus the maximum bias for the measured ground data went from -0.12 m3/m3 for processor version 309 to -0.02 m3/m3 for processor version 551, and the soil moisture error seems to be less dependent on the absolute soil moisture for the two last versions. Highest correlation coefficients with ground measurements were obtained with SMOS processor version 551 (R ? 0.58), ASCAT (R ? 0.55), and AMSR-E/NSIDC (R ? 0.54) products for ascending overpasses. For descending overpasses AMSR-E/NSIDC (R ? 0.82) is better correlated to ground measurements followed by SMOS (R ? 0.58) and ASCAT (R ? 0.32). However, AMSR-E/VUA appears weakly correlated with ground truth for both overpasses. Despite the good correlation found with ground data, the temporal evolution of AMSR-E/NSIDC data became stable with the vegetation growth and presented a weak sensitivity to rainfall. Over the forested site, SMOS soil moisture estimates were generally overestimated, especially before the active vegetation period where the bias obtained with prototype 551 was greater than 0.10 m3/m3. Moreover, due to the denser and more complex vegetation cover, SMOS data were less correlated with the in situ data than for the Kenaston agricultural site. Soil moisture values from the ascending overpass were closer to the ground measurements (bias ? 0.01m3/m3) than the estimates from the descending overpasses (0.09 ? bias ? 0.11 m3/m3). ASCAT presented correlation coefficients to ground data comparable to those obtained by SMOS (version 551), whereas lower correlation coefficients were obtained with AMSR-E-NSIDC and mainly with AMSR-E/VUA data.

Djamai, Najib; Magagi, Ramata; Goïta, Kalifa; Hosseini, Mehdi; Cosh, Michael H.; Berg, Aaron; Toth, Brenda

2015-01-01

254

Estimating soil moisture in gullies from adjacent upland measurements through different observation operators  

NASA Astrophysics Data System (ADS)

SummarySoil moisture datasets in large gullies are rare due to the difficulty of direct sampling in such landform. This study attempted to estimate spatial soil moisture averages in gullies from measurements of adjacent uplands by using observation operators, based on three-year soil moisture datasets in a gully catchment of the Loess Plateau. Soil moisture datasets in 2010 and 2011 were used for developing observation operators and those in 2012 were used for validation. Several nonlinear and linear methods including cumulative distribution function (CDF) matching method, linear regression (LRG) method, mean relative difference (MRD) method and linear rescaling (LRS) method were used to define observation operators. The results showed observation operators significantly improved the predictions compared to when using spatial averages of uplands as the direct surrogates for gullies. Among different methods, the CDF matching method performed best in estimating soil moisture in gullies followed by the LRG, LRS and MRD methods. Validation analysis showed that the linear observation operators such as LRS, MRD and LRG had better temporal transferability than the nonlinear operators. The MRD observation operators for various layers could successfully transfer in time whereas temporal transferability only succeeds to a limited extent for other observation operators. Furthermore, the MRD, LRG and LRS methods exhibited better vertical transferability than the CDF matching method. However, the transferability of observation operators across the whole root zone layers was not successful.

Gao, X.; Wu, P.; Zhao, X.; Zhou, X.; Zhang, B.; Shi, Y.; Wang, J.

2013-04-01

255

Estimation of groundwater recharge using the soil moisture budget method and the base-flow model  

NASA Astrophysics Data System (ADS)

Estimation of groundwater recharge is extremely important for proper management of groundwater systems. Many different approaches exist for estimating recharge. The main purpose of this paper is to apply a water balance concept with two methods to estimate the groundwater recharge in the Ching-Shui watershed, Taiwan. First, a soil moisture budget method is established to estimate the infiltration, runoff, evapotranspiration, and groundwater recharge in the watershed, where the moisture content of the soil is tracked through time. Both soil-water properties of the unsaturated zone and climatic conditions must be fully considered. Second the base-flow model uses the base-flow separation from the total streamflow discharge to obtain a measure of groundwater recharge so that groundwater evapotranspiration is negligible. In contrast to the soil moisture budget method, base-flow estimation does not require complex hydrogeologic modeling and detailed knowledge of soil characteristics. In a previous study, we suggested that high base-flow is caused by rainstorm events. Using model analysis, depths of recharge estimated by stable-base-flow analysis are adopted to obtain more reasonable groundwater recharge values. The results indicate that assessment of the average annual recharge obtained with a soil moisture budget and the base-flow are very close; the ratio of the two methods is about 95.3%.

Lee, Cheng-Haw; Yeh, Hsin-Fu; Chen, Jin-Fa

2008-06-01

256

Assimilation of streamflow and soil moisture observations in a distributed physically-based hydrological model  

NASA Astrophysics Data System (ADS)

Data assimilation techniques not only enhance model simulations and predictions, they also give the opportunity to pose a diagnostic on both model and observations used in the assimilation process. The goal of this research is to assimilate streamflow and soil moisture in a distributed physically-based hydrological model, CATHY (CATchment HYdrology). The study site is the des Anglais Watershed, a 690-km2 river basin located in southern Québec, Canada. An ensemble Kalman filter was used to assimilate streamflow observations at the basin outlet and at interior locations, as well as soil moisture at different depths (15, 45, and 90 cm) measured with probes (6 stations) and surface soil moisture estimated from radar remote sensing. The use of a Latin hypercube sampling instead of the Monte Carlo method to generate the ensemble reduced the size of ensemble, and therefore the calculation time. An important issue in data assimilation is the estimation of error covariance matrices. Different post-assimilation diagnostics, based on innovations (observation-minus-background), analysis residuals (observation-minus-analysis) and analysis increments (analysis-minus-background) were used to evaluate assimilation optimality. A calibration approach was performed to determine the standard deviation of model parameters, forcing data and observations that lead to optimal assimilations. The analysis of innovations showed a lag between the model prediction and the observation during rainfall events. The assimilation of streamflow observations (outlet or interior locations) corrected this discrepancy. The assimilation of outlet streamflow observations improved the Nash-Sutcliffe efficiencies (NSE) at both outlet and interior point locations. The structure of the state vector used in this study allowed the assimilation of outlet streamflow observations to have an impact over streamflow simulations at interior point locations. Indeed, the state vector contains the outlet streamflow (Qout) and the incoming streamflow (Qin), since both these informations are used by the Muskingum-Cunge surface routing equation in CATHY. However, assimilation of streamflow observations increased systematically the soil moisture values simulated at 15 and 45 cm. The combined assimilation of outlet streamflow and soil moisture improved the NSE of streamflow without degrading the simulation of soil moisture. Moreover, the assimilation of streamflow and soil moisture observations from one station (at 45 cm depth) appeared to have a similar impact on soil moisture simulations compared to a combined assimilation of streamflow and soil moisture observations from five stations. Finally, it was found that the frequency of the assimilation of soil moisture observations has a greater impact on the results than the spatial coverage of the assimilation: assimilation of daily soil moisture measured with probes at six stations gives better results than the assimilation of surface soil moisture estimated from radar remote sensing 8 times over the course of a summer season.

Trudel, M.; Leconte, R.; Paniconi, C.

2012-04-01

257

Moisture Controls on Trace Gas Fluxes in Semiarid Riparian Soils  

Microsoft Academic Search

Variability in seasonal soil moisture (SM) and temperature (T) can alter ecosystem\\/atmosphere exchange of the trace gases carbon di- oxide (CO2), nitrous oxide (N2O), and methane (CH4). This study re- ports the impact of year-round SM status on trace gas fluxes in three semiarid vegetation zones, mesquite (30 g organic C kg 21 soil), open\\/ forb (6 g organic C

Jean E. T. McLain; Dean A. Martens

2006-01-01

258

Influence of soil moisture on C incorporation and preservation in soil  

NASA Astrophysics Data System (ADS)

Sequestration of atmospheric C into soil is only mediated by plant. Plant leaf can use atmospheric C by photosynthesis, thereafter this C is translocated into soil through plant root exudates and root fragments. With changing climatic conditions like decreasing rainfall especially during growing seasons of plants, water availability is thought to raise as limiting factor for plant growth and thus sequestration of C. However, little is known about the pathway of translocation of C from atmosphere to soil at different moisture regimes. To quantify atmospheric C incorporation in plant and its preservation into soil via the rhizosphere, a laboratory experiment on Juncus effusus, which is adapted to very moist conditions, was conducted. The plants were kept at levels of 70 and 100% soil moisture (relative to field capacity, which was adjusted daily to a difference of 30% between high and low moisture levels) for several months. C uptake by plants and translocation towards soil was traced 3, 7, 14 and 21 days after 14CO2 pulse labeling in bulk carbon and lipid fractions of plants and soils. J. effusus produced higher leaf and root biomass at 100% moisture as compared to 70% soil moisture. Consequently, rhizosphere-dry mass increased with increasing root biomass. Considering whole pot (plant & soil together), 14C proportion of shoots decreased and that of roots increased successively from 3 to 21 days after labelling due to translocation of C from shoots to roots. 14C content of rhizosphere was observed to be highest at day 14 after labeling at 100% soil moisture, implied an exceptional increase of root exudates, whereas root exudation was less in 70% soil moisture. As a result of C translocation from roots to soil, 14C content of soil increased until day 7 after labeling. Thereafter, soil 14C content decreased more sharply with time at 100% soil moisture than at 70% moisture. Moreover, to gain quantitative knowledge of 14C preservation, a comparatively recalcitrant C fraction, lipid-14C, was also measured. J. effusus leaf, grown at 70% soil moisture; showed higher percentage of lipid-14C of organic C, probably to protect higher loss of water through respiration. Similarly, rhizosphere and soil lipid-14C content were also high under 70% soil moisture, probably because of lower diffusion of root exudates at 70% soil moisture as compared to that at 100% soil moisture. With these result it can be concluded that incorporation of 14C in soil was high in 100% soil moisture but preservation, of bulk C and in the form of lipid-14C, was higher under 70% than that of 100% soil moisture. This clearly explains commonly lower C contents in dry vs. wet soils, where the latter benefit from improved C incorporation, whereas preservation might be less pronounced.

Majumder, B.; Gocke, M.; Kuzyakov, Y.; Wiesenberg, G.

2012-04-01

259

Modeling and application of soil moisture at varying spatial scales with parameter scaling  

E-print Network

The dissertation focuses on characterization of subpixel variability within a satellite-based remotely sensed coarse-scale soil moisture footprint. The underlying heterogeneity of coarse-scale soil moisture footprint is masked by the area...

Das, Narendra Narayan

2009-05-15

260

Evaluation of SMAP Level 2 Soil Moisture Algorithms Using SMOS Data  

NASA Technical Reports Server (NTRS)

The objectives of the SMAP (Soil Moisture Active Passive) mission are global measurements of soil moisture and land freeze/thaw state at 10 km and 3 km resolution, respectively. SMAP will provide soil moisture with a spatial resolution of 10 km with a 3-day revisit time at an accuracy of 0.04 m3/m3 [1]. In this paper we contribute to the development of the Level 2 soil moisture algorithm that is based on passive microwave observations by exploiting Soil Moisture Ocean Salinity (SMOS) satellite observations and products. SMOS brightness temperatures provide a global real-world, rather than simulated, test input for the SMAP radiometer-only soil moisture algorithm. Output of the potential SMAP algorithms will be compared to both in situ measurements and SMOS soil moisture products. The investigation will result in enhanced SMAP pre-launch algorithms for soil moisture.

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

2011-01-01

261

The Soil Moisture Active and Passive Mission (SMAP): Science and Applications  

E-print Network

The soil moisture active and passive mission (SMAP) will provide global maps of soil moisture content and surface freeze/thaw state. Global measurements of these variables are critical for terrestrial water and carbon cycle ...

Entekhabi, Dara

262

Ground truth report 1975 Phoenix microwave experiment. [Joint Soil Moisture Experiment  

NASA Technical Reports Server (NTRS)

Direct measurements of soil moisture obtained in conjunction with aircraft data flights near Phoenix, Arizona in March, 1975 are summarized. The data were collected for the Joint Soil Moisture Experiment.

Blanchard, B. J.

1975-01-01

263

Fostering applications opportunities for the NASA Soil Moisture Active Passive (SMAP) mission  

E-print Network

The NASA Soil Moisture Active Passive (SMAP) Mission will provide global observations of soil moisture and freeze/thaw state from space. We outline how priority applications contributed to the SMAP mission measurement ...

Moran, M. Susan

264

Evaluation of an agro--ecosystem model using cosmicray neutron soil moisture  

NASA Astrophysics Data System (ADS)

The properties of the land surface affect the interaction of the surface and the atmosphere. The partitioning of absorbed shortwave radiation into emitted radiation, sensible heat flux, latent heat flux, and soil heat flux is determined by the presence of soil moisture. When the land surface is dry, there will be higher sensible heat flux, emitted radiation and soil heat flux. However, when liquid water is present, latent energy will be used to change the phase of water from solid to liquid and liquid to gas. This latent heat flux moves water and energy to a different part of the atmosphere. A contributing factor to soil moisture available for latent heat flux is the water table. With a shallow water table (< 5 m), plant roots are able to extract water for growth and generally an increase in latent heat flux is seen. In the Midwest U.S., the management of fields changes the latent heat flux through different crop choices, planting and harvest date, fertilizer application, and tile drainage. Therefore, land surface models, like Agro--IBIS, need to be simulated and evaluated at the field--scale. Agro--IBIS is an agroecosystem model that is able to incorporate changes in vegetation growth as well as management practices, which in turn impact soil moisture available for latent heat flux. Agro--IBIS has been updated with the soil physics of HYDRUS--1D in order to accurately simulate the impact of the water table. In measuring soil moisture, a consistent challenge is the representative scale of the instrument, which is often a point. A newer method of obtaining soil moisture over the field--scale is using a cosmic--ray neutron detector, which is sensitive to a diameter of 700 m and to a depth of ˜ 20 cm. I used soil moisture observed by the cosmic--ray neutron detector in an agricultural field to evaluate estimates made with the Agro--IBIS model over a growing season of maize and a growing season of soybean. Because of the large area observed by the cosmic-ray neutron detector, a soil texture sensitivity analysis was performed using Agro--IBIS to determine the texture that would produce the best hydraulic properties and therefore the best estimate of soil moisture. The maize year results show Agro--IBIS with silt loam soil texture with a RMSE of 0.037 cm3 cm-33 and bias of -0.02 cm3 cm3 cm--3 and the updated Agro--IBIS (AgroIBIS--VSF) had a RMSE of 0.033 cm3 cm--3 and bias of -0:006 cm3 cm-3 compared to the cosmic--ray neutron soil moisture. In the soybean year, sandy clay loam with Agro--IBIS had a RMSE of 0.028 cm3 cm --3 and bias of -0.014 cm3 cm--3 and AgroIBIS--VSF had a RMSE of 0.028 cm3 cm --3 and bias of 0.023 cm3 cm--3. These low values for RMSE and bias demonstrate that the models are in good agreement with the field--scale observation of soil moisture for the growing season in 2011 (maize) and 2012 (soybean). Adding a water table did not improve AgroIBIS--VSF's accuracy against the observed cosmic--ray neutron soil moisture in the top 20 cm, except with the sandy clay loam soil texture simulations. The original version of Agro--IBIS conserved water to within 1% of total precipitation, but the water balance for AgroIBIS--VSF lost close to 10%. Both the original and new version of Agro--IBIS performed poorly during the 2012 drought year as shown by their inconsistency with observed yield and the change in soil moisture storage, as well as expected LAI and canopy height.

Carr, Benjamin David

265

Soil Moisture Experiments: SMEX02 and SMEX03  

NASA Astrophysics Data System (ADS)

Soil moisture field experiments have been very successful at addressing a broad range of science question, focusing technology development and demonstration, and providing educational experiences for undergraduate and graduate students. The data have been used in studies that went well beyond the algorithm research, primarily due to an emphasis on developing map-based products. For 2002, a soil moisture field experiment (SMEX02will be conducted that will support the science needs of the NASA Terrestrial Hydrology Program Soil Moisture Mission (EX-4a), the NASA Global Water and Energy Cycle Research Program, the EOS Aqua Advanced Microwave Scanning Radiometer (AMSR), and NOAA-DOD prototype land parameter algorithms utilizing data from the Special Sensor Microwave Imager (SSM/I). The objectives of SMEX02 are to understand land-atmosphere interactions, extension of instrument observations and algorithms to a broader range of vegetation conditions, validation of land surface parameters retrieved from SSM/I and potentially AMSR data, and the evaluation of new instrument technologies for soil moisture remote sensing. The combined objectives will be addressed with ground/aircraft/spacecraft observations over sites in Iowa during the summer of 2002. Plans are being developed for intensive studies to validate AMSR in 2003 that will include sites in Oklahoma, Georgia, and Alabama.

Jackson, T. J.

2002-05-01

266

ESTIMATION OF GROUND WATER RECHARGE USING SOIL MOISTURE BALANCE APPROACH  

E-print Network

ESTIMATION OF GROUND WATER RECHARGE USING SOIL MOISTURE BALANCE APPROACH C. P. Kumar* ABSTRACT The amount of water that may be extracted from an aquifer without causing depletion is primarily dependent upon the ground water recharge. Thus, a quantitative evaluation of spatial and temporal distribution

Kumar, C.P.

267

WindSat Global Soil Moisture Retrieval and Validation  

Technology Transfer Automated Retrieval System (TEKTRAN)

A physically based six-channel land algorithm is developed to simultaneously retrieve the global soil moisture, vegetation water content and land surface temperature. The algorithm is based on a maximum-likelihood estimation and uses WindSat passive microwave data at 10, 18.7 and 37 GHz. The global ...

268

Overview of the NASA soil moisture active/passive mission  

Technology Transfer Automated Retrieval System (TEKTRAN)

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...

269

An adaptive ensemble Kalman filter for soil moisture data assimilation  

Technology Transfer Automated Retrieval System (TEKTRAN)

In a 19-year twin experiment for the Red-Arkansas river basin we assimilate synthetic surface soil moisture retrievals into the NASA Catchment land surface model. We demonstrate how poorly specified model and observation error parameters affect the quality of the assimilation products. In particul...

270

A comparison of soil moisture sensors for space flight applications  

NASA Technical Reports Server (NTRS)

Plants will be an important part of future long-term space missions. Automated plant growth systems require accurate and reliable methods of monitoring soil moisture levels. There are a number of different methods to accomplish this task. This study evaluated sensors using the capacitance method (ECH2O), the heat-pulse method (TMAS), and tensiometers, compared to soil water loss measured gravimetrically in a side-by-side test. The experiment monitored evaporative losses from substrate compartments filled with 1- to 2-mm baked calcinated clay media. The ECH2O data correlated well with the gravimetric measurements, but over a limited range of soil moisture. The averaged TMAS sensor data overstated soil moisture content levels. The tensiometer data appeared to track evaporative losses in the 0.5- to 2.5-kPa range of matric potential that corresponds to the water content needed to grow plants. This small range is characteristic of large particle media, and thus high-resolution tensiometers are required to distinguish changing moisture contents in this range.

Norikane, J. H.; Prenger, J. J.; Rouzan-Wheeldon, D. T.; Levine, H. G.

2005-01-01

271

U.S National cropland soil moisture monitoring using SMAP  

Technology Transfer Automated Retrieval System (TEKTRAN)

Crop condition information is critical for public and private sector decision making that concerns agricultural policy, food production, food security, and food commodity prices. Crop conditions change quickly due to various growing condition events, such as temperature extremes, soil moisture defic...

272

Combined Passive Active Soil Moisture Observations During CLASIC  

Technology Transfer Automated Retrieval System (TEKTRAN)

An important issue in advancing higher spatial resolution and better accuracy in soil moisture remote sensing is the integration of active and passive observations. In an effort to address these questions an airborne passive/active L-band system (PALS) was flown as part of CLASIC in Oklahoma over th...

273

Integrating soil moisture and groundwater into climate models  

E-print Network

make droughts longer or bigger, and where? More generally, what is the impact of soil moisture feedback on space and time correlation scales? Potential applications: seasonal drought prediction, impact of land perish after coexisting with humans for millennia? #12;How mammoths could go extinct dNh dt =h Nh1- Nm

Krakauer, Nir Y.

274

Radon diffusion coefficients in soils of varying moisture content  

NASA Astrophysics Data System (ADS)

Radon is a naturally occurring radioactive gas that is generated in the Earth's crust and is free to migrate through soil and be released to the atmosphere. Due to its unique properties, soil gas radon has been established as a powerful tracer used for a variety of purposes, such as exploring uranium ores, locating geothermal resources and hydrocarbon deposits, mapping geological faults, predicting seismic activity or volcanic eruptions and testing atmospheric transport models. Much attention has also been given to the radiological health hazard posed by increased radon concentrations in the living and working environment. In order to exploit radon profiles for geophysical purposes and also to predict its entry indoors, it is necessary to study its transport through soils. Among other factors, the importance of soil moisture in such studies has been largely highlighted and it is widely accepted that any measurement of radon transport parameters should be accompanied by a measurement of the soil moisture content. In principle, validation of transport models in the field is encountered by a large number of uncontrollable and varying parameters; laboratory methods are therefore preferred, allowing for experiments to be conducted under well-specified and uniform conditions. In this work, a laboratory technique has been applied for studying the effect of soil moisture content on radon diffusion. A vertical diffusion chamber was employed, in which radon was produced from a 226Ra source, was allowed to diffuse through a soil column and was finally monitored using a silicon surface barrier detector. By solving the steady-state radon diffusion equation, diffusion coefficients (D) were determined for soil samples of varying moisture content (m), from null (m=0) to saturation (m=1). For dry soil, a D value of 4.1×10-7 m2s-1 was determined, which increased moderately by a factor of ~3 for soil with low moisture content, i.e. up to m ~0.2. At higher water fractions, a decrease in D was initiated and became particularly pronounced approaching complete saturation; at m =0.9, D was as low as 2×10-9 m2s-1. A series of field experiments has also been conducted using alpha-track CR-39 detectors to follow the moisture-dependence of radon diffusion through soil under natural conditions. Diffusion coefficients were determined as a function of surface soil moisture assuming a one-dimensional diffusive radon transport model. Comparison between results obtained by the two methods showed that laboratory studies may provide a good indication of radon diffusion coefficients to be expected in the field. However, values determined in the field were systematically lower than those assessed in the laboratory. This finding could be attributed to soil-dependent parameters, such as differences in pore space geometry between the soil used in laboratory experiments and the undisturbed soil. In the latter case, the higher degree of compaction imposes a more tortuous pathway to soil gas, while at the same time the diffusive gas flux is hindered by local-scale zones of higher bulk density or water content.

Papachristodoulou, C.; Ioannides, K.; Pavlides, S.

2009-04-01

275

[Effects of nitrogen fertilization, soil moisture and soil temperature on soil respiration during summer fallow season].  

PubMed

On the loess plateau, summer fallow season is a hot rainy time with intensive soil microbe activities. To evaluate the response of soil respiration to soil moisture, temperature, and N fertilization during this period is helpful for a deep understanding about the temporal and spatial variability of soil respiration and its impact factors, then a field experiment was conducted in the Changwu State Key Agro-Ecological Experimental Station, Shaanxi, China. The experiment included five N application rates: unfertilized 0 (N0), 45 (N45), 90 (N90), 135(N135), and 180 (N180) kg x hm(-2). The results showed that at the fallow stage, soil respiration rate significantly enhanced from 1.24 to 1.91 micromol x (m2 x s)(-1) and the average of soil respiration during this period [6.20 g x (m2 x d)(-1)] was close to the growing season [6.95 g x (m2 x d)(-1)]. The bivariate model of soil respiration with soil water and soil temperature was better than the single-variable model, but not so well as the three-factor model when explaining the actual changes of soil respiration. Nitrogen fertilization alone accounted for 8% of the variation soil respiration. Unlike the single-variable model, the results could provide crucial information for further research of multiple factors on soil respiration and its simulation. PMID:22295609

Zhang, Fang; Guo, Sheng-Li; Zou, Jun-Liang; Li, Ze; Zhang, Yan-Jun

2011-11-01

276

The COsmic-ray Soil Moisture Observing System (COSMOS): a non-invasive, intermediate scale soil moisture measurement network  

NASA Astrophysics Data System (ADS)

Soil moisture at a horizontal scale of ca. 600 m averaged over depths of 15-70 cm can be inferred from measurements of cosmic-ray neutrons that are generated within air and soil, moderated mainly by hydrogen atoms in the soil, and emitted back to the atmosphere where they are measured. These neutrons are sensitive to water content changes, largely insensitive to soil chemistry, and their intensity is inversely correlated with hydrogen content of the soil. The measurement with a neutron detector placed above the ground takes minutes to hours, permitting high-resolution, long-term monitoring of undisturbed soil moisture. The ability to provide non-invasive, precise, rapid and continuous measurements over a large footprint make the method suitable for calibration and validation (cal/val) of satellite microwave instruments, such as SMOS and SMAP. We envision three types of cal/val activities. In the first, multiple probes would be installed over the satellite microwave footprint to provide average soil moisture continuously. Given the disparity between the microwave footprint (40 km) and the cosmic-ray footprint (0.6 km), this approach would require a large number of probes, and may be too expensive. The second approach would use a smaller number of stationary probes that would be relocated every hour or so, or probes mounted on moving vehicles, to cover a microwave pixel within a short time. This approach would provide snapshots of soil moisture rather than continuous coverage, but would require a small number of probes and be inexpensive. The third approach would utilize the COsmic-ray Soil Moisture Observing System (COSMOS), which comprises initially a network of 50 probes (to provide a proof of concept) and subsequently 500 probes distributed across the contiguous USA. Additional COSMOS probes are also being deployed on an experimental basis in Australia, Europe, and China. SMOS data could be compared with the changing spatio-temporal pattern of continental soil moisture as sampled by initially 50, subsequently 500 COSMOS probes, ultimately providing a continental scale validation mechanism.

Zreda, Marek; Shuttleworth, W. James; Zweck, Chris; Zeng, Xubin; Ferre, Ty

2010-05-01

277

Effects of Soil Moisture on the Temperature Sensitivity of Soil Heterotrophic Respiration: A Laboratory Incubation Study  

PubMed Central

The temperature sensitivity (Q10) of soil heterotrophic respiration (Rh) is an important ecological model parameter and may vary with temperature and moisture. While Q10 generally decreases with increasing temperature, the moisture effects on Q10 have been controversial. To address this, we conducted a 90-day laboratory incubation experiment using a subtropical forest soil with a full factorial combination of five moisture levels (20%, 40%, 60%, 80%, and 100% water holding capacity - WHC) and five temperature levels (10, 17, 24, 31, and 38°C). Under each moisture treatment, Rh was measured several times for each temperature treatment to derive Q10 based on the exponential relationships between Rh and temperature. Microbial biomass carbon (MBC), microbial community structure and soil nutrients were also measured several times to detect their potential contributions to the moisture-induced Q10 variation. We found that Q10 was significantly lower at lower moisture levels (60%, 40% and 20% WHC) than at higher moisture level (80% WHC) during the early stage of the incubation, but became significantly higher at 20%WHC than at 60% WHC and not significantly different from the other three moisture levels during the late stage of incubation. In contrast, soil Rh had the highest value at 60% WHC and the lowest at 20% WHC throughout the whole incubation period. Variations of Q10 were significantly associated with MBC during the early stages of incubation, but with the fungi-to-bacteria ratio during the later stages, suggesting that changes in microbial biomass and community structure are related to the moisture-induced Q10 changes. This study implies that global warming’s impacts on soil CO2 emission may depend upon soil moisture conditions. With the same temperature rise, wetter soils may emit more CO2 into the atmosphere via heterotrophic respiration. PMID:24647610

Zhou, Weiping; Hui, Dafeng; Shen, Weijun

2014-01-01

278

Soil microbial community responses to antibiotic-contaminated manure under different soil moisture regimes.  

PubMed

Sulfadiazine (SDZ) is an antibiotic frequently administered to livestock, and it alters microbial communities when entering soils with animal manure, but understanding the interactions of these effects to the prevailing climatic regime has eluded researchers. A climatic factor that strongly controls microbial activity is soil moisture. Here, we hypothesized that the effects of SDZ on soil microbial communities will be modulated depending on the soil moisture conditions. To test this hypothesis, we performed a 49-day fully controlled climate chamber pot experiments with soil grown with Dactylis glomerata (L.). Manure-amended pots without or with SDZ contamination were incubated under a dynamic moisture regime (DMR) with repeated drying and rewetting changes of >20 % maximum water holding capacity (WHCmax) in comparison to a control moisture regime (CMR) at an average soil moisture of 38 % WHCmax. We then monitored changes in SDZ concentration as well as in the phenotypic phospholipid fatty acid and genotypic 16S rRNA gene fragment patterns of the microbial community after 7, 20, 27, 34, and 49 days of incubation. The results showed that strongly changing water supply made SDZ accessible to mild extraction in the short term. As a result, and despite rather small SDZ effects on community structures, the PLFA-derived microbial biomass was suppressed in the SDZ-contaminated DMR soils relative to the CMR ones, indicating that dynamic moisture changes accelerate the susceptibility of the soil microbial community to antibiotics. PMID:24743980

Reichel, Rüdiger; Radl, Viviane; Rosendahl, Ingrid; Albert, Andreas; Amelung, Wulf; Schloter, Michael; Thiele-Bruhn, Sören

2014-07-01

279

Assessing the SMOS Soil Moisture Retrieval Parameters With High-Resolution NAFE'06 Data  

Microsoft Academic Search

The spatial and temporal invariance of Soil Moisture and Ocean Salinity (SMOS) forward model parameters for soil moisture retrieval was assessed at 1-km resolution on a diurnal basis with data from the National Airborne Field Experiment 2006. The approach used was to apply the SMOS default parameters uniformly over 27 1-km validation pixels, retrieve soil moisture from the airborne observations,

Olivier Merlin; Jeffrey Phillip Walker; Rocco Panciera; Maria JosÉ Escorihuela; Thomas J. Jackson

2009-01-01

280

Validation of the ASAR Global Monitoring Mode Soil Moisture Product Using the NAFE'05 Data Set  

Microsoft Academic Search

The Advanced Synthetic Aperture Radar (ASAR) Global Monitoring (GM) mode offers an opportunity for global soil moisture (SM) monitoring at much finer spatial resolution than that provided by the currently operational Advanced Microwave Scanning Radiometer for the Earth Observing System and future planned missions such as Soil Moisture and Ocean Salinity and Soil Moisture Active Passive. Considering the difficulties in

Iliana Mladenova; Venkat Lakshmi; Jeffrey P. Walker; Rocco Panciera; Wolfgang Wagner; Marcela Doubkova

2010-01-01

281

Calibration and validation of the soil moisture active passive mission with USDA-ARS experimental watersheds  

Technology Transfer Automated Retrieval System (TEKTRAN)

The Soil Moisture Active Passive Mission (SMAP) is a new NASA mission scheduled for 2014 that will provide a number of soil moisture and freeze/thaw products. The soil moisture products will span spatial resolutions from 3 to 36 km. Key to the validation and calibration of the satellite products are...

282

INTERACTIONS BETWEEN SOIL MOISTURE CONTENT AND PHOSPHORUS SUPPLY IN SPRING WHEAT PLANTS GROWN IN POT CULTURE  

Microsoft Academic Search

A pot culture experiment was carried out in a glasshouse to investigate the interactions between soil moisture content and phosphorus (P) supply in spring wheat (Triticum aestivum cv. Krichauff). Increases in soil moisture content and P supply significantly increased plant biomass production. Plant P uptake was also significantly enhanced by increases in soil moisture content and P supply. With no

Y. Q. He; Y. G. Zhu; S. E. Smith; F. A. Smith

2002-01-01

283

Canadian experiment for soil moisture in 2010 (CanEx-SM10): Overview and preliminary results  

Technology Transfer Automated Retrieval System (TEKTRAN)

The Canadian Experiment for Soil Moisture in 2010 (CanEx-SM10) was carried out in Saskatchewan, Canada from 31 May to 16 June, 2010. Its main objective was to contribute to the Soil Moisture and Ocean Salinity (SMOS) mission validation and the pre-launch assessment of the proposed Soil Moisture and ...

284

Calibration and validation of the COSMOS rover for surface soil moisture  

Technology Transfer Automated Retrieval System (TEKTRAN)

The mobile COsmic-ray Soil Moisture Observing System (COSMOS) rover may be useful for validating satellite-based estimates of near surface soil moisture, but the accuracy with which the rover can measure 0-5 cm soil moisture has not been previously determined. Our objectives were to calibrate and va...

285

Soil moisture estimation using WindSat based passive microwave polarimetric observations  

Technology Transfer Automated Retrieval System (TEKTRAN)

Global soil moisture estimates are critical to study its role in weather and climate. Microwave remote sensing is the most feasible technique for large-scale soil moisture observations. Efforts have been made towards the goal of obtaining accurate satellite-based soil moisture products. Low frequenc...

286

Evaluation of the SMAP radiometer lever 2 pre-launch soil moisture algorithms using SMOS data  

Technology Transfer Automated Retrieval System (TEKTRAN)

The objectives of the upcoming SMAP (Soil Moisture Active Passive) satellite mission include global measurements of soil moisture at 40 km, 10 km and 3 km resolutions with a 3-day revisit time at an accuracy of 0.04 m3/m3. The 40 km resolution soil moisture product is based primarily on the passiv...

287

A Soil Moisture–Rainfall Feedback Mechanism: 1. Theory and observations  

Microsoft Academic Search

This paper presents a hypothesis regarding the fundamental role of soil moisture conditions in land-atmosphere interactions. We propose that wet soil moisture conditions over any large region should be associated with relatively large boundary layer moist static energy, which favors the occurrence of more rainfall. Since soil moisture conditions themselves reflect past occurrence of rainfall, the proposed hypothesis implies a

Elfatih A. B. Eltahir

1998-01-01

288

Assimilating Remote Sensing based Soil Moisture in an Ecosystem Model (BEPS) for Agricultural Drought Assessment  

Microsoft Academic Search

Process-based terrestrial ecosystem models inevitably need model initialization and parameters specification. In this study, remotely sensed surface soil moisture derived from near infrared and shortwave infrared bands was assimilated in BEPS (Boreal Ecosystem Production Simulator) to initialize soil moisture in BEPS and fine-tune BEPS key parameters which are closely related to soil moisture estimation including maximum stomotal conductance, leaf area

Lin Zhu; Jing M. Chen; Qiming Qin; Mei Huang; Lianxi Wang; Jianping Li; Bao Cao

2008-01-01

289

Using ERS-2 and ALOS PALSAR images for soil moisture and inundation mapping in Cyprus  

NASA Astrophysics Data System (ADS)

Floods are among the most frequent and costly natural disasters in terms of human and economic loss and are considered to be a weather-related natural disaster. This study strives to highlight the potential of active remote sensing imagery in flood inundation monitoring and mapping in a catchment area in Cyprus (Yialias river). GeoEye-1 and ASTER images were employed to create updated Land use /Land cover maps of the study area. Following, the application of fully polarimetric (ALOS PALSAR) and dual polarimetric (ERS - 2) Synthetic Aperture Radar (SAR) data for soil moisture and inundation mapping is presented. For this purpose 2 ALOS PALSAR images and 3 ERS-2 images were acquired. This study offers an integrated methodology by the use of multi-angle radar images to estimate roughness and soil moisture without the use of ancillary field data such as field measurements. The relationship between soil moisture and backscattering coefficient was thoroughly studied and linear regression models were developed to predict future flood inundation events. Multi-temporal FCC images, classification, image fusion, moisture indices, texture and PCA analysis were employed to assist soil moisture mapping. Certain land cover classes were characterized as flood prone areas according to statistics of their signal response. The results will be incorporated in an integrated flood risk assessment model of Yialias catchment area.

Alexakis, Dimitrios D.; Agapiou, Athos; Themistocleous, Kyriacos; Retalis, Adrianos; Hadjimitsis, Diofantos G.

2013-08-01

290

Characteristics of soil moisture in permafrost observed in East Siberian taiga with stable isotopes of water  

Microsoft Academic Search

Soil moisture and its isotopic composition were observed at Spasskaya Pad experimental forest near Yakutsk, Russia, during summer in 1998, 1999, and 2000. The amount of soil water (plus ice) was estimated from volumetric soil water content obtained with time domain reflectometry. Soil moisture and its 18O showed large interannual variation depending on the amount of summer rainfall. The soil

A. Sugimoto; D. Naito; N. Yanagisawa; K. Ichiyanagi; N. Kurita; J. Kubota; T. Kotake; T. Ohata; T. C. Maximov; A. N. Fedorov

2003-01-01

291

Satellite microwave observations of soil moisture variations. [by the microwave radiometer on the Nimbus 5 satellite  

NASA Technical Reports Server (NTRS)

The electrically scanning microwave radiometer (ESMR) on the Nimbus 5 satellite was used to observe microwave emissions from vegetated and soil surfaces over an Illinois-Indiana study area, the Mississippi Valley, and the Great Salt Lake Desert in Utah. Analysis of microwave brightness temperatures (T sub B) and antecedent rainfall over these areas provided a way to monitor variations of near-surface soil moisture. Because vegetation absorbs microwave emission from the soil at the 1.55 cm wavelength of ESMR, relative soil moisture measurements can only be obtained over bare or sparsely vegetated soil. In general T sub B increased during rainfree periods as evaporation of water and drying of the surface soil occurs, and drops in T sub B are experienced after significant rainfall events wet the soil. Microwave observations from space are limited to coarse resolutions (10-25 km), but it may be possible in regions with sparse vegetation cover to estimate soil moisture conditions on a watershed or agricultural district basis, particularly since daily observations can be obtained.

Schmugge, T. J.; Rango, A.; Neff, R.

1975-01-01

292

Identification of optimal soil hydraulic functions and parameters for predicting soil moisture  

EPA Science Inventory

We examined the accuracy of several commonly used soil hydraulic functions and associated parameters for predicting observed soil moisture data. We used six combined methods formed by three commonly used soil hydraulic functions ? i.e., Brooks and Corey (1964) (BC), Campbell (19...

293

SOIL MOISTURE NEUTRON PROBE CALIBRATION AND USE IN FIVE SOILS OF UZBEKISTAN  

Technology Transfer Automated Retrieval System (TEKTRAN)

The soil moisture neutron probe (SMNP) is a key tool in measurements of crop water use, necessary for accurate irrigation and minimization of salinization; but it is not useful in all soils. We showed that the SMNP could be accurately field calibrated at five locations in Uzbekistan, in soils rangin...

294

Can SMAP radar observations be used to determine vegetation moisture status and root zone soil moisture?  

NASA Astrophysics Data System (ADS)

Recently, large differences in backscatter between the ascending (evening) and descending (morning) tracks of the wind scatterometer onboard the ERS-1 and ERS-2 satellites have been identified in times and locations of vegetation water stress. This suggests that vegetation might be considered as a source of information rather than a barrier to soil moisture retrieval. The goal here is to develop a quantitative relationship between the magnitude of the diurnal variation in backscatter and the vegetation water status. In turn, this will lead to information on the availability of water in the root zone. Diurnal variation in the backscatter response of vegetation was identified as early as the 1970s and was first observed from space in Seasat-1 scatterometer data in 1982. Subsequent field and laboratory experiments, primarily those of Ulaby and McDonald, have demonstrated that the variation is largely driven by changes in the dielectric properties of vegetation, which in turn depend on vegetation moisture content, sap chemistry and temperature. The magnitude of the diurnal variation in dielectric constant varies considerably within the vegetation itself. Furthermore, the contribution of individual vegetation components to backscatter depends on polarization and frequency. A combination of microwave theory and a numerical study will be used to argue that the morning and evening passes of the L-band radar on the SMAP satellite could be combined to yield information on vegetation water stress and root zone soil moisture. An innovative data assimilation strategy will be presented that could be used to merge the SMAP radar observations with a microwave backscatter model and a resistance-capacitance model to estimate vegetation moisture status and infer root zone soil moisture.

Steele-Dunne, S. C.; Friesen, J.; van de Giesen, N.

2010-12-01

295

Is the PDO or AMO the climate driver of soil moisture in the Salmon River Basin, Idaho?  

NASA Astrophysics Data System (ADS)

Current droughts and increasing water demands are straining water resources in the Salmon River Basin (SRB) and are anticipated to continue in the future. As a robust drought indictor, soil moisture plays an important role in characterizing prolonged droughts. The current study investigates the impacts of two oceanic-atmospheric patterns, i.e. the Pacific Decadal Oscillation (PDO) and the Atlantic Multidecadal Oscillation (AMO), on soil moisture and identify the most complete driver (PDO/AMO) of soil moisture in the SRB. Using wavelet analysis tools, we found that: 1) soil moisture in both Stanley station (a snow-dominated region) and White Bird station (a rain-dominated region) in the SRB are linked to the variations of the PDO and AMO; 2) both the PDO and AMO have less significant impacts on soil moisture in Stanley station; and 3) the PDO produces, with respect to AMO, a stronger correlation with soil moisture in the SRB. Given the importance of the soil moisture to the drought, the results could allow an estimation of drought availability under forecasted oceanic-atmospheric patterns, which will provide useful information for water resources management in the SRB.

Tang, Chunling; Chen, Dong; Crosby, Benjamin T.; Piechota, Thomas C.; Wheaton, Joseph M.

2014-09-01

296

Evaluation of SMOS L2 soil moisture data over the Eastern Poland using ground measurements  

NASA Astrophysics Data System (ADS)

Validation of SMOS products is vital for their further use in the study of climate and hydrology. Several authors [1,2] have recently evaluated SMOS soil moisture data with an aid of in-situ observations of soil moisture. Collow and Robock have reported a dry bias as compared to in situ observations. Since their results are not much conclusive, they call for further studies using more data. Bircher and co-authors have also noted significant discrepancies between Danish network and SMOS soil moisture. SWEX_POLAND soil moisture network consists of 9 stations located in Eastern Poland. These stations are located on the areas representing variety types of land use: meadows, cultivated fields, wetlands and forests. We have expanded our analysis, as presented in the EGU 2012, using data from all network stations. Similarly as before, we have used three methods in our comparison studies: the Bland-Altman method, concordance correlation coefficient and total deviation index. Using these methods we have confirmed a fair/moderate agreement of SMOS L2 SM data and network observations. Like the other authors we have also noted the significant biases in SMOS soil moisture. However, the general trends in dynamics of soil moisture revealed by SMOS, the SWEX_POLAND network and referred to GLDAS, are in a considerable relevancy. We have shown that the SMOS satellite measurements are reliable, so can be used to detect areas of dry and moist soil. In Poland the trends indicating the growth of agricultural droughts are depicted by SMOS L2 very well, even better than national drought services for the agriculture. It is worth to note that the year 2011 was more variable and drier than the 2010 for Poland. Moreover, SMOS data prove the well-known property of central Poland to be drier than the rest of the country. It is expected that further mitigation of RFI contamination in Poland will be available due to the cooperation of ESA SMOS to the national spectrum control services (UKE). Therefore, we confirm that SMOS is a very valuable source of data, which is going to be used on regional studies related to the climate in Poland. 1. Collow, T.W., A. Robock, J. B. Basara, and B. G. Illston (2012), Evaluation of SMOS retrievals of soil moisture over the central United States with currently available in situ observations, J. Geophys. Res., 117, D09113, doi:10.1029/2011JD017095. 2. Bircher, S., Skou, N., Jensen, K. H.,. Walker, J. P and Rasmussen L. (2012), A soil moisture and temperature network for SMOS validation in Western Denmark, Hydrol. Earth Syst. Sci., 16, 1445-1463, doi:10.5194/hess-16-1445-2012

Usowicz, Jerzy; ?ukowski, Mateusz; S?omi?ski, Jan; Stankiewicz, Krystyna; Usowicz, Bogus?aw; Lipiec, Jerzy; Marczewski, Wojciech

2013-04-01

297

Sensitivity of soil organic matter decomposition to simultaneous changes in temperature and moisture  

NASA Astrophysics Data System (ADS)

Soil organic matter decomposition depends on multiple factors that are being altered simultaneously as a result of global environmental change. For this reason it is important to study the overall sensitivity of soil organic matter decomposition with respect to multiple and interacting drivers. Here we present an analysis of the potential response of decomposition rates to simultaneous changes in temperature and moisture. To address this problem, we first present a theoretical framework to study the sensitivity of soil organic matter decomposition when multiple driving factors change simultaneously. We then apply this framework to models and data at different levels of abstraction: 1) to a mechanistic model that addresses the limitation of enzyme activity by simultaneous effects of temperature and soil water content, the latter controlling substrate supply and oxygen concentration for microbial activity; 2) to different mathematical functions used to represent temperature and moisture effects on decomposition in biogeochemical models. To contrast model predictions at these two levels of organization, we compiled different datasets of observed responses in field and laboratory studies. Then we applied our conceptual framework to: 3) observations of soil respiration at the ecosystem level; 4) laboratory experiments looking at the response of heterotrophic respiration to independent changes in moisture and temperature; and 5) ecosystem-level experiments manipulating soil temperature and water content simultaneously. The combined theoretical and empirical evidence reviewed suggests: first, large uncertainties still remain regarding the combined controls of temperature and moisture on decomposition rates, particularly at high temperatures and the extremes of the soil moisture range; second, the highest sensitivities of decomposition rates are likely in systems where temperature and moisture are high such as tropical peatlands, and at temperatures near the freezing point of water such as in soils under freeze-thaw cycles. These regions also exhibit the largest differences in projected changes in decomposition rates among different models. Third, the lowest sensitivity of decomposition rates to changes in temperature and moisture is expected in soils with temperatures well below the freezing point. Uncertainty in models can be reduced if some of the functions representing the effects of temperature and moisture on decomposition can be discredited based on empirical observations or experiments.

Sierra, Carlos; Trumbore, Susan; Davidson, Eric; Vicca, Sara; Janssens, Ivan

2014-05-01

298

Soil moisture-temperature feedbacks at meso-scale during summer heat waves over Western Europe  

NASA Astrophysics Data System (ADS)

This paper investigates the impact of soil moisture-temperature feedback during heatwaves occurring over France between 1989 and 2008. Two simulations of the weather research and forecasting regional model have been analysed, with two different land-surface models. One resolves the hydrology and is able to simulate summer dryness, while the other prescribes constant and high soil moisture and hence no soil moisture deficit. The sensitivity analysis conducted for all heatwave episodes highlights different soil moisture-temperature responses (1) over low-elevation plains, (2) over mountains and (3) over coastal regions. In the plains, soil moisture deficit induces less evapotranspiration and higher sensible heat flux. This has the effect of heating the planetary boundary layer and at the same time of creating a general condition of higher convective instability and a slight increase of shallow cloud cover. A positive feedback is created which increases the temperature anomaly during the heatwaves. In mountainous regions, enhanced heat fluxes over dry soil reinforce upslope winds producing strong vertical motion over the mountain slope, first triggered by thermal convection. This, jointly to the instability conditions, favors convection triggering and produces clouds and precipitation over the mountains, reducing the temperature anomaly. In coastal regions, dry soil enhances land/sea thermal contrast, strengthening sea-breeze circulation and moist cold marine air advection. This damps the magnitude of the heatwave temperature anomaly in coastal areas, expecially near the Mediterranean coast. Hence, along with heating in the plains, soil dryness can also have a significant cooling effect over mountains and coastal regions due to meso-scale circulations.

Stéfanon, Marc; Drobinski, Philippe; D'Andrea, Fabio; Lebeaupin-Brossier, Cindy; Bastin, Sophie

2014-03-01

299

Assimilation of SMOS soil moisture data and incorporation to the HL Research Distributed Hydrologic Model (HL-RDHM)  

NASA Astrophysics Data System (ADS)

Soil moisture is often derived from models and agencies such as the National Oceanic and Atmospheric Administration's National Weather Service (NOAA/NWS) use proxy estimates of soil moisture at the surface in order support operational flood forecasting. In particular, a daily national map of Flash Flood Guidance (FFG) is produced that is based on surface soil moisture deficit and threshold runoff estimates. Flash flood warnings are issued by Weather Forecast Offices (WFOs) and are underpinned by information from the Flash Flood Guidance (FFG) system operated by the River Forecast Centers (RFCs). The current FFG system at the ABRFC provides gridded flash flood guidance (GFFG) System using the NWS Hydrology Laboratory-Research Distributed Hydrologic Model (HL-RDHM) to translate the upper zone soil moisture to estimates of Soil Conservation Service Curve Numbers. The remote sensing observations of soil moisture can improve the flood forecasting accuracy. The Soil Moisture Active and Passive (SMAP) and Soil Moisture and Ocean Salinity (SMOS) satellites are two potential sources of remotely sensed soil moisture data. SMOS measures the microwave radiation emitted from the Earth's surface operating at L-band (1.20-1.41 GHz) to measure surface soil moisture directly. Microwave radiation at this wavelength offers relatively deeper penetration and has lower sensitivity to vegetation impacts. The main objective of this research is to evaluate the contribution of remote sensing technology to quantifiable improvements in flash flood applications as well as adding a remote sensing component to the NWS FFG Algorithm. The challenge of this study is employing the direct soil moisture data from SMOS to replace the model-calculated soil moisture state which is based on the soil water balance in 4 km x 4 km Hydrologic Rainfall Analysis Project (HRAP) grid cells. The resolutions differences in spatial, vertical and temporal between SMOS data and the model needs involve with data assimilation and scale adjustment. This study will show the techniques of SMOS soil moisture data assimilation using physical parameters in four dimensions to be ingested by HL-RDHM.

Seo, D.; Khanbilvardi, R.; Lakhankar, T.; Cosgrove, B.

2013-12-01

300

Zinc movement in sewage-sludge-treated soils as influenced by soil properties, irrigation water quality, and soil moisture level  

USGS Publications Warehouse

A soil column study was conducted to assess the movement of Zn in sewage-sludge-amended soils. Varables investigated were soil properties, irrigation water quality, and soil moisture level. Bulk samples of the surface layer of six soil series were packed into columns, 10.2 cm in diameter and 110 cm in length. An anaerobically digested municipal sewage sludge was incorporated into the top 20 cm of each column at a rate of 300 mg ha-1. The columns were maintained at moisture levels of saturation and unsaturation and were leached with two waters of different quality. At the termination of leaching, the columns were cut open and the soil was sectioned and analyzed. Zinc movement was evaluated by mass balance accounting and correlation and regression analysis. Zinc movement in the unsaturated columns ranged from 3 to 30 cm, with a mean of 10 cm. The difference in irrigation water quality did not have an effect on Zn movement. Most of the Zn applied to the unsaturated columns remained in the sludge-amended soil layer (96.1 to 99.6%, with a mean of 98.1%). The major portion of Zn leached from the sludge-amended soil layer accumulated in the 0- to 3-cm depth (35.7 to 100%, with a mean of 73.6%). The mean final soil pH values decreased in the order: saturated columns = sludge-amended soil layer > untreated soils > unsaturated columns. Total Zn leached from the sludge-amended soil layer was correlated negatively at P = 0.001 with final pH (r = -0.85). Depth of Zn movement was correlated negatively at P = 0.001 with final pH (r = -0.91). Multiple linear regression analysis showed that the final pH accounted for 72% of the variation in the total amounts of Zn leached from the sludge-amended soil layer of the unsaturated columns and accounted for 82% of the variation in the depth of Zn movement among the unsaturated columns. A significant correlation was not found between Zn and organic carbon in soil solutions, but a negative correlation significant at P = 0.001 was found between pH and Zn (r = -0.61).

Welch, J.E.; Lund, L.J.

1989-01-01

301

Soil moisture surpasses elevated CO2 and temperature as a control on soil carbon dynamics in a multi-factor climate change experiment  

SciTech Connect

Some single-factor experiments suggest that elevated CO2 concentrations can increase soil carbon, but few experiments have examined the effects of interacting environmental factors on soil carbon dynamics. We undertook studies of soil carbon and nitrogen in a multi-factor (CO2 x temperature x soil moisture) climate change experiment on a constructed old-field ecosystem. After four growing seasons, elevated CO2 had no measurable effect on carbon and nitrogen concentrations in whole soil, particulate organic matter (POM), and mineral-associated organic matter (MOM). Analysis of stable carbon isotopes, under elevated CO2, indicated between 14 and 19% new soil carbon under two different watering treatments with as much as 48% new carbon in POM. Despite significant belowground inputs of new organic matter, soil carbon concentrations and stocks in POM declined over four years under soil moisture conditions that corresponded to prevailing precipitation inputs (1,300 mm yr-1). Changes over time in soil carbon and nitrogen under a drought treatment (approximately 20% lower soil water content) were not statistically significant. Reduced soil moisture lowered soil CO2 efflux and slowed soil carbon cycling in the POM pool. In this experiment, soil moisture (produced by different watering treatments) was more important than elevated CO2 and temperature as a control on soil carbon dynamics.

Garten Jr, Charles T [ORNL; Classen, Aimee T [ORNL; Norby, Richard J [ORNL

2009-01-01

302

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

PubMed

Water application is a low-cost strategy to control emissions of soil fumigant to meet the requirements of the stringent environmental regulations and it is applicable for a wide range of commodity groups. Although it is known that an increase in soil moisture reduces emissions, the range of soil moisture for minimizing emissions without risking pest control, is not well defined for various types of soils. With two column studies, we determined the effect of different soil moisture levels on emission and distribution of 1,3-dichloropropene and chloropicrin in three different textured soils. Results on sandy loam and loam soils showed that by increasing soil moisture from 30% to 100% of field capacity (FC), peak fluxes were lowered by 77-88% and their occurrences were delayed 5-15 h, and cumulative emissions were reduced 24-49%. For the sandy soil, neither peak fluxes nor the cumulative emissions were significantly different when soil moisture increased from 30% to 100% FC. Compared to the drier soils, the wetter soils retained consistently higher fumigant concentrations in the gas-phase, suggesting efficacy may not be impacted in these soils. The air-filled porosity positively and linearly correlated with the cumulative emission loss across all soil types indicating that it may serve as a good indicator for estimating emissions. These laboratory findings can be further tested under field conditions to conclude what irrigation regime should be used for increasing soil water content before fumigant application that can achieve maximum emission reduction and uniform fumigant distribution with high exposure index values. PMID:23137872

Qin, Ruijun; Gao, Suduan; Ajwa, Husein

2013-01-01

303

The GLOBE Soil Moisture Project's examination of a low-technology method for measuring gravimetric soil moisture  

NASA Astrophysics Data System (ADS)

GLOBE (see http://www.globe.org) is an NSF-funded effort that supports a worldwide hands-on, primary and secondary school-based science and education program. The GLOBE Soil Moisture Project (see http://www.hwr.arizona.edu/globe/sci/SM/SMC/) is a subset of the overall Program, and aims to mobilize GLOBE-participating students worldwide to collect near-surface (i.e. 0-5 cm and 10 cm below ground surface) gravimetric soil moisture data twice a year. The selected annual target dates are during World Space Week/U.S Earth Science Week (early October) and Earth Day Week (mid-April). In order to include schools with limited resources, the authors are examining the reliability of a low-technology method of measuring soil moisture, namely, the "light-bulb" method of drying soil samples. The device uses the heat from a low-wattage light bulb under an inverted, insulated container under which soil samples are placed to dry. Results from preliminary testing of the light-bulb device will be compared with results from samples dries in a traditional 105 C convection oven. A method will be proposed for using the light bulb device to yield results comparable to those of the standard gravimetric methods that use convection or microwave ovens.

Whitaker, M. P. L.; Ferre, T. P. A.; Nijssen, B.; Washburne, J.

2003-04-01

304

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

NASA Astrophysics Data System (ADS)

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

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

2012-04-01

305

Soil moisture estimation by airborne active and passive microwave remote sensing: A test-bed for SMAP fusion algorithms  

NASA Astrophysics Data System (ADS)

The objective of the NASA Soil Moisture Active & Passive (SMAP) mission is to provide global measurements of soil moisture and its freeze/thaw state. The SMAP launch is currently planned for 2014-2015. The SMAP measurement approach is to integrate L-band radar and L-band radiometer as a single observation system combining the respective strengths of active and passive remote sensing for enhanced soil moisture mapping. The radar and radiometer measurements can be effectively combined to derive soil moisture maps that approach the accuracy of radiometer-only retrievals, but with a higher resolution (being able to approach the radar resolution under some conditions). Aircraft and tower-based instruments will be a key part of the SMAP validation program. Here, we present an airborne campaign in the Rur catchment in Germany, in which the passive L-band system Polarimetric L-band Multi-beam Radiometer (PLMR2) and the active L-band system DLR F-SAR were flown on six dates in 2013. The flights covered the full heterogeneity of the area under investigation, i.e. all types of land cover and experimental monitoring sites. These data are used as a test-bed for the analysis of existing and development of new active-passive fusion techniques. A synergistic use of the two signals can help to decouple soil moisture effects from the effects of vegetation (or roughness) in a better way than in the case of a single instrument. In this study, we present and evaluate three approaches for the fusion of active and passive microwave records for an enhanced representation of the soil moisture status: i) estimation of soil moisture by passive sensor data and subsequent disaggregation by active sensor backscatter data, ii) disaggregation of passive microwave brightness temperature by active microwave backscatter and subsequent inversion to soil moisture, and iii) fusion of two single-source soil moisture products from radar and radiometer.

Montzka, Carsten; Bogena, Heye; Jagdhuber, Thomas; Hajnsek, Irena; Horn, Ralf; Reigber, Andreas; Hasan, Sayeh; Rüdiger, Christoph; Jaeger, Marc; Vereecken, Harry

2014-05-01

306

Operational Monitoring of Soil Moisture at 1 km Scale: from ENVISAT to Sentinel-1  

NASA Astrophysics Data System (ADS)

With support from ESA, over the last three years a 1km soil moisture product based on the ENVISAT ASAR Global Mode (GM) data has been disseminated as an operational service for Southern Africa and Australia. Validation studies have confirmed the quality of the product. Currently, extension of the operational services and further validation, retrieval algorithm development and development of practical uses are pursued. Soil moisture has been identified as a land surface parameter of great importance in various fields of application. In 2006 the first medium resolution soil moisture dataset has been developed as part of the ESA project SHARE. The algorithm used a change detection approach that scales the normalized backscatter between historical minimum and maximum backscatter values. Besides its simplicity, an attractive feature of the method is that it works without the need for auxiliary data. Data from the Global Mode of the Advanced Synthetic Aperture Radar (ASAR) on board ENVISAT were utilized mainly because of the high temporal resolution (up to three acquisitions weekly) - a characteristic important for soil moisture monitoring. Over the last three years the soil moisture product developed at the Vienna University of Technology (TU Wien) has been used for regular monitoring of large parts of Africa and entire Australia. The validation studies performed over Oklahoma, USA and Australia showed a good correspondence with in-situ measurements and other remotely sensed soil moisture products and modeled datasets. Current research aims at the qualitative and quantitative analysis of the ASAR GM model parameters with geophysical land parameters (soil types, soil texture, vegetation indices) over the Murrumbidgee field experimental region in southeastern Australia. In this presentation, the first results will be discussed. In addition, the work done towards transforming the existing algorithm from the ENVISAT to the Sentinel-1 sensor will be presented. The improved understanding of the physical behavior of the model parameters may not only improve the soil moisture retrieval process but may also assist to retrieve additional variables such as biomass or physical soil properties. These might be subsequently derived at global scale from operational SAR sensors such as Sentinel-1.

Doubkova, Marcela; Sabel, Daniel; Bartsch, Annett; Wagner, Wolfgang; van Dijk, Albert

2010-05-01

307

The NASA Soil Moisture Active Passive (SMAP) Mission Formulation  

NASA Technical Reports Server (NTRS)

The Soil Moisture Active Passive (SMAP) mission is one of the first-tier projects recommended by the U.S. National Research Council Committee on Earth Science and Applications from Space. The SMAP mission is in formulation phase and it is scheduled for launch in 2014. The SMAP mission is designed to produce high-resolution and accurate global mapping of soil moisture and its freeze/thaw state using an instrument architecture that incorporates an L-band (1.26 GHz) radar and an L-band (1.41 GHz) radiometer. The simultaneous radar and radiometer measurements will be combined to derive global soil moisture mapping at 9 [km] resolution with a 2 to 3 days revisit and 0.04 [cm3 cm-3] (1 sigma) soil water content accuracy. The radar measurements also allow the binary detection of surface freeze/thaw state. The project science goals address in water, energy and carbon cycle science as well as provide improved capabilities in natural hazards applications.

Entekhabi, Dara; Njoku, Eni; ONeill, Peggy; Kellogg, Kent; Entin, Jared

2011-01-01

308

Short- and long-term patterns of soil moisture in alpine tundra  

SciTech Connect

Time domain reflectometry (TDR), a nondestructive technique for monitoring water content of soils, was used to measure volumetric soil moisture in three different communities in the alpine tundra during the summer of 1992. Data were converted to gravimetric estimates in order to allow comparison with 20 yr of records of gravimetric data, some of which date back to 1953. Analysis for growing-season trends indicated progressive depletion of soil moisture in all three community types studied. Using a liner model, mesic meadows showed the strongest seasonal decline and wet meadows the weakest. Curvilinear fits of the data suggested midsummer minima in xeric and mesic meadows and a midsummer maximum in wet meadows. Average summer soil moisture values for xeric meadows during the 1953-1964 interval were lower than those made in later years. This result may reflect sample site difference, but is consistent with a directional trend in increasing precipitation over this interval. Average summer soil moisture content of xeric meadows was correlated with annual precipitation, but not growing season (June-August) rainfall; this pattern was only discernible with the 20 yr data set. 35 refs., 2 figs., 3 tabs.

Taylor, R.V. (Univ. of New Mexico, Albuquerque, NM (United States)); Seastedt, T.R. (Univ. of Colorado, Boulder, CO (United States))

1994-02-01

309

Synergy between passive (SMOS) and active (RADARSAT-2) microwave soil moisture over Berambadi, India  

NASA Astrophysics Data System (ADS)

This study presents comparison and analysis towards blending of the SMOS derived soil moisture and RADARSAT-2 derived soil moisture over the Berambadi watershed, South India. SMOS (Soil Moisture and Ocean Salinity) satellite from ESA has a passive microwave L-Band sensor providing acquisition at ~40 km resolution and less than 3 days temporal resolution. RADARSAT-2 is an active microwave sensor from (CSA) operating in C-Band at a decametric spatial resolution and 24 days temporal resolution. Both satellites are all-weather satellites. SMOS is less impacted by roughness effects as it operates in passive mode at L-Band compared to RADARSAT-2, which on the other hand has a significantly higher spatial resolution. Twenty four images of RADARSAT-2 and SMOS-L2UDP soil moisture product, along with extensive field data collected in field campaigns during 2010-2012 in the framework of the ongoing AMBHAS (Assimilation of Multi-satellite data at Berambadi watershed for Hydrology And land Surface experiment) project were used in the analysis. A non parametric algorithm based on the CDF transformation method was developed to retrieve the soil moisture from RADARSAT-2 backscatter coefficient at a spatial resolution of 100 m. This product is validated using a random sampling procedure to divide the data into calibration and validation set each one consisting of 12 images. The developed algorithm provided a good estimate of the surface soil moisture with a RMSE of 0.05 m3 m-3. Then the validated RADARSAT-2 soil moisture maps were upscaled to compare with the SMOS data. Eight upscaling strategies were considered, taking into account the surface heterogeneity in terms of texture (clay sand), surface cover (forest, land cover) and SMOS mean antenna pattern. The strategies use linear combination of the different parameters. Significant differences were observed between the eight strategies. The RMSE and coefficient of determination of the different strategies varied between 0.06-0.09 m3 m-3 and 0.3-0.9 respectively. The best comparisons with a RMSE of 0.06 m3 m-3 and a coefficient of determination of 0.7 were obtained for upscaling strategies that include land cover effect. This result was used in the development of a downscaling procedure to merge the spatial information from RADARSAT-2 with the temporal dynamics from SMOS acquisitions. In order to implement this method the persistence of the spatial patterns in the RADARSAT-2 soil moisture map were evaluated by inspecting the spatiotemporal correlation coefficient across the two years, which was approximately 0.55. The impact of rain and farming activities were also taken into consideration in the analysis of the spatial heterogeneity. This study shows the potential synergy between the use of active/passive microwave soil moisture retrievals for spatial and temporal down-scaling of soil moisture. This study also shows the potential synergies between SMOS and SMAP (Soil Moisture Active Passive) mission from NASA due to launch in 2015 since SMAP will make active L-band acquisitions.

Tomer, Sat Kumar; Bitar, Ahmad Al; Sekhar, Muddu; Merlin, Olivier; Bandyopadhyay, Soumya; Kerr, Yann

2013-04-01

310

MoistureMap: A soil moisture monitoring, prediction and reporting system for sustainable land and water management  

NASA Astrophysics Data System (ADS)

A prototype soil moisture monitoring, prediction and reporting system is being developed for Australia, with the Murrumbidgee catchment as the demonstration catchment. The system will provide current and future soil moisture information and its uncertainty at 1km resolution, by combining weather, climate and land surface model predictions with soil moisture data from ESA's Soil Moisture and Ocean Salinity (SMOS) satellite; the first-ever dedicated microwave soil moisture mission. A major aspect of this project is developing and testing the soil moisture retrieval algorithms to be used for SMOS and verifying SMOS data for Australian conditions, through a number of airborne campaigns. The key elements of this project will develop and test innovative techniques for monitoring, prediction and reporting of 1km resolution soil moisture content from ground-, air- and space-based measurements for Australian conditions. The ground based and air-borne data will be used for: (i) calibration/validation of the SMOS satellite; (ii) development and verification of surface soil moisture retrieval algorithm components of the SMOS Simulator; (iii) development and verification of soil hydraulic property estimation; and (iv) verification of 1km moisture from MoistureMap. The Murrumbidgee catchment is an 80,000km2 watershed located in south-eastern Australia, with a large diversity in climatic, topographic and land cover characteristics making it an excellent demonstration test-bed for SMOS Simulator and MoistureMap developments. The Murrumbidgee River Catchment has been instrumented and monitored for soil moisture and supporting data for more than 7 years. The existing network of monitoring sites, data management systems, data sets, and detailed knowledge of the catchment provide an ideal basis for the field work and data requirements of this study. The soil moisture prediction model to be used is CSIRO Atmosphere Biosphere Land Exchange (CABLE), a column model based on Richards’ equation that simulates water and energy fluxes between a vertical profiles, land surface, vegetation and the atmosphere. This model is ideally suited to the assimilation requirements of this project due to its prediction of hydrological and thermal states soil and vegetation states, which are necessary for radiance and thermal data assimilation via ensemble CABLE simulations. In this presentation, we discuss the initial simulations with the land surface model (CABLE) and also the established data assimilation scheme. Moreover, we present the results from the first airborne campaigns to Central Australia and the Murrumbidgee River catchment. Finally, the progress of the developments of the different projects is presented, providing a first idea of the information that can be obtained from the SMOS data sets.

Rudiger, C.; Walker, J. P.; Barrett, D. J.; Gurney, R. J.; Kerr, Y. H.; Kim, E. J.; Lemarshall, J.

2009-12-01

311

Implementing a Terrestrial Carbon Flux Model in Preparation for the Soil Moisture Active Passive Mission  

NASA Astrophysics Data System (ADS)

The NASA Soil Moisture Active Passive (SMAP) mission has a projected launch in 2014 and will provide global mapping of surface soil moisture and landscape freeze/thaw (F/T) status using L-band (1.26 GHz) active and passive microwave remote sensing. Primary science objectives for SMAP include reducing uncertainty regarding terrestrial carbon (CO2) uptake and release and the purported missing carbon sink on land. An operational level 4 carbon (L4_C) product is planned under SMAP to quantify surface soil organic carbon (SOC) stocks, soil moisture and temperature controls for heterotrophic respiration and the net ecosystem exchange of CO2 (NEE) using model assimilation based soil moisture, temperature and F/T inputs from SMAP retrievals with ancillary information on global land cover and vegetation productivity (GPP). We conducted an initial global implementation and evaluation of the SMAP L4_C algorithms using MODIS (MOD17) GPP inputs and MERRA reanalysis based daily surface air temperature and soil moisture fields. The resulting model simulations are generally consistent with the distribution and magnitude of SOC stocks available from global soil inventories, while estimated carbon fluxes also correspond (R2 > 0.6; RMSE < 1.5 g C/m2/day) with CO2 flux measurements from the global tower network (FLUXNET). A model uncertainty analysis indicates an anticipated L4_C product accuracy for NEE within 30 g C / m2 / yr or 1.6 g C / m2 / day, and similar to accuracies attained from tower eddy covariance measurements. The resulting NEE calculations are used as a land surface constraint within an atmospheric transport model assimilation framework (CarbonTracker) to quantify terrestrial source-sink activity for atmospheric CO2. Portions of this work were conducted at the University of Montana and at the Jet Propulsion Laboratory, California Institute of Technology under contract to the National Aeronautics and Space Administration.

Kimball, J. S.; Yi, Y.; Jones, L. A.; Nemani, R. R.; Reichle, R. H.; McDonald, K. C.

2010-12-01

312

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

NASA Astrophysics Data System (ADS)

It is important to assess soil moisture to develop strategies to better manage its availability and use. At the landscape scale, soil moisture distribution derives from an integration of hydrologic, pedologic and geomorphic processes that cause soil moisture variability (SMV) to be time, space, and scale-dependent. Traditional methods to assess SMV at this scale are often costly, labor intensive, and invasive, which can lead to inadequate sampling density and spatial coverage. Fusing traditional sampling techniques with georeferenced auxiliary sensing technologies, such as geoelectric sensing and LiDAR, provide an alternative approach. Because geoelectric and LiDAR measurements are sensitive to soil properties and terrain features that affect soil moisture variation, they are often employed as auxiliary measures to support less dense direct sampling. Georeferenced proximal sensing acquires rapid, real-time, high resolution data over large spatial extents that is enriched with spatial, temporal and scale-dependent information. Data fusion becomes important when proximal sensing is used in tandem with more sparse direct sampling. Multicollocated factorial cokriging (MFC) is one technique of multivariate geostatistics to fuse multiple data sources collected at different sampling scales to study the spatial characteristics of environmental properties. With MFC sparse soil observations are supported by more densely sampled auxiliary attributes to produce more consistent spatial descriptions of scale-dependent parameters affecting SMV. This study uses high resolution geoelectric and LiDAR data as auxiliary measures to support direct soil sampling (n=127) over a 40 hectare Central Kentucky (USA) landscape. Shallow and deep apparent electrical resistivity (ERa) were measured using a Veris 3100 in tandem with soil moisture sampling on three separate dates with ascending soil moisture contents ranging from plant wilting point to field capacity. Terrain features were produced from 2010 LiDAR returns collected at ?1 m nominal pulse spacing. Exploratory statistics revealed 12 variables that best associate with soil moisture including slope, elevation, calcium, organic matter, clay, sand and geoelectric measurements (ERa for each date). A linear combination of basic variogram functions, called the linear model of coregionalization (LMC), was fitted using a matrix of direct and cross experimental variograms constituting the 12 different variables studied. The LMC consisted of 3 basic components: nugget, spherical (short range scale=40m) and exponential (long range scale=250m) where each component explained 17%, 22% and 60% of the total measured variation, respectively. Applying principal component analysis to the coregionalization matrix at each spatial scale produced a set of regionalized factors summarizing the variation at that spatial scale. Mapping regionalized factors decomposes the total measured system variation into scale-dependent synthetic homogeneous zones that lend insight into the properties influencing SMV. Results suggest that soil texture and OM drive the soil moisture variation under the soil moisture regimes observed. This study shows the potential for using ERa and multivariate statistics to develop soil moisture management strategies under water stressed conditions.

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

2013-12-01

313

Comparison of ASCAT satellite soil moisture measurements data with in-situ measurements  

NASA Astrophysics Data System (ADS)

The topsoil moisture defined at meteorological stations and the one defined with the use of MetOp satellite has been compared in the paper. The comparison is made with the measurements at stations located on the USA territory and included in the observation network FLUXNET-AMERIFLUX and Soil Climate Analysis Network (SCAN). The stations are located in different climatic zones, defined according to the vegetation type as per the IGBP classification. The research period is 2007-2012. The satellite observation data are corrected to the in-situ measurements and measurement accuracy is assessed. The assessment has been done for different types of underlying terrains. A good agreement with the real data of in-situ moisture measurements has been shown, which allows to use the satellite soil moisture measurement data in data assimilation systems for numerical weather prediction models.

Bogoslovskiy, Nicholay N.; Erin, Sergey I.; Borodina, Irina A.; Kizhner, Lubov I.

2014-11-01

314

Active and passive microwave measurements of soil moisture in FIFE  

NASA Technical Reports Server (NTRS)

During the intensive field campaigns of the First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE) in May-October of 1987, several nearly simultaneous measurements were made with low-altitude flights of the L-band radiometer and C- and X-band scatterometers over two transects in the Konza Prairie Natural Research Area, some 8 km south of Manhattan, Kansas. These measurements showed that although the scatterometers were sensitive to soil moisture variations in most regions under the flight path, the L-band radiometer lost most of its sensitivity in regions unburned for many years. The correlation coefficient derived from the regression between the radar backscattering coefficient and the soil moisture was found to improve with the increase in antenna incidence angle. This is attributed to a steeper falloff of the backscattering coefficient as a function of local incidence at angles near nadir than at angles greater than 30 deg.

Wang, J. R.; Gogineni, S. P.; Ampe, J.

1992-01-01

315

Assimilation of surface soil moisture into a multilayer soil model: design and evaluation at local scale  

NASA Astrophysics Data System (ADS)

Land surface models (LSM) have improved considerably in the last two decades. In this study, the Interactions between Surface, Biosphere, and Atmosphere (ISBA) LSM soil diffusion scheme is used (with 11 soil layers represented). A simplified extended Kalman filter (SEKF) allows ground observations of surface soil moisture (SSM) to be assimilated in the multilayer LSM in order to constrain deep soil moisture. In parallel, the same simulations are performed using the ISBA LSM with 2 soil layers (a thin surface layer and a bulk reservoir). Simulations are performed over a 3 yr period (2003-2005) for a bare soil field in southwestern France, at the SMOSREX (Surface Monitoring Of the Soil Reservoir Experiment) site. Analyzed soil moisture values correlate better with soil moisture observations when the ISBA LSM soil diffusion scheme is used. The Kalman gain is greater from the surface to 45 cm than below this limit. For dry periods, corrections introduced by the assimilation scheme mainly affect the first 15 cm of soil whereas weaker corrections impact the total soil column for wet periods. Such seasonal corrections cannot be described by the two-layer ISBA LSM. Sensitivity studies performed with the multilayer LSM show improved results when SSM (0-6 cm) is assimilated into the second layer (1-5 cm) than into the first layer (0-1 cm). The introduction of vertical correlations in the background error covariance matrix is also encouraging. Using a yearly cumulative distribution function (CDF)-matching scheme for bias correction instead of matching over the three years permits the seasonal variability of the soil moisture content to be better transcribed. An assimilation experiment has also been performed by forcing ISBA-DF (diffusion scheme) with a local forcing, setting precipitation to zero. This experiment shows the benefit of the SSM assimilation for correcting inaccurate atmospheric forcing.

Parrens, M.; Mahfouf, J.-F.; Barbu, A. L.; Calvet, J.-C.

2014-02-01

316

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

NASA Astrophysics Data System (ADS)

Soil moisture plays an important role in determining the likelihood of droughts and floods that may affect an area. Knowledge of soil moisture distribution as a function of time and space is highly relevant for hydrological, ecological and agricultural applications, especially in water-limited or drought-prone regions. However, measuring soil moisture is challenging because of its high variability; point-scale in-situ measurements are scarce being remote sensing the only practical means to obtain regional- and global-scale soil moisture estimates. The ESA's Soil Moisture and Ocean Salinity (SMOS) is the first satellite mission ever designed to measuring the Earth's surface soil moisture at near daily time scales with levels of accuracy previously not attained. Since its launch in November 2009, significant efforts have been dedicated to validate and fine-tune the retrieval algorithms so that SMOS-derived soil moisture estimates meet the standards required for a wide variety of applications. In this line, the SMOS Barcelona Expert Center (BEC) is distributing daily, monthly, and annual temporal averages of 0.25-deg global soil moisture maps, which have proved useful for assessing drought and water-stress conditions. In addition, a downscaling algorithm has been developed to combine SMOS and NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) data into fine-scale (< 1km) soil moisture estimates, which permits extending the applicability of the data to regional and local studies. Fine-scale soil moisture maps are currently limited to the Iberian Peninsula but the algorithm is dynamic and can be transported to any region. Soil moisture maps are generated in a near real-time fashion at BEC facilities and are used by Barcelona's fire prevention services to detect extremely dry soil and vegetation conditions posing a risk of fire. Recently, they have been used to explain drought-induced tree mortality episodes and forest decline in the Catalonia region. These soil moisture products can also be a useful tool to monitor the effectiveness of land restoration management practices. The aim of this work is to demonstrate the feasibility of using SMOS soil moisture maps for monitoring drought and water-stress conditions. In previous research, SMOS-derived Soil Moisture Anomalies (SSMA), calculated in a ten-day basis, were shown to be in close relationship with well-known drought indices (the Standardized Precipitation Index and the Standardized Precipitation Evapotranspiration Index). In this work, SSMA have been calculated for the period 2010-2013 in representative arid, semi-arid, sub-humid and humid areas across global land biomes. The SSMA reflect the cumulative precipitation anomalies and is known to provide 'memory' in the climate and hydrological system; the water retained in the soil after a rainfall event is temporally more persistent than the rainfall event itself, and has a greater persistence during periods of low precipitation. Besides, the Normalized Difference Vegetation Index (NDVI) from MODIS is used as an indicator of vegetation activity and growth. The NDVI time series are expected to reflect the changes in surface vegetation density and status induced by water-deficit conditions. Understanding the relationships between SSMA and NDVI concurrent time series should provide new insight about the sensitivity of land biomes to drought.

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

2014-05-01

317

Soil moisture dynamics of calcareous grassland under elevated CO 2  

Microsoft Academic Search

Water relations of nutrient-poor calcareous grassland under long-term CO2 enrichment were investigated. Understanding CO2 effects on soil moisture is critical because productivity in these grasslands is water limited. In general, leaf conductance\\u000a was reduced at elevated CO2, but responses strongly depended on date and species. Evapotranspiration (measured as H2O gas exchange) revealed only small, non-significant reductions at elevated CO2, indicating

Pascal A. Niklaus; D. Spinnler; C. Körner

1998-01-01

318

Surface Roughness Parameter Uncertainties on Radar Based Soil Moisture Retrievals  

NASA Technical Reports Server (NTRS)

Surface roughness variations are often assumed to be negligible for the retrieval of sol moisture. Although previous investigations have suggested that this assumption is reasonable for natural vegetation covers (i.e. Moran et al. 2002), in-situ measurements over plowed agricultural fields (i.e. Callens et al. 2006) have shown that the soil surface roughness can change considerably due to weathering induced by rain.

Joseph, A. T.; vanderVelde, R.; O'Neill, P. E.; Lang, R.; Su, Z.; Gish, T.

2012-01-01

319

Investigation of Soil Moisture - Vegetation Interactions in Oklahoma  

E-print Network

INVESTIGATION OF SOIL MOISTURE ? VEGETATION INTERACTIONS IN OKLAHOMA A Thesis by TRENTON W. FORD Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment of the requirements for the degree... of MASTER OF SCIENCE Approved by: Chair of Committee, Steven M. Quiring Committee Members, Oliver W. Frauenfeld John Nielsen-Gammon Head of Department, Vatche P. Tchakerian May 2013 Major Subject: Geography Copyright 2013 Trenton W. Ford...

Ford, Trenton W.

2013-03-06

320

Soil moisture sensing via swept frequency based microwave sensors.  

PubMed

There is a need for low-cost, high-accuracy measurement of water content in various materials. This study assesses the performance of a new microwave swept frequency domain instrument (SFI) that has promise to provide a low-cost, high-accuracy alternative to the traditional and more expensive time domain reflectometry (TDR). The technique obtains permittivity measurements of soils in the frequency domain utilizing a through transmission configuration, transmissometry, which provides a frequency domain transmissometry measurement (FDT). The measurement is comparable to time domain transmissometry (TDT) with the added advantage of also being able to separately quantify the real and imaginary portions of the complex permittivity so that the measured bulk permittivity is more accurate that the measurement TDR provides where the apparent permittivity is impacted by the signal loss, which can be significant in heavier soils. The experimental SFI was compared with a high-end 12 GHz TDR/TDT system across a range of soils at varying soil water contents and densities. As propagation delay is the fundamental measurement of interest to the well-established TDR or TDT technique; the first set of tests utilized precision propagation delay lines to test the accuracy of the SFI instrument's ability to resolve propagation delays across the expected range of delays that a soil probe would present when subjected to the expected range of soil types and soil moisture typical to an agronomic cropping system. The results of the precision-delay line testing suggests the instrument is capable of predicting propagation delays with a RMSE of +/-105 ps across the range of delays ranging from 0 to 12,000 ps with a coefficient of determination of r(2) = 0.998. The second phase of tests noted the rich history of TDR for prediction of soil moisture and leveraged this history by utilizing TDT measured with a high-end Hewlett Packard TDR/TDT instrument to directly benchmark the SFI instrument over a range of soil types, at varying levels of moisture. This testing protocol was developed to provide the best possible comparison between SFI to TDT than would otherwise be possible by using soil moisture as the bench mark, due to variations in soil density between soil water content levels which are known to impact the calibration between TDR's estimate of soil water content from the measured propagation delay which is converted to an apparent permittivity measurement. This experimental decision, to compare propagation delay of TDT to FDT, effectively removes the errors due to variations in packing density from the evaluation and provides a direct comparison between the SFI instrument and the time domain technique of TDT. The tests utilized three soils (a sand, an Acuff loam and an Olton clay-loam) that were packed to varying bulk densities and prepared to provide a range of water contents and electrical conductivities by which to compare the performance of the SFI technology to TDT measurements of propagation delay. For each sample tested, the SFI instrument and the TDT both performed the measurements on the exact same probe, thereby both instruments were measuring the exact same soil/soil-probe response to ensure the most accurate means to compare the SFI instrument to a high-end TDT instrument. Test results provided an estimated instrumental accuracy for the SFI of +/-0.98% of full scale, RMSE basis, for the precision delay lines and +/-1.32% when the SFI was evaluated on loam and clay loam soils, in comparison to TDT as the bench-mark. Results from both experiments provide evidence that the low-cost SFI approach is a viable alternative to conventional TDR/TDT for high accuracy applications. PMID:22368494

Pelletier, Mathew G; Karthikeyan, Sundar; Green, Timothy R; Schwartz, Robert C; Wanjura, John D; Holt, Greg A

2012-01-01

321

A Continental Scale Assessment of SMOS Derived Soil Moisture over the United States  

NASA Astrophysics Data System (ADS)

There has been a range of spaceborne remote sensing sensors deployed during the last two decades to retrieve near surface (~ 0 - 2 cm) soil moisture. The retrieval techniques to derive satellite based soil moisture include either physically based algorithms (such as radiative transfer equations) or various indirect statistical algorithms. Soil Moisture and Ocean Salinity (SMOS) mission is the latest addition to those suits of spaceborne sensors which was launched in November 2009, and has been providing 1.4GHz (L-band) measurements since then. The advantage of using the L-band channel is its better surface emission characteristics, which allows expanded spatial coverage over denser vegetated surfaces and should improve the retrieved surface soil moisture estimates. The latter offers information that can be used to estimate deeper soil layer moisture conditions for many agricultural, hydrologic and climate applications. Prior to using the SMOS soil moisture (SM) retrievals for scientific applications, it is absolutely necessary to verify the quality of the data products. In this study, we assess the recently available SMOS 1.4 GHz based soil moisture retrievals for 2010 are assessed over the Continental United States (CONUS) region, along with soil moisture retrievals produced at Princeton University based on AMSR-E 10.7 GHz brightness temperatures using the Land Surface Microwave Emission Model (AMSR-E/LSMEM) and in-situ measurements from the Natural Resource Conservation Service's (NRCS) Soil Climate Analysis Network (SCAN). The assessment is carried out using a performance metric developed earlier by Crow and Zhan (2007), which calculates the ability of soil moisture estimates to correct errors in water balance predictions through a linear Kalman filter algorithm. Within the framework proposed by Crow and Zhan (2007), it is found that current SMOS retrievals, which are based mostly on default parameters in its retrieval algorithm, performs slightly worse than the AMSR-E retrievals from a more mature algorithm LSMEM (AMSR-E/LSMEM). Over the 154 SCAN stations, the SCAN and AMSR-E/LSMEM retrievals performed in an equivalent manner, and better than the SMOS retrievals. At the same time, large uncertainties remain in this performance evaluation due to the short length (1 year) of available SMOS data, which controlled the overall period of the analysis. The findings suggest that it is very important for SMOS to continue its validation at different scales and locations, and to use the results to improve the calibration of the SMOS retrieval algorithm. The proposed method and the analysis results provide new insights into the SMOS SM retrieval at continental scale. Reference: Crow, W. T., and Zhan, X. (2007), "Continental-scale evaluation of remotely-sensed soil moisture products," IEEE Geoscience and Remote Sensing Letters, 4(3), 451-455.

Sahoo, A. K.; Pan, M.; Wood, E. F.; Al Bitar, A.; Leroux, D.; Kerr, Y. H.

2011-12-01

322

Effect of moisture on alachlor retention in the soil  

E-print Network

(~sor hum ~vul are 9 rs. , var RS 610) as a bioassay to study the relative phyto- toxicity of alachlor in various soils' Stickler et al. (21) use(i giant foxtail (Setaria faberii Herrm. ) in studying the relationship between soil moisture... adsorption of the her'bicide. Knake and wax (13) reported higher injuries to giant foxtail when alachlor was placed above the germinating seed rather . han below its LITERATURE CITED l. Ashton, F. N ~ and Ka Dunster. 1961. The herbicidal effect of EPTC...

Hargrove, Raford Stanley

1970-01-01

323

Effects of soil moisture variations on deposition velocities above vegetation.  

SciTech Connect

The parameterized subgrid-scale surface flux (PASS) model provides a simplified means of using remote sensing data from satellites and limited surface meteorological information to estimate the influence of soil moisture on bulk canopy stomatal resistances to the uptake of gases over extended areas. PASS-generated estimates of bulk canopy stomatal resistance were used in a dry deposition module to compute gas deposition velocities with a horizontal resolution of 200 m for approximately 5000 km{sup 2} of agricultural crops and rangeland. Results were compared with measurements of O{sub 3} flux and concentrations made during April and May 1997 at two surface stations and from an aircraft. The trend in simulated O{sub 3} deposition velocity during soil moisture drydown over a period of a few days matched the trend observed at the two surface stations. For areas under the aircraft flight paths, the variability in simulated O{sub 3} deposition velocity was substantially smaller than the observed variability, while the averages over tens of kilometers were usually in agreement within 0.1 cm s{sup -1}. Model results indicated that soil moisture can have a major role in deposition of O{sub 3} and other substances strongly affected by canopy stomatal resistance.

Wesely, M. L.; Song, J.; McMillen, R. T.; Meyers, T. P.; Environmental Research; Northern Illinois Univ.; National Oceanic and Atmospheric Administration

2001-01-01

324

Vegetation Dynamics And Soil Moisture: Consequences For Hydrologic Modeling  

NASA Astrophysics Data System (ADS)

Current global population growth and economical development accelerates land cover conversion in many parts of the world. Introducing non-native species and woody species encroachment, with different water demands, can affect the partitioning of hydrological fluxes. The impacts on the hydrologic cycle at local to regional scales are poorly understood. The present study investigates the hydrologic implications of land use conversion from native vegetation to rubber. We first compare the vegetation dynamics of rubber (Hevea brasiliensis), a non- native specie in Southeast Asia, to the other main vegetation types in the study area. The experimental catchment, Nam Ken (69km 2), is located in the Xishuangbanna Prefecture (21 °N, 100 °E), in the south of Yunnan province in South China. From 2005 to 2006, we collected continuous records of 2 m deep soil moisture profiles in four different land covers (tea, secondary forest, grassland and rubber), and measured surface radiation in tea and rubber canopies. Our observations show that root water uptake by rubber during the dry season is controlled by the change of day-length, whereas water demand of the native vegetation starts with the arrival of the first monsoon rainfall. The different root water uptake dynamics of rubber result in distinct depletion of deeper layer soil moisture. Traditional evapotranspiration and soil moisture models are unable to simulate this specific behavior, thus a different conceptual model is needed to predict hydrologic changes due to land use conversion in the area.

Guardiola-Claramonte, M.; Troch, P. A.

2007-12-01

325

Diurnal and seasonal variation in the control of soil temperature and moisture on soil CO2 efflux during secondary succession  

NASA Astrophysics Data System (ADS)

The carbon sink activity of the eastern United States over the last several decades has been attributed to secondary succession1. The extent of this sink activity depends on the balance between gross primary production and ecosystem respiration (RE), i.e. net ecosystem production (NEP). Because soil CO2 efflux, a component of RE, can influence the magnitude or sign of NEP, constraining the dynamics of soil CO2 efflux and its controls over diurnal, seasonal and decadal time scales is important. The aims of this study were twofold. (1) To examine the influence of soil temperature and moisture on soil CO2 efflux in abandoned agricultural fields undergoing secondary succession. (2) To investigate whether the soil CO2 efflux - soil temperature and moisture relationship varied diurnally, seasonally, or among successional stages. To test these questions, we employed a chronosequence approach at Blandy Experimental Farm near Boyce, VA. Six study fields, ranging in age from 6 to >100 years, were classified as early, mid or late successional. Each pair of fields in the same successional stage was closely age-matched. We concurrently measured soil CO2 efflux, soil temperature at 5 cm, and soil volumetric water content (VWC) to 12 cm (%) year round for two years both during the day (1000-1400) and at night (2200-0200). Soil samples to 15 cm from each study plot were collected and analyzed in the laboratory to determine bulk density (?B) and particle density (?P). Soil porosity (?) was calculated as (1 - ?B / ?P)*100. Soil water filled pore space (WFPS) was calculated as VWC/?. A stepwise multiple regression of soil CO2 efflux against soil temperature and WFPS showed that temperature and WFPS significantly affected soil CO2 efflux (p<0.0001; R2=0.41; Flux = 0.42(Temp) + 5.72(WFPS) - 4.18). An analysis of covariance with season, chronosequence, successional stage and time of day as independent variables, and a new principle component derived from soil temperature and WFPS as a covariate showed that while soil CO2 efflux did vary by season (p<0.0001) and by chronosequence (p=0.040), it did not vary by successional stage (p=0.970) or by time of day (p=0.129). The soil CO2 efflux - soil temperature and moisture relationship varied seasonally (p<0.0001), but did not vary between the two chronosequences (p=0.299), between day and night (p=0.139) or among successional stages (p=0.052). The similarity in the soil CO2 efflux - soil temperature and moisture relationship between the two chronosequences, despite the difference in soil CO2 efflux magnitude, suggests that while land use history can impact the amount of CO2 released by the soil, the influence of environmental drivers remains the same. Notably, there was no difference between daytime and nighttime in the amount of CO2 released by soil, nor in the soil CO2 efflux - soil temperature and moisture relationship. This suggests that extrapolations of nighttime estimates of RE by eddy covariance systems to total daily RE are reasonable. 1Albani et al.. 2006. Global Change Biology 12:2370-2390.

Dunker, S. L.; Epstein, H. E.

2012-12-01

326

Soil Moisture Active/Passive (SMAP) Forward Brightness Temperature Simulator  

NASA Technical Reports Server (NTRS)

The SMAP is one of four first-tier missions recommended by the US National Research Council's Committee on Earth Science and Applications from Space (Earth Science and Applications from Space: National Imperatives for the Next Decade and Beyond, Space Studies Board, National Academies Press, 2007) [1]. It is to measure the global soil moisture and freeze/thaw from space. One of the spaceborne instruments is an L-band radiometer with a shared single feedhorn and parabolic mesh reflector. While the radiometer measures the emission over a footprint of interest, unwanted emissions are also received by the antenna through the antenna sidelobes from the cosmic background and other error sources such as the Sun, the Moon and the galaxy. Their effects need to be considered accurately, and the analysis of the overall performance of the radiometer requires end-to-end performance simulation from Earth emission to antenna brightness temperature, such as the global simulation of L-band brightness temperature simulation over land and sea [2]. To assist with the SMAP radiometer level 1B algorithm development, the SMAP forward brightness temperature simulator is developed by adapting the Aquarius simulator [2] with necessary modifications. This poster presents the current status of the SMAP forward brightness simulator s development including incorporating the land microwave emission model and its input datasets, and a simplified atmospheric radiative transfer model. The latest simulation results are also presented to demonstrate the ability of supporting the SMAP L1B algorithm development.

Peng, Jinzheng; Peipmeier, Jeffrey; Kim, Edward

2012-01-01

327

Beyond triple collocation: Applications to soil moisture monitoring  

NASA Astrophysics Data System (ADS)

collocation (TC) is routinely used to resolve approximated linear relationships between different measurements (or representations) of a geophysical variable that are subject to errors. It has been utilized in the context of calibration, validation, bias correction, and error characterization to allow comparisons of diverse data records from various direct and indirect measurement techniques including in situ remote sensing and model-based approaches. However, successful applications of TC require sufficiently large numbers of coincident data points from three independent time series and, within the analysis period, homogeneity of their linear relationships and error structures. These conditions are difficult to realize in practice due to infrequent spatiotemporal sampling of satellite and ground-based sensors. TC can, however, be generalized within the framework of instrumental variable (IV) regression theory to address some of the conceptual constraints of TC. We review the theoretics of IV and consider one possible strategy to circumvent the three-data constraint by use of lagged variables (LV) as instruments. This particular implementation of IV is suitable for circumstances where multiple data records are limited and the geophysical variable of interest is sampled at time intervals shorter than its temporal correlation length. As a demonstration of utility, the LV method is applied to microwave satellite soil moisture data sets to recover their errors over Australia and to estimate temporal properties of their relationships with in situ and model data. These results are compared against standard two-data linear estimators and the TC estimator as benchmark.

Su, Chun-Hsu; Ryu, Dongryeol; Crow, Wade T.; Western, Andrew W.

2014-06-01

328

Assimilation of surface soil moisture into a multilayer soil model: design and evaluation at local scale  

NASA Astrophysics Data System (ADS)

Land surface models (LSM) have improved considerably in the last two decades. In this study, the ISBA LSM soil diffusion scheme is used (with 11 soil layers represented). A Simplified Extended Kalman Filter (SEKF) allows surface soil moisture (SSM) to be assimilated in the multi-layer LSM in order to constrain deep soil moisture. In parallel, the same simulations are performed using the ISBA LSM with 2 soil layers (a thin surface layer and a bulk reservoir). Simulations are performed over a 3 yr period (2003-2005) for a bare soil field in southwestern France, at the SMOSREX experimental site. Analyzed soil moisture values correlate better with soil moisture observations when the ISBA LSM soil diffusion scheme is used. The Kalman gain is greater from the surface to 45 cm than below this limit. For dry periods, corrections introduced by the assimilation scheme mainly affect the first 25 cm of soil whereas weaker corrections impact the total soil column for wet periods. Such seasonal corrections cannot be described by the two-layer ISBA LSM. Sensitivity studies performed with the multi-layer LSM show improved results when SSM (0-6 cm) is assimilated into the second layer (1-5 cm) than into the first layer (0-1 cm). The introduction of vertical correlations in the background error covariance matrix is also encouraging. Using a yearly CDF-matching scheme for bias correction instead of matching over the three years permits the seasonal variability of the soil moisture content to be better transcribed. An assimilation experiment has also been performed by forcing ISBA-DF with a local forcing setting precipitation to zero. This experiment shows the benefit of the SSM assimilation for correcting inaccurate atmospheric forcing.

Parrens, M.; Mahfouf, J.-F.; Barbu, A.; Calvet, J.-C.

2013-07-01

329

Evaluation of Intergovernmental Panel on Climate Change Fourth Assessment soil moisture simulations for the second half of the twentieth century  

Microsoft Academic Search

Soil moisture trends, particularly during the growing season, are an important possible consequence of global warming. Climate model simulations of future soil moisture changes should be made with models that can produce reliable simulations of soil moisture for past climate changes. In this paper, we compare soil moisture simulations from Intergovernmental Panel on Climate Change Fourth Assessment climate models forced

Haibin Li; Alan Robock; Martin Wild

2007-01-01

330

Analysis of the relationship between the volumetric soil moisture content and the NDVI from high resolution multi-spectral images for definition of vineyard management zones to improve irrigation  

Microsoft Academic Search

As suggested by previous research in the field of precision viticulture, intra-field yield variability is dependent on the variation of soil properties, and in particular the soil moisture content. Since the mapping in detail of this soil property for precision viticulture applications is highly costly, the objective of the present research is to analyse its relationship with the normalised difference

J. A. Martínez-Casasnovas; M. C. Ramos

2009-01-01

331

Impact of Soil Moisture Dynamics on ASAR ?o Signatures and Its Spatial Variability Observed over the Tibetan Plateau  

PubMed Central

This paper reports on the analysis of a 2.5 year-long time series of ASAR wide swath mode (WSM) observations for characterizing the soil moisture dynamics. The employed ASAR WSM data set consists of 152 VV-polarized scenes acquired in the period between April 2005 and September 2007 over the Naqu river basin located on the Tibetan Plateau. For four different spatial domains, with areas of 30×30 km2, 5×5 km2 and (two domains of) 1×1 km2, the mean backscatter (?o) and the standard deviation (stdev) have been computed for each ASAR acquisition. Comparison of the mean ?o values with the stdev values results in a specific triangular distribution of data points for all spatial domains. Analysis of the mean ?o and stdev with respect to in-situ soil moisture measurements demonstrates that this triangular shaped distribution can be explained by soil moisture dynamics during monsoon and winter periods. This shows that the relationship between the spatial mean soil moisture and variability is not uniquely defined and may change throughout seasons. Downscaling of coarse resolution soil moisture products should, therefore, be ideally based on additional near real time data sources. In this context, the presented results could form a basis for the development of SAR-based soil moisture downscaling methodologies.

van der Velde, Rogier; Su, Zhongbo; Ma, Yaoming

2008-01-01

332

Two Topics in Seasonal Streamflow Forecasting: Soil Moisture Initialization Error and Precipitation Downscaling  

NASA Technical Reports Server (NTRS)

Continental-scale offline simulations with a land surface model are used to address two important issues in the forecasting of large-scale seasonal streamflow: (i) the extent to which errors in soil moisture initialization degrade streamflow forecasts, and (ii) the extent to which the downscaling of seasonal precipitation forecasts, if it could be done accurately, would improve streamflow forecasts. The reduction in streamflow forecast skill (with forecasted streamflow measured against observations) associated with adding noise to a soil moisture field is found to be, to first order, proportional to the average reduction in the accuracy of the soil moisture field itself. This result has implications for streamflow forecast improvement under satellite-based soil moisture measurement programs. In the second and more idealized ("perfect model") analysis, precipitation downscaling is found to have an impact on large-scale streamflow forecasts only if two conditions are met: (i) evaporation variance is significant relative to the precipitation variance, and (ii) the subgrid spatial variance of precipitation is adequately large. In the large-scale continental region studied (the conterminous United States), these two conditions are met in only a somewhat limited area.

Koster, Randal; Walker, Greg; Mahanama, Sarith; Reichle, Rolf

2012-01-01

333

GPS-R L1 interference signal processing for soil moisture estimation: an experimental study  

NASA Astrophysics Data System (ADS)

Global positioning system reflectometry (GPS-R) is an emerging area of GPS applications in microwave remote sensing using multipath reflected signals. Soil moisture estimation is one of the many potential applications of the GPS-R technique. The focus of this study is on investigating the feasibility of soil moisture estimation based on GPS L1 band interference signals which can be readily captured using a low-cost off-the-shelf L1-band GPS receiver. The theoretical background is studied, and the field experiments conducted are described. Power spectrum analysis is performed on the received interference signals to determine the interference signal frequency variation, and cosine similarity is applied to identify the initial phase change. Data collected at a number of continuously operating GPS stations are also analyzed. The results demonstrate that both interference signal frequency and phase have changed significantly after rainfalls occurred. That is, it is possible to estimate soil moisture by analyzing the frequency change and phase shift. However, it is also observed that the phase shift is inconsistent in some cases. Ongoing work will focus on figuring out the source of the inconsistency so that reliable estimation of soil moisture can be achieved.

Yan, Songhua; Li, Zhengyong; Yu, Kegen; Zhang, Kefei

2014-12-01

334

Growth of three species of Bidens under different levels of soil moisture content  

Microsoft Academic Search

By the assumption that both soil moisture and soil air affect plant growth as linear factor, the relationship between mean\\u000a plant dry weight and soil moisture content was newly formulated. Its applicability to actual growth data was tested by growing\\u000a three species ofBidens under different levels of soil moisture content. The growth data ofBidens well satisfied the new formula. The

Kiyokazu Suehiro; Kazuo Hozumi; Kichiro Shinozaki

1984-01-01

335

Microwave remote sensing of soil moisture with vegetation effect  

NASA Astrophysics Data System (ADS)

The objectives of this study were: to examine the sensitivity of radar backscatter, to estimate soil moisture under a corn plot and to evaluate the effectiveness and sensitivity of a Radiative Transfer Model (RTM), adapted from the earlier work of Njoku and Kong, (1977) in predicting brightness temperature from a grass plot. Microwave radar measurements were collected from plots of different vegetation cover types, vegetation density, and moisture conditions during the Huntsville 1998 field experiment. A large amount of ground data on brightness temperatures, soil moisture, and vegetation characteristics (e.g., biomass, and water content) were collected. The experiments were conducted at Alabama A&M University's, Winfred Thomas Agricultural Research Station, located near Hazel Green, Alabama. Six plots, one 50 X 60 m smooth bare plot, one 50 X 60 m grass plot, and four 30 X 50 m corn plots at full, 2/3, 1/2, and 1/3 densities were used. Radar backscatter data were obtained from a ground based truck mounted radar operating at L, C, and X bands (1.6, 4.75, and 10 GHz) with four linear polarization HH, HV, VV, and VH and two incidence angles (15 and 45 degrees). Soil moisture values were determined using Water Content Reflectometry (WCR). Three types of soil temperature sensors (Infrared Thermometer, Thermistor, and a 4-sensor averaging thermocouple probes) were used. A discrete backscatter approach model and RTM were evaluated. Comparisons between model prediction and experimental observation for HH polarization indicated good agreement for a corn full plot. The direct-reflected scattering coefficient is found to be the most dominant term for both polarization and the backscatter is also highly sensitive to soil moisture. The trends in time variation of brightness temperature are in agreement with the experimental results and the numerical results are within a few percent of the experimental results. The vegetation corrections as estimated by the Jackson and Schmugge method are very small. Detailed examination of the vegetation canopy contribution including the geometry of the canopy, the various absorption and scattering mechanisms are necessary.

Tsegaye, Teferi D.; Inguva, Ramarao; Lang, Roger H.; O'Neill, Peggy E.; Fahsi, Ahmed; Coleman, Tommy L.; Tadesse, Wubishet; Rajbhandari, Narayan B.; Aburemie, Sunnie A.; de Matthaeis, Paolo

1999-12-01

336

State of the Art in Large-Scale Soil Moisture Monitoring  

NASA Technical Reports Server (NTRS)

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.

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.; Zreda, Marek G.

2013-01-01

337

Scaling Soil Moisture Variations from Ground-Based to Satellite Scales  

NASA Astrophysics Data System (ADS)

Soil moisture variability exhibits a range of behaviors over the entire spectrum of dynamic wetness. This variability depends critically on variables such as topography, land cover, soil properties and rainfall patterns, but also on the area of the region under consideration. Moreover, space-time scales of the representative sample also play an important role in how scaling behavior manifests itself. In this presentation, results from several ground-based soil moisture variability studies will be reviewed and extended to incorporate aircraft and satellite remote sensing scales. Of particular interest are scaling behavior changes associated with surface soil moisture versus total water storage, hysteresis, and the expression of extreme events. Results will have implications for the representation of soil moisture in land surface models, for soil moisture network design, and for downscaling/upscaling remotely-sensed soil moisture.

Famiglietti, James

2014-05-01

338

Use of visible, near-infrared, and thermal infrared remote sensing to study soil moisture  

NASA Technical Reports Server (NTRS)

Two methods are described which are used to estimate soil moisture remotely using the 0.4- to 14.0 micron wavelength region: (1) measurement of spectral reflectance, and (2) measurement of soil temperature. The reflectance method is based on observations which show that directional reflectance decreases as soil moisture increases for a given material. The soil temperature method is based on observations which show that differences between daytime and nighttime soil temperatures decrease as moisture content increases for a given material. In some circumstances, separate reflectance or temperature measurements yield ambiguous data, in which case these two methods may be combined to obtain a valid soil moisture determination. In this combined approach, reflectance is used to estimate low moisture levels; and thermal inertia (or thermal diffusivity) is used to estimate higher levels. The reflectance method appears promising for surface estimates of soil moisture, whereas the temperature method appears promising for estimates of near-subsurface (0 to 10 cm).

Blanchard, M. B.; Greeley, R.; Goettelman, R.

1974-01-01

339

Use of visible, near-infrared, and thermal infrared remote sensing to study soil moisture  

NASA Technical Reports Server (NTRS)

Two methods are used to estimate soil moisture remotely using the 0.4- to 14.0-micron wavelength region: (1) measurement of spectral reflectance, and (2) measurement of soil temperature. The reflectance method is based on observations which show that directional reflectance decreases as soil moisture increases for a given material. The soil temperature method is based on observations which show that differences between daytime and nighttime soil temperatures decrease as moisture content increases for a given material. In some circumstances, separate reflectance or temperature measurements yield ambiguous data, in which case these two methods may be combined to obtain a valid soil moisture determination. In this combined approach, reflectance is used to estimate low moisture levels; and thermal inertia (or thermal diffusivity) is used to estimate higher levels. The reflectance method appears promising for surface estimates of soil moisture, whereas the temperature method appears promising for estimates of near-subsurface (0 to 10 cm).

Blanchard, M. B.; Greeley, R.; Goettelman, R.

1974-01-01

340

Measurement scheduling for soil moisture sensing: From physical models to optimal control  

E-print Network

In this paper, we consider the problem of monitoring soil moisture evolution using a wireless network of in situ sensors. Continuously sampling moisture levels with these sensors incurs high-maintenance and energy consumption ...

Shuman, David I.

341

Using soil moisture and spatial yield patterns to identify subsurface flow pathways.  

PubMed

Subsurface soil water dynamics can influence crop growth and the fate of surface-applied fertilizers and pesticides. Recently, a method was proposed using only ground-penetrating radar (GPR) and digital elevation maps (DEMs) to identify locations where subsurface water converged into discrete pathways. For this study, the GPR protocol for identifying horizontal subsurface flow pathways was extended to a 3.2-ha field, uncertainty is discussed, and soil moisture and yield patterns are presented as confirming evidence of the extent of the subsurface flow pathways. Observed soil water contents supported the existence of discrete preferential funnel flow processes occurring near the GPR-identified preferential flow pathways. Soil moisture also played a critical role in the formation of corn (Zea mays L.) grain yield patterns with yield spatial patterns being similar for mild and severe drought conditions. A buffer zone protocol was introduced that allowed the impact of subsurface flow pathways on corn grain yield to be quantified. Results indicate that when a GPR-identified subsurface clay layer was within 2 m of the soil surface, there was a beneficial impact on yield during a drought year. Furthermore, the buffer zone analysis demonstrated that corn grain yields decreased as the horizontal distance from the GPR-identified subsurface flow pathways increased during a drought year. Averaged real-time soil moisture contents at 0.1 m also decreased with increasing distance from the GPR-identified flow pathways. This research suggests that subsurface flow pathways exist and influence soil moisture and corn grain yield patterns. PMID:15647558

Gish, T J; Walthall, C L; Daughtry, C S T; Kung, K-J S

2005-01-01

342

Radar backscattering sensitivity to soil moisture content of sugar beet fields  

NASA Astrophysics Data System (ADS)

The objective of this paper is to investigate the possibility of soil moisture retrieval from radar backscatter data in sugar beet fields. The analysis is based on a simulation study using two models capable of computing electromagnetic backscattering from a vegetated surface, viz. the model developed by Karam et al. and the model developed by Lang. First, we validate the models based on data from the AGRISCATT'88 field campaign, held in Flevoland, The Netherlands. The data collected during this campaign allows us to test the model predictions under different soil surface and canopy conditions and for different radar configurations. In general, both models are capable of mimicking the change in backscattering due changes in radar configuration and surface- vegetation characteristics. Next, both models are subjected to a sensitivity analysis with respect to different surface and canopy parameters. Based on this sensitivity analysis it is concluded that estimates of surface soil moisture content under a medium sugar beet cover (15 cm high crop) from L-band radar observations is only possible within 10% accuracy. For a fully developed sugar beet field (50 cm high crop), soil moisture retrieval is not possible.

Schoups, Gerrit; Troch, Peter A.; Verhoest, Niko

1997-12-01

343

Estimating soil moisture and the relationship with crop yield using surface temperature and vegetation index  

NASA Astrophysics Data System (ADS)

Soil moisture availability affects rainfed crop yield. Therefore, the development of methods for pre-harvest yield prediction is essential for the food security. A study was carried out to estimate regional crop yield using the Temperature Vegetation Dryness Index (TVDI). Triangular scatters from land surface temperature (LST) and enhanced vegetation index (EVI) space from MODIS (Moderate Resolution Imaging Spectroradiometer) were utilized to obtain TVDI and to estimate soil moisture availability. Then soybean and wheat crops yield was estimated on four agro-climatic zones of Argentine Pampas. TVDI showed a strong correlation with soil moisture measurements, with R2 values ranged from 0.61 to 0.83 and also it was in agreement with spatial pattern of soil moisture. Moreover, results showed that TVDI data can be used effectively to predict crop yield on the Argentine Pampas. Depending on the agro-climatic zone, R2 values ranged from 0.68 to 0.79 for soybean crop and 0.76 to 0.81 for wheat. The RMSE values were 366 and 380 kg ha-1 for soybean and they varied between 300 and 550 kg ha-1 in the case of wheat crop. When expressed as percentages of actual yield, the RMSE values ranged from 12% to 13% for soybean and 14% to 22% for wheat. The bias values indicated that the obtained models underestimated soybean and wheat yield. Accurate crop grain yield forecast using the developed regression models was achieved one to three months before harvest. In many cases the results were better than others obtained using only a vegetation index, showing the aptitude of surface temperature and vegetation index combination to reflect the crop water condition. Finally, the analysis of a wide range of soil moisture availability allowed us to develop a generalized model of crop yield and dryness index relationship which could be applicable in other regions and crops at regional scale.

Holzman, M. E.; Rivas, R.; Piccolo, M. C.

2014-05-01

344

Soil moisture estimation by Passive Distributed Temperature Sensing (DTS) using data assimilation  

NASA Astrophysics Data System (ADS)

Soil moisture is a key parameter for hydrology and climate processes modeling. However, the gap between footprint and point scale measurements limits not only the model performance but also the utilization of satellite soil moisture products. DTS (distributed temperature sensing) is a newly developed technique for measuring environmental temperature with high resolutions (spatial < 1m and temporal < 1 min), over cables kilometers in length. Soil with different moisture will present a different thermal diffusivity at a given net radiation. The thermal response of a soil column to incident net radiation depends on the soil's thermal properties, which in turn depends on the soil moisture content of the soil. Previous studies indicated that soil moisture information could be obtained from Passive DTS, where the soil temperature profile is measured with DTS. They also highlighted the challenges in retrieving soil moisture from passive DTS, notably the influence of uncertain cable depth and the non-uniqueness of the relationship between thermal conductivity and soil moisture. This study uses a combination of synthetic data, and real observations to compare three techniques to retrieve soil moisture from soil temperature profile information such as that obtained using DTS. We will demonstrate that both a dual state-parameter estimation (data assimilation) approach as well as an "inversion" approach can yield reasonable estimates of soil moisture. We will also show that including knowledge on the vertical profile in thermal properties improves estimation of both thermal properties and soil moisture. The accuracy of the temperature observations themselves also influences the RMSE in soil moisture and thermal properties. Cable depth could be estimated by either data assimilation or using the amplitudes of the daily temperature cycle, and the accuracy of the cable depth estimate is also determined by the temperature observation error.

Dong, Jianzhi; Steele-Dunne, Susan; van de Giesen, Nick

2014-05-01

345

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

NASA Astrophysics Data System (ADS)

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

Priesack, Eckart; Schuh, Max

2014-05-01

346

Plot- and watershed-scale soil moisture variability in a humid Piedmont watershed  

NASA Astrophysics Data System (ADS)

We investigate space-time dynamics of soil water through extreme drought and wet periods for a Mid-Atlantic Piedmont catchment. Soil moisture is a nonlinear control of soil nitrogen cycling processes, providing "hot spot" and "hot moment" dynamics that are not well modeled using time- or space-averaged conditions. We document spatial variation in near-surface soil moisture and examine relationships between mean and variance in soil moisture at plot and watershed scales. Riparian plot soil moisture spatial variance was significantly higher than the variance in uplands and was high relative to soil moisture variance reported by other studies. Plot soil moisture means closely followed a linear trend with the topographic wetness index. However, high within-plot variance obscured this relationship for experiments where smaller subsets of samples were used, emphasizing the importance of replicate plot measurements to account for fine-scale heterogeneity in soil moisture. We demonstrate the importance of these spatial-temporal patterns of soil moisture for estimates of hydrologic controls on biogeochemical cycling by showing that undersampling of fine-scale soil moisture variation is likely to lead to overestimation and underestimation of nitrification and denitrification, respectively.

Tague, C.; Band, L.; Kenworthy, S.; Tenebaum, D.

2010-12-01

347

Identifying sampling locations for field-scale soil moisture estimation using K-means clustering  

NASA Astrophysics Data System (ADS)

and understanding the impact of field-scale soil moisture patterns is currently limited by the time and resources required to do sufficient monitoring. This study uses K-means clustering to find critical sampling points to estimate field-scale near-surface soil moisture. Points within the field are clustered based upon topographic and soils data and the points representing the center of those clusters are identified as the critical sampling points. Soil moisture observations at 42 sites across the growing seasons of 4 years were collected several times per week. Using soil moisture observations at the critical sampling points and the number of points within each cluster, a weighted average is found and used as the estimated mean field-scale soil moisture. Field-scale soil moisture estimations from this method are compared to the rank stability approach (RSA) to find optimal sampling locations based upon temporal soil moisture data. The clustering approach on soil and topography data resulted in field-scale average moisture estimates that were as good or better than RSA, but without the need for exhaustive presampling of soil moisture. Using an electromagnetic inductance map as a proxy for soils data significantly improved the estimates over those obtained based on topography alone.

Van Arkel, Zach; Kaleita, Amy L.

2014-08-01

348

[Response of mineralization of dissolved organic carbon to soil moisture in paddy and upland soils in hilly red soil region].  

PubMed

Typical paddy and upland soils were collected from a hilly subtropical red-soil region. 14C-labeled dissolved organic carbon (14C-DOC) was extracted from the paddy and upland soils incorporated with 14C-labeled straw after a 30-day (d) incubation period under simulated field conditions. A 100-d incubation experiment (25 degrees C) with the addition of 14C-DOC to paddy and upland soils was conducted to monitor the dynamics of 14C-DOC mineralization under different soil moisture conditions [45%, 60%, 75%, 90%, and 105% of the field water holding capacity (WHC)]. The results showed that after 100 days, 28.7%-61.4% of the labeled DOC in the two types of soils was mineralized to CO2. The mineralization rates of DOC in the paddy soils were significantly higher than in the upland soils under all soil moisture conditions, owing to the less complex composition of DOC in the paddy soils. The aerobic condition was beneficial for DOC mineralization in both soils, and the anaerobic condition was beneficial for DOC accumulation. The biodegradability and the proportion of the labile fraction of the added DOC increased with the increase of soil moisture (45% -90% WHC). Within 100 days, the labile DOC fraction accounted for 80.5%-91.1% (paddy soil) and 66.3%-72.4% (upland soil) of the cumulative mineralization of DOC, implying that the biodegradation rate of DOC was controlled by the percentage of labile DOC fraction. PMID:24984493

Chen, Xiang-Bi; Wang, Ai-Hua; Hu, Le-Ning; Huang, Yuan; Li, Yang; He, Xun-Yang; Su, Yi-Rong

2014-03-01

349

Estimating Sahelian and East African soil moisture using the Normalized Difference Vegetation Index  

NASA Astrophysics Data System (ADS)

Rainfall gauge networks in Sub-Saharan Africa are inadequate for assessing Sahelian agricultural drought, hence satellite-based estimates of precipitation and vegetation indices such as the Normalized Difference Vegetation Index (NDVI) provide the main source of information for early warning systems. While it is common practice to translate precipitation into estimates of soil moisture, it is difficult to quantitatively compare precipitation and soil moisture estimates with variations in NDVI. In the context of agricultural drought early warning, this study quantitatively compares rainfall, soil moisture and NDVI using a simple statistical model to translate NDVI values into estimates of soil moisture. The model was calibrated using in-situ soil moisture observations from southwest Niger, and then used to estimate root zone soil moisture across the African Sahel from 2001-2012. We then used these NDVI-soil moisture estimates (NSM) to quantify agricultural drought, and compared our results with a precipitation-based estimate of soil moisture (the Antecedent Precipitation Index, API), calibrated to the same in-situ soil moisture observations. We also used in-situ soil moisture observations in Mali and Kenya to assess performance in other water-limited locations in sub Saharan Africa. The separate estimates of soil moisture were highly correlated across the semi-arid, West and Central African Sahel, where annual rainfall exhibits a uni-modal regime. We also found that seasonal API and NDVI-soil moisture showed high rank correlation with a crop water balance model, capturing known agricultural drought years in Niger, indicating that this new estimate of soil moisture can contribute to operational drought monitoring. In-situ soil moisture observations from Kenya highlighted how the rainfall-driven API needs to be recalibrated in locations with multiple rainy seasons (e.g., Ethiopia, Kenya, and Somalia). Our soil moisture estimates from NDVI, on the other hand, performed well in Niger, Mali and Kenya. This suggests that the NDVI-soil moisture relationship may be more robust across rainfall regimes than the API because the relationship between NDVI and plant available water is less reliant on local characteristics (e.g., infiltration, runoff, evaporation) than the relationship between rainfall and soil moisture.

McNally, A.; Funk, C.; Husak, G. J.; Michaelsen, J.; Cappelaere, B.; Demarty, J.; Pellarin, T.; Young, T. P.; Caylor, K. K.; Riginos, C.; Veblen, K. E.

2013-06-01

350

Assimilation of cosmic-ray neutron counts for updating of soil moisture and soil properties with application to irrigation scheduling  

NASA Astrophysics Data System (ADS)

The soil moisture is a good indicator of water stress during the irrigation scheduling. The cosmic-ray probes can measure the soil moisture at an intermediate scale through the interaction between the land surface neutron counts and soil moisture profile. This study investigated the assimilation of neutron measurements by a cosmic-ray probe for updating root zone soil moisture as well as soil properties (sand fraction, clay fraction and organic matter density) in Community Land Model (CLM) using the Local Ensemble Transform Kalman Filter (LETKF) for the real time optimal scheduling of irrigation. In order to map the soil moisture into measured neutron counts, the new COSMIC model is used as the non-linear measurement operator. The background uncertainties in CLM forecast were described by the uncertain model forcings and soil properties in the assimilation. Two groups of synthetic scenarios were studied for the optimization of real-time irrigation scheduling for fields of citrus trees: for the first group of scenarios soil texture was systematically finer with more clay and less sand than in the reference ('Wet bias') whereas for the second group of scenarios soil texture was coarser with less clay and more sand than in reality ('Dry bias'). The irrigation requirements were calculated based on the water deficit method using as input updated soil moisture contents after assimilation of neutron counts. For each of these two groups of scenarios seven scenarios, in which different combinations of ensemble weather forecast, data assimilation, soil properties optimization, were defined to estimate the irrigation requirement. Results show that the joint soil moisture and soil properties updating results overall in the best estimation of soil moisture, actual evapotranspiration and irrigation requirement. The characterization of soil moisture and soil properties can be improved after assimilation of cosmic-ray neutron counts. The biased soil properties result in wrong irrigation requirement. If soil parameters are also updated, the sensible and latent heat flux characterization is improved for biased soil properties.

Han, Xujun; Hendricks Franssen, Harrie-Jan; Ángel Jiménez Bello, Miguel; Rosolem, Rafael; Bogena, Heye; Martínez Alzamora, Fernando; Chanzy, André; Vereecken, Harry

2014-05-01

351

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

NASA Technical Reports Server (NTRS)

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

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

2015-01-01

352

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

NASA Astrophysics Data System (ADS)

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

Orth, René; Seneviratne, Sonia I.

2014-12-01

353

Automated system for generation of soil moisture products for agricultural drought assessment  

NASA Astrophysics Data System (ADS)

Drought is a frequently occurring disaster affecting lives of millions of people across the world every year. Several parameters, indices and models are being used globally to forecast / early warning of drought and monitoring drought for its prevalence, persistence and severity. Since drought is a complex phenomenon, large number of parameter/index need to be evaluated to sufficiently address the problem. It is a challenge to generate inpu