Soil moisture and precipitation monitoring in the South Fork experimental watershed during the Iowa flood studies (IFloodS)

USDA-ARS?s Scientific Manuscript database

Soil moisture estimates are valuable for hydrologic modeling and agricultural decision support. These estimates are typically produced via a combination of sparse in situ networks and remotely-sensed products or where sensory grids and quality satellite estimates are unavailable, through derived hy...

Feasibility analysis of using inverse modeling for estimating natural groundwater recharge from a large-scale soil moisture monitoring network

NASA Astrophysics Data System (ADS)

Wang, Tiejun; Franz, Trenton E.; Yue, Weifeng; Szilagyi, Jozsef; Zlotnik, Vitaly A.; You, Jinsheng; Chen, Xunhong; Shulski, Martha D.; Young, Aaron

2016-02-01

Despite the importance of groundwater recharge (GR), its accurate estimation still remains one of the most challenging tasks in the field of hydrology. In this study, with the help of inverse modeling, long-term (6 years) soil moisture data at 34 sites from the Automated Weather Data Network (AWDN) were used to estimate the spatial distribution of GR across Nebraska, USA, where significant spatial variability exists in soil properties and precipitation (P). To ensure the generality of this study and its potential broad applications, data from public domains and literature were used to parameterize the standard Hydrus-1D model. Although observed soil moisture differed significantly across the AWDN sites mainly due to the variations in P and soil properties, the simulations were able to capture the dynamics of observed soil moisture under different climatic and soil conditions. The inferred mean annual GR from the calibrated models varied over three orders of magnitude across the study area. To assess the uncertainties of the approach, estimates of GR and actual evapotranspiration (ETa) from the calibrated models were compared to the GR and ETa obtained from other techniques in the study area (e.g., remote sensing, tracers, and regional water balance). Comparison clearly demonstrated the feasibility of inverse modeling and large-scale (>104 km2) soil moisture monitoring networks for estimating GR. In addition, the model results were used to further examine the impacts of climate and soil on GR. The data showed that both P and soil properties had significant impacts on GR in the study area with coarser soils generating higher GR; however, different relationships between GR and P emerged at the AWDN sites, defined by local climatic and soil conditions. In general, positive correlations existed between annual GR and P for the sites with coarser-textured soils or under wetter climatic conditions. With the rapidly expanding soil moisture monitoring networks around the globe, this study may have important applications in aiding water resources management in different regions.

A ground based L-band radiometer for the monitoring of soil moisture in the region of Millbrook, New York, USA

USDA-ARS?s Scientific Manuscript database

A field experiment was performed in grassland near Millbrook, New York, using a NOAA Microwave Observation Facility, which comprises a network for in situ observation of soil moisture and a mobile dual polarized L band radiometer. During the field campaign, intensive measurements of L band brightnes...

Analysis of in situ resources for the Soil Moisture Active Passive Validation Experiments in 2015 and 2016

NASA Astrophysics Data System (ADS)

Cosh, M. H.; Jackson, T. J.; Colliander, A.; Bindlish, R.; McKee, L.; Goodrich, D. C.; Prueger, J. H.; Hornbuckle, B. K.; Coopersmith, E. J.; Holifield Collins, C.; Smith, J.

2016-12-01

With the launch of the Soil Moisture Active Passive Mission (SMAP) in 2015, a new era of soil moisture monitoring was begun. Soil moisture is available on a near daily basis at a 36 km resolution for the globe. But this dataset is only as valuable if its products are accurate and reliable. Therefore, in order to demonstrate the accuracy of the soil moisture product, NASA enacted an extensive calibration and validation program with many in situ soil moisture networks contributing data across a variety of landscape regimes. However, not all questions can be answered by these networks. As a result, two intensive field experiments were executed to provide more detailed reference points for calibration and validation. Multi-week field campaigns were conducted in Arizona and Iowa at the USDA Agricultural Research Service Walnut Gulch and South Fork Experimental Watersheds, respectively. Aircraft observations were made to provide a high resolution data product. Soil moisture, soil roughness and vegetation data were collected at high resolution to provide a downscaled dataset to compare against aircraft and satellite estimates.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

West Africa is greatly vulnerable, especially in terms of food sustainability. Mainly based on rainfed agriculture, the high variability of the rainy season strongly impacts the crop production driven by the soil water availability in the soil. To monitor this water availability, classical methods are based on daily precipitation measurements. However, the raingauge network suffers from the poor network density in Africa (1/10000km2). Alternatively, real-time satellite-derived precipitations can be used, but they are known to suffer from large uncertainties which produce significant error on crop yield estimations. The present study proposes to use root soil moisture rather than precipitation to evaluate crop yield variations. First, a local analysis of the spatiotemporal impact of water deficit on millet crop production in Niger was done, from in-situ soil moisture measurements (AMMA-CATCH/OZCAR (French Critical Zone exploration network)) and in-situ millet yield survey. Crop yield measurements were obtained for 10 villages located in the Niamey region from 2005 to 2012. The mean production (over 8 years) is 690 kg/ha, and ranges from 381 to 872 kg/ha during this period. Various statistical relationships based on soil moisture estimates were tested, and the most promising one (R>0.9) linked the 30-cm soil moisture anomalies from mid-August to mid-September (grain filling period) to the crop yield anomalies. Based on this local study, it was proposed to derive regional statistical relationships using 30-cm soil moisture maps over West Africa. The selected approach was to use a simple hydrological model, the Antecedent Precipitation Index (API), forced by real-time satellite-based precipitation (CMORPH, PERSIANN, TRMM3B42). To reduce uncertainties related to the quality of real-time rainfall satellite products, SMOS soil moisture measurements were assimilated into the API model through a Particular Filter algorithm. Then, obtained soil moisture anomalies were compared to 17 years of crop yield estimates from the FAOSTAT database (1998-2014). Results showed that the 30-cm soil moisture anomalies explained 89% of the crop yield variation in Niger, 72% in Burkina Faso, 82% in Mali and 84% in Senegal.

Establishing a Multi-spatial Wireless Sensor Network to Monitor Nitrate Concentrations in Soil Moisture

NASA Astrophysics Data System (ADS)

Haux, E.; Busek, N.; Park, Y.; Estrin, D.; Harmon, T. C.

2004-12-01

The use of reclaimed wastewater for irrigation in agriculture can be a significant source of nutrients, in particular nitrogen species, but its use raises concern for groundwater, riparian, and water quality. A 'smart' technology would have the ability to measure wastewater nutrients as they enter the irrigation system, monitor their transport in situ and optimally control inputs with little human intervention, all in real-time. Soil heterogeneity and economic issues require, however, a balance between cost and the spatial and temporal scales of the monitoring effort. Therefore, a wireless and embedded sensor network, deployed in the soil vertically across the horizon, is capable of collecting, processing, and transmitting sensor data. The network consists of several networked nodes or 'pylons', each outfitted with an array of sensors measuring humidity, temperature, precipitation, soil moisture, and aqueous nitrate concentrations. Individual sensor arrays are controlled by a MICA2 mote (Crossbow Technology Inc., San Jose, CA) programmed with TinyOS (University of California, Berkeley, CA) and a Stargate (Crossbow Technology Inc., San Jose, CA) base-station capable of GPRS for data transmission. Results are reported for the construction and testing of a prototypical pylon at the benchtop and in the field.

Landscape complexity and soil moisture variation in south Georgia, USA, for remote sensing applications

NASA Astrophysics Data System (ADS)

Giraldo, Mario A.; Bosch, David; Madden, Marguerite; Usery, Lynn; Kvien, Craig

2008-08-01

SummaryThis research addressed the temporal and spatial variation of soil moisture (SM) in a heterogeneous landscape. The research objective was to investigate soil moisture variation in eight homogeneous 30 by 30 m plots, similar to the pixel size of a Landsat Thematic Mapper (TM) or Enhanced Thematic Mapper plus (ETM+) image. The plots were adjacent to eight stations of an in situ soil moisture network operated by the United States Department of Agriculture-Agriculture Research Service USDA-ARS in Tifton, GA. We also studied five adjacent agricultural fields to examine the effect of different landuses/land covers (LULC) (grass, orchard, peanuts, cotton and bare soil) on the temporal and spatial variation of soil moisture. Soil moisture field data were collected on eight occasions throughout 2005 and January 2006 to establish comparisons within and among eight homogeneous plots. Consistently throughout time, analysis of variance (ANOVA) showed high variation in the soil moisture behavior among the plots and high homogeneity in the soil moisture behavior within them. A precipitation analysis for the eight sampling dates throughout the year 2005 showed similar rainfall conditions for the eight study plots. Therefore, soil moisture variation among locations was explained by in situ local conditions. Temporal stability geostatistical analysis showed that soil moisture has high temporal stability within the small plots and that a single point reading can be used to monitor soil moisture status for the plot within a maximum 3% volume/volume (v/v) soil moisture variation. Similarly, t-statistic analysis showed that soil moisture status in the upper soil layer changes within 24 h. We found statistical differences in the soil moisture between the different LULC in the agricultural fields as well as statistical differences between these fields and the adjacent 30 by 30 m plots. From this analysis, it was demonstrated that spatial proximity is not enough to produce similar soil moisture, since t-test's among adjacent plots with different LULCs showed significant differences. These results confirm that a remote sensing approach that considers homogeneous LULC landscape fragments can be used to identify landscape units of similar soil moisture behavior under heterogeneous landscapes. In addition, the in situ USDA-ARS network will serve better in remote sensing studies in which sensors with fine spatial resolution are evaluated. This study is a first step towards identifying landscape units that can be monitored using the single point reading of the USDA-ARS stations network.

Landscape complexity and soil moisture variation in south Georgia, USA, for remote sensing applications

USGS Publications Warehouse

Giraldo, M.A.; Bosch, D.; Madden, M.; Usery, L.; Kvien, Craig

2008-01-01

This research addressed the temporal and spatial variation of soil moisture (SM) in a heterogeneous landscape. The research objective was to investigate soil moisture variation in eight homogeneous 30 by 30 m plots, similar to the pixel size of a Landsat Thematic Mapper (TM) or Enhanced Thematic Mapper plus (ETM+) image. The plots were adjacent to eight stations of an in situ soil moisture network operated by the United States Department of Agriculture-Agriculture Research Service USDA-ARS in Tifton, GA. We also studied five adjacent agricultural fields to examine the effect of different landuses/land covers (LULC) (grass, orchard, peanuts, cotton and bare soil) on the temporal and spatial variation of soil moisture. Soil moisture field data were collected on eight occasions throughout 2005 and January 2006 to establish comparisons within and among eight homogeneous plots. Consistently throughout time, analysis of variance (ANOVA) showed high variation in the soil moisture behavior among the plots and high homogeneity in the soil moisture behavior within them. A precipitation analysis for the eight sampling dates throughout the year 2005 showed similar rainfall conditions for the eight study plots. Therefore, soil moisture variation among locations was explained by in situ local conditions. Temporal stability geostatistical analysis showed that soil moisture has high temporal stability within the small plots and that a single point reading can be used to monitor soil moisture status for the plot within a maximum 3% volume/volume (v/v) soil moisture variation. Similarly, t-statistic analysis showed that soil moisture status in the upper soil layer changes within 24 h. We found statistical differences in the soil moisture between the different LULC in the agricultural fields as well as statistical differences between these fields and the adjacent 30 by 30 m plots. From this analysis, it was demonstrated that spatial proximity is not enough to produce similar soil moisture, since t-test's among adjacent plots with different LULCs showed significant differences. These results confirm that a remote sensing approach that considers homogeneous LULC landscape fragments can be used to identify landscape units of similar soil moisture behavior under heterogeneous landscapes. In addition, the in situ USDA-ARS network will serve better in remote sensing studies in which sensors with fine spatial resolution are evaluated. This study is a first step towards identifying landscape units that can be monitored using the single point reading of the USDA-ARS stations network. ?? 2008 Elsevier B.V.

Recent advances in near-surface moisture monitoring using commercial microwave links in Tel-Aviv University

NASA Astrophysics Data System (ADS)

Alpert, Pinhas; David, Noam; Messer, Hagit

2015-04-01

The propagation of electromagnetic radiation in the lower atmosphere, at centimeter wavelengths, is impaired by atmospheric conditions. Absorption and scattering of the radiation, at frequencies of tens of GHz, are directly related to the atmospheric phenomena, primarily precipitation, oxygen, mist, fog and water vapor. As was recently shown, wireless communication networks supply high resolution precipitation measurements at ground level while often being situated in flood prone areas, covering large parts of these hazardous regions. On the other hand, at present, there are no satisfactory real time flash flood warning facilities found to cope well with this phenomenon. I will exemplify the flash flood warning potential of the commercial wireless communication system for two different semi-arid region cases when floods occurred in the Judean desert and in the northern Negev in Israel. In addition, I will review our recent improvements in monitoring rainfall as well as other-than-rain phenomena like, atmospheric moisture. Special focus on fog monitoring potential will be highlighted. References: N. David, O. Sendik, H. Messer and P. Alpert, "Cellular network infrastructure- the future of fog monitoring?", BAMS, (in press, 2015). N. David, P. Alpert and H. Messer, "The potential of cellular network infrastructures for sudden rainfall monitoring in dry climate regions", Atmospheric Research, 131, 13-21, 2013.

Soil moisture and plant canopy temperature sensing for irrigation application in cotton

USDA-ARS?s Scientific Manuscript database

A wireless sensor network was deployed in a cotton field to monitor soil water status for irrigation. The network included two systems, a Decagon system and a microcontroller-based system. The Decagon system consists of soil volumetric water-content sensors, wireless data loggers, and a central data...

The Raam regional soil moisture monitoring network in the Netherlands

NASA Astrophysics Data System (ADS)

Benninga, Harm-Jan F.; Carranza, Coleen D. U.; Pezij, Michiel; van Santen, Pim; van der Ploeg, Martine J.; Augustijn, Denie C. M.; van der Velde, Rogier

2018-01-01

We have established a soil moisture profile monitoring network in the Raam region in the Netherlands. This region faces water shortages during summers and excess of water during winters and after extreme precipitation events. Water management can benefit from reliable information on the soil water availability and water storing capacity in the unsaturated zone. In situ measurements provide a direct source of information on which water managers can base their decisions. Moreover, these measurements are commonly used as a reference for the calibration and validation of soil moisture content products derived from earth observations or obtained by model simulations. Distributed over the Raam region, we have equipped 14 agricultural fields and 1 natural grass field with soil moisture and soil temperature monitoring instrumentation, consisting of Decagon 5TM sensors installed at depths of 5, 10, 20, 40 and 80 cm. In total, 12 stations are located within the Raam catchment (catchment area of 223 km2), and 5 of these stations are located within the closed sub-catchment Hooge Raam (catchment area of 41 km2). Soil-specific calibration functions that have been developed for the 5TM sensors under laboratory conditions lead to an accuracy of 0.02 m3 m-3. The first set of measurements has been retrieved for the period 5 April 2016-4 April 2017. In this paper, we describe the Raam monitoring network and instrumentation, the soil-specific calibration of the sensors, the first year of measurements, and additional measurements (soil temperature, phreatic groundwater levels and meteorological data) and information (elevation, soil physical characteristics, land cover and a geohydrological model) available for performing scientific research. The data are available at https://doi.org/10.4121/uuid:dc364e97-d44a-403f-82a7-121902deeb56.

ERT to aid in WSN based early warning system for landslides

NASA Astrophysics Data System (ADS)

T, H.

2017-12-01

Amrita University's landslide monitoring and early warning system using Wireless Sensor Networks (WSN) consists of heterogeneous sensors like rain gauge, moisture sensor, piezometer, geophone, inclinometer, tilt meter etc. The information from the sensors are accurate and limited to that point. In order to monitor a large area, ERT can be used in conjunction with WSN technology. To accomplish the feasibility of ERT in landslide early warning along with WSN technology, we have conducted experiments in Amrita's landslide laboratory setup. The experiment was aimed to simulate landslide, and monitor the changes happening in the soil using moisture sensor and ERT. Simulating moisture values from resistivity measurements to a greater accuracy can help in landslide monitoring for large areas. For accomplishing the same we have adapted two mathematical approaches, 1) Regression analysis between resistivity measurements and actual moisture values from moisture sensor, and 2) Using Waxman Smith model to simulate moisture values from resistivity measurements. The simulated moisture values from Waxman Smith model is compared with the actual moisture values and the Mean Square Error (MSE) is found to be 46.33. Regression curve is drawn for the resistivity vs simulated moisture values from Waxman model, and it is compared with the regression curve of actual model, which is shown in figure-1. From figure-1, it is clear that there the regression curve from actual moisture values and the regression curve from simulated moisture values, follow the similar pattern and there is a small difference between them. Moisture values can be simulated to a greater accuracy using actual regression equation, but the limitation is that, regression curves will differ for different sites and different soils. Regression equation from actual moisture values can be used, if we have conducted experiment in the laboratory for a particular soil sample, otherwise with the knowledge of soil properties, Waxman model can be used to simulate moisture values. The promising results assure that, ERT measurements when used in conjunction with WSN technique, vital paramters triggering landslides like moisture can be simulated for a large area, which will help in providing early warning for large areas.

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

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

Gravity changes, soil moisture and data assimilation

NASA Astrophysics Data System (ADS)

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

2003-04-01

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

Reconstruction of FY-3B/MWRI soil moisture using an artificial neural network based on reconstructed MODIS optical products over the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Cui, Y.; Long, D.; Hong, Y.; Zeng, C.; Han, Z.

2016-12-01

Reconstruction of FY-3B/MWRI soil moisture using an artificial neural network based on reconstructed MODIS optical products over the Tibetan Plateau Yaokui Cui, Di Long, Yang Hong, Chao Zeng, and Zhongying Han State Key Laboratory of Hydroscience and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China Abstract: Soil moisture is a key variable in the exchange of water and energy between the land surface and the atmosphere, especially over the Tibetan Plateau (TP) which is climatically and hydrologically sensitive as the world's third pole. Large-scale consistent and continuous soil moisture datasets are of importance to meteorological and hydrological applications, such as weather forecasting and drought monitoring. The Fengyun-3B Microwave Radiation Imager (FY-3B/MWRI) soil moisture product is one of relatively new passive microwave products. The FY-3B/MWRI soil moisture product is reconstructed using the back-propagation neural network (BP-NN) based on reconstructed MODIS products, i.e., LST, NDVI, and albedo using different gap-filling methods. The reconstruction method of generating the soil moisture product not only considers the relationship between the soil moisture and the NDVI, LST, and albedo, but also the relationship between the soil moisture and the four-dimensional variation using the longitude, latitude, DEM and day of year (DOY). Results show that the soil moisture could be well reconstructed with R2 larger than 0.63, and RMSE less than 0.1 cm3 cm-3 and bias less than 0.07 cm3 cm-3 for both frozen and unfrozen periods, compared with in-situ measurements in the central TP. The reconstruction method is subsequently applied to generate spatially consistent and temporally continuous surface soil moisture over the TP. The reconstructed FY-3B/MWRI soil moisture product could be valuable in studying meteorology, hydrology, and agriculture over the TP. Keywords: FY-3B/MWRI; Soil moisture; Reconstruction; Tibetan Plateau

Toward a Continental-Scale Mesonet: USDA National Resources Conservation Service SCAN and SNOTEL System

NASA Astrophysics Data System (ADS)

Schaffer, G.; Marks, D.

2004-12-01

Since 1978 snow deposition and SWE in the inter-mountain western US have been monitored by the NRCS SNOTEL (SNOwpack TELemetry) system. This revolutionary network utilizes Meteorburst technology to telemeter data back to a central location in near real-time. With a pilot program starting in 1991, NRCS introduced SCAN (Soil Climate and Analysis Network) adding a focus on soil moisture and climate in regions outside the intermountain west. In the mid-1990's SNOTEL sites began to be augmented to match the full climate instrumentation (air temperature, humidity, solar radiation, wind, and soil moisture and temperature in addition to precipitation, snow depth and SWE) of the SCAN system. At present there are nearly 700 SNOTEL sites in 12 states in the western US and Alaska, and over 100 SCAN sites in 40 states, Puerto Rico, and several foreign countries. Though SNOTEL was originally a western snow-monitoring network, differences between SCAN and SNOTEL have largely disappeared. The combined SNOTEL/SCAN system provides a continental-scale mesonet to support river basin to continental scale hydro-climatic analysis. The system is flexible and based on off-the-shelf data recording technology, allowing instrumentation, sampling and averaging intervals to be specified by site conditions, issues, or scientific questions. Because of the NRCS data management structure, all sites have active telemetery and provide near real-time access to data through the internet. An ongoing research program is directed to improved instrumentation for measuring precipitation, snow depth and SWE, and soil moisture and temperature. Future directions include expansion of the network to be more comprehensive, and to develop focused monitoring efforts to more effectively observe elevational and regional gradients, and to capture high intensity hydro-climatic events such as potential flooding from convective storms and rain-on-snow.

Development of a Coordinated National Soil Moisture Network: A Pilot Study

NASA Astrophysics Data System (ADS)

Lucido, J. M.; Quiring, S. M.; Verdin, J. P.; Pulwarty, R. S.; Baker, B.; Cosgrove, B.; Escobar, V. M.; Strobel, M.

2014-12-01

Soil moisture data is critical for accurate drought prediction, flood forecasting, climate modeling, prediction of crop yields and water budgeting. However, soil moisture data are collected by many agencies and organizations in the United States using a variety of instruments and methods for varying applications. These data are often distributed and represented in disparate formats, posing significant challenges for use. In recognition of these challenges, the President's Climate Action Plan articulated the need for a coordinated national soil moisture network. In response to this action plan, a team led by the National Integrated Drought Information System has begun to develop a framework for this network and has instituted a proof-of-concept pilot study. This pilot is located in the south-central plains of the US, and will serve as a reference architecture for the requisite data systems and inform the design of the national network. The pilot comprises both in-situ and modeled soil moisture datasets (historical and real-time) and will serve the following use cases: operational drought monitoring, experimental land surface modeling, and operational hydrological modeling. The pilot will be implemented using a distributed network design in order to serve dispersed data in real-time directly from data providers. Standard service protocols will be used to enable future integration with external clients. The pilot network will additionally contain a catalog of data sets and web service endpoints, which will be used to broker web service calls. A mediation and aggregation service will then intelligently request, compile, and transform the distributed datasets from their native formats into a standardized output. This mediation framework allows data to be hosted and maintained locally by the data owners while simplifying access through a single service interface. These data services will then be used to create visualizations, for example, views of the current soil moisture conditions compared to historical baselines via a map-based web application. This talk will comprise an overview of the pilot design and implementation, a discussion of strategies for integrating in-situ and modeled soil moisture data sets as well as lessons learned during the course of the pilot.

Strengths and weaknesses of temporal stability analysis for monitoring and estimating grid-mean soil moisture in a high-intensity irrigated agricultural landscape

NASA Astrophysics Data System (ADS)

Ran, Youhua; Li, Xin; Jin, Rui; Kang, Jian; Cosh, Michael H.

2017-01-01

Monitoring and estimating grid-mean soil moisture is very important for assessing many hydrological, biological, and biogeochemical processes and for validating remotely sensed surface soil moisture products. Temporal stability analysis (TSA) is a valuable tool for identifying a small number of representative sampling points to estimate the grid-mean soil moisture content. This analysis was evaluated and improved using high-quality surface soil moisture data that were acquired by a wireless sensor network in a high-intensity irrigated agricultural landscape in an arid region of northwestern China. The performance of the TSA was limited in areas where the representative error was dominated by random events, such as irrigation events. This shortcoming can be effectively mitigated by using a stratified TSA (STSA) method, proposed in this paper. In addition, the following methods were proposed for rapidly and efficiently identifying representative sampling points when using TSA. (1) Instantaneous measurements can be used to identify representative sampling points to some extent; however, the error resulting from this method is significant when validating remotely sensed soil moisture products. Thus, additional representative sampling points should be considered to reduce this error. (2) The calibration period can be determined from the time span of the full range of the grid-mean soil moisture content during the monitoring period. (3) The representative error is sensitive to the number of calibration sampling points, especially when only a few representative sampling points are used. Multiple sampling points are recommended to reduce data loss and improve the likelihood of representativeness at two scales.

Spatial-temporal variability of soil moisture and its estimation across scales

NASA Astrophysics Data System (ADS)

Brocca, L.; Melone, F.; Moramarco, T.; Morbidelli, R.

2010-02-01

The soil moisture is a quantity of paramount importance in the study of hydrologic phenomena and soil-atmosphere interaction. Because of its high spatial and temporal variability, the soil moisture monitoring scheme was investigated here both for soil moisture retrieval by remote sensing and in view of the use of soil moisture data in rainfall-runoff modeling. To this end, by using a portable Time Domain Reflectometer, a sequence of 35 measurement days were carried out within a single year in seven fields located inside the Vallaccia catchment, central Italy, with area of 60 km2. Every sampling day, soil moisture measurements were collected at each field over a regular grid with an extension of 2000 m2. The optimization of the monitoring scheme, with the aim of an accurate mean soil moisture estimation at the field and catchment scale, was addressed by the statistical and the temporal stability. At the field scale, the number of required samples (NRS) to estimate the field-mean soil moisture within an accuracy of 2%, necessary for the validation of remotely sensed soil moisture, ranged between 4 and 15 for almost dry conditions (the worst case); at the catchment scale, this number increased to nearly 40 and it refers to almost wet conditions. On the other hand, to estimate the mean soil moisture temporal pattern, useful for rainfall-runoff modeling, the NRS was found to be lower. In fact, at the catchment scale only 10 measurements collected in the most "representative" field, previously determined through the temporal stability analysis, can reproduce the catchment-mean soil moisture with a determination coefficient, R2, higher than 0.96 and a root-mean-square error, RMSE, equal to 2.38%. For the "nonrepresentative" fields the accuracy in terms of RMSE decreased, but similar R2 coefficients were found. This insight can be exploited for the sampling in a generic field when it is sufficient to know an index of soil moisture temporal pattern to be incorporated in conceptual rainfall-runoff models. The obtained results can address the soil moisture monitoring network design from which a reliable soil moisture temporal pattern at the catchment scale can be derived.

A multi-scale automatic observatory of soil moisture and temperature served for satellite product validation in Tibetan Plateau

NASA Astrophysics Data System (ADS)

Tang, S.; Dong, L.; Lu, P.; Zhou, K.; Wang, F.; Han, S.; Min, M.; Chen, L.; Xu, N.; Chen, J.; Zhao, P.; Li, B.; Wang, Y.

2016-12-01

Due to the lack of observing data which match the satellite pixel size, the inversion accuracy of satellite products in Tibetan Plateau(TP) is difficult to be evaluated. Hence, the in situ observations are necessary to support the calibration and validation activities. Under the support of the Third Tibetan Plateau Atmospheric Scientific Experiment (TIPEX-III) projec a multi-scale automatic observatory of soil moisture and temperature served for satellite product validation (TIPEX-III-SMTN) were established in Tibetan Plateau. The observatory consists of two regional scale networks, including the Naqu network and the Geji network. The Naqu network is located in the north of TP, and characterized by alpine grasslands. The Geji network is located in the west of TP, and characterized by marshes. Naqu network includes 33 stations, which are deployed in a 75KM*75KM region according to a pre-designed pattern. At Each station, soil moisture and temperature are measured by five sensors at five soil depths. One sensor is vertically inserted into 0 2 cm depth to measure the averaged near-surface soil moisture and temperature. The other four sensors are horizontally inserted at 5, 10, 20, and 30 cm depths, respectively. The data are recorded every 10 minutes. A wireless transmission system is applied to transmit the data in real time, and a dual power supply system is adopted to keep the continuity of the observation. The construction of Naqu network has been accomplished in August, 2015, and Geji network will be established before Oct., 2016. Observations acquired from TIPEX-III-SMTN can be used to validate satellite products with different spatial resolution, and TIPEX-III-SMTN can also be used as a complementary of the existing similar networks in this area, such as CTP-SMTMN (the multiscale Soil Moistureand Temperature Monitoring Network on the central TP) . Keywords: multi-scale soil moisture soil temperature, Tibetan Plateau Acknowledgments: This work was jointly supported by CMA Special Fund for Scientific Research in the Public Interest (Grant No. GYHY201406001, GYHY201206008-01), and Climate change special fund (QHBH2014)'

On the advance of non-invasive techniques implementation for monitoring moisture distribution in cultural heritage: a case study

NASA Astrophysics Data System (ADS)

Inmaculada Martínez Garrido, María; Gómez Heras, Miguel; Fort González, Rafael; Valles Iriso, Javier; José Varas Muriel, María

2015-04-01

This work presents a case study developed in San Juan Bautista church in Talamanca de Jarama (12th -16th Century), which have been selected as an example of a historical church with a complex construction with subsequent combination of architectural styles and building techniques and materials. These materials have a differential behavior under the influence of external climatic conditions and constructive facts. Many decay processes related to humidity are affecting the building's walls and also have influence in the environmental dynamics inside the building. A methodology for monitoring moisture distribution on stone and masonry walls and floors was performed with different non-invasive techniques as thermal imaging, wireless sensor networks (WSN), portable moisture meter, electrical resistivity tomography (ERT) and ground-penetrating radar (GPR), in order to the evaluate the effectiveness of these techniques for the knowledge of moisture distribution inside the walls and the humidity origin. North and south oriented sections, both on walls and floors, were evaluated and also a general inspection in the church was carried out with different non-invasive techniques. This methodology implies different monitoring stages for a complete knowledge of the implication of outdoors and indoors conditions on the moisture distribution. Each technique is evaluated according to its effectiveness in the detection of decay processes and maintenance costs. Research funded by Geomateriales (S2013/MIT-2914) and Deterioration of stone materials in the interior of historic buildings as a result induced variation of its microclimate (CGL2011-27902) projects. The cooperation received from the Complutense University of Madrid's Research Group Alteración y Conservación de los Materiales Pétreos del Patrimonio (ref. 921349), the Laboratory Network in Science and Technology for Heritage Conservation (RedLabPat, CEI Moncloa) and the Diocese of Alcalá is gratefully acknowledged. MI Martínez-Garrido and M. Gomez-Heras are funded by Moncloa Campus of International Excellence (UPM-UCM, CSIC) PICATA fellowships.

Multi-Scale Soil Moisture Monitoring and Modeling at ARS Watersheds for NASA's Soil Moisture Active Passive (SMAP) Calibration/Validation Mission

NASA Astrophysics Data System (ADS)

Coopersmith, E. J.; Cosh, M. H.

2014-12-01

NASA's SMAP satellite, launched in November of 2014, produces estimates of average volumetric soil moisture at 3, 9, and 36-kilometer scales. The calibration and validation process of these estimates requires the generation of an identically-scaled soil moisture product from existing in-situ networks. This can be achieved via the integration of NLDAS precipitation data to perform calibration of models at each ­in-situ gauge. In turn, these models and the gauges' volumetric estimations are used to generate soil moisture estimates at a 500m scale throughout a given test watershed by leveraging, at each location, the gauge-calibrated models deemed most appropriate in terms of proximity, calibration efficacy, soil-textural similarity, and topography. Four ARS watersheds, located in Iowa, Oklahoma, Georgia, and Arizona are employed to demonstrate the utility of this approach. The South Fork watershed in Iowa represents the simplest case - the soil textures and topography are relative constants and the variability of soil moisture is simply tied to the spatial variability of precipitation. The Little Washita watershed in Oklahoma adds soil textural variability (but remains topographically simple), while the Little River watershed in Georgia incorporates topographic classification. Finally, the Walnut Gulch watershed in Arizona adds a dense precipitation network to be employed for even finer-scale modeling estimates. Results suggest RMSE values at or below the 4% volumetric standard adopted for the SMAP mission are attainable over the desired spatial scales via this integration of modeling efforts and existing in-situ networks.

Integrating Enhanced Grace Terrestrial Water Storage Data Into the U.S. and North American Drought Monitors

NASA Technical Reports Server (NTRS)

Housborg, Rasmus; Rodell, Matthew

2010-01-01

NASA's Gravity Recovery and Climate Experiment (GRACE) satellites measure time variations nf the Earth's gravity field enabling reliable detection of spatio-temporal variations in total terrestrial water storage (TWS), including ground water. The U.S. and North American Drought Monitors are two of the premier drought monitoring products available to decision-makers for assessing and minimizing drought impacts, but they rely heavily on precipitation indices and do not currently incorporate systematic observations of deep soil moisture and groundwater storage conditions. Thus GRACE has great potential to improve the Drought Monitors hy filling this observational gap. Horizontal, vertical and temporal disaggregation of the coarse-resolution GRACE TWS data has been accomplished by assimilating GRACE TWS anomalies into the Catchment Land Surface Model using ensemble Kalman smoother. The Drought Monitors combine several short-term and long-term drought indices and indicators expressed in percentiles as a reference to their historical frequency of occurrence for the location and time of year in question. To be consistent, we are in the process of generating a climatology of estimated soil moisture and ground water based on m 60-year Catchment model simulation which will subsequently be used to convert seven years of GRACE assimilated fields into soil moisture and groundwater percentiles. for systematic incorporation into the objective blends that constitute Drought Monitor baselines. At this stage we provide a preliminary evaluation of GRACE assimilated Catchment model output against independent datasets including soil moisture observations from Aqua AMSR-E and groundwater level observations from the U.S. Geological Survey's Groundwater Climate Response Network.

Soil moisture from ground-based networks and the North American Land Data Assimilation System Phase 2 Model: Are the right values somewhere in between?

NASA Astrophysics Data System (ADS)

Caldwell, T. G.; Scanlon, B. R.; Long, D.; Young, M.

2013-12-01

Soil moisture is the most enigmatic component of the water balance; nonetheless, it is inherently tied to every component of the hydrologic cycle, affecting the partitioning of both water and energy at the land surface. However, our ability to assess soil water storage capacity and status through measurement or modeling is challenged by error and scale. Soil moisture is as difficult to measure as it is to model, yet land surface models and remote sensing products require some means of validation. Here we compare the three major soil moisture monitoring networks across the US, including the USDA Soil Climate Assessment Network (SCAN), NOAA Climate Reference Network (USCRN), and Cosmic Ray Soil Moisture Observing System (COSMOS) to the soil moisture simulated using the North American Land Data Assimilation System (NLDAS) Phase 2. NLDAS runs in near real-time on a 0.125° (12 km) grid over the US, producing ensemble model outputs of surface fluxes and storage. We focus primarily on soil water storage (SWS) in the upper 0-0.1 m zone from the Noah Land Surface Model and secondarily on the effects of error propagation from atmospheric forcing and soil parameterization. No scaling of the observational data was attempted. We simply compared the extracted time series at the nearest grid center from NLDAS and assessed the results by standard model statistics including root mean square error (RMSE) and mean bias estimate (MBE) of the collocated ground station. Observed and modeled data were compared at both hourly and daily mean coordinated universal time steps. In all, ~300 stations were used for 2012. SCAN sites were found to be particularly troublesome at 5- and 10-cm depths. SWS at 163 SCAN sites departed significantly from Noah with a mean R2 of 0.38 × 0.0.23, a mean RMSE of 14.9 mm with a MBE of -13.5 mm. SWS at 111 USCRN sites has a mean R2 of 0.53 × 0.20, a mean RMSE of 8.2 mm with a MBE of -3.7 mm relative to Noah. Finally, 62 COSMOS sites, the instrument with the largest measurement footprint (0.03 km2), we calculated a mean R2 of 0.53 × 0.21, a mean RMSE of 9.7 mm with a MBE of -0.3 mm. Forcing errors and textural misclassifications correlate well with model biases, indicating that scale and structural errors are equally present in NLDAS. Scaling issues aside, these confounding errors make cal/val missions, such as NASA's upcoming Soil Moisture Active Passive (SMAP) mission, problematic without significant quality control and maintenance of for our monitoring networks. Land surface models, such as NLDAS-2, may provide valuable insight into our soil moisture data and somewhere in between the real values likely exist.

Subsurface material identification and sensor selection

NASA Astrophysics Data System (ADS)

T, H.; Reghunadh, R.; Ramesh, M. V.

2017-12-01

In India, most of the landslides occur during monsoon season and causes huge loss of life and property. Design of an early warning system for highly landslide prone area will reduce losses to a great extent. The in-situ monitoring systems needs deployment of several sensors inside a borehole for monitoring a particular slope. Amrita Center for Wireless Networks and Applications (AmritaWNA), Amrita University has designed, developed and deployed a Wireless Sensor Network (WSN) for real time landslide monitoring using geotechnical instruments and sensors like rain gauge, moisture sensor, piezometer, strain gauge, tilt meter and geophone inside a Deep Earth Probe (DEP) at different locations. These sensors provide point measurements of the subsurface at a higher accuracy. Every landslide prone terrain is unique with respect to its geology, hydrological conditions, meteorological conditions, velocity of movement etc. The decision of installing different geotechnical instruments in a landslide prone terrain is a crucial step to be considered. Rain gauge, moisture sensor, and piezometer are usually used in clay rich areas to sense the moisture and pore pressure values. Geophone and Crack meter are instruments used in rocky areas to monitor cracks and vibrations associated with a movement. Inclinometer and Strain gauge are usually placed inside a casing and can be used in both rocky and soil areas. In order to place geotechnical instruments and sensors at appropriate places Electrical Resistivity Tomography (ERT) method can be used. Variation in electrical resistivity values indicate the changes in composition, layer thickness, or contaminant levels. The derived true resistivity image can be used for identifying the type of materials present in the subsurface at different depths. We have used this method for identifying the type of materials present in our site at Chandmari (Sikkim). Fig 1 shows the typical resistivity values of a particular area in Chandmari site. The results shows that the area has more clay so the placement of moisture sensor and piezometer are required instead of placing geophone, crack meter etc.

Validation and reconstruction of FY-3B/MWRI soil moisture using an artificial neural network based on reconstructed MODIS optical products over the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Cui, Yaokui; Long, Di; Hong, Yang; Zeng, Chao; Zhou, Jie; Han, Zhongying; Liu, Ronghua; Wan, Wei

2016-12-01

Soil moisture is a key variable in the exchange of water and energy between the land surface and the atmosphere, especially over the Tibetan Plateau (TP) which is climatically and hydrologically sensitive as the Earth's 'third pole'. Large-scale spatially consistent and temporally continuous soil moisture datasets are of great importance to meteorological and hydrological applications, such as weather forecasting and drought monitoring. The Fengyun-3B Microwave Radiation Imager (FY-3B/MWRI) soil moisture product is a relatively new passive microwave product, with the satellite being launched on November 5, 2010. This study validates and reconstructs FY-3B/MWRI soil moisture across the TP. First, the validation is performed using in situ measurements within two in situ soil moisture measurement networks (1° × 1° and 0.25° × 0.25°), and also compared with the Essential Climate Variable (ECV) soil moisture product from multiple active and passive satellite soil moisture products using new merging procedures. Results show that the ascending FY-3B/MWRI product outperforms the descending product. The ascending FY-3B/MWRI product has almost the same correlation as the ECV product with the in situ measurements. The ascending FY-3B/MWRI product has better performance than the ECV product in the frozen season and under the lower NDVI condition. When the NDVI is higher in the unfrozen season, uncertainty in the ascending FY-3B/MWRI product increases with increasing NDVI, but it could still capture the variability in soil moisture. Second, the FY-3B/MWRI soil moisture product is subsequently reconstructed using the back-propagation neural network (BP-NN) based on reconstructed MODIS products, i.e., LST, NDVI, and albedo. The reconstruction method of generating the soil moisture product not only considers the relationship between the soil moisture and NDVI, LST, and albedo, but also the relationship between the soil moisture and four-dimensional variations using the longitude, latitude, DEM and day of year (DOY). Results show that the soil moisture could be well reconstructed with R2 higher than 0.56, RMSE less than 0.1 cm3 cm-3, and Bias less than 0.07 cm3 cm-3 for both frozen and unfrozen seasons, compared with the in situ measurements at the two networks. Third, the reconstruction method is applied to generate surface soil moisture over the TP. Both original and reconstructed FY-3B/MWRI soil moisture products could be valuable in studying meteorology, hydrology, and ecosystems over the TP.

Regional Evapotranspiration Estimation by Using Wireless Sap Flow and Soil Moisture Measurement Systems

NASA Astrophysics Data System (ADS)

Kuo, C.; Yu, P.; Yang, T.; Davis, T. W.; Liang, X.; Tseng, C.; Cheng, C.

2011-12-01

The objective of this study proposed herein is to estimate regional evapotranspiration via sap flow and soil moisture measurements associated with wireless sensor network in the field. Evapotranspiration is one of the important factors in water balance computation. Pan evaporation collected from the meteorological station can only be accounted as a single-point scale measurement rather than the water loss of the entire region. Thus, we need a multiple-site measurement for understanding the regional evapotranspiration. Applying sap flow method with self-made probes, we could calculate transpiration. Soil moisture measurement was used to monitor the daily soil moisture variety for evaporation. Sap flow and soil moisture measurements in multiple sites are integrated by using wireless sensor network (WSN). Then, the measurement results of each site were scaled up and combined into the regional evapotranspiration. This study used thermal dissipation method to measure sap flow in trees to represent the plant transpiration. Sap flow was measured by using the self-made sap probes which needed to be calibrated before setting up at the observation field. Regional transpiration was scaled up through the Leaf Area Index (LAI). The LAI of regional scale was from the MODIS image calculated at 1km X 1km grid size. The soil moistures collected from areas outside the distributing area of tree roots and tree canopy were used to represent the evaporation. The observation was undertaken to collect soil moisture variety from five different soil depths of 10, 20, 30, 40 and 50 cm respectively. The regional evaporation can be estimated by averaging the variation of soil moisture from each site within the region. The result data measured by both sap flow and soil moisture measurements of each site were collected through the wireless sensor network. The WSN performs the functions of P2P and mesh networking. That can collect data in multiple locations simultaneously and has less power consumption. WSN is the best way for collecting sap flow and soil moisture data in this study. Since the data were collected through the radio in the field, there may have some noise randomly. The weighted least-squares method was used to filter the raw data. Through collecting the observation data by WSN and transferring them into regional scale, we could get regional evapotranspiration.

Multi-model perspectives and inter-comparison of soil moisture and evapotranspiration in East Africa—an application of Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS)

NASA Astrophysics Data System (ADS)

Pervez, M. S.; McNally, A.; Arsenault, K. R.

2017-12-01

Convergence of evidence from different agro-hydrologic sources is particularly important for drought monitoring in data sparse regions. In Africa, a combination of remote sensing and land surface modeling experiments are used to evaluate past, present and future drought conditions. The Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS) routinely simulates daily soil moisture, evapotranspiration (ET) and other variables over Africa using multiple models and inputs. We found that Noah 3.3, Variable Infiltration Capacity (VIC) 4.1.2, and Catchment Land Surface Model based FLDAS simulations of monthly soil moisture percentile maps captured concurrent drought and water surplus episodes effectively over East Africa. However, the results are sensitive to selection of land surface model and hydrometeorological forcings. We seek to identify sources of uncertainty (input, model, parameter) to eventually improve the accuracy of FLDAS outputs. In absence of in situ data, previous work used European Space Agency Climate Change Initiative Soil Moisture (CCI-SM) data measured from merged active-passive microwave remote sensing to evaluate FLDAS soil moisture, and found that during the high rainfall months of April-May and November-December Noah-based soil moisture correlate well with CCI-SM over the Greater Horn of Africa region. We have found good correlations (r>0.6) for FLDAS Noah 3.3 ET anomalies and Operational Simplified Surface Energy Balance (SSEBop) ET over East Africa. Recently, SSEBop ET estimates (version 4) were improved by implementing a land surface temperature correction factor. We re-evaluate the correlations between FLDAS ET and version 4 SSEBop ET. To further investigate the reasons for differences between models we evaluate FLDAS soil moisture with Advanced Scatterometer and SMAP soil moisture and FLDAS outputs with MODIS and AVHRR normalized difference vegetation index. By exploring longer historic time series and near-real time products we will be aiding convergence of evidence for better understanding of historic drought, improved monitoring and forecasting, and better understanding of uncertainties of water availability estimation over Africa

Evaluation of MODIS NDVI and NDWI for vegetation drought monitoring using Oklahoma Mesonet soil moisture data

USGS Publications Warehouse

Gu, Yingxin; Hunt, E.; Wardlow, B.; Basara, J.B.; Brown, Jesslyn F.; Verdin, J.P.

2008-01-01

The evaluation of the relationship between satellite-derived vegetation indices (normalized difference vegetation index and normalized difference water index) and soil moisture improves our understanding of how these indices respond to soil moisture fluctuations. Soil moisture deficits are ultimately tied to drought stress on plants. The diverse terrain and climate of Oklahoma, the extensive soil moisture network of the Oklahoma Mesonet, and satellite-derived indices from the Moderate Resolution Imaging Spectroradiometer (MODIS) provided an opportunity to study correlations between soil moisture and vegetation indices over the 2002-2006 growing seasons. Results showed that the correlation between both indices and the fractional water index (FWI) was highly dependent on land cover heterogeneity and soil type. Sites surrounded by relatively homogeneous vegetation cover with silt loam soils had the highest correlation between the FWI and both vegetation-related indices (r???0.73), while sites with heterogeneous vegetation cover and loam soils had the lowest correlation (r???0.22). Copyright 2008 by the American Geophysical Union.

Soil moisture retrieval from Sentinel-1 satellite data

NASA Astrophysics Data System (ADS)

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

2016-04-01

Reliable up-to-date information on the current water availability and models to evaluate management scenarios are indispensable for skilful water management. The Sentinel-1 radar satellite programme provides an opportunity to monitor water availability (as surface soil moisture) from space on an operational basis at unprecedented fine spatial and temporal resolutions. However, the influences of soil roughness and vegetation cover complicate the retrieval of soil moisture states from radar data. In this contribution, we investigate the sensitivity of Sentinel-1 radar backscatter to soil moisture states and vegetation conditions. The analyses are based on 105 Sentinel-1 images in the period from October 2014 to January 2016 covering the Twente region in the Netherlands. This area is almost flat and has a heterogeneous landscape, including agricultural (mainly grass, cereal and corn), forested and urban land covers. In-situ measurements at 5 cm depth collected from the Twente soil moisture monitoring network are used as reference. This network consists of twenty measurement stations (most of them at agricultural fields) distributed across an area of 50 km × 40 km. The Normalized Difference Vegetation Index (NDVI) derived from optical images is adopted as proxy to represent seasonal variability in vegetation conditions. The results from this sensitivity study provide insight into the potential capability of Sentinel-1 data for the estimation of soil moisture states and they will facilitate the further development of operational retrieval methods. An operationally applicable soil moisture retrieval method requires an algorithm that is usable without the need for area specific model calibration with detailed field information (regarding roughness and vegetation). Because it is not yet clear which method provides the most reliable soil moisture retrievals from Sentinel-1 data, multiple soil moisture retrieval methods will be studied in which the fine spatiotemporal resolution and the dual-polarized information of Sentinel-1 are utilized. Three candidate algorithms are presented at the conference, which are a data-driven algorithm, inversion of a radar scattering model and downscaling of coarser resolution soil moisture products. The research is part of the OWAS1S project (Optimizing Water Availability with Sentinel-1 Satellites), which stands for integration of the freely available global Sentinel-1 data and local knowledge on soil physical processes, to optimize water management of regional water systems and to develop value-added products for agriculture.

Soil moisture monitoring in Candelaro basin, Southern Italy

NASA Astrophysics Data System (ADS)

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

2012-04-01

The signature of the hydrologic regime can be investigated, in principle, by recognizing the main mechanisms of runoff generation that take place in the basin and affect the seasonal behavior or the rainfall-driven events. In this framework, besides the implementation of hydrological models, a crucial role should be played by direct observation of key state variables such as soil moisture at different depths and different distances from the river network. In fact, understanding hydrological systems is often limited by the frequency and spatial distribution of observations. Experimental catchments, which are field laboratories with long-term measurements of hydrological variables, are not only sources of data but also sources of knowledge. Wireless distributed sensing platforms are a key technology to address the need for overcoming field limitations such as conflicts between soil use and cable connections. A stand-alone wireless network system has been installed for continuous monitoring of soil water contents at multiple depths along a transect located in Celone basin (sub-basin of Candelaro basin in Puglia, Southern Italy). The transect consists of five verticals, each one having three soil water content sensors at multiple depths: 0,05 m, 0,6 m and 1,2 m below the ground level. The total length of the transect is 307 m and the average distance between the verticals is 77 m. The main elements of the instrumental system installed are: fifteen Decagon 10HS Soil Moisture Sensors, five Decagon Em50R Wireless Radio Data Loggers, one Rain gauge, one Decagon Data Station and one Campbell CR1000 Data Logger. Main advantages of the system as described and presented in this work are that installation of the wireless network system is fast and easy to use, data retrieval and monitoring information over large spatial scales can be obtained in (near) real-time mode and finally other type of sensors can be connected to the system, also offering wide potentials for future applications. First records of the wireless underground network system indicate the presence of interesting patterns in space-time variability of volumetric soil moisture content, that provide evidence of the combined process of vertical infiltration and lateral flow. ACKNOWLEDGEMENT The research in this work is supported by the MIRAGE FP7 project (Grant agreement n. 211732).

Self-Powered Wearable Electronics Based on Moisture Enabled Electricity Generation.

PubMed

Shen, Daozhi; Xiao, Ming; Zou, Guisheng; Liu, Lei; Duley, Walter W; Zhou, Y Norman

2018-05-01

Most state-of-the-art electronic wearable sensors are powered by batteries that require regular charging and eventual replacement, which would cause environmental issues and complex management problems. Here, a device concept is reported that can break this paradigm in ambient moisture monitoring-a new class of simple sensors themselves can generate moisture-dependent voltage that can be used to determine the ambient humidity level directly. It is demonstrated that a moisture-driven electrical generator, based on the diffusive flow of water in titanium dioxide (TiO 2 ) nanowire networks, can yield an output power density of up to 4 µW cm -2 when exposed to a highly moist environment. This performance is two orders of magnitude better than that reported for carbon-black generators. The output voltage is strongly dependent on humidity of ambient environment. As a big breakthrough, this new type of device is successfully used as self-powered wearable human-breathing monitors and touch pads, which is not achievable by any existing moisture-induced-electricity technology. The availability of high-output self-powered electrical generators will facilitate the design and application of a wide range of new innovative flexible electronic devices. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Comparison of Three Soil Moisture Sensor Types Under Field Conditions Based on the Marena, Oklahoma, In Situ Sensor Testbed (MOISST)

NASA Astrophysics Data System (ADS)

Zhang, N.; Quiring, S. M.; Ochsner, T. E.

2017-12-01

Each soil moisture monitoring network commonly adopts different sensor technologies. This results in different measurement units, depths and impedes large-scale soil moisture applications that seek to integrate data from multiple networks. Therefore, a comprehensive comparison of different sensors to identify the best approach for integrating and homogenizing measurements from different sensors is required. This study compares three commonly used sensors, including Stevens Water Hydra Probes, Campbell Scientific CS616 TDR and CS 229-L heat dissipation sensors based on data from May 2010 to December 2012 from the Marena, Oklahoma, In Situ Sensor Testbed (MOISST). All sensors are installed at common depths of 5, 10, 20, 50, 100 cm. The results reveal that the differences between the three sensors tends to increase with depth. The CDF plots showed CS 229 is most sensitive to moisture variation in dry condition and most easily saturated in wet condition, followed by Hydra probe and CS616. Our results show that calculating percentiles is a good normalization method for standardizing measurements from different sensors. Our preliminary results demonstrate that CDF matching can be used to convert measurements from one sensor to another.

Repeated electromagnetic induction measurements for mapping soil moisture at the field scale: validation with data from a wireless soil moisture monitoring network

NASA Astrophysics Data System (ADS)

Martini, Edoardo; Werban, Ulrike; Zacharias, Steffen; Pohle, Marco; Dietrich, Peter; Wollschläger, Ute

2017-01-01

Electromagnetic induction (EMI) measurements are widely used for soil mapping, as they allow fast and relatively low-cost surveys of soil apparent electrical conductivity (ECa). Although the use of non-invasive EMI for imaging spatial soil properties is very attractive, the dependence of ECa on several factors challenges any interpretation with respect to individual soil properties or states such as soil moisture (θ). The major aim of this study was to further investigate the potential of repeated EMI measurements to map θ, with particular focus on the temporal variability of the spatial patterns of ECa and θ. To this end, we compared repeated EMI measurements with high-resolution θ data from a wireless soil moisture and soil temperature monitoring network for an extensively managed hillslope area for which soil properties and θ dynamics are known. For the investigated site, (i) ECa showed small temporal variations whereas θ varied from very dry to almost saturation, (ii) temporal changes of the spatial pattern of ECa differed from those of the spatial pattern of θ, and (iii) the ECa-θ relationship varied with time. Results suggest that (i) depending upon site characteristics, stable soil properties can be the major control of ECa measured with EMI, and (ii) for soils with low clay content, the influence of θ on ECa may be confounded by changes of the electrical conductivity of the soil solution. Further, this study discusses the complex interplay between factors controlling ECa and θ, and the use of EMI-based ECa data with respect to hydrological applications.

Implementation of Sensor and Control Designs for Bioregenerative Systems

NASA Technical Reports Server (NTRS)

Rodriguez, Pedro R. (Editor)

1990-01-01

The goal of the Spring 1990 EGM 4001 Design class was to design, fabricate, and test sensors and control systems for a closed loop life support system (CLLSS). The designs investigated were to contribute to the development of NASA's Controlled Ecological Life Support System (CELSS) at Kennedy Space Center (KSC). Designs included a seed moisture content sensor, a porous medium wetness sensor, a plant health sensor, and a neural network control system. The seed group focused on the design and implementation of a sensor that could detect the moisture content of a seed batch. The porous medium wetness group concentrated on the development of a sensor to monitor the amount of nutrient solution within a porous plate incorporating either infrared reflectance or thermal conductance properties. The plant health group examined the possibility of remotely monitoring the health of the plants within the Biomass Production Chamber (BPC) using infrared reflectance properties. Finally, the neural network group concentrated on the ability to use parallel processing in order to control a robot arm and analyze the data from the health sensor to detect regions of a plant.

A 868MHz-based wireless sensor network for ground truthing of soil moisture for a hyperspectral remote sensing campaign - design and preliminary results

NASA Astrophysics Data System (ADS)

Näthe, Paul; Becker, Rolf

2014-05-01

Soil moisture and plant available water are important environmental parameters that affect plant growth and crop yield. Hence, they are significant parameters for vegetation monitoring and precision agriculture. However, validation through ground-based soil moisture measurements is necessary for accessing soil moisture, plant canopy temperature, soil temperature and soil roughness with airborne hyperspectral imaging systems in a corresponding hyperspectral imaging campaign as a part of the INTERREG IV A-Project SMART INSPECTORS. At this point, commercially available sensors for matric potential, plant available water and volumetric water content are utilized for automated measurements with smart sensor nodes which are developed on the basis of open-source 868MHz radio modules, featuring a full-scale microcontroller unit that allows an autarkic operation of the sensor nodes on batteries in the field. The generated data from each of these sensor nodes is transferred wirelessly with an open-source protocol to a central node, the so-called "gateway". This gateway collects, interprets and buffers the sensor readings and, eventually, pushes the data-time series onto a server-based database. The entire data processing chain from the sensor reading to the final storage of data-time series on a server is realized with open-source hardware and software in such a way that the recorded data can be accessed from anywhere through the internet. It will be presented how this open-source based wireless sensor network is developed and specified for the application of ground truthing. In addition, the system's perspectives and potentials with respect to usability and applicability for vegetation monitoring and precision agriculture shall be pointed out. Regarding the corresponding hyperspectral imaging campaign, results from ground measurements will be discussed in terms of their contributing aspects to the remote sensing system. Finally, the significance of the wireless sensor network for the application of ground truthing shall be determined.

Application of Microwave Moisture Sensor for Determination of Oil Palm Fruit Ripeness

NASA Astrophysics Data System (ADS)

Yeow, You Kok; Abbas, Zulkifly; Khalid, Kaida

2010-01-01

This paper describes the development of a low cost coaxial moisture sensor for the determination of moisture content (30 % to 80 % wet-weight basis) of the oil palm fruits of various degree of fruit ripeness. The sensor operating between 1 GHz and 5 GHz was fabricated from an inexpensive 4.1 mm outer diameter SMA coaxial stub contact panel which is suitable for single fruit measurement. The measurement system consists of the sensor and a PC-controlled vector network analyzer (VNA). The actual moisture content was determined by standard oven drying method and compared with predicted value of fruit moisture content obtained using the studied sensor. The sensor was used to monitor fruit ripeness based on the measurement of the phase or magnitude of reflection coefficient and the dielectric measurement software was developed to control and acquire data from the VNA using Agilent VEE. This software was used to calculate the complex relative permittivity from the measured reflection coefficient between 1GHz and 5 GHz.

Remote sensing of an agricultural soil moisture network in Walnut Creek, Iowa

USDA-ARS?s Scientific Manuscript database

The calibration and validation of soil moisture remote sensing products is complicated by the logistics of installing a soil moisture network for a long term period in an active landscape. Usually soil moisture sensors are added to existing precipitation networks which have as a singular requiremen...

The role of rock moisture on regulating hydrologic and solute fluxes in the critical zone

NASA Astrophysics Data System (ADS)

Rempe, D. M.; Druhan, J. L.; Hahm, W. J.; Wang, J.; Murphy, C.; Cargill, S.; Dietrich, W. E.; Tune, A. K.

2017-12-01

In environments where the vadose zone extends below the soil layer into underlying weathered bedrock, the water held in the weathering -generated pores can be an important source of moisture to vegetation. The heterogeneous distribution of pore space in weathered bedrock, furthermore, controls the subsurface water flowpaths that dictate how water is partitioned in the critical zone (CZ) and evolves geochemically. Here, we present the results of direct monitoring of the fluxes of water and solutes through the deep CZ using a novel vadose zone monitoring system (VMS) as well as geophysical logging and sampling in a network of deep wells across a steep hillslope in Northern California. At our study site (Eel River CZO), multi-year monitoring reveals that a significant fraction of incoming rainfall (up to 30%) is seasonally stored in the fractures and matrix of the upper 12 m of weathered bedrock as rock moisture. Intensive geochemical and geophysical observations distributed from the surface to the depth of unweathered bedrock indicate that the seasonal addition and depletion of rock moisture has key implications for hydrologic and geochemical processes. First, rock moisture storage provides an annually consistent water storage reservoir for use by vegetation during the summer, which buffers transpiration fluxes against variability in seasonal precipitation. Second, because the timing and magnitude of groundwater recharge and streamflow are controlled by the annual filling and drainage of the rock moisture, rock moisture regulates the partitioning of hydrologic fluxes. Third, we find that rock moisture dynamics—which influence the myriad geochemical and microbial processes that weather bedrock—strongly correspond with the observed vertical weathering profile. As a result of the coupling between chemical weathering reactions and hydrologic fluxes, the geochemical composition of groundwater and streamflow is influenced by the temporal dynamics of rock moisture. Our findings highlight the strong influence of water transport and storage dynamics in the weathered bedrock beneath the soil layer on catchment-scale hydrologic and geochemical fluxes, and underscore the need for further exploration of the fractured bedrock vadose zones common to many upland landscapes.

Static sampling of dynamic processes - a paradox?

NASA Astrophysics Data System (ADS)

Mälicke, Mirko; Neuper, Malte; Jackisch, Conrad; Hassler, Sibylle; Zehe, Erwin

2017-04-01

Environmental systems monitoring aims at its core at the detection of spatio-temporal patterns of processes and system states, which is a pre-requisite for understanding and explaining their baffling heterogeneity. Most observation networks rely on distributed point sampling of states and fluxes of interest, which is combined with proxy-variables from either remote sensing or near surface geophysics. The cardinal question on the appropriate experimental design of such a monitoring network has up to now been answered in many different ways. Suggested approaches range from sampling in a dense regular grid using for the so-called green machine, transects along typical catenas, clustering of several observations sensors in presumed functional units or HRUs, arrangements of those cluster along presumed lateral flow paths to last not least a nested, randomized stratified arrangement of sensors or samples. Common to all these approaches is that they provide a rather static spatial sampling, while state variables and their spatial covariance structure dynamically change in time. It is hence of key interest how much of our still incomplete understanding stems from inappropriate sampling and how much needs to be attributed to an inappropriate analysis of spatial data sets. We suggest that it is much more promising to analyze the spatial variability of processes, for instance changes in soil moisture values, than to investigate the spatial variability of soil moisture states themselves. This is because wetting of the soil, reflected in a soil moisture increase, is causes by a totally different meteorological driver - rainfall - than drying of the soil. We hence propose that the rising and the falling limbs of soil moisture time series belong essentially to different ensembles, as they are influenced by different drivers. Positive and negative temporal changes in soil moisture need, hence, to be analyzed separately. We test this idea using the CAOS data set as a benchmark. Specifically, we expect the covariance structure of the positive temporal changes of soil moisture to be dominated by the spatial structure of rain- and through-fall and saturated hydraulic conductivity. The covariance in temporarily decreasing soil moisture during radiation driven conditions is expect to be dominated by the spatial structure of retention properties and plant transpiration. An analysis of soil moisture changes has furthermore the advantage that those are free from systematic measurement errors.

Analysis of spatiotemporal soil moisture patterns at the catchment scale using a wireless sensor network

NASA Astrophysics Data System (ADS)

Bogena, Heye R.; Huisman, Johan A.; Rosenbaum, Ulrike; Weuthen, Ansgar; Vereecken, Harry

2010-05-01

Soil water content plays a key role in partitioning water and energy fluxes and controlling the pattern of groundwater recharge. Despite the importance of soil water content, it is not yet measured in an operational way at larger scales. The aim of this paper is to present the potential of real-time monitoring for the analysis of soil moisture patterns at the catchment scale using the recently developed wireless sensor network SoilNet [1], [2]. SoilNet is designed to measure soil moisture, salinity and temperature in several depths (e.g. 5, 20 and 50 cm). Recently, a small forest catchment Wüstebach (~27 ha) has been instrumented with 150 sensor nodes and more than 1200 soil sensors in the framework of the Transregio32 and the Helmholtz initiative TERENO (Terrestrial Environmental Observatories). From August to November 2009, more than 6 million soil moisture measurements have been performed. We will present first results from a statistical and geostatistical analysis of the data. The observed spatial variability of soil moisture corresponds well with the 800-m scale variability described in [3]. The very low scattering of the standard deviation versus mean soil moisture plots indicates that sensor network data shows less artificial soil moisture variations than soil moisture data originated from measurement campaigns. The variograms showed more or less the same nugget effect, which indicates that the sum of the sub-scale variability and the measurement error is rather time-invariant. Wet situations showed smaller spatial variability, which is attributed to saturated soil water content, 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 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. Interpolation using the external drift kriging method demonstrated that the high sampling density allows capturing the key patterns of soil moisture variation in the Wüstebach catchment. References: [1] Bogena, H.R., J.A. Huisman, C. Oberdörster, H. Vereecken (2007): Evaluation of a low-cost soil water content sensor for wireless network applications. Journal of Hydrology: 344, 32- 42. [2] Rosenbaum, U., Huisman, J.A., Weuthen, A., Vereecken, H. and Bogena, H.R. (2010): Quantification of sensor-to-sensor variability of the ECH2O EC-5, TE and 5TE sensors in dielectric liquids. Accepted for publication in Vadose Zone Journal (09/2009). [3] Famiglietti J.S., D. Ryu, A. A. Berg, M. Rodell and T. J. Jackson (2008), Field observations of soil moisture variability across scales, Water Resour. Res. 44, W01423, doi:10.1029/2006WR005804.

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

NASA Astrophysics Data System (ADS)

Larson, Kristine; Small, Eric; Chew, Clara

2015-04-01

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

Rapid and non-destructive determination of rancidity levels in butter cookies by multi-spectral imaging.

PubMed

Xia, Qing; Liu, Changhong; Liu, Jinxia; Pan, Wenjuan; Lu, Xuzhong; Yang, Jianbo; Chen, Wei; Zheng, Lei

2016-03-30

Rancidity is an important attribute for quality assessment of butter cookies, while traditional methods for rancidity measurement are usually laborious, destructive and prone to operational error. In the present paper, the potential of applying multi-spectral imaging (MSI) technology with 19 wavelengths in the range of 405-970 nm to evaluate the rancidity in butter cookies was investigated. Moisture content, acid value and peroxide value were determined by traditional methods and then related with the spectral information by partial least squares regression (PLSR) and back-propagation artificial neural network (BP-ANN). The optimal models for predicting moisture content, acid value and peroxide value were obtained by PLSR. The correlation coefficient (r) obtained by PLSR models revealed that MSI had a perfect ability to predict moisture content (r = 0.909), acid value (r = 0.944) and peroxide value (r = 0.971). The study demonstrated that the rancidity level of butter cookies can be continuously monitored and evaluated in real-time by the multi-spectral imaging, which is of great significance for developing online food safety monitoring solutions. © 2015 Society of Chemical Industry.

Quantifying Seasonal Dynamic Water Storage in a Fractured Bedrock Vadose Zone With Borehole Nuclear Magnetic Resonance

NASA Astrophysics Data System (ADS)

Schmidt, L.; Minton, B.; Soto-Kerans, N.; Rempe, D.; Heidari, Z.

2017-12-01

In many uplands landscapes, water is transiently stored in the weathered and fractured bedrock that underlies soils. The timing and spatial pattern of this "rock moisture" has strong implications for ecological and biogeochemical processes that influence global cycling of water and solutes. However, available technologies for direct monitoring of rock moisture are limited. Here, we quantify temporal and spatial changes in rock moisture at the field scale across thick (up to 20 m) fractured vadose zone profiles using a novel narrow diameter borehole nuclear magnetic resonance system (BNMR). Successive BNMR surveys were performed using the Vista Clara Inc. Dart system in a network of boreholes within two steep, intensively hydrologically monitored hillslopes associated with the Eel River Critical Zone Observatory (ERCZO) in Northern California. BNMR data showed agreement with estimates of the temporal and spatial pattern of rock moisture depletion over the dry season via downhole neutron and gamma density surveys, as well as permanently installed continuous time domain reflectometry. Observable shifts in the BNMR-derived T2 distribution over time provide a direct measure of changes in the amount of water held within different pore sizes (large vs. small) in fractured rock. Analysis of both BNMR and laboratory-scale NMR (using a 2MHz benchtop NMR spectrometer) measurements of ERCZO core samples at variable saturation suggest that rock moisture changes associated with summer depletion occur within both large (fracture) and small (matrix) pore sizes. Collectively, our multi-method field- and laboratory- scale measurements highlight the potential for BNMR to improve quantification of rock moisture storage for better understanding of the biogeochemical and ecohydrological implications of rock moisture circulation in the Critical Zone.

Comparing soil moisture anomalies from multiple independent sources over different regions across the globe

NASA Astrophysics Data System (ADS)

Cammalleri, Carmelo; Vogt, Jürgen V.; Bisselink, Bernard; de Roo, Ad

2017-12-01

Agricultural drought events can affect large regions across the world, implying the need for a suitable global tool for an accurate monitoring of this phenomenon. Soil moisture anomalies are considered a good metric to capture the occurrence of agricultural drought events, and they have become an important component of several operational drought monitoring systems. In the framework of the JRC Global Drought Observatory (GDO, http://edo.jrc.ec.europa.eu/gdo/), the suitability of three datasets as possible representations of root zone soil moisture anomalies has been evaluated: (1) the soil moisture from the Lisflood distributed hydrological model (namely LIS), (2) the remotely sensed Land Surface Temperature data from the MODIS satellite (namely LST), and (3) the ESA Climate Change Initiative combined passive/active microwave skin soil moisture dataset (namely CCI). Due to the independency of these three datasets, the triple collocation (TC) technique has been applied, aiming at quantifying the likely error associated with each dataset in comparison to the unknown true status of the system. TC analysis was performed on five macro-regions (namely North America, Europe, India, southern Africa and Australia) detected as suitable for the experiment, providing insight into the mutual relationship between these datasets as well as an assessment of the accuracy of each method. Even if no definitive statement on the spatial distribution of errors can be provided, a clear outcome of the TC analysis is the good performance of the remote sensing datasets, especially CCI, over dry regions such as Australia and southern Africa, whereas the outputs of LIS seem to be more reliable over areas that are well monitored through meteorological ground station networks, such as North America and Europe. In a global drought monitoring system, the results of the error analysis are used to design a weighted-average ensemble system that exploits the advantages of each dataset.

Spatial structure and scaling of macropores in hydrological process at small catchment scale

NASA Astrophysics Data System (ADS)

Silasari, Rasmiaditya; Broer, Martine; Blöschl, Günter

2013-04-01

During rainfall events, the formation of overland flow can occur under the circumstances of saturation excess and/or infiltration excess. These conditions are affected by the soil moisture state which represents the soil water content in micropores and macropores. Macropores act as pathway for the preferential flows and have been widely studied locally. However, very little is known about their spatial structure and conductivity of macropores and other flow characteristic at the catchment scale. This study will analyze these characteristics to better understand its importance in hydrological processes. The research will be conducted in Petzenkirchen Hydrological Open Air Laboratory (HOAL), a 64 ha catchment located 100 km west of Vienna. The land use is divided between arable land (87%), pasture (5%), forest (6%) and paved surfaces (2%). Video cameras will be installed on an agricultural field to monitor the overland flow pattern during rainfall events. A wireless soil moisture network is also installed within the monitored area. These field data will be combined to analyze the soil moisture state and the responding surface runoff occurrence. The variability of the macropores spatial structure of the observed area (field scale) then will be assessed based on the topography and soil data. Soil characteristics will be supported with laboratory experiments on soil matrix flow to obtain proper definitions of the spatial structure of macropores and its variability. A coupled physically based distributed model of surface and subsurface flow will be used to simulate the variability of macropores spatial structure and its effect on the flow behaviour. This model will be validated by simulating the observed rainfall events. Upscaling from field scale to catchment scale will be done to understand the effect of macropores variability on larger scales by applying spatial stochastic methods. The first phase in this study is the installation and monitoring configuration of video cameras and soil moisture monitoring equipment to obtain the initial data of overland flow occurrence and soil moisture state relationships.

Remote Sensing of Terrestrial Water Storage and Application to Drought Monitoring

NASA Technical Reports Server (NTRS)

Rodell, Matt

2007-01-01

Terrestrial water storage (TWS) consists of groundwater, soil moisture and permafrost, surface water, snow and ice, and wet biomass. TWS variability tends to be dominated by snow and ice in polar and alpine regions, by soil moisture in mid-latitudes, and by surface water in wet, tropical regions such as the Amazon (Rodell and Famiglietti, 2001; Bates et al., 2007). Drought may be defined as a period of abnormally dry weather long enough to cause significant deficits in one or more of the TWS components. Thus, along with observations of the agricultural and socioeconomic impacts, measurements of TWS and its components enable quantification of drought severity. Each of the TWS components exhibits significant spatial variability, while installation and maintenance of sufficiently dense monitoring networks is costly and labor-intensive. Thus satellite remote sensing is an appealing alternative to traditional measurement techniques. Several current remote sensing instruments are able to detect variations in one or more TWS variables, including the Advanced Microwave Scanning Radiometer (AMSR) on NASA's Aqua satellite and the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA's Terra and Aqua. Future satellite missions have been proposed to improve this capability, including the European Space Agency's Soil Moisture Ocean Salinity mission (SMOS) and the Soil Moisture Active Passive (SMAP), Surface Water Ocean Topography (SWOT), and Snow and Cold Land Processes (SCLP) missions recommended by the US National Academy of Science's Decadal Survey for Earth Science (NRC, 2007). However, only one remote sensing technology is able to monitor changes in TWS from the land surface to the base of the deepest aquifer: satellite gravimetry. This paper focuses on NASA's Gravity Recovery and Climate Experiment mission (GRACE; http://www.csr.utexas.edu/grace/) and its potential as a tool for drought monitoring.

Enhancing soil moisture monitoring via cosmic-ray neutron sensing in farmlands by combining field site tests with an uncertainty analysis

NASA Astrophysics Data System (ADS)

Oswald, S. E.; Scheiffele, L. M.; Baroni, G.; Ingwersen, J.; Schrön, M.

2017-12-01

One application of Cosmic-Ray Neutron Sensing (CRNS) is to investigate soil moisture on agricultural fields during the crop season. This fully employs the non-invasive character of CRNS without interference with agricultural practices of the farmland. The changing influence of vegetation on CRNS has to be dealt with as well as spatio-temporal influences, e.g. by irrigation or harvest. Previous work revealed that the CRNS signal on farmland shows complex and non-unique response because of the hydrogen pools in different depths and distances. This creates a challenge for soil moisture estimation and subsequent use for irrigation management or hydrological modelling. Thus, a special aim of our study was to assess the uncertainty of CRNS in cropped fields and to identify underlying causes of uncertainty. We have applied CRNS at two field sites during the growing season that were accompanied by intensive measurements of soil moisture, vegetation parameters, and irrigation events. Sources of uncertainty were identified from the experimental data. A Monte Carlo approach was used to propagate these uncertainties to CRNS soil moisture estimations. In addition, a sensitivity analysis was performed to identify the most important factors explaining this uncertainty. Results showed that CRNS soil moisture compares well to the soil moisture network when the point values were converted to weighted water content with all hydrogen pools included. However, when considered as a stand-alone method to retrieve volumetric soil moisture, the performance decreased. The support volume including its penetration depth showed also a considerable uncertainty, especially in relatively dry soil moisture conditions. Of seven factors analyzed, actual soil moisture profile, bulk density, incoming neutron correction and calibrated parameter N0 were found to play an important role. One possible improvement could be a simple correction factor based on independent data of soil moisture profiles to better account for the sensitivity of the CRNS signal to the upper soil layers. This is an important step to improve the method for validation of remote sensing products or agricultural water management and establish CRNS as an applied monitoring tool on farmland.

Monitoring Climate Variability and Change in Northern Alaska: Updates to the U.S. Geological Survey (USGS) Climate and Permafrost Monitoring Network

NASA Astrophysics Data System (ADS)

Urban, F. E.; Clow, G. D.; Meares, D. C.

2004-12-01

Observations of long-term climate and surficial geological processes are sparse in most of the Arctic, despite the fact that this region is highly sensitive to climate change. Instrumental networks that monitor the interplay of climatic variability and geological/cryospheric processes are a necessity for documenting and understanding climate change. Improvements to the spatial coverage and temporal scale of Arctic climate data are in progress. The USGS, in collaboration with The Bureau of Land Management (BLM) and The Fish and Wildlife Service (FWS) currently maintains two types of monitoring networks in northern Alaska: (1) A 15 site network of continuously operating active-layer and climate monitoring stations, and (2) a 21 element array of deep bore-holes in which the thermal state of deep permafrost is monitored. Here, we focus on the USGS Alaska Active Layer and Climate Monitoring Network (AK-CLIM). These 15 stations are deployed in longitudinal transects that span Alaska north of the Brooks Range, (11 in The National Petroleum Reserve Alaska, (NPRA), and 4 in The Arctic National Wildlife Refuge (ANWR)). An informative overview and update of the USGS AK-CLIM network is presented, including insight to current data, processing and analysis software, and plans for data telemetry. Data collection began in 1998 and parameters currently measured include air temperature, soil temperatures (5-120 cm), snow depth, incoming and reflected short-wave radiation, soil moisture (15 cm), wind speed and direction. Custom processing and analysis software has been written that calculates additional parameters such as active layer thaw depth, thawing-degree-days, albedo, cloudiness, and duration of seasonal snow cover. Data from selected AK-CLIM stations are now temporally sufficient to begin identifying trends, anomalies, and inter-annual variability in the climate of northern Alaska.

High-resolution Mapping of Permafrost and Soil Freeze/thaw Dynamics in the Tibetan Plateau Based on Multi-sensor Satellite Observations

NASA Astrophysics Data System (ADS)

Zhang, W.; Yi, Y.; Yang, K.; Kimball, J. S.

2016-12-01

The Tibetan Plateau (TP) is underlain by the world's largest extent of alpine permafrost ( 2.5×106 km2), dominated by sporadic and discontinuous permafrost with strong sensitivity to climate warming. Detailed permafrost distributions and patterns in most of the TP region are still unknown due to extremely sparse in-situ observations in this region characterized by heterogeneous land cover and large temporal dynamics in surface soil moisture conditions. Therefore, satellite-based temperature and moisture observations are essential for high-resolution mapping of permafrost distribution and soil active layer changes in the TP region. In this study, we quantify the TP regional permafrost distribution at 1-km resolution using a detailed satellite data-driven soil thermal process model (GIPL2). The soil thermal model is calibrated and validated using in-situ soil temperature/moisture observations from the CAMP/Tibet field campaign (9 sites: 0-300 cm soil depth sampling from 1997-2007), a multi-scale soil moisture and temperature monitoring network in the central TP (CTP-SMTMN, 57 sites: 5-40 cm, 2010-2014) and across the whole plateau (China Meteorology Administration, 98 sites: 0-320 cm, 2000-2015). Our preliminary results using the CAMP/Tibet and CTP-SMTMN network observations indicate strong controls of surface thermal and soil moisture conditions on soil freeze/thaw dynamics, which vary greatly with underlying topography, soil texture and vegetation cover. For regional mapping of soil freeze/thaw and permafrost dynamics, we use the most recent soil moisture retrievals from the NASA SMAP (Soil Moisture Active Passive) sensor to account for the effects of temporal soil moisture dynamics on soil thermal heat transfer, with surface thermal conditions defined by MODIS (Moderate Resolution Imaging Spectroradiometer) land surface temperature records. Our study provides the first 1-km map of spatial patterns and recent changes of permafrost conditions in the TP.

A Concept for the Development of Spatially Resolved Measurements for Soil Moisture with TEM Waveguides

NASA Astrophysics Data System (ADS)

Lapteva, Yulia; Schmidt, Felix; Bumberger, Jan

2014-05-01

Soil water content plays a leading role in delimitating water and energy fluxes at the land surface and controlling groundwater recharging. The information about water content in the soil would be very useful in overcoming the challenge of managing water resources under conditions of increasing scarcity in Southern Europe and the Mediterranean region.For collecting data about the water content in soil, it is possible to use remote sensing and groundwater monitoring, built wireless sensor networks for water monitoring. Remote sensing provides a unique capability to get the information of soil moisture at global and regional scales. Wireless environmental sensor networks enable to connect local and regional-scale soil water content observations. There exist different ground based soil moisture measurement methods such as TDR, FDR, electromagnetic waves (EW), electrical and acoustic methods. Among these methods, the time domain reflectometry (TDR) is considered to be the most important and widely used electromagnetic approach. The special techniques for the reconstruction of the layered soil with TDR are based on differential equations in the time domain and numerical optimization algorithms. However, these techniques are time- consuming and suffering from some problems, like multiple reflections at the boundary surfaces. To overcome these limitations, frequency domain measurement (FDM) techniques could be used. With devices like vector network analyzers (VNA) the accuracy of the measurement itself and of the calibration can be improved. For field applicable methods the reflection coefficient is mathematically transformed in the time domain, which can be treated like TDR-data and the same information can be obtained. There are already existed some experiments using the frequency domain data directly as an input for inversion algorithms to find the spatial distribution of the soil parameters. The model that is used represents an exact solution of the Maxwell's equations. It describes the one-dimensional wave propagation in a multi-layered medium, assuming the wave to be transverse electromagnetic (TEM). In the particular case of transmission lines with perpendicularly arranged layer transitions this assumption is very close to reality. Such waveguides and their frequency domain measurements in layered media are promising concerning a development ways working with soil moisture detection.

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

NASA Technical Reports Server (NTRS)

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

2016-01-01

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

METEOPOLE-FLUX: an observatory of terrestrial water, energy, and CO2 fluxes in Toulouse

NASA Astrophysics Data System (ADS)

Calvet, Jean-Christophe; Roujean, Jean-Louis; Zhang, Sibo; Maurel, William; Piguet, Bruno; Barrié, Joël; Bouhours, Gilles; Couzinier, Jacques; Garrouste, Olivier; Girres, Sandrine; Suquia, David; Tzanos, Diane

2016-04-01

The METEOPOLE-FLUX project (http://www.cnrm.meteo.fr/spip.php?article874&lang=en) aims at monitoring a large suburban set-aside field in the city of Toulouse (43.572898 N, 1.374384 E). Since June 2012, these data contribute to the international effort to monitor terrestrial ecosystems (grasslands in particular), to the validation of land surface models, and to the near real time quality monitoring of operational weather forecast models. Various variables are monitored at a subhourly rate: wind speed, air temperature, air humidity, atmospheric pressure, precipitation, turbulent fluxes (H, LE, CO2), downwelling and upwelling solar and infrared radiation, downwelling and upwelling PAR, fraction of diffuse incoming PAR, presence of water intercepted by vegetation (rain, dew), soil moisture profile, soil temperature profile, surface albedo, transmissivity of PAR in vegetation canopy. Moreover, local observations are performed using remote sensing techniques: infrared radiometry, GNSS reflectometry, and multi-band surface reflectometry using an aerosol photometer from the AERONET network. Destructive measurements of LAI, green/brown above-ground biomass, and necromass are performed twice a year. This site is characterized by a large fraction of gravels and stones in the soil, ranging from 17% to 35% in the top soil layer (down to 0.6 m), and peaking at 81% at 0.7 m. The impact of gravels and stones on thermal and moisture fluxes in the soil has not been much addressed in the past and is not represented in most land surface models. Their impact on the available water content for plant transpiration and plant growth is not much documented so far. The long term monitoring of this site will therefore improve the knowledge on land processes. The data will be used together with urban meteorological data to characterize the urban heat island. Finally, this site will be used for the CAL/VAL of various satellite products in conjunction with the SMOSMANIA soil moisture network (http://www.cnrm.meteo.fr/spip.php?article251&lang=en). The site will be presented together a first comparison of the ISBA land surface model with the observations.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

Cosmic-ray neutron sensing (CRNS) has developed into a valuable, indirect and non-invasive method to estimate soil moisture at the field scale. It provides continuous temporal data (hours to days), relatively large depth (10-70 cm), and intermediate spatial scale measurements (hundreds of meters), thereby overcoming some of the limitations in point measurements (e.g., TDR/FDR) and of remote sensing products. All these characteristics make CRNS a favorable approach for soil moisture estimation, especially for applications in cropped fields and agricultural water management. Various studies compare CRNS measurements to soil sensor networks and show a good agreement. However, CRNS is sensitive to more characteristics of the land-surface, e.g. additional hydrogen pools, soil bulk density, and biomass. Prior to calibration the standard atmospheric corrections are accounting for the effects of air pressure, humidity and variations in incoming neutrons. In addition, the standard calibration approach was further extended to account for hydrogen in lattice water and soil organic material. Some corrections were also proposed to account for water in biomass. Moreover, the sensitivity of the probe was found to decrease with distance and a weighting procedure for the calibration datasets was introduced to account for the sensors' radial sensitivity. On the one hand, all the mentioned corrections showed to improve the accuracy in estimated soil moisture values. On the other hand, they require substantial additional efforts in monitoring activities and they could inherently contribute to the overall uncertainty of the CRNS product. In this study we aim (i) to quantify the uncertainty in the field soil moisture estimated by CRNS and (ii) to understand the role of the different sources of uncertainty. To this end, two experimental sites in Germany were equipped with a CRNS probe and compared to values of a soil moisture network. The agricultural fields were cropped with winter wheat (Pforzheim, 2013) and maize (Braunschweig, 2014) and differ in soil type and management. The results confirm a general good agreement between soil moisture estimated by CRNS and the soil moisture network. However, several sources of uncertainty were identified i.e., overestimation of dry conditions, strong effects of the additional hydrogen pools and an influence of the vertical soil moisture profile. Based on that, a global sensitivity analysis based on Monte Carlo sampling can be performed and evaluated in terms of soil moisture and footprint characteristics. The results allow quantifying the role of the different factors and identifying further improvements in the method.

Drought Indicators Based on Model Assimilated GRACE Terrestrial Water Storage Observations

NASA Technical Reports Server (NTRS)

Houborg, Rasmus; Rodell, Matthew; Li, Bailing; Reichle, Rolf; Zaitchik, Benjamin F.

2012-01-01

The Gravity Recovery and Climate Experiment (GRACE) twin satellites observe time variations in Earth's gravity field which yield valuable information about changes in terrestrial water storage (TWS). GRACE is characterized by low spatial (greater than 150,000 square kilometers) and temporal (greater than 10 day) resolution but has the unique ability to sense water stored at all levels (including groundwater) systematically and continuously. The GRACE Data Assimilation System (GRACE-DAS), based on the Catchment Land Surface Model (CLSM) enhances the value of the GRACE water storage data by enabling spatial and temporal downscaling and vertical decomposition into moisture 39 components (i.e. groundwater, soil moisture, snow), which individually are more useful for scientific applications. In this study, GRACE-DAS was applied to North America and GRACE-based drought indicators were developed as part of a larger effort that investigates the possibility of more comprehensive and objective identification of drought conditions by integrating spatially, temporally and vertically disaggregated GRACE data into the U.S. and North American Drought Monitors. Previously, the Drought Monitors lacked objective information on deep soil moisture and groundwater conditions, which are useful indicators of drought. Extensive datasets of groundwater storage from USGS monitoring wells and soil moisture from the Soil Climate Analysis Network (SCAN) were used to assess improvements in the hydrological modeling skill resulting from the assimilation of GRACE TWS data. The results point toward modest, but statistically significant, improvements in the hydrological modeling skill across major parts of the United States, highlighting the potential value of GRACE assimilated water storage field for improving drought detection.

Monitoring Drought at Continental Scales Using Thermal Remote Sensing of Evapotranspiration (Invited)

NASA Astrophysics Data System (ADS)

Anderson, M. C.; Hain, C.; Mecikalski, J. R.; Kustas, W. P.

2009-12-01

Thermal infrared (TIR) remote sensing of land-surface temperature (LST) provides valuable information about the sub-surface moisture status: soil surface temperature increases with decreasing water content, while moisture depletion in the plant root zone leads to stomatal closure, reduced transpiration, and elevated canopy temperatures that can be effectively detected from space. Empirical indices measuring anomalies in LST and vegetation amount (e.g., as quantified by the Normalized Difference Vegetation Index; NDVI) have demonstrated utility in monitoring drought conditions over large areas, but may provide ambiguous results when vegetation growth is limited by energy (radiation, air temperature) rather than moisture. A more physically based interpretation of LST and NDVI and their relationship to sub-surface moisture conditions can be obtained with a surface energy balance model driven by TIR remote sensing. In this approach, moisture stress can be quantified in terms of the reduction of evapotranspiration (ET) from the potential rate (PET) expected under non-moisture limiting conditions. The Atmosphere-Land Exchange Inverse (ALEXI) model couples a two-source (soil+canopy) land-surface model with an atmospheric boundary layer model in time-differencing mode to routinely and robustly map fluxes across the U.S. continent at 5-10km resolution using thermal band imagery from the Geostationary Operational Environmental Satellites (GOES). Finer resolution flux maps can be generated through spatial disaggregation using TIR data from polar orbiting instruments such as Landsat (60-120m) and MODIS (1km). A derived Evaporative Stress Index (ESI), given by 1-ET/PET, shows good correspondence with standard drought metrics and with patterns of antecedent precipitation, but can be produced at significantly higher spatial resolution due to limited reliance on ground observations. Because the ESI does not use precipitation data as input, it provides an independent means for assessing standard meteorologically-based drought indicators, and may be more robust in regions with limited monitoring networks. In this study, monthly maps of ESI anomalies for 2000-2008 are compared to standard drought indices and to drought classifications in the U.S. Drought Monitor. The ESI shows better skill in ranking drought severity than do precipitation-based indices composited over comparable time intervals. The thermal remote sensing inputs to ALEXI detect drought conditions even under the dense forest cover along the East Coast of the United States, where microwave soil moisture retrievals typically lose sensitivity. On the other hand, microwave observations are not constrained by cloud cover and provide better temporal continuity, but typically at significantly lower spatial resolution. A merged TIR-microwave moisture anomaly product may have potential for optimizing both spatial and temporal coverage in continental-scale drought monitoring.

ESA's Soil Moisture dnd Ocean Salinity Mission - Contributing to Water Resource Management

NASA Astrophysics Data System (ADS)

Mecklenburg, S.; Kerr, Y. H.

2015-12-01

The Soil Moisture and Ocean Salinity (SMOS) mission, launched in November 2009, is the European Space Agency's (ESA) second Earth Explorer Opportunity mission. The scientific objectives of the SMOS mission directly respond to the need for global observations of soil moisture and ocean salinity, two key variables used in predictive hydrological, oceanographic and atmospheric models. SMOS observations also provide information on the characterisation of ice and snow covered surfaces and the sea ice effect on ocean-atmosphere heat fluxes and dynamics, which affects large-scale processes of the Earth's climate system. The focus of this paper will be on SMOS's contribution to support water resource management: SMOS surface soil moisture provides the input to derive root-zone soil moisture, which in turn provides the input for the drought index, an important monitoring prediction tool for plant available water. In addition to surface soil moisture, SMOS also provides observations on vegetation optical depth. Both parameters aid agricultural applications such as crop growth, yield forecasting and drought monitoring, and provide input for carbon and land surface modelling. SMOS data products are used in data assimilation and forecasting systems. Over land, assimilating SMOS derived information has shown to have a positive impact on applications such as NWP, stream flow forecasting and the analysis of net ecosystem exchange. Over ocean, both sea surface salinity and severe wind speed have the potential to increase the predictive skill on the seasonal and short- to medium-range forecast range. Operational users in particular in Numerical Weather Prediction and operational hydrology have put forward a requirement for soil moisture data to be available in near-real time (NRT). This has been addressed by developing a fast retrieval for a NRT level 2 soil moisture product based on Neural Networks, which will be available by autumn 2015. This paper will focus on presenting the above applications and used SMOS data products.

NY-uHMT: A dense hydro-meteorological network to characterize urban land-atmosphere interactions

NASA Astrophysics Data System (ADS)

Ramamurthy, P.; Lakhankar, T.; Khanbilvardi, R.; Devineni, N.

2016-12-01

Most people in the US live in large Metropolitan areas that have a dense urban core in the center, dominated by built surfaces and surrounded by residential/suburban areas that consist a mix of built, vegetated and permeable surfaces. This creates a gradient in the hydro-meteorological environment giving rise to complex land-atmosphere interactions. Current modeling platforms and observational techniques like tower measurements do not adequately account for the underlying heterogeneity. To address this critical gap in our understanding we have instituted a dense network of sensors in the New York Metropolitan area. This unique urban sensor network consists of instrumentation to monitor soil moisture at multiple depths along with air temperature, relative humidity and precipitation, with room to add additional sensors in the future. The network is autonomous and connected to a centralized server using cellular towers. Apart from describing the spatial variability in hydro-meteorological quantities the network will also aid in conducting high-resolution numerical simulations to study and forecast urban weather and climate. In one such simulation conducted to partition the influence of storage flux, wind pattern and circulation and soil moisture deficit on urban heat island intensity (UHI), we found that the daily variability in UHI in NYC was sensitive to available energy and wind pattern. The long-term trend in UHI was however related to soil moisture deficit. In fact a prolonged heat wave period witnessed during summer 2006 correlated well with an extended dry period and the daily UHI in NYC almost doubled. Moreover, the urban soils also suffered from high degree of dessication, owing to drier urban boundary layer.

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

NASA Astrophysics Data System (ADS)

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

2011-02-01

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

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

NASA Astrophysics Data System (ADS)

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

2011-05-01

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

Topographical controls on soil moisture distribution and runoff response in a first order alpine catchment

NASA Astrophysics Data System (ADS)

Penna, Daniele; Gobbi, Alberto; Mantese, Nicola; Borga, Marco

2010-05-01

Hydrological processes driving runoff generation in mountain basins depend on a wide number of factors which are often strictly interconnected. Among them, topography is widely recognized as one of the dominant controls influencing soil moisture distribution in the root zone, depth to water table and location and extent of saturated areas possibly prone to runoff production. Morphological properties of catchments are responsible for the alternation between steep slopes and relatively flat areas which have the potentials to control the storage/release of water and hence the hydrological response of the whole watershed. This work aims to: i) identify the role of topography as the main factor controlling the spatial distribution of near-surface soil moisture; ii) evaluate the possible switch in soil moisture spatial organization between wet and relatively dry periods and the stability of patterns during triggering of surface/subsurface runoff; iii) assess the possible connection between the develop of an ephemeral river network and the groundwater variations, examining the influence of the catchment topographical properties on the hydrological response. Hydro-meteorological data were collected in a small subcatchment (Larch Creek Catchment, 0.033 km²) of Rio Vauz basin (1.9 km²), in the eastern Italian Alps. Precipitation, discharge, water table level over a net of 14 piezometric wells and volumetric soil moisture at 0-30 cm depth were monitored continuously during the late spring-early autumn months in 2007 and 2008. Soil water content at 0-6 and 0-20 cm depth was measured manually during 22 field surveys in summer 2007 over a 44-sampling point experimental plot (approximately 3000 m²). In summer 2008 the sampling grid was extended to 64 points (approximately 4500 m²) and 28 field surveys were carried out. The length of the ephemeral stream network developed during rainfall events was assessed by a net of 24 Overland Flow Detectors (OFDs), which are able to detect the presence/absence of surface runoff. Results show a significant correlation between plot-averaged soil moisture at 0-20 cm depth, local slope and local curvature, while poor correlations were found with aspect and solar radiation: this suggests a sharp control of the catchment topological architecture (likely coupled with soil properties) on soil moisture distribution. This was also confirmed by the visual inspection of interpolated maps which reveal the persistence of high values of soil moisture in hollow areas and, conversely, of low values over the hillslopes. Moreover, a strong correlation between plot-averaged soil moisture patterns over time, with no decline after rainfall events, indicates a good temporal stability of water content distribution and its independence from the triggering of surface flow and transient lateral subsurface flow during wet conditions. The analysis of the time lag between storm centroid and piezometric peak shows an increasing delay of water table reaction with increasing distance from the stream, revealing different groundwater dynamics between the near-stream and the hillslope zone. Furthermore, the significant correlation between groundwater time lag monitored for the net of piezometers and the local slope suggests a topographical influence on the temporal and spatial variability of subsurface runoff. Finally, the extent of the ephemeral stream network was clearly dependent on the amount of precipitation but a different percentage of active OFDs and piezometers for the same rainfall event suggests a decoupling between patterns of surface and subsurface flows in the study area. Key words: topographical controls, soil moisture patterns, groundwater level, overland flow.

Performance of MODIS satellite and mesoscale model based land surface temperature for soil moisture deficit estimation using Neural Network

NASA Astrophysics Data System (ADS)

Srivastava, Prashant K.; Petropoulos, George P.; Gupta, Manika; Islam, Tanvir

2015-04-01

Soil Moisture Deficit (SMD) is a key variable in the water and energy exchanges that occur at the land-surface/atmosphere interface. Monitoring SMD is an alternate method of irrigation scheduling and represents the use of the suitable quantity of water at the proper time by combining measurements of soil moisture deficit. In past it is found that LST has a strong relation to SMD, which can be estimated by MODIS or numerical weather prediction model such as WRF (Weather Research and Forecasting model). By looking into the importance of SMD, this work focused on the application of Artificial Neural Network (ANN) for evaluating its capabilities towards SMD estimation using the LST data estimated from MODIS and WRF mesoscale model. The benchmark SMD estimated from Probability Distribution Model (PDM) over the Brue catchment, Southwest of England, U.K. is used for all the calibration and validation experiments. The performances between observed and simulated SMD are assessed in terms of the Nash-Sutcliffe Efficiency (NSE), the Root Mean Square Error (RMSE) and the percentage of bias (%Bias). The application of the ANN confirmed a high capability WRF and MODIS LST for prediction of SMD. Performance during the ANN calibration and validation showed a good agreement between benchmark and estimated SMD with MODIS LST information with significantly higher performance than WRF simulated LST. The work presented showed the first comprehensive application of LST from MODIS and WRF mesoscale model for hydrological SMD estimation, particularly for the maritime climate. More studies in this direction are recommended to hydro-meteorological community, so that useful information will be accumulated in the technical literature domain for different geographical locations and climatic conditions. Keyword: WRF, Land Surface Temperature, MODIS satellite, Soil Moisture Deficit, Neural Network

A Networked Sensor System for the Analysis of Plot-Scale Hydrology.

PubMed

Villalba, German; Plaza, Fernando; Zhong, Xiaoyang; Davis, Tyler W; Navarro, Miguel; Li, Yimei; Slater, Thomas A; Liang, Yao; Liang, Xu

2017-03-20

This study presents the latest updates to the Audubon Society of Western Pennsylvania (ASWP) testbed, a $50,000 USD, 104-node outdoor multi-hop wireless sensor network (WSN). The network collects environmental data from over 240 sensors, including the EC-5, MPS-1 and MPS-2 soil moisture and soil water potential sensors and self-made sap flow sensors, across a heterogeneous deployment comprised of MICAz, IRIS and TelosB wireless motes. A low-cost sensor board and software driver was developed for communicating with the analog and digital sensors. Innovative techniques (e.g., balanced energy efficient routing and heterogeneous over-the-air mote reprogramming) maintained high success rates (>96%) and enabled effective software updating, throughout the large-scale heterogeneous WSN. The edaphic properties monitored by the network showed strong agreement with data logger measurements and were fitted to pedotransfer functions for estimating local soil hydraulic properties. Furthermore, sap flow measurements, scaled to tree stand transpiration, were found to be at or below potential evapotranspiration estimates. While outdoor WSNs still present numerous challenges, the ASWP testbed proves to be an effective and (relatively) low-cost environmental monitoring solution and represents a step towards developing a platform for monitoring and quantifying statistically relevant environmental parameters from large-scale network deployments.

A Networked Sensor System for the Analysis of Plot-Scale Hydrology

PubMed Central

Villalba, German; Plaza, Fernando; Zhong, Xiaoyang; Davis, Tyler W.; Navarro, Miguel; Li, Yimei; Slater, Thomas A.; Liang, Yao; Liang, Xu

2017-01-01

This study presents the latest updates to the Audubon Society of Western Pennsylvania (ASWP) testbed, a $50,000 USD, 104-node outdoor multi-hop wireless sensor network (WSN). The network collects environmental data from over 240 sensors, including the EC-5, MPS-1 and MPS-2 soil moisture and soil water potential sensors and self-made sap flow sensors, across a heterogeneous deployment comprised of MICAz, IRIS and TelosB wireless motes. A low-cost sensor board and software driver was developed for communicating with the analog and digital sensors. Innovative techniques (e.g., balanced energy efficient routing and heterogeneous over-the-air mote reprogramming) maintained high success rates (>96%) and enabled effective software updating, throughout the large-scale heterogeneous WSN. The edaphic properties monitored by the network showed strong agreement with data logger measurements and were fitted to pedotransfer functions for estimating local soil hydraulic properties. Furthermore, sap flow measurements, scaled to tree stand transpiration, were found to be at or below potential evapotranspiration estimates. While outdoor WSNs still present numerous challenges, the ASWP testbed proves to be an effective and (relatively) low-cost environmental monitoring solution and represents a step towards developing a platform for monitoring and quantifying statistically relevant environmental parameters from large-scale network deployments. PMID:28335534

AMMA-CATCH a Hydrological, Meteorological and Ecological Long Term Observatory on West Africa : Some Recent Results

NASA Astrophysics Data System (ADS)

Galle, S.; Grippa, M.; Peugeot, C.; Bouzou Moussa, I.; Cappelaere, B.; Demarty, J.; Mougin, E.; Lebel, T.; Chaffard, V.

2015-12-01

AMMA-CATCH is a multi-scale observation system dedicated to long-term monitoring of the water cycle, the vegetation dynamics and their interaction with climate and water resources in West Africa. In the context of the global change, long-term observations are required to i) gain understanding in eco-hydrological processes over this highly contrasted region, ii) help their representation in Earth System Models, and iii) detect trends and infer their impacts on water resources and living conditions. It is made of three meso-scale sites (~ 1°x1°) in Mali, Niger and Benin, extending along the West African eco-climatic gradient. Within this regional window (5° by 9°), each of the three sites comprises a multi-scale set-up which helps documenting the components of the hydrologic budget and the evolutions of the surface conditions over a range of time scales: raingages, piezometers, river discharge stations, soil moisture and temperature profiles, turbulent fluxes measurements, LAI/biomass monitoring. This observation system has been continuously generating coherent datasets for 10 to 25 years depending on the datasets. It is jointly operated by French and African (Mali, Niger and Benin) research institutions. The data-base is available to the community through the website (www.amma-catch.org). AMMA-CATCH is a member of the French critical zone observatory network "Réseau des Bassins Versants", (RBV). AMMA-CATH participates to several global or regional observation networks, such as FluxNet, CarboAfrica, International Soil Moisture Networks (ISMN) and to calibration/validation campaigns for satellite missions such as SMOS (CNES, ESA), MEGHA-TROPIQUES (France/India) or SWAP(NASA). AMMA-CATCH fills a gap over a region, West Africa, where environmental data are largely lacking, and thus, it can usefully contribute to the international networking effort for environmental monitoring and research. Recent results on regional evolution of land cover, rainfall intensity and their consequences on eco-hydrological processes and hydrosystems will be presented.

Downscaling SMAP Radiometer Soil Moisture over the CONUS using Soil-Climate Information and Ensemble Learning

NASA Astrophysics Data System (ADS)

Abbaszadeh, P.; Moradkhani, H.

2017-12-01

Soil moisture contributes significantly towards the improvement of weather and climate forecast and understanding terrestrial ecosystem processes. It is known as a key hydrologic variable in the agricultural drought monitoring, flood modeling and irrigation management. While satellite retrievals can provide an unprecedented information on soil moisture at global-scale, the products are generally at coarse spatial resolutions (25-50 km2). This often hampers their use in regional or local studies, which normally require a finer resolution of the data set. This work presents a new framework based on an ensemble learning method while using soil-climate information derived from remote-sensing and ground-based observations to downscale the level 3 daily composite version (L3_SM_P) of SMAP radiometer soil moisture over the Continental U.S. (CONUS) at 1 km spatial resolution. In the proposed method, a suite of remotely sensed and in situ data sets in addition to soil texture information and topography data among others were used. The downscaled product was validated against in situ soil moisture measurements collected from a limited number of core validation sites and several hundred sparse soil moisture networks throughout the CONUS. The obtained results indicated a great potential of the proposed methodology to derive the fine resolution soil moisture information applicable for fine resolution hydrologic modeling, data assimilation and other regional studies.

An agronomic field-scale sensor network for monitoring soil water and temperature variation

NASA Astrophysics Data System (ADS)

Brown, D. J.; Gasch, C.; Brooks, E. S.; Huggins, D. R.; Campbell, C. S.; Cobos, D. R.

2014-12-01

Environmental sensor networks have been deployed in a variety of contexts to monitor plant, air, water and soil properties. To date, there have been relatively few such networks deployed to monitor dynamic soil properties in cropped fields. Here we report on experience with a distributed soil sensor network that has been deployed for seven years in a research farm with ongoing agronomic field operations. The Washington State University R. J. Cook Agronomy Farm (CAF), Pullman, WA, USA has recently been designated a United States Department of Agriculture (USDA) Long-Term Agro-Ecosystem Research (LTAR) site. In 2007, 12 geo-referenced locations at CAF were instrumented, then in 2009 this network was expended to 42 locations distributed across the 37-ha farm. At each of this locations, Decagon 5TE probes (Decagon Devices Inc., Pullman, WA, USA) were installed at five depths (30, 60, 90, 120, and 150 cm), with temperature and volumetric soil moisture content recorded hourly. Initially, data loggers were wirelessly connected to a data station that could be accessed through a cell connection, but due to the logistics of agronomic field operations, we later buried the dataloggers at each site and now periodically download data via local radio transmission. In this presentation, we share our experience with the installation, maintenance, calibration and data processing associated with an agronomic soil monitoring network. We also present highlights of data derived from this network, including seasonal fluctuations of soil temperature and volumetric water content at each depth, and how these measurements are influenced by crop type, soil properties, landscape position, and precipitation events.

Environmental Monitoring Using Sensor Networks

NASA Astrophysics Data System (ADS)

Yang, J.; Zhang, C.; Li, X.; Huang, Y.; Fu, S.; Acevedo, M. F.

2008-12-01

Environmental observatories, consisting of a variety of sensor systems, computational resources and informatics, are important for us to observe, model, predict, and ultimately help preserve the health of the nature. The commoditization and proliferation of coin-to-palm sized wireless sensors will allow environmental monitoring with unprecedented fine spatial and temporal resolution. Once scattered around, these sensors can identify themselves, locate their positions, describe their functions, and self-organize into a network. They communicate through wireless channel with nearby sensors and transmit data through multi-hop protocols to a gateway, which can forward information to a remote data server. In this project, we describe an environmental observatory called Texas Environmental Observatory (TEO) that incorporates a sensor network system with intertwined wired and wireless sensors. We are enhancing and expanding the existing wired weather stations to include wireless sensor networks (WSNs) and telemetry using solar-powered cellular modems. The new WSNs will monitor soil moisture and support long-term hydrologic modeling. Hydrologic models are helpful in predicting how changes in land cover translate into changes in the stream flow regime. These models require inputs that are difficult to measure over large areas, especially variables related to storm events, such as soil moisture antecedent conditions and rainfall amount and intensity. This will also contribute to improve rainfall estimations from meteorological radar data and enhance hydrological forecasts. Sensor data are transmitted from monitoring site to a Central Data Collection (CDC) Server. We incorporate a GPRS modem for wireless telemetry, a single-board computer (SBC) as Remote Field Gateway (RFG) Server, and a WSN for distributed soil moisture monitoring. The RFG provides effective control, management, and coordination of two independent sensor systems, i.e., a traditional datalogger-based wired sensor system and the WSN-based wireless sensor system. The RFG also supports remote manipulation of the devices in the field such as the SBC, datalogger, and WSN. Sensor data collected from the distributed monitoring stations are stored in a database (DB) Server. The CDC Server acts as an intermediate component to hide the heterogeneity of different devices and support data validation required by the DB Server. Daemon programs running on the CDC Server pre-process the data before it is inserted into the database, and periodically perform synchronization tasks. A SWE-compliant data repository is installed to enable data exchange, accepting data from both internal DB Server and external sources through the OGC web services. The web portal, i.e. TEO Online, serves as a user-friendly interface for data visualization, analysis, synthesis, modeling, and K-12 educational outreach activities. It also provides useful capabilities for system developers and operators to remotely monitor system status and remotely update software and system configuration, which greatly simplifies the system debugging and maintenance tasks. We also implement Sensor Observation Services (SOS) at this layer, conforming to the SWE standard to facilitate data exchange. The standard SensorML/O&M data representation makes it easy to integrate our sensor data into the existing Geographic Information Systems (GIS) web services and exchange the data with other organizations.

Long-term SMOS soil moisture products: A comprehensive evaluation across scales and methods in the Duero Basin (Spain)

NASA Astrophysics Data System (ADS)

González-Zamora, Ángel; Sánchez, Nilda; Martínez-Fernández, José; Gumuzzio, Ángela; Piles, María; Olmedo, Estrella

The European Space Agency's Soil Moisture and Ocean Salinity (SMOS) Level 2 soil moisture and the new L3 product from the Barcelona Expert Center (BEC) were validated from January 2010 to June 2014 using two in situ networks in Spain. The first network is the Soil Moisture Measurement Stations Network of the University of Salamanca (REMEDHUS), which has been extensively used for validating remotely sensed observations of soil moisture. REMEDHUS can be considered a small-scale network that covers a 1300 km2 region. The second network is a large-scale network that covers the main part of the Duero Basin (65,000 km2). At an existing meteorological network in the Castilla y Leon region (Inforiego), soil moisture probes were installed in 2012 to provide data until 2014. Comparisons of the temporal series using different strategies (total average, land use, and soil type) as well as using the collocated data at each location were performed. Additionally, spatial correlations on each date were computed for specific days. Finally, an improved version of the Triple Collocation (TC) method, i.e., the Extended Triple Collocation (ETC), was used to compare satellite and in situ soil moisture estimates with outputs of the Soil Water Balance Model Green-Ampt (SWBM-GA). The results of this work showed that SMOS estimates were consistent with in situ measurements in the time series comparisons, with Pearson correlation coefficients (R) and an Agreement Index (AI) higher than 0.8 for the total average and the land-use averages and higher than 0.85 for the soil-texture averages. The results obtained at the Inforiego network showed slightly better results than REMEDHUS, which may be related to the larger scale of the former network. Moreover, the best results were obtained when all networks were jointly considered. In contrast, the spatial matching produced worse results for all the cases studied. These results showed that the recent reprocessing of the L2 products (v5.51) improved the accuracy of soil moisture retrievals such that they are now suitable for developing new L3 products, such as the presented in this work. Additionally, the validation based on comparisons between dense/sparse networks and satellite retrievals at a coarse resolution showed that temporal patterns in the soil moisture are better reproduced than spatial patterns.

40 CFR 75.11 - Specific provisions for monitoring SO2 emissions.

Code of Federal Regulations, 2011 CFR

2011-07-01

... wood and 14.0% for natural gas (boilers, only); or (2) Install, operate, maintain, and quality assure a continuous moisture monitoring system for measuring and recording the moisture content of the flue gases, in... monitoring systems are acceptable: a continuous moisture sensor; an oxygen analyzer (or analyzers) capable of...

40 CFR 75.11 - Specific provisions for monitoring SO2 emissions.

Code of Federal Regulations, 2010 CFR

2010-07-01

... wood and 14.0% for natural gas (boilers, only); or (2) Install, operate, maintain, and quality assure a continuous moisture monitoring system for measuring and recording the moisture content of the flue gases, in... monitoring systems are acceptable: a continuous moisture sensor; an oxygen analyzer (or analyzers) capable of...

A regional-scale network for geoid monitoring and satellite gravimetry validation

NASA Astrophysics Data System (ADS)

Winester, D.; Pool, D.; Kennedy, J.

2010-12-01

In the past two decades, improved measurements of acceleration due to gravity have allowed for accurate detection of temporal gravity change. Terrestrial absolute gravimeters (for example, Micro-g LaCoste FG5 or A-10) can sense changes of gravity induced by elevation or mass changes, including local effects that may bias regional studies. Satellite instrumentation (e.g. GRACE) can detect large scale mass changes on a regular basis. However, the Nyquist wave number for satellite observations is often much too small for the size of regional studies. Also, satellites are limited by their life of deployment. Both techniques are used to (in)validate change models generated from other geophysical observations including water storage(underground and glacial), geoid definition, isostatic adjustments and tectonic(magmatic and faulting)activity. The gap between terrestrial and satellite gravity observations (and between satellite missions) might be bridged by developing a terrestrial network of sites of various observation techniques that define a representative sample of a given, regional study area. This information could then be statistically extrapolated to the extent of the region. The Southern High Plains Aquifer is such a region, since it has widespread relatively uniform geology, has relatively flat topography, and is well monitored for groundwater levels and soil moisture. Each site would have extensive instrumentation for monitoring, at a minimum, gravity (periodic and continuous) using absolute and tidal gravimeters, soil moisture, precipitation, depths to water in wells, evapotranspiration, air pressure, and land surface (GPS). Where possible, the network would build upon existing, data collection infrastructure. Preferably, the region would also have seismic tomography or crustal seismic reflection observations to characterize Moho-depth mass changes and have regional Bouguer anomaly mapping. In addition to information on local hydrology and geology, data collection would allow for characterization of local seasonal corrections, earth tides, atmospheric loading and episodic slip. No test network has yet been funded, but cost and man-power can be estimated. Such a network would rely on co-operation between various federal, state, local and university groups.

Monitoring water cycle elements using GNSS geodetic receivers at the field research station Marquardt, Germany

NASA Astrophysics Data System (ADS)

Simeonov, Tzvetan; Vey, Sibylle; Alshawaf, Fadwa; Dick, Galina; Guerova, Guergana; Güntner, Andreas; Hohmann, Christian; Kunwar, Ajeet; Trost, Benjamin; Wickert, Jens

2017-04-01

Water storage variations in the atmosphere and in soils are among the most dynamic within the Earth's water cycle. The continuous measurement of water storage in these media with a high spatial and temporal resolution is a challenging task, not yet completely solved by various observation techniques. With the development of the Global Navigation Satellite Systems (GNSS) a new approach for atmospheric water vapor estimation in the atmosphere and in parallel of soil moisture in the vicinity of GNSS ground stations was established in the recent years with several key advantages compared to traditional techniques. Regional and global GNSS networks are nowadays operationally used to provide the Integrated Water Vapor (IWV) information with high temporal resolution above the individual stations. Corresponding data products are used to improve the day-by-day weather prediction of leading forecast centers. Selected stations from these networks can be used to additionally derive the soil moisture in the vicinity of the receivers. Such parallel measurement of IWV and soil moisture using a single measuring device provides a unique possibility to analyze water fluxes between the atmosphere and the land surface. We installed an advanced experimental GNSS setup for hydrology at the field research station of the Leibniz Institute for Agricultural Engineering and Bioeconomy in Marquardt, around 30km West of Berlin, Germany. The setup includes several GNSS receivers, various Time Domain Reflectometry (TDR) sensors at different depths for soil moisture measurement and an meteorological station. The setup was mainly installed to develop and improve GNSS based techniques for soil moisture determination and to analyze GNSS IWV and SM in parallel on a long-term perspective. We introduce initial results from more than two years of measurements. The comparison in station Marquardt shows good agreement (correlation 0.79) between the GNSS derived soil moisture and the TDR measurements. A detailed study for several periods with different GNSS settings, vegetation and soil conditions in the vicinity of the station is presented with emphasis on the behavior of GNSS derived soil moisture, compared to TDR. Case studies of intense rainfall events and lasting dry periods show the interaction between the IWV and soil moisture.

Estimating surface soil moisture from SMAP observations using a neural network technique

USDA-ARS?s Scientific Manuscript database

A Neural Network (NN) algorithm was developed to estimate global surface soil moisture for April 2015 to June 2016 with a 2-3 day repeat frequency using passive microwave observations from the Soil Moisture Active Passive (SMAP) satellite, surface soil temperatures from the NASA Goddard Earth Observ...

[Detecting the moisture content of forest surface soil based on the microwave remote sensing technology.

PubMed

Li, Ming Ze; Gao, Yuan Ke; Di, Xue Ying; Fan, Wen Yi

2016-03-01

The moisture content of forest surface soil is an important parameter in forest ecosystems. It is practically significant for forest ecosystem related research to use microwave remote sensing technology for rapid and accurate estimation of the moisture content of forest surface soil. With the aid of TDR-300 soil moisture content measuring instrument, the moisture contents of forest surface soils of 120 sample plots at Tahe Forestry Bureau of Daxing'anling region in Heilongjiang Province were measured. Taking the moisture content of forest surface soil as the dependent variable and the polarization decomposition parameters of C band Quad-pol SAR data as independent variables, two types of quantitative estimation models (multilinear regression model and BP-neural network model) for predicting moisture content of forest surface soils were developed. The spatial distribution of moisture content of forest surface soil on the regional scale was then derived with model inversion. Results showed that the model precision was 86.0% and 89.4% with RMSE of 3.0% and 2.7% for the multilinear regression model and the BP-neural network model, respectively. It indicated that the BP-neural network model had a better performance than the multilinear regression model in quantitative estimation of the moisture content of forest surface soil. The spatial distribution of forest surface soil moisture content in the study area was then obtained by using the BP neural network model simulation with the Quad-pol SAR data.

A soil water based index as a suitable agricultural drought indicator

NASA Astrophysics Data System (ADS)

Martínez-Fernández, J.; González-Zamora, A.; Sánchez, N.; Gumuzzio, A.

2015-03-01

Currently, the availability of soil water databases is increasing worldwide. The presence of a growing number of long-term soil moisture networks around the world and the impressive progress of remote sensing in recent years has allowed the scientific community and, in the very next future, a diverse group of users to obtain precise and frequent soil water measurements. Therefore, it is reasonable to consider soil water observations as a potential approach for monitoring agricultural drought. In the present work, a new approach to define the soil water deficit index (SWDI) is analyzed to use a soil water series for drought monitoring. In addition, simple and accurate methods using a soil moisture series solely to obtain soil water parameters (field capacity and wilting point) needed for calculating the index are evaluated. The application of the SWDI in an agricultural area of Spain presented good results at both daily and weekly time scales when compared to two climatic water deficit indicators (average correlation coefficient, R, 0.6) and to agricultural production. The long-term minimum, the growing season minimum and the 5th percentile of the soil moisture series are good estimators (coefficient of determination, R2, 0.81) for the wilting point. The minimum of the maximum value of the growing season is the best estimator (R2, 0.91) for field capacity. The use of these types of tools for drought monitoring can aid the better management of agricultural lands and water resources, mainly under the current scenario of climate uncertainty.

Inversion of Farmland Soil Moisture in Large Region Based on Modified Vegetation Index

NASA Astrophysics Data System (ADS)

Wang, J. X.; Yu, B. S.; Zhang, G. Z.; Zhao, G. C.; He, S. D.; Luo, W. R.; Zhang, C. C.

2018-04-01

Soil moisture is an important parameter for agricultural production. Efficient and accurate monitoring of soil moisture is an important link to ensure the safety of agricultural production. Remote sensing technology has been widely used in agricultural moisture monitoring because of its timeliness, cyclicality, dynamic tracking of changes in things, easy access to data, and extensive monitoring. Vegetation index and surface temperature are important parameters for moisture monitoring. Based on NDVI, this paper introduces land surface temperature and average temperature for optimization. This article takes the soil moisture in winter wheat growing area in Henan Province as the research object, dividing Henan Province into three main regions producing winter wheat and dividing the growth period of winter wheat into the early, middle and late stages on the basis of phenological characteristics and regional characteristics. Introducing appropriate correction factor during the corresponding growth period of winter wheat, correcting the vegetation index in the corresponding area, this paper establishes regression models of soil moisture on NDVI and soil moisture on modified NDVI based on correlation analysis and compare models. It shows that modified NDVI is more suitable as a indicator of soil moisture because of the better correlation between soil moisture and modified NDVI and the higher prediction accuracy of the regression model of soil moisture on modified NDVI. The research in this paper has certain reference value for winter wheat farmland management and decision-making.

Impact of SMOS soil moisture data assimilation on NCEP-GFS forecasts

NASA Astrophysics Data System (ADS)

Zhan, X.; Zheng, W.; Meng, J.; Dong, J.; Ek, M.

2012-04-01

Soil moisture is one of the few critical land surface state variables that have long memory to impact the exchanges of water, energy and carbon between the land surface and atmosphere. Accurate information about soil moisture status is thus required for numerical weather, seasonal climate and hydrological forecast as well as for agricultural production forecasts, water management and many other water related economic or social activities. Since the successful launch of ESA's soil moisture ocean salinity (SMOS) mission in November 2009, about 2 years of soil moisture retrievals has been collected. SMOS is believed to be the currently best satellite sensors for soil moisture remote sensing. Therefore, it becomes interesting to examine how the collected SMOS soil moisture data are compared with other satellite-sensed soil moisture retrievals (such as NASA's Advanced Microwave Scanning Radiometer -AMSR-E and EUMETSAT's Advanced Scatterometer - ASCAT)), in situ soil moisture measurements, and how these data sets impact numerical weather prediction models such as the Global Forecast System of NOAA-NCEP. This study implements the Ensemble Kalman filter in GFS to assimilate the AMSR-E, ASCAT and SMOS soil moisture observations after a quantitative assessment of their error rate based on in situ measurements from ground networks around contiguous United States. in situ soil moisture measurements from ground networks (such as USDA Soil Climate Analysis network - SCAN and NOAA's U.S. Climate Reference Network -USCRN) are used to evaluate the GFS soil moisture simulations (analysis). The benefits and uncertainties of assimilating the satellite data products in GFS are examined by comparing the GFS forecasts of surface temperature and rainfall with and without the assimilations. From these examinations, the advantages of SMOS soil moisture data products over other satellite soil moisture data sets will be evaluated. The next step toward operationally assimilating soil moisture and other land observations into GFS will also be discussed.

On the temporal and spatial variability of near-surface soil moisture for the identification of representative in situ soil moisture monitoring stations

USDA-ARS?s Scientific Manuscript database

The high spatio-temporal variability of soil moisture complicates the validation of remotely sensed soil moisture products using in-situ monitoring stations. Therefore, a standard methodology for selecting the most repre- sentative stations for the purpose of validating satellites and land surface ...

Evaluating new SMAP soil moisture for drought monitoring in the rangelands of the US High Plains

USGS Publications Warehouse

Velpuri, Naga Manohar; Senay, Gabriel B.; Morisette, Jeffrey T.

2016-01-01

Level 3 soil moisture datasets from the recently launched Soil Moisture Active Passive (SMAP) satellite are evaluated for drought monitoring in rangelands.Validation of SMAP soil moisture (SSM) with in situ and modeled estimates showed high level of agreement.SSM showed the highest correlation with surface soil moisture (0-5 cm) and a strong correlation to depths up to 20 cm.SSM showed a reliable and expected response of capturing seasonal dynamics in relation to precipitation, land surface temperature, and evapotranspiration.Further evaluation using multi-year SMAP datasets is necessary to quantify the full benefits and limitations for drought monitoring in rangelands.

SoilSCAPE in-Situ Observations of Soil Moisture for SMAP Validation: Pushing the Envelopes of Spatial Coverage and Energy Efficiency in Sparse Wireless Sensor Networks (Invited)

NASA Astrophysics Data System (ADS)

Moghaddam, M.; Silva, A.; Clewley, D.; Akbar, R.; Entekhabi, D.

2013-12-01

Soil Moisture Sensing Controller and oPtimal Estimator (SoilSCAPE) is a wireless in-situ sensor network technology, developed under the support of NASA ESTO/AIST program, for multi-scale validation of soil moisture retrievals from the Soil Moisture Active and Passive (SMAP) mission. The SMAP sensor suite is expected to produce soil moisture retrievals at 3 km scale from the radar instrument, at 36 km from the radiometer, and at 10 km from the combination of the two sensors. To validate the retrieved soil moisture maps at any of these scales, it is necessary to perform in-situ observations at multiple scales (ten, hundreds, and thousands of meters), representative of the true spatial variability of soil moisture fields. The most recent SoilSCAPE network, deployed in the California central valley, has been designed, built, and deployed to accomplish this goal, and is expected to become a core validation site for SMAP. The network consists of up to 150 sensor nodes, each comprised of 3-4 soil moisture sensors at various depths, deployed over a spatial extent of 36 km by 36 km. The network contains multiple sub-networks, each having up to 30 nodes, whose location is selected in part based on maximizing the land cover diversity within the 36 km cell. The network has achieved unprecedented energy efficiency, longevity, and spatial coverage using custom-designed hardware and software protocols. The network architecture utilizes a nested strategy, where a number of end devices (EDs) communicate to a local coordinator (LC) using our recently developed hardware with ultra-efficient circuitry and best-effort-timeslot allocation communication protocol. The LCs in turn communicates with the base station (BS) via text messages and a new compression scheme. The hardware and software technologies required to implement this latest deployment of the SoilSCAPE network will be presented in this paper, and several data sets resulting from the measurements will be shown. The data are available publicly in near-real-time from the project web site, and are also available and searchable via an extensive set of metadata fields through the ORNL-DAAC.

Improving the soil moisture data record of the U.S. Climate Reference Network (USCRN) and Soil Climate Analysis Network (SCAN)

USDA-ARS?s Scientific Manuscript database

Soil moisture estimates are valuable for hydrologic modeling, drought prediction and management, climate change analysis, and agricultural decision support. However, in situ measurements of soil moisture have only become available within the past few decades with additional sensors being installed ...

Validating the BERMS in situ soil moisture network with a large scale temporary network

USDA-ARS?s Scientific Manuscript database

Calibration and validation of soil moisture satellite products requires data records of large spatial and temporal extent, but obtaining this data can be challenging. These challenges can include remote locations, and expense of equipment. One location with a long record of soil moisture data is th...

Assimilation of SMOS Soil Moisture Retrievals in the Land Information System

NASA Technical Reports Server (NTRS)

Blankenship, Clay; Case, Jonathan L.; Zavodsky, Brad

2014-01-01

Soil moisture is a crucial variable for weather prediction because of its influence on evaporation. It is of critical importance for drought and flood monitoring and prediction and for public health applications. The NASA Short-term Prediction Research and Transition Center (SPoRT) has implemented a new module in the NASA Land Information System (LIS) to assimilate observations from the ESA's Soil Moisture and Ocean Salinity (SMOS) satellite. SMOS Level 2 retrievals from the Microwave Imaging Radiometer using Aperture Synthesis (MIRAS) instrument are assimilated into the Noah LSM within LIS via an Ensemble Kalman Filter. The retrievals have a target volumetric accuracy of 4% at a resolution of 35-50 km. Parallel runs with and without SMOS assimilation are performed with precipitation forcing from intentionally degraded observations, and then validated against a model run using the best available precipitation data, as well as against selected station observations. The goal is to demonstrate how SMOS data assimilation can improve modeled soil states in the absence of dense rain gauge and radar networks.

Soil moisture monitoring for crop management

NASA Astrophysics Data System (ADS)

Boyd, Dale

2015-07-01

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

Interactions Between Structure and Processing that Control Moisture Uptake in High-Performance Polycyanurates (Briefing Charts)

DTIC Science & Technology

2015-03-24

distribution is unlimited.  . Interactions Between Structure and Processing that Control Moisture Uptake in High-Performance Polycyanurates Presenter: Dr...Edwards AFB, CA 4 California State University, Long Beach, CA 90840 2 Outline: Basic Studies of Moisture Uptake in Cyanate Ester Networks • Background...Motivation • SOTA Theories of Moisture Uptake in Thermosetting Networks • New Tools and New Discoveries • Unresolved Issues and Ways to Address Them

Real-time monitoring of moisture levels in wound dressings in vitro: an experimental study.

PubMed

McColl, David; Cartlidge, Brian; Connolly, Patricia

2007-10-01

Retaining an appropriate level of moisture at the interface between a healing wound and an applied dressing is considered to be critical for effective wound healing. Failure to control exudate at this interface can result in maceration or drying out of the wound surface. The ability to control moisture balance at the wound interface is therefore a key aspect of wound dressing performance. To date it has not been possible to monitor in any effective manner the distribution of moisture within dressings or how this varies with time. A new measurement system is presented based on sensors placed at the wound/dressing interface which are capable of monitoring moisture levels in real time. The system comprises a model wound bed and sensor array complete with fluid injection path to mimic exudate flow. Eight monitoring points, situated beneath the test dressing, allow the moisture profile across the complete dressing to be measured both during and after fluid injection. The system has been used to evaluate the performance of four foam dressings, a composite hydrofibre dressing and a film dressing. Stark contrasts in the performance of the wound contact layer were found between the different wound dressing types. The composite hydrofibre dressing retained moisture at the wound interface throughout the experiments while areas of the foam dressing quickly became dry, even during constant injection of fluid. The abundance of sensors allowed a moisture map of the surface of the wound dressing to be constructed, illustrating that the moisture profile was not uniform across several of the dressings tested during absorption and evaporation of liquid. These results raise questions as to how the dressings behave on a wound in vivo and indicate the need for a similar clinical monitoring system for tracking wound moisture levels.

Advances in Measuring Soil Moisture using Global Navigation Satellite Systems Interferometric Reflectometry (GNSS-IR)

NASA Astrophysics Data System (ADS)

Moore, A. W.; Small, E. E.; Owen, S. E.; Hardman, S. H.; Wong, C.; Freeborn, D. J.; Larson, K. M.

2016-12-01

GNSS Interferometric Reflectometry (GNSS-IR) uses GNSS signals reflected off the land to infer changes in the near-antenna environment and monitor fluctuations in soil moisture, as well as other related hydrologic variables: snow depth/snow water equivalent (SWE), vegetation water content, and water level [Larson and Small, 2013; McCreight, et al., 2014; Larson et al., 2013]. GNSS instruments installed by geoscientists and surveyors to measure land motions can measure soil moisture fluctuations with accuracy (RMSE <0.04 cm3/cm3 [Small et al., 2016]) and latency sufficient for many applications (e.g., weather forecasting, climate studies, satellite validation). The soil moisture products have a unique and complementary footprint intermediate in scale between satellite and standard in situ sensors. Variations in vegetation conditions introduce considerable errors, but algorithms have been developed to address this issue [Small et al., 2016]. A pilot project (PBO H2O) using 100+ GPS sites in the western U.S. (Figure 1) from a single network (the Plate Boundary Observatory) has been operated by the University of Colorado (CU) at http://xenon.colorado.edu/portal since October 2012. JPL and CU are funded by NASA ESTO to refactor the PBO H2O software within an Apache OODT framework for robust operational analysis of soil moisture data and auto-configuration when new stations are added. We will report progress on the new GNSS H2O analysis portal, and plans to expand to global networks and from GPS to other GNSS signals. ReferencesLarson, K. M., & Small, E. E. (2013) Eos, 94(52), 505-512. McCreight, J. L., Small, E. E., & Larson, K. M. (2014). Water Resour. Res., 50(8), 6892-6909. Larson, K. M., Ray, R. D., Nievinski, F. G., & Freymueller, J. T. (2013). IEEE Geosci Remote S, 10(5), 1200-1204. Small, E. E., Larson, K. M., Chew, C. C., Dong, J., & Ochsner, T. E. (2016). IEEE J Sel. Top. Appl. PP(39). Figure 1: (R) Western U.S. GPS-IR soil moisture sites. (L): Products derived from GNSS reflection data for (clockwise from upper left) vegetation water content, SWE, sea level, and volumetric soil moisture.

Relative skills of soil moisture and vegetation optical depth retrievals for agricultural drought monitoring

USDA-ARS?s Scientific Manuscript database

Soil moisture condition is an important indicator for agricultural drought monitoring. Through the Land Parameter Retrieval Model (LPRM), vegetation optical depth (VOD) as well as surface soil moisture (SM) can be retrieved simultaneously from brightness temperature observations from the Advanced Mi...

Validating modeled soil moisture with in-situ data for agricultural drought monitoring in West Africa

NASA Astrophysics Data System (ADS)

McNally, A.; Yatheendradas, S.; Jayanthi, H.; Funk, C. C.; Peters-Lidard, C. D.

2011-12-01

The declaration of famine in Somalia on July 21, 2011 highlights the need for regional hydroclimate analysis at a scale that is relevant for agropastoral drought monitoring. A particularly critical and robust component of such a drought monitoring system is a land surface model (LSM). We are currently enhancing the Famine Early Warning Systems Network (FEWS NET) monitoring activities by configuring a custom instance of NASA's Land Information System (LIS) called the FEWS NET Land Data Assimilation System (FLDAS). Using the LIS Noah LSM, in-situ measurements, and remotely sensed data, we focus on the following question: How can Noah be best parameterized to accurately simulate hydroclimate variables associated with crop performance? Parameter value testing and validation is done by comparing modeled soil moisture against fortuitously available in-situ soil moisture observations in the West Africa. Direct testing and application of the FLDAS over African agropastoral locations is subject to some issues: [1] In many regions that are vulnerable to food insecurity ground based measurements of precipitation, evapotranspiration and soil moisture are sparse or non-existent, [2] standard landcover classes (e.g., the University of Maryland 5 km dataset), do not include representations of specific agricultural crops with relevant parameter values, and phenologies representing their growth stages from the planting date and [3] physically based land surface models and remote sensing rain data might still need to be calibrated or bias-corrected for the regions of interest. This research aims to address these issues by focusing on sites in the West African countries of Mali, Niger, and Benin where in-situ rainfall and soil moisture measurements are available from the African Monsoon Multidisciplinary Analysis (AMMA). Preliminary results from model experiments over Southern Malawi, validated with Normalized Difference Vegetation Index (NDVI) and maize yield data, show that the ability to detect a drought signal in modeled soil moisture and actual evapotranspiration was sensitive to parameters like minimum stomatal resistance, green vegetation fraction, and minimum threshold for transpiration stress. In addition to improving our understanding and representation of the land surface physics in agropastoral drought, this study moves us closer to confidently validating LSM estimates with remotely sensed data (e.g. MODIS NDVI), essential in regions that lack ground based measurements. Ultimately, these improved information products serve to better inform decision makers about seasonal food production and anticipate the need for relief, as well as guide climate change adaptation strategies, potentially saving millions of lives.

On the use of L-band microwave and multi-mission EO data for high resolution soil moisture

NASA Astrophysics Data System (ADS)

Bitar, Ahmad Al; Merlin, Olivier; Malbeteau, Yoann; Molero-Rodenas, Beatriz; Zribi, Mehrez; Sekhar, Muddu; Tomer, Sat Kumar; José Escorihuela, Maria; Stefan, Vivien; Suere, Christophe; Mialon, Arnaud; Kerr, Yann

2017-04-01

Sub-kilometric soil moisture maps have been increasingly mentioned as a need in the scientific community for many applications ranging from agronomical and hydrological (Wood et al. 2011). For example, this type of dataset will become essential to support the current evolution of the land surface and hydrologic modelling communities towards high resolution global modelling. But the ability of the different sensors to monitor soil moisture is different. The L-Band microwave EO provides, at a coarse resolution, the most sensitive information to surface soil moisture when compared to C-Band microwave, optical or C-band SAR. On the other hand the optical and radar sensors provide the spatial distribution of associated variables like surface soil moisture,surface temperature or vegetation leaf area index. This paper describes two complementary fusion approaches to obtain such data from optical or SAR in combination to microwave EO, and more precisely L-Band microwave from the SMOS mission. The first approach, called MAPSM, is based on the use of high resolution soil moisture from SAR and microwave. The two types of sensors have all weather capabilities. The approach uses the new concept of water change capacity (Tomer et al. 2015, 2016). It has been applied to the Berambadi watershed in South-India which is characterised by high cloud coverage. The second approach, called Dispatch, is based on the use of optical sensors in a physical disaggregation approach. It is a well-established approach (Merlin et al. 2012, Malbeteau et al. 2015) that has been implemented operationally in the CATDS (Centre Aval de Traitement des Données SMOS) processing centre (Molero et al. 2016). An analysis on the complementarity of the approaches is discussed. The results show the performances of the methods when compared to existing soil moisture monitoring networks in arid, sub-tropical and humid environments. They emphasis on the need for large inter-comparison studied for the qualification of such products on different climatic zones and on the need of an adaptative multisensor approach. The availability of the recent Sentinel-1 2 and 3 missions from ESA provides an exceptional environment to apply such algorithms at larger scales.

Value of Available Global Soil Moisture Products for Agricultural Monitoring

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Prediction of near-surface soil moisture at large scale by digital terrain modeling and neural networks.

PubMed

Lavado Contador, J F; Maneta, M; Schnabel, S

2006-10-01

The capability of Artificial Neural Network models to forecast near-surface soil moisture at fine spatial scale resolution has been tested for a 99.5 ha watershed located in SW Spain using several easy to achieve digital models of topographic and land cover variables as inputs and a series of soil moisture measurements as training data set. The study methods were designed in order to determining the potentials of the neural network model as a tool to gain insight into soil moisture distribution factors and also in order to optimize the data sampling scheme finding the optimum size of the training data set. Results suggest the efficiency of the methods in forecasting soil moisture, as a tool to assess the optimum number of field samples, and the importance of the variables selected in explaining the final map obtained.

The advanced qualtiy control techniques planned for the Internation Soil Moisture Network

NASA Astrophysics Data System (ADS)

Xaver, A.; Gruber, A.; Hegiova, A.; Sanchis-Dufau, A. D.; Dorigo, W. A.

2012-04-01

In situ soil moisture observations are essential to evaluate and calibrate modeled and remotely sensed soil moisture products. Although a number of meteorological networks and field campaigns measuring soil moisture exist on a global and long-term scale, their observations are not easily accessible and lack standardization of both technique and protocol. Thus, handling and especially comparing these datasets with satellite products or land surface models is a demanding issue. To overcome these limitations the International Soil Moisture Network (ISMN; http://www.ipf.tuwien.ac.at/insitu/) has been initiated to act as a centralized data hosting facility. One advantage of the ISMN is that users are able to access the harmonized datasets easily through a web portal. Another advantage is the fully automated processing chain including the data harmonization in terms of units and sampling interval, but even more important is the advanced quality control system each measurement has to run through. The quality of in situ soil moisture measurements is crucial for the validation of satellite- and model-based soil moisture retrievals; therefore a sophisticated quality control system was developed. After a check for plausibility and geophysical limits a quality flag is added to each measurement. An enhanced flagging mechanism was recently defined using a spectrum based approach to detect spurious spikes, jumps and plateaus. The International Soil Moisture Network has already evolved to one of the most important distribution platforms for in situ soil moisture observations and is still growing. Currently, data from 27 networks in total covering more than 800 stations in Europe, North America, Australia, Asia and Africa is hosted by the ISMN. Available datasets also include historical datasets as well as near real-time measurements. The improved quality control system will provide important information for satellite-based as well as land surface model-based validation studies.

Effects of relaxation of gluten network on rehydration kinetics of pasta.

PubMed

Ogawa, Takenobu; Hasegawa, Ayako; Adachi, Shuji

2014-01-01

The aim of this study was to investigate the effects of the relaxation of the gluten network on pasta rehydration kinetics. The moisture content of pasta, under conditions where the effects of the diffusion of water on the moisture content were negligible, was estimated by extrapolating the average moisture content of pasta of various diameters to 0 mm. The moisture content of imaginary, infinitely thin pasta did not reach equilibrium even after 1 h of rehydration. The rehydration of pasta made of only gluten was also measured. The rate constants estimated by the Long and Richman equation for both the pasta indicated that the rehydration kinetics of infinitely thin pasta were similar to those of gluten pasta. These results suggest that the swelling of starch by fast gelatinization was restricted by the honeycomb structural network of gluten and the relaxation of the gluten network controlled pasta rehydration kinetics.

Improved Prediction of Quasi-Global Vegetation Conditions Using Remotely-Sensed Surface Soil Moisture

NASA Technical Reports Server (NTRS)

Bolten, John; Crow, Wade

2012-01-01

The added value of satellite-based surface soil moisture retrievals for agricultural drought monitoring is assessed by calculating the lagged rank correlation between remotely-sensed vegetation indices (VI) and soil moisture estimates obtained both before and after the assimilation of surface soil moisture retrievals derived from the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) into a soil water balance model. Higher soil moisture/VI lag correlations imply an enhanced ability to predict future vegetation conditions using estimates of current soil moisture. Results demonstrate that the assimilation of AMSR-E surface soil moisture retrievals substantially improve the performance of a global drought monitoring system - particularly in sparsely-instrumented areas of the world where high-quality rainfall observations are unavailable.

A spatiotemporal analysis of hydrological patterns based on a wireless sensor network system

NASA Astrophysics Data System (ADS)

Plaza, F.; Slater, T. A.; Zhong, X.; Li, Y.; Liang, Y.; Liang, X.

2017-12-01

Understanding complicated spatiotemporal patterns of eco-hydrological variables at a small scale plays a profound role in improving predictability of high resolution distributed hydrological models. However, accurate and continuous monitoring of these complex patterns has become one of the main challenges in the environmental sciences. Wireless sensor networks (WSNs) have emerged as one of the most widespread potential solutions to achieve this. This study presents a spatiotemporal analysis of hydrological patterns (e.g., soil moisture, soil water potential, soil temperature and transpiration) based on observational data collected from a dense multi-hop wireless sensor network (WSN) in a steep-forested testbed located in Southwestern Pennsylvania, USA. At this WSN testbed with an approximate area of 3000 m2, environmental variables are collected from over 240 sensors that are connected to more than 100 heterogeneous motes. The sensors include the soil moisture of EC-5, soil temperature and soil water potential of MPS-1 and MPS-2, and sap flow sensors constructed in house. The motes consist of MICAz, IRIS and TelosB. In addition, several data loggers have been installed along the site to provide a comparative reference to the WSN measurements for the purpose of checking the WSN data quality. The edaphic properties monitored by the WSN sensors show strong agreement with the data logger measurements. Moreover, sap flow measurements, scaled to tree stand transpiration, are found to be reasonable. This study also investigates the feasibility and roles that these sensor measurements play in improving the performance of high-resolution distributed hydrological models. In particular, we explore this using a modified version of the Distributed Hydrological Soil Vegetation Model (DHSVM).

A data management and publication workflow for a large-scale, heterogeneous sensor network.

PubMed

Jones, Amber Spackman; Horsburgh, Jeffery S; Reeder, Stephanie L; Ramírez, Maurier; Caraballo, Juan

2015-06-01

It is common for hydrology researchers to collect data using in situ sensors at high frequencies, for extended durations, and with spatial distributions that produce data volumes requiring infrastructure for data storage, management, and sharing. The availability and utility of these data in addressing scientific questions related to water availability, water quality, and natural disasters relies on effective cyberinfrastructure that facilitates transformation of raw sensor data into usable data products. It also depends on the ability of researchers to share and access the data in useable formats. In this paper, we describe a data management and publication workflow and software tools for research groups and sites conducting long-term monitoring using in situ sensors. Functionality includes the ability to track monitoring equipment inventory and events related to field maintenance. Linking this information to the observational data is imperative in ensuring the quality of sensor-based data products. We present these tools in the context of a case study for the innovative Urban Transitions and Aridregion Hydrosustainability (iUTAH) sensor network. The iUTAH monitoring network includes sensors at aquatic and terrestrial sites for continuous monitoring of common meteorological variables, snow accumulation and melt, soil moisture, surface water flow, and surface water quality. We present the overall workflow we have developed for effectively transferring data from field monitoring sites to ultimate end-users and describe the software tools we have deployed for storing, managing, and sharing the sensor data. These tools are all open source and available for others to use.

Monitoring the subsurface hydrologic response to shallow landsliding in the San Francisco Bay Area, California

NASA Astrophysics Data System (ADS)

Collins, B. D.; Stock, J. D.; Foster, K. A.; Knepprath, N.; Reid, M. E.; Schmidt, K. M.; Whitman, M. W.

2011-12-01

Intense or prolonged rainfall triggers shallow landslides in steeplands of the San Francisco Bay Area each year. These landslides cause damage to built infrastructure and housing, and in some cases, lead to fatalities. Although our ability to forecast and map the distribution of rainfall has improved (e.g., NEXRAD, SMART-R), our ability to estimate landslide susceptibility is limited by a lack of information about the subsurface response to rainfall. In particular, the role of antecedent soil moisture content in setting the timing of shallow landslide failures remains unconstrained. Advances in instrumentation and telemetry have substantially reduced the cost of such monitoring, making it feasible to set up and maintain networks of such instruments in areas with a documented history of shallow landslides. In 2008, the U.S. Geological Survey initiated a pilot project to establish a series of shallow landslide monitoring stations in the San Francisco Bay area. The goal of this project is to obtain a long-term (multi-year) record of subsurface hydrologic conditions that occur from winter storms. Three monitoring sites are now installed in key landslide prone regions of the Bay Area (East Bay Hills, Marin County, and San Francisco Peninsula Hills) each consisting of a rain gage and multiple nests of soil-moisture sensors, matric-potential sensors, and piezometers. The sites were selected with similar characteristics in mind consisting of: (1) convergent bedrock hollow topographic settings located near ridge tops, (2) underlying sandstone bedrock substrates, (3) similar topographic gradients (~30°), (4) vegetative assemblages of grasses with minor chaparral, and (5) a documented history of landsliding in the vicinity of each site. These characteristics are representative of shallow-landslide-prone regions of the San Francisco Bay Area and also provide some constraint on the ability to compare and contrast subsurface response across different regions. Data streams from two of the sites, one operational in 2009 and one in 2010 have been analyzed and showcase both the seasonal patterns of moisture increase and decrease between summer-winter-summer conditions, as well as patterns of cyclical short-term wetting and drying as storms pass through the region. Further, the data show that at one location (East Bay Hills), storm-generated antecedent soil moisture conditions led to positive pore water pressures that correlate directly to shallow landsliding observed in the immediate vicinity of the monitoring site. This information, along with more extensive and continued monitoring and analysis should provide a basis and methodology for performing future shallow landslide assessments which depend not only on forecast rainfall, but also on pre-storm antecedent, subsurface soil moisture conditions.

Deploying temporary networks for upscaling of sparse network stations

NASA Astrophysics Data System (ADS)

Coopersmith, Evan J.; Cosh, Michael H.; Bell, Jesse E.; Kelly, Victoria; Hall, Mark; Palecki, Michael A.; Temimi, Marouane

2016-10-01

Soil observations networks at the national scale play an integral role in hydrologic modeling, drought assessment, agricultural decision support, and our ability to understand climate change. Understanding soil moisture variability is necessary to apply these measurements to model calibration, business and consumer applications, or even human health issues. The installation of soil moisture sensors as sparse, national networks is necessitated by limited financial resources. However, this results in the incomplete sampling of the local heterogeneity of soil type, vegetation cover, topography, and the fine spatial distribution of precipitation events. To this end, temporary networks can be installed in the areas surrounding a permanent installation within a sparse network. The temporary networks deployed in this study provide a more representative average at the 3 km and 9 km scales, localized about the permanent gauge. The value of such temporary networks is demonstrated at test sites in Millbrook, New York and Crossville, Tennessee. The capacity of a single U.S. Climate Reference Network (USCRN) sensor set to approximate the average of a temporary network at the 3 km and 9 km scales using a simple linear scaling function is tested. The capacity of a temporary network to provide reliable estimates with diminishing numbers of sensors, the temporal stability of those networks, and ultimately, the relationship of the variability of those networks to soil moisture conditions at the permanent sensor are investigated. In this manner, this work demonstrates the single-season installation of a temporary network as a mechanism to characterize the soil moisture variability at a permanent gauge within a sparse network.

Monitoring groundwater storage changes in the highly seasonal humid tropics: Validation of GRACE measurements in the Bengal Basin

NASA Astrophysics Data System (ADS)

Shamsudduha, M.; Taylor, R. G.; Longuevergne, L.

2012-02-01

Satellite monitoring of changes in terrestrial water storage provides invaluable information regarding the basin-scale dynamics of hydrological systems where ground-based records are limited. In the Bengal Basin of Bangladesh, we test the ability of satellite measurements under the Gravity Recovery and Climate Experiment (GRACE) to trace both the seasonality and trend in groundwater storage associated with intensive groundwater abstraction for dry-season irrigation and wet-season (monsoonal) recharge. We show that GRACE (CSR, GRGS) datasets of recent (2003 to 2007) groundwater storage changes (ΔGWS) correlate well (r = 0.77 to 0.93, p value < 0.0001) with in situ borehole records from a network of 236 monitoring stations and account for 44% of the total variation in terrestrial water storage (ΔTWS); highest correlation (r = 0.93, p value < 0.0001) and lowest root-mean-square error (<4 cm) are realized using a spherical harmonic product of CSR. Changes in surface water storage estimated from a network of 298 river gauging stations and soil-moisture derived from Land Surface Models explain 22% and 33% of ΔTWS, respectively. Groundwater depletion estimated from borehole hydrographs (-0.52 ± 0.30 km3 yr-1) is within the range of satellite-derived estimates (-0.44 to -2.04 km3 yr-1) that result from uncertainty associated with the simulation of soil moisture (CLM, NOAH, VIC) and GRACE signal-processing techniques. Recent (2003 to 2007) estimates of groundwater depletion are substantially greater than long-term (1985 to 2007) mean (-0.21 ± 0.03 km3 yr-1) and are explained primarily by substantial increases in groundwater abstraction for the dry-season irrigation and public water supplies over the last two decades.

Diagnosing soil moisture anomalies and neglected soil moisture source/sink processes via a thermal infrared-based two-source energy balance model

USDA-ARS?s Scientific Manuscript database

Atmospheric processes, especially those that occur in the surface and boundary layer, are significantly impacted by soil moisture (SM). Due to the observational gaps in the ground-based monitoring of SM, methodologies have been developed to monitor SM from satellite platforms. While many have focuse...

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

USDA-ARS?s Scientific Manuscript database

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

[The evaluation of the error of the thermal pulse technique used to measure moisture content of root substrates in space greenhouse

NASA Technical Reports Server (NTRS)

Podol'skii, I. G.; Norokh, A. A.; Bingham, G. E.; Brigham, G. E. (Principal Investigator); Campbell, W. F. (Principal Investigator)

2002-01-01

Point thermopulse probes were used to monitor moisture level in the root substrates during cultivation of higher plants in a space greenhouse. Investigated were performance data of the thermopulse moisture probe in integration with the space greenhouse. It was shown that within the substrate moisture range from 20 up to 100% of the full saturation the technique error does not exceed 1.5%. The thermopulse technique bears much promise for metrologic monitoring of the root substrate moisture content in space greenhouses no matter water and air supply technology.

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

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

Temporal changes of spatial soil moisture patterns: controlling factors explained with a multidisciplinary approach

NASA Astrophysics Data System (ADS)

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

2016-04-01

Characterizing the spatial patterns of soil moisture is critical for hydrological and meteorological models, as soil moisture is a key variable that controls matter and energy fluxes and soil-vegetation-atmosphere exchange processes. Deriving detailed process understanding at the hillslope scale is not trivial, because of the temporal variability of local soil moisture dynamics. Nevertheless, it remains a challenge to provide adequate information on the temporal variability of soil moisture and its controlling factors. Recent advances in wireless sensor technology allow monitoring of soil moisture dynamics with high temporal resolution at varying scales. In addition, mobile geophysical methods such as electromagnetic induction (EMI) have been widely used for mapping soil water content at the field scale with high spatial resolution, as being related to soil apparent electrical conductivity (ECa). The objective of this study was to characterize the spatial and temporal pattern of soil moisture at the hillslope scale and to infer the controlling hydrological processes, integrating well established and innovative sensing techniques, as well as new statistical methods. We combined soil hydrological and pedological expertise with geophysical measurements and methods from digital soil mapping for designing a wireless soil moisture monitoring network. For a hillslope site within the Schäfertal catchment (Central Germany), soil water dynamics were observed during 14 months, and soil ECa was mapped on seven occasions whithin this period of time using an EM38-DD device. Using the Spearman rank correlation coefficient, we described the temporal persistence of a dry and a wet characteristic state of soil moisture as well as the switching mechanisms, inferring the local properties that control the observed spatial patterns and the hydrological processes driving the transitions. Based on this, we evaluated the use of EMI for mapping the spatial pattern of soil moisture under different hydrologic conditions and the factors controlling the temporal variability of the ECa-soil moisture relationship. The approach provided valuable insight into the time-varying contribution of local and nonlocal factors to the characteristic spatial patterns of soil moisture and the transition mechanisms. The spatial organization of soil moisture was controlled by different processes in different soil horizons, and the topsoil's moisture did not mirror processes that take place within the soil profile. Results show that, for the Schäfertal hillslope site which is presumed to be representative for non-intensively managed soils with moderate clay content, local soil properties (e.g., soil texture and porosity) are the major control on the spatial pattern of ECa. In contrast, the ECa-soil moisture relationship is small and varies over time indicating that ECa is not a good proxy for soil moisture estimation at the investigated site.Occasionally observed stronger correlations between ECa and soil moisture may be explained by background dependencies of ECa to other state variables such as pore water electrical conductivity. The results will help to improve conceptual understanding for hydrological model studies at similar or smaller scales, and to transfer observation concepts and process understanding to larger or less instrumented sites, as well as to constrain the use of EMI-based ECa data for hydrological applications.

Novel method for water vapour monitoring using wireless communication networks measurements

NASA Astrophysics Data System (ADS)

David, N.; Alpert, P.; Messer, H.

2009-04-01

We propose a new technique for monitoring near-surface water vapour, by estimating humidity from data collected through existing wireless communication networks. Water vapour plays a crucial part in a variety of atmospheric processes. As the most influential of greenhouse gases, it absorbs long-wave terrestrial radiation. The water vapour cycle of evaporation and recondensation is a major energy redistributing mechanism transferring heat energy from the Earth's surface to the atmosphere. Additionally, humidity has an important role in weather forecasting as a key variable required for initialization of atmospheric models and hazard warning techniques. However, current methods of monitoring humidity suffer from low spatial resolution, high cost or a lack of precision when measuring near ground levels. Weather conditions and atmospheric phenomena affect the electromagnetic channel, causing attenuations to the radio signals. Thus, wireless communication networks are in effect built-in environmental monitoring facilities. The wireless microwave links, used in these networks, are widely deployed by cellular providers for backhaul communication between base stations, a few tens of meters above ground level. As a result, the proposed method can provide moisture observations at high temporal and spatial resolution. Further, the implementation cost is minimal, since the data used is already collected and saved by the cellular operators. In addition - many of these links are installed in areas where access is difficult such as orographic terrain and complex topography. As such, our method enables measurements in places that have been hard to measure in the past, or have never been measured before. The technique is restricted to weather conditions which include absence of rain, fog or clouds along the propagation path. We present results from real-data measurements taken from microwave links used in a backhaul cellular network that show very good agreement with surface station humidity measurements.

Moisture Monitoring at Area G, Technical Area 54, Los Alamos National Laboratory, 2016 Status Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Levitt, Daniel Glenn; Birdsell, Kay Hanson; Jennings, Terry L.

Hydrological characterization and moisture monitoring activities provide data required for evaluating the transport of subsurface contaminants in the unsaturated and saturated zones beneath Area G, and for the Area G Performance Assessment and Composite Analysis. These activities have been ongoing at Area G, Technical Area 54 of the Los Alamos National Laboratory since waste disposal operations began in 1957. This report summarizes the hydrological characterization and moisture monitoring activities conducted at Area G. It includes moisture monitoring data collected from 1986 through 2016 from numerous boreholes and access tubes with neutron moisture meters, as well as data collected by automatedmore » dataloggers for water content measurement sensors installed in a waste disposal pit cover, and buried beneath the floor of a waste disposal pit. This report is an update of a nearly identical report by Levitt et al., (2015) that summarized data collected through early 2015; this report includes additional moisture monitoring data collected at Pit 31 and the Pit 38 extension through December, 2016. It also includes information from the Jennings and French (2009) moisture monitoring report and includes all data from Jennings and French (2009) and the Draft 2010 Addendum moisture monitoring report (Jennings and French, 2010). For the 2015 version of this report, all neutron logging data, including neutron probe calibrations, were investigated for quality and pedigree. Some data were recalculated using more defensible calibration data. Therefore, some water content profiles are different from those in the Jennings and French (2009) report. All of that information is repeated in this report for completeness. Monitoring and characterization data generally indicate that some areas of the Area G vadose zone are consistent with undisturbed conditions, with water contents of less than five percent by volume in the top two layers of the Bandelier tuff at Area G. These data also indicate that other areas of the vadose zone are affected by waste disposal activities that have been ongoing at Area G since 1957, a period of nearly 60 years. In some areas, water content profiles indicate increases in water content to depths of tens of meters, especially in areas covered by asphalt and structures.« less

Thermodynamic Profiles of the Destructive June 2012 Derecho

NASA Astrophysics Data System (ADS)

Liu, C.; Novakovskaia, E.; Bosse, J.; Ware, R.; Stillman, D.; Sloop, C.; Blanchette, L.; Demoz, B.; Nelson, M.; Cooper, L.; Czarnetzki, A.; Reehorst, A.

2012-12-01

The June 2012 mid-Atlantic and Midwest Derecho was one of the most destructive and deadly fast-moving severe thunderstorm events in North American history. The derecho produced wind gusts approaching 100 miles per hour as it traveled more than 600 miles across large sections of the Midwestern United States, the central Appalachians and the Mid-Atlantic States on the afternoon and evening of June 29, 2012 and into the early morning of June 30, 2012. It produced hurricane-like impacts with little warning, resulting in more than 20 deaths, widespread damage and millions of power outages across the entire affected region. We present continuous temperature and moisture profiles observed by microwave radiometers, and derived forecast indices, along the storm path at locations in Iowa, Ohio and Maryland, providing unique perspective on the evolution of this historic storm. For example, an extreme CAPE value of 5,000 J/kg was derived from radiometer observations at Germantown, Maryland ten hours before storm passage, and 80 knot Wind Index (WINDEX) was derived seven hours before passage. The Germantown radiometer is operated as part of the Earth Networks Boundary Layer Network (BLN) for continuous thermodynamic monitoring of the planetary boundary layer up to 30,000 feet. The BLN uses Radiometrics microwave profilers providing continuous temperature and humidity soundings with radiosonde-equivalent observation accuracy, and unique liquid soundings. This case study illustrates the promise for severe storm forecast improvement based on continuous monitoring of temperature and moisture in the boundary layer and above.

A new methodology for determination of macroscopic transport parameters in drying porous media

NASA Astrophysics Data System (ADS)

Attari Moghaddam, A.; Kharaghani, A.; Tsotsas, E.; Prat, M.

2015-12-01

Two main approaches have been used to model the drying process: The first approach considers the partially saturated porous medium as a continuum and partial differential equations are used to describe the mass, momentum and energy balances of the fluid phases. The continuum-scale models (CM) obtained by this approach involve constitutive laws which require effective material properties, such as the diffusivity, permeability, and thermal conductivity which are often determined by experiments. The second approach considers the material at the pore scale, where the void space is represented by a network of pores (PN). Micro- or nanofluidics models used in each pore give rise to a large system of ordinary differential equations with degrees of freedom at each node of the pore network. In this work, the moisture transport coefficient (D), the pseudo desorption isotherm inside the network and at the evaporative surface are estimated from the post-processing of the three-dimensional pore network drying simulations for fifteen realizations of the pore space geometry from a given probability distribution. A slice sampling method is used in order to extract these parameters from PN simulations. The moisture transport coefficient obtained in this way is shown in Fig. 1a. The minimum of average D values demonstrates the transition between liquid dominated moisture transport region and vapor dominated moisture transport region; a similar behavior has been observed in previous experimental findings. A function is fitted to the average D values and then is fed into the non-linear moisture diffusion equation. The saturation profiles obtained from PN and CM simulations are shown in Fig. 1b. Figure 1: (a) extracted moisture transport coefficient during drying for fifteen realizations of the pore network, (b) average moisture profiles during drying obtained from PN and CM simulations.

Application of Terrestrial Microwave Remote Sensing to Agricultural Drought Monitoring

NASA Astrophysics Data System (ADS)

Crow, W. T.; Bolten, J. D.

2014-12-01

Root-zone soil moisture information is a valuable diagnostic for detecting the onset and severity of agricultural drought. Current attempts to globally monitor root-zone soil moisture are generally based on the application of soil water balance models driven by observed meteorological variables. Such systems, however, are prone to random error associated with: incorrect process model physics, poor parameter choices and noisy meteorological inputs. The presentation will describe attempts to remediate these sources of error via the assimilation of remotely-sensed surface soil moisture retrievals from satellite-based passive microwave sensors into a global soil water balance model. Results demonstrate the ability of satellite-based soil moisture retrieval products to significantly improve the global characterization of root-zone soil moisture - particularly in data-poor regions lacking adequate ground-based rain gage instrumentation. This success has lead to an on-going effort to implement an operational land data assimilation system at the United States Department of Agriculture's Foreign Agricultural Service (USDA FAS) to globally monitor variations in root-zone soil moisture availability via the integration of satellite-based precipitation and soil moisture information. Prospects for improving the performance of the USDA FAS system via the simultaneous assimilation of both passive and active-based soil moisture retrievals derived from the upcoming NASA Soil Moisture Active/Passive mission will also be discussed.

Data assimilation to extract soil moisture information from SMAP observations

USDA-ARS?s Scientific Manuscript database

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

Application of neural network to remote sensing of soil moisture using theoretical polarimetric backscattering coefficients

NASA Technical Reports Server (NTRS)

Wang, L.; Shin, R. T.; Kong, J. A.; Yueh, S. H.

1993-01-01

This paper investigates the potential application of neural network to inversion of soil moisture using polarimetric remote sensing data. The neural network used for the inversion of soil parameters is multi-layer perceptron trained with the back-propagation algorithm. The training data include the polarimetric backscattering coefficients obtained from theoretical surface scattering models together with an assumed nominal range of soil parameters which are comprised of the soil permittivity and surface roughness parameters. Soil permittivity is calculated from the soil moisture and the assumed soil texture based on an empirical formula at C-, L-, and P-bands. The rough surface parameters for the soil surface, which is described by the Gaussian random process, are the root-mean-square (rms) height and correlation length. For the rough surface scattering, small perturbation method is used for the L-band frequency, and Kirchhoff approximation is used for the C-band frequency to obtain the corresponding backscattering coefficients. During the training, the backscattering coefficients are the inputs to the neural net and the output from the net are compared with the desired soil parameters to adjust the interconnecting weights. The process is repeated for each input-output data entry and then for the entire training data until convergence is reached. After training, the backscattering coefficients are applied to the trained neural net to retrieve the soil parameters which are compared with the desired soil parameters to verify the effectiveness of this technique. Several cases are examined. First, for simplicity, the correlation length and rms height of the soil surface are fixed while soil moisture is varied. Soil moisture obtained using the neural networks with either L-band or C-band backscattering coefficients for the HH and VV polarizations as inputs is in good agreement with the desired soil moisture. The neural net output matches the desired output for the soil moisture range of 16 to 60 percent for the C-band case. The next case investigated is to vary both soil moisture and rms height while keeping the correlation length fixed. For this case, C-band backscattering coefficients are not sufficient for retrieving two parameters because the Kirchhoff approximation gives the same HH and VV backscattering coefficients. Therefore, the backscattering coefficients at two different frequency bands are necessary to find both the soil moisture and rms height. Finally, the neural nets are also applied to simultaneously invert soil moisture, rms height, and correlation length. Overall, the soil moisture retrieved from the neural network agrees very well with the desired soil moisture. This suggests that the neural network shows potential for retrieval of soil parameters from remote sensing data.

Prolongation of SMAP to Spatiotemporally Seamless Coverage of Continental U.S. Using a Deep Learning Neural Network

NASA Astrophysics Data System (ADS)

Fang, Kuai; Shen, Chaopeng; Kifer, Daniel; Yang, Xiao

2017-11-01

The Soil Moisture Active Passive (SMAP) mission has delivered valuable sensing of surface soil moisture since 2015. However, it has a short time span and irregular revisit schedules. Utilizing a state-of-the-art time series deep learning neural network, Long Short-Term Memory (LSTM), we created a system that predicts SMAP level-3 moisture product with atmospheric forcings, model-simulated moisture, and static physiographic attributes as inputs. The system removes most of the bias with model simulations and improves predicted moisture climatology, achieving small test root-mean-square errors (<0.035) and high-correlation coefficients >0.87 for over 75% of Continental United States, including the forested southeast. As the first application of LSTM in hydrology, we show the proposed network avoids overfitting and is robust for both temporal and spatial extrapolation tests. LSTM generalizes well across regions with distinct climates and environmental settings. With high fidelity to SMAP, LSTM shows great potential for hindcasting, data assimilation, and weather forecasting.

Spatial Estimation of Soil Moisture Using Synthetic Aperture Radar in Alaska

NASA Astrophysics Data System (ADS)

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

1999-01-01

A spatially distributed Model of Arctic Thermal and Hydrologic processes (MATH) has been developed. One of the attributes of this model is the spatial and temporal prediction of soil moisture in the active layer. The spatially distributed output from this model required verification data obtained through remote sensing to assess performance at the watershed scale independently. Therefore, a neural network was trained to predict soil moisture contents near the ground surface. The input to train the neural network is synthetic aperture radar (SAR) pixel value, and field measurements of soil moisture, and vegetation, which were used as a surrogate for surface roughness. Once the network was trained, soil moisture predictions were made based on SAR pixel value and vegetation. These results were then used for comparison with results from the hydrologic model. The quality of neural network input was less than anticipated. Our digital elevation model (DEM) was not of high enough resolution to allow exact co-registration with soil moisture measurements; therefore, the statistical correlations were not as good as hoped. However, the spatial pattern of the SAR derived soil moisture contents compares favorably with the hydrologic MATH model results. Primary surface parameters that effect SAR include topography, surface roughness, vegetation cover and soil texture. Single parameters that are considered to influence SAR include incident angle of the radar, polarization of the radiation, signal strength and returning signal integration, to name a few. These factors influence the reflectance, but if one adequately quantifies the influences of terrain and roughness, it is considered possible to extract information on soil moisture from SAR imagery analysis and in turn use SAR imagery to validate hydrologic models

Advanced Soil Moisture Network Technologies; Developments in Collecting in situ Measurements for Remote Sensing Missions

NASA Astrophysics Data System (ADS)

Moghaddam, M.; Silva, A. R. D.; Akbar, R.; Clewley, D.

2015-12-01

The Soil moisture Sensing Controller And oPtimal Estimator (SoilSCAPE) wireless sensor network has been developed to support Calibration and Validation activities (Cal/Val) for large scale soil moisture remote sensing missions (SMAP and AirMOSS). The technology developed here also readily supports small scale hydrological studies by providing sub-kilometer widespread soil moisture observations. An extensive collection of semi-sparse sensor clusters deployed throughout north-central California and southern Arizona provide near real time soil moisture measurements. Such a wireless network architecture, compared to conventional single points measurement profiles, allows for significant and expanded soil moisture sampling. The work presented here aims at discussing and highlighting novel and new technology developments which increase in situ soil moisture measurements' accuracy, reliability, and robustness with reduced data delivery latency. High efficiency and low maintenance custom hardware have been developed and in-field performance has been demonstrated for a period of three years. The SoilSCAPE technology incorporates (a) intelligent sensing to prevent erroneous measurement reporting, (b) on-board short term memory for data redundancy, (c) adaptive scheduling and sampling capabilities to enhance energy efficiency. A rapid streamlined data delivery architecture openly provides distribution of in situ measurements to SMAP and AirMOSS cal/val activities and other interested parties.

Field scale spatiotemporal analysis of surface soil moisture for evaluating point-scale in situ networks

USDA-ARS?s Scientific Manuscript database

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...

Multi-decadal analysis of root-zone soil moisture applying the exponential filter across CONUS

NASA Astrophysics Data System (ADS)

Tobin, Kenneth J.; Torres, Roberto; Crow, Wade T.; Bennett, Marvin E.

2017-09-01

This study applied the exponential filter to produce an estimate of root-zone soil moisture (RZSM). Four types of microwave-based, surface satellite soil moisture were used. The core remotely sensed data for this study came from NASA's long-lasting AMSR-E mission. Additionally, three other products were obtained from the European Space Agency Climate Change Initiative (CCI). These datasets were blended based on all available satellite observations (CCI-active, CCI-passive, and CCI-combined). All of these products were 0.25° and taken daily. We applied the filter to produce a soil moisture index (SWI) that others have successfully used to estimate RZSM. The only unknown in this approach was the characteristic time of soil moisture variation (T). We examined five different eras (1997-2002; 2002-2005; 2005-2008; 2008-2011; 2011-2014) that represented periods with different satellite data sensors. SWI values were compared with in situ soil moisture data from the International Soil Moisture Network at a depth ranging from 20 to 25 cm. Selected networks included the US Department of Energy Atmospheric Radiation Measurement (ARM) program (25 cm), Soil Climate Analysis Network (SCAN; 20.32 cm), SNOwpack TELemetry (SNOTEL; 20.32 cm), and the US Climate Reference Network (USCRN; 20 cm). We selected in situ stations that had reasonable completeness. These datasets were used to filter out periods with freezing temperatures and rainfall using data from the Parameter elevation Regression on Independent Slopes Model (PRISM). Additionally, we only examined sites where surface and root-zone soil moisture had a reasonably high lagged r value (r > 0. 5). The unknown T value was constrained based on two approaches: optimization of root mean square error (RMSE) and calculation based on the normalized difference vegetation index (NDVI) value. Both approaches yielded comparable results; although, as to be expected, the optimization approach generally outperformed NDVI-based estimates. The best results were noted at stations that had an absolute bias within 10 %. SWI estimates were more impacted by the in situ network than the surface satellite product used to drive the exponential filter. The average Nash-Sutcliffe coefficients (NSs) for ARM ranged from -0. 1 to 0.3 and were similar to the results obtained from the USCRN network (0.2-0.3). NS values from the SCAN and SNOTEL networks were slightly higher (0.1-0.5). These results indicated that this approach had some skill in providing an estimate of RZSM. In terms of RMSE (in volumetric soil moisture), ARM values actually outperformed those from other networks (0.02-0.04). SCAN and USCRN RMSE average values ranged from 0.04 to 0.06 and SNOTEL average RMSE values were higher (0.05-0.07). These values were close to 0.04, which is the baseline value for accuracy designated for many satellite soil moisture missions.

Determining the frequency, depth and velocity of preferential flow by high frequency soil moisture monitoring

NASA Astrophysics Data System (ADS)

Hardie, Marcus; Lisson, Shaun; Doyle, Richard; Cotching, William

2013-01-01

Preferential flow in agricultural soils has been demonstrated to result in agrochemical mobilisation to shallow ground water. Land managers and environmental regulators need simple cost effective techniques for identifying soil - land use combinations in which preferential flow occurs. Existing techniques for identifying preferential flow have a range of limitations including; often being destructive, non in situ, small sampling volumes, or are subject to artificial boundary conditions. This study demonstrated that high frequency soil moisture monitoring using a multi-sensory capacitance probe mounted within a vertically rammed access tube, was able to determine the occurrence, depth, and wetting front velocity of preferential flow events following rainfall. Occurrence of preferential flow was not related to either rainfall intensity or rainfall amount, rather preferential flow occurred when antecedent soil moisture content was below 226 mm soil moisture storage (0-70 cm). Results indicate that high temporal frequency soil moisture monitoring may be used to identify soil type - land use combinations in which the presence of preferential flow increases the risk of shallow groundwater contamination by rapid transport of agrochemicals through the soil profile. However use of high frequency based soil moisture monitoring to determine agrochemical mobilisation risk may be limited by, inability to determine the volume of preferential flow, difficulty observing macropore flow at high antecedent soil moisture content, and creation of artificial voids during installation of access tubes in stony soils.

Monitoring of Double Stud Wall Moisture Conditions in the Northeast

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ueno, K.

2015-03-01

Double-stud walls insulated with cellulose or low-density spray foam can have R-values of 40 or higher. However, double stud walls have a higher risk of interior-sourced condensation moisture damage, when compared with high-R approaches using exterior insulating sheathing.; Moisture conditions in double stud walls were monitored in Zone 5A (Massachusetts); three double stud assemblies were compared.

Monitoring moisture content, temperature, and humidity in whole-tree pine chip piles

Treesearch

John Klepac; Dana Mitchell; Jason Thompson

2015-01-01

Two whole-tree chip piles were monitored for moisture content, temperature, and relative humidity from October 8th, 2010 to March 16th, 2011 at a location in south Alabama. Initial moisture content samples were collected immediately after chips were delivered to the study location on October 8th for Pile 1 and October 22nd for Pile 2. During pile construction, Lascar...

Monitoring of Double-Stud Wall Moisture Conditions in the Northeast

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ueno, K.

2015-03-01

Double-stud walls insulated with cellulose or low-density spray foam can have R-values of 40 or higher. However, double-stud walls have a higher risk of interior-sourced condensation moisture damage when compared with high-R approaches using exterior insulating sheathing. Moisture conditions in double-stud walls were monitored in Zone 5A (Massachusetts); three double-stud assemblies were compared.

Model-based surface soil moisture (SSM) retrieval algorithm using multi-temporal RISAT-1 C-band SAR data

NASA Astrophysics Data System (ADS)

Pandey, Dharmendra K.; Maity, Saroj; Bhattacharya, Bimal; Misra, Arundhati

2016-05-01

Accurate measurement of surface soil moisture of bare and vegetation covered soil over agricultural field and monitoring the changes in surface soil moisture is vital for estimation for managing and mitigating risk to agricultural crop, which requires information and knowledge to assess risk potential and implement risk reduction strategies and deliver essential responses. The empirical and semi-empirical model-based soil moisture inversion approach developed in the past are either sensor or region specific, vegetation type specific or have limited validity range, and have limited scope to explain physical scattering processes. Hence, there is need for more robust, physical polarimetric radar backscatter model-based retrieval methods, which are sensor and location independent and have wide range of validity over soil properties. In the present study, Integral Equation Model (IEM) and Vector Radiative Transfer (VRT) model were used to simulate averaged backscatter coefficients in various soil moisture (dry, moist and wet soil), soil roughness (smooth to very rough) and crop conditions (low to high vegetation water contents) over selected regions of Gujarat state of India and the results were compared with multi-temporal Radar Imaging Satellite-1 (RISAT-1) C-band Synthetic Aperture Radar (SAR) data in σ°HH and σ°HV polarizations, in sync with on field measured soil and crop conditions. High correlations were observed between RISAT-1 HH and HV with model simulated σ°HH & σ°HV based on field measured soil with the coefficient of determination R2 varying from 0.84 to 0.77 and RMSE varying from 0.94 dB to 2.1 dB for bare soil. Whereas in case of winter wheat crop, coefficient of determination R2 varying from 0.84 to 0.79 and RMSE varying from 0.87 dB to 1.34 dB, corresponding to with vegetation water content values up to 3.4 kg/m2. Artificial Neural Network (ANN) methods were adopted for model-based soil moisture inversion. The training datasets for the NNs were obtained from theoretical forward-scattering models with controlled parameters, thus allowing the control of wide range of soil and crop parameters with which the network was trained. A preliminary performance analysis showed good results with estimation of soil moisture with RMSE better than 6%.

Drought monitoring with soil moisture active passive (SMAP) measurements

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

Novel method for water vapour monitoring using wireless communication networks measurements

NASA Astrophysics Data System (ADS)

David, N.; Alpert, P.; Messer, H.

2010-09-01

We propose a new technique for monitoring near-surface water vapour, by estimating humidity from data collected through existing wireless communication networks. Weather conditions and atmospheric phenomena affect the electromagnetic channel, causing attenuations to the radio signals. Thus, wireless communication networks are in effect built-in environmental monitoring facilities. The wireless microwave links, used in these networks, are widely deployed by cellular providers for backhaul communication between base stations, a few tens of meters above ground level. As a result, if all available measurements are used, the proposed method can provide moisture observations with high spatial resolution and potentially high temporal resolution. Further, the implementation cost is minimal, since the data used are already collected and saved by the cellular operators. In addition - many of these links are installed in areas where access is difficult such as orographic terrain and complex topography. As such, our method enables measurements in places that have been hard to measure in the past, or have never been measured before. The technique is restricted to weather conditions which exclude rain, fog or clouds along the propagation path. Strong winds that may cause movement of the link transmitter or receiver (or both) may also interfere with the ability to conduct accurate measurements. We present results from real-data measurements taken from microwave links used in a backhaul cellular network that show very good correlation with surface station humidity measurements (comparisons were performed for several links, found at different locations, during different time periods, showing correlations in the range of 0.5-0.9).

Physical aging and its influence on the reliability of network epoxies and epoxy-matrix composites

NASA Technical Reports Server (NTRS)

Heinemann, K.

1983-01-01

The matrix-dominated physical and mechanical properties of a carbon fiber reinforced epoxy composite and a neat epoxy resin were found to be affected by sub-Tg annealing in nitrogen and dark atmosphere. Postcured specimens of Thornel 300 carbon-fiber/Fiberite 934 epoxy as well as Fiberite 934 epoxy resin were quenched from above Tg and given annealing at 140 C, 110 C, or 80 C, for time up to one-hundred thousand minutes. No weight loss was observed during annealing at these temperatures. Significant variations were found in density, modulus, hardness, damping, moisture absorption ability, thermal expansivity. Moisture-epoxy interactious were also studied. The kinetics of aging as well as the molecular aggregation during this densification process were monitored by differential scanning calorimetry, dynamic mechanical analysis, density gradient column, microhardness tester, Instron, and solid-state nuclear magnetic resonance spectroscopy.

Monitoring methods and predictive models for water status in Jonathan apples.

PubMed

Trincă, Lucia Carmen; Căpraru, Adina-Mirela; Arotăriţei, Dragoş; Volf, Irina; Chiruţă, Ciprian

2014-02-01

Evaluation of water status in Jonathan apples was performed for 20 days. Loss moisture content (LMC) was carried out through slow drying of wholes apples and the moisture content (MC) was carried out through oven drying and lyophilisation for apple samples (chunks, crushed and juice). We approached a non-destructive method to evaluate LMC and MC of apples using image processing and multilayer neural networks (NN) predictor. We proposed a new simple algorithm that selects the texture descriptors based on initial set heuristically chosen. Both structure and weights of NN are optimised by a genetic algorithm with variable length genotype that led to a high precision of the predictive model (R(2)=0.9534). In our opinion, the developing of this non-destructive method for the assessment of LMC and MC (and of other chemical parameters) seems to be very promising in online inspection of food quality. Copyright © 2013 Elsevier Ltd. All rights reserved.

Ecohydrological drought monitoring and prediction using a land data assimilation system

NASA Astrophysics Data System (ADS)

Sawada, Y.; Koike, T.

2017-12-01

Despite the importance of the ecological and agricultural aspects of severe droughts, few drought monitor and prediction systems can forecast the deficit of vegetation growth. To address this issue, we have developed a land data assimilation system (LDAS) which can simultaneously simulate soil moisture and vegetation dynamics. By assimilating satellite-observed passive microwave brightness temperature, which is sensitive to both surface soil moisture and vegetation water content, we can significantly improve the skill of a land surface model to simulate surface soil moisture, root zone soil moisture, and leaf area index (LAI). We run this LDAS to generate a global ecohydrological land surface reanalysis product. In this presentation, we will demonstrate how useful this new reanalysis product is to monitor and analyze the historical mega-droughts. In addition, using the analyses of soil moistures and LAI as initial conditions, we can forecast the ecological and hydrological conditions in the middle of droughts. We will present our recent effort to develop a near real time ecohydrological drought monitoring and prediction system in Africa by combining the LDAS and the atmospheric seasonal prediction.

Cloud-based application for rice moisture content measurement using image processing technique and perceptron neural network

NASA Astrophysics Data System (ADS)

Cruz, Febus Reidj G.; Padilla, Dionis A.; Hortinela, Carlos C.; Bucog, Krissel C.; Sarto, Mildred C.; Sia, Nirlu Sebastian A.; Chung, Wen-Yaw

2017-02-01

This study is about the determination of moisture content of milled rice using image processing technique and perceptron neural network algorithm. The algorithm involves several inputs that produces an output which is the moisture content of the milled rice. Several types of milled rice are used in this study, namely: Jasmine, Kokuyu, 5-Star, Ifugao, Malagkit, and NFA rice. The captured images are processed using MATLAB R2013a software. There is a USB dongle connected to the router which provided internet connection for online web access. The GizDuino IOT-644 is used for handling the temperature and humidity sensor, and for sending and receiving of data from computer to the cloud storage. The result is compared to the actual moisture content range using a moisture tester for milled rice. Based on results, this study provided accurate data in determining the moisture content of the milled rice.

Development of Innovative Technology to Provide Low-Cost Surface Atmospheric Observations

NASA Astrophysics Data System (ADS)

Kucera, Paul; Steinson, Martin

2016-04-01

Accurate and reliable real-time monitoring and dissemination of observations of surface weather conditions is critical for a variety of societal applications. Applications that provide local and regional information about temperature, precipitation, moisture, and winds, for example, are important for agriculture, water resource monitoring, health, and monitoring of hazard weather conditions. In many regions in Africa (and other global locations), surface weather stations are sparsely located and/or of poor quality. Existing stations have often been sited incorrectly, not well-maintained, and have limited communications established at the site for real-time monitoring. The US National Weather Service (NWS) International Activities Office (IAO) in partnership with University Corporation for Atmospheric Research (UCAR)/National Center for Atmospheric Research (NCAR) and funded by the United States Agency for International Development (USAID) Office of Foreign Disaster Assistance (OFDA) has started an initiative to develop and deploy low-cost weather instrumentation in sparsely observed regions of the world. The goal is to provide observations for environmental monitoring, and early warning alert systems that can be deployed at weather services in developing countries. Instrumentation is being designed using innovative new technologies such as 3D printers, Raspberry Pi computing systems, and wireless communications. The initial effort is focused on designing a surface network using GIS-based tools, deploying an initial network in Zambia, and providing training to Zambia Meteorological Department (ZMD) staff. The presentation will provide an overview of the project concepts, design of the low cost instrumentation, and initial experiences deploying a surface network deployment in Zambia.

Electrical resistance tomography to monitor unsaturated moisture flow in cementitious materials

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hallaji, Milad; Seppänen, Aku; Pour-Ghaz, Mohammad, E-mail: mpourghaz@ncsu.edu

2015-03-15

Traditionally the electrically-based assessment of the moisture flow in cement-based materials relies on two- or four-point measurements. In this paper, imaging of moisture distribution with electrical resistance tomography (ERT) is considered. Especially, the aim is to study whether ERT could give information on unsaturated moisture flows in cases where the flow is non-uniform. In the experiment, the specimens are monitored with ERT during the water ingress. The ERT reconstructions are compared with neutron radiographs, which provide high resolution information on the 2D distribution of the moisture. The results indicate that ERT is able to detect the moisture movement and tomore » show approximately the shape and position of the water front even if the flow is nonuniform.« less

Implementation monitoring temperature, humidity and mositure soil based on wireless sensor network for e-agriculture technology

NASA Astrophysics Data System (ADS)

Sumarudin, A.; Ghozali, A. L.; Hasyim, A.; Effendi, A.

2016-04-01

Indonesian agriculture has great potensial for development. Agriculture a lot yet based on data collection for soil or plant, data soil can use for analys soil fertility. We propose e-agriculture system for monitoring soil. This system can monitoring soil status. Monitoring system based on wireless sensor mote that sensing soil status. Sensor monitoring utilize soil moisture, humidity and temperature. System monitoring design with mote based on microcontroler and xbee connection. Data sensing send to gateway with star topology with one gateway. Gateway utilize with mini personal computer and connect to xbee cordinator mode. On gateway, gateway include apache server for store data based on My-SQL. System web base with YII framework. System done implementation and can show soil status real time. Result the system can connection other mote 40 meters and mote lifetime 7 hours and minimum voltage 7 volt. The system can help famer for monitoring soil and farmer can making decision for treatment soil based on data. It can improve the quality in agricultural production and would decrease the management and farming costs.

Ground Control Point - Wireless System Network for UAV-based environmental monitoring applications

NASA Astrophysics Data System (ADS)

Mejia-Aguilar, Abraham

2016-04-01

In recent years, Unmanned Aerial Vehicles (UAV) have seen widespread civil applications including usage for survey and monitoring services in areas such as agriculture, construction and civil engineering, private surveillance and reconnaissance services and cultural heritage management. Most aerial monitoring services require the integration of information acquired during the flight (such as imagery) with ground-based information (such as GPS information or others) for improved ground truth validation. For example, to obtain an accurate 3D and Digital Elevation Model based on aerial imagery, it is necessary to include ground-based information of coordinate points, which are normally acquired with surveying methods based on Global Position Systems (GPS). However, GPS surveys are very time consuming and especially for longer time series of monitoring data repeated GPS surveys are necessary. In order to improve speed of data collection and integration, this work presents an autonomous system based on Waspmote technologies build on single nodes interlinked in a Wireless Sensor Network (WSN) star-topology for ground based information collection and later integration with surveying data obtained by UAV. Nodes are designed to be visible from the air, to resist extreme weather conditions with low-power consumption. Besides, nodes are equipped with GPS as well as Inertial Measurement Unit (IMU), accelerometer, temperature and soil moisture sensors and thus provide significant advantages in a broad range of applications for environmental monitoring. For our purpose, the WSN transmits the environmental data with 3G/GPRS to a database on a regular time basis. This project provides a detailed case study and implementation of a Ground Control Point System Network for UAV-based vegetation monitoring of dry mountain grassland in the Matsch valley, Italy.

Recent advances in environmental monitoring using commercial microwave links

NASA Astrophysics Data System (ADS)

Alpert, Pinhas; David, Noam; Messer-Yaron, Hagit; Samuels, Rana

2013-04-01

The propagation of electromagnetic radiation in the lower atmosphere, at centimeter wavelengths, is impaired by atmospheric conditions. Absorption and scattering of the radiation, at frequencies of tens of GHz, are directly related to the atmospheric phenomena, primarily precipitation, oxygen, mist, fog and water vapor. As we have recently shown, commercial wireless communication networks supply high resolution precipitation measurements at ground level while often being situated in flood prone areas, covering large parts of these hazardous regions. On the other hand, at present, there are no satisfactory real time flash flood warning facilities found to cope well with this phenomenon. I will exemplify the flash flood warning potential of the commercial wireless communication system for two different semi-arid region cases when floods occurred in the Judean desert and in the northern Negev in Israel. In addition, I will review our recent improvements in monitoring rainfall as well as other-than-rain phenomena like, atmospheric moisture. Special focus on fog monitoring potential will be discussed. This research was supported by THE ISRAEL SCIENCE FOUNDATION (grant No. 173/08) and the PROCEMA VI coordinated by H. Kunstmann. The research was also supported by the by the United States- Israel BINATIONAL SCIENCE FOUNDATION (BSF, Grant No. 2010342). References: N. David, P. Alpert, and H. Messer, "Technical Note: Novel method for water vapour monitoring using wireless communication networks measurements", Atmos. Chem. Phys., 9, 2413-2418, 2009. A. Rayitsfeld, R. Samuels, A. Zinevich, U. Hadar and P. Alpert,"Comparison of two methodologies for long term rainfall monitoring using a commercial microwave communication system", Atmospheric Research 104-105, 119-127, 2012. N. David, P. Alpert, and H. Messer, "Novel method for fog monitoring using cellular networks infrastructures", Atmos. Meas. Tech. Discuss, 5, 5725-5752, 2012.

Advances in modeling sorption and diffusion of moisture in porous reactive materials.

PubMed

Harley, Stephen J; Glascoe, Elizabeth A; Lewicki, James P; Maxwell, Robert S

2014-06-23

Water-vapor-uptake experiments were performed on a silica-filled poly(dimethylsiloxane) (PDMS) network and modeled by using two different approaches. The data was modeled by using established methods and the model parameters were used to predict moisture uptake in a sample. The predictions are reasonably good, but not outstanding; many of the shortcomings of the modeling are discussed. A high-fidelity modeling approach is derived and used to improve the modeling of moisture uptake and diffusion. Our modeling approach captures the physics and kinetics of diffusion and adsorption/desorption, simultaneously. It predicts uptake better than the established method; more importantly, it is also able to predict outgassing. The material used for these studies is a filled-PDMS network; physical interpretations concerning the sorption and diffusion of moisture in this network are discussed. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Cosmic Ray Neutron Sensing in Complex Systems

NASA Astrophysics Data System (ADS)

Piussi, L. M.; Tomelleri, E.; Tonon, G.; Bertoldi, G.; Mejia Aguilar, A.; Monsorno, R.; Zebisch, M.

2017-12-01

Soil moisture is a key variable in environmental monitoring and modelling: being located at the soil-atmosphere boundary, it is a driving force for water, energy and carbon fluxes. Nevertheless its importance, soil moisture observations lack of long time-series at high acquisition frequency in spatial meso-scale resolutions: traditional measurements deliver either long time series with high measurement frequency at spatial point scale or large scale and low frequency acquisitions. The Cosmic Ray Neutron Sensing (CRNS) technique fills this gap because it supplies information from a footprint of 240m of diameter and 15 to 83 cm of depth at a temporal resolution varying between 15 minutes and 24 hours. In addition, being a passive sensing technique, it is non-invasive. For these reasons, CRNS is gaining more and more attention from the scientific community. Nevertheless, the application of this technique in complex systems is still an open issue: where different Hydrogen pools are present and where their distributions vary appreciably with space and time, the traditional calibration method shows some limits. In order to obtain a better understanding of the data and to compare them with remote sensing products and spatially distributed traditional measurements (i.e. Wireless Sensors Network), the complexity of the surrounding environment has to be taken into account. In the current work we assessed the effects of spatial-temporal variability of soil moisture within the footprint, in a steep, heterogeneous mountain grassland area. Measurement were performed with a Cosmic Ray Neutron Probe (CRNP) and a mobile Wireless Sensors Network. We performed an in-deep sensitivity analysis of the effects of varying distributions of soil moisture on the calibration of the CRNP and our preliminary results show how the footprint shape varies depending on these dynamics. The results are then compared with remote sensing data (Sentinel 1 and 2). The current work is an assessment of different calibration procedures and their effect on the measurement outcome. We found that the response of the CRNP follows quite well the punctual measurement performed by a TDR installed on the site, but discrepancies could be explained by using the Wireless Sensors Network to perform a spatially weighted calibration and to introduce temporal dynamics.

Recent advances in environmental monitoring using commercial microwave links

NASA Astrophysics Data System (ADS)

Alpert, Pinhas; Guez, Oded; Messer, Hagit; David, Noam; Harel, Oz; Eshel, Adam; Cohen, Ori

2016-04-01

Recent advances in environmental monitoring using commercial microwave links Pinhas Alpert, H. Messer, N. David, O. Guez, O. Cohen, O. Harel, A. Eshel Tel Aviv University, Israel The propagation of electromagnetic radiation in the lower atmosphere, at centimeter wavelengths, is impaired by atmospheric conditions. Absorption and scattering of the radiation, at frequencies of tens of GHz, are directly related to the atmospheric phenomena, primarily precipitation, oxygen, mist, fog and water vapor. As was recently shown, wireless communication networks supply high resolution precipitation measurements at ground level while often being situated in flood prone areas, covering large parts of these hazardous regions. On the other hand, at present, there are no satisfactory real time flash flood warning facilities found to cope well with this phenomenon. I will exemplify the flash flood warning potential of the commercial wireless communication system for semi-arid region cases when floods occurred in the Judean desert in Israel with comparison to hydrological measurements in the Dead Sea area. In addition, I will review our recent improvements in monitoring rainfall as well as other-than-rain phenomena like, fog, dew, atmospheric moisture. References: N. David, P. Alpert, and H. Messer, "Technical Note: Novel method for water vapor monitoring using wireless communication networks measurements", Atmos. Chem. Phys., 9, 2413-2418, 2009. A. Rayitsfeld, R. Samuels, A. Zinevich, U. Hadar and P. Alpert,"Comparison of two methodologies for long term rainfall monitoring using a commercial microwave communication system", Atmospheric Research 104-105, 119-127, 2012. N. David, O. Sendik, H. Messer and P. Alpert, "Cellular network infrastructure-the future of fog monitoring?" BAMS (Oct. issue), 1687-1698, 2015. O. Harel, David, N., Alpert, P. and Messer, H., "The potential of microwave communication networks to detect dew using the GLRT- experimental study", IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2015.

On the soil moisture estimate at basin scale in Mediterranean basins with the ASAR sensor: the Mulargia basin case study

NASA Astrophysics Data System (ADS)

Fois, Laura; Montaldo, Nicola

2017-04-01

Soil moisture plays a key role in water and energy exchanges between soil, vegetation and atmosphere. For water resources planning and managementthesoil moistureneeds to be accurately and spatially monitored, specially where the risk of desertification is high, such as Mediterranean basins. In this sense active remote sensors are very attractive for soil moisture monitoring. But Mediterranean basinsaretypicallycharacterized by strong topography and high spatial variability of physiographic properties, and only high spatial resolution sensorsare potentially able to monitor the strong soil moisture spatial variability.In this regard the Envisat ASAR (Advanced Synthetic Aperture Radar) sensor offers the attractive opportunity ofsoil moisture mapping at fine spatial and temporal resolutions(up to 30 m, every 30 days). We test the ASAR sensor for soil moisture estimate in an interesting Sardinian case study, the Mulargia basin withan area of about 70 sq.km. The position of the Sardinia island in the center of the western Mediterranean Sea basin, its low urbanization and human activity make Sardinia a perfect reference laboratory for Mediterranean hydrologic studies. The Mulargia basin is a typical Mediterranean basinin water-limited conditions, and is an experimental basin from 2003. For soil moisture mapping23 satellite ASAR imagery at single and dual polarization were acquired for the 2003-2004period.Satellite observationsmay bevalidated through spatially distributed soil moisture ground-truth data, collected over the whole basin using the TDR technique and the gravimetric method, in days with available radar images. The results show that ASAR sensor observations can be successfully used for soil moisture mapping at different seasons, both wet and dry, but an accurate calibration with field data is necessary. We detect a strong relationship between the soil moisture spatial variability and the physiographic properties of the basin, such as soil water storage capacity, deep and texture of soils, type and density of vegetation, and topographic parameters. Finally we demonstrate that the high resolution ASAR imagery are an attractive tool for estimating surface soil moisture at basin scale, offering a unique opportunity for monitoring the soil moisture spatial variability in typical Mediterranean basins.

Prediction of some physical and drying properties of terebinth fruit (Pistacia atlantica L.) using Artificial Neural Networks.

PubMed

Kaveh, Mohammad; Chayjan, Reza Amiri

2014-01-01

Drying of terebinth fruit was conducted to provide microbiological stability, reduce product deterioration due to chemical reactions, facilitate storage and lower transportation costs. Because terebinth fruit is susceptible to heat, the selection of a suitable drying technology is a challenging task. Artificial neural networks (ANNs) are used as a nonlinear mapping structures for modelling and prediction of some physical and drying properties of terebinth fruit. Drying characteristics of terebinth fruit with an initial moisture content of 1.16 (d.b.) was studied in an infrared fluidized bed dryer. Different levels of air temperatures (40, 55 and 70°C), air velocities (0.93, 1.76 and 2.6 m/s) and infrared (IR) radiation powers (500, 1000 and 1500 W) were applied. In the present study, the application of Artificial Neural Network (ANN) for predicting the drying moisture diffusivity, energy consumption, shrinkage, drying rate and moisture ratio (output parameter for ANN modelling) was investigated. Air temperature, air velocity, IR radiation and drying time were considered as input parameters. The results revealed that to predict drying rate and moisture ratio a network with the TANSIG-LOGSIG-TANSIG transfer function and Levenberg-Marquardt (LM) training algorithm made the most accurate predictions for the terebinth fruit drying. The best results for ANN at predications were R2 = 0.9678 for drying rate, R2 = 0.9945 for moisture ratio, R2 = 0.9857 for moisture diffusivity and R2 = 0.9893 for energy consumption. Results indicated that artificial neural network can be used as an alternative approach for modelling and predicting of terebinth fruit drying parameters with high correlation. Also ANN can be used in optimization of the process.

Building America Case Study: Monitoring of Double Stud Wall Moisture Conditions in the Northeast, Devens, Massachusetts (Fact Sheet)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

2015-03-01

Double-stud walls insulated with cellulose or low-density spray foam can have R-values of 40 or higher. However, double stud walls have a higher risk of interior-sourced condensation moisture damage, when compared with high-R approaches using exterior insulating sheathing. Moisture conditions in double stud walls were monitored in Zone 5A (Massachusetts); three double stud assemblies were compared.

Long-Term Evaluation of the AMSR-E Soil Moisture Product Over the Walnut Gulch Watershed, AZ

NASA Astrophysics Data System (ADS)

Bolten, J. D.; Jackson, T. J.; Lakshmi, V.; Cosh, M. H.; Drusch, M.

2005-12-01

The Advanced Microwave Scanning Radiometer -Earth Observing System (AMSR-E) was launched aboard NASA's Aqua satellite on May 4th, 2002. Quantitative estimates of soil moisture using the AMSR-E provided data have required routine radiometric data calibration and validation using comparisons of satellite observations, extended targets and field campaigns. The currently applied NASA EOS Aqua ASMR-E soil moisture algorithm is based on a change detection approach using polarization ratios (PR) of the calibrated AMSR-E channel brightness temperatures. To date, the accuracy of the soil moisture algorithm has been investigated on short time scales during field campaigns such as the Soil Moisture Experiments in 2004 (SMEX04). Results have indicated self-consistency and calibration stability of the observed brightness temperatures; however the performance of the moisture retrieval algorithm has been poor. The primary objective of this study is to evaluate the quality of the current version of the AMSR-E soil moisture product for a three year period over the Walnut Gulch Experimental Watershed (150 km2) near Tombstone, AZ; the northern study area of SMEX04. This watershed is equipped with hourly and daily recording of precipitation, soil moisture and temperature via a network of raingages and a USDA-NRCS Soil Climate Analysis Network (SCAN) site. Surface wetting and drying are easily distinguished in this area due to the moderately-vegetated terrain and seasonally intense precipitation events. Validation of AMSR-E derived soil moisture is performed from June 2002 to June 2005 using watershed averages of precipitation, and soil moisture and temperature data from the SCAN site supported by a surface soil moisture network. Long-term assessment of soil moisture algorithm performance is investigated by comparing temporal variations of moisture estimates with seasonal changes and precipitation events. Further comparisons are made with a standard soil dataset from the European Centre for Medium-Range Weather Forecasts. The results of this research will contribute to a better characterization of the low biases and discrepancies currently observed in the AMSR-E soil moisture product.

Validation of in situ networks via field sampling: case study in the South Fork Experimental Watershed

USDA-ARS?s Scientific Manuscript database

The calibration and validation of soil moisture remote sensing products is complicated by the logistics of installing a soil moisture network for a long term period in an active landscape. Therefore, these stations are located along field boundaries or in non-representative sites with regards to so...

Using a soil moisture and precipitation network for satellite validation

USDA-ARS?s Scientific Manuscript database

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

Assimilation of spatially sparse in situ soil moisture networks into a continuous model domain

USDA-ARS?s Scientific Manuscript database

Growth in the availability of near-real-time soil moisture observations from ground-based networks has spurred interest in the assimilation of these observations into land surface models via a two-dimensional data assimilation system. However, the design of such systems is currently hampered by our ...

Inter-comparison of soil moisture sensors from the soil moisture active passive marena Oklahoma in situ sensor testbed (SMAP-MOISST)

USDA-ARS?s Scientific Manuscript database

The diversity of in situ soil moisture network protocols and instrumentation led to the development of a testbed for comparing in situ soil moisture sensors. Located in Marena, Oklahoma on the Oklahoma State University Range Research Station, the testbed consists of four base stations. Each station ...

Estimating root-zone soil moisture in the West Africa Sahel using remotely sensed rainfall and vegetation

NASA Astrophysics Data System (ADS)

McNally, Amy L.

Agricultural drought is characterized by shortages in precipitation, large differences between actual and potential evapotranspiration, and soil water deficits that impact crop growth and pasture productivity. Rainfall and other agrometeorological gauge networks in Sub-Saharan Africa are inadequate for drought early warning systems and hence, satellite-based estimates of rainfall and vegetation greenness provide the main sources of information. While a number of studies have described the empirical relationship between rainfall and vegetation greenness, these studies lack a process based approach that includes soil moisture storage. In Chapters I and II, I modeled soil moisture using satellite rainfall inputs and developed a new method for estimating soil moisture with NDVI calibrated to in situ and microwave soil moisture observations. By transforming both NDVI and rainfall into estimates of soil moisture I was able to easily compare these two datasets in a physically meaningful way. In Chapter II, I also show how the new NDVI derived soil moisture can be assimilated into a water balance model that calculates an index of crop water stress. Compared to the analogous rainfall derived estimates of soil moisture and crop stress the NDVI derived estimates were better correlated with millet yields. In Chapter III, I developed a metric for defining growing season drought events that negatively impact millet yields. This metric is based on the data and models used in the Chapters I and II. I then use this metric to evaluate the ability of a sophisticated land surface model to detect drought events. The analysis showed that this particular land surface model's soil moisture estimates do have the potential to benefit the food security and drought early warning communities. With a focus on soil moisture, this dissertation introduced new methods that utilized a variety of data and models for agricultural drought monitoring applications. These new methods facilitate a more quantitative, transparent `convergence of evidence' approach to identifying agricultural drought events that lead to food insecurity. Ideally, these new methods will contribute to better famine early warning and the timely delivery of food aid to reduce the human suffering caused by drought.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

Multi-sphere interactions over the Tibetan Plateau directly impact its surrounding climate and environment at a variety of spatiotemporal scales. Remote sensing and modeling are expected to provide hydro-meteorological data needed for these process studies, but in situ observations are required to support their calibration and validation. For this purpose, we have established two networks on the Tibetan Plateau to measure densely two state variables (soil moisture and temperature) and four soil depths (0 5, 10, 20, and 40 cm). The experimental area is characterized by low biomass, high soil moisture dynamic range, and typical freeze-thaw cycle. As auxiliary parameters of these networks, soil texture and soil organic carbon content are measured at each station to support further studies. In order to guarantee continuous and high-quality data, tremendous efforts have been made to protect the data logger from soil water intrusion, to calibrate soil moisture sensors, and to upscale the point measurements. One soil moisture network is located in a semi-humid area in central Tibetan Plateau (Naqu), which consists of 56 stations with their elevation varying over 4470 4950 m and covers three spatial scales (1.0, 0.3, 0.1 degree). The other is located in a semi-arid area in southern Tibetan Plateau (Pali), which consists of 25 stations and covers an area of 0.25 degree. The spatiotemporal characteristics of the former network were analyzed, and a new spatial upscaling method was developed to obtain the regional mean soil moisture truth from the point measurements. Our networks meet the requirement for evaluating a variety of soil moisture products, developing new algorithms, and analyzing soil moisture scaling. Three applications with the network data are presented in this paper. 1. Evaluation of Current remote sensing and LSM products. The in situ data have been used to evaluate AMSR-E, AMSR2, SMOS and SMAP products and four modeled outputs by the Global Land Data Assimilation System (GLDAS). 2. Development of New Products. We developed a dual-pass land data assimilation system. The essential idea of the system is to calibrate a land data assimilation system before a normal data assimilation. The calibration is based on satellite data rather than in situ data. Through this way, we may alleviate the impact of uncertainties in determining the error covariance of both observation operator and model operation, as it is always tough to determine the covariance. The performance of the data assimilation system is presented through comparison against the Tibetan Plateau soil moisture measuring networks. And the results are encouraging. 3. Estimation of Soil Parameter Values in a Land Surface Model. We explored the possibility to estimate soil parameter values by assimilating AMSR-E brightness temperature (TB) data. In the assimilation system, the TB is simulated by the coupled system of a land surface model (LSM) and a radiative transfer model (RTM), and the simulation errors highly depend on parameters in both the LSM and the RTM. Thus, sensitive soil parameters may be inversely estimated through minimizing the TB errors. The effectiveness of the estimated parameter values is evaluated against intensive measurements of soil parameters and soil moisture in three grasslands of the Tibetan Plateau and the Mongolian Plateau. The results indicate that this satellite data-based approach can improve the data quality of soil porosity, a key parameter for soil moisture modeling, and LSM simulations with the estimated parameter values reasonably reproduce the measured soil moisture. This demonstrates it is feasible to calibrate LSMs for soil moisture simulations at grid scale by assimilating microwave satellite data, although more efforts are expected to improve the robustness of the model calibration.

Evaluating soil moisture retrievals from ESA's SMOS and NASA's SMAP brightness temperature datasets

USDA-ARS?s Scientific Manuscript database

Two satellites are currently monitoring surface soil moisture (SM) from L-band observations: SMOS (Soil Moisture and Ocean Salinity), a European Space Agency (ESA) satellite that was launched on November 2, 2009 and SMAP (Soil Moisture Active Passive), a National Aeronautics and Space Administration...

A Combined Soil Moisture Product of the Tibetan Plateau using Different Sensors Simultaneously

NASA Astrophysics Data System (ADS)

Zeng, Y.; Dente, L.; Su, B.; Wang, L.

2012-12-01

It is always challenging to find a single satellite-derived soil moisture product that has complete coverage of the Tibetan Plateau for a long time period and is suitable for climate change studies at sub-continental scale. Meanwhile, having a number of independent satellite-derived soil moisture data sets does not mean that it is straightforward to create long-term consistent time series, due to the differences among the data sets related to the different retrieval approaches. Therefore, this study is focused on the development and validation of a simple Bayesian based method to merge/blend different satellite-derived soil moisture data. The merging method was firstly tested over the Maqu region (north-eastern fringe of the Tibetan Plateau), where in situ soil moisture data were collected, for the period from May 2008 to December 2010. The in situ data provided by the 20 monitoring stations in the Maqu region were compared to the AMSR-E soil moisture products by VUA-NASA and the ASCAT soil moisture products by TU Wien, in order to determine bias and standard deviation. It was found that the bias between the satellite and the in situ data varies with seasons. The satellite-derived products were first corrected for the bias and then merged. This is generally caused by notable differences in the represented depth, spatial extent and so on. The systematic bias is affected by the spatial variability and the temporal stability (Dente et al. 2012). The dependence of the bias on season was investigated and identified as the monsoon season only (May-September), in winter only (December - February), and in the period between the monsoon season and winter (March-April, October-November, called the transition season) (Dente et al. 2012, Su et al. 2011). After the date merging procedure, the standard deviations between the satellite and the in situ data reduced from 0.0839 to 0.0622 for ASCAT data, and from 0.0682 to 0.0593 for AMSR-E data. The developed merging method is therefore suitable to provide a more accurate soil moisture product than the AMSR-E and ASCAT products. As the merging method was shown to be promising over the Maqu region, it will be extended to the entire Tibetan Plateau. Then, the combined soil moisture product will be validated over the monitored sites located in Ngari and Naqu regions. References: Dente, L.; Vekerdy, Z.; Wen, J.; Su, Z., (2012) Maqu network for validation of satellite-derived soil moisture products. International Journal of Applied Earth Observation and Geoinformation, 17, 55-65. Su, Z., Wen, J., Dente, L., van der Velde, R. and ... [et al.] (2011) The Tibetan plateau observatory of plateau scale soil moisture and soil temperature, Tibet - Obs, for quantifying uncertainties in coarse resolution satellite and model products. In: Hydrology and earth system sciences (HESS): open access, 15 (2011)7 pp. 2303-2016.

Development of an Experimental African Drought Monitoring and Seasonal Forecasting System: A First Step towards a Global Drought Information System

NASA Astrophysics Data System (ADS)

Wood, E. F.; Chaney, N.; Sheffield, J.; Yuan, X.

2012-12-01

Extreme hydrologic events in the form of droughts are a significant source of social and economic damage. Internationally, organizations such as UNESCO, the Group on Earth Observations (GEO), and the World Climate Research Programme (WCRP) have recognized the need for drought monitoring, especially for the developing world where drought has had devastating impacts on local populations through food insecurity and famine. Having the capacity to monitor droughts in real-time, and to provide drought forecasts with sufficient warning will help developing countries and international programs move from the management of drought crises to the management of drought risk. While observation-based assessments, such as those produced by the US Drought Monitor, are effective for monitoring in countries with extensive observation networks (of precipitation in particular), their utility is lessened in areas (e.g., Africa) where observing networks are sparse. For countries with sparse networks and weak reporting systems, remote sensing observations can provide the real-time data for the monitoring of drought. More importantly, these datasets are now available for at least a decade, which allows for the construction of a climatology against which current conditions can be compared. In this presentation we discuss the development of our multi-lingual experimental African Drought Monitor (ADM) (see http://hydrology.princeton.edu/~nchaney/ADM_ML). At the request of UNESCO, the ADM system has been installed at AGRHYMET, a regional climate and agricultural center in Niamey, Niger and at the ICPAC climate center in Nairobi, Kenya. The ADM system leverages off our U.S. drought monitoring and forecasting system (http://hydrology.princeton.edu/forecasting) that uses the NLDAS data to force the VIC land surface model (LSM) at 1/8th degree spatial resolution for the estimation of our soil moisture drought index (Sheffield et al., 2004). For the seasonal forecast of drought, CFSv2 climate forecasts are bias corrected, downscaled and used as inputs to the VIC LSM as well as forecasts based on ESP and CPC official seasonal outlook. For Africa, data from a combination of remote sensing (TMPA-based precipitation, land cover characteristics) and GFS analysis fields (temperature and wind) are used to monitor drought using our soil moisture drought index as well as 1, 3 and and 6-month SPI. River discharge is also estimated at over 900 locations. Seasonal forecasts have been developed using CFSv2 climate forecasts following the approaches used over CONUS. We will discuss the performance of the system to evaluate the depiction of drought over various scales, from regional to the African continent, and over a number of years to capture multiple drought events. Furthermore, the hindcasts from the seasonal drought forecast system are analyzed to assess the ability of seasonal climate models to detect drought on-set and its recovery. Finally, we will discuss whether our ADM provides a pathway to a Global Drought Information System, a goal of the WCRP Drought Task Force.

Why is SMOS Drier than the South Fork In-situ Soil Moisture Network?

NASA Astrophysics Data System (ADS)

Walker, V. A.; Hornbuckle, B. K.; Cosh, M. H.

2014-12-01

Global maps of near-surface soil moisture are currently being produced by the European Space Agency's Soil Moisture and Ocean Salinity (SMOS) satellite mission at 40 km. Within the next few months NASA's Soil Moisture Active Passive (SMAP) satellite mission will begin producing observations of near-surface soil moisture at 10 km. Near-surface soil moisture is the water content of the first 3 to 5 cm of the soil. Observations of near-surface soil moisture are expected to improve weather and climate forecasts. These satellite observations must be validated. We define validation as determining the space/time statistical characteristics of the uncertainty. A standard that has been used for satellite validation is in-situ measurements of near-surface soil moisture made with a network of sensors spanning the extent of a satellite footprint. Such a network of sensors has been established in the South Fork of the Iowa River in Central Iowa by the USDA ARS. Our analysis of data in 2013 indicates that SMOS has a dry bias: SMOS near-surface soil moisture is between 0.05 to 0.10 m^3m^{-3} lower than what is observed by the South Fork network. A dry bias in SMOS observations has also been observed in other regions of North America. There are many possible explanations for this difference: underestimation of vegetation, or soil surface roughness; undetected radio frequency interference (RFI); a retrieval model that is not appropriate for agricultural areas; or the use of an incorrect surface temperature in the retrieval process. We will begin our investigation by testing this last possibility: that SMOS is using a surface temperature that is too low which results in a drier soil moisture that compensates for this error. We will present a comparison of surface temperatures from the European Center for Medium-range Weather Forecasting (ECMWF) used to retrieve near-surface soil moisture from SMOS measurements of brightness temperature, and surface temperatures in the South Fork obtained from both tower and in-situ sensors. We will also use a long-term data set of tower and in-situ sensors collected in agricultural fields to develop a relationship between air temperature and the surface temperature relevant to the terrestrial microwave emission that is detected by SMOS.

Creating soil moisture maps based on radar satellite imagery

NASA Astrophysics Data System (ADS)

Hnatushenko, Volodymyr; Garkusha, Igor; Vasyliev, Volodymyr

2017-10-01

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

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

NASA Technical Reports Server (NTRS)

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

2011-01-01

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

American River Hydrologic Observatory

NASA Astrophysics Data System (ADS)

Glaser, S. D.; Bales, R. C.; Conklin, M. H.

2016-12-01

We have set up fourteen large wireless sensor networks to measure hydrologic parameters over physiographical representative regions of the snow-dominated portion of the river basin. This is perhaps the largest wireless sensor network in the world. Each network covers about a 1 km2 area and consists of about 45 elements. We measure snow depth, temperature humidity soil moisture and temperature, and solar radiation in real time at ten locations per site, as opposed to the traditional once-a-month snow course. As part of the multi-PI SSCZO, we have installed a 62-node wireless sensor network to measure snow depth, temperature humidity soil moisture and temperature, and solar radiation in real time. This network has been operating for approximately six years. We are now installing four large wireless sensor networks to measure snow depth, temperature humidity soil moisture and temperature, and solar radiation in East Branch of the North Fork of the Feather River, CA. The presentation will discuss the planning and operation of the networks as well as some unique results. It will also present information about the networking hardware designed for these installations, which has resulted in a start-up, Metronome Systems.

Real-time process monitoring in a semi-continuous fluid-bed dryer - microwave resonance technology versus near-infrared spectroscopy.

PubMed

Peters, Johanna; Teske, Andreas; Taute, Wolfgang; Döscher, Claas; Höft, Michael; Knöchel, Reinhard; Breitkreutz, Jörg

2018-02-15

The trend towards continuous manufacturing in the pharmaceutical industry is associated with an increasing demand for advanced control strategies. It is a mandatory requirement to obtain reliable real-time information on critical quality attributes (CQA) during every process step as the decision on diversion of material needs to be performed fast and automatically. Where possible, production equipment should provide redundant systems for in-process control (IPC) measurements to ensure continuous process monitoring even if one of the systems is not available. In this paper, two methods for real-time monitoring of granule moisture in a semi-continuous fluid-bed drying unit are compared. While near-infrared (NIR) spectroscopy has already proven to be a suitable process analytical technology (PAT) tool for moisture measurements in fluid-bed applications, microwave resonance technology (MRT) showed difficulties to monitor moistures above 8% until recently. The results indicate, that the newly developed MRT sensor operating at four resonances is capable to compete with NIR spectroscopy. While NIR spectra were preprocessed by mean centering and first derivative before application of partial least squares (PLS) regression to build predictive models (RMSEP = 0.20%), microwave moisture values of two resonances sufficed to build a statistically close multiple linear regression (MLR) model (RMSEP = 0.07%) for moisture prediction. Thereby, it could be verified that moisture monitoring by MRT sensor systems could be a valuable alternative to NIR spectroscopy or could be used as a redundant system providing great ease of application. Copyright © 2017 Elsevier B.V. All rights reserved.

Spatio-Temporal Analysis of Surface Soil Moisture in Evaluating Ground Truth Monitoring Sites for Remotely Sensed Observations

USDA-ARS?s Scientific Manuscript database

Soil moisture is an intrinsic state variable that varies considerably in space and time. Although soil moisture is highly variable, repeated measurements of soil moisture at the field or small watershed scale can often reveal certain locations as being temporally stable and representative of the are...

Measuring moisture content in living chaparral: a field user's manual

Treesearch

Clive M. Countryman; William A. Dean

1979-01-01

This manual standardizes procedures for determining the moisture content of living chaparral for use in a proposed statewide system of monitoring living fuel moisture. The manual includes a comprehensive examination of fuel moisture variations in California chaparral, and describes techniques for sampling these variations. Equipment needed to sample and determine...

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

USDA-ARS?s Scientific Manuscript database

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

Extending the soil moisture record of the climate reference network with machine learning

USDA-ARS?s Scientific Manuscript database

Soil moisture estimation is crucial for agricultural decision-support and a key component of hydrological and climatic research. Unfortunately, quality-controlled soil moisture time series data are uncommon before the most recent decade. However, time series data for precipitation are accessible at ...

Analysis of meteorological variables in the Australasian region using ground- and space-based GPS techniques

NASA Astrophysics Data System (ADS)

Kuleshov, Yuriy; Choy, Suelynn; Fu, Erjiang Frank; Chane-Ming, Fabrice; Liou, Yuei-An; Pavelyev, Alexander G.

2016-07-01

Results of analysis of meteorological variables (temperature and moisture) in the Australasian region using the global positioning system (GPS) radio occultation (RO) and GPS ground-based observations verified with in situ radiosonde (RS) data are presented. The potential of using ground-based GPS observations for retrieving column integrated precipitable water vapour (PWV) over the Australian continent has been demonstrated using the Australian ground-based GPS reference stations network. Using data from the 15 ground-based GPS stations, the state of the atmosphere over Victoria during a significant weather event, the March 2010 Melbourne storm, has been investigated, and it has been shown that the GPS observations has potential for monitoring the movement of a weather front that has sharp moisture contrast. Temperature and moisture variability in the atmosphere over various climatic regions (the Indian and the Pacific Oceans, the Antarctic and Australia) has been examined using satellite-based GPS RO and in situ RS observations. Investigating recent atmospheric temperature trends over Antarctica, the time series of the collocated GPS RO and RS data were examined, and strong cooling in the lower stratosphere and warming through the troposphere over Antarctica has been identified, in agreement with outputs of climate models. With further expansion of the Global Navigation Satellite Systems (GNSS) system, it is expected that GNSS satellite- and ground-based measurements would be able to provide an order of magnitude larger amount of data which in turn could significantly advance weather forecasting services, climate monitoring and analysis in the Australasian region.

Implementing wireless sensor networks for architectural heritage conservation

NASA Astrophysics Data System (ADS)

Martínez-Garrido, M. I.; Aparicio, S.; Fort, R.; Izquierdo, M. A. G.; Anaya, J. J.

2012-04-01

Preventive conservation in architectural heritage is one of the most important aims for the development and implementation of new techniques to assess decay, lending to reduce damage before it has occurred and reducing costs in the long term. For that purpose, it is necessary to know all aspects influencing in decay evolution depending on the material under study and its internal and external conditions. Wireless sensor networks are an emerging technology and a minimally invasive technique. The use of these networks facilitates data acquisition and monitoring of a large number of variables that could provoke material damages, such as presence of harmful compounds like salts, dampness, etc. The current project presents different wireless sensors networks (WSN) and sensors used to fulfill the requirements for a complete analysis of main decay agents in a Renaissance church of the 16th century in Madrid (Spain). Current typologies and wireless technologies are studied establishing the most suitable system and the convenience of each one. Firstly, it is very important to consider that microclimate is in close correlation with material deterioration. Therefore a temperature(T) and relative humidity (RH)/moisture network has been developed, using ZigBee wireless communications protocols, and monitoring different points along the church surface. These points are recording RH/T differences depending on the height and the sensor location (inside the material or on the surface). On the other hand, T/RH button sensors have been used, minimizing aesthetical interferences, and concluding which is the most advisable way for monitoring these specific parameters. Due to the fact that microclimate is a complex phenomenon, it is necessary to examine spatial distribution and time evolution at the same time. This work shows both studies since the development expects a long term monitoring. A different wireless network has been deployed to study the effects of pollution caused by other active systems such as a forced-air heating system, the parishioners presence or feasts and other ventilation conditions. Finally weather conditions are registered through a weather station. Outside and inside conditions are compared to incorporate data to the network for a later decay modeling.

Improving streamflow prediction using remotely-sensed soil moisture and snow depth

USDA-ARS?s Scientific Manuscript database

The monitoring of both cold and warm season hydrologic processes in headwater watersheds is critical for accurate water resource monitoring in many alpine regions. This work presents a new method that explores the simultaneous use of remotely sensed surface soil moisture (SM) and snow depth (SD) ret...

Confronting weather and climate models with observational data from soil moisture networks over the United States

PubMed Central

Dirmeyer, Paul A.; Wu, Jiexia; Norton, Holly E.; Dorigo, Wouter A.; Quiring, Steven M.; Ford, Trenton W.; Santanello, Joseph A.; Bosilovich, Michael G.; Ek, Michael B.; Koster, Randal D.; Balsamo, Gianpaolo; Lawrence, David M.

2018-01-01

Four land surface models in uncoupled and coupled configurations are compared to observations of daily soil moisture from 19 networks in the conterminous United States to determine the viability of such comparisons and explore the characteristics of model and observational data. First, observations are analyzed for error characteristics and representation of spatial and temporal variability. Some networks have multiple stations within an area comparable to model grid boxes; for those we find that aggregation of stations before calculation of statistics has little effect on estimates of variance, but soil moisture memory is sensitive to aggregation. Statistics for some networks stand out as unlike those of their neighbors, likely due to differences in instrumentation, calibration and maintenance. Buried sensors appear to have less random error than near-field remote sensing techniques, and heat dissipation sensors show less temporal variability than other types. Model soil moistures are evaluated using three metrics: standard deviation in time, temporal correlation (memory) and spatial correlation (length scale). Models do relatively well in capturing large-scale variability of metrics across climate regimes, but poorly reproduce observed patterns at scales of hundreds of kilometers and smaller. Uncoupled land models do no better than coupled model configurations, nor do reanalyses outperform free-running models. Spatial decorrelation scales are found to be difficult to diagnose. Using data for model validation, calibration or data assimilation from multiple soil moisture networks with different types of sensors and measurement techniques requires great caution. Data from models and observations should be put on the same spatial and temporal scales before comparison. PMID:29645013

Confronting Weather and Climate Models with Observational Data from Soil Moisture Networks over the United States

NASA Technical Reports Server (NTRS)

Dirmeyer, Paul A.; Wu, Jiexia; Norton, Holly E.; Dorigo, Wouter A.; Quiring, Steven M.; Ford, Trenton W.; Santanello, Joseph A., Jr.; Bosilovich, Michael G.; Ek, Michael B.; Koster, Randal Dean;

Confronting weather and climate models with observational data from soil moisture networks over the United States.

PubMed

Dirmeyer, Paul A; Wu, Jiexia; Norton, Holly E; Dorigo, Wouter A; Quiring, Steven M; Ford, Trenton W; Santanello, Joseph A; Bosilovich, Michael G; Ek, Michael B; Koster, Randal D; Balsamo, Gianpaolo; Lawrence, David M

2016-04-01

Four land surface models in uncoupled and coupled configurations are compared to observations of daily soil moisture from 19 networks in the conterminous United States to determine the viability of such comparisons and explore the characteristics of model and observational data. First, observations are analyzed for error characteristics and representation of spatial and temporal variability. Some networks have multiple stations within an area comparable to model grid boxes; for those we find that aggregation of stations before calculation of statistics has little effect on estimates of variance, but soil moisture memory is sensitive to aggregation. Statistics for some networks stand out as unlike those of their neighbors, likely due to differences in instrumentation, calibration and maintenance. Buried sensors appear to have less random error than near-field remote sensing techniques, and heat dissipation sensors show less temporal variability than other types. Model soil moistures are evaluated using three metrics: standard deviation in time, temporal correlation (memory) and spatial correlation (length scale). Models do relatively well in capturing large-scale variability of metrics across climate regimes, but poorly reproduce observed patterns at scales of hundreds of kilometers and smaller. Uncoupled land models do no better than coupled model configurations, nor do reanalyses outperform free-running models. Spatial decorrelation scales are found to be difficult to diagnose. Using data for model validation, calibration or data assimilation from multiple soil moisture networks with different types of sensors and measurement techniques requires great caution. Data from models and observations should be put on the same spatial and temporal scales before comparison.

Generating large-scale estimates from sparse, in-situ networks: multi-scale soil moisture modeling at ARS watersheds for NASA’s soil moisture active passive (SMAP) calibration/validation mission

USDA-ARS?s Scientific Manuscript database

NASA’s SMAP satellite, launched in November of 2014, produces estimates of average volumetric soil moisture at 3, 9, and 36-kilometer scales. The calibration and validation process of these estimates requires the generation of an identically-scaled soil moisture product from existing in-situ networ...

Comparison Of In Situ Soil Moisture Measurements: An Examination of the Neutron and Dielectric Measurements within the Illinois Climate Network

USDA-ARS?s Scientific Manuscript database

The continuity of soil moisture time series data is crucial for climatic research. Yet, a common problem for continuous data series is the changing of sensors, not only as replacements are necessary, but as technologies evolve. The Illinois Climate Network has one of the longest data records of soi...

Initial validation of the Soil Moisture Active Passive mission using USDA-ARS watersheds

USDA-ARS?s Scientific Manuscript database

The Soil Moisture Active Passive (SMAP) Mission was launched in January 2015 to measure global surface soil moisture. The calibration and validation program of SMAP relies upon an international cooperative of in situ networks to provide ground truth references across a variety of landscapes. The U...

Enhancement of the Automated Quality Control Procedures for the International Soil Moisture Network

NASA Astrophysics Data System (ADS)

Heer, Elsa; Xaver, Angelika; Dorigo, Wouter; Messner, Romina

2017-04-01

In-situ soil moisture observations are still trusted to be the most reliable data to validate remotely sensed soil moisture products. Thus, the quality of in-situ soil moisture observations is of high importance. The International Soil Moisture Network (ISMN; http://ismn.geo.tuwien.ac.at/) provides in-situ soil moisture data from all around the world. The data is collected from individual networks and data providers, measured by different sensors in various depths. The data sets which are delivered in different units, time zones and data formats are then transformed into homogeneous data sets. An erroneous behavior of soil moisture data is very difficult to detect, due to annual and daily changes and most significantly the high influence of precipitation and snow melting processes. Only few of the network providers have a quality assessment for their data sets. Therefore, advanced quality control procedures have been developed for the ISMN (Dorigo et al. 2013). Three categories of quality checks were introduced: exceeding boundary values, geophysical consistency checks and a spectrum based approach. The spectrum based quality control algorithms aim to detect erroneous measurements which occur within plausible geophysical ranges, e.g. a sudden drop in soil moisture caused by a sensor malfunction. By defining several conditions which have to be met by the original soil moisture time series and their first and second derivative, such error types can be detected. Since the development of these sophisticated methods many more data providers shared their data with the ISMN and new types of erroneous measurements were identified. Thus, an enhancement of the automated quality control procedures became necessary. In the present work, we introduce enhancements of the existing quality control algorithms. Additionally, six completely new quality checks have been developed, e.g. detection of suspicious values before or after NAN-values, constant values and values that lie in a spectrum where a high majority of values before and after is flagged and therefore a sensor malfunction is certain. For the evaluation of the enhanced automated quality control system many test data sets were chosen, and manually validated to be compared to the existing quality control procedures and the new algorithms. Improvements will be shown that assure an appropriate assessment of the ISMN data sets, which are used for validations of soil moisture data retrieved by satellite data and are the foundation many other scientific publications.

Sentinel-1 backscatter sensitivity to vegetation dynamics at the field scale.

NASA Astrophysics Data System (ADS)

Vreugdenhil, Mariette; Eder, Alexander; Bauer-Marschallinger, Bernhard; Cao, Senmao; Naeimi, Vahid; Oismueller, Markus; Strauss, Peter; Wagner, Wolfgang

2017-04-01

Vegetation monitoring is pivotal to improve our understanding of the role vegetation dynamics play in the global carbon-, energy- and hydrological cycle. And with the increasing stress on food supply due to the growing world populating and changing climate, vegetation monitoring is of great importance in agricultural areas. By closely tracking crop conditions, droughts and subsequent crop losses could be mitigated. Sensors operating in the microwave domain are sensitive to several surface characteristics, including soil moisture and vegetation. Hence, spaceborne microwave remote sensing provides the means to monitor vegetation and soil conditions on different scales, ranging from field scale to global scale. However, it also presents a challenge since multiple combinations of soil and vegetation characteristics can lead to a similar measurement. Copernicus Sentinel-1 (S-1) is a series of two satellites, developed by the European Space Agency (ESA) , which carry C-band Synthetic Aperture Radars. The C-SAR sensors provide VV, HH, VH and HV backscatter at a 5 m by 20 m spatial resolution. The temporal revisit time of the two satellites is 3-6 days. With their unique capacity for temporally dense and spatially detailed data, the S-1 satellite series provides for the first time the chance to investigate vegetation dynamics at high temporal and spatial resolution. The aim of this study is to assess the sensitivity of Sentinel-1 backscatter to vegetation dynamics. The study is performed in the Hydrological Open Air Laboratory (HOAL), which is a 66 hectare large catchment located in Petzenkirchen, Austria. In the HOAL several vegetation parameters were measured during the course of the growing season (2016) at the overpass time of S-1a. Vegetation height was obtained ten times for the whole catchment, using georeferenced photos made by a motorized paraglider and a Land Surface Model. In addition, vegetation water content, Leaf Area Index and soil moisture were measured in four different cropfields. An in situ soil moisture network provides continuous soil moisture measurements at 31 locations within the catchment. Different polarizations and ratios thereof were calculated and compared, both spatially and temporally, to the in situ measurements of vegetation height, LAI, vegetation water content and soil moisture. Preliminary results show a clear spatial pattern in cross-polarized backscatter, which is related to different crop types. Time series analysis suggests that a ratio between cross- and co-polarized backscatter is affected by both vegetation water content and vegetation structure. This presentation will provide a comprehensive assessment of Sentinel-1's capability for monitoring of vegetation over croplands, using in situ reference data obtained over a full growing season.

Real-Time Alpine Measurement System Using Wireless Sensor Networks

PubMed Central

2017-01-01

Monitoring the snow pack is crucial for many stakeholders, whether for hydro-power optimization, water management or flood control. Traditional forecasting relies on regression methods, which often results in snow melt runoff predictions of low accuracy in non-average years. Existing ground-based real-time measurement systems do not cover enough physiographic variability and are mostly installed at low elevations. We present the hardware and software design of a state-of-the-art distributed Wireless Sensor Network (WSN)-based autonomous measurement system with real-time remote data transmission that gathers data of snow depth, air temperature, air relative humidity, soil moisture, soil temperature, and solar radiation in physiographically representative locations. Elevation, aspect, slope and vegetation are used to select network locations, and distribute sensors throughout a given network location, since they govern snow pack variability at various scales. Three WSNs were installed in the Sierra Nevada of Northern California throughout the North Fork of the Feather River, upstream of the Oroville dam and multiple powerhouses along the river. The WSNs gathered hydrologic variables and network health statistics throughout the 2017 water year, one of northern Sierra’s wettest years on record. These networks leverage an ultra-low-power wireless technology to interconnect their components and offer recovery features, resilience to data loss due to weather and wildlife disturbances and real-time topological visualizations of the network health. Data show considerable spatial variability of snow depth, even within a 1 km2 network location. Combined with existing systems, these WSNs can better detect precipitation timing and phase in, monitor sub-daily dynamics of infiltration and surface runoff during precipitation or snow melt, and inform hydro power managers about actual ablation and end-of-season date across the landscape. PMID:29120376

Real-Time Alpine Measurement System Using Wireless Sensor Networks.

PubMed

Malek, Sami A; Avanzi, Francesco; Brun-Laguna, Keoma; Maurer, Tessa; Oroza, Carlos A; Hartsough, Peter C; Watteyne, Thomas; Glaser, Steven D

2017-11-09

Monitoring the snow pack is crucial for many stakeholders, whether for hydro-power optimization, water management or flood control. Traditional forecasting relies on regression methods, which often results in snow melt runoff predictions of low accuracy in non-average years. Existing ground-based real-time measurement systems do not cover enough physiographic variability and are mostly installed at low elevations. We present the hardware and software design of a state-of-the-art distributed Wireless Sensor Network (WSN)-based autonomous measurement system with real-time remote data transmission that gathers data of snow depth, air temperature, air relative humidity, soil moisture, soil temperature, and solar radiation in physiographically representative locations. Elevation, aspect, slope and vegetation are used to select network locations, and distribute sensors throughout a given network location, since they govern snow pack variability at various scales. Three WSNs were installed in the Sierra Nevada of Northern California throughout the North Fork of the Feather River, upstream of the Oroville dam and multiple powerhouses along the river. The WSNs gathered hydrologic variables and network health statistics throughout the 2017 water year, one of northern Sierra's wettest years on record. These networks leverage an ultra-low-power wireless technology to interconnect their components and offer recovery features, resilience to data loss due to weather and wildlife disturbances and real-time topological visualizations of the network health. Data show considerable spatial variability of snow depth, even within a 1 km 2 network location. Combined with existing systems, these WSNs can better detect precipitation timing and phase in, monitor sub-daily dynamics of infiltration and surface runoff during precipitation or snow melt, and inform hydro power managers about actual ablation and end-of-season date across the landscape.

Calibration of Cosmic Ray Neutron Probes in complex systems: open research issues

NASA Astrophysics Data System (ADS)

Piussi, Laura; Tomelleri, Enrico; Bertoldi, Giacomo; Zebisch, Marc; Niedrist, Georg; Tonon, Giustino

2017-04-01

Soil moisture is a key variable for environmental monitoring, hydrological and climate change research as it controls mass and energy fluxes in the soil-plant-atmosphere continuum. Actual soil moisture monitoring methods are capable of providing observations either at a very big spatial scale and timely spotty satellite observations or at a very small scale and timely continuous point measurements. In this framework, meso-scale timely continuous measurements appear of key relevance, thus, recently, Cosmic Ray Neutron Sensing (CRNS) is gaining more and more importance, because of its capacity to deliver long time-series of observations within a footprint of 500m of diameter. Even if during the last years a remarkable number of papers have been published, the calibration of Cosmic Ray Neutron Probes (CRPs) in heterogeneous ecosystems is still an open issue. The CRP is sensitive to all the Hydrogen species and their distribution within the footprint, thus in environments that can be assumed as homogeneous a good accordance between the CRNS data and observed soil moisture can be reached, but, where Hydrogen distributions are complex, different calibration campaigns lead to different results. In order to improve the efficiency of the method, a better understanding of the effects of combined spatial and temporal variability has to be reached. The aim of the actual work is to better understand the effects of multiple Hydrogen sources that vary in time and space and evaluate different approaches in calibration over complex terrain in a mountain area. We present different calibration approaches used for an alpine pasture, which is a research site of the LTER network in South-Tyrol (Italy). In the study site long-term soil moisture observations are present and are used for remote-sensing data validation. For this specific and highly heterogeneous site, the effects of heterogeneous land-cover and topography on CRP calibration are evaluated and some hypotheses on the major sources of uncertainty are formulated.

Using Satellite Data and Land Surface Models to Monitor and Forecast Drought Conditions in Africa and Middle East

NASA Astrophysics Data System (ADS)

Arsenault, K. R.; Shukla, S.; Getirana, A.; Peters-Lidard, C. D.; Kumar, S.; McNally, A.; Zaitchik, B. F.; Badr, H. S.; Funk, C. C.; Koster, R. D.; Narapusetty, B.; Jung, H. C.; Roningen, J. M.

2017-12-01

Drought and water scarcity are among the important issues facing several regions within Africa and the Middle East. In addition, these regions typically have sparse ground-based data networks, where sometimes remotely sensed observations may be the only data available. Long-term satellite records can help with determining historic and current drought conditions. In recent years, several new satellites have come on-line that monitor different hydrological variables, including soil moisture and terrestrial water storage. Though these recent data records may be considered too short for the use in identifying major droughts, they do provide additional information that can better characterize where water deficits may occur. We utilize recent satellite data records of Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage (TWS) and the European Space Agency's Advanced Scatterometer (ASCAT) soil moisture retrievals. Combining these records with land surface models (LSMs), NASA's Catchment and the Noah Multi-Physics (MP), is aimed at improving the land model states and initialization for seasonal drought forecasts. The LSMs' total runoff is routed through the Hydrological Modeling and Analysis Platform (HyMAP) to simulate surface water dynamics, which can provide an additional means of validation against in situ streamflow data. The NASA Land Information System (LIS) software framework drives the LSMs and HyMAP and also supports the capability to assimilate these satellite retrievals, such as soil moisture and TWS. The LSMs are driven for 30+ years with NASA's Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), and the USGS/UCSB Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) rainfall dataset. The seasonal water deficit forecasts are generated using downscaled and bias-corrected versions of NASA's Goddard Earth Observing System Model (GEOS-5), and NOAA's Climate Forecast System (CFSv2) forecasts. These combined satellite and model records and forecasts are intended for use in different decision support tools, like the Famine Early Warning Systems Network (FEWS NET) and the Middle East-North Africa (MENA) Regional Drought Management System, for aiding and forecasting in water and food insecure regions.

Determination of moisture deficit and heat stress tolerance in corn using physiological measurements and a low-cost microcontroller-based monitoring system

USDA-ARS?s Scientific Manuscript database

In the southern United States, corn production encounters moisture deficit coupled with high temperature stress, particularly during the reproductive stage of the plant. In evaluating plants for environmental stress tolerance, it is important to monitor changes in their physical environment under na...

Use of Normalized Difference Water Index for monitoring live fuel moisture

Treesearch

D.A. Roberts; P.E. Dennison; S.H. Peterson; J. Rechel

2006-01-01

Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) were compared for monitoring live fuel moisture in a shrubland ecosystem. Both indices were calculated from 500m spatial resolution Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance data covering a 33-month period from 2000 to 2002. Both NDVI and NDWI were...

Using Enhanced Grace Water Storage Data to Improve Drought Detection by the U.S. and North American Drought Monitors

NASA Technical Reports Server (NTRS)

Houborg, Rasmus; Rodell, Matthew; Lawrimore, Jay; Li, Bailing; Reichle, Rolf; Heim, Richard; Rosencrans, Matthew; Tinker, Rich; Famiglietti, James S.; Svoboda, Mark;

Soil Moisture Retrieval Using Convolutional Neural Networks: Application to Passive Microwave Remote Sensing

NASA Astrophysics Data System (ADS)

Hu, Z.; Xu, L.; Yu, B.

2018-04-01

A empirical model is established to analyse the daily retrieval of soil moisture from passive microwave remote sensing using convolutional neural networks (CNN). Soil moisture plays an important role in the water cycle. However, with the rapidly increasing of the acquiring technology for remotely sensed data, it's a hard task for remote sensing practitioners to find a fast and convenient model to deal with the massive data. In this paper, the AMSR-E brightness temperatures are used to train CNN for the prediction of the European centre for medium-range weather forecasts (ECMWF) model. Compared with the classical inversion methods, the deep learning-based method is more suitable for global soil moisture retrieval. It is very well supported by graphics processing unit (GPU) acceleration, which can meet the demand of massive data inversion. Once the model trained, a global soil moisture map can be predicted in less than 10 seconds. What's more, the method of soil moisture retrieval based on deep learning can learn the complex texture features from the big remote sensing data. In this experiment, the results demonstrates that the CNN deployed to retrieve global soil moisture can achieve a better performance than the support vector regression (SVR) for soil moisture retrieval.

Computed parameters : moisture content for unbound materials at seasonal monitoring program sites

DOT National Transportation Integrated Search

2000-01-01

Moisture content plays a significant role in the performance of pavements. Variation in the amount of moisture in the subgrade can change the volume of swelling soil, which may result in detrimental deformation of the pavement structure. An increase ...

Soil Moisture Sensing

USDA-ARS?s Scientific Manuscript database

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

Development of a Global Evaporative Stress Index Based on Thermal and Microwave LST towards Improved Monitoring of Agricultural Drought

NASA Astrophysics Data System (ADS)

Hain, C.; Anderson, M. C.; Otkin, J.; Holmes, T. R.; Gao, F.

2017-12-01

This presentation will describe the development of a global agricultural monitoring tool, with a focus on providing early warning of developing vegetation stress for agricultural decision-makers and stakeholders at relatively high spatial resolution (5-km). The tool is based on remotely sensed estimates of evapotranspiration, retrieved via energy balance principals using observations of land surface temperature. The Evaporative Stress Index (ESI) represents anomalies in the ratio of actual-to-potential ET generated with the ALEXI surface energy balance model. The LST inputs to ESI have been shown to provide early warning information about the development of vegetation stress with stress-elevated canopy temperatures observed well before a decrease in greenness is detected in remotely sensed vegetation indices. As a diagnostic indicator of actual ET, the ESI requires no information regarding antecedent precipitation or soil moisture storage capacity - the current available moisture to vegetation is deduced directly from the remotely sensed LST signal. This signal also inherently accounts for both precipitation and non-precipitation related inputs/sinks to the plant-available soil moisture pool (e.g., irrigation) which can modify crop response to rainfall anomalies. Independence from precipitation data is a benefit for global agricultural monitoring applications due to sparseness in existing ground-based precipitation networks, and time delays in public reporting. Several enhancements to the current ESI framework will be addressed as requested from project stakeholders: (a) integration of "all-sky" MW Ka-band LST retrievals to augment "clear-sky" thermal-only ESI in persistently cloudy regions; (b) operational production of ESI Rapid Change Indices which provide important early warning information related to onset of actual vegetation stress; and (c) assessment of ESI as a predictor of global yield anomalies; initial studies have shown the ability of intra-seasonal ESI to provide an early indication of at-harvest agricultural yield anomalies.

Soil Moisture Retrieval During a Corn Growth Cycle using L-band (1.6 GHz) Radar Observations

NASA Technical Reports Server (NTRS)

Joseph, Alicia T.; vanderVelde, Rogier; O'Neill, Peggy E.; Lang, Roger; Gish, Tim

2007-01-01

New opportunities for large-scale soil moisture monitoring will emerge with the launch of two low frequency (L-band 1.4 GHz) radiometers: the Aquarius mission in 2009 and the Soil Moisture and Ocean Salinity (SMOS) mission in 2008. Soil moisture is an important land surface variable affecting water and heat exchanges between atmosphere, land surface and deeper ground water reservoirs. The data products from these sensors provide valuable information in a range of climate and hydrologic applications (e.g., numecal weather prediction, drought monitoring, flood forecasting, water resources management, etc.). This paper describes a unique data set that was collected during a field campaign at OPE^ (Optimizing Production Inputs for Economic and Environmental Enhancements) site in Beltsville, Maryland throughout the eompj2ete corn growing in 2002. This investigation describes a simple methodology to correct active microwave observations for vegetation effects, which could potentially be implemented in a global soil moisture monitoring algorithm. The methodology has been applied to radar observation collected during the entire corn growth season and validation against ground measurements showed that the top 5-cm soil moisture can be retrieved with an accuracy up to 0.033 [cu cm/cu cm] depending on the sensing configuration.

Sensor technologies and non-destructive monitoring for dampness diagnosis in cultural heritage

NASA Astrophysics Data System (ADS)

Inmaculada Martínez Garrido, María; Gómez Heras, Miguel; Fort González, Rafael; Valles Iriso, Javier; José Varas Muriel, María

2016-04-01

This work presents a case study based on results of monitoring campaigns developed in San Juan Bautista church in Talamanca de Jarama (Madrid, Spain). This Church was built in the twelfth-thirteenth centuries (Romanesque style) with dolostone ashlars. It was reconstructed in the sixteenth century (Renaissance style) with rubble stone and mortar, brick and an earth fill. Different sections on walls and floors (north and south oriented) have been selected based on a preliminary study of moisture distribution on stone and masonry wall. The behavior of different materials has been studied according to the influence of indoor (microclimatic conditions) and outdoor conditions (weather conditions) and taking into account constructive facts. Several sensing technologies as dataloggers and wireless sensor networks (WSN) together to other non invasive techniques as thermal imaging, portable moisture meter, electrical resistivity tomography (ERT) and ground-penetrating radar (GPR) have been conducted. By means of this study it has been possible to establish an analysis methodology to determine the dampness origin in each case. Conclusions related to the each technique according to its effectiveness in the detection of decay problems have been established. Research funded by Geomateriales 2(S2013/MIT-2914) and Deterioration of stone materials in the interior of historic buildings as a result induced variation of its microclimate (CGL2011-27902) projects. The cooperation received from the Complutense University of Madrid's Research Group Alteración y Conservación de los Materiales Pétreos del Patrimonio (ref. 921349), the Laboratory Network in Science and Technology for Heritage Conservation (RedLabPat, CEI Moncloa) and the Diocese of Alcalá is gratefully acknowledged.

An efficient approach to imaging underground hydraulic networks

NASA Astrophysics Data System (ADS)

Kumar, Mohi

2012-07-01

To better locate natural resources, treat pollution, and monitor underground networks associated with geothermal plants, nuclear waste repositories, and carbon dioxide sequestration sites, scientists need to be able to accurately characterize and image fluid seepage pathways below ground. With these images, scientists can gain knowledge of soil moisture content, the porosity of geologic formations, concentrations and locations of dissolved pollutants, and the locations of oil fields or buried liquid contaminants. Creating images of the unknown hydraulic environments underfoot is a difficult task that has typically relied on broad extrapolations from characteristics and tests of rock units penetrated by sparsely positioned boreholes. Such methods, however, cannot identify small-scale features and are very expensive to reproduce over a broad area. Further, the techniques through which information is extrapolated rely on clunky and mathematically complex statistical approaches requiring large amounts of computational power.

Assessing Temporal Stability for Coarse Scale Satellite Moisture Validation in the Maqu Area, Tibet

PubMed Central

Bhatti, Haris Akram; Rientjes, Tom; Verhoef, Wouter; Yaseen, Muhammad

2013-01-01

This study evaluates if the temporal stability concept is applicable to a time series of satellite soil moisture images so to extend the common procedure of satellite image validation. The area of study is the Maqu area, which is located in the northeastern part of the Tibetan plateau. The network serves validation purposes of coarse scale (25–50 km) satellite soil moisture products and comprises 20 stations with probes installed at depths of 5, 10, 20, 40, 80 cm. The study period is 2009. The temporal stability concept is applied to all five depths of the soil moisture measuring network and to a time series of satellite-based moisture products from the Advance Microwave Scanning Radiometer (AMSR-E). The in-situ network is also assessed by Pearsons's correlation analysis. Assessments by the temporal stability concept proved to be useful and results suggest that probe measurements at 10 cm depth best match to the satellite observations. The Mean Relative Difference plot for satellite pixels shows that a RMSM pixel can be identified but in our case this pixel does not overlay any in-situ station. Also, the RMSM pixel does not overlay any of the Representative Mean Soil Moisture (RMSM) stations of the five probe depths. Pearson's correlation analysis on in-situ measurements suggests that moisture patterns over time are more persistent than over space. Since this study presents first results on the application of the temporal stability concept to a series of satellite images, we recommend further tests to become more conclusive on effectiveness to broaden the procedure of satellite validation. PMID:23959237

Wide-Area Soil Moisture Estimation Using the Propagation of Lightning Generated Low-Frequency Electromagnetic Signals 1977

USDA-ARS?s Scientific Manuscript database

Land surface moisture measurements are central to our understanding of the earth’s water system, and are needed to produce accurate model-based weather/climate predictions. Currently, there exists no in-situ network capable of estimating wide-area soil moisture. In this paper, we explore an alterna...

Comparing AMSR-E soil moisture estimates to the extended record of the U.S. Climate Reference Network (USCRN)

USDA-ARS?s Scientific Manuscript database

Soil moisture plays an integral role in various aspects ranging from multi-scale hydrologic modeling to agricultural decision analysis to multi-scale hydrologic modeling, from climate change assessments to drought prediction and prevention. The broad availability of soil moisture estimates has only...

Prolongation of SMAP to Spatio-temporally Seamless Coverage of Continental US Using a Deep Learning Neural Network

NASA Astrophysics Data System (ADS)

Fang, K.; Shen, C.; Kifer, D.; Yang, X.

2017-12-01

The Soil Moisture Active Passive (SMAP) mission has delivered high-quality and valuable sensing of surface soil moisture since 2015. However, its short time span, coarse resolution, and irregular revisit schedule have limited its use. Utilizing a state-of-the-art deep-in-time neural network, Long Short-Term Memory (LSTM), we created a system that predicts SMAP level-3 soil moisture data using climate forcing, model-simulated moisture, and static physical attributes as inputs. The system removes most of the bias with model simulations and also improves predicted moisture climatology, achieving a testing accuracy of 0.025 to 0.03 in most parts of Continental United States (CONUS). As the first application of LSTM in hydrology, we show that it is more robust than simpler methods in either temporal or spatial extrapolation tests. We also discuss roles of different predictors, the effectiveness of regularization algorithms and impacts of training strategies. With high fidelity to SMAP products, our data can aid various applications including data assimilation, weather forecasting, and soil moisture hindcasting.

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

NASA Astrophysics Data System (ADS)

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

2013-04-01

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

Determination of the moisture content in the fluoride oxide fluxes of electroslag remelting

NASA Astrophysics Data System (ADS)

Vdovin, K. N.; Feoktistov, N. A.; Pivovarova, K. G.; Deryabin, D. A.

2016-12-01

ANF-32 flux has been studied with regard to the moisture content both after storage and upon operation. A simple and reliable procedure for the determination of the moisture content in ESR fluxes is proposed, and recommendations are given on monitoring the moisture content in calcined fluxes. The main sources of crystallization water of hydration are hydrogen sources.

Foliar moisture content of Pacific Northwest vegetation and its relation to wildland fire behavior.

Treesearch

James K. Agee; Clinton S. Wright; Nathan Williamson; Mark H. Huff

2002-01-01

Fotiar moisture was monitored for five conifers and associated understory vegetation in Pacific Northwest forests. Decline in foliar moisture of new foliage occurred over the dry season, while less variation was evident in older foliage. Late season foliar moisture ranged from 130 to 170%. In riparian-upland comparisons, largest differences were found for understory...

The NASA Soil Moisture Active Passive (SMAP) Mission - Algorithm and Cal/Val Activities and Synergies with SMOS and Other L-Band Missions

NASA Technical Reports Server (NTRS)

Njoku, Eni; Entekhabi, Dara; O'Neill, Peggy; Jackson, Tom; Kellogg, Kent; Entin, Jared

2011-01-01

NASA's Soil Moisture Active Passive (SMAP) mission, planned for launch in late 2014, has as its key measurement objective the frequent, global mapping of near-surface soil moisture and its freeze-thaw state. SMAP soil moisture and freeze/thaw measurements at 10 km and 3 km resolutions respectively, would enable significantly improved estimates of water, energy and carbon transfers between the land and atmosphere. Soil moisture control of these fluxes is a key factor in the performance of atmospheric models used for weather forecasts and climate projections Soil moisture measurements are also of great importance in assessing floods and for monitoring drought. In addition, observations of soil moisture and freeze/thaw timing over the boreal latitudes can help reduce uncertainties in quantifying the global carbon balance. The SMAP measurement concept utilizes an L-band radar and radiometer sharing a rotating 6-meter mesh reflector antenna. The SMAP radiometer and radar flight hardware and ground processing designs are incorporating approaches to identify and mitigate potential terrestrial radio frequency interference (RFI). The radar and radiometer instruments are planned to operate in a 680 km polar orbit, viewing the surface at a constant 40-degree incidence angle with a 1000-km swath width, providing 3-day global coverage. Data from the instruments would yield global maps of soil moisture and freeze/thaw state to be provided at 10 km and 3 km resolutions respectively, every two to three days. Plans are to provide also a radiometer-only soil moisture product at 40-km spatial resolution. This product and the underlying brightness temperatures have characteristics similar to those provided by the Soil Moisture and Ocean Salinity (SMOS) mission. As a result, there are unique opportunities for common data product development and continuity between the two missions. SMAP also has commonalities with other satellite missions having L-band radiometer and/or radar sensors applicable to soil moisture measurement, such as Aquarius, SAO COM, and ALOS-2. The algorithms and data products for SMAP are being developed in the SMAP Science Data System (SDS) Testbed. The algorithms are developed and evaluated in the SDS Testbed using simulated SMAP observations as well as observational data from current airborne and spaceborne L-band sensors including SMOS. The SMAP project is developing a Calibration and Validation (Cal/Val) Plan that is designed to support algorithm development (pre-launch) and data product validation (post-launch). A key component of the Cal/Val Plan is the identification, characterization, and instrumentation of sites that can be used to calibrate and validate the sensor data (Level I) and derived geophysical products (Level 2 and higher). In this presentation we report on the development status of the SMAP data product algorithms, and the planning and implementation of the SMAP Cal/Val program. Several components of the SMAP algorithm development and Cal/Val plans have commonality with those of SMOS, and for this reason there are shared activities and resources that can be utilized between the missions, including in situ networks, ancillary data sets, and long-term monitoring sites.

Using machine learning to produce near surface soil moisture estimates from deeper in situ records at U.S. Climate Reference Network (USCRN) locations: Analysis and applications to AMSR-E satellite validation

NASA Astrophysics Data System (ADS)

Coopersmith, Evan J.; Cosh, Michael H.; Bell, Jesse E.; Boyles, Ryan

2016-12-01

Surface soil moisture is a critical parameter for understanding the energy flux at the land atmosphere boundary. Weather modeling, climate prediction, and remote sensing validation are some of the applications for surface soil moisture information. The most common in situ measurement for these purposes are sensors that are installed at depths of approximately 5 cm. There are however, sensor technologies and network designs that do not provide an estimate at this depth. If soil moisture estimates at deeper depths could be extrapolated to the near surface, in situ networks providing estimates at other depths would see their values enhanced. Soil moisture sensors from the U.S. Climate Reference Network (USCRN) were used to generate models of 5 cm soil moisture, with 10 cm soil moisture measurements and antecedent precipitation as inputs, via machine learning techniques. Validation was conducted with the available, in situ, 5 cm resources. It was shown that a 5 cm estimate, which was extrapolated from a 10 cm sensor and antecedent local precipitation, produced a root-mean-squared-error (RMSE) of 0.0215 m3/m3. Next, these machine-learning-generated 5 cm estimates were also compared to AMSR-E estimates at these locations. These results were then compared with the performance of the actual in situ readings against the AMSR-E data. The machine learning estimates at 5 cm produced an RMSE of approximately 0.03 m3/m3 when an optimized gain and offset were applied. This is necessary considering the performance of AMSR-E in locations characterized by high vegetation water contents, which are present across North Carolina. Lastly, the application of this extrapolation technique is applied to the ECONet in North Carolina, which provides a 10 cm depth measurement as its shallowest soil moisture estimate. A raw RMSE of 0.028 m3/m3 was achieved, and with a linear gain and offset applied at each ECONet site, an RMSE of 0.013 m3/m3 was possible.

Development of an In-Situ Decommissioning Sensor Network Test Bed for Structural Condition Monitoring - 12156

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zeigler, Kristine E.; Ferguson, Blythe A.

2012-07-01

The Savannah River National Laboratory (SRNL) has established an In Situ Decommissioning (ISD) Sensor Network Test Bed, a unique, small scale, configurable environment, for the assessment of prospective sensors on actual ISD system material, at minimal cost. The Department of Energy (DOE) is presently implementing permanent entombment of contaminated, large nuclear structures via ISD. The ISD end state consists of a grout-filled concrete civil structure within the concrete frame of the original building. Validation of ISD system performance models and verification of actual system conditions can be achieved through the development a system of sensors to monitor the materials andmore » condition of the structure. The ISD Sensor Network Test Bed has been designed and deployed to addresses the DOE-Environmental Management Technology Need to develop a remote monitoring system to determine and verify ISD system performance. Commercial off-the-shelf sensors have been installed on concrete blocks taken from walls of the P Reactor Building at the Savannah River Site. Deployment of this low-cost structural monitoring system provides hands-on experience with sensor networks. The initial sensor system consists of groutable thermistors for temperature and moisture monitoring, strain gauges for crack growth monitoring, tilt-meters for settlement monitoring, and a communication system for data collection. Baseline data and lessons learned from system design and installation and initial field testing will be utilized for future ISD sensor network development and deployment. The Sensor Network Test Bed at SRNL uses COTS sensors on concrete blocks from the outer wall of the P Reactor Building to measure conditions expected to occur in ISD structures. Knowledge and lessons learned gained from installation, testing, and monitoring of the equipment will be applied to sensor installation in a meso-scale test bed at FIU and in future ISD structures. The initial data collected from the sensors installed on the P Reactor Building blocks define the baseline materials condition of the P Reactor ISD external concrete structure. Continued monitoring of the blocks will enable evaluation of the effects of aging on the P Reactor ISD structure. The collected data will support validation of the material degradation model and assessment of the condition of the ISD structure over time. The following are recommendations for continued development of the ISD Sensor Network Test Bed: - Establish a long-term monitoring program using the concrete blocks with existing sensor and/or additional sensors for trending the concrete materials and structural condition; - Continue development of a stand-alone test bed sensor system that is self-powered and provides wireless transmission of data to a user-accessible dashboard; - Develop and implement periodic NDE/DE characterization of the concrete blocks to provide verification and validation for the measurements obtained through the sensor system and concrete degradation model(s). (authors)« less

Closing the water balance with cosmic-ray soil moisture measurements and assessing their spatial variability within two semiarid watersheds

NASA Astrophysics Data System (ADS)

Schreiner-McGraw, A. P.; Vivoni, E. R.; Mascaro, G.; Franz, T. E.

2015-06-01

Soil moisture dynamics reflect the complex interactions of meteorological conditions with soil, vegetation and terrain properties. In this study, intermediate scale soil moisture estimates from the cosmic-ray sensing (CRS) method are evaluated for two semiarid ecosystems in the southwestern United States: a mesquite savanna at the Santa Rita Experimental Range (SRER) and a mixed shrubland at the Jornada Experimental Range (JER). Evaluations of the CRS method are performed for small watersheds instrumented with a distributed sensor network consisting of soil moisture sensor profiles, an eddy covariance tower and runoff flumes used to close the water balance. We found an excellent agreement between the CRS method and the distributed sensor network (RMSE of 0.009 and 0.013 m3 m-3 at SRER and JER) at the hourly time scale over the 19-month study period, primarily due to the inclusion of 5 cm observations of shallow soil moisture. Good agreement was obtained in soil moisture changes estimated from the CRS and watershed water balance methods (RMSE = 0.001 and 0.038 m3 m-3 at SRER and JER), with deviations due to bypassing of the CRS measurement depth during large rainfall events. This limitation, however, was used to show that drier-than-average conditions at SRER promoted plant water uptake from deeper layers, while the wetter-than-average period at JER resulted in leakage towards deeper soils. Using the distributed sensor network, we quantified the spatial variability of soil moisture in the CRS footprint and the relation between evapotranspiration and soil moisture, in both cases finding similar predictive relations at both sites that are applicable to other semiarid ecosystems in the southwestern US. Furthermore, soil moisture spatial variability was related to evapotranspiration in a manner consistent with analytical relations derived using the CRS method, opening up new possibilities for understanding land-atmosphere interactions.

Distributed multifunctional sensor network for composite structural state sensing

NASA Astrophysics Data System (ADS)

Qing, Xinlin P.; Wang, Yishou; Gao, Limin; Kumar, Amrita

2012-04-01

Advanced fiber reinforced composite materials are becoming the main structural materials of next generation of aircraft because of their high strength and stiffness to weight ratios, and strong designability. In order to take full advantages of composite materials, there is a need to develop an embeddable multifunctional sensing system to allow a structure to "feel" and "think" its structural state. In this paper, the concept of multifunctional sensor network integrated with a structure, similar to the human nervous system, has been developed. Different types of network sensors are permanently integrated within a composite structure to sense structural strain, temperature, moisture, aerodynamic pressure; monitor external impact on the structure; and detect structural damages. Utilizing this revolutionary concept, future composite structures can be designed and manufactured to provide multiple modes of information, so that the structures have the capabilities for intelligent sensing, environmental adaptation and multi-functionality. The challenges for building such a structural state sensing system and some solutions to address the challenges are also discussed in the paper.

Improving Alpine Streamflow Simulations by Incorporation of Evapotranspiration and Soil Moisture Data

NASA Astrophysics Data System (ADS)

Tobin, K. J.; Bennett, M. E.

2017-12-01

Over the last decade autocalibration routines have become commonplace in watershed modeling. This approach is most often used to simulate a streamflow at a basin's outlet. In alpine settings spring/early summer snowmelt is by far the dominant signal in this system. Therefore, there is great potential for a modeled watershed to underperform during other times of the year. This tendency has been noted in many prior studies. In this work, the Soil and Water Assessment Tool (SWAT) model was autocalibrated with the SUFI-2 routine. Two mountainous watersheds from Idaho and Utah were examined. In this study, the basins were calibrated on a monthly satellite based on the MODIS 16A2 product. The gridded MODIS product was ideally suited to derive an estimate of ET on a subbasin basis. Soil moisture data was derived from extrapolation of in situ sites from the SNOwpack TELemetry (SNOTEL) network. Previous work has indicated that in situ soil moisture can be applied to derive an estimate at a significant distance (>30 km) away from the in situ site. Optimized ET and soil moisture parameter values were then applied to streamflow simulations. Preliminary results indicate improved streamflow performance both during calibration (2005-2011) and validation (2012-2014) periods. Streamflow performance was monitored with not only standard objective metrics (bias and Nash Sutcliffe coefficients) but also improved baseflow accuracy, demonstrating the utility of this approach in improving watershed modeling fidelity outside the main snowmelt season.

Smap Soil Moisture Data Assimilation for the Continental United States and Eastern Africa

NASA Astrophysics Data System (ADS)

Blankenship, C. B.; Case, J.; Zavodsky, B.; Crosson, W. L.

2016-12-01

The NASA Short-Term Prediction Research and Transition (SPoRT) Center at Marshall Space Flight Center manages near-real-time runs of the Noah Land Surface Model within the NASA Land Information System (LIS) over Continental U.S. (CONUS) and Eastern Africa domains. Soil moisture products from the CONUS model run are used by several NOAA/National Weather Service Weather Forecast Offices for flood and drought situational awareness. The baseline LIS configuration is the Noah model driven by atmospheric and combined radar/gauge precipitation analyses, and input satellite-derived real-time green vegetation fraction on a 3-km grid for the CONUS. This configuration is being enhanced by adding the assimilation of Level 2 Soil Moisture Active/Passive (SMAP) soil moisture retrievals in a parallel run beginning on 1 April 2015. Our implementation of SMAP assimilation includes a cumulative distribution function (CDF) matching approach that aggregates points with similar soil types. This method allows creation of robust CDFs with a short data record, and also permits the correction of local anomalies that may arise from poor forcing data (e.g., quality-control problems with rain gauges). Validation results using in situ soil monitoring networks in the CONUS are shown, with comparisons to the baseline SPoRT-LIS run. Initial results are also presented from a modeling run in eastern Africa, forced by Integrated Multi-satellitE Retrievals for GPM (IMERG) precipitation data. Strategies for spatial downscaling and for dealing with effective depth of the retrieval product are also discussed.

Integrating real-time and manual monitored data to predict hillslope soil moisture dynamics with high spatio-temporal resolution using linear and non-linear models

USDA-ARS?s Scientific Manuscript database

Spatio-temporal variability of soil moisture (') is a challenge that remains to be better understood. A trade-off exists between spatial coverage and temporal resolution when using the manual and real-time ' monitoring methods. This restricted the comprehensive and intensive examination of ' dynamic...

Improving soil moisture simulation to support Agricultural Water Resource Management using Satellite-based water cycle observations

NASA Astrophysics Data System (ADS)

Gupta, Manika; Bolten, John; Lakshmi, Venkat

2016-04-01

Efficient and sustainable irrigation systems require optimization of operational parameters such as irrigation amount which are dependent on the soil hydraulic parameters that affect the model's accuracy in simulating soil water content. However, it is a scientific challenge to provide reliable estimates of soil hydraulic parameters and irrigation estimates, given the absence of continuously operating soil moisture and rain gauge network. For agricultural water resource management, the in-situ measurements of soil moisture are currently limited to discrete measurements at specific locations, and such point-based measurements do not represent the spatial distribution at a larger scale accurately, as soil moisture is highly variable both spatially and temporally (Wang and Qu 2009). In the current study, flood irrigation scheme within the land surface model is triggered when the root-zone soil moisture deficit reaches below a threshold of 25%, 50% and 75% with respect to the maximum available water capacity (difference between field capacity and wilting point) and applied until the top layer is saturated. An additional important criterion needed to activate the irrigation scheme is to ensure that it is irrigation season by assuming that the greenness vegetation fraction (GVF) of the pixel exceed 0.40 of the climatological annual range of GVF (Ozdogan et al. 2010). The main hypothesis used in this study is that near-surface remote sensing soil moisture data contain useful information that can describe the effective hydrological conditions of the basin such that when appropriately inverted, it would provide field capacity and wilting point soil moisture, which may be representative of that basin. Thus, genetic algorithm inverse method is employed to derive the effective parameters and derive the soil moisture deficit for the root zone by coupling of AMSR-E soil moisture with the physically based hydrological model. Model performance is evaluated using MODIS-evapotranspiration (ET) and MODIS land surface temperature (LST) products. The soil moisture estimates for the root zone are also validated with the in-situ field data, for three sites (2- irrigated and 1- rainfed) located at the University of Nebraska Agricultural Research and Development Center near Mead, NE and monitored by three AmeriFlux installations (Verma et al., 2005) by evaluating the root mean square error (RMSE) and Mean Bias error (MBE).

The Development of Terrestrial Water Cycle Applications for SMAP Soil Moisture Data Products

USDA-ARS?s Scientific Manuscript database

Soil moisture storage sits at the locus of the terrestrial water cycle and governs the relative partitioning of precipitation into various land surface flux components. Consequently, improved observational constraint of soil moisture variations should improve our ability to globally monitor the te...

40 CFR 75.37 - Missing data procedures for moisture.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 17 2012-07-01 2012-07-01 false Missing data procedures for moisture... PROGRAMS (CONTINUED) CONTINUOUS EMISSION MONITORING Missing Data Substitution Procedures § 75.37 Missing... system shall substitute for missing moisture data using the procedures of this section. (b) Where no...

40 CFR 75.37 - Missing data procedures for moisture.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 16 2010-07-01 2010-07-01 false Missing data procedures for moisture... PROGRAMS (CONTINUED) CONTINUOUS EMISSION MONITORING Missing Data Substitution Procedures § 75.37 Missing... system shall substitute for missing moisture data using the procedures of this section. (b) Where no...

40 CFR 75.37 - Missing data procedures for moisture.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 17 2014-07-01 2014-07-01 false Missing data procedures for moisture... PROGRAMS (CONTINUED) CONTINUOUS EMISSION MONITORING Missing Data Substitution Procedures § 75.37 Missing... system shall substitute for missing moisture data using the procedures of this section. (b) Where no...

40 CFR 75.37 - Missing data procedures for moisture.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 17 2013-07-01 2013-07-01 false Missing data procedures for moisture... PROGRAMS (CONTINUED) CONTINUOUS EMISSION MONITORING Missing Data Substitution Procedures § 75.37 Missing... system shall substitute for missing moisture data using the procedures of this section. (b) Where no...

40 CFR 75.37 - Missing data procedures for moisture.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 16 2011-07-01 2011-07-01 false Missing data procedures for moisture... PROGRAMS (CONTINUED) CONTINUOUS EMISSION MONITORING Missing Data Substitution Procedures § 75.37 Missing... system shall substitute for missing moisture data using the procedures of this section. (b) Where no...

Benchmarking a soil moisture data assimilation system for agricultural drought monitoring

USDA-ARS?s Scientific Manuscript database

Agricultural drought is defined as a shortage of moisture in the root zone of plants. Recently available satellite-based remote sensing data have accelerated development of drought early warning system by providing spatially continuous soil moisture information repeatedly at short-term interval. Non...

Large-scale, dynamic transformations in fuel moisture drive wildfire activity across southeastern Australia

NASA Astrophysics Data System (ADS)

Nolan, R. H.; Boer, M. M.; Resco de Dios, V.; Caccamo, G.; Bradstock, R. A.

2016-05-01

The occurrence of large, high-intensity wildfires requires plant biomass, or fuel, that is sufficiently dry to burn. This poses the question, what is "sufficiently dry"? Until recently, the ability to address this question has been constrained by the spatiotemporal scale of available methods to monitor the moisture contents of both dead and live fuels. Here we take advantage of recent developments in macroscale monitoring of fuel moisture through a combination of remote sensing and climatic modeling. We show there are clear thresholds of fuel moisture content associated with the occurrence of wildfires in forests and woodlands. Furthermore, we show that transformations in fuel moisture conditions across these thresholds can occur rapidly, within a month. Both the approach presented here, and our findings, can be immediately applied and may greatly improve fire risk assessments in forests and woodlands globally.

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

NASA Astrophysics Data System (ADS)

Schrön, M.; Fersch, B.; Jagdhuber, T.

2017-12-01

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

SBIR Phase II Final Report: Low cost Autonomous NMR and Multi-sensor Soil Monitoring Instrument

DOE Office of Scientific and Technical Information (OSTI.GOV)

Walsh, David O.

In this 32-month SBIR Phase 2 program, Vista Clara designed, assembled and successfully tested four new NMR instruments for soil moisture measurement and monitoring: An enhanced performance man-portable Dart NMR logging probe and control unit for rapid, mobile measurement in core holes and 2” PVC access wells; A prototype 4-level Dart NMR monitoring probe and prototype multi-sensor soil monitoring control unit for long-term unattended monitoring of soil moisture and other measurements in-situ; A non-invasive 1m x 1m Discus NMR soil moisture sensor with surface based magnet/coil array for rapid measurement of soil moisture in the top 50 cm of themore » subsurface; A non-invasive, ultra-lightweight Earth’s field surface NMR instrument for non-invasive measurement and mapping of soil moisture in the top 3 meters of the subsurface. The Phase 2 research and development achieved most, but not all of our technical objectives. The single-coil Dart in-situ sensor and control unit were fully developed, demonstrated and successfully commercialized within the Phase 2 period of performance. The multi-level version of the Dart probe was designed, assembled and demonstrated in Phase 2, but its final assembly and testing were delayed until close to the end of the Phase 2 performance period, which limited our opportunities for demonstration in field settings. Likewise, the multi-sensor version of the Dart control unit was designed and assembled, but not in time for it to be deployed for any long-term monitoring demonstrations. The prototype ultra-lightweight surface NMR instrument was developed and demonstrated, and this result will be carried forward into the development of a new flexible surface NMR instrument and commercial product in 2018.« less

Analysis of in situ resources of for the Soil Moisture Active Passive Validation Experiments in 2015 and 2016

USDA-ARS?s Scientific Manuscript database

With the launch of the Soil Moisture Active Passive Mission (SMAP) in 2015, a new era of soil moisture monitoring was begun. Soil moisture is available on a near daily basis at a 36 km resolution for the globe. But this dataset is only as valuable if its products are accurate and reliableas its acc...

Field-scale moisture estimates using COSMOS sensors: a validation study with temporary networks and leaf-area-indices

USDA-ARS?s Scientific Manuscript database

The Cosmic-ray Soil Moisture Observing System (COSMOS) is a new and innovative method for estimating surface and near surface soil moisture at large (~700 m) scales. This system accounts for liquid water within its measurement volume. Many of the sites used in the early validation of the system had...

Bulk Moisture and Salinity Sensor

NASA Technical Reports Server (NTRS)

Nurge, Mark; Monje, Oscar; Prenger, Jessica; Catechis, John

2013-01-01

Measurement and feedback control of nutrient solutions in plant root zones is critical to the development of healthy plants in both terrestrial and reduced-gravity environments. In addition to the water content, the amount of fertilizer in the nutrient solution is important to plant health. This typically requires a separate set of sensors to accomplish. A combination bulk moisture and salinity sensor has been designed, built, and tested with different nutrient solutions in several substrates. The substrates include glass beads, a clay-like substrate, and a nutrient-enriched substrate with the presence of plant roots. By measuring two key parameters, the sensor is able to monitor both the volumetric water content and salinity of the nutrient solution in bulk media. Many commercially available moisture sensors are point sensors, making localized measurements over a small volume at the point of insertion. Consequently, they are more prone to suffer from interferences with air bubbles, contact area of media, and root growth. This makes it difficult to get an accurate representation of true moisture content and distribution in the bulk media. Additionally, a network of point sensors is required, increasing the cabling, data acquisition, and calibration requirements. measure the dielectric properties of a material in the annular space of the vessel. Because the pore water in the media often has high salinity, a method to measure the media moisture content and salinity simultaneously was devised. Characterization of the frequency response for capacitance and conductance across the electrodes was completed for 2-mm glass bead media, 1- to 2-mm Turface (a clay like media), and 1- to 2-mm fertilized Turface with the presence of root mass. These measurements were then used to find empirical relationships among capacitance (C), the dissipation factor (D), the volumetric water content, and the pore water salinity.

Drought Prediction for Socio-Cultural Stability Project

NASA Technical Reports Server (NTRS)

Peters-Lidard, Christa; Eylander, John B.; Koster, Randall; Narapusetty, Balachandrudu; Kumar, Sujay; Rodell, Matt; Bolten, John; Mocko, David; Walker, Gregory; Arsenault, Kristi;

Nondestructive and Real-time Measurement of Moisture in Plant

NASA Astrophysics Data System (ADS)

Ogawa, Yuichi; Kawase, Kodo; Mizuno, Maya; Yamashita, Masatsugu; Otani, Chiko

We constructed a THz transillumination system for water content monitoring, and we succeeded in measuring the moisture level in plants. Our measurement system uses a widely tunable coherent THz parametric oscillator source. As target we chose for this experiment a leaf of Japanese basil. The time variation of the water content in the leaf was monitored in two situations: a leaf freshly cut which is left to dry out, and the leaf of a water stressed plant. We found by real-time measurements that the water content of a cut leaf does not decrease uniformly in time. Also, the response to water stress is delayed by about 5-10 minutes. Furthermore, we demonstrated a moisture measurement using a transillumination THz imaging system. As target we chose for this experiment a leaf of Hedera helix held between two thin plastic sheets. The change of the moisture distribution is clearly visible. These results show that the method described here can be applied to nondestructive and real-time monitoring of water content in plants.

In situ soil moisture and matrix potential - what do we measure?

NASA Astrophysics Data System (ADS)

Jackisch, Conrad; Durner, Wolfgang

2017-04-01

Soil moisture and matric potential are often regarded as state variables that are simple to monitor at the Darcy-scale. At the same time unproven believes about the capabilities and reliabilities of specific sensing methods or sensor systems exist. A consortium of ten institutions conducted a comparison study of currently available sensors for soil moisture and matrix potential at a specially homogenised field site with sandy loam soil, which was kept free of vegetation. In total 57 probes of 15 different systems measuring soil moisture, and 50 probes of 14 different systems measuring matric potential have been installed in a 0.5 meter grid to monitor the moisture state in 0.2 meter depth. The results give rise to a series of substantial questions about the state of the art in hydrological monitoring, the heterogeneity problem and the meaning of soil water retention at the field scale: A) For soil moisture, most sensors recorded highly plausible data. However, they do not agree in absolute values and reaction timing. For matric potential, only tensiometers were able to capture the quick reactions during rainfall events. All indirect sensors reacted comparably slowly and thus introduced a bias with respect to the sensing of soil water state under highly dynamic conditions. B) Under natural field conditions, a better homogeneity than in our setup can hardly be realised. While the homogeneity assumption held for the first weeks, it collapsed after a heavy storm event. The event exceeded the infiltration capacity, initiated the generation of redistribution networks at the surface, which altered the local surface properties on a very small scale. If this is the reality at a 40 m2 plot, what representativity have single point observations referencing the state of whole basins? C) A comparison of in situ and lab-measured retention curves marks systematic differences. Given the general practice of soil water retention parameterisation in almost any hydrological model this poses quite some concern about deriving field parameters from lab measurements. We will present some insights from the comparison study and highlight the conceptual concerns arising from it. Through this we hope to stimulate a discussion towards more critical revision of measurement assumptions and towards the development of alternative techniques to monitor subsurface states. The sensor comparison study consortium is a cooperation of Wolfgang Durner2, Ines Andrä2, Kai Germer2, Katrin Schulz2, Marcus Schiedung2, Jaqueline Haller-Jans2, Jonas Schneider2, Julia Jaquemotte2, Philipp Helmer2, Leander Lotz2, Thomas Graeff3, Andreas Bauer3, Irene Hahn3, Conrad Jackisch1, Martin Sanda4, Monika Kumpan5, Johann Dorner5, Gerrit de Rooij6, Stephan Wessel-Bothe7, Lorenz Kottmann8, and Siegfried Schittenhelm8. The great support by the team and the Thünen Institute Braunschweig is gratefully acknowledged. 1 Karlsruhe Institute of Technology, 2 Technical University of Braunschweig, 3 University of Potsdam, 4 Technical University of Prague, 5 Federal Department for Water Management Petzenkirchen, 6 Helmholtz Centre for Environmental Research Halle, 7 ecoTech GmbH Bonn, 8 Julius Kühn Institute Braunschweig

SMOS disaggregated soil moisture product at 1 km resolution: processor overview and first validation results

USDA-ARS?s Scientific Manuscript database

The SMOS (Soil Moisture and Ocean Salinity) mission provides surface soil moisture (SM) maps at a mean resolution of ~50 km. However, agricultural applications (irrigation, crop monitoring) and some hydrological applications (floods and modeling of small basins) require higher resolution SM...

Modeling the Soil Water and Energy Balance of a Mixed Grass Rangeland and Evaluating a Soil Water Based Drought Index in Wyoming

NASA Astrophysics Data System (ADS)

Engda, T. A.; Kelleners, T. J.; Paige, G. B.

2013-12-01

Soil water content plays an important role in the complex interaction between terrestrial ecosystems and the atmosphere. Automated soil water content sensing is increasingly being used to assess agricultural drought conditions. A one-dimensional vertical model that calculates incoming solar radiation, canopy energy balance, surface energy balance, snow pack dynamics, soil water flow, snow-soil heat exchange is applied to calculate water flow and heat transport in a Rangeland soil located near Lingel, Wyoming. The model is calibrated and validated using three years of measured soil water content data. Long-term average soil water content dynamics are calculated using a 30 year historical data record. The difference between long-term average soil water content and observed soil water content is compared with plant biomass to evaluate the usefulness of soil water content as a drought indicator. Strong correlation between soil moisture surplus/deficit and plant biomass may prove our hypothesis that soil water content is a good indicator of drought conditions. Soil moisture based drought index is calculated using modeled and measured soil water data input and is compared with measured plant biomass data. A drought index that captures local drought conditions proves the importance of a soil water monitoring network for Wyoming Rangelands to fill the gap between large scale drought indices, which are not detailed enough to assess conditions at local level, and local drought conditions. Results from a combined soil moisture monitoring and computer modeling, and soil water based drought index soil are presented to quantify vertical soil water flow, heat transport, historical soil water variations and drought conditions in the study area.

Hydrologic modeling for monitoring water availability in Eastern and Southern Africa

NASA Astrophysics Data System (ADS)

McNally, A.; Harrison, L.; Shukla, S.; Pricope, N. G.; Peters-Lidard, C. D.

2017-12-01

Severe droughts in 2015, 2016 and 2017 in Ethiopia, Southern Africa, and Somalia have negatively impacted agriculture and municipal water supplies resulting in food and water insecurity. Information from remotely sensed data and field reports indicated that the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation (FLDAS) accurately tracked both the anomalously low soil moisture, evapotranspiration and runoff conditions. This work presents efforts to more precisely monitor how the water balance responds to water availability deficits (i.e. drought) as estimated by the FLDAS with CHIRPS precipitation, MERRA-2 meteorological forcing and the Noah33 land surface model.Preliminary results indicate that FLDAS streamflow estimates are well correlated with observed streamflow where irrigation and other channel modifications are not present; FLDAS evapotranspiration (ET) is well correlated with ET from the Operational Simplified Surface Energy Balance model (SSEBop) in Eastern and Southern Africa. We then use these results to monitor availability, and explore trends in water supply and demand.

Airborne Detection and Tracking of Geologic Leakage Sites

NASA Astrophysics Data System (ADS)

Jacob, Jamey; Allamraju, Rakshit; Axelrod, Allan; Brown, Calvin; Chowdhary, Girish; Mitchell, Taylor

2014-11-01

Safe storage of CO2 to reduce greenhouse gas emissions without adversely affecting energy use or hindering economic growth requires development of monitoring technology that is capable of validating storage permanence while ensuring the integrity of sequestration operations. Soil gas monitoring has difficulty accurately distinguishing gas flux signals related to leakage from those associated with meteorologically driven changes of soil moisture and temperature. Integrated ground and airborne monitoring systems are being deployed capable of directly detecting CO2 concentration in storage sites. Two complimentary approaches to detecting leaks in the carbon sequestration fields are presented. The first approach focuses on reducing the requisite network communication for fusing individual Gaussian Process (GP) CO2 sensing models into a global GP CO2 model. The GP fusion approach learns how to optimally allocate the static and mobile sensors. The second approach leverages a hierarchical GP-Sigmoidal Gaussian Cox Process for airborne predictive mission planning to optimally reducing the entropy of the global CO2 model. Results from the approaches will be presented.

Prediction of Root Zone Soil Moisture using Remote Sensing Products and In-Situ Observation under Climate Change Scenario

NASA Astrophysics Data System (ADS)

Singh, G.; Panda, R. K.; Mohanty, B.

2015-12-01

Prediction of root zone soil moisture status at field level is vital for developing efficient agricultural water management schemes. In this study, root zone soil moisture was estimated across the Rana watershed in Eastern India, by assimilation of near-surface soil moisture estimate from SMOS satellite into a physically-based Soil-Water-Atmosphere-Plant (SWAP) model. An ensemble Kalman filter (EnKF) technique coupled with SWAP model was used for assimilating the satellite soil moisture observation at different spatial scales. The universal triangle concept and artificial intelligence techniques were applied to disaggregate the SMOS satellite monitored near-surface soil moisture at a 40 km resolution to finer scale (1 km resolution), using higher spatial resolution of MODIS derived vegetation indices (NDVI) and land surface temperature (Ts). The disaggregated surface soil moisture were compared to ground-based measurements in diverse landscape using portable impedance probe and gravimetric samples. Simulated root zone soil moisture were compared with continuous soil moisture profile measurements at three monitoring stations. In addition, the impact of projected climate change on root zone soil moisture were also evaluated. The climate change projections of rainfall were analyzed for the Rana watershed from statistically downscaled Global Circulation Models (GCMs). The long-term root zone soil moisture dynamics were estimated by including a rainfall generator of likely scenarios. The predicted long term root zone soil moisture status at finer scale can help in developing efficient agricultural water management schemes to increase crop production, which lead to enhance the water use efficiency.

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

PubMed

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

2018-01-01

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

Integrating Multi-Sensor Remote Sensing and In-situ Measurements for Africa Drought Monitoring and Food Security Assessment

NASA Astrophysics Data System (ADS)

Hao, X.; Qu, J. J.; Motha, R. P.; Stefanski, R.; Malherbe, J.

2014-12-01

Drought is one of the most complicated natural hazards, and causes serious environmental, economic and social consequences. Agricultural production systems, which are highly susceptible to weather and climate extremes, are often the first and most vulnerable sector to be affected by drought events. In Africa, crop yield potential and grazing quality are already nearing their limit of temperature sensitivity, and, rapid population growth and frequent drought episodes pose serious complications for food security. It is critical to promote sustainable agriculture development in Africa under conditions of climate extremes. Soil moisture is one of the most important indicators for agriculture drought, and is a fundamentally critical parameter for decision support in crop management, including planting, water use efficiency and irrigation. While very significant technological advances have been introduced for remote sensing of surface soil moisture from space, in-situ measurements are still critical for calibration and validation of soil moisture estimation algorithms. For operational applications, synergistic collaboration is needed to integrate measurements from different sensors at different spatial and temporal scales. In this presentation, a collaborative effort is demonstrated for drought monitoring in Africa, supported and coordinated by WMO, including surface soil moisture and crop status monitoring. In-situ measurements of soil moisture, precipitation and temperature at selected sites are provided by local partners in Africa. Measurements from the Soil Moisture and Ocean Salinity (SMOS) and the Moderate Resolution Imaging Spectroradiometer (MODIS) are integrated with in-situ observations to derive surface soil moisture at high spatial resolution. Crop status is estimated through temporal analysis of current and historical MODIS measurements. Integrated analysis of soil moisture data and crop status provides both in-depth understanding of drought conditions and potential impacts on crop yield. This information is extremely useful in local decision support for agricultural management.

Integrating Multi-Sensor Remote Sensing and In-situ Measurements for Africa Drought Monitoring and Food Security Assessment

NASA Astrophysics Data System (ADS)

Hao, X.; Qu, J. J.; Motha, R. P.; Stefanski, R.; Malherbe, J.

2015-12-01

Drought is one of the most complicated natural hazards, and causes serious environmental, economic and social consequences. Agricultural production systems, which are highly susceptible to weather and climate extremes, are often the first and most vulnerable sector to be affected by drought events. In Africa, crop yield potential and grazing quality are already nearing their limit of temperature sensitivity, and, rapid population growth and frequent drought episodes pose serious complications for food security. It is critical to promote sustainable agriculture development in Africa under conditions of climate extremes. Soil moisture is one of the most important indicators for agriculture drought, and is a fundamentally critical parameter for decision support in crop management, including planting, water use efficiency and irrigation. While very significant technological advances have been introduced for remote sensing of surface soil moisture from space, in-situ measurements are still critical for calibration and validation of soil moisture estimation algorithms. For operational applications, synergistic collaboration is needed to integrate measurements from different sensors at different spatial and temporal scales. In this presentation, a collaborative effort is demonstrated for drought monitoring in Africa, supported and coordinated by WMO, including surface soil moisture and crop status monitoring. In-situ measurements of soil moisture, precipitation and temperature at selected sites are provided by local partners in Africa. Measurements from the Soil Moisture and Ocean Salinity (SMOS) and the Moderate Resolution Imaging Spectroradiometer (MODIS) are integrated with in-situ observations to derive surface soil moisture at high spatial resolution. Crop status is estimated through temporal analysis of current and historical MODIS measurements. Integrated analysis of soil moisture data and crop status provides both in-depth understanding of drought conditions and potential impacts on crop yield. This information is extremely useful in local decision support for agricultural management.

Mobile Wireless Sensor Networks for Advanced Soil Sensing and Ecosystem Monitoring

NASA Astrophysics Data System (ADS)

Mollenhauer, Hannes; Schima, Robert; Remmler, Paul; Mollenhauer, Olaf; Hutschenreuther, Tino; Toepfer, Hannes; Dietrich, Peter; Bumberger, Jan

2015-04-01

For an adequate characterization of ecosystems it is necessary to detect individual processes with suitable monitoring strategies and methods. Due to the natural complexity of all environmental compartments, single point or temporally and spatially fixed measurements are mostly insufficient for an adequate representation. The application of mobile wireless sensor networks for soil and atmosphere sensing offers significant benefits, due to the simple adjustment of the sensor distribution, the sensor types and the sample rate (e.g. by using optimization approaches or event triggering modes) to the local test conditions. This can be essential for the monitoring of heterogeneous and dynamic environmental systems and processes. One significant advantage in the application of mobile ad-hoc wireless sensor networks is their self-organizing behavior. Thus, the network autonomously initializes and optimizes itself. Due to the localization via satellite a major reduction in installation and operation costs and time is generated. In addition, single point measurements with a sensor are significantly improved by measuring at several optimized points continuously. Since performing analog and digital signal processing and computation in the sensor nodes close to the sensors a significant reduction of the data to be transmitted can be achieved which leads to a better energy management of nodes. Furthermore, the miniaturization of the nodes and energy harvesting are current topics under investigation. First results of field measurements are given to present the potentials and limitations of this application in environmental science. In particular, collected in-situ data with numerous specific soil and atmosphere parameters per sensor node (more than 25) recorded over several days illustrates the high performance of this system for advanced soil sensing and soil-atmosphere interaction monitoring. Moreover, investigations of biotic and abiotic process interactions and optimization of sensor positioning for measuring soil moisture are scopes of this work and initial results of these issues will be presented.

Evaluating ESA CCI soil moisture in East Africa.

PubMed

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

2016-06-01

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

Validating Large Scale Networks Using Temporary Local Scale Networks

USDA-ARS?s Scientific Manuscript database

The USDA NRCS Soil Climate Analysis Network and NOAA Climate Reference Networks are nationwide meteorological and land surface data networks with soil moisture measurements in the top layers of soil. There is considerable interest in scaling these point measurements to larger scales for validating ...

Thermo-responsive gels that absorb moisture and ooze water.

PubMed

Matsumoto, Kazuya; Sakikawa, Nobuki; Miyata, Takashi

2018-06-13

The water content of thermo-responsive hydrogels can be drastically altered by small changes in temperature because their polymer chains change from hydrophilic to hydrophobic above their low critical solution temperature (LCST). In general, such smart hydrogels have been utilized in aqueous solutions or in their wet state, and no attempt has been made to determine the phase-transition behavior of the gels in their dried states. Here we demonstrate an application of the thermo-responsive behavior of an interpenetrating polymer network (IPN) gel comprising thermo-responsive poly(N-isopropylacrylamide) and hydrophilic sodium alginate networks in their dried states. The dried IPN gel absorbs considerable moisture from air at temperatures below its LCST and oozes the absorbed moisture as liquid water above its LCST. These phenomena provide energy exchange systems in which moisture from air can be condensed to liquid water using the controllable hydrophilic/hydrophobic properties of thermo-responsive gels with a small temperature change.

Assessing the risk of foliar injury from ozone on vegetation in parks in the U.S. National Park Service's Vital Signs Network.

PubMed

Kohut, Robert

2007-10-01

The risk of ozone injury to plants was assessed in support of the National Park Service's Vital Signs Monitoring Network program. The assessment examined bioindicator species, evaluated levels of ozone exposure, and investigated soil moisture conditions during periods of exposure for a 5-year period in each park. The assessment assigned each park a risk rating of high, moderate, or low. For the 244 parks for which assessments were conducted, the risk of foliar injury was high in 65 parks, moderate in 46 parks, and low in 131 parks. Among the well-known parks with a high risk of ozone injury are Gettysburg, Valley Forge, Delaware Water Gap, Cape Cod, Fire Island, Antietam, Harpers Ferry, Manassas, Wolf Trap Farm Park, Mammoth Cave, Shiloh, Sleeping Bear Dunes, Great Smoky Mountains, Joshua Tree, Sequoia and Kings Canyon, and Yosemite.

Evaluation of a cosmic-ray neutron sensor network for improved land surface model prediction

NASA Astrophysics Data System (ADS)

Baatz, Roland; Hendricks Franssen, Harrie-Jan; Han, Xujun; Hoar, Tim; Reemt Bogena, Heye; Vereecken, Harry

2017-05-01

In situ soil moisture sensors provide highly accurate but very local soil moisture measurements, while remotely sensed soil moisture is strongly affected by vegetation and surface roughness. In contrast, cosmic-ray neutron sensors (CRNSs) allow highly accurate soil moisture estimation on the field scale which could be valuable to improve land surface model predictions. In this study, the potential of a network of CRNSs installed in the 2354 km2 Rur catchment (Germany) for estimating soil hydraulic parameters and improving soil moisture states was tested. Data measured by the CRNSs were assimilated with the local ensemble transform Kalman filter in the Community Land Model version 4.5. Data of four, eight and nine CRNSs were assimilated for the years 2011 and 2012 (with and without soil hydraulic parameter estimation), followed by a verification year 2013 without data assimilation. This was done using (i) a regional high-resolution soil map, (ii) the FAO soil map and (iii) an erroneous, biased soil map as input information for the simulations. For the regional soil map, soil moisture characterization was only improved in the assimilation period but not in the verification period. For the FAO soil map and the biased soil map, soil moisture predictions improved strongly to a root mean square error of 0.03 cm3 cm-3 for the assimilation period and 0.05 cm3 cm-3 for the evaluation period. Improvements were limited by the measurement error of CRNSs (0.03 cm3 cm-3). The positive results obtained with data assimilation of nine CRNSs were confirmed by the jackknife experiments with four and eight CRNSs used for assimilation. The results demonstrate that assimilated data of a CRNS network can improve the characterization of soil moisture content on the catchment scale by updating spatially distributed soil hydraulic parameters of a land surface model.

National Snow and Ice Data Center |

Science.gov Websites

Temperature Glaciers Ice Sheets Permafrost Sea Ice Soil Moisture Snow ...search for more Scientific Data Web pages Data Sets Drought on the range Drought on the range Using satellite soil moisture data as a tool for drought monitoring. Read more ... SMAP Soil Moisture Active Passive Data (SMAP) NASA SMAP data

Integrated Interpretation of Geophysical, Geotechnical, and Environmental Monitoring Data to Define Precursors for Landslide Activation

NASA Astrophysics Data System (ADS)

Uhlemann, S.; Chambers, J.; Merritt, A.; Wilkinson, P.; Meldrum, P.; Gunn, D.; Maurer, H.; Dixon, N.

2014-12-01

To develop a better understanding of the failure mechanisms leading to first time failure or reactivation of landslides, the British Geological Survey is operating an observatory on an active, shallow landslide in North Yorkshire, UK, which is a typical example of slope failure in Lias Group mudrocks. This group and the Whitby Mudstone Formation in particular, show one of the highest landslide densities in the UK. The observatory comprises geophysical (i.e., ERT and self-potential monitoring, P- and S-wave tomography), geotechnical (i.e. acoustic emission and inclinometer), and hydrological and environmental monitoring (i.e. weather station, water level, soil moisture, soil temperature), in addition to movement monitoring using real-time kinematic GPS. In this study we focus on the reactivation of the landslide at the end of 2012, after an exceptionally wet summer. We present an integrated interpretation of the different data streams. Results show that the two lobes (east and west), which form the main focus of the observatory, behave differently. While water levels, and hence pore pressures, in the eastern lobe are characterised by a continuous increase towards activation resulting in significant movement (i.e. metres), water levels in the western lobe are showing frequent drainage events and thus lower pore pressures and a lower level of movement (i.e. tens of centimetres). This is in agreement with data from the geoelectrical monitoring array. During the summer season, resistivities generally increase due to decreasing moisture levels. However, during the summer of 2012 this seasonal pattern was interrupted, with the reactivated lobe displaying strongly decreasing resistivities (i.e. increasing moisture levels). The self-potential and soil moisture data show clear indications of moisture accumulation prior to the reactivation, followed by continuous discharge towards the base of the slope. Using the different data streams, we present 3D volumetric images of gravimetric moisture content (derived from the ERT data) that highlight the reasons for the differential behaviour and indicate precursors for landslide reactivation.

Drought-induced uplift in the western United States as observed by the EarthScope Plate Boundary Observatory GPS network

NASA Astrophysics Data System (ADS)

Borsa, A. A.; Agnew, D. C.; Cayan, D. R.

2014-12-01

The western United States (WUS) has been experiencing severe drought since 2013. The solid earth response to the accompanying loss of surface and near-surface water mass should be a broad region of uplift. We use seasonally-adjusted time series from continuously operating GPS stations in the EarthScope Plate Boundary Observatory and several smaller networks to measure this uplift, which reaches 15 mm in the California Coastal Ranges and Sierra Nevada and has a median value of 4 mm over the entire WUS. The pattern of mass loss due to the drought, which we recover from an inversion of uplift observations, ranges up to 50 cm of water equivalent and is consistent with observed decreases in precipitation and streamflow. We estimate the total deficit to be 240 Gt, equivalent to a uniform 10 cm layer of water over the entire region, or the magnitude of the current annual mass loss from the Greenland Ice Sheet. In the WUS, interannual changes in crustal loading are driven by changes in cool-season precipitation, which cause variations in surface water, snowpack, soil moisture, and groundwater. The results here demonstrate that the existing network of continuous GPS stations can be used to recover loading changes due to both wet and dry climate patterns. This suggests a new role for GPS networks such as that of the Plate Boundary Observatory. The exceptional stability of the GPS monumentation means that this network is also capable of monitoring the long-term effects of regional climate change. Surface displacement observations from GPS have the potential to expand the capabilities of the current hydrological observing network for monitoring current and future hydrological changes, with obvious social and economic benefits.

Assessing the utility of meteorological drought indices in monitoring summer drought based on soil moisture in Chongqing, China

NASA Astrophysics Data System (ADS)

Chen, Hui; Wu, Wei; Liu, Hong-Bin

2018-04-01

Numerous drought indices have been developed to analyze and monitor drought condition, but they are region specific and limited by various climatic conditions. In southwest China, summer drought mainly occurs from June to September, causing destructive and profound impact on agriculture, society, and ecosystems. The current study assesses the availability of meteorological drought indices in monitoring summer drought in this area at 5-day scale. The drought indices include the relative moisture index ( M), the standardized precipitation index (SPI), the standardized precipitation evapotranspiration index (SPEI), the composite index of meteorological drought (CIspi), and the improved composite index of meteorological drought (CIwap). Long-term daily precipitation and temperature from 1970 to 2014 are used to calculate 30-day M ( M 30), SPI (SPI30), SPEI (SPEI30), 90-day SPEI (SPEI90), CIspi, and CIwap. The 5-day soil moisture observations from 2010 to 2013 are applied to assess the performance of these drought indices. Correlation analysis, overall accuracy, and kappa coefficient are utilized to investigate the relationships between soil moisture and drought indices. Correlation analysis indicates that soil moisture is well correlated with CIwap, SPEI30, M 30, SPI30, and CIspi except SPEI90. Moreover, drought classifications identified by M 30 are in agreement with that of the observed soil moisture. The results show that M 30 based on precipitation and potential evapotranspiration is an appropriate indicator for monitoring drought condition at a finer scale in the study area. According to M 30, summer drought during 1970-2014 happened in each year and showed a slightly upward tendency in recent years.

Development of Innovative Technology to Provide Low-Cost Surface Atmospheric Observations in Data Sparse Regions

NASA Astrophysics Data System (ADS)

Kucera, Paul; Steinson, Martin

2017-04-01

Accurate and reliable real-time monitoring and dissemination of observations of surface weather conditions is critical for a variety of societal applications. Applications that provide local and regional information about temperature, precipitation, moisture, and winds, for example, are important for agriculture, water resource monitoring, health, and monitoring of hazard weather conditions. In many regions of the World, surface weather stations are sparsely located and/or of poor quality. Existing stations have often been sited incorrectly, not well-maintained, and have limited communications established at the site for real-time monitoring. The University Corporation for Atmospheric Research (UCAR)/National Center for Atmospheric Research (NCAR), with support from USAID, has started an initiative to develop and deploy low-cost weather instrumentation in sparsely observed regions of the world. The project is focused on improving weather observations for environmental monitoring and early warning alert systems on a regional to global scale. Instrumentation that has been developed use innovative new technologies such as 3D printers, Raspberry Pi computing systems, and wireless communications. The goal of the project is to make the weather station designs, software, and processing tools an open community resource. The weather stations can be built locally by agencies, through educational institutions, and residential communities as a citizen effort to augment existing networks to improve detection of natural hazards for disaster risk reduction. The presentation will provide an overview of the open source weather station technology and evaluation of sensor observations for the initial networks that have been deployed in Africa.

Developing a Soil Moisture Index for California Grasslands from Airborne Hyperspectral Imagery

NASA Astrophysics Data System (ADS)

Flamme, H. E.; Roberts, D. A.; Miller, D. L.

2016-12-01

Soil moisture is a key environmental factor controlling vegetation diversity and productivity, evaporation, transpiration, and rainfall runoff. Despite the contribution of soil moisture to ecological productivity, the hydrologic cycle, and erosion, it is currently not being monitored as accurately or as frequently as other environmental factors. Traditional soil moisture monitoring techniques rely on in situ measurements, which become costly when evaluating areas of unevenly distributed soil characteristics and varying topography. Alternatively, satellite remote sensing, such as passive microwave from SMAP, can provide soil moisture but only at very coarse spatial resolutions. Imagery from the Airborne Visible / Infrared Imaging Spectrometer (AVIRIS) has the potential to allow better spatial and temporal monitoring of soil moisture. This study established a relationship between plant available water and hyperspectral reflectance via linear regressions of data from 2013-2015 for two grassland field sites: 1) near Santa Barbara, California, at Coal Oil Point Reserve (COPR) and 2) Airstrip station (AIRS) at UC Santa Barbara's Sedgwick Reserve near Santa Ynez, California. Volumetric soil moisture measurements at 10 cm and 20 cm depths were provided by meteorological stations situated in COPR and AIRS while reflectance data were extracted from AVIRIS. We found strong correlations between plant available water and bands centered at wavelengths 704 nm and 831 nm, which we used to create Hyperspectral Soil Moisture Index (HSMI): 0.38((ρ831-ρ704)/(ρ831+ρ704))-0.02. HSMI demonstrated a coefficient of determination (R2) of 0.71 for linear regressions of reflectance versus plant available water with a lag time of 28 days. We applied HSMI to the AIRS and COPR grasslands for 2011 AVIRIS scenes. Plant available water values predicted by HSMI were 0.039 higher at AIRS and 0.048 higher at COPR than the field measurements at the sites. Differences in grass species, soil composition, and climate between COPR and AIRS likely contributed to the errors in the soil moisture predicted by HSMI.

Challenges in Ecohydrological Monitoring at Soil-Vegetation Interfaces: Exploiting the Potential for Fibre Optic Technologies

NASA Astrophysics Data System (ADS)

Chalari, A.; Ciocca, F.; Krause, S.; Hannah, D. M.; Blaen, P.; Coleman, T. I.; Mondanos, M.

2015-12-01

The Birmingham Institute of Forestry Research (BIFoR) is using Free-Air Carbon Enrichment (FACE) experiments to quantify the long-term impact and resilience of forests into rising atmospheric CO2 concentrations. The FACE campaign critically relies on a successful monitoring and understanding of the large variety of ecohydrological processes occurring across many interfaces, from deep soil to above the tree canopy. At the land-atmosphere interface, soil moisture and temperature are key variables to determine the heat and water exchanges, crucial to the vegetation dynamics as well as to groundwater recharge. Traditional solutions for monitoring soil moisture and temperature such as remote techniques and point sensors show limitations in fast acquisition rates and spatial coverage, respectively. Hence, spatial patterns and temporal dynamics of heat and water fluxes at this interface can only be monitored to a certain degree, limiting deeper knowledge in dynamically evolving systems (e.g. in impact of growing vegetation). Fibre optics Distributed Temperature Sensors (DTS) can measure soil temperatures at high spatiotemporal resolutions and accuracy, along kilometers of optical cable buried in the soil. Heat pulse methods applied to electrical elements embedded in the optical cable can be used to obtain the soil moisture. In July 2015 a monitoring system based on DTS has been installed in a recently forested hillslope at BIFoR in order to quantify high-resolution spatial patterns and high-frequency temporal dynamics of soil heat fluxes and soil moisture conditions. Therefore, 1500m of optical cables have been carefully deployed in three overlapped loops at 0.05m, 0.25m and 0.4m from the soil surface and an electrical system to send heat pulses along the optical cable has been developed. This paper discussed both, installation and design details along with first results of the soil moisture and temperature monitoring carried out since July 2015. Moreover, interpretations of the collected data to investigate the impact on soil moisture dynamics of i) forest evolution (long timescale), (ii) seasonality and, (iii) high-frequency forcing, are discussed.

Estimating vegetation dryness to optimize fire risk assessment with spot vegetation satellite data in savanna ecosystems

NASA Astrophysics Data System (ADS)

Verbesselt, J.; Somers, B.; Lhermitte, S.; van Aardt, J.; Jonckheere, I.; Coppin, P.

2005-10-01

The lack of information on vegetation dryness prior to the use of fire as a management tool often leads to a significant deterioration of the savanna ecosystem. This paper therefore evaluated the capacity of SPOT VEGETATION time-series to monitor the vegetation dryness (i.e., vegetation moisture content per vegetation amount) in order to optimize fire risk assessment in the savanna ecosystem of Kruger National Park in South Africa. The integrated Relative Vegetation Index approach (iRVI) to quantify the amount of herbaceous biomass at the end of the rain season and the Accumulated Relative Normalized Difference vegetation index decrement (ARND) related to vegetation moisture content were selected. The iRVI and ARND related to vegetation amount and moisture content, respectively, were combined in order to monitor vegetation dryness and optimize fire risk assessment in the savanna ecosystems. In situ fire activity data was used to evaluate the significance of the iRVI and ARND to monitor vegetation dryness for fire risk assessment. Results from the binary logistic regression analysis confirmed that the assessment of fire risk was optimized by integration of both the vegetation quantity (iRVI) and vegetation moisture content (ARND) as statistically significant explanatory variables. Consequently, the integrated use of both iRVI and ARND to monitor vegetation dryness provides a more suitable tool for fire management and suppression compared to other traditional satellite-based fire risk assessment methods, only related to vegetation moisture content.

Exploring applications of GPR methodology and uses in determining floodplain function of restored streams in the Gulf Coastal Plain, Alabama

NASA Astrophysics Data System (ADS)

Eckes, S. W.; Shepherd, S. L.

2017-12-01

Accurately characterizing subsurface structure and function of remediated floodplains is indispensable in understanding the success of stream restoration projects. Although many of these projects are designed to address increased storm water runoff due to urbanization, long term monitoring and assessment are often limited in scope and methodology. Common monitoring practices include geomorphic surveys, stream discharge, and suspended sediment loads. These data are comprehensive for stream monitoring but they do not address floodplain function in terms of infiltration and through flow. Developing noninvasive methods for monitoring floodplain moisture transfer and distribution will aid in current and future stream restoration endeavors. Ground penetrating radar (GPR) has been successfully used in other physiographic regions for noninvasive and continuous monitoring of (1) natural geomorphic environments including subsurface structure and landform change and (2) soil and turf management to monitor subsurface moisture content. We are testing the viability of these existing methods to expand upon the broad capabilities of GPR. Determining suitability will be done in three parts using GPR to (1) find known buried objects of typical materials used in remediation at measured depths, (2) understand GPR functionality in varying soil moisture content thresholds on turf plots, and (3) model reference, remediated, and impacted floodplains in a case study in the D'Olive Creek watershed located in Baldwin County, Alabama. We hypothesize that these methods will allow us to characterize moisture transfer from precipitation and runoff to the floodplain which is a direct function of floodplain health. The need for a methodology to monitor floodplains is widespread and with increased resolution and mobility, expanding GPR applications may help streamline remediation and monitoring practices.

Technical Note: Novel method for water vapour monitoring using wireless communication networks measurements

NASA Astrophysics Data System (ADS)

David, N.; Alpert, P.; Messer, H.

2009-04-01

We propose a new technique that overcomes the obstacles of the existing methods for monitoring near-surface water vapour, by estimating humidity from data collected through existing wireless communication networks. Weather conditions and atmospheric phenomena affect the electromagnetic channel, causing attenuations to the radio signals. Thus, wireless communication networks are in effect built-in environmental monitoring facilities. The wireless microwave links, used in these networks, are widely deployed by cellular providers for backhaul communication between base stations, a few tens of meters above ground level. As a result, if all available measurements are used, the proposed method can provide moisture observations with high spatial resolution and potentially high temporal resolution. Further, the implementation cost is minimal, since the data used are already collected and saved by the cellular operators. In addition - many of these links are installed in areas where access is difficult such as orographic terrain and complex topography. As such, our method enables measurements in places that have been hard to measure in the past, or have never been measured before. The technique is restricted to weather conditions which exclude rain, fog or clouds along the propagation path. Strong winds that may cause movement of the link transmitter or receiver (or both) may also interfere with the ability to conduct accurate measurements. We present results from real-data measurements taken from two microwave links used in a backhaul cellular network that show convincing correlation to surface station humidity measurements. The measurements were taken daily in two sites, one in northern Israel (28 measurements), the other in central Israel (29 measurements). The correlation between the microwave link measurements and the humidity gauges were 0.9 and 0.82 for the north and central sites, respectively. The Root Mean Square Differences (RMSD) were 1.8 g/m3 and 3.4 g/m3 for the northern and central site measurements, respectively.

Capturing 3D resistivity of semi-arid karstic subsurface in varying moisture conditions using a wireless sensor network

NASA Astrophysics Data System (ADS)

Barnhart, K.; Oden, C. P.

2012-12-01

The dissolution of soluble bedrock results in surface and subterranean karst channels, which comprise 7-10% of the dry earth's surface. Karst serves as a preferential conduit to focus surface and subsurface water but it is difficult to exploit as a water resource or protect from pollution because of irregular structure and nonlinear hydrodynamic behavior. Geophysical characterization of karst commonly employs resistivity and seismic methods, but difficulties arise due to low resistivity contrast in arid environments and insufficient resolution of complex heterogeneous structures. To help reduce these difficulties, we employ a state-of-the-art wireless geophysical sensor array, which combines low-power radio telemetry and solar energy harvesting to enable long-term in-situ monitoring. The wireless aspect removes topological constraints common with standard wired resistivity equipment, which facilitates better coverage and/or sensor density to help improve aspect ratio and resolution. Continuous in-situ deployment allows data to be recorded according to nature's time scale; measurements are made during infrequent precipitation events which can increase resistivity contrast. The array is coordinated by a smart wireless bridge that continuously monitors local soil moisture content to detect when precipitation occurs, schedules resistivity surveys, and periodically relays data to the cloud via 3G cellular service. Traditional 2/3D gravity and seismic reflection surveys have also been conducted to clarify and corroborate results.

Neural Network-Based Retrieval of Surface and Root Zone Soil Moisture using Multi-Frequency Remotely-Sensed Observations

NASA Astrophysics Data System (ADS)

Hamed Alemohammad, Seyed; Kolassa, Jana; Prigent, Catherine; Aires, Filipe; Gentine, Pierre

2017-04-01

Knowledge of root zone soil moisture is essential in studying plant's response to different stress conditions since plant photosynthetic activity and transpiration rate are constrained by the water available through their roots. Current global root zone soil moisture estimates are based on either outputs from physical models constrained by observations, or assimilation of remotely-sensed microwave-based surface soil moisture estimates with physical model outputs. However, quality of these estimates are limited by the accuracy of the model representations of physical processes (such as radiative transfer, infiltration, percolation, and evapotranspiration) as well as errors in the estimates of the surface parameters. Additionally, statistical approaches provide an alternative efficient platform to develop root zone soil moisture retrieval algorithms from remotely-sensed observations. In this study, we present a new neural network based retrieval algorithm to estimate surface and root zone soil moisture from passive microwave observations of SMAP satellite (L-band) and AMSR2 instrument (X-band). SMAP early morning observations are ideal for surface soil moisture retrieval. AMSR2 mid-night observations are used here as an indicator of plant hydraulic properties that are related to root zone soil moisture. The combined observations from SMAP and AMSR2 together with other ancillary observations including the Solar-Induced Fluorescence (SIF) estimates from GOME-2 instrument provide necessary information to estimate surface and root zone soil moisture. The algorithm is applied to observations from the first 18 months of SMAP mission and retrievals are validated against in-situ observations and other global datasets.

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

USDA-ARS?s Scientific Manuscript database

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

Using machine learning to produce near surface soil moisture estimates from deeper in situ records at U.S. Climate Reference Network (USCRN) locations: Analysis and applications to AMSR-E satellite validation

USDA-ARS?s Scientific Manuscript database

Surface soil moisture is critical parameter for understanding the energy flux at the land atmosphere boundary. Weather modeling, climate prediction, and remote sensing validation are some of the applications for surface soil moisture information. The most common in situ measurement for these purpo...

Representativeness of the ground observational sites and up-scaling of the point soil moisture measurements

NASA Astrophysics Data System (ADS)

Chen, Jinlei; Wen, Jun; Tian, Hui

2016-02-01

Soil moisture plays an increasingly important role in the cycle of energy-water exchange, climate change, and hydrologic processes. It is usually measured at a point site, but regional soil moisture is essential for validating remote sensing products and numerical modeling results. In the study reported in this paper, the minimal number of required sites (NRS) for establishing a research observational network and the representative single sites for regional soil moisture estimation are discussed using the soil moisture data derived from the ;Maqu soil moisture observational network; (101°40‧-102°40‧E, 33°30‧-35°45‧N), which is supported by Chinese Academy of Science. Furthermore, the best up-scaling method suitable for this network has been studied by evaluating four commonly used up-scaling methods. The results showed that (1) Under a given accuracy requirement R ⩾ 0.99, RMSD ⩽ 0.02 m3/m3, NRS at both 5 and 10 cm depth is 10. (2) Representativeness of the sites has been validated by time stability analysis (TSA), time sliding correlation analysis (TSCA) and optimal combination of sites (OCS). NST01 is the most representative site at 5 cm depth for the first two methods; NST07 and NST02 are the most representative sites at 10 cm depth. The optimum combination sites at 5 cm depth are NST01, NST02, and NST07. NST05, NST08, and NST13 are the best group at 10 cm depth. (3) Linear fitting, compared with other three methods, is the best up-scaling method for all types of representative sites obtained above, and linear regression equations between a single site and regional soil moisture are established hereafter. ;Single site; obtained by OCS has the greatest up-scaling effect, and TSCA takes the second place. (4) Linear fitting equations show good practicability in estimating the variation of regional soil moisture from July 3, 2013 to July 3, 2014, when a large number of observed soil moisture data are lost.

A comparison of soil moisture sensors for space flight applications

NASA Technical Reports Server (NTRS)

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

2005-01-01

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.

Introduction of Drought Monitoring and Forecasting System based on Real-time Water Information Using ICT

NASA Astrophysics Data System (ADS)

Lee, Y., II; Kim, H. S.; Chun, G.

2016-12-01

There were severe damages such as restriction on water supply caused by continuous drought from 2014 to 2015 in South Korea. Through this drought event, government of South Korea decided to establish National Drought Information Analysis Center in K-water(Korea Water Resources Corporation) and introduce a national drought monitoring and early warning system to mitigate those damages. Drought index such as SPI(Standard Precipitation Index), PDSI(Palmer Drought Severity Index) and SMI(Soil Moisture Index) etc. have been developed and are widely used to provide drought information in many countries. However, drought indexes are not appropriate for drought monitoring and early warning in civilized countries with high population density such as South Korea because it could not consider complicated water supply network. For the national drought monitoring and forecasting of South Korea, `Drought Information Analysis System' (D.I.A.S) which is based on the real time data(storage, flowrate, waterlevel etc.) was developed. Based on its advanced methodology, `DIAS' is changing the paradigm of drought monitoring and early warning systems. Because `D.I.A.S' contains the information of water supply network from water sources to the people across the nation and provides drought information considering the real-time hydrological conditions of each and every water source. For instance, in case the water level of a specific dam declines to predetermined level of caution, `D.I.A.S' will notify people who uses the dam as a source of residential or industrial water. It is expected to provide credible drought monitoring and forecasting information with a strong relationship between drought information and the feelings of people rely on water users by `D.I.A.S'.

Design of autonomous sensor nodes for remote soil monitoring in tropical banana plantation

NASA Astrophysics Data System (ADS)

Tiausas, Francis Jerome G.; Co, Jerelyn; Macalinao, Marc Joseph M.; Guico, Maria Leonora; Monje, Jose Claro; Oppus, Carlos

2017-09-01

Determining the effect of Fusarium oxysporum f. sp. cubense Tropical Race 4 on various soil parameters is essential in modeling and predicting its occurrence in banana plantations. One way to fulfill this is through a sensor network that will continuously and automatically monitor environmental conditions at suspect locations for an extended period of time. A wireless sensor network was developed specifically for this purpose. This sensor network is capable of measuring soil acidity, moisture, temperature, and conductivity. The designed prototype made use of off-the-shelf Parrot Flower Power soil sensor, pH sensor, Bluno Beetle, battery, and 3D-printed materials, catering specifically to the conditions of tropical banana plantations with consideration for sensor node size, communication, and power. Sensor nodes were tested on both simulated tropical environments and on an actual banana plantation in San Jose, General Santos City, Philippines. Challenges were resolved through iterative design and development of prototypes. Several tests including temperature and weather resilience, and structural stress tests were done to validate the design. Findings showed that the WSN nodes developed for this purpose are resilient to high tropical temperatures for up to 12 hours of continuous exposure, are able to withstand compressive forces of up to 8880.6 N, and can reliably collect data automatically from the area 47.96% of the time at an hourly frequency under actual field conditions.

Spatial Variability of Soil-Water Storage in the Southern Sierra Critical Zone Observatory: Measurement and Prediction

NASA Astrophysics Data System (ADS)

Oroza, C.; Bales, R. C.; Zheng, Z.; Glaser, S. D.

2017-12-01

Predicting the spatial distribution of soil moisture in mountain environments is confounded by multiple factors, including complex topography, spatial variably of soil texture, sub-surface flow paths, and snow-soil interactions. While remote-sensing tools such as passive-microwave monitoring can measure spatial variability of soil moisture, they only capture near-surface soil layers. Large-scale sensor networks are increasingly providing soil-moisture measurements at high temporal resolution across a broader range of depths than are accessible from remote sensing. It may be possible to combine these in-situ measurements with high-resolution LIDAR topography and canopy cover to estimate the spatial distribution of soil moisture at high spatial resolution at multiple depths. We study the feasibility of this approach using six years (2009-2014) of daily volumetric water content measurements at 10-, 30-, and 60-cm depths from the Southern Sierra Critical Zone Observatory. A non-parametric, multivariate regression algorithm, Random Forest, was used to predict the spatial distribution of depth-integrated soil-water storage, based on the in-situ measurements and a combination of node attributes (topographic wetness, northness, elevation, soil texture, and location with respect to canopy cover). We observe predictable patterns of predictor accuracy and independent variable ranking during the six-year study period. Predictor accuracy is highest during the snow-cover and early recession periods but declines during the dry period. Soil texture has consistently high feature importance. Other landscape attributes exhibit seasonal trends: northness peaks during the wet-up period, and elevation and topographic-wetness index peak during the recession and dry period, respectively.

Capacitive Soil Moisture Sensor for Plant Watering

NASA Astrophysics Data System (ADS)

Maier, Thomas; Kamm, Lukas

2016-04-01

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

Long-term soil moisture patterns in a northern Minnesota forest

Treesearch

Salli F. Dymond; Randall K. Kolka; Paul V. Bolstad; Stephen D. Sebestyen

2014-01-01

Forest hydrological and biogeochemical processes are highly dependent on soil water. At the Marcell Experimental Forest, seasonal patterns of soil moisture have been monitored at three forested locations since 1966. This unique, long-term data set was used to analyze seasonal trends in soil moisture as well as the influence of time-lagged precipitation and modified...

COSMOS: COsmic-ray Soil Moisture Observing System planned for the United States

NASA Astrophysics Data System (ADS)

Zweck, C.; Zreda, M.; Shuttleworth, J.; Zeng, X.

2008-12-01

Because soil water exerts a critical control on weather, climate, ecosystem, and water cycle, understanding soil moisture changes in time and space is crucial for many fields within natural sciences. A serious handicap in soil moisture measurements is the mismatch between limited point measurements using contact methods and remote sensing estimates over large areas. We present a novel method to measure soil moisture non- invasively at an intermediate spatial scale that will alleviate this problem. The method takes advantage of the dependence of cosmic-ray neutron intensity on the hydrogen content of soils (Zreda et al., Geophysical Research Letters, accepted). Low-energy cosmic-ray neutrons are produced and moderated in the soil, transported from the soil into the atmosphere where they are measured with a cosmic-ray neutron probe to provide integrated soil moisture content over a footprint of several hundred meters and a depth of a few decimeters. The method and the instrument are intended for deployment in the continental-scale COSMOS network that is designed to cover the contiguous region of the USA. Fully deployed, the COSMOS network will consist of up to 500 probes, and will provide continuous soil moisture content (together with atmospheric pressure, temperature and relative humidity) measured and reported hourly. These data will be used for initialization and assimilation of soil moisture conditions in weather and short-term (seasonal) climate forecasting, and for other land-surface applications.

A High Space-Time Resolution Dataset Linking Meteorological Forcing and Hydro-Sedimentary Response in a Mesoscale Mediterranean Catchment (Auzon) of the Ardèche Region, France

NASA Astrophysics Data System (ADS)

Nord, G.; Braud, I.; Boudevillain, B.; Gérard, S.; Molinié, G.; Vandervaere, J. P.; Huza, J.; Le Coz, J.; Dramais, G.; Legout, C.; Berne, A.; Grazioli, J.; Raupach, T.; Van Baelen, J.; Wijbrans, A.; Delrieu, G.; Andrieu, J.; Caliano, M.; Aubert, C.; Teuling, R.; Le Boursicaud, R.; Branger, F.; Vincendon, B.; Horner, I.

2014-12-01

A comprehensive hydrometeorological dataset is presented spanning the period 1 Jan 2011-31 Dec 2014 to improve the understanding and simulation of the hydrological processes leading to flash floods in a mesoscale catchment (Auzon, 116 km2) of the Mediterranean region. The specificity of the dataset is its high space-time resolution, especially concerning rainfall and the hydrological response which is particularly adapted to the highly spatially variable rainfall events that may occur in this region. This type of dataset is rare in scientific literature because of the quantity and type of sensors for meteorology and surface hydrology. Rainfall data include continuous precipitation measured by rain-gages (5 min time step for the research network of 21 rain-gages and 1h time step for the operational network of 9 rain-gages), S-band Doppler dual-polarization radar (1 km2, 5 min resolution), and disdrometers (11 sensors working at 1 min time step). During the special observation period (SOP-1) and enhanced observation period (Sep-Dec 2012, Sep-Dec 2013) of the HyMeX (Hydrological Cycle in the Mediterranean Experiment) project, two X-band radars provided precipitation measurements at very fine spatial and temporal scales (1 ha, 5 min). Meteorological data are taken from the operational surface weather observation stations of Meteo France at the hourly time resolution (6 stations in the region of interest). The monitoring of surface hydrology and suspended sediment is multi-scale and based on nested catchments. Three hydrometric stations measure water discharge and additional physico-chemical variables at a 2-10 min time resolution. Two experimental plots monitor overland flow and erosion at 1 min time resolution on a hillslope with vineyard. A network of 11 gauges continuously measures water level and temperature in headwater subcatchments at a time resolution of 2-5 min. A network of soil moisture sensors enable the continuous measurement of soil volumetric water content at 20 min time resolution at 9 sites. Additionally, opportunistic observations (soil moisture measurements and stream gauging) were performed during floods between 2012 and 2014. The data are appropriate for understanding rainfall variability, improving areal rainfall estimations and progress in distributed hydrological modelling.

A High Space-Time Resolution Dataset Linking Meteorological Forcing and Hydro-Sedimentary Response in a Mesoscale Mediterranean Catchment (Auzon) of the Ardèche Region, France

NASA Astrophysics Data System (ADS)

Nord, G.; Braud, I.; Boudevillain, B.; Gérard, S.; Molinié, G.; Vandervaere, J. P.; Huza, J.; Le Coz, J.; Dramais, G.; Legout, C.; Berne, A.; Grazioli, J.; Raupach, T.; Van Baelen, J.; Wijbrans, A.; Delrieu, G.; Andrieu, J.; Caliano, M.; Aubert, C.; Teuling, R.; Le Boursicaud, R.; Branger, F.; Vincendon, B.; Horner, I.

2015-12-01

A comprehensive hydrometeorological dataset is presented spanning the period 1 Jan 2011-31 Dec 2014 to improve the understanding and simulation of the hydrological processes leading to flash floods in a mesoscale catchment (Auzon, 116 km2) of the Mediterranean region. The specificity of the dataset is its high space-time resolution, especially concerning rainfall and the hydrological response which is particularly adapted to the highly spatially variable rainfall events that may occur in this region. This type of dataset is rare in scientific literature because of the quantity and type of sensors for meteorology and surface hydrology. Rainfall data include continuous precipitation measured by rain-gages (5 min time step for the research network of 21 rain-gages and 1h time step for the operational network of 9 rain-gages), S-band Doppler dual-polarization radar (1 km2, 5 min resolution), and disdrometers (11 sensors working at 1 min time step). During the special observation period (SOP-1) and enhanced observation period (Sep-Dec 2012, Sep-Dec 2013) of the HyMeX (Hydrological Cycle in the Mediterranean Experiment) project, two X-band radars provided precipitation measurements at very fine spatial and temporal scales (1 ha, 5 min). Meteorological data are taken from the operational surface weather observation stations of Meteo France at the hourly time resolution (6 stations in the region of interest). The monitoring of surface hydrology and suspended sediment is multi-scale and based on nested catchments. Three hydrometric stations measure water discharge and additional physico-chemical variables at a 2-10 min time resolution. Two experimental plots monitor overland flow and erosion at 1 min time resolution on a hillslope with vineyard. A network of 11 gauges continuously measures water level and temperature in headwater subcatchments at a time resolution of 2-5 min. A network of soil moisture sensors enable the continuous measurement of soil volumetric water content at 20 min time resolution at 9 sites. Additionally, opportunistic observations (soil moisture measurements and stream gauging) were performed during floods between 2012 and 2014. The data are appropriate for understanding rainfall variability, improving areal rainfall estimations and progress in distributed hydrological modelling.

Inversion of parameters for semiarid regions by a neural network

NASA Technical Reports Server (NTRS)

Zurk, Lisa M.; Davis, Daniel; Njoku, Eni G.; Tsang, Leung; Hwang, Jenq-Neng

1992-01-01

Microwave brightness temperatures obtained from a passive radiative transfer model are inverted through use of a neural network. The model is applicable to semiarid regions and produces dual-polarized brightness temperatures for 6.6-, 10.7-, and 37-GHz frequencies. A range of temperatures is generated by varying three geophysical parameters over acceptable ranges: soil moisture, vegetation moisture, and soil temperature. A multilayered perceptron (MLP) neural network is trained with a subset of the generated temperatures, and the remaining temperatures are inverted using a backpropagation method. Several synthetic terrains are devised and inverted by the network under local constraints. All the inversions show good agreement with the original geophysical parameters, falling within 5 percent of the actual value of the parameter range.

Evaluating ESA CCI Soil Moisture in East Africa

NASA Technical Reports Server (NTRS)

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

2016-01-01

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

Summary: Remote sensing soil moisture research

NASA Technical Reports Server (NTRS)

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

1970-01-01

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

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

NASA Technical Reports Server (NTRS)

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

2010-01-01

Soil moisture is a fundamental data source used by the United States Department of Agriculture (USDA) International Production Assessment Division (IPAD) to monitor crop growth stage and condition and subsequently, globally forecast agricultural yields. Currently, the USDA IPAD estimates surface and root-zone soil moisture using a two-layer modified Palmer soil moisture model forced by global precipitation and temperature measurements. However, this approach suffers from well-known errors arising from uncertainty in model forcing data and highly simplified model physics. Here we attempt to correct for these errors by designing and applying an Ensemble Kalman filter (EnKF) data assimilation system to integrate surface soil moisture retrievals from the NASA Advanced Microwave Scanning Radiometer (AMSR-E) into the USDA modified Palmer soil moisture model. An assessment of soil moisture analysis products produced from this assimilation has been completed for a five-year (2002 to 2007) period over the North American continent between 23degN - 50degN and 128degW - 65degW. In particular, a data denial experimental approach is utilized to isolate the added utility of integrating remotely-sensed soil moisture by comparing EnKF soil moisture results obtained using (relatively) low-quality precipitation products obtained from real-time satellite imagery to baseline Palmer model runs forced with higher quality rainfall. An analysis of root-zone anomalies for each model simulation suggests that the assimilation of AMSR-E surface soil moisture retrievals can add significant value to USDA root-zone predictions derived from real-time satellite precipitation products.

Relative permeability of fractured wellbore cement: an experimental investigation using electrical resistivity monitoring for moisture content

NASA Astrophysics Data System (ADS)

Um, W.; Rod, K. A.; Strickland, C. E.

2016-12-01

Permeability is a critical parameter needed to understand flow in subsurface environments; it is particularly important in deep subsurface reservoirs where multiphase fluid flow is common, such as carbon sequestration and geothermal reservoirs. Cement is used in the annulus of wellbores due to its low permeable properties to seal aquifers, reducing leaks to adjacent strata. Extreme subsurface environments of CO2 storage and geothermal production conditions will eventually reduce the cement integrity, propagating fracture networks and increasing the permeability for air and/or water. To date, there have been no reproducible experimental investigations of relative permeability in fractured wellbore cement published. To address this gap, we conducted a series of experiments using fractured Portland cement monoliths with increasing fracture networks. The monolith cylinder sides were jacketed with heavy-duty moisture-seal heat-shrink tubing, then fractured using shear force applied via a hydraulic press. Fractures were generated with different severity for each of three monoliths. Stainless steel endcaps were fixed to the monoliths using the same shrink-wrapped jacket. Fracture characteristics were determined using X-ray microtomography and image analysis. Flow controllers were used to control flow of water and air to supply continuous water or water plus air, both of which were delivered through the influent end cap. Effluent air flow was monitored using a flow meter, and water flow was measured gravimetrically. To monitor the effective saturation of the fractures, a RCON2 concrete bulk electrical resistivity test device was attached across both endcaps and a 0.1M NaNO3 brine was used as the transport fluid to improve resistivity measurements. Water content correlated to resistivity measurements with a r2 > 0.96. Data from the experiments was evaluated using two relative permeability models, the Corey-curve, often used for modeling relative permeability in porous media, and the X-curve, commonly used to depict the relative permeability of fractures. Relative permeability measurements from the cores containing a higher degree of fracturing showed a better fit to X-curve, while data from the minimally fractured cores were better described by fitting to the Corey-curve.

Remote Assessment of Forest Ecosystem Stress (RAFES): Development of a Real Time Decision Support Tool for the Eastern U.S

NASA Astrophysics Data System (ADS)

Clinton, B.; Vose, J.; Novick, K.; Liu, Y.

2011-12-01

Drier and warmer conditions predicted with climate change models are likely to significantly impact forest ecosystems over the next several decades. The U.S. has experienced significant droughts over the past several years that have increased the susceptibility of forests to insect outbreaks, disease, and wildfire. Weather data collected with traditional approaches provide an indirect measure of drought or temperature stress; however, the significance of short-term or prolonged climate-related stress varies considerably across the landscape as topography, elevations, edaphic condition and antecedent conditions vary. This limits the capacity of land managers to anticipate and initiate management activities that could offset the impacts of climate-related forest stress. Decision support tools are needed that allow fine scale monitoring of stress conditions in forest ecosystems in real time to help land managers evaluate response strategies. To assist land managers in managing the impacts of climate change, we are developing a stress monitoring and decision support system across multiple sites in the eastern U.S. that (1) provides remote data capture of environmental parameters that quantify climate-related forest stress, (2) links remotely captured data with physiologically-based indices of tree water stress, and (3) provides a PC-based analytical tool for land managers to monitor and assess the severity of climate-related stress. Currently the network represents southern coastal plain pine plantation, Atlantic coastal flatwoods mixed pine-hardwood, southern piedmont upland mixed pine-hardwood, southern Appalachian dry ridge and mesic riparian, southern Arkansas managed mature pine, and northern Minnesota mature aspen. The strategy for selecting additional sites for the network will be a focus on at-risk ecosystems deemed particularly vulnerable to the affects of predicted climate change such as those in ecotonal transition regions, or those at the fringes of their ranges. The sensor arrays at each site detect water and temperature stress variables and transmit those data to a field office. Sensors include air and soil temperature, relative humidity, fuel moisture and temperature, xylem sap flux density, soil moisture and matric potential, precipitation, and solar radiation. Data are transmitted in real-time to the NOAA Geostationary Operational Environmental Satellite (GOES). A PC-based software program that downloads monitoring data from the GOES satellite, analyzes the data, and provides the land manager with an assessment of climate-related stress conditions and potential forest health threat levels in real time is under development. Data collection began in early 2010 on most sites, and we have at least one year of data from all nine sites within the network. We are currently comparing estimates of stress levels on our sites with estimates of stress from common drought indices. For this presentation, we are comparing and contrasting four sites representing an environmental gradient within the network.

Sensitivity of Land Surface Parameters on Thunderstorm Simulation through HRLDAS-WRF Coupling Mode

NASA Astrophysics Data System (ADS)

Kumar, Dinesh; Kumar, Krishan; Mohanty, U. C.; Kisore Osuri, Krishna

2016-07-01

Land surface characteristics play an important role in large scale, regional and mesoscale atmospheric process. Representation of land surface characteristics can be improved through coupling of mesoscale atmospheric models with land surface models. Mesoscale atmospheric models depend on Land Surface Models (LSM) to provide land surface variables such as fluxes of heat, moisture, and momentum for lower boundary layer evolution. Studies have shown that land surface properties such as soil moisture, soil temperature, soil roughness, vegetation cover, have considerable effect on lower boundary layer. Although, the necessity to initialize soil moisture accurately in NWP models is widely acknowledged, monitoring soil moisture at regional and global scale is a very tough task due to high spatial and temporal variability. As a result, the available observation network is unable to provide the required spatial and temporal data for the most part of the globe. Therefore, model for land surface initializations rely on updated land surface properties from LSM. The solution for NWP land-state initialization can be found by combining data assimilation techniques, satellite-derived soil data, and land surface models. Further, it requires an intermediate step to use observed rainfall, satellite derived surface insolation, and meteorological analyses to run an uncoupled (offline) integration of LSM, so that the evolution of modeled soil moisture can be forced by observed forcing conditions. Therefore, for accurate land-state initialization, high resolution land data assimilation system (HRLDAS) is used to provide the essential land surface parameters. Offline-coupling of HRLDAS-WRF has shown much improved results over Delhi, India for four thunder storm events. The evolution of land surface variables particularly soil moisture, soil temperature and surface fluxes have provided more realistic condition. Results have shown that most of domain part became wetter and warmer after assimilation of soil moisture and soil temperature at the initial condition which helped to improve the exchange fluxes at lower atmospheric level. Mixing ratio were increased along with elevated theta-e at lower level giving a signature of improvement in LDAS experiment leading to a suitable condition for convection. In the analysis, moisture convergence, mixing ratio and vertical velocities have improved significantly in terms of intensity and time lag. Surface variables like soil moisture, soil temperature, sensible heat flux and latent heat flux have progressed in a possible realistic pattern. Above discussion suggests that assimilation of soil moisture and soil temperature improves the overall simulations significantly.

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

USGS Publications Warehouse

Zhang, Li; Ji, Lei; Wylie, Bruce K.

2011-01-01

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.

Modeling seasonal changes in live fuel moisture and equivalent water thickness using a cumulative water balance index

Treesearch

Philip E. Dennison; Dar A. Roberts; Sommer R. Thorgusen; Jon C. Regelbrugge; David Weise; Christopher Lee

2003-01-01

Live fuel moisture, an important determinant of fire danger in Mediterranean ecosystems, exhibits seasonal changes in response to soil water availability. Both drought stress indices based on meteorological data and remote sensing indices based on vegetation water absorption can be used to monitor live fuel moisture. In this study, a cumulative water balance index (...

Field Measurements and Numerical Simulations of Temperature and Moisture in Highway Engineering Using a Frequency Domain Reflectometry Sensor.

PubMed

Yao, Yong-Sheng; Zheng, Jian-Long; Chen, Zeng-Shun; Zhang, Jun-Hui; Li, Yong

2016-06-10

This paper presents a systematic pioneering study on the use of agricultural-purpose frequency domain reflectometry (FDR) sensors to monitor temperature and moisture of a subgrade in highway extension and reconstruction engineering. The principle of agricultural-purpose FDR sensors and the process for embedding this kind of sensors for subgrade engineering purposes are introduced. Based on field measured weather data, a numerical analysis model for temperature and moisture content in the subgrade's soil is built. Comparisons of the temperature and moisture data obtained from numerical simulation and FDR-based measurements are conducted. The results show that: (1) the embedding method and process, data acquisition, and remote transmission presented are reasonable; (2) the temperature and moisture changes are coordinated with the atmospheric environment and they are also in close agreement with numerical calculations; (3) the change laws of both are consistent at positions where the subgrade is compacted uniformly. These results suggest that the data measured by the agricultural-purpose FDR sensors are reliable. The findings of this paper enable a new and effective real-time monitoring method for a subgrade's temperature and moisture changes, and thus broaden the application of agricultural-purpose FDR sensors.

Application of IEM model on soil moisture and surface roughness estimation

NASA Technical Reports Server (NTRS)

Shi, Jiancheng; Wang, J. R.; Oneill, P. E.; Hsu, A. Y.; Engman, E. T.

1995-01-01

Monitoring spatial and temporal changes of soil moisture are of importance to hydrology, meteorology, and agriculture. This paper reports a result on study of using L-band SAR imagery to estimate soil moisture and surface roughness for bare fields. Due to limitations of the Small Perturbation Model, it is difficult to apply this model on estimation of soil moisture and surface roughness directly. In this study, we show a simplified model derived from the Integral Equation Model for estimation of soil moisture and surface roughness. We show a test of this model using JPL L-band AIRSAR data.

Hydrologic response across a snow persistence gradient on the west and east slopes of the Rocky Mountains in Colorado

NASA Astrophysics Data System (ADS)

Richard, G. A.; Hammond, J. C.; Kampf, S. K.; Moore, C. D.; Eurich, A.

2017-12-01

Snowpack trend analyses and modeling studies suggest that lower elevation snowpacks in mountain regions are most sensitive to drought and warming temperatures, however, in Colorado, most snow monitoring occurs in the high elevations where snow lasts throughout the winter and most streamflow monitoring occurs at lower elevations. The lack of combined snow and streamflow monitoring in watersheds along the transition from intermittent to persistent snow creates a gap in our understanding of snowmelt and runoff within the intermittent-persistent snow transition. Expanded hydrologic monitoring that spans the gradient of snow conditions in Colorado can help improve streamflow prediction and inform land and water managers. This study established hydrologic monitoring watersheds in intermittent, transitional, and persistent snow zones on the east slope and west slope of the Rocky Mountains in Colorado, and uses this monitoring network to improve understanding of how snow accumulation and melt affect soil moisture and streamflow generation under different snow conditions. We monitored six small watersheds (three west slope, three east slope) (0.8 to 3.9 km2) that drain intermittent, transitional, and persistent snow zones. At each site, we measured: streamflow, snow depth, soil moisture, precipitation, air temperature, and snow water equivalent (SWE). In our first season of monitoring, the west slope persistent and transitional sites had more mid-winter melt and infiltration, shorter snowpack duration, and lower peak SWE than the east slope sites. Snow cover remained at the east slope persistent site into June, whereas much of the snow at the persistent site on the west slope had already melted by early June. The difference in soil water input likely has consequences for streamflow response that we will continue to examine in future years. At the west slope intermittent site, the stream did not flow during the entire first year of monitoring, while at the east slope intermittent site, the streams flowed intermittently during winter and spring, likely a result of different subsurface geology. With our ongoing watershed monitoring across a broad range of snow conditions in Colorado, we continue to learn about the factors that increase or decrease streamflow in the headwater streams that supply the state's major rivers.

Satellite Gravimetry Applied to Drought Monitoring

NASA Technical Reports Server (NTRS)

Rodell, Matthew

2010-01-01

Near-surface wetness conditions change rapidly with the weather, which limits their usefulness as drought indicators. Deeper stores of water, including root-zone soil wetness and groundwater, portend longer-term weather trends and climate variations, thus they are well suited for quantifying droughts. However, the existing in situ networks for monitoring these variables suffer from significant discontinuities (short records and spatial undersampling), as well as the inherent human and mechanical errors associated with the soil moisture and groundwater observation. Remote sensing is a promising alternative, but standard remote sensors, which measure various wavelengths of light emitted or reflected from Earth's surface and atmosphere, can only directly detect wetness conditions within the first few centimeters of the land s surface. Such sensors include the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) C-band passive microwave measurement system on the National Aeronautic and Space Administration's (NASA) Aqua satellite, and the combined active and passive L-band microwave system currently under development for NASA's planned Soil Moisture Active Passive (SMAP) satellite mission. These instruments are sensitive to water as deep as the top 2 cm and 5 cm of the soil column, respectively, with the specific depth depending on vegetation cover. Thermal infrared (TIR) imaging has been used to infer water stored in the full root zone, with limitations: auxiliary information including soil grain size is required, the TIR temperature versus soil water content curve becomes flat as wetness increases, and dense vegetation and cloud cover impede measurement. Numerical models of land surface hydrology are another potential solution, but the quality of output from such models is limited by errors in the input data and tradeoffs between model realism and computational efficiency. This chapter is divided into eight sections, the next of which describes the theory behind satellite gravimetry. Following that is a summary of the GRACE mission and how hydrological information is gleaned from its gravity products. The fourth section provides examples of hydrological science enabled by GRACE. The fifth and sixth sections list the challenging aspects of GRACE derived hydrology data and how they are being overcome, including the use of data assimilation. The seventh section describes recent progress in applying GRACE for drought monitoring, including the development of new soil moisture and drought indicator products, and that is followed by a discussion of future prospects in satellite gravimetry based drought monitoring.

Near Surface Soil Moisture Estimation Using SAR Images: A Case Study in the Mediterranean Area of Catalonia

NASA Astrophysics Data System (ADS)

Reppucci, Antonio; Moreno, Laura

2010-12-01

Information on Soil moisture spatial and temporal evolution is of great importance for managing the utilization of soils and vegetation, in particular in environments where the water resources are scarce. In-situ measurement of soil moisture are costly and not able to sample the spatial behaviour of a whole region. Thanks to their all weather capability and wide coverage, Synthetic Aperture Radar (SAR) images offer the opportunity to monitor large area with high resolution. This study presents the results of a project, partially founded by the Catalan government, to improve the monitoring of soil moisture using Earth Observation data. In particular the project is focused on the calibration of existing semi-empirical algorithm in the area of study. This will be done using co-located SAR and in-situ measurements acquired during several field campaigns. Observed deviations between SAR measurements and in-situ measurement are discussed.

Fiber Optic Thermo-Hygrometers for Soil Moisture Monitoring.

PubMed

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

2017-06-20

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

Fiber Optic Thermo-Hygrometers for Soil Moisture Monitoring

PubMed Central

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

2017-01-01

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

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

NASA Astrophysics Data System (ADS)

Kolassa, Jana; Aires, Filipe

2013-04-01

A neural network algorithm has been developed for the retrieval of Soil Moisture (SM) from global satellite observations. The algorithm estimates soil moisture from a synergy of passive and active microwave, infrared and visible satellite observations in order to capture the different SM variabilities that the individual sensors are sensitive to. The advantages and drawbacks of each satellite observation have been analysed and the information type and content carried by each observation have been determined. A global data set of monthly mean soil moisture for the 1993-2000 period has been computed with the neural network algorithm (Kolassa et al., in press, 2012). The resulting soil moisture retrieval product has then been used in an inter-comparison study including soil moisture from (1) the HTESSEL model (Balsamo et al., 2009), (2) the WACMOS satellite product (Liu et al., 2011), and (3) in situ measurements from the International Soil Moisture Network (Dorigo et al., 2011). The analysis showed that the satellite remote sensing products are well-suited to capture the spatial variability of the in situ data and even show the potential to improve the modelled soil moisture. Both satellite retrievals also display a good agreement with the temporal structures of the in situ data, however, HTESSEL appears to be more suitable for capturing the temporal variability (Kolassa et al., in press, 2012). The use of this type of neural network approach is currently being investigated as a retrieval option for the SMOS mission. Our soil moisture retrieval product has also been used in a coherence study with precipitation data from GPCP (Adler et al., 2003) and inundation estimates from GIEMS (Prigent et al., 2007). It was investigated on a global scale whether the three observation-based datasets are coherent with each other and show the expected behaviour. For most regions of the Earth, the datasets were consistent and the behaviour observed could be explained with the known hydrological processes. In addition, a regional analysis was conducted over several large river basins, including a detailed analysis of the time-lagged correlations between the three datasets and the spatial propagation of observed signals. Results appear consistent with the knowledge of the hydrological processes governing the individual basins. References Adler, R.F., G.J. Huffman, A. Chang, R. Ferraro, P. Xie, J. Janowiak, B. Rudolf, U. Schneider, S. Curtis, D. Bolvin, A. Gruber, J. Susskind, and P. Arkin (2003), The Version 2 Global Precipita- tion Climatology Project (GPCP) Monthly Precipitation Analysis (1979-Present).J. Hydrometeor., 4,1147-1167. Balsamo, G., Viterbo, P., Beljaars, A., van den Hurk, B., Hirschi, M., Betts, A. and Scipa,l K. (2009) A Revised Hydrology for the ECMWF Model: Verification from Field Site to Terrestrial Water Storage and Impact in the Integrated Forecast System, J. Hydrol., 10, 623-643 Dorigo, W. A., Wagner, W., Hohensinn, R., Hahn, S., Paulik, C., Xaver, A., Gruber, A., Drusch, M., Mecklenburg, S., van Oevelen, P., Robock, A., and Jackson, T. (2011), The International Soil Moisture Network: a data hosting facility for global in situ soil moisture measurements, Hydrol. Earth Syst. Sci., 15, 1675-1698 Kolassa, J., Aires, F., Polcher, J., Prigent, C., and Pereira, J. (2012), Soil moisture Retrieval from Multi-instrument Observations: Information Content Analysis and Retrieval Methodology (2012), J. Geophys. Res., Liu, Y. Y., Parinussa, R. M., Dorigo, W. A., De Jeu, R. A. M., Wagner, W., van Dijk, A. I. J. M., McCabe, M. F., and Evans, J. P.(2011), Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals, Hydrol. Earth Syst. Sci., 15, 425-436. Prigent, C., F. Papa, F. Aires, W. B. Rossow, and E. Matthews (2007), Global inundation dy- namics inferred from multiple satellite observations, 1993-2000, J. Geophys. Res., 112, D12107, doi:10.1029/2006JD007847.

Capacitance Based Moisture Sensing for Microgravity Plant Modules: Sensor Design and Considerations

NASA Technical Reports Server (NTRS)

Schaber, Chad L.; Nurge, Mark; Monje, Oscar

2011-01-01

Life support systems for growing plants in microgravity should strive for providing optimal growing conditions and increased automation. Accurately tracking soil moisture content can forward both of these aims, so an attempt was made to instrument a microgravity growth module currently in development, the VEGGIE rooting pillow, in order to monitor moisture levels. Two electrode systems for a capacitance-based moisture sensor were tested. Trials with both types of electrodes showed a linear correlation between observed capacitance and water content over certain ranges of moisture within the pillows. Overall, both types of the electrodes and the capacitance-based moisture sensor are promising candidates for tracking water levels for microgravity plant growth systems.

Deploying temporary networks for upscaling of sparse network stations

USDA-ARS?s Scientific Manuscript database

Soil observations networks at the national scale play an integral role in hydrologic modeling, drought assessment, agricultural decision support, and our ability to understand climate change. Understanding soil moisture variability is necessary to apply these measurements to model calibration, busin...

Evaluation of three different data fusion approaches that uses satellite soil moisture from different passive microwave sensors to construct one consistent climate record

NASA Astrophysics Data System (ADS)

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

2016-04-01

Datasets that are derived from satellite observations are becoming increasingly important for measuring key parameters of the Earth's climate and are therefore crucial in research on climate change, giving the opportunity to researchers to detect anomalies and long-term trends globally. One of these key parameters is soil moisture (SM), which has a large impact on water, energy and biogeochemical cycles worldwide. A long-term SM data record from active and passive microwave satellite observations was developed as part of ESA's Climate Change Initiative (ESA-CCI-SM, http://www.esa-soilmoisture-cci.org/). Currently the dataset covers a period from 1978 to 2014 and is updated regularly, observations from a several microwave satellites including: ERS-1, ERS-2, METOP-A, Nimbus 7 SMMR, DMSP SSM/I, TRMM TMI, Aqua AMSRE, Coriolis WindSat, and GCOM-W1 AMSR2. In 2009, ESA launched the Soil Moisture and Ocean Salinity (SMOS, Kerr et al., 2010) mission, carrying onboard a unique L-band radiometer, but its SM retrievals are not yet part of this dataset. Due to the different radiometric characteristics of SMOS, integrating SMOS into the ESA-CCI-SM dataset is not straight forward. Therefore several approaches have been tested to fuse soil moisture retrievals from SMOS and AMSRE, which currently forms the basis of the passive microwave part within ESA-CCI-SM project. These approaches are: 1. A Neural Network Fusion approach (Rodríguez-Fernández et al., 2015), 2. A regression approach (Wigneron et al., 2004; Al-Yaari et al., 2015) and 3. A radiative transfer based approach, using the Land Parameter Retrieval Model (Van der Schalie et al., 2016). This study evaluates the three different approaches and tests their skills against multiple datasets, including MERRA-Land, ERA-Interim/Land, the current ESA-CCI-SM v2.2 and in situ measurements from the International Soil Moisture Network and present a recommendation for the potential integration of SMOS soil moisture into the ESA-CCI-SM dataset. This recommendation is based on a series of statistical metrics (i.e. correlation, unbiased root mean square error, bias, spatial correspondence and single to noise ratios (Gruber et al., 2015)) and will provide guidelines for a seamless integration. References Al-Yaari, A., Wigneron, J.P., Kerr, Y., De Jeu, R.A.M., Rodriguez-Fernandez, N., Van der Schalie, R., Al Bitar, A., Mialon, A., Richaume, P., Dolman, A., and Ducharne, A. (2015), "Testing regression equations to derive long-term global soil moisture datasets from passive microwave observations", Remote Sensing of Environment, IN PRESS. Gruber, A., Su, C.-H., Zwieback, S., Crowd, W., Dorigo, W., and Wagner, W. (2015), "Recent advances in (soil moisture) triple collocation analysis", Int. J. Appl. Earth Observ. Geoinf, doi: http://dx.doi.org/10.1016/j.jag.2015.09.002. Kerr, Y.H., Waldteufel, P., Wigneron, J.P., Delwart, S., Cabot, F., Boutin, J., Escorihuela, M.J., Font, J., Reul, N., Gruhier, C., Juglea, S.E., Drinkwater, M.R., Hahne, A., Martin-Neira, M., and Mecklenburg, S. (2010), "The SMOS mission: New tool for monitoring key elements of the global water cycle", Proceedings of the IEEE, vol. 98, no. 5, doi: 10.1109/JPROC.2010.2043043. Rodríguez-Fernández, N.J., Aires, F., Richaume, P., Kerr, Y.H., Prigent, C., Kolassa, J., Cabot, F., Jiménez, C., Mahmoodi, A., and Drusch, M. (2015), "Soil Moisture Retrieval Using Neural Networks: Application to SMOS", IEEE Trans. on Geosc. and Remote Sens., vol. 53, no. 11, doi: 10.1109/TGRS.2015.2430845. Van der Schalie, R., Kerr, Y.H., Wigneron, J.P., Rodriguez-Fernandez, N.J., Al-Yaari, A., and De Jeu, R.A.M. (2015), "Global SMOS Soil Moisture Retrievals from The Land Parameter Retrieval Model", Int. J. Appl. Earth Observ. Geoinf, doi: http://dx.doi.org/10.1016/j.jag.2015.08.005. Wigneron J.-P., Calvet, J.-C., De Rosnay, P., Kerr, Y., Waldteufel, P., Saleh, K., Escorihuela, M.J. and Kruszewski, A. (2004), "Soil Moisture Retrievals from Bi-Angular L-band Passive Microwave Observations", IEEE Trans. Geosc. Remote Sens. Let., vol. 1, no. 4, pp. 277-281.

Effect of Chemical Structure and Network Formation on Physical Properties of Di(Cyanate Ester) Thermosets (Post Print)

DTIC Science & Technology

2012-02-06

with glass or polyethylene reinforcements for use in radomes and antenna structures,4 where their unusually low dielectric constant and low moisture ...are prized for their elevated glass transition temperature, good adhesion to metals, resistance to degradation by moisture , and excellent flame...on the performance of cyanate ester resins and composites. Cyanate ester monomers, particularly when catalyzed, may react with adventitious moisture to

New and Simple Ways to Minimize Water Uptake and Hydrolytic Degradation in Cyanate Esters

DTIC Science & Technology

2016-01-27

Photo by U.S. Navy photo by Photographer’s Mate 1st Class Anibal Rivera (public domain). Importance of Moisture Uptake in Composite Component... Moisture Uptake in Thermoset Resins • Increasing conversion joins together more "loose ends" in the network, eliminating free space where water can be...public release; distribution is unlimited. PA Clearance #16205 6 Proposed Role of Vitrification in Controlling Moisture Uptake • Increasing conversions

Research on Applicability Analysis of Drought Index in Liaoning Area

NASA Astrophysics Data System (ADS)

Wang, Xin; Ding, Hua; Shuang Sun, Li; Li, Ru Ren; Liu, Yu Mei

2018-05-01

Based on brightness temperature data of AMSR-E (advanced microwave scanning radiometer — earth observing system) in 2009 and 2011, the inversion on 8 brightness temperature ratios is performed as alternative drought indexes in this paper. The correlation analysis is made through the soil moisture extracted from inversion drought index and data itself, and 3 kinds of alternative drought that relatively coincide with soil moisture of AMSR-E data itself are selected. And then on this basis, the analysis on the change situation of 3 kinds of microwave moisture indexes in 10 pixel × 10 pixel rectangular region of Shenyang and Chaoyang is made, and the evaluation on the monitoring advantages and disadvantages of 3 kinds of indexes on soil moisture is performed, so as to obtain the optimal index PIv6.9 for drought monitoring. In the end, in order to further study PIv6.9 on soil moisture monitoring situation within the range of Liaoning province, four days with relatively large precipitation are selected according to meteorological station data in 2009, the precipitation data of 51 meteorological stations in Liaoning province are interpolated within the range of the whole province by utilizing Kriging method, and the contrastive analysis on the spatial distribution of precipitation and PIv6.9 index is made. The results show that PIv6.9 can best reflect the spatial distribution characteristics of drought status in Liaoning province.

Spatiotemporal Variability of Hillslope Soil Moisture Across Steep, Highly Dissected Topography

NASA Astrophysics Data System (ADS)

Jarecke, K. M.; Wondzell, S. M.; Bladon, K. D.

2016-12-01

Hillslope ecohydrological processes, including subsurface water flow and plant water uptake, are strongly influenced by soil moisture. However, the factors controlling spatial and temporal variability of soil moisture in steep, mountainous terrain are poorly understood. We asked: How do topography and soils interact to control the spatial and temporal variability of soil moisture in steep, Douglas-fir dominated hillslopes in the western Cascades? We will present a preliminary analysis of bimonthly soil moisture variability from July-November 2016 at 0-30 and 0-60 cm depth across spatially extensive convergent and divergent topographic positions in Watershed 1 of the H.J. Andrews Experimental Forest in central Oregon. Soil moisture monitoring locations were selected following a 5 m LIDAR analysis of topographic position, aspect, and slope. Topographic position index (TPI) was calculated as the difference in elevation to the mean elevation within a 30 m radius. Convergent (negative TPI values) and divergent (positive TPI values) monitoring locations were established along northwest to northeast-facing aspects and within 25-55 degree slopes. We hypothesized that topographic position (convergent vs. divergent), as well as soil physical properties (e.g., texture, bulk density), control variation in hillslope soil moisture at the sub-watershed scale. In addition, we expected the relative importance of hillslope topography to the spatial variability in soil moisture to differ seasonally. By comparing the spatiotemporal variability of hillslope soil moisture across topographic positions, our research provides a foundation for additional understanding of subsurface flow processes and plant-available soil-water in forests with steep, highly dissected terrain.

Optimization of the secondary drying step in freeze drying using TDLAS technology.

PubMed

Schneid, Stefan C; Gieseler, Henning; Kessler, William J; Luthra, Suman A; Pikal, Michael J

2011-03-01

The secondary drying phase in freeze drying is mostly developed on a trial-and-error basis due to the lack of appropriate noninvasive process analyzers. This study describes for the first time the application of Tunable Diode Laser Absorption Spectroscopy, a spectroscopic and noninvasive sensor for monitoring secondary drying in laboratory-scale freeze drying with the overall purpose of targeting intermediate moisture contents in the product. Bovine serum albumin/sucrose mixtures were used as a model system to imitate high concentrated antibody formulations. First, the rate of water desorption during secondary drying at constant product temperatures (-22 °C, -10 °C, and 0 °C) was investigated for three different shelf temperatures. Residual moisture contents of sampled vials were determined by Karl Fischer titration. An equilibration step was implemented to ensure homogeneous distribution of moisture (within 1%) in all vials. The residual moisture revealed a linear relationship to the water desorption rate for different temperatures, allowing the evaluation of an anchor point from noninvasive flow rate measurements without removal of samples from the freeze dryer. The accuracy of mass flow integration from this anchor point was found to be about 0.5%. In a second step, the concept was successfully tested in a confirmation experiment. Here, good agreement was found for the initial moisture content (anchor point) and the subsequent monitoring and targeting of intermediate moisture contents. The present approach for monitoring secondary drying indicated great potential to find wider application in sterile operations on production scale in pharmaceutical freeze drying. © 2011 American Association of Pharmaceutical Scientists

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

SMAP Soil Moisture Disaggregation using Land Surface Temperature and Vegetation Data

NASA Astrophysics Data System (ADS)

Fang, B.; Lakshmi, V.

2016-12-01

Soil moisture (SM) is a key parameter in agriculture, hydrology and ecology studies. The global SM retrievals have been providing by microwave remote sensing technology since late 1970s and many SM retrieval algorithms have been developed, calibrated and applied on satellite sensors such as AMSR-E (Advanced Microwave Scanning Radiometer for the Earth Observing System), AMSR-2 (Advanced Microwave Scanning Radiometer 2) and SMOS (Soil Moisture and Ocean Salinity). Particularly, SMAP (Soil Moisture Active/Passive) satellite, which was developed by NASA, was launched in January 2015. SMAP provides soil moisture products of 9 km and 36 km spatial resolutions which are not capable for research and applications of finer scale. Toward this issue, this study applied a SM disaggregation algorithm to disaggregate SMAP passive microwave soil moisture 36 km product. This algorithm was developed based on the thermal inertial relationship between daily surface temperature variation and daily average soil moisture which is modulated by vegetation condition, by using remote sensing retrievals from AVHRR (Advanced Very High Resolution Radiometer, MODIS (Moderate Resolution Imaging Spectroradiometer), SPOT (Satellite Pour l'Observation de la Terre), as well as Land Surface Model (LSM) output from NLDAS (North American Land Data Assimilation System). The disaggregation model was built at 1/8o spatial resolution on monthly basis and was implemented to calculate and disaggregate SMAP 36 km SM retrievals to 1 km resolution in Oklahoma. The SM disaggregation results were also validated using MESONET (Mesoscale Network) and MICRONET (Microscale Network) ground SM measurements.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Extended monitoring and analysis of moisture-temperature data

DOT National Transportation Integrated Search

2001-10-01

The performance of asphalt concrete pavements is in part affected by the seasonal variations of the resilient modulus of the AC layer and of the subgrade soil. To determine the variation of these parameters throughout Ohio, nine moisture-temperature-...

Equilibrium relative humidity as a tool to monitor seed moisture

Treesearch

Robert P. Karrfalt

2010-01-01

The importance of seed moisture in maintaining high seed viability is well known. The seed storage chapters in the Tropical Tree Seed Manual (Hong and Ellis 2003) and the Woody Plant Seed Manual (Bonner 2008a) give a detailed discussion and many references on this point. Working with seeds in an operational setting requires a test of seed moisture status. It is...

Validation of the Soil Moisture Active Passive mission using USDA-ARS experimental watersheds

USDA-ARS?s Scientific Manuscript database

The calibration and validation program of the Soil Moisture Active Passive mission (SMAP) relies upon an international cooperative of in situ networks to provide ground truth references across a variety of landscapes. The USDA Agricultural Research Service operates several experimental watersheds wh...

DOI/GTN-P climate and active-layer data acquired in the National Petroleum Reserve-Alaska and the Arctic National Wildlife Refuge

USGS Publications Warehouse

Urban, Frank E.; Clow, Gary D.

2014-01-01

This report provides data collected by the climate monitoring array of the U.S. Department of the Interior on Federal lands in Arctic Alaska over the period August 1998 to July 2013; this array is part of the Global Terrestrial Network for Permafrost, (DOI/GTN-P). In addition to presenting data, this report also describes monitoring, data collection, and quality-control methods. This array of 16 monitoring stations spans lat 68.5°N. to 70.5°N. and long 142.5°W. to 161°W., an area of approximately 150,000 square kilometers. Climate summaries are presented along with quality-controlled data. Data collection is ongoing and includes the following climate- and permafrost-related variables: air temperature, wind speed and direction, ground temperature, soil moisture, snow depth, rainfall totals, up- and downwelling shortwave radiation, and atmospheric pressure. These data were collected by the U.S. Geological Survey in close collaboration with the Bureau of Land Management and the U.S. Fish and Wildlife Service.

DOI/GTN-P Climate and active-layer data acquired in the National Petroleum Reserve–Alaska and the Arctic National Wildlife Refuge, 1998–2014

USGS Publications Warehouse

Urban, Frank E.; Clow, Gary D.

2016-03-04

This report provides data collected by the climate monitoring array of the U.S. Department of the Interior on Federal lands in Arctic Alaska over the period August 1998 to July 2014; this array is part of the Global Terrestrial Network for Permafrost (DOI/GTN-P). In addition to presenting data, this report also describes monitoring, data collection, and quality-control methods. The array of 16 monitoring stations spans lat 68.5°N. to 70.5°N. and long 142.5°W. to 161°W., an area of approximately 150,000 square kilometers. Climate summaries are presented along with quality-controlled data. Data collection is ongoing and includes the following climate- and permafrost-related variables: air temperature, wind speed and direction, ground temperature, soil moisture, snow depth, rainfall totals, up- and downwelling shortwave radiation, and atmospheric pressure. These data were collected by the U.S. Geological Survey in close collaboration with the Bureau of Land Management and the U.S. Fish and Wildlife Service.

DOI/GTN-P Climate and active-layer data acquired in the National Petroleum Reserve–Alaska and the Arctic National Wildlife Refuge, 1998–2015

USGS Publications Warehouse

Urban, Frank E.; Clow, Gary D.

2017-02-06

This report provides data collected by the climate monitoring array of the U.S. Department of the Interior on Federal lands in Arctic Alaska over the period August 1998 to July 2015; this array is part of the Global Terrestrial Network for Permafrost (DOI/GTN-P). In addition to presenting data, this report also describes monitoring, data collection, and quality-control methods. The array of 16 monitoring stations spans lat 68.5°N. to 70.5°N. and long 142.5°W. to 161°W., an area of approximately 150,000 square kilometers. Climate summaries are presented along with quality-controlled data. Data collection is ongoing and includes the following climate- and permafrost-related variables: air temperature, wind speed and direction, ground temperature, soil moisture, snow depth, rainfall totals, up- and downwelling shortwave radiation, and atmospheric pressure. These data were collected by the U.S. Geological Survey in close collaboration with the Bureau of Land Management and the U.S. Fish and Wildlife Service.

DOI/GTN-P climate and active-layer data acquired in the National Petroleum Reserve: Alaska and the Arctic National Wildlife Refuge, 1998-2011

USGS Publications Warehouse

Urban, Frank E.; Clow, Gary D.

2014-01-01

This report provides data collected by the climate monitoring array of the U.S. Department of the Interior on Federal lands in Arctic Alaska over the period August 1998 to July 2011; this array is part of the Global Terrestrial Network for Permafrost, (DOI/GTN-P). In addition to presenting data, this report also describes monitoring, data collection, and quality-control methodology. This array of 16 monitoring stations spans lat 68.5°N. to 70.5°N. and long 142.5°W. to 161°W., an area of approximately 150,000 square kilometers. Climate summaries are presented along with quality-controlled data. Data collection is ongoing and includes the following climate- and permafrost-related variables: air temperature, wind speed and direction, ground temperature and soil moisture, snow depth, rainfall, up- and downwelling shortwave radiation, and atmospheric pressure. These data were collected by the U.S. Geological Survey in close collaboration with the Bureau of Land Management and the U.S. Fish and Wildlife Service.

Air temperature, wind speed, and wind direction in the National Petroleum Reserve—Alaska and the Arctic National Wildlife Refuge, 1998–2011

USGS Publications Warehouse

Urban, Frank E.; Clow, Gary D.

2013-01-01

This report provides air temperature, wind speed, and wind direction data collected on Federal lands in Arctic Alaska over the period August 1998 to July 2011 by the U.S. Department of the Interior's climate monitoring array, part of the Global Terrestrial Network for Permafrost. In addition to presenting data, this report also describes monitoring, data collection, and quality control methodology. This array of 16 monitoring stations spans 68.5°N to 70.5°N and 142.5°W to 161°W, an area of roughly 150,000 square kilometers. Climate summaries are presented along with provisional quality-controlled data. Data collection is ongoing and includes several additional climate variables to be released in subsequent reports, including ground temperature and soil moisture, snow depth, rainfall, up- and downwelling shortwave radiation, and atmospheric pressure. These data were collected by the U.S. Geological Survey in close collaboration with the Bureau of Land Management and the U.S. Fish and Wildlife Service.

A TDR-Based Soil Moisture Monitoring System with Simultaneous Measurement of Soil Temperature and Electrical Conductivity

PubMed Central

Skierucha, Wojciech; Wilczek, Andrzej; Szypłowska, Agnieszka; Sławiński, Cezary; Lamorski, Krzysztof

2012-01-01

Elements of design and a field application of a TDR-based soil moisture and electrical conductivity monitoring system are described with detailed presentation of the time delay units with a resolution of 10 ps. Other issues discussed include the temperature correction of the applied time delay units, battery supply characteristics and the measurement results from one of the installed ground measurement stations in the Polesie National Park in Poland. PMID:23202009

Representative locations from time series of soil water content using time stability and wavelet analysis.

PubMed

Rivera, Diego; Lillo, Mario; Granda, Stalin

2014-12-01

The concept of time stability has been widely used in the design and assessment of monitoring networks of soil moisture, as well as in hydrological studies, because it is as a technique that allows identifying of particular locations having the property of representing mean values of soil moisture in the field. In this work, we assess the effect of time stability calculations as new information is added and how time stability calculations are affected at shorter periods, subsampled from the original time series, containing different amounts of precipitation. In doing so, we defined two experiments to explore the time stability behavior. The first experiment sequentially adds new data to the previous time series to investigate the long-term influence of new data in the results. The second experiment applies a windowing approach, taking sequential subsamples from the entire time series to investigate the influence of short-term changes associated with the precipitation in each window. Our results from an operating network (seven monitoring points equipped with four sensors each in a 2-ha blueberry field) show that as information is added to the time series, there are changes in the location of the most stable point (MSP), and that taking the moving 21-day windows, it is clear that most of the variability of soil water content changes is associated with both the amount and intensity of rainfall. The changes of the MSP over each window depend on the amount of water entering the soil and the previous state of the soil water content. For our case study, the upper strata are proxies for hourly to daily changes in soil water content, while the deeper strata are proxies for medium-range stored water. Thus, different locations and depths are representative of processes at different time scales. This situation must be taken into account when water management depends on soil water content values from fixed locations.

Understanding green roof spatial dynamics: results from a scale based hydrologic study and introduction of a low-cost method for wide-range monitoring

NASA Astrophysics Data System (ADS)

Hakimdavar, Raha; Culligan, Patricia J.; Guido, Aida

2014-05-01

Green roofs have the potential, if implemented on a wide scale and with proper foresight, to become an important supplement to traditional urban water management infrastructure, while also helping to change the face of cities from concrete draped, highly modified environments, to hybrid places where nature is more closely integrated into designs rather than pushed out of them. The ability of these systems to act as a decentralized rainwater handling network has been the topic of many recent studies. While these studies have attempted to quantify the hydrologic performance of green roofs, it's clear that they are dynamic systems whose responses are difficult to generalize. What also seems to be lacking from many studies is a discussion on the effects of green roof scale, spatial planning and configuration. This research aims to understand how rainfall characteristics and green roof scale impact its hydrologic performance. Three extensive green roof systems in New York City, with the same engineered components, age and regional climatic conditions, but different drainage areas, are analyzed. We find that rainfall volume and event duration are two of the parameters that most affect green roof performance, while rainfall intensity and antecedent dry weather period are less significant. We also find that green roof scale does in fact affect hydrologic performance, but mainly in reducing runoff peaks, with rainfall retention and lag time being much less affected by drainage area. We also introduce a low-cost monitoring method, termed the Soil Water Apportioning (SWA) method, which uses a water balance approach to analytically link precipitation to substrate moisture, and enable inference of green runoff and evapotranspiration from information on substrate moisture changes over time. Twelve months of in situ rainfall and soil moisture observations from three different green roof systems - extensive vegetated mat, semi-intensive vegetated mat, and semi-intensive tray - are used to test the reliability of the proposed approach using two different low-cost soil moisture probes. The estimates of runoff are compared with observed runoff data for durations ranging between 6 months to 1 year. Preliminary results indicate that this can be an effective low-cost and low-maintenance alternative to the custom made weir and lysimeter systems frequently used to quantify runoff during green roof studies. By significantly reducing the cost and labor associated with typical monitoring efforts, the SWA method makes large scale studies of green roof hydrologic performance more feasible.

Extended monitoring and analysis of moisture temperature data : [executive summary].

DOT National Transportation Integrated Search

2001-01-01

The performance of asphalt concrete pavements is in part affected by the seasonal variations of the resilient modulus of the AC layer and of the subgrade soil. To determine the variation of these parameters throughout Ohio, nine moisture-temperature-...

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

NASA Technical Reports Server (NTRS)

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

2015-01-01

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

Untangling the contribution of aspect, drainage position and elevation to the spatial variability of fine surface fuels in south east Australian forests

NASA Astrophysics Data System (ADS)

Sheridan, Gary; nyman, petter; Duff, Tom; Baillie, Craig; Bovill, William; Lane, Patrick; Tolhurst, Kevin

2015-04-01

The prediction of fuel moisture content is important for estimating the rate of spread of wildfires, the ignition probability of firebrands, and for the efficient scheduling of prescribed fire. The moisture content of fine surface fuels varies spatially at large scales (10's to 100's km) due to variation in meteorological variables (eg. temperature, relative humidity, precipitation). At smaller scales (100's of metres) in steep topography spatial variability is attributed to topographic influences that include differences in radiation due to aspect and slope, differences in precipitation, temperature and relative humidity due to elevation, and differences in soil moisture due to hillslope drainage position. Variable forest structure and canopy shading adds further to the spatial variability in surface fuel moisture. In this study we aim to combine daily 5km resolution gridded weather data with 20m resolution DEM and vegetation structure data to predict the spatial variability of fine surface fuels in steep topography. Microclimate stations were established in south east Australia to monitor surface fine fuel moisture continuously (every 15 minutes) using newly developed instrumented litter packs, in addition to temperature and relative humidity measurements inside the litter pack, and measurement of precipitation and energy inputs above and below the forest canopy. Microclimate stations were established across a gradient of aspect (5 stations), drainage position (7 stations), elevation (15 stations), and canopy cover conditions (6 stations). The data from this extensive network of microclimate stations across a broad spectrum of topographic conditions is being analysed to enable the downscaling of gridded weather data to spatial scales that are relevant to the connectivity of wildfire fuels and to the scheduling and outcome of prescribed fires. The initial results from the first year of this study are presented here.

Global Drought Monitoring and Forecasting based on Satellite Data and Land Surface Modeling

NASA Astrophysics Data System (ADS)

Sheffield, J.; Lobell, D. B.; Wood, E. F.

2010-12-01

Monitoring drought globally is challenging because of the lack of dense in-situ hydrologic data in many regions. In particular, soil moisture measurements are absent in many regions and in real time. This is especially problematic for developing regions such as Africa where water information is arguably most needed, but virtually non-existent on the ground. With the emergence of remote sensing estimates of all components of the water cycle there is now the potential to monitor the full terrestrial water cycle from space to give global coverage and provide the basis for drought monitoring. These estimates include microwave-infrared merged precipitation retrievals, evapotranspiration based on satellite radiation, temperature and vegetation data, gravity recovery measurements of changes in water storage, microwave based retrievals of soil moisture and altimetry based estimates of lake levels and river flows. However, many challenges remain in using these data, especially due to biases in individual satellite retrieved components, their incomplete sampling in time and space, and their failure to provide budget closure in concert. A potential way forward is to use modeling to provide a framework to merge these disparate sources of information to give physically consistent and spatially and temporally continuous estimates of the water cycle and drought. Here we present results from our experimental global water cycle monitor and its African drought monitor counterpart (http://hydrology.princeton.edu/monitor). The system relies heavily on satellite data to drive the Variable Infiltration Capacity (VIC) land surface model to provide near real-time estimates of precipitation, evapotranspiraiton, soil moisture, snow pack and streamflow. Drought is defined in terms of anomalies of soil moisture and other hydrologic variables relative to a long-term (1950-2000) climatology. We present some examples of recent droughts and how they are identified by the system, including objective quantification and tracking of their spatial-temporal characteristics. Further we present strategies for merging various sources of information, including bias correction of satellite precipitation and assimilation of remotely sensed soil moisture, which can augment the monitoring in regions where satellite precipitation is most uncertain. Ongoing work is adding a drought forecast component based on a successful implementation over the U.S. and agricultural productivity estimates based on output from crop yield models. The forecast component uses seasonal global climate forecasts from the NCEP Climate Forecast System (CFS). These are merged with observed climatology in a Bayesian framework to produce ensemble atmospheric forcings that better capture the uncertainties. At the same time, the system bias corrects and downscales the monthly CFS data. We show some initial seasonal (up to 6-month lead) hydrologic forecast results for the African system. Agricultural monitoring is based on the precipitation, temperature and soil moisture from the system to force statistical and process based crop yield models. We demonstrate the feasibility of monitoring major crop types across the world and show a strategy for providing predictions of yields within our drought forecast mode.

Multi-profile analysis of soil moisture within the U.S. Climate Reference Network

USDA-ARS?s Scientific Manuscript database

Soil moisture estimates are crucial for hydrologic modeling and agricultural decision-support efforts. These measurements are also pivotal for long-term inquiries regarding the impacts of climate change and the resulting droughts over large spatial and temporal scales. However, it has only been t...

Investigation of Hydrological Response of Three Identical Artificial Hillslopes at the Landscape Evolution Observatory

NASA Astrophysics Data System (ADS)

Matos, K.; Alves Meira Neto, A.; Troch, P. A. A.; Volkmann, T.

2017-12-01

Hydrological processes at the hillslope scale are complex and heterogeneous, but monitoring hillslopes with a large number of sensors or replicate experimental designs is rarely feasible. The Landscape Evolution Observatory (LEO) at Biosphere 2 consists of three replicated, large (330 m2) artificial hillslopes (East, Center and West) packed with 1-m depth of initially homogeneous, basaltic soil. Each landscape contains a spatially dense network of sensors capable of resolving meter-scale lateral heterogeneity and sub-meter scale vertical heterogeneity in moisture content and water potential, as well as the hillslope-integrated water balance components. A sophisticated irrigation system allows performing controlled forcing experiments. The three hillslopes are thought to be nearly identical, however recent data showed significant differences in discharge and storage behavior. A 45-day periodic-steady-state tracer experiment was conducted in November and December of 2016, where a 3.5-day long, identical irrigation sequence was repeated 15 times. Each sequence's rainfall, runoff, and storage dynamics were recorded, and distributed moisture characteristics were derived using paired moisture content and matric potential data from 496 positions in each hillslope. In order to understand why the three hillslopes behave hydrologically different, we analyzed soil water retention characteristics at various scales ranging from individually paired moisture and matric potential to whole-hillslope soil water retention characteristics. The results confirm the distinct hydrological behavior between the three hillslopes. The East and West hillslopes behave more similar with respect to the release of water. In contrast, the East and Center hillslopes are more similar with respect to their storage behavior. The differences in hillslope behavior arising from three identically built hillslopes are a surprising and beneficial opportunity to explore how differences in small-scale heterogeneity can impact hydrological dynamics at the hillslope scale.

Recent decline in the global land evapotranspiration trend due to limited moisture supply.

PubMed

Jung, Martin; Reichstein, Markus; Ciais, Philippe; Seneviratne, Sonia I; Sheffield, Justin; Goulden, Michael L; Bonan, Gordon; Cescatti, Alessandro; Chen, Jiquan; de Jeu, Richard; Dolman, A Johannes; Eugster, Werner; Gerten, Dieter; Gianelle, Damiano; Gobron, Nadine; Heinke, Jens; Kimball, John; Law, Beverly E; Montagnani, Leonardo; Mu, Qiaozhen; Mueller, Brigitte; Oleson, Keith; Papale, Dario; Richardson, Andrew D; Roupsard, Olivier; Running, Steve; Tomelleri, Enrico; Viovy, Nicolas; Weber, Ulrich; Williams, Christopher; Wood, Eric; Zaehle, Sönke; Zhang, Ke

2010-10-21

More than half of the solar energy absorbed by land surfaces is currently used to evaporate water. Climate change is expected to intensify the hydrological cycle and to alter evapotranspiration, with implications for ecosystem services and feedback to regional and global climate. Evapotranspiration changes may already be under way, but direct observational constraints are lacking at the global scale. Until such evidence is available, changes in the water cycle on land−a key diagnostic criterion of the effects of climate change and variability−remain uncertain. Here we provide a data-driven estimate of global land evapotranspiration from 1982 to 2008, compiled using a global monitoring network, meteorological and remote-sensing observations, and a machine-learning algorithm. In addition, we have assessed evapotranspiration variations over the same time period using an ensemble of process-based land-surface models. Our results suggest that global annual evapotranspiration increased on average by 7.1 ± 1.0 millimetres per year per decade from 1982 to 1997. After that, coincident with the last major El Niño event in 1998, the global evapotranspiration increase seems to have ceased until 2008. This change was driven primarily by moisture limitation in the Southern Hemisphere, particularly Africa and Australia. In these regions, microwave satellite observations indicate that soil moisture decreased from 1998 to 2008. Hence, increasing soil-moisture limitations on evapotranspiration largely explain the recent decline of the global land-evapotranspiration trend. Whether the changing behaviour of evapotranspiration is representative of natural climate variability or reflects a more permanent reorganization of the land water cycle is a key question for earth system science.

NASAs Soil Moisture Active Passive (SMAP) Mission and Opportunities For Applications Users

NASA Technical Reports Server (NTRS)

Brown, Molly E.; Escobar, Vanessa; Moran, Susan; Entekhabi, Dara; O'Neill, Peggy; Njoku, Eni G.; Doorn, Brad; Entin, Jared K.

2013-01-01

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 lives in a number of ways from the ravages of flooding to the needs for monitoring agricultural and hydrologic droughts. Because of their relevance to weather, climate, science, and society, accurate and timely measurements of soil moisture and freeze/thaw state with global coverage are critically important.

High-Resolution Monitoring of Soil Water Dynamics in a Vegetated Hillslope by Active Distributed Temperature Sensing

NASA Astrophysics Data System (ADS)

Ciocca, F.; Krause, S.; Blaen, P.; Hannah, D. M.; Chalari, A.; Mondanos, M.; Abesser, C.

2016-12-01

Water and thermal conditions in the shallow vadose zone can be very complex and dynamic across a range of spatiotemporal scales. The efficient analysis of such dynamics requires technologies capable of precise and high-resolution monitoring of soil temperature and moisture across multiple scales. Optical fibre distributed temperature sensors (DTS) allows for precise temperature measurements at high spatio-temporal resolution, over several kilometres of optical fibre cable. In addition to passive temperature monitoring, hybrid optical cables with embedded metal conductors can be electrically heated and allow for distributed heat pulses. Such Active-DTS technique involves the analysis of temperatures during both heating and cooling phases of an optical fibre cable buried in the soil in order to provide distributed soil moisture estimates. In summer 2015, three loops of a 500m hybrid-optical cable have been deployed at 10cm, 25cm and 40cm depths along a hillslope with juvenile forest. Active-DTS surveys have been conducted with the aim to: (i) monitor the post-installation soil settling around the cable; (ii) analyse different heating strategies (intensity, duration) of the cable; (iii) establish a method for inferring soil moisture from Active-DTS results and validate with independent soil moisture readings from point probes; (iv) monitor the soil moisture response to short forcing events such as storms and artificial irrigation. Results from the surveys will be presented, and first assumptions on how the obtained soil water dynamics can be associated to specific triggers such as precipitation, evapotranspiration, soil inclination, will be discussed. This research is part of the British National Environmental Research Council (NERC) funded Distributed intelligent Heat Pulse System (DiHPS) project and is realised in the context of the Free Air Carbon Enrichment (FACE) experiment, in collaboration with the Birmingham Institute of Forest Research (BIFoR).

Application of Satellite Gravimetry for Water Resource Vulnerability Assessment

NASA Technical Reports Server (NTRS)

Rodell, Matthew

2012-01-01

The force of Earth's gravity field varies in proportion to the amount of mass near the surface. Spatial and temporal variations in the gravity field can be measured via their effects on the orbits of satellites. The Gravity Recovery and Climate Experiment (GRACE) is the first satellite mission dedicated to monitoring temporal variations in the gravity field. The monthly gravity anomaly maps that have been delivered by GRACE since 2002 are being used to infer changes in terrestrial water storage (the sum of groundwater, soil moisture, surface waters, and snow and ice), which are the primary source of gravity variability on monthly to decadal timescales after atmospheric and oceanic circulation effects have been removed. Other remote sensing techniques are unable to detect water below the first few centimeters of the land surface. Conventional ground based techniques can be used to monitor terrestrial water storage, but groundwater, soil moisture, and snow observation networks are sparse in most of the world, and the countries that do collect such data rarely are willing to share them. Thus GRACE is unique in its ability to provide global data on variations in the availability of fresh water, which is both vital to life on land and vulnerable to climate variability and mismanagement. This chapter describes the unique and challenging aspects of GRACE terrestrial water storage data, examples of how the data have been used for research and applications related to fresh water vulnerability and change, and prospects for continued contributions of satellite gravimetry to water resources science and policy.

Field Measurements and Numerical Simulations of Temperature and Moisture in Highway Engineering Using a Frequency Domain Reflectometry Sensor

PubMed Central

Yao, Yong-Sheng; Zheng, Jian-Long; Chen, Zeng-Shun; Zhang, Jun-Hui; Li, Yong

2016-01-01

This paper presents a systematic pioneering study on the use of agricultural-purpose frequency domain reflectometry (FDR) sensors to monitor temperature and moisture of a subgrade in highway extension and reconstruction engineering. The principle of agricultural-purpose FDR sensors and the process for embedding this kind of sensors for subgrade engineering purposes are introduced. Based on field measured weather data, a numerical analysis model for temperature and moisture content in the subgrade’s soil is built. Comparisons of the temperature and moisture data obtained from numerical simulation and FDR-based measurements are conducted. The results show that: (1) the embedding method and process, data acquisition, and remote transmission presented are reasonable; (2) the temperature and moisture changes are coordinated with the atmospheric environment and they are also in close agreement with numerical calculations; (3) the change laws of both are consistent at positions where the subgrade is compacted uniformly. These results suggest that the data measured by the agricultural-purpose FDR sensors are reliable. The findings of this paper enable a new and effective real-time monitoring method for a subgrade’s temperature and moisture changes, and thus broaden the application of agricultural-purpose FDR sensors. PMID:27294935

Compact polarimetric synthetic aperture radar for monitoring soil moisture condition

NASA Astrophysics Data System (ADS)

Merzouki, A.; McNairn, H.; Powers, J.; Friesen, M.

2017-12-01

Coarse resolution soil moisture maps are currently operationally delivered by ESA's SMOS and NASA's SMAP passive microwaves sensors. Despite this evolution, operational soil moisture monitoring at the field scale remains challenging. A number of factors contribute to this challenge including the complexity of the retrieval that requires advanced SAR systems with enhanced temporal revisit capabilities. Since the launch of RADARSAT-2 in 2007, Agriculture and Agri-Food Canada (AAFC) has been evaluating the accuracy of these data for estimating surface soil moisture. Thus, a hybrid (multi-angle/multi-polarization) retrieval approach was found well suited for the planned RADARSAT Constellation Mission (RCM) considering the more frequent relook expected with the three satellite configuration. The purpose of this study is to evaluate the capability of C-band CP data to estimate soil moisture over agricultural fields, in anticipation of the launch of RCM. In this research we introduce a new CP approach based on the IEM and simulated RCM CP mode intensities from RADARSAT-2 images acquired at different dates. The accuracy of soil moisture retrieval from the proposed multi-polarization and hybrid methods will be contrasted with that from a more conventional quad-pol approach, and validated against in situ measurements by pooling data collected over AAFC test sites in Ontario, Manitoba and Saskatchewan, Canada.

Monitoring the Vadose Zone Moisture Regime Below a Surface Barrier

NASA Astrophysics Data System (ADS)

Zhang, Z. F.; Strickland, C. E.; Field, J. G.

2009-12-01

A 6000 m2 interim surface barrier has been constructed over a portion of the T Tank Farm in the Depart of Energy’s Hanford site. The purpose of using a surface barrier was to reduce or eliminate the infiltration of meteoric precipitation into the contaminated soil zone due to past leaks from Tank T-106 and hence to reduce the rate of movement of the plume. As part of the demonstration effort, vadose zone moisture is being monitored to assess the effectiveness of the barrier on the reduction of soil moisture flow. A vadose zone monitoring system was installed to measure soil water conditions at four horizontal locations (i.e., instrument Nests A, B, C, and D) outside, near the edge of, and beneath the barrier. Each instrument nest consists of a capacitance probe with multiple sensors, multiple heat-dissipation units, and a neutron probe access tube used to measure soil-water content and soil-water pressure. Nest A serves as a control by providing subsurface conditions outside the influence of the surface barrier. Nest B provides subsurface measurements to assess barrier edge effects. Nests C and D are used to assess the impact of the surface barrier on soil-moisture conditions beneath it. Monitoring began in September 2006 and continues to the present. To date, the monitoring system has provided high-quality data. Results show that the soil beneath the barrier has been draining from the shallower depth. The lack of climate-caused seasonal variation of soil water condition beneath the barrier indicates that the surface barrier has minimized water exchange between the soil and the atmosphere.

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

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

U.S National cropland soil moisture monitoring using SMAP

USDA-ARS?s Scientific Manuscript database

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...

Exploratory Study of Basement Moisture During Operation of Active Soil Depressurization Radon Control Systems

EPA Pesticide Factsheets

As part of an exploratory study, three houses were monitored for moisture indicators, radon levels, building operations, and other environmental parameters while ASD systems were cycled on and off. December 6, 2007, Revised 3/10/08.

Applications of the EOS SAR to monitoring global change

NASA Technical Reports Server (NTRS)

Schier, Marguerite; Way, Jobea; Holt, Benjamin

1991-01-01

The SAR employed by NASA's Earth Observing System (EOS) is a multifrequency multipolarization radar which can conduct global monitoring of geophysical and biophysical parameters. The present discussion of the EOS SAR's role in global monitoring emphasizes geophysical product variables applicable to global hydrologic, biogeochemical, and energy cycle models. EOS SAR products encompass biomass, wetland areas, and phenologic and environmental states, in the field of ecosystem dynamics; soil moisture, snow moisture and extent, and glacier and ice sheet extent and velocity, in hydrologic cycle studies; surface-wave fields and sea ice properties, in ocean/atmosphere circulation; and the topography, erosion, and land forms of the solid earth.

Monitoring and Data Analysis for the Vadose Zone Monitoring System (VZMS), McClellan AFB. Quarterly Status Report (2/20/98 - 5/20/98)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zawislanski, P.T.; Mountford, H.S.Monitoring and Data Analysis; for the Vadose Zone Monitoring System

1998-06-18

This report contains information on field and laboratory work performed between February 20th, 1998 and May 20th, 1998, at site S-7 in IC 34, at McClellan AFB. At this location, a Vadose Zone Monitoring System (VZMS) (LBNL, 1996) is currently being used to collect subsurface data including hydraulic potential, soil gas pressure, moisture content, water chemistry, gas chemistry, and temperature. This report describes: moisture content changes, based on neutron logging; gas-phase VOC concentrations; aqueous-phase VOC concentrations; temperature profiles; and installation of new instrument cluster.

Transregional Collaborative Research Centre 32: Patterns in Soil-Vegetation-Atmosphere-Systems

NASA Astrophysics Data System (ADS)

Simmer, C.; Thiele-Eich, I.

2015-12-01

The Collaborative Research Centre TR32 has the goal to perform pattern-based prediction of states and fluxes of water, CO2 and energy in terrestrial systems across scales. For this, the TR32 set up the following three elements during the past nine years: measurement techniques that allow us to characterize and monitor the spatiotemporal dynamics and evolution of system properties across scales, a cross-scale, multi-compartment terrestrial system modeling approach that includes all relevant processes using the terrestrial model platform TerrSysMP and state variable assimilation and parameter estimation methods. We will present examples of how the TR32 utilizes these three elements to improve our understanding of the water cycle. The available soil moisture monitoring network consisting of e.g. cosmic-ray sensors or an in situ NMR slim-line logging tool has been helpful in understanding the interactions of plant growth and soil moisture dynamics. New algorithms derive soil moisture from satellite based SAR systems, which showed potential for the derivation of surface roughness and vegetation information. For surface precipitation, a radar composite using observations from two dual-polarized X-band Doppler radars provides nearly 100% coverage of the Rur catchment. To also be able to include other precipitation observations which occur at different temporal and spatial resolutions, such as rain gauges, a high resolution space-time precipitation model is being developed. Commercial microwave links used for cell phone communication have also been experimented with to improve polarimetric quantitative precipitation estimation. In addition, uncertainty plays a major role with respect to the central goal of the TR32 and is taken into account in various ways. For example, model uncertainty in the Rur catchment results in large parts from anthropogenic activities such as e.g. drainage patterns in fields, the control of the Rur discharge, groundwater pumping, storage lakes, etc. Other approaches to quantify uncertainty include sensitivity experiments to evaluate the effects of parameter lumping.

Long-term 4D Geoelectrical Imaging of Moisture Dynamics in an Active Landslide

NASA Astrophysics Data System (ADS)

Uhlemann, S.; Chambers, J. E.; Wilkinson, P. B.; Maurer, H.; Meldrum, P.; Gunn, D.; Smith, A.; Dijkstra, T.

2016-12-01

Landslides are a major natural hazard, endangering communities and infrastructure worldwide. Mitigating landslide risk relies on understanding causes and triggering processes, which are often linked to moisture dynamics in slopes causing material softening and elevated pore water pressures. Geoelectrical monitoring is frequently applied to study landslide hydrology. However, its sensitivity to sensor movements has been a challenge for long-term studies on actively failing slopes. Although 2D data acquisition has previously been favoured, it provides limited resolution and relatively poor representation of important 3D landslide structures. We present a novel methodology to incorporate electrode movements into a time-lapse 3D inversion workflow, resulting in a virtually artefact-free time-series of resistivity models. Using temperature correction and laboratory hydro-geophysical relationships, resistivity models are translated into models of moisture content. The data span more than three years, enabling imaging of processes pre- and post landslide reactivation. In the two years before reactivation, the models showed surficial wetting and drying, drainage pathways, and deeper groundwater dynamics. During reactivation, exceptionally high moisture contents were imaged throughout the slope, which was confirmed by independent measurements. Preferential flow was imaged that stabilized parts of the landslide by diverting moisture, and thus dissipating pore pressures, from the slip surface. The results highlight that moisture levels obtained from resistivity monitoring may provide a better activity threshold than rainfall intensity. Based on this work, pro-active remediation measures could be designed and effective early-warning systems implemented. Eventually, resistivity monitoring that can account for moving electrodes may provide a new means for pro-active mitigation of landslide risk, especially for communities and critical infrastructure.

An integrated monitoring network for hydrologic, geochemical, and sediment fluxes to characterize carbon-mineral fate in the Christina River Basin Critical Zone Observatory

NASA Astrophysics Data System (ADS)

Sawyer, A. H.; Karwan, D. L.; Lazareva, O.

2011-12-01

Organic carbon (C) -mineral complexation mechanism plays an important role in C sequestration within watersheds. The primary goal of the Christina River Basin Critical Zone Observatory in SE Pennsylvania and N Delaware, USA (one of six National Science Foundation-funded observatories) is to quantify net carbon sink or source due to mineral production and transport and its dependence on land use. This effort requires an interdisciplinary understanding of carbon and mineral fluxes across interfaces between soil, aquifer, floodplain, and river. We have established a monitoring network that targets hydrologic, geochemical, and sedimentological transport processes across channel-floodplain-aquifer interfaces within White Clay Creek Watershed. Within the channel, suspended material is sampled and analyzed for organic and mineral composition as well as geochemical fingerprints. Surface water and groundwater are analyzed for C, Fe, and Mn chemistry. Within the floodplain, in-situ sensors monitor soil moisture, pressure, temperature, conductivity, and redox potential. Integrated data analysis should yield estimates of water and solute fluxes between the vadose zone, riparian aquifer, and stream. Our preliminary data show that storm events are important for carbon and mineral fluxes-suspended material in surface water changes in source and composition throughout the storm. Meanwhile, the variation in stream stage drives surface water-groundwater exchange, facilitating changes in redox potential and providing opportunity for enhanced transport and reactions involving C, Fe, and Mn in the riparian aquifer.

Retrieving pace in vegetation growth using precipitation and soil moisture

NASA Astrophysics Data System (ADS)

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

2013-12-01

The complexity of interactions between the biophysical components of the watershed increases the challenge of understanding water budget. Hence, the perspicacity of the continuum soil-vegetation-atmosphere's functionality still remains crucial for science. This study targeted the Texas Gulf watershed and evaluated the behavior of vegetation covers by coupling precipitation and soil moisture patterns. Growing season's Normalized Differential Vegetation Index NDVI for deciduous forest and grassland were used over a 23 year period as well as precipitation and soil moisture data. The role of time scales on vegetation dynamics analysis was appraised using both entropy rescaling and correlation analysis. This resulted in that soil moisture at 5 cm and 25cm are potentially more efficient to use for vegetation dynamics monitoring at finer time scale compared to precipitation. Albeit soil moisture at 5 cm and 25 cm series are highly correlated (R2>0.64), it appeared that 5 cm soil moisture series can better explain the variability of vegetation growth. A logarithmic transformation of soil moisture and precipitation data increased correlation with NDVI for the different time scales considered. Based on a monthly time scale we came out with a relationship between vegetation index and the couple soil moisture and precipitation [NDVI=a*Log(% soil moisture)+b*Log(Precipitation)+c] with R2>0.25 for each vegetation type. Further, we proposed to assess vegetation green-up using logistic regression model and transinformation entropy using the couple soil moisture and precipitation as independent variables and vegetation growth metrics (NDVI, NDVI ratio, NDVI slope) as the dependent variable. The study is still ongoing and the results will surely contribute to the knowledge in large scale vegetation monitoring. Keywords: Precipitation, soil moisture, vegetation growth, entropy Time scale, Logarithmic transformation and correlation between soil moisture and NDVI, precipitation and NDVI. The analysis is performed by combining both scenes 7 and 8 data. Schematic illustration of the two dimension transinformation entropy approach. T(P,SM;VI) stand for the transinformation contained in the couple soil moisture (SM)/precipitation (P) and explaining vegetation growth (VI).

Characterizing meteorological and hydrologic conditions associated with shallow landslide initiation in the coastal bluffs of the Atlantic Highlands, New Jersey

USGS Publications Warehouse

Ashland, Francis; Fiore, Alex R.; Reilly, Pamela A.; De Graff, Jerome V.; Shakoor, Abdul

2017-01-01

Meteorological and hydrologic conditions associated with shallow landslide initiation in the coastal bluffs of the Atlantic Highlands, New Jersey remain undocumented despite a history of damaging slope movement extending back to at least 1903. This study applies an empirical approach to quantify the rainfall conditions leading to shallow landsliding based on analysis of overlapping historical precipitation data and records of landslide occurrence, and uses continuous monitoring to quantify antecedent soil moisture and hydrologic response to rainfall events at two failure-prone hillslopes. Analysis of historical rainfall data reveals that both extended duration and cumulative rainfall amounts are critical characteristics of many landslide-inducing storms, and is consistent with current monitoring results that show notable increases in shallow soil moisture and pore-water pressure in continuous rainfall periods. Monitoring results show that shallow groundwater levels and soil moisture increase from annual lows in late summer-early fall to annual highs in late winter-early spring, and historical data indicate that shallow landslides occur most commonly from tropical cyclones in late summer through fall and nor’easters in spring. Based on this seasonality, we derived two provisional rainfall thresholds using a limited dataset of documented landslides and rainfall conditions for each season and storm type. A lower threshold for landslide initiation in spring corresponds with high antecedent moisture conditions, and higher rainfall amounts are required to induce shallow landslides during the drier soil moisture conditions in late summer-early fall.

Fiber Grating Environmental Sensing System

DOEpatents

Schulz, Whitten L.; Udd, Eric

2003-07-29

Fiber grating environmental measurement systems are comprised of sensors that are configured to respond to changes in moisture or chemical content of the surrounding medium through the action of coatings and plates inducing strain that is measured. These sensors can also be used to monitor the interior of bonds for degradation due to aging, cracking, or chemical attack. Means to multiplex these sensors at high speed and with high sensitivity can be accomplished by using spectral filters placed to correspond to each fiber grating environmental sensor. By forming networks of spectral elements and using wavelength division multiplexing arrays of fiber grating sensors may be processed in a single fiber line allowing distributed high sensitivity, high bandwidth fiber optic grating environmental sensor systems to be realized.

Optimality in Microwave-Assisted Drying of Aloe Vera ( Aloe barbadensis Miller) Gel using Response Surface Methodology and Artificial Neural Network Modeling

NASA Astrophysics Data System (ADS)

Das, Chandan; Das, Arijit; Kumar Golder, Animes

2016-10-01

The present work illustrates the Microwave-Assisted Drying (MWAD) characteristic of aloe vera gel combined with process optimization and artificial neural network modeling. The influence of microwave power (160-480 W), gel quantity (4-8 g) and drying time (1-9 min) on the moisture ratio was investigated. The drying of aloe gel exhibited typical diffusion-controlled characteristics with a predominant interaction between input power and drying time. Falling rate period was observed for the entire MWAD of aloe gel. Face-centered Central Composite Design (FCCD) developed a regression model to evaluate their effects on moisture ratio. The optimal MWAD conditions were established as microwave power of 227.9 W, sample amount of 4.47 g and 5.78 min drying time corresponding to the moisture ratio of 0.15. A computer-stimulated Artificial Neural Network (ANN) model was generated for mapping between process variables and the desired response. `Levenberg-Marquardt Back Propagation' algorithm with 3-5-1 architect gave the best prediction, and it showed a clear superiority over FCCD.

Monitoring and analysis of data obtained from moisture temperature recording stations : executive summary.

DOT National Transportation Integrated Search

2001-09-01

The performance of asphalt concrete pavements is in part affected by the seasonal variations of the resilient modulus of the AC layer and of the subgrade soil. To determine the variation of these parameters throughout Ohio, seven moisture-temperature...

Monitoring and analysis of data obtained from moisture temperature recording stations : final report.

DOT National Transportation Integrated Search

2001-09-01

The performance of asphalt concrete pavements is in part affected by the seasonal variations of the resilient modulus of the AC layer and of the subgrade soil. To determine the variation of these parameters throughout Ohio, seven moisture-temperature...

In-line monitoring of granule moisture in fluidized-bed dryers using microwave resonance technology.

PubMed

Buschmüller, Caroline; Wiedey, Wolfgang; Döscher, Claas; Dressler, Jochen; Breitkreutz, Jörg

2008-05-01

This is the first report on in-line moisture measurement of pharmaceutical products by microwave resonance technology. In order to meet the FDA's PAT approach, a microwave resonance sensor appropriate for pharmaceutical use was developed and implemented into two different fluidized-bed dryers. The novel sensor enables a continuous moisture measurement independent from the product density. Hence, for the first time precise real time determination of the moisture in pharmaceutical granules becomes possible. The qualification of the newly developed sensor was performed by drying placebo granules under experimental conditions and the validation using drug loaded granules under real process conditions. The results of the investigations show good correlations between water content of the granules determined by the microwave resonance sensor and both reference methods, loss on drying by infrared light exposure and Karl Fischer titration. Furthermore, a considerable time saving in the drying process was achieved through monitoring the residual water content continuously by microwave resonance technology instead of the formerly used discontinuous methods.

Prediction of properties of wheat dough using intelligent deep belief networks

NASA Astrophysics Data System (ADS)

Guha, Paramita; Bhatnagar, Taru; Pal, Ishan; Kamboj, Uma; Mishra, Sunita

2017-11-01

In this paper, the rheological and chemical properties of wheat dough are predicted using deep belief networks. Wheat grains are stored at controlled environmental conditions. The internal parameters of grains viz., protein, fat, carbohydrates, moisture, ash are determined using standard chemical analysis and viscosity of the dough is measured using Rheometer. Here, fat, carbohydrates, moisture, ash and temperature are considered as inputs whereas protein and viscosity are chosen as outputs. The prediction algorithm is developed using deep neural network where each layer is trained greedily using restricted Boltzmann machine (RBM) networks. The overall network is finally fine-tuned using standard neural network technique. In most literature, it has been found that fine-tuning is done using back-propagation technique. In this paper, a new algorithm is proposed in which each layer is tuned using RBM and the final network is fine-tuned using deep neural network (DNN). It has been observed that with the proposed algorithm, errors between the actual and predicted outputs are less compared to the conventional algorithm. Hence, the given network can be considered as beneficial as it predicts the outputs more accurately. Numerical results along with discussions are presented.

Dielectric characterization of Bentonite clay at various moisture contents and with mixtures of biomass in the microwave spectrum

USDA-ARS?s Scientific Manuscript database

This study assesses the potential for using bentonite as a microwave absorber for microwave-assisted biomass pyrolysis based on the dielectric properties. Dielectric properties of bentonite at different moisture contents were measured using a coaxial line dielectric probe and vector network analyzer...

Multi-time scale analysis of the spatial representativeness of in situ soil moisture data within satellite footprints

USDA-ARS?s Scientific Manuscript database

We conduct a novel comprehensive investigation that seeks to prove the connection between spatial and time scales in surface soil moisture (SM) within the satellite footprint (~50 km). Modeled and measured point series at Yanco and Little Washita in situ networks are first decomposed into anomalies ...

Using Landsat digital data to detect moisture stress in corn-soybean growing regions

NASA Technical Reports Server (NTRS)

Thompson, D. R.; Wehmanen, O. A.

1980-01-01

As a part of a follow-on study to the moisture stress detection effort conducted in the Large Area Crop Inventory Experiment (LACIE), a technique utilizing transformed Landsat digital data was evaluated for detecting moisture stress in humid growing regions using sample segments from Iowa, Illinois, and Indiana. At known growth stages of corn and soybeans, segments were classified as undergoing moisture stress or not undergoing stress. The remote-sensing-based information was compared to a weekly ground-based index (Crop Moisture Index). This comparison demonstrated that the remote sensing technique could be used to monitor the growing conditions within a region where corn and soybeans are the major crop.

Short-term thermal stability of transformer and motor oils at wide range of moisture contents

NASA Astrophysics Data System (ADS)

Volosnikov, D. V.; Povolotskiy, I. I.; Skripov, P. V.

2018-01-01

Method of controlled pulse heating of a wire probe was used for studying heat transfer and thermal stability of energy oils and motor oils in the presence of low quantities of moisture. The technique of two-pulse heating is the most suitable method for monitoring the actual state of oils. A distinct signal-response accompanying the appearance of moisture in the tested sample has been revealed.

Evaluation of the cosmic-ray neutron method for measuring integral soil moisture dynamics of a forested head water catchment

NASA Astrophysics Data System (ADS)

Bogena, H. R.; Metzen, D.; Baatz, R.; Hendricks Franssen, H.; Huisman, J. A.; Montzka, C.; Vereecken, H.

2011-12-01

Measurements of low-energy secondary neutron intensity above the soil surface by cosmic-ray soil moisture probes (CRP) can be used to estimate soil moisture content. CRPs utilise the fact that high-energy neutrons initiated by cosmic rays are moderated (slowed to lower energies) most effectively by collisions with hydrogen atoms contained in water molecules in the soil. The conversion of neutron intensity to soil moisture content can potentially be complicated because neutrons are also moderated by aboveground water storage (e.g. vegetation water content, canopy storage of interception). Recently, it was demonstrated experimentally that soil moisture content derived from CRP measurements agrees well with average moisture content from gravimetric soil samples taken within the footprint of the cosmic ray probe, which is proposed to be up to several hundred meters in size [1]. However, the exact extension and shape of the CRP integration footprint is still an open question and it is also unclear how CRP measurements are affected by the soil moisture distribution within the footprint both in horizontal and vertical directions. In this paper, we will take advantage of an extensive wireless soil moisture sensor network covering most of the estimated footprint of the CRP. The network consists of 150 nodes and 900 soil moisture sensors which were installed in the small forested Wüstebach catchment (~27 ha) in the framework of the Transregio32 and the Helmholtz initiative TERENO (Terrestrial Environmental Observatories) [2]. This unique soil moisture data set provides a consistent picture of the hydrological status of the catchment in a high spatial and temporal resolution and thus the opportunity to evaluate the CRP measurements in a rigorous way. We will present first results of the comparison with a specific focus on the sensitivity of the CRP measurements to soil moisture variation in both the horizontal and vertical direction. Furthermore, the influence of forest biomass and shallow groundwater table fluctuations on the attenuation of cosmic-ray neutrons will be considered.

An Extended Kriging Method to Interpolate Near-Surface Soil Moisture Data Measured by Wireless Sensor Networks

PubMed Central

Zhang, Jialin; Li, Xiuhong; Yang, Rongjin; Liu, Qiang; Zhao, Long; Dou, Baocheng

2017-01-01

In the practice of interpolating near-surface soil moisture measured by a wireless sensor network (WSN) grid, traditional Kriging methods with auxiliary variables, such as Co-kriging and Kriging with external drift (KED), cannot achieve satisfactory results because of the heterogeneity of soil moisture and its low correlation with the auxiliary variables. This study developed an Extended Kriging method to interpolate with the aid of remote sensing images. The underlying idea is to extend the traditional Kriging by introducing spectral variables, and operating on spatial and spectral combined space. The algorithm has been applied to WSN-measured soil moisture data in HiWATER campaign to generate daily maps from 10 June to 15 July 2012. For comparison, three traditional Kriging methods are applied: Ordinary Kriging (OK), which used WSN data only, Co-kriging and KED, both of which integrated remote sensing data as covariate. Visual inspections indicate that the result from Extended Kriging shows more spatial details than that of OK, Co-kriging, and KED. The Root Mean Square Error (RMSE) of Extended Kriging was found to be the smallest among the four interpolation results. This indicates that the proposed method has advantages in combining remote sensing information and ground measurements in soil moisture interpolation. PMID:28617351

Runoff and recharge processes under a strong semi-arid climatic gradient

NASA Astrophysics Data System (ADS)

Ries, F.; Lange, J.; Sauter, M.; Schmidt, S.

2012-04-01

Hydrological processes in semi-arid environments are highly dynamic. In the eastern slopes of the West Bank these dynamics are even intensified due to the predominant karst morphology, the strong climatic gradient (150-700 mm mean annual precipitation) and the small-scale variability of land use, topography and soil cover. The region is characterized by a scarcity in water resources and a high population growth. Therefore detailed information about the temporal and spatial distribution, amount and variability of available water resources is required. Providing this information by the use of hydrological models is challenging, because available data are extremely limited. From 2007 on, the research area of Wadi Auja, northeast of Jerusalem, has been instrumented with a dense monitoring network. Rainfall distribution and climatic parameters as well as the hydrological reaction of the system along the strong semi-arid climatic gradient are measured on the plot (soil moisture), hillslope (runoff generation) and catchment scale (spring discharge, groundwater level, flood runoff). First data from soil moisture plots situated along the climatic gradient are presented. They allow insights into physical properties of the soil layer and its impact on runoff and recharge processes under different climatic conditions. From continuous soil moisture profiles, soil water balances are calculated for singe events and entire seasons. These data will be used to parameterize the distributed hydrological model TRAIN-ZIN, which has been successfully applied in several studies in the Jordan River Basin.

Global and Regional Real-time Systems for Flood and Drought Monitoring and Prediction

NASA Astrophysics Data System (ADS)

Hong, Y.; Gourley, J. J.; Xue, X.; Flamig, Z.

2015-12-01

A Hydrometeorological Extreme Mapping and Prediction System (HyXtreme-MaP), initially built upon the Coupled Routing and Excess STorage (CREST) distributed hydrological model, is driven by real-time quasi-global TRMM/GPM satellites and by the US Multi-Radar Multi-Sensor (MRMS) radar network with dual-polarimetric upgrade to simulate streamflow, actual ET, soil moisture and other hydrologic variables at 1/8th degree resolution quasi-globally (http://eos.ou.edu) and at 250-meter 2.5-mintue resolution over the Continental United States (CONUS: http://flash.ou.edu).­ Multifaceted and collaborative by-design, this end-to-end research framework aims to not only integrate data, models, and applications but also brings people together (i.e., NOAA, NASA, University researchers, and end-users). This presentation will review the progresses, challenges and opportunities of such HyXTREME-MaP System used to monitor global floods and droughts, and also to predict flash floods over the CONUS.

Monitoring of the secondary drying in freeze-drying of pharmaceuticals.

PubMed

Fissore, Davide; Pisano, Roberto; Barresi, Antonello A

2011-02-01

This paper is focused on the in-line monitoring of the secondary drying phase of a lyophilization process. An innovative software sensor is presented to estimate reliably the residual moisture in the product and the time required to complete secondary drying, that is, to reach the target value of the residual moisture or of the desorption rate. Such results are obtained by coupling a mathematical model of the process and the in-line measurement of the solvent desorption rate and by means of the pressure rise test or another sensors (e.g., windmills, laser sensors) that can measure the vapor flux in the drying chamber. The proposed method does not require extracting any vial during the operation or using expensive sensors to measure off-line the residual moisture. Moreover, it does not require any preliminary experiment to determine the relationship between the desorption rate and residual moisture in the product. The effectiveness of the proposed approach is demonstrated by means of experiments carried out in a pilot-scale apparatus: in this case, some vials were extracted from the drying chamber and the moisture content was measured to validate the estimations provided by the soft-sensor. Copyright © 2010 Wiley-Liss, Inc.

Hyphenation of Raman spectroscopy with gravimetric analysis to interrogate water-solid interactions in pharmaceutical systems.

PubMed

Gift, Alan D; Taylor, Lynne S

2007-01-04

A moisture sorption gravimetric analyzer has been combined with a Raman spectrometer to better understand the various modes of water-solid interactions relevant to pharmaceutical systems. A commercial automated moisture sorption balance was modified to allow non-contact monitoring of the sample properties by interfacing a Raman probe with the sample holder. This hybrid instrument allows for gravimetric and spectroscopic changes to be monitored simultaneously. The utility of this instrument was demonstrated by investigating different types of water-solid interactions including stoichiometric and non-stoichiometric hydrate formation, deliquescence, amorphous-crystalline transformation, and capillary condensation. In each of the model systems, sulfaguanidine, cromolyn sodium, ranitidine HCl, amorphous sucrose and silica gel, spectroscopic changes were observed during the time course of the moisture sorption profile. Analysis of spectroscopic data provided information about the origin of the observed changes in moisture content as a function of relative humidity. Furthermore, multivariate data analysis techniques were employed as a means of processing the spectroscopic data. Principle components analysis was found to be useful to aid in data processing, handling and interpretation of the spectral changes that occurred during the time course of the moisture sorption profile.

SMAP Validation Experiment 2015 (SMAPVEX15)

NASA Astrophysics Data System (ADS)

Colliander, A.; Jackson, T. J.; Cosh, M. H.; Misra, S.; Crow, W. T.; Chae, C. S.; Moghaddam, M.; O'Neill, P. E.; Entekhabi, D.; Yueh, S. H.

2015-12-01

NASA's (National Aeronautics and Space Administration) Soil Moisture Active Passive (SMAP) mission was launched in January 2015. The objective of the mission is global mapping of soil moisture and freeze/thaw state. For soil moisture algorithm validation, the SMAP project and NASA coordinated SMAPVEX15 around the Walnut Gulch Experimental Watershed (WGEW) in Tombstone, Arizona on August 1-19, 2015. The main goals of SMAPVEX15 are to understand the effects and contribution of heterogeneity on the soil moisture retrievals, evaluate the impact of known RFI sources on retrieval, and analyze the brightness temperature product calibration and heterogeneity effects. Additionally, the campaign aims to contribute to the validation of GPM (Global Precipitation Mission) data products. The campaign will feature three airborne microwave instruments: PALS (Passive Active L-band System), UAVSAR (Uninhabited Aerial Vehicle Synthetic Aperture Radar) and AirMOSS (Airborne Microwave Observatory of Subcanopy and Subsurface). PALS has L-band radiometer and radar, and UAVSAR and AirMOSS have L- and P-band synthetic aperture radars, respectively. The PALS instrument will map the area on seven days coincident with SMAP overpasses; UAVSAR and AirMOSS on four days. WGEW was selected as the experiment site due to the rainfall patterns in August and existing dense networks of precipitation gages and soil moisture sensors. An additional temporary network of approximately 80 soil moisture stations was deployed in the region. Rainfall observations were supplemented with two X-band mobile scanning radars, approximately 25 tipping bucket rain gauges, three laser disdrometers, and three vertically-profiling K-band radars. Teams were on the field to take soil moisture samples for gravimetric soil moisture, bulk density and rock fraction determination as well as to measure surface roughness and vegetation water content. In this talk we will present preliminary results from the experiment including comparisons between SMAP and PALS soil moisture retrievals with respect to the in situ measurements. Acknowledgement: This work was carried out in part at Jet Propulsion Laboratory, California Institute of Technology under contract with National Aeronautics and Space Administration.

Estimating the spatial distribution of soil moisture based on Bayesian maximum entropy method with auxiliary data from remote sensing

NASA Astrophysics Data System (ADS)

Gao, Shengguo; Zhu, Zhongli; Liu, Shaomin; Jin, Rui; Yang, Guangchao; Tan, Lei

2014-10-01

Soil moisture (SM) plays a fundamental role in the land-atmosphere exchange process. Spatial estimation based on multi in situ (network) data is a critical way to understand the spatial structure and variation of land surface soil moisture. Theoretically, integrating densely sampled auxiliary data spatially correlated with soil moisture into the procedure of spatial estimation can improve its accuracy. In this study, we present a novel approach to estimate the spatial pattern of soil moisture by using the BME method based on wireless sensor network data and auxiliary information from ASTER (Terra) land surface temperature measurements. For comparison, three traditional geostatistic methods were also applied: ordinary kriging (OK), which used the wireless sensor network data only, regression kriging (RK) and ordinary co-kriging (Co-OK) which both integrated the ASTER land surface temperature as a covariate. In Co-OK, LST was linearly contained in the estimator, in RK, estimator is expressed as the sum of the regression estimate and the kriged estimate of the spatially correlated residual, but in BME, the ASTER land surface temperature was first retrieved as soil moisture based on the linear regression, then, the t-distributed prediction interval (PI) of soil moisture was estimated and used as soft data in probability form. The results indicate that all three methods provide reasonable estimations. Co-OK, RK and BME can provide a more accurate spatial estimation by integrating the auxiliary information Compared to OK. RK and BME shows more obvious improvement compared to Co-OK, and even BME can perform slightly better than RK. The inherent issue of spatial estimation (overestimation in the range of low values and underestimation in the range of high values) can also be further improved in both RK and BME. We can conclude that integrating auxiliary data into spatial estimation can indeed improve the accuracy, BME and RK take better advantage of the auxiliary information compared to Co-OK, and BME outperforms RK by integrating the auxiliary data in a probability form.

Soil Moisture Remote Sensing: Status and Outlook

USDA-ARS?s Scientific Manuscript database

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

40 CFR 264.1085 - Standards: Surface impoundments.

Code of Federal Regulations, 2014 CFR

2014-07-01

... effects of outdoor exposure to wind, moisture, and sunlight; and the operating practices used for the... outdoor exposure to wind, moisture, and sunlight; and the operating practices used for the surface... condition. (3) The owner or operator shall inspect and monitor the air emission control equipment in...

40 CFR 265.1086 - Standards: Surface impoundments.

Code of Federal Regulations, 2013 CFR

2013-07-01

... effects of outdoor exposure to wind, moisture, and sunlight; and the operating practices used for the... outdoor exposure to wind, moisture, and sunlight; and the operating practices used for the surface... unsafe condition. (3) The owner or operator shall inspect and monitor the air emission control equipment...

40 CFR 264.1085 - Standards: Surface impoundments.

Code of Federal Regulations, 2012 CFR

2012-07-01

... effects of outdoor exposure to wind, moisture, and sunlight; and the operating practices used for the... outdoor exposure to wind, moisture, and sunlight; and the operating practices used for the surface... condition. (3) The owner or operator shall inspect and monitor the air emission control equipment in...

40 CFR 265.1086 - Standards: Surface impoundments.

Code of Federal Regulations, 2014 CFR

2014-07-01

... effects of outdoor exposure to wind, moisture, and sunlight; and the operating practices used for the... outdoor exposure to wind, moisture, and sunlight; and the operating practices used for the surface... unsafe condition. (3) The owner or operator shall inspect and monitor the air emission control equipment...

40 CFR 265.1086 - Standards: Surface impoundments.

Code of Federal Regulations, 2012 CFR

2012-07-01

... effects of outdoor exposure to wind, moisture, and sunlight; and the operating practices used for the... outdoor exposure to wind, moisture, and sunlight; and the operating practices used for the surface... unsafe condition. (3) The owner or operator shall inspect and monitor the air emission control equipment...

40 CFR 264.1085 - Standards: Surface impoundments.

Code of Federal Regulations, 2013 CFR

2013-07-01

... effects of outdoor exposure to wind, moisture, and sunlight; and the operating practices used for the... outdoor exposure to wind, moisture, and sunlight; and the operating practices used for the surface... condition. (3) The owner or operator shall inspect and monitor the air emission control equipment in...

40 CFR 264.1085 - Standards: Surface impoundments.

Code of Federal Regulations, 2011 CFR

2011-07-01

... effects of outdoor exposure to wind, moisture, and sunlight; and the operating practices used for the... outdoor exposure to wind, moisture, and sunlight; and the operating practices used for the surface... condition. (3) The owner or operator shall inspect and monitor the air emission control equipment in...

40 CFR 265.1086 - Standards: Surface impoundments.

Code of Federal Regulations, 2011 CFR

2011-07-01

... effects of outdoor exposure to wind, moisture, and sunlight; and the operating practices used for the... outdoor exposure to wind, moisture, and sunlight; and the operating practices used for the surface... unsafe condition. (3) The owner or operator shall inspect and monitor the air emission control equipment...

Multi-proxy monitoring approaches at Kangaroo Island, South Australia

NASA Astrophysics Data System (ADS)

Dixon, Bronwyn; Drysdale, Russell; Tyler, Jonathan; Goodwin, Ian

2017-04-01

Interpretations of geochemical signals preserved in young speleothems are greatly enhanced by comprehensive cave-site monitoring. In the light of this, a cave monitoring project is being conducted concurrently with the development of a new palaeoclimate record from Kelly Hill Cave (Kangaroo Island, South Australia). The site is strategically located because it is situated between longer-lived monitoring sites in southeastern and southwestern Australia, as well as being climatically 'upstream' from major population and agricultural centres. This study aims to understand possible controls on speleothem δ18O in Kelly Hill Cave through i. identification of local and regional δ18O drivers in precipitation; and ii. preservation and modification of climatic signals within the epikarst as indicated by dripwater δ18O. These aims are achieved through analysis of a five-year daily rainfall (amount and δ18O) dataset in conjunction with in-cave drip monitoring. Drivers of precipitation δ18O were identified through linear regression between δ18O values and local meteorological variables, air-parcel back trajectories, and synoptic-typing. Synoptically driven moisture sources were identified through the use of NCEP/NCAR climate reanalysis sea-level pressure, precipitable moisture, and outgoing longwave radiation data in order to trace moisture sources and travel mechanisms from surrounding ocean basins. Local controls on δ18O at Kelly Hill Cave are consistent with published interpretations of southern Australia sites, with oxygen isotopes primarily controlled by rainfall amount on both daily and monthly time scales. Back-trajectory analysis also supports previous observations that the Southern Ocean is the major source for moisture-bearing cold-front systems. However, synoptic typing of daily rainfall δ18O and amount extremes reveals a previously unreported tropical connection and moisture source. This tropical connection appears to be strongest in summer and autumn, but exists throughout the year. This indicates that a wider range of precipitation data sources can be combined to present a more comprehensive understanding of moisture dynamics and interaction of synoptic conditions to drive rainfall geochemistry. Within the cave environment at Kelly Hill Cave there is high spatial variability in drip characteristics, both in terms of drip frequency and drip water δ18O. Ongoing analyses are aimed at determining if monthly and/or seasonal rainfall δ18O drivers are also reflected in dripwater values. Overall, Kangaroo Island presents a new location to investigate the interplay between tropical and temperate influences in southern Australia, as well as a location for east - west comparisons between monitoring sites across southern Australia.

Development of a SMAP-Based Drought Monitoring Product

NASA Astrophysics Data System (ADS)

Sadri, S.; Wood, E. F.; Pan, M.; Lettenmaier, D. P.

2016-12-01

Agricultural drought is defined as a deficit in the amount of soil moisture over a prolonged period of time. Soil moisture information over time and space provides critical insight for agricultural management, including both water availability for crops and moisture conditions that affect management practices such as fertilizer, pesticide applications, and their impact as non-point pollution runoff. Since April of 2015, NASA's Soil Moisture Active Passive (SMAP) mission has retrieved soil moisture using L-band passive radiometric measurements at a 8 day repeat orbit with a swath of 1000 km that maps the Earth in 2-3 days depending on locations. Of particular interest to SMAP-based agricultural applications is a monitoring product that assesses the SMAP soil moisture in terms of probability percentiles for dry (drought) or wet (pluvial) conditions. SMAP observations do result in retrievals that are spatially and temporally discontinuous. Additionally, the short SMAP record length provides a statistical challenge in estimating a drought index and thus drought risk evaluations. In this presentation, we describe a SMAP drought index for the CONUS region based on near-surface soil moisture percentiles. Because the length of the SMAP data record is limited, we use a Bayesian conditional probability approach to extend the SMAP record back to 1979 based on simulated soil moisture of the same period from the Variable Infiltration Capacity (VIC) Land Surface Model (LSM), simulated by Princeton University. This is feasible because the VIC top soil layer (10 cm) is highly correlated with the SMAP 36 km passive microwave during 2015-2016, with more than half the CONUS grids having a cross-correlation greater than 0.6, and over 0.9 in many regions. Given the extended SMAP record, we construct an empirical probability distribution of near-surface soil moisture drought index showing severities similar to those used by the U.S. Drought Monitor (from D0-D4), for a specific SMAP observation. The analysis is done for each of the 8,150 SMAP grids covering the CONUS domain. Comparisons between the SMAP drought index and that from the VIC LSM are presented for selected recent drought events. Issues such as seasonality, robustness of the fitting, regions of poor SMAP-VIC correlations, and extensions to other areas will be discussed.

Land surface dynamics monitoring using microwave passive satellite sensors

NASA Astrophysics Data System (ADS)

Guijarro, Lizbeth Noemi

Soil moisture, surface temperature and vegetation are variables that play an important role in our environment. There is growing demand for accurate estimation of these geophysical parameters for the research of global climate models (GCMs), weather, hydrological and flooding models, and for the application to agricultural assessment, land cover change, and a wide variety of other uses that meet the needs for the study of our environment. The different studies covered in this dissertation evaluate the capabilities and limitations of microwave passive sensors to monitor land surface dynamics. The first study evaluates the 19 GHz channel of the SSM/I instrument with a radiative transfer model and in situ datasets from the Illinois stations and the Oklahoma Mesonet to retrieve land surface temperature and surface soil moisture. The surface temperatures were retrieved with an average error of 5 K and the soil moisture with an average error of 6%. The results show that the 19 GHz channel can be used to qualitatively predict the spatial and temporal variability of surface soil moisture and surface temperature at regional scales. In the second study, in situ observations were compared with sensor observations to evaluate aspects of low and high spatial resolution at multiple frequencies with data collected from the Southern Great Plains Experiment (SGP99). The results showed that the sensitivity to soil moisture at each frequency is a function of wavelength and amount of vegetation. The results confirmed that L-band is more optimal for soil moisture, but each sensor can provide soil moisture information if the vegetation water content is low. The spatial variability of the emissivities reveals that resolution suffers considerably at higher frequencies. The third study evaluates C- and X-bands of the AMSR-E instrument. In situ datasets from the Soil Moisture Experiments (SMEX03) in South Central Georgia were utilized to validate the AMSR-E soil moisture product and to derive surface soil moisture with a radiative transfer model. The soil moisture was retrieved with an average error of 2.7% at X-band and 6.7% at C-band. The AMSR-E demonstrated its ability to successfully infer soil moisture during the SMEX03 experiment.

Trends in Soil Moisture Reflect More Than Slope Position: Soils on San Cristóbal Island, Galápagos as a Case Study

NASA Astrophysics Data System (ADS)

Percy, M.; Singha, K.; Benninger, L. K.; Riveros-Iregui, D. A.; Mirus, B. B.

2015-12-01

The spatial and temporal distribution of soil moisture in tropical critical zones depends upon a number of variables including topographic position, soil texture, overlying vegetation, and local microclimates. We investigate the influences on soil moisture on a tropical basaltic island (San Cristóbal, Galápagos) across a variety of microclimates during the transition from the wetter to the drier season. We used multiple approaches to characterize spatial and temporal patterns in soil moisture at four sites across microclimates ranging from arid to very humid. The microclimates on San Cristóbal vary with elevation, so our monitoring includes two sites in the transitional zone at lower elevations, one in the humid zone at moderate elevations, and one in the very humid zone in higher elevations. We made over 250 near-surface point measurements per site using a Hydrosense II probe, and estimated the lateral variability in soil moisture across each site with an EM-31 electrical conductivity meter. We also monitored continuous time-series of in-situ soil moisture dynamics using three nested TDR probes collocated with meteorological stations at each of the sites. Preliminary analysis indicates that soils in the very humid zone have lower electrical conductivities across all the hillslopes as compared to the humid and transitional zones, which suggests that additional factors beyond climate and slope position are important. While soil texture across the very humid site is fairly uniform, variations in vegetation have a strong control on soil moisture patterns. At the remaining sites the vegetation patterns also have a very strong local influence on soil moisture, but correlation between the depth to clay layers and soil moisture patterns suggests that mineralogy is also important. Our findings suggest that the microclimatic setting is a crucial consideration for understanding relations between vegetation, soil texture, and soil-moisture dynamics in tropical critical zones.

Preferential flows and soil moistures on a Benggang slope: Determined by the water and temperature co-monitoring

NASA Astrophysics Data System (ADS)

Tao, Yu; He, Yangbo; Duan, Xiaoqian; Zou, Ziqiang; Lin, Lirong; Chen, Jiazhou

2017-10-01

Soil preferential flow (PF) has important effects on rainfall infiltration, moisture distribution, and hydrological and ecological process; but it is very difficult to monitor and characterize on a slope. In this paper, soil water and soil temperature at 20, 40, 60, 80 cm depths in six positions were simultaneously monitored at high frequency to confirm the occurrence of PF at a typical Benggang slope underlain granite residual deposits, and to determine the interaction of soil moisture distribution and Benggang erosion. In the presence of PF, the soil temperature was first (half to one hour) governed by the rainwater temperature, then (more than one hour) governed by the upper soil temperature; in the absence of PF (only matrix flow, MF), the soil temperature was initially governed by the upper soil temperature, then by the rainwater temperature. The results confirmed the water replacement phenomenon in MF, thus it can be distinguished from PF by additional temperature monitoring. It indicates that high frequency moisture and temperature monitoring can determine the occurrence of PF and reveal the soil water movement. The distribution of soil water content and PF on the different positions of the slope showed that a higher frequency of PF resulted in a higher variation of average of water content. The frequency of PF at the lower position can be three times as that of the upper position, therefore, the variation coefficient of soil water content increased from 4.67% to 12.68% at the upper position to 8.18%-33.12% at the lower position, where the Benggang erosion (soil collapse) was more possible. The results suggest strong relationships between PF, soil water variation, and collapse activation near the Benggang wall.

Soil moisture status estimation over Three Gorges area with Landsat TM data based on temperature vegetation dryness index

NASA Astrophysics Data System (ADS)

Xu, Lina; Niu, Ruiqing; Li, Jiong; Dong, Yanfang

2011-12-01

Soil moisture is the important indicator of climate, hydrology, ecology, agriculture and other parameters of the land surface and atmospheric interface. Soil moisture plays an important role on the water and energy exchange at the land surface/atmosphere interface. Remote sensing can provide information on large area quickly and easily, so it is significant to do research on how to monitor soil moisture by remote sensing. This paper presents a method to assess soil moisture status using Landsat TM data over Three Gorges area in China based on TVDI. The potential of Temperature- Vegetation Dryness Index (TVDI) from Landsat TM data in assessing soil moisture was investigated in this region. After retrieving land surface temperature and vegetation index a TVDI model based on the features of Ts-NDVI space is established. And finally, soil moisture status is estimated according to TVDI. It shows that TVDI has the advantages of stability and high accuracy to estimating the soil moisture status.

Evaluating Land-Atmosphere Interactions with the North American Soil Moisture Database

NASA Astrophysics Data System (ADS)

Giles, S. M.; Quiring, S. M.; Ford, T.; Chavez, N.; Galvan, J.

2015-12-01

The North American Soil Moisture Database (NASMD) is a high-quality observational soil moisture database that was developed to study land-atmosphere interactions. It includes over 1,800 monitoring stations the United States, Canada and Mexico. Soil moisture data are collected from multiple sources, quality controlled and integrated into an online database (soilmoisture.tamu.edu). The period of record varies substantially and only a few of these stations have an observation record extending back into the 1990s. Daily soil moisture observations have been quality controlled using the North American Soil Moisture Database QAQC algorithm. The database is designed to facilitate observationally-driven investigations of land-atmosphere interactions, validation of the accuracy of soil moisture simulations in global land surface models, satellite calibration/validation for SMOS and SMAP, and an improved understanding of how soil moisture influences climate on seasonal to interannual timescales. This paper provides some examples of how the NASMD has been utilized to enhance understanding of land-atmosphere interactions in the U.S. Great Plains.

A soil moisture index derived from thermal infrared sensor on-board geostationary satellites over Europe, Africa and Australia

NASA Astrophysics Data System (ADS)

Ghilain, Nicolas; Trigo, Isabel; Arboleda, Alirio; Barrios, Jose-Miguel; Batelaan, Okke; Gellens-Meulenberghs, Françoise

2017-04-01

Soil moisture plays a central role in the water cycle. In particular, it is a major component which variability controls the evapotranspiration process. Over the past years, there has been a large commitment of the remote sensing research community to develop satellites and retrieval algorithm for soil moisture monitoring over continents. Most of those rely on the observation in the microwave lengths, making use either of passive, active or both methods combined. However, the available derived products are given at a relatively low spatial resolution for applications at the kilometer scale over entire continents, and with a revisit time that may not be adequate for all applications, as for example agriculture. Thermal infrared observations from a combination of geostationary satellites offer a global view of continents every hour (or even at higher frequency) at a few kilometers resolution, which makes them attractive as another, and potentially complementary, source of information of surface soil moisture. In this study, the Copernicus LST and the LSA-SAF LST are used to derive soil moisture over entire continents (Europe, Africa, Australia). The derived soil moisture is validated against in-situ observations and compared to other available products from remote sensing (SMOS, ASCAT) and from numerical weather prediction (ECMWF). We will present the result of this validation, and will show how it could be used in continental scale evapotranspiration monitoring.

Post-Closure Inspection and Monitoring Report for Corrective Action Unit 110: Area 3 WMD U-3ax/bl Crater, Nevada Test Site, Nevada, For the Period July 2007-June 2008

DOE Office of Scientific and Technical Information (OSTI.GOV)

NSTec Environmental Restoration

2008-08-01

This Post-Closure Inspection and Monitoring Report (PCIMR) provides the results of inspections and monitoring for Corrective Action Unit (CAU) 110, Area 3 WMD [Waste Management Division] U-3ax/bl Crater. This PCIMR includes an analysis and summary of the site inspections, repairs and maintenance, meteorological information, and soil moisture monitoring data obtained at CAU 110 for the period July 2007 through June 2008. Site inspections of the cover were performed quarterly to identify any significant changes to the site requiring action. The overall condition of the cover, perimeter fence, and use restriction (UR) warning signs was good. However, settling was observed thatmore » exceeded the action level as specified in Section VII.B.7 of the Hazardous Waste Permit Number NEV HW021 (Nevada Division of Environmental Protection, 2005). This permit states that cracks or settling greater than 15 centimeters (6 inches) deep that extend 1.0 meter (m) (3 feet [ft]) or more on the cover will be evaluated and repaired within 60 days of detection. Two areas of settling and cracks were observed on the south and east edges of the cover during the September 2007 inspection that exceeded the action level and required repair. The areas were repaired in October 2007. Additional settling and cracks were observed along the east side of the cover during the December 2007 inspection that exceeded the action level, and the area was repaired in January 2008. Significant animal burrows were also observed during the March 2008 inspection, and small mammal trapping and relocation was performed in April 2008. The semiannual subsidence surveys were performed in September 2007 and March 2008. No significant subsidence was observed in the survey data. Monument 5 shows the greatest amount of subsidence (-0.02 m [-0.08 ft] compared to the baseline survey of 2000). This amount is negligible and near the resolution of the survey instruments; it does not indicate that subsidence is occurring overall on the cover. Soil moisture results obtained to date indicate that the CAU 110 cover is performing well. Time Domain Reflectometry (TDR) data show regular changes in the shallow subsurface with significant rain events; however, major changes in volumetric moisture content (VMC) appear to be limited to 1.8 m (6 ft) below ground surface or shallower, depending on the location on the cover. At 2.4 m (8 ft) below the cover surface, TDR data show soil moisture content remained between 9 and 15 percent VMC, depending on the TDR location. The west portion of the cover tends to reflect a lower moisture content and less variability in annual fluctuations in moisture content at this depth. Results of soil moisture monitoring of the cover indicate that VMC at the compliance level (at 2.4 m [8 ft] below the cover surface) is approaching a steady state. If the moisture content at this level remains consistent with recent years, then a recommendation may be made for establishing compliance levels for future monitoring.« less

The use of LANDSAT digital data to detect and monitor vegetation water deficiencies. [South Dakota

NASA Technical Reports Server (NTRS)

Thompson, D. R.; Wehmanen, O. A.

1977-01-01

A technique devised using a vector transformation of LANDSAT digital data to indicate when vegetation is undergoing moisture stress is described. A relation established between the remote sensing-based criterion (the Green Index Number) and a ground-based criterion (Crop Moisture Index) is discussed.

30 CFR 27.41 - Test to determine resistance to moisture.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Test to determine resistance to moisture. 27.41 Section 27.41 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS METHANE-MONITORING SYSTEMS Test Requirements § 27.41 Test to...

Technical note: Equilibrium moisture content of kabuli chickpea, black sesame, and white sesame seeds

USDA-ARS?s Scientific Manuscript database

Sesame and chickpeas are important crops for Ethiopia as both are major exports providing small farmers and the country much revenue. There is a lack of information on fundamental equilibrium moisture content (EMC) relationships for these products which would help facilitate better monitoring and st...

Drought index driven by L-band microwave soil moisture data

NASA Astrophysics Data System (ADS)

Bitar, Ahmad Al; Kerr, Yann; Merlin, Olivier; Cabot, François; Choné, Audrey; Wigneron, Jean-Pierre

2014-05-01

Drought is considered in many areas across the globe as one of the major extreme events. Studies do not all agree on the increase of the frequency of drought events over the past 60 years [1], but they all agree that the impact of droughts has increased and the need for efficient global monitoring tools has become most than ever urgent. Droughts are monitored through drought indexes, many of which are based on precipitation (Palmer index(s), PDI…), on vegetation status (VDI) or on surface temperatures. They can also be derived from climate prediction models outputs. The GMO has selected the (SPI) Standardized Precipitation Index as the reference index for the monitoring of drought at global scale. The drawback of this index is that it is directly dependent on global precipitation products that are not accurate over global scale. On the other hand, Vegetation based indexes show the a posteriori effect of drought, since they are based on NDVI. In this study, we choose to combine the surface soil moisture from microwave sensor with climate data to access a drought index. The microwave data are considered from the SMOS (Soil Moisture and Ocean Salinity) mission at L-Band (1.4 Ghz) interferometric radiometer from ESA (European Space Agency) [2]. Global surface soil moisture maps with 3 days coverage for ascending 6AM and descending 6PM orbits SMOS have been delivered since January 2010 at a 40 km nominal resolution. We use in this study the daily L3 global soil moisture maps from CATDS (Centre Aval de Traitement des Données SMOS) [3,4]. We present a drought index computed by a double bucket hydrological model driven by operational remote sensing data and ancillary datasets. The SPI is also compared to other drought indicators like vegetation indexes and Palmer drought index. Comparison of drought index to vegetation indexes from AVHRR and MODIS over continental United States show that the drought index can be used as an early warning system for drought monitoring as the water shortage can be sensed several weeks before the vegetation dryness occures. Keywords: SMOS, microwave, level 4, soil moisture, drought, precipitation, hydrological model, vegetation index

Automation of peanut drying with a sensor network including an in-shell kernel moisture sensor

USDA-ARS?s Scientific Manuscript database

Peanut drying is an essential task in the processing and handling of peanuts. Peanuts leave the fields with kernel moisture contents > 20% wet basis and need to be dried to < 10.5% w.b. for grading and storage purposes. Current peanut drying processes utilize decision support software based on model...

Soil moisture at local scale: Measurements and simulations

NASA Astrophysics Data System (ADS)

Romano, Nunzio

2014-08-01

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

Moisture variation associated with water input and evaporation during sewage sludge bio-drying.

PubMed

Cai, Lu; Gao, Ding; Chen, Tong-Bin; Liu, Hong-Tao; Zheng, Guo-Di; Yang, Qi-Wei

2012-08-01

The variation of moisture during sewage sludge bio-drying was investigated. In situ measurements were conducted to monitor the bulk moisture and water vapor, while the moisture content, water generation, water evaporation and aeration water input of the bio-drying bulk were calculated based on the water mass balance. The moisture in the sewage sludge bio-drying material decreased from 66% to 54% in response to control technology for bio-drying. During the temperature increasing and thermophilic phases of sewage sludge bio-drying, the moisture content, water generation and water evaporation of the bulk initially increased and then decreased. The peak water generation and evaporation occurred during the thermophilic phase. During the bio-drying, water evaporation was much greater than water generation, and aeration facilitated the water evaporation. Copyright © 2012. Published by Elsevier Ltd.

Wireless sensor networks to assess the impacts of global change in Sierra Nevada (Spain) mountains

NASA Astrophysics Data System (ADS)

Sánchez-Cano, Francisco M.; Bonet-García, Francisco J.; Pérez-Luque, Antonio J.; Suárez-Muñoz, María

2017-04-01

Sierra Nevada Global Change Observatory (southern Spain) aims to improve the ability of ecosystems to address the impacts of global change. To this end, a monitoring program has been implemented based on the collection of long time series on a multitude of biophysical variables. This initiative is part of the Long Term Ecological Research network and is connected to similar ones at national and international level. One of the specific objectives of this LTER site is to improve understanding of the relationships between abiotic factors and ecosystem functioning / structure. Wireless sensor networks are a key instrument for achieving this aim. This contribution describes the design and management of a sensor network that is intended to monitor several biophysical variables with high temporal and spatial resolution in Quercus pyrenaica forests located in this mountain region. The following solution has been adopted in order to obtain the observational data (physical and biological variables). The biological variables will be monitored by PAR sensors (photosynthetically active radiation), and the physical variables will be acquired by a meteorological station and a sensor network composed of temperature and soil moisture sensors, as well as air temperature and humidity ones. To complete the monitoring of the biological variables, a NDVI (Normalized Difference Vegetation Index) camera will be deployed focusing to a Quercus pyrenaica forest from the opposite slope. It should be noted that all monitoring systems exposed will be powered by solar energy. The management of the sensor network covers the deployment of more than 100 sensors, guaranteeing both remote accessibility and reliability of the data. The chosen solution is provided by the company Adevice whose ONE-GO communication system ensures a consistent and efficient sending of those values read by the different sensors towards a central point, from where the information (RAW data) is accessible through WiFi/3G. RAW data is dumped daily in our data center for further processing with the open source software Get-IT. Get-IT was developed by the CNR (National Research Council of Italy) in the context of the RITMARE Flagship Project and LifeWatch Italy in order to combine geographic information with observational data by coupling GeoNode with SOS implementation by 52° North. This solution conforms to our requirements for two reasons, the first is that it provides data persistence, metadata editing and data visualisation tools. The second is that it is the solution adopted by LTER, platform previously mentioned in which we are integrated. This research has been funded by eLTER (Integrated European Long-Term Ecosystem & Socio-Ecological Research Infrastructure) Horizon 2020 EU project, and Sierra Nevada Global Change Observatory (LTER-site).

The NASA GPM Iowa Flood Studies Experiment

NASA Astrophysics Data System (ADS)

Petersen, W. A.; Krajewski, W. F.; Peters-Lidard, C. D.; Rutledge, S. A.; Wolff, D. B.

2013-12-01

The overarching objective of NASA Global Precipitation Measurement Mission (GPM) integrated hydrologic ground validation (GV) is to provide a better understanding of the strengths and limitations of the satellite products, in the context of hydrologic applications. Accordingly, the NASA GPM GV program recently completed the first of several hydrology-oriented field efforts: the Iowa Flood Studies (IFloodS) experiment. IFloodS was conducted in central Iowa during the months of April-June, 2013. IFloodS science objectives focused on: a) The collection of reference multi-parameter radar, rain gauge, disdrometer, soil moisture, and hydrologic network measurements to quantify the physical character and space/time variability of rain (e.g., rates, drop size distributions, processes), land surface- state and hydrologic response; b) Application of the ground reference measurements to assessment of satellite-based rainfall estimation uncertainties; c) Propagation of both ground and satellite rainfall estimation uncertainties in coupled hydrologic prediction models to assess impacts on predictive skill; and d) Evaluation of rainfall properties such as rate and accumulation relative to basin hydrologic characteristics in modeled flood genesis. IFloodS observational objectives were achieved via deployments of the NASA NPOL S-band and D3R Ka/Ku-band dual-polarimetric radars (operating in coordinated scanning modes), four University of Iowa X-band dual-polarimetric radars, four Micro Rain Radars, a network of 25 paired rain gauge platforms with attendant soil moisture and temperature probes, a network of six 2D Video and 14 Parsivel disdrometers, and 15 USDA-ARS rain gauge and soil-moisture stations (collaboration with the USDA-ARS and NASA Soil Moisture Active-Passive mission). The aforementioned platforms complemented existing operational WSR-88D S-band polarimetric radar, USGS streamflow, and Iowa Flood Center-affiliated stream monitoring and rainfall measurements. Coincident low-earth orbiter microwave, geostationary infrared, and derived satellite-algorithm rainfall products were also archived during the experiment. Twice daily NASA Unified Weather Research and Forecasting model simulations were conducted to provide weather forecast guidance and a coupled atmospheric/land-surface model simulation benchmark. During the experiment the IFloodS observational domain experienced heavy rainfall (> 250-300 mm) and significant flooding. Deployed observational assets, especially the research radars performed well throughout the experiment, sampling a broad range of precipitation system types including multi-day mixtures of rain and snow, warm-season mesoscale convective systems, and supercell thunderstorms. The variety of regimes and large rain accumulations sampled creates a rich source of data for testing both satellite products and coupled atmospheric, land system, and hydrologic models. In this study we will provide an overview of the IFloodS experiment, datasets, and preliminary observational results.

Ultrasonic monitoring of spontaneous imbibition experiments: Precursory moisture diffusion effects ahead of water front

NASA Astrophysics Data System (ADS)

David, Christian; Sarout, Joël.; Dautriat, Jérémie; Pimienta, Lucas; Michée, Marie; Desrues, Mathilde; Barnes, Christophe

2017-07-01

Fluid substitution processes have been investigated in the laboratory on 14 carbonate and siliciclastic reservoir rock analogues through spontaneous imbibition experiments on vertical cylindrical specimens with simultaneous ultrasonic monitoring and imaging. The motivation of our study was to identify the seismic attributes of fluid substitution in reservoir rocks and to link them to physical processes. It is shown that (i) the P wave velocity either decreases or increases when the capillary front reaches the Fresnel clearance zone, (ii) the P wave amplitude is systematically impacted earlier than the velocity is, (iii) this precursory amplitude decrease occurs when the imbibition front is located outside of the Fresnel zone, and (iv) the relative variation of the P wave amplitude is always much larger than that of the P wave velocity. These results suggest that moisture diffuses into the pore space ahead of the water front. This postulate is further supported by a quantitative analysis of the time evolution of the observed P wave amplitudes. In a sense, P wave amplitude acts as a precursor of the arrival of the capillary front. This phenomenon is used to estimate the effective diffusivity of moisture in the tested rocks. The effective moisture diffusivity estimated from the ultrasonic data is strongly correlated with permeability: a power law with exponent 0.96 predicts permeability from ultrasonic monitoring within a factor 3 without noticeable bias. When the effective diffusivity is high, moisture diffusion affects ultrasonic P wave attributes even before the imbibition starts and impacts the P wave reflectivity as evidenced by the variations recorded in the waveform coda.

Implementation of SMOS data monitoring in the Integrated Forecast System. Preliminary results.

NASA Astrophysics Data System (ADS)

Muñoz Sabater, Joaquin; de Rosnay, Patricia; Drusch, Mathias; Dahoui, Mohamed; Delwart, Steven; Wright, Norrie

2010-05-01

The Soil Moisture and Ocean Salinity (SMOS) mission of the European Space Agency (ESA) was successfully launched on November 2nd 2009. Using a novel concept based on the Synthetic Aperture Radar technique, it is expected that SMOS observations will provide global accurate maps of brightness temperatures (TB) and soil moisture at L-band every 3 days and at 50 km ground-spatial resolution. Thus, SMOS data will soon provide a valuable input for numerical weather prediction (NWP), hydrological and land surface systems, among others. Operational numerical weather forecast systems are widely used to evaluate and analyse new types of satellite observations. NWP centres use these observations in their analyses to derive level 2 retrieved geophysical parameters (e.g. soil moisture and ocean salinity for SMOS) from the observed radiances. The European Centre for Medium Range Weather Forecasts is monitoring the first flow of SMOS level 1C TB over sea and land. Monitoring, i.e. the systematic comparison between observations and the corresponding model parameters, is a mandatory step prior to data assimilation. Consequently, monitoring provides an overall quality assessment of SMOS data based on departures values between SMOS observations and the modelled equivalent in the observation space. This is a significant contribution to the calibration / validation activities during the SMOS commissioning phase. Any systematic error or spikes in the data become visible and can be reported to ESA and the other calibration and validation teams without significant delays. Furthermore, the monitored data at global scale will help to calibrate the SMOS instrument at key decision points during the commissioning phase. In this paper the first SMOS data over land is monitored. Special emphasis is given to the effect of different parametrisations and auxiliary data sets on the simulated TB. This is a first step towards the assimilation of SMOS TB to improve the initialization of soil moisture for NWP systems.

Assimilation of SMOS Retrieved Soil Moisture into the Land Information System

NASA Technical Reports Server (NTRS)

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

2014-01-01

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

Monitoring and modeling agricultural drought for famine early warning (Invited)

NASA Astrophysics Data System (ADS)

Verdin, J. P.; Funk, C.; Budde, M. E.; Lietzow, R.; Senay, G. B.; Smith, R.; Pedreros, D.; Rowland, J.; Artan, G. A.; Husak, G. J.; Michaelsen, J.; Adoum, A.; Galu, G.; Magadzire, T.; Rodriguez, M.

2009-12-01

The Famine Early Warning Systems Network (FEWS NET) makes quantitative estimates of food insecure populations, and identifies the places and periods during which action must be taken to assist them. Subsistence agriculture and pastoralism are the predominant livelihood systems being monitored, and they are especially drought-sensitive. At the same time, conventional climate observation networks in developing countries are often sparse and late in reporting. Consequently, remote sensing has played a significant role since FEWS NET began in 1985. Initially there was heavy reliance on vegetation index imagery from AVHRR to identify anomalies in landscape greenness indicative of drought. In the latter part of the 1990s, satellite rainfall estimates added a second, independent basis for identification of drought. They are used to force crop water balance models for the principal rainfed staple crops in twenty FEWS NET countries. Such models reveal seasonal moisture deficits associated with yield reduction on a spatially continuous basis. In 2002, irrigated crops in southwest Asia became a concern, and prompted the implementation of a gridded energy balance model to simulate the seasonal mountain snow pack, the main source of irrigation water. MODIS land surface temperature data are also applied in these areas to directly estimate actual seasonal evapotranspiration on the irrigated lands. The approach reveals situations of reduced irrigation water supply and crop production due to drought. The availability of MODIS data after 2000 also brought renewed interest in vegetation index imagery. MODIS NDVI data have proven to be of high quality, thanks to significant spectral and spatial resolution improvements over AVHRR. They are vital to producing rapid harvest assessments for drought-impacted countries in Africa and Asia. The global food crisis that emerged in 2008 has led to expansion of FEWS NET monitoring to over 50 additional countries. Unlike previous practice, these new countries have no local FEWS NET analysts, requiring increased reliance on remote sensing for detection of agricultural drought and potential food insecurity. USGS is increasing its cooperation with NASA, NOAA, and university partners to meet this challenge. New servers for near real time delivery of MODIS NDVI, satellite rainfall estimates, and gridded snow pack estimates are being established. A custom instance of NASA's Land Information System software is also being developed to create a land data assimilation system specifically for FEWS NET domains, data streams, and monitoring and forecast requirements. The system will take better advantage of remote sensing data, including promising new products from the Soil Moisture Active-Passive (SMAP) mission, by integrating them with surface observations for simulation of land surface processes. In this way, the continuous improvement of monitoring and modeling for famine early warning will advance to a new level of sophistication and effectiveness.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

Optical fibre distributed temperature sensing (DTS) is increasingly used in environmental monitoring and for subsurface characterisation, e.g. to obtain precise measurements of soil temperature at high spatio-temporal resolution, over several kilometres of optical fibre cable. When combined with active heating of metal elements embedded in the optical fibre cable (active-DTS), the temperature response of the soil to heating provides valuable information from which other important soil parameters, such as thermal conductivity and soil moisture content, can be inferred. In this presentation, we report the development of an Actively Heated Fibre Optics (AHFO) method for the characterisation of soil thermal conductivity and soil moisture dynamics at high temporal and spatial resolutions at a vegetated hillslope site in central England. The study site is located within a juvenile forest adjacent to the Birmingham Institute of Forest Research (BIFoR) experimental site. It is instrumented with three loops of a 500m hybrid-optical cable installed at 10cm, 25cm and 40cm depths. Active DTS surveys were undertaken in June and October 2016, collecting soil temperature data at 0.25m intervals along the cable, prior to, during and after the 900s heating phase. Soil thermal conductivity and soil moisture were determined according to Ciocca et al. 2012, applied to both the cooling and the heating phase. Independent measurements of soil thermal conductivity and soil moisture content were collected using thermal needle probes, calibrated capacitance-based probes and laboratory methods. Results from both the active DTS survey and independent in-situ and laboratory measurements will be presented, including the observed relationship between thermal conductivity and moisture content at the study site and how it compares against theoretical curves used by the AHFO methods. The spatial variability of soil thermal conductivity and soil moisture content, as observed using the different methods, will be shown and an outlook will be provided of how the AHFO method can benefit soil sciences, ground source heat pump applications and groundwater recharge estimations. This research is part of the Distributed intelligent Heat Pulse System (DiHPS) project which is funded by the UK Natural Environmental Research Council (NERC). The project is supported by BIFoR, the European Space Agency (ESA), CarbonZero Ltd, the UK Forestry Commission and the UK Soil Moisture Observation Network (COSMOS-UK). This work is distributed under the Creative Commons Attribution 3.0 Unported Licence together with an author copyright. This licence does not conflict with the regulations of the Crown Copyright. Ciocca F., Lunati I., van de Giesen N., and Parlange M.B. 2012. Heated optical fiber for distributed soil-moisture measurements: A lysimeter experiment. Vadose Zone J. 11. doi:10.2136/vzj2011.0177

40 CFR 75.74 - Annual and ozone season monitoring and reporting requirements.

Code of Federal Regulations, 2010 CFR

2010-07-01

... owner or operator of an affected unit subject both to an Acid Rain emission limitation and to a State or... State or federal NOX mass reduction program that adopts the provisions of this part and that requires...-diluent monitoring system, each flow rate monitoring system, each moisture monitoring system and each...

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

NASA Astrophysics Data System (ADS)

Willgoose, G. R.

2006-12-01

In humid catchments the spatial distribution of soil water is dominated by subsurface lateral fluxes, which leads to a persistent spatial pattern of soil moisture principally described by the topographic index. In contrast, semi-arid, and dryer, catchments are dominated by vertical fluxes (infiltration and evapotranspiration) and persistent spatial patterns, if they exist, are subtler. In the first part of this presentation the results of a reanalysis of a number of catchment-scale long-term spatially-distributed soil moisture data sets are presented. We concentrate on Tarrawarra and SASMAS, both catchments in Australia that are water-limited for at least part of the year and which have been monitored using a variety of technologies. Using the data from permanently installed instruments (neutron probe and reflectometry) both catchments show persistent patterns at the 1-3 year timescale. This persistent pattern is not evident in the field campaign data where field portable instruments (reflectometry) instruments were used. We argue, based on high-resolution soil moisture semivariograms, that high short-distance variability (100mm scale) means that field portable instrument cannot be replaced at the same location with sufficient accuracy to ensure deterministic repeatability of soil moisture measurements from campaign to campaign. The observed temporal persistence of the spatial pattern can be caused by; (1) permanent features of the landscape (e.g. vegetation, soils), or (2) long term memory in the soil moisture store. We argue that it is permanent in which case it is possible to monitor the soil moisture status of a catchment using a single location measurement (continuous in time) of soil moisture using a permanently installed reflectometry instrument. This instrument will need to be calibrated to the catchment averaged soil moisture but the temporal persistence of the spatial pattern of soil moisture will mean that this calibration will be deterministically stable with time. In the second part of this presentation we will explore aspects of the calibration using data from the SASMAS site using the multiscale spatial resolution data (100m to 10km) provided by permanently installed reflectometry instruments, and how this single site measurement technique may complement satellite data.

Automatic pattern identification of rock moisture based on the Staff-RF model

NASA Astrophysics Data System (ADS)

Zheng, Wei; Tao, Kai; Jiang, Wei

2018-04-01

Studies on the moisture and damage state of rocks generally focus on the qualitative description and mechanical information of rocks. This method is not applicable to the real-time safety monitoring of rock mass. In this study, a musical staff computing model is used to quantify the acoustic emission signals of rocks with different moisture patterns. Then, the random forest (RF) method is adopted to form the staff-RF model for the real-time pattern identification of rock moisture. The entire process requires only the computing information of the AE signal and does not require the mechanical conditions of rocks.

Quality-Controlled Upper-Air Sounding Dataset for DYNAMO/CINDY/AMIE: Development and Corrections

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ciesielski, Paul; Yu, Hungjui; Johnson, Richard

2014-04-01

The upper-air sounding network for DYNAMO (Dynamics of the Madden-Julian Oscillation or MJO) has provided an unprecedented set of observations for studying the MJO over the Indian Ocean (IO) where coupling of this oscillation with deep convection first occurs. With 72 sounding sites and dropsonde data from 13 aircraft mission, the sonde network covers the tropics from Eastern African to the West Pacific. In total nearly 26,000 sondes were collected from this network during the experiment’s 6-month extended observing period (from October 2011 to March 2012). Slightly more than half of the sondes, collected from 33 sites, are at highmore » vertical resolution. Rigorous post-field phase processing of the sonde data included several levels of quality checks and a variety of corrections which address a number of issues (e.g., daytime dry bias, baseline surface data errors, ship deck-heating effects, artificial dry spikes in slow ascent sondes). Because of the importance of an accurate description of the moisture field in meeting the scientific goals of the experiments, particular attention is given to humidity correction and its validation. The humidity corrections, though small relative to some previous field campaigns, produced high fidelity moisture analyses in which sonde precipitable water compared well with independent estimates. An assessment of model operational analyses moisture using corrected sonde data shows an overall good agreement with the exception at upper-levels where model moisture and clouds are more abundant than the sounding data would indicate.« less

Remote sensing techniques for monitoring drought hazards: an intercomparison (Invited)

NASA Astrophysics Data System (ADS)

Brown, J. F.; Anderson, M. C.; Wardlow, B. D.; Svoboda, M. D.

2009-12-01

Drought events are frequently described using many different terms; for example, recurring climate phenomena, creeping natural hazards, agricultural disasters, and moisture deficiencies. In addition, droughts operate at many different spatial and temporal scales and affect different societal sectors, making them quite challenging to monitor, map, and assess impacts. Because of these factors, determining drought severity often requires using a convergence of evidence assisted by an analysis of multiple drought indicators. Frequent optical and thermal observations collected by daily polar-orbiting and geostationary satellites allow for regular monitoring of the land surface. In recent decades, with the launching of more advanced sensors and the maturation of remote sensing techniques, a variety of tools have been designed for improved understanding and tracking of drought events as they are occurring. These applications are intended to provide key decision makers with timely geospatial drought information to support various drought planning and mitigation activities. Two such tools highlighted in this study, are the Vegetation Drought Response Index (VegDRI) and the Evaporative Stress Index (ESI). While both indices incorporate satellite-based inputs, they are involved in different modeling approaches and observations from different parts of the electromagnetic spectrum. The VegDRI is a hybrid remote sensing and climate based indicator of drought-induced vegetation stress that combines satellite-based vegetation index observations from Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Very High Resolution Radiometer (AVHRR) sensors with climate-based drought index data and other biophysical parameters (such as land use/land cover type and soil characteristics). VegDRI provides near real-time vegetation drought severity information at relatively higher spatial resolution (1-km2) than traditional climatic drought indices such as the Standardized Precipitation Index (SPI) or the U.S. Drought Monitor (USDM), which tend to depicted broad-scale spatial drought patterns. . The ESI is an indicator of anomalous land-surface evaporation and soil moisture deficiency. The ESI is related to the ratio of actual-to-potential evapotranspiration (ET), where actual ET is estimated with a thermal-infrared (TIR) based surface energy balance algorithm. The ESI product is generated in near-real time at 10-km2 resolution over the continental U.S. using TIR imagery from the Geostationary Operational Environmental Satellites (GOES). Because it does not use precipitation data as an input, it is a valuable complement to existing precipitation-based indices and is readily portable to data-poor regions with sparse ground-based rainfall monitoring networks. In this study, we present an intercomparison of the VegDRI and the ESI for the 2009 growing season, highlighting weekly, monthly, and seasonal patterns of moisture flux from soils and vegetation.

Combining Multi-Agent Systems and Wireless Sensor Networks for Monitoring Crop Irrigation.

PubMed

Villarrubia, Gabriel; Paz, Juan F De; Iglesia, Daniel H De La; Bajo, Javier

2017-08-02

Monitoring mechanisms that ensure efficient crop growth are essential on many farms, especially in certain areas of the planet where water is scarce. Most farmers must assume the high cost of the required equipment in order to be able to streamline natural resources on their farms. Considering that many farmers cannot afford to install this equipment, it is necessary to look for more effective solutions that would be cheaper to implement. The objective of this study is to build virtual organizations of agents that can communicate between each other while monitoring crops. A low cost sensor architecture allows farmers to monitor and optimize the growth of their crops by streamlining the amount of resources the crops need at every moment. Since the hardware has limited processing and communication capabilities, our approach uses the PANGEA architecture to overcome this limitation. Specifically, we will design a system that is capable of collecting heterogeneous information from its environment, using sensors for temperature, solar radiation, humidity, pH, moisture and wind. A major outcome of our approach is that our solution is able to merge heterogeneous data from sensors and produce a response adapted to the context. In order to validate the proposed system, we present a case study in which farmers are provided with a tool that allows us to monitor the condition of crops on a TV screen using a low cost device.

Combining Multi-Agent Systems and Wireless Sensor Networks for Monitoring Crop Irrigation

PubMed Central

Villarrubia, Gabriel; De Paz, Juan F.; De La Iglesia, Daniel H.; Bajo, Javier

2017-01-01

Monitoring mechanisms that ensure efficient crop growth are essential on many farms, especially in certain areas of the planet where water is scarce. Most farmers must assume the high cost of the required equipment in order to be able to streamline natural resources on their farms. Considering that many farmers cannot afford to install this equipment, it is necessary to look for more effective solutions that would be cheaper to implement. The objective of this study is to build virtual organizations of agents that can communicate between each other while monitoring crops. A low cost sensor architecture allows farmers to monitor and optimize the growth of their crops by streamlining the amount of resources the crops need at every moment. Since the hardware has limited processing and communication capabilities, our approach uses the PANGEA architecture to overcome this limitation. Specifically, we will design a system that is capable of collecting heterogeneous information from its environment, using sensors for temperature, solar radiation, humidity, pH, moisture and wind. A major outcome of our approach is that our solution is able to merge heterogeneous data from sensors and produce a response adapted to the context. In order to validate the proposed system, we present a case study in which farmers are provided with a tool that allows us to monitor the condition of crops on a TV screen using a low cost device. PMID:28767089

The long oasis: understanding and managing saline floodplains in southeastern Australia

NASA Astrophysics Data System (ADS)

Woods, J.; Green, G.; Laattoe, T.; Purczel, C.; Riches, V.; Li, C.; Denny, M.

2017-12-01

In a semi-arid region of southeastern Australia, the River Murray is the predominant source of freshwater for town water supply, irrigation, and floodplain ecosystems. The river interacts with aquifers where the salinity routinely exceeds 18,000 mg/l. River regulation, extraction, land clearance, and irrigation have reduced the size and frequency of floods while moving more salt into the floodplain. Floodplain ecosystem health has declined. Management options to improve floodplain health under these modified conditions include environmental watering, weirpool manipulation, and groundwater pumping. To benefit long-lived tree species, floodplain management needs to increase soil moisture availability. A conceptual model was developed of floodplain processes impacting soil moisture availability. The implications and limitations of the conceptualization were investigated using a series of numerical models, each of which simulated a subset of the processes under current and managed conditions. The aim was to determine what range of behaviors the models predicted, and to identify which parameters were key to accurately predicting the success of management options. Soil moisture availability was found to depend strongly on the properties of the floodplain clay, which controls vertical recharge during inundation. Groundwater freshening near surface water features depended on the riverbed conductivity and the penetration of the river into the floodplain sediments. Evapotranspiration is another critical process, and simulations revealed the limitations of standard numerical codes in environments where both evaporation and transpiration depend on salinity. Finally, maintenance of viable populations of floodplain trees is conceptually understood to rely on the persistence of adequate soil moisture availability over time, but thresholds for duration of exposure to low moisture availability that lead to decline and irreversible decline in tree condition are a major knowledge gap. The work identified critical data gaps which will be addressed in monitoring guidelines to improve management. This includes: hydrogeochemical sampling; in situ soil monitoring combined with tree health observations; monitoring of actual evapotranspiration; and monitoring of bores close to surface water sources.

Closing the water balance with cosmic-ray soil moisture measurements and assessing their relation to evapotranspiration in two semiarid watersheds

NASA Astrophysics Data System (ADS)

Schreiner-McGraw, A. P.; Vivoni, E. R.; Mascaro, G.; Franz, T. E.

2016-01-01

Soil moisture dynamics reflect the complex interactions of meteorological conditions with soil, vegetation and terrain properties. In this study, intermediate-scale soil moisture estimates from the cosmic-ray neutron sensing (CRNS) method are evaluated for two semiarid ecosystems in the southwestern United States: a mesquite savanna at the Santa Rita Experimental Range (SRER) and a mixed shrubland at the Jornada Experimental Range (JER). Evaluations of the CRNS method are performed for small watersheds instrumented with a distributed sensor network consisting of soil moisture sensor profiles, an eddy covariance tower, and runoff flumes used to close the water balance. We found a very good agreement between the CRNS method and the distributed sensor network (root mean square error (RMSE) of 0.009 and 0.013 m3 m-3 at SRER and JER, respectively) at the hourly timescale over the 19-month study period, primarily due to the inclusion of 5 cm observations of shallow soil moisture. Good agreement was also obtained in soil moisture changes estimated from the CRNS and watershed water balance methods (RMSE of 0.001 and 0.082 m3 m-3 at SRER and JER, respectively), with deviations due to bypassing of the CRNS measurement depth during large rainfall events. Once validated, the CRNS soil moisture estimates were used to investigate hydrological processes at the footprint scale at each site. Through the computation of the water balance, we showed that drier-than-average conditions at SRER promoted plant water uptake from deeper soil layers, while the wetter-than-average period at JER resulted in percolation towards deeper soils. The CRNS measurements were then used to quantify the link between evapotranspiration and soil moisture at a commensurate scale, finding similar predictive relations at both sites that are applicable to other semiarid ecosystems in the southwestern US.

Development of an Objective High Spatial Resolution Soil Moisture Index

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

On the synergistic use of microwave and infrared satellite observations to monitor soil moisture and flooding

USDA-ARS?s Scientific Manuscript database

Extreme hydrological processes are often very dynamic and destructive.A better understanding of these processes requires an accurate mapping of key variables that control them. In this regard, soil moisture is perhaps the most important parameter that impacts the magnitude of flooding events as it c...

The evaporative demand drought index: Part II – CONUS-wide assessment against common drought indicators

USDA-ARS?s Scientific Manuscript database

Precipitation, soil moisture, and air temperature are the most commonly used climate variables to monitor drought, however other climatic factors such as solar radiation, wind speed, and specific humidity can be important drivers in the depletion of soil moisture and evolution and persistence of dro...

The use of Landsat digital data to detect and monitor vegetation water deficiencies

NASA Technical Reports Server (NTRS)

Thompson, D. R.; Wehmanen, O. A.

1977-01-01

In the Large Area Crop Inventory Experiment a technique was devised using a vector transformation of Landsat digital data to indicate when vegetation is undergoing moisture stress. A relation was established between the remote-sensing-based criterion (the Green Index Number) and a ground-based criterion (Crop Moisture Index).

40 CFR 265.1085 - Standards: Tanks.

Code of Federal Regulations, 2014 CFR

2014-07-01

... wind, moisture, and sunlight; and the operating practices used for the tank on which the fixed roof is... exposure to wind, moisture, and sunlight; and the operating practices used for the tank on which the fixed... so to avoid an unsafe condition. (3) The owner or operator shall inspect and monitor the air emission...

40 CFR 265.1085 - Standards: Tanks.

Code of Federal Regulations, 2011 CFR

2011-07-01

... wind, moisture, and sunlight; and the operating practices used for the tank on which the fixed roof is... exposure to wind, moisture, and sunlight; and the operating practices used for the tank on which the fixed... so to avoid an unsafe condition. (3) The owner or operator shall inspect and monitor the air emission...

40 CFR 265.1085 - Standards: Tanks.

Code of Federal Regulations, 2012 CFR

2012-07-01

... wind, moisture, and sunlight; and the operating practices used for the tank on which the fixed roof is... exposure to wind, moisture, and sunlight; and the operating practices used for the tank on which the fixed... so to avoid an unsafe condition. (3) The owner or operator shall inspect and monitor the air emission...

40 CFR 265.1085 - Standards: Tanks.

Code of Federal Regulations, 2013 CFR

2013-07-01

... wind, moisture, and sunlight; and the operating practices used for the tank on which the fixed roof is... exposure to wind, moisture, and sunlight; and the operating practices used for the tank on which the fixed... so to avoid an unsafe condition. (3) The owner or operator shall inspect and monitor the air emission...

Hyperspectral surface reflectance data detect low moisture status of pecan orchards during flood irrigation

USDA-ARS?s Scientific Manuscript database

For large fields, remote sensing might permit plant low moisture status to be detected early, and this may improve drought detection and monitoring. The objective of this study was to determine whether canopy and soil surface reflectance data derived from a handheld spectroradiometer can detect mois...

The SMAP level 4 carbon product for monitoring ecosystem land-atmosphere CO2 exchange

USDA-ARS?s Scientific Manuscript database

The NASA Soil Moisture Active Passive (SMAP) mission Level 4 Carbon (L4C) product provides model estimates of Net Ecosystem CO2 exchange (NEE) incorporating SMAP soil moisture information. The L4C product includes NEE, computed as total ecosystem respiration less gross photosynthesis, at a daily ti...

Comparison of dew point temperature estimation methods in Southwestern Georgia

Treesearch

Marcus D. Williams; Scott L. Goodrick; Andrew Grundstein; Marshall Shepherd

2015-01-01

Recent upward trends in acres irrigated have been linked to increasing near-surface moisture. Unfortunately, stations with dew point data for monitoring near-surface moisture are sparse. Thus, models that estimate dew points from more readily observed data sources are useful. Daily average dew temperatures were estimated and evaluated at 14 stations in...

National Centers for Environmental Prediction

Science.gov Websites

albedos (testing) Vegetation types Soil texture Images of Snow files: NAM snow page The NESDIS/IMS snow /ice images On Hua-Lu Pan's home page (EMC/NCEP) On the NCAR/RAP Weather Data Page Related soil moisture web sites NCEP/NASA NDAS CPC Soil Moisture Monitoring and Prediction NOAA / National Weather

75 FR 18757 - Approval and Promulgation of Air Quality Implementation Plans; Indiana; Alternate Monitoring...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-04-13

... Station Unit 7. The scrubber adds moisture to the exhaust gas, which condenses as the gas stream cools. According to Indiana Department of Environmental Management (IDEM), the condensation causes unreliable... impairment caused by particulate and light impairment caused by moisture. The scrubber also removes some PM...

Global-scale assessment and combination of SMAP with ASCAT (Active) and AMSR2 (Passive) soil moisture products

USDA-ARS?s Scientific Manuscript database

Global-scale surface soil moisture (SSM) products retrieved from active and passive microwave remote sensing provide an effective method for monitoring near-real-time SSM content with nearly daily temporal resolution. In the present study, we first inter-compared global-scale error patterns and comb...

An Automated Approach to Peanut dring with real-time monitoring of in-shell Kernel Moisture Content with a Microwave Sensor

USDA-ARS?s Scientific Manuscript database

Today’s peanut drying processes utilize decision support software based on modeling and require substantial human interaction for moisture sampling. These conditions increase the likelihood of peanuts being overdried or underdried. This research addresses the need for an automated controller with re...

Benchmarking a Soil Moisture Data Assimilation System for Agricultural Drought Monitoring

NASA Technical Reports Server (NTRS)

Hun, Eunjin; Crow, Wade T.; Holmes, Thomas; Bolten, John

2014-01-01

Despite considerable interest in the application of land surface data assimilation systems (LDAS) for agricultural drought applications, relatively little is known about the large-scale performance of such systems and, thus, the optimal methodological approach for implementing them. To address this need, this paper evaluates an LDAS for agricultural drought monitoring by benchmarking individual components of the system (i.e., a satellite soil moisture retrieval algorithm, a soil water balance model and a sequential data assimilation filter) against a series of linear models which perform the same function (i.e., have the same basic inputoutput structure) as the full system component. Benchmarking is based on the calculation of the lagged rank cross-correlation between the normalized difference vegetation index (NDVI) and soil moisture estimates acquired for various components of the system. Lagged soil moistureNDVI correlations obtained using individual LDAS components versus their linear analogs reveal the degree to which non-linearities andor complexities contained within each component actually contribute to the performance of the LDAS system as a whole. Here, a particular system based on surface soil moisture retrievals from the Land Parameter Retrieval Model (LPRM), a two-layer Palmer soil water balance model and an Ensemble Kalman filter (EnKF) is benchmarked. Results suggest significant room for improvement in each component of the system.

Soil Moisture Limitations on Monitoring Boreal Forest Regrowth Using Spaceborne L-Band SAR Data

NASA Technical Reports Server (NTRS)

Kasischke, Eric S.; Tanase, Mihai A.; Bourgeau-Chavez, Laura L.; Borr, Matthew

2011-01-01

A study was carried out to investigate the utility of L-band SAR data for estimating aboveground biomass in sites with low levels of vegetation regrowth. Data to estimate biomass were collected from 59 sites located in fire-disturbed black spruce forests in interior Alaska. PALSAR L-band data (HH and HV polarizations) collected on two dates in the summer/fall of 2007 and one date in the summer of 2009 were used. Significant linear correlations were found between the log of aboveground biomass (range of 0.02 to 22.2 t ha-1) and (L-HH) and (L-HV) for the data collected on each of the three dates, with the highest correlation found using the LHV data collected when soil moisture was highest. Soil moisture, however, did change the correlations between L-band and aboveground biomass, and the analyses suggest that the influence of soil moisture is biomass dependent. The results indicate that to use L-band SAR data for mapping aboveground biomass and monitoring forest regrowth will require development of approaches to account for the influence that variations in soil moisture have on L-band microwave backscatter, which can be particularly strong when low levels of aboveground biomass occur

Effects of pruning intensity on jujube transpiration and soil moisture of plantation in the Loess Plateau

NASA Astrophysics Data System (ADS)

Nie, Zhenyi; Wang, Xing; Wang, Youke; Ma, Jianpeng; Wei, Xinguang; Chen, Dianyu

2017-01-01

In order to ease soil desiccation and prevent ecological deterioration in the Loess Plateau, where jujube (Zizyphus jujube MIll) is widely cultivated as a drought tolerant plant, four pruning intensities (PI), from PI-1 (light) to PI-4 (heavy) were set up based on total length of secondary branches to study the effects of pruning on transpiration and soil moisture in jujube plantations. Furthermore, growth indexes were regularly monitored to estimate jujubes biomass. Sap flow, meteorological and soil moisture conditions were monitored using thermal dissipation probes (TDP), weather station (RR-9100) and the combination of time domain transmission (TDT) technology and neutron moisture gauges (CNC503B), respectively. The results showed that daily actual transpiration of jujube was positively correlated with leaf biomass. Compared with PI-1, jujube transpiration during growth period under PI-2, PI-3, and PI-4 dropped by 11.1%, 29.2%, and 47.9%, respectively. On the contrary, annual water storage under PI-2, PI-3, and PI-4 increased by 6.29 mm, 25.78 mm and 34.74 mm while water use efficiency increased by 5.1%, 15.7% and 24.2%, respectively. Overall, increase in pruning intensity could significantly reduce water consumption of jujube and improve soil moisture in jujube plantations.

In-line moisture monitoring in fluidized bed granulation using a novel multi-resonance microwave sensor.

PubMed

Peters, Johanna; Bartscher, Kathrin; Döscher, Claas; Taute, Wolfgang; Höft, Michael; Knöchel, Reinhard; Breitkreutz, Jörg

2017-08-01

Microwave resonance technology (MRT) is known as a process analytical technology (PAT) tool for moisture measurements in fluid-bed granulation. It offers a great potential for wet granulation processes even where the suitability of near-infrared (NIR) spectroscopy is limited, e.g. colored granules, large variations in bulk density. However, previous sensor systems operating around a single resonance frequency showed limitations above approx. 7.5% granule moisture. This paper describes the application of a novel sensor working with four resonance frequencies. In-line data of all four resonance frequencies were collected and further processed. Based on calculation of density-independent microwave moisture values multiple linear regression (MLR) models using Karl-Fischer titration (KF) as well as loss on drying (LOD) as reference methods were build. Rapid, reliable in-process moisture control (RMSEP≤0.5%) even at higher moisture contents was achieved. Copyright © 2017 Elsevier B.V. All rights reserved.

A simple nudging scheme to assimilate ASCAT soil moisture data in the WRF model

NASA Astrophysics Data System (ADS)

Capecchi, V.; Gozzini, B.

2012-04-01

The present work shows results obtained in a numerical experiment using the WRF (Weather and Research Forecasting, www.wrf-model.org) model. A control run where soil moisture is constrained by GFS global analysis is compared with a test run where soil moisture analysis is obtained via a simple nudging scheme using ASCAT data. The basic idea of the assimilation scheme is to "nudge" the first level (0-10 cm below ground in NOAH model) of volumetric soil moisture of the first-guess (say θ(b,1) derived from global model) towards the ASCAT derived value (say ^θ A). The soil moisture analysis θ(a,1) is given by: { θ + K (^θA - θ ) l = 1 θ(a,1) = θ(b,l) (b,l) l > 1 (b,l) (1) where l is the model soil level. K is a constant scalar value that is user specified and in this study it is equal to 0.2 (same value as in similar studies). Soil moisture is critical for estimating latent and sensible heat fluxes as well as boundary layer structure. This parameter is, however, poorly assimilated in current global and regional numerical models since no extensive soil moisture observation network exists. Remote sensing technologies offer a synoptic view of the dynamics and spatial distribution of soil moisture with a frequent temporal coverage and with a horizontal resolution similar to mesoscale NWP model. Several studies have shown that measurements of normalized backscatter (surface soil wetness) from the Advanced Scatterometer (ASCAT) operating at microwave frequencies and boarded on the meteorological operational (Metop) satellite, offer quality information about surface soil moisture. Recently several studies deal with the implementation of simple assimilation procedures (nudging, Extended Kalman Filter, etc...) to integrate ASCAT data in NWP models. They found improvements in screen temperature predictions, particularly in areas such as North-America and in the Tropics, where it is strong the land-atmosphere coupling. The ECMWF (Newsletter No. 127) is currently implementing and testing an EKF for combining conventional observations and remote sensed soil moisture data in order to produce a more accurate analysis. In the present work verification skills (RMSE, BIAS, correlation) of both control and test run are presented using observed data collected by International Soil Moisture Network. Moreover improvements in temperature predictions are evaluated.

Effects of Soil Moisture Thresholds in Runoff Generation in two nested gauged basins

NASA Astrophysics Data System (ADS)

Fiorentino, M.; Gioia, A.; Iacobellis, V.; Manfreda, S.; Margiotta, M. R.; Onorati, B.; Rivelli, A. R.; Sole, A.

2009-04-01

Regarding catchment response to intense storm events, while the relevance of antecedent soil moisture conditions is generally recognized, the role and the quantification of runoff thresholds is still uncertain. Among others, Grayson et al. (1997) argue that above a wetness threshold a substantial portion of a small basin acts in unison and contributes to the runoff production. Investigations were conducted through an experimental approach and in particular exploiting the hydrological data monitored on "Fiumarella of Corleto" catchment (Southern Italy). The field instrumentation ensures continuous monitoring of all fundamental hydrological variables: climate forcing, streamflow and soil moisture. The experimental basin is equipped with two water level installations used to measure the hydrological response of the entire basin (with an area of 32 km2) and of a subcatchment of 0.65 km2. The aim of the present research is to better understand the dynamics of soil moisture and the runoff generation during flood events, comparing the data recorded in the transect and the runoff at the two different scales. Particular attention was paid to the influence of the soil moisture content on runoff activation mechanisms. We found that, the threshold value, responsible of runoff activation, is equal or almost to field capacity. In fact, we observed a rapid change in the subcatchment response when the mean soil moisture reaches a value close to the range of variability of the field capacity measured along a monitored transect of the small subcatchment. During dry periods the runoff coefficient is almost zero for each of the events recorded. During wet periods, however, it is rather variable and depends almost only on the total rainfall. Changing from the small scale (0.65 km2) up to the medium scale (represented by the basin of 32 km2) the threshold mechanism in runoff production is less detectable because masked by the increased spatial heterogeneity of the vegetation cover and soil texture.

Moisture and drug solid-state monitoring during a continuous drying process using empirical and mass balance models.

PubMed

Fonteyne, Margot; Gildemyn, Delphine; Peeters, Elisabeth; Mortier, Séverine Thérèse F C; Vercruysse, Jurgen; Gernaey, Krist V; Vervaet, Chris; Remon, Jean Paul; Nopens, Ingmar; De Beer, Thomas

2014-08-01

Classically, the end point detection during fluid bed drying has been performed using indirect parameters, such as the product temperature or the humidity of the outlet drying air. This paper aims at comparing those classic methods to both in-line moisture and solid-state determination by means of Process Analytical Technology (PAT) tools (Raman and NIR spectroscopy) and a mass balance approach. The six-segmented fluid bed drying system being part of a fully continuous from-powder-to-tablet production line (ConsiGma™-25) was used for this study. A theophylline:lactose:PVP (30:67.5:2.5) blend was chosen as model formulation. For the development of the NIR-based moisture determination model, 15 calibration experiments in the fluid bed dryer were performed. Six test experiments were conducted afterwards, and the product was monitored in-line with NIR and Raman spectroscopy during drying. The results (drying endpoint and residual moisture) obtained via the NIR-based moisture determination model, the classical approach by means of indirect parameters and the mass balance model were then compared. Our conclusion is that the PAT-based method is most suited for use in a production set-up. Secondly, the different size fractions of the dried granules obtained during different experiments (fines, yield and oversized granules) were compared separately, revealing differences in both solid state of theophylline and moisture content between the different granule size fractions. Copyright © 2014 Elsevier B.V. All rights reserved.

GNSS Remote Sensing at GFZ: Overview and Recent Results

NASA Astrophysics Data System (ADS)

Wickert, Jens; Alshawaf, Fadwa; Arras, Christina; Asgarimehr, Milad; Dick, Galina; Heise, Stefan; Larson, Kristine; Li, Xingxing; Lu, Cuixian; Peraza, Luis; Ramatschi, Markus; Schmidt, Torsten; Schuh, Harald; Semmling, Maximilian; Simeonov, Tzvetan; Vey, Sibylle; Zus, Florian

2017-04-01

GNSS atmospheric remote sensing was successfully established during the last two decades and evolved into a major application for high precision GNSS. The most prominent example for this development is the use of GNSS atmospheric data to improve day-by-day regional and global weather forecasts since 2006. Globally distributed vertical profiles of refractivity, temperature and water vapour are derived from satellite based GNSS data (Radio Occultation, RO). Ground based measurements, provided by global and regional GNSS networks, allow for the derivation of vertically (IWV) or along the line-of-sight integrated water vapour (SWV). Another important GNSS remote sensing technique, the exploitation of Earth reflected signals (GNSS Reflectometry, GNSS-R), is not yet operationally applied. But the huge potential for the determination of various physical parameters, as, e.g., sea surface height, wind speed over water and soil moisture on regional and global scales is recognized by the Earth Observation community. Therefore GNSS-R is recently a major challenge of international geophysical research. We review related activities at the German Research Centre for Geosciences GFZ and introduce recent results. The status of the GNSS-RO experiments aboard the satellites GRACE-A, TerraSAR-X and TanDEM-X, which are coordinated by GFZ, is reviewed. Examples of GNSS RO applications are given, as, e.g., climatological investigations of the global vertical temperature structure or the detection of ionospheric irregularities in the E-region. We also focus on ground based activities for GNSS water vapour monitoring. Observations of a global and regionally densified German network, with about 600 stations in total, are processed in near-real time to operationally provide IWV data. These data are assimilated into atmospheric models by several European weather centers. Current research activities are focused on the generation and meteorological application of GNSS based slant data, on real-time and multi-GNSS meteorology. In addition, climatological investigations are described to analyse long-term trends of the atmospheric water vapour over Germany but also as part of the Global Climate Observing System (GCOS) of the WMO (World Meteorological Organization). Multipath data from standard GNSS receivers are used to derive information on soil moisture, vegetation and snow properties. This technique exhibits a large potential to get geophysical parameters for Earth surface monitoring from the existing global and regional GNSS networks. GFZ also applies dedicated GNSS receivers aboard flight and ship platforms to derive sea surface heights using the GNSS-R phase altimetry technique. Other research activities contribute to the preparation of satellite missions for geophysical GNSS-R applications on a global scale. The most prominent current example is the ESA mission GEROS-ISS for global sea surface monitoring.

Long term monitoring of moisture under pavements : executive summary report.

DOT National Transportation Integrated Search

2010-01-01

The research : program consisted of three : distinct : activities. The first activity was a continuation of : the monitoring of environmental instrumentation : under select pavement sections constructed by the : Ohio Department of Transportation (ODO...

Long term monitoring of moisture under pavements.

DOT National Transportation Integrated Search

2010-01-01

Monitoring of the environmental instrumentation installed under select pavement sections constructed : by the Ohio Department of Transportation (ODOT) in 1995 on US 23 in Delaware County, Ohio was : continued. The measurements made consisted of soil ...

Multisensor Capacitance Probes for Simultaneously Monitoring Rice Field Soil-Water- Crop-Ambient Conditions.

PubMed

Brinkhoff, James; Hornbuckle, John; Dowling, Thomas

2017-12-26

Multisensor capacitance probes (MCPs) have traditionally been used for soil moisture monitoring and irrigation scheduling. This paper presents a new application of these probes, namely the simultaneous monitoring of ponded water level, soil moisture, and temperature profile, conditions which are particularly important for rice crops in temperate growing regions and for rice grown with prolonged periods of drying. WiFi-based loggers are used to concurrently collect the data from the MCPs and ultrasonic distance sensors (giving an independent reading of water depth). Models are fit to MCP water depth vs volumetric water content (VWC) characteristics from laboratory measurements, variability from probe-to-probe is assessed, and the methodology is verified using measurements from a rice field throughout a growing season. The root-mean-squared error of the water depth calculated from MCP VWC over the rice growing season was 6.6 mm. MCPs are used to simultaneously monitor ponded water depth, soil moisture content when ponded water is drained, and temperatures in root, water, crop and ambient zones. The insulation effect of ponded water against cold-temperature effects is demonstrated with low and high water levels. The developed approach offers advantages in gaining the full soil-plant-atmosphere continuum in a single robust sensor.

Evaluation of the predicted error of the soil moisture retrieval from C-band SAR by comparison against modelled soil moisture estimates over Australia

PubMed Central

Doubková, Marcela; Van Dijk, Albert I.J.M.; Sabel, Daniel; Wagner, Wolfgang; Blöschl, Günter

2012-01-01

The Sentinel-1 will carry onboard a C-band radar instrument that will map the European continent once every four days and the global land surface at least once every twelve days with finest 5 × 20 m spatial resolution. The high temporal sampling rate and operational configuration make Sentinel-1 of interest for operational soil moisture monitoring. Currently, updated soil moisture data are made available at 1 km spatial resolution as a demonstration service using Global Mode (GM) measurements from the Advanced Synthetic Aperture Radar (ASAR) onboard ENVISAT. The service demonstrates the potential of the C-band observations to monitor variations in soil moisture. Importantly, a retrieval error estimate is also available; these are needed to assimilate observations into models. The retrieval error is estimated by propagating sensor errors through the retrieval model. In this work, the existing ASAR GM retrieval error product is evaluated using independent top soil moisture estimates produced by the grid-based landscape hydrological model (AWRA-L) developed within the Australian Water Resources Assessment system (AWRA). The ASAR GM retrieval error estimate, an assumed prior AWRA-L error estimate and the variance in the respective datasets were used to spatially predict the root mean square error (RMSE) and the Pearson's correlation coefficient R between the two datasets. These were compared with the RMSE calculated directly from the two datasets. The predicted and computed RMSE showed a very high level of agreement in spatial patterns as well as good quantitative agreement; the RMSE was predicted within accuracy of 4% of saturated soil moisture over 89% of the Australian land mass. Predicted and calculated R maps corresponded within accuracy of 10% over 61% of the continent. The strong correspondence between the predicted and calculated RMSE and R builds confidence in the retrieval error model and derived ASAR GM error estimates. The ASAR GM and Sentinel-1 have the same basic physical measurement characteristics, and therefore very similar retrieval error estimation method can be applied. Because of the expected improvements in radiometric resolution of the Sentinel-1 backscatter measurements, soil moisture estimation errors can be expected to be an order of magnitude less than those for ASAR GM. This opens the possibility for operationally available medium resolution soil moisture estimates with very well-specified errors that can be assimilated into hydrological or crop yield models, with potentially large benefits for land-atmosphere fluxes, crop growth, and water balance monitoring and modelling. PMID:23483015

Future opportunities and challenges in remote sensing of drought

USGS Publications Warehouse

Wardlow, Brian D.; Anderson, Martha C.; Sheffield, Justin; Doorn, Brad; Zhan, Xiwu; Rodell, Matt; Wardlow, Brian D.; Anderson, Martha C.; Verdin, James P.

2012-01-01

The value of satellite remote sensing for drought monitoring was first realized more than two decades ago with the application of Normalized Difference Index (NDVI) data from the Advanced Very High Resolution Radiometer (AVHRR) for assessing the effect of drought on vegetation. Other indices such as the Vegetation Health Index (VHI) were also developed during this time period, and applied to AVHRR NDVI and brightness temperature data for routine global monitoring of drought conditions. These early efforts demonstrated the unique perspective that global imagers such as AVHRR could provide for operational drought monitoring through their near-daily, global observations of Earth's land surface. However, the advancement of satellite remote sensing of drought was limited by the relatively few spectral bands of operational global sensors such as AVHRR, along with a relatively short period of observational record. Remote sensing advancements are of paramount importance given the increasing demand for tools that can provide accurate, timely, and integrated information on drought conditions to facilitate proactive decision making (NIDIS, 2007). Satellite-based approaches are key to addressing significant gaps in the spatial and temporal coverage of current surface station instrument networks providing key moisture observations (e.g., rainfall, snow, soil moisture, ground water, and ET) over the United States and globally (NIDIS, 2007). Improved monitoring capabilities will be particularly important given increases in spatial extent, intensity, and duration of drought events observed in some regions of the world, as reported in the International Panel on Climate Change (IPCC) report (IPCC, 2007). The risk of drought is anticipated to further increase in some regions in response to climatic changes in the hydrologic cycle related to evaporation, precipitation, air temperature, and snow cover (Burke et al., 2006; IPCC, 2007; USGCRP, 2009). Numerous national, regional, and global efforts such as the Famine and Early Warning System (FEWS), National Integrated Drought Information System (NIDIS), and Group on Earth Observations (GEO), as well as the establishment of regional drought centers (e.g., European Drought Observatory) and geospatial visualization and monitoring systems (e.g, NASA SERVIR) have been undertaken to improve drought monitoring and early warning systems throughout the world. The suite of innovative remote sensing tools that have recently emerged will be looked upon to fill important data and knowledge gaps (NIDIS, 2007; NRC, 2007) to address a wide range of drought-related issues including food security, water scarcity, and human health.

Future Opportunities and Challenges in Remote Sensing of Drought

NASA Technical Reports Server (NTRS)

Wardlow, Brian D.; Anderson, Martha C.; Sheffield, Justin; Doorn, Brad; Zhan, Xiwu; Rodell, Matt

2011-01-01

The value of satellite remote sensing for drought monitoring was first realized more than two decades ago with the application of Normalized Difference Index (NDVI) data from the Advanced Very High Resolution Radiometer (AVHRR) for assessing the effect of drought on vegetation. Other indices such as the Vegetation Health Index (VHI) were also developed during this time period, and applied to AVHRR NDVI and brightness temperature data for routine global monitoring of drought conditions. These early efforts demonstrated the unique perspective that global imagers such as AVHRR could provide for operational drought monitoring through their near-daily, global observations of Earth's land surface. However, the advancement of satellite remote sensing of drought was limited by the relatively few spectral bands of operational global sensors such as AVHRR, along with a relatively short period of observational record. Remote sensing advancements are of paramount importance given the increasing demand for tools that can provide accurate, timely, and integrated information on drought conditions to facilitate proactive decision making (NIDIS, 2007). Satellite-based approaches are key to addressing significant gaps in the spatial and temporal coverage of current surface station instrument networks providing key moisture observations (e.g., rainfall, snow, soil moisture, ground water, and ET) over the United States and globally (NIDIS, 2007). Improved monitoring capabilities will be particularly important given increases in spatial extent, intensity, and duration of drought events observed in some regions of the world, as reported in the International Panel on Climate Change (IPCC) report (IPCC, 2007). The risk of drought is anticipated to further increase in some regions in response to climatic changes in the hydrologic cycle related to evaporation, precipitation, air temperature, and snow cover (Burke et al., 2006; IPCC, 2007; USGCRP, 2009). Numerous national, regional, and global efforts such as the Famine and Early Warning System (FEWS), National Integrated Drought Information System (NIDIS), and Group on Earth Observations (GEO), as well as the establishment of regional drought centers (e.g., European Drought Observatory) and geospatial visualization and monitoring systems (e.g, NASA SERVIR) have been undertaken to improve drought monitoring and early warning systems throughout the world. The suite of innovative remote sensing tools that have recently emerged will be looked upon to fill important data and knowledge gaps (NIDIS, 2007; NRC, 2007) to address a wide range of drought-related issues including food security, water scarcity, and human health.

Approaching Moisture Recycling Governance

NASA Astrophysics Data System (ADS)

Keys, Patrick; Wang-Erlandsson, Lan; Gordon, Line; Galaz, Victor; Ebbesson, Jonas

2017-04-01

The spatial and temporal dynamics of water resources are a continuous challenge for effective and sustainable national and international governance. Despite the surface watershed being the typical unit of water management, recent advances in hydrology have revealed 'atmospheric watersheds' - otherwise known as precipitationsheds. Also, recent research has demonstrated that water flowing within a precipitationshed may be modified by land-use change in one location, while the effect of this modification could be felt in a different province, nation, or continent. Notwithstanding these insights, the major legal and institutional implications of modifying moisture recycling have remained unexplored. In this presentation, we examine potential approaches to moisture recycling governance. We first identify a set of international study regions, and then develop a typology of moisture recycling relationships within these regions ranging from bilateral moisture exchange to more complex networks. This enables us to classify different types of legal and institutional governance principles. Likewise, we relate the moisture recycling types to existing land and water governance frameworks and management practices. The complexity of moisture recycling means institutional fit will be difficult to generalize for all moisture recycling relationships, but our typology allows the identification of characteristics that make effective governance of these normally ignored water flows more tenable.

Monitoring Welding-Gas Quality

NASA Technical Reports Server (NTRS)

Huddleston, Kevin L.

1988-01-01

System monitors welding gas to ensure characteristics within predetermined values. Responds to changes that might go unnoticed by human operator and acts quickly to prevent weld defects. Electronic pressure controller employs various amounts of gain, equalization, and compensation to respond to changes in gas-supply pressure. Works in conjuction with pressure/oxygen/moisture monitor.

Multivariate Drought Characterization in India for Monitoring and Prediction

NASA Astrophysics Data System (ADS)

Sreekumaran Unnithan, P.; Mondal, A.

2016-12-01

Droughts are one of the most important natural hazards that affect the society significantly in terms of mortality and productivity. The metric that is most widely used by the India Meteorological Department (IMD) to monitor and predict the occurrence, spread, intensification and termination of drought is based on the univariate Standardized Precipitation Index (SPI). However, droughts may be caused by the influence and interaction of many variables (such as precipitation, soil moisture, runoff, etc.), emphasizing the need for a multivariate approach for drought characterization. This study advocates and illustrates use of the recently proposed multivariate standardized drought index (MSDI) in monitoring and prediction of drought and assessing its concerned risk in the Indian region. MSDI combines information from multiple sources: precipitation and soil moisture, and has been deemed to be a more reliable drought index. All-India monthly rainfall and soil moisture data sets are analysed for the period 1980 to 2014 to characterize historical droughts using both the univariate indices, the precipitation-based SPI and the standardized soil moisture index (SSI), as well as the multivariate MSDI using parametric and non-parametric approaches. We confirm that MSDI can capture droughts of 1986 and 1990 that aren't detected by using SPI alone. Moreover, in 1987, MSDI indicated a higher severity of drought when a deficiency in both soil moisture and precipitation was encountered. Further, this study also explores the use of MSDI for drought forecasts and assesses its performance vis-à-vis existing predictions from the IMD. Future research efforts will be directed towards formulating a more robust standardized drought indicator that can take into account socio-economic aspects that also play a key role for water-stressed regions such as India.

Electrical Imaging of Roots and Trunks

NASA Astrophysics Data System (ADS)

Al Hagrey, S.; Werban, U.; Meissner, R.; Ismaeil, A.; Rabbel, W.

2005-05-01

We applied geoelectric and GPR techniques to analyze problems of botanical structures and even processes, e.g., mapping root zones, internal structure of trunks, and water uptake by roots. The dielectric nature of root zones and trunks is generally a consequence of relatively high moisture content. The electric method, applied to root zones, can discriminate between old, thick, isolated roots (high resistivity) and the network of young, active, and hydraulically conductive zones (low resistivity). Both types of roots show low radar velocity and a strong attenuation caused by the dominant effect of moisture (high dielectric constant) on the electromagnetic wave propagation. Single root branches could be observed in radargrams by their reflection and diffraction parabolas. We have perfected the inversion method for perfect and imperfect cylindrical objects, such as trunks, and developed a new multielectrodes (needle or gel) ring array for fast applications on living trees and discs. Using synthetic models we tested the technique successfully and analyzed it as a function of total electrode number and configuration. Measurements at a trunk show a well established inverse relationship between the imaged resistivity and the moisture content determined from cores. The central resistivity maximum of healthy trees strongly decreases toward the rim. This agrees with the moisture decrease to the outside where active sap flow processes take place. Branching, growth anomalies (new or old shoots) and meteorological effects (sunshine and wind direction) lead to deviations of the concentric electric structure. The strongest anomalies are related to infections causing wet, rotting spots or cavities. The heartwood resistivity is highest in olive and oak trunks, intermediate in young fruit trees and lowest in cork oak trunks that are considered to be anomalously wet. Compared to acoustic tomography our electric technique shows a better resolution in imaging internal ring structures where moisture is the most dominating factor. We conclude that our imaging resistivity technique is applicable for investigating or controlling the botanical and physical conditions of endangered trees (health inspection) and capable to monitor dynamic processes of sap flow if adequate tracers are used.

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

NASA Technical Reports Server (NTRS)

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

2013-01-01

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

A wireless soil moisture sensor powered by solar energy.

PubMed

Jiang, Mingliang; Lv, Mouchao; Deng, Zhong; Zhai, Guoliang

2017-01-01

In a variety of agricultural activities, such as irrigation scheduling and nutrient management, soil water content is regarded as an essential parameter. Either power supply or long-distance cable is hardly available within field scale. For the necessity of monitoring soil water dynamics at field scale, this study presents a wireless soil moisture sensor based on the impedance transform of the frequency domain. The sensor system is powered by solar energy, and the data can be instantly transmitted by wireless communication. The sensor electrodes are embedded into the bottom of a supporting rod so that the sensor can measure soil water contents at different depths. An optimal design with time executing sequence is considered to reduce the energy consumption. The experimental results showed that the sensor is a promising tool for monitoring moisture in large-scale farmland using solar power and wireless communication.

Use of geostationary satellite imagery in optical and thermal bands for the estimation of soil moisture status and land evapotranspiration

NASA Astrophysics Data System (ADS)

Ghilain, N.; Arboleda, A.; Gellens-Meulenberghs, F.

2009-04-01

For water and agricultural management, there is an increasing demand to monitor the soil water status and the land evapotranspiration. In the framework of the LSA-SAF project (http://landsaf.meteo.pt), we are developing an energy balance model forced by remote sensing products, i.e. radiation components and vegetation parameters, to monitor in quasi real-time the evapotranspiration rate over land (Gellens-Meulenberghs et al, 2007; Ghilain et al, 2008). The model is applied over the full MSG disk, i.e. including Europe and Africa. Meteorological forcing, as well as the soil moisture status, is provided by the forecasts of the ECMWF model. Since soil moisture is computed by a forecast model not dedicated to the monitoring of the soil water status, inadequate soil moisture input can occur, and can cause large effects on evapotranspiration rates, especially over semi-arid or arid regions. In these regions, a remotely sensed-based method for the soil moisture retrieval can therefore be preferable, to avoid too strong dependency in ECMWF model estimates. Among different strategies, remote sensing offers the advantage of monitoring large areas. Empirical methods of soil moisture assessment exist using remotely sensed derived variables either from the microwave bands or from the thermal bands. Mainly polar orbiters are used for this purpose, and little attention has been paid to the new possibilities offered by geosynchronous satellites. In this contribution, images of the SEVIRI instrument on board of MSG geosynchronous satellites are used. Dedicated operational algorithms were developed for the LSA-SAF project and now deliver images of land surface temperature (LST) every 15-minutes (Trigo et al, 2008) and vegetations indices (leaf area index, LAI; fraction of vegetation cover, FVC; fraction of absorbed photosynthetically active radiation, FAPAR) every day (Garcia-Haro et al, 2005) over Africa and Europe. One advantage of using products derived from geostationary satellites is the close monitoring of the diurnal variation of the land surface temperature. This feature reinforced the statistical strength of empirical methods. An empirical method linking land surface morning heating rates and the fraction of the vegetation cover, also known as a ‘Triangle method' (Gillies et al, 1997) is examined. This method is expected to provide an estimation of a root-zone soil moisture index. The sensitivity of the method to wind speed, soil type, vegetation type and climatic region is explored. Moreover, the impact of the uncertainty of LST and FVC on the resulting soil moisture estimates is assessed. A first impact study of using remotely sensed soil moisture index in the energy balance model is shown and its potential benefits for operational monitoring of evapotranspiration are outlined. References García-Haro, F.J., F. Camacho-de Coca, J. Meliá, B. Martínez (2005) Operational derivation of vegetation products in the framework of the LSA SAF project. Proceedings of the EUMETSAT Meteorological Satellite Conference Dubrovnik (Croatia) 19-23 Septembre. Gellens-Meulenberghs, F., Arboleda, A., Ghilain, N. (2007) Towards a continuous monitoring of evapotranspiration based on MSG data. Proceedings of the symposium on Remote Sensing for Environmental Monitoring and Change Detection. IAHS series. IUGG, Perugia, Italy, July 2007, 7 pp. Ghilain, N., Arboleda, A. and Gellens-Meulenberghs, F., (2008) Improvement of a surface energy balance model by the use of MSG-SEVIRI derived vegetation parameters. Proceedings of the 2008 EUMETSAT meteorological satellite data user's conference, Darmstadt, Germany, 8th-12th September, 7 pp. Gillies R.R., Carlson T.N., Cui J., Kustas W.P. and Humes K. (1997), Verification of the triangle method for obtaining surface soil water content and energy fluxes from remote measurements of Normalized Difference Vegetation Index (NDVI) and surface radiant temperature, International Journal of Remote Sensing, 18, pp. 3145-3166. Trigo, I.F., Monteiro I.T., Olesen F. and Kabsch E. (2008) An assessment of remotely sensed land surface temperature. Journal of Geophysical Research, 113, D17108, doi:10.1029/2008JD010035.

Soil Moisture Remote Sensing with GNSS-R at the Valencia Anchor Station. The SOMOSTA (Soil Moisture Station) Experiment

NASA Astrophysics Data System (ADS)

Lopez-Baeza, Ernesto

2016-07-01

In this paper, the SOMOSTA (Soil Moisture Monitoring Station) experiment on soil moisture monitoring byGlobal Navigation Satellite System Reflected signals(GNSS-R) at the Valencia Anchor Station is introduced. L-band microwaves have very good advantages in soil moisture remote sensing, for being unaffected by clouds and the atmosphere, and for the ability to penetrate vegetation. During this experimental campaign, the ESA GNSS-R Oceanpal antenna was installed on the same tower as the ESA ELBARA-II passive microwave radiometer, both measuring instruments having similar field of view. This experiment is fruitfully framed within the ESA - China Programme of Collaboration on GNSS-R. The GNSS-R instrument has an up-looking antenna for receiving direct signals from satellites, and two down-looking antennas for receiving LHCP (left-hand circular polarisation) and RHCP (right-hand circular polarisation) reflected signals from the soil surface. We could collect data from the three different antennas through the two channels of Oceanpal and, in addition, calibration could be performed to reduce the impact from the differing channels. Reflectivity was thus measured and soil moisture could be retrieved by the L- MEB (L-band Microwave Emission of the Biosphere) model considering the effect of vegetation optical thickness and soil roughness. By contrasting GNSS-R and ELBARA-II radiometer data, a negative correlation existed between reflectivity measured by GNSS-R and brightness temperature measured by the radiometer. The two parameters represent reflection and absorption of the soil. Soil moisture retrieved by both L-band remote sensing methods shows good agreement. In addition, correspondence with in-situ measurements and rainfall is also good.

Measuring moisture dynamics to predict fire severity in longleaf pine forests.

Treesearch

Sue A. Ferguson; Julia E. Ruthford; Steven J. McKay; David Wright; Clint Wright; Roger Ottmar

2002-01-01

To understand the combustion limit of biomass fuels in a longleaf pine (Pinus palustris) forest, an experiment was conducted to monitor the moisture content of potentially flammable forest floor materials (litter and duff) at Eglin Air Force Base in the Florida Panhandle. While longleaf pine forests are fire dependent ecosystems, a long history of...

Overview of SMOS performance in terms of global soil moisture monitoring after six years in operation

USDA-ARS?s Scientific Manuscript database

The Soil Moisture and Ocean Salinity satellite (SMOS) was launched in November 2009 and started delivering data in January 2010. The commissioning phase ended in May 2010. Subsequently, the satellite has been in operation for over 5 years while the retrieval algorithms from Level 1 to Level 2 underw...

Modelling the passive microwave signature from land surfaces: a review of recent results and application to the SMOS & SMAP soil moisture retrieval algorithms

USDA-ARS?s Scientific Manuscript database

Two passive microwave missions are currently operating at L-band to monitor surface soil moisture (SM) over continental surfaces. The SMOS sensor, based on an innovative interferometric technology enabling multi-angular signatures of surfaces to be measured, was launched in November 2009....

Basement radon entry and stack driven moisture infiltration reduced by active soil depressurization

Treesearch

C.R. Boardman; Samuel V. Glass

2015-01-01

This case study presents measurements of radon and moisture infiltration from soil gases into the basement of an unoccupied research house in Madison, Wisconsin, over two full years. The basement floor and exterior walls were constructed with preservative-treated lumber and plywood. In addition to continuous radon monitoring, measurements included building air...

Improving operational flood ensemble prediction by the assimilation of satellite soil moisture: comparison between lumped and semi-distributed schemes

USDA-ARS?s Scientific Manuscript database

Assimilation of remotely sensed soil moisture data (SM-DA) to correct soil water stores of rainfall-runoff models has shown skill in improving streamflow prediction. In the case of large and sparsely monitored catchments, SM-DA is a particularly attractive tool.Within this context, we assimilate act...

Remote monitoring of soil moisture using airborne microwave radiometers

NASA Technical Reports Server (NTRS)

Kroll, C. L.

1973-01-01

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

Mechanisms of Decreased Moisture Uptake in ortho- Methylated Di(Cyanate Esters)

DTIC Science & Technology

2014-10-01

Distribution A: Approved for public release; distribution is unlimited. 1 Mechanisms of Decreased Moisture Uptake in ortho- Methylated Di(Cyanate...when analogous networks containing a single methyl group ortho- to each aryl- cyanurate linkage were prepared by reduction and acid-catalyzed coupling...of salicylic acid followed by treatment with cyanogen bromide and subsequent cyclotrimerization. The differences in water uptake were observed

From ASCAT to Sentinel-1: Soil Moisture Monitoring using European C-Band Radars

NASA Astrophysics Data System (ADS)

Wagner, Wolfgang; Bauer-Marschallinger, Bernhard; Hochstöger, Simon

2016-04-01

The Advanced Scatterometer (ASCAT) is a C-Band radar instrument flown on board of the series of three METOP satellites. Albeit not operating in one of the more favorable longer wavelength ranges (S, L or P-band) as the dedicated Soil Moisture and Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) missions, it is one of main microwave sensors used for monitoring of soil moisture on a global scale. Its attractiveness for soil moisture monitoring applications stems from its operational status, high radiometric accuracy and stability, short revisit time, multiple viewing directions and long heritage (Wagner et al. 2013). From an application perspective, its main limitation is its spatial resolution of about 25 km, which does not allow resolving soil moisture patterns driven by smaller-scale hydrometeorological processes (e.g. convective precipitation, runoff patterns, etc.) that are themselves related to highly variable land surface characteristics (soil characteristics, topography, vegetation cover, etc.). Fortunately, the technique of aperture synthesis allows to significantly improve the spatial resolution of spaceborne radar instruments up to the meter scale. Yet, past Synthetic Aperture Radar (SAR) missions had not yet been designed to achieve a short revisit time required for soil moisture monitoring. This has only changed recently with the development and launch of SMAP (Entekhabi et al. 2010) and Sentinel-1 (Hornacek et al. 2012). Unfortunately, the SMAP radar failed only after a few months of operations, which leaves Sentinel-1 as the only currently operational SAR mission capable of delivering high-resolution radar observations with a revisit time of about three days for Europe, about weekly for most crop growing regions worldwide, and about bi-weekly to monthly over the rest of the land surface area. Like ASCAT, Sentinel-1 acquires C-band backscatter data in VV polarization over land. Therefore, for the interpretation of both ASCAT and Sentinel-1 backscatter observation, the same physical processes and geophysical variables (e.g. vegetation optical depth, surface roughness, soil volume scattering, etc.) need to be considered. The difference lies mainly in the scaling, i.e. how prominently the different variables influence the C-band data at the different spatial (25 km versus 20 m) and temporal (daily versus 3-30 days repeat coverage) scales. Therefore, while the general properties of soil moisture retrievals schemes used for ASCAT and Sentinel-1 can be the same, the details of the algorithm and parameterization will be different. This presentation will review similarities and differences of soil moisture retrieval approaches used for ASCAT and Sentinel-1, with a focus on the change detection method developed by TU Wien. Some first comparisons of ASCAT and Sentinel-1 soil moisture data over Europe will also be shown. REFERENCES Entekhabi, D., Njoku, E.G., O'Neill, P.E., Kellog, K.H., Crow, W.T., Edelstein, W.N., Entin, J.K., Goodman, S.D., Jackson, T.J., Johnson, J., Kimball, J., Piepmeier, J.R., Koster, R., Martin, N., McDonald, K.C., Moghaddam, M., Moran, S., Reichle, R., Shi, J.C., Spencer, M.W., Thurman, S.W., Tsang, L., & Van Zyl, J. (2010). The Soil Moisture Active Passive (SMAP) mission. Proceedings of the IEEE, 98, 704-716 Hornacek, M., Wagner, W., Sabel, D., Truong, H.L., Snoeij, P., Hahmann, T., Diedrich, E., & Doubkova, M. (2012). Potential for High Resolution Systematic Global Surface Soil Moisture Retrieval via Change Detection Using Sentinel-1. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 5, 1303-1311 Wagner, W., Hahn, S., Kidd, R., Melzer, T., Bartalis, Z., Hasenauer, S., Figa-Saldana, J., De Rosnay, P., Jann, A., Schneider, S., Komma, J., Kubu, G., Brugger, K., Aubrecht, C., Züger, C., Gangkofer, U., Kienberger, S., Brocca, L., Wang, Y., Blöschl, G., Eitzinger, J., Steinnocher, K., Zeil, P., & Rubel, F. (2013). The ASCAT soil moisture product: A review of its specifications, validation results, and emerging applications. Meteorologische Zeitschrift, 22, 5-33

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Grower demand for sensor-controlled irrigation

NASA Astrophysics Data System (ADS)

Lichtenberg, Erik; Majsztrik, John; Saavoss, Monica

2015-01-01

Water scarcity is likely to increase in the coming years, making improvements in irrigation efficiency increasingly important. An emerging technology that promises to increase irrigation efficiency substantially is a wireless irrigation sensor network that uploads sensor data into irrigation management software, creating an integrated system that allows real-time monitoring and control of moisture status that has been shown in experimental settings to reduce irrigation costs, lower plant loss rates, shorten production times, decrease pesticide application, and increase yield, quality, and profit. We use an original survey to investigate likely initial acceptance, ceiling adoption rates, and profitability of this new sensor network technology in the nursery and greenhouse industry. We find that adoption rates for a base system and demand for expansion components are decreasing in price, as expected. The price elasticity of the probability of adoption suggests that sensor networks are likely to diffuse at a rate somewhat greater than that of drip irrigation. Adoption rates for a base system and demand for expansion components are increasing in specialization in ornamental production: growers earning greater shares of revenue from greenhouse and nursery operations are willing to pay more for a base system and are willing to purchase larger numbers of expansion components at any given price. We estimate that growers who are willing to purchase a sensor network expect investment in this technology to generate significant profit, consistent with findings from experimental studies.

MoisturEC: an R application for geostatistical estimation of moisture content from electrical conductivity data

NASA Astrophysics Data System (ADS)

Terry, N.; Day-Lewis, F. D.; Werkema, D. D.; Lane, J. W., Jr.

2017-12-01

Soil moisture is a critical parameter for agriculture, water supply, and management of landfills. Whereas direct data (as from TDR or soil moisture probes) provide localized point scale information, it is often more desirable to produce 2D and/or 3D estimates of soil moisture from noninvasive measurements. To this end, geophysical methods for indirectly assessing soil moisture have great potential, yet are limited in terms of quantitative interpretation due to uncertainty in petrophysical transformations and inherent limitations in resolution. Simple tools to produce soil moisture estimates from geophysical data are lacking. We present a new standalone program, MoisturEC, for estimating moisture content distributions from electrical conductivity data. The program uses an indicator kriging method within a geostatistical framework to incorporate hard data (as from moisture probes) and soft data (as from electrical resistivity imaging or electromagnetic induction) to produce estimates of moisture content and uncertainty. The program features data visualization and output options as well as a module for calibrating electrical conductivity with moisture content to improve estimates. The user-friendly program is written in R - a widely used, cross-platform, open source programming language that lends itself to further development and customization. We demonstrate use of the program with a numerical experiment as well as a controlled field irrigation experiment. Results produced from the combined geostatistical framework of MoisturEC show improved estimates of moisture content compared to those generated from individual datasets. This application provides a convenient and efficient means for integrating various data types and has broad utility to soil moisture monitoring in landfills, agriculture, and other problems.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Spatiotemporal monitoring of soil water content profiles in an irrigated field using probabilistic inversion of time-lapse EMI data

NASA Astrophysics Data System (ADS)

Moghadas, Davood; Jadoon, Khan Zaib; McCabe, Matthew F.

2017-12-01

Monitoring spatiotemporal variations of soil water content (θ) is important across a range of research fields, including agricultural engineering, hydrology, meteorology and climatology. Low frequency electromagnetic induction (EMI) systems have proven to be useful tools in mapping soil apparent electrical conductivity (σa) and soil moisture. However, obtaining depth profile water content is an area that has not been fully explored using EMI. To examine this, we performed time-lapse EMI measurements using a CMD mini-Explorer sensor along a 10 m transect of a maize field over a 6 day period. Reference data were measured at the end of the profile via an excavated pit using 5TE capacitance sensors. In order to derive a time-lapse, depth-specific subsurface image of electrical conductivity (σ), we applied a probabilistic sampling approach, DREAM(ZS) , on the measured EMI data. The inversely estimated σ values were subsequently converted to θ using the Rhoades et al. (1976) petrophysical relationship. The uncertainties in measured σa, as well as inaccuracies in the inverted data, introduced some discrepancies between estimated σ and reference values in time and space. Moreover, the disparity between the measurement footprints of the 5TE and CMD Mini-Explorer sensors also led to differences. The obtained θ permitted an accurate monitoring of the spatiotemporal distribution and variation of soil water content due to root water uptake and evaporation. The proposed EMI measurement and modeling technique also allowed for detecting temporal root zone soil moisture variations. The time-lapse θ monitoring approach developed using DREAM(ZS) thus appears to be a useful technique to understand spatiotemporal patterns of soil water content and provide insights into linked soil moisture vegetation processes and the dynamics of soil moisture/infiltration processes.

Biowaste home composting: experimental process monitoring and quality control.

PubMed

Tatàno, Fabio; Pagliaro, Giacomo; Di Giovanni, Paolo; Floriani, Enrico; Mangani, Filippo

2015-04-01

Because home composting is a prevention option in managing biowaste at local levels, the objective of the present study was to contribute to the knowledge of the process evolution and compost quality that can be expected and obtained, respectively, in this decentralized option. In this study, organized as the research portion of a provincial project on home composting in the territory of Pesaro-Urbino (Central Italy), four experimental composters were first initiated and temporally monitored. Second, two small sub-sets of selected provincial composters (directly operated by households involved in the project) underwent quality control on their compost products at two different temporal steps. The monitored experimental composters showed overall decreasing profiles versus composting time for moisture, organic carbon, and C/N, as well as overall increasing profiles for electrical conductivity and total nitrogen, which represented qualitative indications of progress in the process. Comparative evaluations of the monitored experimental composters also suggested some interactions in home composting, i.e., high C/N ratios limiting organic matter decomposition rates and final humification levels; high moisture contents restricting the internal temperature regime; nearly horizontal phosphorus and potassium evolutions contributing to limit the rates of increase in electrical conductivity; and prolonged biowaste additions contributing to limit the rate of decrease in moisture. The measures of parametric data variability in the two sub-sets of controlled provincial composters showed decreased variability in moisture, organic carbon, and C/N from the seventh to fifteenth month of home composting, as well as increased variability in electrical conductivity, total nitrogen, and humification rate, which could be considered compatible with the respective nature of decreasing and increasing parameters during composting. The modeled parametric kinetics in the monitored experimental composters, along with the evaluation of the parametric central tendencies in the sub-sets of controlled provincial composters, all indicate that 12-15 months is a suitable duration for the appropriate development of home composting in final and simultaneous compliance with typical reference limits. Copyright © 2014 Elsevier Ltd. All rights reserved.

Predicting Ascospore Release of Monilinia vaccinii-corymbosi of Blueberry with Machine Learning.

PubMed

Harteveld, Dalphy O C; Grant, Michael R; Pscheidt, Jay W; Peever, Tobin L

2017-11-01

Mummy berry, caused by Monilinia vaccinii-corymbosi, causes economic losses of highbush blueberry in the U.S. Pacific Northwest (PNW). Apothecia develop from mummified berries overwintering on soil surfaces and produce ascospores that infect tissue emerging from floral and vegetative buds. Disease control currently relies on fungicides applied on a calendar basis rather than inoculum availability. To establish a prediction model for ascospore release, apothecial development was tracked in three fields, one in western Oregon and two in northwestern Washington in 2015 and 2016. Air and soil temperature, precipitation, soil moisture, leaf wetness, relative humidity and solar radiation were monitored using in-field weather stations and Washington State University's AgWeatherNet stations. Four modeling approaches were compared: logistic regression, multivariate adaptive regression splines, artificial neural networks, and random forest. A supervised learning approach was used to train the models on two data sets: training (70%) and testing (30%). The importance of environmental factors was calculated for each model separately. Soil temperature, soil moisture, and solar radiation were identified as the most important factors influencing ascospore release. Random forest models, with 78% accuracy, showed the best performance compared with the other models. Results of this research helps PNW blueberry growers to optimize fungicide use and reduce production costs.

SSS variability inferred from recent SMOS reprocessing at CATDS

NASA Astrophysics Data System (ADS)

Boutin, Jacqueline; Vergely, Jean-Luc; Marchand, Stéphane; Tarot, Stéphane; Hasson, Audrey; Reverdin, Gilles

2017-04-01

The Soil Moisture and Ocean Salinity (SMOS) satellite mission has monitored sea surface salinity (SSS) over the global ocean for over 7 years. In this poster, we present results obtained at the LOCEAN/ACRI-st expertise center using recent CATDS (Centre Aval de Traitement des Données) SMOS RE05 reprocessing., We find that correction for systematic errors and removal of data contaminated by ice and radio frequency interferences in fresh regions (river mouths, high latitudes) has been improved with respect to SMOS CATDS RE04 reprocessing. We analyze SSS variability as observed by SMOS on a wide range of spatial and temporal scales using various statistical indicators such as mean, median, standard deviation, minimum, maximum values and spectral analysis. We compare them with ARGO interpolated fields (In Situ Analysis System fields) at global scale and with ship SSS transects from the GOSUD and ORE SSS data base. This allows us 1) to demonstrate and quantify the improvement of SMOS SSS fields with respect to earlier versions and 2) to study SSS variability, especially at spatial scales between 50km and 600km not well covered globally by in situ network. The complementarity of this information with respect to SMAP (Soil Moisture Active Passive) SSS fields will be discussed.

Post-Closure Report for Closed Resource Conservation and Recovery Act Corrective Action Units, Nevada National Security Site, Nevada, for Fiscal Year 2014

DOE Office of Scientific and Technical Information (OSTI.GOV)

Silvas, Alissa J.

2015-01-01

This report serves as the combined annual report for post-closure activities for several Corrective Action Units (CAUs). The locations of the sites are shown in Figure 1. This report covers fiscal year 2014 (October 2013–September 2014). The post-closure requirements for these sites are described in Resource Conservation and Recovery Act Permit Number NEV HW0101 and summarized in each CAU-specific section in Section 1.0 of this report. The results of the inspections, a summary of maintenance activities, and an evaluation of monitoring data are presented in this report. Site inspections are conducted semiannually at CAUs 90 and 91 and quarterly atmore » CAUs 92, 110, 111, and 112. Additional inspections are conducted at CAU 92 if precipitation occurs in excess of 0.50 inches (in.) in a 24-hour period and at CAU 111 if precipitation occurs in excess of 1.0 in. in a 24-hour period. Inspections include an evaluation of the condition of the units, including covers, fences, signs, gates, and locks. In addition to visual inspections, soil moisture monitoring, vegetation evaluations, and subsidence surveys are conducted at CAU 110. At CAU 111, soil moisture monitoring, vegetation evaluations, subsidence surveys, direct radiation monitoring, air monitoring, radon flux monitoring, and groundwater monitoring are conducted. The results of the vegetation surveys and an analysis of the soil moisture monitoring data at CAU 110 are presented in this report. Results of additional monitoring at CAU 111 are documented annually in the Nevada National Security Site Waste Management Monitoring Report Area 3 and Area 5 Radioactive Waste Management Sites and in the Nevada National Security Site Data Report: Groundwater Monitoring Program Area 5 Radioactive Waste Management Site, which will be prepared in approximately June 2015. All required inspections, maintenance, and monitoring were conducted in accordance with the post-closure requirements of the permit. It is recommended to continue inspections and monitoring as scheduled.« less

Effects of Seasonal Land Surface Conditions on Hydrometeorological Dynamics in South-western North America

DTIC Science & Technology

2015-09-21

vehicles, environmental sensor networks, distributed hydrologic modeling, vegetation dynamics, soil moisture, evapotranspiration , remote sensing, North...Received Paper 1.00 5.00 3.00 8.00 9.00 E. Vivoni, J. Rodriguez, C. Watts. On the spatiotemporal variability of soil moisture and evapotranspiration ...Vegetation Impacts on Evapotranspiration and Its Partitioning at the Catchment Scale during SMEX04–NAME, Journal of Hydrometeorology, (10 2012

Non-Nuclear Alternatives to Monitoring Moisture-Density Response in Soils

DTIC Science & Technology

2013-03-01

devices can be done pretest or posttest , as they all provide a means to correct the raw field data readings. Moisture Density Indicator (M+DI) The...obtained from the soil nuclear density gauge. The devices and techniques that were tested are grouped into four broad families: nuclear, electrical...43  Details of device rejection based on errors .............................................................................. 43  Accuracy of

Spectral detection of near-surface moisture content and water-table position in northern peatland ecosystems

Treesearch

Karl M. Meingast; Michael J. Falkowski; Evan S. Kane; Lynette R. Potvin; Brian W. Benscoter; Alistair M.S. Smith; Laura L. Bourgeau-Chavez; Mary Ellen Miller

2014-01-01

Wildland fire occurrence has been increasing in peatland ecosystems during recent decades. As such, there is a need for broadly applicable tools to detect and monitor controls on combustion such as surface peat moisture and water-table position. A field portable spectroradiometer was used to measure surface reflectance of two Sphagnum moss-dominated...

A review of satellite-based methods of estimating live fuel moisture content for fire danger assessment: moving towards operational products

USDA-ARS?s Scientific Manuscript database

One of the primary variables affecting ignition and spread of wildfire is fuel moisture content (FMC), which is the ratio of water mass to dry mass in living and dead plant material. Because dead FMC may be estimated from available weather data, remote sensing is needed to monitor the spatial distr...

Environmental change at Kartchner Caverns: trying to separate natural and anthropogenic changes

Treesearch

Rickard S. Toomey; Ginger Nolan

2005-01-01

Cave temperature and moisture levels are important factors in the environmental health of Kartchner Caverns. Monitoring indicates the cave has warmed and moisture levels have fallen over the past 14 years. Timing and patterns of change within the cave suggest that changes are due to development as a show cave. However, changes in other caves, surface temperature and...

Scaling an in situ network for high resolution modeling during SMAPVEX15

USDA-ARS?s Scientific Manuscript database

Among the greatest challenges within the field of soil moisture estimation is that of scaling sparse point measurements within a network to produce higher resolution map products. Large-scale field experiments present an ideal opportunity to develop methodologies for this scaling, by coupling in si...

Evaluation of the performance of hydrological variables derived from GLDAS-2 and MERRA-2 in Mexico

NASA Astrophysics Data System (ADS)

Real-Rangel, R. A.; Pedrozo-Acuña, A.; Breña-Naranjo, J. A.

2017-12-01

Hydrological studies have found in data assimilation systems and global reanalysis of land surface variables (e.g soil moisture, streamflow) a wide range of applications, from drought monitoring to water balance and hydro-climatology variability assessment. Indeed, these hydrological data sources have led to an improvement in developing and testing monitoring and prediction systems in poorly gauged regions of the world. This work tests the accuracy and error of land surface variables (precipitation, soil moisture, runoff and temperature) derived from the data assimilation reanalysis products GLDAS-2 and MERRA-2. Validate the performance of these data platforms must be thoroughly evaluated in order to consider the error of hydrological variables (i.e., precipitation, soil moisture, runoff and temperature) derived from the reanalysis products. For such purpose, a quantitative assessment was performed at 2,892 climatological stations, 42 stream gauges and 44 soil moisture probes located in Mexico and across different climate regimes (hyper-arid to tropical humid). Results show comparisons between these gridded products against ground-based observational stations for 1979-2014. The results of this analysis display a spatial distribution of errors and accuracy over Mexico discussing differences between climates, enabling the informed use of these products.

Technology Solutions Case Study: Monitoring of Double Stud Wall Moisture Conditions in the Northeast, Devens, Massachusetts

DOE Office of Scientific and Technical Information (OSTI.GOV)

None

2015-03-01

Double stud walls have a higher risk of interior-sourced condensation moisture damage when compared with high-R approaches using exterior insulating sheathing. In this project, Building Science Corporation monitored moisture conditions in double-stud walls from 2011 through 2014 at a new production house located in Devens, Massachusetts. The builder, Transformations, Inc., has been using double-stud walls insulated with 12 in. of open cell polyurethane spray foam (ocSPF); however, the company has been considering a change to netted and blown cellulose insulation for cost reasons. Cellulose is a common choice for double-stud walls because of its lower cost (in most markets). However,more » cellulose is an air-permeable insulation, unlike spray foams, which increases interior moisture risks. The team compared three double-stud assemblies: 12 in. of ocSPF, 12 in. of cellulose, and 5-½ in. of ocSPF at the exterior of a double-stud wall (to approximate conventional 2 × 6 wall construction and insulation levels, acting as a control wall). These assemblies were repeated on the north and south orientations, for a total of six assemblies.« less

A New Approach in Downscaling Microwave Soil Moisture Product using Machine Learning

NASA Astrophysics Data System (ADS)

Abbaszadeh, Peyman; Yan, Hongxiang; Moradkhani, Hamid

2016-04-01

Understating the soil moisture pattern has significant impact on flood modeling, drought monitoring, and irrigation management. Although satellite retrievals can provide an unprecedented spatial and temporal resolution of soil moisture at a global-scale, their soil moisture products (with a spatial resolution of 25-50 km) are inadequate for regional study, where a resolution of 1-10 km is needed. In this study, a downscaling approach using Genetic Programming (GP), a specialized version of Genetic Algorithm (GA), is proposed to improve the spatial resolution of satellite soil moisture products. The GP approach was applied over a test watershed in United States using the coarse resolution satellite data (25 km) from Advanced Microwave Scanning Radiometer - EOS (AMSR-E) soil moisture products, the fine resolution data (1 km) from Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation index, and ground based data including land surface temperature, vegetation and other potential physical variables. The results indicated the great potential of this approach to derive the fine resolution soil moisture information applicable for data assimilation and other regional studies.

Cavitation controlled acoustic probe for fabric spot cleaning and moisture monitoring

DOEpatents

Sheen, Shuh-Haw; Chien, Hual-Te; Raptis, Apostolos C.

1997-01-01

A method and apparatus are provided for monitoring a fabric. An acoustic probe generates acoustic waves relative to the fabric. An acoustic sensor, such as an accelerometer is coupled to the acoustic probe for generating a signal representative of cavitation activity in the fabric. The generated cavitation activity representative signal is processed to indicate moisture content of the fabric. A feature of the invention is a feedback control signal is generated responsive to the generated cavitation activity representative signal. The feedback control signal can be used to control the energy level of the generated acoustic waves and to control the application of a cleaning solution to the fabric.

Remote sensing monitoring the spatio-temporal changes of aridification in the Mongolian Plateau based on the general Ts-NDVI space, 1981-2012

NASA Astrophysics Data System (ADS)

Cao, Xiaoming; Feng, Yiming; Wang, Juanle

2017-06-01

This paper has developed a general Ts-NDVI triangle space with vegetation index time-series data from AVHRR and MODIS to monitor soil moisture in the Mongolian Plateau during 1981-2012, and studied the spatio-temporal variations of drought based on the temperature vegetation dryness index (TVDI). The results indicated that (1) the developed general Ts-NDVI space extracted from the AVHRR and MODIS remote sensing data would be an effective method to monitor regional drought, moreover, it would be more meaningful if the single time Ts-NDVI space showed an unstable condition; (2) the inverted TVDI was expected to reflect the water deficit in the study area. It was found to be in close negative agreement with precipitation and 10 cm soil moisture; (3) in the Mongolian Plateau, TVDI presented a zonal distribution with changes in land use/land cover types, vegetation cover and latitude. The soil moisture is low in bare land, construction land and grassland. During 1981-2012, drought was widely spread throughout the plateau, and aridification was obvious in the study period. Vegetation degradation, overgrazing, and climate warming could be considered as the main reasons.

Critical moisture content for microbial growth in dried food-processing residues.

PubMed

Rezaei, Farzaneh; Vandergheynst, Jean S

2010-09-01

Food-processing residues are good feedstocks for biofuel and biochemical production because they have high energy content and are abundant. Year-round biofuel and biochemical production requires proper storage to prevent microbial decomposition and thermal runaway. In this study, microbial activity of tomato pomace (TP), grape pomace (GP), fermented grape pomace (FGP) and sugar beet pulp (SBP) was monitored at nine different moisture contents. Maximum and cumulative respirations for each feedstock with respect to moisture content followed a sigmoidal relationship. The critical moisture content below which no microbial activity was detected for SBP, TP, FGP and GP was 24-31, 16-21, 23-33 and 43-46% (dry basis) respectively. A logarithmic relationship was observed (R(2) = 0.94) between critical moisture content and initial water-soluble carbohydrate (WSC) content of the processing residues. The critical moisture content below which no microbial activity was detected and the relationship between critical moisture content and initial WSC content were determined in this study for four food-processing residues. Both parameters permit evaluation of the potential for deterioration of food-processing residues during storage based on moisture content and WSC content. Copyright 2010 Society of Chemical Industry.

Time domain reflectometry measured moisture content of sewage sludge compost across temperatures.

PubMed

Cai, Lu; Chen, Tong-Bin; Gao, Ding; Liu, Hong-Tao; Chen, Jun; Zheng, Guo-Di

2013-01-01

Time domain reflectometry (TDR) is a prospective measurement technology for moisture content of sewage sludge composting material; however, a significant dependence upon temperature has been observed. The objective of this study was to assess the impacts of temperature upon moisture content measurement and determine if TDR could be used to monitor moisture content in sewage sludge compost across a range of temperatures. We also investigated the combined effects of temperature and conductivity on moisture content measurement. The results revealed that the moisture content of composting material could be determined by TDR using coated probes, even when the measured material had a moisture content of 0.581 cm(3)cm(-3), temperature of 70°C and conductivity of 4.32 mS cm(-1). TDR probes were calibrated as a function of dielectric properties that included temperature effects. When the bulk temperature varied from 20°C to 70°C, composting material with 0.10-0.70 cm(3)cm(-3) moisture content could be measured by TDR using coated probes, and calibrations based on different temperatures minimized the errors. Copyright © 2012. Published by Elsevier Ltd.

Development of low cost, high reliability sealing techniques for hybrid microcircuit packages. Phase 2, supplement 1: Moisture permeation of adhesive-sealed hybrid microcircuit packages

NASA Technical Reports Server (NTRS)

Perkins, K. L.; Licari, J. J.

1978-01-01

The susceptibility of adhesive-sealed ceramic packages to moisture permeation was investigated. The two adhesives, Ablebond 789-1 and Epo-Tek H77, were evaluated as package sealants. These adhesives were previously selected as the most promising candidates for this application from a group of ten adhesives. Ceramic packages sealed with these adhesives were exposed to temperature-humidity conditions of 25 C/98 percent RH, 50 C/60 percent RH, 50 C/98 percent RH, and 85 C/85 percent RH and their moisture contents using were monitored solid state moisture sensors sealed inside them. Five packages were tested at each of these exposures - two ceramic packages sealed with each of the two adhesives and one seam-sealed gold-plated Kovar package. This latter package was included to serve as a control. The results showed that the adhesive-sealed packages were not hermetic to moisture. The rates at which moisture entered the packages increased with the severity of the exposure environments (i.e., higher temperatures and higher moisture vapor pressures) with greater dependence on temperature than on moisture vapor pressure.

Time-lapse Seismic Refraction Monitoring of an Active Landslide in Lias Group Mudrocks, North Yorkshire, UK

NASA Astrophysics Data System (ADS)

Uhlemann, S.; Whiteley, J.; Chambers, J. E.; Inauen, C.; Swift, R. T.

2017-12-01

Geophysical monitoring of the internal moisture content and processes of landslides is an increasingly common approach to the characterisation and assessment of the hydrogeological condition of rainfall-triggered landslides. Geoelectrical monitoring methods are sensitive to changes in the subsurface moisture conditions that cause the failure of unstable slopes, typically through the increase of pore water pressures and softening of materials within the landslide system. The application of seismic methods to the monitoring of landslides has not been as extensively applied as geoelectrical approaches, but the seismic method can determine elastic properties of landslide materials that can characterise and identify changes in the geomechanical condition of landslide systems that also lead to slope failure. We present the results of a seismic refraction monitoring campaign undertaken at the Hollin Hill Landslide Observatory in North Yorkshire, UK. This campaign has involved the repeat acquisition of surface acquired high resolution P- and S-wave seismic refraction data. The monitoring profile traverses a 142m long section from the crest to the toe of an active landslide comprising of mudstone and sandstone. Data were acquired at six to nine week intervals between October 2016 and October 2017. This repeat acquisition approach allowed for the imaging of seismically determined property changes of the landslide throughout the annual climatic cycle. Initial results showed that changes in the moisture dynamics of the landslide are reflected by changes in the seismic character of the inverted tomograms. Changes in the seismic properties are linked to the changes in the annual climatic cycle, particularly in relation to effective rainfall. The results indicate that the incorporation of seismic monitoring data into ongoing geoelectrical monitoring programmes can provide complementary geomechanical data to enhance our understanding of the internal condition of landslide systems. Future development of this integrated approach will allow for the imaging and monitoring of these systems at unprecedented spatial and temporal scales.

Remote sensing applied to crop disease control, urban planning, and monitoring aquatic plants, oil spills, rangelands, and soil moisture

NASA Technical Reports Server (NTRS)

1975-01-01

The application of remote sensing techniques to land management, urban planning, agriculture, oceanography, and environmental monitoring is discussed. The results of various projects are presented along with cost effective considerations.

Drought monitoring using remote sensing of evapotranspiration

USDA-ARS?s Scientific Manuscript database

Drought assessment is a complex endeavor, requiring monitoring of deficiencies in multiple components of the hydrologic budget. Precipitation anomalies reflect variability in water supply to the land surface, while soil moisture (SM), ground and surface water anomalies reflect deficiencies in moist...

Coordination of load response instrumentation of SHRP pavements, Ohio University : executive summary, May 1999.

DOT National Transportation Integrated Search

1999-05-01

Sensors were installed in 18 test sections to continuously monitor temperature, moisture, and frost within the pavement structure, and 33 test sections were instrumented to monitor strain, deflection and pressure generated by environmental cycling an...

SURFEX modeling of soil moisture fields over the Valencia Anchor Station and their comparison to different SMOS products and in situ measurements

NASA Astrophysics Data System (ADS)

Coll Pajaron, M. Amparo; Lopez-Baeza, Ernesto; Fernandez-Moran, Roberto; Samiro Khodayar-Pardo, D.

2016-07-01

Soil moisture is a difficult variable to obtain proper representation because of its high temporal and spatial variability. It is a significant parameter in agriculture, hydrology, meteorology and related disciplines. {it SVAT (Soil-Vegetation-Atmosphere-Transfer)} models can be used to simulate the temporal behaviour and spatial distribution of soil moisture in a given area. In this work, we use the {bf SURFEX (Surface Externalisée)} model developed at the {it Centre National de Recherches Météorologiques (CNRM)} at Météo-France (http://www.cnrm.meteo.fr/surfex/) to simulate soil moisture at the {bf Valencia Anchor Station}. SURFEX integrates the {bf ISBA (Interaction Sol-Biosphère-Atmosphère}; surfaces with vegetation) module to describe the land surfaces (http://www.cnrm.meteo.fr/isbadoc/model.html) that have been adapted to describe the land covers of our study area. The Valencia Anchor Station was chosen as a core validation site for the {it SMOS (Soil Moisture and Ocean Salinity)} mission and as one of the hydrometeorological sites for the {it HyMeX (HYdrological cycle in Mediterranean EXperiment)} programme. This site represents a reasonably homogeneous and mostly flat area of about 50x50 km2. The main cover type is vineyards (65%), followed by fruit trees, shrubs, and pine forests, and a few small scattered industrial and urban areas. Except for the vineyard growing season, the area remains mostly under bare soil conditions. In spite of its relatively flat topography, the small altitude variations of the region clearly influence climate. This oscillates between semiarid and dry sub-humid. Annual mean temperatures are between 12 ºC and 14.5 ºC, and annual precipitation is about 400-450 mm. The duration of frost free periods is from May to November, with maximum precipitation in spring and autumn. The first part of this investigation consists in simulating soil moisture fields over the Valencia Anchor Station to be compared with SMOS level-2 (resolution 15 km) and level-3 (resolution 25 km) soil moisture maps and high resolution SMOS pixel-disaggregated soil moisture products, obtained by combining SMOS level-2 with MODIS NDVI and LST data (resolution 1 km) (Piles et al., 2011). In situ measurements from the Valencia Anchor Station network of soil moisture stations are also available as reference covering a reduced number of different vegetation cover and soil types, as well as estimations from the ESA ELBARA-II L-band radiometer installed over a vineyard crop to monitor SMOS validation conditions. Different interpolation methods have been applied to all significant atmospheric forcing parameters from the two met stations available in the area (pressure, temperature, relative humidity and precipitation) in order to obtain a good representation of soil conditions. The period of investigation covers the complete year 2012 of which we will particularly focus on selected periods.

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

NASA Astrophysics Data System (ADS)

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

2012-04-01

The knowledge of spatially distributed soil moisture is highly desirable for an enhanced hydrological modeling in terms of flood prevention and for yield optimization in combination with precision farming. Especially in mid-latitudes, the growing agricultural vegetation results in an increasing soil coverage along the crop cycle. For a remote sensing approach, this vegetation influence has to be separated from the soil contribution within the resolution cell to extract the actual soil moisture. Therefore a hybrid decomposition was developed for estimation of soil moisture under vegetation cover using fully polarimetric SAR data. The novel polarimetric decomposition combines a model-based decomposition, separating the volume component from the ground components, with an eigen-based decomposition of the two ground components into a surface and a dihedral scattering contribution. Hence, this hybrid decomposition, which is based on [1,2], establishes an innovative way to retrieve soil moisture under vegetation. The developed inversion algorithm for soil moisture under vegetation cover is applied on fully polarimetric data of the TERENO campaign, conducted in May and June 2011 for the Rur catchment within the Eifel/Lower Rhine Valley Observatory. The fully polarimetric SAR data were acquired in high spatial resolution (range: 1.92m, azimuth: 0.6m) by DLR's novel F-SAR sensor at L-band. The inverted soil moisture product from the airborne SAR data is validated with corresponding distributed ground measurements for a quality assessment of the developed algorithm. The in situ measurements were obtained on the one hand by mobile FDR probes from agricultural fields near the towns of Merzenhausen and Selhausen incorporating different crop types and on the other hand by distributed wireless sensor networks (SoilNet clusters) from a grassland test site (near the town of Rollesbroich) and from a forest stand (within the Wüstebach sub-catchment). Each SoilNet cluster incorporates around 150 wireless measuring devices on a grid of approximately 30ha for distributed soil moisture sensing. Finally, the comparison of both distributed soil moisture products results in a discussion on potentials and limitations for obtaining soil moisture under vegetation cover with high resolution fully polarimetric SAR. [1] S.R. Cloude, Polarisation: applications in remote sensing. Oxford, Oxford University Press, 2010. [2] Jagdhuber, T., Hajnsek, I., Papathanassiou, K.P. and Bronstert, A.: A Hybrid Decomposition for Soil Moisture Estimation under Vegetation Cover Using Polarimetric SAR. Proc. of the 5th International Workshop on Science and Applications of SAR Polarimetry and Polarimetric Interferometry, ESA-ESRIN, Frascati, Italy, January 24-28, 2011, p.1-6.

Determination of atmospheric moisture structure and infrared cooling rates from high resolution MAMS radiance data

NASA Technical Reports Server (NTRS)

Menzel, W. Paul; Moeller, Christopher C.; Smith, William L.

1991-01-01

This program has applied Multispectral Atmospheric Mapping Sensor (MAMS) high resolution data to the problem of monitoring atmospheric quantities of moisture and radiative flux at small spatial scales. MAMS, with 100-m horizontal resolution in its four infrared channels, was developed to study small scale atmospheric moisture and surface thermal variability, especially as related to the development of clouds, precipitation, and severe storms. High-resolution Interferometer Sounder (HIS) data has been used to develop a high spectral resolution retrieval algorithm for producing vertical profiles of atmospheric temperature and moisture. The results of this program are summarized and a list of publications resulting from this contract is presented. Selected publications are attached as an appendix.

Towards Validation of SMAP: SMAPEX-4 & -5

NASA Technical Reports Server (NTRS)

Ye, Nan; Walker, Jeffrey; Wu, Xiaoling; Jackson, Thomas; Renzullo, Luigi; Merlin, Olivier; Rudiger, Christoph; Entekhabi, Dara; DeJeu, Richard; Kim, Edward

2016-01-01

The L-band (1 - 2 GHz) microwave remote sensing has been widely acknowledged as the most promising method to monitor regional to global soil moisture. Consequently, the Soil Moisture Active Passive (SMAP) satellite applied this technique to provide global soil moisture every 2 to 3 days. To verify the performance of SMAP, the fourth and fifth campaign of SMAP Experiments (SMAPEx-4 -5) were carried out at the beginning of the SMAP operational phase in the Murrumbidgee River catchment, southeast Australia. The airborne radar and radiometer observations together with ground sampling on soil moisture, vegetation water content, and surface roughness were collected in coincidence with SMAP overpasses. The SMAPEx-4 and -5 data sets will benefit to SMAP post-launch calibration andvalidation under Australian land surface conditions.

EPMOSt: An Energy-Efficient Passive Monitoring System for Wireless Sensor Networks

PubMed Central

Garcia, Fernando P.; Andrade, Rossana M. C.; Oliveira, Carina T.; de Souza, José Neuman

2014-01-01

Monitoring systems are important for debugging and analyzing Wireless Sensor Networks (WSN). In passive monitoring, a monitoring network needs to be deployed in addition to the network to be monitored, named the target network. The monitoring network captures and analyzes packets transmitted by the target network. An energy-efficient passive monitoring system is necessary when we need to monitor a WSN in a real scenario because the lifetime of the monitoring network is extended and, consequently, the target network benefits from the monitoring for a longer time. In this work, we have identified, analyzed and compared the main passive monitoring systems proposed for WSN. During our research, we did not identify any passive monitoring system for WSN that aims to reduce the energy consumption of the monitoring network. Therefore, we propose an Energy-efficient Passive MOnitoring SysTem for WSN named EPMOSt that provides monitoring information using a Simple Network Management Protocol (SNMP) agent. Thus, any management tool that supports the SNMP protocol can be integrated with this monitoring system. Experiments with real sensors were performed in several scenarios. The results obtained show the energy efficiency of the proposed monitoring system and the viability of using it to monitor WSN in real scenarios. PMID:24949639

Towards SMOS: The 2006 National Airborne Field Experiment Plan

NASA Astrophysics Data System (ADS)

Walker, J. P.; Merlin, O.; Panciera, R.; Kalma, J. D.

2006-05-01

The 2006 National Airborne Field Experiment (NAFE) is the second in a series of two intensive experiments to be conducted in different parts of Australia. The NAFE'05 experiment was undertaken in the Goulburn River catchment during November 2005, with the objective to provide high resolution data for process level understanding of soil moisture retrieval, scaling and data assimilation. The NAFE'06 experiment will be undertaken in the Murrumbidgee catchment during November 2006, with the objective to provide data for SMOS (Soil Moisture and Ocean Salinity) level soil moisture retrieval, downscaling and data assimilation. To meet this objective, PLMR (Polarimetric L-band Multibeam Radiometer) and supporting instruments (TIR and NDVI) will be flown at an altitude of 10,000 ft AGL to provide 1km resolution passive microwave data (and 20m TIR) across a 50km x 50km area every 2-3 days. This will both simulate a SMOS pixel and provide the 1km soil moisture data required for downscale verification, allowing downscaling and near-surface soil moisture assimilation techniques to be tested with remote sensing data which is consistent with that from current (MODIS) and planned (SMOS) satellite sensors.. Additionally, two transects will be flown across the area to provide both 1km multi-angular passive microwave data for SMOS algorithm development, and on the same day, 50m resolution passive microwave data for algorithm verification. The study area contains a total of 13 soil moisture profile and rainfall monitoring sites for assimilation verification, and the transect fight lines are planned to go through 5 of these. Ground monitoring of surface soil moisture and vegetation for algorithm verification will be targeted at these 5 focus farms, with soil moisture measurements made at 250m spacing for 1km resolution flights and 50m spacing for 50m resolution flights. While this experiment has a particular emphasis on the remote sensing of soil moisture, it is open for collaboration from interested scientists from all disciplines of environmental remote sensing and its application. See www.nafe.unimelb.edu.au for more detailed information on these experiments.

A Real-time Irrigation Forecasting System in Jiefangzha Irrigation District, China

NASA Astrophysics Data System (ADS)

Cong, Z.

2015-12-01

In order to improve the irrigation efficiency, we need to know when and how much to irrigate in real time. If we know the soil moisture content at this time, we can forecast the soil moisture content in the next days based on the rainfall forecasting and the crop evapotranspiration forecasting. Then the irrigation should be considered when the forecasting soil moisture content reaches to a threshold. Jiefangzha Irrigation District, a part of Hetao Irrigation District, is located in Inner Mongolia, China. The irrigated area of this irrigation district is about 140,000 ha mainly planting wheat, maize and sunflower. The annual precipitation is below 200mm, so the irrigation is necessary and the irrigation water comes from the Yellow river. We set up 10 sites with 4 TDR sensors at each site (20cm, 40cm, 60cm and 80cm depth) to monitor the soil moisture content. The weather forecasting data are downloaded from the website of European Centre for Medium-Range Weather Forecasts (ECMWF). The reference evapotranspiration is estimated based on FAO-Blaney-Criddle equation with only the air temperature from ECMWF. Then the crop water requirement is forecasted by the crop coefficient multiplying the reference evapotranspiration. Finally, the soil moisture content is forecasted based on soil water balance with the initial condition is set as the monitoring soil moisture content. When the soil moisture content reaches to a threshold, the irrigation warning will be announced. The irrigation mount can be estimated through three ways: (1) making the soil moisture content be equal to the field capacity; (2) making the soil moisture saturated; or (3) according to the irrigation quota. The forecasting period is 10 days. The system is developed according to B2C model with Java language. All the databases and the data analysis are carried out in the server. The customers can log in the website with their own username and password then get the information about the irrigation forecasting and other information about the irrigation. This system can be expanded in other irrigation districts. In future, it is even possible to upgrade the system for the mobile user.

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

NASA Technical Reports Server (NTRS)

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

2015-01-01

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

Temporal Stability of Soil Moisture and Radar Backscatter Observed by the Advanced Synthetic Aperture Radar (ASAR)

PubMed Central

Wagner, Wolfgang; Pathe, Carsten; Doubkova, Marcela; Sabel, Daniel; Bartsch, Annett; Hasenauer, Stefan; Blöschl, Günter; Scipal, Klaus; Martínez-Fernández, José; Löw, Alexander

2008-01-01

The high spatio-temporal variability of soil moisture is the result of atmospheric forcing and redistribution processes related to terrain, soil, and vegetation characteristics. Despite this high variability, many field studies have shown that in the temporal domain soil moisture measured at specific locations is correlated to the mean soil moisture content over an area. Since the measurements taken by Synthetic Aperture Radar (SAR) instruments are very sensitive to soil moisture it is hypothesized that the temporally stable soil moisture patterns are reflected in the radar backscatter measurements. To verify this hypothesis 73 Wide Swath (WS) images have been acquired by the ENVISAT Advanced Synthetic Aperture Radar (ASAR) over the REMEDHUS soil moisture network located in the Duero basin, Spain. It is found that a time-invariant linear relationship is well suited for relating local scale (pixel) and regional scale (50 km) backscatter. The observed linear model coefficients can be estimated by considering the scattering properties of the terrain and vegetation and the soil moisture scaling properties. For both linear model coefficients, the relative error between observed and modelled values is less than 5 % and the coefficient of determination (R2) is 86 %. The results are of relevance for interpreting and downscaling coarse resolution soil moisture data retrieved from active (METOP ASCAT) and passive (SMOS, AMSR-E) instruments. PMID:27879759

Frequency, moisture content, and temperature dependent dielectric properties of potato starch related to drying with radio-frequency/microwave energy.

PubMed

Zhu, Zhuozhuo; Guo, Wenchuan

2017-08-24

To develop advanced drying methods using radio-frequency (RF) or microwave (MW) energy, dielectric properties of potato starch were determined using an open-ended coaxial-line probe and network analyzer at frequencies between 20 and 4,500 MHz, moisture contents between 15.1% and 43.1% wet basis (w.b.), and temperatures between 25 and 75 °C. The results showed that both dielectric constant (ε') and loss factor (ε″) were dependent on frequency, moisture content, and temperature. ε' decreased with increasing frequency at a given moisture content or temperature. At low moisture contents (≤25.4% w.b.) or low temperatures (≤45 °C), ε″ increased with increasing frequency. However, ε″ changed from decrease to increase with increasing frequency at high moisture contents or temperatures. At low temperatures (25-35 °C), both ε' and ε″ increased with increasing moisture content. At low moisture contents (15.1-19.5% w.b.), they increased with increasing temperature. The change trends of ε' and ε″ were different and dependent on temperature and moisture content at their high levels. The penetration depth (d p ) decreased with increasing frequency. RF treatments may provide potential large-scale industrial drying application for potato starch. This research offers useful information on dielectric properties of potato starch related to drying with electromagnetic energy.

A critical care network pressure ulcer prevention quality improvement project.

PubMed

McBride, Joanna; Richardson, Annette

2015-03-30

Pressure ulcer prevention is an important safety issue, often underrated and an extremely painful event harming patients. Critically ill patients are one of the highest risk groups in hospital. The impact of pressure ulcers are wide ranging, and they can result in increased critical care and the hospital length of stay, significant interference with functional recovery and rehabilitation and increase cost. This quality improvement project had four aims: (1) to establish a critical care network pressure ulcer prevention group; (2) to establish baseline pressure ulcer prevention practices; (3) to measure, compare and monitor pressure ulcers prevalence; (4) to develop network pressure ulcer prevention standards. The approach used to improve quality included strong critical care nursing leadership to develop a cross-organisational pressure ulcer prevention group and a benchmarking exercise of current practices across a well-established critical care Network in the North of England. The National Safety Thermometer tool was used to measure pressure ulcer prevalence in 23 critical care units, and best available evidence, local consensus and another Critical Care Networks' bundle of interventions were used to develop a local pressure ulcer prevention standards document. The aims of the quality improvement project were achieved. This project was driven by successful leadership and had an agreed common goal. The National Safety Thermometer tool was an innovative approach to measure and compare pressure ulcer prevalence rates at a regional level. A limitation was the exclusion of moisture lesions. The project showed excellent engagement and collaborate working in the quest to prevent pressure ulcers from many critical care nurses with the North of England Critical Care Network. A concise set of Network standards was developed for use in conjunction with local guidelines to enhance pressure ulcer prevention. © 2015 British Association of Critical Care Nurses.

Form and function in hillslope hydrology: in situ imaging and characterization of flow-relevant structures

NASA Astrophysics Data System (ADS)

Jackisch, Conrad; Angermann, Lisa; Allroggen, Niklas; Sprenger, Matthias; Blume, Theresa; Tronicke, Jens; Zehe, Erwin

2017-07-01

The study deals with the identification and characterization of rapid subsurface flow structures through pedo- and geo-physical measurements and irrigation experiments at the point, plot and hillslope scale. Our investigation of flow-relevant structures and hydrological responses refers to the general interplay of form and function, respectively. To obtain a holistic picture of the subsurface, a large set of different laboratory, exploratory and experimental methods was used at the different scales. For exploration these methods included drilled soil core profiles, in situ measurements of infiltration capacity and saturated hydraulic conductivity, and laboratory analyses of soil water retention and saturated hydraulic conductivity. The irrigation experiments at the plot scale were monitored through a combination of dye tracer, salt tracer, soil moisture dynamics, and 3-D time-lapse ground penetrating radar (GPR) methods. At the hillslope scale the subsurface was explored by a 3-D GPR survey. A natural storm event and an irrigation experiment were monitored by a dense network of soil moisture observations and a cascade of 2-D time-lapse GPR trenches. We show that the shift between activated and non-activated state of the flow paths is needed to distinguish structures from overall heterogeneity. Pedo-physical analyses of point-scale samples are the basis for sub-scale structure inference. At the plot and hillslope scale 3-D and 2-D time-lapse GPR applications are successfully employed as non-invasive means to image subsurface response patterns and to identify flow-relevant paths. Tracer recovery and soil water responses from irrigation experiments deliver a consistent estimate of response velocities. The combined observation of form and function under active conditions provides the means to localize and characterize the structures (this study) and the hydrological processes (companion study Angermann et al., 2017, this issue).

ELBARA II, an L-band radiometer system for soil moisture research.

PubMed

Schwank, Mike; Wiesmann, Andreas; Werner, Charles; Mätzler, Christian; Weber, Daniel; Murk, Axel; Völksch, Ingo; Wegmüller, Urs

2010-01-01

L-band (1-2 GHz) microwave radiometry is a remote sensing technique that can be used to monitor soil moisture, and is deployed in the Soil Moisture and Ocean Salinity (SMOS) Mission of the European Space Agency (ESA). Performing ground-based radiometer campaigns before launch, during the commissioning phase and during the operative SMOS mission is important for validating the satellite data and for the further improvement of the radiative transfer models used in the soil-moisture retrieval algorithms. To address these needs, three identical L-band radiometer systems were ordered by ESA. They rely on the proven architecture of the ETH L-Band radiometer for soil moisture research (ELBARA) with major improvements in the microwave electronics, the internal calibration sources, the data acquisition, the user interface, and the mechanics. The purpose of this paper is to describe the design of the instruments and the main characteristics that are relevant for the user.

ELBARA II, an L-Band Radiometer System for Soil Moisture Research

PubMed Central

Schwank, Mike; Wiesmann, Andreas; Werner, Charles; Mätzler, Christian; Weber, Daniel; Murk, Axel; Völksch, Ingo; Wegmüller, Urs

2010-01-01

L-band (1–2 GHz) microwave radiometry is a remote sensing technique that can be used to monitor soil moisture, and is deployed in the Soil Moisture and Ocean Salinity (SMOS) Mission of the European Space Agency (ESA). Performing ground-based radiometer campaigns before launch, during the commissioning phase and during the operative SMOS mission is important for validating the satellite data and for the further improvement of the radiative transfer models used in the soil-moisture retrieval algorithms. To address these needs, three identical L-band radiometer systems were ordered by ESA. They rely on the proven architecture of the ETH L-Band radiometer for soil moisture research (ELBARA) with major improvements in the microwave electronics, the internal calibration sources, the data acquisition, the user interface, and the mechanics. The purpose of this paper is to describe the design of the instruments and the main characteristics that are relevant for the user. PMID:22315556

Soft computing modelling of moisture sorption isotherms of milk-foxtail millet powder and determination of thermodynamic properties.

PubMed

Simha, H V Vikram; Pushpadass, Heartwin A; Franklin, Magdaline Eljeeva Emerald; Kumar, P Arun; Manimala, K

2016-06-01

Moisture sorption isotherms of spray-dried milk-foxtail millet powder were determined at 10, 25 and 40 °C. Sorption data was fitted using classical and soft-computing approaches. The isotherms were of type II, and equilibrium moisture content (EMC) was temperature dependent. The BET monolayer moisture content decreased from 3.30 to 2.67 % as temperature increased from 10 to 40 °C. Amongst the classical models, Ferro-Fontan gave the best fit of EMC-aw data. However, the Sugeno-type adaptive neuro-fuzzy inference system (ANFIS) with generalized bell-shaped membership function performed better than artificial neural network and classical models with RMSE as low as 0.0099. The isosteric heat of sorption decreased from 150.32 kJ mol(-1) at 1 % moisture content to 44.11 kJ mol(-1) at 15 % moisture. The enthalpy-entropy compensation theory was validated, and the isokinetic and harmonic mean temperatures were determined as 333.1 and 297.5 K, respectively.

In Situ Validation of the Soil Moisture Active Passive (SMAP) Satellite Mission

NASA Technical Reports Server (NTRS)

Jackson, T.; Cosh, M.; Crow, W.; Colliander, A.; Walker, J.

2011-01-01

SMAP is a new NASA mission proposed for 2014 that would provide a number of soil moisture and freeze/thaw products. The soil moisture products span spatial resolutions from 3 to 40 km. In situ soil moisture observations will be one of the key elements of the validation program for SMAP. Data from the currently available set of soil moisture observing sites and networks need improvement if they are to be useful. Problems include a lack of standardization of instrumentation and installation and the disparity in spatial scale between the point-scale in situ data (a few centimeters) and the coarser satellite products. SMAP has initiated activities to resolve these issues for some of the existing resources. The other challenge to soil moisture validation is the need to expand the number of sites and their geographic distribution. SMAP is attempting to increase the number of sites and their value in validation through collaboration. The issues and solutions involving in situ validation being investigated will be described along with recent results from SMAP validation projects.

Modelling and Evaluation of Non-Linear Rootwater Uptake for Winter Cropping of Wheat and Berseem

NASA Astrophysics Data System (ADS)

GS, K.; Prasad, K. S. H.

2017-12-01

The plant water uptake is significant for study to monitor the irrigation supplied to the plant. The Richards equation has been the key governing equation to quantify the root water uptake in the vadose zone and it takes all the sources and sink terms into consideration. The β parameter or the non linearity parameter is used in this modeling to bring the non linearity in the plant root water uptake. The soil parameters are obtained by experimentation and are employed in the Van-Genuchten equation for soil moisture study. Field experiments were carried out at Civil Engineering Department IIT Roorkee, Uttarakhand, India, during the winter season of 2013 and 2014 for berseem and 2016 for wheat as per the local cropping practices. Drainage type lysimeters were installed to study the soil water balance. Soil moisture was monitored using profile probe. Precipitation and all meteorological data were obtained from the nearby gauges located at the National Institute of Hydrology, Roorkee.The moisture data and the deep percolation data were collected on a daily basis and the irrigation supply was controlled and monitored to satisfy the moisture requirements of the crops respectively.In order to study the effect of water scarcity on the crops, the plot was divided and deficited irrigation was applied for the second cropping season for Berseem.The yields for both the seasons was also measured. The solution of Richards equation as applied to the moisture movement in the root zone was modeled. For estimation of root water uptake, the governing equation is the one-dimensional mixed form of Richards' equation is employed (Ji et al., 2007; Shankar et al., 2012).The sink term in the model accounts for the root water uptake, which is utilized by the plant for transpiration. Smaxor the maximum root water uptake for the root zone on a given day must be equal to the maximum transpiration on the corresponding day The model computed moisture content and pressure head is calibrated with the measured soil water content in the crop root zone. The Model output is compared with the output of the HYDRUS 1D software package. The complete calibrated model is now employed to determine the irrigation requirement of crops for a known initial moisture content and available precipitation and can be useful for economical agriculture in the semi-arid regions of India.

40 CFR 75.15 - Special provisions for measuring Hg mass emissions using the excepted sorbent trap monitoring...

Code of Federal Regulations, 2010 CFR

2010-07-01

... the excepted sorbent trap monitoring methodology. For an affected coal-fired unit under a State or...; (c) A certified flow monitoring system is required; (d) Correction for stack gas moisture content is... proportional to the stack gas volumetric flow rate. (f) At the beginning and end of each sample collection...

Yet another cause for blocked sidestream capnogram--beware of the non-threaded cap mount in heat and moisture exchangers.

PubMed

Umesh, Goneppanavar; Jasvinder, Kaur; Shetty, Nanda

2009-08-01

Heat and moisture exchangers (HME) are commonly used during general anaesthesia and intensive care of patients on mechanical ventilators. Some of the HME manufacturers provide HMEs with a Luer lock fitting for connecting side stream CO(2) monitoring line, Luer lock cap, and a non-threaded cap mount. However, HMEs from different manufacturers and HMEs meant for use in children and for adults from the same manufacturer vary in the presence/absence of non-threaded cap mount. This can create confusion to the clinicians and can result in inadvertent connection of the CO(2) monitoring line to the non-threaded cap mount resulting in blocked CO(2) monitoring line and leak in the circuit. We caution all the anaesthesiologists and intensivists regarding this possibility while using HMEs from different manufacturers.

Potential Application of Airborne Passive Microwave Observations for Monitoring Inland Flooding Caused by Tropical Cyclones

NASA Technical Reports Server (NTRS)

Hood, Robbie E.; Radley, C.D.; LaFontaine, F.J.

2008-01-01

Inland flooding from tropical cyclones can be a significant factor in storm-related deaths in the United States and other countries. Information collected during NASA tropical cyclone field studies suggest surface water and flooding induced by tropical cyclone precipitation can be detected and therefore monitored using passive microwave airborne radiometers. In particular, the 10.7 GHz frequency of the NASA Advanced Microwave Precipitation Radiometer (AMPR) flown on the NASA ER-2 has demonstrated high resolution detection of anomalous surface water and flooding in numerous situations. This presentation will highlight the analysis of three cases utilizing primarily satellite and airborne radiometer data. Radiometer data from the 1998 Third Convection and Moisture Experiment (CAMEX-3) are utilized to detect surface water during landfalling Hurricane Georges in both the Dominican Republic and Louisiana. A third case is landfalling Tropical Storm Gert in Eastern Mexico during the Tropical Cloud Systems and Processes (TCSP) experiment in 2005. AMPR data are compared to topographic data and vegetation indices to evaluate the significance of the surface water signature visible in the 10.7 GHz information. The results of this study suggest the benefit of an aircraft 10 GHz radiometer to provide real-time observations of surface water conditions as part of a multi-sensor flood monitoring network.

Quantifying the Influence of Near-Surface Water-Energy Budgets on Soil Thermal Properties Using a Network of Coupled Meteorological and Vadose Zone Instrument Arrays in Indiana, USA

NASA Astrophysics Data System (ADS)

Naylor, S.; Gustin, A. R.; Ellett, K. M.

2012-12-01

Weather stations that collect reliable, sustained meteorological data sets are becoming more widely distributed because of advances in both instrumentation and data server technology. However, sites collecting soil moisture and soil temperature data remain sparse with even fewer locations where complete meteorological data are collected in conjunction with soil data. Thanks to the advent of sensors that collect continuous in-situ thermal properties data for soils, we have gone a step further and incorporated thermal properties measurements as part of hydrologic instrument arrays in central and northern Indiana. The coupled approach provides insights into the variability of soil thermal conductivity and diffusivity attributable to geologic and climatological controls for various hydrogeologic settings. These data are collected to facilitate the optimization of ground-source heat pumps (GSHPs) in the glaciated Midwest by establishing publicly available data that can be used to parameterize system design models. A network of six monitoring sites was developed in Indiana. Sensors that determine thermal conductivity and diffusivity using radial differential temperature measurements around a heating wire were installed at 1.2 meters below ground surface— a typical depth for horizontal GSHP systems. Each site also includes standard meteorological sensors for calculating reference evapotranspiration following the methods by the Food and Agriculture Organization (FAO) of the United Nations. Vadose zone instrumentation includes time domain reflectometry soil-moisture and temperature sensors installed at 0.3-meter depth intervals down to a 1.8-meter depth, in addition to matric potential sensors at 0.15, 0.3, 0.6, and 1.2 meters. Cores collected at 0.3-meter intervals were analyzed in a laboratory for grain size distribution, bulk density, thermal conductivity, and thermal diffusivity. Our work includes developing methods for calibrating thermal properties sensors based on known standards and comparing measurements from transient line heat source devices. Transform equations have been developed to correct in-situ measurements of thermal conductivity and comparing these results with soil moisture data indicates that thermal conductivity can increase by as much as 25 percent during wetting front propagation. Thermal dryout curves have also been modeled based on laboratory conductivity data collected from core samples to verify field measurements, and alternatively, temperature profile data are used to calibrate near-surface temperature gradient models. We compare data collected across various spatial scales to assess the potential for upscaling near-surface thermal regimes based on available soils data. A long-term goal of the monitoring effort is to establish continuous data sets that determine the effect of climate variability on soil thermal properties such that expected ranges in thermal conductivity can be used to determine optimal ground-coupling loop lengths for GSHP systems.

Effect of temporal sampling and timing for soil moisture measurements at field scale

NASA Astrophysics Data System (ADS)

Snapir, B.; Hobbs, S.

2012-04-01

Estimating soil moisture at field scale is valuable for various applications such as irrigation scheduling in cultivated watersheds, flood and drought prediction, waterborne disease spread assessment, or even determination of mobility with lightweight vehicles. Synthetic aperture radar on satellites in low Earth orbit can provide fine resolution images with a repeat time of a few days. For an Earth observing satellite, the choice of the orbit is driven in particular by the frequency of measurements required to meet a certain accuracy in retrieving the parameters of interest. For a given target, having only one image every week may not enable to capture the full dynamic range of soil moisture - soil moisture can change significantly within a day when rainfall occurs. Hence this study focuses on the effect of temporal sampling and timing of measurements in terms of error on the retrieved signal. All the analyses are based on in situ measurements of soil moisture (acquired every 30 min) from the OzNet Hydrological Monitoring Network in Australia for different fields over several years. The first study concerns sampling frequency. Measurements at different frequencies were simulated by sub-sampling the original data. Linear interpolation was used to estimate the missing intermediate values, and then this time series was compared to the original. The difference between these two signals is computed for different levels of sub-sampling. Results show that the error increases linearly when the interval is less than 1 day. For intervals longer than a day, a sinusoidal component appears on top of the linear growth due to the diurnal variation of surface soil moisture. Thus, for example, the error with measurements every 4.5 days can be slightly less than the error with measurements every 2 days. Next, for a given sampling interval, this study evaluated the effect of the time during the day at which measurements are made. Of course when measurements are very frequent the time of acquisition does not matter, but when few measurements are available (sampling interval > 1 day), the time of acquisition can be important. It is shown that with daily measurements the error can double depending on the time of acquisition. This result is very sensitive to the phase of the sinusoidal variation of soil moisture. For example, in autumn for a given field with soil moisture ranging from 7.08% to 11.44% (mean and standard deviation being respectively 8.68% and 0.74%), daily measurements at 2 pm lead to a mean error of 0.47% v/v, while daily measurements at 9 am/pm produce a mean error of 0.24% v/v. The minimum of the sinusoid occurs every afternoon around 2 pm, after interpolation, measurements acquired at this time underestimate soil moisture, whereas measurements around 9 am/pm correspond to nodes of the sinusoid, hence they represent the average soil moisture. These results concerning the frequency and the timing of measurements can potentially drive the schedule of satellite image acquisition over some fields.

NGEE Arctic Plant Traits: Soil Temperature and Moisture, Kougarok Road Mile Marker 64, Seward Peninsula, Alaska, beginning 2016

DOE Data Explorer

Colleen Iversen; Verity Salmon; Amy Breen; Holly Vander Stel; Stan Wullschleger

2017-03-10

Data includes soil temperature and soil moisture measured at the Kougarok hill slope located at Kougarok Road, Mile Marker 64. Most measurements are from monitoring stations with permanently installed probes though the data also includes single point measurements from handheld devices. Data collection began in July 2016 and is ongoing. Data upload will be completed March 2017.

Moisture in untreated, acetylated, and furfurylated Norway Spruce monitored during drying below fiber saturation using time domain NMR

Treesearch

Lisbeth G. Thygesen; Thomas Elder

2009-01-01

Using time domain–nuclear magnetic resonance spectroscopy, the moisture content (MC) in Norway spruce [Picea abies (L.) Karst.] sapwood, subjected to three different treatments (untreated, acetylated, and furfurylated), was studied during drying at 40oC at MCs below fiber saturation. Spin–spin relaxation time distributions were derived from Carr-Purcell-...

Measuring the Moisture Content of Green Wood Using Time Domain Reflectometry

Treesearch

Laurence Schimleck; Kim Love-Myers; Joe Sanders; Heath Raybon; Richard Daniels; Jerry Mahon; Edward Andrews; Erik Schilling

2011-01-01

The responsible usage of water by facilities that rely on wet log storage in the southern United States has become an issue of great importance as restrictions on water usage have grown in recent years. In order to learn about the dynamics of moisture content in wet-stored logs over time, it is necessary to conduct continuous monitoring of log piles. Time domain...

CAOS: the nested catchment soil-vegetation-atmosphere observation platform

NASA Astrophysics Data System (ADS)

Weiler, Markus; Blume, Theresa

2016-04-01

Most catchment based observations linking hydrometeorology, ecohydrology, soil hydrology and hydrogeology are typically not integrated with each other and lack a consistent and appropriate spatial-temporal resolution. Within the research network CAOS (Catchments As Organized Systems), we have initiated and developed a novel and integrated observation platform in several catchments in Luxembourg. In 20 nested catchments covering three distinct geologies the subscale processes at the bedrock-soil-vegetation-atmosphere interface are being monitored at 46 sensor cluster locations. Each sensor cluster is designed to observe a variety of different fluxes and state variables above and below ground, in the saturated and unsaturated zone. The numbers of sensors are chosen to capture the spatial variability as well the average dynamics. At each of these sensor clusters three soil moisture profiles with sensors at different depths, four soil temperature profiles as well as matric potential, air temperature, relative humidity, global radiation, rainfall/throughfall, sapflow and shallow groundwater and stream water levels are measured continuously. In addition, most sensors also measure temperature (water, soil, atmosphere) and electrical conductivity. This setup allows us to determine the local water and energy balance at each of these sites. The discharge gauging sites in the nested catchments are also equipped with automatic water samplers to monitor water quality and water stable isotopes continuously. Furthermore, water temperature and electrical conductivity observations are extended to over 120 locations distributed across the entire stream network to capture the energy exchange between the groundwater, stream water and atmosphere. The measurements at the sensor clusters are complemented by hydrometeorological observations (rain radar, network of distrometers and dense network of precipitation gauges) and linked with high resolution meteorological models. In this presentation, we will highlight the potential of this integrated observation platform to estimate energy and water exchange between the terrestrial and aquatic systems and the atmosphere, to trace water flow pathways in the unsaturated and saturated zone, and to understand the organization of processes and fluxes and thus runoff generation at different temporal and spatial scales.

Determination of the Thermal Properties of Sands as Affected by Water Content, Drainage/Wetting, and Porosity Conditions for Sands With Different Grain Sizes

NASA Astrophysics Data System (ADS)

Smits, K. M.; Sakaki, T.; Limsuwat, A.; Illangasekare, T. H.

2009-05-01

It is widely recognized that liquid water, water vapor and temperature movement in the subsurface near the land/atmosphere interface are strongly coupled, influencing many agricultural, biological and engineering applications such as irrigation practices, the assessment of contaminant transport and the detection of buried landmines. In these systems, a clear understanding of how variations in water content, soil drainage/wetting history, porosity conditions and grain size affect the soil's thermal behavior is needed, however, the consideration of all factors is rare as very few experimental data showing the effects of these variations are available. In this study, the effect of soil moisture, drainage/wetting history, and porosity on the thermal conductivity of sandy soils with different grain sizes was investigated. For this experimental investigation, several recent sensor based technologies were compiled into a Tempe cell modified to have a network of sampling ports, continuously monitoring water saturation, capillary pressure, temperature, and soil thermal properties. The water table was established at mid elevation of the cell and then lowered slowly. The initially saturated soil sample was subjected to slow drainage, wetting, and secondary drainage cycles. After liquid water drainage ceased, evaporation was induced at the surface to remove soil moisture from the sample to obtain thermal conductivity data below the residual saturation. For the test soils studied, thermal conductivity increased with increasing moisture content, soil density and grain size while thermal conductivity values were similar for soil drying/wetting behavior. Thermal properties measured in this study were then compared with independent estimates made using empirical models from literature. These soils will be used in a proposed set of experiments in intermediate scale test tanks to obtain data to validate methods and modeling tools used for landmine detection.

LiDAR-derived topographic indices to inform sampling and mapping of soil moisture at the plot to field scale

NASA Astrophysics Data System (ADS)

Kaleita, A. L.

2013-12-01

Identifying field-scale soil moisture patterns, and quantifying their impact on hydrology and nutrient flux, is currently limited by the time and resources required to do sufficient monitoring. A small number of monitoring locations or occasions may not be sufficient to capture the true spatial and temporal dynamics of these patterns. While process models can help to fill in data gaps, it is often difficult if not impossible to effectively parameterize them at the field and sub-field scale. Thus, empirical methods that can optimize sampling and mapping of soil moisture by using a minimal amount of readily available data may be of significant value. LiDAR is one source of such readily available data. Various topographic indices, including relative elevation, land slope, curvature, and slope aspect are known to influence soil moisture patterns, though the exact nature of that relationship appears to vary from study to study. The objective of this study was to use these data to identify critical sampling locations for mapping soil moisture, and to upscale point measurements at those locations to both a single field-average value, and to a high-resolution pattern map for the field. This study analyzed in-situ soil moisture measurements from the working agricultural field in Story County, Iowa. Theta probe soil moisture measurement values were taken every 50 meters on a 300 x 250 meter grid (~18 acres) during the summer growing seasons of 2004, 2005, 2007, and 2008. The elevation in the field varies by approximately 5 meters and the grid covers six different soil types and a variety of different landscape positions throughout the field. We used self-organizing maps (SOMs) and K-means clustering algorithms to split apart the field study area into distinct categories of similarly-characterized locations. We then used the SOM and clustering metrics to identify locations within each group that were representative of the behavior of that group of locations. We developed a weighted upscaling process to estimate a whole-field average soil moisture content from these few critical samples, and we compared the results to those obtained through the more traditional 'temporal stability' approach. The cluster-based approach was as good as and often better than the temporal stability approach, with the significant advantage that the former does not require any initial period of exhaustive soil moisture monitoring, whereas the latter does. A second objective was to use the classification results of the landscape data to interpolate these sparse critical sampling point data over the whole field. Using what we term 'feature-space interpolation' we were able to re-create a high-resolution soil moisture map for the field using only three measurements, by giving locations with similar landscape characteristics similar soil moisture values. The results showed a small but significant statistical improvement over traditional distance-based interpolation methods, and the resulting patterns also had stronger correlation with end-of-season yield, suggesting this approach may have valuable applications in production agriculture decision-making and assessment.

The Contribution of Soil Moisture Information to Forecast Skill: Two Studies

NASA Technical Reports Server (NTRS)

Koster, Randal

2010-01-01

This talk briefly describes two recent studies on the impact of soil moisture information on hydrological and meteorological prediction. While the studies utilize soil moisture derived from the integration of large-scale land surface models with observations-based meteorological data, the results directly illustrate the potential usefulness of satellite-derived soil moisture information (e.g., from SMOS and SMAP) for applications in prediction. The first study, the GEWEX- and ClIVAR-sponsored GLACE-2 project, quantifies the contribution of realistic soil moisture initialization to skill in subseasonal forecasts of precipitation and air temperature (out to two months). The multi-model study shows that soil moisture information does indeed contribute skill to the forecasts, particularly for air temperature, and particularly when the initial local soil moisture anomaly is large. Furthermore, the skill contributions tend to be larger where the soil moisture initialization is more accurate, as measured by the density of the observational network contributing to the initialization. The second study focuses on streamflow prediction. The relative contributions of snow and soil moisture initialization to skill in streamflow prediction at seasonal lead, in the absence of knowledge of meteorological anomalies during the forecast period, were quantified with several land surface models using uniquely designed numerical experiments and naturalized streamflow data covering mUltiple decades over the western United States. In several basins, accurate soil moisture initialization is found to contribute significant levels of predictive skill. Depending on the date of forecast issue, the contributions can be significant out to leads of six months. Both studies suggest that improvements in soil moisture initialization would lead to increases in predictive skill. The relevance of SMOS and SMAP satellite-based soil moisture information to prediction are discussed in the context of these studies.

Understanding SMAP-L4 soil moisture estimation skill and their dependence with topography, precipitation and vegetation type using Mesonet and Micronet networks.

NASA Astrophysics Data System (ADS)

Moreno, H. A.; Basara, J. B.; Thompson, E.; Bertrand, D.; Johnston, C. S.

2017-12-01

Soil moisture measurements using satellite information can benefit from a land data assimilation model Goddard Earth Observing System (GEOS-5) and land data assimilation system (LDAS) to improve the representation of fine-scale dynamics and variability. This work presents some advances to understand the predictive skill of L4-SM product across different land-cover types, topography and precipitation totals, by using a dense network of multi-level soil moisture sensors (i.e. Mesonet and Micronet) in Oklahoma. 130 soil moisture stations are used across different precipitation gradients (i.e. arid vs wet), land cover (e.g. forest, shrubland, grasses, crops), elevation (low, mid and high) and slope to assess the improvements by the L4_SM product relative to the raw SMAP L-band brightness temperatures. The comparisons are conducted between July 2015 and July 2016 at the daily time scale. Results show the highest L4-SM overestimations occur in pastures and cultivated crops, during the rainy season and at higher elevation lands (over 800 meters asl). The smallest errors occur in low elevation lands, low rainfall and developed lands. Forested area's soil moisture biases lie in between pastures (max biases) and low intensity/developed lands (min biases). Fine scale assessment of L4-SM should help GEOS-5 and LDAS teams refine model parameters in light of observed differences and improve assimilation techniques in light of land-cover, topography and precipitation regime. Additionally, regional decision makers could have a framework to weight the utility of this product for water resources applications.

In Situ Stem Psychrometry: toward a Physiologically-Based Drought Monitoring Network

NASA Astrophysics Data System (ADS)

KOCH, G. W.; Williams, C.; Ambrose, A.

2012-12-01

Plant water potential is a synoptic variable that integrates soil and atmospheric moisture stress and interacts with plant-internal factors to regulate gas exchange and determine vulnerability to drought-induced hydraulic dysfunction. Despite its importance, methods for measuring water potential are labor intensive. This limitation reduces measurement frequency, likely causes important transient events to be overlooked, and restricts development of a richer understanding of the impacts of integrated water stress on plant and ecosystem function. Recent technological advances have enabled in-situ, automated measurement of branch water potential over periods of weeks to months using stem psychrometers. We evaluated this technology through laboratory and field comparisons to standard pressure chamber measurements and with field installations in temperate forest, semi-arid woodland, and chaparral ecosystems. Performance was highly sensitive to installation procedures. With proper sealing, insulation, and radiation shielding, psychrometers typically differed from pressure chamber measurements by less than 0.2 MPa down to water potentials as low as -7 MPa. Measurements in tall trees reaffirmed the influence of gravity on water potential as previously documented with the pressure chamber. Psychrometer performance in situ was stable for periods of several weeks to months, with tissue wound response degrading sensor operation over time. We conclude that stem psychrometer technology is now suitable to serve as the foundation for a physiologically-based drought monitoring network that can anticipate important ecosystem impacts including changes in whole-system fluxes and mortality events.

Complementary effects of surface water and groundwater on soil moisture dynamics in a degraded coastal floodplain forest

NASA Astrophysics Data System (ADS)

Kaplan, D.; Muñoz-Carpena, R.

2011-02-01

SummaryRestoration of degraded floodplain forests requires a robust understanding of surface water, groundwater, and vadose zone hydrology. Soil moisture is of particular importance for seed germination and seedling survival, but is difficult to monitor and often overlooked in wetland restoration studies. This research hypothesizes that the complex effects of surface water and shallow groundwater on the soil moisture dynamics of floodplain wetlands are spatially complementary. To test this hypothesis, 31 long-term (4-year) hydrological time series were collected in the floodplain of the Loxahatchee River (Florida, USA), where watershed modifications have led to reduced freshwater flow, altered hydroperiod and salinity, and a degraded ecosystem. Dynamic factor analysis (DFA), a time series dimension reduction technique, was applied to model temporal and spatial variation in 12 soil moisture time series as linear combinations of common trends (representing shared, but unexplained, variability) and explanatory variables (selected from 19 additional candidate hydrological time series). The resulting dynamic factor models yielded good predictions of observed soil moisture series (overall coefficient of efficiency = 0.90) by identifying surface water elevation, groundwater elevation, and net recharge (cumulative rainfall-cumulative evapotranspiration) as important explanatory variables. Strong and complementary linear relationships were found between floodplain elevation and surface water effects (slope = 0.72, R2 = 0.86, p < 0.001), and between elevation and groundwater effects (slope = -0.71, R2 = 0.71, p = 0.001), while the effect of net recharge was homogenous across the experimental transect (slope = 0.03, R2 = 0.05, p = 0.242). This study provides a quantitative insight into the spatial structure of groundwater and surface water effects on soil moisture that will be useful for refining monitoring plans and developing ecosystem restoration and management scenarios in degraded coastal floodplains.